Assessment of Lake Water Quality in Central Serbia—Using Serbian and Canadian Water Quality Indices on the Example of the Garaši Reservoir
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThe article is devoted to a relevant topic. This research focuses on the water quality evaluation
of reservoir in Serbia, which one is a vital source of drinking water. Authors analyzed three profiles at various depths ranging between 2021 and 2023. The study employed the Serbian and Canadian Water Quality Index to evaluate the water quality.
The topic of the article is relevant and may be of interest to the scientific community.
From a methodological point of view, it is unclear why such water quality assessment indices were chosen. The authors analyze each of these indexes separately, only at the end of the article the result is casually compared. This is insufficient, and it is necessary to focus in more detail on a comparative analysis of the results obtained by these two methods.
Data on the CWQI water quality index is provided, but there are no criteria for assessing water quality according to Serbian Water Quality Index (SWQI).
The structure of the article corresponds to IMRAD. It has clear structure, logical coherence and academic soundness. The list of references is up-to-date, mostly sources from 2010. The literary review is quite complete.
However, there are a number of issues that have received insufficient coverage:
1.It is not entirely clear why the authors chose these particular ones water quality indices: Canadian Water Quality Index (CWQI) and Serbian Water Quality Index (SWQI). What are the advantages and difference of them?
2.Unfortunately, no comparative analysis of the results is provided.
3.Sources of income of Al, Hg, Mn?
Due to my programme originality of the text is 89%. Self-citation is about 6%. The links are appropriately placed
In general, the article is interesting and may be of scientific interest. It can be published with minor edits.
Author Response
Response to Reviewer 1
- It is not entirely clear why the authors chose these particular ones water quality indices: Canadian Water Quality Index (CWQI) and Serbian Water Quality Index (SWQI). What are the advantages and difference of them?
Thank you for raising this insightful question. The choice of the Serbian Water Quality Index (SWQI) and the Canadian Water Quality Index (CWQI) in this study is justified as follows:
- Local Relevance and Applicability (SWQI):
The SWQI, developed by the Serbian Environmental Protection Agency (SEPA), is tailored specifically to the conditions and requirements of water resource protection in Serbia. Its parameter composition includes temperature, pH, electrical conductivity, oxygen saturation, biochemical oxygen demand (BOD), ammonium ion (NH4+), total nitrogen (TN), suspended solids (SS), orthophosphate, and total coliforms. This ensures compliance with national standards and long-term monitoring frameworks established within the country. As such, the SWQI provides a consistent and locally applicable framework for evaluating water quality in alignment with Serbia’s regulatory and resource management context.
- International Applicability and Detailed Assessment (CWQI):
The CWQI, designed by Canadian environmental councils, offers a multidimensional approach to water quality assessment. Its methodology, based on scope, frequency, and amplitude of deviations from established objectives, enables not only an overall evaluation of water quality but also its applicability for specific uses (e.g., drinking, aquatic life, recreation, irrigation, and livestock). Furthermore, the CWQI incorporates parameters such as heavy metals (e.g., Al, Hg, Mn), which are particularly significant for identifying ecological and public health risks.
- Complementary Approaches:
By combining SWQI and CWQI, we achieve a deeper and more comprehensive insight into water quality. While the SWQI provides a reliable assessment within the framework of Serbia’s local standards and practices, the CWQI allows for the evaluation of specific risks and conditions from an internationally recognized perspective. This dual approach enhances the validation of our findings and enables more precise and context-sensitive interpretations of spatial and vertical variations in water quality.
This methodology guarantees that the assessment of water quality in the Garaši reservoir aligns with local standards while incorporating an international perspective, thereby enhancing the depth and reliability of our study.
- Unfortunately, no comparative analysis of the results is provided.
Thank you for your valuable comment. We agree that a clear comparative analysis is essential for interpreting the water quality results in the Garaši Reservoir. In response, we have thoroughly revised the manuscript to address this point. Specifically, we have expanded the Discussion section to include a detailed comparative analysis between the results obtained from the Serbian Water Quality Index (SWQI) and the Canadian Water Quality Index (CWQI).
