区域地面沉降研究进展与展望

朱琳; 宫辉力; 李小娟; 周超凡; 叶淼; 王海刚; 张可; 韩苗苗

doi:10.16030/j.cnki.issn.1000-3665.202212043

区域地面沉降研究进展与展望

doi: 10.16030/j.cnki.issn.1000-3665.202212043

朱琳^{1, 2, 3, 4, 5,},
宫辉力^{1, 2, 3, 4, 5, ,},
李小娟^{1, 2, 3, 4, 5},
周超凡^{1, 2, 3, 4},
叶淼^{1, 2, 3},
王海刚⁵,
张可^{1, 2, 3},
韩苗苗^{1, 2, 3}

1.
首都师范大学资源环境与旅游学院，北京　100048
2.
水资源安全北京实验室，北京　100048
3.
城市环境过程与数字模拟国家重点实验室培育基地，北京　100048
4.
地面沉降机理与防控教育部重点实验室，北京　100048
5.
河北沧州平原区地下水与地面沉降国家野外科学观测研究站，河北沧州　061000

基金项目: 国家自然科学基金项目（42271082；42271487；42201081）

详细信息

作者简介:
朱琳（1980-），女，博士，教授，主要从事水循环、地质灾害过程模拟和风险评价。E-mail：lin.zhu@cnu.edu.cn

通讯作者:
宫辉力（1956-），男，博士，教授，主要从事地理信息系统和遥感、信息水文地质的教学与交叉研究。E-mail：4039@cnu.edu.cn

中图分类号: 中图分类号: 文献标志码: 文章编号:
计量
- 文章访问数: 23
- HTML全文浏览量: 11
- PDF下载量: 7
- 被引次数: 0
出版历程
- 收稿日期: 2022-12-29
- 录用日期: 2023-07-19
- 修回日期: 2023-06-09

Research progress and prospect of land subsidence

ZHU Lin^{1, 2, 3, 4, 5
,},
GONG Huili^{1, 2, 3, 4, 5
, ,},
LI Xiaojuan^{1, 2, 3, 4, 5},
ZHOU Chaofan^{1, 2, 3, 4},
YE Miao^{1, 2, 3},
WANG Haigang⁵,
ZHANG Ke^{1, 2, 3},
HAN Miaomiao^{1, 2, 3}

1.
College of Resource Environment and Tourism, Capital Normal University, Beijing,　100048, China
2.
Beijing Laboratory of Water Resources Security, Beijing,　100048, China
3.
Laboratory Cultivation Base of Environment Process and Digital Simulation, Beijing,　100048, China
4.
Key Laboratory of Mechanism, Prevention and Mitigation of Land Subsidence, MOE, Beijing,　100048, China
5.
Hebei Cangzhou Groundwater and Land Subsidence National Observation and Research Station, Cangzhou,　061000, China

摘要

摘要: 区域差异性地面沉降已经对城市基础设施、线性轨道交通和地下空间开发利用形成重大威胁，制约着经济和社会的可持续发展。本文围绕区域地表形变信息获取、地面沉降演变机制和演变模拟方面的研究进展进行系统阐述，重点分析了InSAR形变监测和多源形变数据融合的区域地表形变信息获取技术，基于室内土工实验数据和长时序观测数据，利用相关分析、统计分析和机器学习等方法分析地面沉降演变与各影响因素的关系。在此基础上，探讨了地下水流场—土体变形模型、数理统计模型和机器学习模型等地面沉降演变模拟模型的优缺点。发现多源形变数据融合能够提高区域地表形变信息的时空分辨率，地质构造、土体岩性、地下水开采和动静载荷等影响因素的差异性是造成地面沉降差异性演化的机制，地面沉降数学模型的计算效率与可解释性难以兼顾是当前沉降模拟存在的主要问题。据文献检索，当前研究主要关注地下水超量开采引发的地面沉降。本文进而提出未来区域地面沉降研究方向，在气候变化叠加新水情、新数据背景下，充分融合遥感大数据与野外观测站实测小数据集，耦合物理模型和机器学习模型，优化集成InSAR、GeoAI、云平台等技术的最新进展，揭示全球气候变化和人类活动综合作用下的区域地面沉降演变机制，为区域地面沉降防控和城市安全提供技术支撑。
- 地面沉降 /
- InSAR /
- 演化机制 /
- 机器学习 /
- 耦合模型
Abstract: Differential land subsidence has posed the major threat to urban infrastructure, linear rail transit and underground space development and utilization, and also restricted the sustainable development of the economy and society. This paper systematically elaborates on the research progresses on land deformation acquisition, evolution mechanism and simulation of land subsidence, and focuses on the analysis of land deformation acquisition technology based on InSAR monitoring and multi-source deformation data fusion, as well as the correlation analysis, statistical analysis, machine learning and other methods to analyze the relationship between the evolution of land subsidence and various influencing factors based on geotechnical experiment and long time series observation data. On this basis, the advantages and disadvantages of land subsidence evolution simulation models such as groundwater flow field-land deformation model, mathematical statistical model and machine learning model are explored. It is found that multi-source deformation data fusion can improve the spatiotemporal resolution of land deformation. The differences in geological structure, lithology, groundwater exploitation, and dynamic and static loads are the mechanisms that cause the differential evolution of land subsidence. The difficulty in balancing the computational efficiency and interpretability of mathematical models for land subsidence is the main problem in simulation. According to the literature review, the current researches mainly focus on land subsidence caused by groundwater over-exploitation. This paper further proposes the future research directions for land subsidence, under the background of climate change, new hydrological condition and dataset, and based on the fusion of data through remote sensing and field observations, integrating the latest progress of InSAR, GeoAI, cloud platform and other technologies to reveal the evolution mechanism of land subsidence considering the climate change and anthropic activities and provide technical support for regional land subsidence prevention and urban safety.
- land subsidence /
- InSAR /
- evolutionary mechanism /
- machine learning /
- coupling model

