基于水文-气象阈值的区域降雨型滑坡预测研究

目前区域降雨型滑坡预测主要依赖降雨阈值开展,然而从降雨诱发滑坡机理可知,除降雨入渗导致的土壤含水量变化外,降雨入渗前的土壤含水量也是影响边坡失稳的重要因素,无法考虑降雨入渗前的土壤湿度情况,被认为是降雨阈值在滑坡预测中表现差的主要原因。针对这一问题,本文以四川省都江堰地区作为试验区域,提出考虑前期土壤湿度的区域降雨型滑坡预测思路,通过统计分析历史滑坡数据,构建了基于前期土壤湿度和近期降雨情况的水文-气象阈值模型,其中前期土壤湿度情况由改进的前期有效降雨指数刻画,近期降雨情况由最近的累积降雨量表示。试验结果表明:在试验区域的降雨型滑坡预测中,水文-气象阈值模型表现出较好的命中率和较低的误报率。本文构建的水文-气象阈值模型,可同时考虑前期土壤湿度和近期降雨对滑坡发生的影响,模型所需数据少、所用方法简单易操作且预测性能较优,适合在区域降雨型滑坡预测中推广应用。

Study on prediction of regional rainfall-induced landslides based on hydro-meteorological threshold

The prediction of regional rainfall-induced landslides mainly relies on the rainfall threshold. However, given the physical mechanism of rainfall-induced landslides, in addition to the changes in soil water content caused by rainfall infiltration, the soil water content before rainfall infiltration is also an important factor affecting slope instability. The inability to consider the soil moisture condition before rainfall infiltration is regarded as the main reason for the poor performance of the rainfall threshold in landslide predictions. Aiming at this problem, this study takes Dujiangyan district of Sichuan province as the experimental area, and proposes the idea of predicting regional rainfall-induced landslides by considering the antecedent soil moisture condition. Through statistical analysis of historical landslide records, we constructed a hydro-meteorological threshold based on the antecedent soil moisture and recent rainfall conditions, in which the antecedent soil moisture condition is described by the modified antecedent precipitation index, and the recent rainfall condition is characterized by the recent cumulated rainfall. Results show that the hydro-meteorological threshold performs well in terms of hit rate and false alarm rate in predicting rainfall-induced landslides at the experimental area. The constructed hydro-meteorological threshold can simultaneously consider the role of the antecedent soil moisture and recent rainfall in the occurrence of landslides, and has advantages of requiring fewer data, easy operation due to the simple method, and good prediction performances, which is suitable for application and promotion in the prediction of regional rainfall-induced landslides.