def test_mflist_reference():
import os
import numpy as np
import shapefile
import flopy.modflow as fmf
# model_ws = os.path.join('..', 'data', 'freyberg')
# ml = fmf.Modflow.load('freyberg.nam', model_ws=model_ws)
# make the model
ml = fmf.Modflow()
assert isinstance(ml, fmf.Modflow)
perlen = np.arange(1, 20, 1)
nstp = np.flipud(perlen) + 3
tsmult = 1.2
nlay = 10
nrow, ncol = 50, 40
botm = np.arange(0, -100, -10)
hk = np.random.random((nrow, ncol))
dis = fmf.ModflowDis(ml,
delr=100.0,
delc=100.0,
nrow=nrow,
ncol=ncol,
nlay=nlay,
nper=perlen.shape[0],
perlen=perlen,
nstp=nstp,
tsmult=tsmult,
top=10,
botm=botm,
steady=False)
assert isinstance(dis, fmf.ModflowDis)
lpf = fmf.ModflowLpf(ml, hk=hk, vka=10.0, laytyp=1)
assert isinstance(lpf, fmf.ModflowLpf)
pcg = fmf.ModflowPcg(ml)
assert isinstance(pcg, fmf.ModflowPcg)
oc = fmf.ModflowOc(ml)
assert isinstance(oc, fmf.ModflowOc)
ibound = np.ones((nrow, ncol))
ibound[:, 0] = -1
ibound[25:30, 30:39] = 0
bas = fmf.ModflowBas(ml, strt=5.0, ibound=ibound)
assert isinstance(bas, fmf.ModflowBas)
rch = fmf.ModflowRch(ml, rech={0: 0.00001, 5: 0.0001, 6: 0.0})
assert isinstance(rch, fmf.ModflowRch)
wel_dict = {}
wel_data = [[9, 25, 20, -200], [0, 0, 0, -400], [5, 20, 32, 500]]
wel_dict[0] = wel_data
wel_data2 = [[45, 20, 200], [9, 49, 39, 400], [5, 20, 32, 500]]
wel_dict[10] = wel_data2
wel = fmf.ModflowWel(ml, stress_period_data={0: wel_data})
assert isinstance(wel, fmf.ModflowWel)
ghb_dict = {0: [1, 10, 10, 400, 300]}
ghb = fmf.ModflowGhb(ml, stress_period_data=ghb_dict)
assert isinstance(ghb, fmf.ModflowGhb)
test = os.path.join('temp', 'test3.shp')
ml.export(test, kper=0)
shp = shapefile.Reader(test)
assert shp.numRecords == nrow * ncol
def pcg(self):
pcg = flomf.ModflowPcg(self.mf,
mxiter=60,
iter1=20,
hclose=1,
rclose=1)
return pcg
# [-1., 1., 1., ..., 1., 1., -1.], # [-1., -1., -1., ..., -1., -1., -1.]]]) # set center cell in upper layer to constant head (-1) ibound[0, Nhalf, Nhalf] = -1 # defining the start-values # in the calculation only the -1 cells will be considered # # all values are set to h1 start = h1 * np.ones((N, N)) # and the center value is set to h2 start[Nhalf, Nhalf] = h2 # instantiate the modflow-basic package with iBound and startvalues bas = mf.ModflowBas(ml, ibound=ibound, strt=start) # set the aquifer properties with the lpf-package lpf = mf.ModflowLpf(ml, hk=k) # instantiation of the solver with default values pcg = mf.ModflowPcg(ml) # instantiation of the output control with default values oc = mf.ModflowOc(ml) rch = mf.ModflowRch(ml) ml.write_input() ml.run_model()
def get_package(self, _mf):
content = self.merge()
return mf.ModflowPcg(
_mf,
**content
)
def create_package(self, name, content):
if name == 'mf':
model_ws = os.path.realpath(os.path.join(self._data_folder, self._model_id, content['model_ws']))
if not os.path.exists(model_ws):
os.makedirs(model_ws)
self._mf = mf.Modflow(
modelname=content['modelname'],
exe_name=content['exe_name'],
version=content['version'],
model_ws=model_ws
)
if name == 'dis':
mf.ModflowDis(
self._mf,
nlay=content['nlay'],
nrow=content['nrow'],
ncol=content['ncol'],
nper=content['nper'],
delr=content['delr'],
delc=content['delc'],
laycbd=content['laycbd'],
top=content['top'],
botm=content['botm'],
perlen=content['perlen'],
nstp=content['nstp'],
