Advancing Crop Modeling and Data Assimilation Using AquaCrop v7.2 in NASA's Land Information System Framework v7.5

This poster introduces the open-source AquaCrop v7.2 model as a new process-based crop model within NASA's Land Information System Framework (LISF) v7.5. Through two showcases, we demonstrate the current capabilities of AquaCrop in the LISF, along with topics for future development. In a first showcase, coarse-scale crop growth simulations with various crop parameterizations are performed over Europe. Satellite-based estimates of land surface phenology are used to inform spatially variable crop parameters. These parameters improve canopy cover simulations in growing degree days compared to using uniform crop parameters in calendar days. The second showcase aims at improving fine-scale agricultural simulations via satellite data assimilation. Specifically, the crop state is updated for winter wheat fields in the Piedmont region of Italy, through assimilation of fine-scale canopy cover satellite data with an ensemble Kalman filter. The state updating is beneficial for the intermediary biomass estimates, but leads to only small improvements in yield estimates. This is due to the strong model (parameter) constraints, and limitations in the assimilated satellite observations and reference yield data. The showcases highlight pathways to improve the current constraints in the crop model and observations, and to advance future crop estimates, e.g. through crop parameter updating and multi-sensor and multi-variate data assimilation.