Investigation of Climate Change Effect on Probable Maximum Flood at a Northern Watershed

Thursday, 18 December 2014
Hassan Rouhani and Robert Leconte, University of Sherbrooke, Sherbrooke, QC, Canada
This study aims at exploring the potential climate change effect on the regime of Summer-Fall probable maximum flood (PMF). To achieve this objective, probable maximum precipitation (PMP) was estimated and was used as an input into the SWAT hydrological model. Climate change conditions were modeled by simulating climate for the period from 1961 to 2095. This period was divided into three horizons: recent past (1961-2005), near future (2006-2050) and far future (2051-2095). Climate data are from the 4th version of Canadian Regional Climate Model (CRCM). CRCM was driven by Canadian Global Coupled Model. The climate projection is based on greenhouse gas emission scenario of SRES-A2. Daily Summer-Fall PMP was estimated for each horizon at Moisie watershed in the center of the province of Quebec, Canada. PMP estimation method is derived from moisture maximization method proposed by the World Meteorological Organization. The estimated PMP was then inserted randomly into climate data of corresponding horizon. The random insertion helped to take into account all possible conditions prior to the occurrence of PMP according to the initial soil saturation level. Around 3000 simulations of random insertions were completed for each horizon. Summer-Fall season was divided into three sub-seasons: June-July, August-September and October-November. Under this classification, the potential climate change effect on soil saturation level, extreme rainfall and flood events could be precisely identified. The PMF is influenced by the mean annual rainfall which influence soil saturation level, PMP and change in regime of extreme rainfall events. Results indicated that the June-July and the August-September PMF will increase by 22% when moving from recent past climate to near future and the PMF will not change in the transition from near future to far future. In October-November sub-season, the PMF will be reduced by 16% in near future; and then it will increase to reach almost the same value as the recent past in far future horizon. Finally, it is worth mentioning that based on results of this study, rise or reduction of PMP does not necessarily imply rise or reduction of PMF.