Efficiency and Capability of Remote Sensing (RS) and Geographic Information Systems (GIS): A Powerful Tool for Sustainable Groundwater Management

Volume 8, Issue 4, April – 2023 International Journal of Innovative Science and Research Technology
ISSN No:-2456-2165
IJISRT23APR690 www.ijisrt.com 275
Efficiency and Capability of Remote Sensing
(RS) and Geographic Information Systems
(GIS): A Powerful Tool for Sustainable
Groundwater Management
Groundwater Exploration, Assessment and Mapping Using Remote Sensing
(RS) and Geographic Information Systems (GIS)
1
Nitin Liladhar Rane
2
Saurabh P. Choudhary
3
Monica Giduturi
4
Chaitanya Baliram Pande
1,2,3
Vivekanand Education Society's College of Architecture (VESCOA) Mumbai, India
4
Indian Institute of Tropical Meteorology, Pune 411008, India Institute of Energy Infrastructure, University Tenaga Nasional,
Kajang 43000, Malaysia, New Era and Development in Civil Engineering Research Group, Scientific Research Center, Al-Ayen
University, Thi-Qar, Nasiriyah, 64001, Iraq
DOI:- https://doi.org/10.5281/zenodo.7845332
Abstract:- In this review paper, the potential of remote
sensing (RS) and geographic information systems (GIS)
for sustainable groundwater management and
development is explored. Recent literature on the use of
RS and GIS in groundwater resource management is
analyzed, evaluating the efficiency and capability of
these technologies throughout various stages of
groundwater management. Challenges and limitations
associated with their use are also highlighted, with
potential solutions proposed to overcome them.
Ultimately, the review concludes that RS and GIS are
powerful tools for sustainable groundwater management
and development, with significant benefits in terms of
cost-effectiveness, accuracy, and time-efficiency.
However, more research is needed to improve their
integration in groundwater management and address
current limitations. Overall, this review offers valuable
insights into the potential of RS and GIS in sustainable
groundwater management and development.
Keywords:- Remote Sensing (RS); Geographic Information
Systems (GIS); Groundwater Management; Groundwater
Potential; Efficiency; Capability of RS and GIS; Scale and
Resolution Effects; Groundwater Vulnerability.
I. INTRODUCTION
Groundwater resources are essential to meet the
growing demand for water caused by population growth,
urbanization, and industrialization. Groundwater is the
primary source of water for various purposes, including
domestic, agricultural, and industrial use, in many regions
worldwide [1-3]. However, the overexploitation of
groundwater resources has become a significant concern in
recent years, posing a severe threat to the sustainability of
water resources.
Overexploitation of groundwater resources has led to a
decline in water tables and groundwater quality, resulting in
the degradation of ecosystems and biodiversity loss.
Additionally, it has caused land subsidence, seawater
intrusion, and land degradation, among other problems.
Depletion of groundwater resources is a significant
environmental, social, and economic issue in many regions
worldwide [4-5].
Efficient monitoring and management of groundwater
resources are crucial to ensure their sustainability. However,
conventional methods of groundwater management, such as
drilling wells and measuring water levels, are time-
consuming and expensive, providing only limited
information on groundwater resources. Moreover, these
methods do not consider the spatial and temporal variability
of groundwater systems [1,5].
In recent years, Remote Sensing (RS) and Geographic
Information Systems (GIS) have emerged as powerful tools
for sustainable groundwater management and development.
RS refers to the collection of data about the Earth's surface
from a distance, using sensors on satellites, airplanes, or
drones. Geographic Information Systems (GIS), on the other
hand, refers to the computer-based processing, analysis, and
visualization of spatial data. Together, RS and Geographic
Information Systems (GIS) offer a powerful means of
analyzing and visualizing spatial data related to groundwater
resources, aiding in decision-making for groundwater
management and development.

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Remote Sensing (RS) and Geographic Information
Systems (GIS) provide several advantages over
conventional methods of groundwater management. Firstly,
they provide a spatially explicit representation of
groundwater resources, enabling the identification of
potential recharge areas and the mapping of groundwater
availability. Secondly, they offer a cost-effective means of
monitoring groundwater resources over large areas and at
different spatial and temporal scales. Thirdly, they can be
used to evaluate the impacts of climate change and human
activities on groundwater resources, providing valuable
insights into the sustainability of groundwater resources [6-
8].
The objective of this research paper is to investigate
the efficiency and capability of Remote Sensing (RS) and
Geographic Information Systems (GIS) in sustainable
groundwater management and development. The study aims
to analyze the role of RS and GIS in monitoring
groundwater resources, identifying potential recharge areas,
and evaluating the impacts of climate change and human
activities on groundwater resources. Additionally, the paper
will explore the challenges and limitations of RS and
Geographic Information Systems (GIS) in groundwater
management and development. The study findings will
contribute to better decision-making for sustainable
groundwater management and development, ensuring the
long-term availability of this vital resource.
Systems (GIS) are essential tools for sustainable
groundwater management. These technologies provide
crucial information on groundwater dynamics, recharge
rates, and quality, enabling effective management and
conservation of this valuable resource. In this section, we
will discuss the various applications of RS and GIS in
sustainable groundwater management, including
groundwater monitoring, mapping of recharge zones, and
assessment of groundwater quality [9-11].
Groundwater Monitoring is a critical application of RS
and GIS technologies. These tools can be used to monitor
changes in groundwater levels, enabling early detection of
changes in groundwater resources. Satellite imagery and
other remote sensing data can be used to map the spatial and
temporal changes in groundwater levels over time.
Additionally, GIS can integrate different types of data, such
as rainfall data and land use data, to create a comprehensive
picture of groundwater dynamics. The GRACE (Gravity
Recovery and Climate Experiment) satellite mission is an
excellent example of the use of RS and Geographic
Information Systems (GIS) for groundwater monitoring.
This mission uses gravity measurements to estimate changes
in groundwater levels, providing a comprehensive view of
groundwater dynamics at a regional scale.
