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Data · dataset · 2026

Uncertainty hotspots in global hydrologic modeling: The impact of precipitation and temperature forcings

Listed in National Center for Atmospheric Research

Quantifying hydrologic modeling uncertainties originating from meteorological uncertainties is crucial yet unexplored on the global scale.

Description

This study integrates a novel ensemble meteorological dataset with process-based hydrologic models, assessing the impact of precipitation and temperature uncertainties across approximately three million subbasins globally. We introduce two metrics to identify uncertainty hotspots: one tracing the uncertainty propagation from inputs to model outputs and the other measuring the uncertainty magnitude relative to hydrologic climatology (i.e., ratio between uncertainty and climate average).

Our findings reveal different uncertainty responses across hydrologic variables to the combined precipitation and temperature uncertainties. For routed river streamflow, uncertainty propagation is strong in tropical rain forests and Europe (except the Scandinavian Peninsula) but weak in the deserts, which is partly attributed to the regional differences in baseflow ratios. In contrast, both uncertainty metrics indicate low streamflow uncertainties in cryosphere areas and downstream areas of major rivers.

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The substantial modeling uncertainties observed, particularly in the Southern Hemisphere and less developed regions, underscore the need to improve global spatial meteorological datasets.

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Climate change processes 77%
Provenance · 1 source records, 8 field assertions
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National Center for Atmospheric Researchf69458ae-1153-47af-becc-a3db7fd8095d12 d agoJSON v1
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concepts[field].local:field:earth-environmentalmapping · data ucar educonnector:data_ucar_edu@1.0.0
concepts[field].local:field:ocean-atmosphericmapping · data ucar educonnector:data_ucar_edu@1.0.0
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descriptionsource · data ucar educonnector:data_ucar_edu@1.0.0/notes
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