The Effects of Low-Impact Development Best Management Practices on Reducing Stormwater Caused by Land Use Changes in Urban Areas: A Case Study of Tehran City, Iran

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The study addresses the important topic of using LID-BMPs to mitigate stormwater impacts caused by land use changes. It presents a detailed analysis of land use changes from 2000 to 2022 using Landsat satellite images. The study applies GIS and MCDA methods to select appropriate LID-BMP types and employs rainfall-runoff modeling to evaluate changes in flood volume and peak discharge for two design storms. The analysis provides valuable insights for practical decision-making regarding LID-BMPs to manage stormwater. However, while the study references many models, it lacks sufficient explanation of their application. Additionally, the conclusion section would benefit from including more detailed findings and practical recommendations to enhance the paper’s overall quality.

Specific Comments:

1.     In the abstract (line 20), is the multi-criteria decision analysis (MCDA) method the same as the GIS-MCDA method mentioned in line 114, the Fuzzy-AHP method in Table 6, or the MCIS in line 329? If not, could the authors clarify what specific method is used for the multi-criteria decision analysis (MCDA)?     

2.     In the introduction, the authors use Table 1 to explain the importance and effects of LID-BMP approaches. Would it be more effective to present this information as text instead of a table? A textual description might enhance clarity and flow in this section.

3.     In Section 2.3.2.1., additional clarification is needed:

(1) What is the purpose of dividing the catchment into different hydrological units?

(2) What criteria were used to define these hydrological units?

(3) It is highly recommended to include streamlines in Figure 3, along with their respective stream order, to improve clarity.

4.     In Figure 4, please include the name and unit for the ordinate to ensure clarity.

5.     In Table 3, the following questions need to be addressed:

(1) Should "average annual rainfall" in the table be "average maximum 24-hour rainfall"?

(2) The numbers listed with the statistical distributions need clarification—what do these parameters represent?

(3) What is the Easy Fit software mentioned in line 263? Please provide a brief description.

(4) Are the meteorological stations used in Section2.3.3.2? the same as those in Section 2.3.3.1.?   

6.     In line 278, the authors state: "Due to the lack of suitable stations containing information near the study area, intensity, duration, and frequency (IDF) diagrams in this report were drawn using experimental and calibrated formulas." Could the IDF curves instead be derived using rainfall data from the three rainfall stations mentioned earlier? Additionally, please clarify the origins of Equations 5 and 6.

7.     In Table 5, please ensure all variables include their respective units. Additionally, in Section 2.3.2.1., the description mentions a non-hydrological unit (Dint?) with no independent stream, where water enters from adjacent basins. However, in Section 2.3.2.4., the time of concentration is calculated using Equation 3 based on the main channel length. How is the time of concentration determined for a unit without a channel? Please clarify.

8.     In Table 6, the following questions should be addressed:

(1)   The fuzzy membership functions for each criterion are determined using a questionnaire and expert opinions. Please provide more detailed explanations of this process.

(2)   How are the maximum and minimum values of the fuzzy function determined?

(3)   Why is the fuzzy function for the land use criterion (how is this criterion defined?) user-defined, and why is its weight factor significantly larger than those of the other seven criteria? Is this reasonable?

(4)   Does the sum of the weighting factors for all criteria for a selected LID-BMP (e.g., Bioretention Basin) equal one?

9.     It is recommended to include more detailed explanations of the processes used to generate Table 7, along with additional discussion on how this table is utilized. Furthermore, brief descriptions of the TerrSet software and the Gamma operator would be helpful.

10. The results in Table 8 are based on cases from China. Should these results be included in this paper? Were these data used in this research? Please clarify.

11. Land use classes are divided into four categories in Table 9, while Table 7 includes 11 different land use categories. Could you explain the rationale for this difference?

12. To analyze runoff changes for different design storms using LID-BMP methods, the SCS-CN rainfall-runoff model was employed to calculate infiltration loss based on CN values. How much can CN values be reduced for each LID-BMP method, and were these reductions used in the simulation model? Additionally, how many input variables were required for the simulation?

13. Section 2.3.2.1 mentions that eight sub-basins were defined, but only five sub-basins are discussed in Table 10. Please explain this discrepancy.

14. It is strongly recommended to rewrite the conclusion to highlight the key findings of this research and suggest actionable recommendations for decision-makers based on the study’s results.

Author Response

Our response follows:

Reviewer #1:

Dear reviewer

We appreciate your time and effort for giving valuable comments on our paper. Indeed the changes we made to this paper on the basis of your questions, have added to the scientific value of the paper. Following you see Responses to your questions in the same order of appearance.

The study addresses the important topic of using LID-BMPs to mitigate stormwater impacts caused by land use changes. It presents a detailed analysis of land use changes from 2000 to 2022 using Landsat satellite images. The study applies GIS and MCDA methods to select appropriate LID-BMP types and employs rainfall-runoff modeling to evaluate changes in flood volume and peak discharge for two design storms. The analysis provides valuable insights for practical decision-making regarding LID-BMPs to manage stormwater. However, while the study references many models, it lacks sufficient explanation of their application. Additionally, the conclusion section would benefit from including more detailed findings and practical recommendations to enhance the paper’s overall quality.

