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Volume 11
Issue 2
10.3390/w11020317
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Article
Peer-Review Record

Meteorological Factors Affecting Pan Evaporation in the Haihe River Basin, China

Water 2019, 11(2), 317; https://doi.org/10.3390/w11020317
by Zhihong Yan 1, Shuqian Wang 1,*, Ding Ma 2, Bin Liu 1,*, Hong Lin 1 and Su Li 1
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Water 2019, 11(2), 317; https://doi.org/10.3390/w11020317
Submission received: 16 December 2018 / Revised: 1 February 2019 / Accepted: 10 February 2019 / Published: 13 February 2019
(This article belongs to the Special Issue Climate Variability and Climate Change Impacts on Land Surface, Hydrological Processes and Water Management)

Round 1

Reviewer 1 Report

The authors presented an interesting climatological issue which I found quite interesting. Previous work and theoretical considerations generated expecttations about the behaviour of pan evaporation as other climate variations (in particular temperature and precipitation) vary. Sometimes the expected behaviour has not materialized. The authors of this paper propose that other variations such as wind speed and sunshine duration can explain the unexpected behaviour. In this the paper has made persuasive arguments supported by extensive results from sub areas in the Haihe River Basin.

I have some hopefully minor concerns about the statistical methodology.

1) The Mann-Kendall test for trends can be used for non-normal data and thus is appropriate for climate data (particularly for precipitation). However the test can be influenced by auto-correlation and this should be checked for the various time series. If it has been checked, this should be stated.

2) Using linear regression for estimating the magnitude of trends is inconsistent with using M-K. M-K as noted above does not require data to be normally distributed but linear regression does or outliers can adversely afftect the results especially if these outliers are at the beginning or end of the time series. If linear regression is to be used normality (as well as autocorrelation) need to be checked. If the authors have not done this already it needs to be tested. If the data are not normally distributed there are other statistical tests available to determine the trend (e.g., Yue et al. 2002).

Author Response

Please refer to the attachment for revision instructions.

Author Response File: Author Response.docx

Reviewer 2 Report

See attached.

Comments for author File: Comments.pdf

Author Response

Please refer to the attachment for revision instructions.

Author Response File: Author Response.docx

Round 2

Reviewer 2 Report

The authors have done a good job responding to comments. I now recommend the paper for publication.

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