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Roland Hollós 2019-01-23 17:40:09 +01:00
commit 9d5b050bd8
15 changed files with 143 additions and 149 deletions
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8
RBBGCMuso/R/setupMuso.R
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@ -1,10 +1,10 @@
#' setupMuso
#'
#' This funcion is fundamental for the BiomBGC-MuSo modell related functions like spinupMuso, normalMuso, rungetMuso, because it sets the modells environment.
#' This funcion is fundamental for the Biome-BGCMuSo model related functions like runMuso, spinupMuso, normalMuso, rungetMuso, as it sets the model's environment. The function reads the INI files from a given directory, analyzes them with error checking, and creates a data structure in R that contains the complete information content for the simulation.
#'
#' @author Roland Hollos
#' @param parallel Do you want to run multiple modell paralelly, if yes, set this variable to TRUE
#' @param executable This parameter stores the place of the modell-executable file. In normal usage, you don't have to be set this, because a RBBgcmuso package contains allways the latest modell executable. In spite of this, if you would like to use this package for modell development or just want to use different models (for example for comparison), you will find it useful
#' @author Roland Hollós
#' @param parallel Set this variable to TRUE if you would like to implement parallel execution of the model
#' @param executable This parameter stores the location (directory) of the modell-executable file. In normal usage, you don't have to set this parameter, because a RBBGCMuso package contains allways the latest modell executable. In spite of this, if you would like to use this package for modell development or just want to use different models (for example for comparison), you will find it useful
#' @param calibrationPar You may want to change some parameters in your epc file, before you run the modell. You have to select the appropirate modell parameters. You can refence to these with the number of the line in the epc file where the variables are. It indexes from one. You should use a vector for this, like: c(1,5,8)
#' @param outputLoc Where should the modell puts its outputs. You should give a location for it via this variable, for example: outputLoc="/place/of/the/outputs/"
#' @param inputLoc Usually it is the root directory, where you put the iniFiles for the modell

2
RBBGCMuso/inst/examples/hhs/CO2_from1961.txt
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@ -52,4 +52,4 @@
2012 393.82
2013 396.48
2014 398.61
2015 400.00
2015 400.00

2
RBBGCMuso/inst/examples/hhs/c3grass.epc
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@ -177,4 +177,4 @@ phase1 phase2 phase3 phase4 phase5 phase6 phase7 (text) name of the pheno
0 0 0 0 0 0 0 (ratio) live coarse root ALLOCATION
0 0 0 0 0 0 0 (ratio) dead coarse root ALLOCATION
49 49 49 49 49 49 49 (m2/kgC) canopy average specific leaf area (projected area basis)
0.37 0.37 0.37 0.37 0.37 0.37 0.37 (prop.) current growth proportion
0.37 0.37 0.37 0.37 0.37 0.37 0.37 (prop.) current growth proportion

