HydPy-L-Knauf-Ic (adoption of LARSIM with Knauf-based snow modelling including snow interception)

lland_knauf_ic is still under development and likely to change in the future. Its goal is to extend lland_knauf with processes dealing with the interception of snow in canopies, similar to the SCHNEEINTERZEPTION option of LARSIM. The publically available LARSIM documentation does not provide all information required for implementing a perfect emulation, but detailed comparisons suggest that the essential process equations are defined similarly.

The following list summarises the current status of lland_knauf_ic by discussing its main differences to lland_knauf:

  • Snow interception occurs only in tree canopies, which is why the results of lland_knauf_ic differ from those of lland_knauf only for the land-use types LAUBW, MISCHW, and NADELW.

  • There is are two additional storages, SInz and STInz, which handle the total and the frozen amount of intercepted snowfall, placed between the “normal” interception and the “normal” snow module.

  • If not stated otherwise, SInz and STInz correspond to WAeS and WATS and are modified by the same or functionally identical methods.

  • If the LARSIM documentation does not suggest otherwise, we reuse the names of the “normal” snow module and suffix “Inz” to it or replace its “Snow” suffix (for example, WaDa becomes WaDaInz and NetRadiationSnow becomes NetRadiationInz).

  • Only a fraction of the water leaving the “normal” interception module reaches the snow interception module (see Calc_NBesInz_V1 and Calc_SnowIntRate_V1).

  • The surface temperature of the intercepted snow is always identical with its bulk temperature (TempSInz), except for the calculation of the latent heat flux (see Return_WSurfInz_V1).

  • The energy balance of the intercepted snow does not (need to) consider the soil heat flux.

  • The radiation exchange with the atmosphere depends on how much the intercepted snow shields the ground (see Calc_NetShortwaveRadiationInz_V1 and Return_NetLongwaveRadiationInz_V1).

  • During periods with intercepted snow, water evaporates (or sublimates) from the snow interception module (EvSInz) but not from the “normal” interception module (EvI).

LEG (2020) discusses many of these points in more detail.

In our experience, lland_knauf_ic tends to calculate thicker snowpacks on the ground than lland_knauf (the highest values of WAeS are usually larger when applying lland_knauf_ic). This counterintuitive behaviour seems to be related to disabling the “normal” interception evaporation (EvI) during snow interception periods and is still under discussion.

We will add further explanations and references as soon as we can consolidate lland_knauf_ic.

The following integration tests are identical to the ones of lland_knauf, except for the additional snow interception processes.

Integration tests

Note

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

daily simulation

>>> from hydpy import pub
>>> pub.timegrids = "1997-08-01", "1997-09-01", "1d"
>>> from hydpy.models.lland_knauf_ic import *
>>> parameterstep("1h")
>>> from hydpy import Node, Element
>>> outlet = Node("outlet")
>>> inlet = Node("inlet")
>>> land = Element("land", inlets=inlet, outlets=outlet)
>>> land.model = model
>>> nhru(1)
>>> ft(1.0)
>>> fhru(1.0)
>>> gh(100.0)

acre (summer)

>>> lnk(ACKER)
>>> kg(0.94)
>>> atg(-0.65)
>>> kt(0.0)
>>> hinz(0.2)
>>> lai.acker_aug = 3.5
>>> tgr(0.0)
>>> trefn(0.0)
>>> tsp(4.0)
>>> pwmax(1.43)
>>> wmax(309.0)
>>> fk(199.0)
>>> pwp(119.4)
>>> kapgrenz(option="0_WMax/10")
>>> kapmax(0.08)
>>> beta(0.001/24)
>>> fbeta(1.0)
>>> rbeta(False)
>>> dmax(r_dmax=0.55)
>>> dmin(r_dmin=10.0)
>>> bsf0(0.0)
>>> bsf(0.3)
>>> volbmax(inf)
>>> gsbmax(1.0)
>>> gsbgrad1(inf)
>>> gsbgrad2(inf)
>>> a1(0.0)
>>> a2(0.5)
>>> tind(0.191056)
>>> eqb(35000.0)
>>> eqi1(400.0)
>>> eqi2(400.0)
>>> eqd1(200.0)
>>> eqd2(50.0)

>>> negq(True)

>>> measuringheightwindspeed(10.0)
>>> wg2z.aug = -2.9
>>> p1strahl(0.5)
>>> p2strahl(1.0/35.0)
>>> p1wind(0.6)
>>> p2wind(1.0/70.0)
>>> turb0(2.0)
>>> turb1(1.6)
>>> albedo0snow(0.9)
>>> snowagingfactor(0.35)
>>> refreezeflag(True)
>>> ktschnee(inf)

>>> fvf(0.3)
>>> bsff(2.0)

>>> p1simax(8.0)
>>> p2simax(1.5)
>>> p1sirate(0.2)
>>> p2sirate(0.02)
>>> p3sirate(0.003)

>>> with model.add_radiationmodel_v4("meteo_psun_sun_glob_io") as submodel_meteo_psun_sun_glob_io:
...     pass

>>> with model.add_aetmodel_v1("evap_aet_morsim"):
...     albedo.acker_aug = 0.24
...     cropheight.acker_aug = 0.4
...     surfaceresistance.acker = 40.0
...     emissivity(0.95)
...     averagesoilheatflux.aug = 2.9
...     soilmoisturelimit(119.4 / 309.0)
...     model.add_radiationmodel_v4(submodel_meteo_psun_sun_glob_io)

>>> from hydpy import IntegrationTest
>>> IntegrationTest.plotting_options.axis1 = inputs.nied
>>> IntegrationTest.plotting_options.axis2 = fluxes.qah
>>> test = IntegrationTest(land)
>>> test.dateformat = "%Y-%d-%m"

>>> test.inits = ((states.inzp, 0.0),
...               (states.stinz, 0.0),
...               (states.sinz, 0.0),
...               (states.esnowinz, 0.0),
...               (states.asinz, 0.0),
...               (states.wats, 0.0),
...               (states.waes, 0.0),
...               (states.esnow, 0.0),
...               (states.taus, 0.0),
...               (states.ebdn, 350.0),
...               (states.bowa, 72.0),
...               (states.sdg1, 0.0),
...               (states.sdg2, 0.0),
...               (states.sig1, 0.0),
...               (states.sig2, 0.0),
...               (states.sbg, 0.0))

>>> inputs.nied.series = (
...     13.3, 0.1, 0.0, 0.1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.1, 0.0, 0.0, 2.7,
...     0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2.0, 0.3, 0.0, 0.1, 10.5, 6.5, 15.0, 9.2, 0.0,
...     0.0)
>>> inputs.teml.series = (
...     16.1, 17.3, 18.9, 17.8, 18.5, 19.9, 20.8, 20.9, 22.3, 23.0, 23.1, 23.2, 23.2,
...     21.7, 20.8, 19.5, 21.0, 21.6, 21.1, 22.4, 22.5, 19.6, 20.3, 24.1, 23.7, 21.1,
...     20.9, 20.2, 16.1, 17.0, 18.2)
>>> inputs.windspeed.series = (
...     2.4, 1.6, 1.5, 2.8, 3.0, 3.5, 3.8, 3.3, 1.8, 1.9, 3.0, 2.5, 1.6, 2.7, 3.2, 1.3,
...     1.9, 2.0, 2.6, 3.6, 2.5, 2.1, 1.5, 2.2, 1.9, 2.3, 2.1, 2.6, 2.6, 2.1, 2.1)
>>> inputs.relativehumidity.series = (
...     86.2, 85.8, 82.4, 77.6, 74.9, 77.9, 73.5, 80.1, 72.9, 68.5, 68.6, 66.0, 69.0,
...     75.6, 81.4, 79.0, 75.9, 70.0, 70.3, 69.0, 62.1, 84.5, 83.6, 76.5, 76.6, 84.2,
...     85.8, 86.5, 89.6, 78.3, 78.5)

>>> model.radiationmodel.sequences.inputs.sunshineduration.series = (
...     6.3, 1.7, 4.5, 12.4, 13.9, 13.0, 13.8, 12.3, 13.1, 12.8, 13.1, 13.3, 12.7,
...     10.2, 9.4, 10.3, 11.1, 11.0, 8.5, 11.3, 12.4, 0.1, 6.7, 10.4, 6.5, 4.9, 6.6,
...     0.3, 0.1, 5.0, 3.8)

