def runBaklidammen(startDate, endDate):
LocationNames = ["Baklidammen 200 moh"]
x = 266550
y = 7040812
from_date = dt.datetime.strptime(startDate, "%Y-%m-%d")
to_date = dt.datetime.strptime(endDate, "%Y-%m-%d")
cs_temp = gcsd.getGriddata(x, y, "tm", from_date, to_date)
cs_sno = gcsd.getGriddata(x, y, "fsw", from_date, to_date)
cs_snotot = gcsd.getGriddata(x, y, "sd", from_date, to_date)
wsCC = gws.getMetData(68860, "NNM", startDate, endDate, 0, "list") # TRONDHEIM - VOLL
temp, date = we.strip_metadata(cs_temp, True)
sno = we.strip_metadata(cs_sno, False)
snotot = we.strip_metadata(cs_snotot, False)
cc = we.strip_metadata(wsCC, False)
observed_ice = gro.get_all_season_ice(LocationNames, startDate, endDate)
if len(observed_ice) == 0:
ice_cover = calculate_ice_cover_air_temp(ice.IceColumn(date[0], []), date, temp, sno, cc)
else:
ice_cover = calculate_ice_cover_air_temp(copy.deepcopy(observed_ice[0]), date, temp, sno, cc)
plot_filename = "{0}Baklidammen {1}-{2}.png".format(plot_folder, startDate[0:4], endDate[0:4])
pts.plot_ice_cover(ice_cover, observed_ice, date, temp, snotot, plot_filename)
def runStorvannetHammerfest(startDate, endDate):
LocationNames = ["Storvannet, 7 moh"]
x = 821340
y = 7862497
from_date = dt.datetime.strptime(startDate, "%Y-%m-%d")
to_date = dt.datetime.strptime(endDate, "%Y-%m-%d")
cs_temp = gcsd.getGriddata(x, y, "tm", from_date, to_date)
cs_sno = gcsd.getGriddata(x, y, "fsw", from_date, to_date)
cs_snotot = gcsd.getGriddata(x, y, "sd", from_date, to_date)
wsCC = gws.getMetData(95350, "NNM", startDate, endDate, 0, "list") # BANAK - østover innerst i fjorden
temp, date = we.strip_metadata(cs_temp, True)
sno = we.strip_metadata(cs_sno, False)
snotot = we.strip_metadata(cs_snotot, False)
cc = we.strip_metadata(wsCC, False)
observed_ice = gro.get_all_season_ice(LocationNames, startDate, endDate)
if len(observed_ice) == 0:
ice_cover = calculate_ice_cover_air_temp(ice.IceColumn(date[0], []), date, temp, sno, cc)
else:
ice_cover = calculate_ice_cover_air_temp(copy.deepcopy(observed_ice[0]), date, temp, sno, cc)
plot_filename = "{0}StorvannetHammerfest {1}-{2}.png".format(plot_folder, startDate[0:4], endDate[0:4])
pts.plot_ice_cover(ice_cover, observed_ice, date, temp, snotot, plot_filename)
def runSkoddebergvatnet(startDate, endDate):
LocationName = "Skoddebergvatnet - nord 101 moh"
# Skoddebergvatnet - sør 101 moh
from_date = dt.datetime.strptime(startDate, "%Y-%m-%d")
to_date = dt.datetime.strptime(endDate, "%Y-%m-%d")
# cs_temp = gcsd.getGriddata('189.3.0','17.1', from_date, to_date)
cs_temp = gcsd.getGriddata(593273, 7612469, "tm", from_date, to_date)
cs_sno = gcsd.getGriddata(593273, 7612469, "fsw", from_date, to_date)
cs_snotot = gcsd.getGriddata(593273, 7612469, "sd", from_date, to_date)
wsCC = gws.getMetData(87640, "NNM", startDate, endDate, 0, "list") # Harstad Stadion
temp, date = we.strip_metadata(cs_temp, True)
sno = we.strip_metadata(cs_sno, False)
