JOURNAL GEOLOGICAL SOCIETY OF INDIA Vol.88, October 2016, pp.481-492

Assessment of Groundwater Potential Zone Using Remote Sensing, GIS and Multi Criteria Decision Analysis Techniques D. C. JHARIYAa*, TARUN KUMARb, M. GOBINATHc, PRABHAT DIWANd and NAWAL KISHOREe a,d

Department of Applied Geology, eDepartment of Mining Engineering, National Institute of Technology Raipur, G.E. Road Raipur – 492 010, India b Department of Applied Geology, National Institute of Technology Raipur, G.E.Road Raipur - 492 010, Chhattisgarh, India C Central Groundwater Board, NCCR, Raipur - 492 010, Chhattisgarh, India Email: [email protected]*; [email protected]; [email protected]; [email protected]; [email protected]

Abstract: The sustainable development and management of groundwater resource needs quantitative assessment, based on scientific principle and recent techniques. In the present study, groundwater potential zone is being determined using remote sensing, Geographical Information System (GIS) and Multi-Criteria Decision Analysis (MCDA) techniques using various thematic layers viz. geomorphology, geology, drainage density, slope, rainfall, soil texture, groundwater depth, soil depth, lineament and land use/ land cover. The Analytic Hierarchy Approach (AHP) is used to determine the weights of various themes for identifying the groundwater potential zone based on weights assignment and normalization with respect to the relative contribution of the different themes to groundwater occurrence. Finally, obtained groundwater potential zones were classified into five categories, viz. low, medium, medium-high, high and very high potential zone. The result depicts the groundwater potential zone in the study area and found to be helpful in better development and management planning of groundwater resource. Keywords: Groundwater Potential Zone, Remote Sensing, GIS and Multi-Criteria Decision Analysis (MCDA). INTRODUCTION

Ever increasing demands of water for domestic, irrigation as well as industrial sectors have created water crisis worldwide. Development of water resources represents a challenge for planners and decision-makers in countries with high population growth and water scarcity (Jawad et al. 2013). Assessment of potential groundwater zone could help in appropriate development and utilization of groundwater and surface water resources for eliminating water scarcity (Rao, 2006). Increasing demands for fresh water in different sectors especially for drinking and agriculture purpose warrant identification of the groundwater potential zones (Hoffmann 2006; Bhattacharya 2010; Patel and Desai 2010). The sustainable development and management of groundwater resource requires precise quantitative assessment, based on modern scientific principles and techniques. In the present study, groundwater potential zone are delineated using remote sensing, Geographical Information System (GIS) and Multi-Criteria Decision Analysis (MCDA) techniques.

Remote sensing provides multi-spectral, multi-temporal and multi-sensor data of the earth’s surface. As groundwater is a dynamic and interdisciplinary in nature, an integrated approach of remote sensing (RS) and GIS techniques is a very useful in groundwater development and management studies. Remote sensing can provide diverse dataset over a large inaccessible area that can be efficiently handled and analyzed on a GIS frame work (Jha et al. 2007; Chowdhury et al 2010; Jenifa et al. 2010; Sharma and Kujur 2012; Dhakate et al. 2012). Remote sensing and GIS has been widely used for the preparation of different types of thematic layers and integrating them for the different purposes (Eastman 1996; Taheri and Zare 2011). Integration of these two techniques has proved to be an efficient tool in groundwater potential zonation and several studied have been conducted in various parts of the world (Chowdhury et al. 2010; Meshram et al. 2010). Multi-Criteria Decision Analysis (MCDA) techniques is one of the upcoming technique and the most important methods of MCDA is Analytic Hierarchy Approach (AHP).

0016-7622/2016-88-4-481/$ 1.00 © GEOL. SOC. INDIA

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AHP is proposed by Saaty (1980) as a method of solving socio-economic decision making problems has been used to solve a wide range of problems. AHP is utilized when dimensions are independent (Saaty 1996) provides a method for input judgment and measurement to derive ratio scale priorities for the distribution of influence between the different thematic layers. Saaty (1996) suggested the use of AHP to solve the problem of independence on alternatives or criteria (Dagdeviren and Ihsan 2007; Suryawanshi 2011; Agarwal et al. 2013). The AHP prioritizes not just elements but also groups or clusters of elements as is often necessary (Saaty 1999). AHP provides a context-specific multi-criteria evaluation method that allows for the measurement of one unique alternative in the face of general criteria (Hamilton 2009; Ghayoumian et al. 2007). The aim of this study is to contribute towards systematic groundwater potential studies utilizing remote sensing, field studies, Geographic Information Systems (GIS) and MultiCriteria Decision Analysis (MCDA) in the assessment of groundwater potential zone. The specific objectives of the present study are: y To prepare thematic maps of the Saja block such as geomorphology, geology, drainage density, slope, rainfall, soil texture, groundwater depth, soil depth, lineament and land use/ land cover from remotely sensed data, other exiting data sources and with field checks. y To identify and delineate groundwater potential zones through integration of various thematic maps with GIS techniques. y Validation of groundwater potential zone map. y Actual yield of bore wells. STUDY AREA

Saja block is a part of Bemetara district in Chhattisgarh state, India. It is located 38 km towards west from district Headquarters, Bemetara and 70 km from state capital Raipur towards Northwest. Study area is confined between the latitude 21°29'40" and longitude 81°30'10" part of Survey of India toposheet no. 64G/1, 64G/2, 64G/6 and 64G/7. Location map of the study area is shown in the Fig.1. Overall the elevation (altitude) in the study area varies between 256 m to 335 m above Mean Sea Level (MSL). Total area around 732.05 Sq km covered in present study. Owing to the geographical location and physical features, the climate of the district can be classified as tropical. It is too hot in summer, and temperature rises up to 45°C while winter temperature fall down up to 9°C. The southwest monsoon bring rainfall. The monsoon season starts immediately after summer till late September. The average yearly rainfall of



India 

 

Chhattisgarh Chhattisgarh Chhattisgarh

Saja Block

Fig.1. Location map of the study area.

the study area is around 1064 mm. The economy of Bemetara is based on agriculture. Almost 80% of the people in Bemetara are farmers. METHODOLOGY Development of Thematic Layers

Development of thematic layers involves digital image processing of remote sensing data, digitization of existing maps and field data for extraction of relevant information. To identify the groundwater potential zone of the study area various thematic layers were prepared using satellite image, Digital Elevation Model (DEM), existing data/map and with field check using Remote Sensing and GIS techniques. The complete work flow of adopted methodology is given in Fig. 2. Criteria/Factors

The factors considered in the present study are geomorphology, geology, slope, soil texture, soil depth, rainfall, lineament, drainage density, groundwater depth and land-use/land-cover. These factors are believed to be controlling factor of the precipitation, flow and storage of water in the area and, hence, influence the groundwater JOUR.GEOL.SOC.INDIA, VOL.88, OCT. 2016

ASSESSMENT OF GROUNDWATER POTENTIAL ZONE USING REMOTE SENSING, GIS AND MCDA TECHNIQUES

Rainfall data

Groundwater Monitoring

Cartosat-1 DEM

Slope

Interpolation using

Satellite data

Geometric Correction & Enhancement

IDW Tool Interp. & Classif. Rainfall in (mm)

Groundwater level in m. (bgl)

483

Existing Maps, SOI Toposheets with Field works

Geomorphology, Geology, Soil Depth, Drainage, and Lineament

Landuse/Landcover

Thematic maps

Geology & Geomorph.

Lineament

Soil Depth & Soil Textu.

Slope

LULC

Drainage

GW Depth

Rainfall

Drainage Density

Re-classification Multi-criteria techniques Multi-criteriadecision decisionmaking making(MCDM)/ (MCDM)/ AHP AHP technique s and and Weighted overlay in in GIS Environment Weighted overlayAnalysis Analysis GIS Environment

Groundwater Potenti Zone Zone Groundwater Potential Accuracy assessment of the groundwater potential ne zo Accuracy assessment of the groundwater potential zone

Fig. 2. Methodology flow chart for the present study

storage potential of the area. The relationships of these influencing factors are weighted according to their response for groundwater occurrence. A factor with a higher weight shows a larger impact and a factor with a lower weight value shows a smaller impact on groundwater potential. Integration of these factors with their potential weights is computed through weighted overlay analysis in GIS environment to determine groundwater potential zone. Geomorphology

Geomorphology reflects various landform and topographical features. Surface water is one of the important geomorphological agent in the development and shaping of landscapes and landforms; thus hydrogeomorphological JOUR.GEOL.SOC.INDIA, VOL.88, OCT. 2016

studies are of importance in planning and execution of groundwater exploration (Fashae et al. 2014). The synoptic view of satellite imagery facilitates better appreciation of geomorphology and helps in mapping of different landforms and their assembladges. The photo-interpretation criteria such as tone, texture, shape, size, location, association, physiography, genesis of the landforms, nature of rocks and sediments, associated geological structures, etc. are to be used for identification of different landforms/geomorphic units (NRSC, 2010). Initially the entire image has to be classified by keeping the physiography and relief as the citeria then within each zone the different geomorphic units have to be mapped based on the landform characteristics, their aerial extent, depth of

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Fig.3. Geomorphological map of the Saja Block, Bemetara district.

