Spatial and Temporal Evolution of Drought Events Using High-Resolution SPEI and Dynamic Drought Detection Algorithm

Drought is one of the world's major natural disasters. In order to monitor drought and reduce drought damage through preemptive response, it is important to understand the spatiotemporal evolutionary characteristics of drought. Droughts have a three-dimensional (3-D) space-time structure, typically spanning hundreds of kilometers and lasting months to years. In this study, a high-resolution(5 km) SPEI-HR(Standardized Precipitation Evaporation Index) dataset was used, considering climatic (typical temperate continental climate) and various geographic characteristics (mountainous terrain, lowland basin, desert, grassland, etc.). In addition, all large- and small-scale drought events that evolve spatiotemporally were extracted using the dynamic drought detection technique (DDDT) algorithm. These 3D-drought properties are important information to explain the spatiotemporal evolution of drought and are characterized by drought patches in dynamic drought maps. As a result, most of the trajectories of droughts in Central Asia during the period 1981 to 2018 tended to move laterally to the east and west (ENE, E, ESE, WNW, W, WSW). In addition, droughts in Central Asia are characterized by very strong correlations between indicators of duration, severity, area, and trajectory movement distance. These Central Asian drought characteristics are interpreted as meaning that there is consistency among various drought information in determining the most severe drought event. In addition, the dynamic drought map, which includes all 3D-drought properties, has the advantage of producing high-level drought information (temporal continuity of drought events and dynamic evolution characteristics, etc.) that are not found in general drought maps through various conditional drought monitoring.

Acknowledgements: This work was supported by the National Research Foundation of Korea (No. NRF-2020R1C1C1014636) and Korea Environment Industry & Technology Institute (KEITI) (No.2022003610001) funded by the Korean government (MSIT and MOE).