├── modules ├── __init__.py ├── routing.py ├── groundwater.py ├── dynamic_veg.py ├── inca.py ├── musle.py ├── hspf.py ├── snow.py ├── reservoirs.py ├── dhsvm.py ├── shetran.py ├── lakes.py ├── sediment_transport.py ├── mmf.py └── advanced_routing.py ├── .gitignore ├── resorder.txt ├── utilities ├── timecalc.py ├── pedotransfer.py ├── reporting.py └── netcdf2PCraster.py ├── hargreaves.py ├── ET.py ├── subzone.py ├── README.md ├── rootzone.py ├── reporting.csv └── LICENSE.TXT /modules/__init__.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | *.pyc 2 | *.pyo -------------------------------------------------------------------------------- /resorder.txt: -------------------------------------------------------------------------------- 1 | order steps 2 | 1 0 3 | 2 0 4 | 3 0 5 | 6 0 6 | 9 0 7 | 10 0 8 | 11 0 9 | 13 0 10 | 14 0 11 | 15 0 12 | 16 0 13 | 17 0 14 | 20 0 15 | 22 0 16 | 24 0 17 | 25 0 18 | 26 0 19 | 27 0 20 | 28 0 21 | 30 0 22 | 32 0 23 | 33 0 24 | 4 1 25 | 5 1 26 | 8 1 27 | 18 1 28 | 29 1 29 | 31 1 30 | 7 2 31 | 19 2 32 | 12 3 33 | 21 3 34 | 23 4 35 | 34 5 36 | -------------------------------------------------------------------------------- /utilities/timecalc.py: -------------------------------------------------------------------------------- 1 | # The Spatial Processes in HYdrology (SPHY) model: 2 | # A spatially distributed hydrological model 3 | # Copyright (C) 2013-2019 FutureWater 4 | # Email: sphy@futurewater.nl 5 | # 6 | # Authors (alphabetical order): 7 | # P. Droogers, J. Eekhout, W. Immerzeel, S. Khanal, A. Lutz, G. Simons, W. Terink 8 | # 9 | # This program is free software: you can redistribute it and/or modify 10 | # it under the terms of the GNU General Public License as published by 11 | # the Free Software Foundation, either version 3 of the License, or 12 | # (at your option) any later version. 13 | # 14 | # This program is distributed in the hope that it will be useful, 15 | # but WITHOUT ANY WARRANTY; without even the implied warranty of 16 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 17 | # GNU General Public License for more details. 18 | # 19 | # You should have received a copy of the GNU General Public License 20 | # along with this program. If not, see . 21 | 22 | 23 | #-Function to return the julian day of the year 24 | def julian(self): 25 | y= self.curdate.year 26 | start= self.datetime.datetime(y,1,1).toordinal() 27 | current= self.curdate.toordinal() 28 | day= current-start+1 29 | return day, 1 30 | 31 | #-Function to calculate the number of timesteps for the model run 32 | def timesteps(self): 33 | nrTimeSteps = (self.enddate - self.startdate).days + 1 34 | print('Running SPHY for '+str(self.startdate.day)+'-'+str(self.startdate.month)+'-'+str(self.startdate.year)+' through '+str(self.enddate.day)+'-'+str(self.enddate.month)+'-'+str(self.enddate.year)) 35 | print('with '+str(nrTimeSteps)+' daily timesteps') 36 | return nrTimeSteps -------------------------------------------------------------------------------- /hargreaves.py: -------------------------------------------------------------------------------- 1 | # The Spatial Processes in HYdrology (SPHY) model: 2 | # A spatially distributed hydrological model 3 | # Copyright (C) 2013-2025 FutureWater 4 | # Email: sphy@futurewater.nl 5 | # 6 | # Authors (alphabetical order): 7 | # P. Droogers, J. Eekhout, A. Fernandez-Rodriguez, W. Immerzeel, S. Khanal, A. Lutz, T. Schults, G. Simons, W. Terink. 8 | # 9 | # This program is free software: you can redistribute it and/or modify 10 | # it under the terms of the GNU General Public License as published by 11 | # the Free Software Foundation, either version 3 of the License, or 12 | # (at your option) any later version. 13 | # 14 | # This program is distributed in the hope that it will be useful, 15 | # but WITHOUT ANY WARRANTY; without even the implied warranty of 16 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 17 | # GNU General Public License for more details. 18 | # 19 | # You should have received a copy of the GNU General Public License 20 | # along with this program. If not, see . 21 | 22 | 23 | # -Extraterrestrial radiation 24 | def extrarad(self, pcr): 25 | DayNo = self.timecalc.julian(self)[0] 26 | LatRad = self.Lat * (self.pi / 180) 27 | dr = 1 + 0.033 * pcr.cos((2 * self.pi * DayNo) / 365) 28 | delta = 0.409 * pcr.sin(((2 * self.pi * DayNo) / 365) - 1.39) 29 | omegas = pcr.acos(-1 * pcr.tan(LatRad) * pcr.tan(delta)) 30 | Ra = ( 31 | ((24 * 60) / self.pi) 32 | * self.Gsc 33 | * dr 34 | * ( 35 | pcr.scalar(omegas) * pcr.sin(LatRad) * pcr.sin(delta) 36 | + pcr.cos(LatRad) * pcr.cos(delta) * pcr.sin(omegas) 37 | ) 38 | ) 39 | return Ra 40 | 41 | 42 | # -Modified Hargreaves for calculation of ETref 43 | def Hargreaves(pcr, ra, temp, tempmax, tempmin): 44 | ETref = pcr.max( 45 | 0.0023 * 0.408 * ra * (temp + 17.8) * (pcr.max(tempmax - tempmin, 0)) ** 0.5, 0 46 | ) 47 | return ETref 48 | -------------------------------------------------------------------------------- /ET.py: -------------------------------------------------------------------------------- 1 | # The Spatial Processes in HYdrology (SPHY) model: 2 | # A spatially distributed hydrological model 3 | # Copyright (C) 2013-2025 FutureWater 4 | # Email: sphy@futurewater.nl 5 | # 6 | # Authors (alphabetical order): 7 | # P. Droogers, J. Eekhout, A. Fernandez-Rodriguez, W. Immerzeel, S. Khanal, A. Lutz, T. Schults, G. Simons, W. Terink. 8 | # 9 | # This program is free software: you can redistribute it and/or modify 10 | # it under the terms of the GNU General Public License as published by 11 | # the Free Software Foundation, either version 3 of the License, or 12 | # (at your option) any later version. 13 | # 14 | # This program is distributed in the hope that it will be useful, 15 | # but WITHOUT ANY WARRANTY; without even the implied warranty of 16 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 17 | # GNU General Public License for more details. 18 | # 19 | # You should have received a copy of the GNU General Public License 20 | # along with this program. If not, see . 21 | 22 | 23 | # -Function to calculate the potential evapotranspiration 24 | def ETpot(etr, kc): 25 | etpot = etr * kc 26 | return etpot 27 | 28 | 29 | # -Function to calculate the actual evapotranspiration 30 | def ETact(pcr, etpot, rootwater, rootsat, etreddry, rainfrac): 31 | etredwet = pcr.ifthenelse(rootwater >= rootsat, pcr.scalar(0), 1) 32 | etact = pcr.ifthenelse( 33 | rainfrac > 0, pcr.min(etpot * etreddry * etredwet, rootwater), 0 34 | ) 35 | return etact 36 | 37 | 38 | # -Determine plant water stress for calculation of actual evapotranspiration 39 | def ks(self, pcr, etpot): 40 | TAW = self.RootField - self.RootDry 41 | p = pcr.max(pcr.min(self.PMap + 0.04 * (5 - etpot), 0.8), 0.1) 42 | RAW = TAW * p 43 | RootPWS = self.RootField - RAW 44 | Ks = pcr.max( 45 | pcr.min((self.RootWater - self.RootDry) / (RootPWS - self.RootDry), 1), 0 46 | ) 47 | return Ks 48 | -------------------------------------------------------------------------------- /subzone.py: -------------------------------------------------------------------------------- 1 | # The Spatial Processes in HYdrology (SPHY) model: 2 | # A spatially distributed hydrological model 3 | # Copyright (C) 2013-2025 FutureWater 4 | # Email: sphy@futurewater.nl 5 | # 6 | # Authors (alphabetical order): 7 | # P. Droogers, J. Eekhout, A. Fernandez-Rodriguez, W. Immerzeel, S. Khanal, A. Lutz, T. Schults, G. Simons, W. Terink. 8 | # 9 | # This program is free software: you can redistribute it and/or modify 10 | # it under the terms of the GNU General Public License as published by 11 | # the Free Software Foundation, either version 3 of the License, or 12 | # (at your option) any later version. 13 | # 14 | # This program is distributed in the hope that it will be useful, 15 | # but WITHOUT ANY WARRANTY; without even the implied warranty of 16 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 17 | # GNU General Public License for more details. 18 | # 19 | # You should have received a copy of the GNU General Public License 20 | # along with this program. If not, see . 21 | 22 | 23 | # -Function to calculate capillary rise 24 | def CapilRise(pcr, subfield, subwater, capmax, rootwater, rootsat, rootfield): 25 | subrelwat = pcr.max(pcr.min((subwater / subfield), 1), 0) 26 | rootrelwat = pcr.max(pcr.min((rootwater / rootfield), 1), 0) 27 | caprise = pcr.min(subwater, capmax * (1 - rootrelwat) * subrelwat) 28 | caprise = pcr.min( 29 | caprise, rootsat - rootwater 30 | ) # adding caprise can not exceed saturated rootwater content 31 | return caprise 32 | 33 | 34 | # -Function to calculate percolation from subsoil (only if groundwater module is used) 35 | def SubPercolation(pcr, subwater, subfield, subTT, gw, gwsat): 36 | subperc = pcr.ifthenelse( 37 | (gw < gwsat) & ((subwater - subfield) > 0), 38 | (subwater - subfield) * (1 - pcr.exp(-1 / subTT)), 39 | 0, 40 | ) 41 | return subperc 42 | 43 | 44 | # -Function to calculate drainage from subsoil (only if groundwater module is NOT used) 45 | def SubDrainage(pcr, subwater, subfield, subsat, drainvel, subdrainage, subTT): 46 | subexcess = pcr.max(subwater - subfield, 0) 47 | subexcessfrac = subexcess / (subsat - subfield) 48 | sublateral = subexcessfrac * drainvel 49 | subdrainage = (sublateral + subdrainage) * (1 - pcr.exp(-1 / subTT)) 50 | subdrainage = pcr.max(pcr.min(subdrainage, subwater), 0) 51 | return subdrainage 52 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Spatial Processes in HYdrology (SPHY) model 2 | Version 3.1 3 | 4 | The Spatial Processes in Hydrology (SPHY) model is a hydrological modeling tool suitable for a wide range of water resource management applications. SPHY is a state-of-the-art, easy to use, robust tool, that can be applied for operational as well as strategic decision support. The SPHY model has been applied and tested in various studies ranging from real-time soil moisture predictions in flat lands, to operational reservoir inflow forecasting applications in mountainous catchments, irrigation scenarios in the Nile Basin, and detailed climate change impact studies in the snow- and glacier-melt dominated the Himalayan region. 5 | 6 | With respect to version 3.0, the code in version 3.1 has an improved procedure for bias-correcting meteorological forcing and increased flexibility for defining simulation periods. 7 | 8 | Journal paper SPHY v2.0 9 | 14 | 15 | Acknowledgements
16 | The development and publication of the SPHY model source code, its binaries, GUIs, and case-studies has been supported through various (research) projects that were partly or completely funded by the following organizations: 17 |
    18 |
  • International Centre for Integrated Mountain Development (ICIMOD)
    • 19 |
  • European Space Agency (ESA)
    • 20 |
  • Asian Development Bank (ADB)
    • 21 |
  • World Bank
    • 22 |
  • Rijksdienst voor Ondernemend Nederland (RVO)
    • 23 |
  • NUFFIC
    • 24 |
25 | We are very grateful to these organizations that made the development of the SPHY model possible. 26 | We hope to continue to collaborate with these organizations in the future in order to further develop and improve the SPHY model and its interfaces. 27 | 28 |
Copyright
29 | Copyright (C) 2013-2025 FutureWater. The Spatial Processes in HYdrology (SPHY) model is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/. 30 | 31 | Contact: 32 | sphy@futurewater.nl 33 | -------------------------------------------------------------------------------- /rootzone.py: -------------------------------------------------------------------------------- 1 | # The Spatial Processes in HYdrology (SPHY) model: 2 | # A spatially distributed hydrological model 3 | # Copyright (C) 2013-2025 FutureWater 4 | # Email: sphy@futurewater.nl 5 | # 6 | # Authors (alphabetical order): 7 | # P. Droogers, J. Eekhout, A. Fernandez-Rodriguez, W. Immerzeel, S. Khanal, A. Lutz, T. Schults, G. Simons, W. Terink. 8 | # 9 | # This program is free software: you can redistribute it and/or modify 10 | # it under the terms of the GNU General Public License as published by 11 | # the Free Software Foundation, either version 3 of the License, or 12 | # (at your option) any later version. 13 | # 14 | # This program is distributed in the hope that it will be useful, 15 | # but WITHOUT ANY WARRANTY; without even the implied warranty of 16 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 17 | # GNU General Public License for more details. 18 | # 19 | # You should have received a copy of the GNU General Public License 20 | # along with this program. If not, see . 21 | 22 | 23 | # -Function to calculate surface runoff 24 | def RootRunoff(self, pcr, rainfrac, rain): 25 | # -Infiltration excess surface runoff 26 | if self.InfilFLAG == 1: 27 | # -Infiltration capacity, scaled based on rootwater content and ksat and corrected for paved surface 28 | Infil_cap = ( 29 | self.K_eff 30 | * self.RootKsat 31 | / 24 32 | * (1 + ((self.RootSat - self.RootWater) / self.RootSat)) ** self.Labda_Infil 33 | ) 34 | 35 | # -Infiltration 36 | Infil_excess = pcr.ifthenelse( 37 | (self.Alpha * rain) > Infil_cap, 38 | rain - ((self.Alpha * rain - Infil_cap) ** 2) / (self.Alpha**2 * rain), 39 | rain, 40 | ) 41 | Saturated_excess = self.RootSat - self.RootWater 42 | Infil = pcr.max(0, pcr.min(Infil_excess, Saturated_excess)) * ( 43 | 1 - self.pavedFrac 44 | ) 45 | 46 | # -Surface runoff 47 | rootrunoff = rain - Infil 48 | 49 | # -Saturation excess surface runoff 50 | else: 51 | # -Assume infiltration capacity to be equal to saturated hydraulic conductivity 52 | Infil_cap = self.RootKsat 53 | 54 | # -Infiltration 55 | Infil = pcr.max(0, pcr.min(rain, Infil_cap, self.RootSat - self.RootWater)) 56 | # -Runoff 57 | rootrunoff = pcr.ifthenelse(rainfrac > 0, rain - Infil, 0) 58 | 59 | return rootrunoff, Infil 60 | 61 | 62 | # -Function to calculate rootzone drainage 63 | def RootDrainage(pcr, rootwater, rootdrain, rootfield, rootsat, drainvel, rootTT): 64 | rootexcess = pcr.max(rootwater - rootfield, 0) 65 | rootexcessfrac = rootexcess / (rootsat - rootfield) 66 | rootlat = rootexcessfrac * drainvel 67 | rootdrainage = pcr.max( 68 | pcr.min( 69 | rootexcess, 70 | rootlat * (1 - pcr.exp(-1 / rootTT)) + rootdrain * pcr.exp(-1 / rootTT), 71 | ), 72 | 0, 73 | ) 74 | return rootdrainage 75 | 76 | 77 | # -Function to calculate rootzone percolation 78 | def RootPercolation(pcr, rootwater, subwater, rootfield, rootTT, subsat): 79 | rootexcess = pcr.max(rootwater - rootfield, 0) 80 | rootperc = rootexcess * (1 - pcr.exp(-1 / rootTT)) 81 | rootperc = pcr.ifthenelse( 82 | subwater >= subsat, 0, pcr.min(subsat - subwater, rootperc) 83 | ) 84 | rootperc = pcr.max(pcr.min(rootperc, rootexcess), 0) 85 | return rootperc 86 | 87 | 88 | # -Function to calculate the right fraction between the two fluxes 89 | def CalcFrac(pcr, rootwater, rootfield, rootdrain, rootperc): 90 | rootexcess = pcr.max(rootwater - rootfield, 0) 91 | frac = ((rootdrain + rootperc) - rootexcess) / (rootdrain + rootperc) 92 | rootdrain = rootdrain - (rootdrain * frac) 93 | rootperc = rootperc - (rootperc * frac) 94 | return rootdrain, rootperc 95 | -------------------------------------------------------------------------------- /reporting.csv: -------------------------------------------------------------------------------- 1 | name,map,avg,timeseries,filename,comment 2 | wbal,NONE,NONE,NONE,wbal,WATER BALANCE (Can only select daily output) 3 | # ONLY FOR LAKE AND/OR RESERVOIR MODULE,,,,, 4 | TotStor,NONE,NONE,NONE,TotS,REPORT TOTAL STORAGE (only D or F options are logical) 5 | RainStor,NONE,NONE,NONE,RainS,REPORT STORAGE FROM RAINFALL (only D or F options are logical) 6 | SnowStor,NONE,NONE,NONE,SnowS,REPORT STORAGE FROM SNOW RUNOFF (only D or F options are logical) 7 | GlacStor,NONE,NONE,NONE,GlacS,REPORT STORAGE FROM GLACIER RUNOFF (only D or F options are logical) 8 | BaseStor,NONE,NONE,NONE,BaseS,REPORT STORAGE FROM BASEFLOW RUNOFF (only D or F options are logical) 9 | # FLUXES IN MM,,,,, 10 | TotPrec,M,NONE,NONE,Prec,PREC 11 | TotPrecF,NONE,NONE,NONE,PrecF,PREC; CORRECTED FOR FRACTION 12 | TotPrecEF,NONE,NONE,NONE,PrecEF,EFFECTIVE PRECIPITATION; CORRECTED FOR FRACTION 13 | LAI,NONE,NONE,NONE,LAI,LEAF AREA INDEX 14 | TotIntF,NONE,NONE,NONE,IntF,INTERCEPTION; CORRECTED FOR FRACTION 15 | TotRain,NONE,NONE,NONE,Rain,RAIN 16 | TotRainF,NONE,NONE,NONE,RainF,RAIN; CORRECTED FOR FRACTION 17 | TotETref,M,NONE,NONE,ETr,ETREF 18 | TotETrefF,NONE,NONE,NONE,ETrF,ETREF; CORRECTED FOR FRACTION 19 | TotETpot,NONE,NONE,NONE,ETp,ETPOT 20 | TotETpotF,NONE,NONE,NONE,ETpF,ETPOT; CORRECTED FOR FRACTION 21 | TotETact,Y,NONE,NONE,ETa,ETACT 22 | TotETactF,NONE,NONE,NONE,ETaF,ETACT; CORRECTED FOR FRACTION 23 | PlantStress,NONE,MA,NONE,Pws,PLANT WATER STRESS 24 | TotSnow,NONE,NONE,NONE,Snow,SNOWFALL 25 | TotSnowF,NONE,NONE,NONE,SnowF,SNOWFALL; CORRECTED FOR FRACTION 26 | TotSnowMelt,NONE,NONE,NONE,SMel,SNOWMELT 27 | TotSnowMeltF,NONE,NONE,NONE,SMelF,SNOWMELT; CORRECTED FOR FRACTION 28 | TotGlacMelt,NONE,NONE,NONE,Gmel,GLACIER MELT 29 | TotGlacMeltF,NONE,NONE,NONE,GMelF,GLACIER MELT; CORRECTED FOR FRACTION 30 | Infil,NONE,NONE,NONE,Infil,INFILTRATION 31 | TotRootRF,M,NONE,NONE,Rootr,ROOTZONE RUNOFF; CORRECTED FOR FRACTION 32 | TotRootDF,M,NONE,NONE,Rootd,ROOTZONE DRAINAGE; CORRECTED FOR FRACTION 33 | TotRootPF,NONE,NONE,NONE,Rootp,ROOTZONE PERCOLATION; CORRECTED FOR FRACTION 34 | TotSubDF,NONE,NONE,NONE,Subd,SUBZONE DRAINAGE; CORRECTED FOR FRACTION 35 | TotSubPF,NONE,NONE,NONE,Subp,SUBZONE PERCOLATION; CORRECTED FOR FRACTION 36 | TotCapRF,NONE,NONE,NONE,Capr,CAPILARY RISE; CORRECTED FOR FRACTION 37 | TotSeepF,NONE,NONE,NONE,Seep,SEEPAGE; CORRECTED FOR FRACTION 38 | TotGlacPercF,NONE,NONE,NONE,Glacp,GLACIER PERCOLATION; CORRECTED FOR FRACTION 39 | TotGwRechargeF,M,NONE,NONE,Gwre,GROUNDWATER RECHARGE; CORRECTED FOR FRACTION 40 | GWL,NONE,NONE,NONE,Gwl,GROUNDWATER LEVEL in m below surface (Can only select daily output) 41 | TotRainRF,NONE,NONE,NONE,Rainr,RAIN RUNOFF; CORRECTED FOR FRACTION 42 | TotSnowRF,NONE,NONE,NONE,Snowr,SNOW RUNOFF; CORRECTED FOR FRACTION 43 | TotGlacRF,NONE,NONE,NONE,Glacr,GLACIER RUNOFF; CORRECTED FOR FRACTION 44 | TotBaseRF,NONE,NONE,NONE,Baser,BASEFLOW RUNOFF; CORRECTED FOR FRACTION 45 | TotRF,M,NONE,NONE,Totr,TOTAL RUNOFF OF ALL FRACTIONS 46 | # STORAGE IN CANOPY AND SOIL LAYERS,,,,, 47 | StorCanop,NONE,Y,NONE,Canop,CANOPY STORAGE 48 | StorSnow,NONE,Y,NONE,SnowS,SNOW STORAGE 49 | StorRootW,NONE,Y,NONE,Rootw,ROOTZONE STORAGE 50 | StorSubW,NONE,Y,NONE,Subw,SUBSOIL STORAGE 51 | StorGroundW,NONE,Y,NONE,GrndW,GROUNDWATER STORAGE 52 | # ROUTED STREAMFLOW FLUXES IN M3/S (only D or F options are logical) ,,,,, 53 | SubSurfRAtot,NONE,NONE,NONE,SSTot,ROUTED SUBSURFACE RUNOFF 54 | RootRRAtot,NONE,NONE,NONE,RRTot,ROUTED ROOT SURFACE RUNOFF 55 | RootDRAtot,NONE,NONE,NONE,RDTot,ROUTED ROOT DRAINAGE RUNOFF 56 | RainRAtot,NONE,NONE,NONE,RTot,ROUTED RAIN RUNOFF 57 | SnowRAtot,NONE,NONE,NONE,STot,ROUTED SNOW RUNOFF 58 | GlacRAtot,NONE,NONE,NONE,GTot,ROUTED GLACIER RUNOFF 59 | BaseRAtot,NONE,NONE,NONE,BTot,ROUTED BASEFLOW RUNOFF 60 | QallRAtot,NONE,NONE,D,QAll,ROUTED TOTAL RUNOFF 61 | # SEDIMENT YIELD,,,,, 62 | DetRn,NONE,NONE,NONE,DetRn,DETACHMENT BY RAIN in metric tons per cell area 63 | DetRun,NONE,NONE,NONE,DetRun,DETACHMENT BY RUNOFF in metric tons per cell area 64 | SDepFld,NONE,NONE,NONE,SDpFld,IN FIELD SEDIMENT DEPOSITION in metric tons per cell area 65 | SedTrans,NONE,NONE,NONE,STrans,SEDIMENT TRANSPORTED in metric tons per cell area 66 | SedDep,NONE,NONE,NONE,Sdep,SEDIMENT DEPOSITION in metric tons per cell area 67 | SedYld,NONE,NONE,NONE,SdYld,SEDIMENT YIELD AT STATIONS in metric tons 68 | SedFlux,NONE,NONE,NONE,SdFlux,SEDIMENT FLUX AT STATIONS in metric tons 69 | TC,NONE,NONE,NONE,TC,TRANSPORT CAPACITY in metric tons 70 | -------------------------------------------------------------------------------- /modules/routing.py: -------------------------------------------------------------------------------- 1 | # The Spatial Processes in HYdrology (SPHY) model: 2 | # A spatially distributed hydrological model 3 | # Copyright (C) 2013-2025 FutureWater 4 | # Email: sphy@futurewater.nl 5 | # 6 | # Authors (alphabetical order): 7 | # P. Droogers, J. Eekhout, A. Fernandez-Rodriguez, W. Immerzeel, S. Khanal, A. Lutz, T. Schults, G. Simons, W. Terink. 8 | # 9 | # This program is free software: you can redistribute it and/or modify 10 | # it under the terms of the GNU General Public License as published by 11 | # the Free Software Foundation, either version 3 of the License, or 12 | # (at your option) any later version. 13 | # 14 | # This program is distributed in the hope that it will be useful, 15 | # but WITHOUT ANY WARRANTY; without even the implied warranty of 16 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 17 | # GNU General Public License for more details. 18 | # 19 | # You should have received a copy of the GNU General Public License 20 | # along with this program. If not, see . 