def Calculate(Basin, P_Product, ET_Product, Inflow_Text_Files,
Reservoirs_Lakes_Calculations, Startdate, Enddate, Simulation):
'''
This functions consists of the following sections:
1. Set General Parameters
2. Download Data
3. Convert the RAW data to NETCDF files
4. Create Mask based on LU map
5. Calculate Runoff based on Budyko
6. Add inflow in Runoff
7. Calculate River flow
7.1 Route Runoff
7.2 Add Reservoirs
7.3 Add surface water withdrawals
'''
# import General modules
import os
import gdal
import numpy as np
import pandas as pd
import copy
# import WA plus modules
from wa.General import raster_conversions as RC
from wa.General import data_conversions as DC
import wa.Functions.Five as Five
import wa.Functions.Start as Start
######################### 1. Set General Parameters ##############################
# Get environmental variable for the Home folder
WA_env_paths = os.environ["WA_HOME"].split(';')
Dir_Home = WA_env_paths[0]
# Create the Basin folder
Dir_Basin = os.path.join(Dir_Home, Basin)
if not os.path.exists(Dir_Basin):
os.makedirs(Dir_Basin)
# Get the boundaries of the basin based on the shapefile of the watershed
# Boundaries, Shape_file_name_shp = Start.Boundaries.Determine(Basin)
Boundaries, LU_dataset = Start.Boundaries.Determine_LU_Based(Basin)
LU_data = RC.Open_tiff_array(LU_dataset)
geo_out_LU, proj_LU, size_X_LU, size_Y_LU = RC.Open_array_info(LU_dataset)
# Define resolution of SRTM
Resolution = '15s'
# Get the amount of months
Amount_months = len(pd.date_range(Startdate, Enddate, freq='MS'))
Amount_months_reservoirs = Amount_months + 1
# Startdate for moving window Budyko
Startdate_2months_Timestamp = pd.Timestamp(Startdate) - pd.DateOffset(
months=2)
Startdate_2months = Startdate_2months_Timestamp.strftime('%Y-%m-%d')
############################# 2. Download Data ###################################
# Download data
Data_Path_P = Start.Download_Data.Precipitation(
Dir_Basin, [Boundaries['Latmin'], Boundaries['Latmax']],
[Boundaries['Lonmin'], Boundaries['Lonmax']], Startdate_2months,
Enddate, P_Product)
Data_Path_ET = Start.Download_Data.Evapotranspiration(
Dir_Basin, [Boundaries['Latmin'], Boundaries['Latmax']],
[Boundaries['Lonmin'], Boundaries['Lonmax']], Startdate_2months,
Enddate, ET_Product)
Data_Path_DEM = Start.Download_Data.DEM(
Dir_Basin, [Boundaries['Latmin'], Boundaries['Latmax']],
[Boundaries['Lonmin'], Boundaries['Lonmax']], Resolution)
if Resolution is not '3s':
Data_Path_DEM = Start.Download_Data.DEM(
Dir_Basin, [Boundaries['Latmin'], Boundaries['Latmax']],
[Boundaries['Lonmin'], Boundaries['Lonmax']], Resolution)
Data_Path_DEM_Dir = Start.Download_Data.DEM_Dir(
Dir_Basin, [Boundaries['Latmin'], Boundaries['Latmax']],
[Boundaries['Lonmin'], Boundaries['Lonmax']], Resolution)
Data_Path_ETref = Start.Download_Data.ETreference(
Dir_Basin, [Boundaries['Latmin'], Boundaries['Latmax']],
[Boundaries['Lonmin'], Boundaries['Lonmax']], Startdate_2months,
Enddate)
Data_Path_JRC_occurrence = Start.Download_Data.JRC_occurrence(
Dir_Basin, [Boundaries['Latmin'], Boundaries['Latmax']],
[Boundaries['Lonmin'], Boundaries['Lonmax']])
Data_Path_P_Monthly = os.path.join(Data_Path_P, 'Monthly')
###################### 3. Convert the RAW data to NETCDF files ##############################
# The sequence of converting the data is:
# DEM
# DEM flow directions
# Precipitation
# Evapotranspiration
# Reference Evapotranspiration
#_____________________________________DEM__________________________________
# Get the data of DEM and save as nc, This dataset is also used as reference for others
Example_dataset = os.path.join(Dir_Basin, Data_Path_DEM,
'DEM_HydroShed_m_%s.tif' % Resolution)
DEMdest = gdal.Open(Example_dataset)
Xsize_CR = int(DEMdest.RasterXSize)
Ysize_CR = int(DEMdest.RasterYSize)
DataCube_DEM_CR = DEMdest.GetRasterBand(1).ReadAsArray()
Name_NC_DEM_CR = DC.Create_NC_name('DEM_CR', Simulation, Dir_Basin, 5)
if not os.path.exists(Name_NC_DEM_CR):
DC.Save_as_NC(Name_NC_DEM_CR, DataCube_DEM_CR, 'DEM_CR',
Example_dataset)
