Soil hydraulic material properties and layered  architecture from time-lapse GPR

Jaumann, Stefan; Roth, Kurt

doi:https://doi.org/10.5194/hess-22-2551-2018

Articles | Volume 22, issue 4

https://doi.org/10.5194/hess-22-2551-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-22-2551-2018

© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 22, issue 4

Research article

|

25 Apr 2018

Research article |

| 25 Apr 2018

Soil hydraulic material properties and layered architecture from time-lapse GPR

Stefan Jaumann and Kurt Roth

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Final revised paper (published on 25 Apr 2018)
Preprint (discussion started on 13 Sep 2017)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Review', Anonymous Referee #1, 15 Sep 2017
- AC1: 'Reply', Stefan Jaumann, 21 Dec 2017
RC2: 'Review', Anonymous Referee #2, 16 Nov 2017
- AC2: 'Reply', Stefan Jaumann, 21 Dec 2017
AC5: 'Revised version of the manuscript as referred to in the replies', Stefan Jaumann, 22 Dec 2017

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

ED: Publish subject to revisions (further review by editor and referees) (04 Jan 2018) by Insa Neuweiler

AR by Stefan Jaumann on behalf of the Authors (04 Jan 2018) Author's response Manuscript

ED: Referee Nomination & Report Request started (05 Jan 2018) by Insa Neuweiler

RR by Anonymous Referee #1 (05 Jan 2018)

RR by Anonymous Referee #2 (07 Mar 2018)

Suggestions for revision or reasons for rejection

The revised manuscript has been significantly improved compared to the original manuscript and duplications within the text have been removed. However, there still remain some open points, which I suggest to by clarified before publishing. All my new comments refer to the revised manuscript with changes marked, which I got from the Copernicus editorial office (hess-2017-538-author_response-version1.pdf). After finishing my review I realised that there are differences compared to the uploaded revised version without changes marked. I don’t know if this is a sloppiness of the authors or caused by a mix up of the editorial office.

Amplitude handling:
The description of amplitude handling has been mostly clarified and an additional flow chart has been provided as suggested. Please also include amplitude handling for the event detection (amplification with arbitrary fct prop t^2, page 11, line 3) in this chart. Please also specify the normalisation in the signal preprocessing box and provide an explanation in the text: does this mean that every radar trace (A-scan) is normalised to its maximum level and these normalised data are used for inversion?
Compared to the original manuscript, spherical divergence is not corrected any more (page 10, L 3-5 has been deleted as it included an incorrect formula). However, regardless the different amplitude handling, the inversion results remain exactly the same compared to the original manuscript. Is this correct?

Effective dielectric properties:
As I understand, you deduce the conductivity from the TDR pulse shape so that it corresponds to the effective conductivity, which includes DC conductivity and dielectric losses. I suggest to make this explicitly clear in the text (e.g. P7 L17). Please also describe how conductivity has been deduced from the TDR data in one sentence (amplitude, shape, which software, references?).

Assuming constant conductivity during the experiment (P8 L23):
This is still my main concern. As the water content changes in the sediment, intrinsic attenuation will also change. Please discuss your assumption of a constant effective conductivity critically and provide an estimate of the effects that you neglect (see my comment in the first review, second main point). For instance calculate and compare attenuation for saturated and unsaturated sand and the effect on reflection amplitudes of signals stemming from deeper interfaces of the experimental setup. I’m wondering that the synthetic data can fit the field data when attenuation effects are assumed to be constant during the experiment.

Further minor comments
(P1 L5) “…signal originating from a fluctuating groundwater table…” is misleading as also reflections at internal interfaces are used.
(P3 L30) “…multi-channel common offset GPR…” you mean multi-offset GPR? The nomenclature “multi-channel” only describes the GPR apparatus but does not provide any information on the measuring layout.
(P11 L3) “preprocessed amplitude”. What does this mean, please also include this in Fig. 3.
(P13 L5) “standard deviation of the measured normalised travel time … and the measured normalized amplitudes”. To me it is not clear how the standard deviations are calculated. Is this the STD of all measured traveltimes/amplitudes for one event during the experiment including changes caused by water table fluctuations or what are the input data for the calculation?
(P16 L25) Infinite dipole: … Gauss dot wavelet leads to a Ricker wavelet. To my knowledge this is only true for 3D simulation but not for 2D simulation especially for the phase spectrum. Please check.
Fig. 9, caption: “radargram is normalized to its maximum absolute amplitude”. The whole radar section is normalised to its maximum or each trace (A-scan) is normalised independently?
(P24 L2) “…calculated the difference to the true water content distribution”. $\Delta$ = true – mean or vice versa?
Figure 13: For every time step, there are much more residuals plotted than localised events.
uncomplete sentences: (P23 L6), (P26 L10), (P26 L27), (P28 L4), (P31 L12), (P31 L26), (P31 L26), (P34 L12), (P34 L21)

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ED: Publish subject to minor revisions (review by editor) (07 Mar 2018) by Insa Neuweiler

AR by Stefan Jaumann on behalf of the Authors (17 Mar 2018) Author's response Manuscript

ED: Publish as is (20 Mar 2018) by Insa Neuweiler

AR by Stefan Jaumann on behalf of the Authors (23 Mar 2018) Manuscript

Short summary

Ground-penetrating radar (GPR) is a noninvasive and nondestructive measurement method to monitor the hydraulic processes precisely and efficiently. We analyze synthetic as well as measured data from the ASSESS test site and show that the analysis yields accurate estimates for the soil hydraulic material properties as well as for the subsurface architecture by comparing the results to references derived from time domain reflectometry (TDR) and subsurface architecture ground truth data.