Kerstin Lesny

This study presents a probabilistic framework for slope stability assessment that systematically accounts for stratigraphic uncertainty derived from cone penetration test (CPT) data. The framework integrates Gaussian mixture models (GMMs) for soft clustering with inverse transformation sampling (ITS) to generate ensembles of plausible soil layering configurations. This combination enables a consistent propagation of stratigraphic uncertainty into a subsequent reliability analysis. Conventional deterministic approaches and probabilistic methods rely solely on the most likely stratification. In contrast, the proposed framework quantifies the full range of plausible subsurface configurations. ITS produces multiple stratigraphic realizations that preserve the probabilistic structure of the GMM by treating each depth as a categorical distribution defined by the posterior cluster probabilities. For subsequent stability assessment, soil parameters, such as the effective friction angle and unit weight, are derived from empirical transformation models. These models take into account both observed variability and transformation uncertainties. The application of the framework to a soil slope founded on bedrock demonstrates that even moderate variations in stratigraphy can lead to substantial differences in the computed mean factor of safety (FS) and the probability of failure (Pf). The results emphasize that accounting for stratigraphic variability provides a more realistic and transparent quantification of slope reliability. The presented approach thus establishes a systematic, data-driven methodology for integrating CPT-based uncertainty into geotechnical design and risk assessment.

Unlike most other measures in flood risk management, flood forecasting stands out because it is not designed to address a pre-defined return period. In principle it is applicable to a whole range of possible events and can be operated continuously in real time. This makes flood forecasting an effective non-structural measure for saving lives and property, even in the face of increased hydro-meteorological variability and extremes. In Germany, a series of regional and transregional flood forecasting centres and services have been established that cover the entire national territory. For large basins, the existing forecasting centres are well equipped to provide accurate real-time forecasts. Nevertheless, there are remaining challenges that need to be met when the focus is on small to medium-sized catchments. This study focuses on discussing the capabilities of six state-of-the-art flood forecasting centres and derives the most important requirements for significant improvements in flood forecasting capabilities for small to medium-sized catchment areas. We emphasise that future research must focus on flood-driven predictions, including the prediction of flood inundation and consequences for buildings and infrastructure, as well as geotechnical failure mechanisms in Germany.

In the new second generation version of Eurocode 7, Part 3 the limit state design for various geotechnical structures is outlined. Spread foundations are covered in Clause 5 of this part where requirements for the verification of ultimate and serviceability limit states are provided. In comparison to the current version of Eurocode 7 the requirements have been improved first by revising the structure of this clause so that it is now unified and consistent with the other clauses in this part and follows the design-path defined in Part 1. In addition, various aspects addressing the limit state design of spread foundations have been complemented or modified such as the inclusion of the well-known Terzaghi-Buisman method for calculating the bearing resistance in the main text, the explicit consideration of rock mass as well as various calculation models provided in Annex B, e.g. models for punching failure and foundation settlement evaluation. The present paper provides an overview of the design of spread foundations according to the new Eurocode 7. A simple design example illustrates the design procedure.