def initial(self):
#####################
# * initial section #
#####################
#-constants
# betaQ [-]: constant of kinematic wave momentum equation
self.betaQ = 0.6
#-channel LDD
self.channelLDD= pcr.ifthenelse(self.waterBodies.distribution != 0,\
pcr.ldd(5),self.LDD)
#-channel area and storage
self.channelArea = self.channelWidth * self.channelLength
self.channelStorageCapacity= pcr.ifthenelse(self.waterBodies.distribution == 0,\
self.channelArea*self.channelDepth,pcr.scalar(0.))
#-basin outlets
self.basinOutlet = pcr.pit(self.LDD) != 0
#-read initial conditions
self.Q = clippedRead.get(self.QIniMap)
self.actualStorage = clippedRead.get(self.actualStorageIniMap)
self.actualStorage= pcr.ifthenelse(self.waterBodies.distribution != 0,\
pcr.ifthenelse(self.waterBodies.location != 0,\
pcr.areatotal(self.actualStorage,self.waterBodies.distribution),0),\
self.actualStorage)
self.waterBodies.actualStorage = self.waterBodies.retrieveMapValue(
self.actualStorage)
#-update targets of average and bankful discharge
self.waterBodies.averageQ = self.waterBodies.retrieveMapValue(
self.averageQ)
self.waterBodies.bankfulQ = self.waterBodies.retrieveMapValue(
self.bankfulQ)
#-return the parameters for the kinematic wave,
# including alpha, wetted area, flood fraction, flood volume and depth
# and the corresponding land area
floodedFraction,floodedDepth,\
self.wettedArea,self.alphaQ= self.kinAlphaComposite(self.actualStorage,self.floodplainMask)
self.wettedArea= self.waterBodies.returnMapValue(self.wettedArea,\
self.waterBodies.channelWidth+2.*self.waterBodies.updateWaterHeight())
self.waterFraction= pcr.ifthenelse(self.waterBodies.distribution == 0,\
pcr.max(self.waterFractionMask,floodedFraction),self.waterFractionMask)
self.landFraction = pcr.max(0., 1. - self.waterFraction)
#-update on velocity and check on Q - NOTE: does not work in case of reservoirs!
self.flowVelocity = pcr.ifthenelse(self.wettedArea > 0,
self.Q / self.wettedArea, 0.)
pcr.report(
self.flowVelocity,
pcrm.generateNameT(flowVelocityFileName,
0).replace('.000', '.ini'))
#-setting initial values for specific runoff and surface water extraction
self.landSurfaceQ = pcr.scalar(0.)
self.potWaterSurfaceQ = pcr.scalar(0.)
self.surfaceWaterExtraction = pcr.scalar(0.)
#-budget check: setting initial values for cumulative discharge and
# net cumulative input, including initial storage [m3]
self.totalDischarge = pcr.scalar(0.)
self.cumulativeDeltaStorage = pcr.catchmenttotal(
self.actualStorage, self.LDD)
def extractDailyData(arcPath,arcFile,varPath,varList,leapYear): #-extracts daily data from tar file nDays= 365 if leapYear: nDays= nDays+1 arcList= [] for var in varList: for day in range(1,nDays+1): arcList.append(generateNameT(var,day)) archive= tarfile.open(os.path.join(arcPath,arcFile),'r:gz') for tarInfo in archive: if tarInfo.name in arcList: archive.extract(tarInfo,varPath) archive.close()
def extractDailyData(arcPath, arcFile, varPath, varList, leapYear):
#-extracts daily data from tar file
nDays = 365
if leapYear: nDays = nDays + 1
arcList = []
for var in varList:
for day in range(1, nDays + 1):
arcList.append(generateNameT(var, day))
archive = tarfile.open(os.path.join(arcPath, arcFile), 'r:gz')
for tarInfo in archive:
if tarInfo.name in arcList:
archive.extract(tarInfo, varPath)
archive.close()
def initial(self):
#####################
# * initial section #
#####################
#-constants
# betaQ [-]: constant of kinematic wave momentum equation
self.betaQ= 0.6
#-channel LDD
self.channelLDD= pcr.ifthenelse(self.waterBodies.distribution != 0,\
pcr.ldd(5),self.LDD)
#-channel area and storage
self.channelArea= self.channelWidth*self.channelLength
self.channelStorageCapacity= pcr.ifthenelse(self.waterBodies.distribution == 0,\
self.channelArea*self.channelDepth,pcr.scalar(0.))
#-basin outlets
self.basinOutlet= pcr.pit(self.LDD) != 0
#-read initial conditions
self.Q= clippedRead.get(self.QIniMap)
self.actualStorage= clippedRead.get(self.actualStorageIniMap)
self.actualStorage= pcr.ifthenelse(self.waterBodies.distribution != 0,\
pcr.ifthenelse(self.waterBodies.location != 0,\
pcr.areatotal(self.actualStorage,self.waterBodies.distribution),0),\
self.actualStorage)
self.waterBodies.actualStorage= self.waterBodies.retrieveMapValue(self.actualStorage)
#-update targets of average and bankful discharge
self.waterBodies.averageQ= self.waterBodies.retrieveMapValue(self.averageQ)
self.waterBodies.bankfulQ= self.waterBodies.retrieveMapValue(self.bankfulQ)
#-return the parameters for the kinematic wave,
# including alpha, wetted area, flood fraction, flood volume and depth
# and the corresponding land area
floodedFraction,floodedDepth,\
self.wettedArea,self.alphaQ= self.kinAlphaComposite(self.actualStorage,self.floodplainMask)
self.wettedArea= self.waterBodies.returnMapValue(self.wettedArea,\
self.waterBodies.channelWidth+2.*self.waterBodies.updateWaterHeight())
self.waterFraction= pcr.ifthenelse(self.waterBodies.distribution == 0,\
pcr.max(self.waterFractionMask,floodedFraction),self.waterFractionMask)
self.landFraction= pcr.max(0.,1.-self.waterFraction)
#-update on velocity and check on Q - NOTE: does not work in case of reservoirs!
self.flowVelocity= pcr.ifthenelse(self.wettedArea > 0,self.Q/self.wettedArea,0.)
pcr.report(self.flowVelocity,pcrm.generateNameT(flowVelocityFileName,0).replace('.000','.ini'))
#-setting initial values for specific runoff and surface water extraction
self.landSurfaceQ= pcr.scalar(0.)
self.potWaterSurfaceQ= pcr.scalar(0.)
self.surfaceWaterExtraction= pcr.scalar(0.)
#-budget check: setting initial values for cumulative discharge and
# net cumulative input, including initial storage [m3]
self.totalDischarge= pcr.scalar(0.)
