Pilot Valley, located in the eastern Basin and Range, north of Wendover, UT, contains numerous shorelines and depositional remnants of late Pleistocene Lake Bonneville. These remnants present classic ground penetrating radar (GPR) targets due to their coherent stratification, low clay, low salinity, and low moisture content. Three-dimensional (3D) GPR imaging can resolve fine-scale stratigraphy of these deposits down to a few centimeters. While lake levels fluctuated due to flooding events, climatic changes were the dominant factor in controlling lake levels. In Pilot Valley, the paleowind entered from the northwest, with storms coming from the south, and circulated clockwise around the basin, forming offshore sand bars. On the western side of the valley, a uniquely well-preserved interpreted regressive phase beach deposit, dated late Pleistocene, is hypothesized to have been a point bar shortly after the Provo Shoreline period. 3D GPR data, measured stratigraphic sections, cores, mineralogical analysis, and the collection of gastropod samples for radiocarbon dating constrain a reconstruction of the deposit's depositional environment and local paleoclimate for Lake Bonneville. The GPR images, visualized with state-of-the-art petroleum industry tools, reveal fine-scale stratigraphic detail that can be analyzed using seismic stratigraphy concepts. Our study provides a comprehensive model for ancient pluvial lake-shore depositional environments in a Basin and Range setting using an integration of geological and geophysical data.

The internal architecture of a beach system can provide clues into the processes involved in its formation, including depositional processes, and/or driving mechanisms (Billy et al., 2014). Several unique events such as cold fronts or Hurricane Irma caused conditions that resulted in erosion and accretion changes in Red Reef Beach - Boca Raton, throughout the year of 2017. Since the lateral extent of these changes is difficult to evaluate using traditional methods such as coring, a Ground Penetrating Radar (GPR) was tested, which allows for a good lateral resolution (cm scale), to image the distribution and evolution of these sediments. The objectives of this study were to 1) explore the lateral variability in the internal architecture of sediments in Red Reef beach in Boca Raton (FL) using an array of ground penetrating radar (GPR) measurements constrained with coring and sediment analysis; 2) explore how dynamics of erosion and accretion induced by changes in wave activity and related to tide variation and storm events, may affect surface topography and the sedimentary internal architecture of beach deposits, using RTK GPS and GPR time-lapse measurements; 3) to explore changes in the lateral extent of the freshsaltwater interface along the beach profile in relation to tide variation and storm events. Reflectors identified in the GPR images showed some evidence of erosional and accretionary surfaces preserved in Red Reef beach. These measurements were repeated over time coinciding with certain events (such as Hurricane Irma) to explore their effects in terms of sediment erosion and accretion as reflected in changes in topography (using time-lapse GPS-RTK measurements), and changes in the internal sedimentary architecture (using time-lapse GPR measurements). The datasets collected also revealed the temporal evolution of the salt-freshwater interface, showing how the lateral extent of saltwater saturated sediment (inferred from areas of GPR signal attenuation along the profiles) evolved over time. This study shows the potential of GPR to provide information about beach sediment processes and dynamics at resolutions beyond traditional measurements (such as coring). It also shows the importance of combining methods that are complementary, such as the use of RTK GPS to explore changes in topography, and GPR that provides information on subsurface sedimentary architecture and the mechanism of change such as post-storm recovery. This study has implications for better understanding changes in coastal sedimentary deposits and processes, both at the subsurface, particularly after high-energy events, such as hurricanes, that result in rapid changes in erosion and/or accretion of sediments. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2017. / FAU Electronic Theses and Dissertations Collection

Ground penetrating radar (GPR) is a promising technique for humanitarian demining applications as it permits providing useful information about the subsurface based on wave reflections produced by electromagnetic (EM) contrasts. Yet, landmine detection using GPR can suffer from: (1) clutter, i.e, undesirable effects from antenna coupling, system ringing and soil surface and subsurface reflections; (2) false alarms, e.g., reflections from buried mine-like objects such as stones or metallic debris; (3) effects of soil properties on the GPR performance, such as attenuation. This thesis addresses these topics in an integrated approach aiming at reducing clutter, identifying landmines from false alarms and analysing GPR performance. For subtracting undesirable reflections, a new physically-based filtering algorithm is developed, which takes into account major antenna effects and soil surface reflection. It is applied in conjunction with a change detection algorithm for enhancing landmine detection. Landmine identification is performed using discriminant characteristics extracted from the pre-filtered data by a novel feature extraction approach in the time-frequency domain. For analysing the effects of soil properties, in particular soil dielectric permittivity, an EM model is coupled to pedotransfer functions for estimating the GPR performance on a given soil. The developed algorithms are validated using data acquired by two different hand-held GPR systems. Promising results are obtained under laboratory and outdoor conditions, where different types of soil (including real mine-affected soils) and landmines (including improvised explosive devices) are considered.

