ArticleScientific reports2019
Critical Nodes in River Networks.
Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Effects of pattern dynamics on carbon storage capacity in the Qinghai-Tibetan Plateau from 1980 to 2020.Scientific reports · 2025Article
- Controllability and heterogeneity of river networks using spectral graph theory approach.Scientific reports · 2025Article
- A rapid assessment methodology for quantifying and visualizing functional landscape connectivity.Frontiers in conservation science · 2024Article
- Generation and application of river network analogues for use in ecology and evolution.Ecology and evolution · 2020Article
- Quantification of node importance in rain gauge network: influence of temporal resolution and rain gauge density.Scientific reports · 2020Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
River drainage networks are important landscape features that have been studied for several decades from a range of geomorphological and hydrological perspectives. However, identifying the most vital (critical) nodes on river networks and analyzing their relationships with geomorphic and climatic properties have not yet been extensively addressed in the literature. In this study, we use an algorithm that determines the set of critical nodes whose removal results in maximum network fragmentation and apply it to various topologies of simulated and natural river networks. Specifically, we consider simulated river networks obtained from optimal channel network (OCN) approach as well as extracted networks from several natural basins across the United States. Our results indicate a power-law relationship between the number of connected node pairs in the remaining network and the number of removed critical nodes. We also investigate the characteristics of sub-basins resulted from the removal of critical nodes and compare them with those of central nodes (in the context of betweenness centrality) for both natural basins and OCNs with varying energy exponent γ to understand vulnerability and resilience of river networks under potential external disruptions.
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Registered trials
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