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main_weekly.py
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# general
import sys
import datetime
from collections import deque
import glob
sys.path.append("../pycatch/pcrasterModules/")
# from PCRaster modules
import generalfunctions
import datetimePCRasterPython
import interceptionuptomaxstore
import surfacestore
import infiltrationonlyksat
import subsurfacewateronelayer
import runoffaccuthreshold
import rainfalleventsfromgammadistribution
import exchangevariables_weekly
import soilwashMMF
import regolith
import bedrockweathering
import evapotranspirationsimple
import biomassmodifiedmay
import baselevel
import creep
import configuration_weekly as cfg
# PCRaster itself
from pcraster import *
from pcraster.framework import *
if cfg.fixedStates:
cfg.numberOfTimeSteps=52*50
fixedStatesReg=spatial(scalar(float(sys.argv[1])))
fixedStatesBio=spatial(scalar(float(sys.argv[2])))
timeStepsWithStatsCalculated = range(cfg.intervalForStatsCalculated, \
cfg.numberOfTimeSteps,cfg.intervalForStatsCalculated)
def calculateGapFractionAndMaxIntStoreFromLAI(leafAreaIndex):
maximumInterceptionCapacityPerLAI=scalar(0.001)
gapFraction=exp(-0.5*leafAreaIndex) # equation 40 in Brolsma et al 2010a
maximumInterceptionStore=maximumInterceptionCapacityPerLAI*leafAreaIndex
return gapFraction, maximumInterceptionStore
class CatchmentModel(DynamicModel,MonteCarloModel):
def __init__(self):
DynamicModel.__init__(self)
MonteCarloModel.__init__(self)
setclone('inputs_weekly/clone.map')
# fix the seed for random functions
setrandomseed(101)
if cfg.filtering:
ParticleFilterModel.__init__(self)
def premcloop(self):
self.clone=boolean("inputs_weekly/clone.map")
self.numberOfCellsOnMap=maptotal(ifthenelse(self.clone,scalar(1),scalar(1)))
# not essential this code
# used for fixedStatesLoop.py
# edgesMap=generalfunctions.edgeZone(self.clone,2.1)
# self.mlocs=uniqueid(~ edgesMap)
# self.report(self.mlocs,'testMap')
# locations where values are reported as a numpy array to disk
self.mlocs=nominal("inputs_weekly/mlocs") # multiple report locations, read from 'mlocs.map'
self.aLocation=self.mlocs
# zone reported at each report location
if cfg.fixedStates:
# option 2 used for fixedStatesLoop.py
# one big zone, resulting in the same value for each report
# location
edgesMap=generalfunctions.edgeZone(self.clone,2.1)
self.zoneMap=ifthen(~ edgesMap,boolean(1))
self.report(self.zoneMap,'testMap')
else:
# option 1 for normal runs, zones across the hillslope for each
# location on mlocs
self.zoneMap=nominal("inputs_weekly/zonsc.map")
self.createInstancesPremcloop()
self.durationHistory=207
# time step duration in hours, typically (and only tested) one week, i.e. 7.0*24.0
self.timeStepDuration = 7.0 * 24.0
def initial(self):
# TIME BEING DIVIDE BY 100 TO AVOID IT RUNS TOO LONG - DK 210519 not clear what this comment is
self.initializeTime(2001,2,26,self.timeStepDuration)
self.createInstancesInitial()
self.d_exchangevariables.upwardSeepageFlux=scalar(0)
self.d_exchangevariables.evapFromSoilMultiplier=scalar(1)
self.timeStepDurationYears=self.timeStepDuration/(365.0*24.0)
self.actualAbstractionFluxFromSubsurface=0.0
# functions and settings for calculating statistics
self.historyOfSoilMoistureFraction=deque([])
self.historyOfBiomass=deque([])
self.historyOfRegolithThickness=deque([])
self.historyOfDem=deque([])
self.historyOfTotQ=deque([])
nrSampleLocs=100
fractionShortDistance=0.4
separationDistance=3
import generalfunctions # not sure why this needs to be imported again
self.samples=generalfunctions.samplingScheme(self.clone, nrSampleLocs, fractionShortDistance, separationDistance,0,0)
self.report(self.samples,'samples')
self.someLocs=pcrne(self.samples,0)
# initial setting for saving grazing pressure
self.grazingPressureArray=numpy.empty([0])
# budgets
self.d_exchangevariables.cumulativePrecipitation=scalar(0)
# initial values
self.grazingRate=0.0
self.runoffMetreWaterDepthPerHour=scalar(0.0)
self.creepDeposition=spatial(scalar(0.0))
def dynamic(self):
import generalfunctions # not sure why this needs to be imported again
#option to print time info
#print self.currentTimeStep()
# time
#self.d_dateTimePCRasterPython.update()
#timeDatetimeFormat=self.d_dateTimePCRasterPython.getTimeDatetimeFormat()
## biomass
if cfg.fixedStates:
self.d_regolithdemandbedrock.setNewRegolith(spatial(scalar(fixedStatesReg)))
self.d_biomassModifiedMay.setNewBiomass(spatial(scalar(fixedStatesBio)))
