Groundwater Transport Modeling Using Fuzzy Sets and Fuzzy Logicby James L. Ross,
George F. Pinder,
Metin M. Ozbeck,
Abstract: Modeling of groundwater flow and transport is inherently uncertain. The predictive capability of the model depends upon both the quantity and quality of hydrogeologic data. The introduction of expert knowledge of the subsurface as a supplement to available field data can bolster the amount of subsurface information. The characterization of this combined body of knowledge using fuzzy logic and fuzzy set theory provides a measure of overall data quality. An important advantage of the fuzzy-based approach is that interpretations of fuzzy-based uncertainty are significantly more intuitive than stochastic uncertainty measures. Traditional modeling procedures cannot employ fuzzy data, and a new framework for groundwater modeling with fuzzy information must be developed. In our approach we employ an integrated strategy that generates a fuzzy-based hydraulic conductivity field and then combines it with a fuzzy-based groundwater modeling process to produce fuzzy number concentration values. The resulting concentration field incorporates both random value based and lack of knowledge based uncertainty.
Subject Headings: Fuzzy sets | Hydrologic models | Data processing | Uncertainty principles | Groundwater | Groundwater flow | Subsurface environment | Information management
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