PROBABILISTIC ANALYSIS OF SUMMER DAILY RAINFALL FOR THE MONTREAL REGION

A probabilistic analysis is carried out to find a parsimonious model for adequately describing the distribution of daily rainfall amounts. The analysis involves fitting four probability models with various degrees of complexity to rainfall data observed at nine raingage stations in the Montreal region. The four distributions considered are: single-parameter exponential; two-parameter gamma and Weibull; and three-parameter mixed exponential. Parameters for each model are estimated by the method of maximum likelihood. For the nine stations studied, based on a graphical comparison and on the basis of an objective model identification (the chi-square and Akaike information criteria), the mixed exponential was found to be the best model. The Weibull and gamma ranked second and third, respectively, leaving the exponential as the worst model.Keywords: Rainfall, Exponential distribution, Gamma distribution, Weibull distribution, Mixed exponential distribution, Chi-square test, Akaike information criterion, Likeli...

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