Flood Hazard: A QGIS Plugin for Assessing Flood

Consequences

Shashikant Verma1, Darshan Mehta2, Ashutosh Pandey3, Shree Ram Malani4,

and Rakesh Pandey4 (2024)
1
National Institute of Technology, Raipur, India
2
Dr. S. & S. S. Ghandhy Government Engineering College, Surat, India
3
Kalinga University, Raipur, India
4
MATS University Aarang, Raipur, India

DOI: https://doi.org/10.14796/JWMM.C529

ABSTRACT
Flash floods cause substantial harm to the social and economic aspects of the affected
countries. This is a significant problem in urban areas where drainage systems are inadequate
and unable to withstand severe flooding. Understanding the specific regions that are
susceptible to flooding is essential to implement strategies aimed at mitigating the risk.
Detecting floods in ungauged basins is challenging. The current work aims to establish a
practical method for identifying and mapping floodplain areas. We can use several tools,
including the FLO-2D integration tool, Flood Risk tool, Geomorphic Flood Area plugin, and
Quantum Geographical Information System (QGIS) with Hydrologic Engineering Centre River
Analysis System (HEC-RAS) to efficiently and cost-effectively detect flood hazard zones. The QGIS
tool, the Geomorphic Flood Index (GFI), is the most valuable tool for identifying flood-prone
areas in cases where the areas are extensive and lack sufficient data. This tool offers high data
analysis and cost calculation precision while using few resources.

1. INTRODUCTION
Floods are intricate phenomena, with variations in frequency and nature of occurrence. A flood
is the result of a significant increase in the volume of water in rivers and streams, causing the
water to exceed the boundaries of their natural and man-made banks (Rostvedt et al. 1972).
India experiences significant flooding from monsoons, which are a widespread hazard around
the world (Domeneghetti et al. 2015). Floods can originate from a variety of sources, typically
caused by multiple influential elements in the valley and offshore regions. The impact they have
on the ecosystem is determined by the size and frequency of the floods. The United Nations
(UN) defines a flood as a significant disruption that causes economic, societal, material, and
__________________________________________________________________________________________________
Verma, S., D. Mehta, A. Pandey, S. Malani, and R. Pandey. 2024. "Flood Hazard: A QGIS Plugin for Assessing Flood
Consequences." Journal of Water Management Modeling 32: C529. https://doi.org/10.14796/JWMM.C529
www.chijournal.org ISSN: 2292-6062 © Verma et al. 2024

This work is licensed under a Creative Commons Attribution 4.0 International License
environmental damage that surpasses the available resources to cope with them (Schanze
2006). Based on historical data, floods can be classified into three categories: ‘impact events’
such as floods, earthquakes, tropical storms, and volcanic eruptions; 'slow-impact' events like
drought and starvation; and 'epidemic illnesses' such as cholera, measles, and plague (Getahun
and Gebre 2015). However, typically, approximately 15% to 20% of rainwater passes into surface
runoff and flows into rivers. The residual water infiltrates into the soil and encounters
groundwater or is released back into the atmosphere by transpiration and evaporation from
vegetation. Elements such as climate, slope, soil, rock type, and vegetation influence the
rainfall-runoff ratio, which varies from 2% to 25%. Persistent precipitation can saturate the
ground and the air, sometimes resulting in floods, as the excess water runs down, encompassing
the entirety of the rainfall. We take prompt action based on timely and precise information on
the event's magnitude to mitigate the impact of flood disasters (Merz et al. 2010). A flood event
occurs when a significant volume of water exceeds the capacity of natural streams, canals, or
the sea, causing water to overflow into places where drainage is inadequate. A flood occurs
when an abundance of precipitation occurs without prior notification. Consequently, this leads
to the overflow of lakes, dams, and rivers, causing significant harm to humans, infrastructure,
and other organisms.
Field (2012) suggests that an increase in the frequency and intensity of severe events like floods
will be one of the most significant effects of climate change. The objective of flood risk
management is to mitigate the consequences of floods. Quantifying and evaluating the
consequences of floods is crucial for determining how to minimize flood damage and assess the
relative advantages and costs of different intervention options (Albano et al. 2014). Within this
framework, we created a freely available analysis toolbox, a component of the open-source
geographic information system Quantum GIS, to assess flood consequences and assist
authorities in gaining a deeper understanding of and effectively managing flood risk (Mancusi et
al. 2016). We do not design these tools to be commercially viable software programs. However,
other parties can use them for assessment and demonstration. The "Flood Risk" prototype
software application can compute and display the impact of a flood scenario on the population
and property damage in a selected area. For instance, if there is a requirement to implement
measures to guarantee the safety of various hydraulic structures, such as dams or levees, which
could potentially pose a risk downstream, it is crucial to determine the criteria for prioritizing
the interventions. When evaluating the outcomes of failures or accidents, it is crucial to
consider the implications as a key factor in determining the priority of solutions. This is
particularly accurate considering the restricted financial resources that are accessible.
The objective of this study is to conduct a comprehensive evaluation of the current literature
about the utilization of the QGIS tool in the field of flood catastrophe management. The study
examines the various categories of flooding, the factors that contribute to its occurrence, and
the social and economic consequences. Additionally, it explores methods for reducing the risks
and dangers associated with floods. The several forms of floods are listed below in detail:

