Abstract
Based on daily temperature and precipitation data of 170 meteorological stations from 1961 to 2010, as well as the soil moisture data and historical drought disaster information in the Huaihe River Basin, the applicability of drought indexes is analyzed. The indexes include the precipitation anomaly percentage (Pa), the Z index (Z), the standardized precipitation index (SPI), the relative moisture index (MI), the compound drought index (CI), the improved CI (CINew) and so on. They are examined from the aspects of inter-annual variation, seasonal evolution, spatial distribution, diagnostic analysis of typical drought processes, unreasonable jumps, the relativity analysis of the soil moisture and drought disaster information. The following results can be reached: All of these drought indexes can be used to diagnose the typical drought years in the Huaihe River Basin effectively, including the year of 1966, 1968, 1976, 1978, 1986, 1988, 1997, 1999, 2001 and so on. When analyzing the seasonal evolution and spatial distribution, both Z index and SPI are not effective, while the diagnosis results of indexes such as Pa, MI, CI and CINew are relatively in consistency and accordant with the fact. As to the diagnoses of typical drought processes and unreasonable jumps, CI and CINew are more effective in describing the mechanism. Analysis on drought relevance to soil moisture and historical drought disaster information shows that CI and CINew have more stable relativity and higher correlation coefficients than Pa, Z index, SPI and MI.In conclusion, as to the monitoring and diagnosis of the drought in the Huaihe River Basin, the applicability of CI and CINew indexes are superior to indexes of Pa, Z index, SPI and MI. The drought is a very complex scientific problem, which is related with many factors such as underlying surface, crop, soil type, rainfall, evaporation and so on. The drought index can have better applicability only when it is built based on reasonable consideration of the occurrence and development mechanism of drought and various influencing factors.