Abstract
Virtual water trade plays a pivotal role in alleviating water scarcity in rapidly urbanizing drylands, and accurately assessing the spillover of local water scarcity pressure to other regions through such trade is essential for sustainable development in these areas. However, systematic research on the spillover of water scarcity risks through virtual water trade and its transmission pathways in arid and semi-arid regions remains relatively limited. Taking the Hohhot-Baotou-Ordos-Yulin (HBOY) urban agglomeration as an example, this study integrated the multi-regional input-output model and structural path analysis to assess the spillover of water scarcity risk through virtual water trade and trace key transmission paths. We found that over 90% of HBOY’s water scarcity risk was transferred to regions experiencing severe or extreme water stress. Spatially, Inner Mongolia and Ningxia were the primary recipients, absorbing 37.2% and 14.5% of HBOY’s total spillover of water scarcity risk, respectively. Sectorally, 62.0% of the risk spillover originated from HBOY’s agriculture, light industry, and construction sectors and was passed to the agricultural sector in external regions. The most important risk transmission path was from HBOY’s agriculture to Inner Mongolia’s agriculture, accounting for 18.3% of HBOY’s total risk spillover. Additionally, potential loss due to insufficient external virtual water supply constituted nearly one-third of HBOY’s total economic loss from water scarcity. We recommend that rapidly urbanizing drylands and their trade partners should actively develop a cross-regional collaborative management system to mitigate the adverse effects of risk spillover.
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1 Beijing Normal University, Key Laboratory of Environmental Change and Natural Disaster of Ministry of Education, Faculty of Geographical Science, Beijing, China (GRID:grid.20513.35) (ISNI:0000 0004 1789 9964); Beijing Normal University, State Key Laboratory of Earth Surface Processes and Disaster Risk Reduction, Faculty of Geographical Science, Beijing, China (GRID:grid.20513.35) (ISNI:0000 0004 1789 9964); Academy of Disaster Reduction and Emergency Management, Ministry of Emergency Management and Ministry of Education, Beijing, China (GRID:grid.419897.a) (ISNI:0000 0004 0369 313X); Beijing Normal University, Faculty of Geographical Science, Beijing, China (GRID:grid.20513.35) (ISNI:0000 0004 1789 9964)
2 Beijing Normal University, Key Laboratory of Environmental Change and Natural Disaster of Ministry of Education, Faculty of Geographical Science, Beijing, China (GRID:grid.20513.35) (ISNI:0000 0004 1789 9964); Beijing Normal University, State Key Laboratory of Earth Surface Processes and Disaster Risk Reduction, Faculty of Geographical Science, Beijing, China (GRID:grid.20513.35) (ISNI:0000 0004 1789 9964); Academy of Disaster Reduction and Emergency Management, Ministry of Emergency Management and Ministry of Education, Beijing, China (GRID:grid.419897.a) (ISNI:0000 0004 0369 313X); People’s Government of Qinghai Province and Beijing Normal University, Academy of Plateau Science and Sustainability, Xining, China (GRID:grid.20513.35) (ISNI:0000 0004 1789 9964)
3 Beijing Normal University, State Key Laboratory of Earth Surface Processes and Disaster Risk Reduction, Faculty of Geographical Science, Beijing, China (GRID:grid.20513.35) (ISNI:0000 0004 1789 9964); Beijing Normal University, Faculty of Geographical Science, Beijing, China (GRID:grid.20513.35) (ISNI:0000 0004 1789 9964)





