In MadoShi64/rstep: rstep: a workflow for STEP-GENDEC-CN model under R

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rstep: a workflow for STEP-GENDEC-CN model under R

Overview

Introducing rstep: Automating Workflow for 1D and 2D STEP-GENDEC-CN simulations

rstep is an R package designed to simplify and automate the essential tasks involved in performing 1D or 2D STEP-GENDEC-CN simulations. With rstep, you can streamline your workflow, from preparing model input data to executing the model and visualizing the results, all within the comfort of your Rstudio environment.

Key Features of rstep:

1- Model Input Data Preparation: rstep provides automated functions to simplify the preparation of model input data. Say goodbye to manual formatting and transformation, and effortlessly convert your data into a suitable format for STEP-GENDEC-CN.

2- Seamless Model Execution: Execute your 1D or 2D simulations directly from Rstudio with ease. rstep seamlessly interfaces with STEP-GENDEC-CN, allowing you to initiate simulations and monitor progress without the need to switch between environments.

3- Automated Visualization: Save time by automating the visualization of your simulation results. rstep offers a range of visualization tools and functions, enabling you to generate informative plots and graphs effortlessly.

Installation

The development version of rstep can be installed from GitHub:

install.packages("remotes")
remotes::install_github("fredi-agbohessou/rstep")

Some examples

Calling a STEP soil file for formatting

rstep::sol

Run the model from R

#run_step_1D(step_daily_original=step_path,
#            daily_original=filepath)

References :

• Agbohessou, Y., Delon, C., Mougin, E., Grippa, M., Tagesson, T., Diedhiou, M., Ba, S., Ngom, D., Vezy, R., Ndiaye, O., Assouma, M.H., Diawara, M., Roupsard, O. (2023). To what extent are greenhouse-gas emissions offset by trees in a Sahelian silvopastoral system? Agricultural and Forest Meteorology, 343, 109780. https://doi.org/10.1016/j.agrformet.2023.109780
• Bigaignon, L., Delon, C., Ndiaye, O., Galy-Lacaux, C., Serça, D., Gue ́rin, F., Tallec, T., Merbold, L., Tagesson, T., Fensholt, R., Andre ́, S., Galliau, S., 2020. Understanding N2O emissions in African ecosystems: assessments from a semi-arid Savanna Grassland in Senegal and sub-tropical agricultural fields in Kenya 26.
• Delon, C., Galy-Lacaux, C., Serça, D., Personne, E., Mougin, E., Adon, M., Le Dantec, V., Loubet, B., Fensholt, R., Tagesson, T., 2019. Modelling land–atmosphere daily exchanges of NO, NH3, and CO2 in a semi-arid grazed ecosystem in Senegal. Biogeosciences 16, 2049–2077. https://doi.org/10.5194/bg-16-2049-2019.
• Mougin, E., Lo Seena, D., Rambal, S., Gaston, A., Hiernaux, P., 1995. A regional Sahelian grassland model to be coupled with multispectral satellite data. I: model description and validation. Remote Sens. Environ. 52, 181–193. https://doi.org/10.1016/00344257(94)00126-8.

MadoShi64/rstep documentation built on July 1, 2024, 4:55 p.m.