Predicting fire severity using surface fuels and moisture

摘要: Fire severity classifications have been used extensively in fire management over the last 30 years to describe specific environmental or ecological impacts of on fuels, vegetation, wildlife, and soils recently burned areas. New need be more objective, predictive, ultimately useful planning. Our objectives were (1) quantify relationships between fuel loading moisture characteristics surface fuels temperature energy produced during combustion, (2) produce a classification that summarized these into unique, realistic classes severity. Using computer simulation, we created 115,280 synthetic beds with diverse compositions conditions them using simulation First Order Effects Model (FOFEM). average intensity, residence time, total consumed, depth soil heating, top 1 cm soil, nine-group separated based first second intensity third consumed. Fuel correctly placed nine 98% time subsets beds.