University of California, Davis (UC Davis) | December 19th, 2025
Summary
Sediment bulk density (ρ-dry) and particle size are two important parameters for predicting sediment bed erosion. ρ-dry, however, is difficult to measure accurately. Th
Sediment bulk density (ρ-dry) and particle size are two important parameters for predicting sediment bed erosion. ρ-dry, however, is difficult to measure accurately. The units of ρdry have not been consistently reported in the literature, leading to confusion, particularly in the calculation of sediment budgets that typically require integrating mass-based and volumetric components. Relationships between ρdry and sediment composition have been developed for multiple regions and differ between systems. Developing a system-specific predictive model for ρdry can help fill data gaps and improve sediment budgets, model accuracy, and estimates of quantities of sediment needed for restoration. In this study, we investigate whether ρdry in San Francisco Estuary can be predicted from organic carbon content or percent of fines, which are more easily or frequently measured than ρdry. We compiled sediment properties from samples collected over the past decade throughout the intertidal and subtidal regions of San Francisco Bay and the Sacramento–San Joaquin Delta to examine this relationship. Sample composition ranged from 2.18 to 99.97% fines (particles < 0.0625 mm), ρ-dry ranged from 0.22 to 1.60 g cm-3, and organic carbon ranged from 0.06 to 7.98%. Regression analysis indicates that the percent of fines explains 93% of the variation of ρ-dry (p-value < 0.05, N = 81). The coefficient of determination decreased by ~1% when organic carbon was incorporated in the regression analysis. Comparison of this predictive ρ-dry model to four published models based on samples from other regions supports previous findings that the relationship between ρdry and grain size may vary by system. We also examined additional factors that may affect sediment erodibility, such as hydrographic and oceanographic conditions. Classification of sample sites as intertidal vs. subtidal or wavy vs. non-wavy each significantly explained the residuals from the ρdry model, and both intertidal and wavy conditions were associated with higher ρ-dry values.