This analysis explores the complementary nature of SWQI and CWQI, highlighting their methodological differences and the unique insights they provide. The discussion emphasizes spatial and depth variability, temporal trends, and the implications of parameter selection on water quality interpretation. To provide clarity, we have also referenced specific textual and graphical comparisons in the Results section (Tables 10 and 11). These additions, we believe, provide a comprehensive overview of the key differences and similarities between the two indices and effectively address your concern.
- Sources of income of Al, Hg, Mn?
Thank you for raising this important question, which helps clarify key aspects of our research. Based on the analysis of our data, we identified the following sources of contamination by aluminium (Al), mercury (Hg), and manganese (Mn) in the Garaši Reservoir:
- Natural Geological Sources;
- Anthropogenic Impacts;
- Internal Reservoir Processes;
- Direct Impact of the Velika Bukulja River;
In the revised manuscript, we have expanded the discussion in the "Discussion" section to include these sources of contamination and their implications for water quality in the Garaši Reservoir.
Reviewer 2 Report
Comments and Suggestions for AuthorsThe manuscript is devoted to an important problem - the development of monitoring methods for a comprehensive assessment of the ecological state of water bodies used for water supply to the population. This is of great importance in the context of population growth, urban and industrial development. This investigation contributes to the development of an effective water resources management policy, guaranteeing their satisfactory condition for drinking purposes, agriculture and recreational use and other tasks.
There are some questions about the manuscript.
Section 2.1.
It is necessary to indicate the average depth of the reservoir. The maximum depth (it can be near a dam only) of reservoirs often does not reflect how deep the reservoir is along the longitudinal profile. As for the average depth it makes possible to understand whether reservoir is shallow or not. Also it is necessary to indicate the water exchange coefficient. This is necessary to understand how flowing the reservoir is.
It is necessary to enlarge the map of the reservoir and mark with lines the sections where samples were taken. It is also unclear how exactly the samples were taken. With a bathometer? At what depth? Please provide necessary information.
Lines 105-107. The sampling was carried out at a depth of 1500 m (1.5 km?). Is there an error in indicating the depths? Is the depth of the reservoir similar to the depth of Lake Baikal?
Section 2 2.
It is necessary to indicate how exactly individual parameters were analyzed. How were water temperature, oxygen, electrical conductivity, etc. measured. What equipments were used? What methods were used to determine total phosphorus?
Section 3. Results.
For all parameters, there should be a table indicating not only the values from and to, but also the average value and standard deviation. It is not clear from the text in which years what parameter value was.
The paper presents numerous research results, and their statistical processing is required. It would be good to compare the index values in different years or at different stations using statistical methods.
Conclusion
It is necessary to shorten the conclusion and make it more concise
Author Response
Response to Reviewer 2
- It is necessary to indicate the average depth of the reservoir. The maximum depth (it can be near a dam only) of reservoirs often does not reflect how deep the reservoir is along the longitudinal profile. As for the average depth it makes possible to understand whether reservoir is shallow or not. Also it is necessary to indicate the water exchange coefficient. This is necessary to understand how flowing the reservoir is.
It is necessary to enlarge the map of the reservoir and mark with lines the sections where samples were taken. It is also unclear how exactly the samples were taken. With a bathometer? At what depth? Please provide necessary information.
Lines 105-107. The sampling was carried out at a depth of 1500 m (1.5 km?). Is there an error in indicating the depths? Is the depth of the reservoir similar to the depth of Lake Baikal?
In the Materials and Methods section (2.1. Study Area and Sampling), we initially stated that the depth of the reservoir was up to 26 meters. However, we have now corrected this in the text to indicate that the maximum depth of the reservoir is up to 26 meters, as this was not properly defined earlier.
It is also important to emphasize that the depth of the reservoir varies depending on the water level, which can significantly change throughout the year. While the maximum depth is typically observed near the dam, this value may not reflect the overall depth profile along the longitudinal axis of the reservoir. Unfortunately, specific data on the average depth are not available, as this would require additional measurements or analyses.
However, based on its morphometry and field observations, the reservoir can be classified as relatively shallow, as its longitudinal depth profile indicates significant variation influenced by seasonal water level fluctuations.
