Fuzzy Inference for Hydraulic Conductivity Estimation

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XVI International Conference on Computational Methods in Water Resources (CMWR-XVI) Ingeniørhuset

Fuzzy Inference for Hydraulic Conductivity Estimation
Paper
Author:James Ross <jlross@uvm.edu> (University of Vermont)
George Pinder <pinder@cems.uvm.edu> (University of Vermont)
Metin Ozbek <ozbek@cems.uvm.edu> (University of Vermont)
Presenter:James Ross <jlross@uvm.edu> (University of Vermont)
Date: 2006-06-18     Track: General Sessions     Session: General
DOI:10.4122/1.1000000365
DOI:10.4122/1.1000000366

A representation of hydraulic conductivity is most vital to the accurate modeling of groundwater flow. However, in practical applications, hydraulic conductivity measurements are few, while information on soil type and grain size is relatively abundant. The relationship between hydraulic conductivity and the above soil parameters is imprecise and should be modeled as such using fuzzy logic. A fuzzy inference system is proposed whereby grain size distributions and field observations are used to estimate hydraulic conductivity values. To rectify the shortcomings of preferential spatial sampling, spatial fuzzy geologic relationships are defined to infer the location of stratigraphic units from the locations of soil samples. Such relationships, founded upon an expert understanding of hydrogeology, increase the amount of available soil type data, which, in turn, increases the number of hydraulic conductivity estimates. The result is a thoroughly “sampled” domain and consequent hydraulic conductivityy field for input to a numerical simulator.