HR: 1340h
AN: H13B-0413    [Abstracts]
TI: Characterizing the K-field in a Spatial Domain Using Fuzzy and Case-Based Spatial Reasoning
AU: * Ross, J
EM: jlross@uvm.edu
AF: Research Center for Groundwater Remediation Design, University of Vermont, 213 Votey Building, Burlington, VT 05405 United States
AU: Ozbek, M
EM: ozbek@emba.uvm.edu
AF: Research Center for Groundwater Remediation Design, University of Vermont, 213 Votey Building, Burlington, VT 05405 United States
AU: Pinder, G F
EM: pinder@emba.uvm.edu
AF: Research Center for Groundwater Remediation Design, University of Vermont, 213 Votey Building, Burlington, VT 05405 United States
AB: Kriging is widely used for the estimation of spatially distributed variables such as hydraulic conductivity. Relying on given measurements of hydraulic conductivity, the kriging system interpolates values to any location in the domain with minimal estimation error. However, the kriging system fails to respect the variable's true spatial dispersion, as it generally produces a smoother-than-reality contour map of values. Furthermore, the estimations of values in areas where few measurements exist are highly suspect. A promising alternative to kriging is the application of expert knowledge in the form of fuzzy rules. With an understanding of the available measurement data, an expert may be able to make statements related to the variable, using fuzzy terms such as {\bf near}, {\bf about 5 meters}, and {\bf roughly 10 m/day}. In the case of hydraulic conductivity the fuzzy rules may tap into the knowledge that experts possess regarding {\it spatial relations} amongst geologic entities. For example, a typical statement may be {\it If a body of clay exists in the northeast section of the domain, then there exists a silty-clay formation about 5 meters to the southwest.} The expert may also describe {\it hydrological relations} between soil types and hydraulic conductivity values such as in the expression {\it If soil type is clay, then hydraulic conductivity is low.} A case-based reasoning system may be used to supplement the expert statements by adding information that cannot be captured by expert knowledge. In this approach a fuzzy retrieval algorithm in the system would find previously studied and documented spatial domains similar to the domain of interest with the intent of harvesting information concerning the possible geologic make-up and hydraulic conductivity field of our spatial domain. Thus, while kriging is restricted to the available measurements, the expression of expert knowledge through fuzzy rules and the information from previous cases supplements the {\it a priori} data to provide an enhanced representation of the field.
DE: 1829 Groundwater hydrology
SC: Hydrology [H]
MN: 2004 AGU Fall Meeting