tsmult=content['tsmult'],
steady=content['steady'],
itmuni=content['itmuni'],
lenuni=content['lenuni'],
extension=content['extension'],
unitnumber=content['unitnumber'],
xul=content['xul'],
yul=content['yul'],
rotation=content['rotation'],
proj4_str=content['proj4_str'],
start_datetime=content['start_datetime']
)
if name == 'bas':
mf.ModflowBas(
self._mf,
ibound=content['ibound'],
strt=content['strt'],
ifrefm=content['ifrefm'],
ixsec=content['ixsec'],
ichflg=content['ichflg'],
stoper=content['stoper'],
hnoflo=content['hnoflo'],
extension=content['extension'],
unitnumber=content['unitnumber']
)
if name == 'lpf':
mf.ModflowLpf(
self._mf,
laytyp=content['laytyp'],
layavg=content['layavg'],
chani=content['chani'],
layvka=content['layvka'],
laywet=content['laywet'],
ipakcb=content['ipakcb'],
hdry=content['hdry'],
iwdflg=content['iwdflg'],
wetfct=content['wetfct'],
iwetit=content['iwetit'],
ihdwet=content['ihdwet'],
hk=content['hk'],
hani=content['hani'],
vka=content['vka'],
ss=content['ss'],
sy=content['sy'],
vkcb=content['vkcb'],
wetdry=content['wetdry'],
storagecoefficient=content['storagecoefficient'],
constantcv=content['constantcv'],
thickstrt=content['thickstrt'],
nocvcorrection=content['nocvcorrection'],
novfc=content['novfc'],
extension=content['extension'],
unitnumber=content['unitnumber']
)
if name == 'pcg':
mf.ModflowPcg(
self._mf,
mxiter=content['mxiter'],
iter1=content['iter1'],
npcond=content['npcond'],
hclose=content['hclose'],
rclose=content['rclose'],
relax=content['relax'],
nbpol=content['nbpol'],
iprpcg=content['iprpcg'],
mutpcg=content['mutpcg'],
damp=content['damp'],
dampt=content['dampt'],
ihcofadd=content['ihcofadd'],
extension=content['extension'],
unitnumber=content['unitnumber']
)
if name == 'oc':
mf.ModflowOc(
self._mf,
ihedfm=content['ihedfm'],
iddnfm=content['iddnfm'],
chedfm=content['chedfm'],
cddnfm=content['cddnfm'],
cboufm=content['cboufm'],
compact=content['compact'],
stress_period_data=self.get_stress_period_data(content['stress_period_data']),
extension=content['extension'],
unitnumber=content['unitnumber']
)
if name == 'risdlkfjlv':
mf.ModflowRiv(
self._mf,
ipakcb=content['ipakcb'],
stress_period_data=content['stress_period_data'],
dtype=content['dtype'],
extension=content['extension'],
unitnumber=content['unitnumber'],
options=content['options'],
naux=content['naux']
)
if name == 'wel':
mf.ModflowWel(
self._mf,
ipakcb=content['ipakcb'],
stress_period_data=content['stress_period_data'],
dtype=content['dtype'],
extension=content['extension'],
unitnumber=content['unitnumber'],
options=content['options']
)
if name == 'rch':
mf.ModflowRch(
self._mf,
ipakcb=content['ipakcb'],
nrchop=content['nrchop'],
rech=content['rech'],
extension=content['extension'],
unitnumber=content['unitnumber']
)
if name == 'chd':
mf.ModflowChd(
self._mf,
stress_period_data=content['stress_period_data'],
dtype=content['dtype'],
options=content['options'],
extension=content['extension'],
unitnumber=content['unitnumber']
)
if name == 'ghb':
mf.ModflowGhb(
self._mf,
ipakcb=content['ipakcb'],
stress_period_data=content['stress_period_data'],
dtype=content['dtype'],
options=content['options'],
extension=content['extension'],
unitnumber=content['unitnumber']
)
(nrow, ncol)
) # in the calculation only the -1 cells will be considered (all values can be set to 0)
