Articles | Volume 17, issue 5
https://doi.org/10.5194/nhess-17-781-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/nhess-17-781-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Evaluating simplified methods for liquefaction assessment for loss estimation
Indranil Kongar
CORRESPONDING AUTHOR
Earthquake and People Interaction Centre (EPICentre), Department of
Civil, Environmental and Geomatic Engineering, University College London,
London, WC1E 6BT, UK
Tiziana Rossetto
Earthquake and People Interaction Centre (EPICentre), Department of
Civil, Environmental and Geomatic Engineering, University College London,
London, WC1E 6BT, UK
Sonia Giovinazzi
Department of Civil and Natural Resources Engineering, University of
Canterbury, Christchurch, 8140, New Zealand
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Total article views: 4,767 (including HTML, PDF, and XML)
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Cited
16 citations as recorded by crossref.
- Multihazard Scenarios for Regional Seismic Risk Assessment of Spatially Distributed Infrastructure N. Soleimani et al. https://doi.org/10.1061/(ASCE)IS.1943-555X.0000598
- Effect of spatial variability of soil properties on liquefaction behaviour – a probabilistic approach Ş. Tuna https://doi.org/10.1007/s10518-025-02349-w
- Assessing liquefaction risk and hazard mapping in a high-seismic region: a case study of Bengkulu City, Indonesia L. Mase et al. https://doi.org/10.1007/s11069-024-07057-3
- Assessing the value of information in pricing insurance against multiple hazards: the case of earthquake and liquefaction S. Keith et al. https://doi.org/10.1016/j.ijdrr.2026.106052
- Causal spatially heterogeneous Bayesian networks with GPs and normalizing flows for seismic multi-hazard estimation X. Li et al. https://doi.org/10.1038/s44304-025-00098-z
- Bayesian Recalibration of Geospatial Liquefaction Model with Regional Data Updating: A Case Study of the 2008 Wenchuan Earthquake Y. Xie et al. https://doi.org/10.3390/eng7060260
- A Probabilistic Liquefaction Hazard Analysis: Case Studies from the Marmara Region I. Sianko et al. https://doi.org/10.1007/s10706-024-03042-6
- A Review on Impacts and Mitigation of Liquefaction of Soil Around the Tunnels T. Fatima et al. https://doi.org/10.1007/s11668-023-01759-9
- An additive framework for developing a hybrid VS30 model: Incorporating geological information into the existing SCK Model for an updated VS30 map of Chinese mainland J. Zhou et al. https://doi.org/10.1016/j.enggeo.2026.108926
- Cost–benefit analysis to appraise technical mitigation options for earthquake-induced liquefaction disaster events N. Wanigarathna et al. https://doi.org/10.1108/JFMPC-12-2021-0073
- Evaluation of liquefaction resistance in chemically grouted sand using cyclic triaxial tests K. Kyaw et al. https://doi.org/10.1016/j.rineng.2025.106875
- Laboratory study of slurry clay utilization to reduce liquefaction potential S. Sumiyanto et al. https://doi.org/10.21303/2461-4262.2026.004057
- Probabilistic framework for regional loss assessment due to earthquake-induced liquefaction including epistemic uncertainty C. Yilmaz et al. https://doi.org/10.1016/j.soildyn.2020.106493
- Deformation Mapping of the 2018 Sulawesi Earthquake by Satellite Radar and Optical Remote Sensing T. Tampubolon et al. https://doi.org/10.1088/1742-6596/1428/1/012043
- Urban growth modelling and social vulnerability assessment for a hazardous Kathmandu Valley C. Mesta et al. https://doi.org/10.1038/s41598-022-09347-x
- A deep learning approach for rapid detection of soil liquefaction using time–frequency images W. Zhang et al. https://doi.org/10.1016/j.soildyn.2023.107788
16 citations as recorded by crossref.
- Multihazard Scenarios for Regional Seismic Risk Assessment of Spatially Distributed Infrastructure N. Soleimani et al. https://doi.org/10.1061/(ASCE)IS.1943-555X.0000598
- Effect of spatial variability of soil properties on liquefaction behaviour – a probabilistic approach Ş. Tuna https://doi.org/10.1007/s10518-025-02349-w
- Assessing liquefaction risk and hazard mapping in a high-seismic region: a case study of Bengkulu City, Indonesia L. Mase et al. https://doi.org/10.1007/s11069-024-07057-3
- Assessing the value of information in pricing insurance against multiple hazards: the case of earthquake and liquefaction S. Keith et al. https://doi.org/10.1016/j.ijdrr.2026.106052
- Causal spatially heterogeneous Bayesian networks with GPs and normalizing flows for seismic multi-hazard estimation X. Li et al. https://doi.org/10.1038/s44304-025-00098-z
- Bayesian Recalibration of Geospatial Liquefaction Model with Regional Data Updating: A Case Study of the 2008 Wenchuan Earthquake Y. Xie et al. https://doi.org/10.3390/eng7060260
- A Probabilistic Liquefaction Hazard Analysis: Case Studies from the Marmara Region I. Sianko et al. https://doi.org/10.1007/s10706-024-03042-6
- A Review on Impacts and Mitigation of Liquefaction of Soil Around the Tunnels T. Fatima et al. https://doi.org/10.1007/s11668-023-01759-9
- An additive framework for developing a hybrid VS30 model: Incorporating geological information into the existing SCK Model for an updated VS30 map of Chinese mainland J. Zhou et al. https://doi.org/10.1016/j.enggeo.2026.108926
- Cost–benefit analysis to appraise technical mitigation options for earthquake-induced liquefaction disaster events N. Wanigarathna et al. https://doi.org/10.1108/JFMPC-12-2021-0073
- Evaluation of liquefaction resistance in chemically grouted sand using cyclic triaxial tests K. Kyaw et al. https://doi.org/10.1016/j.rineng.2025.106875
- Laboratory study of slurry clay utilization to reduce liquefaction potential S. Sumiyanto et al. https://doi.org/10.21303/2461-4262.2026.004057
- Probabilistic framework for regional loss assessment due to earthquake-induced liquefaction including epistemic uncertainty C. Yilmaz et al. https://doi.org/10.1016/j.soildyn.2020.106493
- Deformation Mapping of the 2018 Sulawesi Earthquake by Satellite Radar and Optical Remote Sensing T. Tampubolon et al. https://doi.org/10.1088/1742-6596/1428/1/012043
- Urban growth modelling and social vulnerability assessment for a hazardous Kathmandu Valley C. Mesta et al. https://doi.org/10.1038/s41598-022-09347-x
- A deep learning approach for rapid detection of soil liquefaction using time–frequency images W. Zhang et al. https://doi.org/10.1016/j.soildyn.2023.107788
Saved (final revised paper)
Latest update: 12 Sep 2026
Short summary
The purpose of this research is to evaluate the predictive capability of simplified liquefaction models that can be applied across wide geographical areas for insurance and risk management purposes. Predictions from nine models are compared to observations from the Canterbury earthquake sequence and finds that models based on a previously proposed Liquefaction Potential Index perform the best, whilst the commonly used HAZUS methodology does not perform well.
The purpose of this research is to evaluate the predictive capability of simplified liquefaction...
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