Hurricane Freshwater Flood Risk Assessment Model for Residential Buildings in Southeast US Coastal States Considering Climate Change

2021 ◽  
Vol 22 (2) ◽  
pp. 04020061
Author(s):  
Chi-Ying Lin ◽  
Eun Jeong Cha
Atmosphere ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 104 ◽  
Author(s):  
Qiang Liu ◽  
Hongmao Yang ◽  
Min Liu ◽  
Rui Sun ◽  
Junhai Zhang

Cities located in the transitional zone between Taihang Mountains and North China plain run high flood risk in recent years, especially urban waterlogging risk. In this paper, we take Shijiazhuang, which is located in this transitional zone, as the study area and proposed a new flood risk assessment model for this specific geographical environment. Flood risk assessment indicator factors are established by using the digital elevation model (DEM), along with land cover, economic, population, and precipitation data. A min-max normalization method is used to normalize the indices. An analytic hierarchy process (AHP) method is used to determine the weight of each normalized index and the geographic information system (GIS) spatial analysis tool is adopted for calculating the risk map of flood disaster in Shijiazhuang. This risk map is consistent with the reports released by Hebei Provincial Water Conservancy Bureau and can provide reference for flood risk management.


2011 ◽  
Vol 58 (3) ◽  
pp. 1295-1309 ◽  
Author(s):  
Wen-Ko Hsu ◽  
Pei-Chiung Huang ◽  
Ching-Cheng Chang ◽  
Cheng-Wu Chen ◽  
Dung-Moung Hung ◽  
...  

2012 ◽  
Vol 12 (5) ◽  
pp. 75-81 ◽  
Author(s):  
Jin Gul Joo ◽  
Jung Ho Lee ◽  
Moo Jong Park

2017 ◽  
Vol 9 (11) ◽  
pp. 2005 ◽  
Author(s):  
Jieun Ryu ◽  
Eun Joo Yoon ◽  
Chan Park ◽  
Dong Kun Lee ◽  
Seong Woo Jeon

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 420
Author(s):  
Zening Wu ◽  
Yuhai Cui ◽  
Yuan Guo

With the progression of climate change, the intensity and frequency of extreme rainfall have increased in many parts of the world, while the continuous acceleration of urbanization has made cities more vulnerable to floods. In order to effectively estimate and assess the risks brought by flood disasters, this paper proposes a regional flood disaster risk assessment model combining emergy theory and the cloud model. The emergy theory can measure many kinds of hazardous factor and convert them into unified solar emergy (sej) for quantification. The cloud model can transform the uncertainty in flood risk assessment into certainty in an appropriate way, making the urban flood risk assessment more accurate and effective. In this study, the flood risk assessment model combines the advantages of the two research methods to establish a natural and social dual flood risk assessment system. Based on this, the risk assessment system of the flood hazard cloud model is established. This model was used in a flood disaster risk assessment, and the risk level was divided into five levels: very low risk, low risk, medium risk, high risk, and very high risk. Flood hazard risk results were obtained by using the entropy weight method and fuzzy transformation method. As an example for the application of this model, this paper focuses on the Anyang region which has a typical continental monsoon climate. The results show that the Anyang region has a serious flood disaster threat. Within this region, Linzhou County and Anyang County have very high levels of risk for flood disaster, while Hua County, Neihuang County, Wenfeng District and Beiguan District have high levels of risk for flood disaster. These areas are the core urban areas and the economic center of local administrative regions, with 70% of the industrial clusters being situated in these regions. Only with the coordinated development of regional flood control planning, economy, and population, and reductions in the uncertainty of existing flood control and drainage facilities can the sustainable, healthy and stable development of the region be maintained.


Author(s):  
Michalis I. Vousdoukas ◽  
Dimitrios Bouziotas ◽  
Alessio Giardino ◽  
Laurens M. Bouwer ◽  
Evangelos Voukouvalas ◽  
...  

Abstract. An upscaling of flood risk assessment frameworks beyond regional and national scales has taken place during recent years, with a number of large-scale models emerging as tools for hotspot identification, support for international policy-making and harmonization of climate change adaptation strategies. There is, however, limited insight on the scaling effects and structural limitations of flood risk models and, therefore, the underlying uncertainty. In light of this, we examine key sources of epistemic uncertainty in the Coastal Flood Risk (CFR) modelling chain: (i) the inclusion and interaction of different hydraulic components leading to extreme sea-level (ESL); (ii) inundation modelling; (iii) the underlying uncertainty in the Digital Elevation Model (DEM); (iv) flood defence information; (v) the assumptions behind the use of depth-damage functions that express vulnerability; and (vi) different climate change projections. The impact of these uncertainties to estimated Expected Annual Damage (EAD) for present and future climates is evaluated in a dual case study in Faro, Portugal and in the Iberian Peninsula. The ranking of the uncertainty factors varies among the different case studies, baseline CFR estimates, as well as their absolute/relative changes. We find that uncertainty from ESL contributions, and in particular the way waves are treated, can be higher than the uncertainty of the two greenhouse gas emission projections and six climate models that are used. Of comparable importance is the quality of information on coastal protection levels and DEM information. In the absence of large-extent datasets with sufficient resolution and accuracy the latter two factors are the main bottlenecks in terms of large-scale CFR assessment quality.


2016 ◽  
Vol 11 (6) ◽  
pp. 1128-1136 ◽  
Author(s):  
Youngjoo Kwak ◽  
◽  
Yoichi Iwami ◽  

Globally, large-scale floods are one of the most serious disasters, considering increased frequency and intensity of heavy rainfall. This is not only a domestic problem but also an international water issue related to transboundary rivers in terms of global river flood risk assessment. The purpose of this study is to propose a rapid flood hazard model as a methodological possibility to be used on a global scale, which uses flood inundation depth and works reasonably despite low data availability. The method is designed to effectively simplify complexities involving hydrological and topographical variables in a flood risk-prone area when applied in an integrated global flood risk assessment framework. The model was used to evaluate flood hazard and exposure through pixel-based comparison in the case of extreme flood events caused by an annual maximum daily river discharge of 1/50 probability of occurrence under the condition of climate change between two periods, Present (daily data from 1980 to 2004) and Future (daily data from 2075 to 2099). As preliminary results, the maximum potential extent of inundation area and the maximum number of affected people show an upward trend in Present and Future.


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