the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 26 Sep 2022
Influence of climate change, land use land cover, population and industries on the pollution of Ganga River
Abstract. Climate change, land use land cover (LULC), population, industries, and sewage treatment are factors that can strongly influence river water quality. This paper uses a coupled hydrological-water quality simulation model to assess the influence of each of these drivers on the most polluted river stretch of the Ganga River. The water quality model QUAL2K is driven by these five factors to assess their influence on nine water quality parameters, namely dissolved oxygen (DO), biochemical oxygen demand (BOD), faecal coliform, ammonia, nitrate, total nitrogen, organic-, inorganic-, and total phosphorous. Climate change projections are taken from CMIP5 RCP 4.5 and RCP 8.5 scenarios. Five socio-environmental scenarios which consider sewer network, sewage treatment capacity, level of treatment at sewage treatment plants (STPs), and the type of sewage (domestic or mixed) are also considered. The water quality is simulated using a coupled HEC-HMS-QUAL2K framework. The non-point source pollution is quantified using the export coefficient method, where the export of pollutants from all land use classes are considered. The climate change effect is found to have a larger effect on Kanpur water quality than other drivers, with a percentage contribution of above 70 % because of the large sensitivity of water quality parameters to the amount of streamflow. Climate change projections combined with socio-environmental scenarios imply that the large increase in pollution due to climate change, LULC, industry, and population growth cannot be controlled by the current treatment proposals for 2050. However, providing adequate STPs to meet the population of 2050, and allowing only domestic sewage to reach STPs can help to achieve the objective of the Ganga Action Plan in the mid-21st century.
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CC1: 'Comment on egusphere-2022-796', Kees Bons, 14 Oct 2022
Authors do not make a clear distinction between pollution (defined as the introduction of contaminants into the natural environment that cause adverse change) and poor water quality. Climate change influences water quality, but is does not introduce contaminants. I suggest the authors make a more careful distinction throughout the article. The suggestion that the load of pollutants is high due to climate change (line 521 and 522) is not correct. The concentration may be high, but the load is not changed when climate change reduces dilution.
The article does not make clear whether the flow in the main river Ganga is simulated or only the tributaries. If it refers to the main river, one should include the upstream abstractions in the scenario discussions. These abstractions determine how much flow reaches this part much more than any climate change scenario. If it refers only to the additional flow from the sub-catchment, then the suggestion in the title that impact on the Ganga River is studied must be adapted.
A similar comment can be made on pollution loads and concentrations. The incoming pollution load from upstream will most probably be a significant factor influencing the actual load and concentration in the river for the discussed scenarios.
Line 672: Refrence #3: The correct author name should be Bons, CA (not Bonus)
Citation: https://doi.org/10.5194/egusphere-2022-796-CC1 -
AC1: 'Reply on CC1', Sneha Santy, 15 Oct 2022
Thank you so much for your comment. We will get back to you shortly with our response to yours comments. We are extremely sorry for the typo in your name in the reference. This will be corrected in our revised manuscript.
Citation: https://doi.org/10.5194/egusphere-2022-796-AC1
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AC1: 'Reply on CC1', Sneha Santy, 15 Oct 2022
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RC1: 'Comment on egusphere-2022-796', Anonymous Referee #1, 23 Nov 2022
General comments
The manuscript describes an analysis of how important drivers may impact water quality in a section of the Ganga river by the mid of this century. It makes use of different scenarios for climate change, land use, population development and development of the urban water infrastructure. The topic is highly relevant for science and practice in order to learn how to safeguard water quality in the future. Accordingly, the theme would into the scope of HESS.
Unfortunately, the manuscript falls short of standards for articles in this journal. There are several limitations: one the one hand it is the scope of the manuscript, on the other hand it is its quality.
Scope: The manuscript reads sometimes more like a technical report (site-specific, use of acronyms etc.) for regional managers or authorities than for a general scientific audience. This also expressed in the objective section of the paper by stating that the study shall “… help decision-makers decide in the design of treatment units to ensure water quality.” (L. 122 – 123). There is nothing wrong about this objective, but is not sufficient for a scientific article, which should provide insights for a general scientific audience. As listed in the detailed comments below, there are many parts of the manuscript that lack this general interest but are very site-specific.
