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Model calibration is usually based on trial-and-error procedures that, in turn, rely on expert judgment or previously acquired experiences for similar phenomena. Efficient and reliable procedures for model calibration of the propagation stage of landslides are still needed. This paper addresses this issue by proposing an inverse analysis procedure and applying it to the case history of a short run-out landslide triggered by a rising perched water table after a heavy rainfall. It focuses on the key role played by the field observations used to set up the inverse analysis, and evaluating the reliability of the numerical simulations. It also investigates the effect of different types of optimization parameters on the inverse analysis results, referring to a mixed-phase model or to a two-phase model for the propagating soil. Several sets of observations are used; all of them refer to the soil deposit thickness at the end of propagation, but differ in both location and number of the adopted values. The numerical analysis of the case history is performed through the academic “GeoFlow_SPH” model, and model calibration by inverse analysis is conducted using the “UCODE” software. The results obtained are discussed with the aim to provide practical criteria to identify the minimum amount of information required for a satisfactory model calibration. [ABSTRACT FROM AUTHOR]

The paper proposes a methodology, in two successive steps, to zone the susceptibility to shallow landslides in fine grained soils by means of statistical methods. The first step of the methodology, aiming at defining, calibrating and validating the statistical analysis, ends with a landslide susceptibility computational map; the second step of the methodology is employed to produce a susceptibility map for zoning purposes. This structured methodology arises from the need to distinguish, at any given scale of analysis, between the spatial discretization needed to perform the statistical computations (terrain computational units) and terrain units useful for zoning purposes (terrain zoning units). The applicability of the proposed methodology is tested, at two different scales (1:25,000 and 1:5000), in two areas of southern Italy, the test area for the larger scale being a portion of the test area used for the analysis at the smaller scale. This allows for the generalization of the obtained results through the comparison, for the same phenomena in the same geo-environmental context, of the predisposing factors at two scales of analysis. In both analyses, the relevant variables for the susceptibility assessment are: elevation zone, slope gradient, slope curvature and geology; in the analysis at large scale also the weathered rock thickness, available only at this scale, assumes a relevant role. In both cases, the aggregation of multiple terrain computational units (TCU) into a larger terrain zoning unit (TZU) works best when focal statistic techniques are used with a characteristic dimension of the area of influence equal to 16 TCUs. [ABSTRACT FROM AUTHOR]

The paper deals with the citywide landslide early warning system “Alerta-Rio” operated by the municipality of Rio de Janeiro (Brasil). The city is divided, for warning purposes, into four alert zones. Two different alert sets co-exist within Alerta-Rio: rainfall warnings and landslide warnings. The landslide warning levels are four and they are related to an expected spatial density of landslides. The presented study focuses on the evaluation of the efficiency of the correlation models and rainfall thresholds employed by Alerta-Rio to issue the landslide warnings. The analyses refer to the four-year time frame 2010–2013; they are conducted considering the spatial and temporal distribution of rainfall, landslides and alert phases. An alert phase is herein defined as the time when the landslide warning level is associated to the possibility of diffuse or widespread landsliding within the alert zone. The performance of the system is evaluated by looking at the errors generated by the landslide alerts, computed as a function of the temporal overlap between alert phases and landslide events. Landslides are grouped in events so as to explicitly consider the extent of the landslide disasters in relation to the alerts issued. The discussion on the results of the performed analyses mainly focuses on the following issues: false and missed alerts; duration of alerts; zoning for early-warning purposes. [ABSTRACT FROM AUTHOR]