Abstract
The World Food Studies Simulation Model (WOFOST) model is a daily crop growth and yield forecast model with interactions with the environment, including soil, agricultural management, and especially climate conditions. An El Niño–Southern Oscillation (ENSO) phenomenon directly affected climate change and indirectly affected the rice yield in Thailand. This study aims to simulate rice production in central Thailand using the WOFOST model and to find the relationship between rice yield and ENSO. The meteorological data and information on rice yields of Suphan Buri 1 variety from 2011 to 2018 in central Thailand were used to study the rice yields. The study of rice yield found that the WOFOST model was able to simulate rice yield with a Root Mean Square Error (RMSE) value of 752 kg ha−1, with approximately 16% discrepancy. The WOFOST model was able to simulate the growth of Suphan Buri 1 rice, with an average discrepancy of 16.205%, and Suphan Buri province had the least discrepancy at 6.99%. Most rice yield simulations in the central region were overestimated (except Suphan Buri) because the model did not cover crop damage factors such as rice disease or insect damage. The WOFOST model had good relative accuracy and could respond to estimates of rice yields. When an El Niño phenomenon occurs at Niño 3.4, it results in lower-than-normal yields of Suphan Buri 1 rice in the next 8 months. On the other hand, when a La Niña phenomenon occurs at Niño 3.4, Suphan Buri 1 rice yields are higher than normal in the next 8 months. An analysis of the rice yield data confirms the significant impact of ENSO on rice yields in Thailand. This study shows that climate change leads to impacts on rice production, especially during ENSO years.
Highlights
Rice is the main economic crop and the staple food of most people in Asia [1]
The parameters of the World Food Studies Simulation Model (WOFOST) model were re-calibrated using the data in Thailand
The results of the WOFOST model are compared with the survey data from the Department of Agricultural Statistics, first, to verify that the model’s algorithms work properly and, second, to find the relationship between the Suphan rice yield and El Niño–Southern Oscillation (ENSO) phenomena to determine the effect of rice yield
Summary
Rice is the main economic crop and the staple food of most people in Asia [1]. Approximately 50% of the calories consumed by humans come from wheat, rice, and maize [2].Rice, the most important crop in Thailand, has been an important national income since the Ayutthaya period and is still an agricultural commodity that has made a lot of income for the country until now. Rice is the main economic crop and the staple food of most people in Asia [1]. 50% of the calories consumed by humans come from wheat, rice, and maize [2]. The most important crop in Thailand, has been an important national income since the Ayutthaya period and is still an agricultural commodity that has made a lot of income for the country until now. Rice production in Thailand is a vital part of the Thai economy, and many workers work in rice production. Thailand has the fifth largest rice-growing land globally and is the number one exporter of rice globally. Rice research is critical to developing technologies that increase yields and increase income for farmers who grow rice as their primary occupation [3]
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