Quality: The narrow scope of the study is a lack of scientific quality in itself (for a scientific article). There are additional limitations regarding the content and the way the methods and results are presented. Conceptually, the study seems to only reflect an arbitrary fraction of a hydrological system that requires a more comprehensive view. This holds true first for the spatial aspect: the authors present results for only one part of the Ganga watershed neglecting the entire upstream catchment including its influence on the study area downstream. Second, it turns out (semi-)implicitly that only dry weather conditions (the non-monsoon season) is considered without providing data and a rationale why this specific analysis makes sense compared to a holistic view considering the entire annual (hydrological) cycle. Third, the information regarding the urban water management and its relevant components is very limited. Because the readers for example do not get information about the structure of sewers systems, the degree of connectivity to treatment plants etc., it is difficult to judge statements on measures such as affecting mixed sewers. Also the state of the art of water treatment of relevant industries such as tanneries (L. 131) is not explained. This leaves a reader wonder to which degree the current status reflects best practices such as described in pertinent documents (https://leatherpanel.org/sites/default/files/publications-attachments/common_effluent_treatment_plant_amburtec_ambur_india.pdf).
There are also issues with the literature used, which seems at least partially outdated with relevant papers on the topic and the Ganga river missing (e.g., Bowes et al., 2020; Khan et al., 2018; Nepal & Shrestha, 2015). Other articles are cited (e.g., Chawla & Mujumdar, 2018; Jin et al., 2015), but the respective key findings are not really considered and discussed.
Question marks exist also for some specific aspect regarding modelling and the data analysis. The model for example is only accounting for steady-state flow. This is only mentioned in the SI (Sec. S3). How are then transient conditions modelled? Or did the authors only model steady-state low flow conditions, neglecting any impact during rainfall (including non-point sources from urban and agricultural areas affecting P and coliforms, for example)? On the data analysis side, I have doubts whether the different nitrogen forms are correctly treated or whether nitrate and nitrate-N for example have been mixed up (see also the comment below):
Apart from the content-related issues, the manuscript is hard to follow because the text is often poorly structured, figures and figure captions are not always very clear (see also below for details) or even showing contradicting results (e.g., Fig. S13 and Tab. S9). The water quality model calibration for example, which is an essential part, is poorly described. The fundamental information is only provided in the SI (Section S3). The description is hard to follow. It is not very transparent which data has been used and where and from when data is available (only 3 grab samples during low flow conditions)? This makes it hard to get a complete and consistent understanding (e.g., how to reconcile Fig. 5 with Fig. S10?).
Detailed comments
- 20: what are mixed sewers in this context?
- 23: Kanpur is not mentioned before. Why is this relevant? Is it relevant for the general scientific audience or the regional authorities?
- 23 – 24, 28 – 30: These statements are contradictory: If proper STP development leads to good water quality, this seems to off-set the climate change effect. This implies that management has a stronger effect that climate change.
- 31: Keywords shouldn’t repeat words already used in the title.
- 36: As I read the cited article, there is not much information on how such a proper management looks like.
L: 48: Does the problem only exist in that area?
- 48 – 57: This is very site-specific. What are the general scientific issues to be shared in HESS?
- 66: What's this scenario?
- 77 – 78: Which limits?
L: 89 – 95: What are the findings of these studies? What questions emerge?
- 96: What were the scenarios accounting for?
- 100 – 103: This are very site-specific statements.
- 106 – 108: Why is this of general interest to the scientific community?
L: 113 – 117: What is the relevance of the two data sets? They haven’t been introduced? The structure of the paragraph is not very logical.
L: 122 – 123: Is a meaningful objective, but very site-specific with relevance for the respective authorities. A HESS paper however should provide general insights.
- 125, Sec. 21: Essential information is missing: climate, land use, hydrological data etc. Not sufficient for a scientific paper.
- 134 – 136: Fig. 1 is not very helpful in this form. The relationships between the three maps is not clear (panel a). Panel b is not clear either.
- 140, Table S1: Locations not clear; data not clear (in the SI). Insufficient to properly understand the data.
L: 144 – 152: This paragraph can be skipped.
- 161 – 163: Sentence not clear. Have the findings by these authors (Chawla & Mujumdar, 2018) also be considered for the hydrological analysis (e.g., their result about the substantial uncertainty and the non-stationarity)? Are these findings taken into consideration and if yes, how and where?
- 165: Which city?
- 184: One cannot see that well in the SI.
- 187: What's this?
- 194 – 195: How important are the headwater fluxes (water, nutrients etc.) for the final results? Where have one to set priorities (up-stream or in the section itself)? -> This could be a relevant question for a general scientific audience!
