Alternate Wetting and Drying Irrigated Rice Paddy Field Water Status Monitoring with ALOS-2 Three Components and IoT Sensors

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors The manuscript addresses a relevant and timely topic by integrating L-band polarimetric SAR data with IoT-based water level measurements to monitor alternate wetting and drying (AWD) irrigation practices in rice paddies. The study is based on real field data, uses physically interpretable scattering mechanisms, and has clear potential interest for the readership of Remote Sensing.
However, the manuscript requires major revision before it can be considered for publication. The main issues relate to English language quality, clarity and consistency of the methodological description, excessive repetition in the Results section, and overly strong or insufficiently cautious interpretations in the Discussion and Conclusions. Title, Highlights, and Keywords

• The title is generally appropriate but could be more concise and highlight the main methodological contribution (i.e., polarimetric decomposition).
• The highlights are informative but include some statements that are too strong (e.g., regarding carbon credit verification) given the scope of the results.
• The keywords would benefit from reordering and refinement. In particular, terms related to rice paddies, polarimetric SAR, and irrigation monitoring should be prioritized, while variables such as plant height and water level could be secondary.

Abstract

• The Abstract requires substantial revision for clarity and conciseness.
• Several sentences are long and grammatically incorrect, which obscures the main message.
• The objectives, methods, key results, and conclusions should be more clearly separated.
• Statements implying direct verification of methane emission reductions or carbon credits should be softened, as the study focuses on irrigation monitoring rather than direct emission measurements.

Introduction

• The Introduction provides relevant background on AWD irrigation, water use, and methane emissions, and cites appropriate literature.
• However, the section would benefit from improved structure and clearer writing.
• The objectives of the study should be explicitly and concisely stated at the end of the Introduction.
• Some sentences contain grammatical errors or unclear phrasing that should be revised to improve readability.

Materials and Methods

• The overall methodological framework is appropriate, but several descriptions require clarification and greater consistency.
• Inconsistencies in reported spatial resolution of the SAR data (e.g., 6 m vs. 25 m) should be resolved.
• The description of SAR preprocessing and backscatter calibration (conversion to sigma-naught) should be clarified and made more precise.
• The Random Forest classification approach is insufficiently described. Key details such as parameter settings, training and validation strategy, and feature selection should be provided.
• More technical detail on the IoT sensors (e.g., measurement uncertainty, temporal resolution, synchronization with satellite overpasses) would strengthen the methodological rigor.

Results

• The Results section presents valuable analyses but is excessively long and repetitive.
• Similar interpretations of Freeman–Durden scattering components are repeated across sites and dates; these could be substantially streamlined.
• Some correlation results are weak to moderate, yet are discussed in strong terms. The interpretation should better reflect the statistical strength of the relationships.
• Figures and tables are generally informative, but the number of figures could be reduced, and some captions could be made more concise.

Discussion

• The Discussion largely reiterates the Results and would benefit from deeper critical analysis.
• Comparisons with previous studies using SAR for irrigation or rice monitoring should be strengthened.
• The limitations of the approach, particularly the reduced sensitivity under dense canopy conditions during later growth stages, should be more explicitly acknowledged.
• Claims regarding large-scale implementation and applicability to carbon credit verification should be phrased more cautiously and aligned more closely with the presented evidence.

Conclusions

• The Conclusions summarize the study adequately but, in places, overstate the implications of the results.
• Statements related to policy applications and carbon credit systems should be tempered.
• Emphasis should be placed on the methodological contribution and the conditions under which the approach performs best.

English Language and Style

• The manuscript requires a thorough revision of the English language.
• Numerous grammatical errors, awkward constructions, and imprecise expressions reduce clarity throughout the text.
• A professional language edit by a fluent English speaker (Certified) is strongly recommended.

Author Response

The manuscript addresses a relevant and timely topic by integrating L-band polarimetric SAR data with IoT-based water level measurements to monitor alternate wetting and drying (AWD) irrigation practices in rice paddies. The study is based on real field data, uses physically interpretable scattering mechanisms, and has clear potential interest for the readership of Remote Sensing.
However, the manuscript requires major revision before it can be considered for publication. The main issues relate to English language quality, clarity and consistency of the methodological description, excessive repetition in the Results section, and overly strong or insufficiently cautious interpretations in the Discussion and Conclusions. Title, Highlights, and Keywords

• The title is generally appropriate but could be more concise and highlight the main methodological contribution (i.e., polarimetric decomposition).

