Post-Wildfire Numerical Modeling for Flood Risk Management

The number and intensity of large wildfires in is a growing concern in the United States.  Over the past decade, the National Interagency Fire Centre (NSTC, 2015) reported increases of large fires in every western state in the arid and semi-arid western U.S.  Wildfires, remove vegetation, reduce organic soil horizons to ash, extirpate microbial communities, alters soil structure, and potential development of hydrophobic soils.  These processes all increase water and sediment runoff. Post-wildfire environments can cause a spectrum of hydrologic and sedimentation responses ranging from no response to catastrophic floods and deadly debris flows. Numerical modellers have developed a variety of Newtonian and non-Newtonian shallow-water algorithms to simulate each of these physical processes – making it difficult to model the range of post-wildfire flood conditions and understand model assumption and limitations. This makes a modular non-Newtonian computation library advantageous. This work presents a flexible, numerical model, library framework ‘DebrisLib’ to simulate large-scale, post-wildfire non-Newtonian flows using diverse shallow-water parents code architecture. This work presents the non-Newtonian model framework effectiveness by linking it with two different modelling frameworks, specifically the diffusive-wave one-dimensional and two-dimensional Hydrologic Engineering Center River Analysis System (HEC-RAS), and shallow-water two-dimensional Adaptive Hydraulics (AdH) numerical models. The model library was verified and validated using three flume experiments for mud flows, hyperconcentrated flows, and debris flows under steady and unsteady flow conditions. Additionally the shallow-water model library framework linked with the 1D Hydrologic Engineering Centre Hydrologic Modelling System (HEC-HMS) successfully predicted the 2018 post-wildfire flooding and debris flows following the 2017 Thomas Fire near Santa Barbara, California.