the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 31 Jan 2023
Monetizing the role of water in sustaining watershed ecosystem services using a fully integrated subsurface–surface water model
Abstract. Water is essential for all ecosystem services, yet a comprehensive assessment of total (overall) water contributions to ecosystem services production has never been attempted. Quantification of the many ecosystem services impacted by water demands integrated hydrological simulations that implicitly characterize subsurface and surface water exchange. In this study, we use a fully integrated hydrological model—HydroGeoSphere (HGS)—to capture changes in subsurface water, surface water, and evapotranspiration (green water) combined with the economic valuation approach to assess ecosystem services over an 18-year period (2000–2017) in a mixed-use but predominantly agricultural watershed in eastern Ontario, Canada. Using the green water volumes and ecosystem services values as inputs, we calculate the marginal productivity of water, which is $0.45 per m3 (in 2022 Canadian dollars). The valuation results show that maximum green water is used during the dry years, with a value of $1.16 billion during a severe drought that struck in 2012. The average product of water for ecosystem services declines during the dry years. Because subsurface water is a major contributor to the green water supply, it plays a critical role in sustaining ecosystem services during drought conditions. For instance, during the 2012 drought, the subsurface water contribution to green water was estimated at $743 million, making up 72 % of the total value of green water used in that year. Conversely, the surface water contributions in green water provision over the modeling period are comparatively miniscule. This study informs watershed management on the sustainable use of subsurface water during droughts and provides an improved methodology for watershed-based integrated management of ecosystem services.
- Preprint
(3156 KB) - Metadata XML
- BibTeX
- EndNote
Status: final response (author comments only)
-
RC1: 'Comment on hess-2023-25', Anonymous Referee #1, 07 Mar 2023
The scientific importance of the article is high. Congratulations to the authors! They covered a very interesting and important topic. As a novelty, they tried to link ecosystem services derived from integrated hydrological model results to monetary evaluation.
Grammatical and technical errors are not typical, the article is of high quality from a stylistic point of view.
The written part of the publication is fine. I feel it necessary to place some supporting literature references in some places. I marked them in the attached document.
There are parts in the description of the modeling work that are not completely understandable, and it is essential to clarify them. I marked them in the attached document.
After the clarifications and suggested references have been replaced, the article can definitely be recommended for publication.-
AC1: 'Reply on RC1', Tariq Aziz, 18 Apr 2023
Response to reviewer’s comments
Manuscript number (hess-2023-25)Note: Below are the reviewer’s comments in black, and our responses in blue.
Referee#1 comments:
The scientific importance of the article is high. Congratulations to the authors! They covered a very interesting and important topic. As a novelty, they tried to link ecosystem services derived from integrated hydrological model results to monetary evaluation.
Grammatical and technical errors are not typical, the article is of high quality from a stylistic point of view. The written part of the publication is fine.
Thank you for taking the time to review our paper and for your positive evaluation! We are glad to hear that you found our topic interesting and important. We appreciate your acknowledgment of the scientific significance of our work, and your compliments on the quality of our writing. This feedback is very valuable to us as we continue to refine our research. Thank you again for your review.
I feel it necessary to place some supporting literature references in some places. I marked them in the attached document.There are parts in the description of the modeling work that are not completely understandable, and it is essential to clarify them. I marked them in the attached document.
After the clarifications and suggested references have been replaced, the article can definitely be recommended for publication.
Thank you for your feedback. We will review the manuscript thoroughly and make the necessary changes based on your suggestions. We will also add the suggested literature references. Furthermore, we will revise the model description section to make it more comprehensive, with inclusion of additional detail and examples.
Line 18: You should define what green water means in your article. It can be a bit confusing in this form.Thank you for your valuable comment. We apologize for any confusion caused by not providing a clear definition of the term "green water". We appreciate your input and the revised manuscript will include a clear definition of the term.
Line 67: Maybe you should mention the most simplest approaches like matrix models as well.Thank you for your suggestion. In line with your suggestion, we will revise the text to include a mention of matrix models, as you correctly pointed out that these represent one of the simplest approaches for modeling complex systems.