>>> aetinputs = model.aetmodel.sequences.inputs
>>> aetinputs.atmosphericpressure.series = (
...     1007.0, 1013.0, 1016.0, 1017.0, 1018.0, 1018.0, 1019.0, 1019.0, 1019.0, 1020.0,
...     1021.0, 1022.0, 1019.0, 1015.0, 1016.0, 1019.0, 1019.0, 1018.0, 1019.0, 1019.0,
...     1017.0, 1015.0, 1015.0, 1011.0, 1008.0, 1006.0, 1005.0, 1000.0, 1004.0, 1011.0,
...     1014.0)
>>> aetinputs.windspeed.series = inputs.windspeed.series
>>> aetinputs.relativehumidity.series = inputs.relativehumidity.series

>>> inlet.sequences.sim.series = 0.0

>>> model.radiationmodel.sequences.inputs.possiblesunshineduration.series = (
...     15.69078473, 15.62882066, 15.56613383, 15.50275437, 15.43871163, 15.37403418,
...     15.3087498, 15.24288548, 15.17646742, 15.10952106, 15.04207104, 14.97414122,
...     14.90575471, 14.83693386, 14.76770029, 14.69807488, 14.62807779, 14.5577285,
...     14.48704578, 14.41604776, 14.34475191, 14.27317506, 14.20133345, 14.12924271,
...     14.05691791, 13.98437357, 13.91162366, 13.83868165, 13.76556053, 13.69227282,
...     13.61883057)
>>> model.radiationmodel.sequences.inputs.globalradiation.series = (
...     190.2514903, 127.6607822, 164.4012978, 269.0205016, 287.8486672, 274.6742631,
...     284.0478917, 262.9712633, 272.2564135, 267.0192178, 269.6265466, 270.8782909,
...     261.6971638, 227.9621155, 216.3563213, 226.6379036, 235.5285025, 232.8494284,
...     199.7134896, 233.7719021, 246.1212861, 90.58551, 171.9449932, 216.5498126,
...     166.9168296, 145.9856109, 165.5438903, 87.6933456, 84.356885, 142.3092025,
...     126.7220785)

>>> parameters.update()
>>> test.reset_inits()
>>> conditions = model.conditions
>>> conditions_acker_summer = test(
...     "lland_knauf_ic_acker_summer_daily",
...     axis1=(inputs.nied, fluxes.qah), axis2=states.bowa,
...     get_conditions="1997-08-03")
Click to see the table
>>> from hydpy import round_
>>> round_(model.check_waterbalance(conditions))
0.0

acre (routing)

>>> inlet.sequences.sim.series = 0.02
>>> control.negq(False)
>>> test("lland_knauf_ic_acker_routing_daily",
...      axis1=(inputs.nied, fluxes.qah), axis2=states.bowa)
Click to see the table
>>> round_(model.check_waterbalance(conditions))
0.0

acre (heavy rain)

>>> lnk(ACKER)
>>> inlet.sequences.sim.series = 0.0
>>> nied = inputs.nied.series.copy()
>>> inputs.nied.series = 20.0
>>> conditions_acker_heavy_rain = test(
...     "lland_knauf_ic_acker_heavy_rain_daily",
...     axis1=(inputs.nied, fluxes.qah), axis2=states.bowa,
...     get_conditions="1997-08-03")
Click to see the table
>>> round_(model.check_waterbalance(conditions))
0.0

acre (GARTO)

>>> from hydpy import pub
>>> with model.add_soilmodel_v1("ga_garto_submodel1"):
...     nmbbins(4)
...     with pub.options.parameterstep("1m"):
...         dt(1.0)
...     sealed(False)
...     soildepth(309.0 / 0.434)
...     residualmoisture(0.027)
...     saturationmoisture(0.434)
...     saturatedconductivity(13.2)
...     poresizedistribution(0.252)
...     airentrypotential(111.5)
...     states.moisture = 72.0 / 309.0 * 0.434
...     states.frontdepth = 0.0
...     states.moisturechange = 0.0

>>> test("lland_knauf_ic_acker_garto_daily",
...      axis1=(inputs.nied, fluxes.qah), axis2=states.bowa)
Click to see the table

There is no indication of an error in the water balance:

>>> round_(model.check_waterbalance(conditions))
0.0

>>> del model.soilmodel
>>> inputs.nied.series = nied

water

>>> lnk(WASSER)
>>> negq(False)
>>> model.aetmodel.parameters.control.surfaceresistance.wasser_aug = 0.0
>>> model.aetmodel.parameters.control.cropheight.wasser_aug = 0.05
>>> model.aetmodel.parameters.control.albedo.wasser_aug = 0.7
>>> conditions_wasser = test(
...     "lland_knauf_ic_wasser_daily",
...     axis1=(fluxes.nkor, fluxes.evi, fluxes.qah),
...     get_conditions="1997-08-03")
Click to see the table
>>> round_(model.check_waterbalance(conditions))
0.0

water (routing)

>>> inlet.sequences.sim.series = 0.02
>>> test("lland_knauf_ic_wasser_routing_daily",
...      axis1=(fluxes.nkor, fluxes.evi, fluxes.qah))
Click to see the table
>>> round_(model.check_waterbalance(conditions))
0.0

water (negative runoff)

>>> negq(True)
>>> inlet.sequences.sim.series = 0.0
>>> test("lland_knauf_ic_wasser_negq_daily",
...      axis1=(fluxes.nkor, fluxes.evi, fluxes.qah))
Click to see the table
>>> round_(model.check_waterbalance(conditions))
0.0

lakes

>>> lnk(SEE)
>>> model.aetmodel.parameters.control.surfaceresistance.see_aug = 0.0
>>> model.aetmodel.parameters.control.cropheight.see_aug = 0.05
>>> model.aetmodel.parameters.control.albedo.see_aug = 0.7
>>> negq(False)
>>> test("lland_knauf_ic_see_daily",
...      axis1=(fluxes.nkor, fluxes.evi, fluxes.qah))
Click to see the table
>>> round_(model.check_waterbalance(conditions))
0.0

streams

>>> lnk(FLUSS)
>>> model.aetmodel.parameters.control.surfaceresistance.fluss_aug = 0.0
>>> model.aetmodel.parameters.control.cropheight.fluss_aug = 0.05
>>> model.aetmodel.parameters.control.albedo.fluss_aug = 0.7
>>> test("lland_knauf_ic_fluss_daily",
...      axis1=(fluxes.nkor, fluxes.evi, fluxes.qah))
Click to see the table
>>> round_(model.check_waterbalance(conditions))
0.0

sealed surfaces

>>> lnk(VERS)
>>> negq(True)
>>> model.aetmodel.parameters.control.surfaceresistance.vers_aug = 500
>>> model.aetmodel.parameters.control.cropheight.vers_aug = 5.0
>>> model.aetmodel.parameters.control.albedo.vers_aug = 0.10
>>> lai.vers_aug = 10.0
>>> test("lland_knauf_ic_vers_daily",
...      axis1=(inputs.nied, fluxes.qah, states.bowa))
Click to see the table
>>> round_(model.check_waterbalance(conditions))
0.0

acre (winter)

>>> pub.timegrids = "2010-12-01", "2011-01-01", "1d"
>>> lnk(ACKER)
>>> model.aetmodel.parameters.control.cropheight.acker_dec = 0.05
>>> model.aetmodel.parameters.control.albedo.acker_dec = 0.1
>>> model.aetmodel.parameters.control.leafareaindex.acker_dec = 0.3
>>> lai.acker_dec = 0.3
>>> model.aetmodel.parameters.control.averagesoilheatflux.dec = -8.583333333333
>>> wg2z.dec = 8.583333333333
>>> test = IntegrationTest(land)
>>> test.dateformat = "%Y-%d-%m"

>>> test.inits = ((states.inzp, 0.0),
...               (states.stinz, 0.0),
...               (states.sinz, 0.0),
...               (states.esnowinz, 0.0),
...               (states.asinz, 0.0),
...               (states.wats, 0.0),
...               (states.waes, 0.0),
...               (states.esnow, 0.0),
...               (states.taus, 0.0),
...               (states.ebdn, 0.0),
...               (states.bowa, 72.0),
...               (states.sdg1, 0.0),
...               (states.sdg2, 0.0),
...               (states.sig1, 0.0),
...               (states.sig2, 0.0),
...               (states.sbg, 0.0))

