Land subsidence due to groundwater pumping: hazard  probability assessment through the combination  of Bayesian model and fuzzy set theory

Li, Huijun; Zhu, Lin; Guo, Gaoxuan; Zhang, Yan; Dai, Zhenxue; Li, Xiaojuan; Chang, Linzhen; Teatini, Pietro

doi:https://doi.org/10.5194/nhess-21-823-2021

Articles | Volume 21, issue 2

https://doi.org/10.5194/nhess-21-823-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/nhess-21-823-2021

© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 21, issue 2

Research article

|

02 Mar 2021

Research article |

| 02 Mar 2021

Land subsidence due to groundwater pumping: hazard probability assessment through the combination of Bayesian model and fuzzy set theory

Huijun Li, Lin Zhu, Gaoxuan Guo, Yan Zhang, Zhenxue Dai, Xiaojuan Li, Linzhen Chang, and Pietro Teatini

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Cited articles

Bhattarai, R. and Kondoh, A.: Risk Assessment of Land Subsidence in Kathmandu Valley, Nepal, Using Remote Sensing and GIS, Adv. Remote Sens., 6, 132–146, 2017.

Bonì, R., Meisina, C., Teatini, P., Zucca, F., Zoccarato, C., Franceschini, A., Ezquerro, P., Bejar, M., Fernandez-Merofo, J. A., Guardiola-Albert, C., Pastor Navarro, J., Tomás, R., and Herrera, G.: 3D groundwater flow and deformation modelling of Madrid aquifer, J. Hydrol., 585, 124773, https://doi.org/10.1016/j.jhydrol.2020.124773, 2020.

Chaussard, E., Wdowinski, S., Cabral-Cano, E., and Amelung, F.: Land subsidence in central Mexico detected by ALOS InSAR time-series, Remote Sens. Environ., 140, 94–106, 2014.

Chen, M., Tomás, R., Li, Z. H., Motagh, M., Li, T., Hu, L., Gong, H., Li, X., Yu, J., and Gong, X.: Imaging land subsidence induced by groundwater extraction in Beijing (China) using satellite radar interferometry, Remote Sens., 8, 468–489, 2016.

Chen, Y., Shu, L. C., and Burbey, T.: An Integrated Risk Assessment Model of Township-Scaled Land Subsidence Based on an Evidential Reasoning Algorithm and Fuzzy Set Theory, Risk Anal., 34, 656–669, 2014.