Understanding the water cycle over the upper Tarim Basin: retrospecting the estimated discharge bias to atmospheric variables and model structure

Zhou, Xudong; Polcher, Jan; Yang, Tao; Hirabayashi, Yukiko; Nguyen-Quang, Trung

doi:https://doi.org/10.5194/hess-22-6087-2018

Articles | Volume 22, issue 11

https://doi.org/10.5194/hess-22-6087-2018

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

https://doi.org/10.5194/hess-22-6087-2018

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

Articles | Volume 22, issue 11

Cutting-edge case studies

|

28 Nov 2018

Cutting-edge case studies |

| 28 Nov 2018

Understanding the water cycle over the upper Tarim Basin: retrospecting the estimated discharge bias to atmospheric variables and model structure

Xudong Zhou, Jan Polcher, Tao Yang, Yukiko Hirabayashi, and Trung Nguyen-Quang

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Final revised paper (published on 28 Nov 2018)
Preprint (discussion started on 28 Mar 2018)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'Understanding the water cycle over the upper Tarim basin: retrospect the estimated discharge bias to atmospheric variables and model structure', Anonymous Referee #1, 02 Jun 2018
- AC1: 'Reply to Anonymous Referee #1', Xudong Zhou, 13 Jul 2018
RC2: 'Comment on “Understanding the water cycle over the upper Tarim basin: retrospect the estimated discharge bias to atmospheric variables and model structure” by Xudong Zhou et al.', Anonymous Referee #2, 03 Jul 2018
- AC2: 'Reply to Anonymous Referee #2', Xudong Zhou, 13 Jul 2018

Peer-review completion

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

ED: Publish subject to revisions (further review by editor and referees) (14 Jul 2018) by Zhongbo Yu

AR by Xudong Zhou on behalf of the Authors (18 Jul 2018) Author's response Manuscript

ED: Referee Nomination & Report Request started (27 Jul 2018) by Zhongbo Yu

RR by Anonymous Referee #1 (08 Aug 2018)

RR by Anonymous Referee #2 (12 Sep 2018)

RR by Anonymous Referee #3 (14 Oct 2018)

Suggestions for revision or reasons for rejection

Review comments on the paper entitled “Understanding the water cycle over the upper Tarim basin: retrospect the estimated discharge bias to atmospheric variables and model structure” by Zhou et al.,

The authors found that there is large bias in the modeled river discharge from observations when applying the land surface model-ORCHIDEE to Tarim River basin. They developed a framework with Budyko hypothesis and used it to trace back where the uncertainties come from. Other related studies are reviewed for obtaining useful information to qualify the possibility of different uncertainties. The basic conclusion is that the uncertainty or bias in precipitation is the main contributor to the final discharge bias. The structure of this paper is clear, the method used is correct and the results are reliable.

As per my experience in hydrological modeling, the bias is easily seen in discharge simulations and it can be caused by many kinds of uncertainties. Those uncertainties might also interact together which makes the attribution very difficult. This paper uses Budyko method and finds the possible space of bias in different variables. Although the exact values are not yet identified (that’s really difficult because the precipitation uncertainty cannot be measured), it is already a good improvement and an innovative attempt in uncertainty analysis.

Tarim basin is an interesting study area with complex climate types, topography and human activities. The uncertainties from different sources are probably larger than other regions for its mountain-oasis-desert topography. Therefore, the preparations of the model simulation in this paper by correcting the forcing with available data are very necessary and it shows the authors’ good understanding of the regional characteristics and their own model.

The ORCHIDEE-Budyko can be modified and combined with any other land surface model or hydrological models. Thus, I see the potential applicability of the methodology provided in this paper.

The authors have replied to the referees in details. The replies and corresponding reversions in the manuscript have solved those questions in the previous version of manuscript. Therefore, I think the manuscript of current version is suitable for HESS publication and I suggest acceptance for publication.

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ED: Publish as is (01 Nov 2018) by Zhongbo Yu

Short summary

Model bias is commonly seen in discharge simulation by hydrological or land surface models. This study tested an approach with the Budyko hypothesis to retrospect the estimated discharge bias to different bias sources including the atmospheric variables and model structure. Results indicate that the bias is most likely caused by the forcing variables, and the forcing bias should firstly be assessed and reduced in order to perform pertinent analysis of the regional water cycle.