>>> inputs.nied.series = (
...     0.0, 11.1, 0.4, 1.2, 6.4, 0.0, 0.0, 0.0, 0.7, 3.3, 9.4, 0.2, 2.9, 0.0, 0.0,
...     6.7, 0.0, 0.1, 0.0, 0.2, 0.2, 2.4, 7.0, 0.2, 0.0, 1.2, 0.9, 0.0, 0.0, 0.2, 0.9)
>>> inputs.teml.series = (
...     -5.8, -3.0, -5.6, -3.8, 0.2, -1.1, -2.9, -2.9, -2.1, -3.1, 5.1, 0.2, -3.5,
...     -3.9, -6.3, -3.5, -7.3, -5.8, -7.9, -5.7, -5.6, -4.8, -1.1, -2.9, -9.1, -8.6,
...     -5.3, -7.7, -9.2, -7.4, 1.7)
>>> inputs.windspeed.series = (
...     6.9, 5.2, 2.0, 4.3, 4.0, 2.4, 1.9, 1.8, 2.7, 3.0, 7.4, 5.7, 2.2, 3.1, 2.8, 3.7,
...     0.9, 1.3, 1.9, 2.4, 2.3, 4.6, 8.6, 7.6, 3.8, 1.5, 1.3, 3.0, 2.7, 1.4, 4.2)
>>> inputs.relativehumidity.series = (
...     70.3, 85.0, 95.9, 90.6, 96.5, 99.0, 99.2, 99.1, 96.9, 95.0, 90.6, 78.7, 90.5,
...     88.1, 92.8, 98.1, 96.6, 97.7, 95.8, 97.5, 95.0, 93.8, 94.9, 85.4, 87.2, 92.7,
...     97.8, 95.4, 94.9, 96.0, 96.5)

>>> model.radiationmodel.sequences.inputs.sunshineduration.series = (
...     3.5, 0.0, 0.1, 3.7, 0.0, 0.1, 0.0, 0.0, 4.4, 0.1, 0.2, 0.7, 0.0, 1.2, 3.0, 0.0,
...     0.0, 0.0, 0.0, 0.2, 0.8, 0.0, 0.0, 0.0, 3.2, 4.3, 0.0, 3.4, 0.0, 0.0, 4.0)

>>> aetinputs.atmosphericpressure.series = (
...     1015.0, 1007.0, 1005.0, 1008.0, 996.0, 998.0, 1004.0, 1006.0, 1009.0, 1018.0,
...     1004.0, 1012.0, 1020.0, 1025.0, 1023.0, 1000.0, 991.0, 997.0, 997.0, 997.0,
...     1004.0, 1007.0, 1004.0, 1008.0, 1018.0, 1019.0, 1017.0, 1022.0, 1024.0, 1021.0,
...     1016.0)
>>> aetinputs.windspeed.series = inputs.windspeed.series
>>> aetinputs.relativehumidity.series = inputs.relativehumidity.series

>>> inlet.sequences.sim.series = 0.0

>>> model.radiationmodel.sequences.inputs.possiblesunshineduration.series = (
...     7.64102946, 7.6096444, 7.57982377, 7.55159603, 7.52498861, 7.50002776,
...     7.47673851, 7.45514453, 7.43526809, 7.41712991, 7.40074913, 7.38614323,
...     7.3733279, 7.36231706, 7.35312273, 7.34575502, 7.34022207, 7.33653002,
...     7.33468296, 7.33468296, 7.33653002, 7.34022207, 7.34575502, 7.35312273,
...     7.36231706, 7.3733279, 7.38614323, 7.40074913, 7.41712991, 7.43526809,
...     7.45514453)
>>> model.radiationmodel.sequences.inputs.globalradiation.series = (
...     31.9427981, 9.8738984, 16.6834998, 31.8074275, 9.5325105, 16.1414844,
...     9.3414287, 9.2567644, 33.405815, 15.5911584, 15.8915442, 17.8235189, 8.941324,
...     19.6680679, 26.8315815, 8.8377384, 8.817416, 8.8041854, 8.7980439, 15.4647459,
...     17.8795412, 8.8221612, 8.8443961, 8.8737425, 27.7596417, 32.3287553, 9.0045823,
...     28.9823209, 9.1276454, 9.1999895, 32.0622345)

>>> conditions_acker_winter = test(
...     "lland_knauf_ic_acker_winter_daily",
...     axis1=(inputs.nied, fluxes.wada), axis2=(states.waes, states.wats),
...     get_conditions="2010-12-10")
Click to see the table
>>> round_(model.check_waterbalance(conditions))
0.0

conifers (winter)

>>> lnk(NADELW)
>>> model.aetmodel.parameters.control.surfaceresistance.nadelw = 56.0
>>> model.aetmodel.parameters.control.cropheight.nadelw = 10.0
>>> model.aetmodel.parameters.control.albedo.nadelw = 0.12
>>> model.aetmodel.parameters.control.leafareaindex.nadelw = 11.0
>>> lai.nadelw = 11.0
>>> conditions_nadelw_winter = test(
...     "lland_knauf_ic_nadelw_winter_daily",
...     axis1=(inputs.nied, fluxes.wada), axis2=(states.waes, states.wats),
...     get_conditions="2010-12-10")
Click to see the table
>>> round_(model.check_waterbalance(conditions))
0.0

acre (snow surface temperature)

>>> lnk(ACKER)
>>> ktschnee(5.0)
>>> conditions_acker_winter_ktschnee = test(
...     "lland_knauf_ic_acker_winter_ktschnee_daily",
...     axis1=(inputs.nied, fluxes.wada), axis2=(states.waes, states.wats),
...     get_conditions="2010-12-10")
Click to see the table
>>> round_(model.check_waterbalance(conditions))
0.0

>>> ktschnee(inf)

hourly simulation

>>> pub.timegrids = "1997-08-03", "1997-08-06", "1h"
>>> for parameter in control:
...     if parameter.TIME == True:
...         parameter.value = parameter.value/24
...     if parameter.TIME == False:
...         parameter.value = parameter.value*24
>>> for parameter in fixed:
...     parameter.restore()
>>> for parameter in model.aetmodel.parameters.fixed:
...     parameter.restore()

>>> with model.add_radiationmodel_v1("meteo_glob_morsim") as submodel_meteo_glob_morsim:
...     latitude(54.1)
...     longitude(9.7)
...     angstromconstant(0.25)
...     angstromfactor(0.5)
...     angstromalternative(0.15)

>>> model.aetmodel.add_radiationmodel_v1(submodel_meteo_glob_morsim)

>>> land.prepare_allseries(False)
>>> test = IntegrationTest(land)

acre (summer)

>>> inputs.nied.series = 0.0
>>> inputs.teml.series = (
...     16.9, 16.6, 16.4, 16.3, 16.0, 15.9, 16.0, 16.6, 17.4, 19.0, 20.3, 21.4, 21.3,
...     21.8, 22.9, 22.7, 22.5, 21.9, 21.4, 20.7, 19.4, 17.8, 17.0, 16.4, 15.9, 15.4,
...     15.2, 14.9, 14.3, 14.1, 14.3, 15.4, 16.8, 18.2, 19.5, 20.3, 21.0, 21.8, 21.9,
...     21.8, 22.2, 21.8, 20.9, 19.7, 17.9, 15.8, 14.8, 14.1, 13.4, 12.8, 12.3, 12.0,
...     11.7, 11.6, 12.6, 14.8, 17.1, 19.4, 20.6, 21.4, 22.5, 23.1, 23.4, 23.8, 24.0,
...     24.0, 23.7, 22.8, 21.3, 19.3, 18.3, 17.4)
>>> inputs.windspeed.series = (
...     0.8, 0.8, 0.8, 0.8, 0.8, 0.6, 0.9, 0.9, 0.9, 1.3, 1.5, 1.2, 1.3, 1.5, 1.9, 1.9,
...     2.3, 2.4, 2.5, 2.5, 2.2, 1.7, 1.7, 2.3, 2.3, 2.2, 2.3, 2.0, 2.3, 2.5, 2.4, 2.5,
...     2.5, 2.9, 3.1, 3.3, 3.3, 3.2, 2.5, 2.9, 3.6, 4.2, 4.2, 3.6, 3.2, 2.2, 2.2, 2.1,
...     1.8, 1.8, 1.6, 1.2, 1.9, 1.3, 1.6, 1.9, 3.2, 4.0, 4.6, 4.1, 4.1, 4.4, 4.6, 4.5,
...     4.7, 4.5, 4.1, 3.8, 2.5, 1.9, 2.2, 2.7)
>>> inputs.relativehumidity.series = (
...     95.1, 94.9, 95.9, 96.7, 97.2, 97.5, 97.7, 97.4, 96.8, 86.1, 76.8, 71.8, 67.5,
...     66.1, 63.4, 62.4, 61.1, 62.1, 67.0, 74.5, 81.2, 86.9, 90.1, 90.9, 88.0, 89.2,
...     88.8, 89.7, 93.0, 93.6, 94.6, 93.3, 86.9, 78.9, 75.8, 73.4, 68.3, 61.3, 60.6,
...     58.8, 57.2, 57.2, 59.9, 66.1, 71.7, 80.6, 85.9, 89.3, 91.4, 93.1, 94.6, 95.6,
...     96.2, 95.7, 95.1, 96.3, 89.9, 79.2, 73.4, 67.3, 62.2, 59.6, 55.4, 52.1, 49.5,
...     48.1, 49.4, 57.0, 65.9, 73.0, 76.7, 81.8)

