How can we predict and prevent avalanche
risks? What scientific facts can be taken as the starting point?
Some of the prevention methods used in the past - and still applied
today - have shown their limitations. One example is
nivo-meteorological forecasting, based on data obtained from
nivology (the study of snow) and meteorology; all too often
evacuations planned with this method have gone on to prove
unnecessary. Avalanche maps, which attempt to combine all the
spatial and spatio-?temporal data for a given site, are not much
better and are of little use for forecasting.
Bridging the gaps
The EU's SAME (Snow Avalanche Modelling and Mapping in Europe)
project was set up with the aim of correcting these inadequacies. It
involved close international and interdisciplinary cooperation
between 14 partners over a 30-month period to explore three main
lines of inquiry: avalanche information systems, warning systems and
modelling, and sensor testing
'These lines of inquiry reflect the areas of expertise in the
research teams' explains project coordinator Gérard Brugnot, Natural
Risks Delegate at Cemagref in Grenoble (France). 'Some scientists
focus on measurements in the field, others on models, others on
decision-support tools.'
These approaches also reflect national differences. 'That is no
doubt to do with the fact that management of this kind of natural
risk is closely linked to town and country planning and decision
support, and thus to a political perspective. Before the SAME
project, everybody was convinced that they had the right system. One
of the merits of this project is the way it enabled us to bridge the
gaps between one country and another. The exchanges between
researchers were very rewarding, each one recognising the value of
the others' approach.'
Data, language and models
The first stage of the project was to collect an extensive
variety of data on avalanches, including site maps, incident files,
procedures, etc. Once gathered, they then had to be classified and
harmonised. At this stage, terminology proved a major problem. This
was overcome by creating a multilingual glossary of the terms used
to model and describe avalanches and to record all the relevant
details.
The SAME project also made progress in the field of modelling: an
inventory of about 50 different models was compiled, giving their
characteristics and conditions of application. This allowed
researchers to construct a single computerised platform capable of
using several different avalanche models for risk forecasting.
Some of these were field-tested at five sites in France, Italy,
Switzerland, Spain and Norway - each with a well-documented
avalanche history. 'We can conclude that there is clearly no miracle
model. Each one of them reflects certain parts of the full picture
on the ground and this is why it was so interesting to be able to
compare them. The researchers were able to identify the
complementary elements - all of which will have to be taken into
account in the future.'
Artificially triggered avalanches at specific test sites equipped
with measurement instrumentation, too, have allowed better
measurement and understanding of the internal dynamics of
snowslides. A variety of detectors, radar instruments and sensors of
all kinds were also tested at the same sites. This included precise
analysis of a series of parameters and testing the effectiveness of
systems for warning everyone in imminent danger.
Further research
'The accidents during the winter of 1999 were, in a way,
expected. But much more precise forecasting would have been needed
to avert them, and that is something we are not yet able to do,'
says Gérard Brugnot. 'To make progress, we need to know more about
the mechanisms that govern the build-up of snow - wind and
precipitation - instability within the snow cover, and the flow of
avalanches. The models constructed on the basis of this knowledge
could then be checked by experiments under controlled conditions and
compared with field data provided by historians.'
With further progress in mind, the Cadzie project has been
started to follow up SAME and address the new concerns raised by the
February 1999 avalanches. The objective of this research, which is
focusing on exceptionally catastrophic avalanches, is to improve
zoning and, in parallel, make defences more effective and more
reliable.
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Title Avalanche mapping, model validation
and warning systems (SAME)
Programme Environment and Climate (ENV
2C)
Reference ENV4960258
Contact Gérard
Brugnot Cemagref Grenoble France Fax :
+33-4-76762711 E-mail Web
site
Partners - Norwegian Geotechnical Institute,
Oslo, Norway - Laboratoire d'Instrumentation en
Microinformatique et Electronique, Université de Grenoble I,
Grenoble, France - Faculté de Géologie, Université de
Barcelone, Barcelone, Espagne - Centre d'Etudes de la
Neige, Centre National de Recherches météorologiques,
Saint-Martin-d'Hères, France - Forstliche
Bundesversuchasanstalt, Institut für Lawinen- und
Wilbachforschungf, Innnsbruck, Austria - Instituto de
Cartografia de Catalunya, Barcelone, Spain - Ecole
Polytechnolique Fédérale de Lausanne, Ecublens,
Switzerland - Space Research Institute - Russian Academy of
Sciences, Moscou, Russia - Swiss Federal Institute for
Forest, Sow and Landscape, Davos, Switzerland - Icelandic
Meteorological Office, Reykjavik, Iceland - Technische
Universität Graz, Graz, Austria - Università degli Studi di
Pavia, Pavie, Italy - Centro Sperimentale Valanghe e Difesa
Idrogeologica, Arabba Belluno, Italy - Università degli
Studi di Torina, Turin, Italy |
 Simulation of the February 1999
MontRoc avalanche in the Chamonix area (calculation and image
production: Mohamed Naaim). |