【摘要】 以沅麻盆地典型区域（麻阳、泸溪、沅陵3县）为研究区，基于2013—2022年地质灾害详查数据库，筛选具有完整降雨记录的滑坡事件作为研究对象。采用逻辑回归方法，对影响滑坡发生的降雨因子（包括滑坡当日及滑坡前4日降雨量、滑坡当日最大小时降雨量）进行了显著性筛选，构建沅麻盆地降雨诱发滑坡的逻辑回归预测模型，并选取典型滑坡事件进行实例检验。结果表明，沅麻盆地降雨型滑坡的发生与滑坡当日及滑坡前4天的降雨量呈显著相关性，滑坡当日及滑坡前4天是沅麻盆地滑坡预警的关键降雨期。由R₀（滑坡当日降雨量）、R₁（滑坡前1日降雨量）、R₂（滑坡前2日降雨量）和R_h（滑坡当日最大小时降雨量）构成的降雨因子组合具有最优的统计显著性。经实例验证，基于该组合构建的逻辑回归模型，判对率达到83%,具有较高的预测精度和实用价值。更多还原

【Abstract】 The typical region of the Yuanma Basin（covering Mayang, Luxi and Yuanling counties） was taken in the research of landslide disaster. Based on the database of detailed survey of geological disasters from 2013 to 2022, landslide events with complete rainfall records were selected for research. Then, significant rainfall factors for landslide, including rainfall on the day of landslide occurrence and during those four days prior to it, and maximum rainfall rate on the occurrence day were selected out by adopting logistic regression analysis, and a logistic regression prediction model for rainfall-induced landslides in the Yuanma Basin was developed and validated by studying representative landslide cases. The research results indicate that the rainfall-induced landslides in the Yuanma Basin is significantly correlated with rainfall on the occurrence day and during those 4 days prior to the occurrence. This confirms that the period including the occurrence day and those 4 days prior to the occurrence is critical for early warning of landslide in this region. A combined rainfall factors, consisting of R₀（daily rainfall on the occurrence day）, R₁（rainfall of 1 day before occurrence）, R₂（rainfall of 2 days before occurrence） and R_h（maximum rainfall rate on the occurrence day）, present optimal significance in statistical analysis. The practical cases have validated that this logistic regression model constructed based on this factor combination has a prediction accuracy of 83%. It is concluded that this model can give a prediction with high precision and is of practical value.更多还原