Response: Thank you for taking the time to review our manuscript and for your valuable comments. We appreciate your acknowledgment of the importance of our work and the detailed insights provided. Below, we have addressed each of the points raised.

Specific Comments:

Comment 1: In the abstract (line 20), is the multi-criteria decision analysis (MCDA) method the same as the GIS-MCDA method mentioned in line 114, the Fuzzy-AHP method in Table 6, or the MCIS in line 329? If not, could the authors clarify what specific method is used for the multi-criteria decision analysis (MCDA)?

Response 1: Thank you for your comment. GIS-MCDA (Geographic Information System-based Multi-Criteria Decision Analysis) is a comprehensive and integrated approach used to solve complex decision-making problems by considering spatial dimensions and multiple conflicting or complementary criteria. This approach combines the spatial analysis capabilities of Geographic Information Systems (GIS) with Multi-Criteria Decision Analysis (MCDA) methods to provide richer information for decision-making.

Throughout the article, GIS-MCDA has been consistently utilized. The Fuzzy-AHP method is one of the MCDA techniques. The MCIS method is different from MCDA. The MCIS method was employed for selecting the type of LID-BMP, while the MCDA method was used for weighting the criteria and preparing the final spatial mapping.

Comment 2: In the introduction, the authors use Table 1 to explain the importance and effects of LID-BMP approaches. Would it be more effective to present this information as text instead of a table? A textual description might enhance clarity and flow in this section.

Response 2: Thank you for your valuable suggestion regarding Table 1 in the introduction. We agree that presenting this information as text rather than a table could enhance clarity and flow. Therefore, we will remove Table 1 and provide the relevant information in a more descriptive and cohesive manner within the text of the introduction (Page 2, Line 59-76).

Comment 3:   In Section 2.3.2.1., additional clarification is needed:

(1) What is the purpose of dividing the catchment into different hydrological units?

Response: Dividing a catchment into distinct hydrological units serves several purposes and significantly enhances the accuracy and effectiveness of hydrological analysis and management:

Improved Accuracy in Analysis: Catchments encompass regions with diverse hydrological characteristics, such as land use, soil type, slope, and vegetation cover. By dividing the basin into smaller, more homogeneous units, it becomes possible to conduct more precise analyses of hydrological behavior, leading to more reliable modeling results.

Enhanced Water Resource Management: This division facilitates a better understanding and management of human activities and climate change impacts on various parts of the basin. For instance, it helps identify areas prone to erosion or flooding, enabling targeted interventions.

Better Modeling and Simulation: Hydrological models typically require accurate spatial and temporal input data. Dividing the basin into hydrological units ensures that model inputs are tailored to the specific characteristics of each unit, thereby improving the precision and reliability of predictions.

Identification and Prioritization of Problems: The subdivision allows for the identification of regions facing significant environmental challenges, such as soil erosion, water pollution, or reduced groundwater recharge. This prioritization aids in the effective allocation of resources and planning.

Effective Planning and Policy-making: Decision-makers can design and implement management strategies tailored to the unique conditions of each unit, making interventions more impactful and sustainable.

In the context of our study, dividing the basin was particularly critical due to the substantial variations in topography and land use across the area. The catchment included a mountainous peri-urban region, markedly different in hydrological characteristics from the downstream urban areas. Even within the urban sections, significant land use diversity was observed, with greener and more barren lands in the northern parts compared to denser urban landscapes in the south.

Our ultimate research goal was to evaluate the effectiveness of site-specific LID-BMPs (Low Impact Development – Best Management Practices) in reducing flood volumes and peak discharge due to land use changes. Achieving this required precise hydrological calculations, which were only possible by dividing the basin into smaller hydrological units with similar topographic, hydrological, and land use features.

(2) What criteria were used to define these hydrological units?

Response: (1) Drainage divide, (2) Changes in the density of drainage networks and the condition of main and tributary channels, (3) Changes in surface morphology and soil composition, and (4) Total basin area.

(3) It is highly recommended to include streamlines in Figure 3, along with their respective stream order, to improve clarity.

Response: Thank you for your valuable comment regarding Figure 3. As per your suggestion, we have added the streamlines along with their respective stream orders to the figure. We believe this addition has significantly improved the clarity and comprehensiveness of the figure, and we truly appreciate your insight. To avoid cluttering the map, the streamlines and stream order are presented in a separate map in Figure 3 (b) (Please check Figure 3).

Comment 4: In Figure 4, please include the name and unit for the ordinate to ensure clarity.

Response 4: Thank you for your comment. Corrected (Please check Figure 4).

Comment 5: In Table 3, the following questions need to be addressed:

(1) Should "average annual rainfall" in the table be "average maximum 24-hour rainfall"?

Response: Thank you for your comment. The term "average annual rainfall" in the table is correct and is not intended to be replaced by "average maximum 24-hour rainfall." In fact, "average annual rainfall" is a critical input for calculating the "average maximum 24-hour rainfall" using the EasyFit software.

