scholarly journals An Integrated Approach for the Simulation Modeling and Risk Assessment of Coastal Flooding

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2076
Author(s):  
Yazhi Zheng ◽  
Hai Sun
Keyword(s):  
Risk Assessment ◽  
Storm Surge ◽  
Flood Risk ◽  
Simulation Modeling ◽  
River Estuary ◽  
Coastal Flooding ◽  
Coastal Areas ◽  
Economic Losses ◽  
Actual Case ◽  
Ca Model

The evaluation of storm surge flood risk is vital to disaster management and planning at national, regional and local levels, particularly in coastal areas that are affected more severely by storm surges. The purpose of this paper is to propose a new method that includes two modules for the simulation modeling and risk assessment of coastal flooding. One is a hydrodynamic module for simulating the process of the flood inundation coastal inundation arising from storm surge, which is based on a cellular automata (CA) model. The other is a risk assessment module for quantitatively estimating the economic loss by using the inundation data and land use data. The coastal areas of Pearl River estuary in China were taken as a case study. Simulation results are compared to experimental results from MIKE 21 and depth data from a social-media-based dataset, which demonstrates the effectiveness of the CA model. By analyzing flood risk, the flood area and the direct economic losses predicted are close to the actual case incurred, further demonstrating the computational reliability of the proposed method. Additionally, an automatic risk assessment platform is designed by integrating the two modules in a Geographic Information System (GIS) framework, facilitating a more efficient and faster simulation of coastal flooding. The platform can provide the governments as well as citizens of coastal areas with user-friendly, real-time graphics for coastal flood disaster preparation, warning, response and recovery.

Flood risk influenced by the compound effect of storm surge and rainfall under climate change for low-lying coastal areas

2021 ◽  
Vol 764 ◽  
pp. 144439
Author(s):  
Shih-Chun Hsiao ◽  
Wen-Son Chiang ◽  
Jiun-Huei Jang ◽  
Han-Lun Wu ◽  
Wei-Shiun Lu ◽  
...  
Keyword(s):  
Climate Change ◽  
Storm Surge ◽  
Flood Risk ◽  
Coastal Areas ◽  
Compound Effect

scholarly journals Coastal Flooding Risk Assessment Using a GIS-Based Spatial Multi-Criteria Decision Analysis Approach

Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2379
Author(s):  
Vahid Hadipour ◽  
Freydoon Vafaie ◽  
Kaveh Deilami
Keyword(s):  
Risk Assessment ◽  
High Risk ◽  
Decision Analysis ◽  
Sea Level ◽  
Flood Risk ◽  
Social Vulnerability ◽  
Quantitative Methods ◽  
Coastal Flooding ◽  
Rcp Scenarios ◽  
Multi Criteria Decision Analysis

Coastal areas are expected to be at a higher risk of flooding when climate change-induced sea-level rise (SLR) is combined with episodic rises in sea level. Flood susceptibility mapping (FSM), mostly based on statistical and machine learning methods, has been widely employed to mitigate flood risk; however, they neglect exposure and vulnerability assessment as the key components of flood risk. Flood risk assessment is often conducted by quantitative methods (e.g., probabilistic). Such assessment uses analytical and empirical techniques to construct the physical vulnerability curves of elements at risk, but the role of people’s capacity, depending on social vulnerability, remains limited. To address this gap, this study developed a semiquantitative method, based on the spatial multi-criteria decision analysis (SMCDA). The model combines two representative concentration pathway (RCP) scenarios: RCP 2.6 and RCP 8.5, and factors triggering coastal flooding in Bandar Abbas, Iran. It also employs an analytical hierarchy process (AHP) model to weight indicators of hazard, exposure, and social vulnerability components. Under the most extreme flooding scenario, 14.8% of flooded areas were identified as high and very high risk, mostly located in eastern, western, and partly in the middle of the City. The results of this study can be employed by decision-makers to apply appropriate risk reduction strategies in high-risk flooding zones.

scholarly journals Research Design of Mobile Based Decision Support for Early Flood Warning System