bas = mf.ModflowBas(m, ibound=ibound, strt=strt)
# setting up recharge data and recharge package
recharge_data = 0.250 # recharge flux mm/year (default is 1.e-3)
nrchop = 1 # optional code (1: to top grid layer only; 2: to layer defined in irch 3: to highest active cell)
rch = mf.ModflowRch(m, nrchop=nrchop, rech=recharge_data)
# setting up the well package with stress periods
pumping_rate = -4e+10 # m^3 / year
lrcq = {0: [[0, 5, 6, 0.]], 1: [[0, 5, 6, -4e+10]]}
wel = mf.ModflowWel(m, stress_period_data=lrcq)
# instantiation of the solver with default values
pcg = mf.ModflowPcg(m) # pre-conjugate gradient solver
# instantiation of the output control with default values
oc = mf.ModflowOc(m) # output control
timeStartWritingInput = datetime.now()
ml.write_input()
timeStartRunningModel = datetime.now()
ml.run_model()
timeEndRunningModel = datetime.now()
print "Time writing input: " + str(timeStartRunningModel -
timeStartWritingInput)
print "Calculation Time: " + str(timeEndRunningModel - timeStartRunningModel)
if os.path.exists(workspace):
shutil.rmtree(workspace)
well_LRCQ_list = create_LRCQ_list(
well_obj_list,
grid_obj) # Set the settings of the wells for that timestep
ssm_data = create_conc_list(well_obj_list, attrib='T_inj')
'''Initialize MODFLOW Packages'''
bas = mf.ModflowBas(ml, ibound=grid_obj.IBOUND,
strt=grid_obj.head) # Basemodel Modflow
wel = mf.ModflowWel(ml, stress_period_data=well_LRCQ_list) # Put in Wells
words = ['head', 'drawdown', 'budget', 'phead', 'pbudget']
save_head_every = 1
#oc = mf.ModflowOc(ml) # Output control package class --> moved (p3.7 iso p3.6)
pcg = mf.ModflowPcg(
ml,
mxiter=200,
iter1=200,
npcond=
1, # Preconditioned Conjugate-Gradient Package --> solves the finite differences equations
hclose=0.001,
rclose=0.001,
relax=1.0,
nbpol=0)
ml.write_input()
'''Initialize MT3DMS packages'''
mt = mt3.Mt3dms(name,
'nam_mt3dms',
exe_name=swtexe_name,
modflowmodel=ml,
model_ws=dirs[0])
adv = mt3.Mt3dAdv(
mt,
mixelm=0,
percel=0.8,
# --create model file and run model
modelname = 'swi2ex5'
mf_name = 'mf2005'
if not skipRuns:
ml = mf.Modflow(modelname, version='mf2005', exe_name=mf_name, model_ws=dirs[0])
discret = mf.ModflowDis(ml, nrow=nrow, ncol=ncol, nlay=nlay, delr=delr, delc=delc,
top=0, botm=bot, laycbd=0, nper=nper,
perlen=perlen, nstp=nstp, steady=steady)
bas = mf.ModflowBas(ml, ibound=ibound, strt=ihead)
lpf = mf.ModflowLpf(ml, hk=kh, vka=kv, ss=ss, sy=ssz, vkcb=0, laytyp=0, layavg=1)
wel = mf.ModflowWel(ml, stress_period_data=well_data)
swi = mf.ModflowSwi2(ml, npln=1, istrat=1, toeslope=0.025, tipslope=0.025, nu=[0, 0.025], \
zeta=z, ssz=ssz, isource=isource, nsolver=2, solver2params=solver2params)
oc = mf.ModflowOc(ml, words=savewords)
pcg = mf.ModflowPcg(ml, hclose=1.0e-6, rclose=3.0e-3, mxiter=100, iter1=50)
# --write the modflow files
ml.write_input()
m = ml.run_model(silent=False)
# --read model zeta
get_stp = [364, 729, 1094, 1459, 364, 729, 1094, 1459]
get_per = [0, 0, 0, 0, 1, 1, 1, 1]
nswi_times = len(get_per)
zetafile = os.path.join(dirs[0], '{}.zta'.format(modelname))
zobj = fu.CellBudgetFile(zetafile)
zeta = []
for kk in zip(get_stp, get_per):
zeta.append(zobj.get_data(kstpkper=kk, text=' ZETASRF 1')[0])
zeta = np.array(zeta)
def run_experiment(self, experiment):
'''
Method for running an instantiated model structure.
