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Mapping and Characterization of Imus River Watershed Using Geographic

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Technical Report · April 2022

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 SUBPROJECT 1:

MAPPING AND
CHARACTERIZATION OF IMUS
RIVER WATERSHED USING
GEOGRAPHIC INFORMATION
SYSTEM AND REMOTE SENSING
TECHNOLOGY

Sedigo, N.A., Creencia, G.B.A., Dizon, J.C.R., and Mojica, D.Z.P.

Cavite State University (CvSU)

Editor: Thomas Bell

Formatter: John Castillo
Partnerships in Environmental
Management for the Seas of
East Asia (PEMSEA

1
Abstract
River systems have been identified as major pathways and transporters of wastes,
including plastics, that ultimately end up in the oceans. The Imus River Watershed
(IRW) is located in the Philippine Province of Cavite, one of the provinces in the
CALABARZON Region of southern Luzon. This study delineated and mapped the
physical boundaries of the Imus River watershed and determined the topographic
features, stream characteristics, geomorphology, political subdivisions, barangay
communities, population distribution, land use and land cover, and hydro-climatic
characteristics of the watershed. Both primary and secondary data sources were
used in making comprehensive land use maps, population maps, and hydroclimatic
data analyses.

The boundary of the Imus River Watershed was initially established through an
unsupervised delineation process using a digital elevation model of Cavite with a 5-
meter resolution in ArcGIS. Sangley Point Synoptic Station in Cavite City and the
CvSU-PAGASA Agrometeorological Station in Indang were used to define the general
hydroclimatic condition of IRW due to their close proximity to the watershed. The
total drainage area of IRW is 11,259.80 hectares, covering portions of Tagaytay City,
Amadeo, Silang, Dasmariñas, Imus City, Bacoor City and Kawit. Elevation within the
watershed ranges from 0 to 655 meters above sea level. The lowland area covers
parts of Kawit, Imus City, and Bacoor City; a central hilly area covers parts of Imus
City, Bacoor City, and the majority of communities in Dasmariñas and Silang. The
upland area covers parts of Silang, Amadeo, and Tagaytay City. There were 56
perennial streams identified with a total length of 186.15 km and 36 river segments.
The Imus river system is a combination of headwaters and medium-sized streams.
The sub-watersheds, labeled A, B, and C, have drainage densities of 1.15 km/km2,
1.95 km/km2, and 1.41 km/km2, respectively. The sub-watersheds A and C have
stream frequencies of 0.20/km2 and 0.25/km2 while sub-watershed B has a stream
frequency of 0.39/km2. In alphabetical order, these sub-watersheds have bifurcation
ratios of 5, 3.31, and 2.5, elongation ratios of 0.33, 0.26, and 0.43, and circulatory
ratios of 0.18, 0.11, and 0.26.

A total of 222 barangay communities are located within the boundaries of the
watershed with a total population of 1,351,057 in 2015. 90.67% of the province is
classified as alienable and disposable land, while the remaining forest land
represents only 9.33%. Alienable and disposable lands are further classified as
production land (55.24%) and built-up areas (44.76%). The Sangley Point Synoptic
Station has a normal mean temperature of 28.53°C while the CvSU-PAGASA Agromet
Station has a normal mean temperature of 26.20°C. The average total annual rainfall
recorded at Sangley Point Synoptic station and CvSU Agromet Station were 2,265.69
mm and 2,483.05 mm, respectively. The average flow during wet season was
1,601.84 liters per second, while the average flow during dry season was 1,337.42
liters per second.

2
Acronyms/Abbreviations

ASTI Advanced Science and Technology Institute

CALABARZON Region Cavite, Laguna, Batangas, Rizal and Quezon Region
CLUP Comprehensive Land Use Plan
CvSU Cavite State University
DENR Department of Environment and Natural Resources
DOST Department of Science and Technology
GIS Geographic Information System
IRW Imus River Watershed
LGU Local Government Unit
LULC Land Use, Land Cover
MSL Mean Sea Level
NAMRIA National Mapping and Resource Information Authority
NIVA Norwegian Institute for Water Research
PAGASA Philippine Atmospheric, Geophysical, Astronomical
Services Administration
PEMSEA Partnerships in Environmental Management for Seas of
East Asia
POPCEN Population Census
PPDO Provincial Planning and Development Office
RBCO River Basin Control Office
RS Remote Sensing

3
Contents

Abstract 2

Acronyms/Abbreviations 3

List of Tables 6

List of Figures 7

Glossary of Terms 10

Executive Summary 12

Introduction

Objectives of the Study 17

Methodology

Study Site 18

Data Gathering 18

Delineation and Topographic Characterization of Imus River 19

Watershed

Watershed Geomorphology 19

Mapping of Barangay’s and Population Distribution 21

Mapping of the Land Use/Land Cover (LULC) of Imus River 21

Watershed

Hydroclimatic Characterization of Imus River Watershed 21

Results and Discussion

Delineation and Mapping of the Physical Boundaries of Imus 24

River Watershed

Determination of the Topographic Features of Imus River 24

Watershed

4
 Geomorphology of Imus River Watershed 29

Political Subdivisions and Barangay Communities within the Imus 35

River Watershed

Population Distribution within Imus River Watershed 44

General Land Cover, Vegetation and Comprehensive Land Uses 47

of Imus River Watershed

Hydroclimatic Conditions in Imus River Watershed 58

Conclusion 77

References 79

Annex 82

5
List of Tables

1 Municipalities and cities located within Imus River Watershed 24

2 Stream ordering of each sub-watershed of Imus River 29

Watershed

3 List of barangay communities within the Imus River Watershed 35

4 Land Classification of Imus River Watershed 47

5 The correlation coefficient of the monthly readings between 66

Sangely Point Station and CvSU Agrometeorological Station

6 Streamflow at Daang Hari Bridge outlet during different seasons 76

6
List of Figures

1 Cavite (green) within the CALABARZON region 15

2 The six major river watersheds in Cavite. The Imus River 16

Watershed (IRW) 60is shown in purple

3 Cross-sectional area of the outlet at Daang Hari Bridge 22

4 Developed rating curve of the outlet at Daang Hari Bridge 23

5 Cities and municipalities partially covered by the Imus River 25

Watershed

6 Topographic contours of the Imus River Watershed 26

7 Division of the Imus River Watershed by elevation 27

8 Slope of land within the Imus River Watershed 28

9 The river network of Imus River Watershed overlaid onto local 32

government units (cities and municipalities)

10 The highest and lowest points within the Imus River Watershed 33

11 Sub-watersheds of the Imus River Watershed 34

12 Barangay communities of Tagaytay City overlaid against the 37

Imus River Watershed

13 Barangay communities of Amadeo overlaid against the Imus 38

River Watershed

14 Barangay communities of Silang overlaid against the Imus River 39

Watershed

15 Barangay communities of Dasmariñas City overlaid against the 40

Imus River Watershed

16 Barangay communities of Imus City overlaid against the Imus 41

River Watershed

17 Barangay communities of Bacoor City overlaid against the Imus 42

River Watershed

7
18 Barangay communities of Kawit overlaid against the Imus River 43
Watershed

19 Map showing the population of the barangay communities 45

within the Imus River Watershed

20 Map showing the population density of barangay communities 46

within Imus River Watershed

21 Land cover of the Imus River Watershed 49

22 Normalized difference vegetation index of the Imus River 50

Watershed

23 Land use within Tagaytay City 51

24 Land use within Amadeo 52

25 Land use within Silang 53

26 Land use within Dasmariñas City 54

27 Land use within Imus City 55

28 Land use within Bacoor City 56

29 Land use within Kawit 57

30 Sangley Point Synoptic Station (blue) and CvSU 59

Agrometeorological Station (green), with Imus River Watershed
coverage

31 Temperature trend from 1995 to 2020 at Sangley Point Synoptic 60

Station in Cavite City, Cavite

32 Temperature trend from 2008 to 2020 at CvSU 61

Agrometeorological Station in Indang, Cavite

33 Mean temperature anomalies in Sangley Point Synoptic Station, 61

Cavite City, Cavite

34 Mean temperature anomalies in CvSU Agrometeorological 62

Station, Indang, Cavite

35 Monthly temperature trend in Sangley Point Synoptic Station in 62

Cavite City, Cavite

8
36 Monthly temperature trend in CvSU-PAGASA 63
Agrometeorological Station in Indang, Cavite

37 The diurnal temperature range of Sangley Point Synoptic Station 63

and CvSU Agrometeorological Station

38 The average mean temperature of Sangley Point Station and 64

CvSU Agrometeorological Station using 2008 – 2020
temperature data

39 Rainfall trends in Sangley Point Station and CvSU 65

Agrometeorological Station from 1990 to 2020

40 Average monthly rainfall in Sangley Point Station and CvSU 65

Agrometeorological Station

41 Seasonal rainfall deviation from the normal value in CvSU 66

Agrometeorological Station

42 Seasonal rainfall contribution in CvSU Agrometeorological 67

Station

43 Seasonal rainfall deviation from the normal value in Sangley 67

Point Synoptic Station

44 Seasonal rainfall contribution in Sangley Point Synoptic Station 68

45 The location of Daang Hari Bridge in Imus River Watershed 69

46 Daily streamflow trend at Daang Hari Bridge during the wet 70

season of June 2017 to October 2017 (DOST-ASTI)

47 Daily streamflow trend at Daang Hari Bridge during dry season 71

of November 2017 to April 2018 (DOST-ASTI)

48 Daily streamflow trend at Daang Hari Bridge during wet season 72

of June 2017 to October 2017 (DOST-ASTI)

49 Daily streamflow trend at Daang Hari Bridge during dry season 73

of June 2017 to October 2017 (DOST-ASTI)
50 Daily streamflow trend at Daang Hari Bridge during wet season 74
of May 2019 to October 2019 (DOST-ASTI)

51 Daily streamflow trend at Daang Hari Bridge during dry season 75

of November 2019 to April 2020 (DOST-ASTI)

9
Glossary of Terms

Agrometeorological Station. A derivative station using the advanced remote data-

acquisition unit (arQ) geared with multi-parameter weather sensors which can
simultaneously measure wind speed and direction; air temperature; air humidity; air
pressure, rain amount, duration and intensity, soil moisture and temperature, solar
radiation, and sunshine duration.

Barangay. Historically referred to as barrio, the smallest administrative division in

the Philippines and the native Filipino term for a village, district, or ward. In
metropolitan areas, the term often refers to an inner city neighborhood, a suburb or
a suburban neighborhood.

Census. A survey conducted on the full set of observation objects belonging to a

given population or universe.

Delineation. The process of establishing the boundary of a watershed using

topographic maps.

Discharge/Streamflow. The volume of water that moves over a designated point

over a fixed period.

Diurnal temperature range. The difference between the maximum and minimum
temperatures within a day.

Geomorphology. The study of physical features of the surface of the earth and their
relation to its geological structures.

Land Cover. The surface cover of the ground, whether vegetation, urban,
infrastructure, water, bare soil or other.

Land use. The purpose to which land serves.

Maximum Temperature. The highest temperature recorded in a given period of

observation or the highest temperature of the entire record.

Minimum Temperature. The lowest temperature recorded in a given period of

observation or the lowest temperature of the entire record.

Raster file. An image file of rectangular array of regularly sampled values known as
pixels.

10
Rating Curve. A graph of discharge versus stage for a given point on a stream, usually
at gauging stations, where the stream discharge is measured across the stream
channel with a flow meter.

Shapefile. A simple, non-topological format for storing the geometric location and
attribute information of geographic features.

Sub-watershed. A small watershed delineated within a larger watershed, often for

purposes of describing and managing local conditions.

Synoptic Station. A station at which meteorological observations are made for the
purposes of synoptic analysis.

Temperature Anomaly. The difference from an average or baseline temperature.

