Int. Journal of Applied Sciences and Engineering Research, Vol. 1, No. 2, 2011
© Copyright 2011 - Integrated Publishing Association
Research article
www.ijaser.com
editorial@ijaser.com
ISSN 2277 – 8442
Identification of Ground Water Potential Zone in Hard Rock
Terrain – A Case Study From Parts of Manapparai Block Tamil
Nadu Using Remote Sensing And GIS Techniques
Selvam.G1, Srinivasan.D2, Selvakumar.R3, P.Alaguraja4
1
Mr. G.Selvam Research Scholar Department of Geology National College, (Autonomous)
Tiruchirappalli-620 001.
2
Dr. D.Srinivasan Associate Professor Department of Geology National, College (Autonomous)
Tiruchirappalli-620 001.
3Dr.R.Selvakumar Associate Professor Department of Civil Engineering, Sastra University, Vallam.
4MrP.Alaguraja , DST Inspire Fellow, Research Scholar, Dept.of Geology, Bharathidasan
University, tiruchirappalli-620024
doi: 10.6088/ijaser.0020101021
Abstract: Freshwater is a scarce resource with partial existence above and predominantly beneath the
surface. Owing to population explosion and improper management, the resource is depleting drastically
and is accomplished by extensive mining of groundwater. But the occurrence of groundwater that too in
hard rock terrain still remains enigmatic. The movement and storage of groundwater is controlled by
various terrain parameters. Hence geoscientists were employing various techniques to explore the potential
zone amongst Multi-Criteria Evaluation (MCE) technique seems to be more precise in demarcating the
potential zone. Remote sensing and geographic information system (GIS) has proven as effective tools in
mapping and modeling terrain features. In this context, an attempt has been made to identify groundwater
potential zone in parts of Manapparai block, central Tamil Nadu, India using Remote Sensing and GIS. The
study area chiefly comprises of crystalline gneissic rock of Archaean age. Thematic layers were generated
on geomorphology, landuse/land cover, lineament density etc. Base on the potentiality to groundwater,
weights were assigned to individual themes and ranks to features in each theme and by multiplying both,
feature Scores were derived. Themes were converted into raster datasets and added using raster calculator.
The final integrated map was regrouped into five classes of groundwater potential zones as very good,
good, moderate, moderately poor and poor.
Keywords: Geomorphology, Landuse/land cover, Lineament and its Density, Groundwater potential
zones map.
1. Introduction
Water an essential commodity to mankind. Despite drinking purpose, it is an importance source for
agricultural and industrial Sector. During the past few decades, the available resource is in decline. India
too is heading towards a fresh water crisis. Identification of potential zone ever remains a mystery. Hence
geoscientists were adopting various techniques to target groundwater. Amongst high resolution satellite
images are increasingly used in groundwater exploration because of their utility in identifying various
---------------------------*Corresponding author (email: geoselvar @gmail.com)
Received on, March 2012; Accepted on March 2012; Published on April, 2012
212
Identification of Ground Water Potential Zone in Hard Rock Terrain – A Case Study From Parts of Manapparai Block Tamil
Nadu Using Remote Sensing And GIS Techniques
ground features, which may serve as direct indicators of presence of ground water (Krishanmurthy, et al.,
1996; Das et al., 1997; Ravindran and Jayaram, 1997; Pratap, et al., 2000; Sankar, 2002; Bahuguna, et al.,
2003; Jagadeeswara Rao, et al., 2004; Ratnakar Dhakate, et al., 2008). Indirect analysis of some directly
observable terrain features like geological structures, geomorphology and their hydrologic characteristics
using remote sensing enables to target groundwater (Basudeo Rai, et al., 2005; Lokesha, et al., 2005;
Samuel Corgne, et al., 2010 ).The geographic information system (GIS) has emerged as a powerful tool in
integration and analysis of multi thematic layers in delineating ground water prospect and deficit zones
(Carver, 1991; Hoogendoorn Goyal, et al., 1993; Saraf and Chaudhuray, 1998; Goyal, et al., 1999; Rokade,
et al., 2007, Thushan Chandrasiri Ekneligoda and HerbertHenkel, 2010). In the present study using satellite
data and collateral datasets various surface and subsurface features were interpreted. Based on their
potentiality to groundwater, weights were assigned to individual thematic layers and ranks to individual
features in each theme. By multiplying both, scores of each feature were derived. Finally using GIS, all the
themes were integrated and classified into different classes of groundwater potential zones.
