Next Article in Journal
A Hybrid Grey Wolf Optimization Algorithm Using Robust Learning Mechanism for Large Scale Economic Load Dispatch with Vale-Point Effect
Previous Article in Journal
Gap and Force Adjustment during Laser Beam Welding by Means of a Closed-Loop Control Utilizing Fixture-Integrated Sensors and Actuators
 
 
Review
Peer-Review Record

A Comprehensive Review of Conventional, Machine Leaning, and Deep Learning Models for Groundwater Level (GWL) Forecasting

Appl. Sci. 2023, 13(4), 2743; https://doi.org/10.3390/app13042743
by Junaid Khan 1, Eunkyu Lee 2,3, Awatef Salem Balobaid 4 and Kyungsup Kim 1,2,*
Reviewer 1:
Reviewer 2:
Reviewer 3: Anonymous
Appl. Sci. 2023, 13(4), 2743; https://doi.org/10.3390/app13042743
Submission received: 19 January 2023 / Revised: 14 February 2023 / Accepted: 17 February 2023 / Published: 20 February 2023

Round 1

Reviewer 1 Report

Please revise the abstract part.

Check for grammatical mistakes and minor spell check in introduction part.

Also check section 3 for spelling check and review it one more time to avoid any technical mistakes.

add more references to your paper, the current references is not enough.

1. The author discussed different deep learning methods for groundwater level prediction modelling, suggested the appropriate methods, and concluded with the best method.

2. The topic is interesting, but a brief discussion is required in tables, such as performance measures and each method comparison.

3. Add tables to compare each result already published

4. The authors need to further improve the methodology by citing more papers

5. The conclusion must be modified according to the tables you added.

6. The references are inappropriate because it's a review paper, so kindly add more references, over 100.

7. Please review carefully once you have done the final draft according to my suggestion.

8. Table 1 needs to be discussed in detail. In the current version, it's not enough.

9.  section 5 needs to discuss in detail with a comprehensive table.

10. add the list of terminologies in the last section. 

11. Only 43 references are given. It's not enough.



 

Author Response

Reviewer#1, Concern # 1:  

Please revise the abstract part.

Author response:  Thank you for your suggestion.

Author action: The abstract has been revised according to the revised version.

Reviewer#1, Concern # 2:  

Check for grammatical mistakes and minor spell checks in the introduction part.

Author response:  Thank you for your suggestion.

Author action: The introduction part has been updated.

Reviewer#1, Concern # 3:  

Also, check section 3 for spelling check and review it one more time to avoid any technical mistakes.

Author response:  Thank you for your suggestion.

Author action: section 3 part has been updated.

Reviewer#1, Concern # 4:  

add more references to your paper, and the current references is not enough.

Author response:  Thank you for your suggestion.

Author action: 109 references have been added, and the paper is good enough.

 -------------------------------------------------------------------------------------------------------

Reviewer#1, Concern # 1:  

The author discussed different deep learning methods for groundwater level prediction modelling, suggested the appropriate methods, and concluded with the best method.

Author response:  Thank you for your valuable comments.

Reviewer#1, Concern # 2:  

The topic is interesting, but a brief discussion is required in tables, such as performance measures and each method comparison.

Author response:  Thank you for your suggestion.

Author action: the paper has been revised with detailed methodologies and discussion.

Reviewer#1, Concern # 3:  

Add tables to compare each result already published.

Author response:  Thank you for your suggestion.

Author action: Table 3 has been added.

Reviewer#1, Concern # 4:  

The authors need to further improve the methodology by citing more papers.

Author response:  Thank you for your suggestion.

Author action: 109 references have been added, and the paper is good enough.

Reviewer#1, Concern # 5:  

The conclusion must be modified according to the tables you added.

Author response:  Thank you for your suggestion.

Author action: The conclusion part is also modified in the new version.

Reviewer#1, Concern # 6:  

The references are inappropriate because it's a review paper, so kindly add more references, over 100.

Author response:  Thank you for your suggestion.

Author action: 109 references have been added, and the paper is good enough.

Reviewer#1, Concern # 7:  

Please review carefully once you have done the final draft according to my suggestion.

Author response:  Thank you for your suggestion.

Author action: The papers have been reviewed carefully.

Reviewer#1, Concern # 8:  

Table 1 needs to be discussed in detail. In the current version, it's not enough.

Author response:  Thank you for your suggestion.

Author action: Table 1 is now table 3, briefly discussed.

