Water Resources Research Report



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The increase in greenhouse gas emissions has had a severe impact on global temperature, and is affecting weather patterns worldwide. With this global climate change, precipitation levels are changing, and in many places are drastically increasing. The need to be able to accurately predict extreme precipitation events is imperative in designing for not only the safety of infrastructure, but also people’s lives. To predict these events, the use of historical data is necessary, along with statistical distributions that are used to fit the data.

In this study, historical data from the London International Airport station has been used, along with 11 different Atmosphere Ocean Global Climate Models (AOGCMs), which are used to predict future climate variables. These models produced a total of 27 different data sets of annual maximum precipitation over a period of 117 years, for storm durations of 1, 2, 6, 12 and 24 hours.

The current Environment Canada recommended distribution is the Gumbel (EV1) distribution, and the current United States distribution is the Log-Pearson type 3 (LP3). This report investigates a third distribution, the Generalized Extreme Value (GEV) distribution, in the context of the Upper Thames River Watershed.

The historical data set and the data sets derived from AOGCMs were used with the GEV, LP3 and EV1 distributions, and the goodness of fit tests were performed to select which was most appropriate distribution. L-Moment Ratio diagrams were also constructed to help establish the most suitable distribution. All results showed that GEV was very appropriate to the Upper Thames River Watershed data, and it was often the favored distribution.

This report shows the need for more studies to be carried out on the GEV distribution, to ensure we are using the most appropriate methods for predicting these extreme precipitation events.

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Department of Civil and Environmental Engineering, The University of Western Ontario


London, Ontario, Canada


Civil and Environmental Engineering


Report no.: 077

The Comparison of GEV, Log-Pearson Type 3 and Gumbel Distributions in the Upper Thames River Watershed under Global Climate Models