def Calculate(WA_HOME_folder, Basin, P_Product, ET_Product, LAI_Product,
NDM_Product, NDVI_Product, ETref_Product, dict_crops,
dict_non_crops, Startdate, Enddate, Simulation):
"""
This functions is the main framework for calculating sheet 3.
Parameters
----------
Basin : str
Name of the basin
P_Product : str
Name of the rainfall product that will be used
ET_Product : str
Name of the evapotranspiration product that will be used
LAI_Product : str
Name of the LAI product that will be used
NDM_Product : str
Name of the NDM product that will be used
Startdate : str
Contains the start date of the model 'yyyy-mm-dd'
Enddate : str
Contains the end date of the model 'yyyy-mm-dd'
Simulation : int
Defines the simulation
"""
######################### Import WA modules ###################################
from wa.General import raster_conversions as RC
from wa.General import data_conversions as DC
import wa.Functions.Three as Three
import wa.Functions.Two as Two
import wa.Functions.Start as Start
import wa.Functions.Four as Four
import wa.Generator.Sheet3 as Generate
import wa.Functions.Start.Get_Dictionaries as GD
######################### Set General Parameters ##############################
# Check if there is a full year selected between Startdate and Enddate, otherwise Sheet 3 cannot be produced
try:
years_end = pd.date_range(Startdate, Enddate, freq="A").year
years_start = pd.date_range(Startdate, Enddate, freq="AS").year
if (len(years_start) == 0 or len(years_end) == 0):
print "Calculation period is less than a year, which is not possible for sheet 3"
quit
years = np.unique(np.append(years_end, years_start))
except:
print "Calculation period is less than a year, which is not possible for sheet 3"
quit
# 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)
############################# Download Data ###################################
# Check the years that needs to be calculated
years = range(int(Startdate.split('-')[0]), int(Enddate.split('-')[0]) + 1)
# 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())
for year in years:
# Create Start and End date for time chunk
Startdate_part = '%d-01-01' % int(year)
Enddate_part = '%s-12-31' % year
# 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)
#Set Startdate for moving average
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
# Open variables in netcdf
fh = netCDF4.Dataset(nc_outname)
Variables_NC = [var for var in fh.variables]
fh.close()
# 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_Evapotransporation" 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 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 not "NDVI" in Variables_NC:
Data_Path_NDVI = Start.Download_Data.NDVI(
Dir_Basin, [Boundaries['Latmin'], Boundaries['Latmax']],
[Boundaries['Lonmin'], Boundaries['Lonmax']], Startdate_part,
Enddate_part)
if not "Normalized_Dry_Matter" in Variables_NC:
Data_Path_NPP = Start.Download_Data.NPP(
Dir_Basin, [Boundaries['Latmin'], Boundaries['Latmax']],
[Boundaries['Lonmin'], Boundaries['Lonmax']], Startdate_part,
Enddate_part, NDM_Product)
Data_Path_GPP = Start.Download_Data.GPP(
Dir_Basin, [Boundaries['Latmin'], Boundaries['Latmax']],
[Boundaries['Lonmin'], Boundaries['Lonmax']], Startdate_part,
Enddate_part, NDM_Product)
########################### Create input data #################################
if not "Normalized_Dry_Matter" in Variables_NC:
# Create NDM based on MOD17
if NDM_Product == 'MOD17':
# Create monthly GPP
Start.Eightdaily_to_monthly_state.Nearest_Interpolate(
Data_Path_GPP, Startdate_part, Enddate_part)
Data_Path_NDM = Two.Calc_NDM.NPP_GPP_Based(
Dir_Basin, Data_Path_GPP, Data_Path_NPP, Startdate_part,
Enddate_part)
if not "NDVI" in Variables_NC:
# Create monthly NDVI based on MOD13
if NDVI_Product == 'MOD13':
Start.Sixteendaily_to_monthly_state.Nearest_Interpolate(
Data_Path_NDVI, Startdate_part, Enddate_part)
###################### Save Data as netCDF files ##############################
#______________________________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
#___________________________Normalized Dry Matter__________________________
# 3.) Normalized Dry Matter
if not "Normalized_Dry_Matter" in Variables_NC:
# Get the data of Evaporation and save as nc
DataCube_NDM = RC.Get3Darray_time_series_monthly(
Data_Path_NDM,
Startdate_part,
Enddate_part,
Example_data=Example_dataset)
DC.Add_NC_Array_Variable(nc_outname, DataCube_NDM,
"Normalized_Dry_Matter", "kg_ha", 0.01)
del DataCube_NDM
#_______________________Reference Evaporation______________________________
# 4.) Reference Evapotranspiration data
if 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
#____________________________________NDVI__________________________________
# 4.) Reference Evapotranspiration data
if not "NDVI" in Variables_NC:
# Get the data of Precipitation and save as nc
DataCube_NDVI = RC.Get3Darray_time_series_monthly(
Data_Path_NDVI,
Startdate_part,
Enddate_part,
Example_data=Example_dataset)
DC.Add_NC_Array_Variable(nc_outname, DataCube_NDVI, "NDVI",
"Fraction", 0.0001)
del DataCube_NDVI
############################# Calculate Sheet 3 ###########################
#____________ Evapotranspiration data split in ETblue and ETgreen ____________
if not ("Blue_Evapotranspiration" in Variables_NC
or "Green_Evapotranspiration" in Variables_NC):
# Calculate Blue and Green ET
DataCube_ETblue, DataCube_ETgreen = Four.SplitET.Blue_Green(
Dir_Basin, nc_outname, ETref_Product, P_Product, Startdate,
Enddate)
DC.Add_NC_Array_Variable(nc_outname, DataCube_ETblue,
"Blue_Evapotranspiration", "mm/month",
0.01)
DC.Add_NC_Array_Variable(nc_outname, DataCube_ETgreen,
"Green_Evapotranspiration", "mm/month",
0.01)
del DataCube_ETblue, DataCube_ETgreen
#____________________________ Create the empty dictionaries ____________________________
# Create the dictionaries that are required for sheet 3
wp_y_irrigated_dictionary, wp_y_rainfed_dictionary, wp_y_non_crop_dictionary = GD.get_sheet3_empties(
)
#____________________________________ Fill in the dictionaries ________________________
# Fill in the crops dictionaries
wp_y_irrigated_dictionary, wp_y_rainfed_dictionary = Three.Fill_Dicts.Crop_Dictionaries(
wp_y_irrigated_dictionary, wp_y_rainfed_dictionary, dict_crops,
nc_outname, Dir_Basin)
# Fill in the non crops dictionaries
wp_y_non_crop_dictionary = Three.Fill_Dicts.Non_Crop_Dictionaries(
wp_y_non_crop_dictionary, dict_non_crops)
############################ Create CSV 3 #################################
csv_fh_a, csv_fh_b = Generate.CSV.Create(wp_y_irrigated_dictionary,
wp_y_rainfed_dictionary,
wp_y_non_crop_dictionary, Basin,
Simulation, year, Dir_Basin)
############################ Create Sheet 3 ###############################
Generate.PDF.Create(Dir_Basin, Basin, Simulation, csv_fh_a, csv_fh_b)
return ()
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()
def Calculate(Basin, P_Product, ET_Product, LAI_Product, NDM_Product,
Startdate, Enddate, Simulation):
"""
This functions is the main framework for calculating sheet 2.
