Assessing the groundwater spring potential of Sindh basin in the Kashmir Himalaya

The current study attempts to explore potential groundwater springs utilizing methodological pluralism of analytical hierarchy process (ahp), logistic regression (LR), and frequency ratio (FR) methods in GIS environment. The study is based on fourteen hydro-geological and topographic conditioning factors including lithology, land use, soil, normalized difference vegetative index (NDVI), altitude, slope, profile curvature, plan curvature, topographic wetness index (TWI), sediment transport index (STI), aspect, stream power index (SPI), distance to streams, and lineament density. The data gathered during the field survey was used to create the groundwater spring inventory. A total of 333 springs were identified among which 253 were used for training and 80 were used for validation. The weighted thematic layers were integrated in ArcGis 10.2 using the raster calculator tool to form the three groundwater spring potential maps. The maps were divided into five zones as very low, low, moderate, high, and very high potential occupying 10%, 33%, 35%, 6%, and 16%, in FR model; 25.6%, 27.19%, 30.25%, 9.84%, and 7.14% in AHP; and 25.07%, 21.18%, 19.87%, 16.43%, and 17.42%, in LR model respectively. The use of AUC predicts that the LR model (94.3%) has better technical agility in the exploration of groundwater potential in the region as compared to AHP (75.2%) and FR model (71.5%). The study calls for policy intervention in terms of harnessing groundwater spring potential to adjust raising water demands of increasing population in the study area.