def test_sed_mpi():
model=base_model()
g=unstructured_grid.UnstructuredGrid(max_sides=4)
g.add_rectilinear([0,0],[1000,100],101,11)
g.add_cell_field('depth',-6*np.ones(g.Ncells()))
model.set_grid(g)
model.num_procs=4
model.config['dt']=3.
# slow down the settling velocities to get some advection mixed in
model.config['Ws01']= 0.0001 # constant settling velocity for fraction No.1 (m/s)
model.config['Ws02']= 0.0005 # constant settling velocity for fraction No.2
model.config['Ws03']=-0.0005 # constant settling velocity for fraction No.3
geom=np.array([ [1000,0],
[1000,100]])
Q_bc=sun_driver.FlowBC(name="Q_bc",
geom=geom,
Q=100.0)
model.add_bcs( [Q_bc,
sun_driver.ScalarBC(parent=Q_bc,scalar="S",value=2),
sun_driver.ScalarBC(parent=Q_bc,scalar="T",value=0)] )
point_bc=sun_driver.SourceSinkBC(name="bedPoint",
geom=np.array([500,20]),
Q=10)
model.add_bcs( [point_bc,
sun_driver.ScalarBC(parent=point_bc,scalar="S",value=3),
sun_driver.ScalarBC(parent=point_bc,scalar="T",value=3)] )
model.write()
# leave some dry layers at the surface
model.ic_ds.eta.values[:]=model.bcs[0].z
model.ic_ds.salt.values[:]=1.0
model.ic_ds.temp.values[:]=1.0
model.write_ic_ds()
for sed_idx in range(3):
name="sed%d"%(sed_idx+1)
model.bc_ds['boundary_'+name]=model.bc_ds['boundary_S'].copy()
model.bc_ds[name]=model.bc_ds['S'].copy()
model.bc_ds['point_'+name]=model.bc_ds['point_S'].copy()
model.bc_ds['boundary_'+name].values[:]=sed_idx*1.0
model.bc_ds[name].values[:]=0.0
model.bc_ds['point_'+name].values[:]=sed_idx*2.0
model.write_bc_ds()
model.partition()
model.sun_verbose_flag='-v'
model.run_simulation()
return model
def test_sed_bc():
"""
basic BC
"""
model=base_model()
# slow down the settling velocities to get some advection mixed in
model.config['Ws01']= 0.0001 # constant settling velocity for fraction No.1 (m/s)
model.config['Ws02']= 0.0001 # constant settling velocity for fraction No.2
model.config['Ws03']=-0.0001 # constant settling velocity for fraction No.3
geom=np.array([ [1000,0],
[1000,100]])
Q_bc=sun_driver.FlowBC(name="Q_bc",
geom=geom,
Q=100.0)
model.add_bcs( [Q_bc,
sun_driver.ScalarBC(parent=Q_bc,scalar="S",value=2),
sun_driver.ScalarBC(parent=Q_bc,scalar="T",value=0)] )
point_bc=sun_driver.SourceSinkBC(name="bedPoint",
geom=np.array([500,20]),
Q=10)
model.add_bcs( [point_bc,
sun_driver.ScalarBC(parent=point_bc,scalar="S",value=3),
sun_driver.ScalarBC(parent=point_bc,scalar="T",value=3)] )
model.write()
# leave some dry layers at the surface
model.ic_ds.eta.values[:]=model.bcs[0].z
model.ic_ds.salt.values[:]=1.0
model.ic_ds.temp.values[:]=1.0
model.write_ic_ds()
for sed_idx in range(3):
name="sed%d"%(sed_idx+1)
model.bc_ds['boundary_'+name]=model.bc_ds['boundary_S'].copy()
model.bc_ds[name]=model.bc_ds['S'].copy()
model.bc_ds['point_'+name]=model.bc_ds['point_S'].copy()
model.bc_ds['boundary_'+name].values[:]=sed_idx*1.0
model.bc_ds[name].values[:]=0.0
model.bc_ds['point_'+name].values[:]=sed_idx*2.0
model.write_bc_ds()
model.partition()
model.sun_verbose_flag='-v'
model.run_simulation()
return model
def test_point_source_1d():
"""
Create a 1D water column, with a point source at the bed.