# grazing pressure driver
# note that biomassmodifiedmay.py in the method grazingTerm does
# define a specific function for grazing
# this below increases grazing pressure and then reduces it again, for the hysteris plot
# to create the hysteresis plot, see the folder 'scenarios', revised paper!
#grazingRateIncrease=50.0*(0.00000007/52.0)
grazingRateIncreaseTotal=0.0003
grazingRateIncrease=grazingRateIncreaseTotal/(cfg.numberOfTimeSteps/2.0)
if self.currentTimeStep() < (cfg.numberOfTimeSteps/2.0):
self.grazingRate=self.grazingRate+grazingRateIncrease
else:
self.grazingRate=self.grazingRate-grazingRateIncrease
#print 'grazing rate is ', self.grazingRate
self.grazingPressureArray=numpy.append(self.grazingPressureArray,self.grazingRate)
runoffMetreWaterDepthPerWeek=self.runoffMetreWaterDepthPerHour*cfg.theDurationOfRainstorm
self.biomass,self.LAI=self.d_biomassModifiedMay.update(self.actualAbstractionFluxFromSubsurface, \
runoffMetreWaterDepthPerWeek,self.grazingRate)
# update gap fraction and maximum interception store
gapFraction,maxIntStore=calculateGapFractionAndMaxIntStoreFromLAI(self.LAI)
self.d_interceptionuptomaxstore.setGapFraction(gapFraction)
self.d_interceptionuptomaxstore.setMaximumStore(maxIntStore)
# update stone cover for erosion
fractionOfVegetationAboveSoil=0.7
vegetationCoverForErosion=(1.0-gapFraction)*fractionOfVegetationAboveSoil
self.d_soilwashMMF.updateStoneOrVegetationCover(vegetationCoverForErosion)
# precipitation
isRaining,rainfallFlux,rainfallAmount= self.d_rainfalleventsfromgammadistribution.getRainstorm()
self.d_exchangevariables.cumulativePrecipitation= \
self.d_exchangevariables.cumulativePrecipitation+rainfallFlux*self.timeStepDuration
if isRaining:
# interception store
actualAdditionFluxToInterceptionStore=self.d_interceptionuptomaxstore.addWater(rainfallFlux)
throughfallFlux=rainfallFlux-actualAdditionFluxToInterceptionStore
# surface store
# time being no upward seepage
#totalToSurfaceFlux=throughfallFlux+self.d_exchangevariables.upwardSeepageFlux
totalToSurfaceFlux=throughfallFlux
potentialToSurfaceStoreFlux=self.d_surfaceStore.potentialToFlux()
# potential infiltration
self.d_infiltrationonlyksat.setSaturatedConductivityFluxAsFunctionOfBiomass(self.biomass)
potentialHortonianInfiltrationFlux=self.d_infiltrationonlyksat.potentialInfiltrationFluxFunction()
maximumSaturatedOverlandFlowInfiltrationFlux=self.d_subsurfaceWaterOneLayer.getMaximumAdditionFlux()
potentialInfiltrationFlux=min(potentialHortonianInfiltrationFlux,maximumSaturatedOverlandFlowInfiltrationFlux)
# abstraction from surface water
potentialAbstractionFromSurfaceWaterFlux=potentialToSurfaceStoreFlux + potentialInfiltrationFlux
actualAbstractionFromSurfaceWaterFlux,runoffCubicMetrePerHour=self.d_runoffAccuthreshold.update( \
totalToSurfaceFlux,potentialAbstractionFromSurfaceWaterFlux)
potentialOutSurfaceStoreFlux=self.d_surfaceStore.potentialOutFlux()
# infiltration
availableForInfiltrationFlux=potentialOutSurfaceStoreFlux+actualAbstractionFromSurfaceWaterFlux
availableForInfiltrationNotExceedingMaximumSaturatedOverlandFlowFlux=min( \
availableForInfiltrationFlux,maximumSaturatedOverlandFlowInfiltrationFlux)
actualInfiltrationFlux=self.d_infiltrationonlyksat.update( \
availableForInfiltrationNotExceedingMaximumSaturatedOverlandFlowFlux)
# surface store
surfaceStoreChange=actualAbstractionFromSurfaceWaterFlux-actualInfiltrationFlux
self.d_surfaceStore.update(surfaceStoreChange)
actualAdditionFlux=self.d_subsurfaceWaterOneLayer.addWater(actualInfiltrationFlux)
# empty it again
self.d_surfaceStore.emptyIt()
# surface wash
self.runoffMetreWaterDepthPerHour=runoffCubicMetrePerHour/cellarea()
netDeposition, netDepositionMetre, lateralFluxKg, totalDetachKgPerCell, transportCapacityKgPerCell= \
self.d_soilwashMMF.calculateWash( \
self.runoffMetreWaterDepthPerHour,rainfallFlux,throughfallFlux)
# LET OP: dit is metre flux, maar dat zou het zijn als er slechts 1 regenbui is per jaar
# het is dus de ene week uitgemiddeld over een jaar
# om echt iets te krijgen met een eenheid m/jaar (dwz wat 'zou' de depositie zijn
# als dit event elke week zou optreden), moet dit keer 52 weken
# hetzelfde geldt voor actual deposition flux hieronder
netDepositionMetreFlux=netDepositionMetre/self.timeStepDurationRegolithInYears
##LDD, surface##
if cfg.changeGeomorphology:
actualDepositionFlux=self.d_regolithdemandbedrock.updateWithDeposition(netDepositionMetreFlux)