>>> model.radiationmodel.sequences.inputs.sunshineduration.series = (
...     0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.2, 0.5, 0.7, 0.8, 0.5, 0.4, 0.5,
...     0.5, 0.3, 0.1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.1, 0.9,
...     1.0, 1.0, 0.9, 0.8, 0.9, 0.8, 0.9, 0.9, 0.9, 1.0, 1.0, 1.0, 0.3, 0.0, 0.0, 0.0,
...     0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.6, 0.9, 1.0, 0.9, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
...     1.0, 1.0, 1.0, 1.0, 0.5, 0.0, 0.0, 0.0)

>>> aetinputs.atmosphericpressure.series = (
...     1015.0, 1015.0, 1015.0, 1015.0, 1015.0, 1015.0, 1015.0, 1015.0, 1016.0, 1016.0,
...     1016.0, 1016.0, 1016.0, 1016.0, 1016.0, 1016.0, 1016.0, 1016.0, 1016.0, 1016.0,
...     1016.0, 1016.0, 1017.0, 1017.0, 1017.0, 1016.0, 1016.0, 1016.0, 1016.0, 1017.0,
...     1017.0, 1017.0, 1017.0, 1017.0, 1017.0, 1018.0, 1018.0, 1018.0, 1018.0, 1017.0,
...     1017.0, 1017.0, 1017.0, 1017.0, 1017.0, 1018.0, 1018.0, 1018.0, 1018.0, 1018.0,
...     1018.0, 1018.0, 1018.0, 1018.0, 1018.0, 1019.0, 1019.0, 1019.0, 1019.0, 1019.0,
...     1019.0, 1019.0, 1019.0, 1019.0, 1018.0, 1018.0, 1018.0, 1018.0, 1018.0, 1018.0,
...     1018.0, 1018.0)
>>> aetinputs.windspeed.series = inputs.windspeed.series
>>> aetinputs.relativehumidity.series = inputs.relativehumidity.series

>>> inlet.sequences.sim.series = 0.0

>>> test.inits = (
...     (logs.loggedsunshineduration,
...      [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.2, 0.1, 0.2, 0.1, 0.2, 0.2, 0.3, 0.0,
...       0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]),
...     (logs.loggedpossiblesunshineduration,
...      [0.0, 0.0, 0.0, 0.0, 0.5, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
...       1.0, 1.0, 1.0, 1.0, 1.0, 0.2, 0.0, 0.0, 0.0]),
...     (model.radiationmodel.sequences.logs.loggedunadjustedglobalradiation,
...      [0.0, 0.0, 0.0, 0.0, 0.0, 27.777778, 55.555556, 138.888889, 222.222222,
...       305.555556, 333.333333, 388.888889, 527.777778, 444.444444, 250.0,
...       222.222222, 166.666667, 111.111111, 55.555556, 27.777778, 0.0, 0.0, 0.0,
...       0.0]),
...     (model.aetmodel.sequences.logs.loggedglobalradiation,
...      [0.0, 0.0, 0.0, 0.0, 0.0, 27.8, 55.6, 138.9, 222.2, 305.6, 333.3, 388.9,
...       527.8, 444.4, 250.0, 222.2, 166.7, 111.1, 55.6, 27.8, 0.0, 0.0, 0.0, 0.0]),
...     (model.aetmodel.sequences.logs.loggedairtemperature,
...      [[13.2], [13.2], [13.1], [12.6], [12.7], [13.0], [13.5], [14.8], [16.2],
...       [17.7], [18.8], [19.4], [20.4], [21.0], [21.5], [21.2], [20.4], [20.7],
...       [20.2], [19.7], [19.0], [18.0], [17.5], [17.1]]),
...     (model.aetmodel.sequences.logs.loggedrelativehumidity,
...      [95.1, 94.5, 94.8, 96.4, 96.6, 97.1, 97.1, 96.7, 92.2, 88.5, 81.1, 76.5, 75.1,
...       70.8, 68.9, 69.2, 75.0, 74.0, 77.4, 81.4, 85.3, 90.1, 92.3, 93.8]),
...     (model.aetmodel.sequences.logs.loggedwindspeed2m,
...      [0.8, 1.0, 1.2, 1.3, 0.9, 1.1, 1.3, 1.3, 1.9, 2.2, 1.8, 2.3, 2.4, 2.5, 2.4,
...       2.5, 2.1, 2.2, 1.7, 1.7, 1.3, 1.3, 0.7, 0.8]))

>>> for key, value in locals().copy().items():
...     if key.startswith("conditions_") and ("states" in value.get("model", {})):
...         for name in ("esnowinz", "esnow", "ebdn"):
...             value["model"]["states"][name] *= 24

>>> test("lland_knauf_ic_acker_summer_hourly",
...      axis1=(fluxes.evb, fluxes.qah), axis2=states.bowa,
...      use_conditions=conditions_acker_summer)
Click to see the table
>>> round_(model.check_waterbalance(conditions_acker_summer))
0.0

acre (heavy rain)

>>> inputs.nied.series = 20.0 / 24.0
>>> control.negq(False)
>>> test("lland_knauf_ic_acker_heavy_rain_hourly",
...      axis1=(inputs.nied, fluxes.qah), axis2=states.bowa,
...      use_conditions=conditions_acker_heavy_rain)
Click to see the table
>>> round_(model.check_waterbalance(conditions_acker_heavy_rain))
0.0

water

>>> lnk(WASSER)
>>> inputs.nied.series = 0.05
>>> test("lland_knauf_ic_water_hourly",
...      axis1=(fluxes.nkor, fluxes.evi, fluxes.qah),
...      use_conditions=conditions_wasser)
Click to see the table
>>> inputs.nied.series = 0.0
>>> round_(model.check_waterbalance(conditions_wasser))
0.0

acre (winter)

>>> pub.timegrids = "2010-12-10", "2010-12-13", "1h"

>>> inputs.nied.series = (
...     0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
...     0.1, 0.0, 0.3, 0.2, 0.4, 0.7, 0.5, 1.0, 2.0, 2.1, 1.8, 1.3, 0.5, 0.2, 0.5, 0.2,
...     0.1, 0.3, 0.1, 0.1, 0.0, 0.1, 0.0, 0.1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.1, 0.1,
...     0.0, 0.0, 0.1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.1, 0.0, 0.0, 0.0, 0.0, 0.0,
...     0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0)
>>> inputs.teml.series = (
...     -3.7, -4.8, -5.6, -6.2, -7.3, -8.3, -8.6, -8.5, -9.5, -9.2, -6.9, -4.0, -2.8,
...     -1.4, -0.4, 0.5, 1.0, 1.1, 1.0, 1.4, 1.6, 2.0, 2.4, 2.5, 2.7, 3.2, 3.9, 4.4,
...     4.8, 4.8, 5.1, 5.1, 5.4, 5.3, 5.5, 6.1, 6.4, 6.4, 6.5, 6.3, 5.9, 5.5, 5.1, 4.8,
...     4.9, 4.9, 4.7, 3.8, 3.9, 3.7, 3.5, 3.3, 3.3, 3.0, 1.9, 1.2, 0.8, 0.8, 0.5, 0.3,
...     -0.1, -0.4, -0.6, -0.8, -1.3, -1.6, -2.0, -2.1, -2.2, -2.6, -3.1, -3.9)
>>> inputs.windspeed.series = (
...     3.4, 2.9, 2.5, 3.0, 2.5, 2.3, 2.1, 1.4, 1.1, 1.0, 1.4, 1.3, 1.3, 1.4, 2.3, 2.8,
...     3.1, 3.5, 4.4, 3.8, 5.7, 5.6, 5.8, 6.2, 5.6, 5.2, 5.7, 6.6, 7.0, 7.3, 7.2, 7.6,
...     7.3, 7.1, 7.1, 8.9, 9.5, 7.9, 9.6, 9.1, 8.7, 8.9, 7.9, 7.1, 6.4, 7.2, 7.0, 6.8,
...     6.4, 6.3, 5.7, 5.2, 4.6, 4.9, 6.3, 5.8, 6.1, 5.9, 6.4, 6.8, 7.0, 6.3, 7.3, 7.5,
...     7.0, 6.0, 4.8, 4.2, 4.9, 4.0, 3.4, 3.4)
>>> inputs.relativehumidity.series = (
...     87.5, 90.7, 89.7, 91.3, 94.2, 93.2, 96.5, 95.9, 96.8, 94.3, 96.7, 97.4, 93.9,
...     93.4, 93.3, 94.1, 94.6, 94.4, 96.9, 98.3, 98.7, 99.6, 99.4, 99.2, 99.2, 99.6,
...     99.8, 99.8, 99.0, 97.6, 97.4, 96.3, 95.2, 96.3, 95.5, 91.6, 90.0, 85.7, 82.3,
...     82.5, 82.2, 76.5, 81.7, 83.4, 82.8, 85.8, 87.6, 85.6, 85.3, 86.2, 89.3, 91.4,
...     90.9, 89.2, 85.6, 86.3, 91.2, 87.5, 84.5, 76.7, 74.8, 69.7, 66.9, 64.4, 65.4,
...     67.6, 70.2, 70.4, 69.5, 71.6, 74.5, 80.2)