DEMdest = None
#___________________________________DEM Dir________________________________
# Get the data of flow direction and save as nc.
Dir_dataset = os.path.join(Dir_Basin, Data_Path_DEM_Dir,
'DIR_HydroShed_-_%s.tif' % Resolution)
DEMDirdest = gdal.Open(Dir_dataset)
DataCube_DEM_Dir_CR = DEMDirdest.GetRasterBand(1).ReadAsArray()
Name_NC_DEM_Dir_CR = DC.Create_NC_name('DEM_Dir_CR', Simulation, Dir_Basin,
5)
if not os.path.exists(Name_NC_DEM_Dir_CR):
DC.Save_as_NC(Name_NC_DEM_Dir_CR, DataCube_DEM_Dir_CR, 'DEM_Dir_CR',
Example_dataset)
DEMDirdest = None
del DataCube_DEM_Dir_CR
#______________________________ Precipitation______________________________
# Define info for the nc files
info = [
'monthly', 'mm',
''.join([Startdate_2months[5:7], Startdate_2months[0:4]]),
''.join([Enddate[5:7], Enddate[0:4]])
]
# Precipitation data
Name_NC_Prec_CR = DC.Create_NC_name('Prec_CR', Simulation, Dir_Basin, 5,
info)
if not os.path.exists(Name_NC_Prec_CR):
# Get the data of Precipitation and save as nc
DataCube_Prec_CR = RC.Get3Darray_time_series_monthly(
Dir_Basin,
Data_Path_P_Monthly,
Startdate_2months,
Enddate,
Example_data=Example_dataset)
DC.Save_as_NC(Name_NC_Prec_CR, DataCube_Prec_CR, 'Prec_CR',
Example_dataset, Startdate_2months, Enddate, 'monthly',
0.01)
del DataCube_Prec_CR
#____________________________ Evapotranspiration___________________________
# Evapotranspiration data
info = [
'monthly', 'mm',
''.join([Startdate_2months[5:7], Startdate_2months[0:4]]),
''.join([Enddate[5:7], Enddate[0:4]])
]
Name_NC_ET_CR = DC.Create_NC_name('ET_CR', Simulation, Dir_Basin, 5, info)
if not os.path.exists(Name_NC_ET_CR):
# Get the data of Evaporation and save as nc
DataCube_ET_CR = RC.Get3Darray_time_series_monthly(
Dir_Basin,
Data_Path_ET,
Startdate_2months,
Enddate,
Example_data=Example_dataset)
DC.Save_as_NC(Name_NC_ET_CR, DataCube_ET_CR, 'ET_CR', Example_dataset,
Startdate_2months, Enddate, 'monthly', 0.01)
del DataCube_ET_CR
#_______________________Reference Evapotranspiration_______________________
# Reference Evapotranspiration data
Name_NC_ETref_CR = DC.Create_NC_name('ETref_CR', Simulation, Dir_Basin, 5,
info)
if not os.path.exists(Name_NC_ETref_CR):
# Get the data of Reference Evapotranspiration and save as nc
DataCube_ETref_CR = RC.Get3Darray_time_series_monthly(
Dir_Basin,
Data_Path_ETref,
Startdate_2months,
Enddate,
Example_data=Example_dataset)
DC.Save_as_NC(Name_NC_ETref_CR, DataCube_ETref_CR, 'ETref_CR',
Example_dataset, Startdate_2months, Enddate, 'monthly',
0.01)
del DataCube_ETref_CR
#_______________________fraction surface water _______________________
Name_NC_frac_sw_CR = DC.Create_NC_name('Fraction_SW_CR', Simulation,
Dir_Basin, 5)
if not os.path.exists(Name_NC_frac_sw_CR):
DataCube_frac_sw = np.ones_like(LU_data) * np.nan
import wa.Functions.Start.Get_Dictionaries as GD
# Get dictionaries and keys
lulc = GD.get_sheet5_classes()
lulc_dict = GD.get_sheet5_classes().keys()
consumed_frac_dict = GD.sw_supply_fractions_sheet5()
for key in lulc_dict:
Numbers = lulc[key]
for LU_nmbr in Numbers:
Mask = np.zeros_like(LU_data)
Mask[LU_data == LU_nmbr] = 1
DataCube_frac_sw[Mask == 1] = consumed_frac_dict[key]
dest_frac_sw = DC.Save_as_MEM(DataCube_frac_sw, geo_out_LU, proj_LU)
dest_frac_sw_CR = RC.reproject_dataset_example(dest_frac_sw,
Example_dataset)
DataCube_frac_sw_CR = dest_frac_sw_CR.ReadAsArray()
DataCube_frac_sw_CR[DataCube_frac_sw_CR == 0] = np.nan
DC.Save_as_NC(Name_NC_frac_sw_CR,
DataCube_frac_sw_CR,
'Fraction_SW_CR',
Example_dataset,
Scaling_factor=0.01)
del DataCube_frac_sw_CR
del DataCube_DEM_CR
##################### 4. Create Mask based on LU map ###########################
# Now a mask will be created to define the area of interest (pixels where there is a landuse defined)
#_____________________________________LU___________________________________
destLU = RC.reproject_dataset_example(LU_dataset,
Example_dataset,
method=1)
DataCube_LU_CR = destLU.GetRasterBand(1).ReadAsArray()
Raster_Basin_CR = np.zeros([Ysize_CR, Xsize_CR])
Raster_Basin_CR[DataCube_LU_CR > 0] = 1
Name_NC_Basin_CR = DC.Create_NC_name('Basin_CR', Simulation, Dir_Basin, 5)
if not os.path.exists(Name_NC_Basin_CR):
DC.Save_as_NC(Name_NC_Basin_CR, Raster_Basin_CR, 'Basin_CR',
Example_dataset)
#del Raster_Basin
'''
Name_NC_Basin = DC.Create_NC_name('Basin_CR', Simulation, Dir_Basin, 5)
if not os.path.exists(Name_NC_Basin):
Raster_Basin = RC.Vector_to_Raster(Dir_Basin, Shape_file_name_shp, Example_dataset)
Raster_Basin = np.clip(Raster_Basin, 0, 1)
DC.Save_as_NC(Name_NC_Basin, Raster_Basin, 'Basin_CR', Example_dataset)
#del Raster_Basin
'''
###################### 5. Calculate Runoff based on Budyko ###########################
# Define info for the nc files
info = [
'monthly', 'mm', ''.join([Startdate[5:7], Startdate[0:4]]),
''.join([Enddate[5:7], Enddate[0:4]])
]
# Define the output names of section 5 and 6
Name_NC_Runoff_CR = DC.Create_NC_name('Runoff_CR', Simulation, Dir_Basin,
5, info)
Name_NC_Runoff_for_Routing_CR = Name_NC_Runoff_CR
if not os.path.exists(Name_NC_Runoff_CR):
# Calculate runoff based on Budyko
DataCube_Runoff_CR = Five.Budyko.Calc_runoff(Name_NC_ETref_CR,
Name_NC_Prec_CR)
# Save the runoff as netcdf
DC.Save_as_NC(Name_NC_Runoff_CR, DataCube_Runoff_CR, 'Runoff_CR',