Watershed. Also called as drainage basin or catchment, it is a land area that channels
rainfall to creeks, streams, and rivers and eventually to outflow points such as
reservoirs, bays and the ocean.

11
 Executive Summary
River systems acts as major pathways for the transport of waste, particularly non-
biodegradable plastics. Of the land-based waste which enters rivers, most ends up in
our oceans.

The Imus River watershed is located in the Philippine province of Cavite, south of
Manila. It flows into Manila Bay, a pollution hotspot. This study delineated and
mapped the physical boundaries of the watershed. It studied aspects of physical
geography, such as topographic features, stream characteristics, geomorphology,
land cover, and hydro-climatic characteristics of the watershed, as well as human
geography, such as political subdivisions, population distribution, and land use.

Both primary and secondary data sources were used to make comprehensive land use
maps, population maps, and hydro-climatic data analyses. The boundary of the Imus
River watershed was established using a digital elevation model of the province of
Cavite in ArcGIS. Sangley Point Synoptic Station in Cavite and the CvSU-PAGASA
Agrometeorological Station in Indang were used to assess the general hydro-climatic
condition of IRW due to their close proximity to the watershed.

The total drainage area of the Imus River watershed is 11,259.80 hectares, and its
elevation ranges from 0 to 655 meters above sea level. Areas considered lowland
include parts of Kawit, Imus and Bacoor. A centrally hilly area covers parts of Imus,
Bacoor and the majority of communities in Dasmariñas and Silang. The upland area
covers parts of Silang, Amadeo and Tagaytay. There were 56 perennial streams
identified with a total length of 186.15 km and 36 river segments. These can be
divided into three sub-watersheds, each with their own characteristics.

A total of 222 barangay communities are situated fully or partially within the
boundaries of the watershed, and as of 2015 the estimated population of the
watershed is 1,351,057 people. 90.67% of the province is classified as alienable and
disposable land, divided into production land (55.24%) and built-up areas (44.76%).

Normal mean temperatures ranged from 26.20°C to 28.53°C, while average total
annual rainfall ranged from 2,265.69 mm to 2,483.05 mm. The average flow during
wet season was 1,601.84 liters per second, while the average flow during dry season
was 1,337.42 liters per second.

12
 Introduction

The Philippines Province of Cavite is located within the CALABARZON region in the
south of Luzon Island known as the CALABARZON Region. Cavite is bound by Metro
Manila and Manila Bay in the north, Batangas in the south, Laguna in the east and
the West Philippines sea in the west (Provincial Government of Cavite, 2017). The
land area of the province is 142,706 ha, which comprises 0.4% of the total land area
of the Philippines. The province is composed of 7 cities and 16 municipalities, which
together are made up of a total of 829 barangays (PEMSEA and Provincial
Government of Cavite, 2017). In the 2020 census of the Philippines Statistics
Authority, the total population of Cavite was 4,344,829. Cavite was the fastest
growing province in CALABARZON with an annual population growth rate of 3.57%
from 2015 to 2020, higher than the national average of 1.63%. There is significant
economic development in the province due to its proximity to Metro Manila, with
the provincial government estimating GDP to be PHP 42,000 per capita (PEMSEA,
2020). Economic activity in the province include agriculture, mining, forestry, grazing,
gathering fishing and quarrying. Cavite is also a highly industrialized and urbanized
province in the country and is the best-loved destination of investors next to Metro
Manila as manifested by increasing number of industries. According to the
Department of Trade and Industry (DTI) the average annual revenue of the province
amounted to PHP 9,220,374,201.26 from 2016 to 2020.

There are six major river systems in Cavite namely; Maragondon, Labac-Alemang,
Timalan, Cañas, San Juan, and Imus River (Figure 1). These river systems provide
crucial natural ecological functions and ecological services. In addition to sustaining
local biodiversity, these river systems also sustain the needs of the population of the
province in terms of water, food, livelihood, and recreation (Sedigo et al., 2015). Due
to the rapid agro-industrialization, commercialization, and urbanization in the
province, these river systems are increasingly exposed to waste generation from
households, commercial establishments, industries, and agriculture. Waste entering
the river further risks being transported downstream into Bacoor Bay and other
sections of the wider Manila Bay coastline. These wastes include non-degradable
plastics, which go on to produce secondary plastics (e.g. microplastics) through

13
fragmentation. Accumulating in rivers and the ocean, microplastics may pose a
greater and less visible threat to ecosystems (Andrady, 2011).

Imus River originates in the upland city of Tagaytay. It traverses the upland
municipalities of Amadeo and Silang before passing the densely urbanized cities of
Dasmarinas, Imus, Bacoor, and the coastal municipality of Kawit. It finally drains into
Bacoor Bay, a sheltered part of the wider Manila Bay. As with other rivers running
parallel to Imus River in Cavite, this route conveys waste that finds its way into the
river from homes, commercial centers, industries and agricultural farms, towards the
ocean. Significant waste is transferred by periodic flooding in the river, especially
during the rainy season.

The monitoring of rivers is an essential component of the effective monitoring and

management of plastic pollution. The Imus River system has been identified as the
Philippine study site of the ASEANO project. As a site of a growing population and
economy, it is a likely hotspot for increasing waste output. The ASEANO project is a
project led by the Norwegian Institute for Water Research (NIVA) and financed by
the Norwegian Development Assistance Program Against Marine Litter and
Microplastics. The aim of the ASEANO project is to strengthen knowledge, capacity,
and awareness to deal with plastic pollution in the ASEAN region. To achieve this
aim, having a good understanding of local conditions is crucial. This study seeks to
gather baseline data of the Imus river basin such as drainage area, river morphology,
hydro-climatic data, as well as the socio-economic characteristics of communities
located within its boundaries.

14
Figure 1. Cavite (green) within the CALABARZON region

15
Figure 2. The six major river watersheds in Cavite. The Imus River Watershed (IRW) 60is shown in purple.

16
Objectives of the Study

This project aimed to delineate the boundaries of Imus River Watershed and
characterize the watershed through GIS and RS technologies.

It specifically aimed to:

1. delineate and map the physical boundaries of the Imus River watershed;
2. determine the topographic features of the watershed in terms of:
2.1. contour;
2.2. elevation; and
2.3. slope;
3. determine the stream characteristics and geomorphology of the
watershed in terms of:
3.1. river network;
3.2. stream order;
3.3. drainage density;
3.4. stream frequency;
3.5. bifurcation ratio;
3.6. elongation ratio; and
3.7. circulatory ratio;
4. identify the political subdivisions and barangay communities within the
watershed;
5. determine the population distribution within the watershed in terms of:
5.1. total population per barangay; and
5.2. population density per barangay
6. determine the land use and land cover of the watershed; and
7. determine the hydro-climatic characteristics of the watershed in terms of:
7.1. air temperature;
7.2. rainfall; and
7.3. streamflow

17
 Methodology

Study Site

The main body of the Imus River is 38.4 kilometers long. Counting its smaller streams
and segments, the complete river system spans a total of 186.15 kilometers. It
originates from the mountains of Tagaytay and flows through the communities of
Balite, Sabutan, Biga, Silang, Palapala, Dasmariñas, Pasong Bayog and San Agustin. A
connection to Pasong Bayog passes through the communities of Salitran, Baluctot,
Anabu II, Anabu I, Tanzang Luma, Palico, Imus, Salinas, Mabolo and Bacoor before
draining out at Bacoor Bay. Baluctot also has a separate connection to the Imus
River. Another connection from Pasong Bayog flows through the communities of San
Agustin and Bucal. The Imus River system flows through some of the most densely-
populated cities in Cavite, including Dasmariñas, Imus, Kawit and Bacoor, before
emptying its contents in Manila Bay, one of the world’s most polluted bodies of
water. (Cavite Ecological Profile, 2017). According to DENR-RBCO (2015) as cited by
Paringit and Uy (2017), the outlet of the watershed is located at 14°27'31.16"N,
120°55'34.00"E where the estimated annual runoff is 168 million cubic meters.

Data Gathering
The project performed primary baseline and secondary data gathering procedures. A
5-meter resolution Digital Elevation Map (DEM) and the 2015 land use map of the
province of Cavite were requested from the National Mapping and Resource
Information Authority (NAMRIA). Comprehensive land use maps of all the
municipalities and cities within the Imus River Watershed were requested from the
Provincial Planning and Development Office (PPDO) of the Province of Cavite. The
DEM was used to establish the boundary and other physiographic characteristics of
the watershed. The land use/land cover (LULC) maps were used to characterize the
general land cover and land appropriation of the watershed. The latest published
population census in 2015 was requested from the Philippine Statistics Authority.

18
The climate data from Sangley Point Synoptic Station and CvSU-PAGASA
Agrometeorological Station were requested from the Philippine Atmospheric,
Geophysical and Astronomical Services Administration (PAGASA) while the water
level data was requested from the Department of Science and Technology -
Advanced Science and Technology Institute (DOST-ASTI).

Delineation and Topographic Characterization of Imus River Watershed

The boundary of the Imus River Watershed was initially established through a
delineation process using a digital elevation model of the province of Cavite with 5-
meter resolution in ArcGIS. Through the hydrology toolbox in the spatial analyst
extension of ArcGIS, the sinks of the DEM were filled to remove data imperfections.
To establish how water flowed through the local topography, flow direction was
determined in individual cells. A flow accumulation path was built through the flow
accumulation raster, and pour points (flow outlets) were identified to determine the
watershed pertaining to the flow path. Using the flow direction raster and the pour
point shape file as the input, the watershed was delineated using watershed tool in
hydrology tool box. This was validated through field visits on the ground and using
remote sensing technology to test the consistency of the established boundary. The
topographic features such as contour, elevation, and slope of the Imus River
Watershed were also extracted from the digital elevation model.

Watershed Geomorphology
The geomorphological characterization of the Imus River Watershed was done to
further analyze and understand its structures and dynamics. Its geomorphology
together with its hydroclimatic characteristics determine the structure and
composition of the watershed and its biotic communities. Such characterization also
provides a basis for the prediction of watershed products transported in its channels,
such as sediments, woody debris, and plastics.

Sub-watershed and river network. The Imus River Watershed was divided into three
sub-watersheds for more detailed geomorphological characterization. Analysis of the
river network segments looked at length, confluence, and bed slope.

Stream ordering. Stream ordering is a method of assigning a numeric order to links in

a stream network, allowing for the identification and classification of types of
streams based on their numbers of tributaries. Some characteristics of streams can

19
be inferred by simply knowing their order. Using the stream order, the rivers within
the watershed were identified as headwaters, medium-sized river channels, or large
river channels.

Drainage density. This was calculated as the length of perennial channels divided by
their drainage area. It is usually expressed in kilometers per square kilometer
(km/km2).

Stream frequency. This refers to the number of river segments over the total
drainage area. The river segments or the river confluence is a point where two or
more flowing bodies of water join to form a single channel.

Bifurcation ratio. This is the relationship between the number of stream segments of
a given order and the number of streams of the next higher given order. This
measures how a single stream order discharges water into another (Horton, 1945).
Bifurcation ratio can be computed using the formula:

𝑁𝑢
𝑅𝑏 =
𝑁𝑢 + 1
Where:
Rb = Bifurcation ratio
Nu = number of the given stream order
Nu+1 = number of the next higher stream order

Elongation ratio. A dimensionless property which is the ratio of the diameter of a

circle of the same area as the basin to the maximum basin length (Sukristiyanti,
Maria, & Lestiana, 2018). It was calculated using the formula:

2
𝑅𝑒 =

Where:
Re = Elongation Ratio
A = Area of the watershed/basin
Lb = Watershed length

Circulatory ratio. A dimensionless property which is the ratio between the area of a
watershed and the area of a circle with the same circumference as the perimeter of
the watershed (Sukristiyanti, Maria, & Lestiana, 2018). It can be calculated using the
formula:

20
 4𝜋𝐴
𝑅𝑐 =
𝑃2
Where:
Rc = Circulatory Ratio
A = Area of the watershed/basin
P = Perimeter of the watershed/basin

Mapping of Barangay’s and Population Distribution

The barangays within each of the municipalities and cities covered by the Imus River
watershed were overlaid with established watershed boundary and river network to
identify all the barangay’s within the IRW. Using the population data from the
Philippine Statistics Authority, total population and population density maps of the
IRW were created to identify the population variations among barangay
communities. For those barangays that were partially covered by the IRW, the
population considered in the study was obtained by allocating a percentage of the
barangay population equivalent to the land area covered by the IRW.