1.2 Aim and Objectives
The main aim is to identify groundwater potential zones in parts of Manapparai block, Trichirappalli
District through,
 Preparation of thematic maps on surface and subsurface features viz: Geomorphology,
Landuse/land cover, Lineament and its Density, Drainage and its Density etc.,
 Assigning weight and ranks for individual themes and their corresponding features and thereby
deriving factor scores by multiplying both.
 Integrating all using GIS and demarcating groundwater potential zones.
1.3 Methodology
The occurrence of groundwater is an interdependent phenomenon where multiple parameters like lithology,
geomorphology, slope, thickness of aquifer etc., governs the rate of infiltration and storage potential.
Hence in the present study a Multi-Criteria Evaluation (MCE) method is adopted. For the same thematic
layers were prepared on both surface and subsurface parameters, converted into vectors using ArcGIS 9.2
software. Weights were assigned to individual themes (Wt) and for each features within the theme, ranks
were given (Wi) based on the knowledge upon their significance to groundwater. By multiplying theme
weight (Wt) with feature rank (Wi), factor scores were derived for each features. Likewise scores were
derived for all the themes. Subsequently themes were converted into raster format thus each pixel contains
factor scores with respect to their potentiality to groundwater. Finally, all the thematic layers were
integrated and the total factor scores for each pixel were calculated through raster addition process in
Spatial analyst extension of ArcGIS 9.3.Based on the derived scores, the final integrated map was
classified into five categories of groundwater prospect zones as (i) Very good (ii) Good (iii) Moderate (iv)
Moderately Poor and (v) Poor.
1.4 Study Area
The study area falls in parts of Manapparai block (survey of India toposheet (58 J/6), Tiruchirappalli
district (Fig.1) covering an area of 720 sq.km comprising of twenty eight villages. Mostly rain fed area and
Selvam.G, Srinivasan.D, Selvakumar.R, P.Alaguraja
Int. Journal of Applied Sciences and Engineering Research, Vol. 1, No. 2, 2012
213
Identification of Ground Water Potential Zone in Hard Rock Terrain – A Case Study From Parts of Manapparai Block Tamil
Nadu Using Remote Sensing And GIS Techniques
main source of irrigation are tanks and wells.
Figure 1: Study Area
1.5 Thematic Layers
Thematic layers include surface (Lithology, Geomorphology, Landuse and Cover, Drainage Density and
Lineament Density) and subsurface parameters (depth to water level and bedrock).
Thematic Layers
Weight
(Wt)
Table 1: Weighted Factors
Features
Rank
(Wi)
7
Feature
Scores
42
Hornblende-biotite gneiss
Pink augen gneiss
Amphibolite
Pyroxene granulite
Calc-granulite and limestone
Granite
Quartzite
Buried Pediment Deep
Buried Pediment Moderate
Buried Pediment Shallow
Pediment
Residual Hill
6
6
5
5
3
3
1
8
6
4
3
1
36
36
30
30
18
18
6
80
60
40
30
10
Structural Hill
Crop Land
Plantation
Land With Scrub
Scrub Forest
Land Without Scrub
Very High
High
1
6
5
4
3
2
5
4
10
30
25
20
15
10
35
28
Charnockite
Lithology
6
Geomorphology
10
Landuse Land Cover
5
Lineament Density
7
Selvam.G, Srinivasan.D, Selvakumar.R, P.Alaguraja
Int. Journal of Applied Sciences and Engineering Research, Vol. 1, No. 2, 2012
214
Identification of Ground Water Potential Zone in Hard Rock Terrain – A Case Study From Parts of Manapparai Block Tamil
Nadu Using Remote Sensing And GIS Techniques
Drainage Density
7
Depth to Water level
8
Depth to Bed Rock
7
Moderate
Low
Very Low
Very Low
Low
Moderate
High
Very High
Very Low
Low
Moderate
High
Very High
Very High
High
Moderate
Low
Very Low
3
2
1
5
4
3
2
1
5
4
3
2
1
5
4
3
2
1
21
14
7
35
28
21
14
7
35
28
21
14
7
35
28
21
14
7
Using Survey of India (SOI) toposheet drainage map was prepared and lithology by district resource map
(GSI). Using IRS 1C LISS-III Geocoded satellite data of 20th June 2000 thematic layers on
Geomorphology, Lineament, Land use/land cover were prepared through visual interpretation techniques.
