def update_crop_parameters(self):
"""Function to update certain crop parameters for current
time step (equivalent to lines 97-163 in
compute_crop_calendar)
"""
pd = np.copy(self.var.PlantingDateAdj)
hd = np.copy(self.var.HarvestDateAdj)
hd[hd < pd] += 365
sd = self.var._modelTime.currTime.timetuple().tm_yday
# Update certain crop parameters if using GDD mode
if (self.var.CalendarType == 2):
cond1 = ((self.var.GrowingSeason) &
(self.var._modelTime.doy == pd))
pd[np.logical_not(cond1)] = 0
hd[np.logical_not(cond1)] = 0
max_harvest_date = int(np.max(hd))
if (max_harvest_date > 0):
# Dimension (day,crop,lat,lon)
day_idx = np.arange(sd, max_harvest_date +
1)[:, None, None, None] * np.ones_like(
self.var.PlantingDate)[None, :, :, :]
growing_season_idx = ((day_idx >= pd) & (day_idx <= hd))
# Extract weather data for first growing season
tmin = vos.netcdf2NumPyTimeSlice(
self.var.tmpFileNC,
self.var.tmnVarName,
self.var._modelTime.currTime,
self.var._modelTime.currTime +
datetime.timedelta(int(max_harvest_date - sd)),
cloneMapFileName=self.var.cloneMap,
LatitudeLongitude=True)
tmax = vos.netcdf2NumPyTimeSlice(
self.var.tmpFileNC,
self.var.tmxVarName,
self.var._modelTime.currTime,
self.var._modelTime.currTime +
datetime.timedelta(int(max_harvest_date - sd)),
cloneMapFileName=self.var.cloneMap,
LatitudeLongitude=True)
# broadcast to crop dimension
tmax = tmax[:, None, :, :] * np.ones(
(self.var.nCrop))[None, :, None, None]
tmin = tmin[:, None, :, :] * np.ones(
(self.var.nCrop))[None, :, None, None]
# for convenience
tupp = self.var.Tupp[None, :, :, :] * np.ones(
(tmin.shape[0]))[:, None, None, None]
tbase = self.var.Tbase[None, :, :, :] * np.ones(
(tmin.shape[0]))[:, None, None, None]
# calculate GDD according to the various methods
if self.var.GDDmethod == 1:
tmean = ((tmax + tmin) / 2)
tmean = np.clip(tmean, self.var.Tbase, self.var.Tupp)
elif self.var.GDDmethod == 2:
tmax = np.clip(tmax, self.var.Tbase, self.var.Tupp)
tmin = np.clip(tmin, self.var.Tbase, self.var.Tupp)
tmean = ((tmax + tmin) / 2)
elif self.var.GDDmethod == 3:
tmax = np.clip(tmax, self.var.Tbase, self.var.Tupp)
tmin = np.clip(tmin, None, self.var.Tupp)
tmean = ((tmax + tmin) / 2)
tmean = np.clip(tmean, self.var.Tbase, None)
tmean[np.logical_not(growing_season_idx)] = 0
tbase[np.logical_not(growing_season_idx)] = 0
GDD = (tmean - tbase)
GDDcum = np.cumsum(GDD, axis=0)
# 1 - Calendar days from sowing to maximum canopy cover
maxcanopy_idx = np.copy(day_idx)
maxcanopy_idx[np.logical_not(
GDDcum > self.var.MaxCanopy)] = 999
# maxcanopy_idx[np.logical_not(GDDcum > self.var.MaxCanopy)] = np.nan
maxcanopy_idx = np.nanmin(maxcanopy_idx, axis=0)
MaxCanopyCD = (maxcanopy_idx - pd + 1)
self.var.MaxCanopyCD[cond1] = MaxCanopyCD[cond1]
# 2 - Calendar days from sowing to end of vegetative growth
canopydevend_idx = np.copy(day_idx)
canopydevend_idx[np.logical_not(
GDDcum > self.var.CanopyDevEnd)] = 999
# canopydevend_idx[np.logical_not(GDDcum > self.var.CanopyDevEnd)] = np.nan
canopydevend_idx = np.nanmin(canopydevend_idx, axis=0)
CanopyDevEndCD = canopydevend_idx - pd + 1
self.var.CanopyDevEndCD[cond1] = CanopyDevEndCD[cond1]
# 3 - Calendar days from sowing to start of yield formation
histart_idx = np.copy(day_idx)
histart_idx[np.logical_not(GDDcum > self.var.HIstart)] = 999
# histart_idx[np.logical_not(GDDcum > self.var.HIstart)] = np.nan
histart_idx = np.nanmin(histart_idx, axis=0)
HIstartCD = histart_idx - pd + 1
self.var.HIstartCD[cond1] = HIstartCD[cond1]
# 4 - Calendar days from sowing to end of yield formation
hiend_idx = np.copy(day_idx)
