2022 CSDMS meeting-022
Exploring the utility of a probability-based river bed evolution model
Scott Feehan, University of Nevada Reno Nevada, United States. email@example.com
Scott McCoy, University of Nevada Reno Nevada, United States. firstname.lastname@example.org
Joel Schiengross, University of Nevada Reno Nevada, United States. email@example.com
River-bed grain size distributions in fluvial systems set the initial condition for landscape change on the event to millennia scale. These distributions are used to infer characteristic flow conditions or estimate mass flux through a fluvial system, and this is often under the assumption that sediment grain-size distribution on the bed remains static over time. However, recent work has shown that grain size distributions can fluctuate over individual flow events, can be dependent on the sequence of successive flow events, and can change seasonally. This discrepancy can lead to order of magnitude differences in estimating sediment flux or characteristic hydrologic conditions. To constrain bed grain size evolution, we perform numerical simulations using a probabilistic, discrete model of a river bed in which computational cells represent grains randomly distributed across the surface of the bed. Patterns and timing of grain mobilization are determined according to distributions of entrainment thresholds for individual grains and flow rate dependent distributions of velocity fluctuations that vary over hydrographs. Entrained grains are replaced from a static distribution allowing the bed grain size distribution to evolve throughout the simulation depending on the imposed flow condition. Our preliminary model results from varying initial grain size distribution, individual event shape, and flow sequencing show a significant dependence on the range of grain sizes available for transport as well as the total duration of individual flow events, while seasonal variability has a moderate impact on bed grain size evolution.