This method should always be implemented.
:param case: keyword arguments for running the model. The case is a
dict with the names of the uncertainties as key, and
the values to which to set these uncertainties.
'''
#NetLogo agent attributes to be passed to Python well objects
#when new wells are created in NetLogo
nl_read_sys_attribs = ['who', 'xcor', 'ycor']
nl_read_well_attribs = [
'who', 'xcor', 'ycor', 'IsCold', 'z0', 'FilterLength', 'T_inj', 'Q'
]
#NetLogo agent attributes to be updated by the Python objects after each period
nl_update_well_attribs = ['T_modflow', 'H_modflow']
nl_update_globals = ['ztop', 'Laquifer']
self.netlogo.command('setup')
for key, value in experiment.items():
if key in self.NetLogo_uncertainties:
try:
self.netlogo.command(self.command_format.format(
key, value))
except jpype.JavaException as e:
warning('Variable {0} throws exception: {}'.format(
(key, str(e))))
logging.debug(self.netlogo.report(str(key)))
if key in self.SEAWAT_uncertainties:
setattr(self, key, value)
#Set policy parameters if present
if self.policy:
for key, value in self.policy.items():
if (key in self.NetLogo_uncertainties and key != 'name'):
self.netlogo.command(self.command_format.format(
key, value))
elif key in self.SEAWAT_uncertainties:
setattr(self, key, value)
logging.info('Policy parameters set successfully')
#Update NetLogo globals from input parameters
for var in nl_update_globals:
self.netlogo.command(
self.command_format.format(var, getattr(self, var)))
#Run the NetLogo setup routine, creating the agents
#Create lists of Python objects based on the NetLogo agents
self.netlogo.command('init-agents')
sys_obj_list = update_runtime_objectlist(self.netlogo, [],
nl_read_sys_attribs,
breed='system',
objclass=PySystem)
well_obj_list, newgrid_flag = update_runtime_objectlist(
self.netlogo, [],
nl_read_well_attribs,
breed='well',
objclass=PyWell)
#Assign values for uncertain NetLogo parameters
logging.info('NetLogo parameters set successfully')
#self.netlogo.command('init-agents')
#Calculate geohydrological parameters linked to variable inputs
rho_b = self.rho_solid * (1 - self.PEFF)
kT_b = self.kT_s * (1 - self.PEFF) + self.kT_f * self.PEFF
dmcoef = kT_b / (self.PEFF * self.rho_f * self.Cp_f) * 24 * 3600
trpt = self.al * self.trp_mult
trpv = trpt
#Initialize PyGrid object
itype = mt3.Mt3dSsm.itype_dict()
grid_obj = PyGrid()
grid_obj.make_grid(well_obj_list,
dmin=self.dmin,
dmax=self.dmax,
dz=self.dz,
ztop=self.ztop,
zbot=self.zbot,
nstep=self.nstep,
grid_extents=self.grid_extents)
#Initial arrays for grid values (temperature, head) - for this case, assumes no groundwater flow
#and uniform temperature
grid_obj.ncol = len(grid_obj.XGR) - 1
grid_obj.delr = np.diff(grid_obj.XGR)
grid_obj.nrow = len(grid_obj.YGR) - 1
grid_obj.delc = -np.diff(grid_obj.YGR)
grid_obj.top = self.ztop * np.ones([grid_obj.nrow, grid_obj.ncol])
botm_range = np.arange(self.zbot, self.ztop, self.dz)[::-1]
botm_2d = np.ones([grid_obj.nrow, grid_obj.ncol])
