entities

aquacrop.entities.clockStruct

Contains model information regarding dates and step times etc.

ClockStruct

Contains model information regarding dates and step times etc.

Attributes:

time_step_counter (int): Keeps track of current timestep

model_is_finished (Bool): False unless model has finished

simulation_start_date (np.Datetime64): Date of simulation start

simulation_end_date (np.Datetime64): Date of simulation end

time_step (int): time step (evaluation needed

n_steps (int): total number of days of simulation

time_span (np.array): all dates that lie within the start and end dates of simulation

step_start_time (np.Datetime64): Date at start of timestep

step_end_time (np.Datetime64): Date at end of timestep

evap_time_steps (int): Number of time-steps (per day) for soil evaporation calculation

sim_off_season (str): 'Y' if you want to simulate the off season,'N' otherwise

planting_dates (list-like): list of planting dates in datetime format

harvest_dates (list-like): list of harvest dates in datetime format

n_seasons (int): Total number of seasons to be simulated

season_counter (int): counter to keep track of which season we are currenlty simulating

Source code in aquacrop/entities/clockStruct.py

class ClockStruct:
    """
    Contains model information regarding dates and step times etc.

    Attributes:

        time_step_counter (int): Keeps track of current timestep

        model_is_finished (Bool): False unless model has finished

        simulation_start_date (np.Datetime64): Date of simulation start

        simulation_end_date (np.Datetime64): Date of simulation end

        time_step (int): time step (evaluation needed

        n_steps (int): total number of days of simulation

        time_span (np.array): all dates that lie within the start and end dates of simulation

        step_start_time (np.Datetime64): Date at start of timestep

        step_end_time (np.Datetime64): Date at end of timestep

        evap_time_steps (int): Number of time-steps (per day) for soil evaporation calculation

        sim_off_season (str): 'Y' if you want to simulate the off season,'N' otherwise

        planting_dates (list-like): list of planting dates in datetime format

        harvest_dates (list-like): list of harvest dates in datetime format

        n_seasons (int): Total number of seasons to be simulated

        season_counter (int): counter to keep track of which season we are currenlty simulating


    """

    def __init__(self):

        self.time_step_counter = 0  # Keeps track of current timestep
        self.model_is_finished = False  # False unless model has finished
        self.simulation_start_date = 0  # Date of simulation start
        self.simulation_end_date = 0  # Date of simulation end
        self.time_step = 0  # time step (evaluaiton needed)
        self.n_steps = 0  # total number of days of simulation
        self.time_span = (
            0  # all dates that lie within the start and end dates of simulation
        )
        self.step_start_time = 0  # Date at start of timestep
        self.step_end_time = 0  # Date at start of timestep
        # Number of time-steps (per day) for soil evaporation calculation
        self.evap_time_steps = 20
        self.sim_off_season = (
            "N"  # 'Yes' if you want to simulate the off season, 'N' otherwise
        )
        self.planting_dates = (
            []
        )  # list of crop planting dates during simulation
        self.harvest_dates = []  # list of crop planting dates during simulation
        self.n_seasons = 0  # total number of seasons (plant and harvest)
        self.season_counter = -1  # running counter of seasons

aquacrop.entities.co2

CO2

Bases: object

Attributes:

ref_concentration (float): reference CO2 concentration

current_concentration (float): current CO2 concentration (initialize if constant_conc=True)

constant_conc (bool): use constant conc every season

co2_data (DataFrame): CO2 timeseries (2 columns: 'year' and 'ppm')

Source code in aquacrop/entities/co2.py

class CO2(object):

    """

    Attributes:

        ref_concentration (float): reference CO2 concentration

        current_concentration (float): current CO2 concentration (initialize if constant_conc=True)

        constant_conc (bool): use constant conc every season

        co2_data (DataFrame): CO2 timeseries (2 columns: 'year' and 'ppm')

    """

    def __init__(
        self,
        ref_concentration=369.41,
        current_concentration=0.,
        constant_conc=False,
        co2_data=None,
    ):
        self.ref_concentration = ref_concentration
        self.current_concentration = current_concentration
        self.constant_conc = constant_conc
        if co2_data is not None:
            self.co2_data = co2_data
        else:
            self.co2_data = pd.read_csv(
                    f"{acfp}/data/MaunaLoaCO2.txt",
                    header=1,
                    delim_whitespace=True,
                    names=["year", "ppm"],
    )
        self.co2_data_processed = None

aquacrop.entities.crop

Crop class module

Crop

The Crop Class contains paramaters and variables of the crop used in the simulation

Most Crop attributes can be found in the crops.crop_params.py file

A number of default program properties of type float are also specified during initialisation

Initialization example:

crop = Crop('Maize', planting_date='05/01')

Attributes:

c_name (str): crop name ('custom' or one of built in defaults e.g. 'Maize')

planting_date (str): Planting Date (mm/dd)

harvest_date (str): Latest Harvest Date (mm/dd)

Source code in aquacrop/entities/crop.py

class Crop:
    """
    The Crop Class contains paramaters and variables of the crop used in the simulation

    Most Crop attributes can be found in the `crops.crop_params.py` file

    A number of default program properties of type float are also specified during initialisation

    ```
    Initialization example:

    crop = Crop('Maize', planting_date='05/01')
    ```

    Attributes:

        c_name (str): crop name ('custom' or one of built in defaults e.g. 'Maize')

        planting_date (str): Planting Date (mm/dd)

        harvest_date (str): Latest Harvest Date (mm/dd)


    """

    def __init__(self, c_name, planting_date, harvest_date=None, **kwargs):

        self.Name = c_name

        # Assign default program properties (should not be changed without expert knowledge)

        self.fshape_b = 13.8135  # Shape factor describing the reduction in biomass production for insufficient growing degree days
        self.PctZmin = (
            70  # Initial percentage of minimum effective rooting depth
        )
        self.fshape_ex = (
            -6
        )  # Shape factor describing the effects of water stress on root expansion
        self.ETadj = 1  # Adjustment to water stress thresholds depending on daily ET0 (0 = No, 1 = Yes)
        self.ET0dorm = 0 # Duration of dormant crop period (during early senescence) in terms of cumulative reference ET (mm)
        self.Aer = 5  # Vol (%) below saturation at which stress begins to occur due to deficient aeration
        self.LagAer = (
            3  # Number of days lag before aeration stress affects crop growth
        )
        self.beta = 12  # Reduction (%) to p_lo3 when early canopy senescence is triggered
        self.a_Tr = 1  # Exponent parameter for adjustment of Kcx once senescence is triggered
        self.GermThr = 0.2  # Proportion of total water storage needed for crop to germinate
        self.CCmin = 0.05  # Minimum canopy size below which yield_ formation cannot occur
        self.MaxFlowPct = (
            100 / 3
        )  # Proportion of total flowering time (%) at which peak flowering occurs
        self.HIini = 0.01  # Initial harvest index
        self.bsted = 0.000138  # WP co2 adjustment parameter given by Steduto et al. 2007
        self.bface = (
            0.001165  # WP co2 adjustment parameter given by FACE experiments
        )
        self.SwitchGDDType = 'mean' # calculate GDD phenology based on mean of CD phenology across entire simulation period (mean/median)

        if c_name == "custom":

            self.Name = "custom"
            self.planting_date = planting_date  # Planting Date (mm/dd)
            self.harvest_date = harvest_date  # Latest Harvest Date (mm/dd)

        elif c_name in crop_params.keys():
            self.__dict__.update(
                (k, v) for k, v in crop_params[c_name].items()
            )
            self.planting_date = planting_date  # Planting Date (mm/dd)
            self.harvest_date = harvest_date  # Latest Harvest Date (mm/dd)

        else:
            assert (
                c_name in crop_params.keys()
            ), f"Crop name not defined in crop_params dictionary, \
        if defining a custom crop please use crop name 'custom'. Otherwise use one of the \
        pre-defined crops: {crop_params.keys()}"

