scholarly journals Probabilistic Flood Loss Models for Companies

2020 ◽  
Author(s):  
Lukas Schoppa ◽  
Tobias Sieg ◽  
Kristin Vogel ◽  
Gert Zöller ◽  
Heidi Kreibich
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
Loss Estimation ◽  
Flood Risk Assessment ◽  
Damage Functions ◽  
Flood Loss ◽  
Loss Data ◽  
Multivariable Models ◽  
Loss Models ◽  
Estimation Models

<p>Flood risk assessment strongly relies on accurate and reliable estimation of monetary flood loss. Conventionally, this involves univariable deterministic stage-damage functions. Recent advancements in the field promote the use of multivariable probabilistic loss estimation models which consider damage controlling variables beyond inundation depth. Although companies contribute significantly to total loss figures, multivariable probabilistic modeling approaches for companies are lacking. Scarce data and heterogeneity among companies impedes the development of novel company flood loss models.</p><p>We present three multivariable flood loss estimation models for companies that intrinsically quantify prediction uncertainty. Based on object-level loss data (n=1306), we comparatively evaluate the predictive performance of Bayesian networks, Bayesian regression and random forest in relation to established stage-damage functions. The company loss data stems from four post-event surveys after major floods in Germany between 2002 and 2013 and comprises information on flood intensity, company characteristics and private precaution. We examine the performance of the candidate models separately for losses to building, equipment, and goods and stock. Plausibility checks show that the multivariable models are able to identify and reproduce essential relationships of the flood damage processes from the data. The comparison of the prediction capacity reveals that the proposed models outperform stage-damage functions clearly while differences among the multivariable models are small. Even though the presented models improve the accuracy of loss predictions, wide predictive distributions underline the necessity for the quantification of predictive uncertainty. This applies particularly to companies, for which the heterogeneity and variation in the loss data are more pronounced than for private households. Due to their probabilistic nature, the presented multivariable models contribute towards a transparent treatment of uncertainties in flood risk assessment.</p>

scholarly journals Adaptability and transferability of flood loss functions in residential areas

2013 ◽  
Vol 1 (4) ◽  
pp. 3485-3527 ◽  
Author(s):  
H. Cammerer ◽  
A. H. Thieken ◽  
J. Lammel
Keyword(s):  
Flood Risk ◽  
Residential Buildings ◽  
Model Development ◽  
Loss Functions ◽  
Residential Areas ◽  
Damage Functions ◽  
Residential Sector ◽  
Geographical Regions ◽  
Flood Loss ◽  
Loss Data

Abstract. Flood loss modeling is an important component within flood risk assessments. Traditionally, stage-damage functions are used for the estimation of direct monetary damage to buildings. Although it is known that such functions are governed by large uncertainties, they are commonly applied – even in different geographical regions – without further validation, mainly due to the lack of data. Until now, little research has been done to investigate the applicability and transferability of such damage models to other regions. In this study, the last severe flood event in the Austrian Lech Valley in 2005 was simulated to test the performance of various damage functions for the residential sector. In addition to common stage-damage curves, new functions were derived from empirical flood loss data collected in the aftermath of recent flood events in the neighboring Germany. Furthermore, a multi-parameter flood loss model for the residential sector was adapted to the study area and also evaluated by official damage data. The analysis reveals that flood loss functions derived from related and homogenous regions perform considerably better than those from more heterogeneous datasets. To illustrate the effect of model choice on the resulting uncertainty of damage estimates, the current flood risk for residential areas was assessed. In case of extreme events like the 300 yr flood, for example, the range of losses to residential buildings between the highest and the lowest estimates amounts to a factor of 18, in contrast to properly validated models with a factor of 2.3. Even if the risk analysis is only performed for residential areas, more attention should be paid to flood loss assessments in future. To increase the reliability of damage modeling, more loss data for model development and validation are needed.

scholarly journals Flood Hazard, Vulnerability and Risk Assessment for Different Land Use Classes Using a Flow Model

2019 ◽  
Vol 4 (1) ◽  
pp. 225-244 ◽  
Author(s):  
Md Abdullah Al Baky ◽  
Muktarun Islam ◽  
Supria Paul
Keyword(s):  
Risk Assessment ◽  
Critical Point ◽  
Return Period ◽  
Flood Risk ◽  
Flood Hazard ◽  
Flow Simulation ◽  
Flood Risk Assessment ◽  
Damage Functions ◽  
Flood Vulnerability ◽  
Different Levels