Ground penetrating radar (GPR) is a promising technique for humanitarian demining applications as it permits providing useful information about the subsurface based on wave reflections produced by electromagnetic (EM) contrasts. Yet, landmine detection using GPR can suffer from: (1) clutter, i.e, undesirable effects from antenna coupling, system ringing and soil surface and subsurface reflections; (2) false alarms, e.g., reflections from buried mine-like objects such as stones or metallic debris; (3) effects of soil properties on the GPR performance, such as attenuation. This thesis addresses these topics in an integrated approach aiming at reducing clutter, identifying landmines from false alarms and analysing GPR performance. For subtracting undesirable reflections, a new physically-based filtering algorithm is developed, which takes into account major antenna effects and soil surface reflection. It is applied in conjunction with a change detection algorithm for enhancing landmine detection. Landmine identification is performed using discriminant characteristics extracted from the pre-filtered data by a novel feature extraction approach in the time-frequency domain. For analysing the effects of soil properties, in particular soil dielectric permittivity, an EM model is coupled to pedotransfer functions for estimating the GPR performance on a given soil. The developed algorithms are validated using data acquired by two different hand-held GPR systems. Promising results are obtained under laboratory and outdoor conditions, where different types of soil (including real mine-affected soils) and landmines (including improvised explosive devices) are considered.

Based on technological advances made within the past decades, ground-penetrating radar (GPR) has become a well-established, non-destructive subsurface imaging technique. Catalyzed by recent demands for high-resolution, near-surface imaging (e.g., the detection of unexploded ordnances and subsurface utilities, or hydrological investigations), the quality of today's GPR-based, near-surface images has significantly matured. At the same time, the analysis of oil and gas related reflection seismic data sets has experienced significant advances. Considering the sensitivity of attribute analysis with respect to data positioning in general, and multi-trace attributes in particular, trace positioning accuracy is of major importance for the success of attribute-based analysis flows. Therefore, to study the feasibility of GPR-based attribute analyses, I first developed and evaluated a real-time GPR surveying setup based on a modern tracking total station (TTS). The combination of current GPR systems capability of fusing global positioning system (GPS) and geophysical data in real-time, the ability of modern TTS systems to generate a GPS-like positional output and wireless data transmission using radio modems results in a flexible and robust surveying setup. To elaborate the feasibility of this setup, I studied the major limitations of such an approach: system cross-talk and data delays known as latencies. Experimental studies have shown that when a minimal distance of ~5 m between the GPR and the TTS system is considered, the signal-to-noise ratio of the acquired GPR data using radio communication equals the one without radio communication. To address the limitations imposed by system latencies, inherent to all real-time data fusion approaches, I developed a novel correction (calibration) strategy to assess the gross system latency and to correct for it. This resulted in the centimeter trace accuracy required by high-frequency and/or three-dimensional (3D) GPR surveys. Having introduced this flexible high-precision surveying setup, I successfully demonstrated the application of attribute-based processing to GPR specific problems, which may differ significantly from the geological ones typically addressed by the oil and gas industry using seismic data. In this thesis, I concentrated on archaeological and subsurface utility problems, as they represent typical near-surface geophysical targets. Enhancing 3D archaeological GPR data sets using a dip-steered filtering approach, followed by calculation of coherency and similarity, allowed