High Influence: Identifying and Ranking Stability, Topological Significance, and Redundancies in Water Resource Networks
Publication: Journal of Water Resources Planning and Management
Volume 143, Issue 6
Abstract
Modeling water resources networks is often input-intensive because of network size and complexity. This paper introduces a ranking automation for networks (RANK) tool that weights node connections based on flow capacity and direction and that automates the process to rank nodes that are stable, topologically significant, and redundant. Application to the 55-node, 73-link lower Bear River water system that stretches from southern Idaho to the Great Salt Lake, Utah shows that stable nodes do not depend on other nodes and are typically middle junctions; unstable nodes are located downstream. The most topologically significant nodes make other nodes unstable when added or removed, and they occur throughout the network. The most redundant node pairs have few but identical connections. Results can help water system modelers and planners identify and prioritize locations to (1) transfer water; (2) build, expand, remove, or abandon plans for dams; (3) adopt conservation measures; (4) develop alternative supplies; (5) monitor flows; and (6) protect environmental features. Network spatial resolution, link direction, and data used to weight links influence RANK results.
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Acknowledgments
This research was funded by Utah Mineral Lease funds. The authors thank the several anonymous reviewers for constructive feedback on earlier drafts.
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Information & Authors
Information
Published In
Journal of Water Resources Planning and Management
Volume 143 • Issue 6 • June 2017
Copyright
©2017 American Society of Civil Engineers.
History
Received: Aug 19, 2014
Accepted: Nov 2, 2016
Published online: Feb 16, 2017
Published in print: Jun 1, 2017
Discussion open until: Jul 16, 2017
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