Combining MCDM and geospatial techniques to identify groundwater potential zones and trend analysis of rainfall and well water level data: An investigation in the Prayagraj and Kaushambi districts

This research employed remote sensing and geographic information system (GIS) to figure out the groundwater potential zones (GWPZ) in the Prayagraj and Kaushambi districts of Uttar Pradesh, India, where groundwater is heavily exploited for agriculture and urbanisation and government policies being implemented for enhancing the groundwater level. The study region contains both (confined and unconfined) type of groundwater. The following variables were utilised to produce groundwater potential zone (GWPZ) maps: geology, precipitation, geomorphology, soil texture, lineament frequency, slope, drainage density, topographic wetness index (TWI), land use and land cover and normalised difference vegetation index (NDVI). Prior to the fusion of the layers, multicollinearity assessments were performed to ascertain the accuracy of the predictive outcome. The chosen themes were included into a GIS platform with a weighted linear combination, with distinct weights allocated to different themes through the multi-influencing factor (MIF) and analytical hierarchy process (AHP) methodologies. Based on the groundwater prospective zones, the research area was divided into three groups: high potential, moderate potential, and low potential zones. Groundwater potential zones are sequentially identified by the MIF method as follows: High (16.35%; 1173.79 km 2 ), Moderate (76.28%; 5477.24 km 2 ), and Low (7.38%; 529.64 km 2 ), while the AHP method identifies the same zones as follows: High (10.01%; 717.87 km 2 ), Moderate (80.92%; 5810.41 km 2 ), and Low (9.09%; 652.40 km 2 ) in a consecutive manner. The accuracy of the maps was determined by comparing them to well water level data using the receivers operating characteristic curve (ROC). The AHP and MIF approaches yielded accuracy rates of 79.9% and 77% respectively. According to the trend analysis of rainfall for 34 years and water level of wells of 26 years for post-monsoon and pre-monsoon season the rainfall is increasing and groundwater level is decreasing. The GWPZ assessment and monitoring techniques are accurate and fair. Thus, this research is essential for creating a more efficient framework that can speed up groundwater recharge analysis and guide the installation of artificial recharge structures.