Susan S. Hubbard

Hydrogeological characterization of the south oyster bacterial transport site using geophysical data

A multidisciplinary research team has conducted a field-scale bacterial transport study within an uncontaminated sandy Pleistocene aquifer near Oyster, Virginia. The overall goal of the project was to evaluate the importance of heterogeneities in controlling the field-scale transport of bacteria that are injected into the ground for remediation purposes. Geochemical, hydrological, geological, and geophysical data were collected to characterize the site prior to conducting chemical and bacterial injection experiments. In this paper we focus on results of a hydrogeological characterization effort using geophysical data collected across a range of spatial scales. The geophysical data employed include surface ground-penetrating radar, radar cross-hole tomography, seismic cross-hole tomography, cone penetrometer, and borehole electromagnetic flowmeter. These data were used to interpret the subregional and local stratigraphy, to provide high-resolution hydraulic conductivity estimates, and to provide information about the log conductivity spatial correlation function. The information from geophysical data was used to guide and assist the field operations and to constrain the numerical bacterial transport model. Although more field work of this nature is necessary to validate the usefulness and cost-effectiveness of including geophysical data in the characterization effort, qualitative and quantitative comparisons between tomographically obtained flow and transport parameter estimates with hydraulic well bore and bromide breakthrough measurements suggest that geophysical data can provide valuable, high-resolution information. This information, traditionally only partially obtainable by performing extensive and intrusive well bore sampling, may help to reduce the ambiguity associated with hydrogeological heterogeneity that is often encountered when interpreting field-scale bacterial transport data.

Estimation of permeable pathways and water content using tomographic radar data

Near‐surface environmental investigations often require monitoring of the spatial distribution of water content and identification of preferential fluid flow paths. Water content estimates are needed, for example, to model and predict pollutant transport through the vadose zone and to subsequently design an efficient and reliable remediation plan. The characteristics of preferential flow paths, as well as the location and geometry of these features, are necessary to model and predict flow and transport in complex geological media such as fractured or strongly heterogeneous porous systems.

Estimating the hydraulic conductivity at the south oyster site from geophysical tomographic data using Bayesian Techniques based on the normal linear regression model

This study explores the use of ground penetrating radar (GPR) tomographic velocity, GPR tomographic attenuation, and seismic tomographic velocity for hydraulic conductivity estimation at the South Oyster Site, using a Bayesian framework. Since site- specific relations between hydraulic conductivity and geophysical properties are often nonlinear and subject to a large degree of uncertainty such as at this site, we developed a normal linear regression model that allows exploring these relationships systematically. Although the log-conductivity displays a small variation (s 2 5 0.30) and the geophysical data vary over only a small range, results indicate that the geophysical data improve the estimates of the hydraulic conductivity. The improvement is the most significant where prior information is limited. Among the geophysical data, GPR and seismic velocity are more useful than GPR attenuation.

Thousands of microbial genomes shed light on interconnected biogeochemical processes in an aquifer system.

The subterranean world hosts up to one-fifth of all biomass, including microbial communities that drive transformations central to Earths biogeochemical cycles. However, little is known about how complex microbial communities in such environments are structured, and how inter-organism interactions shape ecosystem function. Here we apply terabase-scale cultivation-independent metagenomics to aquifer sediments and groundwater, and reconstruct 2,540 draft-quality, near-complete and complete strain-resolved genomes that represent the majority of known bacterial phyla as well as 47 newly discovered phylum-level lineages. Metabolic analyses spanning this vast phylogenetic diversity and representing up to 36% of organisms detected in the system are used to document the distribution of pathways in coexisting organisms. Consistent with prior findings indicating metabolic handoffs in simple consortia, we find that few organisms within the community can conduct multiple sequential redox transformations. As environmental conditions change, different assemblages of organisms are selected for, altering linkages among the major biogeochemical cycles.

Hydrogeological parameter estimation using geophysical data: a review of selected techniques

Subsurface environmental, engineering, and agricultural investigations often require characteri- zation of hydraulic parameters. For example, groundwater flow modeling is often performed through an aquifer whose hydrological properties have been created using stochastic simulation techniques; these techniques use as input both hydraulic parameter point values and spatial correlation structure information. Conventional sampling or borehole techniques for measuring these parameters are costly, time-consuming, and invasive. Geophysical data can compliment direct characterization data by providing multi-dimensional and high resolution subsurface mea- surements in a minimally invasive manner. Several techniques have been developed in the preceding decade for using joint geophysical-hydrological data to characterize the subsurface; the purpose of this study is to review three methodologies that we have recently developed for use with geophysical-hydrological data to estimate hydrological parameters and their spatial correla- tion structures. The first two methodologies presented focus on producing high-resolution esti- mates of hydrological properties using densely sampled geophysical data and limited borehole data. Although we find that high-resolution geophysical data are useful for obtaining these estimates, in practice, geophysical profiles often sample only a small portion of the aquifer under investigation, and thus, the estimates obtained from geophysical data may not be sufficient to completely describe the hydraulic properties of the aquifer volume. The third and last section focuses on using high-resolution tomographic data together with limited borehole data to infer the spatial correlation structure of log-permeability, which can be used within stochastic simulation techniques to generate parameter estimates at unsampled locations. Our synthetic case studies suggest that collection of a few tomographic profiles and interpretation of these profiles together with limited wellbore data can yield hydrological point values and spatial correlation structure

Effect of dissolved CO2 on a shallow groundwater system: a controlled release field experiment.

Capturing carbon dioxide (CO(2)) emissions from industrial sources and injecting the emissions deep underground in geologic formations is one method being considered to control CO(2) concentrations in the atmosphere. Sequestering CO(2) underground has its own set of environmental risks, including the potential migration of CO(2) out of the storage reservoir and resulting acidification and release of trace constituents in shallow groundwater. A field study involving the controlled release of groundwater containing dissolved CO(2) was initiated to investigate potential groundwater impacts. Dissolution of CO(2) in the groundwater resulted in a sustained and easily detected decrease of ~3 pH units. Several trace constituents, including As and Pb, remained below their respective detections limits and/or at background levels. Other constituents (Ba, Ca, Cr, Sr, Mg, Mn, and Fe) displayed a pulse response, consisting of an initial increase in concentration followed by either a return to background levels or slightly greater than background. This suggests a fast-release mechanism (desorption, exchange, and/or fast dissolution of small finite amounts of metals) concomitant in some cases with a slower release potentially involving different solid phases or mechanisms. Inorganic constituents regulated by the U.S. Environmental Protection Agency remained below their respective maximum contaminant levels throughout the experiment.

Effects of physical and geochemical heterogeneities on mineral transformation and biomass accumulation during biostimulation experiments at Rifle, Colorado

Electron donor amendment for bioremediation often results in precipitation of secondary minerals and the growth of biomass, both of which can potentially change flow paths and the efficacy of bioremediation. Quantitative estimation of precipitate and biomass distribution has remained challenging, partly due to the intrinsic heterogeneities of natural porous media and the scarcity of field data. In this work, we examine the effects of physical and geochemical heterogeneities on the spatial distributions of mineral precipitates and biomass accumulated during a biostimulation field experiment near Rifle, Colorado. Field bromide breakthrough data were used to infer a heterogeneous distribution of hydraulic conductivity through inverse transport modeling, while the solid phase Fe(III) content was determined by assuming a negative correlation with hydraulic conductivity. Validated by field aqueous geochemical data, reactive transport modeling was used to explicitly keep track of the growth of the biomass and to estimate the spatial distribution of precipitates and biomass. The results show that the maximum mineral precipitation and biomass accumulation occurs in the vicinity of the injection wells, occupying up to 5.4vol.% of the pore space, and is dominated by reaction products of sulfate reduction. Accumulation near the injection wells is not strongly affected by heterogeneities present in the system due to the ubiquitous presence of sulfate in the groundwater. However, accumulation in the down-gradient regions is dominated by the iron-reducing reaction products, whose spatial patterns are strongly controlled by both physical and geochemical heterogeneities. Heterogeneities can lead to localized large accumulation of mineral precipitates and biomass, increasing the possibility of pore clogging. Although ignoring the heterogeneities of the system can lead to adequate prediction of the average behavior of sulfate-reducing related products, it can also lead to an overestimation of the overall accumulation of iron-reducing bacteria, as well as the rate and extent of iron reduction. Surprisingly, the model predicts that the total amount of uranium being reduced in the heterogeneous 2D system was similar to that in the 1D homogeneous system, suggesting that the overall uranium bioremediation efficacy may not be significantly affected by the heterogeneities of Fe(III) content in the down-gradient regions. Rather, the characteristics close to the vicinity of the injection wells might be crucial in determining the overall efficacy of uranium bioremediation. These findings have important implications not only for uranium bioremediation at the Rifle site and for bioremediation of other redox sensitive contaminants at sites with similar characteristics, but also for the development of optimal amendment delivery strategies in other settings.

Quantifying and relating land-surface and subsurface variability in permafrost environments using LiDAR and surface geophysical datasets

The value of remote sensing and surface geophysical data for characterizing the spatial variability and relationships between land-surface and subsurface properties was explored in an Alaska (USA) coastal plain ecosystem. At this site, a nested suite of measurements was collected within a region where the land surface was dominated by polygons, including: LiDAR data; ground-penetrating radar, electromagnetic, and electrical-resistance tomography data; active-layer depth, soil temperature, soil-moisture content, soil texture, soil carbon and nitrogen content; and pore-fluid cations. LiDAR data were used to extract geomorphic metrics, which potentially indicate drainage potential. Geophysical data were used to characterize active-layer depth, soil-moisture content, and permafrost variability. Cluster analysis of the LiDAR and geophysical attributes revealed the presence of three spatial zones, which had unique distributions of geomorphic, hydrological, thermal, and geochemical properties. The correspondence between the LiDAR-based geomorphic zonation and the geophysics-based active-layer and permafrost zonation highlights the significant linkage between these ecosystem compartments. This study suggests the potential of combining LiDAR and surface geophysical measurements for providing high-resolution information about land-surface and subsurface properties as well as their spatial variations and linkages, all of which are important for quantifying terrestrial-ecosystem evolution and feedbacks to climate.ResuméLa portée de la télédétection et des données géophysique de surface pour caractériser la variabilité spatiale et les relations entre la surface du terrain et les propriétés de la subsurface a été étudiée sous tous ses aspects dans l’écosystème de la plaine côtière d’Alaska (USA). Dans cette région, sur un site où la surface du sol est dominée par des polygones, une série de données se recoupant a été collectée, incluant : données LiDAR; géoradar, tomographie électromagnétique et résistivité; profondeur de la couche aquifère, température, teneur en humidité, texture, teneur en carbone et en azote du sol; et cations du fluide des pores. Les données Lidar ont été utilisées pour établir les cotes géomorphiques, qui peuvent indiquer un drainage potentiel. Des données géophysiques ont été utilisées pour déterminer la profondeur de la couche aquifère, la teneur en humidité du sol, et la variabilité du pergélisol. L’analyse par agglomérat des données LiDAR et des attributs géophysiques ont révélé la présence de trois zones spatiales ayant une distribution similaire des propriétés géomorphiques, hydrogéologiques, thermales et géochimiques. La correspondance entre la zonation géomorphique basée sur LiDAR, la couche aquifère selon la géophysique et la zonation permafrost, met en lumière la relation significative entre ces compartiments de l’écosystème. Cette étude montre le potentiel d’une combinaison des mesures LiDAR et des mesures géophysiques de surface pour fournir une information haute résolution sur les propriétés de surface et de subsurface du sol aussi bien que sur leur variations spatiales et liens, toutes étant importantes pour quantifier l’évolution de l’écosystème terrestre et les réponses au climat.ResumenSe exploró el valor de los sensores remotos y de los datos geofísicos de superficie para caracterizar la variabilidad espacial y las relaciones entre la superficie y las propiedades subsuperficiales en un ecosistema de planicie costera en Alaska (EEUU). En este sitio, un conjunto anidado de medidas fue colectado dentro de una región donde la superficie estaba dominada por polígonos, incluyendo: datos LiDAR; datos de radar, electromagnéticos, y tomografías de resistividad eléctrica; profundidad de la capa activa, temperatura del suelo, contenido de humedad del suelo, textura del suelo, contenido de carbono y nitrógeno en suelo; y cationes del fluido de poros. Los datos LiDAR fueron usados para extraer los indicadores geomórficos, que posiblemente indican un drenaje potencial. Los datos geofísicos fueron para caracterizar la profundidad de la capa activa, el contenido de humedad del suelo y la variabilidad del permafrost. En análisis de cluster de los LiDAR y los atributos geofísicos revelaron la presencia espacial de tres zonas, que tenían una única distribución de propiedades geomórficas, hidrológicas, térmicas y geoquímicas. La correspondencia entre la zonación geomórfica basada en LiDAR y la capa activa basada en geofísica y la zonación del permafrost destaca la vinculación significativa entre estos compartimentos del ecosistema. Este estudio sugiere el potencial de la combinación LiDAR y las mediciones geofísicas de superficie para proveer información de alta resolución acerca de las propiedades de la superficie y de la subsuperficie así como su variación espacial y su articulación, todos los cuales son importantes para cuantificar la evolución del ecosistema terrestre y las reacciones con el clima.摘要用来描述地表和地下性质的空间变异性和两者之间的关系的遥感和地面地球物理数据已在阿拉斯加(美国)的一个沿海平原生态系统进行了探讨。在本次研究场地的一个表面呈多边形的区域收集到了一套测量数据,包括激光雷达数据;探地雷达数据,电磁和电阻断层扫描数据;活性层深度,土壤温度,土壤水气含量,土壤质地,土壤碳和氮的含量;以及孔隙流体阳离子数据。激光雷达数据用来提取地貌指标,这可能指示出潜在的排泄。地球物理数据用来刻画活性层的深度,土壤水气含量和永久冻土的变化特征。通过对激光雷达和地球物理数据属性的聚类分析发现了三个在地形,水文,热和地球化学性质分布上存在异常的空间区域。基于激光雷达测量的地貌分区与基于地球物理数据的活性层和永久冻土分区之间的对应关系突出了这些生态系统分区间的紧密联系。本次研究表明可以通过结合激光雷达和地表地球物理测量来为地表和地下的性质以及它们在空间上的变化和关系提供高分辨率的信息,所有这些对于量化陆地生态系统的演化和对气候变化的反应都是非常重要的。ResumoNum ecossistema da planície costeira do Alaska (EUA) foi explorado o valor da deteção remota e de dados de geofísica de superfície para caracterizar a variabilidade espacial e as relações entre propriedades da superfície do terreno e da subsuperfície. Neste local, inserido numa região onde o terreno superficial é dominado por polígonos, foi recolhido um conjunto agregado de medições, incluindo: dados de LiDAR; dados de geoadar, eletromagnéticos e de tomografia de resistência elétrica; profundidade da camada ativa, temperatura do solo, teor de água no solo, textura do solo, teor de carbono e azoto no solo; e catiões no fluido poroso. Os dados LiDAR foram usados para extrair dimensões geomórficas que potencialmente indicam o potencial de drenagem. Os dados geofísicos foram usados para caracterizar a profundidade da camada ativa, o teor de humidade no solo e a variabilidade no permafrost. A análise grupal de atributos LiDAR e geofísicos revelou a presença de três zonas espaciais que tinham distribuições únicas de propriedades geomórficas, hidrológicas, térmicas e geoquímicas. A correspondência entre o zonamento geomórfico baseado no LiDAR e a zonação da camada activa baseada na geofísica e do permafrost, demonstra a significativa conexão entre estes compartimentos do ecossistema. Este estudo sugere o potencial da combinação de medições de LiDAR e de geofísica de superfície para fornecer informação de alta resolução acerca das propriedades da superfície do terreno e da subsuperfície, assim como sobre as variações espaciais e conexões, sendo todas elas importantes para a quantificação da evolução do ecossistema terrestre e as retroações com o clima.