>>> model.radiationmodel.sequences.inputs.sunshineduration.series = (
...     0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.1, 0.0, 0.0, 0.0, 0.0,
...     0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
...     0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0,
...     0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.2, 0.2,
...     0.2, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0)

>>> aetinputs.atmosphericpressure.series = (
...     1017.0, 1018.0, 1018.0, 1019.0, 1020.0, 1020.0, 1021.0, 1021.0, 1022.0, 1022.0,
...     1022.0, 1022.0, 1022.0, 1021.0, 1020.0, 1020.0, 1019.0, 1018.0, 1016.0, 1015.0,
...     1014.0, 1013.0, 1011.0, 1010.0, 1008.0, 1007.0, 1006.0, 1005.0, 1005.0, 1004.0,
...     1004.0, 1004.0, 1003.0, 1003.0, 1003.0, 1002.0, 1002.0, 1002.0, 1002.0, 1003.0,
...     1003.0, 1003.0, 1003.0, 1003.0, 1003.0, 1003.0, 1003.0, 1002.0, 1002.0, 1002.0,
...     1002.0, 1003.0, 1004.0, 1005.0, 1006.0, 1008.0, 1009.0, 1010.0, 1011.0, 1012.0,
...     1013.0, 1014.0, 1015.0, 1015.0, 1017.0, 1017.0, 1018.0, 1019.0, 1019.0, 1020.0,
...     1020.0, 1020.0)
>>> aetinputs.windspeed.series = inputs.windspeed.series
>>> aetinputs.relativehumidity.series = inputs.relativehumidity.series

>>> test.inits = (
...     (logs.loggedsunshineduration,
...      [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.04, 0.25, 0.59, 0.91,
...       0.97, 1.0, 0.65, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]),
...     (logs.loggedpossiblesunshineduration,
...      [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.4, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0,
...       1.0, 0.1, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]),
...     (model.radiationmodel.sequences.logs.loggedunadjustedglobalradiation,
...      [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 27.777778, 55.555556,
...       111.111111, 166.666667, 138.888889, 55.555556, 0.0,0.0, 0.0, 0.0, 0.0, 0.0,
...       0.0, 0.0, 0.0]),
...     (model.aetmodel.sequences.logs.loggedglobalradiation,
...      [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 27.8, 55.6, 111.1, 166.7, 138.9,
...       55.6, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]),
...     (model.aetmodel.sequences.logs.loggedairtemperature,
...      [[-2.8], [-2.6], [-2.2], [-1.8], [-1.8], [-2.4], [-1.5], [-1.4], [-0.8],
...       [-0.8], [-0.9], [0.9], [-0.8], [-1.0], [-1.2], [-1.8], [-2.8], [-3.8],
...       [-4.3], [-4.0], [-3.9], [-1.6], [-1.6], [2.6]]),
...     (model.aetmodel.sequences.logs.loggedrelativehumidity,
...      [99.4, 99.0, 99.6, 99.6, 99.3, 99.3, 99.8, 99.7, 100.0, 99.6, 99.3, 98.9,
...       96.6, 93.0, 91.4, 92.0, 94.5, 96.5, 98.2, 96.9, 98.0, 95.0, 91.8, 88.5]),
...     (model.aetmodel.sequences.logs.loggedwindspeed2m,
...      [2.2, 2.0, 2.5, 2.6, 2.3, 1.7, 2.8, 1.9, 2.6, 2.9, 3.5, 3.4, 3.5, 3.0, 3.9,
...       3.6, 2.2, 2.4, 2.5, 1.5, 2.5, 3.0, 3.2, 3.1]))

>>> lnk(ACKER)
>>> test("lland_knauf_ic_acker_winter_hourly",
...      axis1=(inputs.nied, fluxes.wada), axis2=(states.waes, states.wats),
...      use_conditions=conditions_acker_winter)
Click to see the table
>>> round_(model.check_waterbalance(conditions_acker_winter))
0.0

conifers (winter)

>>> lnk(NADELW)
>>> test("lland_knauf_ic_nadelw_winter_hourly",
...      axis1=(inputs.nied, fluxes.wada), axis2=(states.waes, states.wats),
...      use_conditions=conditions_nadelw_winter)
Click to see the table
>>> round_(model.check_waterbalance(conditions_nadelw_winter))
0.0

acre (snow surface temperature)

>>> lnk(ACKER)
>>> ktschnee(5.0)
>>> test("lland_knauf_ic_acker_winter_ktschnee_hourly",
...      axis1=(inputs.nied, fluxes.wada),
...      axis2=(states.waes, states.wats),
...      use_conditions=conditions_acker_winter_ktschnee)
Click to see the table
>>> round_(model.check_waterbalance(conditions_acker_winter_ktschnee))
0.0

Method features

class hydpy.models.lland_knauf_ic.Model[source]

Bases: Main_RadiationModel_V1, Main_RadiationModel_V4, Main_AETModel_V1B, Main_SoilModel_V1, Sub_TempModel_V1, Sub_PrecipModel_V1, Sub_IntercModel_V1, Sub_SoilWaterModel_V1, Sub_SnowCoverModel_V1, Sub_SnowyCanopyModel_V1, Sub_SnowAlbedoModel_V1

HydPy-L-Knauf-Ic (adoption of LARSIM with Knauf-based snow modelling including snow interception).

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

  • Pick_QZ_V1 Query the current inflow from all inlet nodes.

The following “run methods” are called in the given sequence during each simulation step:
The following “outlet update methods” are called in the given sequence at the end of 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:

  • AETModel_V1 Interface for calculating interception evaporation, evapotranspiration from soils, evaporation from water areas in separate steps.

  • SoilModel_V1 Soil submodel interface for calculating infiltration and percolation in multiple soil compartments.

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

  • PegasusESnowInz Pegasus iterator for finding the correct energy content of the intercepted snow.

  • PegasusESnow Pegasus iterator for finding the correct snow energy content.

  • PegasusTempSSurface Pegasus iterator for finding the correct snow surface temperature.

DOCNAME = ('L-Knauf-Ic', 'adoption of LARSIM with Knauf-based snow modelling including snow interception')
idx_hru

The hydrological response unit index.

radiationmodel

Required submodel that complies with one of the following interfaces: RadiationModel_V1 or RadiationModel_V4.

aetmodel

Required submodel that complies with the following interface: AETModel_V1.

soilmodel

Optional submodel that complies with the following interface: SoilModel_V1.

check_waterbalance(initial_conditions: ConditionsModel[Self]) → float[source]

Determine the water balance error of the previous simulation run in mm.

