Articles | Volume 18, issue 11
https://doi.org/10.5194/hess-18-4565-2014
https://doi.org/10.5194/hess-18-4565-2014
Research article
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20 Nov 2014
Research article | Highlight paper |  | 20 Nov 2014

Complex networks for streamflow dynamics

B. Sivakumar and F. M. Woldemeskel

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ED: Publish as is (14 Oct 2014) by Francesco Laio
AR by Bellie Sivakumar on behalf of the Authors (07 Nov 2014)  Manuscript 
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Short summary
This study introduces the theory of networks, and in particular complex networks, to examine connections in streamflow dynamics. Monthly streamflow data from a network of 639 stations in the United States are studied. The connections are examined primarily using the concept of clustering coefficient, which quantifies the network’s tendency to cluster. The clustering coefficient analysis is performed with several different threshold levels based on correlations in streamflow between the stations.