def get_project(with_solute=False):
if with_solute:
p = cmf.project('X')
X, = p.solutes
else:
p = cmf.project()
X = None
stores = [p.NewStorage('source{}'.format(i)) for i in range(10)]
for l, r in zip(stores[:-1],stores[1:]):
cmf.LinearStorageConnection(l, r, 1)
stores[0].volume = 1
if with_solute:
stores[0][X].source = 1
return p, stores, X
def run_model(self):
"""Runs the model with everything"""
# Initialize project
project = cmf.project()
self.load_cmf_files()
# Add cells and properties to them
self.mesh_to_cells(project, self.mesh_path)
for key in self.ground_dict.keys():
self.configure_cells(project, self.ground_dict[str(key)])
if self.trees_dict:
for key in self.trees_dict.keys():
self.add_tree(project, self.trees_dict[str(key)]['face_index'],
self.trees_dict[str(key)]['property'])
# Create the weather
self.create_weather(project)
# Create boundary conditions
if self.boundary_dict:
self.create_boundary_conditions(project)
# Run solver
self.solve(project, self.solver_settings['tolerance'])
# Save the results
self.save_results()
return project
def __init__(self, begin, end):
"""Initializes the model and build the core setup"""
# tr_soil_GW = Residence time of the water in the soil to the GW
self.params = [param("tr_soil_out", 0., 200.),
# tr_GW_out = Residence time in the groundwater to
# the outlet
param('V0_soil', 0., 300.),
# beta_soil_out = exponent that changes the form of the
# flux from the soil to the outlet
param("beta_soil_out", 0.3, 8.0),
# ETV1 = the Volume that defines that the evaporation
# is lowered because of not enough water in the soil
param('ETV1', 0., 300.),
# fETV0 = factor the ET is multiplied by, when water is
# low
param('fETV0', 0., 0.9),
# Rate of snow melt
param('meltrate', 0.01, 15.),
# Snow_melt_temp = Temperature at which the snow melts
# (needed because of averaged temp
param('snow_melt_temp', -3.0, 3.0)
]
self.begin = begin
self.end = end
# load the weather data and discharge data
prec, temp, temp_min, temp_max, Q, wind, sun, \
rel_hum= self.loadPETQ()
self.Q = Q
# use only one core (faster when model is small
cmf.set_parallel_threads(1)
# Generate a cmf project with one cell for a lumped model
self.project = cmf.project()
p = self.project
# Create a cell in the project
c = p.NewCell(0, 0, 0, 1000)
# Add snow storage
c.add_storage("Snow", "S")
cmf.Snowfall(c.snow, c)
# Add the soil and groundwater layers
soil = c.add_layer(2.0)
# Give the storages a initial volume
c.layers[0].volume = 15
# Install a calculation of the evaporation
cmf.PenmanMonteithET(soil, c.transpiration)
# Create an outlet
self.outlet = p.NewOutlet("outlet", 10, 0, 0)
# Create the meteo stations
self.make_stations(prec, temp, temp_min, temp_max, wind, sun,
rel_hum)
self.project = p
def solve_ready_project(cmf_data):
(ground_list, mesh_path, weather_dict, trees_dict, outputs,
solver_settings, boundary_dict) = cmf_data
project = cmf.project()
project, mesh_info = hydrology.mesh_to_cells(project, mesh_path, False)
for ground in ground_list:
hydrology.configure_cells(project, ground, mesh_info[ground['mesh']])
if trees_dict:
for key in trees_dict.keys():
hydrology.add_tree_to_project(project,
trees_dict[key]['face_index'],
trees_dict[key]['property'])
# Create the weather
if weather_dict:
hydrology.create_weather(project)
# Create boundary conditions
if boundary_dict:
hydrology.create_boundary_conditions(project)
return project, solver_settings, outputs
def __init__(self, par):
cmf.set_parallel_threads(1)
# run the model
self.project = cmf.project()
