| Global urbanization accentuates the problem of planning for the future to ensure sustainable development. Large urban agglomerations represent concentrated areas in terms of population and economy and face potential risk due to natural disasters like earthquakes. This risk is rapidly changing with time due to changing location, exposure and vulnerability. This study develops the framework of Risk-Time Charts (RTCs) to portray variation of risk with time and forecast future urban earthquake disaster risk relative to current risk. The study attempts to determine the factors that change most rapidly with time and tries to identify the underlying mechanisms responsible for the change.; Conceptually, RTCs view the city as a system composed of sub-systems, interacting and changing over time. Two different perspectives---macroscopic and microscopic---are adopted in portraying the dynamic nature of urban earthquake disaster risk. The macroscopic perspective tries to assess the risk of earthquake disaster by taking into account the economic, social, political, and cultural context of earthquake hazard event and uses the Earthquake Disaster Risk Index to measure urban earthquake disaster risk by combining different macroscopic variables into a single index. The microscopic perspective evaluates the performance of each of the region's sectors---residential, commercial and government---by combining scenario loss data and recovery information into a Performance Index.; Using both perspectives, RTCs are developed for Los Angeles for the time-period 1990 to 2020. Sensitivity analysis is done to determine the effects of data quality on the confidence in the final results. Risk-reduction measures are simulated to determine their effects on the overall risk. The macroscopic perspective suggests that urbanization and increased economic interdependence cause the risk for Los Angeles to increase. The microscopic perspective indicates that risk is increasing for each of the sectors as well as the region as a whole in the future. The government experiences the largest increase in risk and is responsible for this situation. A mix of engineering and non-engineering risk-reduction measures could significantly decrease this risk. The results of the case study can be qualitatively extended to urban regions worldwide that have similar trends in urban growth and productivity. |
