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区域降雨型滑坡预报预警方法研究
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摘要
区域降雨型滑坡是我国主要的地质灾害类型之一,具有群发性、同时性、暴发性和成灾大的特点。长期以来,国内对单体滑坡的预报预警较为关注,而对区域性的预警研究进展较缓慢。在全国积极开展地质灾害气象预报预警工作初期,开展降雨型滑坡预报预警研究,探索形成一套科学的、完整的、实用的预警预报方法,具有十分重要的实际意义。 论文选取素有“雨城”之称的四川省雅安市雨城区为研究区,以丰富的实际资料为基础,深入研究了影响滑坡发生的各种因素,全面分析了滑坡时空分布与降雨的关系,探索了确定降雨诱发区域滑坡的降雨临界值的方法,初步建立了区域降雨型滑坡预报预警体系。通过2004 年在研究区的反演模拟,整套方法接近实际,实用、可行,能够为主动减灾防灾提供科学依据。主要研究内容、方法和结论如下:
    (1)论文针对基于 GIS 的统计分析模型在进行滑坡危险性评价时存在的不同数据层的合并以及数据层叠加权重确定等问题,提出了 CF 逻辑回归模型,即滑坡发生确定性系数(CF)与逻辑回归模型(Binary Logistic)相融合,并借助 SPSS 统计分析软件,很好地解决了滑坡评价中因子的选择、异质数据合并和各数据层叠加的权重问题,提高了滑坡危险性区划的精度和效率。
    采用滑坡确定性系数的方法,开展研究区滑坡影响因子的敏感性分析;通过确定性系数的合并检验,确定研究区影响滑坡的关键因子;建立逻辑统计分析预测模型,采用均质网格划分,实现了滑坡危险性的空间定量评价。
    研究表明,雨城区软弱相间岩组、东和西南朝向的 10°~40°的顺向坡、海拔 600~1000 m 的高程范围内的林地区最易于滑坡发生。影响滑坡危险性的关键因子为坡向、高程、岩组、斜坡类型和坡度。根据计算的单元格滑坡发生概率值,将雨城区滑坡危险性划分为 5个等级,即极不稳定、不稳定、潜在不稳定、基本稳定和稳定。
    利用雨城区新滑坡点进行检验。结果显示,极不稳定区和不稳定区中包含了 86%的校验滑坡,说明评价结果与实际发生的滑坡情况基本吻合。
    (2)首次将逻辑回归模型引入区域降雨型滑坡预警预报,并据此建立了降雨诱发区域滑坡临界值表达式及降雨对滑坡的影响概率。
    利用逻辑回归系数,定量研究了诱发区域滑坡降雨临界值的表达雨量。通过滑坡点与降雨量及降雨过程之间的统计分析,建立了同时考虑降雨强度和降雨过程的降雨临界值表达式。
    研究表明,雨城区滑坡发生与 4 天的降雨量有关,即当日降雨量(1 日降雨量)、前一天降雨量(2 日降雨量)、前两天降雨量(3 日降雨量)、前三天降雨量(4 日降雨量)。其中 1 日降雨量对滑坡发生的影响最大。降雨临界值表达雨量确定为滑坡当日降雨量和前三日的累计降雨量。雨城区降雨诱发区域滑坡临界值表达式: R_1 = -0.62R_(L3) + 84.4
Regional precipitation-induced landslide is one of the major geologic hazards in our country, which features large areas of damage, simultaneity, sudden breakout and serious consequences. For quite some time, close attentions have been paid to the forecast and early warning of single landslide in our country while the research of regional early warning proceeds quite slowly. It is essential to carry out the research into the forecast and early warning of precipitation-induced landslide and establish a scientific, complete and practical early warning and forecasting approach at the beginning of the national campaign launched for the geologic hazard weather forecast and early warning.
    Yucheng District of Ya'an City, the so-called rain city of Sichuan province is chosen as the research target in the paper. Based on the rich practical data, the paper makes the in-depth research into various factors affecting the occurrence of landslide, conducts an overall analysis on the relationship between the time-space distribution of landslide and rainfall, and explores the method to determine the threshold of precipitation inducing the regional landslide. It also preliminarily establishes the precipitation-induced landslide forecast and early warning system. Based on the inverse modeling carried out in the research area in 2004, all approaches are practical, feasible and can provide scientific basis for the active disaster mitigation and prevention. The key researches, approaches and conclusions are as follows:
     (1)The paper proposes the CF logic regression model to address the consolidation of different data layers during the landslide critical evaluation through GIS-based statistical analysis model and the determination of data layer superposition weight. By combining the certainty coefficient (CF) and logic regression model (Binary Logistic) and with the assistance of SPSS statistical analysis software, the factor selection, heterogeneity data consolidation and the data layer superposition weight are solved and the precision and efficiency of landslide susceptivity zoning are improved.
    Sensitivity analysis on the landslide impact factor in the research area is carried out by using the landslide certainty coefficient; Key factors affecting the landslide in the research area are determined by the consolidated inspection on the certainty coefficient. Logic statistical analysis predictive model is established, and through homogeneous meshing, the space quantitative evaluation on landslide susceptivity is realized.
    Research shows that landslide is mostly likely to happen at the petrofabric with interlacing softness in Yucheng district, dip slope of 10°~40°facing the east and southwest as well as the forest with elevation between 600~1000 m. Key factors affecting the landslide risk include the aspect of slope, elevation, petrofabric, type of slope and inclination. Based on the calculated cell landslide probability of occurrence, the landslide risk in Yucheng district is divided into 5 grades, namely extremely unstable, unstable, latent unstable, basically stable and stable.
    Inspection is carried out on the new landslide sites of Yucheng district. The result shows that the extremely unstable area and unstable area contain 86% of the verified landslide, indicating that the evaluation result is in reasonable agreement with the actual landslide.
    (2) Logic regression model is introduced into the precipitation-induced landslide early warning and forecast, based on which, the precipitation-induced regional landslide threshold expression and the probability of rainfall's impact on the landslide is established.
    
    Quantitative investigation has been conducted on the expressed rainfall precipitation for the rainfall threshold inducing the regional landslide based on the logical regression coefficient. Expression considering both the rainfall intensity and rainfall threshold during the rainfall is established. Research indicates that the occurrence of landslide in Yucheng district is relevant to the rainfall during the 4 days, i.e.
引文
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