Climate and Disaster Risk Assessment of Quezon City, Philippines | i

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 Climate and Disaster Risk Assessment of Quezon City, Philippines | i

Copyright © 2022 QCG and EMI

The concepts, maps and overall design of the Quezon City Climate and Disaster Risk Assessment
(CDRA) Report for Quezon City are developed by EMI; hence, the aforementioned are intellectual
properties of EMI. Parts of the contents, data, and information contained in this document are
properties of Quezon City.

This document is jointly owned by the Quezon City Government and EMI. Permission to use this
document is granted provided that its use or parts thereof are for educational, informational, non-
commercial, and personal use only. The Quezon City Government and EMI must be acknowledged in
all cases as the source when reproducing or using any part of this publication.

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 Climate and Disaster Risk Assessment of Quezon City, Philippines | ii

Executive Summary

This report constitutes Deliverable 11 of the Conduct of an Updated Climate and Disaster Risk
Assessment (CDRA) Project. It summarizes the climate and disaster risk assessment key parameters,
outputs, their interpretation and their significance. The CDRA is concerned with four hazards: climate
change, flood, landslide and earthquake hazards. This report is a companion report to Deliverable 8:
Hazard, Vulnerability and Risk Maps for all 142 Barangays dated September 30, 2022. The latter
provides detailed explanations on the methodologies, underlying data, assumptions behind the hazard
and risk assessment associated with the four hazards as well as a full presentation of the outputs and
the findings. The reader is referred to the Deliverable 8 report for more details. In addition, the reader
is also referred to the Risk Profile and Atlas (Deliverable 14), which provides large scale maps and non-
technical explanations of the main outputs of the CDRA and puts these outputs in the context of
policy-making, awareness raising, and planning.

This report focuses more on outputs and their relevance in the context of the CDRA requirements. In
addition, it presents the hotspot barangays identified from the Barangay Vulnerability Index (BVI).
Furthermore, it is supported by three accompanying Information, Education and Communication (IEC)
elements, namely: An audio-visual presentation (AVP), infographics for each hazard, and mini booklet,
which contains key highlights of the study and the top risk hotspots in the city. The mini booklet is
produced in both English and Filipino languages. These companion deliverables are submitted
separately. Soft versions of the IEC material can be accessed through the following link.

https://drive.google.com/drive/folders/1vvR2f4cSSH-1TN6Hs0MlPrOGkjuAn_7_?usp=share_link

The report has seven parts:

Part 1 is the summary of the exposure data used in the assessment, particularly in population, land use
and critical point facilities.
Part 2 is a representation of climate change hazards for Quezon City, particularly in terms of impacts
on temperature and rainfall.
Part 3 presents the flood hazard and risk assessment. It includes outputs for climate change
projections for Metro Manila, RCP 8.5 rain flood event for 100-year flood map for the city based on
the QC Drainage Project preliminary studies, and flood vulnerability analysis from the CDRA
workshops held on October 21, October 28 and November 4 with the barangay representatives.
Part 4 tackles the earthquake hazard and risk. It provides a higher-resolution earthquake intensity map,
building damage estimates per barangay, expected casualties (i.e., injuries and loss of life), and
estimates of displaced population based on the M7.2 earthquake scenario on the West Valley Fault.
Part 5 is about the landslide hazard and risk. This provides updated landslide susceptibility maps by
complementing the current available data from the Mines and Geosciences Bureau (MGB). This also
includes the overlay analysis of critical assets to the updated landslide susceptibility maps.
Part 6 presents the Hotspot barangays of Quezon City, which are the barangays that represent the
highest potential vulnerability for one or multiple hazards.
Part 7 reflects on the progress made by Quezon City in the last decade to manage and reduce its
disaster risk and provides a road map for the future.

The report is illustrated with relevant maps and charts to facilitate comprehension and interpretation.

This study does not duplicate data and outputs found in other similar studies. Rather, it updates them
to current 2022 exposure and improves significantly on the resolution of the analysis. It establishes an
in-depth and high resolution (street level) assessment of the impacts of hazards on population,
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 Climate and Disaster Risk Assessment of Quezon City, Philippines | iii

buildings, critical point facilities, and infrastructure. It also includes the assessment of the impact of
secondary effects such as the spread of waterborne diseases for floods or liquefaction and fire
following for earthquakes. The outputs include count of buildings and their associated area affected
by various hazard for each barangay as well as other metrics that are essential for preparedness and
planning purposes. Results are presented by district and by barangay to facilitate the reading and
interpretation of the maps and their association with the related charts. One of the main intent is to
inform the update of the city’s various city development plans, its physical framework and its land use
plan in the early future (2020-2039). Another target objective is to support data-driven and science-
based barangay level and community level planning and preparedness efforts.

The report is a complement to the Hazard, Vulnerability, Risk and Hotspots Assessment (HVRA) for the
earthquake, flood and landslide hazards affecting the 142 barangays of Quezon City (QC) by
integrating inputs from the Climate and Disaster Risk Assessment Workshops for the barangays from
six districts. It also, includes a full chapter on the hotspot barangays as well as a concluding chapter
providing a vision of a resilient future for Quezon City.

The flood susceptibility assessment is anchored on the Quezon City Drainage Master Plan (QC-DMP)
preliminary report in 2021 on RCP 8.5 (2020-2039) 100-year rain return scenario, the Mines and
Geosciences Bureau (MGB) Flood Susceptibility Updating Report in 2021 and the Greater Metro
Manila Area Risk Assessment Project (GMMA-RAP) which is a benchmark study in 2013. The latter
was undertaken through a collaborative project between the Government of the Philippines and
Geoscience Australia. The flood depth maps taken from the QC-DMP and MGB studies are the most
recent scientific representation of inundation useful for hazard and risk analysis for the Quezon City
agencies and recommended for disaster risk management (DRM) planning by public and private
agencies including local government units such as Quezon City Government (QCG).

The earthquake hazard and risk assessment is based on the M7.2 earthquake scenario on the West
Valley Fault. The study attempts to duplicate the science behind the GMMA-RAP earthquake risk
assessment, whenever available, but improves on the resolution by refining the spatial grid of analysis
from 1.1km x 1.1km adopted in the GMMA-RAP to 175m x 175m, corresponding to close to 40 times
increase in the resolution.

The CDRA study adopted the scientific approach and results from the different studies but improved
on several components as follows:
1) It uses updated (2022) exposure data from Quezon to represent today’s conditions.
2) It uses geo-political boundaries for Quezon City and for its 142 barangays that are officially
used by QCG.
3) It significantly improves the analysis resolution to guide barangay level and community level
preparedness and planning.
4) It includes a section on rainfall, temperature tropical cyclones, sea level, and climate extremes
projections and implications of climate change in Metro-Manila and QC.
5) It includes simulation results from the QC-DMP flood studies (preliminary) and MGB flood
susceptibility mapping to develop the flood impact analyses.
6) It establishes the hotspot barangays
7) It customizes all outputs to Quezon City’s DRRM and presents a series of applications
pertinent to improving the management of disaster risk, supporting disaster preparedness and
response, establishing priorities for risk reduction investments and mainstreaming hazard and
risk reduction objectives in land use and development plans.

All outputs are presented in maps and charts and their relevance to Disaster Risk Reduction and
Management planning is elaborated.

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 Climate and Disaster Risk Assessment of Quezon City, Philippines | iv

Authors and Contributors

EMI Authors and Contributors

Dr. Renan Ma. Tanhueco, EMI Flood Risk Assessment and CDRA Practice Leader
Dr. Fouad Bendimerand, EMI Hazard and Vulnerability Risk Assessment Expert
Dr. Bijan Khazai, EMI Landslide Risk Assessment Expert
Ms. Lourdes Tibig, EMI Climate and Disaster Risk Assessment Expert
Eng. Joshua Dimasaka, Urban Resilience Fellow
Eng. Paul Kenneth Luzon, Civil Engineer and GIS Specialist

En. P Joyce Lyn Salunat, EMI Project Manager

Eng. Laarni Hilario, Geodetic Engineer and Project Coordinator
Ms. Bernadette Dimmog, RS-GIS Specialist
Atty. Violeta S. Seva, Senior Disaster Risk and Reduction Management Expert
Dr. Amaryllis Torres, Gender and Social Inclusion Expert
Mr. Jose Mari O. Daclan, Disaster Risk Management Specialist
Mr. Benvictor P. John Turiano, GIS Intern
Mr. Francis Emil Joash Padilla, Graphic Designer and Layout Artist (Prototype 1)
Ms. Rose Anne Detran, Knowledge Management Specialist
Ms. Venice Van Allen Navarro, Graphic Designer and Layout Artist
Mr. Francis Emil Joash Padilla

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 Climate and Disaster Risk Assessment of Quezon City, Philippines | v

Contributors
Quezon City Government
QCG Steering Committee Members and Project Management Team
• Hon. Josefina G. Belmonte | Head of QCDRRM Council and City Mayor
• Mr. Michael Victor N. Alimurung | Project Director and City Administrator
• Hon. Ricardo T. Belmonte, Jr. | Project Manager and QCDRRM Officer
• Ms. Andrea Valentine A. Villaroman | Project Manager and Climate Change and Environmental
Sustainability Department Head
• Dr. Esperanza Anita N. Escaño-Arias | Head, City Health Department
• Arch. Pedro Perlas Rodriguez, Jr. | Head, City Planning and Development Department

QCG Practice Leaders and Technical Working Group Members

• Enp. Ma. Bianca D. Perez | Chief Research and Planning, Geospatial Exposure Database
Practice Leader (PL)
• Ms. Cherry Blessing M. Gutierrez | Chief, Administrative and Finance Section
• Ms. Marie Hope G. Capicenio | Emergency Operations Center Manager, PL
• Ms. Jade Ashley R. Macalalad | Deputy Chief Research and Planning, Technical Working
Group Member

Training and Capacity Building

• Ms. Ma. Cinderella A. Garcia | Chief Logistics and Training, PL
• Ms. Vanessa Claire B. Vinarao | Senior Environmental Management Specialist, PL

Information, Education and Communication

• Mr. Enrico E. De Leus
• Public Affairs and Information Services Department, Member
• Ms. Lou Elizabeth Jade Flores
• Public Affairs and Information Services Department, Member

Emergency Management
• Mr. Edward N. Castillo, Jr. | Chief Operations and Warning Section, PL
• Mr. Erwin Carlos N. Valdez | Deputy Operations and Warning Section, PL
• Ms. Maribel D. Marquez | Sanitation Inspection II, CCESD, PL
• Ms. Agnes Marie De Jesus | Member
• Mr. Audemar Sesperez | Member

Social Inclusion
• Ms. Janete R. Oviedo | Gender and Development Council, Technical Working Group member,
Office of the City Administrator
• Mr. Herbert Fabrero | Special Operations Officer III, Technical Working Group member
• Ms. Berlyn Kae S. Tinonas } Office of the City Administrator, Technical Working Group
member

Other QCG Staff

QC Disaster Risk Reduction and Management Office
• Mr. Julius Czar Buenavista | Special Operations Support Staff
• Ms. Jina Bulaon | Special Operations Support Staff
• Ms. Joanne Carlo Capistrano | Special Operations Support Staff
• Mr. John Reginald Carual | Special Operations Support Staff
• Ms. Mary Andrea Castillo | Special Operations Support Staff

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 Climate and Disaster Risk Assessment of Quezon City, Philippines | vi

• Ms. Myreen Costales | Special Operations Support Staff

• Mr. Efren Cregencia | Special Operations Support Staff
• Ms. Clarice Dela Cruz | Special Operations Support Staff
• Ms. Emelyn Demingoy-Nastor | Special Operations Support Staff
Ms. Bernadette Paz Fajardo | Special Operations Support Staff
• Mr. Paul Ibarra | Special Operations Support Staff
• Ms. Ma. Carmela Lim | Special Operations Support Staff
• Ms. Keneth Joy Lizarondo | Special Operations Support Staff
• Mr. Sean Frances Magatas | Special Operations Support Staff
• Mr. Donnie Ray Marquez | Special Operations Support Staff
• Mr. George Jonathan Mendoza | Special Operations Support Staff
• Ms. Sheriel Morada | Special Operations Support Staff
• Ms. Meryl Flor Montaron | Special Operations Support Staff
• Mr. Larry Pascua | Special Operations Support Staff
• Mr. Miguel Angelo Ramirez | Special Operations Support Staff
• Ms. Minerva Yazmin Reyes | Special Operations Support Staff
• Mr. Fidel Reyes | GIS Specialist
• Ms. Cathrine Tuazon | Special Operations Support Staff

Bureau of Fire Protection

• SSUPT. Gary R. Alto, DSC | District Fire Marshal
• SFO1 Ericka Magtoto Ledesma
City Assessors Department
• Atty. Sherry R. Gonzalvo | Head
City Engineering Department
• Engr. Isagani R. Verzosa, Jr. | OIC
• Engr. Sherwin Usman
City Health Department
• Dr. Amalia III Perpetua Oliva B. Esquivias, MD | Medical Officer III
City Planning and Development Department
• Mr. Jorge Abuan Serrano Jr. | Administrative Officer II
• Ms. Rosalima M. Laude | Project Development Officer II
Department of Building Official
• Atty. Mark Dale P. Perral | OIC
Department of Public Order and Safety
• PBGen. Elmo DG San Diego (Ret) | Head
• Ms. Daisy Dela Cruz
• Ms. Ma. Bernadette Barroga
Department of Sanitation and Cleanup Works
• Mr. Richard S. Santuille | OIC
• Jovy Macatungcal
Gender and Development Council
• Ms. Rowena T. Macatao
• Ms. Pia Lacunsay Roño
General Services Department
• Ms. Fe Bass | OIC
• Ar. Nilda Santos
• Engr. Arthur Ratera
Housing Community Development and Resettlement Department
• Mr. Ramon T. Asprer | Head
Human Resources Management Department

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 Climate and Disaster Risk Assessment of Quezon City, Philippines | vii

• Atty. Noel Del Prado

Persons with Disabilities Affairs Office
• Ms. Deborah Dacanay | OIC
Public Affairs and Information Services Department
• Mr. Engelbert Apostol | Head
• Mr. Ares Gutierrez
QC Public Library
• Ms. Mariza G. Chico | OIC
Quezon City Citizen Services Department
• Mr.Carlos I. Verzonilla | Head
Quezon City Police Department
• PBGen. Nicolas Deloso Torre III
Task Force Streetlighting
• Engr. Ricardo T. Aureo | Action Officer
Transport and Traffic Management Department
• Mr. Dexter C. Cardenas

National Government Offices and Private Organizations

Bureau of Soils and Water Management

• Engr.Pablo M. Montalla | Director
Department of Science and Technology – PAGASA
• Dr. Vicente B. Malano, Ph. D. | Administrator
• Ms. Shalou Maratas
Department of Science and Technology (DOST) – PHIVOLCS
• Dir. Renato U. Solidum Jr. | Director PHIVOLCS and Secretary DOST
Maynilad
• Mr. Juan Paulo De Leon | Head, GIS Department
• Ms. Myra P. Tacderan | Head, DVM/GIS/Technical Services
Metropolitan Waterworks and Sewerage System
• Atty. Elpidio J. Vega | Chairperson MWSS Board of Trustee
• Ms. Rosie Cailao | Asset Information Development Manager
Mines and Geoscience Bureau
• Atty. Wilfredo G. Moncano | Director
• Mr. Julius Umali | Staff
National Mapping and Resource Information Authority
• Usec. Peter N. Tiangco, Ph.D | Undersecretary
Philippine Statistics Authority
• Usec. Claire Dennis S. Mapa, Ph.D. | Undersecretary
• Ms. Lolit Alcantara

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 Climate and Disaster Risk Assessment of Quezon City, Philippines | viii

Acknowledgements
This project could not have been done without the dedication and constant support of the leadership
of the Quezon City Government, the members of the Quezon City Project Management Team and the
members of the Quezon City Technical Working Group. The effort and engagement of the full Quezon
City Team and the mobilization of its departments and offices in supporting the project and particularly
the data collection process and the co-design and validation workshops.

The technical support and collaboration of the following organizations of the Philippines Government
are hereby recognized:
• The Philippine Institute of Volcanology and Seismology (PHIVOLCS) for providing the digitized
earthquake hazard data for Greater Metro Manila and technical clarifications on the hazard
parameters;
• Metro Manila Development Authority (MMDA) through EFCOS for providing data on flood
management operations, rainfall and water level, flood control and flood inundation data for
Metro Manila;
• National Mapping and Resource Information Authority (NAMRIA) for providing LiDAR data
and several baseline digitized data related to Quezon City;
• Department of Science and Technology Philippine Atmospheric, Geophysical and Astronomical
Services Administration (DOST-PAGASA), Manila Observatory and Ateneo de Manila
University for climate and weather data and climate projections;
• The Philippine Statistics Authority for providing the 2015 sociodemographic data and 2020
population count per barangay;
• The DENR-Mines and Geosciences Bureau for the flood and landslide susceptibility map
images and reports.
• The Metropolitan Waterworks and Sewerage System and Maynilad for data on water supply
and distribution and wastewater treatment facilities.

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Disclaimer
This document was developed for the project “Conduct of an Updated Climate and Disaster Risk
Assessment (CDRA) for Quezon City (CONSUL-21-001)”. It was developed by EMI for the Quezon City
Government.

Data, information, maps, tables, findings, and analyses presented in the document are based on
information collected from Quezon City Departments and offices, reports and data from various
hazard and risk assessment studies, as well as information available online or from media sources and
academe. Hypotheses and assumptions were developed by EMI experts with extensive experience in
their respective fields of expertise to treat the datasets and come up with a comprehensive geo-spatial
exposure for Quezon City and a sound assessment of the hazard, vulnerability and risk for Quezon
City.

In order to improve on the assessments, trainings, workshops, focus group exercises, key informants’
interviews and field visits were conducted over several occasions during the undertaking of the
project. The validation procedures include flooding situations to augment flood models, spatial
locations and attributes of essential facilities, and importance of disaster risk variables in terms of
emergency response, coping capacities, and hazard exposures.

The analysis for earthquake related hazards is scenario-based. The magnitude 7.2 earthquake scenario
on the West Valley Fault (Model 8 in MMEIRS) is recognized by PHIVOLCS as well as experts in the
earthquake field as representing the worst-case scenario for Metro Manila. The same scenario is also
considered in the GMMA-Risk Analysis Project (GMMA-RAP) study. The occurrence of such an
earthquake is possible but very rare. While earthquakes with lesser magnitudes will provide lower
levels of constraints and loss, planning for the worst-case scenario is recommended by international
standards (e.g., ISO3000) and by recent earthquake occurrences globally because it help organizations
and institutions prepare for the unforeseen.

The sources of flood data used in the study include various models based on flooding due to Typhoon
Ondoy (2009), Typhoon Ulysses, the Mines and GeoSciences Bureau Flood Susceptibility Study for
Quezon City, the GMMA-RAP study, Quezon City Drainage Master Plan Preliminary Reports. EMI
made no attempt to qualify or validate the assumptions, methodologies or outputs of these studies.
They are used “as-is”. Flood hazard maps are indicative inundation maps for large flood events and
useful for preparedness and for planning purposes.

Vulnerability and Damage impact assessments and projections provided in this report are meant to
inform QCG on the risks provided by climate change, earthquakes, landslides, and floods so they can
improve on their planning and policy making processes. The information provided in this report is not
meant, and should not be interpreted, to replicate the realities of the impacts of an actual event.
Consequences from actual events can vary significantly from the projections provided in this report.

Photos and Images: EMI does not own the copyright for all the images. For these photos not owned by
EMI, individual owners and websites still own the rights to their images. Citations are indicated in each
photo when appropriate.

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 Climate and Disaster Risk Assessment of Quezon City, Philippines | x

Table of Contents

EMI Authors and Contributors ............................................................................................................................... iv

Contributors ................................................................................................................................................................. v

List of Tables ............................................................................................................................................................. xiv

List of Figures .......................................................................................................................................................... xvii

Acronyms ................................................................................................................................................................. xxiv

Link to Annex Tables......................................................................................................................................... xxvi

List of Tables in Annex ..................................................................................................................................... xxvi

Link to Information, Education and Communication (IEC) deliverables associated with the CDRA
report. ................................................................................................................................................................... xxvi

Part1: Key Exposure Data ......................................................................................................................................... 1

1.1. Population Distribution in Quezon City ............................................................................................... 2

1.2. Critical Point Facilities .............................................................................................................................. 2

1.3. Lifeline and Utilities .................................................................................................................................. 2

1.4. Building Footprint ..................................................................................................................................... 2

1.5. Land Uses in Quezon City ....................................................................................................................... 6

Part 2: Climate Change Hazards .............................................................................................................................. 9

2.1. What is Climate Change? ......................................................................................................................10

2.2. Baseline Data and Climate change projections for temperature and rainfall .............................10

2.2.1. Baseline Data .................................................................................................................................................. 10

2.2.2. Climate Projections ........................................................................................................................................ 13

2.2.3. Seasonal mean temperature and rainfall projections .............................................................................. 14

2.2.4. Projections on extreme temperatures and rainfall................................................................................... 15

2.3. Tropical cyclones, and sea-level rise (SLR) baseline data and climate change projections ......19

2.3.1 Tropical Cyclone Baseline Data .................................................................................................................... 19

2.3.2 Frequency of recurrence of tropical cyclones ............................................................................................ 19

2.3.3. Projections on tropical cyclone occurrence for Metro Manila ............................................................... 20

2.3.4. Projection on the sea-level rise for Metro Manila .................................................................................... 20

2.4. The Climate Extremes Risk Analysis Matrix (CERAM) ....................................................................21

2.4.1 What is the CERAM Tool? ............................................................................................................................. 21

2.4.2. Training and implementation of the CERAM Tool with Quezon City stakeholders .......................... 21

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2.4.3. Workshop Summary of Results .................................................................................................................... 23

2.4.4 Impact Chain Diagram and Analysis ........................................................................................................... 29

Part3: Flood Hazard and Risk Assessment ..........................................................................................................31

3.1. Rationale, Justification and Objectives .....................................................................................................32

3.2. Approach to Flood Risk Study ....................................................................................................................32

3.3. What does the flood scenario mean as a flood hazard? ........................................................................33

3.4. The Main Tributaries of Quezon City........................................................................................................33

3.5. MGB Flood Susceptibility Mapping in Quezon City ..............................................................................35

3.5.1 Background and baseline data ..................................................................................................................... 35

3.5.2 Flood susceptibility results by district ......................................................................................................... 35

3.6. QC-Drainage Master Plan (QC-DMP) Flood Hazard Simulation .........................................................45

3.6.1 Background ....................................................................................................................................................... 45

3.6.2 The Climate Change Adjusted 100-Year Rain Return Flood baseline scenario .................................. 45

3.6.3 Flood susceptibility results by district ......................................................................................................... 46

3.7. Flood Risk Assessment (RCP 8.5 100-Year Flood) .................................................................................55

3.7.1. Flood Displaced Population .......................................................................................................................... 55

3.7.2. Flood Affected Buildings ............................................................................................................................... 66

3.7.3. Flood Exposure of Health and Emergency Related Facilities ................................................................. 77

3.7.4. Flood Exposure of Facilities for Safety and Security ............................................................................... 85

3.7.5. Flood Affected Utilities and Infrastructures .............................................................................................. 92

3.7.6. Flood Affected Land Uses .......................................................................................................................... 104

3.8. Post-flood Health Issues – Gastro-Intestinal Infection ...................................................................... 110

Part 4: Earthquake Hazard and Risk Assessment ........................................................................................... 119

4.1. Content and Purpose ................................................................................................................................. 120

4.2. General Approach ...................................................................................................................................... 121

4.3. Quantifying Earthquake Hazard to Quezon City ................................................................................. 124

4.3.1. Earthquake Shaking Severity .................................................................................................................... 124

4.3.2 Earthquake intensity in Modified Mercalli Intensity (MMI).................................................................. 124

4.3.3. Ground rupture along West Valley Fault ................................................................................................ 133

4.4. Earthquake Risk Assessment ................................................................................................................... 136

4.4.1. Introduction .................................................................................................................................................. 136

4.4.2. The concept of risk ...................................................................................................................................... 136

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4.4.3. Building damage approach ........................................................................................................................ 136

4.4.4. Building damage results ............................................................................................................................. 137

4.4.5 Casualty modeling approach ...................................................................................................................... 141

4.4.5. Casualty results ........................................................................................................................................... 142

Part 5: Landslide Hazard and Risk ...................................................................................................................... 169

5.1 Background and Introduction ................................................................................................................... 170

5.2. Methodology ............................................................................................................................................... 173

5.3. Results .......................................................................................................................................................... 174

5.4. Landslide Risk Assessment ....................................................................................................................... 182

5.4.1. Critical Facilities Affected by Landslide Hazard .................................................................................... 182

5.4.2. Facilities for Health and Emergency ........................................................................................................ 182

5.4.3. Facilities for Safety and Security .............................................................................................................. 186

5.5. Impact on Transportation Systems and Mobility ................................................................................. 190

5.5.1. Road Network .............................................................................................................................................. 190

5.5.2. Population Affected by Landslide Hazard .............................................................................................. 190

Part 6: Hotspot Barangays ................................................................................................................................... 197

6.1. Introduction: Hotspots and Indicators ................................................................................................... 198

6.1.1. What are hotspot barangays and related indicators? .......................................................................... 198

6.1.2. Defining the Barangay Vulnerability Index for Quezon City ............................................................... 198

6.1.3. Selection of earthquake and flood indicators to identify hotspot barangays .................................. 199

6.2. Flood and Earthquake Indicators ............................................................................................................ 200

6.3. The Barangay Vulnerability Index ........................................................................................................... 202

6.3.1 Analytical Approach ..................................................................................................................................... 202

6.3.2. Criteria for determining the hotspot barangays .................................................................................... 203

6.4. Hotspot Barangays in Quezon City ........................................................................................................ 203

6.4.1. Earthquake Hotspot Barangays ................................................................................................................ 204

6.4.2. Flood Hotspot Barangays .......................................................................................................................... 207

6.4.3. Landslide Hotspot Barangays ................................................................................................................... 210

6.4.4. Combined Hotspot Barangays for Earthquake and Flood Hazards ................................................... 212

6.5. Recommendations on the Use of Barangay Hotspot ......................................................................... 215

Part 7: Towards a Resilient Quezon City ......................................................................................................... 216

7.1. A Model City for Urban Resilience ......................................................................................................... 217

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7.2. Utilizing Science to Manage and Reduce Risk ...................................................................................... 217

7.3. Forward Looking Plans to Guide Policy and Investments .................................................................. 217

7.4. Roadmap to Urban Resilience .................................................................................................................. 220

References ............................................................................................................................................................... 223

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List of Tables
Table 1. Decadal changes in climatological normals of temperatures and rainfall observed in Science
Garden, Quezon City. ...............................................................................................................................................11
Table 2. Characteristics and features of the two Climate Trends and Projections Report; the PAGASA,
2018 and the Philippine Climate Extremes Report, 2020. ...............................................................................14
Table 3. Projected seasonal changes in temperature in ºC and rainfall in percentages under the
medium- emission scenario (RCP 4.5) during the mid-21st century (2036-2065). .....................................14
Table 4. Projected seasonal changes in mean temperature in ºC and rainfall in percentages under the
high -emission scenario (RCP 8.5) during the mid-21st century (2036-2065) .............................................14
Table 5. Summary of temperature and rainfall indices ......................................................................................16
Table 6. Temperature Extreme Indices for Metro Manila .................................................................................17
Table 7. Rainfall Extreme Indices for Metro Manila ...........................................................................................18
Table 8. Tropical Cyclone (TC) Classifications by PAGASA. .............................................................................19
Table 9. Estimated Average Return of Tropical Cyclones Within 50 km Crossing Metro Manila ............19
Table 10 Summary of extreme temperature and rainfall indices used in the workshop ............................22
Table 11 Examples potential impacts of projected changes in temperature extremes on selected
sectors collected from the stakeholder consultations on Oct 21 and 28 and Nov 4, 2022, workshops 24
Table 12. Summarized list of desired adaptation options collected from the stakeholder consultations
on Oct 21 and 28 and Nov 4, 2022, workshops .................................................................................................27
Table 13. Flood Susceptibility Levels ....................................................................................................................35
Table 14. Flood Susceptibility in District 1 based on percentage of land area assigned to flood water
depth ............................................................................................................................................................................36
Table 15. Flood Susceptibility in District 2 based on percentage of land area assigned to flood water
depth categories. .......................................................................................................................................................37
Table 16. Flood Susceptibility in District 3 based on percentage of land area assigned to flood water
depth categories. .......................................................................................................................................................38
Table 17. Flood Susceptibility in District 4 based on percentage of land area assigned to flood water
depth categories. .......................................................................................................................................................39
Table 18. Flood Susceptibility in District 5 based on percentage of land area assigned to flood water
depth categories. .......................................................................................................................................................41
Table 19. Flood Susceptibility in District 6 based on percentage of land area assigned to flood water
depth categories. .......................................................................................................................................................41
Table 20. Maximum 1-Day Totals for NCR under various Emission Scenarios (Source: QC-Drainage
Master Plan, 2021) ....................................................................................................................................................45
Table 21. RCP 8.5 100 Year Flood Scenario Percentage of Land Area flooded at different flood levels
in District 1. ................................................................................................................................................................47
Table 22. RCP 8.5 100 Year Flood Scenario Percentage of Land Area flooded at different flood levels
in District 2. ................................................................................................................................................................48
Table 23. RCP 8.5 100 Year Flood Scenario Percentage of Land Area flooded at different flood levels
in District 3. ................................................................................................................................................................48

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Table 24. RCP 8.5 100 Year Flood Scenario Percentage of Land Area flooded at different flood levels
in District 4. ................................................................................................................................................................49
Table 25. RCP 8.5 100 Year Flood Scenario Percentage of Land Area Flooded at Different Flood Levels
in District 5. ................................................................................................................................................................50
Table 26. RCP 8.5 100 Year Flood Scenario Percentage of Land Area Flooded at Different Flood Levels
in District 6. ................................................................................................................................................................51
Table 27. Flood displaced population in District 1 in an RCP100-year 8.5 Rain Flood Scenario .............56
Table 28. Flood displaced population in District 2 in an RCP100-year 8.5 Rain Flood Scenario .............58
Table 29. Flood displaced population in District 3 in an RCP100-year 8.5 Rain Flood Scenario .............59
Table 30. Flood displaced population in District 4 in an RCP100-year 8.5 Rain Flood Scenario .............61
Table 31. Flood displaced population in District 5 in an RCP100-year 8.5 Rain Flood Scenario .............63
Table 32. Flood displaced population in District 6 in an RCP100-year 8.5 Rain Flood Scenario .............65
Table 33. Count of building footprint for all occupancy types in a flood category in District 1 for flood
depth 0.5m and higher .............................................................................................................................................67
Table 34. Count of building footprint for all occupancy types in a flood category in District 2 for flood
depth 0.5m and higher .............................................................................................................................................70
Table 35. Count of building footprint for all occupancy types in a flood category in District 3 for flood
depth 0.5m and higher .............................................................................................................................................71
Table 36. Count of building footprint for all occupancy types in a flood category in District 4 for flood
depth 0.5m and higher .............................................................................................................................................73
Table 37. Count of building footprint for all occupancy types in a flood category in District 5 for flood
depth 0.5m and higher .............................................................................................................................................75
Table 38. Count of building footprint for all occupancy types in a flood category in District 6for flood
depth 0.5m and higher .............................................................................................................................................76
Table 39. Barangays with flooded road segments in Districts 1 to 6 (RCP 8.5 100-year rain flood
scenario) ......................................................................................................................................................................92
Table 40. Ranking of barangays (a)-(f) showing the infection rate (per 1000 population) to Gastro-
Enteritis in different Barangays and Districts. .................................................................................................. 111
Table 41. The modified Mercalli intensity (MMI) scale (Wood & Neumann, 1931) ................................. 122
Table 42. District 1 damaged floor area at each damage state (m2) for M7.2 West Valley Fault
earthquake scenario............................................................................................................................................... 137
Table 43. District 2 damaged floor area at each damage state (m2) for M7.2 West Valley Fault
earthquake scenario............................................................................................................................................... 138
Table 44. District 3 damaged floor area at each damage state (m2) for M7.2 West Valley Fault
earthquake scenario............................................................................................................................................... 138
Table 45. District 4 damaged floor area for each damaged state (m2) for M7.2 West Valley Fault
earthquake scenario............................................................................................................................................... 139
Table 46. District 5 damaged floor area at each damage state (m2) for M7.2 West Valley Fault
earthquake scenario............................................................................................................................................... 140
Table 47. District 6 damaged floor area at each damage state (m2) for M7.2 West Valley Fault
earthquake scenario............................................................................................................................................... 140

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Table 48. Injury classification based on Hazus methodology (GMMA-RAP, 2013) ................................. 141
Table 49. Estimated casualties/injuries for a M7.2 West Valley Fault earthquake scenario caused by
building damage for District 1 ............................................................................................................................. 143
Table 50. Estimated casualties/injuries for a M7.2 West Valley Fault earthquake scenario caused by
building damage for District 2 ............................................................................................................................. 144
Table 51. Estimated casualties/injuries for a M7.2 West Valley Fault earthquake scenario caused by
building damage for District 3 ............................................................................................................................. 144
Table 52. Estimated casualties/injuries for a M7.2 West Valley Fault earthquake scenario caused by
building damage for District 4 ............................................................................................................................. 145
Table 53. Estimated casualties/injuries for a M7.2 West Valley Fault earthquake scenario caused by
building damage for District 5 ............................................................................................................................. 146
Table 54. Estimated casualties/injuries for a M7.2 West Valley Fault earthquake scenario caused by
building damage for District 6 ............................................................................................................................. 146
Table 55. Estimated total casualties of Quezon City for a M7.2 West Valley Fault earthquake scenario
.................................................................................................................................................................................... 146
Table 56. Aggregated estimate of displaced population from M7.2 earthquake scenario ..................... 159
Table 57 Estimated number and ratio of displaced population for District 1for M7.2 earthquake
scenario .................................................................................................................................................................... 160
Table 58 Estimated number and ratio of displaced population for District 2 for M7.2 earthquake
scenario .................................................................................................................................................................... 161
Table 59 Estimated number and ratio of displaced population for District 3 for M7.2 earthquake
scenario .................................................................................................................................................................... 161
Table 60............. Estimated number and ratio of displaced population for District 4 for M7.2 earthquake
scenario .................................................................................................................................................................... 162
Table 61 Estimated number and ratio of displaced population for District 5 for M7.2 earthquake
scenario .................................................................................................................................................................... 163
Table 62 Estimated number and ratio of displaced population for District 6 for M7.2 earthquake
scenario .................................................................................................................................................................... 163
Table 63. Landslide susceptibility parameters used during the assessment. ............................................. 170
Table 64. Type of data used and the method of acquisition in preliminary analysis. ............................... 174
Table 65. Slope Stability classes and re-classification in susceptibility mapping ...................................... 175
Table 67. Length of road segments of barangays in Quezon City within high to very high landslide
susceptibility............................................................................................................................................................ 190
Table 67. Indicators Used in the Calculations of the Flood BVI ................................................................... 200
Table 68. Indicators Used in the Calculations of the Earthquake BVI. ........................................................ 201
Table 69. Criteria for Hotspot Barangays in Three Tiers Based on the BVI Percentile Distribution. ... 203
Table 70. Earthquake Hotspot Barangays as Established by the 3-tier Barangay Vulnerability Index
(BVI). .......................................................................................................................................................................... 205
Table 71. Flood Hotspot Barangays as Established by the 3-tier Barangay Vulnerability Index (BVI) .208
Table 72. Landslide Hotspot Barangays in Two Tiers. .................................................................................... 210
Table 73. Hotspot Barangays for Combined Flood and Earthquake Hazards. .......................................... 213