Method check_waterbalance() calculates the balance error as follows:

\[\sum_{t=t0}^{t1} \Bigg( NKor_t + QZH_t - \bigg( \sum_{k=1}^{nhru} fhru^k \cdot \Big( EvI_t^k + EvSInz_t^k + EvS_t^k + EvB_t^k \Big) \bigg) - QAH_t \Bigg) + \sum_{k=1}^{nhru} fhru^k \cdot \bigg( \Big( Inzp_{t0}^k - Inzp_{t1}^k \Big) + \Big( SInz_{t0}^k - SInz_{t1}^k \Big) + \Big( WAeS_{t0}^{k} - WAeS_{t1}^{k} \Big) + \Big( BoWa_{t0}^{k} - BoWa_{t1}^{k} \Big) \bigg) - \bigg( \Big( SDG2_{t0} - SDG2_{t1} \Big) + \Big( SDG1_{t0} - SDG1_{t1} \Big) + \Big( SIG2_{t0} - SIG2_{t1} \Big) + \Big( SIG1_{t0} - SIG1_{t1} \Big) + \Big( SBG_{t0} - SBG_{t1} \Big) \bigg)\]

The returned error should usually be in scale with numerical precision so that it does not affect the simulation results in any relevant manner. The only exception we are aware of is the “generation” of additional water when the base flow storage cannot meet the water demand required for the calculated capillary rise (see acre (capillary rise, water balance error)).

Pick the required initial conditions before starting the simulation run via property conditions. See the integration tests of the application model lland_knauf_ic for some examples.

REUSABLE_METHODS = ()

Parameter features

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

Bases: ControlParameters

Control parameters of model lland_knauf_ic.

The following classes are selected:

  • FT Teileinzugsgebietsfläche (subbasin area) [km²].

  • NHRU Anzahl der Hydrotope (number of hydrological response units) [-].

  • Lnk Landnutzungsklasse (land use class) [-].

  • GH Gebietshöhe (elevation) [m].

  • FHRU Flächenanteile der Hydrotope (area percentages of the respective HRUs) [-].

  • KG Niederschlagskorrekturfaktor (adjustment factor for precipitation) [-].

  • ATG Atmosphärischer Temperaturgradient (atmospheric temperature gradient) [°C/100m].

  • KT Temperaturkorrektursummand (adjustment summand for air temperature) [°C].

  • P1Strahl Konstante der Globalstrahlungsreduktion für Wald (constant for reducing the global radiation in forests) [-].

  • P2Strahl Faktor der Globalstrahlungsreduktion für Wald (factor for reducing the global radiation in forests) [-].

  • Albedo0Snow Albedo von Neuschnee (albedo of fresh snow) [-].

  • SnowAgingFactor Wichtungsfaktor für die Sensitivität der Albedo für die Alterung des Schnees (weighting factor of albedo sensitivity for snow aging) [-].

  • Turb0 Parameter des Übergangskoeffizienten des turbulenten Wärmestroms (parameter of transition coefficient for turbulent heat flux) [W/m²/K].

  • Turb1 Parameter des Übergangskoeffizienten des turbulenten Wärmestroms (parameter of transition coefficient for turbulent heat flux) [J/m³/K].

  • MeasuringHeightWindSpeed The height above ground of the wind speed measurements [m].

  • P1Wind Konstante der Windgeschwindigkeitsreduktion für Wald (constant for reducing the wind speed in forests) [-].

  • P2Wind Faktor der Windgeschwindigkeitsreduktion für Wald (factor for reducing the wind speed in forests) [-].

  • LAI Blattflächenindex (leaf area index) [-].

  • HInz Interzeptionskapazität bezogen auf die Blattoberfläche (interception capacity normalized to the leaf surface area) [mm].

  • P1SIMax Konstante zur Berechnung der maximalen Schneeinterzeptionskapazität basierend auf dem Blattflächenindex (constant for calculating the maximum snow interception capacity based on the leaf area index) [mm].

  • P2SIMax Faktor zur Berechnung der maximalen Schneeinterzeptionskapazität basierend auf dem Blattflächenindex (factor for calculating the maximum snow interception capacity based on the leaf area index) [mm].

  • P1SIRate Konstante zur Berechnung des Verhältnisses von Schneeinerzeptionsrate und Niederschlagsintensität basierend auf dem Blattflächenindex (constant for calculating the ratio of the snow interception rate and the precipitation intensity based on the leaf area index) [-].

  • P2SIRate Faktor zur Berechnung des Verhältnisses von Schneeinerzeptionsrate und Niederschlagsintensität basierend auf dem Blattflächenindex (factor for calculating the ratio of the snow interception rate and precipitation intensity based on the leaf area index) [-].

  • P3SIRate Faktor zur Berechnung des Verhältnisses von Schneeinerzeptionsrate und Niederschlagsintensität basierend auf der bereits interzipierten Schneemenge (factor for calculating the ratio of the snow interception rate and precipitation intensity based on the amount of already intercepted snow) [1/mm].

  • TRefN Niederschlagstemperaturgrenzwert des zur Berechnung des Wärmeeintrags durch Regen (precipitation temperature threshold to calculate heat flux caused by liquid precipitation on snow) [°C].

  • TGr Temperaturgrenzwert flüssiger/fester Niederschlag (threshold temperature liquid/frozen precipitation) [°C].

  • TSp Temperaturspanne flüssiger/fester Niederschlag (temperature range with mixed precipitation) [°C].

  • PWMax Maximalverhältnis Gesamt- zu Trockenschnee (maximum ratio of the total and the frozen water equivalent stored in the snow cover) [-].

  • RefreezeFlag Flag um wiedergefrieren zu aktivieren (flag to activate refreezing) [-].

  • KTSchnee Effektive Wärmeleitfähigkeit der obersten Schneeschicht (effective thermal conductivity of the top snow layer) [W/m²/K].

  • WG2Z Bodenwärmestrom in der Tiefe 2z (soil heat flux at depth 2z) [W/m²].

  • WMax Maximaler Bodenwasserspeicher (maximum soil water storage) [mm].

  • FK Feldkapazität / Mindestbodenfeuchte für die Interflowentstehung (field capacity / threshold value of soil moisture for interflow generation) [mm].

  • PWP Permanenter Welkepunkt / Mindestbodenfeuchte für die Basisabflussentstehung (permanent wilting point threshold value of soil moisture for base flow generation) [mm].

  • BSf0 Mindestbodenfeuchte der Sättigungsflächenbildung (relative soil moisture at which the development of saturated areas starts) [-].

  • BSf Bodenfeuchte-Sättigungsfläche-Parameter (shape parameter for the relation between the avarage soil moisture and the relative saturated area of a subbasin) [-].

  • FVF Frostversiegelungsfaktor zur Ermittelung des Frostversiegelungsgrades (frost sealing factor for determination of the degree of frost sealing FVG) [-].

  • BSFF Exponent zur Ermittelung des Frostversieglungsgrades (frost sealing exponent for determination of degree of frost sealing FVG) [-].

  • DMin Drainageindex des mittleren Bodenspeichers (flux rate for releasing interflow from the middle soil compartment) [mm/T].

  • DMax Drainageindex des oberen Bodenspeichers (additional flux rate for releasing interflow from the upper soil compartment) [mm/T].

  • Beta Drainageindex des tiefen Bodenspeichers (storage coefficient for releasing base flow from the lower soil compartment) [1/T].

  • FBeta Faktor zur Erhöhung der Perkolation im Grobporenbereich (factor for increasing percolation under wet conditions) [-].

  • KapMax Maximale kapillare Aufstiegsrate (maximum capillary rise) [mm/T].

  • KapGrenz Grenzwerte für den kapillaren Aufstieg (threshold values related to the capillary rise) [mm].

  • RBeta Boolscher Parameter der steuert, ob the Perkolation unterhalb der Feldkapazität auf Null reduziert wird (flag to indicate if seepage is reduced to zero below field capacity) [-].

  • VolBMax Maximaler Inhalt des Gebietsspeichers für Basisabfluss (highest possible base flow storage) [mm].

  • GSBMax Faktor zur Anpassung von VolBMax (factor for adjusting VolBMax) [-].

  • GSBGrad1 Höchste Volumenzunahme des Gebietsspeichers für Basisabfluss ohne Begrenzung des Zuflusses (highest possible baseflow storage increase without inflow reductions) [mm/T].

  • GSBGrad2 Volumenzunahme des Gebietsspeichers für Basisabfluss, oberhalb der jeglicher Zufluss ausgeschlossen ist (highest possible baseflow storage increase) [mm/T].