snotot = we.strip_metadata(cs_snotot, False)
cc = we.strip_metadata(wsCC, False)
observed_ice = gro.get_all_season_ice(LocationName, startDate, endDate)
if len(observed_ice) == 0:
ice_cover = calculate_ice_cover_air_temp(ice.IceColumn(date[0], []), date, temp, sno, cc)
else:
ice_cover = calculate_ice_cover_air_temp(copy.deepcopy(observed_ice[0]), date, temp, sno, cc)
plot_filename = "{0}Skoddebergvatnet {1}-{2}.png".format(plot_folder, startDate[0:4], endDate[0:4])
pts.plot_ice_cover(ice_cover, observed_ice, date, temp, snotot, plot_filename)
def runGiljastolsvatnet(startDate, endDate):
LocationNames = ["Giljastølsvatnet 412 moh", "Giljastølvatnet sør 412 moh"]
x = -1904
y = 6553573
from_date = dt.datetime.strptime(startDate, "%Y-%m-%d")
to_date = dt.datetime.strptime(endDate, "%Y-%m-%d")
# cs_temp = gcsd.getStationdata('189.3.0','17.1', from_date, to_date)
cs_temp = gcsd.getGriddata(x, y, "tm", from_date, to_date)
cs_sno = gcsd.getGriddata(x, y, "fsw", from_date, to_date)
cs_snotot = gcsd.getGriddata(x, y, "sd", from_date, to_date)
wsCC = gws.getMetData(
43010, "NNM", startDate, endDate, 0, "list"
) # Eik - Hove. Ligger lenger sør men er litt inn i landet.
# wsCC = getMetData(43010, 'NNM', startDate, endDate, 0, 'list') # Sola (44560) er et alternativ
temp, date = we.strip_metadata(cs_temp, True)
sno = we.strip_metadata(cs_sno, False)
snotot = we.strip_metadata(cs_snotot, False)
cc = we.strip_metadata(wsCC, False)
observed_ice = gro.get_all_season_ice(LocationNames, startDate, endDate)
if len(observed_ice) == 0:
ice_cover = calculate_ice_cover_air_temp(ice.IceColumn(date[0], []), date, temp, sno, cc)
else:
ice_cover = calculate_ice_cover_air_temp(copy.deepcopy(observed_ice[0]), date, temp, sno, cc)
plot_filename = "{0}Giljastolsvatnet {1}-{2}.png".format(plot_folder, startDate[0:4], endDate[0:4])
pts.plot_ice_cover(ice_cover, observed_ice, date, temp, snotot, plot_filename)
def runStorvannetHammerfest(startDate, endDate):
LocationNames = ['Storvannet, 7 moh']
x = 821340
y = 7862497
from_date = dt.datetime.strptime(startDate, "%Y-%m-%d")
to_date = dt.datetime.strptime(endDate, "%Y-%m-%d")
cs_temp = gcsd.getGriddata(x, y, 'tm', from_date, to_date)
cs_sno = gcsd.getGriddata(x, y, 'fsw', from_date, to_date)
cs_snotot = gcsd.getGriddata(x, y, 'sd', from_date, to_date)
wsCC = gws.getMetData(95350, 'NNM', startDate, endDate, 0, 'list') # BANAK - østover innerst i fjorden
temp, date = we.strip_metadata(cs_temp, True)
sno = we.strip_metadata(cs_sno, False)
snotot = we.strip_metadata(cs_snotot, False)
cc = we.strip_metadata(wsCC, False)
observed_ice = gro.get_all_season_ice(LocationNames, startDate, endDate)
if len(observed_ice) == 0:
ice_cover = calculate_ice_cover_air_temp(ice.IceColumn(date[0], []), date, temp, sno, cc)
else:
ice_cover = calculate_ice_cover_air_temp(copy.deepcopy(observed_ice[0]), date, temp, sno, cc)
plot_filename = '{0}StorvannetHammerfest {1}-{2}.png'.format(plot_folder, startDate[0:4], endDate[0:4])
