API Reference - Land

This section of the documentation provides a reference for the API of the nodes.land and nodes.nutrient_pool modules.

Created on Fri May 20 08:58:58 2022.

@author: Barney

GardenSurface

Bases: GrowingSurface

Source code in wsimod\nodes\land.py

class GardenSurface(GrowingSurface):
    """"""

    # TODO - probably a simplier version of this is useful, building just on
    # pervioussurface
    def __init__(self, **kwargs):
        """A specific surface for gardens that treats the garden as a grass crop, but
        that can calculate/receive irrigation through functions that are assigned by the
        parent land node's handlers, which in turn are expected to be triggered by a
        query from an attached Demand node."""
        super().__init__(**kwargs)

    def calculate_irrigation_demand(self, ignore_vqip=None):
        """A check function (assigned by parent to push check from demand nodes) that
        calculations irrigation demand (i.e., difference between evaporation and
        preciptiation).

        Args:
            ignore_vqip (any, optional): Conventional push checks send an optional
                VQIP amount, however the intention with this check is to get the
                irrigation demand

        Returns:
            reply (dict): A VQIP amount of irrigation demand (note only 'volume' key
                is used)
        """
        # Calculate irrigation demand
        irrigation_demand = max(
            self.evaporation["volume"] - self.precipitation["volume"], 0
        )

        root_zone_depletion = self.get_cmd()
        if root_zone_depletion <= constants.FLOAT_ACCURACY:
            # TODO this isn't in FAO... but seems sensible
            irrigation_demand = 0

        # Reply as VQIP
        reply = self.empty_vqip()
        reply["volume"] = irrigation_demand
        return reply

    def receive_irrigation_demand(self, vqip):
        """A set function (assigned by parent to push set from demand nodes) that
        assigns irrigation water supply to the surface tank.

        Args:
            vqip (dict): A VQIP amount of irrigation to receive

        Returns:
            (dict): A VQIP amount of irrigation that was not received (should always
                be empty)
        """
        # update tank
        return self.push_storage(vqip, force=True)

__init__(**kwargs)

A specific surface for gardens that treats the garden as a grass crop, but that can calculate/receive irrigation through functions that are assigned by the parent land node's handlers, which in turn are expected to be triggered by a query from an attached Demand node.

Source code in wsimod\nodes\land.py

def __init__(self, **kwargs):
    """A specific surface for gardens that treats the garden as a grass crop, but
    that can calculate/receive irrigation through functions that are assigned by the
    parent land node's handlers, which in turn are expected to be triggered by a
    query from an attached Demand node."""
    super().__init__(**kwargs)

calculate_irrigation_demand(ignore_vqip=None)

A check function (assigned by parent to push check from demand nodes) that calculations irrigation demand (i.e., difference between evaporation and preciptiation).

Parameters:

Name	Type	Description	Default
ignore_vqip	any	Conventional push checks send an optional VQIP amount, however the intention with this check is to get the irrigation demand	None

Returns:

Name	Type	Description
reply	dict	A VQIP amount of irrigation demand (note only 'volume' key is used)

Source code in wsimod\nodes\land.py

def calculate_irrigation_demand(self, ignore_vqip=None):
    """A check function (assigned by parent to push check from demand nodes) that
    calculations irrigation demand (i.e., difference between evaporation and
    preciptiation).

    Args:
        ignore_vqip (any, optional): Conventional push checks send an optional
            VQIP amount, however the intention with this check is to get the
            irrigation demand

    Returns:
        reply (dict): A VQIP amount of irrigation demand (note only 'volume' key
            is used)
    """
    # Calculate irrigation demand
    irrigation_demand = max(
        self.evaporation["volume"] - self.precipitation["volume"], 0
    )

    root_zone_depletion = self.get_cmd()
    if root_zone_depletion <= constants.FLOAT_ACCURACY:
        # TODO this isn't in FAO... but seems sensible
        irrigation_demand = 0

    # Reply as VQIP
    reply = self.empty_vqip()
    reply["volume"] = irrigation_demand
    return reply

receive_irrigation_demand(vqip)

A set function (assigned by parent to push set from demand nodes) that assigns irrigation water supply to the surface tank.

Parameters:

Name	Type	Description	Default
vqip	dict	A VQIP amount of irrigation to receive	required

Returns:

Type	Description
dict	A VQIP amount of irrigation that was not received (should always be empty)

Source code in wsimod\nodes\land.py

def receive_irrigation_demand(self, vqip):
    """A set function (assigned by parent to push set from demand nodes) that
    assigns irrigation water supply to the surface tank.

    Args:
        vqip (dict): A VQIP amount of irrigation to receive

    Returns:
        (dict): A VQIP amount of irrigation that was not received (should always
            be empty)
    """
    # update tank
    return self.push_storage(vqip, force=True)

GrowingSurface

Bases: PerviousSurface

Source code in wsimod\nodes\land.py

class GrowingSurface(PerviousSurface):
    """"""

    def __init__(
        self,
        rooting_depth=1,
        ET_depletion_factor=1,
        crop_factor_stages=[1, 1],
        crop_factor_stage_dates=[0, 365],
        sowing_day=1,
        harvest_day=365,
        initial_soil_storage=None,
        **kwargs,
    ):
        """Extensive surface subclass that implements the CatchWat equations (Liu,
        Dobson & Mijic (2022) Science of the total environment), which in turn are
        primarily based on FAO document:
        https://www.fao.org/3/x0490e/x0490e0ehtm#soil%20water%20availability. This
        surface is a pervious surface that also has things that grow on it. This
        behaviour includes soil nutrient pools, crop planting/harvest calendars,
        erosion, crop behaviour.

        A key complexity of this surface is the nutrient pool (see wsimod/nodes/
        nutrient_pool.py), which is a class that tracks the amount of phosphorus and
        nitrogen in different states and performs transformations that occur in the
        phosphorus/nitrogen cycle. It is assumed that the phosphate/nitrate/nitrite/
        ammonia amounts in this Surface tank should track the dissolved inorganic pool
        in the nutrient pool. Meanwhile, the org-phosphorus/org-nitrogen amounts in this
        tank should track the dissolved organic pool in the nutrient pool. The total
        amount of pollutants that enter this tank may not be the same as the total
        amount that leave, because pollutants are transformed between inorganic/ organic
        and between wet/dry states - these transformations are accounted for in mass
        balance.

        For users to quickly enable/disable these nutrient processes, which are
        computationally intensive (in current case studies they account for about half
        of the total runtime), they are only active if 'nitrate' is one of the modelled
        pollutants. Note that the code will not check if nitrite/phosphate/
        org-phosphorus/org-nitrogen/ammonia are also included, but they should be if
        nitrate is included and otherwise the code will crash with a key error.

        Args:
            rooting_depth (float, optional): Depth of the soil tank (i.e., how deep do
                crop roots go). Defaults to 1.
            ET_depletion_factor (float, optional): Average fraction of soil that can be
                depleted from the root zone before moisture stress (reduction in ET)
                occurs. Defaults to 1.
            crop_factor_stages (list, optional): Crop factor is a multiplier on et0,
                more grown plants have higher transpiration and higher crop factors.
                This list shows changing crop factor at different times of year in
                relation to crop_factor_stage_dates. See wsimod/preprocessing/
                england_data_formatting.py/format_surfaces for further details on
                formulating these - since the interpolation used to find crop_factors in
                between the given values in the list is a bit involved. Defaults to
                [1,1].
            crop_factor_stage_dates (list, optional): Dates associated with
                crop_factor_stages. Defaults to [0, 365].
            sowing_day (int, optional): day of year that crops are sown. Defaults to 1.
            harvest_day (int, optional): day of year that crops are harvest. Defaults
                to 365.
            initial_soil_storage (dict or float, optional): Initial mass of solid
            pollutants
                in the soil nutrient pools (fast and adsorbed inorganic pools)

        Key assumptions:
             - In the soil water module, crop stages and crop coefficients control the
               evapotranspiration.
             - Fertiliser and manure application are the major source of soil nutrients,
               which are added
                into soil nutrient pools, including dissovled inorganic, dissolved
                organic, fast and humus for both nitrogen and phosphorus.
             - Nutrient transformation processes in soil are simulated, including fluxes
               between the soil
                nutrient pools, denitrification for nitrogen, adsorption/desorption for
                phosphorus. These processes are affected by temperature and soil
                moisture.
             - Crop uptake of nutrients are simulated based on crop stages, which is
               different for spring-sown
                and autumn-sown crops.
             - Soil erosion from the growing surface is simulated as one of the major
               sources of suspended solids
                in rivers, which is mainly affected by rainfall energy and crop/ground
                cover. Phosphorus will also be eroded along with the soil particles, in
                both adsorbed inorganic and humus form.

        Input data and parameter requirements:
             - `data_input_dict` can contain a variety of pollutant deposition data.
                `srp-fertiliser` describes phosphate. `noy-fertiliser` describes
                nitrogen as nitrates. `nhx-fertiliser` describes nitrogen as ammonia.
                `srp/noy/ nhx-manure` can also be used to specify manure application.
                _Units_: kg/m2/timestep (data is read at a monthly timestep)
             - Rooting depth.
                _Units_: m
             - Evapotranspiration depletion factor.
                _Units_: -
             - Sowing day, harvest day and crop calendars.
                _Units_: day number in Julian calendar
             - Crop factor.
                _Units_: -
             - Initial storage for solid pollutants.
                _Units_: kg

        """
        # Crop factors (set when creating object)
        self.ET_depletion_factor = (
            ET_depletion_factor  # To do with water availability, p from FAOSTAT
        )
        self.rooting_depth = (
            rooting_depth  # maximum depth that plants can absorb, Zr from FAOSTAT
        )
        depth = rooting_depth

        # Crop parameters
        self.crop_cover_max = 0.9  # [-] 0~1
        self.ground_cover_max = 0.3  # [-]
        # TODO... really I should just have this as an annual profile parameter and do
        # away with interpolation etc.
        self.crop_factor_stages = crop_factor_stages
        self.crop_factor_stage_dates = crop_factor_stage_dates
        self.sowing_day = sowing_day
        self.harvest_day = harvest_day

        # Soil moisture dependence parameters
        self.satact = 0.6  # [-] for calculating soil_moisture_dependence_factor
        self.thetaupp = 0.12  # [-] for calculating soil_moisture_dependence_factor
        self.thetalow = 0.08  # [-] for calculating soil_moisture_dependence_factor
        self.thetapow = 1  # [-] for calculating soil_moisture_dependence_factorself.
        # satact = 0.6 # [-] for calculating soil_moisture_dependence_factor

        # Crop uptake parameters
        self.uptake1 = (
            15  # [g/m2/y] shape factor for crop (Dissolved) Inorganic nitrogen uptake
        )
        self.uptake2 = (
            1  # [-] shape factor for crop (Dissolved) Inorganic nitrogen uptake
        )
        self.uptake3 = (
            0.02  # [1/day] shape factor for crop (Dissolved) Inorganic nitrogen uptake
        )
        self.uptake_PNratio = 1 / 7.2  # [-] P:N during crop uptake

        # Erosion parameters
        self.erodibility = 0.0025  # [g * d / (J * mm)]
        self.sreroexp = 1.2  # [-] surface runoff erosion exponent
        self.cohesion = 1  # [kPa]
        self.slope = 5  # [-] every 100
        self.srfilt = (
            0.7  # [-] ratio of eroded sediment left in surface runoff after filtration
        )
        self.macrofilt = 0.01  # [-] ratio of eroded sediment left in subsurface flow
        # after filtration

        # Denitrification parameters
        self.limpar = 0.7  # [-] above which denitrification begins
        self.exppar = 2.5  # [-] exponential parameter for
        # soil_moisture_dependence_factor_exp calculation
        self.hsatINs = 1  # [mg/l] for calculation of half-saturation concentration
        # dependence factor
        self.denpar = 0.015  # [-] denitrification rate coefficient

        # Adsorption parameters
        self.adosorption_nr_limit = 0.00001
        self.adsorption_nr_maxiter = 20
        self.kfr = 153.7  # [litter/kg] freundlich adsorption isoterm
        self.nfr = 1 / 2.6  # [-] freundlich exponential coefficient
        self.kadsdes = 0.03  # [1/day] adsorption/desorption coefficient

        # Other soil parameters
        self.bulk_density = 1300  # [kg/m3]
        super().__init__(depth=depth, **kwargs)

        (
            self.harvest_sow_calendar,
            self.ground_cover_stages,
            self.crop_cover_stages,
            self.autumn_sow,
        ) = self.infer_sow_harvest_calendar()

        # State variables
        self.days_after_sow = None
        self.crop_cover = 0
        self.ground_cover = 0
        self.crop_factor = 0
        self.et0_coefficient = 1

        (
            self.total_available_water,
            self.readily_available_water,
        ) = self.calculate_available_water()

        # Initiliase nutrient pools
        self.nutrient_pool = NutrientPool()

        self.inflows.insert(0, self.calc_crop_cover)
        if "nitrate" in constants.POLLUTANTS:
            # Populate function lists
            self.inflows.append(self.effective_precipitation_flushing)
            self.inflows.append(self.fertiliser)
            self.inflows.append(self.manure)
            # self.inflows.append(self.residue)

            self.processes.append(self.calc_temperature_dependence_factor)
            self.processes.append(self.calc_soil_moisture_dependence_factor)
            self.processes.append(self.soil_pool_transformation)
            self.processes.append(self.calc_crop_uptake)

            # TODO possibly move these into nutrient pool
            self.processes.append(self.erosion)
            self.processes.append(self.denitrification)
            self.processes.append(self.adsorption)

            # Reflect initial water concentration in dissolved nutrient pools
            self.nutrient_pool.dissolved_inorganic_pool.storage["P"] = self.storage[
                "phosphate"
            ]
            self.nutrient_pool.dissolved_inorganic_pool.storage["N"] = (
                self.storage["nitrate"]
                + self.storage["ammonia"]
                + self.storage["nitrite"]
            )
            self.nutrient_pool.dissolved_organic_pool.storage["P"] = self.storage[
                "org-phosphorus"
            ]
            self.nutrient_pool.dissolved_organic_pool.storage["N"] = self.storage[
                "org-nitrogen"
            ]
            if initial_soil_storage:
                self.initial_soil_storage = initial_soil_storage
                # Reflect initial nutrient stores in solid nutrient pools
                self.nutrient_pool.adsorbed_inorganic_pool.storage["P"] = (
                    initial_soil_storage["phosphate"]
                )
                self.nutrient_pool.adsorbed_inorganic_pool.storage["N"] = (
                    initial_soil_storage["ammonia"]
                    + initial_soil_storage["nitrate"]
                    + initial_soil_storage["nitrite"]
                )
                self.nutrient_pool.fast_pool.storage["N"] = initial_soil_storage[
                    "org-nitrogen"
                ]
                self.nutrient_pool.fast_pool.storage["P"] = initial_soil_storage[
                    "org-phosphorus"
                ]

    def infer_sow_harvest_calendar(self):
        """Infer basic sow/harvest calendar and indicate autumn-sown.
        Returns:
            (list): havest/sow calendar
            (list): ground cover stages
            (list): crop cover stages
            (boolean): indication for autumn-sown crops
        """
        # Infer basic sow/harvest calendar
        harvest_sow_calendar = [
            0,
            self.sowing_day,
            self.harvest_day,
            self.harvest_day + 1,
            365,
        ]
        ground_cover_stages = [0, 0, self.ground_cover_max, 0, 0]
        crop_cover_stages = [0, 0, self.crop_cover_max, 0, 0]

        # Use day number of 181 to indicate autumn-sown (from HYPE)
        if self.sowing_day > 181:
            autumn_sow = True
        else:
            autumn_sow = False

        return harvest_sow_calendar, ground_cover_stages, crop_cover_stages, autumn_sow

    def calculate_available_water(self):
        """Calculate total/readily available water based on capacity/wp.
        Returns:
            (float): total available water
            (float): readily available water
        """
        # Calculate parameters based on capacity/wp
        total_available_water = self.field_capacity_m - self.wilting_point_m
        if total_available_water < 0:
            print("warning: TAW < 0...")
        readily_available_water = total_available_water * self.ET_depletion_factor

        return total_available_water, readily_available_water

    def apply_overrides(self, overrides=Dict[str, Any]):
        """Override parameters.

        Enables a user to override any of the following parameters

        Args:
            overrides (Dict[str, Any]): Dict describing which parameters should
                be overridden (keys) and new values (values). Defaults to {}.
        """
        overwrite_params = [
            "ET_depletion_factor",
            "crop_cover_max",
            "ground_cover_max",
            "crop_factor_stages",
            "crop_factor_stage_dates",
            "sowing_day",
            "harvest_day",
            "satact",
            "thetaupp",
            "thetalow",
            "thetapow",
            "uptake1",
            "uptake2",
            "uptake3",
            "uptake_PNratio",
            "erodibility",
            "sreroexp",
            "cohesion",
            "slope",
            "srfilt",
            "macrofilt",
            "limpar",
            "exppar",
            "hsatINs",
            "denpar",
            "adosorption_nr_limit",
            "adsorption_nr_maxiter",
            "kfr",
            "nfr",
            "kadsdes",
            "bulk_density",
        ]
        for param in overwrite_params:
            setattr(self, param, overrides.pop(param, getattr(self, param)))

        if "depth" in overrides.keys():
            overrides.pop("depth")
            print(
                "ERROR: specifying depth is depreciated in overrides for \
		GrowingSurface, please specify rooting_depth instead"
            )
        self.rooting_depth = overrides.pop("rooting_depth", self.rooting_depth)
        overrides["depth"] = self.rooting_depth
        super().apply_overrides(overrides)

        (
            self.harvest_sow_calendar,
            self.ground_cover_stages,
            self.crop_cover_stages,
            self.autumn_sow,
        ) = self.infer_sow_harvest_calendar()
        (
            self.total_available_water,
            self.readily_available_water,
        ) = self.calculate_available_water()

    def pull_storage(self, vqip):
        """Pull water from the surface, updating the surface storage VQIP. Nutrient pool
        pollutants (nitrate/nitrite/ammonia/phosphate/org- phosphorus/ org-nitrogen) are
        removed in proportion to their amounts in the dissolved nutrient pools, if they
        are simulated. Other pollutants are removed in proportion to their amount in the
        surface tank.

        Args:
            vqip (dict): VQIP amount to be pulled, (only 'volume' key is needed)

        Returns:
            reply (dict): A VQIP amount successfully pulled from the tank
        """
        if self.storage["volume"] == 0:
            return self.empty_vqip()

        # Adjust based on available volume
        reply = min(vqip["volume"], self.storage["volume"])

        # Update reply to vqip (get concentration for non-nutrients)
        reply = self.v_change_vqip(self.storage, reply)

        if "nitrate" in constants.POLLUTANTS:
            # Update nutrient pool and get concentration for nutrients
            prop = reply["volume"] / self.storage["volume"]
            nutrients = self.nutrient_pool.extract_dissolved(prop)
            reply["nitrate"] = (
                nutrients["inorganic"]["N"]
                * self.storage["nitrate"]
                / (
                    self.storage["nitrate"]
                    + self.storage["ammonia"]
                    + self.storage["nitrite"]
                )
            )
            reply["ammonia"] = (
                nutrients["inorganic"]["N"]
                * self.storage["ammonia"]
                / (
                    self.storage["nitrate"]
                    + self.storage["ammonia"]
                    + self.storage["nitrite"]
                )
            )
            reply["nitrite"] = (
                nutrients["inorganic"]["N"]
                * self.storage["nitrite"]
                / (
                    self.storage["nitrate"]
                    + self.storage["ammonia"]
                    + self.storage["nitrite"]
                )
            )
            reply["phosphate"] = nutrients["inorganic"]["P"]
            reply["org-phosphorus"] = nutrients["organic"]["P"]
            reply["org-nitrogen"] = nutrients["organic"]["N"]

        # Extract from storage
        self.storage = self.extract_vqip(self.storage, reply)

        return reply

    def quick_interp(self, x, xp, yp):
        """A simple version of np.interp to intepolate crop information on the fly.

        Args:
            x (int): Current time (i.e., day of year) xp (list): Predefined times (i.e.,
            list of days of year) yp (list): Predefined values associated with xp

        Returns:
            y (float): Interpolated value for current time
        """
        x_ind = bisect_left(xp, x)
        x_left = xp[x_ind - 1]
        x_right = xp[x_ind]
        dif = x - x_left
        y_left = yp[x_ind - 1]
        y_right = yp[x_ind]
        y = y_left + (y_right - y_left) * dif / (x_right - x_left)
        return y

    def calc_crop_cover(self):
        """Process function that calculates how much crop cover there is, assigns
        whether crops are sown/harvested, and calculates et0_coefficient based on growth
        stage of crops.

        Returns:
            (tuple): A tuple containing a VQIP amount for model inputs and outputs
                for mass balance checking.
        """
        # Get current day of year
        doy = self.parent.t.dayofyear

        if self.parent.t.is_leap_year:
            # Hacky way to handle leap years
            if doy > 59:
                doy -= 1

        if self.days_after_sow is None:
            if self.parent.t.dayofyear == self.sowing_day:
                # sow
                self.days_after_sow = 0
        else:
            if self.parent.t.dayofyear == self.harvest_day:
                # harvest
                self.days_after_sow = None
                self.crop_factor = self.crop_factor_stages[0]
                self.crop_cover = 0
                self.ground_cover = 0
            else:
                # increment days since sow
                self.days_after_sow += 1

        # Calculate relevant parameters
        self.crop_factor = self.quick_interp(
            doy, self.crop_factor_stage_dates, self.crop_factor_stages
        )
        if self.days_after_sow:
            # Move outside of this if, if you want nonzero crop/ground cover outside of
            # season
            self.crop_cover = self.quick_interp(
                doy, self.harvest_sow_calendar, self.crop_cover_stages
            )
            self.ground_cover = self.quick_interp(
                doy, self.harvest_sow_calendar, self.ground_cover_stages
            )

        root_zone_depletion = max(self.field_capacity_m - self.get_smc(), 0)
        if root_zone_depletion < self.readily_available_water:
            crop_water_stress_coefficient = 1
        else:
            crop_water_stress_coefficient = max(
                0,
                (self.total_available_water - root_zone_depletion)
                / ((1 - self.ET_depletion_factor) * self.total_available_water),
            )

        self.et0_coefficient = crop_water_stress_coefficient * self.crop_factor

        return (self.empty_vqip(), self.empty_vqip())

    def adjust_vqip_to_liquid(self, vqip, deposition, in_):
        """Function to interoperate between surface tank and nutrient pool. Most
        depositions are given in terms of ammonia/nitrate/phosphate - they are then
        aggregated to total N or P to enter the nutrient pools. Depending on the source
        of deposition these may transform (e.g., some go to dissolved and some to
        solids) upon entering the nutrient pool. To reflect these transformations in the
        soil tank, the amounts entering the soil tank are adjusted proportionately.

        Args:
            vqip (dict): A VQIP amount of pollutants originally intended to enter the
                soil tank
            deposition (dict): A dict with nutrients (N and P) as keys, showing the
                total amount of nutrients entering the nutrient pool
            in_ (dict): A dict with nutrients as keys, showing the updated amount of
                nutrients that entered the nutrient pool as dissolved pollutants

        Returns:
            vqip (dict): A VQIP amount of pollutants that have been scaled to account
                for nutrient pool transformations
        """
        if "nitrate" in constants.POLLUTANTS:
            if deposition["N"] > 0:
                vqip["nitrate"] *= in_["N"] / deposition["N"]
                vqip["ammonia"] *= in_["N"] / deposition["N"]
                vqip["org-nitrogen"] *= in_["N"] / deposition["N"]
            if deposition["P"] > 0:
                vqip["phosphate"] *= in_["P"] / deposition["P"]
                vqip["org-phosphorus"] *= in_["P"] / deposition["P"]

        return vqip

    def effective_precipitation_flushing(self):
        """Remove the nutrients brought out by effective precipitation, which is surface
        runoff, subsurface runoff, and percolation, from the nutrients pool.

        Returns:
            (tuple): A tuple containing a VQIP amount for model inputs and outputs
                    for mass balance checking.
        """
        # inorganic
        out = self.nutrient_pool.get_empty_nutrient()
        out["N"] = (
            self.subsurface_flow["ammonia"]
            + self.subsurface_flow["nitrite"]
            + self.subsurface_flow["nitrate"]
            + self.percolation["ammonia"]
            + self.percolation["nitrite"]
            + self.percolation["nitrate"]
            + self.infiltration_excess["ammonia"]
            + self.infiltration_excess["nitrite"]
            + self.infiltration_excess["nitrate"]
        )  # TODO what happens if infiltration excess (the real part) has pollutants?
        out["P"] = (
            self.subsurface_flow["phosphate"]
            + self.percolation["phosphate"]
            + self.infiltration_excess["phosphate"]
        )
        self.nutrient_pool.dissolved_inorganic_pool.extract(out)

        # organic
        out = self.nutrient_pool.get_empty_nutrient()
        out["N"] = (
            self.subsurface_flow["org-nitrogen"]
            + self.percolation["org-nitrogen"]
            + self.infiltration_excess["org-nitrogen"]
        )
        out["P"] = (
            self.subsurface_flow["org-phosphorus"]
            + self.percolation["org-phosphorus"]
            + self.infiltration_excess["org-phosphorus"]
        )
        self.nutrient_pool.dissolved_organic_pool.extract(out)

        return (self.empty_vqip(), self.empty_vqip())

    def fertiliser(self):
        """Read, scale and allocate fertiliser, updating the tank.

        Returns:
            (tuple): A tuple containing a VQIP amount for model inputs and outputs
                for mass balance checking.
        """
        # TODO tidy up fertiliser/manure/residue/deposition once preprocessing is sorted

        # Scale for surface
        nhx = self.get_data_input_surface("nhx-fertiliser") * self.area
        noy = self.get_data_input_surface("noy-fertiliser") * self.area
        srp = self.get_data_input_surface("srp-fertiliser") * self.area

        # Update as VQIP
        vqip = self.empty_vqip()
        vqip["ammonia"] = nhx
        vqip["nitrate"] = noy
        vqip["phosphate"] = srp

        # Enter nutrient pool
        deposition = self.nutrient_pool.get_empty_nutrient()
        deposition["N"] = vqip["nitrate"] + vqip["ammonia"]
        deposition["P"] = vqip["phosphate"]
        in_ = self.nutrient_pool.allocate_fertiliser(deposition)

        # Update tank
        vqip = self.adjust_vqip_to_liquid(vqip, deposition, in_)
        self.push_storage(vqip, force=True)

        return (vqip, self.empty_vqip())

    def manure(self):
        """Read, scale and allocate manure, updating the tank.

        Returns:
            (tuple): A tuple containing a VQIP amount for model inputs and outputs
                for mass balance checking.
        """
        # Scale for surface
        nhx = self.get_data_input_surface("nhx-manure") * self.area
        noy = self.get_data_input_surface("noy-manure") * self.area
        srp = self.get_data_input_surface("srp-manure") * self.area

        # Formulate as VQIP
        vqip = self.empty_vqip()
        vqip["ammonia"] = nhx
        vqip["nitrate"] = noy
        vqip["phosphate"] = srp

        # Enter nutrient pool
        deposition = self.nutrient_pool.get_empty_nutrient()
        deposition["N"] = vqip["nitrate"] + vqip["ammonia"]
        deposition["P"] = vqip["phosphate"]
        in_ = self.nutrient_pool.allocate_manure(deposition)

        # Update tank
        vqip = self.adjust_vqip_to_liquid(vqip, deposition, in_)

        self.push_storage(vqip, force=True)

        return (vqip, self.empty_vqip())

    def residue(self):
        """Read, scale and allocate residue, updating the tank (NOT CURRENTLY USED
        BECAUSE NO DATA SOURCES FOR RESIDUE CAN BE IDENTIFIED).

        Returns:
            (tuple): A tuple containing a VQIP amount for model inputs and outputs
                for mass balance checking.
        """
        nhx = self.get_data_input_surface("nhx-residue") * self.area
        noy = self.get_data_input_surface("noy-residue") * self.area
        srp = self.get_data_input_surface("srp-residue") * self.area

        vqip = self.empty_vqip()
        vqip["ammonia"] = nhx * self.nutrient_pool.fraction_residue_to_fast["N"]
        vqip["nitrate"] = noy * self.nutrient_pool.fraction_residue_to_fast["N"]
        vqip["org-nitrogen"] = (
            nhx + noy
        ) * self.nutrient_pool.fraction_residue_to_humus["N"]
        vqip["phosphate"] = srp * self.nutrient_pool.fraction_residue_to_fast["P"]
        vqip["org-phosphorus"] = srp * self.nutrient_pool.fraction_residue_to_humus["P"]

        deposition = self.nutrient_pool.get_empty_nutrient()
        deposition["N"] = vqip["nitrate"] + vqip["ammonia"] + vqip["org-nitrogen"]
        deposition["P"] = vqip["phosphate"] + vqip["org-phosphorus"]

        in_ = self.nutrient_pool.allocate_residue(deposition)
        vqip = self.adjust_vqip_to_liquid(vqip, deposition, in_)

        self.push_storage(vqip, force=True)

        return (vqip, self.empty_vqip())

    def soil_pool_transformation(self):
        """A process function that run transformation functions in the nutrient pool and
        updates the pollutant concentrations in the surface tank.

        Returns:
            (tuple): A tuple containing a VQIP amount for model inputs and outputs
                for mass balance checking.
        """
        # Initialise mass balance tracking variables
        in_ = self.empty_vqip()
        out_ = self.empty_vqip()

        # Get proportion of nitrogen that is nitrate in the soil tank NOTE ignores
        # nitrite - couldn't find enough information on it
        nitrate_proportion = self.storage["nitrate"] / (
            self.storage["nitrate"] + self.storage["ammonia"]
        )

        # Run soil pool functions
        (
            increase_in_dissolved_inorganic,
            increase_in_dissolved_organic,
        ) = self.nutrient_pool.soil_pool_transformation()

        # Update tank and mass balance TODO .. there is definitely a neater way to write
        # this
        if increase_in_dissolved_inorganic["N"] > 0:
            # Increase in inorganic nitrogen, rescale back to nitrate and ammonia
            in_["nitrate"] = increase_in_dissolved_inorganic["N"] * nitrate_proportion
            in_["ammonia"] = increase_in_dissolved_inorganic["N"] * (
                1 - nitrate_proportion
            )
        else:
            # Decrease in inorganic nitrogen, rescale back to nitrate and ammonia
            out_["nitrate"] = -increase_in_dissolved_inorganic["N"] * nitrate_proportion
            out_["ammonia"] = -increase_in_dissolved_inorganic["N"] * (
                1 - nitrate_proportion
            )

        if increase_in_dissolved_organic["N"] > 0:
            # Increase in organic nitrogen
            in_["org-nitrogen"] = increase_in_dissolved_organic["N"]
        else:
            # Decrease in organic nitrogen
            out_["org-nitrogen"] = -increase_in_dissolved_organic["N"]

        if increase_in_dissolved_inorganic["P"] > 0:
            # Increase in inorganic phosphate
            in_["phosphate"] = increase_in_dissolved_inorganic["P"]
        else:
            # Decrease in inorganic phosphate
            out_["phosphate"] = -increase_in_dissolved_inorganic["P"]

        if increase_in_dissolved_organic["P"] > 0:
            # Increase in organic phosphorus
            in_["org-phosphorus"] = increase_in_dissolved_organic["P"]
        else:
            # Decrease in organic phosphorus
            out_["org-phosphorus"] = -increase_in_dissolved_organic["P"]

        # Update tank with inputs/outputs of pollutants
        _ = self.push_storage(in_, force=True)
        out2_ = self.pull_pollutants(out_)

        if not self.compare_vqip(out_, out2_):
            print("nutrient pool not tracking soil tank")

        return (in_, out_)

    def calc_temperature_dependence_factor(self):
        """Process function that calculates the temperature dependence factor for the
        nutrient pool (which impacts soil pool transformations).

