Quantitatively Representing Nonlinear Disaster Recovery

This article provides a new technique for quantitatively characterizing the progress of recovery operations in the aftermath of a disaster event. The approach extends previous research on measuring dynamic, or adaptive, disaster resilience by developing a robust approach for characterizing nonlinear disaster recovery. In doing so, it enables a more accurate mathematical representation of different categories of recovery behavior and provides support for a much broader application of existing theory. Because the new approach inherits the ability to compare the relative behavior of multiple scenarios simultaneously, it also can serve as the basis for analytically comparing the expected performance of different plans for recovery operations. Practical application of the technique is demonstrated and discussed in the context of recovering electrical power after Hurricane Sandy struck the New York metropolitan area.