Thanks for your descriptive review and for highlighting the importance of our study. Your valuable comments will surely improve the quality of our manuscript. Please see below the item-to-item responses to the comments and questions in the attached reply.

Thanks for your suggestions and questions.

1.Line 164-166

As per the authors, there are around 280 precipitation gages. The spatial extent of the river basin (i.e., YZ) is around 250,000 km2. The spatial resolution of the modeling task is 10km. Therefore, the reason for using a machine-learning algorithm to develop a precipitation grid is not understood. Wouldn’t the popular interpolation algorithms that are packaged with GIS products (e.g.,Esri’s ArcGIS) improve the simulation results?

Reply:

Thanks for the comments. The gridded data obtained by interpolating observations at low altitudes tend to largely underestimate basin real precipitation due to the strong precipitation gradient created by orographic enhancements and windinduced undercatch of solid precipitation (Sun and Su, 2020). Sun and Su (2020) also compared different interpolation algorithms in the basin, and suggested that a single correction approach may not fit the entire basin. Therefore, daily precipitation with a spatial resolution of 10×10 km was used as the VIC-Glacier model forcing inputs in this work. Historical meteorological data during 1971–2100 was adopted from Sun et al. (2022), which corrected these data by machine learning algorithm based on estimates form meteorological stations and the ERA5. The daily gridded precipitation estimates from the ERA5 was corrected based on 580 rain gauges in the monsoon-dominated TP region (290 rain gauges in the YZ basin, Figure 1), and was inversely evaluated by the VIC-Glacier model, suggesting the good potential utility in model simulation in the YZ basin (Sun et al., 2022).

References

Sun, H. Su, F., 2020. Precipitation correction and reconstruction for streamflow simulation based on 262 rain gauges in the upper Brahmaputra of southern Tibetan Plateau. J. Hydrol. 590. https://doi.org/10.1016/j.jhydrol.2020.125484.

Sun, H., Yao, T., Su, F., He, Z., Tang, G., Li, N., et al., 2022. Corrected ERA5 precipitation by machine learning significantly improved flow simulations for the Third Pole basins. J. Hydrometeorol. 23. https://doi.org/10.1175/JHM-D-22-0015.1.

2. Is your DDF (see eq.2) a constant for a particular pixel/grid (10km in spatial extent)? Is your T a constant for a particular pixel/grid? This is what has been understood from your eq.2 and eq.3.If these values are constants for a particular pixel/grid, the value of your Rglac is meaningless. Without considering the temperature profile across your elevation bands, does the value of Rglac computed using eq.2 and eq.3 make sense? Without considering the vertical profile of DDF across your elevation bands, does the value of Rglac make sense? See the attached PDF file.

Reply:

Yes, the DDF is a constant for entire YZ basin, mostly due to the limited direct observations in the glacier area, with the high elevation, complex terrain and inaccessibility. T (°C) is the daily average air temperature above the glacier surface, and it is a daily series in each grid. And in this study, each glacierized grid cell underwent division into various elevation bands with an interval of 100 m, and the T is different in different bands with the temperature lapse rate in each grid.

3. For a particular grid/pixel (10km in spatial extent) of your interest, would you be able to show the values of your Ms (see eq.3)? Is the value of your “n” constant for the study area (i.e., YZ)?

Reply:

Yes, we can show the values of meltwater in each grid, and the “n” is constant for the study area.

Thanks for your descriptive review and for highlighting the importance of our study. Your valuable comments will surely improve the quality of our manuscript. Please see below the item-to-item responses to the comments and questions in the attached reply.

1. As per the authors, a lumped concept has been implemented to calculate the runoff from the glacier (see line 282-292). In other words, a calibration parameter named DDF has been used to calculate the runoff from the glacier (see line 282-292). Moreover, as per the authors, a correlation (an exponential curve) between the glacier volume and glacier area (see eq.4) has been used to compute the glacier volume given the glacier area. The initial glacier area is obtained from the first Glacier Inventory of China (CGI V1.0; see line 299-300). In the current version of the manuscript, the actual pipeline, if there exists one, between the DDF and the glacier volume(S, see eq.4) is not found. What is the relationship between DDF and S? Isn’t the glacier volume melted to get Rglac?

Reply:

The DDF was used to calculate glacier melt (glacier volume, V), and the calculated glacier area (S) was updated every year in the model by the volume-area (V-S) scaling approach.

2. I am trying to understand the relationship expressed in eq.2. Assume that the value of DDF is 10 units. I guess this value is reasonable considering the calibrated value that has been presented in the manuscript (see line 338-339). Moreover, assume that the number of elevation bands (n) is set to 1. If the air temperature is 10 units, as per eq.2 and eq.3, the calculated value of Rglac will be 100 units. Similarly, if the air temperature is 20 units, as per eq.2 and eq.3, the calculated value of Rglac will be 200 units. Do the values govern the underlying principles? Since the value of Tbase is set to 0, basically, eq.2 is a linear relationship that goes through the origin. The gradient of the line is the defining parameter (i.e., DDF). What is the physical meaning of DDF? Is it the glacier volume that could be melted given the temperature values?

Reply:

Sorry for the confusion. T (°C) is the daily average air temperature above the glacier surface, and it is a daily series in each grid. It is not a constant for each grid. It will be positive in summer and autumn, and negative in other seasons. When daily T is above 0°C, the glacier will melt; otherwise, it was accumulated. In addition, precipitation will also influence the accumulation in glacier area. Therefore, it is not a linear relationship.

Dear reviewers:

On behalf of my co-authors, thank you very much for your attention to our paper “Spatiotemporal responses of runoff to climate change on the southern Tibetan Plateau”. My co-authors and I think that all the comments are valuable and very helpful for us to improve the manuscript. We have carefully revised the manuscript according to your comments. 

Please see below the item-to-item responses to the reviewers’ comments and questions in the attached reply. We hope this manuscript will satisfy the requirement of the Hydrology and Earth System Sciences. 

Dear reviewers:

On behalf of my co-authors, thank you very much for your attention to our paper “Spatiotemporal responses of runoff to climate change on the southern Tibetan Plateau”. My co-authors and I think that all the comments are valuable and very helpful for us to improve the manuscript. We have carefully revised the manuscript according to your comments. 

Please see below the item-to-item responses to the reviewers’ comments and questions in the attached reply. We hope this manuscript will satisfy the requirement of the Hydrology and Earth System Sciences. 

Thanks for your descriptive review and for highlighting the importance of our study. Your valuable comments will surely improve the quality of our manuscript. Please see below the item-to-item responses to the comments and questions in the attached reply.