Risk assessment of storm surge disaster based on numerical models and remote sensing

2018 ◽  
Vol 68 ◽  
pp. 20-30 ◽  
Author(s):  
Qingrong Liu ◽  
Chengqing Ruan ◽  
Shan Zhong ◽  
Jian Li ◽  
Zhonghui Yin ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Risk Assessment ◽  
Storm Surge ◽  
Numerical Models ◽  
Storm Surge Disaster

scholarly journals Storm surge disaster risk assessment and zoning, taking Cangnan County for instance

2017 ◽  
Vol 25 ◽  
pp. 92-99
Author(s):  
Tao Li ◽  
Cifu Fu ◽  
Fangdong Wang ◽  
Jianxi Dong
Keyword(s):  
Risk Assessment ◽  
Storm Surge ◽  
Disaster Risk ◽  
Disaster Risk Assessment ◽  
Storm Surge Disaster

scholarly journals Fine-Scale Coastal Storm Surge Disaster Vulnerability and Risk Assessment Model: A Case Study of Laizhou Bay, China

2020 ◽  
Vol 12 (8) ◽  
pp. 1301 ◽  
Author(s):  
Yueming Liu ◽  
Chen Lu ◽  
Xiaomei Yang ◽  
Zhihua Wang ◽  
Bin Liu
Keyword(s):  
Risk Assessment ◽  
Storm Surge ◽  
Storm Surges ◽  
Assessment Model ◽  
Storm Water ◽  
Laizhou Bay ◽  
Risk Assessment Model ◽  
Fine Scale ◽  
Disaster Vulnerability ◽  
Storm Surge Disaster

In the assessment of storm surge vulnerability, existing studies have often selected several types of disaster-bearing bodies and assessed their exposure. In reality, however, storm surges impact all types of disaster-bearing bodies in coastal and estuarine areas. Therefore, all types of disaster-bearing bodies exposed to storm surges should be considered when assessing exposure. In addition, geographical factors will also have an impact on the exposure of the affected bodies, and thus need to be fully considered. Hence, we propose a fine-scale coastal storm surge disaster vulnerability and risk assessment model. First, fine-scale land-use data were obtained based on high-resolution remote sensing images. Combined with natural geographic factors, such as the digital elevation model (DEM), slope, and distance to water, the exposure of the disaster-bearing bodies in each geographic unit of the coastal zone was comprehensively determined. A total of five indicators, such as the percentage of females and ratio of fishery products to the gross domestic product (GDP), were then selected to assess sensitivity. In addition, six indicators, including GDP and general public budget expenditure, were selected to assess adaptability. Utilizing the indicators constructed from exposure, sensitivity, and adaptability, a vulnerability assessment was performed in the coastal area of Laizhou Bay, China, which is at high risk from storm surges. Furthermore, the storm surge risk assessment was achieved in combination with storm water statistics. The results revealed that the Kenli District, Changyi City, and the Hanting District have a higher risk of storm surge and require more attention during storm surges. The storm surge vulnerability and risk assessment model proposed in this experiment fully considers the impact of the natural environment on the exposure indicators of the coastal zone’s disaster-bearing bodies, and combines sensitivity, adaptability indicators, and storm water record data to conduct vulnerability and risk assessment. At the same time, the model proposed in this study can also realize multi-scale assessment of storm surge vulnerability and risk based on different scales of socioeconomic statistical data, which has the advantages of flexibility and ease of operation.

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.

Storm surge risk assessment method for a coastal county in China: case study of Jinshan District, Shanghai

2020 ◽  
Vol 34 (5) ◽  
pp. 627-640 ◽  
Author(s):  
Shi Xianwu ◽  
Qiu Jufei ◽  
Chen Bingrui ◽  
Zhang Xiaojie ◽  
Guo Haoshuang ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Storm Surge ◽  
Assessment Method ◽  
Risk Assessment Method ◽  
Coastal County

scholarly journals Remote Sensing Supported Sea Surface pCO2 Estimation and Variable Analysis in the Baltic Sea