Mapping of Recharge Zones is another important
application of RS and GIS technologies in groundwater
management. Recharge zones are areas where rainfall
infiltrates into the ground and replenishes groundwater
resources [12-15]. Mapping these zones can help identify
areas where groundwater is replenished and assess the
potential for future groundwater recharge. Remote Sensing
(RS) and GIS technologies can be used to map the land
surface characteristics that affect recharge rates, such as soil
type, vegetation cover, and topography. This information
can be integrated with rainfall data to identify areas of high
recharge potential. The resulting maps can be used to
prioritize management efforts and identify areas where
groundwater recharge projects should be implemented. A
study conducted in the Upper Guadiana Basin in Spain is an
excellent example of the use of RS and Geographic
Information Systems (GIS) for mapping recharge zones
[1,5]. The study used a combination of Remote Sensing
(RS) data and Geographic Information Systems (GIS) to
map the distribution of recharge zones in the basin,
identifying areas of high recharge potential and prioritizing
management efforts.
Assessment of Groundwater Quality is another
important application of RS and GIS technologies. These
tools can be used to assess groundwater quality by mapping
land use and land cover changes that may impact
groundwater quality. GIS can integrate data from different
sources, such as soil data and groundwater chemistry data,
to create a comprehensive picture of groundwater quality. A
study conducted in the Central Valley of California is an
excellent example of the use of Remote Sensing (RS) and
Geographic Information Systems (GIS) for assessing
groundwater quality. The study used a combination of RS
data and Geographic Information Systems (GIS) to map the
distribution of land use and land cover changes in the area,
identifying areas where groundwater quality may be
impacted and prioritizing management efforts.
Systems (GIS) technologies have numerous applications in
sustainable groundwater management [9,10]]. These
technologies can be used to monitor groundwater levels,
map recharge zones, and assess groundwater quality,
providing important information for effective management
and conservation of this valuable resource. By integrating
different types of data, Remote Sensing (RS) and GIS
technologies can provide a comprehensive view of
groundwater dynamics, allowing for better decision-making
in water resource management.
Groundwater management requires mapping of
recharge zones to identify areas where groundwater is
replenished and assess the potential for future recharge [11].
Remote sensing (RS) and geographic information systems
(GIS) technologies are used to achieve this. RS
technologies, such as satellite imagery, can provide
information on land surface characteristics that affect
recharge rates, while GIS can integrate this information with
other data sources to identify areas of high recharge
potential.
The mapping process involves identifying the areas
where water infiltrates into the ground and replenishes
groundwater resources, which is influenced by factors such
as vegetation cover, soil type, and topography. Satellite

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imagery is commonly used for this purpose, providing a
synoptic view of the land surface to identify areas where
groundwater recharge is likely to occur [12-15].
Other RS technologies, such as airborne lidar and
radar, can also provide high-resolution images to identify
small-scale features affecting recharge rates. Geographic
Information Systems (GIS) technologies can integrate RS
data with other data sources, such as rainfall data, to create
comprehensive maps of recharge zones [12]. Models can
then be created to simulate groundwater recharge rates
under different scenarios, helping to inform sustainable
groundwater management practices by identifying areas
where groundwater recharge is most likely to occur and
predicting changes in recharge rates.
II. OVERVIEW OF REMOTE SENSING
Remote sensing refers to the process of gathering data
about the Earth's surface, atmosphere, and oceans using
sensors that are not in direct contact with these features.
These sensors can be found on satellites, aircraft, or drones,
and they capture images or other forms of data that can be
used to examine the Earth's natural resources, climate, and
other phenomena.
This technique has been in use for many years and is
now an essential tool for numerous scientific fields,
including geology, ecology, atmospheric science, and
geography. Remote sensing is also applied in various areas
such as land use planning, environmental monitoring,
disaster response, and military intelligence.
Remote sensing involves the use of sensors that
capture different types of data such as electromagnetic
radiation, acoustic signals, and gravitational fields. The
sensors can be classified into two categories: passive and
active sensors. Passive sensors detect the natural energy
emitted or reflected by the Earth's surface, while active
sensors emit their own energy and measure the energy that
is reflected back [7].
Satellites are the most popular platforms for remote
sensing because they provide a global view of the Earth's
surface. Satellites can be placed in different orbits,
depending on the application.
Aircraft and drones are also used for remote sensing,
and they can provide higher resolution images than
satellites. Aircraft can fly at lower altitudes and collect data
at specific times and locations, while drones can provide
even higher resolution images and collect data in areas that
are inaccessible or dangerous for aircraft.
Various techniques such as image processing, machine
learning, and data fusion are used to process and analyze
remote sensing data. Image processing involves improving
the quality of the images and extracting useful information
from them. Machine learning techniques are used to classify
the images and identify patterns in the data. Data fusion
involves combining data from different sensors to create
more comprehensive datasets.
Remote sensing has numerous applications in various
fields, including agriculture, forestry, urban planning,
hydrology, and geology [16-21]. For instance, it can be used
to monitor crop growth and detect disease outbreaks in
agriculture, map forest cover and estimate biomass in
forestry, monitor urban growth and detect changes in land
use in urban planning, monitor water resources and predict
floods in hydrology, and study the Earth's crust and detect
mineral deposits in geology.
Remote sensing also plays a crucial role in
environmental monitoring and disaster response. For
example, it can be used to track the spread of wildfires,
monitor air and water quality, and detect changes in sea
level and ocean temperature. In disaster response, it can be
used to assess the damage caused by natural disasters, such
as earthquakes, hurricanes, and floods, and guide relief
efforts.
Remote sensing is a powerful tool that helps us study
the Earth's natural resources, climate, and other phenomena.
It is widely used in various fields and applications and is
increasingly important for understanding and managing the
Earth's resources and environment, especially with advances
in technology.
III. OVERVIEW OF GIS TECHNOLOGY
Geographic Information Systems (GIS) is a
technology that merges data and maps to produce
sophisticated and interactive visualizations of the
environment. It has diverse applications in fields such as
emergency management, urban planning, engineering, and
environmental science. This article gives an overview of
Geographic Information Systems (GIS) technology, its uses,
and the advantages it provides to individuals, businesses,
and governments. Geographic Information Systems (GIS)
enables users to scrutinize, organize, and display
geographical data. Geographic Information Systems (GIS)
systems are created to gather, stock, operate, evaluate, and
present spatial information that can range from the location
of a structure to the limits of a city or the dispersal of a
specific species of flora or fauna.
To produce digital maps and other geographical
illustrations, GIS technology employs software, hardware,
and data. The software provides a foundation for the
analysis and visualization of spatial data, while the hardware
delivers the computing power and storage space essential
for managing huge datasets. The data utilized in Geographic
Information Systems (GIS) systems may originate from
various sources such as GPS data, aerial photography,
satellite imagery, or field observations. This data is
frequently merged with other types of data like climate data,
land use data, or demographic data, to offer a
comprehensive depiction of a particular location.

