class Gday(object):
""" The G'DAY (Generic Decomposition And Yield) model.
GDAY simulates C, N and water cycling between the plant and the soil. The
model is structured into three plant pools (foliage, wood and fine roots),
four litter pools (above/below metabolic and structural litter) and three
soil organic matter (SOM) pools with varying turnover rates (active, slow
and passive). An adapted implementation of the CENTURY model simulates soil
carbon and nutrient dynamics. There is an additional simple soil water
balance module which can be used to limit growth. Model pools can be thought
of as buckets as they don't have dimensions.
References:
----------
* Comins, H. N. and McMurtrie, R. E. (1993) Ecological Applications, 3,
666-681.
* Medlyn, B. E. et al (2000) Canadian Journal of Forest Research, 30,
873-888.
* And any of the other McMurtrie papers!
"""
def __init__(self, fname=None, DUMP=False, spin_up=False, met_header=4):
""" Set up model
* Read meterological forcing file
* Read user config file and adjust the model parameters, control or
initial state attributes that are used within the code.
* Setup all class instances...perhaps this isn't the tidyest place for
this?
* Initialise things, zero stores etc.
Parameters:
----------
fname : string
filename of model parameters, including path
chk_cmd_line : logical
parse the cmd line?
DUMP : logical
dump a the default parameters to a file
met_header : int
row number of met file header with variable names
Returns:
-------
Nothing
Controlling class of the model, runs things.
"""
self.day_output = [] # store daily outputs
# initialise model structures and read met data
(self.control, self.params, self.state, self.files, self.fluxes,
self.met_data, self.print_opts) = initialise_model_data(fname,
met_header,
DUMP=DUMP)
# params are defined in per year, needs to be per day
# Important this is done here as rate constants elsewhere in the code
# are assumed to be in units of days not years!
self.correct_rate_constants(output=False)
# class instances
self.cs = CarbonSoilFlows(self.control, self.params, self.state,
self.fluxes, self.met_data)
self.ns = NitrogenSoilFlows(self.control, self.params, self.state,
self.fluxes, self.met_data)
self.lf = Litter(self.control, self.params, self.state, self.fluxes)
self.pg = PlantGrowth(self.control, self.params, self.state,
self.fluxes, self.met_data)
self.cb = CheckBalance(self.control, self.params, self.state,
self.fluxes, self.met_data)
if self.control.deciduous_model:
self.pg.calc_carbon_allocation_fracs(0.0, 0, 0) #comment this!!
self.pg.allocate_stored_c_and_n(init=True)
self.P = Phenology(
self.fluxes,
self.state,
self.control,
self.params.previous_ncd,
store_transfer_len=self.params.store_transfer_len)
self.pr = PrintOutput(self.params, self.state, self.fluxes,
self.control, self.files, self.print_opts)
# build list of variables to print
(self.print_state, self.print_fluxes) = self.pr.get_vars_to_print()
# print model defaults
if DUMP == True:
self.pr.save_default_parameters()
sys.exit(0)
# calculate initial stuff, e.g. C:N ratios and zero annual flux sums
self.day_end_calculations(0, INIT=True)
self.state.pawater_root = self.params.wcapac_root
self.state.pawater_topsoil = self.params.wcapac_topsoil
self.spin_up = spin_up
self.state.sla = self.params.slainit # Specific leaf area (m2/kg DW)
self.state.lai = (self.params.slainit * const.M2_AS_HA /
const.KG_AS_TONNES / self.params.cfracts *
self.state.shoot)
# figure out the number of years for simulation and the number of
# days in each year
self.years = uniq(self.met_data["year"])
self.days_in_year = [self.met_data["year"].count(yr) \
for yr in self.years]
if self.control.water_stress == False:
sys.stderr.write("**** You have turned off the drought stress")
sys.stderr.write(", I assume you're debugging??!\n")
def run_sim(self):
""" Run model simulation! """
# local variables
years = self.years
days_in_year = self.days_in_year
# =============== #
# YEAR LOOP #
# =============== #
project_day = 0
for i, yr in enumerate(years):
self.day_output = [] # empty daily storage list for outputs
daylen = calculate_daylength(days_in_year[i], self.params.latitude)
if self.control.deciduous_model:
self.P.calculate_phenology_flows(daylen, self.met_data,
days_in_year[i], project_day)
self.zero_stuff()
# =============== #
# DAY LOOP #
# =============== #
for doy in xrange(days_in_year[i]):
#for pft in xrange(4):
# litterfall rate: C and N fluxes
(fdecay, rdecay) = self.lf.calculate_litter(doy)
# co2 assimilation, N uptake and loss
self.pg.calc_day_growth(project_day, fdecay,
rdecay, daylen[doy], doy,
float(days_in_year[i]), i)
# soil C & N model fluxes
self.cs.calculate_csoil_flows(project_day)
self.ns.calculate_nsoil_flows(project_day)
# calculate C:N ratios and increment annual flux sums
self.day_end_calculations(project_day, days_in_year[i])
#print self.state.lai, self.fluxes.gpp*100, self.state.pawater_root, self.state.shootnc
# =============== #
# END OF DAY #
# =============== #
if not self.spin_up:
self.save_daily_outputs(yr, doy + 1)
# check the daily water balance
#self.cb.check_water_balance(project_day)
project_day += 1
# =============== #
# END OF YEAR #
# =============== #
if self.control.deciduous_model:
print "**", self.state.cstore
self.pg.allocate_stored_c_and_n(init=False)
if self.control.print_options == "DAILY" and not self.spin_up:
self.print_output_file()
# close output files
if self.control.print_options == "END" and not self.spin_up:
self.print_output_file()
# only close printing file if not in spin up mode as we have yet
# written the daily output...
if self.spin_up:
return (yr, doy + 1)
else:
self.pr.clean_up()
def spin_up_pools(self, tolerance=1E-03):
""" Spin Up model plant, soil and litter pools.
-> Examine sequences of 1000 years and check if C pools are changing
by more than 0.005 units per 1000 yrs.
References:
----------
Adapted from...
* Murty, D and McMurtrie, R. E. (2000) Ecological Modelling, 134,
185-205, specifically page 196.
"""
prev_plantc = 9999.9
prev_soilc = 9999.9
prev_litterc = 9999.9
while True:
if (fabs(prev_plantc - self.state.plantc) < tolerance
and fabs(prev_soilc - self.state.soilc) < tolerance
and fabs(prev_litterc - self.state.litterc) < tolerance):
break
else:
prev_plantc = self.state.plantc
prev_soilc = self.state.soilc
prev_litterc = self.state.litterc
(yr, doy) = self.run_sim() # run the model...
