Flood risk assessment and associated uncertainty

International audienceFlood disaster mitigation strategies should be based on a comprehensive assessment of the flood risk combined with a thorough investigation of the uncertainties associated with the risk assessment procedure. Within the "German Research Network of Natural Disasters" (DFNK) the working group "Flood Risk Analysis" investigated the flood process chain from precipitation, runoff generation and concentration in the catchment, flood routing in the river network, possible failure of flood protection measures, inundation to economic damage. The working group represented each of these processes by deterministic, spatially distributed models at different scales. While these models provide the necessary understanding of the flood process chain, they are not suitable for risk and uncertainty analyses due to their complex nature and high CPU-time demand. We have therefore developed a stochastic flood risk model consisting of simplified model components associated with the components of the process chain. We parameterised these model components based on the results of the complex deterministic models and used them for the risk and uncertainty analysis in a Monte Carlo framework. The Monte Carlo framework is hierarchically structured in two layers representing two different sources of uncertainty, aleatory uncertainty (due to natural and anthropogenic variability) and epistemic uncertainty (due to incomplete knowledge of the system). The model allows us to calculate probabilities of occurrence for events of different magnitudes along with the expected economic damage in a target area in the first layer of the Monte Carlo framework, i.e. to assess the economic risks, and to derive uncertainty bounds associated with these risks in the second layer. It is also possible to identify the contributions of individual sources of uncertainty to the overall uncertainty. It could be shown that the uncertainty caused by epistemic sources significantly alters the results obtained with aleatory uncertainty alone. The model was applied to reaches of the river Rhine downstream of Cologne

Flood loss reduction of private households due to building precautionary measures -- lessons learned from the Elbe flood in August 2002

Building houses in inundation areas is always a risk, since absolute flood protection is impossible. Where settlements already exist, flood damage must be kept as small as possible. Suitable means are precautionary measures such as elevated building configuration or flood adapted use. However, data about the effects of such measures are rare, and consequently, the efficiency of different precautionary measures is unclear. To improve the knowledge about efficient precautionary measures, approximately 1200 private households, which were affected by the 2002 flood at the river Elbe and its tributaries, were interviewed about the flood damage of their buildings and contents as well as about their precautionary measures. The affected households had little flood experience, i.e. only 15% had experienced a flood before. 59% of the households stated that they did not know, that they live in a flood prone area. Thus, people were not well prepared, e.g. just 11% had used and furnished their house in a flood adapted way and only 6% had a flood adapted building structure. Building precautionary measures are mainly effective in areas with frequent small floods. But also during the extreme flood event in 2002 building measures reduced the flood loss. From the six different building precautionary measures under study, flood adapted use and adapted interior fitting were the most effective ones. They reduced the damage ratio for buildings by 46% and 53%, respectively. The damage ratio for contents was reduced by 48% due to flood adapted use and by 53% due to flood adapted interior fitting. The 2002 flood motivated a relatively large number of people to implement private precautionary measures, but still much more could be done. Hence, to further reduce flood losses, people's motivation to invest in precaution should be improved. More information campaigns and financial incentives should be issued to encourage precautionary measures

Aspects of seasonality and flood generating circulation patterns in a mountainous catchment in south-eastern Germany

International audienceAnalyses of discharge series, precipitation fields and flood producing atmospheric circulation patterns reveal that two governing flood regimes exist in the Mulde catchment in south-eastern Germany: frequent floods during the winter and less frequent but sometimes extreme floods during the summer. Differences in the statistical parameters skewness and coefficient of variation of the discharge data can be found from west to east and are discussed in the context of landscape parameters that influence the discharge. Annual maximum discharge series were assigned to the triggering Großwetterlage in order to evaluate which circulation patterns are likely to produce large floods. It can be shown that the cyclone Vb-weather regime generates the most extreme flood events in the Mulde catchment, whereas westerly winds produce frequently small floods. Vb-weather regimes do not always trigger large flood events in the study area, but large floods are mostly generated by these weather patterns. Based on these findings, it is necessary to revise the traditional flood frequency analysis approach and develop new approaches which can handle different flood triggering processes within the dataset

Risk assessment and mapping of extreme floods in non-dyked communities along the Elbe and Mulde Rivers

International audienceAssessing and mapping damage risk of floods for large river basins is still in its infancy. Damage risk is understood to be the combination of flood hazard and the vulnerability of communities to a flood of a particular return period. Risk is calculated and mapped for two communities in which dykes are not located for flood protection: Meissen on the Elbe River and Döbeln in the Mulde catchment. Different methodologies for the computation of flood depth and inundation extent of varying flood return periods (hazard) are compared. Exposure and relative damage to the flooding (vulnerability) based on land-use coverages of different scale are also compared and discussed. A property asset coverage completes the data requirements for the construction of the risk maps. Recommendations for continued research on risk assessments of large river basins conclude the study

Is flow velocity a significant parameter in flood damage modelling?

