Thanks for these valuable comments on our manuscript. The reviewer is right that we, in this manuscript for the special issue on History in Hydrology, took a somewhat inward look by focusing on the history of the HBV model. A full review of the history of catchment modelling would be beyond the scope of this manuscript, but we will try to be a bit more self-reflecting in the revised version.

Beyond we shortly discuss how we will address the points raised in the reviewers list:

1. Yes, the term hydrological modeling is broader than we use it here. Your suggestion was to change this to rainfall-runoff modelling. As snow is an important part in many HBV studies, this should be precipitation-runoff modelling, or perhaps even precipitation-temperature-runoff modelling – but then there is also potential evapotranspiration as input. Therefore, we will instead change this to ‘catchment modelling’.
2. Yes, we agree that for other types of hydrological models other issues than those discussed here from the aspect of (conceptual) catchment models will be important. We will clarify the more narrow focus of the discussion in our manuscript (see also point 1).
3. Good point, we will not repeat the full (interesting) discussion between these papers, but agree that we should refer to this discussion.
4. Yes, we realize that our use of the term hydrological modelling might cause confusion as we are focusing on catchment (runoff) models here (and not all the other types of hydrological models)
5. Thanks
6. Agreed, we will change the heading to ‘Early catchment models’
7. We here wanted to express that the differences between a simple model and a model based on equations such as Darcy might not be so large if the latter is applied using elements or parameterizations that do not capture the real-world heterogeneities. We will clarify this section.
8. Good point; we will consider implementing these thoughts in the revised version.
9. We agree and will clarify these important details of Breuer et al. (2009) in the revised version.
10. We agree that many hydrologists working with modelling would say that all kinds of catchment models need some form of calibration. However, we also still meet the notion that more complex models with ‘measurable’ parameters would not require calibration or at least not as much calibration (thus, using other terms such as tuning) by colleagues working with these, in their eyes superior, models. We appreciate the nuanced discussion in Hrachowitz & Clark (2017) and also the reviewer statement that the view on the need for calibration has changed over the years. We will include the H&C reference and would, if the reviewer does not object, also add a pers.com. reference to include the changing-ideas-on-calibration point.
11. The (international) success of the HBV model is in our opinion much related to the 3 P-s (parsimony, performance, persistence) as mentioned in the introduction and above in section 3. The parsimony made the model code easy to understand (and re-program), the HBV model often performed well especially in comparison studies, and it certainly helped that the model was intensely used by SMHI and the hydrological services of Norway and Finland, and became a standard tool for the Nordic hydropower industry (opposite to a single researcher or research group as was the case for other models). We will add these thoughts in section 3.3.
12. We agree that new sources of data (including spatial patterns derived from remote sensing) might open new opportunities, but as we write there is a challenging balance between more available data and more model complexity to make these data directly usable for model evaluation. We argue that this applies to any type of catchment model but also see some promising studies such as the one by Stisen et al.. We will modify the text to clarify that we see multi-criteria calibration as a suitable way forward although this approach is challenging in practice. Actually, we have used multi-criteria calibration also in applications of the HBV-model (e.g., Seibert, 2000; Bergström et al. 2002).

Bergström S, Lindström G, Pettersson A. 2002. Multi-variable parameter estimation to increase confidence in hydrological modelling. Hydrological Processes 16: 413–421.

Seibert, J., 2000. Multi-criteria calibration of a conceptual rainfall-runoff model using a genetic algorithm. Hydrology and Earth System Sciences, 4(2): 215-224.

Again, thanks for these valuable comments and interesting thoughts that will help us clarify the manuscript.

Best regards,

Jan and Sten

We appreciate this detailed review of our manuscript. We are glad that our somewhat unusual style is seen as positive. The reviewer lists three more general remarks and a number of detailed comments. In the attached pdf, we discuss how we will address these in the revised version of the manuscript (reviewer comments in blue italic font)

Dear Stein,

Thanks for your comment on our manuscript. We fully agree that many HBV concepts can also be used in distributed approaches. We appreciate that you reminded us about these papers which will be a good basis for discussing this aspect in some more detail.

Best regards,

Jan and Sten

We appreciate the positive assessment of our manuscript and the helpful list of comments. Especially we like the statement, “This is a nicely written story about the HBV model in the context of hydrological model developments in the last 50 years. The style of the paper is somewhat unusual - casual but certainly acceptable.” Here we reply to the seven points raised by the reviewer:

• Good point. We are afraid to make the manuscript harder to read if we insert the model equations. However, we could add an appendix similar to the one we had in Seibert&Vis (2012).
• We agree on this potential for physically-based models like SHE, although we might be less optimistic that the additional constraints (always) compensate for the increased degrees of freedom. But of course, there are applications where we need a better representation of internal fluxes and states. We will clarify this in the revised version.
• Thanks for making us aware that we missed discussing evapotranspiration in any detail. We will add some information on evapotranspiration, especially how to derive Epot for the input, in the revision.
• The often limited sensitivity to random errors is indeed an advantage of HBV, but also other water balance accounting errors. We agree that this is another reason why such models often perform well despite not-so-good input data. We see this related to one of the three P-s and will add this valuable thought to the discussion of model performance.
• Thanks for making us aware of this interesting study. We will add the use of HBV for land-use change studies as suggested by Hundecha and Bárdossy (2004) in section 4.1
• With “insignificant subroutines” we meant subroutines that are not affecting the (runoff) simulation substantially. Following the comment, we will change this to “subroutines representing insignificant process details”
• We agree that it is an interesting question how models like HBV can make use out of different types of data and happily will make this clearer in the revision. We assume the term ‘indirect data’ refers to data such as soft data (Seibert and McDonnell, 2002), data collected by the public in citizen science projects, or as a by-product of social media (e.g., Twitter), or other types of ‘unusual’ data sources.

Hundecha, Y., Bárdossy, A., 2004. Modeling of the effect of land use changes on the runoff generation of a river basin through parameter regionalization of a watershed model. J. Hydrol. 292, 281–295. https://doi.org/10.1016/j.jhydrol.2004.01.002

Seibert, J., and J. J. McDonnell, 2002. On the dialog between experimentalist and modeler in catchment hydrology: Use of soft data for multicriteria model calibration, Water Resour. Res., 38(11), 1241, doi:10.1029/2001WR000978.

Seibert, J. and Vis, M. J. P.: Teaching hydrological modeling with a user-friendly catchment-runoff-model software package, Hydrol. Earth Syst. Sci., 16, 3315–3325, https://doi.org/10.5194/hess-16-3315-2012, 2012.