Determination of water level design for an estuarine city -- Journal of Oceanology and Limnology,2019,37(4):1186-1196

	Cite this paper:
	CHEN Baiyu, LIU Guilin, WANG Liping, ZHANG Kuangyuan, ZHANG Shuaifang. Determination of water level design for an estuarine city[J]. Journal of Oceanology and Limnology, 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 LIU Guilin

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Articles by ZHANG Shuaifang

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