IDEAS home Printed from https://ideas.repec.org/a/spr/nathaz/v103y2020i3d10.1007_s11069-020-04118-1.html
   My bibliography  Save this article

Land subsidence monitoring in sinking coastal areas using distributed fiber optic sensing: a case study

Author

Listed:
  • Su-Ping Liu

    (Nanjing University
    University of Leeds)

  • Bin Shi

    (Nanjing University)

  • Kai Gu

    (Nanjing University)

  • Cheng-Cheng Zhang

    (Nanjing University)

  • Ji-Long Yang

    (China Geological Survey)

  • Song Zhang

    (Nanjing University)

  • Peng Yang

    (Nanjing University)

Abstract

A number of coastal areas have been suffering from severe land subsidence, which draws worldwide attention. Quantifying the subsidence and the contribution of each compacting stratum is crucial to study its development mechanism. In this paper, the distributed fiber optic sensing (DFOS) technique based on Brillouin scattering was adopted to monitor land subsidence in a 100-m-deep borehole located in Tianjin, China. Vertical strain profile was obtained by a kind of fixed-point cable embedded in the borehole, and the DFOS-based land subsidence system successfully achieved a 2-year-period in-situ investigation of the soft soil. The results revealed that the land subsidence rate was 21.6 mm/a after 2017, and the strata deformation measurements were refined up to each 5-m-thickness in vertical direction. The compression strata were localized at shallow strata (3.4–38.4 m), and the dominant contributors were soft soil strata at depth of 3.4 m to 18.4 m that the contribution of every 5 m thick stratum from top to bottom was 34.4%, 27% and 19.1%, respectively. The subsidence and strata contribution obtained by DFOS were in good agreement with those of extensometers. The groundwater fluctuations and additional loading may be the significant triggering factors of the compaction of the soft soil. This study showed that the DFOS-based measurement is an effective approach for land subsidence monitoring and will be a supplement to existing techniques in coastal areas.

