the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 18 Dec 2024
Modelling the effects of climate and landcover change on the hydrologic regime of a snowmelt-dominated montane catchment
Abstract. Climate change poses risks to society through the potential to alter peak flows, low flows, and annual runoff yield. Wildfires are projected to increase due to climate change; however, little is known about their combined effects on hydrology. This study models the combined impacts of climate and landcover changes on the hydrologic regime of a snowmelt-dominated montane catchment, to identify management strategies that mitigate negative impacts. The combination of climate change and stand replacing landcover disturbance in the middle and high elevations is predicted to advance the timing of the peak flow two to nine times (depending on emission pathway) more than the advance generated by disturbance alone. The modelling predicts that the combined impacts of climate change and landcover disturbance on peak flow magnitude are generally offsetting for events with return periods less than 5–25 years, but additive for more extreme events. There is a dependency of extreme peak flows on the distribution of landcover. The modelling predicts an increasing importance of rainfall in controlling peak flow response under a changing climate, at the expense of snowmelt influence. Extreme summer low flows are predicted to become commonplace in the future, with most of the change in frequency occurring by the 2050s. Low annual yield is predicted to become more prevalent by the 2050s, but then fully recover or become less prevalent (compared to the current climate) by the 2080s, because of increased precipitation in the fall-spring period. The modelling suggests that landcover disturbance can have a mitigative influence on low water supply. The mitigative influence is predicted to be sustained under a changing climate for annual water yield, but not for summer low flow. The study results demonstrate the importance of examining complexity in three dimensions with respect to modelling changes to the hydrological regime: climate change, landcover change, and numerous hydrological indicators. Moreover, for managing watershed risk, the results indicate there is a need to carefully evaluate the interplay among environmental variables, the landscape, and the values at risk. Strategies to reduce one risk may increase others, or effective strategies may become less worthwhile in the future.
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RC1: 'Review of hess-2024-361', Anonymous Referee #1, 24 Jan 2025
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This paper combines a large amount of data and different climate and land cover scenarios in a modelling study to determine the combined effects of land cover change and climate change on the snowpack and streamflow regime for a headwater catchment in British Columbia, Canada. This is a huge undertaking and I appreciate that the effects are analysed for many different aspects of the snowpack and hydrograph. The paper clearly shows the interaction between the effects of land cover change and climate change. For some aspects of the hydrograph or snowpack, the land cover change enhances the effects caused by climate change and for others, it mitigates it. The results furthermore highlight the importance of the location of the disturbance in the catchment (i.e., whether the vegetation is replaced in the upper or lower part of the catchment) and the time since the disturbance. These are important results and highlight the need to consider the effects of land cover and climate change jointly and to not study the effects of land cover change for only one climatic period.
Unfortunately, some of the model decisions are not so clearly described and it is not very clear how the model was calibrated. There is also no mention of the uncertainties in the results due to parameter uncertainty. Considering the potentially very large number of parameters that are optimized, it is possible that a different parameter set would lead to considerably different results. The lack of uncertainty analyses is acknowledged in the final part of the discussion, but I would argue that at least some model uncertainties need to be presented. As a result of the lack of a clear description of the calibration procedure and the lack of an uncertainty analysis, it is not clear how the presented results are influenced by the model decisions or model parameter sets (equifinality).
The graphs used to present the results are clear and very useful. But it would be good if they had error bars to represent the range of results caused by equally good fitting model parameter sets. I like it that the time series of the simulated and observed runoff are given for the individual years in the Supplementary material. The paper is long but overall, well written.
Specific comments:
- L14 and 862: Quantify this in a different way, e.g., in days or weeks. 2-9 times more is important if we talk about an advance of a week or several weeks due to disturbance but not if the advance is only 1 day.
- L26: Maybe use a different word than values (hydrograph characteristics, hydrological signatures?)
- L76: Considering all the uncertainties in these assessments, the decimals are probably not warranted here.
- L92: Give some info on the model here already. It would be good to know for the reader early on if you are using a physically based, spatially distributed model or some other model, if it was calibrated or not, etc.
- L126-129: It is nice that you describe the vegetation here and give the codes that you will use for the vegetation codes throughout the text but it is hard for the reader to remember these codes, especially since there are also codes for the different scenarios. In other words, it would be a lot easier for the reader to understand the parts about the vegetation if you would just write out the names instead of using the codes.
