|dc.description.abstract||As one of the most destructive natural hazards, floods have a strong and devastating influence on various aspects of human society and the environment. Damages from floods can include property loss, destruction of infrastructure, loss of life, social and economic disruption from evacuations, and environmental degradation. Floods are inevitable natural events but their impacts on people and the environment can be reduced by putting mitigation measures in place. Underestimation of flood discharges will lead to increase flood risk, while overestimation will lead to unnecessary increased construction costs.
Effective mitigation measures require a solid understanding of the frequency of floods. How frequently a flood event of a given magnitude may be expected to occur, known as frequency analysis, is of great importance. However, estimation of these frequencies is difficult since extreme events are by definition rare and the length of the recorded data for these events is often short. Thus, flood frequency analysis is essentially a problem of information scarcity. Methods of incorporating related samples of data to reach more accurate conclusions, known as regional (or pooled) frequency analysis, are well established and documented in the literature. In Canada, there has been limited research into a standard and formalized procedure for flood frequency analysis. There are no national guidelines for flood frequency analysis in Canada, unlike in other jurisdictions such as USA, UK, and Australia, and there is thus a lack of a standardized approach for flood quantile estimation.
The research in this thesis investigates different approaches in flood frequency analysis to improve flood quantile estimation. This research develops and applies a standardized approach to estimate extreme flood quantiles in Canada. In the context of pooled flood frequency analysis, this work investigates different approaches for flood quantile estimation that consider annual maximum flow series and also peaks-over-threshold series, including techniques to extract events exceeding the threshold. Changes in extreme flow magnitude and frequency over time are also explored in a multi-temporal and multi-faceted approach.
A pooling technique in the context of super regions was developed that improved quantile estimation in comparison to more traditional grouping methods. This work has led to the development of a semi-automated threshold selection method instrumental in extracting peaks-over-threshold series for a large dataset of gauging stations. The semi-automated threshold selection method was employed in developing an effective pooling method that promotes using peaks-over-threshold series in flood frequency analysis. The proposed method generally provided better quantile estimates than those obtained by using annual maximum series. The thesis also investigates the nature of changes in flooding events in Canada and studies the characteristics of the observed temporal trends in the flow series.||en