Numerical Simulation of Typical River Closure Process and Sensitivity Analysis of Influencing Factors

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

This manuscript focuses on the Head Bend section of the Yellow River in Inner Mongolia, China. It conducts numerical simulations and analyses of the processes of ice transport and accumulation during the winters of 2019–2020 and 2020–2021. The study revealed that low-discharge regimes favour stable freeze-up. It also shows that, of all the considered factors, discharge Q and ice concentration N are the variables that govern post-jam water-level rise the most sensitively. The topic has clear theoretical and practical value. The results are reliable, the analyses are thorough and the conclusions are well supported. Nevertheless, some minor revisions are required.

（1） The sources of hydrodynamic boundary and thermodynamic data used in the model should be explicitly stated.

（2）Figure 5 and Figure 6 have the same title but appear to depict the simulation results for two different winters. A more detailed description and clearer legend are needed.

（3） Figure 5 and Figure 6 only show the distribution of ice shapes at critical speeds of 0.25 m/s and 0.35 m/s, but not at 0.30 m/s and 0.40 m/s. It is recommended that the manuscript text be adjusted.

（4）The x-axis labels of Fig. 8(a) and 8(b) should be consistent.

（5）The meaning of W in Table 1 should be explained below the table.

Overall, the paper is well structured and reasonably presented. It is also methodologically sound and scientifically correct, in line with the interests of the [Hydrology] journal. 

Author Response

Response to reviewers’ and editor’s comments

 General comments by Reviewer 1

 This manuscript focuses on the Head Bend section of the Yellow River in Inner Mongolia, China. It conducts numerical simulations and analyses of the processes of ice transport and accumulation during the winters of 2019–2020 and 2020–2021. The study revealed that low-discharge regimes favour stable freeze-up. It also shows that, of all the considered factors, discharge Q and ice concentration N are the variables that govern post-jam water-level rise the most sensitively. The topic has clear theoretical and practical value. The results are reliable, the analyses are thorough and the conclusions are well supported. Nevertheless, some minor revisions are required.

 Specific comments by Reviewer 1

1. Question: The sources of hydrodynamic boundary and thermodynamic data used in the model should be explicitly stated.
   Response: The flow data in the study are derived from the measured daily discharges at the Toudaoguai hydrological station, while the water-level data come from records of gauges installed downstream. Air-temperature and ice concentration data were collected by the research team during field observation conducted in the winters of 2019—2020 and 2020—2021. The relevant descriptions have been highlighted in red in the revised manuscript..

2. Question: Figure 5 and Figure 6 have the same title but appear to depict the simulation results for two different winters. A more detailed description and clearer legend are needed.

Response: Thank you for your suggestion. The captions for Figures 5 and 6 in the original manuscript were unclear; Figure 5 shows the ice-covered channel morphology at different times during the 2019—2020 winter, and Figure 6 shows the same for the 2020—2021 winter. These captions have been revised in the updated manuscript. 

3. Question: Figure 9 and Figure 10 only show the distribution of ice shapes at critical speeds of 0.25 m/s and 0.35 m/s, but not at 0.30 m/s and 0.40 m/s. It is recommended that the manuscript text be adjusted..

 Response: Thank you for your suggestion. Figures 9 and 10 show the ice distribution at critical velocities of 0.25 m/s and 0.35 m/s, respectively; the corresponding wording has also been revised to ensure consistency with the results presented in the figures. 

4. Question: The x-axis labels of Fig. 8(a) and 8(b) should be consistent.

Response: Thank you for your suggestion. In the revised version, The axis titles in Figures 8(a) and 8(b) have been standardized. 

5. Question: The meaning of W in Table 1 should be explained below the table. 

Response: Thank you for your suggestion. The symbol W denotes wind speed; the physical meaning of the symbol W in Table 1 has been clarified in the revised version.

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript presents a two-dimensional coupled hydrodynamic–ice dynamic–thermodynamic numerical model to simulate river freeze-up and ice-jam formation in the Toudaoguai reach of the Yellow River during the winters of 2019–2020 and 2020–2021. Model outputs are validated against observed water levels and ice thickness, and a parameter sensitivity analysis is conducted to identify dominant controls on ice-jam backwater effects.
The study addresses a relevant applied problem in cold-region hydrology and ice-flood prevention. The modeling approach is physically grounded and the case study is appropriate. However, several aspects require clarification and strengthening before publication.
Prior to publication, some minor comments need to be addressed.