self.cell = self.project.NewCell(x=0, y=0, z=238.628, area=1000, with_surfacewater=True)
c = self.cell
r_curve = cmf.VanGenuchtenMualem(Ksat=10**par.pKsat, phi=par.porosity, alpha=par.alpha, n=par.n)
# Make the layer boundaries and create soil layers
lthickness = [.01] * 5 + [0.025] * 6 + [0.05] * 6 + [0.1] * 5
ldepth = np.cumsum(lthickness)
# Create soil layers and pick the new soil layers if they are inside of the evaluation depth's
for d in ldepth:
c.add_layer(d, r_curve)
# Use a Richards model
c.install_connection(cmf.Richards)
# Use shuttleworth wallace
self.ET = c.install_connection(cmf.ShuttleworthWallace)
c.saturated_depth = 0.5
self.gw = self.project.NewOutlet('groundwater', x=0, y=0, z=.9)
cmf.Richards(c.layers[-1], self.gw)
self.gw.potential = c.z - 0.5 #IMPORTANT
self.gw.is_source = True
self.gwhead = cmf.timeseries.from_scalar(c.z - 0.5)
self.solver = cmf.CVodeIntegrator(self.project, 1e-9)
def project_with_cells(cmf_data):
(ground_list, mesh_paths, weather_dict, trees_dict, outputs,
solver_settings, boundary_dict) = cmf_data
project = cmf.project()
return hydrology.mesh_to_cells(project, mesh_paths, False)
def test_describe(self):
p = cmf.project()
c = p.NewCell(0, 0, 0, 1000, True)
p.meteo_stations.add_station('Giessen', (0, 0, 0))
c.add_layer(1.0)
text = cmf.describe(p).split('\n')
self.assertGreaterEqual(len(text), 25)
def canopyStorage():
import cmf
import pylab as plt
p = cmf.project()
c = p.NewCell(0, 0, 0, 1000, True)
# Add a single layer of 1 m depth
l = c.add_layer(1.0, cmf.VanGenuchtenMualem())
# Use GreenAmpt infiltration from surface water
c.install_connection(cmf.GreenAmptInfiltration)
# Add a groundwater boundary condition
gw = p.NewOutlet('gw', 0, 0, -2)
# Use a free drainage connection to the groundwater
cmf.FreeDrainagePercolation(l, gw)
# Add some rainfall
c.set_rainfall(5.0)
# Make c.canopy a water storage
c.add_storage('Canopy', 'C')
# Split the rainfall from the rain source (RS) between
# intercepted rainfall (RS->canopy) and throughfall (RS-surface)
cmf.Rainfall(c.canopy, c, False, True) # RS->canopy, only intercepted rain
cmf.Rainfall(c.surfacewater, c, True, False) # RS->surface, only throughfall
# Use an overflow mechanism, eg. the famous Rutter-Interception Model
cmf.RutterInterception(c.canopy, c.surfacewater, c)
# And now the evaporation from the wet canopy (using a classical Penman equation)
cmf.CanopyStorageEvaporation(c.canopy, c.evaporation, c)
solver = cmf.CVodeIntegrator(p, 1e-9)
res = [l.volume for t in solver.run(solver.t, solver.t + cmf.day, cmf.min * 15)]
plt.figure()
plt.plot(res)
plt.show()
def __init__(self):
self.Params = [
Param("tr_first_out", 0., 300),
Param("tr_first_river", 0., 300),
Param("tr_first_second", 0., 300),
Param("tr_second_third", 0., 300),
Param("tr_second_river", 0., 300),
Param("tr_third_river", 0., 300),
Param("tr_river_out", 0., 300),
Param("beta_first_out", 0., 4),
Param("beta_first_river", 0., 4),
Param("beta_first_second", 0., 4),
Param("beta_second_river", 0., 4),
Param("beta_second_third", 0., 4),
Param("beta_third_river", 0., 4),
Param("beta_river_out", 0., 4),
Param("canopy_lai", 1., 10),
Param("canopy_closure", 0., 1.0),
Param("snow_meltrate", 0.1, 15.),
Param("snow_melt_temp", -5.0, 5.0),
Param("V0_first_out", 0., 200),
Param("V0_first_river", 0., 200),
Param("V0_first_second", 0., 200),
Param("ETV0", 0, 200),
Param("fETV0", 0., 0.85)
]
precipitation, temperature_avg, temperature_min, \
temperature_max, discharge = utils.load_data(
"observed_discharge.txt",
"temperature_max_min_avg.txt",
"precipitation.txt",
2976.41
)
self.Q = discharge
