Application of remote sensing and GIS for delineating ...

Application of remote sensing and GIS for delineating groundwater recharge potential zones of Kovilpatti Municipality, Tamil Nadu using IF technique S. Selvam, Farooq A. Dar, N. S. Magesh, C. Singaraja, S. Venkatramanan & S. Y. Chung Earth Science Informatics ISSN 1865-0473 Earth Sci Inform DOI 10.1007/s12145-015-0242-2

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Author's personal copy Earth Sci Inform DOI 10.1007/s12145-015-0242-2

RESEARCH ARTICLE

Application of remote sensing and GIS for delineating groundwater recharge potential zones of Kovilpatti Municipality, Tamil Nadu using IF technique S. Selvam 1 & Farooq A. Dar 2 & N. S. Magesh 3 & C. Singaraja 4 & S. Venkatramanan 5 & S. Y. Chung 5

Received: 6 July 2015 / Accepted: 7 October 2015 # Springer-Verlag Berlin Heidelberg 2015

Abstract During the last three decades, remotely sensed data (both satellite images and aerial photographs) have been increasingly used in groundwater exploration and management exercises. An integrated approach has been adopted in the present study to delineate groundwater recharge potential zones using RS and GIS techniques. IRS-1C satellite imageries and Survey of India toposheets are used to prepare various thematic layers viz. geology, soil, land-use, slope, lineament and drainage. These layers were then transformed in to raster data using feature to raster converter tool in ArcGIS 9.3 software. The raster maps of these factors are allocated a fixed score and weight computed from Influencing Factor (IF) technique. The weights of factors contributing to the groundwater recharge are derived using aerial photos, geology maps, a land use database, and field verification. Subjective weights are assigned to the respective thematic layers and overlaid in GIS platform for the identification of potential groundwater recharge zones within the study area. Then these potential

zones were categories as ‘high’, ‘moderate’, ‘low’, ‘poor’. The resulted map shows that 19 % of the area has highest recharge potential, mainly confined to buried pediplain, agriculture land-use and river terraces (considerable amount of precipitated water percolates into subsurface), 28 % of the area has moderate groundwater recharge potentiality and rest of the area has low to poor recharge potentiality. The residual hills and linear ridges with steep slopes are not suitable for artificial recharge sites. Finally, 13 % of total average annual precipitated water (840 mm) percolates downward and ultimately contributes to recharge the aquifers in the Kovilpatti Municipality area. The paper is an attempt to suggest for maintaining the proper balance between the groundwater quantity and its exploitation.

Communicated by: H. A. Babaie

Introduction

* S. Selvam [email protected]

In coastal regions across the globe, water scarcity is a major problem, and due to deficit rainfall, tremendous pressure is brought on groundwater. The study area is located in the coastal and semi-arid climatic zone with hard rock terrain. Groundwater in hard rock aquifers is essentially confined to fractured and weathered horizons. Hard rock terrains have complex hydrogeology where occurrence and movement of groundwater is mainly controlled by secondary porosity in the form of fracture (Bagyaraj et al. 2012; Srivastava and Bhattacharya 2006; Singaraja et al. 2015a, b; Venkatramanan et al. 2015; Selvam 2015a, b). In India, about 65 % of the country is underlain by hard rock’s (Saraf and Choudhary 1998; Selvam 2015a). The groundwater resources in India are facing a continuous threat of depletion due to multiple

1

Department of Geology, V.O. Chidambaram College, Tuticorin, Tamil Nadu, India

2

Indo-French Centre for Groundwater Research, CSIR-National Geophysical Research Institute, Hyderabad 500 007, India

3

Center for Geo-technology, Manonmaniam Sundaranar University, Tirunelveli, Tamil Nadu 627 012, India

4

Department of Geology, Presidency College, Chennai-5, Tamil Nadu, India

5

Department of Earth & Environmental Sciences, Institute of Environmental Geosciences, Pukyong National University, Busan 608-737, South Korea

Keywords Remote sensing . GIS . IF . IRS-1C . Recharge potential . Kovilpatti . Tamil Nadu

