HydPy-W-GD (extended version of the WALRUS model with modified groundwater dynamics)

wland_gd is still under development and is likely to change in the future.

When applying wland_wag on the Kiel Catchment river basins, we realised some strengths and limitations of the WALRUS concept. First, wland_wag does not predict the high dynamics of the groundwater levels encountered at many groundwater gauges. This shortcoming is likely with an observed tendency to underestimate streamflow peaks. Second, wland_wag tends to run dry during summer conditions much too fast.

So far, wland_gd offers a physically based approach that increases groundwater dynamics. See the documentation on method Calc_GF_V1 for an in-depth explanation. The second problem seems to be related to a lack of “groundwater recharge areas” where groundwater is less exposed to evapotranspiration. We will address this later.

The following integration tests are identical to the ones of wland_wag, except that we set the additional parameter ThetaR to 0.01. Compare the base scenario example of wland_wag with the base scenario example of wland_gd to see how the differences between both models affect groundwater dynamics.

Integration tests

Note

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

>>> from hydpy import IntegrationTest, Element, pub, round_
>>> pub.timegrids = "2017-02-10", "2017-04-10", "1d"
>>> from hydpy.models.wland_gd import *
>>> parameterstep("1d")
>>> land = Element("land", outlets="outlet")
>>> land.model = model
>>> at(10.0)
>>> nu(4)
>>> lt(FIELD, CONIFER, SEALED, WATER)
>>> er(False)
>>> aur(0.6 * 0.98, 0.3 * 0.98, 0.1 * 0.98, 0.02)
>>> gl(1.5)
>>> bl(0.0)
>>> cp(0.8)
>>> lai.sealed = 10.0
>>> lai.conifer = 11.0
>>> lai.field = 0.4, 0.4, 0.3, 0.7, 3.0, 5.2, 4.6, 3.1, 1.3, 0.2, 0.0, 0.0
>>> ih(0.2)
>>> tt(0.0)
>>> ti(4.0)
>>> ddf(5.0)
>>> ddt(0.0)
>>> cw(400.0)
>>> cv(0.2)
>>> cg(200000.0)
>>> cgf(1.0)
>>> cq(0.5)
>>> b(soil=SANDY_LOAM)
>>> psiae(soil=SANDY_LOAM)
>>> thetas(soil=SANDY_LOAM)
>>> thetar(0.01)
>>> zeta1(0.02)
>>> zeta2(400.0)
>>> cwe(nan)
>>> cge(nan)
>>> ac(nan)
>>> sh(1.0)
>>> st(1.0)
>>> rg(False)
>>> with model.add_petmodel_v1("evap_pet_mlc"):
...     landmonthfactor.sealed = 0.7
...     landmonthfactor.conifer = 1.3
...     landmonthfactor.field[1:4] = 0.73, 0.77, 0.95
...     landmonthfactor.water[1:4] = 1.22, 1.26, 1.28
...     dampingfactor(1.0)
...     with model.add_retmodel_v1("evap_ret_io"):
...         evapotranspirationfactor(0.9)
>>> with model.add_dischargemodel_v2("wq_walrus"):
...     crestheight(0.0)
...     bankfulldischarge(8.0)
...     dischargeexponent(1.5)
>>> test = IntegrationTest(land)
>>> test.inits = (
...     (states.ic, (-3.0, -3.0, -3.0, 0.0)),
...     (states.sp, (-3.0, -3.0, -3.0, 0.0)),
...     (states.dve, 140.0),
...     (states.dv, 140.0),
...     (states.hge, 900.0),
...     (states.dg, 1600.0),
...     (states.hq, 0.0),
...     (states.hs, -2.0),
...     (model.petmodel.sequences.logs.loggedpotentialevapotranspiration, 0.0),
... )
>>> inputs.t.series = (
...     -2.8, -1.5, -0.9, -1.6, -1.3, 1.7, 4.4, 4.5, 3.4, 4.8, 6.7, 5.8, 6.5, 5.0, 3.0,
...     3.1, 7.1, 9.4, 4.6, 3.7, 4.7, 5.9, 7.7, 6.3, 3.7, 1.6, 4.0, 5.6, 5.8, 5.7, 4.6,
...     4.2, 7.4, 6.3, 8.7, 6.4, 5.2, 5.1, 8.7, 6.2, 5.9, 5.2, 5.2, 5.9, 6.7, 7.0, 8.3,
...     9.0, 12.4, 15.0, 11.8, 9.4, 8.1, 7.9, 7.5, 7.2, 8.1, 8.6, 10.5)
>>> inputs.p.series = (
...     0.0, 0.4, 0.0, 0.0, 0.0, 0.0, 0.2, 4.5, 0.0, 3.2, 4.6, 2.3, 18.0, 19.2, 0.4,
...     8.3, 5.3, 0.7, 2.7, 1.6, 2.5, 0.6, 0.2, 1.7, 0.3, 0.0, 1.8, 8.9, 0.0, 0.0,
...     0.0, 0.9, 0.1, 0.0, 0.0, 3.9, 8.7, 26.4, 11.5, 0.9, 0.0, 0.0, 0.0, 0.0, 0.0,
...     0.0, 0.0, 1.5, 0.3, 0.2, 4.5, 0.0, 0.0, 0.0, 0.4, 0.0, 0.0, 0.0, 0.0)
>>> model.petmodel.retmodel.sequences.inputs.referenceevapotranspiration.series = (
...     0.6, 0.8, 0.7, 0.4, 0.4, 0.4, 0.4, 0.3, 0.3, 0.4, 0.3, 0.6, 0.8, 0.5, 0.8,
...     0.5, 0.4, 1.3, 0.9, 0.7, 0.7, 1.1, 1.0, 0.8, 0.6, 0.7, 0.7, 0.5, 0.8, 1.0,
...     1.2, 0.9, 0.9, 1.2, 1.4, 1.1, 1.1, 0.5, 0.6, 1.5, 2.0, 1.6, 1.6, 1.2, 1.3,
...     1.6, 1.9, 0.8, 1.5, 2.7, 1.5, 1.6, 2.0, 2.1, 1.7, 1.7, 0.8, 1.3, 2.5)
>>> inputs.fxg.series = 0.0
>>> inputs.fxs.series = 0.0
>>> test.reset_inits()
>>> conditions = model.conditions

