基于Newmark模型的概率地震滑坡危险性模型参数优化与应用:以鲁甸地震区为例

Optimization of Parameters and Application of Probabilistic Seismic Landslide Hazard Analysis Model Based on Newmark Displacement Model:A Case Study in Ludian Earthquake Area

应用概率地震危险性评价模型进行地震滑坡危险性区划,是解决潜在地震诱发滑坡危险性评价中震源不确定性与诱发滑坡时空不确定性的有效方法.通过理论分析,结合鲁甸地震区的实际情况,对基于力学原理的Newmark滑块位移模型与概率地震滑坡危险性分析方法中的参数的不确定性问题进行了分析,将斜坡岩土体地震作用下的强度衰减效应、地震加速度地形放大效应、断层破碎带效应融合到了斜坡累积位移计算模型中,进行了模型计算参数的优化.改进后的分析模型,更好地反映了高陡斜坡地形与断层破碎带对地震滑坡灾害发育的控制作用,在鲁甸地震区域滑坡应用中,优化模型中的滑坡失稳极高风险区与实际地震滑坡分布表现出了较好的一致性,在超越概率2%的滑坡失稳概率分布中,鲁甸地区包谷垴-小河断裂、鲁甸-昭通断裂带及牛栏江河谷地带地震滑坡高-极高风险区分布面积增幅十分显著.因此,在Newmark滑块位移模型中考虑地震动参数与岩土参数动态响应规律与变量间的定量关系,对于提高区域斜坡稳定性分析的可靠性具有重要意义.

Applying probabilistic seismic hazard evaluation model for seismic landslide hazard zonation is an effective method to handle the uncertainty of seismic source and spatial and temporal uncertainty of seismic-induced landslide evaluation in potential seismic area.Combined with theoretical analysis and actual ground motion parameters of Ludian earthquake and landslide hazards,the uncertainty of earthquake parameters and the geotechnical strength parameters in the proposed Newmark model were optimized and verified.Specifically,the strength attenuation effect of slope rock mass,the topographic amplification effect of seismic acceleration,and the fault zone effect were integrated into the Newmark model to optimize the model parameters.The optimized model shows a better effect of the slope topography and fault zone on the development of earthquake-induced landslide.Meanwhile,the calculation results have a higher agreement with the actual seismic landslide distribution in Ludian earthquake area.In addition,the prediction results show that the probability of seismic landslide will greatly increase in the Baogunao-Xiaohe fault,the Ludian-Zhaotong fault,and the Niulanjiang River valley for 2%probability of exceedance in 50 years.Therefore,it is necessary to take into account the dynamic response laws of earthquake parameters and geotechnical parameters in the Newmark model,which has great effect to improve the reliability of regional slope stability analysis.