Verifies that all cells with valid thickness (dzz>0.001m)
have near unity salinity.
"""
g=unstructured_grid.UnstructuredGrid(max_sides=4)
g.add_rectilinear([0,0],[10,10],2,2)
g.add_cell_field('depth',-6*np.ones(g.Ncells()))
model=sun_driver.SuntansModel()
model.load_template('point_source_test.dat')
model.set_grid(g)
model.run_start=np.datetime64("2018-01-01 00:00")
model.run_stop =np.datetime64("2018-01-01 10:00")
source=sun_driver.SourceSinkBC(name='inflow',geom=np.array([5,5]),
z=-10,Q=1.0)
model.add_bcs(source)
model.add_bcs( [sun_driver.ScalarBC(parent=source,scalar="S",value=1),
sun_driver.ScalarBC(parent=source,scalar="T",value=1)] )
model.set_run_dir('rundata_point_1d', mode='pristine')
model.projection='EPSG:26910'
model.config['dt']=2.5
model.config['ntout']=1
model.config['Cmax']=30
model.config['Nkmax']=10
model.config['stairstep']=0
model.config['mergeArrays']=0
model.write()
model.ic_ds.eta.values[:]=-5.999
model.ic_ds.salt.values[:]=1.0
model.ic_ds.temp.values[:]=1.0
model.write_ic_ds()
model.partition()
model.sun_verbose_flag='-v'
model.run_simulation()
ds=xr.open_dataset(model.map_outputs()[0])
dzz=ds.dzz.values
dzz_thresh=0.001
salt=ds.salt.values
salt_errors=salt[dzz>=dzz_thresh] - 1.0
assert np.max( np.abs(salt_errors) )<0.001
def add_potw_bcs(model, cache_dir, temperature=20.0):
# WWTP discharging into sloughs
potw_dir = "../sfbay_potw"
potw_ds = xr.open_dataset(
os.path.join(potw_dir, "outputs", "sfbay_delta_potw.nc"))
# the gazetteer uses the same names for potws as the source data
# omits some of the smaller sources, and this does not include any
# benthic discharges
for potw_name in [
'sunnyvale', 'san_jose', 'palo_alto', 'lg', 'sonoma_valley',
'petaluma', 'cccsd', 'fs', 'ddsd', 'ebda', 'ebmud', 'sf_southeast'
]:
# This has variously worked and not worked with strings vs bytes.
# Brute force and try both.
try:
Q_da = potw_ds.flow.sel(site=potw_name)
except KeyError:
Q_da = potw_ds.flow.sel(site=potw_name.encode())
# Have to seek back in time to find a year that has data for the
# whole run
offset = np.timedelta64(0, 'D')
while model.run_stop > Q_da.time.values[-1] + offset:
offset += np.timedelta64(365, 'D')
if offset:
log.info("Offset for POTW %s is %s" % (potw_name, offset))
# use the geometry to decide whether this is a flow BC or a point source
hits = model.match_gazetteer(name=potw_name)
if hits[0]['geom'].type == 'LineString':
log.info("%s: flow bc" % potw_name)
Q_bc = drv.FlowBC(name=potw_name,
flow=Q_da,
filters=[hm.Lag(-offset)],
dredge_depth=model.dredge_depth)
else:
log.info("%s: source bc" % potw_name)
Q_bc = drv.SourceSinkBC(name=potw_name,
flow=Q_da,
filters=[hm.Lag(-offset)],
dredge_depth=model.dredge_depth)
salt_bc = drv.ScalarBC(parent=Q_bc, scalar='salinity', value=0.0)
temp_bc = drv.ScalarBC(parent=Q_bc,
scalar='temperature',
value=temperature)
model.add_bcs([Q_bc, salt_bc, temp_bc])
def add_usgs_stream_bcs(model, cache_dir):
# USGS gauged creeks
for station, name in [
(11172175, "COYOTE"),
(11169025, "SCLARAVCc"), # Alviso Sl / Guad river
(11180700, "UALAMEDA"), # Alameda flood control
(11458000, "NAPA")
]:
Q_bc = hm.NwisFlowBC(name=name,
station=station,
cache_dir=cache_dir,
dredge_depth=model.dredge_depth)
