Assessment of groundwater potential zone using GIS-based multi-influencing factor (MIF), multi-criteria decision analysis (MCDA) and electrical resistivity survey techniques in Raipur city, Chhattisgarh, India

The present study involved the combined applications of advanced techniques and tools like remote sensing, geographic informatic system (GIS), electrical resistivity, MCDA, to assess the potential zones of groundwater occurrence. Several prepared thematic layers, including geology, geomorphology, rainfall, lineament, land use land cover (LULC), drainage density, soil type, slope, and soil texture, were assigned with a weight, depending on their influence on groundwater potential. Normalization concerned with relative contribution is applied in this study using the AHP method. Vertical electrical sounding has been conducted on different points to locate water-bearing formations/fracture zones. The resulting groundwater potential areas that are delineated applying these methods have been categorized into five zones, low, medium, medium-high, high, and very high potential. The groundwater potential zones demarcated show that high potential zones are present in the west and north-eastern portion, while low to medium groundwater potential is located in the central and eastern portion. The obtained result was validated using well yield data, and ROC method from which result accuracy obtained is 80% and the area under the ROC curve is found to be 0.857 at a significance value of less than 0.001, which justifies the efficacy of the proposed approach in the demarcation of groundwater potential zone.


INTRODUCTION
Urban areas are dynamic networks that experience rapid population growth, surface water shortage, and high groundwater demand. The groundwater potential of a region depends on different facts and it varies from place to place according to its change. Variation of the groundwater potential within a short distance and the same geological formation has also been observed (Dar et  MCDA is a technique that has wide applications in different fields. It is mainly used to solve complex problems by dividing them into different sections and solving and integrating each of them to get the ultimate result. It is used in fields where decision-making is a little tough and complex. Since, compared to others, MCDA is considered as one of the approachable techniques, within that, the AHP is marked as an important one. The method was developed and introduced by Thomas L. Saaty in 1977 (Saaty ).
The AHP (Saaty ) is accepted worldwide for quantitative analysis. It is a dependable decision-making tool for problems with different criteria and with different natures, which can also be used to evaluate the probable zones of groundwater occurrence chosen in this study. AHP has been accepted as a very useful tool by the international scientific community due to its ability to deal with complex problems and making suitable decisions. This method itself introduced the concept of pairwise comparison. In the absence of a quantitative rating, one can still manipulate each controlling factor's rank by proper assignment of the rank of each parameter gained from the literature study and field observation, according to its importance. In this case, the pairwise comparison is converted into a set of numbers with the help of AHP, to categorize it into different ranks according to its relative priority (Saaty ; Agarwal & Garg ). The pairwise comparison technique is considered as a theoretical-based approach that applies to the computation of weights representing their relative importance. Comparing all possible pairs from the eigenvector of the square reciprocal matrix (normalized matrix) derives a set of weights from the best fit, used for the assignment of weight for thematic layers.
Finding and locating the water-bearing/fractures zones, with the provision of electrical resistivity method is con- Therefore, the integrated use of AHP, GIS, RS, and electrical resistivity techniques by taking into account hydrogeological, geomorphologic, and meteorological data is much more reliable than applying the techniques individually.
Integration of all these factors helps to produce a more appropriate result, which can refer to any other area, especially in a highly populated, developing area like Raipur.
The current study employed the above-integrated method for the evaluation of potential zones of groundwater in Raipur city.

STUDY AREA
Raipur city is the capital of Chhattisgarh province, which is The maximum temperature is recorded around 47 C during May. The monsoon starts in June and extends up to the end of September. The average annual precipitation is 1,240 mm, and the climate is humid. The Kharun River bounds the study area on the western side of Raipur city.

DATA USED
In the present study, numerous spatial data sets have been utilized to analyze probable potential zones of groundwater within the study area (Table 1).

