Permafrost Map of Switzerland

PERMAFROST MAP OF SWITZERLAND

Felix Keller1, Regula Frauenfelder2, Jean-Michel Gardaz3, Martin Hoelzle4, Christoph Kneisel5, Ralph Lugon6, Marcia Phillips7, Emmanuel Reynard8, Laurent Wenker9

1. GEOalpin, Center for alpine landscape analyses, Academia Engiadina, 7503 Samedan, Switzerland, e-mail: [email protected]

2. Institute of Geography, University of Zurich, Switzerland, e-mail: [email protected]

3. 6. Institute of Geography, University of Fribourg, Switzerland, 3. e-mail: [email protected] 6. e-mail: [email protected]

4. Institute of Geography,University of Zurich and Laboratory of Hydraulics, Hydrology and Glaciology, ETH-Zurich, Switzerland, e-mail: [email protected]

5. Institute of Geography, University of Trier, Germany, e-mail: [email protected]

6. Institute of Geography, University of Fribourg, Switzerland,

7. Swiss Federal Institute for Snow and Avalanche Research, 7260 Davos-Dorf, Switzerland e-mail: [email protected]

8. 9. Institute of Geography, University of Lausanne, Switzerland, 8. e-mail: [email protected] 9. e-mail: [email protected]

Abstract

Recently, computer programs have been developed within Geographical Information Systems (GIS) for automated mapping of mountain permafrost in combination with digital elevation information. One of these programs, PERMAKART - which is based on empirical knowledge about topographic factors affecting the distribution pattern of discontinuous permafrost in the Alps - was used to compile a permafrost-map of Switzerland (altitudes above 2000 m a.s.l.) using a grid resolution (mesh width) of 100 m. The reliability of this map was sta- tistically tested by comparison with a sample of 3943 BTS-measurements (bottom temperature of winter snow cover) as indicators for permafrost presence/absence. Mountain permafrost is estimated to be present beneath about 3.6% of the total area of Switzerland. Together with the 2.5% of transitional zone at the lower boundary of permafrost, this occurrence is slightly larger than the presently glacierized area.

Introduction protection, and hazards from debris flows and rock falls (Haeberli, 1992). Disturbance of the sensitive thermal Permafrost existence has not always been anticipated conditions of permafrost may lead to unforeseen con- in high mountain regions. Today, awareness is growing struction expenses or even render certain construction of the influence of alpine permafrost on construction techniques impossible. The presented permafrost map work, the operation of ski runs, avalanche and flood of Switzerland gives an overview of the current

Felix Keller, et al. 557 Figure 1. Permafrost in Switzerland determined by the surface factors elevation, exposure and general surface morphology. permafrost distribution. The applied empirical know- annual ground temperature (MAGT) is mainly ledge is based on geophysical measurements and direct determined by: observations. To open up attractive new areas (e.g., glaciers, high mountain landscapes) for tourism and to 1) Mean annual air temperature (MAAT): in the inves- ensure a long winter season at ski resorts, mountain tigated region, the altitude of 2400 m a.s.l. defines the railways are constructed at higher and higher altitudes. general lower limit of discontinuous permafrost occur- This leads to increasing problems in connection with rence. Statistical analyses of 14 meteorological stations permafrost. in the Grisons, Eastern Swiss Alps, yield an average altitude for the 0¡C isotherm of 2200 m a.s.l. (Hoelzle, One of the first methods for efficient permafrost map- 1992). Hence, discontinuous permafrost occurs at a ping in mountain areas in the Alps was developed by MAAT below 1¡C, this result stands in accordance with Haeberli (1975). Using refraction seismics, DC resistivi- observations in many other parts of the world (e.g., ty soundings, as well as a large number of ground tem- Cheng, 1983; King, 1984). perature data and visual inspection of outcrops, he derived the Òrules of thumb for the prediction of moun- 2) Solar radiation: aspect values of the surface indicate tain permafrost in the AlpsÓ. A part of these rules is an an approximate pattern of the solar radiation. empirical model of the mountain permafrost distribution in the Alps which determined a probable per- 3) Snow cover: the snow cover is an important factor mafrost zone and the permafrost limit as a transitional of the relationship between the MAAT and the ground zone with possible permafrost. This model was con- temperature (Keller and Gubler, 1993). A thick snow firmed by the analysis of infrared air-photo interpreta- cover during winter shields the contact zone between tion and BTS measurements (Hoelzle, 1992). the snow and the underlying ground from cold air tem- Incorporated in the model are the primary physical peratures, whereas a long snow cover duration pre- parameters which influence the ground temperature: vents the penetration of heat during spring, or even air temperature, solar radiation and general surface during some summer months. Avalanche snow tends to morphology (snow effects). Figure 1 shows the transla- accumulate at the foot of slopes. In these situations, the tion of these parameters into surface factors. The mean influence of long snow cover duration is more important than differences in aspect.