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reasons. In the coastal tracts of India groundwater is facing depletion problems as well as sea water intrusion problems. Groundwater is an important source of water for domestic, agricultural and industrial uses in Tamil Nadu, India. High population density, uneven distribution of water resources and its demand spatially and temporally, economic development, changing climate, etc. have led to an increase of consumption and shortages of surface water. Most of the precipitation is lost as surface run-off directly to the ocean very quickly due to steep slopes. Therefore, the reliance on groundwater has increased, leading to its overdraft which resulted in decline of groundwater levels, deterioration of water quality and seawater ingression. Therefore, it is important to thoroughly understand the groundwater resources of this coastal belt for its sustainable development. Various researchers have used different criteria for delineating groundwater potential zones. For example, use of lineament and hydrogeomorphology (Nag 2005), geophysical data with geospatial information (Antony Ravindran and Selvam 2014; Kumar et al. 2007; Rodell et al. 2009; Srivastava and Bhattacharya 2006; Selvam 2012; Selvam and Sivasubramanian 2012), delineation of artificial recharge sites using RS and GIS (Saraf and Choudhary 1998; Jasrotia et al. 2007; Chenini et al. 2010;), use of RS and GIS for geomorphic features and lineaments (Kamal and Midorikawa 2004; Gustavsson et al. 2006; Singh et al. 2007; Selvam et al. 2013a, b, c; Singaraja et al. 2015a). Remote sensing (RS) and geographic information system (GIS) is increasingly used as a tool for a number of applications (Selvam et al. 2014a, b, c, d). The technique is used to integrate various data to delineate not only groundwater potential zone but also solve other groundwater related problems. RS and GIS technology is a rapid and cost-effective tool in producing valuable data on geology, geomorphology, lineaments, slope, etc., which are important parameters for groundwater exploration, exploitation and management strategy. This paper uses the integrated approach of remote sensing and GIS to decipher the groundwater recharge potential zones in an agricultural area of Kovilpatti Taluk of Tamil Nadu. Study area Kovilpatti is located 60 km north-west of Tuticorin, on National Highway No.7 in the Tamil Nadu state of India (Fig. 1). The average elevation of the area is 106 masl. The climate of the area is hot and dry where temperatures range between a minimum of 22 °C to a maximum of 37 °C. April to June is the hottest months and December and January are coldest with temperatures rising towards the end of February. The temperature is relatively high and this increases the rate of evaporation of the surface water and also the actual evapotranspiration, which is nearly equal to that of the annual precipitation. Based on the scanty contribution of rainfall over

recharge into the groundwater system is expected to be very less. Rainfall occurs mostly during the north-east monsoon between October to December. The town receives an average rainfall of 840 mm a year. Annual rainfall ranged from 964 to 228 mm during past decades (Selvam et al. 2013a, b). Though many small, medium and large scale tanks are located within this area they are almost dry for about 6 to 7 months in a year and from March onwards farmers depend mostly on the available groundwater resources. The percentage of gross area irrigated under tanks to the total area sown is only 15 %. Tamiraparani river has a number of canal systems in Murappanad and Srivaikundam. In recent years farmers draw out the groundwater along the river banks and around the irrigation tank though large diameter dugwell and dug-cum bore well. Tamiraparani river is an important irrigation tank in the study area (Balasubramanian et al. 1993; Selvam et al. 2014a).

Materials and methods The linear image self-scanning (LISS) III data of Indian Remote Sensing Satellite (IRS) 1C, of scale 1:50,000 were used for the present study. The Survey of India toposheets 58 H/13, 58 H/14, 58 L/1&5, 58 L/2 on a scale of 1:50,000 were used for the preparation of thematic maps. The imagery was visually interpreted to delineate lithology and land use/ land cover with the help of slandered characteristic image interpretation elements like tone, texture, shape, size, pattern and association. The thematic maps were converted into raster form to easily integrate into GIS platform. Shuttle Radar Topography Mission (SRTM) DEM data on a global scale at 90 m horizontal resolution (http://srtm.csi.cgiar.org/) is used for topographic analysis (Fig. 2). Each of these thematic maps has been assigned suitable weightage factor. During weightage overlay analysis, the ranking was given for each individual parameter of each thematic map and weights were assigned according to the influencing factor of that particular feature on the hydro-environment of the area. These thematic maps were then integrated using “Spatial Analysis tool” in Arc GIS 9.3 (Fig. 3). The remotely sensed data and topographical information from available maps have been used for preparing various thematic layers, such as lithology, drainage density, lineament density, rainfall, slope, soil, and land-use with assigned weightage in a spatial domain. The data was cross-checked with necessary ground surveys. Factors affecting groundwater recharges potential The methodology developed here to determine groundwater potential consists of four main steps. The first step starts with the identification of the thematic layers which are relevant to groundwater potential. The second involves preprocessing