2020 ◽  
Vol 14 (17) ◽  
pp. 130
Author(s):  
Mohd Faizal Omar ◽  
Mohd Nasrun Mohd Nawi ◽  
Jastini Mohd Jamil ◽  
Ani Munirah Mohamad ◽  
Saslina Kamaruddin
Keyword(s):  
Mathematical Model ◽  
Risk Assessment ◽  
Decision Making ◽  
Decision Support ◽  
Research Design ◽  
Flood Risk ◽  
Architectural Design ◽  
Warning System ◽  
Economic Losses ◽  
Flood Risk Assessment

Flooding has become one of the most rapidly growing types of natural disaster that has spread around the globe. It is is one of the major natural hazards in many countries and mostly affected in the low-lying or flood prone areas. In order to minimize loss of life and economic losses, a detailed and comprehensive decision making tool is necessary for both flood control planning and emergency service operations. In this paper, we demonstrate our research design for mobile based decision support of Flood Early Warning System (FEWS). We outlined four research objectives. Firstly, critical criteria for flood risk assessment will be identified and the second step will involve develop measurement model for relative flood risk using Geographic Information System (GIS), Multi Attribute Decision Making (MADM) and data mining technique. In the third objectives, the holistic architectural design is develop by incorporating the communication technology and other related ICT requirements for the mobile decision support. The fourth objective is to validate the mathematical model and architectural design. Case study approach is chosen in order to understand the flood event and validate the decision support model. Following well-defined procedures, flood maps were drawn based on the data collected from expert responses to a questionnaire, the field survey, satellite images, and documents from flood management agencies. It is anticipates that by integrating of mathematical model, GIS and mobile application in flood risk assessment could provide useful detailed information for flood risk management, evacuation, communication. The decision support design from this study is perhaps to improve the warning system and contribute to reduction of casualties.

scholarly journals Flood Risk Assessment for the Long-Term Strategic Planning Considering the Placement of Industrial Parks in Slovakia

2020 ◽  
Vol 12 (10) ◽  
pp. 4144 ◽  
Author(s):  
Henrich Grežo ◽  
Matej Močko ◽  
Martin Izsóff ◽  
Gréta Vrbičanová ◽  
František Petrovič ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
River Flow ◽  
Flow Simulation ◽  
Current Data ◽  
Economic Losses ◽  
Historical Maps ◽  
Flood Risk Assessment ◽  
Industrial Parks ◽  
Flood Maps

The intention of the article is to demonstrate how data from historical maps might be applied in the process of flood risk assessment in peri-urban zones located in floodplains and be complementary datasets to the national flood maps. The research took place in two industrial parks near the rivers Žitava and Nitra in the town of Vráble (the oldest industrial park in Slovakia) and the city of Nitra (one of the largest industrial parks in Slovakia, which is still under construction concerning the Jaguar Land Rover facility). The historical maps from the latter half of the 18th and 19th centuries and from the 1950s of the 20th century, as well as the field data on floods gained with the GNSSS receiver in 2010 and the Q100 flood line of the national flood maps (2017), were superposed in geographic information systems. The flood map consists of water flow simulation by a mathematical hydrodynamic model which is valid only for the current watercourse. The comparison of historical datasets with current data indicated various transformations and shifts of the riverbanks over the last 250 years. The results proved that the industrial parks were built up on traditionally and extensively used meadows and pastures through which branched rivers flowed in the past. Recent industrial constructions intensified the use of both territories and led to the modifications of riverbeds and shortening of the watercourse length. Consequently, the river flow energy increased, and floods occurred during torrential events in 2010. If historical maps were respected in the creation of the flood maps, the planned construction of industrial parks in floodplains could be limited or forbidden in the spatial planning documentation. This study confirmed that the flood modelling using the Q100 flood lines does not provide sufficient arguments for investment development groups, and flood maps might be supplied with the data derived from historical maps. The proposed methodology represents a simple, low cost, and effective way of identifying possible flood-prone areas and preventing economic losses and other damages.