cmf.set_parallel_threads(1)
self.project = cmf.project()
project = self.project
cell = project.NewCell(0, 0, 0, 1000)
cell.add_storage("Snow", "S")
cmf.Snowfall(cell.snow, cell)
cell.add_layer(2.0)
cell.add_layer(5.0)
cell.add_layer(10.0)
cmf.HargreaveET(cell.layers[0], cell.transpiration)
self.outlet = project.NewOutlet("outlet", 10, 0, 0)
self.make_stations(precipitation, temperature_avg, temperature_min,
temperature_max)
self.river = cell.add_storage("River", "R")
self.canopy = cell.add_storage("Canopy", "C")
self.begin = datetime.datetime(1979, 1, 1)
self.end = datetime.datetime(1986, 12, 31)
def test_describe(self):
p = cmf.project()
c = p.NewCell(0, 0, 0, 1000, True)
p.meteo_stations.add_station('Giessen', (0, 0, 0))
c.add_layer(1.0)
text = cmf.describe(p).split('\n')
print('cmf.describe(project) returns {} lines'.format(len(text)))
self.assertGreaterEqual(len(text), 5)
def __init__(self):
self.p = cmf.project()
self.c = self.p.NewCell(0, 0, 0, 1000, with_surfacewater=True)
self.c.add_layer(1.0)
self.c: cmf.Cell
cmf.RutterInterception.use_for_cell(self.c)
self.et = cmf.ShuttleworthWallace.use_for_cell(self.c)
cmf.MatrixInfiltration(self.c.layers[0], self.c.surfacewater)
def __init__(self):
p = cmf.project('N DOC')
self.project = p
self.decompcell = self.cell_setup()
self.outlet = self.make_boundaries()
self.initialize()
self.decompcell.depose_litter(10000, 0)
def test_mesh_to_cells(obj_file_paths):
project = cmf.project()
hydrology.mesh_to_cells(project, [
obj_file_paths,
], False)
assert project
assert project.cells
def testState(self):
p = cmf.project('X Y Z')
X, Y, Z = p.solutes
ws = p.NewStorage('storage')
ws.volume = 1.0
ws[X].state = 1.0
ws.volume = 2.0
self.assertAlmostEqual(ws[X].conc, 0.5)
self.assertAlmostEqual(ws[X].state, 1.0)
self.assertAlmostEqual(ws[Y].conc, 0.0)
def __init__(self, dataprovider: DataProvider):
"""
Creates the basic structure of the model
"""
self.data = dataprovider
self.project = cmf.project()
self.cell: cmf.Cell = self.project.NewCell(0, 0, 0, 1000)
self.create_nodes()
self.data.add_stations(self.project)
self.create_connections(spotpy.parameter.create_set(self, 'optguess'))
def create_project(W0=0.9):
"""
Creates the cmf project with a single cell and one layer
:return:
"""
p = cmf.project()
c = p.NewCell(0, 0, 0, 1000, with_surfacewater=True)
l = c.add_layer(0.1)
c.set_rainfall(l.get_capacity())
si_con = cmf.SimpleInfiltration(l, c.surfacewater, W0)
return p, si_con
def __init__(self, climate_file='data/climate.csv'):
self.project = cmf.project()
self.cell = self.project.NewCell(0, 0, 0, 1000)
self.soil = self.cell.add_layer(1.0)
self.gw = self.cell.add_layer(1.0)
self.snow = self.cell.add_storage('Snow', 'S')
self.outlet = self.project.NewOutlet('outlet')
self.meteo, self.rainstation = load_climate_data(
self.project, climate_file)
def __init__(self,
subsurface_lateral_connection,
surface_lateral_connection=None,
layercount=0):
"""
Creates the cmf project
:param subsurface_lateral_connection: Type of lateral subsurface connection, eg. cmf.Darcy
:param surface_lateral_connection: Type of lateral surface flux connection, eg. cmf.KinematicSurfaceRunoff or None
:param layercount: Number of layers in the subsurface
:return:
"""
p = cmf.project()
shp = Shapefile('data/vollnkirchner_bach_cells.shp')
# Create cells
self.outlet_cells = []
for feature in shp:
# Create a cell for each feature in the shape file
c = cmf.geometry.create_cell(p,
feature.shape,
feature.HEIGHT,
feature.OID,
with_surfacewater=False)
# If it is an outlet feature, add cell to the list of outletcells
if feature.LANDUSE_CU.startswith('outlet'):
