Water Regulation Ecosystem Services of Multifunctional Landscape Dominated by Monoculture Plantations

Round 1

Reviewer 1 Report

I commend the authors for such a timely modeling study on using different ecosystem types to look into how integrating forest patches, and agroforestry can improve the water regulation ecosystem services. The abstract and introduction were well-written. The methods can be improved slightly because of some questions about data used as model inputs. However, I particularly enjoyed reading the discussion section as the results were thoroughly discussed. The paper needs some revisions to be improved.

These are my comments:

Major

1. Please describe the ground observations clearly. What parameters were obtained in situ and what variables were modeled-based? Particularly on soil inputs, these must be described thoroughly. This is important so that the readers will gauge the reliability of your model output.
2. Please make a paragraph or two about the level of model uncertainties and your limitations. You are talking of a few hundred kilometers of area coverage, yet there is a question of your meager data input. Not enough data used for model calibration and validation may overestimate or underestimate your resulting modeled outputs. Do not overly generalize your results/discussions. You are talking of landscape-level, but this cannot be backed up with ground observations strong enough to support the model output. This weakens your study. State the uncertainties. Caution the readers about the reliability of your results.
3. Please clearly state the novelty of your study how this differs from a wealth of literatures relative to this topic. What are your contributions to the growing demand for more studies about hydrology and water balance in Palm Oil plantations?         

Minor:

Author Response

I am pleased to revise an original research article entitled Multifunctional Landscape Water Regulation Ecosystem Services Dominated by Monoculture Plantations in Tropical Landscape for consideration for publication in the MDPI Land. Based on the reviews and suggestions that you have provided; we hereby convey improvements to our paper. For more detailed response, please see the attachment.

Major

1. Please describe the ground observations clearly. What parameters were obtained in situ and what variables were modeled-based? Particularly on soil inputs, these must be described thoroughly. This is important so that the readers will gauge the reliability of your model output.

 The scientific contribution of this research on the topic of ecosystem service assessment lies in how soil compaction is related to oil palm plantation management as the main factor that causes changes in the water balance. The contribution of this research is also to find appropriate soil and water conservation strategies in oil palm plantations. Our scientific contribution is nothing but to answer false statements about oil palm, where the spread information shows that oil palm plants are "water-hungry." However, we tried to straighten that statement by writing this manuscript to answer the real problem and conservation strategy. In addition, the contribution of this research is linking soil water retention characteristics and WRES that occur at the HRU scale. The information from the SWRC is inputted into .sol to update the soil characteristics for each HRU, especially in the calculation of retention parameter of curve number and range of soil moisture dynamics that affect surface runoff, actual evapotranspiration, and soil water storage. We have conveyed the novelty and contribution of this research and added it to the last paragraph of the introduction.

2. Please make a paragraph or two about the level of model uncertainties and your limitations. You are talking of a few hundred kilometers of area coverage, yet there is a question of your meager data input. Not enough data used for model calibration and validation may overestimate or underestimate your resulting modeled outputs. Do not overly generalize your results/discussions. You are talking of landscape-level, but this cannot be backed up with ground observations strong enough to support the model output. This weakens your study. State the uncertainties. Caution the readers about the reliability of your results.

We have written about model uncertainty and limitation in the initial manuscript, but we deleted it when we submitted it. We have added one paragraph related to model uncertainty testing and two paragraphs related to the model's limitations on the methodology.

Parameters optimization during the calibration process can produce identical streamflow output with observational data regardless of how the best-fit parameters affect other WRES imprecision. However, because this research is related to the WRES assessment, the interpretation of the model is based not only on streamflow outputs but also on other WRES, such as soil water storage and actual evapotranspiration. This study obtained precipitation as WRES input and other meteorological data for ETP calculation from the automatic weather station. Due to the limitations of time-series observations of soil moisture, we used soil hydrological properties and soil water retention curves (SWRC) observations from soil sampling and laboratory analysis. We linked the information from SWRC with the SWAT model by updating the .sol data-base for each HRU as soil moisture modeling inputs.

