Estimation of Irrigation Water Use by Using Irrigation Signals from SMAP Soil Moisture Data
Round 1
Reviewer 1 Report
The manuscript (agriculture-2574258) emphasises the crucial importance of accurate irrigation water use data in agricultural water management. By utilising satellite remote sensing technology, it confronts challenges such as obscured ground cover and subjective decision-making in irrigation. Centreing on Henan Province and employing SMAP soil moisture data, the study refines estimation methodologies by considering false soil moisture signals. The results provide a more nuanced comprehension of irrigation water use, which is pivotal for regions where water is a rare commodity.
The sections on introduction, materials and methods, results, and discussion are well-presented. This is a typical survey work on irrigation areas. The writing is straightforward and effective. There is not much about the questioning concerning the data collection by researchers. It is a simple work, but publishable.
The grammatical structure is sound, as are the figures, which require minor corrections and adjustments. There's a need to standardise all the units throughout the text and in the figures. For example, change mm/day to mm day^−1.
L387. "Accor"?
Figure 6b's legend needs corrections!
Check minor grammar adjusts, and spelling in some extensive phrases.
Author Response
Response to Reviewer 1 Comments
The manuscript (agriculture-2574258) emphasises the crucial importance of accurate irrigation water use data in agricultural water management. By utilising satellite remote sensing technology, it confronts challenges such as obscured ground cover and subjective decision-making in irrigation. Centreing on Henan Province and employing SMAP soil moisture data, the study refines estimation methodologies by considering false soil moisture signals. The results provide a more nuanced comprehension of irrigation water use, which is pivotal for regions where water is a rare commodity.
The sections on introduction, materials and methods, results, and discussion are well-presented. This is a typical survey work on irrigation areas. The writing is straightforward and effective. There is not much about the questioning concerning the data collection by researchers. It is a simple work, but publishable.
We appreciate Reviewer 1’s effort in carefully reading our manuscript and providing us with very constructive comments.
In this paper, by identifying the irrigation signals in satellite microwave remote sensing of soil moisture, and constructing the model of estimating irrigation water use （SM2Rainfall Model）, the irrigation water use of Henan Province was estimated by using the irrigation signals in SMAP soil moisture data. According to the evaluation findings, the method proposed in this paper effectively improved the estimation accuracy of irrigation water use by using the irrigation signals in dryland.
The grammatical structure is sound, as are the figures, which require minor corrections and adjustments. There's a need to standardise all the units throughout the text and in the figures. For example, change mm/day to mm day^−1.
Response 1: Thanks for your constructive comments. All units in the text and figures have been rephrased.
L387. "Accor"?
Response 2: Thanks for your constructive comments. This sentence has been rephrased.
Figure 6b's legend needs corrections!
Response 3: Thanks for your constructive comments. The legend of Figure 6b has been corrected.
Reviewer 2 Report
The article with the title “Estimation of irrigation water use by using irrigation signals in SMAP soil moisture data” is interesting, and the scope deals with the agriculture journal particularly for the section (Digital Agriculture). The authors used SMAP (Soil Moisture Active Passive) soil moisture data to estimate irrigation water. However, there are some general issues that should be addressed:
a. The use data in 2016 and 2017. It should be clearly explained why the author chose those years. Is there any extraordinary event related to water use?
b. The term SMAP should be explained or defined in the Introduction. Probably many readers of Agriculture Journal are not familiar with the term.
c. The validation process should be added to the article. Since the authors used Satellite data, they should validate with ground data. Fig 10 is not representative of the validation process.
In addition, there are some minor’s issues that should also be addressed:
a. Abstract. The objective was not stated clearly enough in the abstract, introduction in this part is too long.
b. Introduction. There is no term of SMAP is stated in this part. So weird, because this is the main part of the article.
c. The objective is not clear in the Introduction part.
d. E(t) is surface evapotranspiration is not correct, it should be surface evaporation?
e. The equation of water balance should be revised, there should be ET(t)
Therefore, I think the article can be accepted after revision by addressing the issues.
Author Response
Response to Reviewer 2 Comments
The article with the title “Estimation of irrigation water use by using irrigation signals in SMAP soil moisture data” is interesting, and the scope deals with the agriculture journal particularly for the section (Digital Agriculture). The authors used SMAP (Soil Moisture Active Passive) soil moisture data to estimate irrigation water. However, there are some general issues that should be addressed:
We appreciate Reviewer 2’s effort in carefully reading our manuscript and providing us with very constructive comments.
- The use data in 2016 and 2017. It should be clearly explained why the author chose those years. Is there any extraordinary event related to water use?
Response 1: Thanks for your constructive comments.
Due to lack of statistical data for irrigation water use, we only estimate the irrigation water usage of 2016 and 2017 in dryland fields in Henan Province.
This sentence has been rephrased.
- The term SMAP should be explained or defined in the Introduction. Probably many readers of Agriculture Journal are not familiar with the term.
Response 2: Thanks for your constructive comments. This sentence has been rephrased.
- The validation process should be added to the article. Since the authors used Satellite data, they should validate with ground data. Fig 10 is not representative of the validation process.
Response 3: Thanks for your constructive comments.
Remote sensing precipitation data and satellite soil moisture data were used to determine and verify the model. No site data is used. This is also a shortcoming of this study, which is a direction of the follow-up research in this paper.
Therefore, in the follow-up study, the authors used validation data to verify the model. The results appear in a separate journal (Agriculture 2023, 13,757). This paper has been cited in present paper.
In addition, there are some minor’s issues that should also be addressed:
- Abstract. The objective was not stated clearly enough in the abstract, introduction in this part is too long.
