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load_data.py
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load_data.py
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from __future__ import division
from collections import OrderedDict
from datetime import datetime
from numpy import *
import pandas as pd
import numpy as np
#################################################################
#
# Date Edited: Oct 1, 2021
# Edited By: Dr. Kendra Garner
#
#################################################################
class LoadData:
def __init__(self, chem_type, chem_file, region_file, release_file, start_date, end_date, sim_days):
self.chem_type = chem_type
self.chem_file = chem_file
self.release_file = release_file
self.region_file = region_file
self.start_date = start_date
self.end_date = end_date
self.sim_days = sim_days
def load_date(self):
# load the start rows and end rows from the climate dataset
original_start_date = datetime.strptime('2005 1 1', "%Y %m %d")
start_day = datetime.strptime(self.start_date, "%Y %m %d")
start_row = (start_day - original_start_date).days + 1
end_day = datetime.strptime(self.end_date, "%Y %m %d")
sim_days = (end_day - start_day).days
end_row = start_row + sim_days + 1
return start_row, end_row
def get_Koc_acid(self, smiles, cas):
# if the chemical is organic acid, this parameter would be used to calculate Kd_i in soil
Koc_acid = None
df = pd.read_excel('./IonizableChem_DB.xlsx', sheet_name='Koc_organicAcid')
# check if smiles in the SMILES column
# if contains, a row of values would return
# if not contain, an empty dataframe would return
if smiles is not None:
df2 = df[df['SMILES'] == smiles]
else:
df2 = df[df['SMILES'] == '--']
if cas is not None:
df3 = df[df['CAS'].str.contains(cas)]
else:
df3 = df[df['CAS'].str.contains('--')]
if df2['SMILES'].empty:
# check if cas column contains the cas
if df3['CAS'].empty:
return Koc_acid
else:
Koc_acid = df3['Koc_i'].values[0]
else:
Koc_acid = df2['Koc_i'].values[0]
return Koc_acid
def get_infil_rate(self, soil_type, slope):
infil_rate = None
slope_col = None
df = pd.read_excel('./IonizableChem_DB.xlsx', sheetname='infiltrationRate', index_col=0)
if slope <= 4:
slope_col = '0-4%'
elif slope <= 8:
slope_col = '5-8%'
elif slope <= 12:
slope_col = '8-12%'
elif slope <= 16:
slope_col = '12-16%'
else:
slope_col = 'over 16%'
infil_rate = df.loc[soil_type, slope_col]
return infil_rate
def load_chemParams(self, chem_type, env):
# load chemical properties
df = pd.read_excel(self.chem_file, sheet_name="Sheet1")
chem_loading = zip(df["Code"], df["Value"])
chem_params = {}
for code, value in chem_loading:
chem_params[code] = value
# get the Koc_acid value
if chem_type == 'IonizableOrganic':
chem_params['Koc_acid'] = self.get_Koc_acid(chem_params['smiles'], chem_params['cas'])
if chem_type == 'NonionizableOrganic':
# soil/water partition coefficient Kd = Koc * foc
# sorbed concentration (mg/kg) / dissolved concentration (mg/L) = L/kg
# unit of Koc is equal to the unit of Kd: L/kg, divide by 1000, 1000 L = 1 m^3
# Kd in m^3-water/kg-soil
chem_params['Kd1'] = (chem_params['Koc_n'] * env['soilOC1']) / 1000
