Suchergebnisse

Cover -- Titel -- Impressum -- Inhaltsverzeichnis -- Zusammenfassung -- 1 Einführung -- 1.1 Bedeutung von Risikoanalysen -- 1.2 Ziele und Vorgehensweise -- 2 Sicherheit und Risiko: Begriffe und Konzepte -- 2.1 Begriffe -- 2.2 Management von öffentlichen Risiken -- 2.2.1 Risikomanagement als Sicherheitsstrategie -- 2.2.2 Optimale Reduzierung des Risikos -- 2.2.3 Bestmögliche Beherrschung des Restrisikos -- 2.2.4 Schutzziele für öffentliche Risiken -- 2.3 Grundsätzliches zu Risikoanalysen -- 2.3.1 Zur historischen Entwicklung von naturwissenschaftlichtechnischen Risikoanalysen -- 2.3.2 Vorgehen bei Risikoanalysen -- 3 Methoden zur Abschätzung von Risiken -- 3.1 Gefahrenanalyse und Szenariobildung -- 3.2 Eintrittswahrscheinlichkeit von Schadenszenarien -- 3.2.1 Hinweise zur Ableitung von Eintrittswahrscheinlichkeiten -- 3.2.2 Historische Ereignisse und Beobachtungsdaten -- 3.2.3 Modellierung von Schadenszenarien -- 3.2.4 Expertenmeinung -- 3.3 Darstellung von Risikoaussagen -- 3.3.1 Risikoindikatoren -- 3.3.2 Risikokurven -- 3.4 Risikoanalysen und Unsicherheiten -- 3.4.1 Bedeutung von Unsicherheitsbetrachtungen -- 3.4.2 Quellen von Unsicherheit -- 3.4.3 Natürliche Variabilität und Unwissenheit -- 3.4.4 Unsicherheitsanalyse -- 3.5 Validierung von Risikoanalysen -- 3.5.1 Indikatoren zur Modellvalidierung -- 3.5.2 Datenverfügbarkeit und Extrapolation -- 4 Grundlegende Aspekte des Hochwasserrisikos -- 4.1 Gefährdung, Vulnerabilität und Risiko -- 4.2 Raumskalen -- 4.3 Datengüte, Instationarität und Extrapolation -- 4.3.1 Beobachtungsdaten für Hochwasserrisikoanalysen -- 4.3.2 Instationarität -- 4.3.3 Extrapolation -- 4.4 Risikomanagement als Kreislauf -- 5 Hochwasserbemessung und Risikoanalysen -- 5.1 Bemessungshochwasser -- 5.2 Traditionelle Bemessungsverfahren -- 5.2.1 Empirische Bemessung -- 5.2.2 Bemessung nach Grenzwerten des Abflusses.

Abstract. Floods affect more people than any other natural hazard; thus flood warning and disaster management are of utmost importance. However, the operational hydrological forecasts do not provide information about affected areas and impact but only discharge and water levels at gauges. We show that a simple hydrodynamic model operating with readily available data is able to provide highly localized information on the expected flood extent and impacts, with simulation times enabling operational flood warning. We demonstrate that such an impact forecast would have indicated the deadly potential of the 2021 flood in western Germany with sufficient lead time.

Flood loss modeling is an important component for risk analyses and decision support in flood risk management. Commonly, flood loss models describe complex damaging processes by simple, deterministic approaches like depth‐damage functions and are associated with large uncertainty. To improve flood loss estimation and to provide quantitative information about the uncertainty associated with loss modeling, a probabilistic, multivariable Bagging decision Tree Flood Loss Estimation MOdel (BT‐FLEMO) for residential buildings was developed. The application of BT‐FLEMO provides a probability distribution of estimated losses to residential buildings per municipality. BT‐FLEMO was applied and validated at the mesoscale in 19 municipalities that were affected during the 2002 flood by the River Mulde in Saxony, Germany. Validation was undertaken on the one hand via a comparison with six deterministic loss models, including both depth‐damage functions and multivariable models. On the other hand, the results were compared with official loss data. BT‐FLEMO outperforms deterministic, univariable, and multivariable models with regard to model accuracy, although the prediction uncertainty remains high. An important advantage of BT‐FLEMO is the quantification of prediction uncertainty. The probability distribution of loss estimates by BT‐FLEMO well represents the variation range of loss estimates of the other models in the case study.

In Germany, flood insurance is provided by private insurers as a supplement to building or contents insurance. This article presents the results of a survey of insurance companies with regard to eligibility conditions for flood insurance changes after August 2002, when a severe flood caused 1.8 billion euro of insured losses in the Elbe and the Danube catchment areas, and the general role of insurance in flood risk management in Germany. Besides insurance coverage, governmental funding and public donations played an important role in loss compensation after the August 2002 flood. Therefore, this article also analyzes flood loss compensation, risk awareness, and mitigation in insured and uninsured private households. Insured households received loss compensation earlier. They also showed slightly better risk awareness and mitigation strategies. Appropriate incentives should be combined with flood insurance in order to strengthen future private flood loss mitigation. However, there is some evidence that the surveyed insurance companies do little to encourage precautionary measures. To overcome this problem, flood hazards and mitigation strategies should be better communicated to both insurance companies and property owners.