# Have we reached a steady state?
msg = "Spinup: Plant C - %f, Soil C - %f, Litter C - %f\n" % \
(self.state.plantc, self.state.soilc, self.state.litterc)
sys.stderr.write(msg)
self.save_daily_outputs(yr, doy)
self.pr.clean_up()
self.print_output_file()
def print_output_file(self):
""" Either print the daily output file (at the end of the year) or
print the final state + param file. """
# print the daily output file, this is done once at the end of each yr
if self.control.print_options == "DAILY":
self.pr.write_daily_outputs_file(self.day_output)
# print the final state
elif self.control.print_options == "END":
if not self.control.deciduous_model:
if float_eq(self.state.shoot, 0.0):
self.params.slainit = 0.01
else:
# need to save initial SLA to current one!
conv = const.M2_AS_HA * const.KG_AS_TONNES
self.params.slainit = (self.state.lai / const.M2_AS_HA *
const.KG_AS_TONNES *
self.params.cfracts /
self.state.shoot)
self.correct_rate_constants(output=True)
self.pr.save_state()
def zero_stuff(self):
self.state.shoot = 0.0
self.state.shootn = 0.0
self.state.shootnc = 0.0
self.state.lai = 0.0
self.state.cstore = 0.0
self.state.nstore = 0.0
self.state.anpp = 0.0
def correct_rate_constants(self, output=False):
""" adjust rate constants for the number of days in years """
time_constants = [
'rateuptake', 'rateloss', 'retransmob', 'fdecay', 'fdecaydry',
'rdecay', 'rdecaydry', 'bdecay', 'wdecay', 'sapturnover', 'kdec1',
'kdec2', 'kdec3', 'kdec4', 'kdec5', 'kdec6', 'kdec7', 'nuptakez',
'nmax', 'adapt'
]
conv = const.NDAYS_IN_YR
if output == False:
for i in time_constants:
setattr(self.params, i, getattr(self.params, i) / conv)
else:
for i in time_constants:
setattr(self.params, i, getattr(self.params, i) * conv)
def day_end_calculations(self, prjday, days_in_year=None, INIT=False):
"""Calculate derived values from state variables.
Parameters:
-----------
day : integer
day of simulation
INIT : logical
logical defining whether it is the first day of the simulation
"""
# update N:C of plant pools
if float_eq(self.state.shoot, 0.0):
self.state.shootnc = 0.0
else:
self.state.shootnc = self.state.shootn / self.state.shoot
#print self.state.rootn , self.state.root
if float_eq(self.state.root, 0.0):
self.state.rootnc = 0.0
else:
self.state.rootnc = max(0.0, self.state.rootn / self.state.root)
# total plant, soil & litter nitrogen
self.state.soiln = (self.state.inorgn + self.state.activesoiln +
self.state.slowsoiln + self.state.passivesoiln)
self.state.litternag = self.state.structsurfn + self.state.metabsurfn
self.state.litternbg = self.state.structsoiln + self.state.metabsoiln
self.state.littern = self.state.litternag + self.state.litternbg
self.state.plantn = (self.state.shootn + self.state.rootn +
self.state.branchn + self.state.stemn)
self.state.totaln = (self.state.plantn + self.state.littern +
self.state.soiln)
# total plant, soil, litter and system carbon
self.state.soilc = (self.state.activesoil + self.state.slowsoil +
self.state.passivesoil)
self.state.littercag = self.state.structsurf + self.state.metabsurf
self.state.littercbg = self.state.structsoil + self.state.metabsoil
self.state.litterc = self.state.littercag + self.state.littercbg
self.state.plantc = (self.state.root + self.state.shoot +
self.state.stem + self.state.branch)
self.state.totalc = (self.state.soilc + self.state.litterc +
self.state.plantc)
# optional constant passive pool
if self.control.passiveconst == True:
self.state.passivesoil = self.params.passivesoilz
self.state.passivesoiln = self.params.passivesoilnz
if INIT == False:
#Required so max leaf & root N:C can depend on Age
self.state.age += 1.0 / days_in_year
def save_daily_outputs(self, year, doy):
""" Save the daily fluxes + state in a big list.
This should be a more efficient way to write the daily output in a
single step at the end of the year.
Parameters:
-----------
project_day : integer
simulation day
"""
output = [year, doy]
for var in self.print_state:
output.append(getattr(self.state, var))
for var in self.print_fluxes:
output.append(getattr(self.fluxes, var))
self.day_output.append(output)
class Gday(object):
""" The G'DAY (Generic Decomposition And Yield) model.
GDAY simulates C, N and water cycling between the plant and the soil. The
model is structured into three plant pools (foliage, wood and fine roots),
four litter pools (above/below metabolic and structural litter) and three
soil organic matter (SOM) pools with varying turnover rates (active, slow
and passive). An adapted implementation of the CENTURY model simulates soil
carbon and nutrient dynamics. There is an additional simple soil water
balance module which can be used to limit growth. Model pools can be thought
of as buckets as they don't have dimensions.
References:
----------
* Comins, H. N. and McMurtrie, R. E. (1993) Ecological Applications, 3,
666-681.
* Medlyn, B. E. et al (2000) Canadian Journal of Forest Research, 30,
873-888.
"""
def __init__(self, fname=None, DUMP=False, spin_up=False):
""" Set up model
Read meterological forcing file and user config file and adjust the
model parameters, control or initial state attributes that are used
within the code.
Parameters:
----------
fname : string
filename of model parameters, including path
chk_cmd_line : logical
parse the cmd line?
DUMP : logical
dump a the default parameters to a file
Returns:
-------
Nothing
Controlling class of the model, runs things.
"""
self.day_output = [] # store daily outputs
(self.control, self.params,
self.state, self.files,
self.fluxes, self.met_data,
self.print_opts) = initialise_model_data(fname, DUMP=DUMP)
if self.control.water_stress == False:
sys.stderr.write("**** You have turned off the drought stress")
sys.stderr.write(", I assume you're debugging??!\n")
# printing stuff
self.pr = PrintOutput(self.params, self.state, self.fluxes,
self.control, self.files, self.print_opts)
# build list of variables to print
(self.print_state, self.print_fluxes) = self.pr.get_vars_to_print()
# print model defaults
if DUMP == True:
self.pr.save_default_parameters()
sys.exit(0)
self.correct_rate_constants(output=False)
# class instances
self.cs = CarbonSoilFlows(self.control, self.params, self.state,
self.fluxes, self.met_data)
self.ns = NitrogenSoilFlows(self.control, self.params, self.state,
self.fluxes, self.met_data)
self.lf = Litter(self.control, self.params, self.state, self.fluxes)
self.pg = PlantGrowth(self.control, self.params, self.state,
self.fluxes, self.met_data)
if self.control.deciduous_model:
self.pg.calc_carbon_allocation_fracs(0.0)
self.pg.allocate_stored_c_and_n(init=True)
self.P = Phenology(self.fluxes, self.state, self.control,
self.params.previous_ncd,
store_transfer_len=self.params.store_transfer_len)
# calculate initial C:N ratios and zero annual flux sums
self.day_end_calculations(0, INIT=True)
self.state.pawater_root = self.params.wcapac_root
self.state.pawater_tsoil = self.params.wcapac_topsoil
self.spin_up = spin_up
self.state.sla = self.params.slainit # Specific leaf area (m2/kg DW)
self.state.lai = (self.params.slainit * const.M2_AS_HA /
const.KG_AS_TONNES / self.params.cfracts *
self.state.shoot)
def spin_up_pools(self, tolerance=1E-03):
""" Spin Up model plant, soil and litter pools.
-> Examine sequences of 1000 years and check if C pools are changing
or at steady state to 3 d.p.
References:
----------
Adapted from...
* Murty, D and McMurtrie, R. E. (2000) Ecological Modelling, 134,
185-205, specifically page 196.
"""
prev_plantc = 9999.9
prev_soilc = 9999.9
while True:
if (fabs(prev_plantc - self.state.plantc) < tolerance and
fabs(prev_soilc - self.state.soilc) < tolerance):
break
else:
prev_plantc = self.state.plantc
prev_soilc = self.state.soilc
self.run_sim() # run the model...
