def pwtgas(io_manager, siminfo, uci, ts):
''' Estimate water temperature, dissolved oxygen, and carbon dioxide in the outflows
from a pervious landsegment. calculate associated fluxes through exit gates'''
simlen = siminfo['steps']
ui = make_numba_dict(uci)
ui['simlen'] = siminfo['steps']
ui['uunits'] = siminfo['units']
ui['errlen'] = len(ERRMSG)
u = uci['PARAMETERS']
if 'IDVFG' in u:
ts['IDOXP'] = initm(siminfo, uci, u['IDVFG'], 'MONTHLY_IDOXP', u['IDOXP'])
else:
ts['IDOXP'] = full(simlen, u['IDOXP'])
if 'ICVFG' in u:
ts['ICO2P'] = initm(siminfo, uci, u['ICVFG'], 'MONTHLY_ICO2P', u['ICO2P'])
else:
ts['ICO2P'] = full(simlen, u['ICO2P'])
if 'GDVFG' in u:
ts['ADOXP'] = initm(siminfo, uci, u['GDVFG'], 'MONTHLY_ADOXP', u['ADOXP'])
else:
ts['ADOXP'] = full(simlen, u['ADOXP'])
if 'GCVFG' in u:
ts['ACO2P'] = initm(siminfo, uci, u['GCVFG'], 'MONTHLY_ACO2P', u['ACO2P'])
else:
ts['ACO2P'] = full(simlen, u['ACO2P'])
ts['DAYFG'] = hourflag(siminfo, 0, dofirst=True).astype(float64)
############################################################################
errors = _pwtgas_(ui, ts) # run PWTGAS simulation code
############################################################################
return errors, ERRMSG
def iwtgas(io_manager, siminfo, uci, ts): ''' Estimate water temperature, dissolved oxygen, and carbon dioxide in the outflows from a impervious land segment. calculate associated fluxes through exit gate''' simlen = siminfo['steps'] ui = make_numba_dict(uci) ui['simlen'] = siminfo['steps'] ui['uunits'] = siminfo['units'] ui['errlen'] = len(ERRMSG) u = uci['PARAMETERS'] if 'WTFVFG' in u: ts['AWTF'] = initm(siminfo, uci, u['WTFVFG'], 'MONTHLY_AWTF', u['AWTF']) ts['BWTF'] = initm(siminfo, uci, u['WTFVFG'], 'MONTHLY_BWTF', u['BWTF']) else: ts['AWTF'] = full(simlen, u['AWTF']) ts['BWTF'] = full(simlen, u['BWTF']) for name in ['AIRTMP', 'WYIELD', 'SURO', 'SURLI']: if name not in ts: ts[name] = zeros(simlen) ts['DAYFG'] = hourflag(siminfo, 0, dofirst=True).astype(float64) ############################################################################ errors = _iwtgas_(ui, ts) # run IWTGAS simulation code ############################################################################ return errors, ERRMSG
def sedmnt(io_manager, siminfo, uci, ts): ''' Produce and remove sediment from the land surface''' simlen = siminfo['steps'] ui = make_numba_dict(uci) # Note: all values converted to float automatically ui['simlen'] = siminfo['steps'] ui['uunits'] = siminfo['units'] ui['delt'] = siminfo['delt'] ui['errlen'] = len(ERRMSG) u = uci['PARAMETERS'] if 'CRVFG' in u: ts['COVERI'] = initm(siminfo, uci, u['CRVFG'], 'MONTHLY_COVER', u['COVER']) else: ts['COVERI'] = full(simlen, u['COVER']) if 'VSIVFG' in u: ts['NVSI'] = initm(siminfo, uci, u['VSIVFG'], 'MONTHLY_NVSI', u['NVSI']) else: ts['NVSI'] = full(simlen, u['NVSI']) ts['DAYFG'] = hourflag(siminfo, 0, dofirst=True).astype(float64) ############################################################################ errors = _sedmnt_(ui, ts) # run SEDMNT simulation code ############################################################################ return errors, ERRMSG
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 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 solids(io_manager, siminfo, uci, ts):
'''Accumulate and remove solids from the impervious land segment'''
simlen = siminfo['steps']
for name in ['SURO', 'SURS', 'PREC', 'SLSLD']:
if name not in ts:
ts[name] = zeros(simlen)
u = uci['PARAMETERS']
# process optional monthly arrays to return interpolated data or constant array
if 'VASDFG' in u:
