Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Hurricane Freshwater Flood Risk Assessment Model for Residential Buildings in Southeast US Coastal States Considering Climate Change
A significant amount of hurricane losses are caused by rainfall-induced freshwater flooding, and hurricane precipitation is expected to increase in the warming climate. However, the climate change impact on the hurricane rainfall-induced flood risk has not been investigated well yet, which leads to the potential increase in the flood risk in the future being overlooked. Investigation of future hurricane rainfall-induced flood risk can be very time-consuming because of the high resolution of the models for climate-dependent hazard simulation and regional loss assessment. Therefore, this study developed a statistical model for future hurricane freshwater flood loss assessment considering climate change scenarios by utilizing artificial neural networks (ANNs) and gradient boosting. Future hurricane freshwater flood risks to residential buildings in the southeastern US coastal states were investigated with the model. It was found that the hurricane rainfall–induced freshwater flood loss can increase by 16% and 30% from 2020 to 2030 and from 2090 to 2100, respectively. The investigation suggests the need to consider climate change impact on future flood risk management practices.
Hurricane Freshwater Flood Risk Assessment Model for Residential Buildings in Southeast US Coastal States Considering Climate Change
A significant amount of hurricane losses are caused by rainfall-induced freshwater flooding, and hurricane precipitation is expected to increase in the warming climate. However, the climate change impact on the hurricane rainfall-induced flood risk has not been investigated well yet, which leads to the potential increase in the flood risk in the future being overlooked. Investigation of future hurricane rainfall-induced flood risk can be very time-consuming because of the high resolution of the models for climate-dependent hazard simulation and regional loss assessment. Therefore, this study developed a statistical model for future hurricane freshwater flood loss assessment considering climate change scenarios by utilizing artificial neural networks (ANNs) and gradient boosting. Future hurricane freshwater flood risks to residential buildings in the southeastern US coastal states were investigated with the model. It was found that the hurricane rainfall–induced freshwater flood loss can increase by 16% and 30% from 2020 to 2030 and from 2090 to 2100, respectively. The investigation suggests the need to consider climate change impact on future flood risk management practices.
Hurricane Freshwater Flood Risk Assessment Model for Residential Buildings in Southeast US Coastal States Considering Climate Change
Lin, Chi-Ying (Autor:in) / Cha, Eun Jeong (Autor:in)
16.12.2020
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
| British Library Online Contents | 2017