Research On The Algorithm Of Return Period Water Level And Its Spatial Distribution In The Coastal Area Of China

Due to human activities and global warming and other factors,sea level rise has become a problem we have to face.The ocean expansion,sea air interaction and glacial melting caused by climate warming increase the rate of sea level rise.The extreme high water level events caused by sea level rise will seriously threaten the economic development and social life of coastal cities.Therefore,under the current climate change background,it is particularly important and urgent to carry out risk assessment of extreme high water level events.Extreme water level plays an important role in coastal engineering,offshore engineering,flood control and dampproof engineering,and it is an important reference to determine whether the offshore engineering can meet the safety requirements.China's coastal cities have a large population density,with a total population of about 500 million and a developed economy.The total output value of industry and agriculture in the coastal areas accounts for about 60% of the total output value of the country.Under the current situation of accelerated sea-level rise,it is particularly important to carry out risk assessment of return period of extreme high water level in China's coastal areas.In this paper,the distribution of the return period of extreme water level in the coastal area of China is calculated by the joint probability method of conditional distribution and the calculation method of extreme water level considering sea level rise.At the same time,the storm surge model is established by using FVCOM(Finite Volume Coast and Ocean Model)ocean model to simulate 21 typhoons which have great influence on the sea area near Zhoushan for 21 years.The spatial distribution of extreme water level and extreme value increase in Zhoushan sea area after many years of encounter is calculated by the Gumbel model.The main contents and conclusions are as follows:1.In this paper,the extreme water levels of two different situations,which are independent of the tide level and the residual water level and related to the tidal level and the residual water level,are calculated.By comparison,it is concluded that the joint probability method can use the water level observation data more fully than the extreme value method.The joint probability method can consider the different distributions of the remaining water levels under different tidal water levels,but the disadvantage is that some of the large increase and decrease water information is not used in the calculation of the extreme value distribution.At the same time,the digital characteristics of the residual water level distribution of the coastal tide stations in China are analyzed,and the conclusions are as follows: the spatial distribution of the residual water level standard deviation shows a trend of gradually decreasing from north to south,and the residual water level standard deviation of the estuary station is generally greater than that of the open sea station Poor;the spatial distribution of residual water level skew is mostly positive for southern ports and negative for northern ports;from the spatial distribution of residual water level kurtosis,the kurtosis of stations in Bohai,Yellow and South China Seas is greater than the kurtosis of stations in East China Sea.2.Since most of the previous algorithms for calculating extreme water levels did not consider the effect of sea level rise,this paper combines future sea level rise with the extreme water level of the current scenario,and uses the P-III model to recalculate the extreme water level and the recurrence period.The results show that the return period of extreme events is obviously shortened due to the sea level rise caused by climate change.Specifically,the change of water level between CEWL(Current Extreme Water Level)and SEWL(Scenario Extreme Water Level)in different time scale RCP(Representative Concentration Pathway)scenarios and in each RCP scenario shows that sea level rise has a significant impact on the change of extreme water level.The return period is shortened most significantly under the RCP 8.5 scenario;at the higher level under the RCP 8.5 scenario,the 100 year return period extreme water level under the normal scenario will gradually change to about 17 year return period in 2050,and only 2 year return period in 2100.Therefore,CEWLs along the coast of China will become a common event in 2050 under this concentration scenario.3.In this paper,the storm surge model is used to simulate the process of 21 typhoons which had a great influence on the sea area near Zhoushan from 1997 to 2017.The extreme water level and the extreme water increase are calculated by Gumbel distribution.The spatial distribution characteristics of the multi-year extreme water level near Zhoushan are that the near shore is larger than the open sea.The spatial distribution of annual extreme water increase is gradually decreasing from near shore to open sea.