HTML全文

参考文献(76)

[1]	薛禹群. 论地下水超采与地面沉降[J]. 地下水,2012,34(6):1 − 5. [XUE Yuqun. Discussion on groundwater overexploitation and ground settlement[J]. Ground Water,2012,34(6):1 − 5. (in Chinese with English abstract) XUE Yuqun. Discussion on groundwater overexploitation and ground settlement[J]. Ground Water, 2012, 34（6）: 1 − 5. （in Chinese with English abstract）
[2]	PENG Mimi,ZHAO Chaoying,ZHANG Qin,et al. Research on spatiotemporal land deformation (2012–2018) over Xi’an,China,with multi-sensor SAR datasets[J]. Remote Sensing,2019,11(6):664. doi: 10.3390/rs11060664
[3]	ZHU Lin,GONG Huili,CHEN Yun,et al. Effects of Water Diversion Project on groundwater system and land subsidence in Beijing,China[J]. Engineering Geology,2020,276:105763. doi: 10.1016/j.enggeo.2020.105763
[4]	YE Shujun,FRANCESCHINI A,ZHANG Yan,et al. A novel approach to model earth fissure caused by extensive aquifer exploitation and its application to the Wuxi case,China[J]. Water Resources Research,2018,54(3):2249 − 2269. doi: 10.1002/2017WR021872
[5]	GUALANDI A,LIU Zhen. Variational Bayesian independent component analysis for InSAR displacement time-series with application to central California,USA[J]. Journal of Geophysical Research:Solid Earth,2021,126(4):e2020JB020845. doi: 10.1029/2020JB020845
[6]	YOUSEFI R,TALEBBEYDOKHTI N. Subsidence monitoring by integration of time series analysis from different SAR images and impact assessment of stress and aquitard thickness on subsidence in Tehran,Iran[J]. Environmental Earth Sciences,2021,80(11):1 − 12.
[7]	HERRERA-GARCÍA G,EZQUERRO P,TOMÁS R,et al. Mapping the global threat of land subsidence[J]. Science,2021,371(6524):34 − 36. doi: 10.1126/science.abb8549
[8]	GALLOWAY D L,HUDNUT K W,INGEBRITSEN S E,et al. Detection of aquifer system compaction and land subsidence using interferometric synthetic aperture radar,Antelope Valley,Mojave Desert,California[J]. Water Resources Research,1998,34(10):2573 − 2585. doi: 10.1029/98WR01285
[9]	宫辉力,张有全,李小娟,等. 基于永久散射体雷达干涉测量技术的北京市地面沉降研究[J]. 自然科学进展,2009,19(11):1261 − 1266. [GONG Huili,ZHANG Youquan,LI Xiaojuan,et al. Study on land subsidence in Beijing based on radar interferometry with permanent scatterers[J]. Progress in Natural Science,2009,19(11):1261 − 1266. (in Chinese) GONG Huili, ZHANG Youquan, LI Xiaojuan, et al. Study on land subsidence in Beijing based on radar interferometry with permanent scatterers[J]. Progress in Natural Science, 2009, 19（11）: 1261 − 1266. （in Chinese）
[10]	卢旺达,韩春明,岳昔娟,等. 基于Sentinel-1A数据的天津地区PS-InSAR地面沉降监测与分析[J]. 遥感技术与应用,2020,35(2):416 − 423. [LU Wangda,HAN Chunming,YUE Xijuan,et al. Land subsidence monitoring in Tianjin with PS-InSAR technique based on sentinel-1 data[J]. Remote Sensing Technology and Application,2020,35(2):416 − 423. (in Chinese with English abstract) LU Wangda, HAN Chunming, YUE Xijuan, et al. Land subsidence monitoring in Tianjin with PS-InSAR technique based on sentinel-1 data[J]. Remote Sensing Technology and Application, 2020, 35（2）: 416 − 423. （in Chinese with English abstract）
[11]	罗小军,黄丁发,刘国祥. 基于永久散射体雷达差分干涉测量的城市地面沉降研究——以上海地面沉降监测为例[J]. 测绘通报,2009(4):4 − 8. [LUO Xiaojun,HUANG Dingfa,LIU Guoxiang. On urban ground subsidence detection based on PS-DInSAR:A case study for Shanghai[J]. Bulletin of Surveying and Mapping,2009(4):4 − 8. (in Chinese) LUO Xiaojun, HUANG Dingfa, LIU Guoxiang. On urban ground subsidence detection based on PS-DInSAR: A case study for Shanghai[J]. Bulletin of Surveying and Mapping, 2009（4）: 4 − 8. （in Chinese）
[12]	周洪月,汪云甲,闫世勇,等. 沧州地区地面沉降现状Sentinel-1A/B时序InSAR监测与分析[J]. 测绘通报,2017(7):89 − 93. [ZHOU Hongyue,WANG Yunjia,YAN Shiyong,et al. Land subsidence monitoring and analyzing of Cangzhou area sentinel-1A/B based time series InSAR[J]. Bulletin of Surveying and Mapping,2017(7):89 − 93. (in Chinese with English abstract) ZHOU Hongyue, WANG Yunjia, YAN Shiyong, et al. Land subsidence monitoring and analyzing of Cangzhou area sentinel-1A/B based time series InSAR[J]. Bulletin of Surveying and Mapping, 2017（7）: 89 − 93. （in Chinese with English abstract）
