plans.hydrology.downscaled#

{Short module description (1-3 sentences)} todo docstring

Features#

todo docstring

  • {feature 1}

  • {feature 2}

  • {feature 3}

  • {etc}

Overview#

todo docstring {Overview description}

Examples#

todo docstring {Examples in rST}

Print a message

# print message
print("Hello world!")
# [Output] >> 'Hello world!'

Classes

DownscaledModel([name, alias])

This is a local Rainfall-Runoff model.
class plans.hydrology.downscaled.DownscaledModel(name='MyLocal', alias='Loc001')[source]#

Bases: UpscaledModel

This is a local Rainfall-Runoff model. Simulates the the catchment globally and locally by applying downscaling methods. Expected inputs:

  • clim.csv for Precipitation (P) and Potential Evapotranspiration (E_pot).

  • path_areas.csv for deriving the geomorphic unit hydrograph.

  • # todo [complete]

# todo [major docstring] examples

__init__(name='MyLocal', alias='Loc001')[source]#

Initialize the DataSet object.

Parameters:

  • name (str) – unique object name

  • alias (str) – unique object alias. If None, it takes the first and last characters from name

filename_data_lulc#

Instructions: make a model that handles both G2G and HRU approach. The trick seems to have a area matrix that is the same…

  • Use downscale_values() functions from plans.geo

  • Downscaling may include parameter maps as proxys.

_set_model_vars()[source]#
_set_scenario(scenario_clim='obs', scenario_lulc='obs')[source]#
_set_sbasin(n=0)[source]#
_set_basemap()[source]#
_setup_wmask()[source]#
_setup_vars()[source]#
_setup_params()[source]#
_setup_add_lulc_to_data()[source]#
_setup_start()[source]#
setter(dict_setter)[source]#

Set selected attributes based on an incoming dictionary. This is calling the superior method using load_data=False.

Parameters:

dict_setter (dict) – incoming dictionary with attribute values

Returns:

None

Return type:

None

get_evaldata()[source]#
load_basin()[source]#
load_tsi()[source]#
load_soils()[source]#
load_lulc()[source]#
load_data()[source]#

Load simulation data. Expected to increment superior methods.

Returns:

None

Return type:

None

setup()[source]#

Set model simulation.

Warning

This method overwrites model data.

Returns:

None

Return type:

None

solve()[source]#

Solve the model for inputs and initial conditions by numerical methods.

Warning

This method overwrites model data.

Returns:

None

Return type:

None

export(folder, filename, views=False, mode=None)[source]#

Export object resources. Expected to be called after setup.

Parameters:

  • folder (str) – path to folder

  • filename (str) – file name without extension

Returns:

None

Return type:

None

static demo()[source]#