scholarly journals FREQUENCY OF OCCURRENCE OF STORM SURGES IN AN ESTUARY: A STOCHASTIC APPROACH

1984 ◽  
Vol 1 (19) ◽  
pp. 14
Author(s):  
Marc Sas
Keyword(s):  
Storm Surge ◽  
Joint Probability ◽  
Extreme Value Distribution ◽  
Simulation Models ◽  
Storm Surges ◽  
Stochastic Approach ◽  
Frequency Of Occurrence ◽  
Basic Principles ◽  
Probability Methods ◽  
A New Technique

This paper presents the results of a study on the frequency of occurrence of storm surge levels in the river Scheldt at Antwerp, related to the design of a storm surge barrier and the evaluation of the dike safety in the Scheldt basin. The basic principles of the extreme value distribution methods, the joint probability methods and simulation models are examined. A new technique, based upon the simulation of storms by variables characterizing the resulting surge is proposed. Results are compared with those of other methods.

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>

Storm Surge Estimation Along Tokyo Bay Based on a Simple Stochastic Approach

2018 ◽  
Author(s):  
Rikito Hisamatsu ◽  
Sooyoul Kim ◽  
Shigeru Tabeta
Keyword(s):  
Numerical Model ◽  
Storm Surge ◽  
Return Period ◽  
Empirical Formula ◽  
Stochastic Analysis ◽  
Storm Surges ◽  
Stochastic Approach ◽  
Insurance Companies ◽  
Tokyo Bay ◽  
Risk Transfer

In recent years, refinement of stochastic storm surge estimation is essential for risk management in insurance industries because the Japanese government promotes flood risk transfer to insurance companies. Insurance systems may reach peak risk when storm surge damage occurs; however, there are only a few studies on the stochastic analysis of storm surges. This paper presents the stochastic evaluation of storm surges in Tokyo Bay. First, storm surges are assessed using two methods of an empirical formula and a numerical model. Then, the return period of storm surges is stochastically evaluated. It is found that an empirical formula underestimates the surge level in comparison to the numerical model. Based on the results of numerical model, the return period of a storm surge is proposed in Tokyo Bay.

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 Field Survey of 2018 Typhoon Jebi in Japan: Lessons for Disaster Risk Management

Geosciences ◽  
2018 ◽  
Vol 8 (11) ◽  
pp. 412 ◽  
Author(s):  
Tomoyuki Takabatake ◽  
Martin Mäll ◽  
Miguel Esteban ◽  
Ryota Nakamura ◽  
Thit Kyaw ◽  
...  
Keyword(s):  
Risk Management ◽  
Storm Surge ◽  
Field Survey ◽  
Simulation Models ◽  
Storm Surges ◽  
Disaster Risk ◽  
Disaster Risk Management ◽  
Risk Area ◽  
Local Residents ◽  
Hyogo Prefecture

Typhoon Jebi struck Japan on the 4 September 2018, damaging and inundating many coastal areas along Osaka Bay due to the high winds, a storm surge, and wind driven waves. In order to understand the various damage mechanisms, the authors conducted a field survey two days after the typhoon made landfall, measuring inundation heights and depths at several locations in Hyogo Prefecture. The survey results showed that 0.18–1.27 m inundation depths were caused by Typhoon Jebi. As parts of the survey, local residents were interviewed about the flooding, and a questionnaire survey regarding awareness of typhoons and storm surges, and their response to the typhoon was distributed. The authors also mapped the location of some of the containers that were displaced by the storm surge, aiming to provide information to validate future simulation models of container displacement. Finally, some interesting characteristics of the storm surge are summarized, such as possible overtopping at what had initially been thought to be a low risk area (Suzukaze town), and lessons learnt in terms of disaster risk management are discussed.

scholarly journals Comparison of Methods for Imputing Non-Wetting Storm Surge to Improve Hazard Characterization

Water ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1420
Author(s):  
Matthew P. Shisler ◽  
David R. Johnson
Keyword(s):  
Response Surface ◽  
Storm Surge ◽  
Joint Probability ◽  
Training Data ◽  
Fitting Procedure ◽  
Hazard Characterization ◽  
Probability Methods ◽  
Response Surface Function ◽  
Coastal Louisiana ◽  
The Relationship

Joint probability methods for characterizing storm surge hazards involve the use of a collection of hydrodynamic storm simulations to fit a response surface function describing the relationship between storm surge and storm parameters. However, in areas with a sufficiently low probability of flooding, few storms in the simulated storm suite may produce surge, resulting in a paucity of information for training the response surface fit. Previous approaches have replaced surge elevations for non-wetting storms with a constant value or truncated them from the response surface fitting procedure altogether. The former induces bias in predicted estimates of surge from wetting storms, and the latter can cause the model to be non-identifiable. This study compares these approaches and improves upon current methodology by introducing the concept of “pseudo-surge,” with the intent to describe how close a storm comes to producing surge at a given location. Optimal pseudo-surge values are those which produce the greatest improvement to storm surge predictions when they are used to train a response surface. We identify these values for a storm suite used to characterize surge hazard in coastal Louisiana and compare their performance to the two other methods for adjusting training data. Pseudo-surge shows potential for improving hazard characterization, particularly at locations where less than half of training storms produce surge. We also find that the three methods show only small differences in locations where more than half of training storms wet.