To avoid potential misunderstandings, we propose modifying the title of Table 3 from "Selected statistical distributions of average maximum 24-hour rainfall (along with distribution parameters) for index stations" to "Selected statistical distributions used for calculating average maximum 24-hour rainfall (along with distribution parameters) for index stations." We believe this adjustment will make the context of the table clearer and align it better with the methodology described in the study (Page 9, Line 298-299).

(2) The numbers listed with the statistical distributions need clarification—what do these parameters represent?

Response: Thank you for your comment. The numbers associated with the statistical distributions represent the parameters of the fitted probability distributions, which are used to model the average maximum 24-hour rainfall at the meteorological stations. These parameters are crucial for characterizing the distribution and predicting extreme rainfall events. Explanations of each parameter have been added to the manuscript, and the corresponding values are now clearly specified in the table to indicate which parameter they represent (Page 9, Line 289-295 and Table 3). Here is a breakdown of what each parameter represents:

Wakeby distributions:

ξ (xi): 189.15 - Location parameter: This parameter defines the shifting point of the distribution along the x-axis.

α (alpha): 11.046 - Scale parameter: This parameter controls the spread or dispersion of the distribution.

β (beta): 8.697 - Shape parameter: This parameter defines the shape of the distribution curve, affecting its skewness.

γ (gamma): 0.19457 - Scale parameter: Similar to α, this parameter controls the spread of the distribution.

δ (delta): 16.588 - Shape parameter: This parameter also influences the skewness and the shape of the distribution.

LogLogistic distributions (Niavaran):

α (alpha): 3.7741 - Scale parameter: Determines the width of the distribution.

β (beta): 19.409 - Shape parameter: Controls the shape and asymmetry of the distribution.

γ (gamma): 7.1402 - Location parameter: It defines the shifting point along the x-axis of the distribution.

LogLogistic distributions (Abbaspour):

α (alpha): 2.558 - Scale parameter: Controls the spread of the distribution.

β (beta): 15.643 - Shape parameter: Influences the shape and skew of the distribution.

γ (gamma): 17.546 - Location parameter: Defines where the distribution is shifted along the x-axis.

These parameters allow hydrologists to estimate the probabilities of extreme rainfall events over various return periods, which is crucial for hydrological modeling and flood risk assessments.

(3) What is the Easy Fit software mentioned in line 263? Please provide a brief description.

Response: Thank you for your comment. As per your suggestion, we have now included a brief description of the EasyFit software. We appreciate your input, which has helped improve the clarity of the manuscript (Page 9, Line 286-288).

(4) Are the meteorological stations used in Section2.3.3.2? the same as those in Section 2.3.3.1.?

Response: Thank you for your question. Yes, the meteorological stations mentioned in Section 2.3.3.2 are the same as those in Section 2.3.3.1.

Comment 6: In line 278, the authors state: "Due to the lack of suitable stations containing information near the study area, intensity, duration, and frequency (IDF) diagrams in this report were drawn using experimental and calibrated formulas." Could the IDF curves instead be derived using rainfall data from the three rainfall stations mentioned earlier? Additionally, please clarify the origins of Equations 5 and 6.

Response 6: Thank you for your comment. The derivation of IDF curves requires minute-by-minute rainfall data, which, even if available from the mentioned stations, are typically in paper format and not easily accessible to researchers. Additionally, deriving these curves using such data would be a time-consuming and labor-intensive process, which was beyond the scope of this study.

The IDF relationships used in this study are based on a comprehensive analysis conducted by Dr. Ghahreman and Abkhezr (2004) for 34 rain gauge stations. These relationships have been widely adopted in various studies. Recently, these relationships have been updated and revised using data from a larger number of stations and longer statistical periods. In 2004, Dr. Ghahreman presented updated IDF relationships, dividing Iran into six regions and providing specific equations for each region to calculate one-hour rainfall for a 10-year return period. The study area falls within Region 2, and the Equations (5 and 6) used in this study are derived from this analysis.

Reference: Ghahraman, B.; Abkhezr, H. Improvement in intensity-duration-frequency relationships of rainfall in Iran. JWSS-Isfahan University of Technology 2004, 8, 1-14.

Comment 7: In Table 5, please ensure all variables include their respective units. Additionally, in Section 2.3.2.1., the description mentions a non-hydrological unit (Dint?) with no independent stream, where water enters from adjacent basins. However, in Section 2.3.2.4., the time of concentration is calculated using Equation 3 based on the main channel length. How is the time of concentration determined for a unit without a channel? Please clarify.

Response 7: Thank you for your valuable comment. Regarding Table 5, all variables have been updated with their respective units, as requested. As mentioned in Section 2.3.2.4, the Kirpich method was used to calculate the time of concentration (TOC) for all sub-basins. However, as you pointed out, the Dint sub-basin does not have an independent stream, so its calculation of TOC requires a different approach. While the Kirpich method is typically used for channels with a defined flow, there are alternative methods for estimating TOC in areas without a defined stream. For the Dint sub-basin, we applied an adjusted version of the Kirpich equation to account for the lack of a defined channel.