Mapping of the Land Use/Land Cover (LULC) of Imus River Watershed

A general land cover map for the IRW showing the presence of crops,
grasslands, water bodies, open/barren areas and built-up areas was generated using
the 2015 land cover map from NAMRIA. The comprehensive land use maps of the
cities/municipalities were requested from the PPDO and then overlaid with the
watershed boundary to show the land use and appropriation of the watershed.

Hydroclimatic Characterization of Imus River Watershed

Two weather stations in close proximity to the watershed were used to assess
hydroclimatic condition: Sangley Point Synoptic Station in Cavite City (14o 29’ 29.94”
N, 120o 53’ 54.96”E) and the CvSU-PAGASA Agrometeorological Station in Indang
(14o 11’ 52.39” N, 120o 53’ 0.80”E). The watershed was divided into two approximate
areas of influence relating to each weather station through the Thiessen Polygon
Method. In this method, perpendicular bisectors are constructed at the midpoint of
the line segment connecting the two stations. These bisectors determined the
boundary between the area of influence of each station. Sangley Point Synoptic

21
Station generally covers the lowland area whilst the CvSU-PAGASA Agro-met Station
represents the upland area of the watershed.

Air temperature. Air temperature data from Sangley Point Synoptic Station cover up
to 26 years (1995 – 2020) and those from CvSU-PAGASA Agromet Station about 14
years (2007 – 2020). The daily measurements of air temperature (daily maximum and
minimum air temperature) from each station were used to analyze temperature
variation. The maximum and minimum readings were used to determine the diurnal
temperature range for each station.

Rainfall. Available rainfall data from Sangley Point Synoptic Station cover 26 years
(1995 – 2020) and those from CvSU-PAGASA Agromet Station cover 14 years (2007 –
2020). The rainfall data was used to determine rainfall normal, areal distribution, and
seasonal variation. Data augmentation using a correlation technique was used to
lengthen the rainfall data for CvSU-PAGASA Agrometeorological Station (See Annex
A).

Streamflow. The Water Level Station installed by DOST-ASTI at Daang Hari Bridge,
Imus, Cavite was used to measure streamflow of the IRW. It is located at 14 o 22’
22.49”N, 120o 56’ 31.66” E and was installed in February 2017.The cross-sectional
survey done by Paringit and Uy (2017) at Daang Bridge, Imus, Cavite was used to
develop a rating curve to translate the water level readings into discharge (Figure 1).
The elevation at the left bank of the river is 37.91m at Mean Sea Level (MSL) while
the elevation at the right bank of the river is 37.82m at MSL. The lowest part of the
cross-section (Zero Datum) is at 25.91m at MSL.

Figure 3. Cross-sectional area of the outlet at Daang Hari Bridge

22
The relationship between known discharge and the water level (Figure 4) shows a
trend line of the rating curve is 𝑦=0.2078𝑥3.1002, where y = discharge and x = water
level. This allows an approximation of streamflow discharge readings from water
level readings.

Rating Curve
300
y = 0.2078x3.1002
250 R² = 0.9907
Discharge (LPS)

200

150

100

50

0
0 2 4 6 8 10 12

Water Level (m)

Figure 4. Developed rating curve of the outlet at Daang Hari Bridge.

23
 Results and Discussion

Delineation and Mapping of the Physical Boundaries of Imus River Watershed

Based on the final boundary established (Figure 5), the total drainage area of the
IRW is 11,259.80 hectares. It covers portions of three municipalities, namely:
Amadeo, Kawit and Silang, and portions of four cities, namely: Bacoor, Dasmariñas,
Imus, and Tagaytay. Among these municipalities and cities, Dasmariñas City has the
largest area within the watershed, around 4,830.42 ha, or 42.92% of the total
watershed. Amadeo has the least area covered by the watershed, only 4.09 ha or
0.03% of the watershed (Table 1).

Table 1. Municipalities and cities located within Imus River Watershed

Municipality/City Area (ha) Share of Watershed (%)
Amadeo 4.09 0.03
Bacoor 1,880.31 16.70
Dasmariñas 4,830.42 42.92
Imus 2,993.66 26.60
Kawit 137.74 1.21
Silang 1,263.36 11.22
Tagaytay 150.19 1.32
Total 11,259.80 100

Determination of the Topographic Features of Imus River Watershed

The elevation within the watershed ranges from 0 to 655 meters above sea level
(Figure 6). The Imus River Watershed is divided into three distinct areas: the lowland
area has an elevation of 0 – 30 meters above sea level which is relatively flat; central
hilly area has an elevation of 30.01 – 400 meters above sea level and a slope of 0.5%
to 2%; and upland area has an elevation of 400.01 – 655 meters above sea level and
a slope greater than 2% (Figure 7, Figure 8). The lowland area covers parts of Kawit,
Imus City and Bacoor City; centrally hilly area covers parts of Imus City and Bacoor
City and the majority of the communities found in Dasmariñas and Silang; the upland
area includes parts of Silang, Amadeo, and Tagaytay City.

24
Figure 5. Cities and municipalities partially covered by the Imus River Watershed.

25
Figure 6. Topographic contours of the Imus River Watershed.

26
Figure 7. Division of the Imus River Watershed by elevation.

27
Figure 8. Slope of land within the Imus River Watershed.

28
Geomorphology of Imus River Watershed

The geomorphology of a watershed influences the dynamics of streams and rivers

that are important in understanding the formation and alteration of the stream or
river channels, flood plains, and associated upland transitional zones. This
information is useful for an effective, long-term watershed management (O'Keefe,
Elliot, & Naiman, 2020).

Sub-watershed and river network. There were 56 perennial streams identified with a
total length of 186.15 km. 36 river segments were identified (Figure 9), along with
their highest and the lowest points (Figure 10). The elevations of the identified points
were extracted and used in determining the bed slope of each river (Table 2). The
watershed was divided into three major sub-watersheds (Figure 11). Sub-watershed
A has a total drainage area of 2,034.87 ha and a perimeter of 37.37 km, covering
portions of Imus, Dasmariñas, and Kawit. Sub-watershed B has a total drainage area
of 6,873.79 ha and a perimeter of 90.26 km which covers portions of Imus,
Dasmarinas, Silang, Amadeo and Tagaytay; and sub-watershed C has a total drainage
area of 2,025.62 ha and a perimeter of 31.20 km which covers Bacoor.

Stream order. Based on river category, rivers with stream order ranging 1 to 3 are
considered as headwaters while those ranging from 4 to 6 are medium sized rivers.
Based upon this, the river system of the Imus River Watershed is characterized by a
combination of headwaters and medium-sized streams.

Table 2. Stream ordering of each sub-watershed of Imus River Watershed.

Total Length
Sub-watershed Stream Order Number of Streams
A 1 5 10.13
2 1 13.41
1 31 68.87
B 2 7 44.46
3 2 9.71
4 1 11.09
1 6 15.65
C 2 2 12.09
3 1 0.76

Drainage density. According to Sukritiyani et al. (2017), there are five classes of
drainage area based on its drainage density: very coarse (<2 km/km 2); coarse (2 – 4
km/km2); moderate (4 – 6 km/km2); fine (6 – 8 km/km2); and very fine (>8 km/km2).

29
In the case of IRW, sub-watersheds A, B, and C have values of 1.15 km/km2, 1.95
km/km2, and 1.41 km/km2, respectively. These values classify as very coarse or very
low-density drainage areas that may indicate a poorly drained basin with a slow
hydrologic response, making them more susceptible to flooding and erosion.

Stream frequency. According to Prabhakaran & Raj (2018), watersheds can be

grouped into three classes based on their stream frequency: low frequency (< 2.5 per
km2); moderate frequency (2.6 – 3.5 per km2); and high frequency (>3.5 per km2). In
the case of IRW, sub-watersheds A and C have values of 0.20/km2 and 0.25/km2,
which classify as low stream frequency. This indicates lower permeability, less relief,
and a gentler slope, which is consistent with sub-watersheds A and C covering
relatively flatter lowland areas. On the other hand, sub-watershed B has a value of
0.39/km2, which falls under a high stream frequency, indicating a steep slope and
greater rainfall, consistent with what is common in mountainous areas.

Bifurcation ratio. The values of bifurcation ratio range from 2 to 5 with an average of
3.5. According to Yangchan (2015), high bifurcation ratios ranging from 3 to 5
indicate a structurally more disturbed watershed with prominent distortion in
drainage pattern. These values may indicate mountainous or highly dissected
drainage basins (Horton, 1945). On the other hand, low bifurcation ratios (<3)
indicate a more structurally stable watershed and a clearer drainage pattern
(Yangchan, 2015). These range of values may indicate a flat or rolling drainage basins
(Horton, 1945).

In the case of IRW, sub-watersheds A and B have bifurcation ratios of 5 and 3.31
respectively, which indicates that the majority of these sub-watersheds are
mountainous and highly dissected, with lower flood susceptibility. On the other
hand, sub-watershed C has a bifurcation ratio of 2.5, indicating a flat or rolling basin
that has a higher possibility of flooding.

Elongation ratio. The elongation ratio is classified into two classes: low value (<1),
which indicates an elongated watershed having high relief and steep slope, and high
value (>1), which indicates a circular watershed with low relief and low slope.
Watersheds with high relief are more susceptible to erosion (Sukristiyanti, Maria, &
Lestiana, 2018). In the case of the IRW, sub-watersheds A, B, and C have values of
0.33, 0.26, and 0.43 respectively, indicating that they are all highly elongated and
susceptible to erosion due to high relief and steeper slope.

30
Circulatory ratio. The value of circulatory ratio varies from 0 (minimum circulatory) to
1 (maximum circulatory). It is used to determine the geomorphological stages of
development of any basin or watershed. The high, medium, and low values of
circulatory ratios are indicative of old, mature, or young stages of the
geomorphological adjustment of any basin (Mahala, 2020). In the case of the IRW,
sub-watersheds A, B, and C have values of 0.18, 0.11, and 0.26 respectively. These
are low values indicating the watershed is in a young dendric stage.

31
Figure 9. The river network of Imus River Watershed overlaid onto local government units (cities and municipalities)

32
Figure 10. The highest and lowest points within the Imus River Watershed.

33
Figure 11. Sub-watersheds of the Imus River Watershed.

34
Political Subdivisions and Barangay Communities within the Imus River
Watershed

The province of Cavite has seven cities and sixteen municipalities, with 829 barangay
communities subdivided into eight legislative districts. The barangay communities
within IRW have been identified based on the established physical boundary of the
watershed (Figures 12 to 18). Dasmariñas has the highest number of barangay’s (69)
located within the watershed, while Amadeo has only one barangay inside the
watershed (Table 3).

Table 3. List of barangay communities within the Imus River Watershed.

