CIMCA: Infusing computational intelligence in multi-criteria analysis to assess groundwater potential for recharge.

Accurate location-based groundwater potential mapping for recharge is a vital tool to infer simple, efficient groundwater management in policy level planning. In this context, this study introduces a novel metaheuristic based multiobjective optimization model, namely, CIMCA for preparing groundwater accumulation maps in parallel to analyzing four different Multi-Criteria Analysis (MCA) techniques. In CIMCA, computational intelligence (CI) based optimization is infused within the traditional MCA techniques, which is carefully guided/influenced by the domain expert's input within the MCA part. The CIMCA model has been found to exploit the best of both worlds, i.e., optimization and domain expert's influence, thereby achieving unbiased and consistent outputs having great prospects for mapping potential groundwater resources for sustainable planning. Takeaways from these comparative assessments, impact information at district and sub-district levels, exposure detailing on total numbers of pumping wells, etc., will be useful in formulating current planning and devising future strategies under the umbrella of sustainable groundwater management. • We present and analyze models to assess groundwater potential. • We introduce CIMCA, a novel metaheuristic based multiobjective optimization model. • We analyze multi-criteria analysis (MCA) techniques. • CIMCA infuses computational intelligence (CI) based optimization within MCA. • The optimization in CIMCA is carefully guided by the domain expert's input. [ABSTRACT FROM AUTHOR]