chem_params['Kd2'] = (chem_params['Koc_n'] * env['soilOC2']) / 1000
chem_params['Kd3'] = (chem_params['Koc_n'] * env['soilOC3']) / 1000
chem_params['Kd4'] = (chem_params['Koc_n'] * env['soilOC4']) / 1000
chem_params['Kd1_d'] = (chem_params['Koc_n'] * env['dsoilOC1']) / 1000
chem_params['Kd2_d'] = (chem_params['Koc_n'] * env['dsoilOC1']) / 1000
chem_params['Kd3_d'] = (chem_params['Koc_n'] * env['dsoilOC1']) / 1000
chem_params['Kd4_d'] = (chem_params['Koc_n'] * env['dsoilOC1']) / 1000
# convert Kd to unitless, multiply by soil density
# m3-water/kg-soil * kg-soil/m3-soil = m3-water/m3-soil
chem_params['Kd1_unitless'] = chem_params['Kd1'] * env['dSS1']
chem_params['Kd2_unitless'] = chem_params['Kd2'] * env['dSS2']
chem_params['Kd3_unitless'] = chem_params['Kd3'] * env['dSS3']
chem_params['Kd4_unitless'] = chem_params['Kd4'] * env['dSS4']
chem_params['Kd1_d_unitless'] = chem_params['Kd1_d'] * env['deepsP1']
chem_params['Kd2_d_unitless'] = chem_params['Kd2_d'] * env['deepsP2']
chem_params['Kd3_d_unitless'] = chem_params['Kd3_d'] * env['deepsP3']
chem_params['Kd4_d_unitless'] = chem_params['Kd4_d'] * env['deepsP4']
# sediment/water partition coefficient Kssw (suspended sediment - water) and Kbsw (bottom sediment - water)
chem_params['Kssrw'] = (chem_params['Koc_n'] * env['riverssOC']) / 1000
chem_params['Kssfw'] = (chem_params['Koc_n'] * env['freshssOC']) / 1000
chem_params['Ksssw'] = (chem_params['Koc_n'] * env['seassOC']) / 1000
chem_params['Kbsrw'] = (chem_params['Koc_n'] * env['sedRiverOC']) / 1000
chem_params['Kbsfw'] = (chem_params['Koc_n'] * env['sedFWOC']) / 1000
chem_params['Kbssw'] = (chem_params['Koc_n'] * env['sedSWOC']) / 1000
# convert Kss and Kbs to unitless, multiple suspended sediment and sediment's density
chem_params['Kssrw_unitless'] = chem_params['Kssrw'] * env['riverssP']
chem_params['Kssfw_unitless'] = chem_params['Kssfw'] * env['freshssP']
chem_params['Ksssw_unitless'] = chem_params['Ksssw'] * env['seassP']
chem_params['Kbsrw_unitless'] = chem_params['Kbsrw'] * env['dRiverSedS']
chem_params['Kbsfw_unitless'] = chem_params['Kbsfw'] * env['dFWSedS']
chem_params['Kbssw_unitless'] = chem_params['Kbssw'] * env['dSWSedS']
# aerosol-air partition coefficient Kp in m^3-air/ug-aer
# m^3/ug * 10^9 ug/kg = 10^9 m^3/kg
# convert Kp to unitless, multiply by its density
# chem_params['Kp_unitless'] = chem_params['Kp_n'] * (10 ** 9) * env['aerP']
chem_params['Kp_unitless'] = 0.54 * (chem_params['Kow_n']/chem_params['Kaw_n']) * env['aerOC'] * (env['aerP']/1000)
# air-aerosol partiton coefficient Kairaer
try:
chem_params['Kairaer'] = 1 / chem_params['Kp_unitless']
except:
chem_params['Kairaer'] = 0
# degradation rate: k = 0.693/(halflife/24)
# transform the units from hours to days
if self.chem_type != 'Metal':
chem_params['kDeg_air_n'] = 24.0 * log(2.0) / chem_params['HL_air_n']
chem_params['kDeg_aer_n'] = 24.0 * log(2.0) / chem_params['HL_aer_n']
chem_params['kDeg_rw_n'] = 24.0 * log(2.0) / chem_params['HL_rWater_n']
chem_params['kDeg_rSS_n'] = 24.0 * log(2.0) / chem_params['HL_rSS_n']
chem_params['kDeg_rSedW_n'] = 24.0 * log(2.0) / chem_params['HL_rSedW_n']
chem_params['kDeg_rSedS_n'] = 24.0 * log(2.0) / chem_params['HL_rSedS_n']
