Delineation of groundwater potential zones using the integration of geospatial and MIF techniques: A case study on Rarh region of West Bengal, India

Abstract

Geospatial techniques are very important tools for the assessment, management and conservation of groundwater as well as any natural resources. This study area i.e. Saltora block in Bankura district, West Bengal [WB], India falls under the Rarh region [semi-arid] of West Bengal which is prone to water scarcity. Keeping the concern about the following problems in mind, in this study, an integrated approach of the geospatial technique i.e. remote sensing and geographical information system [GIS] and multi influencing factors [MIF] has been applied to delineate the groundwater potential zones in this study. Six influential factors like geology, lineament, slope, LULC, drainage density, and soil texture have been used to delineate the groundwater potential zones, and their influences in groundwater potential were assessed by weightage scores using the MIF technique. All thematic layers were prepared using satellite data and imageries, conventional data sets, etc. in the GIS environment, all the layers were merged using the multi influencing factor (MIF) method and thus the groundwater potential zone [GWPZ] map was constructed as a result of overlay analysis. The total Saltora block was classified into five classes in terms of groundwater potential i.e., Very high potential zone [5.23%], high potential zone [36.02%], Moderate [41.8%], Low [15.05%], and last very low potential [1.90%]. Based on the overall potentiality scenario, the Gram Panchayats [GP] of the blocks have been ranked using by TOPSIS statistical technique and the result reveals that the Bamuntore and Salma GP ranked first; Tiluri, Dhekit, Saltora, and Kanuri GP were second followed by Pabra and Gogra GP respectively. The final GWPZ delineation result was validated through ground verification using 43 dug wells data. The cut-off independent measure of the ROC-AUC curve is employed in this study to validate the GMS outcome using model testing data. The accuracy value is 0.837 and the value of AUC indicates the acceptability of the model as the AUC value > 0.75 which is considered a strong effect. In light of the aforementioned factors, the statistical model for the study is 0.754, which accurately projected groundwater potential. So, the generated map could be used as a preliminary reference for site selection of groundwater exploration.