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Article
Peer-Review Record

A Comparison of Model Calculations of Ice Thickness with the Observations on Small Water Bodies in Katowice Upland (Southern Poland)

Water 2022, 14(23), 3886; https://doi.org/10.3390/w14233886
by Maksymilian Solarski 1,* and Mariusz Rzetala 2
Reviewer 1:
Reviewer 2: Anonymous
Reviewer 3: Anonymous
Water 2022, 14(23), 3886; https://doi.org/10.3390/w14233886
Submission received: 2 November 2022 / Revised: 22 November 2022 / Accepted: 24 November 2022 / Published: 28 November 2022
(This article belongs to the Section Hydrology)

Round 1

Reviewer 1 Report

This study presented empirical methodologies and physical observation for developing an actual ice thickness model over small anthropogenic water bodies during winter seasons. Ice thickness observations are particularly important as they provide information about the distribution of ice, understanding the condition, and future behavior of ice in the small anthropogenic water bodies around human settlements. This helps us to forecast snowfall and ice accumulation around the human habitat. This topic is original and relevant in the field of limnology and is also related to ice phenology. Ice thickness data of winter seasons over anthropogenic water bodies are a very important contribution to understanding ice phenology.

However, certain criticisms are observed in this article that needs further reconstruction as suggested below:

1.      There is confusion about the importance of endorheic and polymictic processes. Clarify this with the implications in the study of ice phenology.

2.      Discuss the utility of CLimo, Flake, MinLake, and BW88 models with respect to the present study.

3. A regional scale comparison could be provided that significantly improve the present model. Considering similar data from the other parts of Europe to enhanced ice thickness model.

4. Recent work of Pirazzini et al (2020; Sensors) suggested standard practices of snow measurement, which could be very helpful in proving the harmonized monitoring of snow for the benefit of climate change scenarios, hydrology, and numerical ice thickness predictions in urban areas.

5. Results of the regional scale ice thickness model may bring more impact in the present study and convey significant advances in obtaining the transforming conclusions.

 

It is observed that this article contributes original data from small anthropogenic water bodies located in the Katowice Upland and related to the study on ice phenology, which should be appropriate to recommend for publication in the Water.

Author Response

Dear Reviewer,

Thank you very much for your kind comments. Obviously, we have attempted to incorporate all remarks and suggestions. All introduced changes are marked. Please, find our point-by point responses to all Reviewers critiques and remarks that are attached below. We hope that as a result of the changes introduced the article has more merit.

Yours sincerely,

Maksymilian Solarski and Mariusz Rzetala

 

 

Response to the remarks of the Reviewer 1

 

This study presented empirical methodologies and physical observation for developing an actual ice thickness model over small anthropogenic water bodies during winter seasons. Ice thickness observations are particularly important as they provide information about the distribution of ice, understanding the condition, and future behavior of ice in the small anthropogenic water bodies around human settlements. This helps us to forecast snowfall and ice accumulation around the human habitat. This topic is original and relevant in the field of limnology and is also related to ice phenology. Ice thickness data of winter seasons over anthropogenic water bodies are a very important contribution to understanding ice phenology.

However, certain criticisms are observed in this article that needs further reconstruction as suggested below:

Author’s Response: Thank you very much for your kind comments.

 

Reviewer: There is confusion about the importance of endorheic and polymictic processes. Clarify this with the implications in the study of ice phenology.

Author’s Response: Indeed, our description of the criteria for selecting water bodies (especially endorheic and polymictic ones) for study purposes was not entirely clear. The selection of water bodies with similar surface areas, volumes, depths, hydrological characteristics and mixing patterns was dictated by the desire to reduce the number of factors that could affect the thickness of the forming ice cover, e.g., water bodies into which warmer mine waters or river waters burdened with thermal pollutants flowed, which could inhibit ice cover development in such small water bodies, were not selected (Stigebrandt, 1978; Solarski, Rzetala 2021). Endorheic and polymictic water bodies with small surface areas and volumes freeze almost simultaneously, which is also reflected in further changes in ice thickness and the ability to conduct objective observations (Solarski et al., 2011, Bengtsson, 2012).

Description have been supplemented (lines 79-87). New publication have been included in the literature review (lines 450-451).

 

Reviewer:

  1. Discuss the utility of CLimo, Flake, MinLake, and BW88 models with respect to the present study.

Author’s Response:

