Search

Representativeness and quality of collected meteorological data impact accuracy and precision of climate, hydrological, and biogeochemical analyses and predictions. We developed a comprehensive Quality Assurance (QA) and Quality Control (QC) statistical framework, consisting of three major phases: Phase I—Preliminary data exploration, i.e., processing of raw datasets, with the challenging problems of time formatting and combining datasets of different lengths and different time intervals; Phase II—QA of the datasets, including detecting and flagging of duplicates, outliers, and extreme data; and Phase III—the development of time series of a desired frequency, imputation of missing values, visualization and a final statistical summary. The paper includes two use cases based on the time series data collected at the Billy Barr meteorological station (East River Watershed, Colorado), and the Barro Colorado Island (BCI, Panama) meteorological station. The developed statistical framework is suitable for both real-time and post-data-collection QA/QC analysis of meteorological datasets.

Over multi-decadal time scales, assuming that changes in subsurface water storage are negligible, the continental precipitative water flux, P, can be divided into two principal components, Q (run-off, including soil infiltration and groundwater recharge) and ET (evapotranspiration). Taking into account a broadly applied Budyko's phenomenology to describe the relationship of ET/P as a function of PET/P, where PET is the potential evapotranspiration, we propose a theoretical framework for predicting characteristics of the water cycle from scaling relationships. In this framework, the ecosystem net primary productivity is expressed in terms of soil formation and vegetation growth, which is mathematically optimized with respect to the water partitioning, generating directly the value ET/P. The mathematical optimization is based on the general ecological principle that dominant ecosystems tend to be those that, for any given conditions, maximize conversion of atmospheric carbon to biomass. It is shown that application of the results of mathematical optimization to water-limited ecosystems is possible by applying the optimization only to a vegetation covered portion of the surface. For energy-limited ecosystems, the optimization can be applied only to a portion of the precipitation equal to PET, assuming that the remaining P simply runs off. We use theoretical and actual values of plant root fractal dimensionalities, df, to predict ranges of ET/P as a function of PET/P for 0 ≤ PET/P ≤ 1 and compare with annual and multi-decadal means of ET/P. By comparing the developed approach with a large amount of data collected from the literature, we demonstrate its successful applications to both water- and energy-limited systems.

Scientific datasets are growing rapidly and becoming critical to next-generation scientific discoveries. The validity of scientific results relies on the quality of data used and data are often subject to change, for example, due to observation additions, quality assessments, or processing software updates. The effects of data change are not well understood and difficult to predict. Datasets are often repeatedly updated and recomputing derived data products quickly becomes time consuming and resource intensive and may in some cases not even be necessary, thus delaying scientific advance. Despite its importance, there is a lack of systematic approaches for best comparing data versions to quantify the changes, and ad-hoc or manual processes are commonly used. In this article, we propose a novel hierarchical approach for analyzing data changes, including real-time (online) and offline analyses. We employ a variety of fast-to-compute numerical analyses, graphical data change representations, and more resource-intensive recomputations of a subset of the data product. We illustrate the application of our approach using three scientific diverse use cases, namely, satellite, cosmological, and x-ray data. The results show that a variety of data change metrics should be employed to enable a comprehensive representation and qualitative evaluation of data changes.

Forest disturbance and regrowth are key processes in forest dynamics, but detailed information on these processes is difficult to obtain in remote forests such as the Amazon. We used chronosequences of Landsat satellite imagery (Landsat 5 Thematic Mapper and Landsat 7 Enhanced Thematic Mapper Plus) to determine the sensitivity of surface reflectance from all spectral bands to windthrow, clear-cut, and clear-cut and burned (cut + burn) and their successional pathways of forest regrowth in the Central Amazon. We also assessed whether the forest demography model Functionally Assembled Terrestrial Ecosystem Simulator (FATES) implemented in the Energy Exascale Earth System Model (E3SM) Land Model (ELM), ELM-FATES, accurately represents the changes for windthrow and clear-cut. The results show that all spectral bands from the Landsat satellites were sensitive to the disturbances but after 3 to 6 years only the near-infrared (NIR) band had significant changes associated with the successional pathways of forest regrowth for all the disturbances considered. In general, the NIR values decreased immediately after disturbance, increased to maximum values with the establishment of pioneers and early successional tree species, and then decreased slowly and almost linearly to pre-disturbance conditions with the dynamics of forest succession. Statistical methods predict that NIR values will return to pre-disturbance values in about 39, 36, and 56 years for windthrow, clear-cut, and cut + burn disturbances, respectively. The NIR band captured the observed, and different, successional pathways of forest regrowth after windthrow, clear-cut, and cut + burn. Consistent with inferences from the NIR observations, ELM-FATES predicted higher peaks of biomass and stem density after clear-cuts than after windthrows. ELM-FATES also predicted recovery of forest structure and canopy coverage back to pre-disturbance conditions in 38 years after windthrows and 41 years after clear-cut. The similarity of ELM-FATES predictions of regrowth patterns after windthrow and clear-cut to those of the NIR results suggests the NIR band can be used to benchmark forest regrowth in ecosystem models. Our results show the potential of Landsat imagery data for mapping forest regrowth from different types of disturbances, benchmarking, and the improvement of forest regrowth models.

