Int. Journal of Applied Sciences and Engineering Research, Vol. 1, No. 2, 2011 www.ijaser.com© Copyright 2011 - Integrated Publishing Association editorial@ijaser.comResearch article 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

1Mr. G.Selvam Research Scholar Department of Geology National College, (Autonomous)Tiruchirappalli-620 001.

2Dr. 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-620024doi: 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 ---------------------------- 212*Corresponding author (email: geoselvar @gmail.com)Received on, March 2012; Accepted on March 2012; Published on April, 2012

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

images are increasingly used in groundwater exploration because of their utility in identifying various 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

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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

district (Fig.1) covering an area of 720 sq.km comprising of twenty eight villages. Mostly rain fed area and 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).

Table 1: Weighted FactorsThematic Layers Weight

(Wt)Features Rank

(Wi)Feature Scores

Lithology 6

Charnockite 7 42

Hornblende-biotite gneiss 6 36Pink augen gneiss 6 36Amphibolite 5 30Pyroxene granulite 5 30Calc-granulite and limestone 3 18Granite 3 18Quartzite 1 6

Geomorphology 10

Buried Pediment Deep 8 80Buried Pediment Moderate 6 60Buried Pediment Shallow 4 40Pediment 3 30Residual Hill 1 10

Structural Hill 1 10Landuse Land Cover 5 Crop Land 6 30

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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

Plantation 5 25Land With Scrub 4 20Scrub Forest 3 15Land Without Scrub 2 10

Lineament Density 7

Very High 5 35High 4 28Moderate 3 21Low 2 14Very Low 1 7

Drainage Density 7

Very Low 5 35Low 4 28Moderate 3 21High 2 14Very High 1 7

Depth to Water level 8

Very Low 5 35Low 4 28Moderate 3 21High 2 14Very High 1 7

Depth to Bed Rock 7

Very High 5 35High 4 28Moderate 3 21Low 2 14Very Low 1 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 20 th 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)

1.6 Surface Parameters

1.6.1 LithologyThe 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

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Feature Score (Fs) = Theme Weight (Wt) × Feature Rank (Wi)

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

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 GeomorphologyAs far as groundwater potentiality is concerned the hilly and undulatory topography forms runoff zones 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 CoverBased 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

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given and classified into five categories (Table-I).

1.6.4 Drainage DensityDrainage 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.

1.6.5 Lineament DensityIn 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 LevelWater 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 BedrockThe 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,

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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.

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

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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.

AcknowledgementThe 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 support also PWD, Govt. of Tamil Nadu for providing water level and geophysical data.

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