salt_bc = drv.ScalarBC(name=name, scalar='salinity', value=0.0)
temp_bc = drv.ScalarBC(name=name, scalar='temperature', value=20.0)
model.add_bcs([Q_bc, salt_bc, temp_bc])
def base_model():
"""
Channel
"""
g=unstructured_grid.UnstructuredGrid(max_sides=4)
g.add_rectilinear([0,0],[1000,100],21,3)
g.add_cell_field('depth',-6*np.ones(g.Ncells()))
model=sun_driver.SuntansModel()
model.load_template('point_source_test.dat')
model.set_grid(g)
model.run_start=np.datetime64("2018-01-01 00:00")
model.run_stop =np.datetime64("2018-01-05 00:00")
dt=np.timedelta64(600,'s')
times=np.arange(model.run_start-dt,model.run_stop+2*dt,dt)
secs=(times-times[0])/np.timedelta64(1,'s')
eta0=-1
eta_bc=sun_driver.StageBC(name="eta_bc",
geom=np.array([ [0,0],
[0,100]]),
z=eta0)
model.add_bcs(eta_bc)
model.add_bcs( [sun_driver.ScalarBC(parent=eta_bc,scalar="S",value=34),
sun_driver.ScalarBC(parent=eta_bc,scalar="T",value=15)] )
model.set_run_dir('rundata_met_3d', mode='pristine')
model.projection='EPSG:26910'
model.num_procs=1 # test single first
model.config['dt']=120
model.config['ntout']=5
model.config['Cmax']=30
model.config['Nkmax']=10
model.config['stairstep']=0
model.config['mergeArrays']=0
return model
def add_delta_bcs(model, cache_dir):
# Delta inflow
# SacRiver, SJRiver
sac_bc = hm.NwisFlowBC(name='SacRiver',
station=11455420,
cache_dir=cache_dir,
filters=[hm.Lowpass(cutoff_hours=3)],
dredge_depth=model.dredge_depth)
tmi_bc = hm.NwisFlowBC(
name='SacRiver',
station=11337080,
cache_dir=cache_dir,
filters=[hm.Lowpass(cutoff_hours=3),
hm.Transform(fn=lambda x: -x)],
mode='add')
sj_bc = hm.NwisFlowBC(name='SJRiver',
station=11337190,
cache_dir=cache_dir,
filters=[hm.Lowpass(cutoff_hours=3)],
dredge_depth=model.dredge_depth)
dutch_bc = hm.NwisFlowBC(name='SJRiver',
station=11313433,
cache_dir=cache_dir,
filters=[hm.Lowpass(cutoff_hours=3)],
mode='add')
sac_salt_bc = drv.ScalarBC(name='SacRiver', scalar='salinity', value=0.0)
sj_salt_bc = drv.ScalarBC(name='SJRiver', scalar='salinity', value=0.0)
sac_temp_bc = drv.ScalarBC(name='SacRiver',
scalar='temperature',
value=20.0)
sj_temp_bc = drv.ScalarBC(name='SJRiver', scalar='temperature', value=20.0)
model.add_bcs(
[sac_bc, sj_bc, sac_salt_bc, sj_salt_bc, sac_temp_bc, sj_temp_bc])
model.set_grid(g)
model.run_start = np.datetime64("2018-01-01 00:00")
model.run_stop = np.datetime64("2018-01-01 10:00")
dt = np.timedelta64(600, 's')
times = np.arange(model.run_start - dt, model.run_stop + 2 * dt, dt)
secs = (times - times[0]) / np.timedelta64(1, 's')
eta_values = -6 + 0.75 * np.cos(secs * np.pi / 7200)
eta_da = xr.DataArray(eta_values, coords=[('time', times)])
eta_bc = sun_driver.StageBC(name="eta_bc",
geom=np.array([[0, 0], [0, 500]]),
z=eta_da)
model.add_bcs(eta_bc)
model.add_bcs([
sun_driver.ScalarBC(parent=eta_bc, scalar="S", value=1),
sun_driver.ScalarBC(parent=eta_bc, scalar="T", value=1)
])
# point source that is typically dry
hill_source = sun_driver.SourceSinkBC(name='inflow',
geom=np.array([150, 150]),
z=-10,
Q=1.0)
# on a saddle
saddle_source = sun_driver.SourceSinkBC(name='inflow',
geom=np.array([220, 225]),
z=-10,
Q=1.0)
def test_point_source_3d():
"""
A square 3D grid with wetting and drying.
