Description Usage Arguments Value Author(s) References See Also Examples

This function offers the user the possibility to perturb inputs to Rothermel's (1972) fire behavior model and propagate the uncertainty to the resulting estimate of Rate of spread [m/min] by means of Monte Carlo iterative sampling. Random values are extracted from Gaussian distributions with mean = observed values, and spread defined by a custom ratio of standard deviation to the mean defined by the user.

1 2 3 | ```
rosunc (modeltype, w, s, delta, mx.dead, h, m, u, slope,
sdu = 0, sdm = 0, sds = 0, sdw = 0, sdd = 0,
nsim = 1000)
``` |

`modeltype` |
S(tatic), D(ynamic) |

`w` |
a vector of fuel load [t/ha] for fuel classes 1-hour, 10-hour, 100-hour, live herbs and live woody, respectively (5 values; 0 if fuel class is absent). |

`s` |
a vector of surface-to-volume ratio [m2/m3] for fuel classes 1-hour, 10-hour, 100-hour, live herbs and live woody, respectively (5 values; 0 if fuel class is absent). |

`delta` |
atomic vector, fuel bed depth [cm] |

`mx.dead` |
atomic vector, dead fuel moisture of extinction [percent] |

`h` |
a vector of heat content [kJ/kg] for fuel classes 1-hour, 10-hour, 100-hour, live herbs and live woody, respectively (5 values; 0 if fuel class is absent). |

`m` |
a vector of percent moisture on a dry weight basis [percent] for fuel classes 1-hour, 10-hour, 100-hour, live herbs and live woody, respectively (5 values; 0 if fuel class is absent). |

`u` |
atomic vector, midflame windspeed [km/h] |

`slope` |
atomic vector, site slope [percent] |

`sdu` |
coefficient of variation for wind speed (ratio of standard deviation to the mean; default = no perturbation) |

`sdm` |
coefficient of variation for fuel moistures (ratio of standard deviation to the mean; default = no perturbation) |

`sds` |
coefficient of variation for slope (ratio of standard deviation to the mean; default = no perturbation) |

`sdw` |
coefficient of variation for fuel loadings (ratio of standard deviation to the mean; default = no perturbation) |

`sdd` |
coefficient of variation for fuel bed depth (ratio of standard deviation to the mean; default = no perturbation) |

`nsim` |
number of Monte Carlo iterations (default =1000) |

A vector of predicted ROS [m/min] from Monte Carlo simulations.

Giorgio Vacchiano, Davide Ascoli (DISAFA, University of Torino, Italy)

Cruz M. G. (2010). Monte Carlo-based ensemble method for prediction of grassland fire spread. International Journal of Wildland Fire 19: 521-530.

Jimenez E., Hussaini M. Y., Goodrick S. (2008). Quantifying parametric uncertainty in the Rothermel model. International Journal of Wildland Fire, 17: 638-649.

Rothermel, R. C. (1972). A mathematical model for fire spread predictions in wildland fires. Research Paper INT-115. Ogden, UT: US Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | ```
data ("firexp")
varnames <- names (firexp)
# select only one observation and create a numeric vector for function input
firexp <- as.numeric (firexp [5,])
names (firexp) <- varnames
pred <- rosunc (
modeltype = "D",
w = firexp [1:5],
s = firexp [6:10],
delta = firexp ["Fuel_Bed_Depth"],
mx.dead = firexp ["Mx_dead"],
h = firexp [13:17],
m = firexp [18:22],
u = firexp ["u"],
slope = firexp ["slope"],
sdm = 0.3,
nsim = 100)
summary (pred)
# Figure
hist (pred,
xlab = "ROS [m/min]",
freq = FALSE,
xlim = c (0, max (pred)),
breaks = 20,
main = "")
lines (density (pred), lty=2, lwd=2)
abline (v = firexp ["ros"],col = "red")
text (firexp ["ros"],
max (density (pred)$y),
labels = "obs",
pos = 4)
``` |

```
Loading required package: GA
Loading required package: foreach
Loading required package: iterators
Package 'GA' version 3.2
Type 'citation("GA")' for citing this R package in publications.
Attaching package: 'GA'
The following object is masked from 'package:utils':
de
Loading required package: ftsa
Loading required package: forecast
Loading required package: rainbow
Loading required package: MASS
Loading required package: pcaPP
Loading required package: sde
Loading required package: stats4
Loading required package: fda
Loading required package: splines
Loading required package: Matrix
Attaching package: 'fda'
The following object is masked from 'package:forecast':
fourier
The following object is masked from 'package:graphics':
matplot
Loading required package: zoo
Attaching package: 'zoo'
The following objects are masked from 'package:base':
as.Date, as.Date.numeric
sde 2.0.15
Companion package to the book
'Simulation and Inference for Stochastic Differential Equations With R Examples'
Iacus, Springer NY, (2008)
To check the errata corrige of the book, type vignette("sde.errata")
Attaching package: 'ftsa'
The following objects are masked from 'package:stats':
sd, var
Min. 1st Qu. Median Mean 3rd Qu. Max.
7.26 10.72 12.48 13.23 14.54 30.96
```

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