Simulating Groundwater Potential Zones in Mountainous Indian Himalayas-A Case Study of Himachal Pradesh

Groundwater resources are increasingly important as the main supply of fresh water for household, industrial, and agricultural activities. However, overuse and depletion of these resources can lead to water scarcity and resource deterioration. Therefore, assessing groundwater availability is essential for sustainable water management. This study aims to identify potential groundwater zones in the Bilaspur district of Himachal Pradesh using the Multi Influencing Factor (MIF) technique, a modern decision-making method widely used in various sectors. Geospatial models were integrated with the MIF technique to evaluate prospective groundwater areas. Grid layouts of all underground water influencing variables were given a predetermined score and weight in this decision-making strategy. The potential groundwater areas were then statistically assessed using graded data maps of slope, lithology, land-use, lineament, aspect, elevation, soil, drainage, geomorphology, and rainfall. These maps were converted into raster data using the raster converter tool in ArcGIS software, utilizing Survey of India toposheets, SRTM DEM data, and Resourcesat-2A satellite imageries. The prospective groundwater zones obtained were classified into five categories: nil-very low, covering 0.34% of the total area; very low-low (51.64%); low-moderate (4.92%); moderate-high (18%) and high-very high (25%). Scholars and policymakers can collaborate to develop systematic exploration plans for future developments and implement preservative and protective strategies by identifying groundwater recharge zones to reduce groundwater levels. This study provides valuable insights for long-term planning and management of water resources in the region.

Automated summary

This study used the MIF technique combined with geospatial models to evaluate potential groundwater zones in the Bilaspur district. The results classified the potential groundwater areas into five categories: nil-very low, very low-low, low-moderate, moderate-high, and high-very high. This study provides valuable insights for long-term planning and water resource management in the region.