Water level data was collected for 30 years and mean water level was worked out. Similarly using
resistivity data, depth to bedrock (aquifer thickness) was worked out. Contours were generated on depth to
water level and depth to bed rock. Overall a weight of fifty is taken into account. Since geomorphology
seems to be the most dominant controlling theme a weight (Wt) of 10 is given followed by depth to water
level with 8, lineament density, drainage density and depth to bed rock with 7, lithology 6 and land use and
land cover 5. Similarly based on potentiality to groundwater ranks were assigned to each features. Using
the formula, feature scores were calculated (Table – I)
Feature Score (Fs) = Theme Weight (Wt) × Feature Rank (Wi)
1.6 Surface Parameters
1.6.1 Lithology
The study area comprises of Precambrian metamorphic rocks viz: amphibole, calc-granulite, charnokite,
granite, quartzite, augen gneiss and pyroxene granulite amongst, hornblende-biotite gneiss covers major
part. Ranks were assigned to each lithological unit on the basis of their porosity and permeability. Since
Charnockite posses high porosity and permeability, a rank of 7 is assigned similarly a rank of 6 to
hornblende – biotite gneiss and pink augen gneiss, 5 to amphibolites and pyroxene granulite and 3 to
granite and quartzite. By multiplying theme weight (6) with feature rank (Wi), factor scores were derived
(Table – I). The derived score ranges from maximum of 42 to a minimum of 6. Based on the groundwater
potentiality, were classified into five categories as very high, high, medium, low and very low and the
same is converted into raster format (Fig.2).
1.6.2 Geomorphology
As far as groundwater potentiality is concerned the hilly and undulatory topography forms runoff zones
Selvam.G, Srinivasan.D, Selvakumar.R, P.Alaguraja
Int. Journal of Applied Sciences and Engineering Research, Vol. 1, No. 2, 2012
215
Identification of Ground Water Potential Zone in Hard Rock Terrain – A Case Study From Parts of Manapparai Block Tamil
Nadu Using Remote Sensing And GIS Techniques
whereas plain and depressed topography forms infiltration zone (Jayakumar and Ramasamy 1996).
Generally buried pediment zones forms favorable locales for infiltration and based on their thickness, buried
pediment deep zones were assigned with rank of 8, medium 6 and shallow with 4. Whereas the pediments act
more as runoff zone with subtle infiltration hence rank of 3 is assigned. Since residual and structural hills acts
as runoff zones, a rank of 1 is assigned to both. As earlier factor scores were derived and classified into five
categories (Table – I).
Figure 2: Lithology
1.6.3 Land use / Land Cover
Based on the potentiality, Land use / Land cover features were assigned ranks. In agriculture land water
will be stored for agriculture practices thus acts as better recharge zones and hence a rank of 6 is assigned.
Likewise rank of 5 to plantation, 4 for land with scrub, 3 for scrub land and 2 for land without scrub is
given and classified into five categories (Table-I).
1.6.4 Drainage Density
Drainage density indicates closeness in spacing of channels, thus providing quantitative measures of length
of stream within a square grid of the study area. Wherever the density is high then surface runoff will be
more on contrary in low density areas infiltration will be more. Grid map having a cell size of 250 x 250m
each is superposed over the drainage layer and total length of the drainage per grid is calculated. In order to
normalize the data, contours were generated using SURFER Software. The contour map shows that
drainage density ranges from 28 km/sq.km to 2 km/sq.km. Classified into five categories and highest rank
of 5 is assigned to low density area and least for high density area.
