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Generic Framework for Computation of Spatial Dynamic Resilience
  • Roshan Srivastav
Increasing number of catastrophic disaster events across the world due to natural hazards (floods, droughts, hurricanes, and tornadoes) has led to loss of thousands of human lives and shattered the global economic growth. The current scientific consensus is that this could be due to the effects of climate change. According to the Intergovernmental Panel for Climate Change fifth assessment report (IPCC, 2013) the climate characteristics and patterns are changing in time and space. Further it is reported that the increase in greenhouse gases would lead to more catastrophic events in the near future with varying degree of exposures. Therefore, there is a need to (a) increase our understanding of mechanisms causing natural disasters; (b) investigate various options for mitigation of their impacts; and (c) develop various adaptation options in order to minimize their future impacts Natural disaster management is embedded in the study of complex systems (natural and constructed) that are vulnerable to multiple failures. Recent research focus of many disaster management studies has been related to the concept of resilience – measure that integrates vulnerability and adaptive capacity of a complex system (Park et al., 2013). Resilience of complex systems is linking their behavior to system structure through feedback (in time and space). The concept of resilience has been adopted in various fields such as ecology, economics, risk management, and others (Holling, 1973; Arthur, 1999; Folke et al. 2002; Starr et al. 2003; Fiksel 2006; Park et al, 2013). Recently this concept is been adopted to quantify the impacts of climate change on urban environments (Chang et al., 2013; Simonovic and Peck, 2013). The work presented in this report is part of the project “Simple Proxies for Risk Analysis and Natural Hazard Estimation” supported by MITACS and Property and Casualty Insurance Compensation Corporation. This report focuses on the concept of resilience for understanding the complex behavior of a system exposed to various impacts caused by natural disasters. The proposed framework quantifies the dynamic behavior of the system which can serve for the improvement in understanding of the impacts and inform decision making processes. The objectives of the study are to (i) use the system dynamics modeling approach for integration of complex system behavior as a consequence of system structure; and (ii) develop a generic computerized framework for quantification of spatial dynamic resilience.
  • Spatio-Temporal Resilience
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Roshan Srivastav. Generic Framework for Computation of Spatial Dynamic Resilience. (2014)
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