grid_obj.botm = botm_2d * botm_range[:, None, None]
grid_obj.nlay = len(botm_range)
grid_obj.IBOUND, grid_obj.ICBUND = boundaries(
grid_obj) #Create grid boundaries
#Initial arrays for grid values (temperature, head)
init_grid = np.ones((grid_obj.nlay, grid_obj.nrow, grid_obj.ncol))
grid_obj.temp = 10. * init_grid
grid_obj.HK = self.HK * init_grid
grid_obj.VK = self.VK * init_grid
#Set initial heads according to groundwater flow (based on mfLab Utrecht model)
y_array = np.array([(grid_obj.YGR[:-1] - np.mean(grid_obj.YGR[:-1])) *
self.PEFF * -self.gwflow_y / 365 / self.HK])
y_tile = np.array([np.tile(y_array.T, (1, grid_obj.ncol))])
x_array = (grid_obj.XGR[:-1] - np.mean(
grid_obj.XGR[:-1])) * self.PEFF * -self.gwflow_x / 365 / self.HK
y_tile += x_array
grid_obj.head = np.tile(y_tile, (grid_obj.nlay, 1, 1))
#Set times at which to read SEAWAT output for each simulation period
timprs = np.array([self.perlen])
nprs = len(timprs)
logging.info('SEAWAT parameters set successfully')
#Iterate the coupled model
for period in range(self.run_length):
#Set up the text output from NetLogo
commands = []
self.fns = {}
for outcome in self.outcomes:
#if outcome.time:
name = outcome.name
fn = r'{0}{3}{1}{2}'.format(self._working_directory, name,
'.txt', os.sep)
self.fns[name] = fn
fn = '"{}"'.format(fn)
fn = fn.replace(os.sep, '/')
if self.netlogo.report('is-agentset? {}'.format(name)):
#If name is name of an agentset, we
#assume that we should count the total number of agents
nc = r'{2} {0} {3} {4} {1}'.format(fn, name, 'file-open',
'file-write', 'count')
else:
#It is not an agentset, so assume that it is
#a reporter / global variable
nc = r'{2} {0} {3} {1}'.format(fn, name, 'file-open',
'file-write')
commands.append(nc)
c_out = ' '.join(commands)
self.netlogo.command(c_out)
logging.info(' -- Simulating period {0} of {1}'.format(
period, self.run_length))
#Run the NetLogo model for one tick
self.netlogo.command('go')
logging.debug('NetLogo step completed')
#Create placeholder well list - required for MODFLOW WEL package if no wells active in NetLogo
well_LRCQ_list = {}
well_LRCQ_list[0] = [[0, 0, 0, 0]]
ssm_data = {}
ssm_data[0] = [[0, 0, 0, 0, itype['WEL']]]
#Check the well agents which are active in NetLogo, and update the Python objects if required
#The newgrid_flag indicates whether or not the grid should be recalculated to account for changes
#in the list of active wells
if well_obj_list:
well_obj_list, newgrid_flag = update_runtime_objectlist(
self.netlogo, well_obj_list, nl_read_well_attribs)
if well_obj_list and newgrid_flag:
#If the list of active wells has changed and if there are active wells, create a new grid object
newgrid_obj = PyGrid()
newgrid_obj.make_grid(well_obj_list,
dmin=self.dmin,
dmax=self.dmax,
dz=self.dz,
ztop=self.ztop,
zbot=self.zbot,
nstep=self.nstep,
grid_extents=self.grid_extents)
#Interpolate the temperature and head arrays to match the new grid
newgrid_obj.temp = grid_interpolate(grid_obj.temp[0, :, :],
grid_obj, newgrid_obj)
