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A three-dimensional fluid-solid model, coupling high-rise building load and groundwater abstraction, for prediction of regional land subsidence

  • Zhao Li
  • Zujiang LuoEmail author
  • Qi Wang
  • Jingjing Du
  • Wei Lu
  • Di Ning
Paper

Abstract

The main factors that cause land subsidence are groundwater withdrawal and the load of high-rise buildings. Previous studies on land subsidence caused by high-rise buildings have focused on small areas. Few scholars have proposed land subsidence models that combine the effects of groundwater withdrawal and high-rise building load at a regional scale. This work was based on Biot’s consolidation theory and the nonlinear rheology theory. The soil parameters were varied in accordance with the Kozeny-Carman equation and Duncan-Zhang nonlinear model, and applied to a site in eastern China. A three-dimensional finite element method (FEM) program, fully coupling varying soil parameter values and fluid-solid characteristics of land subsidence, was coded using FORTRAN. The program was used to simulate and predict regional land subsidence and to study the coupling effects of groundwater withdrawal and high-rise building load. The results showed that the soil parameters varied in reasonable range and the trend of variation was consistent with the characteristics of soil deformation. The sum of the land subsidence under high-rise building load alone and groundwater withdrawal alone differed from land subsidence under the combined effects of groundwater withdrawal and high-rise building load. The coupling effect of land subsidence caused by high-rise building load and groundwater withdrawal was shown to be nonlinear.

Keywords

Numerical modeling Subsidence Groundwater flow Varying parameter values China 

Modèle fluide-solide tridimensionnel, couplant la charge d’une tour d’immeuble et les prélèvements en eau souterraine, pour la prévision de la subsidence régionale

Résumé

Les principaux facteurs causant la subsidence des terrains sont les prélèvements en eau souterraine et la charge des tours d’immeubles. Les précédentes études portant sur la subsidence causée par des tours d’immeuble ont porté sur des emprises restreintes. Peu de chercheurs ont proposé des modélisations de subsidence qui combinent les effets de prélèvements en eau souterraine et de la charge d’immeubles à échelle régionale. Le présent travail a été basé sur la théorie de Biot et sur la théorie de rhéologie non-linéaire. Les propriétés des sols ont été modifiées selon l’équation de Kozeny-Carman et le modèle non-linéaire de Duncan-Zhang, et appliquées à un site de Chine orientale. Un programme construit en trois dimensions par la méthode des éléments finis (MEF), et couplant intégralement les variations des propriétés des sols avec les caractéristiques fluide-solide de la subsidence, a été codé en FORTRAN. Le programme a été utilisé afin de simuler et prédire la subsidence régionale, et d’étudier les effets couplés de l’exploitation des eaux souterraines et de la charge des tours d’immeuble. Les résultats ont montré que les propriétés des sols varient dans une gamme raisonnable et que la tendance d’évolution est. cohérente avec les caractéristiques de la déformation des sols. La somme des subsidences conséquentes à la seule charge des immeubles d’une part et aux seuls prélèvements en eau souterraine d’autre part diffère de la subsidence sous les deux effets combinés des prélèvements en eau et de la charge des immeubles. Il a été démontré que l’effet couplé de la subsidence causée par la charge des immeubles et les prélèvements en eau souterraine est. non-linéaire.

Un modelo tridimensional fluido-sólido, que combina cargas de edificios de gran Altura y extracción de agua subterránea, para la predicción de subsidencia regional del terreno

Resumen

Los principales factores que causan la subsidencia del terreno son la extracción de agua subterránea y la carga de edificios de gran altura. Los estudios previos sobre subsidencia del terreno causados por edificios de gran altura se han centrado en áreas pequeñas. Pocos investigadores han propuesto modelos de subsidencia del terreno que combinen los efectos de la extracción de agua subterránea y la carga de edificios de gran altura a escala regional. Este trabajo se basó en la teoría de la consolidación de Biot y la teoría de la reología no lineal. Los parámetros del suelo se variaron de acuerdo con la ecuación de Kozeny-Carman y el modelo no lineal Duncan-Zhang, y se aplicaron a un sitio en el este de China. Un programa de método de elementos finitos (FEM) tridimensional, que combina valores de parámetros de suelo variables y características fluidas y sólidas de subsidencia del terreno, se codificó utilizando FORTRAN. El programa se usó para simular y predecir la subsidencia regional del terreno y para estudiar los efectos de acoplamiento de la extracción de agua subterránea y la carga de edificios de gran altura. Los resultados mostraron que los parámetros del suelo variaron en un rango razonable y la tendencia de variación fue consistente con las características de la deformación del suelo. La suma de la subsidencia del terreno bajo la carga de un edificio de gran altura sola y la extracción de agua subterránea sola difería de la subsidencia del terreno bajo los efectos combinados de la extracción de agua subterránea y la carga del edificio de gran altura. Se demostró que el efecto de acoplamiento de la subsidencia del terreno causado por la gran altura de la construcción y la extracción de agua subterránea no es lineal.