21 | 22 | print("routing module imported") 23 | 24 | 25 | def ROUT(pcr, q, oldq, flowdir, kx): 26 | rr = (q * 0.001 * pcr.cellarea()) / (24 * 3600) 27 | ra = pcr.accuflux(flowdir, rr) 28 | ra = (1 - kx) * ra + kx * oldq 29 | return ra 30 | 31 | 32 | # -init routing processes 33 | def init(self, pcr, config): 34 | self.FlowDir = pcr.readmap(self.inpath + config.get("ROUTING", "flowdir")) 35 | try: 36 | self.kx = pcr.readmap(self.inpath + config.get("ROUTING", "kx")) 37 | except: 38 | self.kx = config.getfloat("ROUTING", "kx") 39 | 40 | 41 | # -initial conditions routing 42 | def initial(self, pcr, config): 43 | # -initial routed total runoff 44 | try: 45 | self.QRAold = config.getfloat("ROUT_INIT", "QRA_init") 46 | except: 47 | try: 48 | self.QRAold = pcr.readmap(self.inpath + config.get("ROUT_INIT", "QRA_init")) 49 | except: 50 | self.QRAold = 0 51 | # -initial routed runoff for the individual components 52 | pars = ["RootR", "RootD", "Rain", "Snow", "Glac", "Base"] 53 | for i in pars: 54 | try: 55 | setattr( 56 | self, 57 | i + "RAold", 58 | pcr.readmap(self.inpath + config.get("ROUT_INIT", i + "RA_init")), 59 | ) 60 | setattr(self, i + "RA_FLAG", True) 61 | except: 62 | try: 63 | setattr(self, i + "RAold", config.getfloat("ROUT_INIT", i + "RA_init")) 64 | setattr(self, i + "RA_FLAG", True) 65 | except: 66 | setattr(self, i + "RA_FLAG", False) 67 | 68 | 69 | # -dynamic routing processes 70 | def dynamic(self, pcr, TotR): 71 | # -Rout total runoff 72 | Q = self.routing.ROUT(pcr, TotR, self.QRAold, self.FlowDir, self.kx) 73 | self.QRAold = Q 74 | self.reporting.reporting(self, pcr, "QallRAtot", Q) 75 | if self.mm_rep_FLAG == 1 and self.QTOT_mm_FLAG == 1: 76 | self.QTOTSubBasinTSS.sample( 77 | ((Q * 3600 * 24) / pcr.catchmenttotal(pcr.cellarea(), self.FlowDir)) * 1000 78 | ) 79 | 80 | # -Routing of surface runoff, root drainage, rain, snow, glacier and baseflow 81 | pars = ["RootR", "RootD", "Rain", "Snow", "Glac", "Base"] 82 | for i in pars: 83 | if getattr(self, i + "RA_FLAG") == 1: 84 | try: 85 | ParsRA = self.routing.ROUT( 86 | pcr, 87 | getattr(self, i + "R"), 88 | getattr(self, i + "RAold"), 89 | self.FlowDir, 90 | self.kx, 91 | ) 92 | except: 93 | ParsRA = self.routing.ROUT( 94 | pcr, 95 | eval(i + "R"), 96 | getattr(self, i + "RAold"), 97 | self.FlowDir, 98 | self.kx, 99 | ) 100 | setattr(self, i + "RAold", ParsRA) 101 | self.reporting.reporting(self, pcr, i + "RAtot", ParsRA) 102 | if ( 103 | self.mm_rep_FLAG == 1 104 | and getattr(self, "Q" + i.upper() + "_mm_FLAG") == 1 105 | ): 106 | setattr( 107 | self, 108 | "Q" + i.upper() + "SubBasinTSS.sample", 109 | ( 110 | (ParsRA * 3600 * 24) 111 | / pcr.catchmenttotal(pcr.cellarea(), self.FlowDir) 112 | ) 113 | * 1000, 114 | ) 115 | 116 | return Q 117 | -------------------------------------------------------------------------------- /modules/groundwater.py: -------------------------------------------------------------------------------- 1 | # The Spatial Processes in HYdrology (SPHY) model: 2 | # A spatially distributed hydrological model 3 | # Copyright (C) 2013-2025 FutureWater 4 | # Email: sphy@futurewater.nl 5 | # 6 | # Authors (alphabetical order): 7 | # P. Droogers, J. Eekhout, A. Fernandez-Rodriguez, W. Immerzeel, S. Khanal, A. Lutz, T. Schults, G. Simons, W. Terink. 8 | # 9 | # This program is free software: you can redistribute it and/or modify 10 | # it under the terms of the GNU General Public License as published by 11 | # the Free Software Foundation, either version 3 of the License, or 12 | # (at your option) any later version. 13 | # 14 | # This program is distributed in the hope that it will be useful, 15 | # but WITHOUT ANY WARRANTY; without even the implied warranty of 16 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 17 | # GNU General Public License for more details. 18 | # 19 | # You should have received a copy of the GNU General Public License 20 | # along with this program. If not, see . 21 | 22 | print("groundwater module imported") 23 | 24 | 25 | # -Function to calculate groundwater recharge 26 | def GroundWaterRecharge(pcr, deltagw, gwrecharge, subperc, glacperc): 27 | gwseep = (1 - pcr.exp(-1 / deltagw)) * (subperc + glacperc) 28 | gwrecharge = (pcr.exp(-1 / deltagw) * gwrecharge) + gwseep 29 | return gwrecharge 30 | 31 | 32 | # -Function to calculate baseflow 33 | def BaseFlow(pcr, gw, baser, gwrecharge, basethresh, alphagw): 34 | baser = pcr.ifthenelse( 35 | gw <= basethresh, 36 | 0, 37 | (baser * pcr.exp(-alphagw) + gwrecharge * (1 - pcr.exp(-alphagw))), 38 | ) 39 | return baser 40 | 41 | 42 | # -Function to calculate the groundwater height, taken from the bottom of the gw layer (zero reference) 43 | def HLevel(pcr, Hgw, alphagw, gwrecharge, yield_gw): 44 | Hgw = (Hgw * pcr.exp(-alphagw)) + ( 45 | (gwrecharge * (1 - pcr.exp(-alphagw))) / (800 * yield_gw * alphagw) 46 | ) 47 | return Hgw 48 | 49 | 50 | # -init groundwater processes 51 | def init(self, pcr, config): 52 | pars = ["GwDepth", "GwSat", "deltaGw", "BaseThresh", "alphaGw", "YieldGw"] 53 | for i in pars: 54 | try: 55 | setattr(self, i, pcr.readmap(self.inpath + config.get("GROUNDW_PARS", i))) 56 | except: 57 | setattr(self, i, config.getfloat("GROUNDW_PARS", i)) 58 | 59 | 60 | # -initial conditions groundwater 61 | def initial(self, pcr, config): 62 | # -initial groundwater recharge 63 | try: 64 | self.GwRecharge = config.getfloat("GROUNDW_INIT", "GwRecharge") 65 | except: 66 | self.GwRecharge = pcr.readmap( 67 | self.inpath + config.get("GROUNDW_INIT", "GwRecharge") 68 | ) 69 | # -initial baseflow 70 | try: 71 | self.BaseR = config.getfloat("GROUNDW_INIT", "BaseR") 72 | except: 73 | self.BaseR = pcr.readmap(self.inpath + config.get("GROUNDW_INIT", "BaseR")) 74 | # -initial groundwater storage 75 | try: 76 | self.Gw = config.getfloat("GROUNDW_INIT", "Gw") 77 | except: 78 | self.Gw = pcr.readmap(self.inpath + config.get("GROUNDW_INIT", "Gw")) 79 | # -initial groundwater level 80 | try: 81 | self.H_gw = config.getfloat("GROUNDW_INIT", "H_gw") 82 | except: 83 | self.H_gw = pcr.readmap(self.inpath + config.get("GROUNDW_INIT", "H_gw")) 84 | self.H_gw = pcr.max( 85 | (self.RootDepthFlat + self.SubDepthFlat + self.GwDepth) / 1000 - self.H_gw, 0 86 | ) 87 | 88 | 89 | # -dynamic groundwater processes 90 | def dynamic(self, pcr, ActSubPerc, GlacPerc): 91 | # GwOld = self.Gw 92 | # -Groundwater recharge 93 | self.GwRecharge = self.groundwater.GroundWaterRecharge( 94 | pcr, self.deltaGw, self.GwRecharge, ActSubPerc, GlacPerc 95 | ) 96 | # -Report groundwater recharge 97 | self.reporting.reporting(self, pcr, "TotGwRechargeF", self.GwRecharge) 98 | # -Update groundwater storage 99 | self.Gw = self.Gw + self.GwRecharge 100 | # -Baseflow 101 | self.BaseR = self.groundwater.BaseFlow( 102 | pcr, self.Gw, self.BaseR, self.GwRecharge, self.BaseThresh, self.alphaGw 103 | ) 104 | # -Update groundwater storage 105 | self.Gw = self.Gw - self.BaseR 106 | # -Report groundwater storage 107 | self.reporting.reporting( 108 | self, pcr, "StorGroundW", self.Gw * (1 - self.openWaterFrac) 109 | ) 110 | # -Correct for open-water fraction 111 | self.BaseR = self.BaseR * (1 - self.openWaterFrac) 112 | # -Report Baseflow 113 | self.reporting.reporting(self, pcr, "TotBaseRF", self.BaseR) 114 | # -Calculate groundwater level 115 | self.H_gw = self.groundwater.HLevel( 116 | pcr, self.H_gw, self.alphaGw, self.GwRecharge, self.YieldGw 117 | ) 118 | # -Report groundwater level 119 | self.reporting.reporting( 120 | self, 121 | pcr, 122 | "GWL", 123 | ((self.SubDepthFlat + self.RootDepthFlat + self.GwDepth) / 1000 - self.H_gw) 124 | * -1, 125 | ) 126 | -------------------------------------------------------------------------------- /modules/dynamic_veg.py: -------------------------------------------------------------------------------- 1 | # The Spatial Processes in HYdrology (SPHY) model: 2 | # A spatially distributed hydrological model 3 | # Copyright (C) 2013-2025 FutureWater 4 | # Email: sphy@futurewater.nl 5 | # 6 | # Authors (alphabetical order): 7 | # P. Droogers, J. Eekhout, A. Fernandez-Rodriguez, W. Immerzeel, S. Khanal, A. Lutz, T. Schults, G. Simons, W. Terink. 8 | # 9 | # This program is free software: you can redistribute it and/or modify 10 | # it under the terms of the GNU General Public License as published by 11 | # the Free Software Foundation, either version 3 of the License, or 12 | # (at your option) any later version. 13 | # 14 | # This program is distributed in the hope that it will be useful, 15 | # but WITHOUT ANY WARRANTY; without even the implied warranty of 16 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 17 | # GNU General Public License for more details. 18 | # 19 | # You should have received a copy of the GNU General Public License 20 | # along with this program. If not, see . 21 | 22 | print("dynamic vegetation module imported") 23 | 24 | 25 | # -Function that returns crop factor (Kc) and maximum storage (Smax) 26 | def Veg_function( 27 | pcr, ndvi, fpar_max, fpar_min, lai_max, ndvi_min, ndvi_max, kc_min, kc_max 28 | ): 29 | SR = (1 + ndvi) / (1 - ndvi) 30 | SR_max = (1 + ndvi_max) / (1 - ndvi_max) 31 | SR_min = (1 + ndvi_min) / (1 - ndvi_min) 32 | FPAR = pcr.min((SR - SR_min) / (SR_max - SR_min) * (fpar_max - fpar_min), 0.95) 33 | LAI = lai_max * pcr.log10(1 - FPAR) / pcr.log10(1 - fpar_max) 34 | Smax = 0.935 + 0.498 * LAI - 0.00575 * (LAI**2) 35 | Kc = kc_min + (kc_max - kc_min) * pcr.max( 36 | pcr.min((ndvi - ndvi_min) / (ndvi_max - ndvi_min), 1), 0 37 | ) 38 | return Kc, Smax, LAI 39 | 40 | 41 | # -Function that returns the interception, precipitation throughfall, and remaining storage 42 | def Inter_function(pcr, S, Smax, Etr): 43 | PreT = pcr.max(0, S - Smax) 44 | S = S - PreT 45 | Int = pcr.min(1.5 * Etr, S) 46 | S = S - Int 47 | return Int, PreT, S 48 | 49 | 50 | # -init processes dynamic vegetation 51 | def init(self, pcr, config): 52 | # -set the ndvi map series to be read 53 | self.ndvi = self.inpath + config.get("DYNVEG", "NDVI") 54 | # -read the vegetation parameters 55 | LAImax_table = self.inpath + config.get("DYNVEG", "LAImax") 56 | self.LAImax = pcr.lookupscalar(LAImax_table, self.LandUse) 57 | pars = ["NDVImax", "NDVImin", "NDVIbase", "KCmax", "KCmin", "FPARmax", "FPARmin"] 58 | for i in pars: 59 | try: 60 | setattr(self, i, pcr.readmap(self.inpath + config.get("DYNVEG", i))) 61 | except: 62 | setattr(self, i, config.getfloat("DYNVEG", i)) 63 | 64 | 65 | # -initial conditions dynamic vegetation 66 | def initial(self, pcr): 67 | # -initial canopy storage 68 | self.Scanopy = 0 69 | # -initial ndvi if first map is not provided 70 | self.ndviOld = pcr.scalar((self.NDVImax + self.NDVImin) / 2) 71 | # -set initial kc value to one, if kc map is not available for first timestep 72 | self.KcOld = pcr.scalar(1) 73 | 74 | 75 | # -dynamic processes dynamic vegetation 76 | def dynamic(self, pcr, pcrm, np, Precip, ETref): 77 | # -try to read the ndvi map series. If not available, then use ndvi old 78 | try: 79 | ndvi = pcr.readmap(pcrm.generateNameT(self.ndvi, self.counter)) 80 | except: 81 | ndvi = self.ndviOld 82 | self.ndviOld = ndvi 83 | # -fill missing ndvi values with average 84 | ndviAvg = np.nanmean(pcr.pcr2numpy(ndvi, np.nan)) 85 | ndvi = pcr.cover(ndvi, float(ndviAvg)) 86 | # -set maximum value to 0.999 87 | ndvi = pcr.min(ndvi, 0.999) 88 | 89 | # -calculate the vegetation parameters 90 | vegoutput = self.dynamic_veg.Veg_function( 91 | pcr, 92 | ndvi, 93 | self.FPARmax, 94 | self.FPARmin, 95 | self.LAImax, 96 | self.NDVImin, 97 | self.NDVImax, 98 | self.KCmin, 99 | self.KCmax, 100 | ) 101 | # -Kc 102 | self.Kc = vegoutput[0] 103 | # -LAI 104 | self.LAI = vegoutput[2] 105 | # -report leaf area index 106 | self.reporting.reporting(self, pcr, "LAI", self.LAI) 107 | 108 | # -Update canopy storage 109 | self.Scanopy = self.Scanopy + Precip 110 | # -interception and effective precipitation 111 | intercep = self.dynamic_veg.Inter_function(pcr, self.Scanopy, vegoutput[1], ETref) 112 | # -interception 113 | Int = intercep[0] 114 | Int = Int * (1 - self.openWaterFrac) 115 | # -report interception corrected for fraction 116 | self.reporting.reporting(self, pcr, "TotIntF", Int * (1 - self.GlacFrac)) 117 | # -effective precipitation 118 | Precip = intercep[1] 119 | # -Report effective precipitation corrected for fraction 120 | self.reporting.reporting(self, pcr, "TotPrecEF", Precip * (1 - self.GlacFrac)) 121 | # -canopy storage 122 | self.Scanopy = intercep[2] 123 | # -Report effective precipitation corrected for fraction 124 | self.reporting.reporting( 125 | self, pcr, "StorCanop", self.Scanopy * (1 - self.openWaterFrac) 126 | ) 127 | 128 | return Precip 129 | -------------------------------------------------------------------------------- /modules/inca.py: -------------------------------------------------------------------------------- 1 | # Soil erosion module using the INCA soil erosion model 2 | # Copyright (C) 2020 Joris Eekhout / Spanish National Research Council (CEBAS-CSIC) 3 | # Email: jeekhout@cebas.csic.es 4 | # 5 | # This program is free software: you can redistribute it and/or modify 6 | # it under the terms of the GNU General Public License as published by 7 | # the Free Software Foundation, either version 3 of the License, or 8 | # (at your option) any later version. 9 | # 10 | # This program is distributed in the hope that it will be useful, 11 | # but WITHOUT ANY WARRANTY; without even the implied warranty of 12 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 13 | # GNU General Public License for more details. 14 | # 15 | # You should have received a copy of the GNU General Public License 16 | # along with this program. If not, see . 17 | 18 | 19 | print('INCA module imported') 20 | 21 | #-Detachment of soil particles by raindrop impact (kg/km2) 22 | def DetachmentRaindrop(self, pcr, c_X1, p_Sed, E_SP, V, CG): 23 | p = p_Sed / (24 * 60 * 60) * 1e-3 24 | S_SP = pcr.max(0, 1 - CG - self.NoErosion_INCA) * c_X1 * p * E_SP**(10 / (10 - V)) * 8.64 * 1e10 25 | return S_SP 26 | 27 | #-Detachment of soil particles by runoff (kg/km2) 28 | def DetachmentRunoff(self, pcr, q_dr, S_SP, S_TC, E_FL, a1, a2, a3, CG, A, L): 29 | K = a1 * E_FL * 86400 * ((A * q_dr) / L - a2)**a3 30 | S_FL = pcr.max(0, pcr.ifthenelse(S_TC + K == 0, 0, K * (S_TC - S_SP) / (S_TC + K)) * pcr.max(0, 1 - self.NoErosion_INCA)) 31 | 32 | #-set values in channels to 0 in case channels should be excluded 33 | if self.exclChannelsFLAG == 1: 34 | S_FL = S_FL * self.Hillslope 35 | return S_FL, K 36 | 37 | #-Transport capacity of the flow (kg/km2) 38 | def TransportCapacity(self, pcr, q_dr, a4, a5, a6, A, L): 39 | S_TC = a4 * 86400 * ((A * q_dr) / L - a5)**a6 40 | return S_TC 41 | 42 | #-Update sediment store (kg/km2) 43 | def UpdateSedimentStore(self, pcr, S_SP, S_FL, S_TC, K): 44 | if self.exclChannelsFLAG == 1: 45 | dStore_dt = pcr.ifthenelse(self.Hillslope == 1, -K * (S_SP - S_TC) / (S_TC + K), S_SP) 46 | else: 47 | dStore_dt = -K * (S_SP - S_TC) / (S_TC + K) 48 | dStore_dt = pcr.ifthenelse(S_TC + K == 0, 0, dStore_dt) 49 | 50 | S_store = pcr.max(0, self.S_store + pcr.ifthenelse(self.S_store + S_SP > S_TC, S_SP - S_TC, dStore_dt)) 51 | return S_store 52 | 53 | #-Mass of sediment transported (kg/km2) 54 | def sedimentTransported(self, pcr, S_SP, S_FL, S_TC): 55 | M_Out = pcr.ifthenelse(self.S_store + S_SP > S_TC, S_TC, S_SP + S_FL) * pcr.max(0, 1 - self.NoErosion_INCA) 56 | return M_Out 57 | 58 | #-init processes inca 59 | def init(self, pcr, config): 60 | #-read table with INCA landuse specific model parameters 61 | pcr.setglobaloption('matrixtable') 62 | inca_table = self.inpath + config.get('INCA', 'inca_table') 63 | self.V_INCA = pcr.lookupscalar(inca_table, 1, self.LandUse) 64 | self.GC_INCA = pcr.lookupscalar(inca_table, 2, self.LandUse) 65 | try: 66 | self.a4_INCA = config.getfloat('INCA', 'a4') 67 | except: 68 | self.a4_INCA = pcr.lookupscalar(inca_table, 3, self.LandUse) 69 | self.NoErosion_INCA = pcr.lookupscalar(inca_table, 4, self.LandUse) 70 | pcr.setglobaloption('columntable') 71 | 72 | #-read other model parameters 73 | self.c_x1_INCA = config.getfloat('INCA', 'c_x1') 74 | self.a1_INCA = config.getfloat('INCA', 'a1') 75 | self.a2_INCA = config.getfloat('INCA', 'a2') 76 | self.a3_INCA = config.getfloat('INCA', 'a3') 77 | self.a5_INCA = config.getfloat('INCA', 'a5') 78 | self.a6_INCA = config.getfloat('INCA', 'a6') 79 | self.E_SP_INCA = config.getfloat('INCA', 'E_SP') 80 | self.E_FL_INCA = config.getfloat('INCA', 'E_FL') 81 | 82 | #-Determine cell size and slope length 83 | self.A_INCA = pcr.cellarea() * 1e-6 84 | alpha = pcr.atan(self.Slope) 85 | self.L_INCA = pcr.celllength() * 1e-3 / pcr.cos(alpha) 86 | 87 | #-Initiate sediment store variable 88 | self.S_store = self.DEM * 0 89 | 90 | #-dynamic processes inca 91 | def dynamic(self, pcr, Precip, Q): 92 | #-determine canopy cover from LAI 93 | if self.DynVegFLAG == 1: 94 | V_INCA = pcr.min(9.999, pcr.min(1, self.LAI) * 10) 95 | else: 96 | V_INCA = self.V_INCA 97 | 98 | #-determine detachment of soil particles by raindrop impact (kg/km2) 99 | S_SP = self.inca.DetachmentRaindrop(self, pcr, self.c_x1_INCA, Precip, self.E_SP_INCA, V_INCA, self.GC_INCA) 100 | 101 | #-report detachment of soil particles by raindrop impact (ton / cell) 102 | self.reporting.reporting(self, pcr, 'DetRn', S_SP * pcr.cellarea() * 1e-9) 103 | 104 | #-Determine transport capacity of the flow (kg/km2) 105 | S_TC = self.inca.TransportCapacity(self, pcr, Q, self.a4_INCA, self.a5_INCA, self.a6_INCA, self.A_INCA, self.L_INCA) 106 | 107 | #-determine detachment of soil particles by runoff (kg/km2) 108 | S_FL, K = self.inca.DetachmentRunoff(self, pcr, Q, S_SP, S_TC, self.E_FL_INCA, self.a1_INCA, self.a2_INCA, self.a3_INCA, self.GC_INCA, self.A_INCA, self.L_INCA) 109 | 110 | #-report detachment of soil particles by runoff (ton / cell) 111 | self.reporting.reporting(self, pcr, 'DetRun', S_FL * pcr.cellarea() * 1e-9) 112 | 113 | #-determine mass of sediment in transport (kg/km2) 114 | sed = self.inca.sedimentTransported(self, pcr, S_SP, S_FL, S_TC) 115 | 116 | #-update sediment store (kg/km2) 117 | self.S_store = self.inca.UpdateSedimentStore(self, pcr, S_SP, S_FL, S_TC, K) 118 | 119 | #-report sediment in transport (ton / cell) 120 | self.reporting.reporting(self, pcr, 'SedTrans', sed * pcr.cellarea() * 1e-9) 121 | 122 | return sed 123 | -------------------------------------------------------------------------------- /modules/musle.py: -------------------------------------------------------------------------------- 1 | # The Spatial Processes in HYdrology (SPHY) model: 2 | # A spatially distributed hydrological model 3 | # Copyright (C) 2013-2025 FutureWater 4 | # Email: sphy@futurewater.nl 5 | # 6 | # Authors (alphabetical order): 7 | # P. Droogers, J. Eekhout, A. Fernandez-Rodriguez, W. Immerzeel, S. Khanal, A. Lutz, T. Schults, G. Simons, W. Terink. 8 | # 9 | # This program is free software: you can redistribute it and/or modify 10 | # it under the terms of the GNU General Public License as published by 11 | # the Free Software Foundation, either version 3 of the License, or 12 | # (at your option) any later version. 13 | # 14 | # This program is distributed in the hope that it will be useful, 15 | # but WITHOUT ANY WARRANTY; without even the implied warranty of 16 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 17 | # GNU General Public License for more details. 18 | # 19 | # You should have received a copy of the GNU General Public License 20 | # along with this program. If not, see . 21 | 22 | 23 | # Equations to calculate sediment yield accoding to the soil loss equation (Williams, 1995) 24 | # from rootzone import RootRunoff 25 | 26 | print("MUSLE module imported") 27 | 28 | 29 | # -Modified unviversal soil loss equation to calculate sediment yield (metric tons) 30 | def MUSLE(self, pcr, Q_surf, q_peak): 31 | sed = ( 32 | 11.8 33 | * (Q_surf * q_peak * self.ha_area) ** 0.56 34 | * self.K_USLE 35 | * self.C_USLE 36 | * self.P_USLE 37 | * self.LS_USLE 38 | * self.CFRG 39 | ) 40 | sed = (sed / 10000) * pcr.cellarea() # conversion to ton / cell 41 | return sed 42 | 43 | 44 | # -Peak runoff (m3/s) 45 | def q_peak(self, pcr, Runoff): 46 | q_peak = (self.Alpha_tc * Runoff * pcr.cellarea()) / ( 47 | 3600000 * self.Tc 48 | ) # peak runoff in m3/s 49 | return q_peak 50 | 51 | 52 | # -LS topographic factor 53 | def LS_ULSE(self, pcr): 54 | m = 0.6 * (1 - pcr.exp(-35.835 * self.Slope)) 55 | alpha_hill = pcr.atan(self.Slope) 56 | L_hill = pcr.celllength() / pcr.cos(alpha_hill) 57 | LS = ((L_hill / 22.1) ** m) * ( 58 | 65.41 * pcr.sin(alpha_hill) ** 2 + 4.56 * pcr.sin(alpha_hill) + 0.065 59 | ) 60 | return LS 61 | 62 | 63 | # -K factor 64 | def K_USLE(self, pcr): 65 | # ksat_hourly = self.RootKsat / 24 / self.RootKsatFrac 66 | ksat_hourly = self.RootKsat / 24 67 | M_textural = (self.RootSiltMap * 100 + 0) * (100 - self.RootClayMap * 100) 68 | permeability = pcr.scalar(ksat_hourly > 150) * 1 69 | permeability = ( 70 | permeability + pcr.scalar(pcr.pcrand(ksat_hourly > 50, ksat_hourly < 150)) * 2 71 | ) 72 | permeability = ( 73 | permeability + pcr.scalar(pcr.pcrand(ksat_hourly > 15, ksat_hourly < 50)) * 3 74 | ) 75 | permeability = ( 76 | permeability + pcr.scalar(pcr.pcrand(ksat_hourly > 5, ksat_hourly < 15)) * 4 77 | ) 78 | permeability = ( 79 | permeability + pcr.scalar(pcr.pcrand(ksat_hourly > 1, ksat_hourly < 5)) * 5 80 | ) 81 | permeability = permeability + pcr.scalar(ksat_hourly < 1) * 6 82 | s = 2 83 | K_USLE = ( 84 | ( 85 | 2.1 * 10**-4 * M_textural**1.14 * (12 - self.RootOMMap) 86 | + 3.25 * (s - 2) 87 | + 2.5 * (permeability - 3) 88 | ) 89 | / 100 90 | ) * 0.1317 91 | return K_USLE 92 | 93 | 94 | # -Time of concentration 95 | def Tc(self, pcr): 96 | slope_adjusted = pcr.ifthenelse( 97 | self.Slope < 0.0025, self.Slope + 0.0005, self.Slope 98 | ) 99 | alpha_hill = pcr.atan(slope_adjusted) 100 | L = pcr.celllength() / pcr.cos(alpha_hill) 101 | # -Kirpich channel flow time of concentration 102 | T_ch = 0.0195 * L**0.77 * slope_adjusted**-0.385 103 | # -Kerby overland flow time of concentration 104 | T_ov = 1.44 * (L * self.N) ** 0.467 * slope_adjusted**-0.235 105 | Tc = (T_ch + T_ov) / 60 # conversion to hours 106 | return Tc 107 | 108 | 109 | # -init processes musle 110 | def init(self, pcr, config): 111 | # -read table with MUSLE C-factor and retardance coefficient values per landuse class 112 | pcr.setglobaloption("matrixtable") 113 | musle_table = self.inpath + config.get("MUSLE", "musle_table") 114 | self.C_USLE = pcr.lookupscalar(musle_table, 1, self.LandUse) 115 | self.N = pcr.lookupscalar(musle_table, 2, self.LandUse) 116 | pcr.setglobaloption("columntable") 117 | 118 | # -read P-factor values map or float 119 | try: 120 | self.P_USLE = pcr.readmap(self.inpath + config.get("MUSLE", "P_USLE")) 121 | except: 122 | self.P_USLE = config.getfloat("MUSLE", "P_USLE") 123 | 124 | # -when pedotransfer module is used, calculate the K-factor based on texture maps, else read K-factor values from table 125 | if self.PedotransferFLAG == 1: 126 | self.K_USLE = self.musle.K_USLE(self, pcr) 127 | else: 128 | self.K_USLE = pcr.readmap(self.inpath + config.get("MUSLE", "K_USLE")) 129 | 130 | # -calculate other input parameters 131 | self.LS_USLE = self.musle.LS_ULSE(self, pcr) 132 | self.CFRG = pcr.exp(-0.053 * (self.RockFrac * 100)) 133 | self.Tc = self.musle.Tc(self, pcr) 134 | self.Alpha_tc = 1 - pcr.exp(2 * self.Tc * pcr.ln(1 - (self.Alpha / 2))) 135 | self.ha_area = pcr.cellarea() / 10000 136 | 137 | 138 | # -dynamic processes musle 139 | def dynamic(self, pcr, Runoff): 140 | # -determine peak runoff 141 | q_peak = self.musle.q_peak(self, pcr, Runoff) # -peak runoff in m3/s 142 | 143 | # -determine soil erosion 144 | sed = self.musle.MUSLE(self, pcr, Runoff, q_peak) # -sediment yield in ton 145 | 146 | # -report sediment in transport (ton / cell) 147 | self.reporting.reporting(self, pcr, "SedTrans", sed) 148 | -------------------------------------------------------------------------------- /utilities/pedotransfer.py: -------------------------------------------------------------------------------- 1 | # Tool to determine soil hydraulic properties from texture and organic matter input maps, 2 | # based on the pedotransfer function from Saxton & Rawls (2006) 3 | # Copyright (C) 2016-2019 Joris Eekhout / Spanish National Research Council (CEBAS-CSIC) 4 | # Email: jeekhout@cebas.csic.es 5 | # 6 | # This program is free software: you can redistribute it and/or modify 7 | # it under the terms of the GNU General Public License as published by 8 | # the Free Software Foundation, either version 3 of the License, or 9 | # (at your option) any later version. 