Where,  L flow length (m) and S average slope (m/m).

Specifically, the equation was modified to include characteristics of the surrounding basin area and hydrological conditions. While this adjustment was not explicitly detailed in the section for conciseness, it was used to ensure accurate TOC estimation for the Dint sub-basin. We hope this clarification addresses your concern, and we appreciate your helpful feedback.

Comment 8: In Table 6, the following questions should be addressed:

(1) The fuzzy membership functions for each criterion are determined using a questionnaire and expert opinions. Please provide more detailed explanations of this process.

Response: Thank you for your nice comment. Here is a more detailed explanation of the process for determining fuzzy membership functions:

1. Designing the Questionnaire:

   A questionnaire was designed containing questions about the importance or intensity of each criterion. These questions were structured to collect experts' opinions in qualitative terms (e.g., "low," "medium," "high"). 

2. Collecting Experts' Opinions:

   Experts' feedback was gathered through the completion of questionnaires or interviews. These experts included specialists and researchers with sufficient experience in the relevant field. 

3. Analyzing Collected Data:

   The collected data were analyzed to identify overall trends in the opinions. For instance, the number of responses assessing each criterion at various levels of importance was examined. 

4. Defining Initial Membership Functions:

   Based on the analyzed data, initial membership functions were defined using common function types (such as linear decrease, or linear increase). The parameters of these functions (e.g., minimum, maximum, and peak points) were adjusted according to the questionnaire results and experts’ feedback. 

5. Validation and Refinement:

   Finally, to ensure validity, the designed membership functions were reviewed and refined by the experts to confirm their alignment with the actual opinions and the problem's real-world conditions. 

We hope these explanations have addressed your concerns and clarified the process.

(2)   How are the maximum and minimum values of the fuzzy function determined?

Response: In this study, the maximum and minimum values ​​were determined by experts and specialists. Also, decreasing and increasing linear fuzzy functions were used. The Fuzzy Linear transformation function applies a linear function between the user-specified minimum and maximum values. Anything below the minimum will be assigned a 0 (definitely not a member) and anything above the maximum a 1 (definitely a member). The blue line in the image below represents a positive sloped linear transformation with a minimum of 30 and a maximum of 80. Any value below 30 will be assigned a zero and anything above 80 a 1.

If the minimum is greater than the maximum, a negative linear relationship (a negative slope) is established. The red line in the image below represents a negative slope linear transformation. Any value less than 30 will be assigned a 1 and anything above 80 a 0.

Where the slope of the line is increasing or decreasing defines the transition zone (between 30 to 80 in the image below).

(3)   Why is the fuzzy function for the land use criterion (how is this criterion defined?) user-defined, and why is its weight factor significantly larger than those of the other seven criteria? Is this reasonable?

Response: The fuzzy function for the land use criterion is defined by the user because this criterion is diverse and dependent on the specific conditions of the project. Land use can include various types such as residential, commercial, and agricultural, with the importance of each varying depending on the project’s goals and local conditions. Also, the precise definition of a fuzzy function requires detailed information about the study area, including land use patterns, constraints, and local regulations. This information is often specifically collected and analyzed by the user. Therefore, the user is the best person to determine the appropriate membership function based on their specific needs and priorities.

The weights of the criteria were determined by experts and are highly reliable. Land use has the highest weight in the Bioretention Basin type of LID-BMP and Green Roof, while the distance from the street criterion has the highest weight in Grassland, and the slope criterion holds the highest weight in Porous Pavement.

(4)   Does the sum of the weighting factors for all criteria for a selected LID-BMP (e.g., Bioretention Basin) equal one?

 Response: Thank you for your precise comment. Yes, the sum of the weights of all criteria for each LID-BMP type equals one. In this study, the sum of the weights for the Green Roof was greater than one, which was due to an error where the weight for the rainfall criterion was written as 0.232 instead of 0.231. This issue has been corrected in the new version (Please check Table 6).

Comment 9: It is recommended to include more detailed explanations of the processes used to generate Table 7, along with additional discussion on how this table is utilized. Furthermore, brief descriptions of the TerrSet software and the Gamma operator would be helpful.

Response 9: Thank you for your insightful comment. We have revised the manuscript accordingly. Detailed explanations of the processes used to generate Table 7 have been added, including the methodology for collecting expert opinions and the analysis to determine the priorities of land use types for each LID-BMP. Additionally, a more comprehensive discussion on how Table 7 is utilized in the research has been provided. 

Furthermore, brief descriptions of the TerrSet software and the Gamma operator have been included. These additions clarify the role of TerrSet in fuzzifying the land use layer and the importance of the Gamma operator in aggregating criteria layers effectively (Page 13 and 14, Line 411-441 and Line 446-452).

Comment 10: The results in Table 8 are based on cases from China. Should these results be included in this paper? Were these data used in this research? Please clarify.

Response 10: Thank you for your comment. Table 8 presents results from a study conducted in China, which was referenced in this paper to demonstrate the general effectiveness of LID-BMPs in reducing stormwater runoff. These results were not directly used in the calculations or modeling of this research; instead, they were included to provide a broader context and support the rationale for selecting LID-BMPs as effective methods for stormwater management. 