高层建筑荷载和地下水开采叠加作用下区域地面沉降预测三维流固耦合模型

摘要

引发地面沉降主要因素是地下水开采和高层建筑荷载,过去对高层建筑荷载引发地面沉降的研究集中在小区域,很少有学者提出在大区域地面沉降模型上将地下水开采和高层建筑荷载耦合起来。研究基于比奥固结理论和非线性流变理论,根据Kozeny-Carman公式和Duncan-Zhang非线性模型认为土体参数是变化的,并将其应用于中国东部某场地。应用Fortran语言编写一个三维变参数流固耦合地面沉降预测有限元程序,程序用于模拟预测区域地面沉降,并研究地下水开采和高层建筑荷载引发地面沉降的耦合效应。结果表明,土力学参数变化的趋势符合土体变性特征且参数值的变化在土层代表范畴之内,高层建筑荷载单独引发的地面沉降量与地下水开采单独引发的地面沉降量之和不等于地下水开采和高层建筑荷载叠加作用下的地面沉降量。高层建筑荷载和地下水开采引发的地面沉降耦合效应表现为非线性的。

Um modelo fluido-sólido tridimensional, acoplando carga de edifícios altos com captação de águas subterrâneas, para previsão de subsidência regional

Resumo

Os principais fatores que causam a subsidência de terrenos são a captação de águas subterrâneas e a carga exercida por edifícios altos. Estudos anteriores sobre subsidência de terrenos causada por edifícios altos concentraram-se em pequenas áreas. Poucos estudiosos têm proposto modelos de subsidência que combinam os efeitos do bombeamento de águas subterrâneas e da carga de edifícios altos em escala regional. Este trabalho foi baseado na teoria de consolidação de Biot e na teoria de reologia não-linear. Os parâmetros de solo foram variados de acordo com a equação de Kozeny-Carman e o modelo não-linear de Duncan-Zhang, e aplicados no leste da China. Um programa tridimensional utilizando o método de elementos finitos (MEF), inteiramente acoplado às variáveis de parâmetros do solo e características fluido-sólido de subsidência terrestre, foi codificado empregando FORTRAN. O programa foi utilizado para simular e prever subsidência regional de terra e estudar os efeitos em conjunto da captação de águas subterrâneas e da carga de edifícios altos. Os resultados revelaram que os parâmetros do solo variaram numa faixa razoável e a tendência de variação foi consistente com as características de deformação do solo. A soma da subsidência sob carga de edifícios altos isolada e da captação de águas subterrâneas também isolada difere da subsidência do terreno sob efeito combinado da retirada de águas subterrâneas e da carga de edifícios altos. O efeito combinado da subsidência de terrenos causada pela carga de edifícios altos e captação de águas subterrâneas mostrou-se ser não-linear.

Notes

Acknowledgments

The authors would also gratefully acknowledge Jiangsu Department of Land and Resources for support of this work under Nantong Urban Geological Survey Program.

Funding information

The research work described herein was funded by the National Natural Science Foundation of China (Grant No. 41874014).

