Forecasting Rice Yields in Thailand with the AquaCrop Model
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Abstract
Background and Objectives: Rice is a staple economic crop in Thailand, but calamities induced by climate change, such as drought and flooding, are admonishing productivity. Therefore, the goal of this study is to predict future rice yields, enabling farmers to prepare for agricultural adaptation.
Methodology: This study used 2019 farmer data as a baseline year. It was then analyzed with daily climate databased on six parameters: minimum and maximum temperature, precipitation, wind speed, relative humidity, and solar radiation. The study incorporated future climate simulation data from the PRECIS model and considers economic development (A2) and environmentally sustainable development (B2). The data was then statistically analyzed using a Least Significant Difference (LSD) at a 95% confidence level. The accuracy of the AquaCrop model was tested by calculating the Mean Absolute Percent Error (MAPE), comparing the actual yield with the predicted yield for 2020 and 2021. The MAPE values were -0.10% in A2 and -0.04% in B2, with lower values indicating higher accuracy.
Main Results: In the reference year, the average rice yield was 562.24 kg/rai. Future production was then forecasted. In 2030, scenarios A2 and B2 show an increase compared to the base year, with average yield of 646.00 and 600.77 kg/rai, respectively. In 2060, there is also a tendency for an increase, with average yields of 668.95 and 669.16 kg/rai, respectively. All pairs exhibit a statistically significant difference (P < 0.05).
Conclusions: The AquaCrop model predicts an increase in future rice yield compared to the base year. The projected results can serve as a guide for future agricultural planning and adjustment, as well as for the proper management of rice fields.
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