WBM: A scalable gridded global hydrologic model with water tracking functionality
- 1Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, 03824, US
- 2Department of Natural Resources and the Environment, University of New Hampshire, NH, 03824, USA
- 1Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH, 03824, US
- 2Department of Natural Resources and the Environment, University of New Hampshire, NH, 03824, USA
Abstract. This paper describes the University of New Hampshire Water Balance Model, WBM, a process-based gridded global hydrologic model that simulates the land surface components of the global water cycle and includes water extraction for use in agriculture and domestic sectors. WBM has a long publication history; here we describe the first fully open source WBM version. This version includes a suite of water source tracking modules that enable analysis of flow-path histories on water supply. Earlier descriptions of WBM methods provide the foundation of the most recent model version detailed here. WBM is available here: https://github.com/wsag/WBM. WBM is written in the perl data programming language (PDL), making use of several open-source perl libraries. As a convenience we also provide a Singularity container that simplifies installation of dependencies. We present an overview of the model functionality, utility, and validation of global river discharge and irrigation water use using data from the Global Runoff Data Centre and FAO statistics. A key feature of WBM is the ability to identify the partitioning of sources for each stock or flux within the model. Therefore, users can determine what proportion of any flux consists of each of the primary inputs of water to the surface of the terrestrial hydrologic cycle, previously extracted water for human uses, or runoff generated from any place on the Earth’s surface. Such component tracking provides both a more fully transparent model in that users can identify the underlying mechanisms generating the simulated behavior, as well as perform model experiments in new ways.
Danielle S. Grogan et al.
Status: final response (author comments only)
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RC1: 'Comment on gmd-2022-59', Anonymous Referee #1, 30 Mar 2022
The model description paper of Grogan et al. describes an Open Source version of the model WBM. Overall, thy provide a well-structured summary of the model. I like to also highlight the availability of data and model source code. However, I also think the manuscript requires some clarifications to be a helpful addition to the scientific community.
Foremost, the abstract and introduction provide no indication of why the model is relevant and how its result already has or will contribute to our scientific knowledge. It is also unclear how this model differs from the vast collection of other global hydrological models. What are the features that make it unique? Why should I be interested as a potential user and scientist to have a closer look? What are the current challenges?Additional notes:
Previous GMD guidelines stated that the model version needs to be noted in the manuscript title. Please check if that is still the case.
11: what does long mean? Maybe instead, refer to the first published version in year X
12: So, the previous versions have not included it, and this is a new feature?
14: I do not think it is necessary to refer to the GitHub link in the abstract. Please instead describe what makes WBM unique and why it is useful. I am halfway into the abstract and still have no idea why I should care about the model
15: Remove unnecessary technical detail in the abstract.
16-17: Ok, so what have you learned? What is the model able to do? Why should I care as a scientist and possible user?
17 - 22: Ok, so this is really interesting, but the sentences are long. If this is a unique feature of this model, it should be stated. In what new ways can we perform experiments with that model that are not possible with other models? After reading only the abstract, it is still unclear why I should care about this model and how it has maybe already contributed to science and will continue to be of interest. What are the scientific questions that it is designed to answer or will enable us to answer in the future? How does it differ from other models? How well or bad does it perform overall / compared to other models? What is the spatial resolution?
These are all questions that can be touched upon in the abstract.Introduction: I think you provide an excellent summary of what has been developed. However, I wonder if that should be condensed to a table instead. Half of the test is just references. Also, it would be nice to focus more on why we build these global models and what kind of questions they are supposed to answer, and what they can't do. There are obvious limitations, and people have been criticizing them a lot (sometimes fairly, sometimes not); because of that I think it is essential to highlight the ongoing discussion of what they are and what scientific insights we gained. And specifically, what the remaining challenges are - possibly hinting on your model? How is it different from all the literature that you are outlining?
Fig.1: This is very helpful. Could you add the timescales on which these fluxes and storages are simulated?