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List of Figures
Figure 1. Population data for District 1 and District 2 (Source: QC –CPDO 2022) ...................................... 3
Figure 2. Population data for District 3 and District 4 (Source: QC –CPDO 2022) ...................................... 4
Figure 3. Population data for District 5 and District 6 (Source: QC–CPDO 2022) ..................................... 5
Figure 4. Residential Use Areas and Institutional Use Areas in Quezon City (Source: QC-City Planning
and Development Department (CPDD), 2019) ..................................................................................................... 7
Figure 5. Commercial Use Areas and Industrial Use Areas in Quezon City (Source: QC-City Planning
and Development Department (CPDD), 2019) ..................................................................................................... 8
Figure 6. Climate Types under Corona’s Classification (Source: Science Garden) .......................................11
Figure 7. Annual departure of mean temperature from the normal (1991-2020) at Science Garden,
Quezon City (Source: PAGASA) .............................................................................................................................12
Figure 8. Annual departure of rainfall from the normal (1991-2020) at Science Garden, Diliman,
Quezon City. (Source: PAGASA) ............................................................................................................................12
Figure 9. The Annual Rainfall Totals by Year from 1971 to 2020 Observed at the Science Garden
Station in Quezon City (Source: PAGASA) ...........................................................................................................13
Figure 10. Simplified impact chain diagram for Quezon City ...........................................................................29
Figure 11. Chain diagram for increase in temperature that could be applied to assess climate impact on
Quezon City ................................................................................................................................................................30
Figure 12. Rivers and Creeks in Quezon City (Source: QC-City Planning and Development Department
(CPDD), 2022) ............................................................................................................................................................34
Figure 13. Flood Susceptibility of District 1 of Quezon City ..............................................................................
Figure 14. Flood Susceptibility of District 2 of Quezon City ...........................................................................42
Figure 15. Flood Susceptibility of District 3 of Quezon City ..............................................................................
Figure 16. Flood Susceptibility of District 4 of Quezon City ...........................................................................43
Figure 17. Flood Susceptibility of District 5 of Quezon City ..............................................................................
Figure 18. Flood Susceptibility of District 6 of Quezon City ...........................................................................44
Figure 19. RCP 8.5(2020-2039) 100-Year Rain Flood Scenario in Quezon City (Source: QC-DMP,
Preliminary Report, 2022) .......................................................................................................................................46
Figure 20. RCP 8.5(2020-2039) 100-Year Rain Flood Scenario in District 1 ...................................................
Figure 21. RCP 8.5(2020-2039) 100-Year Rain Flood Scenario in District 2 ...............................................52
Figure 22. RCP 8.5(2020-2039) 100-Year Rain Flood Scenario in District 3 ..................................................
Figure 23. RCP 8.5(2020-2039) 100-Year Rain Flood Scenario for District 4 .............................................53
Figure 24. RCP 8.5(2020-2039) 100-Year Rain Flood Scenario for District 5 ................................................
Figure 25. RCP 8.5(2020-2039) 100-Year Rain Flood Scenario for District 6 .............................................54
Figure 26. Displaced Population from Single Family, One- and Two-Story Structures and Informal
Settler Family Structures in a 100-Year Rain Flood Scenario for District 1 (Source: QC-DMP,
Preliminary Report, 2021) .......................................................................................................................................57
Figure 27. Displaced Population from Single Family, One- and Two-Story Structures and Informal
Settler Family Structures in a 100-Year Rain Flood Scenario for District 2 (Source: QC-DMP,
Preliminary Report, 2021) .......................................................................................................................................58

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Figure 28. Displaced Population from Single Family, One- and Two-Story Structures and Informal
Settler Family Structures in a 100-Year Rain Flood Scenario for District 3 (Source: QC-DMP,
Preliminary Report, 2022) .......................................................................................................................................60
Figure 29. Displaced Population from Single Family, One- and Two-Story Structures and Informal
Settler Family Structures in a 100-Year Rain Flood Scenario for District 4 (Source: QC-DMP,
Preliminary Report, 2022) .......................................................................................................................................62
Figure 30. Displaced Population from Single Family, One- and Two-Story Structures and Informal
Settler Family Structures in a 100-Year Rain Flood Scenario for District 5 (Source: QC-DMP,
Preliminary Report, 2022) .......................................................................................................................................64
Figure 31. Displaced Population from Single Family, One- and Two-Story Structures and Informal
Settler Family Structures in a 100-Year Rain Flood Scenario for District 6 (Source: QC-DMP,
Preliminary Report, 2022) .......................................................................................................................................66
Figure 32. Area of One -Story, Single Family and Informal Settler Family Building Footprint in depths
greater than half meter in District 1 ......................................................................................................................69
Figure 33. Area of One -Story, Single Family and Informal Settler Family Building Footprint in depths
greater than half meter in District 2 ......................................................................................................................70
Figure 34. Area of One -Story, Single Family and Informal Settler Family Building Footprint in depths
greater than half meter in District 3 ......................................................................................................................72
Figure 35. Area of One -Story, Single Family and Informal Settler Family Building Footprint in depths
greater than half meter in District 4 ......................................................................................................................74
Figure 36. Area of One -Story, Single Family and Informal Settler Family Building Footprint in depths
greater than half meter in District 5 ......................................................................................................................76
Figure 37. Area of One -Story, Single Family and Informal Settler Family Building Footprint in depths
greater than half meter in District 6 ......................................................................................................................77
Figure 38. Public Facility (Emergency management related) locations in an RCP 8.5 100- year rain flood
scenario in District 1. Facilities in deep flood locations are shown with their names and flood level
indicator (ex. L2). Open/Vacant spaces are shown relative to the evacuation center locations ..............79
Figure 39. Public Facility (Emergency management related) locations in an RCP 8.5 100- year rain flood
scenario in District 2. Facilities in deep flood locations are shown with their names and flood level
indicator (ex. L2). Open/Vacant spaces are shown relative to the evacuation center locations ..............80
Figure 40. Public Facility (Emergency management related) locations in an RCP 8.5 100- year rain flood
scenario in District 3. Facilities in deep flood locations are shown with their names and flood level
indicator (ex. L2). Open/Vacant spaces are shown relative to the evacuation center locations ..............81
Figure 41. Public Facility (Emergency management related) locations in an RCP 8.5 100- year rain flood
scenario in District 4. Facilities in deep flood locations are shown with their names and flood level
indicator (ex. L2). Open/Vacant spaces are shown relative to the evacuation center locations ..............82
Figure 42. Public Facility (Emergency management related) locations in an RCP 8.5 100- year rain flood
scenario in District 5. Facilities in deep flood locations are shown with their names and flood level
indicator (ex. L2). Open/Vacant spaces are shown relative to the evacuation center locations ..............83

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Figure 43. Public Facility (Emergency management related) locations in an RCP 8.5 100- year rain flood
scenario in District 6. Facilities in deep flood locations are shown with their names and flood level
indicator (ex. L2). Open/Vacant spaces are shown relative to the evacuation center locations ..............84
Figure 44. Public Facility (Safety and Security related) locations in an RCP 8.5 100- year rain flood
scenario in District 1. Facilities in deep flood locations are shown with their names and flood level
indicator (ex. L2). Source: QC-Drainage Master Plan, Preliminary Report 2022, City Planning and
Development Department, 2022) ..........................................................................................................................86
Figure 45. Public Facility (Safety and Security related) locations in an RCP 8.5 100- year rain flood
scenario in District 2. Facilities in deep flood locations are shown with their names and flood level
indicator (ex. L2). Source: QC-Drainage Master Plan, Preliminary Report 2022, City Planning and
Development Department, 2022) ..........................................................................................................................87
Figure 46. Public Facility (Safety and Security related) locations in an RCP 8.5 100- year rain flood
scenario in District 3. Facilities in deep flood locations are shown with their names and flood level
indicator (ex. L2). Source: QC-Drainage Master Plan, Preliminary Report 2022, City Planning and
Development Department, 2022) ..........................................................................................................................88
Figure 47. Public Facility (Safety and Security related) locations in an RCP 8.5 100- year rain flood
scenario in District 4. Facilities in deep flood locations are shown with their names and flood level
indicator (ex. L2). Source: QC-Drainage Master Plan, Preliminary Report 2022, City Planning and
Development Department, 2022) ..........................................................................................................................89
Figure 48. Public Facility (Safety and Security related) locations in an RCP 8.5 100- year rain flood
scenario in District 5. Facilities in deep flood locations are shown with their names and flood level
indicator (ex. L2). Source: QC-Drainage Master Plan, Preliminary Report 2022, City Planning and
Development Department, 2022) ..........................................................................................................................90
Figure 49. Public Facility (Safety and Security related) locations in an RCP 8.5 100- year rain flood
scenario in District 6. Facilities in deep flood locations are shown with their names and flood level
indicator (ex. L2). Source: QC-Drainage Master Plan, Preliminary Report 2022, City Planning and
Development Department, 2022)..........................................................................................................................91
Figure 50. Utilities and Infrastructure locations in an RCP 8.5 100- year rain flood scenario in District 1.
Facilities in deep flood locations are shown with their names and flood level indicator (ex. L2). Source:
QC-Drainage Master Plan, Preliminary Report 2022, City Planning and Development Department,
2022 .............................................................................................................................................................................98
Figure 51. Utilities and Infrastructure locations in an RCP 8.5 100- year rain flood scenario in District 2.
Facilities in deep flood locations are shown with their names and flood level indicator (ex. L2). Source:
QC-Drainage Master Plan, Preliminary Report 2022, City Planning and Development Department,
2022 .............................................................................................................................................................................99
Figure 52. Utilities and Infrastructure locations in an RCP 8.5 100- year rain flood scenario in District 3.
Facilities in deep flood locations are shown with their names and flood level indicator (ex. L2). Source:
QC-Drainage Master Plan, Preliminary Report 2022, City Planning and Development Department,
2022 .......................................................................................................................................................................... 100
Figure 53. Utilities and Infrastructure locations in an RCP 8.5 100- year rain flood scenario in District 4.
Facilities in deep flood locations are shown with their names and flood level indicator (ex. L2). Source:

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QC-Drainage Master Plan, Preliminary Report 2022, City Planning and Development Department,
2022 .......................................................................................................................................................................... 101
Figure 54. Utilities and Infrastructure locations in an RCP 8.5 100- year rain flood scenario in District 5.
Facilities in deep flood locations are shown with their names and flood level indicator (ex. L2). Source:
QC-Drainage Master Plan, Preliminary Report 2022, City Planning and Development Department,
2022 .......................................................................................................................................................................... 102
Figure 55. Utilities and Infrastructure locations in an RCP 8.5 100- year rain flood scenario in District 6.
Facilities in deep flood locations are shown with their names and flood level indicator (ex. L2). Source:
QC-Drainage Master Plan, Preliminary Report 2022, City Planning and Development Department,
2022 .......................................................................................................................................................................... 103
Figure 56. Institutional areas in District 4 in an RCP 8.5 100- year rain flood scenario. Source: QC-
Drainage Master Plan, Preliminary Report 2022, City Planning and Development Department, 2022)
.................................................................................................................................................................................... 105
Figure 57. Commercial use areas in District 4 in an RCP 8.5 100- year rain flood scenario. (Source: QC-
Drainage Master Plan, Preliminary Report 2022, City Planning and Development Department, 2022)
.................................................................................................................................................................................... 106
Figure 58. Commercial use areas in District 1 in an RCP 8.5 100- year rain flood scenario. (Source: QC-
Drainage Master Plan, Preliminary Report 2022, City Planning and Development Department, 2022)
.................................................................................................................................................................................... 107
Figure 59. Industrial use areas in District 5 in an RCP 8.5 100- year rain flood scenario. (Source: QC-
Drainage Master Plan, Preliminary Report 2022, City Planning and Development Department, 2022)
.................................................................................................................................................................................... 108
Figure 60. Industrial use areas in District 6 in an RCP 8.5 100- year rain flood scenario. Source: QC-
Drainage Master Plan, Preliminary Report 2022, City Planning and Development Department, 2022)
.................................................................................................................................................................................... 109
Figure 61. Infection risk to Gastro-Enteritis (infected/1000 persons) in District 1 in an RCP 8.5 100 -
year Rain Flood Scenario ...................................................................................................................................... 113
Figure 62. Infection risk to Gastro-Enteritis (infected/1000 persons) in District 2 in an RCP 8.5 100 -
year Rain Flood Scenario ...................................................................................................................................... 114
Figure 63. Infection risk to Gastro-Enteritis (infected/1000 persons) in District 3 in an RCP 8.5 100 -
year Rain Flood Scenario ...................................................................................................................................... 115
Figure 64. Infection risk to Gastro-Enteritis (infected/1000 persons) in District 4 in an RCP 8.5 100 -
year Rain Flood Scenario ...................................................................................................................................... 116
Figure 65. Infection risk to Gastro-Enteritis (infected/1000 persons) in District 5 in an RCP 8.5 100 -
year Rain Flood Scenario ...................................................................................................................................... 117
Figure 66. Infection risk to Gastro-Enteritis (infected/1000 persons) in District 6 in an RCP 8.5 100 -
year Rain Flood Scenario ...................................................................................................................................... 118
Figure 67. Trace of West Valley Fault in the Vicinity of Quezon City ........................................................ 121
Figure 68. Earthquake intensity (in MMI) for M7.2 scenario of the Greater Metro Manila from the
GMMA-RAP study ................................................................................................................................................. 123

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Figure 69. Ground Shaking Severity in Quezon City for an M7.2 West Valley Fault Earthquake Scenario
in Modified Mercalli Intensity Scale. (Developed by EMI guided by GMMA-RAP) .................................. 126
Figure 70. Ground shaking severity for a M7.2 West Valley Fault earthquake scenario for District 1 127
Figure 71. Ground shaking severity for a M7.2 West Valley Fault earthquake scenario for District 2 128
Figure 72. Ground shaking severity for a M7.2 West Valley Fault earthquake scenario for District 3 129
Figure 73. Ground shaking severity for a M7.2 West Valley Fault earthquake scenario for District 4 130
Figure 74. Ground shaking severity for a M7.2 West Valley Fault earthquake scenario for District 5 131
Figure 75. Ground shaking severity (MMI) for a M7.2 West Valley Fault earthquake scenario for
District 6................................................................................................................................................................... 132
Figure 76. Intersection of District 2 along West Valley Fault with indication of major road segment
along the fault trace ............................................................................................................................................... 134
Figure 77. Intersection of District 3 along West Valley Fault with indication of major road segment
along the fault trace ............................................................................................................................................... 135
Figure 78. District 1 injuries requiring hospitalization for an M7.2 West Valley Fault earthquake
scenario caused by building damage. ................................................................................................................. 147
Figure 79. District 2 injuries requiring hospitalization for an M7.2 West Valley Fault earthquake
scenario caused by building damage. ................................................................................................................. 148
Figure 80. District 3 injuries requiring hospitalization for an M7.2 West Valley Fault earthquake
scenario caused by building damage. ................................................................................................................. 149
Figure 81. District 4 injuries requiring hospitalization for an M7.2 West Valley Fault earthquake
scenario caused by building damage. ................................................................................................................. 150
Figure 82. District 5 injuries requiring hospitalization for an M7.2 West Valley Fault earthquake
scenario caused by building damage. ................................................................................................................. 151
Figure 83. District 6 injuries requiring hospitalization for an M7.2 West Valley Fault earthquake
scenario caused by building damage. ................................................................................................................. 152
Figure 84. District 1 estimated fatalities for an M7.2 West Valley Fault earthquake scenario caused by
building damage. ..................................................................................................................................................... 153
Figure 85. District 2 estimated fatalities for an M7.2 West Valley Fault earthquake scenario caused by
building damage. ..................................................................................................................................................... 154
Figure 86. District 3 estimated fatalities for an M7.2 West Valley Fault earthquake scenario caused by
building damage. ..................................................................................................................................................... 155
Figure 87. District 4 estimated fatalities for an M7.2 West Valley Fault earthquake scenario caused by
building damage. ..................................................................................................................................................... 156
Figure 88. District 5 estimated fatalities for an M7.2 West Valley Fault earthquake scenario caused by
building damage. ..................................................................................................................................................... 157
Figure 89. District 6 estimated fatalities for an M7.2 West Valley Fault earthquake scenario caused by
building damage. ..................................................................................................................................................... 158
Figure 90 Estimate number of displaced population by barangay for M7,2 earthquake scenario ........ 164
Figure 91 Estimate of proportion of displaced population by barangay from the M7.2 earthquake
scenario .................................................................................................................................................................... 165
Figure 92 Displaced populations for the M7.2 earthquake scenario for District 1 and District 2 ........ 166

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Figure 93 Displaced populations for the M7.2 earthquake scenario for District 3 and District 4 ........ 167
Figure 94 Displaced populations for the M7.2 earthquake scenario for District 5 and District 6 ........ 168
Figure 95. Updated Flood and Landslide Susceptibility Map (MGB, 2021) ............................................... 172
Figure 96. Landslide susceptibility map of District 1 (recalibrated MGB data at moderate and high
susceptibility)........................................................................................................................................................... 176
Figure 97. Landslide susceptibility map of District 2 (recalibrated MGB data at moderate and high
susceptibility)........................................................................................................................................................... 177
Figure 98. Landslide susceptibility map of District 3 (recalibrated MGB data at moderate and high
susceptibility)........................................................................................................................................................... 178
Figure 99. Landslide susceptibility map of District 4 (recalibrated MGB data at moderate and high
susceptibility)........................................................................................................................................................... 179
Figure 100. Landslide susceptibility map of District 5 (recalibrated MGB data at moderate and high
susceptibility)........................................................................................................................................................... 180
Figure 101. Landslide susceptibility map of District 6 (recalibrated MGB data at moderate and high
susceptibility)........................................................................................................................................................... 181
Figure 102. Landslide susceptibility map with hospitals, health center, ……………………………………… .. 183
Figure 103. Landslide susceptibility map with hospitals, health center, evacuation ................................ 183
Figure 104. Landslide susceptibility map with hospitals, health center, ………………………………………… 185
Figure 105. Landslide susceptibility map with hospitals, health center, evacuation centers ................. 184
Figure 106. Landslide susceptibility map with hospitals, health center, evacuation ……………………… 186
Figure 107. Landslide susceptibility map with hospitals, health center, evacuation ................................ 185
Figure 108. Landslide susceptibility map with police and fire stations, …………………………………………… 187
Figure 109. Landslide susceptibility map with police and fire stations, ...................................................... 187
Figure 110. Landslide susceptibility map with police and fire stations, …………………………………………… 189
Figure 111. Landslide susceptibility map with police and fire stations, ...................................................... 188
Figure 112. Landslide susceptibility map with police and fire stations, ………………………………………….190
Figure 113. Landslide susceptibility map with police and fire stations, ...................................................... 189
Figure 114. Percent population per barangay in moderate to very high landslide susceptibility ------191
Figure 115. Percent population per barangay in moderate to very high landslide susceptibility .......... 191
Figure 116. Percent population per barangay in moderate to very high landslide susceptibility ………193
Figure 117. Percent population per barangay in moderate to tvery high landslide susceptibility ........ 192
Figure 118. Percent population per barangay in moderate to very high landslide susceptibility ………194
Figure 119. Percent population per barangay in moderate to very high landslde susceptibility ……….193
Figure 120. Percent population per barangay in high to very high landslde susceptibility ……………... 193
Figure 121. Percent population per barangay in high to very high landslde susceptibility ……………..194
Figure 122. Percent population per barangay in high to very high landslde susceptibility ……………. 194
Figure 123. Percent population per barangay in high to very high landslde susceptibility ……………. 195
Figure 124. Percent population per barangay in high very high landslde susceptibility ………………. 195
Figure 125. Percent population per barangay in high to ................................................................................ 196
Figure 126.. Hazard and Risk Quantities Reflecting the Indicators that are Incorporated in the BVI. . 199
Figure 127. Earthquake Hotspot Barangays in Three Tiers. ........................................................................ 206

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Figure 128. Flood Hotspot Barangays in Three Tiers. .................................................................................... 209

Figure 129. Landslide Hotspot Barangays. ....................................................................................................... 211
Figure 130. Combined Flood and Earthquake Hotspot Barangays. ............................................................. 214
Figure 131 Quezon City Government planning instruments from 2017-2022 ........................................ 219
Figure 132 Timeline of Quezon City awards and recognitions from 2017-2022 ..................................... 221
Figure 133 Quezon City’s 14-Point agenda...................................................................................................... 222

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Acronyms
AEP Annual Exceedance Probability
BDRRMP Barangay Disaster Risk Reduction and Management Plans
BSWM Bureau of Soils and Water Management
CENRO City Environmental and Natural Resources Department
CEO City Engineering Office
CHD City Health Department
CPDD City Planning and Development Department
CSCAND Collective Strengthening of Community Awareness for Natural Disasters
CSWD City Social Welfare and Development
DEM Digital Elevation Model
DENR Department of Environment and Natural Resources
DEPED Department of Education
DFE Design Flood Event
DO Dissolved Oxygen
DOH Department of Health
DOST Department of Science and Technology
DPWH Department of Public Works and Highways
DRR Disaster Risk Reduction
DRRM Disaster Risk Reduction and Management
DRRMO Disaster Risk Reduction and Management Office
EMI Earthquakes and Megacities Initiative
GA Geoscience Australia
GIS Geographic Information System
GK Gawad KALASAG
GMICE Ground Motion Intensity Equation
GMMA Greater Metro Manila Area
GMMA-RAP Enhancing Risk Analysis Capacities for Flood, Tropical Cyclone Severe Wind
and Earthquake for the Greater Metro Manila Area’ Project also referred to as
Greater Metro Manila Area Risk Analysis Project
GMPEs Ground Motion Prediction Equations
GMPMs Ground Motion Prediction Models
GSED Geo Spatial Exposure Database
GSO General Services Office
HVRA Hazards, Vulnerability, Risk Assessment
IFSAR Interferometric Synthetic Aperture Radar
ILQ Institutional Living Quarter
IPCC AR6 Intergovernmental Panel on Climate Change Sixth Assessment Report
IPCC SROCC Intergovernmental Panel on Clliate Change Special Report on the Ocean and
Cryosphere in a Changing Climate
JICA Japan International Cooperation Agency
KALASAG Kalamidad at Sakuna Labanan, Sariling Galing ang Kaligtasan
KKK Kataastaasan, Kagalanggalangan na Katipunan
LGU Local Government Unit
LiDAR Light Detection and Ranging
MERALCO Manila Electric Railroad and Light Company
MGB Mines and Geosciences Bureau
MMEIRS Metropolitan Manila Earthquake Impact Reduction Study
MMI Modified Mercalli Intensity Scale
MSL Mean Sea Level

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NAMRIA National Mapping and Resource Information Authority

NDSM Normalized Digital Surface Model
NEHRP National Earthquake Hazard Reduction Program
NHCS Napindan Hydraulic Control Structure
NOAH Nationwide Operational Assessment of Hazards
OBO Office of the Building Official
OSM OpenStreetMap
PAGASA Philippine Atmospheric, Geophysical, and Astronomical Services
Administration
PAR Philippine Area of Responsibility
PCG BFP PCG Bureau of Fire Protection
PEIS PHIVOLCS Earthquake Intensity Scale
PEMSEA Partnerships in the Environmental Management of the Seas of East Asia
PGA peak ground acceleration
PHIVOLCS Philippine Institute of Volcanology and Seismology
PIO Public Information Office
PRRCMO Pasig River Coordinating and Management Office
PSA Philippine Statistics Authority
QCDRRMO Quezon City Disaster Risk Reduction and Management Office
QCG Quezon City Government
QC-DMP Quezon City Drainage Master Plan
RA Republic Act
RCP 4.5 Representative Concentrated Pathways 4.5
RCP 8.5 Representative Concentrated Pathways 8.5
RCP 8.5 (2020-2039) RCP 8.5 early future
RIDF Rainfall Intensity Duration and Frequency
RPA Risk Profile and Atlas
SLR Sea level rise
TS Tropical Storm
TSS Total Suspended Solids
TWG Technical Working Group
UNDRR United Nations Office for Disaster Risk Reduction
UP University of the Philippines
UPAO Urban Poor Affairs Office
USEPA United States Environmental Protection Agency
USGS United States Geological Survey
VHU Vacant Homes Unit
VS30 time-averaged shear velocity to 30 m depth
WB World Bank
WVF West Valley Fault

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Link to Annex Tables

Drive Link: https://drive.google.com/drive/folders/

10A0Khji3yoZzpqI9NxvpblWp3vJG1MPS?usp=share_link

*You may also access using the bit.ly link and the QR Code shown

List of Tables in Annex

Table A.1 A count of evacuation centers in highly flood prone areas.
Table A.2 A count of health centers in highly flood prone areas.
Table A.3 A count of hospitals in highly flood prone areas.
Table A.4 A count of multi-purpose halls in highly flood prone areas.
Table A.5 A count of Barangay Halls in highly flood prone areas.
Table A.6 A count of Fire Stations in highly flood prone areas.
Table A.7 A count of Police Stations in highly flood prone areas.
Table A.8 Bridges located in various flood locations (RCP 8.5 100-year rain flood scenario)
Table A.9 A count of Sewage Treatment Plants (STPs) in highly flood prone areas.
Table A.10 A count of Pumping Station Facilities in highly flood prone areas.
Table A.11 A count of Materials Recovery Facilities in highly flood prone areas.
Table A.12 A count of Schools in highly flood prone areas.
Table A.13 A count of Markets in highly flood prone areas.
Note: Number of stalls information needs updating.
Table A.14 A count of Day Care centers in highly flood prone areas.

Link to Information, Education and Communication (IEC)

deliverables associated with the CDRA report.

Drive Link: https://drive.google.com/drive/folders/1vvR2f4cSSH-

1TN6Hs0MlPrOGkjuAn_7_?usp=share_link
*You may also access using the bit.ly link and the QR Code shown
• Audio-visual Presentation (AVP)

• Infographics for each hazard

• Mini booklet (available in both English and Filipino

languages)

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Definition of Terms
Adaptive Capacity
The ability of people, organizations and systems using available skills and resources, to adapt, adjust
and transform to the negative impact of hazardous events.

Capacity
The combination of all the strengths, attributes, and resources available within a community, society or
organization that can be used to achieve agreed goals.

Climate Change
The change in the state of the climate (i.e., temperature, humidity, atmospheric pressure, wind,
precipitation, and other meteorological variables) in a given region that can be identified by changes in
the mean and/or variability of its properties and that persists for an extended period, typically three
decades or longer.

Climate Change Adaptation

The process of adjustment to actual or expected climate and its effects. In human systems, it seeks to
moderate or avoid harm or exploit beneficial opportunities.

Contingency Planning
A management process that analyses disaster risks and establishes arrangements in advance to enable
timely, effective and appropriate responses.

Coping Capacity
The ability of people, organizations and systems, using available skills and resources, to manage
adverse conditions, risk or disasters. The capacity to cope requires continuing awareness, resources
and good management, both in normal times as well as during disasters or adverse conditions. Coping
capacities contribute to the reduction of disaster risks.

Critical Infrastructure
The physical structures, facilities, networks and other assets which provide services that are essential
to the social and economic functioning of a community or society

Critical Point Facility

Critical facilities are facilities needed for emergency response such as hospitals, fire stations,
emergency centers, police stations, certain public buildings that house functions needed by the public,
data centers, and power plants.

Disaster Risk
The potential loss of life, injury, or destroyed or damaged assets which could occur to a system, society
or a community in a specific period of time, determined probabilistically as a function of hazard,
exposure, vulnerability and capacity.

Disaster Management
The organization, planning and application of measures preparing for, responding to and recovering
from disasters.

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Disaster Risk Management

Disaster risk management is the application of disaster risk reduction policies and strategies to prevent
new disaster risk, reduce existing disaster risk and manage residual risk, contributing to the
strengthening of resilience and reduction of disaster losses.

Disaster Risk Reduction

Disaster risk reduction is aimed at preventing new and reducing existing disaster risk and managing
residual risk, all of which contribute to strengthening resilience and therefore to the achievement of
sustainable development.

Exposure
The totality of tangible assets (i.e., people, property, infrastructure, cultural heritage, natural and
biological systems, production capacity, services, institutions, or other material elements) present in
hazard zones that are, thereby, subject to potential losses.

Hazard
A process, phenomenon or human activity that may cause loss of life, injury or other health impacts,
property damage, social and economic disruption or environmental degradation.

High-loss facility
High-loss facilities are facilities whose failure carries a large potential for loss of life. Typically, they
include gas stations and other industrial facilities that contain hazardous materials, schools, markets,
malls, hotels and high occupancy buildings, hospitals, and assembly halls such as churches, sports
arenas, and others.

Mitigation
The lessening or minimizing of the adverse impacts of a hazardous event.

Preparedness
The knowledge and capacities developed by governments, response and recovery organizations,
communities and individuals to effectively anticipate, respond to and recover from the impacts of
likely, imminent or current disasters.

Prevention
Activities and measures to avoid existing and new disaster risks.

Recovery
The restoring or improving of livelihoods and health, as well as economic, physical, social, cultural and
environmental assets, systems and activities, of a disaster-affected community or society, aligning with
the principles of sustainable development and “build back better”, to avoid or reduce future disaster
risk.

Response
Actions taken directly before, during or immediately after a disaster in order to save lives, reduce
health impacts, ensure public safety and meet the basic subsistence needs of the people affected.

Resilience
The ability of a system, community or society exposed to hazards to resist, absorb, accommodate,
adapt to, transform and recover from the effects of a hazard in a timely and efficient manner, including
through the preservation and restoration of its essential basic structures and functions through risk
management.

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Rehabilitation
The restoration of basic services and facilities for the functioning of a community or a society affected
by a disaster.

Risk
The probability (or likelihood) of any exposed asset to sustain a certain amount of loss should a hazard
event happen.

Risk Identification & Assessment

A structured analytical process designed to determine the nature and extent of risk by analyzing
potential hazards and evaluating existing conditions of vulnerability that, together, could potentially
harm exposed people, property, services, livelihoods, and the environment on which they depend.

Social Impacts
Consequences of a hazardous event on the physical, economic, and psychological well-being of
individuals and on the functioning of a community. They also refer to the features of a social system
that help to avoid losses and maintain or recover satisfying living conditions after a shock.

Vulnerability
The conditions determined by physical, social, economic and environmental factors or processes which
increase the susceptibility of an individual, a community, assets or systems to the impacts of hazards.

Vulnerable Population
Vulnerable populations are individuals who are at greater risk of poor physical and social health status.
They are considered vulnerable because of disparities in physical, economic, and social health status
when compared with the dominant population. Vulnerable populations may be less able to anticipate,
cope with, resist, or recover from the impacts of a hazard. The degree to which populations are
vulnerable to disasters is not primarily dependent on proximity to the source of disaster. For instance,
it may take only a moderate hazard event to disrupt the well-being of many socially vulnerable
populations.

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Part 1:
Key Exposure Data

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1. Key Exposure Data

This chapter reproduces selected exposure data, including population distribution, lifelines and
building distribution, critical point facilities, and land use in Quezon City (QC). These are the main
exposure data that were considered in the hazard, vulnerability and risk assessment. The actual layers
identifying the characteristics of this data is included in the Geo-Spatial Exposure Database, which is
Deliverable 12 of the project.

1.1. Population Distribution in Quezon City

The population distribution in each of district of Quezon City are shown in Figure 1 to Figure 3. They
are based on the projected values for year 2022 provided by the QC City Planning and Development
Department (CPDD).

1.2. Critical Point Facilities

Information on critical facilities provides an overview of private and public sector capabilities providing
support, resources, programs, implementation, and services to save lives, properties and environment,
and restore essential facilities during an emergency. These datasets may include but not limited to
police stations, fire stations, evacuation center, hospitals, health centers. These data were collected
from different departments of Quezon City Government (mostly CPDD) and other national and private
agencies.

1.3. Lifeline and Utilities

Major lifeline and utilities that are affected by different hazards are road networks and water supply
facilities. These are datasets collected for the use risk assessment. Impacts to these infrastructures are
important to assess for appropriate response and continuous delivery of service during and after an
emergency.

1.4. Building Footprint

Based on the high resolution ortho-imagery and LiDAR-derived elevation model provided by the
National Mapping and Resource Information Authority (NAMRIA), building footprint was manually
digitized. Update occupancy distribution and story categories are key attributes in the risk assessment.
These were derived from data collected from the different department of the Quezon City
Government, national and private agencies, and open sources.

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Figure 1. Population data for District 1 and District 2 (Source: QC –CPDO 2022)

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Figure 2. Population data for District 3 and District 4 (Source: QC –CPDO 2022)

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Figure 3. Population data for District 5 and District 6 (Source: QC–CPDO 2022)

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1.5. Land Uses in Quezon City

The total land area of Quezon City is estimated at 16, 113 hectares. Residential uses include 3,898 hectares
of formal properties, 400 hectares of low-cost housing and 901 hectares of informal settlements. As of 2018,
the formal residential properties have a total of 3,898 hectares, socialized housing 800 hectares, and informal
settlements occupying 800 hectares. New residential subdivision developments took place Barangays Sauyo,
Tandang Sora, Talipapa, Culiat, Open spaces and vacant lots, are interspersed in these residential areas.

Pasong Tamo, Matandang Balara while high-rise or condominium type of developments are noted especially
at the southern half and some at the Lagro and Fairview areas in the north. In-filling of vacant areas
throughout the city can be seen from construction of new houses in once vacant lots of existing communities
and in the vacant portions of already occupied lots.

Institutional areas in 2018 have about 1,226 hectares comprising of school campuses, hospitals, government
offices, religious institutions, and other similar land uses. Between 2009 and 2018 District 6 had the biggest
share in this growth followed by District 2 with 10.6 hectares added, District 1 with 6 hectares and 2
hectares in District 3.

Figure 4 shows the land use area distributions for Residential-Informal Settlements and for Institutional for
Quezon City based on data provided by the QC City Planning and Development Office (CPDO).

The commercial uses cover 1,212 hectares of the city area. These areas follow a ribbon-like pattern along
roads and create commercial nodes over the city. Cubao, Balintawak and Novaliches are the old commercial
hubs in the city that have considerably expanded in land area covered.

The development and growth of North EDSA, Munoz and Sta. Mesa considerably expanded. Commercial
nodes also followed towards Ugong Norte and at Lagro-North Fairview vicinity such as at Ever
Commonwealth, Bagumbayan. In the last two decades, a rejuvenation of the Timog-Morato area, the
Banawe area, sometimes called the “Chinatown of Quezon City” and the addition of new commercial nodes
such as the U.P. Techno Hub and Town Center, the Robinson’s Magnolia and Ayala Mall at Balintawak are
among the evidences of commercial growth in the City.
These nodes are crossed by several main roads and are supported by various modes of transport such as
railways (e.g., LRTs, MRTs) and other public transport such as jeepneys, buses and taxis. The ride sharing
schemes (e.g., Grab, UV express) in the Metro has allowed more access to these commercial nodes.

Utility areas amount to 360 hectares of the City area and include water pipelines, power transmission lines,
easements for stormwater drainage utilities, sewerage treatment plants and water filtration, treatment, Q and
recovery facilities, the closed dump site (Payatas), telecommunication facilities, garages and terminals for
cargo and commuter transport units, gasoline stations and slaughterhouses.

The largest area of natural open space is the La Mesa Watershed Reservation; also known as the Novaliches
Reservoir. It is 2500-hectare watershed hectares protected area that feeds to the La Mesa Dam and
Reservoir, the primary source of potable drinking water for Metro-Manila population.

Figure 5 shows a distribution of commercial and industrial use areas in Quezon City. One can find the clusters
of industrial sites to be located on the western side of Quezon City and adjacent to waterways.

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Figure 4. Residential Use Areas and Institutional Use Areas in Quezon City (Source: QC-City Planning and Development Department (CPDD), 2019)

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Figure 5. Commercial Use Areas and Industrial Use Areas in Quezon City (Source: QC-City Planning and Development Department (CPDD), 2019)

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Part 2:
Climate Change Hazards

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2. Climate Change Hazards

This section summarizes climate projections in Metro Manila, the implications of climate change in Quezon City
and the tools for climate risk assessments, in terms of changes in mean values of temperature and rainfall as
well as in terms of trends of extreme temperature and rainfall. More in-depth discussion, additional pertinent
data, projections and potential impacts of climate change are provided in Deliverable 8: Hazard, Vulnerability
and Risk Assessment of 142 Barangays, dated September 30, 2022.

Climate-resilient disaster risk reduction planning requires a careful consideration of the so-called climate
projections or climate scenarios. The CERAM tool is introduced to gather initial perceptions and input from
relevant stakeholders on climate change impact for various sectors. Training was provided to officials from the
142 barangays of Quezon City to introduce them to the CERAM tool and to get them engaged in
understanding the terminologies and concept behind climate change hazard assessment as well as to raise
awareness on climate change.

2.1. What is Climate Change?

The United Nations defines climate change as referring to long-term shifts in temperature and weather
patterns. These shifts may be natural such as through the variations in the solar cycle. But since the 1800s,
human activities have been the main driver of climate change, primarily due to burning fossil fuels like coal, oil
and gas, and land-use change. Burning fossil fuels generates greenhouse gas emissions that act like a blanket
wrapped around the Earth, trapping the sun’s heat, and raising temperatures. Examples of greenhouse gas
emissions that are causing climate change include carbon dioxide and methane. These come from using
gasoline for driving a car or coal for heating a building, for example. Clearing land and forests can also release
carbon dioxide. Landfills for garbage are a major source of methane emissions.

2.2. Baseline Data and Climate change projections for temperature

and rainfall
This section discusses the parameters of hydro-meteorological hazards such as baseline and decadal
climatological data on Quezon City and Metro Manila.

2.2.1. Baseline Data

Quezon City Climate Type

Quezon City, situated in the heart of Metro Manila, is endowed with a climate best characterized as Climate
Type I (based on the rainfall-dependent Modified Coronas climate classification) shown in Figure 6. The City
has distinct wet (June to September) and dry (December to April) periods (PAGASA,2018).