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IV. COMPONENTS OF REMOTE SENSING AND
GIS TECHNOLOGY
Remote Sensing and Geographic Information Systems
are two technologies that are closely related and
complement each other. Remote Sensing refers to the
collection of data about the Earth's surface without physical
contact, typically through sensors on aircraft or satellites,
while Geographic Information Systems (GIS) involves the
processing, analysis, and visualization of this data in a
geographic context. These technologies are critical for
collecting, analyzing, and sharing spatial data in various
fields such as agriculture, ecology, geology, urban planning,
and more. Passive remote sensing measures the energy
emitted or reflected by the Earth's surface, whereas active
remote sensing measures the energy transmitted from a
sensor and reflected back from the surface [22-25].
 Listed below are Several Essential Elements of Remote
Sensing:
 Platform: This pertains to the airborne or satellite
equipment utilized in data collection.
 Sensor: This refers to the instrument or camera used for
obtaining data.
 Resolution: This pertains to the level of detail presented
in the data, ranging from low to very high resolution.
 Spectral bands: This refers to the range of wavelengths
that the sensor can detect.
 Radiometric resolution: This pertains to the sensitivity
of the sensor to changes in color or brightness.
 On the contrary, Geographic Information Systems
(GIS) involves the examination and organization of
spatial data, frequently in the form of maps. The
following are some of the critical components of
Geographic Information Systems (GIS):
 Data input: This refers to the process of gathering and
digitizing spatial data.
 Database management: This refers to the storage,
organization, and retrieval of spatial data.
 Spatial analysis: This refers to the use of GIS tools to
analyze and manipulate spatial data.
 Cartography: This pertains to the creation of maps and
other visual representations of spatial data.
 Geocoding: This refers to the process of assigning
geographic coordinates to data points to accurately
locate them on a map.
V. RS AND GIS APPLICATIONS IN
EXPLORATION AND ASSESSMENT OF
GROUNDWATER RESOURCES
RS and GIS are useful tools for the exploration and
assessment of groundwater resources. These technologies
can be applied to various areas, including mapping
groundwater potential zones, monitoring changes in
groundwater levels, evaluating groundwater quality,
identifying recharge zones, and managing groundwater
resources. By mapping land use/land cover types, geological
structures, and hydrological features like rivers and
wetlands, RS and GIS can identify areas with high potential
for groundwater. Techniques like InSAR and LIDAR can
monitor changes in land surface elevation to estimate
changes in groundwater levels. GIS can overlay maps of
geological and hydrological features with data on
groundwater quality, including pH, electrical conductivity,
and the presence of contaminants, to identify areas at risk of
contamination and prioritize remediation efforts. RS and
GIS can also identify areas where groundwater recharge
occurs and help prioritize conservation or restoration efforts
to enhance groundwater recharge. By monitoring
groundwater extraction rates and estimating recharge rates,
Remote Sensing (RS) and GIS can help develop sustainable
groundwater management plans for the long-term
availability of groundwater resources. Overall, the
applications of RS and GIS in groundwater exploration and
assessment are essential for sustainable management of
these resources [26,27].
VI. GROUNDWATER POTENTIAL ZONES
Groundwater is a vital natural resource that plays a
crucial role in meeting the domestic, agricultural, and
industrial water needs. However, the availability of
groundwater varies significantly in different regions,
making it necessary to identify the potential groundwater
zones for sustainable management and utilization of this
resource. This is where remote sensing (RS) and geographic
information system (GIS) come into play. The integration of
these technologies has emerged as a powerful tool for
identifying groundwater potential zones, which can aid in
efficient groundwater management.
Mapping groundwater potential zones using RS and
Geographic Information Systems (GIS) provides critical
information for groundwater exploration, selection of
suitable locations for drilling wells, and estimation of
groundwater availability. With RS, satellite images are used
to identify geological and hydrogeological factors that
influence groundwater availability. These images help
identify surface features like topography, land use, and
vegetation cover that impact groundwater recharge and
storage. Geographic Information Systems (GIS) is then used
to develop a hydrological model of the study area, which
simulates the movement of water through the hydrological
cycle. Geophysical surveys can also be conducted using
various techniques to identify potential groundwater zones.
Multi-criteria decision analysis is another GIS-based
method that evaluates and ranks potential groundwater
zones based on different criteria, such as land use,
topography, soil type, and hydrogeology. The method helps
in identifying the most suitable areas for groundwater
exploration based on the selected criteria.
The identification of groundwater potential zones is a
crucial step towards sustainable groundwater management.
With the integration of RS and Geographic Information
Systems (GIS), we can efficiently identify potential
groundwater zones, aiding in the exploration and
management of this valuable resource. By ensuring the
efficient and optimal utilization of groundwater resources,

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we can protect our environment and guarantee the
availability of water for future generations.
VII. SELECTION OF ARTIFICIAL
RECHARGE SITES
Artificial recharge (AR) refers to the process of
enhancing the natural recharge of groundwater through the
use of human-made systems, such as recharge trenches,
infiltration basins, and injection wells. In regions facing
water scarcity due to overexploitation and climate change
impacts, the proper selection of suitable AR sites is crucial
for sustainable water resource management. Remote
Sensing (RS) and Geographic Information System (GIS)
technologies are useful tools for identifying and evaluating
potential AR sites based on various hydrogeological,
climatic, and land-use parameters [28-32].
RS techniques collect data from satellites or aircraft to
provide high-resolution imagery of the study area. These
images can help identify land-use types, vegetation cover,
soil properties, and topography, which are important factors
in determining appropriate AR sites. For instance, the
Normalized Difference Vegetation Index (NDVI) can
determine vegetation density and health, indicating areas
with high infiltration rates and potential AR sites.
Additionally, digital elevation models (DEM) can be used to
spot areas with suitable topography for infiltration basins or
recharge trenches.
Geographic Information Systems (GIS) is another
crucial tool for analyzing and integrating data layers to
identify suitable AR sites. GIS software generates maps and
spatial databases that combine hydrogeological, climatic,
and land-use parameters [17]. For instance, Geographic
Information Systems (GIS) can combine soil hydraulic
conductivity, depth to the water table, and land-use data to
locate areas with appropriate infiltration rates and minimal
contamination risks. Geographic Information Systems (GIS)
can also analyze the spatial distribution of potential recharge
sites and their proximity to existing infrastructure to reduce
AR implementation costs.
