def iwater(io_manager, siminfo, uci, ts):
''' Driver for IMPLND IWATER code. CALL: iwater(store, general, ui, ts)
store is the Pandas/PyTable open store
general is a dictionary with simulation info (OP_SEQUENCE for example)
ui is a dictionary with ILS specific HSPF UCI like data
ts is a dictionary with ILS specific timeseries'''
# WATIN, WATDIF, IMPS not saved since trival calculation from saved data
# WATIN = SUPY + SURLI
# WATDIF = WATIN - (SURO + IMPEV)
# IMPS = RETS + SURS
steps = siminfo['steps'] # number of simulation points
# insure defined, but not usable - just in case
for name in ('AIRTMP', 'PETINP', 'PREC', 'RAINF', 'SNOCOV', 'WYIELD'):
if name not in ts:
ts[name] = full(steps, nan, dtype=float64)
# treat missing flows as zero flow
for name in ['SURLI']: # RTLIFG = 1 requires this timeseries
if name not in ts:
ts[name] = zeros(steps, dtype=float64)
# Replace fixed parameters in HSPF with timeseries
for name in ['PETMAX', 'PETMIN']:
if name not in ts:
ts[name] = full(steps, uci['PARAMETERS'][name], dtype=float64)
# process optional monthly arrays to return interpolated data or constant array
u = uci['PARAMETERS']
if 'VRSFG' in u:
ts['RETSC'] = initm(siminfo, uci, u['VRSFG'], 'MONTHLY_RETSC',
u['RETSC'])
ts['NSUR'] = initm(siminfo, uci, u['VNNFG'], 'MONTHLY_NSUR', u['NSUR'])
else:
ts['RETSC'] = full(steps, u['RETSC'])
ts['NSUR'] = full(steps, u['NSUR'])
# true the first time and at 1am every day of simulation
ts['HR1FG'] = hourflag(siminfo, 1, dofirst=True).astype(
float64) # numba Dict limitation
# true the first time and at every hour of simulation
ts['HRFG'] = hoursval(siminfo, ones(24), dofirst=True).astype(
float64) # numba Dict limitation
ui = make_numba_dict(
uci) # Note: all values coverted to float automatically
ui['steps'] = steps
ui['delt'] = siminfo['delt']
ui['errlen'] = len(ERRMSGS)
ui['uunits'] = siminfo['units']
############################################################################
errors = _iwater_(ui, ts) # run IWATER simulation code
############################################################################
return errors, ERRMSGS
def hour6flag(siminfo, dofirst=False):
'''timeseries with 1 at 6am and earlier each day, and zero otherwise'''
hours24 = zeros(24)
hours24[0] = 1.0
hours24[1] = 1.0
hours24[2] = 1.0
hours24[3] = 1.0
hours24[4] = 1.0
hours24[5] = 1.0
return hoursval(siminfo, hours24, dofirst)
def snow(store, siminfo, uci, ts):
''' high level driver for SNOW module
CALL: snow(store, general, ui, ts)
store is the Pandas/PyTable open store
siminfo is a dictionary with simulation level infor (OP_SEQUENCE for example)
ui is a dictionary with segment specific HSPF UCI like data
ts is a dictionary with segment specific timeseries'''
steps = siminfo['steps'] # number of simulation timesteps
ts['SVP'] = store['TIMESERIES/Saturated_Vapor_Pressure_Table'].to_numpy()
ts['SEASONS'] = monthval(siminfo, store['TIMESERIES/SEASONS_Table'])
cloudfg = 'CLOUD' in ts
# insure defined, but can't be used accidently
for name in ['AIRTMP', 'CLOUD', 'DTMPG', 'PREC', 'SOLRAD', 'WINMOV']:
if name not in ts:
ts[name] = full(steps, nan)
# Replace fixed parameters in HSPF with time series
for name in [
'CCFACT', 'COVIND', 'MGMELT', 'MWATER', 'SHADE', 'SNOEVP',
'SNOWCF', 'KMELT'
]:
if name not in ts and name in uci['PARAMETERS']:
ts[name] = full(steps, uci['PARAMETERS'][name])
# true the first time and at 6am every day of simulation
ts['HR6FG'] = hourflag(siminfo, 6, dofirst=True).astype(float)
# true the first time and at every hour of simulation
ts['HRFG'] = hoursval(siminfo, ones(24), dofirst=True).astype(float)
# make ICEFG available to PWATER later.
siminfo['ICEFG'] = uci['FLAGS']['ICEFG'] if 'ICEFG' in uci['FLAGS'] else 0
ui = make_numba_dict(
uci) # Note: all values coverted to float automatically
ui['steps'] = steps
ui['delt'] = siminfo['delt']
ui['errlen'] = len(ERRMSGS)
ui['cloudfg'] = cloudfg
############################################################################
errors = _snow_(ui, ts)
############################################################################
if siminfo['delt'] > 360 and int(siminfo['ICEFLG']):
errors[0] += 1
return errors, ERRMSGS
def atemp(io_manager: SupportsReadTS, siminfo, uci, ts):
''' high level driver for air temperature module'''
ts['LAPSE'] = hoursval(siminfo, LAPSE, lapselike=True)
ui = make_numba_dict(
uci) # Note: all values coverted to float automatically
ui['k'] = siminfo['delt'] * 0.000833 # convert to in/timestep
ui['steps'] = siminfo['steps']
ui['errlen'] = len(ERRMSGS)
############################################################################
errors = _atemp_(ui, ts) # run ATEMP_ simulation code
############################################################################
return errors, ERRMSGS
def pstemp(io_manager, siminfo, uci, ts):
'''Estimate soil temperatures in a pervious land segment'''
simlen = siminfo['steps']
ui = make_numba_dict(uci)
ui['simlen'] = siminfo['steps']
ui['uunits'] = siminfo['units']
ui['delt'] = siminfo['delt']
ui['errlen'] = len(ERRMSG)
u = uci['PARAMETERS']
if 'SLTVFG' in u:
ts['ASLT'] = initm(siminfo, uci, u['SLTVFG'], 'MONTHLY_ASLT',
u['ASLT'])
ts['BSLT'] = initm(siminfo, uci, u['SLTVFG'], 'MONTHLY_BSLT',
u['BSLT'])
else:
ts['ASLT'] = full(simlen, u['ASLT'])
ts['BSLT'] = full(simlen, u['BSLT'])
if 'ULTVFG' in u:
ts['ULTP1'] = initm(siminfo, uci, u['ULTVFG'], 'MONTHLY_ULTP1',
u['ULTP1'])
ts['ULTP2'] = initm(siminfo, uci, u['ULTVFG'], 'MONTHLY_ULTP2',
u['ULTP2'])
else:
ts['ULTP1'] = full(simlen, u['ULTP1'])
ts['ULTP2'] = full(simlen, u['ULTP2'])
if 'LGTVFG' in u:
ts['LGTP1'] = initm(siminfo, uci, u['LGTVFG'], 'MONTHLY_LGTP1',
u['LGTP1'])
ts['LGTP2'] = initm(siminfo, uci, u['LGTVFG'], 'MONTHLY_LGTP2',
u['LGTP2'])
else:
ts['LGTP1'] = full(simlen, u['LGTP1'])
ts['LGTP2'] = full(simlen, u['LGTP2'])
ts['HRFG'] = hoursval(siminfo, ones(24), dofirst=True).astype(
float64) # numba Dict limitation
############################################################################
errors = _pstemp_(ui, ts) # run PSTEMP simulation code
############################################################################
return errors, ERRMSG
def htrch(io_manager, siminfo, uci, ts):
'''Simulate heat exchange and water temperature'''
advectData = uci['advectData']
(nexits, vol, VOL, SROVOL, EROVOL, SOVOL, EOVOL) = advectData
