I am satisfied the authors addressed the issues raised by the previous reviewers, and did so in a professional and courteous manner. The one exception is with respect to improving the readability of the document, more work needs to be done in this space (please see below). In responding to the reviewers comments the authors have clearly undertaken considerable additional analysis to overcome the shortcomings in the original manuscript, including re-running the model at a finer resolution, and using different and more appropriate statistical downscaling methods. As a result the manuscript would appear to be greatly improved upon the original. However, as mentioned below the main short coming with the manuscript is that the language is still poor and quite loose in places.
I found the introduction to be long and I was unsure of its direction. Given its length I think it would be helpful to the reader if there were some subheadings to provide some additional structure this section. The introduction and consequently the entire manuscript would also benefit from a paragraph at the end of the introduction clearly describing the structure of the rest of the paper. This would greatly assist the reader follow the manuscript. There appears to be some semblance of this at the end of the introduction but I could not understand it.
Before this manuscript is published it needs to be professionally edited by a native English speaker, and the language needs to be tightened considerably to be considered for publication. The authors state in their response to review that the language has been corrected by a native English speaker, however, I found the manuscript still very difficult and slow to read. In most (though not all) cases the meaning of a sentence is apparent but only after reading the sentence multiple times. I provide a few miscellaneous examples below. There are far too many poorly worded sentences to list here.
e.g. Line 269 – “….from WRF at mountainous over 4000 m and 4800 m amsl are almost triple times as that from Gauge”.
Line 306 – “We used the data of 1986 for three preceding spin-up years.”
Line 322 – “The results confirmed that there is much heavier precipitation at high altitude in Himalya regions than what we knew from the gauge data and other gridded data set”.
Line 384 – “The annual mean temperature of Beas river basin is approximately warm up to 1.8C (RCP4.5) and 2.8 (RCP8.5)….”
Line 408 – “There is a consistent trend of projected hydrological changes over all the scenarios, although there are large uncertainities”.
Line 432 – “There are many uncertainties and challenges for the future hydrological projection under climate change in the Beas river basin”.
Line 438 – “Most common knowledge of one o fhte challenges in high mountain areas is the data issue”.
In a number of cases language is too colloquial. E.g. Line 207 – “right now”.
The word “uncertainty” is used very loosely throughout the entire manuscript. Finding a range in the output of selection of models (e.g. 6 GCM) is not a measure of “uncertainty”. In most instances it would be more appropriate to say the models displayed a large range or a large variability in results. I appreciate that this loose use of the word uncertainty is somewhat common in this field of science, nevertheless I ask the authors to be more considered in using the word “uncertainty” in this manuscript, preferably only using the term if the uncertainty is being explicitly quantified.
For example Line 109 – “Chen e al. (2011) investigated the uncertainty of six dynamical and statistical downscaling methods in quantifying the hydrological impacts under climate change in a Canadian river basin. A significant uncertainty was found to be associated with the choice of downscaling methods, which is comparable to uncertainty from GCM.” I am not familiar with this study but I suspect the authors didn’t really investigate the uncertainty but simply compared the range in output of the methods/models.
Please avoid using the phrase “water availability” unless you define it upfront. Water availability is ambiguous and means different things to different people. For example Line 63 – “reduction in water availability” – what do you mean? I honestly don’t know. Do you mean reduction in streamflow or discharge? If so why not just say a reduction in streamflow or discharge.
In a number of places the language needs to be tightened. Again too many to list every instance but for example:
Line 427 – (6) the largest increase of evaporation will be in April, with also the largest spread…” Aside from the fact the meaning of the sentence is unclear, the use of “will” is inappropriate and should be replaced with “…is projected to…”.
There are already a lot of figures and the authors have already undertaken considerable additional analysis in response to the reviewer’s comments. Hence I am hesitant to suggest additional material. However, given the authors comment that in re-running all simulations at 3*3 km resolution and that they found that the results of calibration and validation were no better than the results using 10*10 km resolution, this may be an additional finding that may be worth documenting in the manuscript. I do not recall seeing any mention of this in the manuscript. Assuming the 3 and 10 km output data constitute an apples with apples comparison the authors may like to consider structuring an additional question/aim around providing insights into the additional value provided by using a finer model resolution?
50 – “proper” – who is to say this is a “proper” representative glacier module. What makes this one proper and all others improper? They are all models after all.
69 – I suggest changing introductory sentence to paragraph to something like “…GMCs are USUALLY downscaled by an appropriate regional climate model (RCM) OR STATISTICAL DOWNSCALED for use ….” Caps are new words. Then go onto talk about RCM and their limitations before talking about statistical downscaling. Note I included usually because often many studies just use pattern scaling or simple empirical scaling methods.
79 – Are statistical downscaling methods the most popular and widely used approach? What about pattern scaling and other simple empirical scaling approaches (which are not statistical downscaling methods).
153 – I think the aims need to be rewritten. Do the authors really quantify the uncertainty in the precipitation data? What do they mean by (3) How are the uncertainties of the future water from GCMs or statistical downscaling methods? It was difficult to compare the conclusions with the aims. Furthermore the structure of the introduction doesn’t entirely sit comfortably with the order of the aims. For example it seems a little odd that the first question the paper seeks to address is the uncertainty in precipitation, yet this was the last thing discussed in the introduction.
170 – A bit unclear. Elsewhere you talk of max and min temperature. Is this mean daily temperature or mean daily maximum temperature and is it the mean daily temperature that falls below 2 C in January or the mean daily minimum temperature.
186 – two ensembles of four GCM, can you please be a little more clear, the brevity of this description is to ambiguous for such an important point.
190 – methodology – sorry but this is one of my pet hates, and you may choose to ignore me as others do . Technically and originally methodology is the study of methods (e.g. a study of different farming systems is a methodology) or the science or organisation. What you describe is a method or methods not a methodology.
195 – Did ESRI ARcGIS system v9.0 really define the glacier grid cells?
222- Does a conceptual glacio-hydrological model really mean that the glacial extent does not change in the historical simulation? To me a conceptual model simply means that one or more parameters cannot be physically assigned, and requires calibration. Maybe this sentence needs rephrasing?
306 – “We used the data of 1986…” This does not make sense.
311-314 –Note Nash-Sutcliffe efficiency (NSE) coefficient is the original reference not NSC. Also how did you select the best parameter set based on three indices? Did you equally weight them? Did you give more preference to one than the other?
314- This needs to be rephrased. It is very loose definition.
316 – annual already specified hence do not need to say mm/yr.
356 – “w.e. a-1” a-1 is not necessary given you already state this is the measured annual glacier mass balance.
435 – How is 5% during 1986-2004 (i.e. 18 years) comparable to 5% during 2003-2008 (i.e. 5 years)?? One is three times the time period of the other?
431 – This heading is misleading. No uncertainty assessment is provided.
Figures and tables
Sorry to be vague but all figure and table captions need tightening and editing.
Figure 1 – can you use a different colour ramp for elevation? The blue (low values) is too similar to the blue colour of the glaciers. Also legend should be Elevation (m) not DEM (m).
Figure 2 – Need to define JAS and DJFM so figures can be read as stand alone.
Figure 7 – This figure is hard to interpret because some of the data appear to be missing or exactly overlay on one another. Is it possible to show these more clearly. For example LOCI would appear to be missing from three of the four plots.