1 GASAKe : forecasting landslide activations by a Genetic-Algorithms based hydrological model 2 3 Oreste G. Terranova1, Stefano Luigi Gariano2,3*, Pasquale Iaquinta1 & Giulio G.R. Iovine1 4 5 1) CNR-IRPI (National Research Council – Research Institute for Geo-Hydrological Protection), 6 via Cavour 6, 87036, Rende, Cosenza, Italia. 7 2) CNR-IRPI (National Research Council – Research Institute for Geo-Hydrological Protection), 8 via Madonna Alta 126, 06128, Perugia, Italia. 9 3) University of Perugia, Department of Physics and Geology, via A. Pascoli, 06123, Perugia, 10 Italia. 11 *Corresponding Author:
[email protected], Phone: +39 075 5014424. 12 13 ABSTRACT 14 GASAKe is a new hydrological model aimed at forecasting the triggering of landslides. The model is 15 based on Genetic-Algorithms and allows to obtaining thresholds of landslide activation from the set 16 of historical occurrences and from the rainfall series. 17 GASAKe can be applied to either single landslides or set of similar slope movements in a 18 homogeneous environment. Calibration of the model is based on Genetic Algorithms, and provides 19 for families of optimal, discretized solutions (kernels) that maximize the fitness function. Starting 20 from these latter, the corresponding mobility functions (i.e. the predictive tools) can be obtained 21 through convolution with the rain series. The base time of the kernel is related to the magnitude of 22 the considered slope movement, as well as to hydro-geological complexity of the site. Generally, 23 smaller values are expected for shallow slope instabilities with respect to large-scale phenomena. 24 Once validated, the model can be applied to estimate the timing of future landslide activations in the 25 same study area, by employing recorded or forecasted rainfall series.