Table 1: I think this can be moved to the supplement.
199: This documentation should be appended as supplemental material or uploaded somewhere to provide a doi. If the GitHub repository is lost, this link is not really helpful. This is also the case in various other places in the manuscript.
Fig3: The y-axis is different on the plots and thus confusing. Also, the quality does not seem to be high. Not much to see when zooming in.
Please also add a comparison to other global models. If it performs worse, state why the model's unique features are still useful.
Further, I was expecting to see something like Fig 6 and 5 here. Maybe move Fig. 3 to the supplement and refer to the result section.Fig.4: Please refer to Table 6.
Table6: Please add the model name. Is that the absolute difference to the simulation that you are showing? Or the absolute value? The description text is confusing on this matter.
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RC2: 'Comment on gmd-2022-59', Anonymous Referee #2, 31 Mar 2022
This manuscript presents the UNH Water Balance Model, a hydrology model that has been developed over several decades, but released publicly (open source code) for the first time.
The authors provide a literature review of the model history and evaluate the current model performance against river discharge observations and irrigation water supply requirements. The WBM performs better across North America and Europe in terms of discharge and irrigation water supply, but relatively poorly across Asia and portions of South America.
The manuscript then provides examples of regional simulations including the Indus River watershed as well as the Wyoming headwaters contributing to river flow to the Colorado, Colombia and Mississippi River. This provides an opportunity to demonstrate the novel water component tracking functionality that enables identification of source regions and source stocks for river discharge and irrigation water supply.
The tracking feature appears to be a significant advance in river flow diagnostics and is capable of determining source spatial regions, and source water components (precip, agriculture, groundwater). This should be a valuable tool for land management and government policy makers. Finally, the authors provide an overview of WBM run-time instructions describing the necessary input data and setup scripts to perform a simulation.
This reviewer was impressed with the breadth of the manuscript included 1) a literature performance review, 2) multi-domain simulations with emphasis on the new diagnostic tracking functionality and 3) an overview of a model setup.
This reviewer would have liked much more discussion devoted to WBM performance.The WBM had a strong high bias in simulating global irrigation water supply as compared to other studies (Table 6). This apparently was caused by a systematic underestimation of discharge for the China/Asia region, but very little discussion (only a mention regarding better parameters are needed) was devoted to this topic. Whereas the authors provided a comparison against similar hydrology models in terms of simulated irrigation supply, no comparison was provided for discharge rates against other models for better context and perhaps lead to a discussion of what model components or parameters are most in need of improvements. This reviewer would have liked more justification or explanation to describe the skill of WBM such that a new user could avoid certain regions or pay special attention to parameters which are poorly constrained. Also an inclusion/reference of a model tutorial would be helpful for new users to begin interacting with the WBM.
Line 66: Very nice explanation of the value of this source component tracking feature in this paragraph.Line 85: Global models come an out-of-the-box setup of preferred sub-model structures and parameterizations. There is a table devoted to the key default parameters (Table 2), but no discussion of the optimization process that is required for regional simulations, or representation of the range of parameters to make these regional simulations perform well. The authors do present some discussion and results based upon the contribution of uncertainty due to the climate forcing (Figure 3), but missed an opportunity to discuss the contribution of parameter uncertainty in the manuscript.
How modular is WBM in terms of testing particular hypotheses about hydrology and competing methods, etc. ? There is some brief description at the very end of turning flags on/off, but no specifics in how this influences representation of hydrology. Given the source tracking capability it would be interesting to test the impact of certain model assumption/hypotheses.Model Description:
Line 140: I am assuming the representation of snow is considered single-layer, and does not include multiple layers. Things like snow properties and albedo are not explicitly taken into account. Also insolation and aspect are not considered within the melting term? Care to comment how this might influence your snow source? Has this ever been validated against gridded snow data sets?
Line 200: “Actual evapotranspiration (AET) from naturally vegetated land areas is a function of the PET, soil moisture, and soil properties.”