Fig.4. Geological map of the Saja block, Bemetara district.

weathering and thickness of deposition etc. Six geomorphic classes indentified in the study area are pediment shallow, pediment moderate, pediment, flood plain shallow, buried pediplan shallow and moderate alluvial plain. Geomorphological map of the study area is shown in Fig.3. The geomorhic units/landforms interpreted from the satellite images has been verified during the field visit through nala/stream cutting, dug wells cuttings in the area.

(Pandian et al. 2013; Selvam et al. 2014). Lineaments were interpreted from the satellite data of study area and have been categorized into five buffer zone viz. 50 m, 100 m, 150 m, 200 m and 250 m as shown in the Fig. 5. In the study area numbers of criss-crosed lineaments are present. The intersection of lineaments are considered as groundwater potential zones.

Geology

Groundwater occurrence and its movement depend on the geological setting. Study area falls under the Chhattisgarh basin comprising calcareous and argillaceous sediments represented by mainly shale and limestone of Raipur Group (CGWB 2009). Recent alluvium occurs as thin discontinuous and elongated patch along the small streams and nala. Visual interpretation of the satellite image has been used for delineation of geological features. Geologically study area has been classified into five classes viz. shale with calcareous rock, shale, calcareous rock, laterite and colluvium (Fig.4).

Slope Map

The slope of a surface refers to the maximum rate of change in elevation across a region of the surface. Slope is an important terrain parameter and it affects the surface

Lineament

Lineaments are the linear, rectilinear, curvilinear features of tectonic origin which can easily observe in the satellite imagery. These lineaments normally show tonal, textural, soil tonal, relief, drainage and vegetation linearity and curvilinerities in satellite data. These lineaments are mapped with the help of satellite data and can be correlated with faults, fractures, joints, bedding planes and geological contacts which are useful for the groundwater potential study

Fig.5. Lineament buffer map of the Saja block, Bemetara district. JOUR.GEOL.SOC.INDIA, VOL.88, OCT. 2016

ASSESSMENT OF GROUNDWATER POTENTIAL ZONE USING REMOTE SENSING, GIS AND MCDA TECHNIQUES

runoff and land stability (Bhunia et al. 2012; Kumar et al. 2014) and also one of the factors controlling the infiltration and recharge of groundwater system (Fashae et al. 2014). The slope map (Fig. 6) has been prepared with the help of Cartosat-I DEM in GIS environment. The slope of the study area mainly varies between 0% and 5%. Slopes of the study area has been categorized into three classes i.e. 0-1% ( nearly level), 1-3% (very gently sloping) and 3-5% (gently sloping) as per the IMSD Guidelines (NRSA, 1995). Slope class having less value is assigned higher rank due to almost flat terrain while the class having maximum value is categorized as lower rank due to relatively high run-off. Soil Texture

The rate of infiltration largely depends on the grain size and related hydraulic characteristics of the soils. (Fashae et al. 2014). Soil texture map of the Saja block, prepared with the help of exiting soil map with field check. The soil for the study area reveals seven soil texture categories namely clay, clay loam, gravelly clay loam, gravelly sandy clay, gravelly sandy loam, sandy clay, sandy. Rank of soil has been assigned on the basis of their infiltration rate. Sandy soil has high infiltration rate, hence given higher priority, while, the clayey soil has least infiltration rate hence assigned low priority. Soil texture map of the study area is shown in Fig.7.

