scholarly journals The calculation of maximum elevation due to storm surge by using joint probability method

MAUSAM ◽  
2021 ◽  
Vol 48 (4) ◽  
pp. 587-594
Author(s):  
WANG XIUQIN ◽  
WANG JINGYONG
Keyword(s):  
Storm Surge ◽  
Joint Probability ◽  
Storm Surges ◽  
Guangdong Province ◽  
Probability Method ◽  
Historical Records ◽  
Probability Curve ◽  
Hydrological Data ◽  
Maximum Elevation ◽  
Joint Probability Method

In the present paper the maximum storm surge elevations with certain return years were calculated by using a joint probability method. Based on the analyses of the typhoons which, affected coastal zone of Guangdong Province in history, a group of model typhoons was established. A number of parameters, which described the typhoons, were selected. The data of each parameter I was graded into a few sub-groups according to their values, and this was done in accordance with the historical observations. The probability of each value of the parameters was calculated based on the historical records. The probability of a typhoon with a group of values of parameters could be calculated. Simulation results of the storm surges caused by the above model typhoons with their probabilities were analysed statistically. Thus an accumulated probability curve and maximum elevations with certain return years were obtained. A number of spots was selected. At some of the spots there are tidal stations and at the others there are none. The maximum elevations with certain return years at the spots were calculated and the results were found satisfactory. By using this method all the meteorological and hydrological data, which were available, can be fully utilized. This method is most suitable for calculating the  maximum elevations at a place where there is no tidal station or at many places simultaneously.    

scholarly journals An objective and efficient method for estimating probabilistic coastal inundation hazards

2019 ◽  
Vol 99 (2) ◽  
pp. 1105-1130 ◽  
Author(s):  
Kun Yang ◽  
Vladimir Paramygin ◽  
Y. Peter Sheng
Keyword(s):  
High Resolution ◽  
Storm Surge ◽  
Computational Cost ◽  
Joint Probability ◽  
Water Levels ◽  
Computational Time ◽  
Probability Method ◽  
Highly Efficient ◽  
Inundation Maps ◽  
Flood Elevation

Abstract The joint probability method (JPM) is the traditional way to determine the base flood elevation due to storm surge, and it usually requires simulation of storm surge response from tens of thousands of synthetic storms. The simulated storm surge is combined with probabilistic storm rates to create flood maps with various return periods. However, the map production requires enormous computational cost if state-of-the-art hydrodynamic models with high-resolution numerical grids are used; hence, optimal sampling (JPM-OS) with a small number of (~ 100–200) optimal (representative) storms is preferred. This paper presents a significantly improved JPM-OS, where a small number of optimal storms are objectively selected, and simulated storm surge responses of tens of thousands of storms are accurately interpolated from those for the optimal storms using a highly efficient kriging surrogate model. This study focuses on Southwest Florida and considers ~ 150 optimal storms that are selected based on simulations using either the low fidelity (with low resolution and simple physics) SLOSH model or the high fidelity (with high resolution and comprehensive physics) CH3D model. Surge responses to the optimal storms are simulated using both SLOSH and CH3D, and the flood elevations are calculated using JPM-OS with highly efficient kriging interpolations. For verification, the probabilistic inundation maps are compared to those obtained by the traditional JPM and variations of JPM-OS that employ different interpolation schemes, and computed probabilistic water levels are compared to those calculated by historical storm methods. The inundation maps obtained with the JPM-OS differ less than 10% from those obtained with JPM for 20,625 storms, with only 4% of the computational time.