Parameters
----------
Basin : str
Name of the basin
P_Product : str
Name of the rainfall product that will be used
ET_Product : str
Name of the evapotranspiration product that will be used
LAI_Product : str
Name of the LAI product that will be used
NDM_Product : str
Name of the NDM product that will be used
Startdate : str
Contains the start date of the model 'yyyy-mm-dd'
Enddate : str
Contains the end date of the model 'yyyy-mm-dd'
Simulation : int
Defines the simulation
"""
######################### Import WA modules ###################################
from wa.General import raster_conversions as RC
from wa.General import data_conversions as DC
import wa.Functions.Two as Two
import wa.Functions.Start as Start
import wa.Generator.Sheet2 as Generate
######################### 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, Example_dataset = Start.Boundaries.Determine_LU_Based(Basin)
############################# Download Data ###################################
# Set the NPP and GPP data for the whole year
StartYear = Startdate[:4]
EndYear = Enddate[:4]
StartdateNDM = '%d-01-01' % int(StartYear)
EnddateNDM = '%d-12-31' % int(EndYear)
# Download data
Data_Path_P = Start.Download_Data.Precipitation(
Dir_Basin, [Boundaries['Latmin'], Boundaries['Latmax']],
[Boundaries['Lonmin'], Boundaries['Lonmax']], Startdate, Enddate,
P_Product)
Data_Path_ET = Start.Download_Data.Evapotranspiration(
Dir_Basin, [Boundaries['Latmin'], Boundaries['Latmax']],
[Boundaries['Lonmin'], Boundaries['Lonmax']], Startdate, Enddate,
ET_Product)
Data_Path_LAI = Start.Download_Data.LAI(
Dir_Basin, [Boundaries['Latmin'], Boundaries['Latmax']],
[Boundaries['Lonmin'], Boundaries['Lonmax']], Startdate, Enddate,
LAI_Product)
if NDM_Product == 'MOD17':
Data_Path_NPP = Start.Download_Data.NPP(
Dir_Basin, [Boundaries['Latmin'], Boundaries['Latmax']],
[Boundaries['Lonmin'], Boundaries['Lonmax']], StartdateNDM,
EnddateNDM, NDM_Product)
Data_Path_GPP = Start.Download_Data.GPP(
Dir_Basin, [Boundaries['Latmin'], Boundaries['Latmax']],
[Boundaries['Lonmin'], Boundaries['Lonmax']], StartdateNDM,
EnddateNDM, NDM_Product)
Data_Path_P_Daily = os.path.join(Data_Path_P, 'Daily')
Data_Path_P_Monthly = os.path.join(Data_Path_P, 'Monthly')
########################### Create input data #################################
# Create Rainy Days based on daily CHIRPS
Data_Path_RD = Two.Rainy_Days.Calc_Rainy_Days(Dir_Basin, Data_Path_P_Daily,
Startdate, Enddate)
# Create monthly LAI and GPP
Dir_path_LAI = os.path.join(Dir_Basin, Data_Path_LAI)
Start.Eightdaily_to_monthly_state.Nearest_Interpolate(
Dir_path_LAI, Startdate, Enddate)
Dir_path_GPP = os.path.join(Dir_Basin, Data_Path_GPP)
Start.Eightdaily_to_monthly_state.Nearest_Interpolate(
Dir_path_GPP, StartdateNDM, EnddateNDM)
# Create NDM based on MOD17
if NDM_Product == 'MOD17':
Data_Path_NDM = Two.Calc_NDM.NPP_GPP_Based(Dir_Basin, Data_Path_GPP,
Data_Path_NPP, Startdate,
Enddate)
###################### Save Data as netCDF files ##############################
#___________________________________Land Use_______________________________
# Get the data of LU and save as nc, This dataset is also used as reference for others
LUdest = gdal.Open(Example_dataset)
DataCube_LU = LUdest.GetRasterBand(1).ReadAsArray()
Name_NC_LU = DC.Create_NC_name('LU', Simulation, Dir_Basin, 2)
if not os.path.exists(Name_NC_LU):
DC.Save_as_NC(Name_NC_LU, DataCube_LU, 'LU', Example_dataset)
LUdest = None
del DataCube_LU
#______________________________Precipitation_______________________________
# Define info for the nc files
info = [
'monthly', 'mm', ''.join([Startdate[5:7], Startdate[0:4]]),
''.join([Enddate[5:7], Enddate[0:4]])
]
# Precipitation data
Name_NC_P = DC.Create_NC_name('Prec', Simulation, Dir_Basin, 2, info)
if not os.path.exists(Name_NC_P):
# Get the data of Precipitation and save as nc
DataCube_Prec = RC.Get3Darray_time_series_monthly(
Dir_Basin,
Data_Path_P_Monthly,
Startdate,
Enddate,
Example_data=Example_dataset)
DC.Save_as_NC(Name_NC_P, DataCube_Prec, 'Prec', Example_dataset,
Startdate, Enddate, 'monthly', 0.01)
del DataCube_Prec
#_______________________________Evaporation________________________________
# Evapotranspiration data
Name_NC_ET = DC.Create_NC_name('ET', Simulation, Dir_Basin, 2, info)
if not os.path.exists(Name_NC_ET):
# Get the data of Evaporation and save as nc
DataCube_ET = RC.Get3Darray_time_series_monthly(
Dir_Basin,
Data_Path_ET,
Startdate,
Enddate,
Example_data=Example_dataset)
DC.Save_as_NC(Name_NC_ET, DataCube_ET, 'ET', Example_dataset,
Startdate, Enddate, 'monthly', 0.01)
del DataCube_ET
#___________________________Normalized Dry Matter__________________________
# Define info for the nc files
info = [
'monthly', 'kg_ha-1', ''.join([Startdate[5:7], Startdate[0:4]]),
''.join([Enddate[5:7], Enddate[0:4]])
]
Name_NC_NDM = DC.Create_NC_name('NDM', Simulation, Dir_Basin, 2, info)
if not os.path.exists(Name_NC_NDM):
# Get the data of Evaporation and save as nc
DataCube_NDM = RC.Get3Darray_time_series_monthly(
Dir_Basin,
Data_Path_NDM,
Startdate,
Enddate,
Example_data=Example_dataset)
DC.Save_as_NC(Name_NC_NDM, DataCube_NDM, 'NDM', Example_dataset,
Startdate, Enddate, 'monthly', 100)
del DataCube_NDM
#_______________________________Rainy Days_________________________________
# Define info for the nc files
info = [
'monthly', 'days', ''.join([Startdate[5:7], Startdate[0:4]]),
''.join([Enddate[5:7], Enddate[0:4]])
]
Name_NC_RD = DC.Create_NC_name('RD', Simulation, Dir_Basin, 2, info)
if not os.path.exists(Name_NC_RD):
# Get the data of Evaporation and save as nc
DataCube_RD = RC.Get3Darray_time_series_monthly(
Dir_Basin,
Data_Path_RD,
Startdate,
Enddate,
Example_data=Example_dataset)
DC.Save_as_NC(Name_NC_RD, DataCube_RD, 'RD', Example_dataset,
Startdate, Enddate, 'monthly', 100)
del DataCube_RD
#_______________________________Leaf Area Index____________________________
# Define info for the nc files
info = [
'monthly', 'm2-m-2', ''.join([Startdate[5:7], Startdate[0:4]]),
''.join([Enddate[5:7], Enddate[0:4]])
]
Name_NC_LAI = DC.Create_NC_name('LAI', Simulation, Dir_Basin, 2, info)
if not os.path.exists(Name_NC_LAI):
# Get the data of Evaporation and save as nc
DataCube_LAI = RC.Get3Darray_time_series_monthly(
Dir_Basin,
Data_Path_LAI,
Startdate,
Enddate,
Example_data=Example_dataset)
DC.Save_as_NC(Name_NC_LAI, DataCube_LAI, 'LAI', Example_dataset,
Startdate, Enddate, 'monthly', 1)
del DataCube_LAI
####################### Calculations Sheet 2 ##############################
DataCube_I, DataCube_T, DataCube_E = Two.SplitET.ITE(
Dir_Basin, Name_NC_ET, Name_NC_LAI, Name_NC_P, Name_NC_RD, Name_NC_NDM,
Name_NC_LU, Startdate, Enddate, Simulation)
############################ Create CSV 2 #################################
Dir_Basin_CSV = Generate.CSV.Create(Dir_Basin, Simulation, Basin,
Startdate, Enddate, Name_NC_LU,
DataCube_I, DataCube_T, DataCube_E,
Example_dataset)
############################ Create Sheet 2 ###############################
Generate.PDF.Create(Dir_Basin, Basin, Simulation, Dir_Basin_CSV)
return ()
def Calculate(WA_HOME_folder, Basin, P_Product, ET_Product, LAI_Product, ETref_Product, Runoff_Product, Startdate, Enddate, Simulation):
"""
This functions is the main framework for calculating sheet 4.
