the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 31 Jul 2024
A subgrid method for the linear inertial equations of a compound flood model
Abstract. Accurate flood risk assessments and early warning systems are needed to protect and prepare people in coastal areas from storms. In order to provide this information efficiently and on time, computational costs need to be kept as low as possible. Reduced-complexity models using linear inertial equations and subgrid approaches have been used previously to achieve this goal. In this paper, for the first time, we developed a subgrid approach for the Linear Inertial Equations (LIE) that account for bed level and friction variations. We implemented this method in the SFINCS model. Pre-processed lookup tables that correlate water levels with hydrodynamic quantities make more precise simulations with lower computational costs possible. These subgrid corrections have undergone validation through a variety of conceptual and real-world application scenarios, including analyses of hurricane hazards and tidal fluctuations. We demonstrate that the subgrid corrections for Linear Inertial Equations significantly improve model accuracy while utilizing the same resolution without subgrid corrections. Moreover, coarser model resolutions with subgrid corrections can provide the same accuracy as finer resolutions without subgrid corrections. Limitations are discussed, for example, when grids do not adequately resolve river meanders, fluxes can be overestimated. Our findings show that subgrid corrections are an invaluable asset for hydrodynamic modelers striving to achieve a balance between accuracy and efficiency.
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Notice on discussion status
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Preprint
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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- Final revised paper
Journal article(s) based on this preprint
Accurate flood risk assessments are crucial for storm protection. To achieve efficiency, computational costs must be minimized. This paper introduces a novel subgrid approach for linear inertial equations (LIEs) with bed level and friction variations, implemented in the Super-Fast INundation of CoastS (SFINCS) model. Pre-processed lookup tables enhance simulation precision with lower costs. Validations show significant accuracy improvement even at coarser resolutions.
Interactive discussion
Status: closed
-
CEC1: 'Comment on egusphere-2024-1839', Astrid Kerkweg, 05 Aug 2024
Dear authors,
in my role as Executive editor of GMD, I would like to bring to your attention our Editorial version 1.2: https://www.geosci-model-dev.net/12/2215/2019/
This highlights some requirements of papers published in GMD, which is also available on the GMD website in the ‘Manuscript Types’ section: http://www.geoscientific-model-development.net/submission/manuscript_types.html
In particular, please note that for your paper, the following requirements have not been met in the Discussions paper:
- "The main paper must give the model name and version number (or other unique identifier) in the title."
- “If the model development relates to a single model then the model name and the version number must be included in the title of the paper. If the main intention of an article is to make a general (i.e. model independent) statement about the usefulness of a new development, but the usefulness is shown with the help of one specific model, the model name and version number must be stated in the title. The title could have a form such as, “Title outlining amazing generic advance: a case study with Model XXX (version Y)”.''
As you implemented your method into the SFINCS model, please add something like “a case study using SFINCS version x.y” to the title of your manuscript in your revised submission to GMD.
Yours, Astrid Kerkweg
Citation: https://doi.org/10.5194/egusphere-2024-1839-CEC1 -
AC3: 'Reply on CEC1', Nederhoff Kees, 04 Nov 2024
We want to thank the Executive Editor for pointing this out. In the revised manuscript, we changed the title and included the model's name and version number (Line 2)
Citation: https://doi.org/10.5194/egusphere-2024-1839-AC3
-
RC1: 'Comment on egusphere-2024-1839', Anonymous Referee #1, 23 Aug 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1839/egusphere-2024-1839-RC1-supplement.pdf
- AC1: 'Reply on RC1', Nederhoff Kees, 04 Nov 2024
-
CC1: 'Comment on egusphere-2024-1839', Jingming Hou, 27 Aug 2024
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.Citation: https://doi.org/10.5194/egusphere-2024-1839-CC1 - AC4: 'Reply on CC1', Nederhoff Kees, 04 Nov 2024
-
CC2: 'Comment on egusphere-2024-1839', Jingming Hou, 27 Aug 2024
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.Citation: https://doi.org/10.5194/egusphere-2024-1839-CC2 - AC5: 'Reply on CC2', Nederhoff Kees, 04 Nov 2024
-
RC2: 'Comment on egusphere-2024-1839', Anonymous Referee #2, 10 Sep 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1839/egusphere-2024-1839-RC2-supplement.pdf
- AC2: 'Reply on RC2', Nederhoff Kees, 04 Nov 2024
Interactive discussion
Status: closed
-
CEC1: 'Comment on egusphere-2024-1839', Astrid Kerkweg, 05 Aug 2024
Dear authors,
in my role as Executive editor of GMD, I would like to bring to your attention our Editorial version 1.2: https://www.geosci-model-dev.net/12/2215/2019/
This highlights some requirements of papers published in GMD, which is also available on the GMD website in the ‘Manuscript Types’ section: http://www.geoscientific-model-development.net/submission/manuscript_types.html
In particular, please note that for your paper, the following requirements have not been met in the Discussions paper:
- "The main paper must give the model name and version number (or other unique identifier) in the title."
