Combining statistical and expert evidence using belief functions: Application to centennial sea level estimation taking into account climate change

Nadia Ben Abdallah (1) , Nassima Mouhous-Voyneau (2) , Thierry Denoeux (1)

1 Heudiasyc - Heuristique et Diagnostic des Systèmes Complexes [Compiègne]
2 AVENUES - AVENUES

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.

Mots clés: Sea level rise; structural design; coastal defense; Dempster-Shafer theory; Evidence theory; random intervals; experts opinions; statistical inference; likelihood-based belief functions

Domaines: Intelligence artificielle [cs.AI]

Nadia Ben Abdallah, Nassima Mouhous-Voyneau, Thierry Denoeux. Combining statistical and expert evidence using belief functions: Application to centennial sea level estimation taking into account climate change. International Journal of Approximate Reasoning, 2014, 55 (1), pp.341-354. ⟨10.1016/j.ijar.2013.03.008⟩. ⟨hal-00932879⟩