Conjunctive Water Resources Management in Densely Urbanized Karst Areas: A Study in the Sete Lagoas Region, State of Minas Gerais, Brazil
and Fernando António Leal Pacheco 4,*Round 1
Reviewer 1 Report
1) The explanation for the estimation of the reference flow conditions, given in the manuscript is not satisfactory. It is stated that it was calculated based on flow duration curves but no exact description of how the human influence on the flow regime was extracted in order to simulate the reference conditions, is not given. Please amend this.
2) The authors state that modelling downscaling occurred in the study area and particularly in the Marinheiro sub-basin. What was the grid cell size of the model in both cases (original and Marinheiro models)? Was this a real downscaling or it was another run of the model in an area with discharge measurements available? Were the HRUs different between the two models?
3) The authors state in page 11, lines 354-357: ‘The duration curve of Marinheiro catchment indicates that base flows are permanently (90% of the time) equal or greater than 0.06 m3 s–1 (1.89 hm3 year–1). These flows can be seen as ecologic and therefore not proper for 356 uses such as public water supply…’. How this threshold can be considered as appropriate ecological flow? Is there a bibliographic or other justification for this statement?
4) The model’s quality indices that are presented in the methodological section of the manuscript are not provided in the results. Please give the estimated PBIAS and NSE values for both the calibration and validation simulations and comment on them.
5) The discussion section needs significant improvement. The authors should try to present and comment on all the different findings and aspects of their work. They should also attempt to propose more and specific management measures to avoid water overexploitation or eliminate its impacts. The outcomes regarding the ecological and reference flows should be analytically discussed and justified based on the international and local experience.
Author Response
Response to Reviewer #1
Note: The changes to the text are shaded in yellow here and in the revised manuscript.«, for better identification.
The explanation for the estimation of the reference flow conditions, given in the manuscript is not satisfactory. It is stated that it was calculated based on flow duration curves but no exact description of how the human influence on the flow regime was extracted in order to simulate the reference conditions, is not given. Please amend this.
We thank the reviewer for this pertinent observation. Reference stream flows may have multiple meanings dependent from the context. In hydrologic modeling, the term “reference stream flow” is meant to describe stream flow conditions in the absence of human interference. In water resources management, however, it is used to describe specific flows, such as the Q7,10, which is the minimum flow of 7 days duration and 10 years return period, with a 10% risk of not being reached, or the Q90, which corresponds to a flow with 90% probability of being exceeded in time. In our study, the reference stream flows adhere to the water resources management concept. In order to clarify our point, we added the following text to the revised manuscript.
A reference stream flow launches the upper limit of water uses in a water course. According to Harris et al. [48], the application of a reference flow favors the protection of rivers, because the grants for stream water diversion in that context are based on low risk base flows. However, the set up of reference flows is also an obstacle to the implementation of a grant system [49]. The most common reference values are [50]: Q7,10, which is the minimum flow of 7 days duration and 10 years return period, with a 10% risk of not being reached; Q90, which corresponds to a flow with 90% probability of being exceeded in time. In Brazil, states have adopted different criteria for setting up reference flows for granting, but did not present justifications for the adoption of specific values. In Minas Gerais state, the Mining Institute of Water Management (IGAM; http://www.igam.mg.gov.br/) defined threshold values for the Marinheiro catchment, namely: Q7,10 = 0.029 m3 s–1; Q90 = 0.075 m3 s–1. The comparison of IGAM values with counterparts determined by the JAMS J2000 model represents additional performance criteria.
Besides the use in model performance assessment, the reference stream flows…
2) The authors state that modelling downscaling occurred in the study area and particularly in the Marinheiro sub-basin. What was the grid cell size of the model in both cases (original and Marinheiro models)? Was this a real downscaling or it was another run of the model in an area with discharge measurements available? Were the HRUs different between the two models?
The HRU delineation is an overlay analysis (NOT a cross tabulation) of different layers, which can comprise different resolutions. In our case, the overlay was based on the input map resolutions, for example the digital elevation model at 10 m resolution or the land use map at 12.5 m resolution. These resolutions did not change from the original to the Marinheiro model. The downscaling was another run of the model in an area with discharge measurements available. The HRU were the same in the original and Marinheiro models.