Answer: revised and updated

• The highlights are informative but include some statements that are too strong (e.g., regarding carbon credit verification) given the scope of the results.

Answer: revised and updated

• The keywords would benefit from reordering and refinement. In particular, terms related to rice paddies, polarimetric SAR, and irrigation monitoring should be prioritized, while variables such as plant height and water level could be secondary.

Answer: revised and updated

Abstract

• The Abstract requires substantial revision for clarity and conciseness.

Answer: revised and updated

• Several sentences are long and grammatically incorrect, which obscures the main message.

Answer: reviewed carefully and try to updated

• The objectives, methods, key results, and conclusions should be more clearly separated.

Answer: reviewed carefully and try to updated

 

• Statements implying direct verification of methane emission reductions or carbon credits should be softened, as the study focuses on irrigation monitoring rather than direct emission measurements.

Answer: reviewed carefully and try to updated

 

Introduction

• The Introduction provides relevant background on AWD irrigation, water use, and methane emissions, and cites appropriate literature.
• However, the section would benefit from improved structure and clearer writing.
• The objectives of the study should be explicitly and concisely stated at the end of the Introduction.
• Some sentences contain grammatical errors or unclear phrasing that should be revised to improve readability.

Answer: reviewed carefully and try to updated

 

Materials and Methods

• The overall methodological framework is appropriate, but several descriptions require clarification and greater consistency.
• Inconsistencies in reported spatial resolution of the SAR data (e.g., 6 m vs. 25 m) should be resolved.
• The description of SAR preprocessing and backscatter calibration (conversion to sigma-naught) should be clarified and made more precise.
• The Random Forest classification approach is insufficiently described. Key details such as parameter settings, training and validation strategy, and feature selection should be provided.
• More technical detail on the IoT sensors (e.g., measurement uncertainty, temporal resolution, synchronization with satellite overpasses) would strengthen the methodological rigor.

Answer: reviewed carefully and try to updated

 

Results

• The Results section presents valuable analyses but is excessively long and repetitive.
• Similar interpretations of Freeman–Durden scattering components are repeated across sites and dates; these could be substantially streamlined.
• Some correlation results are weak to moderate, yet are discussed in strong terms. The interpretation should better reflect the statistical strength of the relationships.
• Figures and tables are generally informative, but the number of figures could be reduced, and some captions could be made more concise.

Answer: reviewed carefully and try to updated

 

Discussion

• The Discussion largely reiterates the Results and would benefit from deeper critical analysis.
• Comparisons with previous studies using SAR for irrigation or rice monitoring should be strengthened.
• The limitations of the approach, particularly the reduced sensitivity under dense canopy conditions during later growth stages, should be more explicitly acknowledged.
• Claims regarding large-scale implementation and applicability to carbon credit verification should be phrased more cautiously and aligned more closely with the presented evidence.

Answer: reviewed carefully and try to updated

 

Conclusions

• The Conclusions summarize the study adequately but, in places, overstate the implications of the results.
• Statements related to policy applications and carbon credit systems should be tempered.
• Emphasis should be placed on the methodological contribution and the conditions under which the approach performs best.

English Language and Style

• The manuscript requires a thorough revision of the English language.
• Numerous grammatical errors, awkward constructions, and imprecise expressions reduce clarity throughout the text.

Answer: reviewed carefully and try to updated

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

Daer Authors,

 

The manuscript presents an integrated approach combining ALOS‑2 PALSAR‑2 L‑band polarimetric SAR, IoT water‑level sensors, and field data to distinguish AWD and non‑AWD irrigation practices in rice paddies. The overall scientific contribution is meaningful and addresses an important gap in remote‑sensing‑based water‑management monitoring, particularly relevant for carbon‑credit MRV systems. The study is generally well‑organized; however, several aspects require improvement to meet the standards of clarity, coherence, and academic rigor expected in MDPI journals.

