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RESEARCH PAPER
Geospatial technology for delineating groundwater
potential zones in Doddahalla watershed
of Chitradurga district, India
K. Ibrahim-Bathis
*
, S.A. Ahmed
Department of Applied Geology, Kuvempu University, Shankaraghatta, 577 451, India
Received 6 August 2015; revised 31 May 2016; accepted 17 June 2016
Available online 4 July 2016
KEYWORDS
Remote sensing;
GIS;
Semi-arid watershed;
Thematic maps;
Groundwater potential map
Abstract Groundwater is one of the valuable natural resources which determines the health of a
human being in an area. The present research investigated the hydrogeological determinants to
assess the sensitivity of each factor to the infiltration pattern and to map the regional groundwater
potential zone for the semi-arid watershed in Karnataka, India using a geographic information sys-
tem (GIS) and satellite remote sensing. It was one of the driest and water scarcest regions in the
country. Groundwater potential zones are demarcated by integrating the highly impacting thematic
layers such as land use, soil texture and depth, rainfall, slope, drainage density, lineament and geo-
morphology. The thematic layers are prepared from the remote sensing satellite images, ground
truth data and available secondary data. Cartosat-1 CartoDEM (30 m), IRS P6 LISS III (24 m)
and Landsat 8 (30 m), SOI toposheet (57 B/7, 57 B/8, 57 B/11, 57 B/12, 57 B/15 and57 B/16)
and high resolution satellite images from Google Earth were used for the preparation of thematic
maps. ArcGIS software was utilized to manipulate these data sets. Weight is assigned to each class
for each thematic map according to their characteristic and interrelationship with groundwater. All
the thematic layers are integrated into a GIS domain, and assigned weight values are added for each
polygon in the attribute table. Then each polygon is classified a groundwater zone into five different
subclasses according to the gained weight value. Only 15% of the total land area is rich with
groundwater resources. More than 70% of the total land area is moderate to poor with groundwa-
ter resources.
Ó2016 National Authority for Remote Sensing and Space Sciences. Production and hosting by Elsevier B.V.
This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-
nd/4.0/).
1. Introduction
Groundwater, or subsurface water, is a term used to denote all
the waters found beneath the ground surface (Bear and
Verruijt, 1987). It is one of the most significant natural
resources worldwide serving as a primary source of water for
communities for domestic purpose, industries, agricultural
*Corresponding author.
E-mail address: ibrahimbathis@gmail.com (K. Ibrahim-Bathis).
Peer review under responsibility of National Authority for Remote
Sensing and Space Sciences.
The Egyptian Journal of Remote Sensing and Space Sciences (2016) 19, 223–234
HOSTED BY
National Authority for Remote Sensing and Space Sciences
The Egyptian Journal of Remote Sensing and Space
Sciences
www.elsevier.com/locate/ejrs
www.sciencedirect.com
http://dx.doi.org/10.1016/j.ejrs.2016.06.002
1110-9823 Ó2016 National Authority for Remote Sensing and Space Sciences. Production and hosting by Elsevier B.V.
This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
productions (Ayazi et al., 2010; Manap et al., 2012; Neshat
et al., 2013; Pradhan, 2009), and for tourist developments
(Jaturon et al., 2014). Groundwater is naturally replenished
by rain or snow melts which seep down through the soil
and/or through pore spaces of underlying rocks (Nampak
et al., 2014). Hence, its occurrence and distribution depends
on the climate and regional setting of the region, surface and
subsurface characteristics such as fractures in the underlying
rock, land use type, geomorphic features, structural features
and their interrelationships with the hydrological characteris-
tics (Edet et al., 1998; Greenbaum, 1992; Jaturon et al.,
2014; Kumar et al., 2007; Saud, 2010; Senthil Kumar and
Shankar, 2014). Groundwater accounts for 26% of global
renewable fresh water resources (FAO, 2003). Salt water
(mainly in oceans) represents about 97.2% of the global water
resources with only 2.8% available as fresh water. Surface
water represents about 2.2% out of the 2.8% and 0.6% as
groundwater. Groundwater contributes to about 80% of the
drinking water requirements in the rural areas, 50% of the
urban water demands and more than 50% of the irrigation
needs of the nation (National Remote Sensing Agency,
2008). Groundwater demand is drastically increasing due to
the immense pressure on population and urbanization, global
impact due to climate and weather change, repetitive drought
condition and lack of rainfall. Over exploitation of the ground-
water resource caused a sudden decline in the groundwater
table and an excess in the sustainability of groundwater
resources (Jaturon et al., 2014; Rahman, 2001). Especially
the agrarian states like Karnataka, the groundwater depen-
dence is high. Recent studies indicate that 26% of the area
of Karnataka state is under overexploited category and num-
bers of villages are under the critical category (Central
Ground Water Board, 2013). According to a World Bank
report, India will be in water stress zone by the year 2025
and water scarce zone by 2050. Insufficient education on
groundwater exploitation and conservation, improper balance
in exploitation and recharge, failure of government schemes in
rural areas where poor access to the groundwater, etc. are
some of the major groundwater and drinking water problems
in India.