self.outlet_cells.append(c)
else:
# If it is a normal upload cell, add layers
self.build_cell(c, layercount)
# Build topology
cmf.geometry.mesh_project(p, verbose=True)
# Connect cells with fluxes
cmf.connect_cells_with_flux(p, subsurface_lateral_connection)
if surface_lateral_connection:
cmf.connect_cells_with_flux(p, surface_lateral_connection)
# Connect outlets with neighbor cells
for o_cell in self.outlet_cells:
self.connect_outlet_cell(o_cell, subsurface_lateral_connection,
surface_lateral_connection)
# Load driver data
load_meteo(p)
self.project = p
self.solver = cmf.CVodeIntegrator(p, 1e-9)
self.solver.t = p.meteo_stations[0].T.begin
def __init__(self, begin, end):
"""
Initialisiert das Modell und baut das Grundsetup zusammen
MP111 - Änderungsbedarf: Sehr groß, hier wird es Euer Modell definiert
Verständlichkeit: mittel
"""
# TODO: Parameterliste erweitern und anpassen.
# Wichtig: Die Namen müssen genau die gleichen sein,
# wie die Argumente in der Funktion setparameters.
#
# Parameter werden wie folgt definiert:
# param(<Name>,<Minimum>,<Maximum>)
self.params = [
param('tr', 0., 1000.),
param('ETV1', 0., 1000.),
param('Vr', 0., 1000.),
param('fETV0', 0., 1.),
param('beta', 0.3, 5.0)
]
# Lädt die Treiber Daten
P, T, Tmin, Tmax, Q = self.loadPETQ()
self.Q = Q
# Nutze nur einen Kern - für unser Modell ist das schneller
cmf.set_parallel_threads(1)
# Erzeuge ein Projekt mit einer Zelle für lumped Modell
self.project = cmf.project()
p = self.project
c = p.NewCell(0, 0, 0, 1000)
# Füge Speicher zur Zelle
l = c.add_layer(1.0)
# TODO: Weitere Layer / Speicher zur Zelle hinzufügen
# Verdunstung
cmf.HargreaveET(l, c.transpiration)
# Outlet
self.outlet = p.NewOutlet('outlet', 10, 0, 0)
# Regen
self.makestations(P, T, Tmin, Tmax)
self.project = p
self.begin = begin
self.end = end
def create_project(self):
"""
Creates and CMF project with an outlet and other basic stuff and
returns it.
:return: cmf project and cmf outlet
"""
# Use only a single thread, that is better for a calibration run and
# for small models
cmf.set_parallel_threads(1)
# make the project
p = cmf.project()
# make the outlet
outlet = p.NewOutlet("outlet", 10, 0, 0)
return p, outlet
def __init__(self, size, residence_time=1.0):
"""
Parameters
----------
size
residence_time
"""
self.project = p = cmf.project()
self.storages = []
self.outlet = p.NewOutlet('outlet', 0, 0, 0)
for i in range(1, size+1):
stor = p.NewStorage("S{}".format(i), i, 0, i)
if self.storages:
cmf.LinearStorageConnection(stor, self.storages[-1], residence_time / size)
else:
cmf.LinearStorageConnection(stor, self.outlet, residence_time / size)
self.storages.append(stor)
def __init__(self, begin: datetime.datetime, end: datetime.datetime,
subcatchment_names):
"""
:param begin:
:param end:
"""
project = cmf.project()
# Add outlet
self.outlet = project.NewOutlet("Outlet", 50, 0, 0)
self.project = project
self.begin = begin
self.end = end
self.subcatchment_names = subcatchment_names
self.dis_eval, self.subcatchments = self.load_data()
self.params = self.create_params()
self.cell_list = self.create_cells()
cmf.set_parallel_threads(1)
def first_simple_model():
import cmf
import datetime
p = cmf.project()
# Create W1 in project p
W1 = p.NewStorage(name="W1",x=0,y=0,z=0)
# Create W2 in project p without any volume as an initial state
W2 = p.NewStorage(name="W2",x=10,y=0,z=0)
# Create a linear storage equation from W1 to W2 with a residence time tr of one day
q = cmf.kinematic_wave(source=W1,target=W2,residencetime=1.0)