1.1 River floods

The primary form of natural disaster is river flooding. Flooding occurs when rivers exceed their
maximum capacity due to excessive water inflow. The excess water breaches the river banks
and other protective barriers, flowing into lower-lying areas. River floods result in significant

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human casualties, damage to infrastructure, and economic losses for the nation (Jodhani et al.
2024a). Seasons do not limit river flooding; it can occur at any time. However, the most frequent
occurrence of flooding occurs during periods of high rainfall in the monsoon season, as well as
occasionally due to snowmelt. Rupinder (2008) defines a flood as a persistent and inevitable
occurrence in rivers. Flooding occurs when high rainfall and precipitation, including melted
snow, combined to inundate the river valley with water. Furthermore, intense rainfall from
cyclones or tropical systems can also lead to river flooding (Jodhani et al. 2021).

1.2 Coastal floods

Coastal floods, which are natural phenomena, occur when the sea level rises significantly above
the usual tidal level, flooding coastal regions. Storms, high tides, and tsunamis can trigger these
occurrences. Coastal flooding can have severe implications, causing significant damage to both
human populations and the ecosystem. Coastal floods pose a severe threat to infrastructure in
densely populated coastal regions, such as cities or towns (Jodhani et al. 2024b; Jodhani et al.
2023a; Jodhani et al. 2023b). Residences, commercial establishments, and vital infrastructure
may experience inundation resulting in the relocation of inhabitants, financial setbacks, and
interruptions to crucial services. Furthermore, coastal ecosystems, such as marshes and
estuaries, are susceptible to the detrimental impacts of flooding. The incursion of saltwater into
freshwater areas can have detrimental effects on local plant and animal life, causing
disturbances to fragile ecological equilibriums. Climate change-induced sea level rise and
alterations in weather patterns are expected to increase the frequency and severity of coastal
floods. Increasing global temperatures cause polar ice caps to melt and saltwater to expand due
to heat, which worsens the dangers of coastal flooding around the world. Therefore, it is
essential to implement efficient coastal management methods, such as measures to protect
shorelines, early warning systems, and sustainable land use planning, to reduce the effects of
coastal floods and protect vulnerable coastal communities and ecosystems.

1.3 Urban floods

Urban floods occur when an abundance of rainfall surpasses the ability of urban drainage
systems to handle it, resulting in waterlogging and flooding of city streets, buildings, and
infrastructure (Rafiq et al. 2016). The floods are worsened by factors such as non-porous
surfaces, insufficient drainage systems, increased urbanization, and intense weather events
caused by climate change (Verma et al. 2024). Urban floods have a variety of complex and
serious effects (Tinsanchali 2012). They can disturb transportation networks, resulting in traffic
jams and delays, as well as causing harm to cars. Moreover, urban floods provide substantial
hazards to public health, as the presence of polluted water can lead to the transmission of
diseases and harmful substances. Urban flooding often leads to economic losses resulting from
property damage, business interruptions, and infrastructure repairs. Urban flood mitigation
efforts commonly entail a blend of infrastructure enhancements, such as the enhancement of
drainage systems and the creation of retention ponds, as well as land-use planning measures,
such as the preservation of natural water retention areas and the implementation of green
infrastructure solutions like rain gardens and permeable pavements. Nevertheless, despite the
implementation of these measures, the growing occurrence and intensity of urban floods
emphasize the immediate need for all-encompassing, integrated strategies in urban planning,
infrastructure development, and adaptation of climate change (Tandel et al. 2023). These

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strategies aim to construct more resilient cities that can withstand the difficulties presented by
urban flooding.