ts['ACCSDP'] = initm(siminfo, uci, u['VASDFG'], 'MONTHLY_ACCSDP',
u['ACCSDP'])
else:
ts['ACCSDP'] = full(simlen, u['ACCSDP'])
if 'VRSDFG' in u:
ts['REMSDP'] = initm(siminfo, uci, u['VRSDFG'], 'MONTHLY_REMSDP',
u['REMSDP'])
else:
ts['REMSDP'] = full(simlen, u['REMSDP'])
ui = make_numba_dict(
uci) # Note: all values converted to float automatically
ui['uunits'] = siminfo['units']
ui['simlen'] = siminfo['steps']
ui['delt60'] = siminfo[
'delt'] / 60 # delt60 - simulation time interval in hours
ui['errlen'] = len(ERRMSG)
ts['DAYFG'] = hourflag(siminfo, 0, dofirst=True).astype(float64)
############################################################################
errors = _solids_(ui, ts) # run SOLIDS 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 iqual(io_manager, siminfo, uci, ts): ''' Simulate washoff of quality constituents (other than solids, Heat, dox, and co2) using simple relationships with solids And/or water yield''' simlen = siminfo['steps'] nquals = 1 if 'PARAMETERS' in uci: if 'NQUAL' in uci['PARAMETERS']: nquals = uci['PARAMETERS']['NQUAL'] constituents = [] for index in range(nquals): iqual = str(index + 1) flags = uci['IQUAL' + iqual + '_FLAGS'] constituents.append(flags['QUALID']) ui = make_numba_dict(uci) ui['simlen'] = siminfo['steps'] ui['delt60'] = siminfo['delt'] / 60 # delt60 - simulation time interval in hours ui['nquals'] = nquals ui['errlen'] = len(ERRMSGS) # constituents = ui['CONSTITUENTS'] # (short) names of constituents if 'FLAGS' in uci: u = uci['FLAGS'] index = 0 for constituent in constituents: # simulate constituent index += 1 # update UI values for this constituent here! ui_flags = uci['IQUAL' + str(index) + '_FLAGS'] ui_parms = uci['IQUAL' + str(index) + '_PARAMETERS'] qualid = ui_flags['QUALID'] qtyid = ui_flags['QTYID'] QSDFG = ui_flags['QSDFG'] QSOFG = ui_flags['QSOFG'] VQOFG = ui_flags['VQOFG'] sqo = ui_parms['SQO'] wsqop = ui_parms['WSQOP'] ui['QSDFG' + str(index)] = QSDFG ui['QSOFG' + str(index)] = QSOFG ui['VQOFG' + str(index)] = VQOFG ui['sqo' + str(index)] = sqo ui['wsqop' + str(index)] = wsqop # handle monthly tables ts['POTFW' + str(index)] = initm(siminfo, uci, ui_flags['VPFWFG'], 'IQUAL' + str(index) + '_MONTHLY/POTFW', ui_parms['POTFW']) ts['ACQOP' + str(index)] = initm(siminfo, uci, ui_flags['VQOFG'], 'IQUAL' + str(index) + '_MONTHLY/ACQOP', ui_parms['ACQOP']) ts['SQOLIM' + str(index)] = initm(siminfo, uci, ui_flags['VQOFG'], 'IQUAL' + str(index) + '_MONTHLY/SQOLIM', ui_parms['SQOLIM']) iqadfgf = 0 iqadfgc = 0 ts['IQADFX' + str(index)] = zeros(simlen) ts['IQADCN' + str(index)] = zeros(simlen) if 'FLAGS' in uci: # get atmos dep timeseries iqadfgf = u['IQADFG' + str((index * 2) - 1)] if iqadfgf > 0: ts['IQADFX' + str(index)] = initm(siminfo, uci, iqadfgf, 'IQUAL' + str(index) + '_MONTHLY/IQADFX', 0.0) elif iqadfgf == -1: ts['IQADFX' + str(index)] = ts['IQADFX' + str(index) + ' 1'] iqadfgc = u['IQADFG' + str(index * 2)] if iqadfgc > 0: ts['IQADCN' + str(index)] = initm(siminfo, uci, iqadfgc, 'IQUAL' + str(index) + '_MONTHLY/IQADCN', 0.0) elif iqadfgc == -1: ts['IQADCN' + str(index)] = ts['IQADCN' + str(index) + ' 1'] ui['iqadfgf' + str(index)] = iqadfgf ui['iqadfgc' + str(index)] = iqadfgc for name in ['SLIQSX', 'SLIQO', 'SLIQSP']: if name not in ts: ts[name] = full(simlen, -1.0E30) ts['DAYFG'] = hourflag(siminfo, 0, dofirst=True).astype(float64) ############################################################################ errors = _iqual_(ui, ts) # run IQUAL simulation code ############################################################################ 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