Parameters
----------
Basin : str
Name of the basin
P_Product : str
Name of the rainfall product that will be used
ET_Product : str
Name of the evapotranspiration product that will be used
LAI_Product : str
Name of the LAI product that will be used
Runoff_Product : str
Name of the Runoff product that will be used
Moving_Averiging_Length, int
Defines the length of the moving average
Startdate : str
Contains the start date of the model 'yyyy-mm-dd'
Enddate : str
Contains the end date of the model 'yyyy-mm-dd'
Simulation : int
Defines the simulation
"""
######################### Import WA modules ###################################
from wa.General import raster_conversions as RC
from wa.General import data_conversions as DC
import wa.Functions.Four as Four
import wa.Functions.Start as Start
import wa.Generator.Sheet4 as Generate
import wa.Functions.Start.Get_Dictionaries as GD
######################### 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)
# 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
############################# 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 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 not "Grey_Water_Footprint" in Variables_NC:
Data_Path_GWF = Start.Download_Data.GWF(Dir_Basin, [Boundaries['Latmin'],Boundaries['Latmax']],[Boundaries['Lonmin'],Boundaries['Lonmax']])
if not "Theta_Saturated_Topsoil" in Variables_NC:
Data_Path_ThetaSat_topsoil = Start.Download_Data.Soil_Properties(Dir_Basin, [Boundaries['Latmin'],Boundaries['Latmax']],[Boundaries['Lonmin'],Boundaries['Lonmax']], Para = 'ThetaSat_TopSoil')
###################### Save Data as netCDF files ##############################
#______________________________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
#_______________________Reference Evaporation______________________________
# 2.) Reference Evapotranspiration data
if 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
#_______________________________Evaporation________________________________
# 3.) 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
#_____________________________________GWF__________________________________
# 4.) Grey Water Footprint data
if not "Grey_Water_Footprint" in Variables_NC:
# Get the data of grey water footprint and save as nc
GWF_Filepath = os.path.join(Dir_Basin, Data_Path_GWF, "Gray_Water_Footprint_Fraction.tif")
dest_GWF = RC.reproject_dataset_example(GWF_Filepath, Example_dataset, method=1)
DataCube_GWF = dest_GWF.GetRasterBand(1).ReadAsArray()
DC.Add_NC_Array_Static(nc_outname, DataCube_GWF, "Grey_Water_Footprint", "fraction", 0.0001)
del DataCube_GWF
####################### Calculations Sheet 4 ##############################
############## Cut dates into pieces if it is needed ######################
years = range(int(Startdate.split('-')[0]),int(Enddate.split('-')[0]) + 1)
for year in years:
if len(years) > 1.0:
if year is years[0]:
Startdate_part = Startdate
Enddate_part = '%s-12-31' %year
if year is years[-1]:
Startdate_part = '%s-01-01' %year
Enddate_part = Enddate
else:
Startdate_part = Startdate
Enddate_part = Enddate
#____________ Evapotranspiration data split in ETblue and ETgreen ____________
if not ("Blue_Evapotranspiration" in Variables_NC or "Green_Evapotranspiration" in Variables_NC):
# Calculate Blue and Green ET
DataCube_ETblue, DataCube_ETgreen = Four.SplitET.Blue_Green(Dir_Basin, nc_outname, ETref_Product, P_Product, Startdate, Enddate)
DC.Add_NC_Array_Variable(nc_outname, DataCube_ETblue, "Blue_Evapotranspiration", "mm/month", 0.01)
DC.Add_NC_Array_Variable(nc_outname, DataCube_ETgreen, "Green_Evapotranspiration", "mm/month", 0.01)
del DataCube_ETblue, DataCube_ETgreen
#____________ Calculate non-consumend and Total supply maps by using fractions and consumed maps (blue ET) ____________
if not ("Total_Supply" in Variables_NC or "Non_Consumed_Water" in Variables_NC):
# Do the calculations
DataCube_Total_Supply, DataCube_Non_Consumed = Four.Total_Supply.Fraction_Based(nc_outname, Startdate_part, Enddate_part)
# Save the Total Supply and non consumed data as NetCDF files
DC.Add_NC_Array_Variable(nc_outname, DataCube_Total_Supply, "Total_Supply", "mm/month", 0.01)
DC.Add_NC_Array_Variable(nc_outname, DataCube_Non_Consumed, "Non_Consumed_Water", "mm/month", 0.01)
del DataCube_Total_Supply, DataCube_Non_Consumed
#____________ Apply fractions over total supply to calculate gw and sw supply ____________
if not ("Total_Supply_Surface_Water" in Variables_NC or "Total_Supply_Ground_Water" in Variables_NC):
# Do the calculations
DataCube_Total_Supply_SW, DataCube_Total_Supply_GW = Four.SplitGW_SW_Supply.Fraction_Based(nc_outname, Startdate_part, Enddate_part)
# Save the Total Supply surface water and Total Supply ground water data as NetCDF files
DC.Add_NC_Array_Variable(nc_outname, DataCube_Total_Supply_SW, "Total_Supply_Surface_Water", "mm/month", 0.01)
DC.Add_NC_Array_Variable(nc_outname, DataCube_Total_Supply_GW, "Total_Supply_Ground_Water", "mm/month", 0.01)
del DataCube_Total_Supply_SW, DataCube_Total_Supply_GW
#____________ Apply gray water footprint fractions to calculated non recoverable flow based on the non consumed flow ____________
if not ("Non_Recovable_Flow" in Variables_NC or "Recovable_Flow" in Variables_NC):