        # overide any pre-defined paramater with any passed by the user
        allowed_keys = {
            "fshape_b",
            "PctZmin",
            "fshape_ex",
            "ETadj",
            "ET0dorm",
            "Aer",
            "LagAer",
            "beta",
            "a_Tr",
            "GermThr",
            "CCmin",
            "MaxFlowPct",
            "HIini",
            "bsted",
            "bface",
            "Name",
            "CropType",
            "PlantMethod",
            "CalendarType",
            "SwitchGDD",
            "SwitchGDDType",
            "planting_date",
            "harvest_date",
            "Emergence",
            "MaxRooting",
            "Senescence",
            "Maturity",
            "HIstart",
            "Flowering",
            "YldForm",
            "YldWC",
            "GDDmethod",
            "Tbase",
            "Tupp",
            "PolHeatStress",
            "Tmax_up",
            "Tmax_lo",
            "PolColdStress",
            "Tmin_up",
            "Tmin_lo",
            "TrColdStress",
            "GDD_up",
            "GDD_lo",
            "Zmin",
            "Zmax",
            "fshape_r",
            "SxTopQ",
            "SxBotQ",
            "SeedSize",
            "PlantPop",
            "CCx",
            "CDC",
            "CGC",
            "Kcb",
            "fage",
            "WP",
            "WPy",
            "fsink",
            "HI0",
            "dHI_pre",
            "a_HI",
            "b_HI",
            "dHI0",
            "Determinant",
            "exc",
            "p_up1",
            "p_up2",
            "p_up3",
            "p_up4",
            "p_lo1",
            "p_lo2",
            "p_lo3",
            "p_lo4",
            "fshape_w1",
            "fshape_w2",
            "fshape_w3",
            "fshape_w4",
            "CGC_CD",
            "CDC_CD",
            "EmergenceCD",
            "MaxRootingCD",
            "SenescenceCD",
            "MaturityCD",
            "HIstartCD",
            "FloweringCD",
            "YldFormCD",
        }

        self.__dict__.update(
            (k, v) for k, v in kwargs.items() if k in allowed_keys
        )

        self.calculate_additional_params()

    def calculate_additional_params(
        self,
    ):
        '''
        Calculate additional parameters for all self types in mix
        '''

        # Fractional canopy cover size at emergence
        self.CC0 = self.PlantPop * self.SeedSize * 1e-8
        # Root extraction terms
        SxTopQ = self.SxTopQ
        SxBotQ = self.SxBotQ
        S1 = self.SxTopQ
        S2 = self.SxBotQ
        if S1 == S2:
            SxTop = S1
            SxBot = S2
        else:
            if SxTopQ < SxBotQ:
                S1 = SxBotQ
                S2 = SxTopQ

            xx = 3 * (S2 / (S1 - S2))
            if xx < 0.5:
                SS1 = (4 / 3.5) * S1
                SS2 = 0
            else:
                SS1 = (xx + 3.5) * (S1 / (xx + 3))
                SS2 = (xx - 0.5) * (S2 / xx)

            if SxTopQ > SxBotQ:
                SxTop = SS1
                SxBot = SS2
            else:
                SxTop = SS2
                SxBot = SS1

        self.SxTop = SxTop
        self.SxBot = SxBot

        # Water stress thresholds
        self.p_up = np.array([self.p_up1, self.p_up2, self.p_up3, self.p_up4])

        self.p_lo = np.array([self.p_lo1, self.p_lo2, self.p_lo3, self.p_lo4])

        self.fshape_w = np.array(
            [self.fshape_w1, self.fshape_w2, self.fshape_w3, self.fshape_w4]
        )

calculate_additional_params()

Calculate additional parameters for all self types in mix

Source code in aquacrop/entities/crop.py

def calculate_additional_params(
    self,
):
    '''
    Calculate additional parameters for all self types in mix
    '''

    # Fractional canopy cover size at emergence
    self.CC0 = self.PlantPop * self.SeedSize * 1e-8
    # Root extraction terms
    SxTopQ = self.SxTopQ
    SxBotQ = self.SxBotQ
    S1 = self.SxTopQ
    S2 = self.SxBotQ
    if S1 == S2:
        SxTop = S1
        SxBot = S2
    else:
        if SxTopQ < SxBotQ:
            S1 = SxBotQ
            S2 = SxTopQ

        xx = 3 * (S2 / (S1 - S2))
        if xx < 0.5:
            SS1 = (4 / 3.5) * S1
            SS2 = 0
        else:
            SS1 = (xx + 3.5) * (S1 / (xx + 3))
            SS2 = (xx - 0.5) * (S2 / xx)

        if SxTopQ > SxBotQ:
            SxTop = SS1
            SxBot = SS2
        else:
            SxTop = SS2
            SxBot = SS1

    self.SxTop = SxTop
    self.SxBot = SxBot

    # Water stress thresholds
    self.p_up = np.array([self.p_up1, self.p_up2, self.p_up3, self.p_up4])

    self.p_lo = np.array([self.p_lo1, self.p_lo2, self.p_lo3, self.p_lo4])

    self.fshape_w = np.array(
        [self.fshape_w1, self.fshape_w2, self.fshape_w3, self.fshape_w4]
    )

CropStruct

Bases: object

Duplicate crop object for Jit compilation

Source code in aquacrop/entities/crop.py

class CropStruct(object):
    """
    Duplicate crop object for Jit compilation


    """

    def __init__(
        self,
    ):

        # Assign default program properties (should not be changed without expert knowledge)

        self.fshape_b = 13.8135  # Shape factor describing the reduction in biomass production for insufficient growing degree days
        self.PctZmin = (
            70  # Initial percentage of minimum effective rooting depth
        )
        self.fshape_ex = (
            -6
        )  # Shape factor describing the effects of water stress on root expansion
        self.ETadj = 1  # Adjustment to water stress thresholds depending on daily ET0 (0 = No, 1 = Yes)
        self.ET0dorm = 0 # Duration of dormant crop period (during early senescence) in terms of cumulative reference ET (mm)
        self.Aer = 5  # Vol (%) below saturation at which stress begins to occur due to deficient aeration
        self.LagAer = (
            3  # Number of days lag before aeration stress affects crop growth
        )
        self.beta = 12  # Reduction (%) to p_lo3 when early canopy senescence is triggered
        self.a_Tr = 1  # Exponent parameter for adjustment of Kcx once senescence is triggered
        self.GermThr = 0.2  # Proportion of total water storage needed for crop to germinate
        self.CCmin = 0.05  # Minimum canopy size below which yield_ formation cannot occur
        self.MaxFlowPct = (
            100 / 3
        )  # Proportion of total flowering time (%) at which peak flowering occurs
        self.HIini = 0.01  # Initial harvest index
        self.bsted = 0.000138  # WP co2 adjustment parameter given by Steduto et al. 2007
        self.bface = (
            0.001165  # WP co2 adjustment parameter given by FACE experiments
        )

        # added in Read_Model_Paramaters
        self.CropType = 3  # Crop Type (1 = Leafy vegetable, 2 = Root/tuber, 3 = Fruit/grain)
        self.PlantMethod = 1  # Planting method (0 = Transplanted, 1 =  Sown)
        self.CalendarType = (
            2  # Calendar Type (1 = Calendar days, 2 = Growing degree days)
        )
        self.SwitchGDD = 0  # Convert calendar to gdd mode if inputs are given in calendar days (0 = No; 1 = Yes)
        self.SwitchGDDType = 'mean' # calculate GDD phenology based on mean of CD phenology across entire simulation period (mean/median)

        self.EmergenceCD = 0
        self.Canopy10PctCD = 0
        self.MaxRootingCD = 0
        self.SenescenceCD = 0
        self.MaturityCD = 0
        self.MaxCanopyCD = 0
        self.CanopyDevEndCD = 0
        self.HIstartCD = 0
        self.HIendCD = 0
        self.YldFormCD = 0

