Evaluation of Satellite Images and Products for the Estimation of Regional Reference Crop Evapotranspiration in a Valley of the Ecuadorian Andes
Round 1
Reviewer 1 Report
Review of “Evaluation of satellite images and products for the estimation of reference crop evapotranspiration in a valley of the Ecuadorian Andes”
Journal: Remote Sensing
Manuscript Number: remotesensing-1851033
Author: Fernando Oñate-Valdivieso, Arianna Oñate-Paladines and Deiber Núñez
The study is interesting to compare between different satellite products (LANDSAT 8, ASTER, SENTINEL 3 and MODIS) and were successfully applied to determine parameters and calculate ETo. The topic and the current condition of the manuscript is well suited to be published in the Remote sensing journal.
However, if its possible to add and relate the different ETo results from multiple sources with the climate variations and land use land cover changes of the study area, then it would increase its impact over the scientific community and more worthy to read the impact of different satellite sensors over the current climatic problems at hand.
Comments for author File: 
Comments.pdf
Author Response
Response to Reviewer 1 Comments
Dear Reviewer:
Thank you for your letter and for the comments concerning our manuscript entitled “Evaluation of satellite images and products for the estimation of regional reference crop evapotranspiration in a valley of the Ecuadorian Andes”. These comments are all valuable and very helpful for revising and improving our article, as well as the important guiding significance for our researches. We have studied comments carefully and have made correction which we hope meet with approval. The revised portions are marked on red in the paper. The main corrections in the paper and the responses to the reviewer’s comments are as follows.
Overview
Review of “Evaluation of satellite images and products for the estimation of reference crop evapotranspiration in a valley of the Ecuadorian Andes”
Journal: Remote Sensing
Manuscript Number: remotesensing-1851033
Author: Fernando Oñate-Valdivieso, Arianna Oñate-Paladines and Deiber Núñez
The study is interesting to compare between different satellite products (LANDSAT 8, ASTER, SENTINEL 3 and MODIS) and were successfully applied to determine parameters and calculate ETo. The topic and the current condition of the manuscript is well suited to be published in the Remote sensing journal.
Thank you to the reviewer for taking their time to review our paper.
Point 1. However, if its possible to add and relate the different ETo results from multiple sources with the climate variations and land use land cover changes of the study area, then it would increase its impact over the scientific community and more worthy to read the impact of different satellite sensors over the current climatic problems at hand.
Response 1: We greatly appreciate the suggestion, we consider that it is a research topic that could be of great interest. The study of climatic variations and the multi-temporal change of land use are means to understand the implications that climate change could have in a given territory, define possible scenarios and outline adaptation actions. Despite its importance, the suggested approach exceeds the scope proposed for our study, since it would require a multi-temporal analysis of the ETo using the different sensors, also studying the real ET, so we cannot accept the suggestion, we apologize in advance. Due to its importance, we consider studying it in a future work.
We appreciate for Reviewer’s warm work earnestly, and hope that the correction will meet with approval.
Once again, thank you very much for your comments and suggestions.
Thank you and best wishes. Yours sincerely,
Fernando Oñate-Valdivieso
Email: [email protected]
Author Response File: 
Author Response.docx
Reviewer 2 Report
see the file
Comments for author File: Comments.pdf
Author Response
Response to Reviewer 2 Comments
Dear Reviewer:
Thank you for your letter and for the comments concerning our manuscript entitled “Evaluation of satellite images and products for the estimation of regional reference crop evapotranspiration in a valley of the Ecuadorian Andes”. These comments are all valuable and very helpful for revising and improving our article, as well as the important guiding significance for our researches. We have studied comments carefully and have made correction which we hope meet with approval. The revised portions are marked on red in the paper. The main corrections in the paper and the responses to the reviewer’s comments are as follows.
Overview
I have reviewed the manuscript Number: remotesensing-1851033, “Evaluation of satellite images and products for the estimation of reference crop evapotranspiration in a valley of the Ecuadorian Andes” by F. Oñate-Valdivieso et al.
