metab_sim: Simulate dissolved oxygen data from input data

In USGS-R/streamMetabolizer: Models for Estimating Aquatic Photosynthesis and Respiration

Simulate dissolved oxygen data from input data

Description

Takes input data in the form of a sub-daily time series (data) of DO.sat, depth, temperature, and light, and a daily time series (data_daily) of GPP, ER, and K600 values, and turns these into simulated DO.obs. Either data or data_daily should specify a starting DO.obs value for each day; if in data, this takes the form of a DO.obs column with values on at least the first time point of each day (all other values are ignored), or if in data_daily, this takes the form of a DO.mod.1 column with one starting DO value per day.

Usage

metab_sim(
  specs = specs(mm_name("sim")),
  data = mm_data(solar.time, DO.obs, DO.sat, depth, temp.water, light, optional =
    "DO.obs"),
  data_daily = mm_data(date, discharge.daily, DO.mod.1, K600.daily, GPP.daily, Pmax,
    alpha, ER.daily, ER20, err.obs.sigma, err.obs.phi, err.proc.sigma, err.proc.phi,
    optional = "all"),
  info = NULL
)

Arguments

specs	a list of model specifications and parameters for a model. Although this may be specified manually (it's just a list), it is easier and safer to use specs to generate the list, because the set of required parameters and their defaults depends on the model given in the model_name argument to specs. The help file for specs lists the necessary parameters, describes them in detail, and gives default values.
data	data.frame (not a tbl_df) of input data at the temporal resolution of raw observations (unit-value). Columns must have the same names, units, and format as the default. The solar.time column must also have a timezone code ('tzone' attribute) of 'UTC'. See the 'Formatting data' section below for a full description.
data_daily	data.frame containing inputs with a daily timestep. See the 'Formatting data_daily' section below for a full description.
info	any information, in any format, that you would like to store within the metab_model object

Value

A metab_sim object containing the fitted model. This object can be inspected with the functions in the metab_model_interface.

See Also

Other metab_model: metab_Kmodel, metab_bayes, metab_mle, metab_night

Examples

## simulations with variation all at sub-daily scale
# prepare input data (DO used only to pick first DO of each day)
dat <- data_metab('3', res='15')
dat_daily <- data.frame(date=as.Date(paste0("2012-09-", 18:20)),
  GPP.daily=2, ER.daily=-3, K600.daily=21, stringsAsFactors=FALSE)

# define simulation parameters
mm <- metab_sim(
  specs(mm_name('sim'), err_obs_sigma=0.1, err_proc_sigma=2,
    GPP_daily=NULL, ER_daily=NULL, K600_daily=NULL),
  data=dat, data_daily=dat_daily)
# actual simulation happens during prediction - different each time
get_params(mm)
predict_metab(mm)
predict_DO(mm)[seq(1,50,by=10),]
predict_DO(mm)[seq(1,50,by=10),]

# or same each time if seed is set
mm@specs$sim_seed <- 236
predict_DO(mm)$DO.obs[seq(1,50,by=10)]
predict_DO(mm)$DO.obs[seq(1,50,by=10)]

# fancy GPP equation
dat_daily <- data.frame(date=as.Date(paste0("2012-09-", 18:20)),
  Pmax=8, alpha=0.01, ER.daily=-3, K600.daily=21, stringsAsFactors=FALSE)
mm <- metab_sim(
  specs(mm_name('sim', GPP_fun='satlight'), err_obs_sigma=0.1, err_proc_sigma=2,
    Pmax=NULL, alpha=NULL, ER_daily=NULL, K600_daily=NULL),
  data=dat, data_daily=dat_daily)
get_params(mm)
predict_metab(mm) # metab estimates are for data without errors
predict_DO(mm)[seq(1,50,by=10),]

## simulations with variation at both sub-daily and multi-day scales
sp <- specs(mm_name('sim', pool_K600='none'),
  K600_daily = function(n, ...) pmax(0, rnorm(n, 10, 3))) # n is available within sim models
mm <- metab(sp, dat)
get_params(mm)
predict_metab(mm)

## K~Q model
dat <- data_metab('10','15')
sp <- specs(mm_name('sim', pool_K600='binned'))
mm <- metab(sp, dat)
pars <- get_params(mm)
attr(pars, 'K600_eqn')

## Not run: 
plot_DO_preds(predict_DO(mm))
plot_DO_preds(mm)
library(ggplot2)

## End(Not run)

USGS-R/streamMetabolizer documentation built on Aug. 15, 2023, 7:50 a.m.