Article thumbnail

Analyse der Unsicherheiten bei der Ermittlung der Schadenspotentiale infolge Überschwemmung

By Gesa Kutschera


The risk assessment tool RAPID (Risk Assessment: Probability, Inundation, Damage), developed at the Institute of Hydraulic Engineering and Water Resources Management (IWW), RWTH Aachen University, offers an effective and precise instrument for the calculation of risks associated with hydraulic engineering structures. The procedure is divided into three steps: risk analysis, risk assessment and risk management. Within the risk analysis risk is defined as the product of the failure probability and the resulting damage, which is the focus of this thesis. The damage resulting from flooding is relevant to people, buildings, infrastructure, companies, ecological and cultural goods and can be divided up into economic, ecological and psychosocial damages. Compared to ecological and psychosocial damages the damage assessment of economic damages is much more developed, but there is still a lack in data of the existing models, which leads to uncertainties of the model outputs when calculating the damages. Although the quantification of the uncertainties is an important information when calculating the absolute damage in monetary terms and deciding whether to implement a mitigation measure within the risk management, the uncertainties are not considered yet in the damage models. Following a close study of literature a probabilistic model for the calculation of direct economic damages due to hydrostatic water pressure after a dam/levee failure will be developed on a meso scale within this thesis. Additionally a new tool for the quantification of indirect economic damages will be introduced, thus a further step to enhance the determination of flood risks has been taken. As ecological and psychological damages have not been considered yet as part of the RAPID procedure, current research activities are summarized and two concepts for the integration of these damage categories are suggested. The developed probabilistic damage model is based on the application of the bootstrap method for the generation of a sufficient number of samples to identify the probability distributions as an input for the Monte-Carlo-Simulation (MC-Simulation). The MC-Simulation is carried out for each damage category and the results are displayed as a probability distribution and its statistical moments. The results of the uncertainty analysis of the direct economic damages show a significant difference in the variability of the results between the damage categories. The categories without any buildings like agriculture, forestry and recreation comprise the highest uncertainties while their contribution to the total damage amount is negligible compared to the developed areas, where high damages are caused even at low water depths. Generally, the uncertainty of the damages to buildings is highest at water depths below two meters. The results of the mobile damage potentials are equivalent to the immobile ones, but the coefficients of variance are lower. The evaluation of the sensitivity analysis clearly showed the influence of the parameters damage function and asset values, whereras the variation of the standard deviation of the normal distribution function of the water depth only resulted in minor changes of the results of damage calculation. The influence of the asset values on the categories private housing, industry and companies is low, while it is much higher for the mobile damages. The sensitivity of the results of these categories is vice versa on the variation of the damage functions. Regarding the open space areas, the uncertainties of the asset values determine the outputs of the model. It can be concluded that there is a potential for reducing the uncertainties of all damage categories when improving the database. The thesis closes with an example of an area at the Lower Rhine in North Rhine-Westphalia. The damage is calculated with the deterministic model as it is traditionally used at the IWW and with the new probabilistic model. The comparison of the results shows that the deterministic model overestimates the damages compared to the mean values of the probabilistic model, but the results lie within the 95%-confidence interval of the probabilistic model. Finally it can be concluded that the integration of the uncertainties in the direct economic damage model and the development of modules and concepts for the determination of the indirect economic, ecological and psychosocial damages contributes to the goals of the European flood directive to reduce negative consequences of floods. Thus, when conducting a cost-benefit analysis, the assessment of the efficiency of mitigation measures can be optimized considerably

Topics: info:eu-repo/classification/ddc/620, Hochwasser, Hochwasserschaden, Risikoanalyse, Risikomanagement, Monte-Carlo-Simulation, Unsicherheit, Ingenieurwissenschaften, Unsicherheitsanalyse, Schadenspotentiale, Risk-Assessment, flood damage assessment, uncertainty, monte-carlo simulation, flood-risk-assessment
Publisher: Publikationsserver der RWTH Aachen University
Year: 2008
OAI identifier:

Suggested articles

To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.