Drought is a widespread phenomenon in the context of global climate change. Owing to the geographical location of Hunan Province in the middle reaches of Yangtze River and the abundance of forests area in this region with a large population, there is a need to focus on the impacts of drought for devising policies. The spatiotemporal distribution scheme of a given area must be determined to plan water management and protect ecosystems effectively. This study proposes a framework for exploring the spatiotemporal distribution model of drought using comprehensive surveys of historical meteorological stations, which consists of two parts, namely the characteristics of drought extraction in the spatiotemporal distribution and drought models discovered by the clustering method. Firstly, we utilized the run theory to extract drought characteristics, such as drought duration, drought severity, and drought intensity. Secondly, the K-means clustering method was adopted to explore the distribution patterns on the basis of the drought characteristics. Lastly, the method was applied to Hunan Province. Results show that historical drought conditions can be monitored with their characteristics of spatiotemporal variability. Three drought distribution clusters exist in this region. Cluster 1 in western Hunan tends to be a long-term, low-intensity drought, cluster 2 in the southern part tends to be a short-term, high-intensity drought, and cluster 3 in the central part is prone to severe drought. The proposed framework is flexible as it allows parameters to be adjusted and extraction methods to achieve reasonable results for a given area.