Modeling approaches can also simulate
hydrogeological conditions at potential AR sites. For
example, numerical models such as MODFLOW can
simulate groundwater flow and recharge rates in the study
area. These models can be calibrated using field data, such
as groundwater levels and hydraulic conductivity
measurements, to improve prediction accuracy. Moreover,
uncertainty and sensitivity analysis can identify the most
influential parameters and evaluate the reliability of model
predictions.
The selection of suitable AR sites necessitates
stakeholder involvement and public participation. Remote
Sensing (RS) and GIS technologies can generate maps and
visualizations to communicate the potential benefits and
risks of AR implementation to stakeholders and the public.
Remote Sensing (RS) and GIS can also identify areas
vulnerable to contamination or land-use conflicts that can be
excluded from the selection process. Public participation
can also provide valuable information on local
hydrogeological conditions and potential impacts of AR
implementation on the community.
RS and GIS technologies are valuable tools for
identifying and assessing potential AR sites based on
various hydrogeological, climatic, and land-use parameters.
When combined with modeling approaches and stakeholder
involvement, they can improve the accuracy and reliability
of the site selection process. Successful AR implementation
requires careful site selection, appropriate infrastructure
design, and effective stakeholder engagement, and Remote
Sensing (RS) and GIS can contribute to these aspects of AR
implementation and improve water resource management
sustainability in water-scarce regions [3,5].
VIII. GIS-BASED SUBSURFACE FLOW:
DEVELOPMENT OF MODEL,
APPLICATIONS AND EVALUATION
Subsurface flow modeling using GIS and MODFLOW
is employed to simulate groundwater flow through porous
media. The development of a MODFLOW model involves
integrating geologic, hydrologic, and land-use data into a
Geographic Information Systems (GIS) platform. This
integration enables the creation of a digital elevation model
that defines the spatial distribution of hydraulic
conductivity, recharge, and boundary conditions necessary
for the groundwater flow model. The resulting model can
simulate complex hydrological processes within the
subsurface environment.
GIS-based subsurface flow modeling has multiple
applications, including the evaluation of groundwater
resources. The MODFLOW model can estimate the quantity
and quality of groundwater in an aquifer system, enabling
informed decisions regarding pumping rates and well
placement. The model can also predict the potential impacts
of land-use changes, such as new housing developments or
urbanization, on groundwater resources.
Additionally, GIS-based subsurface flow modeling is
used to evaluate contaminant transport in groundwater. The
MODFLOW model simulates contaminant movement
through the subsurface environment, predicting the impact
of a release on groundwater quality. This information is
critical for identifying sources of contamination and
developing remediation strategies to protect the
environment and human health.
Calibration and validation of the MODFLOW model
are used to evaluate groundwater resources and contaminant
transport. Calibration involves adjusting model parameters
to match observed data such as groundwater levels or
pumping rates, while validation tests model accuracy by
comparing simulated results to independent data sets.
Geographic Information Systems (GIS) visualization aids in
interpreting and communicating complex hydrological
processes to stakeholders.

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GIS-based subsurface flow modeling is a powerful
tool for evaluating groundwater resources and contaminant
transport. The integration of Geographic Information
Systems (GIS) data with the MODFLOW model enables a
comprehensive understanding of hydrological processes
within an aquifer system. The resulting model supports
informed decision-making for water management and
environmental protection. The visualization of model results
aids in communicating complex hydrological processes to
stakeholders.
IX. GIS-BASED SUBSURFACE FLOW AND
POLLUTION MODELING: MODEL
DEVELOPMENT, APPLICATIONS AND
EVALUATION
The technique of GIS-based subsurface pollution flow
modeling is utilized to anticipate and simulate the
movement of pollutants in the subsurface environment. This
technology is widely applied in several fields, such as
environmental management, engineering, and
hydrogeology. The method involves the creation of a digital
model that represents the subsurface environment's
geological structure, soil characteristics, and water table.
The model predicts the contaminants' flow in the subsurface
environment, thus allowing the prediction of potential
pollution pathways and the design of appropriate
remediation strategies.
The primary application of GIS-based subsurface
pollution flow modeling is in managing contaminated sites.
By simulating the contaminants' movement, environmental
managers can assess potential risks to human health and the
environment and develop effective remediation strategies.
This leads to more efficient resource allocation and a better
understanding of potential long-term impacts.
The technology is also useful in designing and
planning new industrial facilities. Engineers and planners
can model the potential impact of these facilities on the
subsurface environment, enabling the appropriate design of
containment and remediation systems to reduce the potential
for contamination and minimize future liability.
In hydrogeology, GIS-based subsurface pollution flow
modeling is widely applied to simulate groundwater flow.
By doing so, hydrogeologists gain a better understanding of
water movement through the subsurface environment and
predict the potential impact of pollutants on water resources.
This is particularly crucial in areas where groundwater is the
primary source of drinking water [4-6].
Evaluating GIS-based subsurface pollution flow
modeling is critical to ensuring model accuracy and
reliability. One aspect of evaluation involves comparing
predicted model outcomes to actual field measurements to
validate the model's accuracy. Another aspect is sensitivity
analysis, where the model's response to changes in input
parameters is tested. This assesses the model's uncertainty
degree and identifies areas requiring further data analysis or
collection.
GIS-based subsurface pollution flow modeling is a
potent tool in predicting the movement of contaminants in
the subsurface environment. The technology's applications
span across different fields, including environmental
management, engineering, and hydrogeology. However, the
model's accuracy and reliability must undergo validation
and sensitivity analysis to provide accurate and useful
information for decision-making.
X. PARAMETERS USED IN GROUNDWATER
ASSESSMENT STUDIES
The assessment of groundwater potential requires the
consideration of several parameters, including geological,
hydrogeological, environmental, and geophysical factors.
Lithology, structure, and geomorphology are critical
geological parameters that provide insight into the
subsurface characteristics that affect water movement
through rocks [7,8]. Hydrogeological parameters, such as
groundwater recharge, aquifer properties, and water quality,
are also crucial in evaluating the potential for groundwater
development. Environmental parameters, such as land use,
topography, and climate, can affect the likelihood of
pollutants entering the groundwater system and the speed
and direction of water movement. Geophysical parameters,
including resistivity, magnetic susceptibility, and seismic
velocity, can provide additional information on the
subsurface characteristics of the groundwater system.