chem_params['kDeg_fw_n'] = 24.0 * log(2.0) / chem_params['HL_fWater_n']
chem_params['kDeg_fSS_n'] = 24.0 * log(2.0) / chem_params['HL_fSS_n']
chem_params['kDeg_fSedW_n'] = 24.0 * log(2.0) / chem_params['HL_fSedW_n']
chem_params['kDeg_fSedS_n'] = 24.0 * log(2.0) / chem_params['HL_fSedS_n']
chem_params['kDeg_sw_n'] = 24.0 * log(2.0) / chem_params['HL_sWater_n']
chem_params['kDeg_sSS_n'] = 24.0 * log(2.0) / chem_params['HL_sSS_n']
chem_params['kDeg_sSedW_n'] = 24.0 * log(2.0) / chem_params['HL_sSedW_n']
chem_params['kDeg_sSedS_n'] = 24.0 * log(2.0) / chem_params['HL_sSedS_n']
chem_params['kDeg_soilA1_n'] = 24.0 * log(2.0) / chem_params['HL_soilA1_n']
chem_params['kDeg_soilW1_n'] = 24.0 * log(2.0) / chem_params['HL_soilW1_n']
chem_params['kDeg_soilS1_n'] = 24.0 * log(2.0) / chem_params['HL_soilS1_n']
chem_params['kDeg_deepS1_n'] = 24.0 * log(2.0) / chem_params['HL_soilDeep1_n']
chem_params['kDeg_soilA2_n'] = 24.0 * log(2.0) / chem_params['HL_soilA2_n']
chem_params['kDeg_soilW2_n'] = 24.0 * log(2.0) / chem_params['HL_soilW2_n']
chem_params['kDeg_soilS2_n'] = 24.0 * log(2.0) / chem_params['HL_soilS2_n']
chem_params['kDeg_deepS2_n'] = 24.0 * log(2.0) / chem_params['HL_soilDeep2_n']
chem_params['kDeg_soilA3_n'] = 24.0 * log(2.0) / chem_params['HL_soilA3_n']
chem_params['kDeg_soilW3_n'] = 24.0 * log(2.0) / chem_params['HL_soilW3_n']
chem_params['kDeg_soilS3_n'] = 24.0 * log(2.0) / chem_params['HL_soilS3_n']
chem_params['kDeg_deepS3_n'] = 24.0 * log(2.0) / chem_params['HL_soilDeep3_n']
chem_params['kDeg_soilA4_n'] = 24.0 * log(2.0) / chem_params['HL_soilA4_n']
chem_params['kDeg_soilW4_n'] = 24.0 * log(2.0) / chem_params['HL_soilW4_n']
chem_params['kDeg_soilS4_n'] = 24.0 * log(2.0) / chem_params['HL_soilS4_n']
chem_params['kDeg_deepS4_n'] = 24.0 * log(2.0) / chem_params['HL_soilDeep4_n']
if chem_type == 'IonizableOrganic':
chem_params['kDeg_aer_i'] = 24.0 * log(2.0) / chem_params['HL_aer_i']
chem_params['kDeg_rw_i'] = 24.0 * log(2.0) / chem_params['HL_rWater_i']
chem_params['kDeg_rSS_i'] = 24.0 * log(2.0) / chem_params['HL_rSS_i']
chem_params['kDeg_rSedW_i'] = 24.0 * log(2.0) / chem_params['HL_rSedW_i']
chem_params['kDeg_rSedS_i'] = 24.0 * log(2.0) / chem_params['HL_rSedS_i']
chem_params['kDeg_fw_i'] = 24.0 * log(2.0) / chem_params['HL_fWater_i']
chem_params['kDeg_fSS_i'] = 24.0 * log(2.0) / chem_params['HL_fSS_i']
chem_params['kDeg_fSedW_i'] = 24.0 * log(2.0) / chem_params['HL_fSedW_i']
chem_params['kDeg_fSedS_i'] = 24.0 * log(2.0) / chem_params['HL_fSedS_i']
chem_params['kDeg_sw_i'] = 24.0 * log(2.0) / chem_params['HL_sWater_i']
chem_params['kDeg_sSS_i'] = 24.0 * log(2.0) / chem_params['HL_sSS_i']
chem_params['kDeg_sSedW_i'] = 24.0 * log(2.0) / chem_params['HL_sSedW_i']
chem_params['kDeg_sSedS_i'] = 24.0 * log(2.0) / chem_params['HL_sSedS_i']
chem_params['kDeg_soilA1_i'] = 24.0 * log(2.0) / chem_params['HL_soilA1_i']
chem_params['kDeg_soilW1_i'] = 24.0 * log(2.0) / chem_params['HL_soilW1_i']
chem_params['kDeg_soilS1_i'] = 24.0 * log(2.0) / chem_params['HL_soilS1_i']
chem_params['kDeg_deepS1_i'] = 24.0 * log(2.0) / chem_params['HL_soilDeep1_i']