Analysis
In this article the Authors compare the reference crop evapotranspiration (RCE) estimation performance by remote sensors with great spatial detail and sensors with greater temporal detail, using as reference values the RCE estimates obtained from ground sensors. For this purpose they refer to data reported in a study area located in the province of Loja (Ecuador).
No new methods of estimating the RCE are proposed. Reference is made to the daily RCE only. The comparison stations are only 5. The days taken into consideration are a total of about fifteen. Nonetheless, the potential results of these analyzes promise interesting application results.
Thank you to the reviewer for taking their time to review our paper.
Major comments:
Since there are no real methodological innovations, it is necessary to evaluate the quality of the presentation of the case study.
Essentially, little information is reported on the quality of the results presented:
Point 1. With which techniques was the regionalization carried out (lines86,176,181,...)?
Response 1: An explanatory paragraph was included in the lines 186 - 202
Point 2. Regional estimates are affected by uncertainty and this uncertainty varies from point to point, varies according to the instrument used, from one day to the next: has the regression between these estimates and the values measured on the ground taken into account the different uncertainties?
Response 2: To reduce uncertainty as much as possible, data recorded through a network of 5 Davis Vantage Pro weather stations was used. These stations are identical in terms of their sensors, which were calibrated based on a standard weather station from the National Institute of Meteorology and Hydrology of Ecuador (INAMHI).
Point 3. Many of the figures shown (fig-2-5) want to show the great variability of values, but if there are no elaborations on this information they can also be eliminated. My suggestion is to replace these figures by integrating table 4 and showing not only global adaptation indicators, but also the variances of the different estimates (in the different sites, in the different days, ...).
Response 3 Figures 2 – 5 present the spatial variability of the parameters determined by remote sensing products.
Table 5 has been included, which contains the values determined by means of the products obtained by remote sensing, and Table 6, which includes the values of the differences between the values of the table in Table 4 and Table 5, as well as the values of the deviation typical by date, site and sensor.
A paragraph was added to discuss the results of Table 5 (lines 263 - 269) and another paragraph to discuss the results of Table 6 (lines 275-287)
Point 4. The Authors should expand the section relating to the commenting on the results
Response 4: Section 3. Results and Discussion was included.
We appreciate for Reviewer’s warm work earnestly, and hope that the correction will meet with approval.
Once again, thank you very much for your comments and suggestions.
Thank you and best wishes. Yours sincerely,
Fernando Oñate-Valdivieso
Email: [email protected]
Author Response File: Author Response.docx
Reviewer 3 Report
In this manuscript, the author combined remote sensing-based data and meteorological data to estimate ETo; however, it is a work with minimal significance. As the reference to evapotranspiration, ETo is always used for ET calculation or to characterize the evaporative status in the angle of meteorology. The PM method is a more accurate ETo estimation method. Still, its disadvantage is that it requires more meteorological data, and it isn't easy to collect all the necessary meteorological data on a large scale. In this paper, the authors attempt to use remote sensing products to obtain large-scale meteorological data to estimate regional ETo. However, the meteorological indicators mentioned in the article that can be calculated using remote sensing products are limited to Ts, Ta, and Rn. In contrast, the critical meteorological data such as Vapor pressure, relative humidity, and wind speed appear to be provided using regional interpolation results of several weather station data, which is not consistent with the original intention of the manuscript. For another, in terms of ET calculation, the RS-based and meteorological data in this study can be entirely and directly used for ET calculation, for example, using energy balance or the P-M method (MOD16 algorithm).
Moreover, the manuscript missed many steps for the ETo calculation. Regarding characterizing the evaporative status, the method of using RS data is more like upscaling the spatial scale from point (site observed) to distributed regional scale. In terms of the writing, there were also many problems, e.g., inconsistent terms (ETo and ET0 were all in the text) and varying font size of the equation.