regolithThickness,demOfBedrock,dem,bedrockLdd,surfaceLdd=self.d_regolithdemandbedrock.getRegolithProperties()
amountOfMoistureThickNetAdded=self.d_subsurfaceWaterOneLayer.updateRegolithThickness(regolithThickness)
self.d_soilwashMMF.setSurfaceProperties(surfaceLdd,dem)
self.d_runoffAccuthreshold.setSurfaceProperties(surfaceLdd)
else:
# surface wash
netDeposition, netDepositionMetre, lateralFluxKg, totalDetachKgPerCell, transportCapacityKgPerCell= \
self.d_soilwashMMF.noWash()
actualDepositionFlux=spatial(scalar(0))
self.runoffMetreWaterDepthPerHour=scalar(0)
if cfg.changeGeomorphology:
# random noise
netDepositionMetreNoiseFlux=normal(1)/5000
##LDD, surface##
actualDepositionNoiseFlux=self.d_regolithdemandbedrock.updateWithDeposition(netDepositionMetreNoiseFlux)
regolithThickness,demOfBedrock,dem,bedrockLdd,surfaceLdd=self.d_regolithdemandbedrock.getRegolithProperties()
# potential evapotranspiration, m/hour
fWaterPotential=self.d_subsurfaceWaterOneLayer.getFWaterPotential()
potentialEvapotranspirationFlux=self.d_evapotranspirationSimple.potentialEvapotranspiration(fWaterPotential,self.biomass)
# evapotranspirate first from interception store
# assume this does not depend on vegetation, and does not influence transpiration
# assume it immediately empties (ie, within a week)
potentialEvaporationFromInterceptionStore=99999.9
actualAbstractionFluxFromInterceptionStore=self.d_interceptionuptomaxstore.abstractWater( \
potentialEvaporationFromInterceptionStore)
# evapotranspirate from subsurface store
potentialEvapotranspirationFluxFromSubsurface= \
max(0.0,potentialEvapotranspirationFlux)
self.actualAbstractionFluxFromSubsurface= \
self.d_subsurfaceWaterOneLayer.abstractWater(potentialEvapotranspirationFluxFromSubsurface)
# lateral flow in subsurface and upward seepage from subsurfacestore
# typically switched off and never tested
##self.d_exchangevariables.upwardSeepageFlux=self.d_subsurfaceWaterOneLayer.lateralFlow()
#self.checkBudgets(self.currentSampleNumber(), self.currentTimeStep())
#self.printMemberVariables()
####
# geomorpology
####
if cfg.changeGeomorphology and (self.currentTimeStep() % 52 == 0):
# bedrock weathering
regolithThickness,demOfBedrock,dem,bedrockLdd,surfaceLdd=self.d_regolithdemandbedrock.getRegolithProperties()
bedrockWeatheringFlux=self.d_bedrockweathering.weatheringRate(regolithThickness)
###LDD, bedrock###
self.d_regolithdemandbedrock.updateWithBedrockWeathering(bedrockWeatheringFlux)
# creep
regolithThickness,demOfBedrock,dem,bedrockLdd,surfaceLdd=self.d_regolithdemandbedrock.getRegolithProperties()
newRegolithThickness,outflow,flowOverBoundaries,correctedFactor,amountX,amountY,inflowX,inflowY= \
self.d_creep.diffuse(regolithThickness,dem,1)
self.creepDeposition=newRegolithThickness-regolithThickness
###LDD, surface###
self.d_regolithdemandbedrock.setNewRegolith(newRegolithThickness)
# update bedrock with baselevel change
baselevel=self.d_baselevel.getBaselevel(self.currentTimeStep())
###LDD, surface, bedrock###
self.d_regolithdemandbedrock.setBaselevel(baselevel)
# update subsurface store with new regolith thickness
regolithThickness,demOfBedrock,dem,bedrockLdd,surfaceLdd=self.d_regolithdemandbedrock.getRegolithProperties()
amountOfMoistureThickNetAdded=self.d_subsurfaceWaterOneLayer.updateRegolithThickness(regolithThickness)
# no lateral flow, so bedrock does not need to be updated
# self.d_subsurfaceWaterOneLayer=updateBedrock(self,bedRockLdd,demOfBedrock)
# update soil wash and runoff with new surface properties
self.d_soilwashMMF.setSurfaceProperties(surfaceLdd,dem)
self.d_runoffAccuthreshold.setSurfaceProperties(surfaceLdd)
# option to do a test run with a very thin regolith
#print 'test with thin regolith'
#if self.currentTimeStep() == 6000:
# self.d_regolithdemandbedrock.setNewRegolith(spatial(scalar(0.001)))
# reports
self.reportComponentsDynamic()
#self.printComponentsDynamic()
############
# statistics
############
calculateStats = (self.currentTimeStep()% cfg.intervalForStatsCalculated ) == 0
boundVector=(30.5,40.5)
# SOIL MOISTURE
self.d_subsurfaceWaterOneLayer.calculateSoilMoistureFraction()
variable=self.d_subsurfaceWaterOneLayer.soilMoistureFraction
variableSampled=ifthen(self.someLocs, variable)
self.historyOfSoilMoistureFraction=generalfunctions.keepHistoryOfMaps(self.historyOfSoilMoistureFraction, \
variableSampled, \
self.durationHistory)
stackOfMapsAsListVariable=list(self.historyOfSoilMoistureFraction)
if calculateStats:
if cfg.variances:
# temporal
dist,gamma=generalfunctions.experimentalVariogramValuesInTime(stackOfMapsAsListVariable,list(boundVector))
numpy.savetxt(generateNameST('sfT',self.currentSampleNumber(),self.currentTimeStep()),numpy.array(gamma))
# spatial
dist,gamma=generalfunctions.experimentalVariogramValues(stackOfMapsAsListVariable,boundVector,1,1,'test',2.0)
numpy.savetxt(generateNameST('sfS',self.currentSampleNumber(),self.currentTimeStep()),numpy.array(gamma))
# mean
#meanVariable=maptotal(variable)/self.numberOfCellsOnMap
meanVariable=areaaverage(variable,self.zoneMap)
generalfunctions.reportLocationsAsNumpyArray(self.aLocation,meanVariable,'sfA', \
self.currentSampleNumber(),self.currentTimeStep())
# BIOMASS
variable=self.d_biomassModifiedMay.biomass
variableSampled=ifthen(self.someLocs, variable)
#self.grazingRate=self.grazingRate+0.25*(0.0000000375/52.0)
self.historyOfBiomass=generalfunctions.keepHistoryOfMaps(self.historyOfBiomass, \
variableSampled, \
self.durationHistory)
stackOfMapsAsListVariable=list(self.historyOfBiomass)
if calculateStats:
if cfg.variances:
# temporal
dist,gamma=generalfunctions.experimentalVariogramValuesInTime(stackOfMapsAsListVariable,list(boundVector))
numpy.savetxt(generateNameST('bioT',self.currentSampleNumber(),self.currentTimeStep()),numpy.array(gamma))
# spatial
dist,gamma=generalfunctions.experimentalVariogramValues(stackOfMapsAsListVariable,boundVector,1,1,'test',2.0)
numpy.savetxt(generateNameST('bioS',self.currentSampleNumber(),self.currentTimeStep()),numpy.array(gamma))
# mean
#meanVariable=maptotal(variable)/self.numberOfCellsOnMap
meanVariable=areaaverage(variable,self.zoneMap)
generalfunctions.reportLocationsAsNumpyArray(self.aLocation,meanVariable,'bioA', \
self.currentSampleNumber(),self.currentTimeStep())
# REGOLITH THICKNESS
variable=self.d_regolithdemandbedrock.regolithThickness
variableSampled=ifthen(self.someLocs, variable)
self.historyOfRegolithThickness=generalfunctions.keepHistoryOfMaps(self.historyOfRegolithThickness, \
variableSampled, \
self.durationHistory)
stackOfMapsAsListVariable=list(self.historyOfRegolithThickness)
if calculateStats:
if cfg.variances:
# temporal
dist,gamma=generalfunctions.experimentalVariogramValuesInTime(stackOfMapsAsListVariable,list(boundVector))
numpy.savetxt(generateNameST('regT',self.currentSampleNumber(),self.currentTimeStep()),numpy.array(gamma))
# spatial
dist,gamma=generalfunctions.experimentalVariogramValues(stackOfMapsAsListVariable,boundVector,1,1,'test',2.0)
numpy.savetxt(generateNameST('regS',self.currentSampleNumber(),self.currentTimeStep()),numpy.array(gamma))
# mean
#meanVariable=maptotal(variable)/self.numberOfCellsOnMap
meanVariable=areaaverage(variable,self.zoneMap)
generalfunctions.reportLocationsAsNumpyArray(self.aLocation,meanVariable,'regA', \
self.currentSampleNumber(),self.currentTimeStep())
# DEM
variable=self.d_regolithdemandbedrock.dem
variableSampled=ifthen(self.someLocs, variable)
self.historyOfDem=generalfunctions.keepHistoryOfMaps(self.historyOfDem, \
variableSampled, \
self.durationHistory)
stackOfMapsAsListVariable=list(self.historyOfDem)
if calculateStats:
if cfg.variances:
# temporal
dist,gamma=generalfunctions.experimentalVariogramValuesInTime(stackOfMapsAsListVariable,list(boundVector))
numpy.savetxt(generateNameST('demT',self.currentSampleNumber(),self.currentTimeStep()),numpy.array(gamma))
# spatial
dist,gamma=generalfunctions.experimentalVariogramValues(stackOfMapsAsListVariable,boundVector,1,1,'test',2.0)
numpy.savetxt(generateNameST('demS',self.currentSampleNumber(),self.currentTimeStep()),numpy.array(gamma))
# mean
#meanVariable=maptotal(variable)/self.numberOfCellsOnMap
meanVariable=areaaverage(variable,self.zoneMap)
generalfunctions.reportLocationsAsNumpyArray( \
self.aLocation,meanVariable,'demA',self.currentSampleNumber(),self.currentTimeStep())
# discharge
downstreamEdge=generalfunctions.edge(self.clone,2,0)
pits=pcrne(pit(self.d_runoffAccuthreshold.ldd),0)
outflowPoints=pcrand(downstreamEdge,pits)
totQ=ifthen(self.clone,maptotal(ifthenelse(outflowPoints,self.d_runoffAccuthreshold.RunoffCubicMetrePerHour,scalar(0))))
variable=totQ
variableSampled=ifthen(self.someLocs, variable)
self.historyOfTotQ=generalfunctions.keepHistoryOfMaps(self.historyOfTotQ, \
variableSampled, \
self.durationHistory)
stackOfMapsAsListVariable=list(self.historyOfTotQ)
if calculateStats:
if cfg.variances:
# temporal
dist,gamma=generalfunctions.experimentalVariogramValuesInTime(stackOfMapsAsListVariable,list(boundVector))
