the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 19 Apr 2023
High-resolution mapping of monthly industrial water withdrawal in China from 1965 to 2020
Abstract. High-quality gridded data on industrial water use is vital for research and water resource management. However, such data in China usually have low accuracy. In this study, we developed a gridded dataset of monthly industrial water withdrawal (IWW) for China, namely, the China industrial water withdrawal dataset (CIWW), which spans a 56-year period from 1965 to 2020 at a spatial resolution of 0.1° and 0.25°. We utilized >400,000 records of industrial enterprises, monthly industrial product output data, continuous statistical IWW records from 1965 to 2020, to facilitate spatial scaling, seasonal allocation, and long-term temporal coverage in the developing the dataset. The CIWW dataset presented significant improvement in characterizing the spatial and seasonal patterns of IWW dynamics in China, with a much higher accuracy at fine scale while ensuring consistency with statistical records. The CIWW dataset, together with its methodology, and auxiliary data, is useful for water resource management and for research in hydrology, geography, environment, and sustainability sciences. This new dataset is now available at https://doi.org/10.6084/m9.figshare.21901074.v1 (Hou and Li, 2023).
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RC1: 'Comment on essd-2023-66', Anonymous Referee #1, 18 May 2023
This manuscript developed a gridded dataset of monthly industrial water withdrawal (IWW) for China, spanning a 56-year period from 1965 to 2020 at a spatial resolution of 0.1° and 0.25°. While the dataset covers a wide range of time, the spatial precision appears to be high. However, I have some concerns regarding the spatialization method used in the study. I think the method has too many uncertainties and strong assumptions, and the use of some definitions of industrial water is unclear. Therefore, I suggest that you make the following modifications to your manuscript to address these concerns:
Major suggestions:
1.The authors need to make the abstract more concise and focused. Instead of mentioning hydrology and geographical sustainability in a broad sense, the relevance of the dataset to specific research areas or applications should be emphasized.
2.line35-45. The author lists the spatialization methods of sectoral IWW , but does not demonstrate the shortcomings of the current methods. The low accuracy of dataset is mentioned, but how the author judges the low accuracy of these datasets is not clear.
3.line65-70. The rationale for the need for long-term and high-resolution IWW data in China requires further clarification. The reasons mentioned in the manuscript, such as water conflicts caused by increased water demand and water resource management are too broad and do not provide a specific explanation for the need of such data.
4.Why should this sentence be placed here alone.
5.In this manuscript, industrial water withdrawal and industrial water use are considered to have the same meaning. But in fact, the definitions of the two are different, industrial water use also includes industrial reuse water consumption.
6.I think the spatialization method used has a lot of uncertainties. The authors assume the industrial water use efficiency was the same for all industrial enterprises in the same province and the same subsector. A province contains large, medium and small enterprises, and their water use coefficients must be different. Also, the distribution coefficient of monthly water shortage regards the whole country as a whole, without considering the differences among provinces. Moreover, the manuscriptuse the water use efficiency of enterprises in 2008 for the spatialization of IWW from 1965 to 2020. Can the coefficient of 2008 represent the period from 1965 to 2020?
Citation: https://doi.org/10.5194/essd-2023-66-RC1 -
AC1: 'Reply on RC1', Chengcheng Hou, 08 Sep 2023
Dear Referee #1:
We deeply appreciate the reviewer for the detailed and constructive comments.
Following the helpful suggestions and comments, we have carefully revised the manuscript and provided a point-to-point response to each comment. The original comments are in bold font, our response is in regular font, and the changes in the text are blue. Please see the attachment.
Once again, we are particularly grateful for your careful reading and valuable comments.
Thank you!
Best regards,
Chengcheng Hou
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AC1: 'Reply on RC1', Chengcheng Hou, 08 Sep 2023
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RC2: 'Comment on essd-2023-66', Anonymous Referee #2, 16 Jun 2023
Hou et al. offer a new high resolution gridded water industrial water withdrawal dataset for China, covering the period 1965 through 2020. The dataset relies on inudstry data not previously adopted in national water withdrawal datasets for China, and thus offer a promising contribution for water resources studies. The method is unclear, with some very questionable assumptions, including: (a) use of a constant water efficiency estimate from 2008 to extrapolate water withdrawal through time, not giving ample consideration to possible changes in industrial water use efficiencies and production per unit of water for each industry type since the 1960s; (b) lack of units (e.g., unit of industrial output value ?), (c) unlcear descriptions of existing water data used (the term "statistical data" is used throughout... does this mean "observed", "surveyed", "modeled" ... ?); (d) repeating seasonal pattern that fails to consider the important factors raised in the introduction, including weather and climate conditions changing though time. The authors provide a limitations section that raises some of these problems. However, the assumptions lead to a dataset that fails to deliver on the stated goals of the manuscript--"a dataset with higher accuracy at fine scale." I would suggest either finding a way to extrapolate the more accurately, or reducing the ambition, so that the dataset not present water withdrawal from decades ago that is surely not credible given the assumptions used. Method must be described more clearly with all necessary details for a reader to reproduce the approach.
