基于贡献率模型的崩塌易发性评价--以广州市白云区为例

Evaluation of Collapse Susceptibility Based on a Contribution Rate Model--A Case Study at Baiyun District,Guangzhou City

[目的]根据地质灾害野外普查空间数据库,分析花岗岩风化残积土发育地区崩塌形成机理和破坏模式,探究不同环境孕灾因子对崩塌发育的贡献率,评估崩塌灾害空间易发性与分布规律,为中国东南沿海地质灾害多发区的灾害防治工作提供科学支持。[方法]在分析广州市白云区花岗岩风化残积土崩塌发育特征的基础上,选取高程、坡度、坡向、地形起伏度、距地表水体距离、降雨量、地层岩性、土地利用类型共8个与崩塌灾害发育密切关联的致灾因子构建崩塌灾害易发性评价指标体系,叠加研究区内404个历史崩塌数据,依据贡献率模型计算统计各指标因子崩塌灾害敏感性和空间分布特征。采用各二级指标因子贡献率的修正样本差确定因子权重。[结果](1)研究区内坡度、高程和地形起伏度对崩塌易发性贡献程度较高,坡向、地层岩性、降雨量在崩塌灾害易发性评价中贡献程度较低。(2)极高易发区主要集中在丘陵西麓,崩塌易发性由山地线范围外层边缘向中心逐级降低。(3)崩塌极高易发区和高易发区崩塌比率占总崩塌比率超过85%,模型易发性评价成功率和预测率分别达到91.3%和92.6%。[结论]斜坡地形地貌因子对崩塌发育影响较显著,基于贡献率的崩塌灾害易发性评价模型能够客观量化指标因子权重,模型预测评价结果精度较高,易发性区划符合实际崩塌发育空间分布特征。

[Objective] The spatial database of geological disaster field survey was conducted to analyze the formation mechanism and failure mode of collapse in the area where granite weathered residual soil was developed, to explore the contribution rate of different environmental disaster factors to collapse development, and to evaluate the spatial susceptibility and distribution law of collapse disaster. [Methods] Based on the analysis of the development characteristics of granite weathered residual soil collapse at Baiyun District, Guangzhou City, eight disaster-causing factors closely related to the development of collapse disaster(including elevation, slope, slope direction, topographic relief, distance to stream, rainfall, stratum lithology, and land use) were selected to construct the evaluation index system of collapse disaster susceptibility, and 404 historical collapses in the study area were superimposed. Using the contribution rate model, the collapse disaster sensitivity and spatial distribution characteristics of each index factor were calculated and counted. The modified sample difference of the factor contribution rate of each secondary index was used to determine the factor weight. [Results](1) The contributions of slope, elevation, and topographic relief to collapse susceptibility in the study area were relatively high, while slope direction, stratum lithology and rainfall had low contributions to the assessments of collapse susceptibility.(2) The extremely high-prone areas were mainly concentrated in the western foothills, and the collapse susceptibility decreased gradually from the outer edge of the mountain ground line to the center.(3) The collapse rates of the extremely high and high prone areas accounted for more than 85% of the total collapse rate. The model susceptibility evaluation success rate and prediction rate reached 91.3% and 92.6% respectively. [Conclusion] Topography and geomorphic factors of slope had significant impacts on collapse development. The collapse disaster susceptibility evaluation model based on contribution rate could objectively quantify the index factor weight, and the prediction results of the model had high accuracy. The susceptibility zoning conformed to the actual spatial distribution characteristics of collapse development.