self.cumulativeDeltaStorage= pcr.catchmenttotal(self.actualStorage,self.LDD)
def stackAverage(path,Root,StackStart,StackEnd): #calculates the average from a stack of maps, missing maps are skipped #Initialization MV= pcr.scalar(-999) NCount= pcr.scalar(0) SumStack= pcr.scalar(0) for StackNumber in range(StackStart,StackEnd): try: InMap= pcr.readmap(generateNameT(os.path.join(path,Root),StackNumber)) except: InMap= MV; InMap= pcr.cover(InMap,MV) SumStack= SumStack+InMap NCount= NCount+pcr.ifthenelse(InMap <> MV,pcr.scalar(1),pcr.scalar(0)) AvgStack= pcr.ifthenelse(NCount>0,SumStack/NCount,MV) return AvgStack
def stackAverage(path, Root, StackStart, StackEnd):
#calculates the average from a stack of maps, missing maps are skipped
#Initialization
MV = pcr.scalar(-999)
NCount = pcr.scalar(0)
SumStack = pcr.scalar(0)
for StackNumber in range(StackStart, StackEnd):
try:
InMap = pcr.readmap(
generateNameT(os.path.join(path, Root), StackNumber))
except:
InMap = MV
InMap = pcr.cover(InMap, MV)
SumStack = SumStack + InMap
NCount = NCount + pcr.ifthenelse(InMap <> MV, pcr.scalar(1),
pcr.scalar(0))
AvgStack = pcr.ifthenelse(NCount > 0, SumStack / NCount, MV)
return AvgStack
pcr.report(bankfulQ,targetFileName)
targetFileName= os.path.join(pathIniSource,'qwat_avg_longterm.map')
pcr.report(averageQWat,targetFileName)
#-define initital values for waterbodies
#-initializing class of water bodies for the first year
if not initializeRoutingModel:
pathIniSource= os.path.join(pathIni,modelSignature,'ini_%04d' % startYear)
fractionWater= clippedRead.get(os.path.join(tempDir,'fracwat_%d.map' % initYear))
waterBodies= pcrglobWaterBodies(os.path.join(tempDir,'waterbodyid_%d.map' % initYear),\
os.path.join(tempDir,'waterbodyoutlet_%d.map' % initYear),os.path.join(tempDir,'waterbodytype_%d.map' % initYear),\
os.path.join(mapsDir,'channel_width.map'),os.path.join(pathIniSource,'qavg_longterm.map'),\
os.path.join(pathIniSource,'qbank_longterm.map'),LDDMap,os.path.join(tempDir,'reservoirparameters_%d_30min_.tbl' % initYear),timeSec,clippedRead)
#-create initial files if the routing model is initialized
if initializeRoutingModel:
for variable in resStackList[iniOutVarStart:addOutVarStart]:
targetFileName= os.path.join(pathIniSource,pcrm.generateNameT(variable,0).replace('.000','.ini'))
if 'qc' in variable:
pcr.report(pcr.scalar(0),targetFileName)
elif 'wst'in variable:
waterBodiesType= pcr.nominal(waterBodies.returnMapValue(pcr.spatial(pcr.scalar(0.)),waterBodies.type))
endorheicLakes= pcr.ifthenelse((pcr.areatotal(pcr.scalar(waterBodies.outlet != 0),waterBodies.distribution) == 0) & \
(waterBodies.distribution != 0),waterBodies.distribution,0)
#-storage of water bodies is assigned at outlets
#-storage over endorheic lakes
actualStorage= pcr.ifthen(endorheicLakes != 0,\
pcr.upstream(LDD,pcr.ifthenelse((endorheicLakes == 0) & ((waterBodies.distribution == 0) | (waterBodies.outlet != 0)),\
averageQ,0)))
actualStorage= pcr.ifthen((waterBodies.location != 0) & (endorheicLakes != 0),\
pcr.max(0.,pcr.areatotal(pcr.cover(actualStorage*timeSec*365.25+averageQWat,0),endorheicLakes)))
#-storage over other water bodies
actualStorage= pcr.cover(actualStorage,\
def dynamic(self):
#####################
# * dynamic section #
#####################
#-evaluation of the current date: return current month and the time step used
#-reading in fluxes over land and water area for current time step [m/d]
# and read in reservoir demand and surface water extraction [m3]
try:
self.landSurfaceQ = clippedRead.get(
pcrm.generateNameT(landSurfaceQFileName,
self.currentTimeStep()))
except:
pass
try:
self.potWaterSurfaceQ = clippedRead.get(
pcrm.generateNameT(waterSurfaceQFileName,
self.currentTimeStep()))
except:
pass
#-surface water extraction and reservoir demand currently set to zero, should
# be computed automatically and updated to reservoirs
self.potSurfaceWaterExtraction = pcr.spatial(pcr.scalar(0.))
#self.waterBodies.demand= #self.reservoirDemandTSS.assignID(self.waterBodies.ID,self.currentTimeStep(),0.)*self.timeSec
#-initialization of cumulative values of actual water extractions
self.actWaterSurfaceQ = pcr.spatial(pcr.scalar(0.))
self.actSurfaceWaterExtraction = pcr.spatial(pcr.scalar(0.))
#-definition of sub-loop for routing scheme - explicit scheme has to satisfy Courant condition
timeLimit= pcr.cellvalue(pcr.mapminimum((pcr.cover(pcr.ifthen(self.waterBodies.distribution == 0,\
self.channelLength/self.flowVelocity),\
self.timeSec/self.nrIterDefault)*self.timeSec/self.nrIterDefault)**0.5),1)[0]
nrIter = int(self.timeSec / timeLimit)
nrIter = min(nrIter, int(self.timeSec / 300.))
while float(self.timeSec / nrIter) % 1 <> 0:
nrIter += 1
deltaTime = self.timeSec / nrIter
#-sub-loop for current time step
if self.currentDate.day == 1 or nrIter >= 24:
print '\n*\tprocessing %s, currently using %d substeps of %d seconds\n' % \
(self.currentDate.date(),nrIter,deltaTime)
#-update discharge and storage
for nrICur in range(nrIter):
#-initializing discharge for the current sub-timestep and fill in values
# for channels and at outlets of waterbodies
# * channels *
estQ= pcr.ifthenelse((self.actualStorage > 0.) & (self.waterBodies.distribution == 0) ,\
(self.wettedArea/self.alphaQ)**(1./self.betaQ),0.)
#estQ= pcr.ifthenelse((self.actualStorage > 0.) & (self.waterBodies.distribution == 0) ,\
#0.5*(self.Q+(self.wettedArea/self.alphaQ)**(1./self.betaQ)),0.)
#estQ= pcr.min(estQ,self.actualStorage/deltaTime)
self.report(estQ, 'results/qest')
self.Q = pcr.spatial(pcr.scalar(0.))
self.Q= pcr.ifthenelse(self.waterBodies.distribution == 0,\
pcr.kinematic(self.channelLDD,estQ,0.,self.alphaQ,\
self.betaQ,1,deltaTime,self.channelLength),self.Q)
# * water bodies *
self.waterBodies.dischargeUpdate()
self.Q = self.waterBodies.returnMapValue(self.Q,
self.waterBodies.actualQ)
#-fluxes and resulting change in storage: first the local fluxes are evaluated
# and aggregated over the water bodies where applicable; this includes the specific runoff [m/day/m2]
# from input and the estimated extraction from surface water as volume per day [m3/day];
# specific runoff from the land surface is always positive whereas the fluxes over the water surface
# are potential, including discharge, and are adjusted to match the availabe storage; to this end,
# surface water storage and fluxes over water bodies are totalized and assigned to the outlet;
# discharge is updated in a separate step, after vertical fluxes are compared to the actual storage
deltaActualStorage= ((self.landFraction*self.landSurfaceQ+\
self.waterFraction*self.potWaterSurfaceQ)*self.cellArea-\
self.potSurfaceWaterExtraction)*float(self.duration)/nrIter
deltaActualStorage= pcr.ifthenelse(self.waterBodies.distribution != 0,\
pcr.ifthenelse(self.waterBodies.location != 0,\
pcr.areatotal(deltaActualStorage,self.waterBodies.distribution),0),\
deltaActualStorage)
adjustmentRatio= pcr.ifthenelse(deltaActualStorage < 0.,\
pcr.min(1.,-self.actualStorage/deltaActualStorage),1.)
