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Flood Risk and Community Resilience in Northeast Thailand: A Multi-Temporal Analysis of Population Dynamics and Environmental Indicators for Sustainable Development

Aug 2026 · Sustainability · 0 citations

Abstract

Northeast Thailand’s Chi-Mun River Basin is among Southeast Asia’s most flood-prone regions, experiencing annual monsoon inundation and extreme flood events that threaten community sustainability. Despite substantial investment in flood management infrastructure, community responses to flood hazards vary considerably, with some areas demonstrating adaptive capacity while others exhibit maladaptive development patterns that increase vulnerability. This study assesses community resilience to flood hazards by integrating flood exposure, environmental conditions (Sentinel-2 spectral indices), and population dynamics across 1157 locations in the Upper Chi River Basin, Maha Sarakham Province. A two-stage analytical framework combining K-means clustering and Random Forest classification identified five resilience classes: Slow Recovery (36.3%), Vulnerable Decline (25.8%), Unknown (17.7%), High Resilience (14.2%), and Maladaptive Growth (6.1%). Results reveal that Maladaptive Growth and High Resilience were clearly distinguished by population volatility (254.3 vs. 65.4), population change (+585.8% vs. −18.7%), and elevation (152.7 m vs. 168.1 m). Population trend emerged as the strongest predictor (importance = 0.135), followed by MNDWI (0.114) and elevation (0.113), indicating that demographic dynamics and topographic characteristics are more influential than flood frequency alone in determining resilience class membership. The findings reveal that Maladaptive Growth areas exhibit extreme population growth with high volatility in lower-elevation areas, whereas High Resilience communities maintain environmental quality and demographic stability despite population decline. These findings inform targeted interventions for sustainable flood risk management and contribute to understanding maladaptation in flood-prone regions, supporting the achievement of Sustainable Development Goals 11, 13, and 15.

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