Water resources asset accounting and driver analysis in the Yangtze River Economic Belt based on the "quantity-value" framework

Le résumé fourni par la source

Accounting for water resources assets is an important part of the inventory of nationally owned natural resources assets, and is a basic prerequisite for the preparation of natural resources balance sheets. This study examines the macroeconomic data of the 11 provincial-level regions in the Yangtze River Economic Belt (YREB) from 2012 to 2021. It begins by elucidating the natural system of water resources formation and the economic system of water resources asset formation. The concept of potential water resources assets is introduced, and the cyclical patterns of water resources asset evolution are investigated. Then, based on the "quantity-value" framework, the adjusted coefficient method and energy value analysis method are adopted to construct models for the physical quantity and value accounting of regional water resources assets. Finally, an indicator system is designed from economic, social, environmental, and ecological dimensions. The geographic detector model is selected to explore the influencing factors of spatial differentiation of water resources assets. The research findings reveal that: (1) The physical volume of water resources assets in the YREB demonstrates fluctuating changes, reaching a peak of 2734.27 billion m3 in 2019 and a low value of 2548.70 billion m3 in 2020. Specifically, Shanghai, Jiangsu, Hunan, and Yunnan display "N"-shaped trends, while Jiangxi, Hubei, and Guizhou demonstrate "W"-shaped trends. The remaining regions exhibit more moderate trends. (2) The overall value of water resources assets fluctuates, showing an upward trend with an average annual increase of 13.14%. The spatial distribution of water resources asset value exhibits a pattern of "downstream>midstream>upstream" differentiation. (3) Population density is identified as the primary driver of spatial differentiation in water resources assets within the YREB. The cumulative explanatory power of the social subsystem is the highest, indicating that social factors have the greatest influence on the spatial pattern of water resources assets. The research findings contribute to elucidating the cyclic evolution process of water resources, latent water assets, and water resources assets, improving the macroeconomic accounting system, and providing valuable insights for the sustainable utilization of water resources.

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