Drought risk management is an effective countermeasure to drought disaster mitigation. Process identification and frequency analysis of drought characteristics are the basis for risk management. Currently, the major issues associated with drought process identification are:1) consistency of hydrological drought indicators (e.g., surface runoff, soil moisture content, groundwater depth) is susceptible to the impact of human activities;2) definitions of threshold values in drought process identification are usually lack of clear physical meaning, and the beginning and end time of drought process vary with these values;3) traditional drought duration defined as the number of periods from the beginning to end time of drought process, may lead to identify the drought event with low intensity and several drought alleviation periods as the severe one due to its long duration; 4) drought intensity lacks time comparability. Therefore, in this study, we used the Palmer drought severity index (PDSI) method by taking the meteorological factors of less influenced as the input to determine the dry/wet states and the PDSI value at each period. Determination of the dry/wet states and the PDSI value at each period included five main steps: hydrological accounting based on meteorological and soil water characteristics data, calculation of climatic coefficients, analysis of the amount of climatically appropriate for existing conditions (CAFEC) precipitation, calculation of Palmer moisture anomaly z-index based on actual and CAFEC precipitation, and estimation of the dry/wet states and the PDSI value based on z-index. The dry/wet states consisted of dry period, wet period, transition period, transition period in dry spell, and transition period in wet spell. Then the drought process identification criteria were analyzed based on the dry/wet states and the PDSI value by trial and error method according to actual drought in the study area. Drought duration was defined as the number of periods under dry states, while the drought severity was estimated as summation of absolute value of negative moisture anomaly index, which was of time-comparability during a drought event. On the basis of the distribution of drought duration and drought severity generated by the frequency curve fitting method, their joint distribution was constructed via the GH Copula, and accordingly the estimation of drought recurrence periods at Kunming station from 1951 to 2011 were conducted. There were 43 droughts were identified, and the drought that occurred in 2009-2010 was the most severe drought event in the study period with the recurrence period of 64.7 years. Results showed that drought process indentified based on the PSDI model was consistent with the actual regional drought circumstances and the results by using runoff index methods, notwithstanding the disparity from that by applying the precipitation index that were not concerned with surface hydrological process. The proposed drought frequency analysis was of clear physical concept, and the expression of drought duration and severity was of physically reasonability. The results of this study can provide a reference for assessment of drought disaster hazard.%干旱过程识别及干旱特征值频率分析是旱灾风险管理的重要基础性工作。目前干旱频率分析中存在的主要问题有：水文干旱指标易受人类活动影响，其序列的一致性条件常难满足；基于阈值的干旱过程识别法中存在着阈值无明确物理意义；干旱历时定义为干旱过程中的时段数，会使过程中有较多旱情缓解期但烈度并不大的干旱因干旱历时较长而被识别为严重干旱；干旱烈度常不具有时间可比性。采用受人类活动影响较小的气象因子为输入，基于帕尔默旱度模式计算了研究区逐时段的干、湿状态及帕尔默干旱指数，根据其干、湿状态及帕尔默干旱指数识别了干旱过程，以干旱过程中处于干期状态的时段数为干旱历时并以干旱过程中具有时间可比性的帕尔默水分距平指数的累积值为干旱烈度。在采用适线法确定干旱历时、干旱烈度分布的基础上，利用GH Copula函数构建了两者的联合分布，计算了昆明站1951－2011年干旱事件的重现期，其中2009－2010年干旱为61 a资料中最严重干旱，重现期达64.7 a一遇。经与昆明实际旱情及由降水、径流指标识别的干旱过程比较，表明基于帕尔默旱度模式识别的干旱过程能较好地反映实际旱情，与由径流指标识别的干旱过程具有较高一致性，而与未涉及地表水文过程的降水指标识别的干旱过程有所差异。研究结果为旱灾危险性评估提供参考。
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