1. Proportional loss functions for debris flow events
- Author
-
Christoph M. Rheinberger, Hans Romang, Michael Bründl, Economie des Ressources Naturelles (LERNA), Université Toulouse 1 Capitole (UT1), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Recherche Agronomique (INRA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Federal Office of Meteorology and Climatology MeteoSwiss, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, This paper was partly funded through EU FP6 STREP contract no. 081412 ('IRASMOS')., Université Toulouse Capitole (UT Capitole), and Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National de la Recherche Agronomique (INRA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)
- Subjects
Generalized linear model ,010504 meteorology & atmospheric sciences ,risk-assessment ,landslide risk ,vulnerability ,damage ,management ,regression ,hazards ,0211 other engineering and technologies ,02 engineering and technology ,01 natural sciences ,lcsh:TD1-1066 ,Debris flow ,Economies et finances ,Overdispersion ,Statistics ,Range (statistics) ,Econometrics ,lcsh:Environmental technology. Sanitary engineering ,lcsh:Environmental sciences ,risk-assessment, landslide risk, vulnerability, damage, management, regression, hazards ,0105 earth and related environmental sciences ,lcsh:GE1-350 ,021110 strategic, defence & security studies ,Hydrogeology ,lcsh:QE1-996.5 ,Confounding ,lcsh:Geography. Anthropology. Recreation ,[SHS.ECO]Humanities and Social Sciences/Economics and Finance ,Debris ,lcsh:Geology ,Economies and finances ,lcsh:G ,General Earth and Planetary Sciences ,Environmental science ,Risk assessment - Abstract
Quantitative risk assessments of debris flows and other hydrogeological hazards require the analyst to predict damage potentials. A common way to do so is by use of proportional loss functions. In this paper, we analyze a uniquely rich dataset of 132 buildings that were damaged in one of five large debris flow events in Switzerland. Using the double generalized linear model, we estimate proportional loss functions that may be used for various prediction purposes including hazard mapping, landscape planning, and insurance pricing. Unlike earlier analyses, we control for confounding effects of building characteristics, site specifics, and process intensities as well as for overdispersion in the data. Our results suggest that process intensity parameters are the most meaningful predictors of proportional loss sizes. Cross-validation tests suggest that the mean absolute prediction errors of our models are in the range of 11%, underpinning the accurateness of the approach.
- Published
- 2013