METHODOLOGY Development of thematic layers
The base map of Raipur city was prepared according to the Survey of India (SOI) toposheets (1:50,000 scale). To assess groundwater potential zones, multi-parametric data set, namely, geology, geomorphology, rainfall, lineament, LULC, drainage density, soil type, slope, and soil texture were prepared using topographic maps, existing map, data collected from the field study, and satellite image using integrated techniques such as RS and GIS (Thakur et al. ).
The satellite data, Sentinel-2 geocoded imagery, were accessed from Earth to explore the site (http://glovis.usgs. gov/). The LULC, drainage, lineament, and soil texture map were prepared based on the Sentinel-2 (spatial resolution 10 meter) false color composite (FCC) images in ERDAS IMAGINE software using visual interpretation techniques with field check.
A geology and geomorphology map of the area has been produced from the existing maps from the reports of Central Groundwater Board (CGWB ), subsequently updated with Geological Survey of India (GSI) toposheets and satellite image and field check. Topography (slope map) has been prepared by using Shuttle Radar Topography Mission-Digital Elevation Model (SRTM-DEM) with a 30 m spatial resolution. Groundwater level data collected from the bore wells and the inventory wells of the CGWB located in the study area were employed for the generation of groundwater depth maps, with the help of interpolation techniques in the ArcGIS environment. Meteorological data collected from the Water Resource Department, Raipur Chhattisgarh (WRD) were used to generate rainfall maps with the help of ArcGIS software. The whole technical flowchart of the methodology adopted in this study is given in Figure 2.
Criteria/Factors to determine the groundwater potential zone In the present study, nine criteria, geomorphology, geology, lineament, slope, soil, groundwater depth, rainfall, drainage density, and LULC were considered to assess potential

Soil texture
Soil is a significant parameter for the identity zone of potential groundwater occurrence. The study area consists of four types of soil, i.e., sandy loam soil, sandy clay loam, clay loam, and clay soil ( Figure 7). The soil texture of the area      is one of the major factors that control the surface runoff and infiltration of rainwater. Sandy group soil has a low runoff rate and high groundwater potential, whereas the clay soil group has a high runoff rate and very low groundwater. Sandy soil shows a high infiltration rate, and clayey soil offers the least infiltration capacity. The majority of the study area (52.52%) was covered by clay loam soil with a low to medium infiltration rate.
Depth to water level The depth to the groundwater level depends upon the recharge and discharge of the groundwater. Groundwater level data collected from CGWB Raipur, used for water level maps, has been generated by the inverse distance weighting (IDW) interpolation method. Normal depth to water level within the study area ranges between 3 and 12 mbgl. The depth to water level map is categorized into four classes, 3-6 mbgl, 6 and 9 mbgl, 9 and 12 mbgl, and >12 mbgl. This parameter is important for the groundwater potential zone. The thematic representation of the depth to water level shows that the eastern part of the study area is found as an area of low groundwater level ( Figure 8).

Rainfall
Rainwater is considered the primary source of the groundwater resource. The rainfall distribution associated with surface gradient influences the runoff and infiltration rate, hence indicating the possible groundwater potential zones.
The southwest monsoon is prominent within the study area, and is active from June and extends up to September.
With the aid of five rain gauge stations, the recorded daily rainfall of the year 2016 indicates that rainfall was above normal with significantly high intensity than that compared to the past 15 years. The maximum rainfall is recorded at approximately 1,267 mm. According to the available data, four classes have been derived to characterize the potential zone ( Figure 9).

Drainage density
The length of the stream to a unit area of the region is defined as the drainage density (Horton ; Strahler ). It is a suitable tool for analysis of the landform in terms of groundwater potential. The ordering of the tributary streams has been done according to Strahler's stream   (1): where Dd denotes drainage density and Li is the total length of drainage. Dd is drainage density that is significantly correlated with the groundwater recharge. It is a fact that a high Dd zone indicates a probable recharge zone of groundwater.
According to the recharge rate, the weight of the subclasses of drainage density is assigned in a manner that high weight is given to the areas of low drainage density, as a representative of low runoff rate and high infiltration rates, and similarly, low weight has been given to the regions having high drainage density with a high rate of surface runoff and low rate of infiltration. This indirectly infers that the area with high drainage density represents the land of impermeable rock and low drainage density represents a permeable basement. In conclusion, the possible groundwater occurrence zones can be identified by the presence of low drainage density areas and of high infiltration rates.

