Temporal Characteristics and Spatial Homogeneity of Virtual Water Trade: A Complex Network Analysis
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International trade of commodities causes an international water flow in virtual form. This study focuses on the virtual water flow related to international crop trade. We build complex networks of virtual water trade (Virtual Water Trade Networks, VWTNs hereafter) with annual data of trade and its virtual water content from 1986 to 2013 among all countries. By analyzing the temporal characteristics and spatial homogeneity of the VWTNs, we find that trade networks display a feature of scale-free. This suggests those core export and import countries play dominant roles in international virtual water flows. However, the structure of the VWTN becomes more heterogeneous with time, indicating that virtual water trade has been getting more globalized. By spatially recoding the trade volumes and using detrended fluctuation analysis, this study finds that geographical distance becomes less binding in international virtual water trades. Other important findings from our VWTNs analysis include that virtual water trade patterns remain relative stable within trading groups and that geopolitical, political, and economic environments can significantly influence world virtual water trade flows. This study provides an understanding of the international water trade and its relationship with the macro social and economical conditions at the global scale. Its method thus can be applied to analyze the temporal and spatial dynamics of other networks with directed trade flow.
KeywordsVirtual water International trade network Complex network Agriculture trade Spatial relativity
Research is supported by the National Natural Science Foundation of China [No. 71673116], Natural Science Foundation of Jiangsu Province [No. SBK2015021674], and the Humanistic and Social Science Foundation from Ministry of Education of China [Grant 16YJAZH007].
Compliance with Ethical Standards
Conflict of interests
The authors declare that they have no conflict of interest.
- Blondel V D, Guillaume J L, Lambiotte R (2008) Fast unfolding of communities in large networks. J Stat Mech: Theory E 10008Google Scholar
- Dalin C, Konar M, Hanasaki N, Rinaldo A, Rodriguez-Iturbe I (2012a) Evolution of the global virtual water trade network. PNAS 109(16):5989–5994Google Scholar
- Dalin C, Suweis S, Konar M, Hanasaki N, Rodriguez-Iturbe I (2012b) Modeling past and future structure of the global virtual water trade network. Geophys Res Lett 39(24):0094–8276Google Scholar
- Debaere P (2014) The global economcis of water: Is water a source of comparative advantage? Cepr Discussion Papers 6(2):32–48Google Scholar
- Fred AL, Jain AK (2003) Robust data clustering. In: Proceedings of the IEEE computer society conference on computer vision and pattern recognition. IEEE Computer Society, Los Alamitos, pp 128–133Google Scholar
- Goswami P, Nishad S N (2015) Virtual water trade and time scales for loss of water sustainability: A comparative regional analysis. Sci Rep 5:930Google Scholar
- Hoekstra A Y (2003) Virtual water trade between nations: a global mechanism affecting regional water systems. IGBP Global Change News Letter 54:2–4Google Scholar
- Mekonnen M, Hoekstra A (2010) The green blue and grey water footprint of farm animals and animal products. UNESCO-IHE Institute for Water Education, The NetherlandsGoogle Scholar
- Mekonnen M, Hoekstra A (2011) National water footprint accounts: the green blue and grey water footprint of production and consumption. UNESCO-IHE Institute for Water Education, The NetherlandsGoogle Scholar
- Niu S, Jin F, Liu Y (2004) Virtual water method and application in water resources trade. J North China Inst Technol 25(6):479–481. (in Chinese)Google Scholar
- Sadek A E (2011) Virtual water: an effective mechanism for integrated water resource management. Agric Sci 2:248–261Google Scholar
- Sartori M, Schiavo S (2014) Virtual water trade and country vulnerability: A network perspective. Iefe Working Papers 69(35):521–544Google Scholar