3) The authors state in page 11, lines 354-357: ‘The duration curve of Marinheiro catchment indicates that base flows are permanently (90% of the time) equal or greater than 0.06 m3 s–1 (1.89 hm3 year–1). These flows can be seen as ecologic and therefore not proper for 356 uses such as public water supply…’. How this threshold can be considered as appropriate ecological flow? Is there a bibliographic or other justification for this statement?
Yes. There are various references to the use of Q90 as ecological flow in Brazil. In the revised text, we clarified this point as follow:
The most common reference values are [50]: Q7,10, which is the minimum flow of 7 days duration and 10 years return period, with a 10% risk of not being reached; Q90, which corresponds to a flow with 90% probability of being exceeded in time. They are both seen as ecological flows, meaning that any granted stream water diversion needs to permanently ensure these or larger flows in the target river [51,52].
4) The model’s quality indices that are presented in the methodological section of the manuscript are not provided in the results. Please give the estimated PBIAS and NSE values for both the calibration and validation simulations and comment on them.
We believe the reviewer missed something here. Please see lines 288-291 in the original manuscript, where the following sentence was written: “The analysis of model performance was based on the PBIAS and NSE indices. The calculated PBIAS were –9.50 (calibration period), –3.65 (validation period) and 3.80 (whole period), indicating very good performance within the whole period (see reference levels in Appendix D). As regards NSE, the homologous results were 0.58, 0.67 and 0.64, indicating good to fair performance.”
5) The discussion section needs significant improvement. The authors should try to present and comment on all the different findings and aspects of their work. They should also attempt to propose more and specific management measures to avoid water overexploitation or eliminate its impacts. The outcomes regarding the ecological and reference flows should be analytically discussed and justified based on the international and local experience.
The discussion was improved as suggested. Several new sentences and references were added to the revised version in this section. Please see them in the yellow-shaded sentences.
Reviewer 2 Report
The manuscript focuses on the hydrologic modeling of and ungauged watershed the Marinheiro catchment (state of Minas Gerais, Brazil). The paper is interesting and presents a good statistical analysis, however, in my opinion there are few drawbacks in the paper, which can be eliminated by carrying out some major revisions following the list of comments below.
MAIN CONCERNS
As to what concern the methodology, the authors do not provide a deep description of some procedures used in the paper. Can the authors provide more information about the online platform HRU-WEB and about the spatially distributed JAMS J2000 hydrologic model? For example, which equations have been considered for the evaluation at basin scale of the different components of the water balance?
Lines 217-219: The authors stated that “In the first step, data on daily precipitation, minimum, medium and maximum air temperature, wind speed, relative humidity and sun hours per day were compiled and corrected for discrepant and / or absent values”. Can the authors better explain how the data were compiled and corrected?
Can the authors add a short description of the PBIAS and NSE indices? A reference for this indices is also needed
Is it possible to add a graphical technique to evaluate the model performance? It would be great to see a figure with the comparison of the simulated and measured discharges
Can the authors provide a Figure similar to Figure 6 but only for the Marinheiro catchment?
MINOR COMMENTS
Figure 5: If the authors speak about 4 step they must add the 4th step in this figure
Figure 6: Change the symbol of percolation in the figure (ES must be S)
Figure 7: Precipitation instead of Precipittion
Figure 7: avoid to overlap precipitation and discharge
Table 2: Check the residual values. E.g. in January it must be 0.16
Author Response
Response to Reviewer #2
Note: The changes to the text are shaded in yellow here and in the revised manuscript.«, for better identification.
The manuscript focuses on the hydrologic modeling of and ungauged watershed the Marinheiro catchment (state of Minas Gerais, Brazil). The paper is interesting and presents a good statistical analysis, however, in my opinion there are few drawbacks in the paper, which can be eliminated by carrying out some major revisions following the list of comments below.
We very much appreciate the nice general comments on our manuscript. We did our utmost to thoroughly address your comments. We hope you will be satisfied with the revised version.
MAIN CONCERNS
As to what concern the methodology, the authors do not provide a deep description of some procedures used in the paper. Can the authors provide more information about the online platform HRU-WEB and about the spatially distributed JAMS J2000 hydrologic model? For example, which equations have been considered for the evaluation at basin scale of the different components of the water balance?
In the revised manuscript we added or improved the sentences related to HRU-WEB and JAMS J2000, to answer positively the reviewer comment.
