Dry-Wet Transition Events in China: Identification, Temporal Dynamics, and Spatial Patterns

XIE Yu-ying; LIU Zhi-yong; LIN Kai-rong

doi:10.11988/ckyyb.20200658

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Journal of Changjiang River Scientific Research Institute ›› 2021, Vol. 38 ›› Issue (9) : 77-85. DOI: 10.11988/ckyyb.20200658

WATER-RELATED DISASTERS

Dry-Wet Transition Events in China: Identification, Temporal Dynamics, and Spatial Patterns

XIE Yu-ying^1,2,3, LIU Zhi-yong^1,2,3, LIN Kai-rong^1,2,3

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Abstract

To identify dry-wet transition events over China and analyze their temporal and spatial distribution characteristics, we present a method to identify dry-wet transition events on monthly scale based on the rainfall anomaly index (RAI). Our findings indicate that the frequency of dry-wet transition events increased from April to August, while declined after August. The spatial patterns of dry-wet transition frequency vary among different months. During April to June, the high-frequency area mainly located in south China, while southwestern, northern, northeastern parts of China experienced more frequent dry-wet transition events during June to September. In general, dry-wet transition events occurred more frequently in southeastern part of China than the northwestern part, while intensity distribution of such events showed an opposite pattern. We further examined the variations of both the frequency and intensity in nine large river basins over different periods. Our results demonstrate that the occurrence of dry to wet events showed an increasing trend in Pearl River Basin, Yellow River Basin, Haihe River Basin, since 2000. However, there was no significant trend in the intensity of transition events. The study would provide a valuable reference for the flood and drought managements in China.

Key words

dry-wet transition / rainfall / rainfall anomaly index (RAI) / temporal and spatial distribution characteristics / basins

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XIE Yu-ying, LIU Zhi-yong, LIN Kai-rong. Dry-Wet Transition Events in China: Identification, Temporal Dynamics, and Spatial Patterns[J]. Journal of Changjiang River Scientific Research Institute. 2021, 38(9): 77-85 https://doi.org/10.11988/ckyyb.20200658

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