SpatialAquaCrop, an R Package for Raster-Based Implementation of the AquaCrop Model

Area of Science:

• Agricultural Science
• Hydrology
• Environmental Modeling

Background:

• Increasingly critical need for modeling crop water use and soil moisture due to drought events.
• Importance of accurate water resource management in agriculture.
• Limitations of traditional point-based modeling for large-scale assessments.

Purpose of the Study:

• To spatially apply and validate the AquaCrop model using a raster-based approach in an R environment.
• To assess crop water use and soil moisture dynamics across a catchment.
• To evaluate the model's performance against satellite-derived vegetation indices.

Main Methods:

• Raster-based spatial application of the AquaCrop model within an R environment.
• Testing and validation using point-based examples in Central Hungary.
• Application to the Rákos Stream catchment and comparison with satellite-based NDVI data.

Main Results:

• Strong correlation observed between Normalized Difference Vegetation Index (NDVI) and model-based biomass estimation.
• AquaCrop model simulated soil moisture content with a correlation coefficient of 0.82.
• Methodology demonstrated validity for spatial application of the AquaCrop model.

Conclusions:

• The applied raster-based AquaCrop methodology is effective for spatial modeling of crop water use and soil moisture.
• Satellite data (NDVI) can be a valuable tool for model evaluation.
• Availability and quality of input data remain critical challenges for accurate spatial modeling.