def pqual(io_manager, siminfo, uci, ts): ''' Simulate quality constituents (other than sediment, heat, dox, and co2) using simple relationships with sediment and water yield''' simlen = siminfo['steps'] nquals = 1 if 'PARAMETERS' in uci: if 'NQUAL' in uci['PARAMETERS']: nquals = uci['PARAMETERS']['NQUAL'] constituents = [] for index in range(nquals): pqual = str(index + 1) flags = uci['PQUAL' + pqual + '_FLAGS'] constituents.append(flags['QUALID']) ui = make_numba_dict(uci) ui['simlen'] = siminfo['steps'] ui['delt60'] = siminfo['delt'] / 60 # delt60 - simulation time interval in hours ui['nquals'] = nquals ui['errlen'] = len(ERRMSGS) # constituents = ui['CONSTITUENTS'] # (short) names of constituents if 'FLAGS' in uci: u = uci['FLAGS'] index = 0 for constituent in constituents: # simulate constituent index += 1 # update UI values for this constituent here! ui_flags = uci['PQUAL' + str(index) + '_FLAGS'] ui_parms = uci['PQUAL' + str(index) + '_PARAMETERS'] qualid = ui_flags['QUALID'] qtyid = ui_flags['QTYID'] QSDFG = ui_flags['QSDFG'] QSOFG = ui_flags['QSOFG'] QIFWFG = ui_flags['QIFWFG'] QAGWFG = ui_flags['QAGWFG'] sqo = ui_parms['SQO'] wsqop = ui_parms['WSQOP'] ui['QSDFG' + str(index)] = QSDFG ui['QSOFG' + str(index)] = QSOFG ui['QIFWFG' + str(index)] = QIFWFG ui['QAGWFG' + str(index)] = QAGWFG ui['SQO' + str(index)] = sqo ui['WSQOP' + str(index)] = wsqop ui['VIQCFG' + str(index)] = ui_flags['VIQCFG'] ui['VAQCFG' + str(index)] = ui_flags['VAQCFG'] ts['POTFW' + str(index)] = initm(siminfo, uci, ui_flags['VPFWFG'], 'PQUAL' + str(index) + '_MONTHLY/POTFW', ui_parms['POTFW']) ts['POTFS' + str(index)] = initm(siminfo, uci, ui_flags['VPFSFG'], 'PQUAL' + str(index) + '_MONTHLY/POTFS', ui_parms['POTFS']) ts['ACQOP' + str(index)] = initm(siminfo, uci, ui_flags['VQOFG'], 'PQUAL' + str(index) + '_MONTHLY/ACQOP', ui_parms['ACQOP']) ts['SQOLIM' + str(index)] = initm(siminfo, uci, ui_flags['VQOFG'], 'PQUAL' + str(index) + '_MONTHLY/SQOLIM', ui_parms['SQOLIM']) ts['IOQCP' + str(index)] = initm(siminfo, uci, ui_flags['VIQCFG'], 'PQUAL' + str(index) + '_MONTHLY/IOQC', ui_parms['IOQC']) ts['AOQCP' + str(index)] = initm(siminfo, uci, ui_flags['VAQCFG'], 'PQUAL' + str(index) + '_MONTHLY/AOQC', ui_parms['AOQC']) pqadfgf = 0 pqadfgc = 0 ts['PQADFX' + str(index)] = zeros(simlen) ts['PQADCN' + str(index)] = zeros(simlen) if 'FLAGS' in uci: # get atmos dep timeseries pqadfgf = u['PQADFG' + str((index * 2) - 1)] if pqadfgf > 0: ts['PQADFX' + str(index)] = initm(siminfo, uci, pqadfgf, 'PQUAL' + str(index) + '_MONTHLY/PQADFX', 0.0) elif pqadfgf == -1: ts['PQADFX' + str(index)] = ts['PQADFX' + str(index) + ' 1'] pqadfgc = u['PQADFG' + str(index * 2)] if pqadfgc > 0: ts['PQADCN' + str(index)] = initm(siminfo, uci, pqadfgc, 'PQUAL' + str(index) + '_MONTHLY/PQADCN', 0.0) elif pqadfgc == -1: ts['PQADCN' + str(index)] = ts['PQADCN' + str(index) + ' 1'] ui['pqadfgf' + str(index)] = pqadfgf ui['pqadfgc' + str(index)] = pqadfgc for name in ['SLIQSP', 'ILIQC', 'ALIQC']: if name not in ts: ts[name] = zeros(simlen) ts['DAYFG'] = hourflag(siminfo, 0, dofirst=True).astype(float64) for name in ['SURO', 'IFWO', 'AGWO', 'PERO', 'WSSD', 'SCRSD']: if name not in ts: ts[name] = zeros(simlen) ############################################################################ errors = _pqual_(ui, ts) # run PQUAL simulation code ############################################################################ return errors, ERRMSGS