The study proposes a capacity loss rate (LR) index to reconstruct the water level-storage (WLS) relationship of reservoirs, utilizing measured water/sediment data and operational records. The suitability of the proposed method is evaluated through water balance principles and comparison with traditional approaches. Subsequently, the impact of reconstructed WLS curves on reservoir flood control and operation is quantified using a flood regulation algorithm with varying design inflow scenarios. The experimental design from WLS curve reconstruction to flood operation impact assessment is systematic. While the proposed methods offer practical values for reservoir management, issues remain in language expression and method application. Therefore, I recommend Major Revision for this manuscript. The detailed comments are as follows:

• The terms “Fig.” and “Figure” are used interchangeably in the manuscript. Please standardize to one format for consistency. Additionally, proofreading by a native English speaker should be conducted to improve overall language quality.
• This study uses the sediment deposition rate (Te) to calculate LR. It is recommended to introduce the concept and development history of Te in Introduction Section and reduce the examples of traditional methods to better highlight the study’s core methodology.
• For 2.1 Section of the study area, in Line 151, a period is missing after “Fig. 1”. Please revise throughout the manuscript. In Line 152, the phrase “the Wujiang River Basin has aggravated the interception of sediment” should be reworded to “sediment interception in the basin has increased”.
• In Methods Section, since the Brune model is an empirical model based on U.S. reservoir siltation survey data, its applicability to reservoir siltation calculation in China may be limited. It is suggested to add a discussion on the model’s applicability, supported by relevant literature.
• In 3.1, according to Eq. 1, as n_i in the denominator increases, the reservoir capacity loss rate LR_i also increases. This implies that LR grows over time, suggesting an unrealistic scenario where reservoirs would silt up indefinitely. Please clarify the constraints of this equation to reflect real-world limitations.
• The study establishes Brune model to calculate Te, but multiple approaches exist for this purpose. It is recommended to compare the results with those from other models in the Methods section to strengthen methodological robustness.
• The reservoir exhibits complicated morphometry, with significant variations in water depth and width. In the current study, several reservoirs (e.g., Hongjiadu and Goupitan) also cover extensive surface areas. On the other hand, the authors employ mathematical functions with exponential, polynomial and power function forms in Eqs. (3-5) to estimate reservoir water storage changes. Please address potential errors induced by the simplified estimation formula. Could the accuracy of the WLS curve be improved by subdividing the reservoir into smaller sections based on morphometry and summing their contributions?
• In Eqs. (3-5), the water level (Z) is treated as the response variable, while the reservoir water storage is the explanatory variable, Yet, the reservoir WLS curve reconstruction is evaluated based on the water storage variable. This inconsistency needs clarification.
• In Figure 1, the abbreviation for the “GLT” reservoir should be corrected to “GLQ” (Geliqiao).
• The Discussion Section should include a comparison of your WLS curve construction method with other existing approaches. Additionally, please elaborate on how the accuracy of WLS curve impacts the reliability of the water storage estimation.
• The abbreviations in the text and figures should be independent of each other. It is recommended that the corresponding vocabulary of the reservoir name abbreviations should also be clearly stated in the data methods in the manuscript text.