me to conduct subsurface interpretations far beyond those obtained by classical time-slice analyses. I could show that the incorporation of additional data sets (magnetic and topographic) and attributes derived from these data sets can further improve the interpretation. In a case study, such an approach revealed the complementary nature of the individual data sets and, for example, allowed conclusions about the source location of magnetic anomalies by concurrently analyzing GPR time/depth slices to be made. In addition to archaeological targets, subsurface utility detection and characterization is a steadily growing field of application for GPR. I developed a novel attribute called depolarization. Incorporation of geometrical and physical feature characteristics into the depolarization attribute allowed me to display the observed polarization phenomena efficiently. Geometrical enhancement makes use of an improved symmetry extraction algorithm based on Laplacian high-boosting, followed by a phase-based symmetry calculation using a two-dimensional (2D) log-Gabor filterbank decomposition of the data volume. To extract the physical information from the dual-component data set, I employed a sliding-window principle component analysis. The combination of the geometrically derived feature angle and the physically derived polarization angle allowed me to enhance the polarization characteristics of subsurface features. Ground-truth information obtained by excavations confirmed this interpretation. In the future, inclusion of cross-polarized antennae configurations into the processing scheme may further improve the quality of the depolarization attribute. In addition to polarization phenomena, the time-dependent frequency evolution of GPR signals might hold further information on the subsurface architecture and/or material properties. High-resolution, sparsity promoting decomposition approaches have recently had a significant impact on the image and signal processing community. In this thesis, I introduced a modified tree-based matching pursuit approach. Based on different synthetic examples, I showed that the modified tree-based pursuit approach clearly outperforms other commonly used time-frequency decomposition approaches with respect to both time and frequency resolutions. Apart from the investigation of tuning effects in GPR data, I also demonstrated the potential of high-resolution sparse decompositions for advanced data processing. Frequency modulation of individual atoms themselves allows to efficiently correct frequency attenuation effects and improve resolution based on shifting the average frequency level. GPR-based attribute analysis is still in its infancy. Considering the growing widespread realization of 3D GPR studies there will certainly be an increasing demand towards improved subsurface interpretations in the future. Similar to the assessment of quantitative reservoir properties through the combination of 3D seismic attribute volumes with sparse well-log information, parameter estimation in a combined manner represents another step in emphasizing the potential of attribute-driven GPR data analyses. / Geophysikalische Erkundungsmethoden haben in den vergangenen Jahrzehnten eine weite Verbreitung bei der zerstörungsfreien beziehungsweise zerstörungsarmen Erkundung des oberflächennahen Untergrundes gefunden. Im Vergleich zur Vielzahl anderer existierender Verfahrenstypen ermöglicht das Georadar (auch als Ground Penetrating Radar bezeichnet) unter günstigen Standortbedingungen Untersuchungen mit der höchsten räumlichen Auflösung. Georadar zählt zu den elektromagnetischen (EM) Verfahren und beruht als Wellenverfahren auf der Ausbreitung von hochfrequenten EM-Wellen, das heisst deren Reflektion, Refraktion und Transmission im Untergrund. Während zweidimensionale Messstrategien bereits weit verbreitet sind, steigt gegenwärtig das Interesse an hochauflösenden, flächenhaften Messstrategien, die es erlauben, Untergrundstrukturen dreidimensional abzubilden. Ein dem Georadar prinzipiell ähnliches Verfahren ist die Reflexionsseismik, deren Hauptanwendung in der Lagerstättenerkundung liegt. Im Laufe des letzten Jahrzehnts führte der zunehmende Bedarf an neuen Öl- und Gaslagerstätten