def initialize(data, grid, grid1):
"""Initialize random plant type field.
Plant types are defined as the following:
* GRASS = 0
* SHRUB = 1
* TREE = 2
* BARE = 3
* SHRUBSEEDLING = 4
* TREESEEDLING = 5
"""
grid1.at_cell['vegetation__plant_functional_type'] = compose_veg_grid(
grid1,
percent_bare=data['percent_bare_initial'],
percent_grass=data['percent_grass_initial'],
percent_shrub=data['percent_shrub_initial'],
percent_tree=data['percent_tree_initial'])
# Assign plant type for representative ecohydrologic simulations
grid.at_cell['vegetation__plant_functional_type'] = np.arange(6)
grid1.at_node['topographic__elevation'] = np.full(grid1.number_of_nodes,
1700.)
grid.at_node['topographic__elevation'] = np.full(grid.number_of_nodes,
1700.)
precip_dry = PrecipitationDistribution(
mean_storm_duration=data['mean_storm_dry'],
mean_interstorm_duration=data['mean_interstorm_dry'],
mean_storm_depth=data['mean_storm_depth_dry'])
precip_wet = PrecipitationDistribution(
mean_storm_duration=data['mean_storm_wet'],
mean_interstorm_duration=data['mean_interstorm_wet'],
mean_storm_depth=data['mean_storm_depth_wet'])
radiation = Radiation(grid)
pet_tree = PotentialEvapotranspiration(grid,
method=data['PET_method'],
MeanTmaxF=data['MeanTmaxF_tree'],
delta_d=data['DeltaD'])
pet_shrub = PotentialEvapotranspiration(grid,
method=data['PET_method'],
MeanTmaxF=data['MeanTmaxF_shrub'],
delta_d=data['DeltaD'])
pet_grass = PotentialEvapotranspiration(grid,
method=data['PET_method'],
MeanTmaxF=data['MeanTmaxF_grass'],
delta_d=data['DeltaD'])
soil_moisture = SoilMoisture(grid, **data) # Soil Moisture object
vegetation = Vegetation(grid, **data) # Vegetation object
vegca = VegCA(grid1, **data) # Cellular automaton object
# Initializing inputs for Soil Moisture object
grid.at_cell['vegetation__live_leaf_area_index'] = (
1.6 * np.ones(grid.number_of_cells))
grid.at_cell['soil_moisture__initial_saturation_fraction'] = (
0.59 * np.ones(grid.number_of_cells))
return (precip_dry, precip_wet, radiation, pet_tree, pet_shrub, pet_grass,
soil_moisture, vegetation, vegca)
def Initialize_(data, grid, grid1):
# Plant types are defined as following:
# GRASS = 0; SHRUB = 1; TREE = 2; BARE = 3;
# SHRUBSEEDLING = 4; TREESEEDLING = 5
# Initialize random plant type field
grid1['cell']['vegetation__plant_functional_type'] = compose_veg_grid(
grid1,
percent_bare=data['percent_bare_initial'],
percent_grass=data['percent_grass_initial'],
percent_shrub=data['percent_shrub_initial'],
percent_tree=data['percent_tree_initial'])
# Assign plant type for representative ecohydrologic simulations
grid['cell']['vegetation__plant_functional_type'] = np.arange(0, 6)
grid1['node']['topographic__elevation'] = (1700. *
np.ones(grid1.number_of_nodes))
grid['node']['topographic__elevation'] = (1700. *
np.ones(grid.number_of_nodes))
PD_D = PrecipitationDistribution(
mean_storm_duration=data['mean_storm_dry'],
mean_interstorm_duration=data['mean_interstorm_dry'],
mean_storm_depth=data['mean_storm_depth_dry'])
PD_W = PrecipitationDistribution(
mean_storm_duration=data['mean_storm_wet'],
mean_interstorm_duration=data['mean_interstorm_wet'],
mean_storm_depth=data['mean_storm_depth_wet'])
Rad = Radiation(grid)
PET_Tree = PotentialEvapotranspiration(grid,
method=data['PET_method'],
MeanTmaxF=data['MeanTmaxF_tree'],
delta_d=data['DeltaD'])
PET_Shrub = PotentialEvapotranspiration(grid,
method=data['PET_method'],
MeanTmaxF=data['MeanTmaxF_shrub'],
delta_d=data['DeltaD'])
PET_Grass = PotentialEvapotranspiration(grid,
method=data['PET_method'],
MeanTmaxF=data['MeanTmaxF_grass'],
