Data Evaluation or Data Analysis for Fire Modeling
Development of equations for predicting fuel bed depth (called "bulk depth" herein) appropriate for modeling fire behavior in slash is described. Bulk depth (y) was correlated with the expected number of 1/4-to 1-inch-diameter particle intercepts per foot of vertical plane transect (x) by regressions of the form y = a\x. Values of "a" suitable for use in fire models were 0.767 for high-lead harvest debris, 0.940 for precommercial thinning of pines, 1.22 for precommercial thinning in several other western conifers, 0.877 for ground-lead harvest debris in pines, and 0.542 for ground-lead harvest in other species. Lopping of slash reduced average depth 17 percent for harvest debris and 3l percent for precommercial thinning debris. Correlation of high intercept depth (maximum height of sampled fuel particles)with bulk depth showed that the bulk depth can be well predicted using 64 percent of the more easily measured high intercept depth. Models for settling of slash, retention of foliage and fine twigs, and species mixing, useful in preparing data for fire models, are presented. Application of the models in a slash hazard appraisal computer program is illustrated.