the bathymetry is a wavy cos(x)*cos(y) function.
two point sources and an oscillating freesurface.
one point source at a saddle point, and the other
on top of a bump which goes dry.
This currently does pretty well, but it could be
better -- see the test thresholds near the end which
have been relaxed somewhat.
"""
g=unstructured_grid.UnstructuredGrid(max_sides=4)
g.add_rectilinear([0,0],[500,500],50,50)
# wavy bed
half_wave=150
cc=g.cells_center()
cell_depth=-6 + np.cos(cc[:,0]*np.pi/half_wave) * np.cos(cc[:,1]*np.pi/half_wave)
g.add_cell_field('depth',cell_depth)
model=sun_driver.SuntansModel()
model.load_template('point_source_test.dat')
model.set_grid(g)
model.run_start=np.datetime64("2018-01-01 00:00")
model.run_stop =np.datetime64("2018-01-01 10:00")
dt=np.timedelta64(600,'s')
times=np.arange(model.run_start-dt,model.run_stop+2*dt,dt)
secs=(times-times[0])/np.timedelta64(1,'s')
eta_values=-6 + 0.75*np.cos(secs*np.pi/7200)
eta_da=xr.DataArray(eta_values,coords=[ ('time',times) ])
eta_bc=sun_driver.StageBC(name="eta_bc",geom=np.array([ [0,0],
[0,500]]),
z=eta_da)
model.add_bcs(eta_bc)
model.add_bcs( [sun_driver.ScalarBC(parent=eta_bc,scalar="S",value=1),
sun_driver.ScalarBC(parent=eta_bc,scalar="T",value=1)] )
# point source that is typically dry
hill_source=sun_driver.SourceSinkBC(name='inflow',geom=np.array([150,150]),
z=-10,Q=1.0)
# on a saddle
saddle_source=sun_driver.SourceSinkBC(name='inflow',geom=np.array([220,225]),
z=-10,Q=1.0)
model.add_bcs(hill_source)
model.add_bcs(saddle_source)
model.add_bcs( [sun_driver.ScalarBC(parent=hill_source,scalar="S",value=1),
sun_driver.ScalarBC(parent=hill_source,scalar="T",value=1)] )
model.add_bcs( [sun_driver.ScalarBC(parent=saddle_source,scalar="S",value=1),
sun_driver.ScalarBC(parent=saddle_source,scalar="T",value=1)] )
model.set_run_dir('rundata_point_3d', mode='pristine')
model.projection='EPSG:26910'
model.num_procs=4
model.config['dt']=2.5
model.config['ntout']=5
model.config['Cmax']=30
model.config['Nkmax']=10
model.config['stairstep']=0
model.config['mergeArrays']=0
model.write()
model.ic_ds.eta.values[:]=eta_da.values[1]
model.ic_ds.salt.values[:]=1.0
model.ic_ds.temp.values[:]=1.0
model.write_ic_ds()
model.partition()
model.sun_verbose_flag='-v'
model.run_simulation()
for map_fn in model.map_outputs():
ds=xr.open_dataset(map_fn)