sowie die Notwendigkeit zur optimalen Nutzung existierender Reservoirs zu einer verstärkten Anwendung und Entwicklung sogenannter seismischer Attribute. Attribute repräsentieren ein Datenmaß, welches zu einer verbesserten visuellen Darstellung oder Quantifizierung von Dateneigenschaften führt die von Relevanz für die jeweilige Fragestellung sind. Trotz des Erfolgs von Attributanalysen bei reservoirbezogenen Anwendungen und der grundlegenden Ähnlichkeit von reflexionsseismischen und durch Georadar erhobenen Datensätzen haben attributbasierte Ansätze bisher nur eine geringe Verbreitung in der Georadargemeinschaft gefunden. Das Ziel dieser Arbeit ist es, das Potential von Attributanalysen zur verbesserten Interpretation von Georadardaten zu untersuchen. Dabei liegt der Schwerpunkt auf Anwendungen aus der Archäologie und dem Ingenieurwesen. Der Erfolg von Attributen im Allgemeinen und von solchen mit Berücksichtigung von Nachbarschaftsbeziehungen im Speziellen steht in engem Zusammenhang mit der Genauigkeit, mit welcher die gemessenen Daten räumlich lokalisiert werden können. Vor der eigentlichen Attributuntersuchung wurden deshalb die Möglichkeiten zur kinematischen Positionierung in Echtzeit beim Georadarverfahren untersucht. Ich konnte zeigen, dass die Kombination von modernen selbstverfolgenden Totalstationen mit Georadarinstrumenten unter Verwendung von leistungsfähigen Funkmodems eine zentimetergenaue Positionierung ermöglicht. Experimentelle Studien haben gezeigt, dass die beiden potentiell limitierenden Faktoren - systeminduzierte Signalstöreffekte und Datenverzögerung (sogenannte Latenzzeiten) - vernachlässigt beziehungsweise korrigiert werden können. In der Archäologie ist die Untersuchung oberflächennaher Strukturen und deren räumlicher Gestalt wichtig zur Optimierung geplanter Grabungen. Das Georadar hat sich hierbei zu einem der wohl am meisten genutzten zerstörungsfreien geophysikalischen Verfahren entwickelt. Archäologische Georadardatensätze zeichnen sich jedoch oft durch eine hohe Komplexität aus, was mit der wiederholten anthropogenen Nutzung des oberflächennahen Untergrundes in Verbindung gebracht werden kann. In dieser Arbeit konnte gezeigt werden, dass die Verwendung zweier unterschiedlicher Attribute zur Beschreibung der Variabilität zwischen benachbarten Datenspuren eine deutlich verbesserte Interpretation in Bezug auf die Fragestellung ermöglicht. Des Weiteren konnte ich zeigen, dass eine integrative Auswertung von mehreren Datensätzen (methodisch sowie bearbeitungstechnisch) zu einer fundierteren Interpretation führen kann, zum Beispiel bei komplementären Informationen der Datensätze. Im Ingenieurwesen stellen Beschädigungen oder Zerstörungen von Versorgungsleitungen im Untergrund eine große finanzielle Schadensquelle dar. Polarisationseffekte, das heisst Änderungen der Signalamplitude in Abhängigkeit von Akquisitions- sowie physikalischen Parametern stellen ein bekanntes Phänomen dar, welches in der Anwendung bisher jedoch kaum genutzt wird. In dieser Arbeit wurde gezeigt, wie Polarisationseffekte zu einer verbesserten Interpretation verwendet werden können. Die Überführung von geometrischen und physikalischen Attributen in ein neues, so genanntes Depolarisationsattribut hat gezeigt, wie unterschiedliche Leitungstypen extrahiert und anhand ihrer Polarisationscharakteristika klassifiziert werden können. Weitere wichtige physikalische Charakteristika des Georadarwellenfeldes können mit dem Matching Pursuit-Verfahren untersucht werden. Dieses Verfahren hatte in den letzten Jahren einen großen Einfluss auf moderne Signal- und Bildverarbeitungsansätze. Matching Pursuit wurde in der Geophysik bis jetzt hauptsächlich zur hochauflösenden Zeit-Frequenzanalyse verwendet. Anhand eines modifizierten Tree-based Matching Pursuit Algorithmus habe ich demonstriert, welche weiterführenden Möglichkeiten solche Datenzerlegungen für die Bearbeitung und Interpretation von Georadardaten eröffnen. Insgesamt zeigt diese Arbeit, wie moderne Vermessungstechniken und attributbasierte Analysestrategien genutzt werden können um dreidimensionale Daten effektiv und genau zu akquirieren beziehungsweise die resultierenden Datensätze effizient und verlässlich zu interpretieren.