- 293 – 294: What happens upstream?
- 305 – 306: How is that calculated?
- 307, Sec. 3.1.2: This not really a result, but describes the scenarios used as boundary conditions.
- 318, Sec. 3.1.3: This are not results, but reasons for the scenarios.
- 345 – 347: Adding loads of different water constituents does not make sense. They have to be treated separately. Which non-point sources have been considered? Are urban areas also delivering non-point source inputs?
- 348, Fig. 5: Partially poor scales: one cannot see actual values of many data points (e.g., for nitrate or P).
- 356 – 357: What about the upstream basin?
- 372 – 374: why should that be a general result for which this reference makes sense? I assume this very much depends on the spatial distribution of land use within a watershed.
- 395 – 397: Does this hold true also for nitrate? Is groundwater no nitrate source? Distinguishing between non-point and point sources seems needed.
- 415: Why should municipal sewage not contain P? Human excreta contain a lot of P!
- 418 – 422: Very specific results related to scenario assumptions.
- 460: This basically reflects the assumed changes in sources and the assumed climate effect on low flow.
- 470 – 475: This results are relevant for regional decision makers but not for a general scientific audience.
L: 501: Which treatment units?
- 544: Units missing.
- 551: This will happen anyway during rain periods?! But does it happen under dry weather conditions? Basic explanations of the existing sewage system are missing.
- 564: From the figures, it seems that the 7 mg /L refer to nitrate-N, not nitrate. This implied a nitrate value of around 28 mg nitrate /L. Please check the entire data for consistency.
- 579 – 581: Such technical issues haven't been mentioned so far: the system description regarding the urban water management system is not presented in sufficient details.
- 619 – 621: There are major uncertainties! These should be treated much more explicitly and quantitatively.
Table S1: What do the data represent? Mean values of measured data? How many data, what type of samples, period of sampling etc.? Please clarify.
Fig. S2: No seasonal patterns? What are upstream conditions?
Fig. S3: How have these data be derived?
Fig. S4: For which gauging station?
Fig. S9: Where are measured data to compare with?
Tab. S9: The data contradict the results in Fig. S13. That’s confusing.
Fig. S13: Units are missing. What does CWC stand for?
References:
Bowes, M. J., Read, D. S., Joshi, H., Sinha, R., Ansari, A., Hazra, M., . . . Rees, H. G. (2020). Nutrient and microbial water quality of the upper Ganga River, India: identification of pollution sources. Environmental Monitoring and Assessment, 192(8), 533. doi:10.1007/s10661-020-08456-2
Chawla, I., & Mujumdar, P. P. (2018). Partitioning uncertainty in streamflow projections under nonstationary model conditions. Advances in Water Resources, 112, 266-282. doi:https://doi.org/10.1016/j.advwatres.2017.10.013
Jin, L., Whitehead, P. G., Sarkar, S., Sinha, R., Futter, M. N., Butterfield, D., . . . Crossman, J. (2015). Assessing the impacts of climate change and socio-economic changes on flow and phosphorus flux in the Ganga river system. Environmental Science: Processes & Impacts, 17(6), 1098-1110. doi:10.1039/C5EM00092K
Khan, S., Sinha, R., Whitehead, P., Sarkar, S., Jin, L., & Futter, M. N. (2018). Flows and sediment dynamics in the Ganga River under present and future climate scenarios. Hydrological Sciences Journal, 63(5), 763-782. doi:10.1080/02626667.2018.1447113
Nepal, S., & Shrestha, A. B. (2015). Impact of climate change on the hydrological regime of the Indus, Ganges and Brahmaputra river basins: a review of the literature. International Journal of Water Resources Development, 31(2), 201-218. doi:10.1080/07900627.2015.1030494
Citation: https://doi.org/10.5194/egusphere-2022-796-RC1 - AC2: 'Reply on RC1', Sneha Santy, 27 Dec 2022
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RC2: 'Comment on egusphere-2022-796', Anonymous Referee #2, 27 Nov 2022
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-796/egusphere-2022-796-RC2-supplement.pdf
- AC3: 'Reply on RC2', Sneha Santy, 27 Dec 2022
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CC2: 'Comment on egusphere-2022-796', Johan C. van Snippenberg, 28 Nov 2022
This review was prepared as part of graduate program course work at Wageningen University, and has been produced under supervision of Prof Jos van Dam. The review has been posted because of its good quality, and likely usefulness to the authors and editor. This review was not solicited by the journal.