So rooting depth is not taken into account? What function or purpose is setting the soil moisture pool depth to that of the rooting depth? I assume it’s a single layer soil subsurface then?Line 210: “While AET from other land cover types (e.g., forest or grassland) can be parameterized and simulated, no published study has yet used this option of WBM. Actual evapotranspiration from other consumptive water uses are described below in Section 2.2.5.”
Are the default parameters provided for forest/grassland types to calculate AET, or does the user have to provide them? If this option has never been used, how does the model treat forest/grassland if run globally – which includes forest and grassland cover?Line 275: The term “Shallow groundwater pool” is not used in Figure 1. I assume this is the same thing as “groundwater recharge pool”? If so, make sure the terminology is consistent.
Do the grid cells communicate for surface runoff and subsurface discharge or does this get routed directly to river transport model?The term “unlimited unsustainable groundwater source” seems confusing. Is there a better way to describe this fossil ground water?
Line 550-555: Here you mention spin up time in the context of water source tracking, but I feel this discussion could come much earlier when describing the model dynamics and features themselves.
Table 4: Please define ‘relict’ here.
Because the model is becoming open source, the presumption is to allow for a wider user community. Do you provide a tutorial to familiarize the user with WBM? The authors provide a four-step description towards the end of the manuscript, plus a reference to an instruction manual, but a tutorial would be a great advance.Model Validation:
Line 620: I recognize this section is devoted to a summary of WBM literature, but it is difficult to evaluate the skill of the model without the context of comparing against other similar hydrology models. There must be some model hydrology intercomparison studies to show here for global river discharge. Certainly Figure 3 might benefit for a comparison against other models.
Line 624: What sort of parameter calibration is performed here? Hand tuning, or more formal DA approaches? Are these parameters available for the user?
Section 3.2.1: Table 2 is good, but a physical definition for the parameters should be stated in the table and not just in text. Perhaps a summary table of parameter values for the literature review manuscripts performed at different regions/resolutions, in addition to the default values.
Line 690: “Above, we reviewed previously-published WBM validations. As none of the prior versions of WBM code have been released open source, it is important to validate the exact model structure in this first open-source release. “
Was there significant mechanistic changes to these pre-release versions? Was adding the tracking capability the only significant difference from this official release version? From Table 7 it seems like you add some new functionality from previous versions: “Added rainfed agriculture, other land cover types, inter-basin transfers, domestic and livestock water demand”, but you don’t mention that here, and it seems to the reader that the only change is making it open source, when there are some structural changes.
Table 6: Appreciated how the WBM irrigation withdrawal estimate was put in the context of other studies. Would it be possible to construct something similar for global discharge? Especially since the author attributes the high irrigation withdrawal estimate (China) to relatively high discharge rates in the Asia domain, it seems like it would be worthwhile to hone in on discharge biases, and diagnose where and what location these are occurring.
Line 800: “Global discharge is dominated by rain over most of the globe, with snowmelt an important contributor at the poles, and both glacier runoff and unsustainable groundwater important regionally.”
“Snowmelt is an important contributor at the poles”: That seems like an oversimplification. Seems that Figure 8 shows there is significant snowmelt contributions well down into the northern mid-latitudes especially for mountainous terrain such as the Rocky Mountains and the Himalayas where a larger population rely on snow runoff for irrigation etc. This should be mentioned.Figure 8: Glacier run-off seems to be unrealistic in the SouthWest and MidWest US where none should be occurring. Glaciers are apparently determined solely by snow input and melting algorithm and not prescribed like land cover types?
Figure 11: Perhaps outline the watershed domain of the Indus river in this figure within the larger figure 10 for better reference and perspective.Figure 11b: There are no units in this figure. Why is there such a large discontinuity between months 12 and month 1? Why does glacier runoff have such a strong contribution upstream at point A, yet such a small contribution downstream at point B?
