HydPy-Evap-AET-HBV96 (actual evapotranspiration after HBV96)

evap_aet_hbv96 serves as a submodel that supplies its main model with estimates of actual evapotranspiration from soils and actual evaporation from interception storages and water areas. Therefore, it requires potential evapotranspiration data calculated by a sub-submodel. If you long to emulate HBV96 (Lindström et al., 1997) as closely as possible, select evap_pet_hbv96.

Additionally, evap_aet_hbv96 requires information about the current air temperature, the initial water contents of the interception and soil storages, and the current degree of snow coverage. By default, evap_aet_hbv96 queries all these properties from its main model and, at least for the last three properties, this should be the desired behaviour in most cases as it fully synchronises the related states. However, the following tests use evap_aet_hbv96 as a stand-alone model. Hence, we need to connect additional submodels to it that provide pre-defined temperature, water content, and snow cover data.

Integration tests

Note

When new to HydPy, consider reading section Integration Tests first.

According to the intended usage as a submodel, evap_aet_hbv96 requires no connections to any nodes. Hence, assigning a model instance to a blank Element instance is sufficient:

>>> from hydpy import Element
>>> from hydpy.models.evap_aet_hbv96 import *
>>> parameterstep("1h")
>>> element = Element("element")
>>> element.model = model

We perform the integration test for two simulation steps. We will configure the first step identical to the first hour of the second day of the simulation period selected for the integration tests of hland_96:

>>> from hydpy import IntegrationTest, pub
>>> pub.timegrids = "2000-01-01", "2000-01-03", "1d"

We set all parameter values identical to the ones defined in the field example of hland_96:

>>> nmbhru(1)
>>> maxsoilwater(200.0)
>>> soilmoisturelimit(0.8)
>>> excessreduction(0.5)
>>> temperaturethresholdice(0.0)

We add submodels of type evap_ret_io, meteo_temp_io, dummy_interceptedwater, dummy_soilwater, and dummy_snowcover for providing pre-defined values of potential evapotranspiration (identical values for potential interception evaporation and soil evapotranspiration), air temperature, intercepted water, soil water, and snow cover:

>>> with model.add_petmodel_v1("evap_ret_io"):
...     hruarea(1.0)
...     evapotranspirationfactor(1.0)
>>> with model.add_tempmodel_v2("meteo_temp_io"):
...     hruarea(1.0)
...     temperatureaddend(0.0)
>>> with model.add_intercmodel_v1("dummy_interceptedwater"):
...     pass
>>> with model.add_soilwatermodel_v1("dummy_soilwater"):
...     pass
>>> with model.add_snowcovermodel_v1("dummy_snowcover"):
...     pass

Now, we can initialise an IntegrationTest object:

>>> test = IntegrationTest(element)
>>> test.dateformat = "%d/%m"

The first temperature input also stems from the input data of the field example, while the second represents winter conditions:

>>> model.tempmodel.sequences.inputs.temperature.series = 19.2, 0.0

The (constant) potential evapotranspiration value stems from the output of the integration test of evap_pet_hbv96, which is also consistent with the field example:

>>> model.petmodel.sequences.inputs.referenceevapotranspiration.series = 0.06896

The following interception and soil water contents are intermediate values of the field example that occur after adding precipitation but before removing evapotranspiration:

>>> model.intercmodel.sequences.inputs.interceptedwater.series = 2.0
>>> model.soilwatermodel.sequences.inputs.soilwater.series = 99.622389

The first snow cover value represents summer conditions (like in the field example), while the second represents winter conditions:

>>> model.snowcovermodel.sequences.inputs.snowcover.series = [[0.0], [1.0]]

vegetated soil

For “vegetated soils”, interception evaporation and soil evapotranspiration are relevant:

>>> interception(True)
>>> soil(True)
>>> water(False)

For the first hour, interception evaporation equals potential evapotranspiration, while soil evaporation is smaller due to restricted soil water availability and the priority of interception evaporation. In the second hour, the snow cover suppresses soil evapotranspiration but does not affect interception evaporation:

