Treatment of Ferruginous Water in the Performance of Drip Irrigation Systems

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

no comments

Author Response

Thanks for your reviewing

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript entitled “Treatment of ferruginous water in the performance of drip irrigation systems” depicted the effects of five emitter models on the efficiency of the chlorination, aeration, decantation, and filtration processes. The work is interesting and has a certain meaning to the field. The experiment is well-designed. The content of the paper fits the scope of the journal. The writing is also acceptable. My suggestion is accepted.

Author Response

Thanks for you reviewing.

Reviewer 3 Report

Comments and Suggestions for Authors

This MS is a review of five different drip irrigation emitters and their robustness against clogging due to iron precipitates in source water. The authors aim to identify emitter designs and source water treatment processes that allow reliable drip irrigation use in areas with high amounts of iron in source water. 

 

The MS is well written. The results may be useful for farmers using drip irrigation in areas with high iron content in source water. 

 

There are some challenges with the MS with details about methods and statistics. Overall I’d like to see more results that were measured/calcuated but not shown in the MS: e.g., concentrations of other elements like Ca and Mg in the water; how distribution uniformity was calculated. Lack of detail on how statistics were used in some sections make me concerned that multiple samples weren’t taken during the experiment, limiting the conclusions that can be drawn from the results. The authors also definitively stated the causes of line clogging (e.g., the growth of iron-metabolizing bacteria) without measuring these. I would have liked to have seen Fe measured from various other places in the system (e.g., at the bottom of the sedimentation tanks and from the in-line filters) to show that it precipitates and thus is the cause of the reduction in flow rates. Thus, conclusions about the causes of line clogging should include words like “may” or “suggest” rather than “prove”.

 

Once the concerns above and below are addressed, the MS should be suitable for publication.

 

M&M: provide more information about the methods used. E.g., 

• how was Ca, Mg, Mn, total solid content determined in source water (line 134) and during the experiments (line 135)?... ICP-MS or alternatives; how many replicates per treatment. Sampling methods are implied in the results (lines 198-201), but please state the experimental setup in the M&M.

• Identify softwared use for statistical analysis (lines 154-160).

 

164: Ca and Mg results in mmolc/L; is the c a typo? Choose one way of reporting concentrations: Ca and Mg are mM, while Mn, total solids and Fe are mg/L.

 

Please report the Ca, Mg, Mn, total solids content for the water samples. These might vary more than the Fe and contribute to clogging the emitters. Since these can also precipitate and clog irrigation lines, their effects might even be more important than those of Fe.

 

Table 2 and throughout: use consistent terminology, either dripper or emitter.

 

Table 2, total Fe in the system: put lines under “Water source”, “System 2”, etc. to better indicate columns covered by each of these. Are the values from a single sampling each? At least n=3 should have been done at random points in the system for each value to show consistency among the emitters. Why do all the values have 2 decimal places and end in zero; it seems that the detection limit is 0.1 mg/L, as implied in the results for system 1. If so, remove all second decimal places from results (e.g., water source 1 all results are <0.1 mg/L).

 

184: not proving, but further suggesting. Don’t use “prove”. Also line 294.

 

193-6: conjecture about the causes of iron concentration variation shouldn’t be stated so definitively since the authors didn’t measure whether these actually occurred; e.g., whether Fe precipitated in the reservoirs of systems 3 and 4, and whether iron-metabolizing bacteria grew in the lines of system 2 (also in discussion, lines 254-6 and 286).

 

Tables 3 and 5 need a legend: define G.F. (degrees of freedom?); what do the asterisks mean in terms of significance.

 

Table 4: like table 2, include more dividing lines to separate groups of data, e.g., G1, G2 etc. Align columns better. Include SD and n for each measurement to let readers easily do a visual check on the stats. These data might be better presented as a histogram figure.

 

3.3 Distribution uniformity. What is this (need a definition). Why is low DU bad for irrigation? How did you measure it… looking at flow rates of all or a sample of emitters for each system? Detail method used in M&M section in more detail than in lines 145-8. Is there a difference between the CUD you reference in the M&M and the DU in the discussion? If the DU values are averages, data points in fig. 2 should contain error bars.

Author Response

Comment 1: This MS is a review of five different drip irrigation emitters and their robustness against clogging due to iron precipitates in source water. The authors aim to identify emitter designs and source water treatment processes that allow reliable drip irrigation use in areas with high amounts of iron in source water. 

The MS is well written. The results may be useful for farmers using drip irrigation in areas with high iron content in source water. 

There are some challenges with the MS with details about methods and statistics. Overall I’d like to see more results that were measured/calcuated but not shown in the MS: e.g., concentrations of other elements like Ca and Mg in the water; how distribution uniformity was calculated. Lack of detail on how statistics were used in some sections make me concerned that multiple samples weren’t taken during the experiment, limiting the conclusions that can be drawn from the results. The authors also definitively stated the causes of line clogging (e.g., the growth of iron-metabolizing bacteria) without measuring these. I would have liked to have seen Fe measured from various other places in the system (e.g., at the bottom of the sedimentation tanks and from the in-line filters) to show that it precipitates and thus is the cause of the reduction in flow rates. Thus, conclusions about the causes of line clogging should include words like “may” or “suggest” rather than “prove”.

