An integrated observation dataset of the hydrological and thermal deformation in permafrost slopes and engineering infrastructure in the Qinghai–Tibet Engineering Corridor

Luo, Lihui; Zhuang, Yanli; Zhang, Mingyi; Zhang, Zhongqiong; Ma, Wei; Zhao, Wenzhi; Zhao, Lin; Wang, Li; Shi, Yanmei; Zhang, Ze; Duan, Quntao; Tian, Deyu; Zhou, Qingguo

doi:https://doi.org/10.5194/essd-13-4035-2021

Articles | Volume 13, issue 8

https://doi.org/10.5194/essd-13-4035-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/essd-13-4035-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 13, issue 8

Data description paper

|

20 Aug 2021

Data description paper |

| 20 Aug 2021

An integrated observation dataset of the hydrological and thermal deformation in permafrost slopes and engineering infrastructure in the Qinghai–Tibet Engineering Corridor

Lihui Luo, Yanli Zhuang, Mingyi Zhang, Zhongqiong Zhang, Wei Ma, Wenzhi Zhao, Lin Zhao, Li Wang, Yanmei Shi, Ze Zhang, Quntao Duan, Deyu Tian, and Qingguo Zhou

Download

Final revised paper (published on 20 Aug 2021)
Supplement to the final revised paper
Preprint (discussion started on 15 Jul 2020)

Interactive discussion

Status: closed

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

- Printer-friendly version

- Supplement

RC1: 'Review to QTEC permafrost dataset', Jan Beutel, 13 Aug 2020
- AC1: 'Reply on RC1', Lihui Luo, 14 Apr 2021
RC2: 'Comment on essd-2020-106', Anonymous Referee #2, 23 Feb 2021
- AC2: 'Reply on RC2', Lihui Luo, 14 Apr 2021

Peer-review completion

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

AR by Lihui Luo on behalf of the Authors (03 May 2021) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (04 May 2021) by Kirsten Elger

RR by Jan Beutel (10 May 2021)

Suggestions for revision or reasons for rejection

Dear authors,

as stated in the previous review report your submission is lacking w.r.t. the dataset preparation. I acknowledge your efforts done for this the revision, especially the preparation of an extensive README document as guidance, a working R codebase and the inclusion of the InSAR data, however data files mentioned are still missing and/or the data described cannot be found. Also, some of the files I downloaded from Zenodo are labeled as corrupt.

In your response you add two figures R2/R3 as well as argumentation about certain subjects. If these figures/argumentation is important for the understanding of the manuscript they should be included there, and not only in the response of the authors. IMHO the figures R2 and R3 would be nice to have in the full paper.

Concerning data cleaning/validation you mention a column "corrected_p" and give a table 3 on correction values. however i cannot find these in any data file provided.

You mention a multitude of data corrections as well as gap filling. The details remain unclear and especially w.r.t. figure 2 the utility is not given. you simply interpolate over large gaps of ~a year of data. That is not correct here. remove the green daily means at least for the large gaps.

The README files you have created greatly simplify the data access. However the contain incorrect/incomplete information w.r.t. the data files provided. A number of the files listed in table 2 cannot be found in the repository or they are named slightly different. Furthermore the data variables listed in table 3 cannot be found. As such the data description paper as well as the dataset are not in agreement and should be rejected.

As a last comment i don't think it is necessary to make a copy of the readme file in each directory as well as in the supplement and it's subdirectories. rather than having many (copied) README file, concentrate on generating one that contains full and correct information.

(In the README to your data)
Data Sources and Terms of Use
The use of data is conditional on citing the original data sources. Full details on how to cite the data are given at the bottom of each page. For research projects, if the data are essential to the work, or if an important result or conclusion depends on the data, co-authorship may need to be considered. Permafrost engineering and slope monitoring facilitate the acquisition of data to encourage its use and promote understanding of the potential impact of freeze-thaw cycles on Permafrost engineering. Respecting original data sources is key to help secure the support of data providers to enhance, maintain and update valuable data.

Hide

ED: Reconsider after major revisions (21 May 2021) by Kirsten Elger

AR by Lihui Luo on behalf of the Authors (02 Jun 2021) Author's response Author's tracked changes Manuscript

ED: Referee Nomination & Report Request started (02 Jun 2021) by Kirsten Elger

RR by Jan Beutel (08 Jun 2021)

Suggestions for revision or reasons for rejection

Dear authors,

the last revision is greatly improved w.r.t. consistency and completeness. It is commendable that you also took the time to update some of the data up to the year 2020 (in part). However again here, consistency is key and consistency across the four data/code packages as well as the paper supplement you supply is not given. There are a few discrepancies left that you should/may address in order to facilitate re-use of this dataset:

- The README files given should be synchronized. The new README file in the supplement is different to the one in R-code/TLS data. Filenames, listings, license.

- The data files in the R-Code https://zenodo.org/record/4686141 are not in agreement with the data files in https://zenodo.org/record/4879639. Not concerning the data duration and especially not concerning the format. Therefore it is unclear to me which data is which? And what benefit the R-code really brings, apart from generating your two figures for the paper. It is certainly not a show killer, but it requires some manual checking by everyone that wants to build on your paper/data.

- w.r.t. figure 2 my gap filling comment earlier was specifically geared at the one year+ gap on the wind data for 2014-2016. Here the green line should really removed as the wind speed is not deviating that much. Also it is a pity you supply data up to recently (2020) but do not show this data in one of the plots.

- The data files in https://zenodo.org/record/4879639 have different formats. While the data in the .CSV is explained in detail (README, tables, columns, quality control, corrections) Meteo_00000_Xidatan_2014-2019.xlsx and GT_00000_Slopes_2014-2019.xlsx are not explained. Specifically, if these files are not quality controlled/checked this should be specifically mentioned.

- the xidatan Meteo data already has a DOI citation 10.11888/Meteoro.tpdc.270084. this one should be specified in full as it allows the reader to obtain regular updates autonomously.

- It is great that your UAV/RBG/TIR data now works.

Hide

ED: Publish subject to minor revisions (review by editor) (14 Jun 2021) by Kirsten Elger

AR by Lihui Luo on behalf of the Authors (23 Jun 2021) Author's response Author's tracked changes Manuscript

ED: Publish as is (18 Jul 2021) by Kirsten Elger

AR by Lihui Luo on behalf of the Authors (27 Jul 2021) Manuscript

Download

Article (35030 KB)
Full-text XML

Short summary

We implement a variety of sensors to monitor the hydrological and thermal deformation between permafrost slopes and engineering projects in the hinterland of the Qinghai–Tibet Plateau. We present the integrated observation dataset from the 1950s to 2020, explaining the instrumentation, processing, data visualisation, and quality control.