Regarding the water exchange coefficient, we must note that, unfortunately, it is not possible for us to calculate this parameter. One of the key reasons is the lack of official monitoring data for the river Velika Bukulja, which feeds into and drains the reservoir. There is no established hydrological regime for this river, including flow rate measurements, which makes it challenging to determine the volume of water entering or exiting the reservoir.
Without this crucial data, calculating the water exchange coefficient would require assumptions that could compromise the accuracy of our findings. We acknowledge the importance of this parameter and recommend future studies that include detailed hydrological monitoring of the river to address this gap.
The map in Figure 1 clearly marks the sampling locations (profiles A1, B1, and C1) with dots, ensuring clarity for the reader regarding the specific sites where water samples were collected for analysis. However, we acknowledge that the original title of Figure 1 might not have been sufficiently descriptive, which we have now corrected in the revised version of the manuscript.
Additionally, the map provides not only a detailed representation of the reservoir but also its geographical position within Serbia. This broader view adds valuable context by depicting the reservoir's location relative to neighbouring countries, which we consider an important element for understanding the study area.
Enlarging the map to highlight sampling sections more prominently would likely require removing the depiction of the reservoir’s position within Serbia. Since this regional context is highly informative, we believe retaining the current format of the figure, with adjustments to its title, better serves the manuscript's overall presentation. We trust this explanation resolves any concerns, but we remain open to further refinements based on additional feedback.
The water quality parameters analyzed in our study were obtained from data provided by the Serbian Environmental Protection Agency (2021–2023). Since we relied on these official datasets, we do not have direct insight into the specific sampling methods employed during water collection. Therefore, we are unable to confirm whether a bathometer was used or the precise depths at which samples were taken. Additionally, we acknowledge the need for specifying these methods in future studies where data collection is conducted firsthand.
Thank you for bringing this significant oversight to our attention. We have carefully reviewed the text and realized that there was an error in how we indicated the depths throughout the manuscript. Specifically, we mistakenly used "m" instead of "cm" when referring to the depths at which water samples were collected.
The correct depth values are in centimeters, not meters, and we have now corrected this error in the revised version of the manuscript to ensure clarity and accuracy. We sincerely appreciate your observation, which has helped us address this critical detail and improve the quality of our work.
- It is necessary to indicate how exactly individual parameters were analyzed. How were water temperature, oxygen, electrical conductivity, etc. measured. What equipments were used? What methods were used to determine total phosphorus?
In the revised version of the manuscript, we have provided detailed descriptions of the methods utilized by the Environmental Protection Agency of the Republic of Serbia to determine the physico-chemical parameters of water quality. The methods employed by the Agency have been clearly specified, ensuring transparency and adherence to established standards.
- For all parameters, there should be a table indicating not only the values from and to, but also the average value and standard deviation. It is not clear from the text in which years what parameter value was.
The paper presents numerous research results, and their statistical processing is required. It would be good to compare the index values in different years or at different stations using statistical methods.
In the revised manuscript, we have incorporated a comprehensive tables (for each parameter) presenting the average annual values for each analyzed parameter over the period 2021–2023. Additionally, standard deviations have been determined and included, ensuring statistical representation. This approach provides a clear and transparent overview of the dataset.
We have included a table presenting the Canadian Water Quality Index (CWQI) values in the Garaši Reservoir for the period 2021–2023. Additionally, we have expanded the Discussion section to incorporate a detailed comparative analysis of the Serbian Water Quality Index (SWQI) and Canadian Water Quality Index (CWQI) within the Garaši Reservoir. This addition provides a thorough statistical evaluation and enables a clearer comparison of index values across different years and methodologies.
To explore the correlation between SWQI and CWQI values at joint measurement depths (50 cm, 200 cm, and 500 cm) of all three profiles, regression analysis was employed. Since the P-value in the analysis of variance exceeds 0.10, there is no statistically significant relationship between SWQI and CWQI results at the 90% or higher confidence level. The correlation coefficient equals 0.21, indicating a relatively weak relationship between the variables. A more in-depth statistical analysis was not feasible due to the limitations of the available data series.
- Conclusion
It is necessary to shorten the conclusion and make it more concise.
The Conclusion section has been revised to make it more concise, reflecting the additional analyses and incorporating suggestions from all reviewers. This update ensures alignment with the improvements made throughout the manuscript and enhances its overall clarity.
