Transboundary water pollution coordination decision-making model: an application in Taihu Basin in China

Transboundary water pollution is a persistent problem in China. The Chinese government has been tentatively experimenting with eco-compensation schemes for decades to protect and sustainably use ecosystem services. However, compensation standards and pollutant reduction are the key problems in these eco-compensation schemes. This study proposes a coordination decision-making model that incorporates a typical Stackelberg game between the administrator and individual region of a river basin to solve the problems. Based on prospect theory, the model considers the bidirectional eco-compensation mechanism, the different risk preference, and the loss aversion degree of the administrator and individual regions of a river basin to compute an optimal compensation standard. Given the compensation standard, the individual regions can decide their optimal pollution reductions. Taking the Taihu lake basin as a case, the conclusions were drawn as follows. The optimal compensation standard is 3394 yuan/ton, and the optimal regional pollutant reductions of Zhejiang, Shanghai for Jiangsu are 1854 tons and 270 tons separately. The results of the coefficient sensitivity analysis show that, according to the risk preference and loss aversion degree of individual regionals, the administrator can adjust compensation standard to promote regions to reduce pollutants and maximize the utility of eco-compensation scheme.

Automated summary

Transboundary water pollution has been a persistent problem in China, and the government has been experimenting with eco-compensation schemes to address it. This study proposes a decision-making model that incorporates a game between the administrator and individual regions of a river basin to determine optimal compensation standards and pollutant reductions. Using the Taihu lake basin as a case study, the optimal compensation standard was found to be 3394 yuan/ton, and the optimal regional pollutant reductions for Zhejiang, Shanghai, and Jiangsu were determined. The results show that adjusting the compensation standard based on risk preferences and loss aversion can maximize the effectiveness of the eco-compensation scheme.