the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 11 Jul 2024
Runoff component quantification and future streamflow projection in a large mountainous basin based on a multidata-constrained cryospheric-hydrological model
Abstract. The Yarlung Tsangpo River (YTR) is one of the several major rivers originating from the Tibetan Plateau (TP) and plays a pivotal role in providing invaluable fresh water to its downstream countries. Large uncertainties existed in the studies related to streamflow variations in this basin, and the investigation is difficult due to the widely distributed snowpack, glaciers and permafrost and their complex effects on hydrological processes. In this study, we conducted a systematic analysis on the streamflow variations and runoff components in the YTR basin, using a physically-based hydrological model validated by streamflow and multiple datasets related to cryospheric processes. Main findings include (1) The contributions of snowmelt and glacier melt runoff to streamflow were limited, both for about 5~6 % for the whole basin, which might be overestimated by previous studies. (2) Under the climate change, the annual runoff would increase evidently in the future. The relative change of annual streamflow could exceed 90 mm (~38 %) at the outlet station in the far future compared to the historical period under the high emission scenario, while the amount and contributions of meltwater runoff would both decrease. (3) Adopting more observational data to calibrate the hydrological model played a critical role in reducing the uncertainty of hydrological simulation. The biases of snow and glacier simulation for data unconstrained led to a marked overestimation of contributions of snowmelt and glacier melt runoff to streamflow and further brought about an underestimation of the increasing trends of annual runoff by approximately 5~10 % in future projection. These results provide a relatively reliable reference of the streamflow change and the runoff components in both historical and future periods in the YTR basin, and have the potential to serve as a “reference value” in this region because we used more datasets to constrain the model uncertainty compared to previous studies.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2024-1464', Anonymous Referee #1, 09 Aug 2024
I appreciate the opportunity to review the manuscript, entitled "Runoff component quantification and future streamflow projection in a large mountainous basin based on a multidata-constrained cryospheric-hydrological model." The topic of this study is of great importance not only to the earth and environmental science community but also to policymakers and practitioners such as hydropower companies and water resource managers. This study presents an attempt to systematically analyze streamflow variations and runoff components in the Yarlung Tsangpo River (YTR) basin using a physically-based hydrological model validated by streamflow and multiple datasets related to cryospheric processes. Despite some limitations, the proposed method is capable of reconstructing the sediment yield over the past decades with satisfactory performance.
Overall, I like the study and would recommend a moderate revision before publication. Below are my major and specific comments.
Major Comments
Comment 1: Model Validation and Result Presentation
Based on the modeling scheme, model validation should target multiple hydrological processes, including streamflow, snow, and glaciers. The authors used multiple datasets to validate the model, which is commendable. However, in the results section, the authors seem to focus primarily on streamflow validation. It is suggested that the authors provide a more detailed presentation of the validation results for snow water equivalent (SWE), snow cover area (SCA), and glacier mass balance (GMB) to comprehensively evaluate the model's performance.
Comment 2: Simulation of Extreme Events
Typically, extreme hydrological events contribute significantly to annual runoff and can have severe socio-economic impacts. However, daily-scale models often underestimate these extreme events. Have the authors considered the model's performance in simulating extreme events? If there is underestimation, can the model structure or parameterization be improved to enhance simulation accuracy?
Comment 3: Uncertainty Analysis in Future Projections
The authors used data from 10 CMIP6 global climate models for future projections, which is a robust approach. However, significant differences may exist between different climate models. It is recommended that the authors provide a more detailed analysis of these inter-model differences and discuss how they affect the uncertainty in future streamflow projections.
Comment 4: Focusing on the different time periods
The authors adopt different time periods in different parts, which makes me really confused. For example, 1980-2018 is used for model calibration and validation, 1960-2020 is used for the historical trend analysis, 1960-2014 is the historical period of CMIP6 (L202), and 1980-2009 was used as the baseline of historical simulation. I suggest authors to summarize the different time period adopted in different analyses, and clarify the reason why different time periods are adopted.
Specific Comments
- Abstract: The abstract can be substantially shortened to one paragraph. It should focus on the study's innovation and main findings.
