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JOURNAL OF INTERNATIONAL ACADEMIC RESEARCH FOR MULTIDISCIPLINARY Impact Factor 2.417, ISSN: 2320-5083, Volume 4, Issue 2, March 2016
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DELINEATION OF GROUNDWATER POTENTIAL ZONES IN MYSURU
DISTRICT, KARNATAKA, INDIA USING GEOINFORMATICS TECHNIQUE
VAHID SHARIFI1
SRIKANTASWAMY. S1
MANJUNATHA M.C2
BASAVARAJAPPA H.T2
1Department of Studies in Environmental Science, University of Mysore, Mysuru, Karnataka, India
2Department of Studies in Earth Science, Centre for Advanced Studies in Precambrian Geology, University of Mysore, Manasagangothri,
Mysuru, Karnataka, India
ABSTRACT
Water is one of the main natural resources that essential for human’s daily life,
domestic, industrial and other various fields. This needs periodic assessing and monitoring
for its sustainability. Mapping and integration of lithology, geomorphology, drainage,
lineament, soil, slope, land use/land cover and other related features had carried out in
Southern tip of Karnataka State using GIS techniques in assessing the groundwater prospect
zones. The present study aims to predict the good, moderate, poor and very poor groundwater
prospects zones using water level measured in available dug/bore wells of the study area
collected during the year 2014. Each lithological units and geomorphological landforms are
mapped during limited field visits and digitized using Visual Image Interpretation (VIIT) and
Digital Image Processing (DIP) on Satellite Remote Sensing data through GIS’s software.
The final results highlight the potentiality of GIS application in mapping of groundwater
prospect zones and its periodic monitoring and exploration in Southern tip of Karnataka
State.
KEYWORDS: Groundwater Prospect Zones; Mysuru District; Geoinformatics.
1. INTRODUCTION
Groundwater is one of the most vital natural resources and the largest available source
of fresh water (Neelakantan and Yuvaraj., 2012; Kumar., 2013). Over exploitation and large
withdrawal of groundwater resources imposes stress on groundwater regime distorting the
aquifer recharge-withdrawal equilibrium and majorly affecting the ecological imbalance
(Garg, 1976). The groundwater prospecting especially in hard rock terrains requires thorough
understanding of geology, geomorphology and lineaments of an area, which are directly
controlled by the terrain characteristics such as weathering grade, fracture extent,
permeability, slope, drainage pattern, landforms, land use/land cover and climate (Lokesha et
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al., 2005). Geomorphology controls the subsurface movement of groundwater resources at
many locations and this can be utilized for management of groundwater resources
(Valliammai et al., 2013). Lithology affects the groundwater recharge by controlling the
percolation of water flow in the study area (El-Baz and Himida., 1995). Geoinformatics
technique has emerged as a powerful tool for better delineation of groundwater prospect
zones using subsurface water level and correlation by integrating the multi thematic layers of
the study area (Carver., 1991; Goyal, et al., 1999).
2. STUDY AREA
The study area lies in between 11044’ to 12
039’ N latitudes and 75
054’ to 77
008’ E
longitudes covering an area of 6316.05 Km2 in Southern tip of Karnataka. The district is
divided into seven taluks namely Mysuru, Hunasuru, Krishna Raja Nagara, Piriyapatna,
Heggadadevana Kote, Nanjanagudu and Thirumalakudalu Narsipura (Fig.1). The general
elevation in the district ranges from 700-800 m above MSL except for the denudational hills
and ridges. Average annual rainfall is 776 mm (2012) and temperature ranges from 180 to
380C. The climate is semi-arid and undulating plains, valleys and hillocks in the area
represent the topography. Relative humidity ranges from 21 to 84% while wind speed ranges
from 7.9 (during October) to 14.1 Kmph (during July). Annual potential evapo-transpiration
is 1533.5 mm (CGWB., 2012).
