Research area: Applied Earth Sciences
Coordinators: Claudia Meisina, Massimiliano Bordoni, Farncesco Zucca
ERC sectors: PE10_20 Geohazards
1. Mapping and characterization of soils subject to rainfall-induced landslides
This research topic aims to provide a multidisciplinary characterization of soils subject to rainfall-induced landslides. Characterization is performed through laboratory tests to measure the physical, grain size, mechanical, and hydrological characteristics of materials; field tests to characterize hydrological and permeability characteristics of materials; and static penetrometer tests (CPT and CPTU). Data-driven methods are used to assess the thickness of overburden subjected to rainfall-induced landslides.
2. Mapping and monitoring of rainfall-induced landslides using remote sensing data and proximal remote sensing data
Automatic rapid mapping methodologies are being developed following intense rainfall events based on satellite imagery. Methodologies are being developed for the interpretation of satellite interferometric data (A-DInSAR) at regional and detailed scales for updating inventories and monitoring landslide events. Satellite rainfall and soil moisture data are analyzed to define hydrological thresholds for landslide triggering and to create dynamic hazard maps. Proximal remote sensing techniques based on thermal imaging are being developed to monitor the temporal and spatial evolution of rainfall-induced landslides.
3. Hydrological and geotechnical monitoring of slopes subject to rainfall-induced landslides
Several hydrological-geotechnical monitoring stations have been installed in different geological and land-use contexts to understand the triggering mechanisms of rainfall-induced landslides and to define trigger thresholds for use in Landslide Early Warning Systems. At these sites, sensors and geophysical methods for measuring soil water content and pore pressure are being tested. Various physically-based and data-driven methodologies are being developed for modeling soil water content and pore pressure.
4. Modeling Rainfall-Induced Landslide Susceptibility and Hazard
This research topic aims to develop models that quantify the susceptibility and hazard to rainfall-induced landslides at different spatial (local, basin, regional) and temporal (sub-daily, daily; considering current conditions or future scenarios) scales. Physically based or data-driven models are developed, integrating: predisposing geological and geomorphological factors; soil hydrological factors derived from in-situ monitoring; rainfall maps and soil hydrological parameters obtained from satellite remote sensing; and landslide inventories detected using various techniques (field surveys, aerial photo analysis, satellite image analysis).
5. Analysis of the Role of Land Use and Agricultural Practices in Rainfall-Induced Landslide Susceptibility
Land use and agricultural management practices on cultivated slopes are predisposing factors for the development of rainfall-induced shallow landslides. The susceptibility of different land uses to these processes and the assessment of which practices can limit these phenomena are assessed by incorporating, into physically based or data-driven stability models, the mechanical contribution of roots present in the soil (root reinforcement) and how various management practices can influence the soil's hydrological response to periods of rainfall and drought. Scenarios of changes in landslide or erosion hazard related to land use changes are also developed. The results are used to develop best practices for land management.
6. Measurement and modeling of shallow landslide propagation areas
Rainfall-induced shallow landslides cause serious consequences for people, infrastructure, and crops. For proper land management and the risk associated with these phenomena, it is essential to estimate not only the trigger areas of these landslides, but also their spatial propagation. In this research topic, models are developed to estimate the propagation areas and volumes of material mobilized by shallow landslides. Furthermore, models are developed to predict the size of propagation areas at a regional scale based on geological, geomorphological, and hydrological data. This allows us to predict the connectivity of mobilized sediments, which elements in the area may be affected by materials mobilized by shallow landslides, and which natural or anthropogenic parameters may reduce their propagation.
7. Mitigation of shallow landslides using Nature-Based Solutions
Soil treatment methods are tested with various natural additives to improve soil characteristics and reduce susceptibility to landslides. The effects of different types of agricultural management (e.g., grass management with different types of grass cover crops, alternating crops, and tillage in vineyards) on soil properties and hydrogeological instability are studied.
Colorado School of Mines, Chang’An University, Universidad de Granada, Katholische Universität Eichstätt-Ingolstadt, Università di Parma, Università di Bologna, ARPA Piemonte, Università di Padova, Istituto di Ricerca per la Protezione Idrogeologica, Università di Milano, Università di Pisa, Università di Genova, Università di Napoli, Università Cattolica del Sacro Cuore, Università di Catania, Centro di Ricerca per la Protezione e la Certificazione delle piante, Università di Pavia (Dipartimento di Ingegneria Civile e Ambientale), International Consortium on Landslides (ICL), International EcorisQ Association (ecorisQ), Associazione Italiana di Geologia Applicata e Ambientale (AIGAA)
Giarola, A., Meisina, C., Tarolli, P., Zucca, F., Galve, J.P., Bordoni, M. (2024). A data-driven method for the estimation of shallow landslide runout. Catena, 234, 107573.
Bordoni, M., Vivaldi, V., Lucchelli, L., Ciabatta, L., Brocca, L., Galve, J.P. & Meisina, C. (2021). Development of a data-driven model for spatial and temporal shallow landslide probability of occurrence at catchment scale. Landslides, 18, 1209-1229.
Bordoni, M., Vercesi, A., Maerker, M., Ganimede, C., Reguzzi, M.C., Capelli, E., Wei, X., Mazzoni, E., Simoni, S., Gagnarli, E. & Meisina C. (2019). Effects of vineyard soil management on the characteristics of soils and roots in the lower Oltrepò Apennines (Lombardy, Italy). Science of the Total Environment, 693, 133390.
Bordoni, M., Bonì, R., Colombo, A., Lanteri, L. & Meisina, C. (2018). A methodology for ground motion area detection (GMA-D) using A-DInSAR time series in landslide investigations. Catena, 163, 89-110.
Persichillo, M.G., Bordoni, M., Cavalli, M., Crema, S. & Meisina, C. (2018). The role of human activities on sediment connectivity of shallow landslides. Catena, 160, 261-274.
Bordoni, M., Meisina, C., Valentino, R., Lu, N., Bittelli, M. & Chersich S. (2015). Hydrological factors affecting rainfall-induced shallow landslides: from the field monitoring to a simplified slope stability analysis. Engineering Geology, 193, 19–37.