2021 ◽  
Vol 13 (2) ◽  
pp. 259
Author(s):  
Shuping Zhang ◽  
Anna Rutgersson ◽  
Petra Philipson ◽  
Marcus B. Wallin
Keyword(s):  
Remote Sensing ◽  
Baltic Sea ◽  
Mean Squared Error ◽  
Numerical Models ◽  
Mixed Layer Depth ◽  
Sea Surface ◽  
The Baltic Sea ◽  
Chl A ◽  
Marginal Seas ◽  
The Baltic

Marginal seas are a dynamic and still to large extent uncertain component of the global carbon cycle. The large temporal and spatial variations of sea-surface partial pressure of carbon dioxide (pCO2) in these areas are driven by multiple complex mechanisms. In this study, we analyzed the variable importance for the sea surface pCO2 estimation in the Baltic Sea and derived monthly pCO2 maps for the marginal sea during the period of July 2002–October 2011. We used variables obtained from remote sensing images and numerical models. The random forest algorithm was employed to construct regression models for pCO2 estimation and produce the importance of different input variables. The study found that photosynthetically available radiation (PAR) was the most important variable for the pCO2 estimation across the entire Baltic Sea, followed by sea surface temperature (SST), absorption of colored dissolved organic matter (aCDOM), and mixed layer depth (MLD). Interestingly, Chlorophyll-a concentration (Chl-a) and the diffuse attenuation coefficient for downwelling irradiance at 490 nm (Kd_490nm) showed relatively low importance for the pCO2 estimation. This was mainly attributed to the high correlation of Chl-a and Kd_490nm to other pCO2-relevant variables (e.g., aCDOM), particularly in the summer months. In addition, the variables’ importance for pCO2 estimation varied between seasons and sub-basins. For example, the importance of aCDOM were large in the Gulf of Finland but marginal in other sub-basins. The model for pCO2 estimate in the entire Baltic Sea explained 63% of the variation and had a root of mean squared error (RMSE) of 47.8 µatm. The pCO2 maps derived with this model displayed realistic seasonal variations and spatial features of sea surface pCO2 in the Baltic Sea. The spatially and seasonally varying variables’ importance for the pCO2 estimation shed light on the heterogeneities in the biogeochemical and physical processes driving the carbon cycling in the Baltic Sea and can serve as an important basis for future pCO2 estimation in marginal seas using remote sensing techniques. The pCO2 maps derived in this study provided a robust benchmark for understanding the spatiotemporal patterns of CO2 air-sea exchange in the Baltic Sea.

scholarly journals Assessing storm surge hazard and impact of sea level rise in the Lesser Antilles case study of Martinique

2017 ◽  
Vol 17 (9) ◽  
pp. 1559-1571 ◽  
Author(s):  
Yann Krien ◽  
Bernard Dudon ◽  
Jean Roger ◽  
Gael Arnaud ◽  
Narcisse Zahibo
Keyword(s):  
Sea Level Rise ◽  
Sea Level ◽  
Storm Surge ◽  
Numerical Models ◽  
Lesser Antilles ◽  
Adaptation Measures ◽  
Worst Case ◽  
Mitigation And Adaptation ◽  
The Impact

Abstract. In the Lesser Antilles, coastal inundations from hurricane-induced storm surges pose a great threat to lives, properties and ecosystems. Assessing current and future storm surge hazards with sufficient spatial resolution is of primary interest to help coastal planners and decision makers develop mitigation and adaptation measures. Here, we use wave–current numerical models and statistical methods to investigate worst case scenarios and 100-year surge levels for the case study of Martinique under present climate or considering a potential sea level rise. Results confirm that the wave setup plays a major role in the Lesser Antilles, where the narrow island shelf impedes the piling-up of large amounts of wind-driven water on the shoreline during extreme events. The radiation stress gradients thus contribute significantly to the total surge – up to 100 % in some cases. The nonlinear interactions of sea level rise (SLR) with bathymetry and topography are generally found to be relatively small in Martinique but can reach several tens of centimeters in low-lying areas where the inundation extent is strongly enhanced compared to present conditions. These findings further emphasize the importance of waves for developing operational storm surge warning systems in the Lesser Antilles and encourage caution when using static methods to assess the impact of sea level rise on storm surge hazard.

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