the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 22 Apr 2021
Daily standardized precipitation index with multiple time scale for monitoring water deficit across the mainland China from 1961 to 2018
Abstract. With the increasing shortage of water resources, drought has become one of the hot issues in the world. The standardized precipitation index (SPI) is one of the widely used drought assessment indicators because of its simple and effective calculation method, but it can only assess drought events more than one month. We developed a new multi-scale daily SPI dataset to make up for the shortcomings of the commonly used SPI and meet the needs of drought types at different time scales. Taking three typical stations in Henan, Yunnan and Fujian Province as examples, the drought events identified by SPI with different scales were consistent with the historical drought events recorded. Meanwhile, we took the 3-month scale SPI of soil and agricultural drought as an example, and analyzed the characteristics of drought events in 484 stations in Chinese mainland. The results showed that most of the drought events the mainland China did not increase significantly, and some parts of the northwestern Xinjiang and Northeast China showed signs of gradual relief. In short, our daily SPI data set is freely available to the public on the website https://doi.org/10.6084/m9.figshare.14135144, and can effectively capture drought events of different scales. It can also meet the needs of drought research in different fields such as meteorology, hydrology, agriculture, social economy, etc.
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Interactive discussion
Status: closed
-
RC1: 'Comment on essd-2021-105', Anonymous Referee #1, 10 May 2021
The authors present a common methodology and analysis for the drought index SPI with 1-month scale, 3-month scale, 6-month scale, 9-month scale and 12-month scale over China. It is meaningful for the drought research in different fields. However, the daily SPI is wider used, since many studies have carried out the drought research in China using daily SPI (e.g. Xie et al., 2019 (in Chinese)). The method of gamma distribution used for calculating SPI is common with no special changes. Additionally, there are still some detailed analyses needed for improving the quality of this manuscript.
Specific comments:
- Introduction: The necessity of this study is not clearly described and lack of logic, e.g. in this section the authors do not explain shortcomings of existing SPI (on daily scale), and why they need to do this research.
- Daily SPI calculation: The method used in this manuscript refers to McKee et al., 1993 and 1995 without special changes, which has been used in many studies, such as Guttman, 1998 and 1999, Mcgree et al., 2016 and 2019, Turco et al., 2020, and so on.
- Table 1: It should be added some references, such as McKee et al., 1993 or Guttman, 1999.
- Analysis of drought characteristics of typical stations: Why the authors selected these three stations not the others, some reasons are needed for this. And there should be some comparisons with similar data products or using other means for validating the reliability and superiority of the daily SPI in this manuscript, not just a few examples from Chinese Disaster Dictionary and Disaster Yearbook.
- L310-311: Is the expression correct? Please check it.
- Figure 6b-8b: The symbols for P-value are blurring.
The references mentioned above are as follows:
- Guttman, N., B.: Comparing the palmer drought index and the standardized precipitation index, Journal of the American Water Resources Association, 34(1): 113-121, 1998.
- Guttman, N., B.: Accepting the standardized precipitation index: A calculation algorithm, Journal of the American Water Resources Association, 35(2): 311-322, 1999.
- Mcgree, S., Schreider, S., and Kuleshov, Y.: Trends and variability in droughts in the Pacific Islands and Northeast Australia, Journal of Climate, 29: 8377-8397, http://doi.org/ 10.1175/JCLI-D-16-0332.1, 2016.
- Mcgree, S., Herold, N., Alexander, L., Schreider, S., Kuleshov, Y., Ene, E., Finaulahi, S., Inape, K., Mackenzie, B., Malala, H., Ngari, A., Prakash, B., and Tahani, L.: Recent changes in mean and extreme temperature and precipitation in the Western Pacific Islands, Journal of Climate, 32: 4919-4941, http://doi.org/ 10.1175/JCLI-D-18-0748.1, 2019.
- Turco, M., Jerez, S., Donat M., G., Toreti, A., Vicente-Serrano, S., M., and Doblas-Reyes F., J.: A global probabilistic dataset for monitoring meteorological droughts, BAMS, E1628-E1644, https://doi.org/10.1175/BAMS-D-19-0192.2, 2020.
- Xie, W. S., Tang W. A., and Song, A., W.: Applicability study of SPI in multiple time scales in meteorological drought monitoring in Anhui Province, Meteorological Monthly (in Chinese), 45(11): 1560-1568, https://doi.org/10.7519/j.issn.1000-0526.2019.11.006, 2019.
