Complex coupled engineered systems: resilience and efficiency in design and management

The dynamics of two coupled complex systems, one natural and another engineered, are examined regarding resilience. In this thesis, I explore several emergent phenomena which are generated by the coupling of complex systems, and argue that those are the signatures of change in resilience. The emergent phenomena include (1) functional homogenization, (2) fragmentation, and (3) stochastic tipping points. To this end, two types of coupling are recognized: (1) managed ecological systems which are extensively altered and intensively managed to meet human needs (e.g., agricultural landscapes, catchments with dams and levees); and (2) human-created engineered systems (e.g., infrastructure; cities, industrial districts). Both systems are subject to stochastic, natural disturbance regimes, and because of the emergent phenomena which imply inherent uncertainties in the dynamics of complex systems, conventional risk-based management approaches cannot be sufficient for designing and managing those systems. Therefore, it is shown in this thesis that: (1) resilience of coupled complex systems is not a static property that a system has, but instead it emerges from what the system does in response to stochastic external disturbances and dynamics of internal coupled processes; and (2) stochastic, non-stationary tipping points emerge as a result of multiple types of stochastic forcing. Irreducible uncertainties and unexpected hazards are always present in complex systems. Thus, management of coupled complex engineered systems must be based on a recursive process that involves sensing, anticipating, adapting, and learning. Distributed control, anticipatory management, and organizational interaction strategies are also suggested as ways to be better prepared for unexpected shocks. I suggest integration of risk- and resilience based management approaches that optimize resilience and efficiency for design and management of coupled complex engineered systems. Optimization goal is to minimize adverse impacts of unexpected shocks and surprises resulting from stochastic forcing, and to help expedite recovery. I use several case studies (2011 Fukushima Earthquake/ Tsunami; 2011 Mississippi River Flooding; 2010 Deep Water Oil rig Explosion; 2005 Katrina flooding of New Orleans; Long-term trends in wet deposition patterns in U.S. and East Asia) to examine each of these aspects of coupled complex system dynamics and resilience.