Citation: https://doi.org/10.5194/essd-2023-66-RC2 -
AC2: 'Reply on RC2', Chengcheng Hou, 08 Sep 2023
Dear Referee #2:
We deeply appreciate the reviewer for the detailed and constructive comments.
Following the helpful suggestions and comments, we have carefully revised the manuscript and provided a point-to-point response to each comment. The original comments are in bold font, our response is in regular font, and the changes in the text are blue. Please see the attachment.
Once again, we are particularly grateful for your careful reading and valuable comments.
Thank you!
Best regards,
Chengcheng Hou
-
AC2: 'Reply on RC2', Chengcheng Hou, 08 Sep 2023
-
RC3: 'Comment on essd-2023-66', Anonymous Referee #3, 02 Aug 2023
This paper aims to create a monthly-scale spatial distribution dataset of China's industrial water use over the past 40 years. While the method of spatial downscaling in the article is clear, there are several key issues that require further explanation.
Although the author discusses the uncertainty, it is not enough to be convinced. For instance, the author proposed that "We found that the spatial pattern from the 1998 data was similar to 2008 at 0.25˚". However, the Pearson correlation can only reflect the correlation between the variables. The author must use other statistical indicators to compare the differences between two years. In addition, the years span from 1965 to 2020. Would the enterprise data for 35 years be not changed?
The results in Figure 6d-f, which depict IWW for electricity and gas production and supply, are represented by scattered points. Can these scattered points reflect the general trend ?
Therefore, the author should address these issues in greater detail and providing a more comprehensive discussion of the uncertainties and limitations of the study.
Citation: https://doi.org/10.5194/essd-2023-66-RC3 -
AC3: 'Reply on RC3', Chengcheng Hou, 08 Sep 2023
Dear Referee #3:
We deeply appreciate the reviewer for the detailed and constructive comments.
Following the helpful suggestions and comments, we have carefully revised the manuscript and provided a point-to-point response to each comment. The original comments are in bold font, our response is in regular font, and the changes in the text are blue. Please see the attachment.
Once again, we are particularly grateful for your careful reading and valuable comments.
Thank you!
Best regards,
Chengcheng Hou
-
AC3: 'Reply on RC3', Chengcheng Hou, 08 Sep 2023
Status: closed
-
RC1: 'Comment on essd-2023-66', Anonymous Referee #1, 18 May 2023
This manuscript developed a gridded dataset of monthly industrial water withdrawal (IWW) for China, spanning a 56-year period from 1965 to 2020 at a spatial resolution of 0.1° and 0.25°. While the dataset covers a wide range of time, the spatial precision appears to be high. However, I have some concerns regarding the spatialization method used in the study. I think the method has too many uncertainties and strong assumptions, and the use of some definitions of industrial water is unclear. Therefore, I suggest that you make the following modifications to your manuscript to address these concerns:
Major suggestions:
1.The authors need to make the abstract more concise and focused. Instead of mentioning hydrology and geographical sustainability in a broad sense, the relevance of the dataset to specific research areas or applications should be emphasized.
2.line35-45. The author lists the spatialization methods of sectoral IWW , but does not demonstrate the shortcomings of the current methods. The low accuracy of dataset is mentioned, but how the author judges the low accuracy of these datasets is not clear.
3.line65-70. The rationale for the need for long-term and high-resolution IWW data in China requires further clarification. The reasons mentioned in the manuscript, such as water conflicts caused by increased water demand and water resource management are too broad and do not provide a specific explanation for the need of such data.
4.Why should this sentence be placed here alone.
5.In this manuscript, industrial water withdrawal and industrial water use are considered to have the same meaning. But in fact, the definitions of the two are different, industrial water use also includes industrial reuse water consumption.
6.I think the spatialization method used has a lot of uncertainties. The authors assume the industrial water use efficiency was the same for all industrial enterprises in the same province and the same subsector. A province contains large, medium and small enterprises, and their water use coefficients must be different. Also, the distribution coefficient of monthly water shortage regards the whole country as a whole, without considering the differences among provinces. Moreover, the manuscriptuse the water use efficiency of enterprises in 2008 for the spatialization of IWW from 1965 to 2020. Can the coefficient of 2008 represent the period from 1965 to 2020?