The parameters and data used in this research are based on local conditions and specific modeling inputs, which are detailed in the methodology section. However, the findings from the referenced study align with the principles applied in this research and serve to strengthen the discussion of LID-BMP effectiveness. We have clarified this distinction in the revised manuscript to avoid any confusion.

Comment 11: Land use classes are divided into four categories in Table 9, while Table 7 includes 11 different land use categories. Could you explain the rationale for this difference?

Response 11: Thank you for your question. The land use categories in Table 9 represent classifications derived from satellite imagery, specifically aimed at illustrating the changes in land use over the past 22 years in the study area. These categories were simplified for ease of analysis in the context of temporal changes. 

In contrast, the land use categories in Table 7 are part of a detailed map used specifically for the siting of LID-BMPs. These categories are more granular and were defined based on the requirements of the LID-BMP suitability analysis. The difference in the number of categories reflects the distinct purposes and data sources of the two tables. We hope this clarification addresses your concern.

Comment 12: To analyze runoff changes for different design storms using LID-BMP methods, the SCS-CN rainfall-runoff model was employed to calculate infiltration loss based on CN values. How much can CN values be reduced for each LID-BMP method, and were these reductions used in the simulation model? Additionally, how many input variables were required for the simulation?

Response 12: Thank you for your thoughtful comment. LID-BMPs (Low Impact Development - Best Management Practices) effectively reduce runoff by increasing infiltration and delaying surface water flow, thereby lowering the Curve Number (CN). The degree of reduction depends on several factors, including the type of LID-BMP employed, site-specific conditions, soil type, and the initial hydrological state of the area. Consistent with the guidelines provided by the USDA NRCS (2004) and various field studies, features like bioretention basins and grass swales typically reduce CN values by 10 to 15 points when compared to conventional impervious surfaces.

Porous pavements, another widely-used LID practice, have variable impacts on CN reduction based on the initial CN value of the surface and the pavement's permeability. For instance, as highlighted by Madrazo-Uribeetxebarria et al. (2023), the use of permeable pavements can result in CN reductions ranging from 5 to 15 points for urban surfaces with initially high CN values (e.g., above 88).

Green roofs, while less impactful on CN reduction compared to bioretention or porous pavements, still contribute modestly. Liu et al. (2020) investigated their efficiency and found potential reductions of up to 6 points under optimal conditions. This highlights their complementary role in urban hydrological management, especially when combined with other LID-BMPs.

It is important to note that the exact reduction in CN values depends on site-specific modeling inputs such as land use, soil type, and hydrological condition. Accurate simulation models that account for these variables can enhance the precision of CN estimates and the effectiveness of LID-BMPs in stormwater management strategies.

References:

• Madrazo-Uribeetxebarria, E., Garmendia Antín, M., Almandoz Berrondo, J., & Andrés-Doménech, I. (2022). Modelling runoff from permeable pavements: a link to the curve number method. Water, 15(1), 160.
• Liu, W., Feng, Q., Chen, W., & Wei, W. (2020). Assessing the runoff retention of extensive green roofs using runoff coefficients and curve numbers and the impacts of substrate moisture. Hydrology Research, 51(4), 635-647.
• USDA Natural Resources Conservation Service. (2004). Urban hydrology for small watersheds (TR-55). U.S. Department of Agriculture. Retrieved from http://www.nrcs.usda.gov/Internet/FSE_Documents/stelprdb1044171.pdf

Comment 13: Section 2.3.2.1 mentions that eight sub-basins were defined, but only five sub-basins are discussed in Table 10. Please explain this discrepancy.

Response 13: Thank you for your attention to detail. We appreciate the reviewer's careful attention. To ensure accurate and comprehensive hydrological analyses, it was necessary to consider the entire watershed, including the upstream mountainous areas where the main river originates. Therefore, in the initial stages of the study, eight sub-basins were defined, encompassing both upstream and downstream areas. However, the ultimate goal of this study was to identify suitable locations for implementing LID-BMPs as a means to mitigate the impacts of land use changes. Since the selected LID-BMPs could only be installed and applied in urban downstream sub-basins, the final stages of the analysis, including the data presented in Table 10, focused exclusively on the five urban downstream sub-basins. This approach ensured that the study remained targeted on areas where management practices could be practically implemented.

Comment 14: It is strongly recommended to rewrite the conclusion to highlight the key findings of this research and suggest actionable recommendations for decision-makers based on the study’s results.

Response 14: Thank you for your insightful comment. We have completely revised the conclusion to address your suggestion. The new version now emphasizes the key findings of the research and provides actionable recommendations for decision-makers based on the study’s results.  We believe the updated conclusion better reflects the practical implications of the research and offers clear guidance for implementing the findings in real-world scenarios (Please check section 5).

Reviewer 2 Report

Comments and Suggestions for Authors

The manuscript under the title “The effects of LID-BMPs in reducing stormwater caused by land use changes in urban areas: Case study in Tehran City, Iran” raises very important and current issues related to the validity of using LID-BMPs. Its topic is interesting, current and within the scope of the Land journal. However, I have a few comments that the authors should consider. Please find some details below.

1. In the introduction, the authors focused on the positive aspects of using LID-BMPs. However, there is no consideration of their negative sides. For example, in Table 1, the authors indicated that the use of such systems can reduce the costs of drainage infrastructure. However, there are studies showing that in some cases, extending stormwater systems with devices that are designed to restore the original water conditions can be expensive and vastly exceed the costs of traditional drainage systems. Another problem may be the lack of space for the development of such systems, especially in areas characterized by significant population density. Ground and water conditions are also important. Please include these aspects in the description in the Introduction. In the rest of the paper, there are brief references to these issues, but this should be emphasized at the beginning of the manuscript.

2. The text does not clearly indicate which years are being compared. According to Figure 2, it is 2002 and 2022, and the analysis covers a 20-year period. However, the manuscript text indicates that the authors analyzed conditions in the year 2000. The year 2000 appears in the description in all subsequent sections. Please standardize the data or explain the discrepancies.

3. Is the trend line drawn based on just three points (Figure 5) sufficiently reliable? Please add a justification in the text. Please also indicate in the figure to which stations each point refers.

4. The authors claim to have used multi-criteria analysis to select devices (Section 2.3.4), but provide essentially no details beyond which devices were selected. How were the individual devices evaluated, and what other devices were considered in addition to those selected? What subcriteria were used to evaluate them? Who evaluated them? Please add this information in the text of the manuscript.

5. How many people completed the questionnaire in the case of the AHP method? How were the final results obtained? Based on individual judgments or ratings?

6. Please label the vertical axes in the graphs. Giving only units is misleading. Please also refer in the text to specific numerical values ​​that are included in the figures. The current description of the figures in section 3 is very general and not very related to the research results.

7. Section 4.1 - This section does not contain discussion elements. It is a repetition of information that appeared earlier in the manuscript. Therefore, this subsection can be removed. Instead, please expand on the comparison of the research results to those presented by the other authors. Please describe in more detail what the differences are.

8. Please also add directions for further research in section 4 or 5.

9. Please also consider the following issues:

- Some of the descriptions in Figure 1 are very illegible. Please enlarge them.

- Abbreviations should be explained in the first place they appear in the text. For example, in the title of section 2.3.1 (line 154) the abbreviation LULC appears, which is explained in the text in line 155.

- For equations in section 2, please add references where possible (e.g. to eq. (3)).

- The symbols below equation (7) are different from those in this equation. In some places, the authors use subscripts, while in other places, including the main text, they are not. Please standardize the symbols throughout the manuscript.

- Please check the text in lines 370-372.

- Table 11 has the wrong title. Likewise, Figure 16.

- There are minor formatting errors in the manuscript, e.g. in tables and equations. Please adjust the formatting to the guidelines.

Best regards

Author Response

Reviewer #2:

Dear reviewer

We appreciate your time and effort for giving valuable comments on our paper. Indeed the changes we made to this paper on the basis of your questions, have added to the scientific value of the paper. Following you see Responses to your questions in the same order of appearance.

The manuscript under the title “The effects of LID-BMPs in reducing stormwater caused by land use changes in urban areas: Case study in Tehran City, Iran” raises very important and current issues related to the validity of using LID-BMPs. Its topic is interesting, current and within the scope of the Land journal. However, I have a few comments that the authors should consider. Please find some details below.

 Comment 1: In the introduction, the authors focused on the positive aspects of using LID-BMPs. However, there is no consideration of their negative sides. For example, in Table 1, the authors indicated that the use of such systems can reduce the costs of drainage infrastructure. However, there are studies showing that in some cases, extending stormwater systems with devices that are designed to restore the original water conditions can be expensive and vastly exceed the costs of traditional drainage systems. Another problem may be the lack of space for the development of such systems, especially in areas characterized by significant population density. Ground and water conditions are also important. Please include these aspects in the description in the Introduction. In the rest of the paper, there are brief references to these issues, but this should be emphasized at the beginning of the manuscript.

Response 1: Many thanks for this precise and nice comment. Based on your suggestion, the introduction has been revised to address the challenges associated with LID-BMP systems. Specifically, the following points have been included: potential high costs of development compared to traditional drainage systems, space limitations in densely populated areas, and the impact of ground and water conditions. 

These revisions aim to provide a more balanced perspective by highlighting both the advantages and limitations of these systems. We hope these changes meet your expectations (Page 2, Line 59-76).

Comment 2: The text does not clearly indicate which years are being compared. According to Figure 2, it is 2002 and 2022, and the analysis covers a 20-year period. However, the manuscript text indicates that the authors analyzed conditions in the year 2000. The year 2000 appears in the description in all subsequent sections. Please standardize the data or explain the discrepancies.

Response 2: Thank you for pointing out this inconsistency. It was a typographical error, and we sincerely apologize for any confusion caused. The correct time frame for the analysis is 2000 to 2022, as reflected in the manuscript text and Figure 2. We have reviewed the manuscript thoroughly to ensure consistency across all sections and corrected any discrepancies. We appreciate your attention to detail and your valuable feedback (Please check Figure 2).

