ALPMON FINAL REPORT - ARC systems research

Contract ENV4-CT96-0359 ALPMON
The costs of acquisition of homogeneous morphological, geological, soil and climate information over
the Alpine regions should be certainly huge but they could be paid off along several decades because
these information are durable and, like land cover, they could be applied for the assessment of other
critical environmental risks like run-off, floods and avalanches.
From this point of view the periodical use of remote sensing technology every few years (1-5) for land
cover updating over Alpine areas is surely the most cost-effective approach even though some limiting
factors to the use of satellite imagery in mountain areas last for the moment, like a significant
percentage of shadowed areas (e.g. in Cordevole test site nearly 10% of areas are permanently
shadowed) and a rather low probability to have fine weather conditions during satellite acquisitions
(e.g. in Veneto, only 20% of Thematic Mapper imagery is cloud free).
The erosion risk model FSTAB developed during this feasibility study was aimed to take into account a
wide range of mass erosion phenomena specific of Alpine areas. It must be pointed out that the
FSTAB differs from other erosion models because it does not provide an erosion rate index, which
would not in any case help preventing natural disasters, but an index (MEHI) representing the
propensity towards the generation of mass erosion.
To allow the model to represent the erosion risk inside the test site area of Cordevole with a level of
detail (scale 1:25.000) compatible with the customer requirements, which deal with the regional
planning of hydro-geological defence, were necessary both a calibration based on a geological ground
survey and a quite complex tuning of the fuzzy inference engine. The ground survey consisted in 115
points spread over 265 Km 2 with an average density of 0.43 points per Km 2 . The density of ground
points is a function of the complexity of the geomorphological features present in the study area as well
as of the required accuracy for the final erosion risk index. The tuning of the fuzzy inference engine
must be carried out by an expert geologist with the following skills: 1) sound background on mass
erosion phenomena; 2) general knowledge of the geomorphic processes present in the study area; 3)
good knowledge of principles of fuzzy set logic.
The FSTAB model was not conceived to work over bare rocks and slopes deeper than 45° because on
these areas rock falls are prevailing over mass erosion and these two phenomena are too different to
be considered by the same model. Therefore the full modelling of both mass erosion and rock falls
phenomena should require the integration of a further model.
The application of Discriminant Analysis in sub-model DA provided good results for the land zoning
giving a stability index which is strictly representative of the local intrinsic features. The value of DA
index could be even used alone as local stability index, anyway it cannot account for changes in
infiltration potential related to critical run-off events and needs therefore to be integrated to the SCS-
CN sub-model.
Fuzzy methods provided a good solution to the integration of the two sub-models. After a first
integration, the implementation of two separated sets of fuzzy inference rules was tested: the first for
debris flows and the second for all the other areas. Debris flows areas were discriminated using the
geomorphological map. This approach can be justified by the time difference which normally
differentiates debris flows from other slower mass movements. The problem of two different time
scales was solved introducing two diverse run-off thresholds.
In order to assess the erosion risk over the whole Alpine area, the erosion model should be flexible to
fit input data with very different accuracy. FSTAB has demonstrated to be a rather flexible model, as
compared to other erosion models like RUSLE, because some input parameters potentially affecting
the mass erosion risk can be even discarded, when their accuracy is not enough good, without prevent
the model from working. This was the case of the parameter ‘surface convexity’ which can significantly
affect the dynamics of surface water flow. In fact the surface convexity in Alpine areas characterised
by complex morphology must be estimated with high accuracy from a very high resolution Digital
Elevation Model. The pixel resolution of DEM should be around 5 metres i.e. the source topographic
map should be at scale 1:5000. In the test site area of Cordevole the DEM was derived from a
topographic map at 1:25.000 scale so it was non accurate enough to estimate surface convexity,
therefore this parameter was not taken into account.
JR, RSDE, ALU, LMU, Seibersdorf, WSL 52