The comment can be found in the supplement
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EC1: 'Comment on egusphere-2022-796', Christian Stamm, 28 Nov 2022
Dear authors
it seems that there was a technical issue with the comments by Reviewer 2 such that not the entire feedback was available. To make sure that all comments are communicated, I add the text by Reviewer 2 below:
Comments by Reviewer 2:
"This paper has integrated hydrological, LULC, and water quality data with the climate change simulation models to derive projections on water quality in one of the most polluted stretches of the Ganga river around Kanpur. While the concept and idea of the paper are sound, the paper is not very coherent and organized. There are also several; issues with the language several sections need a thorough rewriting. The figures are very bad, and they need to be redrawn. My specific comments on different sections are as follows:
Abstract: The abstract starts by saying that they have analysed the ‘most’ polluted stretch of the Ganga River but the definition of the stretch comes much later. In any case, this definition of the ‘most’ polluted stretch (Kanpur) may be debatable, and it may be better to replace this with ‘one of the most polluted' stretches. There are minor language issues that I have marked.
Introduction: The introduction sets the background and motivation well but lacks comprehensive referencing. The Ganga river has been studied quite extensively for water quality including modeling efforts by Indian workers. It is suggested to include a short review of these papers and more importantly presents a summary of water quality data to justify the pollution level of this stretch vis-à-vis global standards. Interestingly, the authors do not present the actual number of WQ parameters anywhere except in the plots with modeling results. It would be useful to let the readers know the pollution status of the river early in the paper.
Study area and Methodology: This section is generally okay but again the authors use subjective assessment of WQ parameters such as BOD, Chemical oxygen demand (COD), solids, TN, chromium, sulphate, sulphide and chloride without providing any data. Figure 1 is very badly drawn and does not reflect the rigour expected for a manuscript. The Ganga basin map is directly taken from the website, and the subbasin maps lack details of the site, drainage network, major locations etc. The schematic diagram is very poorly drawn and various symbols have not been explained. It is also not clear how this diagram was prepared and the data source for this figure should be cited. Similarly, Figure 2 is poorly formatted and it seems to be a part of some report rather than a manuscript figure. This needs to be simplified and made legible – the idea of this figure should be to provide an overall view of the methodology and details of different kinds of models and specific parameters can be minimised. Also, this can be shortened a bit by improving Tables 1 and 2 and avoiding duplication of information between text and tables.
Results and discussion: The results section is generally well-written and the interpretations are clear. However, the figures need a lot of improvement to make these publishable and to bring clarity. In Figure 4, the plots are too small to see the different classes and there is too much blank space. You can also combine the legend. Parts e and f might be better represented as column graphs.
Some specific comments are as follows:
Line 373 says that the effect of landuse changes on stream flow is more pronounced at sub-basin level but there is no analysis done at this scale. Therefore, I am not sure why this statement is required here. Also, I am not convinced about the statement itself. River basins are completely hierarchical and impacts should be visible at all scales. In fact, you are analyzing at sub-basin scale only. You must explain why the impacts of LULC changes on stream flow are not visible at this scale. This is rather contrary to the previous work done in several basins (see e.g. Ocgoa-Tocachi et al., 2016, Hydrological Processes; Buytaert et al., 2004, HESS) including the Ganga basin.
Line 410-412 again says that LULC alone does not lead to higher pollution but together with climate change it can aggravate it. I really do not understand this and this finding is also quite different from the earlier work done in the same area by Shukla et al. (2018). It is very surprising that the authors have not even cited this paper even though this work is exactly in the same area and on a similar theme. You may or may not agree with the results but omitting such directly relevant papers is not a good practice.
Shukla, A. K., Ojha, C. S. P., Mijic, A., Buytaert, W., Pathak, S., Garg, R. D., and Shukla, S.: Population growth, land use and land cover transformations, and water quality nexus in the Upper Ganga River basin, Hydrol. Earth Syst. Sci., 22, 4745–4770, https://doi.org/10.5194/hess-22-4745-2018, 2018.
In general, none of these findings are new in terms of science. The impacts of LULC, population, and industry on water quality are well established. The impact of climate change on some of the specific WQ parameters such as N and P on the Ganga river has also been modelled (e.g. Whitehead et al., 2015, 2018; Jin et al., 2015). So, the authors should clearly highlight what is different in this paper and what new information has been provided. In a broader sense, the findings do not seem to be different from the previous works although the quantum of change etc. might be different. However, this needs to be highlighted clearly in this manuscript.