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Figure 6. Climate Types under Corona’s Classification (Source: Science Garden)

Temperature
In a similar manner as that of the changing climate that is being observed regionally and nationally, Quezon
City has also been experiencing some changes in terms of weather/climate variables called climate impact
drivers; notably, temperatures and rainfall. Referring to Table 1 below, the following observations can be made:
• The mean annual rainfall has been steadily increasing but in a highly variable way. A gradual increase is
seen in the first two assessment periods (1961-1990 and 1971-2000), then a more significant increase
(as much as 13%) between the two assessment periods, then a decrease in the 1981-2020 assessment.
• Minimum temperatures are increasing faster than maximum temperatures; and mean temperatures
have also steadily increased.

Table 1. Decadal changes in climatological normals of temperatures and rainfall observed in Science Garden, Quezon City.
Weather variable Climatological Climatological Climatological Climatological
normals normals normals normals
(1961-1990) (1971-2000) (1981-2010) (1991-2020)

Maximum Temperature (°C) 31.8 32.1 32.2 32.1

Minimum Temperature (°C) 22.3 22.8 23.1 23.6

Mean Temperature (°C) 27.1 27.4 27.7 27.8

Rainfall (mm) 2,403.8 2,531.0 2,574.4 2,785.6

Number of rainy days 134 135 153 143

Note: Climatological normals are 30-year averages of these weather parameters and being indicated here are essentially
moving 30-year averages. (Adopted from PAGASA’s Climatological Normals)

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Figure 7 and Figure 8 show the observed trends in the climate of Quezon City, in terms of temperature and
rainfall anomalies or departures from 30-year (1990-2020) averages or normals.

Annual Departure of Temperature from the

Normal (1991-2020) in Science Garden
1

0.5

0
Departure

-0.5
y = 0.0244x - 1.0337
R² = 0.6434
-1

-1.5

-2
1961
1963
1965
1967
1969
1971
1973
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
2005
2007
2009
2011
2013
2015
2017
2019
Years
Figure 7. Annual departure of mean temperature from the normal (1991-2020) at Science Garden, Quezon City (Source:
PAGASA)

Annual Departure of Rainfall from the

Normal (1991-2020) in Science Garden
2000
y = 10.307x - 474.19
1500 R² = 0.0963

1000

500
Departure

-500

-1000

-1500
1967
1961
1963
1965

1969
1971
1973
1975
1977
1979
1981
1983
1985
1987
1989
1991
1993
1995
1997
1999
2001
2003
2005
2007
2009
2011
2013
2015
2017
2019

Years

Figure 8. Annual departure of rainfall from the normal (1991-2020) at Science Garden, Diliman, Quezon City. (Source:
PAGASA)

These graphs indicate increasing trends in both annual mean temperatures and annual rainfall totals in Quezon
City. Trend line analysis indicates that the yearly mean temperature has increased by one degree Celsius over
50 years.

Rainfall Distribution and Rainfall Extremes for Metro-Manila

Annual rainfall distribution is shown in Figure 9. The year 2012 with an annual rainfall total of 4,431.7 mm
(brought about by both strong monsoon and tropical cyclone-associated rains) was the wettest year on record.
The strongest floods usually are brought by one-day to two-day rainfall periods.

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Figure 9. The Annual Rainfall Totals by Year from 1971 to 2020 Observed at the Science Garden Station in Quezon City
(Source: PAGASA)

The highest rainfall totals for a one-day rainfall recorded at Science Garden was on September 26, 2009,
pouring 455mm of rainfall brought by severe tropical storm Ondoy (International: Ketsana). People from Metro
Manila remember that Ondoy produced one of the worst floods in Metro Manila. However, the southwest
monsoon torrential rains from August 1 to 8, 2012 brought in the highest two-day rainfall totals in Metro
Manila with 684mm.

2.2.2. Climate Projections

Climate projections are simply defined as plausible climate futures that could happen in any area of interest.
These are quantitative projections of future climate change presented in ranges. The ranges allow for
differences in how future climate may evolve in an area of interest due to three factors, namely: The
greenhouse gas emissions, the climate response and the natural variability in the climate.

The Philippine Atmospheric, Geophysical and Astronomical Services Administration (PAGASA) developed and
prepared climate projections for the country and published these in a Report entitled “Observed Climate
Trends and Projected Climate Change in the Philippines” in 2018. This was followed by another set of climate
trends and projected climate extremes developed and prepared jointly by the PAGASA, the Manila
Observatory and the Ateneo de Manila University in a Report entitled “Philippine Climate Extremes Report
2020: Observed and Projected Climate Extremes in the Philippines to Support Informed Decisions on Climate
Change Adaptation and Risk Management” in recognition of the glaring fact that extreme weather/climate
events have been increasingly causing many adverse impacts on communities and natural and managed
systems in the country.

These two sets of climate projections consist of changes in the mean values of temperature and rainfall; in the
tropical cyclone occurrence; and in sea level rise in the country (in PAGASA,2018) and in the extreme
temperature and rainfall indices (in Philippine Climate Extremes Report 2020).

Table 2 below delineates the features and differences between these two sets of projections for Metro Manila.

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Table 2. Characteristics and features of the two Climate Trends and Projections Report; the PAGASA, 2018 and the
Philippine Climate Extremes Report, 2020.
Characteristics Climate projections in the PAGASA, Climate projections in the
2018 Report Philippine Extremes Report, 2020

Greenhouse gas RCP 4.5 and RCP 8.5 RCP 4.5 and RCP8.5
emission scenarios used
Time frames Mid-21st century (2036-2065) Early future (2020-2039)
Late-21st century (2070-2099) Mid-future (2045-2065)
Late-future (2080-2099)
Baseline used 1971-2000 climatological normals* 1986-2005 climatological normals
Weather/ climate Observed values based on 1971-2000 Observed values based on 1986-
variables or parameters climatological normals and range of 2005 climatological normals and
projected changes of temperatures range of projected values of each
(maximum, minimum and mean) and of the climate extremes indices
rainfall
*Normals means the 30-year average value of the variable or parameter. Source: PAGASA, 2018, 2020

2.2.3. Seasonal mean temperature and rainfall projections

A set of ranges in seasonal changes in temperature and rainfall under two emission scenarios (the moderate-
emission or RCP 4.5 and the worst-emission scenario or RCP8.5) during the mid-century (2036-2065) for
Metro Manila are provided in the PAGASA, 2018 Report and given below in Table 3 and Table 4. respectively.

Table 3. Projected seasonal changes in temperature in ºC and rainfall in percentages under the medium- emission scenario
(RCP 4.5) during the mid-21st century (2036-2065).

Climate variable Dec-Jan-Feb Mar-Apr-May Jun-Jul-Aug Sept-Oct-Nov

Mean Temperature 1.0 to 1.6 °C 0.9 to 1.7°C 1.0 to 1.8°C 1.0 to 1.8°C
Rainfall 0.1%-decrease to 0.7% to 25.7%- 21.3%-decrease 10%-decrease to
55%-increase increase to 0.4%-decrease 7.7 %-increase
Source: PAGASA, 2020

Table 4. Projected seasonal changes in mean temperature in ºC and rainfall in percentages under the high -emission
scenario (RCP 8.5) during the mid-21st century (2036-2065)

Climate variable Dec-Jan-Feb Mar-Apr-May Jun-Jul-Aug Sept-Oct-Nov

Mean Temperature 1.2 to 1.9 ºC 1.3 to 2.2 ºC 1.3 to 2.3 ºC 1.3 to 2.2 ºC
Rainfall 2.7% to 55%- 7.2%-decrease to 17%-decrease to 8%-decrease to
increase 14.8 %-increase 7.7 %-increase 19.9 %-increase
Source: PAGASA, 2020

The climate futures indicate the differentiated projected changes in rainfall during the four seasons of the
country for a specific time period (2036-2065). The actual change will depend on the actual global temperature
increase and will be influenced by whether the world follows a medium-emission or a high-emission scenario.
For example, for the coldest season of the year (December to February) temperature increases will range from
1.0 ºC to 1.9 ºC. Whereas, the projected changes in rainfall are from a 0.1 %-decrease to as much as a 55%
increase. On the other hand, during the warmest season of the year (March to May), the mean temperature
during the same period of 2036-2065, will increase from 0.9 ºC to 2.2 ºC. For rainfall, during this season, the
range of increase will be from 0.7%-increase to 14.8%-increase.

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2.2.4. Projections on extreme temperatures and rainfall

For Metro Manila, a set of ranges in changes in extreme temperature and rainfall indices under two emission
scenarios (the moderate-emission RCP 4.5 and the worst-emission or RCP8.5) are given.
gives a summary of the terminologies used for temperature and rainfall indices to describe the projections.

Table 6 and 7 below provide the projections for median extreme temperature and median extreme rainfall
indices as given in the Philippine Climate Extremes Report 2020. The median values are the most suitable for
planning purpose and are recommended by EMI.

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Table 5. Summary of temperature and rainfall indices

Name Units Definition Description

Temperature Extremes Indices
Magnitude
TNn °C Minimum daily minimum temperature Coldest nighttime temperature
TNm °C Mean daily minimum temperature Average nighttime temperature
TNx °C Maximum daily minimum temperature Warmest nighttime temperature
TXn °C Minimum daily maximum temperature Coldest daytime temperature
TXm °C Mean daily maximum temperature Average daytime temperature
TXx °C Maximum daily maximum temperature Warmest daytime temperature
DTR °C Average range of daily maximum and Daily temperature range
minimum temperature
Frequency
TN10p % Percentage of days when daily Fraction of cold nights
temperature <10th percentile
TN90p % Percentage of days when daily minimum Fraction of warm nights
temperature>90th percentile
TX10p % Percentage of days when maximum Fraction of cool days
temperature <10th percentile
TX90p % Percentage of days when maximum Fraction of hot days
temperature>90th percentile
Duration
WSDI days Warm Spell Duration Indicator: number of Number of days contributing to a
days contributing to events when 6 or warm period
more consecutive days have daily
maximum temperature >90th percentile
Rainfall Extremes Indices Magnitude
PRCPTOT mm Total precipitation on wet days Total wet-day rainfall
SDN mm/day Simple daily intensity index: total rainfall Average daily rainfall intensity
divided by the number of wet days
Rx1day mm Maximum amount of rainfall that falls in 1 Maximum 1-day rainfall total
day
Rx5day mm Maximum amount of rainfall that falls in 5 Maximum 5-day rainfall total
consecutive days
P95 mm 95th percentile of wet days Rainfall on very wet days
P99 mm 99th percentile of wet days Rainfall on extremely wet days
R95p mm Total daily rainfall >95th percentile Total rainfall from very wet days
R99p mm Total daily rainfall >99th percentile Total rainfall from extremely wet
days
Frequency
P95d days Number of days when daily rainfall>95th Number of very wet days
percentile
P99d days Number of days when daily rainfall>99th Number of extremely wet days
percentile
Duration
CWD days Consecutive wet days: maximum number Longest wet spell
of consecutive days when daily rainfall> 1
mm
CDD days Consecutive dry days: maximum number Longest dry spell
of daily rainfall < 1 mm
Source: PAGASA, 2020

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Table 6. Temperature Extreme Indices for Metro Manila

TEMPERATURE Baseline Scenario Range EARLY-CENTURY MID-CENTURY Projected LATE CENTURY Projected
Climate Extreme Indices Projected Change Change Change

Description Projected Projected Projected Projected Projected

CODE Col 3 Col 4 Col 4 Projected
(unit ) Change Value Change Value Change

Coldest RCP4.5 Median 19 1 19.3 1.3 19.6 1.6

nighttime
TNn 18
temperature
(˚C) RCP8.5 Median 19 1 19.8 1.8 21.5 3.5

Average RCP4.5 Median 23.8 0.7 24.3 1.2 24.6 1.5

nighttime
TNm 23.1
temperature
(˚C) RCP8.5 Median 23.9 0.8 24.8 1.7 26.3 3.2

Warmest RCP4.5 Median 27.3 0.7 27.8 1.2 28.2 1.6

nighttime
TNx 26.6
temperature
(˚C) RCP8.5 Median 27.4 0.8 28.3 1.7 29.7 3.2

Coldest RCP4.5 Median 26.4 0.7 26.8 1.2 27.1 1.4

daytime
TXn 25.7
temperature
(˚C) RCP8.5 Median 26.4 0.8 27.3 1.7 28.6 3

Average RCP4.5 Median 32.4 0.6 33 1.2 33.3 1.5

daytime
TXm 31.8
temperature
(˚C) RCP8.5 Median 32.6 0.8 33.4 1.6 35 3.2

Warmest RCP4.5 Median 37.1 0.6 37.7 1.3 38.2 1.7

daytime
TXx 36.4
temperature
(˚C) RCP8.5 Median 37.3 0.9 38.2 1.8 40.1 3.6

Daily RCP4.5 Median 8.6 -0.1 8.7 0 8.8 0.1

DTR Temperature 8.7
Range (˚C) RCP8.5 Median 8.7 0 8.7 0 8.7 0

RCP4.5 Median 3.3 -8.1 1.7 -9.7 1.3 -10.1

Fraction of
TN10p 11.4
cold nights (%)
RCP8.5 Median 2.6 -8.8 1 -10.4 0.4 -11.1

Fraction of RCP4.5 Median 35.9 24.6 59.3 48 70.7 59.4

TN90p warm nights 11.5
(%) RCP8.5 Median 43.2 31.9 78.3 67 96.5 85.2

RCP4.5 Median 5 -6.5 2.4 -9.2 1.7 -9.9

Fraction of
TX10p 11.4
cool days (%)
RCP8.5 Median 4.1 -7.5 1.6 -10 0.9 -10.6

RCP4.5 Median 26.3 14.7 49.7 38.2 61.9 50.3

Fraction of hot
TX90p 11.6
days (%)
RCP8.5 Median 35.4 23.8 63.2 51.6 90.6 79

Number of
days RCP4.5 Median 73.6 66.5 226.2 219 364.3 357.1
WSDI contributing to 7.2
a warm period RCP8.5 Median 129.1 121.9 448.8 441.6 930.3 923.1
(days)

Source: PAGASA, 2020

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Table 7. Rainfall Extreme Indices for Metro Manila

RAINFALL Baseline Scenario Range EARLY-CENTURY MID-CENTURY Projected LATE-CENTURY
Climate Extreme Indices Projected Change Change Projected Change
Description Projected
CODE Col 3 Col 4 Col 4 Projected Projected Projected Projected Projected
(unit ) Change
Change Change
Value Value Value

RCP4.5 Median 2204.6 -55.1 2214.8 -44.9 2147 -112.7

Total wet-day
PRCPTOT 2259.8
rainfal (mm)
RCP8.5 Median 2255.6 -4.1 2198.9 -60.9 2029.1 -230.6

Average daily RCP4.5 Median 15.3 -0.2 15.1 -0.3 14.6 -0.8
rainfall
SDII 15.4
intensity
(mm/day) RCP8.5 Median 15.3 -0.2 14.9 -0.6 14.2 -1.2

Maximum 1- RCP4.5 Median 126.9 5.5 132.3 10.9 124.7 3.3

Rx1day day rainfall 121.4
total (mm) RCP8.5 Median 135.7 14.3 131.3 9.9 128.2 6.8

Maximum 5- RCP4.5 Median 289.3 20.5 290.5 21.7 261.9 -6.9

Rx5day day rainfall 268.8
total (mm) RCP8.5 Median 277.6 8.8 289 20.2 279 10.2

Rainfall on RCP4.5 Median 50.6 -1.8 51.3 -1.1 48.5 -3.8

P95 very wet days 52.4
(mm) RCP8.5 Median 51.1 -1.3 50.4 -1.9 48.4 -3.9

Rainfall on RCP4.5 Median 100 -1 106.1 5.2 98.8 -2.2

P99 extremely wet 101
days (mm) RCP8.5 Median 98.9 -2.1 103.5 2.5 103.3 2.4

Total rainfall RCP4.5 Median 564.2 -21.6 632 46.2 552.4 -33.4
R95p from very wet 585.8
days (mm) RCP8.5 Median 590.6 4.8 579.6 -6.1 543.2 -42.6

Total rainfall RCP4.5 Median 175.9 -13.9 216.2 26.4 198.6 8.9
from
R99p 189.7
extremely wet
days (mm) RCP8.5 Median 200.3 10.5 215.4 25.6 198.3 8.6

Number of RCP4.5 Median 6.7 -0.4 7.1 0 6.4 -0.8

P95d very wet days 7.2
(days) RCP8.5 Median 6.9 -0.2 6.8 -0.4 6.3 -0.9

Number of RCP4.5 Median 1.5 0 1.7 0.2 1.5 0

P99d extremely wet 1.5
days (days) RCP8.5 Median 1.5 0 1.6 0.1 1.5 0

RCP4.5 Median 14.4 -2.7 17 0 15.7 -1.3

Longest wet
CWD 17
spell (days)
RCP8.5 Median 15.5 -1.5 17.2 0.2 15.3 -1.7

RCP4.5 Median 37.4 -2.4 37 -2.9 41.8 2

Longest dry
CDD 39.8
spell (days)
RCP8.5 Median 37.1 -2.7 36.7 -3.1 37.2 -2.6
Source:
PAGASA, 2020

It is to be noted that this study this study focuses on two indices, i.e., extreme temperatures and extreme
rainfall for the early 21st century (2020-2039) and not the whole set of extreme indices. These have the most
impact on floods and landslides hazards.

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2.3. Tropical cyclones, and sea-level rise (SLR) baseline data and
climate change projections

This section provides the baseline data and climate change projections for tropical cyclone and sea-level rise
(SLR)

2.3.1 Tropical Cyclone Baseline Data

Tropical Cyclone (TC) classifications by PAGASA are shown in Table 8. It also gives the range of wind speeds
used prior to 2015, between 2015 and 2022, and recently in March 2022. In 2015, PAGASA added the
category of a super typhoon and recently, the ranges of wind speeds were redefined between a typhoon and a
super typhoon category.

Table 8. Tropical Cyclone (TC) Classifications by PAGASA.

Classification May 2015 to Feb March 2022 to

Before May 2015 2022 Present
TD-Tropical Depression 63 kph or less 61 kph or less 61 kph or less
TS-Tropical Storm 64-118 kph 62-88 kph 62-88 kph
STS-Severe Tropical Storm 89-117 kph 89-117 kph

TY-Typhoon More than 118kph 118-120 kph 118-184 kph

STY-Super Typhoon More than 120 kph More than 184 kph

A total of 71 tropical cyclones have crossed within 50 km from Metro Manila from 1948 to 2021. Among these
13 (18%) were tropical depressions, 19 (27%) were tropical storms, 4 (6%) were severe tropical storms, 26
(36%) were typhoons, and 9 (12%) were super typhoons. Thus, close to 50% of the tropical cyclones were
either typhoons or super typhoons. About 18 of the 71 have crossed Metro-Manila. Typhoons that crossed
within a 50-kilometer radius of Metro Manila from 1960 to 2021.

The strongest of these windstorms were super typhoons Olive, Lusing, Welming in the 60’s, Yuling and Unding
in the 70s, Rosing and Loleng in the 90’s. Typhoon Ulysses and Severe Tropical Storm Ondoy are shown for
reference.

2.3.2 Frequency of recurrence of tropical cyclones

How often does a tropical cyclone of a certain category recur (Filipino-maulit) in Metro Manila? Table 9
provides and estimates for storms that cross within 50 kilometers of Metro-Manila. On average, super
typhoons recur almost every 90 months (7.5 years), while typhoons recur every 35 months (2.9 years).

Table 9. Estimated Average Return of Tropical Cyclones Within 50 km Crossing Metro Manila
Category Number of First Last No. of Number of Average
Occurrence Occurrence Occurrence months in Recurrence return
between (mos,)
TD 13 20/11/1948 11/08/2002 644 12 53.7
TS 19 12/10/1957 11/06/2020 751 18 41.7
STS 4 28/04/1971 24/09/2009 460 3 153.3

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TY 26 23/07/1948 06/09/2021 877 25 35.1

STY 9 23/06/1960 29/10/2020 724 8 90.5

2.3.3. Projections on tropical cyclone occurrence for Metro Manila

There are no detailed projections for tropical cyclone occurrence in Metro Manila. The PAGASA 2018 Report
provides projections for the whole country. It is highlighted that tropical cyclones in the western North Pacific
basin (in which the Philippine Area of Responsibility or the so-called PAR is situated) will see an increase in the
intensity of those classified as typhoons and super typhoons. Tropical cyclone frequency is not projected to
increase, although there have been changes in their trajectories. It is, moreover, to be noted that in the
recently released Intergovernmental Panel on Climate Change Sixth Assessment Reports (IPCC SROCC, IPCC
AR6), the projections on these short-lived weather systems are also affirmed.

2.3.4. Projection on the sea-level rise for Metro Manila

Projections on the sea-level rise as indicated in the PAGASA, 2018 Report is for the country and the increase is
found to be slightly larger than the global rate. Under both emission scenarios (RCP 4.5 and RCP 8.5, the
projected sea-level rise will be approximately the same until the mid-century (2036-2065), diverging only
towards the end of the 21st century when that of the RCP 8.5 will be at 0.2m. It is being highlighted that the
projected increase in sea level may worsen storm surge hazards and must be considered in disaster risk
reduction planning.

Other important related findings are those of the Partnerships in Environmental Management for the Seas in
East Asia (PEMSEA) 2012 study on integrating climate change risk scenarios into coastal and sea use planning
in Manila Bay. The study stressed that the areas around Manila Bay are vulnerable to inundation under sea-
level rise and that extreme relative sea level consists of the effects of global warming, rate of subsidence, and
storm surge during the passage of intense tropical cyclones. The most important findings for Quezon City are:

1) Under a 1-m sea-level rise in the Manila Bay area, 16,365. 899 ha of land area in Quezon City will be
affected, 0.03 % of which (or an estimated 5.463 ha) will be inundated; and
2) Under a 2-m sea-level rise, 14.735 ha (or approximately 0.09%) of the affected areas will be under
water.

The different sets of projections (e.g., increases in mean temperatures, changes in rainfall, changes in extreme
temperature and rainfall indices, frequency and intensity of tropical cyclones and sea-level rise) will have
serious implications for the characterization of future climate hazards and risks; in particular, those of floods,
including cascading impacts on the population, urban use, lifelines, and critical facilities.

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2.4. The Climate Extremes Risk Analysis Matrix (CERAM)

2.4.1 What is the CERAM Tool?

The Climate Extremes Risk Analysis Matrix (CERAM) Tool was developed to provide decision makers/policy
makers a wider range of plausible futures for adaptation planning. The CERAM Tool can be used to update the
risk assessments in the Quezon City’s Enhanced LCCAP (2020-2050) which had used the first set of
projections (on the changes in seasonal mean temperature and rainfall), as it can identify areas and sectors
which are at high risk to climate extremes. It will, however, require more in-depth rapid disaster risk
assessment and climate change adaptation planning. Additionally, it is a tool to collect and process inputs from
various stakeholders, typically completed either individually by key informants or in small-group workshop
settings.

We need to change Quezon City’s Enhanced LCCAP (2020-2050) to Quezon City’s Enhanced LCCAP (2021-
2050).

2.4.2. Training and implementation of the CERAM Tool with Quezon City stakeholders
A series of trainings/workshops were held in October 21, 28 and November 4, 2022, with barangay
representatives to undertake the CERAM exercise. Table 10 shows selected annual extreme indices used in
the exercise. The first objective was to train the participants in the CERAM tool and to raise their awareness on
climate change. The second objective was to use the set of future changes to get the participant’s perceptions
and inputs on the impacts of and adaptation to climate change in Quezon City relative to populations,
communities, and ecosystems, and more particularly to identify areas and sectors at high risk from climate
extremes. The general approach is to undertake a more in-depth disaster risk assessment that would lead to
climate change adaptation planning for these particular areas. Due to time limitations, only two indices each
were used in the workshop; namely, maximum daytime temperature and fraction of hot days for extreme
temperature indices to examine the impacts of increasing heat index, and maximum 1-day and maximum 5-
day rainfall totals to analyze impacts on flood hazards. An important consideration for participants was the
flooding already occurring regularly in the barangays. It was important to examine how these flooding events
will evolve in the future considering the projections.

The CERAM exercise is quite elaborate and this was the first exposure to this type of exercise for the majority
in the audience. Thus, this was more an opportunity to undertake training and to get the participants familiar
with its process and content. The objective is for Quezon City to further develop the capacity to use this Tool
and to continue these types of exercises as a training tool first, and also to start the collection of related
pertinent data that would ultimately be used in the risk analysis/assessment and planning process on the
impacts of climate change.

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Table 10 Summary of extreme temperature and rainfall indices used in the workshop

Name Units Definition Description

Temperature Extremes Indices
Magnitude
TXx °C Maximum daily maximum temperature Warmest daytime temperature
DTR °C Average range of daily maximum and minimum temperature Daily temperature range
Frequency
TN10p % Percentage of days when daily temperature <10th percentile Fraction of cold nights
th
TN90p % Percentage of days when daily minimum temperature>90 percentile Fraction of warm nights
TX90p % Percentage of days when maximum temperature>90th percentile Fraction of hot days
Duration
WSDI days Warm Spell Duration Indicator: number of days contributing to events Number of days contributing to a warm
when 6or more consecutive days have daily maximum temperature period
>90th percentile
Rainfall Extremes Indices Magnitude

PRCPTOT mm Total precipitation on wet days Total wet-day rainfall

Rx1day mm Maximum amount of rainfall that falls in 1 day Maximum 1-day rainfall total
Rx5day mm Maximum amount of rainfall that falls in 5 consecutive days Maximum 5-day rainfall total

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2.4.3. Workshop Summary of Results

Table 11 summarizes the inputs provided by stakeholders of potential impacts of projected changes in temperature and rainfall extremes in selected sectors. The
considered sectors are: water resources, including associated flooding risks, health, environment and biodiversity, infrastructure, including critical facilities and
lifelines, services (including energy) supply and delivery.

Table 12 gives a summary of the adaptation options given by participants relative to the same selected sectors. It is interesting to note the range of options
provided by the stakeholders indicating a fairly high level of interest and knowledge in climate change issues.

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Table 11 Examples potential impacts of projected changes in temperature extreme indices on selected sectors collected from the stakeholder consultations on Oct 21 and 28 and
Nov 4, 2022, workshops
Sectors Potential impacts
Water resources, Impacts (both positive and negative) on water supply to result from increases/decreases in rainfall extremes, such as:
including associated
flooding risks • Drier conditions resulting from increase in extreme temperature indices and those from projected decrease in extreme rainfall
indices can lead to lower streamflow and lower water supply that could impact adversely on communities in terms of less
water (water rationing) and possibly, less water quality;
• More frequent and longer dry conditions could lead to water service disruption;
• Increased rainfall extremes could increase flood risks to low-lying areas and those already identified to be at moderate and
high risks for floods;
• Increase in the extreme 1-day and 5-day rainfall totals may lead to less stable ground stability (Bgy. Payatas) and possibly lead
to land movement or landsides in slopes near creeks;
• Increase in extreme rainfall indices could lead to challenges in water management and flood control infrastructures;
• Increase in extreme rainfall indices could lead disruption in water service delivery and quality of water.

Health • Higher temperatures shorten the life stages in the life cycle of mosquitoes that lead to their increased number and thus,
more biting rates and increased transmission, spread and prevalence of dengue;
• Changes in extreme rainfall frequency and intensity could increase occurrences of dengue and gastro-enteritis and other
diseases such as leptospirosis and others;
• Projected increase in extreme temperature indices such as warmest daytime temperature and fraction of hot days could lead
to more incidences of respiratory illnesses including asthma and skin diseases (rashes) among the young and hypertension
and heart attack among the elderly;
• Mortality, especially in young children and the elderly and those with comorbidities are heat-related with a daytime and
nighttime threshold value of 38.3°C and 24. 3°C, respectively;
• Increases in incidences of discomfort, irritable, difficulty in sleeping and, bouts of depression, both when indices of extreme
temperature and rainfall increase;
• Projected food shortages;
• Could lead to increased air pollution;

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• Could possibly lead to more street dwellers.

Environment and • Improper waste disposal during rainfall extremes could lead to degraded environment including clogged drainage, pollution,
biodiversity and unsanitary conditions;
• Dryness in some land areas under extreme temperature;
• Could lead to more fires;
• Wilting of plants under heat stress.

Infrastructure, • Infrastructures are prone to damages, especially from excessive rainfall, as they age;
including critical • Extreme temperatures could lead to structural damage in bridges and other infrastructures, such as in light railway tracks,
facilities and etc.;
lifelines • Extreme rainfall amounts, including those from intense typhoons result to flooding, landslides, erosion that could cause
infrastructures to weaken;
• Extreme rainfall leading to floods could lead to closure of roads and bridges, including the electrical operation of traffic and
streetlights;
• Extreme rainfall could lead to partial/total damages to properties (houses) and even slow down communication.

• Increase in drier conditions (increase in extreme temperature indices) could lead to heat events and demand for more
energy supply;
• Increase in extreme temperature indices could lead to problems in service delivery and even disruption/brown-outs;
• Increase in rainfall extreme indices could lead to more service delivery disruption and even, stoppage;
• Hospitals could be overwhelmed with medical emergencies and with increased number of patients after events of increases
in extreme temperature and rainfall indices;
• Schools could be rendered unable to cope with damages in their resources, not discounting school suspensions;
• Disruption of services, including means of communications.

Mobility • Increase in extreme rainfall indices could lead to more frequent flooding events and higher flood water levels resulting to
less mobility among the population and most affected are school children, housewives needing to purchase food and
medicinal supplies and wage earners commuting for work;
• Difficulty in doing rescue operations when events warrant these services;

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• Difficulty in moving people to evacuation centers, hospitals.

Work productivity Increase in both extreme temperature and extreme rainfall indices could lead to decreased work productivity, thereby could lead to
and livelihoods less income and cascading effects could be diminished capacity to provide for family’s basic needs;

• Loss of jobs;
• Could lead to price increases and hoarding;
• Increased expenditures on utilities;
• Economic losses.

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Table 12. Summarized list of desired adaptation options collected from the stakeholder consultations on Oct 21 and 28 and Nov 4, 2022, workshops
Sectors Adaptation Options
Water • Structural and physical: engineering and built • Social: educational, informational, • Institutional:
resources environment, technological, ecosystem-based behavioral. laws/regulations/resolutions,
• Regular maintenance. • Rational and efficient use of resources • Government programs.
• EWS to include telemetering in waterways • Coordination with PAGASA. • Full implementation and monitoring of
and EWS protocols for monitoring and • Awareness campaign on climate- compliance to land use plan;
preparedness. related risks. • Initiate resolutions to address climate
change from the barangay to the city
level

Public health • Efficient/effective surveillance and provision • More health workers for health info •
and/or enhancement of adequate, capable dissemination.
and well-equipped health services in • Easy access to health services when
barangays. needed.
• Early warning system (EWS), including access • Preparedness for emergencies.
to correct interpretation of forecasts. • Practice proper hygienic practices
• Regular clean-up drives, including fumigation • Rescue operations.
if warranted.
Environment • Tree planting in all vacant spaces, • 3 R’s; • Compliance to environment codes
and biodiversity • maintenance of existing parks/urban • Rational use of resources; (e.g., proper disposal of wastes).
gardening, vertical gardens; • Engage in programs like para sa Tao-
• Engage in urban farms, including love mother Earth, IEC and
hydrophonics • Awareness campaign on environment
• Green architecture protection;
• Shift to renewable energy (solar panels in • Stop use of plastics and other
rooftops, etc.); hazardous materials;
• Clean up drives, declogging, etc.
Infrastructures, • Updating of risks assessments, cognizant of • Regular/enhanced awareness and • Updating of green building codes;
critical facilities lifetimes of existing infrastructures. dissemination campaigns and • Regular monitoring and
and lifelines • Strategic planning, specifically for critical engaging residents in better implementation of compliance to green
lifelines under different scenarios to avoid building codes;

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late and/or non-delivery, especially during monitoring and surveillance during

times of emergency; extreme events;
• Review, maintenance of flood drainage • Activate BDRMMC;
systems.
• Additional better evacuation centers,
retaining walls, drainage systems, color-coded
EWS devices; etc.
• Provision of more rubber boats, ayuda food
packs,
• Relocation of some IFS, especially those
located near waterways
Service delivery • Efficient use of supply (e.g., electrical power); • Awareness campaign on green • Green building codes to minimize use
• Strategic plan for sufficient supply where and energy; of power (e.g., bigger windows for
when critically needed; • Use of solar panels increased ventilation, vertical gardens,
etc.)

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2.4.4 Impact Chain Diagram and Analysis

Hereunder are two simplified impact chain diagrams to facilitate the analysis of direct and indirect impacts
of projected climate change scenarios, including increase in temperature, changes in rainfall amounts,
changes in frequency and/or severity of tropical cyclones; in particular, typhoons and super typhoons)
which could translate to higher maximum winds and gustiness and possibly, greater associated rainfall, and
accelerated sea level rise). Figure 10 presents an impact chain for Quezon City.

CLIMATE BIOPHYSICAL SOCIOECONOMIC

HAZARD IMPACT
STIMULI IMPACT

Increase in temperature Extreme maximum Increases in heat stress, Health impacts such as
temperatures increasing heat index, increases in pulmonary
stress on infrastructures, such diseases, cardiovascular
as MRT tracks in extreme diseases such as heat strokes,
cases etc.
Impacts are increased need
for medical services

Changes in rainfall Floods /droughts Injuries/mortalities Diminished mobility that

amounts/patterns Damage to property, could lead to less work
infrastructure, critical productivity
facilities, lifelines, roads & Increased loss and damage
bridges, etc. Stress on QC budgetary
requirements

Increased intensity/frequency Increasing maximum winds Same as above Same as above

of tropical cyclone and more intense associated
occurrences rainfall

Sea level rise Salt water intrusion in Diminished quality of water Health impacts such as
groundwater supply water-based diseases (e.g.
gastroenteritis)
Higher floodwater depths Same as those of flooding Same as those of flooding
near waterways in QC events events

Figure 10. Simplified impact chain diagram for Quezon City

Another way of analyzing impacts (direct and indirect) is looking individually at each of the projected
changes/ increases for each of the climate impact drivers and consider potential impacts of these changes,
based on historical and/or present impacts. See Figure 11 below.

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Figure 11. Chain diagram for increase in temperature that could be applied to assess climate impact on Quezon City

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Part 3:
Flood Hazard and Risk
Assessment

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3. Flood Hazard and Risk Assessment

3.1. Rationale, Justification and Objectives

The methods, underlying data, assumptions, findings, outputs and interpretation of outputs for the climate
change and flood hazard and risk assessment have been presented and extensively discussed in the Hazard,
Vulnerability and Risk Maps for all 142 Barangays – Deliverable 8 Report dated September 30, 2022. The
reader is referred to that particular deliverable for more details. This chapter summarizes key outputs and
their relevance in the context of the CDRA requirements.

The hazard and risk assessment of the CDRA focuses on analyzing the impact of an RCP8.5 100-year rain
return flood scenario on the population and buildings in District 1 to District 6 of Quezon City. The flood
hazard parameter in this study is flood depth. Flood duration and/or flood speed are not considered. The
flood depth values were obtained from Quezon City Drainage Master Plan (QC-DMP) study and the Mines
and Geosciences Bureau (MGB) flood susceptibility map, which provided information on the highest flood
depths expected along a set of grid (or pixel) points covering the full geography of Quezon City. For brevity,
the RCP8.5 (2020-2039) 100-year rain return flood scenario will be named the “RCP 8.5 100-year flood” in
this report. The selection of the ‘100-year flood’ term used in this report was made because the patterns of
inundation and damages that can be expected are closer to TS Ondoy and the City Quezon City
stakeholders can relate to this event.

This study does not reproduce information found elsewhere such as estimates of casualties and economic
loss find in GMMA-RAP study of 2013. The flood hazard and risk analysis intends to, as much as possible,
find meaningful interpretations of the MGB flood susceptibility map and the QC-DMP’s RCP 8.5 100-year
flood scenario map for the time frame 2022-2032. It focuses more on assessing the impact of the projected
flood hazards in these study, particularly the RCP 8.5 100-year flood scenario. It establishes an in-depth and
high resolution (street level) assessment of the impacts of floods on population, buildings, critical point
facilities, and infrastructure. It also includes the assessment of the impact of secondary effects such as the
spread of waterborne diseases. The count of buildings and their associated area affected by flood is
provided for each barangay as well as other metrics that are essential for planning purposes. Results are
presented by district and by barangay to facilitate the reading and interpretation of the maps and their
association with the related charts. One of the main intent is to inform the update of the city’s various city
development plans, its physical framework and its land use plan in the early future (2020-2039). Another
target objective is to inform data-driven and science-based barangay level and community level planning
and preparedness efforts.

3.2. Approach to Flood Risk Study

Flood risk analysis involves the combination of 1) flood hazard information, which describes the likelihood
and intensity of a flood event; 2) exposure information, which describes the distribution of people and
elements ‘at-risk’ from a flood event; and 3) vulnerability information, which describes how the exposed
elements would be affected when subject to a given intensity of flooding. The impact is assessed by
overlay of the exposure data over the flood hazard using GIS technology. Flood depth of half a meter (0.5
m) was selected as the threshold that would pose significant hazards to people and support systems and
facilities.