dzz=ds.dzz.values
# This is not as strict as it should be.
# should be 0.001 or less.
dzz_thresh=0.05
salt=ds.salt.values
valid=np.isfinite(dzz) & (dzz>=dzz_thresh)
salt_errors=salt[valid] - 1.0
# This is not as strict as it should be.
# we should be able to get this down to 1e-4 or
# better.
assert np.max( np.abs(salt_errors) )<0.01
ds.close()
if utils.is_stale(dest_grid, [src_grid, "bathy.py"]):
set_bathy(src_grid, dest_grid)
g = unstructured_grid.UnstructuredGrid.from_ugrid(dest_grid)
g.cells['z_bed'] += z_offset_manual
g.edges['edge_z_bed'] += z_offset_manual
model.set_grid(g)
else:
print("Grid comes from restart")
model.dredge_depth = None # no need to dredge grid if a restart
model.add_gazetteer("grid-lsb/linear_features.shp")
##
ocean_salt_bc = drv.ScalarBC(name='ocean', scalar='salinity', value=25)
ocean_temp_bc = drv.ScalarBC(name='ocean', scalar='temperature', value=10)
msl_navd88 = 0.94 # m
ocean_bc = drv.NOAAStageBC(
name='ocean',
station=9414575, # Coyote - will come in as MSL
# station=9414750, # Alameda.
cache_dir=cache_dir,
filters=[dfm.Lowpass(cutoff_hours=1.5)])
ocean_offset_bc = drv.StageBC(name='ocean',
mode='add',
z=z_offset_manual + msl_navd88)
model.add_bcs([ocean_bc, ocean_salt_bc, ocean_temp_bc, ocean_offset_bc])
# eta_da=xr.DataArray(eta_values,coords=[ ('time',times) ])
# eta_bc=sun_driver.StageBC(name="eta_bc",geom=np.array([ [0,0],
# [0,500]]),
# z=eta_da)
# model.add_bcs(eta_bc)
#model.add_bcs( [sun_driver.ScalarBC(parent=eta_bc,scalar="S",value=1),
# sun_driver.ScalarBC(parent=eta_bc,scalar="T",value=1)] )
# on a saddle
source = sun_driver.SourceSinkBC(name='inflow',
geom=np.array([5, 5]),
z=-10,
Q=1.0)
model.add_bcs(source)
model.add_bcs([
sun_driver.ScalarBC(parent=source, scalar="S", value=1),
sun_driver.ScalarBC(parent=source, scalar="T", value=1)
])
model.set_run_dir('rundata_1d', mode='pristine')
model.projection = 'EPSG:26910'
model.sun_bin_dir = "/home/rusty/src/suntans/main"
model.config['dt'] = 2.5
model.config['ntout'] = 1
model.config['Cmax'] = 30
model.config['Nkmax'] = 10
model.config['stairstep'] = 0
model.config['mergeArrays'] = 0
model.write()
def base_model():
"""
A channel, uniform bathy.
