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<p>Landslide occurrences have intensified due to climate-driven extreme weather and improper land-use pressures, necessitating robust hazard mapping strategies. This study presents a probabilistic landslide hazard assessment for the Bolaman Micro Basin, a region in northern Türkiye prone to rainfall-induced landslides. A total of 231 shallow landslides were inventoried and correlated with daily rainfall data (2010–2022) obtained from the Fatsa meteorological station. The study first identified critical rainfall thresholds triggering landslides, followed by temporal probability estimation using Poisson distribution. A 2-day cumulative rainfall of 86&#xa0;mm was found to be the most influential threshold, corresponding to a recurrence interval of two years. The temporal exceedance probabilities for 1, 2, 5, 10, and 25-year periods were calculated and integrated with spatial landslide susceptibility derived via Random Forest classification. The resulting hazard maps clearly indicate increased landslide hazard over extended return periods. This integrated methodology provides a reliable framework for assessing landslide hazards in data-scarce regions. The findings offer actionable insights for urban planners, disaster risk managers, and policymakers in enhancing regional resilience against mass movements.</p>

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Probabilistic modelling of rainfall triggered landslide hazards using Poisson distribution in the Bolaman Micro Basin (Türkiye)

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年12月18日

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  • Zehra Kaya Topacli,
  • Candan Gokceoglu

摘要

Landslide occurrences have intensified due to climate-driven extreme weather and improper land-use pressures, necessitating robust hazard mapping strategies. This study presents a probabilistic landslide hazard assessment for the Bolaman Micro Basin, a region in northern Türkiye prone to rainfall-induced landslides. A total of 231 shallow landslides were inventoried and correlated with daily rainfall data (2010–2022) obtained from the Fatsa meteorological station. The study first identified critical rainfall thresholds triggering landslides, followed by temporal probability estimation using Poisson distribution. A 2-day cumulative rainfall of 86 mm was found to be the most influential threshold, corresponding to a recurrence interval of two years. The temporal exceedance probabilities for 1, 2, 5, 10, and 25-year periods were calculated and integrated with spatial landslide susceptibility derived via Random Forest classification. The resulting hazard maps clearly indicate increased landslide hazard over extended return periods. This integrated methodology provides a reliable framework for assessing landslide hazards in data-scarce regions. The findings offer actionable insights for urban planners, disaster risk managers, and policymakers in enhancing regional resilience against mass movements.