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Journal Article

Multi-model evaluation of catchment- and global-scale hydrological model simulations of drought characteristics across eight large river catchments

Authors

Kumar,  Amit
External Organizations;

Gosling,  Simon N.
External Organizations;

Johnson,  Matthew F.
External Organizations;

Jones,  Matthew D.
External Organizations;

Zaherpour,  Jamal
External Organizations;

Kumar,  Rohini
External Organizations;

Leng,  Guoyong
External Organizations;

Schmied,  Hannes Müller
External Organizations;

Kupzig,  Jenny
External Organizations;

Breuer,  Lutz
External Organizations;

Hanasaki,  Naota
External Organizations;

Tang,  Qiuhong
External Organizations;

/persons/resource/sebastian.ostberg

Ostberg,  Sebastian
Potsdam Institute for Climate Impact Research;

Stacke,  Tobias
External Organizations;

Pokhrel,  Yadu
External Organizations;

Wada,  Yoshihide
External Organizations;

Masaki,  Yoshimitsu
External Organizations;

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Fulltext (public)

1-s2.0-S0309170822000847-main.pdf
(Publisher version), 3MB

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Citation

Kumar, A., Gosling, S. N., Johnson, M. F., Jones, M. D., Zaherpour, J., Kumar, R., Leng, G., Schmied, H. M., Kupzig, J., Breuer, L., Hanasaki, N., Tang, Q., Ostberg, S., Stacke, T., Pokhrel, Y., Wada, Y., Masaki, Y. (2022): Multi-model evaluation of catchment- and global-scale hydrological model simulations of drought characteristics across eight large river catchments. - Advances in Water Resources, 165, 104212.
https://doi.org/10.1016/j.advwatres.2022.104212


Cite as: https://publications.pik-potsdam.de/pubman/item/item_27931
Abstract
Although global- and catchment-scale hydrological models are often shown to accurately simulate long-term runoff time-series, far less is known about their suitability for capturing hydrological extremes, such as droughts. Here we evaluated simulations of hydrological droughts from nine catchment scale hydrological models (CHMs) and eight global scale hydrological models (GHMs) for eight large catchments: Upper Amazon, Lena, Upper Mississippi, Upper Niger, Rhine, Tagus, Upper Yangtze and Upper Yellow. The simulations were conducted within the framework of phase 2a of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2a). We evaluated the ability of the CHMs, GHMs and their respective ensemble means (Ens-CHM and Ens-GHM) to simulate observed hydrological droughts of at least one month duration, over 31 years (1971–2001). Hydrological drought events were identified from runoff-deficits and the Standardised Runoff Index (SRI). In all catchments, the CHMs performed relatively better than the GHMs, for simulating monthly runoff-deficits. The number of drought events identified under different drought categories (i.e. SRI values of -1 to -1.49, -1.5 to -1.99, and ≤-2) varied significantly between models. All the models, as well as the two ensemble means, have limited abilities to accurately simulate drought events in all eight catchments, in terms of their occurrence and magnitude. Overall, there are opportunities to improve both CHMs and GHMs for better characterisation of hydrological droughts.