The Weather Research and Forecasting (WRF) model was used to simulate precipitation for three flooding events in Alberta, Canada. A detailed comparison was made between the 48 hour spatial distribution of model rainfall and observations obtained from rainfall gauges. Verification was evaluated in terms of Probability of Detection, False Alarm Ratio, BIAS, and Equitable Threat scores from over 120 observation stations. Evaluation was also performed using the root-mean-squared-error at each model grid box as well as integration over the major river basins of Alberta. Simulations with 15 km grid resolution were compared using five different cumulus parameterization schemes: Explicit, Kain-Fritsch, Betts-Miller-Janjić, Grell-Dévényi and Grell 3D ensembles.The Kain-Fritsch and explicit cumulus parameterization schemes were found to be the most accurate when simulating precipitation across three summer events. The model simulations using the Kain-Fritsch scheme often overestimated precipitation, resulting in higher Probability of Detection values. Combined with low False Alarm Ratio values, this typically yielded the highest Equitable Threat scores. Greater precipitation accuracy was generally observed when the horizontal resolution of the model was increased to 6 km. Model simulations performed without using a cumulus parameterization scheme (i.e. explicit precipitation only) performed with similar accuracy as simulations using a cumulus parameterization scheme at 6 km resolution.