# Set the initial state of w1 to 1m³ of water.
W1.volume = 1.0
# Create Outlet
Out = p.NewOutlet(name="Outlet",x=20,y=0,z=0)
qout = cmf.kinematic_wave(source=W2,target=Out,residencetime=2.0)
# Create a Neumann Boundary condition connected to W1
In = cmf.NeumannBoundary.create(W1)
# Create a timeseries with daily alternating values.
In.flux = cmf.timeseries(begin = datetime.datetime(2012,1,1),
step = datetime.timedelta(days=1),
interpolationmethod = 0)
for i in range(10):
# Add 0.0 m3/day for even days, and 1.0 m3/day for odd days
In.flux.add(i % 2)
# Create an integrator for the ODE represented by project p, with an error tolerance of 1e-9
solver = cmf.RKFIntegrator(p,1e-9)
# Set the intitial time of the solver
solver.t = datetime.datetime(2012,1,1)
# Iterate the solver hourly through the time range and return for each time step the volume in W1 and W2
result = [[W1.volume,W2.volume] for t in solver.run(datetime.datetime(2012,1,1),datetime.datetime(2012,1,7),datetime.timedelta(hours=1))]
import pylab as plt
plt.plot(result)
plt.xlabel('hours')
plt.ylabel('Volume in $m^3$')
plt.legend(('W1','W2'))
plt.show()
def create_project(self):
"""
Creates the cmf project with its basic elements
"""
# Use only a single thread, that is better for a calibration run and for small models
cmf.set_parallel_threads(1)
# make the project
p = cmf.project()
# make a new cell
c = p.NewCell(0, 0, 0, 1000)
# Add a storage
layer = c.add_layer(1.0)
# ET
cmf.HargreaveET(layer, c.transpiration)
# Outlet
outlet = p.NewOutlet('outlet', 10, 0, 0)
return p, outlet
def run_model(folder: str) -> cmf.project:
"""
Runs the model with everything.
:return: Simulated CMF project
"""
# Initialize project
project = cmf.project()
(ground_list, mesh_paths, weather_dict, trees_dict, outputs,
solver_settings, boundary_dict) = load_cmf_files(folder, False)
# Add cells and properties to them
project, mesh_info = mesh_to_cells(project, mesh_paths)
for ground in ground_list:
configure_cells(project, ground, mesh_info[ground['mesh']])
if trees_dict:
for key in trees_dict.keys():
add_tree_to_project(project, trees_dict[key]['face_index'],
trees_dict[key]['property'])
# Create the weather
if weather_dict:
create_weather(project)
# Create boundary conditions
if boundary_dict:
create_boundary_conditions(project)
# Run solver
results = solve_project(project, solver_settings, outputs)
# Save the results
save_results(results, folder)
return project
def basic_model_setup():
"""
Creates the basic layout needed for every model structure.