Another weakness of the paper is that it lacks any serious discussion on the trends and results obtained from the modeling. All it has presented is different trends and numbers but the process understanding of these projected changes attributed to climate change is missing.
The conclusions section brings out some good points, particularly about the STPs and segregation of wastes which was demonstrated by the model. However, I think that this section can be sharpened and made more precise. Since most of these points have already been discussed in the main text, this section should be short and crisp.
Overall, this manuscript presents some good ideas, but it needs significant reorganization and restructuring. The writing as well as the figures need to be improved significantly before it becomes publishable. "
Please consider these comments by Reviewer 2 for providing your response to all feedback.
Christian Stamm, Editor HESS
Citation: https://doi.org/10.5194/egusphere-2022-796-EC1
Status: closed
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CC1: 'Comment on egusphere-2022-796', Kees Bons, 14 Oct 2022
Authors do not make a clear distinction between pollution (defined as the introduction of contaminants into the natural environment that cause adverse change) and poor water quality. Climate change influences water quality, but is does not introduce contaminants. I suggest the authors make a more careful distinction throughout the article. The suggestion that the load of pollutants is high due to climate change (line 521 and 522) is not correct. The concentration may be high, but the load is not changed when climate change reduces dilution.
The article does not make clear whether the flow in the main river Ganga is simulated or only the tributaries. If it refers to the main river, one should include the upstream abstractions in the scenario discussions. These abstractions determine how much flow reaches this part much more than any climate change scenario. If it refers only to the additional flow from the sub-catchment, then the suggestion in the title that impact on the Ganga River is studied must be adapted.
A similar comment can be made on pollution loads and concentrations. The incoming pollution load from upstream will most probably be a significant factor influencing the actual load and concentration in the river for the discussed scenarios.
Line 672: Refrence #3: The correct author name should be Bons, CA (not Bonus)
Citation: https://doi.org/10.5194/egusphere-2022-796-CC1 -
AC1: 'Reply on CC1', Sneha Santy, 15 Oct 2022
Thank you so much for your comment. We will get back to you shortly with our response to yours comments. We are extremely sorry for the typo in your name in the reference. This will be corrected in our revised manuscript.
Citation: https://doi.org/10.5194/egusphere-2022-796-AC1
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AC1: 'Reply on CC1', Sneha Santy, 15 Oct 2022
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RC1: 'Comment on egusphere-2022-796', Anonymous Referee #1, 23 Nov 2022
General comments
The manuscript describes an analysis of how important drivers may impact water quality in a section of the Ganga river by the mid of this century. It makes use of different scenarios for climate change, land use, population development and development of the urban water infrastructure. The topic is highly relevant for science and practice in order to learn how to safeguard water quality in the future. Accordingly, the theme would into the scope of HESS.
Unfortunately, the manuscript falls short of standards for articles in this journal. There are several limitations: one the one hand it is the scope of the manuscript, on the other hand it is its quality.
Scope: The manuscript reads sometimes more like a technical report (site-specific, use of acronyms etc.) for regional managers or authorities than for a general scientific audience. This also expressed in the objective section of the paper by stating that the study shall “… help decision-makers decide in the design of treatment units to ensure water quality.” (L. 122 – 123). There is nothing wrong about this objective, but is not sufficient for a scientific article, which should provide insights for a general scientific audience. As listed in the detailed comments below, there are many parts of the manuscript that lack this general interest but are very site-specific.
Quality: The narrow scope of the study is a lack of scientific quality in itself (for a scientific article). There are additional limitations regarding the content and the way the methods and results are presented. Conceptually, the study seems to only reflect an arbitrary fraction of a hydrological system that requires a more comprehensive view. This holds true first for the spatial aspect: the authors present results for only one part of the Ganga watershed neglecting the entire upstream catchment including its influence on the study area downstream. Second, it turns out (semi-)implicitly that only dry weather conditions (the non-monsoon season) is considered without providing data and a rationale why this specific analysis makes sense compared to a holistic view considering the entire annual (hydrological) cycle. Third, the information regarding the urban water management and its relevant components is very limited. Because the readers for example do not get information about the structure of sewers systems, the degree of connectivity to treatment plants etc., it is difficult to judge statements on measures such as affecting mixed sewers. Also the state of the art of water treatment of relevant industries such as tanneries (L. 131) is not explained. This leaves a reader wonder to which degree the current status reflects best practices such as described in pertinent documents (https://leatherpanel.org/sites/default/files/publications-attachments/common_effluent_treatment_plant_amburtec_ambur_india.pdf).