        self.Emergence = 80  # Growing degree/Calendar days from sowing to emergence/transplant recovery
        self.MaxRooting = (
            1420  # Growing degree/Calendar days from sowing to maximum rooting
        )
        self.Senescence = (
            1420  # Growing degree/Calendar days from sowing to senescence
        )
        self.Maturity = (
            1670  # Growing degree/Calendar days from sowing to maturity
        )
        self.HIstart = 850  # Growing degree/Calendar days from sowing to start of yield_ formation
        self.Flowering = 190  # Duration of flowering in growing degree/calendar days (-999 for non-fruit/grain crops)
        self.YldForm = (
            775  # Duration of yield_ formation in growing degree/calendar days
        )
        self.HIend = 0
        self.MaxCanopy = 0
        self.CanopyDevEnd = 0
        self.Canopy10Pct = 0
        self.YldWC = 0
        self.GDDmethod = 2  # Growing degree day calculation method
        self.Tbase = (
            8  # Base temperature (degC) below which growth does not progress
        )
        self.Tupp = 30  # Upper temperature (degC) above which crop development no longer increases
        self.PolHeatStress = (
            1  # Pollination affected by heat stress (0 = No, 1 = Yes)
        )
        self.Tmax_up = 40  # Maximum air temperature (degC) above which pollination begins to fail
        self.Tmax_lo = 45  # Maximum air temperature (degC) at which pollination completely fails
        self.PolColdStress = (
            1  # Pollination affected by cold stress (0 = No, 1 = Yes)
        )
        self.Tmin_up = 10  # Minimum air temperature (degC) below which pollination begins to fail
        self.Tmin_lo = 5  # Minimum air temperature (degC) at which pollination completely fails
        self.TrColdStress = 1  # Transpiration affected by cold temperature stress (0 = No, 1 = Yes)
        self.GDD_up = 12  # Minimum growing degree days (degC/day) required for full crop transpiration potential
        self.GDD_lo = 0  # Growing degree days (degC/day) at which no crop transpiration occurs
        self.Zmin = 0.3  # Minimum effective rooting depth (m)
        self.Zmax = 1.7  # Maximum rooting depth (m)
        self.fshape_r = 1.3  # Shape factor describing root expansion
        self.SxTopQ = 0.0480  # Maximum root water extraction at top of the root zone (m3/m3/day)
        self.SxBotQ = 0.0117  # Maximum root water extraction at the bottom of the root zone (m3/m3/day)

        self.SxTop = 0.0
        self.SxBot = 0.0

        self.SeedSize = 6.5  # Soil surface area (cm2) covered by an individual seedling at 90% emergence
        self.PlantPop = 75_000  # Number of plants per hectare
        self.CCx = 0.96  # Maximum canopy cover (fraction of soil cover)
        self.CDC = (
            0.01  # Canopy decline coefficient (fraction per gdd/calendar day)
        )
        self.CGC = 0.0125  # Canopy growth coefficient (fraction per gdd)
        self.CDC_CD = (
            0.01  # Canopy decline coefficient (fraction per gdd/calendar day)
        )
        self.CGC_CD = 0.0125  # Canopy growth coefficient (fraction per gdd)
        self.Kcb = 1.05  # Crop coefficient when canopy growth is complete but prior to senescence
        self.fage = 0.3  #  Decline of crop coefficient due to ageing (%/day)
        self.WP = 33.7  # Water productivity normalized for ET0 and C02 (g/m2)
        self.WPy = 100  # Adjustment of water productivity in yield_ formation stage (% of WP)
        self.fsink = 0.5  # Crop performance under elevated atmospheric CO2 concentration (%/100)
        self.HI0 = 0.48  # Reference harvest index
        self.dHI_pre = 0  # Possible increase of harvest index due to water stress before flowering (%)
        self.a_HI = 7  # Coefficient describing positive impact on harvest index of restricted vegetative growth during yield_ formation
        self.b_HI = 3  # Coefficient describing negative impact on harvest index of stomatal closure during yield_ formation
        self.dHI0 = 15  # Maximum allowable increase of harvest index above reference value
        self.Determinant = (
            1  # Crop Determinancy (0 = Indeterminant, 1 = Determinant)
        )
        self.exc = 50  # Excess of potential fruits
        self.p_up = np.zeros(
            4
        )  # Upper soil water depletion threshold for water stress effects on affect canopy expansion
        self.p_lo = np.zeros(
            4
        )  # Lower soil water depletion threshold for water stress effects on canopy expansion
        self.fshape_w = np.ones(
            4
        )  # Shape factor describing water stress effects on canopy expansion

        self.CC0 = 0.0

        self.HIGC = 0.0
        self.tLinSwitch = 0
        self.dHILinear = 0.0

        self.fCO2 = 0.0

        self.FloweringCD = 0
        self.FloweringEnd = 0.0

aquacrop.entities.fieldManagement

FieldMngt

Field Management Class containing mulches and bunds parameters

Attributes:

mulches (bool):  Soil surface covered by mulches (yield_ or N)

bunds (bool):  Surface bunds present (yield_ or N)

curve_number_adj (bool): Field conditions affect curve number (yield_ or N)

sr_inhb (bool): Management practices fully inhibit surface runoff (yield_ or N)

mulch_pct (float):  Area of soil surface covered by mulches (%)

f_mulch (float): Soil evaporation adjustment factor due to effect of mulches

z_bund (float): Bund height, user specifies in (m) but immediately converted to (mm) on initialisation for coherent calculations

bund_water (float): Initial water height in surface bunds (mm)

curve_number_adj_pct (float): Percentage change in curve number (positive or negative)

Source code in aquacrop/entities/fieldManagement.py

class FieldMngt:
    """
    Field Management Class containing mulches and bunds parameters

    Attributes:

        mulches (bool):  Soil surface covered by mulches (yield_ or N)

        bunds (bool):  Surface bunds present (yield_ or N)

        curve_number_adj (bool): Field conditions affect curve number (yield_ or N)

        sr_inhb (bool): Management practices fully inhibit surface runoff (yield_ or N)

        mulch_pct (float):  Area of soil surface covered by mulches (%)

        f_mulch (float): Soil evaporation adjustment factor due to effect of mulches

        z_bund (float): Bund height, user specifies in (m) but immediately converted to (mm) on initialisation for coherent calculations

        bund_water (float): Initial water height in surface bunds (mm)

        curve_number_adj_pct (float): Percentage change in curve number (positive or negative)

    """

    def __init__(
        self,
        mulches=False,
        bunds=False,
        curve_number_adj=False,
        sr_inhb=False,
        mulch_pct=50,
        f_mulch=0.5,
        z_bund=0,
        bund_water=0,
        curve_number_adj_pct=0,
    ):

        self.mulches = mulches  #  Soil surface covered by mulches (yield_ or N)
        self.bunds = bunds  #  Surface bunds present (yield_ or N)
        self.curve_number_adj = curve_number_adj  # Field conditions affect curve number (yield_ or N)
        self.sr_inhb = sr_inhb  # Management practices fully inhibit surface runoff (yield_ or N)

        self.mulch_pct = mulch_pct  #  Area of soil surface covered by mulches (%)
        self.f_mulch = f_mulch  # Soil evaporation adjustment factor due to effect of mulches
        self.z_bund = z_bund * 1000 # Bund height, user-specified as (m), here immediately converted to (mm)
        self.bund_water = bund_water  # Initial water height in surface bunds (mm)
        self.curve_number_adj_pct = curve_number_adj_pct  # Percentage change in curve number (positive or negative)

FieldMngtStruct

Source code in aquacrop/entities/fieldManagement.py

class FieldMngtStruct:

    """


    """

    def __init__(self):
        self.mulches = False
        self.bunds = False
        self.curve_number_adj = False
        self.sr_inhb = False

        self.mulch_pct = 0.0
        self.f_mulch = 0.0
        self.z_bund = 0.0
        self.bund_water = 0.0
        self.curve_number_adj_pct = 0.0

aquacrop.entities.groundWater

GroundWater

Ground Water Class stores information on water table params

Attributes:

water_table (str):  Water table considered (Y or N)

method (str):  Water table input data ('Constant' or 'Variable')

dates (list): water table observation dates

values (list): water table observation depths

Source code in aquacrop/entities/groundWater.py

class GroundWater:
    """
    Ground Water Class stores information on water table params

    Attributes:

        water_table (str):  Water table considered (Y or N)

        method (str):  Water table input data ('Constant' or 'Variable')

        dates (list): water table observation dates

        values (list): water table observation depths

    """

    def __init__(self, water_table="N", method="Constant", dates=[], values=[]):

        self.water_table = water_table
        self.method = method
        self.dates = dates
        self.values = values

aquacrop.entities.inititalWaterContent

InitialWaterContent

Initial water content Class defines water content at start of sim

Attributes:

wc_type (str):  Type of value ('Prop' = 'WP'/'FC'/'SAT'; 'Num' = XXX m3/m3; 'Pct' = % taw))

method (str):  method ('Depth' = Interpolate depth points; 'Layer' = Constant value for each soil layer)

depth_layer (list): location in soil profile (soil layer or depth)

value (list): value at each location given in depth_layer

Source code in aquacrop/entities/inititalWaterContent.py

class InitialWaterContent:
    """
    Initial water content Class defines water content at start of sim