1.4 Flash floods

A flash flood happens when there is unexpected and heavy rainfall. Floods are caused by high
rainfall over a short period (Collier 2007). A variety of factors can cause flash floods, but heavy
rainfall from thunderstorms is the main contributor. Flash floods may occur due to dam or levee
ruptures. A variety of factors, such as the intensity, location, and distribution of rainfall, land
use, topography, vegetation types and density, soil type, and soil water content, can determine
flash flooding (Ozger 2017). Urban areas are susceptible to swift floods, primarily due to rainfall.
Urban environments characterized by impermeable layers impede the rapid drainage of water,
resulting in the swift movement of water toward lower-elevation locations (Jodhani et al. 2024c;
2024d). Flash flooding is a highly dangerous event characterized by the presence of a substantial
volume of swiftly moving water.

1.5 Identification of Flood Hazard Areas

The identification of flood hazard zones is necessary to determine the specific locations that are
at risk of flooding. Maps can be constructed that accurately pinpoint locations inundated by
floodwaters by utilizing historical river data, information on previous flood volumes, and
topographical data (Azharuddin et al. 2022). Flood hazard mapping is necessary for identifying
locations prone to flooding and the elements that contribute to the risk, especially in the
context of development plans. We implement various policies and guidelines to reduce and
control hazards in specific locations. To develop a flood danger map, it is essential to have
efficient and cost-effective administrative units that can accurately and swiftly prepare
counteractive strategies. Obtaining aerial photographs and satellite images of the flood-affected
area, both before and after the occurrence, is necessary to facilitate the process of adapting
flood management strategies. These visual materials are essential for creating accurate and
effective flood maps. We created a theoretical map based on this data, representing a flood
with a return period of 10 years, a flood with a return period of 50 years, and a flood with a
return period of 100 years. We also develop scale models to pinpoint locations vulnerable to
flooding. Only synchronizing these models with flood occurrences promptly makes them
effective. In response to the flood dangers in 1954, the Government of India implemented
several measures and established multiple committees to address and oversee the issue of
flooding in the country. To reduce the impact of floods, stakeholders and implementers have
developed several guidelines to identify the most crucial areas affected. The National Disaster
Management Authority (NDMA) is responsible for overseeing disaster management. We have
used satellite images from IRS, LANDSAT, ERS, and RADARSAT for flood monitoring. Wide Field
Sensor Images (WiFS) data from IRC-1C and 1D is suitable for improving flood monitoring
accuracy, particularly on a geographical scale. We conduct the assessment of flood threats by
integrating geographical, hydrological, and environmental data (Ozger 2017).

1.6 Importance of flood hazard assessment

An assessment of flood hazards is essential for comprehending and reducing the dangers posed
by floods. The purpose of this tool is to identify regions that are susceptible to flooding,

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evaluate the potential consequences on communities, infrastructure, and the environment, and
provide information for land use planning and disaster preparedness plans (UNDRR 2021).
Assessments offer vital insights for designing successful flood risk management plans by
analyzing elements such as rainfall patterns, geography, river flow, and infrastructure
vulnerabilities. According to Sayers et al. (2013), they facilitate the implementation of early
warning systems, evacuation strategies, and enhancements to infrastructure, which can
effectively mitigate the loss of human lives and property damage caused by flood catastrophes.
In addition, flood hazard assessments have a role in enhancing resilience to the impacts of
climate change, particularly as shifting weather patterns increase flood hazards on a worldwide
scale (IPCC 2021). Consequently, it is imperative to allocate resources toward thorough
evaluations of flood hazards to promote sustainable development, mitigate disaster risks, and
protect communities from the growing menace of floods.

