Abstract
Agrometeorological modeling is crucial to predict the impact of climatic conditions on agricultural production. However, its application in large regions faces challenges due to the lack of weather stations and limited access to real-time data. In this study, the multiplicative agrometeorological model was used to estimate soybean productivity in the seven municipalities of the Southern Cone of Rondônia in the 2020/21 to 2022/23 harvests. This model considers the relationships between actual and potential evapotranspirations and water conditions during different phenological stages. Ten-year water balances were developed for each municipality, using air temperature data from ERA5-Land from the ECMWF and precipitation data estimated by NASA’s GPM_v06 satellite. The results showed satisfactory performance of the model, with coefficients of determination ranging from 0.48 to 0.88 and agreement indices from 0.41 to 0.90 compared to the data observed by IBGE.
Published Version
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