The impact of the flood scenario is analyzed base on the updated the 2022 Geospatial Exposure Database
(GSED) of Quezon City (Deliverable 12 of this report) incorporating the implications of the RCP 8.5

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climate-change related rainfall projection. More details on the approach, methodology and underlying
data for modeling can be found in the Hazard, Vulnerability and Risk for 142 barangays report
(Deliverable 8). Some of the key considerations are reproduced here.

3.3. What does the flood scenario mean as a flood hazard?

Typically, the category starts at 0.2 meter (8 inches) where any increase of floodwater may start to affect
stability of a moving vehicle. A 0.5m flood depth can result in drowning esp. for small children and threaten
the stability of adults. It can also cause injuries (e.g., cuts, falling into open manholes, and body
contamination from microbial hazards). Moving water at this depth is enough to 'carry' or dislodge small to
medium sized vehicles from the road. Roads are likely impassable to light and medium sized vehicles,
resulting in disruption to movement.

When these flood heights exceed the thresholds of building openings (e.g., doors, windows, cracks), a
disruption of household activities, possible injuries (e.g., electrocution, contamination of water taps), and
damage to house furniture and appliances and other building contents typically happens. Some residents
will be forced to evacuate to higher grounds.

At 1.5 meters of standing water, one may expect the building utilities and services to be no longer
functional (water and sanitation, electrical) or possibly cut-off from supply.

When flood waters rise to 3 meters deep, space for human occupancy is lost within the ground floor level.
People in buildings with upper floors can move to these spaces but more damage can be expected to the
building contents and to the structure. The opportunity to body harm or getting a disease by infections
through skin contact (e.g., leptospirosis) or ingestion of contaminated water (e.g., gastro-enteritis, diarrhea)
is appreciable.

3.4. The Main Tributaries of Quezon City

Quezon City is drained by four (4) main waterways namely: San Juan River, Tullahan River, Marikina River,
and Meycauayan River as indicated in Figure 12.

• San Juan River stretches about 100 km has the largest coverage. It includes the east side of of
Quirino Highway at Barangays San Bartolome, Bagbag and Talipapa eastwards to Holy Spirit then
at south from Mayon Street in La Loma down to Camp Aguinaldo on the east side.

• Tullahan River stretches 12 kms and drains the Barangays of Commonwealth, Fairview, Lagro then
westward to Novaliches, Nagkaisang Nayon then southwards to part of Talipapa on the west side
of Quirino Highway. Tullahan River also is the outflow channel of La Mesa Reservoir. About 28 km
of creeks act as tributaries to this waterway (CLUP 2011-2025, CPDD).

• About 9 km of Marikina River serves as the city’s natural boundary into which 25 kilometers of
creeks and canals directly flow. It covers the area on the north side of Commonwealth Avenue in
Barangay Commonwealth, eastward to Payatas, Bagong Silangan then southwards following the
down slope of the ridge at Batasan Hills, Old Balara and Pansol towards Ugong Norte.

• The northernmost part of the City (Green Fields Subd in Barangay San Agustin and Kaligayahan and
Maligaya Park Subd in Pasong Putik) is part of the Meycauayan River basin. A small catchment area

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can be found at the southwest periphery of the city which flows down towards Pasig River (CLUP
2011-2025, CPDD).

Figure 12. Rivers and Creeks in Quezon City (Source: QC-City Planning and Development Department (CPDD), 2022)

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3.5. MGB Flood Susceptibility Mapping in Quezon City

3.5.1 Background and baseline data
Mines and Geo-Sciences Bureau (MGB) produced a 1:10,000 scale for flood susceptibility and rain-induced
landslide map for Quezon City in 2021. Table 13 presents the four susceptibility levels for flood considered
in the MGB map. The relevant flood considerations by district are presented below:

Table 13. Flood Susceptibility Levels

Susceptibility Levels Descriptions

Very High Flood Areas likely to experience flood heights in excess of 2.0 meters and/or
Susceptibility (VHF Depth) flood duration of more than 3 days; also prone to flashfloods

High Flood Susceptibility Areas likely to experience flood heights of 1.0 to 2.0 meters and/or flood
(HF) duration of more than 3 days.
These areas are immediately flooded during heavy rains of several hours.

Moderate Flood Areas likely to experience flood heights of 0.5 to 1.0 meter and/or flood
Susceptibility (MF) duration of 1 to 3 days.

Low Flood Susceptibility Areas likely to experience flood heights of <0.5 meter and/or flood
(LF) duration of less than 1 day. These areas include low hills and gentle
slopes. They also have sparse to moderate drainage density.
Source: Mines and Geosciences Bureau, 2021

3.5.2 Flood susceptibility results by district

Flood Susceptibility of Barangays in District 1
• Barangays Mariblo, Katipunan, Talayan, St.Peter, Damayan, Sienna, Sto.Domingo (Matalahib),
Paraiso and Maharlika and Masambong make up the top 10 of the 37 barangays whose land area
are identified with moderate to very high susceptibility to flooding in District 1. Most of these
barangays are traversed by creeks that drain to the San Juan River. Maharlika and St. Peter are
farther from creeksides but join the flooded parts of Sienna and Sto. Domingo (Matalahib).

• Sta. Cruz, Masambong, Bahay Toro, Del Monte and Damar round the barangays where half (50%)
of the land areas experiences flood depths of 0.5m and higher flood.

Table 14 provides a breakdown of the percentages of the barangays with highest percentage of flooded
area. Figure 13 presents a distribution of flood susceptibility assignment in District 1. The map should be
used conjointly with Table 14.

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Table 14. Flood Susceptibility in District 1 based on percentage of land area assigned to flood water depth
District 1 Barangay Land Area Submerged in Percent
depth depth depth flooded
Barangay 0.5m-1m 1m-2m >2m area >0.5m
Mariblo 23.37 17.84 58.51 99.72
Katipunan 25.34 33.80 36.47 95.61
Talayan 13.65 15.84 43.10 72.59
St. Peter 11.82 49.36 10.34 71.52
Damayan 34.10 13.44 22.61 70.15
Sienna 13.73 33.07 22.85 69.65
Sto. Domingo (Matalahib) 20.22 19.42 27.21 66.84
Paraiso 30.69 12.21 21.62 64.52
Maharlika 39.50 23.30 0.70 63.49
Masambong 11.50 13.50 35.18 60.18
Del Monte 11.77 23.87 20.14 55.78
Sta. Cruz 19.57 10.43 23.72 53.72
Damar 53.50 0.00 0.00 53.50
Nayong Kanluran 14.44 13.92 17.28 45.64
Balingasa 20.78 6.07 15.70 42.55
Paltok 29.30 5.81 5.30 40.40
San Antonio 10.72 11.42 15.54 37.67
Vasra 14.86 13.32 3.98 32.16
Ramon Magsaysay 14.81 12.75 2.81 30.37
Sta. Teresita 29.66 0.00 0.00 29.66
Bahay Toro 13.11 8.86 6.66 28.63
Bagong Pag-asa 8.80 12.30 7.03 28.13
Manresa 10.56 10.08 7.47 28.11
Alicia 11.12 9.86 6.20 27.18
San Isidro Labrador 24.92 0.00 0.00 24.92
Lourdes 13.01 4.95 0.00 17.95
West Triangle 10.58 5.66 1.31 17.55
Salvacion 16.93 0.00 0.00 16.93
Pag-ibig sa Nayon 15.57 0.00 0.00 15.57
Sto. Cristo 4.75 2.80 3.55 11.10
Phil-Am 8.58 1.71 0.36 10.65
Paang Bundok 7.91 0.00 0.00 7.91
San Jose 7.05 0.00 0.00 7.05
N. S. Amoranto (Gintong Silahis) 4.29 0.00 0.00 4.29
Project 6 1.89 1.71 0.00 3.60
Veterans Village 3.35 0.18 0.00 3.53
Bungad 1.13 0.00 0.00 1.13
Source of data: CPDD, 2022, MGB, 2021

Flood Susceptibility of Barangays in District 2

• Barangays of District 2 have less than 22% of their barangay land areas in the range of moderate to
very high flood susceptibility.

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• Batasan Hills and Bagong Silangan lead the five barangays on susceptibility. They lie near the
Marikina River while Barangays Commonwealth and Holy Spirit area traversed by the Novaliches
River
Table 15 provides a breakdown of the percentages.. Figure 154 presents a distribution of flood
susceptibility assignment in District 2. The map should be used conjointly with Table 15.

Table 15. Flood Susceptibility in District 2 based on percentage of land area assigned to flood water depth categories.
District 2 Barangay Land Area Submerged in Percent
depth 0.5m- depth 1m- depth flooded area
Barangay 1m 2m >2m >0.5m
Batasan Hills 9.27 5.03 7.33 21.63
Bagong Silangan 4.80 4.17 9.50 18.47
Commonwealth 6.73 4.85 5.17 16.75
Holy Spirit 6.93 4.02 0.12 11.07
Payatas 2.58 2.12 0.04 4.74
Source of data: CPDD, 2022, MGB, 2021

Flood Susceptibility of Barangays in District 3

• Three barangays of District 3 land area were found to have about fifty percent of more of the
barangay areas to be in the range of moderate to very high flood susceptibility. These include
Barangays Libis, West Kamias and Bagumbayan.
• Barangays Libis, Blue Ridge, Bagumbayan and Ugong Norte lie to the east side of the Marikina
River. Barangay West Kamias, Quirino2-A, Quirino 2-B and Quirino 2-C are traversed by the
Diliman Creek.
Table 16 provides a breakdown of the percentages. Figure 15 presents a distribution of flood susceptibility
assignment in District 2.

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Table 16. Flood Susceptibility in District 3 based on percentage of land area assigned to flood water depth
categories.

District 3 Barangay Land Area Submerged in Percent

Libis 28.62 36.97 32.24 97.83
West Kamias 0.00 68.16 8.05 76.21
Bagumbayan 21.93 24.94 16.08 62.95
Quirino 2-A 0.00 15.36 20.92 36.29
East Kamias 0.00 24.41 10.32 34.74
Quirino 2-B 0.00 16.15 16.44 32.59
Quirino 2-C 0.00 30.81 0.00 30.81
Bagumbuhay 0.00 26.42 0.00 26.42
Blue Ridge B 8.07 10.77 6.13 24.97
Claro (Quirino 3-B) 0.00 20.20 4.13 24.34
Quirino 3-A 0.00 14.70 4.81 19.51
Silangan 0.00 10.47 6.68 17.15
Mangga 0.00 16.64 0.00 16.64
Tagumpay 0.00 12.69 0.00 12.69
E. Rodriguez 0.00 6.49 3.02 9.51
Ugong Norte 5.58 1.90 1.33 8.81
Matandang Balara 3.05 1.41 2.37 6.83
Loyola Heights 0.93 5.52 0.00 6.45
Socorro 2.42 0.00 0.00 2.42
Amihan 0.00 1.61 0.00 1.61
Milagrosa 0.00 1.48 0.00 1.48
Pansol 0.65 0.00 0.00 0.66
Source of data: CPDD, 2022, MGB, 2021
Flood Susceptibility of Barangays in District 4
• District 4 is traversed by San Juan River stretching across Roxas, Tatalon, Kalusugan, Damayang
Lagi and Dona Imelda. Santol located on the downstream stretch is inside the highly susceptible
areas. Barangays Horseshoe and Valencia and Bagong Lipunan ng Crame are traversed by the
Valencia Creek. Pinyahan (East Triangle), San Vicente and Old Capitol Site are found to be traversed
by upstream creeks.
• Interior flooding of UP Village may be more related to storm water drainage system performance
rather than overbank spills of smaller natural waterways.

Barangays Doña Imelda, Tatalon, Santol, San Vicente and Damayang Lagi top the highly flood susceptible
areas, having more than 50% of their land areas in high to very high flood susceptibility.

Table 17 provides a breakdown of these percentages. Figure 16 presents a distribution of flood

susceptibility assignment in District 4.

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Table 17. Flood Susceptibility in District 4 based on percentage of land area assigned to flood water depth categories.
District 4 Percent of Barangay Land Area Submerged
depth depth 1m- depth flooded area
Barangay 0.5m-1m 2m >2m >0.5m
Doña Imelda 4.91 17.08 68.10 90.08
Tatalon 5.34 12.00 72.11 89.45
Santol 20.59 47.42 16.86 84.87
San Vicente 17.82 43.08 19.30 80.20
Damayang Lagi 28.05 14.01 36.71 78.77
Old Capitol Site 20.12 23.10 0.00 43.22
Roxas 6.94 7.26 27.36 41.55
U. P. Village 30.76 3.28 0.00 34.03
Kalusugan 13.94 0.00 16.65 30.59
Doña Josefa 13.60 8.76 1.65 24.01
Sto. Niño 17.49 6.48 0.00 23.98
Valencia 20.01 0.00 2.86 22.87
Pinyahan 11.74 8.26 2.08 22.07
Bagong Lipunan ng Crame 10.40 9.09 0.00 19.49
Teachers Village West 17.93 0.00 0.00 17.93
Mariana 13.40 0.00 0.18 13.58
Teachers Village East 13.27 0.00 0.00 13.27
Don Manuel 11.42 0.00 0.00 11.42
U. P. Campus 3.52 3.65 0.98 8.15
Horseshoe 8.04 0.00 0.00 8.04
San Isidro 7.03 0.00 0.00 7.03
Paligsahan 3.64 2.29 0.64 6.56
Malaya 0.00 6.41 0.00 6.41
Doña Aurora 5.34 0.25 0.00 5.59
South Triangle 4.71 0.00 0.27 4.98
Central 4.41 0.00 0.00 4.41
Botocan 0.00 4.12 0.00 4.12
Kristong Hari 0.40 0.00 1.85 2.25
Kaunlaran 1.45 0.00 0.00 1.45
Laging Handa 0.14 0.00 0.00 0.14
Source of data: CPDD, 2022, MGB, 2021
Flood Susceptibility of Barangays in District 5
• Fourteen barangays of District 5 land area were found to be identified with moderate to very high
flood susceptibility. Barangays Capri, Sta. Lucia, Sta. Monica, and Novaliches Proper have more
than 50% of the areas susceptible to more than 0.5m depth of flood. These barangays are traversed
by the Novaliches River continuing to Tullahan River outside of Quezon City.

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Table 18 provides a breakdown of the percentages. Figure 17 presents a distribution of flood susceptibility
assignment in District 5.

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Table 18. Flood Susceptibility in District 5 based on percentage of land area assigned to flood water depth categories.

District 5 Barangay Land Area Submerged in Percent

depth 0.5m- depth 1m- depth flooded area
Barangay 1m 2m >2m >0.5m
Capri 13.92 14.34 57.45 85.71
Sta. Lucia 14.57 13.19 30.20 57.97
Novaliches Proper 10.41 13.32 30.50 54.24
Gulod 10.73 10.52 23.74 44.99
Sta. Monica 8.72 8.49 23.46 40.67
San Agustin 8.58 11.31 7.96 27.86
Nagkaisang Nayon 9.10 7.11 10.40 26.62
San Bartolome 8.63 4.71 10.16 23.49
Bagbag 8.14 8.96 5.49 22.58
Fairview 7.13 5.61 2.38 15.12
North Fairview 4.33 3.05 5.73 13.11
Pasong Putik Proper 6.09 1.09 0.75 7.93
Kaligayahan 5.14 1.86 0.85 7.85
Greater Lagro 0.30 0.00 0.00 0.30
Source of data: CPDD, 2022, MGB, 2021

Flood Susceptibility of Barangays in District 6

• Eleven Barangays of District 6 were found to be in the range of moderate to very high flood
susceptibility. Barangay Sangandaan has more than 50% of its area under high flood depths.

Table 19 provides a breakdown of the percentages. Figure 18 presents a distribution of flood susceptibility
assignment in District 6.

Table 19. Flood Susceptibility in District 6 based on percentage of land area assigned to flood water depth categories.
District 6 Barangay Land Area Submerged in Percent
depth 0.5m- depth 1m- depth flooded area
Barangay 1m 2m >2m >0.5m
Sangandaan 30.23 23.25 5.39 58.87
Talipapa 20.76 17.38 5.27 43.41
Apolonio Samson 23.48 5.54 13.77 42.79
Unang Sigaw 33.50 0.00 2.10 35.60
Culiat 12.51 13.41 7.00 32.92
Baesa 15.90 8.52 1.09 25.52
Pasong Tamo 12.47 6.25 0.26 18.98
Sauyo 7.96 6.56 3.87 18.39
Balong-bato 12.74 0.00 0.00 12.74
Tandang Sora 5.65 3.28 1.39 10.33
New Era 0.22 0.00 0.00 0.22
Source of data: CPDD, 2022, MGB, 2021

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Figure 13. Flood Susceptibility of District 1 of Quezon City Figure 14. Flood Susceptibility of District 2 of Quezon City
(Source: MGB Flood Susceptibility Report, 2021) (Source: MGB Flood Susceptibility Report, 2021)
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Figure 15. Flood Susceptibility of District 3 of Quezon City Figure 16. Flood Susceptibility of District 4 of Quezon City
(Source: MGB Flood Susceptibility Report, 2021) (Source: MGB Flood Susceptibility Report, 2021)

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Figure 17. Flood Susceptibility of District 5 of Quezon City Figure 18. Flood Susceptibility of District 6 of Quezon City
(Source: MGB Flood Susceptibility Report, 2021) (Source: MGB Flood Susceptibility Report, 2021)

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3.6. QC-Drainage Master Plan (QC-DMP) Flood Hazard Simulation

3.6.1 Background
Flood inundation simulation results for Quezon City for flow depth maps for the 5-year, 25-year, 50-year,
and 100-year rain return scenarios were made available for the QC-DMP study. These scenarios were
simulated for the early-future, mid-future, and late-future periods, and with moderate (RCP 4.5) and high
(RCP 8.5) emission scenarios. The climate-change adjusted rainfall values used for flood model simulation
in Quezon City were calculated based on the data provided in the Philippine Climate Extremes Report
2020 published by PAGASA and the Manila Observatory and the Ateneo de Manila University (DOST-
PAGASA, Manila Observatory and the Ateneo de Manila University, 2021). The flood simulation results
provided information on the flood behavior over 36 hours, with rain falling over the initial 24 hours. A
maximum 1-day rainfall total was taken to produce extreme flood flow values and attain flood peak
depths.

3.6.2 The Climate Change Adjusted 100-Year Rain Return Flood baseline scenario
The adjusted 100-year rainfall return flood may be the worst flood scenario. Table 20 provides an
estimate of the maximum rainfall totals for the National Capital Region (Source; QC- Drainage Master
Plan). For the climate-adjusted rainfall, the percent change between the baseline rainfall value for a 100-
year event (e.g., 436.6 mm) and the different projected percentage increases under scenarios for the early
future, mid future and late future (i.e., under RCP 4.5 and RCP 8.5) can be multiplied to obtain the Climate
adjusted rainfalls.

Table 20. Maximum 1-Day Totals for NCR under various Emission Scenarios (Source: QC-Drainage Master Plan,
2021)
Moderate Emission (RCP 4.5) High Emission (RCP 8.5)
Early Mid Late Early Mid Late
Baseline (2020- (2046 – (2080 – (2020- (2046 – (2080 –
2039) 2065) 2099) 2039) 2065) 2099)
% Increase 5.50% 10.90% 3.30% 14.30% 9.90% 6.80%
5-yr 229.9 242.6 255 237.5 262.8 252.7 245.6
25-yr 343.2 362 380.6 354.5 392.2 377.1 366.5
50-yr 390.1 411.5 432.6 402.9 445.8 428.7 416.6
100-yr 436.6 460.6 484.2 451 499 479.8 466.3

The 100-year rain return flood scenario map shown in Figure 19 it is simulated using a one-day rainfall of
an early future scenario (2020-2039) under RCP 8.5 that the baseline one-day total rainfall is 436.6 mm,
and when multiplied by 14.3% gives 499 mm. This rainfall is then distributed over a 24-hour period having
a peak value at some hour in a day. In comparison STS-Ondoy generated 455mm of rainfall in a day
(Source: Science Garden, PAGASA). The flood depth in Figure 19 are segregated into four colors with each
representing a flood depth category - 0.2m to 0.5m, 0.5m to 1.5m, 1.5m to 3m, and 3m and above. The
map indicates the highest flood depths that may be expected at each location.

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Figure 19. RCP 8.5(2020-2039) 100-Year Rain Flood Scenario in Quezon City (Source: QC-DMP, Preliminary Report,
2022)

3.6.3 Flood susceptibility results by district

RCP 8.5 rain flood scenario in District 1
• Thirty-seven barangays in District 1 can be severely flooded with depths more than half a meter
under the climate adjusted rainfall for a 100-year flood scenario.
• Eight barangays with more than 50 percent of barangay bounded area affected include Katipunan
(97 %), Talayan (91%), Masambong (88%), Sto. Domingo -Matalahib (81%), St.Peter (65%), Maribo
(64%), Sienna(62%) and Maharlika (61%).

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Table 21 provides a breakdown of the percentages of land area. Figure 20 presents a distribution of
barangays according to flood depth categories.

Table 21. RCP 8.5 100 Year Flood Scenario Percentage of Land Area flooded at different flood levels in District 1.
District 1 Barangay Land Area Flooded in Percent
depth 0.5m- Depth Flooded
Barangay
1.5m > 1.5m area >0.5m
Katipunan 8 89 97
Talayan 7 84 91
Masambong 20 68 88
Sto. Domingo (Matalahib) 14 66 81
FloodSt. Peter 16 48 65
Mariblo 9 55 64
Sienna 10 52 62
Maharlika 18 44 61
Alicia 10 30 39
Damayan 5 31 37
San Antonio 6 29 36
Bahay Toro 15 20 36
Nayong Kanluran 18 18 35
Del Monte 7 26 33
Paltok 21 11 32
Balingasa 20 11 30
Sta. Cruz 9 21 30
Paraiso 6 22 28
N. S. Amoranto (Gintong Silahis) 23 5 28
West Triangle 19 6 25
Manresa 8 17 25
Vasra 15 8 23
Sto. Cristo 12 10 22
Bagong Pag-asa 14 6 20
Ramon Magsaysay 9 9 18
Phil-Am 12 3 16
Project 6 14 2 16
Damar 14 0 14
Bungad 11 4 14
San Isidro Labrador 14 0 14
Sta. Teresita 12 0 12
Veterans Village 7 4 12
Lourdes 7 2 10
Salvacion 8 0 8
San Jose 5 0 5
Paang Bundok 3 0 3
Pag-ibig sa Nayon 2 0 2

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RCP 8.5 rain flood scenario in District 2

• Five barangays that are affected by deep floods and ranges between 8-25 percent of their areas.
Bagong Silangan leads with about 25 percent of the land area susceptible to flooding with more
than 0.5m.

Table 22 provides a breakdown of the percentages. Figure 21 presents a distribution of barangays

according to flood depth levels for District 2.

Table 22. RCP 8.5 100 Year Flood Scenario Percentage of Land Area flooded at different flood levels in District 2.
District 2 Barangay Land Area Flooded in Percent
depth 0.5m- Depth Flooded
Barangay
1.5m > 1.5m area >0.5m
Bagong Silangan 7.23 18.25 25.48
Batasan Hills 9.78 13.01 22.79
Payatas 3.98 7.02 11
Holy Spirit 6.84 1.57 8.41
Commonwealth 4.23 4.08 8.31

RCP 8.5 rain flood scenario in District 3

• Thirty-five barangays in District 3 can be severely flooded with depths more than half a meter
under the climate adjusted rainfall for a 100-year flood scenario.
• Four barangays with more than 50 percent of barangay bounded area include Bagumbayan (66
%), Claro-Quirino 3B (62%), Libis (62%), and West-Kamias (61%).

Table 23 and Error! Reference source not found.22 present a distribution of barangays according to flood
depth levels for District 3.

Table 23. RCP 8.5 100 Year Flood Scenario Percentage of Land Area flooded at different flood levels in District 3.
District 3 Barangay Land Area Submerged in Percent
depth 0.5m- Depth Flooded
Barangay
1.5m > 1.5m area >0.5m
Bagumbayan 33.29 33.13 66.42
Claro (Quirino 3-B) 19.14 42.81 61.95
Libis 24.06 37.67 61.73
West Kamias 24.03 36.66 60.69
Silangan 17.6 27.69 45.29
Masagana 39.39 2.32 41.71
Tagumpay 29.86 10.06 39.92
Quirino 2-A 11.4 28.35 39.75
East Kamias 25.21 14.32 39.53
Quirino 2-C 22.26 16.52 38.78
Mangga 27.12 11.59 38.71
Villa Maria Clara 34.48 0.06 34.54
Quirino 3-A 15.94 17 32.94
Bagumbuhay 18.65 14.15 32.8
Quirino 2-B 11.13 20.51 31.64
Amihan 19.45 7.56 27.01

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District 3 Barangay Land Area Submerged in Percent

depth 0.5m- Depth Flooded
Barangay
1.5m > 1.5m area >0.5m
Loyola Heights 15.32 5.96 21.28
E. Rodriguez 11.79 8.27 20.06
Milagrosa 16.1 3.23 19.33
Ugong Norte 12.14 2.86 15
Blue Ridge B 5.68 8.83 14.51
Matandang Balara 8.93 3.26 12.19
Bayanihan 9.75 0.47 10.22
White Plains 4.07 5.15 9.22
San Roque 7.76 0.23 7.99
Pansol 5.9 2.05 7.95
Duyan-duyan 7.25 0.04 7.29
Marilag 7.17 0.04 7.21
Socorro 5.51 1.2 6.71
Camp Aguinaldo 6.24 0.15 6.39
St. Ignatius 3.56 0.46 4.02
Dioquino Zobel 3.98 0 3.98
Blue Ridge A 2.64 0.27 2.91
Escopa 2 1.42 0 1.42
Escopa 3 0.11 0 0.11

RCP 8.5 rain flood scenario in District 4

• Thirty-eight barangays in District 4 can be severely flooded with depths more than half a meter
under the climate adjusted rainfall for a 100-year flood scenario.
• Three barangays with more than 50 percent of barangay bounded area include Tatalon (79%),
Doña Imelda (77%), and Damayang Lagi (55%).

Table 24 and Figure 23 present a distribution of barangays according to flood depth levels for District 4.

Table 24. RCP 8.5 100 Year Flood Scenario Percentage of Land Area flooded at different flood levels in District 4.
District 4 Barangay Land Area Submerged in Percent
depth 0.5m- Depth Flooded
Barangay
1.5m > 1.5m area >0.5m
Tatalon 10.42 68.73 79.15
Doña Imelda 17.14 59.76 76.9
Damayang Lagi 11.55 43.54 55.09
San Vicente 40.61 4.48 45.09
Santol 13.59 23.74 37.33
Kalusugan 16.06 19.79 35.85
Roxas 6.5 28.8 35.3
Old Capitol Site 25.75 7.37 33.12
Kristong Hari 8.31 24.55 32.86
Kamuning 11.18 20.8 31.98
Botocan 28.54 1.06 29.6

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District 4 Barangay Land Area Submerged in Percent

depth 0.5m- Depth Flooded
Barangay
1.5m > 1.5m area >0.5m
Valencia 8.24 16.2 24.44
Central 20.55 3.55 24.1
Horseshoe 14.59 6.6 21.19
Obrero 5.22 14.17 19.39
Don Manuel 18.66 0 18.66
South Triangle 13.74 3.76 17.5
Immaculate Concepcion 9.4 7.16 16.56
Pinagkaisahan 6.25 8.86 15.11
Bagong Lipunan ng Crame 8.58 5.77 14.35
Pinyahan 9.2 3.58 12.78
U. P. Campus 9.25 2.78 12.03
Mariana 8.08 1.81 9.89
Paligsahan 6.42 1.45 7.87
Laging Handa 7.31 0.11 7.42
San Martin de Porres 5.09 2.31 7.4
Teachers Village West 6.31 0.13 6.44
Kaunlaran 3.63 2.58 6.21
Doña Josefa 6.01 0.14 6.15
San Isidro 5.33 0 5.33
Sikatuna Village 5.28 0 5.28
Sacred Heart 3.61 0.13 3.74
U. P. Village 3.17 0 3.17
Doña Aurora 2.89 0 2.89
Krus na Ligas 2.56 0 2.56
Teachers Village East 2.52 0 2.52
Sto. Niño 1.56 0 1.56
Malaya 0.61 0 0.61

RCP 8.5 rain flood scenario in District 5

• Fourteen barangays in District 5 can be severely flooded with depths more than half a meter
under the climate adjusted rainfall for a 100-year flood scenario.
• Barangay Capri in District 5 has 97 percent of its area flooded. Other barangays are flooded
varying from 6- 38 percent of their areas.

Table 25 and Error! Reference source not found.24 presents a distribution of barangays according to
flood depth levels.

Table 25. RCP 8.5 100 Year Flood Scenario Percentage of Land Area Flooded at Different Flood Levels in District 5.
District 5 Barangay Land Area Submerged in Percent
depth 0.5m- Depth Flooded
Barangay
1.5m > 1.5m area >0.5m
Capri 24.17 72.52 96.69

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District 5 Barangay Land Area Submerged in Percent

depth 0.5m- Depth Flooded
Barangay
1.5m > 1.5m area >0.5m
Gulod 9.97 27.65 37.62
Novaliches Proper 22.25 13 35.25
Sta. Lucia 8.25 26.42 34.67
Sta. Monica 9.31 23.18 32.49
Nagkaisang Nayon 9.44 14.24 23.68
San Bartolome 7.92 13.56 21.48
Bagbag 7.27 10.29 17.56
North Fairview 7.37 9.69 17.06
Fairview 6.6 8.56 15.16
San Agustin 8.6 0.8 9.4
Greater Lagro 6.05 1.78 7.83
Pasong Putik Proper 6.12 1.05 7.17
Kaligayahan 5.52 0.51 6.03

RCP 8.5 rain flood scenario in District 6

• District 6 has eleven areas that are affected by deep floods but range between 10-41 percent of
the barangay areas.

Table 26 and Figure 25 present a distribution of barangays according to flood depth levels.

Table 26. RCP 8.5 100 Year Flood Scenario Percentage of Land Area Flooded at Different Flood Levels in District 6.
District 6 Barangay Land Area Submerged in Percent
depth 0.5m- Depth Flooded
Barangay
1.5m > 1.5m area >0.5m
Apolonio Samson 14.49 26.14 40.63
Unang Sigaw 29.95 1.64 31.59
Culiat 13.32 16.67 29.99
Baesa 20.63 5.8 26.43
Sangandaan 9.95 13.41 23.36
Balong-bato 20.49 2.61 23.1
Talipapa 14.18 5.1 19.28
Pasong Tamo 10.68 8.49 19.17
Tandang Sora 10.51 4.06 14.57
Sauyo 8.22 3.81 12.03
New Era 9.94 0.13 10.07

(Source: QC-DMP, Preliminary Report, 2022)

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Figure 20. RCP 8.5(2020-2039) 100-Year Rain Flood Scenario in District 1 Figure 21. RCP 8.5(2020-2039) 100-Year Rain Flood Scenario in District 2
(Source: QC-DMP, Preliminary Report, 2022) (Source: QC-DMP, Preliminary Report, 2022)

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Figure 22. RCP 8.5(2020-2039) 100-Year Rain Flood Scenario in District 3 Figure 23. RCP 8.5(2020-2039) 100-Year Rain Flood Scenario for District 4
(Source: QC-DMP, Preliminary Report, 2022) (Source: QC-DMP, Preliminary Report, 2022)

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Figure 24. RCP 8.5(2020-2039) 100-Year Rain Flood Scenario for District 5 Figure 25. RCP 8.5(2020-2039) 100-Year Rain Flood Scenario for District 6
(Source: QC-DMP, Preliminary Report, 2022) (Source: QC-DMP, Preliminary Report, 2022)

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3.7. Flood Risk Assessment (RCP 8.5 100-Year Flood)

To demonstrate the parameters of risk to Quezon City, this section used the 100-year flood map to overlay
exposure and establish the risk to the following exposed assets:
• Population and settlements
• Buildings of various occupancies
• Public facilities used for health and emergency
• Facilities used for safety and security
• Urban Land Use
• Utilities and infrastructures

The 100-year flood model simulation runs using the RCP 8.5-rain projections from the QC-DMP study
provide the most relevant outputs for planning and for preparedness.

3.7.1. Flood Displaced Population

This section discusses the flood displaced population under an RCP8.5 100-year rain flood scenario. The
distribution of the flood-affected population in Quezon City is discussed. The building footprints in (light
colored shapes shown in Figures 26-31 in a barangay boundary) indicate one-and two story structures that
should expect more than half a meter (0.5 m) of flood which will be potentially damaging to the building
structure or its contents. Most one-story buildings are largely for residential use and are less than four (4)
meters high from floor to ceiling.
The flood-displaced population was obtained by taking the proportion of the residential, one- and two-story
building footprint area that are in locations where flood depths exceed half a meter. This is multiplied by an
estimate of the population per unit area of the building footprint to obtain the potential number of flood
displaced population. The flood depth ranges used were 0.5m and below, 0.5 m- 1.5 m, and 1.5 m and
above were derived from the RCP8.5 rain flood scenario.
Informal settlers that reside in Quezon City are high-risk areas. These settlements, due to their informality,
are often not built to code or with flood resistant materials which increases their vulnerability to flood
events.
In 2021, there are 200, 591 informal settler families (ISFs) listed in 2021 by the Quezon City Government.
A great number of these are in flood prone areas. District 1 lists 21,518 ISFs and about 95 % (20,491) are
situated where flood depths can be higher than 0.5 meter. All of 61,439 ISFs can experience high flood
depths. District 3 has 21,780 ISFs, and 21,039 or about 97% can experience depths higher than 0.5m.
District 4 has 42,722 ISFs and 98% (41,955) can experience depths higher than 0.5m. District 5 has 11,060
ISFs listed, and all are in locations prone to floods. District 6 has 42,072 ISFs and all these families are in
flood prone areas. Long term solutions tied with affordable housing, relocation and resettlement can reduce
the ISFs in dangerous locations. Pre- evacuation sites, resources and response are needed when a 100-year
rain flood scenario like this develops
The sections below provide the findings per district.

Flood Displaced Population in District 1

A summary of the flood-displaced population in District 1 at three flood levels (moderate flood with depth
of 0.5 to 1.5 m and high flood with depth of >1.5 m) is shown Table 27. Barangays Bahay Toro, San
Antonio, Masambong are estimated to bring the larger numbers of flood displaced population affected
under 0.5 m and above depths. Figure 26 presents a distribution of displaced population for District 1.

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Table 27. Flood displaced population in District 1 in an RCP100-year 8.5 Rain Flood Scenario
Barangay (District 1) Number of people
Displaced
Bahay Toro 16,849
San Antonio 6,568
Masambong 6,201
Sto. Domingo (Matalahib) 5,042
Paltok 3,821
Del Monte 2,740
Bagong Pag-asa 2,602
Talayan 2,529
Damayan 1,942
Vasra 1,888
Alicia 1,822
Mariblo 1,638
Manresa 1,491
Project 6 1,405
Maharlika 1,404
Veterans Village 1,395
St. Peter 1,390
Balingasa 1,356
Katipunan 1,217
San Isidro Labrador 1,129
Sto. Cristo 1,108
Sta. Cruz 957
Sienna 919
N. S. Amoranto (Gintong Silahis) 807
Ramon Magsaysay 752
Bungad 577
West Triangle 559
Paraiso 554
Sta. Teresita 497
Salvacion 480
Phil-Am 428
Lourdes 407
Nayong Kanluran 406
Pag-ibig sa Nayon 283
Damar 204
San Jose 130
Paang Bundok 12
Total 73,511

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Figure 26. Displaced Population from Single Family, One- and Two-Story Structures and Informal Settler Family
Structures in a 100-Year Rain Flood Scenario for District 1 (Source: QC-DMP, Preliminary Report, 2021)

Flood Displaced Population in District 2

A summary of the flood-displaced population in District 2 is shown in Table 28. The flood depth ranges
used 0.5 m- 1.5 m, and 1.5 m and above were derived from the RCP8.5 rain flood scenario. Barangay
Batasan Hills is estimated to bring the larger numbers of flood displaced population affected under 0.5 m
and above depths. Figure 27 presents a distribution of displaced population for District 2.

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Table 28. Flood displaced population in District 2 in an RCP100-year 8.5 Rain Flood Scenario
Barangay (District 2) Number of people
Displaced
Batasan Hills 19,064
Commonwealth 11,387
Bagong Silangan 10,286
Holy Spirit 7,221
Payatas 3,004
Total 50,962

Figure 27. Displaced Population from Single Family, One- and Two-Story Structures and Informal Settler Family
Structures in a 100-Year Rain Flood Scenario for District 2 (Source: QC-DMP, Preliminary Report, 2021)

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Flood Displaced Population in District 3

A summary of the flood-displaced population in District 3. Barangays Bagumbayan and Matandang Balara
are estimated to bring the larger numbers of flood displaced population affected under 0.5 m and above
depths as shown in Table 29. Figure 28 presents a distribution of displaced population for District 3.

