Spatial correlations and risk transmission of virtual water flow at city scale: A case study of the Yellow River Basin

Abstract

By introducing virtual water (VW) flow correlation coefficients and risk indicators, this study examines the VW transmission relationship between urban agglomerations and cities in the Yellow River Basin (YRB) and its impact on regional water resources pressure. The results show that: except for the Shandong Peninsula Urban Agglomeration (SPUA) and Central Plains Urban Agglomeration (CPUA), the other urban agglomerations primarily act as VW exporting regions, while virtual water-importing cities are concentrated in the eastern regions. Notably, the Ningxia Urban Agglomeration (NUA) demonstrates significantly higher VW impact and sensitivity coefficients values than the remaining six urban agglomerations. First-tier cities generally display lower virtual water impact and sensitivity coefficients, whereas emerging cities exhibit the opposite trend. Additionally, we observe uneven risk variations between VW importing and exporting regions. Taking NUA as an example, the risk increase resulting from VW exports significantly exceeds the risk reduction associated with VW imports in the corresponding regions. It’s important to highlight that first-tier cities consistently decrease water resource risk through VW imports in the study years. However, among second and third-tier cities, only 38.9 % experience reduced water resource risk through VW imports. Therefore, we recommend a focused examination of VW imports and exports in western region urban agglomerations, cities, and second and third-tier cities within the watershed. Leveraging virtual water’s asymmetric and high-value transfer can alleviate water resource pressure and scarcity risks in high-pressure regions by shifting them to lower-pressure regions, thus mitigating water resource stress across regions.

Keywords

Input-output model / Risk transmission / Water resource stress / Virtual water flow

CRediT authorship contribution statement

Jingjing Yang: Writing – original draft, Software, Methodology. Zhong Ma: Writing – original draft, Visualization, Software, Methodology, Conceptualization. Weijing Ma: Writing – review & editing, Supervision, Methodology, Conceptualization. Xingxing Niu: Visualization, Software, Methodology. Ting Mao: Visualization, Software, Methodology.

Declaration of competing interests

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This work was supported by the National Natural Science Foundation of China (Grant No. 42201302), the “Double First-Class” University Construction Project of Lanzhou University (Grant No. 561120213), and the Graduate Research Funding Project of Northwest Normal University (Grant No. 2022KYZZ—S195).

Supplementary materials

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.geosus.2024.07.011.

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