The loss of life and economic impact of natural hazards are most severe if they have been not properly evaluated and considered as determinants of development planning. Over the decades, demands from the public sector for openly available disaster risk profiles have increased. For decision-makers, it’s essential to comprehensively understand the risk, estimate the probable loss and reconstruction costs to better develop disaster risk reduction strategies. Earthquakes are one of the natural hazards that can cause tremendous and often crippling economic losses, especially in developing countries. Generally there are two ways in modelling earthquake catastrophe: the traditional engineering method and the rapid estimation based on historic disaster information. Their main difference lies in that, the former requires a very detailed exposure information collection, which is not always straightforward to retrieve; while the loss function is derived from analytical exposure fragility function. In the latter method, the loss function is strongly based on the processing of historical disaster information; while the exposure data is conveniently derived using economic indicator as proxy, e.g. GDP, fixed capital stock etc. In this work, we’ll show the difference in overall loss values and detailed loss distribution patterns modelled using these two methods based on several earthquake scenarios.
Earthquake Catastrophe Modeling: Comparison between Traditional Engineering Method and Rapid Estimation