R: Simple degree day factor snow model

snow {hydromad}

R Documentation

Simple degree day factor snow model

Description

Simple degree day factor snow model coupled with IHACRES CMD soil moisture model.

Usage

snow.sim(DATA, Tmax, Tmin, kd, kf, rcap, Tmelt = Tmin,
         cr = 1, cs = 1, LSWE_0 = 0, ISWE_0 = 0,
         ..., return_state = FALSE)

Arguments

`DATA`	a `ts`-like object with named columns: `P` time series of areal rainfall depths, usually in mm. `E` time series of potential evapo-transpiration, or more typically, temperature as an indicator of this.
`Tmax`	temperature threshold for rain, all rain is liquid above this threshold.
`Tmin`	temperature threshold for rain, all rain is snow below this threshold.
`Tmelt`	temperature threshold for snowmelt and freezing in the snowpack.
`kd`	degree day factor for snowmelt.
`kf`	degree day factor for freezing.
`rcap`	retention parameter for liquid water capacity of snowpack.
`cr`	correction factor for rainfall.
`cs`	correction factor for snowfall.
`LSWE_0, ISWE_0`	initial values of state variables.
`...`	parameters for the IHACRES.CMD.model.
`return_state`	to return state variables as well as the effective rainfall.

Details

SWE snow water equivalent

ISWE water equivalent of ice in the snowpack

LSWE liquid water retained in the snowpack

Value

snow.sim returns the modelled time series of effective rainfall, or if return_state = TRUE, a multi-variate time series with named columns U (effective rainfall), SWE (snow water equivalent) and TF, as well as the CMD state variables.

Author(s)

Coded in R by Jarkko Koskela @tkk.fi 2010-02-26.

Converted to C by Felix Andrews felix@nfrac.org.

References

Kokkonen T., Jakeman A.J, Koivusalo.H, Norton.J.: COMPUTATIONAL METHODS FOR WATER RESOURCE ASSESSMENTS: AN EXERCISE KIT Educational Series on Modelling and Software iEMSs International Modelling and Software Society Available through www.iemss.org

Examples

## view default parameter ranges:
str(hydromad.options("snow"))

data(HydroTestData)
mod0 <- hydromad(HydroTestData, sma = "snow", routing = "expuh")
mod0

## simulate with some arbitrary parameter values
mod1 <- update(mod0, Tmax = 15, Tmin = 5, cr = 1, cs = 1, 
               kd = 3, kf = 1, rcap = 0.5,
               d = 200, f = 0.5, e = 0.1, tau_s = 10)

## plot results with state variables
testQ <- predict(mod1, return_state = TRUE)
xyplot(cbind(HydroTestData[,1:2], snow = testQ))

## show effect of increase/decrease in each parameter
parlist <- list(Tmax = c(10, 20), Tmin = c(0, 10),
                cr = c(0.5, 2), cs = c(0.5, 2),
                kd = c(2, 5), kf = c(0, 2), rcap = c(0, 1))
parsims <- mapply(val = parlist, nm = names(parlist),
  FUN = function(val, nm) {
    lopar <- min(val)
    hipar <- max(val)
    names(lopar) <- names(hipar) <- nm
    fitted(runlist(decrease = update(mod1, newpars = lopar),
                   increase = update(mod1, newpars = hipar)))
  }, SIMPLIFY = FALSE)

xyplot.list(parsims, superpose = TRUE, layout = c(1,NA),
            strip = FALSE, strip.left = TRUE,
            main = "Simple parameter perturbation example") +
  layer(panel.lines(fitted(mod1), col = "grey", lwd = 2))

[Package hydromad version 0.9-18 Index]