Example_dataset, Startdate, Enddate, 'monthly', 0.01)
del DataCube_Runoff_CR
'''
###################### Calculate Runoff with P min ET ###########################
Name_NC_Runoff_CR = DC.Create_NC_name('Runoff_CR', Simulation, Dir_Basin, 5, info)
if not os.path.exists(Name_NC_Runoff_CR):
ET = RC.Open_nc_array(Name_NC_ET_CR)
P = RC.Open_nc_array(Name_NC_Prec_CR)
DataCube_Runoff_CR = P - ET
DataCube_Runoff_CR[:,:,:][DataCube_Runoff_CR<=0.1] = 0
DataCube_Runoff_CR[:,:,:][np.isnan(DataCube_Runoff_CR)] = 0
DC.Save_as_NC(Name_NC_Runoff_CR, DataCube_Runoff_CR, 'Runoff_CR', Example_dataset, Startdate, Enddate, 'monthly')
del DataCube_Runoff_CR
'''
############### 6. Add inflow in basin by using textfile #########################
# add inlets if there are textfiles defined
if len(Inflow_Text_Files) > 0:
# Create name of the Runoff with inlets
Name_NC_Runoff_with_Inlets_CR = DC.Create_NC_name(
'Runoff_with_Inlets_CR', Simulation, Dir_Basin, 5, info)
# Use this runoff name for the routing (it will overwrite the runoff without inlets)
Name_NC_Runoff_for_Routing_CR = Name_NC_Runoff_with_Inlets_CR
# Create the file if it not exists
if not os.path.exists(Name_NC_Runoff_with_Inlets_CR):
# Calculate the runoff that will be routed by including the inlets
DataCube_Runoff_with_Inlets_CR = Five.Inlets.Add_Inlets(
Name_NC_Runoff_CR, Inflow_Text_Files)
# Save this runoff as netcdf
DC.Save_as_NC(Name_NC_Runoff_with_Inlets_CR,
DataCube_Runoff_with_Inlets_CR,
'Runoff_with_Inlets_CR', Example_dataset, Startdate,
Enddate, 'monthly', 0.01)
del DataCube_Runoff_with_Inlets_CR
######################### 7. Now the surface water is calculated #################
# Names for dicionaries and nc files
# CR1 = Natural_flow with only green water
# CR2 = Natural_flow with only green water and reservoirs
# CR3 = Flow with green, blue and reservoirs
######################### 7.1 Apply Channel Routing ###############################
# Create the name for the netcdf outputs for section 7.1
info = [
'monthly', 'pixels', ''.join([Startdate[5:7], Startdate[0:4]]),
''.join([Enddate[5:7], Enddate[0:4]])
]
Name_NC_Acc_Pixels_CR = DC.Create_NC_name('Acc_Pixels_CR', Simulation,
Dir_Basin, 5)
info = [
'monthly', 'm3', ''.join([Startdate[5:7], Startdate[0:4]]),
''.join([Enddate[5:7], Enddate[0:4]])
]
Name_NC_Discharge_CR1 = DC.Create_NC_name('Discharge_CR1', Simulation,
Dir_Basin, 5, info)
# If one of the outputs does not exists, run this part
if not (os.path.exists(Name_NC_Acc_Pixels_CR)
and os.path.exists(Name_NC_Discharge_CR1)):
Accumulated_Pixels_CR, Discharge_CR1 = Five.Channel_Routing.Channel_Routing(
Name_NC_DEM_Dir_CR,
Name_NC_Runoff_for_Routing_CR,
Name_NC_Basin_CR,
Example_dataset,
Degrees=1)
# Save Results
DC.Save_as_NC(Name_NC_Acc_Pixels_CR, Accumulated_Pixels_CR,
'Acc_Pixels_CR', Example_dataset)
DC.Save_as_NC(Name_NC_Discharge_CR1, Discharge_CR1, 'Discharge_CR1',
Example_dataset, Startdate, Enddate, 'monthly')
################# Calculate the natural river and river zones #################
Name_NC_Rivers_CR = DC.Create_NC_name('Rivers_CR', Simulation, Dir_Basin,
5, info)
if not os.path.exists(Name_NC_Rivers_CR):
# Open routed discharge array
Discharge_CR1 = RC.Open_nc_array(Name_NC_Discharge_CR1)
Raster_Basin = RC.Open_nc_array(Name_NC_Basin_CR)
# Calculate mean average over the period
if len(np.shape(Discharge_CR1)) > 2:
Routed_Discharge_Ave = np.nanmean(Discharge_CR1, axis=0)
else:
Routed_Discharge_Ave = Discharge_CR1
# Define the 2% highest pixels as rivers
Rivers = np.zeros([
np.size(Routed_Discharge_Ave, 0),
np.size(Routed_Discharge_Ave, 1)
])
Routed_Discharge_Ave[Raster_Basin != 1] = np.nan
Routed_Discharge_Ave_number = np.nanpercentile(Routed_Discharge_Ave,
98)
Rivers[
Routed_Discharge_Ave >
Routed_Discharge_Ave_number] = 1 # if yearly average is larger than 5000km3/month that it is a river
# Save the river file as netcdf file
DC.Save_as_NC(Name_NC_Rivers_CR, Rivers, 'Rivers_CR', Example_dataset)
########################## Create river directories ###########################
Name_py_River_dict_CR1 = os.path.join(
Dir_Basin, 'Simulations', 'Simulation_%d' % Simulation, 'Sheet_5',
'River_dict_CR1_simulation%d.npy' % (Simulation))
Name_py_DEM_dict_CR1 = os.path.join(
Dir_Basin, 'Simulations', 'Simulation_%d' % Simulation, 'Sheet_5',
'DEM_dict_CR1_simulation%d.npy' % (Simulation))
Name_py_Distance_dict_CR1 = os.path.join(
Dir_Basin, 'Simulations', 'Simulation_%d' % Simulation, 'Sheet_5',
'Distance_dict_CR1_simulation%d.npy' % (Simulation))
if not (os.path.exists(Name_py_River_dict_CR1)
and os.path.exists(Name_py_DEM_dict_CR1)
and os.path.exists(Name_py_Distance_dict_CR1)):
# Get river and DEM dict
River_dict_CR1, DEM_dict_CR1, Distance_dict_CR1 = Five.Create_Dict.Rivers_General(
Name_NC_DEM_CR, Name_NC_DEM_Dir_CR, Name_NC_Acc_Pixels_CR,
Name_NC_Rivers_CR, Example_dataset)
np.save(Name_py_River_dict_CR1, River_dict_CR1)
np.save(Name_py_DEM_dict_CR1, DEM_dict_CR1)
np.save(Name_py_Distance_dict_CR1, Distance_dict_CR1)
else:
# Load
River_dict_CR1 = np.load(Name_py_River_dict_CR1).item()
DEM_dict_CR1 = np.load(Name_py_DEM_dict_CR1).item()
Distance_dict_CR1 = np.load(Name_py_Distance_dict_CR1).item()
Name_py_Discharge_dict_CR1 = os.path.join(
Dir_Basin, 'Simulations', 'Simulation_%d' % Simulation, 'Sheet_5',