4.2 Return flow tracking
Line 867: I feel like this “relict” and “pristine” distinction should be made earlier, because it is used in an earlier table.
Return water diagnostics and source water diagnostics and tracking seem to be some of the most useful components of the system. Would it be easy to port these ‘diagnostics’ modules to other hydrology models or is it baked into the system?
Figure 12 and 13: Care to comment on why the irrigation return flow waters are so high in the Northern India region? It might help the reader contextualize this diagnostic, and make for interesting discussion of what makes that region so unique.
Figure 14: These plots are interesting and potentially very valuable. Couple questions, in Figure 14b could the color scale be changed to emphasize the 0 to 0.2 discharge fraction? A large part of the watershed domain seems to be the same color of green that is hard to distinguish at all.Could you not color Wyoming such that the river network can be seen easily? It doesn’t seem to be a need to color Wyoming dark blue since it is the headwater region. Also in Figure 14a is this distribution pattern mostly driven by snowmelt? It doesn’t look like the distribution is picking up the summer monsoon season where a larger fraction of the water should derive from Arizona and New Mexico. I suppose this depends if the climate forcing captures the SouthWest monsoon.
Model Code development section: Although I do find this section interesting it may be better suited for the appendix, such that the reader can immediately go from the results to the discussion. You have provided steps, and there is access to an instruction manual, but do you also provide a simple user tutorial for a cut down domain and provide the input files so the user can familiarize themselves with the steps?
Discussion:The tracking capabilities of this model which can attribute discharge source regions, or impact from agriculture on discharge are a great feature and worthy of discussion. The authors refer to the modular nature of the model in order to toggle on/off different features, but they don’t provide a test case of this, where for a single experiment, different model structures/assumptions/parameters are switched up to identify the model sensitivity. Just a suggestion.
I was certainly expecting at least more discussion concerning model performance related to river discharge and irrigation water withdrawal as covered in the first part of the manuscript. It was a bit concerning that the WBM was a bit of an outlier when estimating global irrigation water withdrawal, and this was partially attributed by the authors to low discharge rates across China and Asia. Very little to no discussion or explanation was provided for this. The discharge rates seemed to perform relatively well in other regions includes North America, but it was difficult to contextualize given no comparison in performance was provided from other hydrology models.
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RC3: 'Comment on gmd-2022-59', Anonymous Referee #3, 13 Apr 2022
General comments
The paper describes the WBM global hydrological model in detail. WBM is one of the earliest global hydrological models which contributed to the establishing the field of global hydrology. This paper provides the full description of the model together with the development history which will be quite useful for the modeling community. In particular, the water source tracking function is novel and very interesting. The paper is well prepared and mostly very readable. I have only minor technical comments.
Specific comments
Line 189 “Soil moisture balance calculations for natural landcovers are fully described in (Wisser et al., 2010a) and crop landcovers in (Grogan, 2016).”: Better to show the essence here because soil moisture balance calculation is the most fundamental function of any hydrological models.
Line 270 “PyGEM’s standard output format is not gridded; rather, post-processed PyGEM output is required as input for WBM (Prusevich, et al., 2021).”: How frequently is the glacier fraction updated (e.g. daily, monthly, annually)?
Line 358 “Rather, they collect rainwater and surface runoff, storing it on the land surface and preventing it from reaching the rivers system”: How are these processes formulated? What are the key inputs and parameters?
Line 368 “WBM’s inter-basin transfer methods were first developed and described in (Zaveri et al., 2016) and described again in (Liu et al., 2017).”: Can this inter-basin transfer scheme be applied to global simulations? If so, how the parameters were set (i.e. is such information available)?
Line 400 “Stream water available for extraction is estimated as 80% of water retained in river and reservoir storage following routing during the previous time-step ðð−1, plus the volume, Vstream, represented by flow through the reach during the previous time-step:” A bit hard to read and associate with Equation 26. What is Vstream? Is this representing the available surface water?