base scenario

>>> test("wland_gd_base_scenario",
...      axis1=(fluxes.pc, fluxes.fqs, fluxes.fgs, fluxes.rh),
...      axis2=(states.dg, states.hs))
Click to see the table
Click to see the graph
>>> round_(model.check_waterbalance(conditions))
0.0

seepage

>>> inputs.fxg.series = 10.0

>>> test("wland_gd_seepage",
...      axis1=(fluxes.pc, fluxes.fqs, fluxes.fgs, fluxes.rh),
...      axis2=(states.dg, states.hs))
Click to see the table
Click to see the graph
>>> round_(model.check_waterbalance(conditions))
0.0

surface water supply

>>> inputs.fxg.series =  0.0
>>> inputs.fxs.series = 10.0

>>> test("wland_gd_surface_water_supply",
...      axis1=(fluxes.pc, fluxes.fqs, fluxes.fgs, fluxes.rh),
...      axis2=(states.dg, states.hs))
Click to see the table
Click to see the graph
>>> round_(model.check_waterbalance(conditions))
0.0

elevated regions

>>> inputs.fxs.series = 0.0
>>> er(conifer=True, default=False)
>>> ac(100.0)
>>> cwe(400.0)
>>> cge(200000.0)

>>> test("wland_wag_elevated_regions",
...      axis1=(fluxes.pc, fluxes.fgse, fluxes.fgs),
...      axis2=(states.hge, states.dg))
Click to see the table
Click to see the graph
>>> round_(model.check_waterbalance(conditions))
0.0

snowfall

>>> er(False)
>>> inputs.t.series -= 8.0

>>> test("wland_gd_snowfall", axis1=(fluxes.pc, states.sp), axis2=(inputs.t,))
Click to see the table
Click to see the graph
>>> round_(model.check_waterbalance(conditions))
0.0

