GASAKe is a new hydrological model aimed at forecasting the triggering of landslides. The model is based on genetic algorithms and allows one to obtain thresholds for the prediction of slope failures using dates of landslide activations and rainfall series. It can be applied to either single landslides or a set of similar slope movements in a homogeneous environment. Calibration of the model provides families of optimal, discretized solutions (kernels) that maximize the fitness function. Starting from the kernels, the corresponding mobility functions (i.e., the predictive tools) can be obtained through convolution with the rain series. The base time of the kernel is related to the magnitude of the considered slope movement, as well as to the hydro-geological complexity of the site. Generally, shorter base times are expected for shallow slope instabilities compared to larger-scale phenomena. Once validated, the model can be applied to estimate the timing of future landslide activations in the same study area, by employing measured or forecasted rainfall series. Examples of application of GASAKe to a medium-size slope movement (the Uncino landslide at San Fili, in Calabria, southern Italy) and to a set of shallow landslides (in the Sorrento Peninsula, Campania, southern Italy) are discussed. In both cases, a successful calibration of the model has been achieved, despite unavoidable uncertainties concerning the dates of occurrence of the slope movements. In particular, for the Sorrento Peninsula case, a fitness of 0.81 has been obtained by calibrating the model against 10 dates of landslide activation; in the Uncino case, a fitness of 1 (i.e., neither missing nor false alarms) has been achieved using five activations. As for temporal validation, the experiments performed by considering further dates of activation have also proved satisfactory. In view of early-warning applications for civil protection, the capability of the model to simulate the occurrences of the Uncino landslide has been tested by means of a progressive, self-adaptive procedure. Finally, a sensitivity analysis has been performed by taking into account the main parameters of the model. The obtained results are quite promising, given the high performance of the model against different types of slope instabilities characterized by several historical activations. Nevertheless, further refinements are still needed for application to landslide risk mitigation within early-warning and decision-support systems.

A deficit in precipitation may impact greatly on soil moisture, snowpack, stream flow, groundwater, and reservoir storage. Among the several approaches available to analyze this phenomenon, one of the most applied is the analysis of dry spells. In this paper, an investigation of the spatial and temporal patterns of dry spells, in a region of southern Italy, has been carried out on a daily precipitation dataset. First, the frequency distributions of the sequences of dry days have been analyzed. Then, the regional areas most affected by dry events have been evaluated at annual and seasonal scale. Finally, the long-term trend of the dry spells has been estimated at annual and seasonal scale. Results show that the lower probabilities of long dry spells occur in the main reliefs of the region, while the highest values have been detected in the Ionian side. The spatial distribution of the mean and maximum length values of the dry spells evidenced a west-east gradient. The trend analysis mainly revealed a negative behavior in the duration of the dry spells at annual scale and a positive trend in the winter period.

A deficit in precipitation has different impacts on soil moisture, snowpack, streamflow, groundwater and reservoir storage. In this study, drought, expressed using the SPI, has been analysed in a region of southern Italy (Calabria) using a homogenised and gap-filled database for 129 monthly rainfall series in the 1916-2006 period. Both the short-term (3 and 6 months) and the long-term (12 and 24 months) SPI were estimated and, in order to identify the worst events, the percentages of the regional area falling within severe or extreme dry conditions have been evaluated. With the aim to spatially characterize the most severe drought event, the SPI data were estimated at ungauged locations and mapped using a geostatistical approach. Finally, a time series analysis of long-term SPI was performed to detect possible trends. Results showed that several heavy drought episodes have widely affected the Calabria region and, among these events, the worst one occurred between December 2001 and April 2002. The trend analysis showed a reduction in the SPI values that is a tendency towards drier conditions, although the running trend approach, carried out only for the long-term SPI, revealed that this tendency is not persistent throughout the series length, but it depends on the period examined.

This paper investigates how atmospheric circulation and orography affect the spatial variability of extreme precipitation in terms of depth-duration-frequency (DDF) curve parameters. To this aim, the Italian territory was considered because it is characterized by a complex orography and different precipitation dynamics and regimes. A database of 1494 time series with more than 20 years of maximum annual precipitation data was collected for the durations of 1, 3, 6, 12, and 24 h. For each data series, the parameters of DDF curves were estimated using a statistical simple scale invariance model. Hence, the combined effect of orography and atmospheric fields on parameter variability was investigated considering the spatial distribution of the parameters and their relation with elevation. The vertically integrated atmospheric moisture flux J was used as a measurement of the principal direction of the vapor transport at a given location. The analysis highlights the variability of DDF parameters and quantiles according to orography and precipitation climatology. This is confirmed by the evaluation of J modal direction over the study area. The variability of DDF parameters with mere elevation shows that maxima at high elevations seem to be upper bounded and more variable than those at lower elevations. Moreover, the mean of maximum annual precipitation of unit duration decreases with elevation. This last phenomenon is defined as "reverse orographic effect" on extreme precipitation of short durations.