FFig.1. Location map of the study area
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Fig.2. Observation Well points map of the study area
3. Materials and Methods
i. Collection of Groundwater level data: Subsurface water level data has been collected as
secondary data (Zilla Panchayat, Mysuru) for the year 2014.
ii. Satellite data: Landsat-8; ASTER G-DEM and Google Earth Image.
iii. Thematic maps: Single theme maps have been generated such as Google Earth map,
Observation well point, Lithology, Geomorphology, Drainage, Lineament, Soil, Slope,
Land use/land cover, Integration and final Groundwater prospect map (2014).
iv. GIS software: ArcGIS v10.2 and PCI Geomatica v2012.
v. GPS: Limited Ground Truth Check (GTC) has been carried out using a handheld GPS
(Garmin 12) to check the conditions of drainage, lineament, soil, slope categories and
land use/land cover patterns.
Fig.3. Landsat-8 Image of the study area
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Fig.4. Google Earth Image of the Study Area
4. Results and Discussion
4.a Lithology:
Geologically, the district is mainly composed of igneous and metamorphic rocks of
Precambrian age either exposed at the surface or covered with a thin mantle of residual and
transported soils. The rock formation in the district falls into two groups, charnockite series,
granite gneiss and gneissic complex (Basavarajappa et al., 2012). Pegmatite veins and
dolerite dykes are common intrusive in the study area. The low-lying areas are covered by a
thick mantle of fertile soil, while, the elevated portions and hills are capped by laterite
(CGWB., 2009). Chamundi granite is one of the batholiths observed within the city limits of
Mysuru (Basavarajappa et al., 2012). Dolerites are in large numbers to the west of Hunsur
and Gundlupet taluks. The Sargur schist belt in H. D. Kote taluk extends from Sargur to
Mysore city for about 40 km (Basavarajappa et al., 2012) comprising the complex series of
meta sediments and basic igneous rocks.
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Fig.5. lithology map of the study area
4.b Physiography
Mullur betta noticed with an elevation of 3150 m above MSL falls in the area. Hekkan
betta (3732 m) of the Naganpur Reserved Forest; Shigebetta (3724 m) of the Ainurmarigudi
Reserved Forest and Jainbaribetta (3231m) of the Bedrampadi reserved forest mark the water
divide making the southern boundary of H.D Kote taluk (Basavarajappa et al., 2012; CGWB.,
2012). The South Western parts of the district falls under semi-malnad category with
elevation ranging from 2,200 to 3,150 m above MSL, where as the general elevation of
uplands is noticed as 700-900 m.
4.c Geomorphology
Geomorphological process is generally complex and reflect interrelationship among
the variables such as climate, geology, soil and vegetation (Buol., 1973).
Geomorphologically, the district is classified as denudational uplands covering upto 85 to
90% of an area; while the next important geomorphological unit is noticed as older flood
plains mainly observed in H.D Kote and parts of Mysore taluks. The third important units are
the ridges and valleys which are mainly restricted to Nanjangud, H.D Kote and North
Western parts of Mysore taluks. Flat valleys are not very common except for isolated
appearances. However, the H.D Kote taluk in the southern parts of the district has higher
elevation ranging from 2200-3150 m above MSL (Pushpavathi., 2011).
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Fig.6. Geomorphology map of the study area
4.d Drainage:
The drainage pattern of the study area was digitized using ASTER GDEM of 30m
resolution; each tanks, ponds, streams, lakes and rivers were identified and digitized.
Identification of stream pattern studies help in interpreting many geological features
(Basavarajappa et al., 2012) in water resources management and groundwater studies (Anil
Kumar Misra., 2011). Drainage pattern refers to spatial relationship among streams or rivers,
which may be influenced in their erosion by inequalities of slope, soils, rock resistance,
structure and geological history of a region.
Fig.7. Drainage map of the study area
The study area is endowed with five perennial rivers namely East flowing Cauvery,
Kabini, Nugu, Gundal and Lakshmanthirtha draining major part within the district
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(Basavarajappa et al., 2012; CGWB., 2009). The main Cauvery River flows from west to east
in the northern parts of the district till its confluence Kabini River at T.Narsipura taluk.