MODFLOW is a groundwater modeling software
package that is widely used for simulating the flow of
groundwater in a heterogeneous, three-dimensional aquifer
system. To define the properties of the aquifer and other
conditions that affect groundwater flow, various parameters
are used in MODFLOW. The hydraulic conductivity (K)
parameter measures the ability of the aquifer to transmit
water and affects the velocity and direction of groundwater
flow. Another important parameter is the specific yield (Sy),
which represents the amount of water that can be stored in
the aquifer per unit volume and is crucial for determining
how much water can be extracted from the aquifer before it
becomes depleted. The recharge (R) parameter, which is
influenced by factors such as precipitation, infiltration, and
surface runoff, specifies the rate at which water enters the
aquifer from the surface. Boundary conditions are also
critical parameters in MODFLOW modeling, with the head
boundary condition determining the water table's elevation
at the aquifer boundary, and the flux boundary condition
defining the rate of flow into or out of the aquifer at the
boundary.
Overall, the assessment of groundwater potential
zones is important for identifying areas where groundwater
is likely to be present and the ease with which it can be
extracted. This information is essential for making informed
decisions on water resource management and ensuring
access to clean and reliable water for communities. By
considering various parameters, including geological,
hydrogeological, environmental, and geophysical factors, it
is possible to evaluate the potential occurrence and
availability of groundwater in an area.

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 Hydrological-Related Parameters
To comprehend the quality and quantity of
groundwater in a particular area, groundwater evaluation
studies are crucial. These studies use various hydrological-
related parameters to assess the features of groundwater.
Among these parameters, hydraulic conductivity is vital, as
it denotes the soil's ability to transmit water, determining the
water flow rate through the soil and into the aquifer. It is
influenced by the saturation, porosity, and soil type.
Porosity, another parameter used in groundwater evaluation
studies, reflects the void space between soil particles,
determining the amount of water stored in the soil, with
higher porosity indicating greater water retention.
The water table is also a critical parameter for
assessing groundwater, representing the level at which water
is situated below the surface, varying based on precipitation,
soil type, and land use. The water table is important as it
indicates the depth at which groundwater can be accessed
and the amount that can be extracted. Groundwater recharge
is another key parameter, referring to the process of water
infiltrating the soil and entering the aquifer. This recharge
rate is affected by factors such as precipitation, soil type,
and land use and determines the speed at which groundwater
replenishes.
Groundwater flow direction is also an essential
parameter used in evaluation studies, indicating the
direction of water flow in the aquifer, influenced by
hydraulic gradient, topography, geology, and hydraulic
conductivity. Finally, groundwater quality, referring to the
chemical and physical properties of groundwater, is a
crucial parameter affected by factors such as land use,
human activities, and geology. The quality determines the
suitability of groundwater for various uses, including
drinking, irrigation, and industrial applications.
Groundwater evaluation studies rely on several
hydrological-related parameters to assess the features of
groundwater. These parameters include hydraulic
conductivity, porosity, water table, groundwater recharge,
groundwater flow direction, and groundwater quality. These
parameters are crucial in understanding the quantity and
quality of groundwater in an area and are vital in managing
this resource effectively.
 Climate-Related Parameters
Groundwater evaluation studies rely heavily on
climate-related parameters as they significantly impact the
amount and quality of water available in the aquifer.
Temperature, precipitation, humidity, wind speed, and
atmospheric pressure are some of the critical parameters
affected by various atmospheric factors. Temperature
influences groundwater through evapotranspiration, leading
to the depletion of groundwater resources. Precipitation is
the primary source of recharge for groundwater and affects
the recharge rate, leading to fluctuations in groundwater
availability. Humidity influences the rate of
evapotranspiration, affecting the amount of water available.
Wind speed affects evaporation rates and the distribution of
precipitation, leading to variations in recharge rates.
Atmospheric pressure influences the distribution of
precipitation and infiltration of water into the soil, affecting
the rate of recharge. In summary, understanding these
climate-related parameters is vital in managing groundwater
resources effectively and sustainably. Decision-makers need
to consider the interaction between these parameters to
make informed decisions regarding groundwater use and
conservation.
 Land Cover Related Parameters:
Assessing groundwater resources is critical for
understanding their quantity and quality in a particular
region. Among the key factors that influence groundwater
availability and quality are land cover-related parameters.
Land cover refers to the physical and biological features
covering the earth's surface, including vegetation, water
bodies, bare ground, and urban areas.
Vegetation cover is one of the most crucial parameters
used in groundwater evaluation studies. It impacts
groundwater recharge by affecting infiltration rates and
evapotranspiration. Vegetation plays a vital role in
maintaining the water balance in the soil-plant-atmosphere
system. It reduces runoff and enhances infiltration, which
increases the amount of water available for recharge.
Moreover, vegetation slows down the speed of surface
water, providing more time for infiltration.
Land use and land cover changes (LULCC) are
another essential parameter. It refers to the alteration or
conversion of land cover types due to human activities such
as urbanization, agriculture, or deforestation. These changes
significantly affect groundwater availability and quality.
Urbanization leads to more impervious surfaces, reducing
infiltration rates and increasing runoff. Agricultural
activities often involve the use of pesticides and fertilizers,
which can contaminate groundwater. Deforestation results
in reduced vegetation cover, which affects infiltration rates
and soil moisture, and thus groundwater recharge.
Soil cover is a vital parameter that influences
infiltration rates, which affect groundwater recharge. Soils
filter, store, and transmit water to groundwater. The texture,
structure, and depth of soils determine their hydraulic
conductivity, which affects infiltration rates. Soil types also
affect the availability of nutrients and pollutants that can
impact groundwater quality. Sandy soils are more
permeable than clay soils, and pollutants can quickly
penetrate into the groundwater in sandy soils.
Landform and topography are additional parameters
that affect groundwater recharge. The shape and slope of the
landform influence the direction and velocity of water flow,
which affects the amount of water available for recharge.
Steep slopes increase the velocity of water flow, reducing
the amount of water available for infiltration. Landforms
also impact the amount and duration of solar radiation,
which affects evapotranspiration and, thus, groundwater
recharge.

ISSN No:-2456-2165
Surface water bodies, such as rivers, lakes, and
wetlands, are crucial in groundwater evaluation studies.
