Modelling the coupling evolution of the water environment and social economic system using PSO-SVM in the Yangtze River Economic Belt, China

Abstract

Being a crucial focal point of China's regional development, green development is a novel concept for the coordinated development of the environment and social economy. Therefore, elucidation of the relationship between the aforementioned factors is scientifically necessary to achieve regional green sustainability. Based on the theory of the gray water footprint and physical and statistical models, this study aims to analyze, evaluate, and predict the spatiotemporal dynamics of the coupling evolution between the water environment and social economy in the Yangtze River Economic Belt to provide a scientific reference for exploring basic laws of coordinated development, identifying influencing factors, and formulating management strategies. The results showed that: (1) from 2003 to 2017, the carrying capacity coefficients of the gray water footprint (i.e., the KCOD, KNH3-N, and KTP, except for KTN) decreased over time, as shown by a decreasing trend in the degree of the coupling coordination, which was observed from the east to the west; (2) the coupling coordination degree showed a decreasing trend from the east to the west at the spatial level and an increasing trend from 2003 to 2017 at the temporal level; and (3) the optimal scenario was green development (Plan IV) and the overall coordination degree improved. In addition, corresponding policy recommendations were proposed. The research results are scientifically significant and present a theoretical reference for the coordinated and sustainable development of the regional ecological environment and social economy.

Keywords

• Gray water footprint
• Coupling coordination degree
• Machine learning
• Green development
• Scenario analysis