Abstract
AbstractStudies carried out to analyse the risks of levees must include an evaluation of the probabilities of occurrence of different failure mechanisms. The probabilistic quantitative evaluation of these mechanisms remains difficult due to often insufficient data, the natural variability of the materials, structures that are very long, and the unavailability of mechanical models for certain failure mechanisms. This makes it necessary to call for expert judgement to evaluate the probabilities of failure. However, expert judgement generally has qualitative and subjective dimensions, and it includes biases that are liable to impair the capacities of an expert to elicit their evaluations. This article proposes an approach to processing expert judgement that includes the modalities of Individual expert Elicitation, Calibration, Aggregation, and Debiasing of expert judgement (IeCAD). This IeCAD approach has been developed for river levees in view to correcting biased expert evaluations in the case of evaluating the failure probability of structures.
Highlights
River levees are structures that are raised above the natural level of the land in view to protecting naturally floodable areas (Peyras et al, 2015)
The levee studied is an earth-fill levee 5,500 m long raised to protect a town in France (Figure 4)
The results obtained in the case study show that the calibration-aggregation phase as well as the debiasing phase of the developed approach allow improving the results obtained from expert elicitations
Summary
River levees are structures that are raised above the natural level of the land in view to protecting naturally floodable areas (Peyras et al, 2015). Evaluating the reliability of levees is a major challenge for the managers of these structures in order to predict a risk of failure (Kolen, Slomp, & Jonkman, 2013). Many regulations require the evaluation of the reliability of structures in a probabilistic framework, in order to demonstrate levee failure risks (Ciria et al, 2013). Many levees are old structures and there is limited knowledge on their initial construction and further reinforcements over time, and information on their behaviour is seldom available (Ciria et al, 2013; Tourment, 2018). Evaluating the reliability of river levees in a probabilistic framework is difficult due to the scarcity of available data, related to the material composition of the levee throughout its length, their geotechnical properties, hydraulic and mechanical behaviour of levees as leakages, pore pressures, and displacements. Contrary to other hydraulic structures such as dams for which large
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