The Impact of Distant Hurricanes on Perception of Flood Risk in Local Housing Markets

2020 ◽  
Author(s):  
Lu Fang ◽  
Lingxiao Li ◽  
Abdullah Yavas
Keyword(s):  
Flood Risk ◽  
Housing Markets ◽  
The Impact

Vulnerability to Natural Disaster and Welfare Effect: A Case Study of Flood Risk in Vietnam’s North Central Region

2021 ◽  
pp. 002190962199349
Author(s):  
Manh-Hung Nguyen ◽  
Dung P Le ◽  
Thang T Vo
Keyword(s):  
Flood Risk ◽  
Sampling Method ◽  
Household Survey ◽  
North Central ◽  
Household Level ◽  
Central Vietnam ◽  
Housing Costs ◽  
Household Vulnerability ◽  
The Impact

This article investigates the impact of flood risk on vulnerability and welfare at the household level in Vietnam. The analytical sample is taken from a household survey conducted in a north central Vietnam community through a three-stage stratified random sampling method. The propensity score matching approach is employed to compare various welfare indicators between flooded and non-flooded households. This study finds that flooding results in significant income losses and imposes higher costs of living, especially housing costs. The two types of households are vulnerable, implying that other natural disasters or socio-economic disadvantages may have adverse effects on households’ livelihoods. The insignificant effect of floods on vulnerability indicates that the flooded households can cope with floods to some extent. However, contrary to family support, formal coping strategies are insufficient or ineffective at reducing household vulnerability to floods.

scholarly journals The Impact of Single-Family Rental REITs on Regional Housing Markets: A Case Study of Nashville, TN

Societies ◽  
2018 ◽  
Vol 8 (4) ◽  
pp. 93 ◽  
Author(s):  
Ken Chilton ◽  
Robert Silverman ◽  
Rabia Chaudhrey ◽  
Chihaungji Wang
Keyword(s):  
Real Estate ◽  
Census Data ◽  
Housing Markets ◽  
Future Research ◽  
Individual Investors ◽  
Single Family ◽  
Real Estate Investment ◽  
Wealth Concentration ◽  
The Impact ◽  
The U.S

The U.S. Congress authorized the creation of real estate investment trusts (REITs) in 1960 so companies could develop publically traded real estate investment portfolios. REITs focus on commercial property, retail property, and rental property. During the last decade, REITs became more active in regional housing markets across the U.S. Single-family rental (SFR) REITs have grown tremendously, buying up residential properties across the country. In some regional housing markets, SFR REITs own noticeable shares of single-family homes. In those settings, SFR REITs take large numbers of housing units off of real estate markets where homeownership transactions occur and manage these properties as part of commercial rental inventories. This has resulted in a new category of multiple property owners, composed of institutional investors as opposed to individual investors, which further exacerbates property wealth concentration and polarization. This study examines the socio–spatial distribution of properties in SFR REIT portfolios to determine if SFR REIT properties tend to cluster in distinct areas. This study will focus on the regional housing market in Nashville, TN. Nashville has one of the most active SFR REIT sectors in the country. County tax assessor records were used to identify SFR REIT properties. These data were joined with U.S. Census data to create a profile of communities. The data were analyzed using SPSS statistical software and GIS software. Our analysis suggests that neighborhoods with clusters of SFR REITs fit the SFR REIT business model. Clusters occur in communities with newer homes, residents with higher levels of educational attainment, and middle to upper-middle incomes. The paper concludes with several recommendations for future research on SFR REITs.

scholarly journals Understanding epistemic uncertainty in large-scale coastal flood risk assessment for present and future climates

2018 ◽  
Author(s):  
Michalis I. Vousdoukas ◽  
Dimitrios Bouziotas ◽  
Alessio Giardino ◽  
Laurens M. Bouwer ◽  
Evangelos Voukouvalas ◽  
...  
Keyword(s):  
Climate Change ◽  
Risk Assessment ◽  
Flood Risk ◽  
Large Scale ◽  
Epistemic Uncertainty ◽  
Coastal Protection ◽  
Flood Risk Assessment ◽  
Coastal Flood ◽  
Coastal Flood Risk ◽  
The Impact

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.

scholarly journals Analysis of Flood Risk of Urban Agglomeration Polders Using Multivariate Copula

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1470 ◽  
Author(s):  
Yuqin Gao ◽  
Dongdong Wang ◽  
Zhenxing Zhang ◽  
Zhenzhen Ma ◽  
Zichen Guo ◽  
...  
Keyword(s):  
Water Level ◽  
River Basin ◽  
Flood Risk ◽  
Eastern China ◽  
Urban Agglomeration ◽  
Dependence Structure ◽  
Flood Risks ◽  
The Impact ◽  
Flood Characteristics ◽  
Qinhuai River