    Attributes:

        wc_type (str):  Type of value ('Prop' = 'WP'/'FC'/'SAT'; 'Num' = XXX m3/m3; 'Pct' = % taw))

        method (str):  method ('Depth' = Interpolate depth points; 'Layer' = Constant value for each soil layer)

        depth_layer (list): location in soil profile (soil layer or depth)

        value (list): value at each location given in depth_layer

    """

    def __init__(self, wc_type="Prop", method="Layer", depth_layer=[1], value=["FC"]):

        self.wc_type = wc_type
        self.method = method
        self.depth_layer = depth_layer
        self.value = value

aquacrop.entities.initParamVariables

InitialCondition

The InitCond Class contains all Paramaters and variables used in the simulation

updated each timestep with the name NewCond

Source code in aquacrop/entities/initParamVariables.py

class InitialCondition:
    """
    The InitCond Class contains all Paramaters and variables used in the simulation

    updated each timestep with the name NewCond


    """

    def __init__(self, num_comp):
        # counters
        self.age_days = 0
        self.age_days_ns = 0
        self.aer_days = 0
        self.aer_days_comp = np.zeros(num_comp)
        self.irr_cum = 0
        self.delayed_gdds = 0
        self.delayed_cds = 0
        self.pct_lag_phase = 0
        self.t_early_sen = 0
        self.gdd_cum = 0
        self.day_submerged = 0
        self.irr_net_cum = 0
        self.dap = 0
        self.e_pot = 0
        self.t_pot = 0

        # States
        self.pre_adj = False
        self.crop_mature = False
        self.crop_dead = False
        self.germination = False
        self.premat_senes = False
        self.harvest_flag = False
        self.growing_season = False
        self.yield_form = False
        self.stage2 = False

        self.wt_in_soil = False

        # harvest_index
        self.stage = 1
        self.f_pre = 1
        self.f_post = 1
        self.fpost_dwn = 1
        self.fpost_upp = 1

        self.h1_cor_asum = 0
        self.h1_cor_bsum = 0
        self.f_pol = 0
        self.s_cor1 = 0
        self.s_cor2 = 0
        self.hi_ref = 0.0
        self.HIfinal = 0.0

        # GS
        self.growth_stage = 0

        # Transpiration
        self.tr_ratio = 1

        # crop growth
        self.r_cor = 1

        self.canopy_cover = 0
        self.canopy_cover_adj = 0
        self.canopy_cover_ns = 0
        self.canopy_cover_adj_ns = 0
        self.biomass = 0
        self.biomass_ns = 0
        self.YieldPot = 0
        self.harvest_index = 0
        self.harvest_index_adj = 0
        self.ccx_act = 0
        self.ccx_act_ns = 0
        self.ccx_w = 0
        self.ccx_w_ns = 0
        self.ccx_early_sen = 0
        self.cc_prev = 0
        self.protected_seed = 0
        self.DryYield = 0
        self.FreshYield = 0

        self.z_root = 0.0
        self.cc0_adj = 0
        self.surface_storage = 0
        self.z_gw = ModelConstants.NO_VALUE

        self.th_fc_Adj = np.zeros(num_comp)
        self.th = np.zeros(num_comp)
        self.thini = np.zeros(num_comp)

        self.time_step_counter = 0

        self.precipitation = 0
        self.temp_max = 0
        self.temp_min = 0
        self.et0 = 0
        self.sumET0EarlySen = 0
        self.gdd = 0

        self.w_surf = 0
        self.evap_z = 0
        self.w_stage_2 = 0

        self.depletion = 0
        self.taw = 0

aquacrop.entities.irrigationManagement

IrrMngtStruct

Source code in aquacrop/entities/irrigationManagement.py

class IrrMngtStruct:

    """


    """

    def __init__(self, sim_len):
        self.irrigation_method = 0

        self.WetSurf = 100.0
        self.AppEff = 100.0
        self.MaxIrr = 25.0
        self.MaxIrrSeason = 10_000
        self.SMT = np.zeros(4)
        self.IrrInterval = 0
        self.Schedule = np.zeros(sim_len)
        self.NetIrrSMT = 80.0
        self.depth = 0.0

IrrigationManagement

IrrigationManagement Class defines irrigation strategy

Attributes:

irrigation_method (int):  Irrigation method {0: rainfed, 1: soil moisture targets, 2: set time interval,
                                        3: predifined schedule, 4: net irrigation, 5: constant depth }

WetSurf (int): Soil surface wetted by irrigation (%)

AppEff (int): Irrigation application efficiency (%)

MaxIrr (float): Maximum depth (mm) that can be applied each day

SMT (list):  Soil moisture targets (%taw) to maintain in each growth stage (only used if irrigation method is equal to 1)

IrrInterval (int): Irrigation interval in days (only used if irrigation method is equal to 2)

Schedule (pandas.DataFrame): DataFrame containing dates and depths

NetIrrSMT (float): Net irrigation threshold moisture level (% of taw that will be maintained, for irrigation_method=4)

Depth (float): constant depth to apply on each day (mm)

Source code in aquacrop/entities/irrigationManagement.py

class IrrigationManagement:

    """
    IrrigationManagement Class defines irrigation strategy

    Attributes:


        irrigation_method (int):  Irrigation method {0: rainfed, 1: soil moisture targets, 2: set time interval,
                                                3: predifined schedule, 4: net irrigation, 5: constant depth }

        WetSurf (int): Soil surface wetted by irrigation (%)

        AppEff (int): Irrigation application efficiency (%)

        MaxIrr (float): Maximum depth (mm) that can be applied each day

        SMT (list):  Soil moisture targets (%taw) to maintain in each growth stage (only used if irrigation method is equal to 1)

        IrrInterval (int): Irrigation interval in days (only used if irrigation method is equal to 2)

        Schedule (pandas.DataFrame): DataFrame containing dates and depths

        NetIrrSMT (float): Net irrigation threshold moisture level (% of taw that will be maintained, for irrigation_method=4)

        Depth (float): constant depth to apply on each day (mm)

    """

    def __init__(self, irrigation_method, **kwargs):
        self.irrigation_method = irrigation_method

        self.WetSurf = 100.0
        self.AppEff = 100.0
        self.MaxIrr = 25.0
        self.MaxIrrSeason = 10_000.0
        self.SMT = np.zeros(4)
        self.IrrInterval = 0
        self.Schedule = []
        self.NetIrrSMT = 80.0
        self.depth = 0.0

        if irrigation_method == 1:
            self.SMT = [100] * 4

        if irrigation_method == 2:
            self.IrrInterval = 3

        if irrigation_method == 3:
            # wants a pandas dataframe with Date and Depth, pd.Datetime and float
            """
            dates = pd.DatetimeIndex(['20/10/1979','20/11/1979','20/12/1979'])
            depths = [25,25,25]
            irr=pd.DataFrame([dates,depths]).T
            irr.columns=['Date','Depth']
            """
            self.Schedule = pd.DataFrame(columns=["Date", "Depth"])

        if irrigation_method == 4:
            self.NetIrrSMT = 80

        if irrigation_method == 5:
            self.depth = 0

        allowed_keys = {
            "name",
            "WetSurf",
            "AppEff",
            "MaxIrr",
            "MaxIrrSeason",
            "SMT",
            "IrrInterval",
            "NetIrrSMT",
            "Schedule",
            "depth",
        }

        self.__dict__.update((k, v) for k, v in kwargs.items() if k in allowed_keys)

aquacrop.entities.moistureDepletion

Dr

Depletion class to hold the rootzone and topsoil depletion

Attributes:

Rz (float): Root zone soil-water depletion

Zt (float): Top soil depletion

Source code in aquacrop/entities/moistureDepletion.py

class Dr:
    """
    Depletion class to hold the rootzone and topsoil depletion

    Attributes:

    Rz (float): Root zone soil-water depletion

    Zt (float): Top soil depletion


    """

    def __init__(self):
        self.Rz = 0.0
        self.Zt = 0.0

aquacrop.entities.output

Output

Class to hold output data

During Simulation these are numpy arrays and are converted to pandas dataframes at the end of the simulation