IMPACT ASSESSMENT ON STORM SURGE RISKS TO CONTAINERS CONSIDERING GLOBAL WARMING

2017 ◽  
Author(s):  
Rikito Hisamatsu ◽  
Rikito Hisamatsu ◽  
Kei Horie ◽  
Kei Horie
Keyword(s):  
Risk Assessment ◽  
Global Warming ◽  
Storm Surge ◽  
Storm Surges ◽  
Assessment Tools ◽  
Inundation Depth ◽  
Risk Assessment Tools ◽  
Risk Maps ◽  
The Impact ◽  
Vulnerability Functions

Container yards tend to be located along waterfronts that are exposed to high risk of storm surges. However, risk assessment tools such as vulnerability functions and risk maps for containers have not been sufficiently developed. In addition, damage due to storm surges is expected to increase owing to global warming. This paper aims to assess storm surge impact due to global warming for containers located at three major bays in Japan. First, we developed vulnerability functions for containers against storm surges using an engineering approach. Second, we simulated storm surges at three major bays using the SuWAT model and taking global warming into account. Finally, we developed storm surge risk maps for containers based on current and future situations using the vulnerability function and simulated inundation depth. As a result, we revealed the impact of global warming on storm surge risks for containers quantitatively.

scholarly journals Storm Surges in the Bohai Sea: The Role of Waves and Tides

Water ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1509
Author(s):  
Yuanyi Li ◽  
Huan Feng ◽  
Guillaume Vigouroux ◽  
Dekui Yuan ◽  
Guangyu Zhang ◽  
...  
Keyword(s):  
Storm Surge ◽  
Bohai Sea ◽  
Storm Surges ◽  
Wave Force ◽  
Laizhou Bay ◽  
Bohai Bay ◽  
Coastal Regions ◽  
The Bohai Sea ◽  
Tidal Phase ◽  
Set Up

A storm surge is a complex phenomenon in which waves, tide and current interact. Even though wind is the predominant force driving the surge, waves and tidal phase are also important factors that influence the mass and momentum transport during the surge. Devastating storm surges often occur in the Bohai Sea, a semi-enclosed shallow sea in North China, due to extreme storms. However, the effects of waves on storm surges in the Bohai Sea have not been quantified and the mechanisms responsible for the higher surges that affect part of the Bohai Sea have not been thoroughly studied. In this study, we set up a storm surge model, considering coupled effects of tides and waves on the surges. Validation against measured data shows that the coupled model is capable of simulating storm surges in the Bohai Sea. The simulation results indicate that the longshore currents, which are induced by the large gradient of radiation stress due to wave deformation, are one of the main contributors to the higher surges occurring in some coastal regions. The gently varying bathymetry is another factor contributing to these surges. With such bathymetry, the wave force direction is nearly uniform, and pushes a large amount of water in that direction. Under these conditions, the water accumulates in some parts of the coast, leading to higher surges in nearby coastal regions such as the south coast of the Bohai Bay and the west and south coasts of the Laizhou Bay. Results analysis also shows that the tidal phase at which the surge occurs influences the wave–current interactions, and these interactions are more evident in shallow waters. Neglecting these interactions can lead to inaccurate predictions of the storm surges due to overestimation or underestimation of wave-induced set-up.

scholarly journals Measuring compound flood potential from river discharge and storm surge extremes at the global scale

2020 ◽  
Vol 20 (2) ◽  
pp. 489-504 ◽  
Author(s):  
Anaïs Couasnon ◽  
Dirk Eilander ◽  
Sanne Muis ◽  
Ted I. E. Veldkamp ◽  
Ivan D. Haigh ◽  
...  
Keyword(s):  
Storm Surge ◽  
River Discharge ◽  
Flood Hazard ◽  
Joint Probability ◽  
Global Scale ◽  
Statistical Dependence ◽  
Dependence Structure ◽  
Meteorological Forcing ◽  
Continental Scale ◽  
Bivariate Dependence

Abstract. The interaction between physical drivers from oceanographic, hydrological, and meteorological processes in coastal areas can result in compound flooding. Compound flood events, like Cyclone Idai and Hurricane Harvey, have revealed the devastating consequences of the co-occurrence of coastal and river floods. A number of studies have recently investigated the likelihood of compound flooding at the continental scale based on simulated variables of flood drivers, such as storm surge, precipitation, and river discharges. At the global scale, this has only been performed based on observations, thereby excluding a large extent of the global coastline. The purpose of this study is to fill this gap and identify regions with a high compound flooding potential from river discharge and storm surge extremes in river mouths globally. To do so, we use daily time series of river discharge and storm surge from state-of-the-art global models driven with consistent meteorological forcing from reanalysis datasets. We measure the compound flood potential by analysing both variables with respect to their timing, joint statistical dependence, and joint return period. Our analysis indicates many regions that deviate from statistical independence and could not be identified in previous global studies based on observations alone, such as Madagascar, northern Morocco, Vietnam, and Taiwan. We report possible causal mechanisms for the observed spatial patterns based on existing literature. Finally, we provide preliminary insights on the implications of the bivariate dependence behaviour on the flood hazard characterisation using Madagascar as a case study. Our global and local analyses show that the dependence structure between flood drivers can be complex and can significantly impact the joint probability of discharge and storm surge extremes. These emphasise the need to refine global flood risk assessments and emergency planning to account for these potential interactions.

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