Abstract
In recent years, there has been an increase in studies suggesting that gridded weather database (GWD) is a suitable source for simulating crop yield. Brazil has low geospatial coverage by measured weather database (MWD). Based on that, this study aimed to compare two different GWD sources, Daily Gridded (DG) and NASA/POWER (NP), on the simulated yield of upland rice (UR) against the MWD input. The GWD and MWD were obtained for seven locations across UR Brazilian region, considering a period ranging from 1984 to 2016. GWD and MWD were used to estimate rice potential (Yp) and attainable yield (Ya), in clay soil and sandy soil, using the ORYZA (v3) model. DG had the best performance for all variables. GWD-based yields had a reasonable performance. However, DG had a slightly better performance than NP in all conditions, DG-based yields showed RMSE values of 0.57, 0.71, and 0.52 for Yp and Ya in clay and sandy soil, and NP showed RMSE values of 0.86, 0.91, and 0.64. DG also showed higher R2 and d values for yields assessed. Both GWD overestimated Ya; these overestimations in DG-based yield were 3.54, 9.61, and 21.35% for Yp and Ya in clay and sandy soil, respectively, in NP-based yield were 13.67, 18.45, 29.11%, showing that for both GWD-based yield increased as the soil type texture as well as water storage decreased. As a consequence, we do not recommend the use of precipitation data in daily time-step crop modeling.
Highlights
Mathematical models that simulate growth and yield of agricultural crops are important tools for decision making (Caetano and Casaroli 2017; Ferreira et al 2019; Battisti et al 2020; Caetano et al 2021)
The two gridded weather databases (GWD) and its variables applied in this study are: i) Daily Gridded (Xavier et al 2016), which has daily variables at 0.1° x 0.1° for maximum and minimum air temperature, and 0.25° × 0.25° spatial resolution for rainfall and solar radiation; and ii) NASA/POWER (National Aeronautics and Space Administration’s POWER, 2020) which has daily variables, including maximum and minimum air temperature, rainfall and solar radiation at scale of 0.5° × 0.5° horizontal resolution
ECDF for daily solar radiation (Sr) and maximum air temperature (Tmax) in Daily Gridded (DG) data showed a higher similarity to the measured weather data (MWD) than NASA/POWER (NP) (Fig. 1a and c)
Summary
Mathematical models that simulate growth and yield of agricultural crops are important tools for decision making (Caetano and Casaroli 2017; Ferreira et al 2019; Battisti et al 2020; Caetano et al 2021). The use of estimated weather data has been widely used, improving its degree of accuracy more and more (Jha et al 2019; Dubrovsky et al 2020). These data can be used in different applications, such as, to obtain yield gap in agrometeorological models (Santos et al 2021; Paixão et al 2021). Useful and reliable weather datasets are a time-saving tool for crop modeling purposes. The absence of measured weather data (MWD) and a proper spatial resolution are impediments to predicting both, current and future effect of climate on crop yields. GWD has the advantage of complete geospatial cover, becoming an option for regions where the MWD has a lower spatial distribution or incomplete data (Paixão et al 2021)
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