Fit a hydromad model using DDS (Dynamically Dimensioned Search) algorithm.

fitByDDS(
  MODEL,
  objective = hydromad.getOption("objective"),
  control = hydromad.getOption("dds.control"),
  save = NULL
)

Arguments

MODEL: a model specification created by hydromad. It should not be fully specified, i.e one or more parameters should be defined by ranges of values rather than exact values.
objective: objective function to maximise, given as a function(Q, X, ...). See objFunVal.
control: settings for the DDS algorithm. These are the arguments to optim_dds.
save: Optional function(pars,objective value,model) that will be called for every model evaluation, for example to save every model run.

Value

the best model from those sampled, according to the given objective function. Also, these extra elements are inserted:

fit.result: the result from SCEoptim.
objective: the objective function used.
funevals: total number of evaluations of the model simulation function.
timing: timing vector as returned by system.time.

Details

This function depends on the ppso package, available from http://www.rforge.net/ppso/. For alternative optimisation algorithms, consider fitBySCE.

References

Tolson, B. A., and C. A. Shoemaker (2007) Dynamically dimensioned search algorithm for computationally efficient watershed model calibration, Water Resour. Res., 43, W01413, doi:10.1029/2005WR004723. http://www.agu.org/journals/wr/wr0701/2005WR004723/

Author

Joseph Guillaume josephguillaume@gmail.com

Examples


data(Cotter)
x <- Cotter[1:1000]

## IHACRES CWI model with power law unit hydrograph
modx <- hydromad(x, sma = "cwi", routing = "powuh")
modx
#> 
#> Hydromad model with "cwi" SMA and "powuh" routing:
#> Start = 1966-05-01, End = 1969-01-24
#> 
#> SMA Parameters:
#>       lower upper     
#> tw        0   100     
#> f         0     8     
#> scale    NA    NA     
#> l         0     0 (==)
#> p         1     1 (==)
#> t_ref    20    20 (==)
#> Routing Parameters:
#>   lower upper  
#> a  0.01    60  
#> b  0.50     3  
#> c  0.50     2  

## run with cut-down settings (for a speedy example only!)
foo <- fitByDDS(modx, control = list(
  max_number_function_calls = 100,
  logfile = NULL,
  projectfile = NULL,
  load_projectfile = "no"
))
#> Loading required namespace: ppso
#> Warning: Package lhs not installed, lhs_init disabled

summary(foo)
#> 
#> Call:
#> hydromad(DATA = x, sma = "cwi", routing = "powuh", a = 6.04208, 
#>     b = 1.38496, c = 1.78048, tw = 99.7441, f = 4.55294, scale = 0.00127934)
#> 
#> Time steps: 900 (0 missing).
#> Runoff ratio (Q/P): (0.7028 / 2.285) = 0.3075
#> rel bias: -4.716e-17
#> r squared: 0.7543
#> r sq sqrt: 0.8364
#> r sq log: 0.8356
#> 
#> For definitions see ?hydromad.stats
#> 

## return value from DDS:
str(foo$fit.result)
#> List of 4
#>  $ value         : num -0.854
#>  $ par           : num [1:5(1d)] 6.04 1.38 1.78 99.74 4.55
#>   ..- attr(*, "dimnames")=List of 1
#>   .. ..$ : chr [1:5] "a" "b" "c" "tw" ...
#>  $ function_calls: num 100
#>  $ break_flag    : chr "max number of function calls reached"