Dykes provide protection from the risk of flooding to approximately 60% of the Netherlands, by area. Unfortunately, most of the country’s major cities lie within this zone, placing a large proportion of the population at risk should these flood defences fail. In total the Netherlands have over 3800 km of primary flood defences protecting the coast and inland river systems with another 14000km protecting individual polders. Recent flood events in Europe caused by extreme rainfall have raised concerns about the ability of the Dutch river dykes to resist similar events. This paper describes a quantitative assessment of the vulnerability to flooding of a primary river dyke outside Dordrecht. The dyke has shown significant signs of distress over recent years developing large tension cracks during periods of drought on its leeward side, which have progressively increased in size. It is regularly inspected by the local water authority due to its concerning visible deterioration. In this study, soil uncertainty is quantified from in-situ geotechnical tests and laboratory tests. Several failure mechanisms are then considered probabilistically, namely global stability, rapid drawdown, internal erosion and overtopping. Fragility curves are generated for each failure mechanism describing how the probability of failure would change if a given flood level were to occur, event trees are used to link the individual failure mechanisms and quantify the system probability of failure. This paper illustrates the use of fragility curves for earthwork asset management and advantages and limitations of the methodology utilised are discussed.@en

The paper describes a study on the liquefaction potential of flood defences along the rivers running through the delta area of the Netherlands. The study concentrates on an area south of Rotterdam. The dykes used as primary flood defences protect an urban, rural, and industrial area of 102,400 ha. In this paper the data from more than 4200 Cone Penetration Tests, CPT traces are used to assess more than 200 km of dykes. The pore pressure, u2 data is analysed, then used to separate the material response into contractive and dilative zones. Using the separation of liquefaction susceptible soils, and geometry of the riverbed a regional hazard map is generated. The choices for the data visualisation and their effect on the generated map are discussed and presented. The final liquefaction susceptibility map is used by the water governing authority Waterschap Hollandse Delta as a decision-making tool to improve the efficacy of liquefaction hazard assessment such as the location and return period of bathymetry measurements, and the scale of site-and laboratory investigation.

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In an attempt to evaluate current models for the safety assessment of dykes on soft soils, STOWA, the foundation for research on regional dykes in the Netherlands, launched and supported a full scale test on a regional historical dyke, which included observation of the pre-failure response and the design of its failure. The stress test on the dyke included progressive excavation at the toe and rapid drawdown in the ditch next to the toe of the embankment, until failure eventually occurred. The data and the observations collected on site during the test are a unique body of information on the coupled hydro-mechanical pre-failure behaviour and on the resistance of the earth construction. A selection of these data was included in the formulation of the Theme C of the 15th International Benchmark Workshop on Numerical Analysis of Dams, held in September 2019 in Milano, Italy. This contribution presents the main outcomes of the numerical benchmark, coming from the results of the different groups, which analysed the case with current geotechnical constitutive and numerical models.

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Soil spatial variability has a significant impact on the reliability of geotechnical structures. In particular, the horizontal variability is important for linear infrastructure, which has only limited vertical height and width, but extensive length. Due to depositional and geological processes, the variability is often substantially different in the vertical and lateral directions. This variability can be characterised by a spatial correlation length, or scale of fluctuation, which is a measure of how significantly soil properties are correlated in space. An analysis of the reliability of such a measure has been undertaken using synthetic data, leading to a design chart which quantifies the statistical uncertainty in the scale of fluctuation for specific site investigation designs, which can be an important input for probabilistic analyses of the structure response. Moreover, practical guidance for site investigation design is proposed which can reduce the statistical uncertainty. The method has been applied to a real site investigation comprising a row of 29 closely spaced cone penetration tests (CPTs), within a larger site investigation of 100 CPTs, and applied to a simple design calculation for a long embankment to illustrate the impact on slope stability assessment. The site investigation data are made available to add to the limited amount of detailed data in this field.

