Correlation between extreme rainfall and insurance claims due to urban flooding – case study Fredrikstad, Norway

Torgersen, Geir

doi:10.4090/juee.2015.v9n2.127-138

Cited by 15 publications

(16 citation statements)

References 10 publications

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“…Our findings also align with the results of previous studies (Spekkers et al, 2013;Zhou et al, 2013;Wobus et al, 2014;Torgersen et al, 2015) and further indicate that insurance databases are a promising source for flood-damage assessment at the local (Garrote et al, 2016;Le Bihan et al, 2017;Zischg et al, 2018;Zhou et al, 2013) and regional scale (Barredo et al, 2012;Kim et al, 2012;Wobus et al, 2014;Zhou et al, 2017). However, using insurance data as a unique source for defining flood damage leads to only considering the direct and tangible damage.…”

Section: Valencian Communitysupporting

confidence: 90%

“…Future research should focus on incorporating further variables into the model to reproduce the complexity of flood risk, not only regarding hazard drivers but also considering more variables related to the exposure and vulnerability, as for example those related to the buildings present in the study region. Furthermore, the present study only focuses on daily precipitation data, while several studies point out the possible better relationship found between sub-daily data and insurance data in the case of surface water floods (Spekkers et al, 2013;Torgersen et al, 2015;. Nevertheless, the analysis of sub-daily extremes would require convectionpermitting regional climate models (Tramblay and Somot, 2018), and studies such as Beranová et al (2018) have shown that convection is not captured realistically.…”

Section: Limitations and Future Researchmentioning

confidence: 95%

“…In this section we have shown that precipitation is a key factor in explaining the damage caused by flood events in regions in which water surface floods are the main type of flood, as is the case in the Mediterranean region of study. Studies like Zhou et al (2013) and Torgersen et al (2015) also apply regression models to observe the relationship between different precipitation observation measures and the compensation paid by insurance companies. In both studies, a good correlation is observed between these two variables in the case of surface water floods, and it is shown that it is feasible to build models that explain the costs of damage as a simple function of precipitation (Zhou et al, 2013).…”

Section: Valencian Communitymentioning

confidence: 99%

“…Insurance data may provide a good proxy for describing flood damage (Barredo et al, 2012), and several studies note their potential for describing economic damage caused by surface water and urban floods (Spekkers et al, 2013;Torgersen et al, 2015;. However, there are still few studies that relate flooding to insurance data, since these companies are reluctant to provide their databases, and some of them are not even available due to confidentiality restrictions (André et al, 2013;Leal et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

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Changes in flood damage with global warming on the eastern coast of Spain

Cortès

Turco

Ward

et al. 2019

Nat. Hazards Earth Syst. Sci.

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Abstract. Flooding is one of the main natural hazards in the world and causes huge economic and human impacts. Assessing the flood damage in the Mediterranean region is of great importance, especially because of its large vulnerability to climate change. Most past floods affecting the region were caused by intense precipitation events; thus the analysis of the links between precipitation and flood damage is crucial. The main objective of this paper is to estimate changes in the probability of damaging flood events with global warming of 1.5, 2 and 3 ∘C above pre-industrial levels and taking into account different socioeconomic scenarios in two western Mediterranean regions, namely Catalonia and the Valencian Community. To do this, we analyse the relationship between heavy precipitation and flood-damage estimates from insurance datasets in those two regions. We consider an ensemble of seven regional climate model (RCM) simulations spanning the period 1976–2100 to evaluate precipitation changes and to drive a logistic model that links precipitation and flood-damage estimates, thus deriving statistics under present and future climates. Furthermore, we incorporate population projections based on five different socioeconomic scenarios. The results show a general increase in the probability of a damaging event for most of the cases and in both regions of study, with larger increments when higher warming is considered. Moreover, this increase is higher when both climate and population change are included. When population is considered, all the periods and models show a clearly higher increase in the probability of damaging events, which is statistically significant for most of the cases. Our findings highlight the need for limiting global warming as much as possible as well as the importance of including variables that consider change in both climate and socioeconomic conditions in the analysis of flood damage.