Applying POT methods to the Revised Joint Probability Method for determining extreme sea levels

2014 ◽  
Vol 91 ◽  
pp. 140-150 ◽  
Author(s):  
Franck Mazas ◽  
Xavier Kergadallan ◽  
Philippe Garat ◽  
Luc Hamm
Keyword(s):  
Joint Probability ◽  
Probability Method ◽  
Sea Levels ◽  
Extreme Sea Levels ◽  
Joint Probability Method

Compound impact of rainfall, tidal level and storm surge on flood risk from tropical cyclones in the coastal area of shanghai

2020 ◽  
Author(s):  
Hanqing Xu
Keyword(s):  
Tropical Cyclone ◽  
Tropical Cyclones ◽  
Storm Surge ◽  
Extreme Events ◽  
Joint Probability ◽  
Storm Surges ◽  
Heavy Precipitation ◽  
Tidal Level ◽  
Sea Levels ◽  
The Impact

<p>Catastrophic flooding resulting from extreme tropical cyclones has occurred more frequently and drawn great attention in recent years in China. Coastal cities are particularly vulnerable to flood under multivariable conditions, such as heavy precipitation, high sea levels, and storms surge. In coastal areas, floods caused by rainstorms and storm surges have been one of the most costly and devastating natural hazards in coastal regions. Extreme precipitation and storm tide are both inducing factors of flooding and therefore their joint probability would be critical to determine the flooding risk. Usually, extreme events such as tidal level, storm surges, precipitation occur jointly, leading to compound flood events with significantly higher hazards compared to the sum of the single extreme events. The purpose of this study is to improve our understanding of multiple drivers to compound flooding in shanghai. The Wind Enhance Scheme (WES) model characterized by Holland model is devised to generate wind "spiderweb" both for historical (1949-2018) and future (2031-2060, 2069-2098) tropical cyclones. The tidal level and storm surge model based on Delft3D-FLOW is employed with an unstructured grid to simulate the change of water level. For precipitation, maximum value between tropical cyclone events is selected. Following this, multivariate Copula model would be employed to compare the change of joint probability between tidal level, storm surge and heavy precipitation under climate change, taking into account sea-level rise and land subsidence. Finally, the impact of tropical cyclone on the joint risk of tidal, storm surge and heavy precipitation is investigated. </p>

scholarly journals Risk Assessment of Coastal Flooding under Different Inundation Situations in Southwest of Taiwan (Tainan City)

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 880
Author(s):  
Moslem Imani ◽  
Chung-Yen Kuo ◽  
Pin-Chieh Chen ◽  
Kuo-Hsin Tseng ◽  
Huan-Chin Kao ◽  
...  
Keyword(s):  
Sea Level ◽  
Tide Gauge ◽  
Spring Tide ◽  
Joint Probability ◽  
High Water ◽  
Probability Method ◽  
Tide Gauge Records ◽  
Regional Sea Level ◽  
Tainan City ◽  
Joint Probability Method

The Pacific island countries are particularly vulnerable to the effects of global warming including more frequent and intense natural disasters. Seawater inundation, one of the most serious disasters, could damage human property and life. Regional sea level rise, highest astronomic tide, vertical land motions, and extreme sea level could result in episodic, recurrent, or permanent coastal inundation. Therefore, assessing potential flooding areas is a critical task for coastal management plans. In this study, a simulation of the static flooding situation in the southwest coast of Taiwan (Tainan city) at the end of this century was conducted by using a combination of the Taiwan Digital Elevation Model (DEM), regional sea level changes reconstructed by tide gauge and altimetry data, vertical land deformation derived from leveling and GPS data, and ocean tide models. In addition, the extreme sea level situation, which typically results from high water on a spring tide and a storm surge, was also evaluated by the joint probability method using tide gauge records. To analyze the possible static flood risk and avoid overestimation of inundation areas, a region-based image segmentation method was employed in the estimated future topographic data to generate the flood risk map. In addition, an extreme sea level situation, which typically results from high water on a spring tide and a storm surge, was also evaluated by the joint probability method using tide gauge records. Results showed that the range of inundation depth around the Tainan area is 0–8 m with a mean value of 4 m. In addition, most of the inundation areas are agricultural land use (60% of total inundation area of Tainan), and two important international wetlands, 88.5% of Zengwun Estuary Wetlands and 99.5% of Sihcao Wetlands (the important Black-faced Spoonbills Refuge) will disappear under the combined situation. The risk assessment of flooding areas is potentially useful for coastal ocean and land management to develop appropriate adaptation policies for preventing disasters resulting from global climate change.

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