Minor comments:
- L93: “Theses”-> “These”
- L95: “except of”-> “except for”
Citation: https://doi.org/10.5194/essd-2021-105-RC1 -
RC2: 'Comment on essd-2021-105', Anonymous Referee #2, 11 May 2021
This manuscript (ID: essd-2021-105) developed a new multi-scale daily SPI dataset to make up for the shortcomings of the commonly used SPI. Three typical sites were used as examples to validate the data set, and the drought characteristics of 484 sites in mainland China are analyzed. SPI is one of the very important indicators in drought assessment and drought monitoring. Authors improved the commonly used monthly SPI, which can identify flash droughts less than one month and can accurately identify the start and end dates of drought events. The study is timely and important, and the produced datasets are useful for various types of drought research, like meteorology, hydrology, agriculture, social economy, etc.
In general, the improved SPI datasets in this article have been carefully validated and are consistent with the official record of historical drought events, suggesting the derived datasets should be reliable for use. The paper fits well with the scope of the ESSD, therefore, I recommend it to be accepted with minor revisions.
The authors need to check the text carefully to avoid confusing sentences.
Please see below for detailed comments:
(1) I suggest that the authors clarify and explain in the introduction why they chose three typical sites in Henan, Yunnan, and Fujian.
(2) Line38: “most of the drought events the mainland China” should be revised into “most of the drought events in mainland China”.
(3) Line48: “severe natural disasters” should be revised into “severe natural disaster”.
(4) Line52: “is suffer to” should be revised into “is suffering to”.
(5) Line 59: “Drought have induced the severe economic impacts” should be revised into “Drought has induced severe economic impacts”.
(6) Line66: It appears that “evidences” is an uncountable noun and should not be made plural. Consider changing the noun.
(7) Line71: “at the large scale” should be revised into “at a large scale”.
(8) Line72: “drought risks management” should be revised into “drought risk management”.
(9) Line80: “different type drought” should be revised into “different drought types”.
(10) Line108: It appears that you have an unnecessary comma after “precipitation”. Consider removing it.
(11) Line126: The word “though” doesn’t seem to fit this context. Consider removing it.
(12) Line129: “develop SPI to daily resolution” should be revised into “develop SPI with daily resolution”.
(13) Line144: It appears that you typed “growth” twice in a row.
Citation: https://doi.org/10.5194/essd-2021-105-RC2 -
EC1: 'Comment on essd-2021-105', Qingxiang Li, 19 Jun 2021
Two reviews are in that both suggest the paper needs to be improved much.
However, we also feel that from a broader perspective, this is not a good fit for ESSD. Perhaps other research journals would be better suited to publish this manuscript. The reasons are :
- No new data are presented, already published data are rescaled.
- This paper is designed as a research paper, trying to asses increase/decrease of draught events, as outlined in the abstract.
Citation: https://doi.org/10.5194/essd-2021-105-EC1
Interactive discussion
Status: closed
-
RC1: 'Comment on essd-2021-105', Anonymous Referee #1, 10 May 2021
The authors present a common methodology and analysis for the drought index SPI with 1-month scale, 3-month scale, 6-month scale, 9-month scale and 12-month scale over China. It is meaningful for the drought research in different fields. However, the daily SPI is wider used, since many studies have carried out the drought research in China using daily SPI (e.g. Xie et al., 2019 (in Chinese)). The method of gamma distribution used for calculating SPI is common with no special changes. Additionally, there are still some detailed analyses needed for improving the quality of this manuscript.
Specific comments:
- Introduction: The necessity of this study is not clearly described and lack of logic, e.g. in this section the authors do not explain shortcomings of existing SPI (on daily scale), and why they need to do this research.
- Daily SPI calculation: The method used in this manuscript refers to McKee et al., 1993 and 1995 without special changes, which has been used in many studies, such as Guttman, 1998 and 1999, Mcgree et al., 2016 and 2019, Turco et al., 2020, and so on.
- Table 1: It should be added some references, such as McKee et al., 1993 or Guttman, 1999.
- Analysis of drought characteristics of typical stations: Why the authors selected these three stations not the others, some reasons are needed for this. And there should be some comparisons with similar data products or using other means for validating the reliability and superiority of the daily SPI in this manuscript, not just a few examples from Chinese Disaster Dictionary and Disaster Yearbook.
- L310-311: Is the expression correct? Please check it.
- Figure 6b-8b: The symbols for P-value are blurring.
The references mentioned above are as follows:
- Guttman, N., B.: Comparing the palmer drought index and the standardized precipitation index, Journal of the American Water Resources Association, 34(1): 113-121, 1998.
- Guttman, N., B.: Accepting the standardized precipitation index: A calculation algorithm, Journal of the American Water Resources Association, 35(2): 311-322, 1999.
