Resilience: Measurement Science
The United Nations Office for Disaster Risk Reduction reported that the 2011 natural disasters, including the earthquake and tsunami that struck Japan, resulted in $366 billion in direct damages and 29,782 fatalities worldwide. Storms and floods accounted for up to 70% of the 302 natural disasters worldwide in 2011, with earthquakes producing the greatest number of fatalities. Average annual losses in the United States amount to about $55 billion. Enhancing community and system resilience could lead to massive savings through risk reduction and expeditious recovery. The rational management of such reduction and recovery is facilitated by an appropriate definition of resilience and associated metrics. In this article, a resilience definition is provided that meets a set of requirements with clear relationships to the metrics of the relevant abstract notions of reliability and risk. Those metrics also meet logically consistent requirements drawn from measure theory, and provide a sound basis for the development of effective decision-making tools for multihazard environments. Improving the resiliency of a system to meet target levels requires the examination of system enhancement alternatives in economic terms, within a decision-making framework. Relevant decision analysis methods would typically require the examination of resilience based on its valuation by society at large. The article provides methods for valuation and benefit-cost analysis based on concepts from risk analysis and management. The figure below provides a representation of resilience.
Climate Change: Its Impacts on Washington, DC
The city of Washington, District of Columbia (DC) will face flooding, and eventual geographic changes, in both the short- and long-term future because of sea level rise (SLR) brought on by climate change, including global warming. To fully assess the potential damage, a linear model was developed to predict SLR in Washington, DC, and its results compared to other nonlinear model results. Using geographic information systems (GIS) and graphical visualization, analytical models were created for the city and its underlying infrastructure. Values of SLR used in the assessments were 0.1 m for the year 2043 and 0.4 m for the year 2150 to model short-term SLR; 1.0 m, 2.5 m, and 5.0 m were used for long-term SLR. All necessary data layers were obtained from free data banks from the U.S. Geological Survey and Washington, DC government websites. Using GIS software, inventories of the possibly affected infrastructure were made at different SLR. Results of the analysis show that low SLR would lead to a minimal loss of city area. Damages to the local properties, however, are estimated at an assessment value of at least US$2 billion based on only the direct losses of properties listed in real estate databases, without accounting for infrastructure damages that include military installations, residential areas, governmental property, and cultural institutions. The projected value of lost property is in excess of US$24.6 billion at 5.0 m SLR. The Washington Post reported on this effort as follows (worst-case scenario): “A powerful hurricane making landfall around Virginia Beach would push loads of water into the Chesapeake Bay, causing a massive storm surge up the Potomac. Here is what a 16-foot rise in water level might look like, according to a 2011 study led by a University of Maryland professor.” The reported map is provided below.
Sustainable Construction and Manufacturing: Measurement Science
The term sustainability has many definitions in varied contexts. The development of metrics requires an examination of these definitions in terms of their hierarchical and nesting relationships. An understanding of these relationships could offer a basis for introducing requirements and ultimately the adoption of working sustainability definitions for construction and manufacturing. A comparative examination of these definitions revealed that the general definition by the American Society of Civil Engineers (ASCE 2009), “Sustainable Development is the challenge of meeting human needs for natural resources, industrial products, energy, food, transportation, shelter, and effective waste management while conserving and protecting environmental quality and the natural resource base essential for future development,” provides a reasonable basis for metrics. Also, the Organization for Economic Cooperation and Development (OECD 2009) provides a suitable manufacturing centric definition as “Reducing the intensity of materials use, energy consumption, emissions, and the creation of unwanted by-products while maintaining, or improving, the value of products to society and to organizations;” whereas Sassi (2006) provides a suitable construction centric definition as “building practices, which strive for integral quality (including economic, social and environmental performance) in a very broad way. Thus, the rational use of natural resources and appropriate management of the building stock will contribute to saving scarce resources, reducing energy consumption (energy conservation), and improving environmental quality.” Sustainability definitions that meet a set of requirements are necessary for developing metrics and valuation methods. Current practices represent sustainability using the traditional spider diagram and using metrics based on indices. The ongoing efforts focus on new quantification methods suitable for valuation and tradeoffs.