These bodies are often connected to groundwater through
underground aquifers. The recharge of groundwater through
surface water bodies is known as baseflow. The quantity
and quality of baseflow depend on several factors, such as
the permeability of the aquifer, the size of the surface water
body, and the velocity of water flow. Additionally, surface
water bodies can also be sources of pollutants that can
contaminate groundwater.
Land cover-related parameters play a critical role in
groundwater evaluation studies. Vegetation cover, land use
and land cover changes, soil cover, landform and
topography, and surface water bodies all affect groundwater
quality and availability. To ensure sustainable groundwater
use and protection, groundwater management plans must
consider these parameters.
XI. VALIDATION METHODOLOGIES IN
GROUNDWATER ASSESSMENT STUDIES
Validating the results of groundwater evaluation
studies is crucial to ensure the accuracy and reliability of the
findings. This involves comparing the model-generated
results with available field data to verify the model's ability
to accurately represent the groundwater system's behavior
and produce dependable predictions.
Groundwater evaluation studies employ various
validation methods, such as visual inspection, statistical
analysis, and sensitivity analysis. Visual inspection involves
comparing the model predictions with observed data using
graphs and plots to identify discrepancies and fine-tune the
model [12,14].
Statistical analysis involves quantifying the accuracy
and reliability of the model predictions by using statistical
methods like correlation coefficients, mean square error, and
root mean square error to compare the model predictions
with observed data.
Sensitivity analysis entails varying the model
parameters to determine the critical parameters that affect
the model's accuracy and reliability and observing the effect
on the model predictions.
XII. UNDERSTANDING THE SCALE AND
RESOLUTION EFFECTS IN REMOTE
SENSING AND GIS
The use of remote sensing and GIS has revolutionized
the way we study and analyze the Earth's surface. Remote
sensing involves acquiring data about the Earth's surface
from a distance, typically through sensors mounted on
aircraft or satellites. GIS, on the other hand, involves
analyzing and visualizing spatial data using computer-based
tools. These tools provide a wealth of information about the
Earth's surface that can be used to better understand natural
disasters, urban growth, and other aspects of the planet.
One important concept to understand when working
with remote sensing and Geographic Information Systems
(GIS) is the scale and resolution effects. These effects refer
to how the spatial and temporal resolution of remote sensing
data can affect the accuracy and interpretation of the data.
Spatial resolution is the size of the individual pixels in an
image, while temporal resolution is the frequency at which
data is acquired over time.
To ensure accurate groundwater evaluation, it is
crucial to give careful consideration to the scale and
resolution of the data used. This may involve utilizing
multiple sensors with varying resolutions to capture features
at different scales, and selecting data at the appropriate scale
for the analysis being conducted. For example, Landsat data
may be sufficient for assessing groundwater resources on a
regional scale, but a higher resolution sensor may be
necessary for identifying individual recharge areas or wells.
When using Geographic Information Systems (GIS), it
is also important to carefully consider the scale and
resolution of each layer of data used and ensure that they are
appropriate for the analysis being conducted [13,27]. This
may involve incorporating multiple layers with different
scales and resolutions, or resampling data to a common
scale and resolution. It may also be necessary to conduct
sensitivity analyses to evaluate the impact of scale and
resolution on the results.
In addition to scale and resolution, other factors such
as atmospheric conditions, terrain effects, and data
processing methods can impact the accuracy of groundwater
evaluation using remote sensing and GIS. Correcting for
atmospheric conditions is crucial for removing the effects of
haze and other atmospheric interferences from remote
sensing data. Terrain effects such as shading and aspect can
also have an impact on the accuracy of DEM-derived data.
Finally, data processing methods like interpolation can
result in errors if applied incorrectly.
An understanding of the effects of scale and resolution
in remote sensing and Geographic Information Systems
(GIS) is crucial for accurate groundwater evaluation.
Researchers and practitioners should carefully consider the
appropriate scale and resolution of data used, as well as
accounting for other factors that may impact accuracy, to
ensure that their results are reliable and robust. This can
help inform sustainable management of groundwater
resources for present and future generations.
The scale and resolution effects are illustrated by
considering the example of a satellite image of a city. If the
spatial resolution of the image is low, individual buildings
may not be visible, and the overall appearance of the city
may be blurry. In contrast, if the spatial resolution is high,
individual buildings may be visible, and it may be possible
to distinguish between different types of structures, such as
residential buildings and commercial buildings.

ISSN No:-2456-2165
The scale and resolution effects are also important
when studying natural features such as forests, rivers, and
oceans. If the spatial resolution of a satellite image of a
forest is low, it may be difficult to distinguish between
different types of trees and identify areas of forest that have
been damaged by natural disasters or human activity.
However, with high spatial resolution, it may be possible to
identify individual trees and distinguish between different
types of forest cover.
Another important factor to consider when working
with remote sensing and GIS data is the spatial scale of the
data. This refers to the size of the area covered by a
particular dataset. A satellite image of a city may cover
several hundred square kilometers, while an image of a
single building may cover only a few square meters.
Different spatial scales may be more or less appropriate for
different types of analysis.
The temporal scale of remote sensing and Geographic
Information Systems (GIS) data is also important. This
refers to the length of time over which data is collected. For
example, a satellite may acquire data about a particular area
of the Earth's surface every day, week, or month. Different
temporal scales may be more or less appropriate for
different types of analysis.
To use remote sensing and GIS effectively, it is critical
to understand the scale and resolution effects [12,30]. By
carefully considering the spatial and temporal resolution of
remote sensing data, as well as the spatial and temporal
scale of the data, it is possible to obtain more accurate and
meaningful results. Remote sensing and GIS provide a
wealth of information that can help us better understand our
planet and the forces that shape it. Whether studying natural
disasters, urban growth, or any other aspect of the Earth's
surface, remote sensing and GIS can provide insights that
would be difficult or impossible to obtain through other
means.
XIII. CONSTRAINTS FOR RS AND GIS
APPLICATIONS IN DEVELOPING
COUNTRIES
RS and GIS technologies have become essential tools
in various fields such as urban planning, agriculture,
forestry, natural resources management, and disaster
management. However, their effective implementation in
developing countries is often hindered by various
constraints. This article highlights the major constraints that
limit the use of RS and GIS applications in these countries.
One of the major constraints is the lack of adequate
infrastructure, particularly in remote and rural areas. These
areas often lack reliable electricity, telecommunication
networks, and computing facilities. This makes it
challenging to process and analyze large amounts of data,
which is required for RS and GIS technologies. Without
these facilities, the accuracy of the results may be
compromised, making it challenging to effectively use these
technologies in developing countries where infrastructure
development is often not a priority.
