the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Identifying mountain permafrost degradation by repeating historical ERT-measurements
Johannes Buckel
Jan Mudler
Rainer Gardeweg
Christian Hauck
Christin Hilbich
Regula Frauenfelder
Christof Kneisel
Sebastian Buchelt
Jan Henrik Blöthe
Andreas Hördt
Matthias Bücker
Abstract. Ongoing global warming intensifies the degradation of mountainous permafrost. Permafrost thawing impacts landform evolution, reduces fresh water resources, enhances the potential of natural hazards, and thus has significant socio-economic impact. Electrical resistivity tomography (ERT) has been widely used to map the ice-containing permafrost by its resistivity contrast compared to the surrounding non-frozen medium. This study aims to reveal the effects of ongoing climate warming on alpine permafrost by repeating historical ERT and analysing the temporal changes in the resistivity distribution. In order to facilitate the measurements, we introduce and discuss the employment of textile electrodes. These newly developed electrodes significantly reduce working effort, are easy to deploy on blocky surfaces, and yield sufficiently low contact resistances. We analyse permafrost evolution on three periglacial landforms (two rock glaciers and one talus slope) in the Swiss and Austrian Alps by repeating historical surveys after periods of 10, 12, and 16 years, respectively. The resistivity values have been significantly reduced in ice-poor permafrost landforms at all study sites. Interestingly, resistivity values related to ice-rich permafrost in the studied active rock glacier partly increased during the studied time period. To explain this apparently counterintuitive (in view of increased resistivity) observation, geomorphological circumstances such as the relief and increased creeping velocity of the active rock glacier, are discussed by using additional remote sensing data. The present study highlights ice-poor permafrost degradation in the Alps resulting from ever-accelerating global warming.
Johannes Buckel et al.
Status: final response (author comments only)
-
RC1: 'Comment on tc-2022-207', Jacopo Boaga, 27 Nov 2022
The paper concerns the use of time-repeated ERT surveys to assess the evolution of permafrost degradation in several Alps sites (from Switzerland and Austria). The paper is well written, clear and represents a relevant case study for the long time monitoring of periglacial landforms as rock glaciers. The work deserves publication in TC, after the minor comments suggested here below.
Ln 55-60 This paragraph seems to introduce ERT use in permafrost studies, but most of the references here cited are not relative to ERT application case studies. It sounds strange.
Ln 66-70 I'm not sure statistical approach can solve the problems of contact resistance, maybe this sentence should be re-phrased.
Ln 85 Here or in line 440, for specific galvanic contact in debris problem consider also https://doi.org/10.1002/nsg.12192
Ln 179-186 No clear the relative standard deviation 0.3%. Is this the stack error? Which error was used during the inversion process? Authors for sure appreciated how pre-processing is essential in ERT inversion. The filtering of the dataset should be then better described, if it is done with some pre-processing code or in the RES2DINV suite. 'Visually identifiable' is a weak approach for repeatable measurements.
Ln 252-260 The very important point highlighted by Uhlemann and Kuras should be inserted here, since breaking the point assumption is the first doubt arising from this (very interesting) textile approach.
Ln 278 Input voltage ? Do you mean current injection ?
Ln 285-290 This is my main criticism to the work: authors do not present a quantitative comparison of the most relevant aspect of these new electrodes: contact resistance. I expect that, as first testing of these very interesting approach, authors measure and compare contact resistance in KOhm. Did you measure contact resistance before collecting measurements ? Which range was measured? Did you compare textile and electrode contact resistance during the hybrid line collected ? When different instruments were used, internal resistance problem should be addressed too in the comparison of the electrodes performance.
Ln 395 Here contact resistance is cited but without values, as in ln 567.
Ln 558-560 This speculation about increasing in resistivity is very interesting and maybe need more space in the discussion, rather than in the conclusion. Here again injected current and contact resistance may play a relevant role and should be compared in the time-repeated ERT section.
