Giovanna Capparelli

Low-Cost Radars Integrated into a Landslide Early Warning System

Radar activities performed at University of Calabria in the framework of a national project on “Landslides Early Warning” are described in this contribution. After a brief outline of the whole Landslides Early Warning Integrated System, two compact and low-cost radar configurations, the first one based on the adoption of a software radio platform, the second one using a compact Vector Network Analyzer as SFCW scatterometer module, are deeply described. Experimental results are discussed as validation tests to demonstrate the radars range detection capabilities.

On Verification of Forecasting Capability of the FlaIR Regional Model in Landslide Early Warning

Over recent years, the link which exists between meteoric precipitation and terrain mobility has been the focus of many studies, even in the hydrologic and hydraulic sectors. These studies are the logical consequence of the close connection between the occurrence of each type of terrain instability and rains which, directly or indirectly, influence a slope. The analytical approaches which can be found in the specific technical literature differ greatly in terms of methodology and formulation.

TXT-tool 4.039-4.1: Landslide Investigations and Risk Mitigation: The Sarno, Italy, Case

Recently, a number of catastrophic debris flows revealed the high risk in an extensive area of the Campania Region, Southern Italy. Following intense rainfall, on May 5th 1998, over 100 flow slides occurred on Pizzo d’Alvano mountain and hit the urban areas of Sarno and neighboring. The hills and mountains of this area are covered by air-fall pyroclastic soils deposited during volcanic eruptions occurred in the last tens of thousands years. In order to reduce the risk a lot of studies and investigations have been carried out and big and meaningful structural measures have been achieved, described in this paper.

TXT-tool 2.039-4.1: FLaIR Model (Forecasting of Landslides Induced by Rainfalls)

Mathematical models for landslide forecasting constitute an important component for Early Warning Systems. This teaching tool focuses on the empirical model named FLaIR (Forecasting of Landslides Induced by Rainfalls), developed at Laboratory of Environmental Carthography and Hydraulic and Geological Modelling (CAMILab) of University of Calabria (Italy). FLaIR is a general framework for many empirical models proposed in technical literature: in particular, it reproduces as particular cases all the ID (Intensity-Duration) schemes (Capparelli and Versace 2011). From the website www.camilab.unical.it it is possible to download the software FLaIR.exe, together with a user guide.

TXT-tool 2.039-4.2 LEWIS Project: An Integrated System for Landslides Early Warning

In the framework of the National Operational Programme 2007-13 “Research and Competitiveness”, co-funded by the European Regional Development Fund, the Ministry of Research (MIUR) financed the project “AN INTEGRATED SYSTEMS FOR HYDROGEOLOGICAL RISK MONITORING, EARLY WARNING AND MITIGATION ALONG THE MAIN LIFELINES” with the acronym LEWIS (Landslides Early Warning Integrated System). The project aims to develop an integrated, innovative and efficient solution to manage risk issues associated with infrastructure, on landslide-prone slopes by developing and testing a system able to identify potentially dangerous landslides in a timely manner, and to activate all needed measures for impact mitigation, including information delivery. The system includes many components: standard criteria for evaluation and mapping landslides susceptibility: monitoring equipment for measuring the onset of landslide movement; telecommunication networks; mathematical models for both triggering and propagation of landslides induced by rainfall; models for risk scenario forecasting; a centre for data acquisition and processing; and a traffic control centre.

Study of an Active Landslide on A16 Highway (Italy): Modeling, Monitoring and Triggering Alarm

This paper presents the preliminary results of a study carried out on an active landslide, which insists on the A16 (E842) Highway, between Campania and Puglia region (South of Italy). The area lies at the foot of a large gravitational mass, classified as “ancient landslide deposit” where a system of landslides, with different types and activity states, are present. It is characterized by the widespread presence of clayey sequences that affect the stability of the slopes looming over the highway. The site has been instrumented with a series of automated sensors, both innovative and traditional, which monitor different physical entities. Furthermore, a photogrammetry survey was carried out with a drone in order to know precisely the geometry of the slope. Once the geotechnical and hydraulic parameters were collected, a 2D finite difference numerical model (FLAC® software) of the slope was set up and a series of back analysis were carried out comparing the model results with those obtained from the monitoring database. Through these back analyses, the choice of the geotechnical parameter was refined and validated. Different physical variables and results are shown into a unique representation, in comparison with the developed model and the geological and geotechnical information. Following the trends of data, the weekly/monthly average displacements and the possible causes (heavy rainfall, raising of the water table), it is possible to study the mechanical behavior of the landslide and establish preliminary warning thresholds, which have to be verified in future. The large number of acquisitions, provided by the automated monitoring system, permits to use a statistical approach in order to identify a good reliability and increase the confidence on the results. The obtained knowledge allows for the automation of the data processing procedure and for the control of the highway stability in near real time.