485

In general, the depth to water level ranged between 3 and 12 mbgl in the study area. Groundwater level map has been categorized on the basis of occurrence of groundwater in the phreatic aquifer into four classes as very shallow groundwater levels ranging between 3 and 5 mbgl, shallow groundwater levels ranging between 5 and 9 mbgl, deeper water level between 9 and 12 mbgl and very deep water level more than 12 mbgl (Fig.8). Rainfall

The study area receives rainfall from the southwest monsoon starting during the month of June and extending up to September. The study area falls under the Mahanadi basin which covers nearly about 58% of the total geographical area of the state, also known as Chhattishgarh plain. Rainfall distribution along with the slope gradient directly affects the infiltration rate of runoff water. In the study area the minimum rainfall is 750 mm and the maximum rainfall is around 1152 mm. The annual average rainfall of the study area is around 1064 mm. The rainfall of the study area are categorized into eight classes as shown in Fig. 9. Soil Depth

Groundwater level of the study area has been monitored during the study from different location of the study area and groundwater depth map prepared using collected data.

Depth of soil includes topsoil and sub-soil. It is considered to be the “skin of the earth” with interfaces between the lithosphere, hydrosphere, atmosphere and biosphere. Soil is a mixture of minerals, organic matter, gases, liquids and the myriad of organisms that together support plant life (Voroney, 2006). It is a medium for plant growth, water storage, supply and purification. Infiltration

Fig.6. Slope map of the Saja block, Bemetara district.

Fig. 7. Soil texture map of the Saja block, Bemetara district.

Groundwater Depth

JOUR.GEOL.SOC.INDIA, VOL.88, OCT. 2016

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Fig.8. Groundwater level map of the Saja block, Bemetara district.

rate and water availability become limited as the topsoil erodes. The sub-soil does not absorb the rainfall as rapidly, leading to more surface water runoff and available water is less for crop production. Soil depth of the study are categorized into five class as very deep, deep, moderate, shallow and very shallow (see Fig.10).

dissection and analysis of landform, although it is a function of climate, lithology and structures and relief history of the region and can be used as an indirect indicator to explain, those variables as well as the morphogenesis of landform (Pareta et al. 2011). The streams present in the study area have been ordered using Strahler’s system of stream ordering (Strahler, 1957). The drainage density map reveals density value ranging from 1.00 to 6.99 km/km2. These are reclassified into five categories, i.e., 1.00 to 1.75 km/km2, 1.75 to 2.48 km/km2, 2.48 to 3.32 km/km2, 3.32 to 4.48 km/km2 and 4.48 to 6.99 km/km2 (Fig.11). More weightages is assigned to very low drainage density regions, whereas, low weightages assigned to very high drainage density from recharge point of view. Low drainage density indicate high permeable surface stream frequency of the area whereas high drainage density indicate impermeable ground surface/rock formation. With respect to groundwater occurrences the higher drainage density is related to less infiltration of water to the ground, which in turn leads to higher run off and vice versa. Land Use/Land Cover (LULC)

Drainage density is the stream length per unit area in region of watershed (Horton, 1932, 1945; Strahler, 1952). Drainage density is a better quantitative expression to the

Land use/land cover studies provide important indicators of the extent of groundwater requirements and groundwater utilization, as well as being an important indicator in the selection of sites for artificial recharge of groundwater (Singh et al. 2011). Land use/land cover plays a vital role in groundwater prospecting. Land use/land cover affect the rate of recharge, runoff and evapotranspiration. Land use/ land cover map prepared from remotely sensed data (satellite

Fig.9. Rainfall map of the Saja block, Bemetara district.

Fig.10. Soil depth map of the Saja block, Bemetara district.

Drainage Density

JOUR.GEOL.SOC.INDIA, VOL.88, OCT. 2016

ASSESSMENT OF GROUNDWATER POTENTIAL ZONE USING REMOTE SENSING, GIS AND MCDA TECHNIQUES

487

Fig.11. Drainage density map of the Saja block, Bemetara district.

Fig.12. Land use/land cover map of the Saja block, Bemetara district.

images) using supervised classification in ERDAS IMAGINE software with field verification. The land use/ land cover were categorized into five broad classes such as agriculture, built-up land, waste lands and water bodies as shown in Fig.12. Water bodies are continuous and excellent source of recharge of groundwater, therefore, water bodies are assigned highest weight for groundwater potential. The agricultural fields with good vegetation cover promote the infiltration rate and prevent excess runoff and, therefore, are assigned high rank for groundwater prospecting. The rate of infiltration is directly proportional to the density of vegetation cover, i.e. if the surface is covered by dense forest, the infiltration will be more and the runoff will be less. The runoff increases gradually from barren land or waste land. Therefore waste lands are assigned low weightage. Built-up land are assigned very low weightage as the infiltration rate is very low.

