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White, David J., Feng, Kuishuang, Sun, Laixiang and Hubacek, Klaus (2015) 'A Hydro-economic MRIO Analysis of the Haihe River Basin’s Total Water Footprint and Water Stress.' Ecological Modelling, 318. pp. 157-167.

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Abstract

Water, in particular water scarcity, is the fulcrum of China’s dilemma in pursuing industrialization, income growth, modernization, and national food security. The Haihe River Basin is an extremely water stressed hydrological system, which encompasses the two megacities of Beijing and Tianjin, and is experiencing the detrimental impacts of the recent unprecedented economic growth on its scarce water resources. We applied an integrated multi-regional input-output (MRIO) hydro-economic model combined with the Water Scarcity Index to analyze the total and scarce water consumption, footprint, and embedded flows in interregional trade in the Haihe River Basin. The study shows that in 2007, the total water footprint (WF) of the Basin was approximately 37.1 billion m3 (277 m3 per capita), of which the ‘scarce’ WF was approximately 26.7 billion m3 or 72% of the total WF. In line with its high level of water scarcity, the Basin’s net import level of virtual water was 11.3 billion m3 (84 m3 per capita), with the total import of 25.9 billion m3 and total export of 14.6 billion m3. In contrast, the Basin’s net import level of virtual scarce water is at a moderate scale of 1.8 billion m3, with the import of 15.7 billion m3 and export of 13.9 billion m3. While it is highly desirable to import more virtual water from water rich regions, a caution is needed in importing virtual scarce water because the latter will lead to greater water stress in other water scarce regions. Accounting for water scarcity in the WF analysis increases the effectiveness of the analysis and generates more valuable and accurate information for water management and planning.

Item Type: Journal Article
SOAS Departments & Centres: Legacy Departments > Faculty of Law and Social Sciences > School of Finance and Management
ISSN: 03043800
DOI (Digital Object Identifier): https://doi.org/10.1016/j.ecolmodel.2015.01.017
Date Deposited: 20 Feb 2015 10:00
URI: https://eprints.soas.ac.uk/id/eprint/19587
Related URLs: http://www.else ... ocate/ecolmodel (Publisher URL)

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