        Returns:
            (tuple): A tuple containing a VQIP amount for model inputs and outputs
                for mass balance checking.
        """
        # Parameters/equations from HYPE documentation
        if self.storage["temperature"] > 5:
            temperature_dependence_factor = 2 ** (
                (self.storage["temperature"] - 20) / 10
            )
        elif self.storage["temperature"] > 0:
            temperature_dependence_factor = self.storage["temperature"] / 5
        else:
            temperature_dependence_factor = 0
        self.nutrient_pool.temperature_dependence_factor = temperature_dependence_factor
        return (self.empty_vqip(), self.empty_vqip())

    def calc_soil_moisture_dependence_factor(self):
        """Process function that calculates the soil moisture dependence factor for the
        nutrient pool (which impacts soil pool transformations).

        Returns:
            (tuple): A tuple containing a VQIP amount for model inputs and outputs
                for mass balance checking.
        """
        # Parameters/equations from HYPE documentation
        current_soil_moisture = self.get_smc()
        if current_soil_moisture >= self.field_capacity_m:
            self.nutrient_pool.soil_moisture_dependence_factor = self.satact
        elif current_soil_moisture <= self.wilting_point_m:
            self.nutrient_pool.soil_moisture_dependence_factor = 0
        else:
            fc_diff = self.field_capacity_m - current_soil_moisture
            fc_comp = (fc_diff / (self.thetaupp * self.rooting_depth)) ** self.thetapow
            fc_comp = (1 - self.satact) * fc_comp + self.satact
            wp_diff = current_soil_moisture - self.wilting_point_m
            wp_comp = (wp_diff / (self.thetalow * self.rooting_depth)) ** self.thetapow
            self.nutrient_pool.soil_moisture_dependence_factor = min(
                1, wp_comp, fc_comp
            )
        return (self.empty_vqip(), self.empty_vqip())

    def calc_crop_uptake(self):
        """Process function that calculates how much nutrient crops uptake and updates
        nutrient pool and surface tank.

        Returns:
            (tuple): A tuple containing a VQIP amount for model inputs and outputs
                for mass balance checking.
        """
        # Parameters/equations from HYPE documentation

        # Initialise
        N_common_uptake = 0
        P_common_uptake = 0

        if self.days_after_sow:
            # If there are crops

            days_after_sow = self.days_after_sow

            if self.autumn_sow:
                temp_func = max(0, min(1, (self.storage["temperature"] - 5) / 20))
                days_after_sow -= 25  # Not sure why this is (but it's in HYPE)
            else:
                temp_func = 1

            # Calculate uptake
            uptake_par = (self.uptake1 - self.uptake2) * exp(
                -self.uptake3 * days_after_sow
            )
            if (uptake_par + self.uptake2) > 0:
                N_common_uptake = (
                    self.uptake1
                    * self.uptake2
                    * self.uptake3
                    * uptake_par
                    / ((self.uptake2 + uptake_par) ** 2)
                )
            N_common_uptake *= temp_func * constants.G_M2_TO_KG_M2 * self.area  # [kg]
            P_common_uptake = N_common_uptake * self.uptake_PNratio
            # calculate maximum available uptake
            N_maximum_available_uptake = (
                max(0, self.storage["volume"] - self.wilting_point_m * self.area)
                / self.storage["volume"]
                * self.nutrient_pool.dissolved_inorganic_pool.storage["N"]
            )
            P_maximum_available_uptake = (
                max(0, self.storage["volume"] - self.wilting_point_m * self.area)
                / self.storage["volume"]
                * self.nutrient_pool.dissolved_inorganic_pool.storage["P"]
            )

            uptake = {
                "P": min(P_common_uptake, P_maximum_available_uptake),
                "N": min(N_common_uptake, N_maximum_available_uptake),
            }
            crop_uptake = self.nutrient_pool.dissolved_inorganic_pool.extract(uptake)
            out_ = self.empty_vqip()

            # Assuming plants eat N and P as nitrate and phosphate
            out_["nitrate"] = crop_uptake["N"]
            out_["phosphate"] = crop_uptake["P"]

            out2_ = self.pull_pollutants(out_)
            if not self.compare_vqip(out_, out2_):
                print("nutrient pool not tracking soil tank")

            return (self.empty_vqip(), out_)
        else:
            return (self.empty_vqip(), self.empty_vqip())

    def erosion(self):
        """Outflow function that erodes adsorbed/humus phosphorus and sediment and sends
        onwards to percolation/surface runoff/subsurface runoff.

        Returns:
            (tuple): A tuple containing a VQIP amount for model inputs and outputs
                for mass balance checking.
        """
        # Parameters/equations from HYPE documentation (which explains why my
        # documentation is a bit ambiguous - because theirs is too)

        # Convert precipitation to MM since all the equations assume that
        precipitation_depth = self.get_data_input("precipitation") * constants.M_TO_MM

        # Calculate how much rain is mobilising erosion
        if precipitation_depth > 5:
            rainfall_energy = 8.95 + 8.44 * log10(
                precipitation_depth
                * (
                    0.257
                    + sin(2 * constants.PI * ((self.parent.t.dayofyear - 70) / 365))
                    * 0.09
                )
                * 2
            )
            rainfall_energy *= precipitation_depth
            mobilised_rain = rainfall_energy * (1 - self.crop_cover) * self.erodibility
        else:
            mobilised_rain = 0

        # Calculate if any infiltration is mobilising erosion
        if self.infiltration_excess["volume"] > 0:
            mobilised_flow = (
                self.infiltration_excess["volume"] / self.area * constants.M_TO_MM * 365
            ) ** self.sreroexp
            mobilised_flow *= (
                (1 - self.ground_cover)
                * (1 / (0.5 * self.cohesion))
                * sin(self.slope / 100)
                / 365
            )
        else:
            mobilised_flow = 0

        # Sum flows (not sure why surface runoff isn't included) TODO I'm pretty sure it
        # should be included here
        total_flows = (
            self.infiltration_excess["volume"]
            + self.subsurface_flow["volume"]
            + self.percolation["volume"]
        )  # m3/dt + self.tank_recharge['volume'] (guess not needed)

        # Convert to MM/M2
        erodingflow = total_flows / self.area * constants.M_TO_MM

        # Calculate eroded sediment
        transportfactor = min(1, (erodingflow / 4) ** 1.3)
        erodedsed = (
            1000 * (mobilised_flow + mobilised_rain) * transportfactor
        )  # [kg/km2]
        # TODO not sure what conversion this HYPE 1000 is referring to

        # soil erosion with adsorbed inorganic phosphorus and humus phosphorus (erodedP
        # as P in eroded sediments and effect of enrichment)
        if erodingflow > 4:
            enrichment = 1.5
        elif erodingflow > 0:
            enrichment = 4 - (4 - 1.5) * erodingflow / 4
        else:
            return (self.empty_vqip(), self.empty_vqip())

        # Get erodable phosphorus
        erodableP = (
            self.nutrient_pool.get_erodable_P() / self.area * constants.KG_M2_TO_KG_KM2
        )
        erodedP = (
            erodedsed
            * (
                erodableP
                / (
                    self.rooting_depth
                    * constants.M_TO_KM
                    * self.bulk_density
                    * constants.KG_M3_TO_KG_KM3
                )
            )
            * enrichment
        )  # [kg/km2]

        # Convert to kg
        erodedP *= self.area * constants.M2_TO_KM2  # [kg]
        erodedsed *= self.area * constants.M2_TO_KM2  # [kg]

        # Allocate to different flows
        surface_erodedP = (
            self.srfilt * self.infiltration_excess["volume"] / total_flows * erodedP
        )  # [kg]
        surface_erodedsed = (
            self.srfilt * self.infiltration_excess["volume"] / total_flows * erodedsed
        )  # [kg]

        subsurface_erodedP = (
            self.macrofilt * self.subsurface_flow["volume"] / total_flows * erodedP
        )  # [kg]
        subsurface_erodedsed = (
            self.macrofilt * self.subsurface_flow["volume"] / total_flows * erodedsed
        )  # [kg]

        percolation_erodedP = (
            self.macrofilt * self.percolation["volume"] / total_flows * erodedP
        )  # [kg]
        percolation_erodedsed = (
            self.macrofilt * self.percolation["volume"] / total_flows * erodedsed
        )  # [kg]

        # Track mass balance
        in_ = self.empty_vqip()

        # Total eroded phosphorus
        eff_erodedP = percolation_erodedP + surface_erodedP + subsurface_erodedP  # [kg]
        if eff_erodedP > 0:
            # Update nutrient pool
            org_removed, inorg_removed = self.nutrient_pool.erode_P(eff_erodedP)
            total_removed = inorg_removed + org_removed

            if abs(total_removed - eff_erodedP) > constants.FLOAT_ACCURACY:
                print("weird nutrients")

            # scale flows to split between inorganic and organic eroded P
            self.infiltration_excess["org-phosphorus"] += (
                surface_erodedP * org_removed / eff_erodedP
            )
            self.subsurface_flow["org-phosphorus"] += (
                subsurface_erodedP * org_removed / eff_erodedP
            )
            self.percolation["org-phosphorus"] += (
                percolation_erodedP * org_removed / eff_erodedP
            )

            # TODO Leon reckons this is conceptually dodgy.. but i'm not sure where else
            # adsorbed inorganic phosphorus should go
            self.infiltration_excess["phosphate"] += (
                surface_erodedP * inorg_removed / eff_erodedP
            )
            self.subsurface_flow["phosphate"] += (
                subsurface_erodedP * inorg_removed / eff_erodedP
            )
            self.percolation["phosphate"] += (
                percolation_erodedP * inorg_removed / eff_erodedP
            )

            # Entering the model (no need to uptake surface tank because both adsorbed
            # inorganic pool and humus pool are solids and so no tracked in the soil
            # water tank)
            in_["phosphate"] = inorg_removed
            in_["org-phosphorus"] = org_removed
        else:
            pass

        # Track sediment as solids
        self.infiltration_excess["solids"] += surface_erodedsed
        self.subsurface_flow["solids"] += subsurface_erodedsed
        self.percolation["solids"] += percolation_erodedsed

        in_["solids"] = surface_erodedsed + subsurface_erodedsed + percolation_erodedsed

        return (in_, self.empty_vqip())

    def denitrification(self):
        """Outflow function that performs denitirication processes, updating nutrient
        pool and soil tank.

        Returns:
            (tuple): A tuple containing a VQIP amount for model inputs and outputs
                for mass balance checking.
        """
        # Parameters/equations from HYPE documentation TODO could more of this be moved
        # to NutrientPool Calculate soil moisture dependence of denitrification
        soil_moisture_content = self.get_smc()
        if soil_moisture_content > self.field_capacity_m:
            denitrifying_soil_moisture_dependence = 1
        elif soil_moisture_content / self.field_capacity_m > self.limpar:
            denitrifying_soil_moisture_dependence = (
                ((soil_moisture_content / self.field_capacity_m) - self.limpar)
                / (1 - self.limpar)
            ) ** self.exppar
        else:
            denitrifying_soil_moisture_dependence = 0
            return (self.empty_vqip(), self.empty_vqip())

        # Get dissolved inorg nitrogen as a concentration and calculate factor
        din_conc = (
            self.nutrient_pool.dissolved_inorganic_pool.storage["N"]
            / self.storage["volume"]
        )  # [kg/m3]
        din_conc *= constants.KG_M3_TO_MG_L
        half_saturation_concentration_dependence_factor = din_conc / (
            din_conc + self.hsatINs
        )

        # Calculate and extract dentrified nitrogen
        denitrified_N = (
            self.nutrient_pool.dissolved_inorganic_pool.storage["N"]
            * half_saturation_concentration_dependence_factor
            * denitrifying_soil_moisture_dependence
            * self.nutrient_pool.temperature_dependence_factor
            * self.denpar
        )
        denitrified_request = self.nutrient_pool.get_empty_nutrient()
        denitrified_request["N"] = denitrified_N
        denitrified_N = self.nutrient_pool.dissolved_inorganic_pool.extract(
            denitrified_request
        )

        # Leon reckons this should leave the model (though I think technically some
        # small amount goes to nitrite)
        out_ = self.empty_vqip()
        out_["nitrate"] = denitrified_N["N"]

        # Update tank
        out2_ = self.pull_pollutants(out_)
        if not self.compare_vqip(out_, out2_):
            print("nutrient pool not tracking soil tank")

        return (self.empty_vqip(), out_)

    def adsorption(self):
        """Outflow function that calculates phosphorus adsorption/desorptions and
        updates soil tank and nutrient pools.

        Returns:
            (tuple): A tuple containing a VQIP amount for model inputs and outputs
                for mass balance checking.
        """
        # Parameters/equations from HYPE documentation TODO could this be moved to the
        # nutrient pool?

        # Initialise mass balance checking
        in_ = self.empty_vqip()
        out_ = self.empty_vqip()

        # Get total phosphorus in pool available for adsorption/desorption
        limit = self.adosorption_nr_limit
        ad_de_P_pool = (
            self.nutrient_pool.adsorbed_inorganic_pool.storage["P"]
            + self.nutrient_pool.dissolved_inorganic_pool.storage["P"]
        )  # [kg]
        ad_de_P_pool /= self.area * constants.M2_TO_KM2  # [kg/km2]
        if ad_de_P_pool == 0:
            return (self.empty_vqip(), self.empty_vqip())

        # Calculate coefficient and concentration of adsorbed phosphorus
        soil_moisture_content = (
            self.get_smc() * constants.M_TO_MM
        )  # [mm] (not sure why HYPE has this in mm but whatever)
        conc_sol = (
            self.nutrient_pool.adsorbed_inorganic_pool.storage["P"]
            * constants.KG_TO_MG
            / (self.bulk_density * self.rooting_depth * self.area)
        )  # [mg P/kg soil]
        coeff = self.kfr * self.bulk_density * self.rooting_depth  # [mm]

        # calculate equilibrium concentration
        if conc_sol <= 0:
            # Not sure how this would happen
            print("Warning: soil partP <=0. Freundlich will give error, take shortcut.")
            xn_1 = ad_de_P_pool / (soil_moisture_content + coeff)  # [mg/l]
            ad_P_equi_conc = self.kfr * xn_1  # [mg/ kg]
        else:
            # Newton-Raphson method
            x0 = exp(
                (log(conc_sol) - log(self.kfr)) / self.nfr
            )  # initial guess of equilibrium liquid concentration
            fxn = x0 * soil_moisture_content + coeff * (x0**self.nfr) - ad_de_P_pool
            xn = x0
            xn_1 = xn
            j = 0
            while (
                abs(fxn) > limit and j < self.adsorption_nr_maxiter
            ):  # iteration to calculate equilibrium concentations
                fxn = xn * soil_moisture_content + coeff * (xn**self.nfr) - ad_de_P_pool
                fprimxn = soil_moisture_content + self.nfr * coeff * (
                    xn ** (self.nfr - 1)
                )
                dx = fxn / fprimxn
                if abs(dx) < (0.000001 * xn):
                    # From HYPE... not sure what it means
                    break
                xn_1 = xn - dx
                if xn_1 <= 0:
                    xn_1 = 1e-10
                xn = xn_1
                j += 1
            ad_P_equi_conc = self.kfr * (xn_1**self.nfr)
            # print(ad_P_equi_conc, conc_sol)

        # Calculate new pool and concentration, depends on the equilibrium concentration
        if abs(ad_P_equi_conc - conc_sol) > 1e-6:
            request = self.nutrient_pool.get_empty_nutrient()

            # TODO not sure about this if statement, surely it would be triggered every
            # time
            adsdes = (ad_P_equi_conc - conc_sol) * (
                1 - exp(-self.kadsdes)
            )  # kinetic adsorption/desorption
            request["P"] = (
                adsdes
                * self.bulk_density
                * self.rooting_depth
                * (self.area * constants.M2_TO_KM2)
            )  # [kg]
            if request["P"] > 0:
                # Adsorption
                adsorbed = self.nutrient_pool.dissolved_inorganic_pool.extract(request)
                if (adsorbed["P"] - request["P"]) > constants.FLOAT_ACCURACY:
                    print("Warning: freundlich flow adjusted, was larger than pool")
                self.nutrient_pool.adsorbed_inorganic_pool.receive(adsorbed)

                # Dissolved leaving the soil water tank and becoming solid
                out_["phosphate"] = adsorbed["P"]

                # Update tank
                out2_ = self.pull_pollutants(out_)
                if not self.compare_vqip(out_, out2_):
                    print("nutrient pool not tracking soil tank")
            else:
                # Desorption
                request["P"] = -request["P"]
                desorbed = self.nutrient_pool.adsorbed_inorganic_pool.extract(request)
                if (desorbed["P"] - request["P"]) > constants.FLOAT_ACCURACY:
                    print("Warning: freundlich flow adjusted, was larger than pool")
                self.nutrient_pool.dissolved_inorganic_pool.receive(desorbed)

                # Solid phosphorus becoming inorganic P in the soil water tank
                in_["phosphate"] = desorbed["P"]
                _ = self.push_storage(in_, force=True)

        return (in_, out_)

    def dry_deposition_to_tank(self, vqip):
        """Allocate dry deposition to surface tank, updating nutrient pool accordingly.

        Args:
            vqip (dict): A VQIP amount of dry deposition to send to tank

        Returns:
            vqip (dict): A VQIP amount of dry deposition that entered the tank (used
                for mass balance checking)
        """
        # Convert to nutrients
        deposition = self.nutrient_pool.get_empty_nutrient()
        deposition["N"] = vqip["nitrate"] + vqip["ammonia"]
        deposition["P"] = vqip["phosphate"]

        # Update nutrient pool
        in_ = self.nutrient_pool.allocate_dry_deposition(deposition)
        vqip = self.adjust_vqip_to_liquid(vqip, deposition, in_)

        # Update tank
        self.push_storage(vqip, force=True)
        return vqip

    def wet_deposition_to_tank(self, vqip):
        """Allocate wet deposition to surface tank, updating nutrient pool accordingly.

        Args:
            vqip (dict): A VQIP amount of dry deposition to send to tank

        Returns:
            vqip (dict): A VQIP amount of dry deposition that entered the tank (used
                for mass balance checking)
        """
        # Convert to nutrients
        deposition = self.nutrient_pool.get_empty_nutrient()
        deposition["N"] = vqip["nitrate"] + vqip["ammonia"]
        deposition["P"] = vqip["phosphate"]

        # Update nutrient pool
        in_ = self.nutrient_pool.allocate_wet_deposition(deposition)
        vqip = self.adjust_vqip_to_liquid(vqip, deposition, in_)

        # Update tank
        self.push_storage(vqip, force=True)
        return vqip

__init__(rooting_depth=1, ET_depletion_factor=1, crop_factor_stages=[1, 1], crop_factor_stage_dates=[0, 365], sowing_day=1, harvest_day=365, initial_soil_storage=None, **kwargs)

Extensive surface subclass that implements the CatchWat equations (Liu, Dobson & Mijic (2022) Science of the total environment), which in turn are primarily based on FAO document: https://www.fao.org/3/x0490e/x0490e0ehtm#soil%20water%20availability. This surface is a pervious surface that also has things that grow on it. This behaviour includes soil nutrient pools, crop planting/harvest calendars, erosion, crop behaviour.

A key complexity of this surface is the nutrient pool (see wsimod/nodes/ nutrient_pool.py), which is a class that tracks the amount of phosphorus and nitrogen in different states and performs transformations that occur in the phosphorus/nitrogen cycle. It is assumed that the phosphate/nitrate/nitrite/ ammonia amounts in this Surface tank should track the dissolved inorganic pool in the nutrient pool. Meanwhile, the org-phosphorus/org-nitrogen amounts in this tank should track the dissolved organic pool in the nutrient pool. The total amount of pollutants that enter this tank may not be the same as the total amount that leave, because pollutants are transformed between inorganic/ organic and between wet/dry states - these transformations are accounted for in mass balance.

For users to quickly enable/disable these nutrient processes, which are computationally intensive (in current case studies they account for about half of the total runtime), they are only active if 'nitrate' is one of the modelled pollutants. Note that the code will not check if nitrite/phosphate/ org-phosphorus/org-nitrogen/ammonia are also included, but they should be if nitrate is included and otherwise the code will crash with a key error.

Parameters:

Name	Type	Description	Default
rooting_depth	float	Depth of the soil tank (i.e., how deep do crop roots go). Defaults to 1.	1
ET_depletion_factor	float	Average fraction of soil that can be depleted from the root zone before moisture stress (reduction in ET) occurs. Defaults to 1.	1
crop_factor_stages	list	Crop factor is a multiplier on et0, more grown plants have higher transpiration and higher crop factors. This list shows changing crop factor at different times of year in relation to crop_factor_stage_dates. See wsimod/preprocessing/ england_data_formatting.py/format_surfaces for further details on formulating these - since the interpolation used to find crop_factors in between the given values in the list is a bit involved. Defaults to [1,1].	[1, 1]
crop_factor_stage_dates	list	Dates associated with crop_factor_stages. Defaults to [0, 365].	[0, 365]
sowing_day	int	day of year that crops are sown. Defaults to 1.	1
harvest_day	int	day of year that crops are harvest. Defaults to 365.	365
initial_soil_storage	dict or float	Initial mass of solid	None

Key assumptions

• In the soil water module, crop stages and crop coefficients control the evapotranspiration.
• Fertiliser and manure application are the major source of soil nutrients, which are added into soil nutrient pools, including dissovled inorganic, dissolved organic, fast and humus for both nitrogen and phosphorus.
• Nutrient transformation processes in soil are simulated, including fluxes between the soil nutrient pools, denitrification for nitrogen, adsorption/desorption for phosphorus. These processes are affected by temperature and soil moisture.
• Crop uptake of nutrients are simulated based on crop stages, which is different for spring-sown and autumn-sown crops.
• Soil erosion from the growing surface is simulated as one of the major sources of suspended solids in rivers, which is mainly affected by rainfall energy and crop/ground cover. Phosphorus will also be eroded along with the soil particles, in both adsorbed inorganic and humus form.

Input data and parameter requirements

• data_input_dict can contain a variety of pollutant deposition data. srp-fertiliser describes phosphate. noy-fertiliser describes nitrogen as nitrates. nhx-fertiliser describes nitrogen as ammonia. srp/noy/ nhx-manure can also be used to specify manure application. Units: kg/m2/timestep (data is read at a monthly timestep)
• Rooting depth. Units: m
• Evapotranspiration depletion factor. Units: -
• Sowing day, harvest day and crop calendars. Units: day number in Julian calendar
• Crop factor. Units: -
• Initial storage for solid pollutants. Units: kg

Source code in wsimod\nodes\land.py

def __init__(
    self,
    rooting_depth=1,
    ET_depletion_factor=1,
    crop_factor_stages=[1, 1],
    crop_factor_stage_dates=[0, 365],
    sowing_day=1,
    harvest_day=365,
    initial_soil_storage=None,
    **kwargs,
):
    """Extensive surface subclass that implements the CatchWat equations (Liu,
    Dobson & Mijic (2022) Science of the total environment), which in turn are
    primarily based on FAO document:
    https://www.fao.org/3/x0490e/x0490e0ehtm#soil%20water%20availability. This
    surface is a pervious surface that also has things that grow on it. This
    behaviour includes soil nutrient pools, crop planting/harvest calendars,
    erosion, crop behaviour.

    A key complexity of this surface is the nutrient pool (see wsimod/nodes/
    nutrient_pool.py), which is a class that tracks the amount of phosphorus and
    nitrogen in different states and performs transformations that occur in the
    phosphorus/nitrogen cycle. It is assumed that the phosphate/nitrate/nitrite/
    ammonia amounts in this Surface tank should track the dissolved inorganic pool
    in the nutrient pool. Meanwhile, the org-phosphorus/org-nitrogen amounts in this
    tank should track the dissolved organic pool in the nutrient pool. The total
    amount of pollutants that enter this tank may not be the same as the total
    amount that leave, because pollutants are transformed between inorganic/ organic
    and between wet/dry states - these transformations are accounted for in mass
    balance.

    For users to quickly enable/disable these nutrient processes, which are
    computationally intensive (in current case studies they account for about half
    of the total runtime), they are only active if 'nitrate' is one of the modelled
    pollutants. Note that the code will not check if nitrite/phosphate/
    org-phosphorus/org-nitrogen/ammonia are also included, but they should be if
    nitrate is included and otherwise the code will crash with a key error.

    Args:
        rooting_depth (float, optional): Depth of the soil tank (i.e., how deep do
            crop roots go). Defaults to 1.
        ET_depletion_factor (float, optional): Average fraction of soil that can be
            depleted from the root zone before moisture stress (reduction in ET)
            occurs. Defaults to 1.
        crop_factor_stages (list, optional): Crop factor is a multiplier on et0,
            more grown plants have higher transpiration and higher crop factors.
            This list shows changing crop factor at different times of year in
            relation to crop_factor_stage_dates. See wsimod/preprocessing/
            england_data_formatting.py/format_surfaces for further details on
            formulating these - since the interpolation used to find crop_factors in
            between the given values in the list is a bit involved. Defaults to
            [1,1].
        crop_factor_stage_dates (list, optional): Dates associated with
            crop_factor_stages. Defaults to [0, 365].
        sowing_day (int, optional): day of year that crops are sown. Defaults to 1.
        harvest_day (int, optional): day of year that crops are harvest. Defaults
            to 365.
        initial_soil_storage (dict or float, optional): Initial mass of solid
        pollutants
            in the soil nutrient pools (fast and adsorbed inorganic pools)

    Key assumptions:
         - In the soil water module, crop stages and crop coefficients control the
           evapotranspiration.
         - Fertiliser and manure application are the major source of soil nutrients,
           which are added
            into soil nutrient pools, including dissovled inorganic, dissolved
            organic, fast and humus for both nitrogen and phosphorus.
         - Nutrient transformation processes in soil are simulated, including fluxes
           between the soil
            nutrient pools, denitrification for nitrogen, adsorption/desorption for
            phosphorus. These processes are affected by temperature and soil
            moisture.
         - Crop uptake of nutrients are simulated based on crop stages, which is
           different for spring-sown
            and autumn-sown crops.
         - Soil erosion from the growing surface is simulated as one of the major
           sources of suspended solids
            in rivers, which is mainly affected by rainfall energy and crop/ground
            cover. Phosphorus will also be eroded along with the soil particles, in
            both adsorbed inorganic and humus form.

    Input data and parameter requirements:
         - `data_input_dict` can contain a variety of pollutant deposition data.
            `srp-fertiliser` describes phosphate. `noy-fertiliser` describes
            nitrogen as nitrates. `nhx-fertiliser` describes nitrogen as ammonia.
            `srp/noy/ nhx-manure` can also be used to specify manure application.
            _Units_: kg/m2/timestep (data is read at a monthly timestep)
         - Rooting depth.
            _Units_: m
         - Evapotranspiration depletion factor.
            _Units_: -
         - Sowing day, harvest day and crop calendars.
            _Units_: day number in Julian calendar
         - Crop factor.
            _Units_: -
         - Initial storage for solid pollutants.
            _Units_: kg

    """
    # Crop factors (set when creating object)
    self.ET_depletion_factor = (
        ET_depletion_factor  # To do with water availability, p from FAOSTAT
    )
    self.rooting_depth = (
        rooting_depth  # maximum depth that plants can absorb, Zr from FAOSTAT
    )
    depth = rooting_depth

    # Crop parameters
    self.crop_cover_max = 0.9  # [-] 0~1
    self.ground_cover_max = 0.3  # [-]
    # TODO... really I should just have this as an annual profile parameter and do
    # away with interpolation etc.
    self.crop_factor_stages = crop_factor_stages
    self.crop_factor_stage_dates = crop_factor_stage_dates
    self.sowing_day = sowing_day
    self.harvest_day = harvest_day

    # Soil moisture dependence parameters
    self.satact = 0.6  # [-] for calculating soil_moisture_dependence_factor
    self.thetaupp = 0.12  # [-] for calculating soil_moisture_dependence_factor
    self.thetalow = 0.08  # [-] for calculating soil_moisture_dependence_factor
    self.thetapow = 1  # [-] for calculating soil_moisture_dependence_factorself.
    # satact = 0.6 # [-] for calculating soil_moisture_dependence_factor

    # Crop uptake parameters
    self.uptake1 = (
        15  # [g/m2/y] shape factor for crop (Dissolved) Inorganic nitrogen uptake
    )
    self.uptake2 = (
        1  # [-] shape factor for crop (Dissolved) Inorganic nitrogen uptake
    )
    self.uptake3 = (
        0.02  # [1/day] shape factor for crop (Dissolved) Inorganic nitrogen uptake
    )
    self.uptake_PNratio = 1 / 7.2  # [-] P:N during crop uptake

    # Erosion parameters
    self.erodibility = 0.0025  # [g * d / (J * mm)]
    self.sreroexp = 1.2  # [-] surface runoff erosion exponent
    self.cohesion = 1  # [kPa]
    self.slope = 5  # [-] every 100
    self.srfilt = (
        0.7  # [-] ratio of eroded sediment left in surface runoff after filtration
    )
    self.macrofilt = 0.01  # [-] ratio of eroded sediment left in subsurface flow
    # after filtration

    # Denitrification parameters
    self.limpar = 0.7  # [-] above which denitrification begins
    self.exppar = 2.5  # [-] exponential parameter for
    # soil_moisture_dependence_factor_exp calculation
    self.hsatINs = 1  # [mg/l] for calculation of half-saturation concentration
    # dependence factor
    self.denpar = 0.015  # [-] denitrification rate coefficient

    # Adsorption parameters
    self.adosorption_nr_limit = 0.00001
    self.adsorption_nr_maxiter = 20
    self.kfr = 153.7  # [litter/kg] freundlich adsorption isoterm
    self.nfr = 1 / 2.6  # [-] freundlich exponential coefficient
    self.kadsdes = 0.03  # [1/day] adsorption/desorption coefficient

    # Other soil parameters
    self.bulk_density = 1300  # [kg/m3]
    super().__init__(depth=depth, **kwargs)

    (
        self.harvest_sow_calendar,
        self.ground_cover_stages,
        self.crop_cover_stages,
        self.autumn_sow,
    ) = self.infer_sow_harvest_calendar()

    # State variables
    self.days_after_sow = None
    self.crop_cover = 0
    self.ground_cover = 0
    self.crop_factor = 0
    self.et0_coefficient = 1

    (
        self.total_available_water,
        self.readily_available_water,
    ) = self.calculate_available_water()

    # Initiliase nutrient pools
    self.nutrient_pool = NutrientPool()

    self.inflows.insert(0, self.calc_crop_cover)
    if "nitrate" in constants.POLLUTANTS:
        # Populate function lists
        self.inflows.append(self.effective_precipitation_flushing)
        self.inflows.append(self.fertiliser)
        self.inflows.append(self.manure)
        # self.inflows.append(self.residue)

        self.processes.append(self.calc_temperature_dependence_factor)
        self.processes.append(self.calc_soil_moisture_dependence_factor)
        self.processes.append(self.soil_pool_transformation)
        self.processes.append(self.calc_crop_uptake)

        # TODO possibly move these into nutrient pool
        self.processes.append(self.erosion)
        self.processes.append(self.denitrification)
        self.processes.append(self.adsorption)

        # Reflect initial water concentration in dissolved nutrient pools
        self.nutrient_pool.dissolved_inorganic_pool.storage["P"] = self.storage[
            "phosphate"
        ]
        self.nutrient_pool.dissolved_inorganic_pool.storage["N"] = (
            self.storage["nitrate"]
            + self.storage["ammonia"]
            + self.storage["nitrite"]
        )
        self.nutrient_pool.dissolved_organic_pool.storage["P"] = self.storage[
            "org-phosphorus"
        ]
        self.nutrient_pool.dissolved_organic_pool.storage["N"] = self.storage[
            "org-nitrogen"
        ]
        if initial_soil_storage:
            self.initial_soil_storage = initial_soil_storage
            # Reflect initial nutrient stores in solid nutrient pools
            self.nutrient_pool.adsorbed_inorganic_pool.storage["P"] = (
                initial_soil_storage["phosphate"]
            )
            self.nutrient_pool.adsorbed_inorganic_pool.storage["N"] = (
                initial_soil_storage["ammonia"]
                + initial_soil_storage["nitrate"]
                + initial_soil_storage["nitrite"]
            )
            self.nutrient_pool.fast_pool.storage["N"] = initial_soil_storage[
                "org-nitrogen"
            ]
            self.nutrient_pool.fast_pool.storage["P"] = initial_soil_storage[
                "org-phosphorus"
            ]

adjust_vqip_to_liquid(vqip, deposition, in_)

Function to interoperate between surface tank and nutrient pool. Most depositions are given in terms of ammonia/nitrate/phosphate - they are then aggregated to total N or P to enter the nutrient pools. Depending on the source of deposition these may transform (e.g., some go to dissolved and some to solids) upon entering the nutrient pool. To reflect these transformations in the soil tank, the amounts entering the soil tank are adjusted proportionately.