chem_params['kDeg_soilA2_i'] = 24.0 * log(2.0) / chem_params['HL_soilA2_i']
chem_params['kDeg_soilW2_i'] = 24.0 * log(2.0) / chem_params['HL_soilW2_i']
chem_params['kDeg_soilS2_i'] = 24.0 * log(2.0) / chem_params['HL_soilS2_i']
chem_params['kDeg_deepS2_i'] = 24.0 * log(2.0) / chem_params['HL_soilDeep2_i']
chem_params['kDeg_soilA3_i'] = 24.0 * log(2.0) / chem_params['HL_soilA3_i']
chem_params['kDeg_soilW3_i'] = 24.0 * log(2.0) / chem_params['HL_soilW3_i']
chem_params['kDeg_soilS3_i'] = 24.0 * log(2.0) / chem_params['HL_soilS3_i']
chem_params['kDeg_deepS3_i'] = 24.0 * log(2.0) / chem_params['HL_soilDeep3_i']
chem_params['kDeg_soilA4_i'] = 24.0 * log(2.0) / chem_params['HL_soilA4_i']
chem_params['kDeg_soilW4_i'] = 24.0 * log(2.0) / chem_params['HL_soilW4_i']
chem_params['kDeg_soilS4_i'] = 24.0 * log(2.0) / chem_params['HL_soilS4_i']
chem_params['kDeg_deepS4_i'] = 24.0 * log(2.0) / chem_params['HL_soilDeep4_i']
if chem_type == 'Metal':
# assign the fraction value when user enters 0, make it to 1e-20
for key in chem_params.keys():
if chem_params[key] == 0:
chem_params[key] = 1e-20
# g/mol / (g/cm3) = cm3/mol
chem_params['molar_mass'] = chem_params['MW'] / 1000.0 # kg/mol
if self.chem_type == 'NonionizableOrganic':
chem_params['molar_volume'] = chem_params['MW'] / chem_params['MD'] # cm3/mol
return chem_params
def load_compart_presence(self):
# load presence of each compartment
df = pd.read_excel(self.region_file, sheet_name="Presence")
presence_loading = zip(df["Code"], df["Presence"])
presence = OrderedDict()
for name, value in presence_loading:
presence[name] = value
return presence
def load_env_params(self, climate, sim_days):
# load the environmental parameters
df = pd.read_excel(self.region_file, sheet_name="Environment")
env_loading = zip(df["Code"], df["Value"])
env = {}
for code, value in env_loading:
env[code] = value
# area calculation
env['rwA'] = env['riverL'] * (env['riverW_min'] + env['riverW_max'])/2 # surface area is length * width
env['fwA'] = env['freshwA']
env['swA'] = env['seawA']
env['area'] = env['fwA'] + env['rwA'] + env['swA'] + env['soilA1'] + env['soilA2'] + env['soilA3'] + env['soilA4']
env['airA'] = env['area']
env['sedRWA'] = env['rwA']
env['sedFWA'] = env['freshwA']
env['sedSWA'] = env['seawA']
env['deepsA1'] = env['soilA1']
env['deepsA2'] = env['soilA2']
env['deepsA3'] = env['soilA3']
env['deepsA4'] = env['soilA4']
env['riverwA'] = env['rwA']
# volume calculation
env['areaV'] = env['area'] * env['airH']
env['rWaterV'] = [(x * env['riverL']) for x in climate['waterflow1_s']] # cross section area * length of river = volume; river water volume directly correlated with flow
env['fWaterV'] = env['freshwA'] * env['freshwD']
env['sWaterV'] = env['seawA'] * env['seawD']
# kg-aer/m3-air * m3-air / (kg-aer/m3-aer) = m3 aer
if env['aerP'] == 0:
env['aerV'] = 0
else:
env['aerV'] = env['aerC'] * (env['areaV'] / env['aerP'])
if env['riverssP'] == 0:
env['rSSV'] = np.repeat(0, sim_days)
else:
env['rSSV'] = env['riverssC'] * np.array(env['rWaterV']) / env['riverssP']
if env['freshssP'] == 0:
env['fSSV'] = 0
else:
env['fSSV'] = env['freshssC'] * (env['fWaterV'] / env['freshssP'])
if env['seassP'] == 0:
env['sSSV'] = 0
else:
env['sSSV'] = env['seassC'] * (env['sWaterV'] / env['seassP'])
env['airV'] = env['areaV'] - env['aerV']
env['rwV'] = env['rWaterV'] - env['rSSV']
env['fwV'] = env['fWaterV'] - env['fSSV']
env['swV'] = env['sWaterV'] - env['sSSV']
# freshwater sediment volume
env['sedRWV'] = env['sedRWA'] * env['sedRiverD']
env['sedFWV'] = env['sedFWA'] * env['sedFWD']
env['sedSWV'] = env['sedSWA'] * env['sedSWD']
env['rSedWV'] = env['sedRWV'] * (1 - env['riversedpercSolid'])
env['rSedSV'] = env['sedRWV'] * env['riversedpercSolid']
env['fSedWV'] = env['sedFWV'] * (1 - env['fsedpercSolid'])
env['fSedSV'] = env['sedFWV'] * env['fsedpercSolid']
env['sSedWV'] = env['sedSWV'] * (1 - env['ssedpercSolid'])
env['sSedSV'] = env['sedSWV'] * env['ssedpercSolid']
# soil commpartments volume (m^3)
env['soilV1'] = env['soilA1'] * env['soilD1']
env['soilV2'] = env['soilA2'] * env['soilD2']
env['soilV3'] = env['soilA3'] * env['soilD3']
env['soilV4'] = env['soilA4'] * env['soilD4']
env['soilAV1'] = env['soilA1'] * env['soilD1'] * env['soilAC1']
env['soilAV2'] = env['soilA2'] * env['soilD2'] * env['soilAC2']
env['soilAV3'] = env['soilA3'] * env['soilD3'] * env['soilAC3']
env['soilAV4'] = env['soilA4'] * env['soilD4'] * env['soilAC4']
# surface soil water volume
env['soilWV1'] = env['soilA1'] * env['soilD1'] * env['soilWC1']
env['soilWV2'] = env['soilA2'] * env['soilD2'] * env['soilWC2']
env['soilWV3'] = env['soilA3'] * env['soilD3'] * env['soilWC3']
env['soilWV4'] = env['soilA4'] * env['soilD4'] * env['soilWC4']
# surface soil solid volume
env['soilSV1'] = env['soilA1'] * env['soilD1'] * (1 - env['soilWC1'] - env['soilAC1'])
env['soilSV2'] = env['soilA2'] * env['soilD2'] * (1 - env['soilWC2'] - env['soilAC2'])
env['soilSV3'] = env['soilA3'] * env['soilD3'] * (1 - env['soilWC3'] - env['soilAC3'])
env['soilSV4'] = env['soilA4'] * env['soilD4'] * (1 - env['soilWC4'] - env['soilAC4'])
# env['soilSV2'] = env['soilA2'] * env['soilD2'] * env['soilSC2']
# env['soilSV1'] = env['soilA1'] * env['soilD1'] * env['soilSC1']
# env['soilSV3'] = env['soilA3'] * env['soilD3'] * env['soilSC3']
# env['soilSV4'] = env['soilA4'] * env['soilD4'] * env['soilSC4']
# deep soil volume (m^3)
env['deepSV1'] = env['soilA1'] * env['deepsD1']
env['deepSV2'] = env['soilA2'] * env['deepsD2']
env['deepSV3'] = env['soilA3'] * env['deepsD3']
env['deepSV4'] = env['soilA4'] * env['deepsD4']
# volumn percentage calculation
if all(x == 0 for x in env['rWaterV']):
env['rSSVf'] = np.repeat(0, sim_days)
else:
env['rSSVf'] = env['rSSV'] / env['rWaterV']
if env['fWaterV'] == 0:
env['fSSVf'] = 0
else:
env['fSSVf'] = env['fSSV'] / env['fWaterV']
if env['sWaterV'] == 0:
env['sSSVf'] = 0
else:
env['sSSVf'] = env['sSSV'] / env['sWaterV']
env['rwVf'] = 1 - env['rSSVf']
env['fwVf'] = 1 - env['fSSVf']
env['swVf'] = 1 - env['sSSVf']
env['aerVf'] = (env['aerV'] / env['areaV'])
env['airVf'] = 1 - env['aerVf']
env['soilSC1'] = 1 - env['soilWC1'] - env['soilAC1']
env['soilSC2'] = 1 - env['soilWC2'] - env['soilAC2']
env['soilSC3'] = 1 - env['soilWC3'] - env['soilAC3']
env['soilSC4'] = 1 - env['soilWC4'] - env['soilAC4']
