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Modeling and risk assessment for soil temperatures beneath prescribed forest firesAuthor(s): Haiganoush K. Preisler; Sally M. Haase; Stephen S. Sackett
Source: Environmental and Ecological Statistics. 7: 239-254
Publication Series: Scientific Journal (JRNL)
Station: Pacific Southwest Research Station
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DescriptionPrescribed fire is a management tool used by wildland resource management organizations in many ecosystems to reduce hazardous fuels and to achieve a host of other objectives. To study the effects of fire in naturally accumulating fuel conditions, the ambient soil temperature is monitored beneath prescribed burns. In this study we developed a stochastic model for temperature profiles (values at 15 minute intervals) recorded at four depths beneath the soil during a large prescribed burn study. The model was used to assess the temporal fit of the data to particular solutions of the heat equation. We used a random effects model to assess the effects of observed site characteristics on maximum temperatures and to estimate risks of temperatures exceeding critical levels in future similar prescribed fires. Contour plots of estimated risks of temperatures exceeding 60°C for a range of fuel levels and soil depths indicated high risks of occurrence, especially when the moisture levels are low. However, the natural variability among sites seems to be large, even after controlling fuel and moisture levels, resulting in large standard errors of predicted risks.
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CitationPreisler, H.K.; Haase, S.M.; Sackett, S.S. 2000. Modeling and risk assessment for soil temperatures beneath prescribed forest fires. Environmental and Ecological Statistics. 7: 239-254.
Keywordsambient temperature, autoregressive models, functional data, heat equation, nonlinear regression, random effects
- Lethal soil temperatures during burning of masticated forest residues
- Performance of high temperature heat flux plates and soil moisture probes during controlled surface fires
- Long term consequences of a prescribed burn and slash mastication to soil moisture and CO2
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