Integrated study of GIS and Remote Sensing to identify potential sites for rainwater harvesting structures

Abstract

Water accessibility is necessary for agricultural and socioeconomic development in the area. One of the best solutions to the water crisis in the Kohat region is to build rainwater harvesting structures (RWH) to collect water from local watersheds for artificial groundwater recharge. Our main objective was to identify suitable RWH locations in the study area. However, the optimum site selection for RWH in regional areas is crucial. In such a case, geospatial techniques have revealed decisive in optimum site selection for RWH structures. In the current study, we have used GIS-based models like the Analytical Hierarchy Process (AHP) and Weight of Evidence (WOE) to identify suitable sites for rainwater harvesting. Seven influential parameters, i.e., LULC, rainfall, drainage density, slope, lineament density, soil, and lithology, were considered, reclassified, and assigned ranks according to literature for analysis to produce potential site maps for RWH structures. The findings of the current study indicate that, based on the Analytic Hierarchy Process (AHP), 44% (1320 km2) of the study area is classified as highly suitable for rainwater harvesting, while 40% (1200 km2) is considered moderately appropriate, and 16% (470 km2) is deemed unsuitable. In contrast, when utilizing the Weight of Evidence (WOE) approach, the high suitability class encompasses 32% (956.8 km2) of the area, the moderate suitability class covers 43% (1285.7 km2), and the low suitability class accounts for 25% (748 km2) of the study area. The outcome of the current study aims to contribute and assist the planner, manager, and officials in finding sites for RWH structures to overcome the water table, irrigation demand, and agricultural issues in the study area.