Identification of suitable Managed Aquifer Recharge locations In California's Central Valley using an evolutionary multi-objective optimization

Population growth and expansion of irrigated agriculture have forced a six-fold increase in global groundwater withdrawals over the last century. To address and potentially mitigate adverse effects of groundwater overdraft many groundwater dependent regions implement Managed Aquifer Recharge (MAR) programs to enhance the quantity and quality of groundwater. However, the numerical simulation of MAR and the siting of best recharge locations still pose significant scientific challenges. In order to improve or optimize the joint management of surface water and groundwater resources, decision makers increasingly rely on integrated studies that consider both the groundwater hydrology and the behavioral economic use of groundwater. Using advanced numerical optimization strategies increases further the overall modeling flexibility and allows obtaining and testing multiple suboptimal management solutions for decision makers to consider. In this study, we explore the use of the California Central Valley Groundwater-Surface Water Simulation Model C2VSim coupled with an evolutionary multi-objective optimization algorithm to identify optimal MAR locations. The modeling framework is used to calculate multiple optimal locations for a set of recharge basins across the Central Valley that use excess, high-magnitude streamflow to recharge groundwater. Hydrological (e.g. maximization of groundwater storage, regional water table rise) and economic (e.g. land price, conveyance cost, lift cost, water acquisition cost, Mar maintenance cost) objective functions are used to obtain a two-dimensional Pareto front. Results demonstrate that a more integrated use of water resources coupled with an optimal distribution of recharge basins can significantly improve long-term groundwater storage in the Central Valley. Furthermore, results confirm the usefulness of the proposed modeling framework, which identifies compromise MAR locations, able to minimize economic costs and maximize hydrological benefits.