10 | # 11 | # This program is distributed in the hope that it will be useful, 12 | # but WITHOUT ANY WARRANTY; without even the implied warranty of 13 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 14 | # GNU General Public License for more details. 15 | # 16 | # You should have received a copy of the GNU General Public License 17 | # along with this program. If not, see . 18 | 19 | 20 | #-function to calculate the wilting point (1500 kPa, %) 21 | def Dry(pcr, self, sand, clay, OM, bulk): 22 | #-1500 kPa moisture, first solution, %v (Eq. 1) 23 | dry_first = -0.024 * sand + 0.487 * clay + 0.006 * OM + 0.005 * sand * OM - 0.013 * clay * OM + 0.068 * sand * clay + 0.031 24 | #-1500 kPa moisture, %v (Eq. 1) 25 | dry = dry_first + (0.14 * dry_first - 0.02) 26 | return dry 27 | 28 | 29 | #-function to calculate the field capacity (33 kPa, %) 30 | def Field(pcr, self, sand, clay, OM, bulk): 31 | #-33 kPa moisture, first solution, %v (Eq. 2) 32 | field_first = -0.251 * sand + 0.195 * clay + 0.011 * OM + 0.006 * sand * OM - 0.027 * clay * OM + 0.452 * sand * clay + 0.299 33 | #-33 kPa moisture, normal density, %v (Eq. 2) 34 | field = field_first + (1.283 * field_first**2 - 0.374 * field_first - 0.015) 35 | return field 36 | 37 | 38 | #-function to calculate the saturated water content (0 kPa, %) 39 | def Sat(pcr, self, sand, clay, OM, bulk): 40 | #-SAT-33 kPa moisture, first solution, %v (Eq. 3) 41 | poros_first = 0.278 * sand + 0.034 * clay + 0.022 * OM - 0.018 * sand * OM - 0.027 * clay * OM - 0.584 * sand * clay + 0.078 42 | #-SAT-33 kPa moisture, normal density, %v (Eq. 3) 43 | poros = poros_first + (0.636 * poros_first - 0.107) 44 | #-Saturated moisture (0 kPa), normal density, %v (Eq. 5) 45 | sat = poros + self.pedotransfer.Field(pcr, self, sand, clay, OM, bulk) - 0.097 * sand + 0.043 46 | return sat 47 | 48 | 49 | #-function to calculate the field capacity adjusted for density (33 kPa, %) and saturated water content adjusted for density (0 kPa, %) 50 | def FieldAdj(pcr, self, sand, clay, OM, bulk): 51 | #-Normal density, g cm-3 (Eq. 6) 52 | density = (1-self.pedotransfer.Sat(pcr, self, sand, clay, OM, bulk))*2.65 53 | #-Adjusted density, g cm-3 (Eq. 7) 54 | density_adj = density * bulk 55 | #-Saturated moisture (0 kPa), adjusted density, %v (Eq. 8) 56 | sat_adj_dens = 1 - density_adj/2.65 57 | #-33 kPa moisture, adjusted density, %v (Eq. 9) 58 | field_adj_dens = self.pedotransfer.Field(pcr, self, sand, clay, OM, bulk) + 0.2 * (self.pedotransfer.Sat(pcr, self, sand, clay, OM, bulk) - sat_adj_dens) 59 | #-SAT-33 kPa moisture, adjusted density, %v (Eq. 10) 60 | poros_adj_dens = sat_adj_dens - field_adj_dens 61 | return field_adj_dens, poros_adj_dens, sat_adj_dens 62 | 63 | 64 | #-function to calculate the saturated hydraulic conductivity (mm/day) 65 | def KSat(pcr, self, sand, clay, OM, bulk): 66 | #-Calculate wilting, field capacity and porosity 67 | dry = self.pedotransfer.Dry(pcr, self, sand, clay, OM, bulk) 68 | temp = self.pedotransfer.FieldAdj(pcr, self, sand, clay, OM, bulk) 69 | field_adj_dens = temp[0] 70 | poros_adj_dens = temp[1] 71 | #-Inverse of B (Eq. 18) 72 | lamda = (pcr.log10(field_adj_dens) - pcr.log10(dry)) / (pcr.log10(1500) - pcr.log10(33)) 73 | #-Saturated conductivity (matric soil), mm/day (Eq. 16) 74 | ksat = (1930 * (poros_adj_dens)**(3 - lamda)) * 24 75 | return ksat 76 | 77 | #-function to calculate the wilting point based on previous pedotransfer functions 78 | def Wilt(pcr, self, np): 79 | #-Determine exponents B and A for logarithmic function 80 | B = (np.log(1500) - np.log(33)) / (pcr.ln(self.RootFieldMap) - pcr.ln(self.RootDryMap)) 81 | A = pcr.exp(np.log(33) + B * pcr.ln(self.RootFieldMap)) 82 | 83 | #-Wilting point based on logarithmic function 84 | wilt = (100 / A)**(-1/B) 85 | return wilt 86 | 87 | #-init pedotransfer processes 88 | def init(self, pcr, config, np): 89 | self.RootSandMap = pcr.readmap(self.inpath + config.get('PEDOTRANSFER','RootSandMap')) / 100 90 | self.RootClayMap = pcr.readmap(self.inpath + config.get('PEDOTRANSFER','RootClayMap')) / 100 91 | self.RootSiltMap = 1 - self.RootSandMap - self.RootClayMap 92 | self.RootOMMap = pcr.readmap(self.inpath + config.get('PEDOTRANSFER','RootOMMap')) 93 | try: 94 | self.RootBulkMap = config.getfloat('PEDOTRANSFER','RootBulkMap') 95 | except: 96 | self.RootBulkMap = pcr.readmap(self.inpath + config.get('PEDOTRANSFER','RootBulkMap')) 97 | 98 | self.SubSandMap = pcr.readmap(self.inpath + config.get('PEDOTRANSFER','SubSandMap')) / 100 99 | self.SubClayMap = pcr.readmap(self.inpath + config.get('PEDOTRANSFER','SubClayMap')) / 100 100 | self.SubOMMap = pcr.readmap(self.inpath + config.get('PEDOTRANSFER','SubOMMap')) 101 | try: 102 | self.SubBulkMap = config.getfloat('PEDOTRANSFER','SubBulkMap') 103 | except: 104 | self.SubBulkMap = pcr.readmap(self.inpath + config.get('PEDOTRANSFER','SubBulkMap')) 105 | 106 | self.RootDryMap = self.pedotransfer.Dry(pcr, self, self.RootSandMap, self.RootClayMap, self.RootOMMap, self.RootBulkMap) 107 | temp = self.pedotransfer.FieldAdj(pcr, self, self.RootSandMap, self.RootClayMap, self.RootOMMap, self.RootBulkMap) 108 | self.RootFieldMap = temp[0] * self.RootFieldFrac 109 | self.RootSatMap = temp[2] * self.RootSatFrac 110 | self.RootFieldMap = pcr.min(self.RootSatMap - 0.0001, self.RootFieldMap) 111 | self.RootWiltMap = self.pedotransfer.Wilt(pcr, self, np) * self.RootWiltFrac 112 | self.RootDryMap = self.RootDryMap * self.RootDryFrac 113 | self.RootKsat = self.pedotransfer.KSat(pcr, self, self.RootSandMap, self.RootClayMap, self.RootOMMap, self.RootBulkMap) * self.RootKsatFrac 114 | self.RootDrainVel = self.RootKsat * self.Slope 115 | 116 | temp = self.pedotransfer.FieldAdj(pcr, self, self.SubSandMap, self.SubClayMap, self.SubOMMap, self.SubBulkMap) 117 | self.SubFieldMap = temp[0] 118 | self.SubSatMap = temp[2] 119 | self.SubKsat = self.pedotransfer.KSat(pcr, self, self.SubSandMap, self.SubClayMap, self.SubOMMap, self.SubBulkMap) 120 | -------------------------------------------------------------------------------- /modules/hspf.py: -------------------------------------------------------------------------------- 1 | # Soil erosion module using the HSPF soil erosion model 2 | # Copyright (C) 2020 Joris Eekhout / Spanish National Research Council (CEBAS-CSIC) 3 | # Email: jeekhout@cebas.csic.es 4 | # 5 | # This program is free software: you can redistribute it and/or modify 6 | # it under the terms of the GNU General Public License as published by 7 | # the Free Software Foundation, either version 3 of the License, or 8 | # (at your option) any later version. 9 | # 10 | # This program is distributed in the hope that it will be useful, 11 | # but WITHOUT ANY WARRANTY; without even the implied warranty of 12 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 13 | # GNU General Public License for more details. 14 | # 15 | # You should have received a copy of the GNU General Public License 16 | # along with this program. If not, see . 17 | 18 | 19 | print('HSPF module imported') 20 | 21 | #-Detachment of soil particles by raindrop impact (ton/acre) 22 | def DetachmentRaindrop(self, pcr, DELT60, CR, SMPF, KRER, RAIN, JRER): 23 | DET = DELT60 * pcr.max(0, (1 - CR - self.NoErosion_HSPF)) * SMPF * KRER * (RAIN / DELT60)**JRER 24 | return DET 25 | 26 | #-Detached sediment in storage (ton/acre) 27 | def SedimentStorage(self, pcr, DETS, AFFIX, DET): 28 | DETS = DETS * (1 - AFFIX) + DET 29 | 30 | return DETS 31 | 32 | #-Detachment of soil particles by washoff (ton/acre) 33 | def DetachmentWashoff(self, pcr, STCAP, DETS, SURO, SURS, CR): 34 | WSSD = pcr.ifthenelse(STCAP > DETS, DETS * SURO / (SURS + SURO), STCAP * SURO / (SURS + SURO)) * (1 - self.NoErosion_HSPF) 35 | 36 | return WSSD 37 | 38 | #-Detachment of soil particles from the soil matrix (ton/acre) 39 | def DetachmentSoilScour(self, pcr, SURO, SURS, DELT60, KGER, JGER): 40 | SCRSD = SURO / (SURS + SURO) * DELT60 * KGER * ((SURS + SURO)/DELT60)**JGER * (1 - self.NoErosion_HSPF) 41 | 42 | #-set values in channels to 0 in case channels should be excluded 43 | if self.exclChannelsFLAG == 1: 44 | SCRSD = SCRSD * self.Hillslope 45 | 46 | return SCRSD 47 | 48 | #-Transport capacity (ton/acre) 49 | def TransportCapacity(self, pcr, DELT60, KSER, SURO, SURS, JSER): 50 | STCAP = DELT60 * KSER * ((SURS + SURO)/DELT60)**JSER * (1 - self.NoErosion_HSPF) 51 | 52 | return STCAP 53 | 54 | #-K factor (-) 55 | def K_HSPF(self, pcr): 56 | ksat_hourly = self.RootKsat / 24 57 | M_textural = (self.RootSiltMap * 100 + 0) * (100 - self.RootClayMap * 100) 58 | permeability = pcr.scalar(ksat_hourly > 150) * 1 59 | permeability = permeability + pcr.scalar(pcr.pcrand(ksat_hourly > 50, ksat_hourly < 150)) * 2 60 | permeability = permeability + pcr.scalar(pcr.pcrand(ksat_hourly > 15, ksat_hourly < 50)) * 3 61 | permeability = permeability + pcr.scalar(pcr.pcrand(ksat_hourly > 5, ksat_hourly < 15)) * 4 62 | permeability = permeability + pcr.scalar(pcr.pcrand(ksat_hourly > 1, ksat_hourly < 5)) * 5 63 | permeability = permeability + pcr.scalar(ksat_hourly < 1) * 6 64 | s = 2 65 | K_HSPF = ((2.1 * 10**-4 * M_textural**1.14 * (12 - self.RootOMMap) + 3.25 * (s - 2) + 2.5 * (permeability - 3))/100) 66 | return K_HSPF 67 | 68 | #-init processes hspf 69 | def init(self, pcr, config): 70 | #-read table with HSPF landuse specific model parameters 71 | pcr.setglobaloption('matrixtable') 72 | hspf_table = self.inpath + config.get('HSPF', 'hspf_table') 73 | self.CR_HSPF = pcr.lookupscalar(hspf_table, 1, self.LandUse) 74 | try: 75 | self.KGER_HSPF = config.getfloat('HSPF', 'KGER') 76 | except: 77 | self.KGER_HSPF = pcr.lookupscalar(hspf_table, 2, self.LandUse) 78 | self.NoErosion_HSPF = pcr.lookupscalar(hspf_table, 3, self.LandUse) 79 | pcr.setglobaloption('columntable') 80 | 81 | #-read other model parameters 82 | self.JRER_HSPF = config.getfloat('HSPF', 'JRER') 83 | self.KSER_HSPF = config.getfloat('HSPF', 'KSER') 84 | self.JSER_HSPF = config.getfloat('HSPF', 'JSER') 85 | self.JGER_HSPF = config.getfloat('HSPF', 'JGER') 86 | self.AFFIX_HSPF = config.getfloat('HSPF', 'AFFIX') 87 | 88 | #-initial sediment storage 89 | self.DETS_HSPF = 0 90 | self.SURSold = 0 91 | 92 | #-define some constants 93 | self.acre_m2_HSPF = 4046.9 94 | self.inch_mm_HSPF = 25.4 95 | 96 | #-read P-factor values map or float 97 | try: 98 | self.P_HSPF = pcr.readmap(self.inpath + config.get('HSPF', 'P_USLE')) 99 | except: 100 | self.P_HSPF = config.getfloat('HSPF', 'P_USLE') 101 | 102 | #-when pedotransfer module is used, calculate the K-factor based on texture maps, else read K-factor values from the config file 103 | if self.PedotransferFLAG == 1: 104 | self.K_HSPF = self.hspf.K_HSPF(self, pcr) 105 | else: 106 | try: 107 | self.K_HSPF = pcr.readmap(self.inpath + config.get('HSPF', 'KRER')) 108 | except: 109 | self.K_HSPF = config.getfloat('HSPF', 'KRER') 110 | 111 | 112 | #-dynamic processes hspf 113 | def dynamic(self, pcr, np, Precip, Runoff): 114 | #-determine daily precipitation in inch 115 | Precip_inch = Precip / self.inch_mm_HSPF 116 | 117 | #-get acre to m2 transformation value 118 | acre_m2_HSPF = self.acre_m2_HSPF 119 | 120 | #-determine detachment of soil particles by raindrop impact (ton/acre) 121 | DET = self.hspf.DetachmentRaindrop(self, pcr, 24, self.CR_HSPF, self.P_HSPF, self.K_HSPF, Precip_inch, self.JRER_HSPF) 122 | 123 | #-determine the sediment storage (ton/acre) 124 | self.DETS_HSPF = self.hspf.SedimentStorage(self, pcr, self.DETS_HSPF, self.AFFIX_HSPF, DET) 125 | 126 | #-determine the surface water storage 127 | SURS = 0 128 | 129 | #-determine the surface outflow (inch) (= routed runoff) 130 | SURO = pcr.max(0.0001, Runoff / self.inch_mm_HSPF) 131 | 132 | #-determine transport capacity (ton/acre) 133 | STCAP = self.hspf.TransportCapacity(self, pcr, 24, self.KSER_HSPF, SURO, SURS, self.JSER_HSPF) 134 | 135 | #-determine detachment of soil particles by washoff (ton/acre) 136 | WSSD = self.hspf.DetachmentWashoff(self, pcr, STCAP, self.DETS_HSPF, SURO, SURS, self.CR_HSPF) 137 | 138 | #-report detachment of soil particles by raindrop impact (ton / cell) 139 | self.reporting.reporting(self, pcr, 'DetRn', WSSD * (pcr.cellarea() / acre_m2_HSPF)) 140 | 141 | #-update sediment storage 142 | self.DETS_HSPF = self.DETS_HSPF - WSSD 143 | 144 | #-determine detachment of soil particles from the soil matrix (ton/acre) 145 | SCRSD = self.hspf.DetachmentSoilScour(self, pcr, SURO, SURS, 24, self.KGER_HSPF, self.JGER_HSPF) 146 | 147 | #-report detachment of soil particles by runoff (ton / cell) 148 | self.reporting.reporting(self, pcr, 'DetRun', SCRSD * (pcr.cellarea() / acre_m2_HSPF)) 149 | 150 | #-determine mass of sediment in transport (ton/acre) 151 | sed = WSSD + SCRSD 152 | 153 | #-report sediment in transport (ton / cell) 154 | self.reporting.reporting(self, pcr, 'SedTrans', sed * (pcr.cellarea() / acre_m2_HSPF)) 155 | 156 | return sed 157 | -------------------------------------------------------------------------------- /modules/snow.py: -------------------------------------------------------------------------------- 1 | # The Spatial Processes in HYdrology (SPHY) model: 2 | # A spatially distributed hydrological model 3 | # Copyright (C) 2013-2025 FutureWater 4 | # Email: sphy@futurewater.nl 5 | # 6 | # Authors (alphabetical order): 7 | # P. Droogers, J. Eekhout, A. Fernandez-Rodriguez, W. Immerzeel, S. Khanal, A. Lutz, T. Schults, G. Simons, W. Terink. 8 | # 9 | # This program is free software: you can redistribute it and/or modify 10 | # it under the terms of the GNU General Public License as published by 11 | # the Free Software Foundation, either version 3 of the License, or 12 | # (at your option) any later version. 13 | # 14 | # This program is distributed in the hope that it will be useful, 15 | # but WITHOUT ANY WARRANTY; without even the implied warranty of 16 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 17 | # GNU General Public License for more details. 18 | # 19 | # You should have received a copy of the GNU General Public License 20 | # along with this program. If not, see . 21 | 22 | 23 | print("snow module imported") 24 | 25 | 26 | # -Function to calculate the potential snow melt 27 | def PotSnowMelt(pcr, temp, tempmax, ddfs): 28 | thour = pcr.scalar(0) 29 | for ij in range(1, 25, 1): 30 | th_max = pcr.max(0, (temp + (tempmax - temp) * pcr.cos(3.1415 * ij / 12))) 31 | thour = thour + th_max 32 | melt = thour * ddfs / 24 33 | return melt 34 | 35 | 36 | # -Function to calculate the actual snow melt 37 | def ActSnowMelt(pcr, snowstore, potmelt): 38 | melt = pcr.min(snowstore, potmelt) 39 | return melt 40 | 41 | 42 | # -Function that updates the snow storage 43 | def SnowStoreUpdate(pcr, snowstore, snow, actmelt, temp, snowwatstore): 44 | snowstore = ( 45 | snowstore 46 | + snow 47 | - actmelt 48 | + pcr.ifthenelse(temp < 0, pcr.scalar(snowwatstore), 0) 49 | ) 50 | return snowstore 51 | 52 | 53 | # -Function that determines the maximum amount of water that can be stored in the snowpack 54 | def MaxSnowWatStorage(snowsc, snowstore): 55 | maxsnowwatstore = snowsc * snowstore 56 | return maxsnowwatstore 57 | 58 | 59 | # -Function to calculate the actual snow water storage 60 | def SnowWatStorage(pcr, temp, maxsnowwatstore, snowwatstore, actmelt, rain): 61 | snowwatstore = pcr.ifthenelse( 62 | temp < 0, 0, pcr.min(maxsnowwatstore, snowwatstore + actmelt + rain) 63 | ) 64 | return snowwatstore 65 | 66 | 67 | # -Function to calculate the total snow storage (snowstore + snowwatstore) 68 | def TotSnowStorage(snowstore, snowwatstore, snowfrac, rainfrac): 69 | totalsnowstore = (snowstore + snowwatstore) * (snowfrac + rainfrac) 70 | return totalsnowstore 71 | 72 | 73 | # -Function to calculate runoff from snow 74 | def SnowR(pcr, snowwatstore, maxsnowwatstore, actmelt, rain, oldsnowwatstore, snowfrac): 75 | snowr = pcr.ifthenelse( 76 | snowwatstore == maxsnowwatstore, 77 | (((actmelt + rain) - (snowwatstore - oldsnowwatstore)) * snowfrac), 78 | 0, 79 | ) 80 | return snowr 81 | 82 | 83 | # -init snow processes 84 | def init(self, pcr, config): 85 | pars = ["Tcrit", "SnowSC", "DDFS", "SnowF", "SnowCth"] 86 | for i in pars: 87 | try: 88 | setattr(self, i, pcr.readmap(self.inpath + config.get("SNOW", i))) 89 | except: 90 | setattr(self, i, config.getfloat("SNOW", i)) 91 | 92 | 93 | # -initial snow processes 94 | def initial(self, pcr, config): 95 | try: 96 | self.SnowStore = config.getfloat("SNOW_INIT", "SnowIni") 97 | except: 98 | self.SnowStore = pcr.readmap(self.inpath + config.get("SNOW_INIT", "SnowIni")) 99 | # -initial water stored in snowpack 100 | try: 101 | self.SnowWatStore = config.getfloat("SNOW_INIT", "SnowWatStore") 102 | except: 103 | self.SnowWatStore = pcr.readmap( 104 | self.inpath + config.get("SNOW_INIT", "SnowWatStore") 105 | ) 106 | self.TotalSnowStore = self.SnowStore + self.SnowWatStore 107 | 108 | 109 | # -dynamic snow processes 110 | def dynamic( 111 | self, 112 | pcr, 113 | Temp, 114 | TempMax, 115 | Precip, 116 | Snow_GLAC, 117 | ActSnowMelt_GLAC, 118 | SnowFrac, 119 | RainFrac, 120 | SnowR_GLAC, 121 | ): 122 | # -Snow and rain differentiation 123 | Snow = pcr.ifthenelse(Temp >= self.Tcrit, 0, Precip) 124 | Rain = pcr.ifthenelse(Temp < self.Tcrit, 0, Precip) 125 | # -Report Snow for entire cell (snow+glacier fraction) 126 | self.reporting.reporting(self, pcr, "TotSnow", Snow) 127 | self.reporting.reporting( 128 | self, pcr, "TotSnowF", Snow * (1 - self.GlacFrac) + Snow_GLAC 129 | ) 130 | # -Snow melt sonu added 131 | PotSnowMelt = pcr.ifthenelse( 132 | TempMax < 0, 0, self.snow.PotSnowMelt(pcr, Temp, TempMax, self.DDFS) 133 | ) 134 | ActSnowMelt = self.snow.ActSnowMelt(pcr, self.SnowStore, PotSnowMelt) 135 | # -Report snow melt for entire cell (snow+glacier fraction) 136 | self.reporting.reporting(self, pcr, "TotSnowMelt", ActSnowMelt) 137 | self.reporting.reporting( 138 | self, pcr, "TotSnowMeltF", ActSnowMelt * (1 - self.GlacFrac) + ActSnowMelt_GLAC 139 | ) 140 | # -Update snow store 141 | self.SnowStore = self.snow.SnowStoreUpdate( 142 | pcr, self.SnowStore, Snow, ActSnowMelt, Temp, self.SnowWatStore 143 | ) 144 | # -Caclulate the maximum amount of water that can be stored in snowwatstore 145 | MaxSnowWatStore = self.snow.MaxSnowWatStorage(self.SnowSC, self.SnowStore) 146 | OldSnowWatStore = self.SnowWatStore 147 | # -Calculate the actual amount of water stored in snowwatstore 148 | self.SnowWatStore = self.snow.SnowWatStorage( 149 | pcr, TempMax, MaxSnowWatStore, self.SnowWatStore, ActSnowMelt, Rain 150 | ) 151 | # -Changes in total water storage in snow (SnowStore and SnowWatStore) 152 | OldTotalSnowStore = self.TotalSnowStore 153 | self.TotalSnowStore = ( 154 | self.snow.TotSnowStorage(self.SnowStore, self.SnowWatStore, SnowFrac, RainFrac) 155 | + self.TotalSnowStore_GLAC 156 | ) # for entire cell 157 | # -Report Snow storage 158 | self.reporting.reporting(self, pcr, "StorSnow", self.TotalSnowStore) 159 | # -Determine if cell is covered with snow 160 | SnowCover = pcr.ifthenelse( 161 | self.TotalSnowStore > self.SnowCth, pcr.scalar(1), pcr.scalar(0) 162 | ) 163 | self.reporting.reporting(self, pcr, "SCover", SnowCover) 164 | self.reporting.reporting( 165 | self, pcr, "StorSnowW", self.SnowWatStore 166 | ) # sonu added note this is only SnowWatStore 167 | # -Snow runoff 168 | SnowR = ( 169 | self.snow.SnowR( 170 | pcr, 171 | self.SnowWatStore, 172 | MaxSnowWatStore, 173 | ActSnowMelt, 174 | Rain, 175 | OldSnowWatStore, 176 | SnowFrac, 177 | ) 178 | + SnowR_GLAC 179 | ) # for entire cell 180 | ##sonu added snow infiltration## 181 | SnowSoil = SnowR * self.SnowF 182 | SnowR = SnowR * (1 - self.SnowF) 183 | SnowR = SnowR * (1 - self.openWaterFrac) 184 | # -Report Snow runoff 185 | self.reporting.reporting(self, pcr, "TotSnowRF", SnowR) 186 | 187 | return Rain, SnowR, SnowSoil, OldTotalSnowStore 188 | -------------------------------------------------------------------------------- /modules/reservoirs.py: -------------------------------------------------------------------------------- 1 | # The Spatial Processes in HYdrology (SPHY) model: 2 | # A spatially distributed hydrological model 3 | # Copyright (C) 2013-2025 FutureWater 4 | # Email: sphy@futurewater.nl 5 | # 6 | # Authors (alphabetical order): 7 | # P. Droogers, J. Eekhout, A. Fernandez-Rodriguez, W. Immerzeel, S. Khanal, A. Lutz, T. Schults, G. Simons, W. Terink. 