Mapping the volumetric soil water content of a California vineyard using high-frequency GPR ground wave data

Water distribution in the top 1 m of the earths surface soil layer often controls the success of agricultural crops. In this near-surface zone, large spatial and temporal variations in soil water content are associated with soil heterogeneities, topography, land cover, evapotranspiration, and precipitation. Conventional techniques of measuring soil water content for agricultural purposes—e.g., time domain reflectometry (TDR), neutron probe, or gravimetric techniques, are intrusive and provide information at a point scale only, which is often inadequate for capturing the variations in soil water content with sufficient resolution. Both passive and active remote sensing methods have also been investigated as a tool to provide soil water content in the top 0–5 cm of the subsurface over large spatial areas and in a rapid manner. However, it is still a challenge to obtain information about soil water content from remote sensing data in the presence of a mature crop cover. At the spatial and temporal scales ne...

A comparison between Gauss-Newton and Markov-chain Monte Carlo–based methods for inverting spectral induced-polarization data for Cole-Cole parameters

We have developed a Bayesian model to invert spectral induced-polarization (SIP) data for Cole-Cole parameters using Markov-chain Monte Carlo (MCMC) sampling methods. We compared the performance of the MCMC-based stochastic method with an iterative Gauss-Newton-based deterministic method for Cole-Cole parameter estimation through inversion of synthetic and laboratory SIP data. The Gauss-Newton-based method can provide an optimal solution for given objective functions under constraints, but the obtained optimal solution generally depends on the choice of initial values and the estimated uncertainty information often is inaccurate or insufficient. In contrast, the MCMC-based inversion method provides extensive globalinformation on unknown parameters, such as the marginal probability distribution functions, from which we can obtain better estimates and tighter uncertainty bounds of the parameters than with the deterministic method. In addition, the results obtained with the MCMC method are independent of the choice of initial values. Because the MCMC-based method does not explicitly offer a single optimal solution for given objective functions, the deterministic and stochastic methods can complement each other. For example, the stochastic method can be used first to obtain the medians of unknown parameters by starting from an arbitrary set of initial values. The deterministic method then can be initiated using the medians as starting values to obtain the optimal estimates of the Cole-Cole parameters.