The improved sentence about the HRU-WEB is:
“The online platform HRU-WEB (http://intecral.uni-jena.de/hruweb-qs/) was used to delineate the homogeneous hydrologic response units (HRU). The HRU are used as modeling entities that have the same pedological, lithological, topographical and land use/land cover characterizations, and are heterogeneous from each other. They are connected by a topological routing scheme [43]. The lateral water flow is simulated allowing a fully explicit spatial discretization of hydrologic response within the modeled catchment. However, the delineation of HRUs may not account for karst heterogeneity. Nevertheless, the model can be calibrated so that the observed and modeled stream flows match well. This HRU-WEB platform is embedded with tools to intersect the digital elevation model with soil, geology and land use and cover maps producing the HRUs as output. Each HRU holds a specific identification number, centroid coordinates, and connection codes to adjacent HRUs or specific water lines [44].”
A new sentence relative to JAMS J2000 is:
“The J2000 is a process based spatially explicit hydrological model, which simulates eco-hydrological processes on the river basin scale. The method was developed by Krause [45] and is a part of modular and object oriented modeling system called JAMS (Kralisch and Krause, 2006). Altogether, the JAMS J2000 framework contains different environmental models and a plethora of components to create custom tailored models for different research questions. In addition, JAMS possess modules data preparation, analysis and visualization. The full inventory of hydrologic modules used in this study is listed in Appendix A. It is beyond the scope of this paper to describe them in detail, especially their mechanics. Readers are invited to consult the original works.”
Lines 217-219: The authors stated that “In the first step, data on daily precipitation, minimum, medium and maximum air temperature, wind speed, relative humidity and sun hours per day were compiled and corrected for discrepant and / or absent values”. Can the authors better explain how the data were compiled and corrected?
The sentence was rephrased to clarify how we prepared the climatic and hydrometric data for JAMS J2000 model. The revised sentence is reproduced here.
“In the first step, the variables precipitation, temperature, relative humidity, hours of sunshine, wind speed, as well as daily stream flow data, compiled from the weather and hydrometric stations, were organized in a series of Excel spreadsheets, namely listed in ascending order of time. In turn, these spreadsheets were submitted to the online platform INTECRAL RBIS (http://leutra.geogr.uni-jena.de/intecralRBIS) for conversion into files in the specific format of JAMS J2000.”
Can the authors add a short description of the PBIAS and NSE indices? A reference for this indices is also needed
The following description was added to the revised manuscript to provide a description and references for the PBIAS and NSE indices:
“According to Gupta et al. [47], the PBIAS estimates the percentage trend of simulated data to be higher or lower than the observed data and can be described by the following equation:
x 100 (1)
where PBIAS is the percentage of bias (%), yi is the simulated flow (m³/s) and oi is the observed flow (m³/s). A PBIAS = 0 occurs for a hydrological model with optimal performance. Positive or negative values indicate, respectively, that the model overestimates or underestimates the simulated flows. The NSE and LNSE coefficients are equated as follows [48]:
(3)
(4)
where “ln” represents the natural logarithm and oi, omed, yi and ymed represent, respectively, the observed flow, the average observed flow, the simulated flow and the mean simulated flow (m³/s). The values of NSE and LNSE (dimensionless) can vary from -∞ to 1. The closer to 1, the greater the adjustment between the simulated and observed values. Results below 0 indicate that the mean observed values are more representative than the values predicted by the model.”
Is it possible to add a graphical technique to evaluate the model performance? It would be great to see a figure with the comparison of the simulated and measured discharges
We only have that information on a monthly basis, that is described in Table 2. Presentation of a figure to illustrate this data would be a repetition.
Can the authors provide a Figure similar to Figure 6 but only for the Marinheiro catchment?
For the sake of consistency with the other maps, we prefer to keep Figure 6 as is.
MINOR COMMENTS
Figure 5: If the authors speak about 4 step they must add the 4th step in this figure
Step 4 is indicated in Figure 5
Figure 6: Change the symbol of percolation in the figure (ES must be S)
Changed
Figure 7: Precipitation instead of Precipittion
Corrected
Figure 7: avoid to overlap precipitation and discharge
Done
Table 2: Check the residual values. E.g. in January it must be 0.16
The residuals were checked (see yellow-shaded cells in Table 2).
Author Response File: 
Author Response.pdf
Round 2
Reviewer 1 Report
The authors followed the reviewers' comments and improved the manuscript significantly
Reviewer 2 Report
In the previous reviews, my main comments referred to the methodology. I recognize that in this revised manuscript almost all my suggestions have been addressed and incorporated. Therefore, I think that, in the present form, the paper can be published in Sustainability.