References

  1. Albano M, Polcari M, Bignami C, Moro M, Saroli M, Stramondo S (2016) An innovative procedure for monitoring the change in soil seismic response by InSAR data: application to the Mexico City subsidence. Int J Appl Earth Obs Geoinf 53:146–158.  https://doi.org/10.1016/j.jag.2016.08.011 CrossRefGoogle Scholar
  2. Alfaro P, Liesch T, Goldscheider N (2017) Modelling groundwater over-extraction in the southern Jordan Valley with scarce data. Hydrogeol J 25(5):1319–1340.  https://doi.org/10.1007/s10040-017-1535-y CrossRefGoogle Scholar
  3. Chai JC, Shen SL, Zhu HH, Zhang XL (2004) Land subsidence due to groundwater drawdown in Shanghai. Geotechnique 54(2):143–147.  https://doi.org/10.1680/geot.54.2.143.36332 CrossRefGoogle Scholar
  4. 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 CrossRefGoogle Scholar
  5. Chen XX, Luo ZJ, Zhou SL (2014) Influences of soil hydraulic and mechanical parameters on land subsidence and ground fissures caused by groundwater exploitation. J Hydrodyn 26(1):155–164.  https://doi.org/10.1016/S1001-6058(14)60018-4 CrossRefGoogle Scholar
  6. Cui ZD, Yang JQ, Yuan L (2015) Land subsidence caused by the interaction of high-rise buildings in soft soil areas. Nat Hazards 79(2):1199–1217.  https://doi.org/10.1007/s11069-015-1902-8 CrossRefGoogle Scholar
  7. Gambolati G, Freeze RA (1973) Mathematical simulation of the subsidence of Venice: 1. theory. Water Resour Res 9(3):721–733.  https://doi.org/10.1029/WR009i003p00721 CrossRefGoogle Scholar
  8. Ge Y, Xu W, Gu ZH, Zhang YC, Chen L (2011) Risk perception and hazard mitigation in the Yangtze River Delta region, China. Nat Hazards 56(3):633–648.  https://doi.org/10.1007/s11069-010-9579-5 CrossRefGoogle Scholar
  9. He XT (2016) Study on the coupled numerical simulation of groundwater flow, land subsidence and freshwater salinisation in Nantong area (in Chinese). MSc Thesis, Nanjing University, Nanjing, ChinaGoogle Scholar
  10. Helm DC (1975) One-dimensional simulation of aquifer system compaction near Pixley, California: 1. constant parameters. Water Resour Res 11(3):465–478.  https://doi.org/10.1029/wr011i003p00465 CrossRefGoogle Scholar
  11. Hu J, Shi B, Inyang HI, Chen J, Sui Z (2009) Patterns of subsidence in the lower Yangtze Delta of China: the case of the Suzhou-Wuxi-Changzhou region. Environ Monit Assess 153(1–4):61–72.  https://doi.org/10.1007/s10661-008-0336-0 CrossRefGoogle Scholar
  12. Jin WZ, Luo ZJ, Wu XH (2016) Sensitivity analysis of related parameters in simulation of land subsidence and ground fissures caused by groundwater exploitation. Bull Eng Geol Environ 75(3):1143–1156.  https://doi.org/10.1007/s10064-016-0897-z CrossRefGoogle Scholar
  13. Khan AS, Khan SD, Kakar DM (2013) Land subsidence and declining water resources in Quetta Valley, Pakistan. Environ Earth Sci 70(6):2719–2727.  https://doi.org/10.1007/s12665-013-2328-9 CrossRefGoogle Scholar
  14. Li HE, He YJ, Fan GY, Li TC, Pastor M (2011) Recent developments of generalized plasticity models for saturated and unsaturated soils. Water Sci Eng 4(3):329–344.  https://doi.org/10.3882/j.issn.1674-2370.2011.03.009 Google Scholar
  15. Liu CH, Pan YW, Liao JJ, Huang CT, Ouyang S (2004) Characterization of land subsidence in the Choshui River alluvial fan, Taiwan. Environ Geol 45(8):1154–1166.  https://doi.org/10.1007/s00254-004-0983-6 CrossRefGoogle Scholar
  16. Luo ZJ, Zeng F (2011) Finite element numerical simulation of land subsidence and groundwater exploitation based on visco-elastic-plastic Biot’s consolidation theory. J Hydrodyn 23(5):615–624.  https://doi.org/10.1016/S1001-6058(10)60157-6 CrossRefGoogle Scholar
  17. Luo ZJ, Zhang YY, Wu YX (2008) Finite element numerical simulation of three-dimensional seepage control for Deep Foundation pit dewatering. J Hydrodyn 20(5):596–602.  https://doi.org/10.1016/S1001-6058(08)60100-6 CrossRefGoogle Scholar
  18. Ma Q, Luo Z (2015) Numerical simulation of groundwater exploitation and land subsidence in Cangzhou city (in Chinese). Water Resour Prot 31(4):20–26.  https://doi.org/10.3880/j.issn.1004-6933.2015.04.004
