A parsimonious approach to delineating groundwater potential zones using geospatial modeling and multicriteria decision analysis techniques under limited data availability condition. Issue 5 (12th December 2019) - Kumar, Sanjay; Machiwal, Deepesh; Parmar, Babu S
Abstract : This study delineates groundwater potential zones by following an "equifinality" approach and adopting a standard methodology using remote sensing, geospatial modeling, geographic information system (GIS) and multicriteria decision analysis (MCDA) techniques. A total of 11 thematic layers (ie, rainfall, topographic elevation, slope, slope length, slope steepness, soil, geomorphology, geology, drainage density, and pre‐ and post‐monsoon groundwater levels) which have an influence on the occurrence of the groundwater are developed. The suitable weights to themes and their features are assigned and then normalized by using an analytic hierarchy process (AHP)—MCDA technique. All themes are integrated in GIS for generating a groundwater potential index (GPI) map, which classifies the study area into three zones of "good" (588.5 km 2, 34.1%), "moderate" (933.4 km 2, 54.1%), and "poor" (203.3 km 2, 11.8%) groundwater potential. Furthermore, the accuracy of the developed GPI map is verified from the coherent estimates of rainfall‐recharge. Unlike earlier studies, this study further evaluates relative sensitivity of the themes, and develops a novel "parsimonious" groundwater potential index (PGPI). The PGPI is a cost‐effective and time‐efficient method that excludes redundant parameters from the analysis and employs only the most sensitive themes in assessing groundwater potential. The results of both GPI and PGPI are found in good harmony over 86.7% area, which confirms the efficacy of the developed PGPI. The results of this study may be of interest to planners and policymakers as a guideline for locating appropriate groundwater development sites and managing sustainable water supplies, especially under data scarcity conditions and/or in developing countries.