Evidence map›Paper›PMID 36213515›Full record

ArticleNature sustainability2022

Assessing placement bias of the global river gauge network.

Corey A Krabbenhoft, George H Allen, Peirong Lin, Sarah E Godsey, Daniel C Allen, Ryan M Burrows, Amanda G DelVecchia, Ken M Fritz, Margaret Shanafield, Amy J Burgin and 12 more

Open access · bronzeAbstract read
In one paragraph

Article in Nature sustainability, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
51.7field-weighted citation impact, top 1% of its field
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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

17 citing papers in PubMed, 204 citations in OpenAlex.

  1. Article
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  6. Challenges and opportunities of ML and explainable AI in large-sample hydrology.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2025
    Article
  7. Article
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  11. Non-perennial segments in river networks.Nature reviews. Earth & environment · 2023
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  12. Article
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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

22 authors at 19 institutions in 6 countries.

Corey A KrabbenhoftDepartment of Biological Sciences and Research and Education in Energy, Environment and Water (RENEW) Institute, University at Buffalo, Buffalo, NY, USA.
George H AllenDepartment of Geography, Texas A&M University, College Station, TX, USA.
Peirong LinInstitute of Remote Sensing and GIS, School of Earth and Space Sciences, Peking University, Beijing, China.
Sarah E GodseyDepartment of Geosciences, Idaho State University, Pocatello, ID, USA.
Daniel C AllenDepartment of Ecosystem Science and Management, The Pennsylvania State University, University Park, PA, USA.
Ryan M BurrowsSchool of Ecosystem and Forest Sciences, The University of Melbourne, Burnley, Victoria, Australia.
Amanda G DelVecchiaDepartment of Biology, Duke University, Durham, NC, USA.
Ken M FritzOffice of Research and Development, US Environmental Protection Agency, Cincinnati, OH, USA.
Margaret ShanafieldNational Centre for Groundwater Research and Training, College of Science and Engineering, Flinders University, Bedford Park, South Australia, Australia.
Amy J BurginKansas Biological Survey-Center for Ecological Research, Environmental Studies Program, and Department of Ecology & Evolutionary Biology, University of Kansas, Lawrence, KS, USA.
Margaret A ZimmerDepartment of Earth and Planetary Sciences, University of California, Santa Cruz, CA, USA.
Thibault DatryINRAE, UR Riverly, Centre Lyon-Grenoble Auvergne-Rhône-Alpes, Villeurbanne, France.
Walter K DoddsDivision of Biology, Kansas State University, Manhattan, KS, USA.
C Nathan JonesBiological Sciences, University of Alabama, Tuscaloosa, AL, USA.
Meryl C MimsDepartment of Biological Sciences, Virginia Tech, Blacksburg, VA, USA.
Catherin FranklinDepartment of Geography, Texas A&M University, College Station, TX, USA.
John C HammondUS Geological Survey MD-DE-DC Water Science Center, Catonsville, MD, USA.
Sam ZipperKansas Geological Survey, University of Kansas, Lawrence, KS, USA.
Adam S WardO'Neill School of Public and Environmental Affairs, Indiana University, Bloomington, IN, USA.
Katie H CostiganBiological Sciences, University of Alabama, Tuscaloosa, AL, USA.
Hylke E BeckJoint Research Centre of the European Commission, Ispra, Italy.
Julian D OldenSchool of Aquatic and Fishery Sciences, University of Washington, Seattle, WA, USA.
Texas A&M University · USUnited States Geological Survey · USUniversity of Alabama · USDuke University · USEnvironmental Protection Agency · USFlinders University · AUIdaho State University · USIndiana University Bloomington · USInstitut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement · FRJoint Research Centre · ITKansas State University · USPeking University · CNPennsylvania State University · USThe University of Melbourne · AUUniversity at Buffalo, State University of New York · USUniversity of California, Santa Cruz · USUniversity of Kansas · USUniversity of Washington · USVirginia Tech · US

Funding

Intramural EPA EPA999999
6 · The paper itself

Abstract

Knowing where and when rivers flow is paramount to managing freshwater ecosystems. Yet stream gauging stations are distributed sparsely across rivers globally and may not capture the diversity of fluvial network properties and anthropogenic influences. Here we evaluate the placement bias of a global stream gauge dataset on its representation of socioecological, hydrologic, climatic and physiographic diversity of rivers. We find that gauges are located disproportionally in large, perennial rivers draining more human-occupied watersheds. Gauges are sparsely distributed in protected areas and rivers characterized by non-perennial flow regimes, both of which are critical to freshwater conservation and water security concerns. Disparities between the geography of the global gauging network and the broad diversity of streams and rivers weakens our ability to understand critical hydrologic processes and make informed water-management and policy decisions. Our findings underscore the need to address current gauge placement biases by investing in and prioritizing the installation of new gauging stations, embracing alternative water-monitoring strategies, advancing innovation in hydrologic modelling, and increasing accessibility of local and regional gauging data to support human responses to water challenges, both today and in the future.

Identifiers

PMID36213515
PMCPMC9534037
OpenAlexW4224442013

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.