| 07 Nov 2025
Uncovering the melt: UAS and in-situ sensor synergies reveal DOC pathways in a northern peatland
Abstract. Spring snowmelt is a critical period for dissolved organic carbon (DOC) export from northern boreal peatlands, yet the spatiotemporal dynamics of this process remain poorly understood. To reveal the spatial patterns, we used a novel combination of high-resolution Unmanned Aircraft System (UAS) snow depth mapping, topographic wetness index, and high-frequency stream monitoring. Our results show that substantial DOC leaching is triggered after widespread snow cover depletion, likely due to thawing of surficial peat layers. High-resolution UAS snow surveys captured the progression of snowmelt from drier, south-facing slopes and forested areas toward wetter fen areas, with the expansion of snow-free areas in high-wetness zones initiating hydrological connectivity and rapid DOC flushing. Event-based hysteresis and flushing analyses enabled by high-frequency stream monitoring revealed transitions from deeper to more surficial flow paths towards the final peak melt. The integration of high-resolution spatial and temporal datasets enabled the detailed identification of DOC transport mechanisms during the snowmelt period. These findings underscore the sensitivity of peatland carbon dynamics to late winter processes and snow conditions, highlighting their potential vulnerability to future shifts in climate.
General comments
This is an interesting setup touching a weak spot in hydrology and solute mobilization: While connectivity is used to explain solute export dynamics, it is hard to actually map and measure. This study can go a step in this direction by a drone-based assessment of snow cover changes during a major snowmelt event combined with concentration dynamics in the receiving stream. This topic is of great interest to readers of HESS.
While the data and effort are impressive, I am not totally convinced about the way results are described and interpreted. From my point of view the result section can be more concise and the discussion section much more integrative. I see a tendency to overinterpret patterns. My suggestion is a careful revision following the points raised below. I moreover encourage the authors to look for a measure of connectivity in the snow cover data that can be used as an explanatory variable in the event C-Q analysis. Just fraction of area covered by snow or snow depths is not telling a story of connectivity of source zones to the stream. However, measures of spatial connectivity of snow-free area changing over time may provide that.
Specific comments
Title
For me UAS is not self-explaining and I would even avoid DOC as an abbreviation in the title.
Abstract
L9: I miss a reference to the location and size of the catchment/area to help the reader understanding what dimension you are talking about.
Introduction
The introduction reads very well – not much to revise from my point of view. However, I found the isotope analysis as not at all motivated in the introduction. You should mention at some point here and / or in the methods what this analysis is used for.
L56: “water table” or better “water levels” is enough.
L60: These studies use the TWI at catchment scale or in riparian zones but not in peatlands. Are there also examples from peatlands pointing a dominant topographic control of discharge generation?
Methods
L109: To what is the abbreviation “FMI” pointing to?
L115: Try to be more precise here. Is this the pH in the surface water or in the soil water?
Fig. 1: I find it rather unusual to use a copy of a topographic map as a background. All shown features are useless unless explained in a legend. But are all shown features necessary to know? Isolines lack numbers! Potentially use the right map to show the location of the research station/ precipitation sampler.
L177: Explain GCPs.
Fig. S2: This relationship looks rather weak. Can you report on the R2 and bias and have you used the confidence interval later on as shown (but not described) here?
Results
I find the description of snowmelt with 5 figures and 2 tables as too extensive. Information can be transferred in a more condensed way focusing on the information that is really needed in the subsequent analysis.
L291: What caused the rapid snowmelt? Temperature? Rainfall on snow?
L292: To what statistic measure “variation” is referring to? Can you be more quantitative here?
L331: For me it is a surprise that the SWI is dynamic. The description in the method does not point to SWI being used as a dynamic surface feature. I interpreted it as a static topography feature. So, for me this is hard to understand. Do you describe snow melt in different classes of the snow-free topography or temporally dynamic SWI of the snow surface?
L334f: Can you state if difference were statistically significant?
Table 3: For me it would be a better option to show the content of that table in Fig. 6 as a third panel.
Chapter 3.2: The title implies a description of DOC only but the chapter contains much more.
Fig. 7: Use TSSeq concentrations in the axis as well. Is this mg/L as a unit or rather unitless? What is the data source for snow depths here? Is this the same data as described above (UAS)? I am not sure if there is a reason to display load of DOC and TSS concentrations in the same plot. Same for WTD and water temperature.
L355: Consider a different wording as “followed by” implies that first discharge increased and then air temperature and rainfall increased (that actually triggered the discharge?).
L362-374: Concentration of DOC hardly change over time so that the discharge dynamics are the overwhelmingly dominant driver of the load, right? This stark differences in the variation of both could be mentioned here.
L398: This statement puzzles me as the relative position of DOC and Q in the plot (Fig. 8) is matter of the scaling of the two different Y-axes.
Fig. 8: Why is cumulative Q and SWE loss with the same unit referring to different Y-axes. This should be on the same axis. I have troubles understanding the SWE loss in the figure. Majority happens at the 9th May – I see that this is due to a gap in the data. However, the way to display this is not helpful. Consider to leave out the vertical line starting from 0.
L433-435: Some of the information are redundant here as anticlockwise and HI<0 is the same thing.
Fig. 9: Use TSSeq on the axis.
Discussion
I have issues with the cut between chapter 4.1, 4.2 and 4.3. For me the separation is not clear but redundancies are large. Discussion circles around the same processes that are explained by different data in the different chapters. The idea of a discussion should be more integrative and less along the steps of the result section, especially when the same processes are discussed.
L462: Again, I have issues to make the link of snowmelt and SWI. A high SWI marks areas in the landscape that tends to be wetter as flow paths converge (large upstream area, low slope) while low SWI values mark areas that are steeper and have smaller upstream area. How does that come together with the snow melt? In a direct causative way? Or because both are a function of topography? Steeper hillslopes do not allow for snowpack accumulation and are more exposed to radiation… So how does that link to connectivity in the landscape?
L478f: The ice cover is a new result brought up here. For me it does not really explain why ice is forming here especially.
L503: This relative increase was not convincingly shown nor quantified in the result. So, it is a bit hard to follow that argument here.
L509f: However, consider that the dilution effect is very small with concentration hardly changing during the event. This speaks rather for a transport and not a source limitation of DOC. So, from my observation I see very mild dilution effects only and therefore nearly every flow path loaded with DOC and therefore no major changes in sources of flowpath. This is basically a chemostatic system.
L538-553: For me this discussion repeats former statement but add some TSS data. I suggest to strongly reduce redundancies and combine with the discussion above.
L555ff: This is a long statement for a rather simple fact. Nearly invariant concentrations multiplied with highly variant discharge will result in a load that is exactly the same as the discharge.
L592ff: Again, I would be careful in interpreting the mild concentration changes too much. Yes, the described processes are meaningful but I don’t think we see a fundamental change of flow paths and sources but rather slight changes. So, phrases such as “quick depletion” or “sudden depletion” are a bit too much for me.