:return: None
"""
# Basic Layout, same for all possible models
prec = data["prec"]
obs_discharge = data["discharge"]
t_mean = data["t_mean"]
t_min = data["t_min"]
t_max = data["t_max"]
self.obs_discharge = obs_discharge
# Use only one core (quicker for smaller models)
cmf.set_parallel_threads(1)
# Generate a project with one cell for a lumped model
self.project = cmf.project()
project = self.project
# Add one cell, which will include all other parts. The area is set
# to 1000 m², so the units are easier to understand
cell = project.NewCell(0, 0, 0, 1000)
# Add a first layer, this one is always present, as a model with no
# layers makes no sense
first_layer = cell.add_layer(2.0)
# Add an evapotranspiration
cmf.HargreaveET(first_layer, cell.transpiration)
# Create the CMF meteo and rain stations
weather_stations.make_stations(self.project, prec, t_mean, t_min,
t_max)
# Create an outlet
self.outlet = project.NewOutlet("outlet", 10, 0, 0)
def __init__(self,begin,end, with_valid_data = False, shift_one_day = False):
"""
Initializes the model and builds the core setup
begin: begin of the calibration period
eng: end of the calibration period
with_calib_data: save also the data from the validation period
the calibration is still only done form 'begin' to 'end'
"""
# tr_S = Residence time of the water in the soil to the GW
self.params = [param('tr_soil_GW',0.5,150.),
# tr_soil_river = residence time from soil to river
param("tr_soil_fulda", 0.5,55.),
# tr_surf = Residence time from surface
param('tr_surf',0.001,30),
# tr_GW_l = residence time in the lower groundwate
param('tr_GW_l',1.,1000.),
# tr_GW_u = Residence time in the upper groundwater to the river
param('tr_GW_u_fulda',1.,750.),
# tr_GW_u_GW_l = residencete time to GW_l from GW_u
param("tr_GW_u_GW_l", 10., 750.),
# tr_fulda = Residence time in the river (in days)
param('tr_fulda', 0., 3.5),
# V0_soil = field capacity for the soil
param('V0_soil',15.,350.),
# beta_P_soil = Exponent that changes the form of the flux from the soil
param('beta_soil_GW',0.5,3.2),
# beta_fulda = exponent that changes the form of the flux from the soil
param("beta_fulda", 0.3,4.),
# ETV1 = the Volume that defines that the evaporation is lowered because of not enough water
param('ETV1',0.,100.),
# fETV0 = factor the ET is multiplied with when water is low
param('fETV0',0.,0.25),
# Rate of snow melt
param('meltrate',0.15,10.),
# Snow_melt_temp = Temperature at which the snow melts (needed because of averaged temp
param('snow_melt_temp',-1.0,4.2) ,
# #Qd_max = maximal flux from lower groundwater to drinking water production
# param('Qd_max', 0.,3.),
# # tw_thresholt = amount of water that can't be slurped out by the water pumps
# param("TW_threshold", 0.,100.),
# LAI = leaf area index
param('LAI', 1.,12.),
# Canopy Closure
param("CanopyClosure",0.,0.5),
# Ksat = saturated conductivity of the soil
param("Ksat", 0., 1)
]
# loads the data
P,T,Tmin,Tmax,Q = self.loadPETQ()
self.Q=Q
# only use one core (quicker for small models)
cmf.set_parallel_threads(1)
# Generate a project with on ecell for a lumped model
self.project = cmf.project()
p = self.project
# Add cell for soil and so on (x,y,z,area)
c = p.NewCell(0,0,0,1000)
# Add snow storage
c.add_storage('Snow','S')
cmf.Snowfall(c.snow,c)
# Surfacewater is treated as a storage
c.surfacewater_as_storage()
# Add the soil and groundwater layers to the soil cell
soil = c.add_layer(2.0)
gw_upper = c.add_layer(5.0)
gw_lower = c.add_layer(20.0)
# Fill storages
c.layers[0].volume = 15
c.layers[1].volume = 80
c.layers[2].volume = 120
# Evapotranspiration
cmf.HargreaveET(soil,c.transpiration)
#cmf.PenmanMonteith()
