Adaptability and transferability of flood loss functions in residential areas

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.

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Adaptability and transferability of flood loss functions in residential areas

Natural Hazards and Earth System Science ◽

10.5194/nhess-13-3063-2013 ◽

2013 ◽

Vol 13 (11) ◽

pp. 3063-3081 ◽

Cited By ~ 74

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.

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Probabilistic Flood Loss Models for Companies

10.5194/egusphere-egu2020-7334 ◽

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

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.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.

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Development and assessment of uni- and multi-variable flood loss models for Emilia-Romagna (Italy)

10.5194/nhess-2017-342 ◽

2017 ◽

Author(s):

Francesca Carisi ◽

Kai Schröter ◽

Alessio Domeneghetti ◽

Heidi Kreibich ◽

Attilio Castellarin

Keyword(s):

Residential Buildings ◽

Economic Value ◽

Flood Damage ◽

Data Sets ◽

Local Data ◽

Data Set ◽

Damage Models ◽

Flood Loss ◽

Loss Data ◽

Loss Models

Abstract. Simplified flood loss models are one important source of uncertainty in flood risk assessments. Many countries experience sparseness or absence of comprehensive high-quality flood loss data sets which is often rooted in a lack of protocols and reference procedures for compiling loss data sets after flood events. Such data are an important reference for developing and validating flood loss models. We consider the Secchia river flood event of January 2014, when a sudden levee-breach caused the inundation of nearly 52 km2 in Northern Italy. For this event we compiled a comprehensive flood loss data set of affected private households including buildings footprint, economic value, damages to contents, etc. based on information collected by local authorities after the event. By analysing this data set we tackle the problem of flood damage estimation in Emilia-Romagna (Italy) by identifying empirical uni- and multi-variable loss models for residential buildings and contents. The accuracy of the proposed models is compared with those of several flood-damage models reported in the literature, providing additional insights on the transferability of the models between different contexts. Our results show that (1) even simple uni-variable damage models based on local data are significantly more accurate than literature models derived for different contexts; (2) multi-variable models that consider several explanatory variables outperform uni-variable models which use only water depth. However, multi-variable models can only be effectively developed and applied if sufficient and detailed information is available.

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Do hazard maps mirror loss data? – A vulnerability assessment based on loss data and hazard maps

10.5194/egusphere-egu2020-19685 ◽

2020 ◽

Author(s):

Mirjam Mertin ◽

Mattia Brughelli ◽

Andreas Zischg ◽

Veronika Röthlisberger ◽

Matthias Schlögl ◽

...

Keyword(s):

Flood Risk ◽

Risk Mitigation ◽

Flood Hazard ◽

Flood Damage ◽

Hazard Maps ◽

Protection Measures ◽

Essential Information ◽

Flood Loss ◽

Loss Data ◽

First Results

Implementing effective flood risk strategies is an essential task for policy-makers which will gain in importance as flood losses are expected to increase due to socio-economic and climatic drivers in near future. Flood risk mitigation incorporates structural and non-structural measures such as the declaration of flood hazard zones, both of which are associated with high financial expenses. Essential information to ensure maximum effectiveness and cost efficiency of flood protection measures is provided by quantitative flood loss analyses based, for example, on data from insurance claims.This project aims to model the expected flood damage, thus the vulnerability to buildings by examining country-wide, empirical flood loss data of Switzerland of the past 35 years. The developed method includes several steps: First, the loss data are statistically analysed, second the spatial distribution of the loss data in the different hazard zones is assessed and third, vulnerability models for each hazard zone are developed including further parameters such as building values or building zones. A further objective is to provide an overview of possible methods which differ in complexity and data requirement and can be adapted for other applications outside of Switzerland. First results show that the extent of loss increases as the degree of hazard rises. In contrast, however, the number of damage events is highest in flood zones with a lower degree of hazard. Further possibilities how risk adaptation strategies can be supported or complemented by flood loss data are presented within this project.

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Flood Risk Assessment of Residential Neighbourhoods in Calabar Metropolis, Cross River State, Nigeria

Environment and Natural Resources Research ◽

10.5539/enrr.v6n2p115 ◽

2016 ◽

Vol 6 (2) ◽

pp. 115 ◽

Cited By ~ 1

Author(s):

Benedict E. Ojikpong ◽

Bassey E. Ekeng ◽

Ukpali E. Obonga ◽

Samuel I. Emri

Keyword(s):

