def set_river_package(self, discharge):
logger.info("Set the river package.")
# specify the river package
#
# - surface water river bed/bottom elevation
#
# - for lakes and resevoirs, make the bottom elevation deep --- Shall we do this?
#~ additional_depth = 500.
#~ surface_water_bed_elevation = pcr.ifthen(pcr.scalar(self.WaterBodies.waterBodyIds) > 0.0, \
#~ self.dem_riverbed - additional_depth)
#~ surface_water_bed_elevation = pcr.cover(surface_water_bed_elevation, self.dem_riverbed)
#
surface_water_bed_elevation = self.dem_riverbed # This is an alternative, if we do not want to introduce very deep bottom elevations of lakes and/or reservoirs.
#
# rounding values for surface_water_bed_elevation
self.surface_water_bed_elevation = pcr.roundup(
surface_water_bed_elevation * 1000.) / 1000.
#
# - river bed condutance (unit: m2/day)
bed_surface_area = pcr.ifthen(pcr.scalar(self.WaterBodies.waterBodyIds) > 0.0, \
self.WaterBodies.fracWat * self.cellAreaMap) # TODO: Incorporate the concept of dynamicFracWat
bed_surface_area = pcr.cover(bed_surface_area, \
self.bankfull_width * self.channelLength)
bed_surface_area = self.bankfull_width * self.channelLength
bed_conductance = (1.0 / self.bed_resistance) * bed_surface_area
bed_conductance = pcr.ifthenelse(bed_conductance < 1e-20, 0.0, \
bed_conductance)
self.bed_conductance = pcr.cover(bed_conductance, 0.0)
#
# - 'channel width' for lakes and reservoirs
channel_width = pcr.areamaximum(self.bankfull_width,
self.WaterBodies.waterBodyIds)
channel_width = pcr.cover(channel_width, self.bankfull_width)
#
# - convert discharge value to surface water elevation (m)
river_water_height = (channel_width**(-3 / 5)) * (discharge**(
3 / 5)) * ((self.gradient)**(-3 / 10)) * (self.manningsN**(3 / 5))
surface_water_elevation = self.dem_riverbed + \
river_water_height
#
# - calculating water level (unit: m) above the flood plain # TODO: Improve this concept (using Rens's latest innundation scheme)
#----------------------------------------------------------
water_above_fpl = pcr.max(
0.0, surface_water_elevation - self.dem_floodplain
) # unit: m, water level above the floodplain (not distributed)
water_above_fpl *= self.bankfull_depth * self.bankfull_width / self.cellAreaMap # unit: m, water level above the floodplain (distributed within the cell)
# TODO: Improve this concept using Rens's latest scheme
#
# - corrected surface water elevation
surface_water_elevation = pcr.ifthenelse(surface_water_elevation > self.dem_floodplain, \
self.dem_floodplain + water_above_fpl, \
surface_water_elevation)
# - surface water elevation for lakes and reservoirs:
lake_reservoir_water_elevation = pcr.ifthen(
self.WaterBodies.waterBodyOut, surface_water_elevation)
lake_reservoir_water_elevation = pcr.areamaximum(
lake_reservoir_water_elevation, self.WaterBodies.waterBodyIds)
lake_reservoir_water_elevation = pcr.cover(lake_reservoir_water_elevation, \
pcr.areaaverage(surface_water_elevation, self.WaterBodies.waterBodyIds))
# - maximum and minimum values for lake_reservoir_water_elevation
lake_reservoir_water_elevation = pcr.min(
self.dem_floodplain, lake_reservoir_water_elevation)
lake_reservoir_water_elevation = pcr.max(
surface_water_bed_elevation, lake_reservoir_water_elevation)
# - smoothing
lake_reservoir_water_elevation = pcr.areaaverage(
surface_water_elevation, self.WaterBodies.waterBodyIds)
#
# - merge lake and reservoir water elevation
surface_water_elevation = pcr.cover(lake_reservoir_water_elevation,
surface_water_elevation)
#
# - pass values to the river package
surface_water_elevation = pcr.cover(surface_water_elevation,
self.surface_water_bed_elevation)
surface_water_elevation = pcr.rounddown(
surface_water_elevation * 1000.) / 1000.