'Discharge_dict_CR1_simulation%d.npy' % (Simulation))
if not os.path.exists(Name_py_Discharge_dict_CR1):
# Get discharge dict
Discharge_dict_CR1 = Five.Create_Dict.Discharge(
Name_NC_Discharge_CR1, River_dict_CR1, Amount_months,
Example_dataset)
np.save(Name_py_Discharge_dict_CR1, Discharge_dict_CR1)
else:
# Load
Discharge_dict_CR1 = np.load(Name_py_Discharge_dict_CR1).item()
###################### 7.2 Calculate surface water storage characteristics ######################
Name_py_Discharge_dict_CR2 = os.path.join(
Dir_Basin, 'Simulations', 'Simulation_%d' % Simulation, 'Sheet_5',
'Discharge_dict_CR2_simulation%d.npy' % (Simulation))
Name_py_River_dict_CR2 = os.path.join(
Dir_Basin, 'Simulations', 'Simulation_%d' % Simulation, 'Sheet_5',
'River_dict_CR2_simulation%d.npy' % (Simulation))
Name_py_DEM_dict_CR2 = os.path.join(
Dir_Basin, 'Simulations', 'Simulation_%d' % Simulation, 'Sheet_5',
'DEM_dict_CR2_simulation%d.npy' % (Simulation))
Name_py_Distance_dict_CR2 = os.path.join(
Dir_Basin, 'Simulations', 'Simulation_%d' % Simulation, 'Sheet_5',
'Distance_dict_CR2_simulation%d.npy' % (Simulation))
Name_py_Diff_Water_Volume = os.path.join(
Dir_Basin, 'Simulations', 'Simulation_%d' % Simulation, 'Sheet_5',
'Diff_Water_Volume_CR2_simulation%d.npy' % (Simulation))
Name_py_Regions = os.path.join(Dir_Basin, 'Simulations',
'Simulation_%d' % Simulation, 'Sheet_5',
'Regions_simulation%d.npy' % (Simulation))
if not (os.path.exists(Name_py_Discharge_dict_CR2)
and os.path.exists(Name_py_River_dict_CR2)
and os.path.exists(Name_py_DEM_dict_CR2)
and os.path.exists(Name_py_Distance_dict_CR2)):
# Copy dicts as starting adding reservoir
Discharge_dict_CR2 = copy.deepcopy(Discharge_dict_CR1)
River_dict_CR2 = copy.deepcopy(River_dict_CR1)
DEM_dict_CR2 = copy.deepcopy(DEM_dict_CR1)
Distance_dict_CR2 = copy.deepcopy(Distance_dict_CR1)
if Reservoirs_Lakes_Calculations == 1:
# define input tiffs for surface water calculations
input_JRC = os.path.join(Dir_Basin, Data_Path_JRC_occurrence,
'JRC_Occurrence_percent.tif')
DEM_dataset = os.path.join(Dir_Basin, Data_Path_DEM,
'DEM_HydroShed_m_3s.tif')
sensitivity = 700 # 900 is less sensitive 1 is very sensitive
Regions = Five.Reservoirs.Calc_Regions(Name_NC_Basin_CR, input_JRC,
sensitivity, Boundaries)
Diff_Water_Volume = np.zeros(
[len(Regions), Amount_months_reservoirs - 1, 3])
reservoir = 0
for region in Regions:
popt = Five.Reservoirs.Find_Area_Volume_Relation(
region, input_JRC, DEM_dataset)
Area_Reservoir_Values = Five.Reservoirs.GEE_calc_reservoir_area(
region, Startdate, Enddate)
Diff_Water_Volume[
reservoir, :, :] = Five.Reservoirs.Calc_Diff_Storage(
Area_Reservoir_Values, popt)
reservoir += 1
################# 7.3 Add storage reservoirs and change outflows ##################
Discharge_dict_CR2, River_dict_CR2, DEM_dict_CR2, Distance_dict_CR2 = Five.Reservoirs.Add_Reservoirs(
Name_NC_Rivers_CR, Name_NC_Acc_Pixels_CR, Diff_Water_Volume,
River_dict_CR2, Discharge_dict_CR2, DEM_dict_CR2,
Distance_dict_CR2, Regions, Example_dataset)
np.save(Name_py_Regions, Regions)
np.save(Name_py_Diff_Water_Volume, Diff_Water_Volume)
np.save(Name_py_Discharge_dict_CR2, Discharge_dict_CR2)
np.save(Name_py_River_dict_CR2, River_dict_CR2)
np.save(Name_py_DEM_dict_CR2, DEM_dict_CR2)
np.save(Name_py_Distance_dict_CR2, Distance_dict_CR2)
else:
# Load
Discharge_dict_CR2 = np.load(Name_py_Discharge_dict_CR2).item()
River_dict_CR2 = np.load(Name_py_River_dict_CR2).item()
DEM_dict_CR2 = np.load(Name_py_DEM_dict_CR2).item()
Distance_dict_CR2 = np.load(Name_py_Distance_dict_CR2).item()
####################### 7.3 Add surface water withdrawals #############################
Name_py_Discharge_dict_CR3 = os.path.join(
Dir_Basin, 'Simulations', 'Simulation_%d' % Simulation, 'Sheet_5',
'Discharge_dict_CR3_simulation%d.npy' % (Simulation))
if not os.path.exists(Name_py_Discharge_dict_CR3):
Discharge_dict_CR3, DataCube_ETblue_m3 = Five.Irrigation.Add_irrigation(
Discharge_dict_CR2, River_dict_CR2, Name_NC_Rivers_CR,
Name_NC_ET_CR, Name_NC_ETref_CR, Name_NC_Prec_CR, Name_NC_Basin_CR,
Name_NC_frac_sw_CR, Startdate, Enddate, Example_dataset)
np.save(Name_py_Discharge_dict_CR3, Discharge_dict_CR3)
# save ETblue as nc
info = [
'monthly', 'm3-month-1', ''.join([Startdate[5:7], Startdate[0:4]]),
''.join([Enddate[5:7], Enddate[0:4]])
]
Name_NC_ETblue = DC.Create_NC_name('ETblue', Simulation, Dir_Basin, 5,
info)
DC.Save_as_NC(Name_NC_ETblue, DataCube_ETblue_m3, 'ETblue',
Example_dataset, Startdate, Enddate, 'monthly')
else:
Discharge_dict_CR3 = np.load(Name_py_Discharge_dict_CR3).item()
################################# Plot graph ##################################
# Draw graph
Five.Channel_Routing.Graph_DEM_Distance_Discharge(
Discharge_dict_CR3, Distance_dict_CR2, DEM_dict_CR2, River_dict_CR2,
Startdate, Enddate, Example_dataset)
######################## Change data to fit the LU data #######################
# Discharge
# Define info for the nc files
info = [
'monthly', 'm3-month-1', ''.join([Startdate[5:7], Startdate[0:4]]),
''.join([Enddate[5:7], Enddate[0:4]])
]
Name_NC_Discharge = DC.Create_NC_name('Discharge', Simulation, Dir_Basin,
5, info)
if not os.path.exists(Name_NC_Discharge):
# Get the data of Reference Evapotranspiration and save as nc
DataCube_Discharge_CR = DC.Convert_dict_to_array(