SWAT simulates soil moisture for each HRU as soil water storage (mm) in the range of available water content (AWC) between permanent wilting point (WP) and field capacity (FC). To get %v/v AWC, SWAT divides the soil water storage (mm) by soil depth (SOL_Z) and adds this result with WP. Based on the information of FC, AWC, and WP from SWRC, the results of the soil moisture from the SWAT model are still within the AWC range following AWC observations on each land use. Finally, we consider the actual evapotranspiration as the "residual" component of the modeling based on the water balance equation (AET = PRECIP – Q – ΔSW). Therefore, the reliability of meteorological observation, SWRC observation, streamflow modeling, and SW modeling would affect the reliability of AET. If we could appropriately simulate the streamflow and soil moisture, then the AET value can also be relied upon in the future WRES evaluation.

In addition, even though we are talking about landscape scale, we evaluate the scale of micro-watersheds with an area of less than 20 square kilometers. More accurate modeling of WRES for micro-watersheds can serve as complementary information for environmental restoration planning at a local scale.

3. Please clearly state the novelty of your study how this differs from a wealth of literatures relative to this topic. What are your contributions to the growing demand for more studies about hydrology and water balance in Palm Oil plantations?

The scientific contribution of this research on the topic of ecosystem service assessment lies in how soil compaction is related to oil palm plantation management as the main factor that causes changes in the water balance. The contribution of this research is also to find appropriate soil and water conservation strategies in oil palm plantations. Our scientific contribution is nothing but to answer false statements about oil palm, where the spread information shows that oil palm plants are "water-hungry." However, we tried to straighten that statement by writing this manuscript to answer the real problem and conservation strategy. In addition, the contribution of this research is linking soil water retention characteristics and WRES that occur at the HRU scale. The information from the SWRC is inputted into .sol to update the soil characteristics for each HRU, especially in the calculation of retention parameter of curve number and range of soil moisture dynamics that affect surface runoff, actual evapotranspiration, and soil water storage. We have conveyed the novelty and contribution of this research and added it to the last paragraph of the introduction.

Author Response File: Author Response.pdf

Reviewer 2 Report

The article covers a relevant topic and the text is overall well written.

However, scientific innovations of the work are not relevant for the journal. Behind "Multifunctional Landscape Water Regulation Ecosystem Services" are finally well known water balance components, nothing more, like a buzz word sticker for something, which has been done since decades, namely, investigating the water balance of agricultural catchments with some field experiments and models. I did not find a new scientific contribution beyond the case study, in particular in the topic of ecosystem services assessment.
The SWAT modelling exercise is questionable because the authors used automatic calibration with the Nash-Sutcliff criterion as objective function. This may have some practical advantages, but the model is calibrated against streamflow and it is unclear how good it performs for the other components, which are of more relevance for the results of this research. Parameter equifinality does not allow to evaluate sub-processes of SWAT after it was calibrated automatically. At least before checking thoroughly the plausibility of flow components. So, the hydrological processes have not been investigated as processes. For such work, as the article is more of hydrological nature, it would be required even though it is clear that data about flow components are scarce. At least, MODIS data for ET could be evaluated, as the calibration could use adequate objective functions for th study of water balance and flow paths.

In the end, the article is an acceptable hydrological case study dealing with palm plantations. After some minor improvements the article might be suitable for a journal like "Hydrology", where cross-cutting hydrological case studies can be published.

Author Response

Dear Reviewer of MDPI Land,

I am pleased to revise an original research article entitled Multifunctional Landscape Water Regulation Ecosystem Services Dominated by Monoculture Plantations in Tropical Landscape for consideration for publication in the MDPI Land. Based on the reviews and suggestions that you have provided; we hereby convey improvements to our paper. For more detailed response, please see the attachment.

1. Behind "Multifunctional Landscape Water Regulation Ecosystem Services" are finally well-known water balance components, nothing more, like a buzz word sticker for something, which has been done since decades, namely, investigating the water balance of agricultural catchments with some field experiments and models. I did not find a new scientific contribution beyond the case study, in the topic of ecosystem services assessment.

 The scientific contribution of this research on the topic of ecosystem service assessment lies in how soil compaction is related to oil palm plantation management as the main factor that causes changes in the water balance. The contribution of this research is also to find appropriate soil and water conservation strategies in oil palm plantations. Our scientific contribution is nothing but to answer false statements about oil palm, where the spread information shows that oil palm plants are "water-hungry." However, we tried to straighten that statement by writing this manuscript to answer the real problem and conservation strategy. In addition, the contribution of this research is linking soil water retention characteristics and WRES that occur at the HRU scale. The information from the SWRC is inputted into .sol to update the soil characteristics for each HRU, especially in the calculation of retention parameter of curve number and range of soil moisture dynamics that affect surface runoff, actual evapotranspiration, and soil water storage. We have conveyed the novelty and contribution of this research and added it to the last paragraph of the introduction.

