Remotely Sensed Agriculture Drought Indices for Assessing the Impact on Cereal Yield

Round 1

Reviewer 1 Report

Dear Authors,

This study uses remote sensing data to compare selected drought indices, cereal yields, and cereal vegetative status for dryland and irrigated cereals. Four drought indices have been used: Soil moisture Anomaly Index, Vegetation Anomaly Index, Evapotranspiration Anomaly Index, and Inverse Temperature Anomaly Index. This study aims to find the relationship between these drought indices and cereal yields with the correlation between them.

In general, the subject is important and needs more research in terms of food security and agricultural aspects. Unfortunately, this paper seems limited in terms of explanation of the methodology and discussion, and I believe it should be accepted with major revisions and modifications. It could become a much better study with a more clearly defined methodology in terms of more explanation of the drought indices; each drought index must be explained, and the discussion must be in terms of the relation between the results and the physical condition and its relation to food security. I list out some main concerns and modifications below, and then the comments for the numbering lines.

1-    You mentioned “semi-arid area” in the title, but two study areas have been evaluated with dryland and irrigated cereal. Also, you used the “performance of remote sensing indices,” but you used the drought indices based on remote sensing data. I think you have to change the title.

2-     The introduction needs more information about the drought indices, soil moisture, etc. For example, the paragraph needs more explanations from Line 70 to Line 90.

3-    The methodology needs more clarification; each type of drought index must be explained more. Also, the physical characteristics of cereal must be mentioned.

4-    The drought indices have been calculated based on 11 years dataset. Prove that is enough.

5-    The discussion parts must include the

Line 46: “climate change show that more than 33 countries will suffer” which countries? It may be small countries. I recommend mentioning the population instead of 33 counties.

Line 71: In some cases, using satellites and remote sensing data provides denser distributed data, and in some cases, it gives less distributed data based on the distribution of the gridded data. This point must be mentioned in the introduction.

Line 72 – Line 90: Rewrite it again and make it more readable.

Line 95: It mainly depends on the soil moisture, not the soil moisture from satellite measurements.

Line 156: What is the location of this metrological station? Is this station a representative station for all the study area? If there is more than one station, please summarize all of them.

Line 165: “This area occupies the first rank in the production of cereals in Catalonia”, write a reference for this sentence.

Line 175: “The annual rainfall varies between 200 mm and less than 150 mm” The sentence is not clear, rewrite.

Line 162 + Line 179: Why did you mention the reference evapotranspiration? Is there any relation between it and the drought index? You mentioned that both rainfed and irrigated are available.

Figure 1: the figure is not readable; please modify it and separate each area alone with more features.

Line 138 + Line 201: LST (Land Surface Temperature): you mention this abbreviation without explaining it. Revise it, please.

Line 202: What do you mean by cereal maps?

Line 204:

Line 215: “methodology proposed by Zribi et al. [84] and validated by Chahbi et al. [85] “ At least you have to explain the main points for these methodologies.

Line 217: Which database has been used for NDVI values? Also, for each year you used a specific Landsat, I would recommend summarizing the formula, Landsat, band, and resolutions. All of them must be mentioned.

Line 222: “different agricultural years” mention these years.

Line 258: Remote sensing data: the whole paragraph needs more modifications like separating and numbering each piece of data. 1- Soil moisture 2- ETP 3- NDVI

Line 259: “SMOS” mention what is it: Soil Moisture and Ocean Salinity.

Line 262: “improvement of the SM spatial resolution from 40 km to 1 km has been used” needs more explanation.

Line 265: this method needs more explanation.

Line 272: “The algorithm of this product selects the best available pixel” Revise it.

Line 291: there are many types of Anomaly algorithms. Which one was used?

Line 292: each drought index must be explained more. This research focuses on these drought indices but not of them has been explained sufficiently.

Line 339: Need reference(s) for a statement that Pearson’s correlation analysis “is the most used correlation method to study the relative strength of the linear relationship between two variables.”

Line 345 to 353: STD is well-known. No need for this explanation. Actually, methodology and drought indices need more explanation than well-known std.

Drought characteristics like drought period must be identified in the methodology section. It differs based on the drought definition.

Line 360: 2014/2015: Why did you select this year as a case study? Does it have the maximum drought period?

Line 364 to 370: precipitation and temperature records have been determined. So, I recommend summarizing all these data in a table to make it more readable.

Figure 5: First, thank you for this map, with the same legend for all drought indices’ maps. But, the differences between drought indices for the same month must be discussed regarding soil moisture, ETP, and NDVI. The methodology, variables, and distribution functions must also explain this point.  

Figure 5: the maximum and minimum index was 2 and -2. Explain why?

Figure 7: needs more discussion.

Line 433: ETAI should be ITAI.

Line 433 and 434: “ITAI show the most delayed variations as can be observed at the end of 2011 and 2014”. This can not be observed in the figure. Maybe another symbol should be used to make this figure more readable.

