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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. [ABSTRACT FROM AUTHOR]

Temporal properties of 152 575 rainfall events, recorded at time steps of 5 min, having different durations and occurring between 1989 and 2008 at 155 localities of Calabria (Italy), have been analysed in this paper. Samples from 45 533 storms have been selected to classify rainfall events as "significant" with regard to their contribution to soil erosion, flooding and/or other geo-hydrological processes. The samples are representative of a wide variety of situations in terms of duration, total rainfall, intensity, etc. The use of standardized rainfall profiles (SRP) is proposed to describe the within-storm temporal pattern. The main attraction of this method lies in the fact that it is based on actual data of regional precipitation. Its weak point is that large samples of data are required to obtain regional profiles. The research necessities for improving the use of Huff curves for storm disaggregation and its the potential use are summarized in this paper on the basis of the specific literature. A new criterion -- based on the comparison of the areas A1, A2, A3 and A4 that underlie the four 25% of durations of a given SRP, and the corresponding four values of the "uniform" SRP (USRP), is suggested here with the aim of improving the use of the information content of SRP. Some interesting results concerning the sample frequency and the characterization of parameters for hydrological applications are commented on. The study conducted so far has produced important, albeit preliminary, results for different contexts of Calabria concerning the use of SRP among the methods for constructing design storm hyetographs. [ABSTRACT FROM AUTHOR]