Polythermal glaciers, i.e. glaciers with a combination of ice at and below the freezing point, are widespread in arctic and subarctic environments. The polythermal structure has major implications for glacier hydrology, ice flow and glacial erosion. However, the interplay of factors governing its spatial and temporal variations such as net mass balance, ice advection and water content in the ice is poorly investigated and as yet not fully understood. This study deals with a thorough investigation of the polythermal regime on Storglaciären, northern Sweden, a small valley glacier with a cold surface layer in the ablation area. Extensive field work was performed including mapping of the cold surface layer using ground-penetrating radar, ice temperature measurements, mass balance and ice velocity measurements. Analyses of these data combined with numerical modelling were used specifically to investigate the spatial and temporal variability of the cold surface layer, the spatial distribution of the water content just below the cold surface layer transition, the effect of radar frequency on the detection of the surface layer, and the sensitivity of the cold surface layer to changes in forcing. A comparison between direct temperature measurements in boreholes and ground-penetrating surveys shows that the radar-inferred cold-temperate transition depth is within ±1 m from the melting point of ice at frequencies above ~300 MHz. At frequencies below ~155 MHz, the accuracy degrades because of reduced scattering efficiency that occurs when the scatterers become much smaller compared to the wavelength. The mapped spatial pattern of the englacial cold-temperate transition boundary is complex. This pattern reflects the observed spatial variation in net loss of ice at the surface by ablation and vertical advection of ice, which is suggested to provide the predominant forcing of the cold surface layer thickness pattern. This is further supported by thermomechanical modeling of the cold surface layer, which indicates high sensitivity of the cold surface layer thickness to changes in vertical advection rates. The water content is the least investigated quantity that is relevant for the thermal regime of glaciers, but also the most difficult to assess. Spatial variability of absolute water content in the temperate ice immediately below the cold surface layer on Storglaciären was determined by combining relative estimates of water content from ground-penetrating radar data with absolute determination from temperature measurements and the thermal boundary condition at the freezing front. These measurements indicate large-scale spatial variability in the water content, which seems to arise from variations in entrapment of water at the firn-ice transition. However, this variability cannot alone explain the spatial pattern in the thermal regime on Storglaciären. Repeated surveys of the cold surface layer show a 22% average thinning of the cold surface layer on Storglaciären between 1989 and 2001. Transient thermomechanical modeling results suggest that the cold surface layer adapts to new equilibrium conditions in only a few decades after a perturbation in the forcing is introduced. An increased winter air temperature since mid-1980s seems to be the cause of the observed thinning of the cold surface layer. Over the last decades, mass balance measurements indicate that the glacier has been close to a steady state. The quasi-steady state situation is also reflected in the vertical advection, which shows no significant changes during the last decades. Increased winter temperatures at the ice surface would result in a slow-down of the formation of cold ice at the base of the cold surface layer and lead to a larger imbalance between net loss of ice at the surface and freezing of temperate ice at the cold-temperate transition.

<p>This dissertation addresses the problem of detecting buried explosive threats (i.e., landmines and improvised explosive devices) with ground-penetrating radar (GPR) and hyperspectral imaging (HSI) across widely-varying environmental conditions. Automated detection of buried objects with GPR and HSI is particularly difficult due to the sensitivity of sensor phenomenology to variations in local environmental conditions. Past approahces have attempted to mitigate the effects of ambient factors by designing statistical detection and classification algorithms to be invariant to such conditions. These methods have generally taken the approach of extracting features that exploit the physics of a particular sensor to provide a low-dimensional representation of the raw data for characterizing targets from non-targets. A statistical classification rule is then usually applied to the features. However, it may be difficult for feature extraction techniques to adapt to the highly nonlinear effects of near-surface environmental conditions on sensor phenomenology, as well as to re-train the classifier for use under new conditions. Furthermore, the search for an invariant set of features ignores that possibility that one approach may yield best performance under one set of terrain conditions (e.g., dry), and another might be better for another set of conditions (e.g., wet).</p><p>An alternative approach to improving detection performance is to consider exploiting differences in sensor behavior across environments rather than mitigating them, and treat changes in the background data as a possible source of supplemental information for the task of classifying targets and non-targets. This approach is referred to as context-dependent learning. </p><p>Although past researchers have proposed context-based approaches to detection and decision fusion, the definition of context used in this work differs from those used in the past. In this work, context is motivated by the physical state of the world from which an observation is made, and not from properties of the observation itself. The proposed context-dependent learning technique therefore utilized additional features that characterize soil properties from the sensor background, and a variety of nonparametric models were proposed for clustering these features into individual contexts. The number of contexts was assumed to be unknown a priori, and was learned via Bayesian inference using Dirichlet process priors.</p><p>The learned contextual information was then exploited by an ensemble on classifiers trained for classifying targets in each of the learned contexts. For GPR applications, the classifiers were trained for performing algorithm fusion For HSI applications, the classifiers were trained for performing band selection. The detection performance of all proposed methods were evaluated on data from U.S. government test sites. Performance was compared to several algorithms from the recent literature, several which have been deployed in fielded systems. Experimental results illustrate the potential for context-dependent learning to improve detection performance of GPR and HSI across varying environments.</p> / Dissertation

This study presents a comprehensive overview of the current state of the Milne Ice Shelf and how it has changed over the last 59 years. The 205 ±1 km2 ice shelf experienced a 28% (82 ±0.8 km2) reduction in area between 1950 – 2009, and a 20% (2.5 ±0.9km3 water equivalent (w.e.)) reduction in volume between 1981 – 2008/2009, suggesting a long-term state of negative mass balance. Comparison of mean annual specific mass balances (up to -0.34 m w.e. yr-1) with surface mass balance measurements for the nearby Ward Hunt Ice Shelf suggest that basal melt is a key contributor to total ice shelf thinning. The development and expansion of new and existing surface cracks, as well as ice-marginal and epishelf lake development, indicate significant ice shelf weakening. Over the next few decades it is likely that the Milne Ice Shelf will continue to deteriorate.