2. QUANTUM GIS TOOLS

Quantum GIS (QGIS), an open-source geographic information system (GIS) program, allows
users to view, organize, modify, examine, and share geographical data. This software offers a
wide range of tools for a variety of GIS activities, from basic mapping to sophisticated spatial
analysis. The core of QGIS tools is their user-friendly interface, which enables users to
effortlessly access and employ a wide range of features. QGIS offers a user-friendly interface for
dealing with spatial data, suitable for both experienced GIS professionals and beginners. QGIS
provides a wide range of tools for data input, including the ability to work with many file types,
such as shapefiles, GeoTIFFs, and GPS data. Users can import data from various sources, such as
online services like OpenStreetMap and WMS/WFS servers. This allows for the smooth
integration of external data into GIS applications. QGIS offers a wide range of geoprocessing
tools that are highly useful for manipulating and analyzing data. These technologies allow users
to carry out spatial operations such as buffering, overlay analysis, and spatial joins, which make
complex geographical analysis workflows easier. Furthermore, QGIS provides robust support for
sophisticated geostatistical analysis, allowing users to interpolate data, execute spatial
regression analysis, and undertake terrain analysis. QGIS provides tools for map creation,
arrangement, and visual design. Users can generate visually attractive maps by customizing the
symbols, labels, and arrangements. In addition, QGIS has map composer capabilities, enabling
users to create high-quality maps suitable for presentations and publications.
For complete analysis and planning, a variety of data formats and sources are required in flood
hazard assessment. Digital elevation models (DEMs) provide critical topographic data for
understanding land characteristics and water flow direction. Hydrological models replicate river
flow behavior and predict flood situations using data such as rainfall, soil composition, and land
surface characteristics (Jha et al. 2024). River gauge data provides up-to-date or historical
readings of river levels, aiding in flood prediction and surveillance. Land use/land cover maps
aid in assessing surface attributes that affect water flow and flooding vulnerability (Rimba et al.
2017). Precipitation data, which includes records of rainfall and snowmelt, are crucial for
evaluating the magnitude and timing of precipitation events that have the potential to cause
floods.
Geographic Information Systems (GIS) widely employ geospatial data formats such as shapefiles,
GeoTIFFs, and raster datasets for the storage and analysis of various data types. In addition,

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databases such as PostgreSQL quickly store massive datasets, making it easier to do
geographical queries and analytics. The integration of multiple formats and sources enables a
thorough comprehension of flood dangers, facilitating the implementation of efficient risk
management and mitigation measures in areas that are susceptible to such hazards.
The process of incorporating diverse data sources into QGIS plugins might vary in terms of
difficulty, contingent upon the format and compatibility of the data sources. QGIS has extensive
support for several data types, such as shapefiles, GeoTIFFs, CSVs, and databases like
PostgreSQL and SQLite. QGIS provides developers with a powerful API and comprehensive
documentation that facilitates the task of accessing and processing various data sources within
plugins. In addition, QGIS plugins can utilize Python scripting, enabling developers to effortlessly
incorporate APIs, online services, and real-time data feeds. Nevertheless, difficulties may
develop when managing proprietary or less prevalent formats that necessitate supplementary
libraries or customized treatment. In general, QGIS's adaptability and assistance from the
community make it reasonably simple to include various data sources in plugins, hence
improving its usefulness for a wide range of spatial analysis and mapping tasks (Jodhani et al.
2023c).
Additionally, users can modify parameters and models within QGIS plugins to accommodate
specific local conditions or scenarios. QGIS plugins frequently offer configurable settings and
choices in their interfaces, enabling users to adjust factors such as input data sources, spatial
extents, analysis methods, and output formats. In addition, developers can design plugins that
incorporate adaptable algorithms and models, allowing for customization to different
geographic, environmental, or administrative conditions. Users can utilize this flexibility to
customize studies and simulations according to their individual needs, thereby making QGIS
plugins highly adaptable tools for processing geographical data and making informed decisions
in many applications.

2.1 FLO-2D tool

FLO-2D is a highly efficient flood simulation tool that is cost-effective and user-friendly. This
model is advantageous for modeling intense urban flooding because it includes comprehensive
information, including storm drainage. FLO-2D provides data regarding the preservation of
volume, velocity, and numerical stability. This plugin is highly beneficial for modeling floods
caused by heavy rainfall.

