Location: Watershed Physical Processes Research
Title: Advancements in predicting bank erosion processes with the Bank Stability and Toe Erosion Model (BSTEM)Author
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Submitted to: Joint Federal Interagency Sedimentation and Hydrologic Modeling
Publication Type: Proceedings Publication Acceptance Date: 4/1/2023 Publication Date: 5/8/2023 Citation: Ursic, M.E., Langendoen, E.J. 2023. Advancements in predicting bank erosion processes with the Bank Stability and Toe Erosion Model (BSTEM). Joint Federal Interagency Sedimentation and Hydrologic Modeling. 7 pp. In Proceedings of SEDHYD 2023. St. Louis, MO, May 8-12, 2023. Interpretive Summary: The USDA-ARS computer model Bank Stability and Toe Erosion Model (BSTEM) is widely used by federal agencies and private industry to evaluate the integrity of streambanks. Model usage was constraint by single-valued erosion-resistance parameters for each soil comprising the bank material. To account for the variability associated with testing, and potential spatial and temporal variability of bank soil erosion-resistance, ARS scientists in Oxford, MS, updated BSTEM to perform probabilistic analyses that use distributions of soil erosion-resistance properties as input. These distributions reflect the variability in soil erosion-resistance. The US Army Corps of Engineers, Sacramento District, is using the enhanced BSTEM to prioritize bank stabilization measures along reaches of the American and Sacramento Rivers to protect the City of Sacramento as authorized by the Water Resources Development Act of 2016. Technical Abstract: Modeling bank erosion is problematic not only because of limiting process 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. The ability to vary parameters within known ranges provides the user with quantified confidence in BSTEM results. The new BSTEM improvements and capabilities were demonstrated by assessing the retreat of a bank with a simple, bi-linear profile. |