>>> test()
Click to see the table

bare soil

Next, we assume a “bare soil” where interception processes are irrelevant:

>>> interception(False)
>>> soil(True)
>>> water(False)

Unlike the vegetated soil, soil evapotranspiration is stronger in the first hour since interception evaporation does not “consume” any potential evapotranspiration:

>>> test()
Click to see the table

sealed soil

The following “sealed soil” can evaporate water from its surface but not from its body:

>>> interception(True)
>>> soil(False)
>>> water(False)

The results are consistent with those of the previous examples:

>>> test()
Click to see the table

water area

A “water area” comes neither with a solid surface nor a soil body:

>>> interception(False)
>>> soil(False)
>>> water(True)

In the first hour, the actual evaporation from the water area is identical to potential evapotranspiration. In the second hour, an assumed ice surface suppresses any evaporation:

>>> test()
Click to see the table

unequal potential values, soil

The previous examples relied on the evap_ret_io submodel, which complies with the PETModel_V1 interface that provides only a single potential evapotranspiration value per time step. evap_aet_hbv96 is also compatible with submodels that follow PETModel_V2, which offers separate potential values for interception evaporation, soil evapotranspiration, and evaporation from water areas. We use evap_pet_ambav1 to demonstrate this functionality:

>>> with model.add_petmodel_v2("evap_pet_ambav1"):
...     hrutype(0)
...     plant(True)
...     measuringheightwindspeed(10.0)
...     leafalbedo(0.2)
...     leafalbedosnow(0.8)
...     groundalbedo(0.2)
...     groundalbedosnow(0.8)
...     leafareaindex(5.0)
...     cropheight(1.0)
...     leafresistance(40.0)
...     wetsoilresistance(100.0)
...     soilresistanceincrease(1.0)
...     wetnessthreshold(0.5)
...     cloudtypefactor(0.2)
...     nightcloudfactor(1.0)
...     with model.add_tempmodel_v2("meteo_temp_io"):
...         hruarea(1.0)
...         temperatureaddend(0.0)
...     with model.add_precipmodel_v2("meteo_precip_io"):
...         hruarea(1.0)
...         precipitationfactor(1.0)
...     with model.add_radiationmodel_v4("meteo_psun_sun_glob_io"):
...         pass
...     with model.add_snowcovermodel_v1("dummy_snowcover"):
...         pass

After recreating the IntegrationTest object, we can define the time series and initial conditions required by evap_pet_ambav1:

>>> test = IntegrationTest(element)
>>> test.dateformat = "%d/%m"

>>> model.petmodel.sequences.inputs.windspeed.series = 2.0
>>> model.petmodel.sequences.inputs.relativehumidity.series = 80.0
>>> model.petmodel.sequences.inputs.atmosphericpressure.series = 1000.0
>>> model.petmodel.tempmodel.sequences.inputs.temperature.series = 19.2, 0.0
>>> model.petmodel.precipmodel.sequences.inputs.precipitation.series = 0.0
>>> model.petmodel.radiationmodel.sequences.inputs.sunshineduration.series = 6.0
>>> model.petmodel.radiationmodel.sequences.inputs.possiblesunshineduration.series = 16.0
>>> model.petmodel.radiationmodel.sequences.inputs.globalradiation.series = 190.0
>>> model.petmodel.snowcovermodel.sequences.inputs.snowcover.series = [[0.0], [1.0]]

>>> test.inits = (
...     (model.petmodel.sequences.states.soilresistance, 100.0),
...     (model.petmodel.sequences.logs.loggedprecipitation, [0.0]),
...     (model.petmodel.sequences.logs.loggedpotentialsoilevapotranspiration, [1.0])
... )

The time series of air temperature, intercepted water, soil water, and the snow cover degree correspond to the previous examples:

>>> model.tempmodel.sequences.inputs.temperature.series = 19.2, 0.0
>>> model.intercmodel.sequences.inputs.interceptedwater.series = 2.0
>>> model.soilwatermodel.sequences.inputs.soilwater.series = 99.622389
>>> model.snowcovermodel.sequences.inputs.snowcover.series = [[0.0], [1.0]]

