Fine particles or sediments have various effects on water quality and aquatic ecosystems. Thus, understanding the dynamics of these fine particles between water body and stream bed is an important issue in sediment research. Previous studies and analysis of empirical data suggest that fine particles are stored in the sediment bed in the low flow regime, where flow rate is smaller than the critical flow rate that mobilizes the sediment bed. These fine particles are re-suspended during flood events when the flow rate becomes larger than the critical flow rate that mobilizes bed material. The transition from pattern recognition to process analysis required incorporation of the dominant processes controlling fine particle dynamics within gravel-bedded streams into a model. The process analysis was performed using continuous flow and turbidity data at two locations on the Russian River in California to test process descriptions and then calibrate a quantitative model to represent those processes. The resulting process model coupled fine particle retention within the sediment bed by filtration and sedimentation with the release of accumulated fine particles in response to flood events. Model parameters, such as the critical flow rate required for initiating sediment bed fluidization, the maximum fine particle storage capacity within the sediment bed, and background particle concentration for the watershed, were estimated from the monitoring data. Model calibration optimized the filtration and the sediment bed fluidization parameters over two or three years of data. Overall, the difference between modeled and observed fine particle mass released from the sediment bed was within 20% of the measured mass.