We calibrated the watershed model SPARROW (Spatially Referenced Regressions on Watershed attributes) to give estimates of suspended-sediment loads for western Oregon and parts of northwestern California. Estimates of suspended-sediment loads were derived from a nonlinear least squares regression that related explanatory variables representing landscape and transport conditions to measured suspended-sediment loads at 68 measurement stations. The model gives estimates of model coefficients and their uncertainty within a spatial framework defined by the National Hydrography Dataset Plus hydrologic network. The resulting model explained 64 percent of the variability in suspended-sediment yield and had a root mean squared error value of 0.737. The predictor variables selected for the final model were (1) generalized lithologic province, (2) mean annual precipitation, and (3) burned area (by recent wildfire). Other landscape characteristics also were considered, but they were not significant predictors of sediment transport, were strongly correlated with another predictor variable, or were not as significant as the predictors selected for the final model.
Knowledge of the regionally important patterns and factors in suspended-sediment sources and transport could support broad-scale, water-quality management objectives and priorities. Because of biases and limitations of this model, however, these results are most applicable for general comparisons and for broad areas such as large watersheds. For example, despite having similar area, precipitation, and land-use, the Umpqua River Basin generates 68 percent more suspended sediment than the Rogue River Basin, chiefly because of the large area of Coast Range sedimentary province in the Umpqua River Basin.Keyword Tags: