Articles | Volume 20, issue 10
https://doi.org/10.5194/hess-20-4223-2016
https://doi.org/10.5194/hess-20-4223-2016
Research article
 | 
18 Oct 2016
Research article |  | 18 Oct 2016

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

Sang-Hyun Lee, Rabi H. Mohtar, Jin-Yong Choi, and Seung-Hwan Yoo

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
ED: Reconsider after major revisions (14 Aug 2016) by Lixin Wang
AR by Sanghyun Lee on behalf of the Authors (22 Aug 2016)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (23 Aug 2016) by Lixin Wang
RR by Anonymous Referee #1 (24 Aug 2016)
RR by Anonymous Referee #2 (18 Sep 2016)
ED: Publish as is (19 Sep 2016) by Lixin Wang
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Short summary
Virtual water trade (VWT) embedded in crop trade is an important component of water management. Vulnerable importers in VWT were classified through connectivity and volume of VWT using degree centrality of a VWT network. Influential traders on entire VWT were classified through eigenvector centrality of a VWT network.