滑坡影响的范围主要根据滑坡滑动距离来确定,现阶段的研究空间仍较大。以甘肃黑方台地区所有滑坡的滑动距离作为整体样本,根据研究区实际情况,将滑坡群分为Ⅰ段、Ⅱ段、Ⅲ段、Ⅳ段、Ⅴ段和Ⅵ段;基于核密度估计模型与Value-at-Risk(VaR)模型对研究区滑坡影响范围展开分析。结果表明:MISE窗宽值为68.723 8的核密度估计能较好地表述整体样本的概率分布规律;VaR模型计算得到了符合滑坡分段实情的滑坡风险滑动距离值(DR);结合分区实际情况,可在Ⅰ段、Ⅱ段、Ⅲ段和Ⅵ段的滑坡底部DR处修建简易牢固拦挡措施,以及基于Ⅳ段和Ⅴ段的黄土滑坡样本研究滑坡滑带部位含水量与滑动距离的关系。该模型具有良好的理论基础及应用前景,能在该领域发挥一定积极作用。
Abstract
Hazard mapping is a prevailing part of spatial analysis of landslides. Previous researches use runout distances to map the hazard ranges. In this paper, we present an improved methodology by using the dataset that contains all runout distances of landslide locations in Heifangtai area. According to the runout distances, the landslide locations are categorized into six groups. For each group, the kernel density estimation and Value-at-Risk (VaR) measurement are conducted for statistical modeling. Statistical results indicate a kernel density with MISE=68.7238 fit the probability distributions of runout distances best. Furthermore, for each group, hazards are mapped according to the runout distances at different levels of risks (DR). According to the experimental results, a preventive construction measure is proposed in the location computed as DR for Groups I, II, III and VI. Meanwhile, the correlation between moisture content and runout distance in Group IV and V is derived by further numerical analysis.
关键词
滑坡影响范围 /
核密度估计 /
VaR模型 /
滑坡风险滑动距离 /
风险度量滑动距离
Key words
hazard mapping /
Kernel density estimation /
Value-at-Risk /
runout distance of landslide /
Value-at-Risk measurements of runout distances
{{custom_sec.title}}
{{custom_sec.title}}
{{custom_sec.content}}
参考文献
[1] 姜 波,柴 波,方 恒,等. 万州孙家荆竹屋基滑坡滑动模型研究[J]. raybet体育在线
院报,2015,32(8):103-109.[2] VOON K C, INGHAM J M. Experimental In-plane Shear Strength Investigation of Reinforced Concrete Masonry Walls[J]. Journal of Structural Engineering, 2006, 132(3):400-408.[3] LI X Z,KONG J M. Runout Distance Estimation of Landslides Triggered by“5·12”Wenchuan Earthquake [J]. Journal of Sichuan University (Engineering Science), 2010, 42(5): 243-249.[4] 李骅锦, 许 强, 何雨森, 等. 甘肃黑方台滑坡滑距参数的BP 神经网络模型[J]. 水文地质工程地质, 2016,43(4): 141-152.[5] LEGROS F. The Mobility of Long-runout Landslides[J]. Engineering Geology,2002, 63(3): 301-331.[6] 李骅锦,许 强,王思澄,等. WA-BT-ELM耦合模型在黄土滑坡位移预测中的应用[J]. raybet体育在线
