wolfhece.hydrology.SubBasin
Author: HECE - University of Liege, Pierre Archambeau, Christophe Dessers Date: 2024
Copyright (c) 2024 University of Liege. All rights reserved.
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Module Contents
- class wolfhece.hydrology.SubBasin.SubBasin(_dateBegin: datetime.datetime = None, _dateEnd: datetime.datetime = None, _deltaT: int = 0, _model=cst.measures, _workingDir: str = '', _hyeto: dict = {}, _x: float = 0.0, _y: float = 0.0, surfaceDrained: float = 0.0, _iD_interiorPoint: int = 1, _idSorted: int = 1, name: str = None, readHydro=True, _tz: int = 0, version: str = cst.VERSION_WOLFHYDRO)[source]
-
- property outFlow_global[source]
The outFlow global property. Returns the outFlow in the global time, i.e. the hydrograph to which the timeDelay is applied.
- property outFlowRaw_global[source]
The outFlow global property. Returns the outFlow in the global time, i.e. the hydrograph to which the timeDelay is applied.
- transferParam: wolfhece.PyParams.Wolf_Param[source]
- get_outFlow_noDelay(unit='m3/s')[source]
This function returns the total outlet of the basin and considers t0=0 at the outlet of the subbasin without considering timeDelay (the time of the real outlet of the whole potential catchment)
- get_outFlowRaw_noDelay(unit='m3/s')[source]
This function returns the total raw outlet of the basin and considers t0=0 at the outlet of the subbasin without considering timeDelay (the time of the real outlet of the whole potential catchment)
- get_inlets_noDelay(unit='m3/s')[source]
This function returns the total inlets of the basin and considers t0=0 at the outlet of the subbasin without considering timeDelay (the time of the real outlet of the whole potential catchment)
- add_downstreamObj(toPoint, name='DEFAULT')[source]
This procedure link the downstream element to the object
- compute_hydro()[source]
This procedure computes the total hydrograph and raw hydrograph of subbasin
The total hydrograph $q_{tot} is obtained with the formula:
- [
q_{tot} = sum q_{ ext{inlets}} + q_{ ext{me}}$
- ]
, with $q_{ ext{me}}$ the hydrograph of the subbasin alone.
Internal variable changed: outFlowRaw, outFlow, inletsRaw CAUTION:
Discussion about the ceil or the floor for the timeDelay indice!!!
UPDATE 2023.1 now the outFlow are not delayed anymore !!!! -> IMPORTANT UPDATE
- sum_inlets()[source]
Sum all the inlet hydrographs of a subbasin. Return an array of zeros otherwise.
Internal variable changed: self.inlets, self.inletsRaw
- add_rain(workingDir, fileName=None, tzDelta=datetime.timedelta(hours=0))[source]
This procedure - reads: the time, rain in the rain file - saves: the rain of the subbasin, sum of the rain’s inlets - returns: the time array read. - Variables modified: self.rain, self.myRain
- add_evap(workingDir, fileName=None, tzDelta=datetime.timedelta(hours=0))[source]
This procedure - reads: the time, evapotranspiration in the evap file - saves: the evapotranspiration of the subbasin, sum of the evapotranspiration’s inlets -> to correct with surface of the basin - returns: the time array read. - Variables modified: self.evap, self.myEvap
- add_temp(workingDir, fileName=None, tzDelta=datetime.timedelta(hours=0))[source]
This procedure - reads: the time, mean temperature in a day in the Temp file - saves: the temperatures of the subbasin - returns: the time array read. - Variables modified: self.myTemp
- add_hyeto(workingDir, hyetoDict)[source]
Add hyetographs to the subbasin TO DO: Adapt the code to find automatically the .dbf files. E.G. when data are read in NetCDF files.
- plot(workingDir, plotRaw=False, axis='Hours', yAdd=[], yAddName=[], rangeData=[], deltaMajorTicks=12.0 * 3600.0, deltaMinorTicks=3600.0, tzPlot=0)[source]
This procedure plots: - the inlets: in color chosen randomly by matplotlib - the outlet: in black solid line - the raw outlet: in black dashed line
- plot_myBasin(Measures=None, rangeData=[], yrangeRain=[], yrangeData=[], factor=1.5, graph_title='', withEvap=False, writeFile='', withCt=False, figure=None)[source]
This procedure plots its own hydrographs and hyetographs
- plot_outlet(Measures=None, rangeData=[], yrangeRain=[], yrangeData=[], ylabel=[], addData=[], dt_addData=[], beginDates_addData=[], endDates_addData=[], label_addData=[], color_addData=[], factor=1.5, graph_title='', withEvap=False, writeFile='', withDelay=True, deltaMajorTicks=-1, deltaMinorTicks=-1, tzPlot=0, Measure_unit='m3/s', addTable=False, figure=None)[source]
This procedure plots its own hydrographs and hyetographs
- read_myMainCharacteristics(workingDir: str, fileNameList: list = [])[source]
This procedure read the main characteristics of the subbasin and hydro subbasin TO COMPLETE …
- get_outFlow(typeOutFlow: str = 'Net', unit: str = 'm3/s', whichOutFlow='', lag: float = 0.0)[source]
- plot_diff_cumulRain_with_lagtime(interval, lagTime, graph_title='', factor=1.5, writeDir='', lawNetRain=cst.tom_netRain_no, netRainParams={})[source]
@var interval interval to consider in the gliding sum [sec] @var lagTime time to skip before applyihng the current rain [sec]
- apply_stock_reservoir(Hs, Ts, curS0=0.0)[source]
This function returns the net rain vector after applying a storage reservoir. @var H_s max height of the reservoir [mm] @var T_s time to empty completely the reservoir [h]
- activate(effSubs: list = [], effSubsSort: list = [], mask: list = [], onlyItself: bool = False)[source]
- get_value_outlet(wolfarray: wolfhece.wolf_array.WolfArray)[source]
- read_landuses(fileName: str = '', onlySub: bool = True, landuseName: str = '', landuse_index_transform: str = '', toSave: bool = True) dict[source]
- collect_x_from_production() dict[str, wolfhece.PyParams.np.array][source]
This procedure is collecting all the time series fractions of each outflow of the hydrological production models written in Fortran
- Returns:
A dictionary containing the fractions of each outflow.
- Return type:
dict[str, np.array]
- collect_fractions() dict[str, wolfhece.PyParams.np.array][source]
This procedure is collecting all the fractions of each outflow of the hydrological production models.
- Returns:
A dictionary containing the fractions of each outflow.
- Return type:
dict[str, np.array]
- collect_all_internal_variables() dict[str, wolfhece.PyParams.np.array][source]
This procedure is collecting all internal variables of the hydrological production models.
- Returns:
A dictionary containing the fractions of each outflow.
- Return type:
dict[str, np.array]
- activate_all_internal_variables()[source]
This procedure is activating all internal variables of all the hydrological modules.
- collect_x_VHM() dict[str, wolfhece.PyParams.np.array][source]
This procedure is collecting all the fractions of each outflow of the VHM model.
Returns: - all_x: A dictionary containing the fractions of each outflow of the VHM model.
- _collect_fractions_VHM(all_x: dict[str, wolfhece.PyParams.np.array]) dict[str, wolfhece.PyParams.np.array][source]
This procedure is collecting all the fractions of each outflow of the VHM model.
Returns: - all_f: A dictionary containing the fractions of each outflow of the VHM model.
- collect_iv_VHM() dict[str, wolfhece.PyParams.np.array][source]
This procedure is collecting all internal variables of the VHM model in each module.
Returns: - all_iv: A dictionary containing all internal variables of the VHM model.
- activate_all_iv_VHM()[source]
This procedure is activating all internal variables of the VHM model in each module.
- collect_x_GR4() dict[str, wolfhece.PyParams.np.array][source]
This procedure is collecting the fractions of each outflow of the GR4 model.
- Returns:
A dictionary containing all fractions of each outflow of the GR4 model.