The most commonly used models include the Canadian Lake Ice Model (CLIMo) (Ménard et al, 2002; Duguay et al, 2003; Jeffries et al., 2005a; Morris et al., 2005; Brown, Duguay, 2011a; Kheyrollah et al., 2012), Minnesota Lake Model (MINLAKE96) (Gao, Stefan, 1999; Fang, Stef-an, 2009), Multi-Year Lake Simulation Model (MYLAKE) (Dibike et al., 2011; Dibike et al., 2012), Freshwater Lake Model (FLAKE) (Bernhardt et al., 2011; Kheyrollah-Pour et al., 2012), and the Lake Ice Model Numerical Operational Simulation developed for Wisconsin lakes (LIMNOS) (Vavrus et al., 1996; Walsh et al., 1998). These are one-dimensional thermodynamic models developed mainly for lakes situated in North America (Canada, United States), but they can also be used to study other lakes located in temperate latitudes (Walsh et al., 1998; Dibike et al., 2011; Dibike et al., 2012). These models require the use of certain data that are often not available to researchers, for instance due to their inability to deploy portable weather stations (e.g., in densely populated urban areas where the risk of damage to, or theft of, research equipment is high). Ice thickness modelling and remote sensing data acquisition methods have recently become primary sources of data on ice cover on water bodies, which is dictated, inter alia, by financial, logistical and personnel considerations (Kheyrollah-Pour et al. 2012, Wang et al, 2018,  Cai et al. 2022).

Description have been supplemented (lines45-58). New publication have been included in the literature review (lines 410-440).

 

Reviewer:

  1. A regional scale comparison could be provided that significantly improve the present model. Considering similar data from the other parts of Europe to enhanced ice thickness model.

Author’s Response: We consider the above comments to be very useful, and the data collected by the authors, when combined with data on ice phenomena in water bodies located in other parts of Europe, would undoubtedly be very valuable and raise the profile of this study. Unfortunately, we do not have data on ice and snow thickness in small anthropogenic water bodies located in other parts of Europe. However, we do not rule out that such data will be included in future studies.

 

Reviewer:  4. Recent work of Pirazzini et al (2020; Sensors) suggested standard practices of snow measurement, which could be very helpful in proving the harmonized monitoring of snow for the benefit of climate change scenarios, hydrology, and numerical ice thickness predictions in urban areas.

Author’s Response: Ice and snow thickness measurements were conducted in accordance with the methodological guidelines contained in, inter alia, Doesken, N.J. and Judson, A. (1996). The paper indicated by the Reviewer (Pirazzini et al., 2018) has also been taken into account in the revised version of the article, adding recent guidelines to the description of study methods.

Description have been supplemented (line 104). New publication have been included in the literature review (lines 454-456).

 

Reviewer: 5. Results of the regional scale ice thickness model may bring more impact in the present study and convey significant advances in obtaining the transforming conclusions.

Author’s Response:  For the reasons mentioned above (including the lack of detailed data on ice phenomena in small bodies of water), the research topic indicated by the Reviewer was not undertaken on a broader geographical scale. The Reviewer’s suggestion provides an inspiration for us to embark on new cross-regional research.

 

Reviewer: It is observed that this article contributes original data from small anthropogenic water bodies located in the Katowice Upland and related to the study on ice phenology, which should be appropriate to recommend for publication in the Water.

Author’s Response: Thank you very much!

Author Response File: Author Response.pdf

Reviewer 2 Report

Dear Authors, your work is interesting and the results are clearly presented. Additionally the manuscript is very well written. 

Following some additional comments on the manuscript:

The AFDD (sum of the daily computed freezing degree days) is commonly used for estimating the thickness of ice cover.
This method together with the method developed by Martin Ajne is regarded as good method for predicting ice growth on lakes or rivers.
The authors investigate 11 antrhopogenic lakes in south Poland and use the data from 3 seasons with different weather conditions in order to model the ice growth.
They utilize the classic 100 years old formula of Stefan in order to model the ice thickness growth, which provided the best prediction (in comparison to Zubov's) within the limited range of annual f-d-d associated with this specific location.
Since engineering problems require an estimate of ice thickness especially in cold areas, such studies are important for the local communities.
Despite the only 3-years period of analyses, in my opinion the data are detailed enough in order to produce a decent model.
Indeed, other, more modern, models like MyLake (Multi-year simulation model for Lake thermo- and phytoplankton dynamics) need a much more detailed database.

What probably miss in the discussion, is validation and testing of the model with more recent data (ice cover thickness).
Also in the abstract and introduction, miss the reason for conducting this research. ie. Engineering reasons? 

Kind regards

Author Response

Dear Reviewer,

Thank you very much for your kind comments. Obviously, we have attempted to incorporate all remarks and suggestions. All introduced changes are marked. Please, find our point-by point responses to all Reviewers critiques and remarks that are attached below. We hope that as a result of the changes introduced the article has more merit.

Yours sincerely,

Maksymilian Solarski and Mariusz Rzetala

 

Response to the remarks of the Reviewer 2

 

Reviewer: Dear Authors, your work is interesting and the results are clearly presented. Additionally the manuscript is very well written.

Author’s Response: Thank you very much for your kind comments.

 

Reviewer:  Following some additional comments on the manuscript:

The AFDD (sum of the daily computed freezing degree days) is commonly used for estimating the thickness of ice cover.

This method together with the method developed by Martin Ajne is regarded as good method for predicting ice growth on lakes or rivers.

The authors investigate 11 antrhopogenic lakes in south Poland and use the data from 3 seasons with different weather conditions in order to model the ice growth.

They utilize the classic 100 years old formula of Stefan in order to model the ice thickness growth, which provided the best prediction (in comparison to Zubov's) within the limited range of annual f-d-d associated with this specific location.