86
RBBGCMuso/inst/examples/hhs/normal_gyep.ini → RBBGCMuso/inst/examples/hhs/grass_normal.ini
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@ -1,7 +1,7 @@
BBGC_MuSo simulation (missing data: -9999)
MET_INPUT
hhs_2013-2016.mtc43 (filename) met file name
hhs_2013-2016.mtc43 (filename) met file name
4 (int) number of header lines in met file
365 (int) number of simdays in last simyear (truncated year: < 365)
@ -9,12 +9,12 @@ RESTART
1 (flag) 1 = read restart; 0 = dont read restart
0 (flag) 1 = write restart; 0 = dont write restart
0 (flag) 1 = use restart metyear; 0 = reset metyear
hhs.endpoint (filename) name of the input restart file
hhs.endpoint (filename) name of the output restart file
hhs.endpoint (filename) name of the input restart file
hhs.endpoint (filename) name of the output restart file
TIME_DEFINE
4 (int) number of meteorological data years
4 (int) number of simulation years
4 (int) number of simulation years
2013 (int) first simulation year
0 (flag) 1 = spinup run; 0 = normal run
6000 (int) maximum number of spinup years
@ -29,17 +29,17 @@ CLIM_CHANGE
CO2_CONTROL
0 (flag) 0=constant; 1=vary with file
395.0 (ppm) constant atmospheric CO2 concentration
CO2_from2013.txt (filename) name of the CO2 file
CO2_from2013.txt (filename) name of the CO2 file
NDEP_CONTROL
0 (flag) 0=constant; 1=vary with file
0.001400 (kgN/m2/yr) wet+dry atmospheric deposition of N
Ndep_from2013.txt (filename) name of the N-dep file
Ndep_from2013.txt (filename) name of the N-dep file
SITE
30.0 30.0 30.0 30.0 30.0 30.0 30.0 30.0 30.0 30.0 (%) sand percentage by volume in rock-free soil
50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0 (%) silt percentage by volume in rock-free soil
7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 (dimless) soil pH
7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 (dimless) soil pH
248.0 (m) site elevation
46.95 (degrees) site latitude (- for S.Hem.)
0.20 (DIM) site shortwave albedo
@ -54,7 +54,7 @@ SITE
-9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 (m3/m3) SWC at hygroscopic water content
EPC_FILE
maize.epc (filename) EPC file name
maize.epc (filename) EPC file name
W_STATE
0.0 (kg/m2) water stored in snowpack
@ -81,7 +81,7 @@ CN_STATE
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 (kgN/m2) soil mineralized nitrogen, NO3 pool
OUTPUT_CONTROL
hegyhatsal (filename) output prefix
hegyhatsal (filename) output prefix
1 (flag) writing daily output (0 = no; 1 = binary; 2 = ascii)
0 (flag) writing monthly average of daily output (0 = no; 1 = binary; 2 = ascii)
0 (flag) writing annual average of daily output (0 = no; 1 = binary; 2 = ascii)
@ -90,30 +90,30 @@ hegyhatsal
DAILY_OUTPUT
39 number of daily output variables
49 0 tsoil[0]
171 1 evapotranspiration
159 2 soilw_evap
397 3 litr1c_total
398 4 litr2c_total
399 5 litr3c_total
400 6 litr4c_total
518 7 soil1c_total
519 8 soil2c_total
520 9 soil3c_total
521 10 soil4c_total
313 11 fruitc
49 1 tsoil[0]
171 2 evapotranspiration
159 3 soilw_evap
397 4 litr1c_total
398 5 litr2c_total
399 6 litr3c_total
400 7 litr4c_total
518 8 soil1c_total
519 9 soil2c_total
520 10 soil3c_total
521 11 soil4c_total
313 12 fruitc
552 13 HRV_transportC
2520 14 proj_lai
3017 15 total litterfall aboveground
3018 16 total litterfall belowground
2599 17 vwc[0] =soilw layer1 first layer 0-2 cm
2600 18 vwc[1] the second 2-5 cm
2601 19 vwc[2] the third is at 5-10 cm
2602 20 vwc[3] the fourth is at 10-20 cm
2603 21 vwc[4] the fifth is at 20-50 cm
2604 22 vwc[5] the sixth is at 50-100
2599 17 vwc[0] soilw layer1 first layer 0-2 cm
2600 18 vwc[1] the second 2-5 cm
2601 19 vwc[2] the third is at 5-10 cm
2602 20 vwc[3] the fourth is at 10-20 cm
2603 21 vwc[4] the fifth is at 20-50 cm
2604 22 vwc[5] the sixth is at 50-100
407 23 standing dead biomass
3006 24 daily_npp;
3006 24 daily_npp
3005 25 daily_nep
3009 26 daily_gpp
3010 27 daily_mr
@ -121,12 +121,12 @@ DAILY_OUTPUT
3012 29 daily_hr
3051 30 litrc
3052 31 soilc
3037 32 cum_yieldC_HRV (kgC/m2)
3037 32 cum_yieldC_HRV
74 33 GDD
1531 34 SUM of the soil mineral NH4 in the total soil [kgN/m2]
1532 35 SUM of the soil mineral NO3 in the total soil [kgN/m2]
