Application of Sensitivity Analysis for Process Model Calibration of Natural Hazards

Sensitivity analysis (SA) describes how varying inputs to a model subsequently varies its outputs. Its inclusion can support the systematic calibration of numerical models to back-calculate intensity properties of past torrent events that would otherwise be difficult or impossible to collect during...

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Main Authors: Candace Chow, Jorge Ramirez, Margreth Keiler
Format: Article
Language:English
Published: MDPI AG 2018-06-01
Series:Geosciences
Subjects:
Online Access:http://www.mdpi.com/2076-3263/8/6/218
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spelling doaj-bbb5cd32698e4cecaf23f8d8dcc514652020-11-24T21:08:00ZengMDPI AGGeosciences2076-32632018-06-018621810.3390/geosciences8060218geosciences8060218Application of Sensitivity Analysis for Process Model Calibration of Natural HazardsCandace Chow0Jorge Ramirez1Margreth Keiler2Institute of Geography, University of Bern, 3012 Bern, SwitzerlandInstitute of Geography, University of Bern, 3012 Bern, SwitzerlandInstitute of Geography, University of Bern, 3012 Bern, SwitzerlandSensitivity analysis (SA) describes how varying inputs to a model subsequently varies its outputs. Its inclusion can support the systematic calibration of numerical models to back-calculate intensity properties of past torrent events that would otherwise be difficult or impossible to collect during their occurrence. Sensitivity analysis for model calibration is assessed with the back-calculation of a known torrent event. In particular, FLO-2D, a cell-based numerical model, is used to simulate the 2005 debris flow event that occurred in Brienz, Switzerland. Under 4000 simulations were completed with ranges of physically reasonable parameter values. Model results were compared in 3-dimensions with both sediment deposition extents (x, y) and estimated deposition heights (z) from available post-event images. The comparisons highlighted that more accurate input and validation data, namely the flow behavior of hazardous processes and post-event deposition heights, are required to produce stronger agreements between simulated and observed results. Furthermore, the application of SA for model calibration supports systematic exploration of large parameter spaces characteristic of complex phenomena like natural hazard events. These findings demonstrated how important model input factors can be identified, which provide guidance for future data collection efforts to capture both the rheology and the spatial distribution of hazards more accurately.http://www.mdpi.com/2076-3263/8/6/218sensitivity analysiscalibrationphysical vulnerabilityrisk analysissummary scalar variables
collection DOAJ
language English
format Article
sources DOAJ
author Candace Chow
Jorge Ramirez
Margreth Keiler
spellingShingle Candace Chow
Jorge Ramirez
Margreth Keiler
Application of Sensitivity Analysis for Process Model Calibration of Natural Hazards
Geosciences
sensitivity analysis
calibration
physical vulnerability
risk analysis
summary scalar variables
author_facet Candace Chow
Jorge Ramirez
Margreth Keiler
author_sort Candace Chow
title Application of Sensitivity Analysis for Process Model Calibration of Natural Hazards
title_short Application of Sensitivity Analysis for Process Model Calibration of Natural Hazards
title_full Application of Sensitivity Analysis for Process Model Calibration of Natural Hazards
title_fullStr Application of Sensitivity Analysis for Process Model Calibration of Natural Hazards
title_full_unstemmed Application of Sensitivity Analysis for Process Model Calibration of Natural Hazards
title_sort application of sensitivity analysis for process model calibration of natural hazards
publisher MDPI AG
series Geosciences
issn 2076-3263
publishDate 2018-06-01
description Sensitivity analysis (SA) describes how varying inputs to a model subsequently varies its outputs. Its inclusion can support the systematic calibration of numerical models to back-calculate intensity properties of past torrent events that would otherwise be difficult or impossible to collect during their occurrence. Sensitivity analysis for model calibration is assessed with the back-calculation of a known torrent event. In particular, FLO-2D, a cell-based numerical model, is used to simulate the 2005 debris flow event that occurred in Brienz, Switzerland. Under 4000 simulations were completed with ranges of physically reasonable parameter values. Model results were compared in 3-dimensions with both sediment deposition extents (x, y) and estimated deposition heights (z) from available post-event images. The comparisons highlighted that more accurate input and validation data, namely the flow behavior of hazardous processes and post-event deposition heights, are required to produce stronger agreements between simulated and observed results. Furthermore, the application of SA for model calibration supports systematic exploration of large parameter spaces characteristic of complex phenomena like natural hazard events. These findings demonstrated how important model input factors can be identified, which provide guidance for future data collection efforts to capture both the rheology and the spatial distribution of hazards more accurately.
topic sensitivity analysis
calibration
physical vulnerability
risk analysis
summary scalar variables
url http://www.mdpi.com/2076-3263/8/6/218
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