# Calculate the non recovable flow and recovable flow by using Grey Water Footprint values
DataCube_NonRecovableFlow, Datacube_RecovableFlow = Four.SplitNonConsumed_NonRecov.GWF_Based(nc_outname, Startdate_part, Enddate_part)
# Get the data of Evaporation and save as nc
DC.Add_NC_Array_Variable(nc_outname, DataCube_NonRecovableFlow, "Non_Recovable_Flow", "mm/month", 0.01)
DC.Add_NC_Array_Variable(nc_outname, Datacube_RecovableFlow, "Recovable_Flow", "mm/month", 0.01)
del DataCube_NonRecovableFlow, Datacube_RecovableFlow
#____________Apply fractions to calculate the non recovarable SW/GW and recovarable SW/GW ____________
# 1. Non recovarable flow
if not ("Non_Recovable_Flow_Ground_Water" in Variables_NC or "Non_Recovable_Flow_Surface_Water" in Variables_NC):
# Calculate the non recovable return flow to ground and surface water
DataCube_NonRecovableFlow_Return_GW, Datacube_NonRecovableFlow_Return_SW = Four.SplitGW_SW_Return.Fraction_Based(nc_outname, "Non_Recovable_Flow", Startdate_part, Enddate_part)
# Get the data of Evaporation and save as nc
DC.Add_NC_Array_Variable(nc_outname, DataCube_NonRecovableFlow_Return_GW, "Non_Recovable_Flow_Ground_Water", "mm/month", 0.01)
DC.Add_NC_Array_Variable(nc_outname, Datacube_NonRecovableFlow_Return_SW, "Non_Recovable_Flow_Surface_Water", "mm/month", 0.01)
del DataCube_NonRecovableFlow_Return_GW, Datacube_NonRecovableFlow_Return_SW
# 2. Recovarable flow
if not ("Recovable_Flow_Ground_Water" in Variables_NC or "Recovable_Flow_Surface_Water" in Variables_NC):
# Calculate the non recovable return flow to ground and surface water
DataCube_RecovableFlow_Return_GW, Datacube_RecovableFlow_Return_SW = Four.SplitGW_SW_Return.Fraction_Based(nc_outname, "Recovable_Flow", Startdate_part, Enddate_part)
# Get the data of Evaporation and save as nc
DC.Add_NC_Array_Variable(nc_outname, DataCube_RecovableFlow_Return_GW, "Recovable_Flow_Ground_Water", "mm/month", 0.01)
DC.Add_NC_Array_Variable(nc_outname, Datacube_RecovableFlow_Return_SW, "Recovable_Flow_Surface_Water", "mm/month", 0.01)
del DataCube_RecovableFlow_Return_GW, Datacube_RecovableFlow_Return_SW
############################ Create CSV 4 #################################
Dir_Basin_CSV, Unit_front = Generate.CSV.Create(Dir_Basin, Simulation, Basin, Startdate_part, Enddate_part, nc_outname)
############################ Create Sheet 4 ###############################
Generate.PDF.Create(Dir_Basin, Basin, Simulation, Dir_Basin_CSV, Unit_front)
return()
def Complete_3D_Array(nc_outname, Var, Startdate, Enddate,
Additional_Months_front, Additional_Months_tail,
Data_Path):
from netCDF4 import Dataset
import wa.General.raster_conversions as RC
# Define startdate and enddate with moving average
Startdate_Moving_Average = pd.Timestamp(Startdate) - pd.DateOffset(
months=Additional_Months_front)
Enddate_Moving_Average = pd.Timestamp(Enddate) + pd.DateOffset(
months=Additional_Months_tail)
Startdate_Moving_Average_String = '%d-%02d-%02d' % (
Startdate_Moving_Average.year, Startdate_Moving_Average.month,
Startdate_Moving_Average.day)
Enddate_Moving_Average_String = '%d-%02d-%02d' % (
Enddate_Moving_Average.year, Enddate_Moving_Average.month,
Enddate_Moving_Average.day)
# Extract moving average period before
Year_front = int(Startdate_Moving_Average.year)
filename_front = os.path.join(os.path.dirname(nc_outname),
"%d.nc" % Year_front)
Enddate_Front = pd.Timestamp(Startdate) - pd.DateOffset(days=1)
# Extract inside start and enddate
Array_main = RC.Open_nc_array(nc_outname, Var, Startdate, Enddate)
if Additional_Months_front > 0:
# Extract moving average period before
if os.path.exists(filename_front):
# Open variables in netcdf
fh = Dataset(filename_front)
Variables_NC = [var for var in fh.variables]
fh.close()
if Var in Variables_NC:
Array_front = RC.Open_nc_array(
filename_front, Var, Startdate_Moving_Average_String,
Enddate_Front)
else:
Array_front = RC.Get3Darray_time_series_monthly(
Data_Path, Startdate_Moving_Average_String, Enddate_Front,
nc_outname)
else:
Array_front = RC.Get3Darray_time_series_monthly(
Data_Path, Startdate_Moving_Average_String, Enddate_Front,
nc_outname)
# Merge dataset
Array_main = np.vstack([Array_front, Array_main])
if Additional_Months_tail > 0:
# Extract moving average period after
Year_tail = int(Enddate_Moving_Average.year)
filename_tail = os.path.join(os.path.dirname(nc_outname),
"%d.nc" % Year_tail)
Startdate_tail = pd.Timestamp(Enddate) + pd.DateOffset(days=1)
# Extract moving average period after
if os.path.exists(filename_tail):
# Open variables in netcdf
fh = Dataset(filename_tail)
Variables_NC = [var for var in fh.variables]
fh.close()
if Var in Variables_NC:
Array_tail = RC.Open_nc_array(filename_tail, Var,
Startdate_tail,
Enddate_Moving_Average_String)
else:
Array_tail = RC.Get3Darray_time_series_monthly(
Data_Path, Startdate_tail, Enddate_Moving_Average_String,
nc_outname)
else:
Array_tail = RC.Get3Darray_time_series_monthly(
Data_Path, Startdate_tail, Enddate_Moving_Average_String,
nc_outname)
# Merge dataset
Array_main = np.vstack([Array_main, Array_tail])
return (Array_main)
def Calculate(WA_HOME_folder, Basin, P_Product, ET_Product, LAI_Product, NDM_Product, Startdate, Enddate, Simulation):
"""
This functions is the main framework for calculating sheet 2.
