Peak-over-threshold flood frequency analysis of streamflow series for insular Newfoundland
In this thesis, regional models for the prediction of flood quantiles for streams on the island of Newfoundland are developed using historical streamflow data which has been subject to peak-over-threshold analysis. The Peak-Over-Threshold method of flood frequency analysis allows extraction of more...
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| Format: | Thesis |
| Language: | English |
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Memorial University of Newfoundland
2001
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| Online Access: | https://research.library.mun.ca/6605/ https://research.library.mun.ca/6605/1/KennethTaylor.pdf https://research.library.mun.ca/6605/3/KennethTaylor.pdf |
| Summary: | In this thesis, regional models for the prediction of flood quantiles for streams on the island of Newfoundland are developed using historical streamflow data which has been subject to peak-over-threshold analysis. The Peak-Over-Threshold method of flood frequency analysis allows extraction of more relevant data from a historical flow series than would be available using the conventional annual maximum flow method. As a result, the peak-over-threshold method is of particular interest in regions where data on streamflows is limited. This is the case in Newfoundland. -- Streamflow series from 63 rivers on the island of Newfoundland are considered. This data is modelled using a Poisson arrival process and the Exponential and Pareto magnitude distributions. Results from single-station peak-over-threshold analysis are compared to those obtained from the annual maxima series modelled using the 3-Parameter Lognormal and Generalized Extreme Value distributions. The island is divided into hydrologically homogeneous regions. Hydrologically homogeneous regions are defined as geographic areas in which flood flows are identically distributed except for scale. Regional index flood estimators are developed using the data generated from the peak-over-threshold approach. -- For the quantile estimates generated for the 63 data series analysed, there is no statistically significant difference between the central position of the results of the 3-Parameter Lognormal, Generalized Extreme Value, Poisson-Exponential, and Poisson-Pareto models. Model error for the single station analysis is tested using a bootstrap approach. For the standard error of quantile estimates generated by resampling, the Poisson-Exponential Distribution model exhibited comparable standard error for lower quantiles and lower standard error for higher quantiles. Because of this, the Poisson-Exponential model was determined to be the most robust for a variety of quantiles. Although the Poisson-Pareto distribution is more flexible, it appears to be inferior to the ... |
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