Identification of Extreme Droughts Based on a Coupled Hydrometeorology Index from GRACE-Derived TWSA and Precipitation in the Yellow River and Yangtze River Basins

Round 1

Reviewer 1 Report

Dear Authors and Edtors,

I've added the comments to the file.

Best luck

 

Comments for author File: Comments.pdf

Author Response

We sincerely appreciate your valuable feedback on our manuscript, and we have carefully addressed each of your comments and revised our paper accordingly. Detailed responses to your comments are provided in the attached document. Thank you again for your guidance and support.

Author Response File: Author Response.pdf

Reviewer 2 Report

In the study, the authors proposed a new Copula-based Multivariate Standardize Drought Index (CMSDI) based on TWSA and precipitation data to reflect their combined effect on drought. The new index was used to detected the drought events in two large basins over 2002-2020, and was compared with other four commonly used drought indexes. The topic is interesting and suitable for the special issue of “Hydrological Responses to Climate Change”, and the methods and results are sound. The manuscript is generally well-structured, providing enough technical and experimental details, and the results are well presented. But more explanations about the result should be provided, especially for the performance differences of different drought indexes. There are several comments listed below that should be addressed.

 

Major Comments:

1.      The authors should pay more attention to and provide further explanations on the performance differences of different drought indexes (especially for Section 3.3). Differences in the results are not only related to differences in the detection capabilities of these indices, but also related to the type and definition of drought events. Based on the calculating methods, the two indexes (WSDI and CMSDI) mainly discussed in the study, are both related to hydrological drought as both indices partially (CMSDI) or completely (WSDI) consider terrestrial water storage. While the other three indexes are all meteorological drought indexes as they only refer to meteorological variables (precipitation and/or potential evapotranspiration). Drought characteristics (e.g., onset, duration and severity) of meteorological drought and hydrological drought are somewhat different. For example, as shown in Fig. 8b, the onset time of drought events detected by WSDI are typically later than that detected by CMSDI, which is known as the propagation time from meteorological drought to hydrological drought.

2.      Terrestrial water storage (TWSA), which was used to calculate drought indexes in the study, is affected by both climate change and human activities (e.g., large scale vegetation protection projects in YRB, and dense constructions of dam and reservoirs in both two basins). Human activities (e.g., reservoir operation) have greatly changed the natural conditions of TWS, and may have a significant impact on related hydrological drought. But drought indexes calculated based on meteorological variables hardly reflect those effects of human activities. This may also be a possible reason for the differences in the detection results for different indices, although these effects are difficult to quantify, they should be mentioned in the paper.

3.      More theoretical expansions about the superiority of the WSDI, as well as the drawbacks of other indexes, should be added and furtherly analyzed.

4.      As Figure 8 shows, both WSDI and CMSDI detected drought events in most years during 2002-2020 in the YZRB, but the drought events detected by WSDI are quiet less than that detected by CMSDI in the YRB. Why the comparison of the two indexes shows such great discrepancy in the two basins as higher correlations between CMSDI and WSDI has been observed in both two basins (Fig. 6).

5.      The author did a comparision study in two large basins with different climate types and hydrological conditions. As the results shows, the performance of different drought indexes are also different in the two basins. As a comparision study, more expansions about the performance difference in the two basins should be added. For example, in the arid and semi-arid YRB, drought could be more sensitive to precipitation deficit, precipitation related drought indexes (e.g., SPI) could also provide effective detection on drought events. While in the YZRB with abundant precipitation, drought could be more sensitive to water storage deficit, thus the performance of SPI is quite poor.

6.      More introductions about the calculation of different drought indexes, especially for the forcing variables, should be provided.

 

Minor Comments:

1.      Line 198: delete “above”;

2.      Line 201: Providing the full expression of “K-S test” for the first use, and essential reference is also suggested;

3.      Table 1: What are the meanings of u and v? Are they parameters or variables? Please provide more explanations about u and v;

4.      Line 269: delete “is”;

5.      Line 459: “normalization” instead of “standardization”.

Author Response

We sincerely appreciate your valuable feedback on our manuscript, and we have carefully addressed each of your comments and revised our paper accordingly. Detailed responses to your comments are provided in the attached document. Thank you again for your guidance and support.

Author Response File: Author Response.pdf

Reviewer 3 Report

The authors build a new drought index called CMSDI based on TWSA data and precipitation. By comparing with historical severe drought records, the CMSDI showed better performance in monitoring drought than other four indexes. The research has some innovation and relatively well organized. There are some specific comments:

1. There are different types of drought, and drought index CMSDI is mainly used to identify which type of drought?

2. Line 88-89, why TWSA data can reflect the human impacts on water storage? Please explain more clearly.

3. Line 97-100, I'm confused about this part. Since that a single GRACE has proven to be very good at identifying drought, why is there a need for a joint index? What is the significance of combining TWSA with precipitation that needs elaboration carefully.