# Have we reached a steady state?
sys.stderr.write("Spinup: Plant C - %f, Soil C - %f\n" % \
(self.state.plantc, self.state.soilc))
self.print_output_file()
def run_sim(self):
""" Run model simulation! """
project_day = 0
# figure out the number of years for simulation and the number of
# days in each year
years = uniq(self.met_data["year"])
days_in_year = [self.met_data["year"].count(yr) for yr in years]
# =============== #
# YEAR LOOP #
# =============== #
for i, yr in enumerate(years):
self.day_output = [] # empty daily storage list for outputs
daylen = calculate_daylength(days_in_year[i], self.params.latitude)
if self.control.deciduous_model:
self.P.calculate_phenology_flows(daylen, self.met_data,
days_in_year[i], project_day)
self.zero_stuff()
# =============== #
# DAY LOOP #
# =============== #
for doy in xrange(days_in_year[i]):
# litterfall rate: C and N fluxes
(fdecay, rdecay) = self.lf.calculate_litter(doy)
# co2 assimilation, N uptake and loss
self.pg.calc_day_growth(project_day, fdecay, rdecay,
daylen[doy], doy,
float(days_in_year[i]))
# soil C & N model fluxes
self.cs.calculate_csoil_flows(project_day)
self.ns.calculate_nsoil_flows(project_day)
# calculate C:N ratios and increment annual flux sums
self.day_end_calculations(project_day, days_in_year[i])
#print self.state.shoot, self.state.lai
#print self.fluxes.gpp * 100, self.state.lai
# =============== #
# END OF DAY #
# =============== #
self.save_daily_outputs(yr, doy+1)
project_day += 1
# =============== #
# END OF YEAR #
# =============== #
if self.control.deciduous_model:
self.pg.allocate_stored_c_and_n(init=False)
if self.control.print_options == "DAILY" and self.spin_up == False:
self.print_output_file()
# close output files
if self.control.print_options == "END" and self.spin_up == False:
self.print_output_file()
self.pr.clean_up()
def print_output_file(self):
""" Either print the daily output file (at the end of the year) or
print the final state + param file. """
# print the daily output file, this is done once at the end of each yr
if self.control.print_options == "DAILY":
self.pr.write_daily_outputs_file(self.day_output)
# print the final state
elif self.control.print_options == "END":
if not self.control.deciduous_model:
# need to save initial SLA to current one!
conv = const.M2_AS_HA * const.KG_AS_TONNES
self.params.slainit = (self.state.lai / const.M2_AS_HA *
const.KG_AS_TONNES *
self.params.cfracts /self.state.shoot)
self.correct_rate_constants(output=True)
self.pr.save_state()
def zero_stuff(self):
self.state.shoot = 0.0
self.state.shootn = 0.0
self.state.shootnc = 0.0
self.state.lai = 0.0
self.state.cstore = 0.0
self.state.nstore = 0.0
self.state.anpp = 0.0
def correct_rate_constants(self, output=False):
""" adjust rate constants for the number of days in years """
time_constants = ['rateuptake', 'rateloss', 'retransmob',
'fdecay', 'fdecaydry', 'rdecay', 'rdecaydry',
'bdecay', 'wdecay', 'kdec1', 'kdec2', 'kdec3',
'kdec4', 'kdec5', 'kdec6', 'kdec7', 'nuptakez']
conv = const.NDAYS_IN_YR
if output == False:
for i in time_constants:
setattr(self.params, i, getattr(self.params, i) / conv)
else:
for i in time_constants:
setattr(self.params, i, getattr(self.params, i) * conv)
def day_end_calculations(self, prjday, days_in_year=None, INIT=False):
"""Calculate derived values from state variables.
Parameters:
-----------
day : integer
day of simulation
INIT : logical
logical defining whether it is the first day of the simulation
"""
# update N:C of plant pools
if float_eq(self.state.shoot, 0.0):
self.state.shootnc = 0.0
else:
self.state.shootnc = self.state.shootn / self.state.shoot
self.state.rootnc = max(0.0, self.state.rootn / self.state.root)
# total plant, soil & litter nitrogen
self.state.soiln = (self.state.inorgn + self.state.activesoiln +
self.state.slowsoiln + self.state.passivesoiln)
self.state.litternag = self.state.structsurfn + self.state.metabsurfn
self.state.litternbg = self.state.structsoiln + self.state.metabsoiln
self.state.littern = self.state.litternag + self.state.litternbg
self.state.plantn = (self.state.shootn + self.state.rootn +
self.state.branchn + self.state.stemn)
self.state.totaln = (self.state.plantn + self.state.littern +
self.state.soiln)
# total plant, soil, litter and system carbon
self.state.soilc = (self.state.activesoil + self.state.slowsoil +
self.state.passivesoil)
self.state.littercag = self.state.structsurf + self.state.metabsurf
self.state.littercbg = self.state.structsoil + self.state.metabsoil
self.state.litterc = self.state.littercag + self.state.littercbg
self.state.plantc = (self.state.root + self.state.shoot +
self.state.stem + self.state.branch)
self.state.totalc = (self.state.soilc + self.state.litterc +
self.state.plantc)
# optional constant passive pool
if self.control.passiveconst == True:
self.state.passivesoil = self.params.passivesoilz
self.state.passivesoiln = self.params.passivesoilnz
if INIT == False:
#Required so max leaf & root N:C can depend on Age
self.state.age += 1.0 / days_in_year
def save_daily_outputs(self, year, doy):
""" Save the daily fluxes + state in a big list.
This should be a more efficient way to write the daily output in a
single step at the end of the year.
Parameters:
-----------
project_day : integer
simulation day
"""
output = [year, doy]
for var in self.print_state:
output.append(getattr(self.state, var))
for var in self.print_fluxes:
output.append(getattr(self.fluxes, var))
self.day_output.append(output)
class Gday(object):
""" The G'DAY (Generic Decomposition And Yield) model.
GDAY simulates C, N and water cycling between the plant and the soil. The
model is structured into three plant pools (foliage, wood and fine roots),
four litter pools (above/below metabolic and structural litter) and three
soil organic matter (SOM) pools with varying turnover rates (active, slow
and passive). An adapted implementation of the CENTURY model simulates soil
carbon and nutrient dynamics. There is an additional simple soil water
balance module which can be used to limit growth. Model pools can be though
of as buckets as they don't have dimensions.
References:
----------
* Comins, H. N. and McMurtrie, R. E. (1993) Ecological Applications, 3,
666-681.
* Medlyn, B. E. et al (2000) Canadian Journal of Forest Research, 30,
873-888.
* And any of the other McMurtrie papers!
"""
def __init__(self, fname=None, DUMP=False, spin_up=False, met_header=4):
""" Set up model
* Read meterological forcing file
* Read user config file and adjust the model parameters, control or
initial state attributes that are used within the code.
* Setup all class instances...perhaps this isn't the tidyest place for
this?
* Initialise things, zero stores etc.
Parameters:
----------
fname : string
filename of model parameters, including path
chk_cmd_line : logical
parse the cmd line?
DUMP : logical
dump a the default parameters to a file
met_header : in
row number of met file header with variable name
Returns:
-------
Nothing
Controlling class of the model, runs things.