3013 36 daily soil respiration
307 37 leafC -----------------new
307 37 leafC
310 38 fine root C
316 39 soft stem C
@ -149,13 +149,13 @@ ANNUAL_OUTPUT
MANAGEMENT_SECTION
-------------------
PLANTING
1 (flag) do PLANTING? 0=no; 1=yes; filepath=reading from file
1 (flag) do PLANTING? 0=no; 1=yes; filepath=reading from file
121 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(yday) PLANTING day
0.05 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(m) germination depth
7 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(n/m2) number of seedlings
380 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(g/1000n) weight of 1000-seed
40 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(%) C content of seed
100 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(%) emergence rate
100 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(%) emergence rate
THINNING
0 (flag) do THINNING? 0=no; 1=yes; filepath=reading from file
@ -194,30 +194,30 @@ GRAZING
HARVESTING
0 (flag) do HARVESTING? 0=no; 1=yes; filepath=reading from file
275 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(yday) HARVESTING day
0.03 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(kgC/m2) soft stem C content after HARVESTING
90 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(%) transported part of plant material
275 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(yday) HARVESTING day
0.03 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(kgC/m2) soft stem C content after HARVESTING
90 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(%) transported part of plant material
PLOUGHING
0 (flag) do PLOUGHING? 0=no; 1=yes; filepath=reading from file
110 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(yday) PLOUGHING day
0.3 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(m) PLOUGHING depth
0.1 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(prop) dissolving coefficient of ploughed biome to litter
110 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(yday) PLOUGHING day
0.3 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(m) PLOUGHING depth
0.1 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(prop) dissolving coefficient of ploughed biome to litter
FERTILIZING
0 (flag) do FERTILIZING? 0=no; 1=yes; filepath=reading from file
90 140 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(yday) FERTILIZING day
0.28 0.28 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(m) fertilizing depth
120. 30. -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(kgN fertilizer/ha/day) amount of fertilizer
120. 30. -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(kgN fertilizer/ha/day) amount of fertilizer
100 100 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(%) dry matter content of fertilizer
0.5 0.5 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(kgN/kg fertilizer) nitrate content of fertilizer
0.5 0.5 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(kgN/kg fertilizer) ammonium content of fertilizer
0. 0. -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(kgN/kg fertilizer) organic nitrogen content of fertilizer
0. 0. -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(kgC/kg fertilizer) organic carbon content of fertilizer
0. 0. -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(%) labile fraction of fertilizer
0. 0. -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(%) unshielded cellulose fraction of fertilizer
0. 0. -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(%) shielded cellulose fraction of fertilizer
0. 0. -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(%) lignin fraction of fertilizer
0. 0. -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(%) labile fraction of fertilizer
0. 0. -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(%) unshielded cellulose fraction of fertilizer
0. 0. -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(%) shielded cellulose fraction of fertilizer
0. 0. -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(%) lignin fraction of fertilizer
0.01 0.01 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(kgN2O-N:kgN) emission factor for N-additions
IRRIGATION

