Abstract
Land subsidence is often associated with compaction of subsurface strata, which cannot be recorded in detail by precise leveling, satellite imagery, and even extensometers. The distributed fiber optic sensing (DFOS) technique is advantageous in subsurface deformation monitoring, because it can image distributed profiles of vertical deformation by distributed strain sensing. Here, we propose to use the relationship between the soil porosity change and soil strain to verify the DFOS monitoring results. An observation case in Shengze, Suzhou (southern Yangtze Delta, China) 2012–2019 shows that compression strain occurs mainly in two aquitards adjacent to the pumping aquifer. The compression-rebound deformation of soil layers is closely related to the change in groundwater level. The microstructure, especially pore structure, affects the compressibility of soils. Changes in pore size derived by groundwater level fluctuations are macroscopically expressed as soil strain. The calculated strain induced by water level drop was basically consistent with the monitoring value, proving the credibility of DFOS technique. Moreover, DFOS can be used for the estimation of strata compression potential, which is of great significance to the management of land subsidence and groundwater exploitation.
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Abidin HZ, Djaja R, Darmawan D, Hadi S, Akbar A, Rajiyowiryono H, Sudibyo Y, Meilano I et al (2001) Land subsidence of Jakarta (Indonesia) and its geodetic monitoring system. Nat Hazards 23:365–387
Abidin HZ, Gumilar I, Andreas H, Murdohardono D, Fukuda Y (2012) On causes and impacts of land subsidence in Bandung Basin, Indonesia. Environ Earth Sci 68:1545–1553. https://doi.org/10.1007/s12665-012-1848-z
Amighpey M, Arabi S (2016) Studying land subsidence in Yazd province, Iran, by integration of InSAR and levelling measurements. Remote Sensing Applications: Society and Environment 4:1–8. https://doi.org/10.1016/j.rsase.2016.04.001
Baldi P, Casula G, Cenni N, Loddo F, Pesci A (2009) GPS-based monitoring of land subsidence in the Po Plain (Northern Italy). Earth Planet Sci Lett 288:204–212. https://doi.org/10.1016/j.epsl.2009.09.023
Bao X, Dhliwayo J, Heron ND, Webb DJ, Jackson DA (1995) Experimental and theoretical studies on a distributed temperature sensor based on Brillouin scattering. J Lightwave Technol 13:1340–1348
Castellazzi P, Arroyo-Domínguez N, Martel R, Calderhead AI, Normand JCL, Gárfias J, Rivera A (2016) Land subsidence in major cities of Central Mexico: interpreting InSAR-derived land subsidence mapping with hydrogeological data. Int J Appl Earth Obs Geoinf 47:102–111. https://doi.org/10.1016/j.jag.2015.12.002
Chaussard E, Wdowinski S, Cabral-Cano E, Amelung F (2014) Land subsidence in central Mexico detected by ALOS InSAR time-series. Remote Sens Environ 140:94–106. https://doi.org/10.1016/j.rse.2013.08.038
Chuhan FA, Kjeldstad A, Bjørlykke K, Høeg K (2002) Porosity loss in sand by grain crushing— experimental evidence and relevance to reservoir quality. Mar Pet Geol 19:39–53
Chuhan FA, Kjeldstad A, Bjørlykke K, Høeg K (2003) Experimental compression of loose sands: relevance to porosity reduction during burial in sedimentary basins. Can Geotech J 40:995–1011. https://doi.org/10.1139/t03-050
Cui ZD, Jia YJ (2013) Analysis of electron microscope images of soil pore structure for the study of land subsidence in centrifuge model tests of high-rise building groups. Eng Geol 164:107–116. https://doi.org/10.1016/j.enggeo.2013.07.004
Erban LE, Gorelick SM, Zebker HA, Fendorf S (2013) Release of arsenic to deep groundwater in the Mekong Delta, Vietnam, linked to pumping-induced land subsidence. Proc Natl Acad Sci U S A 110:13751–13756. https://doi.org/10.1073/pnas.1300503110
Fan H, Deng K, Ju C, Zhu C, Xue J (2011) Land subsidence monitoring by D-InSAR technique. Mining Science and Technology (China) 21:869–872. https://doi.org/10.1016/j.mstc.2011.05.030
Figueroa-Miranda S, Tuxpan-Vargas J, Ramos-Leal JA, Hernández-Madrigal VM, Villaseñor-Reyes CI (2018) Land subsidence by groundwater over-exploitation from aquifers in tectonic valleys of Central Mexico: a review. Eng Geol 246:91–106. https://doi.org/10.1016/j.enggeo.2018.09.023
Galloway DL, Burbey TJ (2011) Review: regional land subsidence accompanying groundwater extraction. Hydrogeol J 19:1459–1486. https://doi.org/10.1007/s10040-011-0775-5
