Abstract: Rice is one of the most important staple foods globally, eaten by more than half the world population. China is the largest producer of rice, accounting for 18.5% of the rice planted area globally and 28% of the global rice production. Rice is easily exposed to heat stress because of highly frequent heat-stress events in recent climate warming. Heat-stress is one of the main meteorological disasters causing yield loss in agriculture. Thus, it is essential to explore spatial and temporal characteristics along with extreme heat-wave distribution in early rice so as to develop measures for agricultural adaptation to climate change and to prevent and reduce natural disasters. Studies on heat-stress in rice have mainly focused on spatial and/or temporal distributions of heat-stress at provincial or catchment scales and on the relationship between heat-stress and yield production. However, spatial and temporal distributions of heat-stress at national scale and extreme heat-wave distribution have remained rarely explored. Extreme-value (outlier) theory is a branch of statistical deviation of median probability distribution, which is widely used in structural engineering, hydrology and traffic prediction. Here, we introduced extreme-value theory to analyze heat-stress in early rice and hypothesized that heat-stress in rice obeyed specific outlier distribution. Thus, using 214 meteorological data on early rice region in China, we studied spatial and temporal characteristics along with extreme-value distribution of heat-stress in early rice. Non-parametric methods (such as the Mann-Kendal trend test and extreme-value distribution) were used in this study. We found that:1) mean values of two heat-stress indices-ADHS (cumulative heat-stress days) and HDD (heat-stress degree days)-used to determine the extent of heat-stress were larger in the south and central Hunan Province, central Jiangxi Province, central Zhejiang and Fujian Provinces than that in other areas. This indicated that there were more severe heat-stress events in these areas. The two heat-stress indices significantly increased in more than a third of the investigated site (more than half of the sites in 1990-2015). This further indicated that early rice at these sites suffered from worsening heat-stress. 2) ADHS and HDD at more than half of the sites satisfied the extreme-value (outlier) distribution. ADHS at 56 sites obeyed the Gumbel distribution and at 82 sites satisfied the General extreme-value (outlier) distribution. HDD at 61 sites obeyed Gumbel distribution and at 58 sites satisfied the general extreme-value distribution. 3) The spatial distributions of the 10-, 50-and 100-year return periods of the two heat indices were similar to their mean values. It then meant that regions with larger mean values of the two heat-stress indices also had larger return periods. Furthermore, the return periods of the two heat-stress indices were not significantly correlated with longitude, latitude and altitude. The results improved our understanding of spatial and temporal distributions along with extreme-value (outlier) distributions of heat-stress in rice. It provided the scientific basis for adaptation to climate change and agricultural weather index insurance.