Parameters:

Name	Type	Description	Default
vqip	dict	A VQIP amount of pollutants originally intended to enter the soil tank	required
deposition	dict	A dict with nutrients (N and P) as keys, showing the total amount of nutrients entering the nutrient pool	required
in_	dict	A dict with nutrients as keys, showing the updated amount of nutrients that entered the nutrient pool as dissolved pollutants	required

Returns:

Name	Type	Description
vqip	dict	A VQIP amount of pollutants that have been scaled to account for nutrient pool transformations

Source code in wsimod\nodes\land.py

def adjust_vqip_to_liquid(self, vqip, deposition, in_):
    """Function to interoperate between surface tank and nutrient pool. Most
    depositions are given in terms of ammonia/nitrate/phosphate - they are then
    aggregated to total N or P to enter the nutrient pools. Depending on the source
    of deposition these may transform (e.g., some go to dissolved and some to
    solids) upon entering the nutrient pool. To reflect these transformations in the
    soil tank, the amounts entering the soil tank are adjusted proportionately.

    Args:
        vqip (dict): A VQIP amount of pollutants originally intended to enter the
            soil tank
        deposition (dict): A dict with nutrients (N and P) as keys, showing the
            total amount of nutrients entering the nutrient pool
        in_ (dict): A dict with nutrients as keys, showing the updated amount of
            nutrients that entered the nutrient pool as dissolved pollutants

    Returns:
        vqip (dict): A VQIP amount of pollutants that have been scaled to account
            for nutrient pool transformations
    """
    if "nitrate" in constants.POLLUTANTS:
        if deposition["N"] > 0:
            vqip["nitrate"] *= in_["N"] / deposition["N"]
            vqip["ammonia"] *= in_["N"] / deposition["N"]
            vqip["org-nitrogen"] *= in_["N"] / deposition["N"]
        if deposition["P"] > 0:
            vqip["phosphate"] *= in_["P"] / deposition["P"]
            vqip["org-phosphorus"] *= in_["P"] / deposition["P"]

    return vqip

adsorption()

Outflow function that calculates phosphorus adsorption/desorptions and updates soil tank and nutrient pools.

Returns:

Type	Description
tuple	A tuple containing a VQIP amount for model inputs and outputs for mass balance checking.

Source code in wsimod\nodes\land.py

def adsorption(self):
    """Outflow function that calculates phosphorus adsorption/desorptions and
    updates soil tank and nutrient pools.

    Returns:
        (tuple): A tuple containing a VQIP amount for model inputs and outputs
            for mass balance checking.
    """
    # Parameters/equations from HYPE documentation TODO could this be moved to the
    # nutrient pool?

    # Initialise mass balance checking
    in_ = self.empty_vqip()
    out_ = self.empty_vqip()

    # Get total phosphorus in pool available for adsorption/desorption
    limit = self.adosorption_nr_limit
    ad_de_P_pool = (
        self.nutrient_pool.adsorbed_inorganic_pool.storage["P"]
        + self.nutrient_pool.dissolved_inorganic_pool.storage["P"]
    )  # [kg]
    ad_de_P_pool /= self.area * constants.M2_TO_KM2  # [kg/km2]
    if ad_de_P_pool == 0:
        return (self.empty_vqip(), self.empty_vqip())

    # Calculate coefficient and concentration of adsorbed phosphorus
    soil_moisture_content = (
        self.get_smc() * constants.M_TO_MM
    )  # [mm] (not sure why HYPE has this in mm but whatever)
    conc_sol = (
        self.nutrient_pool.adsorbed_inorganic_pool.storage["P"]
        * constants.KG_TO_MG
        / (self.bulk_density * self.rooting_depth * self.area)
    )  # [mg P/kg soil]
    coeff = self.kfr * self.bulk_density * self.rooting_depth  # [mm]

    # calculate equilibrium concentration
    if conc_sol <= 0:
        # Not sure how this would happen
        print("Warning: soil partP <=0. Freundlich will give error, take shortcut.")
        xn_1 = ad_de_P_pool / (soil_moisture_content + coeff)  # [mg/l]
        ad_P_equi_conc = self.kfr * xn_1  # [mg/ kg]
    else:
        # Newton-Raphson method
        x0 = exp(
            (log(conc_sol) - log(self.kfr)) / self.nfr
        )  # initial guess of equilibrium liquid concentration
        fxn = x0 * soil_moisture_content + coeff * (x0**self.nfr) - ad_de_P_pool
        xn = x0
        xn_1 = xn
        j = 0
        while (
            abs(fxn) > limit and j < self.adsorption_nr_maxiter
        ):  # iteration to calculate equilibrium concentations
            fxn = xn * soil_moisture_content + coeff * (xn**self.nfr) - ad_de_P_pool
            fprimxn = soil_moisture_content + self.nfr * coeff * (
                xn ** (self.nfr - 1)
            )
            dx = fxn / fprimxn
            if abs(dx) < (0.000001 * xn):
                # From HYPE... not sure what it means
                break
            xn_1 = xn - dx
            if xn_1 <= 0:
                xn_1 = 1e-10
            xn = xn_1
            j += 1
        ad_P_equi_conc = self.kfr * (xn_1**self.nfr)
        # print(ad_P_equi_conc, conc_sol)

    # Calculate new pool and concentration, depends on the equilibrium concentration
    if abs(ad_P_equi_conc - conc_sol) > 1e-6:
        request = self.nutrient_pool.get_empty_nutrient()

        # TODO not sure about this if statement, surely it would be triggered every
        # time
        adsdes = (ad_P_equi_conc - conc_sol) * (
            1 - exp(-self.kadsdes)
        )  # kinetic adsorption/desorption
        request["P"] = (
            adsdes
            * self.bulk_density
            * self.rooting_depth
            * (self.area * constants.M2_TO_KM2)
        )  # [kg]
        if request["P"] > 0:
            # Adsorption
            adsorbed = self.nutrient_pool.dissolved_inorganic_pool.extract(request)
            if (adsorbed["P"] - request["P"]) > constants.FLOAT_ACCURACY:
                print("Warning: freundlich flow adjusted, was larger than pool")
            self.nutrient_pool.adsorbed_inorganic_pool.receive(adsorbed)

            # Dissolved leaving the soil water tank and becoming solid
            out_["phosphate"] = adsorbed["P"]

            # Update tank
            out2_ = self.pull_pollutants(out_)
            if not self.compare_vqip(out_, out2_):
                print("nutrient pool not tracking soil tank")
        else:
            # Desorption
            request["P"] = -request["P"]
            desorbed = self.nutrient_pool.adsorbed_inorganic_pool.extract(request)
            if (desorbed["P"] - request["P"]) > constants.FLOAT_ACCURACY:
                print("Warning: freundlich flow adjusted, was larger than pool")
            self.nutrient_pool.dissolved_inorganic_pool.receive(desorbed)

            # Solid phosphorus becoming inorganic P in the soil water tank
            in_["phosphate"] = desorbed["P"]
            _ = self.push_storage(in_, force=True)

    return (in_, out_)

apply_overrides(overrides=Dict[str, Any])

Override parameters.

Enables a user to override any of the following parameters

Parameters:

Name	Type	Description	Default
overrides	Dict[str, Any]	Dict describing which parameters should be overridden (keys) and new values (values). Defaults to {}.	Dict[str, Any]

Source code in wsimod\nodes\land.py

    def apply_overrides(self, overrides=Dict[str, Any]):
        """Override parameters.

        Enables a user to override any of the following parameters

        Args:
            overrides (Dict[str, Any]): Dict describing which parameters should
                be overridden (keys) and new values (values). Defaults to {}.
        """
        overwrite_params = [
            "ET_depletion_factor",
            "crop_cover_max",
            "ground_cover_max",
            "crop_factor_stages",
            "crop_factor_stage_dates",
            "sowing_day",
            "harvest_day",
            "satact",
            "thetaupp",
            "thetalow",
            "thetapow",
            "uptake1",
            "uptake2",
            "uptake3",
            "uptake_PNratio",
            "erodibility",
            "sreroexp",
            "cohesion",
            "slope",
            "srfilt",
            "macrofilt",
            "limpar",
            "exppar",
            "hsatINs",
            "denpar",
            "adosorption_nr_limit",
            "adsorption_nr_maxiter",
            "kfr",
            "nfr",
            "kadsdes",
            "bulk_density",
        ]
        for param in overwrite_params:
            setattr(self, param, overrides.pop(param, getattr(self, param)))

        if "depth" in overrides.keys():
            overrides.pop("depth")
            print(
                "ERROR: specifying depth is depreciated in overrides for \
		GrowingSurface, please specify rooting_depth instead"
            )
        self.rooting_depth = overrides.pop("rooting_depth", self.rooting_depth)
        overrides["depth"] = self.rooting_depth
        super().apply_overrides(overrides)

        (
            self.harvest_sow_calendar,
            self.ground_cover_stages,
            self.crop_cover_stages,
            self.autumn_sow,
        ) = self.infer_sow_harvest_calendar()
        (
            self.total_available_water,
            self.readily_available_water,
        ) = self.calculate_available_water()

calc_crop_cover()

Process function that calculates how much crop cover there is, assigns whether crops are sown/harvested, and calculates et0_coefficient based on growth stage of crops.

Returns:

Type	Description
tuple	A tuple containing a VQIP amount for model inputs and outputs for mass balance checking.

Source code in wsimod\nodes\land.py

def calc_crop_cover(self):
    """Process function that calculates how much crop cover there is, assigns
    whether crops are sown/harvested, and calculates et0_coefficient based on growth
    stage of crops.

    Returns:
        (tuple): A tuple containing a VQIP amount for model inputs and outputs
            for mass balance checking.
    """
    # Get current day of year
    doy = self.parent.t.dayofyear

    if self.parent.t.is_leap_year:
        # Hacky way to handle leap years
        if doy > 59:
            doy -= 1

    if self.days_after_sow is None:
        if self.parent.t.dayofyear == self.sowing_day:
            # sow
            self.days_after_sow = 0
    else:
        if self.parent.t.dayofyear == self.harvest_day:
            # harvest
            self.days_after_sow = None
            self.crop_factor = self.crop_factor_stages[0]
            self.crop_cover = 0
            self.ground_cover = 0
        else:
            # increment days since sow
            self.days_after_sow += 1

    # Calculate relevant parameters
    self.crop_factor = self.quick_interp(
        doy, self.crop_factor_stage_dates, self.crop_factor_stages
    )
    if self.days_after_sow:
        # Move outside of this if, if you want nonzero crop/ground cover outside of
        # season
        self.crop_cover = self.quick_interp(
            doy, self.harvest_sow_calendar, self.crop_cover_stages
        )
        self.ground_cover = self.quick_interp(
            doy, self.harvest_sow_calendar, self.ground_cover_stages
        )

    root_zone_depletion = max(self.field_capacity_m - self.get_smc(), 0)
    if root_zone_depletion < self.readily_available_water:
        crop_water_stress_coefficient = 1
    else:
        crop_water_stress_coefficient = max(
            0,
            (self.total_available_water - root_zone_depletion)
            / ((1 - self.ET_depletion_factor) * self.total_available_water),
        )

    self.et0_coefficient = crop_water_stress_coefficient * self.crop_factor

    return (self.empty_vqip(), self.empty_vqip())

calc_crop_uptake()

Process function that calculates how much nutrient crops uptake and updates nutrient pool and surface tank.

Returns:

Type	Description
tuple	A tuple containing a VQIP amount for model inputs and outputs for mass balance checking.

Source code in wsimod\nodes\land.py

def calc_crop_uptake(self):
    """Process function that calculates how much nutrient crops uptake and updates
    nutrient pool and surface tank.

    Returns:
        (tuple): A tuple containing a VQIP amount for model inputs and outputs
            for mass balance checking.
    """
    # Parameters/equations from HYPE documentation

    # Initialise
    N_common_uptake = 0
    P_common_uptake = 0

    if self.days_after_sow:
        # If there are crops

        days_after_sow = self.days_after_sow

        if self.autumn_sow:
            temp_func = max(0, min(1, (self.storage["temperature"] - 5) / 20))
            days_after_sow -= 25  # Not sure why this is (but it's in HYPE)
        else:
            temp_func = 1

        # Calculate uptake
        uptake_par = (self.uptake1 - self.uptake2) * exp(
            -self.uptake3 * days_after_sow
        )
        if (uptake_par + self.uptake2) > 0:
            N_common_uptake = (
                self.uptake1
                * self.uptake2
                * self.uptake3
                * uptake_par
                / ((self.uptake2 + uptake_par) ** 2)
            )
        N_common_uptake *= temp_func * constants.G_M2_TO_KG_M2 * self.area  # [kg]
        P_common_uptake = N_common_uptake * self.uptake_PNratio
        # calculate maximum available uptake
        N_maximum_available_uptake = (
            max(0, self.storage["volume"] - self.wilting_point_m * self.area)
            / self.storage["volume"]
            * self.nutrient_pool.dissolved_inorganic_pool.storage["N"]
        )
        P_maximum_available_uptake = (
            max(0, self.storage["volume"] - self.wilting_point_m * self.area)
            / self.storage["volume"]
            * self.nutrient_pool.dissolved_inorganic_pool.storage["P"]
        )

        uptake = {
            "P": min(P_common_uptake, P_maximum_available_uptake),
            "N": min(N_common_uptake, N_maximum_available_uptake),
        }
        crop_uptake = self.nutrient_pool.dissolved_inorganic_pool.extract(uptake)
        out_ = self.empty_vqip()

        # Assuming plants eat N and P as nitrate and phosphate
        out_["nitrate"] = crop_uptake["N"]
        out_["phosphate"] = crop_uptake["P"]

        out2_ = self.pull_pollutants(out_)
        if not self.compare_vqip(out_, out2_):
            print("nutrient pool not tracking soil tank")

        return (self.empty_vqip(), out_)
    else:
        return (self.empty_vqip(), self.empty_vqip())

calc_soil_moisture_dependence_factor()

Process function that calculates the soil moisture dependence factor for the nutrient pool (which impacts soil pool transformations).

Returns:

Type	Description
tuple	A tuple containing a VQIP amount for model inputs and outputs for mass balance checking.

Source code in wsimod\nodes\land.py

def calc_soil_moisture_dependence_factor(self):
    """Process function that calculates the soil moisture dependence factor for the
    nutrient pool (which impacts soil pool transformations).

    Returns:
        (tuple): A tuple containing a VQIP amount for model inputs and outputs
            for mass balance checking.
    """
    # Parameters/equations from HYPE documentation
    current_soil_moisture = self.get_smc()
    if current_soil_moisture >= self.field_capacity_m:
        self.nutrient_pool.soil_moisture_dependence_factor = self.satact
    elif current_soil_moisture <= self.wilting_point_m:
        self.nutrient_pool.soil_moisture_dependence_factor = 0
    else:
        fc_diff = self.field_capacity_m - current_soil_moisture
        fc_comp = (fc_diff / (self.thetaupp * self.rooting_depth)) ** self.thetapow
        fc_comp = (1 - self.satact) * fc_comp + self.satact
        wp_diff = current_soil_moisture - self.wilting_point_m
        wp_comp = (wp_diff / (self.thetalow * self.rooting_depth)) ** self.thetapow
        self.nutrient_pool.soil_moisture_dependence_factor = min(
            1, wp_comp, fc_comp
        )
    return (self.empty_vqip(), self.empty_vqip())

calc_temperature_dependence_factor()

Process function that calculates the temperature dependence factor for the nutrient pool (which impacts soil pool transformations).

Returns:

Type	Description
tuple	A tuple containing a VQIP amount for model inputs and outputs for mass balance checking.

Source code in wsimod\nodes\land.py

def calc_temperature_dependence_factor(self):
    """Process function that calculates the temperature dependence factor for the
    nutrient pool (which impacts soil pool transformations).

    Returns:
        (tuple): A tuple containing a VQIP amount for model inputs and outputs
            for mass balance checking.
    """
    # Parameters/equations from HYPE documentation
    if self.storage["temperature"] > 5:
        temperature_dependence_factor = 2 ** (
            (self.storage["temperature"] - 20) / 10
        )
    elif self.storage["temperature"] > 0:
        temperature_dependence_factor = self.storage["temperature"] / 5
    else:
        temperature_dependence_factor = 0
    self.nutrient_pool.temperature_dependence_factor = temperature_dependence_factor
    return (self.empty_vqip(), self.empty_vqip())

calculate_available_water()

Calculate total/readily available water based on capacity/wp. Returns: (float): total available water (float): readily available water

Source code in wsimod\nodes\land.py

def calculate_available_water(self):
    """Calculate total/readily available water based on capacity/wp.
    Returns:
        (float): total available water
        (float): readily available water
    """
    # Calculate parameters based on capacity/wp
    total_available_water = self.field_capacity_m - self.wilting_point_m
    if total_available_water < 0:
        print("warning: TAW < 0...")
    readily_available_water = total_available_water * self.ET_depletion_factor

    return total_available_water, readily_available_water

denitrification()

Outflow function that performs denitirication processes, updating nutrient pool and soil tank.

Returns:

Type	Description
tuple	A tuple containing a VQIP amount for model inputs and outputs for mass balance checking.

Source code in wsimod\nodes\land.py

def denitrification(self):
    """Outflow function that performs denitirication processes, updating nutrient
    pool and soil tank.

    Returns:
        (tuple): A tuple containing a VQIP amount for model inputs and outputs
            for mass balance checking.
    """
    # Parameters/equations from HYPE documentation TODO could more of this be moved
    # to NutrientPool Calculate soil moisture dependence of denitrification
    soil_moisture_content = self.get_smc()
    if soil_moisture_content > self.field_capacity_m:
        denitrifying_soil_moisture_dependence = 1
    elif soil_moisture_content / self.field_capacity_m > self.limpar:
        denitrifying_soil_moisture_dependence = (
            ((soil_moisture_content / self.field_capacity_m) - self.limpar)
            / (1 - self.limpar)
        ) ** self.exppar
    else:
        denitrifying_soil_moisture_dependence = 0
        return (self.empty_vqip(), self.empty_vqip())

    # Get dissolved inorg nitrogen as a concentration and calculate factor
    din_conc = (
        self.nutrient_pool.dissolved_inorganic_pool.storage["N"]
        / self.storage["volume"]
    )  # [kg/m3]
    din_conc *= constants.KG_M3_TO_MG_L
    half_saturation_concentration_dependence_factor = din_conc / (
        din_conc + self.hsatINs
    )

    # Calculate and extract dentrified nitrogen
    denitrified_N = (
        self.nutrient_pool.dissolved_inorganic_pool.storage["N"]
        * half_saturation_concentration_dependence_factor
        * denitrifying_soil_moisture_dependence
        * self.nutrient_pool.temperature_dependence_factor
        * self.denpar
    )
    denitrified_request = self.nutrient_pool.get_empty_nutrient()
    denitrified_request["N"] = denitrified_N
    denitrified_N = self.nutrient_pool.dissolved_inorganic_pool.extract(
        denitrified_request
    )

    # Leon reckons this should leave the model (though I think technically some
    # small amount goes to nitrite)
    out_ = self.empty_vqip()
    out_["nitrate"] = denitrified_N["N"]

    # Update tank
    out2_ = self.pull_pollutants(out_)
    if not self.compare_vqip(out_, out2_):
        print("nutrient pool not tracking soil tank")

    return (self.empty_vqip(), out_)

dry_deposition_to_tank(vqip)

Allocate dry deposition to surface tank, updating nutrient pool accordingly.

Parameters:

Name	Type	Description	Default
vqip	dict	A VQIP amount of dry deposition to send to tank	required

Returns:

Name	Type	Description
vqip	dict	A VQIP amount of dry deposition that entered the tank (used for mass balance checking)

Source code in wsimod\nodes\land.py

def dry_deposition_to_tank(self, vqip):
    """Allocate dry deposition to surface tank, updating nutrient pool accordingly.

    Args:
        vqip (dict): A VQIP amount of dry deposition to send to tank

    Returns:
        vqip (dict): A VQIP amount of dry deposition that entered the tank (used
            for mass balance checking)
    """
    # Convert to nutrients
    deposition = self.nutrient_pool.get_empty_nutrient()
    deposition["N"] = vqip["nitrate"] + vqip["ammonia"]
    deposition["P"] = vqip["phosphate"]

    # Update nutrient pool
    in_ = self.nutrient_pool.allocate_dry_deposition(deposition)
    vqip = self.adjust_vqip_to_liquid(vqip, deposition, in_)

    # Update tank
    self.push_storage(vqip, force=True)
    return vqip

effective_precipitation_flushing()

Remove the nutrients brought out by effective precipitation, which is surface runoff, subsurface runoff, and percolation, from the nutrients pool.

Returns:

Type	Description
tuple	A tuple containing a VQIP amount for model inputs and outputs for mass balance checking.

Source code in wsimod\nodes\land.py

def effective_precipitation_flushing(self):
    """Remove the nutrients brought out by effective precipitation, which is surface
    runoff, subsurface runoff, and percolation, from the nutrients pool.

    Returns:
        (tuple): A tuple containing a VQIP amount for model inputs and outputs
                for mass balance checking.
    """
    # inorganic
    out = self.nutrient_pool.get_empty_nutrient()
    out["N"] = (
        self.subsurface_flow["ammonia"]
        + self.subsurface_flow["nitrite"]
        + self.subsurface_flow["nitrate"]
        + self.percolation["ammonia"]
        + self.percolation["nitrite"]
        + self.percolation["nitrate"]
        + self.infiltration_excess["ammonia"]
        + self.infiltration_excess["nitrite"]
        + self.infiltration_excess["nitrate"]
    )  # TODO what happens if infiltration excess (the real part) has pollutants?
    out["P"] = (
        self.subsurface_flow["phosphate"]
        + self.percolation["phosphate"]
        + self.infiltration_excess["phosphate"]
    )
    self.nutrient_pool.dissolved_inorganic_pool.extract(out)

    # organic
    out = self.nutrient_pool.get_empty_nutrient()
    out["N"] = (
        self.subsurface_flow["org-nitrogen"]
        + self.percolation["org-nitrogen"]
        + self.infiltration_excess["org-nitrogen"]
    )
    out["P"] = (
        self.subsurface_flow["org-phosphorus"]
        + self.percolation["org-phosphorus"]
        + self.infiltration_excess["org-phosphorus"]
    )
    self.nutrient_pool.dissolved_organic_pool.extract(out)

    return (self.empty_vqip(), self.empty_vqip())

erosion()

Outflow function that erodes adsorbed/humus phosphorus and sediment and sends onwards to percolation/surface runoff/subsurface runoff.

Returns:

Type	Description
tuple	A tuple containing a VQIP amount for model inputs and outputs for mass balance checking.

Source code in wsimod\nodes\land.py

def erosion(self):
    """Outflow function that erodes adsorbed/humus phosphorus and sediment and sends
    onwards to percolation/surface runoff/subsurface runoff.

    Returns:
        (tuple): A tuple containing a VQIP amount for model inputs and outputs
            for mass balance checking.
    """
    # Parameters/equations from HYPE documentation (which explains why my
    # documentation is a bit ambiguous - because theirs is too)

    # Convert precipitation to MM since all the equations assume that
    precipitation_depth = self.get_data_input("precipitation") * constants.M_TO_MM

    # Calculate how much rain is mobilising erosion
    if precipitation_depth > 5:
        rainfall_energy = 8.95 + 8.44 * log10(
            precipitation_depth
            * (
                0.257
                + sin(2 * constants.PI * ((self.parent.t.dayofyear - 70) / 365))
                * 0.09
            )
            * 2
        )
        rainfall_energy *= precipitation_depth
        mobilised_rain = rainfall_energy * (1 - self.crop_cover) * self.erodibility
    else:
        mobilised_rain = 0

    # Calculate if any infiltration is mobilising erosion
    if self.infiltration_excess["volume"] > 0:
        mobilised_flow = (
            self.infiltration_excess["volume"] / self.area * constants.M_TO_MM * 365
        ) ** self.sreroexp
        mobilised_flow *= (
            (1 - self.ground_cover)
            * (1 / (0.5 * self.cohesion))
            * sin(self.slope / 100)
            / 365
        )
    else:
        mobilised_flow = 0

    # Sum flows (not sure why surface runoff isn't included) TODO I'm pretty sure it
    # should be included here
    total_flows = (
        self.infiltration_excess["volume"]
        + self.subsurface_flow["volume"]
        + self.percolation["volume"]
    )  # m3/dt + self.tank_recharge['volume'] (guess not needed)

    # Convert to MM/M2
    erodingflow = total_flows / self.area * constants.M_TO_MM

    # Calculate eroded sediment
    transportfactor = min(1, (erodingflow / 4) ** 1.3)
    erodedsed = (
        1000 * (mobilised_flow + mobilised_rain) * transportfactor
    )  # [kg/km2]
    # TODO not sure what conversion this HYPE 1000 is referring to

    # soil erosion with adsorbed inorganic phosphorus and humus phosphorus (erodedP
    # as P in eroded sediments and effect of enrichment)
    if erodingflow > 4:
        enrichment = 1.5
    elif erodingflow > 0:
        enrichment = 4 - (4 - 1.5) * erodingflow / 4
    else:
        return (self.empty_vqip(), self.empty_vqip())

    # Get erodable phosphorus
    erodableP = (
        self.nutrient_pool.get_erodable_P() / self.area * constants.KG_M2_TO_KG_KM2
    )
    erodedP = (
        erodedsed
        * (
            erodableP
            / (
                self.rooting_depth
                * constants.M_TO_KM
                * self.bulk_density
                * constants.KG_M3_TO_KG_KM3
            )
        )
        * enrichment
    )  # [kg/km2]

    # Convert to kg
    erodedP *= self.area * constants.M2_TO_KM2  # [kg]
    erodedsed *= self.area * constants.M2_TO_KM2  # [kg]

    # Allocate to different flows
    surface_erodedP = (
        self.srfilt * self.infiltration_excess["volume"] / total_flows * erodedP
    )  # [kg]
    surface_erodedsed = (
        self.srfilt * self.infiltration_excess["volume"] / total_flows * erodedsed
    )  # [kg]

    subsurface_erodedP = (
        self.macrofilt * self.subsurface_flow["volume"] / total_flows * erodedP
    )  # [kg]
    subsurface_erodedsed = (
        self.macrofilt * self.subsurface_flow["volume"] / total_flows * erodedsed
    )  # [kg]

    percolation_erodedP = (
        self.macrofilt * self.percolation["volume"] / total_flows * erodedP
    )  # [kg]
    percolation_erodedsed = (
        self.macrofilt * self.percolation["volume"] / total_flows * erodedsed
    )  # [kg]

    # Track mass balance
    in_ = self.empty_vqip()

    # Total eroded phosphorus
    eff_erodedP = percolation_erodedP + surface_erodedP + subsurface_erodedP  # [kg]
    if eff_erodedP > 0:
        # Update nutrient pool
        org_removed, inorg_removed = self.nutrient_pool.erode_P(eff_erodedP)
        total_removed = inorg_removed + org_removed

        if abs(total_removed - eff_erodedP) > constants.FLOAT_ACCURACY:
            print("weird nutrients")

        # scale flows to split between inorganic and organic eroded P
        self.infiltration_excess["org-phosphorus"] += (
            surface_erodedP * org_removed / eff_erodedP
        )
        self.subsurface_flow["org-phosphorus"] += (
            subsurface_erodedP * org_removed / eff_erodedP
        )
        self.percolation["org-phosphorus"] += (
            percolation_erodedP * org_removed / eff_erodedP
        )

        # TODO Leon reckons this is conceptually dodgy.. but i'm not sure where else
        # adsorbed inorganic phosphorus should go
        self.infiltration_excess["phosphate"] += (
            surface_erodedP * inorg_removed / eff_erodedP
        )
        self.subsurface_flow["phosphate"] += (
            subsurface_erodedP * inorg_removed / eff_erodedP
        )
        self.percolation["phosphate"] += (
            percolation_erodedP * inorg_removed / eff_erodedP
        )

        # Entering the model (no need to uptake surface tank because both adsorbed
        # inorganic pool and humus pool are solids and so no tracked in the soil
        # water tank)
        in_["phosphate"] = inorg_removed
        in_["org-phosphorus"] = org_removed
    else:
        pass

    # Track sediment as solids
    self.infiltration_excess["solids"] += surface_erodedsed
    self.subsurface_flow["solids"] += subsurface_erodedsed
    self.percolation["solids"] += percolation_erodedsed

    in_["solids"] = surface_erodedsed + subsurface_erodedsed + percolation_erodedsed

    return (in_, self.empty_vqip())

fertiliser()

Read, scale and allocate fertiliser, updating the tank.

Returns:

Type	Description
tuple	A tuple containing a VQIP amount for model inputs and outputs for mass balance checking.

Source code in wsimod\nodes\land.py

def fertiliser(self):
    """Read, scale and allocate fertiliser, updating the tank.

    Returns:
        (tuple): A tuple containing a VQIP amount for model inputs and outputs
            for mass balance checking.
    """
    # TODO tidy up fertiliser/manure/residue/deposition once preprocessing is sorted

    # Scale for surface
    nhx = self.get_data_input_surface("nhx-fertiliser") * self.area
    noy = self.get_data_input_surface("noy-fertiliser") * self.area
    srp = self.get_data_input_surface("srp-fertiliser") * self.area

    # Update as VQIP
    vqip = self.empty_vqip()
    vqip["ammonia"] = nhx
    vqip["nitrate"] = noy
    vqip["phosphate"] = srp

    # Enter nutrient pool
    deposition = self.nutrient_pool.get_empty_nutrient()
    deposition["N"] = vqip["nitrate"] + vqip["ammonia"]
    deposition["P"] = vqip["phosphate"]
    in_ = self.nutrient_pool.allocate_fertiliser(deposition)

    # Update tank
    vqip = self.adjust_vqip_to_liquid(vqip, deposition, in_)
    self.push_storage(vqip, force=True)

    return (vqip, self.empty_vqip())

infer_sow_harvest_calendar()

Infer basic sow/harvest calendar and indicate autumn-sown. Returns: (list): havest/sow calendar (list): ground cover stages (list): crop cover stages (boolean): indication for autumn-sown crops

Source code in wsimod\nodes\land.py

def infer_sow_harvest_calendar(self):
    """Infer basic sow/harvest calendar and indicate autumn-sown.
    Returns:
        (list): havest/sow calendar
        (list): ground cover stages
        (list): crop cover stages
        (boolean): indication for autumn-sown crops
    """
    # Infer basic sow/harvest calendar
    harvest_sow_calendar = [
        0,
        self.sowing_day,
        self.harvest_day,
        self.harvest_day + 1,
        365,
    ]
    ground_cover_stages = [0, 0, self.ground_cover_max, 0, 0]
    crop_cover_stages = [0, 0, self.crop_cover_max, 0, 0]

    # Use day number of 181 to indicate autumn-sown (from HYPE)
    if self.sowing_day > 181:
        autumn_sow = True
    else:
        autumn_sow = False

    return harvest_sow_calendar, ground_cover_stages, crop_cover_stages, autumn_sow

manure()

Read, scale and allocate manure, updating the tank.

