Articles | Volume 30, issue 20
https://doi.org/10.5194/hess-30-6443-2026
© Author(s) 2026. This work is distributed under the Creative Commons Attribution 4.0 License.
Evaluation of SWOT HR PIXC version D water level time series of small lakes
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- Final revised paper (published on 22 Oct 2026)
- Preprint (discussion started on 11 Feb 2026)
Interactive discussion
Status: closed
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
| : Report abuse
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RC1: 'Comment on egusphere-2025-6366', Salvatore Manfreda, 04 Mar 2026
- AC1: 'Reply on RC1', Simon Köhn, 19 Mar 2026
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RC2: 'Comment on egusphere-2025-6366', Anonymous Referee #2, 05 Mar 2026
- AC2: 'Reply on RC2', Simon Köhn, 19 Mar 2026
In the manuscript “Evaluation of SWOT HR PIXC version D water level time series of small lakes”, the authors validate the SWOT HR PIXC product for constructing water surface elevation (WSE) time series over 37 Danish lakes. The study proposes a filtering and aggregation workflow for HR PIXC point-cloud data and evaluates the resulting lake-level estimates against in situ gauge observations.
The topic is relevant to the hydrology and remote-sensing communities, and the technical processing appears generally sound. However, in its current form the paper reads largely as a product-validation and methodological benchmarking study, and it feels borderline relative to the scope typically expected for a full Research Article in HESS. The manuscript could potentially fit better as a Technical Note in HESS unless the broader hydrological implications and generalizability are strengthened.
Major comments
Native PIXC spatial sampling and implications for robustness
A key advantage of SWOT is its dense, two-dimensional spatial sampling of water surfaces. While the validation ultimately compares a single aggregated WSE value per lake per overpass, the reliability of this estimate depends strongly on the spatial sampling and point density of the HR PIXC data retained after filtering.
Please (i) clearly state the native spatial sampling characteristics of the HR PIXC dataset (e.g., effective point spacing/footprint and any relevant along-/across-track considerations), and (ii) discuss how these characteristics interact with the selected filtering/selection criteria (e.g., water fraction thresholds, quality flags, distance-to-shore constraints, etc.). In particular, it would be helpful to explain how the retained point-cloud geometry affects representativeness for small lakes, near-shore zones, and narrow/irregular lake shapes.
Hydrological relevance and limitations of validating only relative WSE changes with a static mask
The Introduction motivates applications such as flood detection and small-lake monitoring, but the methodology primarily validates relative WSE changes and relies on a static lake mask for extracting PIXC data. This choice has important implications: a static mask can include land pixels during low-water conditions and exclude wetted areas during high-water conditions, potentially introducing systematic errors—especially when hydrological dynamics cause appreciable changes in lake extent.
Moreover, the study does not attempt to infer changes in surface area, storage, or volume—metrics that are often more directly relevant for water resources management and flood/drought assessment than WSE alone. As written, this constraint represents the main methodological weakness, because it limits interpretability in dynamic conditions and may lead to systematic volumetric biases even if WSE variability is captured reasonably well.
I recommend that the authors more rigorously justify this design choice and explicitly discuss the hydrological implications and potential biases. At minimum, the manuscript should clarify the intended use-case (e.g., lake-level anomaly tracking vs. hydrologic accounting) and delineate when the approach is expected to be reliable or unreliable. If feasible, the paper would be substantially strengthened by either (i) a sensitivity analysis demonstrating the impact of mask mismatch across hydrologic states, or (ii) a discussion (and possibly a proof-of-concept) of strategies to incorporate dynamic water extent (e.g., time-varying masks or classification) and how this would affect WSE and downstream storage estimates.
Structure and separation of Results vs. Discussion (Sections 4 and 5)
Sections 4 and 5 would benefit from clearer separation between Results and Discussion. Currently, interpretive statements appear interwoven with results, and the subdivision into multiple short subsections makes the narrative feel fragmented. I suggest consolidating the results into a more coherent sequence (e.g., overall performance metrics → sensitivity to filtering choices → lake-size/geometry effects → outlier/failure cases), followed by a Discussion that synthesizes the key findings, explains mechanisms behind observed patterns, and articulates limitations and practical guidance.
In addition, a concise discussion of the broader applicability of the proposed workflow beyond the Danish lake set (e.g., expected behavior in different geomorphologies, vegetation, turbidity, wind conditions, or hydrological regimes) would improve the manuscript’s relevance to the wider HESS readership.
Overall recommendation
The study is technically robust, but it remains primarily a validation/benchmarking effort. I therefore consider it borderline for a full Research Article in HESS in its current form. It may be better positioned as a Technical Note in HESS, or alternatively as a Research Article if the authors (i) clarify and justify key methodological choices—especially the static mask and the focus on relative WSE—and (ii) strengthen the discussion of hydrological implications and generalizability.