oneStation_DOPredict: Predict a time series of dissolved oxygen concentration

In mtalluto/NSmetabolism: N-Station Stream Metabolism Modelling

Description

Predict a time series of dissolved oxygen concentration

Usage

oneStation_DOPredict(
  initial,
  times,
  params,
  data,
  dt = 1,
  method = c("euler", "lsoda"),
  gpp = FALSE
)

Arguments

initial	initial dissolved oxygen concentration
times	The times at which to solve the system
params	a named vector of parameters; see details
data	a list of data for the ode; see details
dt	Time step for integration; only used if method == 'euler'
method	The integration method to use; default is euler
gpp	Logical, should GPP at each time step be returned as well?

Details

Light and temperature time series will be approximated using linear interpolation at the desired time steps

params must be a vector including the following named items:

• P1 $(W min g^-1 O_2)$ inverse of the slope of a photosynthesis–irradiance curve at low light intensity

• P2 $(m^2 min g^-1 O_2)$ inverse maximum photosynthesis rate; can be zero to assume GPP is linear with light intensity instead of saturating

• k600 coefficient of gas exchange for a gas with a Schmidt number of 600; (see kT())

• ER24_20 daily ecosystem respiration rate, standardized at 20 degrees C

data is a named list of (constant) data items, including the following:

• PAR 2-column data frame; first column is light, second is time of observation

• temp 2-column data frame; first column is temperature, second is time of observation

• P pressure, in atmospheres

• z Depth, in meters

Value

Time series of dissolved oxygen concentrations

mtalluto/NSmetabolism documentation built on May 3, 2021, 7:51 p.m.