Fuels, consumption, and emissions estimated for two stand-replacing prescribed crown fires in Utah

Abstract:

The JFSP-funded Western Wildfire Campaign (WWC) of the Fire And Smoke Modeling Evaluation Experiment (FASMEE) is characterizing source fuels burned on 2018 and 2019 western wildfires, selected for airborne emissions sampling by two NSF-funded projects (WE-CAN and BB-FLUX) in 2018 and by the NOAA/NASA-funded FIREX-AQ project in 2019. Emissions were sampled by airborne instruments mounted on the C-130 (WE-CAN), King Air (BB-FLUX), and DC-8 (FIREX-AQ) aircrafts that flew through the smoke plumes. Our objective was to predict fuel loads by fuel type both pre- and post-fire and to estimate consumption to reduce these large sources of uncertainty in emissions, across a broad range of fuel types in the western USA. Two of the ten fires sampled as part of the WWC were not wildfires but prescribed crown fires that were ignited in Fishlake National Forest, south central Utah, where the heaviest surface fuel loads were observed from among any of the ten fires sampled. Prescribed fires provided the opportunity to safely sample fuels on the ground not just post-fire, but pre-fire, in co-located field plots; this further reduces uncertainties by controlling for high spatial heterogeneity in the fuel conditions sampled. We associated pre- and post-fire fuel loadings with pre- and post-fire airborne lidar datasets, such that we could develop independent predictive models to estimate overstory and understory (including surface) fuel loads across the entire extent of these prescribed crown fires, which were 982 ha and 327 ha and burned in the spring and fall, respectively. Within the spatial footprint of the sample plots, the point cloud data were summarized into height and density metrics that were used to train predictive Random Forests models, which were subsequently applied to the same metrics gridded across the landscape at similar resolution. The resulting pre- and post-fire fuel maps were subsequently differenced to estimate consumption, and these estimates were summarized by fuel bed type as defined by the Fuel Characteristics Classification System (FCCS). Finally, emissions were estimated using the CONSUME model customized for these fuel bed types as informed by the in situ field and airborne lidar measurements.