Temporal Variations in Chemical Proprieties of Waterbodies within Coastal Polders: Forecast Modeling for Optimizing Water Management Decisions

Round 1

Reviewer 1 Report

Overall this is a good quality paper.  Below are a few comments to help with the further improvement.

Abstract:

1.     The abstract could benefit from providing a clearer and more concise description of the specific objectives of the study and a more explicit statement regarding the novelty or significance of the research findings. It is important to clearly state the research questions or hypotheses that the study aims to address.

2.     The abstract mentions the lack of a clear connection between water salinity of surface water bodies and groundwater, but does not provide an explanation or interpretation for this finding. It would be beneficial to briefly discuss the implications of this observation and any potential factors contributing to the lack of correlation.

Introduction:

1.     The introduction lacks a clear synthesis of the existing literature on the topic. It would benefit from a critical review of previous studies examining the temporal variations of water properties in coastal polders and their limitations, highlighting the unique contribution of this research.

2.     The introduction does not provide a clear rationale for why the VAR model was chosen for water salinity forecasting and how it addresses the complex dynamics of the study area. More justification for the choice of this particular modeling approach is needed.

3.     Please consider providing a stronger concluding paragraph that succinctly summarizes the research objectives, highlights the expected contributions of the study, and outlines the structure of the paper. This would provide a clearer roadmap for the reader and reinforce the importance of the research.

Discussions:

1.     The discussion does not adequately address the limitations and uncertainties of the study. It is important to acknowledge and discuss any limitations or potential sources of error in the data, methods, or models used. This would provide a more balanced perspective on the findings and their reliability.

2.     It would be beneficial to discuss in more detail how the forecasting models can be utilized for water management decisions and crop production optimization, and to provide specific recommendations for mitigating salinization and improving water quality in the polder-type agricultural floodplain.

Author Response

Dear reviewer,

thank you very much for the great effort and constructive suggestions to improve this paper. Everything you noticed was carefully read, accepted, and adjusted in a suitable way through the manuscript (you can find it in the revised version) and you can find the answers to your comments down below and also in the attachment.

Kind regards!

 Abstract:

Comment:

The abstract could benefit from providing a clearer and more concise description of the specific objectives of the study and a more explicit statement regarding the novelty or significance of the research findings. It is important to clearly state the research questions or hypotheses that the study aims to address.

Answer:

Thank you for this observation, I’m also aware of the shortcoming in the abstract and it was rewritten (lines 14-26; 39-42). The study seeks to emphasize the significance of understanding these features and their influence on agricultural production and water management practices, particularly in relation to irrigation. By presenting and evaluating the unique aspects of lower-lying land, this research aims to provide valuable insights for management authorities and agricultural producers, enabling them to effectively plan and manage future production activities. The findings will contribute to sustainable agricultural practices, ultimately benefiting the wider Mediterranean area. Anyway, our work was not intended to propose specific management options for the practitioners, but to clarify problems and processes they are facing with, and which would be a base for their engineering solutions.

Comment:

The abstract mentions the lack of a clear connection between water salinity of surface water bodies and groundwater but does not provide an explanation or interpretation for this finding. It would be beneficial to briefly discuss the implications of this observation and any potential factors contributing to the lack of correlation.

Answer:

Thank you for your comment. Indeed, due to the unique characteristics of the study area terrain, including the lower-laying parcels of predominantly polder-type, formed by intensive land reclamation and hydro-technical interventions, canals network, and water complex connectivity in both horizontal and vertical direction, each dataset comes with its context. Indeed, many different parameters can be used in hydrochemical studies, including a wide range of physical, chemical, and biological variables. However, in this specific research, our focus was on identifying the parameters that are most relevant for developing an accurate salinity prediction model. This approach can help to simplify the model and make it more parsimonious and also make it more computationally efficient. So, choosing the best model highly depends on many available (and possibly unrevealed) factors. In this study, we tried to extract accurate information from the long-term water chemistry monitoring program and develop a model which should align with stakeholders needs and expectations, and provide outputs that are meaningful and useful for decision-making or further research. In fact, develop a model that can be easily adapted and applied in different contexts by means of saving time and effort in the long run. Furthermore, the lack of correlation lies in the complex hydrological dynamics and interconnectivity of the water bodies highly affected by the artificial maintenance of the groundwater level within the polder area, as well as interventions in temporal releasing of fresh water into the drainage canals network. To address your suggestion, lines 30-32 have been added.