[13]	彭米米,赵超英,张勤,等. 利用Sentinel-1A数据监测大西安2015—2017年地面沉降[J]. 地球物理学进展,2018,33(6):2264 − 2269. [PENG Mimi,ZHAO Chaoying,ZHANG Qin,et al. Monitoring Xi’an land subsidence during 2015—2017 using Sentinel-1A images[J]. Progress in Geophysics,2018,33(6):2264 − 2269. (in Chinese with English abstract) PENG Mimi, ZHAO Chaoying, ZHANG Qin, et al. Monitoring Xi’an land subsidence during 2015—2017 using Sentinel-1A images[J]. Progress in Geophysics, 2018, 33（6）: 2264 − 2269. （in Chinese with English abstract）
[14]	郑世友,周晔,贺丰收,等. 有重叠区域的SAR图像序列拼接新方法[C]//中国自动化学会智能自动化专业委员会. 2009年中国智能自动化会议论文集(第三分册). 南京,2009:105 − 110. [ZHENG Shiyou,ZHOU Ye,HE Fengshou,et al. A new method for SAR image sequence splicing with overlapping regions[C]//Intelligent Automation Professional Committee of Chinese Association of Automation. 2009 China Intelligent Automation Conference (Volume 3). Nanjing,2009:105 − 110. (in Chinese with English abstract) ZHENG Shiyou, ZHOU Ye, HE Fengshou, et al. A new method for SAR image sequence splicing with overlapping regions[C]//Intelligent Automation Professional Committee of Chinese Association of Automation. 2009 China Intelligent Automation Conference （Volume 3）. Nanjing, 2009: 105 − 110. （in Chinese with English abstract）
[15]	孙权,张华,荆于勤. SAR图像并行拼接方法研究与实现——基于改进完全二叉树模型[J]. 重庆工商大学学报(自然科学版),2015,32(7):75 − 80. [SUN Quan,ZHANG Hua,JING Yuqin. Parallel research and implementation of SAR image mosaic based on optimized complete binary tree model[J]. Journal of Chongqing Technology and Business University (Natural Science Edition),2015,32(7):75 − 80. (in Chinese with English abstract) SUN Quan, ZHANG Hua, JING Yuqin. Parallel research and implementation of SAR image mosaic based on optimized complete binary tree model[J]. Journal of Chongqing Technology and Business University （Natural Science Edition）, 2015, 32（7）: 75 − 80. （in Chinese with English abstract）
[16]	罗湾,张红波,夏欣. 基于SIFT-FFT的大面积多视角SAR图像快速拼接方法[J]. 计算机工程与应用,2017,53(增刊2):340 − 344. [LUO Wan,ZHANG Hongbo,XIA Xin. Large-area multi-view SAR image quick mosaic method based on SIFT-FFT. Computer Engineering and Applications,2017,53(S2):340 − 344. (in Chinese with English abstract) LUO Wan, ZHANG Hongbo, XIA Xin. Large-area multi-view SAR image quick mosaic method based on SIFT-FFT. Computer Engineering and Applications, 2017, 53（S2）: 340 − 344. （in Chinese with English abstract）
[17]	罗三明,单新建,朱文武,等. 多轨PSInSAR监测华北平原地表垂直形变场[J]. 地球物理学报,2014,57(10):3129 − 3139. [LUO Sanming,SHAN Xinjian,ZHU Wenwu,et al. Monitoring vertical ground deformation in the North China Plain using the multitrack PSInSAR technique[J]. Chinese Journal of Geophysics,2014,57(10):3129 − 3139. (in Chinese with English abstract) LUO Sanming, SHAN Xinjian, ZHU Wenwu, et al. Monitoring vertical ground deformation in the North China Plain using the multitrack PSInSAR technique[J]. Chinese Journal of Geophysics, 2014, 57（10）: 3129 − 3139. （in Chinese with English abstract）
[18]	梁媚蓉,王晨沁,毛新华. 基于极坐标格式算法的大斜视条带SAR子孔径拼接成像算法[J]. 南京航空航天大学学报,2016,48(5):649 − 655. [LIANG Meirong,WANG Chenqin,MAO Xinhua. Subaperture mosaic imaging algorithm for highly squinted stripmap SAR based on polar format algorithm[J]. Journal of Nanjing University of Aeronautics & Astronautics,2016,48(5):649 − 655. (in Chinese with English abstract) LIANG Meirong, WANG Chenqin, MAO Xinhua. Subaperture mosaic imaging algorithm for highly squinted stripmap SAR based on polar format algorithm[J]. Journal of Nanjing University of Aeronautics & Astronautics, 2016, 48（5）: 649 − 655. （in Chinese with English abstract）
[19]	胡俊,李志伟,朱建军,等. 融合升降轨SAR干涉相位和幅度信息揭示地表三维形变场的研究[J]. 中国科学:地球科学,2010,40(3):307 − 318. [HU Jun,LI Zhiwei,ZHU Jianjun,et al. Study on revealing the three-dimensional deformation field of the surface by fusing the phase and amplitude information of SAR interference in ascending and descending orbit[J]. Scientia Sinica (Terrae),2010,40(3):307 − 318. (in Chinese) doi: 10.1360/zd2010-40-3-307 HU Jun, LI Zhiwei, ZHU Jianjun, et al. Study on revealing the three-dimensional deformation field of the surface by fusing the phase and amplitude information of SAR interference in ascending and descending orbit[J]. Scientia Sinica （Terrae）, 2010, 40（3）: 307 − 318. （in Chinese） doi: 10.1360/zd2010-40-3-307