Municipality/City List of Barangays Within IRW

Tagaytay (7 barangays) Kaybagal East, Mag-Asawang Ilat, Maharlika

(See Figure 12) East, Maitim 2nd Central, Maitim 2nd West, Silang Junction
North, Silang Junction South

Amadeo (1 barangay) Buho

(See Figure 13)
Silang (19 barangays) Balite I & II, Barangay I – IV, Biga II, Buho,
(See Figure 14) Iba, Lalaan I & II, Malabag, Malaking Tatyao, Mataas Na
Burol, Sabutan, San Vicente II, Toledo, Tubuan I & III

Dasmariñas (69 barangays) Zone IV, Burol I – III, Burol, Datu Esmael,
(See Figure 15) Emmanuel Bergado I & II, Fatima I – III, Luzviminda I & II,
Paliparan I – III, Sabang, Saint Peter I & II, Salawag, Salitran
I – IV, Sampaloc I – V, San Agustin I – III, San Andres I & II,
San Antonio de Padua I & II, San Dionisio, San Esteban, San
Francisco I & II, San Isidro, Labrador I & II, San Jose, San
Juan, San Lorenzo Ruiz I & II, San Luis I & II, San Manuel I &
II, San Mateo, San Miguel II, San Miguel, San Nicolas I & II,
San Roque, San Simon, Santa Cristina I & II, Santa Cruz I &
II, Santa Fe, Santa Lucia, Santa Maria, Santo Cristo, Santo
Niño I & II, Zone I-B, Zone I

35
Table 3. Continued…

Municipality/City List of Barangays Within IRW

Imus (73 barangays) Anabu I (A – G), Anabu II (A – F), Bagong

(See Figure 16) Silang, Bayan Luma I – IX, Bucandala I, II, V, Buhay na
Tubig, Carsadang Bago I, Magdalo, Maharlika,
Malagasang I (F&G), Malagasang II (E, F, G), Mariano
Espeleta I – III, Medicion I (C&D), Medicion II (C – F),
Palico I – III & V, Pasong Buaya I & II, Pinagbuklod,
Poblacion I (A – C), Poblacion II (A & B), Poblacion III (A
& B), Poblacion IV (A–D), Tanzang Luma I – IV, Toclong I
(A–C), Toclong II (A&B)
Bacoor (48 Barangays) Alima, Aniban I, Banalo, Bayanan, Campo
(See Figure 17) Santo, Daang Bukid, Digman, Dulong Bayan, Habay I & II,
Kaingin, Ligas III, Mabolo I – III, Maliksi I, Mambog I – V,
Molino II – V & VII, Niog I & II, P.F. Espiritu I – VIII,
Queens Row East, Real I & II, Salinas I – IV,
Sineguelasan, Tabing Dagat
Kawit (8 Barangays) Toclong, Balsahan-Bisita, Binakayan-
(See Figure 18) Aplaya, Binakayan-Kanluran,Congbalay-Legaspi,
Manggahan-Lawin, Pulvorista, Samala-Marquez

36
Figure 12. Barangay communities of Tagaytay City overlaid against the Imus River Watershed.

37
Figure 13. Barangay communities of Amadeo overlaid against the Imus River Watershed.

38
Figure 14. Barangay communities of Silang overlaid against the Imus River Watershed.

39
Figure 15. Barangay communities of Dasmariñas City overlaid against the Imus River Watershed.

40
Figure 16. Barangay communities of Imus City overlaid against the Imus River Watershed.

41
Figure 17. Barangay communities of Bacoor City overlaid against the Imus River Watershed.

42
Figure 18. Barangay communities of Kawit overlaid against the Imus River Watershed.

43
Population Distribution within Imus River Watershed

The total population of Cavite based on the POPCEN 2020 is 4,344,829, making it the
most populous province in the Philippines. There was a significant increase in the
population from 2015 to 2020 with a 3.57% growth rate representing an increase of
587,610. Due to its proximity to Metro Manila, this population increase can be
attributed to the migration of people from Metro Manila and other nearby provinces
to the province of Cavite seeking employment opportunities. The top three cities in
terms of population in the province are the City of Dasmariñas, contributing 17.92
percent to the total population of the province, followed by the City of Bacoor
(16.33%) and City of Imus (10.9%). Major portions of these three populous cities are
within the boundary of the Imus River Watershed.

There are 222 barangay communities located within the watershed with a total
population of 1,351,057 in 2020. The biggest barangay in terms of land area is
Barangay Salawag in Dasmarinas with an area of 21,193,476 m2, while San Roque in
Dasmarinas is the smallest with an area of 15,337.36 m2. Barangay Salawag was also
the most populous barangay with 80,136 inhabitants, while Barangay Poblacion 1-B
in Imus was the least populous with only 316 inhabitants. In terms of population
density, the densest barangay is Sta. Fe (20.10 per 100 sqm) in Dasmarinas, while the
least dense barangay is Pasong Buaya (0.03 per 100 sqm) in Imus. Figures 19 and 20
shows the total population and population density map of Imus River Watershed.

44
Figure 19. Map showing the population of the barangay communities within the Imus River Watershed.

45
Figure 20. Map showing the population density of barangay communities within Imus River Watershed.

46
General Land Cover, Vegetation and Comprehensive Land Uses of Imus River
Watershed

The assessment of land use/land cover helps to determine the anthropogenic

influence on natural systems and is significant in understanding natural settings and
socioeconomic conditions at local, regional, and global levels (Chowdhury, Hasan, &
Abdullah-Al-Mamun, 2020). Changes in land use and land cover can be caused by
socio-economic development, population expansion, and conversion to agriculture
(Lambin, Geist, & Lepers, 2013). The multiple land uses within a typical watershed
have significant impact on the watershed’s hydrological characteristics (Haque,
2013). Vegetative and forest cover loss is accompanied by an increase in stream
discharge and surface runoff. This may cause intense flooding, soil erosion, and
landslides within the watershed (Guzha, Rufino, Okoth, Jacobs, & Nobrega, 2018).

In total, 90.67% of the province is classified as alienable and disposable land, while
the remaining forest land represents only 9.33%. Alienable and disposable lands are
further classified as production land (55.24%) and built-up areas (44.76%). The built-
up areas include residential, industrial, commercial, and tourism areas. Built-up areas
constitute more than half of the total drainage area of the watershed, followed by
areas devoted to annual and perennial crops (Table 4).

Table 4. Land Classification of Imus River Watershed.

Land Cover Area (ha) Percent Share
Annual Crop 2,110.70 18.759
Brush and Shrubs 77.87 0.692
Built-up 6,754.90 60.034
Fishpond 134.19 1.193
Grassland 1,034.47 9.194
Inland Water 18.37 0.163
Mangrove Forest 1.86 0.016
Open/Barren 0.54 0.005
Perennial Crop 1,118.89 9.944

Total 11, 259.80 100

47
The Vegetative Index map of IRW shows that most of the upland area (including
Tagaytay and Silang) is highly vegetated. The majority of the areas in Dasmariñas and
the lowland areas such as Imus, Bacoor, and Kawit have less vegetation (Figure 21).
Isolated areas of high vegetation found in Imus and Dasmariñas mainly represent rice
fields.

The Comprehensive Land Use Plan (CLUP) is a planning document prepared by Local
Government Units (LGUs) to rationalize the allocation and proper use of land
resources. It projects public and private land uses in accordance with the future
spatial organization of economic and social activities. The land use maps from each
city and municipality were overlaid with the boundary map and river system map of
the IRW to show the public and private land uses within the watershed (Figures 23 to
29).

48
Figure 21. Land cover of the Imus River Watershed.

49
Figure 22. Normalized difference vegetation index of the Imus River Watershed.

50
Figure 23. Land use within Tagaytay City.

51
Figure 24. Land use within Amadeo.

52
Figure 25. Land use within Silang.

53
Figure 26. Land use within Dasmariñas City.

54
Figure 27. Land use within Imus City.

55
Figure 28. Land use within Bacoor City.

56
Figure 29. Land use within Kawit.

57
Hydroclimatic Conditions in Imus River Watershed

The analysis of hydroclimatic variables such as precipitation, temperature, and river

flow dynamics in a given spatial-temporal scale is an emerging strategic research
approach to better comprehend natural systems such as watersheds (Montanari, et
al., 2013). Understanding the use and movement of water in a watershed will
provide a strong foundation towards understanding and describing how the
landscapes and water interact (Edwards, Williard, & Schoonover, 2015). Figure 30
shows the proximity of the two environmental monitoring stations to the IRW and
their respective regions of influence.

58
Figure 30. Sangley Point Synoptic Station (blue) and CvSU Agrometeorological Station (green), with Imus River Watershed coverage.

59
Air Temperature

Based on the 25-year temperature data from Sangley Point Synoptic Station, the
normal mean temperature is 28.53°C, with a normal maximum temperature of
32.04°C and normal minimum temperature of 25.85°C. On the other hand, based on
the 14-year temperature data in CvSU Agrometerological Station (also referred to as
the CvSU-PAGASA Agromet Station), the normal mean temperature is 26.20°C, the
normal maximum temperature is 30.46°C, and the normal minimum temperature is
21.70°C.

Temperature Trend
Sangley Point Synoptic Station
34.00
Tempreature (Degree Celcius)

33.00
32.00
31.00
30.00
29.00
28.00
27.00
26.00
25.00
24.00
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
Tmax Mean Tmin

Figure 31. Temperature trend from 1995 to 2020 at Sangley Point Synoptic Station in
Cavite City, Cavite.

60
 Temperature Trend
CvSU-PAGASA Agromet Station
33.00
Temperature (Degree Celcius)

31.00

29.00

27.00

25.00

23.00

21.00

19.00
2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

Tmax Mean Tmin

Figure 32. Temperature trend from 2008 to 2020 at CvSU Agrometeorological Station
in Indang, Cavite.

The temperature anomalies for mean, maximum, and minimum temperatures are
shown in Figures 33 to 34. A positive anomaly indicates that the observed
temperature is warmer than the normal, while a negative anomaly indicates that the
observed temperature is cooler than the normal. In Sangley Point Station, mean
temperature anomalies had average values of +0.29°C and -0.29°C, In CvSU-PAGASA
Agromet Station, the mean temperature anomalies had average values of +0.39°C
and -0.34°C.

Mean Temperature Anomalies

0.8
Temperature Anomaly (oC)

0.6
0.4
0.2
0
-0.2
-0.4
-0.6
-0.8
2006
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005

2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020

Figure 33. Mean temperature anomalies in Sangley Point Synoptic Station,

Cavite City, Cavite.

61
 Mean Temperature Anomalies
1
0.8
Temperature Anomaly (oC)

0.6
0.4
0.2
0
-0.2
-0.4
-0.6
-0.8
2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

Figure 34. Mean temperature anomalies in CvSU Agrometeorological Station, Indang,

Cavite.

May is, on average, the warmest month, while January is the coldest month. Sangley
Point Station recorded mean temperatures for these months of 30.28°C and 26.94°C
respectively (Figure 35). On the other hand, whilst May was also the hottest month
recorded in CvSU Agrometeorological Station, February was the coldest month, with
mean temperatures of 28.29°C and 24.10°C respectively (Figure 36).

Monthly Temperature Trend

40

35

30
Tempreature (oC)

25

20

15

10

0
Jan Feb Mar Apr May Jun July Aug Sep Oct Nov Dec

Tmax Mean Tmin

Figure 35. Monthly temperature trend in Sangley Point Synoptic Station in

Cavite City, Cavite.

62
 Monthly Temperature Trend
35.00

30.00
Temperature (oC)

25.00

20.00

15.00

10.00

5.00

0.00
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Tmax Mean Tmin

Figure 36. Monthly temperature trend in CvSU-PAGASA Agrometeorological Station

in Indang, Cavite.

Rainfall and cloud cover are factors that greatly affect the diurnal temperature range
variation because of their significant influence on surface energy and hydrological
balance (Karolyn, et al., 2003). At Sangley Point Synoptic Station, the diurnal
temperature variation was highest during the month of April and lowest during the
month of December. At CvSU Agrometeorological Station, the diurnal temperature
variation was also highest during the month of April and lowest during the month of
December. Diurnal temperature variation thus seems wider in the upland areas than
the lowland areas (Figure 37).

