Application of statistical techniques to proportional loss data: Evaluating the predictive accuracy of physical vulnerability to hazardous hydro-meteorological events

Chow, Candace Wing-Yuen; Andrášik, Richard; Fischer, Benjamin; Keiler, Margreth (2019). Application of statistical techniques to proportional loss data: Evaluating the predictive accuracy of physical vulnerability to hazardous hydro-meteorological events. Journal of environmental management, 246, pp. 85-100. Elsevier 10.1016/j.jenvman.2019.05.084

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Knowledge about the cause of differential structural damages following the occurrence of hazardous hydrometeorological events can inform more effective risk management and spatial planning solutions. While studies have been previously conducted to describe relationships between physical vulnerability and features about building properties, the immediate environment and event intensity proxies, several key challenges remain. In particular, observations, especially those associated with high magnitude events, and studies designed to evaluate a comprehensive range of predictive features are both limited. To build upon previous developments, we described a workflow to support the continued development and assessment of empirical, multivariate physical vulnerability functions based on predictive accuracy. Within this workflow, we evaluated several statistical approaches, namely generalized linear models and their more complex alternatives. A series of models were built 1) to explicitly consider the effects of dimension reduction, 2) to evaluate the inclusion of interaction effects between and among predictors, 3) to evaluate an ensemble prediction method for applications where data observations are sparse, 4) to describe how model results can inform about the relative importance of predictors to explain variance in expected damages and 5) to assess the predictive accuracy of the models based on prescribed metrics. The utility of the workflow was demonstrated on data with characteristics of what is commonly acquired in ex-post field assessments. The workflow and recommendations from this study aim to provide guidance to researchers and practitioners in the natural hazards community.

Item Type:

Journal Article (Original Article)

Division/Institute:

08 Faculty of Science > Institute of Geography > Physical Geography > Unit Geomorphology
08 Faculty of Science > Institute of Geography
08 Faculty of Science > Institute of Geography > Physical Geography

UniBE Contributor:

Chow, Candace Wing-Yuen and Keiler, Margreth

ISSN:

0301-4797

Publisher:

Elsevier

Language:

English

Submitter:

Chantal Laeticia Schmidt

Date Deposited:

24 Jul 2019 09:21

Last Modified:

24 Jul 2019 09:21

Publisher DOI:

10.1016/j.jenvman.2019.05.084

Uncontrolled Keywords:

Multivariate analysis, Predictive accuracy, Dimension reduction, Proportional loss, Empirical physical vulnerability functions, Hydro-meteorological hazards

BORIS DOI:

10.7892/boris.131361

URI:

https://boris.unibe.ch/id/eprint/131361

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