Davide Luongo

This study presents the results of a numerical analysis aimed to investigate the ground movements induced by groundwater table rise in drained soil conditions on slopes and the deformation patterns associated with axially rigid, shallow-founded buildings located along the slope for a preliminary assessment of the potential induced damage. Slope geometry is examined using a multi-step elastoplastic finite element approach. The numerical simulations reproduce progressive groundwater rise, generating incremental greenfield displacements and strains with the progressive reduction of the factor of safety. The deformation parameters are quantified through greenfield displacements and strains evaluated at different positions along the slope. Damage categories (e.g., slight, moderate, severe) are inferred by correlating computed deformation parameters with established limiting-strain thresholds consistent with an axially rigid structural model. Results demonstrate that increasing pore water pressures significantly amplifies ground displacements whereas the spatial distribution of damage-related strains is primarily controlled by the evolving kinematics of the slope. The modelled ground displacements indicate a predominantly translational response in the central portion of the slope, combined with finite-slope and rotational components near the crest and toe. These kinematic differences control the spatial distribution of greenfield strain distribution, with the highest values mainly concentrated in the upper part of the slope. The proposed approach should therefore be interpreted as a preliminary greenfield-based assessment of strain levels for idealised axially rigid, shallow-founded buildings, rather than as a direct prediction of observed building damage. The results represent an initial step towards a screening-level framework linking groundwater-induced slope deformation, stability reduction and potential building-related strain levels.

Historical quay walls in low-lying delta cities are increasingly challenged by ageing materials, changing load conditions, and long-term ground deformations. In the inner-city of Amsterdam (The Netherlands), a dense network of masonry quay walls founded on timber piles requires continuous prioritization to manage collapse risk at municipal scale. This paper presents a multi-source monitoring-based framework that integrates conventional (ground-based) and innovative (remote-sensing) techniques with damage information collected during in-situ surveys to support the identification of potentially critical quay walls. Displacement information derived from terrestrial instruments (acquired in both vertical and horizontal directions) and satellite Multi-temporal Interferometric Synthetic Aperture Radar (MT-InSAR) recorded along the line-of-sight (LOS) are combined with qualitative indicators describing damage conditions (e.g. deformations and cracks on apron or wall façade) and kinematic behaviour (e.g. tilting, bulging) observed during in-situ inspections. Rather than aiming at detailed structural and stability verification of the single retaining structure (quay wall), the proposed analysis focuses on extracting consistent patterns between observed damage and recorded displacements, posing the base knowledge for developing a methodological procedure that allows the investigation of existing cause-effect relationships and the identification of the most probable collapse mechanisms. The results achieved highlights how multi-source monitoring and surveying sources can be jointly interpreted to support, at municipal scale, risk-informed decision making and the planning of mitigation strategies for historical retaining structures.

Road networks are typically the main component of transportation systems, acting as critical lifelines for mobility, emergency response, and access to essential services. In mountainous and hilly regions, these infrastructures are frequently threatened by slow-moving landslides, which can lead to progressive ground deformation and long-term serviceability loss. Despite the need for continuous operability, local authorities often face significant challenges in risk management due to budget limitations and lack of complete and accurate information.This study proposes a framework aimed at identifying risk-mitigation priorities for road networks exposed to slow-moving landslides at municipal scale by integrating the assessment of landslide exposure with the analysis of criticality along the road network. The exposure assessment follows a matrix-based approach combining three indicators: a statistical susceptibility index, displacement measurements derived from Advanced Differential Synthetic Aperture Radar Interferometry (A-DInSAR), and damage severity derived from virtual surveys using Google Street View. The criticality of the road stretches is quantified based on the reduction in network efficiency under disruption scenarios.The methodology was applied to the road networks in the municipalities of Vaglio Basilicata, Brindisi Montagna and Trivigno (Basilicata region, southern Italy), which are highly affected by slow-moving landslides. The results indicate that, although approximately 31% of the network intersects slow-moving landslides, only 5% of the road stretches are classified at very high level of priority. This highlights the critical role of network topology in influencing risk-mitigation priorities. The proposed framework provides a cost-effective, flexible tool for local administrations to optimize resource allocation and prioritize site-specific investigations.

Slow-moving landslides are widespread natural hazards that can affect social and economic activities, causing damage to structures and infrastructures. This paper aims at proposing a procedure to analyze road damage induced by slow-moving landslides based on the joint use of landslide susceptibility maps, a road-damage database developed using Google Street View images and ground-displacement measurements derived from the interferometric processing of satellite SAR images. The procedure is applied to the municipalities of Vaglio Basilicata and Trivigno in the Basilicata region (southern Italy) following a matrix-based approach. First, a susceptibility analysis is carried out at the municipal scale, using data from landslide inventories and thematic information available over the entire municipalities. Then, the susceptibility index, the class of movement and the level of damage are calculated for the territorial units corresponding to the road corridors under investigation. Finally, the road networks are divided into stretches, each one characterized by a specific level of risk (or attention required) following the aggregation of the information provided by the performed analyses. The results highlight the importance of integrating all of these different approaches and data for obtaining quantitative information on the spatial and temporal behavior of slow-moving landslides affecting road networks.