Returns:

Type	Description
tuple	A tuple containing a VQIP amount for model inputs and outputs for mass balance checking.

Source code in wsimod\nodes\land.py

def manure(self):
    """Read, scale and allocate manure, updating the tank.

    Returns:
        (tuple): A tuple containing a VQIP amount for model inputs and outputs
            for mass balance checking.
    """
    # Scale for surface
    nhx = self.get_data_input_surface("nhx-manure") * self.area
    noy = self.get_data_input_surface("noy-manure") * self.area
    srp = self.get_data_input_surface("srp-manure") * self.area

    # Formulate as VQIP
    vqip = self.empty_vqip()
    vqip["ammonia"] = nhx
    vqip["nitrate"] = noy
    vqip["phosphate"] = srp

    # Enter nutrient pool
    deposition = self.nutrient_pool.get_empty_nutrient()
    deposition["N"] = vqip["nitrate"] + vqip["ammonia"]
    deposition["P"] = vqip["phosphate"]
    in_ = self.nutrient_pool.allocate_manure(deposition)

    # Update tank
    vqip = self.adjust_vqip_to_liquid(vqip, deposition, in_)

    self.push_storage(vqip, force=True)

    return (vqip, self.empty_vqip())

pull_storage(vqip)

Pull water from the surface, updating the surface storage VQIP. Nutrient pool pollutants (nitrate/nitrite/ammonia/phosphate/org- phosphorus/ org-nitrogen) are removed in proportion to their amounts in the dissolved nutrient pools, if they are simulated. Other pollutants are removed in proportion to their amount in the surface tank.

Parameters:

Name	Type	Description	Default
vqip	dict	VQIP amount to be pulled, (only 'volume' key is needed)	required

Returns:

Name	Type	Description
reply	dict	A VQIP amount successfully pulled from the tank

Source code in wsimod\nodes\land.py

def pull_storage(self, vqip):
    """Pull water from the surface, updating the surface storage VQIP. Nutrient pool
    pollutants (nitrate/nitrite/ammonia/phosphate/org- phosphorus/ org-nitrogen) are
    removed in proportion to their amounts in the dissolved nutrient pools, if they
    are simulated. Other pollutants are removed in proportion to their amount in the
    surface tank.

    Args:
        vqip (dict): VQIP amount to be pulled, (only 'volume' key is needed)

    Returns:
        reply (dict): A VQIP amount successfully pulled from the tank
    """
    if self.storage["volume"] == 0:
        return self.empty_vqip()

    # Adjust based on available volume
    reply = min(vqip["volume"], self.storage["volume"])

    # Update reply to vqip (get concentration for non-nutrients)
    reply = self.v_change_vqip(self.storage, reply)

    if "nitrate" in constants.POLLUTANTS:
        # Update nutrient pool and get concentration for nutrients
        prop = reply["volume"] / self.storage["volume"]
        nutrients = self.nutrient_pool.extract_dissolved(prop)
        reply["nitrate"] = (
            nutrients["inorganic"]["N"]
            * self.storage["nitrate"]
            / (
                self.storage["nitrate"]
                + self.storage["ammonia"]
                + self.storage["nitrite"]
            )
        )
        reply["ammonia"] = (
            nutrients["inorganic"]["N"]
            * self.storage["ammonia"]
            / (
                self.storage["nitrate"]
                + self.storage["ammonia"]
                + self.storage["nitrite"]
            )
        )
        reply["nitrite"] = (
            nutrients["inorganic"]["N"]
            * self.storage["nitrite"]
            / (
                self.storage["nitrate"]
                + self.storage["ammonia"]
                + self.storage["nitrite"]
            )
        )
        reply["phosphate"] = nutrients["inorganic"]["P"]
        reply["org-phosphorus"] = nutrients["organic"]["P"]
        reply["org-nitrogen"] = nutrients["organic"]["N"]

    # Extract from storage
    self.storage = self.extract_vqip(self.storage, reply)

    return reply

quick_interp(x, xp, yp)

A simple version of np.interp to intepolate crop information on the fly.

Parameters:

Name	Type	Description	Default
x	int	Current time (i.e., day of year) xp (list): Predefined times (i.e.,	required
list	of days of year) yp (list	Predefined values associated with xp	required

Returns:

Name	Type	Description
y	float	Interpolated value for current time

Source code in wsimod\nodes\land.py

def quick_interp(self, x, xp, yp):
    """A simple version of np.interp to intepolate crop information on the fly.

    Args:
        x (int): Current time (i.e., day of year) xp (list): Predefined times (i.e.,
        list of days of year) yp (list): Predefined values associated with xp

    Returns:
        y (float): Interpolated value for current time
    """
    x_ind = bisect_left(xp, x)
    x_left = xp[x_ind - 1]
    x_right = xp[x_ind]
    dif = x - x_left
    y_left = yp[x_ind - 1]
    y_right = yp[x_ind]
    y = y_left + (y_right - y_left) * dif / (x_right - x_left)
    return y

residue()

Read, scale and allocate residue, updating the tank (NOT CURRENTLY USED BECAUSE NO DATA SOURCES FOR RESIDUE CAN BE IDENTIFIED).

Returns:

Type	Description
tuple	A tuple containing a VQIP amount for model inputs and outputs for mass balance checking.

Source code in wsimod\nodes\land.py

def residue(self):
    """Read, scale and allocate residue, updating the tank (NOT CURRENTLY USED
    BECAUSE NO DATA SOURCES FOR RESIDUE CAN BE IDENTIFIED).

    Returns:
        (tuple): A tuple containing a VQIP amount for model inputs and outputs
            for mass balance checking.
    """
    nhx = self.get_data_input_surface("nhx-residue") * self.area
    noy = self.get_data_input_surface("noy-residue") * self.area
    srp = self.get_data_input_surface("srp-residue") * self.area

    vqip = self.empty_vqip()
    vqip["ammonia"] = nhx * self.nutrient_pool.fraction_residue_to_fast["N"]
    vqip["nitrate"] = noy * self.nutrient_pool.fraction_residue_to_fast["N"]
    vqip["org-nitrogen"] = (
        nhx + noy
    ) * self.nutrient_pool.fraction_residue_to_humus["N"]
    vqip["phosphate"] = srp * self.nutrient_pool.fraction_residue_to_fast["P"]
    vqip["org-phosphorus"] = srp * self.nutrient_pool.fraction_residue_to_humus["P"]

    deposition = self.nutrient_pool.get_empty_nutrient()
    deposition["N"] = vqip["nitrate"] + vqip["ammonia"] + vqip["org-nitrogen"]
    deposition["P"] = vqip["phosphate"] + vqip["org-phosphorus"]

    in_ = self.nutrient_pool.allocate_residue(deposition)
    vqip = self.adjust_vqip_to_liquid(vqip, deposition, in_)

    self.push_storage(vqip, force=True)

    return (vqip, self.empty_vqip())

soil_pool_transformation()

A process function that run transformation functions in the nutrient pool and updates the pollutant concentrations in the surface tank.

Returns:

Type	Description
tuple	A tuple containing a VQIP amount for model inputs and outputs for mass balance checking.

Source code in wsimod\nodes\land.py

def soil_pool_transformation(self):
    """A process function that run transformation functions in the nutrient pool and
    updates the pollutant concentrations in the surface tank.

    Returns:
        (tuple): A tuple containing a VQIP amount for model inputs and outputs
            for mass balance checking.
    """
    # Initialise mass balance tracking variables
    in_ = self.empty_vqip()
    out_ = self.empty_vqip()

    # Get proportion of nitrogen that is nitrate in the soil tank NOTE ignores
    # nitrite - couldn't find enough information on it
    nitrate_proportion = self.storage["nitrate"] / (
        self.storage["nitrate"] + self.storage["ammonia"]
    )

    # Run soil pool functions
    (
        increase_in_dissolved_inorganic,
        increase_in_dissolved_organic,
    ) = self.nutrient_pool.soil_pool_transformation()

    # Update tank and mass balance TODO .. there is definitely a neater way to write
    # this
    if increase_in_dissolved_inorganic["N"] > 0:
        # Increase in inorganic nitrogen, rescale back to nitrate and ammonia
        in_["nitrate"] = increase_in_dissolved_inorganic["N"] * nitrate_proportion
        in_["ammonia"] = increase_in_dissolved_inorganic["N"] * (
            1 - nitrate_proportion
        )
    else:
        # Decrease in inorganic nitrogen, rescale back to nitrate and ammonia
        out_["nitrate"] = -increase_in_dissolved_inorganic["N"] * nitrate_proportion
        out_["ammonia"] = -increase_in_dissolved_inorganic["N"] * (
            1 - nitrate_proportion
        )

    if increase_in_dissolved_organic["N"] > 0:
        # Increase in organic nitrogen
        in_["org-nitrogen"] = increase_in_dissolved_organic["N"]
    else:
        # Decrease in organic nitrogen
        out_["org-nitrogen"] = -increase_in_dissolved_organic["N"]

    if increase_in_dissolved_inorganic["P"] > 0:
        # Increase in inorganic phosphate
        in_["phosphate"] = increase_in_dissolved_inorganic["P"]
    else:
        # Decrease in inorganic phosphate
        out_["phosphate"] = -increase_in_dissolved_inorganic["P"]

    if increase_in_dissolved_organic["P"] > 0:
        # Increase in organic phosphorus
        in_["org-phosphorus"] = increase_in_dissolved_organic["P"]
    else:
        # Decrease in organic phosphorus
        out_["org-phosphorus"] = -increase_in_dissolved_organic["P"]

    # Update tank with inputs/outputs of pollutants
    _ = self.push_storage(in_, force=True)
    out2_ = self.pull_pollutants(out_)

    if not self.compare_vqip(out_, out2_):
        print("nutrient pool not tracking soil tank")

    return (in_, out_)

wet_deposition_to_tank(vqip)

Allocate wet deposition to surface tank, updating nutrient pool accordingly.

Parameters:

Name	Type	Description	Default
vqip	dict	A VQIP amount of dry deposition to send to tank	required

Returns:

Name	Type	Description
vqip	dict	A VQIP amount of dry deposition that entered the tank (used for mass balance checking)

Source code in wsimod\nodes\land.py

def wet_deposition_to_tank(self, vqip):
    """Allocate wet deposition to surface tank, updating nutrient pool accordingly.

    Args:
        vqip (dict): A VQIP amount of dry deposition to send to tank

    Returns:
        vqip (dict): A VQIP amount of dry deposition that entered the tank (used
            for mass balance checking)
    """
    # Convert to nutrients
    deposition = self.nutrient_pool.get_empty_nutrient()
    deposition["N"] = vqip["nitrate"] + vqip["ammonia"]
    deposition["P"] = vqip["phosphate"]

    # Update nutrient pool
    in_ = self.nutrient_pool.allocate_wet_deposition(deposition)
    vqip = self.adjust_vqip_to_liquid(vqip, deposition, in_)

    # Update tank
    self.push_storage(vqip, force=True)
    return vqip

ImperviousSurface

Bases: Surface

Source code in wsimod\nodes\land.py

class ImperviousSurface(Surface):
    """"""

    def __init__(self, pore_depth=0, et0_to_e=1, **kwargs):
        """A surface to represent impervious surfaces that drain to storm sewers. Runoff
        is generated by the surface tank overflowing, if a user wants all precipitation
        to immediately go to runoff then they should reduce 'pore_depth', however
        generally this is not what happens and a small (a few mm) depth should be
        assigned to the tank. Also includes urban pollution deposition, though this will
        only be mobilised if runoff occurs.

        Note that the tank does not have a runoff coefficient because it doesn't make
        sense from an integrated perspective. If a user wants to mimic runoff
        coefficient-like behaviour, then they should reduce the ImperviousSurface tank
        size, and increase other surfaces of the parent land node accordingly.

        Args:
            pore_depth (float, optional): The depth of the tank that must be exceeded
                to generate runoff. Intended to represent the pores in ashpalt that
                water accumulates in before flowing. Defaults to 0.
            et0_to_e (float, optional): Multiplier applied to the parent's data
                timeseries of et0 to determine how much evaporation takes place on the
                ImperviousSurface. Defaults to 1.
        """
        # Assign parameters
        self.et0_to_e = et0_to_e  # Total evaporation
        self.pore_depth = pore_depth

        super().__init__(depth=pore_depth, **kwargs)

        # Initialise state variables
        self.evaporation = self.empty_vqip()
        self.precipitation = self.empty_vqip()

        # Populate function lists
        self.inflows.append(self.precipitation_evaporation)

        self.outflows.append(self.push_to_sewers)

    def apply_overrides(self, overrides=Dict[str, Any]):
        """Override parameters.

        Enables a user to override any of the following parameters:
        eto_to_e, pore_depth.

        Args:
            overrides (Dict[str, Any]): Dict describing which parameters should
                be overridden (keys) and new values (values). Defaults to {}.
        """
        self.et0_to_e = overrides.pop("et0_to_e", self.et0_to_e)
        if "depth" in overrides.keys():
            overrides.pop("depth")
            print(
                "ERROR: specifying depth is depreciated in overrides for \
		impervious surface, please specify pore_depth instead"
            )
        self.pore_depth = overrides.pop("pore_depth", self.pore_depth)
        self.depth = self.pore_depth
        self.capacity = self.area * self.depth
        super().apply_overrides(overrides)

    def precipitation_evaporation(self):
        """Inflow function that is a simple rainfall-evaporation model, updating the.

        surface tank. All precipitation that is not evaporated is forced into the tank
        (even though some of that will later be pushed to sewers) - this enables runoff
        to mix with the accumulated pollutants in the surface pores.

        Returns:
            (tuple): A tuple containing a VQIP amount for model inputs and outputs
                for mass balance checking.
        """
        # Read data in length units
        precipitation_depth = self.get_data_input("precipitation")
        evaporation_depth = self.get_data_input("et0") * self.et0_to_e

        if precipitation_depth < evaporation_depth:
            # No effective precipitation
            net_precipitation = 0

            # Calculate how much should be evaporated from pores
            evaporation_from_pores = evaporation_depth - precipitation_depth

            # Scale
            evaporation_from_pores *= self.area

            # Pull from tank
            evaporation_from_pores = self.evaporate(evaporation_from_pores)

            # Scale to get actual evaporation
            total_evaporation = evaporation_from_pores + precipitation_depth * self.area
        else:
            # Effective precipitation
            net_precipitation = precipitation_depth - evaporation_depth

            # Scale
            net_precipitation *= self.area
            net_precipitation = self.v_change_vqip(self.empty_vqip(), net_precipitation)

            # Assign a temperature value TODO how hot is rain? No idea... just going to
            # use surface air temperature
            net_precipitation["temperature"] = self.get_data_input("temperature")

            # Update tank
            _ = self.push_storage(net_precipitation, force=True)
            total_evaporation = evaporation_depth * self.area

        # Converrt to VQIP
        self.evaporation = self.v_change_vqip(self.empty_vqip(), total_evaporation)
        self.precipitation = self.v_change_vqip(
            self.empty_vqip(), precipitation_depth * self.area
        )

        return (self.precipitation, self.evaporation)

    def push_to_sewers(self):
        """Outflow function that distributes ponded water (i.e., surface runoff) to the
        parent node's attached sewers.

        Returns:
            (tuple): A tuple containing a VQIP amount for model inputs and outputs
                for mass balance checking.
        """
        # Get runoff
        surface_runoff = self.pull_ponded()

        # Distribute TODO in cwsd_partition this is done with timearea
        reply = self.parent.push_distributed(surface_runoff, of_type=["Sewer"])

        # Update tank (forcing, because if the water can't go to the sewer, where else
        # can it go)
        _ = self.push_storage(reply, force=True)
        # TODO... possibly this could flow to attached river or land nodes.. or other
        # surfaces? I expect this doesn't matter for large scale models.. but may need
        # to be revisited for detailed sewer models

        # Return empty mass balance because outflows are handled by parent
        return (self.empty_vqip(), self.empty_vqip())

__init__(pore_depth=0, et0_to_e=1, **kwargs)

A surface to represent impervious surfaces that drain to storm sewers. Runoff is generated by the surface tank overflowing, if a user wants all precipitation to immediately go to runoff then they should reduce 'pore_depth', however generally this is not what happens and a small (a few mm) depth should be assigned to the tank. Also includes urban pollution deposition, though this will only be mobilised if runoff occurs.

Note that the tank does not have a runoff coefficient because it doesn't make sense from an integrated perspective. If a user wants to mimic runoff coefficient-like behaviour, then they should reduce the ImperviousSurface tank size, and increase other surfaces of the parent land node accordingly.

Parameters:

Name	Type	Description	Default
pore_depth	float	The depth of the tank that must be exceeded to generate runoff. Intended to represent the pores in ashpalt that water accumulates in before flowing. Defaults to 0.	0
et0_to_e	float	Multiplier applied to the parent's data timeseries of et0 to determine how much evaporation takes place on the ImperviousSurface. Defaults to 1.	1

Source code in wsimod\nodes\land.py

def __init__(self, pore_depth=0, et0_to_e=1, **kwargs):
    """A surface to represent impervious surfaces that drain to storm sewers. Runoff
    is generated by the surface tank overflowing, if a user wants all precipitation
    to immediately go to runoff then they should reduce 'pore_depth', however
    generally this is not what happens and a small (a few mm) depth should be
    assigned to the tank. Also includes urban pollution deposition, though this will
    only be mobilised if runoff occurs.

    Note that the tank does not have a runoff coefficient because it doesn't make
    sense from an integrated perspective. If a user wants to mimic runoff
    coefficient-like behaviour, then they should reduce the ImperviousSurface tank
    size, and increase other surfaces of the parent land node accordingly.

    Args:
        pore_depth (float, optional): The depth of the tank that must be exceeded
            to generate runoff. Intended to represent the pores in ashpalt that
            water accumulates in before flowing. Defaults to 0.
        et0_to_e (float, optional): Multiplier applied to the parent's data
            timeseries of et0 to determine how much evaporation takes place on the
            ImperviousSurface. Defaults to 1.
    """
    # Assign parameters
    self.et0_to_e = et0_to_e  # Total evaporation
    self.pore_depth = pore_depth

    super().__init__(depth=pore_depth, **kwargs)

    # Initialise state variables
    self.evaporation = self.empty_vqip()
    self.precipitation = self.empty_vqip()

    # Populate function lists
    self.inflows.append(self.precipitation_evaporation)

    self.outflows.append(self.push_to_sewers)

apply_overrides(overrides=Dict[str, Any])

Override parameters.

Enables a user to override any of the following parameters: eto_to_e, pore_depth.

Parameters:

Name	Type	Description	Default
overrides	Dict[str, Any]	Dict describing which parameters should be overridden (keys) and new values (values). Defaults to {}.	Dict[str, Any]

Source code in wsimod\nodes\land.py

    def apply_overrides(self, overrides=Dict[str, Any]):
        """Override parameters.

        Enables a user to override any of the following parameters:
        eto_to_e, pore_depth.

        Args:
            overrides (Dict[str, Any]): Dict describing which parameters should
                be overridden (keys) and new values (values). Defaults to {}.
        """
        self.et0_to_e = overrides.pop("et0_to_e", self.et0_to_e)
        if "depth" in overrides.keys():
            overrides.pop("depth")
            print(
                "ERROR: specifying depth is depreciated in overrides for \
		impervious surface, please specify pore_depth instead"
            )
        self.pore_depth = overrides.pop("pore_depth", self.pore_depth)
        self.depth = self.pore_depth
        self.capacity = self.area * self.depth
        super().apply_overrides(overrides)

precipitation_evaporation()

Inflow function that is a simple rainfall-evaporation model, updating the.

surface tank. All precipitation that is not evaporated is forced into the tank (even though some of that will later be pushed to sewers) - this enables runoff to mix with the accumulated pollutants in the surface pores.

Returns:

Type	Description
tuple	A tuple containing a VQIP amount for model inputs and outputs for mass balance checking.

Source code in wsimod\nodes\land.py

def precipitation_evaporation(self):
    """Inflow function that is a simple rainfall-evaporation model, updating the.

    surface tank. All precipitation that is not evaporated is forced into the tank
    (even though some of that will later be pushed to sewers) - this enables runoff
    to mix with the accumulated pollutants in the surface pores.

    Returns:
        (tuple): A tuple containing a VQIP amount for model inputs and outputs
            for mass balance checking.
    """
    # Read data in length units
    precipitation_depth = self.get_data_input("precipitation")
    evaporation_depth = self.get_data_input("et0") * self.et0_to_e

    if precipitation_depth < evaporation_depth:
        # No effective precipitation
        net_precipitation = 0

        # Calculate how much should be evaporated from pores
        evaporation_from_pores = evaporation_depth - precipitation_depth

        # Scale
        evaporation_from_pores *= self.area

        # Pull from tank
        evaporation_from_pores = self.evaporate(evaporation_from_pores)

        # Scale to get actual evaporation
        total_evaporation = evaporation_from_pores + precipitation_depth * self.area
    else:
        # Effective precipitation
        net_precipitation = precipitation_depth - evaporation_depth

        # Scale
        net_precipitation *= self.area
        net_precipitation = self.v_change_vqip(self.empty_vqip(), net_precipitation)

        # Assign a temperature value TODO how hot is rain? No idea... just going to
        # use surface air temperature
        net_precipitation["temperature"] = self.get_data_input("temperature")

        # Update tank
        _ = self.push_storage(net_precipitation, force=True)
        total_evaporation = evaporation_depth * self.area

    # Converrt to VQIP
    self.evaporation = self.v_change_vqip(self.empty_vqip(), total_evaporation)
    self.precipitation = self.v_change_vqip(
        self.empty_vqip(), precipitation_depth * self.area
    )

    return (self.precipitation, self.evaporation)

push_to_sewers()

Outflow function that distributes ponded water (i.e., surface runoff) to the parent node's attached sewers.

Returns:

Type	Description
tuple	A tuple containing a VQIP amount for model inputs and outputs for mass balance checking.

Source code in wsimod\nodes\land.py

def push_to_sewers(self):
    """Outflow function that distributes ponded water (i.e., surface runoff) to the
    parent node's attached sewers.

    Returns:
        (tuple): A tuple containing a VQIP amount for model inputs and outputs
            for mass balance checking.
    """
    # Get runoff
    surface_runoff = self.pull_ponded()

    # Distribute TODO in cwsd_partition this is done with timearea
    reply = self.parent.push_distributed(surface_runoff, of_type=["Sewer"])

    # Update tank (forcing, because if the water can't go to the sewer, where else
    # can it go)
    _ = self.push_storage(reply, force=True)
    # TODO... possibly this could flow to attached river or land nodes.. or other
    # surfaces? I expect this doesn't matter for large scale models.. but may need
    # to be revisited for detailed sewer models

    # Return empty mass balance because outflows are handled by parent
    return (self.empty_vqip(), self.empty_vqip())

IrrigationSurface

Bases: GrowingSurface

Source code in wsimod\nodes\land.py

class IrrigationSurface(GrowingSurface):
    """"""

    def __init__(self, irrigation_coefficient=0.1, **kwargs):
        """A subclass of GrowingSurface that can calculate water demand for the crops
        that is not met by precipitation and use the parent node to acquire water. When
        the surface is created by the parent node, the irrigate function below is
        assigned.

        Args:
            irrigation_coefficient (float, optional): proportion area irrigated *
                proportion of demand met. Defaults to 0.1.
        """
        # Assign param
        self.irrigation_coefficient = irrigation_coefficient  # proportion area
        # irrigated * proportion of demand met

        super().__init__(**kwargs)

    def apply_overrides(self, overrides=Dict[str, Any]):
        """Override parameters.

        Enables a user to override irrigation_coefficient

        Args:
            overrides (Dict[str, Any]): Dict describing which parameters should
                be overridden (keys) and new values (values). Defaults to {}.
        """
        self.irrigation_coefficient = overrides.pop(
            "irrigation_coefficient", self.irrigation_coefficient
        )
        super().apply_overrides(overrides)

    def irrigate(self):
        """Calculate water demand for crops and call parent node to acquire water,
        updating surface tank and nutrient pools."""
        if self.days_after_sow:
            # Irrigation is just difference between evaporation and precipitation amount
            irrigation_demand = (
                max(self.evaporation["volume"] - self.precipitation["volume"], 0)
                * self.irrigation_coefficient
            )
            if irrigation_demand > constants.FLOAT_ACCURACY:
                root_zone_depletion = self.get_cmd()
                if root_zone_depletion <= constants.FLOAT_ACCURACY:
                    # TODO this isn't in FAO... but seems sensible
                    irrigation_demand = 0

                # Pull water using parent node
                supplied = self.parent.pull_distributed(
                    {"volume": irrigation_demand},
                    of_type=["River", "Node", "Groundwater", "Reservoir"],
                )

                # update tank
                _ = self.push_storage(supplied, force=True)

                # update nutrient pools
                organic = {
                    "N": supplied["org-nitrogen"],
                    "P": supplied["org-phosphorus"],
                }
                inorganic = {
                    "N": supplied["ammonia"] + supplied["nitrate"],
                    "P": supplied["phosphate"],
                }
                self.nutrient_pool.allocate_organic_irrigation(organic)
                self.nutrient_pool.allocate_inorganic_irrigation(inorganic)

__init__(irrigation_coefficient=0.1, **kwargs)

A subclass of GrowingSurface that can calculate water demand for the crops that is not met by precipitation and use the parent node to acquire water. When the surface is created by the parent node, the irrigate function below is assigned.

Parameters:

Name	Type	Description	Default
irrigation_coefficient	float	proportion area irrigated * proportion of demand met. Defaults to 0.1.	0.1

Source code in wsimod\nodes\land.py

def __init__(self, irrigation_coefficient=0.1, **kwargs):
    """A subclass of GrowingSurface that can calculate water demand for the crops
    that is not met by precipitation and use the parent node to acquire water. When
    the surface is created by the parent node, the irrigate function below is
    assigned.

    Args:
        irrigation_coefficient (float, optional): proportion area irrigated *
            proportion of demand met. Defaults to 0.1.
    """
    # Assign param
    self.irrigation_coefficient = irrigation_coefficient  # proportion area
    # irrigated * proportion of demand met

    super().__init__(**kwargs)

apply_overrides(overrides=Dict[str, Any])

Override parameters.

Enables a user to override irrigation_coefficient

Parameters:

Name	Type	Description	Default
overrides	Dict[str, Any]	Dict describing which parameters should be overridden (keys) and new values (values). Defaults to {}.	Dict[str, Any]

Source code in wsimod\nodes\land.py

def apply_overrides(self, overrides=Dict[str, Any]):
    """Override parameters.

    Enables a user to override irrigation_coefficient

    Args:
        overrides (Dict[str, Any]): Dict describing which parameters should
            be overridden (keys) and new values (values). Defaults to {}.
    """
    self.irrigation_coefficient = overrides.pop(
        "irrigation_coefficient", self.irrigation_coefficient
    )
    super().apply_overrides(overrides)

irrigate()

Calculate water demand for crops and call parent node to acquire water, updating surface tank and nutrient pools.

Source code in wsimod\nodes\land.py

def irrigate(self):
    """Calculate water demand for crops and call parent node to acquire water,
    updating surface tank and nutrient pools."""
    if self.days_after_sow:
        # Irrigation is just difference between evaporation and precipitation amount
        irrigation_demand = (
            max(self.evaporation["volume"] - self.precipitation["volume"], 0)
            * self.irrigation_coefficient
        )
        if irrigation_demand > constants.FLOAT_ACCURACY:
            root_zone_depletion = self.get_cmd()
            if root_zone_depletion <= constants.FLOAT_ACCURACY:
                # TODO this isn't in FAO... but seems sensible
                irrigation_demand = 0

            # Pull water using parent node
            supplied = self.parent.pull_distributed(
                {"volume": irrigation_demand},
                of_type=["River", "Node", "Groundwater", "Reservoir"],
            )

            # update tank
            _ = self.push_storage(supplied, force=True)

            # update nutrient pools
            organic = {
                "N": supplied["org-nitrogen"],
                "P": supplied["org-phosphorus"],
            }
            inorganic = {
                "N": supplied["ammonia"] + supplied["nitrate"],
                "P": supplied["phosphate"],
            }
            self.nutrient_pool.allocate_organic_irrigation(organic)
            self.nutrient_pool.allocate_inorganic_irrigation(inorganic)

Land

Bases: Node

Source code in wsimod\nodes\land.py

class Land(Node):
    """"""

    def __init__(
        self,
        name,
        subsurface_residence_time=5,
        percolation_residence_time=50,
        surface_residence_time=1,
        surfaces=[],
        data_input_dict={},
    ):
        """An extensive node class that represents land processes (agriculture, soil,
        subsurface flow, rural runoff, urban drainage, pollution deposition). The
        expected use is that each distinctive type of land cover (different crop types,
        gardens, forests, impervious urban drainage, etc.) each have a Surface object,
        which is a subclass of Tank. The land node will iterate over its surfaces each
        timestep, which will generally (except in the case of an impervious surface)
        send water to three common Tanks: surface flow, subsurface flow and percolation.
        These tanks will then send flows to rivers or groundwater.

        (See wsimod/nodes/land.py/Surface and subclasses for currently available
        surfaces)

        Args:
            name (str): node name. subsurface_residence_time (float, optional):
            Residence time for
                subsurface flow (see nodes.py/ResidenceTank). Defaults to 5.
            percolation_residence_time (int, optional): Residence time for
                percolation flow (see nodes.py/ResidenceTank). Defaults to 50.
            surface_residence_time (int, optional): Residence time for surface flow
                (see nodes.py/ResidenceTank). Defaults to 1.
            surfaces (list, optional): list of dicts where each dict describes the
                parameters of each surface in the Land node. Each dict also contains an
                entry under 'type_' which describes which subclass of surface to use.
                Defaults to [].
            data_input_dict (dict, optional): Dictionary of data inputs relevant for
                the node (generally, et0, precipitation and temperature). Keys are
                tuples where first value is the name of the variable to read from the
                dict and the second value is the time. Defaults to {}.

        Functions intended to call in orchestration:
            run apply_irrigation (if used)

        Key assumptions:
             - Percolation, surface runoff, and subsurface runoff, can be described with
                a residence-time method.
             - Flows to percolation, surface runoff, and subsurface runoff are
                generated by different hydrological response units (subclasses of
                `land.py/Surface`), but aggregated for a given land node.
             - Flows to percolation are distributed to `storage.py/Groundwater`
                nodes while surface/subsurface runoff to `nodes.py/Node` or
                `storage.py/River` nodes.
             - Input data associated with the land node (precipitation,
                temperature, evapotranspiartion) are the same for every surface.
             - Water received from `sewer.py/Sewer` objects is sent to the first
                `land.py/ImperviousSurface` in the surfaces list.