"""
g=unstructured_grid.UnstructuredGrid(max_sides=4)
g.add_rectilinear([0,0],[1000,100],21,3)
g.add_cell_field('depth',-6*np.ones(g.Ncells()))
model=sun_driver.SuntansModel()
model.load_template('point_source_test.dat')
model.set_grid(g)
model.run_start=np.datetime64("2018-01-01 00:00")
model.run_stop =np.datetime64("2018-01-01 10:00")
dt=np.timedelta64(600,'s')
times=np.arange(model.run_start-dt,model.run_stop+2*dt,dt)
secs=(times-times[0])/np.timedelta64(1,'s')
eta0=-2
eta_bc=sun_driver.StageBC(name="eta_bc",
geom=np.array([ [0,0],
[0,100]]),
z=eta0)
model.add_bcs(eta_bc)
model.add_bcs( [sun_driver.ScalarBC(parent=eta_bc,scalar="S",value=1),
sun_driver.ScalarBC(parent=eta_bc,scalar="T",value=1)] )
model.set_run_dir('rundata_sedi_3d', mode='pristine')
model.projection='EPSG:26910'
model.num_procs=1 # test single first
model.config['dt']=30
model.config['ntout']=5
model.config['Cmax']=30
model.config['Nkmax']=10
model.config['stairstep']=0
model.config['mergeArrays']=0
# Sediment:
model.config['computeSediments']=1 # whether include sediment model
model.config['Nlayer']=0 # Number of bed layers (MAX = 5)
model.config['Nsize']=3 # Number of sediment fractions (Max = 3)
model.config['TBMAX']=1 # whether to output tb for each cell
model.config['SETsediment']=0 # When Nlayer>5 or Nsize>3, SETsediment=1 to use SetSediment
model.config['WSconstant']=1 # if 1, ws for sediment = ws0
model.config['readSediment']=0 # if 1, read sediment concentration data as IC. only work with Nsize==1
model.config['bedInterval']=150 # the interval steps to update bed change
model.config['bedComplex']=0 # whether to consider the possibility to flush away a whole layer
model.config['ParabolKappa']=0 # whether to use parabolic tubulent diffusivity
model.config['Ds90']=0.000008 # ds90 for calculation of erosion taub
model.config['Ds1']=0.00000057 # sediment diameter for fraction No.1 (m)
model.config['Ds2']=0.0002 # sediment diameter for fraction No.2
model.config['Ds3']=0.0002 # sediment diameter for fraction No.3
model.config['Ws01']= 0.0001 # constant settling velocity for fraction No.1 (m/s)
model.config['Ws02']= 0.01 # constant settling velocity for fraction No.2
model.config['Ws03']=-0.01 # constant settling velocity for fraction No.3
model.config['Gsedi1']=2.65 # relative density for fraction No.1
model.config['Gsedi2']=2.65 # relative density for fraction No.2
model.config['Gsedi3']=2.65 # relative density for fraction No.3
model.config['Prt1']=1 # Prandtl Number for fraction No.1
model.config['Prt2']=1 # Prandtl Number for fraction No.2
model.config['Prt3']=1 # Prandtl Number for fraction No.3
model.config['Consolid1']=0.00 # Consolidation rate (g/m^2/s) for layer No.1
model.config['E01']=0.1 # Basic Erosion Rate Constant (g/m^2/s) for layer No.1
model.config['Taue1']=0.0 # Erosion Critical Shear Stress (N/m^2) for layer No.1
# Taud1 isn't actually used in current code. Deposition always occurs at the rate
# of w_s.
model.config['Taud1']=0.0 # Deposition Critical Shear Stress (N/m^2) for layer No.1
model.config['Drydensity1']=530000 # Dry density (g/m^3) for layer No.1
model.config['Thickness1']=0.0 # Thickness (m) for layer No.1
model.config['softhard1']=1 # 0 soft or hard for layer No.1 to decide how to calculate erosion
model.config['Bedmudratio1']=0.8 # Bed mud ratio for layer No.1
model.config['Chind']=1000000 # Concentration (in volumetric fraction) criterion for hindered settling velocity
model.config['Cfloc']=500000 # Concentration (in volumetric fraction) criterion for flocculated settling velcoity
model.config['k']=0.0002 # Constant coefficient for settling velocity as a function of conc.
model.config['Sediment1File']='sedi1.dat'
model.config['Sediment2File']='sedi2.dat'
model.config['Sediment3File']='sedi3.dat'
model.config['LayerFile']='sedilayer.dat'
model.config['tbFile']='Seditb.dat'
model.config['tbmaxFile']='Seditbmax.dat'
return model
