the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 08 Jan 2024
Employing Automated Electrical Resistivity Tomography for detecting short- and long-term changes in permafrost and active layer dynamics in the Maritime Antarctic
Abstract. Repeated electrical resistivity tomography (ERT) surveys can substantially advance the understanding of spatial and temporal freeze-thaw dynamics in remote regions, such as Antarctica, where the evolution of permafrost has been poorly investigated. To enable the time-lapse ERT surveys in Antarctica, however, an automated ERT (A-ERT) system is required, as regular site visits are not feasible. In this context, we developed a robust A-ERT prototype and installed it in the Crater Lake CALM-S site at Deception Island, Antarctica to collect quasi-continuous ERT measurements. To efficiently process a large number of obtained A-ERT datasets, we developed an automated data processing workflow to efficiently filter and invert the A-ERT datasets and extract the key information required for a detailed investigation of permafrost and active layer dynamics.
In this paper, we report on the results of two complete year-round A-ERT datasets collected in 2010 and 2019 at Crater Lake CALM-S site and compare them with available climate and borehole data. The A-ERT profile has a length of 9.5 m with an electrode spacing of 0.5 m, enabling a maximum investigation depth of approximately 2 m. Our detailed investigation of the A-ERT data and inverted modeling results shows that the A-ERT system can detect the active-layer freezing and thawing events with very high temporal resolution. The resistivity of the permafrost zone in 2019 is very similar to the values found in 2010, suggesting the stability of the permafrost over almost one decade at this site. The evolution of thaw depth exhibits also a similar pattern in both years, with the active layer thickness fluctuating between 0.20–0.35 m. However, a slight thinning of the active layer is evident in early 2019, compared to the equivalent period in 2010.
These findings show that A-ERT, combined with the new processing workflow that we developed, is an efficient tool for studying permafrost and active layer dynamics with very high resolution and minimal environmental disturbance. The ability of the A-ERT setup to monitor the real-time progression of thaw depth, and to detect brief surficial refreezing and thawing of the active layer reveals the significance of the automatic ERT monitoring system to record continuous resistivity changes. This shows that the A-ERT setup described in this paper can be a significant addition to the Global Terrestrial Network for Permafrost (GTN-P) and the Circumpolar Active Layer Monitoring (CALM) networks to further investigate the impact of fast-changing climate and extreme meteorological events on the upper soil horizons and work towards establishing an early warning system for the consequences of climate change.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
(1636 KB)
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
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- Final revised paper
Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2023-2908', Anonymous Referee #1, 21 Mar 2024
Review "Employing Automated Electrical Resistivity Tomography for detecting short- and long-term changes in permafrost and active layer dynamics in the Maritime Antarctic" by Farzamian et al.
This paper presents a comparative study of electrical resistivity monitoring data acquired in 2010 and 2019 on Deception Island, Antarctica. The paper is set out to address three objectives: 1) present a novel automated ERT monitoring system, 2) describe an automated processing workflow to deal with >1000 repeated ERT measurements, and 3) to compare the data of the two years.
The third part is described in a lot of detail, yet for objective 1) the reader is referred to a previous paper, and for 2) the description is rather brief. Hence, you may want to reconsider the objectives of your paper.
Other than this very general comment, the paper reads well and is clear structured. While I appreciate the clear distinction between methods and results, I occasionally found myself flipping back and forth between them, since you describe some results in the methods section already, but then provide more detail in the actual results section. I would suggest to revise this. One suggestion would be to break from this strict divide into methods and results, and perhaps address your objectives 1) and 2) in the methods section (including presenting the results of the processing scheme), and then focusing on objective 3) of your paper in the results section.
I would also suggest to add a figure that shows the general trend in temperature and precipitation for the period from 2010 to now, just to show whether the years you are comparing have similar weather characteristics, and whether they are representative of the general trend. Some of your observations could also come from the temperature signal of previous years, and hence it would be good to show how these years compare to other years.
In your abstract, introduction, and conclusion, you are highlighting the advantage of ERT monitoring to image spatio-temporal freeze-thaw dynamics. Yet, you present data which doesn't show much spatial heterogeneity, and you focus your data presentation on a virtual borehole. This makes me wonder, and likely other readers too, why you would do ERT monitoring, where you are measuring resistivity i.e. a proxy to temperature, instead of installing an array of temperature sensors, which would give you direct temperature measurements at comparable resolution (i.e. 5 - 10 cm), and which would allow you to derive the same properties such as thaw depth. I think the data presentation as it is right now is fully appropriate, but I would suggest to perhaps extend the discussion and highlight cases where ERT monitoring may provide more information than a simple temperature sensor array. You do have this in the discussion at the moment, but it is not very prominent.
