干旱概率研究对于旱灾风险管理具有重要意义。选取广西18个气象站点1960—2020年的降水数据，通过标准化降水指数计算季尺度干旱等级阈值，利用GAMLSS模型确定季尺度降水的最优概率分布函数，利用Copula函数和平方欧氏距离构建二维联合概率分布，分析了广西季尺度气象干旱的时空分布及概率特征。研究结果表明：广西春季标准化降水指数（SPI）缓慢下降，干旱频率呈上升趋势，夏、秋、冬3季的SPI缓慢上升，干旱频率呈下降趋势。在春夏、夏秋、秋冬、冬春4个连续季节中，冬春发生连续干旱、中旱、重旱、特旱的概率较高，范围更广，主要分布在桂南沿海、桂中、桂东北等地；发生连季重旱和特旱概率较高的地区分布在柳州、来宾、钦州、百色等地，其中春夏季柳州的概率最高，分别为7.1%、3.9%。

[Objective] This study aims to analyze the spatiotemporal distribution and probabilistic characteristics of multi-level meteorological droughts at the seasonal scale in Guangxi， China， with a focus on seasonal continuous drought events. The study quantitatively analyzes drought frequency trends， identifies the optimal probability distribution function for seasonal precipitation， and assesses the joint probability of consecutive seasonal droughts with the goal of providing more scientific basis for drought risk management in Guangxi. [Methods] Using daily precipitation data from 18 meteorological stations （1960-2020）， we calculated the Standardized Precipitation Index （SPI） for four seasonal scales and classified drought thresholds into four levels （mild， moderate， severe， and extreme）. The GAMLSS （Generalized Additive Models for Location， Scale and Shape） model compared six probability distributions （Gamma， Normal， Lognormal， Gumbel， Weibull， and Logistic） to fit precipitation sequences， and the Gamma function was selected as the optimal model based on the AIC （Akaike Information Criterion）. Five Copula functions （Clayton， Frank， Gaussian， Gumbel， and t-Copula） were used to construct the joint distribution of continuous seasonal drought， and the optimal Copula function was determined using the squared Euclidean distance （OSL）. Spatial interpolation techniques were applied to visualize regional drought probabilities. [Results] The SPI in spring showed a decreasing trend （-0.005 8/a）， indicating an increase in drought frequency， while the SPI in summer （0.007 6/a）， autumn （0.002 1/a）， and winter （0.015 3/a） showed an increasing trend， indicating a decrease in drought frequency. Based on the fitting results of the GAMLSS model using six probability distribution functions for the seasonal precipitation series in Guangxi， the gamma function appeared most frequently in the optimal and suboptimal distributions， indicating that the gamma function can effectively describe the characteristics of precipitation changes. The seasonal frequencies of different drought levels at various stations show that mild droughts （30%-48%） are more common in summer， while moderate droughts （20%-37%）， severe droughts （10%-27%）， and extreme droughts （5%-17%） are more likely to occur in autumn. The gamma distribution performs exceptionally well， with the difference between theoretical and empirical frequencies not exceeding 11%. Different regions in Guangxi exhibit significant differences in consecutive drought characteristics. Among the four consecutive seasons of spring-summer， summer-autumn， autumn-winter， and winter-spring， the probability of consecutive droughts， moderate droughts， severe droughts， and extreme droughts is higher and more widespread during the winter-spring season. The probability range for consecutive winter-spring droughts is 13.1%-20.9%， primarily distributed in the southern coastal areas of Guangxi， central Guangxi， and northeastern Guangxi， with the highest probability of drought occurring in the northwestern part of Wuzhou City. Regions with a higher probability of severe consecutive droughts are distributed in Liuzhou， Laibin， Qinzhou， and Baise. Regions with a higher probability of severe and extreme consecutive droughts are distributed in Liuzhou， Laibin， Qinzhou， and Baise， among which Liuzhou has the highest probability of severe and extreme consecutive droughts during the spring-summer season， with probabilities of 7.1% and 3.9%， respectively. [Conclusions] The study revealed differences in seasonal drought trends in Guangxi， with spring becoming increasingly dry， while other seasons exhibit a trend toward greater moisture. The robustness of the gamma function in precipitation modeling highlights its practicality in drought frequency analysis. Crucially， the Copula-based joint probability analysis identified winter and spring as the most susceptible periods for consecutive droughts， particularly in regions dominated by karst topography. These findings provide scientific basis for adaptive drought management strategies， emphasizing the need to prioritize addressing composite drought risks in regional water resource planning.