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      XING Fucheng, LI Ning, XIANG Han, et al. Research progress of debris flow activity evaluation methods[J]. Express Water Resources & Hydropower Information, 2025, 46(12): 66-73, 80. DOI: 10.15974/j.cnki.slsdkb.2025.12.011
      Citation: XING Fucheng, LI Ning, XIANG Han, et al. Research progress of debris flow activity evaluation methods[J]. Express Water Resources & Hydropower Information, 2025, 46(12): 66-73, 80. DOI: 10.15974/j.cnki.slsdkb.2025.12.011

      Research progress of debris flow activity evaluation methods

      • As one of the most common mountain hazards, debris flows have long been a focal point and challenge in disaster prevention and mitigation efforts in mountainous regions.Accurately and rapidly assessing debris flow activity is crucial for effective hazard management.This study systematically reviews the research progress on debris flow activity assessment, with a focus on the evolution of evaluation methods, identification of existing research gaps, and exploration of future research directions.By employing a literature review approach, we analyzed the development of research methodologies, compared different evaluation criteria, examined dominant assessment models, and discussed variations in assessment across different spatial scales.The review can categorize assessment methods into three main types: quantitative analysis based on rainfall and topography, semi-quantitative analysis based on historical disaster records, and quantitative methods integrating GIS, remote sensing (RS), and numerical simulations.Additionally, it contrasted single-channel and regional-scale assessments.The findings indicate that debris flow activity assessment has evolved from qualitative descriptions to quantitative analysis, with recent studies predominantly relying on statistical models, multi-factor analyses, and computational techniques.However, distinctions among susceptibility, sensitivity, activity, and hazard remain ambiguous, and a standardized assessment framework has yet to be established.Future research should refine assessment indicators, develop more precise dynamic evaluation models, integrate susceptibility and sensitivity analyses into a comprehensive activity assessment system, and incorporate big data, machine learning, and digital twin technologies to enhance assessment accuracy and timeliness, ultimately providing more robust scientific support for debris flow disaster prevention and mitigation.
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