Landslides are one of the most significant natural hazards worldwide. They can have far-reaching negative impacts on societies in different socio-economic sectors as well as on the landscape. Among the different types and processes that can also affect infrastructure and land use planning, slow-moving landslides are often underestimated. Therefore, studying areas affected by slow movements provide an opportunity to better understand the spatial and temporal patterns of these processes, their forcings, mechanisms, and potential risks. This study aims to investigate the importance of historical data for improving landslide hazard assessment in Lower Austria (Austria), which is particularly prone to landslides. This paper focuses on how historical information formed the basis for the establishment of three long-term landslide monitoring observatories in this region. The analysis conducted highlights the importance of using historical data to better assess the frequency and magnitude relationships and phases of landslide activity. In particular, they can extend the temporal window and provide relevant information on past events and accelerations to improve knowledge of landslide dynamics and the resulting socio-economic impacts. In order to better assess the landslide hazard associated, it is necessary to integrate historical data and monitoring datasets obtained by surface and subsurface methods. Both components allow for the characterization of the spatio-temporal evolution of slow movements and the analysis of the hazard over time. Based on a variety of historical sources, it was possible to install the instruments constituting the long-term landslide monitoring observatories in a meaningful manner. The results demonstrate the influential role of human impact on the stability conditions, which may also contribute to landslide occurrence. In this regard, the attempt to combine historical data and long-term, continuous monitoring systems in the presented landslide observatories can improve landslide risk reduction measures in the region. The integration of different techniques and tools, along with ongoing research and collaboration with local authorities, will further improve our understanding of these slow-moving processes and the development of effective management strategies.

Soil moisture plays a crucial role in landslide research as it directly influences slope stability and the occurrence of landslides. The amount of water present in the soil significantly impacts its strength and cohesion. Excessive soil moisture, especially during periods of heavy rainfall, can reduce the frictional resistance within the soil, leading to a decrease in shear strength and an increased likelihood of landslides. The province of Lower Austria is situated in a region highly prone to landslides due to its specific geological characteristics. The prevailing geological formations consist mainly of the Flysch and the Klippen Zone, characterized by mechanically weak units comprising intercalated limestones and deeply weathered materials. These geological conditions, coupled with hydrological factors, changes in land use, and various anthropogenic influences, collectively contribute to the inherent instability of the region.Monitoring and understanding soil moisture levels provide valuable insights into the predisposing and triggering factors, potentially enhancing the prediction and mitigation of these hazardous events. Advancements in technologies like Cosmic Rays Neutron Sensing (CRNS) enables to obtain spatially averaged soil moisture measurements, offering a more comprehensive understanding of moisture distribution across different scales. The defining characteristic of (CRNS) technology lies in its ability to directly measure water content, naturally averaged within a volume known as the footprint. This volume encompasses a horizontal extension with a radius spanning up to hundreds of meters and penetrates the soil to depths of tens of centimeters. This is widely acknowledged as the primary advantage of the CRNS probe compared to point-scale measurements, as it yields a valuable representative value for water availability in the designated area. In this study, we apply CRNS at a slow-moving landslide in Lower Austria and explore its potential.

Despite extensive literature on the effectiveness of drainage systems and documented cases of landslides linked to leaking and burst pipes, malfunctioning drainage systems are rarely incorporated into hazard modelling. Porewater pressure is a major control of landslides, commonly managed through the installation of drainage systems. Paradoxically, such an intervention can act as a landslide driver rather than a mitigation measure. Malfunctioning drainage systems and burst pipes may disrupt slope hydrological connectivity and, in some cases, lead to oversaturation, thereby elevating localized pore water pressure. This study aims to quantify in data scarce regions, through numerical simulations, the influence of malfunctioning drainage systems on landslide dynamics, from initiation to propagation.The complex Hofermühle landslide in Lower Austria is an illustrative case of the interplay between natural and anthropogenic processes. Previous activities of this landslide and its proximity to a stream have led to the installation of subsurface drainage for decades to dewater the hillslope. We develop a landslide conceptual model of a mudflow event that occurred on 21 April 2013 using long-term monitoring data, residents' reports, 2D seepage and slope stability analyses, and propagation modelling (r.avaflow). The seepage and slope stability analysis demonstrates that the malfunctioning drainage scenario is the most plausible trigger of the reported landslide event.Our results indicate that a drainage capacity of less than 40% and an antecedent malfunction of at least 68 days before failure were likely factors in the 2013 landslide. The mudflow results from sufficient water storage, localized porewater pressures, seepage emergence, and, thus, slope failure which transformed into a flow. The preliminary propagation analysis showed that a minimum volume of 100 m-3 is necessary to propagate the initial landslide mass downstream. Our findings suggest that abandoned drainage infrastructure may play a crucial role in landslide occurrences. The backward simulation is a demonstrative example of a process that may become increasingly important as projected future urbanization and associated hillslope modifications unfold.

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.