ts['VOL'] = VOL
ts['SROVOL'] = SROVOL
ts['EROVOL'] = EROVOL
for i in range(nexits):
ts['SOVOL' + str(i + 1)] = SOVOL[:, i]
ts['EOVOL' + str(i + 1)] = EOVOL[:, i]
simlen = siminfo['steps']
ts['DAYFG'] = hourflag(siminfo, 0, dofirst=True).astype(float64)
ui = make_numba_dict(uci)
nexits = int(ui['NEXITS'])
ui['simlen'] = siminfo['steps']
ui['uunits'] = siminfo['units']
ui['delt'] = siminfo['delt']
ui['delt60'] = siminfo['delt'] / 60
ui['errlen'] = len(ERRMSGS)
ui['vol'] = vol
bedflg = 0
if 'BEDFLG' in ui:
bedflg = ui['BEDFLG']
tgrnd = 59.0
if bedflg == 1 or bedflg == 2:
tgrnd = ui['TGRND']
tstop = 55
if 'TSTOP' in ui:
tstop = ui['TSTOP']
# even though delh and deltt are not ts, numba requires them to be passed as such
if 'DELH' in ui:
delh = ui['DELH']
else:
delh = zeros(int(tstop))
ts['DELH'] = delh
if 'DELTT' in ui:
deltt = ui['DELTT']
else:
deltt = zeros(int(tstop))
ts['DELTT'] = deltt
u = uci['PARAMETERS']
# process optional monthly arrays to return interpolated data or constant array
if 'TGFLG' in u:
ts['TGRND'] = initm(siminfo, uci, u['TGFLG'], 'TGRND', tgrnd)
else:
ts['TGRND'] = full(simlen, tgrnd)
ts['LAPSE'] = hoursval(siminfo, mlapse, lapselike=True)
############################################################################
errors = _htrch_(ui, ts) # run HTRCH simulation code
############################################################################
if nexits > 1:
u = uci['SAVE']
key = 'OHEAT'
for i in range(nexits):
u[f'{key}{i + 1}'] = u[key]
del u[key]
return errors, ERRMSGS
def snow(io_manager:SupportsReadTS, siminfo, uci, ts):
''' high level driver for SNOW module
CALL: snow(store, general, ui, ts)
store is the Pandas/PyTable open store
siminfo is a dictionary with simulation level infor (OP_SEQUENCE for example)
ui is a dictionary with segment specific HSPF UCI like data
ts is a dictionary with segment specific timeseries'''
steps = siminfo['steps'] # number of simulation timesteps
UUNITS = siminfo['units']
ts['SVP'] = SVP
ts['SEASONS'] = monthval(siminfo, SEASONS)
cloudfg = 'CLOUD' in ts
# insure defined, but can't be used accidently
for name in ['AIRTMP', 'CLOUD', 'DTMPG', 'PREC', 'SOLRAD', 'WINMOV']:
if name not in ts:
ts[name] = full(steps, nan)
# Replace fixed parameters in HSPF with time series
for name in ['CCFACT','COVIND','MGMELT','MWATER','SHADE','SNOEVP','SNOWCF','KMELT']:
if name not in ts and name in uci['PARAMETERS']:
ts[name] = full(steps, uci['PARAMETERS'][name])
# true the first time and at 6am and earlier every day of simulation
ts['HR6IND'] = hour6flag(siminfo, dofirst=True).astype(float)
# true the first time and at every hour of simulation
ts['HRFG'] = hoursval(siminfo, ones(24), dofirst=True).astype(float)