each and every criterion is given a weightage to represent its genuine importance in the phenomenon (Chow and Sadler, 2010). The integration of GIS and MCDA methods provides powerful spatial analysis functions (Yu et al. 2009). The Analytical Hierarchical Process (AHP) method is based on subjective approach in which weightages are assigned by pair wise comparison between various criteria obtained through policies by decision makers Saaty (1980). The Analytic Hierarchy Process (AHP) method calculates the required weights associated with the respective criterion map layers with the help of a preference matrix, in which all relevant criteria identified are compared against each other on the basis of preference factors then the weights are aggregated. GIS-based AHP has gained popularity because of its capacity to integrate a large quantity of heterogeneous data and also for obtaining the required weights relatively in a straight forward manner even for a large number of criteria (Chen et al. 2010; Feizizadeh et al. 2012; Kumar and Jhariya, 2015).

Multi-Criteria Decision Analysis (MCDA)

Multi-Criteria Decision Analysis (MCDA) process can provide the optimum solution in which the uncertainties associated with evaluating criteria are ranked on the basis of overall performance of various input decision options with respect to the multiple objectives, for the complex, fuzzy and linguistic characteristics (Aher et al. 2013). MCDA methods can be broadly divided into either multiobjective or multi-attribute methods and are primarily concerned with ways of combining several criteria to form a single evaluation index (Malczewski, 2004). In MCDA JOUR.GEOL.SOC.INDIA, VOL.88, OCT. 2016

Rating of the Classified Thematic Layers

Rates were assigned to each class according to the order of the influence of the class on groundwater storage potential. Rate gives the ranges of groundwater storage potentiality within each factor. Ratings of 1–5 were adopted where rates 1, 2, 3, 4 and 5 represent very low, low, medium, high and very high groundwater storage potential respectively. The classes of the thematic layers for all parameters and their corresponding ratings are given in Table 5. Table 6 represents the weight of each thematic layer using

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AHP and weights of their corresponding classes using AHP. The groundwater potential evaluated by the weighted linear combination of these weights is shown in Fig.13. Deriving the Weights using AHP

Analytic Hierarchy Process (AHP) used for decision making in which a problem is divided into various parameters, arranging them in a hierarchical structure making judgments on the relative importance of pairs of elements and synthesizing the results (Saaty, 1999; Agarwal et al. 2013). The relationship between these ten thematic layers has been derived using Analytic Hierarchy Process (AHP). The methodology for deriving the weights to the thematic layers and their corresponding classes using AHP involves following steps (Saaty 1999; 2004; Agarwal et al. 2013; Kumar et al. 2014; Kumar and Jhariya, 2015). Generation of Pair-wise Comparison Matrices

The relative importance values are determined with Saaty’s 1–9 scale (Table 1), where a score of 1 represents equal importance between the two themes and a score of 9 indicates the extreme importance of one theme compared to the other one (Saaty 1980). A pair wise comparison matrix is derived using Saaty’s nine point importance scale based on ten thematic layers used to determine groundwater potential zone. The AHP captures the idea of uncertainty in judgments through the principal eigen value and the consistency index (Saaty, 2004). Saaty (2004) gave a measure of consistency, called Consistency Index (CI) and calculated using the following formula. λmax – n CI = (1) n–1 where n = number of factors (i.e. 10) and λ = average value of the consistency vector λ = 7.18+10.32+10.90+10.34+7.71+10.86+9.95+ 9.84 + 9.76+9.02/10 = 9.59 and CI = (9.59-10)/ (10-1) = - 0.045 Table 1. Saaty’s 1–9 scale of relative importance Scale 1 2 3 4 5 6 7 8 9

Importance Equal Importance Weak Moderate Importance Moderate Plus Strong importance Strong Plus Very Strong Importance Very, very Strong Extreme Importance

Table 2. Saaty’s ratio index for diûerent values of n. N

1

2

3

4

5

6

7

8

9

10

RI

0

0

0.58

0.89

1.12

1.24

1.32

1.41

1.45

1.49

Consistency Ratio (CR) is a measure of consistency of pair wise comparison matrix CR =

