Characterizing operational signatures of reservoirs with the SWOT satellite by comparing natural lake and reservoir dynamics
Due to a lack of management operations data, hydrological models may represent reservoirs as natural lakes, leading to poor discharge predictions in regulated basins. To parse seasonal operational signatures, we compare the dynamics of natural lake and reservoir systems across North America using Surface Water and Ocean Topography (SWOT) satellite observations and derived discharge estimates. Overall, reservoirs and their adjacent river reaches exhibit significantly greater variability (in standard deviation) than their natural counterparts across almost all SWOT observed (e.g. water surface elevation) and inferred (e.g. discharge) variables. Natural lakes show strong same-day correlations between inflow and outflow discharge (median Spearman R = 0.8), whereas 76% of reservoirs exhibit maximum correlation when outflow is lagged, suggesting operations buffer seasonal flow variability. Our findings indicate operations not only affect reservoir dynamics themselves but also have upstream and downstream consequences, which, when integrated into models, will offer more realistic hydrologic conditions.
Citation Information
| Publication Year | 2026 |
|---|---|
| Title | Characterizing operational signatures of reservoirs with the SWOT satellite by comparing natural lake and reservoir dynamics |
| DOI | 10.1088/1748-9326/ae436e |
| Authors | Ryan Matthew Riggs, Jesse E. Dickinson, Craig B. Brinkerhoff, Md. Safat Sikder, Jida Wang, Huilin Gao, George H. Allen |
| Publication Type | Article |
| Publication Subtype | Journal Article |
| Series Title | Environmental Research Letters |
| Index ID | 70273939 |
| Record Source | USGS Publications Warehouse |
| USGS Organization | WMA - Integrated Modeling and Prediction Division |