Comparing GIS-based multi-criteria decision-making and Boolean logic modelling approaches for delineating groundwater recharge zones

Artificial groundwater recharge is a corrective measure for restoring the fast-depleting groundwater resources. This study, for the first time, employed and compared both the multi-criteria decision-making (MCDM) and Boolean logic modelling (BLM) approaches to delineate groundwater recharge zones in a hard-rock catchment of Udaipur, India. Thematic maps of geomorphology, soil, land use, ground elevation, percent slope, slope length, slope steepness, drainage density, transmissivity and groundwater fluctuation were prepared by using remote sensing and geographical information system. Suitable relative weights to variables and their classes were assigned depending upon their influence on groundwater recharge. The weights were normalized by MCDM technique to remove subjectivity. Thematic maps were integrated to delineate recharge zones. In BLM approach, decision rules were developed and AND operator was used to integrate the thematic maps to delineate recharge zones. It was found that 36.07 km2 (10 % of total area) and 30.55 km2 (9 % of total area) were rendered as suitable zone by the MCDM and BLM approaches, respectively. Two approaches were successfully validated based on net recharge estimates of 50 sites, and results were found in agreement and comparable to each other in 90 % area. Moreover, 29 favourable artificial recharge sites were identified in suitable recharge zone based on drainage map. Finally, the recharge sites were grouped into four clusters by using multivariate statistical analyses, which characterized the most influencing variables. These findings may be useful for decision-makers to formulate appropriate groundwater management strategies, and the approach may be well-opted in other hard-rock regions of the world especially in economically poor nations.