Pasquale Versace

DISTRIBUTED ESTIMATION OF ACTUAL EVAPOTRANSPIRATION THROUGH REMOTE SENSING TECHNIQUES

Evapotranspiration (ET) is one of the main water balance components, and its actual value appears to be the most difficult to measure directly. Therefore, the choice of reliable models capable of predicting spatially distributed actual ET represents a drought monitoring fundamental aspect. This chapter presents a brief introduction to the main remote sensing methods for ET estimate and, by means of ground ET measurements carried out through eddy covariance systems at three different sites in southern Italy, analyzes the performance given by the Surface Energy Balance Algorithm for Land (SEBAL) model using images of the Moderate Resolution Imaging Spectroradiometer (MODIS) on areas characterized by different physiographic and vegetative conditions (sparse vegetation, crop canopy and high mountain vegetation). The distributed results obtained for different days from summer 2004 to summer 2006 on a wide southern Italian area pointed out generally good ET predictions in the eddy covariance sites, also if some differences arose depending on the type and density of vegetation

A comprehensive framework for empirical modeling of landslides induced by rainfall: the Generalized FLaIR Model (GFM)

In this paper, a new version of the hydrological model named FLaIR (Forecasting of Landslides Induced by Rainfall) is described, and it is indicated as GFM (Generalized FLaIR Model). Nonstationary rainfall thresholds, depending on antecedent precipitation, are introduced in this new release, which allows for a better prediction of landslide occurrences. Authors demonstrate that GFM is able to reproduce all the antecedent precipitation models (AP) proposed in technical literature as particular cases, besides intensity-duration schemes (ID) and more conceptual approaches, like Leaky Barrel, whose reconstruction with the first release of FlaIR model, which adopts only stationary thresholds, was already discussed in technical literature. Authors applied GFM for two case studies: 1) Gimigliano municipality, which is located in Calabria region (southern Italy) and where a consistent number of landslides occurred in the past years; in particular, during the period 2008–2010, this area (like the whole Calabria region) was affected by persistent rainfall events, which severely damaged infrastructures and buildings; 2) Barcelonnette Basin, which is located in the dry intra-Alpine zone (South French Alps). The high flexibility of GFM allows to obtain significant improvements in landslide prediction; in details, a substantial reduction of false alarms is obtained with respect to application of classical ID and AP schemes.

Software-Defined Radar System for Landslides Monitoring

An integrated system for landslides early warning, based on a flexible network architecture and including different sensors, is described to monitoring landslides evolution in critical scenarios. Particular focus is devoted on the experimental assessment of an L-band Software Defined Radar sensor, specifically designed for the application, by discussing the measurement results obtained on a real landslide scenario located on the A3 highway in Calabria (Italy). In particular, a mathematical estimator useful for the proper detection of landslide movements is defined and applied to the measured range profiles, thus demonstrating the usefulness of the proposed radar monitoring approach.

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.

Deterministic and Probabilistic Rainfall Thresholds for Landslide Forecasting

Open image in new window In this paper, authors focus attention on different threshold schemes, which can be adopted when a model is used for landslide forecasting. In some cases they represent the occurrence probability of a landslide, in other cases the exceedance probability of a critical value for an assigned mobility function Y (a function of rainfall heights), indicated as Y cr , and in further cases they only indicate the exceeding of Y cr or its prefixed percentages. Clearly, the discussion here reported can be easily extended to the case of flood forecasting models. The empirical model named FLaIR (Forecasting of Landslides Induced by Rainfall, Capparelli and Versace 2011) is used for the study area of Gimigliano municipality (located in Calabria region, southern Italy), characterized by a database with 27 historical landslide events in the period 1940–2011.

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.

A contribution for the assessment of sliding susceptibility in Sarno area, Southern Italy

Rainfall is accepted as a major factor in many types of slope movement, including rapid, shallow soil slips and deeper landslides. Actually, rainfall-triggered landslides constitute a serious hazard in many part of the world. More efforts are needed to improve knowledge and understanding of the mechanisms that control the triggering landslides. The technical literature is rich in examples of study cases and analysis models. In general, the models can be traced to two categories: hydrological and complete models. Although with very different procedures, both models attempt to describe the relationships rainfall-landslides for defining conditions of triggering phases. The first ones involve simple empirical relationships linking antecedent precipitation to the time that the landslide occurs; the latter consist of more complex expressions that take several components into account, including specific site conditions, mechanical, hydraulic and physical soil properties, local seepage conditions, and the contribution of these to soil strength. This study shows the results obtained by using a model belonging to the second category. The analysis was carried out in a landslide-prone area in Campania region (South Italy), were disastrous mud-flows occurred on May 5 th ,1998. After the events, an analysis of the triggering conditions has been developed working with the complete model SUSHI (Saturated Unsaturated Simulation for Hillslope Instability). The obtained results made possible to better define the triggering conditions and differentiate the scenarios leading to instability of those slopes.

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.