558 The 7th International Permafrost Conference Areas with a thin snow cover in early autumn show the permafrost distribution is performed using the special thermal conditions. The highest heat fluxes from capabilities of the cell-based geoprocessing system Grid the ground to the surface are to be expected when the within the GIS Software Arc/Info. The classification ground is covered only by a thin snow cover with an values for aspect and slope can be derived directly from emissivity of about 0.99. During cloudless nights, the the DEM, but adjustments need to be made to deter- energy loss through long-wave emission is distinctively mine which foot-slope segments have spring avalanche higher in such areas than in areas without snow. snow deposits. For this reason, a grid with a mesh Because of the low insulation influence of the thin snow width of 100 m is calculated with respect to the magni- cover, the main part of this energy flows from the sub- tude of the concavity of these topographical forms. surface. If the snow cover is more than 40 to 50 cm Surface classification produces a grid which can be thick, the surface temperature decreases and the long- combined with the empirical model generator (relatio- wave radiation is reduced, respecting BoltzmanÕs law. nal database table). Joining this information table with This Òfall snow effectÓ could induce permafrost if it the attribute table of the surface classification grid occurs repeatedly. results in a new grid containing the permafrost limits (probable/possible) for every cell. These limits are then Automated mapping of mountain permafrost compared with elevation values for each cell read from the input DEM. The final product is a digital map of the The computer-program PERMAKART applies a part modelled discontinuous permafrost distribution. of the rules of thumb from Haeberli, transferring a relation between altitude above sea level, exposure and Permafrost map of Switzerland permafrost probability (Keller, 1992). The main input is a digital elevation model (DEM). The application con- The Permafrost map of Switzerland (Figure 2) was tains three blocks: (1) a model-generator, (2) the calcula- calculated with PERMAKART using the digital elevation module and (3) a plotting system. The model ge- tion model TOPOPT of Switzerland (Swiss Federal nerator is the tool to convert the empirical model data Statistical Office, Section Geostat) with a cell resolution (Figure 1), which is to be used for mapping the per- of 100 m. In Switzerland, permafrost exists mainly in mafrost distribution, into a relational database table. four mountain regions, namely in the regions of Menu interfaces were developed to consider change of Engadin (St. Moritz area), Wallis (Zermatt area), mean annual air temperature, air-temperature gradient Bernese Alps (south of Berne) and the Tšdi Area (south and influence of different exposures. The calculation of of Zurich) (Figure 2). Generally, it can be noticed, that

Figure 2. Permafrost Map of Switzerland calculated with PERMAKART. Both categories (permafrost possible and probable) are shown in black. Digital elevation model: TOPOPT of Switzerland (Swiss Federal Statistical Office, Section Geostat).