Selvam.G, Srinivasan.D, Selvakumar.R, P.Alaguraja
Int. Journal of Applied Sciences and Engineering Research, Vol. 1, No. 2, 2012
216
Identification of Ground Water Potential Zone in Hard Rock Terrain – A Case Study From Parts of Manapparai Block Tamil
Nadu Using Remote Sensing And GIS Techniques
1.6.5 Lineament Density
In hard rock terrain lineaments and fractures act as master conduits in movement and storage of
groundwater (Ramasamy, et.al. 2005, Subash Chandra, et.al., 2010). On contrary to above, if lineament
density is high then higher will be the rate of infiltration whereas low density leads to more runoff (Kumar,
et al., 1999). Contours were generated on lineament density and the same shows density ranges from 2 km
in length to 40 km in length. On the basis of groundwater potentiality they were regrouped into five classes
as very high (34 - 40 km), high (26 – 33 km), Moderate (18 – 25 km), Low (10 – 17 km) and very low (2 –
9 km) and accordingly ranks were assigned (Table - I).
1.7 Subsurface Parameters
1.7.1 Depth to Water Level
Water level data was collected from over 12 wells (PWD department) for both pre and post monsoon
period from 1991 – 2000. Mean water level was worked out and plotted in their respective geographical
positions and contours were generated using SURFER software. The perusal of map shows that the value
ranges between 6.6 meter and 10.2 meter below ground level. As far as water level is concern lower the
value then water is available at shallow depth while higher value means water is at deeper level.
Accordingly classified into five group’s and feature scores were derived (Table - I).
1.7.2 Depth to Bedrock
The thickness of aquifer determines the amount of water that can be stored beneath the surface of the earth.
It includes thickness of topsoil, weathered and fractured zone in that area. In order to estimate the same,
resistivity data was collected, plotted in their respective geographical locations and contours were
generated as stated earlier. In order to evolve the potentiality the same is classified into to five classes,
ranks were assigned and feature scores were derived accordingly (Table - I).
1.8 Identification of Groundwater Potential Zone
The above thematic vector layers were converted into to raster format. Using raster calculator in spatial analysis
module of Arc GIS, all the raterised thematic layers were added one over the other and there from final integrated
groundwater prospect map was derived (Fig.3). The overall feature scores of individual pixel ranges from 73 to
258. The pixels were regrouped into five categories of groundwater prospects zones viz. very good, good,
moderate, moderately poor and poor. Perusal of map shows that very good groundwater prospect with overall
feature score 200 – 258 occurs in northwestern, eastern and southwestern parts of the study area thus constituting
about 21% of the total area. Good category is mostly found on the western and central parts of the study area
having feature score of 188 – 220 and occupying 23%. Moderate zone with feature score of 157 – 189 are found
sporadically in the entire study area with an aerial coverage of 25%. Similarly, moderately poor category is also
found sporadically in the entire study area with feature score of 121 – 157 and covering an area of 25%. Whereas
poor groundwater prospect zone seems to be confined as patches in the northern and southern parts of the study
area with feature score of 73 – 121 and encompassing an area of 6% From the above it is evident that moderate and
moderately poor potential zone comprises 50% of the study area followed by good and very good zones whereas
the poor potential zone seems to occupy the least area.
Selvam.G, Srinivasan.D, Selvakumar.R, P.Alaguraja
Int. Journal of Applied Sciences and Engineering Research, Vol. 1, No. 2, 2012
217
Identification of Ground Water Potential Zone in Hard Rock Terrain – A Case Study From Parts of Manapparai Block Tamil
Nadu Using Remote Sensing And GIS Techniques
Figure 3: Ground Water Prospect map
1.9 Results and Discussion
Occurrence of groundwater is governed by multiple parameters. Hence in the present study, using remote
sensing data, surface and ground truth data, subsurface features were mapped. Knowledge based weights and
ranks were assigned, feature scores were calculated and classified into five classes. Classified vector layers
were converted into raster format and using raster calculator, thematic layers were added. Thus final
integrated groundwater prospect map was obtained and shows a range of feature scores between 73 and 258.
This range has been further regrouped into five classes as very good, good, moderate, moderately poor and
poor zones.
The derived map was validated with the available water level data and the same shows that as the potentiality
decreases, the water level also decreases. Hence it is evident that modern tools like remote sensing and GIS
can be effectively used in targeting groundwater potential zones.