newgrid_obj.head = grid_interpolate(grid_obj.head[0, :, :],
grid_obj, newgrid_obj)
#Use the new simulation grid
grid_obj = newgrid_obj
logging.debug('Python update completed')
if well_obj_list:
for i in well_obj_list:
#Read well flows from NetLogo and locate each well in the simulation grid
i.Q = read_NetLogo_attrib(self.netlogo, 'Q', i.who)
i.calc_LRC(grid_obj)
#Create well and temperature lists following MODFLOW/MT3DMS format
well_LRCQ_list = create_LRCQ_list(well_obj_list, grid_obj)
ssm_data = create_conc_list(well_obj_list)
#Initialize MODFLOW packages using FloPy
#ml = mf.Modflow(self.name, version='mf2005', exe_name=self.swtexe_name, model_ws=self.dirs[0])
swtm = swt.Seawat(self.name,
exe_name=self.swtexe_name,
model_ws=self.dirs[0])
discret = mf.ModflowDis(swtm,
nrow=grid_obj.nrow,
ncol=grid_obj.ncol,
nlay=grid_obj.nlay,
delr=grid_obj.delr,
delc=grid_obj.delc,
laycbd=0,
top=self.ztop,
botm=self.zbot,
nper=self.nper,
perlen=self.perlen,
nstp=self.nstp,
steady=self.steady)
bas = mf.ModflowBas(swtm,
ibound=grid_obj.IBOUND,
strt=grid_obj.head)
lpf = mf.ModflowLpf(swtm,
hk=self.HK,
vka=self.VK,
ss=0.0,
sy=0.0,
laytyp=0,
layavg=0)
wel = mf.ModflowWel(swtm, stress_period_data=well_LRCQ_list)
words = ['head', 'drawdown', 'budget', 'phead', 'pbudget']
save_head_every = 1
oc = mf.ModflowOc(swtm)
pcg = mf.ModflowPcg(swtm,
mxiter=200,
iter1=200,
npcond=1,
hclose=0.001,
rclose=0.001,
relax=1.0,
nbpol=0)
#ml.write_input()
#Initialize MT3DMS packages
#mt = mt3.Mt3dms(self.name, 'nam_mt3dms', modflowmodel=ml, model_ws=self.dirs[0])
adv = mt3.Mt3dAdv(
swtm,
mixelm=0, #-1 is TVD
percel=1,
nadvfd=1,
#Particle based methods
nplane=0,
mxpart=250000,
itrack=3,
dceps=1e-4,
npl=5,
nph=8,
npmin=1,
npmax=16)
btn = mt3.Mt3dBtn(swtm,
cinact=-100.,
icbund=grid_obj.ICBUND,
prsity=self.PEFF,
sconc=[grid_obj.temp][0],
ifmtcn=-1,
chkmas=False,
nprobs=0,
nprmas=1,
dt0=0.0,
ttsmult=1.5,
ttsmax=20000.,
ncomp=1,
nprs=nprs,
timprs=timprs,
mxstrn=9999)
dsp = mt3.Mt3dDsp(swtm,
al=self.al,
trpt=trpt,
trpv=trpv,
dmcoef=dmcoef)
rct = mt3.Mt3dRct(swtm, isothm=0, ireact=0, igetsc=0, rhob=rho_b)
gcg = mt3.Mt3dGcg(swtm,
mxiter=50,
iter1=50,
isolve=1,
cclose=1e-3,
iprgcg=0)
ssm = mt3.Mt3dSsm(swtm, stress_period_data=ssm_data)
#mt.write_input()
#Initialize SEAWAT packages
# mswtf = swt.Seawat(self.name, 'nam_swt', modflowmodel=ml, mt3dmsmodel=mt,
# model_ws=self.dirs[0])
swtm.write_input()
#Run SEAWAT
#m = mswtf.run_model(silent=True)
m = swtm.run_model(silent=True)
logging.debug('SEAWAT step completed')
#Copy Modflow/MT3DMS output to new files
shutil.copyfile(
os.path.join(self.dirs[0], self.name + '.hds'),
os.path.join(self.dirs[0], self.name + str(period) + '.hds'))
shutil.copyfile(
os.path.join(self.dirs[0], 'MT3D001.UCN'),
os.path.join(self.dirs[0], self.name + str(period) + '.UCN'))
#Create head file object and read head array for next simulation period
h_obj = bf.HeadFile(
os.path.join(self.dirs[0], self.name + str(period) + '.hds'))
grid_obj.head = h_obj.get_data(totim=self.perlen)