Felix Keller, et al. 559 the southern side of the Alps is influenced more by per- measurements were performed. These BTS-measure- mafrost than the northern side, where the slopes and ments date from the years 1985 to 1997 and were mea- the highest valley floors show - as a result of higher sured in different locations of the Swiss Alps (Wallis, precipitation - a greater abundance of glaciers. Engadin, Bernese Alps) (Tenthorey, 1993; Gerber, 1994; According to the computer modelling, the occurence of Hoelzle, 1994; Keller, 1994; Gardaz et al., 1995; Kneisel, permafrost is calculated to be 4-6% of Swiss territory. 1995; Phillips and Reynard, 1996; Reynard, 1996; This area is significantly greater than the area that was Frauenfelder, 1997; Gardaz 1997; Reynard and Wenker, covered by glaciers (3.5%) around 1960. 1997; Wenker, 1997; Lugon and Monbaron, 1998; Gardaz, in preparation). The analysis of all mountain railways (cable railways, chair-lifts, ski-lifts) in the Swiss Alps showed that 15%, First, the BTS-measurements Ð which are originally or 288 of a total of 1894 mountain railway installations, stored as point features Ð are transformed into grids are located in the permafrost area. Analysing the length with a cell resolution of 100 m. The values of the cells indicates 51 km in probable permafrost, 55 km in possi- are based upon a statistical frequency analysis: the most ble permafrost, 1856 km in non-permafrost areas. Of frequently appearing BTS-class gives its value to the more importance is, which part of the construction is cell the measurements are located in. A permafrost cell situated in permafrost. Often problems occur at the must contain at least 50% of BTS-measurements with upper stations and at exposed pylons. values < -3.0¡C and may contain 15% BTS-temperatures > -2.0¡C at the maximum. The reverse function was For methodical reasons, permafrost patches that are applied for non-permafrost cells. If a cell contains less situated at lower altitudes (mostly in very shady loca- than 50% of one class, it is attributed to the transitional tions) could not be taken into consideration. Such zone, where the presence or absence of permafrost can regions are expected to exist in deeply incised valleys. not be determined with certainty. The output of these At the moment, the best tool to detect their locations is calculations is a new grid containing permafrost proba- the program PERMAMAP (Hoelzle, 1994). This model, bilities for each cell, that are based on the BTS-tempera- which was also implemented in Arc/Info is based on a tures. In a second step, this grid is combined with the statistical relation between potential direct solar radia- permafrost map of Switzerland. As the simulation of tion, air temperatures and BTS-temperatures. the permafrost distribution by PERMAKART can only be applied to regions above 2000 m. a.s.l., all measure- Test with BTS measurements ments below this altitude are excluded. The resulting grid contains information about the accordance of the BTS, as used for mapping permafrost, is defined as two approaches: if a cell is modelled as in the same the bottom temperature of the winter snow cover in class in both models, it is not taken into further consi- February and March beneath a seasonal snow depth deration. The remaining cells were classified into diffe- > 0.8 m. Snow, with its low thermal conductivity, is a rent categories by the two models. The altitude above high-frequency thermal filter between the atmosphere sea level can be extracted for each of these cells. Cells and the earthÕs surface. Therefore, the BTS value is which are classified by PERMAKART a class higher mainly controlled by heat flux in the uppermost part of than in the BTS-model (e.g., Òprobable permafrostÓ the ground. In the Alps, the BTS value is warmer than instead of Òpossible permafrostÓ) indicate locations, Ð2¡C when near-surface permafrost is absent (Haeberli, where the instructions of the original Òrules of thumbÓ 1973). A near-surface permafrost body in the ground have to be adjusted upwards. This means, that in such reduces the heat flux to the base of the snow cover and cases, the boundary is estimated as being too low by the keeps the BTS value in general below Ð3¡C. Òrules of thumbÓ. The reverse situation exists, if a cell is classified a class lower by PERMAKART than by the To test the reliability of the permafrost map of BTS-model (e.g., Òno permafrostÓ instead of Òpossible Switzerland (Figure 2), statistical tests with 3943 BTS- permafrostÓ). Here, the original boundaries have to be

Table 1. Analyses of the incorrectly predicted cells within the Permafrost Map of Switzerland in comparison to the 3943 BTS-measurements

560 The 7th International Permafrost Conference adjusted downwards. The statistical evaluation of all According to the evaluation with 3943 BTS-measure- resulting data leads to an average value (in meters ments, the boundary levels that are included in the a.s.l.) of the adjustments to be made for each permafrost original Òrules of thumb for predicting mountain per- category (Table 1). mafrostÓ seem to need adjustment. Though it is true that regional effects have to be taken into consideration, The maximum values for the category Òpossible per- the general tendency that is implied by the analysis is mafrostÓ Ð the limit between no permafrost and per- clear: the lower boundary of the Òpossible permafrostÓ mafrost possible - are +613 m for the upward adjust- category should be adjusted by about +58 m, while the ment and Ð685 m for the downward adjustment. This lower boundary of Òprobable permafrostÓ should be amounts to a mean difference and a mean adjustment adjusted by Ð43 m. to be made, of +58 m. The standard deviation is 219 m. For the limit between probable and possible permafrost The large variance of the error estimations show that Ð in the class Òprobable permafrostÓ Ð the maximum regional and local effects Ð such as local climate, radia- differences vary between +482 m and Ð727 m. On ave- tion differences due to the relief, geological precondi- rage, the lower boundary of probable permafrost distri- tions Ð are very important. In the ÒPermafrost Map of bution should be adjusted by Ð43 m, with a standard the SwitzerlandÓ these effects are not taken into consi- deviation of 253 m. The adjustment has to be applied deration in order to allow the large-scale analysis of the differentially according to slope preconditions: in slope- BTS-measurements. foot segments, the lower boundary has to be adjusted downwards, but in steep slopes, it must be adjusted The permafrost map of Switzerland presented here, upwards. will allow improvement of present and future permafrost estimation using both the original empirical Conclusions knowledge and the new results of the current The map shows that one has to expect a mean error of computer-assisted evaluation. altitude of +/-300 m. Given a slope angle of 20¡, this implies that the map has an accuracy of 800 m which can not be shown on the map (Figure 2) due to its scale.

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