8 | # 9 | # This program is free software: you can redistribute it and/or modify 10 | # it under the terms of the GNU General Public License as published by 11 | # the Free Software Foundation, either version 3 of the License, or 12 | # (at your option) any later version. 13 | # 14 | # This program is distributed in the hope that it will be useful, 15 | # but WITHOUT ANY WARRANTY; without even the implied warranty of 16 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 17 | # GNU General Public License for more details. 18 | # 19 | # You should have received a copy of the GNU General Public License 20 | # along with this program. If not, see . 21 | 22 | print("Reservoir module imported") 23 | 24 | 25 | # -Advanced reservoir 26 | def QAdv(self, pcr): 27 | DayNo = self.timecalc.julian(self)[0] 28 | # -determine if it is flood or dry season 29 | S1 = pcr.ifthenelse( 30 | self.ResFlStart < self.ResFlEnd, 31 | pcr.ifthenelse( 32 | DayNo >= self.ResFlStart, 33 | pcr.ifthenelse(DayNo <= self.ResFlEnd, pcr.boolean(1), pcr.boolean(0)), 34 | pcr.boolean(0), 35 | ), 36 | pcr.ifthenelse( 37 | DayNo >= self.ResFlEnd, 38 | pcr.ifthenelse(DayNo >= self.ResFlStart, pcr.boolean(1), pcr.boolean(0)), 39 | pcr.ifthenelse( 40 | DayNo <= self.ResFlEnd, 41 | pcr.ifthenelse( 42 | DayNo <= self.ResFlStart, pcr.boolean(1), pcr.boolean(0) 43 | ), 44 | pcr.boolean(0), 45 | ), 46 | ), 47 | ) 48 | 49 | S_avail = pcr.max(self.StorRES - self.ResPVOL, 0) 50 | Q = pcr.max( 51 | pcr.ifthenelse( 52 | S1, 53 | self.ResMaxFl * S_avail / (self.ResEVOL - self.ResPVOL), 54 | self.ResDemFl * S_avail / (self.ResEVOL - self.ResPVOL), 55 | ), 56 | self.StorRES - self.ResEVOL, 57 | ) 58 | return Q 59 | 60 | 61 | # -Simple reservoir 62 | def QSimple(self, pcr): 63 | Q = pcr.max( 64 | pcr.min( 65 | self.ResKr * self.StorRES * (self.StorRES / self.ResSmax) ** self.ResB, 66 | self.StorRES, 67 | ), 68 | self.StorRES - self.ResSmax, 69 | ) 70 | return Q 71 | 72 | 73 | # -Calculates reservoir outflow and the fraction to release, depending on the type of reservoir (simple or advanced) 74 | def QRes(self, pcr): 75 | if self.ResSimple and self.ResAdvanced: 76 | Qout = pcr.ifthenelse( 77 | self.ResFunc == 1, 78 | QSimple(self, pcr), 79 | pcr.ifthenelse(self.ResFunc == 2, QAdv(self, pcr), 0), 80 | ) 81 | elif self.ResSimple: 82 | Qout = pcr.ifthenelse(self.ResFunc == 1, QSimple(self, pcr), 0) 83 | else: 84 | Qout = pcr.ifthenelse(self.ResFunc == 2, QAdv(self, pcr), 0) 85 | 86 | return Qout 87 | 88 | 89 | # -init processes reservoirs 90 | def init(self, pcr, config): 91 | # -set the option to calculate the reservoir inflow, outflow and storage per component 92 | pars = ["RootR", "RootD", "Rain", "Snow", "Glac", "Base"] 93 | for i in pars: 94 | var = "Rep" + i + "_FLAG" 95 | setattr(self, var, config.getint("REPORTING", var)) 96 | 97 | pcr.setglobaloption("matrixtable") 98 | # nominal map with reservoir IDs 99 | self.ResID = pcr.cover( 100 | pcr.readmap(self.inpath + config.get("RESERVOIR", "ResId")), 0 101 | ) 102 | # boolean map with stations that are not reservoirs 103 | self.LocationsNoRes = pcr.ifthenelse( 104 | pcr.pcrand(pcr.scalar(self.Locations) > 0, pcr.scalar(self.ResID) == 0), 105 | pcr.boolean(1), 106 | pcr.boolean(0), 107 | ) 108 | 109 | # lookup table with operational scheme to use (simple or advanced) 110 | ResFunc_Tab = self.inpath + config.get("RESERVOIR", "ResFuncStor") 111 | # Reservoir function 112 | self.ResFunc = pcr.cover(pcr.lookupscalar(ResFunc_Tab, 1, self.ResID), 0) 113 | try: 114 | # lookup table with coefficients for simple reservoirs 115 | ResSimple_Tab = self.inpath + config.get("RESERVOIR", "ResSimple") 116 | # Read coefficients for simple reservoirs 117 | self.ResKr = pcr.lookupscalar(ResSimple_Tab, 1, self.ResID) 118 | self.ResB = pcr.lookupscalar(ResSimple_Tab, 2, self.ResID) 119 | self.ResSmax = ( 120 | pcr.lookupscalar(ResSimple_Tab, 3, self.ResID) * 10**6 121 | ) # convert to m3 122 | self.ResSimple = True 123 | except: 124 | self.ResSimple = False 125 | try: 126 | # lookup table with coefficients for advanced reservoirs 127 | ResAdvanced_Tab = self.inpath + config.get("RESERVOIR", "ResAdv") 128 | # Read coefficients for advanced reservoirs 129 | self.ResEVOL = ( 130 | pcr.lookupscalar(ResAdvanced_Tab, 1, self.ResID) * 10**6 131 | ) # convert to m3 132 | self.ResPVOL = ( 133 | pcr.lookupscalar(ResAdvanced_Tab, 2, self.ResID) * 10**6 134 | ) # convert to m3 135 | self.ResMaxFl = ( 136 | pcr.lookupscalar(ResAdvanced_Tab, 3, self.ResID) * 10**6 137 | ) # convert to m3/d 138 | self.ResDemFl = ( 139 | pcr.lookupscalar(ResAdvanced_Tab, 4, self.ResID) * 10**6 140 | ) # convert to m3/d 141 | self.ResFlStart = pcr.lookupscalar(ResAdvanced_Tab, 5, self.ResID) 142 | self.ResFlEnd = pcr.lookupscalar(ResAdvanced_Tab, 6, self.ResID) 143 | self.ResAdvanced = True 144 | except: 145 | self.ResAdvanced = False 146 | pcr.setglobaloption("columntable") 147 | 148 | 149 | # -initial conditions reservoirs 150 | def initial(self, pcr, config): 151 | ResStor_Tab = self.inpath + config.get("RESERVOIR", "ResFuncStor") 152 | ResStor = ( 153 | pcr.cover(pcr.lookupscalar(ResStor_Tab, 2, self.ResID), 0) * 10**6 154 | ) # convert to m3 155 | try: 156 | self.StorRES = self.StorRES + ResStor 157 | # -Qfrac for reservoir cells should be zero, else 1 158 | self.QFRAC = pcr.ifthenelse(self.ResID != 0, pcr.scalar(0), self.QFRAC) 159 | except: 160 | self.StorRES = ResStor 161 | # -Qfrac for reservoir cells should be zero, else 1 162 | self.QFRAC = pcr.ifthenelse(self.ResID != 0, pcr.scalar(0), 1) 163 | 164 | 165 | # -initial conditions reporting reservoirs 166 | def initial_reporting(self, pcr, pcrm): 167 | self.ResInTSS = pcrm.TimeoutputTimeseries( 168 | "ResInTSS", self, self.ResID, noHeader=True 169 | ) 170 | self.ResOutTSS = pcrm.TimeoutputTimeseries( 171 | "ResOutTSS", self, self.ResID, noHeader=True 172 | ) 173 | self.ResStorTSS = pcrm.TimeoutputTimeseries( 174 | "ResStorTSS", self, self.ResID, noHeader=True 175 | ) 176 | self.ResETaTSS = pcrm.TimeoutputTimeseries( 177 | "ResETaTSS", self, self.ResID, noHeader=True 178 | ) 179 | self.ResInCalTSS = pcrm.TimeoutputTimeseries( 180 | "ResInCalTSS", self, self.ResID, noHeader=True 181 | ) 182 | # -set reporting of water balances for individual components 183 | pars = ["RootR", "RootD", "Rain", "Snow", "Glac", "Base"] 184 | for i in pars: 185 | if eval("self." + i + "RA_FLAG") and getattr(self, "Rep" + i + "_FLAG"): 186 | setattr( 187 | self, 188 | "Res" + i + "InTSS", 189 | pcrm.TimeoutputTimeseries( 190 | "Res" + i + "InTSS", self, self.ResID, noHeader=True 191 | ), 192 | ) 193 | setattr( 194 | self, 195 | "Res" + i + "OutTSS", 196 | pcrm.TimeoutputTimeseries( 197 | "Res" + i + "OutTSS", self, self.ResID, noHeader=True 198 | ), 199 | ) 200 | setattr( 201 | self, 202 | "Res" + i + "StorTSS", 203 | pcrm.TimeoutputTimeseries( 204 | "Res" + i + "StorTSS", self, self.ResID, noHeader=True 205 | ), 206 | ) 207 | -------------------------------------------------------------------------------- /utilities/reporting.py: -------------------------------------------------------------------------------- 1 | # The Spatial Processes in HYdrology (SPHY) model: 2 | # A spatially distributed hydrological model 3 | # Copyright (C) 2013-2019 FutureWater 4 | # Email: sphy@futurewater.nl 5 | # 6 | # Authors (alphabetical order): 7 | # P. Droogers, J. Eekhout, W. Immerzeel, S. Khanal, A. Lutz, G. Simons, W. Terink 8 | # 9 | # This program is free software: you can redistribute it and/or modify 10 | # it under the terms of the GNU General Public License as published by 11 | # the Free Software Foundation, either version 3 of the License, or 12 | # (at your option) any later version. 13 | # 14 | # This program is distributed in the hope that it will be useful, 15 | # but WITHOUT ANY WARRANTY; without even the implied warranty of 16 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 17 | # GNU General Public License for more details. 18 | # 19 | # You should have received a copy of the GNU General Public License 20 | # along with this program. If not, see . 21 | 22 | 23 | #-Function to report the output 24 | def REPM(self, pcr, tot, var, fname, outops, TSS=False, MAP=False, AVG=False): 25 | dim = [31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31] 26 | if self.calendar.isleap(self.curdate.year): 27 | dim[1] = 29 28 | 29 | if self.calendar.isleap(self.curdate.year): 30 | ydays = 366 31 | else: 32 | ydays = 365 33 | 34 | if outops == 'Day': 35 | if TSS: 36 | TSS.sample(var) 37 | if MAP: 38 | self.report(var, self.outpath + fname) 39 | tot = 0 40 | 41 | elif outops == 'Month': 42 | tot = tot + var 43 | if self.curdate.day == dim[self.curdate.month-1]: 44 | if TSS: 45 | TSS.sample(tot) 46 | if MAP: 47 | self.report(tot, self.outpath + fname + 'M') 48 | if AVG: 49 | self.report(tot / dim[self.curdate.month-1], self.outpath + fname + 'M') 50 | tot = 0 51 | 52 | elif outops == 'Year': 53 | if self.timecalc.julian(self)[0] != ydays: 54 | tot = tot + var 55 | else: 56 | tot = tot + var 57 | if TSS: 58 | TSS.sample(tot) 59 | if MAP: 60 | self.report(tot, self.outpath + fname + 'Y') 61 | if AVG: 62 | self.report(tot / ydays, self.outpath + fname + 'Y') 63 | tot = 0 64 | 65 | elif outops == 'MonthSum': 66 | if self.curdate.day != dim[self.curdate.month-1] and self.curdate.year >= self.startYear + self.spinUpYears: 67 | tot[self.curdate.month-1] = tot[self.curdate.month-1] + var 68 | if self.curdate.day == dim[self.curdate.month-1] and self.curdate.year == self.endYear: 69 | pcr.report(tot[self.curdate.month-1] / (self.simYears), self.outpath + fname + 'SumM' + str(self.curdate.month).zfill(2) + '.map') 70 | 71 | elif outops == 'YearSum': 72 | if self.curdate.year >= self.startYear + self.spinUpYears: 73 | tot = tot + var 74 | if self.curdate == self.enddate: 75 | pcr.report(tot / (self.simYears), self.outpath + fname + 'SumY.map') 76 | 77 | elif outops == 'MonthAvg': 78 | if self.curdate.day != dim[self.curdate.month-1] and self.curdate.year >= self.startYear + self.spinUpYears: 79 | tot[self.curdate.month-1] = tot[self.curdate.month-1] + var / dim[self.curdate.month-1] 80 | elif self.curdate.day == dim[self.curdate.month-1] and self.curdate.year == self.endYear: 81 | pcr.report(tot[self.curdate.month-1] / (self.simYears), self.outpath + fname + 'AvgM' + str(self.curdate.month).zfill(2) + '.map') 82 | 83 | elif outops == 'YearAvg': 84 | if self.curdate.year >= self.startYear + self.spinUpYears: 85 | tot = tot + var / ydays 86 | if self.curdate == self.enddate: 87 | pcr.report(tot / (self.simYears), self.outpath + fname + 'AvgY.map') 88 | 89 | else: 90 | if self.curdate != self.enddate: 91 | tot = tot + var 92 | else: 93 | pcr.report(tot, self.outpath + fname + '.map') 94 | tot = 0 95 | return tot 96 | 97 | #-Function to initialise the reporting 98 | def reporting(self, pcr, tot, var): 99 | for outops in ['Day','Month','Year','Final','MonthSum','YearSum','MonthAvg','YearAvg']: 100 | try: 101 | TSS = eval('self.' + tot + '_' + outops + 'TS') 102 | except: 103 | TSS = False 104 | try: 105 | MAP = eval('self.' + tot + '_' + outops + '_map') 106 | except: 107 | MAP = False 108 | try: 109 | AVG = eval('self.' + tot + '_' + outops + '_avg') 110 | except: 111 | AVG = False 112 | if TSS or MAP or AVG: 113 | setattr(self, tot + '_'+outops, REPM(self, pcr, eval('self.'+tot+'_'+outops), var, eval('self.'+tot+'_fname'), outops, TSS, MAP, AVG)) 114 | 115 | #-read reporting from csv file 116 | def initial(self, pcr, csv, pcrm): 117 | #-set reporting options and read initial values 118 | with open(self.inpath + self.RepTab, 'r') as f: 119 | next(f) # skip headings 120 | reader = csv.reader(f, delimiter=',') 121 | for row in reader: 122 | if row[0][:1] != '#': 123 | i = row[0] 124 | mapoutops = row[1] 125 | avgoutops = row[2] 126 | TSoutops = row[3] 127 | if mapoutops == 'NONE' and avgoutops == 'NONE' and TSoutops == 'NONE': 128 | print(i + ' will NOT be reported') 129 | else: 130 | print(i + ' will be reported') 131 | fname = row[4] 132 | setattr(self, i+'_fname', fname) 133 | setattr(self, i, 0.) # use this instead of the commented part above, because it is more logical to always zero as initial condition for reporting 134 | if mapoutops != 'NONE': 135 | mapoutops = mapoutops.split("+") 136 | for j in mapoutops: 137 | if j == 'D': 138 | setattr(self, i+'_Day', eval('self.'+i)) 139 | setattr(self, i+'_Day_map', 1) 140 | elif j == 'M': 141 | setattr(self, i+'_Month', eval('self.'+i)) 142 | setattr(self, i+'_Month_map', 1) 143 | elif j == 'Y': 144 | setattr(self, i+'_Year', eval('self.'+i)) 145 | setattr(self, i+'_Year_map', 1) 146 | elif j == 'MS': 147 | setattr(self, i+'_MonthSum', {m: self.DEM * 0 for m in range(0, 13, 1)}) 148 | setattr(self, i+'_MonthSum_map', 1) 149 | elif j == 'YS': 150 | setattr(self, i+'_YearSum', eval('self.'+i)) 151 | setattr(self, i+'_YearSum_map', 1) 152 | else: 153 | setattr(self, i+'_Final', eval('self.'+i)) 154 | setattr(self, i+'_Final_map', 1) 155 | if avgoutops != 'NONE': 156 | avgoutops = avgoutops.split("+") 157 | for j in avgoutops: 158 | if j == 'M': 159 | setattr(self, i+'_Month', eval('self.'+i)) 160 | setattr(self, i+'_Month_avg', 1) 161 | elif j == 'Y': 162 | setattr(self, i+'_Year', eval('self.'+i)) 163 | setattr(self, i+'_Year_avg', 1) 164 | elif j == 'MA': 165 | setattr(self, i+'_MonthAvg', {m: self.DEM * 0 for m in range(0, 13, 1)}) 166 | setattr(self, i+'_MonthAvg_avg', 1) 167 | elif j == 'YA': 168 | setattr(self, i+'_YearAvg', eval('self.'+i)) 169 | setattr(self, i+'_YearAvg_avg', 1) 170 | if TSoutops != 'NONE': 171 | TSoutops = TSoutops.split("+") 172 | for j in TSoutops: 173 | if j == 'D': 174 | setattr(self, i+'_Day', eval('self.'+i)) 175 | setattr(self, i+'_DayTS', eval('pcrm.TimeoutputTimeseries("'+fname+'DTS'+'", self, self.Locations, noHeader=False)')) 176 | elif j == 'M': 177 | setattr(self, i+'_Month', eval('self.'+i)) 178 | setattr(self, i+'_MonthTS', eval('pcrm.TimeoutputTimeseries("'+fname+'MTS'+'", self, self.Locations, noHeader=False)')) 179 | elif j == 'Y': 180 | setattr(self, i+'_Year', eval('self.'+i)) 181 | setattr(self, i+'_YearTS', eval('pcrm.TimeoutputTimeseries("'+fname+'YTS'+'", self, self.Locations, noHeader=False)')) -------------------------------------------------------------------------------- /modules/dhsvm.py: -------------------------------------------------------------------------------- 1 | # Soil erosion module using the DHSVM soil erosion model 2 | # Copyright (C) 2020 Joris Eekhout / Spanish National Research Council (CEBAS-CSIC) 3 | # Email: jeekhout@cebas.csic.es 4 | # 5 | # This program is free software: you can redistribute it and/or modify 6 | # it under the terms of the GNU General Public License as published by 7 | # the Free Software Foundation, either version 3 of the License, or 8 | # (at your option) any later version. 9 | # 10 | # This program is distributed in the hope that it will be useful, 11 | # but WITHOUT ANY WARRANTY; without even the implied warranty of 12 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 13 | # GNU General Public License for more details. 14 | # 15 | # You should have received a copy of the GNU General Public License 16 | # along with this program. If not, see . 17 | 18 | 19 | print('DHSVM module imported') 20 | 21 | #-Detachment of soil particles by raindrop impact (kg/m2/s) 22 | def DetachmentRaindrop(self, pcr, k_r, F_w, C_G, C_C, M_R, M_D): 23 | D_R = k_r * F_w * pcr.max(0, 1 - C_G - self.NoErosion_DHSVM) * (pcr.max(0, 1 - C_C) * M_R + M_D) 24 | return D_R 25 | 26 | #-Rainfall drop momentum (kg2/s3) 27 | def MomentumRainDrop(self, pcr, np, precSum): 28 | #-store daily precipitation 29 | precipDaily = precSum 30 | 31 | #-determine sum over all raster cells 32 | precIntTotal = np.sum(pcr.pcr2numpy(precSum, 0)) 33 | 34 | #-initiate hour counter and set M_r to 0 35 | hour = 0 36 | M_R = self.DEM * 0 37 | 38 | #-while precipitation sum is larger than 0 39 | while (precIntTotal > 0): 40 | #-determine hourly rainfall intensity 41 | I = pcr.max(0, self.Alpha * precipDaily - ((self.Alpha**2 * precipDaily) / 2) * hour) 42 | 43 | #-determine coefficient alpha 44 | alpha = pcr.scalar(I >= 100) * 11.75 * 1e-8 45 | alpha = alpha + pcr.scalar(pcr.pcrand(I >= 50, I < 100)) * 6.12 * 1e-8 46 | alpha = alpha + pcr.scalar(pcr.pcrand(I >= 10, I < 50)) * 3.75 * 1e-8 47 | alpha = alpha + pcr.scalar(I < 10) * 2.69 * 1e-8 48 | 49 | #-determine coefficient beta 50 | beta = pcr.scalar(I >= 100) * 1.2821 51 | beta = beta + pcr.scalar(pcr.pcrand(I >= 50, I < 100)) * 1.4242 52 | beta = beta + pcr.scalar(pcr.pcrand(I >= 10, I < 50)) * 1.5545 53 | beta = beta + pcr.scalar(I < 10) * 1.6896 54 | 55 | #-calculate rainfall drop momentum based on hourly precipitation intensity and multiply with 1/24 56 | M_R_hour = alpha * I**beta * 1/24 57 | 58 | #-add to daily rainfall drop momentum 59 | M_R = M_R + M_R_hour 60 | 61 | #-determine sum over all raster cells 62 | precIntTotal = np.sum(pcr.pcr2numpy(I, 0)) 63 | 64 | #-increase hour with 1 65 | hour += 1 66 | return M_R 67 | 68 | #-Leaf drip momentum (kg2 / s3) 69 | def MomentumLeafDrip(self, pcr, D, X, rho, DRAIN, g, C_C): 70 | #-determine coefficient a 71 | a = pcr.scalar(pcr.pcrand(D >= 0.033, X >= 7.5)) * 5.14 72 | a = a + pcr.scalar(pcr.pcrand(D >= 0.033, X < 7.5)) * 1.93 73 | a = a + pcr.scalar(D < 0.033) * 0 74 | 75 | #-determine coefficient b 76 | b = pcr.scalar(pcr.pcrand(D >= 0.033, X >= 7.5)) * 660 77 | b = b + pcr.scalar(pcr.pcrand(D >= 0.033, X < 7.5)) * 1640 78 | b = b + pcr.scalar(D < 0.033) * 2200 79 | 80 | #-Ratio M/beta (m) 81 | M_beta = a + b * D 82 | #-Leaf drip fall speed (m/s) 83 | V = (M_beta * g * (1 - pcr.exp(-2*X/M_beta)))**0.5 84 | #-Set the proportion of the drainage that falls as leaf drip equal to the canopy cover 85 | DRIP = C_C 86 | #-Determine the momentum squared for leaf drip (kg2 / s3) 87 | M_D = (((V * rho * self.pi * D**3) / 6)**2 * DRIP * DRAIN) / ((self.pi * D**3) / 6) 88 | return M_D 89 | 90 | #-Detachment of soil particles by runoff (kg/m2/s) 91 | def DetachmentRunoff(self, pcr, beta_de, dy, v_s, TC, C_G): 92 | D_of = beta_de * dy * v_s * TC * pcr.max(0, 1 - self.NoErosion_DHSVM) 93 | 94 | #-set values in channels to 0 in case channels should be excluded 95 | if self.exclChannelsFLAG == 1: 96 | D_of = D_of * self.Hillslope 97 | return D_of 98 | 99 | #-Detachment efficiency (-) 100 | def DetachmentEfficiency(self, pcr, C_s): 101 | beta_de = 0.79 * pcr.exp(-0.6 * C_s) 102 | return beta_de 103 | 104 | #-Settling velocity (m/s) 105 | def SettlingVelocity(self, pcr, g, rho_s, rho, nu, d50): 106 | #-Initial guess of the settling velocity (m/s) 107 | v_s = (4/3 * g * (rho_s / rho) - 1)**0.5 * d50 108 | #-Reynolds number (-) 109 | Rn = (v_s * d50) / nu 110 | #-Drag coefficient (-) 111 | Cd = (24 / Rn) + (3 / (Rn**0.5)) + 0.34 112 | #-Settling velocity (m/s) 113 | v_s = ((4/3 * g * ((rho_s/rho) - 1) * d50) / Cd)**0.5 114 | return v_s 115 | 116 | #-Stream power (kg/m/s3) 117 | def StreamPower(self, pcr, rho, g, Q, S): 118 | SP = rho * g * Q * S 119 | return SP 120 | 121 | #-Transport capacity (m3/m3) 122 | def TransportCapacity(self, pcr, d50, rho, rho_s, S, h, g, SP, SP_cr): 123 | TC = (0.05 / (d50 * (rho_s / rho - 1)**2)) * ((S * h) / g)**0.5 * pcr.max(0, (SP - SP_cr)) 124 | return TC 125 | 126 | #-Water depth (m), flow velocity (m/s) 127 | def Manning(self, pcr, Q, n, WD_ratio, S): 128 | #-Determine flow area and water depth 129 | A = ((Q * n * (2 * ((WD_ratio**2 + 1) / WD_ratio)**0.5)**(2/3)) / S**0.5)**(3/4) 130 | h = (A / WD_ratio)**0.5 131 | 132 | #-Set minimum value for flow area and water depth 133 | h = pcr.max(self.h_min_DHSVM, h) 134 | return h 135 | 136 | #-init processes dhsvm 137 | def init(self, pcr, config): 138 | #-read table with DHSVM landuse specific model parameters 139 | pcr.setglobaloption('matrixtable') 140 | dhsvm_table = self.inpath + config.get('DHSVM', 'dhsvm_table') 141 | self.D_DHSVM = pcr.lookupscalar(dhsvm_table, 1, self.LandUse) 142 | self.X_DHSVM = pcr.lookupscalar(dhsvm_table, 2, self.LandUse) 143 | self.C_G_DHSVM = pcr.lookupscalar(dhsvm_table, 3, self.LandUse) 144 | self.C_C_table_DHSVM = pcr.lookupscalar(dhsvm_table, 4, self.LandUse) 145 | self.n_table_DHSVM = pcr.lookupscalar(dhsvm_table, 5, self.LandUse) 146 | self.root_cohesion_DHSVM = pcr.lookupscalar(dhsvm_table, 6, self.LandUse) 147 | self.NoErosion_DHSVM = pcr.lookupscalar(dhsvm_table, 7, self.LandUse) 