ANALYSIS AND DEVELOPMENT OF GEO-HAZARDS MONITORING IN THREE GORGES RESERVOIR AREA
-
摘要: 本文结合三峡库区地质灾害监测预警建设历程、地质灾害监测分析现状及面临的问题,从地质灾害监测分析概念和内涵、发展趋势等方面进行了探讨,获得了以下认识:(1)探讨了地质灾害监测分析的内涵,提出了地质灾害监测分析的定义,即围绕着监测目的、监测内容和监测方法,对地质灾害监测数据及相关成果资料开展综合性分析的工作,针对预警预报、防控决策、施工安全、工程效果等不同监测目的,总结了地质灾害监测分析的主要内容;(2)面对多源、异构、实时、海量的地质灾害监测及相关数据,发展地质灾害智能化监测分析系统,实现地质灾害监测数据、分析技术方法、应用服务以及监测分析工作流程化等方面有效集成,是破解监测分析困境和问题的关键。Abstract: This paper is based on the geological hazard monitoring, the early warning work, the monitoring data analysis and the information system construction examples of geological hazards in Three Gorges Reservoir area. It focuses on the concept and connotation of geological hazard monitoring data analysis, and the development trend of geological hazard monitoring data analysis. The main findings are as follows. (1)The definition of geological hazard monitoring data analysis is put forward. It is the comprehensive analysis of geological hazard monitoring data and related achievements and data according to the purposes, contents and methods of geological hazard monitoring. (2)In the face of multi-source, heterogeneous, real-time, massive geological hazard monitoring data, the development of intelligent geological hazard monitoring data analysis system is the key to solve the problem. The system can integrate the geological hazards monitoring big data, the various analytical techniques, methods and application service systems as well as the workflow of monitoring data analysis.
-
表 1 三峡库区大石板滑坡监测预警综合指标体系
Table 1. Comprehensive index system for monitoring and early warning of large slate landslides in Three Gorges Reservoir Area
一级指标 二级指标 四级预警指标 等速变形阶段 加速变形初期 加速变形中期 临滑阶段 变形监测 位移速率 v≤10 mm·d-1 10<v≤50 mm·d-1 50<v≤150 mm·d-1 v>150 mm·d-1 切线角 αi≤45° 45° <αi≤80° 80° <αi≤85° αi>85° 位移时间曲线为倾斜直线,切线角相对恒定 位移时间曲线弯曲向上抬升,切线角缓慢增大 位移时间曲线持续上弯增长,切线角持续增大 位移时间曲线快速增长,趋于直立,切线角骤然陡立 位移矢量 各监测点位移矢量方向不一致 各监测点位移矢量方向逐渐一致指向主滑方向,位移量值一般是后部大前部小、中部大、两侧小 不同部位监测点位移矢量方向基本统一,指向主滑方向,位移量值差别逐渐缩小 不同部位监测点位移矢量方向和量值均趋于一致 裂缝分期配套 后缘裂缝 断续延伸、初具雏形 基本连通、开始加大加深 已经连通、出现下错台坎 迅速拉张甚或闭合 侧缘裂缝 裂缝分布于中后部,并逐渐从向前缘扩展、延伸 两侧裂缝逐渐向坡体中前部扩展延伸 两侧裂缝基本贯通 裂缝完全贯通、擦痕明显 前缘剪出口 肉眼察觉不到明显变形 前缘开始隆起、鼓胀 前缘隆起部位出现纵向张裂缝和横向鼓胀裂缝 前缘隆起加剧,出现局部坍塌不断。临空面开始剪出 关键影响因子 降雨 日降雨量≤120 mm,一次降雨过程累积降雨量≤160 mm 120<日降雨量≤160 mm,160 mm<一次降雨过程累积降雨量≤200 mm 160<日降雨量≤220 mm,200<一次降雨过程累积降雨量≤320 mm 日降雨量>220 mm·d-1,一次降雨过程累积降雨量>320 mm 库水 库水升降速率≤1.2 m·d-1 1.2 m·d-1<库水升降速率≤2 m·d-1 2 m·d-1<库水升降速率≤4 m·d-1 库水升降速率>4 m·d-1 表 2 三峡库区滑坡灾害变形特征及监测优化建议
Table 2. The deformation characteristics and monitoring optimization suggestions of landslide disaster in Three Gorges reservoir area
