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

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

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 Urheber:
Kumar, Amit1, Autor
Gosling, Simon N.1, Autor
Johnson, Matthew F.1, Autor
Jones, Matthew D.1, Autor
Zaherpour, Jamal1, Autor
Kumar, Rohini1, Autor
Leng, Guoyong1, Autor
Schmied, Hannes Müller1, Autor
Kupzig, Jenny1, Autor
Breuer, Lutz1, Autor
Hanasaki, Naota1, Autor
Tang, Qiuhong1, Autor
Ostberg, Sebastian2, Autor              
Stacke, Tobias1, Autor
Pokhrel, Yadu1, Autor
Wada, Yoshihide1, Autor
Masaki, Yoshimitsu1, Autor
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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Schlagwörter: Global hydrological models, Catchment hydrological models, Hydrological droughts, Model evaluation, Model validation,ISIMIP
 Zusammenfassung: 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.

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Sprache(n): eng - Englisch
 Datum: 2021-10-142022-04-182022-04-212022-07
 Publikationsstatus: Final veröffentlicht
 Seiten: 11
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: Expertenbegutachtung
 Identifikatoren: DOI: 10.1016/j.advwatres.2022.104212
Organisational keyword: RD2 - Climate Resilience
PIKDOMAIN: RD2 - Climate Resilience
Working Group: Adaptation in Agricultural Systems
MDB-ID: No MDB - stored outside PIK (see DOI)
Research topic keyword: Extremes
Research topic keyword: Freshwater
Regional keyword: Africa
Regional keyword: Asia
Regional keyword: Europe
Regional keyword: North America
Regional keyword: South America
Model / method: LPJmL
Model / method: Model Intercomparison
Model / method: SWIM
OATYPE: Hybrid Open Access
 Art des Abschluß: -

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Titel: Advances in Water Resources
Genre der Quelle: Zeitschrift, SCI, Scopus, p3
 Urheber:
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Ort, Verlag, Ausgabe: -
Seiten: - Band / Heft: 165 Artikelnummer: 104212 Start- / Endseite: - Identifikator: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/1402273
Publisher: Elsevier