Advancements In Predicting Bank Erosion Processes With The Bank Stability and Toe Erosion Model (bstem)

Modeling bank erosion is problematic not only because of limiting assumptions but also constraints associated with assigning discrete values for controlling variables. Often, repeated in-situ tests will result in a range of potential values for a given parameter which can make it difficult on the modeler to determine the appropriate input. To account for the variability associated with testing, and potential spatial and temporal variability, the dynamic version of the Bank Stability and Toe Erosion Model (BSTEM) has been updated to include stochastic predictions using Monte Carlo analyses. Values for bank profile parameters used to determine fluvial erosion rates and resistance to bank failure can be generated using a variety of stochastic distributions. Having the ability to vary parameters within known ranges provides the user with quantified confidence in BSTEM results. Additional improvements and capabilities will be presented along with example case studies.