Construction and applicability analysis of the standardized precipitation actual evapotranspiration index

Abstract: Understanding the drought process and accurately monitoring the drought situation are significant for the people’s livelihood and facilitating sustainable social-economic development in China. Due to the vast territory of the whole country and the widespread impacts of drought, there is a lack of a proper drought index for drought monitoring in China. Based on the calculation of actual evapotranspiration and the choice of most suitable distribution types, this study proposed a standardized Precipitation Actual Evapotranspiration Index (SPAEI) to monitor the drought in central China, using methods such as the Maximum Entropy Production theory. Firstly, we introduced the definition of SPAEI. Then the actual evapotranspiration datasets calculated by the Maximum Entropy Production (MEP) model were validated, followed by the Kolmogorov-Smirnov test used to determine the most suitable probability distribution type of fitting water deficit. Also, the SPEI values were calculated by the Thornthwaite method and Penman-Monteith method (referred to as the SPEI-Th and SPEI-PM) with different time scales (monthly, seasonal, semiannual, and yearly) and compared with the SPAEI values calculated by the MEP model. Further, to assess the applicability of SPAEI in central China and the feasibility of the actual evapotranspiration in the field of drought monitoring, we established comprehensive historical data sets with provincial drought statistics data sets, Vegetation Health Index (VHI), and historical drought records. These data sets were used to validate these indexes by correlation analysis and extreme historical drought events. Finally, SPAEI based on the Mann-Kendall trend test and wavelet analysis was used to analyze drought’s changing trend and periodicity in central China. The results showed that: 1) In central China, every grid and month based on log-logistic distribution under three parameters passed the K-S test (P<0.05), which indicated log-logistic under three parameters distribution was the suitable distribution function of fitting water deficit. 2) There was a significant correlation between SPEI-Th, SPEI-PM, and SPAEI of all time scales (P<0.01), and a strong linear correlation between the SPEI and SPAEI values (R2=0.92-0.97). The correlation coefficient between similar indexes decreased with the increase of time scale. The correlation decreased slightly. The different drought indexes of varying time scales had the same judgment on humidity, but the judgment on drought was relatively different. 3) The comparative analysis of various indexes using relevant drought data showed that the correlation coefficient between SPAEI and VHI were higher than other types of drought indexes among the drought indexes of the same time scale, and SPAEI of seasonal time scale. The correlation between SPAEI of seasonal time scale and drought-affected areas in each province was significant (r=0.56-0.65). Compared with the SPEI values, the SPAEI had better performance to indicate vegetation drought. SPAEI of seasonal time scale had more advantages than other indexes in predicting the actual drought area, vegetation drought performance, and drought identification. 4) The application analysis of seasonal time scale SPAEI in central China showed that the drought in southwest Hubei, northwest Hubei, western Hunan, and southern Hunan had an aggravating trend. The main drought period in central China was about 16 months; the short period was between 6 and 8 months and the long period was about six years. It is indicated in statistics data research that actual evapotranspiration had strong feasibility in the field of drought assessment in China. Our study provided a new drought index for drought monitoring, conducive to the continuous monitoring of drought and water resources management in certain regions. Also, SPAEI could provide a reference for drought monitoring and drought degree quantification in Central China and contribute to the world's understanding of drought monitoring.