Flood Risk and Vulnerability Analysis Project - Atlantic Climate ...

Development of Projected Intensity-Duration-Frequency Curves
for Corner Brook and Goulds/Petty Harbour, Newfoundland May 16, 2012
would affect the ―weight‖ of the tail, which is of the most interest in modeling extreme
values. The strength of predictors was evaluated to condition the shape parameter of
the Frechet distribution explicitly, but no variables showed appreciable strength. This
may be because there are not a sufficiently large number of annual values to derive a
significant relationship. Accordingly, the Gumbel distribution was adopted.
The GEV models were fitted using the extRemes package (http://cran.rproject.org/web/packages/extRemes/extRemes.pdf)
in the statistical package ―R‖
(http://www.r-project.org/). To allow for possible seasonal shifts in extreme event
occurrence, seasonal models were fit for each storm duration. In the seasonal model
fitting process, all predictor data across May to October were fit against all the data for
each individual storm duration. For each duration, models for three principal predictors
were evaluated: average precipitation, average temperature and the product of average
temperature and average precipitation. For each duration, models based on different
predictors were accepted based on statistical significance at a criterion of 0.05 and the
best model was selected based on the Akaike Information Criterion (AIC) (explained in
Towler, et al., 2010; referenced from Akaike 1974).
For the 9 different durations, statistically significant models were found for each station.
Of these, the best predictor for 5 of the models was total monthly precipitation, for 11
models the best predictor was the product of monthly precipitation and temperature, and
for the remaining 2 models the best predictor was average monthly temperature. The
final model predictors are provided in Appendix A. The parameter selected as the best
predictor for each of the month/duration combinations is shown in Table 4-3.
AMEC Environment & Infrastructure 22