Drainage pattern is dendritic to sub-dendritic controlled by fractures, joints & lineaments
parallel to sub-Parallel drainage pattern is also developed at few places (Basavarajappa et al.,
2012; CGWB., 2009).
4.e Lineament:
A lineament is a linear feature of structural, lithological, vegetation, drainage
anomalies which represents the underlying geological structure (Basavarajappa et al., 2012).
In hard rock terrain; lineaments & fractures act as master conduits in occurrence, movement
and storage of groundwater (Ramasamy, et al., 2005, Subash Chandra et al., 2010). The study
area is traversed by 3 sets of joints-trending in N-S, NE-SW and E-W direction. There are 4
sets of lineaments in the study area trending in NNE-SSW, NNW-SSE, NE-SW & E-W
(Basavarajappa et al., 2012; 2013; CGWB., 2009). A large part of Talakadu is covered by
sand dunes in the river bank due to fault running through the river Cauvery (Valdiya, 2008).
Fig.8. lineament map of the study area
4.f Soil:
Soil is the essential unit in controlling the infiltration of rainwater and surface flow
patterns (Basavarajappa et al., 2012). The soil types of the district are grouped into three viz.,
the red sandy soils, red loamy soils and deep black soils. Almost entire district is covered by
red sandy soil except for small parts of T.Narsipura taluk with a pH of neutral-7 measuring a
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thickness of 6m (Basavarajappa et al., 2012). The red soils are shallow to deep well drained
and do not contain lime nodules. North Eastern parts of T.Narsipura taluk comprises of red
loamy soil which is less permeable than sandy soil. It shows good moisture holding capacity
and fertile measuring a thickness of 16m (Basavarajappa et al., 2012). Deep Black soils are
dark brown, dark greyish brown to very dark grey or black in colour noticed in South
Western parts of T.Narsipura taluk (Basavarajappa et al., 2012). The texture is usually clayey
throughout the profile, fertile and produces good yields. The black soils are 1 to 1.5 m in
thickness with good water holding capacity for a longer time (CGWB., 2009).
Fig.9. Soil map of the study area
4.g Slope:
Slope is the loss or gain in altitude per unit horizontal distance in a direction
depending upon lithology, climate, meteorological parameter, runoff, vegetation, geological
structure and the process of denudation that can estimate run-off and erosion (Basavarajappa
et al., 2012). Steep slopes acts as a high runoff zone whereas gentle slope encourage more
infiltration and groundwater recharge (CGWB, 2009). Slope is an essential aspect for surface
water flow, has a bearing over the infiltration possibilities.
Fig.10. Slope map of the study area
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The slope aspect information has been derived from SoI top maps on 1:50,000 scale
(20 m contour interval) using guidelines on slope categories (AIS & LUS., 1990). The slope
of the study area is classified into 7 classes viz., nearly level (0-1%); very gently sloping (1-
3%); gently sloping (3-5%); moderately sloping (5-10%); strongly sloping (10-15%);
moderately steep to steep sloping (15-35%) and steep slopes (>35%).
Table.1. Slope categories in the study area Sl No Slope Category Slope percentage Area (Km2) Percentage (%)
1. Nearly level 0-1 2,143.34 33.93
2. Very gently sloping 1-3 2,210.41 34.99
3. Gently sloping 3-5 1,268.77 20.08
4. Moderately sloping 5-10 393.48 6.22
5. Strongly sloping 10-15 155.92 2.45
6. Moderately steep to steep sloping 15-35 77.95 1.23
7. Very steep sloping >35 55.97 0.88
Total 6,305.84 99.83
TGA 6,316.05
4.h Land use / land cover:
Earth's Land Use/Land Cover (LC/LU) classification provides information
particularly in mapping and monitoring of natural resources (Dinakar., 2005). LU/LC plays
an important role in facilitating natural groundwater recharge to the aquifers (Anirudh, 2013;
Sidhu and Rishi, 2014). Land use systems need thorough systematic management to maintain
food security, to minimize deforestation, conservation of biological diversity and to protect
the natural resources. It is necessary to enhance human occupation to the changing social,
economic and natural environmental conditions (Basavarajappa et al., 2012). LU/LC patterns
of the study area had been divided into seven classes such as agricultural land; built-up land;
forest; wastelands; water bodies and others.
