Modeling the spatial pattern of potential groundwater zone using MCDM-AHP and geospatial technique in sub-tropical plain region: a case study of Islampur sub-division, West Bengal, India

The demand for groundwater is escalating with increasing population pressure because it is one of the most critical sources of freshwater resources utilized in domestic purposes, public supply, livestock, irrigation, and agricultural sectors. As a result, depletion of groundwater and contamination-related issues have been increased rapidly in the recent decade. Thus, it becomes vital to point out the geographical areas where the groundwater resource is most likely to be available and conserve such precious asset sustainably in the long run. In the study, a densely populated and agrarian-based Islampur sub-division of West Bengal was used as a study area to identify the potential groundwater resource zones using the GIS environment. In this connection, multi-criteria decision-making (MCDM) approach by applying analytic hierarchy process (AHP) has been applied in this present study to determine the weightage values and normalization of weights for each of eight parameters. The AHP-MCDM technique allows for all recognized classes of eight selected characteristics divided into separate classes and ranked according to their respective importance for groundwater identification based on the possibility of groundwater storage. Finally, using the Weighted Overlay Approach, five potential groundwater zones were identified. The analysis shows that an area of 191.75 square kilometers has a very high potential, which is occupied by only 10.84% of the area of the Islampur sub-division. Furthermore, 15 sample data regarding groundwater levels were collected from the CGWB to evaluate the accuracy of the classified groundwater zonation map. Also, the hot spot and cluster analysis shows that the potential groundwater zones have a critical spatial association with the input feature, where the z-score of 209.999 has a statistically significant model cluster with Moran's Index value of 0.556.