backwater effects

>>> del model.dischargemodel
>>> with model.add_waterlevelmodel_v1("exch_waterlevel"):
...     pass
>>> from hydpy import Node
>>> waterlevel = Node("waterlevel", variable="WaterLevel")
>>> land = Element("land", outlets="outlet", receivers=waterlevel)
>>> land.model.connect()
>>> test.hydpy.update_devices(nodes=("outlet", waterlevel), elements=land)
>>> waterlevel.prepare_simseries()
>>> waterlevel.deploymode = "oldsim"
>>> waterlevel.sequences.sim.series = [
...     -1.955539, -1.593272, -1.554112, -1.514237, -1.474332, -1.434671, -1.237946,
...     2.127124, 1.721998, 3.728419, 18.207013, 25.802253, 71.102022, 99.231277,
...     90.580027, 87.096102, 104.142108, 247.067521, 291.608204, 251.76909,
...     213.036118, 180.529412, 163.8984, 149.153668, 131.288692, 115.204072,
...     102.991454, 98.139161, 87.168564, 77.587424, 69.085831, 62.643619, 60.153237,
...     56.181454, 122.382442, 155.691919, 147.940892, 148.543172, 321.621321,
...     368.151976, 308.494631, 253.669569, 211.316972, 178.790605, 153.349539,
...     133.098674, 153.5539, 254.793577, 673.736602, 1281.108691, 1200.030141,
...     859.04159, 626.665696, 481.755443, 387.029438, 320.183349, 271.859287,
...     234.668462, 205.397587]
>>> waterlevel.sequences.sim.series /= 1000.0

>>> test("wland_gd_backwater_effects",
...      axis1=(fluxes.pc, states.sp), axis2=(inputs.t,))
Click to see the table
Click to see the graph
>>> round_(model.check_waterbalance(conditions))
0.0

>>> del model.waterlevelmodel
>>> with model.add_dischargemodel_v2("wq_walrus"):
...     crestheight(0.0)
...     bankfulldischarge(8.0)
...     dischargeexponent(1.5)

no vadose zone

>>> lt(SEALED, SEALED, SEALED, WATER)
>>> assert lt.value[0] != model.petmodel.parameters.control.hrutype.values[0]  # ToDo
>>> model.petmodel.prepare_zonetypes(lt.values)

>>> test("wland_gd_no_vadose_zone",
...      axis1=(fluxes.pc, fluxes.fqs, fluxes.fgs, fluxes.rh),
...      axis2=(states.dg, states.hs))
Click to see the table
Click to see the graph
>>> round_(model.check_waterbalance(conditions))
0.0

no land area

>>> nu(1)
>>> aur(1.0)
>>> lt(WATER)
>>> er(False)
>>> model.update_parameters()
>>> model.petmodel.parameters.control.dampingfactor(1.0)
>>> model.petmodel.retmodel.parameters.control.evapotranspirationfactor(0.9)
>>> test.inits.ic = 0.0
>>> test.inits.sp = 0.0
>>> test.reset_inits()
>>> conditions = model.conditions

>>> test("wland_gd_no_land_area",
...      axis1=(fluxes.pc, fluxes.et, fluxes.rh),
...      axis2=(states.hs,))
Click to see the table
Click to see the graph
>>> round_(model.check_waterbalance(conditions))
0.0
class hydpy.models.wland_gd.Model[source]

Bases: BaseModel, Main_PETModel_V1, Main_PETModel_V2, Main_DischargeModel_V2, Main_WaterLevelModel_V1, Sub_TempModel_V1, Sub_PrecipModel_V1, Sub_SnowCoverModel_V1

HydPy-W-GD (extended version of the WALRUS model with modified groundwater dynamics)

The following “receiver update methods” are called in the given sequence before performing a simulation step:
The following “inlet update methods” are called in the given sequence at the beginning of each simulation step:

  • Calc_PE_PET_V1 Let a submodel that complies with the PETModel_V1 or PETModel_V2 interface calculate the potential evapotranspiration of the land areas and the potential evaporation of the surface water storage.

  • Calc_FR_V1 Determine the fraction between rainfall and total precipitation.

  • Calc_PM_V1 Calculate the potential snowmelt of the land areas.

The following methods define the relevant components of a system of ODE equations (e.g. direct runoff):

  • Calc_FXS_V1 Query the current surface water supply/extraction.

  • Calc_FXG_V1 Query the current seepage/extraction.

  • Calc_PC_V1 Calculate the corrected precipitation.