  • A1 Parameter für die kontinuierliche Aufteilung der Direktabflusskomponenten (threshold value for the continuous seperation of direct runoff in a slow and a fast component) [mm/T]

  • A2 Parameter für die diskontinuierliche Aufteilung der Direktabflusskomponenten (threshold value for the discontinuous seperation of direct runoff in a slow and a fast component) [mm/T]

  • TInd Fließzeitindex (factor related to the time of concentration) [T].

  • EQB Kalibrierfaktor für die Basisabflusskonzentration (factor for adjusting the concentration time of baseflow). [-].

  • EQI1 Kalibrierfaktor für die “untere” Zwischenabflusskonzentration (factor for adjusting the concentration time of the first interflow component) [-].

  • EQI2 Kalibrierfaktor für die “obere” Zwischenabflusskonzentration (factor for adjusting the concentration time of the second interflow component) [-].

  • EQD1 Kalibrierfaktor für die langsamere Direktabflusskonzentration (factor for adjusting the concentration time of the slower component of direct runoff). [-].

  • EQD2 Kalibrierfaktor für die schnellere Direktabflusskonzentration (factor for adjusting the concentration time of the faster component of direct runoff). [-].

  • NegQ Option: sind negative Abflüsse erlaubt (flag that indicated whether negative discharge values are allowed or not) [-].

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

Bases: DerivedParameters

Derived parameters of model lland_knauf_ic.

The following classes are selected:

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

  • Seconds The length of the actual simulation step size in seconds [s].

  • NmbLogEntries The number of log entries required for a memory duration of 24 hours [-].

  • AbsFHRU Flächen der Hydrotope (areas of the respective HRUs) [km²].

  • MGH Mittlere Gebietshöhe (average elevation) [m].

  • KInz Interzeptionskapazität bezogen auf die Bodenoberfläche (interception capacity normalized to the soil surface area) [mm].

  • HeatOfFusion Heat which is necessary to melt the frozen soil water content [WT].

  • Fr Reduktionsfaktor für Strahlung according to LEG (2020) (basierend auf LUWG (2015)) (reduction factor for short- and long wave radiation) LEG (2020) (based on LUWG (2015)) [-].

  • KB Konzentrationszeit des Basisabflusses (concentration time of the baseflow storage) [T].

  • KI1 Konzentrationszeit des “unteren” Zwischenabflusses (concentration time of the first interflow storage) [T].

  • KI2 Konzentrationszeit des “oberen” Zwischenabflusses” (concentration time of the second interflow storage) [T].

  • KD1 Konzentrationszeit des “langsamen” Direktabflusses (concentration time of the slow direct runoff storage) [T].

  • KD2 Konzentrationszeit des “schnellen” Direktabflusses (concentration time of the fast direct runoff storage) [T].

  • QFactor Factor for converting mm/T to m³/s.

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

Bases: FixedParameters

Fixed parameters of model lland_knauf_ic.

The following classes are selected:

  • CPWasser Spezifische Wärmekapazität von Wasser (specific heat capacity of water) [WT/kg/K].

  • CPEis Spezifische Wärmekapazität von Eis bei 0 °C (specific heat capacity of ice at a temperature of 0 °C) [WT/kg/K].

  • RSchmelz Spezifische Schmelzwärme von Wasser (specific melt heat of water) [WT/kg].

  • Z Halbe Mächtigkeit der in der Temperaturmodellierung betrachteten Bodensäule (the half thickness of the surface soil layer relevant for modelling soil temperature) [m].

  • BoWa2Z Bodenwassergehalt der Bodenschicht bis zu einer Tiefe 2z (soil water content of the soil layer down two a depth of 2z) [mm].

  • LambdaG Wärmeleitfähigkeit des Bodens (thermal conductivity of the top soil layer) [W/m/K].

  • Sigma Stefan-Boltzmann-Konstante (Stefan-Boltzmann constant) [W/m²/K].

  • LWE Mittlere latente Verdunstungswärme für Wasser und Eis (average heat of condensation for water and ice) [WT/kg].

  • PsyInv Kehrwert der Psychrometerkonstante über Schnee und Eis bei 0°C (inverse psychrometric constant for ice and snow at 0°C) [K/hPa].

  • Z0 Rauhigkeitslänge für Wiese (roughness length for short grass) [m].

  • FrAtm Empirischer Faktor zur Berechnung der atmosphärischen Gegenstrahlung (empirical factor for the calculation of atmospheric radiation) [-]

  • CG Volumetrische Wärmekapazität des Bodens (volumetric heat capacity of soil) [WT/m³/K].

Sequence features

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

Bases: InputSequences

Input sequences of model lland_knauf_ic.

The following classes are selected:

  • Nied Niederschlag (precipitation) [mm/T].

  • TemL Lufttemperatur (air temperature) [°C].

  • RelativeHumidity Relative humidity [%].

  • WindSpeed Windgeschwindigkeit (wind speed) [m/s].

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

Bases: FactorSequences

Factor sequences of model lland_knauf_ic.

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

Bases: FluxSequences

Flux sequences of model lland_knauf_ic.

The following classes are selected:

  • QZ Zufluss in das Teilgebiet (inflow into the subcatchment) [m³/s].

  • QZH Abflussspende in das Teilgebiet (inflow into the subcatchment) [mm/T].

  • DailySunshineDuration Daily sunshine duration [h].

  • DailyPossibleSunshineDuration Astronomically possible daily sunshine duration [h].

  • GlobalRadiation Globalstrahlung (global radiation) [W/m²].

  • NKor Korrigierter Niederschlag (corrected precipitation) [mm/T].

  • TKor Korrigierte Lufttemperatur (corrected air temperature) [°C].

  • WindSpeed2m Wind speed at a height of 2 m above the ground for grass [m/s].

  • ReducedWindSpeed2m Land-use-specific wind speed at a height of 2 m above the ground [m/s].

  • SaturationVapourPressure Saturation vapour pressure [hPa].

  • SaturationVapourPressureInz Sättigungsdampdruck unmittelbar oberhalb der Oberfläche des interzepierten Schnees (saturation vapour pressure directly above the surface of the intercepted snow) [hPa].

  • SaturationVapourPressureSnow Saturation vapour pressure snow [hPa].

  • ActualVapourPressure Actual vapour pressure [hPa].

  • TZ Bodentemperatur in der Tiefe z (soil temperature at depth z) [°C].

  • WG “Dynamischer” Bodenwärmestrom (“dynamic” soil heat flux) [W/m²].

  • NetShortwaveRadiationInz Kurzwellige Netto-Strahlungsbilanz für den interzipierten Schnee (net shortwave radiation for intercepted snow) [W/m²].

  • NetShortwaveRadiationSnow Kurzwellige Netto-Strahlungsbilanz für Schneeoberflächen (net shortwave radiation for snow surfaces) [W/m²].

  • NetLongwaveRadiationInz Langwellige Nettostrahlung des interzepierten Schnees (net longwave radiation of the intercepted snow [W/m²].

  • NetLongwaveRadiationSnow Net longwave radiation for snow-surfaces [W/m²].

  • NetRadiationInz Nettostrahlung des interzepierten Schnees (total net radiation of the intercepted snow [W/m²].

  • NetRadiationSnow Total net radiation for snow-surfaces [W/m²].

  • NBes Gesamter Bestandsniederschlag (total stand precipitation) [mm/T].

  • SBes Schneeanteil Bestandsniederschlag (frozen stand precipitation) [mm/T].

  • SnowIntMax Schneeinterzeptionsspeicherkapazität (capacity of the snow interception storage) [mm].

  • SnowIntRate Anteil des im Schneeinterzeptionsspeicher zurückgehaltenen Niederschlags (ratio between the snow interception rate and precipitation) [-].

  • NBesInz Gesamter Bestandsniederschlag, der den Schneeinterzeptionsspeicher erreicht (total stand precipitation reaching the snow interception storage) [mm/T].

  • SBesInz Gefrorener Bestandsniederschlag, der den Schneeinterzeptionsspeicher erreicht (frozen amount of stand precipitation reaching the snow interception storage) [mm/T].

  • WNiedInz Niederschlagsbedingter Wärmestrom in den Schneeinterzeptionsspeicher (heat flux into the snow interception storage due to precipitation) [W/m²].

  • ActualAlbedoInz Aktuelle Albedo der Oberfläche des interzeptierten Schnees (the current albedo of the surface of the intercepted snow) [-].

  • WaDaInz Wasserdargebot des Schneeinterzeptionsspeichers (water leaving the snow interception storage) [mm/T].

  • SchmPotInz Potentielle Schmelze des interzepierten Schnees (potential amount of snow melting within the snow interception storage) [mm/T].

