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| Titel |
Complex network theory, streamflow, and hydrometric monitoring system design |
| VerfasserIn |
M. J. Halverson, S. W. Fleming |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 19, no. 7 ; Nr. 19, no. 7 (2015-07-31), S.3301-3318 |
| Datensatznummer |
250120773
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| Publikation (Nr.) |
 copernicus.org/hess-19-3301-2015.pdf |
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| Zusammenfassung |
| Network theory is applied to an array of streamflow gauges located in the
Coast Mountains of British Columbia (BC) and Yukon, Canada. The goal of the
analysis is to assess whether insights from this branch of mathematical graph
theory can be meaningfully applied to hydrometric data, and, more
specifically, whether it may help guide decisions concerning stream gauge
placement so that the full complexity of the regional hydrology is
efficiently captured. The streamflow data, when represented as a complex
network, have a global clustering coefficient and average shortest path
length consistent with small-world networks, which are a class of stable and
efficient networks common in nature, but the observed degree distribution did
not clearly indicate a scale-free network. Stability helps ensure that the
network is robust to the loss of nodes; in the context of a streamflow
network, stability is interpreted as insensitivity to station removal at
random. Community structure is also evident in the streamflow network. A
network theoretic community detection algorithm identified separate
communities, each of which appears to be defined by the combination of its
median seasonal flow regime (pluvial, nival, hybrid, or glacial, which in
this region in turn mainly reflects basin elevation) and geographic proximity
to other communities (reflecting shared or different daily meteorological
forcing). Furthermore, betweenness analyses suggest a handful of key stations
which serve as bridges between communities and might
be highly valued. We
propose that an idealized sampling network should sample high-betweenness
stations, small-membership communities which are by definition rare or
undersampled relative to other communities, and index stations having large
numbers of intracommunity links, while retaining some degree of redundancy to
maintain network robustness. |
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