2
RBBGCMuso/inst/examples/hhs/hhs_1961-2014.mtc43
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@ -1,4 +1,4 @@
Hegyhatsal 1961-2014 FORESEE alapjan
Hegyhatsal 1961-2014 based on FORESEE database
MTCLIM v4.3 OUTPUT FILE : Wed Jul 29 14:02:27 2015
year yday Tmax Tmin Tday prcp VPD srad daylen
(deg C) (deg C) (deg C) (cm) (Pa) (W m-2) (s)

6
RBBGCMuso/inst/examples/hhs/hhs_2013-2016.mtc43
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@ -1,5 +1,5 @@
Hegyhatsal FORESEE alapjan
MTCLIM v4.3 OUTPUT FILE
Hegyhatsal based on FORESEE database
MTCLIM v4.3 OUTPUT FILE
year yday Tmax Tmin Tday prcp VPD srad daylen
(degC) (degC) (degC) (cm) (Pa) (Wm-2) (s)
2013 1 6.59 -4.73 3.48 0.00 63.75 172.69 30217
@ -1461,4 +1461,4 @@ year yday Tmax Tmin Tday prcp VPD srad daylen
2016 362 8.50 -4.00 5.06 0.00 421.47 164.50 30042
2016 363 3.30 -1.40 2.01 0.00 154.57 99.03 30078
2016 364 3.40 -2.40 1.80 0.00 183.68 119.63 30120
2016 365 -1.40 -8.40 -3.33 0.00 153.65 139.92 30166
2016 365 -1.40 -8.40 -3.33 0.00 153.65 139.92 30166

26
RBBGCMuso/inst/examples/hhs/maize.epc
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@ -1,4 +1,4 @@
ECOPHYS FILE - MAIZE
ECOPHYS FILE - MAIZE
----------------------------------------------------------------------------------------
FLAGS
0 (flag) biome type flag (1 = WOODY 0 = NON-WOODY)
@ -166,15 +166,15 @@ CH4 PARAMETERS
0.010 (DIM) param1 for CH4 calculations (empirical function of Tsoil)
----------------------------------------------------------------------------------------
PHENOLOGICAL (ALLOCATION) PARAMETERS (7 phenological phases)
csirazas keles levelnov_felfut levelnov_lin viragzas szemtelitodes erett (text) name of the phenophase
0 45 225 630 90 730 10000 (Celsius) length of phenophase (GDD)
0.0 0.5 0.60 0.30 0.05 0.0 0. (ratio) leaf ALLOCATION
0.0 0.5 0.35 0.25 0.20 0.15 0. (ratio) fine root ALLOCATION
0.0 0. 0.0 0.0 0.05 0.65 1. (ratio) fruit ALLOCATION
0.0 0. 0.05 0.45 0.70 0.20 0. (ratio) soft stem ALLOCATION
0 0 0 0 0 0 0 (ratio) live woody stem ALLOCATION
0 0 0 0 0 0 0 (ratio) dead woody stem ALLOCATION
0 0 0 0 0 0 0 (ratio) live coarse root ALLOCATION
0 0 0 0 0 0 0 (ratio) dead coarse root ALLOCATION
50 50 50 50 50 50 50 (m2/kgC) canopy average specific leaf area (projected area basis)
1.0 1.0 1.0 1.0 1.0 1.0 1.0 (prop.) current growth proportion
germination emergence leafunfold leafunfoldlin flowering grainfilling maturity (text) name of the phenophase
0 45 225 630 90 730 10000 (Celsius) length of phenophase (GDD)
0.0 0.5 0.60 0.30 0.05 0.0 0. (ratio) leaf ALLOCATION
0.0 0.5 0.35 0.25 0.20 0.15 0. (ratio) fine root ALLOCATION
0.0 0. 0.0 0.0 0.05 0.65 1. (ratio) fruit ALLOCATION
0.0 0. 0.05 0.45 0.70 0.20 0. (ratio) soft stem ALLOCATION
0 0 0 0 0 0 0 (ratio) live woody stem ALLOCATION
0 0 0 0 0 0 0 (ratio) dead woody stem ALLOCATION
0 0 0 0 0 0 0 (ratio) live coarse root ALLOCATION
0 0 0 0 0 0 0 (ratio) dead coarse root ALLOCATION
50 50 50 50 50 50 50 (m2/kgC) canopy average specific leaf area (projected area basis)
1.0 1.0 1.0 1.0 1.0 1.0 1.0 (prop.) current growth proportion