  • SchmInz Tatsächliche Schmelze des interzepierten Schnees (actual amount of snow melting within the snow cover) [mm/T].

  • GefrPotInz Potentielles Wiedergefrieren des interzipierten Schnees (potential amount of water refreezing within the snow interception storage) [mm/T].

  • GefrInz Tatsächliche Wiedergefrieren des interzipierten Schnees (actual amount of water refreezing within the snow interception storage) [mm/T].

  • EvSInz Tatsächliche Verdunstung des interzepierten Schnees (actual evaporation of the intercepted snow) [mm/T].

  • EvI Tatsächliche Verdunstung von Interzeptions- und permanenten Wasserflächen (actual evaporation from interception storages and water areas) [mm/T].

  • EvB Tatsächliche Verdunstung von Bodenwasser (actual evaporation of soil water) [mm/T].

  • EvS Tatsächliche Schneeverdunstung (actual evaporation of snow-water) [mm/T].

  • WNied Niederschlagsbedingter Wärmestrom in die Schneedecke (heat flux into the snow layer due to precipitation) [W/m²].

  • TempSSurface Schneetemperatur an der Schneeoberfläche (the snow temperature at the snow surface) [°C].

  • ActualAlbedo Aktuelle Albedo der relevanten Oberfläche (the current albedo of the relevant surface) [-].

  • SchmPot Potentielle Schneeschmelze (potential amount of water melting within the snow cover) [mm/T].

  • Schm Tatsächliche Schneeschmelze (actual amount of water melting within the snow cover) [mm/T].

  • GefrPot Potentielles Schnee-Wiedergefrieren (potential amount of water refreezing within the snow cover) [mm/T].

  • Gefr Tatsächliche Schnee-Wiedergefrieren (actual amount of water refreezing within the snow cover) [mm/T].

  • WLatInz Latente Wärmestrom interzepierter Schnee/Atmosphäre (latent heat flux between the intercepted snow and the atmosphere) [W/m²].

  • WLatSnow Latente Wärmestrom Schnee/Atmosphäre (latent heat flux between the snow-layer and the atmosphere) [W/m²].

  • WSensInz Fühlbare Wärmestrom interzipierter Schnee/Atmosphäre (sensible heat flux between the intercepted snow and the atmosphere) [W/m²].

  • WSensSnow Fühlbare Wärmestrom Schnee/Atmosphäre (sensible heat flux between the snow-layer and the atmosphere) [W/m²].

  • WSurfInz Wärmestrom vom Körper des interzepierten Schnees bis zu dessen Schneeoberfläche (heat flux from the body of the intercepted snow to its surface) [W/m²].

  • WSurf Wärmestrom von der Schneedecke zur Schneeoberfläche (heat flux from the snow layer to the snow surface) [W/m²].

  • SFF Relativer Anteil des gefrorenen Bodenwassers bis zu einer Tiefe von 2z (relative proportion of frozen soil water) [-].

  • FVG Frostversiegelungsgrad (degree of frost sealing) [-].

  • WaDa Wasserdargebot (water reaching the soil routine) [mm/T].

  • QDB Direktabfluss-Abgabe aus dem Bodenspeicher (direct runoff release from the soil storage) [mm/T].

  • QIB1 Erste Komponente der Interflow-Abgabe aus dem Bodenspeicher (first component of the interflow release from the soil storage) [mm/T].

  • QIB2 Zweite Komponente der Interflow-Abgabe aus dem Bodenspeicher (second component of the interflow release from the soil storage) [mm/T].

  • QBB Basisabfluss-Abgabe aus dem Bodenspeicher (base flow release from the soil storage) [mm/T].

  • QKap Kapillarer Aufstieg in den Bodenspeicher (capillary rise to soil storage) [mm/T].

  • QDGZ Gesamtzufluss in beide Direktabfluss-Gebietsspeicher (total inflow to both direct runoff storages) [mm/T].

  • QDGZ1 Zufluss in den trägeren Direktabfluss-Gebietsspeicher (inflow to the slow direct runoff storage) [mm/T].

  • QDGZ2 Zufluss in den dynamischeren Direktabfluss-Gebietsspeicher (inflow to the fast direct runoff storage) [mm/T].

  • QIGZ1 “Zufluss in den ersten Zwischenabfluss-Gebietsspeicher (inflow to the first interflow storage) [mm/T].

  • QIGZ2 Zufluss in den zweiten Zwischenabfluss-Gebietsspeicher (inflow to the second interflow storage) [mm/T].

  • QBGZ Zufluss in den Basisabfluss-Gebietsspeicher (inflow to the base flow storage) [mm/T].

  • QDGA1 Abfluss aus dem trägeren Direktabfluss-Gebietsspeicher (outflow from the slow direct runoff storage) [mm/T].

  • QDGA2 Abfluss aus dem dynamischeren Direktabfluss-Gebietsspeicher (outflow from the fast direct runoff storage) [mm/T].

  • QIGA1 Abfluss aus dem “unteren” Zwischenabfluss-Gebietsspeicher (outflow from the first interflow storage) [mm/T].

  • QIGA2 Abfluss aus dem “oberen” Zwischenabfluss-Gebietsspeicher (outflow from the second interflow storage) [mm/T].

  • QBGA Abfluss aus dem Basisabfluss-Gebietsspeicher (outflow from the base flow storage) [mm/T].

  • QAH Abflussspende des Teilgebiets (runoff at the catchment outlet) [mm/T].

  • QA Abfluss des Teilgebiets (runoff at the catchment outlet) [m³/s].

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

Bases: StateSequences

State sequences of model lland_knauf_ic.

The following classes are selected:

  • Inzp Interzeptionsspeicherung (interception storage) [mm].

  • STInz Wasseräquivalent Trockenschnee im Interzeptionsspeicher (total water equivalent of the intercepted snow) [mm].

  • SInz Wasseräquivalent Gesamtschnee im Interzeptionsspeicher (frozen water equivalent of the intercepted snow) [mm].

  • ESnowInz Kälteinhalt der Schneedecke des Interzeptionsspeichers [WT/m²].

  • ASInz Dimensionsloses Alter des interzipierten Schnees (dimensionless age of the intercepted snow layer) [-].

  • WATS Wasseräquivalent Trockenschnee auf der Bodenoberfläche (frozen water equivalent of the snow cover) [mm].

  • WAeS Wasseräquivalent Gesamtschnee auf der Bodenoberfläche (total water equivalent of the snow cover) [mm].

  • ESnow Thermischer Energieinhalt der Schneedecke bezogen auf 0°C (thermal energy content of the snow layer with respect to 0°C) [WT/m²].

  • TauS Dimensionsloses Alter der Schneedecke (dimensionless age of the snow layer) [-].

  • EBdn Energiegehalt des Bodenwassers (energy content of the soil water) [WT/m²].

  • BoWa Bodenwasserspeicherung (soil water storage) [mm].

  • SDG1 Träger Direktabfluss-Gebietsspeicher (slow direct runoff storage) [mm].

  • SDG2 Dynamischer Direktabfluss-Gebietsspeicher (fast direct runoff storage) [mm].

  • SIG1 Erster Zwischenabfluss-Gebietsspeicher (first interflow storage) [mm].

  • SIG2 Zweiter Zwischenabfluss-Gebietsspeicher (second interflow storage) [mm].

  • SBG Basisabfluss-Gebietsspeicher (base flow storage) [mm].

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

Bases: LogSequences

Log sequences of model lland_knauf_ic.

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

Bases: InletSequences

Inlet sequences of model lland_knauf_ic.

The following classes are selected:

  • Q Abfluss (runoff) [m³/s].

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

Bases: OutletSequences

Outlet sequences of model lland_knauf_ic.

The following classes are selected:

  • Q Abfluss (runoff) [m³/s].

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

Bases: AideSequences

Aide sequences of model lland_knauf_ic.

The following classes are selected:

  • SNRatio Ratio of frozen precipitation to total precipitation [-].

  • RLAtm Atmosphärische Gegenstrahlung (longwave radiation emitted from the atmosphere) [W/m²].

  • TempS Temperatur der Schneedecke (temperature of the snow layer) [°C].

  • TempSInz Temperatur des interzepierten Schnees (temperature of the intercepted snow) [°C].

Auxiliary features

class hydpy.models.lland_knauf_ic.Masks[source]

Bases: Masks

Masks applicable to lland_knauf_ic.

The following classes are selected: