James H. Lambert

A Survey of Approaches for Assessing and Managing the Risk of Extremes

In this paper, we review methods for assessing and managing the risk of extreme events, where “extreme events” are defined to be rare, severe, and outside the normal range of experience of the system in question. First, we discuss several systematic approaches for identifying possible extreme events. We then discuss some issues related to risk assessment of extreme events, including what type of output is needed (e.g., a single probability vs. a probability distribution), and alternatives to the probabilistic approach. Next, we present a number of probabilistic methods. These include: guidelines for eliciting informative probability distributions from experts; maximum entropy distributions; extreme value theory; other approaches for constructing prior distributions (such as reference or noninformative priors); the use of modeling and decomposition to estimate the probability (or distribution) of interest; and bounding methods. Finally, we briefly discuss several approaches for managing the risk of extreme events, and conclude with recommendations and directions for future research.

Scenario and multiple criteria decision analysis for energy and environmental security of military and industrial installations

Military and industrial facilities need secure and reliable power generation. Grid outages can result in cascading infrastructure failures as well as security breaches and should be avoided. Adding redundancy and increasing reliability can require additional environmental, financial, logistical, and other considerations and resources. Uncertain scenarios consisting of emergent environmental conditions, regulatory changes, growth of regional energy demands, and other concerns result in further complications. Decisions on selecting energy alternatives are made on an ad hoc basis. The present work integrates scenario analysis and multiple criteria decision analysis (MCDA) to identify combinations of impactful emergent conditions and to perform a preliminary benefits analysis of energy and environmental security investments for industrial and military installations. Application of a traditional MCDA approach would require significant stakeholder elicitations under multiple uncertain scenarios. The approach proposed in this study develops and iteratively adjusts a scoring function for investment alternatives to find the scenarios with the most significant impacts on installation security. A robust prioritization of investment alternatives can be achieved by integrating stakeholder preferences and focusing modeling and decision-analytical tools on a few key emergent conditions and scenarios. The approach is described and demonstrated for a campus of several dozen interconnected industrial buildings within a major installation.

Integration of Decision Analysis and Scenario Planning for Coastal Engineering and Climate Change

This paper develops a methodology for eliciting shifts in preference across future scenarios in the performance assessment of infrastructure policies and investments. The methodology quantifies the robustness of alternative portfolios across a variety of scenarios and identifies the scenarios that greatly affect the assessments. An innovation of the methodology is to elicit, for each scenario, only a few relative increases or decreases in importance of selected terms of the value function, which is more efficient than a full elicitation of the value function for each scenario. The identification of critical scenarios via our methodology can be used to focus resource-intensive and potentially costly modeling activities. The methodology integrates preference orders, centroid weights, and the Borda method. In a demonstration, the methodology assesses the relative sea level and other climate-change scenarios that could affect the performance of coastal protections.

Scenario‐based multiple criteria analysis for infrastructure policy impacts and planning

The consideration of emergent scenarios of economy, environment, technology, etc. is mandated by the US Department of Transportation for long‐range transportation planning of infrastructure that will involve federal funding. This paper develops a practical methodology of scenario‐based planning within a multi‐criteria decision aid to support the comparison of transportation policies across state, regional, and local agencies. The methodology is demonstrated in a case study. First, we review existing methods and practices of scenario‐based planning. Second, we perform a limited survey of select Metropolitan Planning Organizations on their concerns for emergent scenarios. Third, we develop the methodology for scenario‐based reweighting of an additive value function. Fourth, we demonstrate the methodology in four regions in the Commonwealth of Virginia. The paper builds in part on an existing approach to adjust the weights performance criteria based on scenarios. Our approach uses emergent scenarios to reweight multiple performance criteria with an efficient use of survey/expert information.

Evaluating deep uncertainties in strategic priority-setting with an application to facility energy investments

A recent paper in this journal described the identification and integration of sources of risk in a systems engineering process model [Lambert, Jennings, and Joshi, Syst Eng 9(3) (2006), 187–198]. The earlier effort falls short in addressing sources of deep, nonprobabilistic uncertainty that should enter to strategic systems design and reengineering. Our new paper incorporates the earlier effort to a framework for evaluating which are the deep uncertainties that most influence a priority-setting among investments in large-scale systems with multiple stakeholders, and therefore warrant more investigation. The framework addresses that deep uncertainties are continuously discovered and reflective of diverse and unique stakeholder experiences, knowledge bases, and advocacy positions. Deep uncertainties are epistemic viewpoints across which the strategic priorities for investments will differ. The framework modifies existing tools of scenario analysis and multicriteria analysis to process and filter the deep uncertainties. The framework is demonstrated in an application to reengineering of an energy system for a defense installation where frequent outages are disruptive to scientific and other missions. The sources of deep uncertainty in the demonstration include regulatory, economic, environment, cyber-threat, and others. The investments include innovative microturbine and microgrid technologies. An example of a result is that international economic disruption is relatively more influential than cyber-threats to strategic priority-setting for investing in a microgrid at the particular installation. ©2012 Wiley Periodicals, Inc. Syst Eng 15

Prioritizing Infrastructure Investments in Afghanistan with Multiagency Stakeholders and Deep Uncertainty of Emergent Conditions

