摘要
利用分布于我国不同气候区的 7个气象台站 195 1～ 1995年的月降水资料 ,比较分析了标准化降水指标(Standardizedprecipitationindex,SPI)和在我国已成熟应用的Z指数。结果表明 ,SPI计算简单 ,资料容易获取 ,而且计算结果与Z指数有极好的一致性。同时 ,由于SPI是通过概率密度函数求解累积概率 ,再将累积概率标准化而得 ,具有稳定的计算特性 ,消除了降水的时空分布差异 ,在各个区域和各个时段均能有效地反映旱涝状况 ,优于在我国广泛应用的Z指数。此外 ,SPI还可以计算不同时间尺度的指标值 ,能够满足不同水资源状况分析的要求。以北京为例 ,探讨了应用 4种时间尺度的SPI值反映 195 1～ 1995年期间的旱涝事件 ,发现SPI能准确地反映北京4 5年间的旱涝趋势 ,对于旱涝灾害有着良好的预测作用 。
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 (SPI 24), 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 (SPI 12) as the SPI 24, although there were some interruptions where the SPI 12 values approached zero or became negative for short periods. For 3-month periods (SPI 3), 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.
出处
《植物生态学报》
CAS
CSCD
北大核心
2004年第4期523-529,共7页
Chinese Journal of Plant Ecology
基金
国家重点基础研究发展规划项目 ( 973项目 ) (G19990 43 40 7)
中国科学院创新工程项目 (KZCXI_SW_0 1_12
KSCX2_1_0 7)
国家自然科学基金项目 ( 4 0 2 3 10 18
3 0 0 70 64 2
3 0 0 2 80 0 1
4990 5 0 0 5
3 973 0 110
3 0 3 0 0 0 49)
