Avalanche risk evaluation and protective dam optimal design using extreme value statistics
ABSTRACT In snow avalanche long-term forecasting, existing risk-based methods remain difficult to use in a real engineering context. In this work, we expand a quasi analytical decisional model to obtain simple formulae to quantify risk and to perform the optimal design of an avalanche dam in a quick...
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crcambridgeupr:10.1017/jog.2016.64 2024-06-16T07:41:09+00:00 Avalanche risk evaluation and protective dam optimal design using extreme value statistics FAVIER, PHILOMÈNE ECKERT, NICOLAS FAUG, THIERRY BERTRAND, DAVID NAAIM, MOHAMED 2016 http://dx.doi.org/10.1017/jog.2016.64 https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0022143016000642 en eng Cambridge University Press (CUP) http://creativecommons.org/licenses/by/4.0/ Journal of Glaciology volume 62, issue 234, page 725-749 ISSN 0022-1430 1727-5652 journal-article 2016 crcambridgeupr https://doi.org/10.1017/jog.2016.64 2024-05-22T12:55:42Z ABSTRACT In snow avalanche long-term forecasting, existing risk-based methods remain difficult to use in a real engineering context. In this work, we expand a quasi analytical decisional model to obtain simple formulae to quantify risk and to perform the optimal design of an avalanche dam in a quick and efficient way. Specifically, the exponential runout model is replaced by the Generalized Pareto distribution (GPD), which has theoretical justifications that promote its use for modelling the different possible runout tail behaviours. Regarding the defence structure/flow interaction, a simple law based on kinetic energy dissipation is compared with a law based on the volume stored upstream of the dam, whose flexibility allows us to cope with various types of snow. We show how a detailed sensitivity study can be conducted, leading to intervals and bounds for risk estimates and optimal design values. Application to a typical case study from the French Alps, highlights potential operational difficulties and how they can be tackled. For instance, the highest sensitivity to the runout tail type and interaction law is found at abscissas of legal importance for hazard zoning (return periods of 10–1000 a), a crucial result for practical purposes. Article in Journal/Newspaper Journal of Glaciology Cambridge University Press Journal of Glaciology 62 234 725 749 |
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Open Polar |
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Cambridge University Press |
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crcambridgeupr |
language |
English |
description |
ABSTRACT In snow avalanche long-term forecasting, existing risk-based methods remain difficult to use in a real engineering context. In this work, we expand a quasi analytical decisional model to obtain simple formulae to quantify risk and to perform the optimal design of an avalanche dam in a quick and efficient way. Specifically, the exponential runout model is replaced by the Generalized Pareto distribution (GPD), which has theoretical justifications that promote its use for modelling the different possible runout tail behaviours. Regarding the defence structure/flow interaction, a simple law based on kinetic energy dissipation is compared with a law based on the volume stored upstream of the dam, whose flexibility allows us to cope with various types of snow. We show how a detailed sensitivity study can be conducted, leading to intervals and bounds for risk estimates and optimal design values. Application to a typical case study from the French Alps, highlights potential operational difficulties and how they can be tackled. For instance, the highest sensitivity to the runout tail type and interaction law is found at abscissas of legal importance for hazard zoning (return periods of 10–1000 a), a crucial result for practical purposes. |
format |
Article in Journal/Newspaper |
author |
FAVIER, PHILOMÈNE ECKERT, NICOLAS FAUG, THIERRY BERTRAND, DAVID NAAIM, MOHAMED |
spellingShingle |
FAVIER, PHILOMÈNE ECKERT, NICOLAS FAUG, THIERRY BERTRAND, DAVID NAAIM, MOHAMED Avalanche risk evaluation and protective dam optimal design using extreme value statistics |
author_facet |
FAVIER, PHILOMÈNE ECKERT, NICOLAS FAUG, THIERRY BERTRAND, DAVID NAAIM, MOHAMED |
author_sort |
FAVIER, PHILOMÈNE |
title |
Avalanche risk evaluation and protective dam optimal design using extreme value statistics |
title_short |
Avalanche risk evaluation and protective dam optimal design using extreme value statistics |
title_full |
Avalanche risk evaluation and protective dam optimal design using extreme value statistics |
title_fullStr |
Avalanche risk evaluation and protective dam optimal design using extreme value statistics |
title_full_unstemmed |
Avalanche risk evaluation and protective dam optimal design using extreme value statistics |
title_sort |
avalanche risk evaluation and protective dam optimal design using extreme value statistics |
publisher |
Cambridge University Press (CUP) |
publishDate |
2016 |
url |
http://dx.doi.org/10.1017/jog.2016.64 https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0022143016000642 |
genre |
Journal of Glaciology |
genre_facet |
Journal of Glaciology |
op_source |
Journal of Glaciology volume 62, issue 234, page 725-749 ISSN 0022-1430 1727-5652 |
op_rights |
http://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.1017/jog.2016.64 |
container_title |
Journal of Glaciology |
container_volume |
62 |
container_issue |
234 |
container_start_page |
725 |
op_container_end_page |
749 |
_version_ |
1802008266094411776 |