hiend_idx[np.logical_not(GDDcum > self.var.HIend)] = 999
# hiend_idx[np.logical_not(GDDcum > self.var.HIend)] = np.nan
hiend_idx = np.nanmin(hiend_idx, axis=0)
HIendCD = hiend_idx - pd + 1
self.var.HIendCD[cond1] = HIendCD[cond1]
# Duration of yield formation in calendar days
self.var.YldFormCD[cond1] = (self.var.HIendCD -
self.var.HIstartCD)[cond1]
cond11 = (cond1 & (self.var.CropType == 3))
# 1 Calendar days from sowing to end of flowering
floweringend_idx = np.copy(day_idx)
floweringend_idx[np.logical_not(
GDDcum > self.var.FloweringEnd)] = 999
# floweringend_idx[np.logical_not(GDDcum > self.var.FloweringEnd)] = np.nan
floweringend_idx = np.nanmin(floweringend_idx, axis=0)
FloweringEnd = floweringend_idx - pd + 1
# 2 Duration of flowering in calendar days
self.var.FloweringCD[cond11] = (FloweringEnd -
self.var.HIstartCD)[cond11]
# Harvest index growth coefficient
self.calculate_HIGC()
# Days to linear HI switch point
self.calculate_HI_linear()
def compute_crop_calendar(self):
# "Time from sowing to end of vegetative growth period"
cond1 = (self.var.Determinant == 1)
self.var.CanopyDevEnd = np.copy(self.var.Senescence)
self.var.CanopyDevEnd[cond1] = (
np.round(self.var.HIstart + (self.var.Flowering / 2)))[cond1]
# "Time from sowing to 10% canopy cover (non-stressed conditions)
self.var.Canopy10Pct = np.round(self.var.Emergence +
(np.log(0.1 / self.var.CC0) /
self.var.CGC))
# "Time from sowing to maximum canopy cover (non-stressed conditions)
self.var.MaxCanopy = np.round(self.var.Emergence + (np.log(
(0.25 * self.var.CCx * self.var.CCx / self.var.CC0) /
(self.var.CCx - (0.98 * self.var.CCx))) / self.var.CGC))
# "Time from sowing to end of yield formation"
self.var.HIend = self.var.HIstart + self.var.YldForm
cond2 = (self.var.CropType == 3)
# TODO: declare these in __init__
arr_zeros = np.zeros_like(self.var.CropType)
self.var.FloweringEnd = np.copy(arr_zeros)
self.var.FloweringEndCD = np.copy(arr_zeros)
self.var.FloweringCD = np.copy(arr_zeros)
self.var.FloweringEnd[cond2] = (self.var.HIstart +
self.var.Flowering)[cond2]
self.var.FloweringEndCD[cond2] = self.var.FloweringEnd[cond2]
self.var.FloweringCD[cond2] = self.var.Flowering[cond2]
# Mode = self.var.CalendarType
# if Mode == 1:
if self.var.CalendarType == 1:
# "Duplicate calendar values (needed to minimise if-statements when
# switching between GDD and CD runs)
self.var.EmergenceCD = np.copy(
self.var.Emergence) # only used in this function
self.var.Canopy10PctCD = np.copy(
self.var.Canopy10Pct) # only used in this function
self.var.MaxRootingCD = np.copy(
self.var.MaxRooting) # only used in this function
self.var.SenescenceCD = np.copy(
self.var.Senescence) # only used in this function
self.var.MaturityCD = np.copy(
self.var.Maturity) # only used in this function
self.var.MaxCanopyCD = np.copy(self.var.MaxCanopy)
self.var.CanopyDevEndCD = np.copy(self.var.CanopyDevEnd)
self.var.HIstartCD = np.copy(self.var.HIstart)
self.var.HIendCD = np.copy(self.var.HIend)
self.var.YldFormCD = np.copy(self.var.YldForm)
self.var.FloweringEndCD = np.copy(
self.var.FloweringEnd) # only used in this function
self.var.FloweringCD = np.copy(self.var.Flowering)
# Pre-compute cumulative GDD during growing season
if (self.var.CalendarType
== 1 & self.var.SwitchGDD) | (self.var.CalendarType == 2):
pd = np.copy(self.var.PlantingDate)
hd = np.copy(self.var.HarvestDate)
sd = self.var._modelTime.startTime.timetuple().tm_yday
# NEW:
isLeapYear1 = calendar.isleap(self.var._modelTime.startTime.year)