2. The SWAT modelling exercise is questionable because the authors used automatic calibration with the Nash-Sutcliff criterion as objective function. This may have some practical advantages, but the model is calibrated against streamflow, and it is unclear how good it performs for the other components, which are of more relevance for the results of this research. Parameter equifinality does not allow to evaluate sub-processes of SWAT after it was calibrated automatically. At least before checking thoroughly the plausibility of flow components. So, the hydrological processes have not been investigated as processes. For such work, as the article is more of hydrological nature, it would be required even though data about flow components are scarce.

We have written about model uncertainty and limitation in the initial manuscript, but we deleted it when we submitted it. We have added one paragraph related to model uncertainty testing and two paragraphs related to the model's limitations on the methodology. We used NSE as the goal, but we also checked for other statistical indicators that can describe the match between simulated discharge and observed discharge during automatic calibration based on SUFI-2 algorithms such as R2, KGE, and PBIAS. Because NSE is more commonly used, in this research, we discuss the value of NSE plus R2. The uncertainty of the model is evaluated by r-Factor and p-Factor to control the upper bound and lower bound of the calibrated parameters. The values of r-Factor and p-Factor in this research, which show the uncertainty of the model, are acceptable. The calibrated and sensitive parameters can represent all water balance components under consideration, such as soil moisture, discharge, and evapotranspiration. WRES other than streamflow was not calibrated in this study due to our limitations in measuring and obtaining local soil moisture and evapotranspiration time series data.

Parameters optimization during the calibration process can produce identical streamflow output with observational data regardless of how the best-fit parameters affect other WRES imprecision. However, because this research is related to the WRES assessment, the interpretation of the model is based not only on streamflow outputs but also on other WRES, such as soil water storage and actual evapotranspiration. This study obtained precipitation as WRES input and other meteorological data for ETP calculation from the automatic weather station. Due to the limitations of time-series observations of soil moisture, we used soil hydrological properties and soil water retention curves (SWRC) observations from soil sampling and laboratory analysis. We linked the information from SWRC with the SWAT model by updating the .sol database for each HRU as soil moisture modeling inputs.

SWAT simulates soil moisture for each HRU as soil water storage (mm) in the range of available water content (AWC) between permanent wilting point (WP) and field capacity (FC). To get %v/v AWC, SWAT divides the soil water storage (mm) by soil depth (SOL_Z) and adds this result with WP. Based on the information of FC, AWC, and WP from SWRC, the results of the soil moisture from the SWAT model are still within the AWC range following AWC observations on each land use. Finally, we consider the actual evapotranspiration as the "residual" component of the modeling based on the water balance equation (AET = PRECIP – Q – ΔSW). Therefore, the reliability of meteorological observation, SWRC observation, streamflow modeling, and SW modeling would affect the reliability of AET. If we could appropriately simulate the streamflow and soil moisture, then the AET value can also be relied upon in the future WRES evaluation. Through the basic water balance equation modeled by a dynamic system-based model (SWAT), we investigate the WRES as a process in a watershed system.

3. MODIS data for ET could be evaluated, as the calibration could use adequate objective functions for the study of water balance and flow paths.

We did not use MODIS AET for this study because MODIS's spatial resolution is too large compared with input data for SWAT modeling, which caused the MODIS AET value could be on more than one different land use or HRU. Besides that, MODIS is also not a direct measurement. As explained above, we evaluate the reliability of evapotranspiration as the remainder of the "water balance" equation based on our observations of discharge and available water content. We also observed in situ climate data and leaf area index, so we believe our evapotranspiration values can describe conditions in the plot.

4. The article is an acceptable hydrological case study dealing with palm plantations. After some minor improvements the article might be suitable for a journal like "Hydrology", where cross-cutting hydrological case studies can be published.

