Research on the early warning threshold for typhoon rainstorm-induced landslides based on rainfall index: A case study of Yongtai County, Fuzhou
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摘要:
我国东南丘陵地区极端降雨频繁，滑坡灾害多发、突发、群发，确定滑坡降雨预警阈值是区域防灾减灾工作的关键。基于前期有效降雨量和激发降雨量构建的经验性统计指标——降雨指数（R′），已被成功应用于日本广岛地区滑坡灾害的预警预报。福建沿海丘陵地区与日本广岛地区的孕灾环境十分相似，因此，以福州市永泰县为研究区，借鉴广岛的经验开展类似的研究具有重要的应用意义。通过统计分析“海葵”“尼伯特”典型台风暴雨型滑坡事件的历史降雨及灾情数据，确定降雨指数（R′）模型的关键参数，开展典型降雨过程和滑坡灾害点反演验证，提出适用于永泰县的降雨预警阈值。结果表明：（1）确定了前期有效降雨量基准值R1=120 mm、激发降雨量基准值r1=135 mm、降雨权重因子a=2.5及有效降雨折减系数α=0.85等R′模型的关键参数值；（2）提出R′=156 mm为永泰县台风暴雨型滑坡降雨预警阈值，该阈值可实现“尼伯特”台风降雨诱发滑坡的完全预警，也能对单点滑坡提前预警，推荐的提前预警时间为30 min。基于降雨指数（R′）模型及其确定的降雨阈值在永泰县台风暴雨型滑坡预警中显示出良好的适用性，该方法可供我国东南沿海类似地区的地质灾害气象预警借鉴。
Abstract:In the southeastern hilly regions of China, extreme rainfall frequently triggers landslide disasters, characterized by their rapid occurrence and clustering. Establishing effective rainfall thresholds for early warning systems is crucial for regional disaster prevention and mitigation. The empirical rainfall index R′, which is based on antecedent effective rainfall and triggering rainfall, has been successfully utilized for early warnings and forecasting of landslide disasters in Hiroshima, Japan. Considering the strong similarities in disaster-prone environments between the coastal-hilly areas of Fujian Province and Hiroshima Prefecture, applying this methodology in Yongtai County, Fuzhou, is of significant practical value. This study involved statistical analysis of historical rainfall and disaster data from typical typhoon-induced rainstorm events, such as the Typhoons Haikui and Nepartak. Key parameters of the R′ model were established, and typical rainfall processes and landslide disaster points were analyzed for inverse verification, to propose a rainfall warning threshold suitable for Yongtai County. The results show that: 1) key parameters for the R′ model are determined, including the baseline values for antecedent rainfall (R1)=120 mm, triggering rainfall (r1)=135 mm, a rainfall weight factor (a)=2.5, and an effective rainfall reduction coefficient (α)=0.85. 2) a rainfall warning threshold of R′=156mm was proposed for typhoon rainstorm-induced landslides in Yongtai County. This threshold has proven effective in fully predicting landslides triggered triggered by Typhoon Nepartak, and it can also provide early warning for isolated landslide events, with a recommended lead time of 30 minutes. The rainfall index R′ model and its established threshold demonstrate excellent applicability for early warnings of typhoon rainstorm-induced landslides in Yongtai County, serving as a valuable reference for meteorological early warnings of geological disasters in similar coastal areas across southeastern China.
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表 1 福州市永泰县与日本广岛县孕灾环境对比
Table 1. Comparison of disaster-prone environments between Yongtai County, Fuzhou and Hiroshima Prefecture, Japan
地区 福州市永泰县 日本广岛县 地质历史 寒武纪到第四纪 前寒武纪到第四纪 构造特征 地处华南构造板块的边缘，构造板块活动相对缓和，地震、火山活动少 地处环太平洋地震带，构造板块活动多而剧烈，地震、火山活动多发 岩石类型 以凝灰岩和玄武岩为主的长英质火山岩与中酸性花岗岩分布广泛，花岗岩在该地区的岩石类型中占主导 以玄武岩、安山岩和流纹岩为主的长英质火山岩与中酸性花岗岩分布广泛，大部分地区都覆盖着严重风化的花岗岩 土体特性 丘陵和低山地区广泛分布红壤，具有较强的风化性，排水性较好，但遇强降雨时易受侵蚀；部分丘陵地带分布黄壤，其水分保持能力强，稳定性较差；河谷地带和沿河区域，冲积土和砂土较为常见，该土粒度较大，渗透性较强，暴雨后易发生水土流失；土层厚度一般在40～90 cm 在低山丘陵地带，尤其是靠近河流、湖泊的地区，常见黏土沉积；在沿海及河流流域，基岩顶部常见有1～2 m厚的砂土和砾石沉积物，其具有较好的排水性，但遇强降雨易发水土流失和滑坡；山区岩石风化层较为发育，风化土层一般较松散 地形地貌 以丘陵和山地为主；西南部山脉连绵起伏，东北部地势相对平缓，县内以中低山区为主；没有海岸线地貌 以丘陵和山地为主；西部和北部山脉纵深，中部有较低丘陵地区，平原带多位于东南部的濑户内海沿岸；海岸地貌错综复杂，地形变化更加剧烈 植被特征 森林植被覆盖率76.8%；境内主要植被为马尾松、杉木、国外松等常绿针叶林，辅以壳斗科、樟科、山茶科、木兰科和杜英科等常绿阔叶树种 森林植被覆盖率73%，境内主要分布为栎树、竹柏等常绿阔叶林；桦树、红枫等落叶阔叶林；以及杉树、松树等针叶林 气候特征 亚热带季风气候，7—9月台风活跃 温带季风气候，7—9月台风活跃 降水特征 降水丰富，年降水量 1400 ～2000 mm，春夏季节雨量集中，台风多伴随短时极端强降雨降水丰富，年降水量 1500 ～2000 mm，夏秋季降水集中，台风暴雨更为频繁且强烈
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表 2 福州市永泰县与日本广岛县历史灾情对比
Table 2. Comparison of historical disaster data between Yongtai County, Fuzhou and Hiroshima Prefecture, Japan
地区 永泰县 广岛县 灾害时间 2016年7月 2023年9月 2014年8月 2018年7月 灾害成因 台风暴雨 台风暴雨 台风暴雨 台风暴雨 灾害形式 滑坡、
泥石流滑坡、
泥石流泥石流、
边坡崩塌泥石流、
边坡坍塌峰值雨强/（mm·h−1） 100 88 126 70
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表 3 有效降雨折减系数与滑坡发生的相关性分析
Table 3. Correlation analysis between the effective rainfall reduction coefficient and landslide occurrence
有效降雨折减系数（α） 0.60 0.65 0.70 0.75 0.80 0.85 0.90 0.95 相关系数（r） 0.6159 0.6065 0.6037 0.5968 0.5888 0.6181 0.5847 0.5562
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