cffdrs (version 1.8.20)

gfmc: Grass Fuel Moisture Code

Description

gfmc calculates both the moisture content of the surface of a fully cured matted grass layer and also an equivalent Grass Fuel Moisture Code (gfmc) (Wotton, 2009) to create a parallel with the hourly ffmc (see the fwi and hffmcfunctions). The calculation is based on hourly (or sub-hourly) weather observations of temperature, relative humidity, wind speed, rainfall, and solar radiation. The user must also estimate an initial value of the gfmc for the layer. This function could be used for either one weather station or multiple weather stations.

Usage

gfmc(input, GFMCold=85,batch=TRUE,time.step=1,roFL=0.3, out="GFMCandMC")

Value

gfmc returns GFMC and moisture content (MC) values collectively (default) or separately.

Arguments

input

A dataframe containing input variables of daily noon weather observations. Variable names have to be the same as in the following list, but they are case insensitive. The order in which the input variables are entered is not important.

temp	(required)	Temperature (centigrade)
rh	(required)	Relative humidity (%)
ws	(required)	10-m height wind speed (km/h)
prec	(required)	1-hour rainfall (mm)
isol	(required)	Solar radiation (kW/m^2)
mon	(recommended)	Month of the year (integer 1-12)
day	(optional)	Day of the month (integer)

GFMCold

Previous value of GFMC (i.e. value calculated at the previous time step)[default is 85 (which corresponds to a moisture content of about 16%)]. On the first calculation this is the estimate of the GFMC value at the start of the time step. The GFMCold argument can accept a single initial value for multiple weather stations, and also accept a vector of initial values for multiple weather stations. NOTE: this input represents the CODE value, not a direct moisture content value. The CODE values in the Canadian FWI System increase within decreasing moisture content. To roughly convert a moisture content value to a CODE value on the FF-scale (used in the FWI Systems FFMC) use GFMCold =101-gmc (where gmc is moisture content in %)

time.step

Time step (hour) [default 1 hour]

roFL

The nominal fuel load of the fine fuel layer, default is 0.3 kg/m^2

batch

Whether the computation is iterative or single step, default is TRUE. When batch=TRUE, the function will calculate hourly or sub-hourly GFMC for one weather station over a period of time iteratively. If multiple weather stations are processed, an additional "id" column is required in the input to label different stations, and the data needs to be sorted by time sequence and "id". If batch=FALSE, the function calculates only one time step (1 hour) base on either the previous hourly GFMC or the initial start value.

out

Output format, default is "GFMCandMC", which contains both GFMC and moisture content (MC) in a data.frame format. Other choices include: "GFMC", "MC", and "ALL", which include both the input and GFMC and MC.

Author

Xianli Wang, Mike Wotton, Alan Cantin, and Mike Flannigan

Details

The Canadian Forest Fire Danger Rating System (CFFDRS) is used throughout Canada, and in a number of countries throughout the world, for estimating fire potential in wildland fuels. This new Grass Fuel Moisture Code (GFMC) is an addition (Wotton 2009) to the CFFDRS and retains the structure of that System's hourly Fine Fuel Moisture Code (HFFMC) (Van Wagner 1977). It tracks moisture content in the top 5 cm of a fully-cured and fully-matted layer of grass and thus is representative of typical after winter conditions in areas that receive snowfall. This new moisture calculation method outputs both the actual moisture content of the layer and also the transformed moisture Code value using the FFMC's FF-scale. In the CFFDRS the moisture codes are in fact relatively simple transformations of actual moisture content such that decreasing moisture content (increasing dryness) is indicated by an increasing Code value. This moisture calculation uses the same input weather observations as the hourly FFMC, but also requires an estimate of solar radiation incident on the fuel.

References

Wotton, B.M. 2009. A grass moisture model for the Canadian Forest Fire Danger Rating System. In: Proceedings 8th Fire and Forest Meteorology Symposium, Kalispell, MT Oct 13-15, 2009. Paper 3-2. https://ams.confex.com/ams/pdfpapers/155930.pdf

Van Wagner, C.E. 1977. A method of computing fine fuel moisture content throughout the diurnal cycle. Environment Canada, Canadian Forestry Service, Petawawa Forest Experiment Station, Chalk River, Ontario. Information Report PS-X-69. https://cfs.nrcan.gc.ca/pubwarehouse/pdfs/25591.pdf

See Also

fwi, hffmc

Examples

library(cffdrs)
#load the test data
data("test_gfmc")
# show the data format:
head(test_gfmc)
#     yr mon day hr temp   rh   ws prec  isol
# 1 2006   5  17 10 15.8 54.6  5.0    0 0.340
# 2 2006   5  17 11 16.3 52.9  5.0    0 0.380
# 3 2006   5  17 12 18.8 45.1  5.0    0 0.626
# 4 2006   5  17 13 20.4 40.8  9.5    0 0.656
# 5 2006   5  17 14 20.1 41.7  8.7    0 0.657
# 6 2006   5  17 15 18.6 45.8 13.5    0 0.629
# (1) gfmc default: 
# Re-order the data by year, month, day, and hour:
dat<-test_gfmc[with(test_gfmc,order(yr,mon,day,hr)),]
# Because the test data has 24 hours input variables 
# it is possible to calculate the hourly GFMC continuously 
# through multiple days(with the default initial GFMCold=85):
dat$gfmc_default<-gfmc(dat) 
# two variables will be added to the input, GFMC and MC
head(dat)
# (2) For multiple weather stations:
# One time step (1 hour) with default initial value:
  foo<-gfmc(dat,batch=FALSE)
# Chronical hourly GFMC with only one initial 
# value (GFMCold=85), but multiple weather stations. 
# Note: data is ordered by date/time and the station id. Subset 
# the data by keeping only the first 10 hours of observations 
# each day:
dat1<-subset(dat,hr%in%c(0:9))
#assuming observations were from the same day but with 
#9 different weather stations:
dat1$day<-NULL
dat1<-dat1[with(dat1,order(yr,mon,hr)),]
dat1$id<-rep(1:8,nrow(dat1)/8)
#check the data:
head(dat1)
# Calculate GFMC for multiple stations:
dat1$gfmc01<-gfmc(dat1,batch=TRUE)
# We can provide multiple initial GFMC (GFMCold) as a vector:   
dat1$gfmc02<- gfmc(dat1,GFMCold = sample(70:100,8, replace=TRUE),batch=TRUE)
# (3)output argument
## include all inputs and outputs:
dat0<-dat[with(dat,order(yr,mon,day,hr)),]
foo<-gfmc(dat,out="ALL")
## subhourly time step:
gfmc(dat0,time.step=1.5)