scholarly journals Direct and Indirect Loss Evaluation of Storm Surge Disaster Based on Static and Dynamic Input-Output Models

2020 ◽  
Vol 12 (18) ◽  
pp. 7347
Author(s):  
Xue Jin ◽  
U. Rashid Sumaila ◽  
Kedong Yin
Keyword(s):  
Storm Surge ◽  
Coastal Areas ◽  
Practical Significance ◽  
Economic Losses ◽  
Total Output ◽  
National Bureau ◽  
Input Output ◽  
Output Loss ◽  
Disaster Assessment ◽  
Storm Surge Disaster

Storm surge disaster is one of the biggest threats to coastal areas. Over the years, it has brought serious losses to the economy and environment of China’s coastal areas. In this paper, Guangdong Province is taken as the research object to evaluate the damage caused by storm surge disasters. First of all, regarding the three-industry classification standards of the National Bureau of Statistics, combined with the storm surge disaster assessment index system, the 10-sector storm surge disaster loss input-output table is compiled and analyzed. Secondly, the indirect economic losses of storm surge disasters between 2007–2017 are determined by calculating the direct and indirect consumption coefficients. Thirdly, based on the static input-output model, considering the time factor, the dynamic input-output model of storm surge disaster assessment is established to calculate the cumulative output loss under different recovery periods (30 days, 90 days, 120 days, 180 days, 360 days). The results indicate that: (1) the losses, after a storm surge, in the agricultural economy have the greatest impact on the manufacturing sector, and conversely, they have less effect on the science, education and health service sectors; as well as the construction sector; (2) taking the industry with the biggest loss ratio as an example, the recovery of damaged industries is relatively rapid in the early stage and tends to be stable in the later stage of recovery; (3) the total output loss calculated using the static input-output model is greater than that computed using the dynamic input-output model. Researching the assessment of the direct and indirect loss due to storm surge disasters is of great value and practical significance for the scientific and rational planning of the country’s production layout, the maintenance of social and economic stability and the protection of life and property.

Coastal risk assessments due to hybrid disasters in Korea

2020 ◽  
Author(s):  
Tae-Soon Kang ◽  
Hyeong-Min Oh ◽  
Soon-Mi Hwang ◽  
Ho-Kyun Kim ◽  
Kwang-Young Jeong
Keyword(s):  
Climate Change ◽  
Risk Assessment ◽  
Storm Surge ◽  
Risk Index ◽  
Coastal Areas ◽  
Observation Data ◽  
Blue Color ◽  
Wave Overtopping ◽  
Coastal Risk Assessment ◽  
Coastal Risk

<p>Korean coasts are exposed to high risks such as storm surge, storm-induced high waves and wave overtopping. Also, localized heavy rainfall events have occurred frequently due to climate change, too. Especially, since coastal urban areas depend heavily on pump and pipe systems, extreme rainfalls that exceed the design capacity of drainage facility result in increasing inland flood damage. Nevertheless, the population in Korea is concentrated in the coastal areas and the value and density of coastal utilization are increasing. In this study, the risk of hybrid disasters in the coastal areas was assessed for safe utilization and value enhancement of coastal areas. The framework of the coastal risk assessment has been adopted from the concept of climate change vulnerability of the IPCC(2001). Coastal Risk Index(CRI) in this study was defined as a function of Exposure and Sensitivity exclude Adaptive Capacity using GIS-based DBs. Indicators of Exposure consisted of a storm surge, storm-induced high waves, wave overtopping and rainfalls. Indicators of Sensitivity consisted of human(population density), property(buildings and roads), and geography(inundation area). All these indicators were gathered from government agencies, numerical model experiments(ADCIRC, unSWAN, FLOW3D and XP-SWMM model), and field surveys(Drone & Lidar survey). And then spatial analysis was performed by using a GIS program after passing the quality control and analyzed data were standardized and classified 4 grades; Attention(blue color), Caution(yellow color), Warning(orange color) and Danger(red color). This frame of risk assessment was first applied to Marine City, Haeundae in Busan, Korea which was heavily damaged by the typhoon CHABA in 2018. According to the assessment results, it was confirmed that the results were in good agreement with the observation data and damage range. At present, the study area of risk assessment is expanding to other areas. The results of coastal risk assessment are used as reference indicators to identify and prevent the cause of coastal disasters, establish countermeasures, determine the development or management of coastal areas based on GIS, thus will contribute to effective and safe coastal management.</p>

What value do mangroves have in reducing the cost of storm surges?