Atributes:

water_flux (pandas.DataFrame, numpy.array): Daily water flux changes

water_storage (pandas.DataFrame, numpy array): daily water content of each soil compartment

crop_growth (pandas.DataFrame, numpy array): daily crop growth variables

final_stats (pandas.DataFrame, numpy array): final stats at end of each season

Source code in aquacrop/entities/output.py

class Output:
    """
    Class to hold output data

    During Simulation these are numpy arrays and are converted to pandas dataframes
    at the end of the simulation

    Atributes:

        water_flux (pandas.DataFrame, numpy.array): Daily water flux changes

        water_storage (pandas.DataFrame, numpy array): daily water content of each soil compartment

        crop_growth (pandas.DataFrame, numpy array): daily crop growth variables

        final_stats (pandas.DataFrame, numpy array): final stats at end of each season

    """

    def __init__(self, time_span, initial_th):

        self.water_storage = np.zeros((len(time_span), 3 + len(initial_th)))
        self.water_flux = np.zeros((len(time_span), 16))
        self.crop_growth = np.zeros((len(time_span), 15))
        self.final_stats = pd.DataFrame(
            columns=[
                "Season",
                "crop Type",
                "Harvest Date (YYYY/MM/DD)",
                "Harvest Date (Step)",
                "Dry yield (tonne/ha)",
                "Fresh yield (tonne/ha)",
                "Yield potential (tonne/ha)",
                "Seasonal irrigation (mm)",
            ]
        )

aquacrop.entities.paramStruct

ParamStruct

The ParamStruct class contains the bulk of model Paramaters. In general these will not change over the course of the simulation

Attributes:

Soil (Soil): Soil object contains data and paramaters related to the soil

FallowFieldMngt (FieldMngt): Object containing field management variables for the off season (fallow periods)

NCrops (int): Number of crop types to be simulated

SpecifiedPlantCalander (str):  Specified crop rotation calendar (yield_ or N)

CropChoices (list): List of crop type names in each simulated season

CO2data (pd.Series): CO2 data indexed by year

CO2 (CO2): object containing reference and current co2 concentration

water_table (int): Water table present (1=yes, 0=no)

z_gw (np.array): water_table depth (mm) for each day of simulation

zGW_dates (np.array): Corresponding dates to the z_gw values

WTMethod (str): 'Constant' or 'Variable'

CropList (list): List of Crop Objects which contain paramaters for all the differnet crops used in simulations

python_crop_list (list): List of Crop Objects, one for each season

python_fallow_crop (Crop): Crop object for off season

Seasonal_Crop_List (list): List of CropStructs, one for each season (jit class objects)

crop_name_list (list): List of crop names, one for each season

Fallow_Crop (CropStruct): CropStruct object (jit class) for off season

Fallow_Crop_Name (str): name of fallow crop

Source code in aquacrop/entities/paramStruct.py

class ParamStruct:
    """
    The ParamStruct class contains the bulk of model Paramaters. 
    In general these will not change over the course of the simulation


    Attributes:

        Soil (Soil): Soil object contains data and paramaters related to the soil

        FallowFieldMngt (FieldMngt): Object containing field management variables for the off season (fallow periods)

        NCrops (int): Number of crop types to be simulated

        SpecifiedPlantCalander (str):  Specified crop rotation calendar (yield_ or N)

        CropChoices (list): List of crop type names in each simulated season

        CO2data (pd.Series): CO2 data indexed by year

        CO2 (CO2): object containing reference and current co2 concentration

        water_table (int): Water table present (1=yes, 0=no)

        z_gw (np.array): water_table depth (mm) for each day of simulation

        zGW_dates (np.array): Corresponding dates to the z_gw values

        WTMethod (str): 'Constant' or 'Variable'

        CropList (list): List of Crop Objects which contain paramaters for all the differnet crops used in simulations

        python_crop_list (list): List of Crop Objects, one for each season

        python_fallow_crop (Crop): Crop object for off season

        Seasonal_Crop_List (list): List of CropStructs, one for each season (jit class objects)

        crop_name_list (list): List of crop names, one for each season

        Fallow_Crop (CropStruct): CropStruct object (jit class) for off season

        Fallow_Crop_Name (str): name of fallow crop

        """

    def __init__(self):

        # soil
        self.Soil = 0

        # field management
        self.FallowFieldMngt = 0

        # variables extracted from cropmix.txt
        self.NCrops = 0
        self.SpecifiedPlantCalander = ""
        self.RotationFilename = ""

        # calculated Co2 variables
        self.CO2data = []
        self.CO2 = 0
        self.co2_concentration_adj = None

        # water table
        self.water_table = 0
        self.z_gw = []
        self.zGW_dates = []
        self.WTMethod = ""

        # crops
        self.CropList = []
        self.python_crop_list = []
        self.python_fallow_crop = 0
        self.Seasonal_Crop_List = []
        self.crop_name_list = []
        self.Fallow_Crop = 0
        self.Fallow_Crop_Name = ""

aquacrop.entities.rootZoneWaterContent

RootZoneWater

Bases: object

TODO: This class is not used

root zone water content

Attributes:

Act : float : .

S : float : .

FC : float : .

WP : float : .

Dry : float : .

Aer : float : .

Source code in aquacrop/entities/rootZoneWaterContent.py

class RootZoneWater(object):
    """
    TODO: This class is not used

    root zone water content

    **Attributes:**\n



    `Act` : `float` : .

    `S` : `float` : .

    `FC` : `float` : .

    `WP` : `float` : .

    `Dry` : `float` : .

    `Aer` : `float` : .



    """

    def __init__(self):
        self.Act = 0.0
        self.S = 0.0
        self.FC = 0.0
        self.WP = 0.0
        self.Dry = 0.0
        self.Aer = 0.0

aquacrop.entities.soil

Soil

The Soil Class contains Paramaters and variables of the soil used in the simulation

More float attributes are specified in the initialisation of the class

Attributes:

profile (pandas.DataFrame): holds soil profile information

Profile (SoilProfile): jit class object holdsing soil profile information

Hydrology (pandas.DataFrame): holds soil layer hydrology informaiton

Comp (pandas.DataFrame): holds soil compartment information

Source code in aquacrop/entities/soil.py

class Soil:
    """
    The Soil Class contains Paramaters and variables of the soil used in the simulation

    More float attributes are specified in the initialisation of the class

    Attributes:

        profile (pandas.DataFrame): holds soil profile information

        Profile (SoilProfile): jit class object holdsing soil profile information

        Hydrology (pandas.DataFrame): holds soil layer hydrology informaiton

        Comp (pandas.DataFrame): holds soil compartment information


    """

    def __init__(
        self,
        soil_type,
        dz=[0.1] * 12,
        adj_rew=1,
        rew=9.0,
        calc_cn=0,
        cn=61.0,
        z_res=ModelConstants.NO_VALUE,
        evap_z_surf=0.04,
        evap_z_min=0.15,
        evap_z_max=0.30,
        kex=1.1,
        f_evap=4,
        f_wrel_exp=0.4,
        fwcc=50,
        z_cn=0.3,
        z_germ=0.3,
        adj_cn=1,
        fshape_cr=16,
        z_top=0.1,
    ):

        self.Name = soil_type

        self.zSoil = sum(dz)  # Total thickness of soil profile (m)
        self.nComp = len(dz)  # Total number of soil compartments
        self.nLayer = 0  # Total number of soil layers
        self.adj_rew = adj_rew  # Adjust default value for readily evaporable water (0 = No, 1 = Yes)
        self.rew = rew  # Readily evaporable water (mm) (only used if adjusting from default value)
        self.calc_cn = calc_cn  # adjust Curve number based on Ksat
        self.cn = cn  # Curve number  (0 = No, 1 = Yes)
        self.z_res = z_res  # Depth of restrictive soil layer (set to negative value if not present)

