Evaluating the impact of rainfall–runoff model structural uncertainty on the hydrological rating of regional climate model simulations

Autor: Hamouda Dakhlaoui, Khalil Djebbi
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Journal of Water and Climate Change, Vol 12, Iss 8, Pp 3820-3838 (2021)
Druh dokumentu: article
ISSN: 2040-2244
2408-9354
DOI: 10.2166/wcc.2021.004
Popis: We propose to evaluate the impact of rainfall–runoff model (RRM) structural uncertainty on climate model evaluation, performed within a process-oriented framework using the RRM. Structural uncertainty is assessed with an ensemble approach using three conceptual RRMs (HBV, IHACRES and GR4J). We evaluate daily precipitation and temperature from 11 regional climate models forced by five general circulation models (GCM–RCMs), issued from EURO-CORDEX. The assessment was performed over the reference period (1970–2000) for five catchments situated in northern Tunisia. Seventeen discharge performance indexes were used to explore the representation of hydrological processes. The three RRMs performed well over the reference period, with Nash–Sutcliffe efficiency values ranging from 0.70 to 0.90 and bias close to 0%. The ranking of GCM–RCMs according to hydrological performance indexes is more meaningful before the bias correction, which considerably reduces the differences between GCM- and RCM-driven hydrological simulations. Our results illustrate a strong similarity between the different RRMs in terms of raw GCM–RCM performances over the reference period for the majority of performance indexes, in spite of their different model structures. This proves that the structural uncertainty induced by RRMs does not affect GCM–RCM evaluation and ranking, which contributes to consolidate the RRM as a standard tool for climate model evaluation. HIGHLIGHTS Structural uncertainty induced using rainfall–runoff models does not affect climate model evaluation and ranking performed using hydrological modelling.; Importance of considering a wide set of hydrological performance indexes to evaluate climate model performance.; Climate models that rank well on high-flow performance indexes rank poorly on low-flow performance indexes and vice versa.;
Databáze: Directory of Open Access Journals
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