#
# - make sure that HRIV >= RBOT ; no infiltration if HRIV = RBOT (and h < RBOT)
self.surface_water_elevation = pcr.max(
surface_water_elevation, self.surface_water_bed_elevation)
#
# - pass the values to the RIV package
self.pcr_modflow.setRiver(self.surface_water_elevation, \
self.surface_water_bed_elevation, self.bed_conductance, 2)
def set_river_package(self, discharge, currTimeStep):
logger.info("Set the river package.")
# - surface water river bed/bottom elevation and conductance
need_to_define_surface_water_bed = False
if currTimeStep == None:
# this is for a steady state simulation (no currTimeStep define)
need_to_define_surface_water_bed = True
else:
# only at the first month of the model simulation or the first month of the year
if self.firstMonthOfSimulation or currTimeStep.month == 1:
need_to_define_surface_water_bed = True
self.firstMonthOfSimulation = False # This part becomes False as we don't need it anymore.
if need_to_define_surface_water_bed:
logger.info("Estimating the surface water bed elevation and surface water bed conductance.")
#~ # - for lakes and resevoirs, alternative 1: make the bottom elevation deep --- Shall we do this?
#~ additional_depth = 500.
#~ surface_water_bed_elevation = pcr.ifthen(pcr.scalar(self.WaterBodies.waterBodyIds) > 0.0, \
#~ self.dem_riverbed - additional_depth)
#
# - for lakes and resevoirs, estimate bed elevation from dem and bankfull depth
surface_water_bed_elevation = pcr.ifthen(pcr.scalar(self.WaterBodies.waterBodyIds) > 0.0, self.dem_average)
surface_water_bed_elevation = pcr.areaaverage(surface_water_bed_elevation, self.WaterBodies.waterBodyIds)
surface_water_bed_elevation -= pcr.areamaximum(self.bankfull_depth, self.WaterBodies.waterBodyIds)
#
surface_water_bed_elevation = pcr.cover(surface_water_bed_elevation, self.dem_riverbed)
#~ surface_water_bed_elevation = self.dem_riverbed # This is an alternative, if we do not want to introduce very deep bottom elevations of lakes and/or reservoirs.
#
# rounding values for surface_water_bed_elevation
self.surface_water_bed_elevation = pcr.roundup(surface_water_bed_elevation * 1000.)/1000.
#
# - river bed condutance (unit: m2/day)
bed_surface_area = pcr.ifthen(pcr.scalar(self.WaterBodies.waterBodyIds) > 0.0, \
self.WaterBodies.fracWat * self.cellAreaMap) # TODO: Incorporate the concept of dynamicFracWat # I have problem with the convergence if I use this one.
bed_surface_area = pcr.min(bed_surface_area,\
pcr.ifthen(pcr.scalar(self.WaterBodies.waterBodyIds) > 0.0, \
pcr.areaaverage(self.bankfull_width * self.channelLength, self.WaterBodies.waterBodyIds)))
bed_surface_area = pcr.cover(bed_surface_area, \
self.bankfull_width * self.channelLength)
#~ bed_surface_area = self.bankfull_width * self.channelLength
bed_conductance = (1.0/self.bed_resistance) * bed_surface_area
bed_conductance = pcr.ifthenelse(bed_conductance < 1e-20, 0.0, \
bed_conductance)
self.bed_conductance = pcr.cover(bed_conductance, 0.0)
logger.info("Estimating outlet widths of lakes and/or reservoirs.")
# - 'channel width' for lakes and reservoirs
channel_width = pcr.areamaximum(self.bankfull_width, self.WaterBodies.waterBodyIds)
self.channel_width = pcr.cover(channel_width, self.bankfull_width)
logger.info("Estimating surface water elevation.")