0
RBBGCMuso/inst/examples/hhs/muso.exe Executable file → Normal file
View File

84
RBBGCMuso/inst/examples/hhs/n.ini
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@ -1,7 +1,7 @@
BBGC_MuSo simulation (missing data: -9999)
MET_INPUT
hhs_2013-2016.mtc43 (filename) met file name
hhs_2013-2016.mtc43 (filename) met file name
4 (int) number of header lines in met file
365 (int) number of simdays in last simyear (truncated year: < 365)
@ -9,12 +9,12 @@ RESTART
1 (flag) 1 = read restart; 0 = dont read restart
0 (flag) 1 = write restart; 0 = dont write restart
0 (flag) 1 = use restart metyear; 0 = reset metyear
hhs.endpoint (filename) name of the input restart file
hhs.endpoint (filename) name of the output restart file
hhs.endpoint (filename) name of the input restart file
hhs.endpoint (filename) name of the output restart file
TIME_DEFINE
4 (int) number of meteorological data years
4 (int) number of simulation years
4 (int) number of simulation years
2013 (int) first simulation year
0 (flag) 1 = spinup run; 0 = normal run
6000 (int) maximum number of spinup years
@ -29,17 +29,17 @@ CLIM_CHANGE
CO2_CONTROL
0 (flag) 0=constant; 1=vary with file
395.0 (ppm) constant atmospheric CO2 concentration
CO2_from2013.txt (filename) name of the CO2 file
CO2_from2013.txt (filename) name of the CO2 file
NDEP_CONTROL
0 (flag) 0=constant; 1=vary with file
0.001400 (kgN/m2/yr) wet+dry atmospheric deposition of N
Ndep_from2013.txt (filename) name of the N-dep file
Ndep_from2013.txt (filename) name of the N-dep file
SITE
30.0 30.0 30.0 30.0 30.0 30.0 30.0 30.0 30.0 30.0 (%) sand percentage by volume in rock-free soil
50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0 (%) silt percentage by volume in rock-free soil
7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 (dimless) soil pH
7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 (dimless) soil pH
248.0 (m) site elevation
46.95 (degrees) site latitude (- for S.Hem.)
0.20 (DIM) site shortwave albedo
@ -54,7 +54,7 @@ SITE
-9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 (m3/m3) SWC at hygroscopic water content
EPC_FILE
maize.epc (filename) EPC file name
maize.epc (filename) EPC file name
W_STATE
0.0 (kg/m2) water stored in snowpack
@ -81,7 +81,7 @@ CN_STATE
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 (kgN/m2) soil mineralized nitrogen, NO3 pool
OUTPUT_CONTROL
hegyhatsal (filename) output prefix
hegyhatsal (filename) output prefix
1 (flag) writing daily output (0 = no; 1 = binary; 2 = ascii)
0 (flag) writing monthly average of daily output (0 = no; 1 = binary; 2 = ascii)
0 (flag) writing annual average of daily output (0 = no; 1 = binary; 2 = ascii)
@ -90,28 +90,28 @@ hegyhatsal
DAILY_OUTPUT
39 number of daily output variables
49 0 tsoil[0]
171 1 evapotranspiration
159 2 soilw_evap
397 3 litr1c_total
398 4 litr2c_total
399 5 litr3c_total
400 6 litr4c_total
518 7 soil1c_total
519 8 soil2c_total
520 9 soil3c_total
521 10 soil4c_total
313 11 fruitc
49 1 tsoil[0]
171 2 evapotranspiration
159 3 soilw_evap
397 4 litr1c_total
398 5 litr2c_total
399 6 litr3c_total
400 7 litr4c_total
518 8 soil1c_total
519 9 soil2c_total
520 10 soil3c_total
521 11 soil4c_total
313 12 fruitc
552 13 HRV_transportC
2520 14 proj_lai
3017 15 total litterfall aboveground
3018 16 total litterfall belowground
2599 17 vwc[0] =soilw layer1 first layer 0-2 cm
2600 18 vwc[1] the second 2-5 cm
2601 19 vwc[2] the third is at 5-10 cm
2602 20 vwc[3] the fourth is at 10-20 cm
2603 21 vwc[4] the fifth is at 20-50 cm
2604 22 vwc[5] the sixth is at 50-100
2599 17 vwc[0] soilw layer1 first layer 0-2 cm
2600 18 vwc[1] the second 2-5 cm
2601 19 vwc[2] the third is at 5-10 cm
2602 20 vwc[3] the fourth is at 10-20 cm
2603 21 vwc[4] the fifth is at 20-50 cm
2604 22 vwc[5] the sixth is at 50-100
407 23 standing dead biomass
3006 24 daily_npp;
3005 25 daily_nep
@ -121,12 +121,12 @@ DAILY_OUTPUT
3012 29 daily_hr
3051 30 litrc
3052 31 soilc
3037 32 cum_yieldC_HRV (kgC/m2)
3037 32 cum_yieldC_HRV (kgC/m2)
74 33 GDD
1531 34 SUM of the soil mineral NH4 in the total soil [kgN/m2]
1532 35 SUM of the soil mineral NO3 in the total soil [kgN/m2]
3013 36 daily soil respiration
307 37 leafC -----------------new
307 37 leafC
310 38 fine root C
316 39 soft stem C
@ -149,13 +149,13 @@ ANNUAL_OUTPUT
MANAGEMENT_SECTION
-------------------
PLANTING
1 (flag) do PLANTING? 0=no; 1=yes; filepath=reading from file
1 (flag) do PLANTING? 0=no; 1=yes; filepath=reading from file
121 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(yday) PLANTING day
0.05 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(m) germination depth
7 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(n/m2) number of seedlings
380 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(g/1000n) weight of 1000-seed
40 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(%) C content of seed
100 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(%) emergence rate
100 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(%) emergence rate
THINNING
0 (flag) do THINNING? 0=no; 1=yes; filepath=reading from file
@ -194,30 +194,30 @@ GRAZING
HARVESTING
1 (flag) do HARVESTING? 0=no; 1=yes; filepath=reading from file
275 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(yday) HARVESTING day
0.03 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(kgC/m2) soft stem C content after HARVESTING
90 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(%) transported part of plant material
275 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(yday) HARVESTING day
0.03 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(kgC/m2) soft stem C content after HARVESTING
90 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(%) transported part of plant material
PLOUGHING
1 (flag) do PLOUGHING? 0=no; 1=yes; filepath=reading from file
110 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(yday) PLOUGHING day
0.3 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(m) PLOUGHING depth
0.1 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(prop) dissolving coefficient of ploughed biome to litter
110 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(yday) PLOUGHING day
0.3 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(m) PLOUGHING depth
0.1 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(prop) dissolving coefficient of ploughed biome to litter
FERTILIZING
1 (flag) do FERTILIZING? 0=no; 1=yes; filepath=reading from file
90 140 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(yday) FERTILIZING day
0.28 0.28 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(m) fertilizing depth
120. 30. -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(kgN fertilizer/ha/day) amount of fertilizer
120. 30. -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(kgN fertilizer/ha/day) amount of fertilizer
100 100 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(%) dry matter content of fertilizer
0.5 0.5 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(kgN/kg fertilizer) nitrate content of fertilizer
0.5 0.5 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(kgN/kg fertilizer) ammonium content of fertilizer
0. 0. -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(kgN/kg fertilizer) organic nitrogen content of fertilizer
0. 0. -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(kgC/kg fertilizer) organic carbon content of fertilizer
0. 0. -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(%) labile fraction of fertilizer
0. 0. -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(%) unshielded cellulose fraction of fertilizer
0. 0. -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(%) shielded cellulose fraction of fertilizer
0. 0. -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(%) lignin fraction of fertilizer
0. 0. -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(%) labile fraction of fertilizer
0. 0. -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(%) unshielded cellulose fraction of fertilizer
0. 0. -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(%) shielded cellulose fraction of fertilizer
0. 0. -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(%) lignin fraction of fertilizer
0.01 0.01 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 *(kgN2O-N:kgN) emission factor for N-additions
IRRIGATION

