Cite this paper:
CHEN Baiyu, LIU Guilin, WANG Liping, ZHANG Kuangyuan, ZHANG Shuaifang. Determination of water level design for an estuarine city[J]. HaiyangYuHuZhao, 2019, 37(4): 1186-1196

Determination of water level design for an estuarine city

CHEN Baiyu1, LIU Guilin2, WANG Liping3, ZHANG Kuangyuan4, ZHANG Shuaifang5
1 College of Engineering, University of California Berkeley, Berkeley 94720, USA;
2 College of Engineering, Ocean University of China, Qingdao 266000, China;
3 College of Mathematical Science, Ocean University of China, Qingdao 266000, China;
4 Department of Economics, Penn State University, State College 16801, USA;
5 Department of Mechanical Engineering, University of Florida, Gainesville 32611, USA
Abstract:
Based on the extreme value theory, self-affinity, and scale invariance, we studied the temporal and spatial relationship and the variation of water level and established a model of Gumbel-Pareto distribution for designed flood calculation. The model includes the previous extreme value models, the over-threshold data, and the fractal features shared by previous extreme value models. The model was simplified into a logarithmic normal distribution and a Pareto distribution for specific parameter values, and was used to calculate the designed flood values for the Shanghai Wusong Station in 100- and 1 000-year return periods. The calculated results show that the value of the designed flood height calculated in the Gumbel-Pareto distribution is between those in the Gumbel and Pearson-Ⅲ distributions. The designed flood values in the 100- and 1 000-year return periods of the model were 0.03% and 0.11% lower, respectively, than the Gumbel distribution and 0.06% and 1.54% higher, respectively, than the Pearson-Ⅲ distribution. Compared to the traditional model based solely on extreme probability, the Gumbel-Pareto distribution model could better describe the probabilistic characteristics of extreme marine elements and better use the data.
Key words:    self-affinity|scale invariance|extreme value distribution   
Received: 2018-04-24   Revised: 2018-08-08
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Articles by CHEN Baiyu
Articles by LIU Guilin
Articles by WANG Liping
Articles by ZHANG Kuangyuan
Articles by ZHANG Shuaifang
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