Remote sensing and geographical information system with
their advantages of spatial, spectral and temporal availability
and manipulation of Earth surface and subsurface data cover-
ing vast and inaccessible areas within a short time have a great
potentiality in groundwater hydrology for accessing, monitor-
ing and conserving groundwater resources (Dar et al., 2010).
The complexity of conventional exploration methods such as
field-based hydrogeological, geophysical resistivity surveys,
exploratory drilling which is more time-consuming and very
expensive, supports the application of satellite-based Geospa-
tial Science (Gumma and Pavelic, 2013; Nampak et al., 2014;
Singh and Prakash, 2002). Hydrologists are now familiar with
the integration of multi-thematic maps of the Earth surface
and subsurface through the application of remote sensing
(RS) and geographical information system (GIS) techniques
for delineating the groundwater prospective zones for explo-
ration, development and sustainable management of ground-
water resources (Gumma and Pavelic, 2013; Murthy, 2000;
Rashid et al., 2011; Senthil Kumar and Shankar, 2014).
Researchers have utilized the Geospatial technology for the
groundwater mapping by integrating thematic maps such as
geomorphology, drainage pattern, lineament, soil (Preeja
et al., 2011; Rassam et al., 2008; Saraf and Choudhary,
1998), rainfall intensity and soil texture (Magesh et al.,
2012), resistivity, aquifer thickness, or fault maps (Senthil
Kumar and Shankar, 2014). In the present work groundwater
prospective zone mapping was carried out for Doddahalla
watershed in the drought prone district of Karnataka state,
India by integrating the thematic maps such land use land
cover, geomorphology, soil texture and depth, slope, linea-
ment, drainage and rainfall maps in a spatial domain of GIS
environment.
2. Study area
The Doddahalla watershed is part of the lower Tungabhadra
catchment of Krishna basin. The watershed covers an area
of 1082 km
2
lying in between Chitradurga, Hiriyur and Chal-
lakere taluk of Chitradurga district of Karnataka (Fig. 1).
Geographically the area extends from 76°2101000Eto
76°5003000E longitude and 14°409.4200 Nto14°2500000N latitude.
Physiographically the watershed can be called a dry and thirsty
land with broken hills ranges and huge undulating plains
(Ibrahim-bathis and Ahmed, 2014a). The average rainfall in
the area is 578 mm. Fifty percent of the annual rainfall is
received during the southwest monsoon season (Ibrahim-
bathis and Ahmed, 2014b). The quality of vegetation is poor
because of poor rains. However, small groves of the trees are
to be seen in rural villages. The agricultural seasons in the dis-
trict highly depend on the rainfall and the climate (Ibrahim-
bathis and Ahmed, 2013). The region experienced severe
drought in the year 2002, 2003, 2004 and 2006 (Central
Ground Water Board, 2013) resulted in the failure of agricul-
ture. Due to the scarcity of abundant surface water farmers
have to turn groundwater resources for irrigation. Groundwa-
ter contributes to more than 70% for irrigation. Hence, the
present research contributes and delineates the potential
groundwater prospective zones for the sustainable develop-
ment of the agriculture and to fulfill the domestic water needs.
