Flood prone areas are often protected against flooding by an extensive network of flood defenses. To ensure their structural integrity, these flood defenses are periodically assessed. Many levees have been functioning well for decades, and have survived several relatively high hydraulic loads within their lifetime. However, information on survived load conditions is seldom included in levee safety assessments. Observed degradation from levee inspections is also not taken into account. That way, information that is useful to improve the accuracy of estimations of the actual strength of the levee remains unexploited. This study proposes a pragmatic approach to include observations of survived loads and levee degradation in the levee safety assessment. This approach consists of three steps: (1) a prior estimation of the failure probability, based on levee characteristics, (2) a posterior estimation of the failure probability, based on observed hydraulic loads, and (3) correction of the posterior failure probability estimation, based on levee inspections. In a case study, the estimated failure probabilities using this approach were much lower than when information on levee performance was not included. This study demonstrates the value of levee performance observations and how they could be included to improve levee safety assessments.

In levee system reliability, the length effect is the term given to the phenomenon that the longer the levee, the higher the probability that it will have a weak spot and fail. Quantitatively, it is the ratio of the segment failure probability to the cross-sectional failure probability. The literature is lacking in methods to calculate the length effect in levees, and often over-simplified methods are used. An efficient (but approximate) method, which we refer to as the modified outcrossing (MO) method, was developed for the system reliability model used in Dutch national flood risk analysis and for the provision of levee assessment tools, but it is poorly documented and its accuracy has not been tested. In this paper, we propose a method to calculate the length effect in levees by sampling the joint spatial distribution of the resistance variables using a copula approach, and represented by a Bayesian Network (BN). We use the BN to verify the MO method, which is also described in detail in this paper. We describe how both methods can be used to update failure probabilities of (long) levees using survival observations (i.e., high water levels and no levee failure), which is important because we have such observations in abundance. We compared the methods via a numerical example, and found that the agreement between the segment failure probability estimates was nearly perfect in the prior case, and very good in the posterior case, for segments ranging from 500 m to 6000 m in length. These results provide a strong verification of both methods, either of which provide an attractive alternative to the more simplified approaches often encountered in the literature and in practice.

Gas extraction in the Groningen Province in the Netherlands has caused seismicity. A method was needed for probabilistic assessments of the seismic performance of the levees that protect low-lying polders against flooding. By combining the First Order Reliability Method with response surfaces it proved possible to strongly reduce the required number of simulations with advanced numerical models to obtain reliable failure probability estimates. To illustrate the workings of the method, an application to a levee cross-section along the Eemscanal with a sheet pile wall is presented. The probabilistic method can be used for probabilistic assessments and the probability-based calibration of partial factors, and it could serve as a starting point for quantitative risk analyses for levee systems in earthquake prone regions.