        Input data and parameter requirements:
             - Precipitation and evapotranspiration are in the `data_input_dict`
                at the model timestep. _Units_: metres/timestep
             - Temperature in the `data_input_dict` at the model timestep.
                _Units_: C
             - Residence time of surface, subsurface and percolation flows.
                _Units_: number of timesteps
        """
        # Assign parameters
        self.subsurface_residence_time = subsurface_residence_time
        self.percolation_residence_time = percolation_residence_time
        self.surface_residence_time = surface_residence_time
        self.data_input_dict = data_input_dict

        super().__init__(name, data_input_dict=data_input_dict)

        # This could be a deny but then you would have to know in advance whether a
        # demand node has any gardening or not
        self.push_check_handler[("Demand", "Garden")] = lambda x: self.empty_vqip()
        self.push_set_handler[("Demand", "Garden")] = lambda x: self.empty_vqip()

        # Create surfaces
        self.irrigation_functions = [lambda: None]

        surfaces_ = surfaces.copy()
        surfaces = []
        for surface in surfaces_:
            # Assign parent (for data reading and to determine where to send flows to)
            surface["parent"] = self

            # Get surface type
            type_ = surface["type_"]
            del surface["type_"]

            # Instantiate surface and store in list of surfaces
            surfaces.append(getattr(sys.modules[__name__], type_)(**surface))

            # Assign ds (mass balance checking)
            self.mass_balance_ds.append(surfaces[-1].ds)

            # Assign any irrigation functions
            if isinstance(surfaces[-1], IrrigationSurface):
                # TODO, this should probably be done in the Surface initialisation
                self.irrigation_functions.append(surfaces[-1].irrigate)

            # Assign garden surface functions
            if isinstance(surfaces[-1], GardenSurface):
                # TODO, this should probably be done in the Surface initialisation
                self.push_check_handler[("Demand", "Garden")] = surfaces[
                    -1
                ].calculate_irrigation_demand
                self.push_set_handler[("Demand", "Garden")] = surfaces[
                    -1
                ].receive_irrigation_demand

        # Update handlers
        self.push_set_handler["default"] = self.push_set_deny
        self.push_check_handler["default"] = self.push_check_deny
        self.push_set_handler["Sewer"] = self.push_set_sewer

        # Create subsurface runoff, surface runoff and percolation tanks Can also do as
        # timearea if this seems dodge (that is how it is done in IHACRES) TODO should
        # these be decayresidencetanks?
        self.subsurface_runoff = ResidenceTank(
            residence_time=self.subsurface_residence_time,
            capacity=constants.UNBOUNDED_CAPACITY,
        )
        self.percolation = ResidenceTank(
            residence_time=self.percolation_residence_time,
            capacity=constants.UNBOUNDED_CAPACITY,
        )
        self.surface_runoff = ResidenceTank(
            residence_time=self.surface_residence_time,
            capacity=constants.UNBOUNDED_CAPACITY,
        )

        # Store surfaces
        self.surfaces = surfaces

        # Mass balance checkign vqips and functions
        self.running_inflow_mb = self.empty_vqip()
        self.running_outflow_mb = self.empty_vqip()

        self.mass_balance_in.append(lambda: self.running_inflow_mb)
        self.mass_balance_out.append(lambda: self.running_outflow_mb)
        self.mass_balance_ds.append(self.surface_runoff.ds)
        self.mass_balance_ds.append(self.subsurface_runoff.ds)
        self.mass_balance_ds.append(self.percolation.ds)

    def apply_overrides(self, overrides=Dict[str, Any]):
        """Apply overrides to the Land.

        Enables a user to override any parameter of the residence_time and update
        the residence_tank accordingly.

        Args:
            overrides (Dict[str, Any]): Dict describing which parameters should
                be overridden (keys) and new values (values). Defaults to {}.
        """
        self.surface_residence_time = overrides.pop(
            "surface_residence_time", self.surface_residence_time
        )
        self.subsurface_residence_time = overrides.pop(
            "subsurface_residence_time", self.subsurface_residence_time
        )
        self.percolation_residence_time = overrides.pop(
            "percolation_residence_time", self.percolation_residence_time
        )
        self.surface_runoff.residence_time = self.surface_residence_time
        self.subsurface_runoff.residence_time = self.subsurface_residence_time
        self.percolation.residence_time = self.percolation_residence_time
        super().apply_overrides(overrides)

    def apply_irrigation(self):
        """Iterate over any irrigation functions (needs further testing..

        maybe).
        """
        for f in self.irrigation_functions:
            f()

    def run(self):
        """Call the run function in all surfaces, update surface/subsurface/ percolation
        tanks, discharge to rivers/groundwater."""
        # Run all surfaces
        for surface in self.surfaces:
            surface.run()

        # Apply residence time to percolation
        percolation = self.percolation.pull_outflow()

        # Distribute percolation
        reply = self.push_distributed(percolation, of_type=["Groundwater"])

        if reply["volume"] > constants.FLOAT_ACCURACY:
            # Update percolation 'tank'
            _ = self.percolation.push_storage(reply, force=True)

        # Apply residence time to subsurface/surface runoff
        surface_runoff = self.surface_runoff.pull_outflow()
        subsurface_runoff = self.subsurface_runoff.pull_outflow()

        # Total runoff
        total_runoff = self.sum_vqip(surface_runoff, subsurface_runoff)
        if total_runoff["volume"] > 0:
            # Send to rivers (or nodes, which are assumed to be junctions)
            reply = self.push_distributed(total_runoff, of_type=["River", "Node"])

            # Redistribute total_runoff not sent
            if reply["volume"] > 0:
                reply_surface = self.v_change_vqip(
                    reply,
                    reply["volume"] * surface_runoff["volume"] / total_runoff["volume"],
                )
                reply_subsurface = self.v_change_vqip(
                    reply,
                    reply["volume"]
                    * subsurface_runoff["volume"]
                    / total_runoff["volume"],
                )

                # Update surface/subsurface runoff 'tanks'
                if reply_surface["volume"] > 0:
                    self.surface_runoff.push_storage(reply_surface, force=True)
                if reply_subsurface["volume"] > 0:
                    self.subsurface_runoff.push_storage(reply_subsurface, force=True)

    def push_set_sewer(self, vqip):
        """Receive water from a sewer and send it to the first ImperviousSurface in
        surfaces.

        Args:
            vqip (dict): A VQIP amount to be sent to the impervious surface

        Returns:
            vqip (dict): A VQIP amount of water that was not received
        """
        # TODO currently just push to the first impervious surface... not sure if people
        # will be having multiple impervious surfaces. If people would be only having
        # one then it would make sense to store as a parameter... this is probably fine
        # for now
        for surface in self.surfaces:
            if isinstance(surface, ImperviousSurface):
                vqip = self.surface.push_storage(vqip, force=True)
                break
        return vqip

    def end_timestep(self):
        """Update mass balance and end timestep of all tanks (and surfaces)."""
        self.running_inflow_mb = self.empty_vqip()
        self.running_outflow_mb = self.empty_vqip()
        for tanks in self.surfaces + [
            self.surface_runoff,
            self.subsurface_runoff,
            self.percolation,
        ]:
            tanks.end_timestep()

    def get_surface(self, surface_):
        """Return a surface from the list of surfaces by the 'surface' entry in the
        surface. I.e., the name of the surface.

        Args:
            surface_ (str): Name of the surface

        Returns:
            surface (Surface): The first surface that matches the name
        """
        for surface in self.surfaces:
            if surface.surface == surface_:
                return surface
        return None

    def reinit(self):
        """"""
        self.end_timestep()
        for surface in self.surfaces + [
            self.surface_runoff,
            self.subsurface_runoff,
            self.percolation,
        ]:
            surface.reinit()

__init__(name, subsurface_residence_time=5, percolation_residence_time=50, surface_residence_time=1, surfaces=[], data_input_dict={})

An extensive node class that represents land processes (agriculture, soil, subsurface flow, rural runoff, urban drainage, pollution deposition). The expected use is that each distinctive type of land cover (different crop types, gardens, forests, impervious urban drainage, etc.) each have a Surface object, which is a subclass of Tank. The land node will iterate over its surfaces each timestep, which will generally (except in the case of an impervious surface) send water to three common Tanks: surface flow, subsurface flow and percolation. These tanks will then send flows to rivers or groundwater.

(See wsimod/nodes/land.py/Surface and subclasses for currently available surfaces)

Parameters:

Name	Type	Description	Default
name	str	node name. subsurface_residence_time (float, optional):	required
percolation_residence_time	int	Residence time for percolation flow (see nodes.py/ResidenceTank). Defaults to 50.	50
surface_residence_time	int	Residence time for surface flow (see nodes.py/ResidenceTank). Defaults to 1.	1
surfaces	list	list of dicts where each dict describes the parameters of each surface in the Land node. Each dict also contains an entry under 'type_' which describes which subclass of surface to use. Defaults to [].	[]
data_input_dict	dict	Dictionary of data inputs relevant for the node (generally, et0, precipitation and temperature). Keys are tuples where first value is the name of the variable to read from the dict and the second value is the time. Defaults to {}.	{}

Functions intended to call in orchestration

run apply_irrigation (if used)

Key assumptions

• Percolation, surface runoff, and subsurface runoff, can be described with a residence-time method.
• Flows to percolation, surface runoff, and subsurface runoff are generated by different hydrological response units (subclasses of land.py/Surface), but aggregated for a given land node.
• Flows to percolation are distributed to storage.py/Groundwater nodes while surface/subsurface runoff to nodes.py/Node or storage.py/River nodes.
• Input data associated with the land node (precipitation, temperature, evapotranspiartion) are the same for every surface.
• Water received from sewer.py/Sewer objects is sent to the first land.py/ImperviousSurface in the surfaces list.

Input data and parameter requirements

• Precipitation and evapotranspiration are in the data_input_dict at the model timestep. Units: metres/timestep
• Temperature in the data_input_dict at the model timestep. Units: C
• Residence time of surface, subsurface and percolation flows. Units: number of timesteps

Source code in wsimod\nodes\land.py

def __init__(
    self,
    name,
    subsurface_residence_time=5,
    percolation_residence_time=50,
    surface_residence_time=1,
    surfaces=[],
    data_input_dict={},
):
    """An extensive node class that represents land processes (agriculture, soil,
    subsurface flow, rural runoff, urban drainage, pollution deposition). The
    expected use is that each distinctive type of land cover (different crop types,
    gardens, forests, impervious urban drainage, etc.) each have a Surface object,
    which is a subclass of Tank. The land node will iterate over its surfaces each
    timestep, which will generally (except in the case of an impervious surface)
    send water to three common Tanks: surface flow, subsurface flow and percolation.
    These tanks will then send flows to rivers or groundwater.

    (See wsimod/nodes/land.py/Surface and subclasses for currently available
    surfaces)

    Args:
        name (str): node name. subsurface_residence_time (float, optional):
        Residence time for
            subsurface flow (see nodes.py/ResidenceTank). Defaults to 5.
        percolation_residence_time (int, optional): Residence time for
            percolation flow (see nodes.py/ResidenceTank). Defaults to 50.
        surface_residence_time (int, optional): Residence time for surface flow
            (see nodes.py/ResidenceTank). Defaults to 1.
        surfaces (list, optional): list of dicts where each dict describes the
            parameters of each surface in the Land node. Each dict also contains an
            entry under 'type_' which describes which subclass of surface to use.
            Defaults to [].
        data_input_dict (dict, optional): Dictionary of data inputs relevant for
            the node (generally, et0, precipitation and temperature). Keys are
            tuples where first value is the name of the variable to read from the
            dict and the second value is the time. Defaults to {}.

    Functions intended to call in orchestration:
        run apply_irrigation (if used)

    Key assumptions:
         - Percolation, surface runoff, and subsurface runoff, can be described with
            a residence-time method.
         - Flows to percolation, surface runoff, and subsurface runoff are
            generated by different hydrological response units (subclasses of
            `land.py/Surface`), but aggregated for a given land node.
         - Flows to percolation are distributed to `storage.py/Groundwater`
            nodes while surface/subsurface runoff to `nodes.py/Node` or
            `storage.py/River` nodes.
         - Input data associated with the land node (precipitation,
            temperature, evapotranspiartion) are the same for every surface.
         - Water received from `sewer.py/Sewer` objects is sent to the first
            `land.py/ImperviousSurface` in the surfaces list.

    Input data and parameter requirements:
         - Precipitation and evapotranspiration are in the `data_input_dict`
            at the model timestep. _Units_: metres/timestep
         - Temperature in the `data_input_dict` at the model timestep.
            _Units_: C
         - Residence time of surface, subsurface and percolation flows.
            _Units_: number of timesteps
    """
    # Assign parameters
    self.subsurface_residence_time = subsurface_residence_time
    self.percolation_residence_time = percolation_residence_time
    self.surface_residence_time = surface_residence_time
    self.data_input_dict = data_input_dict

    super().__init__(name, data_input_dict=data_input_dict)

    # This could be a deny but then you would have to know in advance whether a
    # demand node has any gardening or not
    self.push_check_handler[("Demand", "Garden")] = lambda x: self.empty_vqip()
    self.push_set_handler[("Demand", "Garden")] = lambda x: self.empty_vqip()

    # Create surfaces
    self.irrigation_functions = [lambda: None]

    surfaces_ = surfaces.copy()
    surfaces = []
    for surface in surfaces_:
        # Assign parent (for data reading and to determine where to send flows to)
        surface["parent"] = self

        # Get surface type
        type_ = surface["type_"]
        del surface["type_"]

        # Instantiate surface and store in list of surfaces
        surfaces.append(getattr(sys.modules[__name__], type_)(**surface))

        # Assign ds (mass balance checking)
        self.mass_balance_ds.append(surfaces[-1].ds)

        # Assign any irrigation functions
        if isinstance(surfaces[-1], IrrigationSurface):
            # TODO, this should probably be done in the Surface initialisation
            self.irrigation_functions.append(surfaces[-1].irrigate)

        # Assign garden surface functions
        if isinstance(surfaces[-1], GardenSurface):
            # TODO, this should probably be done in the Surface initialisation
            self.push_check_handler[("Demand", "Garden")] = surfaces[
                -1
            ].calculate_irrigation_demand
            self.push_set_handler[("Demand", "Garden")] = surfaces[
                -1
            ].receive_irrigation_demand

    # Update handlers
    self.push_set_handler["default"] = self.push_set_deny
    self.push_check_handler["default"] = self.push_check_deny
    self.push_set_handler["Sewer"] = self.push_set_sewer

    # Create subsurface runoff, surface runoff and percolation tanks Can also do as
    # timearea if this seems dodge (that is how it is done in IHACRES) TODO should
    # these be decayresidencetanks?
    self.subsurface_runoff = ResidenceTank(
        residence_time=self.subsurface_residence_time,
        capacity=constants.UNBOUNDED_CAPACITY,
    )
    self.percolation = ResidenceTank(
        residence_time=self.percolation_residence_time,
        capacity=constants.UNBOUNDED_CAPACITY,
    )
    self.surface_runoff = ResidenceTank(
        residence_time=self.surface_residence_time,
        capacity=constants.UNBOUNDED_CAPACITY,
    )

    # Store surfaces
    self.surfaces = surfaces

    # Mass balance checkign vqips and functions
    self.running_inflow_mb = self.empty_vqip()
    self.running_outflow_mb = self.empty_vqip()

    self.mass_balance_in.append(lambda: self.running_inflow_mb)
    self.mass_balance_out.append(lambda: self.running_outflow_mb)
    self.mass_balance_ds.append(self.surface_runoff.ds)
    self.mass_balance_ds.append(self.subsurface_runoff.ds)
    self.mass_balance_ds.append(self.percolation.ds)

apply_irrigation()

Iterate over any irrigation functions (needs further testing..

maybe).

Source code in wsimod\nodes\land.py

def apply_irrigation(self):
    """Iterate over any irrigation functions (needs further testing..

    maybe).
    """
    for f in self.irrigation_functions:
        f()

apply_overrides(overrides=Dict[str, Any])

Apply overrides to the Land.

Enables a user to override any parameter of the residence_time and update the residence_tank accordingly.

Parameters:

Name	Type	Description	Default
overrides	Dict[str, Any]	Dict describing which parameters should be overridden (keys) and new values (values). Defaults to {}.	Dict[str, Any]

Source code in wsimod\nodes\land.py

def apply_overrides(self, overrides=Dict[str, Any]):
    """Apply overrides to the Land.

    Enables a user to override any parameter of the residence_time and update
    the residence_tank accordingly.

    Args:
        overrides (Dict[str, Any]): Dict describing which parameters should
            be overridden (keys) and new values (values). Defaults to {}.
    """
    self.surface_residence_time = overrides.pop(
        "surface_residence_time", self.surface_residence_time
    )
    self.subsurface_residence_time = overrides.pop(
        "subsurface_residence_time", self.subsurface_residence_time
    )
    self.percolation_residence_time = overrides.pop(
        "percolation_residence_time", self.percolation_residence_time
    )
    self.surface_runoff.residence_time = self.surface_residence_time
    self.subsurface_runoff.residence_time = self.subsurface_residence_time
    self.percolation.residence_time = self.percolation_residence_time
    super().apply_overrides(overrides)

end_timestep()

Update mass balance and end timestep of all tanks (and surfaces).

Source code in wsimod\nodes\land.py

def end_timestep(self):
    """Update mass balance and end timestep of all tanks (and surfaces)."""
    self.running_inflow_mb = self.empty_vqip()
    self.running_outflow_mb = self.empty_vqip()
    for tanks in self.surfaces + [
        self.surface_runoff,
        self.subsurface_runoff,
        self.percolation,
    ]:
        tanks.end_timestep()

get_surface(surface_)

Return a surface from the list of surfaces by the 'surface' entry in the surface. I.e., the name of the surface.

Parameters:

Name	Type	Description	Default
surface_	str	Name of the surface	required

Returns:

Name	Type	Description
surface	Surface	The first surface that matches the name

Source code in wsimod\nodes\land.py

def get_surface(self, surface_):
    """Return a surface from the list of surfaces by the 'surface' entry in the
    surface. I.e., the name of the surface.

    Args:
        surface_ (str): Name of the surface

    Returns:
        surface (Surface): The first surface that matches the name
    """
    for surface in self.surfaces:
        if surface.surface == surface_:
            return surface
    return None

push_set_sewer(vqip)

Receive water from a sewer and send it to the first ImperviousSurface in surfaces.

Parameters:

Name	Type	Description	Default
vqip	dict	A VQIP amount to be sent to the impervious surface	required

Returns:

Name	Type	Description
vqip	dict	A VQIP amount of water that was not received

Source code in wsimod\nodes\land.py

def push_set_sewer(self, vqip):
    """Receive water from a sewer and send it to the first ImperviousSurface in
    surfaces.

    Args:
        vqip (dict): A VQIP amount to be sent to the impervious surface

    Returns:
        vqip (dict): A VQIP amount of water that was not received
    """
    # TODO currently just push to the first impervious surface... not sure if people
    # will be having multiple impervious surfaces. If people would be only having
    # one then it would make sense to store as a parameter... this is probably fine
    # for now
    for surface in self.surfaces:
        if isinstance(surface, ImperviousSurface):
            vqip = self.surface.push_storage(vqip, force=True)
            break
    return vqip

reinit()

Source code in wsimod\nodes\land.py

def reinit(self):
    """"""
    self.end_timestep()
    for surface in self.surfaces + [
        self.surface_runoff,
        self.subsurface_runoff,
        self.percolation,
    ]:
        surface.reinit()

run()

Call the run function in all surfaces, update surface/subsurface/ percolation tanks, discharge to rivers/groundwater.

Source code in wsimod\nodes\land.py

def run(self):
    """Call the run function in all surfaces, update surface/subsurface/ percolation
    tanks, discharge to rivers/groundwater."""
    # Run all surfaces
    for surface in self.surfaces:
        surface.run()

    # Apply residence time to percolation
    percolation = self.percolation.pull_outflow()

    # Distribute percolation
    reply = self.push_distributed(percolation, of_type=["Groundwater"])

    if reply["volume"] > constants.FLOAT_ACCURACY:
        # Update percolation 'tank'
        _ = self.percolation.push_storage(reply, force=True)

    # Apply residence time to subsurface/surface runoff
    surface_runoff = self.surface_runoff.pull_outflow()
    subsurface_runoff = self.subsurface_runoff.pull_outflow()

    # Total runoff
    total_runoff = self.sum_vqip(surface_runoff, subsurface_runoff)
    if total_runoff["volume"] > 0:
        # Send to rivers (or nodes, which are assumed to be junctions)
        reply = self.push_distributed(total_runoff, of_type=["River", "Node"])

        # Redistribute total_runoff not sent
        if reply["volume"] > 0:
            reply_surface = self.v_change_vqip(
                reply,
                reply["volume"] * surface_runoff["volume"] / total_runoff["volume"],
            )
            reply_subsurface = self.v_change_vqip(
                reply,
                reply["volume"]
                * subsurface_runoff["volume"]
                / total_runoff["volume"],
            )

            # Update surface/subsurface runoff 'tanks'
            if reply_surface["volume"] > 0:
                self.surface_runoff.push_storage(reply_surface, force=True)
            if reply_subsurface["volume"] > 0:
                self.subsurface_runoff.push_storage(reply_subsurface, force=True)

PerviousSurface

Bases: Surface

Source code in wsimod\nodes\land.py

class PerviousSurface(Surface):
    """"""

    def __init__(
        self,
        depth=0.75,
        total_porosity=0.4,
        field_capacity=0.3,
        wilting_point=0.12,
        infiltration_capacity=0.5,
        surface_coefficient=0.05,
        percolation_coefficient=0.75,
        et0_coefficient=0.5,
        ihacres_p=10,
        **kwargs,
    ):
        """A generic pervious surface that represents hydrology with the IHACRES model.

        Args:
            depth (float, optional): Soil tank (i.e., root) depth. Defaults to 0.75.
            total_porosity (float, optional): The total porosity IHACRES parameter
                (i.e., defines the total porouse volume of the soil - the maximum volume
                of soil pores can contain when saturated). Defaults to 0.4.
            field_capacity (float, optional): The field capacity IHACRES parameter
                (i.e., when water content in the soil tank is above this value - flows
                of any kind can be generated). Defaults to 0.3.
            wilting_point (float, optional): The wilting point IHACRES parameter (i.e.,
                when water content content in the soil tank is above this value - plants
                can uptake water and evaporation from the soil tank can occur). Defaults
                to 0.12.
            infiltration_capacity (float, optional): Depth of water per day that can
                enter the soil tank. Non infiltrated water will pond and travel as
                surface runoff from the parent Land node. Defaults to 0.5.
            surface_coefficient (float, optional): If flow is generated, the proportion
                of flow that goes to surface runoff. Defaults to 0.05.
            percolation_coefficient (float, optional): If flow is generated, then the
                proportion of water that does not go to surface runoff that goes to
                percolation (i.e., groundwater) - the remainder goes to subsurface
                runoff. Defaults to 0.75.
            et0_coefficient (float, optional): Convert between the parent nodes data
                timeseries et0 - and potential evaptranspiration per unit area for this
                surface. Defaults to=0.5,
            ihacres_p (float, optional): The IHACRES p parameter. Unless it is an
                ephemeral stream this parameter probably can stay high. Defaults to 10.

        Key assumptions:
             - In IHACRES, the maximum infiltration per time step is controlled by an
                infiltration capacity, beyond which the precipitation will flow directly
                as surface runoff.
             - Evapotranspiration and effective precipitation are calculated based on
                soil moisture content.
             - Effective precipitation is then divided into percolation, surface runoff,
                and subsurface runoff by multiplying the corresponding coefficient.
             - Percolation, surface runoff, and subsurface runoff are sent into the
                corresponding residence tanks for rounting to downstream.
             - The mass of pollutants in soil water tank proportionately leaves the
                soil water tank into the routing residence tanks. Evapotranspiration can
                only bring out water, with pollutants left in the soil tank.

        Input data and parameter requirements:
             - Field capacity and wilting point.
                _Units_: -, both should in [0-1], with field capacity > wilting point
             - Infiltration capacity.
                _Units_: m/day
             - Surface, percolation coefficient.
                _Units_: -, both should in [0-1]
             - et0 coefficient.
                _Units_: -
             - ihacres_p.
                _Units_: -
        """
        # Assign parameters (converting field capacity and wilting point to depth)
        self.field_capacity = field_capacity
        self.field_capacity_m = field_capacity * depth
        self.wilting_point = wilting_point
        self.wilting_point_m = wilting_point * depth
        self.infiltration_capacity = infiltration_capacity
        self.surface_coefficient = surface_coefficient
        self.percolation_coefficient = percolation_coefficient
        self.et0_coefficient = et0_coefficient
        self.ihacres_p = ihacres_p
        self.total_porosity = total_porosity

        # Parameters to determine how to calculate the temperature of outflowing water
        # TODO what should these params be?
        self.soil_temp_w_prev = 0.1  # previous timestep weighting
        self.soil_temp_w_air = 0.6  # air temperature weighting
        self.soil_temp_w_deep = 0.1  # deep soil temperature weighting
        self.soil_temp_deep = 10  # deep soil temperature

        # IHACRES is a deficit not a tank, so doesn't really have a capacity in this
        # way... and if it did.. I don't know if it would be the root depth
        super().__init__(depth=depth * total_porosity, **kwargs)

        # Calculate subsurface coefficient
        self.subsurface_coefficient = 1 - self.percolation_coefficient

        # Initiliase state variables
        self.infiltration_excess = self.empty_vqip()
        self.subsurface_flow = self.empty_vqip()
        self.percolation = self.empty_vqip()
        self.tank_recharge = 0
        self.evaporation = self.empty_vqip()
        self.precipitation = self.empty_vqip()

        # Populate function lists
        self.inflows.append(self.ihacres)  # work out runoff

        # TODO interception if I hate myself enough?
        self.processes.append(
            self.calculate_soil_temperature
        )  # Calculate soil temp + dependence factor

        # self.processes.append(self.decay) #apply generic decay (currently handled by
        # decaytank at end of timestep) TODO decaytank uses air temperature not soil
        # temperature... probably need to just give it the decay function

        self.outflows.append(self.route)

    def apply_overrides(self, overrides=Dict[str, Any]):
        """Override parameters.

        Enables a user to override any of the following parameters:
        field_capacity, wilting_point, total_porosity, infiltration_capacity,
        surface_coefficient, percolation_coefficient, et0_coefficient, ihacres_p,
        soil_temp_w_prev, soil_temp_w_air, soil_temp_w_deep, soil_temp_deep,
        and the corresponding parameter values, including field_capacity_m,
        wilting_point_m, depth, capacity, subsurface_coefficient.

        Args:
            overrides (Dict[str, Any]): Dict describing which parameters should
                be overridden (keys) and new values (values). Defaults to {}.
        """

        self.depth /= self.total_porosity  # restore the physical depth (root)

        overwrite_params = [
            "field_capacity",
            "wilting_point",
            "total_porosity",
            "infiltration_capacity",
            "surface_coefficient",
            "percolation_coefficient",
            "et0_coefficient",
            "ihacres_p",
            "soil_temp_w_prev",
            "soil_temp_w_air",
            "soil_temp_w_deep",
            "soil_temp_deep",
        ]
        for param in overwrite_params:
            setattr(self, param, overrides.pop(param, getattr(self, param)))

        self.subsurface_coefficient = 1 - self.percolation_coefficient

        super().apply_overrides(overrides)
        # After the depth has been changed ...
        self.field_capacity_m = self.field_capacity * self.depth
        self.wilting_point_m = self.wilting_point * self.depth
        self.depth *= self.total_porosity  # update the simulation depth
        self.capacity = self.depth * self.area

    def get_cmd(self):
        """Calculate moisture deficit (i.e., the tank excess converted to depth).

        Returns:
            (float): current moisture deficit
        """
        return self.get_excess()["volume"] / self.area

    def get_smc(self):
        """Calculate moisture content (i.e., the tank volume converted to depth).

        Returns:
            (float): soil moisture content
        """
        # Depth of soil moisture
        return self.storage["volume"] / self.area

    def get_climate(self):
        """

        Returns:

        """
        precipitation_depth = self.get_data_input("precipitation")
        evaporation_depth = self.get_data_input("et0") * self.et0_coefficient
        return precipitation_depth, evaporation_depth

    def ihacres(self):
        """Inflow function that runs the IHACRES model equations, updates tanks, and
        store flows in state variables (which are later sent to the parent land node in
        the route function).

        Returns:
            (tuple): A tuple containing a VQIP amount for model inputs and outputs
                for mass balance checking.
        """
        # Read data (leave in depth units since that is what IHACRES equations are in)
        precipitation_depth, evaporation_depth = self.get_climate()
        temperature = self.get_data_input("temperature")

        # Apply infiltration
        infiltrated_precipitation = min(precipitation_depth, self.infiltration_capacity)
        infiltration_excess = max(precipitation_depth - infiltrated_precipitation, 0)

        # Get current moisture deficit
        current_moisture_deficit_depth = self.get_cmd()

        # IHACRES equations (we do (depth - wilting_point_m or field capacity) to
        # convert from a deficit to storage tank)
        evaporation = evaporation_depth * min(
            1,
            exp(
                2
                * (
                    1
                    - current_moisture_deficit_depth
                    / (self.depth - self.wilting_point_m)
                )
            ),
        )
        outflow = infiltrated_precipitation * (
            1
            - min(
                1,
                (current_moisture_deficit_depth / (self.depth - self.field_capacity_m))
                ** self.ihacres_p,
            )
        )

        # Can't evaporate more than available moisture (presumably the IHACRES equation
        # prevents this ever being needed)
        evaporation = min(evaporation, precipitation_depth + self.get_smc())

        # Scale to volumes and apply proportions to work out percolation/surface
        # runoff/subsurface runoff
        surface = outflow * self.surface_coefficient * self.area
        percolation = (
            outflow
            * (1 - self.surface_coefficient)
            * self.percolation_coefficient
            * self.area
        )
        subsurface_flow = (
            outflow
            * (1 - self.surface_coefficient)
            * self.subsurface_coefficient
            * self.area
        )
        tank_recharge = (infiltrated_precipitation - evaporation - outflow) * self.area
        infiltration_excess *= self.area
        infiltration_excess += surface
        evaporation *= self.area
        precipitation = precipitation_depth * self.area

        # Mix in tank to calculate pollutant concentrations
        total_water_passing_through_soil_tank = (
            tank_recharge + subsurface_flow + percolation
        )

        if total_water_passing_through_soil_tank > 0:
            # Net effective preipitation
            total_water_passing_through_soil_tank = self.v_change_vqip(
                self.empty_vqip(), total_water_passing_through_soil_tank
            )
            # Assign a temperature before sending into tank
            total_water_passing_through_soil_tank["temperature"] = temperature
            # Assign to tank
            _ = self.push_storage(total_water_passing_through_soil_tank, force=True)
            # Pull flows (which now have nonzero pollutant concentrations)
            subsurface_flow = self.pull_storage({"volume": subsurface_flow})
            percolation = self.pull_storage({"volume": percolation})
        else:
            # No net effective precipitation (instead evaporation occurs)
            evap = self.evaporate(-total_water_passing_through_soil_tank)
            subsurface_flow = self.empty_vqip()
            percolation = self.empty_vqip()

            if (
                abs(
                    evap
                    + infiltrated_precipitation * self.area
                    - evaporation
                    - infiltration_excess
                )
                > constants.FLOAT_ACCURACY
            ):
                print(
                    "inaccurate evaporation calculation of {0}".format(
                        abs(
                            evap
                            + infiltrated_precipitation * self.area
                            - evaporation
                            - infiltration_excess
                        )
                    )
                )

        # TODO saturation excess (think it should just be 'pull_ponded'  presumably in
        # net effective precipitation? )

        # Convert to VQIPs
        infiltration_excess = self.v_change_vqip(self.empty_vqip(), infiltration_excess)
        infiltration_excess["temperature"] = temperature
        precipitation = self.v_change_vqip(self.empty_vqip(), precipitation)
        evaporation = self.v_change_vqip(self.empty_vqip(), evaporation)

        # Track flows (these are sent onwards in the route function)
        self.infiltration_excess = infiltration_excess
        self.subsurface_flow = subsurface_flow
        self.percolation = percolation
        self.tank_recharge = tank_recharge
        self.evaporation = evaporation
        self.precipitation = precipitation

        # Mass balance
        in_ = precipitation
        out_ = evaporation

        return (in_, out_)

    def route(self):
        """An outflow function that sends percolation, subsurface runoff and surface
        runoff to their respective tanks in the parent land node.