Lines 70-77: You should emphasize the uncertainties of these tools from a hydrologic point of view. There are studies that highlighted their limitations.We have taken your suggestion into consideration and in the revised manuscript we will include a discussion on the limitations and uncertainties associated with hydrologic models.
Line 86-89: Perhaps the best support for the weakness and unreliability of these models is when they yielded the same results as simple matrix models (without any hydrological calculations). Maybe this article raises your interest: https://doi.org/10.1016/j.ecolind.2022.109143
Maybe you should refer to the model.
This one seems to be appropriate:
https://doi.org/10.1111/j.1745-6584.2011.00882.x
or this:
https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=HydroGeoSphere:+A+Three-Dimensional+Numerical+Model+Describing+Fully-Integrated+Subsurface+and+Surface+Flow+and+Solute+Transport&btnG=
Are there other models which would be capable to handle hydrology similar? E.g.: MIKE SHE..
You may pay attention for this:
https://www.frontiersin.org/articles/10.3389/feart.2021.721009/full#B3Thank you very much for your valuable suggestions and for providing us with the links to the relevant papers. We have thoroughly reviewed the articles you recommended. We will take into account the information contained in these articles and incorporate it into the revised manuscript. We will also more clearly emphasize our rational for using fully-integrated groundwater – surface water models, in the sense that our research objectives necessitate that groundwater, and groundwater – surface water interactions are quantified, which is beyond the capability of simple matrix models. We will also explicitly mention and cite other common integrated models (i.e., Parflow and MikeSHE).
Line 120-122: Maybe you should refer to- or describe in a nutshell the definition Strahler order to help readers from other disciplines (economy, ecology).Thank you for the suggestion. We will add a brief description of the Strahler order in the revised version of the manuscript.
Line 153-163: This paragraph should be supported with some reference related to the topic of applicable models on different spatial scales.
Thank you for this suggestion. We will include the relevant references in the revised text.
Line 192: Did you carry out some kin of harmonization on input spatial data regarding to their resolution?
In the revised manuscript we will describe that land surface and subsurface hydraulic properties were mapped into the HGS model’s unstructured FEM using a dominant component approach, meaning that if two or more property classes exist within the input dataset for a single element, the majority class is represented.
Line 217-219: How do these stations operate? At what intervals is data recorded?
In the revised manuscript we will clearly note that the surface water flow monitoring stations provide daily temporal resolution, while the groundwater monitoring network data provide hourly temporal resolution. We will also embed the URL for the monitoring data sources in the text.
Line 220-221: Why did you use other metrics to evaluate groundwater performance?
Why did you used this one? Maybe you should take into account other statistical evaluation tools. In the results section we can see that, the coefficient of determination is almost perfect, but the difference between the mean GWLs are significant. Maybe you should bring in the RMSE as well.We agree that it would be valuable to incorporate additional statistical evaluation tools in our analysis of groundwater performance and will include RMSE values for the simulated vs observed groundwater levels in the revised manuscript.
Line 266-267: Good accuracy, according to what? You should cite a reference.
In the revised manuscript, we will provide the reference (Moriasi et al., 2007) to support our model performance interpretation. We will also reword the text in this section so that it is less subjective.
Line 268-271: What was the temporal resolution of the compared data (daily, weekly, monthly, yearly)? What does the R2 value refer to? The large difference between the observed and modeled average groundwater level depth is worrisome. Especially knowing that in L107-L109 you wrote about a shallow GW depth of 1-3 m. This can also significantly affect the modeled actual evapotranspiration values.Regarding the temporal resolution of the compared data, the observed groundwater level data was collected at a hourly resolution from the nine WSC hydrometric stations across the SNW; however, the hourly data was aggregated to daily average prior to being used for model performance evaluation. Both groundwater and surface water simulation performance was evaluated based on daily temporal frequency. In the revised manuscript we will rewrite this section to be more clear in regards to the temporal frequency.
The R2 value refers to the proportion of the variance in the observed groundwater level that is predicted from the simulated groundwater level. A high R2 value indicates a good fit between the observed and simulated data.
We acknowledge your concern regarding the large difference between the observed and modeled average groundwater level depth. However, we would actually regard the average difference of 2.8 m between simulated and observed groundwater levels to be very good for two primary reasons. Firstly, the model covers 3830 km2 and has element edge lengths that vary from ~100 m to 300 m, hence subtle variabilities in local topography (from which groundwater depths are referenced) are not perfectly captured in the model geometry. Secondly, because groundwater extractions were not represented in the model, simulated groundwater levels are biased higher, and this bias will be most pronounced in groundwater production areas, where the monitoring wells tend to be placed.
In the revised manuscript we will include supplemental material that graphically depicts surface water and groundwater simulation performance.
Line 366-368: What about the limitations of the fine-grained models? Are they applicable anywhere with any spatial scale? Data needs, other requirements (resource, financial, expert, so on).
We appreciate your input and acknowledge the importance of discussing the limitations of fine-grained models in our paper. In the revised manuscript we will include a section that outlines the limitations of fine-grained models along with their data requirements, expert knowledge, and computational requirements. We will also highlight the applicability of these models across different spatial scales and discuss their potential limitations in certain contexts.
Finally, we thank the reviewer for dedicating their time to reviewing our manuscripts. Their valuable suggestions and feedback have greatly contributed to enhancing the quality of our research work.
-
AC1: 'Reply on RC1', Tariq Aziz, 18 Apr 2023
-
RC2: 'Comment on hess-2023-25', Anonymous Referee #2, 19 Mar 2023
The comment was uploaded in the form of a supplement: https://hess.copernicus.org/preprints/hess-2023-25/hess-2023-25-RC2-supplement.pdf
-
AC2: 'Reply on RC2', Tariq Aziz, 18 Apr 2023
Response to reviewer’s comments
Manuscript number (hess-2023-25)Note: Below are the reviewer’s comments in black, and our responses in blue.
Referee#2:
The paper on Monetizing the role of water in sustaining watershed ecosystem services using a fully integrated subsurface–surface water model by Tariq Aziz et al presents an interesting case study of integrating subsurface–surface water model with valuation of ecosystem services. However, there are few queries about the methodology adopted as well as the results presented and discussed. A line-by-line comment is given below:We appreciate your positive evaluation of our work. In the revised version of the paper, we will address all the queries you have about the methodology and results presented.
Introduction
Page 1, L 24-25: What is the relationship between subsurface water and ecosystem services? Kindly extend on this point in the introduction to provide a clear picture of how subsurface water is linked to ecosystem function and, as a result, the production of ecosystem services. Furthermore, a conceptual diagram connecting subsurface water with various ecosystem services would help readers connect the paper by providing a clear picture.We appreciate your suggestion to provide a more detailed explanation of the relationship between subsurface water and ecosystem services in the introduction, and to include a conceptual diagram that illustrates this connection.
We agree that this is an important aspect of our study, and we will certainly take your feedback into consideration for our revised paper. We plan to expand our introduction to provide a more comprehensive overview of how subsurface water is linked to ecosystem function, and how these functions contribute to the production of ecosystem services. Additionally, we will include a figure to illustrate the connections between subsurface water and various ecosystem services.
Methodology
217-219: How the observed data is used to run the model. Did you run the model for all 9 sites for surface water flow calibration, or did you run it in an integrated fashion? This is unclear. Please clarify the same for Groundwater Monitoring Network wells.
We apologize for any confusion regarding the use of observed data to run the model and the approach taken for surface water flow calibration and groundwater monitoring network wells. The model was run continuously for the 2000 to 2017 time interval, with gridded, daily temporal resolution climate forcing as the primary input to the model. All nine surface water flow gauges were concurrently used for calibration, in conjunction with the 10 groundwater monitoring wells. We will make sure to clarify this aspect of the methodology in the revised manuscript.217-219: It would be better to indicate on what time scale the model is calibrated/validated? Daily, Monthly, Hourly?
