Abstract Submission: Fine-grained, suspended sediments are a leading pollutant of water bodies (streams, lakes, reservoirs, etc.) in the United States (US) of America. Farmland and stream banks are the main sources of the fine-grained sediments. US Government and other organizations are transitioning to the development of physically- and process-based prediction technology to improve the assessment of sheet and rill, gully and embankment erosion processes, and the impact of best management practices to control these types of erosion. Unfortunately, measured soil erosion-resistance parameters exhibit large variability (up to several orders of magnitude) not only between different soil types, but also for same or similar soil types. This variability is not only caused by the inherent, spatial variability in soil properties (e.g., texture, density, moisture, and organic content), but also by the different instrumentation and post-processing techniques employed to quantify soil erosion-resistance. Therefore, it can be problematic to use generalized, published soil erosion-resistance values when designing critical structures such as bank protection and levees. Past work along the Lower American and Sacramento Rivers (LASRs), CA, has shown that improved post-processing techniques can minimize differences in measured erosion resistance values obtained using the Jet Erosion Test (JET) and Erosion Function Apparatus (EFA). Further, the improved erosion-resistance values appear to group by Unified Soil Classification System soil type. The US Department of Agriculture database of over 1,000 JETs was reanalyzed using the new, improved post-processing technique. Bank erosion simulations for the LASRs have shown that the reanalyzed data provide more reliable erosion estimates.