序号 变形程度 多年监测的年变形量 稳定性状态 监测优化建议 1 不变形或微变形 ≤20 mm 稳定-基本稳定 以群测群防替代专业监测:尽量减少监测点数量和监测频次;甚至可降为群测群防,适当加强极端条件下的地质巡查 2 缓慢变形 (20,50]mm 基本稳定 适当弱化专业监测,加强群测群防:可以降低监测频次,根据需要可适当减少监测点数量(对于综合立体监测点);在可以分析出变形主导因素的条件下,重点进行对主导因素不利条件下的监测。加强极端条件下的地质巡查和群测群防监测 3 较明显变形 (50,100]mm 基本稳定-欠稳定 优化监测网络,强化群测群防:分析变形监测点是否布设合理、能否满足监测预警需求,优化专业监测网点布设和监测方案,重点监测诱发主导因素及变化,同时强化影响因素极端条件下的群测群防巡查 4 明显变形 >100 mm 欠稳定-不稳定 监测关键要素和重点部位,加强监测分析与群测群防:优化专业监测网点布设和监测方案,分析变形监测点是否布设合理,重点捕捉主导因素变化和监测关键变形部位,必要时增加监测点甚至监测方法;强化监测数据分析与变形趋势预测工作,密切关注诱发因素的变化情况,加强宏观地质巡查 表 3 人工监测和自动化监测的特征对比
Table 3. Comparison of characteristics between manual monitoring and automated monitoring
监测方式 人工监测阶段 自动化监测阶段 监测主要工作 以野外数据采集为主要工作量 以室内监测分析为主要工作量 监测分析方式 人工现场采集,室内分析 数据自动采集传输,系统后台分析 监测分析时效 监测分析工作明显滞后 监测数据可实时处理分析 监测分析方法 单体地质灾害监测数据分析 地质灾害大数据综合分析 监测分析工具 人工分析为主,借助通用软件 专业软件系统,实现分析技术方法集成 监测分析过程 碎片化,需不同软件 流程化,同一系统完成 监测分析结果 定性分析,经验判断为主 定量分析,推理科学化,结果精细化 分析的规范性 因监测单位技术人员组成而差异 监测分析工作规范化、统一化 监测人员组成 地质类专业+测绘类专业为主 地质类专业+信息类专业为主 -
Duan G H, Niu R Q, Peng L, et al. 2017. A landslide displacement prediction research based on optimization-parameter ARIMA model under the inducing factors[J]. Geomatics and Information Science of Wuhan University, 42 (4): 531-536. Fan X M, Xu Q, Huang R Q, et al. 2007. Dynamical optimal anchoring design and information construction of Danba landslide[J]. Chinese Journal of Rock Mechanics and Engineering, 26 (S2): 4139-4146. Ge D Q, Dai K R, Guo Z C, et al. 2019. Early identification of serious geological hazards with integrated remote sensing technologies: thoughts and recommendations[J]. Geomatics and Information Science of Wuhan University, 44 (7): 949-956. Guan F J, Shen W Z, Zhang Z F. 2018. Analysis and forecast of geological hazard prevention and control in China[J]. The Chinese Journal of Geological Hazard and Control, 29 (1): 1-2. Han G, Gong W, Wu T, et al. 2014. A stage-divided method for landslide deformation prediction by using rough set[J]. Journal of Jilin University(Earth Science Edition), 44 (3): 925-931. He C Y, Ju N P, Fan Q, et al. 2014. Research on data integration technology of multi-source heterogeneous geo-hazard monitoring[J]. Yangtze River, 45 (13): 94-98. doi: 10.3969/j.issn.1001-4179.2014.13.029 He K Q, Chen W G, Zhang P. 2016. Real-time monitoring of dynamic stability coefficient and displacement criterion of the creep slope[J]. Chinese Journal of Rock Mechanics and Engineering, 35 (7): 1377-1385. He Y Q, Xu Z M, Zhang Y, et al. 2012. Rainfall threshold model of rainfall-induced slope instability and its application[J]. Chinese Journal of Rock Mechanics and Engineering, 31 (7): 1484-1490. doi: 10.3969/j.issn.1000-6915.2012.07.023 Hou J D, Hou S Y, Lü J, et al. 2012. Analysis on economic benefit evaluation of geological disaster monitoring & warning engineering for Three Gorges Reservoir Area[J]. The Chinese Journal of