O

Total radiation

Snow height

Snow height

SONDJ FMAMJJAS 1999-2000

Unfrozen water content, S

Flux through snow cover

Flux through snow cover

Total resistivity

2500

SONDJ FMAMJJAS 1999-2000

1500

Total resistivity

SONDJ FMAMJJAS 1999-2000

Figure 6.9 Comparison between borehole temperatures, energy balance parameters and resistivity. (a) Total temperature difference per day in the uppermost 10 m in the borehole, (b) net radiation at the energy balance station, (c) snow height, (d) calculated unfrozen water content (Equation (6.5)), (e) energy flux through the snow cover and (f) total resistivity variation at the borehole location (weighted vertical mean). From Hauck, C. & Vonder Miihll, D. 2003b. Permafrost monitoring using time-lapse resistivity tomography. In: Phillips, M., Springman, S.M. & Arenson, L.U. (eds): Permafrost. Proc. 8th International Conference on Permafrost, 21-25 July, Zurich, Switzerland, Vol. 1, 361-366, published by Balkema, Lisse. Reproduced by permission of Taylor and Francis

there, resistivities decrease again until September 2000, where a slightly larger value than the initial value in September 1999 is reached. Note that the strong resistivity increase during winter coincides with an almost zero total temperature change in the borehole (Figure 6.9a).

6.6 CONCLUSIONS

A multi-method approach using time-lapse resistivity tomography measurements at a mountain permafrost site in combination with laboratory measurements, borehole temperature and energy balance data has been presented as an example for state-of-the-art monitoring systems in mountain permafrost research. A set of 11 DC resistivity tomography measurements was obtained between September 1999 and September 2000 using a fixed electrode array at Schilthorn, Switzerland. The resulting resistivity changes were analysed in terms of subsurface freeze and thaw processes. Key results from this multi-parameter data set include the following:

• Temporal resistivity changes for permafrost monitoring in high Alpine environments can be accurately determined using a fixed electrode array, which is accessible throughout winter.

• Laboratory experiments using a miniature DC resistivity system can be used to determine material specific resistivity-temperature curves to validate the field data.

• Maximum resistivity changes on Schilthorn were observed in autumn (September-October), before a permanent snow cover has been established, and in late spring (May-June), when the thawing snow cover and additional water from precipitation greatly decreased the resistivity values in the active layer.

• During winter, the snow cover effectively decouples the ground from atmospheric influences. The heat flux through the snow cover was less than 1 W/m2, estimated from energy balance measurements. Consequently, a small but steady resistivity increase was obtained during winter, which was due to the trapped, cold October temperatures. From December to May, the freezing front moved gradually downward by thermal conduction, reaching 6 m in mid-April. After the start of the melting season, the resistivities decreased again until the previous September values are reached again at the end of August 2000.

• Resistivity-temperature relationships between the resistivity values at the borehole location and borehole temperatures show good agreement with theory. The increase of resistivity with decreasing temperature is small and linear for temperatures above the freezing point and exponential for temperatures below.

• The calculated temporal evolution of the unfrozen water content shows a strong decrease during the winter months in the active layer and a quasi-sinusoidal behaviour below.

• A comparison between borehole temperatures, resistivity and energy balance data emphasises the dominant role of the snow cover evolution in winter and net radiation in summer. In addition, resistivity monitoring may be used to determine the amount of freezing and thawing in the subsurface in future long-term monitoring programmes.

6.7 ACKNOWLEDGEMENTS

The authors would like to thank the Schilthornbahn AG for logistic support and C. Mittaz for supplying the energy balance data. This study was financed by the PACE project (Contract Nr ENV4-CT97-0492 and BBW Nr 97.0054-1). C. Hauck acknowledges a grant by the German Science Foundation (DFG) within the Graduiertenkolleg Natural Disasters, University of Karlsruhe.

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