This study presents the first comprehensive assessment of the Petersen Ice Shelf and the Petersen Bay epishelf lake, and examines their current characteristics and changes to their structure between 1959 and 2012. The surface of the Petersen Ice Shelf is characterized by a rolling topography of ridges and troughs, which is balanced by a rolling basal topography, with thicker ice under the surface ridges and thinner ice under the surface troughs. Based on thickness measurements collected in 2011 and area measurements from August 2012, the Petersen Ice Shelf has a surface area of 19.32 km2 and a mean thickness of 29 m, with the greatest thicknesses (>100 m) occurring at the fronts of tributary glaciers feeding into the ice shelf. The tributary glaciers along the northern coast of Petersen Bay contributed an estimated area-averaged 7.89 to 13.55 cm yr-1 of ice to the ice shelf between 2011 and 2012. This input is counteracted by a mean surface ablation of 1.30 m yr-1 between 2011 and 2012, suggesting strongly negative current mass balance conditions on the ice shelf. The Petersen Ice Shelf remained relatively stable until 2005 when the first break-up in recent history occurred, removing >8 km2 of ice shelf surface area. This break-up led to the drainage of the epishelf lake once the ice shelf separated from the southern coast, providing a conduit through which the freshwater from the lake escaped. More break-ups occurred in summers 2008, 2011 and 2012, which resulted in a >31.2 km2 loss in surface area (~63% of June 2005 area). While ephemeral regions of freshwater have occurred along the southern coast of Petersen Bay since 2005 (with areas ranging from 0.32-0.53 km2), open water events and a channel along the southern coast have prevented the epishelf lake from reforming. Based on these past and present observations it is unlikely that Petersen Ice Shelf will continue to persist long into the future.

Near-surface sediments in the vadose zone play a fundamental role in the hydrologic system. The shallow vadose zone can act as a buffer to delay or attenuate surface contaminants before they reach the water table. It also acts as a temporary soil moisture reservoir for plant and atmospheric uptake, and regulates the seasonal groundwater recharge process. Over the past few decades, geophysical methods have received unprecedented attention as an effective vadose zone characterization tool offering a range of non-invasive to minimally invasive techniques with the capacity to provide detailed soil moisture information at depths typically unattainable using conventional point-measurement sensors. Ground-penetrating radar (GPR) has received much of this attention due to its high sensitivity to the liquid water phase in geologic media. While much has been learned about GPR soil moisture monitoring and characterization techniques, it has not been evaluated across highly dynamic natural soil conditions. Consequently, GPR’s capacity to characterize a complete range of naturally occurring vadose zone conditions including wetting/drying and freeze/thaw cycles, is not yet fully understood. Further, the nature of GPR response during highly dynamic moisture periods has not been thoroughly investigated. The objective of this thesis is to examine the capacity of various surface GPR techniques and methodologies for the characterization of soil moisture dynamics in the upper few meters of vadose zone, and to develop measurement strategies capable of providing quantitative information about the current and future state of the shallow hydrologic system. To achieve this, an exhaustive soil moisture monitoring campaign employing a range of GPR antenna frequencies and survey acquisition geometries was initiated at three different agricultural field sites located in southern Ontario, Canada, between May 2006 and October 2008. This thesis represents the first attempt to evaluate multiple annual cycles of soil conditions and associated hydrological processes using high-frequency GPR measurements. Summaries of the seven major works embodied in this thesis are provided below. Direct ground wave (DGW) measurements obtained with GPR have been used in a number of previous studies to monitor volumetric water content changes in the root zone; however, these studies have involved controlled field experiments or measurements collected across limited ranges in soil moisture. To further investigate the capacity of the DGW method, multi-frequency (i.e., 225 MHz, 450 MHz and 900 MHz) common-midpoint (CMP) measurements were used to monitor a complete annual cycle of soil water content variations at three sites with different soil textures (i.e., sand, sandy loam and silt loam). CMP surveys permitted characterization of the nature and evolution of the near-surface electromagnetic wavefields, and their subsequent impact on DGW velocity measurements. GPR results