降雨及库水位共同作用下滑坡阶跃位移临界面的识别方法

doi:10.13722/j.cnki.jrme.2022.1311

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摘要针对目前“阶跃式”滑坡位移预测模型的不足，提出一种表征“阶跃式”滑坡特征的降雨及库水位作用下的阶跃位移预测模型。该模型首先采用西原蠕变模型拟合滑坡趋势项位移，经过自适应遗传算法下的滑动阶跃识别方法与移动平均算法下的阶跃位移提取方法得到阶跃位移；然后针对阶跃位移，分析选取降雨及库水位影响因子，经过粒子群优化算法(PSO)得到最优相关性下的降雨及库水位综合指标；最后对数据集进行LOF(local outlier factor)算法剔除离群值处理与ADASYN(adaptive synthetic)算法过采样处理，经过蝗虫优化算法优化支持向量机(GOA-SVM)进行二分类后实现对滑坡阶跃位移的分类与预测。以“阶跃式”滑坡—— 白水河滑坡为例，选取监测点ZG118从2003年6月～2009年8月典型阶跃时间段的数据进行研究。预测结果：数据集总体预测准确率为72.73%，阶跃位移数据集预测准确率为100%，未发生阶跃位移数据集预测准确率为66.67%，预测效果良好。当降雨与库水位作用成为“阶跃式”滑坡阶跃发生的主导因素时，该模型为此类滑坡位移预测提供了新的思路与探索。

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	冯谕1
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关键词 ：边坡工程, &ldquo, 阶跃式&rdquo, 滑坡, 阶跃位移预测, 滑动阶跃识别方法, 阶跃位移提取方法, 综合指标, 支持向量机分类

Abstract：To overcome the deficiency of the current “step-type” landslide displacement prediction model，a new model is proposed to characterize the features of “step-type” landslides under the combined effects of rainfall and reservoir water level. The model first uses the Nishihara creep model to fit the trend term displacement of the landslide，and then obtains the step displacement through the sliding step identification method based on the adaptive Genetic Algorithm and the step displacement extraction method based on the Moving Average Algorithm. After the step displacement is extracted，the influencing factors of rainfall and reservoir water level are analyzed and selected，and the optimal comprehensive index of rainfall and reservoir water level under the best correlation is obtained utilizing the Particle Swarm Optimization(PSO) algorithm. Finally，the LOF(Local Outlier Factor) Algorithm is utilized to remove outliers of the data set，and the ADASYN(Adaptive Synthetic) Algorithm is utilized for oversampling. After binary classification by the Grasshopper Optimization Algorithm optimized Support Vector Machine(GOA-SVM)，the classification and prediction of landslide step displacement are realized. Taking the Baishuihe landslide as an example of “step-type” landslides，the data of monitoring point ZG118 in the typical step period from June 2003 to August 2009 are selected for research. The prediction results show that the overall prediction accuracy of the data set is 72.73%，the prediction accuracy of the step displacement data set is 100%，and the prediction accuracy of the data set without step displacement is 66.67%，It indicates good prediction performance. When rainfall and reservoir water level become the dominant factors of the occurrence of step-type landslide steps，this model provides new ideas and exploration for the prediction of such landslides.

Key words： slope engineering;“step-type&rdquo landslide;step displacement prediction;sliding step identification method;step displacement extraction method;comprehensive index;support vector machine classification

引用本文:

冯谕1，涂鹏飞1，2，曾怀恩1，2，3. 降雨及库水位共同作用下滑坡阶跃位移临界面的识别方法[J]. 岩石力学与工程学报, 2023, 42(11): 2788-2805.
FENG Yu1，TU Pengfei1，2，ZENG Huaien1，2，3. A method for identifying critical displacement threshold of landslide step under combined effects of rainfall and reservoir water level. , 2023, 42(11): 2788-2805.

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http://rockmech.whrsm.ac.cn/CN/10.13722/j.cnki.jrme.2022.1311 或 http://rockmech.whrsm.ac.cn/CN/Y2023/V42/I11/2788

[1]	许强，黄润秋，李秀珍. 滑坡时间预测预报研究进展[J].地球科学进展，2004，19(3)：478-483.(XU Qiang，HUANG Runqiu，LI Xiuzhen. Research progress on the landslide time prediction[J]. Advance in Earth Sciences，2004，19(3)：478-483.(in Chinese))
[3]	曹博，汪帅，宋丹青，等. 基于蚁群算法优化极限学习机模型的滑坡位移预测[J]. 水资源与水工程学报，2022，33(2)：172-178.(CAO Bo，WANG Shuai，SONG Danqing，et al. Landslide displacement prediction based on extreme learning machine optimized by ant colony algorithm[J]. Journal of Water Resources and Water Engineering，2022，33(2)：172-178.(in Chinese))
[5]	黄发明，殷坤龙，杨背背，等. 基于时间序列分解和多变量混沌模型的滑坡阶跃式位移预测[J]. 地球科学，2018，43(3)：887-898.(HUANG Faming，YIN Kunlong，YANG Beibei，et al. Step-like displacement prediction of landslide based on time series decomposition and multivariate chaotic model[J]. Earth Science，2018，43(3)：887-898.(in Chinese))
[7]	邓冬梅，梁烨，王亮清，等. 基于集合经验模态分解与支持向量机回归的位移预测方法：以三峡库区滑坡为例[J]. 岩土力学，2017，38(12)：3 660-3 669.(DENG Dongmei，LIANG Ye，WANG Liangqing，et al. Displacement prediction method based on ensemble empirical mode decomposion and support vector machine regression—A case of landslide in Three Gorges Reservoir area[J]. Rock and Soil Mechanics，2017，38(12)：3 660-3 669.(in Chinese))
[11]	李麟玮，吴益平，苗发盛. 基于不同Bootstrap方法和KELM-BPNN模型的滑坡位移区间预测[J]. 岩石力学与工程学报，2019，38(5)：912-926.(LI Linwei，WU Yiping，MIAO Fasheng. Landslide displacement interval prediction based on different Bootstrap methods and KELM-BPNN model[J]. Chinese Journal of Rock Mechanics and Engineering，2019，38(5)：912-926.(in Chinese))
[9]	高彩云. 基于新型智能算法ELM的滑坡变形位移预测[J]. 人民长江，2017，48(7)：46-49.(GAO Caiyun. Displacement prediction of landslide based on new intelligent algorithm of ELM[J]. Yangtze River，2017，48(7)：46-49.(in Chinese))
[13]	张俊，殷坤龙，王佳佳，等. 基于时间序列与PSO-SVR耦合模型的白水河滑坡位移预测研究[J]. 岩石力学与工程学报，2015，34(2)：382-391.(ZHANG Jun，YIN Kunlong，WANG Jiajia，et al. Displacement prediction of baishuihe landslide base on time series and PSO-SVR model[J]. Chinese Journal of Rock Mechanics and Engineering，2015，34(2)：382-391.(in Chinese))
[19]	MIAO F，WU Y，XIE Y，et al. Prediction of landslide displacement with step-like behavior based on multialgorithm optimization and a support vector regression model[J]. Landslides，2017，(3)：1-14.
[21]	张倬元，王仕天，王兰生. 工程地质分析原理[M]. 4版. 北京：地质出版社，2016：276-277.(ZHANG Zhuoyuan，WANG Shitian，WANG Lansheng. Principles of engineering geology analysis[M]. 4th ed. Beijing：Geology Press，2016：276-277.(in Chinese))
[47]	SAREMI S，MIRJALILI S，LEWIS A. Grasshopper optimization algorithm：theory and application[J]. Advances in Engineering Software，2017，105：30-47.
[6]	XU S L，NIU R Q. Displacement prediction of Baijiabao landslide based on empircal mode decomposition and long short-term memory neural network in Three Gorges area，China[J]. Computers and Geosciences，2018，111：87-96.
[16]	姜桥. 水-岩作用下砂岩卸荷损伤机制及演化模型研究[博士学位论文][D]. 宜昌：三峡大学，2020.(JIANG Qiao. Study on damage evolution model and deterioration mechanism of unloading damage sandstone under water-rock interaction[Ph. D. Thesis][D]. Yichang：China Three Gorges University，2020.(in Chinese))
[23]	董秀军，许强，唐川，等. 滑坡位移-时间曲线特征的物理模拟试验研究[J]. 工程地质学报，2015，23(3)：401-407.(DONG Xiujun，XU Qiang，TANG Chuan，et al. Characteristics of landslide displacement-time curve by physical simulation experiment[J]. Journal of Engineering Geology，2015，23(3)：401-407.(in Chinese))
[26]	齐亚静，姜清辉，王志俭，等. 改进西原模型的三维蠕变本构方程及其参数辨识[J]. 岩石力学与工程学报，2012，31(2)：347-355.(QI Yajing，JIANG Qinghui，WANG Zhijian，et al. 3D creep constitutive equation of modified nishihara model and its parameters identification[J]. Chinese Journal of Rock Mechanics and Engineering，2012，31(2)：347-355.(in Chinese))
[29]	隋学深，杨忠海. 沪深两市股指时间序列突变点贝叶斯检测模型研究[J]. 商业研究，2007，(2)：41-43.(SUI Xueshen，YANG Zhonghai. The research on bayesian measure model of change points in Shanghai and Shenzhen stock index time series[J]. Commercial Research，2007，(2)：41-43.(in Chinese))
[31]	王晓峰，石东伟，王慧敏，等. 数值分析[M]. 开封：河南大学出版社，2019：82-94.(WANG Xiaofeng，SHI Dongwei，WANG Huimin，et al. Numerical analysis[M]. Kaifeng：Henan University Press，2019：82-94.(in Chinese))
[46]	VAPNIK V. The nature of statistical learning theory[M]. New York，USA：Springer-Verlag，2000：138-167.
[8]	GUO Z Z，CHEN L X，GUI L，et al. Landslide displacement prediction based on variational mode decomposition and WA-GWO-BP model[J]. Landslides，2020，17(3)：567-583.
[18]	李麟玮. 三峡库区库岸堆积层滑坡位移预测与稳定性评价方法研究[博士学位论文][D]. 武汉：中国地质大学，2021.(LI Linwei. Displacement prediction and stability evaluation methods of reservoir colluvial landslides in Three Gorges Reservoir area[Ph. D. Thesis][D]. Wuhan：China University of Geosciences，2021.(in Chinese))
[28]	邵骏，杜涛，郭卫，等. 金沙江上游河段水温变化规律及其影响因素探讨[J]. 长江科学院院报，2022，39(8)：17-22.(SHAO Jun，DU Tao，GUO Wei，et al. Water temperature variation and its influencing factors in the upper Jinsha river[J]. Journal of Yangize River Scientific Research Institute，2022，39(8)：17-22.(in Chinese))
[33]	李德毅，杜鹢. 不确定性人工智能[M]. 2版. 北京：国防工业出版社，2014：44-56.(LI Deyi，DU Yi. Uncertainty in artificial intelligence[M]. 2nd ed. Beijing：National Defense Industry Press，2014：44-56.(in Chinese))
[36]	陈洪凯，魏来，谭玲. 降雨型滑坡经验性降雨阈值研究综述[J].重庆交通大学学报：自然科学版，2012，31(5)：990-996.(CHEN Hongkai，WEI Lai，TAN Ling. Review of research on empirical rainfall threshold of rainfall-induced landslide[J]. Journal of Chongqing Jiaotong University：Natural Science，2012，31(5)：990-996.(in Chinese))
[38]	吴益平，张秋霞，唐辉明，等. 基于有效降雨强度的滑坡灾害危险性预警[J]. 地球科学，2014，39(7)：889-895.(WU Yiping，ZHANG Qiuxia，TANG Huiming，et al. Landslide hazard warning based on effective rainfall intensity[J]. Journal of Earth Science，2014，39(7)：889-895.(in Chinese))
[39]	朱智杰，卢书强，梅军. 基于有效降雨量的滑坡位移-降雨相关性研究[J/OL]. 长江科学院院报，DOI：10.11988/ckyyb.20220908.(ZHU Zhijie，LU Shuqiang，MEI Jun. Study on landslide displacement-rainfall correlation based on effective rainfall[J/OL]. Journal of Yangtze River Scientific Research Institute，DOI：10.11988/ckyyb.20220908.(in Chinese))
[41]	高华喜，殷坤龙. 降雨与滑坡灾害相关性分析及预警预报阀值之探讨[J]. 岩土力学，2007，28(5)：1 055-1 060.(GAO Huaxi，YIN Kunlong. Discuss on the correlations between landslides and rainfall and threshold for landslide early-warning and prediction[J]. Rock and Soil Mechanics，2007，28(5)：1 055-1 060.(in Chinese))