pts.plot_ice_cover(ice_cover, observed_ice, date, temp, snotot, plot_filename)
def runHakkloa(startDate, endDate):
LocationName = "Hakkloa nord 372 moh"
from_date = dt.datetime.strptime(startDate, "%Y-%m-%d")
to_date = dt.datetime.strptime(endDate, "%Y-%m-%d")
cs_temp = gcsd.getStationdata("6.24.4", "17.1", from_date, to_date, timeseries_type=0)
cs_sno = gcsd.getGriddata(260150, 6671135, "fsw", from_date, to_date, timeseries_type=0)
cs_snotot = gcsd.getGriddata(260150, 6671135, "sd", from_date, to_date, timeseries_type=0)
wsCC = gws.getMetData(18700, "NNM", startDate, endDate, 0, "list")
temp, date = we.strip_metadata(cs_temp, True)
sno = we.strip_metadata(cs_sno, False)
snotot = we.strip_metadata(cs_snotot, False)
cc = we.strip_metadata(wsCC, False)
observed_ice = gro.get_all_season_ice(LocationName, startDate, endDate)
if len(observed_ice) == 0:
ice_cover = calculate_ice_cover_air_temp(ice.IceColumn(date[0], []), date, temp, sno, cc)
else:
ice_cover = calculate_ice_cover_air_temp(copy.deepcopy(observed_ice[0]), date, temp, sno, cc)
plot_filename = "{0}Hakkloa {1}-{2}.png".format(plot_folder, startDate[0:4], endDate[0:4])
pts.plot_ice_cover(ice_cover, observed_ice, date, temp, snotot, plot_filename)
def runBaklidammen(startDate, endDate):
LocationNames = ['Baklidammen 200 moh']
x = 266550
y = 7040812
from_date = dt.datetime.strptime(startDate, "%Y-%m-%d")
to_date = dt.datetime.strptime(endDate, "%Y-%m-%d")
cs_temp = gcsd.getGriddata(x, y, 'tm', from_date, to_date)
cs_sno = gcsd.getGriddata(x, y, 'fsw', from_date, to_date)
cs_snotot = gcsd.getGriddata(x, y, 'sd', from_date, to_date)
wsCC = gws.getMetData(68860, 'NNM', startDate, endDate, 0, 'list') # TRONDHEIM - VOLL
temp, date = we.strip_metadata(cs_temp, True)
sno = we.strip_metadata(cs_sno, False)
snotot = we.strip_metadata(cs_snotot, False)
cc = we.strip_metadata(wsCC, False)
observed_ice = gro.get_all_season_ice(LocationNames, startDate, endDate)
if len(observed_ice) == 0:
ice_cover = calculate_ice_cover_air_temp(ice.IceColumn(date[0], []), date, temp, sno, cc)
else:
ice_cover = calculate_ice_cover_air_temp(copy.deepcopy(observed_ice[0]), date, temp, sno, cc)
plot_filename = '{0}Baklidammen {1}-{2}.png'.format(plot_folder, startDate[0:4], endDate[0:4])
pts.plot_ice_cover(ice_cover, observed_ice, date, temp, snotot, plot_filename)
def runGiljastolsvatnet(startDate, endDate):
LocationNames = ['Giljastølsvatnet 412 moh', 'Giljastølvatnet sør 412 moh']
x = -1904
y = 6553573
from_date = dt.datetime.strptime(startDate, "%Y-%m-%d")
to_date = dt.datetime.strptime(endDate, "%Y-%m-%d")
#cs_temp = gcsd.getStationdata('189.3.0','17.1', from_date, to_date)
cs_temp = gcsd.getGriddata(x, y, 'tm', from_date, to_date)
cs_sno = gcsd.getGriddata(x, y, 'fsw', from_date, to_date)
cs_snotot = gcsd.getGriddata(x, y, 'sd', from_date, to_date)
wsCC = gws.getMetData(43010, 'NNM', startDate, endDate, 0, 'list') # Eik - Hove. Ligger lenger sør men er litt inn i landet.