self.actWaterSurfaceQ += adjustmentRatio * self.potWaterSurfaceQ
self.actSurfaceWaterExtraction += adjustmentRatio * self.actSurfaceWaterExtraction
deltaActualStorage *= adjustmentRatio
#-local water balance check
if testLocalWaterBalance:
differenceActualStorage = self.actualStorage
differenceActualStorage += deltaActualStorage
#-overall water balance check: net input
self.cumulativeDeltaStorage += pcr.catchmenttotal(
deltaActualStorage, self.LDD)
#-update storage first with local changes, then balance discharge with storage and update storage
# with lateral flow and return value to water bodies
self.actualStorage += deltaActualStorage
self.actualStorage = pcr.max(0., self.actualStorage)
self.Q = pcr.min(self.Q, self.actualStorage / deltaTime)
deltaActualStorage = (-self.Q +
pcr.upstream(self.LDD, self.Q)) * deltaTime
deltaActualStorage= pcr.ifthenelse(self.waterBodies.distribution != 0,\
pcr.ifthenelse(self.waterBodies.location != 0,\
pcr.areatotal(deltaActualStorage,self.waterBodies.distribution),0),\
deltaActualStorage)
self.actualStorage += deltaActualStorage
self.actualStorage = pcr.max(0., self.actualStorage)
self.waterBodies.actualStorage = self.waterBodies.retrieveMapValue(
self.actualStorage)
#-flooded fraction returned
floodedFraction,floodedDepth,\
self.wettedArea,self.alphaQ= self.kinAlphaComposite(self.actualStorage,self.floodplainMask)
self.wettedArea= self.waterBodies.returnMapValue(self.wettedArea,\
self.waterBodies.channelWidth+2.*self.waterBodies.updateWaterHeight())
self.waterFraction= pcr.ifthenelse(self.waterBodies.distribution == 0,\
pcr.max(self.waterFractionMask,floodedFraction),self.waterFractionMask)
self.landFraction = pcr.max(0., 1. - self.waterFraction)
self.flowVelocity = pcr.ifthenelse(self.wettedArea > 0,
self.Q / self.wettedArea, 0.)
#-local water balance check
if testLocalWaterBalance:
differenceActualStorage += deltaActualStorage
differenceActualStorage -= self.actualStorage
totalDifference = pcr.cellvalue(
pcr.maptotal(differenceActualStorage), 1)[0]
minimumDifference = pcr.cellvalue(
pcr.mapminimum(differenceActualStorage), 1)[0]
maximumDifference = pcr.cellvalue(
pcr.mapmaximum(differenceActualStorage), 1)[0]
if abs(totalDifference) > 1.e-3:
print 'water balance error: total %e; min %e; max %e' %\
(totalDifference,minimumDifference,maximumDifference)
if reportLocalWaterBalance:
pcr.report(differenceActualStorage,
'mbe_%s.map' % self.currentDate.date())
#-overall water balance check: updating cumulative discharge and total storage [m3]
self.totalDischarge += self.Q * deltaTime
self.totalStorage = pcr.catchmenttotal(self.actualStorage,
self.LDD)
#-check on occurrence of last day and report mass balance
if self.currentDate == self.endDate:
#-report initial maps
pcr.report(self.Q, self.QIniMap)
pcr.report(self.actualStorage, self.actualStorageIniMap)
#-return relative and absolute water balance error per cell and
# as total at basin outlets
self.totalDischarge= pcr.ifthen((self.waterBodies.distribution == 0) | \
(self.waterBodies.location != 0),self.totalDischarge)
self.cumulativeDeltaStorage= pcr.ifthen((self.waterBodies.distribution == 0) | \
(self.waterBodies.location != 0),self.cumulativeDeltaStorage)
massBalanceError= self.totalStorage+self.totalDischarge-\
self.cumulativeDeltaStorage
relMassBalanceError = 1. + pcr.ifthenelse(
self.cumulativeDeltaStorage <> 0.,
massBalanceError / self.cumulativeDeltaStorage, 0.)
totalMassBalanceError= pcr.cellvalue(pcr.maptotal(pcr.ifthen(self.basinOutlet,\
massBalanceError)),1)[0]
totalCumulativeDeltaStorage= pcr.cellvalue(pcr.maptotal(pcr.ifthen(self.basinOutlet,\
self.cumulativeDeltaStorage)),1)[0]
if totalCumulativeDeltaStorage > 0:
totalRelativeMassBalanceError = 1. + totalMassBalanceError / totalCumulativeDeltaStorage
else:
totalRelativeMassBalanceError = 1.
#-report maps and echo value
pcr.report(massBalanceError, mbeFileName)
pcr.report(relMassBalanceError, mbrFileName)
print '\n*\ttotal global mass balance error [m3]: %8.3g' % totalMassBalanceError
print '\n*\trelative global mass balance error [-]: %5.3f' % totalRelativeMassBalanceError
#-echo to screen: total mass balance error and completion of run
print '\trun completed'
#-end of day: return states and fluxes
#-get surface water attributes?
if getSurfaceWaterAttributes:
#-compute the following secondary variables:
# surface water area [m2]: area given dynamic surface water fraction
# residence time [days]: volume over discharge, assigned -1 in case discharge is zero
# surface water depth [m], weighed by channel and floodplain volume
surfaceWaterArea = self.waterFraction * self.cellArea
surfaceWaterArea= pcr.ifthenelse(self.waterBodies.distribution != 0,\
pcr.ifthenelse(self.waterBodies.location != 0,\
pcr.areatotal(surfaceWaterArea,self.waterBodies.distribution),0),\
surfaceWaterArea)
surfaceWaterResidenceTime = pcr.ifthenelse(
self.Q > 0., self.actualStorage / (self.Q * self.timeSec), -1)
surfaceWaterDepth= pcr.ifthenelse(self.actualStorage > 0.,\
pcr.max(0.,self.actualStorage-self.channelStorageCapacity)**2/\
(self.actualStorage*surfaceWaterArea),0.)
surfaceWaterDepth+= pcr.ifthenelse(self.actualStorage > 0.,\
pcr.min(self.channelStorageCapacity,self.actualStorage)**2/(self.waterFractionMask*\
self.cellArea*self.actualStorage),0.)
#-reports: values at outlet of lakes or reservoirs are assigned to their full extent
self.report(pcr.ifthenelse(self.waterBodies.distribution != 0,\
pcr.areamaximum(surfaceWaterArea,self.waterBodies.distribution),surfaceWaterArea),\
surfaceWaterAreaFileName)
self.report(pcr.ifthenelse(self.waterBodies.distribution != 0,\
pcr.areamaximum(surfaceWaterResidenceTime,self.waterBodies.distribution),surfaceWaterResidenceTime),\
surfaceWaterResidenceTimeFileName)
self.report(pcr.ifthenelse(self.waterBodies.distribution != 0,\
pcr.areamaximum(surfaceWaterDepth,self.waterBodies.distribution),surfaceWaterDepth),\
surfaceWaterDepthFileName)
#-reports on standard output: values at outlet of lakes or reservoirs are assigned to their full extent
self.report(
pcr.ifthenelse(
self.waterBodies.distribution != 0,
pcr.areamaximum(self.flowVelocity,
self.waterBodies.distribution),
self.flowVelocity), flowVelocityFileName)
self.report(
pcr.ifthenelse(
self.waterBodies.distribution != 0,
pcr.areamaximum(self.Q, self.waterBodies.distribution),
self.Q), QFileName)
self.report(pcr.ifthenelse(self.waterBodies.distribution == 0,\
floodedFraction,0.),floodedFractionFileName)
self.report(pcr.ifthenelse(self.waterBodies.distribution == 0,\
floodedDepth,0.),floodedDepthFileName)
self.report(self.actualStorage, actualStorageFileName)
#-update date for time step and report relevant daily output
self.currentDate = self.currentDate + datetime.timedelta(self.duration)
def __init__(self, startDate, endDate, nrIterDefault=12.):
pcrm.DynamicModel.__init__(self)
##############
# * __init__ #
##############
#-echo to screen
print 'PCR-GLOBWB dynamic floodplain model - version 3.0 June 2012'
print '\tbeta version with smoothed floodplain elevations'
print '\tincluding lakes and reservoirs'
#-constants: duration of time step (day) in seconds
self.timeSec = duration * timeSec
#-passing global variables to local ones
#-cloone and cell area
self.clone = clone
self.cellArea = cellArea
#-model settings
self.nrIterDefault = nrIterDefault
self.duration = duration
self.currentDate = startDate
self.endDate = endDate
self.areaFractions = areaFractions
self.relZFileName = os.path.join(mapsDir, relZFileName)
self.reductionKK = reductionKK
self.criterionKK = criterionKK
#-number of entries in list and derived slopes and volumes
self.nrEntries = len(self.areaFractions)
self.relZ = [0.] * self.nrEntries
self.floodVolume = [0.] * (self.nrEntries)
#-flood plain and channel characteristics
self.channelGradient = pcr.max(1.e-7, channelGradient)
self.LDD = LDD
self.channelWidth = channelWidth
self.channelLength = channelLength
self.channelDepth = channelDepth
self.channelManN = channelManN
self.floodplainManN = floodplainManN
self.floodplainMask = floodplainMask
self.waterFractionMask = fractionWater
#-waterBodies
self.waterBodies = waterBodies
self.waterBodies.actualArea= self.waterBodies.retrieveMapValue(pcr.areatotal(self.waterFractionMask*\
self.cellArea,self.waterBodies.distribution))
#self.reservoirDemandTSS= readTSS(reservoirDemandTSS)
#-map names: initial maps of discharge and storage
self.QIniMap = pcrm.generateNameT(QFileName, 0).replace('.000', '.ini')
self.actualStorageIniMap = pcrm.generateNameT(actualStorageFileName,
0).replace(
'.000', '.ini')
self.averageQ = averageQ
self.bankfulQ = bankfulQ
#-patch elevations: those that are part of sills are updated on the basis of the floodplain gradient
# using local distances deltaX per increment upto z[N] and the sum over sills
#-fill all lists including smoothing interval and slopes
for iCnt in range(1, self.nrEntries):
self.relZ[iCnt]= clippedRead.get(self.relZFileName %\
(self.areaFractions[iCnt]*100))
#-minimum slope of floodplain, being defined as the longest sill, first used to retrieve
# longest cumulative distance
deltaX = [self.cellArea**0.5] * self.nrEntries
deltaX[0] = 0.