There are also issues with the literature used, which seems at least partially outdated with relevant papers on the topic and the Ganga river missing (e.g., Bowes et al., 2020; Khan et al., 2018; Nepal & Shrestha, 2015). Other articles are cited (e.g., Chawla & Mujumdar, 2018; Jin et al., 2015), but the respective key findings are not really considered and discussed.
Question marks exist also for some specific aspect regarding modelling and the data analysis. The model for example is only accounting for steady-state flow. This is only mentioned in the SI (Sec. S3). How are then transient conditions modelled? Or did the authors only model steady-state low flow conditions, neglecting any impact during rainfall (including non-point sources from urban and agricultural areas affecting P and coliforms, for example)? On the data analysis side, I have doubts whether the different nitrogen forms are correctly treated or whether nitrate and nitrate-N for example have been mixed up (see also the comment below):
Apart from the content-related issues, the manuscript is hard to follow because the text is often poorly structured, figures and figure captions are not always very clear (see also below for details) or even showing contradicting results (e.g., Fig. S13 and Tab. S9). The water quality model calibration for example, which is an essential part, is poorly described. The fundamental information is only provided in the SI (Section S3). The description is hard to follow. It is not very transparent which data has been used and where and from when data is available (only 3 grab samples during low flow conditions)? This makes it hard to get a complete and consistent understanding (e.g., how to reconcile Fig. 5 with Fig. S10?).
Detailed comments
- 20: what are mixed sewers in this context?
- 23: Kanpur is not mentioned before. Why is this relevant? Is it relevant for the general scientific audience or the regional authorities?
- 23 – 24, 28 – 30: These statements are contradictory: If proper STP development leads to good water quality, this seems to off-set the climate change effect. This implies that management has a stronger effect that climate change.
- 31: Keywords shouldn’t repeat words already used in the title.
- 36: As I read the cited article, there is not much information on how such a proper management looks like.
L: 48: Does the problem only exist in that area?
- 48 – 57: This is very site-specific. What are the general scientific issues to be shared in HESS?
- 66: What's this scenario?
- 77 – 78: Which limits?
L: 89 – 95: What are the findings of these studies? What questions emerge?
- 96: What were the scenarios accounting for?
- 100 – 103: This are very site-specific statements.
- 106 – 108: Why is this of general interest to the scientific community?
L: 113 – 117: What is the relevance of the two data sets? They haven’t been introduced? The structure of the paragraph is not very logical.
L: 122 – 123: Is a meaningful objective, but very site-specific with relevance for the respective authorities. A HESS paper however should provide general insights.
- 125, Sec. 21: Essential information is missing: climate, land use, hydrological data etc. Not sufficient for a scientific paper.
- 134 – 136: Fig. 1 is not very helpful in this form. The relationships between the three maps is not clear (panel a). Panel b is not clear either.
- 140, Table S1: Locations not clear; data not clear (in the SI). Insufficient to properly understand the data.
L: 144 – 152: This paragraph can be skipped.
- 161 – 163: Sentence not clear. Have the findings by these authors (Chawla & Mujumdar, 2018) also be considered for the hydrological analysis (e.g., their result about the substantial uncertainty and the non-stationarity)? Are these findings taken into consideration and if yes, how and where?
- 165: Which city?
- 184: One cannot see that well in the SI.
- 187: What's this?
- 194 – 195: How important are the headwater fluxes (water, nutrients etc.) for the final results? Where have one to set priorities (up-stream or in the section itself)? -> This could be a relevant question for a general scientific audience!
- 293 – 294: What happens upstream?
- 305 – 306: How is that calculated?
- 307, Sec. 3.1.2: This not really a result, but describes the scenarios used as boundary conditions.
- 318, Sec. 3.1.3: This are not results, but reasons for the scenarios.
- 345 – 347: Adding loads of different water constituents does not make sense. They have to be treated separately. Which non-point sources have been considered? Are urban areas also delivering non-point source inputs?
- 348, Fig. 5: Partially poor scales: one cannot see actual values of many data points (e.g., for nitrate or P).
- 356 – 357: What about the upstream basin?
- 372 – 374: why should that be a general result for which this reference makes sense? I assume this very much depends on the spatial distribution of land use within a watershed.
- 395 – 397: Does this hold true also for nitrate? Is groundwater no nitrate source? Distinguishing between non-point and point sources seems needed.