148 | 149 | #-read table with soil cohesion per soil class 150 | self.SoilClass_DHSVM = pcr.readmap(self.inpath + config.get('DHSVM', 'SoilClass')) 151 | dhsvm_cohesion_table = self.inpath + config.get('DHSVM', 'dhsvm_cohesion_table') 152 | self.soil_cohesion_DHSVM = pcr.lookupscalar(dhsvm_cohesion_table, 1, self.SoilClass_DHSVM) 153 | pcr.setglobaloption('columntable') 154 | 155 | #-determine overall cohesion from soil and root cohesion 156 | self.C_s_DHSVM = self.soil_cohesion_DHSVM + self.root_cohesion_DHSVM 157 | 158 | #-read other model parameters 159 | self.WD_ratio_DHSVM = config.getfloat('DHSVM', 'WD_ratio') 160 | self.rho_DHSVM = config.getfloat('DHSVM', 'rho') 161 | self.rho_s_DHSVM = config.getfloat('DHSVM', 'rho_s') 162 | self.deltaClay_DHSVM = config.getfloat('DHSVM', 'deltaClay') * 1e-6 163 | self.deltaSilt_DHSVM = config.getfloat('DHSVM', 'deltaSilt') * 1e-6 164 | self.deltaSand_DHSVM = config.getfloat('DHSVM', 'deltaSand') * 1e-6 165 | self.k_r_DHSVM = config.getfloat('DHSVM', 'k_r') 166 | self.h_min_DHSVM = config.getfloat('DHSVM', 'h_min') 167 | self.SP_crit_DHSVM = config.getfloat('DHSVM', 'SP_crit') 168 | 169 | #-define constants 170 | self.F_w_DHSVM = 1 171 | self.g_DHSVM = 9.81 172 | self.visc_DHSVM = 1e-06 173 | 174 | #-determine median grain size 175 | if self.PedotransferFLAG == 1: 176 | self.D50_DHSVM = pcr.ifthenelse(self.RootClayMap > 0.5, pcr.scalar(self.deltaClay_DHSVM), 0) 177 | self.D50_DHSVM = pcr.ifthenelse(self.RootClayMap + self.RootSiltMap > 0.5, self.deltaClay_DHSVM + (self.deltaSilt_DHSVM - self.deltaClay_DHSVM) * (0.5 - self.RootClayMap) / self.RootSiltMap, 0) + self.D50_DHSVM 178 | self.D50_DHSVM = pcr.ifthenelse(self.RootClayMap + self.RootSiltMap < 0.5, self.deltaSilt_DHSVM + (self.deltaSand_DHSVM - self.deltaSilt_DHSVM) * (self.RootSandMap - 0.5) / self.RootSandMap, 0) + self.D50_DHSVM 179 | else: 180 | self.D50_DHSVM = config.getfloat('DHSVM', 'D50') * 1e-6 181 | 182 | #-dynamic processes dhsvm 183 | def dynamic(self, pcr, np, Precip, Q): 184 | #-determine canopy cover from LAI 185 | if self.DynVegFLAG == 1: 186 | C_C_DHSVM = pcr.min(1, self.LAI) 187 | else: 188 | C_C_DHSVM = self.C_C_table_DHSVM 189 | 190 | #-determine rainfall drop momentum (kg2/s3) 191 | M_R = self.dhsvm.MomentumRainDrop(self, pcr, np, Precip) 192 | 193 | #-determine water drainage rate from canopy (m/s) 194 | DRAIN = Precip * 1e-3 / (24 * 60 * 60) 195 | 196 | #-determine leaf drop momentum (kg2/s3) 197 | M_D = self.dhsvm.MomentumLeafDrip(self, pcr, self.D_DHSVM, self.X_DHSVM, self.rho_DHSVM, DRAIN, self.g_DHSVM, C_C_DHSVM) 198 | 199 | #-determine detachment of soil particles by raindrop impact (kg/m2/s) 200 | D_R = self.dhsvm.DetachmentRaindrop(self, pcr, self.k_r_DHSVM, self.F_w_DHSVM, self.C_G_DHSVM, C_C_DHSVM, M_R, M_D) 201 | 202 | #-report detachment of soil particles by raindrop impact (ton / cell) 203 | self.reporting.reporting(self, pcr, 'DetRn', D_R * pcr.cellarea() * 1e-3 * (24 * 60 * 60)) 204 | 205 | #-determine water depth (m) and width of the flow (m) 206 | h = self.dhsvm.Manning(self, pcr, Q, self.n_table_DHSVM, self.WD_ratio_DHSVM, self.Slope) 207 | 208 | #-determine detachment efficiency (-) 209 | beta_de = self.dhsvm.DetachmentEfficiency(self, pcr, self.C_s_DHSVM) 210 | 211 | #-determine settling velocity (m/s) 212 | v_s = self.dhsvm.SettlingVelocity(self, pcr, self.g_DHSVM, self.rho_s_DHSVM, self.rho_DHSVM, self.visc_DHSVM, self.D50_DHSVM) 213 | 214 | #-determine stream power (kg m/s3) 215 | SP = self.dhsvm.StreamPower(self, pcr, self.rho_DHSVM, self.g_DHSVM, Q, self.Slope) 216 | 217 | #-determine transport capacity (m3/m3) 218 | TC = self.dhsvm.TransportCapacity(self, pcr, self.D50_DHSVM, self.rho_DHSVM, self.rho_s_DHSVM, self.Slope, h, self.g_DHSVM, SP, self.SP_crit_DHSVM) 219 | 220 | #-determine detachment of soil particles by runoff (kg/m2/s) 221 | D_of = self.dhsvm.DetachmentRunoff(self, pcr, beta_de, pcr.celllength(), v_s, TC, self.C_G_DHSVM) 222 | 223 | #-report detachment of soil particles by runoff (ton / cell) 224 | self.reporting.reporting(self, pcr, 'DetRun', D_of * pcr.cellarea() * 1e-3 * (24 * 60 * 60)) 225 | 226 | #-determine mass of sediment in transport (kg/m2/s) 227 | sed = D_R + D_of 228 | 229 | #-report sediment in transport (ton / cell) 230 | self.reporting.reporting(self, pcr, 'SedTrans', sed * pcr.cellarea() * 1e-3 * (24 * 60 * 60)) 231 | 232 | return sed 233 | -------------------------------------------------------------------------------- /modules/shetran.py: -------------------------------------------------------------------------------- 1 | # Soil erosion module using the SHETRAN soil erosion model 2 | # Copyright (C) 2020 Joris Eekhout / Spanish National Research Council (CEBAS-CSIC) 3 | # Email: jeekhout@cebas.csic.es 4 | # 5 | # This program is free software: you can redistribute it and/or modify 6 | # it under the terms of the GNU General Public License as published by 7 | # the Free Software Foundation, either version 3 of the License, or 8 | # (at your option) any later version. 9 | # 10 | # This program is distributed in the hope that it will be useful, 11 | # but WITHOUT ANY WARRANTY; without even the implied warranty of 12 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 13 | # GNU General Public License for more details. 14 | # 15 | # You should have received a copy of the GNU General Public License 16 | # along with this program. If not, see . 17 | 18 | 19 | print('SHETRAN module imported') 20 | 21 | #-Detachment of soil particles by raindrop impact (kg/m2/s) 22 | def DetachmentRaindrop(self, pcr, k_r, F_w, C_g, C_r, M_r, M_d): 23 | D_r = k_r * F_w * pcr.max(0, 1 - C_g - C_r - self.NoErosion_SHETRAN) * (M_r + M_d) 24 | return D_r 25 | 26 | #-Rainfall drop momentum (kg2/s3) 27 | def MomentumRainDrop(self, pcr, np, C_c, precSum): 28 | #-store daily precipitation 29 | precipDaily = precSum 30 | 31 | #-determine sum over all raster cells 32 | precIntTotal = np.sum(pcr.pcr2numpy(precSum, 0)) 33 | 34 | #-initiate hour counter and set M_r to 0 35 | hour = 0 36 | M_r = self.DEM * 0 37 | 38 | #-while precipitation sum is larger than 0 39 | while (precIntTotal > 0): 40 | #-determine hourly rainfall intensity 41 | I = pcr.max(0, self.Alpha * precipDaily - ((self.Alpha**2 * precipDaily) / 2) * hour) 42 | 43 | a_1 = pcr.scalar(I >= 100) * 11.737 * 1e-8 44 | a_1 = a_1 + pcr.scalar(pcr.pcrand(I >= 50, I < 100)) * 6.1192 * 1e-8 45 | a_1 = a_1 + pcr.scalar(pcr.pcrand(I >= 10, I < 50)) * 3.7514 * 1e-8 46 | a_1 = a_1 + pcr.scalar(I < 10) * 2.6893 * 1e-8 47 | 48 | b_1 = pcr.scalar(I >= 100) * 1.2821 49 | b_1 = b_1 + pcr.scalar(pcr.pcrand(I >= 50, I < 100)) * 1.4242 50 | b_1 = b_1 + pcr.scalar(pcr.pcrand(I >= 10, I < 50)) * 1.5545 51 | b_1 = b_1 + pcr.scalar(I < 10) * 1.6896 52 | 53 | #-calculate rainfall drop momentum based on hourly precipitation intensity and multiply with 1/24 54 | M_r_hour = (1 - C_c) * a_1 * I**b_1 * 1/24 55 | 56 | #-add to daily rainfall drop momentum 57 | M_r = M_r + M_r_hour 58 | 59 | #-determine sum over all raster cells 60 | precIntTotal = np.sum(pcr.pcr2numpy(I, 0)) 61 | 62 | #-increase hour with 1 63 | hour += 1 64 | return M_r 65 | 66 | #-Leaf drip momentum (kg2/s3) 67 | def MomentumLeafDrip(self, pcr, d_l, X, rho, DRAINA, g, C_c): 68 | a_2 = pcr.scalar(pcr.pcrand(d_l >= 0.033, X >= 7.5)) * 5.14 69 | a_2 = a_2 + pcr.scalar(pcr.pcrand(d_l >= 0.033, X < 7.5)) * 1.93 70 | a_2 = a_2 + pcr.scalar(d_l < 0.033) * 0 71 | 72 | b_2 = pcr.scalar(pcr.pcrand(d_l >= 0.033, X >= 7.5)) * 660 73 | b_2 = b_2 + pcr.scalar(pcr.pcrand(d_l >= 0.033, X < 7.5)) * 1640 74 | b_2 = b_2 + pcr.scalar(d_l < 0.033) * 2200 75 | 76 | M_beta = a_2 + b_2 * d_l 77 | V_d = (M_beta * g * (1 - pcr.exp(-2*X/M_beta)))**0.5 78 | 79 | L_d = C_c 80 | 81 | M_d = self.pi / 6 * V_d**2 * rho**2 * d_l**3 * L_d * DRAINA 82 | return M_d 83 | 84 | #-Detachment of soil particles by runoff (kg/m2/s) 85 | def DetachmentRunoff(self, pcr, k_f, C_r, tau, tau_cr, C_g): 86 | D_q = pcr.ifthenelse(tau > tau_cr, k_f * pcr.max(0, 1 - C_g - C_r - self.NoErosion_SHETRAN) * (tau/tau_cr - 1), 0) 87 | 88 | #-set values in channels to 0 in case channels should be excluded 89 | if self.exclChannelsFLAG == 1: 90 | D_q = D_q * self.Hillslope 91 | return D_q 92 | 93 | #-Water depth (m) and flow width (m) 94 | def Manning(self, pcr, Q, n, WD_ratio, S): 95 | A = ((Q * n * (2 * ((WD_ratio**2 + 1) / WD_ratio)**0.5)**(2/3)) / S**0.5)**(3/4) 96 | h = (A / WD_ratio)**0.5 97 | l = WD_ratio * h 98 | return h, l 99 | 100 | #-Shear stress (N/m2) 101 | def ShearStress(self, pcr, rho, g, h, S): 102 | tau = rho * g * h * S 103 | return tau 104 | 105 | #-Critical shear stress (N/m2) 106 | def ShearStressCritical(self, pcr, tau, rho_s, rho, g, D_50, nu): 107 | R_star = pcr.max(0.03, (D_50 * (tau / rho)**0.5) / nu) 108 | 109 | a_3 = pcr.scalar(R_star > 400) * 0.056 110 | a_3 = a_3 + pcr.scalar(pcr.pcrand(R_star > 135, R_star <= 400)) * 0.03 111 | a_3 = a_3 + pcr.scalar(pcr.pcrand(R_star > 30, R_star <= 135)) * 0.013 112 | a_3 = a_3 + pcr.scalar(pcr.pcrand(R_star > 6, R_star <= 30)) * 0.033 113 | a_3 = a_3 + pcr.scalar(pcr.pcrand(R_star > 1, R_star <= 6)) * 0.1 114 | a_3 = a_3 + pcr.scalar(pcr.pcrand(R_star >= 0.03, R_star <= 1)) * 0.1 115 | 116 | b_3 = pcr.scalar(R_star > 400) * 0 117 | b_3 = b_3 + pcr.scalar(pcr.pcrand(R_star > 135, R_star <= 400)) * 0.1 118 | b_3 = b_3 + pcr.scalar(pcr.pcrand(R_star > 30, R_star <= 135)) * 0.28 119 | b_3 = b_3 + pcr.scalar(pcr.pcrand(R_star > 6, R_star <= 30)) * 0 120 | b_3 = b_3 + pcr.scalar(pcr.pcrand(R_star > 1, R_star <= 6)) * -0.62 121 | b_3 = b_3 + pcr.scalar(pcr.pcrand(R_star >= 0.03, R_star <= 1)) * -0.3 122 | 123 | tau_cr = (rho_s - rho) * g * D_50 * a_3 * R_star**b_3 124 | return tau_cr 125 | 126 | 127 | #-Capacity particulate transport rate for overland flow (m3/s) 128 | def Capacity(self, pcr, np, tau, tau_cr, rho, rho_s, g, h, l, Q, D50, S): 129 | if self.CapacityEquation == 1: # Yalin (1963) 130 | a = 2.45 * (tau_cr / ((rho_s - rho) * g * D50))**0.5 * (rho_s / rho)**(-0.4) 131 | delta = pcr.max(tau / tau_cr - 1, 0) 132 | 133 | G_tot = 0.635 * (tau / rho)**0.5 * l * D50 * delta * (1 - 1 / (a * pcr.max(1e-6, delta)) * pcr.ln(1 + a * delta)) 134 | elif self.CapacityEquation == 2: # Engelund & Hansen (1963) 135 | G_tot = pcr.ifthenelse(h > 0, (0.05 * Q**2 * S**(3/2)) / ((g * h)**0.5 * (rho_s / rho - 1)**2 * D50 * l), 0) 136 | return G_tot 137 | 138 | #-Mass of sediment transported (kg/m2/s) 139 | def sedimentTransported(self, pcr, D_r, D_q, G_tot, rho_s): 140 | #-determine transport capacity in (kg/m2/s) 141 | TC = G_tot * rho_s / pcr.cellarea() 142 | sed = pcr.ifthenelse(D_r + D_q < TC, D_r + D_q, TC) 143 | return sed 144 | 145 | #-init processes shetran 146 | def init(self, pcr, config): 147 | #-read table with SHETRAN landuse specific model parameters 148 | pcr.setglobaloption('matrixtable') 149 | shetran_table = self.inpath + config.get('SHETRAN', 'shetran_table') 150 | self.d_l_SHETRAN = pcr.lookupscalar(shetran_table, 1, self.LandUse) 151 | self.X_SHETRAN = pcr.lookupscalar(shetran_table, 2, self.LandUse) 152 | self.C_g_SHETRAN = pcr.lookupscalar(shetran_table, 3, self.LandUse) 153 | self.C_c_table_SHETRAN = pcr.lookupscalar(shetran_table, 4, self.LandUse) 154 | self.n_table_SHETRAN = pcr.lookupscalar(shetran_table, 5, self.LandUse) 155 | self.NoErosion_SHETRAN = pcr.lookupscalar(shetran_table, 6, self.LandUse) 156 | pcr.setglobaloption('columntable') 157 | 158 | #-read other model parameters 159 | self.WD_ratio_SHETRAN = config.getfloat('SHETRAN', 'WD_ratio') 160 | self.rho_SHETRAN = config.getfloat('SHETRAN', 'rho') 161 | self.rho_s_SHETRAN = config.getfloat('SHETRAN', 'rho_s') 162 | self.deltaClay_SHETRAN = config.getfloat('SHETRAN', 'deltaClay') * 1e-6 163 | self.deltaSilt_SHETRAN = config.getfloat('SHETRAN', 'deltaSilt') * 1e-6 164 | self.deltaSand_SHETRAN = config.getfloat('SHETRAN', 'deltaSand') * 1e-6 165 | self.CapacityEquation = config.getint('SHETRAN', 'capacityEquation') 166 | self.k_r_SHETRAN = config.getfloat('SHETRAN', 'k_r') 167 | self.k_f_SHETRAN = config.getfloat('SHETRAN', 'k_f') 168 | 169 | #-define some constants 170 | self.F_w_SHETRAN = 1 171 | self.g_SHETRAN = 9.81 172 | self.nu_SHETRAN = 1e-06 173 | 174 | #-determine median grain size 175 | if self.PedotransferFLAG == 1: 176 | self.D50_SHETRAN = pcr.ifthenelse(self.RootClayMap > 0.5, pcr.scalar(self.deltaClay_SHETRAN), 0) 177 | self.D50_SHETRAN = pcr.ifthenelse(self.RootClayMap + self.RootSiltMap > 0.5, self.deltaClay_SHETRAN + (self.deltaSilt_SHETRAN - self.deltaClay_SHETRAN) * (0.5 - self.RootClayMap) / self.RootSiltMap, 0) + self.D50_SHETRAN 178 | self.D50_SHETRAN = pcr.ifthenelse(self.RootClayMap + self.RootSiltMap < 0.5, self.deltaSilt_SHETRAN + (self.deltaSand_SHETRAN - self.deltaSilt_SHETRAN) * (self.RootSandMap - 0.5) / self.RootSandMap, 0) + self.D50_SHETRAN 179 | else: 180 | self.D50_SHETRAN = config.getfloat('SHETRAN', 'D50') * 1e-6 181 | 182 | 183 | #-dynamic processes shetran 184 | def dynamic(self, pcr, np, Precip, Q): 185 | #-determine canopy cover from LAI 186 | if self.DynVegFLAG == 1: 187 | C_c_SHETRAN = pcr.min(1, self.LAI) 188 | else: 189 | C_c_SHETRAN = self.C_c_table_SHETRAN 190 | 191 | #-determine rainfall drop momentum (kg2/s3) 192 | M_r = self.shetran.MomentumRainDrop(self, pcr, np, C_c_SHETRAN, Precip) 193 | 194 | #-determine water drainage rate from canopy (m/s) 195 | DRAINA = Precip * 1e-3 / (24 * 60 * 60) 196 | 197 | #-determine leaf drop momentum (kg2/s3) 198 | M_d = self.shetran.MomentumLeafDrip(self, pcr, self.d_l_SHETRAN, self.X_SHETRAN, self.rho_SHETRAN, DRAINA, self.g_SHETRAN, C_c_SHETRAN) 199 | 200 | #-determine detachment of soil particles by raindrop impact (kg/m2/s) 201 | D_r = self.shetran.DetachmentRaindrop(self, pcr, self.k_r_SHETRAN, self.F_w_SHETRAN, self.C_g_SHETRAN, self.RockFrac, M_r, M_d) 202 | 203 | #-report detachment of soil particles by raindrop impact (ton / cell) 204 | self.reporting.reporting(self, pcr, 'DetRn', D_r * pcr.cellarea() * 1e-3 * (24 * 60 * 60)) 205 | 206 | #-determine water depth (m) and width of the flow (m) 207 | h, l = self.shetran.Manning(self, pcr, Q, self.n_table_SHETRAN, self.WD_ratio_SHETRAN, self.Slope) 208 | 209 | #-determine shear stress (N/m2) 210 | tau = self.shetran.ShearStress(self, pcr, self.rho_SHETRAN, self.g_SHETRAN, h, self.Slope) 211 | 212 | #-determine shear stress (N/m2) 213 | tau_cr = self.shetran.ShearStressCritical(self, pcr, tau, self.rho_s_SHETRAN, self.rho_SHETRAN, self.g_SHETRAN, self.D50_SHETRAN, self.nu_SHETRAN) 214 | 215 | #-determine detachment of soil particles by runoff (kg/m2/s) 216 | D_q = self.shetran.DetachmentRunoff(self, pcr, self.k_f_SHETRAN, self.RockFrac, tau, tau_cr, self.C_g_SHETRAN) 217 | 218 | #-report detachment of soil particles by runoff (ton / cell) 219 | self.reporting.reporting(self, pcr, 'DetRun', D_q * pcr.cellarea() * 1e-3 * (24 * 60 * 60)) 220 | 221 | #-Determine transport capacity of the flow (m3/s) 222 | G_tot = self.shetran.Capacity(self, pcr, np, tau, tau_cr, self.rho_SHETRAN, self.rho_s_SHETRAN, self.g_SHETRAN, h, l, Q, self.D50_SHETRAN, self.Slope) 223 | 224 | #-determine mass of sediment in transport (kg/m2/s) 225 | sed = self.shetran.sedimentTransported(self, pcr, D_r, D_q, G_tot, self.rho_s_SHETRAN) 226 | 227 | #-report sediment in transport (ton / cell) 228 | self.reporting.reporting(self, pcr, 'SedTrans', sed * pcr.cellarea() * 1e-3 * (24 * 60 * 60)) 229 | 230 | return sed 231 | -------------------------------------------------------------------------------- /modules/lakes.py: -------------------------------------------------------------------------------- 1 | # The Spatial Processes in HYdrology (SPHY) model: 2 | # A spatially distributed hydrological model 3 | # Copyright (C) 2013-2025 FutureWater 4 | # Email: sphy@futurewater.nl 5 | # 6 | # Authors (alphabetical order): 7 | # P. Droogers, J. Eekhout, A. Fernandez-Rodriguez, W. Immerzeel, S. Khanal, A. Lutz, T. Schults, G. Simons, W. Terink. 8 | # 9 | # This program is free software: you can redistribute it and/or modify 10 | # it under the terms of the GNU General Public License as published by 11 | # the Free Software Foundation, either version 3 of the License, or 12 | # (at your option) any later version. 13 | # 14 | # This program is distributed in the hope that it will be useful, 15 | # but WITHOUT ANY WARRANTY; without even the implied warranty of 16 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 17 | # GNU General Public License for more details. 18 | # 19 | # You should have received a copy of the GNU General Public License 20 | # along with this program. If not, see . 21 | 22 | print("Lake module imported") 23 | 24 | 25 | # -Function that updates the lake storage and lake level given a measured lake level. If no lake 26 | # level is measured, then the actual storage is not updated with a measured level. The function 27 | # returns the updated storage and lake level 28 | def UpdateLakeHStore(self, pcr, pcrm): 29 | # -buffer actual storage 30 | OldStorage = self.StorRES 31 | # -Check if measured lake levels area available 32 | try: 33 | LakeLevel = pcr.readmap(pcrm.generateNameT(self.LLevel, self.counter)) 34 | Level = True 35 | except: 36 | Level = False 37 | if Level: 38 | # -update lake storage according to measured water level 39 | self.StorRES = pcr.ifthenelse( 40 | self.UpdateLakeLevel, 41 | pcr.ifthenelse( 42 | pcr.defined(LakeLevel), 43 | pcr.ifthenelse( 44 | self.LakeSH_Func == 1, 45 | self.LakeSH_exp_a * pcr.exp(self.LakeSH_exp_b * LakeLevel), 46 | pcr.ifthenelse( 47 | self.LakeSH_Func == 2, 48 | self.LakeSH_pol_a1 * LakeLevel + self.LakeSH_pol_b, 49 | pcr.ifthenelse( 50 | self.LakeSH_Func == 3, 51 | (self.LakeSH_pol_a2 * LakeLevel**2) 52 | + self.LakeSH_pol_a1 * LakeLevel 53 | + self.LakeSH_pol_b, 54 | (self.LakeSH_pol_a3 * LakeLevel**3) 55 | + (self.LakeSH_pol_a2 * LakeLevel**2) 56 | + (self.LakeSH_pol_a1 * LakeLevel + self.LakeSH_pol_b), 57 | ), 58 | ), 59 | ), 60 | self.StorRES, 61 | ), 62 | self.StorRES, 63 | ) 64 | # prevent storage becoming negative for whatever reason 65 | self.StorRES = pcr.max(self.StorRES, 0) 66 | # -Update the lake level based on the storage for lakes where no levels are measured 67 | LakeLevel = pcr.ifthenelse( 68 | self.UpdateLakeLevel, 69 | pcr.ifthenelse( 70 | pcr.defined(LakeLevel), 71 | LakeLevel, 72 | pcr.ifthenelse( 73 | self.LakeHS_Func == 1, 74 | self.LakeHS_exp_a * pcr.exp(self.LakeHS_exp_b * self.StorRES), 75 | pcr.ifthenelse( 76 | self.LakeHS_Func == 2, 77 | self.LakeHS_pol_a1 * self.StorRES + self.LakeHS_pol_b, 78 | pcr.ifthenelse( 79 | self.LakeHS_Func == 3, 80 | (self.LakeHS_pol_a2 * self.StorRES**2) 81 | + self.LakeHS_pol_a1 * self.StorRES 82 | + self.LakeHS_pol_b, 83 | (self.LakeHS_pol_a3 * self.StorRES**3) 84 | + (self.LakeHS_pol_a2 * self.StorRES**2) 85 | + self.LakeHS_pol_a1 * self.StorRES 86 | + self.LakeHS_pol_b, 87 | ), 88 | ), 89 | ), 90 | ), 91 | pcr.ifthenelse( 92 | self.LakeHS_Func == 1, 93 | self.LakeHS_exp_a * pcr.exp(self.LakeHS_exp_b * self.StorRES), 94 | pcr.ifthenelse( 95 | self.LakeHS_Func == 2, 96 | self.LakeHS_pol_a1 * self.StorRES + self.LakeHS_pol_b, 97 | pcr.ifthenelse( 98 | self.LakeHS_Func == 3, 99 | (self.LakeHS_pol_a2 * self.StorRES**2) 100 | + self.LakeHS_pol_a1 * self.StorRES 101 | + self.LakeHS_pol_b, 102 | (self.LakeHS_pol_a3 * self.StorRES**3) 103 | + (self.LakeHS_pol_a2 * self.StorRES**2) 104 | + self.LakeHS_pol_a1 * self.StorRES 105 | + self.LakeHS_pol_b, 106 | ), 107 | ), 108 | ), 109 | ) 110 | 111 | else: 112 | # if no lake level map is available, then calculate the h based on storages 113 | LakeLevel = pcr.ifthenelse( 114 | self.LakeHS_Func == 1, 115 | self.LakeHS_exp_a * pcr.exp(self.LakeHS_exp_b * self.StorRES), 116 | pcr.ifthenelse( 117 | self.LakeHS_Func == 2, 118 | self.LakeHS_pol_a1 * self.StorRES + self.LakeHS_pol_b, 119 | pcr.ifthenelse( 120 | self.LakeHS_Func == 3, 121 | (self.LakeHS_pol_a2 * self.StorRES**2) 122 | + self.LakeHS_pol_a1 * self.StorRES 123 | + self.LakeHS_pol_b, 124 | (self.LakeHS_pol_a3 * self.StorRES**3) 125 | + (self.LakeHS_pol_a2 * self.StorRES**2) 126 | + self.LakeHS_pol_a1 * self.StorRES 127 | + self.LakeHS_pol_b, 128 | ), 129 | ), 130 | ) 131 | self.StorRES = pcr.ifthenelse(self.LakeID != 0, self.StorRES, OldStorage) 132 | return LakeLevel, self.StorRES 133 | 134 | 135 | # -function that calculates the fraction of lake storage that is available for routing, and the lake outflow 136 | def QLake(self, pcr, LakeLevel): 137 | Qout = pcr.ifthenelse( 138 | self.LakeQH_Func == 1, 139 | self.LakeQH_exp_a * pcr.exp(self.LakeQH_exp_b * LakeLevel), 140 | pcr.ifthenelse( 141 | self.LakeQH_Func == 2, 142 | self.LakeQH_pol_a1 * LakeLevel + self.LakeQH_pol_b, 143 | pcr.ifthenelse( 144 | self.LakeQH_Func == 3, 145 | (self.LakeQH_pol_a2 * LakeLevel**2) 146 | + self.LakeQH_pol_a1 * LakeLevel 147 | + self.LakeQH_pol_b, 148 | (self.LakeQH_pol_a3 * LakeLevel**3) 149 | + (self.LakeQH_pol_a2 * LakeLevel**2) 150 | + self.LakeQH_pol_a1 * LakeLevel 151 | + self.LakeQH_pol_b, 152 | ), 153 | ), 154 | ) 155 | Qout = pcr.max(0, Qout) 156 | Qout = Qout * 3600 * 24 # -convert to m3/d 157 | Qout = pcr.cover(Qout, 0) # -for non-lake cells, Qout is zero 158 | return Qout 159 | 160 | 161 | # -init processes lake 162 | def init(self, pcr, config): 163 | # -set the option to calculate the lake inflow, outflow and storage per component 164 | pars = ["RootR", "RootD", "Rain", "Snow", "Glac", "Base"] 165 | for i in pars: 166 | var = "Rep" + i + "_FLAG" 167 | setattr(self, var, config.getint("REPORTING", var)) 168 | 169 | pcr.setglobaloption("matrixtable") 170 | # nominal map with lake IDs 171 | self.LakeID = pcr.cover(pcr.readmap(self.inpath + config.get("LAKE", "LakeId")), 0) 172 | # lookup table with function for each lake (exp, 1-order poly, 2-order poly, 3-order poly) 173 | LakeFunc_Tab = self.inpath + config.get("LAKE", "LakeFunc") 174 | # lookup table with Qh-coeficients for each lake 175 | LakeQH_Tab = self.inpath + config.get("LAKE", "LakeQH") 176 | # lookup table with Sh-coeficients for each lake 177 | LakeSH_Tab = self.inpath + config.get("LAKE", "LakeSH") 178 | # lookup table with hS-coeficients for each lake 179 | LakeHS_Tab = self.inpath + config.get("LAKE", "LakeHS") 180 | # create lake coefficient maps 181 | self.LakeQH_Func = pcr.lookupnominal(LakeFunc_Tab, 1, self.LakeID) 182 | self.LakeSH_Func = pcr.lookupnominal(LakeFunc_Tab, 2, self.LakeID) 183 | self.LakeHS_Func = pcr.lookupnominal(LakeFunc_Tab, 3, self.LakeID) 184 | # Read QH coefficients 185 | self.LakeQH_exp_a = pcr.lookupscalar(LakeQH_Tab, 1, self.LakeID) 186 | self.LakeQH_exp_b = pcr.lookupscalar(LakeQH_Tab, 2, self.LakeID) 187 | self.LakeQH_pol_b = pcr.lookupscalar(LakeQH_Tab, 3, self.LakeID) 188 | self.LakeQH_pol_a1 = pcr.lookupscalar(LakeQH_Tab, 4, self.LakeID) 189 | self.LakeQH_pol_a2 = pcr.lookupscalar(LakeQH_Tab, 5, self.LakeID) 190 | self.LakeQH_pol_a3 = pcr.lookupscalar(LakeQH_Tab, 6, self.LakeID) 191 | # Read SH coefficients 192 | self.LakeSH_exp_a = pcr.lookupscalar(LakeSH_Tab, 1, self.LakeID) 193 | self.LakeSH_exp_b = pcr.lookupscalar(LakeSH_Tab, 2, self.LakeID) 194 | self.LakeSH_pol_b = pcr.lookupscalar(LakeSH_Tab, 3, self.LakeID) 195 | self.LakeSH_pol_a1 = pcr.lookupscalar(LakeSH_Tab, 4, self.LakeID) 196 | self.LakeSH_pol_a2 = pcr.lookupscalar(LakeSH_Tab, 5, self.LakeID) 197 | self.LakeSH_pol_a3 = pcr.lookupscalar(LakeSH_Tab, 6, self.LakeID) 198 | # Read HS coefficients 199 | self.LakeHS_exp_a = pcr.lookupscalar(LakeHS_Tab, 1, self.LakeID) 200 | self.LakeHS_exp_b = pcr.lookupscalar(LakeHS_Tab, 2, self.LakeID) 201 | self.LakeHS_pol_b = pcr.lookupscalar(LakeHS_Tab, 3, self.LakeID) 202 | self.LakeHS_pol_a1 = pcr.lookupscalar(LakeHS_Tab, 4, self.LakeID) 203 | self.LakeHS_pol_a2 = pcr.lookupscalar(LakeHS_Tab, 5, self.LakeID) 204 | self.LakeHS_pol_a3 = pcr.lookupscalar(LakeHS_Tab, 6, self.LakeID) 205 | # -read water level maps and parameters if available 206 | try: 207 | self.UpdateLakeLevel = pcr.readmap( 208 | self.inpath + config.get("LAKE", "updatelakelevel") 209 | ) 210 | self.LLevel = self.inpath + config.get("LAKE", "LakeFile") 211 | print("measured lake levels will be used to update lake storage") 212 | except: 213 | pass 214 | pcr.setglobaloption("columntable") 215 | 216 | 217 | # -initial conditions lakes 218 | def initial(self, pcr, config): 219 | LakeStor_Tab = self.inpath + config.get("LAKE", "LakeStor") 220 | self.StorRES = ( 221 | pcr.cover(pcr.lookupscalar(LakeStor_Tab, 1, self.LakeID), 0) * 10**6 222 | ) # convert to m3 223 | # -Qfrac for lake cells should be zero, else 1 224 | self.QFRAC = pcr.ifthenelse(self.LakeID != 0, pcr.scalar(0), 1) 225 | 226 | 227 | # -initial conditions reporting lakes 228 | def initial_reporting(self, pcr, pcrm): 229 | self.LakeInTSS = pcrm.TimeoutputTimeseries( 230 | "LakeInTSS", self, self.LakeID, noHeader=True 231 | ) 232 | self.LakeOutTSS = pcrm.TimeoutputTimeseries( 233 | "LakeOutTSS", self, self.LakeID, noHeader=True 234 | ) 235 | self.LakeStorTSS = pcrm.TimeoutputTimeseries( 236 | "LakeStorTSS", self, self.LakeID, noHeader=True 237 | ) 238 | # -set reporting of water balances for individual components 239 | pars = ["RootR", "RootD", "Rain", "Snow", "Glac", "Base"] 240 | for i in pars: 241 | if eval("self." + i + "RA_FLAG") and getattr(self, "Rep" + i + "_FLAG"): 242 | setattr( 243 | self, 244 | "Lake" + i + "InTSS", 245 | pcrm.TimeoutputTimeseries( 246 | "Lake" + i + "InTSS", self, self.ResID, noHeader=True 247 | ), 248 | ) 249 | setattr( 250 | self, 251 | "Lake" + i + "OutTSS", 252 | pcrm.TimeoutputTimeseries( 253 | "Lake" + i + "OutTSS", self, self.ResID, noHeader=True 254 | ), 255 | ) 256 | setattr( 257 | self, 258 | "Lake" + i + "StorTSS", 259 | pcrm.TimeoutputTimeseries( 260 | "Lake" + i + "StorTSS", self, self.ResID, noHeader=True 261 | ), 262 | ) 263 | -------------------------------------------------------------------------------- /utilities/netcdf2PCraster.py: -------------------------------------------------------------------------------- 1 | # Tool to force the SPHY model with NetCDF files 2 | # Copyright (C) 2018-2019 Joris Eekhout / Spanish National Research Council (CEBAS-CSIC) 3 | # Email: jeekhout@cebas.csic.es 4 | # 5 | # This program is free software: you can redistribute it and/or modify 6 | # it under the terms of the GNU General Public License as published by 7 | # the Free Software Foundation, either version 3 of the License, or 8 | # (at your option) any later version. 9 | # 10 | # This program is distributed in the hope that it will be useful, 11 | # but WITHOUT ANY WARRANTY; without even the implied warranty of 12 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 13 | # GNU General Public License for more details. 14 | # 15 | # You should have received a copy of the GNU General Public License 16 | # along with this program. If not, see . 17 | 18 | import subprocess 19 | import netCDF4 as nc 20 | import os 21 | import numpy as np 22 | # import sys 23 | # np.set_printoptions(threshold=sys.maxsize) 24 | import csv 25 | from scipy.interpolate import griddata 26 | from scipy import spatial 27 | from scipy.spatial import distance 28 | from pyproj import Proj, transform 29 | from math import * 30 | 31 | #-file cache to minimize/reduce opening/closing files 32 | filecache = dict() 33 | 34 | #-initial processes to determine the x and coordinates of the model grid and netcdf grid 35 | def netcdf2pcrInit(self, pcr, forcing): 36 | #-define input and ouput projections 37 | if getattr(self, forcing + 'InProj') == "rotated": 38 | inProj = Proj(init="epsg:4326") 39 | else: 40 | inProj = Proj(init = getattr(self, forcing + 'InProj')) 41 | outProj = Proj(init = getattr(self, forcing + 'OutProj')) 42 | 43 | #-get the attributes of cloneMap 44 | attributeClone = getMapAttributesALL(self.clonefile) 45 | cellsizeClone = attributeClone['cellsize'] 46 | rowsClone = attributeClone['rows'] 47 | colsClone = attributeClone['cols'] 48 | xULClone = attributeClone['xUL'] 49 | yULClone = attributeClone['yUL'] 50 | 51 | #-read netcdf file 52 | f = nc.Dataset(getattr(self, forcing + 'NC')) 53 | filecache[getattr(self, forcing + 'NC')] = f 54 | 55 | #-get coordinates of upper right and lower left corners of model grid 56 | xURClone = xULClone + cellsizeClone * colsClone 57 | yURClone = yULClone 58 | xLLClone = xULClone 59 | yLLClone = yULClone - cellsizeClone * rowsClone 60 | yLRClone = yLLClone 61 | xLRClone = xURClone 62 | 63 | #-transform coordinates to netcdf projection coordinates 64 | xULCloneInput,yULCloneInput = transform(outProj, inProj, xULClone, yULClone) 65 | xURCloneInput,yURCloneInput = transform(outProj, inProj, xURClone, yURClone) 66 | xLRCloneInput,yLRCloneInput = transform(outProj, inProj, xLRClone, yLRClone) 67 | xLLCloneInput,yLLCloneInput = transform(outProj, inProj, xLLClone, yLLClone) 68 | 69 | #-determine netcdf cell size and subset coordinates to model domain 70 | if getattr(self, forcing + 'InProj') == "rotated": 71 | #-get coordinates from netcdf file 72 | xrot = f.variables[getattr(self, forcing + 'VarX')][:] 73 | yrot = f.variables[getattr(self, forcing + 'VarY')][:] 74 | 75 | #-get coordinates of north pole 76 | npLat = f.variables[getattr(self, forcing + 'VarX')].grid_north_pole_latitude 77 | npLon = f.variables[getattr(self, forcing + 'VarX')].grid_north_pole_longitude 78 | 79 | #-transform x and y coordinates to grid 80 | xrot,yrot = np.meshgrid(xrot, yrot) 81 | 82 | #-transform rotated grid to lat,lon-coordinates 83 | xLatLon = xrot * 0 84 | yLatLon = yrot * 0 85 | for idx, row in enumerate(xrot): 86 | for idy, val in enumerate(row): 87 | x, y = rotated_grid_transform((xrot[idx, idy], yrot[idx, idy]), 2, (npLon, npLat)) 88 | xLatLon[idx, idy] = x 89 | yLatLon[idx, idy] = y 90 | 91 | #-transform x,y-coordinates to 2d array 92 | xyLatLon = [np.array(xLatLon).flatten(), np.array(yLatLon).flatten()] 93 | xyLatLon = list(map(list, zip(*xyLatLon))) 94 | 95 | #-function to find closest node from list of coordinates 96 | def closest_node(node, nodes): 97 | closest_index = distance.cdist([node], nodes).argmin() 98 | indices = np.where(np.ma.getdata(xLatLon) == nodes[closest_index][0]) 99 | indices = np.array(indices).flatten().astype('int32') 100 | return indices.tolist() 101 | 102 | #-get indices of corner points clone map from netcdf 103 | indicesUL = closest_node((xULCloneInput,yULCloneInput), xyLatLon) 104 | indicesLL = closest_node((xLLCloneInput,yLLCloneInput), xyLatLon) 105 | indicesUR = closest_node((xURCloneInput,yURCloneInput), xyLatLon) 106 | indicesLR = closest_node((xLRCloneInput,yLRCloneInput), xyLatLon) 107 | 108 | #-determine indices of the corners of netcdf grid corresponding to model grid (+ buffer) 109 | xyUL = max(min(indicesUL[0], indicesLL[0], indicesUR[0], indicesLR[0]) - 2, 0) 110 | xyLL = min(max(indicesUL[0], indicesLL[0], indicesUR[0], indicesLR[0]) + 2, xLatLon.shape[0] - 1) 111 | xyUR = max(min(indicesUL[1], indicesLL[1], indicesUR[1], indicesLR[1]) - 2, 0) 112 | xyLR = min(max(indicesUL[1], indicesLL[1], indicesUR[1], indicesLR[1]) + 2, xLatLon.shape[1] - 1) 113 | 114 | #-determine x,y-coordinates corresponding to model grid (+ buffer) from netcdf grid 115 | x = xLatLon[xyUL:(xyLL + 1), xyUR:(xyLR + 1)] 116 | y = yLatLon[xyUL:(xyLL + 1), xyUR:(xyLR + 1)] 117 | 118 | else: 119 | #-get cell size, number of rows and columns and upper left corner coordinates from netcdf grid 120 | cellsizeInput = f.variables[getattr(self, forcing + 'VarY')][1]- f.variables[getattr(self, forcing + 'VarY')][0] 121 | cellsizeInput = float(cellsizeInput) 122 | 123 | #-determine x-coordinates corresponding to model grid (+ buffer) from netcdf grid 124 | xIdxSta = np.argmin(abs(f.variables[getattr(self, forcing + 'VarX')][:] - (min(xULCloneInput, xLLCloneInput) - 2 * cellsizeInput))) 125 | xIdxEnd = np.argmin(abs(f.variables[getattr(self, forcing + 'VarX')][:] - (max(xURCloneInput, xLRCloneInput) + 2 * cellsizeInput))) 126 | x = f.variables[getattr(self, forcing + 'VarX')][xIdxSta:(xIdxEnd + 1)] 127 | 128 | #-determine y-coordinates corresponding to model grid (+ buffer) from netcdf grid 129 | yIdxEnd = np.argmin(abs(f.variables[getattr(self, forcing + 'VarY')][:] - (max(yULCloneInput, yURCloneInput) + 2 * cellsizeInput))) 130 | yIdxSta = np.argmin(abs(f.variables[getattr(self, forcing + 'VarY')][:] - (min(yLLCloneInput, yLRCloneInput) - 2 * cellsizeInput))) 131 | y = f.variables[getattr(self, forcing + 'VarY')][yIdxSta:(yIdxEnd + 1)] 132 | 133 | #-transform x and y coordinates to grid 134 | x,y = np.meshgrid(x, y) 135 | 136 | #-project x and y coordinates to model grid projection 137 | x,y = transform(inProj, outProj, x, y) 138 | 139 | #-transform x and y coordinates to arrays 140 | x = np.asarray(x).ravel() 141 | y = np.asarray(y).ravel() 142 | 143 | #-determine model grid x and y coordinates and save in grid 144 | xi = np.arange(xULClone + cellsizeClone * 0.5, (xULClone + cellsizeClone * 0.5) + colsClone * cellsizeClone, cellsizeClone) 145 | yi = np.arange((yULClone + cellsizeClone * 0.5) - rowsClone * cellsizeClone, yULClone + cellsizeClone * 0.5, cellsizeClone) 146 | yi = np.flipud(yi) 147 | xi,yi = np.meshgrid(xi,yi) 148 | 149 | #-determine x,y-coordinates of netcdf file and model domain and indices of netcdf corresponding to model domain 150 | setattr(self, forcing + 'x', x) 151 | setattr(self, forcing + 'y', y) 152 | setattr(self, forcing + 'xi', xi) 153 | setattr(self, forcing + 'yi', yi) 154 | if getattr(self, forcing + 'InProj') == "rotated": 155 | setattr(self, forcing + 'xyUL', xyUL) 156 | setattr(self, forcing + 'xyLL', xyLL) 157 | setattr(self, forcing + 'xyUR', xyUR) 158 | setattr(self, forcing + 'xyLR', xyLR) 159 | else: 160 | setattr(self, forcing + 'xIdxSta', xIdxSta) 161 | setattr(self, forcing + 'xIdxEnd', xIdxEnd) 162 | setattr(self, forcing + 'yIdxSta', yIdxSta) 163 | setattr(self, forcing + 'yIdxEnd', yIdxEnd) 164 | 165 | #-function to interpolate netcdf gridded data to model grid 166 | def netcdf2pcrDynamic(self, pcr, forcing): #ncFile, varName, dateInput, method, factor, x, y, xi, yi, xIdxSta, xIdxEnd, yIdxSta, yIdxEnd): 167 | #-read netcdf file 168 | f = nc.Dataset(getattr(self, forcing + 'NC')) 169 | filecache[getattr(self, forcing + 'NC')] = f 170 | 171 | #-get index from netcdf corresponding with current date 172 | idx = int(nc.date2index(self.curdate, f.variables['time'], select ='exact')) 173 | 174 | #-get raw netcdf gridded data from netcdf, transform to array and multiply with factor 175 | if getattr(self, forcing + 'InProj') == "rotated": 176 | z = f.variables[getattr(self, forcing + 'VarName')][idx, getattr(self, forcing + 'xyUL'):(getattr(self, forcing + 'xyLL') + 1), getattr(self, forcing + 'xyUR'):(getattr(self, forcing + 'xyLR') + 1)] 177 | else: 178 | z = f.variables[getattr(self, forcing + 'VarName')][idx, getattr(self, forcing + 'yIdxSta'):(getattr(self, forcing + 'yIdxEnd') + 1), getattr(self, forcing + 'xIdxSta'):(getattr(self, forcing + 'xIdxEnd') + 1)] 179 | z = np.asarray(z).ravel() 180 | with np.errstate(invalid='ignore'): # surpress error message when there are already nans in the z array 181 | z = np.where(z<=-9999, np.nan, z) * getattr(self, forcing + 'Factor') 182 | 183 | #-remove nans from arrays 184 | x = getattr(self, forcing + 'x')[~np.isnan(z)] 185 | y = getattr(self, forcing + 'y')[~np.isnan(z)] 186 | z = z[~np.isnan(z)] 187 | 188 | #-interpolate with method (linear or cubic) 189 | zi = griddata((x, y), z, (getattr(self, forcing + 'xi'), getattr(self, forcing + 'yi')), method=getattr(self, forcing + 'Method')) 190 | zi = np.where(np.isnan(zi), -9999, zi) 191 | 192 | #-convert to PCRaster Python map 193 | output = pcr.numpy2pcr(pcr.Scalar, zi, -9999) 194 | 195 | return output 196 | 197 | #-function to interpolate netcdf gridded data to model grid 198 | def netcdf2pcrTimeIdx(self, pcr, forcing): #ncFile, varName, dateInput, method, factor, x, y, xi, yi, xIdxSta, xIdxEnd, yIdxSta, yIdxEnd): 199 | #-read netcdf file 200 | f = nc.Dataset(getattr(self, forcing + 'NC')) 201 | filecache[getattr(self, forcing + 'NC')] = f 202 | 203 | #-get index from netcdf corresponding with current date 204 | setattr(self, forcing + 'TimeIdx', nc.date2index(self.curdate, f.variables['time'], select ='exact')) 205 | 206 | #-function to get map attributes from clone map 207 | def getMapAttributesALL(cloneMap): 208 | cOut,err = subprocess.Popen(str('mapattr -p %s ' %(cloneMap)), stdout=subprocess.PIPE, stderr=open(os.devnull), shell=True).communicate() 209 | cellsize = float(cOut.split()[7]) 210 | mapAttr = {'cellsize': float(cellsize) ,\ 211 | 'rows' : float(cOut.split()[3]) ,\ 212 | 'cols' : float(cOut.split()[5]) ,\ 213 | 'xUL' : float(cOut.split()[17]),\ 214 | 'yUL' : float(cOut.split()[19])} 215 | co = None; cOut = None; err = None 216 | del co; del cOut; del err 217 | return mapAttr 218 | 219 | #-function to read the config and 220 | def getConfigNetcdf(self, config, forcing, section): 221 | setattr(self, forcing + 'NC', config.get(section, forcing + 'Netcdf')) 222 | setattr(self, forcing + 'NetcdfInput', config.get(section, forcing + 'NetcdfInput').split(',')) 223 | netcdfInput = getattr(self, forcing + 'NetcdfInput') 224 | setattr(self, forcing + 'VarName', netcdfInput[0]) 225 | setattr(self, forcing + 'VarX', netcdfInput[1]) 226 | setattr(self, forcing + 'VarY', netcdfInput[2]) 227 | setattr(self, forcing + 'Method', netcdfInput[3]) 228 | setattr(self, forcing + 'Factor', float(netcdfInput[4])) 229 | setattr(self, forcing + 'InProj', netcdfInput[5]) 230 | setattr(self, forcing + 'OutProj', netcdfInput[6]) 231 | 232 | 233 | #-function to transform rotated lat-lon to regular lat-lon 234 | def rotated_grid_transform(grid_in, option, SP_coor): 235 | lon = grid_in[0] 236 | lat = grid_in[1] 237 | 238 | if option == 2: 239 | lon = -lon 240 | lat = -lat 241 | 242 | lon = (lon*pi)/180 # Convert degrees to radians 243 | lat = (lat*pi)/180 244 | 245 | SP_lon = SP_coor[0] 246 | SP_lat = SP_coor[1] 247 | 248 | theta = 90+SP_lat # Rotation around y-axis 249 | phi = SP_lon # Rotation around z-axis 250 | 251 | theta = (theta*pi)/180 252 | phi = (phi*pi)/180 # Convert degrees to radians 253 | 254 | x = cos(lon)*cos(lat) # Convert from spherical to cartesian coordinates 255 | y = sin(lon)*cos(lat) 256 | z = sin(lat) 257 | 258 | if option == 1: # Regular -> Rotated 259 | 260 | x_new = cos(theta)*cos(phi)*x + cos(theta)*sin(phi)*y + sin(theta)*z 261 | y_new = -sin(phi)*x + cos(phi)*y 262 | z_new = -sin(theta)*cos(phi)*x - sin(theta)*sin(phi)*y + cos(theta)*z 263 | 264 | else: # Rotated -> Regular 265 | 266 | phi = -phi 267 | theta = -theta 268 | 269 | x_new = cos(theta)*cos(phi)*x + sin(phi)*y + sin(theta)*cos(phi)*z 270 | y_new = -cos(theta)*sin(phi)*x + cos(phi)*y - sin(theta)*sin(phi)*z 271 | z_new = -sin(theta)*x + cos(theta)*z 272 | 273 | 274 | 275 | lon_new = atan2(y_new,x_new) # Convert cartesian back to spherical coordinates 276 | lat_new = asin(z_new) 277 | 278 | lon_new = (lon_new*180)/pi # Convert radians back to degrees 279 | lat_new = (lat_new*180)/pi 280 | 281 | if option == 1: # Regular -> Rotated 282 | lon_new = -lon_new 283 | lat_new = -lat_new 284 | 285 | return lon_new, lat_new 286 | -------------------------------------------------------------------------------- /modules/sediment_transport.py: -------------------------------------------------------------------------------- 1 | # Sediment transport module that determines sediment flux and sediment yield at the stations, 2 | # considering reservoir sedimentation when the reservoir module is used 3 | # Copyright (C) 2015-2019 Joris Eekhout / Spanish National Research Council (CEBAS-CSIC) 4 | # Email: jeekhout@cebas.csic.es 5 | # 6 | # This program is free software: you can redistribute it and/or modify 7 | # it under the terms of the GNU General Public License as published by 8 | # the Free Software Foundation, either version 3 of the License, or 9 | # (at your option) any later version. 10 | # 11 | # This program is distributed in the hope that it will be useful, 12 | # but WITHOUT ANY WARRANTY; without even the implied warranty of 13 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 14 | # GNU General Public License for more details. 15 | # 16 | # You should have received a copy of the GNU General Public License 17 | # along with this program. If not, see . 