Parameters
----------
Basin : str
Name of the basin
P_Product : str
Name of the rainfall product that will be used
ET_Product : str
Name of the evapotranspiration product that will be used
LAI_Product : str
Name of the LAI product that will be used
NDM_Product : str
Name of the NDM product that will be used
Startdate : str
Contains the start date of the model 'yyyy-mm-dd'
Enddate : str
Contains the end date of the model 'yyyy-mm-dd'
Simulation : int
Defines the simulation
"""
######################### Import WA modules ###################################
# import general python modules
import os
from netCDF4 import Dataset
from wa.General import raster_conversions as RC
from wa.General import data_conversions as DC
import wa.Functions.Two as Two
import wa.Functions.Start as Start
import wa.Generator.Sheet2 as Generate
######################### 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
# 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)
############## 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 Start and End date for time chunk
Startdate_part = '%d-01-01' %int(year)
Enddate_part = '%s-12-31' %int(year)
# Create Directory
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)
# 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)
############################# Download Data ###################################
# Open variables in netcdf
fh = Dataset(nc_outname)
Variables_NC = [var for var in fh.variables]
fh.close()
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 "Rainy_Days" in Variables_NC:
Data_Path_P_Daily = Start.Download_Data.Precipitation_Daily(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 not "LAI" in Variables_NC:
Data_Path_LAI = Start.Download_Data.LAI(Dir_Basin, [Boundaries['Latmin'],Boundaries['Latmax']],[Boundaries['Lonmin'],Boundaries['Lonmax']], Startdate_part, Enddate_part, LAI_Product)
if not "Normalized_Dry_Matter" in Variables_NC:
Data_Path_NPP = Start.Download_Data.NPP(Dir_Basin, [Boundaries['Latmin'],Boundaries['Latmax']],[Boundaries['Lonmin'],Boundaries['Lonmax']], Startdate_part, Enddate_part, NDM_Product)
Data_Path_GPP = Start.Download_Data.GPP(Dir_Basin, [Boundaries['Latmin'],Boundaries['Latmax']],[Boundaries['Lonmin'],Boundaries['Lonmax']], Startdate_part, Enddate_part, NDM_Product)
########################### Create input data #################################
if not "Rainy_Days" in Variables_NC:
# Create Rainy Days based on daily CHIRPS
Data_Path_RD = Two.Rainy_Days.Calc_Rainy_Days(Dir_Basin, Data_Path_P_Daily, Startdate_part, Enddate_part)
if not "LAI" in Variables_NC:
# Create monthly LAI
Start.Eightdaily_to_monthly_state.Nearest_Interpolate(Data_Path_LAI, Startdate_part, Enddate_part)
if not "Normalized_Dry_Matter" in Variables_NC:
# Create NDM based on MOD17
if NDM_Product == 'MOD17':
# Create monthly GPP
Start.Eightdaily_to_monthly_state.Nearest_Interpolate(Data_Path_GPP, Startdate_part, Enddate_part)
Data_Path_NDM = Two.Calc_NDM.NPP_GPP_Based(Dir_Basin, Data_Path_GPP, Data_Path_NPP, Startdate_part, Enddate_part)
###################### Save Data as netCDF files ##############################
#______________________________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
#___________________________Normalized Dry Matter__________________________
# 3.) Normalized Dry Matter
if not "Normalized_Dry_Matter" in Variables_NC:
# Get the data of Evaporation and save as nc
DataCube_NDM = RC.Get3Darray_time_series_monthly(Data_Path_NDM, Startdate_part, Enddate_part, Example_data = Example_dataset)
DC.Add_NC_Array_Variable(nc_outname, DataCube_NDM, "Normalized_Dry_Matter", "kg_ha", 0.01)
del DataCube_NDM
#_______________________________Rainy Days_________________________________
if not "Rainy_Days" in Variables_NC:
# Get the data of rainy days and save as nc
DataCube_RD = RC.Get3Darray_time_series_monthly(Data_Path_RD, Startdate_part, Enddate_part, Example_data = Example_dataset)
DC.Add_NC_Array_Variable(nc_outname, DataCube_RD, "Rainy_Days", "amount_of_days", 0.01)
del DataCube_RD
#_______________________________Leaf Area Index____________________________
if not "LAI" in Variables_NC:
# Get the data of leave area index and save as nc
DataCube_LAI = RC.Get3Darray_time_series_monthly(Data_Path_LAI, Startdate_part, Enddate_part, Example_data = Example_dataset)
DC.Add_NC_Array_Variable(nc_outname, DataCube_LAI, "LAI", "m2-m-2", 0.01)
del DataCube_LAI
####################### Calculations Sheet 2 ##########################
if not ("Interception" in Variables_NC or "Transpiration" in Variables_NC or "Evaporation" in Variables_NC):
DataCube_I, DataCube_T, DataCube_E = Two.SplitET.ITE(Dir_Basin, nc_outname, Startdate_part, Enddate_part, Simulation)
DC.Add_NC_Array_Variable(nc_outname, DataCube_I, "Interception", "mm/month", 0.01)
DC.Add_NC_Array_Variable(nc_outname, DataCube_T, "Transpiration", "mm/month", 0.01)
DC.Add_NC_Array_Variable(nc_outname, DataCube_E, "Evaporation", "mm/month", 0.01)
del DataCube_I, DataCube_T, DataCube_E
######################### Create CSV 2 ################################
Dir_Basin_CSV = Generate.CSV.Create(Dir_Basin, Simulation, Basin, Startdate_part, Enddate_part, nc_outname, Example_dataset)
############################ Create Sheet 2 ###############################
Generate.PDF.Create(Dir_Basin, Basin, Simulation, Dir_Basin_CSV)
return()
def main(files_DEM_dir, files_DEM, files_Basin, files_Runoff, files_Extraction,
startdate, enddate, input_nc, resolution, Format_DEM_dir, Format_DEM,
Format_Basin, Format_Runoff, Format_Extraction):
# Define a year to get the epsg and geo
Startdate_timestamp = pd.Timestamp(startdate)
year = Startdate_timestamp.year
############################## Drainage Direction #####################################
# Open Array DEM dir as netCDF
if Format_DEM_dir == "NetCDF":
file_DEM_dir = os.path.join(files_DEM_dir, "%d.nc" % year)
DataCube_DEM_dir = RC.Open_nc_array(file_DEM_dir, "Drainage_Direction")
geo_out_example, epsg_example, size_X_example, size_Y_example, size_Z_example, Time_example = RC.Open_nc_info(
files_DEM_dir)
# Create memory file for reprojection
gland = DC.Save_as_MEM(DataCube_DEM_dir, geo_out_example, epsg_example)
dataset_example = file_name_DEM_dir = gland
# Open Array DEM dir as TIFF
if Format_DEM_dir == "TIFF":
file_name_DEM_dir = os.path.join(files_DEM_dir,
"DIR_HydroShed_-_%s.tif" % resolution)
DataCube_DEM_dir = RC.Open_tiff_array(file_name_DEM_dir)
geo_out_example, epsg_example, size_X_example, size_Y_example = RC.Open_array_info(
file_name_DEM_dir)
dataset_example = file_name_DEM_dir
# Calculate Area per pixel in m2
import wa.Functions.Start.Area_converter as AC
DataCube_Area = AC.Degrees_to_m2(file_name_DEM_dir)
################################## DEM ##########################################
# Open Array DEM as netCDF
if Format_DEM == "NetCDF":
file_DEM = os.path.join(files_DEM, "%d.nc" % year)
DataCube_DEM = RC.Open_nc_array(file_DEM, "Elevation")
# Open Array DEM as TIFF
if Format_DEM == "TIFF":