Flood Risk ◽

Flood Control ◽

Residential Buildings ◽

Drainage System ◽

Secondary Data ◽

Least Square Method ◽

Least Square ◽

Control Measures ◽

Primary Data ◽

Residential Areas

The study is aimed at examining the vulnerability of some residential neighbourhoods in Calabar to the menace of flooding with a view to determining residential areas of high, medium and low flood risk. Two hypotheses were formulated such as: there is no significant relationship between the magnitude of flood, and the vulnerability of residential neighbourhoods and the elements-at-risk to flood in residential neighbourhoods in Calabar do not vary significantly according to the topography of the area. The major primary data were obtained from the metric measurement of the coverage of flood and the assessment of the numerical value of the residential buildings considered vulnerable to flood within the areas measured. Secondary data were also obtained from the collection of both published and unpublished materials and data on flooded buildings and displaced persons were also obtained from the State Emergency Management Agency (SEMA), Calabar. The data were analyzed using descriptive statistics and hypotheses tested using the regression coefficient of the least square method and scatter grams for prediction. The results of the hypotheses were found to be significant as the magnitude of flood determined the vulnerability of some residential neighbourhoods. Vulnerability was found to be higher in low lying residential neighbourhoods. The study, however, recommends among others, planned and autonomous adaptation responses, flood plain zoning to urban agriculture, landscaping and recreational uses. Proper channelization of Calabar urban drainage system, stringent flood control legislation, and development control measures should be enforced so as to discourage people from building on or near flood-prone areas of Calabar.

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Drivers of flood risk change in residential areas

Natural Hazards and Earth System Science ◽

10.5194/nhess-12-1641-2012 ◽

2012 ◽

Vol 12 (5) ◽

pp. 1641-1657 ◽

Cited By ~ 51

Author(s):

F. Elmer ◽

J. Hoymann ◽

D. Düthmann ◽

S. Vorogushyn ◽

H. Kreibich

Keyword(s):

Land Use ◽

Land Use Change ◽

Flood Risk ◽

Flood Hazard ◽

Residential Buildings ◽

Economic Effects ◽

Dominant Factor ◽

Residential Areas ◽

Land Use Patterns ◽

Land Use Scenario

Abstract. The observed increase of direct flood damage over the last decades may be caused by changes in the meteorological drivers of floods, or by changing land-use patterns and socio-economic developments. It is still widely unknown to which extent these factors will contribute to future flood risk changes. We survey the change of flood risk in terms of expected annual damage for residential buildings in the lower part of the Mulde River basin (Vereinigte Mulde) between 1990 and 2020 in 10-yr time steps based on measurements and model projections. For this purpose we consider the complete risk chain from climate impact via hydrological and hydraulic modelling to damage and risk estimation. We analyse what drives the changes in flood risk and quantify the contributions of these drivers: flood hazard change due to climate change, land-use change and changes in building values. We estimate flood risk and building losses based on constant values and based on effective (inflation adjusted) values separately. For constant values, estimated building losses for the most extreme inundation scenario amount to more than 360 million € for all time steps. Based on effective values, damage estimates for the same inundation scenario decrease from 478 million € in 1990 to 361 million € in 2000 and 348 million € in 2020 (maximum land-use scenario). Using constant values, flood risk is 111% (effective values: 146%) of the 2000 estimate in 1990 and 121% (effective values: 115%) of the 2000 estimate for the maximum land-use scenario in 2020. The quantification of driver contributions reveals that land-use change in the form of urban sprawl in endangered areas is the main driver of flood risk in the study area. Climate induced flood hazard change is important but not a dominant factor of risk change in the study area. With the historical exception of the economic effects in Eastern Germany following the German reunification, value developments only have minor influence on the development of flood risk.

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Energy Performance Assessment Framework for Residential Buildings in Saudi Arabia

Sustainability ◽

10.3390/su13042232 ◽

2021 ◽

Vol 13 (4) ◽

pp. 2232 ◽

Cited By ~ 1

Author(s):

Mohammad AlHashmi ◽

Gyan Chhipi-Shrestha ◽

Rajeev Ruparathna ◽

Kh Md Nahiduzzaman ◽

Kasun Hewage ◽

...

Keyword(s):

Saudi Arabia ◽

Performance Assessment ◽

Energy Demand ◽

Residential Buildings ◽

Energy Performance ◽

Performance Criteria ◽

Assessment Framework ◽

Residential Sector ◽

Building Type ◽

Geographical Regions

The residential sector consumes about 50% of the electricity produced from fossil fuels in Saudi Arabia. The residential energy demand is increasing. Moreover, a simple building energy performance assessment framework is not available for hot arid developing countries. This research proposes an energy performance assessment framework for residential buildings in hot and arid regions, which focuses on three performance criteria: operational energy, GHG emissions, and cost. The proposed framework has been applied to three types of residential buildings, i.e., detached, attached, and low-rise apartments, in five geographical regions of Saudi Arabia. Design Builder® was used to simulate the energy demand in buildings over a whole year. Four types of efficiency improvement interventions, including double-glazed windowpanes, triple-glazed windowpanes, LED lighting, and split air conditioners, were introduced in 12 combinations. Overall, 180 simulations were performed which are based on 12 intervention combinations, three building types, and five regions. Three performance criteria were evaluated for each simulation and then aggregated using a multi-criteria decision analysis method to identify the best intervention strategy for a given building type and a geographical region in Saudi Arabia. Each building type with interventions consumes higher energy in the western, central, and eastern regions and consumes a lesser amount of energy in the southern and northern regions. The proposed framework is helpful for long-term planning of the residential sector.