#wsCC = getMetData(43010, 'NNM', startDate, endDate, 0, 'list') # Sola (44560) er et alternativ
temp, date = we.strip_metadata(cs_temp, True)
sno = we.strip_metadata(cs_sno, False)
snotot = we.strip_metadata(cs_snotot, False)
cc = we.strip_metadata(wsCC, False)
observed_ice = gro.get_all_season_ice(LocationNames, startDate, endDate)
if len(observed_ice) == 0:
ice_cover = calculate_ice_cover_air_temp(ice.IceColumn(date[0], []), date, temp, sno, cc)
else:
ice_cover = calculate_ice_cover_air_temp(copy.deepcopy(observed_ice[0]), date, temp, sno, cc)
plot_filename = '{0}Giljastolsvatnet {1}-{2}.png'.format(plot_folder, startDate[0:4], endDate[0:4])
pts.plot_ice_cover(ice_cover, observed_ice, date, temp, snotot, plot_filename)
def runSkoddebergvatnet(startDate, endDate):
LocationName = 'Skoddebergvatnet - nord 101 moh'
# Skoddebergvatnet - sør 101 moh
from_date = dt.datetime.strptime(startDate, "%Y-%m-%d")
to_date = dt.datetime.strptime(endDate, "%Y-%m-%d")
#cs_temp = gcsd.getGriddata('189.3.0','17.1', from_date, to_date)
cs_temp = gcsd.getGriddata(593273, 7612469, 'tm', from_date, to_date)
cs_sno = gcsd.getGriddata(593273, 7612469, 'fsw', from_date, to_date)
cs_snotot = gcsd.getGriddata(593273, 7612469, 'sd', from_date, to_date)
wsCC = gws.getMetData(87640, 'NNM', startDate, endDate, 0, 'list') # Harstad Stadion
temp, date = we.strip_metadata(cs_temp, True)
sno = we.strip_metadata(cs_sno, False)
snotot = we.strip_metadata(cs_snotot, False)
cc = we.strip_metadata(wsCC, False)
observed_ice = gro.get_all_season_ice(LocationName, startDate, endDate)
if len(observed_ice) == 0:
ice_cover = calculate_ice_cover_air_temp(ice.IceColumn(date[0], []), date, temp, sno, cc)
else:
ice_cover = calculate_ice_cover_air_temp(copy.deepcopy(observed_ice[0]), date, temp, sno, cc)
plot_filename = '{0}Skoddebergvatnet {1}-{2}.png'.format(plot_folder, startDate[0:4], endDate[0:4])
pts.plot_ice_cover(ice_cover, observed_ice, date, temp, snotot, plot_filename)
def runHakkloa(startDate, endDate):
LocationName = 'Hakkloa nord 372 moh'
from_date = dt.datetime.strptime(startDate, "%Y-%m-%d")
to_date = dt.datetime.strptime(endDate, "%Y-%m-%d")
cs_temp = gcsd.getStationdata('6.24.4','17.1', from_date, to_date, timeseries_type=0)
cs_sno = gcsd.getGriddata(260150, 6671135, 'fsw', from_date, to_date, timeseries_type=0)
cs_snotot = gcsd.getGriddata(260150, 6671135, 'sd', from_date, to_date, timeseries_type=0)
wsCC = gws.getMetData(18700, 'NNM', startDate, endDate, 0, 'list')
temp, date = we.strip_metadata(cs_temp, True)
sno = we.strip_metadata(cs_sno, False)
snotot = we.strip_metadata(cs_snotot, False)
cc = we.strip_metadata(wsCC, False)
observed_ice = gro.get_all_season_ice(LocationName, startDate, endDate)
if len(observed_ice) == 0:
ice_cover = calculate_ice_cover_air_temp(ice.IceColumn(date[0], []), date, temp, sno, cc)
else:
ice_cover = calculate_ice_cover_air_temp(copy.deepcopy(observed_ice[0]), date, temp, sno, cc)
plot_filename = '{0}Hakkloa {1}-{2}.png'.format(plot_folder, startDate[0:4], endDate[0:4])
pts.plot_ice_cover(ice_cover, observed_ice, date, temp, snotot, plot_filename)
def harvest_for_mylake_hakkloa(from_string, to_string):
"""Method gathers meteorological parameters needed to run myLake on Hakkloa and saves them to a
formatted file as needed to run myLake. For columns needed se MyLakeInput class.