  • Calc_TF_V1 Calculate the total amount of throughfall of the land areas.

  • Calc_EI_V1 Calculate the interception evaporation of the land areas.

  • Calc_RF_V1 Calculate the liquid amount of throughfall (rainfall) of the land areas.

  • Calc_SF_V1 Calculate the frozen amount of throughfall (snowfall) of the land areas.

  • Calc_AM_V1 Calculate the actual snowmelt of the land areas.

  • Calc_PS_V1 Calculate the precipitation entering the surface water reservoir.

  • Calc_WE_W_V1 Calculate the wetness index for the elevated and the lowland regions.

  • Calc_PVE_PV_V1 Calculate the rainfall (and snowmelt) entering the vadose zone in the elevated and lowland regions.

  • Calc_PQ_V1 Calculate the rainfall (and snowmelt) entering the quickflow reservoir.

  • Calc_BetaE_Beta_V1 Calculate the evapotranspiration reduction factor for the elevated and lowland regions.

  • Calc_ETVE_ETV_V1 Calculate the actual evapotranspiration from the elevated and lowland regions’ vadose zone.

  • Calc_ES_V1 Calculate the actual evaporation from the surface water reservoir.

  • Calc_GR_V1 Calculate the elevated region’s groundwater recharge.

  • Calc_FQS_V1 Calculate the quickflow.

  • Calc_FGSE_V1 Calculate the groundwater flow between the elevated and the lowland regions.

  • Calc_FGS_V1 Calculate the groundwater drainage or surface water infiltration.

  • Calc_RH_V1 Let a submodel that complies with the DischargeModel_V2 interface calculate the runoff height or, if no such submodel is available, equate it with all other flows in and out of the surface water storage.

  • Calc_DVEq_V3 Calculate the equilibrium storage deficit of the vadose zone.

  • Calc_DGEq_V1 Calculate the equilibrium groundwater depth.

  • Calc_GF_V1 Calculate the gain factor for changes in groundwater depth.

  • Calc_CDG_V2 Calculate the vadose zone’s storage deficit change due to percolation, capillary rise, macropore infiltration, seepage, groundwater flow, and channel water infiltration.

The following methods define the complete equations of an ODE system (e.g. change in storage of fast water due to effective precipitation and direct runoff):
The following “outlet update methods” are called in the given sequence at the end of each simulation step:

  • Calc_ET_V1 Calculate the total actual evapotranspiration.

  • Calc_R_V1 Calculate the runoff in m³/s.

  • Pass_R_V1 Update the outlet link sequence.

The following interface methods are available to main models using the defined model as a submodel:

  • Get_Temperature_V1 Get the current subbasin-wide air temperature value (that applies to all hydrological response units so that the given index does not matter).

  • Get_MeanTemperature_V1 Get the current subbasin-wide air temperature value.

  • Get_Precipitation_V1 Get the current subbasin-wide precipitation value (that applies to all hydrological response units so that the given index does not matter).

  • Get_SnowCover_V1 Get the selected response unit’s current snow cover degree.

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:

  • Calc_PE_PET_PETModel_V1 Let a submodel that complies with the PETModel_V1 interface calculate the potential evapotranspiration of the land areas and the potential evaporation of the surface water storage.

  • Calc_PE_PET_PETModel_V2 Let a submodel that complies with the PETModel_V2 interface calculate the potential interception evaporation and potential vadose zone evapotranspiration of the land areas and the potential evaporation of the surface water storage.

  • Return_DVH_V2 Return the storage deficit of the vadose zone at a specific height above the groundwater table.

  • Return_ErrorDV_V1 Calculate the difference between the equilibrium and the actual storage deficit of the vadose zone.

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.

  • PETModel_V2 Interface for calculating separate potential interception, soil, and water evapotranspiration values.

  • DischargeModel_V2 Simple interface for calculating discharge in mm/T based on the current water depth.

  • WaterLevelModel_V1 Pure getter interface for querying the current water level.

The following “submodels” might be called by one or more of the implemented methods or are meant to be directly called by the user:

  • PegasusDGEq Pegasus iterator for finding the equilibrium groundwater depth.

