Evaluating the vulnerability of physical and virtual water resource networks in China's megacities

被引:34
作者
Zhang, Xinxin [1 ]
Zhao, Xu [2 ]
Li, Ruoshui [3 ]
Mao, Ganquan [4 ]
Tillotson, Martin R. [5 ]
Liao, Xiawei [6 ]
Zhang, Chao [7 ]
Yi, Yujun [8 ]
机构
[1] Shandong Univ, Business Sch, Weihai 264209, Peoples R China
[2] Shandong Univ, Inst Blue & Green Dev, Weihai 264209, Peoples R China
[3] Duke Univ, Nicholas Sch Environm, Durham, NC 27705 USA
[4] Southern Univ Sci & Technol, Sch Environm Sci & Engn, Shenzhen 518055, Peoples R China
[5] Univ Leeds, Sch Civil Engn, Water Leeds, Leeds LS2 9JT, W Yorkshire, England
[6] Peking Univ, Sch Environm & Energy, Shenzhen Grad Sch, Shenzhen 518055, Peoples R China
[7] Tongji Univ, Sch Econ & Management, Shanghai 200092, Peoples R China
[8] Beijing Normal Univ, Sch Environm, Key Lab Water & Sediment Sci, Minist Educ, Beijing 100875, Peoples R China
基金
中国国家自然科学基金; 北京市自然科学基金;
关键词
Input-output analysis; Virtual water; Water footprint; Water Stress Index; DECOMPOSITION ANALYSIS; ENVIRONMENTAL IMPACTS; CONSUMPTION; FOOTPRINTS; SUSTAINABILITY; URBANIZATION; STRESS;
D O I
10.1016/j.resconrec.2020.104972
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The water resource networks that provide water for urban consumption consists not only of physical water supply, but also water embodied in imported goods and services i.e. virtual water supply or external water footprint. However, it remains unknown that if relying on external water footprint will increase or decrease the vulnerability of cities' water resource networks. Here, we evaluate the vulnerability of urban water resource networks for China's six megacities i.e. Beijing, Tianjin, Shanghai, Chongqing, Guangzhou, and Shenzhen. The vulnerability index was developed through combining a refined multi-region input-output table with both water footprint and water scarcity footprint analysis. The results showed that megacities need to import large volumes of virtual water embodied in food related sectors to balance their physical water shortages. The external blue water footprint (BWF) of the six megacities accounted for 80.7% of their total BWF, and was almost twice their physical water supply. The large share of external BWF helped Beijing, Tianjin, and Shanghai, which suffer extreme water stress in their urban areas, to decrease their total vulnerability by 39%, 33%, and 28% respectively, but conversely increase their vulnerability to external water shortages i.e. indirect vulnerability. Establishing megacity physical and virtual water resource networks based on input-output analysis provides an opportunity for urban water planners to internalize the risk of their external water footprint. Avoiding import water-intensive products from regions suffering extreme water stress, or managing indirect vulnerability through cooperation with those regions are suggested as viable water management approaches.
引用
收藏
页数:12
相关论文
共 48 条
  • [1] Allan T., 1992, FORTUNATELY THERE AR, P13
  • [2] [Anonymous], ENV SCI TECHNOL
  • [3] The WULCA consensus characterization model for water scarcity footprints: assessing impacts of water consumption based on available water remaining (AWARE)
    Boulay, Anne-Marie
    Bare, Jane
    Benini, Lorenzo
    Berger, Markus
    Lathuilliere, Michael J.
    Manzardo, Alessandro
    Margni, Manuele
    Motoshita, Masaharu
    Nunez, Montserrat
    Pastor, Amandine Valerie
    Ridoutt, Bradley
    Oki, Taikan
    Worbe, Sebastien
    Pfister, Stephan
    [J]. INTERNATIONAL JOURNAL OF LIFE CYCLE ASSESSMENT, 2018, 23 (02) : 368 - 378
  • [4] Direct and indirect urban water footprints of the United States
    Chini, Christopher M.
    Konar, Megan
    Stillwell, Ashlynn S.
    [J]. WATER RESOURCES RESEARCH, 2017, 53 (01) : 316 - 327
  • [5] THE INS AND OUTS OF WATER USE - A REVIEW OF MULTI-REGION INPUT-OUTPUT ANALYSIS AND WATER FOOTPRINTS FOR REGIONAL SUSTAINABILITY ANALYSIS AND POLICY
    Daniels, Peter L.
    Lenzen, Manfred
    Kenway, Steven J.
    [J]. ECONOMIC SYSTEMS RESEARCH, 2011, 23 (04) : 353 - 370
  • [6] Exposure of urban food-energy-water (FEW) systems to water scarcity
    Djehdian, Lucas A.
    Chini, Christopher M.
    Marston, Landon
    Konar, Megan
    Stillwell, Ashlynn S.
    [J]. SUSTAINABLE CITIES AND SOCIETY, 2019, 50
  • [7] Estimates and Predictions of Methane Emissions from Wastewater in China from 2000 to 2020
    Du, Mingxi
    Zhu, Qiuan
    Wang, Xiaoge
    Li, Peng
    Yang, Bin
    Chen, Huai
    Wang, Meng
    Zhou, Xiaolu
    Peng, Changhui
    [J]. EARTHS FUTURE, 2018, 6 (02) : 252 - 263
  • [8] Integrating ecological and water footprint accounting in a multi-regional input-output framework
    Ewing, Brad R.
    Hawkins, Troy R.
    Wiedmann, Thomas O.
    Galli, Alessandro
    Ercin, A. Ertug
    Weinzettel, Jan
    Steen-Olsen, Kjartan
    [J]. ECOLOGICAL INDICATORS, 2012, 23 : 1 - 8
  • [9] Virtual Scarce Water in China
    Feng, Kuishuang
    Hubacek, Klaus
    Pfister, Stephan
    Yu, Yang
    Sun, Laixiang
    [J]. ENVIRONMENTAL SCIENCE & TECHNOLOGY, 2014, 48 (14) : 7704 - 7713
  • [10] COMPARISON OF BOTTOM-UP AND TOP-DOWN APPROACHES TO CALCULATING THE WATER FOOTPRINTS OF NATIONS
    Feng, Kuishuang
    Chapagain, Ashok
    Suh, Sangwon
    Pfister, Stephan
    Hubacek, Klaus
    [J]. ECONOMIC SYSTEMS RESEARCH, 2011, 23 (04) : 371 - 385