the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 20 Jan 2025
Multi-scale water balance analysis of a thawing boreal peatland complex near the southern permafrost limit in western Canada
Abstract. Permafrost thaw profoundly changes landscapes in the Arctic-boreal region, affecting ecosystem composition, structure, function and services and their hydrological controls. The water balance provides insights into water movement and distribution within a specific area and thus helps understand how different components of the hydrological cycle interact with each other. However, the water balance of small- (<101 km²) and meso-scale basins (101–103 km²) in thawing landscapes remains poorly understood. Here, we conducted an observational study in three small-scale basins (0.1–0.3 km²) of a thawing boreal peatland complex. The three small-scale basins were situated in the Scotty Creek basin headwater portion, a meso-scale low-relief basin (drainage area estimates from 130 to 202 km²) near the southern permafrost limit in the Taiga Plains ecozone in western Canada. By measuring water losses (discharge, evapotranspiration [ET]), inputs (rainfall [R], snow water equivalent [SWE]) and storage change (ΔS), and calculating runoff (Q), we (1) aimed at quantifying growing season (May–September, 2014–2016) headwater small-scale basins water balances, i.e., sub-basins. After (2) comparing monthly sub-basin- and corresponding basin water losses through ET and Q, we aimed at (3) assessing the long-term (1996–2022) annual basin water balance using publicly available observations of discharge (and thus calculated Q), R and SWE in combination with simulated ET. (1) Growing season water balance residuals (RES) for the sub-basins ranged from -81 to +122 mm. The monthly growing season water balance for the sub-basin for which all the water balance components throughout the three-year study period were recorded exhibited large positive RES for May (+117 to +176 mm) since it included late-winter SWE routinely estimated in late March right before snowmelt. In contrast, lower monthly RES were obtained from June to September (-41 to 0 mm). For two sub-basins, we provide two different drainage area estimates highlighting the challenge of automated terrain analysis using digital elevation models in low-relief landscapes. Drainage areas were similar for one sub-basin but exhibited a fivefold difference for the other. This discrepancy was attributed to the high degree of landscape heterogeneity and resulting hydrological connectivity with implications for Q calculations and RES. (2) The spring freshet contributed 41 to 100 % (sub-basins) and 50 to 79 % (basin) of the April–September Q. Spring freshet peaks were comparable, except for the driest year (2014), when basin Q was more than ten times lower than in the sub-basins. At both scales ET was the dominating water loss, more than twice Q. (3) Over the long-term (1996–2022), the increase of basin runoff ratio (ratio of runoff to precipitation) from 1996 to 2012 (0.1 to 0.5) has been attributed to the increasing connectivity of wetlands to the drainage network caused by permafrost thaw. However, the smaller average and more variable runoff ratio from 2013 to 2022 may be due to wetland drying and/or changes in precipitation patterns. Long-term hydrological monitoring is crucial to identify and understand potential threshold effects (e.g., hydrological connectivity) and ecohydrological feedbacks affecting local (e.g., subsistence activities), regional (e.g., weather) and global ecosystem services (e.g., carbon storage) provided by thawing boreal peatland complexes.
- Preprint
(2178 KB) - Metadata XML
-
Supplement
(1620 KB) - BibTeX
- EndNote
Status: final response (author comments only)
-
RC1: 'Comment on hess-2024-367', Anonymous Referee #1, 16 Feb 2025
The paper by Lhosmot and co-authors presents considerable empirical data from the well studied Scotty Creek watershed where research has been ongoing for decades. In this work, the authors collate water balance data across temporal and spatial scales to answer questions regarding hydrological partitioning and dominant flux, and also touch on issues related to basin delineation, data products versus observations and other issues.
First, I want to acknowledge that there is a lot of field data that has gone into this work and it is important to acknowledge the true challenges that this entails. The method section provides sufficient detail for the readers to evaluate where this data came from, how it was processed, and points to companion papers for further information. In short, I see no substantive issues with the data presented or the approaches used to assemble it.
The paper is quite long because of all the data presented. Data is presented in both tabular and figure format directly, and I’d suggest the author to select one for the main part of the manuscript and move the other to the SI. Perhaps the figures as opposed to the tables. While water balances are interesting for those looking at long-term studies impacts of hydrological change, the most important contributions come from the isights of the authors. My question to the authors is: what new insights are there in this paper? For me, the discussion section does not advance much on the results, restating general patterns without a critical assessment of what insights can be gained from this data set. The general fluxes patterns are not new, but is there something that can be gained by linking this small scale with larger scale data? What here advances our understanding of process from this well studied system?
In addition, much is made of the changes in runoff ratio at the basin scale, but again, this is speculative at the moment talking about changes in drainage efficiency, changing plant communities, etc. Can the authors convince us that this is the case. The runoff ratios are presented on an annual basis, so I’m unsure if that plant community and peat drying hypothesis holds. Is the change in the ratio largely due to differences in the freshet SWE to Q in May? Or is it the rest of the year? These are important issues considering that these changes in runoff ratios are more regional. These ecosystems are changing remarkably fast, but how can something as complex as hydrological response (and runoff which integrates a lot of processes) be linked to that. I would have liked some additional analysis here, perhaps looking at previous season wetness or fall wetness which may influence the following spring runoff. There is talk of regional teleconnections that at this long-term scale could be explored even simply.
Section 4.5 is perhaps not needed. Much of this has been touched on in the introduction to the paper so the authors may consider trimming or deleting. I’m not sure how much value it has.