Land use land cover (LULC)
Consumption of land for different processes also affects the lake, and road, that has been identified and demarcated, as shown in Figure 11. The majority of the study area is covered with cultivation (43.78%), settlement (24.04%), open land (22.18%), road (2.21%), and lake (5.37%). Each subclass in the land uses land cover class assigned with    In contrast, the settlement and road possess low weight due to high runoff, and moderate to good groundwater potential can be found in the areas that cover open land and cultivation land, which consist of medium weight ( Figure 11).

Multi-criteria decision analysis (MCDA)
The AHP is a subunit of the multi-criteria decision-making method, which involves the analysis and associated    (3) and (4): (3) where, W ¼ eigenvector, w i ¼ eigenvalue of criterion i, and, λ max ¼ eigenvalue of the pairwise comparison matrix.
The judgment of uncertainty is based on Saaty's Consistency Index (CI), calculated using Equation (5): where n represents the number of criteria or classes.
Measurement of consistency ratio, CR is a pairwise comparison matrix, which is calculated with Equation (6): The RI values representing different numbers of n are shown in

Demarcation of groundwater potential zones (GWPZ)
The detailed methodology adopted for the demarcation of GWPZ by the assistance of different tools like RS, GIS, and MCDM is illustrated in Figure 2. Integration of selected thematic maps for the computation of GWPZ using Equation (7) has been completed in the GIS environment.
where, x i and w j are the normalized weights of the i th and j th  The resulting curves subject to the curve matching method with the theoretical curve of the known vertical distribution of the resistivity and thickness gives the information of sequences representing the geo-electrical layer at the point and depth of investigation.

Schlumberger configuration
In sounding with Schlumberger configuration, the movement of electrodes is carried out to always follow a straight line by keeping the potential electrodes closely spaced. In practice, the potential electrode spacing is kept at not more than 1/ • The apparent resistivity ρa ¼ π{(AB/2) 2 À (MN/2) 2 }/MN * R ¼ K * R.

RESULTS AND DISCUSSION
Deviation from conventional methods and the adoption of potential mapping techniques/tools such as RS, GIS, and electrical resistivity can be applied for the delineation of groundwater probable zones. Different thematic layers were developed according to each of them and their importance on groundwater occurrence of the study area ( Figures 3-11). The rate of each assigned factor decides the contribution of each factor on groundwater storage and potentiality. In this process, the GIS layers of different factors such as geomorphology, geology, LULC, soil, lineament buffer, slope, rainfall, and drainage density were analyzed carefully, and weights were assigned to corresponding thematic maps. Allocation of rates from 1 to 5 indicate very low, low, medium, high, and very high in ascending order, associated with each class, were selected based on the control of each factor on the groundwater potential.
The representative weight of each thematic layer and associated classes derived from applying the AHP method are given in Tables 4 and 5. The linear combinations of these weights that are adopted for the evaluation of groundwater potential are shown in Table 6.
Where RI is the Ratio Index, the value of RI for selected 'n' values are given in Table 3 Table 4). The weights of the different criteria and corresponding CR are shown in Table 4.  Figure 12). According to the spatial variation of groundwater potential, the study area was split into five zones, namely, low, medium, medium-high, high, and very high, whose spatial distribution and extents 58.14 km 2 (11.86%), 141.34 km 2 (28.82%), 166.33 km 2 (33.92%), 103.27 km 2 (21.06%), and 21.35 km 2 (4.35%) are given in Table 7.
The interpreted results of resistivity data indicate there are four different layers (the results are given in Table 8 and Figure 13) as given below: • The first layer is topsoil cover, except at Kurru (VES-64), Banjari (VES-65), and IIIT Naya Raipur (VES-68), where the top layer is laterite. The resistivity ranges of this layer vary from 3 to 360 Ohm-m. The depth ranges vary from 1.1 m to 3.6 m.
• The second layer is weather formation (shale/limestone), and its resistivity varies from 2 to 115 Ohm-m. The thickness varies from 1.3 to 19.4 m.
• The third layer is the fractured formation (fracture shale/ limestone), and its resistivity varies from 15 to 345 Ohmm. The thickness of this layer is between 12 and 39.3 m.
• The fourth layer, i.e., the last layer, is the massive formation (massive shale/limestone) below the fracture formation. The resistivity of this layer varies from 150 to 950 Ohm-m.
The maximum resistivity value was observed in Dharampura (VES No.43) and the resistivity value is 950 Ohmm below a depth of 16.7 m. The high resistivity indicates that the formation is compact at this depth and the rock type is limestone. To identify fractures at depth in hard rock area by conducting VES, a factor analysis method is used. In this method, first of all, the value of apparent resistivity should be taken for the same potential dipole (MN/2) value. The factor for any AB/2 value is the ratio of apparent resistivity value of that AB/2 and the sum of all the apparent resistivity values of all the earlier AB/2. If the total number of apparent resistivity values of a sounding is 'n' then the total factor will be n-1, as there will be a factor for the first AB/2. We can identify the same factor value for two consecutive readings of AB/2 from the obtained factor values to indicate the fracture zone at the respective depth. The provable fracture zones are given in Table 8.
Assessment of potential zones within the study area reveals that the high potential zone has been detected in the west and north-eastern portion. In contrast, low to medium groundwater potential is located in the central and eastern parts. Derived groundwater potential results from the integrated operation of various factors such as slope, rainfall, lineament, drainage density, and soil patterns including the geomorphic and geological control.
The result shows that LULC and geology are the main factors that control the groundwater occurrence in the area. The geomorphology and slope do not have much influence on the groundwater potential because of the low slope and moderately horizontal and plain nature of the terrain.
Groundwater occurrence of the area is mainly controlled by the geological succession of the area. Even though the LULC may play a significant role in the infiltration of the water and recharge of the groundwater, the geology itself provides the space for its free movement. Comparison of the resulting groundwater potential and the geology of the area shows that the zone of high to a very