4. Figure 6, the results shows that there is no significant correlation between SPEI and SPI, I seriously doubt the accuracy of your results. The two indices are calculated similarly, and normally have a very high correlation.

5. Performance assessment of CMSDI is the most important part for this paper. While the article does not do this well. In part 3.3, It does not make sense that considering identify more droughts as a better index. Using historical drought record is a suitable way, however, quantitative analysis is lacking.

6. The format of references cited in the text is not standard. Such as the authors of the document are more than one ‘et al.’ should be added.

Author Response

We sincerely appreciate your valuable feedback on our manuscript, and we have carefully addressed each of your comments and revised our paper accordingly. Detailed responses to your comments are provided in the attached document. Thank you again for your guidance and support.

Author Response File: Author Response.pdf

Reviewer 4 Report

Peer review of “Identification of extreme droughts based on a coupled hydrometeorology index from GRACE-derived TWSA and Precipitation in the Yellow River and Yangtze River basins” by Wu et al.

 Summary

 

The authors developed a novel drought index combining GRACE-derived TWSA with precipitation and compare it to four other drought indices in the Yellow River and Yangtze River basins in China. Drought indices were calculated using gridded meteorological data and GRACE data from 2002 to 2020.

Comments

 1.   This manuscript is very well written and well organized, with appropriate citations and clear figures. The authors appropriately identified sources of uncertainty in GRACE-derived TWSA data relating to the coarse spatial resolution of mascons and significant data gaps.

2.   The authors make direct comparisons between five drought indices without fully explaining the differences between them and without discussing some important consequences of those differences.

TWSA-based drought indices reflect changes in water stored in the entire water column: snow, glaciers, surface water, soil water, and groundwater. This is different from the other indices in very important ways.

 

 a.       scPDSI, SPI and SPEI assume that all precipitation falls as rain, so in cold, snowy  regions, it overestimates water availability in the winter when precipitation is stored as snow, and underestimates it in the spring when snow melts.

b.       SPI and SPEI include no consideration of water stored in soil or groundwater.

c.       scPDSI includes a primitive estimate of surficial soil water, but no  estimate of groundwater.

d.       Only TWSA reflects changes in water stored in glaciers.

e.       Water released from snow and glaciers in the spring and summer is available for evapotranspiration even in months with no precipitation, which is a source of error in SPEI in cold regions.

 

While these differences make it difficult to directly compare the drought indices, it could be helpful (in regions without snow or glaciers) to uncover the impact of groundwater extraction.

 

Author Response

We would like to express our sincere gratitude for your valuable time and effort in reviewing our manuscript. Your insightful comments and suggestions have greatly helped us to improve the quality of our work. In the following, we will address each of your comments in detail and explain the corresponding revisions made to our manuscript.

Comments

1. This manuscript is very well written and well organized, with appropriate citations and clear figures. The authors appropriately identified sources of uncertainty in GRACE-derived TWSA data relating to the coarse spatial resolution of mascons and significant data gaps.

Reply: Thank you for your positive feedback on our manuscript. We have revised the manuscript based on your comments and suggestions. We appreciate your time to review our work.

 

2. The authors make direct comparisons between five drought indices without fully explaining the differences between them and without discussing some important consequences of those differences.

TWSA-based drought indices reflect changes in water stored in the entire water column: snow, glaciers, surface water, soil water, and groundwater. This is different from the other indices in very important ways.

1. sc-PDSI, SPI and SPEI assume that all precipitation falls as rain, so in cold, snowy regions, it overestimates water availability in the winter when precipitation is stored as snow, and underestimates it in the spring when snow melts.
2. SPI and SPEI include no consideration of water stored in soil or groundwater.
3. scPDSI includes a primitive estimate of surficial soil water, but no estimate of groundwater.
4. Only TWSA reflects changes in water stored in glaciers.
5. Water released from snow and glaciers in the spring and summer is available for evapotranspiration even in months with no precipitation, which is a source of error in SPEI in cold regions.

While these differences make it difficult to directly compare the drought indices, it could be helpful (in regions without snow or glaciers) to uncover the impact of groundwater extraction.

Reply: Thank you for your valuable feedback and they are extremely helpful! We agree that the differences between the drought indices are important to consider and could have been discussed more thoroughly in the manuscript. We have revised and highlighted the manuscript, especially in the discussion section to include a more detailed discussion of the limitations and assumptions of each index. The added new section 4.1 (L. 433 - L. 469) includes the differences between TWSA-based indices and the other indices mentioned, and how these differences may impact drought identification in different regions. In future studies, we may further investigate the status of groundwater depletion and its impact on drought conditions in conjunction with actual groundwater extraction data. We appreciate again for your insightful comments and suggestions for improving our work.

Round 2

Reviewer 1 Report

Dear All,

The manuscript could be accepted for publication.

Best wishes

 

Reviewer 4 Report

Thank you for making revisions as suggested.