- Return type:
dict[str, np.array]
- _collect_fractions_GR4(all_x: dict[str, wolfhece.PyParams.np.array]) dict[str, wolfhece.PyParams.np.array][source]
This procedure is collecting all the fractions of each outflow of the GR4 model.
Returns: - all_f: A dictionary containing the fractions of each outflow of the GR4 model.
- collect_iv_GR4() dict[str, wolfhece.PyParams.np.array][source]
This procedure is collecting all internal variables of the GR4 model in each module.
Returns: - all_iv: A dictionary containing all internal variables of the GR4 model.
- activate_all_iv_GR4()[source]
This procedure is activating all internal variables of the GR4 model in each module.
- collect_x_2layers() dict[str, wolfhece.PyParams.np.array][source]
This procedure is collecting the fractions of each outflow of the 2 layers model.
- Returns:
A dictionary containing the collected fractions of each outflow variables.
- _collect_fractions_2layers(all_x: dict[str, wolfhece.PyParams.np.array]) dict[str, wolfhece.PyParams.np.array][source]
This procedure is collecting all the fractions of each outflow of the 2 layers model.
Returns: - all_f: A dictionary containing the fractions of each outflow of the 2 layers model.
- collect_iv_2layers() dict[str, wolfhece.PyParams.np.array][source]
This procedure is collecting all internal variables of the 2 layers model in each module.
Returns: - all_iv: A dictionary containing the fractions all internal variables of the 2 layers model.
- activate_all_iv_2layers()[source]
This procedure is activating all internal variables of the 2 layers model in each module.
- collect_internal_variables(list_keys: list[str], files_per_keys: list[list[str]], group_name: str = 'Internal variables to save', param_name: str = 'simul_soil') dict[str, wolfhece.PyParams.np.array][source]
Collects all the internal variables of the 2 layers model.
Parameters: - list_keys (list[str]): List of keys representing the internal variables to collect. - files_per_keys (list[list[str]]): List of lists containing the file names associated with each key. - group_name (str, optional): Name of the group containing the internal variables to save. Default is “Internal variables to save”. - production_name (str, optional): Name of the production file. Default is “simul_soil”.
Returns: - dict[str,np.array]: A dictionary containing the collected internal variables, where the keys are the variable names and the values are numpy arrays.
- activate_internal_variables(list_keys: list[str], group_name: str = 'Internal variables to save', param_name: str = 'simul_soil')[source]
Activates all the internal variables of the 2 layers model.
Parameters: - list_keys (list[str]): List of keys representing the internal variables to collect.
- get_summary_fractions(summary: str = 'mean', all_f: dict = {}, interval: list[tuple[datetime.datetime, datetime.datetime]] = None) dict[str, wolfhece.PyParams.np.array][source]
This procedure is returning a summary of the fractions of the current module.
Parameters: - summary (str): The type of summary to return. - interval (list[datetime.datetime], optional): The interval of time to consider. Default is None.
Returns: - dict: A dictionary containing the summary of the fractions of the current module.
- get_volume_fractions(all_f: dict = {}, interval: list[tuple[datetime.datetime, datetime.datetime]] = None) dict[str, wolfhece.PyParams.np.array][source]
This procedure is returning a summary of the fractions of the current module.
Parameters: - summary (str): The type of summary to return. - interval (list[datetime.datetime], optional): The interval of time to consider. Default is None.
Returns: - dict: A dictionary containing the summary of the fractions of the current module.
- check_presence_of_iv()[source]
This procedure is checking the presence of internal variables in the current module.
- get_all_Qtest(nb_atttempts=-1, typeOutFlow: str = 'Net', unit: str = 'm3/s', whichOutFlow='', lag: float = 0.0) wolfhece.PyParams.np.array[source]
This function returns the Qtest hydrograph of the current module.
Parameters: - which (str, optional): The type of hydrograph to return. Default is “Net”.
Returns: - np.array: The Qtest hydrograph of the current module.
- plot_all_fractions(all_fractions: dict[str:np.array] = {}, figure=None, to_show: bool = False, writeDir: str = '', range_data: list[datetime.datetime] = []) None[source]