Reviewer#1, Concern # 9:  

section 5 needs to discuss in detail with a comprehensive table.

Author response:  Thank you for your suggestion.

Author action: Table 4 has been added in detail performance measures.

Reviewer#1, Concern # 10:  

add the list of terminologies in the last section. 

Author response:  Thank you for your suggestion.

Author action: table has been added.

Reviewer#1, Concern # 11:  

Only 43 references are given. It's not enough.

Author response:  Thank you for your suggestion.

Author action: Now the references are 109.

Reviewer 2 Report

Comments and Suggestions on Review Paper titled as “A Comparison on groundwater level (GWL) prediction modeling with different ML and Deep Learning Models: A Review

 

Overall the paper is good to be published but a few comments and suggestions are given in the PDF file as attached and a couple of comments are as follows”

 

1.      You need to revisit the criteria as one of the most recent publication “https://www.mdpi.com/2073-4441/14/4/565” is missed to be cited in this review paper. This study is a comprehensive description of all the methods of groundwater research (which includes also the methods i.e. classical, satellite, numerical, ANN etc. and also combination of some). So cite this at appropriate place. Similarly, there is another method of groundwater levels analysis which is described in this paper “ https://d1wqtxts1xzle7.cloudfront.net/71828945/8ec8aea7ceabe113b409cc898e3f43bfb9e7-libre.pdf?1634081270=&response-content-disposition=inline%3B+filename%3DGroundwater_share_quantification_through.pdf&Expires=1675766350&Signature=UvCw8CRlJCuh8t4J3Jj9OOReWtL0qF8gJ2qMu3IrU6re1zVDLgRXqSnkZmnnJd~fveuAWNkOYqFwog47aaQPNan76zz11-0VBFarSnsH5ygonMgcsnr5d7URU49lg9WTnq7YF9U9TenPhKuuIsngZ7Gnk7pxvxHQJjdccR3A8Dqa4Ct-iEXwXCibUaacSKTosAzvGwCXqIB2OOMcQPjhxrecpWsA~P0-8-tWexMunP89V3BrN78Mqe2MKtSYOb1tWicpilWxDCc9NJaHtAzvX8H9u8KXX~ZRMJUxI2mYMUZ9YW2wi5ToNgbhizfOOMWr8UiDiwJ3vpeEJa39vsNcpw__&Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA ” that should also need to be cited at some appropriate place.

2.      References are not sufficient for a review paper; it still needs to be enhanced in this review paper i.e. at least more than 100.

3.      Line # 110-112 i.e.

1.      The main objective of this research is to explore the current GWL methodologies.

2.      Deep learning-based models for GWL.

3.      Machine learning perspectives-based groundwater modeling.

may be replaced with as follows:

The main objectives of this research are:

1.      To explore the current GWL methodologies

2.      Deep learning-based models for GWL

3.      Machine learning perspectives-based groundwater modeling

Comments for author File: Comments.pdf

Author Response

Overall, the paper is good to be published but a few comments and suggestions are given in the PDF file as attached and a couple of comments are as follows”

 

  1. You need to revisit the criteria as one of the most recent publication “https://www.mdpi.com/2073-4441/14/4/565” is missed to be cited in this review paper. This study is a comprehensive description of all the methods of groundwater research (which includes also the methods i.e. classical, satellite, numerical, ANN etc. and also combination of some). So cite this at appropriate place. Similarly, there is another method of groundwater levels analysis which is described in this paper “ https://d1wqtxts1xzle7.cloudfront.net/71828945/8ec8aea7ceabe113b409cc898e3f43bfb9e7-libre.pdf?1634081270=&response-content-disposition=inline%3B+filename%3DGroundwater_share_quantification_through.pdf&Expires=1675766350&Signature=UvCw8CRlJCuh8t4J3Jj9OOReWtL0qF8gJ2qMu3IrU6re1zVDLgRXqSnkZmnnJd~fveuAWNkOYqFwog47aaQPNan76zz11-0VBFarSnsH5ygonMgcsnr5d7URU49lg9WTnq7YF9U9TenPhKuuIsngZ7Gnk7pxvxHQJjdccR3A8Dqa4Ct-iEXwXCibUaacSKTosAzvGwCXqIB2OOMcQPjhxrecpWsA~P0-8-tWexMunP89V3BrN78Mqe2MKtSYOb1tWicpilWxDCc9NJaHtAzvX8H9u8KXX~ZRMJUxI2mYMUZ9YW2wi5ToNgbhizfOOMWr8UiDiwJ3vpeEJa39vsNcpw__&Key-Pair-Id=APKAJLOHF5GGSLRBV4ZA ” that should also need to be cited at some appropriate place.