18 | 19 | #- Equations for simulating sediment transport 20 | print('Sediment transport module imported') 21 | 22 | #-Sediment transport capacity 23 | def TC(self, pcr, runoff): 24 | #-runoff discharge per unit width in m2/day 25 | q = (runoff/1000) * pcr.celllength() 26 | #-transport capacity calculation ton/day 27 | TC = self.TC_k * q**self.TC_beta * self.Slope**self.TC_gamma 28 | #-only apply TC to cells with runoff (>0) and in the channel (upstream area > upstream_km2) 29 | TC_upstream = pcr.ifthen(pcr.pcrand(self.Channel == 1, runoff > 0), TC) 30 | #-determine average transport capacity per subcatchment 31 | TCSubcatchment = pcr.areaaverage(TC_upstream, self.subcatchmentRes) 32 | #-set all other cells to 0 33 | TCSubcatchment = pcr.cover(TCSubcatchment, 0) 34 | return TC 35 | # return TCSubcatchment 36 | 37 | #-Sediment transport 38 | def SedTrans(self, pcr, np, sed, TC): 39 | #-determine sediment transport without reservoirs 40 | if self.ResFLAG == 0: 41 | #-rout sediment based on transport capacity 42 | sedimentFlux = pcr.accucapacityflux(self.FlowDir, sed, TC) 43 | sedimentYield = pcr.accucapacitystate(self.FlowDir, sed, TC) 44 | sedDep = sedimentYield 45 | 46 | #-determine sediment transport with reservoirs 47 | else: 48 | #-store sed in sedTrans to be used in routing algorithm 49 | sedTrans = sed 50 | 51 | #-initiate empty map to be used in for-loop 52 | sedimentYield = self.DEM * 0 53 | sedimentFlux = self.DEM * 0 54 | subFinished = self.DEM * 0 55 | sedDep = self.DEM * 0 56 | 57 | #-increase the transport capacity in the reservoir cells such that all sediment is transported towards the end of the reservoir 58 | TC = pcr.ifthenelse(pcr.scalar(self.SedReservoirs) > 0, 1e10, TC) 59 | 60 | #-Determine total soil erosion 61 | sedTotal = np.sum(pcr.pcr2numpy(sed, 0)) 62 | 63 | #-Only rout sediment when soil erosion > 0 64 | if (sedTotal > 0): 65 | #-loop through the catchments, rout sediment and determine sedimentation in reservoirs based on trapping efficiency 66 | for step in range(max(self.subcatchmentSteps)+1): #-for-loop through the steps 67 | #-determine the subcatchments for this step 68 | subcatchments = np.where(self.subcatchmentSteps == step)[0] 69 | 70 | #-rout sediment based on transport capacity 71 | sedTransCapFlux = pcr.accucapacityflux(self.FlowDir, sedTrans, TC) 72 | sedTransCapState = pcr.accucapacitystate(self.FlowDir, sedTrans, TC) 73 | 74 | #-initiate empty map to be used in for-loop 75 | stepBool = self.DEM * 0 76 | 77 | #-for-loop through the subcatchments per step 78 | for subcatchment in subcatchments: 79 | #-create boolean map with location of reservoir 80 | reservoirBool = pcr.scalar(pcr.ifthenelse(self.ResSedID == int(self.subcatchmentOrder[subcatchment]), pcr.scalar(1), pcr.scalar(0))) 81 | 82 | #-extract routed sediment value at the reservoir from sedTransCapFlux 83 | reservoirFluxTC = pcr.ifthen(reservoirBool == 1, sedTransCapFlux) 84 | 85 | #-store trapped sediment in sedimentYield (multiply routed sediment value with trapping efficiency to be stored in reservoir cell) 86 | sedimentYield = pcr.ifthenelse(reservoirBool == 1, reservoirFluxTC * self.TrappingEff, sedimentYield) 87 | 88 | #-update subFinished and give subcatchment cells value 1 89 | subFinished = pcr.ifthenelse(pcr.scalar(self.subcatchmentRes) == int(self.subcatchmentOrder[subcatchment]), pcr.scalar(1), subFinished) 90 | 91 | #-update sedTrans, set all subcatchment cells to 0 92 | sedTrans = pcr.ifthenelse(pcr.scalar(subFinished) == 1, 0, sedTrans) 93 | #-add reservoir outflow to cell downstream of reservoir (multiply routed sediment value with outflow efficiency) 94 | sedTrans = sedTrans + pcr.upstream(self.FlowDir, pcr.ifthenelse(reservoirBool == 1, reservoirFluxTC * self.OutflowEff, pcr.scalar(0))) 95 | 96 | #-create boolean map with location of reservoir 97 | stepBool = stepBool + pcr.scalar(pcr.ifthenelse(self.subcatchmentRes == int(self.subcatchmentOrder[subcatchment]), self.subcatchmentRes == int(self.subcatchmentOrder[subcatchment]), pcr.boolean(0))) 98 | 99 | # store sedTransCapFlux in sedimentFlux 100 | sedimentFlux = sedTransCapFlux * subFinished + sedimentFlux 101 | 102 | #-rout sediment based on transport capacity 103 | sedDep = sedDep + sedTransCapState * stepBool 104 | 105 | #-rout sediment based on transport capacity 106 | sedTransCapFlux = pcr.accucapacityflux(self.FlowDir, sedTrans, TC) 107 | 108 | # store sedTransCapFlux in sedimentFlux 109 | sedimentFlux = sedTransCapFlux * (1 - subFinished) + sedimentFlux 110 | 111 | return sedimentYield, sedDep, sedimentFlux 112 | 113 | 114 | #-init processes 115 | def init(self, pcr, config, csv, np): 116 | #-init processes when reservoir module is used 117 | if self.ResFLAG == 1: 118 | #-nominal map with reservoir IDs 119 | self.ResSedID = pcr.cover(self.ResID, 0) 120 | else: 121 | self.ResSedID = self.Locations 122 | 123 | #-determine upstream area map 124 | self.UpstreamArea = pcr.accuflux(self.FlowDir, 1) * pcr.cellarea() / 10**6 125 | 126 | #-determine upstream area smaller than upstream_km2 and define channel cells based on upstream area 127 | self.Upstream_km2 = config.getfloat('SEDIMENT_TRANS', 'upstream_km2') 128 | self.Channel = self.UpstreamArea > self.Upstream_km2 129 | 130 | #-determine average slope per stream based on stream order and averaged per subcatchment 131 | self.Basin = pcr.subcatchment(self.FlowDir, self.ResSedID) 132 | self.StreamOrder = pcr.streamorder(self.FlowDir) 133 | self.Streams = pcr.scalar(self.Channel) * pcr.scalar(self.Basin) * 10 + pcr.scalar(self.Channel) * pcr.scalar(self.StreamOrder) 134 | self.SlopeStreams = pcr.areaaverage(self.Slope, pcr.nominal(self.Streams)) 135 | self.SlopeStreams = pcr.ifthenelse(self.Channel == 1, self.SlopeStreams, self.Slope) 136 | 137 | #-read transport capacity parameters 138 | self.TC_beta = config.getfloat('SEDIMENT_TRANS', 'TC_beta') 139 | self.TC_gamma = config.getfloat('SEDIMENT_TRANS', 'TC_gamma') 140 | 141 | #-init processes when reservoir module is used 142 | if self.ResFLAG == 1: 143 | #-nominal map with reservoir IDs and extent 144 | if self.ETOpenWaterFLAG == 1: 145 | self.SedReservoirs = pcr.cover(self.openWaterNominal, 0) 146 | else: 147 | self.SedReservoirs = pcr.readmap(self.inpath + config.get('RESERVOIR', 'reservoirs')) 148 | self.SedReservoirs = pcr.cover(self.SedReservoirs, 0) 149 | 150 | #-read table with the trapping efficiency per reservoir 151 | self.TrapEffTab = self.inpath + config.get('SEDIMENT_TRANS', 'TrapEffTab') 152 | self.TrappingEff = pcr.cover(pcr.lookupscalar(self.TrapEffTab, self.ResSedID), 0) 153 | 154 | #-construct map where all cells have 1 and only the reservoir cells have trapping efficiency value obtained from the table 155 | self.OutflowEff = pcr.cover(1-pcr.lookupscalar(self.TrapEffTab, self.ResSedID), 1) 156 | 157 | #-determine subcatchment map 158 | self.subcatchmentRes = pcr.subcatchment(self.FlowDir, self.ResSedID) 159 | 160 | #-read reservoir order for sediment transport and add the values to self.subcatchmentOrder and self.subcatchmentSteps 161 | self.ResOrder = config.get('SEDIMENT_TRANS', 'ResOrder') 162 | self.subcatchmentOrder = [] 163 | self.subcatchmentSteps = [] 164 | 165 | #-loop through the rows of the text file 166 | with open(self.inpath + self.ResOrder, 'rt') as f: 167 | next(f) # skip headings 168 | reader = csv.reader(f, delimiter='\t') 169 | for row in reader: 170 | self.subcatchmentOrder = np.append(self.subcatchmentOrder, int(row[0])) 171 | self.subcatchmentOrder = self.subcatchmentOrder.astype(np.int) 172 | self.subcatchmentSteps = np.append(self.subcatchmentSteps, int(row[1])) 173 | self.subcatchmentSteps = self.subcatchmentSteps.astype(np.int) 174 | 175 | #-loop through the steps and define map with step per subcatchment 176 | self.subcatchmentStepsMap = self.DEM * 0 177 | for step in range(max(self.subcatchmentSteps)+1): 178 | #-determine the subcatchments for this step 179 | subcatchments = np.where(self.subcatchmentSteps == step)[0] 180 | 181 | #-for-loop through the subcatchments per step 182 | for subcatchment in subcatchments: 183 | #-update subFinished and give subcatchment cells value 1 184 | self.subcatchmentStepsMap = pcr.ifthenelse(pcr.scalar(self.subcatchmentRes) == int(self.subcatchmentOrder[subcatchment]), pcr.scalar(step + 1), self.subcatchmentStepsMap) 185 | #-set all subcatchments with value 0 to the maximum step 186 | self.subcatchmentStepsMap = pcr.ifthenelse(self.subcatchmentStepsMap == 0, int(max(self.subcatchmentSteps)+1), self.subcatchmentStepsMap) 187 | #-map with step value for stations that are not reservoirs 188 | self.LocationsNoResSteps = pcr.scalar(self.LocationsNoRes) * self.subcatchmentStepsMap 189 | 190 | #-determine roughness factor for mmf only 191 | if self.SedModel == 2: 192 | #-Read flag if channels should be excluded from the detachment by runoff calculation 193 | self.manningChannelsFLAG = config.getint('SEDIMENT_TRANS', 'manningChannelFLAG') 194 | 195 | #-read manning value for channels 196 | if self.manningChannelsFLAG == 1: 197 | self.manningChannel = config.getfloat('SEDIMENT_TRANS', 'manningChannel') 198 | 199 | #-Determine flow velocity for transport capacity calculation 200 | self.n_veg_TC = self.mmf.manningVegetation(self, pcr, self.d_TC, self.Diameter, self.NoElements) 201 | self.n_veg_TC = pcr.ifthenelse(self.NoVegetation == 1, 0, self.n_veg_TC) 202 | self.n_veg_TC = pcr.ifthenelse(self.NoErosion == 1, 0, self.n_veg_TC) 203 | self.n_veg_TC = pcr.ifthenelse(self.n_table > 0, self.n_table, self.n_veg_TC) 204 | self.n_TC = (self.n_soil**2 + self.n_veg_TC**2)**0.5 205 | #-set manning value of channels to predetermined value 206 | if self.manningChannelsFLAG == 1: 207 | self.n_TC = pcr.ifthenelse(self.Channel == 1, self.manningChannel, self.n_TC) 208 | self.v_TC = self.mmf.FlowVelocity(self, pcr, self.n_TC, self.d_TC) 209 | 210 | #-Determine flow velocity after harvest, manning for tilled conditions is used 211 | if self.harvest_FLAG: 212 | self.n_veg_TC_harvest = self.mmf.manningVegetation(self, pcr, self.d_field, self.Diameter_harvest, self.NoElements_harvest) 213 | self.n_veg_TC_harvest = pcr.ifthenelse(self.Tillage_harvest == 1, 0, self.n_veg_field_harvest) 214 | self.n_TC_harvest = (self.n_soil**2 + self.n_veg_TC_harvest**2)**0.5 215 | #-set manning value of channels to predetermined value 216 | if self.manningChannelsFLAG == 1: 217 | self.n_TC_harvest = pcr.ifthenelse(pcr.pcrand(self.Channel == 1, self.n_TC_harvest > 0), self.manningChannel, self.n_TC_harvest) 218 | self.v_TC_harvest = self.mmf.FlowVelocity(self, pcr, self.n_TC_harvest, self.d_TC) 219 | 220 | #-Determine flow velocity for bare soil conditions (reference conditions) 221 | self.v_b = self.mmf.FlowVelocity(self, pcr, self.n_bare, self.d_bare) 222 | 223 | #-Determine roughness factor for transport capacity calculation 224 | self.roughnessFactor = self.v_TC / self.v_b 225 | 226 | #-initial conditions sediment transport 227 | def initial(self, pcr, config): 228 | try: 229 | self.SYieldR = pcr.readmap(self.inpath + config.get('SEDIMENT_TRANS', 'Sed_init')) 230 | except: 231 | self.SYieldR = config.getfloat('SEDIMENT_TRANS', 'Sed_init') 232 | 233 | #-dynamic sediment transport processes musle 234 | def dynamic_musle(self, pcr): 235 | #-transport capacity 236 | TC = self.sediment_transport.TC(self, pcr, (Q * 3600 * 24) / pcr.cellarea() * 1000) 237 | 238 | #-report the transport capacity per subcatchment 239 | self.reporting.reporting(self, pcr, 'TC', TC) 240 | 241 | #-determine sediment yield at reservoirs 242 | tempvar = self.sediment_transport.SedTrans(self, pcr, np, sed, TC) 243 | sedimentYield = tempvar[0] 244 | sedDep = tempvar[1] 245 | 246 | #-report the deposition in channel cells 247 | self.reporting.reporting(self, pcr, 'SedDep', sedDep) 248 | 249 | #-report sediment yield in the reservoirs 250 | self.reporting.reporting(self, pcr, 'SYieldRA', sedimentYield) 251 | 252 | #-dynamic sediment transport processes mmf 253 | def dynamic_mmf(self, pcr, Runoff, np, G): 254 | #-change the flow factor for harvested areas to actual and tillage conditions 255 | if self.harvest_FLAG == 1: 256 | self.roughnessFactorUpdate = pcr.ifthenelse(self.Harvested == 1, self.v_TC_harvest / self.v_b, self.roughnessFactor) 257 | else: 258 | self.roughnessFactorUpdate = self.roughnessFactor 259 | 260 | #-determine transport capacity 261 | TC = self.mmf.TransportCapacity(self, pcr, self.roughnessFactorUpdate, self.RootClayMap + self.RootSiltMap + self.RootSandMap, Runoff) 262 | 263 | #-report the transport capacity 264 | self.reporting.reporting(self, pcr, 'TC', TC) 265 | 266 | #-determine sediment yield at stations 267 | sedYield, sedDep, sedFlux = self.sediment_transport.SedTrans(self, pcr, np, G * pcr.cellarea() / 1000, TC) 268 | 269 | #-report the sediment deposition by transport capacity (ton/day) 270 | self.reporting.reporting(self, pcr, 'SedDep', sedDep) 271 | 272 | #-report sediment yield in the stations (ton/day) 273 | self.reporting.reporting(self, pcr, 'SedYld', sedYield) 274 | 275 | #-report sediment flux in the stations (ton/day) 276 | self.reporting.reporting(self, pcr, 'SedFlux', sedFlux) -------------------------------------------------------------------------------- /modules/mmf.py: -------------------------------------------------------------------------------- 1 | # Soil erosion module using the Morgan-Morgan-Finney soil erosion model 2 | # Copyright (C) 2017-2019 Joris Eekhout / Spanish National Research Council (CEBAS-CSIC) 3 | # Email: jeekhout@cebas.csic.es 4 | # 5 | # This program is free software: you can redistribute it and/or modify 6 | # it under the terms of the GNU General Public License as published by 7 | # the Free Software Foundation, either version 3 of the License, or 8 | # (at your option) any later version. 9 | # 10 | # This program is distributed in the hope that it will be useful, 11 | # but WITHOUT ANY WARRANTY; without even the implied warranty of 12 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 13 | # GNU General Public License for more details. 14 | # 15 | # You should have received a copy of the GNU General Public License 16 | # along with this program. If not, see . 17 | 18 | print('MMF module imported') 19 | 20 | #-Effective rainfall (Rf, mm) 21 | def RainEff(self, pcr, precip): 22 | Rf = precip * pcr.cos(self.Slope) 23 | return Rf 24 | 25 | #-Leaf drainage (LD; mm) 26 | def LeafDrain(self, pcr, Rf): 27 | LD = Rf * self.CC 28 | return LD 29 | 30 | #-Direct throughfall (DT; mm) 31 | def DirectThroughfall(self, pcr, Rf, LD): 32 | DT = Rf - LD 33 | return DT 34 | 35 | #-Kinetic energy of the direct throughfall (KE_DT; J/m2) 36 | def KineticEnergyDT(self, pcr, DT, PrecInt): 37 | # KE_DT = DT * (8.95 + 8.44 * pcr.log10(PrecInt)) # Marshall and Palmer (1948) 38 | # KE_DT = DT * (0.283 * (1 - 0.52 * pcr.exp(-0.042 * PrecInt))) * 100 # Van Dijk et al (2002) 39 | # KE_DT = DT * (0.384 * (1 - 0.54 * pcr.exp(-0.029 * PrecInt))) * 100 # Cerro et al (1998) 40 | # KE_DT = DT * (0.1418 * PrecInt**0.172) * 100 # Meshesha et al. (2016) 41 | KE_DT = DT * (0.29 * (1 - 0.72 * pcr.exp(-0.05 * PrecInt))) * 100 # Brown and Foster (1987) 42 | return KE_DT 43 | 44 | #-Kinetic energy of the leaf drainage (KE_LD; J/m2) 45 | def KineticEnergyLD(self, pcr, LD, PlantHeight): 46 | KE_LD = pcr.ifthenelse(PlantHeight < 0.15, 0, LD * (15.8 * PlantHeight**0.5 - 5.87)) 47 | return KE_LD 48 | 49 | #-Detachment of soil particles by raindrop impact (F; kg/m2) 50 | def DetachmentRaindrop(self, pcr, K, texture, KE): 51 | F = K * texture * pcr.max(0, 1 - (self.NoErosion + self.Cover)) * KE * 1e-3 52 | return F 53 | 54 | #-Detachment of soil particles by runoff (H; kg/m2) 55 | def DetachmentRunoff(self, pcr, DR, texture, Q): 56 | H = DR * texture * Q**1.5 * pcr.max(0, 1 - (self.NoErosion + self.Cover)) * pcr.sin(self.Slope)**(0.3) * 1e-3 57 | 58 | #-set values in channels to 0 in case channels should be excluded 59 | if self.exclChannelsFLAG == 1: 60 | H = H * self.Hillslope 61 | 62 | return H 63 | 64 | #-Manning for tilled conditions (manningTilled; s/m1/3) 65 | def ManningTillage(self, pcr): 66 | manningTilled = pcr.exp(-2.1132 + 0.0349 * self.RFR) 67 | return manningTilled 68 | 69 | #-Manning for vegetated conditions (manningVegetated; s/m1/3) 70 | def manningVegetation(self, pcr, waterDepth, diameter, noElements): 71 | manningVegetated = (waterDepth**(0.67)) / ((2 * 9.81) / (diameter * noElements))**0.5 72 | return manningVegetated 73 | 74 | #-Flow velocity based on manning (v; m/s) 75 | def FlowVelocity(self, pcr, manning, waterDepth): 76 | v = 1 / manning * waterDepth**(0.67) * pcr.ifthenelse(self.Slope == 0, 1e-5, self.Slope)**0.5 77 | return v 78 | 79 | #-Particle fall number (N_f; -) 80 | def ParticleFallNumber(self, pcr, delta, velocity, waterDepth): 81 | v_s = (float(1)/18 * (delta ** 2) * (self.rho_s - self.rho) * 9.81) / (self.eta) 82 | N_f = (pcr.celllength() / pcr.cos(self.Slope) * v_s) / (velocity * waterDepth) 83 | return N_f 84 | 85 | #-Percentage of the detached sediment that is deposited (DEP; %) 86 | def Deposition(self, pcr, N_f): 87 | DEP = pcr.min(100, 44.1 * N_f ** 0.29) 88 | return DEP 89 | 90 | #-Delivery of detached particles to runoff (G; kg/m2) 91 | def MaterialTransport(self, pcr, F, H, DEP): 92 | G = (F + H) * (1 - DEP / 100) 93 | D = (F + H) * DEP / 100 94 | return G, D 95 | 96 | #-Transport capacity of the runoff (TC; ton/ha) 97 | def TransportCapacity(self, pcr, roughnessFactor, texture, Q): 98 | q = (Q/1000) * pcr.celllength() #-runoff discharge per unit width in m2/day 99 | TC = roughnessFactor * q**self.TC_beta * self.SlopeStreams**self.TC_gamma #-determine transport capacity 100 | return TC 101 | 102 | #-init processes mmf 103 | def init(self, pcr, config): 104 | #-if pedotransfer functions are not used read the sand and clay maps 105 | if self.PedotransferFLAG == 0: 106 | self.RootSandMap = pcr.readmap(self.inpath + config.get('PEDOTRANSFER','RootSandMap')) / 100 107 | self.RootClayMap = pcr.readmap(self.inpath + config.get('PEDOTRANSFER','RootClayMap')) / 100 108 | self.RootSiltMap = 1 - self.RootSandMap - self.RootClayMap 109 | 110 | #-read precipitation intensity map or float 111 | try: 112 | self.PrecInt = pcr.readmap(self.inpath + config.get('MMF', 'PrecInt')) 113 | except: 114 | self.PrecInt = config.getfloat('MMF', 'PrecInt') 115 | 116 | #-read flag if the canopy cover should be determined based on LAI 117 | self.CanopyCoverLAIFlag = config.getfloat('MMF', 'CanopyCoverLAIFlag') 118 | 119 | #-read table with MMF input parameters per landuse class 120 | pcr.setglobaloption('matrixtable') 121 | MMF_table = self.inpath + config.get('MMF', 'MMF_table') 122 | self.PlantHeight = pcr.lookupscalar(MMF_table, 1, self.LandUse) 123 | self.NoElements = pcr.lookupscalar(MMF_table, 2, self.LandUse) 124 | self.Diameter = pcr.lookupscalar(MMF_table, 3, self.LandUse) 125 | self.CC_table = pcr.lookupscalar(MMF_table, 4, self.LandUse) 126 | self.GC_table = pcr.lookupscalar(MMF_table, 5, self.LandUse) 127 | self.NoErosion = pcr.lookupscalar(MMF_table, 6, self.LandUse) 128 | self.Tillage = pcr.lookupscalar(MMF_table, 7, self.LandUse) 129 | self.n_table = pcr.lookupscalar(MMF_table, 8, self.LandUse) 130 | self.NoVegetation = pcr.lookupscalar(MMF_table, 9, self.LandUse) 131 | pcr.setglobaloption('columntable') 132 | 133 | #-nominal map with reservoir IDs and extent 134 | if self.ResFLAG == 1: 135 | if self.ETOpenWaterFLAG == 1: 136 | self.Reservoirs = pcr.ifthenelse(pcr.scalar(self.openWaterNominal) > 0, pcr.scalar(1), pcr.scalar(0)) 137 | self.Reservoirs = pcr.cover(self.Reservoirs, 0) 138 | else: 139 | self.Reservoirs = pcr.readmap(self.inpath + config.get('RESERVOIR', 'reservoirs')) 140 | self.NoErosion = pcr.min(self.NoErosion + pcr.scalar(self.Reservoirs), 1) 141 | 142 | #-read table with MMF input parameters per landuse class for the period after harvest 143 | self.harvest_FLAG = config.getfloat('MMF', 'harvestFLAG') 144 | pcr.setglobaloption('matrixtable') 145 | if self.harvest_FLAG: 146 | MMF_harvest_table = self.inpath + config.get('MMF', 'MMF_harvest') 147 | self.Sowing = pcr.lookupscalar(MMF_harvest_table, 1, self.LandUse) 148 | self.Harvest = pcr.lookupscalar(MMF_harvest_table, 2, self.LandUse) 149 | self.PlantHeight_harvest = pcr.lookupscalar(MMF_harvest_table, 3, self.LandUse) 150 | self.NoElements_harvest = pcr.lookupscalar(MMF_harvest_table, 4, self.LandUse) 151 | self.Diameter_harvest = pcr.lookupscalar(MMF_harvest_table, 5, self.LandUse) 152 | self.CC_harvest = pcr.lookupscalar(MMF_harvest_table, 6, self.LandUse) 153 | self.GC_harvest = pcr.lookupscalar(MMF_harvest_table, 7, self.LandUse) 154 | self.Tillage_harvest = pcr.lookupscalar(MMF_harvest_table, 8, self.LandUse) 155 | pcr.setglobaloption('columntable') 156 | 157 | #-read other model parameters 158 | self.K_c = config.getfloat('MMF', 'K_c') 159 | self.K_z = config.getfloat('MMF', 'K_z') 160 | self.K_s = config.getfloat('MMF', 'K_s') 161 | self.DR_c = config.getfloat('MMF', 'DR_c') 162 | self.DR_z = config.getfloat('MMF', 'DR_z') 163 | self.DR_s = config.getfloat('MMF', 'DR_s') 164 | self.deltaClay = config.getfloat('MMF', 'deltaClay') 165 | self.deltaSilt = config.getfloat('MMF', 'deltaSilt') 166 | self.deltaSand = config.getfloat('MMF', 'deltaSand') 167 | self.n_bare = config.getfloat('MMF', 'manning') 168 | self.d_bare = config.getfloat('MMF', 'depthBare') 169 | self.d_field = config.getfloat('MMF', 'depthInField') 170 | self.d_TC = config.getfloat('MMF', 'depthTC') 171 | self.RFR = config.getfloat('MMF', 'RFR') 172 | self.rho_s = config.getfloat('MMF', 'rho_s') 173 | self.rho = config.getfloat('MMF', 'rho') 174 | self.eta = config.getfloat('MMF', 'eta') 175 | 176 | #-Determine manning for soil and tilled conditions 177 | self.n_tilled = self.mmf.ManningTillage(self, pcr) 178 | self.n_soil = pcr.ifthenelse(self.Tillage == 1, self.n_tilled, self.n_bare) 179 | 180 | #-Determine flow velocity for in field deposition 181 | self.n_veg_field = self.mmf.manningVegetation(self, pcr, self.d_field, self.Diameter, self.NoElements) 182 | self.n_veg_field = pcr.ifthenelse(self.NoVegetation == 1, 0, self.n_veg_field) 183 | self.n_veg_field = pcr.ifthenelse(self.NoErosion == 1, 0, self.n_veg_field) 184 | self.n_veg_field = pcr.ifthenelse(self.n_table > 0, self.n_table, self.n_veg_field) 185 | self.n_field = (self.n_soil**2 + self.n_veg_field**2)**0.5 186 | self.v_field = self.mmf.FlowVelocity(self, pcr, self.n_field, self.d_field) 187 | 188 | #-Determine flow velocity after harvest 189 | if self.harvest_FLAG: 190 | self.n_veg_field_harvest = self.mmf.manningVegetation(self, pcr, self.d_field, self.Diameter_harvest, self.NoElements_harvest) 191 | self.n_veg_field_harvest = pcr.ifthenelse(self.Tillage_harvest == 1, 0, self.n_veg_field_harvest) 192 | self.n_field_harvest = (self.n_soil**2 + self.n_veg_field_harvest**2)**0.5 193 | self.v_field_harvest = self.mmf.FlowVelocity(self, pcr, self.n_field_harvest, self.d_field) 194 | 195 | 196 | #-dynamic processes 197 | def dynamic(self, pcr, Precip, Runoff): 198 | #-determine canopy cover from LAI 199 | if self.CanopyCoverLAIFlag == 1 and self.DynVegFLAG == 1: 200 | self.CC = pcr.min(1, self.LAI) 201 | else: 202 | self.CC = self.CC_table 203 | 204 | #-determine areas that have been harvested 205 | if self.harvest_FLAG: 206 | self.Harvested = self.Slope * 0 207 | self.Harvested = pcr.ifthenelse(self.Harvest < self.Sowing, pcr.ifthenelse(pcr.pcrand(self.Harvest < self.curdate.timetuple().tm_yday, self.Sowing > self.curdate.timetuple().tm_yday), 1, self.Harvested), self.Harvested) 208 | self.Harvested = pcr.ifthenelse(self.Harvest > self.Sowing, pcr.ifthenelse(pcr.pcror(self.curdate.timetuple().tm_yday > self.Harvest, self.curdate.timetuple().tm_yday < self.Sowing), 1, self.Harvested), self.Harvested) 209 | self.Harvested = pcr.ifthenelse(self.Harvest == 0, 0, self.Harvested) 210 | 211 | #-set canopy cover to value from MMF harvest table for months between harvest and sowing 212 | if self.CanopyCoverLAIFlag == 0 and self.harvest_FLAG: 213 | self.CC = pcr.ifthenelse(self.Harvested == 1, self.CC_harvest, self.CC_table) 214 | 215 | #-set ground cover to value from MMF harvest table for months between harvest and sowing 216 | if self.harvest_FLAG: 217 | self.GC = pcr.ifthenelse(self.Harvested == 1, self.GC_harvest, self.GC_table) 218 | else: 219 | self.GC = self.GC_table 220 | 221 | #-define cover as fraction of soil covered by ground cover and rock 222 | if self.SnowFLAG == 1: 223 | SCover = pcr.scalar(self.TotalSnowStore > 0) 224 | self.Cover = pcr.min(SCover + self.GC + self.RockFrac, 