# density calculation
# soil bulk density (kg/m3)
env['soilP1'] = env['dSS1'] * env['soilSC1'] + env['freshwP'] * env['soilWC1'] + env['airP'] * env['soilAC1']
env['soilP2'] = env['dSS2'] * env['soilSC2'] + env['freshwP'] * env['soilWC2'] + env['airP'] * env['soilAC2']
env['soilP3'] = env['dSS3'] * env['soilSC3'] + env['freshwP'] * env['soilWC3'] + env['airP'] * env['soilAC3']
env['soilP4'] = env['dSS4'] * env['soilSC4'] + env['freshwP'] * env['soilWC4'] + env['airP'] * env['soilAC4']
# CN values will be used in soilRunoff.py
env['CN1'] = 1000.0 / env['CN1'] - 10.0
env['CN2'] = 1000.0 / env['CN2'] - 10.0
env['CN3'] = 1000.0 / env['CN3'] - 10.0
env['CN4'] = 1000.0 / env['CN4'] - 10.0
return env
def load_climate(self):
# load climate parameters
start_row, end_row = self.load_date()
df = pd.read_excel(self.region_file, sheet_name="Climate")
df = df.iloc[start_row:end_row]
climate_month = df["Month"].tolist()
climate_day = df["Day"].tolist()
climate_year = df["Year"].tolist()
# precipitation unit: mm/day
climate_precip = df["Precipitation (mm/day)"].tolist()
# windspeed unit: m/second
climate_windspeed = df["Windspeed (m/second)"].tolist()
# water flow unit: m3/second
climate_flow1 = df["River Flow (m^3/s)"].tolist() # river
climate_flow2 = df["Lake flow (m^3/s)"].tolist() # lake
# temperature unit: C
climate_temp = df["Temperature ('C)"].tolist()
# evaporation unit: mm
climate_evap = df["Evaporation (mm)"].tolist()
new_month = [int(i) for i in climate_month]
new_day = [int(i) for i in climate_day]
new_year = [int(i) for i in climate_year]
date = zip(new_year, new_month, new_day)
# unit conversion
climate = OrderedDict()
climate['dates'] = date
climate['precip_mm'] = climate_precip # mm/day
climate['precip_m'] = [(x / 1000.0) for x in climate['precip_mm']] # m/day
climate['windspeed_s'] = climate_windspeed # m/second
climate['windspeed_d'] = [(x * 86400.0) for x in climate['windspeed_s']] # m/day
climate['waterflow1_s'] = climate_flow1 # m3/s
climate['waterflow1_d'] = [(x * 86400.0) for x in climate['waterflow1_s']] # m^3/day
climate['waterflow2_s'] = climate_flow2 # m3/s
climate['waterflow2_d'] = [(x * 86400.0) for x in climate['waterflow2_s']] # m^3/day
climate['temp_C'] = climate_temp # C - celcius
climate['temp_K'] = [(x + 273.15) for x in climate['temp_C']] # K
climate['evap_mm'] = climate_evap
return climate
def load_bg_conc(self, chem_params):
# load background concentration
df = pd.read_excel(self.release_file, sheet_name="bgConc", skiprows=1)
bgConc_loading = zip(df["Code"], df["kg/m^3"])
bgConc = {}
for code, value in bgConc_loading:
# unit conversion from kg/m^3 to mol/m^3
# kg/m3 / kg/mol = mol/m3
bgConc[code] = value/ chem_params['molar_mass']
return bgConc
def load_release(self, chem_params, presence):
# load release data
start_row, end_row = self.load_date()
# to take into account of the row of release scenario
df = pd.read_excel(self.release_file, sheet_name="Release", skiprows=1)
df2 = pd.read_excel(self.release_file, sheet_name="Release", index_col="Release Scenario")
release_scenario = df2.columns[0]
df = df.iloc[start_row:end_row]
release_month = df["Month"].tolist()
release_day = df["Day"].tolist()
release_year = df["Year"].tolist()
