Abstract: Droughts are the world’s costliest natural disasters, causing an estimated $6-$8 billion in global damages annually and affecting more people than any other form of natural disaster. Given the consequences and pervasiveness of droughts, it is important to assess the specialized indices that are used to assess drought severity. The standardized precipitation index (SPI) has several characteristics that are an improvement over previous indices, including its simplicity and temporal flexibility that allow it to examine both short term and long term drought conditions. Computation of the SPI involves fitting a gamma probability density function to a given time series of monthly precipitation totals for a weather station. The resulting parameters are then used to find the probability of a particular precipitation event over a given time scale. This probability is then converted to the standard normal random variable SPI index value. In this article, 1-month SPI are calculated and compared with the Z-index, the most widely used index in China. The results demonstrated that 1-month SPI calculated for 7 observational stations are greatly consistent with Zindex, but that the SPI rarely relates to distributing on precipitation, avoiding some of the irregularities associated with the Z-index. Thus, the SPI is superior to the Z-index in its application. We also investigated drought and flood events from 1951-1995 for Beijing in greater detail. By using the 24-month SPI (SPI24), three well-defined drought and flood events were identified from the data series. In general, the same drought and flood events were observed using the 12-month SPI (SPI12) as the SPI24, although there were some interruptions where the SPI12 values approached zero or became negative for short periods. For 3-month periods (SPI3), the SPI values frequently fell above and below zero. These results highlight the SPI characteristics at different time scales. As the time scale increases from 1 to 24 months, the SPI responds more slowly to short-term precipitation variation, and the cycles of positive (wet conditions) and negative (drought) SPI values become more visible. The possibility of calculating the SPI for different time scales enhances its analysis capacity, since it allows the estimation of different antecedent conditions in the soils. Whereas the shortest scales (1 to 3 months) quantifies superficial soil water, which bears a direct significance for agriculture, the longest accumulation scales (12 to 24 months) indicate the state of subsoil moisture as well as other surface and subsurface water resources. The joint consideration of different SPI scales in the analysis contributed to a satisfactory explanation of risk conditions before each flood event reported. These results indicate that the SPI is an effective index for assessing drought conditions at different time scales and should be adopted for use in China.