A conjunctive management framework for the optimal design of pumping and injection strategies to mitigate seawater intrusion

Coastal aquifer management (CAM) considering conjunctive optimization of pumping and injection system for seawater intrusion (SI) mitigation poses significant decision-making challenges. CAM needs to pose multiple objectives and massive decision variables to explore tradeoff strategies between the conflicting resources, economic, and environmental requirements. Here, we investigate a joint artificial injection scheme for ameliorating SI by establishing an evolutionary multi-objective decision-making framework that combines simulation-optimization (S-O) modelling with a cost-benefit analysis, and demonstrate the framework on a large-scale CAM case in Baldwin County, Alabama. First, a SI numerical model, using SEAWAT, was configured to predict the vulnerable region as an SI encroachment area with the scenarios of minimum and maximum pumping capacity. As a result, a smaller number of candidate sites were selected in the SI encroachment area for implementing groundwater injection to avoid the computationally infeasible SI optimization with an inordinate number of injection related decision variables. Second, the effective S-O methodology of niched Pareto tabu search combined with a genetic algorithm (NPTSGA), which considers the moving-well option, was applied to discover optimal pumping/injection (P/I) strategies (including P/I rates and injection well locations) between three conflicting management objectives under complicated SI constraints. Third, for practical operation of the P/I schemes, a cost-benefit analysis provides judgment criteria to allow decision-makers to implement more sustainable P/I strategies to capture the different realistic preferences. The implementation of three extreme optimization solutions for the case study indicates that, compared to the initial unoptimized scheme, a maximum increase of a factor of 3 in groundwater extraction rates, a maximum reduction of 17% in extent of SI, and a maximum 82.3 million US dollars in comprehensive benefits are specifically achieved by conjunctive P/I optimization. The robustness in the decision alternatives attributed to the uncertainty in physical parameters of hydraulic conductivity was discovered through global sensitivity analysis. The proposed framework provides a decision support system for multi-objective CAM with combined pumping control and engineering measures for SI mitigation.