Frequency analysis for predicting 1% annual maximum water levels along Florida coast, US


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Abstract

In the Coastal Flood Insurance Study by the Federal Emergency Management Agency (FEMA, 2005), 1% annual maximum coastal water levels are used in coastal flood hazard mitigation and engineering design in coastal areas of USA. In this study, a frequency analysis method has been developed to provide more accurate predictions of 1% annual maximum water levels for the Florida coast waters. Using 82 and 94 years of annual maximum water level data at Pensacola and Fernandina, performances of traditional frequency analysis methods, including advanced method of Generalized Extreme Value distribution method, have been evaluated. Comparison with observations of annual maximum water levels with 83 and 95 years of return periods indicate that traditional methods are unable to provide satisfactory predictions of 1% annual maximum water levels to account for hurricane-induced extreme water levels. Based on the characteristics of annual maximum water level distribution of Pensacola and Fernandina stations, a new probability distribution method has been developed in this study. Comparison with observations indicates that the method presented in this study significantly improves the accuracy of predictions of 1% annual maximum water levels. For Fernandina station, predictions of extreme water level match well with the general trend of observations. With a correlation coefficient of 0.98, the error for the maximum observed extreme water level of 3.11 m (National Geodetic Vertical Datum) with 95 years of return period is 0.92%. For Pensacola station, the prediction error for the maximum observed extreme water level with a return period of 83 years is 5.5%, with a correlation value of 0.98. The frequency analysis has also been reasonably compared to the more costly Monte Carlo simulation method.

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