numpy.savetxt(generateNameST('qT',self.currentSampleNumber(),self.currentTimeStep()),numpy.array(gamma))
# mean
generalfunctions.reportLocationsAsNumpyArray(self.aLocation,totQ,'qA',self.currentSampleNumber(),self.currentTimeStep())
# grazing rate
if calculateStats:
generalfunctions.reportLocationsAsNumpyArray( \
self.aLocation,spatial(scalar(self.grazingRate)),'gA',self.currentSampleNumber(),self.currentTimeStep())
# some extra outputs
if calculateStats:
# growth part
meanVariable=areaaverage(self.d_biomassModifiedMay.growthPart,self.zoneMap)
generalfunctions.reportLocationsAsNumpyArray( \
self.aLocation,meanVariable,'gpA',self.currentSampleNumber(),self.currentTimeStep())
# grazing part
meanVariable=0.0-areaaverage(spatial(self.d_biomassModifiedMay.grazing),self.zoneMap)
generalfunctions.reportLocationsAsNumpyArray( \
self.aLocation,meanVariable,'grA',self.currentSampleNumber(),self.currentTimeStep())
# net growth
meanVariable=areaaverage(self.d_biomassModifiedMay.netGrowth,self.zoneMap)
generalfunctions.reportLocationsAsNumpyArray( \
self.aLocation,meanVariable,'grNA',self.currentSampleNumber(),self.currentTimeStep())
# net deposition
#meanVariable=areaaverage(netDepositionMetre,self.zoneMap)
meanVariable=areaaverage(actualDepositionFlux,self.zoneMap)
generalfunctions.reportLocationsAsNumpyArray( \
self.aLocation,meanVariable,'depA',self.currentSampleNumber(),self.currentTimeStep())
# net weathering
meanVariable=areaaverage(self.d_bedrockweathering.weatheringMetrePerYear,self.zoneMap)
generalfunctions.reportLocationsAsNumpyArray( \
self.aLocation,meanVariable,'weaA',self.currentSampleNumber(),self.currentTimeStep())
# net creep deposition
meanVariable=areaaverage(self.creepDeposition,self.zoneMap)
generalfunctions.reportLocationsAsNumpyArray( \
self.aLocation,meanVariable,'creA',self.currentSampleNumber(),self.currentTimeStep())
if self.currentTimeStep() == cfg.numberOfTimeSteps:
name=generateNameS('grazing', self.currentSampleNumber())
numpy.save(name,self.grazingPressureArray)
def postmcloop(self):
import generalfunctions
names=['grA', 'bioA', 'sfA', 'regA', 'demA', 'qA','gA','gpA', 'grNA','depA','weaA','creA']
for name in names:
aVariable = generalfunctions.openSamplesAndTimestepsAsNumpyArraysAsNumpyArray( \
name,range(1,cfg.nrOfSamples+1),timeStepsWithStatsCalculated)
numpy.save(name,aVariable)
if cfg.variances:
names=['sfT', 'sfS', 'bioT', 'bioS', 'regT', 'regS', 'demT', 'demS', 'qT']
aVariable = generalfunctions.openSamplesAndTimestepsAsNumpyArraysAsNumpyArray( \
name,range(1,cfg.nrOfSamples+1),timeStepsWithStatsCalculated)
numpy.save(name,aVariable)
self.a='jan'
def createInstancesPremcloop(self):
pass
def createInstancesInitial(self):
import generalfunctions
# basis:
#timeStepsToReportAll = range(100,cfg.numberOfTimeSteps + 1,100)
# varianten
#timeStepsToReportAll = range(0,cfg.numberOfTimeSteps + 1,52)
#timeStepsToReportAll = range(1000,cfg.numberOfTimeSteps + 1,1000)
#timeStepsToReportAll = range(2,cfg.numberOfTimeSteps + 1,2)
#timeStepsToReportAll = range(100,cfg.numberOfTimeSteps + 1,100)
timeStepsToReportAll = range(100,cfg.numberOfTimeSteps + 1,100)
#timeStepsToReportAll = range(1,cfg.numberOfTimeSteps + 1,1)
timeStepsToReportSome = range(3000,cfg.numberOfTimeSteps + 1,100)
# class for exchange variables in initial and dynamic
# introduced to make filtering possible
self.d_exchangevariables=exchangevariables_weekly.ExchangeVariables( \
timeStepsToReportSome, \
cfg.exchange_report_rasters
)
# base level
#deterministicDem=(ycoordinate(1)*0.4)
deterministicDem=scalar('inputs_weekly/demini.map')
#dem=deterministicDem+uniform(1)/2
dem=deterministicDem
baselevelRise=-0.0001
self.d_baselevel=baselevel.Baselevel( \
generalfunctions.bottom(self.clone), \
deterministicDem, \
baselevelRise, \
self.timeStepDuration/(365.0*24.0), \
timeStepsToReportAll, \
cfg.baselevel_report_rasters)
weatheringRateBareBedrock=0.0005
weatheringExponentParameter=4.0
self.d_bedrockweathering=bedrockweathering.BedrockWeathering( \
weatheringRateBareBedrock, \
weatheringExponentParameter, \
timeStepsToReportAll,\
cfg.bedrockweathering_report_rasters)
steadyStateSoilDepth=self.d_bedrockweathering.steadyStateSoilDepth(0-baselevelRise)
self.report(steadyStateSoilDepth,'sssd')
# regolith
regolithThickness=spatial(steadyStateSoilDepth)
#regolithThickness=spatial(scalar(0.49))
#print "LET OP REG THICKNESS VAST GEZET OP 0.49!!!!!!!!!"