Since engineering problems require an estimate of ice thickness especially in cold areas, such studies are important for the local communities.

Despite the only 3-years period of analyses, in my opinion the data are detailed enough in order to produce a decent model.

Indeed, other, more modern, models like MyLake (Multi-year simulation model for Lake thermo- and phytoplankton dynamics) need a much more detailed database.

Author’s Response: Thank you very much for your valuable comments.

 

Reviewer: What probably miss in the discussion, is validation and testing of the model with more recent data (ice cover thickness).

Author’s Response: Unfortunately, a problem exists with respect to validating and testing the model on the basis of the data on ice cover thickness in subsequent years in the water bodies in question. As for more recent data, unfortunately these are not available to us. One reason, which is most likely related to rapid climate change, is that in the last decade, there was no period during which ice cover formed on the water bodies studied that would be sufficiently thick to guarantee the safety of the measurements.

 

Reviewer: Also in the abstract and introduction, miss the reason for conducting this research. ie. Engineering reasons?

Author’s Response:  We have revised and supplemented the abstract (lines 11-15, 23-26) and introduction (lines 62-66, 69-73).

Author Response File: Author Response.pdf

Reviewer 3 Report

Dear Authors;

My suggestion about you manuscript is acceptance with considering the following major revisions/modifications:

I would suggest the authors o start Abstract with a general problem statement instead of the specific objectives.

Line 16: Empirical coefficient? What do you mean? Do you mean regression coefficient? Please clarify.

Abstract can end with some implications of the findings in a broader context.

The authors should extend Introduction to better picture out the impact of main natural and anthropogenic factors on the evolution of ice thickness in high latitude regions. The literature review does help in this regard. I suggest he authors to go through the following papers and clarify the impact of climate change in ice-covered lakes (e.g., “Strong Warming Rates in the Surface and Bottom Layers of a Boreal Lake: Results from approximately Six Decades of Measurements (1964‐2020)” and “Six Decades of Thermal Change in a Pristine Lake Situated North of the Arctic Circle”).

Line 56: My main concern is about the study period. Why so short? To better evaluate a formula, it would be better to extend the study period. Please justify the selected study period.

Figure 2: Please add title of x-axis.

Figure 3: Please add title of x- and y- axes.

Figure 4: Please add full title of x- and y- axes.

Good luck

 

 

 

 

 

 

Author Response

Dear Reviewer,

Thank you very much for your kind comments. Obviously, we have attempted to incorporate all remarks and suggestions. All introduced changes are marked. Please, find our point-by point responses to all Reviewers critiques and remarks that are attached below. We hope that as a result of the changes introduced the article has more merit.

Yours sincerely,

Maksymilian Solarski and Mariusz Rzetala

 Response to the remarks of the Reviewer 3

 

Reviewer: Dear Authors; My suggestion about you manuscript is acceptance with considering the following major revisions/modifications:

Author’s Response: Thank you very much for your kind comments.

 

Reviewer: I would suggest the authors o start Abstract with a general problem statement instead of the specific objectives.

Author’s Response: We have revised and supplemented the introductory section of the abstract (lines 11-15).

 

Reviewer:  Line 16: Empirical coefficient? What do you mean? Do you mean regression coefficient? Please clarify.

Author’s Response: Yes, it means regression coefficient.

 

Reviewer:  Abstract can end with some implications of the findings in a broader context.

Author’s Response: The abstract has been modified (lines 23-26).

 

Reviewer:  The authors should extend Introduction to better picture out the impact of main natural and anthropogenic factors on the evolution of ice thickness in high latitude regions. The literature review does help in this regard. I suggest he authors to go through the following papers and clarify the impact of climate change in ice-covered lakes (e.g., “Strong Warming Rates in the Surface and Bottom Layers of a Boreal Lake: Results from approximately Six Decades of Measurements (1964‐2020)” and “Six Decades of Thermal Change in a Pristine Lake Situated North of the Arctic Circle”).

Author’s Response: The introduction has been modified (lines 39-43, 45-58, 62-66, 69-73). We have also added the publications mentioned by the Reviewer (lines 39-43, 395-400).

 

Reviewer:  Line 56: My main concern is about the study period. Why so short? To better evaluate a formula, it would be better to extend the study period. Please justify the selected study period.

Author’s Response: The research was carried out during three ice seasons, because they were not conducted in the context of climate change, subsequent winter seasons were very weak and ice sheets either did not appear or did not guarantee safety during the measurement. The series will be increased if the test conditions are safe.

 

Reviewer:  Figure 2: Please add title of x-axis.

Author’s Response: The figures have been modified as recommended by the Reviewer.

 

Reviewer:  Figure 3: Please add title of x- and y- axes.

Author’s Response: The figures have been modified as recommended by the Reviewer.

 

Reviewer:  Figure 4: Please add full title of x- and y- axes.

Author’s Response: The figures have been modified as recommended by the Reviewer.

Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report

The Authors have properly addressed my comments. My suggestion is acceptance. Congratulations to the Authors.

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