running cnmodel for error tests
This repository contains a reproducible workflow that demonstrates the setup and usage of the rsofun package, specifically built from the cnmodel branch. The workflow includes necessary scripts, data, and steps to execute a basic CN model simulation with additional processing, parameter updates, and result plotting.
Before running the scripts in this repository, ensure you have the following R packages installed:
install.packages(c("dplyr", "tidyr", "ggplot2", "patchwork", "cowplot", "visdat",
"here", "lubridate", "readr", "naniar", "purrr", "remotes"))
remotes::install_github("stineb/rsofun", ref = "cnmodel")
Also, ensure you create an 'output' folder in the cloned repository. This is where the 'output' graphs will save.
reproducible-workflow/
|-- data/
| |-- ch0e2_drivers.rds # Input data file
|-- scripts/
| |-- cn_model_test_run.R # Main workflow script
|-- output/ # Folder for outputs
| |--
|-- README.md # This README file
library(dplyr)
library(tidyr)
library(ggplot2)
library(patchwork)
library(cowplot)
library(visdat)
library(here)
library(lubridate)
library(readr)
library(naniar)
library(purrr)
library(rsofun)
Note: The rsofun package is specifically installed from the cnmodel branch.
library(dplyr)
library(tidyr)
library(ggplot2)
library(patchwork)
library(cowplot)
library(visdat)
library(here)
library(lubridate)
library(readr)
library(naniar)
library(purrr)
library(rsofun)
The main input data for this model is sourced from FLUXNET (CH-OE2) and loaded from an RDS file:
ch0e2_drivers <- readRDS(here("data", "ch0e2_drivers.rds"))
A sample N deposition input is added to the forcing time series, specifying the quantity of N added daily.
n_input_test <- function(data) {
data <- data %>%
mutate(forcing = purrr::map(
forcing,
~mutate(.,
fharv = 0.0,
dno3 = 0.002003263,
dnh4 = 0.002017981))
)
return(data)
}
ch0e2_drivers <- n_input_test(ch0e2_drivers)
Assumes zero harvesting and new seeds planted post-harvest, updating drivers accordingly.
fharv_seed <- function(data, use_cseed = 5, cn_seed = 20) {
use_nseed <- use_cseed / cn_seed
data <- data %>%
mutate(
forcing = purrr::map(
forcing, ~mutate(
.,
fharv = ifelse(month(date) == 7 & mday(date) == 15, 0.0, 0.0),
cseed = ifelse(month(date) == 2 & mday(date) == 15, use_cseed, 0.0),
nseed = ifelse(month(date) == 2 & mday(date) == 15, use_nseed, 0.0))
)
)
return(data)
}
ch0e2_drivers <- fharv_seed(ch0e2_drivers)
Sets the spinup and recycle years for the model to ensure equilibrium.
modify_params <- function(df_list, spinupyears_val, recycle_val) {
df_list <- map(df_list, ~mutate(.x, spinupyears = spinupyears_val, recycle = recycle_val))
return(df_list)
}
ch0e2_drivers$params_siml <- modify_params(ch0e2_drivers$params_siml, 2021, 2)
Defines various model parameters for the P-model and plant characteristics.
pars <- list(
# Add parameter values as per your model requirements
kphio = 0.04998,
# ... [other parameters] ...
)
Run the Model
cnmodel_run_plot <- function(drivers, pars, save_path, df_name) {
# Run the model
output <- runread_cnmodel_f(drivers, par = pars)
# ... [generate and save plots] ...
}
cnmodel_run_plot(ch0e2_drivers, pars, "CH-0E2_NTRUE")