Civil Engineering ETDs

Author

Dylan Harp

Publication Date

2-9-2010

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.

Keywords

Aquifers--Analysis--Statistical methods, Aquifers--Mathematical models, Hydrogeology--Statistical methods, Parameter estimation.

Sponsors

Los Alamos National Laboratory

Document Type

Dissertation

Language

English

Degree Name

Civil Engineering

Level of Degree

Doctoral

Department Name

Civil Engineering

First Advisor

Thomson, Bruce

First Committee Member (Chair)

Vesselinov, Velimir

Second Committee Member

Stormont, John

Third Committee Member

Weissmann, Gary

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