Abstract
Abstract. This paper addresses the use of reliability techniques such as Rosenblueth's Point-Estimate Method (PEM) as a practical alternative to more precise Monte Carlo approaches to get estimates of the mean and variance of uncertain flood parameters water depth and velocity. These parameters define the flood severity, which is a concept used for decision-making in the context of flood risk assessment. The method proposed is particularly useful when the degree of complexity of the hydraulic models makes Monte Carlo inapplicable in terms of computing time, but when a measure of the variability of these parameters is still needed. The capacity of PEM, which is a special case of numerical quadrature based on orthogonal polynomials, to evaluate the first two moments of performance functions such as the water depth and velocity is demonstrated in the case of a single river reach using a 1-D HEC-RAS model. It is shown that in some cases, using a simple variable transformation, statistical distributions of both water depth and velocity approximate the lognormal. As this distribution is fully defined by its mean and variance, PEM can be used to define the full probability distribution function of these flood parameters and so allowing for probability estimations of flood severity. Then, an application of the method to the same river reach using a 2-D Shallow Water Equations (SWE) model is performed. Flood maps of mean and standard deviation of water depth and velocity are obtained, and uncertainty in the extension of flooded areas with different severity levels is assessed. It is recognized, though, that whenever application of Monte Carlo method is practically feasible, it is a preferred approach.
Highlights
Flooding poses a risk to people and causes significant economic costs
This paper addresses the use of reliability techniques such as Rosenblueth’s Point-Estimate Method, PEM, as a practical alternative to more precise Monte Carlo approaches to get estimates of the mean and variance of flood parameters such as water depth and velocity
In the context of assessing the uncertainty in flood modelling in a river reach, the results presented have shown the practical applicability of the point-estimate method to perform uncertainty flood analysis, considering the Manning’s n roughness coefficient as the main source of uncertainty
Summary
Flooding poses a risk to people and causes significant economic costs. In the last century flood disasters accounted for 12 % of all deaths from natural hazards (DEFRA, 2009). Altarejos-Garcıa et al.: Assessing the impact of uncertainty on flood risk estimates with reliability analysis 1897 the method becomes inapplicable for practical purposes To avoid this problem it is possible to use simplified models that are much less demanding in terms of computing time. This paper addresses the use of reliability techniques such as Rosenblueth’s Point-Estimate Method, PEM, as a practical alternative to more precise Monte Carlo approaches to get estimates of the mean and variance of flood parameters such as water depth and velocity These parameters define the flood severity, which is a concept used for decision-making in the context of flood disaster risk assessment. The paper compares results between different methods to deal with uncertainty using the same mathematical hydraulic models
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