Analysis and Predictions of Extreme Coastal Water Levels

• Other Authors: Xu, Sudong (authoraut), Huang, Wenrui (professor directing dissertation), Niu, Xufeng (outside committee member), Nnaji, Soronnadi (committee member), Abichou, Tarek (committee member), Department of Civil and Environmental Engineering (degree granting department), Florida State University (degree granting institution)
• Format: Text
• Language: English
• Published: Tallahassee, Florida: Florida State University 2007
• Subjects: Civil engineering; Environmental engineering; Pacific; Northeast Atlantic
• Online Access: https://diginole.lib.fsu.edu/islandora/object/fsu%3A168560/datastream/TN/view/Analysis%20and%20Predictions%20of%20Extreme%20Coastal%20Water%20Levels.jpg

Understanding the characteristics of probability distribution of extreme water levels is important for coastal flood mitigation and engineering design. In this study, frequency analysis has been conducted to investigate probability distributions along the coast of the U.S. by using three-parameter General Extreme Value (GEV) method. The GEV model combines three types of probability distributions (Type I for Gumbel distribution, Type II for Fretchet, or Type III for Weibull) into one expression. Types of distributions can be clarified by one of the three parameters of the GEV model for the corresponding studied stations. In this study, the whole U.S. coast was divided into four study areas: Pacific Coast, Northeast Atlantic Coast, Southeast Atlantic Coast and Gulf of Mexico Coast. Nine National Oceanic and Atmospheric Administration (NOAA) stations with a long history of data (more than 70 years) in the four study areas were chosen in this study. Parameters of the GEV model were estimated by using the annual maximum water level of studied stations based on the Maximum Likelihood Estimation (MLE) method. T-test was applied in this study to tell if the parameter, , was greater than, less than or equal to 0, which was used to tell the type of the GEV model. Results show that different coastal areas have different probability distribution characteristics. The characteristics of probability distribution in Pacific Coast and Northeast Atlantic Coast are similar with extreme value I and III model. The Southeast Atlantic Coast and Gulf of Mexico Coast were found to have similar probability distribution characteristics. The probability distributions were found to be extreme value I and II model, which are different from those of the Pacific Coast and Northeast Atlantic Coast. The performance of the GEV model was also studied in the four coastal areas. GEV model works well in the five studied stations of both the Pacific Coast and the Northeast Atlantic Coast but does not work well in the Southeast Atlantic Coast and the ...