Assessing placement bias of the global river gauge network
2022
Krabbenhoft, Corey | Allen, George | Lin, Peirong | Godsey, Sarah | Allen, Daniel | Burrows, Ryan | Delvecchia, Amanda | Fritz, Ken | Shanafield, Margaret | Burgin, Amy | Zimmer, Margaret | Datry, Thibault | Dodds, Walter | Jones, C. Nathan | Mims, Meryl | Franklin, Catherin | Hammond, John | Zipper, Sam | Ward, Adam | Costigan, Katie | Beck, Hylke | Olden, Julian | University at Buffalo [SUNY] (SUNY Buffalo) ; State University of New York (SUNY) | RiverLy - Fonctionnement des hydrosystèmes (RiverLy) ; Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE) | National Science Foundation (NSF)DEB-17543892207232
International audience
Show more [+] Less [-]English. Hydrologic data collected from river gauges inform critical decisions for allocating water resources, conserving ecosystems and predicting the occurrence of droughts and floods. The current global river gauge network is biased towards large, perennial rivers, and strategic adaptations are needed to capture the full scope of rivers on Earth.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.
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