Improved Resolution of Drought Monitoring in the Yellow River Basin Based on a Daily Drought Index Using GRACE Data
Round 1
Reviewer 1 Report
Comments and Suggestions for Authors-The title of the study indicates a novel drought index combining GRACE and GNSS; however, there is no related objective in lines 95-100.
-There is no clarity on how this novel index was constructed. The method section presented TWSA Reconstruction, Time Series Decomposition, GNSS Inversion and concluded with the severity index. The method section is vague and needs to be rewritten.
-Line 229. This is a drought severity index, not a comprehensive drought index; however, if some wish to use it for drought duration or frequency analysis, then how can this index be utilized? Please elaborate or change the title of the study.
-What are the criteria for DDSI classification?
-Why is the reconstruction of climate-driven water storage anomalies carried out? Please elaborate on it.
-What are the dots in Figure 10 a?
Figure 11 shows that DDSI does not capture drought events as accurately as scPDSI. Please explain.
-Figure 12. Spatial distribution during peak periods of historical drought events based on DDSI? If so, then why is there a significant difference between Figure 11 and the others?
-Refine the discussion part. These are like the results, not the discussion.
Author Response
Please see the attachment.
Author Response File: 
Author Response.pdf
Reviewer 2 Report
Comments and Suggestions for AuthorsQ1. The current abstract needs to be improved, as follows:
- The Gravity Recovery and Climate Experiment (GRACE) and Global Navigation Satellite System (GNSS) should come with their full names.
- Long-term use of GRACE then should be GRACE and its Follow-On mission (GRACE-FO)?
- Please numerically label major findings, e.g., (1), (2), etc.
Q2. In keywords, consider including “China.”
Q3. The Introduction needs major improvements, as follows:
- L36-37: This sentence lacks reference, please provide to correctly claim it “Climate change is a global challenge facing the world at present, and its impacts are becoming more visible (suggest 10.1016/j.scitotenv.2024.174289)”. Similarly, do for L37-39,
- L43-45: GRACE and its Follow-On mission (GRACE-FO)?
- L45-47: This sentence lacks reference to correctly claim “GRACE opens a new approach to monitoring extreme hydrological events with its comprehensive spatial coverage, high accuracy, and independence from weather conditions (10.1038/s43247-024-01532-2).”
- L88: Please provide the full name of SPI before using its abbreviation.
- L100: After objective (3), please include a general sentence show highlight how the findings of this work will gap-fill or add new knowledge to the current literature.
Q4. L106-109: Please include references for these claims “Region gradually decreases in elevation from west to east, and the west is mainly dominated by high mountains, while the eastern region suffers from flooding. Located in the mid-latitudes, the YRB relies on natural precipitation to recharge the water reserves. However, the rainfall in the region is low and spatially uneven.”
Q5. Figure 1, can the authors add the Geological map of China either (1) in a mini-map at the corner or (2) background of the current map?
Q6. Although the reconstructed TWSA (REC_TWSA) shows a good overall correlation with CSR_TWSA (CC = 0.94), the accuracy significantly drops during years with extreme climate events. The authors note poor performance in 2013 and 2016, years marked by abnormal precipitation and drought. This limitation suggests that the model may be insufficiently sensitive to rapid or extreme hydrological changes, which are crucial for operational drought monitoring and early warning.
Q7. The GNSS-derived TWSA shows notably lower correlation coefficients with other datasets compared to the reconstructed GRACE-based TWSA. While GNSS inversion is a useful alternative, the relatively weak agreement with other datasets raises concerns about its standalone reliability, especially in areas with sparse station coverage.
Q8. Despite using complex methods such as MCMC calibration and multiple data sources, the uncertainty analysis is minimal or qualitative only. There is no detailed propagation of errors across datasets (GRACE, GNSS, REC_TWSA, etc.) or discussion of spatial/temporal variance in uncertainties. While the study mentions “error” in calibration and gives ± values for trends (e.g., TWSA trend in lower reaches: –24.94 ± 1.13 mm/yr), there is no comprehensive uncertainty map or statistical evaluation of how these errors influence conclusions drawn about drought severity or human influence. Given the study’s reliance on reconstructed datasets and model-based separation of human vs. climate effects, more rigorous uncertainty quantification is essential for validating the robustness of these conclusions.
Q9. In conclusion, can the authors add a short and brief general highlight of how these findings could help other works, stakeholders, and authors, in terms of drought monitoring and prevention?
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Reviewer 3 Report
Comments and Suggestions for AuthorsThe authors address an important and timely issue, namely the long-term monitoring of drought, using the Yellow River Basin in China as a case study.
The analysis combines GRACE and GNSS data, introducing a new drought index. The main goal of the analysis is to provide a more comprehensive perspective and improved accuracy in drought monitoring.
Overall, the manuscript is well written and structured. The English is fine and does not require any improvement. The references are relevant and relatively recent.
Regarding the analysis presented in the manuscript, I have the following major comments:
- A “new drought index” is mentioned, but there is insufficient and unclear information about how it is constructed or how it combines GRACE and GNSS data.
- The advantages of this index compared to existing methods (SPI, SPEI, etc.) should be emphasized more clearly.
- It is necessary to explain in more detail how this index performs better and achieves greater accuracy (including quantitative information). The calibration and validation process of this index should also be described in more depth.
- Relevant information should be provided regarding the limitations of the proposed model, clearly highlighting the uncertainties associated with the combination process, etc.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Round 2
Reviewer 1 Report
Comments and Suggestions for AuthorsThe authors have addressed all my comments. This manuscript could be accepted for publication.
Reviewer 2 Report
Comments and Suggestions for AuthorsThank you for the revision, I have no further comments.
Reviewer 3 Report
Comments and Suggestions for AuthorsThe authors responded adequately to my observations.