River_dict_CR2, Discharge_dict_CR3, Example_dataset)
DC.Save_as_NC(Name_NC_Discharge, DataCube_Discharge_CR, 'Discharge',
Example_dataset, Startdate, Enddate, 'monthly')
del DataCube_Discharge_CR
# DEM
Name_NC_DEM = DC.Create_NC_name('DEM', Simulation, Dir_Basin, 5)
if not os.path.exists(Name_NC_DEM):
# Get the data of Reference Evapotranspiration and save as nc
DataCube_DEM_CR = RC.Open_nc_array(Name_NC_DEM_CR)
DataCube_DEM = RC.resize_array_example(DataCube_DEM_CR,
LU_data,
method=1)
DC.Save_as_NC(Name_NC_DEM, DataCube_DEM, 'DEM', LU_dataset)
del DataCube_DEM
# flow direction
Name_NC_DEM_Dir = DC.Create_NC_name('DEM_Dir', Simulation, Dir_Basin, 5)
if not os.path.exists(Name_NC_DEM_Dir):
# Get the data of Reference Evapotranspiration and save as nc
DataCube_DEM_Dir_CR = RC.Open_nc_array(Name_NC_DEM_Dir_CR)
DataCube_DEM_Dir = RC.resize_array_example(DataCube_DEM_Dir_CR,
LU_data,
method=1)
DC.Save_as_NC(Name_NC_DEM_Dir, DataCube_DEM_Dir, 'DEM_Dir', LU_dataset)
del DataCube_DEM_Dir
# Precipitation
# Define info for the nc files
info = [
'monthly', 'mm', ''.join([Startdate[5:7], Startdate[0:4]]),
''.join([Enddate[5:7], Enddate[0:4]])
]
Name_NC_Prec = DC.Create_NC_name('Prec', Simulation, Dir_Basin, 5)
if not os.path.exists(Name_NC_Prec):
# Get the data of Reference Evapotranspiration and save as nc
DataCube_Prec = RC.Get3Darray_time_series_monthly(
Dir_Basin, Data_Path_P_Monthly, Startdate, Enddate, LU_dataset)
DC.Save_as_NC(Name_NC_Prec, DataCube_Prec, 'Prec', LU_dataset,
Startdate, Enddate, 'monthly', 0.01)
del DataCube_Prec
# Evapotranspiration
Name_NC_ET = DC.Create_NC_name('ET', Simulation, Dir_Basin, 5)
if not os.path.exists(Name_NC_ET):
# Get the data of Reference Evapotranspiration and save as nc
DataCube_ET = RC.Get3Darray_time_series_monthly(
Dir_Basin, Data_Path_ET, Startdate, Enddate, LU_dataset)
DC.Save_as_NC(Name_NC_ET, DataCube_ET, 'ET', LU_dataset, Startdate,
Enddate, 'monthly', 0.01)
del DataCube_ET
# Reference Evapotranspiration data
Name_NC_ETref = DC.Create_NC_name('ETref', Simulation, Dir_Basin, 5, info)
if not os.path.exists(Name_NC_ETref):
# Get the data of Reference Evapotranspiration and save as nc
DataCube_ETref = RC.Get3Darray_time_series_monthly(
Dir_Basin, Data_Path_ETref, Startdate, Enddate, LU_dataset)
DC.Save_as_NC(Name_NC_ETref, DataCube_ETref, 'ETref', LU_dataset,
Startdate, Enddate, 'monthly', 0.01)
del DataCube_ETref
# Rivers
Name_NC_Rivers = DC.Create_NC_name('Rivers', Simulation, Dir_Basin, 5,
info)
if not os.path.exists(Name_NC_Rivers):
# Get the data of Reference Evapotranspiration and save as nc
Rivers_CR = RC.Open_nc_array(Name_NC_Rivers_CR)
DataCube_Rivers = RC.resize_array_example(Rivers_CR, LU_data)
DC.Save_as_NC(Name_NC_Rivers, DataCube_Rivers, 'Rivers', LU_dataset)
del DataCube_Rivers, Rivers_CR
# Discharge
# Define info for the nc files
info = [
'monthly', 'm3', ''.join([Startdate[5:7], Startdate[0:4]]),
''.join([Enddate[5:7], Enddate[0:4]])
]
Name_NC_Routed_Discharge = DC.Create_NC_name('Routed_Discharge',
Simulation, Dir_Basin, 5,
info)
if not os.path.exists(Name_NC_Routed_Discharge):
# Get the data of Reference Evapotranspiration and save as nc
Routed_Discharge_CR = RC.Open_nc_array(Name_NC_Discharge)
DataCube_Routed_Discharge = RC.resize_array_example(
Routed_Discharge_CR, LU_data)
DC.Save_as_NC(Name_NC_Routed_Discharge, DataCube_Routed_Discharge,
'Routed_Discharge', LU_dataset, Startdate, Enddate,
'monthly')
del DataCube_Routed_Discharge, Routed_Discharge_CR
# Get raster information
geo_out, proj, size_X, size_Y = RC.Open_array_info(Example_dataset)
Rivers = RC.Open_nc_array(Name_NC_Rivers_CR)
# Create ID Matrix
y, x = np.indices((size_Y, size_X))
ID_Matrix = np.int32(
np.ravel_multi_index(np.vstack((y.ravel(), x.ravel())),
(size_Y, size_X),
mode='clip').reshape(x.shape)) + 1
# Get tiff array time dimension:
time_dimension = int(np.shape(Discharge_dict_CR3[0])[0])
# create an empty array
Result = np.zeros([time_dimension, size_Y, size_X])
for river_part in range(0, len(River_dict_CR2)):
for river_pixel in range(1, len(River_dict_CR2[river_part])):
river_pixel_ID = River_dict_CR2[river_part][river_pixel]
if len(np.argwhere(ID_Matrix == river_pixel_ID)) > 0:
row, col = np.argwhere(ID_Matrix == river_pixel_ID)[0][:]
Result[:, row,
col] = Discharge_dict_CR3[river_part][:, river_pixel]
print(river_part)
Outflow = Discharge_dict_CR3[0][:, 1]
for i in range(0, time_dimension):
output_name = r'C:/testmap/rtest_%s.tif' % i
Result_one = Result[i, :, :]
DC.Save_as_tiff(output_name, Result_one, geo_out, "WGS84")
import os
# Get environmental variable for the Home folder
WA_env_paths = os.environ["WA_HOME"].split(';')
Dir_Home = WA_env_paths[0]
# Create the Basin folder
Dir_Basin = os.path.join(Dir_Home, Basin)
info = [
'monthly', 'm3-month-1', ''.join([Startdate[5:7], Startdate[0:4]]),
''.join([Enddate[5:7], Enddate[0:4]])
]
Name_Result = DC.Create_NC_name('DischargeEnd', Simulation, Dir_Basin, 5,
info)
Result[np.logical_and(Result == 0.0, Rivers == 0.0)] = np.nan
DC.Save_as_NC(Name_Result, Result, 'DischargeEnd', Example_dataset,
Startdate, Enddate, 'monthly')
return ()
