the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 11 Feb 2026
Evaluation of SWOT HR PIXC version D water level time series of small lakes
Abstract. Satellite altimetry has successfully monitored inland waters for more than 30 years and is increasingly important as the demand for freshwater grows and climate change accelerates. Launched in December 2022, the Surface Water and Ocean Topography (SWOT) satellite is the first to provide 2D spatially distributed elevation measurements, with a 21-day revisit time and better coverage depending on latitude and a nominal requirement to detect lakes as small as 0.06 km2. Here, we evaluate the SWOT L2 HR PIXC version D data product (if available at the time of writing) to construct time series of water surface elevation (WSE) and capture their relative WSE change in 37 Danish lakes with a surface area between 0.25 km2 and 40 km2 via the summary measures RMSE and Pearson’s correlation coefficient (PCC). We tested six selection criteria to aggregate one WSE value per lake and timestamp. The median unbiased RMSE of SWOT vs gauge is 5.34 cm, and the median PCC is 0.91. We find indications that SWOT’s PIXC data contains time–varying residual roll–errors over Danish lakes. We demonstrate that our approach performs slightly better than filtered SWOT L2 HR LakeSP prior data from Hydrocron in terms of RMSE and PCC (6.05 cm and 0.89), while retaining roughly double the number of valid timestamps over the overlapping period.
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Status: open (until 25 Mar 2026)
- RC1: 'Comment on egusphere-2025-6366', Salvatore Manfreda, 04 Mar 2026 reply
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RC2: 'Comment on egusphere-2025-6366', Anonymous Referee #2, 05 Mar 2026
reply
This manuscript evaluates the use of SWOT L2 HR PIXC data to derive relative water surface elevation (WSE) time series for small Danish lakes and compares the results with the LakeSP product. The topic is timely and the validation dataset is potentially valuable. However, in its current form, the paper reads more like a processing/engineering report than a scientific study, and the broader significance of the proposed workflow is not yet convincingly demonstrated. Several methodological choices also require clearer definition and stronger justification. Below I outline major issues that should be addressed before the manuscript can be considered for publication.
Major comments
1) Novelty and scientific contribution relative to LakeSP are not sufficiently established.
At present, the manuscript mainly documents a processing workflow and reports summary metrics for Danish lakes. The improvement over the filtered LakeSP product appears modest (median RMSE 5.34 cm vs. 6.05 cm; median PCC 0.91 vs. 0.89), which raises the question of whether the contribution is a conceptual advance or primarily an alternative filtering/aggregation strategy. The authors should explicitly clarify:What is fundamentally new in the proposed approach (beyond parameter choices and filtering rules)?
Why this constitutes a meaningful advancement over LakeSP in terms of methodological design, robustness, or interpretability?
Under what conditions the proposed method is expected to outperform LakeSP (e.g., lakes with small seasonal amplitudes? high-latitude multi-pass coverage?), and why.
Without a clearer positioning, the contribution currently appears incremental.
2) Limited geographic scope and weak discussion of transferability/scalability.
The study focuses exclusively on Danish lakes. While this is a reasonable testbed, the manuscript does not clearly explain how the findings generalize to other hydroclimatic settings (e.g., arid regions, vegetated shorelines, tropical systems) or to regions with different viewing geometries and sampling densities. In particular, it is unclear whether key selection criteria (e.g., ≥200 points per acquisition, strict geo-flag handling) are transferable to areas with fewer valid observations per pass, smaller lakes, or more heterogeneous shorelines.3) Methodological description needs clearer formalization and stronger justification.
Despite the technical focus, several core steps are not described with sufficient precision to ensure reproducibility or to interpret why performance improves:The WSE aggregation procedure should be formally defined (e.g., summary statistic used, whether any weighting is applied, outlier handling rules, spatial screening, and how multiple water bodies within a mask are treated).
The sensitivity of results to the ≥200-point threshold should be assessed more explicitly (e.g., dependence on lake area, swath edge vs. near-nadir sampling, and seasonal/ice conditions).
The rule to exclude all geo-flagged observations (unless the point count drops below 200) needs a clearer statistical rationale. Why is this threshold optimal or conservative, and how robust is it?
In addition, the roll-error discussion remains largely qualitative. If residual roll error is emphasized as affecting ~18% of acquisitions, the manuscript should provide a more systematic quantification approach (e.g., uncertainty envelopes, swath-position dependence, cycle-to-cycle variability), and discuss the implications for inland-water monitoring beyond Denmark.
4) LakeSP comparison is not sufficiently diagnostic to support strong conclusions.
The manuscript argues that the proposed approach performs slightly better while retaining more timestamps, but the comparison does not yet isolate why differences occur. In particular:The evaluation should include a more systematic statistical comparison (e.g., lake-by-lake paired differences in RMSE/PCC, confidence intervals/bootstrapping, performance stratified by lake size, WSE amplitude, swath position, and presence/absence of roll error).
The trade-off between operational simplicity (LakeSP) and configurability (proposed workflow) should be framed explicitly: in what use cases does the proposed method justify additional complexity?
As written, the marginal performance gains make it difficult to justify the proposed workflow as a replacement or substantive supplement to LakeSP.
5) Structure and framing should be revised toward a hypothesis-driven scientific narrative.
The manuscript would benefit from substantial restructuring to move from a workflow description to a clearer scientific contribution. Specifically:State explicit research questions/hypotheses early (e.g., “Can PIXC-derived relative WSE time series for small lakes achieve cm-level accuracy, and what selection criteria are required?”).
Separate methodology development, validation results, and implications for broader SWOT inland-water applications.
Strengthen the discussion to emphasize what the Danish case study reveals about SWOT capabilities/limitations for small lakes globally.
Summary recommendation
The dataset and topic are valuable, and applying SWOT to small lakes is an important research direction. However, the current manuscript does not yet demonstrate a sufficiently strong methodological innovation or convincingly argue global relevance. I recommend Major Revision, focusing on (i) clarifying novelty relative to LakeSP, (ii) formalizing and justifying methodological choices, and (iii) providing a clearer framework for transferability and scalability beyond Denmark.
Citation: https://doi.org/10.5194/egusphere-2025-6366-RC2
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- 1
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.