Geological Hazard and Control, 23 (2): 64-69. doi: 10.3969/j.issn.1003-8035.2012.02.014 Huang J, Ju N P. 2012. Evaluation approach of countermeasure efficiency for landslide hazards[J]. Journal of Engineering Geology, 20 (2): 189-194. doi: 10.3969/j.issn.1004-9665.2012.02.006 Huang R Q. 2004. On time predication of landslide[J]. Scientific and Technological Management of Land and Resources, 21 (6): 15-21. doi: 10.3969/j.issn.1009-4210.2004.06.006 Li C, Zhu J B, Wang B, et al. 2016. Critical deformation velocity of landslides in different deformation phases[J]. Chinese Journal of Rock Mechanics and Engineering, 35 (7): 1407-1414. Li X Z, Xu Q, Liu X L. 2005. A GIS-based comprehensive landslide forecasting information system[J]. Journal of Engineering Geology, 13 (3): 398-403. doi: 10.3969/j.issn.1004-9665.2005.03.020 Liu Q, Yi W. 2019. Prediction of landslide displacement based on induced factors response and BP neural network[J]. Journal of China Three Gorges University(Natural Sciences), 41 (3): 41-45. Liu X H, Wu X C, Luo X G. 2013. Object-oriented geological disaster data model and spati-otemporal process expression[J]. Geomatics and Information Science of Wuhan University, 38 (8): 958-962. Meng X F, Du Z J. 2016. Research on the big data fusion: issues and challenges[J]. Journal of Computer Research and Development, 53 (2): 231-246. Peng L, Niu R Q, Ye R Q, et al. 2012. Prediction of ground water level in landslides based on genetic-support vector machine[J]. Journal of Central South University(Science and Technology), 43 (12): 4788-4795. Research group of Xintan landslide. 1985. Success of observation and forecast of Xintan Earh slide[J]. Rock and Soil Mechanics, 6 (2): 1-3. Tang Y, Wang L J, Ma G C, et al. 2019. Disaster monitoring and application prospect analysis of the Jinsha river landslide based on"Gaofen+"[J]. Geomatics and information Science of Wuhan University, 44 (7): 1082-1092. Tao Z G, Zhang H J, Peng Y Y, et al. 2017. Frame structure and engineering applications of multi-source system cloud service platform for landslide monitoring[J]. Chinese Journal of Rock Mechanics and Engineering, 36 (7): 1649-1658. Tian P, Huo Z T, Yu Z Z, et al. 2018. Operation and effectiveness analysis of geological hazard monitoring and early warning system in Three Gorges Reservoir Area[J]. Geology and Mineral Resources of South China, 34 (4): 354-359. doi: 10.3969/j.issn.1007-3701.2018.04.011 Tian Y P, Zhou H, Wu C L. 2010. Research o fgeological hazard prevention data and decision support system of Three Gorges Reservoir area[J]. Yangtze River, 41 (17): 22-24. Tu M Y. 2016. Method system and architecture of geological disaster emergency services at provincial level——Taking Hubei province as example[D]. Wuhan: China University of Geosciences. Wang H D, Gao Y L, Xue X Q, et al. 2013. Optimal placement of monitoring point at typical landslide[J]. Journal of Jilin University(Earth Science Edition), 43 (3): 856-866. Wang H D, Yao X J, Gao Y L, et al. 2003. The disturbance of the controlling engineering constructiong to the Lianzi cliff dangerous rock body[J]. Acta Geoscientia Sinca, 24 (4): 375-378. Wang M, Yi W. 2015. Geological characteristics and formation mechanism of Shanshucao landslide in Three Gorges Reservoir Area[J]. Journal of China Three Gorges University(Natural Sciences), 37 (5): 44-47. Wang Z F. 2011. Study and application of the key technology on the geo-hazard spatial information sharing platform[D]. Chengdu: Chengdu University of Technology. Xu Q, Dong X J, Li W L. 2019. Intergrated space-air-ground early detection, monitoring and warning system for potential catastrophic geohazards[J]. Geomatics and Information Science of Wuhan University, 44 (7): 957-966. Xu Q, Huang R Q, Li X Z. 2004. Research progress in time forecast and prediction of landslides[J]. Advance in Earth Sciences, 19 (3): 478-483. Xu Q, Zheng G, Li W L, et al. 2018. Study on successive landslide damming events of Jinsha River in Baige Village on Octorber 11 and November 3[J]. Journal of Engineering Geology, 26 (6): 1534-1551. Xu S L, Niu R Q. 2018. Displacement prediction of Baijiabao landslide based on empirical mode decomposition and long short-term memory neural network in Three Gorges area, China[J]. Computers and Geosciences, 111, 87-96. doi: 10.1016/j.cageo.2017.10.013 Xu X H, Shang Y Q, Wang Y C. 2010. Research on comprehensive evaluation decision system for landslide disaster[J]. Rock and Soil Mechanics, 31 (10): 3157-3172. Yi Q L, Wen K, Qin S L, et al. 2018. Analysis on effect of emergency treatment project of Shuping Landslide in Three Gorges Reservoir Area[J]. Water Resources and Hydropower Engineering, 49 (11): 165-172. Yu M L, Ren X X, Zeng Q S, et al. 2016. Discussion and application of data integration method for geological environment data[J]. The Chinese Journal of Geological Hazard and Control, 27 (4): 103-108. Yu Z S, Liang R E, Wang Y J, et al. 2012. WebGIS based landslide hazard meteorological early-warning system of diversification model in Lanzhou city[J]. Journal of Engineering Geology, 20 (4): 556-563. Zhang K X, Niu R Q, Hu Y J, et al. 2017. Landslide displacement prediction based on wavelet transform and external cause[J]. Journal of China University of Mining & Technology, 46 (4): 924-931. Zhang L, Chen Z J, Xia Y Z, et al. 2014. Design and realization of spatial assistant decision support system of emergency