Response 4: Thanks for your constructive comments. The Abstract has been rephrased.
- Introduction. There is no term of SMAP is stated in this part. So weird, because this is the main part of the article.
Response 5: Thanks for your constructive comments.The introduction already mentions SMAP.
- The objective is not clear in the Introduction part.
Response 6: Thanks for your constructive comments.
The objective of this this is to improve the estimation of irrigation water use in dryland. The objective has been rephrased.
- E(t) is surface evapotranspiration is not correct, it should be surface evaporation?
Response 7: Thanks for your constructive comments. This sentence has been rephrased.
- The equation of water balance should be revised, there should be ET(t)
Response 8: Thanks for your constructive comments. This sentence has been rephrased.
Therefore, I think the article can be accepted after revision by addressing the issues.
Author Response File: 
Author Response.pdf
Reviewer 3 Report
Material is very helpful and detailed. Everything is thoroughly explained and illustrated. Irrigation, fertilization, etc. models have their place in precision agriculture. The question of the efficient use of the water resource is important.
I have notes for the authors.
It is not specified what surface soil layer we are talking about. Each crop depletes soil moisture from a different soil horizon (depending on the depth of the root system), during the growing season this depth is a dynamic value, taking into account plant development.
Observations of the differences obtained by the two methods should be continued. Only two years of data is not representative enough in my opinion. I encourage the authors to continue their observations. Given the anomalies of the climate, conclusions can be drawn after observations carried out over a larger number of years.
The study is very important, but only large arrays are considered. It is not applicable to small areas - of what size?
Note - no literary source is cited in the conclusion!?!
Potential evapotranspiration is greater than maximum. Yes, it is. Scientifically proven. That's why there are formulas for the real and the potential evapotranspiration.
Author Response
Response to Reviewer 3 Comments
Material is very helpful and detailed. Everything is thoroughly explained and illustrated. Irrigation, fertilization, etc. models have their place in precision agriculture. The question of the efficient use of the water resource is important.
I have notes for the authors.
We appreciate Reviewer 3’s effort in carefully reading our manuscript and providing us with very constructive comments.
It is not specified what surface soil layer we are talking about. Each crop depletes soil moisture from a different soil horizon (depending on the depth of the root system), during the growing season this depth is a dynamic value, taking into account plant development.
Response 1: Thanks for your constructive comments. This study focuses on estimating irrigation water requirements for winter wheat. The root density of winter wheat in Henan Province is primarily concentrated in the 0-50cm soil layer, with the water consumption in the 0-20cm soil layer accounting for 40%-70% of the total water consumption. Therefore, studying the soil moisture in the 20cm soil layer can provide a direct reflection of the water absorption by winter wheat.
Observations of the differences obtained by the two methods should be continued. Only two years of data is not representative enough in my opinion. I encourage the authors to continue their observations. Given the anomalies of the climate, conclusions can be drawn after observations carried out over a larger number of years.
Response 2: Thanks for your constructive comments. In the following research, we will use more years of data for observation and analysis.
The study is very important, but only large arrays are considered. It is not applicable to small areas - of what size?
Response 3: Thanks for your constructive comments. This study primarily applies to the estimation of irrigation water requirements for dryland agriculture in large regional areas. Research at the field scale is mainly focused on small-scale studies.
Note - no literary source is cited in the conclusion!?!
Response 4: Thanks for your constructive comments. The conclusion section has cited references.
Potential evapotranspiration is greater than maximum. Yes, it is. Scientifically proven. That's why there are formulas for the real and the potential evapotranspiration.
Response 5: Thanks for your constructive comments.
This study use potential evapotranspiration instead of actual evapotranspiration based on the assumption that the surface moisture is abundant after irrigation. We admit this assumption is rough. So in the follow-up study, we use actual evapotranspiration instead of potential evapotranspiration. The results appear in a separate journal (Agriculture 2023, 13,757).
Anyway, We appreciate Reviewer’s effort in carefully reading our manuscript and providing us with very constructive comments.
Round 2
Reviewer 2 Report
I think the revised article does not respond to all of my comments. The objective in the abstract is still not clear and it's different from the introduction
The conclusion is too long, it seems like a summary rather than a conclusion. The conclusion is to address all of the objectives.
So, I think it should be improved again.
Author Response
Response to Reviewer 2 Comments
We appreciate Reviewer 2’s effort in carefully reading our manuscript and providing us with very constructive comments in Round 2. Thank you very much.
I think the revised article does not respond to all of my comments. The objective in the abstract is still not clear and it's different from the introduction.
Response 1: Thanks for your constructive comments. The objective in the abstract has been rephrased.
“Therefore, the purpose of this study is to improve the estimation of irrigation water use in dryland by using irrigation signals in SMAP soil moisture data. ”
The conclusion is too long, it seems like a summary rather than a conclusion. The conclusion is to address all of the objectives.
So, I think it should be improved again.
Response 2: Thanks for your constructive comments. The conclusion has been rephrased.
This study aims to improve the estimation of irrigation water use in dryland by using irrigation signals in SMAP soil moisture data. The results of this study revealed that the irrigation water use calculated with irrigation signals in SMAP soil moisture data was smaller than the statistical irrigation water use. The calculated amount of irrigation water was 48% less in 2016 and 35% less in 2017 than the statistical data indicated. This is because small-scale irrigation (membership value low irrigation events) would be excluded in the recognition of irrigation signals. By contrast, the contrast method used in this study is not removed the noise in the satellite soil moisture data, resulting in a significantly higher result for irrigation water use compared to the statistical value. On the whole, the irrigation water use calculated with irrigation signals deviated less from the statistical data than those calculated by the compared method.
