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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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Volume 16, issue 1 | Copyright
Nat. Hazards Earth Syst. Sci., 16, 149-166, 2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 19 Jan 2016

Research article | 19 Jan 2016

Quantifying the effectiveness of early warning systems for natural hazards

M. Sättele1, M. Bründl1, and D. Straub2 M. Sättele et al.
  • 1WSL Institute for Snow and Avalanche Research SLF, Davos Dorf, Switzerland
  • 2Technische Universität München, Engineering Risk Analysis Group, Munich, Germany

Abstract. Early warning systems (EWSs) are increasingly applied as preventive measures within an integrated risk management approach for natural hazards. At present, common standards and detailed guidelines for the evaluation of their effectiveness are lacking. To support decision-makers in the identification of optimal risk mitigation measures, a three-step framework approach for the evaluation of EWSs is presented. The effectiveness is calculated in function of the technical and the inherent reliability of the EWS. The framework is applicable to automated and non-automated EWSs and combinations thereof. To address the specifics and needs of a wide variety of EWS designs, a classification of EWSs is provided, which focuses on the degree of automations encountered in varying EWSs. The framework and its implementation are illustrated through a series of example applications of EWS in an alpine environment.

Publications Copernicus
Short summary
We suggest a generic classification of early warning systems for natural hazards, which distinguishes alarm, warning, and forecasting systems. On the basis of this classification, we developed a three-step framework for evaluating the effectiveness of such systems and illustrate its applicability using case studies. Our results will support practitioners in comparing the effectiveness of early warning systems with those of structural mitigation measures.
We suggest a generic classification of early warning systems for natural hazards, which...