Development of a Drought Propagation Methodology Using Meteorological and Climate Data

In recent years, climate change has increased the spatiotemporal variability of precipitation, leading to a rise in both the frequency and severity of drought events. Consequently, the importance of water resource management and drought response has been steadily growing. Drought is not merely a result of precipitation deficiency; rather, it is a complex phenomenon that propagates from meteorological drought to agricultural, hydrological, and eventually socioeconomic drought. However, previous studies on drought propagation have largely focused on individual stages, which limits the comprehensive understanding of compound drought propagation under climate crisis conditions. In this study, regions that have experienced severe historical drought damage were selected to analyze the characteristics of drought propagation. By integrating meteorological and climate data with regional characteristic data, this study aims to develop a methodology for evaluating compound drought propagation. First, drought indices were calculated for each stage: the Standardized Precipitation Index (SPI) for meteorological drought, the Standardized Precipitation Evapotranspiration Index (SPEI) for agricultural drought, and the Streamflow Drought Index (SDI) for hydrological drought. Next, various spatiotemporal correlation analyses were conducted to investigate both spatial and temporal propagation characteristics of drought indices. Transition matrices for each drought stage were then constructed and analyzed using network analysis techniques. Furthermore, based on the identified propagation characteristics, transition probability analysis between drought stages was performed. This enabled the estimation of when meteorological drought conditions are likely to propagate into agricultural and hydrological drought stages. The proposed drought propagation-based analytical methodology quantitatively reflects both time lags and transition characteristics of drought events. It is expected to serve as a foundational tool for the development of drought early warning systems and to support decision-making in water resource management.