Table 29. Flood displaced population in District 3 in an RCP100-year 8.5 Rain Flood Scenario
Barangay Number of people
Displaced
Bagumbayan 4,746
Matandang Balara 4,387
Loyola Heights 3,295
E. Rodriguez 2,481
West Kamias 2,072
Pansol 2,070
East Kamias 1,625
Bagumbuhay 1,620
Claro (Quirino 3-B) 1,596
Masagana 1,589
Quirino 2-A 1,481
Silangan 1,476
Ugong Norte 1,248
San Roque 1,087
Amihan 955
Villa Maria Clara 830
Marilag 813
Milagrosa 784
Quirino 2-C 678
Quirino 2-B 672
White Plains 656
Socorro 440
Quirino 3-A 354
Libis 254
Tagumpay 227
Duyan-duyan 227
Mangga 205
Blue Ridge B 166
St. Ignatius 136
Bayanihan 127
Dioquino Zobel 124
Blue Ridge A 110
Escopa 3 17
Escopa 4 0
Escopa 1 0
Camp Aguinaldo 0
Escopa 2 0
Total 38547

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Figure 28. Displaced Population from Single Family, One- and Two-Story Structures and Informal Settler Family
Structures in a 100-Year Rain Flood Scenario for District 3 (Source: QC-DMP, Preliminary Report, 2022)

Flood Displaced Population in District 4

Table 30 gives a summary of the flood-displaced population in District 4. The flood depth ranges used were
0.5 m- 1.5 m, and 1.5 m and above were derived from the RCP8.5 rain flood scenario. Barangay Tatalon is
estimated to bring the larger numbers of flood displaced population affected under 0.5 m and above
depths. Figure 29 presents a distribution of displaced population for District 4.

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Table 30. Flood displaced population in District 4 in an RCP100-year 8.5 Rain Flood Scenario
Barangay Number of people
Displaced
Tatalon 20,921
Damayang Lagi 5,018
Roxas 3,350
Kamuning 3,194
Doña Imelda 2,608
Central 1,834
Bagong Lipunan ng Crame 1,533
Obrero 1,277
Santol 1,184
South Triangle 878
Mariana 840
Pinagkaisahan 757
Immaculate Concepcion 708
San Isidro 707
U. P. Campus 696
Botocan 688
Kristong Hari 524
Pinyahan 485
Don Manuel 477
Valencia 404
Laging Handa 384
Horseshoe 380
San Vicente 376
Teachers Village West 311
Sto. Niño 279
San Martin de Porres 254
Paligsahan 228
Sacred Heart 203
U. P. Village 189
Sikatuna Village 164
Kaunlaran 142
Teachers Village East 124
Doña Aurora 121
Kalusugan 43
Malaya 32
Old Capitol Site 24
Doña Josefa 20
Krus na Ligas 0
Total 51,354

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Figure 29. Displaced Population from Single Family, One- and Two-Story Structures and Informal Settler Family
Structures in a 100-Year Rain Flood Scenario for District 4 (Source: QC-DMP, Preliminary Report, 2022)

Flood Displaced Population in District 5

A summary of the flood-displaced population in District 5 is shown in Table 31. The flood depth ranges
used were 0.5 m- 1.5 m, and 1.5 m and above were derived from the RCP8.5 rain flood scenario. Barangays
Capri, Bagbag and Sta. Monica are estimated to bring the larger numbers of flood displaced population
affected under 0.5 m and above depths. Figure 30 presents a distribution of displaced population for
District 5.

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Table 31. Flood displaced population in District 5 in an RCP100-year 8.5 Rain Flood Scenario
Barangay Number of people
Displaced
Capri 13,405
Bagbag 13,364
Sta. Monica 10,561
San Bartolome 8,169
Nagkaisang Nayon 7,817
Gulod 7,369
Sta. Lucia 4,551
Novaliches Proper 4,302
North Fairview 3,598
Fairview 3,575
Kaligayahan 3,126
Greater Lagro 1,905
San Agustin 1,869
Pasong Putik Proper 1,147
Total 84,760

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Figure 30. Displaced Population from Single Family, One- and Two-Story Structures and Informal Settler Family
Structures in a 100-Year Rain Flood Scenario for District 5 (Source: QC-DMP, Preliminary Report, 2022)

Flood Displaced Population in District 6

A summary of the flood-displaced population in District 6 is shown in Table 32. The flood depth ranges
used were 0.5 m- 1.5 m, and 1.5 m and above were derived from the RCP8.5 rain flood scenario. Barangays
Culiat, Baesa, and Pasong Tamo are estimated to bring the larger numbers of flood displaced population
affected under 0.5 m and above depths. Figure 31 presents a distribution of displaced population for
District 6.

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Table 32. Flood displaced population in District 6 in an RCP100-year 8.5 Rain Flood Scenario
Barangay Number of people
Displaced
Culiat 15,688
Baesa 12,604
Pasong Tamo 12,575
Tandang Sora 11,419
Apolonio Samson 7,724
Sauyo 5,902
Sangandaan 5,546
Talipapa 4,765
New Era 2,916
Balong-bato 1,152
Unang Sigaw 310
Total 80,600

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Figure 31. Displaced Population from Single Family, One- and Two-Story Structures and Informal Settler Family
Structures in a 100-Year Rain Flood Scenario for District 6 (Source: QC-DMP, Preliminary Report, 2022)

3.7.2. Flood Affected Buildings

A focus on vacant or open spaces that are less prone to flooding from river overflows can be used for the
deployment of emergency response services. This is taken as potentially damaging to the building structure
or its contents. Most one-story buildings are largely for residential use and are less than four (4) meters high
from floor to ceiling.

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Table 33 to Table 38 show the distribution of flood affected buildings located in Quezon City in an RCP 8.5
100-year rain flood scenario. They present a count of structures that should expect more than half a meter
(0.5 m) of flood which maybe potentially damaging to the building structure or its contents.

The key metrics are provided below by district.

Flood Affected Buildings in District 1

In terms of count of building footprint covering all occupancy types (1-2 stories) in a flood depth of half a
meter deep or more, Barangays Toro, San Antonio, Sto. Domingo (Matalahib) forms the top 3 barangays.

In terms of area of building footprint covering single family residential type (1-2 stories) and including those
in Informal Settler Families that were estimated to be flooded in half a meter deep or more, Barangays Toro,
Talayan, San Antonio form the top 3 barangays.

Table 323 shows a ranking of the one- and two-story building footprint areas expected to be flooded under
0.5m and higher in District 1.

Table 33. Count of building footprint for all occupancy types in a flood category in District 1 for flood depth 0.5m and
higher
Barangay L2: 0. 5m- 1.5m L3: 1. 5m- 3 m L4: 3m and Total
above (depth>0.5m)
Bahay Toro 1,443 1,020 3,956 6,419
San Antonio 296 728 1,234 2,258
Sto. Domingo 243 781 1,203 2,227
(Matalahib)
Talayan 97 576 727 1,400
Masambong 260 309 814 1,383
Bagong Pag-asa 272 108 918 1,298
Manresa 347 191 641 1,179
Del Monte 115 404 647 1,166
Paltok 181 91 744 1,016
St. Peter 169 192 504 865
Sienna 134 247 459 840
Damayan 53 273 383 709
Maharlika 177 88 380 645
Balingasa 161 34 422 617
Vasra 155 32 401 588
Mariblo 54 209 304 567
Sto. Cristo 86 129 290 505
Sta. Cruz 63 139 270 472
Katipunan 42 186 232 460
Alicia 86 110 257 453
Veterans Village 122 2 309 433
Project 6 61 3 352 416
West Triangle 81 5 220 306
Bungad 66 6 218 290
Ramon Magsaysay 61 39 156 256

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Barangay L2: 0. 5m- 1.5m L3: 1. 5m- 3 m L4: 3m and Total

above (depth>0.5m)
Nayong Kanluran 62 36 142 240
Paraiso 36 59 122 217
San Isidro Labrador 210 210
Lourdes 27 159 186
Phil-Am 35 149 184
N. S. Amoranto (Gintong 19 164 183
Silahis)
Sta. Teresita 144 144
Salvacion 74 74
Damar 69 69
Pag-ibig sa Nayon 44 44
San Jose 27 27
Paang Bundok 6 6
Total 5,004 5,997 17,351 28,352

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Building Floor Area of One-Two Story Structures in

Flood depth > 0.5m (Single Family and ISF)
Bahay Toro 553,498
Sto. Domingo (Matalahib) 229,206
Talayan 156,678
Masambong 114,479
San Antonio 112,476
Paltok 111,329
Bagong Pag-asa 109,096
Maharlika 99,775
Sienna 96,680
St. Peter 80,006
Del Monte 66,500
Sta. Cruz 63,573
Manresa 55,386
West Triangle 54,021
Phil-Am 49,273
Project 6 44,216
Barangays in District

Lourdes 39,637
Veterans Village 39,304
Vasra 38,666
1

Mariblo 37,587 Total

Damayan 36,727
San Isidro Labrador 36,158
Sto. Cristo 32,046
Bungad 27,883
Damar 26,180
Balingasa 25,418
Alicia 24,881
Katipunan 22,666
Nayong Kanluran 21,048
N. S. Amoranto (Gintong Silahis) 19,742
Sta. Teresita 17,018
Paraiso 15,469
Ramon Magsaysay 11,645
Salvacion 11,323
Pag-ibig sa Nayon 7,416
San Jose 2,419
Paang Bundok 350
0 200,000 400,000 600,000
Floor Area ( sq.m)

Figure 32. Area of One -Story, Single Family and Informal Settler Family Building Footprint in depths greater than half
meter in District 1

Flood Affected Buildings in District 2

A count of building footprint covering all occupancy types (1-2 stories) that were estimated to be flooded in
half a meter or more, Barangays Bagong Silangan, Commonwealth and Batasan Hills form the top 3
barangays.

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Table 334 shows a ranking of the one- and two-story building footprint including those in Informal Settler
Families areas expected to be flooded under 0.5m and higher in District 2.

Table 34. Count of building footprint for all occupancy types in a flood category in District 2 for flood depth 0.5m and
higher

L4: 3m and Total

Barangay L2: 0. 5m- 1.5m L3: 1. 5m- 3 m
above (depth > 0.5m)
Bagong Silangan 1,197 1,810 4,287 7,294
Commonwealth 920 852 2,878 4,650
Payatas 473 812 2,336 3,621
Batasan Hills 1,018 500 3,339 4,857
Holy Spirit 488 8 1,868 2,364
Grand Total 4,096 3,982 14,708 22,786

A sum of building footprint area covering single family residential type (1-2 stories) estimated to be flooded
in half a meter or more, Barangays Batasan Hills, Bagong Silangan, and Holy Spirit form the top 3 barangays.

Building Floor Area of One & Two Story Structures

in Flood depth > 0.5m (Single Family and ISF)

Batasan Hills 431,562

Bagong Silangan 342,884

Barangays in District

Holy Spirit 206,174

2

Total

Commonwealth 204,478

Payatas 194,886

0 100,000 200,000 300,000 400,000 500,000

Floor Area (sq.m)

Figure 33. Area of One -Story, Single Family and Informal Settler Family Building Footprint in depths greater than half
meter in District 2

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Flood Affected Buildings in District 3

A count of total of building footprints covering all occupancy types (1 & 2 stories) that were estimated to be
flooded in half a meter or more, Barangays Matandang Balara, Loyola Heights and Bagumbayan form the
top 3 barangays.

Table 345 shows a ranking of the one- and two-story building footprint areas and including those in
Informal Settler Family areas expected to be flooded under 0.5m and higher in District 3.

Table 35. Count of building footprint for all occupancy types in a flood category in District 3 for flood depth 0.5m and
higher
Barangay L2: 0. 5m- 1.5m L3: 1. 5m- 3 m L4: 3m and above Total (depth>0.5m)
Matandang Balara 443 62 1,726 2,231
Bagumbayan 347 170 1,056 1,573
Loyola Heights 352 29 973 1,354
Claro (Quirino 3-B) 259 32 416 707
Quirino 2-A 171 95 369 635
West Kamias 195 51 362 608
E. Rodriguez 114 27 460 601
Bagumbuhay 192 399 591
East Kamias 110 49 407 566
Quirino 2-B 158 27 277 462
Masagana 36 388 424
Amihan 110 3 278 391
Ugong Norte 12 15 339 366
Silangan 117 23 219 359
Pansol 15 6 325 346
Quirino 2-C 79 9 181 269
Tagumpay 79 155 234
San Roque 9 218 227
Milagrosa 35 189 224
Marilag 1 207 208
White Plains 58 123 181
Libis 27 13 105 145
Villa Maria Clara 144 144
Quirino 3-A 42 11 87 140
Socorro 3 119 122
Mangga 41 3 54 98
Camp Aguinaldo 74 74
Duyan-duyan 53 53
Blue Ridge B 15 38 53
St. Ignatius 6 38 44
Blue Ridge A 2 34 36
Bayanihan 2 24 26
Dioquino Zobel 9 9
Escopa 3 2 2
Total 3,027 628 9,848 13,503

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In terms of area of building footprint covering single-family residential type (1 & 2 stories) and estimated to
be flooded in half a meter or more, Barangays Ugong Norte, Matandang Balara, and Loyola Heights form
the top 3 barangays.

Building Floor Area of One & Two Story Structures

in Flood depth > 0.5m (Single Family and ISF)
Ugong Norte 244,826
Loyola Heights 226,709
Matandang Balara 182,401
Bagumbayan 150,617
Pansol 91,781
E. Rodriguez 63,401
East Kamias 63,052
White Plains 54,119
West Kamias 52,538
Masagana 49,225
Quirino 2-A 43,705
Bagumbuhay 42,303
Silangan 41,760
Claro (Quirino 3-B) 38,089
Barangays in District

Quirino 2-B 30,767

Marilag 28,303
Amihan 24,595
3

San Roque 22,436 Total

Milagrosa 21,178
Quirino 2-C 20,544
Villa Maria Clara 18,996
Tagumpay 15,516
Blue Ridge B 12,024
St. Ignatius 11,879
Quirino 3-A 9,449
Blue Ridge A 8,433
Libis 8,425
Socorro 8,316
Mangga 3,639
Duyan-duyan 3,566
Dioquino Zobel 2,151
Bayanihan 2,080
Escopa 3 64
0 50,000 100,000150,000200,000250,000300,000
Floor Area (sq.m)

Figure 34. Area of One -Story, Single Family and Informal Settler Family Building Footprint in depths greater than half
meter in District 3
Flood Affected Buildings in District 4
Using a count of building footprint covering all occupancy types (1 & 2 stories) estimated to be flooded in
half a meter or more, Barangays Tatalon, U.P. Campus and Doña Imelda form the top 3 barangays.

In terms of count of building footprint covering single-family residential type (1 & 2 stories) and including
those in Informal Settler Family areas that were estimated to be flooded in half a meter or more, Barangays

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Tatalon, Damayang Lagi, and Roxas form the top 3 barangays. Table 356 shows a ranking of the one- and
two-story building footprint areas expected to be flooded under 0.5m and higher in District 4.

Table 36. Count of building footprint for all occupancy types in a flood category in District 4 for flood depth 0.5m and
higher
L4: 3m Total
L2: 0. 5m- L3: 1. 5m-
Barangay and (depth>0.5m
1.5m 3m
above and above)
Tatalon 957 1,362 2,611 4,930
U. P. Campus 482 20 1,134 1,636
Doña Imelda 225 314 607 1,146
Damayang Lagi 251 178 544 973
Roxas 98 322 521 941
Kamuning 119 200 515 834
Pinyahan 92 53 330 475
Santol 153 12 277 442
Bagong Lipunan ng Crame 76 16 260 352
Kristong Hari 59 80 179 318
Mariana 42 6 256 304
Valencia 85 37 174 296
Obrero 35 89 170 294
Central 16 1 264 281
San Vicente 24 235 259
Pinagkaisahan 28 42 145 215
South Triangle 33 4 174 211
Immaculate Concepcion 64 3 144 211
Kalusugan 34 24 117 175
Old Capitol Site 49 15 90 154
Laging Handa 1 126 127
Horseshoe 25 7 79 111
Don Manuel 106 106
Kaunlaran 19 1 60 80
Botocan 3 76 79
San Martin de Porres 20 52 72
Paligsahan 9 58 67
San Isidro 65 65
Teachers Village West 3 53 56
Sacred Heart 1 52 53
Sikatuna Village 39 39
Sto. Niño 37 37
U. P. Village 32 32
Doña Aurora 29 29
Teachers Village East 26 26

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L4: 3m Total
L2: 0. 5m- L3: 1. 5m-
Barangay and (depth>0.5m
1.5m 3m
above and above)
Krus na Ligas 22 22
Doña Josefa 14 14
Malaya 2 2
Total 3,003 2,786 9,677 15,466

Building Floor Area of One&Two Story Structures in

Flood depth > 0.5m (Single Family and ISF)
192,029
Damayang Lagi 183,483
102,804
Doña Imelda 94,538
90,384
Roxas 68,550
55,738
Bagong Lipunan ng Crame 42,311
41,581
Central 40,957
40,679
South Triangle 30,921
27,303
Pinyahan 24,803
24,343
Barangays in District

Pinagkaisahan 22,621
22,293
San Vicente 22,198
20,890
4

Kalusugan 20,501
20,251 Total
Immaculate Concepcion 18,093
10,232
Botocan 9,607
9,436
Sacred Heart 8,598
6,772
Kaunlaran 6,601
6,221
Sikatuna Village 5,872
5,676
Teachers Village East 5,359
3,590
Sto. Niño 3,488
2,209
Krus na Ligas 1,820
1,354
Malaya 646
0 50,000 100,000 150,000 200,000 250,000
Floor Area (sq.m)

Figure 35. Area of One -Story, Single Family and Informal Settler Family Building Footprint in depths greater than half
meter in District 4

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Flood Affected Buildings in District 5

Using a count of building footprint covering all occupancy types (1 & 2 stories) that were estimated to be
flooded in half a meter or more, Barangays Sta. Monica, Gulod and San Bartolome form the top 3
barangays.
In terms of count of building footprint covering single-family residential type (1-2 stories) and including
those in Informal Settler Family areas that were estimated to be flooded in half a meter or more, Barangays
Sta. Monica, San Bartolome and Nagkaisang Nayon form the top 3 barangays. Table 367 shows a ranking of
the one- and two-story building footprint areas expected to be flooded under 0.5m and higher in District 5.

Table 37. Count of building footprint for all occupancy types in a flood category in District 5 for flood depth 0.5m and
higher
L4: 3m
L2: 0. 5m- L3: 1. 5m- Total
Barangay and
1.5m 3m (depth>0.5m)
above
Sta. Monica 891 1,231 2,825 4,947
Gulod 887 1,092 2,519 4,498
San Bartolome 521 632 1,788 2,941
Sta. Lucia 581 662 1,559 2,802
Nagkaisang Nayon 487 301 1,602 2,390
Fairview 386 544 1,455 2,385
Bagbag 429 363 1,380 2,172
North Fairview 298 337 1,121 1,756
Capri 356 348 1,003 1,707
Novaliches Proper 196 92 671 959
Pasong Putik Proper 142 20 728 890
Kaligayahan 82 555 637
Greater Lagro 27 1 383 411
San Agustin 83 312 395
Grand Total 5,381 5,702 18,003 29,086

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Building Floor Area of One-Two Story Structures in Flood

depth > 0.5m (Single Family and ISF)
Sta. Monica 261,090
San Bartolome 190,252
Gulod 187,062
Sta. Lucia 136,768
Fairview 125,657
Barangays in District

Nagkaisang Nayon 122,554

Bagbag 120,143
North Fairview 98,718
5

Novaliches Proper 67,207 Total

Greater Lagro 62,652
Kaligayahan 53,919
Pasong Putik Proper 50,750
Capri 49,810
San Agustin 29,215
Reservoir 11,831

0 50,000 100,000 150,000 200,000 250,000 300,000

Floor Area (sq.m)

Figure 36. Area of One -Story, Single Family and Informal Settler Family Building Footprint in depths greater than half
meter in District 5

Flood Affected Buildings in District 6

Using a count of building footprint covering all occupancy types (1-2 stories) estimated to be flooded in half
a meter or more, Barangays Baesa, Pasong Tamo and Culiat form the top 3 barangays.
In terms of count of building footprint covering single-family residential type (1-2 stories) and including
those in ISF locations estimated to be flooded in half a meter or more, Barangays Culiat, Pasong Tamo and
Tandang Sora form the top 3 barangays.

Table 378 shows a ranking of the one- and two-story building footprint areas expected to be flooded under
0.5m and higher in District 6.

Table 38. Count of building footprint for all occupancy types in a flood category in District 6for flood depth 0.5m and
higher
Total
Barangay L2: 0. 5m- 1.5m L3: 1. 5m- 3 m L4: 3m and above
(depth>0.5 m)
Pasong Tamo 1,425 449 4,025 5,899
Baesa 941 603 4,192 5,736
Culiat 1,262 358 3,156 4,776
Tandang Sora 533 40 2,533 3,106
Apolonio Samson 258 1,069 1,668 2,995
Sauyo 578 85 1,846 2,509

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Total
Barangay L2: 0. 5m- 1.5m L3: 1. 5m- 3 m L4: 3m and above
(depth>0.5 m)
Sangandaan 233 204 937 1,374
Talipapa 206 35 1,088 1,329
Balong-bato 79 289 368
Unang Sigaw 28 253 281
New Era 18 224 242
Grand Total 5,561 2,843 20,211 28,615

Building Floor Area of One-Two Story Structures in Flood

depth > 0.5m (Single Family and ISF)

Pasong Tamo 424,833

Culiat 424,735

Tandang Sora 343,092

Baesa 279,195
Barangays in District

Apolonio Samson 241,443

Sauyo 173,439
6

Total
Sangandaan 155,799

Talipapa 136,491

Balong-bato 35,458

New Era 16,218

Unang Sigaw 14,743

0 100,000 200,000 300,000 400,000

Floor Area (sq.m)

Figure 37. Area of One -Story, Single Family and Informal Settler Family Building Footprint in depths greater than half
meter in District 6

3.7.3. Flood Exposure of Health and Emergency Related Facilities

The distribution of police stations, fire stations, and public facilities within the city are considered to be
essential functions that must be preserved and functioning during a disaster. In the event of a 100-year
flood, these facilities can provide essential services to community members who had to evacuate before the
storm. They can serve as temporary shelters during times of emergency. By identifying the facilities most at
risk of flooding, actions can be taken to decrease their vulnerability.

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Figure 38 to Figure 43 show the distribution hospitals, health centers, identified evacuation centers within
Quezon City. The maps also indicate vacant or open spaces that are less prone to flooding from river
overflows and can be used for deployment of emergency response services.

Additional key metrics are provided below.

For greater benefits, the outputs from these analyses are provided in the form of Annex A in electronic
format and can be accessed through the following link:

LINK TO ANNEX A:
https://drive.google.com/drive/folders/10A0Khji3yoZzpqI9NxvpblWp3vJG1MPS?usp=share_link

Flood Evacuation Centers

There are 272 sites identified as evacuation sites during flood events in QC. Eighty of them are in areas
where flood depths can be higher than 0.5m. These include 32 evacuation sites in District 1; 6 in District 2;
13 in District 3; 17 in District 4; 5 in District 5; and 7 in District 6. Refer to Table A1 for a complete list of
flood evacuation centers under various flood levels per barangay in link to Annex A provided above.

Health Centers
There are health center structures, two-stories high that are in areas where flood exceeds 0.5m (Level 2 and
up). Twelve health centers are at risk from high flood depths. There are four each in District 1 and in
District 3, two in District 5 and one each in District 4 and 6. Refer to Table A2 for a complete list of
hospitals under various flood levels per barangay in link to Annex A provided above.

Hospitals
Thirteen hospitals were found in locations where flood depths can be higher than 0.5m in the RCP 8.5 100-
year flood scenario. Two in District 1 located in Barangays Sienna and West Triangle, one in Barangay
Milagrosa, District 3, Seven in District 4 in barangays Central, Damayang Lagi, Doña Imelda, Doña Josefa,
Immaculate Concepcion and Kalusugan. Refer to Table A3 for a complete list of hospitals under various
flood levels per barangay in link to Annex A provided above.

Multi-purpose halls
There are 101 multipurpose hall locations in Quezon City. About 11 of them are situated where flood
waters vary from 0.2m to less than 0.5m. About 16 multi-purpose halls comprising of one- and two-story
buildings were situated in areas where flood depths can exceed 0.5m. These buildings and their contents
are more susceptible to damage. Disruption of services and barangay operations are more likely to extend
in longer periods. This comprises seven multipurpose hall locations in District 1, three each in Districts 4
and 5 and one each in Districts 2 and 3 and 6. Refer to Table A4 for a complete list of multi-purpose halls
under various flood levels per barangay in link to Annex A provided above.

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Figure 38. Public Facility (Emergency management related) locations in an RCP 8.5 100- year rain flood scenario in
District 1. Facilities in deep flood locations are shown with their names and flood level indicator (ex. L2). Open/Vacant
spaces are shown relative to the evacuation center locations

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Figure 39. Public Facility (Emergency management related) locations in an RCP 8.5 100- year rain flood scenario in
District 2. Facilities in deep flood locations are shown with their names and flood level indicator (ex. L2). Open/Vacant
spaces are shown relative to the evacuation center locations

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Figure 40. Public Facility (Emergency management related) locations in an RCP 8.5 100- year rain flood scenario in
District 3. Facilities in deep flood locations are shown with their names and flood level indicator (ex. L2). Open/Vacant
spaces are shown relative to the evacuation center locations

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Figure 41. Public Facility (Emergency management related) locations in an RCP 8.5 100- year rain flood scenario in
District 4. Facilities in deep flood locations are shown with their names and flood level indicator (ex. L2). Open/Vacant
spaces are shown relative to the evacuation center locations

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Figure 42. Public Facility (Emergency management related) locations in an RCP 8.5 100- year rain flood scenario in
District 5. Facilities in deep flood locations are shown with their names and flood level indicator (ex. L2). Open/Vacant
spaces are shown relative to the evacuation center locations

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Figure 43. Public Facility (Emergency management related) locations in an RCP 8.5 100- year rain flood scenario in
District 6. Facilities in deep flood locations are shown with their names and flood level indicator (ex. L2). Open/Vacant
spaces are shown relative to the evacuation center locations

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3.7.4. Flood Exposure of Facilities for Safety and Security

Figure 44 to Figure 49 show the distribution police stations, fire stations, barangay halls within Quezon City
that, during times of emergency, serve to assist in response, ensure security of affected sites.

The key planning metrics are provided below.

For greater benefits, the outputs from these analyses are provided in the form of Annex A in electronic
format and can be accessed through the following link:

LINK TO ANNEX A:
https://drive.google.com/drive/folders/10A0Khji3yoZzpqI9NxvpblWp3vJG1MPS?usp=share_link

Barangay Hall
Several one-story and two-story Barangay halls in Districts 1,3,4 and 5 that are surrounded by half a meter
or more deep flood waters (i.e., flood level 2-4). Access to these barangay halls, as well as the possibility of
damage to contents inside these buildings can be disruptive to barangay operations after the event. Refer
to Table A5 for a complete list of barangay halls under various flood levels per barangay in link to Annex A
provided above.

Fire station
There are 19 Fire sub-stations all over Quezon City. Three of these in District 1 are in areas that can
experience flooding higher than 0.5m. Refer to Table A6 for a complete list of fire stations under various
flood levels per barangay in link to Annex A provided above.

Police Station
Twenty -eight police locations in Quezon City comprising 11 police stations, 14 community precincts and 3
police assistance centers. About seven them were found to be located in areas where flood depths can be
higher than 0.5m. They include three community precincts in District 1, one in District 2, and 1 in District 3.
Two are police stations in District 1. Refer to Table A7 for a complete list of police stations under various
flood levels per barangay in link to Annex A provided above.

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Figure 44. Public Facility (Safety and Security related) locations in an RCP 8.5 100- year rain flood scenario in District 1.
Facilities in deep flood locations are shown with their names and flood level indicator (ex. L2). Source: QC-Drainage
Master Plan, Preliminary Report 2022, City Planning and Development Department, 2022)

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Figure 45. Public Facility (Safety and Security related) locations in an RCP 8.5 100- year rain flood scenario in District 2.
Facilities in deep flood locations are shown with their names and flood level indicator (ex. L2). Source: QC-Drainage
Master Plan, Preliminary Report 2022, City Planning and Development Department, 2022)

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Figure 46. Public Facility (Safety and Security related) locations in an RCP 8.5 100- year rain flood scenario in District 3.
Facilities in deep flood locations are shown with their names and flood level indicator (ex. L2). Source: QC-Drainage
Master Plan, Preliminary Report 2022, City Planning and Development Department, 2022)

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Figure 47. Public Facility (Safety and Security related) locations in an RCP 8.5 100- year rain flood scenario in District 4.
Facilities in deep flood locations are shown with their names and flood level indicator (ex. L2). Source: QC-Drainage
Master Plan, Preliminary Report 2022, City Planning and Development Department, 2022)

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Figure 48. Public Facility (Safety and Security related) locations in an RCP 8.5 100- year rain flood scenario in District 5.
Facilities in deep flood locations are shown with their names and flood level indicator (ex. L2). Source: QC-Drainage
Master Plan, Preliminary Report 2022, City Planning and Development Department, 2022)

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Figure 49. Public Facility (Safety and Security related) locations in an RCP 8.5 100- year rain flood scenario in District 6.
Facilities in deep flood locations are shown with their names and flood level indicator (ex. L2). Source: QC-Drainage
Master Plan, Preliminary Report 2022, City Planning and Development Department, 2022)

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3.7.5. Flood Affected Utilities and Infrastructures

Exposed utilities, infrastructure and other lifelines, such as segments of roads and bridges to higher risks
from rain-induced hazards point to increasing sensitivity to climate projections. Higher risks resulting from
the projected changes in rainfall under the worst-emission climate scenario will most likely increase the
vulnerability and complicate response and recovery after a major disaster.

Figure 50 to Figure 55 highlight the utilities and infrastructure facilities whose operations are likely to be
disrupted by the flood. Quantitative metrics are provided in related tables.

Roads
Table 39 gives the total length of flooded roads under of an RCP 8.5 100-year flood scenario for each
district. Barangays Toro, Sto Domingo, Masambong, Talayan and San Antonio of District 1 have more than
five kilometers of road flooded under 0.5 m and above. Batasan Hills, Bagong Silangan and Holy Spirit of
District 2 have road lengths that can be inundated with 0.5m and higher flood depths and can total 5 km.
Barangays Ugong Norte, Bagumbayan, Loyola Heights, Matandang Balara tops District 3.

Barangays Tatalon, Doña Imelda, Damayang Lagi, are the barangays in District 4 with more than 5 km of
roads that potentially can submerge under 0.5m and above flood depths. In District 5, San Bartolome, Sta,
Monica and Nagkaisang Nayon and Gulod have road lengths inundated with 0.5m and higher totalling more
than 8 km. District 6, Pasong Tamo, Tandang Sora, Culiat and Apolonio Samson have inundated road
segments that exceed 9 km. Possible disruptions to the population movements in these identified areas are
expected and can also put people’s lives in danger.

Table 39. Barangays with flooded road segments in Districts 1 to 6 (RCP 8.5 100-year rain flood scenario)
Flood Level Total
District
L2 L3 L4 flooded (m)
District 1
Bahay Toro 8,747 6,741 1,814 17,302
Sto. Domingo (Matalahib) 1,742 2023 8247 12,012
Masambong 1,837 2331 2490 6,658
San Antonio 1,069 1,490 3239 5,799
Talayan 758 805 4167 5,730
Sienna 694 986 3143 4,823
Paltok 3,319 854 302 4,475
St. Peter 1,240 1,278 1,830 4,348
Maharlika 1,028 2168 1082 4,278
Manresa 958 1780 1152 3,890
Balingasa 2,521 1049 272 3,842
Bagong Pag-asa 2,737 520 346 3,602
Del Monte 703 644 2007 3,354
West Triangle 2,323 801 3,124
Sta. Cruz 615 835 1341 2,791
Sto. Cristo 976 461 717 2,155
Project 6 1,992 151 2,143

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Flood Level Total

District
L2 L3 L4 flooded (m)
Vasra 1,259 826 10 2,096
Mariblo 260 372 1,398 2,030
N. S. Amoranto (Gintong
1500 421 1,921
Silahis)
Katipunan 254 290 1,185 1,729
Lourdes 1356 330 26 1712
Damayan 242 255 1,138 1,635
Sta. Teresita 1576 1576
Veterans Village 1046 506 1,552
Phil-Am 1055 314 1,370
San Isidro Labrador 1299 1299
Bungad 1189 87 1277
Alicia 303 475 190 968
Damar 907 907
Paraiso 284 213 344 840
Nayong Kanluran 623 157 781
Salvacion 724 724
Ramon Magsaysay 224 243 192 659
San Jose 623 623
Pag-ibig sa Nayon 293 293
Paang Bundok 202 202
District 2
Batasan Hills 12,667 9,337 957 22,961
Bagong Silangan 7,322 4,277 4,332 15,931
Holy Spirit 5,220 983 40 6,242
Payatas 1,985 1081 1036 4,102
Commonwealth 2,627 614 138 3,380
District 3
Bagumbayan 6,400 2796 571 9,766
Ugong Norte 8,454 488 8,942
Loyola Heights 5,198 1,960 22 7,180
Matandang Balara 4,266 761 93 5,120
Pansol 3,277 323 48 3,648
West Kamias 848 1274 236 2,357
East Kamias 1,552 714 58 2,324
Bagumbuhay 1,201 1070 2,271
Masagana 2,163 30 2,192
E. Rodriguez 1,570 445 27 2,041
Socorro 1,667 94 1,761
Milagrosa 1,369 376 1,744

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Flood Level Total

District
L2 L3 L4 flooded (m)
Claro (Quirino 3-B) 355 1203 139 1,696
Silangan 770 912 1682
Quirino 2-A 436 713 181 1,330
Quirino 2-B 411 863 47 1,322
Camp Aguinaldo 1196 1,196
Marilag 1098 1098
White Plains 583 446 1,029
San Roque 972 36 1008
Villa Maria Clara 976 976
Amihan 733 221 955
Libis 492 341 833
Quirino 2-C 388 291 679
Quirino 3-A 217 216 433
Tagumpay 300 123 423
Duyan-duyan 318 318
St. Ignatius 259 49 308
Blue Ridge B 111 151 39 300
Mangga 55 96 151
Blue Ridge A 114 11 125
Bayanihan 94 94
Dioquino Zobel 26 26
Escopa 3 2 2
District 4
Tatalon 1,561 4416 7749 13,726
Doña Imelda 1,051 3334 4046 8,431
Damayang Lagi 1,211 3581 861 5,653
Central 3,441 546 108 4,096
Mariana 3,392 489 112 3,992
Kamuning 1,471 889 1604 3,965
Kalusugan 2,390 736 643 3,769
Santol 1,055 1873 636 3,564
U. P. Campus 3,154 377 3,531
Pinyahan 2,483 419 15 2,916
South Triangle 2,267 538 20 2,825
Roxas 496 378 1871 2,746
Bagong Lipunan ng Crame 1,029 533 1,561
Don Manuel 1,459 1,459
Valencia 413 897 67 1377
Laging Handa 1267 83 1350

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Flood Level Total

District
L2 L3 L4 flooded (m)
Obrero 321 302 620 1243
Old Capitol Site 761 174 935
Paligsahan 663 152 49 863
Kristong Hari 258 434 153 844
Immaculate Concepcion 459 378 836
San Vicente 710 86 795
Horseshoe 419 320 32 771
Sikatuna Village 645 645
Doña Josefa 559 70 629
Kaunlaran 328 270 598
Pinagkaisahan 375 118 55 548
San Martin de Porres 337 192 529
Sacred Heart 488 488
San Isidro 397 397
Teachers Village West 356 11 366
U. P. Village 346 346
Botocan 180 180
Teachers Village East 141 141
Doña Aurora 97 97
Malaya 85 85
Sto. Niño 70 70
Krus na Ligas 21 21
District 5
San Bartolome 5,475 3,922 3866 13,263
Sta. Monica 3,550 3,766 3,936 11,252
Nagkaisang Nayon 4,445 3,099 1,314 8,857
Gulod 2,879 3,738 2,080 8,698
North Fairview 3,840 2,243 1,595 7,677
Greater Lagro 6,294 1144 99 7,537
Fairview 3,293 1,416 2,027 6,737
Bagbag 2,765 2,282 641 5,689
Sta. Lucia 1,517 2,511 1,026 5,053
Capri 1,619 1,627 1706 4,952
Novaliches Proper 3,000 1224 103 4,327
Kaligayahan 3,301 188 3,489
Pasong Putik Proper 2,680 91 2,770
San Agustin 1629 39 1,668
District 6
Pasong Tamo 9,167 4,533 616 14,317
Culiat 6,204 5,344 1416 12,964

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Flood Level Total

District
L2 L3 L4 flooded (m)
Tandang Sora 8,778 1,855 207 10,839
Apolonio Samson 3,150 1744 4228 9,123
Sauyo 4,915 1,408 245 6,568
Baesa 4,961 409 41 5,411
Talipapa 4,456 613 123 5,191
Sangandaan 1,575 1,614 705 3,893
New Era 1,189 0 1,189
Unang Sigaw 1,069 20 1,088
Balong-bato 854 854
Grand Total 255,871 129,066 89,702 474,639

Bridges
Bridges, both concrete and steel are also identified to be subjected to different flood depths. Forty bridges
were found to be in locations where water depths can be higher than 0.5m. The information only reveals
location and not actual immersion of structures as these bridges lie above canals and located above ground.
In water depths greater than 3m at bridge locations, there are five in District 1, one each in Districts 2 and
3, seven in District 4, two in District 5 and three in District 6, which may need past flood information (e.g.,
STS Ondoy) to reveal if deck of bridge can get immersed in flood water. Bridges, both concrete and steel
(under different conditions as poor, fair and good) are also identified to be subjected to different flood
depths. Refer to Table A8 for a complete list of bridges in various flood levels per barangay in link to Annex
A provided above.