Fig.11. Land Use/ Land Cover map of the study area
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Agricultural lands the land primarily used for farming, production of food, fiber, other
commercial and horticultural crops. It includes land under different seasonal crops (irrigated
and unirrigated), fallow, agricultural plantations, etc covering an area of 4,175.13 Km2. Built-
up lands are the man-made constructions due to non-agricultural use including buildings,
transportation network, communication, industrial, commercial complexes, utilities and
services in association with water, vegetation & vacant lands (Basavarajappa et al., 2012).
This category covers an area of about 257.91 Km2. Forest is an area (within the notified forest
boundary) bearing an association predominantly of trees, other vegetation types capable of
producing timer and other forest products (Basavarajappa et al., 2012). Satellite data has
become useful tool in mapping the different forest types and density classes with reliable
accuracy through visual as well as digital techniques (Sudhakar et al., 1992). Ever green/semi
evergreen, deciduous, degraded & forest plantations had digitized in the study area covering
an area of 1,005.52 Km2. Many industrial, mining and salt affected areas had demarcated as
Wastelands using Satellite image covering an area of 205.37 Km2. Water bodies includes 5
major perennial rivers, streams, canals, lakes, tanks and K.R.Reservoir was digitized using
SoI toposheets of 1:50,000 scale covering an area of 156.01 Km2 (CGWB., 2009). Others
includes mainly wetlands, aquaculture pond, dense and open grassland/ grazing land,
habitation with vegetation, tree groves and salt pans covering an area of 222.45 Km2
(Basavarajappa et al., 2012).
5. Integration
Each thematic map such as lithology, geomorphology, drainage, soil, slope, land use/
land cover layers are integrated one above the other each time to generate final output map by
providing certain weightage for each layer (Basavarajappa et al., 2012; NRSA., 2000). The
integrated map was generated to match/ compare with subsurface water level in the study
area. Each of the thematic maps is assigned a weightage grades and ranking from 1 to 4, [1-
represents Excellent; 2-Good; 3- Moderate; 4-poor groundwater prospects] (Manjunatha and
Basavarajappa., 2015). Excellent groundwater prospect zones are noticed in the alluvium
along the stream courses and weathered zones of granites & gneisses observed in parts of
Piriyapatna, K.R.Nagar, Nanjungud and H.D.Kote taluks; whereas poor prospect zones are
observed in jointed and fractured granites, gneisses and charnockites noticed in parts of
Mysuru and Hunasuru taluks (CGWB., 2009).