        Returns:
            (tuple): A tuple containing a VQIP amount for model inputs and outputs
                for mass balance checking.
        """
        self.parent.surface_runoff.push_storage(self.infiltration_excess, force=True)
        self.parent.subsurface_runoff.push_storage(self.subsurface_flow, force=True)
        self.parent.percolation.push_storage(self.percolation, force=True)

        return (self.empty_vqip(), self.empty_vqip())

    def calculate_soil_temperature(self):
        """Process function that calculates soil temperature based on a weighted.

        average. This equation is from Lindstrom, Bishop & Lofvenius (2002),
        hydrological processes - but it is not clear what the parameters should be.

        Returns:
            (tuple): A tuple containing a VQIP amount for model inputs and outputs
                for mass balance checking.
        """
        auto = self.storage["temperature"] * self.soil_temp_w_prev
        air = self.get_data_input("temperature") * self.soil_temp_w_air
        total_weight = (
            self.soil_temp_w_air + self.soil_temp_w_deep + self.soil_temp_w_prev
        )
        self.storage["temperature"] = (
            auto + air + self.soil_temp_deep * self.soil_temp_w_deep
        ) / total_weight

        return (self.empty_vqip(), self.empty_vqip())

__init__(depth=0.75, total_porosity=0.4, field_capacity=0.3, wilting_point=0.12, infiltration_capacity=0.5, surface_coefficient=0.05, percolation_coefficient=0.75, et0_coefficient=0.5, ihacres_p=10, **kwargs)

A generic pervious surface that represents hydrology with the IHACRES model.

Parameters:

Name	Type	Description	Default
depth	float	Soil tank (i.e., root) depth. Defaults to 0.75.	0.75
total_porosity	float	The total porosity IHACRES parameter (i.e., defines the total porouse volume of the soil - the maximum volume of soil pores can contain when saturated). Defaults to 0.4.	0.4
field_capacity	float	The field capacity IHACRES parameter (i.e., when water content in the soil tank is above this value - flows of any kind can be generated). Defaults to 0.3.	0.3
wilting_point	float	The wilting point IHACRES parameter (i.e., when water content content in the soil tank is above this value - plants can uptake water and evaporation from the soil tank can occur). Defaults to 0.12.	0.12
infiltration_capacity	float	Depth of water per day that can enter the soil tank. Non infiltrated water will pond and travel as surface runoff from the parent Land node. Defaults to 0.5.	0.5
surface_coefficient	float	If flow is generated, the proportion of flow that goes to surface runoff. Defaults to 0.05.	0.05
percolation_coefficient	float	If flow is generated, then the proportion of water that does not go to surface runoff that goes to percolation (i.e., groundwater) - the remainder goes to subsurface runoff. Defaults to 0.75.	0.75
et0_coefficient	float	Convert between the parent nodes data timeseries et0 - and potential evaptranspiration per unit area for this surface. Defaults to=0.5,	0.5
ihacres_p	float	The IHACRES p parameter. Unless it is an ephemeral stream this parameter probably can stay high. Defaults to 10.	10

Key assumptions

• In IHACRES, the maximum infiltration per time step is controlled by an infiltration capacity, beyond which the precipitation will flow directly as surface runoff.
• Evapotranspiration and effective precipitation are calculated based on soil moisture content.
• Effective precipitation is then divided into percolation, surface runoff, and subsurface runoff by multiplying the corresponding coefficient.
• Percolation, surface runoff, and subsurface runoff are sent into the corresponding residence tanks for rounting to downstream.
• The mass of pollutants in soil water tank proportionately leaves the soil water tank into the routing residence tanks. Evapotranspiration can only bring out water, with pollutants left in the soil tank.

Input data and parameter requirements

• Field capacity and wilting point. Units: -, both should in [0-1], with field capacity > wilting point
• Infiltration capacity. Units: m/day
• Surface, percolation coefficient. Units: -, both should in [0-1]
• et0 coefficient. Units: -
• ihacres_p. Units: -

Source code in wsimod\nodes\land.py

def __init__(
    self,
    depth=0.75,
    total_porosity=0.4,
    field_capacity=0.3,
    wilting_point=0.12,
    infiltration_capacity=0.5,
    surface_coefficient=0.05,
    percolation_coefficient=0.75,
    et0_coefficient=0.5,
    ihacres_p=10,
    **kwargs,
):
    """A generic pervious surface that represents hydrology with the IHACRES model.

    Args:
        depth (float, optional): Soil tank (i.e., root) depth. Defaults to 0.75.
        total_porosity (float, optional): The total porosity IHACRES parameter
            (i.e., defines the total porouse volume of the soil - the maximum volume
            of soil pores can contain when saturated). Defaults to 0.4.
        field_capacity (float, optional): The field capacity IHACRES parameter
            (i.e., when water content in the soil tank is above this value - flows
            of any kind can be generated). Defaults to 0.3.
        wilting_point (float, optional): The wilting point IHACRES parameter (i.e.,
            when water content content in the soil tank is above this value - plants
            can uptake water and evaporation from the soil tank can occur). Defaults
            to 0.12.
        infiltration_capacity (float, optional): Depth of water per day that can
            enter the soil tank. Non infiltrated water will pond and travel as
            surface runoff from the parent Land node. Defaults to 0.5.
        surface_coefficient (float, optional): If flow is generated, the proportion
            of flow that goes to surface runoff. Defaults to 0.05.
        percolation_coefficient (float, optional): If flow is generated, then the
            proportion of water that does not go to surface runoff that goes to
            percolation (i.e., groundwater) - the remainder goes to subsurface
            runoff. Defaults to 0.75.
        et0_coefficient (float, optional): Convert between the parent nodes data
            timeseries et0 - and potential evaptranspiration per unit area for this
            surface. Defaults to=0.5,
        ihacres_p (float, optional): The IHACRES p parameter. Unless it is an
            ephemeral stream this parameter probably can stay high. Defaults to 10.

    Key assumptions:
         - In IHACRES, the maximum infiltration per time step is controlled by an
            infiltration capacity, beyond which the precipitation will flow directly
            as surface runoff.
         - Evapotranspiration and effective precipitation are calculated based on
            soil moisture content.
         - Effective precipitation is then divided into percolation, surface runoff,
            and subsurface runoff by multiplying the corresponding coefficient.
         - Percolation, surface runoff, and subsurface runoff are sent into the
            corresponding residence tanks for rounting to downstream.
         - The mass of pollutants in soil water tank proportionately leaves the
            soil water tank into the routing residence tanks. Evapotranspiration can
            only bring out water, with pollutants left in the soil tank.

    Input data and parameter requirements:
         - Field capacity and wilting point.
            _Units_: -, both should in [0-1], with field capacity > wilting point
         - Infiltration capacity.
            _Units_: m/day
         - Surface, percolation coefficient.
            _Units_: -, both should in [0-1]
         - et0 coefficient.
            _Units_: -
         - ihacres_p.
            _Units_: -
    """
    # Assign parameters (converting field capacity and wilting point to depth)
    self.field_capacity = field_capacity
    self.field_capacity_m = field_capacity * depth
    self.wilting_point = wilting_point
    self.wilting_point_m = wilting_point * depth
    self.infiltration_capacity = infiltration_capacity
    self.surface_coefficient = surface_coefficient
    self.percolation_coefficient = percolation_coefficient
    self.et0_coefficient = et0_coefficient
    self.ihacres_p = ihacres_p
    self.total_porosity = total_porosity

    # Parameters to determine how to calculate the temperature of outflowing water
    # TODO what should these params be?
    self.soil_temp_w_prev = 0.1  # previous timestep weighting
    self.soil_temp_w_air = 0.6  # air temperature weighting
    self.soil_temp_w_deep = 0.1  # deep soil temperature weighting
    self.soil_temp_deep = 10  # deep soil temperature

    # IHACRES is a deficit not a tank, so doesn't really have a capacity in this
    # way... and if it did.. I don't know if it would be the root depth
    super().__init__(depth=depth * total_porosity, **kwargs)

    # Calculate subsurface coefficient
    self.subsurface_coefficient = 1 - self.percolation_coefficient

    # Initiliase state variables
    self.infiltration_excess = self.empty_vqip()
    self.subsurface_flow = self.empty_vqip()
    self.percolation = self.empty_vqip()
    self.tank_recharge = 0
    self.evaporation = self.empty_vqip()
    self.precipitation = self.empty_vqip()

    # Populate function lists
    self.inflows.append(self.ihacres)  # work out runoff

    # TODO interception if I hate myself enough?
    self.processes.append(
        self.calculate_soil_temperature
    )  # Calculate soil temp + dependence factor

    # self.processes.append(self.decay) #apply generic decay (currently handled by
    # decaytank at end of timestep) TODO decaytank uses air temperature not soil
    # temperature... probably need to just give it the decay function

    self.outflows.append(self.route)

apply_overrides(overrides=Dict[str, Any])

Override parameters.

Enables a user to override any of the following parameters: field_capacity, wilting_point, total_porosity, infiltration_capacity, surface_coefficient, percolation_coefficient, et0_coefficient, ihacres_p, soil_temp_w_prev, soil_temp_w_air, soil_temp_w_deep, soil_temp_deep, and the corresponding parameter values, including field_capacity_m, wilting_point_m, depth, capacity, subsurface_coefficient.

Parameters:

Name	Type	Description	Default
overrides	Dict[str, Any]	Dict describing which parameters should be overridden (keys) and new values (values). Defaults to {}.	Dict[str, Any]

Source code in wsimod\nodes\land.py

def apply_overrides(self, overrides=Dict[str, Any]):
    """Override parameters.

    Enables a user to override any of the following parameters:
    field_capacity, wilting_point, total_porosity, infiltration_capacity,
    surface_coefficient, percolation_coefficient, et0_coefficient, ihacres_p,
    soil_temp_w_prev, soil_temp_w_air, soil_temp_w_deep, soil_temp_deep,
    and the corresponding parameter values, including field_capacity_m,
    wilting_point_m, depth, capacity, subsurface_coefficient.

    Args:
        overrides (Dict[str, Any]): Dict describing which parameters should
            be overridden (keys) and new values (values). Defaults to {}.
    """

    self.depth /= self.total_porosity  # restore the physical depth (root)

    overwrite_params = [
        "field_capacity",
        "wilting_point",
        "total_porosity",
        "infiltration_capacity",
        "surface_coefficient",
        "percolation_coefficient",
        "et0_coefficient",
        "ihacres_p",
        "soil_temp_w_prev",
        "soil_temp_w_air",
        "soil_temp_w_deep",
        "soil_temp_deep",
    ]
    for param in overwrite_params:
        setattr(self, param, overrides.pop(param, getattr(self, param)))

    self.subsurface_coefficient = 1 - self.percolation_coefficient

    super().apply_overrides(overrides)
    # After the depth has been changed ...
    self.field_capacity_m = self.field_capacity * self.depth
    self.wilting_point_m = self.wilting_point * self.depth
    self.depth *= self.total_porosity  # update the simulation depth
    self.capacity = self.depth * self.area

calculate_soil_temperature()

Process function that calculates soil temperature based on a weighted.

average. This equation is from Lindstrom, Bishop & Lofvenius (2002), hydrological processes - but it is not clear what the parameters should be.

Returns:

Type	Description
tuple	A tuple containing a VQIP amount for model inputs and outputs for mass balance checking.

Source code in wsimod\nodes\land.py

def calculate_soil_temperature(self):
    """Process function that calculates soil temperature based on a weighted.

    average. This equation is from Lindstrom, Bishop & Lofvenius (2002),
    hydrological processes - but it is not clear what the parameters should be.

    Returns:
        (tuple): A tuple containing a VQIP amount for model inputs and outputs
            for mass balance checking.
    """
    auto = self.storage["temperature"] * self.soil_temp_w_prev
    air = self.get_data_input("temperature") * self.soil_temp_w_air
    total_weight = (
        self.soil_temp_w_air + self.soil_temp_w_deep + self.soil_temp_w_prev
    )
    self.storage["temperature"] = (
        auto + air + self.soil_temp_deep * self.soil_temp_w_deep
    ) / total_weight

    return (self.empty_vqip(), self.empty_vqip())

get_climate()

Returns:

Source code in wsimod\nodes\land.py

def get_climate(self):
    """

    Returns:

    """
    precipitation_depth = self.get_data_input("precipitation")
    evaporation_depth = self.get_data_input("et0") * self.et0_coefficient
    return precipitation_depth, evaporation_depth

get_cmd()

Calculate moisture deficit (i.e., the tank excess converted to depth).

Returns:

Type	Description
float	current moisture deficit

Source code in wsimod\nodes\land.py

def get_cmd(self):
    """Calculate moisture deficit (i.e., the tank excess converted to depth).

    Returns:
        (float): current moisture deficit
    """
    return self.get_excess()["volume"] / self.area

get_smc()

Calculate moisture content (i.e., the tank volume converted to depth).

Returns:

Type	Description
float	soil moisture content

Source code in wsimod\nodes\land.py

def get_smc(self):
    """Calculate moisture content (i.e., the tank volume converted to depth).

    Returns:
        (float): soil moisture content
    """
    # Depth of soil moisture
    return self.storage["volume"] / self.area

ihacres()

Inflow function that runs the IHACRES model equations, updates tanks, and store flows in state variables (which are later sent to the parent land node in the route function).

Returns:

Type	Description
tuple	A tuple containing a VQIP amount for model inputs and outputs for mass balance checking.

Source code in wsimod\nodes\land.py

def ihacres(self):
    """Inflow function that runs the IHACRES model equations, updates tanks, and
    store flows in state variables (which are later sent to the parent land node in
    the route function).

    Returns:
        (tuple): A tuple containing a VQIP amount for model inputs and outputs
            for mass balance checking.
    """
    # Read data (leave in depth units since that is what IHACRES equations are in)
    precipitation_depth, evaporation_depth = self.get_climate()
    temperature = self.get_data_input("temperature")

    # Apply infiltration
    infiltrated_precipitation = min(precipitation_depth, self.infiltration_capacity)
    infiltration_excess = max(precipitation_depth - infiltrated_precipitation, 0)

    # Get current moisture deficit
    current_moisture_deficit_depth = self.get_cmd()

    # IHACRES equations (we do (depth - wilting_point_m or field capacity) to
    # convert from a deficit to storage tank)
    evaporation = evaporation_depth * min(
        1,
        exp(
            2
            * (
                1
                - current_moisture_deficit_depth
                / (self.depth - self.wilting_point_m)
            )
        ),
    )
    outflow = infiltrated_precipitation * (
        1
        - min(
            1,
            (current_moisture_deficit_depth / (self.depth - self.field_capacity_m))
            ** self.ihacres_p,
        )
    )

    # Can't evaporate more than available moisture (presumably the IHACRES equation
    # prevents this ever being needed)
    evaporation = min(evaporation, precipitation_depth + self.get_smc())

    # Scale to volumes and apply proportions to work out percolation/surface
    # runoff/subsurface runoff
    surface = outflow * self.surface_coefficient * self.area
    percolation = (
        outflow
        * (1 - self.surface_coefficient)
        * self.percolation_coefficient
        * self.area
    )
    subsurface_flow = (
        outflow
        * (1 - self.surface_coefficient)
        * self.subsurface_coefficient
        * self.area
    )
    tank_recharge = (infiltrated_precipitation - evaporation - outflow) * self.area
    infiltration_excess *= self.area
    infiltration_excess += surface
    evaporation *= self.area
    precipitation = precipitation_depth * self.area

    # Mix in tank to calculate pollutant concentrations
    total_water_passing_through_soil_tank = (
        tank_recharge + subsurface_flow + percolation
    )

    if total_water_passing_through_soil_tank > 0:
        # Net effective preipitation
        total_water_passing_through_soil_tank = self.v_change_vqip(
            self.empty_vqip(), total_water_passing_through_soil_tank
        )
        # Assign a temperature before sending into tank
        total_water_passing_through_soil_tank["temperature"] = temperature
        # Assign to tank
        _ = self.push_storage(total_water_passing_through_soil_tank, force=True)
        # Pull flows (which now have nonzero pollutant concentrations)
        subsurface_flow = self.pull_storage({"volume": subsurface_flow})
        percolation = self.pull_storage({"volume": percolation})
    else:
        # No net effective precipitation (instead evaporation occurs)
        evap = self.evaporate(-total_water_passing_through_soil_tank)
        subsurface_flow = self.empty_vqip()
        percolation = self.empty_vqip()

        if (
            abs(
                evap
                + infiltrated_precipitation * self.area
                - evaporation
                - infiltration_excess
            )
            > constants.FLOAT_ACCURACY
        ):
            print(
                "inaccurate evaporation calculation of {0}".format(
                    abs(
                        evap
                        + infiltrated_precipitation * self.area
                        - evaporation
                        - infiltration_excess
                    )
                )
            )

    # TODO saturation excess (think it should just be 'pull_ponded'  presumably in
    # net effective precipitation? )

    # Convert to VQIPs
    infiltration_excess = self.v_change_vqip(self.empty_vqip(), infiltration_excess)
    infiltration_excess["temperature"] = temperature
    precipitation = self.v_change_vqip(self.empty_vqip(), precipitation)
    evaporation = self.v_change_vqip(self.empty_vqip(), evaporation)

    # Track flows (these are sent onwards in the route function)
    self.infiltration_excess = infiltration_excess
    self.subsurface_flow = subsurface_flow
    self.percolation = percolation
    self.tank_recharge = tank_recharge
    self.evaporation = evaporation
    self.precipitation = precipitation

    # Mass balance
    in_ = precipitation
    out_ = evaporation

    return (in_, out_)

route()

An outflow function that sends percolation, subsurface runoff and surface runoff to their respective tanks in the parent land node.

Returns:

Type	Description
tuple	A tuple containing a VQIP amount for model inputs and outputs for mass balance checking.

Source code in wsimod\nodes\land.py

def route(self):
    """An outflow function that sends percolation, subsurface runoff and surface
    runoff to their respective tanks in the parent land node.

    Returns:
        (tuple): A tuple containing a VQIP amount for model inputs and outputs
            for mass balance checking.
    """
    self.parent.surface_runoff.push_storage(self.infiltration_excess, force=True)
    self.parent.subsurface_runoff.push_storage(self.subsurface_flow, force=True)
    self.parent.percolation.push_storage(self.percolation, force=True)

    return (self.empty_vqip(), self.empty_vqip())

Surface

Bases: DecayTank

Source code in wsimod\nodes\land.py

class Surface(DecayTank):
    """"""

    def __init__(
        self,
        surface="",
        area=1,
        depth=1,
        data_input_dict={},
        pollutant_load={},
        **kwargs,
    ):
        """A subclass of DecayTank. Each Surface is anticipated to represent a different
        land cover type of a Land node. Besides functioning as a Tank, Surfaces have
        three lists of functions (inflows, processes and outflows) where behaviour can
        be added by appending new functions. We anticipate that customised surfaces
        should be a subclass of Surface or its subclasses and add functions to these
        lists. These lists are executed (inflows first, then processes, then outflows)
        in the run function, which is called by the run function in Land. The lists must
        return any model inflows or outflows as a VQIP for mass balance checking.

        If a user wishes the DecayTank portion to be active, then can provide 'decays',
        which are passed upwards (see wsimod/core/core.py/DecayObj for documentation)

        Args:
            surface (str, optional): String description of the surface type. Doesn't
                serve a modelling purpose, just used for user reference. Defaults to ''.
            area (float, optional): Area of surface. Defaults to 1. depth (float,
            optional): Depth of tank (this has different physical
                implications for different subclasses). Defaults to 1.
            data_input_dict (dict, optional):  Dictionary of data inputs relevant for
                the surface (generally, deposition). Keys are tuples where first value
                is the name of the variable to read from the dict and the second value
                is the time. Note that this input should be specific to the surface, and
                is not intended to be the same data input as for the land node. Also
                note that with each surface having its own timeseries of data inputs,
                this can take up a lot of memory, thus the default behavior is to have
                this as monthly data where the time variable is a monthyear. Defaults to
                {}.
            pollutant_load (dict, optional): A dict of different pollutant amounts that
                are deposited on the surface (units are mass per area per timestep).
                Defaults to {}.

        Key assumptions:
            - Generic `Surface` that reads data and can apply simple forms of pollution
              deposition.
            - Formulated as a `Tank` object.
            - Ammonia->Nitrite->Nitrate decay takes place if parameters describing this
                process are provided in `decays` (see `core.py/DecayObj` for
                transformation details).

        Input data and parameter requirements:
            - `data_input_dict` can contain a variety of pollutant deposition data.
                `srp-dry` describes phosphate. `noy-dry` describes nitrogen as nitrates.
                `nhx-dry` describes nitrogen as ammonia. `srp/noy/ nhx-wet` can also be
                used to specify wet deposition. _Units_: kg/m2/timestep (data is read at
                a monthly timestep)
        """
        # Assign parameters
        self.depth = depth
        self.data_input_dict = data_input_dict
        self.surface = surface
        self.pollutant_load = pollutant_load
        # TODO this is a decaytank but growing surfaces don't have decay parameters...
        # is it a problem.. we don't even take decays as an explicit argument and insert
        # them in kwargs..
        capacity = area * depth
        # Parameters
        super().__init__(capacity=capacity, area=area, **kwargs)

        # Populate function lists TODO.. not sure why I have deposition but no
        # precipitation here
        if "nhx-dry" in set(x[0] for x in data_input_dict.keys()):
            self.inflows = [self.atmospheric_deposition, self.precipitation_deposition]
        else:
            self.inflows = []
        if len(self.pollutant_load) > 0:
            self.inflows.append(self.simple_deposition)
        self.processes = []
        self.outflows = []

    def apply_overrides(self, overrides=Dict[str, Any]):
        """Override parameters.

        Enables a user to override any of the following parameters:
        area and depth (both will update the capacity), pollutant_load (the
        entire dict does not need to be redefined, only changed values need to
        be included).

        Args:
            overrides (Dict[str, Any]): Dict describing which parameters should
                be overridden (keys) and new values (values). Defaults to {}.
        """
        self.surface = overrides.pop("surface", self.surface)
        self.pollutant_load.update(overrides.pop("pollutant_load", {}))

        self.area = overrides.pop("area", self.area)
        self.depth = overrides.pop("depth", self.depth)
        self.capacity = self.area * self.depth

        if "capacity" in overrides.keys():
            overrides.pop("capacity")
            print(
                "Warning: specifying capacity is depreciated in overrides for surface, \
		please specify depth and area instead. capacity override value has been ignored"
            )

        # overrides data_input_dict
        from wsimod.orchestration.model import read_csv

        content = overrides.pop("data_input_dict", self.data_input_dict)
        if isinstance(content, str):
            self.data_input_dict = read_csv(content)
        elif isinstance(content, dict):
            self.data_input_dict = content
        else:
            raise ValueError(
                f"{content.__class__} is not a recognised format for data_input_dict"
            )

        super().apply_overrides(overrides)

    def run(self):
        """Call run function (called from Land node)."""
        if "nitrite" in constants.POLLUTANTS:
            # Assume that if nitrite is modelled then nitrification is also modelled You
            # will need ammonia->nitrite->nitrate decay to accurate simulate ammonia
            # Thus, these decays are simulated here

            # NOTE decay in a decaytank happens at start of timestep (confusingly) in
            # the end_timestep function
            self.storage["nitrate"] += self.total_decayed["nitrite"]
            self.parent.running_inflow_mb["nitrate"] += self.total_decayed["nitrite"]

            # Decayed ammonia becomes nitrite
            self.storage["nitrite"] += self.total_decayed["ammonia"]
            self.parent.running_inflow_mb["nitrite"] += self.total_decayed["ammonia"]

        for f in self.inflows + self.processes + self.outflows:
            # Iterate over function lists, updating mass balance
            in_, out_ = f()
            self.parent.running_inflow_mb = self.sum_vqip(
                self.parent.running_inflow_mb, in_
            )
            self.parent.running_outflow_mb = self.sum_vqip(
                self.parent.running_outflow_mb, out_
            )

    def get_data_input(self, var):
        """Read data input from parent Land node (i.e., for precipitation/et0/temp).

        Args:
            var (str): Name of variable

        Returns:
            Data read
        """
        return self.parent.get_data_input(var)

    def get_data_input_surface(self, var):
        """Read data input from this surface's data_input_dict.

        Args:
            var (str): Name of variable

        Returns:
            Data read
        """
        return self.data_input_dict[(var, self.parent.monthyear)]

    def dry_deposition_to_tank(self, vqip):
        """Generic function for allocating dry pollution deposition to the surface.
        Simply sends the pollution into the tank (some subclasses overwrite this
        behaviour).

        Args:
            vqip (dict): A VQIP amount of dry deposition to send to tank

        Returns:
            vqip (dict): A VQIP amount of dry deposition that entered the tank (used
                for mass balance checking)
        """
        # Default behaviour is to just enter the tank
        _ = self.push_storage(vqip, force=True)
        return vqip

    def wet_deposition_to_tank(self, vqip):
        """Generic function for allocating wet pollution deposition to the surface.
        Simply sends the pollution into the tank (some subclasses overwrite this
        behaviour).

        Args:
            vqip (dict): A VQIP amount of wet deposition to send to tank

        Returns:
            vqip (dict): A VQIP amount of wet deposition that entered the tank (used
                for mass balance checking)
        """
        # Default behaviour is to just enter the tank
        _ = self.push_storage(vqip, force=True)
        return vqip

    def simple_deposition(self):
        """Inflow function to cause simple pollution deposition to occur, updating the
        surface tank.

        Returns:
            (tuple): A tuple containing a VQIP amount for model inputs and outputs
                for mass balance checking.
        """
        pollution = self.empty_vqip()

        # Scale by area
        for pol, item in self.pollutant_load.items():
            if pol in constants.ADDITIVE_POLLUTANTS:
                pollution[pol] = item * self.area
            else:
                pollution[pol] = item
        pollution["volume"] = 0

        # Update tank
        _ = self.push_storage(pollution, force=True)

        return (pollution, self.empty_vqip())

    def atmospheric_deposition(self):
        """Inflow function to cause dry atmospheric deposition to occur, updating the
        surface tank.

        Returns:
            (tuple): A tuple containing a VQIP amount for model inputs and outputs
                for mass balance checking.
        """
        # TODO double check units in preprocessing - is weight of N or weight of
        # NHX/noy?

        # Read data and scale
        nhx = self.get_data_input_surface("nhx-dry") * self.area
        noy = self.get_data_input_surface("noy-dry") * self.area
        srp = self.get_data_input_surface("srp-dry") * self.area

        # Assign pollutants
        vqip = self.empty_vqip()
        vqip["ammonia"] = nhx
        vqip["nitrate"] = noy
        vqip["phosphate"] = srp

        # Update tank
        in_ = self.dry_deposition_to_tank(vqip)

        # Return mass balance
        return (in_, self.empty_vqip())

    def precipitation_deposition(self):
        """Inflow function to cause wet precipitation deposition to occur, updating the
        surface tank.

        Returns:
            (tuple): A tuple containing a VQIP amount for model inputs and outputs
                for mass balance checking.
        """
        # TODO double check units - is weight of N or weight of NHX/noy?

        # Read data and scale
        nhx = self.get_data_input_surface("nhx-wet") * self.area
        noy = self.get_data_input_surface("noy-wet") * self.area
        srp = self.get_data_input_surface("srp-wet") * self.area

        # Assign pollutants
        vqip = self.empty_vqip()
        vqip["ammonia"] = nhx
        vqip["nitrate"] = noy
        vqip["phosphate"] = srp

        # Update tank
        in_ = self.wet_deposition_to_tank(vqip)

        # Return mass balance
        return (in_, self.empty_vqip())

__init__(surface='', area=1, depth=1, data_input_dict={}, pollutant_load={}, **kwargs)

A subclass of DecayTank. Each Surface is anticipated to represent a different land cover type of a Land node. Besides functioning as a Tank, Surfaces have three lists of functions (inflows, processes and outflows) where behaviour can be added by appending new functions. We anticipate that customised surfaces should be a subclass of Surface or its subclasses and add functions to these lists. These lists are executed (inflows first, then processes, then outflows) in the run function, which is called by the run function in Land. The lists must return any model inflows or outflows as a VQIP for mass balance checking.

If a user wishes the DecayTank portion to be active, then can provide 'decays', which are passed upwards (see wsimod/core/core.py/DecayObj for documentation)

Parameters:

Name	Type	Description	Default
surface	str	String description of the surface type. Doesn't serve a modelling purpose, just used for user reference. Defaults to ''.	''
area	float	Area of surface. Defaults to 1. depth (float,	1
optional)		Depth of tank (this has different physical implications for different subclasses). Defaults to 1.	required
data_input_dict	dict	Dictionary of data inputs relevant for the surface (generally, deposition). Keys are tuples where first value is the name of the variable to read from the dict and the second value is the time. Note that this input should be specific to the surface, and is not intended to be the same data input as for the land node. Also note that with each surface having its own timeseries of data inputs, this can take up a lot of memory, thus the default behavior is to have this as monthly data where the time variable is a monthyear. Defaults to {}.	{}
pollutant_load	dict	A dict of different pollutant amounts that are deposited on the surface (units are mass per area per timestep). Defaults to {}.	{}

Key assumptions

• Generic Surface that reads data and can apply simple forms of pollution deposition.
• Formulated as a Tank object.
• Ammonia->Nitrite->Nitrate decay takes place if parameters describing this process are provided in decays (see core.py/DecayObj for transformation details).

Input data and parameter requirements

• data_input_dict can contain a variety of pollutant deposition data. srp-dry describes phosphate. noy-dry describes nitrogen as nitrates. nhx-dry describes nitrogen as ammonia. srp/noy/ nhx-wet can also be used to specify wet deposition. Units: kg/m2/timestep (data is read at a monthly timestep)

Source code in wsimod\nodes\land.py

def __init__(
    self,
    surface="",
    area=1,
    depth=1,
    data_input_dict={},
    pollutant_load={},
    **kwargs,
):
    """A subclass of DecayTank. Each Surface is anticipated to represent a different
    land cover type of a Land node. Besides functioning as a Tank, Surfaces have
    three lists of functions (inflows, processes and outflows) where behaviour can
    be added by appending new functions. We anticipate that customised surfaces
    should be a subclass of Surface or its subclasses and add functions to these
    lists. These lists are executed (inflows first, then processes, then outflows)
    in the run function, which is called by the run function in Land. The lists must
    return any model inflows or outflows as a VQIP for mass balance checking.

    If a user wishes the DecayTank portion to be active, then can provide 'decays',
    which are passed upwards (see wsimod/core/core.py/DecayObj for documentation)

    Args:
        surface (str, optional): String description of the surface type. Doesn't
            serve a modelling purpose, just used for user reference. Defaults to ''.
        area (float, optional): Area of surface. Defaults to 1. depth (float,
        optional): Depth of tank (this has different physical
            implications for different subclasses). Defaults to 1.
        data_input_dict (dict, optional):  Dictionary of data inputs relevant for
            the surface (generally, deposition). Keys are tuples where first value
            is the name of the variable to read from the dict and the second value
            is the time. Note that this input should be specific to the surface, and
            is not intended to be the same data input as for the land node. Also
            note that with each surface having its own timeseries of data inputs,
            this can take up a lot of memory, thus the default behavior is to have
            this as monthly data where the time variable is a monthyear. Defaults to
            {}.
        pollutant_load (dict, optional): A dict of different pollutant amounts that
            are deposited on the surface (units are mass per area per timestep).
            Defaults to {}.

    Key assumptions:
        - Generic `Surface` that reads data and can apply simple forms of pollution
          deposition.
        - Formulated as a `Tank` object.
        - Ammonia->Nitrite->Nitrate decay takes place if parameters describing this
            process are provided in `decays` (see `core.py/DecayObj` for
            transformation details).