self.timeStepDurationRegolithInYears=1.0
self.d_regolithdemandbedrock=regolith.RegolithDemAndBedrock(
dem, \
regolithThickness, \
self.timeStepDurationRegolithInYears, \
timeStepsToReportAll, \
cfg.regolith_report_rasters)
regolithThickness,demOfBedrock,dem,bedrockLdd,surfaceLdd=self.d_regolithdemandbedrock.getRegolithProperties()
report(regolithThickness,'regIni.map')
# biomass
initialBiomass=2.0
waterUseEfficiency=5.0
maintenanceRate=0.5/(365.0*24.0)
# original
gamma=0.004 # runoff
## gamma zero
#gamma=0.0001 # runoff
## gamma low
#gamma=0.001 # runoff
## gamma medium
#gamma=0.002 # runoff
alpha = 0.4 # grazing
dispersion = 0.01/(365.0*24)
runoff = 0.0 # niet gebruikt ! (?) kan dus weg
sdOfNoise = 0.000000000001
LAIPerBiomass = 2.5
self.d_biomassModifiedMay = biomassmodifiedmay.BiomassModifiedMay( \
initialBiomass, \
waterUseEfficiency, \
maintenanceRate, \
gamma, \
alpha, \
dispersion, \
runoff, \
sdOfNoise, \
LAIPerBiomass, \
self.timeStepDuration, \
timeStepsToReportAll, \
cfg.biomassmodifiedmay_report_rasters)
# precipitation
# scenario: original
probabilityOfARainstorm=0.4
durationOfRainstorm=cfg.theDurationOfRainstorm
expectedRainfallIntensity=0.002
gammaShapeParameter=100
# scenario: higher intensity
#probabilityOfARainstorm=0.4*0.75
#durationOfRainstorm=cfg.theDurationOfRainstorm
#expectedRainfallIntensity=0.002/0.75
#gammaShapeParameter=100
# scenario: much higher intensity
#probabilityOfARainstorm=0.4*0.25
#durationOfRainstorm=cfg.theDurationOfRainstorm
#expectedRainfallIntensity=0.002/0.25
#gammaShapeParameter=100
# scenario: less rainstorms, longer duration
#probabilityOfARainstorm=0.4*0.50
#durationOfRainstorm=cfg.theDurationOfRainstorm/0.50
#expectedRainfallIntensity=0.002
#gammaShapeParameter=100
# scenario: shorter rainstorm
#probabilityOfARainstorm=0.4
#durationOfRainstorm=cfg.theDurationOfRainstorm/2.0
#expectedRainfallIntensity=0.002*2.0
#gammaShapeParameter=100
# scenario: more rainstorms (and also more rain in total)
#probabilityOfARainstorm=0.999
#durationOfRainstorm=cfg.theDurationOfRainstorm
#expectedRainfallIntensity=0.002
#gammaShapeParameter=100
# scenario: all more
#probabilityOfARainstorm=0.4
#durationOfRainstorm=cfg.theDurationOfRainstorm*2.0
#expectedRainfallIntensity=0.004
#gammaShapeParameter=100
self.d_rainfalleventsfromgammadistribution= \
rainfalleventsfromgammadistribution.RainfallEventsFromGammaDistribution( \
probabilityOfARainstorm, \
durationOfRainstorm, \
expectedRainfallIntensity, \
gammaShapeParameter, \
timeStepsToReportAll,
cfg.rainfalleventsfromgammadistribution_report_rasters)
# interception
initialLeafAreaIndex=initialBiomass*LAIPerBiomass
initialInterceptionStore=scalar(0.000001)
gapFraction,maximumInterceptionStore=calculateGapFractionAndMaxIntStoreFromLAI(initialLeafAreaIndex)
self.d_interceptionuptomaxstore=interceptionuptomaxstore.InterceptionUpToMaxStore( \
spatial(ldd(5)), \
initialInterceptionStore, \
maximumInterceptionStore, \
gapFraction, \
cfg.calculateUpstreamTotals, \
durationOfRainstorm,
timeStepsToReportAll,
cfg.interception_report_rasters)
# surface store
initialSurfaceStore=scalar(0.0)
maxSurfaceStore=scalar(0.0001)
self.d_surfaceStore=surfacestore.SurfaceStore( \
initialSurfaceStore, \
maxSurfaceStore, \
durationOfRainstorm,
timeStepsToReportAll,
cfg.surfacestore_report_rasters)
# infiltration
bareSoilSaturatedConductivityFlux=scalar(0.0001)
#maxSaturatedConductivityFluxFromVegetation=scalar(0.01)
maxSaturatedConductivityFluxFromVegetation=scalar(0.1)
biomassHalfSaturation=scalar(1.0)
ksat=bareSoilSaturatedConductivityFlux
self.d_infiltrationonlyksat=infiltrationonlyksat.InfiltrationOnlyKsat( \
ksat, \
bareSoilSaturatedConductivityFlux, \
maxSaturatedConductivityFluxFromVegetation, \
biomassHalfSaturation, \
durationOfRainstorm, \
timeStepsToReportAll, \
cfg.infiltration_report_rasters)
# subsurface water
# loam values from Niko Wanders, see mac disk articles/crittransGeom table
#initialSoilMoistureFraction=scalar(0.03)
initialSoilMoistureFraction=scalar(0.43)
soilPorosityFraction= scalar(0.43)
fieldCapacityFraction=scalar(0.22)
limitingPointFraction=scalar(0.05)
wiltingPointFraction= scalar(0.019)
saturatedConductivityMetrePerDay=generalfunctions.mapuniformBounds( \
2,8,scalar(12.5),cfg.createRealizations)
self.d_subsurfaceWaterOneLayer=subsurfacewateronelayer.SubsurfaceWaterOneLayer(
bedrockLdd,
demOfBedrock,
regolithThickness,
