格点天气预报数据与机理模型耦合的冬小麦干旱预警方法

为了开展大范围的冬小麦干旱预警,以中国北方冬小麦区为实例,构建了土壤水分动态预报模型,结合未来10 d高精度天气要素预报、土壤自动水分观测和冬小麦发育期观测数据,建立了北方冬小麦区干旱预警系统。利用该系统对2018年4—5月进行逐日的冬小麦干旱预警,对干旱预警产品的分析表明:系统对未来10 d土壤相对湿度预报的决定系数在0. 63～0. 91之间,均方根误差在5. 6%～18. 2%之间,预报时效越近,准确率越高。从不同的干旱等级预测准确率看,对于干旱等级较高的重旱和特旱预报准确率较高,轻旱和中旱的预报准确率略低。该系统基本满足冬小麦干旱预警需求,对国家级农业气象部门大范围农业干旱监测和预警业务是有益的补充。

Drought Early Warning of Winter Wheat Based on Soil Water Dynamic Model Coupled with Grid Weather Forecast Data

Drought is one of the most serious natural disasters and a threat of food security. It is extremely important to have accurate and timely early warning of drought for prevention and reduction of agricultural disasters. Current method of drought early warning was characterized by weak mechanism, low spatial resolution and lack of crop growth information. A daily crop growth and soil moisture dynamics simulation system using a soil water dynamic model in northern winter wheat zone was constructed. Based on this soil moisture simulation system, a drought early warning system for winter wheat was constructed. Daily drought early warning products from April to May in 2018 were generated by using this warning system. The results showed that forecast accuracy of soil relative moisture in next 10 days was high since its coefficient of determination was 0.63~0.91 and its root mean squared error was 5.6%~18.2%. The closer soil moisture forecast was in time, the more accurate was. Forecast accuracy of drought grades for severe and extreme drought was higher than those of mild and moderate grade. This drought warning system satisfied the needs of drought early warning in national agro-meteorological service department in China. The research result would provide scientific basis for prevention and reduction of agricultural disasters and national drought early warning services.