Incorporating water quality responses into the framework of best management practices optimization

Determining cost-effective configurations of best management practices (BMPs) is a notably complex problem, especially for large-scale watersheds. In this paper, a Markov-based simulator that has been developed to quantify water quality responses is described, and a new framework is also proposed for the optimal design of BMPs by integrating the Markov approach, a watershed model, and an evolutionary algorithm. This new framework was then tested in a typical watershed, the Three Georges Reservoir Region in China. The results obtained from this application indicate the integration of water quality responses is vital for the optimal design of BMPs, especially for the downstream areas of the targeted river assessment section. The Markov-based algorithm had a computational advantage over traditional algorithm and this new algorithm offers the prospect of providing more cost-effective medium-cost solutions. The relative impacts of upstream BMPs were also highlighted in protecting water quality at multiple river assessment sections. This new algorithm can easily be extended to any other watershed to aid decision managers in the optimal design of BMPs at the watershed scale.