Gianluca Martelloni

Rainfall thresholds for the forecasting of landslide occurrence at regional scale

This paper concerns a regional scale warning system for landslides that relies on a decisional algorithm based on the comparison between rainfall recordings and statistically defined thresholds. The latter were based on the total amount of rainfall, which was cumulated considering different time intervals: 1-, 2- and 3-day cumulates took into account the critical rainfall influencing shallow movements, whilst a variable time interval cumulate (up to 240 days) was used to consider the triggering of deep-seated landslides in low permeability terrains. A prototypal version of the model was initially set up to define statistical thresholds. Then, thresholds were calibrated using a database of past georegistered and dated landslides. A validation procedure showed that the calibration highly improves the results and therefore the model was integrated in the regional warning system of Emilia Romagna (Italy) for civil protection purposes. The proposed methodology could be easily implemented in other similar regions and countries where a sufficiently organised meteorological network is present.

Two GUIs-based analysis tool for spectroradiometer data pre-processing

A new graphical user interface (GUI) for pre-processing reflectance spectra, built using MATLAB and expressly designed for the ASD FieldSpec® spectroradiometer, was developed to solve problems that generally affect experimental ASD data. The GUI is characterised by an easily readable, graphic visualisation of spectra, from which the absorption band depth (ABD) can be obtained for a selected wavelength. The output format of the ASD data is a binary file with an .asd extension. The binary file, that provides a single spectrum, can be processed using a software functionality, by means of a GUI, that allows to select one or more binary files to produce a spectral library in a unique .txt file. The spectral reflectance is re-calibrated with the “convex-hull” methodology to eliminate the convex shape, which is typical of reflectance spectra. Different examples of the use of the new GUI are provided.

A computational toy model for shallow landslides: Molecular dynamics approach

Abstract The aim of this paper is to propose a 2D computational algorithm for modeling the triggering and propagation of shallow landslides caused by rainfall. We used a molecular dynamics (MD) approach, similar to the discrete element method (DEM), that is suitable to model granular material and to observe the trajectory of a single particle, so to possibly identify its dynamical properties. We consider that the triggering of shallow landslides is caused by the decrease of the static friction along the sliding surface due to water infiltration by rainfall. Thence the triggering is caused by the two following conditions: (a) a threshold speed of the particles and (b) a condition on the static friction, between the particles and the slope surface, based on the Mohr–Coulomb failure criterion. The latter static condition is used in the geotechnical model to estimate the possibility of landslide triggering. The interaction force between particles is modeled, in the absence of experimental data, by means of a potential similar to the Lennard-Jones one. The viscosity is also introduced in the model and for a large range of values of the model’s parameters, we observe a characteristic velocity pattern, with acceleration increments, typical of real landslides. The results of simulations are quite promising: the energy and time triggering distribution of local avalanches show a power law distribution, analogous to the observed Gutenberg–Richter and Omori power law distributions for earthquakes. Finally, it is possible to apply the method of the inverse surface displacement velocity [4] for predicting the failure time.

An Operational Warning System for the Forecasting of Landslide Occurrence at Regional Scale

In this work we present a regional scale warning system (named SIGMA) for rainfall induced landslides. The system combines rain gauges measurements and rainfall forecasts and compares them with a series of statistical rainfall thresholds based on the total amount of rainfall. The system was specifically built to take into account both shallow and deep seated landslides. A decisional algorithm integrated in the warning system automatically provides a criticality level depending on which thresholds are exceeded. The model was integrated in the regional warning system of the Emilia Romagna region (Italy) for civil protection purposes. This paper accounts also for the main modifications that the model had during its development, passing form a base version relying on thresholds defined by means of a statistical analysis on rainfall data, to an advanced version in which thresholds were calibrated using a landslide database. The passage from a system to another was straightforward and for its flexibility and versatility, the proposed methodology seems particularly appropriate for emerging countries that have not yet gathered extensive and complete information on the location and time of occurrence of landslides.

Modeling warfare in social animals: a "chemical" approach.

We present here a general method for modelling the dynamics of battles among social animals. The proposed method exploits the procedures widely used to model chemical reactions, but still uncommon in behavioural studies. We applied this methodology to the interpretation of experimental observations of battles between two species of ants (Lasius neglectus and Lasius paralienus), but this scheme may have a wider applicability and can be extended to other species as well. We performed two types of experiment labelled as interaction and mortality. The interaction experiments are designed to obtain information on the combat dynamics and lasted one hour. The mortality ones provide information on the casualty rates of the two species and lasted five hours. We modelled the interactions among ants using a chemical model which considers the single ant individuals and fighting groups analogously to atoms and molecules. The mean-field behaviour of the model is described by a set of non-linear differential equations. We also performed stochastic simulations of the corresponding agent-based model by means of the Gillespie event-driven integration scheme. By fitting the stochastic trajectories with the deterministic model, we obtained the probability distribution of the reaction parameters. The main result that we obtained is a dominance phase diagram, that gives the average trajectory of a generic battle, for an arbitrary number of opponents. This phase diagram was validated with some extra experiments. With respect to other war models (e.g., Lanchesters ones), our chemical model considers all phases of the battle and not only casualties. This allows a more detailed description of the battle (with a larger number of parameters), allowing the development of more sophisticated models (e.g., spatial ones), with the goal of distinguishing collective effects from the strategic ones.

Infiltration effects on a two-dimensional molecular dynamics model of landslides

Abstract We propose a two-dimensional computational model for deep landslides triggered by rainfall, based on interacting particles or grains. The model describes a vertical section of a fictitious granular material along a slope, in order to study the behavior of a wide-thickness landslide. The triggering of the landslide is caused by the exceeding of two conditions: a threshold speed and a condition on the static friction of the particles, the latter based on the Mohr–Coulomb failure criterion (Coulomb in Mem Acad R Div Sav 7:343–387, 1776; Mohr in Abhandlungen aus dem Gebiete der Technischen Mechanik. Ernst, Berlin, 1914). The interparticle interactions are represented as a potential that, in the absence of suitable experimental data and due to the arbitrariness of the grain dimension, is modeled similarly to the Lennard-Jones’ one (Lennard-Jones in Proc R Soc Lond A 106(738):463–477, 1924), i.e., with an attractive and a repulsive part. For the updating of the particle positions, we use a molecular dynamics method, which is quite suitable for this type of systems (Herrmann and Luding in Continuum Mech Thermodyn 10:189–231, 1998). An infiltration scheme is introduced for modeling the increasing pore pressure due to the rainfall. Finally, we also introduce the viscosity in the dynamical equations of motion. The statistical characterization and dynamical behavior of the results of simulations are quite satisfactory relative to real landslides: We obtain a power law distribution of landslide triggering times, and the velocity patterns are typical of real cases, including the acceleration progression. Therefore, we can claim that this type of modeling can represent a new method to simulate landslides triggered by rainfall.

Different Methods to Produce Distributed Soil Thickness Maps and Their Impact on the Reliability of Shallow Landslide Modeling at Catchment Scale

In this paper we made a comparison between various methods to enter soil thickness as a spatial variable in a deterministic basin scale slope stability simulator. We used a slope stability model that couples a simplified solution of Richards infiltration equation and an infinite slope model with soil suction effect. Soil thickness was entered in the stability modelling using spatially variable maps obtained with four state-of-art methods: linear correlation with elevation; linear correlation with slope gradient; exponential correlation with slope gradient; a more complex geomorphologically indexed model (GIST model). Soil thickness maps and the derivate Factor of Safety (FS) maps were validated. Results confirmed that FS is very sensitive to soil thickness and showed that the same slope stability model can be highly sensitive or highly specific depending on the input soil thickness data. The uncertainty in the FS calculation can be reduced by applying more precise soil thickness input data: mean error of soil thickness maps is closely related to the sensitivity or specificity of the FS computation, while the overall performance of the stability simulation depends on mean absolute error and skewness of the frequency distribution of the errors of soil thickness maps. Despite the fact that slope-based methods are the most used in literature to derive soil thickness, in our application they returned poor results. Conversely, the use of the GIST model improved the performance of the stability model.

A 3D model for rain-induced landslides based on molecular dynamics with fractal and fractional water diffusion

Abstract We present a three-dimensional model of rain-induced landslides, based on cohesive spherical particles. The rainwater infiltration into the soil follows either the fractional or the fractal diffusion equations. We analytically solve the fractal partial differential equation (PDE) for diffusion with particular boundary conditions to simulate a rainfall event. We developed a numerical integration scheme for the PDE, compared with the analytical solution. We adapt the fractal diffusion equation obtaining the gravimetric water content that we use as input of a triggering scheme based on Mohr-Coulomb limit-equilibrium criterion. This triggering is then complemented by a standard molecular dynamics algorithm, with an interaction force inspired by the Lennard–Jones potential, to update the positions and velocities of particles. We present our results for homogeneous and heterogeneous systems, i.e., systems composed by particles with same or different radius, respectively. Interestingly, in the heterogeneous case, we observe segregation effects due to the different volume of the particles. Finally, we analyze the parameter sensibility both for the triggering and the propagation phases. Our simulations confirm the results of a previous two-dimensional model and therefore the feasible applicability to real cases.

Snowmelt Modelling for Improving the Forecasts of Rainfall Threshold-Based Landslide Triggering

In Central Italy a significant number of landslides occurrence have been triggered by rapid snow melt: recent seasonal events in the Northern Apennines, the study area, demonstrate that it is necessary to consider this phenomenon and to integrate snow precipitation within existing statistical models for landslide prediction. The proposed snow melt modeling (SMM) is divided in two modules depending on whether or not a threshold temperature is exceeded: the first one for the accumulation of solid rainfall in the snowpack and the latter for the snow melting. For the modeling identification we employ empirical data of depth of snow cover using an optimization algorithm to deduce the optimal values of the model parameters. This work is developed to increase the predictive capacity of the statistical models for landslide prediction based on rainfall thresholds. In the study area an improvement was achieved: several landslides, caused by snow melting, were correctly detected.