Physical Modelling of the Rainfall Infiltration Processes in Pyroclastic Soil Responsible of Landslide Trigger

Landslides cause many damages to people, structures and infrastructure. The prediction of these natural processes is important. A good predictive model can allow the implementation of an equally good warning system, reducing the risk caused by such phenomenons (Capparelli et al. in “Ingredienti essenziali” di un sistema Early Warning per l’innesco di colate di fango in coltri di natura pirocalstica: resistenza a taglio in condizioni di parziale saturazione e curve di ritenzione idrica, 2014). There are many researches to understand the underlying processes trigger a landslide. Rainfall is the most common cause of landslides, so it is important to know the infiltration processes responsible for a failure. In our research, we study the infiltration processes, using an integrated approach, comparing data station in situ with the results and interpretations of physical models, trying to simulate with mathematical models. The aim is to observe and interpret laboratory tests to reproduce and simulate the phenomenon with mathematical models. The following we propose two tests carried out in laboratory scale using a physical model for the simulation of landslides induced by rainfall. The soil used for the tests was taken from the site Sarno (Southern Italy), near the volcano Vesuvius. This area had a mudflow in May 1998.

Quantifying the Performances of Simplified Physically Based Landslide Susceptibility Models: An Application Along the Salerno-Reggio Calabria Highway

Landslides are one of the most dangerous natural hazards in the world causing fatalities, destructive effects on properties, infrastructures, and environment. A correct evaluation of landslide risk is based on an accurate landslide susceptibility mapping that will affect urban planning, landuse planning, and infrastructure designs. Great effort has been devoted by the scientific community to develop landslide susceptibility models. Only few studies have been focused on defining accurate procedures for model selection, assessment, and inter-comparison. In this study we applied a methodology for objectively calibrate and compare different landslide susceptibility models in a framework based on three steps. The first step involves the automatic model parameter calibration based on different objective functions and the comparison of the models results in the ROC plane. The second step involves the intercomparison of a set of model performance indicators in order to exclude objective functions that provide the same information. Finally the third step involves a model parameter sensitivity analysis to understand how model parameter variations affect the model performances. In this study the three-step procedure was applied to compare two different simplified physically based landslide susceptibility models along the highway Salerno-Reggio Calabria in Italy. The model M2, able to consider the spatial variability of the soil depth respect to the model M1, coupled the distance to perfect classification index provided the most accurate result for the study area.

Performance of I-D Thresholds and FLaIR Model for Recent Landslide Events in Calabria Region (Southern Italy)

During the period 2008–2010 heavy and persistent rainfall events induced thousands of shallow landslides and hundreds of deep-seated landslides in Calabria Region (Southern Italy), with more than 2,000 crisis points and damages related to about 94 % of the municipalities. These events are comparable, or even worse, with those occurred in the 50’s and in the early 70’s. In this context, the performance of mathematical models, which are used for the Early Warning System of Calabria Region, is evaluated. In details, Intensity–Duration (I–D) thresholds for several temporal aggregations (hourly and multi daily) of rainfall heights and the hydrological model named FLaIR (Forecasting of Landslides Induced by Rainfall, Sirangelo and Versace 1996) are considered. Moreover, the use of a regional approach for these models was also tested, which is particularly useful when it is necessary to predict the triggering of landslide movements in vast areas where there are concerns not only about the reactivation of pre-existing movements, but also activation of new movements whose exact location is unforeseeable and for which there is no available past information. The obtained results highlight a good model performance, in particular for FLaIR, which can be considered as a general case of I–D rainfall thresholds (Capparelli et al. 2009) and it is characterized by a more flexibility, as it takes into account the real pattern of rainfall heights along the time, and not average values of temporal intensity.