In all all the ERT sections I suggest to increase fonts of axes, legend scale and labels.
I encourage the publication of this very interesting study for the cryosphere community.
Citation: https://doi.org/10.5194/tc-2022-207-RC1 -
AC1: 'Reply on RC1', Johannes Buckel, 18 Jan 2023
Dear Prof. Dr. Jacopo Boaga!
I hope you started well into the new year. Thank you very much for your review and your encouraging as well as important comments. This letter contains point by point responses on your comments (thick black letters). New/rephrased sentences are indicated by italic letters.
Ln 55-60 This paragraph seems to introduce ERT use in permafrost studies, but most of the references here cited are not relative to ERT application case studies. It sounds strange.
We carefully scrutinized citations to permafrost studies regarding typical periglacial landforms (protalus ramparts, talus slopes and rock glaciers). All the mentioned studies detected and characterized subsurface ice by using ERT except one: The citation “Kenner, R., Phillips, M., Beutel, J., Hiller, M., Limpach, P., Pointner, E. and Volken, M.: Factors controlling velocity variations at short-term, seasonal and multiyear time scales, Ritigraben rock glacier, Western Swiss Alps, Permafr. Periglac. Process., 28(4), 675–684, doi:10.1002/ppp.1953, 2017.” was replaced by the correct citation“Kenner, R., Phillips, M., Hauck, C., Hilbich, C., Mulsow, C., Bühler, Y., Stoffel, A. and Buchroithner, M.: New insights on permafrost genesis and conservation in talus slopes based on observations at Flüelapass, Eastern Switzerland, Geomorphology, 290(April), 101–113, doi:10.1016/j.geomorph.2017.04.011, 2017.”
The sentence was re-phrased to: “ERT measurements have also been successfully applied to detect and characterize permafrost on periglacial landforms as…”
Ln 66-70 I'm not sure statistical approach can solve the problems of contact resistance, maybe this sentence should be re-phrased.
We re-phrased the sentence as follows: Emerging challenges such as changing contact resistances, different instruments or inversion artefacts can be addressed, for example, by statistical analysis (Supper et al., 2014) or adapted data processing schemes (Oldenborger and LeBlanc, 2018).
Ln 85 Here or in line 440, for specific galvanic contact in debris problem consider also https://doi.org/10.1002/nsg.12192
We agree and have now included the mentioned publication in Ln 85 and in the citation list.
Ln 179-186 No clear the relative standard deviation 0.3%. Is this the stack error? Authors for sure appreciated how pre-processing is essential in ERT inversion. The filtering of the dataset should be then better described, if it is done with some pre-processing code or in the RES2DINV suite. 'Visually identifiable' is a weak approach for repeatable measurements.
This unclear paragraph was re-written as follows:
“An initial quality assessment of the field data was achieved during the data acquisition 2021 by using the GeoTom software (V. 7.19, Geolog 2000). In a first step, the data quality of each quadrupole measurement is checked visually by comparing its value with neighbouring points in the pseudo section. Large deviations or outliers (e.g. given by a defect in one cable which produced random values for measurements with one specific electrode) indicate poor data quality. In a second step, (a) all data points with a relative standard deviation of all stacks (stack error) above 0.3 %, and (b) all data points collected with the maximum value of the input voltage, which indicates that no sufficient signal strength can be achieved, were identified. Visually identified outliers as well as the values identified by (a) and (b) were re-measured after checking the placement of the electrodes and improving the contact between the electrode and the surface by adding salted water. Remeasured data points still meeting one of the criteria (a) or (b) or being obvious outliers were deleted and reconstructed by interpolating the neighbouring values before the inversion. Because information on stack error and input voltage was unavailable, this process could not be performed on the historical data. Instead, the historical data were filtered manually using the “Exterminate bad datum points”-function in the RES2DINV software. Bad data points are values with apparent resistivity that are apparently too large or too small compared to the neighbouring values. The overall number of filtered data points is given in tables 2 to 4 for the three surveyed catchments.”
