Evidence map›Paper›PMID 31371735›Full record

ArticleScientific reports2019

Critical Nodes in River Networks.

Shiblu Sarker, Alexander Veremyev, Vladimir Boginski, Arvind Singh

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Shiblu SarkerDepartment of Civil, Environmental and Construction Engineering, University of Central Florida, Orlando, Florida, 32816, USA.
Alexander VeremyevDepartment of Industrial Engineering and Management Systems, University of Central Florida, Orlando, Florida, 32816, USA.
Vladimir BoginskiDepartment of Industrial Engineering and Management Systems, University of Central Florida, Orlando, Florida, 32816, USA.
Arvind SinghDepartment of Civil, Environmental and Construction Engineering, University of Central Florida, Orlando, Florida, 32816, USA. Arvind.Singh@ucf.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Identifiers

PMID31371735
PMCPMC6672004

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.