"""
self.day_output = [] # store daily output
# initialise model structures and read met data
(self.control, self.params,
self.state, self.files,
self.fluxes, self.met_data,
self.print_opts) = initialise_model_data(fname, met_header, DUMP=DUMP)
# params are defined in per year, needs to be per day
# Important this is done here as rate constants elsewhere in the code
# are assumed to be in units of days not years!
self.correct_rate_constants(output=False)
# class instance
self.cs = CarbonSoilFlows(self.control, self.params, self.state,
self.fluxes, self.met_data)
self.ns = NitrogenSoilFlows(self.control, self.params, self.state,
self.fluxes, self.met_data)
self.lf = Litter(self.control, self.params, self.state, self.fluxes)
self.pg = PlantGrowth(self.control, self.params, self.state,
self.fluxes, self.met_data)
self.cb = CheckBalance(self.control, self.params, self.state,
self.fluxes, self.met_data)
self.db = Disturbance(self.control, self.params, self.state,
self.fluxes, self.met_data)
if self.control.deciduous_model:
if self.state.max_lai is None:
self.state.max_lai = 0.01 # initialise to something really low
self.state.max_shoot = 0.01 # initialise to something really low
# Are we reading in last years average growing season?
if (float_eq(self.state.avg_alleaf, 0.0) and
float_eq(self.state.avg_alstem, 0.0) and
float_eq(self.state.avg_albranch, 0.0) and
float_eq(self.state.avg_alleaf, 0.0) and
float_eq(self.state.avg_alroot, 0.0) and
float_eq(self.state.avg_alcroot, 0.0)):
self.pg.calc_carbon_allocation_fracs(0.0) #comment this!!
else:
self.fluxes.alleaf = self.state.avg_alleaf
self.fluxes.alstem = self.state.avg_alstem
self.fluxes.albranch = self.state.avg_albranch
self.fluxes.alroot = self.state.avg_alroot
self.fluxes.alcroot = self.state.avg_alcroot
self.pg.allocate_stored_c_and_n(init=True)
#self.pg.enforce_sensible_nstore()
self.P = Phenology(self.fluxes, self.state, self.control,
self.params.previous_ncd,
store_transfer_len=self.params.store_transfer_len)
self.pr = PrintOutput(self.params, self.state, self.fluxes,
self.control, self.files, self.print_opts)
# build list of variables to prin
(self.print_state, self.print_fluxes) = self.pr.get_vars_to_print()
# print model defaul
if DUMP == True:
self.pr.save_default_parameters()
sys.exit(0)
self.dead = False # johnny 5 is alive
# calculate initial stuff, e.g. C:N ratios and zero annual flux sum
self.day_end_calculations(INIT=True)
self.state.pawater_root = self.params.wcapac_root
self.state.pawater_topsoil = self.params.wcapac_topsoil
self.spin_up = spin_up
self.state.lai = max(0.01, (self.params.sla * const.M2_AS_HA /
const.KG_AS_TONNES / self.params.cfracts *
self.state.shoot))
# figure out the number of years for simulation and the number of
# days in each year
self.years = uniq(self.met_data["year"])
self.days_in_year = [self.met_data["year"].count(yr)
for yr in self.years]
if self.control.water_stress == False:
sys.stderr.write("**** You have turned off the drought stress")
sys.stderr.write(", I assume you're debugging??!\n")
def run_sim(self):
""" Run model simulation! """
# local variable
years = self.years
days_in_year = self.days_in_year
if self.control.disturbance:
# Figure out if any years have a disturbance
self.db.initialise(years)
# ===================== #
# Y E A R L O O P #
# ===================== #
project_day = 0
for i, yr in enumerate(years):
self.day_output = [] # empty daily storage list for outpu
daylen = calculate_daylength(days_in_year[i], self.params.latitude)
if self.control.deciduous_model:
self.P.calculate_phenology_flows(daylen, self.met_data,
days_in_year[i], project_day)
# Change window size to length of growing season
self.pg.sma.window_size = self.P.growing_seas_len
self.zero_stuff()
# =================== #
# D A Y L O O P #
# =================== #
for doy in xrange(days_in_year[i]):
# standard litter calculation
# litterfall rate: C and N fluxe
(fdecay, rdecay) = self.lf.calculate_litter(doy)
# Fire Disturbance?
if (self.control.disturbance != 0 and
self.params.disturbance_doy == doy):
self.db.check_for_fire(yr, self.pg)
# Hurricane?
elif (self.control.hurricane == 1 and
self.params.hurricane_yr == yr and
self.params.hurricane_doy == doy):
self.db.hurricane()
# photosynthesis & growth
fsoilT = self.cs.soil_temp_factor(project_day)
self.pg.calc_day_growth(project_day, fdecay, rdecay,
daylen[doy], doy,
float(days_in_year[i]), i, fsoilT)
# soil C & N calculation
self.cs.calculate_csoil_flows(project_day, doy)
self.ns.calculate_nsoil_flows(project_day, doy)
if self.control.ncycle == False:
# Turn off all N calculations
self.reset_all_n_pools_and_fluxes()
# calculate C:N ratios and increment annual flux sum
self.day_end_calculations(days_in_year[i])
# checking if we died during the timestep
# - added for desert simulation
if (not self.control.deciduous_model and
self.control.disturbance == 0):
self.are_we_dead()
#print self.state.plantc, self.state.soilc
#print yr, doy, self.state.lai, self.fluxes.gpp*100
#print self.fluxes.gpp*100, self.state.prev_sma
# ======================= #
# E N D O F D A Y #
# ======================= #
if not self.spin_up:
self.save_daily_outputs(yr, doy+1)
# check the daily water balance
#self.cb.check_water_balance(project_day)
project_day += 1
# ========================= #
# E N D O F Y E A R #
# ========================= #
# Allocate stored C&N for the following year
if self.control.deciduous_model:
# Using average alloc fracs across growing season instead
#self.pg.calc_carbon_allocation_fracs(0.0) #comment this!!
self.pg.calculate_average_alloc_fractions(self.P.growing_seas_len)
self.pg.allocate_stored_c_and_n(init=False)
# reset the stress buffer at the end of the growing season
self.pg.sma.reset_stream()
#print self.fluxes.alleaf, self.fluxes.alroot, \
# (self.fluxes.albranch+self.fluxes.alstem)
#print
# GDAY died in the previous year, re-establish gday for the next yr
# - added for desert simulation
if (self.dead and not
self.control.deciduous_model and
self.control.disturbance == 0):
self.re_establish_gday()
if self.control.print_options == "DAILY" and not self.spin_up:
self.print_output_file()
# close output file
if self.control.print_options == "END" and not self.spin_up:
self.print_output_file()
# only close printing file if not in spin up mode as we have ye
# written the daily output...
if self.spin_up:
return (yr, doy+1)
else:
# Need to pass the project day to calculate NROWS for .hdr file
self.pr.clean_up(project_day)
def are_we_dead(self):
""" Simplistic scheme to allow GDAY to die and re-establish the
following year """
if float_eq(self.state.lai, 0.0):
print "DEAD"
# i.e. we have just died put stem C into struct litter
# works for grasses as this would be zero anyway
if not self.dead:
self.state.structsurf = self.state.stem
self.state.structsurfn = self.state.stemn
# Need to zero stuff for output state and fluxes.
self.state.age = 0.0
self.state.branch = 0.0
self.state.branchn = 0.0
self.state.cstore = 0.0
self.state.nstore = 0.0
self.state.root = 0.0
self.state.rootn = 0.0
self.state.sapwood = 0.0
self.state.shoot = 0.0
self.state.shootn = 0.0
self.state.stem = 0.0
self.state.stemn = 0.0
self.state.stemnimm = 0.0
self.state.stemnmob = 0.0
self.dead = True # johnny 5 is dead
print "dead"
def re_establish_gday(self):
""" grow from seed the following year following death. Concept is tha
somewhere along the line GDAY saved enough C to be able to
re-establish in a new year. C isnt explicitly accounted for, so thi
C just appears. Perhaps this makes sense, i.e. wind/animals dropping
seeds, alternatively we could force GDAY to save a tiny amount of C
for reproduction. For the moment -> it just appears."""
self.state.lai = 0.01
# C/N = 25 of default pools.
if self.control.alloc_model == "GRASSES":
self.state.age = 0.0
self.state.branch = 0.0
self.state.branchn = 0.0
self.state.cstore = 0.001
self.state.nstore = 0.00004
self.state.root = 0.001
self.state.rootn = 0.00004
self.state.sapwood = 0.0
self.state.shoot = 0.001
self.state.shootn = 0.00004
self.state.stem = 0.0
self.state.stemn = 0.0
self.state.stemnimm = 0.0
self.state.stemnmob = 0.0
self.state.croot = 0.0
self.state.crootn = 0.0
else:
self.state.branch = 0.001
self.state.branchn = 0.00004
self.state.croot = 0.001
self.state.crootn = 0.00004
self.state.sapwood = 0.001
self.state.stem = 0.001
self.state.stemn = 0.00004
self.state.stemnimm = 0.00004
self.state.stemnmob = 0.0
self.state.sapwood = 0.001
print "re-seeding"
def spin_up_pools(self, tol=5E-03):
""" Spin up model plant & soil pools to equilibrium.
