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

Xia Xu,Lina Zhang,Fengping Wu,Xin Gao

doi:10.3390/ijerph17093103

Abstract

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.

Highlights

Water pollution is one of the most pressing environmental issues in many parts of the world [1,2,3,4,5,6].The failure to meet the basic needs for safe water is one of the great tragedies of our age, and billions of people have suffered for it [7,8]
Was greater than under non-River Chief Policy (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
Based on the above analysis, we found that there were two defects in the current studies evaluating the effect of the RCP on water pollution control: (1) There has been no quantitative study regarding the RCP’s water pollution control effect, nor have there been any analyses of the main coefficients to ensure the effect of the RCP; (2) the interference of random factors has been ignored, which could influence the water pollution control effect and produce a certain error related to the RCP’s effect

Summary

Introduction

Water pollution is one of the most pressing environmental issues in many parts of the world [1,2,3,4,5,6].The failure to meet the basic needs for safe water is one of the great tragedies of our age, and billions of people have suffered for it [7,8]. Water pollution control is one of the most important tasks for governments, and attempts have been undertaken by many countries around the world to manage the problem. Many European countries have unified their policy frameworks to centralize environmental supervision powers in order to solve the problem of water pollution [9,10]. The concentration of environmental policies has had no effect on solving the problem of water pollution due to the strategy’s inability to maximize social benefits [10,11]. The United States adopted an integrated-decentralized management model to control water pollution [12], and empirical evidence has suggested that the free riding cost of a decentralized water environment policy is very high but it can improve regulatory efficiency [13,14]. Brazil’s water pollution control policy has caused a large number of cross-border negative spillovers due to a lack of cooperation between local governments [13]; India’s poor enforcement of water pollution regulations might explain why these laws have had no measurable benefits [15]

Methods

Results

Discussion

Conclusion