Introduction:

Comment:

The introduction lacks a clear synthesis of the existing literature on the topic. It would benefit from a critical review of previous studies examining the temporal variations of water properties in coastal polders and their limitations, highlighting the unique contribution of this research.

Answer:

Thank you for the comment. It would be useful to specify which aspect of the issue researched have not been sufficiently explained/tackled in the introduction. Polders are unique operational systems and the variations in water geochemistry are governed by a complex array of natural and anthropogenic factors. We tried to characterize each specific/dominant factor, and afterwards find the statistical and modelling method which would explain most of the determined variability. Several new references have been added in lines 123-154 addressing temporal variation of water properties in polders.

Comment:

The introduction does not provide a clear rationale for why the VAR model was chosen for water salinity forecasting and how it addresses the complex dynamics of the study area. More justification for the choice of this particular modeling approach is needed.

Answer:

Thank you for your observation. We already noted in the Introduction, after considering different methods of the time series analysis, that VAR is a multivariate model that considers multiple time series at the same time. VAR models the relationships between multiple variables, making it more suitable for modeling non-stationary time series data and data sets with multiple variables. Recent research showed that time series models, especially VAR can be efficiently used for predicting different water properties allowing different variables and their lagged values to be included in the model, unlike ARIMA which uses only lagged values of one variable. This is the main reason why VAR models was used, as it allows modeling based on several variables, in our case ionic composition of water which in the study area significantly differs among different water bodies and different monitoring locations. Also VAR model is usually coupled with Granger causality test which explores causal relationship between variables allowing us to investigate causal relationship between water salinity and sea level rise in the study area which represents one of the most vulnerable areas in Croatia to climate change, especially sea level rise. Several new references have been added in lines 189-205 to clarify the reasons for use of VAR model.

Comment:

Please consider providing a stronger concluding paragraph that succinctly summarizes the research objectives, highlights the expected contributions of the study, and outlines the structure of the paper. This would provide a clearer roadmap for the reader and reinforce the importance of the research.

Answer:

Thank you for the comment. The concluding section of the introduction has been rewritten and rearranged (lines 215-232).

Discussions:

Comment:

The discussion does not adequately address the limitations and uncertainties of the study. It is important to acknowledge and discuss any limitations or potential sources of error in the data, methods, or models used. This would provide a more balanced perspective on the findings and their reliability.

Answer:

Thank you for your comment. The complex hydrological dynamics and interconnectivity of the water bodies are severely affected by the artificial maintenance of the groundwater level within the polder area. This could be one of the reasons why the developed models do not adequately represent the groundwater conditions. The available variables used to develop predictive models could be one of the shortcomings and future research could consider the inclusion of other variables that may improve the performance of the model. Accordingly, lines addressing this (914-922) were added in the last paragraph of the discussion.

Comment:

It would be beneficial to discuss in more detail how the forecasting models can be utilized for water management decisions and crop production optimization, and to provide specific recommendations for mitigating salinization and improving water quality in the polder-type agricultural floodplain.

Answer:

Thank you for your comment. By establishing a scientific basis for water quality monitoring and management actions, this research aims to support the decision-making process of management authorities and provide practical insights for practitioners in the study area. The statistical and modeling methodologies tested in this study have the potential for broader application within the scientific community. It is essential to clarify that the research does not propose specific management options but rather serves as a foundation for practitioners to develop engineering solutions that address the identified problems and processes. The manuscript emphasizes the practice-oriented nature of the research and includes additional clarification on this matter in lines 899-913.

Thank you again for your feedback and suggestions. We hope that all the problems raised by your review have been addressed.

Author Response File: Author Response.docx

Reviewer 2 Report

I have reviewed manuscript agriculture-2411959 by Romic et al. The manuscript describes the efforts of the authors to use data on water quality in the Neretva River Delta to explain the dynamics of salinity in the surface and groundwater and to develop a model that might be used to predict salinity. The specific goals are summarized in lines 169–174 as follows: to (i) identify common features in the chemical composition of various classes of water bodies by applying multivariate statistics, (ii) establish the relationship between different classes of surface waters and groundwater that governs the magnitude and extent of water salinity, (iii) test the stationarity of time series and investigate the causal relationship between sea level and water salinity, and (iv) recognize patterns in water salinity by developing a 12-month-ahead salinity forecast using the VAR [vector autoregression] model.