def Calculate(WA_HOME_folder, Basin, P_Product, ET_Product, ETref_Product, DEM_Product, Water_Occurence_Product, Inflow_Text_Files, WaterPIX_filename, Reservoirs_GEE_on_off, Supply_method, Startdate, Enddate, Simulation):
'''
This functions consists of the following sections:
1. Set General Parameters
2. Download Data
3. Convert the RAW data to NETCDF files
4. Run SurfWAT
'''
# import General modules
import os
import gdal
import numpy as np
import pandas as pd
from netCDF4 import Dataset
# import WA plus modules
from wa.General import raster_conversions as RC
from wa.General import data_conversions as DC
import wa.Functions.Five as Five
import wa.Functions.Start as Start
import wa.Functions.Start.Get_Dictionaries as GD
######################### 1. Set General Parameters ##############################
# Get environmental variable for the Home folder
if WA_HOME_folder == '':
WA_env_paths = os.environ["WA_HOME"].split(';')
Dir_Home = WA_env_paths[0]
else:
Dir_Home = WA_HOME_folder
# Create the Basin folder
Dir_Basin = os.path.join(Dir_Home, Basin)
output_dir = os.path.join(Dir_Basin, "Simulations", "Simulation_%d" %Simulation)
if not os.path.exists(output_dir):
os.makedirs(output_dir)
# Get the boundaries of the basin based on the shapefile of the watershed
# Boundaries, Shape_file_name_shp = Start.Boundaries.Determine(Basin)
Boundaries, Example_dataset = Start.Boundaries.Determine_LU_Based(Basin, Dir_Home)
geo_out, proj, size_X, size_Y = RC.Open_array_info(Example_dataset)
# Define resolution of SRTM
Resolution = '15s'
# Find the maximum moving window value
ET_Blue_Green_Classes_dict, Moving_Window_Per_Class_dict = GD.get_bluegreen_classes(version = '1.0')
Additional_Months_tail = np.max(Moving_Window_Per_Class_dict.values())
############## Cut dates into pieces if it is needed ######################
# Check the years that needs to be calculated
years = range(int(Startdate.split('-')[0]),int(Enddate.split('-')[0]) + 1)
for year in years:
# Create .nc file if not exists
nc_outname = os.path.join(output_dir, "%d.nc" % year)
if not os.path.exists(nc_outname):
DC.Create_new_NC_file(nc_outname, Example_dataset, Basin)
# Open variables in netcdf
fh = Dataset(nc_outname)
Variables_NC = [var for var in fh.variables]
fh.close()
# Create Start and End date for time chunk
Startdate_part = '%d-01-01' %int(year)
Enddate_part = '%s-12-31' %int(year)
if int(year) == int(years[0]):
Startdate_Moving_Average = pd.Timestamp(Startdate) - pd.DateOffset(months = Additional_Months_tail)
Startdate_Moving_Average_String = Startdate_Moving_Average.strftime('%Y-%m-%d')
else:
Startdate_Moving_Average_String = Startdate_part
############################# 2. Download Data ###################################
# Download data
if not "Precipitation" in Variables_NC:
Data_Path_P_Monthly = Start.Download_Data.Precipitation(Dir_Basin, [Boundaries['Latmin'],Boundaries['Latmax']],[Boundaries['Lonmin'],Boundaries['Lonmax']], Startdate_part, Enddate_part, P_Product)
if not "Actual_Evapotranspiration" in Variables_NC:
Data_Path_ET = Start.Download_Data.Evapotranspiration(Dir_Basin, [Boundaries['Latmin'],Boundaries['Latmax']],[Boundaries['Lonmin'],Boundaries['Lonmax']], Startdate_part, Enddate_part, ET_Product)
if (WaterPIX_filename == "" or Supply_method == "Fraction") and not ("Reference_Evapotranspiration" in Variables_NC):
Data_Path_ETref = Start.Download_Data.ETreference(Dir_Basin, [Boundaries['Latmin'],Boundaries['Latmax']],[Boundaries['Lonmin'],Boundaries['Lonmax']], Startdate_Moving_Average_String, Enddate_part, ETref_Product)
if Reservoirs_GEE_on_off == 1 and not ("Water_Occurrence" in Variables_NC):
Data_Path_JRC_occurrence = Start.Download_Data.JRC_occurrence(Dir_Basin, [Boundaries['Latmin'],Boundaries['Latmax']],[Boundaries['Lonmin'],Boundaries['Lonmax']], Water_Occurence_Product)
input_JRC = os.path.join(Data_Path_JRC_occurrence, "JRC_Occurrence_percent.tif")
else:
input_JRC = None
# WaterPIX input
Data_Path_DEM_Dir = Start.Download_Data.DEM_Dir(Dir_Basin, [Boundaries['Latmin'],Boundaries['Latmax']],[Boundaries['Lonmin'],Boundaries['Lonmax']], Resolution, DEM_Product)
Data_Path_DEM = Start.Download_Data.DEM(Dir_Basin, [Boundaries['Latmin'],Boundaries['Latmax']],[Boundaries['Lonmin'],Boundaries['Lonmax']], Resolution, DEM_Product)
###################### 3. Convert the RAW data to NETCDF files ##############################
# The sequence of converting the data into netcdf is:
# Precipitation
# Evapotranspiration
# Reference Evapotranspiration
# DEM flow directions
#______________________________Precipitation_______________________________
# 1.) Precipitation data
if not "Precipitation" in Variables_NC:
# Get the data of Precipitation and save as nc
DataCube_Prec = RC.Get3Darray_time_series_monthly(Data_Path_P_Monthly, Startdate_part, Enddate_part, Example_data = Example_dataset)
DC.Add_NC_Array_Variable(nc_outname, DataCube_Prec, "Precipitation", "mm/month", 0.01)
del DataCube_Prec
#_______________________________Evaporation________________________________
# 2.) Evapotranspiration data
if not "Actual_Evapotranspiration" in Variables_NC:
# Get the data of Evaporation and save as nc
DataCube_ET = RC.Get3Darray_time_series_monthly(Data_Path_ET, Startdate_part, Enddate_part, Example_data = Example_dataset)
DC.Add_NC_Array_Variable(nc_outname, DataCube_ET, "Actual_Evapotranspiration", "mm/month", 0.01)