Which error was used during the inversion process?
The inversion in Res2DInv was carried out without taking information on the data error into account.
Ln 252-260 The very important point highlighted by Uhlemann and Kuras should be inserted here, since breaking the point assumption is the first doubt arising from this (very interesting) textile approach.
In the corresponding paragraph in the Methods and Data section, we added information (Ln 258) on the actual electrode size (“Our design results in an approximately circular contact area with a diameter of roughly 15 cm.”) and make reference to the discussion in 5.1 (“Possible effects of the large electrode size and the violation of the point-source assumption during the inversion of the ERT data will be addressed in the discussion section.”).
The discussion of possible effects of the electrode size in section 5.1 is further extended as follows:
“For capacitively coupled electrodes, Uhlemann and Kuras (2014) argue that the point-pole approximation is valid, if the electrode spacing is at least 4 times the diameter of the contact area. Since the diameter of the contact area of our new textile electrode is <15 cm and our minimum electrode spacing is 4 m, we are well within these limits. To assess the effect of the size of square surface electrodes on ERT measurements, Cardarelli and De Donno (2019) carry out finite-element modelling studies. They find that for electrode separations five times the electrode size or larger, the relative error compared to a point source falls well below 1 %. This is in good agreement with the findings by Uhlemann and Kuras (2014) and further supports the feasibility of our relatively small textile electrodes.”
Ln 278 Input voltage ? Do you mean current injection ?
Changed to “…the input voltage used for current injection.”
Ln 285-290 This is my main criticism to the work: authors do not present a quantitative comparison of the most relevant aspect of these new electrodes: contact resistance. I expect that, as first testing of these very interesting approach, authors measure and compare contact resistance in KOhm. Did you measure contact resistance before collecting measurements ? Which range was measured? Did you compare textile and electrode contact resistance during the hybrid line collected ? When different instruments were used, internal resistance problem should be addressed too in the comparison of the electrodes performance.
In fact we did not measure contact resistance at this particular site, because under these difficult logistical conditions we tried to be as time-efficient as possible. We relied on earlier investigations of the textile electrodes within a bachelor’s thesis (see Westphal et al. 2022: (https://dgg2022.dgg-tagung.de/englisch/conference-booklet/)), in which the contact impedances of textile electrodes were investigated and compared with conventional steel electrodes over different surfaces. The main conclusion is that the textile electrodes perform as well as steel electrodes as long as a small amount of water is used to moisten the textile. Following these guidelines, we had no concerns about contact impedances during this survey. We added a few sentences in section 3.3 summarizing the results of previous investigations, including actual values of contact impedances.
Moreover, in order not to exceed the scope of this manuscript, a compromise had to be found to present different, very interesting aspects (permafrost degradation, geomorphological interpretation, remote sensing, ERT) in this manuscript. We focused on permafrost degradation and the geomorphological interpretation by ERT and remote sensing data. The use of the textile electrodes is (not mentioned in the title) therefore helpful, but detailed analyses can be expected in a separate manuscript in order not to go beyond the scope of the present manuscript here.
We added in Ln 271: “Our design results in an approximately circular contact area with a diameter of roughly 15 cm. Contacted resistances were investigated prior to the campaign over different surfaces and compared with those of conventional steel electrodes. It was found that the textile electrodes generally perform as well as steel electrodes as long as a small amount of water (e.g. 80 ml) is being used to moisten the textile. For example, on a semi-paved surface, both electrode types provided resistances between 2 and 5 kΩ, and even on a hard gravelly path where the steel electrodes could not be used, the average resistance of the textile electrodes was 6 kΩ, which is far below the threshold above which the equipment cannot reliably measure any more (> 1 MΩ for the Geotom).
During the survey described here, the surfaces were generally rugged, blocky and not flat, and therefore additional measures had to be taken. We placed wet sediment and sediment containing biotic material (e.g. roots, moss) between the textile electrode and the rugged surface of boulders.”