1. The manuscript's topic is reference ET (ETo), but the introduction is all about ET, and the relationship between ET and ETo has not even been explained; the introduction of ET was also not clear and detailed.
2. Table 1, the spatial resolution of Landsat 8 TIR band is 100m.
3. Table 2, The height of the site observations should be clarified.
4. Eq. 3, "x" should be "×," and what does the ρ indicate?
5. Line 142, what does the "y" mean?
6. Line 148, should the equation for Ts calculation be Eq. 2?
7. Line 146, The multiple regression equation for Ta calculation should be clarified in detail; it is a crucial step for ETo calculation.
8. Line 146, Ninyerola [38] used altitude (ALT), latitude (LAT), continentality (CON), solar radiation (RAD), and a cloudiness factor (CLO) for multiple regression, not only Ts and DEM.
9. Eq. 7, line 163, how to obtain the spatial distributed Rsd, Rl? Energy flux obtained from remote sensing is all instantaneous. Moreover, how to get the spatial distributed daily wind speed of 2 m height and relative humidity for ET0 calculation from RS?
10. How to obtain the albedo from Landsat?
11. What does the "Cd" mean, and reference should be cited here to clarify the Eq. 8 source.
12. How to conduct the cross-validation here? The ETo was calculated using P-M, which does not need to be trained.
13. Line 235, "…which can be attributed to their good spatial resolution"; however, Aster has an even better spatial resolution.
14. A scatter plot is better to present here in terms of accuracy validation.
15. Even one sentence of Discussion was not found in the manuscript.
Author Response
Response to Reviewer 3 Comments
Dear Reviewer:
Thank you for your letter and for the comments concerning our manuscript entitled “Evaluation of satellite images and products for the estimation of regional reference crop evapotranspiration in a valley of the Ecuadorian Andes”. These comments are all valuable and very helpful for revising and improving our article, as well as the important guiding significance for our researches. We have studied comments carefully and have made correction which we hope meet with approval. The revised portions are marked on red in the paper. The main corrections in the paper and the responses to the reviewer’s comments are as follows.
Overview
In this manuscript, the author combined remote sensing-based data and meteorological data to estimate ETo; however, it is a work with minimal significance. As the reference to evapotranspiration, ETo is always used for ET calculation or to characterize the evaporative status in the angle of meteorology. The PM method is a more accurate ETo estimation method. Still, its disadvantage is that it requires more meteorological data, and it isn't easy to collect all the necessary meteorological data on a large scale. In this paper, the authors attempt to use remote sensing products to obtain large-scale meteorological data to estimate regional ETo. However, the meteorological indicators mentioned in the article that can be calculated using remote sensing products are limited to Ts, Ta, and Rn. In contrast, the critical meteorological data such as Vapor pressure, relative humidity, and wind speed appear to be provided using regional interpolation results of several weather station data, which is not consistent with the original intention of the manuscript. For another, in terms of ET calculation, the RS-based and meteorological data in this study can be entirely and directly used for ET calculation, for example, using energy balance or the P-M method (MOD16 algorithm).
Moreover, the manuscript missed many steps for the ETo calculation. Regarding characterizing the evaporative status, the method of using RS data is more like upscaling the spatial scale from point (site observed) to distributed regional scale. In terms of the writing, there were also many problems, e.g., inconsistent terms (ETo and ET0 were all in the text) and varying font size of the equation.
Thank you to the reviewer for taking their time to review our paper.
Point 1. The manuscript's topic is reference ET (ETo), but the introduction is all about ET, and the relationship between ET and ETo has not even been explained; the introduction of ET was also not clear and detailed.
Response 1: The introduction has been improved with a greater emphasis on ETo
Point 2. Table 1, the spatial resolution of Landsat 8 TIR band is 100m.
Response 2: Table 1 has been corrected
Point 3. Table 2, The height of the site observations should be clarified.
Response 3: Table 2 has been modified
Point 4. Eq. 3, "x" should be "×," and what does the ρ indicate?