We agree that it is important to indicate the time scale used for calibration and validation in our modeling study. To clarify, we used a daily time scale for model calibration and validation. We will make sure to specify this in the revised text to enhance the clarity of our work.
219: 221: Is the model validated? if yes, mention years for calibration and validationThank you for raising this point. For the purpose of our study, the model was calibrated over the full 2000 to 2017 time interval, and the performance metrics are calculated/reported for the same time interval. Accordingly, the model performance metrics reflect the same time interval over which the ecosystem service analysis is conducted. A formal validation was not conducted as our intention was to optimize model performance for the full 18 year interval.
Results:
The paper makes no mention of the model's performance. For instance, how the model behaved at various gauge stations.We appreciate your feedback and agree that the model’s performance should be clearly presented in the manuscript, and we note that reviewer 1 also raised this point (see above). We will provide a clear presentation of the model’s performance in the revised manuscript through supplemental material and enhanced methodology description.
268-271: Are these value aggregate for all gauge station and observation well?
The model performance metrics presented here are indeed aggregated across all stations. In the revised manuscript we will present the model performance metrics on a per station basis, along with additional graphical material depicting simulated vs observed conditions.
277-280: Check figure 5(a), Can you show the observed and simulated graph of the stream flow? Similarly for surface water storage as well and mentioned the NSE and PbIAS value for each zone/site.
Thank you for the suggestion; in the revised version of the paper, we will include observed and simulated graphs for stream flow and surface water storage, as well as the corresponding NSE and Pbias values for each zone/site.
277-280: Check figure5 (b), Is the watershed evaporation one of the outputs from the model? What are others? mention either in methodology or results?
Yes, the model outputs include surface evaporation, subsurface evaporation, and subsurface transpiration. We will clarify this in the revised version of the manuscript.
289: Table 1: Is this value calculated or obtained from secondary sources?
The marginal productivity of water value mentioned in the manuscript is derived from the water production function, which represents the relationship between ecosystem services values and the volume of water consumed in producing them. The slope of this production function gives us the marginal productivity of water value. For our study area (i.e., SNW), the marginal productivity of water is $0.45/m3.
Discussion:
The discussion section focuses heavily on the results and very little on the validity of the findings. Most important, the authors provide little reflection on uncertainty in their data, models, and underlying assumptions. What does that mean in terms of reliability of the modelled results? The authors should consider where their modeling efforts. shine versus where they fall short, and how the shortcomings can be addressed. I would suggest the authors to discuss the results based on model uncertainty, and future implications of the study in terms of valuation of ecosystem services as well.We agree with your comment regarding the importance of discussing the validity and reliability of the modeled results in the discussion section. We also appreciate your suggestion to reflect on the uncertainty in the data, models, and underlying assumptions and to discuss the shortcomings of our modeling efforts and how they can be addressed. This comment aligns with a comment made by Reviewer 1 as well. In the revised manuscript, we will address these concerns by adding a section related to model limitations and uncertainties associated with our study. Furthermore, we will add a subsection to the Discussion section that will specifically focus on the future implications of the study in terms of the valuation of ecosystem services.
Conclusion:
The conclusion may be subsequently modified.After incorporating all the suggested changes and revising the manuscript, we will modify the conclusion section to ensure that it accurately summarizes the key findings of our study and their implications. We will ensure that the conclusion section is in line with the updated results, limitations, and future implications discussed in the manuscript.
Finally, we thank the reviewer for taking the time to review our manuscripts. Their insightful suggestions and feedback are highly valuable and have significantly contributed to improving the quality of our research work.
-
AC2: 'Reply on RC2', Tariq Aziz, 18 Apr 2023
Viewed
| HTML | XML | Total | BibTeX | EndNote | |
|---|---|---|---|---|---|
| 1,072 | 290 | 30 | 1,392 | 27 | 27 |
- HTML: 1,072
- PDF: 290
- XML: 30
- Total: 1,392
- BibTeX: 27
- EndNote: 27
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1