system-class {ecosim}

Class "system"

Description

This class represents a system consisting of linked reactors, substances/organisms in the reactors and transformation processes.

Once a model is described by an object of the class system (system-class), simulations can be performed using the member function

calcres,

This function integrates the system of ordinary differential equations numerically using the function ode of the package deSolve and produces time series of the volumes and substance and organisms concentrations as a R matrix. The results can be visualized with arbitrary R functions or a summary of all results can be produced with the function

plotres.

Objects from the Class

Objects can be created by calls of the form new("system", ...).

Slots

name:

Character string specifying the name of the system.

reactors:

List of reactors that build the system.

links:

List of links that connect the reactors.

cond:

List of expressions that specify global environmental conditions to which all reactrs are exposed.

param:

List of model parameters in the form of numerical values or lists of vectors for x and y values describing a realization of a time-dependent parameter.

t.out:

Numeric vector of points in time at which output should be calculated.

Methods

calcres

Calculates simulation results, see calcres

Author(s)

Peter Reichert <[e-mail]>

References

Omlin, M., Reichert, P. and Forster, R., Biogeochemical model of lake Zurich: Model equations and results, Ecological Modelling 141(1-3), 77-103, 2001.

Reichert, P., Borchardt, D., Henze, M., Rauch, W., Shanahan, P., Somlyody, L. and Vanrolleghem, P., River Water Quality Model no. 1 (RWQM1): II. Biochemical process equations, Water Sci. Tech. 43(5), 11-30, 2001.

Reichert, P. and Schuwirth, N., A generic framework for deriving process stoichiometry in environmental models, Environmental Modelling & Software, 25, 1241-1251, 2010.

Soetaert, K., Petzoldt, T., and Woodrow Setzer, R. Solving differential equations in R: Package deSolve. Journal of Statistical Software, 33(9), 2010.

Soetaert, K., Cash, J., and Mazzia, F. Solving Differential Equations in R. Springer, Heidelberg, Germany. 2012.

See Also

process-class, reactor-class, link-class, calcres, plotres.

Examples

# Definition of parameters:
# =========================

param    <- list(k.gro.ALG   = 1,        # 1/d
                 k.gro.ZOO   = 0.8,      # m3/gDM/d
                 k.death.ALG = 0.4,      # 1/d
                 k.death.ZOO = 0.08,     # 1/d
                 K.HPO4      = 0.002,    # gP/m3
                 Y.ZOO       = 0.2,      # gDM/gDM
                 alpha.P.ALG = 0.002,    # gP/gDM
                 A           = 8.5e+006, # m2
                 h.epi       = 4,        # m
                 Q.in        = 4,        # m3/s
                 C.ALG.ini   = 0.05,     # gDM/m3
                 C.ZOO.ini   = 0.1,      # gDM/m3
                 C.HPO4.ini  = 0.02,     # gP/m3
                 C.HPO4.in   = 0.04)     # gP/m3             

# Definition of transformation processes:
# =======================================

# Growth of algae:
# ----------------

gro.ALG   <- new(Class  = "process",
                 name   = "Growth of algae",
                 rate   = expression(k.gro.ALG
                                     *C.HPO4/(K.HPO4+C.HPO4)
                                     *C.ALG),
                 stoich = list(C.ALG  = expression(1),              # gDM/gDM
                               C.HPO4 = expression(-alpha.P.ALG)))  # gP/gDM

# Death of algae:
# ---------------

death.ALG <- new(Class = "process",
                 name   = "Death of algae",
                 rate   = expression(k.death.ALG*C.ALG),
                 stoich = list(C.ALG  = expression(-1)))            # gDM/gDM

# Growth of zooplankton:
# ----------------------

gro.ZOO   <- new(Class  = "process",
                 name   = "Growth of zooplankton",
                 rate   = expression(k.gro.ZOO
                                     *C.ALG
                                     *C.ZOO),
                 stoich = list(C.ZOO  = expression(1),              # gDM/gDM
                               C.ALG  = expression(-1/Y.ZOO)))      # gP/gDM

# Death of zooplankton:
# ---------------------

death.ZOO <- new(Class  = "process",
                 name   = "Death of zooplankton",
                 rate   = expression(k.death.ZOO*C.ZOO),
                 stoich = list(C.ZOO  = expression(-1)))            # gDM/gDM

# Definition of reactor:
# ======================

# Epilimnion:
# -----------

epilimnion <- 
   new(Class            = "reactor",
       name             = "Epilimnion",
       volume.ini       = expression(A*h.epi),
       conc.pervol.ini  = list(C.HPO4 = expression(C.HPO4.ini),     # gP/m3
                               C.ALG  = expression(C.ALG.ini),      # gDM/m3
                               C.ZOO  = expression(C.ZOO.ini)),     # gDM/m3
       inflow           = expression(Q.in*86400),                   # m3/d
       inflow.conc      = list(C.HPO4 = expression(C.HPO4.in),
                               C.ALG  = 0,
                               C.ZOO  = 0),
       outflow          = expression(Q.in*86400),
       processes        = list(gro.ALG,death.ALG,gro.ZOO,death.ZOO))

# Definition of system:
# =====================

# Lake system:
# ------------

system <- new(Class    = "system",
              name     = "Lake",
              reactors = list(epilimnion),
              param    = param,
              t.out    = seq(0,365,by=1))