Response 4: The Eq. 3 has been removed and its content has been included in the description of the variables of Eq. 2.
Point 5. Line 142, what does the "y" mean?
Response 5: Line 142 has been corrected
Point 6. Line 148, should the equation for Ts calculation be Eq. 2?
Response 6: The equation number has been corrected
Point 7. Line 146, The multiple regression equation for Ta calculation should be clarified in detail; it is a crucial step for ETo calculation.
Response 7: Table 3 has been included in which the equations determined to calculate Ta are presented.
Point 8. Line 146, Ninyerola [38] used altitude (ALT), latitude (LAT), continentality (CON), solar radiation (RAD), and a cloudiness factor (CLO) for multiple regression, not only Ts and DEM.
Response 8: Ninyerola et al., attempt to develop an empirical and statistical procedure to forecast the mean maximum air temperature, mean air temperature, mean minimum air temperature and total precipitation (at monthly and annual timescales) in Catalonia (northeast Spain). This procedure is empirical because it uses data obtained from meteorological stations for building and for validating the model. This procedure is also statistical because it is based on a multiple regression analysis and its corresponding validation.
We apply the concept of Ninyerola et al., that is, determine the air temperature based on multiple regression equations, using the air temperature recorded at the weather stations and auxiliary variables (Ts and z). Latitude, continentality, solar radiation and cloudiness factor were not used because the study area is very small (58 km2) when compared to Catalonia (32000 km2) which is the study site of Ninyerola et al. Being a small inter-Andean valley, the variables used by Ninyerola et al. would have little variability, so the most influential were considered, such as soil temperature and elevation.
Point 9. Eq. 7, line 163, how to obtain the spatial distributed Rsd, Rl? Energy flux obtained from remote sensing is all instantaneous. Moreover, how to get the spatial distributed daily wind speed of 2 m height and relative humidity for ET0 calculation from RS?
Response 9: The values of Rs↓d and Rs↓i were determined based on the records of existing meteorological stations in the study area. The Rl↓d values were obtained with equation 9, in both cases the hour of image capture was used for the instantaneous values and the daily mean for the daily values.
Point 10. How to obtain the albedo from Landsat?
Response 10: The albedo was obtained by applying Eq. 8.
Point 11. What does the "Cd" mean, and reference should be cited here to clarify the Eq. 8 source.
Response 11: Cd represents the ratio between the daily net radiation and the instantaneous net radiation. The requested reference has been included.
Point 12. How to conduct the cross-validation here? The ETo was calculated using P-M, which does not need to be trained.
Response 12: The procedure for carrying out the cross-evaluation is detailed in section 2.6.
Point 13. Line 235, "…which can be attributed to their good spatial resolution"; however, Aster has an even better spatial resolution.
Response 13: The paragraph has been corrected
Point 14. A scatter plot is better to present here in terms of accuracy validation.
Response 14: Figure 6 has been included in which the scatter plots are shown
Point 15. Even one sentence of Discussion was not found in the manuscript.
Response 15: Section 3. Results and Discussion was included.
We appreciate for Reviewer’s warm work earnestly, and hope that the correction will meet with approval.
Once again, thank you very much for your comments and suggestions.
Thank you and best wishes. Yours sincerely,
Fernando Oñate-Valdivieso
Email: [email protected]
Author Response File: Author Response.docx
Round 2
Reviewer 3 Report
The manuscript improved.
Author Response
Dear Reviewer 3:
Thank you for your letter and for the comments concerning our manuscript entitled “Evaluation of satellite images and products for the estimation of regional reference crop evapotranspiration in a valley of the Ecuadorian Andes”. These comments are all valuable and very helpful for revising and improving our article, as well as the important guiding significance for our researches. We have studied comments carefully and have made correction which we hope meet with approval. The revised portions are marked on red in the paper. Thank you and best wishes. Yours sincerely,
Fernando Oñate-Valdivieso
Email: [email protected]