Response 1: Thank you so much for suggesting new articles; the following papers have been added to the references.

  1. References are not sufficient for a review paper; it still needs to be enhanced in this review paper i.e. at least more than 100.

Response 2: Thank you so much for your suggestion. One hundred nine (109) articles have been added.

 

  1. Line # 110-112 i.e.

Response 3: Thank you so much for suggesting Line # 110-112 changes, I have updated and modified these changes. The updates have been highlighted in the new version.

  1. The main objective of this research is to explore the current GWL methodologies.
  2. Deep learning-based models for GWL.
  3. Machine learning perspectives-based groundwater modeling.

may be replaced with as follows:

The main objectives of this research are:

  1. To explore the current GWL methodologies
  2. Deep learning-based models for GWL
  3. Machine learning perspectives-based groundwater modeling

Thank you so much for a comprehensive review of our paper. The other changes you highlighted in the pdf version has been updated in the new version.

Reviewer 3 Report

Groundwater level assessment is a crucial task to maintain the groundwater resources as one-third of the world’s water requirements are met through this resource. Excessive and unplanned extraction leads to the depletion of this important resource and results in a serious issue globally, particularly in surface-water shortage countries. So, in this regard, researchers have developed different models and techniques to simulate groundwater levels.

The contribution of the paper is to present a collection of state-of-the-art theories for developing and designing a novel methodology and improving modeling efficiency are also considered in the applicable field of evaluation.

In conclusion, my opinion on the paper is positive. The contents of the paper is interesting and academically worthwhile. The main results in the paper are correct as far as I can determine and interesting enough to be published. Thus, I am happy to recommend that the paper is accepted for publication in Applied Sciences.

But the exposition can be improved, as is made clear in the comments below. These comments should be addressed before the paper is eligible for publication.

1. page 1, line 19, Replace ``...  ground water  ...'' with ``...  groundwater  ...''.

2. page 1, line 31, Replace ``...   groundwater levels   ...'' with ``...  GWL  ...''. Abbreviations should be defined at first mention and used consistently thereafter.

3. page 1, line 32, Replace ``...  artificial intelligence  ...'' with ``...

 artificial intelligence (AI)...''. Abbreviations should be defined at first mention and used consistently thereafter.

4. page 1, line 32, Replace ``...  artificial intelligence (AI)  ...'' with ``...

AI...''.

Author Response

Groundwater level assessment is a crucial task to maintain the groundwater resources as one-third of the world’s water requirements are met through this resource. Excessive and unplanned extraction leads to the depletion of this important resource and results in a serious issue globally, particularly in surface-water shortage countries. So, in this regard, researchers have developed different models and techniques to simulate groundwater levels.

The contribution of the paper is to present a collection of state-of-the-art theories for developing and designing a novel methodology and improving modeling efficiency are also considered in the applicable field of evaluation.

In conclusion, my opinion on the paper is positive. The contents of the paper is interesting and academically worthwhile. The main results in the paper are correct as far as I can determine and interesting enough to be published. Thus, I am happy to recommend that the paper is accepted for publication in Applied Sciences.

Response: Thank you so much for your valuable comments.

But the exposition can be improved, as is made clear in the comments below. These comments should be addressed before the paper is eligible for publication.

  1. page 1, line 19, Replace ``...  ground water  ...'' with ``...  groundwater  ...''.

Response 1: Thank you so much for your suggestion. I have reviewed my paper carefully and updated similar terminologies.

  1. Page 1, line 31, Replace ``...   groundwater levels   ...'' with ``...  GWL  ...''. Abbreviations should be defined at first mention and used consistently thereafter.

Response 2: Thank you so much for your suggestion. The same changes have been made for “GWL.”

  1. page 1, line 32, Replace ``...  artificial intelligence  ...'' with ``...

 artificial intelligence (AI)...''. Abbreviations should be defined at first mention and used consistently thereafter.

Response 3: Thank you so much for your suggestion, the artificial intelligence is replaced with artificial intelligence (AI).

  1. page 1, line 32, Replace ``...  artificial intelligence (AI)  ...'' with ``... AI...''.

Response 4: Thank you so much for your suggestion, the artificial intelligence is replaced with AI.

Back to TopTop