The Afghanistan National Development Strategy identified billions of dollars of needs for transportation, water, energy, telecommunications, and other necessary infrastructure development for the rebuilding of Afghanistan. With economic sustainability as a primary aim, the coordination and prioritization of investments has been a challenge in part because of Afghanistan’s volatile security situation along with the intricacies of the negotiating and coordinating efforts of numerous stakeholders. An understanding of the contributions of infrastructure systems and associated projects to the national development strategy is needed. This paper formulates a scenario-informed multicriteria approach to prioritize major project investments for infrastructure development subject to deep, nonprobabilistic uncertainties. The methods are inclusive of stakeholder values and accounts for deep uncertainties in governance, security, economy, environment, workforce, and other topics. The methods are applied in Afghanistan’s Nangarhar province to assist in the selection among twenty-seven candidate infrastructure projects that are vulnerable to potential refugee immigration among other emergent conditions. The paper describes the relationships of selected projects to strategic goals while facilitating collaboration among government and nongovernment investors, donors, technologists, and other stakeholders.

DECISION AID FOR ALLOCATION OF TRANSPORTATION FUNDS TO GUARDRAILS

We address the need for allocation of resources to run-off-road and fixed-object hazards on immense secondary road systems. In Virginia, there are 95,000km of roadway with uncharacterized hazards in need of guardrail upgrade, installation, or related warning signs or other protection. A decision aid is developed to assist the planner in guardrail resource allocation by accounting for the potential crash severities, traffic exposures, costs of treatment, and other factors. A premise is that no single benefit-cost ratio or selection criterion applies across all localities. The decision aid enables the planner to interpret the variety of benefits and costs in their own units, emphasizing the needs and preferences of individual localities. The paper describes: (1) archiving and comparison of protected and unprotected hazards; (2) regional screening of hazardous corridors and (3) multicriteria benefit-cost analyses of guardrail sites. A case study of guardrail selection is presented.

Population behavioral scenarios influencing radiological disaster preparedness and planning.

Considerable attention is focused on plans for sheltering or evacuating the population of the US national capital region in response to a regional emergency such as a terrorist attack or natural disaster. Such planning engages multiple disciplines spanning infrastructure engineering, emergency management, health care, mass communication, water and food supply, logistics, and others. Knowledge of population behaviors should influence the many dimensions of protection, prevention, response, and recovery. Of particular interest are the behaviors and needs of the resident and non-resident populations in the aftermath of a regional disaster, including those at home, at work, and traveling. The authors deployed a 30-min telephone survey to 2700 residents of the region to gain knowledge of their intended behaviors in the event of a variety of potential dirty bomb attacks. The survey provides a unique foundation for the current paper. The paper will identify and model the assumptions of population behaviors that most affect agency priorities for emergency planning including regional sheltering and evacuation following a radiological disaster such as a dirty bomb. The technical approach assessed several planning initiatives across performance criteria derived from strategic plans and applied combinations of behavioral assumptions to vary the relative importance of each criterion. The results reveal the behavioral scenarios that are most significant to the prioritization of planning initiatives and identify the highest and lowest priority initiatives across the criteria used.

Climate change scenarios: risk and impact analysis for Alaska coastal infrastructure

Climate change has the potential to impose severe stress on coastal environments. Alaskan coastlines are especially vulnerable to erosion and other changes that have led to significant damage and threats to infrastructure, human health and safety, and economic prosperity. This paper describes an integration of scenario analysis with multi-criteria decision analysis to prioritise the vulnerability of communities for the development of infrastructure protection and other actions. The approach allows stakeholders to account for uncertainty in the prioritisation and also includes value judgements of the multiple relevant stakeholders. We present a case study that evaluates several climate change scenarios and formulates metrics for finding scenarios that most impact priorities. Scenarios including sea-level rise, increased frequency of forest fires, permafrost melting, and others are used. We find the increased frequency of forest fires to be the most upsetting scenario along with four communities that are identified as highly vulnerable and not sensitive to the scenarios.

Climate Change Influence on Priority Setting for Transportation Infrastructure Assets

Transportation infrastructure could be vulnerable to local manifestations of global climate change, such as storm frequencies and durations of seasons. To adapt, transportation agencies need methodologies for reprioritizing their assets subject to the new sources of vulnerability. Prioritizing assets is nontrivial when criteria assessments and owner/operator preferences are considered in conjunction with the possible climate scenarios. Few efforts to date have addressed these scenarios in a priority setting for infrastructure asset management in the literature. This paper extends a scenario-based multicriteria decision framework that can assist decision makers in effectively allocating limited resources to adapt transportation assets to a changing climate. The framework is demonstrated with one of the most susceptible metropolitan transportation systems in the United States, the Hampton Roads region in coastal southeastern Virginia. First, the high-level goals of a long-range transportation plans are used in a traditional multicriteria analysis to generate a baseline prioritization of assets. Next, several scenarios that incorporate and combine a variety of climate conditions are identified. Finally, the scenarios are used to adjust the initial criteria weighting, which results in several reprioritizations of the assets. The results help to identify the most influential scenarios and characterize the sensitivity of the baseline prioritization across multiple scenarios. With these results, additional scientific and investigative efforts can be focused effectively to study and understand the influential scenarios.