Ln 395 Here contact resistance is cited but without values, as in ln 567.
See comment above. No information on the actual contact resistances during the data collection in the field is available.
Ln 558-560 This speculation about increasing in resistivity is very interesting and maybe need more space in the discussion, rather than in the conclusion. Here again injected current and contact resistance may play a relevant role and should be compared in the time-repeated ERT section.
The increasing resistivity during the period of 16 years is indicated in two profiles (GG-P2 and GG-P3). We attribute this resistivity increase to a geomorphic background and not to a technical issue. If this increase should be attributed to contact resistances or the potential injected current, it would also have to be recognizable in other profiles (e.g. GG-P1 and GG-P4).
Furthermore, as long as the contact resistance of the textile electrodes is not orders of magnitudes higher than the contact resistance of traditional spike electrodes, we do not expect any significant effect of the contact resistance on the reconstructed resistivity values in the subsurface. This can be seen in Figure 6 of the manuscript, which compares resistivity models reconstructed from three different electrode-substrate coupling types (steel pikes, steel pikes with sponges, textile electrodes). As long as a reasonable contact can be established between the substrate and the electrode, the apparent resistivity measured with a four-point setup should, in principle, be independent of the contact resistance.
In all all the ERT sections I suggest to increase fonts of axes, legend scale and labels.
We agree and all fonts were increased.
Best regards, Johannes Buckel
References:
Cardarelli, E. and De Donno, G.: Chapter 2 - Advances in electric resistivity tomography: Theory and case studies, in Innovation in Near-Surface Geophysics, edited by R. Persico, S. Piro, and N. Linford, pp. 23–57, Elsevier., 2019.
Westphal K., Mudler J., Buckel J., Bücker M., Hördt A. (2022): Die Anwendung von Textilelektroden bei geoelektrischen Widerstandsmessungen. 82. Jahrestagung Deutsche Geophysikalische Gesellschaft, 07.–10. März 2022, München (online) (Abstract&Poster)
Citation: https://doi.org/10.5194/tc-2022-207-AC1
-
AC1: 'Reply on RC1', Johannes Buckel, 18 Jan 2023
-
CC1: 'Comment on tc-2022-207', Wilfried Haeberli, 07 Dec 2022
Seminal historical resistivity soundings on mountain permafrost
The interesting paper by Buckel et al. points to early electrical resistivity soundings in the Swiss Alps. Correct reference should thereby be made to Fisch et al. (1978; publicly available via ResearchGate). These early measurements constitute the first reported electrical resistivity soundings on viscous creep features in ice-rich mountain permafrost usually called rock glaciers, providing ground-breaking insights already at that time.
On behalf of the Grande Dixence power scheme, long profiles were measured by Werner Fisch, father and son, in the region of Prafleuri (1950s) and Kintole (1960) but only reported in a science context roughly two decades later. At Prafleuri, a deep excavation in ice-supersaturated frozen materials was also carried out, and specific profiles were measured at Kintole on top as well as underneath buried surface ice (cf. Figures 14 and 15 with text comments in Haeberli (1985)). The following were key results from these unique historical soundings and observations:
- Perennially frozen talus/debris in rock glaciers is very rich in ice with visible occurrences of excess ice.
- Such frozen materials have electrical resistivities in the medium to high kΩm range.
- These resistivity values are clearly different from values in the high MΩm-range measured elsewhere in ice of glaciers with a temperate/wet firn-ice metamorphosis.
- Usually thin debris-covered remains of small glaciers or ice patches can be embedded on top of much thicker masses of perennially frozen materials.
In the meantime, a large and steadily increasing number of geophysical soundings and drillings confirmed and continue to confirm these early findings. It is a special merit of the submitted paper to point to early sources of our knowledge and understanding.