Finally, there is very limited discussion of error or uncertainty here. I am not advocating for a full uncertainty or error analysis, but the authors could be a bit more forthcoming about this, particularly given the levels of interpolation and reliance on point measurements. Again, I understand the authors know the data well, but I’m somewhat surprised that there is little discussion on this considering some things like SWE come from a site far from the basins. I’m sure there has been some assessment done as to how effective this is other than citing another paper.
Other comments
+Could you not have used a snowmelt model? You use a complex model for ET at the basin scale so I’m unsure why you can’t apply a simple melt model to appropriately partition SWE at least at the monthly level.
+Line 503-504. This value for black spruce transpiration seems unusually low and does not agree with more modern and methodologically detailed work of Perron et al. (2023) from Scotty Creek.
+Do you examine any patterns int he timing of the hydrograph at the basin scale? You suggest that snowmelt has advanced 25 days since an earlier period? Perhaps no but if you discuss it I’m unsure why you didn’t evaluate it.
+Figure 2 - it is a bit hard to see some of the runoff values or distinguish them, particularly in 2022. Some of this is due to the distracting nature that the uncertainty in runoff area for EAST - perhaps think of a way to make this more clear? Two lines? A dashed line? I’ll leave it up to the authors but the shaded yellow is a bit distracting.
+ Why was the BESS data not corrected to the observations? Claiming that landcover differences are the reason that it underestimates ET is simply guessing and can easily be tested. My guess is that like many land models it is just underestimating ET.
+Check colour scheme on Figure 6 (Rain vs SWE and 2022 which doesn’t match the others)
Citation: https://doi.org/10.5194/hess-2024-367-RC1 -
RC2: 'Comment on hess-2024-367', Anonymous Referee #2, 16 Mar 2025
Lhosmot et al., present water balance studies for a well-instrumented and studied permafrost-affected boreal peatland complex. They quantify the impact of uncertainty in catchment delineation on water budgets, and compare water budgets carried out at different scales and with locally-observed and publicly available observational and simulated data. The find, among other things, that evapotranspiration is the dominant outgoing water flux but that this variable is considerably underestimated in publicly available simulated data. The results also highlight the difficulty of obtaining exact estimates of water fluxes such as discharge in a low relief landscape which is hydrologically dominated by spring freshet, as illustrated by high water balance residuals during this period.
The study provides new and valuable insights on the hydrologic behaviour of rapidly changing permafrost peatland complexes, as well as on the limitations of what information can be retrieved from detailed field-observations of water balance components as well as publicly available monitoring data. I find that the scientific rigour is high, based on the choice and descriptions of methods and the tight link to previous relevant studies from the same, and other similar areas. I have a few minor comments that I recommend that the authors address before publication of this nice manuscript.
L190: It is unclear to me if this instrument failure regards just one or both of the eddy covariance stations. Recommend clarification.
Section 2.4: I read it this section several times to understand what was done here, so there might be a good idea to see if it is possible to make this easier to read (although, I might just have been tired!). On L246, it is stated that 15 rating curves were obtained, one for each flume 2014-2016. There were five flumes, so I suppose that you mean one rating curve per flume and year 2014-2016?
I’m also curious about the gap-filling, especially since the West sub-basin series had 75% of data gap-filled by method 1 plus 14% gap-filled by method 2 (if I understand the text correctly). This adds up to almost 90% gap-filled data for this sub-basin, yet this is the sub-basin that you choose to show monthly water balance for in section 3.3. A motivation for your trust in this gap-filled data is warranted, as is a motivation for choosing to focus on this particular sub-basin in section 3.3, given this gap-filled data. Can you show that the rating curves from wetland WTP generate data that is well correlated with that from original rating curves?
L269: I’m curious why the average 2002-2022 ET was used to calculate the 1996-2001 water balance? If ET data for 1996-2001 was not available, how much can you still say about the basin water balance for those years, considering that ET is the dominant flux in the basin? This is relevant for results presented on L477, if change in storage at the basin level is calculated as the residual of water balance fluxes.
Table 2: The signs for ET and Q are inconsistent for East sub-basin, relative to other sub-basins.
L508: typo, at end of line “the could”?
L543: Suggestion, if you find relevant in context of your results. Another potential mechanism was presented by (Jutebring Sterte et al., 2018, 2021), for a boreal catchment in Sweden. They showed that seasonal freezing of the wetland resulted in high wetland runoff during freshet, while soil frost in the (less saturated) forest soils had less impact on drainage dynamics.
Jutebring Sterte, E., Johansson, E., Sjöberg, Y., Huseby Karlsen, R., & Laudon, H. (2018). Groundwater-surface water interactions across scales in a boreal landscape investigated using a numerical modelling approach. Journal of Hydrology, 560. https://doi.org/10.1016/j.jhydrol.2018.03.011
Jutebring Sterte, E., Lidman, F., Lindborg, E., Sjöberg, Y., & Laudon, H. (2021). How catchment characteristics influence hydrological pathways and travel times in a boreal landscape. Hydrology and Earth System Sciences, 25(4), 2133–2158. https://doi.org/10.5194/hess-25-2133-2021
Citation: https://doi.org/10.5194/hess-2024-367-RC2
Viewed
| HTML | XML | Total | Supplement | BibTeX | EndNote | |
|---|---|---|---|---|---|---|
| 179 | 62 | 8 | 249 | 24 | 5 | 7 |
- HTML: 179
- PDF: 62
- XML: 8
- Total: 249
- Supplement: 24
- BibTeX: 5
- EndNote: 7
Viewed (geographical distribution)
| Country | # | Views | % |
|---|
| Total: | 0 |
| HTML: | 0 |
| PDF: | 0 |
| XML: | 0 |
- 1