sumX = deltaX[:]
minSlope = 0.
for iCnt in range(self.nrEntries):
if iCnt < self.nrEntries - 1:
deltaX[iCnt] = (self.areaFractions[iCnt + 1]**0.5 -
self.areaFractions[iCnt]**0.5) * deltaX[iCnt]
else:
deltaX[iCnt] = (
1. - self.areaFractions[iCnt - 1]**0.5) * deltaX[iCnt]
if iCnt > 0:
sumX[iCnt] = pcr.ifthenelse(
self.relZ[iCnt] == self.relZ[iCnt - 1],
sumX[iCnt - 1] + deltaX[iCnt], 0.)
minSlope= pcr.ifthenelse(self.relZ[iCnt] == self.relZ[iCnt-1],\
pcr.max(sumX[iCnt],minSlope),minSlope)
minSlope = pcr.min(self.channelGradient,
0.5 * pcr.max(deltaX[1], minSlope)**-1.)
#-add small increment to elevations to each sill except in the case of lakes
for iCnt in range(self.nrEntries):
self.relZ[iCnt]= self.relZ[iCnt]+sumX[iCnt]*pcr.ifthenelse(self.relZ[self.nrEntries-1] > 0.,\
minSlope,0.)
#-set slope and smoothing interval between dy= y(i+1)-y(i) and dx= x(i+1)-x(i)
# on the basis of volume
#-slope and smoothing interval
self.kSlope = [0.] * (self.nrEntries)
self.mInterval = [0.] * (self.nrEntries)
for iCnt in range(1, self.nrEntries):
self.floodVolume[iCnt]= self.floodVolume[iCnt-1]+\
0.5*(self.areaFractions[iCnt]+self.areaFractions[iCnt-1])*\
(self.relZ[iCnt]-self.relZ[iCnt-1])*self.cellArea
self.kSlope[iCnt-1]= (self.areaFractions[iCnt]-self.areaFractions[iCnt-1])/\
pcr.max(0.001,self.floodVolume[iCnt]-self.floodVolume[iCnt-1])
for iCnt in range(1, self.nrEntries):
if iCnt < (self.nrEntries - 1):
self.mInterval[iCnt]= 0.5*self.reductionKK*pcr.min(self.floodVolume[iCnt+1]-self.floodVolume[iCnt],\
self.floodVolume[iCnt]-self.floodVolume[iCnt-1])
else:
self.mInterval[iCnt] = 0.5 * self.reductionKK * (
self.floodVolume[iCnt] - self.floodVolume[iCnt - 1])
def dynamic(self):
self.counter += 1
print(
str(self.curdate.day) + '-' + str(self.curdate.month) + '-' +
str(self.curdate.year) + ' t = ' + str(self.counter))
#-Snow and rain fraction settings for non-glacier part of model cell
SnowFrac = pcr.ifthenelse(self.SnowStore > 0,
pcr.scalar(1 - self.GlacFrac), 0)
RainFrac = pcr.ifthenelse(self.SnowStore == 0,
pcr.scalar(1 - self.GlacFrac), 0)
#-Read the precipitation time-series
if self.precNetcdfFLAG == 1:
#-read forcing by netcdf input
Precip = self.netcdf2PCraster.netcdf2pcrDynamic(self, pcr, 'Prec')
else:
#-read forcing by map input
Precip = pcr.readmap(pcrm.generateNameT(self.Prec, self.counter))
PrecipTot = Precip
#-Report Precip
self.reporting.reporting(self, pcr, 'TotPrec', Precip)
self.reporting.reporting(self, pcr, 'TotPrecF',
Precip * (1 - self.GlacFrac))
#-Temperature and determine reference evapotranspiration
if self.tempNetcdfFLAG == 1:
#-read forcing by netcdf input
Temp = self.netcdf2PCraster.netcdf2pcrDynamic(self, pcr, 'Temp')
else:
#-read forcing by map input
Temp = pcr.readmap(pcrm.generateNameT(self.Tair, self.counter))
if self.ETREF_FLAG == 0:
if self.TminNetcdfFLAG == 1:
#-read forcing by netcdf input
TempMin = self.netcdf2PCraster.netcdf2pcrDynamic(
self, pcr, 'Tmin')
else:
#-read forcing by map input
TempMin = pcr.readmap(
pcrm.generateNameT(self.Tmin, self.counter))
if self.TmaxNetcdfFLAG == 1:
#-read forcing by netcdf input
TempMax = self.netcdf2PCraster.netcdf2pcrDynamic(
self, pcr, 'Tmax')
else:
#-read forcing by map input
TempMax = pcr.readmap(
pcrm.generateNameT(self.Tmax, self.counter))
ETref = self.Hargreaves.Hargreaves(
pcr, self.Hargreaves.extrarad(self, pcr), Temp, TempMax,
TempMin)
else:
ETref = pcr.readmap(pcrm.generateNameT(self.ETref, self.counter))
self.reporting.reporting(self, pcr, 'TotETref', ETref)
self.reporting.reporting(self, pcr, 'TotETrefF',
ETref * (1 - self.GlacFrac))
#-Interception and effective precipitation
if self.DynVegFLAG == 1:
#-read dynamic processes dynamic vegetation
Precip = self.dynamic_veg.dynamic(self, pcr, pcrm, np, Precip,
ETref)
elif self.KcStatFLAG == 0:
#-Try to read the KC map series
try:
self.Kc = pcr.readmap(
pcrm.generateNameT(self.Kcmaps, self.counter))
self.KcOld = self.Kc
except:
self.Kc = self.KcOld
#-report mm effective precipitation for sub-basin averages
if self.mm_rep_FLAG == 1 and self.Prec_mm_FLAG == 1 and (
self.RoutFLAG == 1 or self.ResFLAG == 1 or self.LakeFLAG == 1):
self.PrecSubBasinTSS.sample(
pcr.catchmenttotal(Precip *
(1 - self.GlacFrac), self.FlowDir) /
pcr.catchmenttotal(1, self.FlowDir))
#-Snow, rain, and glacier calculations for glacier fraction of cell
if self.GlacFLAG:
#-read dynamic processes glacier
Rain_GLAC, Snow_GLAC, ActSnowMelt_GLAC, SnowR_GLAC, GlacMelt, GlacPerc, self.GlacR = self.glacier.dynamic(
self, pcr, pd, Temp, Precip)
#-If glacier module is not used, then
else:
Rain_GLAC = 0
Snow_GLAC = 0
ActSnowMelt_GLAC = 0
self.TotalSnowStore_GLAC = 0
SnowR_GLAC = 0
self.GlacR = 0
GlacMelt = 0
GlacPerc = 0
# Calculate snow and rain for non-glacier part of cell
if self.SnowFLAG == 1:
#-read dynamic processes snow
Rain, self.SnowR, OldTotalSnowStore = self.snow.dynamic(
self, pcr, Temp, Precip, Snow_GLAC, ActSnowMelt_GLAC, SnowFrac,
RainFrac, SnowR_GLAC)
else:
Rain = Precip
self.SnowR = 0
OldTotalSnowStore = 0
self.TotalSnowStore = 0
#-Report Rain
self.reporting.reporting(self, pcr, 'TotRain', Rain)
self.reporting.reporting(self, pcr, 'TotRainF',
Rain * (1 - self.GlacFrac) +
Rain_GLAC) # for entire cell
#-Potential evapotranspiration
ETpot = self.ET.ETpot(ETref, self.Kc)
if self.ETOpenWaterFLAG == 1:
self.ETOpenWater = self.ET.ETpot(ETref, self.kcOpenWater)
#-Report ETpot
self.reporting.reporting(self, pcr, 'TotETpot', ETpot)
self.reporting.reporting(self, pcr, 'TotETpotF', ETpot * RainFrac)
#-Rootzone calculations
self.RootWater = self.RootWater + self.CapRise
#-Calculate rootzone runoff
tempvar = self.rootzone.RootRunoff(self, pcr, RainFrac, Rain)
#-Rootzone runoff
RootRunoff = tempvar[0]
#-Infiltration
Infil = tempvar[1]
#-Report infiltration
self.reporting.reporting(self, pcr, 'Infil', Infil)
#-Updated rootwater content
self.RootWater = pcr.ifthenelse(RainFrac > 0, self.RootWater + Infil,
self.RootWater)