del DataCube_ET
#_______________________Reference Evaporation______________________________
# 3.) Reference Evapotranspiration data
if (WaterPIX_filename == "" or Supply_method == "Fraction") and not ("Reference_Evapotranspiration" in Variables_NC):
# Get the data of Precipitation and save as nc
DataCube_ETref = RC.Get3Darray_time_series_monthly(Data_Path_ETref, Startdate_part, Enddate_part, Example_data = Example_dataset)
DC.Add_NC_Array_Variable(nc_outname, DataCube_ETref, "Reference_Evapotranspiration", "mm/month", 0.01)
del DataCube_ETref
#____________________________fraction surface water _______________________
DataCube_frac_sw = np.ones([size_Y, size_X]) * np.nan
import wa.Functions.Start.Get_Dictionaries as GD
# Open LU dataset
DataCube_LU = RC.Open_nc_array(nc_outname, "Landuse")
# Get dictionaries and keys
lulc = GD.get_sheet5_classes()
lulc_dict = GD.get_sheet5_classes().keys()
consumed_frac_dict = GD.sw_supply_fractions()
for key in lulc_dict:
Numbers = lulc[key]
for LU_nmbr in Numbers:
DataCube_frac_sw[DataCube_LU==LU_nmbr] = consumed_frac_dict[key]
DC.Add_NC_Array_Static(nc_outname, DataCube_frac_sw, "Fraction_Surface_Water_Supply", "fraction", 0.01)
del DataCube_frac_sw, DataCube_LU
################### 4. Calculate Runoff (2 methods: a = Budyko and b = WaterPIX) #####################
################ 4a. Calculate Runoff based on Precipitation and Evapotranspiration ##################
if (Supply_method == "Fraction" and not "Surface_Runoff" in Variables_NC):
# Calculate runoff based on Budyko
DataCube_Runoff = Five.Fraction_Based.Calc_surface_runoff(Dir_Basin, nc_outname, Startdate_part, Enddate_part, Example_dataset, ETref_Product, P_Product)
# Save the runoff as netcdf
DC.Add_NC_Array_Variable(nc_outname, DataCube_Runoff, "Surface_Runoff", "mm/month", 0.01)
del DataCube_Runoff
###################### 4b. Get Runoff from WaterPIX ###########################
if (Supply_method == "WaterPIX" and not "Surface_Runoff" in Variables_NC):
# Get WaterPIX data
WaterPIX_Var = 'TotalRunoff_M'
DataCube_Runoff = Five.Read_WaterPIX.Get_Array(WaterPIX_filename, WaterPIX_Var, Example_dataset, Startdate_part, Enddate_part)
# Save the runoff as netcdf
DC.Add_NC_Array_Variable(nc_outname, DataCube_Runoff, "Surface_Runoff", "mm/month", 0.01)
del DataCube_Runoff
####################### 5. Calculate Extraction (2 methods: a = Fraction, b = WaterPIX) #############################
###################### 5a. Get extraction from fraction method by using budyko ###########################
if (Supply_method == "Fraction" and not "Surface_Withdrawal" in Variables_NC):
DataCube_surface_withdrawal = Five.Fraction_Based.Calc_surface_withdrawal(Dir_Basin, nc_outname, Startdate_part, Enddate_part, Example_dataset, ETref_Product, P_Product)
# Save the runoff as netcdf
DC.Add_NC_Array_Variable(nc_outname, DataCube_surface_withdrawal, "Surface_Withdrawal", "mm/month", 0.01)
del DataCube_surface_withdrawal
#################################### 5b. Get extraction from WaterPIX ####################################
if (Supply_method == "WaterPIX" and not "Surface_Withdrawal" in Variables_NC):
WaterPIX_Var = 'Supply_M'
DataCube_Supply = Five.Read_WaterPIX.Get_Array(WaterPIX_filename, WaterPIX_Var, Example_dataset, Startdate, Enddate)
# Open array with surface water fractions
DataCube_frac_sw = RC.Open_nc_array(nc_outname, "Fraction_Surface_Water_Supply")
# Total amount of ETblue taken out of rivers
DataCube_surface_withdrawal = DataCube_Supply * DataCube_frac_sw[None,:,:]
# Save the runoff as netcdf
DC.Add_NC_Array_Variable(nc_outname, DataCube_surface_withdrawal, "Surface_Withdrawal", "mm/month", 0.01)
del DataCube_surface_withdrawal
################################## 5. Run SurfWAT #####################################
import wa.Models.SurfWAT as SurfWAT
# Define formats of input data
Format_DEM = "TIFF" # or "TIFF"
Format_Runoff = "NetCDF" # or "TIFF"
Format_Extraction = "NetCDF" # or "TIFF"
Format_DEM_dir = "TIFF" # or "TIFF"
Format_Basin = "NetCDF" # or "TIFF"
# Give path (for tiff) or file (netcdf)
input_nc = os.path.join(Dir_Basin, "Simulations", "Simulation_%s"%Simulation,"SurfWAT_in_%d.nc" %year)
output_nc = os.path.join(Dir_Basin, "Simulations", "Simulation_%s"%Simulation,"SurfWAT_out_%d.nc" %year)
# Create Input File for SurfWAT
SurfWAT.Create_input_nc.main(Data_Path_DEM_Dir,
Data_Path_DEM,
os.path.dirname(nc_outname),
os.path.dirname(nc_outname),
os.path.dirname(nc_outname),
Startdate,
Enddate,
input_nc,
Resolution,
Format_DEM_dir,
Format_DEM,
Format_Basin,
Format_Runoff,
Format_Extraction)
# Run SurfWAT
SurfWAT.Run_SurfWAT.main(input_nc, output_nc, input_JRC, Inflow_Text_Files, Reservoirs_GEE_on_off)
'''
################################# Plot graph ##################################
# Draw graph
Five.Channel_Routing.Graph_DEM_Distance_Discharge(Discharge_dict_CR3, Distance_dict_CR2, DEM_dict_CR2, River_dict_CR2, Startdate, Enddate, Example_dataset)
######################## Change data to fit the LU data #######################
# Discharge
# Define info for the nc files
info = ['monthly','m3-month-1', ''.join([Startdate[5:7], Startdate[0:4]]) , ''.join([Enddate[5:7], Enddate[0:4]])]
Name_NC_Discharge = DC.Create_NC_name('DischargeEnd', Simulation, Dir_Basin, 5, info)