4
RBBGCMuso/inst/examples/hhs/parameters.csv
View File

@ -1,7 +1,7 @@
NAME,INDEX,MIN,MAX
BASETEMP,25,3,9
WPM,36,0,1
keles,170.61,0,1000
EMERGENCE,170.61,0,1000
CN_lv,38,10,50
CN_li,39,32,70
CN_root,40,20,90
@ -13,4 +13,4 @@ STOMA,63,0.003,0.015
ROOTDEPTH,74,0.3,2.
SWCGERMIN,87,0.2,0.9
MAXLIFETIME,110,500,1500
NH4MOBILEPROP,120,0.05,0.7
NH4MOBILEPROP,120,0.05,0.7

1 NAME INDEX MIN MAX
2 BASETEMP 25 3 9
3 WPM 36 0 1
4 keles EMERGENCE 170.61 0 1000
5 CN_lv 38 10 50
6 CN_li 39 32 70
7 CN_root 40 20 90
13 ROOTDEPTH 74 0.3 2.
14 SWCGERMIN 87 0.2 0.9
15 MAXLIFETIME 110 500 1500
16 NH4MOBILEPROP 120 0.05 0.7

18
RBBGCMuso/inst/examples/hhs/s.ini
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@ -1,7 +1,7 @@
BBGC_MuSo simulation (missing data: -9999)
MET_INPUT
hhs_1961-2014.mtc43 (filename) met file name
hhs_1961-2014.mtc43 (filename) met file name
4 (int) number of header lines in met file
365 (int) number of simdays in last simyear (truncated year: < 365)
@ -9,12 +9,12 @@ RESTART
0 (flag) 1 = read restart; 0 = dont read restart
1 (flag) 1 = write restart; 0 = dont write restart
0 (flag) 1 = use restart metyear; 0 = reset metyear
hhs.endpoint (filename) name of the input restart file
hhs.endpoint (filename) name of the output restart file
hhs.endpoint (filename) name of the input restart file
hhs.endpoint (filename) name of the output restart file
TIME_DEFINE
54 (int) number of meteorological data years
54 (int) number of simulation years
54 (int) number of simulation years
1961 (int) first simulation year
1 (flag) 1 = spinup run; 0 = normal run
6000 (int) maximum number of spinup years
@ -29,17 +29,17 @@ CLIM_CHANGE
CO2_CONTROL
0 (flag) 0=constant; 1=vary with file
290.0 (ppm) constant atmospheric CO2 concentration
CO2_from1961.txt (filename) name of the CO2 file
CO2_from1961.txt (filename) name of the CO2 file
NDEP_CONTROL
0 (flag) 0=constant; 1=vary with file
0.000200 (kgN/m2/yr) wet+dry atmospheric deposition of N
Ndep_from1961.txt (filename) name of the N-dep file
Ndep_from1961.txt (filename) name of the N-dep file
SITE
30.0 30.0 30.0 30.0 30.0 30.0 30.0 30.0 30.0 30.0 (%) sand percentage by volume in rock-free soil
50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0 50.0 (%) silt percentage by volume in rock-free soil
7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 (dimless) soil pH
7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 7.0 (dimless) soil pH
248.0 (m) site elevation
46.95 (degrees) site latitude (- for S.Hem.)
0.20 (DIM) site shortwave albedo
@ -54,7 +54,7 @@ SITE
-9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 -9999 (m3/m3) SWC at hygroscopic water content
EPC_FILE
c3grass.epc (filename) EPC file name
c3grass.epc (filename) EPC file name
W_STATE
0.0 (kg/m2) water stored in snowpack
@ -81,7 +81,7 @@ CN_STATE
0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 (kgN/m2) soil mineralized nitrogen, NO3 pool
OUTPUT_CONTROL
spinup_ (filename) output prefix
spinup_ (filename) output prefix
0 (flag) writing daily output (0 = no; 1 = binary; 2 = ascii)
0 (flag) writing monthly average of daily output (0 = no; 1 = binary; 2 = ascii)
0 (flag) writing annual average of daily output (0 = no; 1 = binary; 2 = ascii)

16
RBBGCMuso/inst/examples/hhs/sensitivity.csv
View File

@ -1,16 +0,0 @@
"","x"
"BASETEMP",1.33
"WPM",0.18
"CN_lv",0.67
"CN_li",5.72
"CN_root",0.34
"CN_fruit",0.13
"CN_stem",0.59
"CLEC",4.67
"FLNR",26.17
"STOMA",0.79
"ROOTDEPTH",18.98
"SWCGERMIN",0.01
"MAXLIFETIME",0.09
"NH4MOBILEPROP",0.33
"keles",39.99
1 x
2 BASETEMP 1.33
3 WPM 0.18
4 CN_lv 0.67
5 CN_li 5.72
6 CN_root 0.34
7 CN_fruit 0.13
8 CN_stem 0.59
9 CLEC 4.67
10 FLNR 26.17
11 STOMA 0.79
12 ROOTDEPTH 18.98
13 SWCGERMIN 0.01
14 MAXLIFETIME 0.09
15 NH4MOBILEPROP 0.33
16 keles 39.99