showed significant temporal variations in both the near-surface wavefield and multi-frequency DGW velocities corresponding to both seasonal and shorter term variations in soil conditions. While all of the measurement sites displayed similar temporal responses, the rate and magnitude of these velocity variations corresponded to varying soil water contents which were primarily controlled by the soil textural properties. Overall, the DGW measurements obtained using higher frequency antennas were less impacted by near-surface wavefield interference due to their shorter signal pulse duration. The estimation of soil water content using GPR velocity requires an appropriate petrophysical relationship between the dielectric permittivity and volumetric water content of the soil. The ability of various empirical relationships, volumetric mixing formulae and effective medium approximations were evaluated to predict near-surface volumetric soil water content using high-frequency DGW velocity measurements obtained from CMP soundings. Measurements were collected using 225, 450 and 900 MHz antennas across sand, sandy loam and silt loam soil textures over a complete annual cycle of soil conditions. A lack of frequency dependence in the results indicated that frequency dispersion had minimal impact on the data set. However, the accuracy of soil water content predictions obtained from the various relationships ranged considerably. The best fitting relationships did exhibit some degree of textural bias that should be considered in the choice of petrophysical relationship for a given data set. Further improvements in water content estimates were obtained using a field calibrated third-order polynomial relationship and three-phase volumetric mixing formula. While DGW measurements provide valuable information within the root zone, the characterization of vertical moisture distribution and dynamics requires a different approach. A common approach utilizes normal-moveout (NMO) velocity analysis of CMP sounding data. To further examine this approach, an extensive field study using multi-frequency (i.e., 225 MHz, 450 MHz, 900 MHz) CMP soundings was conducted to monitor a complete annual cycle of vertical soil moisture conditions at the sand, sandy loam and silt loam sites. The use of NMO velocity analysis was examined for monitoring highly dynamic vertical soil moisture conditions consisting of wetting/drying and freeze/thaw cycles with varying degrees of magnitude and vertical velocity gradient. NMO velocity analysis was used to construct interval-velocity-depth models at a fixed location collected every 1 to 4 weeks. Time-lapse models were combined to construct temporal interval-velocity fields, which were converted into soil moisture content. These moisture fields were used to characterize the vertical distribution, and dynamics of soil moisture in the upper few meters of vadose zone. Although the use of multiple antenna frequencies provided varying investigation depths and vertical resolving capabilities, optimal characterization of soil moisture conditions was obtained with 900 MHz antennas. The integration of DGW and NMO velocity data from a single CMP sounding could be used to assess the nature of shallow soil moisture coupling with underlying vadose zone conditions; however, a more quantitative analyses of the surface moisture dynamics would require definitive knowledge of GPR sampling depth. Although surface techniques have been used by a number of previous researchers to characterize soil moisture content in the vadose zone, limited temporal sampling and low resolution near the surface in these studies impeded the quantitative analysis of vertical soil moisture distribution and its associated dynamics within the shallow subsurface. To further examine the capacity of surface GPR, an extensive 26 month field study was undertaken using concurrent high-frequency (i.e., 900 MHz) reflection profiling and CMP soundings to quantitatively monitor soil moisture distribution and dynamics within a sandy vadose zone environment. An analysis on the concurrent use of reflection and CMP measurements was conducted over two contrasting annual cycles of soil conditions. Reflection profiles provided high resolution traveltime data between four stratigraphic reflection events while cumulative results of the CMP sounding data set produced precise depth estimates for those reflecting interfaces, which were used to convert interval traveltime data into soil water content estimates. The downward propagation of episodic infiltration events associated with seasonal and transient conditions were well resolved by the GPR data. The GPR data also revealed variations in the nature of these infiltration events between contrasting annual cycles. The use of CMP soundings also permitted the determination of DGW velocities, which enabled better characterization of