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Article
Peer-Review Record

A Water Shortage Risk Assessment Model Based on Kernel Density Estimation and Copulas

Water 2024, 16(11), 1465; https://doi.org/10.3390/w16111465
by Tanghui Qian 1, Zhengtao Shi 1,*, Shixiang Gu 2,*, Wenfei Xi 1, Jing Chen 2, Jinming Chen 2, Shihan Bai 2 and Lei Wu 2
Reviewer 1:
Reviewer 2: Anonymous
Water 2024, 16(11), 1465; https://doi.org/10.3390/w16111465
Submission received: 21 April 2024 / Revised: 13 May 2024 / Accepted: 17 May 2024 / Published: 21 May 2024

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The authors have compiled a readable analysis of a method to use Kernel Density Estimation to quantify uncertainties in supply and demand based on data and Copula functions to quantify coupled inter-dependencies between them.  It would take substantial time to check their models and analysis in detail, and this has not been done.  However, based on an overall assessment, the paper offers some new approaches to drought severity assessment and seems publishable in its present form.

Should the paper be revised, my suggestion is to create a literature review section that follows a shorter introduction that gets right to the point.  Currently, material down to line 149 is mainly literature review, and it is difficult to find the main objective of the paper.

I also wonder if the term "Comprehensive Evaluation Method" is the best to use (see line 52).  It seems ambiguous and a better title, in my opinion, would be something like "performance indicator method."

On a minor note, the word "supply" is misspelled on Figure 2.

 

Comments on the Quality of English Language

OK, can shorten some of the very lengthy discussions and paragraphs.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

The article is titled “Water Shortage Risk Assessment Model Based on Kernel Density Estimation and Copula”. This paper proposes a water scarcity risk assessment model based on Kernel Density Estimation (KDE) and Copula functions. The authors used Kernel Density Estimation to quantify random uncertainties in water supply and demand based on historical statistical data, thereby calculating their respective marginal probability distributions. The article is interesting, but needs improvement:

- the research area should be described in more detail. Water supply depends on population and economic activity. It should be stated here whether what amounts of water are taken by agriculture, industry and drinking water supply to the population. Apart from the information that such data has been provided, there is no analysis of this data (line 334).

- section 4 is titled discussion and conclusions. The authors did not discuss the results obtained and did not compare them with research conducted by other authors. There is no reference here to scientific publications that analyzed the problem of shortage of water resources due to climate change in other regions of the world.

- Too little references, especially that published since 2020

 

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

The authors improved the article in accordance with the reviewer's comments. There are technical errors that require correction, e.g.

- line 795 ‘53. X., Y.; Y.P., L.; G.H., H.; Y.F., L.; Y.R., L.; X., Z’

- Line 826 ‘Water Diversion Project

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