- Examine sequences of 50 years and check if C pools are changing
by more than 0.005 units per 1000 yrs. Note this check is done in
units of: kg m-2.
References:
----------
Adapted from...
* Murty, D and McMurtrie, R. E. (2000) Ecological Modelling, 134,
185-205, specifically page 196.
"""
prev_plantc = 99999.9
prev_soilc = 99999.9
# check for convergences in units of kg/m2
conv = const.TONNES_HA_2_KG_M2
# If we are prescribing disturbance, first allow the forest to
# establish
if self.control.disturbance != 0:
cntrl_flag = self.control.disturbance
self.control.disturbance = 0
# 200 years (50 yrs x 4 cycles)
for spin_num in xrange(4):
(yr, doy) = self.run_sim() # run the model...
self.control.disturbance = cntrl_flag
while True:
if fabs((prev_soilc*conv) - (self.state.soilc*conv)) < tol:
break
else:
prev_soilc = self.state.soilc
# 1000 years (50 yrs x 20 cycles)
for spin_num in xrange(20):
(yr, doy) = self.run_sim() # run the model...
# Have we reached a steady state?
msg = "Spinup: Soil C - %f\n" % (self.state.soilc)
sys.stderr.write(msg)
else:
while True:
if (fabs((prev_plantc*conv) - (self.state.plantc*conv)) < tol and
fabs((prev_soilc*conv) - (self.state.soilc*conv)) < tol):
break
else:
prev_plantc = self.state.plantc
prev_soilc = self.state.soilc
# 1000 years (50 yrs x 20 cycles)
for spin_num in xrange(20):
(yr, doy) = self.run_sim() # run the model...
# Have we reached a steady state?
msg = "Spinup: Plant C - %f, Soil C - %f\n" % \
(self.state.plantc, self.state.soilc)
sys.stderr.write(msg)
self.save_daily_outputs(yr, doy)
self.pr.clean_up()
self.print_output_file()
def print_output_file(self):
""" Either print the daily output file (at the end of the year) or
print the final state + param file. """
# print the daily output file, this is done once at the end of each yr
if self.control.print_options == "DAILY":
if self.control.output_ascii:
self.pr.write_daily_outputs_file(self.day_output)
else:
self.pr.write_daily_outputs_file_to_binary(self.day_output)
# print the final state
elif self.control.print_options == "END":
if not self.control.deciduous_model:
# This shouldn't do anything, but I will leave it here for
# potential applications. SLA has a N dependancy, though I
# always turn this off...because of this we require this step.
# However this won't work for tress if all the leaves have
# gone! Need to stop that happening! So I guess the sensible
# thing would be to do nothing.
if float_eq(self.state.shoot, 0.0):
pass #
#self.params.slainit = 0.01
else:
# need to save initial SLA to current one!
self.params.sla = (self.state.lai / const.M2_AS_HA *
const.KG_AS_TONNES *
self.params.cfracts /self.state.shoot)
self.correct_rate_constants(output=True)
self.pr.save_state()
def zero_stuff(self):
self.state.shoot = 0.0
self.state.shootn = 0.0
self.state.shootnc = 0.0
self.state.lai = 0.0
self.state.max_lai = 0.0
self.state.max_shoot = 0.0
self.state.cstore = 0.0
self.state.nstore = 0.0
self.state.anpp = 0.0
self.state.grw_seas_stress = 1.0
if self.control.deciduous_model:
self.state.avg_alleaf = 0.0
self.state.avg_alroot = 0.0
self.state.avg_alcroot = 0.0
self.state.avg_albranch = 0.0
self.state.avg_alstem = 0.0
def correct_rate_constants(self, output=False):
""" adjust rate constants for the number of days in years """
time_constants = ['rateuptake', 'rateloss', 'retransmob',
'fdecay', 'fdecaydry', 'crdecay','rdecay',
'rdecaydry', 'bdecay', 'wdecay', 'sapturnover',
'kdec1', 'kdec2', 'kdec3', 'kdec4', 'kdec5', 'kdec6',
'kdec7', 'nuptakez','nmax', 'adapt']
conv = const.NDAYS_IN_YR
if output == False:
for i in time_constants:
setattr(self.params, i, getattr(self.params, i) / conv)
else:
for i in time_constants:
setattr(self.params, i, getattr(self.params, i) * conv)
def day_end_calculations(self, days_in_year=None, INIT=False):
"""Calculate derived values from state variables.
Parameters:
-----------
day : integer
day of simulation
INIT : logical
logical defining whether it is the first day of the simulation
"""
# update N:C of plant pool
if float_eq(self.state.shoot, 0.0):
self.state.shootnc = 0.0
else:
self.state.shootnc = self.state.shootn / self.state.shoot
# Explicitly set the shoot N:C
if self.control.ncycle == False:
self.state.shootnc = self.params.prescribed_leaf_NC
#print self.state.rootn , self.state.roo
if float_eq(self.state.root, 0.0):
self.state.rootnc = 0.0
else:
self.state.rootnc = max(0.0, self.state.rootn / self.state.root)
# total plant, soil & litter nitrogen
self.state.soiln = (self.state.inorgn + self.state.activesoiln +
self.state.slowsoiln + self.state.passivesoiln)
self.state.litternag = self.state.structsurfn + self.state.metabsurfn
self.state.litternbg = self.state.structsoiln + self.state.metabsoiln
self.state.littern = self.state.litternag + self.state.litternbg
self.state.plantn = (self.state.shootn + self.state.rootn +
self.state.crootn + self.state.branchn +
self.state.stemn)
self.state.totaln = (self.state.plantn + self.state.littern +
self.state.soiln)
# total plant, soil, litter and system carbon
self.state.soilc = (self.state.activesoil + self.state.slowsoil +
self.state.passivesoil)
self.state.littercag = self.state.structsurf + self.state.metabsurf
self.state.littercbg = self.state.structsoil + self.state.metabsoil
self.state.litterc = self.state.littercag + self.state.littercbg
self.state.plantc = (self.state.root + self.state.croot +
self.state.shoot + self.state.stem +
self.state.branch)
self.state.totalc = (self.state.soilc + self.state.litterc +
self.state.plantc)
#self.state.plantnc = self.state.plantn / self.state.plantc
#print self.state.plantnc
# optional constant passive pool
if self.control.passiveconst == True:
self.state.passivesoil = self.params.passivesoilz
self.state.passivesoiln = self.params.passivesoilnz
if INIT == False:
#Required so max leaf & root N:C can depend on Age
self.state.age += 1.0 / days_in_year
def save_daily_outputs(self, year, doy):
""" Save the daily fluxes + state in a big list.
This should be a more efficient way to write the daily output in a
single step at the end of the year.
Parameters:
-----------
project_day : integer
simulation day
"""
output = [year, doy]
output.extend(getattr(self.state, var) for var in self.print_state)
output.extend(getattr(self.fluxes, var) for var in self.print_fluxes)
self.day_output.append(output)
def reset_all_n_pools_and_fluxes(self):
""" If the N-Cycle is turned off the way I am implementing this is to
do all the calculations and then reset everything at the end. This is a
waste of resources but saves on multiple IF statements.