# - convert discharge value to surface water elevation (m)
river_water_height = (self.channel_width**(-3/5)) * (discharge**(3/5)) * ((self.gradient)**(-3/10)) *(self.manningsN**(3/5))
surface_water_elevation = self.dem_riverbed + \
river_water_height
#
# - calculating water level (unit: m) above the flood plain # TODO: Improve this concept (using Rens's latest innundation scheme)
#----------------------------------------------------------
water_above_fpl = pcr.max(0.0, surface_water_elevation - self.dem_floodplain) # unit: m, water level above the floodplain (not distributed)
water_above_fpl *= self.bankfull_depth * self.bankfull_width / self.cellAreaMap # unit: m, water level above the floodplain (distributed within the cell)
# TODO: Improve this concept using Rens's latest scheme
#
# - corrected surface water elevation
surface_water_elevation = pcr.ifthenelse(surface_water_elevation > self.dem_floodplain, \
self.dem_floodplain + water_above_fpl, \
surface_water_elevation)
# - surface water elevation for lakes and reservoirs:
lake_reservoir_water_elevation = pcr.ifthen(self.WaterBodies.waterBodyOut, surface_water_elevation)
lake_reservoir_water_elevation = pcr.areamaximum(lake_reservoir_water_elevation, self.WaterBodies.waterBodyIds)
lake_reservoir_water_elevation = pcr.cover(lake_reservoir_water_elevation, \
pcr.areaaverage(surface_water_elevation, self.WaterBodies.waterBodyIds))
# - maximum and minimum values for lake_reservoir_water_elevation
lake_reservoir_water_elevation = pcr.min(self.dem_floodplain, lake_reservoir_water_elevation)
lake_reservoir_water_elevation = pcr.max(self.surface_water_bed_elevation, lake_reservoir_water_elevation)
# - smoothing
lake_reservoir_water_elevation = pcr.areaaverage(surface_water_elevation, self.WaterBodies.waterBodyIds)
#
# - merge lake and reservoir water elevation
surface_water_elevation = pcr.cover(lake_reservoir_water_elevation, surface_water_elevation)
#
# - covering the missing values and rounding
surface_water_elevation = pcr.cover(surface_water_elevation, self.surface_water_bed_elevation)
surface_water_elevation = pcr.rounddown(surface_water_elevation * 1000.)/1000.
#
# - make sure that HRIV >= RBOT ; no infiltration if HRIV = RBOT (and h < RBOT)
self.surface_water_elevation = pcr.max(surface_water_elevation, self.surface_water_bed_elevation)
#
# - pass the values to the RIV package
self.pcr_modflow.setRiver(self.surface_water_elevation, self.surface_water_bed_elevation, self.bed_conductance, 1)
def __init__(self, iniItems,landmask,spinUp):
object.__init__(self)
self.cloneMap = iniItems.cloneMap
self.tmpDir = iniItems.tmpDir
self.inputDir = iniItems.globalOptions['inputDir']
self.landmask = landmask
# option to activate water balance check
self.debugWaterBalance = True
if iniItems.routingOptions['debugWaterBalance'] == "False":
self.debugWaterBalance = False
if iniItems.groundwaterOptions['groundwaterPropertiesNC'] == str(None):
# assign the recession coefficient parameter(s)
self.recessionCoeff = vos.readPCRmapClone(\
iniItems.groundwaterOptions['recessionCoeff'],
self.cloneMap,self.tmpDir,self.inputDir)
else:
groundwaterPropertiesNC = vos.getFullPath(\
iniItems.groundwaterOptions[\
'groundwaterPropertiesNC'],
self.inputDir)
self.recessionCoeff = vos.netcdf2PCRobjCloneWithoutTime(\
groundwaterPropertiesNC,'recessionCoeff',\
cloneMapFileName = self.cloneMap)
# groundwater recession coefficient (day-1_
self.recessionCoeff = pcr.cover(self.recessionCoeff,0.00)
self.recessionCoeff = pcr.min(1.0000,self.recessionCoeff)
#
if 'minRecessionCoeff' in iniItems.groundwaterOptions.keys():
minRecessionCoeff = float(iniItems.groundwaterOptions['minRecessionCoeff'])
else:
minRecessionCoeff = 1.0e-4 # This is the minimum value used in Van Beek et al. (2011).
