Investigating the role of pore water pressure and antecedent conditions in landslide acceleration: Insights from long-term monitoring in Lower Austria

Predicting the spatial and temporal evolution of landslides is still one of the greatest challenges in landslide research. This is mainly due to the heterogeneous and complex interplay of landslide conditioning and triggering factors, which can lead to non-linear temporal and kinematic responses. Despite the growing literature demonstrating that hydrological antecedent conditions play a role in landslide acceleration, most landslide early warning systems (LEWS) often use only rainfall thresholds as the main triggering parameter. Therefore, the development of hydrometeorological threshold models that take into account pore water pressure data, antecedent hydrological conditions, and physiographic characteristics of slopes offers a great opportunity to improve existing LEWS. However, the investigation of slope dynamics and hydrometeorological thresholds requires an accurate, high-resolution data set. For this reason, the University of Vienna has initiated a long-term monitoring project (NoeSLIDE) that aims to obtain long-term in-situ surface and subsurface data (e.g. precipitation, piezometric levels, volumetric water content, vertical displacement) of several slopes in the region of Lower Austria.

In this study, the hydromechanical behaviour of a selected slope, the Hofermühle landslide, is investigated. We use an integrated approach combining field investigations, soil analysis, remote sensing, time series analysis (e.g. PASTAS) and numerical modelling to: (1) characterise the mechanical behaviour of the slope, (2) estimate snowpack and snowmelt rates, (3) understand and simulate the response and timing of groundwater, and thus porewater pressure, to rainfall and snowmelt, and (4) analyse the response of the slope to changes in porewater pressure to determine the critical hydro-meteorological conditions that lead to landslide accelerations. The preliminary results indicate that the studied landslide accelerates mainly in winter and spring and shows a heterogeneous spatial response to rainfall and snowmelt, which is largely influenced by its complex lithologic and hydrologic conditions. Furthermore, although changes in pore water pressure are the main driving mechanism for landslide acceleration, dry antecedent conditions and seasonal preferential flow patterns are also crucial for this process and need to be considered. This study provides useful information for disaster risk reduction as it is a further step towards a better understanding of the complex behaviour of landslides in Lower Austria.