An Evaluation of Coupling Coordination between Rural Development and Water Environment in Northwestern China

Abstract

Balancing the relationship between rural development and the protection of water resources is a challenging undertaking. This study develops a coupling coordination degree (CCD) model to examine the non-linear interaction between rural development and water environment in the 11 prefectures of Gansu, northwestern China. There are three key findings. First, economic development is the key driver of rural development, whereas social development has relatively little impact. For the water environment subsystem, improved water efficiency has been the key contributor, whereas environmental carrying capacity is secondary. Second, the CCD increased steadily in the studied period, which suggests that the relationship between rural development and water environment has gradually changed from antagonistic to mutually beneficial. However, this change is not occurring rapidly and in fact shows signs of slowing. Third, the complex spatial differences of the CCD are related to the level of economic and social development, the process of urban–rural integration, and regional natural conditions. The findings of this study have great significance for further quantitative analysis of the interaction and mutual feedback mechanism between the rural economy and the water environment in China and support evidence-based policymaking.

Is China’s Rural Revitalization Good Enough? Evidence from Spatial Agglomeration and Cluster Analysis

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Evaluation of Environmental and Economic Integrated Benefits of Photovoltaic Poverty Alleviation Technology in the Sanjiangyuan Region of Qinghai Province

“…There is an interactive relationship between the dimensions of PV industry and local development, which may have a positive (PE) or negative (NE) influence. Figure 4 shows the interactive relationship between dimensions, and the annual data of the indicators are standardized [48][49][50] with equations as follows (Equations ( 1)-( 8)):…”

Water poverty assessment based on the random forest algorithm: application to Gansu, Northwest China

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