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Statistical Models of Ember Wash and Their Impact on Wildfire Area Growth

Bryan Quaife, Kevin Speer

Abstract

Wildfire spread is strongly influenced by the transport and ignition of embers. While long-range spotting driven by plume lofting has received significant attention, embers transported near the surface by turbulent winds can also influence fire propagation. We develop a stochastic model for near-surface ember transport, referred to as ember wash. The model represents ember motion as a sequence of short displacements analogous to saltation-like transport and incorporates a probabilistic ignition process that depends on ember survival during transport. This formulation leads to an exponential distribution of ember flight times. The model is implemented within a simplified fire spread model to examine burn patterns and growth dynamics. Simulations demonstrate that ember wash produces spread behavior that differs fundamentally from classical plume-driven spotting. These results suggest that ember wash provides a plausible mechanism for wildfire spread regimes that differ from those predicted by geometric or plume-driven spread models.

Statistical Models of Ember Wash and Their Impact on Wildfire Area Growth

Abstract

Wildfire spread is strongly influenced by the transport and ignition of embers. While long-range spotting driven by plume lofting has received significant attention, embers transported near the surface by turbulent winds can also influence fire propagation. We develop a stochastic model for near-surface ember transport, referred to as ember wash. The model represents ember motion as a sequence of short displacements analogous to saltation-like transport and incorporates a probabilistic ignition process that depends on ember survival during transport. This formulation leads to an exponential distribution of ember flight times. The model is implemented within a simplified fire spread model to examine burn patterns and growth dynamics. Simulations demonstrate that ember wash produces spread behavior that differs fundamentally from classical plume-driven spotting. These results suggest that ember wash provides a plausible mechanism for wildfire spread regimes that differ from those predicted by geometric or plume-driven spread models.

Paper Structure

This paper contains 7 sections, 11 equations, 8 figures.

Figures (8)

  • Figure 1: Infrared imagery of the 2017 NW OK Complex Fire near Woodward showing the intense fingering and complex spread behavior, associated with ember transport, wind and fuel variations, and river drainage slopes. The Complex Fire consisted of several major fires and burned over 834,000 acres. Wind speeds were over 30 mph (15 m/s) with gusts up to 50 mph (25 m/s) in places. Flame heights were reported in places at over 40 ft. Credit: OK Forest Service Public Information Map.
  • Figure 2: Embers transported along the ground in the surface mode of fire spread. Tree and roughness element wake interactions, particle hopping, and jumping effects are illustrated. Credit: Pexel/PublicDomain.
  • Figure 3: The burnt area of 15 wildfires in the Western USA. All areas are normalized according to their final size. The slope of the dashed black lines is 1, indicating a linear growth in the fire's area.
  • Figure 4: The Goodview fire exhibits the linear area scaling $A(t) \sim t$. Notice the lack of spotting.
  • Figure 5: The burnt area of seven wildfires in the western USA. All areas are normalized according to their final size. The slope of the black lines is 2, indicating a quadratic growth in the fire's area.
  • ...and 3 more figures