:param from_string: {string} from date to acquire data
:param to_string: {string} to date to acquire data
:return:
HydraII parameters:
Wind 15
Temperature 17
Relative humidity 2
"""
utm33_x = 259942 # Hakloa (buoy)
utm33_y = 6671218 # Hakloa (buoy)
stnr_met_blind = 18700 # Blindern (met)
stnr_met_bjorn = 18500 # Bjørnholt (met)
stnr_nve = '6.24.4' # Hakloa (NVE)
hydraii_temperature = '{0}6.24.4.17.1 Hakkloa temperatur 20110101-20151009.txt'.format(env.data_path)
hydraii_wind = '{0}6.24.4.15.1 Hakkloa vind 20110101-20151009.txt'.format(env.data_path)
hydraii_relative_humidity = '{0}6.24.4.2.1 Hakkloa relativ fuktighet 20110101-20151009.txt'.format(env.data_path)
from_date = dt.datetime.strptime(from_string, "%Y-%m-%d")
to_date = dt.datetime.strptime(to_string, "%Y-%m-%d")
data = MyLakeInput(from_date, to_date)
data.output_file_path = '{0}HAK_input'.format(env.data_path)
data.output_header = 'MyLake model input data for Hakkloa from Hakkloa (NVE), Bjørnholt (met) and Blindern (met) stations'
data.add_Global_rad(we.constant_weather_element('Hakkloa', from_date, to_date, 'Global_rad', None))
data.add_Cloud_cov(gws.getMetData(stnr_met_blind, 'NNM', from_date, to_date, 0))
data.add_Air_temp(gfd.read_hydra_time_value(stnr_nve, '17.1', hydraii_temperature, from_date, to_date))
data.add_Relat_hum(gfd.read_hydra_time_value(stnr_nve, '2.1', hydraii_relative_humidity, from_date, to_date))
data.add_Air_press(gws.getMetData(stnr_met_blind, 'POM', from_date, to_date, 0))
data.add_Wind_speed(gfd.read_hydra_time_value(stnr_nve, '15.1', hydraii_wind, from_date, to_date))
data.add_Precipitation(we.millimeter_from_meter(gws.getMetData(stnr_met_bjorn, 'RR', from_date, to_date, 0)))
# Inflow is water shed area * precipitation
Inflow = []
precipitation = data.Precipitation # precipitation in [mm]
water_shed_area = 6.49 * 10**6 # [m2]
for p in precipitation:
value = p.Value/1000*water_shed_area
Inflow.append(we.WeatherElement('Hakkloa', p.Date, 'Inflow', value))
data.add_Inflow(Inflow)
# Inflow temperature is assumed air temp but never below 0C and if snow always 0C
snow = gcs.getGriddata(utm33_x, utm33_y, 'sd', from_date, to_date)
temperature = data.Air_temp
#mfd.write_weather_element_list(temperature)
#mfd.write_weather_element_list(snow)
#mfd.write_weather_element_list(data.Relat_hum)
#mfd.write_weather_element_list(data.Wind_speed)
Inflow_T = []
for i in range(0, len(snow), 1):
date = temperature[i].Date
value = max(0., temperature[i].Value) # water never below 0C
if snow[i].Value > 0. and value > 0.: # if snow, water never over 0C
value = 0.
Inflow_T.append(we.WeatherElement('Hakkloa', date, 'Inflow_T', value))
data.add_Inflow_T(Inflow_T)
data.add_Inflow_C(we.constant_weather_element('Hakkloa', from_date, to_date, 'Inflow_C', .5))
data.add_Inflow_S(we.constant_weather_element('Hakkloa', from_date, to_date, 'Inflow_S', .01))
data.add_Inflow_TP(we.constant_weather_element('Hakkloa', from_date, to_date, 'Inflow_TP', 44.))
data.add_Inflow_DOP(we.constant_weather_element('Hakkloa', from_date, to_date, 'Inflow_DOP', 7.))
data.add_Inflow_Chla(we.constant_weather_element('Hakkloa', from_date, to_date, 'Inflow_Chla', .1))
data.add_Inflow_DOC(we.constant_weather_element('Hakkloa', from_date, to_date, 'Inflow_DOC', 3000.))
return data
def harvest_for_mylake_hakkloa(from_string, to_string):
"""Method gathers meteorological parameters needed to run myLake on Hakkloa and saves them to a
formatted file as needed to run myLake. For columns needed se MyLakeInput class.