Figure 8 with its discussion: the results were discussed without explaining the relation between the results and the methodology used. For example, for SMAI, there is an effect on the dataset records with its physical meaning.

Line 456: “shows a high correlation” needs a reference for high correlation. In other words, 0.7 cannot be a high correlation.

 Figure 9: The R-value for ITAI is 0.31, then you have to explain that physically not telling us that it is 0.31. The same point is for the R-value for EAI in June.

Line 534: identify the time delay.

Line 546 and 547: there is no relationship between the resolution and the result of soil moisture.

Line 548 and 549: “it is essential to consider different conditions and not rely on a single index” I agree that for each condition a specific drought index should be used. But the question is what is the best drought index for this situation which is not answered in this research. And sometimes, it is not applicable to find more than one drought index. 

Line 552: “from November to January” their months are rainy months. Why the soil moisture index is negative? What is the physical meaning of this situation.

Sincerely,

Minor editing of English language required

Author Response

Dear Reviewer,

We are sincerely grateful for the opportunity to resubmit a revised copy of our manuscript. We would like to express our heartfelt appreciation for the positive feedback and invaluable comments provided by you during the previous review process. Your guidance and suggestions have been instrumental in enhancing the quality of our work. We believe that these modifications have substantially strengthened and enriched the revised manuscript.

We hope you find the revised manuscript suitable for publication.

Yours sincerely
Manel Khlif
On behalf of the authors

Author Response File: Author Response.pdf

Reviewer 2 Report

It is an interesting study with an important scientific knowledge. The information in the abstract is clear and also the results of study.  The structure of manuscript is good. The manuscript describes an analysis about calorimetry generated from satellite images, however will interesting know as own plays the phenology time of each crops in the all indices, this can change the findings.  Still some questions, for example it´s possible add the evolution of precipitation and phenology to each crop during period of study regards in the dynamic of index. Also point out the irrigate periods or seasons to identify your influence in the index.  May be identify annual drought periods from the precipitation, by fittings of indices by seasons wet and dry for crops, could give other results to help the discussion of results.  In the Figs 11 and 12 the SMAI never reach values greater than 2, because it only shows dryness of the soil which does not show that it is a significant drought, this could be only a feedback from the evaporation of the superficial layer of the soil. For this is adequate aggregate the relationships VPD vs EAI including the others indices. Show the precipitation by year to compared with each year respect to the average rainfall of the period to identify the behavior of dry and wet years, to evaluate the performance of predictions.

 Although the topic is interesting the results are more important if give some values to level of drought in accord ranks of Soil Moisture Index Anomaly, also some graphics could be required to support the discussion of results, and distribution of levels cover canopy during each year because it affects the indices, as areas of foliated vegetation taking scale mixed in the work. 

Author Response

Dear Reviewer,

We are sincerely grateful for the opportunity to resubmit a revised copy of our manuscript. We would like to express our heartfelt appreciation for the positive feedback and invaluable comments provided by you during the previous review process. Your guidance and suggestions have been instrumental in enhancing the quality of our work. We believe that these modifications have substantially strengthened and enriched the revised manuscript.

We hope you find the revised manuscript suitable for publication.

Yours sincerely
Manel Khlif
On behalf of the authors

Author Response File: Author Response.pdf

Round 2

Reviewer 1 Report

Dear Authors,

Your response to my comments and the subsequent revisions have significantly improved the quality and clarity of the manuscript. The changes made have comprehensively addressed the concerns the reviewers raised, making it a valuable contribution to the Remote Sensing journal’s scope.

I recommend the publication in the Remote Sensing journal with minor revisions. I think the revised version of the manuscript should be accepted after adjusting the below-mentioned comments.

Line 29: “The obtained results highlight the importance of EAI and SMAI as 29 key indicators for the estimation and early estimation (respectively) of cereal yield.”

No need to write obtained. I think, “ The results highlights …” is better.

Line 42 – 48: This paragraph improves the introduction quality and addresses the negative impacts of drought on the agricultural sector.

Please revise the references within the manuscript. For example, in lines 100, 112, and 114, No need to mention Anderson et al.

Figure 1: Thank you for making it better. Please make the meteorological station symbol bigger.

Line 242: “of the previous year (yi-1)” In the PDF format, i – 1 is unclear. Revise it, please.

Line 340-344: Need a reference.

Line 348: “Penman” Need a reference of its equation.

Line 356: “The Table 1 below summarizes the used satellite database in this study” Delete The.

Line 382: “Vegetation Anomaly Index (VAI) and Evapotranspiration Anomaly Index (EAI)”

Separate them.

Sincerely,

Author Response

Dear Reviewer,

We would like to thank you for the opportunity to resubmit a revised version of this manuscript. We would also like to take this opportunity to express our sincere thanks for the very detailed comments and suggestions for both revisions. We believe this has helped to improve the revised manuscript. You will find attached a letter responding to your valuable comments.

We sincerely hope that the revised manuscript will be accepted for publication.
Yours sincerely
Manel Khlif
On behalf of the authors

Author Response File: Author Response.pdf