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Zoltán BARCZA 2020-01-11 21:40:01 +01:00 committed by GitHub
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@ -109,9 +109,9 @@ If the simulation is successful, the results can be found in the C:\model direct
*** Visualization of the model output
Once the simulation is completed (hopefully without errors), we can visualize the results. Biome-BGCMuSo provides large flexibility on model output selection, which means that the results will depend on the settings of the user in the normal INI file (DAILY_OUTPUT block). In our hhs example 12 variables are calculated in daily resolution. As the model is run for 9 years by the normal INI file, each output variable will be available for 9x365 days (note the handling of leap years in the [[http://agromo.agrar.mta.hu/bbgc/files/Manual_BBGC_MuSo_v6.pdf][Biome-BGCMuSo User's Guide]]).
Once the simulation is completed (hopefully without errors), we can visualize the results. Biome-BGCMuSo provides large flexibility on model output selection, which means that the results will depend on the settings of the user in the normal INI file (DAILY_OUTPUT block; see below). In our hhs example 12 variables are calculated in daily resolution. As the model is run for 9 years by the normal INI file, each output variable will be available for 9x365 days (note the handling of leap years in the [[http://agromo.agrar.mta.hu/bbgc/files/Manual_BBGC_MuSo_v6.pdf][Biome-BGCMuSo User's Guide]]).
Assume that we would like to visualize Gross Primary Production (GPP) for one simulation year (this is the 2nd variable in the n.ini file). This can be achieved by the following commands. First we re-run the normal phase and redirect the output to the R variable called 'results':
Assume that we would like to visualize Gross Primary Production (GPP) for one simulation year (this is the 2nd variable in the n.ini file; see below). This can be achieved by the following commands. First we re-run the normal phase and redirect the output to the R variable called 'results':
#+BEGIN_SRC R :eval no
results<-runMuso()
@ -167,11 +167,11 @@ DAILY_OUTPUT
671 m_vegc_to_SNSC
#+END_SRC
Note the number right below the DAILY_OUTPUT line that indicates the number of selected output variables. If you decide to change the number of output variables, the number (currently 12) should be adjusted accordingly.
Note the number right below the DAILY_OUTPUT line that indicates the number of selected output variables. If you decide to change the number of output variables, the number (currently 12) should be adjusted accordingly. At present the R package handles only daily output data, but the user should acknowledge the optional annual output set in the ini file as well.
Biome-BGCMuSo offers a large number of posible output variables. The full list of variables are available at the website of the model as an Excel file: http://agromo.agrar.mta.hu/bbgc/files/MUSO6_variables.xlsx
Selection of output variables is primarily driven by the need of the user: it depends on the process that the user would like to study. We made an effort to provide all possible variables that are comparable with the observations.
One might be interested in carbon fluxes like Net Ecosystem Exchange (NEE), Gross Primary Production (GPP), total ecosystem respiation (Reco, all comparable with eddy covariance measurements), evapotransporation, Net Primary Production (NPP), soil organic carbon (SOC) content, leaf area index (LAI), aboveground woody biomass and coarse woody debris in forests, crop yield, root depth, aoveground or total biomass for herbaceous vegetation, litter, soil respiration, soil water content for 10 soil layers, soil N2O efflux, etc.
One might be interested in carbon fluxes like Net Ecosystem Exchange (NEE), Gross Primary Production (GPP), total ecosystem respiation (Reco, all comparable with eddy covariance measurements), evapotransporation (ET), Net Primary Production (NPP), soil organic carbon (SOC) content, leaf area index (LAI), aboveground woody biomass and coarse woody debris in forests, crop yield, rooting depth, aoveground or total biomass for herbaceous vegetation, litter, soil respiration, soil water content for 10 soil layers, soil N2O efflux, etc.
Below we list the most common output variables that can be calculated by the model.
@ -243,9 +243,13 @@ Note that parameters.csv is provided in the hhs example dataset, so you don't ha
*IMPORTANT NOTE: If the result file contains only NAs it means that none of the parameters affected the output variable of interest. In this case you need to adjust the output parameter selection or the EPC parameter list. A simple example for this is soil temperature which is not affected by some of the plant parameters. [[https://github.com/hollorol/RBBGCMuso/issues/3][See this link for further details.]]
*** Parameter estimation (calibration)
RBBGCMuso supports parameter estimation (also called as model optimization) based on the GLUE method. GLUE uses observations and the optimization is driven by the parameter interval file that is described above (parameters.csv). Detailed description of the GLUE method will be published soon. Please contact the authors of the package for sample R scripts that executes the GLUE-based parameter estimation.
*** Contact
E-mail: hollorol@gmail.com
E-mail: hollorol@gmail.com, zoltan.barcza@ttk.elte.hu
** Acknowledgements