EPIC - crop¶

class mef_agri.models.crop.model_epic.Crop_Simple¶

This class acts as root-model containing several child models (i.e. model_name='crop' is passed to the parent class mef_agri.models.base.Model).

It uses

mef_agri.models.crop.development.model_epic.Development as development-model
mef_agri.models.crop.cyield.model_epic.Yield as crop-yield-model

biomass()¶

MQ - State

\(c_{\textrm{bm},k} = c_{\textrm{bm},k-1} + c_{\Delta\textrm{bm},k}\ [\frac{t}{ha}]\)

Monteith (1977) approach is used for biomass increase. Thus, all biomass quantities represent dry matter (see [R6] first sentence of Introduction)

Returns:: total dry biomass (aboveground + roots)
Return type:: numpy.ndarray

biomass_aboveground()¶

MQ - Random Output

\(c_{\textrm{bma},k}\ [\frac{t}{ha}] = c_{\textrm{bm},k} - c_{\textrm{R-bm},k}\ [\frac{t}{ha}]\)

Returns:: above-ground biomass
Return type:: numpy.ndarray

biomass_aboveground_reduction()¶

MQ - Random Output

\(c_{\downarrow\Delta\textrm{bma},k}\ [\frac{t}{ha}]\)

Returns:: reduction of above-ground biomass (only occurs in winter dormancy periods)
Return type:: numpy.ndarray

biomass_rate()¶

MQ - Random Output

\(c_{\Delta\textrm{bm},k}\ [\frac{t}{ha\cdot day}]\) - [R2] (equ. 4, 44)

Returns:: daily increase of total biomass - [1] equ. 4 and 44
Return type:: numpy.ndarray

critical_aeration_factor()¶

MQ - Hyper-Parameter

\(c_{\textrm{caf},0}\ [\ ]\) - [R2] (table 2)

Returns:: critical aeration factor
Return type:: numpy.ndarray

cyield()¶

Child Model

Returns:: model to compute yield increase
Return type:: mef_agri.models.crop.cyield.model_epic.Yield

demand()¶

Child Model

Returns:: model to determine crop demands
Return type:: mef_agri.models.crop.demand.model_epic.Demand

development()¶

Child Model

Returns:: model which computes the crop development stage
Return type:: mef_agri.models.crop.development.model_epic.Development

dl()¶

RQ - 'daylength' from model with id 'zone.atmosphere.daylength'

\(a_{\textrm{dl},k}\ [h]\)

Returns:: current daylength
Return type:: Requirement

dlmin()¶

RQ - 'daylength_min' from model with id 'zone.atmosphere.daylength'

\(a_{\textrm{dlmin},k}\ [h]\)

Returns:: min. daylength in a year at current site
Return type:: Requirement

energy_conversion()¶

MQ - Hyper-Parameter

\(c_{\textrm{e2bm},0}\ [\frac{kg\cdot m^2}{MJ\cdot hat\cdot day}]\) - [R2] (table 2)

Returns:: factor to convert energy to biomass
Return type:: numpy.ndarray

frost_coeff1()¶

MQ - Hyper-Parameter

\(c_{\textrm{frc1},0}\ [\ ]\) - [R2] (equ. 65, table 2)

Returns:: regression coefficient for frost influence on biomass reduction
Return type:: numpy.ndarray

frost_coeff2()¶

MQ - Hyper-Parameter

\(c_{\textrm{frc2},0}\ [\frac{1}{^\circ C}]\) - [R2] (equ. 65, table 2)

Returns:: regression coefficient for frost influence on biomass reduction
Return type:: numpy.ndarray

gc()¶

RQ - 'growth_constraint' from model with id 'crop.stress'

\(c_{\textrm{gc},k}\ [\ ]\)

Returns:: biomass growth constraint (min. value of several stress factors)
Return type:: Requirement

height()¶

MQ - Random Output

\(c_{\textrm{h},k}\ [m]\) - [R2] (equ. 11)

Returns:: crop height
Return type:: numpy.ndarray

height_max()¶

MQ - Hyper-Parameter

\(c_{\textrm{hmax},0}]\ [\ ]\) - [R2] (table 2)

Returns:: max. crop height
Return type:: numpy.ndarray

hufl()¶

RQ - 'heat_unit_factor_leaves' from model with id 'crop.development'

\(c_{\textrm{L-huf},k}\ [\ ]\)

