EPIC - crop.development¶

class mef_agri.models.crop.development.model_epic.Development(**kwargs)¶

Model which computes crop development based on [R2]. Winter dormancy is not considered (i.e. self.winter_dormancy is always set to False). If this is required, see Development_Dormancy.

kwargs \(\rightarrow\) see mef_agri.models.base.Model

dl()¶

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

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

Returns:: current daylength at site
Return type:: Requirement

heat_unit_factor_leaves()¶

MQ - Random Output

\(c_{\textrm{L-huf},k}\ [\ ]\) - [R2] (equ. 9)

Returns:: heat unit factor for leaf growth
Return type:: numpy.ndarray

heat_unit_index()¶

MQ - State

\(c_{\textrm{D-hui},k} = \frac{\sum_k{c_{\textrm{D-dhu},k}}}{c_{\textrm{D-phu},0}}\ [\ ]\) - [R2] (equ. 2)

Returns:: current heat unit index
Return type:: numpy.ndarray

heat_units_pot()¶

MQ - Hyper-Parameter

\(c_{\textrm{D-phu},0}\ [^\circ C]\) - [R2] (equ. 2, table 2)

Returns:: potential heat units for maturity
Return type:: numpy.ndarray

heat_units_rate()¶

MQ - Random Output

\(c_{\textrm{D-dhu},k}\ [^\circ C]\) - [R2] (equ. 1)

Returns:: daily increase of heat units
Return type:: numpy.ndarray

hufl_coeff1()¶

MQ - Hyper-Parameter

\(c_{\textrm{D-lc1},0}\ [\ ]\) - [R2] (equ. 9, table 2)

Returns:: regression coefficient for leaves heat-unit-factor
Return type:: numpy.ndarray

hufl_coeff2()¶

MQ - Hyper-Parameter

\(c_{\textrm{C-lc2},0}\ [\ ]\) - [R2] (equ. 9, table 2)

Returns:: regression coefficient for leaves heat-unit-factor
Return type:: numpy.ndarray

initialize(epoch)¶

Initialization of random outputs with zero vectors.

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

temperature_base()¶

MQ - Hyper-Parameter

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

Returns:: crop-specific base temperature for heat-unit computation
Return type:: numpy.ndarray

temperature_opt()¶

MQ - Hyper-Parameter

\(c_{\textrm{D-to},0}\ [^\circ C]\) - [R2] (equ. 46, table 2)

Returns:: crop-specific optimum temperature regarding temperature stress
Return type:: numpy.ndarray

tmax()¶

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

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

Returns:: daily max. temperature
Return type:: Requirement

tmin()¶

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

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

Returns:: daily min. temperature
Return type:: Requirement

update(epoch)¶

The following computations are performed

call update_dormancy()
if self.winter_dormancy == True
- set heat_units_rate() to zero vector
- heat_unit_index() and heat_unit_factor_leaves() remain unchanged
else

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

update_dormancy()¶: Method which has to be implemented in a child class of Development. It is called in Development.update().

winter_dormancy()¶

MQ - Deterministic Output

\(c_{\textrm{D-wd},k}\ [\ ]\) (boolean value) - [R2] (section Model Description > Growth Constraints > Winter Dormancy)

Returns:: indicator for winter dormancy period
Return type:: bool

class mef_agri.models.crop.development.model_epic.Development_Dormancy(**kwargs)¶

This model considers winter dormancy periods. According to [R2], it is present, when the current daylength is within \(\pm\) one hour around the minimum possible daylength at the current site.

Inherits from Development

kwargs \(\rightarrow\) see mef_agri.models.base.Model

update_dormancy()¶: Determine winter dormancy periods based on current daylength and minimum possible daylength at current site.