Abstract: Weather index insurance can be used to avoid the disadvantages of traditional agricultural insurance. Based on the data of yield and planting area of maize and meteorological data of Changwu in Shaanxi Province from 1990 to 2018, we analyzed the planting area, total yield, yield per unit area, trend yield, relative meteorological yield, water demand, and supply during growth period of maize. The maize planting risk was evaluated using the method of agricultural production loss-risk assessment. The pure rate of maize was determined by the Logistic modeling. The maize precipitation index during the whole growth period was designed according to the relationship between precipitation index and yield. The compensation scheme of maize precipitation index insurance was designed by projection pursuit regression. The results showed that planting area, total yield, yield per unit area, trend yield, and relative meteorological yield all showed an increasing trend over the years. The average water demand, supply, and deficit of maize were 650, 434, and 216 mm in the whole growing season, respectively. From late April to late August, water deficit of maize occurred. The largest water deficit was 33.65 mm in tasseling period in midJuly, and a slight water surplus was shown in September. The maize production was reduced by 14%, 20%, and 44% in 1994, 1995, and 1997, respectively, with the corresponding precipitation anomalies of -42.44%, -47.72% and -29.71% respectively. The planting risk probability of light, medium, severe and excessive disaster was 7.49%, 3.40%, 1.43%, and 1%, respectively. The pure rate of maize agricultural insurance was 2.92%. The cumulative ten-day precipitation during the growing season was designated as maize precipitation index, with a threshold value of 40 mm. The precipitation index was used to make compensation in sections. Our results provide a new choice for agricultural insurance of maize in Changwu, which is of great significance for solving the current dilemma of agricultural insurance.

Key words: weather index, distribution model, risk assessment, premium rate, compensation.