Urban agglomeration polders (UAPs) are often used to control flooding in eastern China. The impacts of UAPs on individual flood events have been extensively examined, but how flood risks are influenced by UAPs is much less examined. This study aimed to explore a three-dimensional joint distribution of annual flood volume, peak flow and water level to examine UAPs’ impact on flood risks based on hydrological simulations. The dependence between pairwise hydrological characteristics are measured by rank correlation coefficients and graphs. An Archimedean Copula is applied to model the dependence structure. This approach is applied to the Qinhuai River Basin where UAPs are used proactively for flood control. The result shows that the Frank Copula can better represent the dependence structure in the Qinhuai River Basin. UAPs increase risks of individual flood characteristics and integrated risks. UAPs have a relatively greater impact on water level than the other two flood characteristics. It is noted that the impact on flood risk levels off for greater floods.

scholarly journals Large-scale application of the flood damage model RAilway Infrastructure Loss (RAIL)

2016 ◽  
Vol 16 (11) ◽  
pp. 2357-2371 ◽  
Author(s):  
Patric Kellermann ◽  
Christine Schönberger ◽  
Annegret H. Thieken
Keyword(s):  
Risk Management ◽  
Risk Aversion ◽  
Flood Risk ◽  
Structural Damage ◽  
Large Scale ◽  
Damage Model ◽  
Flood Damage ◽  
Railway Infrastructure ◽  
Increased Risk ◽  
The Impact

Abstract. Experience has shown that river floods can significantly hamper the reliability of railway networks and cause extensive structural damage and disruption. As a result, the national railway operator in Austria had to cope with financial losses of more than EUR 100 million due to flooding in recent years. Comprehensive information on potential flood risk hot spots as well as on expected flood damage in Austria is therefore needed for strategic flood risk management. In view of this, the flood damage model RAIL (RAilway Infrastructure Loss) was applied to estimate (1) the expected structural flood damage and (2) the resulting repair costs of railway infrastructure due to a 30-, 100- and 300-year flood in the Austrian Mur River catchment. The results were then used to calculate the expected annual damage of the railway subnetwork and subsequently analysed in terms of their sensitivity to key model assumptions. Additionally, the impact of risk aversion on the estimates was investigated, and the overall results were briefly discussed against the background of climate change and possibly resulting changes in flood risk. The findings indicate that the RAIL model is capable of supporting decision-making in risk management by providing comprehensive risk information on the catchment level. It is furthermore demonstrated that an increased risk aversion of the railway operator has a marked influence on flood damage estimates for the study area and, hence, should be considered with regard to the development of risk management strategies.

scholarly journals Understanding the impact of climate change on inland flood risk in the UK

Weather ◽  
2021 ◽  
Vol 76 (10) ◽  
pp. 330-331
Author(s):  
Linda Speight ◽  
Karolina Krupska
Keyword(s):  
Climate Change ◽  
Flood Risk ◽  
Impact Of Climate Change ◽  
The Uk ◽  
The Impact

Estimates of future flood risk in Western Europe and its potential impact on insured losses.

2021 ◽  
Author(s):  
Remi Meynadier ◽  
Hugo Rakotoarimanga ◽  
Madeleine-Sophie Deroche ◽  
Sylvain Buisine
Keyword(s):  
Climate Change ◽  
Flood Risk ◽  
Large Scale ◽  
Western Europe ◽  
Complex Nature ◽  
Flood Risks ◽  
Hazard Exposure ◽  
Modelling Framework ◽  
Loss Modelling ◽  
The Impact

<p>The large-scale and complex nature of climate change makes it difficult to assess and quantify the impact on insurance activities. Climate change is likely affecting the probability of natural hazard occurrence in terms of severity and/or frequency.</p><p>Natural catastrophe risk is a function of hazard, exposure and vulnerability. As a (re)-insurer it is seen that changes in year-on-year losses are a function of all these components and not just the hazard.</p><p>The present study focuses, in a first step, on assessing impacts of climate change on fluvial flood risks in Europe solely due to changes in hazard itself. A stochastic catalogue of future flood risk events is derived from Pan-European data sets of river flood probability of occurrence produced within EU FP7 RAIN project. The loss modelling framework internally developed at AXA is then used to provide a geographical view of changes in future flood risks.</p><p> </p>

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