1.10 Conclusion
The Manapparai and its environs exhibit diverse hydrogeomorphological conditions. The perusal of
Groundwater prospect map clearly indicates that combination of buried pediment deep, high lineament
density, low drainage density, shallow water level and deeper bedrock falls under very good to good
groundwater potential zone. Whereas structural and denudational hills, high drainage density and low
lineament density areas under poor potential zones. The other combinations forms moderate and
moderately poor potential zones and the same encloses 50 % of the study area. By suggesting appropriate
recharge structures, the overall groundwater resource can be enhanced. The multi parametric approach
using GIS and remote sensing has proven an effective tool both as time consuming and cost effective in
identifying groundwater potential zones especially in hard rock terrain.
Acknowledgement
The Authors wish to express sincere thanks to the Head of the Department, Centre for Remote Sensing,
Bharathidasan University, Khajamalai Campus, Tiruchirappalli-23 for providing all necessary institutional
Selvam.G, Srinivasan.D, Selvakumar.R, P.Alaguraja
Int. Journal of Applied Sciences and Engineering Research, Vol. 1, No. 2, 2012
218
Identification of Ground Water Potential Zone in Hard Rock Terrain – A Case Study From Parts of Manapparai Block Tamil
Nadu Using Remote Sensing And GIS Techniques
support also PWD, Govt. of Tamil Nadu for providing water level and geophysical data.
References
1. Bahuguna IM, Nayak S, Tamilarsan V, Moses J., (2003). Groundwater prospective zones in
Basaltic terrain using remote sensing. J Indian Soc Remote Sens. 31(2), 107–118.
2. Basudeo Rai, Tiwari, A, Dubey, V.S., (2005). Identification of groundwater prospective zones by
using remote sensing and geoelectrical methods in Jarla and Raniganj coalfields, Dhanbad district,
Jharkhand state. J of Earth System Scwnces. 114(5), 515-522.
3. Carver S., (1991). Integrating multi-criteria evalua-tion with geographic information systems. Int J
Geogr Inf Sci. 5, 321–339.
4. Das S, Behra SC, Kar A, Narendra P, Guha NS., (1997). Hydrogeomorphological mapping in
groundwater exploration using remotely sensed data – case study in Keonjhar district in Orissa. J
Indian Soc Remote Sens. 25(4), 47–259.
5. Goyal S, Bhardwaj RS, Jugran DK., (1999). Multicriteria analysis using GIS for groundwater
resources evaluation in Rawasen and Pili watershed, U.P. Proc. Map India 99, New Delhi, India.
6. Hoogendoorn, J.H., Van Der Linden, W.S., De Storet, C.B.M., (1993). The Importance of GIS in
Regional Geohydrological Studies. In: Proc.Int. Conf. on Appln. of Geographic Information
System in Hydrology and Water Resource Management, Vienna, Austria, April 19-22, IAHS Pub.
No.211. 375-383.
7. Jagadeeswara Rao, P., Harikrishna, R., Suryaprakasa Rao, B., (2004). An integrated study on
groundwater resources of Pedda Gedda watershed. J. of In&an Soctety of Remote Sensmg. 32(3)
307-311.
8. Jayakumar, R., Ramasamy, SM., (1996). Groundwater Targeting in Hard rock Terrain Through
Geomorphic Mapping: A case study in part of South India. Asian Pacific Remote Sensing and GIS
Journal, 8(2), 17-23.
9. Krishnamurthy, J., Venkataesa Kumar, N., Jayraman, V., Manivel, M., (1996). An approach to
demarcate groundwater potential zones through Remote Sensing and GIS. International Journal of
Remote Sensing. 17(10), 1867-1884.
10. Kumanan, Ramasamy., (2000). Have attempted on GIS integrated approach for rapid groundwater
target in hard rock terrain.
11. Kumar, A., Tomar, S., Prasad, L.B., (1999). Analysis of fractures inferred from DBTM and
remotely sensed data for Groundwater development in Godavari sub-watershed, Giridih, Bihar.
Journal of Indian Society of Remote Sensing. 27(2), 105-114.
12. Lokesha, N., Gopalakrishna, G.S., Honne Gowda, H., Gupta, A.K., (2005). Delineation of
groundwater potential zones in a hard rock terrain of Mysore district, Kamatak using IRS data and
GIS techniques. J. of lndian Society of Remote Sensing. 33(3), 405- 412.
13. Manivel.M., (2010). Identification of Water Potential Zone around Triuchirappalli District Using
Remote Sensing and GIS.