2020 ◽  
Author(s):  
Christopher Thomas ◽  
Siddharth Narayan ◽  
Joss Matthewman ◽  
Christine Shepard ◽  
Laura Geselbracht ◽  
...  
Keyword(s):  
Storm Surge ◽  
Insurance Industry ◽  
Economic Value ◽  
Storm Surges ◽  
Coastal Flooding ◽  
Economic Losses ◽  
Modelling Framework ◽  
Catastrophe Modelling ◽  
The Cost ◽  
The Impact

<p>With coastlines becoming increasingly urbanised worldwide, the economic risk posed by storm surges to coastal communities has never been greater. Given the financial and ecological costs of manmade coastal defences, the past few years have seen growing interest in the effectiveness of natural coastal “defences” in reducing the risk of flooding to coastal properties, but estimating their actual economic value in reducing storm surge risk remains a challenging subject.</p><p>In this study, we estimate the value of mangroves in reducing annual losses to property from storm surges along a large stretch of coastline in Florida (USA), by employing a catastrophe modelling approach widely used in the insurance industry. We use a hydrodynamic coastal flood model coupled to a property loss model and a large property exposure dataset to estimate annual economic losses from hurricane-driven storm surges in Collier County, a hurricane-prone part of Florida. We then estimate the impact that removing mangroves in the region would have on average annual losses (AAL) caused by coastal flooding. We find that mangroves reduce AAL to properties behind them by over 25%, and that these benefits are distributed very heterogeneously along the coastline. Mangrove presence can also act to enhance the storm surge risk in areas where development has occurred seaward of mangroves.</p><p>In addition to looking at annual losses, we also focus on the storm surge caused by a specific severe event in Florida, based on Hurricane Irma (2017), and we estimate that existing mangroves reduced economic property damage by hundreds of millions of USD, and reduced coastal flooding for hundreds of thousands of people.</p><p>Together these studies aim to financially quantify some of the risk reduction services provided by natural defences in terms of reducing the cost of coastal flooding, and show that these services can be included in a catastrophe modelling framework commonly used in the insurance industry.</p>

Uncertainty in coastal flooding: modelling and visualisation

2020 ◽  
Author(s):  
John Maskell
Keyword(s):  
Water Level ◽  
Storm Surge ◽  
Return Period ◽  
Flood Risk ◽  
High Water ◽  
Coastal Flooding ◽  
Water Levels ◽  
Tidal Range ◽  
The Uk ◽  
Flood Maps

<p>Two case studies are considered in the UK, where uncertainty and drivers of coastal flood risk are explored through modelling and visualisations. Visualising the impact of uncertainty is a useful way of explaining the potential range of predicted or simulated flood risk to both expert and non-expert stakeholders.</p><p>Significant flooding occurred in December 2013 and January 2017 at Hornsea on the UK East Coast, where storm surge levels and waves overtopped the town’s coastal defences. Uncertainty in the potential coastal flooding is visualised at Hornsea due to the range of uncertainty in the 100-year return period water level and in the calculated overtopping due to 3 m waves at the defences. The range of uncertainty in the simulated flooding is visualised through flood maps, where various combinations of the uncertainties decrease or increase the simulated inundated area by 58% and 82% respectively.</p><p>Located at the mouth of the Mersey Estuary and facing the Irish Sea, New Brighton is affected by a large tidal range with potential storm surge and large waves. Uncertainty in the coastal flooding at the 100-year return period due to the combination of water levels and waves is explored through Monte-Carlo analysis and hydrodynamic modelling. Visualisation through flood maps shows that the inundation extent at New Brighton varies significantly for combined wave and surge events with a joint probability of 100 years, where the total flooded area ranges from 0 m<sup>2</sup> to 10,300 m<sup>2</sup>. Waves are an important flood mechanism at New Brighton but are dependent on high water levels to impact the coastal defences and reduce the effective freeboard. The combination of waves and high-water levels at this return level not only determine the magnitude of the flood extent but also the spatial characteristics of the risk, whereby flooding of residential properties is dominated by overflow from high water levels, and commercial and leisure properties are affected by large waves that occur when the water level is relatively high at the defences.</p>

