Evaluating simplified methods for liquefaction assessment for loss estimation

Indranil Kongar,Tiziana Rossetto,Sonia Giovinazzi

doi:10.5194/nhess-17-781-2017

Indranil Kongar, Tiziana Rossetto + Show 1 more

Open Access

https://doi.org/10.5194/nhess-17-781-2017

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Abstract

Abstract. Currently, some catastrophe models used by the insurance industry account for liquefaction by applying a simple factor to shaking-induced losses. The factor is based only on local liquefaction susceptibility and this highlights the need for a more sophisticated approach to incorporating the effects of liquefaction in loss models. This study compares 11 unique models, each based on one of three principal simplified liquefaction assessment methods: liquefaction potential index (LPI) calculated from shear-wave velocity, the HAZUS software method and a method created specifically to make use of USGS remote sensing data. Data from the September 2010 Darfield and February 2011 Christchurch earthquakes in New Zealand are used to compare observed liquefaction occurrences to forecasts from these models using binary classification performance measures. The analysis shows that the best-performing model is the LPI calculated using known shear-wave velocity profiles, which correctly forecasts 78 % of sites where liquefaction occurred and 80 % of sites where liquefaction did not occur, when the threshold is set at 7. However, these data may not always be available to insurers. The next best model is also based on LPI but uses shear-wave velocity profiles simulated from the combination of USGS VS30 data and empirical functions that relate VS30 to average shear-wave velocities at shallower depths. This model correctly forecasts 58 % of sites where liquefaction occurred and 84 % of sites where liquefaction did not occur, when the threshold is set at 4. These scores increase to 78 and 86 %, respectively, when forecasts are based on liquefaction probabilities that are empirically related to the same values of LPI. This model is potentially more useful for insurance since the input data are publicly available. HAZUS models, which are commonly used in studies where no local model is available, perform poorly and incorrectly forecast 87 % of sites where liquefaction occurred, even at optimal thresholds. This paper also considers two models (HAZUS and EPOLLS) for estimation of the scale of liquefaction in terms of permanent ground deformation but finds that both models perform poorly, with correlations between observations and forecasts lower than 0.4 in all cases. Therefore these models potentially provide negligible additional value to loss estimation analysis outside of the regions for which they have been developed.

Highlights

The recent earthquakes in Haiti (2010), Canterbury, New Zealand (2010–2011), and Tohoku, Japan (2011), highlighted the significance of liquefaction as a secondary hazard of seismic events and the significant damage that it can cause to buildings and infrastructure
The LPI1, LPI3 and LPIref models are the only models that meet the criteria of having True positive rate (TPR) and True negative rate (TNR) > 0.5 and False positive rate (FPR) < 0.5, with the LPI1 model performing better despite being based on VS rather than ground investigation data
The high TNR but relatively low TPR of the three ZHU models indicate that they all show a bias towards forecasts of non-occurrence of liquefaction

Summary

Introduction

The recent earthquakes in Haiti (2010), Canterbury, New Zealand (2010–2011), and Tohoku, Japan (2011), highlighted the significance of liquefaction as a secondary hazard of seismic events and the significant damage that it can cause to buildings and infrastructure. The insurance sector was caught out by these events, with catastrophe models underestimating the extent and severity of liquefaction that occurred (Drayton and Verdon, 2013). A contributing factor to this is that the method used by some catastrophe models to account for liquefaction is based only on liquefaction susceptibility, a qualitative parameter that considers only surficial geology characteristics. Losses arising from liquefaction are estimated by adding an amplifier to losses estimated due to building damage caused by ground shaking (Drayton and Vernon, 2013). Kongar et al.: Evaluating simplified methods for liquefaction assessment for loss estimation significant losses from liquefaction damage will only be estimated if significant losses are already estimated from ground shaking, whereas it is known that liquefaction can be triggered at relatively low ground shaking intensities (Quigley et al, 2013)

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