Reviewer 3 Report
Comments and Suggestions for AuthorsThe manuscript titled “Assessment of LakeWater Quality in Central Serbia – Using Serbian and Canadian Water Quality Indices on the Example of the Garaši Reservoir” by Jakovljević, D.; et al. is a scientific work where the authors addressed the water quality of the Garaši lake from 2021 to 2023 taking into account two different water quality indexes from Canada and Serbia. Some of the conclusions are not strength enough (overall in terms of the spatial time scale where this study was devoted) but I find this research could be interesting for a certain specialized audience in this field. Furthermore, the manuscript is generally well-written.
However, it exists some points that need to be addressed (please, see them below detailed point-by-point) to improve the scientific quality of the submitted manuscript paper before this article will be consider for its publication in Sustainability.
1) Introduction. “Ensuring high water quality in lakes and reservoirs is essential (…) supporting aquatic life, and enabling recreational and economic activities” (lines 30-33). Could the authors provide quantitative data insights according to the worldwide economic impact to implement the neccesary measures to improve the water quality in the aquatic ecosystems? This information details will significantly aid the potential readers to better undestand this devoted research.
2) “Monitoring water quality allows for early detection of contamination sources (…) vital resources” (lines 36-38). Here, I agree with this statement provided by the authors albeit it may be convenient to add some existing techniques as single-molecule tools [1] to detect with ultrasensitivity changes in the different aquatic levels [2].
[1] https://doi.org/10.22034/IAR.2022.1965012.1317
[2] https://doi.org/10.1016/B978-0-12-824351-0.00007-9
3) Materials & Methods. “2.2.1. Serbian Water Quality Index (SWQI)” (lines 124-147) and “2.2.2. Canadian Water Quality Index (CWQI)” (lines 148-204). What are the main advantages and limitations comparing the Serbian and Canadian Water Quality Indexes? This could affect to the data interpretations of the gathered results in this research?
4) Finally, how many water samples and at what period of the year did the authors collected form the Garaši lake? This point is important because no permanent flows are exising in this aquatic reservoir that could lead to strong differences in the water nature and quality.
5) Results. Figure 2 (line 291). Some statistical analysis needs to be carried out in order to discern if the observed differences among the examined conditions are statistically significant. Same comment for the Fig. 3 (line 304), Fig. 4 (line 315), Fig 5 (line 379) and Fig. 6 (line 398), Fig. 7 (line 422), Fig. 8 (line 429), Fig. 9 (line 431), Fig. 10 (line 438), Fig. 11 (line 444) and Fig. 12 (line 453).
6) Then, the data from some tested conditions were not gathered. How this could affect to the data interpretation? Some insights need to be furnished in this regard.
7) Finally, did the authors examine the freshwater quality in terms of living species in this ecosystem (biological monitoring)?
8) “5. Conclusions” (lines 516-562). This section perfectly remarks the most relevant outcomes found by the authors in this work and also the promising future prospectives. It may be advisable to add a brief statement to remark the potential future action lines to pursue the topic covered in this work.
Author Response
Response to Reviewer 3
- Introduction. “Ensuring high water quality in lakes and reservoirs is essential (…) supporting aquatic life, and enabling recreational and economic activities” (lines 30-33). Could the authors provide quantitative data insights according to the worldwide economic impact to implement the necessary measures to improve the water quality in the aquatic ecosystems? This information details will significantly aid the potential readers to better understand this devoted research.
Thank you for this thoughtful comment. We have revised the introduction to include quantitative data insights to address the global economic impact of implementing measures to improve water quality. The updated section highlights analyses conducted by reputable organizations such as the World Bank and UNESCO, emphasizing the significant economic returns and reduction of losses associated with sustainable water management. We believe these additions will aid readers in better understanding the broader implications and importance of this research. Please let us know if further elaboration is needed.
- “Monitoring water quality allows for early detection of contamination sources (…) vital resources” (lines 36-38). Here, I agree with this statement provided by the authors albeit it may be convenient to add some existing techniques as single-molecule tools [1] to detect with ultrasensitivity changes in the different aquatic levels [2].