You will find some more detailed comments in the attached pdf.
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AC1: 'Reply on RC1', Mohammad Farzamian, 22 Jul 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2023-2908/egusphere-2023-2908-AC1-supplement.pdf
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AC1: 'Reply on RC1', Mohammad Farzamian, 22 Jul 2024
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RC2: 'Comment on egusphere-2023-2908', Anonymous Referee #2, 24 May 2024
General comment
Permafrost is degrading on a global scale and methods to estimate ground ice loss in a quantitative and non-invasive manner are rare. One of these methods is electrical resistivity tomography (ERT), which the authors apply here in an automated manner in the Maritime Antarctic comparing datasets spanning almost a decade (2010 and 2019) illustrating, compared to many other sites, quite stable conditions, which they interpret together with other non-geophysical data.
The manuscript is well written, the figures are of sufficient quality and the topic is of high relevance for the authorship of The Cryosphere. I therefore fully support its publication. My largest and single point of criticism (aside from the specific comments below) is the somewhat fuzzy scope of the manuscript, which needs to be sharpened in my opinion. In particular, the overlaps and differences to other manuscripts of (some of) the authors are not clear and should be clarified.
The authors state that this manuscript has 3 objectives (line 127). The first objective seems to have an overlap with the system presented in Farzamian et al. (2020) and I understand that the authors here present an updated version. A clearer explanation on what exactly changed would be helpful. I am most puzzled about the second objective, where the authors promise a "new semi-automated processing workflow". But later in the text it is written "Following the automated data filtering routine outlined by Herring et al. (2023)", a former publication of the second author. In addition, it seems that the first author also published another manuscript (Farzamian et al., 2024), which also has 3 objectives, where the first two seem to be very close to the objectives of this manuscript. For example, in the other manuscript, the second objective is also a "semi-automated processing workflow to filter and invert large number of A-ERT data sets". And most importantly, this other manuscript is not even mentioned here! (I realize that its publication overlapped with the review process of this publication – and I am sorry for contributing to the long review process – but the other manuscript could have been cited as "submitted" or "in review" for better transparency).
In revision of the papers, the authors are kindly asked to consider the specific comments below and shed light on the overlap and difference of this contribution to the work of Farzamian et al. (2020), Herring et al. (2023) and most importantly Farzamian et al. (2024).
Reference:
Farzamian, M., Blanchy, G., McLachlan, P., Vieira, G., Esteves, M., de Pablo, M. A., et al. (2024). Advancing permafrost monitoring with Autonomous Electrical Resistivity Tomography (A-ERT): Low-cost instrumentation and open-source data processing tool. Geophysical Research Letters, 51, e2023GL105770. https://doi.org/10.1029/2023GL105770
Specific comments
- L36: Remove "the" after "enable" and ", however," is also not needed here.
- L39: I suggest to remove the first somewhat redundant part of the sentence (until the comma), i.e. "We developed an automated data processing workflow to efficiently filter..."
- L45: Remove "modeling" after "inverted" to avoid confusion between inversion and (forward) modeling.
L46: "very high" -> "high" - L49: Redundant space before "0.35"
- L52: "very high" -> "high"
- L107: Acknowledging permanent ERT installations in a non-permafrost context through some additional references would be appropriate here.
- L121: Remove comma before "implying"
- L140: Missing superscipt in the abbreviation of square kilometers.
- Fig. 1: The A, B, ... labels look very pixeled. Is this due to the font used or unintended?
- L198: The formulation can be misleading as the 5 to 9 measurements are not stacked by themselves but used to produce one stacked measurement including a standard deviation, right?
- L208: Filtering here on the apparent resistivity would be enough right? The injected current should never be zero or smaller and depending on the polarity of the potential dipole measured voltages can be negative, right? Please clarify this processing step.
- Fig. 2.: I propose to change the colorbar label/unit to kiloohms to avoid some zeros here.
- L239: "optimized by L-curve" Can the authors elaborate on what is done here and why it is important?
- L240: What is "small" here? Does this mean an absolute noise (of?) in contrast to the 4% relative noise?
- L301: Was the error development over time considered?
