Deutsch
 
Datenschutzhinweis Impressum
  DetailsucheBrowse
  1. Datensatz ansehen / 
  2. Datensatz Übersicht

Datensatz

DATENSATZ AKTIONENEXPORT
Zur Ablage hinzufügen
  Lokale TagsFreigabegeschichteDetailsÜbersicht

Freigegeben
Zeitschriftenartikel

Similarities and divergent patterns in hydrologic fluxes and storages simulated by global water models

Urheber*innen

Tiwari,  Amar Deep
External Organizations;

Pokhrel,  Yadu
External Organizations;

Boulange,  Julien
External Organizations;

Burek,  Peter
External Organizations;

Guillaumot,  Luca
External Organizations;

Gosling,  Simon N.
External Organizations;

Grillakis,  Manolis
External Organizations;

Hanasaki,  Naota
External Organizations;

Koutroulis,  Aristeidis
External Organizations;

/persons/resource/sebastian.ostberg

Ostberg,  Sebastian
Potsdam Institute for Climate Impact Research;

Otta,  Kedar
External Organizations;

Schmied,  Hannes Müller
External Organizations;

Satoh,  Yusuke
External Organizations;

Scanlon,  Bridget
External Organizations;

Stacke,  Tobias
External Organizations;

Yokohata,  Tokuta
External Organizations;

Externe Ressourcen
Es sind keine externen Ressourcen hinterlegt
Volltexte (frei zugänglich)

32173oa.pdf
(Preprint), 7MB

Ergänzendes Material (frei zugänglich)
Es sind keine frei zugänglichen Ergänzenden Materialien verfügbar
Zitation

Tiwari, A. D., Pokhrel, Y., Boulange, J., Burek, P., Guillaumot, L., Gosling, S. N., Grillakis, M., Hanasaki, N., Koutroulis, A., Ostberg, S., Otta, K., Schmied, H. M., Satoh, Y., Scanlon, B., Stacke, T., Yokohata, T. (2025): Similarities and divergent patterns in hydrologic fluxes and storages simulated by global water models. - Nature Water, 3, 550-560.
https://doi.org/10.1038/s44221-025-00435-6


Zitierlink: https://publications.pik-potsdam.de/pubman/item/item_32173
Zusammenfassung
Global water models (GWMs) are critical tools for understanding the Earth’s water cycle and water resource management under a changing climate and accelerating human interventions. Although GWMs have been evaluated for hydrologic fluxes (for example, river discharge) and the role of representing human activities, there is a persistent gap in understanding models’ ability to simultaneously reproduce fluxes and storages (for example, terrestrial water storage (TWS)). Here we show that eight state-of-the-art GWMs do not consistently reproduce discharge and TWS with the same efficacy across varied geographic and climatic regions. Furthermore, model performance for discharge deteriorates as human impacts intensify. While a general agreement between simulated and observed TWS trends is found in two-thirds of major global river basins, models tend to underestimate the trends in both directions. Likewise, no single model simulates TWS trends and seasonality accurately and uniformly across major global river basins. Although improvements in capturing basin-averaged TWS trends, spatial distributions and seasonal fluctuations have been achieved compared with previous reports, challenges remain in accurately reproducing both fluxes and storages, owing primarily to inadequate representation of human activities in heavily managed regions. This study underscores critical disparities in GWM performance, emphasizing the need for further model enhancements, which is crucial for improved and more robust hydrologic assessments and predictions under climate change.