Google Earth Engine as Multi-Sensor Open-Source Tool for Monitoring Stream Flow in the Transboundary River Basin: Doosti River Dam

Round 1

Reviewer 1 Report

While the paper is interesting and could be useful for people focused on studying this region, there are several concerns. First, there is no validation performed on any of the remote sensing techniques. I understand that remote sensing can be used to alleviate the lack of in situ measurements, but it must be validated in order to assess the accuracy. My second concern is that there is an overall lack of citations to support the methods presented in the paper (e.g. lines: 97-98, 99-101, 278, 282-283). Third, I do not understand why the analysis begins in 2001 rather than 2004 when the dam was constructed. My main concern with this is that the trends shown in the analysis may be different or insignificant if the time-series is changed to 2004-2021. Finally, the p-values from the trend analyses seem misleading. For example, Figure 11C shows p-values where white and green pixels represent p-values of 0.25 and 0.5 which are not significant. Why not just make the figure display significant or not significant based on the p<0.05 threshold mentioned in the paper. The trend analyses plots could also benefit from including the p-value as they represent the entire area and I do not find any instance where there is a p-value for the entire region. In addition, many of the figures are difficult to understand as some lack panel labels, scale bars, or units. I think significant work needs to be done to support and validate the techniques presented here in order to truly assess the findings.

Author Response

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Author Response File: Author Response.pdf

Reviewer 2 Report

Understanding the effects of global change and human activities on water supplies depends greatly on surface water dynamics. Investigating a comprehensive examination of hydroclimatic variations at the transboundary level is essential for developing any adaptation or mitigation plans to deal with the negative effects of climate change. This topic is interesting and within the scope of this journal. However, the present version is difficult to follow. I would suggest the authors carefully polishing the language in the next revision round. The concerns should be addressed before publication.

(1)   The relevant studies that addressing the same question should be illustrated. There are so many tools have been used in monitoring streamflow series.

(2)   The Introduction section should be fully rewritten. It is very messy now. The storyline of this study should be presented in more clear way.

(3)   There are many grammar errors: e.g., L40.

(4)   The authors claimed that two meteorological stations are used, but Fig. 1 only present one station.

(5)   Monitoring streamflow in data-sparse regions is an important issue. How to use the developed method by using remote sensing data is also important, particularly in a changing world. The authors should discuss the main limitation and their future works. The following references are suggested.

Tofiq, F. A., & Guven, A. (2015). Potential changes in inflow design flood under future climate projections for darbandikhan dam. Journal of Hydrology, 528, 45-51. https://doi.org/10.1016/j.jhydrol.2015.06.023

Yin, J., et al. Blending multi-satellite, atmospheric reanalysis and gauge precipitation products to facilitate hydrological modelling. Journal of Hydrology, 593. https://doi.org/10.1016/j.jhydrol.2020.125878

Alfieri, L., Bisselink, B., Dottori, F., Naumann, G., de Roo, A., Salamon, P., Wyser, K., & Feyen, L. (2017). Global projections of river flood risk in a warmer world. Earth's Future, 5(2), 171-182. https://doi.org/10.1002/2016ef000485

Yin J, Guo S, Yang Y, Chen J, Gu L, Wang J, He S, Wu B, Xiong J. 2022. Projection of droughts and their socioeconomic exposures based on terrestrial water storage anomaly over China. Science China Earth Sciences, 65, https://doi.org/10.1007/s11430-021-9927-x

(6)   Last, the writing quality should be improved.

Author Response

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Author Response File: Author Response.pdf

Reviewer 3 Report

Reviewer’s Report on the manuscript entitled:

Google Earth Engine as multi-sensor open-source tool for monitoring stream flow in the transboundary river basin: Doosti River Dam

The authors investigated the hydro-climatic factors that contribute to the desiccation of Doosti dam’s basin in the transboundary area using the multi-sensors satellite data through Google Earth Engine (GEE) platform. The topic and results are generally interesting. However, the presentation and figure quality must be improved and some statistical correlation tests (e.g., Pearson’s correlation) need to be reported. Please see below my comments below.