Line 621 “The global simulations described above used a grid cell resolution of 0.5 degrees.”: This should be mentioned in the previous paragraph.
Line 629 “These continental-scale simulations of India used the same 0.5 degree spatial resolution as the global simulations.”: What were the input meteorological data used in these simulations? The performance of river discharge simulation is largely dependent on the quality of input meteorological data (e.g. Hanasaki et al. 2022, HESS).
Line 721 “We also calculate the Index of Agreement, d, (Willmott, 1981)”: Why was this indicator chosen? I recall that most of the earlier works used NSE.
Line 740 “Despite the global average good agreement, there is significant spatial variability, with lower MBE values across much of South America and East Asia (Figs. 5c and 6c).”: When one looks at the absolute MBE, the performance of river discharge simulations in arid or semi-arid regions always appears to be "good" because the runoff is very small. This needs to be pointed out in the text.
Line 750 Figure 6: What is the difference between Figure 5 (c) and 6 (c)? Only the unit is different?
References
Hanasaki, N., Matsuda, H., Fujiwara, M., Hirabayashi, Y., Seto, S., Kanae, S., and Oki, T.: Toward hyper-resolution global hydrological models including human activities: application to Kyushu Island, Japan, Hydrol. Earth Syst. Sci, https://doi.org/10.5194/hess-2021-484, accepted, 2022.
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RC4: 'Comment on gmd-2022-59', Anonymous Referee #4, 19 Apr 2022
General comments
The paper „WBA: A scalable gridded global hydrologic model with water tracking functionality“, by Grogan et al. provides a description of the first open source version of the University of New Hampshire Water Balance Model. The authors chose an approach that combines parts of a “classical” model description – i.e. description of the functionalities and fundamental equations, validation and a selection of case studies – with a literature review of the history of the model, previous studies with WBA and validation of previous model versions. Overall, this structure works really well and the paper is well written, thus, I only have a few minor suggestions.
Minor comments
1) With respect to the model description, the authors did a very good job at providing a general overview over the basic equations and dependencies in the model without overloading the manuscript with technical details (which is perfectly reasonable given that most WBA components have been used in previous studies and have been well documented). However, it would be extremely helpful if the structure of the section 2.2 could be related to what is shown in figure 1, i.e. that all elements that are shown in the figure are discussed in the model description, preferably even in a way that each element in the figure has a subheading in the text.
2) I find the use of the term “unsustainable ground water” somewhat problematic, since it is not the groundwater itself that is unsustainable but its use e.g. for irrigation. A term that clearly states either which real world pool is represented – e.g. fossil water – or what it constitutes in the model – namely an unlimited water supply to balance demand-supply mismatches – would be more appropriate. Maybe the authors could also add some discussion to section 2.2.2, detailing how the use of this pool affects simulations (especially projections) in regions where fossil ground water is being depleted.
3) I think it is a good idea to discuss existing model validation in this paper, rather than repeating the respective simulations with the present model version. However, it would be helpful if the authors could detail if and how the present model version differs to the model versions used in the previous studies and how these differences affect the results. Furthermore, with respect to the FrAMES model (component) I find the model validation a bit out of place here, as it is not merely a different version of WBA but a completely different model. I would expect the performance of the implemented functionalities to depend on many other aspects of the model and the forcing data, hence different simulated nitrogen concentrations with WBA. I think it would be sufficient to state, in the model description sec. 2.2.6, that WBA now includes these functionalities based on the parametrizations of the FrAMES model and reference the studies in which FrAMES was validated. However, I think it would be even better if the authors could actually perform the analysis and validate N and temperature in WBA simulations.
Specific comments
Line 22: “ ... as well as perform model experiments in new ways”. Please, clarify which are these new ways.
Lines 55 ff: Evapotranspiration will eventually lead to precipitation and a large fraction of the respective water is even recycled locally. Thus, the statement that only 50% of water is returned to “the system” is somewhat misleading. In contrast, when talking about specific pools in the system a 50% return rate is also often questionable, e.g. in case of fossil water, at least on a centennial timescale.
Fig. 1: Would it be possible to make the elements of the figure consistent with subheadings in section 2.2.? For example infiltration is not specifically discussed in the text.
Line 166: Eow is not defined.
Line 170: “Storm runoff” is this the same as “stormwater runoff”?
Line 179: What does WBA do in these grid cells e.g. in case of endorheic basins?
Line 183 f: Is this the only limit on infiltration? Is the state of the soil not taken into account?
Line 190: It may be helpful to mention that WBA does not have soil layers and does not explicitly represent the vertical flux through the soil or a soil moisture profile.
Line 257: How do you justify this default value of 1000 mm, i.e. that the model, in the default mode, has no real limit to the surface storage?
Line 280: I am a bit confused by the unit l/d is that per m^2?
Line 490 ff & 503 ff: Is there a lag connected to the return flows?
Line 564: I am not familiar with the term “relic water”, so I am not sure whether some definition is necessary.
Fig. 2: What is the meaning of the colors? Also why is the down-stream cycle different (no subheadings in “sources” and “water”)?
Section 3.1: Could you maybe add a table for a quick overview?
Line 611: What about the UDEL climate? In Fig. 3 The R2 looked very promising?
Fig. 4: Maybe use the same axis for subfigure b and c?
Line 671: While I think it’s a good way to use existing validation, I am not sure about the FrAMES model, as the respective formulations lead to a very different outcome in the WBA framework?
Line 725: Could you also include R2 to make it easier to compare the present simulations to those in section 3.1 ?
Line 725: I would be very curious if you could also include an evaluation of the simulated evapotranspiration … maybe against GLEAM data?
Fig. 5 & 6: Why is there no Index for the Nile/Indus/Ganges in subfigure c ? Also, would a relative measure make more sense than MBE.
Fig. 8 & 9: Could you do such a figure also for evapotranspiration?
Fig. 10: I find the purple and blue colors are very similar, and I am not sure that its only an issue related to my printer.
Line 906 ff: “… published in (Vörösmarty et al., 1989)”. I would not use the brackets here.
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RC5: 'Comment on gmd-2022-59', Anonymous Referee #5, 21 Apr 2022
Overall comments:The authors present and describe a new open-source version of the global hydrologic model WBM, emphasizing new capabilities for tracking water sources. The paper is well written, and the overview is fairly comprehensive, including theory, examples, plentiful references to earlier literature, and a discussion of how this open-source version relates to other versions of WBM that have been used over the 3 decades since the first version was created. Not only is the model now open source, but the authors have provided a Singularity container to simplify access/usage. Overall, this is a nice contribution, and I recommend publication after minor revisions.
Below are listed specific comments keyed to particular line numbers, sections, or equations:Introduction: I appreciate the overview of applications of GHMs, which seems like a useful entry point for those new to the topic.
Sec 1.1: the need for water tracking is well motivated here.
69-70 typo?
86-88 at some point around this section it would be useful to describe how WBM handles gridding. Here an example is given of a fixed-width (120 m) grid, and later examples are noted of lat-lon based grids. Does the user have a choice between these? Does the model account for the variable size of fixed-longitude grid boxes? What happens at the poles? Or does the global configuration exclude very high latitude regions like Antarctica?
124 and ff: thank you for listing units of each variable.
Eq 3 & 4, should this be P^e? (also, in general, instead of introducing equations with 'defined according to', it can be helpful to say something more descriptive like 'so-and-so depends on temperature T and precipitation rate P according to')
Eq 4 and other math: if you want text-like typesetting, e.g., the word "if" in eq 4 or a sub/super-script like "max", use \text{if}, W_i^\text{max}, etc. (requires \usepackage{amsmath})
142 grammar around lapse rates
158 is Pt a user-defined param? A fixed fraction of P? Calculated in some other way?