38
README.org
View File

@ -55,17 +55,18 @@ Once this command is executed in R it will invoke a small Graphical User Interfa
Once the copyMusoExampleTo command is finished, the model input dataset and the model executable (called muso.exe and cygwin1.dll) are available in the C:\model folder. The user might check the content of the files using his/her favourite text editor (we propose Editpad Lite as it can handle both Windows and Linux text files). Note that file extension might be hidden by Windows which could cause problems, so we propose to adjust Windows so that file extensions are visible. Visit [[https://www.thewindowsclub.com/show-file-extensions-in-windows][this website]] to learn how to show file extensions in Windows.
In this example the C:\model directory will contain the following files:
- muso.exe - this is the Biome-BGCMuSo 5.0 model (version might change in the future)
- cygwin1.dll - a so-called DLL file that supports the model execution
- muso.exe - this is the Biome-BGCMuSo 5.0 model executable for Windows (version might change in the future)
- muso - this is the model executable for Linux
- cygwin1.dll - a so-called DLL file that supports the model execution under Windows
- c3grass.epc - ecophysiological constants input file for the model (C3 grass in this case)
- maize.epc - another ecophysiological constants input file (C4 maize in this case)
- n.ini - initialization file for the model, normal mode (INI file controls the entire simulation)
- normal_grass.ini - another initialization file for the model, for the C3 grass simulation
- grass_normal.ini - another initialization file for the model, for the C3 grass simulation
- s.ini - initialization file for the model spinup (also known as self-initialization or equilibrium run)
- parameters.csv - a simple text file to support sensitivity analysis and parameter sweel (see below)
- hhs_1961-2014.mtc43 - meteorology input file; this file is used for spinup simulation
- parameters.csv - a simple text file to support parameter sweep and sensitivity analysis (see below)
- hhs_1961-2014.mtc43 - meteorology input file; in this example this file is used for spinup simulation
- hhs_2013-2016.mtc43 - meteorology input file for the normal simulation
- CO2_from1961.txt - CO_{2} file for the normal simulation
- CO2_from1961.txt - CO_{2} file for the transient simulation
In the followings we will demonstrate the usability of RBBGCMuso with the hhs example dataset. If you have your own model input data set, you might need to change the commands accordingly.
@ -74,7 +75,7 @@ In the followings we will demonstrate the usability of RBBGCMuso with the hhs ex
----------
*Important note on file naming convention*
We propose to use the following filename convention for the INI files. For practical reasons, name your spinup INI file as something_s.ini, and the normal INI file as something_n.ini where something is arbitrary (note the s and n convention). It is not obligatory, but if you do not follow this convention then you have to generate the settings variable
We propose to use the following filename convention for the INI files. For practical considerations, name your spinup INI file as something_s.ini, and the normal INI file as something_n.ini, where something is arbitrary (note the _s and _n convention). It is not obligatory, but if you do not follow this convention then you have to generate the settings variable
manually with the setupMuso command. However, if you do follow this convention, then RBBGCMuSo will automatically recognize your spinup and normal INI file name and content, so the work will be much easier. (See help of setupMuso command in R.)
In our example s.ini and n.ini follows this convention, so by default RBBGCMuso will use these files for spinup and normal run, repsectively.
----------
@ -98,9 +99,9 @@ In order to run the model as it is provided simply use the following command in
runMuso(skipSpinup = FALSE)
#+END_SRC
Note that by default runMuso skips the spinup simulation (in order to speed up the model execution), but in our case we do not yet have the result of the spinup run (the so-called endpoint file), so spinup simulation is obligatory. This is performed with the skipSpinup=FALSE parameter. Note that according to the naming convention described above the model will use s.ini and n.ini for spinup and normal phase, repsectivelt. It means that the 3rd ini file is not used in this case. As n.ini represents a maize simulation, the results will provide simulation data on C4 maize monoculture with predefined management defined by the n.ini file.
Note that by default runMuso skips the spinup simulation (in order to speed up the model execution), but in our case we do not yet have the result of the spinup run (the so-called endpoint file), so spinup simulation is obligatory. This is performed with the skipSpinup=FALSE parameter. Note that according to the naming convention described above the model will use s.ini and n.ini for spinup and normal phase, repsectively (this can be changed with the parameters of runMuso). It means that the 3rd ini file is not used in this case (grass_normal.ini). As n.ini represents a maize simulation, the results will provide simulation data on C4 maize monoculture with predefined management defined by the n.ini file.
If the simulation is successful, the results can be found in the C:\model directory. In our example two files were created with .log extension that contain some information about the spinup and the normal phase. The hhs.endpoint file is the result of the spinup (and optional transient) run, and can be considered as initial conditions for the normal run. (Here we have to note that now runMuso can be called without the skipSpinup parameter which means that the simulation will be restricted to the normal phase only.) The results of the simulation (carbon fluxes, state variables, whatever was set by the user in the DAILY_OUTPUT block of the normal INI file) are available in the file hegyhatsal.dayout. Note that annual output was not requested in this case. Also note that in the hhs example file set binary daily output is created and further processed by RBBGCMuso. One of the most attractive features of RBBGCMuso is that the model output is handled by the package which means that it will be directly available for the user for further processing in R.