1) 225 | else: 226 | self.Cover = pcr.min(self.GC + self.RockFrac, 1) 227 | 228 | #-determine effective rainfall 229 | Rf = self.mmf.RainEff(self, pcr, Precip) 230 | 231 | #-determine leaf drainage 232 | LD = self.mmf.LeafDrain(self, pcr, Rf) 233 | 234 | #-determine direct throughfall 235 | DT = self.mmf.DirectThroughfall(self, pcr, Rf, LD) 236 | 237 | #-obtain precipitation intensity from direct throughfall and fraction of the rain in the highest intensity 238 | if self.InfilFLAG == 1: 239 | self.PrecInt = DT * self.Alpha 240 | 241 | #-determine kinetic energy of the direct throughfall 242 | KE_DT = self.mmf.KineticEnergyDT(self, pcr, DT, self.PrecInt) 243 | KE_DT = pcr.ifthenelse(DT == 0, 0, KE_DT) 244 | 245 | #-update plant height for months between harvest and sowing 246 | if self.harvest_FLAG: 247 | self.PlantHeightUpdate = pcr.ifthenelse(self.Harvested == 1, self.PlantHeight_harvest, self.PlantHeight) 248 | else: 249 | self.PlantHeightUpdate = self.PlantHeight 250 | 251 | #-determine kinetic energy of the leaf drainage 252 | KE_LD = self.mmf.KineticEnergyLD(self, pcr, LD, self.PlantHeightUpdate) 253 | 254 | #-determine total kinetic energy 255 | KE = KE_DT + KE_LD 256 | 257 | #-determine detachment of soil particles by raindrop impact 258 | F_c = self.mmf.DetachmentRaindrop(self, pcr, self.K_c, self.RootClayMap, KE) 259 | F_z = self.mmf.DetachmentRaindrop(self, pcr, self.K_z, self.RootSiltMap, KE) 260 | F_s = self.mmf.DetachmentRaindrop(self, pcr, self.K_s, self.RootSandMap, KE) 261 | F = F_c + F_z + F_s 262 | 263 | #-report detachment of soil particles by raindrop impact (ton / cell) 264 | self.reporting.reporting(self, pcr, 'DetRn', F * pcr.cellarea() / 1000) 265 | 266 | #-determine detachment of soil particles by runoff 267 | H_c = self.mmf.DetachmentRunoff(self, pcr, self.DR_c, self.RootClayMap, Runoff) 268 | H_z = self.mmf.DetachmentRunoff(self, pcr, self.DR_z, self.RootSiltMap, Runoff) 269 | H_s = self.mmf.DetachmentRunoff(self, pcr, self.DR_s, self.RootSandMap, Runoff) 270 | H = H_c + H_z + H_s 271 | 272 | #-report detachment of soil particles by runoff (ton / cell) 273 | self.reporting.reporting(self, pcr, 'DetRun', H * pcr.cellarea() / 1000) 274 | 275 | #-replace velocity for vegetated conditions for tilled soil conditions in case of harvested areas 276 | if self.harvest_FLAG: 277 | self.v_update = pcr.ifthenelse(self.Harvested == 1, self.v_field_harvest, self.v_field) 278 | else: 279 | self.v_update = self.v_field 280 | 281 | #-determine particle fall number 282 | N_f_c = self.mmf.ParticleFallNumber(self, pcr, self.deltaClay, self.v_update, self.d_field) 283 | N_f_z = self.mmf.ParticleFallNumber(self, pcr, self.deltaSilt, self.v_update, self.d_field) 284 | N_f_s = self.mmf.ParticleFallNumber(self, pcr, self.deltaSand, self.v_update, self.d_field) 285 | 286 | #-determine percentage of the detached sediment that is deposited within the cell of origin 287 | DEP_c = self.mmf.Deposition(self, pcr, N_f_c) 288 | DEP_z = self.mmf.Deposition(self, pcr, N_f_z) 289 | DEP_s = self.mmf.Deposition(self, pcr, N_f_s) 290 | 291 | #-determine delivery of detached particles to runoff and sediment that is deposited within the cell of origin 292 | tempvar = self.mmf.MaterialTransport(self, pcr, F_c, H_c, DEP_c) 293 | G_c = tempvar[0] 294 | D_c = tempvar[1] 295 | tempvar = self.mmf.MaterialTransport(self, pcr, F_z, H_z, DEP_z) 296 | G_z = tempvar[0] 297 | D_z = tempvar[1] 298 | tempvar = self.mmf.MaterialTransport(self, pcr, F_s, H_s, DEP_s) 299 | G_s = tempvar[0] 300 | D_s = tempvar[1] 301 | G = G_c + G_z + G_s 302 | D = D_c + D_z + D_s 303 | 304 | #-report in field deposition of detached particles (ton / cell) 305 | self.reporting.reporting(self, pcr, 'SDepFld', D * pcr.cellarea() / 1000) 306 | 307 | #-report sediment in transport (ton / cell) 308 | self.reporting.reporting(self, pcr, 'SedTrans', G * pcr.cellarea() / 1000) 309 | 310 | return G -------------------------------------------------------------------------------- /modules/advanced_routing.py: -------------------------------------------------------------------------------- 1 | # The Spatial Processes in HYdrology (SPHY) model: 2 | # A spatially distributed hydrological model 3 | # Copyright (C) 2013-2025 FutureWater 4 | # Email: sphy@futurewater.nl 5 | # 6 | # Authors (alphabetical order): 7 | # P. Droogers, J. Eekhout, A. Fernandez-Rodriguez, W. Immerzeel, S. Khanal, A. Lutz, T. Schults, G. Simons, W. Terink. 8 | # 9 | # This program is free software: you can redistribute it and/or modify 10 | # it under the terms of the GNU General Public License as published by 11 | # the Free Software Foundation, either version 3 of the License, or 12 | # (at your option) any later version. 13 | # 14 | # This program is distributed in the hope that it will be useful, 15 | # but WITHOUT ANY WARRANTY; without even the implied warranty of 16 | # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 17 | # GNU General Public License for more details. 18 | # 19 | # You should have received a copy of the GNU General Public License 20 | # along with this program. If not, see . 21 | 22 | # Advanced routing that is used for reservoirs or lakes 23 | print("Advanced routing module for lakes and reservoirs imported") 24 | 25 | 26 | # -Function to rout the specific runoff 27 | def ROUT(self, pcr, rvolume, qold, qout, sres): 28 | # Calculate the discharge Q (m3/d) 29 | Q = pcr.accufractionflux(self.FlowDir, rvolume, self.QFRAC) 30 | # Re-calculate Q, based on qold en kx, and assign Qout for cells being lake/reservoir 31 | Q = pcr.ifthenelse( 32 | self.QFRAC == 0, qout, (1 - self.kx) * Q + (qold * 24 * 3600) * self.kx 33 | ) 34 | # Only calculate inflow for lake/reservoir cells 35 | Qin = pcr.ifthenelse(self.QFRAC == 0, pcr.upstream(self.FlowDir, Q), 0) 36 | sres = sres - qout + Qin 37 | Q = Q / (24 * 3600) # -only convert Q to m3/s 38 | return sres, Q, Qin 39 | 40 | 41 | # -init advanced routing processes 42 | def init(self, pcr, config): 43 | self.FlowDir = pcr.readmap(self.inpath + config.get("ROUTING", "flowdir")) 44 | try: 45 | self.kx = pcr.readmap(self.inpath + config.get("ROUTING", "kx")) 46 | except: 47 | self.kx = config.getfloat("ROUTING", "kx") 48 | 49 | 50 | # -initial conditions advanced routing 51 | def initial(self, pcr, config): 52 | # -initial routed total runoff 53 | try: 54 | self.QRAold = config.getfloat("ROUT_INIT", "QRA_init") 55 | except: 56 | try: 57 | self.QRAold = pcr.readmap(self.inpath + config.get("ROUT_INIT", "QRA_init")) 58 | except: 59 | self.QRAold = 0 60 | # -initial routed runoff for the individual components 61 | pars = ["RootR", "RootD", "Rain", "Snow", "Glac", "Base"] 62 | for i in pars: 63 | try: 64 | setattr( 65 | self, 66 | i + "RAold", 67 | pcr.readmap(self.inpath + config.get("ROUT_INIT", i + "RA_init")), 68 | ) 69 | setattr(self, i + "RA_FLAG", True) 70 | except: 71 | try: 72 | setattr(self, i + "RAold", config.getfloat("ROUT_INIT", i + "RA_init")) 73 | setattr(self, i + "RA_FLAG", True) 74 | except: 75 | setattr(self, i + "RA_FLAG", False) 76 | 77 | # -initial storage in lakes/reservoirs of individual flow components 78 | pars = ["RootRRA", "RootDRA", "RainRA", "SnowRA", "GlacRA", "BaseRA"] 79 | for i in pars: 80 | column = pars.index( 81 | i 82 | ) # identify column to be read from lake or reservoir table 83 | try: # -try to sum the storages read from the lake and reservoir tables if both thse modules are used 84 | setattr( 85 | self, 86 | i + "stor", 87 | ( 88 | pcr.cover( 89 | pcr.lookupscalar(LakeStor_Tab, column + 2, self.LakeID), 0 90 | ) 91 | + pcr.cover( 92 | pcr.lookupscalar(ResStor_Tab, column + 3, self.ResID), 0 93 | ) 94 | ) 95 | * 10**6, 96 | ) 97 | if eval("self." + i + "_FLAG"): 98 | setattr(self, i + "_FLAG", True) 99 | else: 100 | setattr(self, i + "_FLAG", False) 101 | except: 102 | try: # -try to read the storages from the lake table 103 | setattr( 104 | self, 105 | i + "stor", 106 | pcr.cover( 107 | pcr.lookupscalar(LakeStor_Tab, column + 2, self.LakeID), 0 108 | ) 109 | * 10**6, 110 | ) 111 | if eval("self." + i + "_FLAG"): 112 | setattr(self, i + "_FLAG", True) 113 | else: 114 | setattr(self, i + "_FLAG", False) 115 | except: # -try to read the storages from the reservoir table 116 | try: 117 | setattr( 118 | self, 119 | i + "stor", 120 | pcr.cover( 121 | pcr.lookupscalar(ResStor_Tab, column + 3, self.ResID), 0 122 | ) 123 | * 10**6, 124 | ) 125 | if eval("self." + i + "_FLAG"): 126 | setattr(self, i + "_FLAG", True) 127 | else: 128 | setattr(self, i + "_FLAG", False) 129 | except: 130 | setattr(self, i + "_FLAG", False) 131 | 132 | 133 | # -dynamic processes advanced routing 134 | def dynamic(self, pcr, pcrm, config, TotR, ETOpenWater, PrecipTot): 135 | # -Update storage in lakes/reservoirs (m3) with specific runoff 136 | self.StorRES = self.StorRES + pcr.ifthenelse( 137 | self.QFRAC == 0, 0.001 * pcr.cellarea() * TotR, 0 138 | ) 139 | OldStorage = self.StorRES 140 | # -Calculate lake/reservoir outflow volumes 141 | if self.LakeFLAG == 1 and self.ResFLAG == 1: 142 | tempvar = self.lakes.UpdateLakeHStore(self, pcr, pcrm) 143 | LakeLevel = tempvar[0] 144 | self.StorRES = tempvar[1] 145 | LakeQ = self.lakes.QLake(self, pcr, LakeLevel) 146 | ResQ = self.reservoirs.QRes(self, pcr) 147 | Qout = pcr.ifthenelse( 148 | self.ResID != 0, ResQ, pcr.ifthenelse(self.LakeID != 0, LakeQ, 0) 149 | ) 150 | elif self.LakeFLAG == 1: 151 | tempvar = self.lakes.UpdateLakeHStore(self, pcr, pcrm) 152 | LakeLevel = tempvar[0] 153 | self.StorRES = tempvar[1] 154 | Qout = self.lakes.QLake(self, pcr, LakeLevel) 155 | else: 156 | Qout = self.reservoirs.QRes(self, pcr) 157 | 158 | # -Calculate volume available for routing (=outflow lakes/reservoir + cell specific runoff) 159 | RunoffVolume = pcr.upstream(self.FlowDir, Qout) + pcr.ifthenelse( 160 | self.QFRAC == 0, 0, 0.001 * pcr.cellarea() * TotR 161 | ) 162 | # -Routing of total flow 163 | tempvar = self.advanced_routing.ROUT( 164 | self, pcr, RunoffVolume, self.QRAold, Qout, self.StorRES 165 | ) 166 | self.StorRES = tempvar[0] 167 | if self.ETOpenWaterFLAG == 1: 168 | # -determine actual evapotranspiration per reservoir in m3/day 169 | ETaRES = pcr.ifthenelse( 170 | self.StorRES > 0, 171 | pcr.min( 172 | ( 173 | pcr.areatotal( 174 | ETOpenWater * pcr.cellarea() * self.openWaterFrac, 175 | self.openWaterNominal, 176 | ) 177 | * 0.001 178 | ), 179 | self.StorRES, 180 | ), 181 | 0, 182 | ) 183 | # -Determine total precipitation as input for fraction of open water 184 | PrecipRES = pcr.ifthenelse( 185 | self.StorRES > 0, 186 | ( 187 | pcr.areatotal( 188 | PrecipTot * pcr.cellarea() * self.openWaterFrac, 189 | self.openWaterNominal, 190 | ) 191 | * 0.001 192 | ), 193 | 0, 194 | ) 195 | # -update storage by subtracting the actual evapotranspiration per reservoir 196 | self.StorRES = self.StorRES - ETaRES + PrecipRES 197 | Q = tempvar[1] 198 | Qin = tempvar[2] 199 | self.QRAold = Q 200 | self.reporting.reporting(self, pcr, "QallRAtot", Q) 201 | # -report flux in mm 202 | if self.mm_rep_FLAG == 1 and self.QTOT_mm_FLAG == 1: 203 | self.QTOTSubBasinTSS.sample( 204 | ((Q * 3600 * 24) / pcr.catchmenttotal(pcr.cellarea(), self.FlowDir)) * 1000 205 | ) 206 | # -report lake and reservoir waterbalance 207 | if self.LakeFLAG == 1 and config.getint("REPORTING", "Lake_wbal") == 1: 208 | self.LakeInTSS.sample(Qin) 209 | self.LakeOutTSS.sample(Qout) 210 | self.LakeStorTSS.sample(self.StorRES) 211 | if self.ResFLAG == 1 and config.getint("REPORTING", "Res_wbal") == 1: 212 | self.ResInTSS.sample(Qin) 213 | self.ResOutTSS.sample(Qout) 214 | self.ResStorTSS.sample(self.StorRES) 215 | if self.ETOpenWaterFLAG: 216 | self.ResETaTSS.sample(ETaRES) 217 | self.ResInCalTSS.sample(Qin - ETaRES) 218 | 219 | # -Routing of individual contributers 220 | # -Snow routing 221 | if self.SnowRA_FLAG == 1 and self.SnowFLAG == 1: 222 | self.SnowRAstor = self.SnowRAstor + pcr.ifthenelse( 223 | self.QFRAC == 0, SnowR * 0.001 * pcr.cellarea(), 0 224 | ) 225 | cQfrac = pcr.cover(self.SnowRAstor / OldStorage, 0) 226 | cQout = cQfrac * Qout 227 | cRunoffVolume = pcr.upstream(self.FlowDir, cQout) + pcr.ifthenelse( 228 | self.QFRAC == 0, 0, 0.001 * pcr.cellarea() * SnowR 229 | ) 230 | tempvar = self.advanced_routing.ROUT( 231 | self, pcr, cRunoffVolume, self.SnowRAold, cQout, self.SnowRAstor 232 | ) 233 | self.SnowRAstor = tempvar[0] 234 | SnowRA = tempvar[1] 235 | cQin = tempvar[2] 236 | self.SnowRAold = SnowRA 237 | self.reporting.reporting(self, pcr, "SnowRAtot", SnowRA) 238 | if self.mm_rep_FLAG == 1 and self.QSNOW_mm_FLAG == 1: 239 | self.QSNOWSubBasinTSS.sample( 240 | ( 241 | (SnowRA * 3600 * 24) 242 | / pcr.catchmenttotal(pcr.cellarea(), self.FlowDir) 243 | ) 244 | * 1000 245 | ) 246 | # -report lake and reservoir waterbalance 247 | if self.LakeFLAG == 1 and config.getint("REPORTING", "Lake_wbal") == 1: 248 | self.LakeSnowInTSS.sample(cQin) 249 | self.LakeSnowOutTSS.sample(cQout) 250 | self.LakeSnowStorTSS.sample(self.SnowRAstor) 251 | if self.ResFLAG == 1 and config.getint("REPORTING", "Res_wbal") == 1: 252 | self.ResSnowInTSS.sample(cQin) 253 | self.ResSnowOutTSS.sample(cQout) 254 | self.ResSnowStorTSS.sample(self.SnowRAstor) 255 | # -Rain routing 256 | if self.RainRA_FLAG == 1: 257 | self.RainRAstor = self.RainRAstor + pcr.ifthenelse( 258 | self.QFRAC == 0, RainR * 0.001 * pcr.cellarea(), 0 259 | ) 260 | cQfrac = pcr.cover(self.RainRAstor / OldStorage, 0) 261 | cQout = cQfrac * Qout 262 | cRunoffVolume = pcr.upstream(self.FlowDir, cQout) + pcr.ifthenelse( 263 | self.QFRAC == 0, 0, 0.001 * pcr.cellarea() * RainR 264 | ) 265 | tempvar = self.advanced_routing.ROUT( 266 | self, pcr, cRunoffVolume, self.RainRAold, cQout, self.RainRAstor 267 | ) 268 | self.RainRAstor = tempvar[0] 269 | RainRA = tempvar[1] 270 | cQin = tempvar[2] 271 | self.RainRAold = RainRA 272 | self.reporting.reporting(self, pcr, "RainRAtot", RainRA) 273 | if self.mm_rep_FLAG == 1 and self.QRAIN_mm_FLAG == 1: 274 | self.QRAINSubBasinTSS.sample( 275 | ( 276 | (RainRA * 3600 * 24) 277 | / pcr.catchmenttotal(pcr.cellarea(), self.FlowDir) 278 | ) 279 | * 1000 280 | ) 281 | # -report lake and reservoir waterbalance 282 | if self.LakeFLAG == 1 and config.getint("REPORTING", "Lake_wbal") == 1: 283 | self.LakeRainInTSS.sample(cQin) 284 | self.LakeRainOutTSS.sample(cQout) 285 | self.LakeRainStorTSS.sample(self.RainRAstor) 286 | if self.ResFLAG == 1 and config.getint("REPORTING", "Res_wbal") == 1: 287 | self.ResRainInTSS.sample(cQin) 288 | self.ResRainOutTSS.sample(cQout) 289 | self.ResRainStorTSS.sample(self.RainRAstor) 290 | # -Glacier routing 291 | if self.GlacRA_FLAG == 1 and self.GlacFLAG == 1: 292 | self.GlacRAstor = self.GlacRAstor + pcr.ifthenelse( 293 | self.QFRAC == 0, GlacR * 0.001 * pcr.cellarea(), 0 294 | ) 295 | cQfrac = pcr.cover(self.GlacRAstor / OldStorage, 0) 296 | cQout = cQfrac * Qout 297 | cRunoffVolume = pcr.upstream(self.FlowDir, cQout) + pcr.ifthenelse( 298 | self.QFRAC == 0, 0, 0.001 * pcr.cellarea() * GlacR 299 | ) 300 | tempvar = self.advanced_routing.ROUT( 301 | self, pcr, cRunoffVolume, self.GlacRAold, cQout, self.GlacRAstor 302 | ) 303 | self.GlacRAstor = tempvar[0] 304 | GlacRA = tempvar[1] 305 | cQin = tempvar[2] 306 | self.GlacRAold = GlacRA 307 | self.reporting.reporting(self, pcr, "GlacRAtot", GlacRA) 308 | if self.mm_rep_FLAG == 1 and self.QGLAC_mm_FLAG == 1: 309 | self.QGLACSubBasinTSS.sample( 310 | ( 311 | (GlacRA * 3600 * 24) 312 | / pcr.catchmenttotal(pcr.cellarea(), self.FlowDir) 313 | ) 314 | * 1000 315 | ) 316 | # -report lake and reservoir waterbalance 317 | if self.LakeFLAG == 1 and config.getint("REPORTING", "Lake_wbal") == 1: 318 | self.LakeGlacInTSS.sample(cQin) 319 | self.LakeGlacOutTSS.sample(cQout) 320 | self.LakeGlacStorTSS.sample(self.GlacRAstor) 321 | if self.ResFLAG == 1 and config.getint("REPORTING", "Res_wbal") == 1: 322 | self.ResGlacInTSS.sample(cQin) 323 | self.ResGlacOutTSS.sample(cQout) 324 | self.ResGlacStorTSS.sample(self.GlacRAstor) 325 | # -Baseflow routing 326 | if self.BaseRA_FLAG == 1: 327 | self.BaseRAstor = self.BaseRAstor + pcr.ifthenelse( 328 | self.QFRAC == 0, self.BaseR * 0.001 * pcr.cellarea(), 0 329 | ) 330 | cQfrac = pcr.cover(self.BaseRAstor / OldStorage, 0) 331 | cQout = cQfrac * Qout 332 | cRunoffVolume = pcr.upstream(self.FlowDir, cQout) + pcr.ifthenelse( 333 | self.QFRAC == 0, 0, 0.001 * pcr.cellarea() * self.BaseR 334 | ) 335 | tempvar = self.routing.ROUT( 336 | self, pcr, cRunoffVolume, self.BaseRAold, cQout, self.BaseRAstor 337 | ) 338 | self.BaseRAstor = tempvar[0] 339 | BaseRA = tempvar[1] 340 | cQin = tempvar[2] 341 | self.BaseRAold = BaseRA 342 | self.reporting.reporting(self, pcr, "BaseRAtot", BaseRA) 343 | if self.mm_rep_FLAG == 1 and self.QBASE_mm_FLAG == 1: 344 | self.QBASESubBasinTSS.sample( 345 | ( 346 | (BaseRA * 3600 * 24) 347 | / pcr.catchmenttotal(pcr.cellarea(), self.FlowDir) 348 | ) 349 | * 1000 350 | ) 351 | # -report lake and reservoir waterbalance 352 | if self.LakeFLAG == 1 and config.getint("REPORTING", "Lake_wbal") == 1: 353 | self.LakeBaseInTSS.sample(cQin) 354 | self.LakeBaseOutTSS.sample(cQout) 355 | self.LakeBaseStorTSS.sample(self.BaseRAstor) 356 | if self.ResFLAG == 1 and config.getint("REPORTING", "Res_wbal") == 1: 357 | self.ResBaseInTSS.sample(cQin) 358 | self.ResBaseOutTSS.sample(cQout) 359 | self.ResBaseStorTSS.sample(self.BaseRAstor) 360 | return Q 361 | -------------------------------------------------------------------------------- /LICENSE.TXT: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. 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No Surrender of Others' Freedom. 541 | 542 | If conditions are imposed on you (whether by court order, agreement or 543 | otherwise) that contradict the conditions of this License, they do not 544 | excuse you from the conditions of this License. If you cannot convey a 545 | covered work so as to satisfy simultaneously your obligations under this 546 | License and any other pertinent obligations, then as a consequence you may 547 | not convey it at all. For example, if you agree to terms that obligate you 548 | to collect a royalty for further conveying from those to whom you convey 549 | the Program, the only way you could satisfy both those terms and this 550 | License would be to refrain entirely from conveying the Program. 551 | 552 | 13. Use with the GNU Affero General Public License. 553 | 554 | Notwithstanding any other provision of this License, you have 555 | permission to link or combine any covered work with a work licensed 556 | under version 3 of the GNU Affero General Public License into a single 557 | combined work, and to convey the resulting work. The terms of this 558 | License will continue to apply to the part which is the covered work, 559 | but the special requirements of the GNU Affero General Public License, 560 | section 13, concerning interaction through a network will apply to the 561 | combination as such. 562 | 563 | 14. Revised Versions of this License. 564 | 565 | The Free Software Foundation may publish revised and/or new versions of 566 | the GNU General Public License from time to time. Such new versions will 567 | be similar in spirit to the present version, but may differ in detail to 568 | address new problems or concerns. 569 | 570 | Each version is given a distinguishing version number. If the 571 | Program specifies that a certain numbered version of the GNU General 572 | Public License "or any later version" applies to it, you have the 573 | option of following the terms and conditions either of that numbered 574 | version or of any later version published by the Free Software 575 | Foundation. If the Program does not specify a version number of the 576 | GNU General Public License, you may choose any version ever published 577 | by the Free Software Foundation. 578 | 579 | If the Program specifies that a proxy can decide which future 580 | versions of the GNU General Public License can be used, that proxy's 581 | public statement of acceptance of a version permanently authorizes you 582 | to choose that version for the Program. 583 | 584 | Later license versions may give you additional or different 585 | permissions. However, no additional obligations are imposed on any 586 | author or copyright holder as a result of your choosing to follow a 587 | later version. 588 | 589 | 15. Disclaimer of Warranty. 590 | 591 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY 592 | APPLICABLE LAW. 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Limitation of Liability. 601 | 602 | IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING 603 | WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS 604 | THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY 605 | GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE 606 | USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF 607 | DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD 608 | PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS), 609 | EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF 610 | SUCH DAMAGES. 611 | 612 | 17. Interpretation of Sections 15 and 16. 613 | 614 | If the disclaimer of warranty and limitation of liability provided 615 | above cannot be given local legal effect according to their terms, 616 | reviewing courts shall apply local law that most closely approximates 617 | an absolute waiver of all civil liability in connection with the 618 | Program, unless a warranty or assumption of liability accompanies a 619 | copy of the Program in return for a fee. 620 | 621 | END OF TERMS AND CONDITIONS 622 | --------------------------------------------------------------------------------