Simulation-optimization model for groundwater replenishment from the river: a case study in the Hutuo River alluvial fan, China

Abstract

AbstractEcological water replenishment (EWR) has been widely implemented for the restoration of the groundwater resources in the North China Plain since 2018, and the Hutuo River is one of the typical rivers. Recovering the groundwater storage capacity while ensuring the safety of the existing land use is essential for groundwater management. To simulate the groundwater response to different recharge schemes, and to determine the optimal recharge strategy that has the maximum amount of water recharged into the aquifers under specific constraints, an optimization framework, which integrates a 3D transient groundwater flow model with a genetic algorithm (GA), was realized in a Python programming environment in this study. The optimization results show that the optimal amount of water recharged into aquifers is 5.36 × 109 m3 from January 2020 to December 2029, and the upper river reaches are the main recharge area, accounting for 67.58% of the total. Compared with constant recharge, optimal results indicate that the total amount of water recharged into aquifers will increase without exceeding the upper limits of the groundwater levels. However, as groundwater exploitation reduces (18.44%), the river's optimal amount of water recharged also decreases (17.23%). Therefore, the developed model can identify the optimal groundwater recharge strategy and eventually facilitate decision-making in the case of EWR.