Comparison of Diurnal Temperature Range

12
Diurnal Temperature Range (oC)

10
8
6
4
2
0
Jan Feb Mar April May Jun Jul Aug Sep Oct Nov Dec

Sangley CvSU

Figure 37. The diurnal temperature range of Sangley Point Synoptic Station and CvSU
Agrometeorological Station.

63
Based on the 2008 – 2020 data of the two stations, the normal maximum
temperature was higher at Sangley Point Synoptic Station than CvSU
Agrometeorological Station, while the normal minimum temperature at CvSU
Agrometeorological station was lower than the readings from the Sangley Point
Synoptic Station. This indicates that the temperature readings were much higher in
lowland areas than in the upland areas.

Mean Temperature
35
30
25
20
15
10
5
0
CvSU Sangley

Figure 38. The average mean temperature of Sangley Point Station and CvSU
Agrometeorological Station using 2008 – 2020 temperature data.

Rainfall

The average total annual rainfall recorded at Sangley Point Synoptic station and CvSU
Agrometeorological Station were 2,265.69 mm and 2,483.05 mm respectively (Figure
39). April (17.39 mm) is the driest month recorded at Sangely Point Station while
March (16.92 mm) was the driest month at the CvSU Agrometeorological Station.
August, which had 518.10 mm, is the wettest month recorded at Sangely Point
Station while July, which had 485.04 mm, was the wettest month at the CvSU
Agrometeorological Station (Figure 40).

64
 Rainfall Trend (1990 - 2020)
4500
Rainfall Depth (mm)

4000
3500
3000
2500
2000
1500
1000
500
0
1991

2003
1990

1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002

2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
Sangley Point CvSU

Figure 39. Rainfall trends in Sangley Point Station and CvSU Agrometeorological
Station from 1990 to 2020.

Average Monthly Rainfall Totals

600

500
Rainfall Depth (mm)

400

300

200

100

0
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Sangley Point CvSU

Figure 40. Average monthly rainfall in Sangley Point Station and CvSU
Agrometeorological Station.

The readings between the two stations show the highest correlation during the
month of December and the lowest correlation during the month of March (Table 5).
This correlation coefficient value can be seen as a measure of the homogeneity of
rainfall in the watershed from upland to lowland. Low values indicate less
homogenous distribution, while high values indicate more homogenous distribution
of rainfall within the watershed. The correlation coefficient of the rainfall readings
was much higher during the wet season (0.70) than the dry season (0.54).

65
 Table 5. The correlation coefficient of the monthly readings between Sangely Point
Station and CvSU Agrometeorological Station.

Month Correlation Coefficient

January 0.5
February 0.64
March 0.15
April 0.5
May 0.82
June 0.8
July 0.71
August 0.73
September 0.79
October 0.37
November 0.62
December 0.84

At CvSU Agrometeorological Station, the normal monthly precipitation was 206.92

mm. During wet season, the estimated monthly rainfall total was 342.50 mm, while
the estimated monthly rainfall total during dry season was only 71.34 mm. There was
a ±66% rainfall deviation from the normal value (Figure 41).

CvSU-PAGSA Agromet Station

400

350

300
Rainfall Depth (mm)

250

200

150

100

50

0
Wet Normal Value Dry

Figure 41. Seasonal rainfall deviation from the normal value in CvSU
Agrometeorological Station.

66
The normal annual precipitation was 2,483.05 mm at CvSU Agrometeorological
Station. During wet season, the estimated rainfall total was 2,055.02 m (83%) while
the estimated rainfall total during dry season was only 428.03 mm (17%) (Figure 42).

CvSU Agromet Station

17%

83%
Wet Dry

Figure 42. Seasonal rainfall contribution in CvSU Agrometeorological Station.

At Sangley Point Station, the normal monthly precipitation was 188.81 mm. During
the wet season, the estimated total monthly rainfall total was 331.49 mm while the
estimated total monthly rainfall during dry season was only 46.13 mm. There was a
±76% rainfall variation from the normal value (Figure 43).

Sangley Point Synoptic Station

350

300
Rainfall Depth (mm)

250

200

150

100

50

0
Wet Normal Average Dry

Figure 43. Seasonal rainfall deviation from the normal value in Sangley Point Synoptic
Station.

67
The normal annual precipitation was 2,265.69 mm at Sangley Point Station. During
wet season, the estimated rainfall total was 1,988.92 mm (88%) while the estimated
rainfall total during dry season was only 276.76 mm (12%) (Figure 44).

Sangley Synoptic Station

12%

88%
Wet Dry

Figure 44. Seasonal rainfall contribution in Sangley Point Synoptic Station.

Streamflow

Streamflow is a volumetric discharge that takes place in a stream or channel and

varies over space and time. Understanding the temporal and spatial distribution of
streamflow is important in hydrology, emergency management, flood forecasting,
water resources planning and management, and environmental protection (Wiche &
Holmes, 2016). Rivers are considered as the main conduits of plastic waste to the
seas, with most plastic waste carried by small rivers that flow through densely
populated urban areas (Parker, 2021). Understanding the streamflow of rivers will
help to explain the movement of plastic waste and inform potential solutions to
reduce the amount that is released into the oceans.

Rainfall is the main factor to consider in the changes of streamflow. Other natural
mechanisms that cause changes in streamflow are transpiration by vegetation,
groundwater discharge and recharge, and natural sedimentation. Human induced
changes should also be considered such as land use changes due to urbanization,
surface withdrawals, reservoir sedimentation, and others. Figures 46 to 51 show the
daily average streamflow at Daang Hari Bridge (located in Figure 45) at different
seasons.

68
Figure 45. The location of Daang Hari Bridge in Imus River Watershed.

69
 DAILY AVERAGE STREAMFLOW AT DAANG HARI BRIDGE
(WET SEASON)
8000

7000

6000

5000
Discharge (lps)

4000

3000

2000

1000

0
Jun '17 Jul '17 Aug '17 Sept '17 Oct '17

Figure 46. Daily streamflow trend at Daang Hari Bridge during the wet season of June 2017 to October 2017 (DOST-ASTI)

70
 DAILY STREAMFLOW AT DAANG HARI BRIDGE
(DRY SEASON)
7000

6000

5000
Discharge (lps)

4000

3000

2000

1000

0
Nov '17 Dec '17 Jan '18 Feb ' 18 Mar '18 Apr '18

Figure 47. Daily streamflow trend at Daang Hari Bridge during dry season of November 2017 to April 2018 (DOST-ASTI)

71
 DAILY STREAMFLOW AT DAANG HARI BRIDGE
(WET SEASON)
16000

14000

12000

10000
Discharge (lps)

8000

6000

4000

2000

0
May '18 Jun '18 Jul '18 Aug '18 Sep '18 Oct '18

Figure 48. Daily streamflow trend at Daang Hari Bridge during wet season of June 2017 to October 2017 (DOST-ASTI)

72
 DAILY AVERAGE STREAMFLOW AT DAANG HARI BRIDGE
(DRY SEASON)
12000

10000

8000
Discharge (LPS)

6000

4000

2000

0
Nov '18 Dec '18 Jan '19 Feb '19 Mar '19 Apr '19

Figure 49. Daily streamflow trend at Daang Hari Bridge during dry season of June 2017 to October 2017 (DOST-ASTI)

73
 DAILY AVERAGE STREAMFLOW AT DAANG HARI BRIDGE
(WET SEASON)
14000

12000

10000
Discharge (LPS)

8000

6000

4000

2000

0
May '19 Jun '19 Jul '19 Aug '19 Sep '19 Oct '19

Figure 50. Daily streamflow trend at Daang Hari Bridge during wet season of May 2019 to October 2019 (DOST-ASTI)

74
 DAILY AVERAGE STREAMFLOW AT DAANG HARI BRIDGE
(DRY SEASON)
6000

5000

4000
Discharge (LPS)

3000

2000

1000

0
Nov '19 Dec '19 Jan '20 Feb '20 Mar '20 Apr '20

Figure 51. Daily streamflow trend at Daang Hari Bridge during dry season of November 2019 to April 2020 (DOST-ASTI)

75
Table 6 shows the average flow, minimum flow and maximum flow at the Daang Hari
Bridge from June 2017 to April 2020. Based on the available data, the average flow
during wet season was 1,601.84 liters per second (Lps), while the average flow
during dry season was 1,337.42 Lps The extreme minimum and extreme maximum
flow were 315.63 lps and 14,941.18 Lps and were both experienced during a wet
season during May 2018 to October 2018.

Table 6. Streamflow at Daang Hari Bridge outlet during different seasons.

Period Season Average flow Minimum Maximum
(Lps) Flow (Lps) Flow (Lps)
Jun 2017 – Oct 2017 Wet 1,767.18 326.24 6,883.20
Nov 2017 – Apr 2018 Dry 857.14 334.41 6,645.02
May 2018 – Oct 2018 Wet 1,862.79 315.63 14,941.18
Nov 2018 – Apr 2019 Dry 1,751.44 394.53 9,742.09
May 2019 – Oct 2019 Wet 1,175.55 392.97 11,741.99
Nov 2019 – Apr 2020 Dry 1,403.67 418.16 5,442.72

76
 Conclusion

The total drainage area of IRW is 11,259.80 hectares and covers portions of Tagaytay
City, Amadeo, Silang, Dasmariñas, Imus City, Bacoor City and Kawit. The elevation
within the watershed ranges from 0 to 655 meters above sea level and can be
subdivided into upland, central hilly, and lowland. The lowland area covers parts of
Kawit, Imus City, and Bacoor City. The central hilly area covers parts of Imus City,
Bacoor City, and the majority of the communities in Dasmariñas and Silang. The
upland area covers parts of Silang, Amadeo, and Tagaytay City.

The Imus river originates in Tagaytay City. Its watershed contains 56 perennial
streams with a total length of 186.15 km, divided between 36 river segments. These
segments are a combination of headwaters and medium-sized streams. The sub-
watersheds A, B, and C have drainage densities of 1.15 km/km2, 1.95 km/km2, and
1.41 km/km2, respectively. The sub-watersheds A and C have stream frequencies of
0.20/km2 and 0.25/km2, which is considered a low value, while sub-watershed B has
a high stream frequency of 0.39/km2. Sub-watersheds A and B have bifurcation ratios
of 5 and 3.31 while sub-watershed C has a bifurcation ratio of 2.5. The elongation
ratio of sub-watersheds A, B, and C have values of 0.33, 0.26, and 0.43, respectively.
The circulatory ratio of sub-watersheds A, B, and C have values of 0.18, 0.11, and
0.26, respectively.

A total of 222 barangay communities were located within the boundaries of the
watershed with a total population of 1,351,057 in 2015. In terms of land
classification, 90.67% of the province is classified as alienable and disposable land,
while the remaining forest land represents only 9.33%. Alienable and disposable
lands are further classified as production land (55.24%) and built-up areas (44.76%).

The Sangley Point Synoptic Station shows a normal mean temperature of 28.53°C,
while the CvSU Agrometeorological Station recoded a normal mean temperature of
26.20°C. The average total annual rainfall recorded at Sangley Point Synoptic station
and CvSU Agrometeorological Station was 2,265.69 mm and 2,483.05 mm,
respectively. The average flow during the wet season was 1,601.84 liters per second
(Lps), while the average flow during the dry season was 1,337.42 Lps.

77
The use of GIS and remote sensing had been found very useful in the fast and
efficient delineation of the boundaries of the Imus river system and the identification
of communities located within its boundaries. These are very useful for identifying
and mapping potential sources of plastic waste within the watershed. Furthermore,
such baseline data can help in measuring the magnitude of waste generation and
monitoring the flow and transport of plastic waste from potential sources into the
sea.