"""
# State
self.state.shootn = 0.0
self.state.rootn = 0.0
self.state.crootn = 0.0
self.state.branchn = 0.0
self.state.stemnimm = 0.0
self.state.stemnmob = 0.0
self.state.structsurfn = 0.0
self.state.metabsurfn = 0.0
self.state.structsoiln = 0.0
self.state.metabsoiln = 0.0
self.state.activesoiln = 0.0
self.state.slowsoiln = 0.0
self.state.passivesoiln = 0.0
self.state.inorgn = 0.0
self.state.stemn = 0.0
self.state.stemnimm = 0.0
self.state.stemnmob = 0.0
self.state.nstore = 0.0
# Fluxes
self.fluxes.nuptake = 0.0
self.fluxes.nloss = 0.0
self.fluxes.npassive = 0.0
self.fluxes.ngross = 0.0
self.fluxes.nimmob = 0.0
self.fluxes.nlittrelease = 0.0
self.fluxes.nmineralisation = 0.0
self.fluxes.npleaf = 0.0
self.fluxes.nproot = 0.0
self.fluxes.npcroot = 0.0
self.fluxes.npbranch = 0.0
self.fluxes.npstemimm = 0.0
self.fluxes.npstemmob = 0.0
self.fluxes.deadleafn = 0.0
self.fluxes.deadrootn = 0.0
self.fluxes.deadcrootn = 0.0
self.fluxes.deadbranchn = 0.0
self.fluxes.deadstemn = 0.0
self.fluxes.neaten = 0.0
self.fluxes.nurine = 0.0
self.fluxes.leafretransn = 0.0
self.fluxes.n_surf_struct_litter = 0.0
self.fluxes.n_surf_metab_litter = 0.0
self.fluxes.n_soil_struct_litter = 0.0
self.fluxes.n_soil_metab_litter = 0.0
self.fluxes.n_surf_struct_to_slow = 0.0
self.fluxes.n_soil_struct_to_slow = 0.0
self.fluxes.n_surf_struct_to_active = 0.0
self.fluxes.n_soil_struct_to_active = 0.0
self.fluxes.n_surf_metab_to_active = 0.0
self.fluxes.n_surf_metab_to_active = 0.0
self.fluxes.n_active_to_slow = 0.0
self.fluxes.n_active_to_passive = 0.0
self.fluxes.n_slow_to_active = 0.0
self.fluxes.n_slow_to_passive = 0.0
self.fluxes.n_passive_to_active = 0.0
class Gday(object):
""" The G'DAY (Generic Decomposition And Yield) model.
GDAY simulates C, N and water cycling between the plant and the soil. The
model is structured into three plant pools (foliage, wood and fine roots),
four litter pools (above/below metabolic and structural litter) and three
soil organic matter (SOM) pools with varying turnover rates (active, slow
and passive). An adapted implementation of the CENTURY model simulates soil
carbon and nutrient dynamics. There is an additional simple soil water
balance module which can be used to limit growth. Model pools can be though
of as buckets as they don't have dimensions.
References:
----------
* Comins, H. N. and McMurtrie, R. E. (1993) Ecological Applications, 3,
666-681.
* Medlyn, B. E. et al (2000) Canadian Journal of Forest Research, 30,
873-888.
* And any of the other McMurtrie papers!
"""
def __init__(self, fname=None, DUMP=False, spin_up=False, met_header=4):
""" Set up model
* Read meterological forcing file
* Read user config file and adjust the model parameters, control or
initial state attributes that are used within the code.
* Setup all class instances...perhaps this isn't the tidyest place for
this?
* Initialise things, zero stores etc.
Parameters:
----------
fname : string
filename of model parameters, including path
chk_cmd_line : logical
parse the cmd line?
DUMP : logical
dump a the default parameters to a file
met_header : in
row number of met file header with variable name
Returns:
-------
Nothing
Controlling class of the model, runs things.
"""
self.day_output = [] # store daily output
# initialise model structures and read met data
(self.control, self.params, self.state, self.files, self.fluxes,
self.met_data, self.print_opts) = initialise_model_data(fname,
met_header,
DUMP=DUMP)
# params are defined in per year, needs to be per day
# Important this is done here as rate constants elsewhere in the code
# are assumed to be in units of days not years!
self.correct_rate_constants(output=False)
# class instance
self.cs = CarbonSoilFlows(self.control, self.params, self.state,
self.fluxes, self.met_data)
self.ns = NitrogenSoilFlows(self.control, self.params, self.state,
self.fluxes, self.met_data)
self.lf = Litter(self.control, self.params, self.state, self.fluxes)
self.pg = PlantGrowth(self.control, self.params, self.state,
self.fluxes, self.met_data)
self.cb = CheckBalance(self.control, self.params, self.state,
self.fluxes, self.met_data)
self.db = Disturbance(self.control, self.params, self.state,
self.fluxes, self.met_data)
if self.control.deciduous_model:
if self.state.max_lai is None:
self.state.max_lai = 0.01 # initialise to something really low
self.state.max_shoot = 0.01 # initialise to something really low
# Are we reading in last years average growing season?
if (float_eq(self.state.avg_alleaf, 0.0)
and float_eq(self.state.avg_alstem, 0.0)
and float_eq(self.state.avg_albranch, 0.0)
and float_eq(self.state.avg_alleaf, 0.0)
and float_eq(self.state.avg_alroot, 0.0)
and float_eq(self.state.avg_alcroot, 0.0)):
self.pg.calc_carbon_allocation_fracs(0.0) #comment this!!
else:
self.fluxes.alleaf = self.state.avg_alleaf
self.fluxes.alstem = self.state.avg_alstem
self.fluxes.albranch = self.state.avg_albranch
self.fluxes.alroot = self.state.avg_alroot
self.fluxes.alcroot = self.state.avg_alcroot
self.pg.allocate_stored_c_and_n(init=True)
#self.pg.enforce_sensible_nstore()
self.P = Phenology(
self.fluxes,
self.state,
self.control,
self.params.previous_ncd,
store_transfer_len=self.params.store_transfer_len)
self.pr = PrintOutput(self.params, self.state, self.fluxes,
self.control, self.files, self.print_opts)
# build list of variables to prin
(self.print_state, self.print_fluxes) = self.pr.get_vars_to_print()
# print model defaul
if DUMP == True:
self.pr.save_default_parameters()
sys.exit(0)
self.dead = False # johnny 5 is alive
# calculate initial stuff, e.g. C:N ratios and zero annual flux sum
self.day_end_calculations(INIT=True)
self.state.pawater_root = self.params.wcapac_root
self.state.pawater_topsoil = self.params.wcapac_topsoil
self.spin_up = spin_up
self.state.lai = max(
0.01, (self.params.sla * const.M2_AS_HA / const.KG_AS_TONNES /
self.params.cfracts * self.state.shoot))
# figure out the number of years for simulation and the number of
# days in each year
self.years = uniq(self.met_data["year"])
self.days_in_year = [
self.met_data["year"].count(yr) for yr in self.years
]
if self.control.water_stress == False:
sys.stderr.write("**** You have turned off the drought stress")
sys.stderr.write(", I assume you're debugging??!\n")
def run_sim(self):
""" Run model simulation! """
# local variable
years = self.years
days_in_year = self.days_in_year
if self.control.disturbance:
# Figure out if any years have a disturbance
self.db.initialise(years)
# ===================== #
# Y E A R L O O P #
# ===================== #
project_day = 0
for i, yr in enumerate(years):
self.day_output = [] # empty daily storage list for outpu
daylen = calculate_daylength(days_in_year[i], self.params.latitude)
if self.control.deciduous_model:
self.P.calculate_phenology_flows(daylen, self.met_data,
days_in_year[i], project_day)
# Change window size to length of growing season
self.pg.sma.window_size = self.P.growing_seas_len
self.zero_stuff()
# =================== #
# D A Y L O O P #
# =================== #
for doy in xrange(days_in_year[i]):
# standard litter calculation
# litterfall rate: C and N fluxe
(fdecay, rdecay) = self.lf.calculate_litter(doy)