#Create concentration file object and read temperature array for next simulation period
t_obj = bf.UcnFile(
os.path.join(self.dirs[0], self.name + str(period) + '.UCN'))
grid_obj.temp = t_obj.get_data(totim=self.perlen)
logging.debug('Output processed')
if well_obj_list:
for i in well_obj_list:
#Update each active Python well object with the temperature and head at its grid location
i.T_modflow = grid_obj.temp[i.L[0], i.R, i.C]
i.H_modflow = grid_obj.head[i.L[0], i.R, i.C]
#Update the NetLogo agents from the corresponding Python objects
write_NetLogo_attriblist(self.netlogo, well_obj_list,
nl_update_well_attribs)
#As an example of data exchange, we can calculate the fraction of the simulated grid in which
#the temperature change is significant, and send this value to a NetLogo global variable
use = subsurface_use(grid_obj, grid_obj.temp)
write_NetLogo_global(self.netlogo, 'SubsurfaceUse', use)
logging.debug('NetLogo update completed')
h_obj.file.close()
t_obj.file.close()
self.netlogo.command('file-close-all')
self._handle_outcomes()
botm=bot,
laycbd=0)
Nhalf = (N - 1) / 2
ibound = np.ones((Nlay, N, N))
ibound[:, 0, :] = -1
ibound[:, -1, :] = -1
ibound[:, :, 0] = -1
ibound[:, :, -1] = -1
ibound[0, Nhalf, Nhalf] = -1
start = h1 * np.ones((N, N))
start[Nhalf, Nhalf] = h2
bas = fmf.ModflowBas(ml, ibound=ibound, strt=start)
print "o"
lpf = fmf.ModflowLpf(ml, hk=k)
pcg = fmf.ModflowPcg(ml)
oc = fmf.ModflowOc(ml)
ml.write_input()
ml.run_model()
head_file = '/home/kiruba/PycharmProjects/area_of_curve/hydrology/hydrology/mf_files/lake_example.hds'
hds = fut.HeadFile(head_file)
h = hds.get_data(kstpkper=(1, 1))
print len(h)
x = y = np.linspace(0, L, N)
c = plt.contour(x, y, h[0], np.arange(90, 100.1, 0.2))
plt.clabel(c, fmt='%2.1f')
plt.axis('scaled')
plt.show()
c = plt.contour(x, y, h[-1], np.arange(90, 100.1, 0.2))
plt.clabel(c, fmt='%1.1f')
def calculate_model(z1_hk, z2_hk, z3_hk):
# Z1_hk = 15 # 3<Z1_hk<15
# Z2_hk = 15 # 3<Z2_hk<15
# Z3_hk = 3 # 3<Z3_hk<15
hobs = [
[0, 20, 10, 69.52],
[0, 40, 10, 71.44],
[0, 60, 10, 72.99],
[0, 80, 10, 73.86],
[0, 20, 45, 58.73],
[0, 40, 45, 50.57],
[0, 60, 45, 54.31],
[0, 80, 45, 58.06],
[0, 20, 80, 56.31],
[0, 40, 80, 52.32],
[0, 60, 80, 46.35],
[0, 80, 80, 29.01],
[0, 20, 100, 57.24],
[0, 40, 100, 54.24],
[0, 60, 100, 39.48],
[0, 80, 100, 48.47],
]
model_path = os.path.join('_model')
if os.path.exists(model_path):
shutil.rmtree(model_path)
modelname = 'parEstMod'
version = 'mf2005'
exe_name = 'mf2005'
if platform.system() == 'Windows':
exe_name = 'mf2005.exe'
ml = mf.Modflow(modelname=modelname,
exe_name=exe_name,
version=version,
model_ws=model_path)
nlay = 1
nrow = 90
ncol = 120
area_width_y = 9000
area_width_x = 12000
delc = area_width_x / ncol
delr = area_width_y / nrow
nper = 1
top = 100
botm = 0
dis = mf.ModflowDis(ml,
nlay=nlay,
nrow=nrow,
ncol=ncol,
delr=delr,
delc=delc,
top=top,
botm=botm,
nper=nper,
steady=True)
ibound = 1
strt = 100
bas = mf.ModflowBas(ml, ibound=ibound, strt=strt)
mask_arr = np.zeros((nlay, nrow, ncol))