14. Pratap K, Ravindran KV and Prabakaran B (2000) Groundwater prospects zoning using remote
sensing and geographical information system: A case study in Dala-Renukoot area, Sonbhadra
district, Uttar Pradesh. J Indian Soc Remote Sens. 28(4), 249–263
15. Ramasamy, SM., Nagappan, N. and Selvakumar, R., (2005). Fracture Pattern Modelling and
Ground water Hydrology in Hard Rock Aquifer System, Central Tamil Nadu, India. SM.
Selvam.G, Srinivasan.D, Selvakumar.R, P.Alaguraja
Int. Journal of Applied Sciences and Engineering Research, Vol. 1, No. 2, 2012
219
Identification of Ground Water Potential Zone in Hard Rock Terrain – A Case Study From Parts of Manapparai Block Tamil
Nadu Using Remote Sensing And GIS Techniques
16.
17.
18.
19.
20.
21.
22.
23.
24.
25.
26.
27.
28.
29.
30.
31.
Ramasamy (ed.) Remote Sensing in Water Resources. Rawat Publ. 121-136.
Ratnakar Dhakate, V.S., Singh, B.C., Negi, Subhash Chandra, V., Ananda Rao (2008).
Geomorphological and geophysical approach for locating favorable groundwater zones in granitic
terrain, Andhra Pradesh, India. Journal of Environmental Management. 88, 1373–1383.
Ravindran, K.V., Jeyaram, A. (1997). Groundwater prospectus of Shahba Teshil, Baran district,
eastern Raiasthan : A remote sensing approach. J ofln&an Society of Remote Sensing. 25(4), 239246.
Rokade, V.M., Kundal, P., Joshi, A.K., (2007). Groundwater potential modeling through remote
sensing and GIS: A case study from Rajura Taluka, Chandrapur District, Maharashtra. Jour. Geol.
Soc. India, 69 (5), 943-948.
Samuel Corgne., Ramata Magagi., Michel Yergeau, Daouda Sylla., (2010). An integrated approach
to hydro-geological lineament mapping of a semi-arid region of West Africa using Radarsat-1 and
GIS. Remote Sensing of Environment 114, 1863–1875.
Sankar K., (2002). Evaluation of groundwater potential zones using remote sensing data in upper
Vaigai river basin, Tamil Nadu, India. J Indian Soc Remote Sens. 30 (3), 119–129.
Saraf, A.K., Chaudhuray, P.R., (1998). Integrated remote sensing and GIS for groundwater
exploration and identification of artificial recharge sites. Int. Jour. Remote Sensing. 19(10), 18251841
Subash Chandra.,Benoit Dewandel., Sushobhan Dutta, Shakeel Ahmed., (2010). Geophysical
model of geological discontinuities in a granitic aquifer: Analyzing small scale variability of
electrical resistivity for groundwater occurrences. Journal of Applied Geophysics. 71, 137–148.
Thushan Chandrasiri Ekneligoda, HerbertHenkel., (2010). Interactive spatial analysis of
lineaments. Computers & Geosciences. 36, 1081–1090.
P.A. Burrough Principles of Geographical Information Systems for Land Resources Assessment
Oxford University Press, New York (1986) pp. 50
I.A. Dar, K. Sankar, M.A. Dar Deciphering groundwater potential zones in hard rock terrain using
geospatial technology Environmental Monitoring and Assessment, 173 (2010), pp. 597–610
Das, D., 2000. GIS application in hydrogeological studies. Available from:
http://www.gisdevelopment.net/application/nrm/water/overview/wato0003.htm (accessed March
2010).