Griffiths FJ, Joshi RC (1989) Changes in pore size distribution due to consolidation of clays. Gtotechnique 39:159–167
Griffiths FJ, Joshi RC (1991) Change in pore size distribution owing to secondary consolidation of clays. Can Geotech J 28(1):20–24 28, 20–24
Gu K, Shi B, Liu C, Jiang H, Li T, Wu J (2018) Investigation of land subsidence with the combination of distributed fiber optic sensing techniques and microstructure analysis of soils. Eng Geol 240:34–47. https://doi.org/10.1016/j.enggeo.2018.04.004
Hung WC, Hwang C, Liou JC, Lin YS, Yang HL (2012) Modeling aquifer-system compaction and predicting land subsidence in central Taiwan. Eng Geol 147-148:78–90. https://doi.org/10.1016/j.enggeo.2012.07.018
Hwang C, Hung WC, Liu CH (2008) Results of geodetic and geotechnical monitoring of subsidence for Taiwan High Speed Rail operation. Nat Hazards 47:1–16. https://doi.org/10.1007/s11069-007-9211-5
Ikeda H, Kunisue S, Nohara D, Ooba K, Kokubo T (2015) In-situ formation compaction monitoring in deep reservoirs by use of fiber optics. Proc Int Assoc Hydrol Sci 372:393–394. https://doi.org/10.5194/piahs-372-393-2015
Kersey AD, Davis MA, Patrick HJ, LeBlanc M, Koo KP, Askins CG, Putnam MA, Friebele EJ (1997) Fiber grating sensors. J Lightwave Technol 15:1442-1463
Kogure T, Okuda Y (2018) Monitoring the vertical distribution of rainfall-induced strain changes in a landslide measured by distributed fiber optic sensing with Rayleigh backscattering. Geophys Res Lett 45:4033–4040. https://doi.org/10.1029/2018gl077607
Liu C, Shi B, Zhou J, Tang C (2011) Quantification and characterization of microporosity by image processing, geometric measurement and statistical methods: application on SEM images of clay materials. Appl Clay Sci 54:97–106. https://doi.org/10.1016/j.clay.2011.07.022
Liu C, Tang CS, Shi B, Suo WB (2013) Automatic quantification of crack patterns by image processing. Comput Geosci 57:77–80. https://doi.org/10.1016/j.cageo.2013.04.008
Liu J, Song Z, Lu Y, Bai Y, Qian W, Kanungo DP, Chen Z, Wang Y (2019) Monitoring of vertical deformation response to water draining–recharging conditions using BOFDA-based distributed optical fiber sensors. Environ Earth Sci 78:406.1-406.11. https://doi.org/10.1007/s12665-019-8409-7
Mahmoudpour M, Khamehchiyan M, Nikudel MR, Ghassemi MR (2016) Numerical simulation and prediction of regional land subsidence caused by groundwater exploitation in the southwest plain of Tehran, Iran. Eng Geol 201:6–28. https://doi.org/10.1016/j.enggeo.2015.12.004
McDaniel A, Fratta D, Tinjum JM, Hart DJ (2018) Long-term district-scale geothermal exchange borefield monitoring with fiber optic distributed temperature sensing. Geothermics 72:193–204. https://doi.org/10.1016/j.geothermics.2017.11.008
Motil A, Bergman A, Tur M (2016) [INVITED] State of the art of Brillouin fiber-optic distributed sensing. Opt Laser Technol 78:81–103. https://doi.org/10.1016/j.optlastec.2015.09.013
Nikos S, Ioannis P, Constantinos L, Paraskevas T, Anastasia K, Charalambos K (2016) Land subsidence rebound detected via multi-temporal InSAR and ground truth data in Kalochori and Sindos regions, Northern Greece. Eng Geol 209:175–186. https://doi.org/10.1016/j.enggeo.2016.05.017
Pei H, Cui P, Yin J, Zhu H, Chen X, Pei L, Xu D (2011) Monitoring and warning of landslides and debris flows using an optical fiber sensor technology. J Mt Sci 8:728–738. https://doi.org/10.1007/s11629-011-2038-2
Peng CX, Yang GH (2008) A simplified method for determining e-p curve of soft soil and its application to analyzing nonlinear settlement of foundation. Rock Soil Mech 29:1706–1710
Revil A, Grauls D, Brévart O (2002) Mechanical compaction of sand/clay mixtures. J Geophys Res: Solid Earth 107:ECV 11-11-ECV 11-15. https://doi.org/10.1029/2001jb000318
Ruiz-Constán A, Ruiz-Armenteros AM, Lamas-Fernández F, Martos-Rosillo S, Delgado JM, Bekaert DPS, Sousa JJ, Gil AJ et al (2016) Multi-temporal InSAR evidence of ground subsidence induced by groundwater withdrawal: the Montellano aquifer (SW Spain). Environ Earth Sci 75:242.1-242.16. https://doi.org/10.1007/s12665-015-5051-x
Santos SMD, Cabral JJDSP, Pontes Filho IDDS (2012) Monitoring of soil subsidence in urban and coastal areas due to groundwater overexploitation using GPS. Nat Hazards 64:421–439. https://doi.org/10.1007/s11069-012-0247-9
Sergeyev YM, Grabowska-Olszewska BO, Osipov VI, Sokolov VN, Kolomenski YN (2011) The classification of microstructures of clay soils. J Microsc 120:237–260