[20]	刘国祥,张瑞,李陶,等. 基于多卫星平台永久散射体雷达干涉提取三维地表形变速度场[J]. 地球物理学报,2012,55(8):2598 − 2610. [LIU Guoxiang,ZHANG Rui,LI Tao,et al. Extracting 3D ground deformation velocity field by multi-platform persistent scatterer SAR interferometry[J]. Chinese Journal of Geophysics,2012,55(8):2598 − 2610. (in Chinese with English abstract) LIU Guoxiang, ZHANG Rui, LI Tao, et al. Extracting 3D ground deformation velocity field by multi-platform persistent scatterer SAR interferometry[J]. Chinese Journal of Geophysics, 2012, 55（8）: 2598 − 2610. （in Chinese with English abstract）
[21]	胡俊,李志伟,朱建军,等. 基于BFGS法融合InSAR和GPS技术监测地表三维形变[J]. 地球物理学报,2013,56(1):117 − 126. [HU Jun,LI Zhiwei,ZHU Jianjun,et al. Measuring three-dimensional surface displacements from combined InSAR and GPS data based on BFGS method[J]. Chinese Journal of Geophysics,2013,56(1):117 − 126. (in Chinese with English abstract) HU Jun, LI Zhiwei, ZHU Jianjun, et al. Measuring three-dimensional surface displacements from combined InSAR and GPS data based on BFGS method[J]. Chinese Journal of Geophysics, 2013, 56（1）: 117 − 126. （in Chinese with English abstract）
[22]	和柯,邹进贵. GPS与InSAR形变结果融合分析[J]. 测绘地理信息,2018,43(2):57 − 60. [HE Ke,ZOU Jingui. Fusion analysis of GPS and InSAR deformation results[J]. Journal of Geomatics,2018,43(2):57 − 60. (in Chinese with English abstract) HE Ke, ZOU Jingui. Fusion analysis of GPS and InSAR deformation results[J]. Journal of Geomatics, 2018, 43（2）: 57 − 60. （in Chinese with English abstract）
[23]	麻源源,左小清,麻卫峰,等. 利用数据同化技术实现InSAR和水准数据融合研究[J]. 工程勘察,2019,47(8):49 − 55. [MA Yuanyuan,ZUO Xiaoqing,MA Weifeng,et al. Study on data fusion of InSAR and leveling by using data assimilation technology[J]. Geotechnical Investigation & Surveying,2019,47(8):49 − 55. (in Chinese with English abstract) MA Yuanyuan, ZUO Xiaoqing, MA Weifeng, et al. Study on data fusion of InSAR and leveling by using data assimilation technology[J]. Geotechnical Investigation & Surveying, 2019, 47（8）: 49 − 55. （in Chinese with English abstract）
[24]	李更尔,周元华. InSAR、水准及GPS数据融合处理方法[J]. 测绘通报,2017(9):78 − 82. [LI Genger,ZHOU Yuanhua. Study on fusion methods of InSAR,leveling and GPS data[J]. Bulletin of Surveying and Mapping,2017(9):78 − 82. (in Chinese with English abstract) LI Genger, ZHOU Yuanhua. Study on fusion methods of InSAR, leveling and GPS data[J]. Bulletin of Surveying and Mapping, 2017（9）: 78 − 82. （in Chinese with English abstract）
[25]	GUO Nannan,ZHAN Wei. Influence of different data fusion methods on the accuracy of three-dimensional displacements field[J]. Advances in Space Research,2020,65(6):1580 − 1590. doi: 10.1016/j.asr.2019.12.017
[26]	WEI Yani,FAN Wen,CAO Yanbo. Experimental study on the vertical deformation of aquifer soils under conditions of withdrawing and recharging of groundwater in Tongchuan region,China[J]. Hydrogeology Journal,2017,25(2):297 − 309. doi: 10.1007/s10040-016-1498-4
[27]	薛禹群,张云,叶淑君,等. 我国地面沉降若干问题研究[J]. 高校地质学报,2006,12(2):153 − 160. [XUE Yuqun,ZHANG Yun,YE Shujun,et al. Research on the problems of land subsidence in China[J]. Geological Journal of China Universities,2006,12(2):153 − 160. (in Chinese with English abstract) XUE Yuqun, ZHANG Yun, YE Shujun, et al. Research on the problems of land subsidence in China[J]. Geological Journal of China Universities, 2006, 12（2）: 153 − 160. （in Chinese with English abstract）
[28]	罗跃,叶淑君,吴吉春,等. 上海市地下水位大幅抬升条件下土层变形特征分析[J]. 高校地质学报,2015,21(2):243 − 254. [LUO Yue,YE Shujun,WU Jichun,et al. Characterization of land subsidence during recovery of groundwater levels in Shanghai[J]. Geological Journal of China Universities,2015,21(2):243 − 254. (in Chinese with English abstract) LUO Yue, YE Shujun, WU Jichun, et al. Characterization of land subsidence during recovery of groundwater levels in Shanghai[J]. Geological Journal of China Universities, 2015, 21（2）: 243 − 254. （in Chinese with English abstract）
[29]	ZHANG Youquan,GONG Huili,GU Zhaoqin,et al. Characterization of land subsidence induced by groundwater withdrawals in the plain of Beijing city,China[J]. Hydrogeology Journal,2014,22(2):397 − 409. doi: 10.1007/s10040-013-1069-x