delta_d=data['DeltaD'])
SM = SoilMoisture(grid, **data) # Soil Moisture object
VEG = Vegetation(grid, **data) # Vegetation object
vegca = VegCA(grid1, **data) # Cellular automaton object
# # Initializing inputs for Soil Moisture object
grid['cell']['vegetation__live_leaf_area_index'] = (
1.6 * np.ones(grid.number_of_cells))
grid['cell']['soil_moisture__initial_saturation_fraction'] = (
0.59 * np.ones(grid.number_of_cells))
# Initializing Soil Moisture
return PD_D, PD_W, Rad, PET_Tree, PET_Shrub, PET_Grass, SM, \
VEG, vegca
pet_shrub = PotentialEvapotranspiration(grid, method='PenmanMonteith',
albedo=data['albedo_shrub'], rl=data['rl_shrub'],
zveg=data['zveg_shrub'], LAI=data['LAI_shrub'],
zm=data['zm_shrub'], zh=data['zh_shrub'])
pet_tree = PotentialEvapotranspiration(grid, method='PenmanMonteith',
albedo=data['albedo_tree'], rl=data['rl_tree'],
zveg=data['zveg_tree'], LAI=data['LAI_tree'],
zm=data['zm_tree'], zh=data['zh_tree'])
if runon_switch:
(ordered_cells, grid2) = get_ordered_cells_for_soil_moisture(
grid2, outlet_id=1449-(2*58)-2)
grid.at_node['flow__receiver_node'] = (
grid2.at_node['flow__receiver_node'])
SM = SoilMoisture(grid, ordered_cells=ordered_cells, **data)
VEG = Vegetation(grid, **data) # Vegetation object
# Create arrays to store modeled data
## For modeled Radiation model
Rad_mod_NFS = np.zeros([days_n, grid.number_of_cells], dtype=float) # Total Short Wave Radiation
PET_mod_NFS = np.zeros([days_n, grid.number_of_cells], dtype=float) # Potential Evapotranspiration
AET_mod_NFS = np.zeros([days_n, grid.number_of_cells], dtype=float) # Actual Evapotranspiration
SM_mod_NFS = np.zeros([days_n, grid.number_of_cells], dtype=float) # Soil Moisture Saturation Fraction
Rad_Factor = np.zeros([days_n, grid.number_of_cells], dtype=float)
AET_annual = np.zeros([4, grid.number_of_cells], dtype=float) # mm - For annual AET ((actual)evapotranspiration)
P_annual = np.zeros([4, grid.number_of_cells], dtype=float) # mm - For annual P (precipitation)
drainage_annual = np.zeros([4, grid.number_of_cells], dtype=float)
AET_over_P = np.zeros([4, grid.number_of_cells], dtype=float) # AET/P ratio - annual
EP30 = np.zeros([days_n, grid.number_of_cells], dtype=float) # 30 day moving average of PET - only for target cell
TrClim = mat_data['Tr']
PET_grass = mat_data['Ep'] # Penman Monteith data from file
# Create radiation, soil moisture and Vegetation objects
Rad = Radiation(grid)
PET_Tree = PotentialEvapotranspiration(grid1, method=data['PET_method'],
MeanTmaxF=data['MeanTmaxF_tree'],
DeltaD=data['DeltaD'])
PET_Shrub = PotentialEvapotranspiration(grid1, method=data['PET_method'],
MeanTmaxF=data['MeanTmaxF_shrub'],
DeltaD=data['DeltaD'])
PET_Grass = PotentialEvapotranspiration(grid1, method = data['PET_method'],
MeanTmaxF=data['MeanTmaxF_grass'],
DeltaD=data['DeltaD'])
SM = SoilMoisture(grid, runon_switch=0, **data) # Soil Moisture object
VEG = Vegetation(grid, **data) # Vegetation object
vegca = VegCA(grid1, **data) # Cellular automaton object
##########
n = 3275 #data['n_short'] # Defining number of storms the model will be run
##########
## Create arrays to store modeled data
P = np.empty(n) # Record precipitation
Tb = np.empty(n) # Record inter storm duration
Tr = np.empty(n) # Record storm duration
Time = np.empty(n) # To record time elapsed from the start of simulation
CumWaterStress = np.empty([n/50, grid1.number_of_cells]) # Cum Water Stress
CumWS = np.empty([n/50, grid.number_of_cells]) # Cum Water Stress of different plant types
def initialize(data, grid, grid1, grid2, elevation):
"""Initialize random plant type field.