CI RI

(2)

where RI is the ratio index. The value of RI for different ‘ n’ values is given in Table 2. For n = 10, CR is 0.030, as 0.030 (CR) < 0.10, it implies that there is a reasonable level of consistency in the pair wise comparison and the inconsistency is acceptable. If CR is greater than 10%, we need to revise the subjective judgment (Saaty, 1999, 2004; Dalalah et al. 2010; Agarwal et al. 2013; Kumar et al. 2014) as shown in Table 3. The weights of the different criteria and their CR are shown in Table 4. The determined weights are 0.021, 0.075, 0.061, 0.119, 0.185, 0.127, 0.128, 0.085, 0.089 and 0.109 respectively for land use /land cover, drainage density, slope, geomorphology, rainfall, geology, soil texture, groundwater depth, soil depth and lineament (Table 4 and 5). Classification of Groundwater Potential Zones

On the basis of weighting of the different thematic layers and theirs individual features, a potential groundwater zone map was produced (Fig. 13). The potential groundwater zone of the study area revealed five distinct zones, namely very high, high, medium-high, medium and low zones. The distribution and extents of different potential groundwater zone are 158.05 km2 (21.59 %), 35.92 km2 (4.91 %), 214.77 km2 (29.34 %), 220.59 km2 (30.13 %), and 102.72 km2 (14.03 %) for very high, high, medium-high, medium and low zone respectively (Table 6). Study area have very high to high potential zone in southern and north-eastern portion, while the central and eastern portion exhibits medium to low groundwater potentials. Assessment of the groundwater potential map revealed that the distribution is more or less a reflection of the rainfall, drainage density, lineament, slope and soil patterns in addition to the geomorphic and geological features. Validation with Borehole Yield Data

Data of existing wells were collated for 20 bore well of the study area in order to validate the classification of the groundwater potential zone which is revealed by the remote sensing, geographical information system and multiJOUR.GEOL.SOC.INDIA, VOL.88, OCT. 2016

ASSESSMENT OF GROUNDWATER POTENTIAL ZONE USING REMOTE SENSING, GIS AND MCDA TECHNIQUES

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Table 3. Pair wise comparison matrix of 10 criteria for the AHP process. Thematic layers T1 T2 T3 T4 T5 T6 T7 T8 T9 T10

T1

T2

T3

T4

T5

T6

T7

T8

T9

T10

1.00 6.00 4.00 7.50 8.25 9.00 7.75 6.25 8.50 8.00

0.17 1.00 1.50 3.60 3.30 4.12 3.50 2.00 3.00 3.10

0.25 2.50 1.00 1.60 2.10 2.34 2.10 1.30 1.40 1.57

0.13 0.90 0.98 1.00 1.20 1.90 1.73 0.90 0.92 0.94

0.12 0.84 0.83 1.40 1.00 1.10 0.91 0.87 0.53 0.74

0.11 0.53 0.54 1.00 0.94 1.00 0.81 0.53 0.32 0.51

0.11 0.35 0.29 0.90 0.73 0.83 1.00 0.25 0.16 0.30

0.16 0.21 0.14 0.54 1.60 0.42 0.72 1.00 0.12 0.15

0.12 0.19 0.11 0.32 1.20 0.23 0.35 0.14 1.00 0.11

0.13 0.09 0.10 0.12 0.80 0.11 0.14 0.11 0.10 1.00

Where, T1= LULC, T2= Drainage density, T3= Slope, T4= Geomorphology, T5= Rainfall, T6= Geology, T7= Soil Texture,T8 = Groundwater depth, T9 = Soil Depth, T10 = Lineament. Table 4. Determining the relative criterion weights Thematic layers T1 T2 T3 T4 T5 T6 T7 T8 T9 T10