# Fire Disturbance?
if (self.control.disturbance != 0
and self.params.disturbance_doy == doy):
self.db.check_for_fire(yr, self.pg)
# Hurricane?
elif (self.control.hurricane == 1
and self.params.hurricane_yr == yr
and self.params.hurricane_doy == doy):
self.db.hurricane()
# photosynthesis & growth
fsoilT = self.cs.soil_temp_factor(project_day)
self.pg.calc_day_growth(project_day, fdecay,
rdecay, daylen[doy], doy,
float(days_in_year[i]), i, fsoilT)
# soil C & N calculation
self.cs.calculate_csoil_flows(project_day, doy)
self.ns.calculate_nsoil_flows(project_day, doy)
if self.control.ncycle == False:
# Turn off all N calculations
self.reset_all_n_pools_and_fluxes()
# calculate C:N ratios and increment annual flux sum
self.day_end_calculations(days_in_year[i])
# checking if we died during the timestep
# - added for desert simulation
if (not self.control.deciduous_model
and self.control.disturbance == 0):
self.are_we_dead()
#print self.state.plantc, self.state.soilc
#print yr, doy, self.state.lai, self.fluxes.gpp*100
#print self.fluxes.gpp*100, self.state.prev_sma
# ======================= #
# E N D O F D A Y #
# ======================= #
if not self.spin_up:
self.save_daily_outputs(yr, doy + 1)
# check the daily water balance
#self.cb.check_water_balance(project_day)
project_day += 1
# ========================= #
# E N D O F Y E A R #
# ========================= #
# Allocate stored C&N for the following year
if self.control.deciduous_model:
# Using average alloc fracs across growing season instead
#self.pg.calc_carbon_allocation_fracs(0.0) #comment this!!
self.pg.calculate_average_alloc_fractions(
self.P.growing_seas_len)
self.pg.allocate_stored_c_and_n(init=False)
# reset the stress buffer at the end of the growing season
self.pg.sma.reset_stream()
#print self.fluxes.alleaf, self.fluxes.alroot, \
# (self.fluxes.albranch+self.fluxes.alstem)
#print
# GDAY died in the previous year, re-establish gday for the next yr
# - added for desert simulation
if (self.dead and not self.control.deciduous_model
and self.control.disturbance == 0):
self.re_establish_gday()
if self.control.print_options == "DAILY" and not self.spin_up:
self.print_output_file()
# close output file
if self.control.print_options == "END" and not self.spin_up:
self.print_output_file()
# only close printing file if not in spin up mode as we have ye
# written the daily output...
if self.spin_up:
return (yr, doy + 1)
else:
# Need to pass the project day to calculate NROWS for .hdr file
self.pr.clean_up(project_day)
def are_we_dead(self):
""" Simplistic scheme to allow GDAY to die and re-establish the
following year """
if float_eq(self.state.lai, 0.0):
print "DEAD"
# i.e. we have just died put stem C into struct litter
# works for grasses as this would be zero anyway
if not self.dead:
self.state.structsurf = self.state.stem
self.state.structsurfn = self.state.stemn
# Need to zero stuff for output state and fluxes.
self.state.age = 0.0
self.state.branch = 0.0
self.state.branchn = 0.0
self.state.cstore = 0.0
self.state.nstore = 0.0
self.state.root = 0.0
self.state.rootn = 0.0
self.state.sapwood = 0.0
self.state.shoot = 0.0
self.state.shootn = 0.0
self.state.stem = 0.0
self.state.stemn = 0.0
self.state.stemnimm = 0.0
self.state.stemnmob = 0.0
self.dead = True # johnny 5 is dead
print "dead"
def re_establish_gday(self):
""" grow from seed the following year following death. Concept is tha
somewhere along the line GDAY saved enough C to be able to
re-establish in a new year. C isnt explicitly accounted for, so thi
C just appears. Perhaps this makes sense, i.e. wind/animals dropping
seeds, alternatively we could force GDAY to save a tiny amount of C
for reproduction. For the moment -> it just appears."""
self.state.lai = 0.01
# C/N = 25 of default pools.
if self.control.alloc_model == "GRASSES":
self.state.age = 0.0
self.state.branch = 0.0
self.state.branchn = 0.0
self.state.cstore = 0.001
self.state.nstore = 0.00004
self.state.root = 0.001
self.state.rootn = 0.00004
self.state.sapwood = 0.0
self.state.shoot = 0.001
self.state.shootn = 0.00004
self.state.stem = 0.0
self.state.stemn = 0.0
self.state.stemnimm = 0.0
self.state.stemnmob = 0.0
self.state.croot = 0.0
self.state.crootn = 0.0
else:
self.state.branch = 0.001
self.state.branchn = 0.00004
self.state.croot = 0.001
self.state.crootn = 0.00004
self.state.sapwood = 0.001
self.state.stem = 0.001
self.state.stemn = 0.00004
self.state.stemnimm = 0.00004
self.state.stemnmob = 0.0
self.state.sapwood = 0.001
print "re-seeding"
def spin_up_pools(self, tol=5E-03):
""" Spin up model plant & soil pools to equilibrium.
- Examine sequences of 50 years and check if C pools are changing
by more than 0.005 units per 1000 yrs. Note this check is done in
units of: kg m-2.
References:
----------
Adapted from...
* Murty, D and McMurtrie, R. E. (2000) Ecological Modelling, 134,
185-205, specifically page 196.
"""
prev_plantc = 99999.9
prev_soilc = 99999.9
# check for convergences in units of kg/m2
conv = const.TONNES_HA_2_KG_M2
# If we are prescribing disturbance, first allow the forest to
# establish
if self.control.disturbance != 0:
cntrl_flag = self.control.disturbance
self.control.disturbance = 0
# 200 years (50 yrs x 4 cycles)
for spin_num in xrange(4):
(yr, doy) = self.run_sim() # run the model...
self.control.disturbance = cntrl_flag
while True:
if fabs((prev_soilc * conv) - (self.state.soilc * conv)) < tol:
break
else:
prev_soilc = self.state.soilc
# 1000 years (50 yrs x 20 cycles)
for spin_num in xrange(20):
(yr, doy) = self.run_sim() # run the model...
# Have we reached a steady state?
msg = "Spinup: Soil C - %f\n" % (self.state.soilc)
sys.stderr.write(msg)
else:
while True:
if (fabs((prev_plantc * conv) -
(self.state.plantc * conv)) < tol
and fabs((prev_soilc * conv) -
(self.state.soilc * conv)) < tol):
break
else:
prev_plantc = self.state.plantc
prev_soilc = self.state.soilc
# 1000 years (50 yrs x 20 cycles)
for spin_num in xrange(20):
(yr, doy) = self.run_sim() # run the model...
