Fragrant rice is an important export commodity of Thailand and obtaining seasonal production estimates well in advance is important for marketing and stock management. Rice4cast is a software platform that has been developed to forecast rice yield several months prior to harvesting; it links a rice model with a Minimum Data Set (MDS) and Weather Research Forecast (WRF) data. The current study aimed to parameterize and evaluate the model and to demonstrate the use of the Rice4cast platform in forecasting seasonal KDML 105 rice yield and production with local data set. The study area encompassed 77 districts in Thailand, covering 0.94 of the total area of KDML 105 in the country. Minimum Data Sets for the 2013–2015 growing seasons were used for model parameterization and evaluation. The annual statistics from the Office of Agricultural Economics (OAE) were used as a reference basis and planted areas from the Geo-Informatics and Space Technology Development Agency (GISTDA) was used for production estimation. Model evaluation showed good to fairly good agreement between the predicted and reported OAE yield. Production forecasts, however, over-estimated the OAE values considerably, primarily because of the use of GISTDA planted areas that were larger than the harvested areas in the production estimates. Adjustment of the planted areas to account for damaged areas need to be explored further. Nevertheless, the results demonstrated the capability of yield predictions with the Rice4cast, making it a valuable tool for in-season estimates for fragrant rice yield and production.

中文翻译：

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使用空间作物建模和天气预报方法估计泰国的季节性香米产量

香米是泰国重要的出口商品，提前获得季节性产量估计值对于营销和库存管理非常重要。Rice4cast 是一个软件平台，用于在收获前几个月预测水稻产量；它将水稻模型与最小数据集 (MDS) 和天气研究预报 (WRF) 数据联系起来。目前的研究旨在参数化和评估模型，并展示使用 Rice4cast 平台使用本地数据集预测季节性 KDML 105 水稻产量和产量。研究区域包括泰国的 77 个区，占该国 KDML 105 总面积的 0.94。2013-2015 年生长季节的最小数据集用于模型参数化和评估。农业经济办公室 (OAE) 的年度统计数据用作参考基础，地理信息学和空间技术发展局 (GISTDA) 的种植面积用于产量估算。模型评估显示预测和报告的 OAE 产量之间的一致性很好。然而，产量预测大大高估了 OAE 值，主要是因为在产量估计中使用的 GISTDA 种植面积大于收获面积。需要进一步探索调整种植面积以考虑受损面积。尽管如此，结果证明了使用 Rice4cast 进行产量预测的能力，使其成为对香米产量和产量进行季节估计的有价值的工具。