  19. Ma Q, Luo Z, Howard KWF, Wang Q (2018) Evaluation of optimal aquifer yield in Nantong city, China, under land subsidence constraints. Q J Eng Geol Hydrogeol 51:124–137.  https://doi.org/10.1144/qjegh2017-028 CrossRefGoogle Scholar
  20. Maghsoudi Y, van der Meer F, Hecker C, Perissin D, Saepuloh A (2018) Using PS-InSAR to detect surface deformation in geothermal areas of West Java in Indonesia. Int J Appl Earth Obs Geoinf 64:386–396.  https://doi.org/10.1016/j.jag.2017.04.001 CrossRefGoogle Scholar
  21. Notti D, Mateos RM, Monserrat O, Devanthéry N, Peinado T, Roldán FJ, Fernández-Chacón F, Galve JP, Lamas F, Azañón JM (2016) Lithological control of land subsidence induced by groundwater withdrawal in new urban AREAS (Granada Basin, SE Spain). Multiband DInSAR monitoring. Hydrol Process 30(13):2317–2331.  https://doi.org/10.1002/hyp.10793 CrossRefGoogle Scholar
  22. Ortega-Guerrero A, Rudolph DL, Cherry JA (1999) Analysis of long-term land subsidence near Mexico City: field investigations and predictive modeling. Water Resour Res 35(11):3327–3341.  https://doi.org/10.1029/1999WR900148 CrossRefGoogle Scholar
  23. Osmanoğlu B, Dixon TH, Wdowinski S, Cabral-Cano E, Jiang Y (2011) Mexico City subsidence observed with Persistent Scatterer InSAR. Int J Appl Earth Obs Geoinf 13(1):1–12.  https://doi.org/10.1016/j.jag.2010.05.009 CrossRefGoogle Scholar
  24. Qin H, Andrews CB, Tian F, Cao G, Luo Y, Liu J (2018) Groundwater-pumping optimization for land-subsidence control in Beijing plain, China. Hydrogeol J 26(4):1061–1081.  https://doi.org/10.1007/s10040-017-1712-z CrossRefGoogle Scholar
  25. Sayyaf M, Mahdavi M, Barani OR, Feiznia S, Motamedvaziri B (2014) Simulation of land subsidence using finite element method: Rafsanjan plain case study. Nat Hazards 72(2):309–322.  https://doi.org/10.1007/s11069-013-1010-6 CrossRefGoogle Scholar
  26. Shen SL, Xu YS (2011) Numerical evaluation of land subsidence induced by groundwater pumping in Shanghai. Can Geotech J 48(9):1378–1392.  https://doi.org/10.1139/t11-049 CrossRefGoogle Scholar
  27. Shen SL, Ma L, Xu YS, Yin ZY (2013) Interpretation of increased deformation rate in aquifer IV due to groundwater pumping in Shanghai. Can Geotech J 50(11):1129–1142.  https://doi.org/10.1139/cgj-2013-0042 CrossRefGoogle Scholar
  28. Shi X, Xue Y, Wu J, Ye S, Zhang Y, Wei Z, Yu J (2008) Characterization of regional land subsidence in Yangtze Delta, China: the example of Su-Xi-Chang area and the city of Shanghai. Hydrogeol J 16(3):593–607.  https://doi.org/10.1007/s10040-007-0237-2 CrossRefGoogle Scholar
  29. Shrestha PK, Shakya NM, Pandey VP, Birkinshaw SJ, Shrestha S (2017) Model-based estimation of land subsidence in Kathmandu Valley, Nepal. Geomat Nat Haz Risk 8(2):974–996.  https://doi.org/10.1080/19475705.2017.1289985 CrossRefGoogle Scholar
  30. Smith IM, Griffiths DV (2004) Programming the finite element method, 4th ed. Wiley, Hoboken, NJGoogle Scholar
  31. Tang YQ, Cui ZD, Wang JX, Lu C, Yan XX (2008) Model test study of land subsidence caused by high-rise building group in Shanghai. Bull Eng Geol Environ 67(2):173–179.  https://doi.org/10.1007/s10064-008-0121-x CrossRefGoogle Scholar
  32. Wu J, Shi X, Ye S, Xue Y, Zhang Y, Wei Z, Fang Z (2010) Numerical simulation of Viscoelastoplastic land subsidence due to groundwater overdrafting in Shanghai, China. J Hydrol Eng 15(3):223–236.  https://doi.org/10.1061/(ASCE)HE.1943-5584.0000172 CrossRefGoogle Scholar
  33. Yin ZZ (2007) Principle of geotechnics (in Chinese). China Waterpower Press, BeijingGoogle Scholar
  34. Yu L, Yang T, Zhao Q, Liu M, Pepe A (2017) The 2015-2016 ground displacements of the Shanghai coastal area inferred from a combined COSMO-SkyMed/Sentinel-1 DInSAR analysis. Remote Sens 9(11).  https://doi.org/10.3390/rs9111194
  35. Zhang Y, Wu H, Kang Y, Zhu C (2016) Ground subsidence in the Beijing-Tianjin-Hebei region from 1992 to 2014 revealed by multiple SAR stacks. Remote Sens 8(8):1–17.  https://doi.org/10.3390/rs8080675 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.School of Earth Sciences and EngineeringHohai UniversityNanjingChina
  2. 2.Environmental Geology Exploration Institute of Jiangsu ProvinceNanjingChina

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