self.recessionCoeff = pcr.max(minRecessionCoeff,self.recessionCoeff)
if iniItems.groundwaterOptions['groundwaterPropertiesNC'] == str(None):
# assign aquifer specific yield
self.specificYield = vos.readPCRmapClone(\
iniItems.groundwaterOptions['specificYield'],
self.cloneMap,self.tmpDir,self.inputDir)
else:
self.specificYield = vos.netcdf2PCRobjCloneWithoutTime(\
groundwaterPropertiesNC,'specificYield',\
cloneMapFileName = self.cloneMap)
self.specificYield = pcr.cover(self.specificYield,0.0)
self.specificYield = pcr.max(0.010,self.specificYield) # TODO: TO BE CHECKED: The resample process of specificYield
self.specificYield = pcr.min(1.000,self.specificYield)
if iniItems.groundwaterOptions['groundwaterPropertiesNC'] == str(None):
# assign aquifer saturated conductivity
self.kSatAquifer = vos.readPCRmapClone(\
iniItems.groundwaterOptions['kSatAquifer'],
self.cloneMap,self.tmpDir,self.inputDir)
else:
self.kSatAquifer = vos.netcdf2PCRobjCloneWithoutTime(\
groundwaterPropertiesNC,'kSatAquifer',\
cloneMapFileName = self.cloneMap)
self.kSatAquifer = pcr.cover(self.kSatAquifer,0.0)
self.kSatAquifer = pcr.max(0.010,self.kSatAquifer)
# limitAbstraction options
self.limitAbstraction = False
if iniItems.landSurfaceOptions['limitAbstraction'] == "True": self.limitAbstraction = True
# option for limitting fossil groundwater abstractions - This option is only defined for IWMI project
self.limitFossilGroundwaterAbstraction = False
if self.limitAbstraction == False and\
"extraOptionsforProjectWithIWMI" in iniItems.allSections and\
iniItems.extraOptionsforProjectWithIWMI['limitFossilGroundWaterAbstraction'] == "True":
logger.info('Fossil groundwater abstraction limit is used (IWMI project).')
self.limitFossilGroundwaterAbstraction = True
# estimate of thickness (unit: mm) of aceesible groundwater: shallow and deep
totalGroundwaterThickness = vos.readPCRmapClone(\
iniItems.extraOptionsforProjectWithIWMI['estimateOfTotalGroundwaterThickness'],
self.cloneMap,self.tmpDir,self.inputDir)
totalGroundwaterThickness = pcr.cover(totalGroundwaterThickness,
pcr.windowaverage(totalGroundwaterThickness, 1.0))
totalGroundwaterThickness = pcr.cover(totalGroundwaterThickness,
pcr.windowaverage(totalGroundwaterThickness, 1.5))
totalGroundwaterThickness = pcr.cover(totalGroundwaterThickness,
pcr.windowaverage(totalGroundwaterThickness, 2.5))
totalGroundwaterThickness = pcr.cover(totalGroundwaterThickness,
pcr.windowaverage(totalGroundwaterThickness, 5.0))
totalGroundwaterThickness = pcr.cover(totalGroundwaterThickness,
pcr.windowaverage(totalGroundwaterThickness, 7.5))
totalGroundwaterThickness = pcr.cover(totalGroundwaterThickness,
pcr.mapmaximum(totalGroundwaterThickness))
# set minimum thickness to 50 m:
totalGroundwaterThickness = pcr.max(50.0, totalGroundwaterThickness)
# estimate of capacity (unit: m) of renewable groundwater (shallow)
storGroundwaterCap = pcr.cover(
vos.readPCRmapClone(\
iniItems.extraOptionsforProjectWithIWMI['estimateOfRenewableGroundwaterCapacity'],
self.cloneMap,self.tmpDir,self.inputDir),\
0.0)
# fossil groundwater capacity (unit: m)
self.fossilWaterCap = pcr.max(0.0,\
totalGroundwaterThickness*self.specificYield - storGroundwaterCap)
# option for limitting regional groundwater abstractions - This option is only defined
self.limitRegionalAnnualGroundwaterAbstraction = False
if "extraOptionsforProjectWithIWMI" in iniItems.allSections and\
iniItems.extraOptionsforProjectWithIWMI['limitRegionalAnnualGroundwaterAbstraction'] == "True":
logger.info('Limit for regional groundwater abstraction is used (IWMI project).')
