CNR ExploRA

Articolo in rivista, 2020, ENG, 10.3390/geosciences10080309

Mapping Landslide Prediction through a GIS-Based Model: A Case Study in a Catchment in Southern Italy

Federico Valerio Moresi, Mauro Maesano, Alessio Collalti, Roy C. Sidle, Giorgio Matteucci, Giuseppe Scarascia Mugnozza

Department of Innovation in Biological, Agro-Food and Forest Systems, University of Tuscia, 01100 Viterbo, Italy; Institute for Agricultural and Forest Systems in the Mediterranean, National Research Council of Italy, 00100 Rome, Italy Mountain Societies Research Institute, University of Central Asia, Khorog 736000, Tajikistan; Institute of Global Innovation Research, Tokyo University of Agriculture and Technology, Tokyo 183-8538, Japan Sustainability Research Centre, University of the Sunshine Coast, Sippy Downs, QLD 4556, Australia Institute of BioEconomy (IBE), 50019 Sesto Fiorentino (FI), Italy;

Shallow landslides are an increasing concern in Italy and worldwide because of the frequent association with vegetation management. As vegetation cover plays a fundamental role in slope stability, we developed a GIS-based model to evaluate the influence of plant roots on slope safety, and also included a landslide susceptibility map. The GIS-based model, 4SLIDE, is a physically based predictor for shallow landslides that combines geological, topographical, and hydrogeological data. The 4SLIDE combines the infinite slope model, TOPMODEL (for the estimation of the saturated water level), and a vegetation root strength model, which facilitates prediction of locations that are more susceptible for shallow landslides as a function of forest cover. The aim is to define the spatial distribution of Factor of Safety (FS) in steep-forested areas. The GIS-based model 4SLIDE was tested in a forest mountain watershed located in the Sila Greca (Cosenza, Calabria, South Italy) where almost 93% of the area is covered by forest. The sensitive ROC analysis (Receiver Operating Characteristic) indicates that the model has good predictive capability in identifying the areas sensitive to shallow landslides. The localization of areas at risk of landslides plays an important role in land management activities because landslides are among the most costly and dangerous hazards.

Geosciences (Basel) 10 (309)