S. Das, S.C. Behera, A. Kar, P. Narendra, S. Guha Hydrogeomorphological mapping in
groundwater exploration using remotely sensed data—A case study in Keonjhar District, Orissa
Journal of Indian Society of Remote Sensing, 25 (1997), pp. 247–259
S. Ganapuram, G. Kumar, I. Krishna, E. Kahya, M. Demirel Mapping of groundwater potential
zones in the Musi basin using remote sensing and GIS Advances in Engineering Software, 40
(2008), pp. 506–518
V.R. Haridas, S. Aravindan, G. Girish Remote sensing and its applications for groundwater
favourable area identification Quarterly Journal of GARC, 6 (1998), pp. 18–22
P. Harinarayana, G.S. Gopalakrishna, A. Balasubramanian Remote sensing data for groundwater
development and management in Keralapura watersheds of Cauvery basin, Karnataka, India The
Indian Mineralogists, 34 (2000), pp. 11–17
M. Leblanc, C. Leduc, M. Razack, J. Lemoalle, D. Dagorne, L. Mofor Application of remote
sensing and GIS for groundwater modeling of large semiarid areas: example of the Lake Chad
Basin, Africa Hydrology of Mediterranean and Semiarid Regions Conference, Montpieller,
Selvam.G, Srinivasan.D, Selvakumar.R, P.Alaguraja
Int. Journal of Applied Sciences and Engineering Research, Vol. 1, No. 2, 2012
220
Identification of Ground Water Potential Zone in Hard Rock Terrain – A Case Study From Parts of Manapparai Block Tamil
Nadu Using Remote Sensing And GIS Techniques
France. Red Books Series, 278IAHS, Wallingford (2003), pp. 186–192
32. N.S. Magesh, N. Chandrasekar, J.P. Soundranayagam Morphometric evaluation of Papanasam and
Manimuthar watersheds, parts of Western Ghats, Tirunelveli district, Tamil Nadu India: a GIS
approach Environmental Earth Science, 64 (2011), pp. 373–381
33. N.S. Magesh, N. Chandrasekar, D. Vetha Roy Spatial analysis of trace element contamination in
sediments of Tamiraparani estuary, southeast coast of India Estuarine, Coastal and Shelf Science,
92 (2011), pp. 618–628
34. M. Muralidhar, K.R.K. Raju, K.S.V.P. Raju, J.R. Prasad Remote sensing applications for the
evaluation of water resources in rainfed area, Warangal district, Andhra PradeshThe Indian
Mineralogists, 34 (2000), pp. 33–40
35. K.S.R. Murthy Groundwater potential in a semi-arid region of Andhra Pradesh—a geographical
information system approach International Journal of Remote Sensing, 21 (2000), pp. 1867–1884
36. R.K. Prasad, N.C. Mondal, P. Banerjee, M.V. Nandakumar, V.S. Singh Deciphering potential
groundwater zone in hard rock through the application of GIS Environmental Geology, 55 (2008),
pp. 467–475
37. P. Sander, M. Chesley, T. Minor Groundwater assessment using remote sensing and GIS in a rural
groundwater project in Ghana: lessons learned Hydrogeology Journal, 4 (1996), pp. 78–93
38. E. Sener, A. Davraz, M. Ozcelik An integration of GIS and remote sensing in groundwater
investigations: a case study in Burdur, Turkey Hydrogeology Journal, 13 (2005), pp. 826–834
39. M.N.R. Shankar, G. Mohan Assessment of the groundwater potential and quality in Bhatsa and
Kalu river basins of Thane district, western Deccan Volcanic Province of India Environmental
Geology, 49 (2006), pp. 990–998
40. R. Teeuw Groundwater exploration using remote sensing and a low-cost geographic information
system Hydrogeology Journal, 3 (1995), pp. 21–30
41. S.O. Tweed, M. Leblanc, J.A. Webb, M.W. Lubczynski Remote sensing and GIS for mapping
groundwater recharge and discharge areas in salinity prone catchments, southeastern Australia
Hydrogeology Journal, 15 (2007), pp. 75–96
42. G.Anbazhagan and M.Manivel Targeting Ground Water Potential Zones
in hard rock Terrain
Using Remote Sensing and GIS. Recent Trends in Water Research remote sensing and general
perspectives, I.K International Publication. New Delhi, pp- 7-24
43.Kalai Selvan.B, Manivel.M, Sathishkumar.V.R, Alaguraja.P and Yuvaraj. Identification of Water
Potential Zone in around Triuchirappalli District Using Remote Sensing and GIS. Recent Trends
in Water Research remote sensing and general perspectives, I.K International Publication. New
Delhi ,PP-25-46
Selvam.G, Srinivasan.D, Selvakumar.R, P.Alaguraja
Int. Journal of Applied Sciences and Engineering Research, Vol. 1, No. 2, 2012
221