DOCNAME: DocName = ('W-GD', 'extended version of the WALRUS model with modified groundwater dynamics')
petmodel: modeltools.SubmodelProperty

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

dischargemodel: modeltools.SubmodelProperty

Required submodel that complies with the following interface: DischargeModel_V2.

waterlevelmodel: modeltools.SubmodelProperty

Required submodel that complies with the following interface: WaterLevelModel_V1.

REUSABLE_METHODS: ClassVar[tuple[type[ReusableMethod], ...]] = ()
numconsts: NumConstsELS
numvars: NumVarsELS
cymodel: CyModelProtocol | None
parameters: parametertools.Parameters
sequences: sequencetools.Sequences
masks: masktools.Masks
class hydpy.models.wland_gd.AideSequences(master: Sequences, cls_fastaccess: type[TypeFastAccess_co] | None = None, cymodel: CyModelProtocol | None = None)

Bases: AideSequences

Aide sequences of model wland_gd.

The following classes are selected:

  • FR() Fraction rainfall / total precipitation [-].

  • WE() Wetness index in the elevated region [-].

  • W() Wetness index in the lowland region [-].

  • BetaE() Evapotranspiration reduction factor in the elevated region [-].

  • Beta() Evapotranspiration reduction factor in the lowland region [-].

  • DVEq() Equilibrium storage deficit of the vadose zone for the actual groundwater depth [mm].

  • DGEq() Equilibrium groundwater depth for the actual storage deficit of the vadose zone [mm].

  • GF() Gain factor for changes in groundwater depth [-].

class hydpy.models.wland_gd.ControlParameters(master: Parameters, cls_fastaccess: type[FastAccessParameter] | None = None, cymodel: CyModelProtocol | None = None)

Bases: SubParameters

Control parameters of model wland_gd.

The following classes are selected:

  • AT() Total area [km²].

  • NU() Number of hydrological response units [-].

  • LT() Landuse type [-].

  • ER() Elevated region [-].

  • AUR() Relative area of each hydrological response unit [-].

  • GL() The lowland region’s average ground level [m].

  • BL() Channel bottom level [m].

  • CP() Factor for correcting precipitation [-].

  • LAI() Leaf area index [-].

  • IH() Interception capacity with respect to the leaf surface area [mm].

  • TT() Threshold temperature for snow/rain [°C].

  • TI() Temperature interval with a mixture of snow and rain [°C].

  • DDF() Day degree factor [mm/°C/T].

  • DDT() Day degree threshold temperature [°C].

  • CWE() Wetness index parameter for the elevated region [mm].

  • CW() Wetness index parameter for the lowland region [mm].

  • CV() Vadose zone relaxation time constant for the lowland region [T].

  • CGE() Groundwater reservoir constant for the elevated region [mm T].

  • CG() Groundwater reservoir constant for the lowland region [mm T].

  • RG() Groundwater reservoir restriction [-].

  • CGF() Groundwater reservoir flood factor [1/mm].

  • CQ() Quickflow reservoir relaxation time [T].

  • B() Pore size distribution parameter [-].

  • PsiAE() Air entry pressure [mm].

  • ThetaS() Soil moisture content at saturation [-].

  • ThetaR() Residual soil moisture deficit at tension saturation [-].

  • AC() Air capacity for the elevated region [mm].

  • Zeta1() Curvature parameter of the evapotranspiration reduction function [-].

  • Zeta2() Inflection point of the evapotranspiration reduction function [mm].

  • SH() General smoothing parameter related to the height of water columns [mm].

  • ST() General smoothing parameter related to temperature [°C].

class hydpy.models.wland_gd.DerivedParameters(master: Parameters, cls_fastaccess: type[FastAccessParameter] | None = None, cymodel: CyModelProtocol | None = None)

Bases: SubParameters

Derived parameters of model wland_gd.

The following classes are selected:

  • MOY() References the “global” month of the year index array [-].

  • NUL() Number of land-related hydrological response units [-].

  • NUGE() Number of groundwater-affected hydrological response units in the elevated region [-].

  • NUG() Number of groundwater-affected hydrological response units in the lowland region [-].

  • ALR() Relative land area [-].

  • ASR() Relative surface water area fraction [-].

  • AGRE() Relative groundwater area in the elevated region [-].

  • AGR() Relative groundwater area in the lowland region [-].

  • QF() Factor for converting mm/T to m³/s [T m³ / mm s].