- L139: In addition to the mean annual runoff, also mention the mean annual precipitation, either averaged over the catchment or for at least one station. This is important information about the study site.
- Section 2.2.1: It would be good to already mention how many HRUs there are in this section (now it is only mentioned on L243) and how many parameters there are per HRU. Now this section is short and a lack of knowledge on the model and its parameters early on in the paper, hampers the understanding of the other parts in section 2.2.
- L195: How well is well? Is there a reference here or a result that you can add to the supp materials?
- L267: How many parameters are there per HRU and in total? and how many of these were calibrated? Even after reading the paper, this is unclear to me. Please add this information clearly in the methods section. Ideally already in section 2.2.1.
- L268: What weighting did you use for the calibration? Equal for each of these objective functions?
- L281, 283 and ff: What exactly do you mean by constrained (or in L301 and 306 by informed)? Did you pick a parameter value a priori and not calibrate it or did you select a parameter range and calibrate within this range?
- L313: This wording is not clear. Did you use it to guess a specific value and then use this in the model? Did you calibrate within a certain range? A bit more information, or clearer wording would be useful.
- L321: This is not clear - how did you get values for each specific channel? How different were these values?
- L331: How many parameters were optimized and how many were fixed based on field knowledge? Also did you use the same parameters for all the HRUs with the same vegetation or soil? Would it be possible to add a table with all parameter values and the range used for the optimization somewhere?
- L333, 389: How did you weigh these different objective functions in the calibration? All equal weight? Or did you optimize each function individually first? From L323-326, it appears that you did it sequentially? Or did you just use different time periods for each of these objective functions and calibrate everything at the same time using some weighted function? The current description doesn’t make the calibration process very clear to me. Also, what is the reason for not using the NSE for the entire study period as well?
- L461: Already mention here if this is largely due to a change in precipitation or due to a change in evapotranspiration.
- Figure 9: The shape of the curve changes as well. What is causing this? This requires some discussion.
- Section 5.2.4: Make it clearer that this is the annual *average* discharge
- L598: A lot of the quickflow probably consists of subsurface stormflow or even groundwater flow. The majority of quickflow is unlikely to be overland flow (surface runoff) for a forested catchment.
- L780: Groundwater would be a more likely source for the streamflow in the dry period than soil water (retention).
Minor comments
- L11: Mention the name of the model or the type of model in the abstract.
- L82-89: Move to the study site description.
- L121: Explain that BEC is the biogeoclimatic ecosystem classification.
- L191: Lowest temperatures instead of coolest temperatures.
- Figure 5: Maybe still add South and North to the axis labels for subpanel b?
- L431: These differences are very small. Highlight that first before giving the values!
- L700: What do you mean by snowpack loads?
- L720-721: Explain better how this sentence fits here / what you mean by this? What is the link to the previous or next sentence?
- L797 values at risk: Do you mean the streamflow signatures / hydrograph characteristics? This could be worded more clearly.
Citation: https://doi.org/10.5194/hess-2024-361-RC1 -
RC2: 'Comment on hess-2024-361', Anonymous Referee #2, 06 Feb 2025
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Dear authors of the manuscript, thank you very much for revising the manuscript. The current version has undergone substantial enhancement in terms of content and presentation.
The manuscript is generally well-written, with figures and tables that are well-placed and clearly illustrate the results. The manuscript provides insights on annual and seasonal hydrological changes, as well as on the development of extreme summer low flows and peak flows under a range of climate scenarios and landcover conditions. The conclusions drawn are supported by the findings of the model. The in-depth analysis of potential future changes is informed by the CSIRO85 model. However, I still have some minor comments that should be addressed:
L 12-14: what does “two to nine times more” mean in absolute terms? Absolute figures would provide more clarity here.
L 26-27: are the “values at risk” related to the society as mentioned in the first sentence of the abstract? This needs clarification, also in the conclusions section.
L 267-268: which parameters have “substantial uncertainty and/or sensitivity”? Please name them. Although these parameters have been calibrated simultaneously, the issue of equifinality should be discussed (at least in section 6.4 on uncertainties).
L 303: I am still struggling with the meaning of these BEC variants. It would be nice if the BEC variants were explained in a table.
Table 5: would be helpful to split the numbers of net P into P and ET. The precipitation data given in other tables to not coincide with the aggregation used in Tab. 5
Citation: https://doi.org/10.5194/hess-2024-361-RC2
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