#-Actual evapotranspiration
if self.PlantWaterStressFLAG == 1:
etreddry = self.ET.ks(self, pcr, ETpot)
else:
etreddry = pcr.max(
pcr.min((self.RootWater - self.RootDry) /
(self.RootWilt - self.RootDry), 1), 0)
self.reporting.reporting(self, pcr, 'PlantStress', 1 - etreddry)
ETact = self.ET.ETact(pcr, ETpot, self.RootWater, self.RootSat,
etreddry, RainFrac)
#-Report the actual evapotranspiration
self.reporting.reporting(
self, pcr, 'TotETact',
ETact * (1 - self.openWaterFrac) +
self.ETOpenWater * self.openWaterFrac)
#-Actual evapotranspiration, corrected for rain fraction
ActETact = ETact * RainFrac
#-Report the actual evapotranspiration, corrected for rain fraction
self.reporting.reporting(self, pcr, 'TotETactF', ActETact)
if self.mm_rep_FLAG == 1 and self.ETa_mm_FLAG == 1 and (
self.RoutFLAG == 1 or self.ResFLAG == 1 or self.LakeFLAG == 1):
self.ETaSubBasinTSS.sample(
pcr.catchmenttotal(ActETact, self.FlowDir) /
pcr.catchmenttotal(1, self.FlowDir))
#-Update rootwater content
self.RootWater = pcr.max(self.RootWater - ETact, 0)
#-Calculate drainage
temp_RootDrain = self.rootzone.RootDrainage(
pcr, self.RootWater, self.RootDrain, self.RootField, self.RootSat,
self.RootDrainVel, self.RootTT)
#-Calculate percolation
temp_rootperc = self.rootzone.RootPercolation(pcr, self.RootWater,
self.SubWater,
self.RootField,
self.RootTT, self.SubSat)
#-Total sum of water able to leave the soil
RootOut = temp_RootDrain + temp_rootperc
#-Calculate new values for drainage and percolation (to be used when RootOut > RootExcess)
newdrain, newperc = self.rootzone.CalcFrac(pcr, self.RootWater,
self.RootField,
temp_RootDrain,
temp_rootperc)
#-Determine whether the new values need to be used
rootexcess = pcr.max(self.RootWater - self.RootField, 0)
self.RootDrain = pcr.ifthenelse(RootOut > rootexcess, newdrain,
temp_RootDrain)
rootperc = pcr.ifthenelse(RootOut > rootexcess, newperc, temp_rootperc)
#-Update the RootWater content
# Roottemp = self.RootWater
self.RootWater = self.RootWater - (self.RootDrain + rootperc)
#-Report rootzone percolation, corrected for fraction
self.reporting.reporting(self, pcr, 'TotRootPF',
rootperc * (1 - self.GlacFrac))
#-Report rootwater content
self.reporting.reporting(self, pcr, 'StorRootW',
self.RootWater * (1 - self.openWaterFrac))
#-Sub soil calculations
self.SubWater = self.SubWater + rootperc
if self.GroundFLAG == 0:
if self.SeepStatFLAG == 0:
try:
self.SeePage = pcr.readmap(
pcrm.generateNameT(self.Seepmaps, self.counter))
self.SeepOld = self.SeePage
except:
self.SeePage = self.SeepOld
#-Report seepage
self.reporting.reporting(self, pcr, 'TotSeepF',
pcr.scalar(self.SeePage))
self.SubWater = pcr.min(pcr.max(self.SubWater - self.SeePage, 0),
self.SubSat)
if self.mm_rep_FLAG == 1 and self.Seep_mm_FLAG == 1 and (
self.RoutFLAG == 1 or self.ResFLAG == 1
or self.LakeFLAG == 1):
self.SeepSubBasinTSS.sample(
pcr.catchmenttotal(self.SeePage, self.FlowDir) /
pcr.catchmenttotal(1, self.FlowDir))
#-Capillary rise
self.CapRise = self.subzone.CapilRise(pcr, self.SubField,
self.SubWater, self.CapRiseMax,
self.RootWater, self.RootSat,
self.RootField)
#-Report capillary rise, corrected for fraction
self.reporting.reporting(self, pcr, 'TotCapRF',
self.CapRise * (1 - self.GlacFrac))
#-Update sub soil water content
self.SubWater = self.SubWater - self.CapRise
if self.GroundFLAG == 1: # sub percolation will be calculated instead of subdrainage
subperc = self.subzone.SubPercolation(pcr, self.SubWater,
self.SubField, self.SubTT,
self.Gw, self.GwSat)
ActSubPerc = subperc * (1 - self.GlacFrac)
#-Report the subzone percolation, corrected for the fraction
self.reporting.reporting(self, pcr, 'TotSubPF', ActSubPerc)
#-Update sub soil water content
self.SubWater = self.SubWater - subperc
else: # sub drainage will be calculated instead of sub percolation
self.SubDrain = self.subzone.SubDrainage(pcr, self.SubWater,
self.SubField,
self.SubSat,
self.SubDrainVel,
self.SubDrain, self.SubTT)
#-Report drainage from subzone
self.reporting.reporting(self, pcr, 'TotSubDF', self.SubDrain)
#-Update sub soil water content
self.SubWater = self.SubWater - self.SubDrain
#-Report rootwater content
self.reporting.reporting(self, pcr, 'StorSubW',
self.SubWater * (1 - self.openWaterFrac))
#-Changes in soil water storage
OldSoilWater = self.SoilWater
self.SoilWater = (self.RootWater + self.SubWater) * (1 - self.GlacFrac)
#-Rootzone runoff
self.RootRR = RootRunoff * RainFrac * (1 - self.openWaterFrac)
#-Report rootzone runoff, corrected for fraction
self.reporting.reporting(self, pcr, 'TotRootRF', self.RootRR)
#-Rootzone drainage
self.RootDR = self.RootDrain * (1 - self.GlacFrac) * (
1 - self.openWaterFrac)
#-Report rootzone drainage, corrected for fraction
self.reporting.reporting(self, pcr, 'TotRootDF', self.RootDR)
#-Rain runoff
self.RainR = self.RootRR + self.RootDR
#-Report rain runoff
self.reporting.reporting(self, pcr, 'TotRainRF', self.RainR)
#-Groundwater calculations
if self.GroundFLAG == 1:
#-read dynamic processes groundwater
self.groundwater.dynamic(self, pcr, ActSubPerc, GlacPerc)
else:
#-Use drainage from subsoil as baseflow
self.BaseR = self.SubDrain
#-Groundwater level as scaled between min and max measured gwl
SoilAct = self.RootWater + self.SubWater
SoilRel = (SoilAct - self.SoilMin) / (
self.SoilMax - self.SoilMin
) # scale between 0 (dry) and 1 (wet)
GWL = self.GWL_base - (SoilRel - 0.5) * self.GWL_base
#-Report groundwater
self.reporting.reporting(self, pcr, 'GWL', GWL)
#-Report Total runoff
TotR = self.BaseR + self.RainR + self.SnowR + self.GlacR
self.reporting.reporting(self, pcr, 'TotRF', TotR)
#-Routing for lake and/or reservoir modules
if self.LakeFLAG == 1 or self.ResFLAG == 1:
#-read dynamic processes advanced routing
Q = self.advanced_routing.dynamic(self, pcr, pcrm, config, TotR,
self.ETOpenWater, PrecipTot)
#-Normal routing module
elif self.RoutFLAG == 1:
self.routing.dynamic(self, pcr, TotR)
if self.GlacFLAG:
#-read dynamic reporting processes glacier
self.glacier.dynamic_reporting(self, pcr, pd, np)
#-Water balance
if self.GlacFLAG and self.GlacRetreat == 1:
GlacTable_MODid = self.GlacTable.loc[:, ['FRAC_GLAC', 'ICE_DEPTH']]
GlacTable_MODid['ICE_DEPTH'] = GlacTable_MODid[
'ICE_DEPTH'] * GlacTable_MODid['FRAC_GLAC']
GlacTable_MODid = GlacTable_MODid.groupby(
GlacTable_MODid.index).sum()
GlacTable_MODid.fillna(0., inplace=True)
#-Report pcraster map of glacier depth
iceDepth = pcr.numpy.zeros(self.ModelID_1d.shape)
iceDepth[self.GlacierKeys] = GlacTable_MODid['ICE_DEPTH']
iceDepth = iceDepth.reshape(self.ModelID.shape)
iceDepth = pcr.numpy2pcr(pcr.Scalar, iceDepth, self.MV)
iceDepth = pcr.ifthen(
self.clone, iceDepth) #-only use values where clone is True
iceDepth = iceDepth * 1000 # in mm
#-change in storage
dS = ((self.RootWater - self.oldRootWater) + (self.SubWater - self.oldSubWater)) * (1-self.GlacFrac) + (self.Gw - self.oldGw) + \
(self.TotalSnowStore-OldTotalSnowStore) + (iceDepth - self.oldIceDepth)
#-set old state variables for glacier
self.oldIceDepth = iceDepth
iceDepth = None
del iceDepth
GlacTable_MODid = None
del GlacTable_MODid
elif self.GroundFLAG:
#-change in storage
dS = ((self.RootWater - self.oldRootWater) + (self.SubWater - self.oldSubWater)) * (1-self.GlacFrac) + (self.Gw - self.oldGw) + \
(self.TotalSnowStore-OldTotalSnowStore)
# set old state variables for groundwater
self.oldGw = self.Gw
else:
#-change in storage
dS = ((self.RootWater - self.oldRootWater) +
(self.SubWater - self.oldSubWater)) * (1 - self.GlacFrac) + (
self.TotalSnowStore - OldTotalSnowStore)
#-water balance per time step
if self.GroundFLAG:
waterbalance = Precip - ActETact - self.BaseR - self.RainR - self.SnowR - self.GlacR - dS
else:
waterbalance = Precip - ActETact - self.BaseR - self.RainR - self.SnowR - dS - self.SeePage
self.reporting.reporting(self, pcr, 'wbal', waterbalance)
#-total water balance
self.waterbalanceTot = self.waterbalanceTot + waterbalance
#-report water balance and accumulated water balance
if self.wbal_TSS_FLAG and (self.RoutFLAG == 1 or self.ResFLAG == 1
or self.LakeFLAG == 1):
self.wbalTSS.sample(
pcr.catchmenttotal(waterbalance, self.FlowDir) /
pcr.catchmenttotal(1., self.FlowDir))
self.wbalTotTSS.sample(
pcr.catchmenttotal(self.waterbalanceTot, self.FlowDir) /
pcr.catchmenttotal(1., self.FlowDir))
# set old state variables
self.oldRootWater = self.RootWater
self.oldSubWater = self.SubWater
waterbalance = None
del waterbalance
dS = None
del dS
#-End of water balance calculations
#-Sediment yield
if self.SedFLAG == 1:
#-determine runoff in mm per day
if self.RoutFLAG == 1 or self.ResFLAG == 1 or self.LakeFLAG == 1:
Runoff = (Q * 3600 * 24) / pcr.cellarea() * 1000
else:
Runoff = TotR
#-MUSLE
if self.SedModel == 1:
#-read dynamic processes musle
self.musle.dynamic(self, pcr, Runoff)
#-sediment transport
if self.SedTransFLAG == 1:
#-read dynamic sediment transport processes musle
self.sediment_transport.dynamic_musle(self, pcr)
#-Modified Morgan-Morgan-Finney model
if self.SedModel == 2:
#-determine soil erosion in transport (G)
G = self.mmf.dynamic(self, pcr, Precip, Runoff)
#-sediment transport
if self.SedTransFLAG == 1:
#-read dynamic sediment transport processes mmf
self.sediment_transport.dynamic_mmf(
self, pcr, Runoff, np, G)
#-update current date
self.curdate = self.curdate + self.datetime.timedelta(days=1)
def dynamic(self): ##################### # * dynamic section # ##################### #-evaluation of the current date: return current month and the time step used #-reading in fluxes over land and water area for current time step [m/d] # and read in reservoir demand and surface water extraction [m3] try: self.landSurfaceQ= clippedRead.get(pcrm.generateNameT(landSurfaceQFileName,self.currentTimeStep())) except: pass try: self.potWaterSurfaceQ= clippedRead.get(pcrm.generateNameT(waterSurfaceQFileName,self.currentTimeStep())) except: pass #-surface water extraction and reservoir demand currently set to zero, should # be computed automatically and updated to reservoirs self.potSurfaceWaterExtraction= pcr.spatial(pcr.scalar(0.)) #self.waterBodies.demand= #self.reservoirDemandTSS.assignID(self.waterBodies.ID,self.currentTimeStep(),0.)*self.timeSec #-initialization of cumulative values of actual water extractions self.actWaterSurfaceQ= pcr.spatial(pcr.scalar(0.)) self.actSurfaceWaterExtraction= pcr.spatial(pcr.scalar(0.)) #-definition of sub-loop for routing scheme - explicit scheme has to satisfy Courant condition timeLimit= pcr.cellvalue(pcr.mapminimum((pcr.cover(pcr.ifthen(self.waterBodies.distribution == 0,\ self.channelLength/self.flowVelocity),\ self.timeSec/self.nrIterDefault)*self.timeSec/self.nrIterDefault)**0.5),1)[0] nrIter= int(self.timeSec/timeLimit) nrIter= min(nrIter,int(self.timeSec/300.)) while float(self.timeSec/nrIter) % 1 <> 0: nrIter+= 1 deltaTime= self.timeSec/nrIter #-sub-loop for current time step if self.currentDate.day == 1 or nrIter >= 24: print '\n*\tprocessing %s, currently using %d substeps of %d seconds\n' % \ (self.currentDate.date(),nrIter,deltaTime) #-update discharge and storage for nrICur in range(nrIter): #-initializing discharge for the current sub-timestep and fill in values # for channels and at outlets of waterbodies # * channels * estQ= pcr.ifthenelse((self.actualStorage > 0.) & (self.waterBodies.distribution == 0) ,\ (self.wettedArea/self.alphaQ)**(1./self.betaQ),0.) #estQ= pcr.ifthenelse((self.actualStorage > 0.) & (self.waterBodies.distribution == 0) ,\ #0.5*(self.Q+(self.wettedArea/self.alphaQ)**(1./self.betaQ)),0.) #estQ= pcr.min(estQ,self.actualStorage/deltaTime) self.report(estQ,'results/qest') self.Q= pcr.spatial(pcr.scalar(0.)) self.Q= pcr.ifthenelse(self.waterBodies.distribution == 0,\ pcr.kinematic(self.channelLDD,estQ,0.,self.alphaQ,\ self.betaQ,1,deltaTime,self.channelLength),self.Q) # * water bodies * self.waterBodies.dischargeUpdate() self.Q= self.waterBodies.returnMapValue(self.Q,self.waterBodies.actualQ) #-fluxes and resulting change in storage: first the local fluxes are evaluated # and aggregated over the water bodies where applicable; this includes the specific runoff [m/day/m2] # from input and the estimated extraction from surface water as volume per day [m3/day]; # specific runoff from the land surface is always positive whereas the fluxes over the water surface # are potential, including discharge, and are adjusted to match the availabe storage; to this end, # surface water storage and fluxes over water bodies are totalized and assigned to the outlet; # discharge is updated in a separate step, after vertical fluxes are compared to the actual storage deltaActualStorage= ((self.landFraction*self.landSurfaceQ+\ self.waterFraction*self.potWaterSurfaceQ)*self.cellArea-\ self.potSurfaceWaterExtraction)*float(self.duration)/nrIter deltaActualStorage= pcr.ifthenelse(self.waterBodies.distribution != 0,\ pcr.ifthenelse(self.waterBodies.location != 0,\ pcr.areatotal(deltaActualStorage,self.waterBodies.distribution),0),\ deltaActualStorage) adjustmentRatio= pcr.ifthenelse(deltaActualStorage < 0.,\ pcr.min(1.,-self.actualStorage/deltaActualStorage),1.) self.actWaterSurfaceQ+= adjustmentRatio*self.potWaterSurfaceQ self.actSurfaceWaterExtraction+= adjustmentRatio*self.actSurfaceWaterExtraction deltaActualStorage*= adjustmentRatio #-local water balance check if testLocalWaterBalance: differenceActualStorage= self.actualStorage differenceActualStorage+= deltaActualStorage #-overall water balance check: net input self.cumulativeDeltaStorage+= pcr.catchmenttotal(deltaActualStorage,self.LDD) #-update storage first with local changes, then balance discharge with storage and update storage # with lateral flow and return value to water bodies self.actualStorage+= deltaActualStorage self.actualStorage= pcr.max(0.,self.actualStorage) self.Q= pcr.min(self.Q,self.actualStorage/deltaTime) deltaActualStorage= (-self.Q+pcr.upstream(self.LDD,self.Q))*deltaTime deltaActualStorage= pcr.ifthenelse(self.waterBodies.distribution != 0,\ pcr.ifthenelse(self.waterBodies.location != 0,\ pcr.areatotal(deltaActualStorage,self.waterBodies.distribution),0),\ deltaActualStorage) self.actualStorage+= deltaActualStorage self.actualStorage= pcr.max(0.,self.actualStorage) self.waterBodies.actualStorage= self.waterBodies.retrieveMapValue(self.actualStorage) #-flooded fraction returned floodedFraction,floodedDepth,\ self.wettedArea,self.alphaQ= self.kinAlphaComposite(self.actualStorage,self.floodplainMask) self.wettedArea= self.waterBodies.returnMapValue(self.wettedArea,\ self.waterBodies.channelWidth+2.*self.waterBodies.updateWaterHeight()) self.waterFraction= pcr.ifthenelse(self.waterBodies.distribution == 0,\ pcr.max(self.waterFractionMask,floodedFraction),self.waterFractionMask) self.landFraction= pcr.max(0.,1.-self.waterFraction) self.flowVelocity= pcr.ifthenelse(self.wettedArea > 0,self.Q/self.wettedArea,0.) #-local water balance check if testLocalWaterBalance: differenceActualStorage+= deltaActualStorage differenceActualStorage-= self.actualStorage totalDifference= pcr.cellvalue(pcr.maptotal(differenceActualStorage),1)[0] minimumDifference= pcr.cellvalue(pcr.mapminimum(differenceActualStorage),1)[0] maximumDifference= pcr.cellvalue(pcr.mapmaximum(differenceActualStorage),1)[0] if abs(totalDifference) > 1.e-3: print 'water balance error: total %e; min %e; max %e' %\ (totalDifference,minimumDifference,maximumDifference) if reportLocalWaterBalance: pcr.report(differenceActualStorage,'mbe_%s.map' % self.currentDate.date()) #-overall water balance check: updating cumulative discharge and total storage [m3] self.totalDischarge+= self.Q*deltaTime self.totalStorage= pcr.catchmenttotal(self.actualStorage,self.LDD) #-check on occurrence of last day and report mass balance if self.currentDate == self.endDate: #-report initial maps pcr.report(self.Q,self.QIniMap) pcr.report(self.actualStorage,self.actualStorageIniMap) #-return relative and absolute water balance error per cell and # as total at basin outlets self.totalDischarge= pcr.ifthen((self.waterBodies.distribution == 0) | \ (self.waterBodies.location != 0),self.totalDischarge) self.cumulativeDeltaStorage= pcr.ifthen((self.waterBodies.distribution == 0) | \ (self.waterBodies.location != 0),self.cumulativeDeltaStorage) massBalanceError= self.totalStorage+self.totalDischarge-\ self.cumulativeDeltaStorage relMassBalanceError= 1.+pcr.ifthenelse(self.cumulativeDeltaStorage <> 0., massBalanceError/self.cumulativeDeltaStorage,0.) totalMassBalanceError= pcr.cellvalue(pcr.maptotal(pcr.ifthen(self.basinOutlet,\ massBalanceError)),1)[0] totalCumulativeDeltaStorage= pcr.cellvalue(pcr.maptotal(pcr.ifthen(self.basinOutlet,\ self.cumulativeDeltaStorage)),1)[0] if totalCumulativeDeltaStorage > 0: totalRelativeMassBalanceError= 1.+totalMassBalanceError/totalCumulativeDeltaStorage else: totalRelativeMassBalanceError= 1. #-report maps and echo value pcr.report(massBalanceError,mbeFileName) pcr.report(relMassBalanceError,mbrFileName) print '\n*\ttotal global mass balance error [m3]: %8.3g' % totalMassBalanceError print '\n*\trelative global mass balance error [-]: %5.3f' % totalRelativeMassBalanceError #-echo to screen: total mass balance error and completion of run print '\trun completed' #-end of day: return states and fluxes #-get surface water attributes? if getSurfaceWaterAttributes: #-compute the following secondary variables: # surface water area [m2]: area given dynamic surface water fraction # residence time [days]: volume over discharge, assigned -1 in case discharge is zero # surface water depth [m], weighed by channel and floodplain volume surfaceWaterArea= self.waterFraction*self.cellArea surfaceWaterArea= pcr.ifthenelse(self.waterBodies.distribution != 0,\ pcr.ifthenelse(self.waterBodies.location != 0,\ pcr.areatotal(surfaceWaterArea,self.waterBodies.distribution),0),\ surfaceWaterArea) surfaceWaterResidenceTime= pcr.ifthenelse(self.Q > 0.,self.actualStorage/(self.Q*self.timeSec),-1) surfaceWaterDepth= pcr.ifthenelse(self.actualStorage > 0.,\ pcr.max(0.,self.actualStorage-self.channelStorageCapacity)**2/\ (self.actualStorage*surfaceWaterArea),0.) surfaceWaterDepth+= pcr.ifthenelse(self.actualStorage > 0.,\ pcr.min(self.channelStorageCapacity,self.actualStorage)**2/(self.waterFractionMask*\ self.cellArea*self.actualStorage),0.) #-reports: values at outlet of lakes or reservoirs are assigned to their full extent self.report(pcr.ifthenelse(self.waterBodies.distribution != 0,\ pcr.areamaximum(surfaceWaterArea,self.waterBodies.distribution),surfaceWaterArea),\ surfaceWaterAreaFileName) self.report(pcr.ifthenelse(self.waterBodies.distribution != 0,\ pcr.areamaximum(surfaceWaterResidenceTime,self.waterBodies.distribution),surfaceWaterResidenceTime),\ surfaceWaterResidenceTimeFileName) self.report(pcr.ifthenelse(self.waterBodies.distribution != 0,\ pcr.areamaximum(surfaceWaterDepth,self.waterBodies.distribution),surfaceWaterDepth),\ surfaceWaterDepthFileName) #-reports on standard output: values at outlet of lakes or reservoirs are assigned to their full extent self.report(pcr.ifthenelse(self.waterBodies.distribution != 0, pcr.areamaximum(self.flowVelocity,self.waterBodies.distribution),self.flowVelocity),flowVelocityFileName) self.report(pcr.ifthenelse(self.waterBodies.distribution != 0, pcr.areamaximum(self.Q,self.waterBodies.distribution),self.Q),QFileName) self.report(pcr.ifthenelse(self.waterBodies.distribution == 0,\ floodedFraction,0.),floodedFractionFileName) self.report(pcr.ifthenelse(self.waterBodies.distribution == 0,\ floodedDepth,0.),floodedDepthFileName) self.report(self.actualStorage,actualStorageFileName) #-update date for time step and report relevant daily output self.currentDate= self.currentDate+datetime.timedelta(self.duration)
def __init__(self,startDate,endDate,nrIterDefault= 12.):
pcrm.DynamicModel.__init__(self)
##############
# * __init__ #
##############
#-echo to screen
print 'PCR-GLOBWB dynamic floodplain model - version 3.0 June 2012'
print '\tbeta version with smoothed floodplain elevations'
print '\tincluding lakes and reservoirs'
#-constants: duration of time step (day) in seconds
self.timeSec= duration*timeSec
#-passing global variables to local ones
#-cloone and cell area
self.clone= clone
self.cellArea= cellArea
#-model settings
self.nrIterDefault= nrIterDefault
self.duration= duration
self.currentDate= startDate
self.endDate= endDate
self.areaFractions= areaFractions
self.relZFileName= os.path.join(mapsDir,relZFileName)
self.reductionKK= reductionKK
self.criterionKK= criterionKK
#-number of entries in list and derived slopes and volumes
self.nrEntries= len(self.areaFractions)
self.relZ= [0.]*self.nrEntries
self.floodVolume= [0.]*(self.nrEntries)
#-flood plain and channel characteristics
self.channelGradient= pcr.max(1.e-7,channelGradient)
self.LDD= LDD
self.channelWidth= channelWidth
self.channelLength= channelLength
self.channelDepth= channelDepth
self.channelManN= channelManN
self.floodplainManN= floodplainManN
self.floodplainMask= floodplainMask
self.waterFractionMask= fractionWater
#-waterBodies
self.waterBodies= waterBodies
self.waterBodies.actualArea= self.waterBodies.retrieveMapValue(pcr.areatotal(self.waterFractionMask*\
self.cellArea,self.waterBodies.distribution))
#self.reservoirDemandTSS= readTSS(reservoirDemandTSS)
#-map names: initial maps of discharge and storage
self.QIniMap= pcrm.generateNameT(QFileName,0).replace('.000','.ini')
self.actualStorageIniMap= pcrm.generateNameT(actualStorageFileName,0).replace('.000','.ini')
self.averageQ= averageQ
self.bankfulQ= bankfulQ
#-patch elevations: those that are part of sills are updated on the basis of the floodplain gradient
# using local distances deltaX per increment upto z[N] and the sum over sills
#-fill all lists including smoothing interval and slopes
for iCnt in range(1,self.nrEntries):
self.relZ[iCnt]= clippedRead.get(self.relZFileName %\
(self.areaFractions[iCnt]*100))
#-minimum slope of floodplain, being defined as the longest sill, first used to retrieve
# longest cumulative distance
deltaX= [self.cellArea**0.5]*self.nrEntries
deltaX[0]= 0.
sumX= deltaX[:]
minSlope= 0.
for iCnt in range(self.nrEntries):
if iCnt < self.nrEntries-1:
deltaX[iCnt]= (self.areaFractions[iCnt+1]**0.5-self.areaFractions[iCnt]**0.5)*deltaX[iCnt]
else:
deltaX[iCnt]= (1.-self.areaFractions[iCnt-1]**0.5)*deltaX[iCnt]
if iCnt > 0:
sumX[iCnt]= pcr.ifthenelse(self.relZ[iCnt] == self.relZ[iCnt-1],sumX[iCnt-1]+deltaX[iCnt],0.)
minSlope= pcr.ifthenelse(self.relZ[iCnt] == self.relZ[iCnt-1],\
pcr.max(sumX[iCnt],minSlope),minSlope)
minSlope= pcr.min(self.channelGradient,0.5*pcr.max(deltaX[1],minSlope)**-1.)
#-add small increment to elevations to each sill except in the case of lakes
for iCnt in range(self.nrEntries):
self.relZ[iCnt]= self.relZ[iCnt]+sumX[iCnt]*pcr.ifthenelse(self.relZ[self.nrEntries-1] > 0.,\
minSlope,0.)
#-set slope and smoothing interval between dy= y(i+1)-y(i) and dx= x(i+1)-x(i)
# on the basis of volume
#-slope and smoothing interval
self.kSlope= [0.]*(self.nrEntries)
self.mInterval= [0.]*(self.nrEntries)
for iCnt in range(1,self.nrEntries):
self.floodVolume[iCnt]= self.floodVolume[iCnt-1]+\
0.5*(self.areaFractions[iCnt]+self.areaFractions[iCnt-1])*\
(self.relZ[iCnt]-self.relZ[iCnt-1])*self.cellArea
self.kSlope[iCnt-1]= (self.areaFractions[iCnt]-self.areaFractions[iCnt-1])/\
pcr.max(0.001,self.floodVolume[iCnt]-self.floodVolume[iCnt-1])
for iCnt in range(1,self.nrEntries):
if iCnt < (self.nrEntries-1):
self.mInterval[iCnt]= 0.5*self.reductionKK*pcr.min(self.floodVolume[iCnt+1]-self.floodVolume[iCnt],\
self.floodVolume[iCnt]-self.floodVolume[iCnt-1])
else:
self.mInterval[iCnt]= 0.5*self.reductionKK*(self.floodVolume[iCnt]-self.floodVolume[iCnt-1])
