地理学报 ›› 2020, Vol. 75 ›› Issue (7): 1346-1358.doi: 10.11821/dlxb202007002

• 虚拟水探索 • 上一篇    下一篇

青藏高原地区城乡虚拟水贸易格局与影响因素

孙思奥1(), 王晶2, 戚伟1   

  1. 1. 中国科学院地理科学与资源研究所,北京 100101
    2. 水利部规划计划司,北京 100053
  • 收稿日期:2019-04-02 修回日期:2020-04-27 出版日期:2020-07-25 发布日期:2020-09-25
  • 作者简介:孙思奥(1983-), 女, 湖南津市人, 博士, 副研究员, 主要从事城市水文和水资源管理与政策相关研究。E-mail: suns@igsnrr.ac.cn
  • 基金资助:
    中国科学院战略性先导科技专项(XDA20040401);国家自然科学基金项目(41730645)

Urban-and-rural virtual water trade of Qinghai-Tibet Plateau: Patterns and influencing factors

SUN Siao1(), WANG Jing2, QI Wei1   

  1. 1. Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China
    2. Department of Planning and Programming, Ministry of Water Resources, Beijing 100053, China
  • Received:2019-04-02 Revised:2020-04-27 Online:2020-07-25 Published:2020-09-25
  • Supported by:
    Strategic Priority Research Program of the Chinese Academy of Sciences(XDA20040401);National Natural Science Foundation of China(41730645)

摘要:

青藏高原是亚洲水塔,其水资源与水生态环境保护意义重大。从虚拟水视角,研究青藏高原与外部的水资源贸易关系和影响因素,有助于理解该地区的水资源问题、制定虚拟水贸易策略、优化区域城乡水资源配置、保障亚洲水塔功能。依托2012年中国区域间投入产出表成果,本文测算了青藏高原与中国其他区域之间的虚拟水贸易关系,建立了中国区域城镇与农村地区的虚拟水贸易网络,采用对数平均迪氏指数模型分析了青藏高原对其他区域虚拟水贸易不平衡的影响因素。结果表明,青藏高原向中国其他区域净输出虚拟水2.25亿m3,其中向西南、华北、华中、华东、华南等5个区域净输出虚拟水,从西北和东北2个区域净输入虚拟水。城乡之间虚拟水贸易联系非常紧密,农村地区生产水足迹较高,而城镇地区由于人口密度较高、消费水平较高,是虚拟水最终消费的热点区域,青藏高原农村地区的虚拟水贸易量大于城镇地区的虚拟水贸易量。青藏高原贸易输出结构以农产品为主导,虚拟水净输出12.7亿m3;青藏高原与其他区域贸易存在逆差,贸易量因素导致虚拟水净输入8.6亿m3;用水效率在青藏高原与不同区域虚拟水贸易中的正负效应不一,总体带来青藏高原虚拟水净输入1.8亿m3。未来,应重点通过灌溉节水减少农业水足迹,引导城镇居民向低水足迹生活方式转变,鼓励内地为青藏高原提供物质与技术支援,实行水资源生态补偿政策,以保护青藏高原水资源,促进区域水资源可持续利用。

关键词: 虚拟水, 水足迹, 贸易网络, 青藏高原, 对数平均迪氏指数模型

Abstract:

It is essentially important to protect water resources and water eco-environment in the Qinghai-Tibet Plateau, the Asian water tower. Understanding water transfers through the trade of different products and services (i.e. virtual water transfers) and their influencing factors between Qinghai-Tibet Plateau and external regions can aid in analyzing local water resources problems and making virtual water strategies. Based on the China multi-region input-output table in 2012, this study calculated the virtual water transferred between Qinghai-Tibet Plateau and other regions in China. The virtual water transfer network comprising urban and rural nodes was constructed. Influencing factors that determine net virtual water trade of Qinghai-Tibet Plateau with other regions were analyzed using the Logarithmic mean Divisia index method. The results indicated that Qinghai-Tibet Plateau delivered a total of 0.23 billion m3 net virtual water to other regions in China. It delivered net virtual water to Southwest, North, Central, East and South China, and received net virtual water from Northwest and Northeast China. Intensive virtual water transfers between urban and rural regions were found. In the Qinghai-Tibet Plateau, production-based water footprint was higher in rural areas, whereas consumption-based water footprint was higher in urban areas due to high population density and consumption level. The node strength in rural areas of Qinghai-Tibet Plateau was higher than that in urban areas. In the plateau, the products transferred to other regions were dominated by agricultural products, which led to 1.27 billion m3 of virtual water export. The Qinghai-Tibet Plateau had a trade deficit with other regions, which resulted in 0.86 billion m3 of net virtual water export. Water use efficiency led to 0.18 billion m3 of virtual water export from the plateau. Water management policies were formulated towards sustainable water resources use. Irrigation water conservation needs to be implemented to reduce production-based agricultural water footprint, and urban inhabitants' consumption corresponding to a lower water footprint should be encouraged. In addition, net import of various products and water resources ecological compensation will be beneficial to water resources protection in the Qinghai-Tibet Plateau.

Key words: urban and rural virtual water trade, virtual water transfer network, water footprint, Qinghai-Tibet Plateau, Logarithmic mean Divisia index method