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

Abstract

The present study involved the combined applications of advanced techniques and tools like remote sensing, GIS, electrical resistivity, MCDA, to assess the potential zones of groundwater occurrence. Several prepared thematic layers, including geology, geomorphology, rainfall, lineament, 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.

Delineation of Groundwater Potential Zones (GWPZs) in a Semi-Arid Basin through Remote Sensing, GIS, and AHP Approaches

“…This curve is a widely used metric for predicting model accuracy in classification issues [100]. In several studies, this method has been used to assess the accuracy of the groundwater potential mapping using a GIS-based AHP method [6,98,[101][102][103][104][105].…”

Groundwater and agriculture potential mapping of Mewat District, Haryana, India

“…In this work, a mix of RS and GIS methods was used to delineate the groundwater and agriculture potential zones. These are one of the most cutting-edge techniques and are also economical since it generates data that is suitable and of excellent quality for this kind of assessment [22][23][24][25][26][27]. Seven thematic layers namely Geomorphology, Soil, Slope, Drainage Density, Land Use/Land Cover, Lineament Density, and Geology were created for groundwater potential zonation based on the availability of groundwater, and six thematic layers namely Digital Elevation Model (DEM), Slope, Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), Soil Moisture Index (SMI), and Rainfall were created for agriculture potential zonation as these factors affect the potentiality for agriculture.…”

An Approach to Delineate Potential Groundwater Zones in Kilinochchi District, Sri Lanka, Using GIS Techniques

“…The use of remote sensing data in hydrological investigations can give information on spatial and temporal scales, which is necessary for effective analysis, prediction, and validation of hydrological models [30]. Satellite imagery's capacity to span vast spatial scales is vital for depicting physiographic and structural characteristics, which are essential requirements for delineating potential groundwater zones [30] and have been used by various researchers [35][36][37][38][39][40][41].…”

“…Integrated GIS and RS with AHP prove that it is a handy tool for delineating potential groundwater zones by reducing time and cost [4,17,32,37,41,44,45,[48][49][50]. Researchers adopt various techniques for delineation potential groundwater zones: statistical method [51], influence factor (IMF) [36,38,40,52], groundwater modelling, the combination of GIS, RS with AHP [37,41,45,49], and GIS-based machine learning [39,53,54]. Many researchers have adopted these methods since they have been demonstrated to be reliable and effective.…”

“…As groundwater is dynamic, RS data integration into the GIS is convenient for identifying the potential groundwater zones (GWPZ). [41] x x x x x x x x Karimi-Rizvandi et al, [39] x x x x x x x x x x Aslan and Çelik, [17] x x x x x x x x x Jhariya et al, [40] x x x x x x x x Sarwar et al, [52] x x x x x x x Nasir et al, [36] x x x x x x x Kumar et al, [37] x x x x x x x x x x Dilekoglu and Aslan, [49] x x x x x x x x x Khan et al, [38] x x x x x x x x x Abijith et al, [44] x x x x x x x x Achu et al, [32] x x x x x x x Ajay Kumar et al, [50] x x x x x x x Ahmad et al, [47] x x x x x x x x Arefin, [31] x x x x x x x x x x Arya et al, [56] x x x x x x x x x x Bhunia, [57] x x x x x x x Qadir et al, [58] x x x x x x Lentswe and Molwalefhe, [48] x x x x x Sl-Slope, Lu-Land use, Ge-Geology, Li-Lithology, Gm-Geomorphology, Rf-Rainfall, SPi-Stream Power Index, El-Elevation, So-Soil, Ld-lineament density, Rd-River density, If-Infiltration TWi-Topographic wetness index, STi-Sediment transport index, Cu-Curvature, Dd-Drainage density, Al-Altitude, Dr-Distance from the river, Aq-Aquifer, Dg-Depth to groundwater.…”