[30]	主灿,张云,何国峰,等. 天津滨海新区抽水引起地面沉降现场试验研究[J]. 水文地质工程地质,2018,45(2):159 − 164. [ZHU Can,ZHANG Yun,HE Guofeng,et al. In-situ tests of land subsidence caused by pumping in the Tianjin Binhai New Area[J]. Hydrogeology & Engineering Geology,2018,45(2):159 − 164. (in Chinese with English abstract) ZHU Can, ZHANG Yun, HE Guofeng, et al. In-situ tests of land subsidence caused by pumping in the Tianjin Binhai New Area[J]. Hydrogeology & Engineering Geology, 2018, 45（2）: 159 − 164. （in Chinese with English abstract）
[31]	张勤,赵超英,丁晓利,等. 利用GPS与InSAR研究西安现今地面沉降与地裂缝时空演化特征[J]. 地球物理学报,2009,52(5):1214 − 1222. [ZHANG Qin,ZHAO Chaoying,DING Xiaoli,et al. Research on recent characteristics of spatio-temporal evolution and mechanism of Xi’an land subsidence and ground fissure by using GPS and InSAR techniques[J]. Chinese Journal of Geophysics,2009,52(5):1214 − 1222. (in Chinese with English abstract) ZHANG Qin, ZHAO Chaoying, DING Xiaoli, et al. Research on recent characteristics of spatio-temporal evolution and mechanism of Xi’an land subsidence and ground fissure by using GPS and InSAR techniques[J]. Chinese Journal of Geophysics, 2009, 52（5）: 1214 − 1222. （in Chinese with English abstract）
[32]	BONÌ R,HERRERA G,MEISINA C,et al. Twenty-year advanced DInSAR analysis of severe land subsidence:The Alto Guadalentín Basin (Spain) case study[J]. Engineering Geology,2015,198:40-52. [LinkOut
[33]	宫辉力. 京津冀地面沉降演化规律及灾变机制研究[R]. 北京:首都师范大学,2015. [GONG Huili. Research on the evolution law and disaster mechanism of land subsidence in Beijing Tianjin Hebei [R]. Beijing:Capital Normal University,2015. (in Chinese) GONG Huili. Research on the evolution law and disaster mechanism of land subsidence in Beijing Tianjin Hebei [R]. Beijing: Capital Normal University, 2015. （in Chinese）
[34]	宫辉力,李小娟,潘云,等. 京津冀地下水消耗与区域地面沉降演化规律[J]. 中国科学基金,2017,31(1):72 − 77. [GONG Huili,LI Xiaojuan,PAN Yun,et al. Groundwater depletion and regional land subsidence of the Beijing-Tianjin-Hebei area[J]. Bulletin of National Natural Science Foundation of China,2017,31(1):72 − 77. (in Chinese with English abstract) GONG Huili, LI Xiaojuan, PAN Yun, et al. Groundwater depletion and regional land subsidence of the Beijing-Tianjin-Hebei area[J]. Bulletin of National Natural Science Foundation of China, 2017, 31（1）: 72 − 77. （in Chinese with English abstract）
[35]	ZHOU Chaofan,GONG Huili,CHEN Beibei,et al. Quantifying the contribution of multiple factors to land subsidence in the Beijing Plain,China with machine learning technology[J]. Geomorphology,2019,335:48 − 61. doi: 10.1016/j.geomorph.2019.03.017
[36]	曹鑫宇,朱琳,宫辉力,等. AM-LSTM网络的北京平原东部地面沉降模拟[J]. 遥感学报,2022,26(7):1302 − 1314. [CAO Xinyu,ZHU Lin,GONG Huili,et al. Land subsidence simulation in the east of Beijing plain based on the AM-LSTM Network[J]. National Remote Sensing Bulletin,2022,26(7):1302 − 1314. (in Chinese with English abstract) doi: 10.11834/jrs.20211297 CAO Xinyu, ZHU Lin, GONG Huili, et al. Land subsidence simulation in the east of Beijing plain based on the AM-LSTM Network[J]. National Remote Sensing Bulletin, 2022, 26（7）: 1302 − 1314. （in Chinese with English abstract） doi: 10.11834/jrs.20211297
[37]	CHEN Beibei,GONG Huili,CHEN Yun,et al. Land subsidence and its relation with groundwater aquifers in Beijing Plain of China[J]. Science of the Total Environment,2020,735:139111. doi: 10.1016/j.scitotenv.2020.139111
[38]	SUN Hanrui,ZHU Lin,GUO Lin,et al. Understanding the different responses from the similarity between displacement and groundwater level time series in Beijing,China[J]. Natural Hazards,2022,111(1):1 − 18. doi: 10.1007/s11069-021-05041-9
[39]	彭建兵. 渭河断裂带的构造演化与地震活动[J]. 地震地质,1992,14(2):113 − 120. [PENG Jianbing. Tectonic evolution and seismicity of Weihe fault zone[J]. Seismology and Geology,1992,14(2):113 − 120. (in Chinese with English abstract) PENG Jianbing. Tectonic evolution and seismicity of Weihe fault zone[J]. Seismology and Geology, 1992, 14（2）: 113 − 120. （in Chinese with English abstract）
[40]	ZHANG Yun,WANG Zhecheng,XUE Yuqun,et al. Mechanisms for earth fissure formation due to groundwater extraction in the Su-Xi-Chang area,China[J]. Bulletin of Engineering Geology and the Environment,2016,75(2):745 − 760. doi: 10.1007/s10064-015-0775-0
