def _init_model(self, solver):
if solver == 'numba':
solver = PegasusNumba()
num_app = ImplicitEulerNumba(root_finder=solver)
elif solver == 'python':
solver = PegasusPython()
num_app = ImplicitEulerPython(root_finder=solver)
fr = PowerReservoir(parameters = {'k' : 0.01,
'alpha' : 2.5},
states = {'S0' : 0.0},
approximation=num_app,
id = 'FR')
ur = UnsaturatedReservoir(parameters = {'Smax' : 50.0,
'Ce' : 1.5,
'm' : 0.01,
'beta' : 1.5,
},
states = {'S0' : 0.2*50.0, 'PET' : None},
approximation=num_app,
id = 'UR')
hru = Unit(layers = [
[ur],
[fr]
],
id = 'H1')
hru.set_timestep(1.0)
self._model = hru
def _init_model(self, solver):
if solver == 'numba':
solver = PegasusNumba()
num_app = ImplicitEulerNumba(root_finder=solver)
elif solver == 'python':
solver = PegasusPython()
num_app = ImplicitEulerPython(root_finder=solver)
fr = PowerReservoir(parameters={
'k': 0.01,
'alpha': 2.5
},
states={'S0': 0.0},
approximation=num_app,
id='FR')
fr.set_timestep(2.0)
self._model = fr
def _init_model(self, solver):
if solver == 'numba':
solver = PegasusNumba()
num_app = ImplicitEulerNumba(root_finder=solver)
elif solver == 'python':
solver = PegasusPython()
num_app = ImplicitEulerPython(root_finder=solver)
ur = UnsaturatedReservoir(parameters={
'Smax': 50.0,
'Ce': 1.5,
'm': 0.01,
'beta': 1.5
},
states={'S0': 0.2 * 50.0},
approximation=num_app,
id='UR')
ur.set_timestep(2.0)
self._model = ur
from superflexpy.implementation.root_finders.pegasus import PegasusPython
from superflexpy.implementation.numerical_approximators.implicit_euler import ImplicitEulerPython
from superflexpy.implementation.elements.hbv import UnsaturatedReservoir, PowerReservoir
from superflexpy.framework.unit import Unit
root_finder = PegasusPython()
numeric_approximator = ImplicitEulerPython(root_finder=root_finder)
ur = UnsaturatedReservoir(parameters={
'Smax': 50.0,
'Ce': 1.0,
'm': 0.01,
'beta': 2.0
},
states={'S0': 25.0},
approximation=numeric_approximator,
id='UR')
fr = PowerReservoir(parameters={
'k': 0.1,
'alpha': 1.0
},
states={'S0': 10.0},
approximation=numeric_approximator,
id='FR')
model = Unit(layers=[[ur], [fr]], id='M4')
from superflexpy.implementation.models.m4_sf_2011 import model
model.set_input([P, E])
Dal Molin, M., Schirmer, M., Zappa, M., and Fenicia, F.: Understanding dominant
controls on streamflow spatial variability to set up a semi-distributed
hydrological model: the case study of the Thur catchment, Hydrol. Earth Syst.
Sci., 24, 1319–1345, https://doi.org/10.5194/hess-24-1319-2020, 2020.
"""
from superflexpy.implementation.root_finders.pegasus import PegasusPython
from superflexpy.implementation.numerical_approximators.implicit_euler import ImplicitEulerPython
from superflexpy.implementation.elements.thur_model_hess import SnowReservoir, UnsaturatedReservoir, PowerReservoir, HalfTriangularLag
from superflexpy.implementation.elements.structure_elements import Transparent, Junction, Splitter
from superflexpy.framework.unit import Unit
from superflexpy.framework.node import Node
from superflexpy.framework.network import Network
solver = PegasusPython()
approximator = ImplicitEulerPython(root_finder=solver)
# Fluxes in the order P, T, PET
upper_splitter = Splitter(
direction=[
[0, 1, None], # P and T go to the snow reservoir
[2, None, None] # PET goes to the transparent element
],
weight=[[1.0, 1.0, 0.0], [0.0, 0.0, 1.0]],
id='upper-splitter')
snow = SnowReservoir(parameters={
't0': 0.0,
'k': 0.01,
'm': 2.0
def _init_model(self, solver):
if solver == 'numba':
solver = PegasusNumba()
num_app = ImplicitEulerNumba(root_finder=solver)
elif solver == 'python':
solver = PegasusPython()
num_app = ImplicitEulerPython(root_finder=solver)
# Define HRU 1 (40%)
fr = PowerReservoir(parameters={
'k': 0.01,
'alpha': 2.5
},
states={'S0': 0.0},
approximation=num_app,
id='FR')
h1 = Unit(layers=[[fr]], id='H1')
# Define HRU 2 (60%)
fr = PowerReservoir(parameters={
'k': 0.01,
'alpha': 2.5
},
states={'S0': 0.0},
approximation=num_app,
id='FR')
sr = PowerReservoir(parameters={
'k': 1e-4,
'alpha': 1.0
},
states={'S0': 0.0},
approximation=num_app,
id='SR')
ur = UnsaturatedReservoir(parameters={
'Smax': 50.0,
'Ce': 1.5,
'm': 0.01,
'beta': 1.5,
},
states={
'S0': 0.2 * 50.0,
'PET': None
},
approximation=num_app,
id='UR')
s = Splitter(weight=[[0.3], [0.7]], direction=[[0], [0]], id='S')
j = Junction(direction=[[0, 0]], id='J')
h2 = Unit(layers=[[ur], [s], [fr, sr], [j]], id='H2')
# Define the catchment
cat = Node(units=[h1, h2], weights=[0.4, 0.6], area=1.0, id='Cat')
cat.set_timestep(1.0)
self._model = cat
CODED BY: Marco Dal Molin
DESIGNED BY: Marco Dal Molin, Fabrizio Fenicia, Dmitri Kavetski
This file implements a version of the model GR4J
"""
from superflexpy.implementation.root_finders.pegasus import PegasusPython
from superflexpy.implementation.numerical_approximators.implicit_euler import ImplicitEulerPython
from superflexpy.implementation.elements.gr4j import InterceptionFilter, ProductionStore, UnitHydrograph1, UnitHydrograph2, RoutingStore, FluxAggregator
from superflexpy.implementation.elements.structure_elements import Transparent, Splitter, Junction
from superflexpy.framework.unit import Unit
x1, x2, x3, x4 = (50.0, 0.1, 20.0, 3.5)
root_finder = PegasusPython() # Use the default parameters
numerical_approximation = ImplicitEulerPython(root_finder)
interception_filter = InterceptionFilter(id='ir')
production_store = ProductionStore(parameters={'x1': x1, 'alpha': 2.0,
'beta': 5.0, 'ni': 4/9},
states={'S0': 10.0},
approximation=numerical_approximation,
id='ps')
splitter = Splitter(weight=[[0.9], [0.1]],
direction=[[0], [0]],
id='spl')
unit_hydrograph_1 = UnitHydrograph1(parameters={'lag-time': x4},