Heavy rainstorms often induce flash floods, shallow landslides and debris flows, which cause several damage to manmade infrastructures and loss of lives. The analysis of spatial distribution and temporal features of intense rainfall events is a fundamental step for a better understanding of the phenomena and for its possible prediction. The present study is an attempt to improve, from a statistical point of view, the understanding at sub-hourly scale of the temporal and spatial structure of intense rainfall events, by examining those that have hit Calabria (Southern Italy) in the years 1998-2008. More in detail, a considerable amount of series with high temporal detail (5 min) related to 155 sites (one rain gauge per less than 100 sq km), were analysed. First, more than 152 thousands rainfall events, separated by at least 6 hours of dry weather, were recognized. Then, less than a third (45,533) were selected, since denoted as erosive. Finally, several heavy rainstorm events (HREs) were chosen by considering the rainfall events recorded simultaneously at different rain gauges, even non-contiguous, within the region. In particular, this further selection was conducted, based on heuristic threshold values of cumulated rainfall ( 100 mm), maximum intensity ( 50 mm/h), and kinetic energy ( 29 MJ/ha). Therefore, 25 distinct HREs, including all the well-known catastrophic geo-hydrological events, were subjected to thorough investigation. The obtained HREs, automatically classified according to their structure in time, were analysed as regards both spatial and temporal evolution. At this end, the 25 HREs were distinguished as widespread (17) or localized (8), if the affected area is 500 sq km or < 500 sq km, respectively. In particular, the temporal storm structure was described by means of the standardized rainfall profile (rainfall amount vs. duration, in terms on cumulative percentages). Then, a 4-digit binary shape code was adopted to automatically identify the shape of the profile (Terranova and Iaquinta, 2011; Terranova and Gariano, 2014). HREs have different spatial extents and temporal patterns. A wide spatial extent of the events does not imply damage proportionally high. Generally, a peak at the beginning of the event (thunderstorm-type) characterizes localized events. On the contrary, widespread events present mixed temporal structures with peaks localized in the last half of their duration. The proposed method improves the knowledge regarding the input of rainfall-runoff watershed models. These models can benefit from design storms, based on the synthesis of recorded rainstorms, having a time structure integrated with the results of the spatial analysis. The notable size of the employed sample, including data with a very detailed time resolution that relate to several rain gauges well distributed throughout the region, gives robustness to the obtained results. References O.G. Terranova, and P. Iaquinta.: Temporal properties of rainfall events in Calabria (southern Italy). Nat. Hazards Earth Syst. Sci., 11, 751-757, 2011. O.G. Terranova, and S.L. Gariano.: Rainstorms able to induce flash floods in a Mediterranean-climate region (Calabria, southern Italy). Nat. Hazards Earth Syst. Sci., 14, 2423-2434, 2014.

In the last decades, building damage caused by landslides in urban areas has increased due to the rapid growth of urbanization even on landslide-prone slopes. This work presents the analysis results of landslide damage evolution by means of a macrodamage index in relation to the characteristics of landslides. The study area is located in southern Italy, and is affected by slow-moving landslides, which, over time, have caused relevant effects on the buildings. A series of geological and geomorphological studies and field surveys, supported by monitoring via conventional geotechnical techniques, allowed us to classify four categories of landslides based on the following criteria_ landslide movement, type of material and estimated depth. Detailed field surveys aimed at evaluating distribution and evolution of the damage to buildings located within and near the unstable area were carried out in 2005 and 2011. The evaluation of the macrodamage index in two different years enabled us to directly correlate the features of the landslide categories and their effects on the urban fabric. © 2014 Springer-Verlag Berlin Heidelberg.

Prediction of rainfall-induced landslides can rely on empirical rainfall thresholds. These are obtained from the analysis of past rainfall events that have (or have not) resulted in slope failures. Accurate prediction requires reliable thresholds, which need to be validated before their use in operational landslide warning systems. Despite the clear relevance of validation, only a few studies have addressed the problem, and have proposed and tested robust validation procedures. We propose a validation procedure that allows for the definition of optimal thresholds for early warning purposes. The validation is based on contingency table, skill scores, and receiver operating characteristic (ROC) analysis. To establish the optimal threshold, which maximizes the correct landslide predictions and minimizes the incorrect predictions, we propose an index that results from the linear combination of three weighted skill scores. Selection of the optimal threshold depends on the scope and the operational characteristics of the early warning system. The choice is made by selecting appropriately the weights, and by searching for the optimal (maximum) value of the index. We discuss weakness in the validation procedure caused by the inherent lack of information (epistemic uncertainty) on landslide occurrence typical of large study areas. When working at the regional scale, landslides may have occurred and may have not been reported. This results in biases and variations in the contingencies and the skill scores. We introduce two parameters to represent the unknown proportion of rainfall events (above and below the threshold) for which landslides occurred and went unreported. We show that even a very small underestimation in the number of landslides can result in a significant decrease in the performance of a threshold measured by the skill scores. We show that the variations in the skill scores are different for different uncertainty of events above or below the threshold. This has consequences in the ROC analysis. We applied the proposed procedure to a catalogue of rainfall conditions that have resulted in landslides, and to a set of rainfall events that - presumably - have not resulted in landslides, in Sicily, in the period 2002-2012. First, we determined regional event duration-cumulated event (ED) rainfall thresholds for shallow landslide occurrence using 200 rainfall conditions that have resulted in 223 shallow landslides in Sicily in the period 2002-2011. Next, we validated the thresholds using 29 rainfall conditions that have triggered 42 shallow landslides in Sicily in 2012, and 1250 rainfall events that presumably have not resulted in landslides in the same year. We performed a back analysis simulating the use of the thresholds in a hypothetical landslide warning system operating in 2012.

This paper illustrates the methodology and techniques for the compilation of a thematic (engineering) geological map based on detailed mapping of the weathering grade of crystalline rocks occurring in a portion of the Sila Massif close to the San Giovanni in Fiore Village (Calabria, Italy). The map (1:5000 scale), covering an area of about 20 km2, was compiled combining new geological and structural data with the results of a weathering grade field survey. The methodology, used to distinguish and map the weathering grade classes, was performed using qualitative criteria, semi-quantitative tests, and petrographic analysis of weathered rock samples. The Main Map, presented in this paper, aims to provide a useful tool for land-use planning, for geological hazard assessment and engineering perspectives.