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Fig.12. Integration map of the study area
Table.2. Average Annual Subsurface Water Level data in meters (2014)
Sl No Observation Well points Latitude Longitude Sub surface Water level (m)
Heggada Devana Kote taluk
1. Chikkeriyur 12.1461 76.3759 16.82
2. Saragur 12.0080 76.3901 11.08
3. Mullur 11.9788 76.4771 9.21
4. Antharasanthe 12.0166 76.2986 24.53
5. Bheemanahalli 12.1856 76.2679 18.59
6. Doddabyranakuppe 11.8697 76.1467 10.79
7. Devalapura 12.0431 76.3736 20.53
8. Gangadahosahalli 12.2322 76.4391 26.44
9. Heggadadevanakote 12.0880 76.3315 3.88
10. Hampapura 12.1220 76.4774 10.83
Hunasuru taluk
11. Koyamathur Colony 12.2548 76.3287 10.25
12. Kamagowdanahalli 12.2566 76.1995 11.43
13. Gavadagere 12.3991 76.3392 7.34
14. Hunsur 12.3128 76.2884 7.82
15. Kattemalalavadi 12.3532 76.2905 9.08
16. Chilkunda 12.3396 76.1864 24.09
17. Somanahalli 12.3207 76.3413 30.66
Krishna Raja Nagara taluk
18. Bherya 12.5879 76.3504 14.06
19. Bommenahalli 12.5450 76.3697 4.54
20. Haradanahalli 12.5813 76.2082 11.78
21. Krishnarajanagar 12.4358 76.3793 11.43
22. Malali 12.4504 76.2994 7.74
23. Chunchanakatte 12.5035 76.2994 2.90
24. Thandre 12.6030 76.2701 7.03
Mysuru taluk
25. Devalapura 12.2246 76.7002 5.82
26. Kadakola 12.1933 76.6653 5.71
27. Keelanapura 12.2530 76.8186 16.67
28. Siddalingapura 12.3653 76.6613 1.78
29. Bhogadi 12.3050 76.5964 23.55
30. Alanahalli 12.2993 76.7014 17.37
31. Elwala 12.3562 76.5441 7.10
32. hebbal 12.3487 76.6123 11.03
Nanjanagudu taluk
33. Hullahalli 12.0986 76.5556 12.57
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34. Nanjangud 12.1231 76.5556 4.09
35. Thagadur 12.0934 76.8112 15.46
36. Debur 12.1198 76.6433 4.82
37. Sindhuvallipura 12.0310 76.6742 13.42
38. Hanumanapura 12.0549 76.8634 27.76
39. Hura 12.0037 76.5439 13.47
40. Kothanahalli 11.9283 76.5672 5.92
Piriyapatna taluk
41. Kanagala 12.5605 76.0270 4.81
42. Kithoor 12.4958 76.2096 5.33
43. Doddanerale 12.4765 76.0467 2.65
44. Kundanahalli 12.3816 76.0369 11.42
45. Panchavalli 12.2858 76.1360 16.53
46. Piriyapatna 12.3379 76.0974 6.58
Tirumalakudu Narasipura taluk
47. Bannahallihundi 12.1888 76.8726 11.08
48. Bannur 12.3301 76.8603 6.36
49. Hemmige 12.2076 77.0054 4.55
50. Thiramakudlu Narasipur 12.2088 76.9026 7.59
51. Thuruganuru 12.3844 76.9011 4.39
52. Mugur 12.1337 76.9316 7.28
53. Boodahalli 12.2851 76.9375 14.70
Source: Zilla Panchayath, Mysuru
Fig.13. Final Groundwater Prospects map of the study area
6. Conclusion
Groundwater potential zones are controlled by various factors and the given
weightages of each factor differs from place to place. Occurrence and yield of groundwater
are noticed to be more controlled by geology, geomorphology and structural set-up of the
study area. The final output reveals four groundwater prospect zones based on the subsurface
water level data and weightages assigned to each thematic layers using ArcGIS v10.
Excellent groundwater prospect zones are noticed in and along the major river Cauvery &
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Kabini basins; good prospect zones are noticed adjacent to the major sub-rivers basins of
Nugu, Gundal and Lakshmanthirtha; moderate prospect zones occupies the weathered &
fractured zones of granites and gneisses whereas poor prospect zones occupies small isolated
patches in southern parts of Mysore. Due to rapid increase in population; the groundwater is
over exploited especially in City centers and by farmers for agricultural activities than its
replenished. Encouraging the construction of check dams and Artificial Recharge Structures
(ARS) are the better option to store water during extreme summer seasons.
Acknowledgements
The authors are indepthly acknowledged to Zilla Panchayath, Mysuru district; Survey
of India (SoI), Bengaluru; CGWB, Bengaluru and Bhuvan, NRSC-ISRO, Hyderabad.
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