The following results are comparable to the vegetated soil example:

>>> interception(True)
>>> soil(True)
>>> water(False)
>>> test()
Click to see the table

unequal potential values, water

For water areas, evap_aet_hbv96 takes the potential water evaporation calculated by evap_pet_ambav1 as actual water evaporation, as long as the occurrence of an ice surface does not suppress evaporation:

>>> interception(False)
>>> soil(False)
>>> water(True)
>>> test()
Click to see the table
class hydpy.models.evap_aet_hbv96.Model[source]

Bases: Main_TempModel_V1, Main_TempModel_V2B, Main_PET_PETModel_V1, Main_PET_PETModel_V2, Main_IntercModel_V1, Main_SoilWaterModel_V1, Main_SnowCoverModel_V1, Sub_ETModel, AETModel_V1

HydPy-Evap-AET-HBV96 (actual evapotranspiration after HBV96).

The following “run methods” are called in the given sequence during each simulation step:
The following interface methods are available to main models using the defined model as a submodel:
The following “additional methods” might be called by one or more of the other methods or are meant to be directly called by the user:
Users can hook submodels into the defined main model if they satisfy one of the following interfaces:

  • PETModel_V1 Simple interface for calculating all potential evapotranspiration values in one step.

DOCNAME: DocName = ('Evap-AET-HBV96', 'actual evapotranspiration after HBV96')
tempmodel: SubmodelProperty

Required submodel that complies with one of the following interfaces: TempModel_V1 or TempModel_V2.

petmodel: modeltools.SubmodelProperty

Required submodel that complies with one of the following interfaces: PETModel_V1 or PETModel_V2.

intercmodel: modeltools.SubmodelProperty

Required submodel that complies with the following interface: IntercModel_V1.

soilwatermodel: modeltools.SubmodelProperty

Required submodel that complies with the following interface: SoilWaterModel_V1.

snowcovermodel: modeltools.SubmodelProperty

Required submodel that complies with the following interface: SnowCoverModel_V1.

REUSABLE_METHODS: ClassVar[tuple[type[ReusableMethod], ...]] = ()
preparemethod2arguments: dict[str, tuple[tuple[Any, ...], dict[str, Any]]]
cymodel: CyModelProtocol | None
parameters: parametertools.Parameters
sequences: sequencetools.Sequences
masks: masktools.Masks
class hydpy.models.evap_aet_hbv96.ControlParameters(master: Parameters, cls_fastaccess: type[FastAccessParameter] | None = None, cymodel: CyModelProtocol | None = None)

Bases: SubParameters

Control parameters of model evap_aet_hbv96.

The following classes are selected:

  • NmbHRU() The number of separately modelled hydrological response units [-].

  • Water() A flag that indicates whether the individual zones are water areas or not.

  • Interception() A flag that indicates whether interception evaporation is relevant for the individual zones.

  • Soil() A flag that indicates whether soil evapotranspiration is relevant for the individual zones.

  • TemperatureThresholdIce() Temperature threshold for evaporation from water areas [°C].

  • MaxSoilWater() Maximum soil water content [mm].

  • SoilMoistureLimit() Relative soil moisture limit for potential evapotranspiration [-].

  • ExcessReduction() A factor for restricting actual to potential evapotranspiration [-].

class hydpy.models.evap_aet_hbv96.FactorSequences(master: Sequences, cls_fastaccess: type[TypeFastAccess_co] | None = None, cymodel: CyModelProtocol | None = None)

Bases: FactorSequences

Factor sequences of model evap_aet_hbv96.

The following classes are selected:
class hydpy.models.evap_aet_hbv96.FluxSequences(master: Sequences, cls_fastaccess: type[TypeFastAccess_co] | None = None, cymodel: CyModelProtocol | None = None)

Bases: FluxSequences

Flux sequences of model evap_aet_hbv96.

The following classes are selected: