Ma et al. (2026) Monitoring Reservoir Storage Using SWOT Satellite Observations and a Reservoir Operation Model

⚠️ Warning: This summary was generated from the abstract only, as the full text was not available.

Identification

• Journal: Water Resources Research
• Year: 2026
• Date: 2026-03-01
• Authors: Xiaoyu Ma, Jida Wang, Shervan Gharari, Naoki Mizukami, Dennis P. Lettenmaier
• DOI: 10.1029/2025wr041223

Research Groups

The abstract does not explicitly list specific research groups or departments. However, the study is centered around the Surface Water and Ocean Topography (SWOT) satellite mission, implying involvement from institutions associated with its development, operation, and data analysis, likely including space agencies and hydrological research centers.

Short Summary

This study evaluates the accuracy of reservoir storage estimates derived from the new Surface Water and Ocean Topography (SWOT) satellite mission against in situ observations for 12 Western U.S. reservoirs, finding that SWOT provides highly accurate water surface elevation and storage data that can effectively constrain hydrological models to fill temporal gaps.

Objective

• To evaluate the accuracy of Surface Water and Ocean Topography (SWOT)-based estimates of reservoir storage by comparing them with in situ observations for 12 reservoirs in the Western U.S.

Study Configuration

• Spatial Scale: 12 reservoirs located in the Western U.S., specifically four in California, four in the Upper Colorado River Basin, and four in the Columbia River Basin.
• Temporal Scale: 19 months of observations, starting from August 2023 (when SWOT science observations began).

Methodology and Data

• Models used: Reservoir simulation model (unspecified, used for filling temporal gaps and constrained by SWOT observations).
• Data sources:
  • Surface Water and Ocean Topography (SWOT) satellite mission: Provides global, simultaneous Water Surface Elevation (WSE) and Surface Area (SA) maps.
  • In situ observations: Used as ground truth for comparison with SWOT-based estimates.

Main Results

• SWOT produces Water Surface Elevation (WSE) measurements with a median absolute error (MAE) of less than 20 cm across all 12 reservoirs and 19 months of observations.
• SWOT-based reservoir storage estimates show a median absolute error (MAE) of less than 10%.
• Model-based reservoir storage estimates, when constrained by SWOT observations, can accurately and efficiently fill temporal gaps, even if fewer than one-quarter of SWOT observations are valid.

Contributions

• Provides an early, comprehensive evaluation of the accuracy of the newly launched SWOT satellite mission for estimating reservoir storage using real-world data.
• Demonstrates the high potential of SWOT data to significantly improve global reservoir monitoring, particularly in regions with limited or no in situ observations.
• Highlights the utility of SWOT observations for constraining and improving reservoir simulation models, enabling accurate temporal gap-filling.

Funding

Not specified in the abstract.

Citation

@article{Ma2026Monitoring,
  author = {Ma, Xiaoyu and Wang, Jida and Gharari, Shervan and Mizukami, Naoki and Lettenmaier, Dennis P.},
  title = {Monitoring Reservoir Storage Using SWOT Satellite Observations and a Reservoir Operation Model},
  journal = {Water Resources Research},
  year = {2026},
  doi = {10.1029/2025wr041223},
  url = {https://doi.org/10.1029/2025wr041223}
}