file_name_DEM = os.path.join(files_DEM,
"DEM_HydroShed_m_%s.tif" % resolution)
DataCube_DEM = RC.Open_tiff_array(file_name_DEM)
################################ Landuse ##########################################
# Open Array Basin as netCDF
if Format_Basin == "NetCDF":
file_Basin = os.path.join(files_Basin, "%d.nc" % year)
DataCube_Basin = RC.Open_nc_array(file_Basin, "Landuse")
geo_out, epsg, size_X, size_Y, size_Z, Time = RC.Open_nc_info(
file_Basin, "Landuse")
dest_basin = DC.Save_as_MEM(DataCube_Basin, geo_out, str(epsg))
destLU = RC.reproject_dataset_example(dest_basin,
dataset_example,
method=1)
DataCube_LU_CR = destLU.GetRasterBand(1).ReadAsArray()
DataCube_Basin = np.zeros([size_Y_example, size_X_example])
DataCube_Basin[DataCube_LU_CR > 0] = 1
# Open Array Basin as TIFF
if Format_Basin == "TIFF":
file_name_Basin = files_Basin
destLU = RC.reproject_dataset_example(file_name_Basin,
dataset_example,
method=1)
DataCube_LU_CR = destLU.GetRasterBand(1).ReadAsArray()
DataCube_Basin = np.zeros([size_Y_example, size_X_example])
DataCube_Basin[DataCube_LU_CR > 0] = 1
################################ Surface Runoff ##########################################
# Open Array runoff as netCDF
if Format_Runoff == "NetCDF":
DataCube_Runoff = RC.Open_ncs_array(files_Runoff, "Surface_Runoff",
startdate, enddate)
size_Z_example = DataCube_Runoff.shape[0]
file_Runoff = os.path.join(files_Runoff, "%d.nc" % year)
geo_out, epsg, size_X, size_Y, size_Z, Time = RC.Open_nc_info(
file_Runoff, "Surface_Runoff")
DataCube_Runoff_CR = np.ones(
[size_Z_example, size_Y_example, size_X_example]) * np.nan
for i in range(0, size_Z):
DataCube_Runoff_one = DataCube_Runoff[i, :, :]
dest_Runoff_one = DC.Save_as_MEM(DataCube_Runoff_one, geo_out,
str(epsg))
dest_Runoff = RC.reproject_dataset_example(dest_Runoff_one,
dataset_example,
method=4)
DataCube_Runoff_CR[i, :, :] = dest_Runoff.GetRasterBand(
1).ReadAsArray()
DataCube_Runoff_CR[:, DataCube_LU_CR == 0] = -9999
DataCube_Runoff_CR[DataCube_Runoff_CR < 0] = -9999
# Open Array runoff as TIFF
if Format_Runoff == "TIFF":
Data_Path = ''
DataCube_Runoff = RC.Get3Darray_time_series_monthly(
files_Runoff,
Data_Path,
startdate,
enddate,
Example_data=dataset_example)
################################ Surface Withdrawal ##########################################
# Open Array Extraction as netCDF
if Format_Extraction == "NetCDF":
DataCube_Extraction = RC.Open_ncs_array(files_Extraction,
"Surface_Withdrawal",
startdate, enddate)
size_Z_example = DataCube_Extraction.shape[0]
file_Extraction = os.path.join(files_Extraction, "%d.nc" % year)
geo_out, epsg, size_X, size_Y, size_Z, Time = RC.Open_nc_info(
file_Extraction, "Surface_Withdrawal")
DataCube_Extraction_CR = np.ones(
[size_Z_example, size_Y_example, size_X_example]) * np.nan
for i in range(0, size_Z):
DataCube_Extraction_one = DataCube_Extraction[i, :, :]
dest_Extraction_one = DC.Save_as_MEM(DataCube_Extraction_one,
geo_out, str(epsg))
dest_Extraction = RC.reproject_dataset_example(dest_Extraction_one,
dataset_example,
method=4)
DataCube_Extraction_CR[i, :, :] = dest_Extraction.GetRasterBand(
1).ReadAsArray()
DataCube_Extraction_CR[:, DataCube_LU_CR == 0] = -9999
DataCube_Extraction_CR[DataCube_Extraction_CR < 0] = -9999
# Open Array Extraction as TIFF
if Format_Extraction == "TIFF":
Data_Path = ''
DataCube_Extraction = RC.Get3Darray_time_series_monthly(
files_Extraction,
Data_Path,
startdate,
enddate,
Example_data=dataset_example)
################################ Create input netcdf ##########################################
# Save data in one NetCDF file
geo_out_example = np.array(geo_out_example)
# Latitude and longitude
lon_ls = np.arange(size_X_example) * geo_out_example[1] + geo_out_example[
0] + 0.5 * geo_out_example[1]
lat_ls = np.arange(size_Y_example) * geo_out_example[5] + geo_out_example[
3] - 0.5 * geo_out_example[5]
lat_n = len(lat_ls)
lon_n = len(lon_ls)
# Create NetCDF file
nc_file = netCDF4.Dataset(input_nc, 'w')
nc_file.set_fill_on()
# Create dimensions
lat_dim = nc_file.createDimension('latitude', lat_n)
lon_dim = nc_file.createDimension('longitude', lon_n)
# Create NetCDF variables
crso = nc_file.createVariable('crs', 'i4')
crso.long_name = 'Lon/Lat Coords in WGS84'
crso.standard_name = 'crs'
crso.grid_mapping_name = 'latitude_longitude'
crso.projection = epsg_example
crso.longitude_of_prime_meridian = 0.0
crso.semi_major_axis = 6378137.0
crso.inverse_flattening = 298.257223563
crso.geo_reference = geo_out_example
lat_var = nc_file.createVariable('latitude', 'f8', ('latitude', ))
lat_var.units = 'degrees_north'
lat_var.standard_name = 'latitude'
lat_var.pixel_size = geo_out_example[5]
lon_var = nc_file.createVariable('longitude', 'f8', ('longitude', ))
lon_var.units = 'degrees_east'
lon_var.standard_name = 'longitude'
lon_var.pixel_size = geo_out_example[1]
Dates = pd.date_range(startdate, enddate, freq='MS')
time_or = np.zeros(len(Dates))
i = 0
for Date in Dates:
time_or[i] = Date.toordinal()
i += 1
nc_file.createDimension('time', None)
timeo = nc_file.createVariable('time', 'f4', ('time', ))
timeo.units = 'Monthly'
timeo.standard_name = 'time'
# Variables
demdir_var = nc_file.createVariable('demdir',
'i', ('latitude', 'longitude'),
fill_value=-9999)
demdir_var.long_name = 'Flow Direction Map'
demdir_var.grid_mapping = 'crs'
dem_var = nc_file.createVariable('dem',
'f8', ('latitude', 'longitude'),
fill_value=-9999)
dem_var.long_name = 'Altitude'
dem_var.units = 'meters'
dem_var.grid_mapping = 'crs'
basin_var = nc_file.createVariable('basin',
'i', ('latitude', 'longitude'),
fill_value=-9999)
basin_var.long_name = 'Altitude'
basin_var.units = 'meters'
basin_var.grid_mapping = 'crs'
area_var = nc_file.createVariable('area',
'f8', ('latitude', 'longitude'),
fill_value=-9999)
area_var.long_name = 'area in squared meters'
area_var.units = 'squared_meters'
area_var.grid_mapping = 'crs'
runoff_var = nc_file.createVariable('Runoff_M',
'f8',
('time', 'latitude', 'longitude'),
fill_value=-9999)
runoff_var.long_name = 'Runoff'
runoff_var.units = 'm3/month'
runoff_var.grid_mapping = 'crs'
extraction_var = nc_file.createVariable('Extraction_M',
'f8',
('time', 'latitude', 'longitude'),
fill_value=-9999)
extraction_var.long_name = 'Surface water Extraction'
extraction_var.units = 'm3/month'
extraction_var.grid_mapping = 'crs'
# Load data
lat_var[:] = lat_ls
lon_var[:] = lon_ls
timeo[:] = time_or
# Static variables
demdir_var[:, :] = DataCube_DEM_dir[:, :]
dem_var[:, :] = DataCube_DEM[:, :]
basin_var[:, :] = DataCube_Basin[:, :]
area_var[:, :] = DataCube_Area[:, :]
for i in range(len(Dates)):
runoff_var[i, :, :] = DataCube_Runoff_CR[i, :, :]
for i in range(len(Dates)):
extraction_var[i, :, :] = DataCube_Extraction_CR[i, :, :]
# Close file
nc_file.close()
return ()
def Calculate(Basin, P_Product, ET_Product, Moving_Averaging_Length, Startdate,
Enddate, Simulation):
"""
This functions is the main framework for calculating sheet 4.
