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This paper presents the first complete process-based model for fuel moisture in the litter layer. The model predicts fuel moisture by modelling the energy and water budgets of the litter, intercepted precipitation, and air spaces in the litter. The model was tested against measurements of fuel moisture from two sets of field observations, one made in Eucalyptus mallee-heath under dry conditions and the other during a rainy period in Eucalyptus obliqua forest. The model correctly predicted minimum and maximum fuel moisture content and the timing of minima and maxima in the mallee-heath. Under wet conditions, wetting and drying of the litter profile were correctly predicted but wetting of the surface litter was over-predicted. The structure of the model and the dependence of predictions on model parameters were examined using sensitivity and parameter estimation studies. The results indicated that it should be possible to adapt the model to any forest type by specifying a limited number of parameters. A need for further experimental research on the wetting of litter during rain was also identified.
Stuart Matthews (Wed,) studied this question.