# Advancing Crop Yield Predictions: AQUACROP Model Application in Poland's JECAM Fields
## 1 Introduction  
The agricultural study conducted in Wielkopolska, situated in central-west Poland, holds significance against the backdrop of the region's recent susceptibility to drought conditions. In particular, this region has experienced a heightened vulnerability to dry spells in recent years [1]. Given the climatic challenges posed by these conditions, monitoring and assessing crop growth has become paramount in this part of Poland. The historical significance of the tested region in Poland as one of the primary agricultural hubs adds depth to its contemporary agricultural challenges. Over the years, Wielkopolska has consistently held a prominent position as one of the main agricultural regions in the country [2]. The rich agricultural heritage of this region has contributed significantly to Poland's agricultural landscape. Wielkopolska, characterized by a warm, humid continental climate [3], faces the intricate task of sustaining various crops, including winter wheat, winter rapeseed, maize, and sugar beet. The region's reliance on rainfed agriculture, combined with evolving climate patterns, underscores the need for a comprehensive understanding of crop dynamics and environmental interactions. While several recognized models, such as APSIM, DSSAT, EPIC, ALMANAC, and CropSyst, alongside studies correlating satellite data with crop yield, simulate crop growth based on physiological responses to environmental factors [4, 5, 6, 7, 8, 9], the decision to employ the AquaCrop model in this study stems from its concurrent testing on maize fields inAfrica as part of the \"SA Polish collaborative crop growth monitoring and yield assessment system for early warning utilizing new satellite Earth Observations data from Copernicus Program\" (SAPOL) project. Given the project's focus on assessing the model's performance under drought conditions, the authors sought to evaluate its applicability in the context of drought susceptibility in Wielkopolska, Poland. This unique opportunity allowed for a comparative analysis of AquaCrop's effectiveness across diverse agricultural settings, providing valuable insights into its potential utility under varying climatic conditions. Existing models often involve extensive numerical datasets, and require appropriate calibration, making them complex, especially for end-users like farmers [10]. The AquaCrop model, devised by the Food and Agriculture Organization (FAO), serves as a farm-level simulation tool specifically designed to address these challenges. It aims to simulate various irrigation scenarios and estimate crop canopy cover, biomass, and final yield [11]. Its balanced combination of simplicity, accuracy, and robustness makes it an optimal solution for irrigation strategies in diverse climatic environments [12]. The integration of in-situ measurements, conducted within the Joint Experiment for Crop Assessment and Monitoring (JECAM) area, becomes pivotal in providing real-time data for the calibration and validation of the AquaCrop model. Notably, JECAM's field campaigns, spanning from 2018 to 2023, have been strategically timed to align with meteorological conditions. This approach ensures the vigilant monitoring of crop variability, especially in the face of the heightened risk of drought in the Wielkopolska region. The selection of key crops, including winter wheat, winter rapeseed, maize, and sugar beet, provides a representative sample for detailed monitoring during the vegetation season. The methodology encompasses a suite of in-situ measurements, capturing parameters such as electromagnetic radiation reflectance, Leaf Area Index (LAI), soil moisture, photo-synthetically active radiation, chlorophyll content, plant development phases, and plant height. The geographical coordinates of the monitored fields are precisely recorded using GPS receivers, facilitating spatial referencing for subsequent analyses. Importantly, this article underscores that the value of the study goes beyond the application of the AquaCrop model for yield prediction and sustainable agriculture.