scholarly journals Research progress and prospect of coastal flood disaster risk assessment against global climate change

2021 ◽  
Vol 4 (2) ◽  
Author(s):  
Jiayi Fang ◽  
Peijun Shi
Keyword(s):  
Climate Change ◽  
Risk Assessment ◽  
Global Climate Change ◽  
Global Climate ◽  
High Tide ◽  
Coastal Flooding ◽  
Coastal Areas ◽  
Mitigation Measures ◽  
Research Progress ◽  
Coastal Flood

The sea level rise under global climate change and coastal floods caused by extreme sea levels due to the high tide levels and storm surges have huge impacts on coastal society, economy, and natural environment. It has drawn great attention from global scientific researchers. This study examines the definitions and elements of coastal flooding in the general and narrow senses, and mainly focuses on the components of coastal flooding in the narrow sense. Based on the natural disaster system theory, the review systematically summarizes the progress of coastal flood research in China, and then discusses existing problems in present studies and provide future research directions with regard to this issue. It is proposed that future studies need to strengthen research on adapting to climate change in coastal areas, including studies on the risk of multi- hazards and uncertainties of hazard impacts under climate change, risk assessment of key exposure (critical infrastructure) in coastal hotspots, and cost-benefit analysis of adaptation and mitigation measures in coastal areas. Efforts to improve the resilience of coastal areas under climate change should be given more attention. The research community also should establish the mechanism of data sharing among disciplines to meet the needs of future risk assessments, so that coastal issues can be more comprehensively, systematically, and dynamically studied.

scholarly journals Development of an operational coastal flooding early warning system

2012 ◽  
Vol 12 (2) ◽  
pp. 379-390 ◽  
Author(s):  
D.-J. Doong ◽  
L. Z.-H. Chuang ◽  
L.-C. Wu ◽  
Y.-M. Fan ◽  
C. C. Kao ◽  
...  
Keyword(s):  
Storm Surge ◽  
Early Warning ◽  
System Integration ◽  
Early Warning System ◽  
Warning System ◽  
Wave Model ◽  
Warning Signal ◽  
Coastal Flooding ◽  
Economic Losses ◽  
Astronomical Tide

Abstract. Coastal floods are a consistent threat to oceanfront countries, causing major human suffering and substantial economic losses. Climate change is exacerbating the problem. An early warning system is essential to mitigate the loss of life and property from coastal flooding. The purpose of this study is to develop a coastal flooding early warning system (CoFEWs) by integrating existing sea-state monitoring technology, numerical ocean forecasting models, historical database and experiences, as well as computer science. The proposed system has capability of offering data for the past, information for the present and future. The system was developed for the Taiwanese coast due to its frequent threat by typhoons. An operational system without any manual work is the basic requirement of the system. Integration of various data sources is the system kernel. Numerical ocean models play an important role within the system because they provide data for assessment of possible flooding. The regional wave model (SWAN) that nested with the large domain wave model (NWW III) is operationally set up for coastal wave forecasting, in addition to the storm surge predicted by a POM model. Data assimilation technology is incorporated for enhanced accuracy. A warning signal is presented when the storm water level that accumulated from astronomical tide, storm surge, and wave-induced run-up exceeds the alarm sea level. This warning system has been in practical use for coastal flooding damage mitigation in Taiwan for years. An example of the system operation during the Typhoon Haitung which struck Taiwan in 2005 is illustrated in this study.

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