General Overview:

The paper presents a novel approach integrating subgrid corrections into the SFINCS model to enhance the accuracy of flood simulations while reducing computational costs.  The study is well-motivated, considering the importance of accurate and efficient flood risk assessments, especially in coastal areas prone to compound flooding.  The methodology, results, and validation against both conceptual and real-world cases are robust and demonstrate the potential benefits of the proposed approach.

Major Comments:

1. Clarity of the Methodology:

The paper's description of the subgrid approach is detailed, but certain sections, particularly the mathematical derivations, may benefit from additional clarification or simplification.  Equations such as (7) and (11) are critical to the paper's argument but might be difficult for non-specialists to follow.  Including a more intuitive explanation or visual aids to complement these equations could make the content more accessible.

The discussion of the limitations of the method, particularly regarding the handling of unresolved meanders and flow-blocking features, should be expanded.  It is important to discuss how these issues might affect the model's performance in different real-world scenarios and suggest possible future research directions or improvements.

Validation and Case Studies:

The validation of the subgrid method using both conceptual and real-world cases is a strong point.  However, the selection of cases could be more diverse.  For instance, including a case study from a different geographical area or a different type of flooding (e.g., urban pluvial flooding in a densely populated area) could demonstrate the broader applicability of the method.

The performance metrics provided (e.g., RMSE, NSE) are appropriate, but a deeper statistical analysis comparing the subgrid approach to other established methods (beyond just the regular SFINCS model) could strengthen the paper’s claims.

Computational Efficiency:

The paper mentions that integrating subgrid corrections increases computational costs by 44 to 129%, which is significant.  A more detailed discussion on the trade-off between computational efficiency and accuracy would be beneficial.  For instance, providing guidance on when it might be preferable to use the subgrid method despite the increased cost would help practitioners.

Additionally, discussing how these computational costs compare to those of alternative models or approaches would provide readers with a better context for evaluating the subgrid method's efficiency.

Figures and Tables:

Figures 7 and 10, which illustrate the model results for the St. Johns River and Hurricane Harvey cases, are informative but could be enhanced by including additional comparative plots.  For example, showing the differences in predicted flood extents or water levels between the regular and subgrid models in a side-by-side comparison could provide a clearer visual demonstration of the subgrid method's benefits.

The tables summarizing the model's performance metrics (e.g., Table 1 and 2) are useful, but adding a column that explicitly shows the percentage improvement (or decline) in performance when using the subgrid method compared to the regular SFINCS model would help highlight the method's effectiveness.

Minor Comments:

1. Terminology:

Ensure consistency in the use of terminology throughout the manuscript.  For instance, terms like "subgrid corrections," "subgrid method," and "subgrid-enabled" should be clearly defined and used consistently to avoid confusion.

2.  Typographical Errors:

There are a few minor typographical errors in the manuscript.  For example, the equation numbering sometimes skips or duplicates, which can confuse the reader.  Ensure that all equations are numbered sequentially and referenced correctly in the text.

A thorough proofread to correct any such errors is recommended before resubmission.

3. Conclusion Section:

The conclusion effectively summarizes the paper's key findings, but it could be strengthened by adding a few sentences on the potential future applications of the subgrid method.  For example, discussing how this method could be adapted or expanded to other types of hydrodynamic models or different environmental conditions would provide a more forward-looking perspective.

Recommendation:

The paper presents significant advancements in hydrodynamic modeling, particularly in the efficient simulation of compound floods.  With the suggested revisions, particularly regarding the clarity of the methodology and the expansion of case studies, I believe the manuscript would make a valuable contribution to the field and recommend it for publication after minor revisions.

These comments should provide the authors with constructive feedback to refine their manuscript and address any potential concerns that might arise during peer review.

General Overview:

The paper presents a novel approach integrating subgrid corrections into the SFINCS model to enhance the accuracy of flood simulations while reducing computational costs.  The study is well-motivated, considering the importance of accurate and efficient flood risk assessments, especially in coastal areas prone to compound flooding.  The methodology, results, and validation against both conceptual and real-world cases are robust and demonstrate the potential benefits of the proposed approach.

Major Comments:

1. Clarity of the Methodology:

The paper's description of the subgrid approach is detailed, but certain sections, particularly the mathematical derivations, may benefit from additional clarification or simplification.  Equations such as (7) and (11) are critical to the paper's argument but might be difficult for non-specialists to follow.  Including a more intuitive explanation or visual aids to complement these equations could make the content more accessible.

The discussion of the limitations of the method, particularly regarding the handling of unresolved meanders and flow-blocking features, should be expanded.  It is important to discuss how these issues might affect the model's performance in different real-world scenarios and suggest possible future research directions or improvements.

Validation and Case Studies:

The validation of the subgrid method using both conceptual and real-world cases is a strong point.  However, the selection of cases could be more diverse.  For instance, including a case study from a different geographical area or a different type of flooding (e.g., urban pluvial flooding in a densely populated area) could demonstrate the broader applicability of the method.

The performance metrics provided (e.g., RMSE, NSE) are appropriate, but a deeper statistical analysis comparing the subgrid approach to other established methods (beyond just the regular SFINCS model) could strengthen the paper’s claims.

Computational Efficiency:

The paper mentions that integrating subgrid corrections increases computational costs by 44 to 129%, which is significant.  A more detailed discussion on the trade-off between computational efficiency and accuracy would be beneficial.  For instance, providing guidance on when it might be preferable to use the subgrid method despite the increased cost would help practitioners.

Additionally, discussing how these computational costs compare to those of alternative models or approaches would provide readers with a better context for evaluating the subgrid method's efficiency.

Figures and Tables:

Figures 7 and 10, which illustrate the model results for the St. Johns River and Hurricane Harvey cases, are informative but could be enhanced by including additional comparative plots.  For example, showing the differences in predicted flood extents or water levels between the regular and subgrid models in a side-by-side comparison could provide a clearer visual demonstration of the subgrid method's benefits.

The tables summarizing the model's performance metrics (e.g., Table 1 and 2) are useful, but adding a column that explicitly shows the percentage improvement (or decline) in performance when using the subgrid method compared to the regular SFINCS model would help highlight the method's effectiveness.

Minor Comments:

1. Terminology:

Ensure consistency in the use of terminology throughout the manuscript.  For instance, terms like "subgrid corrections," "subgrid method," and "subgrid-enabled" should be clearly defined and used consistently to avoid confusion.

2.  Typographical Errors:

There are a few minor typographical errors in the manuscript.  For example, the equation numbering sometimes skips or duplicates, which can confuse the reader.  Ensure that all equations are numbered sequentially and referenced correctly in the text.

A thorough proofread to correct any such errors is recommended before resubmission.

3. Conclusion Section:

The conclusion effectively summarizes the paper's key findings, but it could be strengthened by adding a few sentences on the potential future applications of the subgrid method.  For example, discussing how this method could be adapted or expanded to other types of hydrodynamic models or different environmental conditions would provide a more forward-looking perspective.

Recommendation:

The paper presents significant advancements in hydrodynamic modeling, particularly in the efficient simulation of compound floods.  With the suggested revisions, particularly regarding the clarity of the methodology and the expansion of case studies, I believe the manuscript would make a valuable contribution to the field and recommend it for publication after minor revisions.

These comments should provide the authors with constructive feedback to refine their manuscript and address any potential concerns that might arise during peer review.