Early Warning Systems for Landslides in the urban area of Rome (Italy): an integrated approach

Landslides in densely urbanized areas pose significant risks to infrastructure, services, and public safety, motivating the development of operational Landslide Early Warning Systems (LEWS). Within a collaboration between ISPRA and the Civil Protection Department of the Municipality of Rome, three sites affected by rainfall-induced shallow landslides are currently being investigated to support early warning activities. Among them, the Mt. Mario site is of particular interest due to the occurrence of two severe wildfires (July 2024 and June 2025) that damaged vegetation over approximately 12.5 ha, followed by intense rainfall events that triggered shallow landslide trenches and scarps. Such disturbances alter hydro-mechanical soil properties by modifying root reinforcement, hydraulic conductivity, ash deposition, and surface runoff dynamics, thereby affecting slope stability.

In collaboration with the Civil Protection Department, a multi-scale monitoring strategy has been deployed across the three sites, including IoT in-soil sensors (soil moisture, water potential, biaxial clinometers), meteorological stations (rainfall intensity, solar radiation, temperature, humidity, wind), piezometer, inclinometer, and geophysical surveys. Concurrently, an extensive laboratory campaign is characterizing the site through direct shear tests, permeability measurements, soil water retention curves, and physical property analyses on undisturbed samples – typically made of silty/clayey sands. During the first monitoring year, the aim is to assess the coupled hydro-mechanical response of the slope under varying meteorological conditions.

Digital twins of the monitored sites are being developed by combining finite-element and limit-equilibrium modelling to investigate the behaviour of the slopes in consequence to external meteorological inputs, vegetation presence and root decay, and set the basis for threshold definition for LEWS. The final goal of the study is to inform the design of warning thresholds, optimize sensor deployment, and improve risk mitigation strategies for urban slopes.