2.2 Flood risk tool

The flood risk GIS tool is advantageous for creating risk maps and assessing both current and
projected flood risk due to its versatile applicability (Albano et al. 2017; Dhiwar et al. 2022). This
plugin employs a framework based on 2D inundation modeling. It considers various return
periods as inputs and determines the extent to which structural and non-structural solutions
can reduce the financial impact of floods on households (Kale 2003).

2.3 Geomorphic flood area

The QGIS tool, Geomorphic Flood Index (GFI), is the most valuable tool for identifying flood-
prone locations when dealing with broad areas that lack sufficient data. This program offers high

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levels of accuracy in data analysis and cost calculation while using few resources. We determine
the index by dividing the water depth in the river basin nearest to the research regions (derived
using hydraulic scaling) by the elevation difference between these two places.

3. FLOOD HAZARD: CONCEPTUAL TOOL

3.1 General: Flood hazard—Framework for assessing flood consequences

The definition of "hazard" is broad and encompasses various aspects of social, economic,
environmental, and safety concerns. Various fields and contexts have used the term "risk",
potentially leading to a misinterpretation of the technical terms used in risk assessment. It is
helpful to think about a basic conceptual model to comprehend the relationship between
hazard and risk: for a risk to materialize, there must be a hazard, which is composed of a
"source" or initiator event (such as heavy rainfall); a "receptor" (such as flood plain properties);
and a receptor's vulnerability (Gouldby et al. 2005). Although the presence of a hazard does not
guarantee negative consequences, it does indicate that harm may occur. The degree of
exposure to the risk and the receptor's properties determines the actual injury. Risk can be
simple, and can be understood as "probability times damage," describing the expected damage
that can occur or will exceed a certain probability in a specific period. Awareness of the
consequences often captures exposure and vulnerability (Merz et al. 2010).

Figure 1 depicts the conceptual framework for flood hazard assessment. This architecture
integrates the proposed GIS tool, which focuses on evaluating the repercussions and facilitating
the execution of the operations outlined in the final section of the diagram. Thus, "Flood
Hazard" can facilitate the identification of individuals and resources that are vulnerable to
flooding, the strategic planning and assessment of efficient flood prevention and management
strategies, and the development of flood risk maps to enhance public awareness.

Figure 1 Framework for flood hazard assessment.

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4. METHODOLOGY
The Geomorphic Flood Assessment (GFA) tool categorizes results into two groups: areas
susceptible to flooding and those not susceptible to flooding (Samuels and Gouldby 2009).
Equations 1 and 2 display the specified index.
Ln = (hr/H) (1)
Where:
hr = Water level in the nearest element of the river network, and
H = Elevation difference between these two points.

hr = Ar² (2)
Where:
A = Area affected by flood, and
r = Radius.

The key input data for this method includes a Digital Elevation Model (DEM) used to generate
the flood index and a specific flood risk map often obtained by the ordered weighted averaging
method. An ordered weighted average (OWA) method is used to create a flood hazard map
through multi-criteria evaluation. The outcomes are dependent on the weight allocation for a
specific criterion. We assign the weights based on the relative significance of one choice over
another. Correspondingly, the criteria’s values are linked to changes in order weight. They
allocate attribute values in a diminishing pattern, based on various situations. We have
completed the re-ordering process to provide ordered values based on specific weighted
attribute values. We assign the initial weight value based on each location’s highest weighted
attribute values and subsequent weight values in descending order to the next highest values.
The raster data model assigns the same factor weight to each pixel. These factors have explicit
parameters that validate the objectives.
For the ordered weighted averaging approach, it is necessary to assign a weight value to each
layer that is considered. Multiply the input layer by this weight value. To generate the final
output map, combine all layers and select the "SAGA geo algorithm" from the processing tools.
Then, click on "Grid Analysis." This completes the process of assigning the output map name
and implementing the ordered weighted averaging approach (Seejata et al. 2018). The tool
utilizes data to analyze physical characteristics to calculate various intermediate variables for
each basin area (each pixel of DEM). These variables include i) the change in surface elevation,
G; ii) the drainage network; iii) the hydrological paths; iv) the difference in elevation between a
given location and the nearest point on the drainage network, H; and v) the areas near the
drainage network, Ar. We use the outputs to estimate the GFI and then normalize the resulting
values within the 1:1 range (Seejata et al. 2018). Flood maps are generated by applying a
threshold value, τ, to the flood index. We use this parameter to validate and compare the flood
map with standard flood maps. This evaluation assesses the given presentation by examining
the rates of true positives (TP), false positives (FP), true negatives (TN), and false negatives (FN).
The threshold values serve to differentiate the flooded areas from the non-flooded areas within
a certain basin. This value is used to precisely identify large basin areas that have been impacted
by flooding.

