Abstract: In order to study the quantitative assessment of drought impacts on double cropping early rice, double cropping late rice and single cropping rice, the correlation analysis was applied between comprehensive meteorological drought index, water deficit index and drought covered ratio, drought inundated ratio, yield reduction per unit area in each growth stage of each cropping rice, then drought sensitive period of each cropping rice was determined. The weights of comprehensive meteorological drought index and water deficit index which were combined into a comprehensive evaluation index of each cropping rice were calculated, based on the correlation coefficient. Based on the comprehensive evaluation index and combined with the drought-resistant ability, the assessment models of each cropping rice about drought covered ratio, drought inundated ratio and yield reduction per unit area were built by multiple regression equation. The results showed that: (1) seasonal drought was a significant characteristic in Hunan Province. As for double cropping late rice, the frequency of drought had no significant difference among each growth stage; the drought sensitive period was the turning green to tillering stage and the spike differentiation stage. For double cropping early rice and single cropping rice, the frequency of drought had a significant difference between each growth stage, the high frequency appeared in the late stage of rice growth, and that was also the drought sensitive period. (2) The historical fitting rate of drought disaster assessment model for double cropping early rice was 77.6% in the same levels, it increased to 91.1% while the difference was under a rank. For double cropping late rice, the fitting rate was 70.9% in the same level and 83.0% while the difference was under a rank. For single cropping rice, the fitting rate became 61.8% and 84.5%. The rice drought disaster assessment model which was built based on the factors of precipitation, water demand and water supply had a clear physical meaning and a high accuracy. It could be used to provide technical support for quantitative assessment of drought impacts on rice.