Citation: https://doi.org/10.5194/essd-2023-66-RC1 -
AC1: 'Reply on RC1', Chengcheng Hou, 08 Sep 2023
Dear Referee #1:
We deeply appreciate the reviewer for the detailed and constructive comments.
Following the helpful suggestions and comments, we have carefully revised the manuscript and provided a point-to-point response to each comment. The original comments are in bold font, our response is in regular font, and the changes in the text are blue. Please see the attachment.
Once again, we are particularly grateful for your careful reading and valuable comments.
Thank you!
Best regards,
Chengcheng Hou
-
AC1: 'Reply on RC1', Chengcheng Hou, 08 Sep 2023
-
RC2: 'Comment on essd-2023-66', Anonymous Referee #2, 16 Jun 2023
Hou et al. offer a new high resolution gridded water industrial water withdrawal dataset for China, covering the period 1965 through 2020. The dataset relies on inudstry data not previously adopted in national water withdrawal datasets for China, and thus offer a promising contribution for water resources studies. The method is unclear, with some very questionable assumptions, including: (a) use of a constant water efficiency estimate from 2008 to extrapolate water withdrawal through time, not giving ample consideration to possible changes in industrial water use efficiencies and production per unit of water for each industry type since the 1960s; (b) lack of units (e.g., unit of industrial output value ?), (c) unlcear descriptions of existing water data used (the term "statistical data" is used throughout... does this mean "observed", "surveyed", "modeled" ... ?); (d) repeating seasonal pattern that fails to consider the important factors raised in the introduction, including weather and climate conditions changing though time. The authors provide a limitations section that raises some of these problems. However, the assumptions lead to a dataset that fails to deliver on the stated goals of the manuscript--"a dataset with higher accuracy at fine scale." I would suggest either finding a way to extrapolate the more accurately, or reducing the ambition, so that the dataset not present water withdrawal from decades ago that is surely not credible given the assumptions used. Method must be described more clearly with all necessary details for a reader to reproduce the approach.
Citation: https://doi.org/10.5194/essd-2023-66-RC2 -
AC2: 'Reply on RC2', Chengcheng Hou, 08 Sep 2023
Dear Referee #2:
We deeply appreciate the reviewer for the detailed and constructive comments.
Following the helpful suggestions and comments, we have carefully revised the manuscript and provided a point-to-point response to each comment. The original comments are in bold font, our response is in regular font, and the changes in the text are blue. Please see the attachment.
Once again, we are particularly grateful for your careful reading and valuable comments.
Thank you!
Best regards,
Chengcheng Hou
-
AC2: 'Reply on RC2', Chengcheng Hou, 08 Sep 2023
-
RC3: 'Comment on essd-2023-66', Anonymous Referee #3, 02 Aug 2023
This paper aims to create a monthly-scale spatial distribution dataset of China's industrial water use over the past 40 years. While the method of spatial downscaling in the article is clear, there are several key issues that require further explanation.
Although the author discusses the uncertainty, it is not enough to be convinced. For instance, the author proposed that "We found that the spatial pattern from the 1998 data was similar to 2008 at 0.25˚". However, the Pearson correlation can only reflect the correlation between the variables. The author must use other statistical indicators to compare the differences between two years. In addition, the years span from 1965 to 2020. Would the enterprise data for 35 years be not changed?
The results in Figure 6d-f, which depict IWW for electricity and gas production and supply, are represented by scattered points. Can these scattered points reflect the general trend ?
Therefore, the author should address these issues in greater detail and providing a more comprehensive discussion of the uncertainties and limitations of the study.
Citation: https://doi.org/10.5194/essd-2023-66-RC3 -
AC3: 'Reply on RC3', Chengcheng Hou, 08 Sep 2023
Dear Referee #3:
We deeply appreciate the reviewer for the detailed and constructive comments.
Following the helpful suggestions and comments, we have carefully revised the manuscript and provided a point-to-point response to each comment. The original comments are in bold font, our response is in regular font, and the changes in the text are blue. Please see the attachment.
Once again, we are particularly grateful for your careful reading and valuable comments.
Thank you!
Best regards,
Chengcheng Hou
-
AC3: 'Reply on RC3', Chengcheng Hou, 08 Sep 2023
Data sets
The China industrial water withdrawal dataset Chengcheng Hou and Yan Li https://doi.org/10.6084/m9.figshare.21901074.v1
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