2. Major Comments

2.1. Strengthening the Introduction - Although the introduction includes an extensive overview of AWD, water use, and carbon‑credit relevance, it could benefit from:

• A clearer articulation of the specific research gap this study addresses.
• A more streamlined narrative that distinguishes between background information and the study’s motivation.
• Improved consistency in describing AWD practices and their technical implications.

2.2. Materials and Methods – Clarification and Reproducibility

The methodological workflow is generally comprehensive, yet several areas require clarification:

• Provide more detail on IoT sensor specifications, calibration, and uncertainties.
• Describe preprocessing parameters in SNAP (e.g., multilooking, filtering, terrain correction) more explicitly.
• Clarify the Random Forest classifier setup: number of trees, feature sets, validation strategy, software implementation, and hyperparameter choices.
• Improve figure readability (Figures 1–4) and ensure captions adequately describe the process.

2.3. Results – Statistical Analysis: The results are rich in detail but would benefit from:

• Clearer separation between descriptive and interpretive results.
• Improved visualization of correlation analyses and temporal patterns.
• Stronger justification of claims regarding phenological effects on signal attenuation, ideally supported by cited literature.

2.4. Figures and Tables - Several figures appear low‑resolution or have labels that are difficult to read. Please ensure:

• Higher resolution for Figures 5–9.
• Consistent color schemes across plots.
• All axes, legends, and labels are readable and adhere to MDPI formatting standards.

2.5. Discussion – Strengthen Critical Evaluation. The discussion could be further improved by:

• Providing a deeper comparison with recent remote‑sensing approaches for irrigation monitoring.
• Addressing limitations more transparently, including revisit time, sensor noise, small plot size variability, and model uncertainty.
• Refining the section on carbon‑credit applicability by referencing established MRV challenges and constraints.

Thank you in advance for having my recommendations into account to improve your work.

Kind regards,

Reviewer

 

Comments on the Quality of English Language

English Language and Clarity - The manuscript contains frequent grammatical errors, inconsistent phrasing, and numerous typographical issues (e.g., “it’s creating,” “backdrop,p,” “firld,” “turns out to be,” “isthe”). These issues affect the readability and scientific clarity of the text. A comprehensive English‑language revision is strongly recommended.

Author Response

• The manuscript presents an integrated approach combining ALOS‑2 PALSAR‑2 L‑band polarimetric SAR, IoT water‑level sensors, and field data to distinguish AWD and non‑AWD irrigation practices in rice paddies. The overall scientific contribution is meaningful and addresses an important gap in remote‑sensing‑based water‑management monitoring, particularly relevant for carbon‑credit MRV systems. The study is generally well‑organized; however, several aspects require improvement to meet the standards of clarity, coherence, and academic rigor expected in MDPI journals.

  2. Major Comments

  2.1. Strengthening the Introduction - Although the introduction includes an extensive overview of AWD, water use, and carbon‑credit relevance, it could benefit from:

  Answer: Revised according to the comments

  • Provide more detail on IoT sensor specifications, calibration, and uncertainties.
  • Describe preprocessing parameters in SNAP(e.g., multilooking, filtering, terrain correction) more explicitly.
  • Clarify the Random Forest classifier setup: number of trees, feature sets, validation strategy, software implementation, and hyperparameter choices.
  • Improve figure readability (Figures 1–4) and ensure captions adequately describe the process.

  Answers: Revised and updated

  2.3. Results – Statistical Analysis: The results are rich in detail but would benefit from:

  • Clearer separation between descriptiveand interpretive
  • Improved visualization of correlation analyses and temporal patterns.
  • Stronger justification of claims regarding phenological effects on signal attenuation, ideally supported by cited literature.

  Answer: Reviewed, updated and revised

  2.4. Figures and Tables - Several figures appear low‑resolution or have labels that are difficult to read. Please ensure:

  • Higher resolution for Figures 5–9.
  • Consistent color schemes across plots.
  • All axes, legends, and labels are readable and adhere to MDPI formatting standards.

