Seasonal weather prediction-based decision-support systems for increasing rice production in rainfed areas

Rainfed rice areas contributes less to global rice supply than irrigated one due to its low productivity. However, it is considered as a great potential to the global food security due to its area. Rainfed-rice production relies entirely on rainfall for water supply to support rice growth, which requires substantial amount of water throughout the cropping period. However, rainfall patterns are uncertain considering start and end of the rainy season and total amount and seasonal distribution of rainfall, all of which are crucial factors determining rice productivity. Farmers cultivating rainfed rice usually apply their empirical knowledge to determine when to sow the rice crop, based on certain events/amounts of rainfall occurring at the beginning of the rainy season. However, predicting the sowing date in this manner does not consistently result in greater productivity. Study in Lao-People’s Democratic Republic (Lao PDR, Laos) and Indonesia showed that farmers cultivating rainfed rice did not aim to achieve the highest yield but to obtain stable subsistence-level production because of their insufficient capacity to anticipate forthcoming weather events. To make rainfed rice areas more productive in stable manner than before, it is imperative to improve the local capacity to cope with the uncertainties and make an appropriate decision for better practice and productivities; an element of weather forecasting could play a crucial role in improving the capacity of farmers cultivating rainfed rice to consistently achieve higher yields per unit land area. In this study, a weather–rice–nutrient integrated decision-support system (WeRise) was developed through a collaborative research project by the International Rice Research Institute (IRRI) and Japan International Research Center for Agricultural Sciences (JIRCAS) or IRRI-Japan project funded by the Ministry of Agriculture, Forestry and Fisheries of Japan. SEASONAL WEATHER PREDICTION-BASED DECISION-SUPPORT SYSTEMS FOR INCREASING RICE PRODUCTION