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4.1 Analysis methods
The study employed a remote sensing technique utilizing the Quantum GIS program (Figure 2).
QGIS utilizes data from the Shuttle Radar Topography Mission (SRTM) and the Digital Elevation
Model (DEM) for the study. This data was carefully examined and modified to meet the mapping
projection's requirements, using the UTM WGS 1984 coordinate system (Ariyani 2023).

Figure 2 Methodology.

4.2 Digital Elevation Model (DEM)

A DEM serves as a foundation for determining various topographical characteristics of
watersheds, including catchment area, slope, river flow, and land elevation (Janizadeh et al.
2021; Elmoustafa 2012). Every watershed possesses distinct topographic features that
additionally impact the gradient, river discharge, and altitude.

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Slope factor
Slope is a significant factor contributing to flooding. Surface inclination can enhance the
accuracy of threat indicators for flash flooding in susceptible regions. According to Elmoustafa
(2012), the slope of the land affects how sensitive a watershed is to the velocity of water flow.

River discharge
Using the buffer method, the river flow analysis determines the appropriate distance from the
river. Lee et al. (2021) employs the buffer method to control the river's dispersion within the
designated right and left buffer zones. The implementation of water safety distance can be
viewed as a qualitative method that enhances access to open space. This approach benefits
different groups of humans and ecosystems by effectively managing flood dangers (Münch et al.
2016).

Elevation factor
Land elevation refers to the vertical distance observed from sea level and is often measured in
meters or feet. Five distinct classes divide the elevation categorization. Areas with lower
elevations have a higher susceptibility to flooding, while sites situated at higher elevations offer
greater safety from flood disasters. This occurs because the water moves about the lower
elevation areas. Low-lying locations are more prone to flooding due to their geographical
position and higher altitude, as stated by Seejata et al. (2018).

4.3 Landsat 8
NASA launched Landsat 8 in 2013, which plays a crucial role in the field of Earth observation.
NASA and the US Geological Survey (USGS) jointly manage this satellite, which plays a crucial
role in monitoring and comprehending the constantly changing surface of our planet. Landsat 8
utilizes the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS) to capture
high-resolution multispectral images with exceptional precision and level of detail. The
extensive data provided by this resource enables a wide range of applications, such as
agriculture, forestry, urban planning, and environmental monitoring. The 30-meter resolution
imagery of Landsat 8, together with its worldwide coverage and consistent data collection over
time, allows scientists, governments, and industries to observe changes in land use, monitor
natural disasters, and evaluate the effects of climate change. Landsat 8 plays a vital role in Earth
observation, helping us get a better understanding of the planet and make important decisions
for its sustainable management (Tian et al. 2015; Deng et al. 2019; Breinl et al. 2021).

4.4 CHIRPS
The CHIRPS database is a comprehensive compilation of infrared rainfall data that combines
three different sources of rainfall information: global climatology, satellite rainfall predictions,
and in-situ rainfall observations (Sahu et al. 2024; Sahu et al. 2022). This study utilizes the
CHIRPS map to visualize the millimeter-measured precipitation levels in the watershed. The
magnitude of precipitation is crucial in determining the subsequent flow of water during a
flood, both in practical and theoretical terms (Breinl et al. 2021).

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4.5 Digital Soil Map World (DSMW)
To assess the various soil types in the Bangko and Masjid watersheds and their susceptibility to
rainwater penetration. The properties of soil, such as its type, texture, and permeability, dictate
the extent to which rainfall can infiltrate before reaching its capacity and contribute to flood
vulnerability. Certain soil types can produce runoff rapidly, even in arid conditions, without
allowing water to penetrate the soil. Clay exhibits greater velocity and coverage of runoff
compared to sand when subjected to intense rainfall (Butt et al. 2015; Elkhrachy 2015).

