STP1420: The Use of Decision Support Systems to Address Spatial Variability, Uncertainty, and Risk

    Knowlton, RG
    Duke Engineering and Services, Inc., Albuquerque, NM

    Peterson, DM
    Duke Engineering and Services, Inc., Albuquerque, NM

    Zhang, H
    Duke Engineering and Services, Inc., Albuquerque, NM

    Pages: 13    Published: Jan 2003


    Abstract

    Traditional methods of characterizing contaminated waste sites and evaluating cleanup alternatives generally utilize conservative methods that may not produce optimal results. With the advent of powerful desktop computers, advanced database management tools, sophisticated graphical display capabilities, new statistical methods, as well as decision analysis methods, there is a greater opportunity to employ decision support systems to address spatial variability, uncertainty, sampling efficiency, risk and cost-benefit needs. Several decision support systems have been developed in the past few years that can address these needs directly, and help decision-makers evaluate their environmental liabilities and alternatives for action in a more efficient manner. EPA recognized the value of these new tools in the decision making process and instituted a review of Decision Support Systems. The EPA's Environmental Technology Verification (ETV) program is designed to peer-review innovative technologies for acceptability of use. ETV then publishes these reviews, along with verification certificates, to facilitate more rapid acceptance of the technologies. Two decision support tools that were evaluated by the ETV program, SamplingFX2 and GroundwaterFX2, will be discussed in this paper, along with examples of the use of the tools for decision making purposes. The SamplingFX toolkit utilizes geostatistical analysis techniques and operations research methods to quantify uncertainty in the nature and extent of soil contamination, as well as optimizing the number and location of samples required for characterization. The GroundwaterFX toolkit utilizes Monte Carlo simulation techniques and operations research methods to quantify uncertainty in the nature and extent of groundwater contamination, as well as optimizing the number and location of monitoring wells required for characterization, and evaluating groundwater remediation strategies.

    Keywords:

    geostatistics, groundwater, modeling, decision analysis, decision support, uncertainty, environmental, hydrologic, operations research, sampling design


    Paper ID: STP10917S

    Committee/Subcommittee: D18.01

    DOI: 10.1520/STP10917S


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