self.limitRegionalAnnualGroundwaterAbstraction = True
region_ids = vos.readPCRmapClone(\
iniItems.extraOptionsforProjectWithIWMI['regionIds'],
self.cloneMap,self.tmpDir,self.inputDir)
self.region_ids = pcr.nominal(region_ids)
self.region_ids = pcr.ifthen(self.landmask, self.region_ids)
self.regionalAnnualGroundwaterAbstractionLimit = vos.readPCRmapClone(\
iniItems.extraOptionsforProjectWithIWMI['pumpingCapacity'],
self.cloneMap,self.tmpDir,self.inputDir)
self.regionalAnnualGroundwaterAbstractionLimit = pcr.roundup(self.regionalAnnualGroundwaterAbstractionLimit*1000.)/1000.
self.regionalAnnualGroundwaterAbstractionLimit = pcr.cover(self.regionalAnnualGroundwaterAbstractionLimit, 0.0)
self.regionalAnnualGroundwaterAbstractionLimit *= 1000. * 1000. * 1000. # unit: m3/year
self.regionalAnnualGroundwaterAbstractionLimit = pcr.ifthen(self.landmask,\
self.regionalAnnualGroundwaterAbstractionLimit)
# zones at which water allocation (surface and groundwater allocation) is determined
self.usingAllocSegments = False
if iniItems.landSurfaceOptions['allocationSegmentsForGroundSurfaceWater'] != "None": self.usingAllocSegments = True
# incorporating groundwater distribution network:
if self.usingAllocSegments and self.limitAbstraction == False:
self.allocSegments = vos.readPCRmapClone(\
iniItems.landSurfaceOptions['allocationSegmentsForGroundSurfaceWater'],
self.cloneMap,self.tmpDir,self.inputDir,isLddMap=False,cover=None,isNomMap=True)
self.allocSegments = pcr.ifthen(self.landmask, self.allocSegments)
cellArea = vos.readPCRmapClone(\
iniItems.routingOptions['cellAreaMap'],
self.cloneMap,self.tmpDir,self.inputDir)
cellArea = pcr.ifthen(self.landmask, cellArea) # TODO: integrate this one with the one coming from the routing module
self.segmentArea = pcr.areatotal(pcr.cover(cellArea, 0.0), self.allocSegments)
self.segmentArea = pcr.ifthen(self.landmask, self.segmentArea)
self.report = True
try:
self.outDailyTotNC = iniItems.groundwaterOptions['outDailyTotNC'].split(",")
self.outMonthTotNC = iniItems.groundwaterOptions['outMonthTotNC'].split(",")
self.outMonthAvgNC = iniItems.groundwaterOptions['outMonthAvgNC'].split(",")
self.outMonthEndNC = iniItems.groundwaterOptions['outMonthEndNC'].split(",")
self.outAnnuaTotNC = iniItems.groundwaterOptions['outAnnuaTotNC'].split(",")
self.outAnnuaAvgNC = iniItems.groundwaterOptions['outAnnuaAvgNC'].split(",")
self.outAnnuaEndNC = iniItems.groundwaterOptions['outAnnuaEndNC'].split(",")
except:
self.report = False
if self.report == True:
self.outNCDir = iniItems.outNCDir
self.netcdfObj = PCR2netCDF(iniItems)
#
# daily output in netCDF files:
if self.outDailyTotNC[0] != "None":
for var in self.outDailyTotNC:
# creating the netCDF files:
self.netcdfObj.createNetCDF(str(self.outNCDir)+"/"+ \
