Traditional geotechnical design methodologies for quay walls rely on safety factors and characteristic soil properties to achieve safety; however, they can under-predict actual structural performance. Recent studies show that monitoring data can be used to update reliability calculations to thereby reduce
uncertainty, reveal hidden capacity, and extend the economic lifetime of such structures. However, applications to real-life cases have been limited and focus on single failure mechanisms only. Therefore, the primary objective of this thesis is to develop a computationally efficient framework that uses monitoring data to update the reliability of a quay wall across multiple failure modes. Specifically, yielding of the quay wall structure, yielding of the anchor rod, and loss of overall stability are considered.

In the methodology, the probability density functions of a number of stochastic variables are updated and based on their prior and posterior distributions, the prior and posterior reliabilities are determined. This methodology is executed by coupling a Bayesian updating strategy via subset simulation (aBUSSuS) with a metamodelling technique using active learning Kriging interpolation (ERRAGA). The method uses a “master-shadow” strategy to train separate Kriging models while saving preliminary results, thereby significantly reducing the required number of computationally expensive Plaxis 2D simulations. This framework is validated on a simplified theoretical demonstration case before being applied to a more complex case study at the Maasvlakte in the Port of Rotterdam. This latter case uses deformation data gathered by ShapeAccelArray (SAA) instruments during a full-scale load test.

The demonstration case proved the viability of the method: with targeted Plaxis runs, the probability of failure could be obtained for all three failure modes. Furthermore, the posterior deformations merged toward the fictitious measurements and the probability was updated accordingly. Saving results and
the recycling of Plaxis realizations more than halved the required number of finite element runs for this case. For the Maasvlakte - Port of Rotterdam case, the finite element model was more complex and hence additional strategies were implemented to guarantee convergence within 24 hours. Here, an a priori sensitivity analysis identified the parameters with the greatest impact on the model output, ensuring that computational resources were focused on the variables undergoing the most significant updates. By recycling finite element results across the different steps and optimising the Kriging convergence criteria, the method was then able to quantify and update the reliability of the three failure mechanisms within a practically viable 24-hour window. Ultimately, even with the integration of global model uncertainty, the framework resulted in significant reliability updates for the complex, full-scale quay wall.

The main conclusion of this research is therefore that multi-mechanism reliability updating using monitoring data is viable for full-scale quay walls and offers a way to reduce over-conservatism in existing designs. However, model inaccuracies heavily influence the outcomes and under the presented approach,
conservative models can lead to non-conservative updates by inducing disproportionately large parameter shifts. To fully replicate the field measurements for the Maasvlakte case, the soil friction angles had to be pushed beyond their realistic physical limits, which drove up posterior reliability levels.
The discrepancies are largely attributed to the limitations of the 2D plane-strain modelling. Hence, future research should focus on a fundamental revision of the underlying Plaxis model by transitioning to a 3D setup and a more precise derivation of expected parameter values. To cope with the increased computational demand of 3D simulations, acceleration techniques such as parallel computing should be integrated. Furthermore, future studies should account for additional failure modes and correlations between failure modes to derive a comprehensive system probability of failure. ... Read more

Sand is one of the most extracted natural resources worldwide, and demand continues to rise along with population and infrastructure development. In Argentina, the Lower Paraná Delta has become a key source of sand for both construction and hydraulic fracturing (fracking) activities. While sand mining can generate short-term economic benefits, its environmental and socioeconomic impacts on the delta remain poorly understood. Therefore, this study aims to answer the following research question: ”What are the morphological and socioeconomic effects of sand extraction in the Lower Paraná Delta and how can these be managed to secure a sustainable future?”. Both river and land-based sand mining and their respective effects on the delta were researched.

The research applied a multidisciplinary approach combining hydraulic, geotechnical, and structural engineering perspectives. Quantitative analyses were based on field measurements, sediment sampling, and hydrodynamic modelling with Delft3D. Additionally, stakeholder interviews and data from the Automatic Identification System (AIS) of vessels were used to assess extraction volumes and local perceptions. This combination allowed for a comparative evaluation of river and dry sand mining.

Results show that river sand extraction remains relatively stable across large parts of the study area, while local government intervention has effectively halted dredging activities in the Paraná Ibicuy, in the northern section of the delta. Current extraction volumes are estimated at approximately 588,000 tons
per year. In contrast, dry sand mining has increased sharply, reaching about 2.3 million tons in 2025 in Ibicuy, primarily driven by the growing demand for fracking sand from the Vaca Muerta formation. The established sediment balance of the Paraná Guazú River indicates a negative change in sediment storage of roughly 15,400 tons per day, suggesting a general trend of sediment depletion.

Erosion rates in the study area range between 3 and 7 meters per year, which, although significant, are considerably lower than values reported by some stakeholders. Analyses indicate that natural processes, including river meandering and flood-induced bank instability, are the dominant drivers of bank erosion, while river sand mining does not appear to play a substantial role. Because of their larger scale and intensity, the socioeconomic impacts of dry sand mining are more pronounced, leading to groundwater overuse, road deterioration, and habitat loss. Additionally, low taxation on sand mining activities has enabled these impacts to persist with limited mitigation or compensation. To mitigate erosion, a structural solution in the form of a sheet pile was proposed. Furthermore, Nature-based mitigation strategies have been proposed, the focus lies on floodplains, vegetation and riparian buffer zones.

The accuracy of the study is constrained by the short temporal coverage of field data and the simplified representation of hydrodynamics and sediment transport in the numerical model. To build on these findings, future research should include long-term monitoring, enhanced sediment datasets, and morphodynamic modeling to assess feedbacks between extraction and river response. Integrating Naturebased solutions with targeted structural measures, supported by cost–benefit analyses, would provide a more comprehensive framework for sustainable sand mining management in the Lower Paraná Delta. ... Read more

In the Port of Emden, maintenance of the nautical depth is carried out by continuous re-circulation of sediment, creating a navigable fluid mud layer in the water and thereby facilitating safe navigation for ships. The sediment naturally contains organic matter, which to a certain extent is degradable by sediment microorganisms. Depending on the availability of oxygen, the degradation process generates carbon dioxide only (aerobic conditions) or methane and carbon dioxide (anaerobic conditions). This thesis aims to quantify the production of carbon dioxide and methane from fluid mud in the Port of Emden and analyze its seasonal variability to support carbon footprinting of sediment management activities. In this thesis, an experiment was carried out to determine the carbon production of Emden samples at different temperatures. Results were used and, based on the fluid mud temperatures throughout the year, monthly carbon production was calculated. These values were adjusted for seasonal variations in organic matter availability and finally extrapolated to give the total monthly carbon production for the port. Using data from previous research, upper and lower bounds for this production were found. The findings indicate that carbon production in the Port of Emden, due to micro-organisms in the fluid mud layer, varies significantly over the year. Specifically, the generated carbon was found to differ between 243 tons in February and 958 tons in August, with the upper bound being 7.2 times greater than these values and the lower bound 1.3 times smaller. From April until October, carbon generation was found to be considerably higher than from November until March, due to higher water temperatures and likely a greater availability of organic matter. Finally, the carbon production under aerobic conditions was found to be 2.7 to 2.8 times greater than under current conditions, with similar seasonal variability. Limitations of this thesis include assumptions about uniform seasonal scaling of organic matter availability and incomplete data on fluid mud temperature variations across the year. Future research could address these limitations by gathering and incorporating more data on these parameters. Finally, future studies should focus on applying the findings of this thesis to explore strategies for reducing the carbon footprint of sediment management activities. ... Read more