[41]	王艺伟,叶淑君,于军,等. 中国“采水型”地裂缝特征和成因分析[J]. 高校地质学报,2016,22(4):741 − 752. [WANG Yiwei,YE Shujun,YU Jun,et al. Features and mechanisms of earth fissures induced groundwater withdrawal in China[J]. Geological Journal of China Universities,2016,22(4):741 − 752. (in Chinese with English abstract) WANG Yiwei, YE Shujun, YU Jun, et al. Features and mechanisms of earth fissures induced groundwater withdrawal in China[J]. Geological Journal of China Universities, 2016, 22（4）: 741 − 752. （in Chinese with English abstract）
[42]	BURBEY T J. The influence of faults in basin-fill deposits on land subsidence,Las Vegas Valley,Nevada,USA[J]. Hydrogeology Journal,2002,10(5):525 − 538. doi: 10.1007/s10040-002-0215-7
[43]	彭建兵. 西安地裂缝灾害[M]. 北京:科学出版社,2012. [PENG Jianbing. Ground fissure disaster in Xi’ an[M]. Beijing:Science Press,2012. (in Chinese with English abstract) PENG Jianbing. Ground fissure disaster in Xi’ an[M]. Beijing: Science Press, 2012. （in Chinese with English abstract）
[44]	李志明,杨旭东,兰剑梅,等. 河北邢台柏乡地裂缝成因分析[J]. 水文地质工程地质,2010,37(2):135 − 138. [LI Zhiming,YANG Xudong,LAN Jianmei,et al. An analysis of earth fissure at Baixiang County,Xingtai City[J]. Hydrogeology & Engineering Geology,2010,37(2):135 − 138. (in Chinese with English abstract) doi: 10.3969/j.issn.1000-3665.2010.02.029 LI Zhiming, YANG Xudong, LAN Jianmei, et al. An analysis of earth fissure at Baixiang County, Xingtai City[J]. Hydrogeology & Engineering Geology, 2010, 37（2）: 135 − 138. （in Chinese with English abstract） doi: 10.3969/j.issn.1000-3665.2010.02.029
[45]	骆祖江,王琰,田小伟,等. 沧州市地下水开采与地面沉降地裂缝模拟预测[J]. 水利学报,2013,44(2):198 − 204. [LUO Zujiang,WANG Yan,TIAN Xiaowei,et al. Simulating and forecasting of groundwater exploitation,land subsidence and ground fissure in Cangzhou City[J]. Journal of Hydraulic Engineering,2013,44(2):198 − 204. (in Chinese with English abstract) doi: 10.3969/j.issn.0559-9350.2013.02.011 LUO Zujiang, WANG Yan, TIAN Xiaowei, et al. Simulating and forecasting of groundwater exploitation, land subsidence and ground fissure in Cangzhou City[J]. Journal of Hydraulic Engineering, 2013, 44（2）: 198 − 204. （in Chinese with English abstract） doi: 10.3969/j.issn.0559-9350.2013.02.011
[46]	伍洲云,余勤,张云. 苏锡常地区地裂缝形成过程[J]. 水文地质工程地质,2003,30(1):67 − 72. [WU Zhouyun,YU Qin,ZHANG Yun. Forming process of earth fissure hazard in the Suzhou-Wuxi-Changzhou area[J]. Hydrogeology & Engineering Geology,2003,30(1):67 − 72. (in Chinese with English abstract) doi: 10.3969/j.issn.1000-3665.2003.01.018 WU Zhouyun, YU Qin, ZHANG Yun. Forming process of earth fissure hazard in the Suzhou-Wuxi-Changzhou area[J]. Hydrogeology & Engineering Geology, 2003, 30（1）: 67 − 72. （in Chinese with English abstract） doi: 10.3969/j.issn.1000-3665.2003.01.018
[47]	于军,王晓梅,苏小四,等. 苏锡常地区地裂缝地质灾害形成机理分析[J]. 吉林大学学报(地球科学版),2004,34(2):236 − 241. [YU Jun,WANG Xiaomei,SU Xiaosi,et al. The mechanism analysis on ground fissure disaster formation in Suzhou-Wuxi-Changzhou area[J]. Journal of Jilin University (Earth Science Edition),2004,34(2):236 − 241. (in Chinese with English abstract) YU Jun, WANG Xiaomei, SU Xiaosi, et al. The mechanism analysis on ground fissure disaster formation in Suzhou-Wuxi-Changzhou area[J]. Journal of Jilin University （Earth Science Edition）, 2004, 34（2）: 236 − 241. （in Chinese with English abstract）
[48]	LYU Mingyuan,KE Yinghai,GUO Lin,et al. Change in regional land subsidence in Beijing after south-to-north water diversion project observed using satellite radar interferometry[J]. GIScience & Remote Sensing,2020,57(1):140 − 156.
[49]	GAMBOLATI G,FREEZE R A. Mathematical simulation of the subsidence of Venice:1[J]. Water Resources Research,1973,9(3):721 − 733 doi: 10.1029/WR009i003p00721
[50]	SHEN Shuilong,XU Yeshuang. Numerical evaluation of land subsidence induced by groundwater pumping in Shanghai[J]. Canadian Geotechnical Journal,2011,48(9):1378 − 1392. doi: 10.1139/t11-049
[51]	LEWIS R W,SCHREFLER B. A fully coupled consolidation model of the subsidence of Venice[J]. Water Resources Research,1978,14(2):223 − 230. doi: 10.1029/WR014i002p00223
[52]	HOFFMANN J,GALLOWAY D L,ZEBKER H A. Inverse modeling of interbed storage parameters using land subsidence observations,Antelope Valley,California[J]. Water Resources Research,2003,39(2):1031.