VALIDATION OF THE OBTAINED RESULT
In the present study, the output result has been validated using well yield data and the ROC method.

Validation using well data
An accuracy check of the prediction model is highly essential to prevent errors and improve environmental studies' decision-making. The obtained potential zones derived by integrating different techniques like RS, GIS, and MCDA were validated with correlation studies of data collected from ten wells in the study area (Table 9 and Figure 14).
Locations of the selected wells, yield attained from the prediction map, actual yield data collected from the pumping test, and the acceptance/rejection of values that denote borehole deviation yield data between expected/real in the form of the agreement are shown in Table 9.
Accuracy check of predicted values is estimated as follows: • Total boreholes ¼ 10.
• Number of borehole value which attains agreement between actual yield and expected ¼ 8.
• Number of borehole value which shows disagreement between actual yield and expected ¼ 2.
The accuracy prediction proved that the selected methodology implemented in this study is notably reliable and accurate.

Validation using the ROC method
The resulting outcome has been validated by the quantitative measure validation method, known as the operating characteristics (ROC) method. The quality of a forecast system by describing the system's ability to correctly anticipate the occurrence or non-occurrence of a predefined   (9)): In the present study, the sample size is 10 and the middle and high yield is 1, 2 and the low yield is 0.  The elevated resistivity indicates that the formation is compact at this depth and the rock type is limestone.
The result reveals that the study's potential zones are high in the west and north-eastern portion, while low to medium groundwater potential is located in the central and eastern portion. Derived groundwater potential results from the integrated operation of various factors such as slope, rainfall, lineament, drainage density, and soil patterns, including the geomorphic and geological control. The result revealed that the LULC and geology play a major role in the groundwater condition of the area. This study validated using well yield from which accuracy of 80% was attained and validated using the ROC method. The area under the ROC curve (AUC) is found to be 0.857 (85.7%) at a significance value of less than 0.001. Thus, the high value of AUC justifies the efficacy of the proposed approach in predicting low and middle/high yield areas. Overall, the integrated application of RS and GIS method supported by the resistivity analysis increases the values of the result, therefore, it can be considered as authentic data for future planning, especially for policymakers and development planners that interact with or affect the groundwater resources of the area. However, a slight variation in the future possibly considers the variables rainfall and LULC as the major factors for the computation of groundwater potential zones.