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This thesis presents an investigation of the use and applicability of statistical methods in site investigation and subsequent analyses of dykes and embankments. This comprises a comprehensive site investigation via Cone Penetration Tests (CPTs) and laboratory experiments on sampled material, a large scale field test, and statistical analysis of both the site investigation data and the failure test. This work offers the potential to better design site investigations in order to provide reliable estimates of heterogeneity and to demonstrate how these can be used in practical analyses. Such analyses are computationally expensive, but can offer significant benefits in reducing the requirements of dyke upgrades.@en

A reliability-based analysis framework, accounting for uncertainty arising from the spatial variability of soil properties, has been validated for the controlled, well-instrumented slope failure of an historic dyke in the Netherlands. Using soil property statistics derived from the results of laboratory and cone penetration test (CPT) data for the different soil layers at the site, the dyke was analysed for the initial (i.e. operating) conditions, as well as for the later stage of the test leading up to failure. The computed probabilities of failure and back-figured factors of safety were consistent with the point at which failure occurred in the test, as was the range of possible failure mechanisms. The uncertainty in the stability assessment was reduced by considering the spatial nature of the soil variability, and by conditioning analyses to CPT measurement data. It is shown that the reliability-based approach enables more informed stability assessments that could make the difference between a dyke being assessed as safe or requiring costly improvement.@en

Measuring soil variability has many challenges. One of the challenges is soil deformation, which can change the spatial correlation structure arising from the original geological processes. In particular, this is important in the assessment of existing structures. In this paper, the effect of existing structures on the horizontal spatial correlation is investigated using a dataset consisting of 100 CPTs in close proximity. These data were collected under and adjacent to a dyke structure which has caused considerable deformations. Using CPTs in zones where deformation has not occurred has allowed a quantification of this effect. The impact of the dyke is shown to dominate the natural scale of fluctuation.@en

A case study involving the assessment and re-design of an existing dyke, founded on a layered soil, has compared deterministic analysis based on 5-percentile property values and a reliability-based random finite element analysis consistent with the requirements of Eurocode 7. The results show that a consideration of the spatial nature of soil variability generally leads to higher computed factors of safety and, for those dyke sections requiring remedial action, to more economic designs. Back-figured characteristic values are shown to be considerably higher than the 5-percentile soil properties; hence, a reduction in over-conservatism is achieved.@en

The variability of soil is well known to affect the geotechnical performance of structures. As probabilistic design methods become more commonly used, the ability to measure the variability of soil becomes more important. However, by using only the point statistics of soil parameters in design (e.g. the mean and standard deviation), typically an over-estimation of failure probabilities occurs, leading to over-conservative designs. By looking at the spatial correlation (e.g. scales of fluctuation) a more accurate representation can be achieved. This paper presents a method to use vertical Cone Penetration Tests (CPTs) to detect both the vertical and horizontal scales of fluctuation. An extensive numerical and experimental investigation has been undertaken to understand how spatial variation can be estimated and to quantify the accuracy in that estimation. The impact of being able to quantify the uncertainty is illustrated via a simple slope stability example.@en

The Random Finite Element Method (RFEM) has been shown in many theoretical publications to offer advantages in the quantification of the probability of failure. However, it has rarely been applied in real situations (geometry, material properties, soil layers) and seldom, if at all, to a well instrumented geotechnical failure. This paper reports a case study of a full-scale controlled dyke failure, where the heterogeneity was previously measured via CPTs (Cone Penetration Tests), and the dyke itself was highly instrumented. This offers the opportunity to compare and apply various techniques previously developed (e.g. random field conditioning) with field data, rather than to computer generated data. The RFEM analyses presented are compared with deterministic analyses, demonstrating the relative performance of the methods.@en

The material point method is a finite element variant which allows the material, represented by a point-wise discretization, to move through the background mesh. This means that large deformations, such as those observed post slope failure, can be computed. By coupling this material level discretization to the spatial variability of the material generated by random fields and embedding this into a Monte Carlo framework, a new method called the Random Material Point Method (RMPM) has been developed. This method retains the advantages of the so-called random finite element method, that is, a risk based interpretation of the influence of spatial variability of the material properties, but additionally enables the effective modeling of large deformations to give a risk based interpretation of post-failure mechanisms. After a brief introduction to the RMPM methodology, the analysis of an idealized cohesion strain-softening clay slope is presented, which illustrates the influence of anisotropy of the material variability on the evolution of retrogressive slope failures. @en