TY - JOUR
T1 - Underestimation of Historical Terrestrial Water Storage Droughts in Global Water Models
AU - Tiwari, Amar Deep
AU - Pokhrel, Yadu
AU - Felfelani, Farshid
AU - Elkouk, Ahmed
AU - Boulange, Julien
AU - Gosling, Simon N.
AU - Hanasaki, Naota
AU - Koutroulis, Aristeidis
AU - Mishra, Vimal
AU - Schmied, Hannes Müller
AU - Satoh, Yusuke
AU - Ostberg, Sebastian
AU - Stacke, Tobias
AU - Yin, Jiabo
N1 - Publisher Copyright:
© 2025. The Author(s).
PY - 2025/10/16
Y1 - 2025/10/16
N2 - 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.
AB - 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.
KW - GWM
KW - TWS
KW - drought
KW - hydrology
KW - modeling
UR - https://www.scopus.com/pages/publications/105018186794
U2 - 10.1029/2025GL115164
DO - 10.1029/2025GL115164
M3 - Article
AN - SCOPUS:105018186794
SN - 0094-8276
VL - 52
JO - Geophysical Research Letters
JF - Geophysical Research Letters
IS - 19
M1 - e2025GL115164
ER -