Characterization of Precipitation through Copulas and Expert Judgement for Risk Assessment of Infrastructure
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 3, Issue 4
Abstract
In this paper two methodologies are investigated that contribute to better assessment of risks related to extreme rainfall events. Firstly, one-parameter bivariate copulas are used to analyze rain gauge data in the Netherlands. Out of three models considered, the Gumbel copula, which indicates upper tail dependence, represents the data most accurately for all 33 stations in the Netherlands. Seasonal variability is noticeable, with rank correlation reaching maximum in winter and minimum in summer as well as other temporal and spatial patterns. Secondly, an expert judgment elicitation was undertaken. The experts’ opinions were combined using Cooke’s classical method in order to obtain estimates of future changes in precipitation patterns. Experts predicted mostly an approximate 10% increase in rain amount, duration, intensity and the dependence between amount and duration. The results were in line with official national climate change scenarios, based on numerical modelling. Applicability of both methods was presented based on an example of an existing tunnel in the Netherlands, contributing to better estimates of the tunnel’s limit state function and therefore the probability of failure.
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Acknowledgments
This research was financed by the TNO project “Graphical Methods for Systems’ Risk and Reliability” (GAMES2R) under research program “Enabling Technologies—Models.” The authors are grateful to all eight experts who participated in this study.
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Published In
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 3 • Issue 4 • December 2017
Copyright
©2017 American Society of Civil Engineers.
History
Received: Jul 28, 2016
Accepted: Mar 6, 2017
Published online: Jun 8, 2017
Discussion open until: Nov 8, 2017
Published in print: Dec 1, 2017
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