3. Materials and methodology
In the present study, the groundwater prospective zone map-
ping is carried out by integrating satellite derived multi the-
matic maps using GIS techniques. Cartosat-1 DEM (30 m),
Landsat 8 Operational Land Imager (OLI 30 m), Survey of
India (SOI) toposheets (57 B/7, 57 B/8, 57 B/11, 57 B/12, 57
B/15 and 57 B/16) and high resolution satellite images from
Google Earth (Digital Globe, Astrium and SPOT) were used
for preparation of thematic maps. Seasonal Landsat 8 images
are used to prepare the thematic map and the date and month
of each images are shown in the Table 1. All data are georec-
tified and projected to Geographic Coordinate System-World
Geodetic System 1984 (GCS WGS) Universal Transverse Mer-
cator (UTM) zone 43 North for the easy handling in a GIS
environment (Ibrahim-bathis and Ahmed, 2016). Satellites
data are enhanced and processed in Erdas Imagine 9.2 for
the better visualization. SOI toposheets are used as reference
maps for the preparation of thematic maps. Individual maps
are updated from the recent available images in Google Earth
through the color pattern and their appearance in the image.
Weight is assigned to the individual classes for each thematic
map according to their characteristics and interrelationships
224 K. Ibrahim-Bathis, S.A. Ahmed
with groundwater (Table 2). All the thematic layers are inte-
grated into the GIS domain, and assigned weight values are
collectively summed for each class in the attribute table
(Table 4). The groundwater zones are delineated into five dif-
ferent classes according to the highest value gained as excellent
groundwater potential zone and lowest gained value as nil or
poor groundwater potential zone (Table 4).
3.1. Land use land cover map (LULC)
Land use type gives the necessary information on infiltration,
soil moisture, groundwater, surface water, etc. Cloud-free
Landsat 8 Operational Land Imager (OLI) images of 2014
are utilized for the LULC mapping (Table 1). Each spectral
band of Landsat data is converted to radiance and then to
reflectance to minimize the spectral and sensor noise induced
during image acquisition. Converted reflectance values of red
(band 4) and near infrared (band 5) bands are used for Nor-
malized Difference Vegetation Index (NDVI) measurement
(Eq. (1)). NDVI values range from 1 to +1. NDVI values
for vegetated land areas range from around 0.1 to 0.6, with
values greater than 0.4 indicating dense vegetation. Values less
than 0.15 indicate no vegetation, e.g. barren area, rock, sand
or snow. The value below zero indicates wet areas and water
bodies (Rulinda et al., 2012). NDVI images are then reclassi-
fied into six land cover classes representing forest, Kharif crop-
land, Rabi cropland, double crop land, built up/barren, and
water bodies according to the above mentioned standard val-
ues represented in the images (Fig. 2). SOI toposheet and sec-
ondary LULC maps from NRSC (level I classified image from
AWiFS acquired on 08/03/2008 with six land cover classes) are
used as a reference map for the preparation of LULC map
(Rawat and Manish Kumar, 2015). Individual LULC classes
were updated from the recent available images in Google
Earth through the color pattern and their appearance in the
image. Forest vegetation and agricultural cropland possess
more cracks in the soil and loosen the compactness of the soil
that intern accelerates the infiltration rate in the soil (Table 2).
Cropland covers only 60% of the total land area. Nearly 50%
of the agriculture land is Kharif crop. The high weight is
assigned to the forest plantation, agricultural plantation and
double crop land. The low weight is assigned to the seasonal
crops and fallow land (Table 2).
NDVI ¼NIR RED
NIR þRED ð1Þ
3.2. Soils texture and depth
The area is characterized by a fertile black soil rich in bases
and having water holding capacity. Black soils found in a wide
Figure 1 Location map of Doddahalla watershed.
Table 1 Landsat 8 band information used for the NDVI
analysis.
Satellite/
sensor
Date of image
acquisition
Band Wavelength
(l)
Landsat 8
OLI
2014 January 17
2014 May 25
2014 November 17
Band 4
RED
0.64–0.67
Band 5
NIR
0.85–0.88
Geospatial technology for delineating groundwater potential zones 225
area in the watershed are particularly suited for rainfed crops
like short-staple cotton, groundnut, jowar, and tur dhal. Soils
in the region are found to contain a high concentration of sol-
uble salts which are either critical for growth or critical for ger-
mination. Clay, sandy clay, and silt clay are dominant soils
and food crops are the major agricultural practice. Soil map
can be prepared using the high resolution satellite images
and along with extensive field data (Ismail and Yacoub,
2012). Available secondary maps from the National Bureau
of Soil Survey and Land Use Planning (NBSS and LUP) Ban-
galore and satellite images are used to map the soil types of the
area (Fig. 3). Clay, sandy loam and sandy clay loam together
covers 70% of the total land area. The soil depth varies from
25 cm to 100 cm (Fig. 4). The gravelly sand soils possess more
open spaces to fill the water than the compact clay or silt
soils. The dry clay soil exhibits multiple cracks in the top layer
that enhance rapid infiltration. However, the wet clay soil has
more water holding capacity than the infiltration rate. The
weight is assigned based on the texture and depth of the soil
(Table 2).
