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Groundwater is an essential resource for agricultural and life support, particularly in areas with unpredictable rainfall and rising water demands. The goal of this study is to identify the Groundwater Potential Zones (GWPZ) in Kolhapur district, Maharashtra, by utilizing an integrated method that incorporates the Analytical Hierarchy Process (AHP), Remote Sensing (RS), and Geographic Information Systems (GIS). This study examines the temporal variations of GWLF, Land use/ Land cover, Rainfall from year 2017 to 2022 along with geomorphology, slope, lineament density, drainage density, soil texture, topographic roughness index (TRI), topographic wetness index (TWI) using Arc-GIS 10.8. Meteorological stress is indicated by a significant decrease in decadal mean rainfall and an increase in low rainfall zones, while unpredictable rainfall and urbanization put further demand on groundwater recharge. While the "Safe" zone continued to dominate, spanning over 80% the "High" potential zone shrank by around from 1279.44 km² in 2017 to 876.96 km² in 2022, while the "Poor" zone grew by almost 57%, according to the study. These results demonstrate how urgently integrated groundwater management and recharge measures are needed. The validation of results shows good accuracy with pre and post monsoon groundwater level data.
Keywords:
Analytic Hierarchy Process (AHP), Geographic Information System (GIS), Groundwater Potential Zone (GWPZ), Weighted Overlay Analysis (WOA)
Cite Article:
"Integration of Analytic Hierarchy Process and RS-GIS for Dynamic Groundwater Potential Mapping in Kolhapur District, Maharashtra", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 6, page no.b315-b333, June-2025, Available :http://www.ijrti.org/papers/IJRTI2506139.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator