Taylor F. E. (1), Santangelo M. (2,3), Marchesini I. (2), and Malamud B. D. (1), 2013, A GRASS GIS Semi-Stochastic Model for Evaluating the Probability of Landslides Impacting Road Networks in Collazzone, Central Italy, Geophysical research abstracts (Online) 15 (2013).,
URL: http://www.cnr.it/prodotto/i/273180

During a landslide triggering event, the tens to thousands of landslides resulting from the trigger (e.g., earthquake, heavy rainfall) may block a number of sections of the road network, posing a risk to rescue efforts, logistics and accessibility to a region. Here, we present initial results from a semi-stochastic model we are developing to evaluate the probability of landslides intersecting a road network and the network-accessibility implications of this across a region. This was performed in the open source GRASS GIS software, where we took 'model' landslides and dropped them on a 79 km2 test area region in Collazzone, Umbria, Central Italy, with a given road network (major and minor roads, 404 km in length) and already determined landslide susceptibilities. Landslide areas (AL ) were randomly selected from a three-parameter inverse gamma probability density function, consisting of a power-law decay of about -2.4 for medium and large values of AL and an exponential rollover for small values of AL ; the rollover (maximum probability) occurs at about AL = 400 m2 The number of landslide areas selected for each . triggered event iteration was chosen to have an average density of 1 landslide km-2 , i.e. 79 landslide areas chosen randomly for each iteration. Landslides were then 'dropped' over the region semi-stochastically: (i) random points were generated across the study region; (ii) based on the landslide susceptibility map, points were accepted/rejected based on the probability of a landslide occurring at that location. After a point was accepted, it was assigned a landslide area (AL ) and length to width ratio. Landslide intersections with roads were then assessed and indices such as the location, number and size of road blockage recorded. The GRASS-GIS model was performed 1000 times in a Monte-Carlo type simulation. Initial results show that for a landslide triggering event of 1 landslide km-2 over a 79 km2 region with 404 km of road, the number of road blockages ranges from 6 to 17, resulting in one road blockage every 24-67 km of roads. The average length of road blocked was 33 m. As we progress with model development and more sophisticated network analysis, we believe this semi-stochastic modelling approach will aid civil protection agencies to get a rough idea for the probability of road network potential damage (road block number and extent) as the result of different magnitude landslide triggering event scenarios.

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