- “If the model development relates to a single model then the model name and the version number must be included in the title of the paper. If the main intention of an article is to make a general (i.e. model independent) statement about the usefulness of a new development, but the usefulness is shown with the help of one specific model, the model name and version number must be stated in the title. The title could have a form such as, “Title outlining amazing generic advance: a case study with Model XXX (version Y)”.''
As you implemented your method into the SFINCS model, please add something like “a case study using SFINCS version x.y” to the title of your manuscript in your revised submission to GMD.
Yours, Astrid Kerkweg
Citation: https://doi.org/10.5194/egusphere-2024-1839-CEC1 -
AC3: 'Reply on CEC1', Nederhoff Kees, 04 Nov 2024
We want to thank the Executive Editor for pointing this out. In the revised manuscript, we changed the title and included the model's name and version number (Line 2)
Citation: https://doi.org/10.5194/egusphere-2024-1839-AC3
-
RC1: 'Comment on egusphere-2024-1839', Anonymous Referee #1, 23 Aug 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1839/egusphere-2024-1839-RC1-supplement.pdf
- AC1: 'Reply on RC1', Nederhoff Kees, 04 Nov 2024
-
CC1: 'Comment on egusphere-2024-1839', Jingming Hou, 27 Aug 2024
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.Citation: https://doi.org/10.5194/egusphere-2024-1839-CC1 - AC4: 'Reply on CC1', Nederhoff Kees, 04 Nov 2024
-
CC2: 'Comment on egusphere-2024-1839', Jingming Hou, 27 Aug 2024
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.Citation: https://doi.org/10.5194/egusphere-2024-1839-CC2 - AC5: 'Reply on CC2', Nederhoff Kees, 04 Nov 2024
-
RC2: 'Comment on egusphere-2024-1839', Anonymous Referee #2, 10 Sep 2024
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-1839/egusphere-2024-1839-RC2-supplement.pdf
- AC2: 'Reply on RC2', Nederhoff Kees, 04 Nov 2024
Peer review completion
Journal article(s) based on this preprint
Accurate flood risk assessments are crucial for storm protection. To achieve efficiency, computational costs must be minimized. This paper introduces a novel subgrid approach for linear inertial equations (LIEs) with bed level and friction variations, implemented in the Super-Fast INundation of CoastS (SFINCS) model. Pre-processed lookup tables enhance simulation precision with lower costs. Validations show significant accuracy improvement even at coarser resolutions.
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Cited
1 citations as recorded by crossref.
Maarten van Ormondt
Tim Leijnse
Roel de Goede
Kees Nederhoff
Ap van Dongeren
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
- Preprint
(2163 KB) - Metadata XML
Accurate flood risk assessments are crucial for storm protection. To achieve efficiency, computational costs must be minimized. This paper introduces a novel subgrid approach for Linear Inertial Equations (LIE) with bed level and friction variations, implemented in the SFINCS model. Pre-processed lookup tables enhance simulation precision with lower costs. Validations show significant accuracy improvement, even at coarser resolutions.
Accurate flood risk assessments are crucial for storm protection. To achieve...