3.3. Soil infiltration
Infiltration is the water penetration into the soil and subsur-
face layer from the precipitation or by snowfall. It is one of
the important soil hydraulic properties for agriculture and
water research because of its necessary role in agricultural irri-
gation, land-surface and subsurface hydrology. Prior knowl-
edge of the infiltration pattern in an area is required for
designing the efficient irrigation systems for the sustainable
agriculture especially in the arid and semi-arid rainfed agricul-
tural region. The rate of infiltration is varied spatially and tem-
porally (Table 3). Dry soil infiltrates more rapidly, and
eventually it reaches a steady rate when all air pores in the soil
layer are filled with the water. Quantitative measurement of
the rate of soil infiltration in a watershed is difficult because
it depends on many factors such as soil texture, surface topog-
raphy, the intensity of rainfall and vegetation cover, etc. The
infiltration characteristic is also directly connected with
groundwater resources as the infiltration increases, the ground-
water resource is also getting flourished. The dry clay soil exhi-
bits more cracks and possesses high infiltration but wet clay
soil holds more water content than the infiltration. Black clay
soil covers more than 60% of the study area. The soil infiltra-
tion map is prepared from the quantitative soil measurement
calculated from Soil Conservation Service-Curve Number
(SCS-CN) loss model in the Hydrologic Engineering Center-
Hydrologic Modeling System (HEC-HMS) (Fig. 5) and
cross-validated with the secondary published data (Ibrahim-
bathis and Ahmed, 2016).
3.4. Rainfall
Rainfall is the most dominant influencing factor in the ground-
water potentiality of any area and is the major water source in
the hydrological cycle. Annual rainfall data are collected from
the rain gauging stations of the Indian Meteorological station
(IMD). The study area has a limited number of rain gauge sta-
tions hence the telemetric stations are also used to determine
the average annual rainfall in the area. The rainfall map is pre-
pared by employing an Inverse Distance Weightage (IDW)
interpolation method in ArcGIS. The annual rainfall ranges
from 288 mm to 739 mm, and grouped into five categories
(Fig. 6). Intensity and duration of rainfall play a significant
role in infiltration. High intensity and short duration rain pos-
sesses less infiltration and more surface runoff. Low intensity
and long duration rain possesses high infiltration than the run-
off. High weight is given to the high rainfall area and least
weight is given to low rainfall area (Table 2). More than
50% of the total land area receives only 578 mm average
annual rainfall.
3.5. Slope
Slope is the rate of change of elevation, and is also a significant
factor in identifying groundwater potential zones. Increased
slope results in high runoff and erosion of surface soil. Gentle
and nearly level surface slope allows water to flow very slowly
and provide adequate time to infiltrate into the soil. High
weight is assigned to the nearly level and gentle slope (Table 2).
Cartosat DEM of 30 meter spatial resolution image was used
to prepare the slope map of the area. Slope map was divided
into five classes according to the percentage of their gradient,
and the value ranges from 0% to 50% (Fig. 7). Zero percent-
age is near level plain land, and 50% is very steep slope area.
About 90% of the total area is gentle and nearly level land
which allows the maximum infiltration than runoff.
Table 2 Groundwater and infiltration weightage assigned to
the individual class for a thematic layer (Manap et al., 2013).
Thematic class Weightage Thematic class Weightage
LULC class Soil texture
Forest 5 Clay 1
Kharif + Rabi
(double crop)
5 Clay loam 2
Kharif crop 4 Silty clay loam 2
Rabi crop 4 Loamy sand 3
Built-up land 3 Sandy clay loam 3
Water bodies 5 Gravelly loamy
sand
5
Rainfall (mm)Soil depth (cm)
288–394 1 Very shallow
(10–25)
1
394–465 2 Shallow (25–50) 2
465–523 3 Moderate
shallow (60–75)
3
523–609 4 Moderate deep
(75–100)
4
609–739 5 Deep (>100) 5
Slope in % Drainage density (km/km
2
)
0–1 5 0.26–1.02 5
1–5 3 1.02–2.48 4
5–50 3 2.48–3.97 3
Geomorphology Lineament density (km/km
2
)
Denudational and
structural hills
1 0.0–0.39 1
Pediment – inselberg
complex
2 0.39–0.78 2
Pediplain weathered 3 0.78–1.18 3
Valley fill 4 1.18–1.57 4
Pediplain moderately
weathered
5 1.57–1.97 5
226 K. Ibrahim-Bathis, S.A. Ahmed
Figure 2 LULC classification map of Doddahalla watershed.