Comment 3: Is the trend line drawn based on just three points (Figure 5) sufficiently reliable? Please add a justification in the text. Please also indicate in the figure to which stations each point refers.

Response 3: Thank you for your valuable comment and suggestion regarding the trend line in Figure 5. We have revised the manuscript to address your concern. Specifically, we have added a justification in the text, explaining the selection of the three points and their relevance to the analysis (Page 8, Line 264-270).

Additionally, we have modified Figure 5 to clearly indicate the stations to which each point refers, as per your suggestion (Please check Figure 5).

Comment 4: The authors claim to have used multi-criteria analysis to select devices (Section 2.3.4), but provide essentially no details beyond which devices were selected. How were the individual devices evaluated, and what other devices were considered in addition to those selected? What sub-criteria were used to evaluate them? Who evaluated them? Please add this information in the text of the manuscript.

Response 4: Thank you for your insightful comment regarding the selection process of LID-BMPs. In response, we have revised the manuscript to provide additional details about the multi-criteria analysis used in Section 2.3.4 (Please check Section 2.3.4).

Comment 5: How many people completed the questionnaire in the case of the AHP method? How were the final results obtained? Based on individual judgments or ratings?

Response 5: Thank you for your thoughtful comment regarding the application of the AHP method. We have revised the manuscript to address your concerns and provide further details.

In the revised text, we have clarified that a total of 25 experts participated in completing the AHP questionnaire. These experts were selected based on their expertise in water resources engineers, urban planners, environmental civil engineering, GIS, and environmental engineering’s. The final results were derived by aggregating the individual judgments using the geometric mean method to ensure a balanced and representative evaluation. Additionally, we have noted that the consistency ratio (CR) was calculated, and all values were within the acceptable threshold, confirming the reliability of the judgments (Page 12 and 13, Line 393-404).

Comment 6: Please label the vertical axes in the graphs. Giving only units is misleading. Please also refer in the text to specific numerical values ​​that are included in the figures. The current description of the figures in section 3 is very general and not very related to the research results.

Response 6: Thank you for your nice comment. Based on your suggestion, the necessary revisions have been made. The vertical axes in the graphs have been labeled (regarding Figure 8, the vertical axis represents two parameters: elevation and precipitation. To avoid confusion, these parameters have been described in the figure legend instead of labeling them directly on the vertical axis), and specific numerical values from the figures have been incorporated into the text for better clarity and relevance. These updates have been added to the manuscript accordingly (Page 16, Line 487-459; Page 17, Line 398-516; and Page 17 and 18, Line 529-552).

Comment 7: Section 4.1 - This section does not contain discussion elements. It is a repetition of information that appeared earlier in the manuscript. Therefore, this subsection can be removed. Instead, please expand on the comparison of the research results to those presented by the other authors. Please describe in more detail what the differences are.

Response 7: Thank you for your valuable and insightful comment. Based on your suggestion, Section 4.1 has been revised accordingly. The repeated information has been removed, and the discussion has been expanded to include a detailed comparison of our research findings with those of other studies (Please check Section 4.1).

Comment 8: Please also add directions for further research in section 4 or 5.

Response 8: Thank you for your completely accurate and valuable comment. Based on your suggestion, directions for further research have been added to the end of Section 5 (Page 24 and 25, Line 735-741).

Comment 9: Please also consider the following issues:

- Some of the descriptions in Figure 1 are very illegible. Please enlarge them.

Response: Thank you for your comment. Based on your suggestion, Figure 1 has been redesigned to improve legibility (Please check Figure 1).

 - Abbreviations should be explained in the first place they appear in the text. For example, in the title of section 2.3.1 (line 154) the abbreviation LULC appears, which is explained in the text in line 155.

Response: Thank you for your valuable comment. Based on your suggestion, all abbreviations have been explained at their first appearance throughout the manuscript (For example, please check page 5, lines 163 and 164.).

 - For equations in section 2, please add references where possible (e.g. to eq. (3)).

Response: Thank you for your helpful comment. Based on your suggestion, references have been added to all relevant equations throughout the manuscript. Equations 4, 5, and 6 are derived from the study by Ghahraman and Abkhezr, as mentioned in line 319 (Page 7, Line 225 and 238; Page 11, Line 350).

 - The symbols below equation (7) are different from those in this equation. In some places, the authors use subscripts, while in other places, including the main text, they are not. Please standardize the symbols throughout the manuscript.

Response: Thank you for your careful and valuable comment. Based on your suggestion, the symbols throughout the manuscript have been standardized for consistency, including the subscripts, as per your feedback (Page 11, Line 345-350).

 - Please check the text in lines 370-372.

Response: Thank you for your comment. The text in lines 370-372 has been checked and rewritten. The revised text can now be found in lines 439-441 of the updated manuscript.

 - Table 11 has the wrong title. Likewise, Figure 16.

Response: Thank you for your careful and excellent comment. The incorrect titles for Table 11 and Figure 16 have been replaced with the correct ones. This was a typographical error, and we appreciate your attention to detail in pointing it out (Please check the title of Table 11 and Figure 16).