The limited availability of trained personnel is another
major constraint. There is a shortage of trained professionals
who can effectively operate these technologies in
developing countries. This is due to the limited number of
institutions offering RS and GIS training programs, as well
as the lack of incentives for professionals to stay in the
country. As a result, the few trained personnel that are
available often migrate to developed countries where the
demand for their skills is high, leaving developing countries
with a shortage of personnel.
The lack of access to high-quality and up-to-date data
is another significant constraint. RS and Geographic
Information Systems (GIS) applications rely heavily on
data, including satellite imagery, aerial photography, and
ground data. However, developing countries often lack the
resources to acquire and maintain such data. The cost of
purchasing and maintaining such data can be prohibitively
high, and there is often a lack of institutional arrangements
for data sharing and collaboration.
The lack of institutional capacity for effective RS and
Geographic Information Systems (GIS) implementation is
another constraint. Developing countries often lack the
institutional capacity to effectively implement RS and GIS
applications. This is because the development of
institutional capacity requires a sustained effort over time,
which is often challenging in developing countries where
institutional instability is common. Additionally, the lack of
institutional capacity can result in poor coordination
between different government agencies and stakeholders,
which can limit the effectiveness of RS and GIS
applications.
The limited financial resources available for RS and
Geographic Information Systems (GIS) implementation is
another constraint. Developing countries often have limited
financial resources, which can limit the investment in
Remote Sensing (RS) and GIS applications. This can result
in a lack of funding for research and development, as well
as for the acquisition and maintenance of equipment and
data. Additionally, the limited financial resources can result
in a lack of incentives for professionals to stay in the
country and to pursue careers in RS and GIS technologies.
Finally, the limited access to RS and Geographic
Information Systems (GIS) applications by local
communities is another significant constraint. These
communities often lack access to these technologies due to
the limited infrastructure and personnel available. This can
limit the effectiveness of Remote Sensing (RS) and GIS
applications in developing countries and can result in poor
decision-making and planning.
Addressing these constraints will require a sustained
effort over time and will require the cooperation of different
stakeholders, including government agencies, educational
institutions, and the private sector. There is a need to

ISSN No:-2456-2165
prioritize infrastructure development, improve training
programs for RS and Geographic Information Systems
(GIS) technologies, create institutional arrangements for
data sharing and collaboration, and invest in research and
development. Additionally, there is a need to ensure that
local communities have access to RS and Geographic
Information Systems (GIS) applications to facilitate
effective decision-making and planning. By addressing
these constraints, the potential of RS and GIS technologies
to provide valuable information for decision-making and
planning in developing countries can be fully realized.
XIV. CONCLUSIONS
To sum up, Remote Sensing (RS) and Geographic
Information Systems (GIS) have emerged as powerful
instruments for promoting sustainable groundwater
management and development. Through various studies, the
effectiveness and efficiency of RS and GIS in providing
accurate and timely information on groundwater resources
have been demonstrated. The integration of RS and GIS in
groundwater management and development has led to
enhanced decision-making, planning, and monitoring of
groundwater resources. Moreover, the use of RS and GIS
has facilitated a better understanding of the spatial and
temporal dynamics of groundwater resources, which is
critical for effective management and development. In
conclusion, the indispensable role of RS and GIS in
sustainable groundwater management and development is
undeniable, and their continuous evolution and application
can significantly contribute to ensuring the availability of
safe and reliable groundwater resources for future
generations.
RS and GIS play a critical role in managing
groundwater due to various reasons. Firstly, they facilitate
the collection, analysis, and visualization of intricate data
related to groundwater resources, including water quality,
quantity, and availability. This information is vital for
making informed decisions on sustainable groundwater
management practices.
Secondly, RS and GIS permit the mapping and
monitoring of groundwater resources over large areas and
extended periods, which traditional ground-based methods
cannot achieve. This enables the identification of trends and
changes in groundwater resources, providing valuable
insights for effective management practices.
Thirdly, RS and GIS offer a cost-effective means of
managing and developing groundwater resources by
minimizing the need for expensive fieldwork and surveys.
This optimization of resource allocation can result in
improved efficiency and effectiveness in groundwater
management.
Lastly, the integration of RS and GIS with other
technologies such as modeling and simulation provides
foresight into the future behavior of groundwater systems.
This can aid in the development and implementation of
sustainable management plans that account for climate
change and other factors.
In conclusion, the significance of RS and GIS in
groundwater management stems from their ability to
provide comprehensive, timely, and accurate information on
groundwater resources. This information enables effective
decision-making, planning, monitoring, and management of
these resources.
REFERENCES
[1] Elbeih, S. F. (2015). An overview of integrated
remote sensing and GIS for groundwater mapping in
Egypt. Ain Shams Engineering Journal, 6(1), 1-15.
[2] Jha, M. K., Chowdhury, A., Chowdary, V. M., &
Peiffer, S. (2007). Groundwater management and
development by integrated remote sensing and
geographic information systems: prospects and
constraints. Water resources management, 21, 427-
467.
[3] Singh, A. (2014). Groundwater resources
management through the applications of simulation
modeling: A review. Science of the Total
Environment, 499, 414-423.
[4] Allafta, H., Opp, C., & Patra, S. (2020). Identification
of groundwater potential zones using remote sensing
and GIS techniques: a case study of the Shatt Al-
Arab Basin. Remote Sensing, 13(1), 112.
[5] Kumari, L. (2018). Delineation of potential
groundwater zone using RS and GIS: a review. Int. J.
Curr. Microbiol. App. Sci, 7(12), 196-203.
[6] Preeja, K. R., Joseph, S., Thomas, J., & Vijith, H.
(2011). Identification of groundwater potential zones
of a tropical river basin (Kerala, India) using remote
sensing and GIS techniques. Journal of the Indian
Society of Remote Sensing, 39, 83-94.
[7] Merchant, J. W. (1994). GIS-based groundwater
pollution hazard assessment: a critical review of the
DRASTIC model. Photogrammetric engineering and
remote sensing, 60, 1117-1117.
[8] Agarwal, R., & Garg, P. K. (2016). Remote sensing
and GIS based groundwater potential & recharge
zones mapping using multi-criteria decision making
technique. Water resources management, 30, 243-
260.
[9] Rane, N. L., & Jayaraj, G. K. (2022). Comparison of
multi-influence factor, weight of evidence and
frequency ratio techniques to evaluate groundwater
potential zones of basaltic aquifer systems.
