Modified AquaCrop-OpenSource tool for data-scarce regions

The Food and Agriculture Organization (FAO) AquaCrop model has demonstrated its ability to accurately simulate the growth of various crops. However, the quality of simulation results depends on the calibration of the model, which in turn requires field observations of model inputs and parameters. This limits the utility of AquaCrop in data-scarce regions, such as the Global South. A user-friendly method to analyze parameter sensitivities and model output uncertainties could facilitate the assessment of the model output reliability. The AquaCrop version provided by FAO, however, is run through a standalone graphical user interface (GUI) and therefore does not allow for systematic calibration. Besides, the user cannot customize parameter-specific features like irrigation scheduling.

This work presents a tool that enhances the MATLAB-based open-source application of AquaCrop, AquaCrop-OS (AOS), with the following functionalities: A Bayesian modeling feature is designed to calibrate the AOS model considering input data uncertainty, while the MATLAB toolbox Sensitivity Analysis For Everybody (SAFE) is integrated to automate sensitivity and uncertainty analysis. Irrigation schedules may now also be created dynamically and depending on different simulated parameters like the rooting depth. The user can distinguish between different environmental stresses, either by cause or affected variable. Every functionality is supplemented with intuitive graphics. The tool will be released under an open-source license on GitHub. A standalone executable version with a GUI will cater for non-MATLAB users.

The AOS model is calibrated on field data from an experimental agricultural plot in the Ganga River basin in Kanpur, India, for two wheat cropping seasons between 2018 and 2019. The proposed tool is used to quantify the uncertainty in the model input data and parameters and their effects on model outputs.