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Radionuclides
from opendrift.readers import reader_netCDF_CF_generic
from opendrift.models.radionuclides import RadionuclideDrift
from datetime import timedelta, datetime
import numpy as np
o = RadionuclideDrift(loglevel=0, seed=0) # Set loglevel to 0 for debug information
# Norkyst
#reader_norkyst = reader_netCDF_CF_generic.Reader(o.test_data_folder() + '/14Jan2016_NorKyst_z_3d/NorKyst-800m_ZDEPTHS_his_00_3Dsubset.nc')
reader_norkyst = reader_netCDF_CF_generic.Reader('https://thredds.met.no/thredds/dodsC/sea/norkyst800m/1h/aggregate_be')
o.add_reader([reader_norkyst])
# Adjusting some configuration
o.set_config('drift:vertical_mixing', True)
#o.set_config('vertical_mixing:diffusivitymodel','constant') # include settling without vertical turbulent mixing
o.set_config('vertical_mixing:diffusivitymodel','environment') # apply vertical diffusivity from ocean model
# Vertical mixing requires fast time step
o.set_config('vertical_mixing:timestep', 600.) # seconds
o.set_config('drift:horizontal_diffusivity', 10)
o.set_config('radionuclide:particle_diameter',5.e-6) # m
o.set_config('radionuclide:sediment:resuspension_depth',2.)
o.set_config('radionuclide:sediment:resuspension_depth_uncert',0.1)
o.set_config('radionuclide:sediment:resuspension_critvel',0.15)
#
o.set_config('radionuclide:isotope', '137Cs')
o.set_config('radionuclide:specie_setup','LMM + Rev')
# By default, radionuclides do not strand towards coastline
o.set_config('general:coastline_action', 'previous')
o.set_config('general:seafloor_action','lift_to_seafloor')
o.set_config('seed:LMM_fraction',.45)
o.set_config('seed:particle_fraction',.55)
o.list_configspec()
# SEEDING
td=datetime.today()
time = datetime(td.year, td.month, td.day, 0)
latseed= 60.0; lonseed= 4.5
ntraj=5000
iniz=np.random.rand(ntraj) * -10. # seeding the radionuclides in the upper 10m
o.seed_elements(lonseed, latseed, z=iniz, radius=1000,number=ntraj,
time=time,
)
Running model
o.run(steps=24*2, time_step=1800, time_step_output=3600)
Print and plot results
print(o)
print('Final speciation:')
for isp,sp in enumerate(o.name_species):
print ('{:32}: {:>6}'.format(sp,sum(o.elements.specie==isp)))
print('Number of transformations:')
for isp in range(o.nspecies):
print('{}'.format(['{:>9}'.format(np.int32(item)) for item in o.ntransformations[isp,:]]) )
o.animation(color='specie',
vmin=0,vmax=o.nspecies-1,
colorbar=False,
legend=[o.specie_num2name(i) for i in range(o.nspecies)],
fast = True
)
o.plot_vertical_distribution()
#o.plot_property('specie')
o.animation_profile(color='specie',
vmin=0,vmax=o.nspecies-1,
legend=[o.specie_num2name(i) for i in range(o.nspecies)],
legend_loc =3,
# markersize=10
)
o.plot(linecolor='specie',vmin=0,vmax=o.nspecies-1,fast=True,)
# # Postprocessing: write to concentration netcdf file
o.write_netcdf_radionuclide_density_map('radio_conc.nc', pixelsize_m=500.,
zlevels=[-2.],
activity_unit='Bq',
horizontal_smoothing=True,
smoothing_cells=1,
time_avg_conc=True,
deltat=2., # hours
# llcrnrlon=4.4, llcrnrlat=59.9,
# urcrnrlon=4.8, urcrnrlat=60.2,
)