The Daily Propagation Characteristics of Short‐Duration and Long‐Duration Drought Process From Meteorology to Agriculture in Guangxi, China

持续时间(音乐) 气候学 中国 环境科学 农业 气象学 地理 地质学 文学类 艺术 考古
作者
Zongheng Li,Yunchuan Yang,Jia‐Zhen Yang,Liping Liao,Li-qing Liang,Changzheng Wei,Meilin He,Chongxun Mo,Xungui Li,Guikai Sun
出处
期刊:International Journal of Climatology [Wiley]
标识
DOI:10.1002/joc.8870
摘要

ABSTRACT Guangxi's widespread Karst region and arable land on low hills and slopes have caused agricultural droughts triggered by meteorological droughts to become frequent over the years. This study evaluates meteorological and agricultural droughts using the daily‐scale standardised weighted average precipitation (SWAP) and soil moisture condition index (SMCI), respectively. The objective identification technique for regional extreme events (OITREE) is applied to capture drought events and analyse their dynamics. Droughts are categorised by duration into short‐duration (SD) events (5–30 days) and long‐duration (LD) events (over 30 days). Based on these methodologies, the research reveals daily‐scale relationships of drought propagation from multiple dimensions. From 1979 to 2015, Guangxi experienced 125 meteorological droughts and 178 agricultural droughts, with 67 pairs successfully matched. Agricultural droughts on average lag meteorological droughts by 10 days. The onset lag time varies across different scenarios: seasonal (7 days), consecutive SD (3.3 days) and alternating SD and LD (6.75 days). Similarly, for daily integrated intensity peaks, the lag times in these three scenarios are 14.72, 10.25 and 14.33 days, respectively. Spatial distributions of drought indices under seasonal and alternating SD and LD droughts showed significant consistency, with mean correlation coefficients of 0.49 and 0.61, respectively. In contrast, consecutive SD droughts exhibited weaker correlations, with a mean coefficient of 0.25. The research further revealed correlations between characteristic factors of meteorological and agricultural droughts under both matched and unmatched scenarios. These findings support understanding the daily spatiotemporal evolution of meteorological–agricultural droughts in Guangxi, enabling dynamic risk prediction and early warning for drought mitigation.
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