        # Assign default program properties (should not be changed without expert knowledge)
        self.evap_z_surf = (
            evap_z_surf  # Thickness of soil surface skin evaporation layer (m)
        )
        self.evap_z_min = (
            evap_z_min  # Minimum thickness of full soil surface evaporation layer (m)
        )
        self.evap_z_max = (
            evap_z_max  # Maximum thickness of full soil surface evaporation layer (m)
        )
        self.kex = kex  # Maximum soil evaporation coefficient
        self.f_evap = (
            f_evap  # Shape factor describing reduction in soil evaporation in stage 2.
        )
        self.f_wrel_exp = f_wrel_exp  # Proportional value of Wrel at which soil evaporation layer expands
        self.fwcc = fwcc  # Maximum coefficient for soil evaporation reduction due to sheltering effect of withered canopy
        self.z_cn = z_cn  # Thickness of soil surface (m) used to calculate water content to adjust curve number
        self.z_germ = z_germ  # Thickness of soil surface (m) used to calculate water content for germination
        self.adj_cn = (
            adj_cn  # Adjust curve number for antecedent moisture content (0: No, 1: Yes)
        )
        self.fshape_cr = fshape_cr  # Capillary rise shape factor
        self.z_top = max(
            z_top, dz[0]
        )  # Thickness of soil surface layer for water stress comparisons (m)

        if soil_type == "custom":
            self.create_df(dz)

        elif soil_type == "Clay":
            self.cn = 77
            self.calc_cn = 0
            self.rew = 14
            self.create_df(dz)
            self.add_layer(sum(dz), 0.39, 0.54, 0.55, 35, 100)

        elif soil_type == "ClayLoam":
            self.cn = 72
            self.calc_cn = 0
            self.rew = 11
            self.create_df(dz)
            self.add_layer(sum(dz), 0.23, 0.39, 0.5, 125, 100)

        elif soil_type == 'Default':
            self.cn = 61
            self.calc_cn = 0
            self.rew = 9
            self.create_df(dz)
            self.add_layer(sum(dz), 0.1, 0.3, 0.5, 500, 100)

        elif soil_type == "Loam":
            self.cn = 61
            self.calc_cn = 0
            self.rew = 9
            self.create_df(dz)
            self.add_layer(sum(dz), 0.15, 0.31, 0.46, 500, 100)

        elif soil_type == "LoamySand":
            self.cn = 46
            self.calc_cn = 0
            self.rew = 5
            self.create_df(dz)
            self.add_layer(sum(dz), 0.08, 0.16, 0.38, 2200, 100)

        elif soil_type == "Sand":
            self.cn = 46
            self.calc_cn = 0
            self.rew = 4
            self.create_df(dz)
            self.add_layer(sum(dz), 0.06, 0.13, 0.36, 3000, 100)

        elif soil_type == "SandyClay":
            self.cn = 77
            self.calc_cn = 0
            self.rew = 10
            self.create_df(dz)
            self.add_layer(sum(dz), 0.27, 0.39, 0.5, 35, 100)

        elif soil_type == "SandyClayLoam":
            self.cn = 72
            self.calc_cn = 0
            self.rew = 9
            self.create_df(dz)
            self.add_layer(sum(dz), 0.20, 0.32, 0.47, 225, 100)

        elif soil_type == "SandyLoam":
            self.cn = 46
            self.calc_cn = 0
            self.rew = 7
            self.create_df(dz)
            self.add_layer(sum(dz), 0.10, 0.22, 0.41, 1200, 100)

        elif soil_type == "Silt":
            self.cn = 61
            self.calc_cn = 0
            self.rew = 11
            self.create_df(dz)
            self.add_layer(sum(dz), 0.09, 0.33, 0.43, 500, 100)

        elif soil_type == "SiltClayLoam":
            self.cn = 72
            self.calc_cn = 0
            self.rew = 13
            self.create_df(dz)
            self.add_layer(sum(dz), 0.23, 0.44, 0.52, 150, 100)

        elif soil_type == "SiltLoam":
            self.cn = 61
            self.calc_cn = 0
            self.rew = 11
            self.create_df(dz)
            self.add_layer(sum(dz), 0.13, 0.33, 0.46, 575, 100)

        elif soil_type == "SiltClay":
            self.cn = 72
            self.calc_cn = 0
            self.rew = 14
            self.create_df(dz)
            self.add_layer(sum(dz), 0.32, 0.50, 0.54, 100, 100)

        elif soil_type == "Paddy":
            self.cn = 77
            self.calc_cn = 0
            self.rew = 10
            self.create_df(dz)
            self.add_layer(0.5, 0.32, 0.50, 0.54, 15, 100)
            self.add_layer(1.5, 0.39, 0.54, 0.55, 2, 100)

        elif soil_type == "ac_TunisLocal":
            self.cn = 72
            self.calc_cn = 0
            self.rew = 11
            dz = [0.1] * 6 + [0.15] * 5 + [0.2]
            self.create_df(dz)
            self.add_layer(0.3, 0.24, 0.40, 0.50, 155, 100)
            self.add_layer(1.7, 0.11, 0.33, 0.46, 500, 100)

        else:
            print("wrong soil type")
            assert 1 == 2

    def __repr__(self):
        for key in self.__dict__:
            if key != "profile":
                print(f"{key}: {getattr(self,key)}")

        return " "

    def create_df(self, dz):

        self.profile = pd.DataFrame(
            np.empty((len(dz), 4)), columns=["Comp", "Layer", "dz", "dzsum"]
        )
        self.profile.dz = dz
        self.profile.dzsum = np.cumsum(self.profile.dz).round(2)
        self.profile.Comp = np.arange(len(dz))
        self.profile.Layer = np.nan

        self.profile["zBot"] = self.profile.dzsum
        self.profile["z_top"] = self.profile["zBot"] - self.profile.dz
        self.profile["zMid"] = (self.profile["z_top"] + self.profile["zBot"]) / 2

    def calculate_soil_hydraulic_properties(self, Sand, Clay, OrgMat, DF=1):

        """
        Function to calculate soil hydraulic properties, given textural inputs.
        Calculations use pedotransfer function equations described in Saxton and Rawls (2006)


        """

        # do calculations

        # Water content at permanent wilting point
        Pred_thWP = (
            -(0.024 * Sand)
            + (0.487 * Clay)
            + (0.006 * OrgMat)
            + (0.005 * Sand * OrgMat)
            - (0.013 * Clay * OrgMat)
            + (0.068 * Sand * Clay)
            + 0.031
        )

        th_wp = Pred_thWP + (0.14 * Pred_thWP) - 0.02

        # Water content at field capacity and saturation
        Pred_thFC = (
            -(0.251 * Sand)
            + (0.195 * Clay)
            + (0.011 * OrgMat)
            + (0.006 * Sand * OrgMat)
            - (0.027 * Clay * OrgMat)
            + (0.452 * Sand * Clay)
            + 0.299
        )

        PredAdj_thFC = Pred_thFC + (
            (1.283 * (np.power(Pred_thFC, 2))) - (0.374 * Pred_thFC) - 0.015
        )

        Pred_thS33 = (
            (0.278 * Sand)
            + (0.034 * Clay)
            + (0.022 * OrgMat)
            - (0.018 * Sand * OrgMat)
            - (0.027 * Clay * OrgMat)
            - (0.584 * Sand * Clay)
            + 0.078
        )

        PredAdj_thS33 = Pred_thS33 + ((0.636 * Pred_thS33) - 0.107)
        Pred_thS = (PredAdj_thFC + PredAdj_thS33) + ((-0.097 * Sand) + 0.043)

        pN = (1 - Pred_thS) * 2.65
        pDF = pN * DF
        PorosComp = (1 - (pDF / 2.65)) - (1 - (pN / 2.65))
        PorosCompOM = 1 - (pDF / 2.65)

        DensAdj_thFC = PredAdj_thFC + (0.2 * PorosComp)
        DensAdj_thS = PorosCompOM

        th_fc = DensAdj_thFC
        th_s = DensAdj_thS

        # Saturated hydraulic conductivity (mm/day)
        lmbda = 1 / ((np.log(1500) - np.log(33)) / (np.log(th_fc) - np.log(th_wp)))
        Ksat = (1930 * (th_s - th_fc) ** (3 - lmbda)) * 24