院报,2017,34(9):63-69.[7] SCHEIDEGGER A E. On the Prediction of the Reach and Velocity of Catastrophic Landslides[J]. Rock Mechanics, 1973, 5(4): 231-236.[8] WANG J D,HUI Y H. Landslides in Crows induced by Irrigated Water in Loess Area[J]. Scientia Geographical Sinica, 2002, 22 (3): 305-310.[9] WANG J D,ZHANG Z Y. A Study on the Mechanism of High-speed Loess Landslide induced by Earthquake[J]. Chinese Journal of Geotechnical Engineering,1999,21(6): 670 -674.[10]LIAO X P,JIN B. Related Research of Landslide Volume and Sliding Distance of High-speed Landslide [J]. Subgrade Engineering, 1994, (6): 9-12.[11]HUNGR O,MCDOUGALL S. Two Numerical Models for Landslide Dynamic Analysis[J]. Computers ＆ Geosciences, 2009, 35(5): 978-992.[12]KOKUSHO T, ISHIZAWA T, NISHIDA K. Travel Distance of Failed Slopes during 2004 Chuetsu Earthquake and its Evaluation in Terms of Energy [J]. Soil Dynamics and Earthquake Engineering, 2009, 29(7):1159-1169.[13]王 宇,李 晓,王声星,等. 滑坡渐进破坏运动过程的颗粒流仿真模拟[J]. raybet体育在线
院报,2012,29(12):46-52.[14]BUDETTA P, DE RISO R. The Mobility of Some Debris Flows in Pyroclastic Deposits of the Northwestern Campanian Region (Southern Italy)[J]. Bulletin of Engineering Geology & Environment,2004,63(4):293-302.[15]LI H, FENG W, XU Q, et al. A Revised Formula to Compute Shear Strength of Unsaturated Soils[J]. International Journal of Georesources and Environment, 2017, 3(1): 47-55.[16]ZHANG D X,WANG G H. Study of the 1920 Haiyuan Earthquake-induced Landslides in Loess (China) [J]. Engineering Geology, 2007, 94(1/2): 76-88.[17]OKURA Y, KITAHARA H, SAMMORI T, et al. The Effects of Rockfall Volume on Runout Distance [J]. Engineering Geology, 2000, 58(2): 109-124.[18]吴振翔, 叶五一, 缪柏其. 基于外汇投资组合的风险分析[J]. 中国管理科学, 2004, 12(4):1-5.[19]USAOLA J. Probabilistic Load Flow in Systems with Wind Generation [J].IET Generation, Transmission & Distribution, 2009, 3(12):1031-1041.[20]MORALES J M,PEREZ-RUIZ J. Point Estimate Schemes to Solve the Probabilistic Power Flow [J]. IEEE Transactions on Power Systems, 2007, 22(4): 1594-1601.[21]LEITE da SILVA A M,ARIENTI V L. Probabilistic Load Flow Considering Dependence between Input Nodal Powers [J]. IEEE Transactions on Power Apparatus and Systems, 1984, 103(6):1524-1530.[22]MOAZAMI S, GOLIAN S, KAVIANPOUR M R, et al. Uncertainty Analysis of Bias from Satellite Rainfall Estimates Using Copula Method [J]. Atmospheric Research, 2014, 137(2): 145-166.[23]WU X Z. Development of Fragility Functions for Slope Instability Analysis [J]. Landslides, 2015, 12(1):165-175.[24]管 燕. 基于非参数核密度估计方法的环境责任保险保费厘定研究[D]. 青岛: 中国海洋大学, 2013.[25]刘开云, 刘保国, 徐 冲. 基于遗传-组合核函数高斯过程回归算法的边坡非线性变形时序分析智能模型[J]. 岩石力学与工程学报, 2009, 28(10): 2128-2134.[26]HE Y, KUSIAK A, OUYANG T, et al. Data-driven Modeling of Truck Engine Exhaust Valve Failures: A Case Study[J]. Journal of Mechanical Science and Technology, 2017, 31(6): 2747-2757.[27]许 强, 彭大雷, 亓 星, 等. 2015年4·29甘肃黑方台党川2#滑坡基本特征与成因机理研究[J].工程地质学报, 2016, 24(2): 167-180.[28]李远耀,殷坤龙,柴 波, 等. 三峡库区滑带土抗剪强度参数的统计规律研究[J].岩土力学, 2008, 29(5): 1419-1425.
基金
国家重点基础研究发展计划项目(2014CB744703);国家杰出青年科学基金项目(41225011)
PDF(1706 KB)