release_air = df["Air (kg/day)"].tolist()
release_rw = df["Riverwater (kg/day)"].tolist()
release_rSS = df["Riverwater Suspended Sediment (kg/day)"].tolist()
release_rwSed = df["Riverwater Sediment (kg/day)"].tolist()
release_fw = df["Freshwater (kg/day)"].tolist()
release_fSS = df["Freshwater Suspended Sediment (kg/day)"].tolist()
release_fwSed = df["Freshwater Sediment (kg/day)"].tolist()
release_sw = df["Seawater (kg/day)"].tolist()
release_sSS = df["Seawater Suspended Sediment (kg/day)"].tolist()
release_swSed = df["Seawater Sediment (kg/day)"].tolist()
release_soil1 = df["Undeveloped Surface Soil (kg/day)"].tolist()
release_dsoil1 = df["Undeveloped Deep Soil (kg/day)"].tolist()
release_soil2 = df["Urban Surface Soil (kg/day)"].tolist()
release_dsoil2 = df["Urban Deep Soil (kg/day)"].tolist()
release_soil3 = df["Agricultural Surface Soil (kg/day)"].tolist()
release_dsoil3 = df["Agricultural Deep Soil (kg/day)"].tolist()
release_soil4 = df["Agricultural Surface Soil Biosolid (kg/day)"].tolist()
release_dsoil4 = df["Agricultural Deep Soil Biosolid (kg/day)"].tolist()
# Create Datetime Objects
new_datetime = []
new_month = [int(i) for i in release_month]
new_day = [int(i) for i in release_day]
new_year = [int(i) for i in release_year]
dt = zip(new_year, new_month, new_day)
release = {}
release['dates'] = dt
# mol/day
release['air'] = [(x / chem_params['molar_mass']) for x in release_air]
release['rw'] = [(x / chem_params['molar_mass']) for x in release_rw]
release['rSS'] = [(x / chem_params['molar_mass']) for x in release_rSS]
release['rwSed'] = [(x / chem_params['molar_mass']) for x in release_rwSed]
release['fw'] = [(x / chem_params['molar_mass']) for x in release_fw]
release['fSS'] = [(x / chem_params['molar_mass']) for x in release_fSS]
release['fwSed'] = [(x / chem_params['molar_mass']) for x in release_fwSed]
release['sw'] = [(x / chem_params['molar_mass']) for x in release_sw]
release['sSS'] = [(x / chem_params['molar_mass']) for x in release_sSS]
release['swSed'] = [(x / chem_params['molar_mass']) for x in release_swSed]
release['soil1'] = [(x / chem_params['molar_mass']) for x in release_soil1]
release['dsoil1'] = [(x / chem_params['molar_mass']) for x in release_dsoil1]
release['soil2'] = [(x / chem_params['molar_mass']) for x in release_soil2]
release['dsoil2'] = [(x / chem_params['molar_mass']) for x in release_dsoil2]
release['soil3'] = [(x / chem_params['molar_mass']) for x in release_soil3]
release['dsoil3'] = [(x / chem_params['molar_mass']) for x in release_dsoil3]
release['soil4'] = [(x / chem_params['molar_mass']) for x in release_soil4]
release['dsoil4'] = [(x / chem_params['molar_mass']) for x in release_dsoil4]
return release, release_scenario
def run_loadData(self):
# run the functions above to load all of the data
presence = self.load_compart_presence()
climate = self.load_climate()
env = self.load_env_params(climate, self.sim_days)
chem_params = self.load_chemParams(self.chem_type, env)
bgConc = self.load_bg_conc(chem_params)
release, release_scenario = self.load_release(chem_params, presence)
return chem_params, presence, env, climate, bgConc, release, release_scenario