Author's personal copy Earth Sci Inform Fig. 1 Location map of Kovilpatti Municipality

these thematic layers to ensure uniform projection (projection: UTM, datum: WGS84) and resolution, assigning scores, and weightages. The third step integrates all thematic layers along Fig. 2 DEM map of Kovilpatti Municipality

with scores using the spatial analysis tool in GIS 9.3 software. The final step categorizes the outputs into four (‘poor’, ‘low’, ‘moderate’ and ‘high’) classes and compared with the

Author's personal copy Earth Sci Inform Fig. 3 Flowchart for groundwater potential assessment using integrated remote sensing and GIS techniques

obtained standards by the UN (1967) find out the Recharge water volume of the study area. This study bears similarities to studies performed in other regions (Shaban et al. 2006; Yeh et al. 2009; Adham et al. 2010; Singh et al. 2011; Magesh et al. 2012; Gumma and Pavelic 2012; Selvam et al. 2014b, c) in terms of the approach used but is distinguishable by the larger spatial scale and finer resolution considered here. During weighted overlay analysis, the ranking was given for each individual parameter of each thematic map, and weights were assigned according to the multi influencing factor (IF) of that particular feature on the hydro-geological environment of the study area (Shaban et al. 2006; Yeh et al. 2009; Adham et al. 2010; Singh et al. 2011; Magesh et al. 2012; Gumma and Pavelic 2012; Selvam et al. 2015b). The groundwater conditions at any given site can varying greatly according to various factors that influence the occurrence and replenishment of groundwater. The occurrence and movement of ground water is influenced by lithology, structure, geomorphology and drainage while replenishment is further affected by land use, precipitation and infiltration rate. In this study, seven thematic layers viz. lithology, slope, land-use, lineament, drainage, soil and rainfall have been generated for analysis and integration into a ground water prospect map. Geology The geological formations play a major role in shaping the landscape. The mode of occurrence and movement of groundwater is as varied as the rock types in which they occur. The rock type of any area has a significant effect on the groundwater availability and its recharge. Various digital image

processing techniques, including standard color composites, intensity–hue–saturation (IHS) transformation and decorrelation stretch (DS) were applied to map rock types. Although some investigations have ignored this factor by regarding the lineaments and drainage characters as a function of primary and secondary porosity, this study includes geology to reduce uncertainty in determining lineaments and drainage.

Lineament Lineaments are linear or curvilinear structures on the earth’s surface that represent the underlying crustal structures like, fault, fractures, etc. They depict the weaker zone of bed rocks which are usually considered as secondary porosity in hard rock aquifers (Koch and Mather 1997; Selvam et al. 2015a, b). Lineaments are mapped with the help of satellite data and can be correlated with faults, fractures, joints, bedding planes and lithological contacts from ground-check information and available geological data. Although major lineaments can be detected in the raw image data, most of the finer details are recognizable in the filtered images. In this study, emphasis was to delineate geological lineaments rather than just identification of all linear features. Parameters that were evaluated for lineaments include: Lineament-length density (Ld); the total length of all recorded lineaments divided by the area under study (Greenbaum 1985): Ld ¼

n X i¼1

  Li=A m−1

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Lineament frequency (Lf) or lineament count density; the number of visible lineaments per unit area (Greenbaum 1985): Lf ¼

n X

  Ln=A m−2

i¼1 i¼n

Where ∑ Li is the total length of lineaments in meters and i¼1

A is the area of study in m2.

Soil Soil is an integral part of a terrestrial ecosystem and fulfils numerous functions including the capacity to generate biomass and the filtering or buffering activities between the atmosphere and the groundwater in the biosphere. Soil types of the area are more important, since it is the main criteria in the recharge of groundwater and agricultural production. Soil characteristics invariably control the infiltration of surface water.

