Uncertainty sources in flood projections over contrasting hydrometeorological regimes

ABSTRACT

This study evaluates the uncertainty of four components of the hydroclimatic modelling chain on flood projections over 96 basins covering contrasting hydrometeorological regimes located in Canada and Mexico. Two ensembles of climate simulations are considered, a large ensemble of 22 global climate model simulations and a smaller ensemble of three high-resolution regional climate model simulations. The other components are two post-processing techniques, three lumped hydrological models and six probability distributions. These four sources are assessed through a method of variance decomposition applied to six flood indicators over a reference period and two future periods: 1976–2005, 2041–2070 and 2070–2099. Systematic differences are observed between basins with contrasting flood-generating processes. Snow-dominated basins consistently show larger variance contributions from hydrological models, while rain-dominated basins show climate simulations as their dominant source. These results underline the need to consider the variability of each component’s uncertainty contribution and its link to hydroclimatic conditions and dominant processes.

KEYWORDS:

• floods
• uncertainty
• hydrological modelling
• climate modelling
• climate change

Editor A. Castellarin Associate Editor J. Thompson

Editor A. Castellarin Associate Editor J. Thompson

Acknowledgements

The authors thank the Ouranos Consortium on Regional Climatology and Adaptation for the climate simulations provided for this study and their valuable contributions to this work. As well, we thank the Consejo Nacional de Ciencia y Tecnología (CONACYT), the Fonds de recherche du Québec – Nature et technologies (FRQNT) and the Ministère de l’Économie, de la Science et de l’Innovation for partial funding of this project.

Disclosure statement

No potential conflict of interest was reported by the authors.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/02626667.2022.2137415

Additional information

Funding

This work was supported by the Consejo Nacional de Ciencia y Tecnología; Fonds de Recherche du Québec – Nature et Technologies; Hydro-Québec; Consortium Ouranos sur la climatologie régionale et l’adaptation aux changements climatiques; Ministère de l’économie et de l’innovation du Québec; and Fonds Vert Québec.