References:
Fisch, W. sen., Fisch, W. jun. and Haeberli, W.: Electrical D.C. resistivity soundings with long profiles on rock glaciers and moraines in the Alps of Switzerland, Zeitschrift für Gletscherkunde und Glazialgeologie 13 (1/2), 239-260, 1978.
Haeberli, W.: Creep of mountain permafrost: internal structure and flow of Alpine rock glaciers. Mitteilung VAW/ETHZ 74, 1985.
-
RC2: 'Comment on tc-2022-207', Lukas U. Arenson, 23 Jan 2023
Dear authors,
I enjoyed reading your paper and think it is a valuable contribution to better understand permafrost degradation in mountain environments. Overall, the paper is well written and is of interest to the readers of The Cryosphere. There are, however, several minor aspects I would suggest the authors to clarify and revise. In terms of a general comment, the authors must be careful that permafrost degradation is not limited to changes in ground temperature, but also changes in unfrozen water content, which isn’t mentioned once as a process. Latent heat, which is only mentioned once, plays a key role and the changes in resistivity must be evaluated in the context of phase change and not just temperature change. In addition, it would be helpful if the authors provided more information regarding the limitation, accuracy and errors of the various measurements. In other words, when can once trust that a change is a real change and not related to the limitation of the measurements.
- Line 16: Delete “mountain” as the statement is true for all of the permafrost around the world
- Line 20: “Alpine”. Please try to be consistent throughout the manuscript. Alpine, with a capital A, reference to the Alps, whereas alpine with a small a references mountain environments with alpine climate, but are geographically not restricted to the Alps. Finally, and the most general term is “mountain”. In the context of the paper I suggest to use mountain permafrost consistency.
- Line 24: Delete “periods of”, redundant wording.
- Line 28: Creep instead of Creeping (check also other places in the manuscript!)
- Line 35: “mountain” instead of “mountainous”
- Line 37: Add Arenson et al. (2022) as reference:
Arenson, L. U., Harrington, J. S., Koenig, C. E. M., & Wainstein, P. A. (2022). Mountain Permafrost Hydrology—A Practical Review Following Studies from the Andes. Geosciences, 12(2), 48. https://doi.org/10.3390/geosciences12020048 - Line 44: “used to distinguish ice-poor from ice-rich” replace with “used to differentiate between ice-poor and ice-rich”
- Line 48: delete “of”
- Line 48: what about RST?
- Line 69: mountain permafrost, not mountainous permafrost
- Line 112: Following the latest guidelines from the IPA Rock glacier inventories and kinematics working group, I suggest to call this a talus derived rock glacier and not a protalus rock glacier.
- Line 125: When using a name, rock glacier, is typically capitalize (this applies at various locations in the manuscript), i.e. Gianda Grischa Rock Glacier
- Line 135: Delete “in this study”
- Line 153: Delete “by -1.3 °C”
- Line 156: “Otto et al. (2012)”
- Line 200ff: but also, as permafrost degrades and the amount of unfrozen water increases. Even small amounts of unfrozen water can have significant effects on the electrical resistivity.
- Line 204: delete “perennial”
- Line 224: “large” instead of “huge”
- Line 255: “delete “ice” before maximized.
- Line 300: “ had any lab testing being performed with these electrodes, to evaluate the effect under controlled conditions? I find it very difficult to evaluate the effect if the conditions are not properly controlled. I.e. only a very general and qualitative conclusion is possible at this point.
- Line 310: Delete “nevertheless”
- ERT tomograms. Please add the following parameters from the overview tables (e.g. Table 1) to all the tomograms: Electrode Spacing, No. of Iterations and RMS error [%].
- Line 316: But also increase in unfrozen water content. Decreasing resistivity is a combination of two processes.
- Line 317: this could be a result of seasonal conditions and not necessarily the result of long term change, i.e. wetter summer
- Figure 6 (and other figures): Make sure that the y-Axis are all the same
- Figure 6 (and other figures): Make sure that EVERY number has a unit, or that the units are clearly indicated. Distances are often not labeled with the appropriate unit.