Figure 3 Soil textures classification map of Doddahalla watershed.
Geospatial technology for delineating groundwater potential zones 227
3.6. Drainage density
Drainage density is the closeness of spacing of stream chan-
nels, and it is the ratio of the total length of the stream segment
of all orders per unit area (Singh et al., 2014). The drainage
density is an inverse function of permeability which plays a
vital role in the runoff distribution and level of infiltration.
Drainage networks are extracted and delineated from Carto-
DEM with the help of Arc Hydro tool 9.3 for ArcGIS
(Ibrahim-bathis and Ahmed, 2013). Extracted drainages are
updated both from Landsat 8 data and real-time Google Earth
images. Delineated drainages overlaid on the digitized streams
from SOI topo map, which shows almost similar patterns.
Drainage density map was prepared using the line density
analysis tool in ArcGIS software (Fig. 8). The value ranges
from 0.26 to 3.97 km/km
2
(Sreedevi et al., 2009). Drainage
density is inversely related to the soil infiltration capacity; high
weight is given to low density, and high density is assigned less
weight (Table 2).
3.7. Lineament density
Lineaments are the most prominent structural features that are
important from the groundwater point of view (Pradhan,
2009). They appear as linear alignments of structural, litholog-
ical, topographical and drainage anomalies, etc. as straight
lines or as curvilinear features. Lineament map was prepared
from the drainage network and visual interpretation of false
color Landsat 8 image (Deepika et al., 2013; Chaabouni
et al., 2012; Teikeu Assatse et al., 2016). Google Earth images
Figure 4 Soil depth map of Doddahalla watershed.
Table 3 Rate of soil infiltration in the different soil texture
(Ibrahim-bathis and Ahmed, 2016).
Sl no Soil texture Infiltration rate
mm/h
1 Gravelly loamy sand 30
2 Sandy loam 20–30
3 Loamy sand 15–20
4 Sandy clay loam 10–15
5 Silty clay loam 7.5–10
6 Clay loam 5–10
7 Clay 1–5
Table 4 Area statistics, weightage values and their corre-
sponding rankings for Groundwater potential zone in Dodda-
halla watershed.
Sl
no
Individual
weightage
value
Total values
gained from
integration
Ranking Area
in
km
2
Area
in %
1 1 2–12 Nil 18.98 1.75
2 2 13–16 Poor 422.1 38.98
3 3 17–18 Average 376.91 34.81
4 4 19–20 Moderate 115.32 10.65
5 5 21–22 Good 106.93 9.87
6 5 23–24 Very
good
42.65 3.94
228 K. Ibrahim-Bathis, S.A. Ahmed
Figure 5 Soil infiltration pattern map of Doddahalla watershed.
Figure 6 Annual rainfall map of Doddahalla watershed.
Geospatial technology for delineating groundwater potential zones 229
Figure 7 Slope map of Doddahalla watershed.
Figure 8 Drainage density map of Doddahalla watershed.
230 K. Ibrahim-Bathis, S.A. Ahmed
are utilized to cross check the linear feature in the image where
field data are limited. The density of these linear features
ranges from 0.0 to 1.97 km/km
2
(Fig. 9). An area having the
high lineament density is considered as high groundwater zone
(Table 2).
3.8. Geomorphology
The major geomorphic feature is initially digitized from the
toposheet, and minor feature is then updated from the satellite
images and the Cartosat DEM image (El-Gammal et al.,
2013). The differences in elevation, contour lines, and types
of vegetation give a clue to map the geomorphological fea-
tures. The available secondary data and high resolution satel-
lite images from the Google Earth are used to classify micro
features. The area is nearly plain and shows gentle slope from
southwest to northeast. Elevated hills are seen only in the
extreme southwest region of the watershed (Fig. 10). A shallow
weathered plain covers more than 60% of the total land area.