    Input data and parameter requirements:
        - `data_input_dict` can contain a variety of pollutant deposition data.
            `srp-dry` describes phosphate. `noy-dry` describes nitrogen as nitrates.
            `nhx-dry` describes nitrogen as ammonia. `srp/noy/ nhx-wet` can also be
            used to specify wet deposition. _Units_: kg/m2/timestep (data is read at
            a monthly timestep)
    """
    # Assign parameters
    self.depth = depth
    self.data_input_dict = data_input_dict
    self.surface = surface
    self.pollutant_load = pollutant_load
    # TODO this is a decaytank but growing surfaces don't have decay parameters...
    # is it a problem.. we don't even take decays as an explicit argument and insert
    # them in kwargs..
    capacity = area * depth
    # Parameters
    super().__init__(capacity=capacity, area=area, **kwargs)

    # Populate function lists TODO.. not sure why I have deposition but no
    # precipitation here
    if "nhx-dry" in set(x[0] for x in data_input_dict.keys()):
        self.inflows = [self.atmospheric_deposition, self.precipitation_deposition]
    else:
        self.inflows = []
    if len(self.pollutant_load) > 0:
        self.inflows.append(self.simple_deposition)
    self.processes = []
    self.outflows = []

apply_overrides(overrides=Dict[str, Any])

Override parameters.

Enables a user to override any of the following parameters: area and depth (both will update the capacity), pollutant_load (the entire dict does not need to be redefined, only changed values need to be included).

Parameters:

Name	Type	Description	Default
overrides	Dict[str, Any]	Dict describing which parameters should be overridden (keys) and new values (values). Defaults to {}.	Dict[str, Any]

Source code in wsimod\nodes\land.py

    def apply_overrides(self, overrides=Dict[str, Any]):
        """Override parameters.

        Enables a user to override any of the following parameters:
        area and depth (both will update the capacity), pollutant_load (the
        entire dict does not need to be redefined, only changed values need to
        be included).

        Args:
            overrides (Dict[str, Any]): Dict describing which parameters should
                be overridden (keys) and new values (values). Defaults to {}.
        """
        self.surface = overrides.pop("surface", self.surface)
        self.pollutant_load.update(overrides.pop("pollutant_load", {}))

        self.area = overrides.pop("area", self.area)
        self.depth = overrides.pop("depth", self.depth)
        self.capacity = self.area * self.depth

        if "capacity" in overrides.keys():
            overrides.pop("capacity")
            print(
                "Warning: specifying capacity is depreciated in overrides for surface, \
		please specify depth and area instead. capacity override value has been ignored"
            )

        # overrides data_input_dict
        from wsimod.orchestration.model import read_csv

        content = overrides.pop("data_input_dict", self.data_input_dict)
        if isinstance(content, str):
            self.data_input_dict = read_csv(content)
        elif isinstance(content, dict):
            self.data_input_dict = content
        else:
            raise ValueError(
                f"{content.__class__} is not a recognised format for data_input_dict"
            )

        super().apply_overrides(overrides)

atmospheric_deposition()

Inflow function to cause dry atmospheric deposition to occur, updating the surface tank.

Returns:

Type	Description
tuple	A tuple containing a VQIP amount for model inputs and outputs for mass balance checking.

Source code in wsimod\nodes\land.py

def atmospheric_deposition(self):
    """Inflow function to cause dry atmospheric deposition to occur, updating the
    surface tank.

    Returns:
        (tuple): A tuple containing a VQIP amount for model inputs and outputs
            for mass balance checking.
    """
    # TODO double check units in preprocessing - is weight of N or weight of
    # NHX/noy?

    # Read data and scale
    nhx = self.get_data_input_surface("nhx-dry") * self.area
    noy = self.get_data_input_surface("noy-dry") * self.area
    srp = self.get_data_input_surface("srp-dry") * self.area

    # Assign pollutants
    vqip = self.empty_vqip()
    vqip["ammonia"] = nhx
    vqip["nitrate"] = noy
    vqip["phosphate"] = srp

    # Update tank
    in_ = self.dry_deposition_to_tank(vqip)

    # Return mass balance
    return (in_, self.empty_vqip())

dry_deposition_to_tank(vqip)

Generic function for allocating dry pollution deposition to the surface. Simply sends the pollution into the tank (some subclasses overwrite this behaviour).

Parameters:

Name	Type	Description	Default
vqip	dict	A VQIP amount of dry deposition to send to tank	required

Returns:

Name	Type	Description
vqip	dict	A VQIP amount of dry deposition that entered the tank (used for mass balance checking)

Source code in wsimod\nodes\land.py

def dry_deposition_to_tank(self, vqip):
    """Generic function for allocating dry pollution deposition to the surface.
    Simply sends the pollution into the tank (some subclasses overwrite this
    behaviour).

    Args:
        vqip (dict): A VQIP amount of dry deposition to send to tank

    Returns:
        vqip (dict): A VQIP amount of dry deposition that entered the tank (used
            for mass balance checking)
    """
    # Default behaviour is to just enter the tank
    _ = self.push_storage(vqip, force=True)
    return vqip

get_data_input(var)

Read data input from parent Land node (i.e., for precipitation/et0/temp).

Parameters:

Name	Type	Description	Default
var	str	Name of variable	required

Returns:

Type	Description
	Data read

Source code in wsimod\nodes\land.py

def get_data_input(self, var):
    """Read data input from parent Land node (i.e., for precipitation/et0/temp).

    Args:
        var (str): Name of variable

    Returns:
        Data read
    """
    return self.parent.get_data_input(var)

get_data_input_surface(var)

Read data input from this surface's data_input_dict.

Parameters:

Name	Type	Description	Default
var	str	Name of variable	required

Returns:

Type	Description
	Data read

Source code in wsimod\nodes\land.py

def get_data_input_surface(self, var):
    """Read data input from this surface's data_input_dict.

    Args:
        var (str): Name of variable

    Returns:
        Data read
    """
    return self.data_input_dict[(var, self.parent.monthyear)]

precipitation_deposition()

Inflow function to cause wet precipitation deposition to occur, updating the surface tank.

Returns:

Type	Description
tuple	A tuple containing a VQIP amount for model inputs and outputs for mass balance checking.

Source code in wsimod\nodes\land.py

def precipitation_deposition(self):
    """Inflow function to cause wet precipitation deposition to occur, updating the
    surface tank.

    Returns:
        (tuple): A tuple containing a VQIP amount for model inputs and outputs
            for mass balance checking.
    """
    # TODO double check units - is weight of N or weight of NHX/noy?

    # Read data and scale
    nhx = self.get_data_input_surface("nhx-wet") * self.area
    noy = self.get_data_input_surface("noy-wet") * self.area
    srp = self.get_data_input_surface("srp-wet") * self.area

    # Assign pollutants
    vqip = self.empty_vqip()
    vqip["ammonia"] = nhx
    vqip["nitrate"] = noy
    vqip["phosphate"] = srp

    # Update tank
    in_ = self.wet_deposition_to_tank(vqip)

    # Return mass balance
    return (in_, self.empty_vqip())

run()

Call run function (called from Land node).

Source code in wsimod\nodes\land.py

def run(self):
    """Call run function (called from Land node)."""
    if "nitrite" in constants.POLLUTANTS:
        # Assume that if nitrite is modelled then nitrification is also modelled You
        # will need ammonia->nitrite->nitrate decay to accurate simulate ammonia
        # Thus, these decays are simulated here

        # NOTE decay in a decaytank happens at start of timestep (confusingly) in
        # the end_timestep function
        self.storage["nitrate"] += self.total_decayed["nitrite"]
        self.parent.running_inflow_mb["nitrate"] += self.total_decayed["nitrite"]

        # Decayed ammonia becomes nitrite
        self.storage["nitrite"] += self.total_decayed["ammonia"]
        self.parent.running_inflow_mb["nitrite"] += self.total_decayed["ammonia"]

    for f in self.inflows + self.processes + self.outflows:
        # Iterate over function lists, updating mass balance
        in_, out_ = f()
        self.parent.running_inflow_mb = self.sum_vqip(
            self.parent.running_inflow_mb, in_
        )
        self.parent.running_outflow_mb = self.sum_vqip(
            self.parent.running_outflow_mb, out_
        )

simple_deposition()

Inflow function to cause simple pollution deposition to occur, updating the surface tank.

Returns:

Type	Description
tuple	A tuple containing a VQIP amount for model inputs and outputs for mass balance checking.

Source code in wsimod\nodes\land.py

def simple_deposition(self):
    """Inflow function to cause simple pollution deposition to occur, updating the
    surface tank.

    Returns:
        (tuple): A tuple containing a VQIP amount for model inputs and outputs
            for mass balance checking.
    """
    pollution = self.empty_vqip()

    # Scale by area
    for pol, item in self.pollutant_load.items():
        if pol in constants.ADDITIVE_POLLUTANTS:
            pollution[pol] = item * self.area
        else:
            pollution[pol] = item
    pollution["volume"] = 0

    # Update tank
    _ = self.push_storage(pollution, force=True)

    return (pollution, self.empty_vqip())

wet_deposition_to_tank(vqip)

Generic function for allocating wet pollution deposition to the surface. Simply sends the pollution into the tank (some subclasses overwrite this behaviour).

Parameters:

Name	Type	Description	Default
vqip	dict	A VQIP amount of wet deposition to send to tank	required

Returns:

Name	Type	Description
vqip	dict	A VQIP amount of wet deposition that entered the tank (used for mass balance checking)

Source code in wsimod\nodes\land.py

def wet_deposition_to_tank(self, vqip):
    """Generic function for allocating wet pollution deposition to the surface.
    Simply sends the pollution into the tank (some subclasses overwrite this
    behaviour).

    Args:
        vqip (dict): A VQIP amount of wet deposition to send to tank

    Returns:
        vqip (dict): A VQIP amount of wet deposition that entered the tank (used
            for mass balance checking)
    """
    # Default behaviour is to just enter the tank
    _ = self.push_storage(vqip, force=True)
    return vqip

VariableAreaSurface

Bases: GrowingSurface

Source code in wsimod\nodes\land.py

class VariableAreaSurface(GrowingSurface):
    """"""

    def __init__(self, current_surface_area=0, **kwargs):
        """"""
        super().__init__(**kwargs)
        self.get_climate = self.get_climate_
        self.current_surface_area = current_surface_area

    def get_climate_(self):
        """

        Returns:

        """
        precipitation_depth = self.get_data_input("precipitation")
        evaporation_depth = self.get_data_input("et0") * self.et0_coefficient

        precipitation_depth *= self.current_surface_area / self.area
        evaporation_depth *= self.current_surface_area / self.area

        return precipitation_depth, evaporation_depth

__init__(current_surface_area=0, **kwargs)

Source code in wsimod\nodes\land.py

def __init__(self, current_surface_area=0, **kwargs):
    """"""
    super().__init__(**kwargs)
    self.get_climate = self.get_climate_
    self.current_surface_area = current_surface_area

get_climate_()

Returns:

Source code in wsimod\nodes\land.py

def get_climate_(self):
    """

    Returns:

    """
    precipitation_depth = self.get_data_input("precipitation")
    evaporation_depth = self.get_data_input("et0") * self.et0_coefficient

    precipitation_depth *= self.current_surface_area / self.area
    evaporation_depth *= self.current_surface_area / self.area

    return precipitation_depth, evaporation_depth

Created on Thu May 19 16:42:20 2022.

@author: barna

NutrientPool

Source code in wsimod\nodes\nutrient_pool.py

class NutrientPool:
    """"""

    def __init__(
        self,
        fraction_dry_n_to_dissolved_inorganic=0.9,
        degrhpar={"N": 7 * 1e-5, "P": 7 * 1e-6},
        dishpar={"N": 7 * 1e-5, "P": 7 * 1e-6},
        minfpar={"N": 0.00013, "P": 0.000003},
        disfpar={"N": 0.000003, "P": 0.0000001},
        immobdpar={"N": 0.0056, "P": 0.2866},
        fraction_manure_to_dissolved_inorganic={"N": 0.5, "P": 0.1},
        fraction_residue_to_fast={"N": 0.1, "P": 0.1},
    ):
        """A class to track nutrient pools in a soil tank, intended to be initialised
        and called by GrowingSurfaces (see wsimod/nodes/land.py/GrowingSurface) and
        their subclasses. Contains five pools, which have a storage that tracks the mass
        of nutrients. Equations and parameters are based on HYPE.

        Args:
            fraction_dry_n_to_dissolved_inorganic (float, optional): fraction of dry
            nitrogen deposition going into the soil dissolved inorganic nitrogen pool,
            with the rest added to the fast pool. Defaults to 0.9. degrhpar (dict,
            optional): reference humus degradation rate (fraction of humus pool to fast
            pool). Defaults to {'N' : 7 * 1e-5, 'P' : 7 * 1e-6}. dishpar (dict,
            optional): reference humus dissolution rate (fraction of humus pool to
            dissolved organic pool). Defaults to {'N' : 7 * 1e-5, 'P' : 7 * 1e-6}.
            minfpar (dict, optional): reference fast pool mineralisation rate (fraction
            of fast pool to dissolved inorganic pool). Defaults to {'N' : 0.00013, 'P' :
            0.000003}. disfpar (dict, optional): reference fast pool dissolution rate
            (fraction of fast pool to dissolved organic pool). Defaults to {'N' :
            0.000003, 'P' : 0.0000001}. immobdpar (dict, optional): reference
            immobilisation rate (fraction of dissolved inorganic pool to fast pool).
            Defaults to {'N' : 0.0056, 'P' : 0.2866}.
            fraction_manure_to_dissolved_inorganic (dict, optional): fraction of
            nutrients from applied manure to dissolved inorganic pool, with the rest
            added to the fast pool. Defaults to {'N' : 0.5, 'P' : 0.1}.
            fraction_residue_to_fast (dict, optional): fraction of nutrients from
            residue to fast pool, with the rest added to the humus pool. Defaults to
            {'N' : 0.1, 'P' : 0.1}.

        Key assumptions:
             - Four nutrient pools are conceptualised for both nitrogen and phosphorus
                in soil, which includes humus pool, fast pool, dissolved inorganic pool,
                and dissolved organic pool. Humus and fast pool represent immobile pool
                of organic nutrients in the soil with slow and fast turnover,
                respectively. Dissolved inorganic and organic pool represent nutrients
                in dissolved phase in soil water (for phosphorus, dissolved organic pool
                might contain particulate phase). Given that phoshphorus can be adsorbed
                and attached to soil particles, an adsorbed inorganic pool is created
                specifically for phosphorus.
             - The major sources of nutrients to soil are conceptualised as
                - atmospheric deposition:
                    - dry deposition:
                        - for nitrogen, inorganic fraction of dry deposition is added to
                          the dissovled
                           inorganic pool, while the rest is added to the fast pool;
                        - for phosphorus, all is added to adsorbed inorganic pool.
                    - wet deposition: all is added to the dissolved inorganic pool.
                - fertilisers: all added to the dissolved inorganic pool.
                - manure: the inorganic fraction is added to the dissovled inorganic
                  pool, with
                    the rest added to the fast pool.
                - residue: the part with fast turnover is added to the fast pool, with
                  the rest
                    added to the humus pool.
             - Nutrient fluxes between these pools are simulated to represent the
               biochemical processes
                that can transform the nutrients between different forms. These
                processes include - degradation of humus pool to fast pool - dissolution
                of humus pool to dissovled organic pool - mineralisation of fast pool to
                dissolved inorganic pool - dissolution of fast pool to dissolved organic
                pool - immobilisation of dissolved inroganic pool to fast pool The rate
                of these processes are affected by the soil temperature and moisture
                conditions.
             - When soil erosion happens, a portion of both the adsorbed inorganic pool
               and humus pool
                for phosphorus will be eroded as well.

        Input data and parameter requirements:
             - fraction_dry_n_to_dissolved_inorganic,
               fraction_manure_to_dissolved_inorganic, fraction_residue_to_fast.
                _Units_: -, all should in [0-1]
             - degrhpar, dishpar, minfpar, disfpar, immobdpar.
                _Units_: -, all should in [0-1]
        """
        # TODO I don't think anyone will change most of these params... they could maybe
        # just be set here
        self.init_empty()

        # Assign parameters
        self.temperature_dependence_factor = 0
        self.soil_moisture_dependence_factor = 0

        self.fraction_manure_to_dissolved_inorganic = (
            fraction_manure_to_dissolved_inorganic
        )
        self.fraction_residue_to_fast = fraction_residue_to_fast
        self.fraction_dry_n_to_dissolved_inorganic = (
            fraction_dry_n_to_dissolved_inorganic
        )

        self.degrhpar = degrhpar
        self.dishpar = dishpar
        self.minfpar = minfpar
        self.disfpar = disfpar
        self.immobdpar = immobdpar

        self.fraction_manure_to_fast = None
        self.fraction_residue_to_humus = None
        self.fraction_dry_n_to_fast = None
        self.calculate_fraction_parameters()

        # Initialise different pools
        self.fast_pool = NutrientStore()
        self.humus_pool = NutrientStore()
        self.dissolved_inorganic_pool = NutrientStore()
        self.dissolved_organic_pool = NutrientStore()
        self.adsorbed_inorganic_pool = NutrientStore()
        self.pools = [
            self.fast_pool,
            self.humus_pool,
            self.dissolved_inorganic_pool,
            self.dissolved_organic_pool,
            self.adsorbed_inorganic_pool,
        ]

    def calculate_fraction_parameters(self):
        """Update fractions of nutrients input transformed into other forms in soil
        based on the input parameters
        Returns:
            (dict): fraction of manure to fast pool
            (dict): fraction of plant residue to humus pool
            (float): fraction of dry nitrogen deposition to fast pool
        """
        self.fraction_manure_to_fast = {
            x: 1 - self.fraction_manure_to_dissolved_inorganic[x]
            for x in constants.NUTRIENTS
        }
        self.fraction_residue_to_humus = {
            x: 1 - self.fraction_residue_to_fast[x] for x in constants.NUTRIENTS
        }
        self.fraction_dry_n_to_fast = 1 - self.fraction_dry_n_to_dissolved_inorganic

    def apply_overrides(self, overrides=Dict[str, Any]):
        """Override parameters.

        Enables a user to override any of the following parameters:
        eto_to_e, pore_depth.

        Args:
            overrides (Dict[str, Any]): Dict describing which parameters should
                be overridden (keys) and new values (values). Defaults to {}.
        """
        self.fraction_dry_n_to_dissolved_inorganic = overrides.pop(
            "fraction_dry_n_to_dissolved_inorganic",
            self.fraction_dry_n_to_dissolved_inorganic,
        )
        self.fraction_residue_to_fast.update(
            overrides.pop("fraction_residue_to_fast", {})
        )
        self.fraction_manure_to_dissolved_inorganic.update(
            overrides.pop("fraction_manure_to_dissolved_inorganic", {})
        )
        self.degrhpar.update(overrides.pop("degrhpar", {}))
        self.dishpar.update(overrides.pop("dishpar", {}))
        self.minfpar.update(overrides.pop("minfpar", {}))
        self.disfpar.update(overrides.pop("disfpar", {}))
        self.immobdpar.update(overrides.pop("immobdpar", {}))

        self.calculate_fraction_parameters()

    def init_empty(self):
        """Initialise an empty nutrient to be copied."""
        self.empty_nutrient = {x: 0 for x in constants.NUTRIENTS}

    def init_store(self):
        """Initialise an empty store to track nutrients."""
        self.init_empty()
        self.storage = self.get_empty_nutrient()

    def allocate_inorganic_irrigation(self, irrigation):
        """Assign inorganic irrigation, which is assumed to contain dissolved inorganic
        nutrients and thus updates that pool.

        Args:
            irrigation (dict): A dict that contains the amount of nutrients entering
                the nutrient pool via irrigation

        Returns:
            irrigation (dict): irrigation above, because no transformations take place
                (i.e., dissolved inorganic is what is received and goes straight into
                that pool)
        """
        # Update pool
        self.dissolved_inorganic_pool.receive(irrigation)
        return irrigation

    def allocate_organic_irrigation(self, irrigation):
        """Assign organic irrigation, which is assumed to contain dissolved organic
        nutrients and thus updates that pool.

        Args:
            irrigation (dict): A dict that contains the amount of nutrients entering
                the nutrient pool via irrigation

        Returns:
            irrigation (dict): irrigation above, because no transformations take place
                (i.e., dissolved organic is what is received and goes straight into that
                pool)
        """
        # Update pool
        self.dissolved_organic_pool.receive(irrigation)
        return irrigation

    def allocate_dry_deposition(self, deposition):
        """Assign dry deposition, which is assumed to go to both dissolved inorganic
        pool and fast pool (nitrogen) and the adsorbed pool (phosphorus).

        Args:
            deposition (dict): A dict that contains the amount of nutrients entering
                the nutrient pool via dry deposition

        Returns:
            (dict): A dict describing the amount of nutrients that enter the nutrient
                pool in a dissolved form (and thus need to be tracked by the soil water
                tank)
        """
        # Update pools
        self.fast_pool.storage["N"] += deposition["N"] * self.fraction_dry_n_to_fast
        self.dissolved_inorganic_pool.storage["N"] += (
            deposition["N"] * self.fraction_dry_n_to_dissolved_inorganic
        )
        self.adsorbed_inorganic_pool.storage["P"] += deposition["P"]
        return {
            "N": deposition["N"] * self.fraction_dry_n_to_dissolved_inorganic,
            "P": 0,
        }

    def allocate_wet_deposition(self, deposition):
        """Assign wet deposition, which is assumed to contain dissolved inorganic
        nutrients and thus updates that pool.

        Args:
            deposition (dict): A dict that contains the amount of nutrients entering
                the nutrient pool via wet deposition

        Returns:
            deposition (dict): deposition above, because no transformations take place
                (i.e., dissolved inorganic is what is received and goes straight into
                that pool)
        """
        # Update pool
        self.dissolved_inorganic_pool.receive(deposition)
        return deposition

    def allocate_manure(self, manure):
        """Assign manure, which is assumed to go to both dissolved inorganic pool and
        fast pool.

        Args:
            manure (dict): A dict that contains the amount of nutrients entering
                the nutrient pool via manure

        Returns:
            (dict): A dict describing the amount of nutrients that enter the nutrient
                pool in a dissolved form (and thus need to be tracked by the soil water
                tank)
        """
        # Assign a proportion of nutrients to the dissolved inorganic pool
        self.dissolved_inorganic_pool.receive(
            self.multiply_nutrients(manure, self.fraction_manure_to_dissolved_inorganic)
        )
        # Assign a proportion of nutrients to the fast pool
        self.fast_pool.receive(
            self.multiply_nutrients(manure, self.fraction_manure_to_fast)
        )
        return self.multiply_nutrients(
            manure, self.fraction_manure_to_dissolved_inorganic
        )

    def allocate_residue(self, residue):
        """Assign residue, which is assumed to go to both humus pool and fast pool.

        Args:
            residue (dict): A dict that contains the amount of nutrients entering
                the nutrient pool via residue

        Returns:
            (dict): A dict describing the amount of nutrients that enter the nutrient
                pool in a dissolved form (and thus need to be tracked by the soil water
                tank) - i.e., none because fast and humus pool are both solid
        """
        # Assign a proportion of nutrients to the humus pool
        self.humus_pool.receive(
            self.multiply_nutrients(residue, self.fraction_residue_to_humus)
        )
        # Assign a proportion of nutrients to the fast pool
        self.fast_pool.receive(
            self.multiply_nutrients(residue, self.fraction_residue_to_fast)
        )
        return self.empty_nutrient()

    def allocate_fertiliser(self, fertiliser):
        """Assign fertiliser, which is assumed to contain dissolved inorganic nutrients
        and thus updates that pool.

        Args:
            fertiliser (dict): A dict that contains the amount of nutrients entering
                the nutrient pool via fertiliser

        Returns:
            fertiliser (dict): fertiliser above, because no transformations take place
                (i.e., dissolved inorganic is what is received and goes straight into
                that pool)
        """
        self.dissolved_inorganic_pool.receive(fertiliser)
        return fertiliser

    def extract_dissolved(self, proportion):
        """Function to extract some amount of nutrients from all dissolved pools.

        Args:
            proportion (float): proportion of the dissolved nutrient pools to extract

        Returns:
            (dict): A dict of dicts, where the top level distinguishes between organic
                and inorganic nutrients, and the bottom level describes how much
                nutrients (i.e., N and P) have been extracted from those pools
        """
        # Extract from dissolved inorganic pool
        reply_di = self.dissolved_inorganic_pool.extract(
            {
                "N": self.dissolved_inorganic_pool.storage["N"] * proportion,
                "P": self.dissolved_inorganic_pool.storage["P"] * proportion,
            }
        )

        # Extract from dissolved organic pool
        reply_do = self.dissolved_organic_pool.extract(
            {
                "N": self.dissolved_organic_pool.storage["N"] * proportion,
                "P": self.dissolved_organic_pool.storage["P"] * proportion,
            }
        )
        return {"organic": reply_do, "inorganic": reply_di}

    def get_erodable_P(self):
        """Return total phosphorus that can be eroded (i.e., humus and adsorbed
        inorganic pools).

        Returns:
            (float): total phosphorus
        """
        return self.adsorbed_inorganic_pool.storage["P"] + self.humus_pool.storage["P"]

    def erode_P(self, amount_P):
        """Update humus and adsorbed inorganic pools to erode some amount. Removed in
        proportion to amount in both pools.

        Args:
            amount_P (float): Amount of phosphorus to be eroded

        Returns:
            (float): Amount of phosphorus eroded from the humus pool (float): Amount of
            phosphorus eroded from the adsorbed inorganic pool
        """
        # Calculate proportion of adsorbed to be eroded
        fraction_adsorbed = self.adsorbed_inorganic_pool.storage["P"] / (
            self.adsorbed_inorganic_pool.storage["P"] + self.humus_pool.storage["P"]
        )

        # Update nutrients in a dict holder
        request = self.get_empty_nutrient()

        # Update inorganic pool
        request["P"] = amount_P * fraction_adsorbed
        reply_adsorbed = self.adsorbed_inorganic_pool.extract(request)

        # Update humus pool
        request["P"] = amount_P * (1 - fraction_adsorbed)
        reply_humus = self.humus_pool.extract(request)

        return reply_humus["P"], reply_adsorbed["P"]

    def soil_pool_transformation(self):
        """Function to be called by a GrowingSurface that performs and tracks changes
        resulting from soil transformation processes.

        Returns:
            (float): increase in dissolved inorganic nutrients resulting from
                transformations (negative value indicates a decrease)
            (float): increase in dissolved organic nutrients resulting from
                transformations (negative value indicates a decrease)
        """
        # For mass balance purposes, assume fast is inorganic and humus is organic

        # Initialise tracking
        increase_in_dissolved_inorganic = self.get_empty_nutrient()
        increase_in_dissolved_organic = self.get_empty_nutrient()

        # Turnover of humus
        amount = self.temp_soil_process(self.degrhpar, self.humus_pool, self.fast_pool)
        # This is solid inorganic to solid organic... no tracking needed since solid
        # nutrients aren't tracked in mass balance of the surface soil water tank!

        # Dissolution of humus
        amount = self.temp_soil_process(
            self.dishpar, self.humus_pool, self.dissolved_organic_pool
        )
        increase_in_dissolved_organic = self.sum_nutrients(
            increase_in_dissolved_organic, amount
        )

        # Turnover of fast
        amount = self.temp_soil_process(
            self.minfpar, self.fast_pool, self.dissolved_inorganic_pool
        )
        increase_in_dissolved_inorganic = self.sum_nutrients(
            increase_in_dissolved_inorganic, amount
        )

        # Dissolution of fast
        amount = self.temp_soil_process(
            self.disfpar, self.fast_pool, self.dissolved_organic_pool
        )
        increase_in_dissolved_organic = self.sum_nutrients(
            increase_in_dissolved_organic, amount
        )

        # Immobilisation
        amount = self.temp_soil_process(
            self.immobdpar, self.dissolved_inorganic_pool, self.fast_pool
        )
        increase_in_dissolved_inorganic = self.subtract_nutrients(
            increase_in_dissolved_inorganic, amount
        )  # TODO will a negative value affect the consequent processes in growing
        # surface?

        return increase_in_dissolved_inorganic, increase_in_dissolved_organic

    def temp_soil_process(self, parameter, extract_pool, receive_pool):
        """Temperature function to take a parameter, calculate transformation, and
        remove nutrients from the extract pool and update the receive pool.

        Args:
            parameter (dict): A dict containing a parameter for each nutrient for the
            given process
                (units in per timestep)
            extract_pool (NutrientStore): The pool to extract from receive_pool
            (NutrientStore): The pool to receive extracted nutrients

        Returns:
            to_extract (dict): A dict containing the amount extracted of each nutrient
            (for mass
                balance)
        """
        # Initialise nutrients
        to_extract = self.get_empty_nutrient()
        for nutrient in constants.NUTRIENTS:
            # Calculate
            to_extract[nutrient] = (
                parameter[nutrient]
                * self.temperature_dependence_factor
                * self.soil_moisture_dependence_factor
                * extract_pool.storage[nutrient]
            )
        # Update pools
        to_extract = extract_pool.extract(to_extract)
        receive_pool.receive(to_extract)
        return to_extract

    def get_empty_nutrient(self):
        """An efficient way to get an empty nutrient.

        Returns:
            (dict): A dict containing 0 for each nutrient
        """
        return self.empty_nutrient.copy()

    def multiply_nutrients(self, nutrient, factor):
        """Multiply nutrients by factors.

        Args:
            nutrient (dict): Dict of nutrients to multiply factor (dict): Dict of
            factors to multiply for each nutrient

        Returns:
            (dict): Multiplied nutrients
        """
        return {x: nutrient[x] * factor[x] for x in constants.NUTRIENTS}

    def receive(self, nutrients):
        """Update nutrient store by amounts.

        Args:
            nutrients (dict): Amount of nutrients to update store by
        """
        # Increase storage
        for nutrient, amount in nutrients.items():
            self.storage[nutrient] += amount

    def sum_nutrients(self, n1, n2):
        """Sum two nutrients.

        Args:
            n1 (dict): Dict of nutrients n2 (dict): Dict of nutrients

        Returns:
            (dict): Summed nutrients
        """
        reply = self.get_empty_nutrient()
        for nutrient in constants.NUTRIENTS:
            reply[nutrient] = n1[nutrient] + n2[nutrient]
        return reply

    def subtract_nutrients(self, n1, n2):
        """Subtract two nutrients.

        Args:
            n1 (dict): Dict of nutrients to subtract from n2 (dict): Dict of nutrients
            to subtract

        Returns:
            (dict): subtracted nutrients
        """
        reply = self.get_empty_nutrient()
        for nutrient in constants.NUTRIENTS:
            reply[nutrient] = n1[nutrient] - n2[nutrient]
        return reply

    def extract(self, nutrients):
        """Remove nutrients from a store.

        Args:
            nutrients (dict): Dict of nutrients to remove from store

        Returns:
            (dict): amount of nutrients successfully removed
        """
        reply = self.get_empty_nutrient()
        for nutrient, amount in nutrients.items():
            reply[nutrient] = min(self.storage[nutrient], amount)
            self.storage[nutrient] -= reply[nutrient]

        return reply

__init__(fraction_dry_n_to_dissolved_inorganic=0.9, degrhpar={'N': 7 * 1e-05, 'P': 7 * 1e-06}, dishpar={'N': 7 * 1e-05, 'P': 7 * 1e-06}, minfpar={'N': 0.00013, 'P': 3e-06}, disfpar={'N': 3e-06, 'P': 1e-07}, immobdpar={'N': 0.0056, 'P': 0.2866}, fraction_manure_to_dissolved_inorganic={'N': 0.5, 'P': 0.1}, fraction_residue_to_fast={'N': 0.1, 'P': 0.1})

A class to track nutrient pools in a soil tank, intended to be initialised and called by GrowingSurfaces (see wsimod/nodes/land.py/GrowingSurface) and their subclasses. Contains five pools, which have a storage that tracks the mass of nutrients. Equations and parameters are based on HYPE.

