Underestimation of Historical Terrestrial Water Storage Droughts in Global 
Water Models

Tiwari, Amar Deep; Pokhrel, Yadu; Felfelani, Farshid; Elkouk, Ahmed; Boulange, Julien; Gosling, Simon N.; Hanasaki, Naota; Koutroulis, Aristeidis; Mishra, Vimal; Schmied, Hannes Müller; Satoh, Yusuke; Ostberg, Sebastian; Stacke, Tobias; Yin, Jiabo

doi:10.1029/2025GL115164

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Underestimation of Historical Terrestrial Water Storage Droughts in Global Water Models

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Tiwari, Amar Deep
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Pokhrel, Yadu
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Felfelani, Farshid
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Elkouk, Ahmed
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Boulange, Julien
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Gosling, Simon N.
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Hanasaki, Naota
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Koutroulis, Aristeidis
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Mishra, Vimal
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Schmied, Hannes Müller
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Satoh, Yusuke
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/persons/resource/sebastian.ostberg

Ostberg, Sebastian
Potsdam Institute for Climate Impact Research;

Stacke, Tobias
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Yin, Jiabo
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Geophysical Research Letters - 2025 - Tiwari - Underestimation of Historical Terrestrial Water Storage Droughts in Global.pdf
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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

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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.