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Groundwater Overexploitation Causing Land Subsidence: Hazard Risk Assessment Using Field Observation and Spatial Modelling

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  • Bijuan Huang
  • Longcang Shu
  • Y. Yang

Abstract

Hazard risk assessment of land subsidence is a complicated issue aiming at identifying areas with potentially high environmental hazard due to land subsidence. The methods of hazard risk assessment of land subsidence were reviewed and a new systematic approach was proposed in this study. Quantitative identification of land subsidence is important to the hazard risk assessment. Field observations using extensometers were used to determine assessment indexes and estimate weights of each index. Spatial modelling was also established in ArcGIS to better visualize the assessment data. These approaches then were applied to the Chengnan region, China as a case study. Three factors, thickness of the second confined aquifer, thickness of the soft clay and the annual recovery rate of groundwater level were incorporated into the hazard risk assessment index system. The weights of each index are 0.33, 0.17 and 0.5 respectively. The zonation map shows that the high, medium and low risk ranked areas for land subsidence account for 9.5 %, 44.7 % and 45.8 % of the total area respectively. The annual recovery rate of groundwater level is the major factor raising land subsidence hazard risk in approximately half of the study area. Copyright The Author(s) 2012

Suggested Citation

  • Bijuan Huang & Longcang Shu & Y. Yang, 2012. "Groundwater Overexploitation Causing Land Subsidence: Hazard Risk Assessment Using Field Observation and Spatial Modelling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(14), pages 4225-4239, November.
    • Handle: RePEc:spr:waterr:v:26:y:2012:i:14:p:4225-4239
    DOI: 10.1007/s11269-012-0141-y
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    1. Rejane Maria Rodrigues Luna & Silvio Jacks dos Anjos Garnés & Jaime Joaquim da Silva Pereira Cabral & Sylvana Melo Santos, 2017. "Groundwater overexploitation and soil subsidence monitoring on Recife plain (Brazil)," 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. 86(3), pages 1363-1376, April.
    2. Rejane Maria Rodrigues Luna & Silvio Jacks Garnés & Jaime Joaquim Cabral & Sylvana Melo Santos, 2021. "Suitability of GNSS for analysis of soil subsidence in Recife in a highly urbanized coastal area," 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. 106(3), pages 1821-1837, April.
    3. Jonas Sundell & Ezra Haaf & Tommy Norberg & Claes Alén & Mats Karlsson & Lars Rosén, 2019. "Risk Mapping of Groundwater‐Drawdown‐Induced Land Subsidence in Heterogeneous Soils on Large Areas," Risk Analysis, John Wiley & Sons, vol. 39(1), pages 105-124, January.
    4. Shabnam Mehrnoor & Maryam Robati & Mir Masoud Kheirkhah Zarkesh & Forough Farsad & Shahram Baikpour, 2023. "Land subsidence hazard assessment based on novel hybrid approach: BWM, weighted overlay index (WOI), and support vector machine (SVM)," 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. 115(3), pages 1997-2030, February.
    5. Claudio Alimonti & Mara Lombardi & Monica Cardarilli & Elena Soldo, 2017. "Reliability Analysis Applied on Land Subsidence Effects of Groundwater Remediation: Probabilistic vs. Deterministic Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(6), pages 1745-1758, April.
    6. Yu Chen & Longcang Shu & Thomas J. Burbey, 2014. "An Integrated Risk Assessment Model of Township‐Scaled Land Subsidence Based on an Evidential Reasoning Algorithm and Fuzzy Set Theory," Risk Analysis, John Wiley & Sons, vol. 34(4), pages 656-669, April.

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