Testing a process-based fine fuel moisture model in two forest types

We test the ability of a recently developed process-based fine fuel moisture model to predict the surface and profile moisture content of litter fuels in two types of eucalytpus forest in Western Australia. The model predicts fuel moisture by modelling the energy and water budgets of the litter, intercepted precipitation, and the air spaces in the litter. The model equations are solved using an initial observation of fuel moisture and boundary conditions derived from basic weather observations. Model predictions are compared with twice-daily field observations made from October 1983 to March 1984. A novel two-stage method is used to assess model performance; the ability of the model to predict whether fuel is flammable is first assessed using contingency table analysis, and then the accuracy of predictions when the fuel is flammable is assessed. The model is capable of predicting the flammability of litter in both forest types with 80%–90% accuracy. Predictions of moisture content in flammable fuels are, on average, accurate to within 3% once the model has been calibrated against field observations. The model can be adapted to other forest types by specifying suitable parameters or by calibration against field observations.