Flash drought characteristics based on three identification methods in the North China Plain, China

环境科学 中国 农业 气候学 自然地理学 降水 地理 气象学 地质学 考古
作者
Qian Zhang,Jianzhu Li,Ting Zhang,Ping Feng
标识
DOI:10.5194/hess-2024-185
摘要

Abstract. Flash drought (FD) is an onset and intensify rapidly type of drought that can harm the terrestrial ecosystem, and cause economic and agricultural losses. The North China Plain (NCP) is an important agricultural region in China where sustainable development is restricted by the frequent droughts and insufficient water resources. Coping with FD requires an understanding of the FD onset and identification in the NCP. Based on root zone soil moisture (RZSM), standardized evaporative stress ratio (SESR) and multiples of mean evaporative stress ratio (MESR), this study identified the FD events in the NCP from 1981 to 2022, revealed the FD characteristics such as frequency, duration, severity and intensity, explored the temporal and spatial trend, determined the FD hotspots, and demonstrated the impact of FD identification thresholds on the FD identification. The frequency distributions of FD events identified by RZSM, SESR, and MESR are all high in the central and northern NCP and low in the southern, whereas the total duration is high in the southern and eastern NCP and low in the northern. As the FD intensity increases, the onset stage lengthens, the recovery stage shortens, the total duration reduces, and the severity declines. The FD affected areas from various FD identification methods exhibit significant and similar seasonal variations, primarily occurring from May to August. Besides, NCP is prone to extreme and exceptional FDs. The NCP has a decreasing tendency of the FD characteristics, and three hotspots with frequent and serious FD events are identified in the northwestern, eastern and southwestern NCP. The FD frequency is also significantly influenced by the thresholds in the identification methods. This study provides insights into the FD characteristics in the NCP, and clarifies its trend and hotspots, which may be valuable for FD understanding and adaptation.
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