mask_arr[:, :, 0] = 80
mask_arr[:, :, -1] = 60
ghb_spd = {0: []}
for layer_id in range(nlay):
for row_id in range(nrow):
for col_id in range(ncol):
if mask_arr[layer_id][row_id][col_id] > 0:
ghb_spd[0].append([
layer_id, row_id, col_id,
mask_arr[layer_id][row_id][col_id], 200
])
ghb = mf.ModflowGhb(ml, stress_period_data=ghb_spd)
rch = 0.0002
rech = {}
rech[0] = rch
rch = mf.ModflowRch(ml, rech=rech, nrchop=3)
welSp = {}
welSp[0] = [
[0, 20, 20, -20000],
[0, 40, 40, -20000],
[0, 60, 60, -20000],
[0, 80, 80, -20000],
[0, 60, 100, -20000],
]
wel = mf.ModflowWel(ml, stress_period_data=welSp)
hk = np.zeros((nlay, nrow, ncol))
hk[:, :, 0:40] = z1_hk
hk[:, :, 40:80] = z2_hk
hk[:, :, 80:120] = z3_hk
lpf = mf.ModflowLpf(ml, hk=hk, layavg=0, layvka=0, sy=0.3, ipakcb=53)
pcg = mf.ModflowPcg(ml, rclose=1e-1)
oc = mf.ModflowOc(ml)
ml.write_input()
ml.run_model(silent=True)
hds = fu.HeadFile(os.path.join(model_path, modelname + '.hds'))
times = hds.get_times()
response = []
for hob in hobs:
observed = hob[3]
calculated = hds.get_data(totim=times[-1])[hob[0]][hob[1]][hob[2]]
response.append(observed - calculated)
return json.dumps(response)
delc=dy,
top=zTop,
botm=zBot,
laycbd=LAYCBD,
nper=NPER,
perlen=PERLEN,
nstp=NSTP,
steady=STEADY)
bas = fm.ModflowBas(mf, ibound=IBOUND, strt=STRTHD)
lpf = fm.ModflowLpf(mf, hk=HK, vka=VKA, sy=SY, ss=SS, laytyp=LAYTYP, vkcb=VKCB)
ghb = fm.ModflowGhb(mf, stress_period_data=GHB)
wel = fm.ModflowWel(mf, stress_period_data=WEL)
rch = fm.ModflowRch(mf, nrchop=3, rech=RECH)
evt = fm.ModflowEvt(mf, nevtop=3, evtr=EVTR)
oc = fm.ModflowOc(mf, stress_period_data=OC, compact=True)
pcg = fm.ModflowPcg(mf)
#%% Write the model input files and running MODFLOW
mf.write_input()
success, mfoutput = mf.run_model(silent=False, pause=False)
print('Running success = {}'.format(success))
if not success:
raise Exception('MODFLOW did not terminate normally.')
#%% SHOWING RESULTS
#%% READ DATA FILES
HDS = bf.HeadFile(modelname + '.hds')
#dictionary specifies that two wells (one in cell 1, 1,
#51 and one in cell 1, 1, 151), each with a rate of
#-1 m3/d, will be active for the first stress period.
#Because this is a steady-state model, there is only
#one stress period and therefore only one entry in the
#dictionary.
fpm.ModflowRch(model, rech=0.001)
lrcQ = {0: [[0, 0, 50, -1], [0, 0, 150, -1]]}
fpm.ModflowWel(model, stress_period_data=lrcQ)
#5. The preconditioned conjugate-gradient (PCG) solver,
#using the default settings, is specified to solve the
#model.
fpm.ModflowPcg(model)
#6. The frequency and type of output that MODFLOW
#writes to an output file is specified with the output
#control (OC) package. In this case, the budget is printed
#and heads are saved (the default), so no arguments are
#needed.
fpm.ModflowOc(model)
#7. Finally the MODFLOW input files are written (eight
#files for this model) and the model is run. This
#requires, of course, that MODFLOW is installed on
#your computer and FloPy can find the executable in
#your path.
