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Assessing the Effect of the Chinese River Chief Policy for Water Pollution Control under Uncertainty—Using Chaohu Lake as a Case

机译:不确定性下中国河流首席政策对水污染控制的效果评估-以巢湖为例

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摘要

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 ( ) was, the better the water pollution control effect under the RCP; (3) the greater the random interference coefficient ( ) and rewarding excellence and punishing inferiority coefficient ( ) were, the bigger the fluctuation of the water pollution control effect was; (4) when using the stochastic differential game, when , , or , , the RCP must be effective for water pollution control. Therefore, we can theoretically adjust the rewarding excellence and punishing inferiority coefficient ( ) and the random interference coefficient ( ) to ensure the effective implementation of the RCP and achieve the purpose of water pollution control.
机译:河流负责人政策(RCP)是中国创新的水资源管理系统,旨在管理水污染和改善水质。尽管RCP已在中国某些流域试行,但很少有学者研究该政策的效果。我们在随机干扰因素的影响下建立了一个差分博弈模型,比较了在没有RCP的情况下,RCP下巢湖的水污染状况,并探讨了确保RCP有效性的条件。研究结果表明:(1)RCP模式下水污染控制的平均效果大于非RCP模式下; (2)优秀奖惩劣度系数()越高,RCP下的水污染防治效果越好; (3)随机干扰系数(),奖励优等奖与劣等系数()越大,水污染防治效果的波动越大; (4)当使用随机微分博弈时,当,,或时,RCP必须有效控制水污染。因此,我们可以从理论上调整奖励优劣系数和劣等系数()和随机干扰系数(),以确保RCP的有效实施并达到水污染控制的目的。

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