Returns:: heat unit factor for leaf growth
Return type:: Requirement

hui()¶

RQ - quantity 'heat_unit_index' from model with id 'crop.development'

\(c_{\textrm{hui},k}\ [\ ]\)

Returns:: current heat unit index
Return type:: Requirement

initialize(epoch)¶

Initialization of random outputs with zero vectors and child models

Parameters:: epoch (datetime.date) – initialization epoch

lai()¶

RQ - 'lai' from model with id 'crop.leaves'

\(c_{\textrm{L-lai},k}\ [\ ]\)

Returns:: current leaf area index
Return type:: Requirement

leaves()¶

Child Model

Returns:: model which computes growth of leaves
Return type:: mef_agri.models.crop.leaves.model_epic.Leaves

rad()¶

RQ - 'radiation_sum' from model with id 'zone.atmosphere.weather'

\(a_{\textrm{rad},k}\ [\frac{MJ}{m^2\cdot day}]\)

Returns:: daily radiation sum
Return type:: numpy.ndarray

radiation_intercepted()¶

MQ - Random Output

\(c_{\textrm{irad},k}\ [\frac{MJ}{m^2\cdot day}]\) - [R2] (equ. 3)

Returns:: intercepted radiation
Return type:: numpy.ndarray

rbm()¶

RQ - 'biomass' from model with id 'crop.roots'

\(c_{\textrm{R-bm},k}\ [\frac{t}{ha}]\)

Returns:: root biomass
Return type:: Requirement

rf_daylength()¶

MQ - Random Output

\(c_{\textrm{rfdl},k}\ [\ ]\) - [R2] (equ. 64)

Returns:: reduction factor on above-ground biomass due to daylength
Return type:: numpy.ndarray

rf_frost()¶

MQ - Random Output

\(c_{\textrm{rffr},k}\ [\ ]\) - [R2] (equ. 65)

Returns:: reduction factor on above-ground biomass due to frost damage
Return type:: numpy.ndarray

roots()¶

Child Model

Returns:: model which computes root growth
Return type:: mef_agri.models.crop.roots.model_epic.Roots

stress()¶

Child model

Returns:: model which determines stress factors
Return type:: mef_agri.models.crop.stress.model_epic.Stress

tmin()¶

RQ - 'temperature_min' from model with id 'zone.atmosphere.weather'

\(a_{\textrm{tmin},k}\ [^\circ C]\)

Returns:: min. temperature at current day
Return type:: Requirement

update(epoch)¶

The following computations are performed

update uptake()
update development()
radiation_intercepted()
if self.wdorm.value == True
- set biomass_rate() to zero vector
- rf_daylength()
- rf_frost()
- biomass_aboveground_reduction()
else
- difference in daylength
- biomass_rate()
- set rf_daylength(), rf_frost() and biomass_aboveground_reduction() to zero vectors
biomass()
height()
update stress()
update leaves()
update roots()
update cyield()
update demand()
biomass_aboveground()
in the case of self.wdorm.value == True > reduce biomass() and biomass_aboveground() by biomass_aboveground_reduction()

Parameters:: epoch (datetime.date) – current evaluation epoch

uptake()¶

Child Model

Returns:: model to determine/map the supplied quantities from the soil (and atmosphere)
Return type:: mef_agri.models.crop.uptake.model_epic.Uptake

water_storage_max()¶

MQ - Hyper-Parameter

\(c_{\textrm{W-csm},0}\ [mm]\) - [R1] (equ. 2:2.1.1)

Returns:: amount of water that can be stored in the canopy when leaves are fully developed
Return type:: numpy.ndarray

wdorm()¶

RQ - 'winter_dormancy' from model with id 'crop.development'

\(c_{\textrm{wd},k}\ [\ ]\) (boolean value)

Returns:: flag if winter dormancy is active
Return type:: Requirement

class mef_agri.models.crop.model_epic.Crop_Extended¶

This class acts as root-model containing several child models (i.e. model_name='crop' is passed to the parent class ssc_csm.models.base.Model).

It uses

ssc_csm.models.crop.development.model_epic.Development_Dormancy as development-model
ssc_csm.models.crop.cyield.model_epic.Yield_Stressed as crop-yield-model

cyield()¶

Child Model

Returns:: model to compute yield increase
Return type:: ssc_csm.models.crop.cyield.model_epic.Yield_Stressed

development()¶

Child Model

Returns:: model to compute crop development
Return type:: ssc_csm.models.crop.development.model_epic.Development_Dormancy