Frequency of floods in a changing climate: a case study from the Red River in Manitoba, Canada

Abstract. Spring flooding in the Red River basin is a recurrent issue in the Province of Manitoba, Canada. There have been a number of flood events in recent years and climate change has been suggested as a potential cause. This paper employs a relatively simple model for predicting changes in the frequency distribution of annual spring peak discharge of the Red River as a response to increased GHG concentrations. A regression model is used to predict spring peak flow from antecedent precipitation in the previous fall, winter snow accumulation, and spring precipitation. Data from the Coupled Model Intercomparison Project – Phase 5 (CMIP5) are used to estimate changes in the predictor variables and this information is then employed to derive flood distributions for future climate conditions. Most climate models predict increased precipitation during winter months but this trend is partly offset by a shorter snow accumulation period and higher winter evaporation rates. The means and medians of an ensemble of 16 climate models do not suggest a particular trend toward more or less frequent floods of the Red River. However, the ensemble range is relatively large, highlighting the difficulties involved in estimating changes in extreme events.