| With the increase of population and the agricultural and industrial demand for water and the change of global environment, the drought disaster is becoming so serious that it has caused the greatest losses of our agricultural production. The drought index is the basis of drought monitoring and prediction. In the recent years, many experts have made a lot of relative research on different indices and methods of drought evaluation. However, the research about prediction on drought degree of Qiantang River based on climate change prediction is scarce, and the prediction and assessment of drought disaster in humid areas is the front issue of hydrological research.In this thesis the DEM technology is used for extraction of features such as flow paths, the digital stream and watershed boundaries of Qiantang River, based on which digital watershed is built, the hydrological process is simulated and the analysis of drought is made.Monthly precipitation data during 1951 to 2008 from 23 weather stations in the Qiantang River Basin are collected for the research. The indices used include the Z index and the SPI index, by which the cumulative probability at a certain time scale is computed for further calculation at multiple time scales. The seasonal and dimensional drought conditions and the trend of the drought situation of different stations in the Qiantang River basin as well as the impact of major drought disasters in the history are analyzed.In this paper, the support vector machine is used for drought prediction under climate change. The NCEP reanalysis data and the precipitation data from 23 meteorological stations in Qiantang River basin during 1961 to 2000 are used. A statistical downscaling method of combining the principal component analysis (PCA) and support vector machine (SVM) is used for the establishment of statistical downscaling model between large-scale meteorological forecasting factors and the monthly precipitation of the meteorological stations in Qiantang River basin. This method combines the PCA and the SVM to calculate the forecasting factors of different global climate model HadCM3, Ccsm3, Echam5 respectively under A1B, A2, B1 emission scenarios and analyze the current and future rainfall condition in the next 30 years(2011-2040) of the Qiantang River basin. The Mann-Kendall nonparametric test method is also used for analyzing the long-term change trend in precipitation and the abrupt change times of drought.Drought duration, drought interval and drought severity are three important indicators in quantitative study of hydrologic drought. But, in present, there is some difficulties in determining drought probability distribution or drought severity through employing analytical method. At present, the most often used method is using assumed theoretical distribution to fit drought severity, and the quality of this method depends on parameter estimation of drought severity probability distribution. On the basis of the premise that drought severity subjects to GEV distribution, we calculate drought severity in different return periods using L-moment approach.The results show that although the value of Z-index and SPI consist with each other and account for the drought conditions of Qiantang River basin over the years reasonably, SPI with multiple time scales is more suitable for the actual situation of Qiantang River Basin. Nine different predicting results of drought conditions in Qiantang River Basin for next 30 years are obtained by applying the global climate models of HadCM3,Echam5 and Ccsm3 on the emission scenarios of A1B,A2 and B1. All the nine results have advantages and disadvantage, and as for which one to use, it depends on particular case. In general, trend modeling results of HadCM3 and Echam5 are better than Ccsm3, but when applied in A1B to model extreme drought, Hadcm3 has better effect than the other two.This study is a significant reference for further drought prediction and analysis, and provides scientific support for drought research and monitoring in humid region.
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