[53]	TEATINI P,FERRONATO M,GAMBOLATI G,et al. Groundwater pumping and land subsidence in the Emilia-Romagna coastland,Italy:modeling the past occurrence and the future trend[J]. Water Resources Research,2006,42(1):W01406.
[54]	MAHMOUDPOUR M,KHAMEHCHIYAN M,NIKUDEL M R,et al. Numerical simulation and prediction of regional land subsidence caused by groundwater exploitation in the southwest plain of Tehran,Iran[J]. Engineering Geology,2016,201:6 − 28. doi: 10.1016/j.enggeo.2015.12.004
[55]	骆祖江,李朗,姚天强,等. 松散承压含水层地区深基坑降水三维渗流与地面沉降耦合模型[J]. 岩土工程学报,2006,28(11):1947 − 1951. [LUO Zujiang,LI Lang,YAO Tianqiang,et al. Coupling model of three dimensional seepage and land-subsidence for dewatering of deep foundation pit in loose confined aquifers[J]. Chinese Journal of Geotechnical Engineering,2006,28(11):1947 − 1951. (in Chinese with English abstract) doi: 10.3321/j.issn:1000-4548.2006.11.006 LUO Zujiang, LI Lang, YAO Tianqiang, et al. Coupling model of three dimensional seepage and land-subsidence for dewatering of deep foundation pit in loose confined aquifers[J]. Chinese Journal of Geotechnical Engineering, 2006, 28（11）: 1947 − 1951. （in Chinese with English abstract） doi: 10.3321/j.issn:1000-4548.2006.11.006
[56]	薛禹群,吴吉春,张云,等. 长江三角洲(南部)区域地面沉降模拟研究[J]. 中国科学(D辑:地球科学),2008,38(4):477 − 492. [XUE Yuqun,WU Jichun,ZHANG Yun,et al. Simulation study on regional land subsidence in the Yangtze River Delta (south)[J]. Science in China (Series D (Earth Sciences)),2008,38(4):477 − 492. (in Chinese) XUE Yuqun, WU Jichun, ZHANG Yun, et al. Simulation study on regional land subsidence in the Yangtze River Delta （south）[J]. Science in China （Series D （Earth Sciences））, 2008, 38（4）: 477 − 492. （in Chinese）
[57]	李文运,崔亚莉,苏晨,等. 天津市地下水流-地面沉降耦合模型[J]. 吉林大学学报(地球科学版),2012,42(3):805 − 813. [LI Wenyun,CUI Yali,SU Chen,et al. An integrated numerical groundwater and land subsidence model of Tianjin[J]. Journal of Jilin University (Earth Science Edition),2012,42(3):805 − 813. (in Chinese with English abstract) LI Wenyun, CUI Yali, SU Chen, et al. An integrated numerical groundwater and land subsidence model of Tianjin[J]. Journal of Jilin University （Earth Science Edition）, 2012, 42（3）: 805 − 813. （in Chinese with English abstract）
[58]	ZHU Lin,FRANCESCHINI A,GONG Huili,et al. The 3-D facies and geomechanical modeling of land subsidence in the chaobai plain,Beijing[J]. Water Resources Research,2020,56(3):e2019WR027026. doi: 10.1029/2019WR027026
[59]	房浩,何庆成,宋建新,等. 基于地下水调控的沧州市地面沉降防治模拟研究[J]. 上海国土资源,2014,35(4):21 − 24. [FANG Hao,HE Qingcheng,SONG Jianxin,et al. Modeling land subsidence prevention based on groundwater regulation in Cangzhou[J]. Shanghai Land & Resources,2014,35(4):21 − 24. (in Chinese with English abstract) FANG Hao, HE Qingcheng, SONG Jianxin, et al. Modeling land subsidence prevention based on groundwater regulation in Cangzhou[J]. Shanghai Land & Resources, 2014, 35（4）: 21 − 24. （in Chinese with English abstract）
[60]	LI Yueting,TEATINI P,YU Jun,et al. Aseismic multifissure modeling in unfaulted heavily pumped basins:mechanisms and applications[J]. Water Resources Research,2021,57(10):e2021WR030127. doi: 10.1029/2021WR030127
[61]	黄丹,卢广达,章青. 准静态变形破坏的近场动力学分析[J]. 计算力学学报,2016,33(5):657 − 662. [HUANG Dan,LU Guangda,ZHANG Qing. A peridynamic study on quasi-static deformation and failure[J]. Chinese Journal of Computational Mechanics,2016,33(5):657 − 662. (in Chinese with English abstract) doi: 10.7511/jslx201605001 HUANG Dan, LU Guangda, ZHANG Qing. A peridynamic study on quasi-static deformation and failure[J]. Chinese Journal of Computational Mechanics, 2016, 33（5）: 657 − 662. （in Chinese with English abstract） doi: 10.7511/jslx201605001
[62]	李江涛. 基岩隆起条件下的地裂缝数值模拟——以无锡光明村为例[D]. 北京:首都师范大学,2022. [LI Jiangtao. Numerical simulation of ground fractures under bedrock uplift:A case study of Guangming Village,Wuxi [D]. Beijing:Capital Normal University,2022. (in Chinese with English abstract) LI Jiangtao. Numerical simulation of ground fractures under bedrock uplift: A case study of Guangming Village, Wuxi [D]. Beijing: Capital Normal University, 2022. （in Chinese with English abstract）