78
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oceans-through-over-1000-rivers

PEMSEA. (2020). Baseline Report The situation and causes of plastic pollution in the
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Prabhakaran, A., & Raj, N. (2018). Drainage morphometric analysis for assessing form
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Sedigo, N., Hermosa, D., Villanueva, M., Espineli, M., & Panizales, J. (2015). Bio-
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science_center_objects

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81
 Annex

Correlation Formula for Climate Data Augmentation

For uncorrelated sequences (r2 ≤ 0.8), which was observed in the rainfall readings
between the two stations, the dependent variable “y” can be solved using the
formula:

𝑦 = 𝑚𝑋𝑖 + 𝑐 +
Where: r = product – moment correlation coefficient

Sy = standard deviation of y from short sequence

ei = random normal variable the zero mean and unit variance.

The product – moment correlation coefficient (r) was obtained using the formula:
1
2
𝑆𝑦𝑥 2
𝑟= 1− 2
𝑆𝑦

𝑆𝑦2 = 𝑦2 −

2
𝑦2 − 𝑐 𝑦−𝑚 𝑥𝑦
𝑆𝑦𝑥 =

Where: x = basis

y = augmented

c, m = regression constant

82
 Annex Table 1. Monthly maximum temperature (OC) at Sangley from 1990 to 2020.
Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
1990 NR NR NR NR NR NR NR NR NR NR NR NR
1991 NR NR NR NR NR NR NR NR NR NR NR NR
1992 NR NR NR NR NR NR NR NR NR NR NR NR
1993 NR NR NR NR NR NR NR 29.68 30.35 30.82 31.43 29.81
1994 30.03 31.04 32.22 34.15 33.92 32.88 30.20 31.59 31.60 31.48 31.88 30.76
1995 30.14 30.55 32.73 33.76 33.66 33.45 32.14 31.86 30.26 31.15 NR 29.00
1996 30.39 30.93 32.78 33.53 34.51 34.12 32.12 32.73 32.01 32.73 30.95 29.84
1997 29.97 31.07 32.10 34.50 33.85 32.99 31.35 30.67 31.89 33.18 32.83 31.66
1998 31.86 33.45 33.59 35.02 34.28 34.26 34.51 33.53 31.69 31.60 33.19 30.80
1999 31.62 31.34 33.36 33.52 34.40 31.81 30.73 30.83 30.64 31.39 30.28 29.86
2000 30.11 30.67 31.81 34.70 32.69 33.01 29.54 31.77 31.51 31.55 31.14 30.54
2001 30.73 30.71 32.23 34.26 33.28 32.69 31.26 30.67 31.91 32.18 31.61 30.08
2002 30.32 30.27 32.36 34.50 33.89 33.95 30.22 31.69 31.67 32.51 30.45 31.14
2003 29.84 30.98 32.63 34.68 33.69 31.91 32.68 31.42 30.61 32.22 31.76 29.45
2004 30.41 31.02 32.69 34.89 33.53 31.11 32.50 30.52 32.52 31.54 30.56 29.88
2005 29.78 31.30 31.78 33.82 34.82 32.45 32.40 31.07 30.78 30.80 30.88 29.17
2006 29.79 30.94 33.10 34.85 33.72 33.79 30.39 30.29 32.44 31.87 31.80 30.62
2007 30.75 31.30 32.94 34.36 34.51 33.60 33.24 30.95 31.41 30.68 29.78 30.16
2008 30.19 29.87 32.51 33.93 32.33 33.00 32.23 31.19 31.34 31.85 30.96 29.58
2009 28.92 31.24 33.04 32.49 32.55 31.65 31.75 31.87 30.35 30.75 31.60 MD
2010 30.26 31.06 32.47 34.29 34.09 33.95 32.90 32.25 32.51 31.65 31.31 30.26
2011 29.98 30.96 31.27 32.66 34.28 32.01 31.27 31.19 31.12 32.46 31.70 29.97
2012 30.80 31.19 31.60 34.46 34.52 32.24 31.66 30.44 31.54 31.68 32.99 32.00
2013 30.16 32.02 33.01 35.35 35.05 34.07 32.68 31.05 30.48 31.20 31.37 31.32
2014 29.48 31.33 32.45 34.66 36.00 32.91 31.66 32.01 31.69 32.00 31.93 30.13
2015 29.48 30.66 32.01 34.36 35.25 34.67 32.32 32.62 32.86 32.13 32.61 30.99
2016 31.28 30.79 32.82 35.00 34.81 33.45 33.07 31.07 32.31 31.96 30.73 30.89
2017 29.74 30.04 32.16 33.83 34.39 33.61 31.77 32.53 32.22 31.60 31.73 30.49
2018 30.32 31.57 32.15 34.32 35.45 31.57 30.41 31.17 31.84 33.14 32.38 30.57
2019 30.64 31.54 33.15 35.41 34.51 34.46 32.49 30.89 31.65 33.22 31.86 31.52
2020 31.04 31.05 33.32 34.98 34.93 34.11 33.85 32.21 33.68 31.80 31.59 30.99
*NR = No reading

83
 Annex Table 2. Monthly minimum temperature (OC) at Sangley from 1990 to 2020.

Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
1990 NR NR NR NR NR NR NR NR NR NR NR NR
1991 NR NR NR NR NR NR NR NR NR NR NR NR
1992 NR NR NR NR NR NR NR NR NR NR NR NR
1993 NR NR NR NR NR NR NR 26.06 NR NR NR NR
1994 NR NR NR 25.89 26.39 25.62 24.19 24.61 24.55 25.55 24.89 24.89
1995 23.48 22.91 24.16 25.85 26.24 26.04 25.22 24.79 25.05 25.11 NR NR
1996 22.69 23.14 25.19 25.84 26.79 26.58 25.66 25.81 25.46 26.18 24.90 24.90
1997 23.25 24.18 24.07 26.29 26.24 26.42 25.53 25.36 26.13 26.12 25.72 25.72
1998 24.45 25.53 25.66 27.14 27.05 26.95 27.28 26.73 25.67 26.30 26.34 26.34
1999 24.40 23.60 25.12 26.07 26.72 25.26 25.14 25.14 25.27 25.25 24.54 24.54
2000 23.93 24.18 24.78 26.32 25.51 25.74 24.75 25.49 24.79 25.22 24.94 24.94
2001 24.41 24.68 25.12 26.61 26.51 25.93 25.31 25.35 25.94 25.83 25.01 25.01
2002 23.36 23.92 24.82 26.22 26.86 27.05 25.37 25.95 25.68 26.22 25.54 25.54
2003 24.07 24.05 25.55 27.20 27.09 26.05 26.61 25.85 25.41 26.24 25.87 25.87
2004 24.39 24.87 25.83 27.32 26.80 25.91 26.01 25.25 26.15 25.95 25.42 25.42
2005 24.10 24.78 25.41 26.32 27.83 26.57 26.70 26.10 25.76 25.86 26.38 26.38
2006 24.89 25.40 26.44 27.31 27.08 27.17 25.90 25.70 26.41 26.49 27.14 27.14
2007 25.44 24.83 25.84 26.94 27.25 27.51 26.85 26.01 26.15 25.82 24.85 24.85
2008 24.82 24.61 25.69 27.14 26.03 26.89 26.38 25.49 25.94 26.32 26.02 26.02
2009 23.71 24.77 26.01 26.40 26.59 26.01 26.00 26.93 25.66 25.92 25.69 25.69
2010 24.34 24.61 25.52 26.83 27.33 27.25 26.91 26.51 26.68 26.60 26.24 26.24
2011 24.67 24.88 25.63 25.99 27.13 26.38 26.36 26.26 25.93 25.85 25.72 25.72
2012 25.26 25.35 25.59 27.00 27.49 26.71 25.88 25.25 25.80 25.60 26.20 26.20
2013 24.18 25.05 26.06 27.74 28.03 27.10 25.93 25.53 25.47 25.68 25.92 25.92
2014 23.37 24.13 25.37 26.80 28.32 26.98 25.83 26.50 26.32 26.20 25.92 25.92
2015 23.63 24.12 25.15 26.78 31.51 27.70 26.68 26.73 26.62 26.65 26.53 26.53
2016 25.34 24.86 26.34 27.87 28.32 27.24 27.01 26.65 26.78 26.65 26.08 26.08
2017 25.07 24.50 25.85 27.17 28.28 27.75 26.79 27.14 27.10 26.61 26.49 26.49
2018 25.45 25.44 25.70 27.24 28.45 26.52 26.04 26.58 26.54 27.04 26.57 26.57
2019 24.95 24.56 25.53 27.30 27.58 27.43 26.39 26.28 25.94 26.46 25.95 25.95
2020 24.82 24.13 26.17 27.38 27.82 27.50 26.64 26.30 26.89 26.08 25.59 25.59
*NR = No reading

84
 Annex Table 3. Monthly mean temperature (OC)at Sangley from 1990 to 2020.

Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
1990 27.15 28.57 29.03 31.32 31.40 29.32 29.20 28.82 29.07 29.07 28.79 27.91
1991 27.61 28.04 28.75 30.22 31.04 29.97 28.76 27.35 NR 28.05 26.87 26.69
1992 25.88 26.50 27.85 29.38 29.60 29.15 27.48 27.40 28.69 29.04 27.63 27.88
1993 27.44 27.78 28.72 30.42 31.13 30.75 29.21 27.75 27.79 27.98 28.40 27.07
1994 26.89 27.48 28.28 29.58 29.79 28.91 27.06 28.38 28.09 28.50 28.25 27.21
1995 26.34 26.39 28.26 29.83 29.45 29.37 28.26 28.05 27.50 27.97 NR 25.98
1996 26.28 26.48 28.49 29.28 29.98 29.83 28.38 28.85 28.16 29.13 27.57 26.61
1997 26.35 27.08 27.65 30.12 29.65 29.39 27.94 27.71 28.53 29.20 28.69 27.53
1998 27.44 28.61 28.78 30.37 30.25 30.02 30.28 29.32 27.99 28.36 28.92 27.37
1999 27.26 26.87 28.85 29.48 30.16 28.27 27.89 27.72 27.79 28.01 27.32 26.76
2000 27.00 27.20 28.20 30.25 28.78 29.12 27.03 28.45 28.02 28.17 27.70 27.28
2001 27.37 27.22 28.38 30.29 29.71 29.16 27.97 27.64 28.73 28.72 27.99 26.69
2002 26.45 26.73 28.12 29.86 30.02 30.10 27.51 28.41 27.87 28.93 27.61 27.72
2003 26.44 26.96 28.39 30.42 29.76 28.79 29.18 28.02 27.64 28.76 28.51 26.33
2004 26.97 27.30 28.69 30.65 29.82 28.25 28.76 27.70 28.89 28.35 27.64 27.02
2005 26.55 27.75 28.25 29.64 30.96 29.27 29.15 28.25 27.90 28.12 28.48 26.90
2006 27.21 27.80 29.24 30.54 30.16 30.20 27.88 27.76 28.92 28.99 29.27 28.19
2007 27.78 27.55 28.90 30.30 30.28 30.13 29.51 28.06 28.43 27.97 27.19 27.45
2008 27.04 26.84 28.53 30.11 28.82 29.53 28.67 27.96 28.31 28.72 28.15 26.93
2009 25.97 27.55 28.89 29.02 29.11 28.54 28.33 29.08 27.61 28.10 28.33 27.75
2010 26.91 27.34 28.53 30.08 29.81 29.74 29.29 28.78 29.20 28.73 28.41 27.63
2011 26.72 27.29 27.77 28.90 30.04 28.78 28.33 28.39 28.26 28.83 28.49 27.48
2012 27.76 27.88 28.34 30.54 30.57 29.05 28.38 27.63 28.34 28.47 29.17 28.48
2013 26.87 28.08 29.14 31.18 30.98 30.01 29.01 28.16 27.67 28.32 28.37 28.15
2014 26.10 27.30 28.45 30.47 31.79 29.95 28.83 28.18 28.24 28.52 28.25 27.21
2015 26.10 26.81 27.96 30.04 31.12 30.72 28.99 29.36 29.34 29.12 29.29 27.85
2016 27.99 27.53 29.15 30.97 31.05 29.99 29.53 28.53 29.04 28.98 28.19 28.20
2017 26.96 26.89 28.53 30.01 30.95 30.09 28.74 29.50 29.36 28.77 28.91 27.81
2018 27.48 28.13 28.51 30.38 31.46 28.67 28.00 28.56 28.74 29.69 29.18 27.80
2019 27.38 27.60 28.75 30.62 30.32 30.28 28.84 27.98 27.93 29.39 28.30 27.92
2020 27.31 26.87 29.00 30.41 30.65 30.23 29.71 28.75 29.67 28.33 28.07 27.73
*NR = No reading
85
 Annex Table 4. Monthly rainfall depth (mm) readings at Sangley from 1990 to 2020.

Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
1990 5.50 0.00 5.50 8.40 179.90 513.30 534.40 633.60 389.70 389.70 179.10 51.80
1991 4.30 2.80 19.90 10.60 13.40 153.80 437.50 1324.30 320.70 49.40 98.50 6.00
1992 13.70 0.00 0.00 0.80 44.20 167.10 370.70 745.00 476.50 266.20 152.00 6.10
1993 2.30 0.00 0.00 16.30 11.80 334.20 410.20 400.60 242.90 158.00 153.50 122.20
1994 28.40 0.00 5.20 36.90 81.60 240.80 677.70 442.40 245.00 73.40 5.00 87.20
1995 4.60 26.60 0.00 1.20 139.90 270.30 340.00 525.40 544.60 290.90 71.10 84.30
1996 6.80 3.20 6.10 27.90 75.80 81.80 562.90 160.00 494.80 75.00 148.90 14.00
1997 7.20 24.40 2.00 7.80 523.50 186.10 351.10 754.50 135.10 52.40 3.20 0.20
1998 11.10 0.00 5.00 0.60 188.70 134.80 62.80 182.20 691.70 352.00 83.20 307.10
1999 17.70 5.80 48.30 44.00 58.20 241.00 558.80 539.60 314.20 315.10 99.20 188.50
2000 33.20 33.80 28.20 38.80 339.20 157.70 883.30 334.50 332.20 505.50 319.30 110.10
2001 48.60 75.60 18.80 21.40 135.20 292.20 281.60 605.50 198.10 104.10 83.00 65.40
2002 4.90 7.80 1.20 9.20 111.20 162.70 1596.70 197.80 313.40 84.70 179.00 13.00
2003 0.60 4.90 0.20 7.40 437.50 707.90 242.30 382.80 441.20 49.00 73.30 5.20
2004 3.20 34.40 0.00 2.70 282.40 295.40 182.10 405.30 111.40 59.10 165.40 49.20
2005 3.80 10.40 18.10 1.20 68.00 334.60 207.30 312.70 362.60 246.00 29.10 78.80
2006 77.60 1.40 30.50 0.00 65.20 93.40 559.10 377.70 437.70 132.70 83.10 177.60
2007 2.30 3.20 1.00 2.00 126.80 134.60 224.80 737.60 394.90 200.20 241.60 55.40
2008 52.60 18.20 0.80 5.60 258.40 325.70 234.20 411.80 433.10 215.40 95.60 51.30
2009 22.80 19.80 49.20 171.60 265.00 476.20 538.50 228.50 786.80 219.10 36.40 9.20
2010 5.80 0.00 10.40 45.40 36.80 151.20 355.90 375.20 291.80 444.70 240.90 98.00
2011 69.70 0.00 48.00 3.00 251.70 744.50 393.10 486.60 423.10 172.10 156.20 198.50
2012 25.20 104.20 88.50 10.50 294.30 232.00 748.00 1186.30 591.50 308.00 12.70 11.40
2013 37.60 110.00 58.40 1.40 47.40 290.90 533.00 1339.50 977.20 246.30 130.20 28.80
2014 0.40 3.30 7.20 1.20 84.50 321.40 523.40 296.80 460.30 212.90 27.80 163.20
*NR = No reading

86
Year Jan Feb Mar Apr May Jun July Aug Sep Oct Nov Dec
2015 31.80 1.00 8.80 0.00 10.20 166.80 352.80 312.60 359.20 103.60 9.20 294.70
2016 1.40 80.60 0.20 20.20 161.80 182.40 302.80 775.00 145.30 189.36 88.90 89.80
2017 52.50 5.40 6.40 39.30 186.40 105.10 467.20 323.00 382.70 196.10 116.40 57.10
2018 16.40 0.80 13.82 0.20 20.00 723.00 757.30 427.20 194.70 72.80 13.70 132.90
2019 5.70 2.00 2.40 3.60 61.90 271.10 309.80 622.90 330.10 33.20 149.80 119.50
2020 4.20 31.60 2.00 0.00 190.20 268.90 230.40 214.20 130.90 375.70 203.60 123.90

Annex Table 5. Monthly maximum temperature (OC) at CvSU Agrometeorological Station from 1990 to 2020.

YEAR Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
2007 NR NR NR NR NR NR NR NR NR NR 28.79 28.79
2008 28.85 28.66 30.92 32.66 30.21 31.01 30.43 30.42 30.51 31.39 29.76 28.36
2009 27.45 29.36 31.64 31.32 30.75 30.03 29.53 29.84 28.86 29.07 29.33 28.50
2010 28.33 30.93 31.25 32.99 32.64 31.07 30.85 30.35 28.92 29.60 29.55 28.33
2011 27.68 28.62 28.94 31.40 31.60 30.26 29.55 29.51 28.53 30.19 29.89 28.50
2012 29.08 28.92 29.66 32.57 31.63 30.53 29.25 28.83 29.72 29.74 30.53 30.05
2013 36.36 29.56 31.08 33.58 32.42 32.08 31.02 29.75 29.23 29.56 29.36 29.40
2014 27.41 29.79 31.02 33.51 33.36 31.47 29.86 30.31 29.69 29.79 30.04 27.92
2015 26.87 28.45 30.38 33.09 33.45 32.98 30.34 31.03 31.45 30.21 30.10 28.68
2016 29.35 29.10 31.88 32.91 33.40 31.79 31.77 29.82 30.72 29.86 29.33 29.13
2017 27.78 28.20 30.61 32.90 33.16 32.29 30.43 30.96 30.98 30.14 28.39 28.60
2018 28.46 29.48 30.60 33.09 34.06 30.24 29.27 29.62 30.44 31.35 30.33 28.55
2019 27.83 28.85 32.29 34.27 34.12 33.24 31.86 30.13 29.93 31.39 30.10 29.37
2020 29.28 29.06 32.81 32.54 33.63 32.99 32.10 31.05 31.83 29.39 29.69 NR
*NR = No reading

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 Annex Table 6. Monthly minimum temperature (OC) at CvSU Agrometeorological Station from 1990 to 2020.

YEAR Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
2007 NR NR NR NR NR NR NR NR NR NR 22.06 22.05
2008 21.17 21.06 21.69 23.96 22.09 22.56 25.10 22.48 22.28 22.72 22.51 21.27
2009 19.85 21.41 21.89 22.38 22.80 22.43 22.51 23.18 22.54 22.11 21.98 20.47
2010 20.62 20.83 21.87 21.63 21.56 20.98 20.38 20.15 20.23 20.64 20.15 19.51
2011 18.60 18.35 19.31 19.03 20.62 20.58 20.48 20.84 20.48 20.18 20.34 19.91
2012 19.40 19.46 19.80 20.71 20.79 20.53 20.38 21.99 21.01 20.36 20.73 19.97
2013 18.87 25.94 20.15 20.96 20.92 21.17 20.25 20.15 19.92 19.36 19.64 19.26
2014 16.45 20.00 21.54 22.77 23.78 23.50 22.87 22.53 22.25 22.12 21.81 21.23
2015 19.47 19.42 20.57 21.94 22.53 22.87 22.21 22.09 22.09 21.65 21.83 20.70
2016 20.34 20.85 21.31 23.35 23.93 23.59 22.87 23.43 23.06 22.94 22.36 22.27
2017 21.21 20.68 21.56 22.61 23.83 23.17 23.13 23.17 23.02 22.86 22.86 22.00
2018 21.56 21.24 21.62 22.97 23.98 22.81 22.88 22.85 22.65 21.76 22.43 22.06
2019 20.63 20.22 21.37 22.89 23.45 23.86 22.93 23.25 22.83 22.58 22.33 21.80
2020 21.07 26.83 22.05 22.93 23.89 23.34 22.98 23.00 23.07 22.87 22.27 NR
*NR = No reading

Annex Table 7. Monthly mean temperature (OC) at CvSU Agrometeorological Station from 1990 to 2020.

YEAR Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
2007 NR NR NR NR NR NR NR NR NR NR 24.69 25.95
2008 25.76 25.71 28.33 29.20 26.48 26.71 27.40 24.31 26.49 26.66 25.78 24.10
2009 23.40 24.69 26.05 27.08 27.30 26.92 26.79 27.06 26.23 25.81 25.37 24.29
2010 24.54 25.95 26.79 28.30 28.50 28.26 27.90 27.00 27.90 26.93 26.49 25.15
2011 24.35 24.82 25.64 26.96 28.08 27.21 26.55 26.09 27.00 26.56 26.44 25.61
2012 25.04 25.56 26.23 28.22 28.57 27.79 26.96 26.03 26.26 25.46 25.94 25.09
2013 23.49 24.17 26.05 28.10 28.26 27.86 26.66 26.38 26.00 26.03 25.46 24.21
2014 28.48 23.29 25.13 27.50 29.07 28.35 26.52 26.45 25.98 25.96 25.19 24.01
2015 22.13 22.47 24.35 27.26 28.29 28.05 26.72 26.61 27.13 26.01 25.39 24.14
2016 23.64 23.35 25.23 27.14 28.24 27.15 26.01 26.06 26.30 26.06 24.61 24.05

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2017 22.97 23.04 24.96 26.98 28.31 27.72 26.53 26.53 26.47 26.07 25.56 24.07
2018 23.60 23.86 24.96 27.01 26.49 26.01 26.02 26.06 26.43 25.67 24.20
2019 23.13 22.58 25.83 28.35 29.15 29.37 27.47 26.69 26.47 27.33 25.98 25.07
2020 24.30 23.80 26.88 28.05 28.84 28.74 27.79 27.57 27.81 26.32 25.86 NR
*NR = No reading

Annex Table 8. Monthly rainfall depth (mm) readings at CvSU Agrometeorological Station from 1990 to 2020.