- 415: Why should municipal sewage not contain P? Human excreta contain a lot of P!
- 418 – 422: Very specific results related to scenario assumptions.
- 460: This basically reflects the assumed changes in sources and the assumed climate effect on low flow.
- 470 – 475: This results are relevant for regional decision makers but not for a general scientific audience.
L: 501: Which treatment units?
- 544: Units missing.
- 551: This will happen anyway during rain periods?! But does it happen under dry weather conditions? Basic explanations of the existing sewage system are missing.
- 564: From the figures, it seems that the 7 mg /L refer to nitrate-N, not nitrate. This implied a nitrate value of around 28 mg nitrate /L. Please check the entire data for consistency.
- 579 – 581: Such technical issues haven't been mentioned so far: the system description regarding the urban water management system is not presented in sufficient details.
- 619 – 621: There are major uncertainties! These should be treated much more explicitly and quantitatively.
Table S1: What do the data represent? Mean values of measured data? How many data, what type of samples, period of sampling etc.? Please clarify.
Fig. S2: No seasonal patterns? What are upstream conditions?
Fig. S3: How have these data be derived?
Fig. S4: For which gauging station?
Fig. S9: Where are measured data to compare with?
Tab. S9: The data contradict the results in Fig. S13. That’s confusing.
Fig. S13: Units are missing. What does CWC stand for?
References:
Bowes, M. J., Read, D. S., Joshi, H., Sinha, R., Ansari, A., Hazra, M., . . . Rees, H. G. (2020). Nutrient and microbial water quality of the upper Ganga River, India: identification of pollution sources. Environmental Monitoring and Assessment, 192(8), 533. doi:10.1007/s10661-020-08456-2
Chawla, I., & Mujumdar, P. P. (2018). Partitioning uncertainty in streamflow projections under nonstationary model conditions. Advances in Water Resources, 112, 266-282. doi:https://doi.org/10.1016/j.advwatres.2017.10.013
Jin, L., Whitehead, P. G., Sarkar, S., Sinha, R., Futter, M. N., Butterfield, D., . . . Crossman, J. (2015). Assessing the impacts of climate change and socio-economic changes on flow and phosphorus flux in the Ganga river system. Environmental Science: Processes & Impacts, 17(6), 1098-1110. doi:10.1039/C5EM00092K
Khan, S., Sinha, R., Whitehead, P., Sarkar, S., Jin, L., & Futter, M. N. (2018). Flows and sediment dynamics in the Ganga River under present and future climate scenarios. Hydrological Sciences Journal, 63(5), 763-782. doi:10.1080/02626667.2018.1447113
Nepal, S., & Shrestha, A. B. (2015). Impact of climate change on the hydrological regime of the Indus, Ganges and Brahmaputra river basins: a review of the literature. International Journal of Water Resources Development, 31(2), 201-218. doi:10.1080/07900627.2015.1030494
Citation: https://doi.org/10.5194/egusphere-2022-796-RC1 - AC2: 'Reply on RC1', Sneha Santy, 27 Dec 2022
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RC2: 'Comment on egusphere-2022-796', Anonymous Referee #2, 27 Nov 2022
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-796/egusphere-2022-796-RC2-supplement.pdf
- AC3: 'Reply on RC2', Sneha Santy, 27 Dec 2022
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CC2: 'Comment on egusphere-2022-796', Johan C. van Snippenberg, 28 Nov 2022
This review was prepared as part of graduate program course work at Wageningen University, and has been produced under supervision of Prof Jos van Dam. The review has been posted because of its good quality, and likely usefulness to the authors and editor. This review was not solicited by the journal.
The comment can be found in the supplement
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EC1: 'Comment on egusphere-2022-796', Christian Stamm, 28 Nov 2022
Dear authors
it seems that there was a technical issue with the comments by Reviewer 2 such that not the entire feedback was available. To make sure that all comments are communicated, I add the text by Reviewer 2 below:
Comments by Reviewer 2:
"This paper has integrated hydrological, LULC, and water quality data with the climate change simulation models to derive projections on water quality in one of the most polluted stretches of the Ganga river around Kanpur. While the concept and idea of the paper are sound, the paper is not very coherent and organized. There are also several; issues with the language several sections need a thorough rewriting. The figures are very bad, and they need to be redrawn. My specific comments on different sections are as follows:
Abstract: The abstract starts by saying that they have analysed the ‘most’ polluted stretch of the Ganga River but the definition of the stretch comes much later. In any case, this definition of the ‘most’ polluted stretch (Kanpur) may be debatable, and it may be better to replace this with ‘one of the most polluted' stretches. There are minor language issues that I have marked.
