Evaluating the propagation characteristics of meteorological drought to hydrological drought using a three-dimensional method

Abstract

In the context of global warming, extreme drought events have become increasingly frequent, resulting in serious losses to industrial and agricultural production. To address drought risks and mitigate substantial impacts, it is essential to study the changes in drought characteristics under climate change. However, traditional drought identification methods based on grid data are inadequate to capture the developmental characteristics of drought events. Therefore, we need to adopt a three-dimensional (3D) drought identification method to describe the evolution of drought events. We improved the existing 3D drought identification and matching processes and constructed a Drought Characteristic Propagation Index (DCPI), by comparing the drought characteristics between historical and future periods. This allowed us to compare the drought propagation characteristics in the Yellow River Basin across historical and future periods and discuss their robustness. Results indicate that: (1) The improved 3D drought identification method can solve the drought identification continuity problem of 25.3% meteorological drought and 39.8% hydrological drought respectively. (2) The meteorological drought in the SSP370 scenario is most likely to cause hydrological drought based on the multi-model ensemble., In the future, drought will show an intensifying trend. The intensity conversion efficiency of drought in the future will increase by 64.3%, and the area conversion efficiency will increase by 54.2%, which are higher than those in the historical period (3) There are some differences between the results of multi-model set and single model, but both show that drought propagation is enhanced compared with the historical period.