# make ICEFG available to PWATER later.
siminfo['ICEFG'] = 0
if 'FLAGS' in uci:
if 'ICEFG' in uci['FLAGS']:
siminfo['ICEFG'] = uci['FLAGS']['ICEFG']
ui = make_numba_dict(uci) # Note: all values coverted to float automatically
ui['steps'] = steps
ui['uunits'] = UUNITS
ui['delt'] = siminfo['delt']
ui['errlen'] = len(ERRMSGS)
ui['cloudfg'] = cloudfg
u = uci['PARAMETERS']
vkmfg = 0
if 'FLAGS' in uci:
uf = uci['FLAGS']
if 'VKMFG' in uf:
vkmfg = uf['VKMFG']
ts['KMELT'] = initm(siminfo, uci, vkmfg, 'MONTHLY_KMELT', u['KMELT'])
############################################################################
errors = _snow_(ui, ts)
############################################################################
if siminfo['delt'] > 360 and int(siminfo['ICEFLG']):
errors[0] += 1
return errors, ERRMSGS
def pwater(io_manager, siminfo, uci, ts):
''' PERLND WATER module
CALL: pwater(store, general, ui, ts)
store is the Pandas/PyTable open store
general is a dictionary with simulation level info (sim_start for example)
ui is a dictionary with PLS specific HSPF UCI like data
ts is a dictionary with PLS specific timeseries '''
steps = siminfo['steps'] # number of simulation points
#if RTOPFG == 3 and 'SURTAB' in ui:
# surtab = typeT(ui['SURTAB']) # FTable
# missing flows are treated as zeros
for name in ('AGWLI', 'IFWLI', 'LGTMP', 'LZLI', 'PETINP', 'PREC', 'SURLI',
'UZLI'):
if name not in ts:
ts[name] = zeros(steps)
# insure defined, but not usable accidently
for name in ('AIRTMP', 'PACKI', 'PETINP', 'PREC', 'RAINF', 'SNOCOV',
'WYIELD'):
if name not in ts:
ts[name] = full(steps, nan)
# Replace fixed parameters with time series if not already present
for name in ('AGWRC', 'DEEPFR', 'INFILT', 'KVARY', 'LZSN', 'PETMIN',
'PETMAX'):
if name not in ts and name in uci['PARAMETERS']:
ts[name] = full(steps, uci['PARAMETERS'][name])
# process optional monthly arrays to return interpolated data or constant array
u = uci['PARAMETERS']
if 'VLEFG' in u:
flag = (u['VLEFG'] == 1) or (u['VLEFG'] == 3)
ts['LZETP'] = initm(siminfo, uci, flag, 'MONTHLY_LZETP', u['LZETP'])
ts['CEPSC'] = initm(siminfo, uci, u['VCSFG'], 'MONTHLY_CEPSC',
u['CEPSC'])
ts['INTFW'] = initm(siminfo, uci, u['VIFWFG'], 'MONTHLY_INTFW',
u['INTFW'])
ts['IRC'] = initm(siminfo, uci, u['VIRCFG'], 'MONTHLY_IRC', u['IRC'])
ts['NSUR'] = initm(siminfo, uci, u['VNNFG'], 'MONTHLY_NSUR', u['NSUR'])
ts['UZSN'] = initm(siminfo, uci, u['VUZFG'], 'MONTHLY_UZSN', u['UZSN'])
else:
ts['LZETP'] = full(steps, u['LZETP'])
ts['CEPSC'] = full(steps, u['CEPSC'])
ts['INTFW'] = full(steps, u['INTFW'])
ts['IRC'] = full(steps, u['IRC'])
ts['NSUR'] = full(steps, u['NSUR'])
ts['UZSN'] = full(steps, u['UZSN'])
# true the first time and at start of every day of simulation
ts['DAYFG'] = hourflag(siminfo, 0, dofirst=True).astype(float)
# true the first time and at every hour of simulation
ts['HRFG'] = hoursval(siminfo, ones(24), dofirst=True).astype(float)
ui = make_numba_dict(
uci) # Note: all values coverted to float automatically
ui['steps'] = siminfo['steps']
ui['delt'] = siminfo['delt']
ui['errlen'] = len(ERRMSGS)
ui['uunits'] = siminfo['units']
# kludge to make ICEFG available from SNOW to PWATER
ui['ICEFG'] = siminfo['ICEFG'] if 'ICEFG' in siminfo else 0.0
CSNOFG = 0
if 'CSNOFG' in ui:
CSNOFG = int(ui['CSNOFG'])
# make CSNOFG available to other sections
u['CSNOFG'] = CSNOFG
############################################################################
errors = _pwater_(ui, ts) # traditional HSPF HPERWAT
############################################################################
return errors, ERRMSGS