[1] https://doi.org/10.22034/IAR.2022.1965012.1317
[2] https://doi.org/10.1016/B978-0-12-824351-0.00007-9
We appreciate your suggestion regarding the incorporation of advanced techniques, such as single-molecule tools, for detecting changes in aquatic systems with ultrasensitivity. While our study primarily focused on physicochemical parameters and their integration into two widely recognized indices (SWQI and CWQI), we acknowledge the potential value of these innovative approaches in enhancing water quality monitoring. Such tools could complement traditional assessments by identifying trace contaminants or subtle shifts across different aquatic layers, offering a higher level of precision.
In the revised manuscript, we have briefly discussed these advanced techniques to highlight their relevance and potential application in future studies. This addition will also be emphasized in the Introduction, underscoring the importance of adopting a multifaceted approach to water quality monitoring, combining established indices with cutting-edge methodologies to achieve a more comprehensive understanding of aquatic ecosystems.
3) Materials & Methods. “2.2.1. Serbian Water Quality Index (SWQI)” (lines 124-147) and “2.2.2. Canadian Water Quality Index (CWQI)” (lines 148-204). What are the main advantages and limitations comparing the Serbian and Canadian Water Quality Indexes? This could affect to the data interpretations of the gathered results in this research?
Thank you for your questions. In revised manuscript we add this explanation:
The Serbian Water Quality Index (SWQI) is suitable for the assessment of organic and nutrient pollution. However, a disadvantage of this index is that it does not provide information about metal pollution. This was the reason for using the Canadian Water Quality Index (CWQI). Besides metal pollution, this index includes many more parameters than SWQI. On the other hand, CWQI is not suitable for evaluating nutrient pollution. Combined approach using these two indices provides more complete and relevant results and reduces the disadvantages of each single index.
4) Finally, how many water samples and at what period of the year did the authors collected form the Garaši lake? This point is important because no permanent flows are existing in this aquatic reservoir that could lead to strong differences in the water nature and quality.
Thank you for your comment. We add this information in revised manuscript: Water sampling was conducted by the Serbian Environmental Protection Agency three times (once per year) in the spring (May 2021 and March 2023) and summer (July 2022).
5) Results. Figure 2 (line 291). Some statistical analysis needs to be carried out in order to discern if the observed differences among the examined conditions are statistically significant. Same comment for the Fig. 3 (line 304), Fig. 4 (line 315), Fig 5 (line 379) and Fig. 6 (line 398), Fig. 7 (line 422), Fig. 8 (line 429), Fig. 9 (line 431), Fig. 10 (line 438), Fig. 11 (line 444) and Fig. 12 (line 453).
We would like to thank you for your suggestion. However, time-series were not enough long and there was no enough data to provide in-depth statistical analysis. We add explanation in revised manuscript:
To explore the correlation between SWQI and CWQI values at joint measurement depths (50 cm, 200 cm, and 500 cm) of all three profiles, regression analysis was employed. Since the P-value in the analysis of variance exceeds 0.10, there is no statistically significant relationship between SWQI and CWQI results at the 90% or higher confidence level. The correlation coefficient equals 0.21, indicating a relatively weak relationship between the variables. A more in-depth statistical analysis was not feasible due to the limitations of the available data series.
- Then, the data from some tested conditions were not gathered. How this could affect to the data interpretation? Some insights need to be furnished in this regard.
Thank you for your thoughtful observation. We agree that the absence of certain data for specific parameters and conditions could influence the interpretation of our results. While the available dataset enabled robust analysis for the majority of parameters, the lack of data for some key parameters, such as Biochemical Oxygen Demand (BOD), Suspended Solids (SS), Total Coliforms (TC), Manganese (Mn), Aluminium (Al), Mercury (Hg) at particular depths and time points may have limited the comprehensiveness of certain conclusions. These data gaps likely constrained our ability to fully assess organic loading, microbial water quality, and metal pollution, in some areas of the reservoir.
To address this, we carefully considered the potential implications of missing data in our analysis and discussed these limitations in the revised manuscript. Specifically, we highlighted how gaps in specific parameters could lead to under- or over-estimation of water quality trends, particularly for profiles and depths where stratification, reduced oxygen saturation, or elevated contaminant levels were more pronounced. Despite these challenges, the results from consistently measured parameters and indices, such as the Serbian Water Quality Index (SWQI) and Canadian Water Quality Index (CWQI), provide valuable insights into spatial and temporal trends in water quality.