If the simulation is successful, the results can be found in the C:\model directory. In our example two files were created with .log extension that contain some information about the spinup and the normal phase. The hhs.endpoint file is the result of the spinup (and optional transient) run, and can be considered as initial conditions for the normal run. (Here we have to note that now runMuso can be called without the skipSpinup parameter which means that the simulation will be restricted to the normal phase only.) The results of the simulation (carbon fluxes, state variables, whatever was set by the user in the DAILY_OUTPUT block of the normal INI file) are available in the file hegyhatsal.dayout. Note that annual output was not requested in this case. Also note that in the hhs example file set binary daily output is created and further processed by RBBGCMuso. One of the most attractive features of RBBGCMuso is that the model output is handled by the package which means that it will be directly available for the user as a variable for further processing in R.
*** Visualization of the model output
@ -125,6 +126,12 @@ plot(gpp*1000)
#+END_SRC
Note that the 1000 multiplier is needed to get GPP in gC/m^{2}/day units.
The result should look like this image:
#+BEGIN_HTML
<img width="600px"
src="https://raw.githubusercontent.com/hollorol/RBBGCMuso/Documentation/images/gpp01.png" alt="GPP plot">
#+END_HTML
Now get the 4th year from the dataset and plot it:
@ -133,6 +140,8 @@ gpp4<-gpp[(3*365+1):(4*365)]
plot(gpp4*1000,type="l")
#+END_SRC
Advanced visualization of the results is possible with plotMuso.
*** Perform Quick experiments
Assume that we would like to dig a bit deeper with the model and understand the effect of changing ecophysiological variables on the model results. This can easily be performed with RBBGCMuso. Execute the following command in R/RStudio:
@ -141,23 +150,24 @@ Assume that we would like to dig a bit deeper with the model and understand the
musoQuickEffect(calibrationPar = 25, startVal = 0, endVal = 9, nSteps = 5, outVar = 3009)
#+END_SRC
This command selects the 265h line in the ecophysiological constants (EPC) file (this is base temperature), then it starts to replace the original value from 0 to 9 in 5 consecutive steps. In this example GPP is selected (variable number 3009, which is the 26th variable), so the effect of varying base temperature on GPP is calculated using 9 simulations. The result is a spectacular plot where color coding is used distinguish the parameter values.
This command selects the 25th line in the ecophysiological constants (EPC) file (this is base temperature), then it starts to replace the original value from 0 to 9 in 5 consecutive steps. In this example GPP is selected (variable number 3009, which is the 26th variable), so the effect of varying base temperature on GPP is calculated using 5 simulations. The result is a spectacular plot where color coding is used distinguish the parameter values.
At present musoQuickEffect is not usable for the allocation parameters due to restrictions of the allocation fractions.
*** Study the effect of ecophysiological parameters using paramSweep
The paramSweep function is the extension of the musoQuickEffect. It can test the effect of the selected parameters on the model results in once. The result of the paramSweep function is a single HTML file with embedded images. paramSweep needs a csv file called parameters.csv which defines the parameters of interest and the corresponding parameter intervals. In case of the hhs sample dataset there is an example parameters/csv file (please open it and check). Note that there is a tricky part in the parameters.csv as the parameter selection is not straightforward in case of multiple columns (see the end of the EPC file). The logic is that real numbers are used to select the appropriate parameter from multiple columns. In the provided example "keles,170.61,0,1000" means that in the 170th line of the EPC file there are 7 columns (numbering starts from 0, so it is 6), and we would like to adjust the 2nd column (marked by 1), which ends up with 170.61. 0,1000 means that sweep starts at 0 and ends with 1000. Invoke the paramSweep with simply issuing this command:
The paramSweep function is the extension of the musoQuickEffect. It can test the effect of the multiple selected parameters on the model results in once. The result of the paramSweep function is a single HTML file with embedded images. paramSweep needs a csv file called parameters.csv which defines the parameters of interest and the corresponding parameter intervals. In case of the hhs sample dataset there is an example parameters/csv file (please open it and check). The structure of the parameters.csv file is simple. First, parameter name is needed (it can be anything but should refer to the parameter), then the line number of the EPC file is provided, then the possible minimum and maximum value of the parameter is given. Note that there is a tricky part in the parameters.csv as the parameter selection is not straightforward in case of multiple columns (see the end of the EPC file). The logic is that fractinal part of a number is used to select the appropriate parameter from multiple columns. In the provided example "emergence,170.61,0,1000" means that in the 170th line of the EPC file there are 7 columns (numbering starts from 0, so it is 6), and we would like to adjust the 2nd column (marked by 1), which ends up with 170.61. 0,1000 means that sweep starts at 0 and ends with 1000. Invoke the paramSweep with simply issuing this command:
#+BEGIN_SRC R :eval no
paramSweep()
#+END_SRC
*IMPORTANT NOTE: After the execution of this command a pop-up window will be opened to select the appropriate parameters.csv file. Due to some R related issues at present the dialog window will appear BEHIND THE MAIN R WINDOW, so it might be hidden from the user. Please check the Windows taskbar and find the dialog window, then select the parameters.csv.*
*IMPORTANT NOTE: After the execution of this command a pop-up window will be opened to select the appropriate parameters.csv file. Due to some R related issues at present the dialog window might appear BEHIND THE MAIN R/Rstudio WINDOW, so it might be hidden from the user. Please check the Windows taskbar and find the dialog window, then select the parameters.csv.*
In advanced mode there is possibility to select the parameters.csv file using the parameters of paramSweep.
*** Sensitivity analysis
[[http://agromo.agrar.mta.hu/files/musoSensi_usage_v6_FINAL.pdf][See this link for details about the sensitivity analysis.]]
Note that parameters.csv is provided in the hhs example dataset, so you don't have to create it manually.
Advanced sensitivity analysis is possible with the musoSensi function of RBBGCMuso. [[http://agromo.agrar.mta.hu/files/musoSensi_usage_v6_FINAL.pdf][See this link to read the manual of the sensitivity analysis.]]
Note that parameters.csv is provided in the hhs example dataset, so you don't have to create it manually. At present sensitivity analysis is not possible for the allocation parameters due to restrictions of the allocation fractions.
*** Contact

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