5. CURRENT CHALLENGES, POSSIBLE SOLUTIONS, AND FUTURE APPROACH

The main objective of this study is to develop a streamlined approach or method that can
generate accurate flood susceptibility maps in locations with limited data and for large-scale
applications. The geomorphic flood plug-in in QGIS is a valuable tool for identifying areas
affected by floods in environments with little data. This plug-in, predicated on the DEM, requires
a flood danger map to comprehend the places that have been impacted by a flood event. The
correctness of this method is entirely contingent upon the quality and resolution of the digital
elevation model utilized. To accurately determine the extent of a flood plain, it is necessary to
have a high-resolution digital elevation model and a precise flood risk map for validation
purposes. This approach is highly advantageous in situations where data is scarce, and one
needs to utilize freely accessible DEMs that have a reasonable level of resolution. In data-scarce
environments where flood hazard maps are lacking, one can utilize the ordered weighted
averaging approach in QGIS, together with the GFA tool, to create a flood hazard map. This map
will effectively identify locations that are prone to flooding.

6. CONCLUSIONS
QGIS tools are highly valuable for conducting a preliminary and efficient delineation process
that is cost-effective, requires minimal computational time, and has straightforward data
requirements. Interlinking conventional maps might be utilized to bridge the gap. It can also be
utilized in unmeasured basins, and GFI tools can be advantageous. The GFA tool was used to
identify and recognize flood-prone areas. It has multiple applications in geomorphology and
hydrology. Using this tool is very beneficial for assessing danger areas over a wide expanse. The
identification of flood hazard areas provides critical information to aid and implement effective
measures to mitigate the effects of floods on human lives, infrastructure, and the district's
economy. However, an advantage of the plugin is its intuitive interface and adaptable features,
enabling users to efficiently modify settings and models to suit certain local situations or
scenarios. The adaptability of this tool makes it useful in different geographic and
environmental situations, helping to make well-informed decisions and prepare for disasters.
Furthermore, the plugin's capacity to process several data types, such as Digital Elevation
Models (DEMs), hydrological models, and land use maps, guarantees a thorough examination of
flood vulnerability and consequences. It helps in the development of proactive measures for
reducing flood risk and planning responses by enabling the integration of real-time data and
offering visualization tools.

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6.1 Future scope of the study
The future potential of the work on "Detection of Flood Hazard Based on QGIS" is highly
promising in multiple domains. First, future research can prioritize improving the precision and
dependability of flood hazard detection algorithms within the QGIS platform. This could entail
the utilization of sophisticated machine learning methodologies or the integration of live data
streams to enhance the accuracy of forecasts. Moreover, there is significant potential for
extending the range of applications for QGIS-based flood danger detection beyond its current
limitations. This may entail modifying the process to suit diverse geographical places with
differing environmental conditions and infrastructural configurations. In addition, investigating
the incorporation of QGIS with other developing technologies, including remote sensing, the
Internet of Things (IoT), and artificial intelligence, has the potential to enhance flood monitoring
and management systems by making them more comprehensive and efficient. Furthermore, the
integration of community participation and participatory mapping methodologies in the study
should enhance comprehension and reduce flood threats at the local level. Finally, the
implementation of user-friendly interfaces and decision support tools in QGIS has the potential
to empower stakeholders, policymakers, and disaster management agencies to make well-
informed decisions and take proactive measures to effectively reduce flood risks.

6.2 Limitations of the study

Several restrictions can apply to the "Detection of Flood Hazard Based on QGIS" study. The
accuracy of flood hazard mapping is highly dependent on the quality and resolution of input
data, such as terrain elevation models and hydrological data, which might vary in availability and
accuracy. Moreover, the accessibility of past flood data for verification and adjustment can
influence the efficacy of the methodology. Moreover, the geographical and climatic
circumstances of the studied location may limit the study's relevance, as flood patterns may
differ greatly between regions. The computational resources required in resource-constrained
contexts may restrict the processing of huge datasets and the running of complex models.
Finally, the study's findings may be questionable because of the assumptions and simplifications
made throughout the analysis. This emphasizes the need for strong sensitivity analysis and
methodologies to quantify uncertainty.

ACKNOWLEDGMENTS
The authors express their sincere gratitude towards the National Institute of Technology Raipur
(C.G.) throughout the study.

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