Search for: All records

Low-head dams (LHDs) are widespread in river systems, yet the volume of sediment impounded behind them remains largely unquantified. Failure or planned removal of these often-aging structures can mobilize stored sediment, posing added risk to reservoirs already losing capacity to sedimentation. In Kansas, the failure of an LHD in May 2018 released sediment equivalent to ~25% of the downstream reservoir's annual accumulation and motivated a broader assessment of storage behind other LHDs. Addressing this knowledge gap, this study quantifies sediment storage behind LHDs located upstream of three federal reservoirs: Tuttle Creek Lake, Perry Lake, and Kanopolis Lake. An integrated approach was employed, combining remote sensing for LHD identification with field-based bathymetric surveys and sediment analysis to directly measure accumulated sediment volumes (VLHD) at representative sites and to estimate VLHD at remotely sensed sites. The relative storage for individual LHDs, expressed as a fraction of downstream annual reservoir sedimentation (fARS), ranged from 0.005 to 0.659, with a median fARS of 0.025. Storage volume (VLHD) was more closely related to local physical properties of LHDs—such as dam height and width—than watershed-scale drivers, such as precipitation and drainage area. Bathymetric maps revealed scour holes immediately upstream of LHDs, typically centered 20–50 m upstream and up to ~1.3 m deep, indicating partial sediment continuity and dynamic equilibrium. This research provides crucial data to inform regional sediment management and enhance reservoir sustainability in Kansas and offers a transferable methodology for quantifying the contribution of LHDs in other watersheds. 

Abstract The Surface Water and Ocean Topography (SWOT) satellite has the potential to transform global hydrologic science by offering simultaneous and synoptic estimates of river discharge and other hydraulic variables. Discharge is estimated from SWOT observations of water surface elevation, width, and slope. A first assessment using just the highest quality SWOT measurements, over the first 15 months (March 2023–July 2024) of the mission evaluated at 65 gauged reaches shows results consistent with pre‐launch expectations. SWOT estimates track discharge dynamics without relying on any gauge information: median correlation is 0.73, with a correlation interquartile range of 0.51–0.89. SWOT estimates capture discharge magnitude correctly in some cases but are biased (median bias is 50%) in others. There are already a total of 11,274 ungauged global locations with highest quality SWOT measurements where SWOT discharge is expected to accurately track discharge variations: this value will increase as SWOT data record length grows, algorithms are refined and SWOT measurements are reprocessed. This first look indicates that SWOT discharge is performing as expected for SWOT data that achieve performance requirements, providing observed information on discharge variations in ungauged basins globally.