scholarly journals INSYDE-BE: Adaptation of the INSYDE model to the Walloon Region (Belgium)

2021 ◽  
Author(s):  
Anna Rita Scorzini ◽  
Benjamin Dewals ◽  
Daniela Rodriguez Castro ◽  
Pierre Archambeau ◽  
Daniela Molinari
Keyword(s):  
Flood Risk ◽  
Damage Model ◽  
Flood Damage ◽  
Original Model ◽  
Risk Assessments ◽  
Damage Functions ◽  
Residential Sector ◽  
Damage Models ◽  
Similarities And Differences ◽  
Walloon Region

Abstract. The spatial transfer of flood damage models among regions and countries is a challenging but unavoidable approach, for performing flood risk assessments in data and model scarce regions. In these cases, similarities and differences between the contexts of application should be considered to obtain reliable damage estimations and, in some cases, the adaptation of the original model to the new conditions is required. This study exemplifies a replicable procedure for the adaptation to the Belgian context of a multi-variable, synthetic flood damage model for the residential sector originally developed for Italy (INSYDE). The study illustrates necessary amendments in model assumptions, especially regarding input default values for the hazard and building parameters and damage functions describing the modelled damage mechanisms.

scholarly journals Comparative flood damage model assessment: towards a European approach

2012 ◽  
Vol 12 (12) ◽  
pp. 3733-3752 ◽  
Author(s):  
B. Jongman ◽  
H. Kreibich ◽  
H. Apel ◽  
J. I. Barredo ◽  
P. D. Bates ◽  
...  
Keyword(s):  
Large Scale ◽  
Best Practice ◽  
Damage Model ◽  
Flood Damage ◽  
Model Assessment ◽  
Care Needs ◽  
Damage Functions ◽  
Damage Models ◽  
European Approach ◽  
Asset Values

Abstract. There is a wide variety of flood damage models in use internationally, differing substantially in their approaches and economic estimates. Since these models are being used more and more as a basis for investment and planning decisions on an increasingly large scale, there is a need to reduce the uncertainties involved and develop a harmonised European approach, in particular with respect to the EU Flood Risks Directive. In this paper we present a qualitative and quantitative assessment of seven flood damage models, using two case studies of past flood events in Germany and the United Kingdom. The qualitative analysis shows that modelling approaches vary strongly, and that current methodologies for estimating infrastructural damage are not as well developed as methodologies for the estimation of damage to buildings. The quantitative results show that the model outcomes are very sensitive to uncertainty in both vulnerability (i.e. depth–damage functions) and exposure (i.e. asset values), whereby the first has a larger effect than the latter. We conclude that care needs to be taken when using aggregated land use data for flood risk assessment, and that it is essential to adjust asset values to the regional economic situation and property characteristics. We call for the development of a flexible but consistent European framework that applies best practice from existing models while providing room for including necessary regional adjustments.

scholarly journals INSYDE: a synthetic, probabilistic flood damage model based on explicit cost analysis

2016 ◽  
Author(s):  
Francesco Dottori ◽  
Rui Figueiredo ◽  
Mario Martina ◽  
Daniela Molinari ◽  
Anna Rita Scorzini
Keyword(s):  
Damage Assessment ◽  
Damage Model ◽  
Flood Damage ◽  
Physical Damage ◽  
Damage Functions ◽  
Technical Literature ◽  
Actual Knowledge ◽  
Damage Models ◽  
Model Based ◽  
Risk Assessment And Management

Abstract. Methodologies to estimate economic flood damages are increasingly important for flood risk assessment and management. In this work, we present a new synthetic flood damage model based on a component-by-component analysis of physical damage to buildings. The damage functions are designed using an expert-based approach with the support of existing scientific and technical literature, and have been calibrated with loss adjustment studies and damage surveys carried out for past flood events in Italy. The model structure is designed to be transparent and flexible, and therefore it can be applied in different geographical contexts and adapted to the actual knowledge of hazard and vulnerability variables. The model has been tested in a recent flood event in Northern Italy. Validation results provided good estimates of post-event damages, with better performances than most damage models available in the literature. In addition, a local sensitivity analysis has been performed, in order to identify the hazard variables that have more influence on damage assessment results.

scholarly journals INSYDE: a synthetic, probabilistic flood damage model based on explicit cost analysis

2016 ◽  
Vol 16 (12) ◽  
pp. 2577-2591 ◽  
Author(s):  
Francesco Dottori ◽  
Rui Figueiredo ◽  
Mario L. V. Martina ◽  
Daniela Molinari ◽  
Anna Rita Scorzini
Keyword(s):  
Damage Assessment ◽  
Damage Model ◽  
Flood Damage ◽  
Physical Damage ◽  
Damage Functions ◽  
Technical Literature ◽  
Actual Knowledge ◽  
Damage Models ◽  
Model Based ◽  
Risk Assessment And Management

Abstract. Methodologies to estimate economic flood damages are increasingly important for flood risk assessment and management. In this work, we present a new synthetic flood damage model based on a component-by-component analysis of physical damage to buildings. The damage functions are designed using an expert-based approach with the support of existing scientific and technical literature, loss adjustment studies, and damage surveys carried out for past flood events in Italy. The model structure is designed to be transparent and flexible, and therefore it can be applied in different geographical contexts and adapted to the actual knowledge of hazard and vulnerability variables. The model has been tested in a recent flood event in northern Italy. Validation results provided good estimates of post-event damages, with similar or superior performances when compared with other damage models available in the literature. In addition, a local sensitivity analysis was performed in order to identify the hazard variables that have more influence on damage assessment results.