 - There are minor formatting errors in the manuscript, e.g. in tables and equations. Please adjust the formatting to the guidelines.

Response: Thank you for your comment. In the new version of the manuscript, Table 11 has been removed based on the feedback from other reviewers. Additionally, the font for the equations has been checked and standardized.

Reviewer 3 Report

Comments and Suggestions for Authors

Dear authors;

This is a very interesting paper, and I enjoyed reading it.

Nevertheless, I have some concerns about the paper.

Firstly, TOC is calculated by Kirpich method. In hydrology, by usage of this method, we calculate the time of concentration for the basin. In this paper is shown that the TOC is calculated by usage of the "So -the main channel slope in meters per meter" (line 228-230). The slope of the channel is not the same as the slope of the basin, and the Kirpich method suggests to use the basin slope. The channel slope can be used when the overall slope of the basin and channel are similar. In this research, there is a difference between the channel slope and basin slope and therefore the basin slope should be estimated. The authors should consider this and evaluate TOC for the overall basin. Since the DEM is also used, the basin slope should be analyzed too. Please, provide the description of the TOC calculation procedure.

The second problem is in the description of the SCS-CN unit hydrograph method (line 309). The SCS-CN method is not an "experimental" method, it is an empirical method. It is a big mistake to present the this method as experimental.

Authors should be more careful about the usage of hydrological terminology and calculation.

Author Response

Reviewer #3:

Dear reviewer

We appreciate your time and effort for giving valuable comments on our paper. Indeed the changes we made to this paper on the basis of your questions, have added to the scientific value of the paper. Following you see Responses to your questions in the same order of appearance.

This is a very interesting paper, and I enjoyed reading it.

Response: Thank you for your positive feedback. We are glad to hear that you found the paper interesting and enjoyable to read.

Comment 1: Firstly, TOC is calculated by Kirpich method. In hydrology, by usage of this method, we calculate the time of concentration for the basin. In this paper is shown that the TOC is calculated by usage of the "So -the main channel slope in meters per meter" (line 228-230). The slope of the channel is not the same as the slope of the basin, and the Kirpich method suggests to use the basin slope. The channel slope can be used when the overall slope of the basin and channel are similar. In this research, there is a difference between the channel slope and basin slope and therefore the basin slope should be estimated. The authors should consider this and evaluate TOC for the overall basin. Since the DEM is also used, the basin slope should be analyzed too. Please, provide the description of the TOC calculation procedure.

Response 1: We sincerely appreciate your insightful comment and completely agree with your observation regarding the importance of using the basin slope in the Kirpich method. To address this, we would like to clarify our methodology:

In our study, the basin was divided into 8 sub-basins to enhance the accuracy of the hydrological analysis. For each sub-basin, we calculated both the basin slope and the main channel slope. The analysis demonstrated that there were negligible differences between these two parameters within individual sub-basins, except for sub-basin A. Consequently, we opted to use the main channel slope to calculate the specific TOC for each sub-basin, as it provided a practical and representative measure of the flow-driving characteristics within the sub-basins.

Table 1. Comparison of the average channel slope and basin slope for sub-basins

Sub-basin	A	B	C	Dint	E	F	G	H
Basin slope (%)	47.79	41.11	45.03	20.21	24.14	6.30	4.31	13.16
Channel slope (%)	44.93	39.87	43.67	19.30	23.34	6	3.93	12.38
Difference (%)	2.86	1.24	1.36	0.91	0.80	0.30	0.38	0.78

While we acknowledge that using the overall basin slope is ideal in cases of significant discrepancies, the localized similarity between basin slope and channel slope in our sub-basins, excluding sub-basin A, justifies this approach. We will ensure that this methodological detail is explicitly clarified in the manuscript to address potential concerns (Please check section 2.3.2.4).

The following references have utilized channel slope in their studies.

• Kamath, M. A., Varun, V. M., Dwarakish, G. S., Kavyashree, B., & Shwetha, H. R. (2011). Kirpich and williams times of concentration in musle: A case study. ISH Journal of Hydraulic Engineering, 17(2), 1-13.
• Adaba, C. S., & Agunwamba, J. C. (2014). Adequacy of Drainage Channels in a Small Urban Watershed in Nigeria. Nigerian Journal of Technology, 33(4), 585-594.
• Alizadeh, A. (2020). Principles of Applied Hydrology. Imam Reza International University Press.

Comment 2: The second problem is in the description of the SCS-CN unit hydrograph method (line 309). The SCS-CN method is not an "experimental" method, it is an empirical method. It is a big mistake to present the this method as experimental.

Response 2: Thank you for your careful and insightful comment. You are absolutely right, and I apologize for the typo. The SCS-CN method is indeed an empirical method, not an experimental one. This has been corrected in the revised version of the manuscript (Page 11, Line 343). 

Comment 3: Authors should be more careful about the usage of hydrological terminology and calculation.

Response 3: Thank you for your attention to detail. In the revised version, the necessary corrections have been carefully reviewed and checked throughout the text.

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

Thank you for considering my comments.