Near‐Channel Versus Watershed Controls on Sediment Rating Curves

Abstract

Predicting riverine suspended sediment flux is a fundamental problem in geomorphology, with important implications for water quality, land and water resource management, and aquatic ecosystem health. To advance understanding, we evaluated environmental and landscape factors that influence sediment rating curves (SRCs). We generated SRCs with recent total suspended solids (TSSs) and discharge data from 45 gages on 36 rivers throughout the state of Minnesota, USA. Watersheds range from 32 to 14,600 km2 and represent distinct settings regarding topography, land cover, and geologic history. Rivers exhibited three distinct SRC shapes: simple power functions, threshold power functions, and peaked or negative‐slope functions. We computed SRC exponents and coefficients (describing the steepness of the relation and the TSS concentration at median flows, respectively). In addition to quantifying watershed topography, climate/hydrology, geology, soil type, and land cover, we used lidar topography to characterize the near‐channel environment upstream of gages. We used random forest models to analyze relations between SRC parameters and attributes of the watershed and the near‐channel environment. The models correctly classify 78% of SRC shapes and explain 37%–60% of variance in SRC parameters. We find that SRC steepness (exponent) is strongly related to near‐channel morphological characteristics including near‐channel relief, channel gradient, and presence of lakes along the local channel network, but not to land use. In contrast, land use influences TSS concentrations at moderate and low flow. These findings suggest that the near‐channel environment controls changes in TSS as flows increase, whereas land use drives median and low flow TSS conditions.

Concentration–discharge relationships describe solute and sediment mobilization, reaction, and transport at event and longer timescales

“…Sediment rating curves, or sediment C‐Q relationships, can be used in combination with knowledge of key watershed hydrologic processes to evaluate particulate sources and transport (Tolorza et al, ; A. A. Vaughan, Belmont, Hawkins, & Wilcock, ). In the case of White Clay Creek, the interannual C‐Q relationship indicates a strongly positive trend in log(C)–log (Q), whereby increasing flows mobilize increasing amounts of particulate materials such as those in and near the channel (e.g., A.…”

“…In the case of White Clay Creek, the interannual C‐Q relationship indicates a strongly positive trend in log(C)–log (Q), whereby increasing flows mobilize increasing amounts of particulate materials such as those in and near the channel (e.g., A. A. Vaughan, Belmont, et al, ). This overall pattern is consistent with observed event‐based clockwise hysteresis (Table ), regional prevalence of streambank erosional sources (Dhillon & Inamdar, ), and observations of subsurface storm flow dominating hydrologic pathways (McLaughlin, ; McLaughlin & Kaplan, ; Sawyer et al, ).…”

Timescale dependence in river channel migration measurements

“…Changes in sediment loading over time have not been examined, although the land‐use history bears many similarities to the well‐studied Coon Creek, directly across the Mississippi River (Trimble, , ). The Root River watershed exhibits some of the steepest relationships between discharge ( Q ) and total suspended solids (TSS) throughout Minnesota (Vaughan et al ., ), indicating the presence of considerable near‐channel sediment sources that are highly vulnerable to erosion, especially under high flow conditions (Stout et al ., ; Belmont et al ., ). Combining three distinct geomorphic settings with the spatially (120 km) and temporally (76 years) robust set of historical air photographs provides an exemplary opportunity to explore timescale dependence of migration measurements along an alluvial river experiencing increased flow.…”

Development and Application of a Large‐Scale, Physically Based, Distributed Suspended Sediment Transport Model on the Fraser River Basin, British Columbia, Canada

“…A number of the empirical sediment models that are used for large‐scale studies (e.g., Hovius, ; Syvitski et al, ) are lumped —treating the entire basin as a homogeneous entity—and therefore only predict load at the basin scale with limited consideration of spatial variability (Pelletier, ). However, studies such as Vaughan et al () have demonstrated that spatially varying properties like near‐channel morphology and land use can influence a basin's relationship to water flux. Smith et al () and Pelletier () both argued that because a large portion of sediment within a basin can be supplied by a relatively small portion of the total catchment area, subbasin supply and load dynamics should be quantified to accurately estimate watershed sediment yield.…”