Statistical driven Vulnerability Assessment for the Resilience Quantification of Urban Areas

Abstract

The formation of new threats and the increasing complexity of infrastructure elements underline the need for more robust and sustainable systems, which are able to cope with adverse events. Achieving sustainability requires the increase of resilience. Currently, a comprehensive approach for the quantification of resilience is missing. Within this paper, a new generalized mathematical framework is presented to assess the resilience of complex systems, like urban areas. A clear definition of terms and their interaction builds the basis of this assessment scheme. Risk-based approaches are extended with the dimension of time, to quantify the susceptibility, the vulnerability and the recovery behavior of complex systems for multiple threat scenarios. Engineering approaches are applied to assess expected damage effects and are combined with statistical methods to weight the probability of occurrence and the exposition of the investigated system to the source of disruptive events. Resilience is covered by indicators for preparation, prevention, protection, response and recovery. The presented approach is able to determine these indicators and provides decision support, which enhancement measures are more effective. Hence, the framework quantifies, if it is better to avoid a hazardous event or to tolerate an event with an increased robustness, for example. An application example assesses urban areas with consideration of multiple adverse events, like terrorist attacks or earthquakes, and multiple buildings. Each urban object includes a certain number of attributes, like the object use, the construction type, the time-dependent number of persons and the value to derive different performance targets. The assessment results in the identification of weak-spots through the evaluation of single resilience indicators.