if not os.path.exists(Name_NC_Discharge):
# Get the data of Reference Evapotranspiration and save as nc
DataCube_Discharge_CR = DC.Convert_dict_to_array(River_dict_CR2, Discharge_dict_CR3, Example_dataset)
DC.Save_as_NC(Name_NC_Discharge, DataCube_Discharge_CR, 'Discharge_End_CR', Example_dataset, Startdate, Enddate, 'monthly')
del DataCube_Discharge_CR
'''
'''
# DEM
Name_NC_DEM = DC.Create_NC_name('DEM', Simulation, Dir_Basin, 5)
if not os.path.exists(Name_NC_DEM):
# Get the data of Reference Evapotranspiration and save as nc
DataCube_DEM_CR = RC.Open_nc_array(Name_NC_DEM_CR)
DataCube_DEM = RC.resize_array_example(DataCube_DEM_CR, LU_data, method=1)
DC.Save_as_NC(Name_NC_DEM, DataCube_DEM, 'DEM', LU_dataset)
del DataCube_DEM
# flow direction
Name_NC_DEM_Dir = DC.Create_NC_name('DEM_Dir', Simulation, Dir_Basin, 5)
if not os.path.exists(Name_NC_DEM_Dir):
# Get the data of Reference Evapotranspiration and save as nc
DataCube_DEM_Dir_CR = RC.Open_nc_array(Name_NC_DEM_Dir_CR)
DataCube_DEM_Dir = RC.resize_array_example(DataCube_DEM_Dir_CR, LU_data, method=1)
DC.Save_as_NC(Name_NC_DEM_Dir, DataCube_DEM_Dir, 'DEM_Dir', LU_dataset)
del DataCube_DEM_Dir
# Precipitation
# Define info for the nc files
info = ['monthly','mm', ''.join([Startdate[5:7], Startdate[0:4]]) , ''.join([Enddate[5:7], Enddate[0:4]])]
Name_NC_Prec = DC.Create_NC_name('Prec', Simulation, Dir_Basin, 5)
if not os.path.exists(Name_NC_Prec):
# Get the data of Reference Evapotranspiration and save as nc
DataCube_Prec = RC.Get3Darray_time_series_monthly(Dir_Basin, Data_Path_P_Monthly, Startdate, Enddate, LU_dataset)
DC.Save_as_NC(Name_NC_Prec, DataCube_Prec, 'Prec', LU_dataset, Startdate, Enddate, 'monthly', 0.01)
del DataCube_Prec
# Evapotranspiration
Name_NC_ET = DC.Create_NC_name('ET', Simulation, Dir_Basin, 5)
if not os.path.exists(Name_NC_ET):
# Get the data of Reference Evapotranspiration and save as nc
DataCube_ET = RC.Get3Darray_time_series_monthly(Dir_Basin, Data_Path_ET, Startdate, Enddate, LU_dataset)
DC.Save_as_NC(Name_NC_ET, DataCube_ET, 'ET', LU_dataset, Startdate, Enddate, 'monthly', 0.01)
del DataCube_ET
# Reference Evapotranspiration data
Name_NC_ETref = DC.Create_NC_name('ETref', Simulation, Dir_Basin, 5, info)
if not os.path.exists(Name_NC_ETref):
# Get the data of Reference Evapotranspiration and save as nc
DataCube_ETref = RC.Get3Darray_time_series_monthly(Dir_Basin, Data_Path_ETref, Startdate, Enddate, LU_dataset)
DC.Save_as_NC(Name_NC_ETref, DataCube_ETref, 'ETref', LU_dataset, Startdate, Enddate, 'monthly', 0.01)
del DataCube_ETref
# Rivers
Name_NC_Rivers = DC.Create_NC_name('Rivers', Simulation, Dir_Basin, 5, info)
if not os.path.exists(Name_NC_Rivers):
# Get the data of Reference Evapotranspiration and save as nc
Rivers_CR = RC.Open_nc_array(Name_NC_Rivers_CR)
DataCube_Rivers = RC.resize_array_example(Rivers_CR, LU_data)
DC.Save_as_NC(Name_NC_Rivers, DataCube_Rivers, 'Rivers', LU_dataset)
del DataCube_Rivers, Rivers_CR
# Discharge
# Define info for the nc files
info = ['monthly','m3', ''.join([Startdate[5:7], Startdate[0:4]]) , ''.join([Enddate[5:7], Enddate[0:4]])]
Name_NC_Routed_Discharge = DC.Create_NC_name('Routed_Discharge', Simulation, Dir_Basin, 5, info)
if not os.path.exists(Name_NC_Routed_Discharge):
# Get the data of Reference Evapotranspiration and save as nc
Routed_Discharge_CR = RC.Open_nc_array(Name_NC_Discharge)
DataCube_Routed_Discharge = RC.resize_array_example(Routed_Discharge_CR, LU_data)
DC.Save_as_NC(Name_NC_Routed_Discharge, DataCube_Routed_Discharge, 'Routed_Discharge', LU_dataset, Startdate, Enddate, 'monthly')
del DataCube_Routed_Discharge, Routed_Discharge_CR
# Get raster information
geo_out, proj, size_X, size_Y = RC.Open_array_info(Example_dataset)
Rivers = RC.Open_nc_array(Name_NC_Rivers_CR)
# Create ID Matrix
y,x = np.indices((size_Y, size_X))
ID_Matrix = np.int32(np.ravel_multi_index(np.vstack((y.ravel(),x.ravel())),(size_Y,size_X),mode='clip').reshape(x.shape)) + 1
# Get tiff array time dimension:
time_dimension = int(np.shape(Discharge_dict_CR3[0])[0])
# create an empty array
Result = np.zeros([time_dimension, size_Y, size_X])
for river_part in range(0,len(River_dict_CR2)):
for river_pixel in range(1,len(River_dict_CR2[river_part])):
river_pixel_ID = River_dict_CR2[river_part][river_pixel]
if len(np.argwhere(ID_Matrix == river_pixel_ID))>0:
row, col = np.argwhere(ID_Matrix == river_pixel_ID)[0][:]
Result[:,row,col] = Discharge_dict_CR3[river_part][:,river_pixel]
print(river_part)
Outflow = Discharge_dict_CR3[0][:,1]
for i in range(0,time_dimension):
output_name = r'C:/testmap/rtest_%s.tif' %i
Result_one = Result[i, :, :]
DC.Save_as_tiff(output_name, Result_one, geo_out, "WGS84")
import os
# Get environmental variable for the Home folder
WA_env_paths = os.environ["WA_HOME"].split(';')
Dir_Home = WA_env_paths[0]
# Create the Basin folder
Dir_Basin = os.path.join(Dir_Home, Basin)
info = ['monthly','m3-month-1', ''.join([Startdate[5:7], Startdate[0:4]]) , ''.join([Enddate[5:7], Enddate[0:4]])]
Name_Result = DC.Create_NC_name('DischargeEnd', Simulation, Dir_Basin, 5, info)
Result[np.logical_and(Result == 0.0, Rivers == 0.0)] = np.nan
DC.Save_as_NC(Name_Result, Result, 'DischargeEnd', Example_dataset, Startdate, Enddate, 'monthly')
'''
return()