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Hydrogeological engineering approaches to investigate and characterize heterogeneous aquifers

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Please use this identifier to cite or link to this item: http://hdl.handle.net/1928/10306

Hydrogeological engineering approaches to investigate and characterize heterogeneous aquifers

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Title: Hydrogeological engineering approaches to investigate and characterize heterogeneous aquifers
Author: Harp, Dylan
Advisor(s): Thomson, Bruce
Committee Member(s): Vesselinov, Velimir
Stormont, John
Weissmann, Gary
Department: University of New Mexico. Dept. of Civil Engineering
Subject(s): hydrogeology
parameter estimation
LC Subject(s): Aquifers--Analysis--Statistical methods.
Aquifers--Mathematical models.
Hydrogeology--Statistical methods.
Parameter estimation.
Degree Level: Doctoral
Abstract: This dissertation presents a compilation of five stand-alone manuscripts (Chapters 2 through 5 and Appendix A). Chapters 2 through 5 present hydrogeological analysis approaches, while Appendix A is utilized within the dissertation introduction as an example of a non-physically based modeling approach, albeit demonstrated on a non-hydrogeologically based application. Chapter 2 presents an inverse approach to decompose pumping influences from water-level fluctuations observed at a monitoring location. Chapter 3 presents an inferencing approach to identify effective aquifer properties at the interwell scale that can be applied to highly transient datasets. Chapter 4 introduces the use of a Markov-chain model of spatial correlation to an automated geostatistical inverse framework, demonstrating the approach on a 2-D two-stratigraphic-unit synthetic aquifer. Chapter 5 utilizes the inverse framework introduced in Chapter 4 to develop a stochastic analysis approach to identify the most plausible geostatistical model given the available data. The dissertation introduction reconciles these hydrogeological engineering approaches within the context of the current hydrogeological perspective, discussing where these approaches within the often conflicting goals of providing operational decision support based on modeling and advancing the science of hydrogeology beyond its current limitations.
Graduation Date: December 2009
URI: http://hdl.handle.net/1928/10306

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