摘要

We describe a model for predicting the moisture content of standardized fuel sticks. Compared to the previously published "Nelson model," which is the basis for the model currently used by agencies involved with fire management, our model's treatment of moisture diffusion, heat conduction, precipitation interception, and evaporation/sorption processes is simplified while its treatment of radiation transfer is more sophisticated. Two independent datasets were used to calibrate and evaluate the model. The optimized models were able to predict 78-94% of the variance in the calibration observations with absolute mean biases ranging from 0.04% to 0.38% fuel moisture content. When evaluated using both an independent time period and an independent dataset, the explained variance decreased slightly, ranging from 72 to 94%, and the model bias increased with absolute mean biases ranging from 0.29% to 2.48%. The best results were achieved when the model was forced with observations taken at the same height and location as the fuel moisture sticks. Model skill was reduced for higher moisture levels. Despite the simplified approach, our model improved on the skill achieved by the Nelson model and has additional features that allow for a more realistic treatment of canopy coverage and changes in sky conditions.

  • 出版日期2017-4-15