Response 1: We made the corrections in the text.

Comment 2: how was Ca, Mg, Mn, total solid content determined in source water (line 134) and during the experiments (line 135)?... ICP-MS or alternatives; how many replicates per treatment. Sampling methods are implied in the results (lines 198-201), but please state the experimental setup in the M&M.

Response 2: Ca, Mg, Mn, and total solid contents were analyzed only at the beginning of the experiment. For these analysis we made 3 replicates. During the experiment (every 50 h) we analyzed values of the total iron content, pH and water temperature were obtained. The experimental setup is described on lines 148-152.

Comment 3: Identify softwared use for statistical analysis (lines 154-160).

Response 3: We inserted this information in the text (lines 159-160).

Comment 4: 164: Ca and Mg results in mmolc/L; is the c a typo? Choose one way of reporting concentrations: Ca and Mg are mM, while Mn, total solids and Fe are mg/L.

Response 4: We corrected the text, converting to units in mg/L. (163)

Comment 5: Please report the Ca, Mg, Mn, total solids content for the water samples. These might vary more than the Fe and contribute to clogging the emitters. Since these can also precipitate and clog irrigation lines, their effects might even be more important than those of Fe.

Response 5: According to Nakayama et al. (2007), these results did not imply a risk of emitters clogging, as stated in lines 163-166. In the region where the experiment was developed, east of the state of Minas Gerais, Brazil, there is generally no occurrence of problematic levels of these elements for drip irrigation.

Comment 6: Table 2 and throughout: use consistent terminology, either dripper or emitter.

Response 6: We made all corrections in the text.

Comment 7: Table 2, total Fe in the system: put lines under “Water source”, “System 2”, etc. to better indicate columns covered by each of these. Are the values from a single sampling each? At least n=3 should have been done at random points in the system for each value to show consistency among the emitters. Why do all the values have 2 decimal places and end in zero; it seems that the detection limit is 0.1 mg/L, as implied in the results for system 1. If so, remove all second decimal places from results (e.g., water source 1 all results are <0.1 mg/L)

Response 7: We made all corrections on the table.

Comment 8: 184: not proving, but further suggesting. Don’t use “prove”. Also line 294.

Response 8: We made all corrections in the text.

Comment 9: 193-6: conjecture about the causes of iron concentration variation shouldn’t be stated so definitively since the authors didn’t measure whether these actually occurred; e.g., whether Fe precipitated in the reservoirs of systems 3 and 4, and whether iron-metabolizing bacteria grew in the lines of system 2 (also in discussion, lines 254-6 and 286).

Response 9: we made many adjustments in the text. 

Comment 10: Tables 3 and 5 need a legend: define G.F. (degrees of freedom?); what do the asterisks mean in terms of significance.

Response 10: We made all corrections on the tables. The statistics were made with 5% of significance. We made a correction, leaving only one asterisk.

Comment 11: Table 4: like table 2, include more dividing lines to separate groups of data, e.g., G1, G2 etc. Align columns better. Include SD and n for each measurement to let readers easily do a visual check on the stats. These data might be better presented as a histogram figure.

Response 11: we made corrections to the table formatting.

We have this information (SD and n), but we decided not to include it in the paper, so as not to make the tables too confusing and overloaded. We can include the raw data as supplementary material, but if the reviewer feels that this information is crucial, we can add it to another table or even in the same Table 4.

Comment 12: 3.3 Distribution uniformity. What is this (need a definition). Why is low DU bad for irrigation? How did you measure it… looking at flow rates of all or a sample of emitters for each system? Detail method used in M&M section in more detail than in lines 145-8. Is there a difference between the CUD you reference in the M&M and the DU in the discussion? If the DU values are averages, data points in fig. 2 should contain error bars.

Response 12: DU is the same as CUD. CUD is used in Brazilian reports. We made the corrections in the text.

Comment 13: Why is low DU bad for irrigation?

Response 13:We inserted a text explaining it (lines 45-157).

The description of methodology can be found in lines 135-147.

Author Response File: Author Response.pdf

Reviewer 4 Report

Comments and Suggestions for Authors

This manuscript, through detailed experimental design and data analysis, explores the impact of irrigation water with different iron contents on the flow rate, clogging, and hydraulic performance of drip irrigation systems, providing an important reference for irrigation issues in actual agricultural production. However, there are still issues that require further revision:

 

It is suggested that the author more clearly describe the experimental details in the manuscript, including the specific construction of the experimental setup, the experimental procedures, and precautions during operation, so that other researchers can reproduce the experimental results and conduct further verification and research.

 

The author considers four systems and different drip irrigation models in the experimental design, but in reality, there are more system types, drip irrigation models, and different water quality conditions. It is recommended to add a discussion on the universality and applicability of the research results.

