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

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