High Influence: Identifying and Ranking Stability, Topological Significance, and Redundancies in Water Resource Networks
Leah Meeks, David Ezechiel Rosenberg · Journal of Water Resources Planning and Management · 2017
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.