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Development of a methodology to evaluate probable maximum precipitation (PMP) under changing climate conditions: Application to southern Quebec, Canada


Rousseau, Alain N; Klein, Iris M; Freudiger, Daphné; Gagnon, Patrick; Frigon, Anne; Ratté-Fortin, Claudie (2014). Development of a methodology to evaluate probable maximum precipitation (PMP) under changing climate conditions: Application to southern Quebec, Canada. Journal of Hydrology, 519:3094-3109.

Abstract

Climate change (CC) needs to be accounted for in the estimation of probable maximum floods (PMFs). However, there does not exist a unique way to estimate PMFs and, furthermore the challenge in estimating them is that they should neither be underestimated for safety reasons nor overestimated for economical ones. By estimating PMFs without accounting for CC, the risk of underestimation could be high for Quebec, Canada, since future climate simulations indicate that in all likelihood extreme precipitation events will intensify. In this paper, simulation outputs from the Canadian Regional Climate Model (CRCM) are used to develop a methodology to estimate probable maximum precipitations (PMPs) while accounting for changing climate conditions for the southern region of the Province of Quebec, Canada. The Kénogami and Yamaska watersheds are herein of particular interest, since dam failures could lead to major downstream impacts. Precipitable water (w) represents one of the key variables in the estimation process of PMPs. Results of stationary tests indicate that CC will not only affect precipitation and temperature but also the monthly maximum precipitable water, wmax, and the ensuing maximization ratio used for the estimation of PMPs. An up-to-date computational method is developed to maximize w using a non-stationary
frequency analysis, and then calculate the maximization ratios. The ratios estimated this way are deemed reliable since they rarely exceed threshold values set for Quebec, and, therefore, provide consistent PMP estimates. The results show an overall significant increase of the PMPs throughout the current century compared to the recent past.

Abstract

Climate change (CC) needs to be accounted for in the estimation of probable maximum floods (PMFs). However, there does not exist a unique way to estimate PMFs and, furthermore the challenge in estimating them is that they should neither be underestimated for safety reasons nor overestimated for economical ones. By estimating PMFs without accounting for CC, the risk of underestimation could be high for Quebec, Canada, since future climate simulations indicate that in all likelihood extreme precipitation events will intensify. In this paper, simulation outputs from the Canadian Regional Climate Model (CRCM) are used to develop a methodology to estimate probable maximum precipitations (PMPs) while accounting for changing climate conditions for the southern region of the Province of Quebec, Canada. The Kénogami and Yamaska watersheds are herein of particular interest, since dam failures could lead to major downstream impacts. Precipitable water (w) represents one of the key variables in the estimation process of PMPs. Results of stationary tests indicate that CC will not only affect precipitation and temperature but also the monthly maximum precipitable water, wmax, and the ensuing maximization ratio used for the estimation of PMPs. An up-to-date computational method is developed to maximize w using a non-stationary
frequency analysis, and then calculate the maximization ratios. The ratios estimated this way are deemed reliable since they rarely exceed threshold values set for Quebec, and, therefore, provide consistent PMP estimates. The results show an overall significant increase of the PMPs throughout the current century compared to the recent past.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:07 Faculty of Science > Institute of Geography
Dewey Decimal Classification:910 Geography & travel
Scopus Subject Areas:Physical Sciences > Water Science and Technology
Language:English
Date:2014
Deposited On:15 Mar 2019 11:10
Last Modified:31 Jul 2020 01:48
Publisher:Elsevier
ISSN:0022-1694
OA Status:Closed
Publisher DOI:https://doi.org/10.1016/j.jhydrol.2014.10.053

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