T1

T2

T3

T4

T5

T6

T7

T8

T9

T10

Weight

Consistency Ratio

0.015 0.091 0.060 0.113 0.125 0.136 0.117 0.094 0.128 0.121

0.01 0.04 0.06 0.14 0.13 0.16 0.14 0.08 0.12 0.12

0.02 0.15 0.06 0.10 0.13 0.14 0.13 0.08 0.09 0.10

0.01 0.08 0.09 0.09 0.11 0.18 0.16 0.08 0.09 0.09

0.01 0.10 0.10 0.17 0.12 0.13 0.11 0.10 0.06 0.09

0.02 0.08 0.09 0.16 0.15 0.16 0.13 0.08 0.05 0.08

0.02 0.07 0.06 0.18 0.15 0.17 0.20 0.05 0.03 0.06

0.03 0.04 0.03 0.11 0.32 0.08 0.14 0.20 0.02 0.03

0.03 0.05 0.03 0.08 0.32 0.06 0.09 0.04 0.27 0.03

0.05 0.03 0.04 0.04 0.30 0.04 0.05 0.04 0.04 0.37

0.021 0.075 0.061 0.119 0.185 0.127 0.128 0.085 0.089 0.109

7.18 10.32 10.90 10.34 7.71 10.86 9.95 9.84 9.76 9.02

Where, T1= LULC, T2= Drainage density, T3= Slope, T4= Geomorphology, T5= Rainfall, T6= Geology, T7= Soil Texture,T8 = Groundwater depth, T9 = Soil Depth, T10 = Lineament.

criteria decision analysis. Bore well locations and theactual yield descriptions of these boreholes are displayed on the prediction map (Fig. 14). The actual borehole yield of the study area are classified as high yield if yield is > 6 lps., medium yield if it is from 3 – 6 lps and low yield if it is < 3 lps. This classification is based on field experience and consultation with hydrolgeologis who are working in the study area. The expected borehole yield description map (Fig. 14) prepared from the determined groundwater potential zone or prediction map (Fig.13). The borehole locations, the expected borehole yield descriptions from the prediction map, the actual yield descriptions obtained from the pumping tests and the agreement/disagreement between the expected/actual borehole yields descriptions are given in Table 7. The accuracy of the prediction is estimated as follows: Total number of boreholes = 20 Number of boreholes where, there is agreement between the expected and the actual yield = 16 Number of boreholes where, there is disagreement between the expected and the actual yield = 4 The accuracy of the prediction = (16/20)*100 = 80 %. The prediction accuracy obtained (80%) reflects that the method applied for present study produced significantly reliable and precise results. JOUR.GEOL.SOC.INDIA, VOL.88, OCT. 2016

CONCLUSION

In this study, Remote Sensing, GIS and MCDM techniques have been successfully used and demonstrated for evaluation of groundwater potential zone. A three-step methodology was used that includes development of thematic layers, deriving the weights using AHP and overlay analysis to find groundwater potential zone. Remotely sensed satellite image data and digitization of existing maps using GIS were used for the preparation of thematic layers. The AHP was used to provide utility weights for the alternatives. The overlay analysis of various thematic maps and assign weights are used for the delineation of groundwater potential zone. In this study area, five categories of groundwater potential zone have been delineated based on remote sensing, GIS and MCDA techniques. The generated groundwater potential zones map was verified with the yield data to ascertain the validity of the developed groundwater potential zones map and found that it is 80% agreement with the actual wells yield data. This illustrates that the approach outlined has merits and can be successfully used elsewhere with appropriate modifications. The above study has demonstrated the capabilities of using remote sensing and geographical information system for demarcation of different groundwater potential zones. Delineation of the groundwater potential zone in Saja block,

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Table 5. Relative weight of various thematic layers and their corresponding classes. Influencing Factors

Category (Classes)

Potentiality for groundwater storage

Rating Normalized weight

Geomorphology

Alluvial Plain Moderate Buried Pediplain Shallow Flood Plain Shallow Pediment Pediment Moderate Pediment Shallow

Very good Poor Good Poor Very poor Poor

5 3 4 2 2 1

0.119

Geology

Colluvium Laterite Calcareous Rock Sahle Shale with Calcareous Rock

Very good Good Poor Very Poor Poor

5 4 2 1 1

0.127

Lineament Buffer

0-50 Meter 50-100 Meter 100-150 Meter 150-200 Meter 200-250 Meter

Very good Good Moderate Poor Very Poor

5 4 3 2 1

0.109

Slope

0-1 % 1-3 % 3-5 %

Very good Good Poor

5 4 2

0.061

Groundwater Depth

Very shallow Shallow Intermediate Deeper

Very good Good Poor Very Poor

5 4 3 2

0.085

Rainfall

750-850 mm. 850-900 mm. 900-950 mm. 950-1000 mm. 1000-1050 mm.

