Vanderkelen et al. present an analysis of reservoir storage implementation in mizuRoute. The paper is very well written with excellent level of detail in method description and clear results. Results are unsurprising and lead to little in the way of new insight from a pure science perspective. The paper is therefore appropriately targeted to GMD rather than a research-oriented journal. I recommend publication if just a couple of relatively minor issues and omissions of recent data/literature can be addressed.

1. Just 26 sites are used to test the performances of the various model settings applied. This is far too few for a robust analysis of model performance.  The authors will be interested in the recent data publication by Steyaert et al. (2022), which provides daily storage and flows for approximately 700 dams in the US - https://www.nature.com/articles/s41597-022-01134-7. Although these data are US centric, they will provide a far better sample for performance analysis.

2. Discussion on limitations of Hanasaki relative to natural lake method cover inflow bias, but don't venture into much detail on the possible limitations of the generic method itself. The authors may wish to support their analysis of "Hansaki" by drawing on the very recent findings of Turner et al. (2021), which compares Hanasaki (forced with observed flow) against observation-driven rules for hundreds of US reservoirs: https://doi.org/10.1016/j.jhydrol.2021.126843. Findings therein suggest significant limitations in the generic scheme, particularly in both storage representation, which may explain weak storage performances relative to natural lake shown in Figure 5.

Other comments:

- Consider strengthening the motivation  in the introduction, particularly the final sentences (~L75 onwards) where you suggest the coupled approach "will enable to invesigate climate change impact on human water management..." As you note earlier, many hydrological models already account for water management and thus already enable impact studies. Therefore I suggest to expand on the importance of reservoir implementation in earth systems models specifically.

- Why just 1773 reservoirs at global scale? GRanD contains many more reservoirs than this.

- How are gridcells containing multple reservoirs dealth with?

As a disclaimer, I have 10+ years of experience in groundwater modeling, including parameter estimation and uncertainty quantification, but no experience in global hydrologic modeling or the simulation of reservoirs within river networks at large scales.

This paper describes an implementation of a "widely used" reservoir parameterization in the global river routing model mizuRoute, with the goal of improving simulation of reservoirs (and downstream flows), by including reservoir operation as a process. Specifically, the motivation seems to be poor representation of reservoir processes in existing global-scale hydrologic models. An approach was developed to estimate irrigation demand on water supply reservoirs, based on downstream proximity and elevation. The approach was tested first with local mizuRoute simulations at 26 sites, and found to have value vs. a simple natural lake scheme. Then the approach was tested in a global scale mizuRoute simluation. The results here were modest at best, showing little improvement from the newly developed "DAM" scheme, vs the generic natural lake ("NAT") scheme (figure 8). There appear to be a lot of confounding factors with modeling at this scale, including a low resolution and important processes such as mountain snowpacks not being considered, as well as potential shortcomings in the Community Land Model formulation. I therefore agree with the other reviewer that the purely scientific contribution of this work is modest. However, it is clear that advancing the types of models and techniques discussed here is necessarily a community effort, so there is value in publishing an attempt to address the motivating problem of reservoir simulation, even if the results are not yet satisfying enough to signify a major advance. The authors seem to acknowledge this in their discussion of potential future work.

I agree with the other reviewer that the motivation part of the paper could be strengthened. As someone who does not do global hydrologic modeling, it is a little difficult to see the importance of the work, especially given the numerous deficiencies of the global scale models that are discussed in the paper.

I also agree that the paper is very well written for the most part.

Kudos to the authors for making their workflow available on GitHub, in what appears to be a very straightforward series of Jupyter Notebooks.

Specific comments

472 The coupling of mizuRoute to CLM and CESM, which is currently ongoing, will enable routing runoff from the land to the ocean with a network-based routing mode, thereby permitting streamflow alteration by dam operations through the reservoir parametrisations.

Is section 6.4 intended to be proposal to couple the two models, or is this supposed to describe ongoing or future work? I get the sense that this is future work. With the current wording, the purpose of this section is a little unclear. I suggest including "future work" in the section heading, and maybe also restructuring the text to more clearly communicate 1) the key shortcomings of the model workflow described in this paper (ok to reiterate them for clarity, and 2) the future work that could address each of these shortcomings and how. In that sense, this section may be more useful as a "Limitations and Future Work" section.

The irrigation module in CLM is calibrated with one free parameter based on global observed irrigation water withdrawals 425 from AQUASTAT (Thiery et al., 2017, 2020).

Really? Maybe CLM is part of the reason for poor predictive skill? A single parameter implies that there are many uncertain aspects of the irrigation model that are being relegated to the model structure, where they can't be improved by data assimilation and hence are likely to contribute to model error.

Figures

Many of the outflow plots in figure A2 are hard to read (for example, the Trinity location). You might consider a logarithmic scale on the y-axis to better illustrate how the flows compare across the full range of values.

I like the way that you present multiple time series spatially in Figure 7, although the runoff comparisons don't look very good.

Technical

79 Consider changing to:

which will enable investigation of climate change impacts on human water management and the potential of water management strategies to mitigate climate change impacts on water resources.

92 Consider changing to:

This approach allows the lake and reservoir water balance to be modeled using data on precipitation and evaporation from the water surface, in combination with parametrisations providing information on the releases, including both natural outflows and regulated discharge.

194 We conducted a global land-only simulation

233 Comparing this simulation to the DAM simulation allows us to assess

435 Consider changing to:

Here, we use the HDMA river network topology and determine the HRUs contributing to reservior water demand, using simple rules based on distance and bottom elevation of river segments.

437 Consider changing to:

However, more detailed river networks, like MERIT-Hydro (Yamazaki et al., 2019) would allow for refinement of the criteria. For example, additional topological details like the Height Above Nearest Drainage index (Nobre et al., 2011; Gharari et al., 2011) could be included.

Code and data availability

The pre-print PDF appears to be missing the link to the mizuRoute code