Introduction: The introduction sets the background and motivation well but lacks comprehensive referencing. The Ganga river has been studied quite extensively for water quality including modeling efforts by Indian workers. It is suggested to include a short review of these papers and more importantly presents a summary of water quality data to justify the pollution level of this stretch vis-à-vis global standards. Interestingly, the authors do not present the actual number of WQ parameters anywhere except in the plots with modeling results. It would be useful to let the readers know the pollution status of the river early in the paper.
Study area and Methodology: This section is generally okay but again the authors use subjective assessment of WQ parameters such as BOD, Chemical oxygen demand (COD), solids, TN, chromium, sulphate, sulphide and chloride without providing any data. Figure 1 is very badly drawn and does not reflect the rigour expected for a manuscript. The Ganga basin map is directly taken from the website, and the subbasin maps lack details of the site, drainage network, major locations etc. The schematic diagram is very poorly drawn and various symbols have not been explained. It is also not clear how this diagram was prepared and the data source for this figure should be cited. Similarly, Figure 2 is poorly formatted and it seems to be a part of some report rather than a manuscript figure. This needs to be simplified and made legible – the idea of this figure should be to provide an overall view of the methodology and details of different kinds of models and specific parameters can be minimised. Also, this can be shortened a bit by improving Tables 1 and 2 and avoiding duplication of information between text and tables.
Results and discussion: The results section is generally well-written and the interpretations are clear. However, the figures need a lot of improvement to make these publishable and to bring clarity. In Figure 4, the plots are too small to see the different classes and there is too much blank space. You can also combine the legend. Parts e and f might be better represented as column graphs.
Some specific comments are as follows:
Line 373 says that the effect of landuse changes on stream flow is more pronounced at sub-basin level but there is no analysis done at this scale. Therefore, I am not sure why this statement is required here. Also, I am not convinced about the statement itself. River basins are completely hierarchical and impacts should be visible at all scales. In fact, you are analyzing at sub-basin scale only. You must explain why the impacts of LULC changes on stream flow are not visible at this scale. This is rather contrary to the previous work done in several basins (see e.g. Ocgoa-Tocachi et al., 2016, Hydrological Processes; Buytaert et al., 2004, HESS) including the Ganga basin.
Line 410-412 again says that LULC alone does not lead to higher pollution but together with climate change it can aggravate it. I really do not understand this and this finding is also quite different from the earlier work done in the same area by Shukla et al. (2018). It is very surprising that the authors have not even cited this paper even though this work is exactly in the same area and on a similar theme. You may or may not agree with the results but omitting such directly relevant papers is not a good practice.
Shukla, A. K., Ojha, C. S. P., Mijic, A., Buytaert, W., Pathak, S., Garg, R. D., and Shukla, S.: Population growth, land use and land cover transformations, and water quality nexus in the Upper Ganga River basin, Hydrol. Earth Syst. Sci., 22, 4745–4770, https://doi.org/10.5194/hess-22-4745-2018, 2018.
In general, none of these findings are new in terms of science. The impacts of LULC, population, and industry on water quality are well established. The impact of climate change on some of the specific WQ parameters such as N and P on the Ganga river has also been modelled (e.g. Whitehead et al., 2015, 2018; Jin et al., 2015). So, the authors should clearly highlight what is different in this paper and what new information has been provided. In a broader sense, the findings do not seem to be different from the previous works although the quantum of change etc. might be different. However, this needs to be highlighted clearly in this manuscript.
Another weakness of the paper is that it lacks any serious discussion on the trends and results obtained from the modeling. All it has presented is different trends and numbers but the process understanding of these projected changes attributed to climate change is missing.
The conclusions section brings out some good points, particularly about the STPs and segregation of wastes which was demonstrated by the model. However, I think that this section can be sharpened and made more precise. Since most of these points have already been discussed in the main text, this section should be short and crisp.
Overall, this manuscript presents some good ideas, but it needs significant reorganization and restructuring. The writing as well as the figures need to be improved significantly before it becomes publishable. "
Please consider these comments by Reviewer 2 for providing your response to all feedback.
Christian Stamm, Editor HESS
Citation: https://doi.org/10.5194/egusphere-2022-796-EC1
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