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Decision Support and Scenario Evaluation Using QnD Methodology: Case Studies in Risk Assessment by and Software Tools for Risk−Based Decision Making and Scenario Planning by
Thursday, July 7, 2005
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Decision Support and Scenario Evaluation Using QnD Methodology: Case Studies in Risk Assessment Gregory Kiker Summary: The Questions and Decisions (QnD) model system has been developed as a spatially explicit risk assessment tool which combines both number-based calculations and value-style judgments. It can integrate technical data with ideas that are estimated from expert knowledge and experience. A specific QnD version is constructed through structured conversations with experts, stakeholders and decision-makers. The wishes of the stakeholders are created through configurable objects designed to be quickly made and quickly altered through subsequent learning and iteration. QnD-simulated ecosystems are represented by combinations of component, process and data objects that are constructed through the use of XML-based input files. This design allows different ecosystem/habitat/organism/chemical combinations to be efficiently formed, simulated and documented. Unlike traditional decision support systems that direct outputs at a discipline-specific management, the model has been created as a game to stimulate discussions and analysis among managers, scientists and stakeholders who are working increasingly closely within an adaptive management context. Several case studies using QnD and scenario gaming are provided showing the utility of the tool within the scenario analysis process. These case studies will include the following:
Biography: Dr. Greg Kiker is an assistant professor in the Agricultural and Biological Engineering Department at the University of Florida (UF) specializing in ecological and hydrological modeling. From 2002 through 2005, Dr Kiker conducted environmental risk research at the Engineer Research and Development Center (ERDC), US Army Corps of Engineers. While at ERDC, he was Team Leader of the Environmental Risk and Decision Analysis Team exploring multi-criteria decision analysis methods and ecological modeling for both civil and military applications. At UF, his current research projects include ecosystem and invasive species modeling, decision support systems and practical linkages of risk analysis, adaptive management and multi-criteria decision analysis. Dr Kiker was a Fulbright Scholar and received his PhD from Cornell University in Agricultural and Biological Engineering in 1998. From 1998 to 2002, Dr Kiker was a Senior Lecturer at the University of KwaZulu-Natal, South Africa where he conducted ecological/hydrological modeling and climate change research. He has consulted internationally in the use of ecological and environmental models for ecosystem management, crop yield prediction, nutrient-transport, and climate change.. Software Tools for Risk−Based Decision Making and Scenario Planning Terry Sullivan Alexandre Grebenkov Igor Linkov Summary: Environmental contamination of lands is wide spread and often requires remediation prior to reuse of the land. Decisions made about site−specific land use planning and remediation alternatives are based on a variety of factors. Risk from chemical exposures for humans and wildlife are often weighed against future use value, remediation cost, technical feasibility, and political considerations. Risk analysis techniques to support decision making have been implemented into software tools that address human and ecological risks, cost/benefit, and societal issues. Often this has led to large system models that contain submodels for all of the possible conditions that could occur. The software is often cumbersome to use and contains information requirements (data) for processes and events that are irrelevant to the problem at hand. In addition, they often do not treat explicitly the impact of uncertainties on the decision process. This panel presentation will cover the newest developments in software tools for providing decision support for land use planning for environmentally contaminated sites. The presentation will emphasize improvements in the treatment of uncertainty and producing more flexible and easy to use tools for decision support. Presentations will cover a) ARAMS (Army Risk Assessment and Modeling System), b) advances in decision support tools for remediation/restoration of contaminated lands, and c) progress on Multi Criteria Decision Analysis tools for contaminated land reuse. Biography : Dr. Sullivan is a member of the Environmental Research and Technology Division staff at Brookhaven National Laboratory. Dr. Sullivan joined BNL in 1983 and has gained national and international recognition for his work on source term assessment for near surface radioactive waste disposal. Dr. Sullivan’s primary research interest is in the application and development of models for soil and groundwater contamination problems. For the Nuclear Regulatory Commission he has developed six different computer models to perform source tern analysis and predict subsurface fate and transport from shallow land disposal facilities. These models have gained international acceptance and use. Dr. Sullivan has provided several International Atomic Energy Agency (IAEA) courses on low-level waste source term analysis and has been a technical expert for the IAEA on five missions. He is a member of the National Council on Radiation Protections subcommittee on safety assessment of radioactive waste disposal facilities. Dr. Sullivan’s other research interests are in risk assessment and management and the use of decision support software to assist in defining clean-up goals in environmental remediation problems. He worked with the Department of Energy’s Center for Risk Excellence on a wide range of risk related issues. He was the principal investigator, for the Environmental Protection Agency, in an Environmental Technology Verification study of decision support software. For DOE and EPA he has prepared 3 state of the art reviews for decision support software and has organized and chaired a NATO session on this topic. Dr. Sullivan is currently the principal investigator for a program that examines human health risks associated with mercury deposition resulting from coal-fired power plants. Dr. Igor Linkov, a Senior Risk Assessor with Cambridge Environmental Inc. and Adjunct Professor in the Department of Engineering and Public Policy at Carnegie Mellon University. He received his PhD in environmental and occupational health from University of Pittsburgh. His educational experience also includes Post-Doctoral Fellowship at Harvard University. Dr. Linkov has managed ecological risk assessments and contributed to human health risk assessment at several Superfund sites. He has developed models and software to support ecological risk assessment and population modeling for contaminated sites. Dr. Linkov currently supports development of the Army Risk Assessment Modeling System (ARAMS). One of the focuses of his current research is integrating risk assessment and multi-criteria decision analysis tools in managing contaminated sites. He is currently developing the Questions and Decision (QnD) model for environmental management at contaminated and disturbed sites for the US Army Corps of Engineers. He has published widely on environmental policy, environmental modeling, and risk analysis, including seven books and over 70 peer-reviewed papers and book chapters. Dr. Linkov has directed and chaired seven international conferences on risk assessment and modeling and participated in organizing many others. Dr. Linkov serves as a Scientific Advisor to the Toxic Use Reduction Institute, a position which requires nomination by the Governor of Massachusetts. Dr. Linkov is President for the Society for Risk Analysis-New England. He is Founding Chair of the SRA Decision Analysis and Risk Specialty Group. He also is the Past Chair of the SRA Ecological Risk Assessment Specialty Group and participates in several SRA and SETAC Committees. Dr. Linkov has served on many review and advisory panels for US and international agencies. |
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