Prototype Scale Evaluation of Non-Newtonian Algorithms in HEC-RAS: Mud and Debris Flow Case Studies of Santa Barbara and Brumadinho

• Published in: Geosciences (Basel) Vol. 12; no. 3; p. 134
• Main Authors: Gibson, Stanford, Moura, Leonardo Zandonadi, Ackerman, Cameron, Ortman, Nikolas, Amorim, Renato, Floyd, Ian, Eom, Moosub, Creech, Calvin, Sánchez, Alejandro
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.03.2022
• Subjects: Algorithms; Alluvial channels; Alluvial plains; Aquatic reptiles; Brumadinho; Case studies; Catastrophic failure analysis; Dam failure; Dams; Debris flow; Detritus; Earth science; Environmental risk; Estimates; Flood forecasting; Flood risk; Flooding; Floods; HEC-RAS; Hydraulics; Hydrology; Methods; Mine tailings; Mine wastes; Mud; mudflow; non-Newtonian; Prototypes; Risk; Santa Barbara; Solid phases; Stochasticity; Tailings; Watersheds; Wildfires; Brazil; United States > US; Santa Barbara California
• ISSN: 2076-3263; 2076-3263
• DOI: 10.3390/geosciences12030134

The Santa Barbara post-wildfire debris flows and the Brumadinho tailing-dam failure were two of the most catastrophic flood events of the late 2010s. Both these events carried so much solid-phase material, that classic, clear-water, flood risk approaches cannot replicate them, or forecast other events like them. This case study applied the new non-Newtonian features in HEC-RAS 6.1 to these two events, testing the most widely used flood risk model on the two most common mud and debris flow hazards (post-wildfire floods and mine tailing dam failures). HEC-RAS reproduced the inundation boundaries and the event timing (where available) for both events. The ratio between the largest debris flow clasts and the channel size, parametric trade-offs, the “convex” alluvial plain topography, and the stochasticity introduced by urban infrastructure made the Santa Barbara modeling more difficult and less precise than Brumadinho. Despite these challenges, the results provide prototype scale validation and verification of these new tools in this widely applied flood risk model.