[4]	周超，殷坤龙，曹颖，等. 基于诱发因素响应与支持向量机的阶跃式滑坡位移预测[J]. 岩石力学与工程学报，2015，34(增2)：4 132-4 139.(ZHOU Chao，YIN Kunlong，CAO Ying，et al. Displacement prediction of step-like landslide based on the response of inducing factors and support vector machine[J]. Chinese Journal of Rock Mechanics and Engineering，2015，34(Supp.2)：4 132-4 139.(in Chinese))
[14]	李麟玮，吴益平，苗发盛，等. 基于变分模态分解与GWO-MIC-SVR模型的滑坡位移预测研究[J]. 岩石力学与工程学报，2018，37(6)：1 395-1 406.(LI Linwei，WU Yiping，MIAO Fasheng，et al. Displacement prediction of landslides based on variational mode decomposition and GWO-MIC-SVR model[J]. Chinese Journal of Rock Mechanics and Engineering，2018，37(6)：1 395-1 406.(in Chinese))
[24]	陈浩，杨春和，任伟中. 蠕动滑坡变形机制的理论分析与模型试验研究[J]. 岩石力学与工程学报，2008，27(增2)：3 705-3 711. (CHEN Hao，YANG Chunhe，REN Weizhong. Theoretical analysis and model test study on deformation mechanism of creep landslide[J]. Chinese Journal of Rock Mechanics and Engineering，2008，27(Supp.2)：3 705-3 711.(in Chinese))
[34]	冯谕，曾怀恩，涂鹏飞. 一种滑动检测算法下的滑坡位移时序分解方法[J/OL]. 长江科学院院报，DOI：10.11988/ckyyb.20221323.(FENG Yu，ZENG Huaien，TU Pengfei. A time series decomposition method of landslide displacement based on sliding detection algorithm[J/OL]. Journal of Yangtze River Scientific Research Institute，DOI：10.11988/ckyyb.20220908.(in Chinese))
[43]	谭文侃，叶义成，胡南燕，等. LOF与改进SMOTE算法组合的强烈岩爆预测[J]. 岩石力学与工程学报，2021，40(6)：1 186-1 194. (TAN Wenkan，YE Yicheng，HU Nanyan，et al. Severe rock burst prediction based on the combination of LOF and improved SMOTE algorithm[J]. Chinese Journal of Rock Mechanics and Engineering，2021，40(6)：1 186-1 194.(in Chinese))
[44]	HE H，YANG B，GARCIA E A，et al. ADASYN：Adaptive synthetic sampling approach for imbalanced learning[C]// Neural Networks，2008. IJCNN. [S. l.]：[s. n.]，2008：1 322-1 328.
[2]	许强，汤明高，徐开祥，等. 滑坡时空演化规律及预警预报研究[J]. 岩石力学与工程学报，2008，27(6)：1 104-1 112.(XU Qiang，TANG Minggao，XU Kaixiang，et al. Research on space-time evolution laws and early warning-prediction of landslides[J]. Chinese Journal of Rock Mechanics and Engineering，2008，27(6)：1 104-1 112.(in Chinese))
[12]	王朝阳，李丽敏，温宗周，等. 基于时间序列和CNN-LSTM的滑坡位移动态预测[J]. 国外电子测量技术，2022，41(3)：1-8.(WANG Chaoyang，LI Limin，WEN Zongzhou，et al. Dynamic prediction of landslide displacement based on time series and CNN-LSTM[J]. Foreign Eletronic Measurement Technology，2022，41(3)：1-8.(in Chinese))
[22]	XU T，XU Q，TANG C A，et al. 2013. The evolution of rock failure with discontinuities due to shear creep[J]. Acta Geotechnica，2013，8(6)：567-581.
[32]	唐秋生，张笑语. 基于云遗传算法的信号交叉口相序相位优化[J].交通科技与经济，2021，23(1)：19-25.(TANG Qiusheng，ZHANG Xiaoyu. Optimization of signal sequence phase sequence based on cloud genetic algorithm[J]. Technology and Economy in Areas of Communications，2021，23(1)：19-25.(in Chinese))
[42]	ABUZAID A H. Detection of outlier in univariate circular data by means of the outlier local factor(LOF)[J]. Statistics in Transition New Series，2020，21(3)：39-51.
[48]	林世发，王欣，秦斌. 基于蝗虫算法的城轨超级电容储能系统能量管理参数优化[J]. 新型工业化，2022，12(3)：82-86.(LIN Shifa，WANG Xin，QIN Bin. Optimization of energy management parameters of urban rail super capacitor energy storage system based on locust algorithm[J]. The Journal of New Industrialization，2022，12(3)：82-86.(in Chinese))
[10]	杨背背，殷坤龙，杜娟. 基于时间序列与长短时记忆网络的滑坡位移动态预测模型[J]. 岩石力学与工程学报，2018，37(10)：2 334-2 343.(YANG Beibei，YIN Kunlong，DU Juan. A model for predicting landslide displacement based on time series and long and short term memory neural network[J]. Chinese Journal of Rock Mechanics and Engineering，2018，37(10)：2 334-2 343.(in Chinese))
[15]	檀梦皎，殷坤龙，郭子正，等. 基于CEEMDAN理论和PSO-ELM模型的滑坡位移预测[J]. 地质科技情报，2019，38(6)：165-175.(TAN Mengjiao，YIN Kunlong，GUO Zizheng，et al. Landslide Displacement prediction based on CEEMDAN method and particle swarm optimized-extreme learning PSO-ELM model[J]. Geological Science and Technology Information，2019，38(6)：165-175.(in Chinese))
[17]	薛阳，吴益平，苗发盛，等. 库水升降条件下考虑饱和渗透系数空间变异性的白水河滑坡渗流变形分析[J]. 岩土力学，2020，41(5)：1 709-1 720.(XUE Yang，WU Yiping，MIAO Fasheng，et al. Seepage and deformation analysis of Baishuihe landslide considering spatial variability of saturated hydraulic conductivity under reservoir water level fluctuation[J]. Rock and Soil Mechanics，2020，41(5)：1 709-1 720.(in Chinese))
[20]	陈曦. 基于新的滑坡时序分解和时滞LSTM的滑坡位移预测研究[C]// 第十三届中国卫星导航年会论文集——S01卫星导航行业应用. [S. l.]：[s. n.]，2022：186-191.(XI Chen. Research on landslide displacement prediction based on new landslide time series decomposition and time-lag LSTM[C]// Selected Papers of the 13th China Annual Conference on Satellite Navigation-Applications of S01 Satellite Navigation Industry. [S. l.]：[s. n.]，2022：186-191.(in Chinese))
[25]	何云明，吴德伦. 岩质边坡蠕变模型及其蠕变机制研究[C]// 第八次全国岩石力学与工程学术大会论文集. [S. l.]：[s. n.]，2004：723-728.(HE Yunming，WU Delun. Study on the creep model and creep mechanism of rock slope[C]// Proceedings of the Eight National Congress of Rock Mechanics and Engineering. [S. l.]：[s. n.]，2004：723-728.(in Chinese))
[27]	欧阳卫，王筱，周维博. 1956-2016年沣河径流量变化特征分析[J]. 水资源与水工程学报，2021，32(3)：118-123.(OUYANG Wei，WANG Xiao，ZHOU Weibo. Variation characteristics of Fenghe River runoff from 1956-2016[J]. Journal of Water Resources and Water Engineering，2021，32(3)：118-123. (in Chinese))
[30]	张世强. 曲线回归的拟合优度指标的探讨[J]. 中国卫生统计，2002，(1)：9-11.(ZHANG Shiqiang. Approach on the fitting optimization index of curve regression[J]. Chinese Journal of Health Statistics，2002，(1)：9-11.(in Chinese))
[35]	肖捷夫. 库水涨落和降雨条件下藕塘滑坡变形演化机制及其预测模型研究[博士学位论文][D]. 武汉：中国地质大学，2021.(XIAO Jiefu. Deformation evolution mechanism and displacement prediction model of outang landslide under water level fluctuation and rainfall[Ph. D. Thesis][D]. Wuhan：China University of Geosciences，2021.(in Chinese))
[37]	李巍岳，刘春，SCAIONI M，等. 基于滑坡敏感性与降雨强度-历时的中国浅层降雨滑坡时空分析与模拟[J]. 中国科学：地球科学，2017，47(4)：473-484.(LI Weiyue，LIU Chun，SCAIONI M，et al. Spatio-temporal analysis and simulation on shallow rainfall-induced landslides in China using landslide susceptibility dynamics and rainfall ID thresholds[J]. Science China Earth Sciences，2017，47(4)：473-484.(in Chinese))
[40]	EBERHART R，KENNEDY J. A new optimizer using particle swarm theory[C]// Preceedings of the Sixth International Symposium on Micro Machine and Human Science. Nagoya，Japan：IEEE，1995：39-43.
[45]	刘东启. 基于支持向量机的不平衡数据分类算法研究[硕士学位论文][D]. 杭州：浙江大学，2017.(LIU Dongqi. Support vector machine based classification algorithms research for imbalanced data[M. S. Thesis][D]. Hangzhou：Zhejiang University，2017.(in Chinese))