:param from_string: {string} from date to acquire data
:param to_string: {string} to date to acquire data
:return:
HydraII parameters:
Wind 15
Temperature 17
Relative humidity 2
"""
utm33_x = 259942 # Hakloa (buoy)
utm33_y = 6671218 # Hakloa (buoy)
stnr_met_blind = 18700 # Blindern (met)
stnr_met_bjorn = 18500 # Bjørnholt (met)
stnr_nve = '6.24.4' # Hakloa (NVE)
hydraii_temperature = '{0}6.24.4.17.1 Hakkloa temperatur 20110101-20151009.txt'.format(
env.data_path)
hydraii_wind = '{0}6.24.4.15.1 Hakkloa vind 20110101-20151009.txt'.format(
env.data_path)
hydraii_relative_humidity = '{0}6.24.4.2.1 Hakkloa relativ fuktighet 20110101-20151009.txt'.format(
env.data_path)
from_date = dt.datetime.strptime(from_string, "%Y-%m-%d")
to_date = dt.datetime.strptime(to_string, "%Y-%m-%d")
data = MyLakeInput(from_date, to_date)
data.output_file_path = '{0}HAK_input'.format(env.data_path)
data.output_header = 'MyLake model input data for Hakkloa from Hakkloa (NVE), Bjørnholt (met) and Blindern (met) stations'
data.add_Global_rad(
we.constant_weather_element('Hakkloa', from_date, to_date,
'Global_rad', None))
data.add_Cloud_cov(
gws.getMetData(stnr_met_blind, 'NNM', from_date, to_date, 0))
data.add_Air_temp(
gfd.read_hydra_time_value(stnr_nve, '17.1', hydraii_temperature,
from_date, to_date))
data.add_Relat_hum(
gfd.read_hydra_time_value(stnr_nve, '2.1', hydraii_relative_humidity,
from_date, to_date))
data.add_Air_press(
gws.getMetData(stnr_met_blind, 'POM', from_date, to_date, 0))
data.add_Wind_speed(
gfd.read_hydra_time_value(stnr_nve, '15.1', hydraii_wind, from_date,
to_date))
data.add_Precipitation(
we.millimeter_from_meter(
gws.getMetData(stnr_met_bjorn, 'RR', from_date, to_date, 0)))
# Inflow is water shed area * precipitation
Inflow = []
precipitation = data.Precipitation # precipitation in [mm]
water_shed_area = 6.49 * 10**6 # [m2]
for p in precipitation:
value = p.Value / 1000 * water_shed_area
Inflow.append(we.WeatherElement('Hakkloa', p.Date, 'Inflow', value))
data.add_Inflow(Inflow)
# Inflow temperature is assumed air temp but never below 0C and if snow always 0C
snow = gcs.getGriddata(utm33_x, utm33_y, 'sd', from_date, to_date)
temperature = data.Air_temp
#mfd.write_weather_element_list(temperature)
#mfd.write_weather_element_list(snow)
#mfd.write_weather_element_list(data.Relat_hum)
#mfd.write_weather_element_list(data.Wind_speed)
Inflow_T = []
for i in range(0, len(snow), 1):
date = temperature[i].Date
value = max(0., temperature[i].Value) # water never below 0C
if snow[i].Value > 0. and value > 0.: # if snow, water never over 0C
value = 0.
Inflow_T.append(we.WeatherElement('Hakkloa', date, 'Inflow_T', value))
data.add_Inflow_T(Inflow_T)
data.add_Inflow_C(
we.constant_weather_element('Hakkloa', from_date, to_date, 'Inflow_C',
.5))
data.add_Inflow_S(
we.constant_weather_element('Hakkloa', from_date, to_date, 'Inflow_S',
.01))
data.add_Inflow_TP(
we.constant_weather_element('Hakkloa', from_date, to_date, 'Inflow_TP',
44.))
data.add_Inflow_DOP(
we.constant_weather_element('Hakkloa', from_date, to_date,
'Inflow_DOP', 7.))
data.add_Inflow_Chla(
we.constant_weather_element('Hakkloa', from_date, to_date,
'Inflow_Chla', .1))
data.add_Inflow_DOC(
we.constant_weather_element('Hakkloa', from_date, to_date,
'Inflow_DOC', 3000.))
return data
