9526888 Butler A considerable body of research has identified the spatial distribution of hydraulic conductivity as a significant control on the movement of contaminants in the subsurface. A number of theories have been developed to quantify the influence of spatial variation of hydraulic conductivity on contaminant transport using stochastic processes or fractal representations to model the conductivity variations. It is increasingly apparent , however, that the modeling of the conductivity variations at a site using, for example, the first two moments of a stationary stochastic process estimated from core data may have limitations in unites composed of a complex mixture of lithologies. Clearly, site-specific features of the hydraulic conductivity distribution of a larger scale need to be quantified in order to reliably predict contaminant movement in such systems. In particular, knowledge of the existence of laterally contiguous zones of high hydraulic conductivity, which serve as preferential flow paths, is often critical for the successful modeling of contaminant transport a site. The field identification of such somes, however, has proven to be a rather difficult task at site. The field identification of such zones, however, has proven to be a rather difficult task. Conventional field techniques only provide information of a highly averaged nature or information restricted to the immediate vicinity of the test well. The ultimate objective of the research proposed here is to develop a completely new field method for the estimation of spatial variations in hydraulic conductivity. Although developed for the general task of estimation of hydraulic conductivity variations in saturated formations, this method would be especially effective for the identification of preferential flow paths. This new methodology involves three primary elements: (1) a recently proposed methods for hydraulic tomography, (2) multilevel sampling wells commonly employed in large-scale tracer tests for obtaini ng vertically isolated water samples, and (3) miniature fiber-optic pressure sensors recentlydeveloped for biomedical applications. One of the primary constraints on the field application of hydraulic tomography has been the need for detailed information about vertical variations in pumping-induced head changes. The use of miniature fiber-optic pressure sensors in the small tubing of the multilevel samplers, however, should enable that constraint to be overcome and the considerable potential of hydraulic tomography to be realized. An initial one-year assessment of the methodology is the primary purpose of the work proposed here. This assessment will include a theoretical extension/analysis of the hydraulic tomography approach and a preliminary field evaluation of the methodology at a very heavily instrumented field site where some information about the interwell variations in hydraulic conductivity is available from a previous large-scale tracer test. The coupling of the detailed head data provided by miniature fiber-optic sensors in multilevel samplers with the tomographic inversion method has the potential of providing extremely useful information about the site-specific hydraulic features controlling contaminant transport. The incorporation of such features into a site model should dramatically improve the quality of the resulting model predictions, thus leading to more reliable risk assessments and a more efficient allocation of resources for site characterization and remediation activities. In addition, this methodology should produce much more detailed description of hydraulic conductivity variations than has previously been possible. These more detailed descriptions should help refine existing approaches for the modeling of conductivity variations and, hopefully, help better tie the conductivity variations to their geologic basis. ??

Agency
National Science Foundation (NSF)
Institute
Division of Earth Sciences (EAR)
Type
Standard Grant (Standard)
Application #
9526888
Program Officer
L. Douglas James
Project Start
Project End
Budget Start
1996-04-01
Budget End
1997-03-31
Support Year
Fiscal Year
1995
Total Cost
$49,998
Indirect Cost
Name
University of Kansas Main Campus
Department
Type
DUNS #
City
Lawrence
State
KS
Country
United States
Zip Code
66045