Global sensitivity analysis and scale effects of a fire propagation model used over Mediterranean shrublands

A Global Sensitivity Analysis (GSA) and an analysis of scale effects have been carried out over the equations given by Rothermel (1972), with some additional modifications. Data mainly derived from Mediterranean shrublands and a spatially close meteorological station have been used to derive probability distribution functions for the variables involved. In spite of the abundant non-linearities contained in the equations studied, scale effects found have been relatively unimportant, thus supporting the current usage of spatial averages (i.e. fuel models) in spatially distributed models based on the Rothermel equations. On the other hand, the results of the GSA clearly showed the negligible effect of the variability of three of the model variables (the low heat content, the particle density and the mineral content) on the output values. However, all other input variables had some noticeable effect over the variability of the output, and they cannot be ignored if an optimal use of the model is desired. Finally, caution is recommended if results have to be extrapolated to other types of vegetation or climate.

[1]  F. Albini.  A Model for Fire Spread in Wildland Fuels by-Radiation† , 1985 .

[2]  M. E. Alexander,et al.  Canadian Forest Fire Danger Rating System: An Overview , 1989 .

[3]  H. Anderson.  Aids to Determining Fuel Models for Estimating Fire Behavior , 1982 .

[4]  Paolo Zannetti,et al.  Computer Techniques in Environmental Studies , 1899 .

[5]  Terry Andres,et al.  Sensitivity analysis of model output: an investigation of new techniques , 1993 .

[6]  Ilya M. Sobol,et al.  Sensitivity Estimates for Nonlinear Mathematical Models , 1993 .

[7]  T. Beer,et al.  Bushfire rate‐of‐spread forecasting: Deterministic and statistical approaches to fire modelling , 1991 .

[8]  S. Ferson,et al.  Propagating Uncertainty in Ecological Risk Analysis Using Interval and Fuzzy Arithmetic , 1992 .

[9]  F. Albini.  Estimating Wildfire Behavior and Effects , 1976 .

[10]  William H. Frandsen,et al.  Fire spread through porous fuels from the conservation of energy , 1971 .

[11]  George L. W. Perry,et al.  Current approaches to modelling the spread of wildland fire: a review , 1998 .

[12]  Josep Piñol,et al.  Estimating live fine fuels moisture content using meteorologically-based indices , 2001 .

[13]  R. O. Weber.  Thermal Theory for Determining the Burning Velocity of a Laminar Flame, Using the Inflection Point in the Temperature Profile , 1989 .

[14]  L. A. Salazar.  Sensitivity of fire behavior simulations to fuel model variations , 1985 .

[15]  Wr Catchpole,et al.  Modelling Moisture Damping for Fire Spread in a Mixture of Live and Dead Fuels , 1991 .

[16]  K. Shuler,et al.  Study of the sensitivity of coupled reaction systems to uncertainties in rate coefficients. III. Analysis of the approximations , 1975 .

[17]  J. Hájek,et al.  Asymptotic Normality of Simple Linear Rank Statistics Under Alternatives II , 1968 .

[18]  A. Saltelli,et al.  A quantitative model-independent method for global sensitivity analysis of model output , 1999 .

[19]  B. Efron,et al.  The Jackknife Estimate of Variance , 1981 .

[20]  M. Finney.  FARSITE : Fire Area Simulator : model development and evaluation , 1998 .

[21]  D. Hamby.  A review of techniques for parameter sensitivity analysis of environmental models , 1994, Environmental monitoring and assessment.

[22]  Jon C. Helton,et al.  Uncertainty and sensitivity analysis techniques for use in performance assessment for radioactive waste disposal , 1993 .

[23]  D. G. Green.  Shapes of simulated fires in discrete fuels , 1983 .

[24]  K. Rutchey,et al.  Fire simulations in the Everglades Landscape using parallel programming , 1996 .

[25]  N. Cheney,et al.  The Influence of Fuel, Weather and Fire Shape Variables on Fire-Spread in Grasslands , 1993 .

[26]  A. Saltelli,et al.  Importance measures in global sensitivity analysis of nonlinear models , 1996 .

[27]  P. Andrews.  BEHAVE : Fire Behavior Prediction and Fuel Modeling System - BURN Subsystem, Part 1 , 1986 .

[28]  E. Pook,et al.  Variation of Live and Dead Fine Fuel Moisture in Pinus radiata Plantations of the Australian-Capital-Territory , 1993 .

[29]  L. M. E. Martín,et al.  Inflamabilidad y energía de las especies de sotobosque , 1989 .

[30]  Emanuel Parzen,et al.  Stochastic Processes , 1962 .