A Spatiotemporal-Magnitude Integrated Framework for Debris Flow Activity Assessment in the Eastern Himalayan Syntaxis

Abstract

Debris flows pose significant threats to mountainous regions, necessitating accurate activity assessments for effective disaster mitigation and risk management. At a regional scale, debris flow studies have predominantly focused on susceptibility, without adequately addressing frequency and magnitude of these events. However, growing demands for hazard mitigation call for more detailed and comprehensive debris flow activity assessments. This study developed an integrated spatiotemporal debris flow activity assessment framework by combining spatial susceptibility modeling, temporal probability estimation, and potential event magnitude estimation. The assessment results for the Eastern Himalayan Syntaxis successfully identified historically active watersheds, including those impacted by catastrophic debris flows such as the 1953 Guxiang Glacier event. The study area was classified into five activity levels, with 37.8% of watersheds categorized as high or very high activity zones. Quantitative validation further confirmed the method’s reliability: the average debris flow occurrence rate increases markedly from 0.02% in the very low activity zone to 86.9% in the very high zone. Compared to traditional susceptibility models, the proposed framework achieves more accurate assessments by integrating temporal triggers and event magnitude, yielding a 9.4% improvement in area under the receiver operating characteristic curve (AUC). This approach provides a robust tool for land-use planning, infrastructure protection, and disaster risk reduction in debris flow-prone regions, particularly under changing climate conditions.

Keywords

Debris flow activity / Disaster risk reduction / Information entropy / Machine learning / Spatiotemporal probability

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