Plant types are defined as the following:
* GRASS = 0
* SHRUB = 1
* TREE = 2
* BARE = 3
* SHRUBSEEDLING = 4
* TREESEEDLING = 5
"""
grid['cell']['vegetation__plant_functional_type'] = compose_veg_grid(
grid,
percent_bare=data['percent_bare_initial'],
percent_grass=data['percent_grass_initial'],
percent_shrub=data['percent_shrub_initial'],
percent_tree=data['percent_tree_initial'])
# Assign plant type for representative ecohydrologic simulations
grid1.at_cell['vegetation__plant_functional_type'] = np.arange(6)
grid1.at_node['topographic__elevation'] = np.full(grid1.number_of_nodes,
1700.)
grid.at_node['topographic__elevation'] = elevation
grid2.at_node['topographic__elevation'] = elevation
if data['runon_switch']:
(ordered_cells, grid2) = get_ordered_cells_for_soil_moisture(
grid2, outlet_id=4877) # hugo10mws: 1331 # 36704
grid.at_node['flow__receiver_node'] = (
grid2.at_node['flow__receiver_node'])
else:
ordered_cells = None
precip_dry = PrecipitationDistribution(
mean_storm_duration=data['mean_storm_dry'],
mean_interstorm_duration=data['mean_interstorm_dry'],
mean_storm_depth=data['mean_storm_depth_dry'],
random_seed=None)
precip_wet = PrecipitationDistribution(
mean_storm_duration=data['mean_storm_wet'],
mean_interstorm_duration=data['mean_interstorm_wet'],
mean_storm_depth=data['mean_storm_depth_wet'],
random_seed=None)
radiation = Radiation(grid)
rad_pet = Radiation(grid1)
pet_tree = PotentialEvapotranspiration(grid1,
method=data['PET_method'],
MeanTmaxF=data['MeanTmaxF_tree'],
delta_d=data['DeltaD'])
pet_shrub = PotentialEvapotranspiration(grid1,
method=data['PET_method'],
MeanTmaxF=data['MeanTmaxF_shrub'],
delta_d=data['DeltaD'])
pet_grass = PotentialEvapotranspiration(grid1,
method=data['PET_method'],
MeanTmaxF=data['MeanTmaxF_grass'],
delta_d=data['DeltaD'])
soil_moisture = SoilMoisture(grid, ordered_cells=ordered_cells,
**data) # Soil Moisture object
vegetation = Vegetation(grid, **data) # Vegetation object
vegca = VegCA(grid, **data) # Cellular automaton object
# # Initializing inputs for Soil Moisture object
grid['cell']['vegetation__live_leaf_area_index'] = (
1.6 * np.ones(grid.number_of_cells))
grid['cell']['soil_moisture__initial_saturation_fraction'] = (
0.59 * np.ones(grid.number_of_cells))
# Initializing Soil Moisture
return (precip_dry, precip_wet, radiation, rad_pet, pet_tree, pet_shrub,
pet_grass, soil_moisture, vegetation, vegca, ordered_cells)