        # Water content at air dry
        th_dry = th_wp / 2

        # round values
        th_dry = round(10_000 * th_dry) / 10_000
        th_wp = round(1000 * th_wp) / 1000
        th_fc = round(1000 * th_fc) / 1000
        th_s = round(1000 * th_s) / 1000
        Ksat = round(10 * Ksat) / 10

        return th_wp, th_fc, th_s, Ksat

    def add_layer_from_texture(self, thickness, Sand, Clay, OrgMat, penetrability):

        th_wp, th_fc, th_s, Ksat = self.calculate_soil_hydraulic_properties(
            Sand / 100, Clay / 100, OrgMat
        )

        self.add_layer(thickness, th_wp, th_fc, th_s, Ksat, penetrability)

    def add_layer(self, thickness, thWP, thFC, thS, Ksat, penetrability):

        self.nLayer += 1

        num_layers = len(self.profile.dropna().Layer.unique())

        new_layer = num_layers + 1

        if new_layer == 1:
            self.profile.loc[
                (round(thickness, 2) >= round(self.profile.dzsum, 2)), "Layer"
            ] = new_layer
        else:
            last = self.profile[self.profile.Layer == new_layer - 1].dzsum.values[-1]
            self.profile.loc[
                (thickness + last >= self.profile.dzsum) & (self.profile.Layer.isna()),
                "Layer",
            ] = new_layer

        self.profile.loc[
            self.profile.Layer == new_layer, "th_dry"
        ] = self.profile.Layer.map({new_layer: thWP / 2})
        self.profile.loc[
            self.profile.Layer == new_layer, "th_wp"
        ] = self.profile.Layer.map({new_layer: thWP})
        self.profile.loc[
            self.profile.Layer == new_layer, "th_fc"
        ] = self.profile.Layer.map({new_layer: thFC})
        self.profile.loc[
            self.profile.Layer == new_layer, "th_s"
        ] = self.profile.Layer.map({new_layer: thS})
        self.profile.loc[
            self.profile.Layer == new_layer, "Ksat"
        ] = self.profile.Layer.map({new_layer: Ksat})
        self.profile.loc[
            self.profile.Layer == new_layer, "penetrability"
        ] = self.profile.Layer.map({new_layer: penetrability})

        # Calculate drainage characteristic (tau)
        # Calculations use equation given by Raes et al. 2012
        tau = round(0.0866 * (Ksat**0.35), 2)
        if tau > 1:
            tau = 1
        elif tau < 0:
            tau = 0

        self.profile.loc[
            self.profile.Layer == new_layer, "tau"
        ] = self.profile.Layer.map({new_layer: tau})

    def fill_nan(
        self,
    ):

        self.profile = self.profile.fillna(method="ffill")

        self.profile.dz = self.profile.dz.round(2)

        self.profile.dzsum = self.profile.dz.cumsum().round(2)

        self.zSoil = round(self.profile.dz.sum(), 2)

        self.nComp = len(self.profile)

        self.profile.Layer = self.profile.Layer.astype(int)

    def add_capillary_rise_params(
        self,
    ):
        # Calculate capillary rise parameters for all soil layers
        # Only do calculation if water table is present. Calculations use equations
        # described in Raes et al. (2012)
        prof = self.profile

        hydf = prof.groupby("Layer").mean().drop(["dz", "dzsum"], axis=1)

        hydf["aCR"] = 0
        hydf["bCR"] = 0

        for layer in hydf.index.unique():
            layer = int(layer)

            soil = hydf.loc[layer]

            thwp = soil.th_wp
            thfc = soil.th_fc
            ths = soil.th_s
            Ksat = soil.Ksat

            # usually just initialise here (both 0), but temporarily hard-coding for sandy-loam for testing
            aCR =  0
            bCR =  0

            # Define aCR and bCR calculations for each Soil Class 
            aCR_sandy=-0.3112 - Ksat/100000
            bCR_sandy=-1.4936 + 0.2416*np.log(Ksat)

            aCR_loamy=-0.4986 + 9*Ksat/100000
            bCR_loamy=-2.1320 + 0.4778*np.log(Ksat)

            aCR_sandy_clayey=-0.5677 - 4*Ksat/100000
            bCR_sandy_clayey=-3.7189 + 0.5922*np.log(Ksat)

            aCR_silty_clayey=-0.6366 + 8*Ksat/10000
            bCR_silty_clayey=-1.9165 + 0.7063*np.log(Ksat)

            # NEW (V7) aCR bCR calculations logic
            # Assign aCR/bCR based on soil class definition from FAO
            if ths <= 0.55:
                if thwp >= 0.20:
                    if (ths >= 0.49) and (thfc >= 0.40):
                        aCR=aCR_silty_clayey
                        bCR=bCR_silty_clayey
                    else:
                        aCR=aCR_sandy_clayey
                        bCR=bCR_sandy_clayey
                else:
                    if thfc < 0.23:
                        aCR=aCR_sandy
                        bCR=bCR_sandy
                    else:
                        if (thwp > 0.16) and (Ksat < 100):
                            aCR=aCR_sandy_clayey
                            bCR=bCR_sandy_clayey
                        else:
                            if (thwp < 0.06) and (thfc < 0.28) and (Ksat > 750):
                                aCR=aCR_sandy
                                bCR=bCR_sandy
                            else:
                                aCR=aCR_loamy
                                bCR=bCR_loamy
            else:
                aCR=aCR_silty_clayey
                bCR=bCR_silty_clayey






            # OLD (V6) aCR bCR calculation logic
            # if (
            #     (thwp >= 0.04)
            #     and (thwp <= 0.15)
            #     and (thfc >= 0.09)
            #     and (thfc <= 0.28)
            #     and (ths >= 0.32)
            #     and (ths <= 0.51)
            # ):

            #     # Sandy soil class
            #     if (Ksat >= 200) and (Ksat <= 2000):
            #         aCR = -0.3112 - (Ksat * (1e-5))
            #         bCR = -1.4936 + (0.2416 * np.log(Ksat))
            #     elif Ksat < 200:
            #         aCR = -0.3112 - (200 * (1e-5))
            #         bCR = -1.4936 + (0.2416 * np.log(200))
            #     elif Ksat > 2000:
            #         aCR = -0.3112 - (2000 * (1e-5))
            #         bCR = -1.4936 + (0.2416 * np.log(2000))

            # elif (
            #     (thwp >= 0.06)
            #     and (thwp <= 0.20)
            #     and (thfc >= 0.23)
            #     and (thfc <= 0.42)
            #     and (ths >= 0.42)
            #     and (ths <= 0.55)
            # ):

            #     # Loamy soil class
            #     if (Ksat >= 100) and (Ksat <= 750):
            #         aCR = -0.4986 + (9 * (1e-5) * Ksat)
            #         bCR = -2.132 + (0.4778 * np.log(Ksat))
            #     elif Ksat < 100:
            #         aCR = -0.4986 + (9 * (1e-5) * 100)
            #         bCR = -2.132 + (0.4778 * np.log(100))
            #     elif Ksat > 750:
            #         aCR = -0.4986 + (9 * (1e-5) * 750)
            #         bCR = -2.132 + (0.4778 * np.log(750))

            # elif (
            #     (thwp >= 0.16)
            #     and (thwp <= 0.34)
            #     and (thfc >= 0.25)
            #     and (thfc <= 0.45)
            #     and (ths >= 0.40)
            #     and (ths <= 0.53)
            # ):

            #     # Sandy clayey soil class
            #     if (Ksat >= 5) and (Ksat <= 150):
            #         aCR = -0.5677 - (4 * (1e-5) * Ksat)
            #         bCR = -3.7189 + (0.5922 * np.log(Ksat))
            #     elif Ksat < 5:
            #         aCR = -0.5677 - (4 * (1e-5) * 5)
            #         bCR = -3.7189 + (0.5922 * np.log(5))
            #     elif Ksat > 150:
            #         aCR = -0.5677 - (4 * (1e-5) * 150)
            #         bCR = -3.7189 + (0.5922 * np.log(150))

            # elif (
            #     (thwp >= 0.20)
            #     and (thwp <= 0.42)
            #     and (thfc >= 0.40)
            #     and (thfc <= 0.58)
            #     and (ths >= 0.49)
            #     and (ths <= 0.58)
            # ):

