Business School of Hohai University, Nanjing 21100, China.
Decision and Planning Institute, Business School of Hohai University, Nanjing 21100, China.
Int J Environ Res Public Health. 2020 Apr 29;17(9):3103. doi: 10.3390/ijerph17093103.
The River Chief Policy (RCP) is an innovative water resource management system in China aimed at managing water pollution and improving water quality. Though the RCP has been piloted in some river basins of China, few scholars have studied the effects of the policy. We built a differential game model under random interference factors to compare the water pollution in Chaohu Lake under the RCP and without the RCP, and we explored the conditions to ensure the effectiveness of the RCP. The results showed that: (1) The average effect of water pollution control under the RCP was greater than under non-RCP; (2) the higher the rewarding excellence and punishing inferiority coefficient ( θ ) was, the better the water pollution control effect under the RCP; (3) the greater the random interference coefficient ( σ ) and rewarding excellence and punishing inferiority coefficient ( θ ) were, the bigger the fluctuation of the water pollution control effect was; (4) when using the stochastic differential game, when σ ≤ 0.0403 , θ ≥ 0.0063 , or σ > 0.0403 , θ ≥ 0.268 , the RCP must be effective for water pollution control. Therefore, we can theoretically adjust the rewarding excellence and punishing inferiority coefficient ( θ ) and the random interference coefficient ( σ ) to ensure the effective implementation of the RCP and achieve the purpose of water pollution control.
河长制政策（RCP）是中国一种创新性的水资源管理系统，旨在管理水污染和改善水质。虽然 RCP 已经在中国的一些流域进行了试点，但很少有学者研究该政策的效果。我们建立了一个随机干扰因素下的微分博弈模型，比较了 RCP 和非 RCP 下巢湖水污染的情况，并探讨了确保 RCP 有效性的条件。结果表明：（1）RCP 下水污染控制的平均效果大于非 RCP 下；（2）奖励优秀和惩罚劣等系数（θ）越高，RCP 下的水污染控制效果越好；（3）随机干扰系数（σ）和奖励优秀和惩罚劣等系数（θ）越大，水污染控制效果的波动越大；（4）在使用随机微分博弈时，当 σ≤0.0403，θ≥0.0063，或 σ>0.0403，θ≥0.268 时，RCP 必须对水污染控制有效。因此，我们可以从理论上调整奖励优秀和惩罚劣等系数（θ）和随机干扰系数（σ），以确保 RCP 的有效实施，并达到控制水污染的目的。
