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Journal Article

Underestimation of Historical Terrestrial Water Storage Droughts in Global Water Models

Authors

Tiwari,  Amar Deep
External Organizations;

Pokhrel,  Yadu
External Organizations;

Felfelani,  Farshid
External Organizations;

Elkouk,  Ahmed
External Organizations;

Boulange,  Julien
External Organizations;

Gosling,  Simon N.
External Organizations;

Hanasaki,  Naota
External Organizations;

Koutroulis,  Aristeidis
External Organizations;

Mishra,  Vimal
External Organizations;

Schmied,  Hannes Müller
External Organizations;

Satoh,  Yusuke
External Organizations;

/persons/resource/sebastian.ostberg

Ostberg,  Sebastian       
Potsdam Institute for Climate Impact Research;

Stacke,  Tobias
External Organizations;

Yin,  Jiabo
External Organizations;

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Citation

Tiwari, A. D., Pokhrel, Y., Felfelani, F., Elkouk, A., Boulange, J., Gosling, S. N., Hanasaki, N., Koutroulis, A., Mishra, V., Schmied, H. M., Satoh, Y., Ostberg, S., Stacke, T., Yin, J. (2025): Underestimation of Historical Terrestrial Water Storage Droughts in Global Water Models. - Geophysical Research Letters, 52, 19, e2025GL115164.
https://doi.org/10.1029/2025GL115164


Cite as: https://publications.pik-potsdam.de/pubman/item/item_33129
Abstract
Enhanced drought modeling is crucial for realistic prediction and effective management of water resources, especially with climate change anticipated to exacerbate drought frequency and severity. Global water models (GWMs) simulate historical and future terrestrial water storage (TWS) with continuous spatial and temporal coverage. However, a global evaluation of TWS simulations by GWMs focused on drought is lacking. Here we evaluate, for the first time, GWMs' capability to represent TWS droughts by comparing simulations with Gravity Recovery and Climate Experiment satellite data. We find notable underestimation of drought severity and coverage by GWMs, across diverse regions, including North America, South America, Africa, and Northern Asia. When examined without trend removal, the underestimation of TWS droughts is more pronounced in recent years (2016–2019) compared to 2002–2015, especially in northern latitudes. This underrepresentation highlights the necessity to improve GWMs to simulate TWS droughts. Our results imply that previously reported future TWS projections could have underestimated droughts.