  • CD() Channel depth [mm].

  • RH1() Regularisation parameter related to the height of water columns used when applying regularisation function smooth_logistic1() [mm].

  • RH2() Regularisation parameter related to the height of water columns used when applying regularisation function smooth_logistic2() [mm].

  • RT2() Regularisation parameter related to temperature for applying regularisation function smooth_logistic2()) [°C].

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

Bases: FactorSequences

Factor sequences of model wland_gd.

The following classes are selected:

  • DHS() External change of the surface water depth [mm/T].

class hydpy.models.wland_gd.FixedParameters(master: Parameters, cls_fastaccess: type[FastAccessParameter] | None = None, cymodel: CyModelProtocol | None = None)

Bases: SubParameters

Fixed parameters of model wland_gd.

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

Bases: FluxSequences

Flux sequences of model wland_gd.

The following classes are selected:

  • PC() Corrected precipitation [mm/T].

  • PE() Potential evaporation from the interception and the surface water storage [mm/T].

  • PET() Potential evapotranspiration from the vadose zone [mm/T].

  • TF() Total amount of throughfall [mm/T].

  • EI() Interception evaporation [mm/T].

  • RF() Rainfall (or, more concrete, the liquid amount of throughfall) [mm/T].

  • SF() Snowfall (or, more concrete, the frozen amount of throughfall) [mm/T].

  • PM() Potential snowmelt [mm/T].

  • AM() Actual snowmelt [mm/T].

  • PS() Precipitation that enters the surface water reservoir [mm/T].

  • PVE() Rainfall (and snowmelt) entering the vadose zone in the elevated region [mm/T].

  • PV() Rainfall (and snowmelt) entering the vadose zone in the lowland region [mm/T].

  • PQ() Rainfall (and snowmelt) entering the quickflow reservoir [mm/T].

  • ETVE() Actual evapotranspiration from the vadose zone in the elevated region [mm/T].

  • ETV() Actual evapotranspiration from the vadose zone in the lowland region [mm/T].

  • ES() Actual evaporation from the surface water [mm/T].

  • ET() Total actual evapotranspiration [mm/T].

  • GR() Groundwater recharge in the elevated region [mm/T].

  • FXS() Surface water supply/extraction (normalised to ASR) [mm/T].

  • FXG() Seepage/extraction (normalised to ALR) [mm/T].

  • CDG() Change in the groundwater depth due to percolation and capillary rise [mm/T].

  • FGSE() Groundwater flow between the elevated and the lowland region [mm/T].

  • FGS() Groundwater drainage/surface water infiltration [mm/T].

  • FQS() Quickflow [mm/T].

  • RH() Runoff height [mm/T].

  • R() Runoff [m³/s].

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

Bases: InputSequences

Input sequences of model wland_gd.

The following classes are selected:

  • T() Air temperature [°C].

  • P() Precipitation [mm/T].

  • FXG() Seepage/extraction (normalised to AT) [mm/T].

  • FXS() Surface water supply/extraction (normalised to AT) [mm/T].

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

Bases: OutletSequences

Outlet sequences of model wland_gd.

The following classes are selected:

  • Q() Discharge [m³/s].

class hydpy.models.wland_gd.SolverParameters(master: Parameters, cls_fastaccess: type[FastAccessParameter] | None = None, cymodel: CyModelProtocol | None = None)

Bases: SubParameters

Solver parameters of model wland_gd.

The following classes are selected:

  • AbsErrorMax() Absolute numerical error tolerance [mm/T].

  • RelErrorMax() Relative numerical error tolerance [-].

  • RelDTMin() Smallest relative integration time step size allowed [-].

  • RelDTMax() Largest relative integration time step size allowed [-].

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

Bases: StateSequences

State sequences of model wland_gd.

The following classes are selected:

  • IC() Interception storage [mm].

  • SP() Snow pack [mm].

  • DVE() Storage deficit of the vadose zone in the elevated region [mm].

  • DV() Storage deficit of the vadose zone in the lowland region [mm].

  • HGE() Groundwater level in the elevated region [mm].

  • DG() Groundwater depth in the lowland region [mm].

  • HQ() Level of the quickflow reservoir [mm].

  • HS() Surface water level [mm].