Drainage The density of the drainage network as well as the occurrence of lineaments, such as faults, fracture, joints, are hydrogeologically very important and have a major influence on groundwater recharge and movement (Murthy 2000; Kumar et al. 2007). Watershed and its parameters were delineated using SRTM data. Drainage densities (DD) were calculated in each of the grid square using following equation (Murthy 2000): DD ¼

X LWS AWS

Where, LWS total length of streams in watershed AWS area of the watershed Land use/land cover Land use/Land cover is a significant factor affecting recharge processes. Remote sensing and GIS technique provide reliable information for land use/land cover mapping (Soundaranayagam et al. 2011; Selvam and Sivasubramanian 2012). This factor involves a number of elements including soils, human settlements, vegetation cover, waste lands, etc. Soil and land use are the important factor to recharge the ground water in this study area. Human settlements such as, concrete embankments, buildings, roads etc., act as impermeable barriers and inhibit water infiltration to the underground. Vegetation has also a major role in groundwater recharge as it affects many processes, (Shaban et al. 2006). Slope The gradient of slope is one of the factors that directly influence the infiltration of rainfall in that steeper slopes generate less recharge because water runs rapidly off the surface during rainfall, allowing insufficient time to infiltrate the surface and recharge the saturated zone (Magesh et al. 2012). Rainfall is the main source of groundwater recharge in this area. The SRTM DEM data was used to derive a slope map in percentage using the SLOPE function in ArcGIS.

Results and discussion Groundwater recharges potential factors and spatial assessment The occurrence and movement of ground water is influenced by lithology, structure, geomorphology and drainage while replenishment is further affected by land use, precipitation and infiltration rate. In this study, six thematic layers viz. lithology, slope, land-use, lineament, drainage and soil have been generated for analysis and integration into a ground water prospect map. Geological maps of 1:50,000 scales indicate four major geologic formations (Fig. 4). The study area consists of the crystalline Archaean complex and Tertiary groups. About two thirds of Kovilpatti Taluk is dominated by mixed composite gneisses and granitoid mica gneiss rocks of Proterozoic age. These rock types are considered to have low water bearing potential and hence, lower scores have been assigned. The remaining area is covered by shell limestone, sand, and quartzite. The limestones are fine to medium grained, hard, compact and fossiliferous possessing shells of gastropods and pelecypods. The quartzite formation extends in the NE-SW direction dipping SE with low angles. Lineament density map is a measure of quantitative length of linear feature expressed in a grid. Lineament density of an area can indirectly reveal the groundwater potential areas since the presence of lineaments usually denotes a permeable zone. For analysis purposes, the lineament map has been prepared and categorized into four classes. Therefore, weightage is assigned high for higher density and low for lower density, the average frequency values ranging from 0 to 1.56 km/km2 (Fig. 5). The drainage density map reveals that density value range from 0.9 to 8.83 km/km2 that were regrouped into four category i.e. 8–13 high, 6–8 moderate, 3–6 low and 0–3 very low (Fig. 6). Considering from recharge point of view more weightage is assigned to very low drainage density regions whereas low weightage assigned to very high drainage density which are not suitable for groundwater development because of the greater surface run off.

Author's personal copy Earth Sci Inform Fig. 4 Thematic layer of the geology map of Kovilpatti Municipality

Land use/land cover patterns of study area were analyzed and mapped using IRS-1C, LlSS-III satellite data and field Fig. 5 Thematic layer of the lineament density map of Kovilpatti Municipality

verification. Water bodies and agricultural lands were assigned a high weightage factor (Fig. 7) because of large

Author's personal copy Earth Sci Inform Fig. 6 Thematic layer of the drainage density map of Kovilpatti Municipality

recharge potential in these areas. The land use/land cover such as built up lands and waste lands which have poor water Fig. 7 Thematic layer of the landuse map of Kovilpatti Municipality

holding capacity have been given a medium to low weightage factor.

Author's personal copy Earth Sci Inform Fig. 8 Thematic layer of the slope map of Kovilpatti Municipality

Slope is classified into five categories along with their weightages and weights were assigned according to the slope Fig. 9 Thematic layer of the soil map of Kovilpatti Municipality

aspect (Fig. 8). A slope < 10 is regarded as plain region because low runoff is usually a very good recharge zone. The

Author's personal copy Earth Sci Inform Fig. 10 Schematic sketch showing the interactive influence of factors concerning recharge properly

areas having 1–20 slopes are considered as good for groundwater storage due to slightly undulating topography with little run off. The areas having a slope of 2–30 cause relatively moderate runoff, and hence are categorized as ‘moderate’. Slopes having 4–50 are almost considered as poor and the areas having a slope > 50 are considered as ‘very poor’ due to higher slope and rapid runoff. In the preparation of groundwater prospecting map least weightage is given to steep dip of beds, whereas more weightage is given to gentle slope as slope plays a significant role in infiltration verses runoff. Soils, such as Sandy clay have high water-holding capacity and have been given a high weightage. These soil types are located in North, South, East, and Eastern region of the study area (Fig. 9). Clay and Sandy Clay Loam have poor waterholding capacity and have been given a low weightage. Such soil types are located in the Upper North, Western parts, and small portion of the central region of the study area (Fig. 9).

Weightage calculation in influence factor (IF) techniques The six major descriptive levels were plotted ranging from very high to very low, also including some interrelated levels. The weightage from 10 to 1 points i.e., very high range is assigned as 10 points and the minimum level as 1 points. All these factors are integrated to obtain a recharge potential map.

Assessing the effects of each factor only the recharge potential was not give in the required complementary picture. The integration of all factors together was necessary in order to obtain a recharge potential map. Based on the degree of influence in the recharge potentiality, a weightage approach is incorporated and the factor on each other is presented as schematic sketch (Fig. 10). Each influencing factor may contribute to delineate the groundwater potential zones and these factors have a relative value of 2 or 1 based on major or minor effect between different layers. The major effect was given 2 point, while the minor effect was given1 point. The cumulative weightage of both major and minor effects are considered for calculating the relative rate. This rate is further used to calculate the score of each influencing factor. Figure 10 shows that the lithology was the most influential one having 5 major Table 1

Factors influencing groundwater recharge classified criteria

Factors

Source of categorization

Geology Soil Landuse/Landcover Lineaments Drainage Slope

Rock type, weathering character, joints, fractures Textures Satellite imageries Lineament-density value Drainage-density value Slope gradient

Author's personal copy Earth Sci Inform Table 2 Factors

Relative rates and score for each potential factor Major effect (A)

Minor Calculation Proposed effect (B) process relative rates (A + B)

(Table 2). Now to obtain a comprehensive evaluation of each influencing factor on recharge potentiality the rates and weights are integrated and thus total weighting assessment, after rounding off values is shown in Table 3 (e.g., Khawlie 1986; Shaban et al. 2001 and Shaban (2003). The grand total weight (GTW) in this case was calculated:

Lineaments 2 + 2

0

4 + 0 = 4.0 4.0

Landuse

2+2+2

1+1

6 + 2 = 8.0 8.0

Lithology Drainage

2+2+2+2+2 0 2 1+1

10 + 0 = 10 10.0 2+2=4 4.0

GTW ¼ lithology ð190Þ þ landuse ð200Þ þ soil ð2Þ þ lineaments density ð84Þ þdrainage density ð84Þ þ slope gradient ð110Þ ¼ 692

Slope Soil

2+2 2

4+1=5 2+1=3

Based on the given value following calculations are made using the formula, 0 X 1 ðX  Y Þ @ X X  A  100 ðX  Y Þ

1 1

5.0 3.0 ∑34

effects i.e., it had an effect on lineaments, land use, slope, drainage and soil (Table 1). Based on relative rates for each influencing factor, this is expressed in points as shown in Table 2. The effect of influencing factor, relative rates and score for each potential factor of the study area is categorized Table 3

Weight evaluations of factors influencing recharge potential capacity Weight (A) Rate (B) Weighted rating Total ∑(A×B) Factors on recharge (1–10) (1–10) (A×B) potentiality capacity in %

Factors

Descriptive level Domain of effect

Geology

High Good Moderate

Shell limestone and Sand 8.5 Quartzite 6.5 Mixed and Composite Gneiss 2.5

Low Very High High Good Moderate Low

Granitoid mica Gneiss Water bodies Cultivated land Settlements Barren lands Uncultivated land

1.5 8.0 6.0 4.5 3.5 2.0

Very Low

Dry land with shrubs

1.0

High Moderate

Sandy Clay Sandy Clay loam

4.5 2.5

Clay 1.56–1.2 1.2–0.8 0.8–0.3 0.3–0.0 0–3 3–6 6–8 >8 0–1 1–2 2–3 3–4 4–5 5–6

1.0 10 6 3.5 1.5 9 6.5 3.5 2 7.5 5.5 4 2.5 1.5 1

Landuse

Soil

Where, X is weight and Y is rate. The concerned score for each influencing factor was divided equally and assigned to each

Low Lineament Density High Good Moderate Low Drainage Density High Good Moderate Low Slope gradient High High-Moderate Moderate Moderate-Low Low Very Low

10

8

85 65 25 15 64 48 36 28 16

190

28 %

200

29 %

24

3%

84

12 %

84

12 %

110

16 %

692

100 %

08 3

4

4

5

13.5 7.5 3 40 24 14 06 36 26 14 8 37.5 27.5 20 12.5 7.5 5

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reclassified factor (Table 3). The percentage of factor effect on the recharge potential follows as, 190 *100 ¼ 28% 692 200 ¼ Landuse ¼ *100 ¼ 29% 692 24 ¼ Soil ¼ *100 ¼ 3% 692 84 ¼ Lineament ¼ *100 ¼ 12% 692 84 ¼ Drainage Density ¼ *100 ¼ 12% 692 110 ¼ Slope gradient ¼ *100 ¼ 16% 692 Total percentage ¼ 28 þ 29 þ 3 þ 12 þ 12 þ 16 ¼ 100% ¼ Geology ¼

Fig. 11 Calculation process adopted in Kovilpatti Municipality

Fig. 12 Groundwater recharge potential zones map of the study area

The final map obtained from each factor was considered as layer each with its own weight the overlapping of which in GIS resulted in different polygons of special characteristics with respect to the overall recharge potential for the area. Figure 11 shows calculation process to get the exact value of the cell by weightage approach. After considering rate assessment, different layers of recharge potential were superimposed. Finally, recharge potential zone map was prepared and divided into four descriptive levels (Fig. 12). The descriptive levels are ‘high’, ‘moderate’, ‘low’ and

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‘poor’ occupying areas of 19 % (72.36 km2), 28 % (111.12 km2), 19 % (73.25 km2), 34 % (131.58 km2) respectively. The maximum area is characterized by moderate to high potential zones that occupies 47 % of the total area. The optimististic values of recharge potential shown in the resulting map was compared with the standards by the UN (1967) and these levels are categorized (Table 4). However, a quantitative estimation of recharged water in Kovilpatti was done by a simplified calculation for the proposed recharges rates (adapted from UN 1967). The estimation of

recharged water volume (W) will be calculated by the following formula, W ¼PRA Where, W Recharge water volume P Precipitated volume R Recharge ratio A Percentage of the area

W ¼ 1520  106 ð0:475  0:0 þ 0:325  0:19 þ 0:15  0:28 þ 0:075  0:19 þ 0:025  0:34Þ W ¼ 1520  106 ð0 þ 0:06175 þ 0:042 þ 0:01425 þ 0:0085Þ W ¼ 1520  106 ð0:1265Þ W ¼ 192:28  106 m3 =year

Thus, 13 % (192.28 × 106 m3/year) of the received precipitation percolates downward to recharge the aquifer and the rest is lost either as evapotranspiration or surface runoff of the study area.

Conclusion An attempt was made to prepare groundwater recharge potential zones of the study area using an IF techniques. Various thematic maps such as geology, soil, land-use, slope, lineament and drainage maps were prepared and integrated for preparing groundwater prospects map. The various thematic maps were assigned with different weightage of numerical value with respect to groundwater potentiality. The weightage values assigned were brought into the raster form for integration of influencing factor. These factors have an increasing or decreasing effect on recharge potential, but each of them has its own value that must be created for factor integration. The results demonstrate that the groundwater recharge potential zone of this area include; ‘high’, ‘moderate’, ‘low’, ‘poor’. Excellent groundwater recharge potential zone is concentrated Table 4

in the downstream region due to the distribution of buried pediplain, agriculture landuse and river terraces with high infiltration ability. The residual hills and linear ridges with steep slopes are not suitable for recharge. About 13 % of average annual precipitation percolates downward and recharges the aquifers. This groundwater prospectus maps will serve many purposes: quickly identify the prospective groundwater zones for conducting site specific investigations and select the sites for planning recharge structures to improve sustainability of water sources. This methodology can be applied effectively in the areas with similar climate and complex hydrological terrains which suffers from acute shortage of water for proper sustainable management of groundwater. Acknowledgments Dr.S.Selvam gratefully acknowledges the financial support by University Grant Commission, Government of India, New Delhi through project No.F MRP-5614/15(SERO/UGC). Authors are also grateful to Shri A.P.C.V.Chockalingam, Secretary and Dr.C.Veerabahu, Principal, V.O.C College, Tuticorin for his support to carry out this study. The Editor-in-Chief Dr. Hassan A. Babaie and the anonymous reviewers had suggested their constructive comments to improve the paper. The authors are also thankful to them.

Recharge potential categories and their quantitative estimation

Recharge potential category

Estimate according to FAO (1967)

Average %

Area Extant (Km2)

Very High High Moderate Low Poor

45–50 % 30–35 % 10–20 % 5–10 %