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Influence of flood frequency on residential building losses

Natural Hazards and Earth System Science ◽

10.5194/nhess-10-2145-2010 ◽

2010 ◽

Vol 10 (10) ◽

pp. 2145-2159 ◽

Cited By ~ 72

Author(s):

F. Elmer ◽

A. H. Thieken ◽

I. Pech ◽

H. Kreibich

Keyword(s):

Residential Buildings ◽

Statistical Error ◽

Residential Building ◽

Water Levels ◽

Recurrence Interval ◽

Flood Events ◽

Flood Loss ◽

Loss Data ◽

Loss Models ◽

Loss Modelling

Abstract. For the purpose of flood risk analysis, reliable loss models are an indispensable need. The most common models use stage-damage functions relating damage to water depth. They are often derived from empirical flood loss data (i.e. loss data collected after a flood event). However, object specific loss data (e.g. losses of single residential buildings) from recent flood events in Germany showed higher average losses in less probable events, regardless of actual water level. Hence, models that were derived from such data tend to overestimate losses caused by more probable events. Therefore, it is the aim of the study to analyse the relation between flood damage and recurrence interval and to propose a method for considering recurrence interval in flood loss modelling. The survey was based on residential building loss data (n=2158) of recent flood events in 2002, 2005 and 2006 in Germany and on-site recurrence interval of the respective events. We discovered a highly significant positive correlation between loss extent and recurrence interval for classified water levels as well as increasing average losses for longer recurrence intervals within each class. The application of principal component analysis revealed the interrelation between factors that influence the damage extent directly or indirectly, and recurrence interval. No single factor or component could be identified that explained the influence of recurrence interval, which led to the conclusion that recurrence interval cannot substitute, but complement other damage influencing factors in flood loss modelling approaches. Finally, a method was developed to include recurrence interval in typical flood loss models and make them applicable to a wider range of flood events. Validation including statistical error analysis showed that the modified models improve loss estimates in comparison to traditional approaches. The proposed multi-parameter model FLEMOps+r performs particularly well.

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Augmenting a Sociohydrological Flood Risk Model for Companies with Process-oriented Loss Estimation

10.5194/egusphere-egu21-10064 ◽

2021 ◽

Author(s):

Lukas Schoppa ◽

Marlies Barendrecht ◽

Tobias Sieg ◽

Nivedita Sairam ◽

Heidi Kreibich

Keyword(s):

Flood Risk ◽

Risk Model ◽

Flood Damage ◽

Modeling Framework ◽

River Elbe ◽

Validation Experiment ◽

Flood Loss ◽

Loss Data ◽

Damage Process ◽

Process Oriented

Sociohydrological models are increasingly used in flood risk analysis to reveal and understand the temporal dynamics in coupled human-flood systems. While most sociohydrological flood risk models are stylized and describe hypothetical human-flood systems, very few recent case studies employ empirical data to investigate real world systems. The mathematical representation of flooding processes in these models is often simplistic and does not reflect the current state of knowledge. This is due to the intricacy of human-flood interactions and the lack of sufficient and suitable historical data.We augment an existing, parsimonious sociohydrological flood risk model with a process-oriented flood loss model to integrate better understanding of flood damage processes into a sociohydrological modeling framework. Using Bayesian inference, we simulate the co-evolution of the flood risk system for companies located at the river Elbe in Dresden, Germany, over the course of 120 years. We compare model versions with differently complex process description on the basis of their loss prediction accuracy and uncertainty. This allows for exploring the added value of (i) resolving the inundation and damage process with more detail and (ii) accounting for heterogeneity across economic sectors. Apart from historical sociohydrological data, the proposed, augmented model versions are informed by object-level loss data, inundation maps, and spatial data, enhancing the pool of information available to the model. A leave-one-out cross-validation experiment shows that the augmented model versions increase the precision and reduce the uncertainty of company flood loss predictions in Dresden. In addition, the augmented models provide reliable loss predictions even in the absence of extensive historical flood loss data.The demonstrated model augmentation concept is not limited to the flood damage process but could be transferred to other processes within the human-flood system. For instance, by incorporating a dedicated model from protection motivation theory that describes how flood awareness and preparedness change after the occurrence of a damaging flood event.

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

10.5194/nhess-2021-363 ◽

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.

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