# Have we reached a steady state?
msg = "Spinup: Plant C - %f, Soil C - %f\n" % \
(self.state.plantc, self.state.soilc)
sys.stderr.write(msg)
self.save_daily_outputs(yr, doy)
self.pr.clean_up()
self.print_output_file()
def print_output_file(self):
""" Either print the daily output file (at the end of the year) or
print the final state + param file. """
# print the daily output file, this is done once at the end of each yr
if self.control.print_options == "DAILY":
if self.control.output_ascii:
self.pr.write_daily_outputs_file(self.day_output)
else:
self.pr.write_daily_outputs_file_to_binary(self.day_output)
# print the final state
elif self.control.print_options == "END":
if not self.control.deciduous_model:
# This shouldn't do anything, but I will leave it here for
# potential applications. SLA has a N dependancy, though I
# always turn this off...because of this we require this step.
# However this won't work for tress if all the leaves have
# gone! Need to stop that happening! So I guess the sensible
# thing would be to do nothing.
if float_eq(self.state.shoot, 0.0):
pass #
#self.params.slainit = 0.01
else:
# need to save initial SLA to current one!
self.params.sla = (self.state.lai / const.M2_AS_HA *
const.KG_AS_TONNES *
self.params.cfracts / self.state.shoot)
self.correct_rate_constants(output=True)
self.pr.save_state()
def zero_stuff(self):
self.state.shoot = 0.0
self.state.shootn = 0.0
self.state.shootnc = 0.0
self.state.lai = 0.0
self.state.max_lai = 0.0
self.state.max_shoot = 0.0
self.state.cstore = 0.0
self.state.nstore = 0.0
self.state.anpp = 0.0
self.state.grw_seas_stress = 1.0
if self.control.deciduous_model:
self.state.avg_alleaf = 0.0
self.state.avg_alroot = 0.0
self.state.avg_alcroot = 0.0
self.state.avg_albranch = 0.0
self.state.avg_alstem = 0.0
def correct_rate_constants(self, output=False):
""" adjust rate constants for the number of days in years """
time_constants = [
'rateuptake', 'rateloss', 'retransmob', 'fdecay', 'fdecaydry',
'crdecay', 'rdecay', 'rdecaydry', 'bdecay', 'wdecay',
'sapturnover', 'kdec1', 'kdec2', 'kdec3', 'kdec4', 'kdec5',
'kdec6', 'kdec7', 'nuptakez', 'nmax', 'adapt'
]
conv = const.NDAYS_IN_YR
if output == False:
for i in time_constants:
setattr(self.params, i, getattr(self.params, i) / conv)
else:
for i in time_constants:
setattr(self.params, i, getattr(self.params, i) * conv)
def day_end_calculations(self, days_in_year=None, INIT=False):
"""Calculate derived values from state variables.
Parameters:
-----------
day : integer
day of simulation
INIT : logical
logical defining whether it is the first day of the simulation
"""
# update N:C of plant pool
if float_eq(self.state.shoot, 0.0):
self.state.shootnc = 0.0
else:
self.state.shootnc = self.state.shootn / self.state.shoot
# Explicitly set the shoot N:C
if self.control.ncycle == False:
self.state.shootnc = self.params.prescribed_leaf_NC
#print self.state.rootn , self.state.roo
if float_eq(self.state.root, 0.0):
self.state.rootnc = 0.0
else:
self.state.rootnc = max(0.0, self.state.rootn / self.state.root)
# total plant, soil & litter nitrogen
self.state.soiln = (self.state.inorgn + self.state.activesoiln +
self.state.slowsoiln + self.state.passivesoiln)
self.state.litternag = self.state.structsurfn + self.state.metabsurfn
self.state.litternbg = self.state.structsoiln + self.state.metabsoiln
self.state.littern = self.state.litternag + self.state.litternbg
self.state.plantn = (self.state.shootn + self.state.rootn +
self.state.crootn + self.state.branchn +
self.state.stemn)
self.state.totaln = (self.state.plantn + self.state.littern +
self.state.soiln)
# total plant, soil, litter and system carbon
self.state.soilc = (self.state.activesoil + self.state.slowsoil +
self.state.passivesoil)
self.state.littercag = self.state.structsurf + self.state.metabsurf
self.state.littercbg = self.state.structsoil + self.state.metabsoil
self.state.litterc = self.state.littercag + self.state.littercbg
self.state.plantc = (self.state.root + self.state.croot +
self.state.shoot + self.state.stem +
self.state.branch)
self.state.totalc = (self.state.soilc + self.state.litterc +
self.state.plantc)
#self.state.plantnc = self.state.plantn / self.state.plantc
#print self.state.plantnc
# optional constant passive pool
if self.control.passiveconst == True:
self.state.passivesoil = self.params.passivesoilz
self.state.passivesoiln = self.params.passivesoilnz
if INIT == False:
#Required so max leaf & root N:C can depend on Age
self.state.age += 1.0 / days_in_year
def save_daily_outputs(self, year, doy):
""" Save the daily fluxes + state in a big list.
This should be a more efficient way to write the daily output in a
single step at the end of the year.
Parameters:
-----------
project_day : integer
simulation day
"""
output = [year, doy]
output.extend(getattr(self.state, var) for var in self.print_state)
output.extend(getattr(self.fluxes, var) for var in self.print_fluxes)
self.day_output.append(output)
def reset_all_n_pools_and_fluxes(self):
""" If the N-Cycle is turned off the way I am implementing this is to
do all the calculations and then reset everything at the end. This is a
waste of resources but saves on multiple IF statements.
"""
# State
self.state.shootn = 0.0
self.state.rootn = 0.0
self.state.crootn = 0.0
self.state.branchn = 0.0
self.state.stemnimm = 0.0
self.state.stemnmob = 0.0
self.state.structsurfn = 0.0
self.state.metabsurfn = 0.0
self.state.structsoiln = 0.0
self.state.metabsoiln = 0.0
self.state.activesoiln = 0.0
self.state.slowsoiln = 0.0
self.state.passivesoiln = 0.0
self.state.inorgn = 0.0
self.state.stemn = 0.0
self.state.stemnimm = 0.0
self.state.stemnmob = 0.0
self.state.nstore = 0.0
# Fluxes
self.fluxes.nuptake = 0.0
self.fluxes.nloss = 0.0
self.fluxes.npassive = 0.0
self.fluxes.ngross = 0.0
self.fluxes.nimmob = 0.0
self.fluxes.nlittrelease = 0.0
self.fluxes.nmineralisation = 0.0
self.fluxes.npleaf = 0.0
self.fluxes.nproot = 0.0
self.fluxes.npcroot = 0.0
self.fluxes.npbranch = 0.0
self.fluxes.npstemimm = 0.0
self.fluxes.npstemmob = 0.0
self.fluxes.deadleafn = 0.0
self.fluxes.deadrootn = 0.0
self.fluxes.deadcrootn = 0.0
self.fluxes.deadbranchn = 0.0
self.fluxes.deadstemn = 0.0
self.fluxes.neaten = 0.0
self.fluxes.nurine = 0.0
self.fluxes.leafretransn = 0.0
self.fluxes.n_surf_struct_litter = 0.0
self.fluxes.n_surf_metab_litter = 0.0
self.fluxes.n_soil_struct_litter = 0.0
self.fluxes.n_soil_metab_litter = 0.0
self.fluxes.n_surf_struct_to_slow = 0.0
self.fluxes.n_soil_struct_to_slow = 0.0
self.fluxes.n_surf_struct_to_active = 0.0
self.fluxes.n_soil_struct_to_active = 0.0
self.fluxes.n_surf_metab_to_active = 0.0
self.fluxes.n_surf_metab_to_active = 0.0
self.fluxes.n_active_to_slow = 0.0
self.fluxes.n_active_to_passive = 0.0
self.fluxes.n_slow_to_active = 0.0
self.fluxes.n_slow_to_passive = 0.0
self.fluxes.n_passive_to_active = 0.0