High weight is assigned to the low lying weathered geomor-
phological unit and low weight to the highly elevated hard
rock hillock (Table 2).
4. Groundwater potential zone
For mapping groundwater prospect zones individual thematic
maps are prepared from the satellite data, toposheet, field sur-
vey and available secondary data. A thematic map classified
into different subclasses, and each is assigned a weight value
according to the interrelationships between the occurrences
of groundwater (Table 2). Previous literature and secondary
data are referred while assigning the weight to individual the-
matic classes. After assigning weights to the individual class in
each theme, the whole thematic layer is integrated into a single
layer in ArcGIS software. The aggregate weight value of each
sub-class in the integrated layer is categorized into five individ-
ual groups as groundwater prospect zones (Table 4). The high
weight value is categorized as the very good prospect zone and
the least weight values as the poor prospect zone. Very less
area identified as the rich in groundwater resource (Fig. 11).
More than 70% of the total land area categorized as moderate
to poor groundwater resource.
5. Result and discussion
Groundwater potential zone map is essential for the agricul-
tural watershed like the Doddahalla watershed. Rainfall is
irregular, and the area is not well irrigated from canals or
channel irrigation. There is no perennial water reservoir or
tanks to supply water for agriculture throughout the year.
Hence, the farmer is forced to drill wells for the crop irrigation
and domestic water purpose. Mapping groundwater prospect
zones is a systematic effort and prepared by considering signif-
icant governing factors, which influence soil infiltration and
enhances groundwater. The present groundwater prospect
map satisfies and exposes the meaningful information and best
site for the groundwater exploration (Fig. 11). Thick vegeta-
tion, tree plantation, and agricultural field are given high
weight in the land use theme. Water penetrates to the ground
through the roots of trees and plants. Weathered pediplain and
Figure 9 Lineament density map of Doddahalla watershed.
Geospatial technology for delineating groundwater potential zones 231
Figure 10 Geomorphology map of Doddahalla watershed.
Figure 11 Groundwater potential zone map of Doddahalla watershed.
232 K. Ibrahim-Bathis, S.A. Ahmed
valley region are given high weight in geomorphology theme.
Groundwater occurs within the weathered and fractured
gneisses, granitic gneisses and Amphibolites rocks. Slopes are
a major governing factor for groundwater. The steep slope
allows the rainwater to runoff, and gentle slope region permits
the rainwater to infiltrate to the soil. High weight is given to
nearly level and gently slope area, and steep slope area is given
poor weight. Lineament density is another important factor in
groundwater resource. Groundwater is stored in the joint and
fractures of hard rock. Soil texture and soil depth play an
important role in the infiltration and ground water zone. The
compact clay soil holds the water than to allow penetration.
However, the gravelly sand particles in the soil allow more
infiltration and water storage. High potential zones mainly
found along lineaments, pediplains and along the nearly level
area with less than 2% slope. The areas of valley fills and river
banks exhibited very good groundwater potential zones.
Moderate potential zones are located in the fallow land and
the gently slope area. The low potential zones typically are
located in the moderate-to-steep slope area, denudation hills,
scrub land and barren land.
6. Conclusions
Groundwater potential map is prepared from high resolution
and freely available satellite images. It reduces the traditional
field survey and consumes less power and time. The present
research result provides the preliminary information on the
groundwater resources of the area. The depth of groundwater
level changes through the seasons and in the monsoon and
post monsoon period the groundwater depth is nearly 5–
10 m below ground level in most places according to the Cen-
tral Ground Water Board (CGWB) report. This depth
increases toward the upstream region and decreases toward
the downstream. The present groundwater resource will be fur-
ther enhanced by adopting the water harvesting structures and
deepening on the existing lakes and tanks. The measure has to
initiate to reduce the surface runoff and increase the infiltra-
tion and surface water bodies. Delineated groundwater zone
map is useful for locating the drilled well and dug well for
the irrigation and domestic water consumption purpose. The
majority of the crops in the region depends on rainfall, and
the development of the irrigation facility will enhance the agri-
cultural productivity in the region.
Conflict of interest
There is no any conflict of interest.
Acknowledgements
The authors acknowledge the Dept. of Applied Geology,
Kuvempu University for providing the available facilities to
carry out this work. The first author also wishes to acknowl-
edge Ministry of Minority Affairs and University Grant Com-
mission for providing MANF fellowship.
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