- L330: This has been mentioned before.
- Fig. 5: Maybe changing the y unit to kiloohms would be clearer and more explicit here as the "1e4" is easily overlooked.
- L393: Move "th" to superscript formatting.
- Fig. 7: Depth is never negative by definition. Use "z (m)" as the label here or remove the minus signs.
- Section 3.3.3: Earlier the authors mention that consideration of the sensitivity is important to avoid misinterpretation. Was this sensitivity considered in calculating the average (i.e., by means of a sensitivity-weighted average)?
- L436: What exactly is meant here by a "phase change lag". This needs a bit more explanation.
- L515: Is this the first time this proposed in the literature? If not, it would be more transparent and correct to write "We support the proposal by ... that electrical resistivity could be ...."
- L519: The GitHub Link appears 4 times in the manuscript. I think mentioning it in the data and code availability sections is sufficient.
Citation: https://doi.org/10.5194/egusphere-2023-2908-RC2 -
AC2: 'Reply on RC2', Mohammad Farzamian, 22 Jul 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2023-2908/egusphere-2023-2908-AC2-supplement.pdf
Interactive discussion
Status: closed
-
RC1: 'Comment on egusphere-2023-2908', Anonymous Referee #1, 21 Mar 2024
Review "Employing Automated Electrical Resistivity Tomography for detecting short- and long-term changes in permafrost and active layer dynamics in the Maritime Antarctic" by Farzamian et al.
This paper presents a comparative study of electrical resistivity monitoring data acquired in 2010 and 2019 on Deception Island, Antarctica. The paper is set out to address three objectives: 1) present a novel automated ERT monitoring system, 2) describe an automated processing workflow to deal with >1000 repeated ERT measurements, and 3) to compare the data of the two years.
The third part is described in a lot of detail, yet for objective 1) the reader is referred to a previous paper, and for 2) the description is rather brief. Hence, you may want to reconsider the objectives of your paper.
Other than this very general comment, the paper reads well and is clear structured. While I appreciate the clear distinction between methods and results, I occasionally found myself flipping back and forth between them, since you describe some results in the methods section already, but then provide more detail in the actual results section. I would suggest to revise this. One suggestion would be to break from this strict divide into methods and results, and perhaps address your objectives 1) and 2) in the methods section (including presenting the results of the processing scheme), and then focusing on objective 3) of your paper in the results section.
I would also suggest to add a figure that shows the general trend in temperature and precipitation for the period from 2010 to now, just to show whether the years you are comparing have similar weather characteristics, and whether they are representative of the general trend. Some of your observations could also come from the temperature signal of previous years, and hence it would be good to show how these years compare to other years.
In your abstract, introduction, and conclusion, you are highlighting the advantage of ERT monitoring to image spatio-temporal freeze-thaw dynamics. Yet, you present data which doesn't show much spatial heterogeneity, and you focus your data presentation on a virtual borehole. This makes me wonder, and likely other readers too, why you would do ERT monitoring, where you are measuring resistivity i.e. a proxy to temperature, instead of installing an array of temperature sensors, which would give you direct temperature measurements at comparable resolution (i.e. 5 - 10 cm), and which would allow you to derive the same properties such as thaw depth. I think the data presentation as it is right now is fully appropriate, but I would suggest to perhaps extend the discussion and highlight cases where ERT monitoring may provide more information than a simple temperature sensor array. You do have this in the discussion at the moment, but it is not very prominent.
You will find some more detailed comments in the attached pdf.
-
AC1: 'Reply on RC1', Mohammad Farzamian, 22 Jul 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2023-2908/egusphere-2023-2908-AC1-supplement.pdf
-
AC1: 'Reply on RC1', Mohammad Farzamian, 22 Jul 2024
-
RC2: 'Comment on egusphere-2023-2908', Anonymous Referee #2, 24 May 2024
General comment
Permafrost is degrading on a global scale and methods to estimate ground ice loss in a quantitative and non-invasive manner are rare. One of these methods is electrical resistivity tomography (ERT), which the authors apply here in an automated manner in the Maritime Antarctic comparing datasets spanning almost a decade (2010 and 2019) illustrating, compared to many other sites, quite stable conditions, which they interpret together with other non-geophysical data.
The manuscript is well written, the figures are of sufficient quality and the topic is of high relevance for the authorship of The Cryosphere. I therefore fully support its publication. My largest and single point of criticism (aside from the specific comments below) is the somewhat fuzzy scope of the manuscript, which needs to be sharpened in my opinion. In particular, the overlaps and differences to other manuscripts of (some of) the authors are not clear and should be clarified.
