Articles | Volume 30, issue 18
https://doi.org/10.5194/hess-30-5999-2026
© Author(s) 2026. This work is distributed under the Creative Commons Attribution 4.0 License.
Calibration using downscaled and bias-corrected satellite soil-moisture data can improve watershed model representation of soil-moisture variability
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- Final revised paper (published on 24 Sep 2026)
- Preprint (discussion started on 04 Dec 2025)
Interactive discussion
Status: closed
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor
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RC1: 'Comment on egusphere-2025-5813', Anonymous Referee #1, 06 Jan 2026
- AC2: 'Reply on RC1', Zachary Easton, 12 Mar 2026
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RC2: 'Comment on egusphere-2025-5813', Mikolaj Piniewski, 12 Feb 2026
- AC1: 'Reply on RC2', Zachary Easton, 12 Mar 2026
Peer review completion
AR – Author's response | RR – Referee report | ED – Editor decision | EF – Editorial file upload
ED: Reconsider after major revisions (further review by editor and referees) (24 Mar 2026) by Roberto Greco
AR by Zachary Easton on behalf of the Authors (04 May 2026)
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ED: Referee Nomination & Report Request started (13 May 2026) by Roberto Greco
RR by Mikolaj Piniewski (13 Jun 2026)
RR by Anonymous Referee #1 (22 Jun 2026)
ED: Publish subject to revisions (further review by editor and referees) (23 Jun 2026) by Roberto Greco
AR by Zachary Easton on behalf of the Authors (04 Aug 2026)
Author's response
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ED: Publish subject to technical corrections (17 Aug 2026) by Roberto Greco
AR by Zachary Easton on behalf of the Authors (17 Aug 2026)
Author's response
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This manuscript examines the use of streamflow and downscaled and bias-corrected satellite soil moisture data for calibrating a SWAT-VSA model in a small, saturation-excess dominated watershed. The topic is relevant and timely; however, some issues need to be addressed before the manuscript can be considered for publication.
1. The Introduction does not sufficiently clarify the specific novelty of this study relative to existing literature. If the main contribution lies in calibrating hydrological models using downscaled and bias-corrected satellite soil moisture, the authors should more clearly review and position their work within existing studies on satellite soil moisture downscaling, bias correction, and reported performance improvements. Similarly, if the key contribution is the application of SWAT-VSA in saturation-excess dominated watersheds, the importance and added value of this choice should be more explicitly articulated. At present, the objectives and innovation of the study are not clearly distinguished from prior work.
2. The study is conducted in a single small watershed (~14 km²) dominated by saturation-excess runoff and relies on the SWAT-VSA model. While this choice is physically appropriate for the study site, it substantially limits the generality of the conclusions. The manuscript should more explicitly discuss the limits of applicability of the proposed approach, and the conclusions should be clearly framed as primarily applicable to small, saturation-excess runoff dominated catchments.
3. The study relies on a pretrained mlhrsm downscaling model and an empirical, precipitation-threshold-based bias correction scheme. However, the regional applicability of the pretrained downscaling model is not evaluated, and no comparison is shown between original, downscaled, and bias-corrected soil moisture. The authors should explicitly show these differences and discuss how the downscaling and bias correction steps influence the soil moisture signal used for calibration and, consequently, the model results.
4. A key concern relates to the representativeness of the soil moisture observations. The 25 soil moisture sensors are located within a 4.2 ha pasture, whereas the modeled watershed covers approximately 14 km². It is unclear whether such a limited area is sufficient for evaluating model performance at the watershed scale.
5. An additional concern is that the evaluation of soil moisture performance throughout the manuscript is based primarily on soil moisture data that have undergone both downscaling and bias correction by the authors, without independent validation. While this preprocessing may be necessary, it raises the question of how the reliability of the calibrated model can be independently assessed.
The manuscript would benefit from a clearer explanation of how the authors ensure that the improved soil moisture performance reflects genuine model skill rather than agreement with a processed target dataset. In particular, the role of independent in-situ soil moisture observations in validating the calibration results should be more explicitly discussed, and the potential circularity introduced by calibrating and evaluating against processed soil moisture data should be acknowledged.
6. In addition, the authors should clarify why downscaling to 500 m resolution is necessary if the soil moisture data are ultimately averaged to the watershed scale for calibration. It should be discussed whether this averaging undermines the advantages of using a spatially explicit, VSA-based distributed model.
7. The Discussion section could be streamlined by reducing repetitive literature comparisons and would benefit from a more critical assessment of which aspects of soil moisture and streamflow dynamics remain poorly captured. The authors should discuss whether these limitations reflect structural constraints of the SWAT model (e.g., simplified representation of unsaturated flow processes), and whether the observed performance gains justify the additional complexity introduced by downscaling, bias correction, and multi-objective calibration. A clearer distinction between statistical improvement and process-level improvement would strengthen the interpretation of the results.
Minor comments
1. Figures in the Appendix (e.g., Fig. A1 and Fig. A2) are essential for understanding the workflow and study area and should be moved to the main text.
2. The description in Section 2.2 and Fig. A2 may give the misleading impression that the study area is the full 57 km² Stroubles Creek watershed rather than the upper ~14.5 km² watershed.
3. The number of calibration iterations is reported in Section 2.5.4 (Parameter Uncertainty) but should be clearly stated in the Calibration Strategy section.
4. The sensitivity analysis period (2015–2019) differs from the calibration and evaluation periods without sufficient justification. In addition, results in Fig. A3 are shown only for 2018, which requires explanation.
5. Figure 1 and Figure 4 do not clearly convey differences among the three calibration strategies and could be improved for clarity.