 

In the results and discussion section, it is suggested to strengthen the in-depth discussion of the experimental results, particularly by conducting a more detailed analysis of the reasons for performance differences among different systems, and proposing possible improvement measures or future research directions.

 

The author uses methods such as variance analysis, but it is recommended to conduct a deeper analysis of the data, such as using multivariate statistical analysis methods, to explore the interactions between different variables and their impact on the performance of drip irrigation systems.

 

There are issues with the format of Table 4, and it is recommended to further modify and improve it.

 

Author Response

Comment 1: 

This manuscript, through detailed experimental design and data analysis, explores the impact of irrigation water with different iron contents on the flow rate, clogging, and hydraulic performance of drip irrigation systems, providing an important reference for irrigation issues in actual agricultural production. However, there are still issues that require further revision:

It is suggested that the author more clearly describe the experimental details in the manuscript, including the specific construction of the experimental setup, the experimental procedures, and precautions during operation, so that other researchers can reproduce the experimental results and conduct further verification and research.

Response 1: Response: We made many improvements in the text, highlighted in red.

Comment 2: The author considers four systems and different drip irrigation models in the experimental design, but in reality, there are more system types, drip irrigation models, and different water quality conditions. It is recommended to add a discussion on the universality and applicability of the research results.

Response 2: 

In this study, we have 5 models of drippers and 4 combinations of water quality and treatment:

System	Water	Treatment
1	Water from well (Fe <0,1)	Filtration
2	Water 2,6-4,0 mg/L Fe	Filtration
3	Water 2,6-4,0 mg/L Fe	Filtration + aeration + decantation
4	Water 2,6-4,0 mg/L Fe	Filtration + aeration + decantation + Chlorine

Comment 3: In the results and discussion section, it is suggested to strengthen the in-depth discussion of the experimental results, particularly by conducting a more detailed analysis of the reasons for performance differences among different systems, and proposing possible improvement measures or future research directions.

Response 3: we improved the discussion and inserted a text indicating future research directions.

Comment 4: The author uses methods such as variance analysis, but it is recommended to conduct a deeper analysis of the data, such as using multivariate statistical analysis methods, to explore the interactions between different variables and their impact on the performance of drip irrigation systems.

Response 4: For the specific case of the variables evaluated in the experiment, the repeated measurements obtained in the different split plit plot assumed the condition of compound symmetry for the variance and covariance matrix (sphericity condition). Therefore, the F test in relation to the split plit plot can assume an exact F distribution, opting for the univariate method with correction of degrees of freedom for the sub-subplot. Thus, the accuracy of the univariate analysis in the case of the experiment was satisfactory.

Comment 5: There are issues with the format of Table 4, and it is recommended to further modify and improve it.

Response 5: we made corrections to the table formatting.

Author Response File: Author Response.pdf

Round 2

Reviewer 3 Report

Comments and Suggestions for Authors

The revised MS is fine. The minor changes below should be made prior to publication.

 

Needs author names and affiliations on page 1

 

Line 122: 12% (v/v)

 

195: sedimentation may have occurred

 

Table 4: formatting issues with letters used in columns

 

290: first mention of algae growing in S1; a column labelled “+/- visible algae growth” should be included for all systems in Table 4 if you’re going to discuss it. It isn’t possible to definitively state that the algae was responsible for the flow reduction since it could also be due to Fe precipitation. I suggest instead: “Algae growth was noted in S1 (Table 4), which may have contributed to clogging in all dripper models in that system, with more significant…”. Also 352: …which may be explained by…

 

Table 5: replace G.F. with Degrees of freedom

 

331, 336, 351, 370, 372: timepoint, not assessment

 

333, 337, 339: round all values to nearest integer %

 

Author Response

Responses for Reviewer

Comments 1: The revised MS is fine. The minor changes below should be made prior to publication.

Response 1: Dear reviewer, we would like to thank you for your suggestions for correction and improvement of our manuscript. They were certainly essential to ensure its quality.

 

Comments 2: Needs author names and affiliations on page 1

Response 2: We inserted these information.

 

Comments 3: Line 122: 12% (v/v)

Response 3: We inserted these information.

 

Comments 4: 195: sedimentation may have occurred

Response 4: We made corrections.

 

Comments 5: Table 4: formatting issues with letters used in columns

Response 5: We made some adjustments. We believe that visibility will be improved when editing the layout. 

 

Comments 6: 290: first mention of algae growing in S1; a column labelled “+/- visible algae growth” should be included for all systems in Table 4 if you’re going to discuss it. It isn’t possible to definitively state that the algae was responsible for the flow reduction since it could also be due to Fe precipitation. I suggest instead: “Algae growth was noted in S1 (Table 4), which may have contributed to clogging in all dripper models in that system, with more significant…”. Also 352: …which may be explained by…

Response 6: We have made some corrections as indicated by the reviewer.

 

Comments 7: Table 5: replace G.F. with Degrees of freedom

Response 7: We made it.

 

 Comments 8: 331, 336, 351, 370, 372: timepoint, not assessment

Response 8: We made it.

 

Comments 9: 333, 337, 339: round all values to nearest integer %

Response 9: We made it.