1 1 1 2 2

0.185

1050-1100 mm. 1100-1150 mm. >1150 mm

Very Poor Poor Moderate Poor Moderate good Moderate Very good Good Very good Very, very good

3 4 5

LULC

Agriculture Built-up Wastelands Water bodies

Good Very poor Poor Very good

3 1 2 4

0.021

Soil Depth

Very deep Deep Moderate Shallow Shallow

Very good Good Moderate Poor Very poor

5 4 3 2 1

0.089

Drainage density

1.00-1.75 1.75-2.48 2.48-3.32 3.32-4.48 4.48-6.99

Very good Good Moderate Poor Very poor

5 4 3 2 1

0.075

Soil Texture

Clay Clay loam Gravelly clay loam Gravelly sandy clay Gravelly sandy loam Sandy clay Sandy

Very Poor Poor Poor Moderate Good Good Very good

1 2 2 3 4 4 5

0.128

Table 6. Groundwater potential zone. Groundwater Potential Zone Class

Area (sq. km)

Area in percent

Low Medium Medium - High High Very High Total

102.72 220.59 214.77 35.92 158.05 732.05

14.03 30.13 29.34 4.91 21.59 100

Fig.13. Groundwater potential zone and well location for accuracy assessment.

Fig.14. Actual yield descriptions of boreholes for accuracy assessment. JOUR.GEOL.SOC.INDIA, VOL.88, OCT. 2016

ASSESSMENT OF GROUNDWATER POTENTIAL ZONE USING REMOTE SENSING, GIS AND MCDA TECHNIQUES

491

Table 7. Accuracy assessment of the developed groundwater potential map. S. No.

Bore Well No.

Latitude

Coordinates

Longitude

Actual yield from drilled borehole (l/s)

Actual yield description

Expected yield description from the prediction map

Agreement between expected and actual yields description

1

1

21°47' 48.635" N

81°27' 2.942" E

7.28

High

Medium–high

Agree

2 3

2 3

21°51' 56.160" N 21°32' 57.939" N

81°24' 51.840" E 81°18' 17.916" E

6.11 4.21

High Medium

Medium–high Low–medium

Agree Agree

4 5

4 5

21°33' 48.856" N 21°36' 15.840" N

81°16' 21.632" E 81°19' 41.160" E

4.88 5.18

Medium Medium

High–Very high Medium–High

Disagree Agree

6 7

6 7

21°35' 53.880" N 21°46' 44.363" N

81°16' 23.160" E 81°23' 38.184" E

4.47 2.10

Medium Low

Very high Low

Disagree Agree

8 9

8 9

21°49' 21.000" N 21°40' 36.120" N

81°21' 0.000" E 81°23' 13.920" E

1.76 5.32

Low Medium

Low- Medium Low- Medium

Agree Agree

10 11

10 11

21°40' 5.880" N 21°43' 35.040" N

81°18' 19.080" E 81°16' 44.040" E

4.63 6.81

Medium High

Medium–High High–Very high

Agree Agree

12 13

12 13

21°45' 51.120" N 21°41' 13.975" N

81°20' 31.920" E 81°25' 48.957" E

5.57 7.69

Medium High

Low- Medium Medium–high

Agree Agree

14 15

14 15

21°43' 39.405" N 21°43' 23.880" N

81°26' 36.334" E 81°21' 33.840" E

6.42 6.92

High High

Medium–high Low

Agree Disagree

16 17

16 17

21°33' 38.160" N 21°35' 17.586" N

81°10' 0.840" E 81°12' 39.094" E

5.31 3.72

Medium Medium

Medium–high High–Very high

Agree Disagree

18 19

18 19

21°38' 38.040" N 21°40' 0.840" N

81°13' 14.160" E 81°11' 42.000" E

0.87 1.68

Low Low

Low- Medium Low

Agree Agree

20

20

21°32' 11.632" N

81°11' 53.063" E

6.74

High

Very high

Agree

Bemetara district of Chhattisgarh, using remote sensing and GIS techniques is found efficient to minimize the time, labour and money and thereby enables quick decision-making for sustainable water resources development and management. This gives more realistic groundwater potential map of the study area which is used for sustainable development and management of groundwater resource. Based on the result of the present study, concerned decision makers can

formulate an efficient groundwater utilization plan for the study area. Acknowledgements: We are extremely thankful to anonymous reviewers for comments and suggestions to improve the manuscript. We are very grateful to the Central Ground Wter Board, (CGWB) NCCR, Raipur, Chhattisgarh for providing valuable data and help for the present study.

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(Received: 23 January 2015; Revised form accepted: 27 July 2015) JOUR.GEOL.SOC.INDIA, VOL.88, OCT. 2016