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 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 Uncertainties in Coastal Flood Risk Assessments in Small Island Developing States

2019 ◽  
Author(s):  
Matteo U. Parodi ◽  
Alessio Giardino ◽  
Ap van Dongeren ◽  
Stuart G. Pearson ◽  
Jeremy D. Bricker ◽  
...  
Keyword(s):  
Flood Risk ◽  
Input Data ◽  
Flood Damage ◽  
Small Island ◽  
Small Island Developing States ◽  
Damage Functions ◽  
Current Time ◽  
Coastal Flood ◽  
Coastal Flood Risk ◽  
The Impact

Abstract. Considering the likely increase of coastal flooding in Small Island Developing States (SIDS), coastal managers at the local and global level have been developing initiatives aimed at implementing Disaster Risk Reduction (DRR) measures and adapting to climate change. Developing science-based adaptation policies requires accurate coastal flood risk (CFR) assessments, which are often subject to the scarcity of sufficiently accurate input data for insular states. We analysed the impact of uncertain inputs on coastal flood damage estimates, considering: (i) significant wave height, (ii) storm surge level and (iii) sea level rise (SLR) contributions to extreme sea levels, as well as the error-driven uncertainty in (iv) bathymetric and (v) topographic datasets, (vi) damage models and (vii) socioeconomic changes. The methodology was tested through a sensitivity analysis using an ensemble of hydrodynamic models (XBeach and SFINCS) coupled with an impact model (Delft-FIAT) for a case study at the islands of São Tomé and Príncipe. Model results indicate that for the current time horizon, depth damage functions (DDF) and digital elevation model (DEM) dominate the overall damage estimation uncertainty. We find that, when introducing climate and socioeconomic uncertainties to the analysis, SLR projections become the most relevant input for the year 2100 (followed by DEM and DDF). In general, the scarcity of reliable input data leads to considerable predictive error in CFR assessments in SIDS. The findings of this research can help to prioritise the allocation of limited resources towards the acquisitions of the most relevant input data for reliable impact estimation.

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.

Comparative analyses of flood damage models in three Asian countries: towards a regional flood risk modelling

2018 ◽  
Vol 39 (2) ◽  
pp. 229-246 ◽  
Author(s):  
Akinola Adesuji Komolafe ◽  
Srikantha Herath ◽  
Ram Avtar ◽  
Jean-Francois Vuillaume
Keyword(s):  
Flood Risk ◽  
Flood Damage ◽  
Asian Countries ◽  
Risk Modelling ◽  
Comparative Analyses ◽  
Damage Models

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

2016 ◽  
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 one hundred million euros 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-year, 100-year 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.

Flood vulnerability assessment: A critical comparison between site derived, national and international depth-damage functions and their use in assessing flood risk in Malaysia

2021 ◽  
Author(s):  
Balqis M. Rehan ◽  
Paul Sayers ◽  
A. Ulwan M. Alayuddin ◽  
M. Fadhil M. Ghamrawi ◽  
James D. Miller ◽  
...  
Keyword(s):  
Flood Risk ◽  
Flood Hazard ◽  
Flood Damage ◽  
Damage Function ◽  
Kuala Lumpur ◽  
Investment Planning ◽  
Damage Functions ◽  
Flood Vulnerability ◽  
Site Specific ◽  
Flood Vulnerability Assessment

<p>Damage functions are widely used to determine flood losses. National and international published damage functions are often used with little scrutiny or validation at local scales; a lack of understanding that unquestionably adds uncertainty to national flood risk assessment and investment planning. This paper examines the differences in aggregate flood damage estimates based on damage functions derived locally using local surveys and questionnaires, published national sector-based damage functions and land-use based damage functions published for Malaysia in the international literature. The paper is presented in two parts: firstly, the construction of a damage function from site-specific post-event flood surveys (covering a range of building types and flood hazard variables) and secondly, the comparison of these locally derived function with available national and international functions. A 0.05 km<sup>2</sup> residential area located in Kuala Lumpur, Malaysia, which consists of sparsely located houses was selected for the study. It was used to drive the site-specific damage function and an associated estimate of flood damage for a range of observed and modelled flood events. The results show that at higher depths, the use of the site-specific function suggest an aggregate damage of approximately twice than an estimate based on national functions but much less (less than 100%) than would be estimated based on international published functions. The paper concludes that the international published damage functions should be used with care and condition using local (where possible) or national understanding of flood damages to avoid a significant over estimation of losses.</p>

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