YEAR Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
1990 31.50 16.54 22.32 85.70 274.72 494.57 631.94 542.30 424.52 236.22 268.16 121.62
1991 11.55 0.97 7.96 40.92 105.53 190.36 385.33 781.92 277.95 105.63 87.89 1.21
1992 23.56 3.02 6.39 43.44 142.97 220.01 382.06 529.01 422.37 237.07 174.58 17.27
1993 17.99 5.05 8.47 67.00 125.89 336.32 431.59 371.47 258.84 199.18 185.76 180.58
1994 34.87 4.56 9.94 90.52 173.31 273.65 643.45 389.41 258.02 157.96 18.82 131.75
1995 7.51 10.37 3.96 19.15 182.15 250.94 269.31 371.63 423.16 191.53 37.38 91.14
1996 21.13 7.30 10.93 81.29 171.00 172.21 556.27 255.11 446.71 162.26 181.38 34.81
1997 9.81 9.51 2.61 28.48 451.60 198.09 283.31 486.04 121.84 86.19 35.19 20.72
1998 45.00 26.42 32.25 100.55 307.88 283.21 336.96 371.88 697.50 407.58 208.22 497.81
1999 15.80 3.70 13.89 69.44 123.94 230.30 442.35 376.42 249.93 200.17 66.55 230.65
2000 61.35 50.28 42.75 150.48 417.57 304.19 1014.28 454.40 438.73 486.90 477.91 236.81
2001 66.76 72.84 34.19 117.65 261.77 374.36 485.82 561.96 315.08 276.72 192.95 161.02
2002 4.42 5.28 6.90 20.61 153.03 168.79 1255.48 195.58 235.08 79.01 141.45 15.68
2003 28.26 19.78 20.34 84.55 454.66 621.60 396.18 420.31 462.86 214.25 150.93 58.69
2004 23.48 32.56 13.52 62.79 328.36 328.79 290.32 398.42 185.48 181.90 222.16 97.45
2005 8.73 1.51 4.71 23.50 136.80 299.28 177.57 276.95 296.72 181.06 0.85 89.29
2006 74.20 12.18 26.38 62.67 180.17 201.60 605.90 391.34 434.13 222.56 136.87 275.02
2007 42.18 31.59 33.88 109.75 273.05 294.12 494.50 657.57 492.14 355.70 324.80 117.00
2008 82.20 25.30 42.30 94.10 264.00 391.50 277.60 262.10 378.70 176.90 92.60 48.10
2009 37.60 34.10 74.50 275.00 286.80 420.90 516.80 331.70 791.50 350.10 66.20 13.80
2010 21.90 0.00 4.00 50.20 107.60 264.70 519.40 288.70 76.60 171.90 106.50 61.70
2011 25.40 5.20 18.00 18.60 254.00 613.10 459.10 636.80 404.70 259.90 134.60 154.90
2012 62.90 57.10 26.10 12.40 340.70 299.40 734.40 821.30 418.20 300.80 27.30 26.40
2013 56.20 118.70 28.40 78.90 246.70 195.80 151.40 733.90 811.00 185.20 215.60 37.30

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2014 0.00 1.30 6.60 139.20 142.40 285.60 574.70 317.40 397.80 127.40 31.20 261.90
2015 39.60 5.30 1.80 33.80 149.20 322.60 660.50 344.80 311.40 251.20 30.60 428.20
2016 5.20 18.10 0.00 36.60 191.80 184.80 287.20 546.60 295.20 389.00 119.70 148.00
2017 43.90 18.80 16.80 86.20 304.00 240.50 342.60 354.10 404.90 194.80 190.40 106.90
2018 24.30 1.80 0.30 8.20 80.60 633.00 830.70 414.90 278.10 40.50 18.70 271.70
2019 18.60 6.20 0.00 36.10 134.30 297.20 455.60 501.70 298.00 68.10 92.20 197.10
2020 14.00 22.10 4.40 112.20 334.90 171.10 143.60 152.10 248.80 413.90 461.10 283.90

Annex Table 9. River segments and its stream order within the Imus River Watershed.

Stream River Highest Point Lowest Point

Order Segment
Point Elevation x y Point Elevation x y Length
1 1-3 1 619.2713 14° 6'42.92"N 120°57'8.71"E 3 463.8022 14° 9'24.35"N 120°57'39.62"E 5046.02
1 2-3 2 490.6514 14° 9'7.76"N 120°57'29.77"E 3 463.8022 14° 9'24.35"N 120°57'39.62"E 593.45
1 4-6 4 480.845 14° 9'22.49"N 120°57'57.96"E 6 374.6301 14°11'13.82"N 120°58'16.49"E 3455.91
1 5-7 5 393.1259 14°10'58.16"N 120°57'53.62"E 7 371.1261 14°11'22.03"N 120°58'9.85"E 869.47
2 3-59 3 463.8022 14° 9'24.35"N 120°57'39.62"E 59 31.22159 14°22'22.69"N 120°56'31.56"E 24004.50
1 13-14 13 145.0812 14°18'23.92"N 120°59'13.72"E 14 133.9903 14° 18.603'N 120° 59.055'E 480.09
1 12-14 12 148.613 14° 18.329'N 120° 59.118'E 14 133.9903 14° 18.603'N 120° 59.055'E 520.31
1 11-16 11 149.663 14° 18.044'N 120° 58.916'E 16 124.3484 14° 18.776'N 120° 58.920'E 1352.01
1 17-18 17 129.7673 14° 18.725'N 120° 58.789'E 18 113.1687 14° 18.826'N 120° 58.684'E 269.93
1 8-17 8 234.711 14° 15.488'N 120° 59.049'E 17 129.7673 14° 18.826'N 120° 58.684'E 6177.91
1 15-19 15 134.8011 14° 18.287'N 120° 58.290'E 19 106.6481 14° 18.642'N 120° 57.908'E 934.09
1 9-22 9 193.35 14° 16.528'N 120° 58.253'E 22 98.39375 14° 18.971'N 120° 57.705'E 4611.45
1 10-23 10 154.1908 14° 17.331'N 120° 57.734'E 23 80.96656 14° 19.516'N 120° 57.397'E 4133.18

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2 14-21 14 133.9903 14° 18.603'N 120° 59.055'E 21 105.7208 14° 19.146'N 120° 58.691'E 1200.74
2 18-21 18 113.1687 14° 18.826'N 120° 58.684'E 21 105.7208 14° 19.146'N 120° 58.691'E 588.31
1 20-44 20 118.0377 14° 18.832'N 14° 18.832'N 44 41.54596 14° 21.588'N 120° 56.563'E 5743.63
1 30-39 30 81.90814 14° 19.637'N 120° 56.697'E 39 55.30947 14° 20.561'N 120° 56.031'E 2080.05
1 31-39 31 80.56731 120° 56.031'E 120° 56.344'E 39 55.30947 14° 20.561'N 120° 56.031'E 1864.71
1 40-47 40 63.21944 14° 20.400'N 120° 55.894'E 47 39.73262 14° 21.616'N 120° 55.748'E 2263.46
2 39-80 39 55.30947 14° 20.561'N 120° 56.031'E 80 0.7 14° 26.517'N 120° 55.910'E 10984.86
1 43-46 43 55.53639 14° 21.077'N 120° 56.297'E 46 39.55898 14° 21.500'N 120° 55.802'E 1181.87
1 35-38 35 83.22163 14° 20.285'N 120° 57.548'E 38 54.51525 14° 21.007'N 120° 57.260'E 1427.96
1 28-38 28 100.3311 14° 19.768'N 120° 58.062'E 38 54.51525 14° 21.007'N 120° 57.260'E 2071.82
1 32-34 32 89.2032 14° 20.251'N 120° 57.963'E 34 83.22689 14° 20.463'N 120° 57.917'E 398.58
1 29-34 29 95.72849 14° 20.002'N 120° 58.183'E 34 83.22689 14° 20.463'N 120° 57.917'E 975.71
1 33-42 33 98.33135 14° 20.313'N 120° 58.199'E 42 46.90046 14° 21.535'N 120° 57.526'E 2545.65
3 21-45 21 105.7208 14°19'8.76"N 120°58'41.46"E 42 46.90046 14°21'44.51"N 120°56'57.15"E 5696.84
1 27-36 27 109.9995 14°19'49.19"N 120°58'44.73"E 36 75.14953 14°20'55.02"N 120°58'41.76"E 2012.85
2 25-26 25 112.2812 14°19'40.95"N 120°59'4.33"E 26 95.35459 14°19'59.17"N 120°59'6.83"E 583.82
1 24-26 24 105.8878 14°19'41.86"N 120°59'12.98"E 26 95.35459 14°19'59.17"N 120°59'6.83"E 562.24
2 26-72 26 95.35459 14°19'59.17"N 120°59'6.83"E 72 7.604295 14°24'49.42"N 120°56'48.71"E 9833.47
2 34-41 34 83.22689 14°20'27.76"N 120°57'54.99"E 41 49.82454 14°21'13.66"N 120°57'13.20"E 1888.49
2 38-41 38 54.51525 14°21'0.42"N 120°57'15.60"E 41 49.82454 14°21'13.66"N 120°57'13.20"E 409.92
1 48-60 48 44.66206 14°21'39.67"N 120°56'8.90"E 60 29.25159 14°22'17.06"N 120°55'54.23"E 1233.53
3 41-45 41 49.82454 14°21'13.66"N 120°57'13.20"E 45 37.939 14°21'44.51"N 120°56'57.15"E 1064.68
1 37-52 37 68.0992 14°21'28.11"N 120°58'45.43"E 52 47.41051 14°22'16.19"N 120°58'22.07"E 1610.23

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 1 51-55 51 52.76982 14°22'6.98"N 120°57'45.77"E 55 30.73618 14°22'50.12"N 120°57'51.56"E 1344.09
1 56-66 56 37.26807 14°22'53.59"N 120°57'39.53"E 66 13.27068 14°23'50.29"N 120°56'46.92"E 2343.48
1 57-63 57 38.37227 14°22'39.23"N 120°57'28.07"E 63 18.47463 14°23'12.35"N 120°56'47.78"E 1576.16
1 58-62 58 35.36711 14°22'36.18"N 120°57'2.61"E 62 19.15739 14°23'9.71"N 120°56'46.15"E 1145.03
1 50-61 50 42.78047 14°22'8.49"N 120°57'15.23"E 61 21.46007 14°22'55.82"N 120°56'37.26"E 1845.97
1 49-49.5 49 46.88607 14°21'52.42"N 120°57'5.37"E 49.5 33.35084 14°22'6.19"N 120°56'46.05"E 720.53
4 45-83 45 37.939 14°21'44.51"N 120°56'57.15"E 83 0 14°27'36.61"N 120°55'20.80"E 11239.10
1 53-68 53 49.90404 14°22'32.34"N 120°58'37.75"E 68 23.32995 14°24'12.32"N 120°57'36.08"E 3614.09
1 54-68 54 48.21714 14°22'39.25"N 120°58'26.37"E 68 23.32995 14°24'12.32"N 120°57'36.08"E 3201.68
1 64-67 64 34.90218 14°23'28.40"N 120°57'58.58"E 67 15.87711 14°24'12.08"N 120°57'19.54"E 1777.35
1 65-71 65 30.7222 14°23'55.80"N 120°58'21.85"E 71 13.64192 14°24'56.61"N 120°57'19.85"E 2634.23
1 69-70 69 15.72534 14°24'28.48"N 120°56'45.31"E 70 10.06625 14°24'44.87"N 120°56'50.86"E 530.68
2 68-81 68 23.32995 14°24'12.32"N 120°57'36.08"E 81 0.76653 14°27'18.08"N 120°55'58.74"E 6713.32
1 73-74 73 11.90761 14°25'11.82"N 120°57'21.39"E 74 7.442218 14°25'49.65"N 120°56'54.36"E 1419.57
1 75-78 75 5.143465 14°26'8.40"N 120°56'47.03"E 78 2.561378 14°26'46.01"N 120°56'26.27"E 1311.24
1 77-78 77 3.051099 14°26'30.27"N 120°56'25.19"E 78 2.561378 14°26'46.01"N 120°56'26.27"E 492.98
2 78-81 78 2.561378 14°26'46.01"N 120°56'26.27"E 81 0.76653 14°27'18.08"N 120°55'58.74"E 1285.42
1 76-79 76 4.254199 14°25'55.45"N 120°56'4.57"E 79 1.035759 14°26'28.11"N 120°56'1.16"E 1019.98
3 81-82 81 0.77 14°27'18.08"N 120°55'58.74"E 82 0.20248 14°27'19.75"N 120°55'40.78"E 523.11

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