Parameters
----------
Basin : str
Name of the basin
P_Product : str
Name of the rainfall product that will be used
ET_Product : str
Name of the evapotranspiration product that will be used
Moving_Averiging_Length, int
Defines the length of the moving average
Startdate : str
Contains the start date of the model 'yyyy-mm-dd'
Enddate : str
Contains the end date of the model 'yyyy-mm-dd'
Simulation : int
Defines the simulation
"""
######################### Import WA modules ###################################
from wa.General import raster_conversions as RC
from wa.General import data_conversions as DC
import wa.Functions.Four as Four
import wa.Functions.Start as Start
import wa.Generator.Sheet4 as Generate
######################### 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, Example_dataset = Start.Boundaries.Determine_LU_Based(Basin)
#Set Startdate and Enddate for moving average
Additional_Months = (Moving_Averaging_Length - 1) / 2
Startdate_Moving_Average = pd.Timestamp(Startdate) - pd.DateOffset(
months=Additional_Months)
Enddate_Moving_Average = pd.Timestamp(Enddate) + pd.DateOffset(
months=Additional_Months)
Startdate_Moving_Average_String = '%d-%02d-%02d' % (
Startdate_Moving_Average.year, Startdate_Moving_Average.month,
Startdate_Moving_Average.day)
Enddate_Moving_Average_String = '%d-%02d-%02d' % (
Enddate_Moving_Average.year, Enddate_Moving_Average.month,
Enddate_Moving_Average.day)
############################# Download Data ###################################
# Download data
Data_Path_P = Start.Download_Data.Precipitation(
Dir_Basin, [Boundaries['Latmin'], Boundaries['Latmax']],
[Boundaries['Lonmin'], Boundaries['Lonmax']],
Startdate_Moving_Average_String,
Enddate_Moving_Average_String,
P_Product,
Daily='n')
Data_Path_ET = Start.Download_Data.Evapotranspiration(
Dir_Basin, [Boundaries['Latmin'], Boundaries['Latmax']],
[Boundaries['Lonmin'], Boundaries['Lonmax']], Startdate, Enddate,
ET_Product)
Data_Path_ETref = Start.Download_Data.ETreference(
Dir_Basin, [Boundaries['Latmin'], Boundaries['Latmax']],
[Boundaries['Lonmin'], Boundaries['Lonmax']],
Startdate_Moving_Average_String, Enddate_Moving_Average_String)
Data_Path_GWF = Start.Download_Data.GWF(
Dir_Basin, [Boundaries['Latmin'], Boundaries['Latmax']],
[Boundaries['Lonmin'], Boundaries['Lonmax']])
Data_Path_P_Monthly = os.path.join(Data_Path_P, 'Monthly')
###################### Save Data as netCDF files ##############################
#___________________________________Land Use_______________________________
# Get the data of LU and save as nc, This dataset is also used as reference for others
LUdest = gdal.Open(Example_dataset)
DataCube_LU = LUdest.GetRasterBand(1).ReadAsArray()
Name_NC_LU = DC.Create_NC_name('LU', Simulation, Dir_Basin, 4)
if not os.path.exists(Name_NC_LU):
DC.Save_as_NC(Name_NC_LU, DataCube_LU, 'LU', Example_dataset)
LUdest = None
del DataCube_LU
#______________________________Precipitation_______________________________
# Define info for the nc files
info = [
'monthly', 'mm', ''.join([
Startdate_Moving_Average_String[5:7],
Startdate_Moving_Average_String[0:4]
]), ''.join([
Enddate_Moving_Average_String[5:7],
Enddate_Moving_Average_String[0:4]
])
]
# Precipitation data
Name_NC_P = DC.Create_NC_name('Prec', Simulation, Dir_Basin, 4, info)
if not os.path.exists(Name_NC_P):
# Get the data of Precipitation and save as nc
DataCube_Prec = RC.Get3Darray_time_series_monthly(
Dir_Basin,
Data_Path_P_Monthly,
Startdate_Moving_Average_String,
Enddate_Moving_Average_String,
Example_data=Example_dataset)
DC.Save_as_NC(Name_NC_P, DataCube_Prec, 'Prec', Example_dataset,
Startdate_Moving_Average_String,
Enddate_Moving_Average_String, 'monthly', 0.01)
del DataCube_Prec
#_______________________Reference Evaporation______________________________
# Reference Evapotranspiration data
Name_NC_ETref = DC.Create_NC_name('ETref', Simulation, Dir_Basin, 4, info)
if not os.path.exists(Name_NC_ETref):
# Get the data of Evaporation and save as nc
DataCube_ETref = RC.Get3Darray_time_series_monthly(
Dir_Basin,
Data_Path_ETref,
Startdate_Moving_Average_String,
Enddate_Moving_Average_String,
Example_data=Example_dataset)
DC.Save_as_NC(Name_NC_ETref, DataCube_ETref, 'ETref', Example_dataset,
Startdate_Moving_Average_String,
Enddate_Moving_Average_String, 'monthly', 0.01)
del DataCube_ETref
#_______________________________Evaporation________________________________
info = [
'monthly', 'mm', ''.join([Startdate[5:7], Startdate[0:4]]),
''.join([Enddate[5:7], Enddate[0:4]])
]
# Evapotranspiration data
Name_NC_ET = DC.Create_NC_name('ET', Simulation, Dir_Basin, 4, info)
if not os.path.exists(Name_NC_ET):
# Get the data of Evaporation and save as nc
DataCube_ET = RC.Get3Darray_time_series_monthly(
Dir_Basin,
Data_Path_ET,
Startdate,
Enddate,
Example_data=Example_dataset)
DC.Save_as_NC(Name_NC_ET, DataCube_ET, 'ET', Example_dataset,
Startdate, Enddate, 'monthly', 0.01)
del DataCube_ET
#_____________________________________GWF__________________________________
# GWF data
Name_NC_GWF = DC.Create_NC_name('GWF_Fraction', Simulation, Dir_Basin, 4)
if not os.path.exists(Name_NC_GWF):
# Get the data of GWF, reproject and save as nc
GWF_Filepath = os.path.join(Dir_Basin, Data_Path_GWF,
"Gray_Water_Footprint_Fraction.tif")
dest_GWF = RC.reproject_dataset_example(GWF_Filepath,
Example_dataset,
method=1)
DataCube_GWF = dest_GWF.GetRasterBand(1).ReadAsArray()
DC.Save_as_NC(Name_NC_GWF,
DataCube_GWF,
'GWF',
Example_dataset,
Scaling_factor=0.01)
del DataCube_GWF
####################### Calculations Sheet 4 ##############################
#____________ Evapotranspiration data split in ETblue and ETgreen ____________
Name_NC_ETgreen = DC.Create_NC_name('ETgreen', Simulation, Dir_Basin, 4,
info)
Name_NC_ETblue = DC.Create_NC_name('ETblue', Simulation, Dir_Basin, 4,
info)
if not (os.path.exists(Name_NC_ETgreen) or os.path.exists(Name_NC_ETblue)):
# Calculate Blue and Green ET
DataCube_ETblue, DataCube_ETgreen = Four.SplitET.Blue_Green(