str(var)+"_dailyTot.nc",\
var,"undefined")
# MONTHly output in netCDF files:
# - cummulative
if self.outMonthTotNC[0] != "None":
for var in self.outMonthTotNC:
# initiating monthlyVarTot (accumulator variable):
vars(self)[var+'MonthTot'] = None
# creating the netCDF files:
self.netcdfObj.createNetCDF(str(self.outNCDir)+"/"+ \
str(var)+"_monthTot.nc",\
var,"undefined")
# - average
if self.outMonthAvgNC[0] != "None":
for var in self.outMonthAvgNC:
# initiating monthlyTotAvg (accumulator variable)
vars(self)[var+'MonthTot'] = None
# initiating monthlyVarAvg:
vars(self)[var+'MonthAvg'] = None
# creating the netCDF files:
self.netcdfObj.createNetCDF(str(self.outNCDir)+"/"+ \
str(var)+"_monthAvg.nc",\
var,"undefined")
# - last day of the month
if self.outMonthEndNC[0] != "None":
for var in self.outMonthEndNC:
# creating the netCDF files:
self.netcdfObj.createNetCDF(str(self.outNCDir)+"/"+ \
str(var)+"_monthEnd.nc",\
var,"undefined")
# YEARly output in netCDF files:
# - cummulative
if self.outAnnuaTotNC[0] != "None":
for var in self.outAnnuaTotNC:
# initiating yearly accumulator variable:
vars(self)[var+'AnnuaTot'] = None
# creating the netCDF files:
self.netcdfObj.createNetCDF(str(self.outNCDir)+"/"+ \
str(var)+"_annuaTot.nc",\
var,"undefined")
# - average
if self.outAnnuaAvgNC[0] != "None":
for var in self.outAnnuaAvgNC:
# initiating annualyVarAvg:
vars(self)[var+'AnnuaAvg'] = None
# initiating annualyTotAvg (accumulator variable)
vars(self)[var+'AnnuaTot'] = None
# creating the netCDF files:
self.netcdfObj.createNetCDF(str(self.outNCDir)+"/"+ \
str(var)+"_annuaAvg.nc",\
var,"undefined")
# - last day of the year
if self.outAnnuaEndNC[0] != "None":
for var in self.outAnnuaEndNC:
# creating the netCDF files:
self.netcdfObj.createNetCDF(str(self.outNCDir)+"/"+ \
str(var)+"_annuaEnd.nc",\
var,"undefined")
#get initial conditions
self.getICs(iniItems,spinUp)
cellArea = pcr.ifthen(landmask,cellArea)
for iYear in range(staYear,endYear+1):
# time stamp
timeStamp = datetime.datetime(int(iYear),int(1),int(1),int(0))
fulldate = '%4i-%02i-%02i' %(int(iYear),int(1),int(1))
print fulldate
# index for time object in the netcdf file:
index = index + 1
# reading values from the input netcdf files (30min)
abstraction_volume_30min = pcr.roundup(
vos.netcdf2PCRobjClone(inputDirectory+inputFiles,\
inputVarNames,
fulldate,
None,
cloneMapFileName)) * 0.001 # unit: bcm/year
abstraction = pcr.cover(abstraction_volume_30min, 0.0)
# use window maximum to be in the conservative side:
window_size = 1.0
abstraction = pcr.windowmaximum(abstraction, 1.0)
# covering the map with zero
pcrValue = pcr.cover(abstraction, 0.0) # unit: m/day
# the value should be higher than the previous year value
if iYear > staYear: pcrValue = pcr.max(preValue, pcrValue)
preValue = pcrValue