Exploring two-decadal risk variability of drought-flood abrupt alternation in a high-plateau basin

[Display omitted] •We present a modeling framework for DFAA risk assessment.•The monthly DFAA index was calculated using long-term river flow data.•DFAA events mostly occurred in the form of drought-to-flood (DTF).•DFAA’s intensity, frequency, and risk display great spatio-temporal disparities. The...

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Veröffentlicht in:Ecological indicators 2023-12, Vol.156, p.111106, Article 111106
Hauptverfasser: Liu, Wei, Dong, Feifei, Hu, Bill X., You, Rui, Li, Jincheng, Shao, Guangwen
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Sprache:eng
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Zusammenfassung:[Display omitted] •We present a modeling framework for DFAA risk assessment.•The monthly DFAA index was calculated using long-term river flow data.•DFAA events mostly occurred in the form of drought-to-flood (DTF).•DFAA’s intensity, frequency, and risk display great spatio-temporal disparities. The escalating intensity and frequency of drought-flood abrupt alternation (DFAA) events, intensified by climate change, pose a significant threat to both the eco-environment and human life. Despite their evident impacts, the risk associated with DFAA events has received limited attention. In this study, we present a comprehensive risk assessment model incorporating multifold natural and anthropogenic indicators to analyze the spatiotemporal variations of DFAA risk. Utilizing a DFAA index (DFAAI) based on river flow data from seven monitoring stations spanning 1999 to 2019, we investigate DFAA events in the Dianchi Basin, the largest lake in the Yunnan-Guizhou Plateau, China. Our analysis reveals that 56% of total DFAA events occurred between June and August, with drought-to-flood (DTF) events accounting for 62.5% of DFAA occurrences in the Dianchi Basin. Notably, the intensity and frequency of DFAA events exhibit significant spatial variations across the basin. The hazard, vulnerability, exposure, and disaster defense indices further exhibit substantial spatial discrepancies, with hazard indicators being the most influential, notably the DFAA rate accounting for 72.4% of the overall impact. Spatial correlations in DFAA risk among monitoring stations were found to be low, primarily influenced by variations in meteorological conditions, underlying surface characteristics, and human activities. The findings of this study can offer valuable insights for effective water resource management in an ever-changing environment.
ISSN:1470-160X
1872-7034
DOI:10.1016/j.ecolind.2023.111106