Name_NC_ET, Name_NC_P, Name_NC_ETref, Startdate, Enddate,
Additional_Months)
# Save the ETblue and ETgreen data as NetCDF files
DC.Save_as_NC(Name_NC_ETblue, DataCube_ETblue, 'ETblue',
Example_dataset, Startdate, Enddate, 'monthly', 0.01)
DC.Save_as_NC(Name_NC_ETgreen, DataCube_ETgreen, 'ETgreen',
Example_dataset, Startdate, Enddate, 'monthly', 0.01)
del DataCube_ETblue, DataCube_ETgreen
#____________ Calculate non-consumend and Total supply maps by using fractions and consumed maps (blue ET) ____________
Name_NC_Total_Supply = DC.Create_NC_name('TotSup', Simulation, Dir_Basin,
4, info)
Name_NC_Non_Consumed = DC.Create_NC_name('NonCon', Simulation, Dir_Basin,
4, info)
if not (os.path.exists(Name_NC_Total_Supply)
or os.path.exists(Name_NC_Non_Consumed)):
# Do the calculations
DataCube_Total_Supply, DataCube_Non_Consumed = Four.Total_Supply.Fraction_Based(
Name_NC_ETblue, Name_NC_LU, Startdate, Enddate)
# Save the Total Supply and non consumed data as NetCDF files
DC.Save_as_NC(Name_NC_Total_Supply, DataCube_Total_Supply, 'TotSup',
Example_dataset, Startdate, Enddate, 'monthly', 0.01)
DC.Save_as_NC(Name_NC_Non_Consumed, DataCube_Non_Consumed, 'NonCon',
Example_dataset, Startdate, Enddate, 'monthly', 0.01)
del DataCube_Total_Supply, DataCube_Non_Consumed
#____________ Apply fractions over total supply to calculate gw and sw supply ____________
Name_NC_Total_Supply_SW = DC.Create_NC_name('TotSupSW', Simulation,
Dir_Basin, 4, info)
Name_NC_Total_Supply_GW = DC.Create_NC_name('TotSupGW', Simulation,
Dir_Basin, 4, info)
if not (os.path.exists(Name_NC_Total_Supply_SW)
or os.path.exists(Name_NC_Total_Supply_GW)):
# Do the calculations
DataCube_Total_Supply_SW, DataCube_Total_Supply_GW = Four.SplitGW_SW_Supply.Fraction_Based(
Name_NC_Total_Supply, Name_NC_LU, Startdate, Enddate)
# Save the Total Supply surface water and Total Supply ground water data as NetCDF files
DC.Save_as_NC(Name_NC_Total_Supply_SW, DataCube_Total_Supply_SW,
'TotSupSW', Example_dataset, Startdate, Enddate,
'monthly', 0.01)
DC.Save_as_NC(Name_NC_Total_Supply_GW, DataCube_Total_Supply_GW,
'TotSupGW', Example_dataset, Startdate, Enddate,
'monthly', 0.01)
del DataCube_Total_Supply_SW, DataCube_Total_Supply_GW
#____________ Apply gray water footprint fractions to calculated non recoverable flow based on the non consumed flow ____________
Name_NC_NonRecovableFlow = DC.Create_NC_name('NonRecov', Simulation,
Dir_Basin, 4, info)
Name_NC_RecovableFlow = DC.Create_NC_name('Recov', Simulation, Dir_Basin,
4, info)
if not (os.path.exists(Name_NC_NonRecovableFlow)
or os.path.exists(Name_NC_RecovableFlow)):
# Calculate the non recovable flow and recovable flow by using Grey Water Footprint values
DataCube_NonRecovableFlow, Datacube_RecovableFlow = Four.SplitNonConsumed_NonRecov.GWF_Based(
Name_NC_Non_Consumed, Name_NC_GWF, Name_NC_LU, Startdate, Enddate)
# Get the data of Evaporation and save as nc
DC.Save_as_NC(Name_NC_NonRecovableFlow, DataCube_NonRecovableFlow,
'NonRecov', Example_dataset, Startdate, Enddate,
'monthly', 0.01)
DC.Save_as_NC(Name_NC_RecovableFlow, Datacube_RecovableFlow, 'Recov',
Example_dataset, Startdate, Enddate, 'monthly', 0.01)
del DataCube_NonRecovableFlow, Datacube_RecovableFlow
#____________Apply fractions to calculate the non recovarable SW/GW and recovarable SW/GW ____________
# 1. Non recovarable flow
Name_NC_NonRecovableFlow_Return_GW = DC.Create_NC_name(
'NonRecov_Return_GW', Simulation, Dir_Basin, 4, info)
Name_NC_NonRecovableFlow_Return_SW = DC.Create_NC_name(
'NonRecov_Return_SW', Simulation, Dir_Basin, 4, info)
if not (os.path.exists(Name_NC_NonRecovableFlow_Return_GW)
or os.path.exists(Name_NC_NonRecovableFlow_Return_SW)):
# Calculate the non recovable return flow to ground and surface water
DataCube_NonRecovableFlow_Return_GW, Datacube_NonRecovableFlow_Return_SW = Four.SplitGW_SW_Return.Fraction_Based(
Name_NC_NonRecovableFlow, Name_NC_LU, Startdate, Enddate)
# Get the data of Evaporation and save as nc
DC.Save_as_NC(Name_NC_NonRecovableFlow_Return_GW,
DataCube_NonRecovableFlow_Return_GW, 'NonRecovReturnGW',
Example_dataset, Startdate, Enddate, 'monthly', 0.01)
DC.Save_as_NC(Name_NC_NonRecovableFlow_Return_SW,
Datacube_NonRecovableFlow_Return_SW, 'NonRecovReturnSW',
Example_dataset, Startdate, Enddate, 'monthly', 0.01)
del DataCube_NonRecovableFlow_Return_GW, Datacube_NonRecovableFlow_Return_SW
# 2. Recovarable flow
Name_NC_RecovableFlow_Return_GW = DC.Create_NC_name(
'Recov_Return_GW', Simulation, Dir_Basin, 4, info)
Name_NC_RecovableFlow_Return_SW = DC.Create_NC_name(
'Recov_Return_SW', Simulation, Dir_Basin, 4, info)
if not (os.path.exists(Name_NC_RecovableFlow_Return_GW)
or os.path.exists(Name_NC_RecovableFlow_Return_SW)):
# Calculate the non recovable return flow to ground and surface water
DataCube_RecovableFlow_Return_GW, Datacube_RecovableFlow_Return_SW = Four.SplitGW_SW_Return.Fraction_Based(
Name_NC_RecovableFlow, Name_NC_LU, Startdate, Enddate)
# Get the data of Evaporation and save as nc
DC.Save_as_NC(Name_NC_RecovableFlow_Return_GW,
DataCube_RecovableFlow_Return_GW, 'NonRecovReturnGW',
Example_dataset, Startdate, Enddate, 'monthly', 0.01)
DC.Save_as_NC(Name_NC_RecovableFlow_Return_SW,
Datacube_RecovableFlow_Return_SW, 'NonRecovReturnSW',
Example_dataset, Startdate, Enddate, 'monthly', 0.01)
del DataCube_RecovableFlow_Return_GW, Datacube_RecovableFlow_Return_SW
############################ Create CSV 4 #################################
Dir_Basin_CSV, Unit_front = Generate.CSV.Create(
Dir_Basin, Simulation, Basin, Startdate, Enddate, Name_NC_LU,
Name_NC_Total_Supply_GW, Name_NC_Total_Supply_SW, Name_NC_Non_Consumed,
Name_NC_ETblue, Name_NC_RecovableFlow_Return_GW,
Name_NC_RecovableFlow_Return_SW, Name_NC_NonRecovableFlow_Return_GW,
Name_NC_NonRecovableFlow_Return_SW)
############################ Create Sheet 4 ###############################
Generate.PDF.Create(Dir_Basin, Basin, Simulation, Dir_Basin_CSV,
Unit_front)
return ()