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Section: Valencian Communitysupporting

confidence: 90%

Section: Limitations and Future Researchmentioning

confidence: 95%

Section: Valencian Communitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Changes in flood damage with global warming on the eastern coast of Spain

Cortès

Turco

Ward

et al. 2019

Nat. Hazards Earth Syst. Sci.

View full text Add to dashboard Cite

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“…25% of the variance of claim frequency could be explained and that the three independent variables most strongly associated to claim frequency were maximum rain intensity, real estate value, and ground floor area. Torgersen, Bjerkholt, Kvaal, and Lindholm (2015) used insurance data and precipitation gauge data to analyse the relationship between extreme rainfall and insured flood damage for the period 2006-2012 in the city of Fredrikstad in south east Norway. The authors found a distinct peak of the a damage amount during the late summer months and the results further indicated that several hours of intense rainfall caused more damage than shorter, extreme rainfall events.…”

mentioning

confidence: 99%

The impact of intense rainfall on insurance losses in two Swedish cities

Blumenthal

Nyberg

2018

J Flood Risk Management

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While a major part of previous research in the field of flood damage has focused on water depth as the most important causal factor, little attention has been paid to the role of rainfall intensity. As a test, this paper used correlation and regression analyses to investigate rainfall intensity as a factor affecting flood damage. For a time period of 15 years, the relationship between insurance losses caused by floods and rainfall intensity data from rain gauges was examined in two Swedish cities. Another objective was to find an approach for damage functions based on rainfall intensity as explanatory variable. Using linear regression, two approaches with considerable high degrees of explanation were found–one based on an exponential function and one on a power function. Using a lower limit for rainfall intensity, the approaches reached degrees of explanation between 30 and 78%. From this study it was concluded that rainfall intensity during the summer months and the occurrence of insurance damages per day caused by floods were correlated and further that rainfall intensity has a great potential to explain urban flood damages. In the future, additional studies are needed to validate the proposed methods and integrate other flood damage affecting factors in the approach.

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Using Climate Factors to Estimate Flood Economic Loss Risk

Wang

et al. 2021

Int J Disaster Risk Sci

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Estimation of economic loss is essential for stakeholders to manage flood risk. Most flooding events are closely related to extreme precipitation, which is influenced by large-scale climate factors. Considering the lagged influence of climate factors, we developed a flood-risk assessment framework and used Hunan Province in China as an example to illustrate the risk assessment process. The main patterns of precipitation—as a connection between climate factors and flood economic losses—were extracted by the empirical orthogonal function (EOF) analysis. We identified the correlative climate factors through cross-correlation analysis and established a multiple stepwise linear regression model to forecast future precipitation patterns. Risk assessment was done based on the main precipitation patterns. Because the economic dataset is limited, a Monte Carlo simulation was applied to simulate 1000-year flood loss events under each precipitation regime (rainy, dry, normal years) to obtain aggregate exceedance probability (AEP) and occurrence exceedance probability (OEP) curves. We found that precipitation has a strong influence on economic loss risk, with the highest risk in rainy years. Regional economic development imbalances are the potential reason for the varying economic loss risks in different regions of Hunan Province. As the climate indices with at least several months prediction lead time are strong indicators in predicting precipitation, the framework we developed can estimate economic loss risk several months in advance.

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Correlation between extreme rainfall and insurance claims due to urban flooding – case study Fredrikstad, Norway

Cited by 15 publications

References 10 publications

Changes in flood damage with global warming on the eastern coast of Spain

Changes in flood damage with global warming on the eastern coast of Spain

The impact of intense rainfall on insurance losses in two Swedish cities

Using Climate Factors to Estimate Flood Economic Loss Risk

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