Castaldo, R.; Tizzani, P.; Lollino, P.; Calò, F.; Ardizzone, F.; Manunta, M.; Guzzetti, F.; Lanari, R., 2015, The Ivancich active landslide process (Assisi, central Italy) analysed via numerical modeling jointly optimized by Dinsar and Inclinometric data, IAEG Congress, pp. 1513–1517, 2014, IAEG Congress,
URL: http://www.cnr.it/prodotto/i/338379

The analysis of the displacement field due to a landslide process can be performed by means of either forward or inverse numerical models. Concerning the evolution of slow landslides, the Finite Element Method (FEM) represents a powerful tool to assess the relationships existing between the causative factors and the related effects, being the latter generally detected by field monitoring data. In this context, inverse models are useful to deduce the values of physical or mechanical parameters that control the landslide behavior over time. In this paper, we combined the potentiality of the FEM with Monte Carlo optimization procedures, based on a Genetic Algorithm (GA) technique, to back-analyze and interpret the kinematical evolution of very slow active landslides. In particular, we performed a two-dimensional time-dependent FE analysis by using a deviatoric creep model to simulate the evolution of the displacement field of the very slow Ivancich landslide (Assisi, Central Italy); an optimization procedure was performed by considering the Differential SAR Interferometry (DInSAR) data to derive the soil creep rate distribution, according to an inverse analysis approach. In particular the longterm Small BAseline Subset (SBAS) DInSAR analysis covering about 20 years was compared with the slope velocities calculated by the numerical model and the best-fit creep model was identified by considering the minimum Root Mean Square Error between field data and model results. Finally the model results in terms of slope displacements over time have been also compared with the available inclinometric measurements. .

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