The spatiotemporal evolution and propagation characteristics of multiple drought types from a three-dimensional perspective

Climate change will increase drought risk, severity, and economic losses. The spatiotemporal evolution and propagation of droughts could be deeply understood based on three-dimensional perspective. In this study, The Standardized Precipitation Evapotranspiration Index, Standardized Runoff Index, and Standardized Soil Moisture Index was used to describe meteorological, hydrological, and agricultural drought, respectively. We identified drought events by the three-dimensional connectedness recognition method and deeply investigate spatial evolution characteristics of drought patches. Subsequently, we compared recorded and identified drought events, and estimate drought propagation in different climate regions of China with drought propagation rate and correlation analysis. The results indicated that the three-dimensional connectedness recognition method could accurately identify large drought event characteristics (including time and area) by comparing and recording large drought disasters. The meteorological drought events usually had higher area coverage proportion, frequency, intensity, and severity than hydrological and agricultural drought events over different climate regions. The three-dimensional connectedness recognition method could accurately recur the spatiotemporal evolution process of historical typical drought events. Both the correlation coefficient and drought propagation ratio showed that drought propagation from meteorological drought to agricultural was larger degree than from meteorological drought to hydrological in China. Moreover, drought had relatively stronger propagation degree from meteorological to agricultural in climate regions of the warm-temperate humid and sub-humid north China, the subtropical humid central and south China, and the tropic humid south China. The drought propagation ratio could complement the uncertainty in the propagation direction shortcomings of the correlation coefficient. This study would be helpful to understand the formation and evolution of drought and provides a reference for three-dimensional spatial prediction and monitoring of drought.