Sewage Treatment Plant

There are 29 sewage treatment plant (STP) locations in Quezon City. Six of them are situated where flood
waters can be less than half a meter deep. Twenty-three of these STPs are situated in areas where flood
depths can exceed 0.5m. These may result to disruption of operations and result to sanitation. Eleven are in
District 1, six in District 6, three in District 3, two in District 4, and one in District 5.

Refer to Table A9 for a complete list of sewage treatment plants in various flood levels per barangay in link
to Annex A provided above.

Water Pumping Station

The twenty-two water pumping stations (PS) in Quezon City are generally safe from deep flood water. A
few of them were located where flood depths can be higher than 0.5 m. These are found in Barangay
Maharlika (D.Tuazon PS) and Barangay Pansol (Balara Water PS) and the UP Water (PS). Refer to Table A10
for a complete list of water pumping stations in various flood levels per barangay in link to Annex A
provided above.

Materials Recovery Facility

Fifty-five locations of materials recovery facilities (MRFs) can be found in Quezon City. About 31 of these
locations are relatively safe from floods. About 22 of these were found to be in areas where flood depth
can be more than half a meter. There were seven each identified in Districts 1 and 3, three each in Districts
4 and 6 and two in District 5. Refer to Table A11 for a complete list of material recovery facilities under
various flood levels per barangay in link to Annex A provided above.

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Schools
There are 115 school locations in Quezon City that can be flooded by more than 0.5m deep. District 1 has
28, District 2 has 6, District 3 has 12, District 4 has 22, District 5 has 30, and District 6 has 17 school
locations. Refer to Table A12 for a complete list of schools under various flood levels per barangay in link to
Annex A provided above.

Markets
There are 53 market locations in Quezon City. Most of these are one-story structures. Thirteen of these
market locations can be flooded by more than 0.5m deep. They are found in Districts 1, 3, 4, 5 and 6.
District 4 has five locations, District 6 has three, Districts 3 and 5 have two each and District 1 has one.
Refer to Table A13 for a complete list of markets under various flood levels per barangay in link to Annex A
provided above.

Daycare centers
There are 296-day care centers in QC. Eighty-nine of them are in areas where flood depths can be higher
than 0.5m. They include 22-day care centers in District 1, 6 in District 2, 19 in District 3, 13 in District 4, 22
in District 5, and 7 in District 6. Refer to Table A14 for a complete list of daycare centers under various
flood levels per barangay in link to Annex A provided above.

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Figure 50. Utilities and Infrastructure locations in an RCP 8.5 100- year rain flood scenario in District 1. Facilities in
deep flood locations are shown with their names and flood level indicator (ex. L2). Source: QC-Drainage Master Plan,
Preliminary Report 2022, City Planning and Development Department, 2022

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Figure 51. Utilities and Infrastructure locations in an RCP 8.5 100- year rain flood scenario in District 2. Facilities in
deep flood locations are shown with their names and flood level indicator (ex. L2). Source: QC-Drainage Master Plan,
Preliminary Report 2022, City Planning and Development Department, 2022

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Figure 52. Utilities and Infrastructure locations in an RCP 8.5 100- year rain flood scenario in District 3. Facilities in
deep flood locations are shown with their names and flood level indicator (ex. L2). Source: QC-Drainage Master Plan,
Preliminary Report 2022, City Planning and Development Department, 2022

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Figure 53. Utilities and Infrastructure locations in an RCP 8.5 100- year rain flood scenario in District 4. Facilities in
deep flood locations are shown with their names and flood level indicator (ex. L2). Source: QC-Drainage Master Plan,
Preliminary Report 2022, City Planning and Development Department, 2022

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Figure 54. Utilities and Infrastructure locations in an RCP 8.5 100- year rain flood scenario in District 5. Facilities in
deep flood locations are shown with their names and flood level indicator (ex. L2). Source: QC-Drainage Master Plan,
Preliminary Report 2022, City Planning and Development Department, 2022

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Figure 55. Utilities and Infrastructure locations in an RCP 8.5 100- year rain flood scenario in District 6. Facilities in
deep flood locations are shown with their names and flood level indicator (ex. L2). Source: QC-Drainage Master Plan,
Preliminary Report 2022, City Planning and Development Department, 2022

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3.7.6. Flood Affected Land Uses

The key flood metrics for land uses are provided below:

Residential Land Uses

Residential land uses that are closer to main rivers and creeks have higher susceptibility to flooding.
Districts 1 and 4 traversed by the San Francisco-San Juan River and the G. Araneta Ave. canal and storm
water tributaries (Culiat Creek, Pasong Tamo Creek, Dario Creek, Diliman Creek) are the locations which
give the higher share of flood area coverage, number of facilities and length of road network under deeper
floods. The floods in residential areas at the eastern side of Districts 2 and 3 are connected to the Marikina
River overflows.

In District 6, residential areas closer to creeks such as Pasong Tamo, Tandang Sora, Culiat are locations
where floods can expand. The Novaliches River which meanders and crosses Fairview, Sta Lucia, Gulod and
Sta. Monica, Nagkaisang Nayon and San Bartolome forms the food prone areas of District 5.

The bigger concentration of institutional use areas is found in District 4 and adjoining areas of District 1 in
Vasra, New Era and Bagong Pag-asa. These sites are traversed by upstream stretches of Culiat Creek.
Strongly affected by the flood are institutional areas nearer to Diliman Creek connecting to the San Juan
River. See Figure 56 for a flood overlay with institutional land use areas.

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Figure 56. Institutional areas in District 4 in an RCP 8.5 100- year rain flood scenario. Source: QC-Drainage Master Plan,
Preliminary Report 2022, City Planning and Development Department, 2022)

Commercial Land Uses

Commercial land uses follow a ribbon-like pattern along roads and create commercial nodes over the city.
When these roads are adjacent to rivers and creeks, they have the potential to be flooded first. Storm water
collector pipes and culverts also connect to these streams allowing for a possible backflow. See Figure 57
and Figure 58 for flood overlays with commercial land use areas in District 4 and District 1.

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Figure 57. Commercial use areas in District 4 in an RCP 8.5 100- year rain flood scenario. (Source: QC-Drainage Master
Plan, Preliminary Report 2022, City Planning and Development Department, 2022)

Most affected commercial use areas are those lining the creeks and rivers and along roads adjacent to these
waterways, esp. San Francisco River, Diliman Creek, and the G Araneta Ave. open channel and culvert
system.

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Figure 58. Commercial use areas in District 1 in an RCP 8.5 100- year rain flood scenario. (Source: QC-Drainage
Master Plan, Preliminary Report 2022, City Planning and Development Department, 2022)

Most affected commercial use areas are those lining the creeks and rivers and along roads adjacent to these
waterways such as the San Francisco River, Culiat Creek and the G Araneta Ave. open channel and culvert
system.

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Industrial land uses

Industrial areas are mostly located at the western side of the City in Districts 1,5 and 6. In District 5, these
areas that locate near the Novaliches river are prone to river overflows. In District 6, many of these
industrial locations are far from Dario Creek but remain flood prone, likely from ponding of water or from
poor drainage.

Figure 59 and Figure 60 show flood overlays with the urban industrial land uses in Quezon City.

Figure 59. Industrial use areas in District 5 in an RCP 8.5 100- year rain flood scenario. (Source: QC-Drainage Master
Plan, Preliminary Report 2022, City Planning and Development Department, 2022)

Affected areas are adjacent to the Novaliches River.

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Figure 60. Industrial use areas in District 6 in an RCP 8.5 100- year rain flood scenario. Source: QC-Drainage Master
Plan, Preliminary Report 2022, City Planning and Development Department, 2022)

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3.8. Post-flood Health Issues – Gastro-Intestinal Infection

Infection can be a result of ingestion of contaminated flood waters as shown in Error! Reference source not f
ound.. The full methodology for establishing the probabilities of gastrointestinal infection is explained in the
Hazard Vulnerability and Risk Assessment (HVRA) for 142 Barangays report (Deliverable 8) and will not be
reproduced here. The key findings are presented below in aggregate and for each district.

The estimated number of exposed populations at three flood levels (low flood with depth of 0.5 m,
moderate flood with depth of 0.5 to 1.5 m and high flood with depth of >1.5 m) are shown in Table 40.

District 1
In District 1, an estimate of 1,543 people can be infected by gastro-enteritis. Barangays Toro, Sto. Domingo
(Matalahib), Masambong and San Antonio lead 37 barangays.
District 2
In District 2, an estimate of 1,259 people can be infected by gastro-enteritis. Barangays Batasan Hills,
Bagong Silangan lead the five barangays of the district.
District 3
In District 3, an estimate of 720 people can be infected by gastro-enteritis. Barangays Bagumbayan and
Matandang Balara lead 37 barangays.
District 4
In District 4, an estimate of 1,514 people can be infected by gastro-enteritis. Barangays Tatalon and
Damayang-Lagi lead the 38 barangays.
District 5
In District 5, an estimate of 1,577 people can be affected by gastro-enteritis. Barangays Gulod, Capri,
Bagbag, Sta. Monica and Nagkaisang Nayon lead the 14 barangays of the district.
District 6
In DIstrict 6, an estimate of 1,321 people can be infected by gastro- enteritis. Barangays Culiat, Pasog
Tamo, Apolonio Samson leads the 11 barangays of the district.

Figure 61 to Figure 66 show maps of infection rates among Districts.

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Table 40. Ranking of barangays (a)-(f) showing the infection rate (per 1000 population) to Gastro-Enteritis in different
Barangays and Districts.

(a) District 1 (b) District 3

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(c) District 2

(d) District 5

(e) District 6 (f) District 4

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Figure 61. Infection risk to Gastro-Enteritis (infected/1000 persons) in District 1 in an RCP 8.5 100 -year Rain Flood
Scenario

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Figure 62. Infection risk to Gastro-Enteritis (infected/1000 persons) in District 2 in an RCP 8.5 100 -year Rain Flood
Scenario

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Figure 63. Infection risk to Gastro-Enteritis (infected/1000 persons) in District 3 in an RCP 8.5 100 -year Rain Flood
Scenario

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Figure 64. Infection risk to Gastro-Enteritis (infected/1000 persons) in District 4 in an RCP 8.5 100 -year Rain Flood
Scenario

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Figure 65. Infection risk to Gastro-Enteritis (infected/1000 persons) in District 5 in an RCP 8.5 100 -year Rain Flood
Scenario

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Figure 66. Infection risk to Gastro-Enteritis (infected/1000 persons) in District 6 in an RCP 8.5 100 -year Rain Flood
Scenario

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Part 4:
Earthquake Hazard and
Risk Assessment

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4. Earthquake Hazard and Risk Assessment

4.1. Content and Purpose

The Earthquake element of the CDRA focuses on analyzing the impact of a magnitude 7.2 earthquake
generated by the West Valley Fault (WVF) on the buildings and population of Quezon City. This chapter
provides the key outputs from the M7.2 earthquake scenario. It presents various exhibits in terms of charts
and maps that illustrate the outputs and can inform internal DRRM and core internal planning functions of
Quezon City Government (QCG). A full description of the methodology can be found in Deliverable 8:
Hazard, Vulnerability and Risk Assessment of 142 Barangays.

The WVF is an active fault that transects the eastern part of Metropolitan Manila including Quezon City.
The aerial view of the trace of the WVF is approximately shown in Figure 67. The maximum magnitude of
M7.2 is approximated from the length of the fault using an empirical formula. This is a scientifically
acceptable approach because there is a direct correlation between the length of a fault and the maximum
magnitude the fault can generate. But it must be kept in mind that the M7.2 represents the worst-case
event. It is more probably that the WVF would trigger an earthquake of a smaller magnitude than M7.2.
However, it is always advisable to plan for the worst-case scenario because experience has shown that for
planning purposes it is possible to scale down but it is very difficult to scale up.

In addition to ground rupture and ground shaking, earthquake can trigger indirect hazards including
landslides, liquefaction, fire following, and tsunamis (for offshore faults only – not the WVF). Earthquakes
are often followed by a number of additional tremors known as aftershocks. Most of the time, these
aftershocks are weaker relative to the main earthquake and decrease in frequency over time. Occurrence of
aftershocks can last for several months and are capable of causing additional impact on assets. They also
cause significant trauma to survivors and can complicate the recovery process.

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Figure 67. Trace of West Valley Fault in the Vicinity of Quezon City

4.2. General Approach

An earthquake hazard and risk assessment is conducted in two distinct steps:

• First the hazard distribution is calculated in terms of the severity of earthquake shaking at the
centroid of a grid point (in this case 175m by 175 m grid) that cover the full geography of the study
area (i.e., Quezon City). This assessment is referred to as hazard assessment. The output is generally
provided in terms of Modified Mercali Intensity (MMI) a widely used earthquake hazard quantity in
earthquake engineering and seismology.

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• Second, the hazard quantity at each grid point is convolved with the vulnerability of the exposed
asset to calculate risk. Risk is a measure of the potential social, physical, economic and
environmental damages and losses. The latter assessment is referred to as risk assessment.

In this study, the calculated risk values are building damage, injuries, fatalities and displaced populations.
These quantities are calculated using sophisticated algorithms that convolve hazard quantities with the so-
called fragility functions associated with each element at risk. The main hazard parameter is the ground
shaking severity in terms of Modified Mercalli Intensity Scale. The scale is shown in Table 41

Table 41. The modified Mercalli intensity (MMI) scale (Wood & Neumann, 1931)
Intensity Shaking Description/Damage
I Not felt Not felt except by a very few under especially favorable conditions
II Weak Felt only by a few persons at rest, especially on upper floors of buildings
III Felt quite noticeably by persons indoors, especially on upper floors of buildings. Many
Weak people do not recognize it as an earthquake. Standing motor cars may rock slightly.
Vibrations are similar to the passing of a truck. Duration estimated.
IV Felt indoors by many, outdoors by few during the day. At night, some awakened. Dishes,
Light windows, doors disturbed, walls make cracking sound. Sensation like heavy truck striking
building. Standing motors rocked noticeably
V Felt by nearly everyone; many awakened. Some dishes, windows broken, and unstable
Moderate
objects were overturned. Pendulum clocks may stop.
VI Felt by all, many frightened. Some heavy furniture moved, a few fallen plasters. Damage
Strong
slight.
VII Damage negligible in buildings of good design and construction; slight to moderate in
Very Strong well-built ordinary structures; considerable damage in poorly built or badly designed
structures; some chimneys were broken.
VIII Damage is slight in specially designed structures; considerable damage in ordinary
Severe substantial buildings with partial collapse. Damage great in poorly built structures. Fall of
chimneys, factory stacks, columns, monuments, walls. Heavy furniture overturned.
IX Damage considerable in specially designed structures; well-designed frame structures;
Violent well-designed frame structures thrown out of plumb. Damage is great in substantial
buildings, with partial collapse. Buildings shifted off foundations.
X Some well-built wooden structures were destroyed; most masonry and frame structures
Extreme
destroyed with foundations. Rails bent

PHIVOLCS has also developed its intensity scale specific to the Philippines referred to as the PHIVOLCS
Earthquake Intensity Scale (PEIS), which is very similar to the MMI scale but is a 10-level scale instead of
the 12-level scale for the MMI. The two-scale are related so one can calculate an equivalent PEIS value
from an MMI value and vice-versa.

The HVRA earthquake study adopts the same scientific approach as the landmark study “Enhancing Risk
Analysis Capacities for Flood, Tropical Cyclone Severe Wind and Earthquake for the Greater Metro Manila
Area’ Project (GMMA-RAP), which was completed for the National Capital Region in 2013 and where all
relevant outputs are made available on the Philippine Institute of Volcanology and Seismology (PHIVOLCS)
geohazard portal (https://gisweb.phivolcs.dost.gov.ph/gisweb/earthquake-volcano-related-hazard-gis-
information).

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Ground shaking intensity for the GMMA was generated for M7.2 (estimated maximum size by MMEIRS)
earthquake generated by the WFV. PHIVOLCS has generously shared with the project team the grid data
for the M7.2 earthquake scenario as shown in Figure 68.

Figure 68. Earthquake intensity (in MMI) for M7.2 scenario of the Greater Metro Manila from the GMMA-RAP study

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4.3. Quantifying Earthquake Hazard to Quezon City

4.3.1. Earthquake Shaking Severity

The approach taken by EMI to undertake the earthquake hazard assessment improves on the GMMA-RAP
study in two ways.

• It makes use of a 2022 building-footprint level exposure data (i.e., population demographics,
buildings, infrastructure and critical facilities) developed on the city and barangays’ geo-political
boundaries officially recognized by the Quezon City Government.

• It improves the resolution of the analysis from 1.1km by 1.1km for the GMMA-RAP study to 175m
by 175m, i.e., the earthquake intensity is calculated at the centroid of a grid of 175mx 175 m
instead of 1.1km x 1.1 km. This represents a resolution close to 40 times better than that of the
GMMA-RAP study. The resolution of the intensity values calculated at each grid is further
improved by re-sampling technique at the building-footprint level. This approach generates close
to 400,000 intensity points in the total geography of Quezon City.

The severity of earthquake shaking at any location in Quezon City from the potential impact of the
magnitude 7.2 WVF earthquake scenario, is dependent on two parameters: 1) the distance from the fault
rupture to the site under consideration; and 2) the characteristics of the soil condition at a particular site.

Considering these two parameters, the earthquake intensity at each grid is calculated from a series of
equations, generally referred to as ground motion predication models (GMPMs). A combination of GMPMs
were used to best match the outputs of the GMMA-RAP M7.2 scenario for Quezon City. First, the so-
called peak ground acceleration (pga) is calculated, then the pga quantities are transformed into MMI values
using an empirical relationship that is available in the literature.

A sophisticated algorithm developed by EMI is used to undertake the calculations on grid of 175m x 175 m.
The calculation of the distance is a simple formula. However, the development of the soil characteristics
requires a highly sophisticated analytical methodology by which the soil data provided in both the GMMA-
RAP study and the MMEIRS study were re-sampled to produce a specific soil parameters at each of the
175m x 175 m grids for the full geography of Quezon at the highest resolution possible. This enables a
finer representation of the hazard within the city and each barangay. The software program developed by
EMI is embedded into the MATLAB platform, which is a powerful engineering development platform. It
enables accurate calculations of the MMI intensities at each grid as well as the re-sampling of the intensity
values at the building footprint level.

4.3.2 Earthquake intensity in Modified Mercalli Intensity (MMI)

Figure 69 shows the generated earthquake intensity map (in terms of MMI) for the M7.2 on the WVF
scenario for the full geography of Quezon City. When compared to the map of figure 68 generated by the
GMMA-RAP study, the improvement in the resolution is clearly visible. With such resolution, barangay
level and community level planning can be done with high reliability. Figure 70 to Figure 75 shows
earthquake intensity distribution for the different districts of Quezon City. The maps are intended to
facilitate understanding and to better informed users.

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The city generally will experience earthquake intensity of 8 – 10 (MMI) in the case of a M 7.2 West Valley
Fault earthquake scenario. In general, the severity of the ground motion is within the same range as the
GMMA-RAP. The differences are in terms of the higher resolution.

At the level of MMI Intensity 8 to 10, there will be considerable damage even to specially designed
structures. For some areas, there will be slight damage in specially designed structures and considerable
damage in ordinary substantial buildings with partial collapse. Damage will be great in poorly built
structures. Factory stacks, columns, monuments, and walls will fall and heavy furniture overturned. In a
large part of Quezon City, well-designed concrete frame structures can be thrown out of plumb. Damage
will be great in substandard buildings that are not competently designed to withstand earthquake forces
and the weakest structures will experience partial or full collapse. Many smaller buildings will be shifted off
foundations. Damage to structures and buildings is strongly correlated with the ground motion intensity.
Also, some well-built wooden structures were destroyed; most masonry and frame structures were
destroyed with foundations and rails bent. Thus, the pattern of damage severity will strongly replicate the
pattern of the severity of ground shaking shown.

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Figure 69. Ground Shaking Severity in Quezon City for an M7.2 West Valley Fault Earthquake Scenario in Modified
Mercalli Intensity Scale. (Developed by EMI guided by GMMA-RAP)

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Figure 70. Ground shaking severity for a M7.2 West Valley Fault earthquake scenario for District 1

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Figure 71. Ground shaking severity for a M7.2 West Valley Fault earthquake scenario for District 2

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Figure 72. Ground shaking severity for a M7.2 West Valley Fault earthquake scenario for District 3

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Figure 73. Ground shaking severity for a M7.2 West Valley Fault earthquake scenario for District 4

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Figure 74. Ground shaking severity for a M7.2 West Valley Fault earthquake scenario for District 5

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Figure 75. Ground shaking severity (MMI) for a M7.2 West Valley Fault earthquake scenario for District 6

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4.3.3. Ground rupture along West Valley Fault

Ground rupture occurs when the movement caused along the fault by an earthquake breaks the Earth's
surface. These ruptures can occur vertically or horizontally and on either side of the fault. Any structure
built across the fault (or in the ground rupture zone) is at risk of severe structural damage and in some cases
can be torn in two.
Along the West Valley Fault, there is a likelihood that ground rupture will occur in the vicinity of around five
to ten meters on each side of the fault. For an M7.2, the rupture length could be as high as 1 meter. Any
man-made structure within the fault zone area will be exposed to ground rupture which can cause the
following effects on various built structures:
• Ground rupture can cause severe damage to buildings and in some instances their complete
collapse.
• Ground rupture can displace roads and bridges and necessitate extensive repairs that will put these
infrastructures out of commission until repairs are made.
• For buried pipes and structures, a rupture could translate into cracking or complete rupture of
pipes, cables, and other underground structures.
Districts 2 and 3 intersects the rupture zone of the West Valley Fault. Barangays situated in the vicinity of
fault are: Bagong Silangan, Batasan Hills, Matandang Balara, Pansol, Loyola Heights, Blue Ridge B, Libis, St.
Ignatius, Bagumbayan, White Plains, and Ugong Norte. Major roads such as the Batasan San Mateo Road
and E. Rodriguez Jr. Avenue intersects the fault rupture zone as shown in Figure 76 and Figure 77.

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Figure 76. Intersection of District 2 along West Valley Fault with indication of major road segment along the fault trace

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Figure 77. Intersection of District 3 along West Valley Fault with indication of major road segment along the fault trace

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4.4. Earthquake Risk Assessment

4.4.1. Introduction
This section will use the estimate the potential damages and losses (i.e., risk) from the M7.2 earthquake
scenario on Quezon City based on the hazard data developed in Chapter 2. The calculation of risk requires
two elements: 1) The quantification of the earthquake intensity at each grid as calculated in the previous
chapter; and 2) the knowledge of vulnerability of (or fragility) of buildings, critical facilities, infrastructure,
and populations present in each grid. In this context, this chapter introduces both the concept of
vulnerability and the concept of risk. The assessment of impact (or risk) is the most relevant to disaster risk
management (DRM) planning and can inform preparedness and awareness activities.

4.4.2. The concept of risk

To better understand this concept of risk, it is important to explain its definition and the factors that
comprise the analytical formulation that one uses to assess risk. By definition, risk is the likelihood for
populations, the built environment or the natural environment to sustain damage (or loss) should a
hazardous event take place. According to the above, risk is a probabilistic quantity, that indicates that there
is some chance that a damage/loss will happen. The likelihood of loss is completely conditional on a
hazardous event taking place. Without the occurrence of a hazardous event, there is simply zero risk. Also,
embedded in the definition of risk is the notion of vulnerability of the exposed assets. In fact, the chances
for the risk to be high are directly correlated to the vulnerability of the exposed assets, i.e., populations,
built environment or natural environment. Therefore, risk can be considered to be the convolution of
physical hazards and the vulnerability of exposed assets.

Risk=Function {Hazard, Vulnerability (Exposed Assets)}

While vulnerability is an inherent property of any asset (i.e., population, built environment or natural
environment), risk is a calculated quantity. A risk value represents a quantity of damage (e.g., damage to
buildings or bridges) or loss (e.g., loss of life or economic loss).
Typically, ground shaking will cause the most damage during and after an earthquake in terms of the
number of structures that will be impacted in various parts of Quezon City.

4.4.3. Building damage approach

It is not economically possible to assess the capacity of each building and how it will withstand ground
shaking. To streamline analyses, buildings are grouped into typical construction classes that have shown to
exhibit similar patterns of damage in the past. Empirical data and available earthquake engineering
knowledge are used to develop fragility and vulnerability functions, which are then applied to estimate the
potential damages to each construction class. Building fragility functions are engineering quantities that
provide the probability of exceedance of specific damage states for a particular building class as a function
of the earthquake intensity. On the other hand, vulnerability curves provide the cumulative distribution
function of the damage ratio of a particular building class as a function of the earthquake intensity. The
damage ratio is defined as the cost of repairing the earthquake-caused damage to the building over the
replacement cost value of the building.

In order to calculate the impact of the M7.2 WVF earthquake scenario, both fragility functions and
vulnerability functions for all the building classes must be developed and applied to each building class at
each 175m x 175 m grid. The results at the grid level are aggregated to calculate the damage by barangay.
The latter are aggregated for the 142 barangays to develop the city-level damage and loss values.

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The fragility functions used by EMI have been developed by engineers and scientists at the UPD-ICE
(Tingatinga, et al., 2019) and are the same as the ones used in the GMMA-RAP study. This is the current
state-of-the-art approach to evaluate the performance of different building types to earthquake shaking
and to estimate building damage. Similarly, the same damage states the GMMA-RAP are considered,
namely: none, slight, moderate, extensive, collapse and complete collapse. Coefficient table is presented in
the paper by Tingatinga et. al., 2019. Some of these values are similar to the input parameters presented in
the GMMA-RAP report based on the illustrations for the different fragility and vulnerability models. The
analysis assumes that the coefficients from the reference paper are the most recent values from the same
team that developed the models for GMMA-RAP.

4.4.4. Building damage results

For an M7.2 WVF earthquake scenario, and following the approach taken by the GMMA-RAP study, the
building damage for the different barangays in Districts 1 to 6 in Quezon City can be estimated in terms of
building floor area (m2) associated with each damage state. The results are shown in Table 42 to Table 47.

Table 42. District 1 damaged floor area at each damage state (m2) for M7.2 West Valley Fault earthquake scenario.
Complete Complete
Barangay with without Extensive Moderate Slight None
Collapse Collapse
Alicia 1,509 11,646 9,827 8,723 3,669 42,752
Bagong Pag-asa 25,733 270,356 134,062 90,296 41,774 526,769
Bahay Toro 73,912 562,079 274,200 215,107 97,052 905,819
Balingasa 12,324 101,238 58,473 49,892 23,367 243,922
Bungad 13,480 109,488 60,783 45,228 19,745 200,837
Damar 6,377 44,282 21,325 17,609 8,380 63,334
Damayan 5,028 39,749 19,741 16,123 7,444 73,976
Del Monte 10,405 88,954 44,675 35,326 16,389 175,182
Katipunan 2,394 20,536 11,132 8,949 4,139 46,168
Lourdes 16,290 131,107 84,865 68,334 29,983 349,594
Maharlika 10,394 80,395 44,673 34,656 15,376 156,744
Manresa 16,746 150,371 85,393 70,574 32,931 387,899
Mariblo 2,822 23,712 12,041 9,874 4,586 49,800
Masambong 8,486 68,510 35,927 28,068 12,666 132,372
N. S. Amoranto 10,122 85,173 44,600 36,469 17,387 190,410
(Gintong Silahis)
Nayong Kanluran 39,653 294,346 181,202 155,607 70,891 649,738
Paang Bundok 4,661 35,860 16,535 11,578 4,760 43,789
Pag-ibig sa Nayon 6,259 53,501 30,788 25,705 11,698 132,987
Paltok 18,728 148,923 71,639 55,145 24,770 234,816
Paraiso 3,116 24,889 15,272 12,643 5,573 61,407
Phil-Am 13,668 100,384 43,058 30,859 13,630 112,831
Project 6 23,142 170,948 80,059 55,214 24,025 273,123
Ramon Magsaysay 6,917 68,729 37,782 29,268 13,525 162,156
Salvacion 12,224 90,615 49,794 41,648 18,858 177,087
San Antonio 44,647 345,123 206,530 168,061 76,931 795,568
San Isidro Labrador 11,423 92,863 39,909 28,581 12,688 121,731
San Jose 5,874 52,674 26,012 19,225 8,539 93,714
Sienna 13,158 96,193 37,276 23,049 8,977 75,456

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Complete Complete
Barangay with without Extensive Moderate Slight None
Collapse Collapse
St. Peter 6,117 54,056 22,724 15,631 6,647 66,141
Sta. Cruz 11,056 84,814 40,377 30,672 13,948 135,526
Sta. Teresita 15,271 118,397 49,684 39,063 18,031 162,858
Sto. Cristo 16,944 200,053 109,288 71,522 33,501 464,062
Sto. Domingo 27,172 227,442 117,352 84,435 38,474 404,961
Talayan
(Matalahib) 10,996 86,286 42,395 33,355 15,461 150,221
Vasra 13,796 111,772 66,804 44,306 18,447 189,425
Veterans Village 17,871 138,547 66,931 49,470 22,430 217,850
West Triangle 17,915 151,228 70,942 49,996 22,222 226,331

Table 43. District 2 damaged floor area at each damage state (m2) for M7.2 West Valley Fault earthquake scenario.
Complete Complete
Barangay with without Extensive Moderate Slight None
Collapse Collapse
Bagong Silangan 105,578 811,085 248,166 135,702 51,012 435,721
Batasan Hills 193,220 1,419,615 437,579 231,228 84,856 690,097
Commonwealth 93,535 699,300 326,653 227,956 91,059 820,604
Holy Spirit 97,605 734,007 324,999 217,970 86,373 757,676
Payatas 92,038 740,552 287,017 186,821 75,642 670,496

Table 44. District 3 damaged floor area at each damage state (m2) for M7.2 West Valley Fault earthquake scenario.
Complete Complete
Barangay with without Extensive Moderate Slight None
Collapse Collapse
Amihan 5,363 37,839 11,959 7,225 2,834 34,428
Bagumbayan 92,111 964,165 279,357 119,159 49,203 502,074
Bagumbuhay 9,685 74,173 26,399 15,295 6,122 59,397
Bayanihan 1,904 16,521 8,208 4,606 1,651 16,685
Blue Ridge A 10,338 72,697 17,672 8,982 3,263 30,076
Blue Ridge B 7,160 48,919 12,278 5,762 1,923 14,995
Camp Aguinaldo 30,095 212,690 97,536 56,423 20,775 179,928
Claro (Quirino 3-B) 4,043 29,628 13,875 8,456 3,056 27,035
Dioquino Zobel 1,822 13,944 4,855 2,888 1,130 10,252
Duyan-duyan 6,072 48,158 22,057 12,491 4,567 43,160
E. Rodriguez 25,111 212,471 91,159 57,448 23,554 234,283
East Kamias 9,425 69,455 32,474 21,024 8,020 69,979
Escopa 1 502 3,494 2,210 1,026 284 2,907
Escopa 2 474 3,511 2,167 933 246 2,792
Escopa 3 2,642 21,309 7,129 3,680 1,341 12,101
Escopa 4 790 5,537 1,532 775 274 2,081
Libis 2,870 21,833 6,320 2,907 1,003 8,782
Loyola Heights 78,706 648,006 222,146 117,472 45,360 411,940
Mangga 4,712 38,789 18,989 10,036 3,791 38,734
Marilag 22,438 161,240 54,464 30,352 11,404 111,146
Masagana 6,861 47,429 14,041 8,332 3,225 44,087
Matandang Balara 91,775 700,511 254,823 156,484 62,254 544,892

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Complete Complete
Barangay with without Extensive Moderate Slight None
Collapse Collapse
Milagrosa 11,227 81,759 26,011 14,706 5,552 56,373
Pansol 68,792 514,796 215,976 117,048 40,192 349,503
Quirino 2-A 4,514 33,627 24,888 15,971 5,451 51,604
Quirino 2-B 6,484 45,730 16,679 10,208 3,939 32,110
Quirino 2-C 3,058 21,349 7,423 4,597 1,772 17,886
Quirino 3-A 3,068 25,955 10,322 5,584 2,289 23,879
San Roque 25,432 206,374 80,300 47,329 18,539 171,817
Silangan 51,206 506,114 218,299 124,786 52,712 558,946
Socorro 32,349 348,561 165,645 105,110 47,344 548,951
St. Ignatius 7,714 64,955 28,817 21,942 10,431 106,052
Tagumpay 3,622 30,854 12,480 7,534 2,951 31,495
Ugong Norte 110,849 837,986 264,357 135,063 48,994 452,927
Villa Maria Clara 3,313 23,328 6,867 4,015 1,549 20,250
West Kamias 5,529 42,833 20,971 14,233 5,707 54,679
White Plains 26,052 178,538 52,114 28,828 10,508 76,840

Table 45. District 4 damaged floor area for each damaged state (m2) for M7.2 West Valley Fault earthquake scenario.
Complete Complete
Barangay with without Extensive Moderate Slight None
Collapse Collapse
Bagong Lipunan ng 26,455 226,221 104,367 64,613 25,918 244,783
Crame
Botocan 1,206 10,882 3,544 2,229 927 8,838
Central 24,429 238,687 127,989 78,820 34,529 386,307
Damayang Lagi 16,286 136,945 60,763 46,421 21,490 216,412
Doña Aurora 3,263 24,193 14,167 11,771 5,148 53,397
Doña Imelda 19,895 211,271 112,449 75,730 35,208 447,950
Doña Josefa 5,613 50,734 31,926 24,638 11,062 138,966
Don Manuel 5,322 44,206 25,047 19,642 8,745 95,531
Horseshoe 8,142 58,651 28,300 19,410 7,704 67,440
Immaculate 13,801 116,197 57,992 37,312 15,269 154,916
Kalusugan
Concepcion 12,211 106,539 62,041 45,060 20,837 234,875
Kamuning 12,426 96,956 41,828 28,953 12,302 113,788
Kaunlaran 16,720 145,691 65,104 42,515 17,582 167,558
Kristong Hari 6,817 61,332 34,216 24,401 10,275 108,213
Krus na Ligas 12,024 88,304 37,948 23,265 8,756 73,557
Laging Handa 18,197 151,394 67,276 46,666 20,640 195,094
Malaya 3,208 28,390 13,584 7,891 3,194 32,976
Mariana 43,654 318,951 151,700 109,791 46,663 425,960
Obrero 4,228 37,374 21,140 16,337 6,976 75,436
Old Capitol Site 2,966 27,011 11,056 7,442 3,215 31,443
Paligsahan 12,448 130,697 69,784 48,004 22,336 270,104
Pinagkaisahan 6,660 54,436 41,808 28,657 10,815 115,853
Pinyahan 33,146 291,762 140,674 89,895 38,169 396,873
Roxas 8,984 65,013 36,116 29,214 12,649 125,015
Sacred Heart 14,032 117,770 59,800 40,654 16,853 169,960

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Complete Complete
Barangay with without Extensive Moderate Slight None
Collapse Collapse
San Isidro 6,920 54,491 24,368 19,014 8,508 83,300
San Martin de Porres 6,014 56,484 27,837 17,647 7,098 71,948
San Vicente 2,227 17,330 8,914 5,560 2,212 36,481
Santol 53,349 405,120 191,507 152,378 69,022 629,421
Sikatuna Village 9,131 75,057 30,642 18,556 7,494 74,109
South Triangle 10,697 76,818 26,331 13,837 4,859 42,472
Sto. Niño 4,651 36,612 16,183 12,755 5,721 55,585
Tatalon 18,560 172,980 87,144 67,720 31,997 374,082
Teachers Village East 7,143 55,449 20,966 13,016 5,227 44,550
Teachers Village West 7,973 56,156 19,954 12,864 5,153 42,109
U. P. Campus 58,428 464,656 228,766 138,571 55,612 549,044
U. P. Village 10,798 78,633 32,847 20,408 8,125 70,788
Valencia 14,497 153,296 67,100 43,023 19,079 194,110

Table 46. District 5 damaged floor area at each damage state (m2) for M7.2 West Valley Fault earthquake scenario.
Complete Complete
Barangay with without Extensive Moderate Slight None
Collapse Collapse
Bagbag 23,179 186,454 97,621 84,984 40,489 437,962
Capri 2,151 15,514 7,890 6,856 3,334 29,184
Fairview 56,981 426,100 187,794 133,324 57,715 508,915
Greater Lagro 45,957 357,340 160,428 111,171 48,596 450,335
Gulod 19,158 155,769 72,534 61,425 29,846 306,461
Kaligayahan 31,200 232,876 126,913 110,032 52,665 532,718
Nagkaisang Nayon 6,608 52,838 25,662 18,428 7,798 74,859
North Fairview 16,298 126,395 69,704 42,798 16,762 166,190
Novaliches Proper 30,975 234,819 96,590 71,752 32,039 272,567
Pasong Putik Proper 23,839 200,424 100,959 81,714 38,858 418,220
San Agustin 15,294 126,329 68,441 55,483 25,216 271,671
San Bartolome 3,472 27,897 12,125 9,029 4,059 38,359
Sta. Lucia 30,755 230,826 119,300 100,635 46,585 469,357
Sta. Monica 10,766 88,070 46,248 34,452 15,703 178,344

Table 47. District 6 damaged floor area at each damage state (m2) for M7.2 West Valley Fault earthquake scenario.
Complete Complete
Barangay with without Extensive Moderate Slight None
Collapse Collapse
Apolonio Samson 44,140 371,421 214,587 178,772 82,578 897,894
Baesa 41,124 312,197 189,806 164,072 74,743 744,194
Balong-bato 7,540 54,173 34,309 28,968 12,775 122,315
Culiat 73,846 566,664 218,338 149,938 63,785 550,192
New Era 4,130 34,625 15,809 11,547 5,245 51,991
Pasong Tamo 121,196 890,841 345,992 241,189 102,452 832,819
Sangandaan 24,723 179,089 89,037 73,256 34,006 301,940
Sauyo 11,757 91,220 44,989 33,846 15,600 151,083
Talipapa 38,550 298,114 150,387 122,421 57,143 545,745

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Complete Complete
Barangay with without Extensive Moderate Slight None
Collapse Collapse
Tandang Sora 102,592 759,537 340,638 262,246 117,618 1,007,603
Unang Sigaw 2,097 20,828 12,364 11,015 5,211 68,424

4.4.5 Casualty modeling approach

The primary cause of fatalities in earthquakes is due to building collapse. Estimates of people affected are
an important source of information for planning and emergency response. At present, building codes are
not retroactive and there are no mandatory requirements for building owners to assess their buildings or to
eventually retrofit them to bring them to current earthquake engineering standards. This means that older
buildings may not be built to current standards and are likely to sustain more damage, if not collapse.
Retrofitting buildings is a complex process that requires high level of earthquake engineering expertise and
could be extremely costly and inconvenient. Experience has shown that establishing public policy and
related regulations for earthquake retrofit could take several years (if not decades), and could be quite
challenging to put in place, particularly for large commercial and residential buildings.
Thus, the casualty estimations provided below should be interpreted within the limitations indicated above.
They are mainly provided as parameters for planning and preparedness. That is the full benefit of
undertaking earthquake scenarios and simulations.

