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<p> <?tk 4?>Monitoring drought-flood abrupt alternation (DFAA) using monthly indices presents limitations, particularly in identifying event timing and accounting for precipitation neutralization effects. This study introduces a daily drought-flood abrupt alternation index (DFAI) to overcome these challenges. Using a gridded observational dataset and simulations from five global climate models (GCMs), we analyse the spatiotemporal characteristics and evolution of DFAA events across mainland China. Validation against historical disaster records shows that the daily DFAI detects DFAA events missed by the monthly DFAI; and identifies the Southwest Monsoon Convergence Zone as a high-frequency hotspot, contrasting with the fragmented patterns of the monthly index analyses. Long-term trend analysis reveal significant nationwide increases in DFAA frequency and intensity; under Shared Socioeconomic Pathways (SSP1-2.6, SSP3-7.0, SSP5-8.5), the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3b) projections indicate no overall increase in future DFAA frequency but a consistent intensification, particularly under SSP5-8.5, where mainland China may experience stronger events. The improved index enables higher-resolution DFAA detection and supports enhanced risk assessment and adaptive strategies for managing compound hydrometeorological hazards.</p> Grapical abstract <p></p>

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Evolution and prediction of drought-flood abrupt alternation in mainland China using an improved index

  • 期刊论文

  • 发表日期：

    2025年10月13日

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  • Yiming Tong,
  • Yu Chen,
  • Yanping Qu,
  • Virgílio A. Bento,
  • Hongquan Song,
  • Han Qiu,
  • Wei Shui,
  • Jingyu Zeng,
  • Qianfeng Wang

摘要

Monitoring drought-flood abrupt alternation (DFAA) using monthly indices presents limitations, particularly in identifying event timing and accounting for precipitation neutralization effects. This study introduces a daily drought-flood abrupt alternation index (DFAI) to overcome these challenges. Using a gridded observational dataset and simulations from five global climate models (GCMs), we analyse the spatiotemporal characteristics and evolution of DFAA events across mainland China. Validation against historical disaster records shows that the daily DFAI detects DFAA events missed by the monthly DFAI; and identifies the Southwest Monsoon Convergence Zone as a high-frequency hotspot, contrasting with the fragmented patterns of the monthly index analyses. Long-term trend analysis reveal significant nationwide increases in DFAA frequency and intensity; under Shared Socioeconomic Pathways (SSP1-2.6, SSP3-7.0, SSP5-8.5), the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3b) projections indicate no overall increase in future DFAA frequency but a consistent intensification, particularly under SSP5-8.5, where mainland China may experience stronger events. The improved index enables higher-resolution DFAA detection and supports enhanced risk assessment and adaptive strategies for managing compound hydrometeorological hazards.

Grapical abstract