The authors state that this manuscript has 3 objectives (line 127). The first objective seems to have an overlap with the system presented in Farzamian et al. (2020) and I understand that the authors here present an updated version. A clearer explanation on what exactly changed would be helpful. I am most puzzled about the second objective, where the authors promise a "new semi-automated processing workflow". But later in the text it is written "Following the automated data filtering routine outlined by Herring et al. (2023)", a former publication of the second author. In addition, it seems that the first author also published another manuscript (Farzamian et al., 2024), which also has 3 objectives, where the first two seem to be very close to the objectives of this manuscript. For example, in the other manuscript, the second objective is also a "semi-automated processing workflow to filter and invert large number of A-ERT data sets". And most importantly, this other manuscript is not even mentioned here! (I realize that its publication overlapped with the review process of this publication – and I am sorry for contributing to the long review process – but the other manuscript could have been cited as "submitted" or "in review" for better transparency).
In revision of the papers, the authors are kindly asked to consider the specific comments below and shed light on the overlap and difference of this contribution to the work of Farzamian et al. (2020), Herring et al. (2023) and most importantly Farzamian et al. (2024).
Reference:
Farzamian, M., Blanchy, G., McLachlan, P., Vieira, G., Esteves, M., de Pablo, M. A., et al. (2024). Advancing permafrost monitoring with Autonomous Electrical Resistivity Tomography (A-ERT): Low-cost instrumentation and open-source data processing tool. Geophysical Research Letters, 51, e2023GL105770. https://doi.org/10.1029/2023GL105770
Specific comments
- L36: Remove "the" after "enable" and ", however," is also not needed here.
- L39: I suggest to remove the first somewhat redundant part of the sentence (until the comma), i.e. "We developed an automated data processing workflow to efficiently filter..."
- L45: Remove "modeling" after "inverted" to avoid confusion between inversion and (forward) modeling.
L46: "very high" -> "high" - L49: Redundant space before "0.35"
- L52: "very high" -> "high"
- L107: Acknowledging permanent ERT installations in a non-permafrost context through some additional references would be appropriate here.
- L121: Remove comma before "implying"
- L140: Missing superscipt in the abbreviation of square kilometers.
- Fig. 1: The A, B, ... labels look very pixeled. Is this due to the font used or unintended?
- L198: The formulation can be misleading as the 5 to 9 measurements are not stacked by themselves but used to produce one stacked measurement including a standard deviation, right?
- L208: Filtering here on the apparent resistivity would be enough right? The injected current should never be zero or smaller and depending on the polarity of the potential dipole measured voltages can be negative, right? Please clarify this processing step.
- Fig. 2.: I propose to change the colorbar label/unit to kiloohms to avoid some zeros here.
- L239: "optimized by L-curve" Can the authors elaborate on what is done here and why it is important?
- L240: What is "small" here? Does this mean an absolute noise (of?) in contrast to the 4% relative noise?
- L301: Was the error development over time considered?
- L330: This has been mentioned before.
- Fig. 5: Maybe changing the y unit to kiloohms would be clearer and more explicit here as the "1e4" is easily overlooked.
- L393: Move "th" to superscript formatting.
- Fig. 7: Depth is never negative by definition. Use "z (m)" as the label here or remove the minus signs.
- Section 3.3.3: Earlier the authors mention that consideration of the sensitivity is important to avoid misinterpretation. Was this sensitivity considered in calculating the average (i.e., by means of a sensitivity-weighted average)?
- L436: What exactly is meant here by a "phase change lag". This needs a bit more explanation.
- L515: Is this the first time this proposed in the literature? If not, it would be more transparent and correct to write "We support the proposal by ... that electrical resistivity could be ...."
- L519: The GitHub Link appears 4 times in the manuscript. I think mentioning it in the data and code availability sections is sufficient.
Citation: https://doi.org/10.5194/egusphere-2023-2908-RC2 -
AC2: 'Reply on RC2', Mohammad Farzamian, 22 Jul 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2023-2908/egusphere-2023-2908-AC2-supplement.pdf
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- 1
Mohammad Farzamian
Teddi Herring
Goncalo Vieira
Miguel Angel de Pablo
Borhan Yaghoobi Tabar
Christian Hauck
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
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