- Line 367 (and other places); Permafrost doesn’t melt, because permafrost is a thermal state. Use degrade in the context of permafrost. If you specifically refer o the ground ice, then you can use melt, but ice must be indicated.
- Line 370: 16-year period
- Line 374 (and other places): Make sure to not use massive ice and ice-rich permafrost as synonyms. I suggest to use ice-rich permafrost in this paper, unless you have physical evidence, e.g. from drilling, that there is massive ice. (e.g. also Line 399).
- Line 395 ff: You have to be careful that increase in resistivity is not automatically attributed to poor data while decrease in resistivity to permafrost degradation. The interpretation of your data cannot be biased towards the second.
- Line 414 (but also other instances): Be careful with preposition “of” and “in”. In this case “in” would be better. When using “reduction of” the focus on is the reduction itself, but when using “in” the focus is on what is reduced. In this case, the focus is the resistivity, because that is what you are measuring and comparing. On line 417 you have a similar situation with “similarity” or in line 472 with “increase”.
- Line 427: This isn’t just rue for alpine settings
- Line 444: delete “of”
- Line 456: creep instead of creeping
- Figure 12b: arrow lengths should be scaled according to velocity
- Line 510: “stronger” is relative. You are just limiting the response to temperature. Changes in unfrozen water content w/o major change in temperature may also be labeled as a strong response.
- Line 425: “increase in MAGT”: Don't just focus on temperatures. The manuscript provides the impression as if permafrost degradation is equal to warming. This is incorrect as changing state, i.e. the thawing of ground ice, is very critical. Changes in resistivity are perfect to record such changes. This must be discussed in more detail and the discussion should not be limited to changes in MAGT.
- Line 528: “faster reaction” ignores the effect of latent heat, which is very energy intensive. But is also a fast reaction, it just doesn’t manifest itself so quickly; and is much more difficult to measure and observe in the field.
- Line 345: degrade not melt
- Section 5, Discussion: I would have liked a discussion on the errors / accuracy of the measurements and inversion techniques used. How much of the changes noted may be attributed to errors and other uncertainties in the measurements? What is the level of change at which one can confidentially say that the properties of the ground have really changed?
- Line 559: amount “of” ice
- Line 560: “increased” instead of “fastened”. Note: a rate cannot get faster. Only a velocity can
- Line 562: “…, by different data acquisition(measurement equipment, electrode array, spacing, profile length) and by geomorphological circumstances that need to be considered for the comparative interpretation of the resistivity data.” This statement only appears in the conclusions, but this should be discussed further in the previous sections. It is very important and essential for the completion of similar studies in the future.
- Line 568: Delete “obviously”
Citation: https://doi.org/10.5194/tc-2022-207-RC2 -
AC2: 'Reply on RC2', Johannes Buckel, 20 Feb 2023
Dear Prof. Dr. Lucas U. Arenson!
We would like to thank you very much for the highly constructive and motivating review which helped us to improve the manuscript. We hope that we have adequately addressed and answered all reviewer comments and changed the manuscript accordingly. This letter contains point by point responses on your comments (thick black letters). New/rephrased sentences are indicated by italic letters. We attached the point by point responses in a seperate pdf due to formatting issues.
Best regards, the author team
Johannes Buckel et al.
Data sets
Identifying mountain permafrost degradation by repeating historical ERT-measurements - supplement Buckel, Johannes, & Gardeweg, Rainer https://doi.org/10.5281/zenodo.7348526
Model code and software
Identifying mountain permafrost degradation by repeating historical ERT-measurements - supplement Buckel, Johannes, & Gardeweg, Rainer https://doi.org/10.5281/zenodo.7348526
Johannes Buckel et al.
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 466 | 191 | 17 | 674 | 6 | 6 |
- HTML: 466
- PDF: 191
- XML: 17
- Total: 674
- BibTeX: 6
- EndNote: 6
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1