- Mcgree, S., Schreider, S., and Kuleshov, Y.: Trends and variability in droughts in the Pacific Islands and Northeast Australia, Journal of Climate, 29: 8377-8397, http://doi.org/ 10.1175/JCLI-D-16-0332.1, 2016.
- Mcgree, S., Herold, N., Alexander, L., Schreider, S., Kuleshov, Y., Ene, E., Finaulahi, S., Inape, K., Mackenzie, B., Malala, H., Ngari, A., Prakash, B., and Tahani, L.: Recent changes in mean and extreme temperature and precipitation in the Western Pacific Islands, Journal of Climate, 32: 4919-4941, http://doi.org/ 10.1175/JCLI-D-18-0748.1, 2019.
- Turco, M., Jerez, S., Donat M., G., Toreti, A., Vicente-Serrano, S., M., and Doblas-Reyes F., J.: A global probabilistic dataset for monitoring meteorological droughts, BAMS, E1628-E1644, https://doi.org/10.1175/BAMS-D-19-0192.2, 2020.
- Xie, W. S., Tang W. A., and Song, A., W.: Applicability study of SPI in multiple time scales in meteorological drought monitoring in Anhui Province, Meteorological Monthly (in Chinese), 45(11): 1560-1568, https://doi.org/10.7519/j.issn.1000-0526.2019.11.006, 2019.
Minor comments:
- L93: “Theses”-> “These”
- L95: “except of”-> “except for”
Citation: https://doi.org/10.5194/essd-2021-105-RC1 -
RC2: 'Comment on essd-2021-105', Anonymous Referee #2, 11 May 2021
This manuscript (ID: essd-2021-105) developed a new multi-scale daily SPI dataset to make up for the shortcomings of the commonly used SPI. Three typical sites were used as examples to validate the data set, and the drought characteristics of 484 sites in mainland China are analyzed. SPI is one of the very important indicators in drought assessment and drought monitoring. Authors improved the commonly used monthly SPI, which can identify flash droughts less than one month and can accurately identify the start and end dates of drought events. The study is timely and important, and the produced datasets are useful for various types of drought research, like meteorology, hydrology, agriculture, social economy, etc.
In general, the improved SPI datasets in this article have been carefully validated and are consistent with the official record of historical drought events, suggesting the derived datasets should be reliable for use. The paper fits well with the scope of the ESSD, therefore, I recommend it to be accepted with minor revisions.
The authors need to check the text carefully to avoid confusing sentences.
Please see below for detailed comments:
(1) I suggest that the authors clarify and explain in the introduction why they chose three typical sites in Henan, Yunnan, and Fujian.
(2) Line38: “most of the drought events the mainland China” should be revised into “most of the drought events in mainland China”.
(3) Line48: “severe natural disasters” should be revised into “severe natural disaster”.
(4) Line52: “is suffer to” should be revised into “is suffering to”.
(5) Line 59: “Drought have induced the severe economic impacts” should be revised into “Drought has induced severe economic impacts”.
(6) Line66: It appears that “evidences” is an uncountable noun and should not be made plural. Consider changing the noun.
(7) Line71: “at the large scale” should be revised into “at a large scale”.
(8) Line72: “drought risks management” should be revised into “drought risk management”.
(9) Line80: “different type drought” should be revised into “different drought types”.
(10) Line108: It appears that you have an unnecessary comma after “precipitation”. Consider removing it.
(11) Line126: The word “though” doesn’t seem to fit this context. Consider removing it.
(12) Line129: “develop SPI to daily resolution” should be revised into “develop SPI with daily resolution”.
(13) Line144: It appears that you typed “growth” twice in a row.
Citation: https://doi.org/10.5194/essd-2021-105-RC2 -
EC1: 'Comment on essd-2021-105', Qingxiang Li, 19 Jun 2021
Two reviews are in that both suggest the paper needs to be improved much.
However, we also feel that from a broader perspective, this is not a good fit for ESSD. Perhaps other research journals would be better suited to publish this manuscript. The reasons are :
- No new data are presented, already published data are rescaled.
- This paper is designed as a research paper, trying to asses increase/decrease of draught events, as outlined in the abstract.
Citation: https://doi.org/10.5194/essd-2021-105-EC1
Data sets
Muliti-scale daily SPI dataset over the Mainland China from 1961-2018 (version March 2021) Wang, Q., Zhang, R., Qi, J., Zeng, J., Zhang, X., Wu, X., Zhou, X., and Ren, B. https://doi.org/10.6084/m9.figshare.14135144
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