initialSoilMoistureFraction,
soilPorosityFraction,
wiltingPointFraction,
fieldCapacityFraction,
limitingPointFraction,
saturatedConductivityMetrePerDay,
cfg.calculateUpstreamTotals,
self.timeStepDurationHours,
timeStepsToReportAll,
cfg.subsurface_report_rasters)
# evapotranspiration
beta=1.0
maximumEvapotranspirationFlux=0.8/(365.0*24.0)
self.d_evapotranspirationSimple=evapotranspirationsimple.EvapotranspirationSimple( \
self.timeStepDuration, \
beta, \
maximumEvapotranspirationFlux, \
timeStepsToReportAll, \
cfg.evapotranspirationsimple_report_rasters) \
# runoff
self.d_runoffAccuthreshold=runoffaccuthreshold.RunoffAccuthreshold(
surfaceLdd,
durationOfRainstorm,
timeStepsToReportAll,
cfg.runoff_report_rasters)
# soilwash
plantHeightMetres=5.0
stoneCoverFraction=0.1
vegetationCoverOfSoilFraction=0.1
manningsN=0.03 # 'original'
# standard erosion scenario
detachabilityOfSoilRaindrops=1.6 # 'original' (used for all scenarios)
detachabilityOfSoilRunoff=6.4 #'original'
## more erosion scenario
#detachabilityOfSoilRaindrops=16
#detachabilityOfSoilRunoff=64
self.d_soilwashMMF=soilwashMMF.SoilWashMMF( \
surfaceLdd,
dem,
durationOfRainstorm,
plantHeightMetres,
detachabilityOfSoilRaindrops,
stoneCoverFraction,
detachabilityOfSoilRunoff,
vegetationCoverOfSoilFraction,
manningsN,
soilPorosityFraction,
timeStepsToReportAll,
cfg.soilwashMMF_report_rasters)
# creep
diffusion=0.01
self.d_creep=creep.Creep( \
dem, \
self.timeStepDurationRegolithInYears, \
diffusion, \
timeStepsToReportAll, \
cfg.creep_report_rasters)
def reportComponentsDynamic(self):
components =[ \
self.d_exchangevariables, \
self.d_evapotranspirationSimple, \
self.d_regolithdemandbedrock, \
self.d_bedrockweathering,
self.d_baselevel, \
self.d_rainfalleventsfromgammadistribution , \
self.d_interceptionuptomaxstore, \
self.d_surfaceStore, \
self.d_infiltrationonlyksat, \
self.d_runoffAccuthreshold, \
self.d_subsurfaceWaterOneLayer, \
self.d_soilwashMMF, \
self.d_creep,
self.d_biomassModifiedMay
]
for component in components:
component.reportAsMaps(self.currentSampleNumber(), self.currentTimeStep())
def printMemberVariables(self):
import generalfunctions
components =[ \
self.d_exchangevariables, \
self.d_interceptionuptomaxstore, \
self.d_surfaceStore, \
self.d_infiltrationonlyksat, \
self.d_runoffAccuthreshold, \
self.d_subsurfaceWaterOneLayer
]
for component in components:
generalfunctions.printMemberVariables(component)
def printComponentsDynamic(self):
self.d_dateTimePCRasterPython.printit()
def initializeTime(self,startTimeYear, startTimeMonth, startTimeDay, timeStepDurationHours):
startTime=datetime.datetime(year=startTimeYear, month=startTimeMonth, day=startTimeDay)
self.timeStepDurationHours = timeStepDurationHours
self.timeStepDatetimeFormat=datetime.timedelta(hours=self.timeStepDurationHours)
self.d_dateTimePCRasterPython=datetimePCRasterPython.DatetimePCRasterPython \
(startTime, self.timeStepDatetimeFormat)
def checkBudgets(self,currentSampleNumber,currentTimeStep):
increaseInPrecipitationStore=0.0-self.d_exchangevariables.cumulativePrecipitation
report(increaseInPrecipitationStore,generateNameST('incP', currentSampleNumber, currentTimeStep))
increaseInInterceptionStore=self.d_interceptionuptomaxstore.budgetCheck(currentSampleNumber, currentTimeStep)
report(increaseInInterceptionStore,generateNameST('incI', currentSampleNumber, currentTimeStep))
increaseInSurfaceStore=self.d_surfaceStore.budgetCheck(currentSampleNumber, currentTimeStep)
report(increaseInSurfaceStore,generateNameST('incS', currentSampleNumber, currentTimeStep))
increaseInSurfaceStoreQM=catchmenttotal(increaseInSurfaceStore,self.ldd)*cellarea()
report(increaseInSurfaceStoreQM,generateNameST('testb', currentSampleNumber, currentTimeStep))
# let op: infiltration store is directly passed to subsurface store, thus is not a real store
increaseInInfiltrationStore=self.d_infiltrationonlyksat.budgetCheck(currentSampleNumber, currentTimeStep)
increaseInSubSurfaceWaterStore,lateralFlowInSubsurfaceStore,abstractionFromSubSurfaceWaterStore= \
self.d_subsurfaceWaterOneLayer.budgetCheck(currentSampleNumber , currentTimeStep)
increaseInSubSurfaceStoreQM=catchmenttotal(increaseInSubSurfaceWaterStore,self.ldd)*cellarea()
increaseInRunoffStoreCubicMetresInUpstreamArea=self.d_runoffAccuthreshold.budgetCheck()
totalIncreaseInStoresCubicMetresInUpstreamArea=0.0