Shi B (1997) Quantitative research on the orientation of microstructures of clayer soil. Acta Geol Sin 71:36–44
Shi X, Xue Y, Wu J, Ye S, Zhang Y, Wei Z, Yu J (2007) Characterization of regional land subsidence in Yangtze Delta, China: the example of Su-Xi-Chang area and the city of Shanghai. Hydrogeol J 16:593–607. https://doi.org/10.1007/s10040-007-0237-2
Shi X, Feng Z, Yao B, Huang X, Wu J (2014) Study on the deformation characteristics of soil layers after banning groundwater pumping in Su-Xi-Chang area. Quaternary Sciences 34:1062–1071
Shirzaei M, Burgmann R (2018) Global climate change and local land subsidence exacerbate inundation risk to the San Francisco Bay Area. Sci Adv 4:eaap9234. https://doi.org/10.1126/sciadv.aap9234
Stutsel BM, Callow JN, Flower KC, Biddulph TB, Issa NA (2020) Application of distributed temperature sensing using optical fibre to understand temperature dynamics in wheat (triticum aestivum) during frost. Eur J Agron 115:126038. https://doi.org/10.1016/j.eja.2020.126038
Sun YJ, Zhang D, Shi B, Tong HJ, Wei GQ, Wang X (2014) Distributed acquisition, characterization and process analysis of multi-field information in slopes. Eng Geol 182:49–62. https://doi.org/10.1016/j.enggeo.2014.08.025
Thoang TT, Giao PH (2015) Subsurface characterization and prediction of land subsidence for HCM City, Vietnam. Eng Geol 199:107–124. https://doi.org/10.1016/j.enggeo.2015.10.009
Verruijt A (2009) Theory of consolidation. Springer, Netherlands
Wang GY, You G, Shi B, Yu J, Tuck M (2009) Long-term land subsidence and strata compression in Changzhou, China. Eng Geol 104:109–118. https://doi.org/10.1016/j.enggeo.2008.09.001
Wang GY, You G, Zhu JQ, Yu J, Li W (2016) Earth fissures in Su–Xi–Chang Region, Jiangsu, China. Surv Geophys 37:1095–1116. https://doi.org/10.1007/s10712-016-9388-9
Wu J, Jiang H, Su J, Shi B, Jiang Y, Gu K (2015) Application of distributed fiber optic sensing technique in land subsidence monitoring. J Civ Struct Heal Monit 5:587–597. https://doi.org/10.1007/s13349-015-0133-8
Wu JB, Hu Y, Luo ZJ (2018) Impact of building load on land subsidence in Shengze area of Wujiang, Jiangsu Province. Journal of Geology 42:167-174
Xue YQ, Zhang Y, Ye SJ, Wu JC, Li QF (2005) Land subsidence in China. Environ Geol 48:713–720. https://doi.org/10.1007/s00254-005-0010-6
Zhang Y, Gong H, Gu Z, Wang R, Li X, Zhao W (2013) Characterization of land subsidence induced by groundwater withdrawals in the plain of Beijing city, China. Hydrogeol J 22:397–409. https://doi.org/10.1007/s10040-013-1069-x
Zhang CC, Zhu HH, Shi B, She JK (2014) Interfacial characterization of soil-embedded optical fiber for ground deformation measurement. Smart Mater Struct 23:095022. https://doi.org/10.1088/0964-1726/23/9/095022
Zhang CC, Shi B, Liu SP, Jiang HT, Wei GQ (2018a) Quantifying fiber-optic cable–soil interfacial behavior toward distributed monitoring of land subsidence. China-Europe Conference on Geotechnical Engineering, Vienna:759–762. https://doi.org/10.1007/978-3-319-97112-4_170
Zhang CC, Shi B, Gu K, Liu SP, Wu JH, Zhang S, Zhang L, Jiang HT et al (2018b) Vertically distributed sensing of deformation using fiber optic sensing. Geophys Res Lett 45:11,732–711,741. https://doi.org/10.1029/2018gl080428
Zhang CC, Shi B, Zhu HH, Wei GQ (2019) Theoretical analysis of mechanical coupling between soil and fiber optic strain sensing cable for distributed monitoring of ground settlement. Chin J Geotech Eng 41:1670–1678. https://doi.org/10.11779/CJGE201909011
Acknowledgments
The writers would like to extend their appreciations to Suzhou NanZee Sensing Technology Co., Ltd. for their valuable help and support in the field study. Great thanks also go to the editorial board and the reviewers of this paper.
Funding
This study was financially supported by the National Natural Science Foundation of China (No. 41907232, 41977217), the Natural Science Foundation of Jiangsu Province (Grants No. BK20180972), and Comprehensive Evaluation of Geological Resources and Environment in the Yangtze River Economic Belt (DD20190260).
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Wu, J., Shi, B., Gu, K. et al. Evaluation of land subsidence potential by linking subsurface deformation to microstructure characteristics in Suzhou, China. Bull Eng Geol Environ 80, 2587–2600 (2021). https://doi.org/10.1007/s10064-020-02056-7
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DOI: https://doi.org/10.1007/s10064-020-02056-7