Thanks for the advice. We submitted this paper to MDPI Land because we focused this research on how soil and land management affect oil palm hydrology and oil palm conservation strategies based on WRES. This research also aims to straighten out the misguided questions circulating in the community about oil palm, which is "water greedy." For this reason, because it is related to soil, land, and hydrology, we include in this journal the special topic "Soil-Water-Sediment." We hope that our paper can be accepted and published in this journal. We believe that this manuscript is appropriate for publication by MDPI Land because it is closely related to one of the special issues offered, "Soil Management for Sustainable Agriculture and Ecosystem Services" and our manuscript explores a paradigm for relevant studies of the ecosystem services monitoring. This manuscript has not been published and is not under consideration for publication elsewhere. We have no conflicts of interest to disclose. Furthermore, all authors have approved the manuscript and agree with its submission to MDPI Land.

Thank you for your consideration!

Author Response File: Author Response.pdf

Reviewer 3 Report

The research is good and with great effort, I appreciate your work.

The manuscript is well written and organized but there are few questions that should be addressed.

Comments for author File: Comments.pdf

Author Response

Dear Reviewer of MDPI Land,

I am pleased to revise an original research article entitled Multifunctional Landscape Water Regulation Ecosystem Services Dominated by Monoculture Plantations in Tropical Landscape for consideration for publication in the MDPI Land. Based on the second-round reviews and suggestions that you have provided; we hereby convey improvements to our paper.

1. Is it possible to add soil classification? Soil general properties would be useful to understand soil degradation. Soil Organic Matter content would be helpful due to its importance in soil structure.

Sorry, we have not added that the soil in the study area is Ultisol (Hapludults) according to the USDA classification. General soil properties such as texture, bulk density, porosity, and organic matter indicate soil degradation based on Dexter (2004). Based on the observation that soil properties differ according to land use, we use these properties as an indicator of soil compaction even with the same soil class. We made field observations and used these soil properties to determine soil water retention as described in the methodology's first part, result, and discussion. We also use soil data in this study as SWAT inputs to simulate WRES.

4. Abbreviation in Figure 3: Solved.
5. Rewrite paragraph after Figure 4: Solved
6. Discussion paragraph 1: We have added soil type information to the study site.
7. As you remark SOM has important effects, so it would be helpful to show the data. Thank you for the suggestion. We will add the SOM information in Table 1 of the Result section.

6. Do you think that soil compaction has a negative effect in oil palm development?

Soil compaction will be positive or negative in terms of its impact on available water pores. Soil compaction, which causes a decrease in drainage pores (macropores), on the one hand, will increase AWC pores, and on the other hand, if intensive, it will decrease both drainage pores and AWC pores. The function of the drainage pores is as a place of air exchange for plant aeration, the development of soil fertilizing microbes, and root development. As shown in this study, soil compaction that reduces drainage pores will harm plant aeration, root development, and microbes development and richness that help nutrient uptake. The decrease in AWC due to soil compaction also decreased soil water available for plant growth. In contrast to the case where soil compaction can increase AWC, soil compaction will positively impact soil water availability. However, soil compaction always negatively impacts drainage pores and causes other adverse effects such as decreased infiltration and increased runoff.

7. References: Solved

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

The authors have addressed my concerns and made tremendous improvements in their manuscript. 

Author Response

Thanks for your suggestions and input to improve our manuscript. We hope that our paper can be accepted and published in this journal. We believe that this manuscript is appropriate for publication by MDPI Land because it is closely related to one of the special issues offered, "Soil Management for Sustainable Agriculture and Ecosystem Services" and our manuscript explores a paradigm for relevant studies of the ecosystem services monitoring. This manuscript has not been published and is not under consideration for publication elsewhere. We have no conflicts of interest to disclose.

Reviewer 2 Report

The authors provided responses, which were very general and partially redundant (see responses to other reviewer). Even though the text itself is well elaborated, the issues mentioned by both reviewers were fundamental and not adequately adressed. The authors are honest to write that "Our scientific contribution is nothing but to answer false statements about oil palm, where the spread information shows that oil palm plants are "water-hungry." "Answers" to common scientific knowledge are not necessarily science, but they may surely make a study and test their hypothesis even though they contradict others. Science needs discussion and being against mainstream is OK. But, it has nothing to do with ecosystem services. The topic relates to hydrological impact of oil palm tree. The authors should give a real proof of their hypothesis by using suitable investigation methods. But, with the data and model used, it will not be possible to proof if oil trees are less "water-hungry" than some others say. A SWAT model autocalibrated against runoff cannot resolve what they search for. So, there is basically nothing new than another SWAT case study. The authors might consider to extract their field experiments and draw conclusions from field based data. Models like SWAT are good for larger scale investigations of case studies, but their uncertainty is considerable when process research on a smaller scale is done. Autocalibration as well as automatic sensitivity analysis are not necessarily giving a kind of "truth" due to high degree of freedom in parameterization.