[63]	张可,宫辉力,李小娟,等. 近场动力学理论在区域地面沉降建模中的应用研究[J]. 地球信息科学学报,2023,25(1):49 − 62. [ZHANG Ke,GONG Huili,LI Xiaojuan,et al. Application of peridynamic theory in regional land subsidence modeling[J]. Journal of Geo-Information Science,2023,25(1):49 − 62. (in Chinese with English abstract) ZHANG Ke, GONG Huili, LI Xiaojuan, et al. Application of peridynamic theory in regional land subsidence modeling[J]. Journal of Geo-Information Science, 2023, 25（1）: 49 − 62. （in Chinese with English abstract）
[64]	MACEK R W,SILLING S A. Peridynamics via finite element analysis[J]. Finite Elements in Analysis and Design,2007,43(15):1169 − 1178. doi: 10.1016/j.finel.2007.08.012
[65]	LIU Shuo,FANG Guodong,LIANG Jun,et al. A coupling model of XFEM/peridynamics for 2D dynamic crack propagation and branching problems[J]. Theoretical and Applied Fracture Mechanics,2020,108:102573. doi: 10.1016/j.tafmec.2020.102573
[66]	周超凡,宫辉力,陈蓓蓓,等. 联合WT-RF的津保高铁沿线地面沉降预测[J]. 自然资源遥感,2021,33(4):34 − 42. [ZHOU Chaofan,GONG Huili,CHEN Beibei,et al. Prediction of land subsidence along Tianjin-Baoding high-speed railway using WT-RF method[J]. Remote Sensing for Natural Resources,2021,33(4):34 − 42. (in Chinese with English abstract) ZHOU Chaofan, GONG Huili, CHEN Beibei, et al. Prediction of land subsidence along Tianjin-Baoding high-speed railway using WT-RF method[J]. Remote Sensing for Natural Resources, 2021, 33（4）: 34 − 42. （in Chinese with English abstract）
[67]	POURGHASEMI H R,MOHSENI SARAVI M. Land-subsidence spatial modeling using the random forest data-mining technique[C]//Spatial Modeling in GIS and R for Earth and Environmental Sciences. Amsterdam:Elsevier,2019:147-159.
[68]	SALAZAR F,TOLEDO M Á,OÑATE E,et al. Interpretation of dam deformation and leakage with boosted regression trees[J]. Engineering Structures,2016,119:230 − 251. doi: 10.1016/j.engstruct.2016.04.012
[69]	SHI Liyuan,GONG Huili,CHEN Beibei,et al. Land subsidence prediction induced by multiple factors using machine learning method[J]. Remote Sensing,2020,12(24):4044. doi: 10.3390/rs12244044
[70]	SU Huaizhi,WU Zhongru,WEN Zhiping. Identification model for dam behavior based on wavelet network[J]. Computer-Aided Civil and Infrastructure Engineering,2007,22(6):438 − 448. doi: 10.1111/j.1467-8667.2007.00499.x
[71]	RANKOVIĆ V,GRUJOVIĆ N,DIVAC D,et al. Development of support vector regression identification model for prediction of dam structural behaviour[J]. Structural Safety,2014,48:33 − 39. doi: 10.1016/j.strusafe.2014.02.004
[72]	ZHU Lin,GONG Huili,LI Xiaojuan,et al. Comprehensive analysis and artificial intelligent simulation of land subsidence of Beijing,China[J]. Chinese Geographical Science,2013,23(2):237 − 248. doi: 10.1007/s11769-013-0589-6
[73]	刘青豪,张永红,邓敏,等. 大范围地表沉降时序深度学习预测法[J]. 测绘学报,2021,50(3):396 − 404. [LIU Qinghao,ZHANG Yonghong,DENG Min,et al. Time series prediction method of large-scale surface subsidence based on deep learning[J]. Acta Geodaetica et Cartographica Sinica,2021,50(3):396 − 404. (in Chinese with English abstract) LIU Qinghao, ZHANG Yonghong, DENG Min, et al. Time series prediction method of large-scale surface subsidence based on deep learning[J]. Acta Geodaetica et Cartographica Sinica, 2021, 50（3）: 396 − 404. （in Chinese with English abstract）
[74]	LU Can,ZHU Lin,LI Xiaojuan,et al. Land subsidence evolution and simulation in the western coastal area of Bohai Bay,China[J]. Journal of Marine Science and Engineering,2022,10(10):1549. doi: 10.3390/jmse10101549
[75]	沈焕锋,张良培. 地球表层特征参量反演与模拟的机理-学习耦合范式[J]. 中国科学:地球科学,2023,53(3):546 − 560. [SHEN Huanfeng,ZHANG Liangpei. Mechanism-learning coupling paradigms for parameter inversion and simulation in earth surface systems[J]. Scientia Sinica(Terrae),2023,53(3):546 − 560. (in Chinese) SHEN Huanfeng, ZHANG Liangpei. Mechanism-learning coupling paradigms for parameter inversion and simulation in earth surface systems[J]. Scientia Sinica（Terrae）, 2023, 53（3）: 546 − 560. （in Chinese）
[76]	李蕙君. 区域地面沉降循环神经网络时空模拟及风险评估[D]. 北京:首都师范大学,2021. [LI Huijun. Spatio-temporal simulation and risk assessment of regional land subsidence cyclic neural network [D]. Beijing:Capital Normal University,2021. (in Chinese with English abstract) LI Huijun. Spatio-temporal simulation and risk assessment of regional land subsidence cyclic neural network [D]. Beijing: Capital Normal University, 2021. （in Chinese with English abstract）