Estimating daily evapotranspiration based on a model  of evaporative fraction (EF) for mixed pixels

Li, Fugen; Xin, Xiaozhou; Peng, Zhiqing; Liu, Qinhuo

doi:https://doi.org/10.5194/hess-23-949-2019

Articles | Volume 23, issue 2

https://doi.org/10.5194/hess-23-949-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/hess-23-949-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 23, issue 2

Research article

|

18 Feb 2019

Research article |

| 18 Feb 2019

Estimating daily evapotranspiration based on a model of evaporative fraction (EF) for mixed pixels

Fugen Li, Xiaozhou Xin, Zhiqing Peng, and Qinhuo Liu

Download

Final revised paper (published on 18 Feb 2019)
Preprint (discussion started on 22 May 2018)

Interactive discussion

Status: closed

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

- Printer-friendly version

- Supplement

RC1: 'Reviewers comment's/suggestions', Anonymous Referee #1, 04 Jun 2018
- AC1: 'Reply-Anonymous Referee #1', Fugen Li, 02 Oct 2018
RC2: 'Comments on manuscript', Anonymous Referee #2, 05 Sep 2018
- AC2: 'Reply-Anonymous Referee #2', Fugen Li, 02 Oct 2018

Peer-review completion

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

ED: Reconsider after major revisions (further review by editor and referees) (11 Oct 2018) by Graham Jewitt

AR by Anna Wenzel on behalf of the Authors (08 Nov 2018) Author's response Manuscript

ED: Reconsider after major revisions (further review by editor and referees) (12 Nov 2018) by Graham Jewitt

ED: Referee Nomination & Report Request started (18 Dec 2018) by Graham Jewitt

RR by Anonymous Referee #2 (10 Jan 2019)

Suggestions for revision or reasons for rejection

Dear Author

I have read through the adjusted manuscript and your reply to the original comments. I believe the manuscript to have been greatly improved, and thank the authors for this. I do have some comments on newly added bits.
1) the introductionairy paragraph now also contains information regarding previous results of scaling methodologies. However these mostly talk about differences found on how aggregating input data to estimate lumped ET causes extra uncertainties in regard to distributed estimations. They do not however talk about efforts on actual disaggregation of ET. While DisAlexi is mentioned, the results of this model are not clearly shown. This (in my view) should be the benchmark to which all disaggregation models should strive. As such, it should be mentioned in the 'discussion section', however apart from the initial mentioning in the introduction it is not discussed.
2) You specify the IPUS is a widely used EB model, capable of handlin multi-scale (VNIR,TIR) observations. The equations provided of this model however do not show this. In fact, the equations appear similar to all other EB models. Particularly because the TIR data used is of much lower resolution then the VNIR (300m vs 30m), the 'sharpening' of the TIR data should be explained more clearly, as the whole focus on this paper is on ET scaling issues.
3) In your response you have indeed clearified that advection is not included in the model. In fact this can be clearly seen in the transition zones in the transition zones between the oasis areas en the uncultivated ones. This however is not clearly highlighted upon on page 19 (where this is shown).
4) You specify that you exlude stations 07,08,10 and 15 from the results as they are located in the area's with pure pixels. However on page 21, you specify RMSE's for the pure pixels. In that regard, I am unsure what you mean. Please clearify and correct.
5) In your study area you had the benefit of meteorological towers, so that you could have very good estimates on Ta, U, humidty.. etc. However in many case's such measurements are not present (and only singular values for these parameters are available for a whole study area, estimated by weather models). In my view, this is one of the most important uncertainties when scaling between coarse and fine resolution. Can you please comment on this in your discussion.
6) I find the modified 'error analyses' of the different hypothesis a good addition. I however miss how this can be used in terms of applicability. For instance, if the difference in dA is too large (for transition zones), one can specify that for those pixels, initial assumptions break down, and now estimations can be made. Similarly, one could specify that if R2 values fall below 90%, those data should not be included filtered out. is this possible?
7) Finally, I find the most of the discussion section in fact not discusses the results, but is more a 'summary' of what the method does. Next to the obvious shortcomings that were highlighted in the main text, I would prefer if here additional information is given regarding other methods (such as Disalexi).

Futher, I have noticed some citations to papers in the main text, which have not been included in the references. This should be addressed

Hide

RR by Anonymous Referee #1 (21 Jan 2019)

ED: Publish subject to minor revisions (review by editor) (23 Jan 2019) by Graham Jewitt

AR by Fugen Li on behalf of the Authors (01 Feb 2019) Author's response Manuscript

ED: Publish subject to technical corrections (06 Feb 2019) by Graham Jewitt

AR by Fugen Li on behalf of the Authors (07 Feb 2019) Author's response Manuscript

Short summary

This study proposes a simple but efficient model for estimating daily evapotranspiration considering heterogeneity of mixed pixels. In order to do so, an equation to calculate evapotranspiration fraction (EF) of mixed pixels was derived based on two key hypotheses. The model is easy to apply and is independent and easy to be embedded in the traditional remote sensing algorithms of heat fluxes to get daily ET.