A multi-objective optimization approach to allocate environmental flows to the artificially restored wetlands of China's Yellow River Delta

In this paper, a multi-objective optimization model has been developed for allocating freshwater to meet the environmental flow requirements of the restored wetlands in the Yellow River Delta, China. The model seeks a rational balance among appropriate water allocation for the wetlands, a healthy ecosystem, and optimum economic returns for the humans that use the wetlands to earn their livelihood, with the degree of ecosystem health represented by the difference between actual and ideal water levels. And then a holistic method has been used for satisfying multiple objectives to avoid the problem of decision-maker subjectivity, and then solved the resulting optimal allocation model for environmental flows of the wetlands using a genetic algorithm. With water from the Yellow River as the source, the model shows how the optimal monthly water release into the restored wetlands can be achieved in dry, average, and wet years. Using the model, 20-56% reductions in water use could be achieved compared with the current pattern of water release, and the optimal water level in each month would coincide better with the ideal value based on an indicator plant community (reeds). The results of the study demonstrate the capability of the multi-objective programming model to optimize ecological water allocation and management for the wetlands of the Yellow River Delta.