A wildland fire model with data assimilation

A wildfire model is formulated based on balance equations for energy and fuel, where the fuel loss due to combustion corresponds to the fuel reaction rate. The resulting coupled partial differential equations have coefficients which can be approximated from prior measurements of wildfires. An Ensemble Kalman Filter technique is then used to assimilate temperatures measured at selected points into running wildfire simulations. The assimilation technique is able to modify the simulations to track the measurements correctly even if the simulations were started with an erroneous ignition location that is quite far away from the correct one. Key words: wildfire; combustion; ensemble Kalman filter; parameter identification; data assimilation; reaction-diffusion equations; partial differential equations; sensors

• Type: Journal
• Year: 2008
• Where: MCS
• Authors: Jan Mandel, Lynn S. Bennethum, Jonathan D. Beezley, Janice L. Coen, Craig C. Douglas, Minjeong Kim, Anthony Vodacek
• Keywords: Kalman Filter, Kalman Filter Technique, MCS 2008, Pattern Recognition, Wildfire