Injury Classification
In earthquake engineering, casualties and injuries are split into three categories:
• Non-life-threatening injuries (essentially people that do not need to immediately go to the hospital
and generally can treat themselves),
• Life-threatening injuries (people who need to go to the hospital), and
• Fatalities.
By classifying casualties and injuries into three categories, public institutions can plan for the number of
people that will need to receive medical care to survive during a specific magnitude earthquake event.
The GMMA-RAP presented 4 injury severity levels with descriptions and factors at which the fraction of
the population at a specific building damage state will be identified at the different injury severity levels.
Table 48 enumerates classification from HAZUS methodology used in the GMMA-RAP study. It should be
noted that the HVRA+H combined levels 1 and 2 to comprise non-life-threatening injuries, level 3 for life-
threatening and level 4 for loss of life. HAZUS is the official loss estimation tool for the US federal
government. Its methodology is widely used in loss estimation and is considered to be state-of-the-art.

Table 48. Injury classification based on Hazus methodology (GMMA-RAP, 2013)

Injury
Severity Description
Level
1 Injuries require basic medical aid that could be administered by paraprofessionals.
These types of injuries would require bandages or observation. Some examples are a
sprain, a severe cut requiring stitches, a minor burn (first degree or second degree on
a small part of the body), or a bump on the head without loss of consciousness.
Injuries of lesser severity that could be self-treated are not estimated.

2 Injuries requiring a greater degree of medical care and use of medical technology such
as x-rays or surgery, but not expected to progress to a life-threatening status. Some

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examples are third-degree burns or second-degree burns over large parts of the body,
a bump on the head that causes loss of consciousness, fractured bone, dehydration or
exposure.

3 Injuries that pose an immediately life-threatening condition if not treated adequately

and expeditiously. Some examples are: uncontrolled bleeding, punctured organ, other
internal injuries, spinal column injuries, or crush syndrome.

4 Instantaneously killed or mortally injured

4.4.5. Casualty results

The estimated number of people in a certain injury severity level is equal to the product of indoor casualty
rate, damage probability and population for each unit. For each severity level, the number of people from all
damage states is summed to obtain the number of people in a severity level. Estimated number of casualties
for Districts 1 to 6 in Quezon City is presented in Table 49 to Table 54. Figure 78 to Figure 83 show the
distribution of severe and life-threatening injuries. Figure 84 to Figure 89 present the distribution of
fatalities for Districts 1 to 6. Total estimated casualties for Quezon City are presented in

Table 55.

An important limitation of the casualty calculations is that the estimates do not consider the potential of
one or multiple large high occupancy building(s) collapsing and causing major loss of life. As explained
previously, the state-of-the-art in loss estimation is based on empirical relations of patterns of damage to
typical construction classes across a city. It is not based on a building-specific assessment. A building-by-
building assessment may be necessary for older high occupancy buildings under separate initiatives that
should be backed up by specific public policy and regulation. The casualty estimations provided below
should be interpreted within the limitations indicated above.

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Table 49. Estimated casualties/injuries for a M7.2 West Valley Fault earthquake scenario caused by building damage for
District 1
Life-
Slight Serious
Barangay threatening Fatalities
Injuries Injuries
Injuries
Alicia 112 37 6 13
Bagong Pag-asa 491 155 24 47
Bahay Toro 2,077 706 126 250
Balingasa 452 150 26 51
Bungad 149 50 9 17
Damar 54 19 3 7
Damayan 230 78 14 27
Del Monte 314 104 18 35
Katipunan 64 21 4 7
Lourdes 100 33 6 11
Maharlika 104 35 6 12
Manresa 512 166 28 55
Mariblo 100 33 6 11
Masambong 339 113 20 39
N. S. Amoranto (Gintong Silahis) 319 106 18 36
Nayong Kanluran 762 258 46 92
Paang Bundok 182 62 11 22
Pag-ibig sa Nayon 119 39 7 13
Paltok 499 168 30 58
Paraiso 84 28 5 10
Phil-Am 78 27 5 10
Project 6 502 172 31 62
Ramon Magsaysay 341 108 18 34
Salvacion 461 157 28 56
San Antonio 1,714 576 102 202
San Isidro Labrador 358 120 21 41
San Jose 161 53 9 17
Sienna 88 31 6 11
St. Peter 89 29 5 10
Sta. Cruz 135 46 8 16
Sta. Teresita 268 91 16 32
Sto. Cristo 251 77 11 22
Sto. Domingo (Matalahib) 389 129 22 44
Talayan 166 56 10 20
Vasra 267 89 16 31
Veterans Village 432 146 26 51
West Triangle 130 43 7 15

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Table 50. Estimated casualties/injuries for a M7.2 West Valley Fault earthquake scenario caused by building damage for
District 2
Life-
Slight Serious
Barangay threatening Fatalities
Injuries Injuries
Injuries
Bagong Silangan 4,972 1,714 307 607
Batasan Hills 8,863 3,085 563 1,116
Commonwealth 7,259 2,485 447 885
Holy Spirit 4,440 1,521 273 541
Payatas 5,530 1,874 329 649

Table 51. Estimated casualties/injuries for a M7.2 West Valley Fault earthquake scenario caused by building damage for
District 3
Life-
Slight Serious
Barangay threatening Fatalities
Injuries Injuries
Injuries
Amihan 215 75 14 28
Bagumbayan 1,044 336 54 107
Bagumbuhay 293 101 18 36
Bayanihan 42 14 2 5
Blue Ridge A 104 37 7 14
Blue Ridge B 103 36 7 14
Camp Aguinaldo 184 64 12 23
Claro (Quirino 3-B) 169 58 11 21
Dioquino Zobel 85 29 5 10
Duyan-duyan 163 55 10 19
E. Rodriguez 672 224 39 76
East Kamias 221 76 14 27
Escopa 1 87 30 6 11
Escopa 2 60 20 4 7
Escopa 3 401 136 24 47
Escopa 4 114 40 7 15
Libis 187 65 12 23
Loyola Heights 912 308 54 107
Mangga 35 12 2 4
Marilag 420 147 27 53
Masagana 189 67 12 25
Matandang Balara 2,919 1,003 180 356
Milagrosa 289 101 18 37
Pansol 1,863 640 115 229
Quirino 2-A 160 54 10 19
Quirino 2-B 120 42 8 15
Quirino 2-C 126 44 8 16
Quirino 3-A 41 14 2 5
San Roque 780 264 46 92
Silangan 1,250 403 66 130
Socorro 648 204 32 63
St. Ignatius 80 27 5 9
Tagumpay 81 27 5 9

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Life-
Slight Serious
Barangay threatening Fatalities
Injuries Injuries
Injuries
Ugong Norte 570 197 36 71
Villa Maria Clara 118 42 8 15

West Kamias 148 50 9 18 Table

White Plains 344 122 23 45 52.
Estimated casualties/injuries for a M7.2 West Valley Fault earthquake scenario caused by building damage for District 4
Life-
Slight Serious
Barangay threatening Fatalities
Injuries Injuries
Injuries
Bagong Lipunan ng Crame 597 198 34 68
Botocan 324 108 18 35
Central 386 123 20 40
Damayang Lagi 552 184 32 62
Doña Aurora 140 47 9 17
Doña Imelda 303 95 15 29
Doña Josefa 45 14 2 5
Don Manuel 86 28 5 10
Horseshoe 114 39 7 14
Immaculate Concepcion 260 86 15 29
Kalusugan 15 5 1 2
Kamuning 500 170 30 60
Kaunlaran 243 81 14 27
Kristong Hari 112 37 6 12
Krus na Ligas 893 308 56 111
Laging Handa 271 91 16 31
Malaya 137 45 8 15
Mariana 363 125 23 45
Obrero 203 66 11 22
Old Capitol Site 18 6 1 2
Paligsahan 152 48 8 15
Pinagkaisahan 158 52 9 18
Pinyahan 805 265 45 89
Roxas 543 186 34 67
Sacred Heart 238 79 14 27
San Isidro 557 188 33 66
San Martin de Porres 361 117 19 38
San Vicente 236 79 14 28
Santol 1,021 348 62 123
Sikatuna Village 213 72 12 25
South Triangle 143 50 9 18
Sto. Niño 323 109 19 38
Tatalon 1,573 510 84 165
Teachers Village East 134 46 8 16
Teachers Village West 193 67 12 25
U. P. Campus 2,025 681 120 238
U. P. Village 220 76 14 28

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Life-
Slight Serious
Barangay threatening Fatalities Table
Injuries Injuries
Injuries 53.
Valencia 278 88 14 28
Estimated casualties/injuries for a M7.2 West Valley Fault earthquake scenario caused by building damage for District 5
Life-
Slight Serious
Barangay threatening Fatalities
Injuries Injuries
Injuries
Bagbag 2,227 745 130 257
Capri 474 163 30 59
Fairview 2,062 707 127 252
Greater Lagro 815 277 49 97
Gulod 1,337 448 78 154
Kaligayahan 1,514 514 92 183
Nagkaisang Nayon 210 71 12 25
North Fairview 842 284 50 100
Novaliches Proper 1,071 367 66 130
Pasong Putik Proper 960 319 55 108
San Agustin 814 270 47 92
San Bartolome 82 28 5 10
Sta. Lucia 1,714 583 104 207
Sta. Monica 462 154 27 53

Table 54. Estimated casualties/injuries for a M7.2 West Valley Fault earthquake scenario caused by building damage for
District 6
Life-
Slight Serious
Barangay threatening Fatalities
Injuries Injuries
Injuries
Apolonio Samson 890 293 50 99
Baesa 1,565 527 94 185
Balong-bato 215 73 13 26
Culiat 3,062 1,049 188 371
New Era 277 92 16 32
Pasong Tamo 5,037 1,741 316 626
Sangandaan 676 232 42 84
Sauyo 508 172 31 61
Talipapa 938 317 56 111
Tandang Sora 3,136 1,076 194 385
Unang Sigaw 140 44 7 14

Table 55. Estimated total casualties of Quezon City for a M7.2 West Valley Fault earthquake scenario
Life-
Slight Serious
Total threatening Fatalities
Injuries Injuries
Injuries
Quezon City 104,955 35,618 6,317 12,494

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Figure 78. District 1 injuries requiring hospitalization for an M7.2 West Valley Fault earthquake scenario caused by
building damage.

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Figure 79. District 2 injuries requiring hospitalization for an M7.2 West Valley Fault earthquake scenario caused by
building damage.

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Figure 80. District 3 injuries requiring hospitalization for an M7.2 West Valley Fault earthquake scenario caused by
building damage.

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Figure 81. District 4 injuries requiring hospitalization for an M7.2 West Valley Fault earthquake scenario caused by
building damage.

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Figure 82. District 5 injuries requiring hospitalization for an M7.2 West Valley Fault earthquake scenario caused by
building damage.

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Figure 83. District 6 injuries requiring hospitalization for an M7.2 West Valley Fault earthquake scenario caused by
building damage.

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Figure 84. District 1 estimated fatalities for an M7.2 West Valley Fault earthquake scenario caused by building damage.

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Figure 85. District 2 estimated fatalities for an M7.2 West Valley Fault earthquake scenario caused by building damage.

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Figure 86. District 3 estimated fatalities for an M7.2 West Valley Fault earthquake scenario caused by building damage.

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Figure 87. District 4 estimated fatalities for an M7.2 West Valley Fault earthquake scenario caused by building damage.

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Figure 88. District 5 estimated fatalities for an M7.2 West Valley Fault earthquake scenario caused by building damage.

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Figure 89. District 6 estimated fatalities for an M7.2 West Valley Fault earthquake scenario caused by building damage.

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Displaced Populations

A critical data point that can be derived from building damage are estimates of how many people would be
displaced under the M7.2 earthquake scenario. The count of displaced population is obtained from the
number of buildings in complete damage state, collapse state and extensive damage state. The assumption
is that buildings in these damage states will not inhabitable and their inhabitants will become homeless.
Only residential buildings are taken into consideration and the assumption is that the earthquake takes
place at night or at the time and day where most people are in their homes. Since there is no data on
amount of population by building, a general assumption is made that the population is evenly distributed
among the buildings.

Table 56 provides an estimate of the total number of people that would need temporary shelters and
eventually require support for a new housing unit after a M7.2 earthquake in Quezon City. It is shown that
the earthquake could put almost half of the total population in need of temporary or permanent sheltering.

Table 56. Aggregated estimate of displaced population from M7.2 earthquake scenario
Total Population Displaced Population Rate
3,242,298 1,561,765 48%

Figure 90 and Figure 91 provide maps for displaced population by barangay in terms of actual estimated
numbers and proportion (or density) of displaced population relative to the total population of the
barangay.
Table 57 to Table 62 provide the number and proportion (or ratio) of population displace by barangay for
each of the six districts of the city.
It is important to note that earthquakes present a unique challenge in terms of sheltering, including the
following:
• Immediately after the earthquake, populations are very scared about going inside their homes
because they fear aftershocks and are not confident about the structural integrity of their buildings.
They would feel much safer outdoors.
• This situation can last several days or weeks, due to the occurrence of aftershocks. However, after
some time, residents can go back to their homes if they develop a sense of security about the
integrity of their building.
• In all cases, the number of people needing shelter after an earthquake can be quite large, in this
case more than 1.5 million.
• There will be significant pressure on city officials to inspect buildings and to assess the structural
integrity of buildings. The city should have a process for rapid safety inspection after an
earthquake and for “placarding the buildings according to the safety level. Typically, a three level
scale is used: Green (for safe), Orange (for requiring more assessment but residents can enter with
caution), and Red (unsafe).
• Earthquakes come with no warning and people who evacuate their homes do not have the time to
take with them essential belongings, valuable documents, and resources (e.g., cash or identity
documents). This creates a situation where most people do not want to evacuate far from their
homes.
• Large earthquakes are followed by several aftershocks that can also be large and damaging. This
creates a level of fear for people to go back into their homes. Many residents will stay outdoors
even if their homes have very little or no damage due to fears of earthquake aftershocks.

These conditions have pushed emergency managers and planners to shift the notion of sheltering for
earthquake to “sheltering-in-place.” We recommend evaluating sheltering for earthquakes within the

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notion of sheltering in place and gradually introducing such a concept based on international best practices
and experience.

Table 57 Estimated number and ratio of displaced population for District 1for M7.2 earthquake scenario
Barangays in District 1 Total Population Displaced Population Ratio
Bahay Toro 72,440 30,981 43%
San Antonio 25,616 9,332 36%
Manresa 24,958 8,471 34%
Bagong Pag-asa 21,066 8,321 39%
Paltok 17,488 7,554 43%
Project 6 16,785 7,345 44%
Balingasa 20,656 7,264 35%
Veterans Village 14,890 6,482 44%
Sto. Domingo (Matalahib) 14,790 6,114 41%
Ramon Magsaysay 16,290 5,804 36%
Masambong 13,346 5,269 39%
Del Monte 12,729 4,943 39%
Sto. Cristo 12,455 4,539 36%
Vasra 9,986 4,321 43%
Sta. Teresita 7,924 3,602 45%
Damayan 8,802 3,504 40%
San Isidro Labrador 7,263 3,409 47%
Salvacion 7,876 3,080 39%
Paang Bundok 5,526 2,691 49%
San Jose 6,264 2,571 41%
Talayan 6,074 2,505 41%
N. S. Amoranto (Gintong Silahis) 6,714 2,445 36%
Bungad 5,774 2,360 41%
Sta. Cruz 4,674 2,013 43%
West Triangle 4,496 2,004 45%
Alicia 6,643 1,954 29%
Pag-ibig sa Nayon 5,591 1,940 35%
St. Peter 3,941 1,907 48%
Sienna 2,925 1,688 58%
Lourdes 4,818 1,645 34%
Maharlika 4,089 1,618 40%
Mariblo 4,197 1,574 38%
Paraiso 3,874 1,364 35%
Phil-Am 2,230 1,114 50%
Nayong Kanluran 2,864 1,061 37%
Katipunan 2,823 1,031 37%
Damar 1735 774 45%

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Table 58 Estimated number and ratio of displaced population for District 2 for M7.2 earthquake scenario

Barangays in District 2 Total Population Displaced Population Ratio

Batasan Hills 176,781 118,587 67%
Commonwealth 215,099 106,591 50%
Payatas 147,053 80,212 55%
Bagong Silangan 103,783 67,639 65%
Holy Spirit 123,802 64,540 52%

Table 59 Estimated number and ratio of displaced population for District 3 for M7.2 earthquake scenario
Barangays in District 3 Total Population Displaced Population Rate
Matandang Balara 70,759 40,918 58%
Pansol 43,655 26,720 61%
Bagumbayan 23,759 15,818 67%
Socorro 30,312 13,275 44%
Loyola Heights 20,822 12,967 62%
San Roque 20,017 11,363 57%
E. Rodriguez 19,921 10,169 51%
Ugong Norte 11,809 7,743 66%
Marilag 9,302 5,665 61%
Escopa 3 8,767 5,653 64%
White Plains 6,431 4,428 69%
Bagumbuhay 7,098 4,096 58%
Milagrosa 6,377 3,879 61%
East Kamias 6,101 3,229 53%
Silangan 5,564 2,854 51%
Amihan 5,129 2,839 55%
Quirino 2-A 5,754 2,665 46%
Camp Aguinaldo 4,620 2,631 57%
Libis 3,533 2,507 71%
Claro (Quirino 3-B) 4,467 2,467 55%
Duyan-duyan 4,376 2,446 56%
Masagana 4,433 2,443 55%
West Kamias 4,645 2,237 48%
Quirino 2-C 2,971 1,686 57%
Quirino 2-B 2,734 1,636 60%
Villa Maria Clara 2,725 1,539 56%
Escopa 4 2,050 1,466 72%
Escopa 1 2,269 1,351 60%
Blue Ridge A 1,871 1,318 70%
Blue Ridge B 1,713 1,286 75%
Tagumpay 2,288 1,208 53%
Dioquino Zobel 1,992 1,177 59%
Escopa 2 1550 942 61%
St. Ignatius 2099 888 42%
Bayanihan 1237 664 54%
Quirino 3-A 1091 604 55%
Mangga 990 538 54%

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Table 60 Estimated number and ratio of displaced population for District 4 for M7.2 earthquake scenario
Barangays in District 4 Total Population Displaced Population Ratio
U. P. Campus 61,137 30,745 50%
Tatalon 69,108 25,594 37%
South Triangle 21,143 13,754 65%
Krus na Ligas 22,529 12,775 57%
Pinyahan 27,031 12,706 47%
Bagong Lipunan ng Crame 17,888 9,225 52%
Damayang Lagi 19,510 8,378 43%
Roxas 20,636 8,204 40%
Kamuning 14,855 7,335 49%
Central 14,816 6,505 44%
San Martin de Porres 12,132 5,860 48%
Mariana 11,302 5,300 47%
Doña Imelda 13,736 5,230 38%
Sto. Niño 10,925 4,772 44%
Botocan 8,391 4,748 57%
Valencia 9,565 4,575 48%
Laging Handa 8,646 4,102 47%
Immaculate Concepcion 8,538 4,059 48%
San Isidro 9,136 3,986 44%
Kaunlaran 7,510 3,754 50%
Sacred Heart 8,169 3,735 46%
Sikatuna Village 6,972 3,724 53%
San Vicente 9,085 3,557 39%
Obrero 8,597 3,340 39%
U. P. Village 5,651 3,118 55%
Santol 7,143 3,093 43%
Pinagkaisahan 6,934 2,763 40%
Paligsahan 6,818 2,624 38%
Teachers Village West 4,455 2,598 58%
Malaya 4,286 2,170 51%
Doña Aurora 5,824 2,166 37%
Teachers Village East 3,343 1,909 57%
Kristong Hari 4,440 1,853 42%
Horseshoe 3,318 1,664 50%
Don Manuel 3,657 1,374 38%
Doña Josefa 2283 766 34%
Old Capitol Site 552 273 49%
Kalusugan 680 255 38%

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Table 61 Estimated number and ratio of displaced population for District 5 for M7.2 earthquake scenario
Barangays in District 5 Total Population Displaced Population Rate
Bagbag 97,933 34,559 35%
Fairview 61,002 29,854 49%
Nagkaisang Nayon 52,377 23,941 46%
Kaligayahan 63,995 23,032 36%
North Fairview 45,317 21,968 48%
San Bartolome 45,794 20,979 46%
Gulod 52,779 20,243 38%
Sta. Monica 49,714 19,307 39%
Pasong Putik Proper 39,913 15,023 38%
Greater Lagro 25,092 12,050 48%
Sta. Lucia 27,311 10,429 38%
San Agustin 23,931 8,938 37%
Novaliches Proper 16,267 7,980 49%
Capri 17,758 6,989 39%

Table 62 Estimated number and ratio of displaced population for District 6 for M7.2 earthquake scenario
Barangays in District 6 Total Population Displaced Population Rate
Pasong Tamo 131,396 70,405 54%
Tandang Sora 97,674 45,354 46%
Culiat 82,205 43,507 53%
Sauyo 77,806 33,036 42%
Baesa 69,441 24,713 36%
New Era 33,979 15,031 44%
Apolonio Samson 40,962 14,425 35%
Talipapa 35,363 14,207 40%
Sangandaan 23,824 9,938 42%
Balong-bato 9,081 3,353 37%
Unang Sigaw 8,282 2,437 29%

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Figure 90 Estimate number of displaced population by barangay for M7,2 earthquake scenario

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Figure 91 Estimate of proportion of displaced population by barangay from the M7.2 earthquake scenario

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Figure 92 Displaced populations for the M7.2 earthquake scenario for District 1 and District 2

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Figure 93 Displaced populations for the M7.2 earthquake scenario for District 3 and District 4

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Figure 94 Displaced populations for the M7.2 earthquake scenario for District 5 and District 6

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Part 5:
Landslide Hazard and Risk

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Part 5. Landslide Hazard and Risk Assessment

5.1 Background and Introduction

Quezon City has a large land area comprising varying geomorphologic features. The city has the highest
elevation of 250 m and an average elevation of 67 m above sea level characterized by plain and gentle to
steep slopes ranging from eight to fifteen percent (8-15%). A rugged mountainous ridge can be observed on
the eastern portion of Quezon City which is influenced by the Valley Fault System, specifically the West
Valley Fault. The geologic and structural character of the area renders it prone to slope instabilities.
Consequently, several landslide susceptibility studies have been carried out for Quezon City, including the
1: 10,000-scale rain-induced landslide susceptibility maps of Quezon City, Metro Manila by the Bureau of
Mines and Geology (MGB) in the Philippines, which are being used as official maps for land-use planning in
Metro Manila since they were created in 2014. Updating of the 1:10,000-scale landslide susceptibility map
to ensure the accuracy of the landslide susceptibility ratings was carried out successfully through field
investigations by a technical team from MGB from August 23 to September 10, 2021 (Mines and
Geosciences Bureau, 2021) as shown in Figure 95. The updated susceptibility rating followed the
Guidebook for 1:10,000-scale Geohazards Mapping (Mines and Geosciences Bureau, 2010) as shown in
Table 63, as well as integrating previous MGB field assessments covering the target areas in Quezon City.

Table 63. Landslide susceptibility parameters used during the assessment.

Landslide
Susceptibility Low Moderate High Very High
Parameters
Low to moderate Moderate to Steep to very Steep to very
A. Slope Gradient
(<18) steep (18-35) steep (>35) steep (>35)

B. Weathering/ Intense; Soil Intense; Soil

Slight to
Soil Moderate usually non- usually non-
moderate
Characteristics cohesive cohesive

C. Rock Mass Very good to

Fair Poor to very poor Poor to very poor
Strength good

Soil creep and

Stable with no Active landslide
other indications Inactive
identified evident; tension
D. Ground for possible landslides
landslide scars, cracks, bulges,
Stability landslide evident; tension
either old, recent terracettes, and
occurrence are cracks present
or active seepage present
present

May be an
E. Human
aggravating
Initiated Effects
factor

The objective of the current project is to re-calibrate the 2021 updated 1:10,000 landslide susceptibility
maps using an infinite slope stability method using the SINMAP software. This recalibration will introduce a
5-meter Digital Elevation Model as well as recent information on soil characteristics and other information
on the surficial and bedrock geology. The goal is to derive updated landslide susceptibility maps by

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complimenting the statistical method and field observations inherent to the 1:10,000 MGB maps using a
process-driven method that accounts for both fully saturated (wet) and no saturation (dry) conditions in the
hydrologic regime to account for best-case and worst-case scenarios due to Climate Change. In a final step,
building, infrastructure, and social and economic data available within the project, will be used in a hotspot
analysis to classify exposed populations and assets susceptible to landslides in Quezon City. Considerations
should also be on the impact of Climate Change in the final report for the landslide risk assessments.

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Figure 95. Updated Flood and Landslide Susceptibility Map (MGB, 2021)

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5.2. Methodology
Landslide susceptibility is the probability of a landslide occurring in an area by local environmental
conditions. It is the degree to which terrain can be affected by slope movements, i.e., an estimate of
“where” landslides are likely to occur. Landslide susceptibility modeling can be carried out using statistical
(bivariate, multivariate, heuristic) methods which account for correlations between landslide incidence and
different layers of geomorphic or lithology data. Another modeling approach is a physics-based or process-
driven method that accounts for the horizontal and vertical forces on the slope, which result in a factor of
safety against failure, which is 1.0 or greater. The Stability Index Mapping (SINMAP) is one method of
landslide susceptibility mapping applied to shallow translational landslide phenomena controlled by shallow
groundwater flow convergence. The advantage of SINMAP model implemented in a geographic information
system (GIS) environment is that it is possible to analyze quickly over large areas even with limited data.
SINMAP modelling combines a slope stability model with a steady-state hydrology model to delineate areas
prone to shallow landslides. SINMAP has been successfully applied in the DOST- Project NOAH, one of the
hazard-mapping initiatives of the government, to map all landslide hazards in the Philippines using both
computer models as well as validating ground data.

SINMAP is the mapping method of landslide susceptibility which uses the slope stability principle. The
slope stability of an area is calculated by the following equations:
𝑅𝛼
𝑆𝐼 = 𝐹𝑆 = (𝑐 + 𝑐𝑜𝑠𝜃 [1 − min ( , 1) 𝑟] 𝑡𝑎𝑛𝜑)/𝑠𝑖𝑛𝜃
𝜏𝑠𝑖𝑛𝜃
𝑅𝛼
𝑤 = 𝑀𝑖𝑛 ( , 1)
𝜏𝑠𝑖𝑛𝜃

where SI is stability index or FS is the factor of safety, θ is the slope angle; C is the dimensionless cohesion
value integrating both soil and root cohesion, as well as soil density and thickness w is the relative wetness
as the relation of water-table height to soil thickness; r is the ratio of the density of water to the density of
soil, φ is the internal friction angle, and equation (2) is an estimate of the relative wetness, which is the
effective water recharge I for a is the internal friction angle. Relative wetness (w) is modeled as induced by
topographic conditions and depends on the specific catchment (a) area of a given point.

SINMAP model needs some parameters related to the physical properties of soil and hydrology data such as
soil cohesion (C), internal friction angle (φ), and a ratio of transmission to effective recharge (T/R) or
relative wetness (w). Soil strength parameters such as cohesion and friction angle are material properties
that are typically not included on geologic maps or soil maps. Thus, this information, which is a very crucial
ingredient to the analysis, often has to be inferred from available databases of soils and geology. A good
rule of thumb is, that the better the resolution of these maps, the better the inference that can be made on
soil strength parameters. Geologic maps describing the units based on composition and properties of
bedrock, the texture of the surficial material (soil cover) and detailed description of material types, bedding
thickness and fracture spacing allow the expert to assign strength parameter values to these units. Likewise,
soil databases conveying information about the units based on a USCS (Universal Soil Classification
System), swelling potential, liquid limit, and particle size among others allow for an intelligent assignment of
strength parameters. Unfortunately, soil strength test data is usually proprietary information and difficult to
obtain and even when it is available it is highly localized and not easily generalized. Thus, in this context, it is
important not to overestimate the predictive capabilities of a GIS model by combining data layers that are
not consistent in their level of detail. The goal in assigning strength parameters to geologic units is to aim
for a conservative estimate of cohesion value and friction angle, but also to integrate as much information
as possible to obtain a level of accuracy consistent with other layers.

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5.3. Results
SINMAP modeling of Quezon City is carried out with a 5-meter Interferometric Synthetic Aperture Radar
(IFSAR) derived digital terrain model (DTM). Topographic, soil-strength and physical hydrologic parameters,
which include cohesion, angle of friction, bulk density and hydraulic conductivity, were assigned to each
pixel of a given DTM grid to compute the corresponding factor of safety. In the preliminary landslide
susceptibility analysis, soil cohesion (C) values with a lower bound of 0 to an upper bound of 0.8, and
internal friction angle (φ) of 25 to 35 degrees were used. A soil density of 1900 kg per cubic meter was
used as input in the calibration parameters.

The update and resolution of the soil strength data, soil depth and soil saturation which accounts for the
effective shear strength parameters are the levers for re-calibrating the 1:10,000 MGB landslide
susceptibility maps. Initial values were used for these parameters in the preliminary landslide susceptibility
map produced based on datasets shown in Table 64. The value of the soil strength parameters was
determined from soil map data based on surficial geologic maps, and Vs30 (260x260m) grids. In the final
analysis, the soil strength parameters and saturation conditions will be updated based on the inclusion of
more studies and other methods.

The three classes of the 1:10,000 MGB landslide susceptibility map (low, moderate and high) were
reclassified into five susceptibility classes of low, moderate, moderate to high, high and very high based on
the correlation of the original susceptibility class of the MGB maps and the FS values produced by the
SINMAP method (Table 65).

Table 64. Type of data used and the method of acquisition in preliminary analysis.

Type Comment Resolution Source

DEM 5-meter Interferomteric Synthetic 5m NAMRIA

Aperture Radar (IFSAR) derived
digital terrain model (DTM).

Vs30 reconstructed using color bands of 260m grid GMMA-RAP, 2014

the 2014 GMMA-RAP report’s figure

Updated Updated from the 2014 maps 1:10,000 Mines and Geosciences Bureau.
Landslide (2021). Updated 1:10,000-scale
Susceptibility Detailed Flood and Landslide
Map Susceptibility Map. Quezon City,
Metro Manila, Philippines.

Geologic Map Digitized from paper map 1:50,000 Philippine Bureau of Mines and
Geo-sciences. (1983). Geological
Map of Manila and Quezon City
Quadrangle. Metropolitan
Manila, Philippines.

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Table 65. Slope Stability classes and re-classification in susceptibility mapping

Factor of Safety Classification in 1:10,000 MGB Re-Classification
Landslide susceptibility map
FS>1.5 Low
Low
1.5 > FS > 1.25 Moderate

1.5 > FS > 1.25 Moderate

1.25 > FS > 1.0 Moderate Moderate to High
FS ≤ 1.0 High

1.5 > FS > 1.25 Moderate to High

1.25 > FS > 1.0 High High
FS ≤ 1.0 Very High

Figure 96 to Figure 101 show the landslide susceptibility map for Quezon City. Most areas are not
susceptible to landslides because they are flat. Landslides only impact particular barangays in Quezon City
that are on sloping unstable terrain. Areas in dark red and red are very high susceptibility and high
susceptibility, respectively. They are in the northeastern and eastern portion of Quezon City and have high
to very high susceptibility. Areas in orange are moderate to high susceptibility areas, green are moderate
susceptibility, and areas in yellow are low susceptibility to landslides. These maps can be used to guide the
barangays to analyze potential impacts of landslides and evaluating existing conditions of slope instability
that could pose a threat to emergency response.

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Figure 96. Landslide susceptibility map of District 1 (recalibrated MGB data at moderate and high susceptibility)

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Figure 97. Landslide susceptibility map of District 2 (recalibrated MGB data at moderate and high susceptibility)

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Figure 98. Landslide susceptibility map of District 3 (recalibrated MGB data at moderate and high susceptibility)

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Figure 99. Landslide susceptibility map of District 4 (recalibrated MGB data at moderate and high susceptibility)

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Figure 100. Landslide susceptibility map of District 5 (recalibrated MGB data at moderate and high susceptibility)

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Figure 101. Landslide susceptibility map of District 6 (recalibrated MGB data at moderate and high susceptibility)

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5.4. Landslide Risk Assessment

5.4.1. Critical Facilities Affected by Landslide Hazard
The following sections present the critical facilities with overlay on the landslide susceptibility data per
district. This indicates that there are a number of critical facilities such as evacuation centers, hospitals,
health centers, police stations, fire stations, barangay halls, and other facilities that will be affected by
possible landslides in Quezon City. The particular barangays where these facilities are located can also be
identified in the related maps.

5.4.2. Facilities for Health and Emergency

Generally, hospitals and health centers are the primary facilities for people needing medical attention in
times of emergency. Evacuation centers are pre-identified locations for different areas of Quezon city to
provide shelter and initial support to affected people during and after an emergency. Figure 102 to Figure
107 shows critical point facilities such as hospitals, health centers, evacuation centers, and multi-purpose
buildings with overlay of the landslide susceptibility map.