  Answer: Updated some of them and also the high resolution figures are uploaded to the data respiratory at zonendo shared folder

  2.5. Discussion – Strengthen Critical Evaluation. The discussion could be further improved by:

  • Providing a deeper comparison with recent remote‑sensing approaches for irrigation monitoring.
  • Addressing limitations more transparently, including revisit time, sensor noise, small plot size variability, and model uncertainty.
  • Refining the section on carbon‑credit applicability by referencing established MRV challenges and constraints.

  Answer: Revised and updated

  Thank you in advance for having my recommendations into account to improve your work.

English Language and Clarity - The manuscript contains frequent grammatical errors, inconsistent phrasing, and numerous typographical issues (e.g., “it’s creating,” “backdrop,p,” “firld,” “turns out to be,” “isthe”). These issues affect the readability and scientific clarity of the text. A comprehensive English‑language revision is strongly recommended.

Answer: Updated

 

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript has improved compared with the previous version. In particular, the methodological framework is now clearer and the discussion more adequately acknowledges the limitations of the approach. The interpretation of the potential application for carbon credit monitoring has also been moderated, which is appreciated.

Nevertheless, the manuscript still requires further revision, especially regarding English language quality, clarity of some methodological aspects, and the structure of the Results section. Given the scope and standards of Remote Sensing, these issues should be addressed carefully.

Major Comments

1. English language and clarity

Although the manuscript has been revised, the English language still requires substantial improvement. Numerous sentences remain grammatically incorrect or awkwardly structured, which affects the readability of the paper.

Examples include issues such as incorrect phrasing, inconsistent terminology, and unclear expressions throughout the manuscript. A thorough language editing by a fluent English speaker or professional editing service is strongly recommended.

2. Spatial resolution inconsistency

There appears to be an inconsistency in the reported spatial resolution of the SAR data. In Section 2.2, the PALSAR-2 data are described as having a spatial resolution of 6 m, whereas later in the manuscript (e.g., in the accuracy assessment section) a 25 m spatial resolution is mentioned.

The authors should clearly explain:

• whether the data were resampled, multilooked, or aggregated prior to analysis,

• the effective spatial resolution used for the classification,

• and how this spatial resolution relates to the typical size of individual rice fields in the study area.

Clarifying this point is important for interpreting the classification accuracy and the relationship between SAR observations and field-level water measurements.

3. Random Forest description

The description of the Random Forest classification has improved but remains somewhat limited. For example, the manuscript indicates that 100 trees were used and that training samples were selected from field observations, but further details would help ensure methodological transparency.

The authors should clarify:

• how the training and validation datasets were separated,

• whether cross-validation was applied,

• how feature importance was evaluated (if applicable),

• and whether parameter tuning was performed.

4. Repetition in the Results section

The Results section remains relatively long and contains repeated interpretations across the three study sites. In several cases, similar explanations are repeated for Rosulpur, Sreemantapur, and Bhabicha.

The section could be improved by:

• synthesizing common patterns across sites,

• reducing repetitive text,

• focusing more clearly on the key differences between AWD and non-AWD irrigation regimes.

Streamlining the Results section would significantly improve readability.

5. Interpretation of correlations

The manuscript reports weak to moderate correlations between scattering components and water level. While this is acknowledged in the text, some interpretations still appear stronger than what the statistical results suggest.

The discussion should ensure that conclusions are fully consistent with the strength of the reported relationships.

Minor Comments

• Some terminology should be standardized (e.g., “phenological” instead of “phonological” when referring to crop development).

• Figure captions could be shortened and clarified to improve readability.

• A careful proofreading would likely identify additional minor grammatical issues.

Author Response

Major Comments

1. English language and clarity

Although the manuscript has been revised, the English language still requires substantial improvement. Spatial resolution inconsistency

2. There appears to be an inconsistency in the reported spatial resolution of the SAR data. In Section 2.2, the PALSAR-2 data are described as having a spatial resolution of 6 m, whereas later in the manuscript (e.g., in the accuracy assessment section) a 25 m spatial resolution is mentioned.

Ans: Carefully review the article, check and update the grammatical errors and language standard. Regarding the resolution issues, by fixing up 6 m

3. Random Forest description

The description of the Random Forest classification has improved but remains somewhat limited. For example, the manuscript indicates that 100 trees were used and that training samples were selected from field observations, but further details would help ensure methodological transparency.