AbstractThis study is concerned with flood risk that can be assessed by integrating GIS, hydraulic modelling and required field information. A critical point in flood risk assessment is that while flood hazard is the same for a given area in terms of intensity, the risk could be different depending on a set of conditions (flood vulnerability). Clearly, risk is a function of hazard and vulnerability. This study aims to introducing a new approach of assessing flood risk, which successfully addresses this above-mentioned critical issue. The flood risk was assessed from flood hazard and vulnerability indices. Two-dimensional flood flow simulation was performed with Delft3D model to compute floodplain inundation depths for hazard assessment. For the purpose of flood vulnerability assessment, elements at risk and flood damage functions were identified and assessed, respectively. Then, finally flood risk was assessed first by combining replacement values assessed for the elements and then using the depth–damage function. Applying this approach, the study finds that areas with different levels of flood risk do not always increase with the increase in return period of flood. However, inundated areas with different levels of flood depth always increase with the increase in return period of flood. The approach for flood risk assessment adopted in this study successfully addresses the critical point in flood risk study, where flood risk can be varied even after there is no change in flood hazard intensity.

scholarly journals Adaptability and transferability of flood loss functions in residential areas

2013 ◽  
Vol 13 (11) ◽  
pp. 3063-3081 ◽  
Author(s):  
H. Cammerer ◽  
A. H. Thieken ◽  
J. Lammel
Keyword(s):  
Flood Risk ◽  
Loss Functions ◽  
Flood Events ◽  
Residential Areas ◽  
Damage Functions ◽  
Residential Sector ◽  
Geographical Regions ◽  
Flood Loss ◽  
Loss Data ◽  
Damage Data

Abstract. Flood loss modeling is an important component within flood risk assessments. Traditionally, stage-damage functions are used for the estimation of direct monetary damage to buildings. Although it is known that such functions are governed by large uncertainties, they are commonly applied – even in different geographical regions – without further validation, mainly due to the lack of real damage data. Until now, little research has been done to investigate the applicability and transferability of such damage models to other regions. In this study, the last severe flood event in the Austrian Lech Valley in 2005 was simulated to test the performance of various damage functions from different geographical regions in Central Europe for the residential sector. In addition to common stage-damage curves, new functions were derived from empirical flood loss data collected in the aftermath of recent flood events in neighboring Germany. Furthermore, a multi-parameter flood loss model for the residential sector was adapted to the study area and also evaluated with official damage data. The analysis reveals that flood loss functions derived from related and more similar regions perform considerably better than those from more heterogeneous data sets of different regions and flood events. While former loss functions estimate the observed damage well, the latter overestimate the reported loss clearly. To illustrate the effect of model choice on the resulting uncertainty of damage estimates, the current flood risk for residential areas was calculated. In the case of extreme events like the 300 yr flood, for example, the range of losses to residential buildings between the highest and the lowest estimates amounts to a factor of 18, in contrast to properly validated models with a factor of 2.3. Even if the risk analysis is only performed for residential areas, our results reveal evidently that a carefree model transfer in other geographical regions might be critical. Therefore, we conclude that loss models should at least be selected or derived from related regions with similar flood and building characteristics, as far as no model validation is possible. To further increase the general reliability of flood loss assessment in the future, more loss data and more comprehensive loss data for model development and validation are needed.

scholarly journals Development of damage functions for flood risk assessment in the city of Colombo (Sri Lanka)

2018 ◽  
Vol 212 ◽  
pp. 332-339 ◽  
Author(s):  
Priyan Dias ◽  
N.M.S.I. Arambepola ◽  
Kumari Weerasinghe ◽  
K.D.N. Weerasinghe ◽  
Dennis Wagenaar ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Sri Lanka ◽  
Flood Risk ◽  
Flood Risk Assessment ◽  
Damage Functions ◽  
The City

Flood Risk Assessment and Forecasting for the Ganges-Brahmaputra-Meghna River Basins

10.1596/28574 ◽  
2017 ◽  
Author(s):  
Satya Priya ◽  
William Young ◽  
Thomas Hopson ◽  
Ankit Avasthi
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
River Basins ◽  
Flood Risk Assessment ◽  
The Ganges

scholarly journals Method for fluvial and pluvial flood risk assessment in rural settlements

MethodsX ◽  
2021 ◽  
pp. 101463
Author(s):  
Maurizio Tiepolo ◽  
Elena Belcore ◽  
Sarah Braccio ◽  
Souradji Issa ◽  
Giovanni Massazza ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
Flood Risk Assessment ◽  
Rural Settlements

scholarly journals An Integrated Flood Risk Assessment Model for Cities Located in the Transitional Zone between Taihang Mountains and North China Plain: A Case Study in Shijiazhuang, Hebei, China

Atmosphere ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 104 ◽  
Author(s):  
Qiang Liu ◽  
Hongmao Yang ◽  
Min Liu ◽  
Rui Sun ◽  
Junhai Zhang
Keyword(s):  
Risk Assessment ◽  
Flood Risk ◽  
North China Plain ◽  
North China ◽  
Transitional Zone ◽  
Assessment Model ◽  
Analysis Tool ◽  
Risk Assessment Model ◽  
Flood Risk Assessment ◽  
Risk Map

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.

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