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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
  • , Margaret A. Zimmer
  • , Thibault Datry
  • , Walter K. Dodds
  • , C. Nathan Jones
  • , Meryl C. Mims
  • , Catherin Franklin
  • , John C. Hammond
  • , Sam Zipper
  • , Adam S. Ward
  • , Katie H. Costigan
  • Hylke E. Beck, Julian D. Olden
  • Texas A&M University
  • Peking University
  • Idaho State University
  • Pennsylvania State University
  • University of Melbourne
  • Duke University
  • United States Environmental Protection Agency
  • Flinders University
  • University of Kansas
  • University of California at Santa Cruz
  • INRAE
  • Kansas State University
  • University of Alabama
  • Virginia Polytechnic Institute and State University
  • U.S. Geological Survey MD-DE-DC Water Science Center
  • Indiana University Bloomington
  • European Commission Joint Research Centre
  • University of Washington
  • Swedish University of Agricultural Sciences

Research output: Contribution to journalArticlepeer-review

173 Scopus citations

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.

Original languageEnglish
Pages (from-to)586-592
Number of pages7
JournalNature Sustainability
Volume5
Issue number7
DOIs
StatePublished - Jul 2022

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