The absence of certain data reinforces the need for continuous and comprehensive monitoring efforts that include all relevant parameters across profiles and depths. Future studies should aim to address these limitations by implementing uniform sampling protocols to ensure more robust and comparable datasets. We hope this explanation clarifies the impact of missing data.
- Finally, did the authors examine the freshwater quality in terms of living species in this ecosystem (biological monitoring)?
In this study, our primary focus was on the assessment of water quality using physicochemical parameters and their integration into two widely recognized indices: the Serbian Water Quality Index (SWQI) and the Canadian Water Quality Index (CWQI). These indices provided a comprehensive evaluation of the overall water quality, with particular emphasis on organic and nutrient pollution as well as specific chemical contaminants.
However, we acknowledge the importance of biological monitoring in providing a more holistic understanding of freshwater quality, especially regarding the health of living species within the ecosystem. While biological parameters were not directly assessed in our study, we have considered the implications of physicochemical conditions—such as reduced oxygen saturation at greater depths and elevated concentrations of metals like aluminium (Al) and manganese (Mn)—which can significantly affect aquatic life. Previous studies have highlighted the impact of these factors on fish health and other biota in reservoirs similar to Garaši.
We recognize that the integration of biological monitoring, including indicators such as benthic invertebrates, plankton diversity, and fish populations, would provide additional insights into the ecological status of the reservoir. This represents a valuable direction for future research, as it would complement the physicochemical data and offer a more complete assessment of ecosystem health.
- “5. Conclusions” (lines 516-562). This section perfectly remarks the most relevant outcomes found by the authors in this work and also the promising future prospectives. It may be advisable to add a brief statement to remark the potential future action lines to pursue the topic covered in this work.
The Conclusion section has been revised to make it more concise, reflecting the additional analyses and incorporating suggestions from all reviewers. This update ensures alignment with the improvements made throughout the manuscript and enhances its overall clarity.
Round 2
Reviewer 2 Report
Comments and Suggestions for AuthorsThe authors made corrections to most of the comments in the manuscript.
The following comments remained:
1. Table 1 - the table formatting and data presentation in it are unclear. What do the empty cells mean? Why is the "OS" column divided into two, starting from the second row?
2. The authors provided regression analysis as statistical processing. They provide this data in section 4.1. of the manuscript. However, they do not indicate the use of statistical processing in the work in the Materials and Methods section.
Author Response
- Table 1 - the table formatting and data presentation in it are unclear. What do the empty cells mean? Why is the "OS" column divided into two, starting from the second row?
Thank you for your comment. According to the SWQI methodology, different parameters have different values of (the last column in the Table 1). Oxygen Saturation (OS) has the highest maximum value of (18), comparing with other parameters. On the other hand, Temperature (T) has the lowest maximum value of (5). That is the reason why all other fields above the 5 are empty for this parameter. Same principle is valid for all parameters. Oxygen saturation (OS) has the highest value of (18) for the best (optimal) quality ranging from 93 to 109%. For all other values (either lower or higher than optimal range 93—109%), is lower than 18. The left part of divided column presents Oxygen Saturation deficit than optimal range, while the right part presents Oxygen Saturation surplus (supersaturation) than optimal range.
- The authors provided regression analysis as statistical processing. They provide this data in section 4.1. of the manuscript. However, they do not indicate the use of statistical processing in the work in the Materials and Methods section.
Thank you for this comment. We added the sentence about regression analysis at the end of Materials and Methods section.
Reviewer 3 Report
Comments and Suggestions for AuthorsThe authors did a great deal of effort to cover all the suggestions raised by the Reviewers. For this reason, the scientific manuscript quality was greatly improved. Based on the significance and novelty of the gathered results, I warmly endorse this research for further publication in Sustainability
Author Response
The authors did a great deal of effort to cover all the suggestions raised by the Reviewers. For this reason, the scientific manuscript quality was greatly improved. Based on the significance and novelty of the gathered results, I warmly endorse this research for further publication in Sustainability.
We are glad to hear your positive opinion. We would like to thank you for your valuable comments, which help us to improve our manuscript.