Environment, Development and Sustainability, 24(2),
2315-2344. https://doi.org/10.1007/s10668-021-
01535-5
[10] Rane, N., & Jayaraj, G. K. (2021). Stratigraphic
modeling and hydraulic characterization of a typical
basaltic aquifer system in the Kadva river basin,
Nashik, India. Modeling Earth Systems and
Environment, 7, 293-306.
https://doi.org/10.1007/s40808-020-01008-0

ISSN No:-2456-2165
[11] Rane, N., & Jayaraj, G. K. (2021). Evaluation of
multiwell pumping aquifer tests in unconfined
aquifer system by Neuman (1975) method with
numerical modeling. In Groundwater resources
development and planning in the semi-arid region
(pp. 93-106). Cham: Springer International
Publishing. https://doi.org/10.1007/978-3-030-68124-
1_5
[12] Mishra, N., Khare, D., Gupta, K. K., & Shukla, R.
(2014). Impact of land use change on groundwater—
a review. Advances in Water Resource and
Protection, 2(28), 28-41.
[13] Meijerink, A. M. J. (1996). Remote sensing
applications to hydrology: groundwater. Hydrological
sciences journal, 41(4), 549-561.
[14] Swain, S., Taloor, A. K., Dhal, L., Sahoo, S., & Al-
Ansari, N. (2022). Impact of climate change on
groundwater hydrology: a comprehensive review and
current status of the Indian hydrogeology. Applied
Water Science, 12(6), 120.
[15] Rane, N. L., Anand, A., Deepak K., (2023).
Evaluating the Selection Criteria of Formwork
System (FS) for RCC Building Construction.
International Journal of Engineering Trends and
Technology, vol. 71, no. 3, pp. 197-205. Crossref,
https://doi.org/10.14445/22315381/IJETT-
V71I3P220
[16] Achari, A., Rane, N. L., Gangar B., (2023).
Framework Towards Achieving Sustainable
Strategies for Water Usage and Wastage in Building
Construction. International Journal of Engineering
Trends and Technology, vol. 71, no. 3, pp. 385-394.
Crossref, https://doi.org/10.14445/22315381/IJETT-
V71I3P241
[17] Thanh, N. N., Thunyawatcharakul, P., Ngu, N. H., &
Chotpantarat, S. (2022). Global review of
groundwater potential models in the last decade:
Parameters, model techniques, and validation.
Journal of Hydrology, 128501.
[18] Chowdhury, A., Jha, M. K., & Chowdary, V. M.
(2010). Delineation of groundwater recharge zones
and identification of artificial recharge sites in West
Medinipur district, West Bengal, using RS, GIS and
MCDM techniques. Environmental Earth Sciences,
59, 1209-1222.
[19] Rane, N. L., & Attarde, P. M. (2016). Application of
value engineering in commercial building projects.
International Journal of Latest Trends in Engineering
and Technology, 6(3), 286-291.
[20] Rane, N. L., (2016). Application of value engineering
techniques in building construction projects.
International Journal of Engineering Sciences &
Technology, 5(7).
[21] Rane, N., Lopes, S., Raval, A., Rumao, D., &
Thakur, M. P. (2017). Study of effects of labour
productivity on construction projects. International
Journal of Engineering Sciences and Research
Technology, 6(6), 15-20.
[22] Kaur, L., Rishi, M. S., Singh, G., & Thakur, S. N.
(2020). Groundwater potential assessment of an
alluvial aquifer in Yamuna sub-basin (Panipat region)
using remote sensing and GIS techniques in
conjunction with analytical hierarchy process (AHP)
and catastrophe theory (CT). Ecological Indicators,
110, 105850.
[23] Manap, M. A., Nampak, H., Pradhan, B., Lee, S.,
Sulaiman, W. N. A., & Ramli, M. F. (2014).
Application of probabilistic-based frequency ratio
model in groundwater potential mapping using
remote sensing data and GIS. Arabian Journal of
Geosciences, 7, 711-724.
[24] Pérez Hoyos, I. C., Krakauer, N. Y., Khanbilvardi,
R., & Armstrong, R. A. (2016). A review of advances
in the identification and characterization of
groundwater dependent ecosystems using geospatial
technologies. Geosciences, 6(2), 17.
[25] Srivastava, P. K., Singh, S. K., Gupta, M., Thakur, J.
K., & Mukherjee, S. (2013). Modeling impact of land
use change trajectories on groundwater quality using
remote sensing and GIS. Environmental Engineering
& Management Journal (EEMJ), 12(12).
[26] Lee, S., Hyun, Y., Lee, S., & Lee, M. J. (2020).
Groundwater potential mapping using remote sensing
and GIS-based machine learning techniques. Remote
Sensing, 12(7), 1200.
[27] Al-Djazouli, M. O., Elmorabiti, K., Rahimi, A.,
Amellah, O., & Fadil, O. A. M. (2021). Delineating
of groundwater potential zones based on remote
sensing, GIS and analytical hierarchical process: a
case of Waddai, eastern Chad. GeoJournal, 86, 1881-
1894.
[28] Elewa, H. H., & Qaddah, A. A. (2011). Groundwater
potentiality mapping in the Sinai Peninsula, Egypt,
using remote sensing and GIS-watershed-based
modeling. Hydrogeology Journal, 19(3), 613.
[29] Hoffmann, J., & Sander, P. (2007). Remote sensing
and GIS in hydrogeology. Hydrogeology journal,
15(1), 1-3.
[30] Elbeih, S. F., Madani, A. A., & Hagage, M. (2021).
Groundwater deterioration in Akhmim District,
Upper Egypt: A Remote Sensing and GIS
investigation approach. The Egyptian Journal of
Remote Sensing and Space Science, 24(3), 919-932.
[31] Madrucci, V., Taioli, F., & de Araújo, C. C. (2008).
Groundwater favorability map using GIS
multicriteria data analysis on crystalline terrain, Sao
Paulo State, Brazil. Journal of Hydrology, 357(3-4),
153-173.
[32] Patra, S., Mishra, P., & Mahapatra, S. C. (2018).
Delineation of groundwater potential zone for
sustainable development: A case study from Ganga
Alluvial Plain covering Hooghly district of India
using remote sensing, geographic information system
and analytic hierarchy process. Journal of Cleaner
Production, 172, 2485-2502.

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