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With the major growth of the world's population over the past century, as well as rapid urbanisation, people increasingly live in crowded cities. This trend is often accompanied by proliferation of poorly built housing, uncontrolled use of land, occupation of unsafe environments and overstretched services. When a natural hazard strikes such a city many people are vulnerable to loss of life and property. This book explores what these people think and feel about the threats that they face. How do they live with perils ranging from earthquakes to monsoons, from floods to hurricanes, in the 21st century?The authors are drawn from a large range of disciplines: Psychology, Engineering, Geography, Anthropology and Urban Planning. They also reflect on how perils are represented in multiple cultures: the United States, Japan, Turkey, Bangladesh, the United Kingdom and New Zealand. The book therefore not only brings to light the ways that different cultures represent natural hazards but also the different ways in which various disciplines write about living with perils in the 21st century.The book is addressed both to researchers and to organizations involved with risk management and risk mitigation

With the major growth of the world's population over the past century, as well as rapid urbanisation, people increasingly live in crowded cities. This trend is often accompanied by proliferation of poorly built housing, uncontrolled use of land, occupation of unsafe environments and overstretched services. When a natural hazard strikes such a city many people are vulnerable to loss of life and property. This book explores what these people think and feel about the threats that they face. How do they live with perils ranging from earthquakes to monsoons, from floods to hurricanes, in the 21st century?The authors are drawn from a large range of disciplines: Psychology, Engineering, Geography, Anthropology and Urban Planning. They also reflect on how perils are represented in multiple cultures: the United States, Japan, Turkey, Bangladesh, the United Kingdom and New Zealand. The book therefore not only brings to light the ways that different cultures represent natural hazards but also the different ways in which various disciplines write about living with perils in the 21st century. The book is addressed both to researchers and to organizations involved with risk management and risk mitigation.

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.