Suggested Citation

  • Su-Ping Liu & Bin Shi & Kai Gu & Cheng-Cheng Zhang & Ji-Long Yang & Song Zhang & Peng Yang, 2020. "Land subsidence monitoring in sinking coastal areas using distributed fiber optic sensing: a case study," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 103(3), pages 3043-3061, September.
    • Handle: RePEc:spr:nathaz:v:103:y:2020:i:3:d:10.1007_s11069-020-04118-1
    DOI: 10.1007/s11069-020-04118-1
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11069-020-04118-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11069-020-04118-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Stijn Temmerman & Patrick Meire & Tjeerd J. Bouma & Peter M. J. Herman & Tom Ysebaert & Huib J. De Vriend, 2013. "Ecosystem-based coastal defence in the face of global change," Nature, Nature, vol. 504(7478), pages 79-83, December.
    2. Jun Wang & Wei Gao & Shiyuan Xu & Lizhong Yu, 2012. "Evaluation of the combined risk of sea level rise, land subsidence, and storm surges on the coastal areas of Shanghai, China," Climatic Change, Springer, vol. 115(3), pages 537-558, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Su-Ping Liu & Bin Shi & Kai Gu & Cheng-Cheng Zhang & Jian-Hui He & Jing-Hong Wu & Guang-Qing Wei, 2021. "Fiber-optic wireless sensor network using ultra-weak fiber Bragg gratings for vertical subsurface deformation monitoring," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 109(3), pages 2557-2573, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhiyi Lin & Minerva Singh, 2024. "Assessing Coastal Vulnerability and Evaluating the Effectiveness of Natural Habitats in Enhancing Coastal Resilience: A Case Study in Shanghai, China," Sustainability, MDPI, vol. 16(2), pages 1-23, January.
    2. Yanjie Zhang & Bilal M. Ayyub & Dongming Zhang & Hongwei Huang & Yalda Saadat, 2019. "Impact of Water Level Rise on Urban Infrastructures: Washington, DC, and Shanghai as Case Studies," Risk Analysis, John Wiley & Sons, vol. 39(12), pages 2718-2731, December.
    3. Xi-Cun He & Tian-Liang Yang & Shui-Long Shen & Ye-Shuang Xu & Arul Arulrajah, 2019. "Land Subsidence Control Zone and Policy for the Environmental Protection of Shanghai," IJERPH, MDPI, vol. 16(15), pages 1-13, July.
    4. Jiyong Ding & Juefang Cai & Guangxiang Guo & Chen Chen, 2018. "An Emergency Decision-Making Method for Urban Rainstorm Water-Logging: A China Study," Sustainability, MDPI, vol. 10(10), pages 1-21, September.
    5. Yaolong Liu & Guorui Feng & Ye Xue & Huaming Zhang & Ruoguang Wang, 2015. "Small-scale natural disaster risk scenario analysis: a case study from the town of Shuitou, Pingyang County, Wenzhou, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 75(3), pages 2167-2183, February.
    6. Buenau, K.E. & Sather, N.K. & Arkema, K.K., 2025. "A marine energy and ecosystem service framework for coastal communities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 216(C).
    7. Ke Wang & Yongsheng Yang & Genserik Reniers & Quanyi Huang, 2021. "A study into the spatiotemporal distribution of typhoon storm surge disasters in China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 108(1), pages 1237-1256, August.
    8. Chen-Kun Chung, 2019. "The exploration of relationship between land subsidence and landscape transformation," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 97(3), pages 1051-1068, July.
    9. Weijiang Li & Jiahong Wen & Bo Xu & Xiande Li & Shiqiang Du, 2018. "Integrated Assessment of Economic Losses in Manufacturing Industry in Shanghai Metropolitan Area Under an Extreme Storm Flood Scenario," Sustainability, MDPI, vol. 11(1), pages 1-19, December.
    10. Gerald Schernewski & Lars Niklas Voeckler & Leon Lambrecht & Esther Robbe & Johanna Schumacher, 2022. "Building with Nature—Ecosystem Service Assessment of Coastal-Protection Scenarios," Sustainability, MDPI, vol. 14(23), pages 1-18, November.
    11. Ping Ai & Dingbo Yuan & Chuansheng Xiong, 2018. "Copula-Based Joint Probability Analysis of Compound Floods from Rainstorm and Typhoon Surge: A Case Study of Jiangsu Coastal Areas, China," Sustainability, MDPI, vol. 10(7), pages 1-18, June.
    12. Lam Thi Mai Huynh & Jie Su & Quanli Wang & Lindsay C. Stringer & Adam D. Switzer & Alexandros Gasparatos, 2024. "Meta-analysis indicates better climate adaptation and mitigation performance of hybrid engineering-natural coastal defence measures," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    13. Pérez-Maqueo, Octavio & Martínez, M. Luisa & Cóscatl Nahuacatl, Rosendo, 2017. "Is the protection of beach and dune vegetation compatible with tourism?," Tourism Management, Elsevier, vol. 58(C), pages 175-183.
    14. Reguero, Borja G. & Beck, Michael W. & Schmid, David & Stadtmüller, Daniel & Raepple, Justus & Schüssele, Stefan & Pfliegner, Kerstin, 2020. "Financing coastal resilience by combining nature-based risk reduction with insurance," Ecological Economics, Elsevier, vol. 169(C).
    15. Álvarez, Xana & Gómez-Rúa, María & Vidal-Puga, Juan, 2019. "Risk prevention of land flood: A cooperative game theory approach," MPRA Paper 91515, University Library of Munich, Germany.
    16. Karla Salgado & M. Luisa Martínez & Octavio Pérez-Maqueo & Miguel Equihua & Ismael Mariño-Tapia & Patrick Hesp, 2024. "Estimating storm-related coastal risk in Mexico using Bayesian networks and the occurrence of natural ecosystems," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 120(6), pages 5919-5940, April.
    17. Roche, R.C. & Walker-Springett, K. & Robins, P.E. & Jones, J. & Veneruso, G. & Whitton, T.A. & Piano, M. & Ward, S.L. & Duce, C.E. & Waggitt, J.J. & Walker-Springett, G.R. & Neill, S.P. & Lewis, M.J. , 2016. "Research priorities for assessing potential impacts of emerging marine renewable energy technologies: Insights from developments in Wales (UK)," Renewable Energy, Elsevier, vol. 99(C), pages 1327-1341.
    18. Takahiro Tsuge & Yasushi Shoji & Koichi Kuriyama & Ayumi Onuma, 2022. "Using a Choice Experiment to Understand Preferences for Disaster Risk Reduction with Uncertainty: A Case Study in Japan," Sustainability, MDPI, vol. 14(8), pages 1-17, April.
    19. Strain, E.M.A. & Kompas, T. & Boxshall, A. & Kelvin, J. & Swearer, S. & Morris, R.L., 2022. "Assessing the coastal protection services of natural mangrove forests and artificial rock revetments," Ecosystem Services, Elsevier, vol. 55(C).
    20. Carus, Jana & Heuner, Maike & Paul, Maike & Schröder, Boris, 2017. "Which factors and processes drive the spatio-temporal dynamics of brackish marshes?—Insights from development and parameterisation of a mechanistic vegetation model," Ecological Modelling, Elsevier, vol. 363(C), pages 122-136.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:nathaz:v:103:y:2020:i:3:d:10.1007_s11069-020-04118-1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.