Journal
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
Volume 55, Issue 1, Pages 341-354Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.ijar.2013.03.008
Keywords
Coastal defense; Dempster-Shafer theory; Evidence theory; Random intervals; Statistical inference; Likelihood-based belief functions
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Estimation of extreme sea levels for high return periods is of prime importance in hydrological design and flood risk assessment. Common practice consists of inferring design levels from historical observations and assuming the distribution of extreme values to be stationary. However, in recent years, there has been a growing awareness of the necessity to integrate the effects of climate change in environmental analysis. In this paper, we present a methodology based on belief functions to combine statistical judgements with expert evidence in order to predict the future centennial sea level at a particular location, taking into account climate change. Likelihood-based belief functions derived from statistical observations are combined with random intervals encoding expert assessments of the 21st century sea level rise. Monte Carlo simulations allow us to compute belief and plausibility degrees for various hypotheses about the design parameter. (C) 2013 Elsevier Inc. All rights reserved.
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