AquaCropPlotter: A Shiny app for visualizing and analyzing AquaCrop simulation results

Area of Science:

• Agricultural Science
• Computational Science
• Data Science

Background:

• The FAO's AquaCrop model aids agricultural management but generates complex output files.
• Analyzing large datasets from AquaCrop simulations presents a significant bottleneck for researchers.
• Efficient processing and visualization are crucial for leveraging AquaCrop's full potential.

Purpose of the Study:

• To develop an R Shiny application, AquaCropPlotter, for streamlined analysis of AquaCrop model outputs.
• To provide an intuitive tool for processing, visualizing, and analyzing AquaCrop simulation data.
• To enhance the accessibility and usability of AquaCrop for agricultural research and practice.

Main Methods:

• Development of AquaCropPlotter as an R Shiny application.
• Automated processing of AquaCrop output text files into structured data tables.
• Integration of flexible visualization tools and statistical analysis functionalities.
• Provision of exportable data tables, plots, and analysis results.

Main Results:

• AquaCropPlotter successfully automates the processing of AquaCrop output files.
• The application offers intuitive data exploration, visualization, and statistical analysis.
• Users can gain insights from AquaCrop simulations without programming expertise.
• Case study in the Republic of Moldova demonstrated AquaCropPlotter's utility.

Conclusions:

• AquaCropPlotter significantly reduces the bottleneck in analyzing AquaCrop simulation outputs.
• The open-source application facilitates broader adoption and application of AquaCrop in agriculture.
• AquaCropPlotter empowers researchers and practitioners to better utilize water-related crop modeling insights.