I see a couple of problems with this manuscript. First, when we get to the conclusions (lines 847–885), the four goals summarized in lines 169–174 seem to have been forgotten. The Conclusions consist of 7 bullet points, and there is no effort to relate the 7 bullet points to the four goals summarized in lines 169–174. I suggest that when the authors get to the Conclusions, they should very clearly and explicitly explain to what extent they were able to achieve the four goals they set out to achieve.

Second, the first sentence in the Abstract says that a short-term forecasting model is “needed to assist in optimizing water management decisions.” Nowhere in this manuscript is there any mention of what sort of management decisions are being made that might benefit from a short-term forecasting model. This manuscript is absolutely silent on that point. For example, if we had some kind of forecasting model that told us a giant meteor was going to hit Earth, what would we do about it? A management decision in the case of the Neretva River Delta might be to abandon the place because sea level is rising. It is just entirely unclear from this manuscript what sort of management decisions the authors have in mind that might somehow benefit from a short-term forecasting model. I think this needs to be clearly spelled out. Otherwise, I just do not see the point of this manuscript.

I detected only one glitch. In line 626, "lower-laying parcels" should be "lower-lying parcels". Lay is a transitive verb, e.g., hens lay eggs. 

Author Response

Dear reviewer,

thank you very much for the great effort and constructive suggestions to improve this paper. Everything you noticed was carefully read, accepted, and adjusted in a suitable way through the manuscript (you can find it in the revised version) and you can find the answers to your comments down below and also in the attachment.

Kind regards! 

I have reviewed manuscript agriculture-2411959 by Romic et al. The manuscript describes the efforts of the authors to use data on water quality in the Neretva River Delta to explain the dynamics of salinity in the surface and groundwater and to develop a model that might be used to predict salinity. The specific goals are summarized in lines 169–174 as follows: to (i) identify common features in the chemical composition of various classes of water bodies by applying multivariate statistics, (ii) establish the relationship between different classes of surface waters and groundwater that governs the magnitude and extent of water salinity, (iii) test the stationarity of time series and investigate the causal relationship between sea level and water salinity, and (iv) recognize patterns in water salinity by developing a 12-month-ahead salinity forecast using the VAR [vector autoregression] model.

Comment:

I see a couple of problems with this manuscript. First, when we get to the conclusions (lines 847–885), the four goals summarized in lines 169–174 seem to have been forgotten. The Conclusions consist of 7 bullet points, and there is no effort to relate the 7 bullet points to the four goals summarized in lines 169–174. I suggest that when the authors get to the Conclusions, they should very clearly and explicitly explain to what extent they were able to achieve the four goals they set out to achieve.

Answer:

Thank you for this comment. Actually, there's no strict form set up for the conclusions in the scientific publication, and it usually varies depending on the structure of the paper. Anyway, following your kind suggestion, the previous conclusion has been substituted with a new one organized into 4 bullet points that address defined goals and overall recommendations for further investigation.

Comment:

Second, the first sentence in the Abstract says that a short-term forecasting model is “needed to assist in optimizing water management decisions.” Nowhere in this manuscript is there any mention of what sort of management decisions are being made that might benefit from a short-term forecasting model. This manuscript is absolutely silent on that point. For example, if we had some kind of forecasting model that told us a giant meteor was going to hit Earth, what would we do about it? A management decision in the case of the Neretva River Delta might be to abandon the place because the sea level is rising. It is just entirely unclear from this manuscript what sort of management decisions the authors have in mind that might somehow benefit from a short-term forecasting model. I think this needs to be clearly spelled out. Otherwise, I just do not see the point of this manuscript.

Answer:

Thank you for your comment. The main motivation for this research, as well as overall activities on the water quality monitoring in the study area, have been undertaken to develop a scientific base for the further practice actions which should be done by the management authorities in the region, but not only. We’ve tested the statistical and modeling methodology that can be used by the wider scientific community. The practical motivated orientation of the research has been driven through the manuscript, mentioned in all manuscript parts. Anyway, we added some additional clarification on the issue in lines 899-913. Our work was not intended to propose specific management options for the practitioners, but to clarify problems and processes they are facing with, and which would be a base for their engineering solutions.

Thank you again for your feedback and suggestions. We hope that all the problems raised by your review have been addressed.

Author Response File: Author Response.docx