Study on the rainfall threshold of red strata landslides in Bazhong, Sichuan using Kriging interpolation method
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摘要:
降雨阈值是目前最常用的降雨型滑坡预警判据之一，然而目前经验性降雨阈值主要是针对滑坡的区域性预警，对于该区域内随空间变化的单个滑坡的降雨阈值还缺乏探讨。基于巴中2014—2021年降雨型滑坡历史数据以及小时降雨数据，采用克里金插值法，提取2014—2020年各滑坡灾害的四类致灾短期雨量（1 h、12 h、24 h、72 h）和相应的长期雨量（滑坡发生前7 d），由此分成4类阈值模型进行分析，确定每组模型长期和短期致灾雨量阈值分布情况，并用2021年滑坡灾害数据验证所得的降雨阈值。研究结果显示4类阈值模型的预测准确率分布在40%～65%，表明4类阈值都具有较好的应用前景。同时，预测准确率随短期降雨时长增加而提高，由72 h至7 d致灾雨量数据所计算的降雨阈值预测准确率最高，为62%；而1 h至7 d模型计算的降雨阈值预测准确率最低，为46%。基于模型的最高预测准确率，研究计算得到4类模型的最佳短期与长期致灾雨量的划分比例，从而定量划分了短期降雨致灾滑坡和长期降雨致灾滑坡。研究通过对致灾雨量空间分布的计算，可提取滑坡隐患点位上的降雨阈值，实现了区域一点一阈值的目标，丰富了现有降雨阈值计算模型。
Abstract:The Rainfall thresholds are among the most commonly used criteria for predicting rainfall-induced landslides. However, existing empirical rainfall thresholds mainly focused on regional landslide warnings, lacking consideration for the spatial variability of rainfall thresholds for individual landslides within the region. This study uses historical rainfall-induced landslide data and hourly rainfall data from Bazhong City (2014 – 2021) to employ Kriging interpolation methods. It extracts four types of short-term rainfall (1 hour, 12 hours, 24 hours, 72 hours) and their corresponding long-term rainfall (7 days before the landslide occurrence). In these four threshold models, the distribution of long-term and short-term rainfall thresholds in each group is calculated and then validated using landslide disaster data from 2021. The research results indicate that the prediction accuracy of the four threshold models ranges from 40% to 65%, suggesting good potential for practical application. Additionally, the prediction accuracy improves with the increase in the duration of short-term rainfall. The prediction accuracy for rainfall thresholds calculated from the 72-hour-7-day model is highest, reaching 62%, while the 1-hour-7-day model achieves 46%. Based on the highest prediction accuracy of these models, the study calculates the optimal ratios for short-term and long-term disaster-causing rainfall for four types of models. This leads to a quantitative division between short-term rainfall-induced landslides and long-term rainfall-induced landslides. By calculating the spatial distribution of disaster-causing rainfall, the study extracts rainfall thresholds at potential landslide locations, achieving the goal of one threshold per site in the region and enhancing existing models for calculating rainfall thresholds.
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Key words:
- Kriging interpolation /
- landslide /
- short-term rainfall /
- long-term rainfall /
- rainfall threshold
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