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This study aims to analyze the characteristics of global virtual water trade (GVWT), such as the connectivity of each trader, vulnerable importers, and influential countries, using degree and eigenvector centrality during the period 2006–2010. The degree centrality was used to measure the connectivity, and eigenvector centrality was used to measure the influence on the entire GVWT network. Mexico, Egypt, China, the Republic of Korea, and Japan were classified as vulnerable importers, because they imported large quantities of virtual water with low connectivity. In particular, Egypt had a\ud15.3 Gm<sup>3</sup> year<sup>−1</sup> blue water saving effect through GVWT: the vulnerable structure could cause a water shortage problem for the importer. The entire GVWT network could be changed by a few countries, termed\ud"influential traders". We used eigenvector centrality to identify those\udinfluential traders. In GVWT for food crops, the USA, Russian Federation,\udThailand, and Canada had high eigenvector centrality with large volumes of\udgreen water trade. In the case of blue water trade, western Asia, Pakistan,\udand India had high eigenvector centrality. For feed crops, the green water\udtrade in the USA, Brazil, and Argentina was the most influential. However,\udArgentina and Pakistan used high proportions of internal water resources for\udvirtual water export (32.9 and 25.1 %); thus other traders should\udcarefully consider water resource management in these exporters

Analysis of the characteristics of the global virtual water trade network using degree and eigenvector centrality, with a focus on food and feed crops