DOI: 10.5194/hess-18-4565-2014
Scopus记录号: 2-s2.0-84912567124
论文题名: Complex networks for streamflow dynamics
作者: Sivakumar B ; , Woldemeskel F ; M
刊名: Hydrology and Earth System Sciences
ISSN: 10275606
出版年: 2014
卷: 18, 期: 11 起始页码: 4565
结束页码: 4578
语种: 英语
Scopus关键词: Catchments
; Stream flow
; Clustering coefficient
; Landscape characteristic
; Monitoring stations
; Network-based approach
; Nonlinear interactions
; Spatial and temporal scale
; Streamflow modeling
; Streamflow networks
; Complex networks
; interpolation
; prediction
; spatiotemporal analysis
; streamflow
; United States
英文摘要: Streamflow modeling is an enormously challenging problem, due to the complex and nonlinear interactions between climate inputs and landscape characteristics over a wide range of spatial and temporal scales. A basic idea in streamflow studies is to establish connections that generally exist, but attempts to identify such connections are largely dictated by the problem at hand and the system components in place. While numerous approaches have been proposed in the literature, our understanding of these connections remains far from adequate. The present study introduces the theory of networks, in particular complex networks, to examine the connections in streamflow dynamics, with a particular focus on spatial connections. Monthly streamflow data observed over a period of 52 years from a large network of 639 monitoring stations in the contiguous US are studied. The connections in this streamflow network are examined primarily using the concept of clustering coefficient, which is a measure of local density and quantifies the network's tendency to cluster. The clustering coefficient analysis is performed with several different threshold levels, which are based on correlations in streamflow data between the stations. The clustering coefficient values of the 639 stations are used to obtain important information about the connections in the network and their extent, similarity, and differences between stations/regions, and the influence of thresholds. The relationship of the clustering coefficient with the number of links/actual links in the network and the number of neighbors is also addressed. The results clearly indicate the usefulness of the network-based approach for examining connections in streamflow, with important implications for interpolation and extrapolation, classification of catchments, and predictions in ungaged basins. © 2014 Author(s). Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/78075
Appears in Collections: 气候变化事实与影响
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作者单位: School of Civil and Environmental Engineering, University of New South Wales, Sydney, Australia; Department of Land, Air and Water Resources, University of California, Davis, CA, United States
Recommended Citation:
Sivakumar B,, Woldemeskel F,M. Complex networks for streamflow dynamics[J]. Hydrology and Earth System Sciences,2014-01-01,18(11)