isLeapYear2 = calendar.isleap(self.var._modelTime.startTime.year +
1)
if isLeapYear1:
pd[pd >= 60] += 1
hd[(hd > pd) & (hd >= 60)] += 1
if isLeapYear2:
hd[(hd < pd) & (hd >= 60)] += 1
hd[hd <
pd] += 365 # already accounted for leap years so this should be OK
cond = sd > pd
pd[cond] += 365
hd[cond] += 365
# OLD:
# # if start day of simulation is greater than planting day the
# # first complete growing season will not be until the
# # following year
# pd[sd > pd] += 365
# hd[sd > pd] += 365
# # if start day is less than or equal to planting day, but
# # harvest day is less than planting day, the harvest day will
# # occur in the following year
# hd[((sd <= pd) & (hd < pd))] += 365
# # adjust values for leap year
# isLeapYear1 = calendar.isleap(self.var._modelTime.startTime.year)
# isLeapYear2 = calendar.isleap(self.var._modelTime.startTime.year + 1)
# pd[(isLeapYear1 & (pd >= 60))] += 1 # TODO: check these
# hd[(isLeapYear1 & (hd >= 60))] += 1
# pd[(isLeapYear2 & (pd >= 425))] += 1
# hd[(isLeapYear2 & (hd >= 425))] += 1
max_harvest_date = int(np.max(hd))
day_idx = np.arange(
sd, max_harvest_date + 1)[:, None, None, None] * np.ones_like(
self.var.PlantingDate)[None, :, :, :]
growing_season_idx = ((day_idx >= pd) & (day_idx <= hd))
# Extract weather data for first growing season
tmin = vos.netcdf2NumPyTimeSlice(
self.var.tmpFileNC,
self.var.tmnVarName,
self.var._modelTime.startTime,
self.var._modelTime.startTime +
datetime.timedelta(int(max_harvest_date - sd)),
cloneMapFileName=self.var.cloneMap,
LatitudeLongitude=True)
tmax = vos.netcdf2NumPyTimeSlice(
self.var.tmpFileNC,
self.var.tmxVarName,
self.var._modelTime.startTime,
self.var._modelTime.startTime +
datetime.timedelta(int(max_harvest_date - sd)),
cloneMapFileName=self.var.cloneMap,
LatitudeLongitude=True)
# broadcast to crop dimension
tmax = tmax[:, None, :, :] * np.ones(
(self.var.PlantingDate.shape[0]))[None, :, None, None]
tmin = tmin[:, None, :, :] * np.ones(
(self.var.PlantingDate.shape[0]))[None, :, None, None]
# for convenience
tupp = self.var.Tupp[None, :, :, :] * np.ones(
(tmin.shape[0]))[:, None, None, None]
tbase = self.var.Tbase[None, :, :, :] * np.ones(
(tmin.shape[0]))[:, None, None, None]
# calculate GDD according to the various methods
if self.var.GDDmethod == 1:
tmean = ((tmax + tmin) / 2)
tmean = np.clip(tmean, self.var.Tbase, self.var.Tupp)
elif self.var.GDDmethod == 2:
tmax = np.clip(tmax, self.var.Tbase, self.var.Tupp)
tmin = np.clip(tmin, self.var.Tbase, self.var.Tupp)
tmean = ((tmax + tmin) / 2)
elif self.var.GDDmethod == 3:
tmax = np.clip(tmax, self.var.Tbase, self.var.Tupp)
tmin = np.clip(tmin, None, self.var.Tupp)
tmean = ((tmax + tmin) / 2)
tmean = np.clip(tmean, self.var.Tbase, None)
tmean[np.logical_not(growing_season_idx)] = 0
tbase[np.logical_not(growing_season_idx)] = 0
GDD = (tmean - tbase)
GDDcum = np.cumsum(GDD, axis=0)
# "Check if converting crop calendar to GDD mode"
# if Mode == 1 & self.var.SwitchGDD:
if self.var.CalendarType == 1 & self.var.SwitchGDD:
# Find GDD equivalent for each crop calendar variable
m, n, p = pd.shape # crop,lat,lon
I, J, K = np.ogrid[:m, :n, :p]
emergence_idx = pd + self.var.EmergenceCD # crop,lat,lon
self.var.Emergence = GDDcum[emergence_idx, I, J, K]
canopy10pct_idx = pd + self.var.Canopy10PctCD
self.var.Canopy10Pct = GDDcum[canopy10pct_idx, I, J, K]
maxrooting_idx = pd + self.var.MaxRootingCD
self.var.MaxRooting = GDDcum[maxrooting_idx, I, J, K]
maxcanopy_idx = pd + self.var.MaxCanopyCD
self.var.MaxCanopy = GDDcum[maxcanopy_idx, I, J, K]
canopydevend_idx = pd + self.var.CanopyDevEndCD
self.var.CanopyDevEnd = GDDcum[canopydevend_idx, I, J, K]
senescence_idx = pd + self.var.SenescenceCD
self.var.Senescence = GDDcum[senescence_idx, I, J, K]
maturity_idx = pd + self.var.MaturityCD
self.var.Maturity = GDDcum[maturity_idx, I, J, K]
histart_idx = pd + self.var.HIstartCD
self.var.HIstart = GDDcum[histart_idx, I, J, K]
hiend_idx = pd + self.var.HIendCD
self.var.HIend = GDDcum[hiend_idx, I, J, K]
yldform_idx = pd + self.var.YldFormCD
self.var.YldForm = GDDcum[yldform_idx, I, J, K]
cond2 = (self.var.CropType == 3)
floweringend_idx = pd + self.var.FloweringEndCD
self.var.FloweringEnd[cond2] = GDDcum[floweringend_idx, I, J,
K][cond2]
self.var.Flowering[cond2] = (self.var.FloweringEnd -
self.var.HIstart)[cond2]
# "Convert CGC to GDD mode"
# self.var.CGC_CD = self.var.CGC
self.var.CGC = (np.log(
(((0.98 * self.var.CCx) - self.var.CCx) * self.var.CC0) /
(-0.25 * (self.var.CCx**2)))) / (
-(self.var.MaxCanopy - self.var.Emergence))
# "Convert CDC to GDD mode"
# self.var.CDC_CD = self.var.CDC
tCD = self.var.MaturityCD - self.var.SenescenceCD
tCD[tCD <= 0] = 1
tGDD = self.var.Maturity - self.var.Senescence
tGDD[tGDD <= 0] = 5
self.var.CDC = (self.var.CCx / tGDD) * np.log(1 + (
(1 - self.var.CCi / self.var.CCx) / 0.05))
# "Set calendar type to GDD mode"
self.var._configuration.cropOptions['CalendarType'] = "2"
# elif Mode == 2:
elif self.var.CalendarType == 2:
# "Find calendar days [equivalent] for some variables"
# "1 Calendar days from sowing to maximum canopy cover"
# # TODO: check this indexing
# day_idx = np.arange(0, GDD.shape[0])[:,None,None,None] * np.ones((self.var.nCrop, self.var.nLon, self.var.nLat))[None,:,:,:]
# pd,hd = self.var.adjust_planting_and_harvesting_date(self.var.modelTime.startTime)
maxcanopy_idx = np.copy(day_idx)
maxcanopy_idx[np.logical_not(
GDDcum > self.var.MaxCanopy)] = 999
# maxcanopy_idx[np.logical_not(GDDcum > self.var.MaxCanopy)] = np.nan
maxcanopy_idx = np.nanmin(maxcanopy_idx, axis=0)
self.var.MaxCanopyCD = maxcanopy_idx - pd + 1
# "2 Calendar days from sowing to end of vegetative growth"
canopydevend_idx = np.copy(day_idx)
canopydevend_idx[np.logical_not(
GDDcum > self.var.CanopyDevEnd)] = 999
# canopydevend_idx[np.logical_not(GDDcum > self.var.CanopyDevEnd)] = np.nan
canopydevend_idx = np.nanmin(canopydevend_idx, axis=0)
self.var.CanopyDevEndCD = canopydevend_idx - pd + 1
# "3 Calendar days from sowing to start of yield formation"
histart_idx = np.copy(day_idx)
histart_idx[np.logical_not(GDDcum > self.var.HIstart)] = 999
# histart_idx[np.logical_not(GDDcum > self.var.HIstart)] = np.nan
histart_idx = np.nanmin(histart_idx, axis=0)
self.var.HIstartCD = histart_idx - pd + 1
# "4 Calendar days from sowing to end of yield formation"
hiend_idx = np.copy(day_idx)
hiend_idx[np.logical_not(GDDcum > self.var.HIend)] = 999
# hiend_idx[np.logical_not(GDDcum > self.var.HIend)] = np.nan
hiend_idx = np.nanmin(hiend_idx, axis=0)
self.var.HIendCD = hiend_idx - pd + 1
# "Duration of yield formation in calendar days"
self.var.YldFormCD = self.var.HIendCD - self.var.HIstartCD
cond1 = (self.var.CropType == 3)
# "1 Calendar days from sowing to end of flowering"
floweringend_idx = np.copy(day_idx)
floweringend_idx[np.logical_not(
GDDcum > self.var.FloweringEnd)] = 999
# floweringend_idx[np.logical_not(GDDcum > self.var.FloweringEnd)] = np.nan
floweringend_idx = np.nanmin(floweringend_idx, axis=0)
FloweringEnd = floweringend_idx - pd + 1
# "2 Duration of flowering in calendar days"
self.var.FloweringCD[cond1] = (FloweringEnd -
self.var.HIstartCD)[cond1]