Frequency Analysis of Storm-Surge-Induced Flooding for the Huangpu River in Shanghai, China

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Abstract

Shanghai, as a coastal city, is vulnerable to various types of flooding. The floodwalls along the Huangpu River provide protection against typhoon-induced flooding. However, there is limited insight into the actual safety level of the flood defences in Shanghai, and recent failures have highlighted their vulnerability. Therefore, the aims of this paper are to derive a series of new flood frequency curves for the Huangpu River, and to evaluate the level of protection of the floodwall system. This paper analysed over 100 years (1912–2013) of annual maximum water levels for three stations at near-sea, mid-stream and inland locations along the Huangpu River. Best-fit curves were determined for a number of selected probability distributions using statistical performance indicators. As a result, new flood frequency curves of the water levels for different storm surge return periods were produced. The results showed that generalised extreme value (GEV) was identified as the most suitable probability distribution for the datasets. Analysis showed that the current design water levels correspond to exceedance probabilities of 1/500 per year at the near-sea and mid-stream stations, and no more than 1/50 per year at the inland station of the Huangpu River, whereas the intended safety standard is 1/1000 per year. A comparison of the findings with a dataset of the crest heights of the floodwalls showed that the current protection level of the floodwalls along the Huangpu River is expected to be around 1/50 per year in terms of overtopping for the lowest sections. The results of this study can be utilized to provide future recommendations for flood risk management in Shanghai
Original languageEnglish
Article number70
Number of pages17
JournalJournal of Marine Science and Engineering
Volume6
Issue number2
DOIs
Publication statusPublished - 2018

Keywords

  • frequency analysis
  • storm surge
  • flood risk
  • protection level
  • Huangpu River
  • OA-Fund TU Delft

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