Abstract: Using the observation data of 10 representative agricultural meteorological observation stations in Hunan Province from 2009 to 2020, and the corresponding daily meteorological data, as well as the output data of rice and rape, the regularity of the continuous cloudy and rainy disaster in Hunan Province and its effects on crop growth and yield were analyzed, and the continuous cloudy and rainy disaster indicators were revised and improved. The Lagrangian interpolation method was used to extract the yield loss rate of rice and rapeseed caused by the continuous cloudy and rainy weather through the expected yield, and the continuous cloudy and rainy disaster risk assessment model was constructed based on the continuous cloudy and rainy disaster indicators. The results showed that the frequency of continuous cloudy and rainy weather during the sowing to transplanting period of rice was the highest, with an average frequency of 31.6%, and the frequency of occurrence during the booting to heading period was the lowest, which was 13.2%; rape had the highest frequency of continuous cloudy and rainy weather during the sowing to seedling period, which was 37.5%, and had the lowest frequency during the flowering to green pod formation period, which was 13.7%. The frequency of mild continuous cloudy and rain weather in rice and rape was 58.2% and 60.6%, the frequency of moderate continuous cloudy and rainy weather was 14.8%, and the frequency of heavy continuous cloudy and rainy weather was 0.3% and 0.5%. The statistical results of the occurrence probability of crop yield loss rate caused by continuous rain showed that 10%~20% yield disaster loss rate had the greatest probability of occurrence, which was 5.73%~8.81%; the probability of occurrence of yield disaster loss rate less than 10% was 1.34%~4.72%; the probability of yield disaster loss rate greater than or equal to 20% was the smallest, ranging from 0.94% to 3.19%. Finally, Changsha City and Hengyang City were selected as the test points for the evaluation model of continuous cloudy and rainy weather, and the results showed that the accuracy rate of the evaluation model was 82.5%~87.7%, indicating that the evaluation model had strong practicability and could be used for daily business monitoring and disaster prediction.

Key words: continuous cloudy and rainy weather, crop, yield, risk assessment, disaster loss rate