stores=[increaseInPrecipitationStore, increaseInInterceptionStore, increaseInSurfaceStore, increaseInSubSurfaceWaterStore]
for store in stores:
increaseInStoreCubicMetresInUpstreamArea=catchmenttotal(store,self.ldd)*cellarea()
totalIncreaseInStoresCubicMetresInUpstreamArea=totalIncreaseInStoresCubicMetresInUpstreamArea+ \
increaseInStoreCubicMetresInUpstreamArea
report(totalIncreaseInStoresCubicMetresInUpstreamArea,generateNameST('inSt',currentSampleNumber,currentTimeStep))
report(increaseInRunoffStoreCubicMetresInUpstreamArea ,generateNameST('inRu',currentSampleNumber,currentTimeStep))
report(catchmenttotal(self.d_exchangevariables.upwardSeepageFlux,self.ldd)*cellarea(),generateNameST('inSe',currentSampleNumber,currentTimeStep))
# total budget is total increase in stores plus the upward seepage flux for each ts that is passed to the next
# timestep and thus not taken into account in the current timestep budgets
budget=totalIncreaseInStoresCubicMetresInUpstreamArea+increaseInRunoffStoreCubicMetresInUpstreamArea + \
lateralFlowInSubsurfaceStore*cellarea() + catchmenttotal(abstractionFromSubSurfaceWaterStore,self.ldd)*cellarea() + \
catchmenttotal(self.d_exchangevariables.upwardSeepageFlux,self.ldd)*cellarea()
report(budget,generateNameST('B-tot', currentSampleNumber, currentTimeStep))
budgetRel=budget/increaseInRunoffStoreCubicMetresInUpstreamArea
report(budgetRel,generateNameST('B-rel', currentSampleNumber, currentTimeStep))
## functions for particle filtering, not used/tested
def suspend(self):
import generalfunctions
if self.currentTimeStep() != cfg.numberOfTimeSteps:
self.timeStepForResume=self.currentTimeStep()
components =[ self.d_exchangevariables, \
self.d_interceptionuptomaxstore, \
self.d_surfaceStore, \
self.d_infiltrationonlyksat, \
self.d_runoffAccuthreshold, \
self.d_subsurfaceWaterOneLayer]
for component in components:
generalfunctions.reportMemberVariablesOfAClassForSuspend(component,self.currentTimeStep(),self.currentSampleNumber())
def updateWeight(self):
print('#### UPDATEWEIGHTING')
print('filter timestep ', self._d_filterTimesteps[self.filterPeriod()-4])
print('lijst ', self._d_filterTimesteps)
print('filter sample ', self.currentSampleNumber())
modelledData=self.readmap('Rqs')
observations=self.readDeterministic('observations/Rqs')
#observations=ifthen(pit(self.ldd) != 0,syntheticData)
measurementErrorSD=0.4*observations+1.0
sum=maptotal(((modelledData-observations)**2)/(2.0*(measurementErrorSD**2)))
weight=exp(-sum)
weightFloatingPoint, valid=cellvalue(weight,1)
return weightFloatingPoint
def resume(self):
print('#### RESUMING')
print(self._d_filterTimesteps)
print(self.filterPeriod())
print(self._d_filterTimesteps[self.filterPeriod()-2])
import generalfunctions
# rerun initial
# self.timeStepDuration = 1.0 plain wrong
self.initializeTime(2001,2,26,self.timeStepDuration)
self.createInstancesInitial()
self.d_exchangevariables.upwardSeepageFlux=scalar(0)
#self.d_exchangevariables.evapFromSoilMultiplier=scalar(1)
self.d_exchangevariables.cumulativePrecipitation=scalar(0)
# resume time information
self.d_dateTimePCRasterPython.resume(self._d_filterTimesteps[self.filterPeriod()-2])
components =[self.d_exchangevariables, \
self.d_interceptionuptomaxstore, \
self.d_surfaceStore, \
self.d_infiltrationonlyksat, \
self.d_runoffAccuthreshold, \
self.d_subsurfaceWaterOneLayer]
for component in components:
generalfunctions.readMemberVariablesOfAClassForResume( \
component,self._d_filterTimesteps[self.filterPeriod()-2],self.currentSampleNumber())
print('removeing files')
# remove files used to resume
for filename in glob.glob(str(self.currentSampleNumber()) + '/stateVar/*/*'):
os.remove(filename)
print('end removing files')
if cfg.filtering:
myModel = CatchmentModel()
dynamicModel = DynamicFramework(myModel,cfg.numberOfTimeSteps)
mcModel = MonteCarloFramework(dynamicModel, cfg.nrOfSamples)
mcModel.setForkSamples(True,12)
#pfModel = SequentialImportanceResamplingFramework(mcModel)
pfModel = ResidualResamplingFramework(mcModel)
#filterTimesteps=range(20,1000,20)
filterTimesteps=range(3000,cfg.numberOfTimeSteps,100)
#filterTimesteps=[20,30,40]
pfModel.setFilterTimesteps(filterTimesteps)
pfModel.run()
else:
myModel = CatchmentModel()
dynamicModel = DynamicFramework(myModel, cfg.numberOfTimeSteps)
mcModel = MonteCarloFramework(dynamicModel, cfg.nrOfSamples)
mcModel.setForkSamples(True,10)
mcModel.run()