The authors should clarify:

• how the training and validation datasets were separated,
• whether cross-validation was applied,
• how feature importance was evaluated (if applicable),
• and whether parameter tuning was performed.

Ans: Added details description of RF classification addressing the reviewer comments.

4. Repetition in the Results section

The Results section remains relatively long and contains repeated interpretations across the three study sites. In several cases, similar explanations are repeated for Rosulpur, Sreemantapur, and Bhabicha.

The section could be improved by:

• synthesizing common patterns across sites,
• reducing repetitive text,
• focusing more clearly on the key differences between AWD and non-AWD irrigation regimes.

Streamlining the Results section would significantly improve readability.

Ans: Revised the result section based on the comments and addressed the issues.

5. Interpretation of correlations

The manuscript reports weak to moderate correlations between scattering components and water level. While this is acknowledged in the text, some interpretations still appear stronger than what the statistical results suggest.

The discussion should ensure that conclusions are fully consistent with the strength of the reported relationships.

Ans: Simonized between interpretation and description to solve the issues

Minor Comments

• Some terminology should be standardized (e.g., “phenological” instead of “phonological” when referring to crop development).
• Figure captions could be shortened and clarified to improve readability.
• A careful proofreading would likely identify additional minor grammatical issues.

Ans: Carefully review the article, check and update the grammatical errors, and try to improve the language standard. Moreover, the figure quality updates by reducing the number.

 

Author Response File: Author Response.docx

Round 3

Reviewer 1 Report

Comments and Suggestions for Authors

The authors have made a substantial effort to address the previous comments, and the manuscript has clearly improved, particularly in the methodological description and the inclusion of limitations. Congratulations!

The clarification of the Random Forest model, the improved discussion of SAR scattering mechanisms, and the more cautious interpretation regarding carbon credit applications are appreciated.

However, several issues still need to be addressed before the manuscript can be accepted:

1. English language quality remains insufficient
   Although improved, the manuscript still contains numerous grammatical errors, awkward phrasing, and unclear sentences. A thorough professional language revision is strongly recommended.

2. Results section remains overly repetitive
   Similar interpretations of scattering mechanisms (SS, DB, VS) are repeated across sections. The text should be streamlined to improve clarity and readability.

3. Some interpretations are still too strong
   Certain statements should be further moderated (e.g., “strong evidence”, “reliable and scalable”), to better reflect the moderate correlations and methodological limitations.

4. Minor methodological clarifications
   Additional clarity on sensor calibration/uncertainty and synchronization with SAR acquisitions would further strengthen the manuscript.

Overall, the study is relevant and methodologically sound, but requires these final refinements to meet the journal’s standards.

Author Response

1. English language quality remains insufficient
   Although improved, the manuscript still contains numerous grammatical errors, awkward phrasing, and unclear sentences. A thorough professional language revision is strongly recommended.

Response: I have carefully reviewed the article thoroughly and tried to enrich the language quality. The changes made during the revision are marked in highlighted color.

2. Results section remains overly repetitive

Response: I have revised the result section, incorporating your comments and suggestions. Removed, replaced with direct references to preceding analysis, avoided the repetition, and highlighted the revised part for your kind consideration.

3. Some interpretations are still too strong
   Certain statements should be further moderated (e.g., “strong evidence”, “reliable and scalable”) to better reflect the moderate correlations and methodological limitations.

Response: Dear professor, I could understand your suggestion regarding the strong statements. Try to avoid them and replaced with comparatively/relatively/stronger words and highlighted with color.

4. Minor methodological clarifications
   Additional clarity on sensor calibration/uncertainty and synchronization with SAR acquisitions would further strengthen the manuscript.

Response: In methodological clarification regarding uncertainty and synchronization, I have tried to add sentences to compare with manual and IoT-based data uncertainty and accuracy.

 In the figure case,

1. Try to increase the quality of figures,
2. Added a figure (Figure-5) instead of table-4
3. Changes the figure 6 and 7
4. Figure-8 and figure-9 reduces from 9 figures to 3 figures
5. Changes the visualization of figure-10

Author Response File: Author Response.docx