Flow velocity is generally presumed to influence flood damage. However, this influence is hardly quantified and virtually no damage models take it into account. Therefore, the influences of flow velocity, water depth and combinations of these two impact parameters on various types of flood damage were investigated in five communities affected by the Elbe catchment flood in Germany in 2002. 2-D hydraulic models with high to medium spatial resolutions were used to calculate the impact parameters at the sites in which damage occurred. A significant influence of flow velocity on structural damage, particularly on roads, could be shown in contrast to a minor influence on monetary losses and business interruption. Forecasts of structural damage to road infrastructure should be based on flow velocity alone. The energy head is suggested as a suitable flood impact parameter for reliable forecasting of structural damage to residential buildings above a critical impact level of 2 m of energy head or water depth. However, general consideration of flow velocity in flood damage modelling, particularly for estimating monetary loss, cannot be recommended

Reply to Comment on "Significance of "high probability/low damage" versus "low probability/high damage" flood events" by C. M. Rheinberger (2009)

In a comment to our recently published paper on the "Significance of "high probability/low damage" versus "low probability/high damage" flood events" (Merz et al., 2009), C. M. Rheinberger questions the use of relative damage as a suitable indicator for risk aversion and the use of the resulting risk aversion functions in judging flood mitigation measures. While the points of criticism are important and should be accounted for, most of these points are considered in our original paper. More importantly, we do not agree with the conclusion that the use of relative damage as indicator for risk aversion is generally not appropriate in decision making about flood mitigation measures

Regionalisation of asset values for risk analyses

International audienceIn risk analysis there is a spatial mismatch of hazard data that are commonly modelled on an explicit raster level and exposure data that are often only available for aggregated units, e.g. communities. Dasymetric mapping techniques that use ancillary information to disaggregate data within a spatial unit help to bridge this gap. This paper presents dasymetric maps showing the population density and a unit value of residential assets for whole Germany. A dasymetric mapping approach, which uses land cover data (CORINE Land Cover) as ancillary variable, was adapted and applied to regionalize aggregated census data that are provided for all communities in Germany. The results were validated by two approaches. First, it was ascertained whether population data disaggregated at the community level can be used to estimate population in postcodes. Secondly, disaggregated population and asset data were used for a loss evaluation of two flood events that occurred in 1999 and 2002, respectively. It must be concluded that the algorithm tends to underestimate the population in urban areas and to overestimate population in other land cover classes. Nevertheless, flood loss evaluations demonstrate that the approach is capable of providing realistic estimates of the number of exposed people and assets. Thus, the maps are sufficient for applications in large-scale risk assessments such as the estimation of population and assets exposed to natural and man-made hazards

Influence of flood frequency on residential building losses

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 (<i>n</i>=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

Pengaruh Karakteristik Pekerjaan, Kompensasi, Dan Kepuasan Kerja Terhadap Produktivitas Kerja Karyawan Pada CV. Ibu Sri “Tilung” Di Boyolali

The purpose of this study is to determine the effect of labor characteristics, compensation, and job satisfaction on employee productivity in CV Ibu Sri Tilung. This study also aims to determine jointly the influence of the three independent variables to the dependent variable. The type of research is quantitative research, with a sample of 35 respondents. Sampling using convinience-purposive sampling technique. Techniques of collecting research data through questionnaires with Likert scale. Data analysis methods used were validity test, reliability test, classical assumption test, and multiple linier regression analysis test. The result showed that both the partial and simultaneous variables influence the characteristics of labor, compensation and job satisfaction have a positive and significant effect on employee work productivity. In the determinant coefficient (R ²), the result is 0.918, it means that the variable of labor characteristics (X1), compensation (X2), and job satisfaction (X3) are able to explain the work productivity (Y) variable of 0.918 or 91.8%, and the rest can be explained variable other outside the research model

Review article "Assessment of economic flood damage"

Damage assessments of natural hazards supply crucial information to decision support and policy development in the fields of natural hazard management and adaptation planning to climate change. Specifically, the estimation of economic flood damage is gaining greater importance as flood risk management is becoming the dominant approach of flood control policies throughout Europe. This paper reviews the state-of-the-art and identifies research directions of economic flood damage assessment. Despite the fact that considerable research effort has been spent and progress has been made on damage data collection, data analysis and model development in recent years, there still seems to be a mismatch between the relevance of damage assessments and the quality of the available models and datasets. Often, simple approaches are used, mainly due to limitations in available data and knowledge on damage mechanisms. The results of damage assessments depend on many assumptions, e.g. the selection of spatial and temporal boundaries, and there are many pitfalls in economic evaluation, e.g. the choice between replacement costs or depreciated values. Much larger efforts are required for empirical and synthetic data collection and for providing consistent, reliable data to scientists and practitioners. A major shortcoming of damage modelling is that model validation is scarcely performed. Uncertainty analyses and thorough scrutiny of model inputs and assumptions should be mandatory for each damage model development and application, respectively. In our view, flood risk assessments are often not well balanced. Much more attention is given to the hazard assessment part, whereas damage assessment is treated as some kind of appendix within the risk analysis. Advances in flood damage assessment could trigger subsequent methodological improvements in other natural hazard areas with comparable time-space properties