1)The manuscript presents valuable insights and contributions to the field. However, to enhance its impact, I suggest reducing claims of novelty in the modeling approach and instead emphasizing the engineering insights and decision-making relevance, as these aspects are particularly significant for practical applications and broader audience engagement.

2)Software/Programming Language Reference: It is important to include references to the software or programming language used for the simulations. Also, here are some additional comments on the modeling results and process:
a) Please clarify why boundary conditions for ice concentration, thickness, and upstream inflow ice flux are not fully quantified.
b) Please clarify whether ice concentration input is spatially uniform or sectional.
c) I would recommend adding quantitative validation metrics for water level and ice thickness.

3)Missing References: There are some missing references in the manuscript.
a) For example, the reason for the choice of ice floe size should be referenced (line 184), and further references are needed for the discussion on lines 205–208.
b) A few recent international river-ice modeling studies (post-2020) could be added.

4)Model Limitations and Future Studies: The visual agreement between simulated and observed results is good. However, it would be helpful to briefly discuss the limitations and weaknesses of the model, along with potential areas for improvement in future studies.
a) Add a short paragraph explicitly acknowledging limitations.
b) The sensitivity analysis yields reasonable and physically intuitive results, but the methodology should be presented more conservatively.
     i)The sensitivity analysis procedure resembles one-factor-at-a-time sensitivity         analysis, not classical Morris screening. Please revise.
c) Clarify the number and timing of observation points used.
d) Briefly discuss measurement uncertainty (especially ice thickness).

Author Response

Jan. 1 2026

Dear Editor and Reviewers:

Thank you for your letter and comments concerning our manuscript entitled “Numerical simulation of typical river closure process and sensitivity analysis of influencing factors” (Manuscript ID. hydrology-4071846). We have found your comments to be very valuable in revising and improving our paper, as well as an important guidance for our future research. We have studied your comments and recommendations carefully and we have made based on them revisions to our paper that we hope to meet your approval. As you will see when examining our revisions, the reviewers’ comments and recommendations have been considered seriously and thoroughly addressed in our revised paper. Please note: red is addition/modification.

We hope that this manuscript is now acceptable for publication in Hydrology.

 If you have any additional comments and/or concerns, please do not hesitate to contact us directly.

Sincerely,

 Lan Ma, Chao Li*, Zhanquan Yao*, And Xuefei Ji

General comments by Reviewer 2

 Question: The manuscript presents a two-dimensional coupled hydrodynamic–ice dynamic–thermodynamic numerical model to simulate river freeze-up and ice-jam formation in the Toudaoguai reach of the Yellow River during the winters of 2019–2020 and 2020–2021. Model outputs are validated against observed water levels and ice thickness, and a parameter sensitivity analysis is conducted to identify dominant controls on ice-jam backwater effects.

The study addresses a relevant applied problem in cold-region hydrology and ice-flood prevention. The modeling approach is physically grounded and the case study is appropriate. However, several aspects require clarification and strengthening before publication.

Prior to publication, some minor comments need to be addressed..

The manuscript presents valuable insights and contributions to the field. However, to enhance its impact, I suggest reducing claims of novelty in the modeling approach and instead emphasizing the engineering insights and decision-making relevance, as these aspects are particularly significant for practical applications and broader audience engagement..

Response: Thank you very much for your positive comments on the valuable insights and contributions. We have carefully considered your comments and suggestions and will make serious revisions below.

 Specific comments by Reviewer 2

1. Question: Software/Programming Language Reference: It is important to include references to the software or programming language used for the simulations.

Response: Thank you for your suggestion. The discretization and solution of the model governing equations are implemented through programming in Fortran90 software.The revised content has been highlighted in red in the updated manuscript.

2. Question: Please clarify why boundary conditions for ice concentration, thickness, and upstream inflow ice flux are not fully quantified.

Response: Thank you for your suggestion. Ice concentration is a temperature-dependent variable obtained from the daily observed ice concentration at the upstream cross-section; the ice element thickness is set at 0.2 m based on field measurements, and the ice-element size is 15 m. With these three quantities—ice thickness, element size, and ice concentration—the incoming ice flux at the upstream boundary can be determined.

3. Question: Please clarify whether ice concentration input is spatially uniform or sectional.

Response: Thank you for your suggestion. Ice concentration is uniformly prescribed at the grid nodes of the upstream boundary.