response for abrupt geological hazards in Zhejiang province[J]. The Chinese Journal of Geological Hazard and Control, 25 (3): 135-140. Zhang M Z, Yu M L, Wang Y, et al. 2013. Designing and building the national geo-environment monitoring data warehouse[J]. Earth Science-Journal of China University of Geoscience, 38 (3): 1347-1355. Zhu J, Jiang H B, Cai Q E. 2012. Instability analysis, observational design and informative construction of K129 landslide on Xikang Highway, Shaanxi[J]. Journal of Engineering Geology, 20 (3): 433-439. 段功豪, 牛瑞卿, 彭令, 等. 2017. 诱发因素影响下的滑坡参数优化预测模型研究[J]. 武汉大学学报(信息科学版), 42 (4): 531-536. https://www.cnki.com.cn/Article/CJFDTOTAL-WHCH201704016.htm 范宣梅, 许强, 黄润秋, 等. 2007. 丹巴县城后山滑坡锚固动态优化设计和信息化施工[J]. 岩石力学与工程学报, 26(增2): 4139-4146. https://www.cnki.com.cn/Article/CJFDTOTAL-YSLX2007S2080.htm 葛大庆, 戴可人, 郭兆成, 等. 2019. 重大地质灾害隐患早期识别中综合遥感应用的思考与建议[J]. 武汉大学学报(信息科学版), 44 (7): 949-956. https://www.cnki.com.cn/Article/CJFDTOTAL-WHCH201907001.htm 关凤峻, 沈伟志, 张志防. 2018. 全国地质灾害防治分析研究与趋势预测[J]. 中国地质灾害与防治学报, 29 (1): 1-2. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGDH201801001.htm 韩舸, 龚威, 吴婷, 等. 2014. 利用粗糙集的滑坡分阶段位移预测方法——以白家包滑坡为例[J]. 吉林大学学报(地球科学版), 44 (3): 925-931. https://www.cnki.com.cn/Article/CJFDTOTAL-CCDZ201403019.htm 何朝阳, 巨能攀, 范强, 等. 2014. 多源异构地质灾害监测数据集成技术研究[J]. 人民长江, 45 (13): 94-98. https://www.cnki.com.cn/Article/CJFDTOTAL-RIVE201413030.htm 何玉琼, 徐则民, 张勇, 等. 2012. 斜坡失稳的降雨阈值模型及其应用[J]. 岩石力学与工程学报, 31 (7): 1484-1490. https://www.cnki.com.cn/Article/CJFDTOTAL-YSLX201207023.htm 贺可强, 陈为公, 张朋. 2016. 蠕滑型边坡动态稳定性系数实时监测及其位移预警判据研究[J]. 岩石力学与工程学报, 35 (7): 1377-1385. https://www.cnki.com.cn/Article/CJFDTOTAL-YSLX201607008.htm 侯俊东, 侯甦予, 吕军, 等. 2012. 三峡库区地质灾害监测预警工程经济效益评估分析[J]. 中国地质灾害与防治学报, 23 (2): 64-69. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGDH201202015.htm 黄健, 巨能攀. 2012. 滑坡治理工程效果评估方法研究[J]. 工程地质学报, 20 (2): 189-194. http://www.gcdz.org/article/id/11118 黄润秋. 2004. 论滑坡预报[J]. 国土资源科技管理, 21 (6): 15-21. https://www.cnki.com.cn/Article/CJFDTOTAL-DZKG200406005.htm 李聪, 朱杰兵, 汪斌, 等. 2016. 滑坡不同变形阶段演化规律与变形速率预警判据研究[J]. 岩石力学与工程学报, 35 (7): 1407-1414. https://www.cnki.com.cn/Article/CJFDTOTAL-YSLX201607011.htm 李秀珍, 许强, 刘希林. 2005. 基于GIS的滑坡综合预测预报信息系统[J]. 工程地质学报, 13 (3): 398-403. http://www.gcdz.org/article/id/9215 刘晓慧, 吴信才, 罗显刚. 2013. 面向对象的地质灾害数据模型与时空过程表达[J]. 武汉大学学报(信息科学版), 38 (8): 958-962. https://www.cnki.com.cn/Article/CJFDTOTAL-WHCH201308018.htm 柳青, 易武. 2019. 基于诱发因素响应与BP神经网络的滑坡位移预测预报[J]. 三峡大学学报(自然科学版), 41 (3): 41-45. https://www.cnki.com.cn/Article/CJFDTOTAL-WHYC201903009.htm 孟小峰, 杜治娟. 2016. 大数据融合研究: 问题与挑战[J]. 计算机研究与发展, 53 (2): 231-246. https://www.cnki.com.cn/Article/CJFDTOTAL-JFYZ201602002.htm 彭令, 牛瑞卿, 叶润青, 等. 2012. 基于进化支持向量机的滑坡地下水位动态预测[J]. 中南大学学报(自然科学版), 43 (12): 4788-4795. https://www.cnki.com.cn/Article/CJFDTOTAL-ZNGD201212031.htm 唐尧, 王立娟, 马国超, 等. 2019. 基于"高分+"的金沙江滑坡灾情监测与应用前景分析[J]. 武汉大学学报(信息科学版), 44 (7): 1082-1092. https://www.cnki.com.cn/Article/CJFDTOTAL-WHCH201907014.htm 陶志刚, 张海江, 彭岩岩, 等. 2017. 滑坡监测多源系统云服务平台架构及工程应用[J]. 岩石力学与工程学报, 36 (7): 1649-1658. https://www.cnki.com.cn/Article/CJFDTOTAL-YSLX201707009.htm 田盼, 霍志涛, 余祖湛, 等. 2018. 三峡库区地质灾害监测预警体系运行与成效分析[J]. 华南地质与矿产, 34 (4): 354-359. https://www.cnki.com.cn/Article/CJFDTOTAL-HNKC201804013.htm 田宜平, 周浩, 吴冲龙. 2010. 三峡库区地质灾害防治信息与决策支持系统研究[J]. 人民长江, 41 (17): 22-24. https://www.cnki.com.cn/Article/CJFDTOTAL-RIVE201017007.htm 涂美义. 2016. 省级地质灾害应急服务架构及方法体系研究——以湖北省为例[D]. 武汉: 中国地质大学. 汪宙峰. 2011. 地质灾害空间信息共享平台关键技术研究及应用——以汶川地震极震区为例[D]. 成都: 成都理工大学. 王洪德, 高幼龙, 薛星桥, 等. 2013. 典型滑坡监测点优化布置[J]. 吉林大学学报(地球科学版), 43 (3): 856-866. https://www.cnki.com.cn/Article/CJFDTOTAL-CCDZ201303022.htm 王洪德, 姚秀菊, 高幼龙, 等. 2003. 防治工程施工对链子崖危岩体的扰动[J]. 地球学报, 24 (4): 375-378. https://www.cnki.com.cn/Article/CJFDTOTAL-DQXB200304018.htm 王鸣, 易武. 2015. 三峡库区杉树槽滑坡地质特征与成因机制分析[J]. 三峡大学学报(自然科学版), 37 (5): 44-47. https://www.cnki.com.cn/Article/CJFDTOTAL-WHYC201505011.htm 新滩滑坡研究组. 1985. 新滩大滑坡的监测预报取得巨大成功[J]. 岩土力学, 6(2): 1-3. https://www.cnki.com.cn/Article/CJFDTOTAL-YTLX198502000.htm 徐兴华, 尚岳全, 王迎超. 2010. 滑坡灾害综合评判决策系统研究[J]. 岩土力学, 31 (10): 3157-3172. https://www.cnki.com.cn/Article/CJFDTOTAL-YTLX201010022.htm 许强, 董秀军, 李为乐. 2019. 基于天-空-地一体化的重大地质灾害隐患早期识别与监测预警[J]. 武汉大学学报(信息科学版), 44 (7): 957-966. https://www.cnki.com.cn/Article/CJFDTOTAL-WHCH201907002.htm 许强, 黄润秋, 李秀珍. 2004. 滑坡时间预测预报研究进展[J]. 地球科学进展, 19 (3): 478-483. https://www.cnki.com.cn/Article/CJFDTOTAL-DXJZ200403020.htm 许强, 郑光, 李为乐, 等. 2018.2018年10月和11月金沙江白格两次滑坡—堰塞堵江事件分析研究[J]. 工程地质学报, 26 (6): 1534-1551. doi: 10.13544/j.cnki.jeg.2018-406 易庆林, 文凯, 覃世磊, 等. 2018. 三峡库区树坪滑坡应急治理工程效果分析[J]. 水利水电技术, 49 (11): 165-172. https://www.cnki.com.cn/Article/CJFDTOTAL-SJWJ201811023.htm 余志山, 梁润娥, 王延江, 等. 2012. 基于WebGIS的兰州市区滑坡灾害气象多元化模型预警系统研究[J]. 工程地质学报, 20 (4): 556-63. http://www.gcdz.org/article/id/11168 喻孟良, 任晓霞, 曾青石, 等. 2016. 地质环境数据集成方法探讨及实例应用[J]. 中国地质灾害与防治学报, 27 (4): 103-108. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGDH201604018.htm 张凯翔, 牛瑞卿, 胡友健, 等. 2017. 基于小波变换及外因响应的滑坡位移预测[J]. 中国矿业大学学报, 46 (4): 924-931. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGKD201704028.htm 张磊, 陈张建, 夏跃珍, 等. 2014. 浙江省突发性地质灾害应急空间辅助决策支持系统设计与实现[J]. 中国地质灾害与防治学报, 25 (3): 135-140. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGDH201403028.htm 张鸣之, 喻孟良, 王勇, 等. 2013. 国家级地质环境数据仓库的设计与实现[J]. 地球科学——中国地质大学学报, 38 (3): 1347-1355. https://www.cnki.com.cn/Article/CJFDTOTAL-DQKX201306023.htm 祝建, 姜海波, 蔡庆娥. 2012. 西康高速公路K129滑坡失稳分析及治理工程动态设计与信息化施工[J]. 工程地质学报, 20 (3): 433-439. http://www.gcdz.org/article/id/11151 -