A method of estimating high elevation of multi-year return periods

LU Si-wen; PAN Ling-zhi; XIAO Wen-jun; GONG Mao-xun; CHEN Bing-rui

doi:10.3969/j.issn.1000-5641.2017.02.017

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Mar. 2017

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Article Navigation > Journal of East China Normal University (Natural Sciences) > 2017 > (2): 138-147

LU Si-wen, PAN Ling-zhi, XIAO Wen-jun, GONG Mao-xun, CHEN Bing-rui. A method of estimating high elevation of multi-year return periods[J]. Journal of East China Normal University (Natural Sciences), 2017, (2): 138-147. doi: 10.3969/j.issn.1000-5641.2017.02.017

Citation:

LU Si-wen, PAN Ling-zhi, XIAO Wen-jun, GONG Mao-xun, CHEN Bing-rui. A method of estimating high elevation of multi-year return periods[J]. Journal of East China Normal University (Natural Sciences), 2017, (2): 138-147. doi: 10.3969/j.issn.1000-5641.2017.02.017

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A method of estimating high elevation of multi-year return periods

doi: 10.3969/j.issn.1000-5641.2017.02.017

1.
College of Marine Science, Shanghai Ocean University, Shanghai 201306, China
2.
East China Sea Marine Forecasting Center of State Oceanic Administration, Shanghai 200136, China
3.
East China Sea Marine Information Center of State Oceanic Administration, Shanghai 200136, China

Received Date: 2016-03-29
Publish Date: 2017-03-25

Abstract

Abstract

This paper introduced a method of estimating extreme water level of multi-year return periods where observed data were inadequate, with the instance of Daxiedao Petrochemical Zone in Ningbo, Zhejiang. Strong weather processes caused annual maximum elevations in the past 25 years were chosen, modelled and validated based on observed wind and water elevation data of 2 nearby ocean stations, Dinghai and Zhenhai. By using well validated wind data from WRF model and the ADCIRC storm surge model, 25 years of annual maximum elevations at Daxiedao Petrochemical Zone were simulated and corrected by using the weight-averaged correlation between the model and observation in 2 ocean stations. The extreme water level of multi-year return periods was analyzed based on Gumbel distribution assumption and used for the ocean engineering design and risk investigation.
- Ningbo Daxiedao,
- multi-year extreme water level,
- numerical simulation,
- Gumbel distribution,
- Weight-averaged correlation

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References(17)

References

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