4. Question: I would recommend adding quantitative validation metrics for water level and ice thickness.

Response: Thank you for your suggestion. Because measured water-level data are sparse, no validation metrics were computed for modeled versus observed stages. Based on the simulated and observed ice thicknesses, the RMSEs for the 2019—2020 and 2020—2021 winters are 0.032 m and 0.009 m, respectively, and the corresponding NSE values are 0.898 and 0.976, demonstrating high accuracy and good performance of the river-ice model. This statement has been highlighted in red in the revised manuscript.

5. Question: Missing References: There are some missing references in the manuscript. For example, the reason for the choice of ice floe size should be referenced (line 184), and further references are needed for the discussion on lines 205–

Response: Thank you for your suggestion. Additional references are provided below:

[22] Shen, H. T.; Lu, S. Crissman R D. Numerical simulation of ice transport over the Lake Erie-Niagara River ice boom.Cold regions science and technology 1997, 26(1): 17-33. doi:10.1016/S0165-232X(97)00005-0.

[25] Shen, H. T., Gao, L., Kolerski, T., et al. Dynamics of ice jam formation and release. Journal of Coastal Research 2008, 10052,25–32. doi:10.2112/1551-5036-52.sp1.25.

6. Question: Missing References: A few recent international river-ice modeling studies (post-2020) could be added.

Response: Thank you for your suggestion. Additional references are provided below:

[15]Zhai, B.; Liu, L.; Shen, H. T.; et al. A numerical model for river ice dynamics based on discrete element method. Journal of Hydraulic Research 2022, 60(4), 543–556. doi: 10.1080/00221686.2021.2004254.

[16]Zhai, B.; Shen, H. T.; Liu, L., et al. DEM simulation of wave-generated river ice cover breakup. Cold Regions Science and Technology 2024, 218,104084. doi: 10.1016/j.coldregions.2023.104084.

7. Question: Model Limitations and Future Studies: The visual agreement between simulated and observed results is good. However, it would be helpful to briefly discuss the limitations and weaknesses of the model, along with potential areas for improvement in future studies. Add a short paragraph explicitly acknowledging limitations.

Response: Thank you for your suggestion. Added text reads as follows: In natural rivers the size of ice floes varies widely and ice concentration changes dynamically with time; both factors are critical to the morphology, location and timing of ice-cover formation. In the present model, however, all ice floes are assigned a uniform size and their density is prescribed from manual observations whose accuracy is limited by the measurement technique, potentially degrading simulation fidelity. Future work could employ semantic-segmentation models to automatically identify floe size and density, and couple this capability with the river-ice model to improve predictive skill. Moreover, because the current ice model is formulated within a continuum framework, subsequent studies could incorporate the discrete-element method to elucidate the micro-mechanisms governing ice-jam initiation.

8. Question: The sensitivity analysis yields reasonable and physically intuitive results, but the methodology should be presented more conservatively. The sensitivity analysis procedure resembles one factor at a time sensitivity analysis, not classical Morris screening. Please revise.

Response: Thank you for your suggestion. The sensitivity analysis in this paper employs the revised Morris screening method—a “simplified fixed-step” variant of the classical Morris technique developed for engineering practice. While retaining the “one-factor-at-a-time” philosophy, it replaces the original random discrete steps with percentage-based increments, yielding controllable perturbation magnitudes and more intuitive operation; sensitivity is then quantified directly by the ratio of relative change rates. This description appears in the revised version.

9. Question: Clarify the number and timing of observation points used.

Response: Thank you for your suggestion. The revised manuscript states as follows: During the freeze-up period of the winters 2019–2020 and 2020–2021, the research team conducted field observations at the Toudaoguai reach, collecting meteorological, ice and hydrological data. The dataset includes air temperature and wind speed in the study area, ice concentration, floe size and thickness at the upstream cross-section, the ice distrubution along the entire reach, ice-cover thickness at a typical section in the Shisifenzixian bend, and water level at the downstream outlet section. Because of the difficult conditions during the freeze-up period, ice thickness was estimated visually by comparison; once ice cover had formed, thickness was measured by drilling holes spaced 20 m apart across the section with an L-shaped ruler.

10. Question: Missing References: Briefly discuss measurement uncertainty (especially ice thickness).

Response: Thank you for your suggestion. This has been clarified in the revised manuscript.