Parameters:

Name	Type	Description	Default
fraction_dry_n_to_dissolved_inorganic	float	fraction of dry	0.9
optional)		reference humus degradation rate (fraction of humus pool to fast	required
pool).	Defaults to {'N'	7 * 1e-5, 'P' : 7 * 1e-6}. dishpar (dict,	required
optional)		reference humus dissolution rate (fraction of humus pool to	required
dissolved	organic pool). Defaults to {'N'	7 * 1e-5, 'P' : 7 * 1e-6}.	required
minfpar	dict	reference fast pool mineralisation rate (fraction	{'N': 0.00013, 'P': 3e-06}
of	fast pool to dissolved inorganic pool). Defaults to {'N'	0.00013, 'P' :	required
0.000003}.	disfpar (dict	reference fast pool dissolution rate	required
(fraction	of fast pool to dissolved organic pool). Defaults to {'N'		required
0.000003,	P	0.0000001}. immobdpar (dict, optional): reference	required
Defaults	to {'N'	0.0056, 'P' : 0.2866}.	required
fraction_manure_to_dissolved_inorganic	dict	fraction of	{'N': 0.5, 'P': 0.1}
added	to the fast pool. Defaults to {'N'	0.5, 'P' : 0.1}.	required
fraction_residue_to_fast	dict	fraction of nutrients from	{'N': 0.1, 'P': 0.1}
{'N'		0.1, 'P' : 0.1}.	required

Key assumptions

• Four nutrient pools are conceptualised for both nitrogen and phosphorus in soil, which includes humus pool, fast pool, dissolved inorganic pool, and dissolved organic pool. Humus and fast pool represent immobile pool of organic nutrients in the soil with slow and fast turnover, respectively. Dissolved inorganic and organic pool represent nutrients in dissolved phase in soil water (for phosphorus, dissolved organic pool might contain particulate phase). Given that phoshphorus can be adsorbed and attached to soil particles, an adsorbed inorganic pool is created specifically for phosphorus.
• The major sources of nutrients to soil are conceptualised as
• atmospheric deposition:
  • dry deposition:
    • for nitrogen, inorganic fraction of dry deposition is added to the dissovled inorganic pool, while the rest is added to the fast pool;
    • for phosphorus, all is added to adsorbed inorganic pool.
  • wet deposition: all is added to the dissolved inorganic pool.
• fertilisers: all added to the dissolved inorganic pool.
• manure: the inorganic fraction is added to the dissovled inorganic pool, with the rest added to the fast pool.
• residue: the part with fast turnover is added to the fast pool, with the rest added to the humus pool.
• Nutrient fluxes between these pools are simulated to represent the biochemical processes that can transform the nutrients between different forms. These processes include - degradation of humus pool to fast pool - dissolution of humus pool to dissovled organic pool - mineralisation of fast pool to dissolved inorganic pool - dissolution of fast pool to dissolved organic pool - immobilisation of dissolved inroganic pool to fast pool The rate of these processes are affected by the soil temperature and moisture conditions.
• When soil erosion happens, a portion of both the adsorbed inorganic pool and humus pool for phosphorus will be eroded as well.

Input data and parameter requirements

• fraction_dry_n_to_dissolved_inorganic, fraction_manure_to_dissolved_inorganic, fraction_residue_to_fast. Units: -, all should in [0-1]
• degrhpar, dishpar, minfpar, disfpar, immobdpar. Units: -, all should in [0-1]

Source code in wsimod\nodes\nutrient_pool.py

def __init__(
    self,
    fraction_dry_n_to_dissolved_inorganic=0.9,
    degrhpar={"N": 7 * 1e-5, "P": 7 * 1e-6},
    dishpar={"N": 7 * 1e-5, "P": 7 * 1e-6},
    minfpar={"N": 0.00013, "P": 0.000003},
    disfpar={"N": 0.000003, "P": 0.0000001},
    immobdpar={"N": 0.0056, "P": 0.2866},
    fraction_manure_to_dissolved_inorganic={"N": 0.5, "P": 0.1},
    fraction_residue_to_fast={"N": 0.1, "P": 0.1},
):
    """A class to track nutrient pools in a soil tank, intended to be initialised
    and called by GrowingSurfaces (see wsimod/nodes/land.py/GrowingSurface) and
    their subclasses. Contains five pools, which have a storage that tracks the mass
    of nutrients. Equations and parameters are based on HYPE.

    Args:
        fraction_dry_n_to_dissolved_inorganic (float, optional): fraction of dry
        nitrogen deposition going into the soil dissolved inorganic nitrogen pool,
        with the rest added to the fast pool. Defaults to 0.9. degrhpar (dict,
        optional): reference humus degradation rate (fraction of humus pool to fast
        pool). Defaults to {'N' : 7 * 1e-5, 'P' : 7 * 1e-6}. dishpar (dict,
        optional): reference humus dissolution rate (fraction of humus pool to
        dissolved organic pool). Defaults to {'N' : 7 * 1e-5, 'P' : 7 * 1e-6}.
        minfpar (dict, optional): reference fast pool mineralisation rate (fraction
        of fast pool to dissolved inorganic pool). Defaults to {'N' : 0.00013, 'P' :
        0.000003}. disfpar (dict, optional): reference fast pool dissolution rate
        (fraction of fast pool to dissolved organic pool). Defaults to {'N' :
        0.000003, 'P' : 0.0000001}. immobdpar (dict, optional): reference
        immobilisation rate (fraction of dissolved inorganic pool to fast pool).
        Defaults to {'N' : 0.0056, 'P' : 0.2866}.
        fraction_manure_to_dissolved_inorganic (dict, optional): fraction of
        nutrients from applied manure to dissolved inorganic pool, with the rest
        added to the fast pool. Defaults to {'N' : 0.5, 'P' : 0.1}.
        fraction_residue_to_fast (dict, optional): fraction of nutrients from
        residue to fast pool, with the rest added to the humus pool. Defaults to
        {'N' : 0.1, 'P' : 0.1}.

    Key assumptions:
         - Four nutrient pools are conceptualised for both nitrogen and phosphorus
            in soil, which includes humus pool, fast pool, dissolved inorganic pool,
            and dissolved organic pool. Humus and fast pool represent immobile pool
            of organic nutrients in the soil with slow and fast turnover,
            respectively. Dissolved inorganic and organic pool represent nutrients
            in dissolved phase in soil water (for phosphorus, dissolved organic pool
            might contain particulate phase). Given that phoshphorus can be adsorbed
            and attached to soil particles, an adsorbed inorganic pool is created
            specifically for phosphorus.
         - The major sources of nutrients to soil are conceptualised as
            - atmospheric deposition:
                - dry deposition:
                    - for nitrogen, inorganic fraction of dry deposition is added to
                      the dissovled
                       inorganic pool, while the rest is added to the fast pool;
                    - for phosphorus, all is added to adsorbed inorganic pool.
                - wet deposition: all is added to the dissolved inorganic pool.
            - fertilisers: all added to the dissolved inorganic pool.
            - manure: the inorganic fraction is added to the dissovled inorganic
              pool, with
                the rest added to the fast pool.
            - residue: the part with fast turnover is added to the fast pool, with
              the rest
                added to the humus pool.
         - Nutrient fluxes between these pools are simulated to represent the
           biochemical processes
            that can transform the nutrients between different forms. These
            processes include - degradation of humus pool to fast pool - dissolution
            of humus pool to dissovled organic pool - mineralisation of fast pool to
            dissolved inorganic pool - dissolution of fast pool to dissolved organic
            pool - immobilisation of dissolved inroganic pool to fast pool The rate
            of these processes are affected by the soil temperature and moisture
            conditions.
         - When soil erosion happens, a portion of both the adsorbed inorganic pool
           and humus pool
            for phosphorus will be eroded as well.

    Input data and parameter requirements:
         - fraction_dry_n_to_dissolved_inorganic,
           fraction_manure_to_dissolved_inorganic, fraction_residue_to_fast.
            _Units_: -, all should in [0-1]
         - degrhpar, dishpar, minfpar, disfpar, immobdpar.
            _Units_: -, all should in [0-1]
    """
    # TODO I don't think anyone will change most of these params... they could maybe
    # just be set here
    self.init_empty()

    # Assign parameters
    self.temperature_dependence_factor = 0
    self.soil_moisture_dependence_factor = 0

    self.fraction_manure_to_dissolved_inorganic = (
        fraction_manure_to_dissolved_inorganic
    )
    self.fraction_residue_to_fast = fraction_residue_to_fast
    self.fraction_dry_n_to_dissolved_inorganic = (
        fraction_dry_n_to_dissolved_inorganic
    )

    self.degrhpar = degrhpar
    self.dishpar = dishpar
    self.minfpar = minfpar
    self.disfpar = disfpar
    self.immobdpar = immobdpar

    self.fraction_manure_to_fast = None
    self.fraction_residue_to_humus = None
    self.fraction_dry_n_to_fast = None
    self.calculate_fraction_parameters()

    # Initialise different pools
    self.fast_pool = NutrientStore()
    self.humus_pool = NutrientStore()
    self.dissolved_inorganic_pool = NutrientStore()
    self.dissolved_organic_pool = NutrientStore()
    self.adsorbed_inorganic_pool = NutrientStore()
    self.pools = [
        self.fast_pool,
        self.humus_pool,
        self.dissolved_inorganic_pool,
        self.dissolved_organic_pool,
        self.adsorbed_inorganic_pool,
    ]

allocate_dry_deposition(deposition)

Assign dry deposition, which is assumed to go to both dissolved inorganic pool and fast pool (nitrogen) and the adsorbed pool (phosphorus).

Parameters:

Name	Type	Description	Default
deposition	dict	A dict that contains the amount of nutrients entering the nutrient pool via dry deposition	required

Returns:

Type	Description
dict	A dict describing the amount of nutrients that enter the nutrient pool in a dissolved form (and thus need to be tracked by the soil water tank)

Source code in wsimod\nodes\nutrient_pool.py

def allocate_dry_deposition(self, deposition):
    """Assign dry deposition, which is assumed to go to both dissolved inorganic
    pool and fast pool (nitrogen) and the adsorbed pool (phosphorus).

    Args:
        deposition (dict): A dict that contains the amount of nutrients entering
            the nutrient pool via dry deposition

    Returns:
        (dict): A dict describing the amount of nutrients that enter the nutrient
            pool in a dissolved form (and thus need to be tracked by the soil water
            tank)
    """
    # Update pools
    self.fast_pool.storage["N"] += deposition["N"] * self.fraction_dry_n_to_fast
    self.dissolved_inorganic_pool.storage["N"] += (
        deposition["N"] * self.fraction_dry_n_to_dissolved_inorganic
    )
    self.adsorbed_inorganic_pool.storage["P"] += deposition["P"]
    return {
        "N": deposition["N"] * self.fraction_dry_n_to_dissolved_inorganic,
        "P": 0,
    }

allocate_fertiliser(fertiliser)

Assign fertiliser, which is assumed to contain dissolved inorganic nutrients and thus updates that pool.

Parameters:

Name	Type	Description	Default
fertiliser	dict	A dict that contains the amount of nutrients entering the nutrient pool via fertiliser	required

Returns:

Name	Type	Description
fertiliser	dict	fertiliser above, because no transformations take place (i.e., dissolved inorganic is what is received and goes straight into that pool)

Source code in wsimod\nodes\nutrient_pool.py

def allocate_fertiliser(self, fertiliser):
    """Assign fertiliser, which is assumed to contain dissolved inorganic nutrients
    and thus updates that pool.

    Args:
        fertiliser (dict): A dict that contains the amount of nutrients entering
            the nutrient pool via fertiliser

    Returns:
        fertiliser (dict): fertiliser above, because no transformations take place
            (i.e., dissolved inorganic is what is received and goes straight into
            that pool)
    """
    self.dissolved_inorganic_pool.receive(fertiliser)
    return fertiliser

allocate_inorganic_irrigation(irrigation)

Assign inorganic irrigation, which is assumed to contain dissolved inorganic nutrients and thus updates that pool.

Parameters:

Name	Type	Description	Default
irrigation	dict	A dict that contains the amount of nutrients entering the nutrient pool via irrigation	required

Returns:

Name	Type	Description
irrigation	dict	irrigation above, because no transformations take place (i.e., dissolved inorganic is what is received and goes straight into that pool)

Source code in wsimod\nodes\nutrient_pool.py

def allocate_inorganic_irrigation(self, irrigation):
    """Assign inorganic irrigation, which is assumed to contain dissolved inorganic
    nutrients and thus updates that pool.

    Args:
        irrigation (dict): A dict that contains the amount of nutrients entering
            the nutrient pool via irrigation

    Returns:
        irrigation (dict): irrigation above, because no transformations take place
            (i.e., dissolved inorganic is what is received and goes straight into
            that pool)
    """
    # Update pool
    self.dissolved_inorganic_pool.receive(irrigation)
    return irrigation

allocate_manure(manure)

Assign manure, which is assumed to go to both dissolved inorganic pool and fast pool.

Parameters:

Name	Type	Description	Default
manure	dict	A dict that contains the amount of nutrients entering the nutrient pool via manure	required

Returns:

Type	Description
dict	A dict describing the amount of nutrients that enter the nutrient pool in a dissolved form (and thus need to be tracked by the soil water tank)

Source code in wsimod\nodes\nutrient_pool.py

def allocate_manure(self, manure):
    """Assign manure, which is assumed to go to both dissolved inorganic pool and
    fast pool.

    Args:
        manure (dict): A dict that contains the amount of nutrients entering
            the nutrient pool via manure

    Returns:
        (dict): A dict describing the amount of nutrients that enter the nutrient
            pool in a dissolved form (and thus need to be tracked by the soil water
            tank)
    """
    # Assign a proportion of nutrients to the dissolved inorganic pool
    self.dissolved_inorganic_pool.receive(
        self.multiply_nutrients(manure, self.fraction_manure_to_dissolved_inorganic)
    )
    # Assign a proportion of nutrients to the fast pool
    self.fast_pool.receive(
        self.multiply_nutrients(manure, self.fraction_manure_to_fast)
    )
    return self.multiply_nutrients(
        manure, self.fraction_manure_to_dissolved_inorganic
    )

allocate_organic_irrigation(irrigation)

Assign organic irrigation, which is assumed to contain dissolved organic nutrients and thus updates that pool.

Parameters:

Name	Type	Description	Default
irrigation	dict	A dict that contains the amount of nutrients entering the nutrient pool via irrigation	required

Returns:

Name	Type	Description
irrigation	dict	irrigation above, because no transformations take place (i.e., dissolved organic is what is received and goes straight into that pool)

Source code in wsimod\nodes\nutrient_pool.py

def allocate_organic_irrigation(self, irrigation):
    """Assign organic irrigation, which is assumed to contain dissolved organic
    nutrients and thus updates that pool.

    Args:
        irrigation (dict): A dict that contains the amount of nutrients entering
            the nutrient pool via irrigation

    Returns:
        irrigation (dict): irrigation above, because no transformations take place
            (i.e., dissolved organic is what is received and goes straight into that
            pool)
    """
    # Update pool
    self.dissolved_organic_pool.receive(irrigation)
    return irrigation

allocate_residue(residue)

Assign residue, which is assumed to go to both humus pool and fast pool.

Parameters:

Name	Type	Description	Default
residue	dict	A dict that contains the amount of nutrients entering the nutrient pool via residue	required

Returns:

Type	Description
dict	A dict describing the amount of nutrients that enter the nutrient pool in a dissolved form (and thus need to be tracked by the soil water tank) - i.e., none because fast and humus pool are both solid

Source code in wsimod\nodes\nutrient_pool.py

def allocate_residue(self, residue):
    """Assign residue, which is assumed to go to both humus pool and fast pool.

    Args:
        residue (dict): A dict that contains the amount of nutrients entering
            the nutrient pool via residue

    Returns:
        (dict): A dict describing the amount of nutrients that enter the nutrient
            pool in a dissolved form (and thus need to be tracked by the soil water
            tank) - i.e., none because fast and humus pool are both solid
    """
    # Assign a proportion of nutrients to the humus pool
    self.humus_pool.receive(
        self.multiply_nutrients(residue, self.fraction_residue_to_humus)
    )
    # Assign a proportion of nutrients to the fast pool
    self.fast_pool.receive(
        self.multiply_nutrients(residue, self.fraction_residue_to_fast)
    )
    return self.empty_nutrient()

allocate_wet_deposition(deposition)

Assign wet deposition, which is assumed to contain dissolved inorganic nutrients and thus updates that pool.

Parameters:

Name	Type	Description	Default
deposition	dict	A dict that contains the amount of nutrients entering the nutrient pool via wet deposition	required

Returns:

Name	Type	Description
deposition	dict	deposition above, because no transformations take place (i.e., dissolved inorganic is what is received and goes straight into that pool)

Source code in wsimod\nodes\nutrient_pool.py

def allocate_wet_deposition(self, deposition):
    """Assign wet deposition, which is assumed to contain dissolved inorganic
    nutrients and thus updates that pool.

    Args:
        deposition (dict): A dict that contains the amount of nutrients entering
            the nutrient pool via wet deposition

    Returns:
        deposition (dict): deposition above, because no transformations take place
            (i.e., dissolved inorganic is what is received and goes straight into
            that pool)
    """
    # Update pool
    self.dissolved_inorganic_pool.receive(deposition)
    return deposition

apply_overrides(overrides=Dict[str, Any])

Override parameters.

Enables a user to override any of the following parameters: eto_to_e, pore_depth.

Parameters:

Name	Type	Description	Default
overrides	Dict[str, Any]	Dict describing which parameters should be overridden (keys) and new values (values). Defaults to {}.	Dict[str, Any]

Source code in wsimod\nodes\nutrient_pool.py

def apply_overrides(self, overrides=Dict[str, Any]):
    """Override parameters.

    Enables a user to override any of the following parameters:
    eto_to_e, pore_depth.

    Args:
        overrides (Dict[str, Any]): Dict describing which parameters should
            be overridden (keys) and new values (values). Defaults to {}.
    """
    self.fraction_dry_n_to_dissolved_inorganic = overrides.pop(
        "fraction_dry_n_to_dissolved_inorganic",
        self.fraction_dry_n_to_dissolved_inorganic,
    )
    self.fraction_residue_to_fast.update(
        overrides.pop("fraction_residue_to_fast", {})
    )
    self.fraction_manure_to_dissolved_inorganic.update(
        overrides.pop("fraction_manure_to_dissolved_inorganic", {})
    )
    self.degrhpar.update(overrides.pop("degrhpar", {}))
    self.dishpar.update(overrides.pop("dishpar", {}))
    self.minfpar.update(overrides.pop("minfpar", {}))
    self.disfpar.update(overrides.pop("disfpar", {}))
    self.immobdpar.update(overrides.pop("immobdpar", {}))

    self.calculate_fraction_parameters()

calculate_fraction_parameters()

Update fractions of nutrients input transformed into other forms in soil based on the input parameters Returns: (dict): fraction of manure to fast pool (dict): fraction of plant residue to humus pool (float): fraction of dry nitrogen deposition to fast pool

Source code in wsimod\nodes\nutrient_pool.py

def calculate_fraction_parameters(self):
    """Update fractions of nutrients input transformed into other forms in soil
    based on the input parameters
    Returns:
        (dict): fraction of manure to fast pool
        (dict): fraction of plant residue to humus pool
        (float): fraction of dry nitrogen deposition to fast pool
    """
    self.fraction_manure_to_fast = {
        x: 1 - self.fraction_manure_to_dissolved_inorganic[x]
        for x in constants.NUTRIENTS
    }
    self.fraction_residue_to_humus = {
        x: 1 - self.fraction_residue_to_fast[x] for x in constants.NUTRIENTS
    }
    self.fraction_dry_n_to_fast = 1 - self.fraction_dry_n_to_dissolved_inorganic

erode_P(amount_P)

Update humus and adsorbed inorganic pools to erode some amount. Removed in proportion to amount in both pools.

Parameters:

Name	Type	Description	Default
amount_P	float	Amount of phosphorus to be eroded	required

Returns:

Type	Description
float): Amount of phosphorus eroded from the humus pool (float	Amount of
	phosphorus eroded from the adsorbed inorganic pool

Source code in wsimod\nodes\nutrient_pool.py

def erode_P(self, amount_P):
    """Update humus and adsorbed inorganic pools to erode some amount. Removed in
    proportion to amount in both pools.

    Args:
        amount_P (float): Amount of phosphorus to be eroded

    Returns:
        (float): Amount of phosphorus eroded from the humus pool (float): Amount of
        phosphorus eroded from the adsorbed inorganic pool
    """
    # Calculate proportion of adsorbed to be eroded
    fraction_adsorbed = self.adsorbed_inorganic_pool.storage["P"] / (
        self.adsorbed_inorganic_pool.storage["P"] + self.humus_pool.storage["P"]
    )

    # Update nutrients in a dict holder
    request = self.get_empty_nutrient()

    # Update inorganic pool
    request["P"] = amount_P * fraction_adsorbed
    reply_adsorbed = self.adsorbed_inorganic_pool.extract(request)

    # Update humus pool
    request["P"] = amount_P * (1 - fraction_adsorbed)
    reply_humus = self.humus_pool.extract(request)

    return reply_humus["P"], reply_adsorbed["P"]

extract(nutrients)

Remove nutrients from a store.

Parameters:

Name	Type	Description	Default
nutrients	dict	Dict of nutrients to remove from store	required

Returns:

Type	Description
dict	amount of nutrients successfully removed

Source code in wsimod\nodes\nutrient_pool.py

def extract(self, nutrients):
    """Remove nutrients from a store.

    Args:
        nutrients (dict): Dict of nutrients to remove from store

    Returns:
        (dict): amount of nutrients successfully removed
    """
    reply = self.get_empty_nutrient()
    for nutrient, amount in nutrients.items():
        reply[nutrient] = min(self.storage[nutrient], amount)
        self.storage[nutrient] -= reply[nutrient]

    return reply

extract_dissolved(proportion)

Function to extract some amount of nutrients from all dissolved pools.

Parameters:

Name	Type	Description	Default
proportion	float	proportion of the dissolved nutrient pools to extract	required

Returns:

Type	Description
dict	A dict of dicts, where the top level distinguishes between organic and inorganic nutrients, and the bottom level describes how much nutrients (i.e., N and P) have been extracted from those pools

Source code in wsimod\nodes\nutrient_pool.py

def extract_dissolved(self, proportion):
    """Function to extract some amount of nutrients from all dissolved pools.

    Args:
        proportion (float): proportion of the dissolved nutrient pools to extract

    Returns:
        (dict): A dict of dicts, where the top level distinguishes between organic
            and inorganic nutrients, and the bottom level describes how much
            nutrients (i.e., N and P) have been extracted from those pools
    """
    # Extract from dissolved inorganic pool
    reply_di = self.dissolved_inorganic_pool.extract(
        {
            "N": self.dissolved_inorganic_pool.storage["N"] * proportion,
            "P": self.dissolved_inorganic_pool.storage["P"] * proportion,
        }
    )

    # Extract from dissolved organic pool
    reply_do = self.dissolved_organic_pool.extract(
        {
            "N": self.dissolved_organic_pool.storage["N"] * proportion,
            "P": self.dissolved_organic_pool.storage["P"] * proportion,
        }
    )
    return {"organic": reply_do, "inorganic": reply_di}

get_empty_nutrient()

An efficient way to get an empty nutrient.

Returns:

Type	Description
dict	A dict containing 0 for each nutrient

Source code in wsimod\nodes\nutrient_pool.py

def get_empty_nutrient(self):
    """An efficient way to get an empty nutrient.

    Returns:
        (dict): A dict containing 0 for each nutrient
    """
    return self.empty_nutrient.copy()

get_erodable_P()

Return total phosphorus that can be eroded (i.e., humus and adsorbed inorganic pools).

Returns:

Type	Description
float	total phosphorus

Source code in wsimod\nodes\nutrient_pool.py

def get_erodable_P(self):
    """Return total phosphorus that can be eroded (i.e., humus and adsorbed
    inorganic pools).

    Returns:
        (float): total phosphorus
    """
    return self.adsorbed_inorganic_pool.storage["P"] + self.humus_pool.storage["P"]

init_empty()

Initialise an empty nutrient to be copied.

Source code in wsimod\nodes\nutrient_pool.py

def init_empty(self):
    """Initialise an empty nutrient to be copied."""
    self.empty_nutrient = {x: 0 for x in constants.NUTRIENTS}

init_store()

Initialise an empty store to track nutrients.

Source code in wsimod\nodes\nutrient_pool.py

def init_store(self):
    """Initialise an empty store to track nutrients."""
    self.init_empty()
    self.storage = self.get_empty_nutrient()

multiply_nutrients(nutrient, factor)

Multiply nutrients by factors.

Parameters:

Name	Type	Description	Default
nutrient	dict	Dict of nutrients to multiply factor (dict): Dict of	required

Returns:

Type	Description
dict	Multiplied nutrients

Source code in wsimod\nodes\nutrient_pool.py

def multiply_nutrients(self, nutrient, factor):
    """Multiply nutrients by factors.

    Args:
        nutrient (dict): Dict of nutrients to multiply factor (dict): Dict of
        factors to multiply for each nutrient

    Returns:
        (dict): Multiplied nutrients
    """
    return {x: nutrient[x] * factor[x] for x in constants.NUTRIENTS}

receive(nutrients)

Update nutrient store by amounts.

Parameters:

Name	Type	Description	Default
nutrients	dict	Amount of nutrients to update store by	required

Source code in wsimod\nodes\nutrient_pool.py

def receive(self, nutrients):
    """Update nutrient store by amounts.

    Args:
        nutrients (dict): Amount of nutrients to update store by
    """
    # Increase storage
    for nutrient, amount in nutrients.items():
        self.storage[nutrient] += amount

soil_pool_transformation()

Function to be called by a GrowingSurface that performs and tracks changes resulting from soil transformation processes.

Returns:

Type	Description
float	increase in dissolved inorganic nutrients resulting from transformations (negative value indicates a decrease)
float	increase in dissolved organic nutrients resulting from transformations (negative value indicates a decrease)

Source code in wsimod\nodes\nutrient_pool.py

def soil_pool_transformation(self):
    """Function to be called by a GrowingSurface that performs and tracks changes
    resulting from soil transformation processes.

    Returns:
        (float): increase in dissolved inorganic nutrients resulting from
            transformations (negative value indicates a decrease)
        (float): increase in dissolved organic nutrients resulting from
            transformations (negative value indicates a decrease)
    """
    # For mass balance purposes, assume fast is inorganic and humus is organic

    # Initialise tracking
    increase_in_dissolved_inorganic = self.get_empty_nutrient()
    increase_in_dissolved_organic = self.get_empty_nutrient()

    # Turnover of humus
    amount = self.temp_soil_process(self.degrhpar, self.humus_pool, self.fast_pool)
    # This is solid inorganic to solid organic... no tracking needed since solid
    # nutrients aren't tracked in mass balance of the surface soil water tank!

    # Dissolution of humus
    amount = self.temp_soil_process(
        self.dishpar, self.humus_pool, self.dissolved_organic_pool
    )
    increase_in_dissolved_organic = self.sum_nutrients(
        increase_in_dissolved_organic, amount
    )

    # Turnover of fast
    amount = self.temp_soil_process(
        self.minfpar, self.fast_pool, self.dissolved_inorganic_pool
    )
    increase_in_dissolved_inorganic = self.sum_nutrients(
        increase_in_dissolved_inorganic, amount
    )

    # Dissolution of fast
    amount = self.temp_soil_process(
        self.disfpar, self.fast_pool, self.dissolved_organic_pool
    )
    increase_in_dissolved_organic = self.sum_nutrients(
        increase_in_dissolved_organic, amount
    )

    # Immobilisation
    amount = self.temp_soil_process(
        self.immobdpar, self.dissolved_inorganic_pool, self.fast_pool
    )
    increase_in_dissolved_inorganic = self.subtract_nutrients(
        increase_in_dissolved_inorganic, amount
    )  # TODO will a negative value affect the consequent processes in growing
    # surface?

    return increase_in_dissolved_inorganic, increase_in_dissolved_organic

subtract_nutrients(n1, n2)

Subtract two nutrients.

Parameters:

Name	Type	Description	Default
n1	dict	Dict of nutrients to subtract from n2 (dict): Dict of nutrients	required

Returns:

Type	Description
dict	subtracted nutrients

Source code in wsimod\nodes\nutrient_pool.py

def subtract_nutrients(self, n1, n2):
    """Subtract two nutrients.

    Args:
        n1 (dict): Dict of nutrients to subtract from n2 (dict): Dict of nutrients
        to subtract

    Returns:
        (dict): subtracted nutrients
    """
    reply = self.get_empty_nutrient()
    for nutrient in constants.NUTRIENTS:
        reply[nutrient] = n1[nutrient] - n2[nutrient]
    return reply

sum_nutrients(n1, n2)

Sum two nutrients.

Parameters:

Name	Type	Description	Default
n1	dict	Dict of nutrients n2 (dict): Dict of nutrients	required

Returns:

Type	Description
dict	Summed nutrients

Source code in wsimod\nodes\nutrient_pool.py

def sum_nutrients(self, n1, n2):
    """Sum two nutrients.

    Args:
        n1 (dict): Dict of nutrients n2 (dict): Dict of nutrients

    Returns:
        (dict): Summed nutrients
    """
    reply = self.get_empty_nutrient()
    for nutrient in constants.NUTRIENTS:
        reply[nutrient] = n1[nutrient] + n2[nutrient]
    return reply

temp_soil_process(parameter, extract_pool, receive_pool)

Temperature function to take a parameter, calculate transformation, and remove nutrients from the extract pool and update the receive pool.

Parameters:

Name	Type	Description	Default
parameter	dict	A dict containing a parameter for each nutrient for the	required
extract_pool	NutrientStore	The pool to extract from receive_pool	required
(NutrientStore)		The pool to receive extracted nutrients	required

Returns:

Name	Type	Description
to_extract	dict	A dict containing the amount extracted of each nutrient
		(for mass balance)

Source code in wsimod\nodes\nutrient_pool.py

def temp_soil_process(self, parameter, extract_pool, receive_pool):
    """Temperature function to take a parameter, calculate transformation, and
    remove nutrients from the extract pool and update the receive pool.

    Args:
        parameter (dict): A dict containing a parameter for each nutrient for the
        given process
            (units in per timestep)
        extract_pool (NutrientStore): The pool to extract from receive_pool
        (NutrientStore): The pool to receive extracted nutrients

    Returns:
        to_extract (dict): A dict containing the amount extracted of each nutrient
        (for mass
            balance)
    """
    # Initialise nutrients
    to_extract = self.get_empty_nutrient()
    for nutrient in constants.NUTRIENTS:
        # Calculate
        to_extract[nutrient] = (
            parameter[nutrient]
            * self.temperature_dependence_factor
            * self.soil_moisture_dependence_factor
            * extract_pool.storage[nutrient]
        )
    # Update pools
    to_extract = extract_pool.extract(to_extract)
    receive_pool.receive(to_extract)
    return to_extract

NutrientStore

Bases: NutrientPool

Source code in wsimod\nodes\nutrient_pool.py

class NutrientStore(NutrientPool):
    """"""

    def __init__(self):
        """Nutrient store, to be instantiated by a NutrientPool."""
        super().init_store()

__init__()

Nutrient store, to be instantiated by a NutrientPool.

Source code in wsimod\nodes\nutrient_pool.py

def __init__(self):
    """Nutrient store, to be instantiated by a NutrientPool."""
    super().init_store()