Eq 7 and others: consider the more traditional use of a dot (\cdot) or no symbol at all to represent multiplication, as opposed to an asterisk (which I think traditionally means convolution, even though most modern programming languages use it as a multiplication operator)
212 no cap
eq 13 ff: this is somewhat confusing because the phrase 'immediately moved' suggests a discontinuity but the differential equation suggests differentiability / continuity. Please clarify (maybe via a delta operator in front of R_EXC, which is 1 if volume of retention pool exceeds the threshold and 0 otherwise?)
250ff isn't there a unit mis-match between W and R in eqs 14-18? And between R and T in 18?
286 unclear what 'stock' means here (it seems to be a standard term with WBM, so please define it before using)
Sec 2.2.3: I appreciate the references to papers that describe the routing methods, but it would still be helpful to have a bit more information on linear reservoir routing. For example, does it mean that each grid cell's river discharge output to its neighbor is calculated as a linear reservoir, that is, as a function of river water within the cell? What, briefly, is the basis for assigning a reservoir coefficient? Are these constant or do they depend, for instance, on channel geometry?
418 does 'scaler' mean 'scaling factor' or 'scalar' or something else?
429-437 Can you elaborate a bit on this treatment and why it is needed?
473 capitalization consistency
Sec 2.2.7 source tracking: this section is a bit confusing, partly (I think) because of the wide variety of sources that could be tracked. If I understand right, a user would not normally track ALL of these sources in any given model run, but rather would pick a type of source to track - is that right? Actually, reading forward in section 4, we learn that there are 3 options. It would be helpful to list these options up here in section 2. In addition, a couple of examples would potentially help a lot. They need not be very elaborate, but could be as simple as something like: 'a user interested in X might choose to track sources Y and Z'.
545 again, are these 3 mutually exclusive (i.e., one chooses from among them), or are all 3 tracked simultaneously? (later text suggests the former, but at this point in the text it is not clear)
557 daily time step: helpful to mention this much earlier
Sec 3: helpful to define what you mean by validation (I'm not personally a stickler for semantics, but some would consider the term problematic, and better described by confirmation, testing, or evaluation).
Sec 3.1: are the summarized validation studies performed in conjunction with some kind of calibration / parameter optimization? Or is calibration only used in regional applications? You kind of answer this question around 635-640 but it would be helpful to clarify near the start of this section.
Validation generally: it would be interesting to summarize some of the lessons from testing and validation, it terms of what might be behind systematic under- or over-prediction of discharge. For example, have past validation exercises revealed certain gaps in knowledge, and/or mathematical approximations that would need to be refined in order to improve model performance? This might fit well under Results or Discussion.
Sec 3.2: thanks for differentiating between validation of different versions, and including this section devoted to the open-source version. It's a nice reminder (and demonstration) that testing of models should ideally include the specific code implementation alongside the theory and numerical algorithms.
Eq 31: the first time I read this, my mind immediately went to cancellation of errors -- but then realized that this is actually desirable for a bias metric. You might consider reversing the order of 32 and 31, and introducing the MBE with a phrase like 'in order to measure systematic bias' or something to that effect, so readers don't get hung up on it.
711 observations per year, or total?
753 tense
Sec 5: I appreciate the code history and summary of different versions
943 uniformly spaced... in geographic coords? (again, helpful to explain grid set up early in the paper)
1039 typo
Danielle S. Grogan et al.
Data sets
Water Balance Model (WBM) Open Source Release Version 1.0.0 Ancillary Data Grogan, D. S., Zuidema, S., Prusevich, A., Wollheim, W. M., Glidden, S., and Lammers, R. B. https://dx.doi.org/10.34051/d/2022.2
Model code and software
WBM v1.0.0 Grogan, D. S., Zuidema, S., Prusevich, A., Wollheim, W. M., Glidden, S., and Lammers, R. B. https://zenodo.org/record/6263097#.Yhhvk5PMKRs
Danielle S. Grogan et al.
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