The article is well fomulated but in my opinion not suitable for publication in a research oriented journal.

Author Response

Dear Reviewer of MDPI Land,

I am pleased to revise an original research article entitled Multifunctional Landscape Water Regulation Ecosystem Services Dominated by Monoculture Plantations in Tropical Landscape for consideration for publication in the MDPI Land. Based on the second-round reviews and suggestions that you have provided; we hereby convey improvements to our paper.

1. The topic relates to hydrological impact of oil palm tree. The authors should give a real proof of their hypothesis by using suitable investigation methods. But, with the data and model used, it will not be possible to proof if oil trees are less "water-hungry" than some others say. A SWAT model auto calibrated against runoff cannot resolve what they search for. So, there is basically nothing new than another SWAT case study.

 In this research, we try to answer the hypothesis by conducting soil experiments and combining field input in the form of "soil compaction" on oil palm and forest assisted by the SWAT model to determine how the conservation technique is. We admit that the use of the SWAT model in this study is no different from other studies, using streamflow as model calibration. However, we detailed SWAT input by experimental, especially in soil database, plant database, and meteorological databases, such as permeability, soil water retention, and leaf area index, to perform better SWAT simulations and reduce parameter calibration. Furthermore, we detail the different soil properties in each land use for the same soil type to observe the soil hydrological characteristics on a smaller spatial scale or HRU. We even differentiated the soil properties of young and mature oil palms to get the different WRES characteristics.

 Based on the observation data and model simulation, the hypotheses we answer and prove on this manuscript are as follows:

- Soil in oil palm is compacted compared with forest patches, based on bulk density and porosity, so the proportion of runoff is higher than in the forest patches. Therefore, surface runoff and lateral flow in oil palms are worse than in forest patches. Because we observed all soil data for SWAT inputs, we did not calibrate this database so that the calibrated parameters were reduced. For example, bulk density, available water capacity that affects soil moisture ranges, and permeability that affects lateral flow are not calibrated.

- To answer the " water-hungry " opinion, besides investigating soil water storage, we also investigated the leaf area index (LAI) sampling, where LAI is a factor that affects evapotranspiration. From the results and discussion presented in the manuscript, it was found that the leaf area index and soil water storage of oil palm were smaller than in forests, so the oil palm evapotranspiration obtained was also smaller. In this case, the forest is "water hungry" to stabilize the microclimate.

2. The authors might consider extracting their field experiments and draw conclusions from field-based data.

This research is not a pure SWAT simulation. However, we have observed the soil hydrological properties based on field experiments to evaluate soil compaction and use it to SWAT inputs. We also use field-based data in extracting discussion and conclusions (especially in the last paragraph 1). In this case, the critical point of the study is the effects of observed soil compaction as a SWAT input that causes a WRES imbalance in oil palm. Furthermore, the conclusion of this study is how to conserve WRES by preserving forest patches and answering that oil palm plants are not "water hungry", although they have worse WRES than forest patches.

3. Models like SWAT are good for larger scale investigations of case studies, but their uncertainty is considerable when process research on a smaller scale is done. Autocalibration as well as automatic sensitivity analysis are not necessarily giving a kind of "truth" due to high degree of freedom in parameterization.

 Automatic calibration indeed provides high uncertainty in the model if not controlled by literature and expert judgment. When we calibrate, we also refer to relevant literature and manual books to control for the upper and lower bound values of each parameter that make sense. We minimize the degree of freedom in our parameterization by evaluating the uncertainty of the model. By uncertainty evaluation using the SUFI-2 algorithm, we control the range of each parameter (lower bound and upper bound) to get the minimum uncertainty, which is indicated by the p-Factor and r-Factor values according to Abbaspour (2015). We have presented the methodology and discussion regarding the uncertainty and limitations of the model in the manuscript.

Author Response File: Author Response.docx