# Add the Fulda River
self.fulda = p.NewOpenStorage(name="Fulda",x=0,y=0,z=0, area = 3.3*10**6)
# Giving the Fulda a mean depth
self.fulda.potential = 1.5
# add the drinking water outlet
# self.trinkwasser = p.NewOutlet('trinkwasser',20,0,0)
# Outlet
self.outlet = p.NewOutlet('outlet',10,0,0)
# Storage for the interception
I=c.add_storage('Canopy','C')
# Rain
self.makestations(P,T,Tmin,Tmax)
self.project = p
self.begin = begin
self.end = end
self.with_valid_data = with_valid_data
self.shift_one_day = shift_one_day
def _run(self,alpha=None,n=None,porosity=None,ksat=None):
#return alpha,n,porosity,ksat
'''
Runs the model instance
Input: Parameter set (in this case VAN-Genuchten Parameter alpha,n,porosity,ksat)
Output: Simulated values on given observation days
'''
#Check if given parameter set is in realistic boundaries
if alpha<self.bound[0][0] or alpha>self.bound[0][1] or ksat<self.bound[1][0] \
or ksat>self.bound[1][1] or n<self.bound[2][0] or n>self.bound[2][1] or \
porosity<self.bound[3][0] or porosity>self.bound[3][1]:
print('The following combination was ignored')
text='n= '+str(n)
print(text)
text='alpha='+str(alpha)
print(text)
text='ksat= '+str(ksat)
print(text)
text='porosity= '+str(porosity)
print(text)
print('##############################')
return self.observations*-np.inf
else:
project=cmf.project()
cell = project.NewCell(x=0,y=0,z=0,area=1000, with_surfacewater=True)
text='n= '+str(n)
print(text)
text='alpha='+str(alpha)
print(text)
text='ksat= '+str(ksat)
print(text)
text='porosity= '+str(porosity)
print(text)
print('##############################')
r_curve = cmf.VanGenuchtenMualem(Ksat=ksat,phi=porosity,alpha=alpha,n=n)
layers=5
ldepth=.01
for i in range(layers):
depth = (i+1) * ldepth
cell.add_layer(depth,r_curve)
cell.install_connection(cmf.Richards)
cell.install_connection(cmf.ShuttleworthWallace)
cell.saturated_depth =.5
solver = cmf.CVodeIntegrator(project,1e-6)
self._load_meteo(project)
gw = project.NewOutlet('groundwater',x=0,y=0,z=.9)#layers*ldepth)
cmf.Richards(cell.layers[-1],gw)
gw.potential = -.5 #IMPORTANT
gw.is_source=True
solver.t = self.datastart
Evalstep,evallist=0,[]
rundays=(self.dataend-self.datastart).days
for t in solver.run(solver.t,solver.t + timedelta(days=rundays),timedelta(hours=1)):
if self.gw_array['Date'].__contains__(t)==True:
Gw_Index=np.where(self.gw_array['Date']==t)
gw.potential=self.gw_array[self.piezometer][Gw_Index]
print(gw.potential) #TO DO: CHECK IF SOMETHING HAPPENS HERE!!!!
if t > self.analysestart:
if Evalstep !=len(self.eval_dates) and t == self.eval_dates[Evalstep]:
evallist.append(cell.layers.wetness[0]*cell.layers.porosity[0]*100)
Evalstep+=1
return evallist
def simple1D():
from matplotlib import pyplot as plt
import cmf
from datetime import datetime, timedelta
project = cmf.project()
# Add one cell at position (0,0,0), Area=1000m2
cell = project.NewCell(0, 0, 0, 1000, with_surfacewater=True)
# Create a retention curve
r_curve = cmf.VanGenuchtenMualem(Ksat=1, phi=0.5, alpha=0.01, n=2.0)
# Add ten layers of 10cm thickness
for i in range(10):
depth = (i + 1) * 0.1
cell.add_layer(depth, r_curve)
# Connect layers with Richards perc.
# this can be shorten as
cell.install_connection(cmf.Richards)
# Create solver
solver = cmf.CVodeIntegrator(project, 1e-6)
solver.t = cmf.Time(1, 1, 2011)
# Create groundwater boundary (uncomment to use it)
# Create the boundary condition
gw = project.NewOutlet('groundwater', x=0, y=0, z=-1.1)
# Set the potential
gw.potential = -2
# Connect the lowest layer to the groundwater using Richards percolation
gw_flux=cmf.Richards(cell.layers[-1],gw)
# Set inital conditions
# Set all layers to a potential of -2 m
cell.saturated_depth = 2.
