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ROCKFALL MODELLING AND RISK ZONING A CASE STUDY IN THE FRENCH ALPS USING GEOMATICS, AIRBORNE LASER SCANNING, 2D & 3D RUNOUT MODELS

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12th Congress INTERPRAEVENT 2012 Grenoble / France – Extended Abstracts www.interpraevent.at

ROCKFALL MODELLING AND RISK ZONING

A CASE STUDY IN THE FRENCH ALPS USING GEOMATICS, AIRBORNE LASER SCANNING, 2D & 3D RUNOUT MODELS

Nicolas Clouet1, Fréderic Berger2 and Jérôme Liévois3

INTRODUCTION

In alpine environments, natural hazards such as rock falls are common but their occurrences are difficult to predict. To protect human lives and infrastructures without hampering town development and economic activities, public authorities must adequately map risk zones and take them into account in town development schemes. Nowadays, trajectory simulation models are increasingly used with the aim of making rock fall hazard maps. Regarding rock fall risk zoning, common practices rely on a limited number of 2D numerical simulation results manually extrapolated to whole hillsides. In areas such as the French Alps, with highly variable topographic and soil conditions, such approaches may overlook local effects which have decisive consequences on rock propagation. Moreover the protective function of forests and vegetation is frequently underestimated or even ignored.

The town of Veyrier du Lac (45° 52’ 59” N, 06° 10’ 41” E) is highly concerned by rock falls: its 8km² are situated downslope of 150 to 200 m high limestone cliffs. We implemented a new methodology based on geomatics for rock fall risk assessment and risk zoning for the Risk Prevention Plan (PPR).

Analysis of airborne laser scanning data, field data, 2D and 3D rock fall simulations were performed with geographic information system (GIS) to accurately map hazard areas.

AIRBORNE LASER SCANNING DATA

The quality of the results of the 2D and 3D run-out simulation models is strongly linked with the quality of the input data. For several years, high precision digital terrain models (DTM) based on remote sensing technologies such as airborne laser scanning (ALS or LiDAR) are available. For the study, the laser data were acquired during late summer 2008. The point density of the final echo was 10m-2. The point cloud was classified into ground and non-ground echoes using the TerraScan software to compute by linear interpolation a DTM and a Digital Surface Model (DSM) of metric resolution.

PRELIMINARY WORK

A PPR refers to a reference hazard, defined by the occurrence probability of 1% per year for a rock fall. This centennial event is needed to choose the rock volume for numerical simulations. An analysis of the past events and Dendrochronological data allows us to determine reference volumes. The study area was finally divided into 9 sectors, depending on the topography (watersheds) and the geology: 7 with a reference volume of 1m3, 1 sector with a volume of 2m3 and one with a volume of 5m3.

A field survey has been undertaken to measure local soil characteristics and get additional informations about the size and frequency of rock falls. The following features, on 104 circular plots of 10 m diameter, distributed on the whole hillside, were inventoried and used to calibrate the models:

- forest: species, stand density and diameter at breast height (DBH) of trees with a DBH larger than 7.5 cm;

- landform: macro topography type, micro topography roughness, mean obstacle height, soil stiffness;

1 Nicolas Clouet. Cemagref, UR EMGR, 2 rue de la papeterie, BP76, F-38402 Saint martin d’Hères, France (e-mail : nicolas.clouet@cemagref.fr)

2 Fréderic Berger, Cemagref, UR MEGR, France

3 Jérôme Liévois, ONF, service RTM, France

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- rock fall activity: number, shape and size of recently deposited rocks, and number and height of rock impacts on trees.

From the irregularly localized sample points of the field survey, estimated values of landform and soil characteristics were computed with GIS on a regular grid using nearest neighbor interpolation. Forest parameters were extrapolated using photointerpretation with LiDAR data and orthophotos. Due to the high number of cliffs, the localization of potential release zones was determined by DTM modelling.

According to the equation: α = 55 x RES-0.075, where RES is the DTM resolution, all cells from the slope surface raster with values higher than α were qualified as potential release zones for rock falls.

2D & 3D MODELLING

RockForLINE is a 2D numerical simulation model based on the Energy Line model, which allows relating rock fall run out envelops to slope angles. The maximal spread of a block is determined by intersecting the ground and an imaginary line drawn from its release point with an angle β. Areas with a β between 32 and 35° have a low but not null probability to be reached by rock falls ; between 35 and 38°, a intermediate probability ; and higher than 38°, a high probability.

Rockyfor3D is a 3D simulation model that calculates trajectories of single falling rocks, taking into account or not the forest effect. All input rasters and DTM were resampled to 5m resolution before they were supplied to Rockyfor3D. From each of the 51552 potential release points, 500 rock fall trajectories were simulated on bare soil, and 500 more with integration of forest effect. All the results have been compared with the 2D simulations and the historical data to ensure that simulation results were consistent with field observations.

PROPOSITION OF A NEW “HAZARD MATRIX” FOR RISK ZONING

Most of the PPR uses a risk zoning based on the frequency or on the reach probability. But it's also fundamental to study the kinetic energy developed by the projectile. We defined 3 hazard levels by cross analysis of 3 mean kinetic energy classes and 4 frequency classes (see Fig.1).

Fig. 1 Hazard maps without (left) and with (right) the forest effect

Hazard maps, with and without forest integration, have been drawn thanks to the hazard matrix. A new rock fall event, occurred in January 2009, allows us to validate rock fall simulations and hazard maps:

the 6.25m3 block path has been correctly modelled and its stopping point was in the high hazard level envelop.

Then, according to these hazard maps and human stakes, a risk map has been proposed. Three levels of risk were mapped: high level of risk, in red, where new buildings are forbidden, medium level in blue, where new buildings are allowed under architectural conditions, and low level, in white, where all new buildings are allowed. Finally, after a public inquiry, the PPR has been validated by the public authorities.

Keywords: rock falls, risk zoning, GIS, 2D & 3D simulations, protection forest

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