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Drought episodes have become the main natural hazards all over the world, resulting in a serious limitation to agricultural production. Based on the daily meteorological data of 34 meteorological stations in Sichuan Province from 1967 to 2016, the reference crop evapotranspiration (ET0) was calculated by comparing the Penman-Monteith method (PM) and seven simplified ET0 methods. The simplified ET0 methods included Hargreaves-Samani (HS) method, Blaney-Criddle (BC) method, Priestley-Taylor (PT) method, Makkink (MK) method, FAO-24Radiation (FAO-Ra) method, Rohwer (Ro) method and World Meteorological Organization (WMO) method. The standardized precipitation evapotranspiration index (SPEI) was calculated based on PM and the three ET0 methods with better performances. To obtain the best calculation methods and assess its adaptability, Sichuan Province was divided into three regions, such as western plateau, southwestern mountain, and central Sichuan basin. The applicability of corresponding SPEI was evaluated with different ET0 methods in each region by time series analysis, error analysis, K-S test and wavelet analysis. The results showed that there were significant differences in the calculation accuracy of seven methods in different regions. The PT method had the best applicability in western plateau and southwestern mountain although the root mean square error (RMSE) of PT method was below 99.11mm and the relative error (RE) of most sites was -3.8%~14.2%. The MK and Ro methods had the stable performances in three regions since the RMSE of both were below 160mm. The SPEI calculated on the basis of PM, MK, Ro and PT ET0 methods had the same trend in the same region. In the year with actual drought event, the minimum values of SPEI were less than 0 so it can identify historical drought events. SPEI_PT and SPEI_PM had the most similar periodic oscillation changes, and the periodic gap between SPEI_Ro and SPEI_PM was the largest. The SPEI correlation at 1 month timescale was better than that at 3 month and 12 month timescales. There was the best correlation between SPEI_MK and SPEI_PM at 1 month timescale, with the correlation coefficient (r) of 0.99 and RMSE of 0.15. Therefore, SPEI_MK can be used as an alternative to SPEI_PM under the condition of missing data. This research can provide a theoretical evidence for drought monitoring and mitigation in Sichuan Province, and it can also give a reference for research in other areas.