Nonparametric estimation of aggregated Sobol’ indices: Application to a depth averaged snow avalanche model

Heredia, María Belén, Prieur, Clémentine and Nicolas Eckert

Reliability Engineering and System Safety, 2021, vol. 212, issue C

Abstract: Avalanche models are increasingly employed for elaborating land-use maps and designing defense structures, but they rely on poorly known parameters. Careful uncertainty assessment is thus required but difficulty arises from the nature of the outputs of these models, which are commonly both functional and scalar. Hence, so far in the avalanche field, few sensitivity analyses have been performed. In this work, we propose to determine the most influential inputs of an avalanche model by estimating aggregated first-order Sobol’ indices. We propose a nonparametric estimation procedure based on the Nadaraya–Watson kernel smoother, which allows to estimate the aggregated Sobol’ indices from a given random sample of small to moderate size. Due to the limited size of the sample, the kernel estimation is biased. Therefore, we propose a bootstrap based bias correction before selecting the bandwidth by cross-validation. To estimate the aggregated Sobol’ indices, we reduce the dimension of the output using principal components analysis. After different test cases showing the efficiency of our approach, it is applied to a real avalanche case. Results show that the friction parameters and the snow depth in the release zone are the most influential parameters determining the avalanche characteristics.

Keywords: Aggregated Sobol’ indices; Nonparametric; Snow avalanche model; Functional output; Bias correction (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S095183202030908X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:212:y:2021:i:c:s095183202030908x

DOI: 10.1016/j.ress.2020.107422

Access Statistics for this article

Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares

More articles in Reliability Engineering and System Safety from Elsevier
Bibliographic data for series maintained by Catherine Liu ().