Line 19. Please mention you used Landsat and MODIS here and/or put them in the keywords.

Line 58. Please also include this article that combines satellite data obtained from GEE to monitor water surface dynamics using QGIS and discusses the challenges in detail:

https://doi.org/10.1109/JSTARS.2022.3196611

Line 84. Please also include the article above after Synthetic Aperture Radar as it also uses Sentinel-1 SAR to fuse with Landsat for water surface monitoring. Also, include here the following article: https://doi.org/10.3390/w14121902

Main concern. The figure quality must be improved, particularly Figure 1. Please see the article above as an example of how this can be improved. The font size must be enlarged. The study region must be highlighted in Iran’s map. The latitude and longitude should be expressed in terms of degrees, the size and clarity of scale bar and legends, etc. Also, highlight where the reservoir is the basin, so Figure 3 will make more sense.

Section 2.3 is general and so 2.4, 2.5, and 2.6 can be their subsections. Ideally, you need to structure the manuscript as 2.1 Study region 2.2 Data sets 2.3 Methods. Now in section 2.2 you can divide it into two parts. 2.2.1 Ground measurements and 2.2.2 Satellite data. There is no need to create any other subsections just use Table 3 and briefly describe the data, so that the reader does not get lost with mostly known stuff. 2.3.1 Mann-Kendall… .2.3.2 Descriptive statistics

Climate and hydrological time series often show seasonal cycles and so Mann-Kendall is not recommended (i.e., the seasonality needs to be removed first). Season-trend fit models like Antileakage Least-Squares Spectral Analysis or LASSO, etc. are preferred. You used Mann-Kendall test. Thus, I suggest the authors discuss the limitations of this method in the Discussion section. Are Mann-Kendall and Sen’s slope applied to annual-scale time series (one datapoint per year) or daily or monthly time series? Please clarify this clearly. Seasonality is not present in annual-scale time series and so Mann-Kendall test is OK.  Please discuss these.

Equations (6)-(9) could be written better and more clear.

Line 249, 260, 265, etc. All the links should move to the references and mention: “last accessed on month/day/year” and simply cite them in the text like other references.

Lines 401,405, etc. I understand that the data is provided in K, but I suggest converting them to Celsius everywhere in the manuscript for easier understanding of the values.

Figures 6,8,10. In the last empty panel (southeast panel), please add a map that is the average of maps for 2001 to 2021 (i.e., the average map of other panels). Also, please improve the quality of the maps.

Please also show the Pearson correlation graphs for temperature, precipitation, water, etc.

Thank you!

Regards,

Author Response

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Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

I am happy with the revised version. It can be accepted!

Author Response

Please see the attachment. It is undoubtedly our honour that you accept our final revision.

Author Response File: Author Response.pdf

Reviewer 3 Report

I would like to thank the authors for addressing most of my comments. I still have some commends listed below:

Lines 576-577. Please add appropriate references for these methods.

Lines 182 and 198. Figure 3 should come before Figure 2. The order of Figures should be increasing in the manuscript: Figure 1,2,3,4...

Figure 7. Please express LST in Celsius not Kelvin. Please check everywhere and correct accordingly.

Figure 13(b) and 14(b). please insert the unit (mm) for Annual rainfall in the legend. The figures are not recommended to have border lines.

Use only past verbs in  Conclusions:

Line 606. The study showed...    It demonstrated.... largely relied on ... did not have a remarkable...

Line 612.... was focused... responded... was employed... MODIS indicated...etc.

The format and style of ALL the references must be according to the MDPI guidelines. Please add volume, page numbers or doi for all the references. Please write the authors last name followed by first letters of their first names, etc. See the MDPI guidelines.

Finally this manuscript must be very carefully proofread before publication.

Author Response

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Author Response File: Author Response.pdf