- Introduction: The introduction lacks acknowledgment of existing literature on multi-decadal sediment observations in other high mountain areas and cold regions such as the Andes and the Arctic. Supplementing this literature would enhance the comprehensiveness of the research background.
- Methods: The methods section should detail how multiple datasets were integrated into model calibration and how the weights of each dataset were determined.
- Discussion: The discussion section could delve deeper into the mechanisms by which climate change affects runoff components, particularly the reasons for the reduction in contributions from snowmelt and glacier melt. Additionally, comparing the findings with studies from other cold regions would enhance the depth of the discussion.
- Conclusions: The conclusion should more clearly summarize the main findings and point out the study's limitations and future research directions.
- Figures and Data: The clarity and informativeness of the figures need improvement. For instance, include the summer discharge trends in Figures 7c-d and ensure consistency with the main text.
- References: It is recommended to supplement relevant references to place this study in a wider framework of when discussing the impact on hydropower and comparing with other related studies. https://doi.org/10.1038/s41561-022-00953-y; https://doi.org/10.1002/hyp.14633; https://doi.org/10.1016/j.geosus.2024.01.001
Additionally there are several very minor issues that need to be addressed:
- L24-25: This statement is rather strong. Maybe better to remove it from the abstract and mention it somewhere in the discussion section.
- L108: There are totally more than 20 GCMs in CMIP6, so how did you select these 10 GCMs?
- L117: Provide the full name of PMV.
- L127: “CGM” should be “GCM”.
- L133-134: Difficult to follow. Maybe provide the specific equation here.
- Table 5: In the notes for DG and DS, “calculated” should be “considered”.
- L188: The historical trend analysis seems to be a separate part from the manuscript. Consider adding some transitional text when describing the methods and results.
- Table 7 and 8: There are two “1980-2009” for discharge NSE; add the unit for the RMSE of SWE and GMB.
- L300-301: Delete this sentence, since “ALL” is the most reliable variant, as mentioned several lines below.
- Figure 7 and 8: Consider adding the simulations obtained by “DSG” variant (if this makes the figure too large, maybe add them in Supplementary Materials). We cannot know the specific performance on these elements (e.g., overestimation or underestimation) solely based on the NSE and RMSE.
- L319-320: Is this “insignificantly” referring to visual or statistical significance?
Overall, this study addresses an important topic with significant implications for understanding hydrological processes in the Tibetan Plateau. The use of multiple datasets to constrain the model is commendable. However, there are areas where the analysis and presentation could be improved. I hope these comments will be helpful in revising and strengthening the manuscript.
Citation: https://doi.org/10.5194/egusphere-2024-1464-RC1 - AC1: 'Reply on RC1', Mengjiao Zhang, 09 Oct 2024
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RC2: 'Comment on egusphere-2024-1464', Anonymous Referee #2, 29 Sep 2024
This manuscript provides a detailed analysis of runoff components and future streamflow projections in the Yarlung Tsangpo River (YTR) basin using a multi-data-constrained cryospheric-hydrological model. The study successfully integrates multiple observational datasets to validate the model, which enhances the reliability of hydrological simulations in a region with complex cryospheric processes. The findings indicate that snowmelt and glacier melt contribute relatively little to the total streamflow compared to previous studies. Here are some suggestions.
1. The introduction of this study is too general. It is recommended to carefully review existing literature on runoff changes and model simulations in the Yarlung Tsangpo River basin and identify the gaps. After reading through the manuscript, I believe the highlight of this paper is the use of multiple datasets and objective functions to calibrate the model and the comparison of runoff and its component changes under different scenarios.
2. The description of the model section in the manuscript is too brief. Please provide a more detailed explanation of how the model represents glaciers and snow cover, and clearly define the terms snowmelt runoff and glacier runoff.
3. In the Data and Methods section, please elaborate on how the future meteorological data were bias-corrected.
4. Please add a discussion section to explore the impact of uncertainties in the historical and future meteorological data used in this study on the model simulations.
Citation: https://doi.org/10.5194/egusphere-2024-1464-RC2 - AC2: 'Reply on RC2', Mengjiao Zhang, 09 Oct 2024
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