# 100 mm water in the surface water storage
cell.surfacewater.depth = 0.1
# The run time loop, run for 72 hours
# Save potential and soil moisture for each layer
potential = [cell.layers.potential]
moisture = [cell.layers.theta]
for t in solver.run(solver.t, solver.t + timedelta(days=7), timedelta(hours=1)):
potential.append(cell.layers.potential)
moisture.append(cell.layers.theta)
"""
# Plot results
plt.subplot(211)
plt.plot(moisture)
plt.ylabel(r'Soil moisture $\theta [m^3/m^3]$')
plt.xlabel(r'$time [h]$')
plt.grid()
plt.subplot(212)
plt.plot(potential)
plt.ylabel(r'Water head $\Psi_{tot} [m]$')
plt.xlabel(r'$time [h]$')
plt.grid()
plt.show()
"""
print(cell.vegetation)
cmf.RutterInterception(c.canopy, c.surfacewater, c)
# And now the evaporation from the wet canopy (using a classical Penman equation)
cmf.CanopyStorageEvaporation(c.canopy, c.evaporation, c)
solver = cmf.CVodeIntegrator(p, 1e-9)
res = [l.volume for t in solver.run(solver.t, solver.t + cmf.day, cmf.min * 15)]
plt.figure()
plt.plot(res)
plt.show()
#canopyStorage()
#----------------------------------------------------------------------------------------------------------------------#
import cmf
import numpy as np
from datetime import datetime,timedelta
# Create a project
project = cmf.project()
print('rain stations', project.rainfall_stations)
# Create a timeseries, starting Jan 1st, 2010 with 1h step, with random data
raindata = cmf.timeseries.from_array(datetime(2010,1,1), timedelta(hours=1), np.random.uniform(0,30,24*365))
# Add a rainfall station to the project
rainstation = project.rainfall_stations.add(Name='Random station',
Data=raindata,
Position=(0,0,0))
print('rain stations', project.rainfall_stations)
def __init__(self, begin, end):
"""Initializes the model and build the core setup"""
# tr_soil_GW = Residence time of the water in the soil to the GW
self.params = [
spotpy.parameter.List("tr_soil_gw",
[361.95603672540824, 361.95603672540824]),
spotpy.parameter.List("tr_soil_out",
[86.36633856546166, 86.36633856546166]),
spotpy.parameter.List("tr_gw_out",
[81.8626412596028, 81.8626412596028]),
spotpy.parameter.List("V0_soil",
[291.9533350694828, 291.9533350694828]),
spotpy.parameter.List("beta_soil_gw",
[2.1866023626527475, 2.1866023626527475]),
spotpy.parameter.List("beta_soil_out", [0.2, 0.2]),
spotpy.parameter.List("ETV1",
[101.66837396299148, 101.66837396299148]),
spotpy.parameter.List("fETV0",
[0.4727208059864018, 0.4727208059864018]),
# spotpy.parameter.List("meltrate",
# [7.609473369272333,
# 7.609473369272333]),
# spotpy.parameter.List("snow_melt_temp",
# [2.887783422377442,
# 2.887783422377442]),
spotpy.parameter.List("LAI", [4.865867934808, 4.865867934808]),
spotpy.parameter.List("CanopyClosure",
[0.1924997461816065, 0.1924997461816065]),
]
self.begin = begin
self.end = end
# load the weather data and discharge data
prec, temp, temp_min, temp_max, Q, = self.loadPETQ()
self.Q = Q
# use only one core (faster when model is small
cmf.set_parallel_threads(1)
# Generate a cmf project with one cell for a lumped model
self.project = cmf.project()
p = self.project
# Create a cell in the projectl_evapotranspiration
c = p.NewCell(0, 0, 0, 1000, True)
# # Add snow storage
# c.add_storage("Snow", "S")
# cmf.Snowfall(c.snow, c)
# Add the soil and groundwater layers
soil = c.add_layer(2.0)
gw_upper = c.add_layer(5.0)
# Give the storages a initial volume
soil.volume = 15
gw_upper.volume = 80
# Create a storage for Interception
I = c.add_storage("Canopy", "C")
# Install a calculation of the evaporation
cmf.HargreaveET(soil, c.transpiration)
# Create an outlet
self.outlet = p.NewOutlet("outlet", 10, 0, 0)
# Create the meteo stations
self.make_stations(prec, temp, temp_min, temp_max)
self.project = p