            #     # Silty clayey soil class
            #     if (Ksat >= 1) and (Ksat <= 150):
            #         aCR = -0.6366 + (8 * (1e-4) * Ksat)
            #         bCR = -1.9165 + (0.7063 * np.log(Ksat))
            #     elif Ksat < 1:
            #         aCR = -0.6366 + (8 * (1e-4) * 1)
            #         bCR = -1.9165 + (0.7063 * np.log(1))
            #     elif Ksat > 150:
            #         aCR = -0.6366 + (8 * (1e-4) * 150)
            #         bCR = -1.9165 + (0.7063 * np.log(150))

            assert aCR != 0
            assert bCR != 0

            prof.loc[prof.Layer == layer, "aCR"] = prof.Layer.map({layer: aCR})
            prof.loc[prof.Layer == layer, "bCR"] = prof.Layer.map({layer: bCR})

        self.profile = prof

calculate_soil_hydraulic_properties(Sand, Clay, OrgMat, DF=1)

Function to calculate soil hydraulic properties, given textural inputs. Calculations use pedotransfer function equations described in Saxton and Rawls (2006)

Source code in aquacrop/entities/soil.py

def calculate_soil_hydraulic_properties(self, Sand, Clay, OrgMat, DF=1):

    """
    Function to calculate soil hydraulic properties, given textural inputs.
    Calculations use pedotransfer function equations described in Saxton and Rawls (2006)


    """

    # do calculations

    # Water content at permanent wilting point
    Pred_thWP = (
        -(0.024 * Sand)
        + (0.487 * Clay)
        + (0.006 * OrgMat)
        + (0.005 * Sand * OrgMat)
        - (0.013 * Clay * OrgMat)
        + (0.068 * Sand * Clay)
        + 0.031
    )

    th_wp = Pred_thWP + (0.14 * Pred_thWP) - 0.02

    # Water content at field capacity and saturation
    Pred_thFC = (
        -(0.251 * Sand)
        + (0.195 * Clay)
        + (0.011 * OrgMat)
        + (0.006 * Sand * OrgMat)
        - (0.027 * Clay * OrgMat)
        + (0.452 * Sand * Clay)
        + 0.299
    )

    PredAdj_thFC = Pred_thFC + (
        (1.283 * (np.power(Pred_thFC, 2))) - (0.374 * Pred_thFC) - 0.015
    )

    Pred_thS33 = (
        (0.278 * Sand)
        + (0.034 * Clay)
        + (0.022 * OrgMat)
        - (0.018 * Sand * OrgMat)
        - (0.027 * Clay * OrgMat)
        - (0.584 * Sand * Clay)
        + 0.078
    )

    PredAdj_thS33 = Pred_thS33 + ((0.636 * Pred_thS33) - 0.107)
    Pred_thS = (PredAdj_thFC + PredAdj_thS33) + ((-0.097 * Sand) + 0.043)

    pN = (1 - Pred_thS) * 2.65
    pDF = pN * DF
    PorosComp = (1 - (pDF / 2.65)) - (1 - (pN / 2.65))
    PorosCompOM = 1 - (pDF / 2.65)

    DensAdj_thFC = PredAdj_thFC + (0.2 * PorosComp)
    DensAdj_thS = PorosCompOM

    th_fc = DensAdj_thFC
    th_s = DensAdj_thS

    # Saturated hydraulic conductivity (mm/day)
    lmbda = 1 / ((np.log(1500) - np.log(33)) / (np.log(th_fc) - np.log(th_wp)))
    Ksat = (1930 * (th_s - th_fc) ** (3 - lmbda)) * 24

    # Water content at air dry
    th_dry = th_wp / 2

    # round values
    th_dry = round(10_000 * th_dry) / 10_000
    th_wp = round(1000 * th_wp) / 1000
    th_fc = round(1000 * th_fc) / 1000
    th_s = round(1000 * th_s) / 1000
    Ksat = round(10 * Ksat) / 10

    return th_wp, th_fc, th_s, Ksat

aquacrop.entities.soilProfile

SoilProfile

Attributes:

Comp : list :

Layer : list :

dz : list :

dzsum : list :

zBot : list :

z_top : list :

zMid : list :

Source code in aquacrop/entities/soilProfile.py

class SoilProfile:
    """

    **Attributes:**\n

    `Comp` : `list` :

    `Layer` : `list` :

    `dz` : `list` :

    `dzsum` : `list` :

    `zBot` : `list` :

    `z_top` : `list` :

    `zMid` : `list` :

    """

    def __init__(self, length):

        self.Comp = np.zeros(length, dtype=np.int64)
        self.dz = np.zeros(length, dtype=np.float64)
        self.Layer = np.zeros(length, dtype=np.int64)
        self.dzsum = np.zeros(length, dtype=np.float64)
        self.th_fc = np.zeros(length, dtype=np.float64)
        self.th_s = np.zeros(length, dtype=np.float64)
        self.th_wp = np.zeros(length, dtype=np.float64)
        self.Ksat = np.zeros(length, dtype=np.float64)
        self.Penetrability = np.zeros(length, dtype=np.float64)
        self.th_dry = np.zeros(length, dtype=np.float64)
        self.tau = np.zeros(length, dtype=np.float64)
        self.zBot = np.zeros(length, dtype=np.float64)
        self.z_top = np.zeros(length, dtype=np.float64)
        self.zMid = np.zeros(length, dtype=np.float64)
        self.th_fc_Adj = np.zeros(length, dtype=np.float64)
        self.aCR = np.zeros(length, dtype=np.float64)
        self.bCR = np.zeros(length, dtype=np.float64)

aquacrop.entities.temperatureStressCoefficients

Kst

Bases: object

TODO: THIS CLASS IS NOT USED

temperature stress coefficients

Attributes:

PolH : float : heat stress

PolC : float : cold stress

Source code in aquacrop/entities/temperatureStressCoefficients.py

class Kst(object):

    """

    TODO: THIS CLASS IS NOT USED

    temperature stress coefficients

    **Attributes:**\n


    `PolH` : `float` : heat stress

    `PolC` : `float` : cold stress


    """

    def __init__(self):
        self.PolH = 1.0
        self.PolC = 1.0

aquacrop.entities.totalAvailableWater

TAW

TODO: THIS CLASS IS NOT USED - seems to now be in use, CB 14.09.23 Attributes:

Rz : float : .

Zt : float : .

Source code in aquacrop/entities/totalAvailableWater.py

class TAW:
    """
    TODO: THIS CLASS IS NOT USED - seems to now be in use, CB 14.09.23
    **Attributes:**\n



    `Rz` : `float` : .

    `Zt` : `float` : .




    """

    def __init__(self):
        self.Rz = 0.0
        self.Zt = 0.0

aquacrop.entities.waterEvaporation

WaterEvaporation

Bases: object

TODO: THIS CLASS IS NOT USED

stores soil water contents in the evaporation layer

Attributes:

Sat : float : Water storage in evaporation layer at saturation (mm)

Fc : float : Water storage in evaporation layer at Field Capacity (mm)

Wp : float: Water storage in evaporation layer at Wilting Point (mm)

Dry : float : Water storage in evaporation layer at air dry (mm)

Act : float : Actual Water storage in evaporation layer (mm)

Source code in aquacrop/entities/waterEvaporation.py

class WaterEvaporation(object):
    """
    TODO: THIS CLASS IS NOT USED

    stores soil water contents in the evaporation layer

    **Attributes:**\n


    `Sat` : `float` :  Water storage in evaporation layer at saturation (mm)

    `Fc` : `float` :  Water storage in evaporation layer at Field Capacity (mm)

    `Wp` : `float`:  Water storage in evaporation layer at Wilting Point (mm)

    `Dry` : `float` : Water storage in evaporation layer at air dry (mm)

    `Act` : `float` : Actual Water storage in evaporation layer (mm)

    """

    def __init__(self):
        self.Sat = 0.0
        self.Fc = 0.0
        self.Wp = 0.0
        self.Dry = 0.0
        self.Act = 0.0

aquacrop.entities.waterStressCoefficients

Ksw

Bases: object

water stress coefficients

Attributes:

exp : float : .

sto : float : .

sen : float : .

pol : float : .

sto_lin : float : .

Source code in aquacrop/entities/waterStressCoefficients.py

class Ksw(object):

    """
    water stress coefficients

    **Attributes:**\n


    `exp` : `float` : .

    `sto` : `float` : .

    `sen` : `float` : .

    `pol` : `float` : .

    `sto_lin` : `float` : .



    """

    def __init__(self):
        self.exp = 1.0
        self.sto = 1.0
        self.sen = 1.0
        self.pol = 1.0
        self.sto_lin = 1.0