The use of decision support systems to address spatial variability, uncertainty, and risk

被引:0
|
作者
Knowlton, RG [1 ]
Peterson, DM [1 ]
Zhang, HB [1 ]
机构
[1] Duke Engn & Serv Inc, Albuquerque, NM 87110 USA
关键词
geostatistics; groundwater; modeling; decision analysis; decision support; uncertainty; environmental; hydrologic; operations research; sampling design;
D O I
10.1520/STP10917S
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
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, SamplingFX(2) and GroundwaterFX(2), 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.
引用
收藏
页码:109 / 121
页数:13
相关论文
共 50 条
  • [31] Uncertainty Management for Rule-based Decision Support Systems
    Mahesar, Quratul-Ain
    Dimitrova, Vania G.
    Magee, Derek R.
    Cohn, Anthony G.
    2017 IEEE 29TH INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE (ICTAI 2017), 2017, : 884 - 891
  • [32] Modeling uncertainty in decision support systems for customer call center
    Holland, A
    Computational Intelligence, Theory and Applications, 2005, : 763 - 770
  • [33] Managing Epistemic Uncertainty for Multimodels of Sociotechnical Systems for Decision Support
    Pennock, Michael J.
    Gaffney, Christopher
    IEEE SYSTEMS JOURNAL, 2018, 12 (01): : 184 - 195
  • [34] Spatial decision support systems for the management of informal settlements
    Dept of Geomatics, University of Cape Town, Rondebosch 7701, South Africa
    Comput Environ Urban Syst, 3-4 (189-208):
  • [35] INTERACTIVE ANALYTICAL DISPLAYS FOR SPATIAL DECISION SUPPORT SYSTEMS
    ARMSTRONG, MP
    LOLONIS, P
    AUTO CARTO 9 : NINTH INTERNATIONAL SYMPOSIUM ON COMPUTER-ASSISTED CARTOGRAPHY, 1989, : 171 - 180
  • [36] Dealing with location uncertainty in mobile networks using contextual Fuzzy Cognitive Maps as spatial decision support systems
    Jamadagni, NSS
    IEEE VEHICULAR TECHNOLOGY CONFERENCE, FALL 2000, VOLS 1-6, PROCEEDINGS: BRINGING GLOBAL MOBILITY TO THE NETWORK AGE, 2000, : 1489 - 1492
  • [37] Spatial decision support systems. Principles and practices
    Jones, Laurence
    INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE, 2013, 27 (05) : 1045 - 1047
  • [38] Relational Algebra in Spatial Decision Support Systems Ontologies
    Diomidous, Marianna
    Chardalias, Kostis
    Koutonias, Panagiotis
    Magnita, Adrianna
    Andrianopolos, Charalampos
    Zimeras, Stelios
    Mechili, Enkeleint Aggelos
    INFORMATICS EMPOWERS HEALTHCARE TRANSFORMATION, 2017, 238 : 243 - 245
  • [39] A framework for model integration in spatial decision support systems
    Taylor, K
    Walker, G
    Abel, D
    INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE, 1999, 13 (06) : 533 - 555
  • [40] On the use of risk and decision analysis to support decision-making
    Aven, T
    Korte, J
    RELIABILITY ENGINEERING & SYSTEM SAFETY, 2003, 79 (03) : 289 - 299