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Figure 102. Landslide susceptibility map with hospitals, health center, Figure 103. Landslide susceptibility map with hospitals, health center, evacuation
evacuation centers and multi-purpose halls for District 1 evacuation centers and multi-purpose halls for District 2

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Figure 104. Landslide susceptibility map with hospitals, health center, Figure 105. Landslide susceptibility map with hospitals, health center,
and multi-purpose halls for District 3 evacuation centers and multi-purpose halls for District 4

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Figure 106. Landslide susceptibility map with hospitals, health center, evacuation Figure 107. Landslide susceptibility map with hospitals, health center, evacuation
centers and multi-purpose halls for District 5 centers and multi-purpose halls for District 6

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5.4.3. Facilities for Safety and Security

Police, fire stations and barangay halls are critical in response and maintaining order during and after an
emergency. Identifying facilities that are in risk of landslides would be crucial to provide uninterrupted and
effective services. Figure 108 to Figure 113 show the location of police and fire stations, and barangay halls
with an overlay of landslide susceptible areas.

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Figure 108. Landslide susceptibility map with police and fire stations, Figure 109. Landslide susceptibility map with police and fire stations,
and barangay halls for District 1 and barangay halls for District 2

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Figure 110. Landslide susceptibility map with police and fire stations, Figure 111. Landslide susceptibility map with police and fire stations,
and barangay halls for District 3 and barangay halls for District 4

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Figure 112. Landslide susceptibility map with police and fire stations, Figure 113. Landslide susceptibility map with police and fire stations,
and barangay halls for District 5 and barangay halls for District 6

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5.5. Impact on Transportation Systems and Mobility

5.5.1. Road Network
One of the impacts of landslides to infrastructure is the possibility of impassable road segments due to
movement of the ground. Road networks at high to very high landslide susceptibility could be an indicator
of possible roadblock, limit in access and potential need for reconstruction to deliver services during and
after disaster. Table 66 shows the length of road segments within the high to very high landslide
susceptibility in the affected area barangays. It is worth noting that barangay Bagong Silangan will have
more than 13km of road impassable. Mobility will be severely impacted for several days if not weeks.
Similarly, barangay Pansol will have close to 9km of roads impassable making it very difficult to access.

Table 66. Length of road segments of barangays in Quezon City within high to very high landslide susceptibility

Barangay Length of Road on High to Very High Landslide Susceptibility (km)

Bagong Silangan 13.26

Pansol 8.95
Batasan Hills 2.59
Matandang Balara 2.02
Greater Lagro 0.39
Commonwealth 0.08
Loyola Heights 0.04

5.5.2. Population Affected by Landslide Hazard

Using an overlay of the recalibrated landslide susceptibility map and residential buildings, population on
different landslide susceptibility levels can be estimated. Figure 114 to Figure 119 present the percentage
of population for each barangay in Quezon City in moderate to very high susceptibility levels. To narrow
down the most susceptible barangays, Figure 120 to Figure 125 show percent population in high to very
high susceptibility.

Barangays with population on high to very high susceptibility are Payatas, Bagong Silangan, Pansol, Batasan
Hills, Commonwealth, Matandang Balara, Greater Lagro, Loyola Heights. Around 20-40% of the population
of barangay Payatas, Bagong Silangan and Pansol are located in high to very high susceptible areas.

In addition to the barangays mentioned above, the following barangays are in moderate to moderate to high
susceptibility: Pasong Tamo, Holy Spirit, Escopa 3, Fairview, Escopa 2, Escopa 4, Blue Ridge A, Sta. Cruz,
and Blue Ridge B.

The rest of Quezon City falls under no to low susceptibility based on the MGB data.

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Figure 114. Percent population per barangay in moderate to Figure 115. Percent population per barangay in moderate to
very high susceptibility to landslide for District 1 very high susceptibility to landslide for District 2

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Figure 116. Percent population per barangay in moderate to Figure 117. Percent population per barangay in moderate to
very high susceptibility to landslide for District 3 very high susceptibility to landslide for District 4

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Figure 118. Percent population per barangay in moderate to Figure 119. Percent population per barangay in moderate to
very high susceptibility to landslide for District 5 very high susceptibility to landslide for District 6

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Figure 120. Percent population per barangay in high to Figure 121. Percent population per barangay in high to
very high susceptibility to landslide for District 1 very high susceptibility to landslide for District 2

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Figure 122. Percent population per barangay in high to Figure 123. Percent population per barangay in high to
very high susceptibility to landslide for District 3 very high susceptibility to landslide for District 4

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Figure 124. Percent population per barangay in high Figure 125. Percent population per barangay in high to
to very high susceptibility to landslide for District 5 very high susceptibility to landslide for District 6

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Part 6:
Hotspot Barangays

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Part 6: Hotspot Barangays

6.1. Introduction: Hotspots and Indicators

6.1.1. What are hotspot barangays and related indicators?

Hotpot barangays are barangays that represent the highest potential vulnerability for one or multiple hazards.
The assessment of vulnerability is measured by an “Index”, which is calculated based on a combination of
relevant vulnerability indicators. To understand the relevance of hotspots, it is important to understand the
related indicators that are used to identify the hotspots.

Indicators are quantitative parameters intended to best represent the core characteristics of a system’s
performance (or lack thereof), which in this case is a measure of barangay vulnerability.
Combining these indicators analytically and applying relative weights will produce a single vulnerability index
that can be used to rank the barangays to determine the hotspot barangays. Identifying hotspot barangays
helps inform decision making in terms of disaster risk reduction investment, build consensus on prioritization
of action, and provide a way to measure progress over time. Indicators are also a powerful tool to raise
awareness and to advocate for investment in DRR.

Indicators’ based indices are widely used for consistent relative ranking of countries or any other process or
system to enable decision making and to measure progress. Among some of the most widely known
indicators are the World Poverty Index, the World Risk Index but also indices such as the Dow-Jones or
countries credit ratings. It is important to note that indices are only relevant to a relative ranking. An index by
itself is often a dimensionless quantity that has relevance relative to a ranking scale. For example, in the
World Poverty Index, the index itself is not objective. However, what is objective and coherent is the ranking
of countries relative to the index. Similarly, for the Dow-Jones the index of the day only takes relevance
when compared to the previous days. Thus, one has to only focus on the relative ranking to benefit from the
value of the indicators.

6.1.2. Defining the Barangay Vulnerability Index for Quezon City

In the development of the Quezon City Risk Profile and Atlas, four hazards were considered, namely:
Earthquakes, Floods, Landslides and Climate Change. As explained in Chapter 3, the impact of climate
change is incorporated in the assessment of the flood hazard and flood risk. Hence, the indicators selected
for the flood hazard, explicitly integrate the effects of climate change.

The index used to determine the hotspot barangays is termed as the Barangay Vulnerability Index (BVI). The
BVI was developed by EMI and is tailored to the particular geographical, physical and social considerations of
Quezon City. A selection of barangays with the highest BVIs are identified as hotspot barangays. A special
algorithm is used to perform sensitivity analysis to understand the variability of each indicator and its related
weight on the BVI values. This is done to ensure that the outcome in terms of determining the hotspot
barangays is coherent, consistent and reliable. The final determination shows that the BVI is a stable and
robust index for the determination of the hotspot barangays of Quezon City.

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Flood and earthquake hazards affect wide areas of Quezon City spanning a multitude, and in the case of the
earthquake hazard, all of the barangays. Each barangay within the city is impacted with varying levels of
physical and social severity. Thus, it is of interest to also develop the list of barangay hotspots that represent
the combined impact of both the flood and earthquake hazards.

The hotspot barangays for combined hazards can be determined by making the indicators dimensionless
quantities and developing a single BVI for the combined hazards. The combined hotspot barangays indicate
barangays where the impacts from multiple hazards cumulate to increase vulnerability. It must be noted that
a barangay can have a very high BVI for one hazard, but that is not sufficient for that barangay to be
represented in the combined hazard hotspot. The exposures and vulnerabilities from multiple hazards must
intersect and compound each other to represent a combined higher vulnerability, i.e., a large combined BVI
number.

This observation has implications on the consideration of landslide hazard. The landslide hazard concerns
only a limited number of barangays that do not intersect with the flood and earthquake hazards in a
significant way. Thus, in Quezon City the landslide hazard does not impact the combined BVIs for flood and
earthquake and can be considered separately. For these last two hazards, several barangays with high impact
for both flood and earthquake hazards intersect and compound to define the combined hotspot barangays.

6.1.3. Selection of earthquake and flood indicators to identify hotspot barangays

Seven indicators are selected for each of the flood hazard and the earthquake hazard and combined with
appropriate weights to develop the Barangay Vulnerability Index (BVI) for each hazard. The selected
indicators that comprise the BVI represent three separate characteristics of vulnerability to the hazards of
flood and earthquake. They are defined by the following hazard and risk quantities:

The selected indicators that comprise the BVI represent three separate characteristics of vulnerability to the
hazards of flood and earthquake, namely they represent the following risk quantities:

a. The expected severity of the hazard of each barangay for flood and earthquake
b. Impact on population either in terms of loss of life, displaced populations and/or disease
c. Aggravating land use constraints such as population density or road congestion

This is represented schematically in Figure 126.

Figure 126.. Hazard and Risk Quantities Reflecting the Indicators that are Incorporated in the BVI.

The severity of hazard drives the impact and the evidence of physical vulnerability (e.g., the greater the
severity of the hazard, the more damage is sustained by buildings, critical point facilities and infrastructure).

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This is valid for both the flood hazard and the earthquake hazard. Thus, the indicator reflecting the severity
of hazard of each barangay is essential to the definition of the BVI.

Impact on population as measured by loss of life and/or displaced populations and/or hazard-induced
diseases is a good measure of social vulnerability that implicitly incorporates vulnerable populations since the
latter are likely to be more affected by the hazards. The demographics of the population is taken from
Quezon City’s latest demographic data (2022).

Land use constraints provide aggravating factors related to both physical and social vulnerability and to
fragilities associated with coping capacity and recovery. These indicators are also strongly correlated with
vulnerable populations and lack of social inclusion. For example, low-income communities tend to live in the
most congested area where mobility and access to services and facilities are the most difficult.

By aggregating the seven indicators representing these quantities, the BVI takes a comprehensive view to the
representation of both social and physical vulnerability for each hazard. The combined flood and earthquake
index considers all 14 indicators. In the following section, each of the indicators for flood and earthquake
hazards is provided and explained.

6.2. Flood and Earthquake Indicators

The seven indicators used in the calculation of the BVI and determining the flood hotspot barangays are
presented in Table 67 below.

Table 67. Indicators Used in the Calculations of the Flood BVI

ID Flood Indicator Description
1 Flooded Area Reflects the ranking in the flood hazard as measured by the percent
Susceptibility area of the barangay that is flooded with flood depth of 0.5m and
greater. The reference flood event used for this indicator is the 2021
MGM Flood Susceptibility Map.
2 Flooded Area ( Reflects the ranking in the flood hazard as measured by the percent
Climate area of the barangay that is flooded with flood depth of 0.5m and
Adjusted) greater. The reference flood event used for this indicator is the RCP
8.5 100-year Rain Return Flood Scenario as established by the
Quezon City Drainage Master Plan project.
3 Risk of Infection Indicates the risk to life during the flood. It made use of flood depth and
to Gastroenteritis other criteria such as mode of infection, duration of flood, depth of flood,
population density, ingestion of contaminated water, and number of fecal
coliforms per 100 ml. The reference flood event used for this indicator is
the RCP 8.5 100-year Rain Return Flood Scenario as established by the
Quezon City Drainage Master Plan project.
4 Flooded Road Indicates ease or difficulty of moving from node to node of connected
Intersections road links. Flood depth is assigned to each node. A cluster of
contiguous flooded nodes can be used to define intensity of flood
along network segments. It also reveals passable or non-passable links
for different vehicle types. Roads are expected to be at lower

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elevations than building ground elevations. The reference flood event

used for this indicator is the RCP 8.5 100-year Rain Return Flood
Scenario as established by the Quezon City Drainage Master Plan
project.
5 Flooded One or Using max flood depth found by intersecting the building footprint
Two-story area with the flood data, the level of water depth compared to the
buildings height of the building provides a proxy for the threat to life for people
trapped in the buildings as well as physical damage to contents and
structures. The threat is predominant in one and two-story buildings.
The reference flood event used for this indicator is the RCP 8.5 100-
year Rain Return Flood Scenario as established by the Quezon City
Drainage Master Plan project.
6 Displaced This indicator represents the percent of the population compared to
Populations the total population of the barangay that is expected to be displaced
by the flood. The reference flood event used for this indicator is the
RCP 8.5 100-year Rain Return Flood Scenario as established by the
Quezon City Drainage Master Plan project.
7 Number of This indicator represents the number of evacuation centers and
barangay official barangay facilities that are made inoperable because they are
Facilities and flooded, thus impairing response, relief and recovery. The reference
Evacuation flood event used for this indicator is the RCP 8.5 100-year Rain
Centers Made Return Flood Scenario as established by the Quezon City Drainage
Inoperable by Master Plan project.
Flood

The seven indicators used in the calculation of the BVI and determining the earthquake hotspot barangays are
presented in Table 68 below.

Table 68. Indicators Used in the Calculations of the Earthquake BVI.

Earthquake Indicator Description
Earthquake Intensity This indicator represents the severity of the earthquake shaking for
each barangay as measured by the value of intensity (in MMI) from
the M7.2 earthquake on the West Valley Fault.
Liquefaction This indicator measures the percent area for different liquefaction
Susceptibility susceptibility levels under M7.2 earthquake for each barangay in
Quezon City.
Injuries that Need This indicator measures the percent of people who would require
Hospitalization medical attention due to injuries sustained from the M7.2 earthquake
on the West Valley Fault compared to the total population of the
barangay. The larger the indicator, the more strain the health system
will sustain.
Loss of Life This indicator measures the percent of expected fatalities from a M7.2
West Valley Fault earthquake scenario compared to the total
population of the barangay Large fatality ratios will pose significant
social disturbance and socio-economic issues. Experience has also

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shown that mortality is higher among women and children in

earthquakes and other disasters.
Displaced Population Measures the potential ratio of population that could be displaced and
would need shelter as percent of the total population of the barangay.
Populations are displaced because the buildings where they reside
have either collapsed or sustained extensive damage under the M7.2
earthquake scenario. Experience has also shown that women,
children and PWDs suffer the blunt of the impact from displacement
and need special arrangements.
Lack of Open Spaces This indicator is a proxy measure for the difficulty in the organization
of the response and relief operations. It also reflects potential
aggravation of the social impact of the disaster. It is represented by
the average open space area per 1000 people in the barangay. This
quantity is calculated for each barangay.
Road Density and Indicates accessibility during and after an earthquake to and from
Distance to Hospitals essential facilities such as hospitals and fire stations. Road density
and Fire Stations assumed to be proportional to possible blockage due to debris and
limited width of the road. Proximity to hospitals and fire stations for
each building indicates the relative length of travel and increase in
potential blockage along the way. This indicator measures the
difficulty for response and relief operations after the M7.2 for each
barangay in terms of access and mobility. It could impair search and
rescue, access of ambulances and other emergency vehicles and
access to hospitals and fire stations. It impacts relief operations and
long term recovery. This quantity is calculated for each barangay.

6.3. The Barangay Vulnerability Index

6.3.1 Analytical Approach
All barangays are ranked relative to each indicator, the ranking being 1 to 142 where rank 1 is the barangay
with the highest value of the indicator (for example highest earthquake intensity) and rank 142 is the lowest
value of the indicator. Weights are assigned to each indicator. The relative ranking of the weights is
established by experience and by undertaking sensitivity analyses.
Using the ranking, the Barangay Vulnerability Index (BVI) is calculated by combining a term that represents
the frequency of each indicator and a second term that represents the severity of each indicator. In essence,
the BVI represents how often in time a barangay is among the worse impacted barangays and, if it is among
the worse, how high is its value compared to the other barangays. If a barangay is highly ranked several times,
it means it is highly susceptible to intense values of hazard. In addition, if the barangay impact (in terms of
seven the physical and social indicators) is among the worse, then both the social and physical vulnerability of
that barangay is among the worse compared to other barangays. In short, the BVI reflects the severity of the
impact of the hazard on each barangay’s infrastructure and population and how the response, relief and
recovery will be aggravated by land use constraints. Implicitly, the BVI also reflects long-term socio-

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economic impact, particularly on the most vulnerable populations, women and children with indicators such as
displaced populations, fatalities and risks of infections.

From an analytical standpoint, the BVI provides a fairly spread-out prediction by which the barangays can
easily be ranked. In fact, the larger the standard deviation, the higher is the predictivity of the indicator. The
BVI is an objective index since all indicators can be consistently and accurately calculated from the hazard,
risk or exposure data. It is stable as the calculation will always result in a discrete number by which the rank of
that barangay can be obtained compared to the other barangays.

6.3.2. Criteria for determining the hotspot barangays

The hotspot barangays are identified based on statistical criteria of the BVI values of the concerned
barangays. The BVIs are first normalized to 100 and then the barangays are ranked according to the
normalized BVI value. The mean and standard deviation are calculated and a distribution is fit on the data to
find the percentile of each value relative to the data. The hotspot barangays are identified on the basis of the
criteria indicated in Table 69.

Table 69. Criteria for Hotspot Barangays in Three Tiers Based on the BVI Percentile Distribution.
Barangay Vulnerability Index (BVI)
Tier 1: Very High BVI These barangays are in the top 90th percentile
These barangays are on the Top First Tier of the BVIs for all barangays.
Hotspot. The vulnerability is very high.
Tier 2: High BVI These barangays are in the top 80th to 90th
These barangays are on the Second Tier Hotspot. percentile of the BVIs for all barangays.
The vulnerability is high but not as high as in Tier
1.
Tier 3: Moderate BVI These barangays are from the 50th to the 80th
These barangays are still part of the hotspot percentile of all the BVIs.
barangays but represent a moderate to high
vulnerability.

The above criteria can vary slightly depending on the statistics for each hazard and the variability in the risk
parameters between barangays as calculated in the climate and disaster risk assessment (CDRA). Note that
the hotspot barangays for earthquake, flood and landslide are different since they are linked to different
hazards. Barangays falling lower than 50th percentile are not considered to be hotspot barangays, which
means that relative to the other barangays, they have a lower vulnerability compared to the first three tiers.

As explained earlier, the combined hotspot barangays (e.g., for both earthquake and flood) reflect both
hazards, meaning that they have high vulnerability for both earthquake hazard and flood hazard.

6.4. Hotspot Barangays in Quezon City

Using the criteria in Table 69, the barangays are grouped into Three (3) Tiers for the earthquake hazard, flood
hazard and flood and earthquake combined. The barangays in Tier 1 represent the highest vulnerability as
measured by the BVI. Tier 2 lists the barangays that follow Tier 1 and can be considered as high vulnerability.
Tier 3 follows Tier 2 and these barangays are considered to be of moderate vulnerability compared to the

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previous two tiers. The BVI value (normalized to 100) is provided for each barangay to have a better
appreciation of the ranking between the barangays.

A few important points should be noted:

1. Barangays that are not listed do not equate to no or low vulnerability. Recall that the BVI is just an
index that enables a rational relative ranking. It simply indicates that the barangays that are not listed
are less vulnerable than the ones that are listed as hotspot barangays.
2. The BVI indicators are normalized relative to the population of each barangay. Thus, they emphasize
the density of loss rather than the absolute value of loss. Consequently, many of the hotspot
barangays are barangays with low geographical area and large density of population.
3. Had the BVI been calculated on the absolute values, the output in terms of the hotspot barangays
would have been different. It would have emphasized the barangays with the largest populations.

The results for each hazard and the combined hazard are as provided and explained in the following
paragraphs.

6.4.1. Earthquake Hotspot Barangays

The earthquake hotspot barangays are presented in Table 70 and graphically shown in Figure 127. Out of the
24 barangays that are considered as hotspot barangays, 20 are in District 3, two (2) are in District 2 and two
(2) are in District 4.
• In Tier 1, four (4) out of the six (6) barangays are in District 3 whereas two (2) are in District 2. The
latter two barangays are large size barangays. All the barangays are very close to or are transected by
the West Valley Fault, have severe earthquake intensities (MMI>9.6) and rank high in terms of lack of
open space, density of injuries, fatalities and displaced population compared to their total
populations.

• Barangay Libis in Tier 2 is expected to have the highest shaking severity with MMI close to 10 and
ranked third in density of displaced population, but it is in Tier 2 because it has more open space and
lower density of injuries and fatalities than the barangays in Tier 1. Most of the barangays in Tier 2
are very constrained by lack of open space, severely impairing their mobility and access to critical
point facilities such as hospitals. Health care centers and shelters.

• Overall, the lack of open space and lack of access to critical point facilities are determinant factors in
sorting the ranking of the hotspots. This is the case, for example, in Teachers Village East, which
ranks 40th in terms of earthquake shaking severity, but it is constrained by lack of open space and
mobility, making it part of Tier 3 of the hotspot barangays. Its ranking moved from 40 on the basis of
intensity to 24 on the basis of all seven indicators.

• These findings are consistent with observations and experiences from urban earthquakes. Lack of
mobility and open space can be major impediments to organizing the response and relief operations.
They can cause dire situations for reaching the affected communities, for communication, for
providing search and rescue or for dealing with injured individuals and providing for the needs of the
survivors. These parameters in turn, delay the recovery process.

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Table 70. Earthquake Hotspot Barangays as Established by the 3-tier Barangay Vulnerability Index (BVI).
Earthquake Hotspot Barangays
Tier Rank Barangay BVI District
1 Blue Ridge B 100 3
2 Batasan Hills 92 2
Tier 1 3 Ugong Norte 90 3
Very High
Vulnerability 4 Bagong Silangan 89 2
5 Escopa 4 88 3
6 Blue Ridge A 88 3
7 Libis 85 3

Tier 2 8 Villa Maria Clara 78 3

High 9 White Plains 78 3
Vulnerability
10 Amihan 77 3
11 Escopa 3 77 3

12 Bagumbayan 72 3

13 Escopa 2 71 3
14 Teachers Village East 71 4
15 Quirino 2-B 70 3
16 Escopa 1 70 3
17 Masagana 68 3
Tier 3
Moderate 18 Pansol 68 3
Vulnerability 29 Loyola Heights 67 3
20 Quirino 2-C 67 3
21 Marilag 63 3
22 Milagrosa 63 3
23 Claro (Quirino 3-B) 60 3
24 Teachers Village West 60 4

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Figure 127. Earthquake Hotspot Barangays in Three Tiers.

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6.4.2. Flood Hotspot Barangays

The flood hotspot barangays are presented in Table 71 and graphically shown in Figure 128.
• Out of the 21 barangays that are considered as hotspot barangays, nine (9) are in District 1, five (5)
are in District 3 and five (5) in District 4, one (1) is in District 5 and one (1) in District 6.

• In Tier 1, six (6) out of the nine (9) barangays are in District 1, whereas one (1) is in each of District 5,
District 4, and District 3. The joining of the San Francisco River and the San Juan River drives the
vulnerability of the barangays in District 1. Barangay Capri in District 5 is impacted by the Novaliches
River.

• The top barangays in Tier 1 typically rank among the top five in each of the seven indicators
including: risk of infections, flooded roads, flooded buildings, displaced populations and difficulty of
access to critical point facilities.

• The barangays in Tier 2 also exhibit BVIs in the mid and upper 80s, showing significant vulnerability.

• The flood hotspot barangay ranking is highly influenced by the RCP 8.5 100-year Return Period Flood
depths. Thus, the impact of climate change is incorporated in the assessment of the flood hotspot.
The above consideration takes a longer time perspective in terms of how the flood hazard and flood
vulnerability will impact Quezon City.

• With the significant experience that Quezon City has had with dealing with flood hazard and flood
risk, the indication of the flood hotspot barangays can further support that experience by providing a
more holistic approach that not only integrates social and physical vulnerabilities but also provides an
assessment of the impact of climate change.

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Table 71. Flood Hotspot Barangays as Established by the 3-tier Barangay Vulnerability Index (BVI) .
Flood Hotspot Barangays
Tier Rank Barangay BVI District
1 Katipunan 100 1
2 Capri 98 5
3 Talayan 97 1
Tier 1 4 Masambong 97 1
Very High 5 Mariblo 94 1
Vulnerability 6 Sto. Domingo (Matalahib) 94 1
7 Tatalon 91 4
8 St. Peter 90 1
9 West Kamias 89 3
Tier 2 10 Doña Imelda 87 4
High 11 Sienna 84 1
Vulnerability 12 Damayang Lagi 83 4
13 Claro (Quirino 3-B) 78 3
14 Maharlika 76 1
15 San Antonio 73 1
Tier 3 16 Santol 71 4
Moderate 17 Bagumbayan 71 3
Vulnerability 18 East Kamias 68 3
19 Apolonio Samson 68 6
20 San Vicente 64 4
21 Quirino 2-B 63 3

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Figure 128. Flood Hotspot Barangays in Three Tiers.

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6.4.3. Landslide Hotspot Barangays

The landslide hazard concerned only a limited number of barangays. In fact, only eight (8) barangays are
indicated as having a Very High or High Susceptibility to Landslides (See Chapter 3). Undertaking a BVI
calculation for such a limited number of barangays is not analytically viable. Thus, the classification in tiers is
undertaken relative to only two indicators: 1) the susceptibility to landslides, and 2) the percent of the
population exposed to landslides compared to the total population of the barangay. The eight hotspot
barangays for landslides are classified into two tiers as indicated in Table 72. The barangay hotspots for
landslides are shown in Figure 129.

Of the eight hotspot barangays, four are in District 2 and three are in District 3. Of the two Tier 1 barangays,
two are in District 2 and one is in District 3.

Note that barangays Bagong Silangan, Pansol, Loyola Height and Barangay Batasan Hills overlap with the
earthquake hotspot barangays. This increases the potential for earthquake-induced landslides for these four
barangays.

Table 72. Landslide Hotspot Barangays in Two Tiers.

Landslide
Tier Rank Barangay District
Tier 1 1 Payatas 2
Very High 2 Pansol 3
Vulnerability 3 Bagong Silangan 2
4 Batasan Hills 2
5 Matandang Balara 3
Tier 2
6 Greater Lagro 5
High Vulnerability
7 Commonwealth 2
8 Loyola Heights 3

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Figure 129. Landslide Hotspot Barangays.

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6.4.4. Combined Hotspot Barangays for Earthquake and Flood Hazards

As explained earlier, the combined hotspot barangays indicate barangays where the impacts from multiple
hazards cumulate to increase vulnerability. The exposures and vulnerabilities from multiple hazards must
intersect and cumulate the value of the BVI to represent a combined high vulnerability. With this
consideration, 14 barangays interact between the earthquake hazard and the flood hazard in a combined
increased vulnerability, resulting in the 14 highest combined BVIs. The results are shown in Table 73 and
graphically in Figure 130.

• All the 14 hotspot barangays for Flood and Earthquake are in District 3 except for one (St. Peter),
which is in District 1. The reason for this concentration is that both physical and social vulnerabilities
of floods and earthquakes accumulate and compound each other) in District 3 more so than any other
district or location in Quezon City.
• Other barangays where the flood impact is high resulting in identification of several flood hotspot
barangays such as District 1 and District 4 have lower impact from earthquake hazard and thus do
not make it in the combined hotspot barangays. The same goes for the barangays where the
earthquake BVIs are very high but the flood BVIs are low.
• Consequently, none of the Tier 1 or Tier 2 hotspot barangays for floods are included in the Tier 1 or
Tier 2 of the Combined Hotspot barangays because their earthquake BVIs are low. Similarly, none of
the Tier 1 hotspot barangays for earthquakes are included in the Tier 1 or Tier 2 of the Combined
Hotspot barangays because their flood BVIs are low.
• Among the Tier 2 earthquake Hotspot barangays, Barangay Libis and Barangay Villa Maria Clara are
included in the Tier 1 and Tier 2 of the Combined Hotspot Barangays, respectively.
• The Combined Hotspot Barangays for Flood and Earthquake should be seen as target barangays
where both earthquake risk and flood risk accumulate. Thus, any investment for risk reduction
would have an impact on reducing risks from both hazards.

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Table 73. Hotspot Barangays for Combined Flood and Earthquake Hazards.
Combined Flood and Earthquake

Tier Rank Barangay BVI District

1 Bagumbayan 100 3

Tier 1 2 Claro (Quirino 3-B) 98 3

Very High 3 St. Peter 97 1
Vulnerability
4 Quirino 2-B 93 3
5 Libis 92 3
6 Masagana 86 3
Tier 2
High 7 Quirino 2-C 81 3
Vulnerability 8 East Kamias 81 3

9 Villa Maria Clara 80 3

10 Silangan 80 3
Tier 3 11 Quirino 3-A 61 3
Moderate
12 Bagumbuhay 60 3
Vulnerability
13 Mangga 57 3
14 Quirino 2-A 55 3

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Figure 130. Combined Flood and Earthquake Hotspot Barangays.

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6.5. Recommendations on the Use of Barangay Hotspot

As explained throughout this chapter, hotspot barangays are barangays where the combined social and
vulnerabilities are high as represented by the indicators that define the BVI. This is very relevant to establish
priorities for investments in disaster risk reduction as well as in efforts to raise awareness and to secure
engagement of the relevant stakeholders. Reasonably, there is never an endless amount of resources
available. Thus, priorities must be established in terms of where to push greater amounts of resources. The
hotspot barangays are a reliable tool for making such decisions. This does not translate and should not be
interpreted as barangays that are not hotspot barangays are not in need of investment. That consideration is
erroneous. Disaster risk reduction is much more effective when undertaken comprehensively and holistically.
The social, environmental and physical conditions of each and every barangay should be considered carefully
in making such decisions. However, the identification of hotspot barangays can facilitate policy and decision
making at the level of the city government.

The hotspot barangays linked to a single hazard shown in tables 70, 71 and 72 are relevant to each barangay
and could be an additional tool for consideration in the development of the barangay DRRM plans, in the
development of contingency plans as well as the development of simulation exercises for response, recovery
and public service continuity planning.

The hotspot barangays for combined hazards (i.e., flood plus earthquake) are appropriate for multi-hazard
approach to risk management. In this case, the 14 barangays listed in Table 73 should be considered as
primary targets for an optimum return on multi-hazard risk reduction investment, starting with the five
barangays in Tier 1.

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Part 7: Towards a Resilient

Quezon City

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Part 7: Towards a Resilient Quezon City

7.1. A Model City for Urban Resilience

Quezon City has made great strides in achieving its vision of becoming a model for resilient urban
development in the country by following transparent, responsive and proactive governance principles,
adopting risk-informed policies, and devoting significant resources to disaster risk reduction. This is in line
with its dynamic and globally competitive economy that is vital to the city’s ability to provide world-class
services and infrastructure. This progress is translating into communities of empowered, disciplined and
resilient citizens.

Nonetheless, natural hazards continue to represent a significant threat to Quezon City’s development and the
well-being of its citizens due to inherent social, physical and environmental vulnerabilities. This requires that
the city continuously and actively works to improve its capacities, increase its competencies and acquire the
latest scientific knowledge and tools to manage the risks and reduce its vulnerabilities. Quezon City’s enabling
policies provide for higher awareness and shared responsibilities from everyone.

7.2. Utilizing Science to Manage and Reduce Risk

The Updating of the Climate and Disaster Risk Assessment of Quezon City project involved the assessment
of the climate, earthquake, flood and landslide hazards and risks to the city, identifying hotspot barangays,
and the development of a risk profile and atlas for the city. It also involves the creation of a roadmap for the
management of complex emergencies, through a simulation exercise based on a realistic but complex disaster
scenario. The project relies on the latest scientific data to develop a comprehensive understanding of the risks
caused by these hazards, using an updated 2022 building-level exposure database and a high-resolution hazard
and risk analysis.

The findings and outputs of the project have been designed not only inform the city’s disaster risk reduction
and management agenda but also provide essential data to other core planning processes such as the
development of local disaster risk management and reduction plan, various contingency plans, the public
service continuity plan (PSCP), the comprehensive land use plan (CLUP) and others plans and policies. The high
resolution and accuracy of data and analysis enables the city to complete reliable science-based plans at the
city level, barangay level and community level. This is a major accomplishment, which in EMI’s opinion has
not been reached by any other city in the Philippines.

7.3. Forward Looking Plans to Guide Policy and Investments

Other plans of the QCG within the last five years that are geared towards guiding planning, policy and
investment to secure livelihoods, improve quality of life and build resilience of Quezon City residents are listed
in Figure 131.

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These plans and manuals represent the road map for policy, investment, and action to achieve a sustainable and
resilient future and in bringing the city in full compliance with national government regulations. These
elaborate plans together with the high resolution CDRA outputs, and risk communication guidebooks such as
the RPA, the city government and the communities within Quezon City will be better prepared for disaster
events through improved local-level planning and more effective preparedness. In turn, this will make them
more capable of safeguarding their human, physical and economic assets from hazard impacts.

The effective development and implementation of these plans require not only a significant investment in
human and financial resources, but most importantly the appropriate policies that engage and enable
communities, institutions and city’s partners to participate, contribute and take ownership. The challenges of
managing disaster risks require orientation and outreach initiatives to various communities, regular trainings
and capacity-building sessions, simulation exercises, and knowledge management activities for climate change
adaptation and mitigation (CCA/M), disaster risk reduction (DRR) and disaster risk reduction and management
(DRRM). It also requires building competencies at the barangay level for the development and implementation
of comprehensive barangay DRRM and CCA/M plans.

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Figure 131 Quezon City Government planning instruments from 2017-2022

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7.4. Roadmap to Urban Resilience

The QCG’s efforts to enhance its DRRM and CCA/M systems and capabilities over the years have been
rewarded by numerous awards and recognitions. Some of the major awards received by the city in the last five
years (2017-2022) are shown in Figure 132. Such recognition is the proof for QCG’s commitment to good
governance, safety and resilience. In particular, Quezon City received the award for having the Top Disaster
and Risk Reduction and Management Council in the Philippines - Gawad KALASAG Award four times,
including the one for 2019.

Nonetheless, climate change adaptation and mitigation and disaster risk reduction are continuous
endeavors requiring consistent policies, sustained efforts and significant investments. Each disaster event
is a learning experience, and each contribution towards the ultimate goal to reduce loss of life and
property and to protect the environment is an additional building-block to realize a resilient city. There are
certainly constant challenges to overcome along the way.

Among the challenges faced by complex urban agglomerations such as Quezon City is understanding and
responding to the special needs of vulnerable populations, mainly the elderly, PWDs, women, children, the
youth and the very poor. These segments of the population suffer the most during disasters and require
most attention and deliberate policies to support them during emergencies and reduce their exposures to
hazards. Reducing the vulnerability of the vulnerable populations to hazards and providing them with safe
living conditions and livelihood will remain a formidable challenge and a long-term effort.

Another formidable challenge relates to preparing and managing for the “Big One”. There is little on-the-
ground experience from low frequency but high severity events such as earthquakes. Part 4 of this report
indicates that large earthquakes such the M7.2 scenario could have devastating impacts on the city.
Preparing for earthquake events requires a novel approach that may be different from one directed to the
management of floods or other more frequent hazards. Earthquakes will cause widespread damage and
will make mobility and access extremely difficult for days, if not weeks after the event. Critical utilities and
lifelines may not be available for a prolonged period. Thus, preparedness and response planning for
earthquake events call for a more decentralized approach that will enable localized decision-making, and
mobilization and assignment of resources. This new approach will rely on barangay officials and community
leaders to have a thorough understanding of their hazard, vulnerability and risk parameters, and to reflect
these parameters adequately into their disaster risk reduction and management plans. It may also require
establishing and evaluating a ‘sheltering-in-place” approach, which is the current trend in earthquake
preparedness in other areas of high earthquake risk, such as in California. Quezon City has a robust capacity
at the city level. The vision for the future will require augmenting that capacity at the barangay level and the
community level to respond to more complex emergencies such as a major earthquake and supporting the
barangays in developing effective, participatory and science-based DRRM plans.

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Figure 132 Timeline of Quezon City awards and recognitions from 2017-2022

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Despite these challenges, guided by the 14-Point Agenda (Figure 133), the future of Quezon City remains on a
positive trajectory to achieve a resilient and sustainable economic and social development.

QUEZON CITY’S 14-POINT

AGENDA
Deliver responsive, efficient and cost-effective social services
Build more homes
Provide better health care
Ensure high-quality education
Empower citizens of every gender and social class
Build a safer and more resilient city
Make Quezon City the preferred destination for businesses
Create new jobs across more businesses
Develop growth hubs
Build a livable, green and sustainable city
Build essential infrastructure
Be a model of good governance
Professionalize and strengthen the Quezon City workforce
Listen to our citizens and understand what they need

Source: QC Economic Development and Investment Plan

2022-2025

Figure 133 Quezon City’s 14-Point agenda

The QCG’s focus on safeguarding development gains by effectively reducing and managing disaster risk,
demonstrates its commitment to engage its own resources and to pro-actively seek the collaboration of the
relevant stakeholders and community leaders in the long process of resilience building. The advancements
and investments of the city for disaster risk reduction, particularly in the last five years, and its constant push
to reach and implement sound international standards of practice, have built strong foundations for the
achievement of its vision to become an exemplar of good governance, with a competitive and inclusive
economy, an ecologically balanced environment, resilient and sustainable communities and institutions.

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