short-duration wetting/drying and freezing/thawing processes. This higher resolution information can be used to examine the nature of the coupling between shallow and deep moisture conditions. High-resolution surface GPR measurements were used to examine vertical soil moisture distribution and its associated dynamics within the shallow subsurface over a 26 month period. While the apparent ability of surface GPR methods to give high quality estimates of soil moisture distribution in the upper 3 meters of the vadose zone was demonstrated, the nature of these GPR-derived moisture data needed to be assessed in the context of other hydrological information. As a result, GPR soil moisture estimates were compared with predictions obtained from a well-accepted hydrological modeling package, HYDRUS-1D (Simunek et al., 2008). The nature of transient infiltration pulses, evapotranspiration episodes, and deep drainage patterns were examined by comparing them with vertical soil moisture flow simulations. Using laboratory derived soil hydraulic property information from soil samples and a number of simplifying assumptions about the system, very good agreement was achieved between measured and simulated soil moisture conditions without model calibration. The overall good agreement observed between forward simulations and field measurements over the vertical profile validated the capacity of surface GPR to provide detailed information about hydraulic state conditions in the upper few meters of vadose zone. A unique DGW propagation phenomenon was observed during early soil frost formation. High-frequency DGW measurements were used to monitor the seasonal development of a thin, high velocity frozen soil layer over a wet low velocity unfrozen substratum. During the freezing process, the progressive attenuation of a low velocity DGW and the subsequent development of a high velocity DGW were observed. Numerical simulations using GPRMAX2D (Giannopoulos, 2005) showed that low velocity DGW occurring after freezing commenced was due to energy leaking across the frozen layer from the spherical body wave in the unfrozen half space. This leaky phase progressively dissipated until the frozen layer reached a thickness equivalent to one quarter of the dominant wavelength in the frozen ground. The appearance of the high velocity DGW was governed by its destructive interference with the reflection events from the base of the frozen layer. This interference obscured the high velocity DGW until the frozen layer thickness reached one half of the dominant wavelength in the frozen ground. While GPR has been extensively used to study frozen soil conditions in alpine environments, its capacity to characterize highly dynamic shallow freeze-thaw processes typically observed in temperate environments is not well understood. High-frequency reflection profiles and CMP soundings were used to monitor the freezing and thawing process during the winter seasonal period at the sand and silt loam sites. Reflection profiles revealed the long-term development of a very shallow (<0.5 m) soil frost zone overlying unfrozen wet substratum. During the course of the winter season, long-term traveltime analysis yielded physical properties of the frozen and unfrozen layers as well as the spatial distribution of the base of the soil frost zone. Short-term shallow thawing events overlying frozen substratum formed a dispersive waveguide for both the CMP and reflection profile surveys. Inversion of the dispersive wavefields for the CMP data yielded physical property estimates for the thawed and frozen soils and thawed layer thickness. It was shown that GPR can be used to monitor very shallow freezing and thawing events by responding to changes in the relative dielectric permittivity of the soil water phase. The works embodied in this thesis demonstrate the effectiveness of high-frequency GPR as a non-invasive soil moisture monitoring tool under a full range of naturally occurring moisture conditions with the temporal and vertical resolution necessary to quantitatively examine shallow vadose zone moisture dynamics. Because this study encompassed an unprecedented range of naturally occurring soil conditions, including numerous short and long duration wetting/drying and freezing/thawing cycles, complex geophysical responses were observed during highly dynamic soil moisture processes. Analysis and interpretation of these geophysical responses yielded both qualitative and quantitative information about the state of the hydrologic system, and hence, provided a non-invasive means of characterizing soil moisture processes in shallow vadose zone environments. In the future, these GPR soil moisture monitoring strategies should be incorporated into advanced land-surface hydrological modeling studies to improve our understanding of shallow hydrologic systems and its impacts on groundwater resources.