Deciphering groundwater potential zones of Sarenga block, West Bengal, India using Geographic Information System and Multi-Criteria Decision-Analysis methods

Abstract

The increasing demand for water in recent decades has led to continuous exploitation and mismanagement of groundwater resources worldwide. This has often resulted in the reduction of the water table and deterioration of water quality due to non-sustainable consumption and excessive extraction practices. To address these issues, it is very crucial to analyse Groundwater Potential (GWP) zones periodically. In this study, Geographic Information System (GIS) and Remote Sensing (RS) techniques coupled with Analytical Hierarchy Process (AHP), Multi Influencing Factor (MIF), and Random Forest (RF) algorithm have been used to define GWP zones. These methods helped to identify, weigh, and rank eleven major hydrogeological factors influencing groundwater potential (GWP). A novel application of the RF algorithm utilized to generate high-resolution GWP maps outperformed AHP (0.875) and MIF (0.828) with a Receiver Operating Characteristic (ROC) of 0.982 in GWP delineation, as assessed by the Area Under the Curve (AUC) analysis. The outcome from AHP, MIF, and RF methods revealed that around 60-70% of the study area showed poor to fair GWP while only 30- 40% of the area exhibited good to excellent GWP. The results revealed that a significant portion of the study area exhibits poor to fair GWP, highlighting the urgent need for sustainable GW management strategies. These findings provide valuable insights for policymakers and local farmers to make informed decisions on sustainable GW management plans tailored to the specific needs of the study area.

Keywords

• Remote Sensing
• Geographic Information System
• Groundwater potential zonation
• Random Forest Model
• Multi-Criteria Decision-Analysis

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