Uncertainties as a Guide for Global Water Model Advancement

ABSTRACT Global water models allow us to explore the terrestrial water cycle in earth‐sized digital laboratories to support science and guide policy. However, these models are still subject to considerable but also reducible uncertainties that can be attributed to mainly three sources: (1) imbalances in data quality and availability across geographical regions and between hydrologic variables, (2) poorly quantified human influence on the water cycle, and (3) difficulties in tailoring process representations to regionally diverse hydrologic systems. New, more accurate, and larger datasets, as well as better accumulated and even enhanced process knowledge, will help to reduce these uncertainties and thus improve model consistency with our perceptions and accuracy given existing observations. This review examines the sources of uncertainty crucial for global water models and proposes actions to mitigate them, thereby providing a roadmap for model advancement. Following this path will yield more consistent and accurate models that are urgently needed to tackle key scientific and societal challenges.

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Publication Details

Journal
Wiley Interdisciplinary Reviews Water
Published
2025-05-01
DOI
https://doi.org/10.1002/wat2.70025
Citations
8
Primary Topic
Hydrology and Watershed Management Studies
Type
article
Field-Weighted Citation Impact
6.54

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article

Uncertainties as a Guide for Global Water Model Advancement

Jafet Andersson, Sebastian Gnann, Sara Nazari, Berit Arheimer et al.
8 citations
Wiley Interdisciplinary Reviews Water
Hydrology and Watershed Management Studies
6.54
article

Uncertainties as a Guide for Global Water Model Advancement

Jafet Andersson, Sebastian Gnann, Sara Nazari, Berit Arheimer, Robert Reinecke, Chaopeng Shen, Andreas Güntner, Stefano Bonetti, Yadu Pokhrel, Thorsten Wagener, Marc F. P. Bierkens, Lina Stein, Nils Moosdorf, Jacob Schewe, Stefan Kollet, Sulagna Mishra, Christel Prudhomme
article en
8 citations

Abstract

ABSTRACT Global water models allow us to explore the terrestrial water cycle in earth‐sized digital laboratories to support science and guide policy. However, these models are still subject to considerable but also reducible uncertainties that can be attributed to mainly three sources: (1) imbalances in data quality and availability across geographical regions and between hydrologic variables, (2) poorly quantified human influence on the water cycle, and (3) difficulties in tailoring process representations to regionally diverse hydrologic systems. New, more accurate, and larger datasets, as well as better accumulated and even enhanced process knowledge, will help to reduce these uncertainties and thus improve model consistency with our perceptions and accuracy given existing observations. This review examines the sources of uncertainty crucial for global water models and proposes actions to mitigate them, thereby providing a roadmap for model advancement. Following this path will yield more consistent and accurate models that are urgently needed to tackle key scientific and societal challenges.

Wiley Interdisciplinary Reviews WaterVol. 12(3)
Swedish Meteorological and Hydrological Institute (SE), Pennsylvania State University (US), World Meteorological Organization (CH), Loughborough University (GB), European Centre for Medium-Range Weather Forecasts (GB), University of Freiburg (DE), University of Potsdam (DE), Utrecht University (NL), Johannes Gutenberg University Mainz (DE), Leibniz Centre for Tropical Marine Research (DE), Leibniz Association (DE), Christian-Albrechts-Universität zu Kiel (DE), Deltares (NL), GFZ Helmholtz Centre for Geosciences (DE), École Polytechnique Fédérale de Lausanne (CH), Potsdam Institute for Climate Impact Research (DE), Michigan State University (US)
National Science Foundation, Alexander von Humboldt-Stiftung, Bundesministerium für Bildung und Forschung, H2020 European Research Council
Openalex Percentile: Top 4%
Hydrology and Watershed Management Studies
6.54
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