In his paper on net primary productivity of terrestrial communities predicted from climatological data, Rosenzweig (1968) argued that variability in productivity is well accounted for by (evapo)-transpiration, and that water from transpiration is, on global scales, the most variable component in the photosynthesis reaction. The goal of this paper is to investigate whether variability in plant growth on local scales and within species is primarily related to transpiration under several scenarios including different terrain curvature, slope aspect, soil characteristics, and climate ranges. We test the hypothesis that this relationship exists because root growth into the surface soil layers (0–2 m) tends to follow paths with minima in resistance, which in turn maximizes water flow and nutrient delivery rates that regulate growth. The set of all connected paths with individual pore-to-pore flow resistances less than a critical, percolating, value forms a cluster with mass fractal dimensionality, df. We propose that roots follow paths through the 2D percolation cluster, defining the set of all optimal flow paths, making the 2D value of df from percolation relevant to root fractal dimensionality. The tortuosity of such optimal paths as defined in percolation theory should then relate root length to root radial extent, linking the parameters of root tortuosity and plant productivity. Our analysis of large data sets across species implies that root radial extent and tree height are both proportional to cumulative transpiration until trees approached maximum height, and their growth rates are proportional to the transpiration rate, not to the moisture content. Local variations in tree height as functions of the variables investigated appear generally consistent with deduced variations in transpiration. Here this correlation is investigated more closely in the context of studies addressing individual tree species.

Plant functional traits determine vegetation responses to environmental variation, but variation in trait values is large, even within a single site. Likewise, uncertainty in how these traits map to Earth system feedbacks is large. We use a vegetation demographic model (VDM), the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), to explore parameter sensitivity of model predictions, and comparison to observations, at a tropical forest site: Barro Colorado Island in Panama. We define a single 12-dimensional distribution of plant trait variation, derived primarily from observations in Panama, and define plant functional types (PFTs) as random draws from this distribution. We compare several model ensembles, where individual ensemble members vary only in the plant traits that define PFTs, and separate ensembles differ from each other based on either model structural assumptions or non-trait, ecosystem-level parameters, which include (a) the number of competing PFTs present in any simulation and (b) parameters that govern disturbance and height-based light competition. While singlePFT simulations are roughly consistent with observations of productivity at Barro Colorado Island, increasing the number of competing PFTs strongly shifts model predictions towards higher productivity and biomass forests. Different ecosystem variables show greater sensitivity than others to the number of competing PFTs, with the predictions that are most dominated by large trees, such as biomass, being the most sensitive. Changing disturbance and height-sorting parameters, i.e., the rules of competitive trait filtering, shifts regimes of dominance or coexistence between early-and late-successional PFTs in the model. Increases to the extent or severity of disturbance, or to the degree of determinism in height-based light competition, all act to shift the community towards early-successional PFTs. In turn, these shifts in competitive outcomes alter predictions of ecosystem states and fluxes, with more early-successional-dominated forests having lower biomass. It is thus crucial to differentiate between plant traits, which are under competitive pressure in VDMs, from those model parameters that are not and to better understand the relationships between these two types of model parameters to quantify sources of uncertainty in VDMs.

The application of groundwater relief, i.e., dewatering, ascending wells, drilled upward from the mining tunnel into the overlying aquifer, is common in underground mining engineering. In this study, the seepage characteristics of single ascending partially and fully penetrating relief wells are investigated using a series of laboratory sand-tank experiments and numerical simulations. The seepage characteristics of ascending wells dewatering an overlying aquifer are different from those of conventional pumping wells descending from the ground surface into the underlying aquifer, because of the pronounced influence of the seepage face boundary condition along the seepage boundary of the ascending dewatering well. The seepage face of the ascending well is formed as the well casing remains open and water is discharged under the action of gravity through the well casing. The results of laboratory sand-tank experiments and modeling show that when the degree of penetration of an ascending relief well does not exceed a critical value, the effect of the seepage face cannot be ignored. In particular, the seepage flux increases as the degree of penetration increases following an exponential function, and the relationship between the seepage flux and the well radius can be described using a power law function. The results of numerical simulations are used to develop a series of type curves to evaluate the effects of the critical degree of penetration for different well radii and different aquifer water levels. Modified versions of the Dupuit and Dupuit-Thiem formulae for a single ascending partially well for the degree of penetration less than the critical one for the unconfined, confined, and confined-unconfined aquifers are developed.

Soil moisture plays a key role in hydrological, biogeochemical, and energy budgets of terrestrial ecosystems. Accurate soil moisture measurements in remote ecosystems such as the Amazon are difficult and limited because of logistical constraints. Time domain reflectometry (TDR) sensors are widely used to monitor soil moisture and require calibration to convert the TDR's dielectric permittivity measurement (Ka) to volumetric water content (θv). In this study, our objectives were to develop a field-based calibration of TDR sensors in an old-growth upland forest in the central Amazon, to evaluate the performance of the calibration, and then to apply the calibration to determine the dynamics of soil moisture content within a 14.2-m-deep vertical soil profile. Depth-specific TDR calibration using local soils in a controlled laboratory setting yielded a novel Ka–θv third-degree polynomial calibration. The sensors were later installed to their specific calibration depth in a 14.2-m pit. The widely used Ka–θv relationship (Topp model) underestimated the site-specific θv by 22–42%, indicating significant error in the model when applied to these well-structured, clay-rich tropical forest soils. The calibrated wet- and dry-season θv data showed a variety of depth and temporal variations highlighting the importance of soil textural differentiation, root uptake depths, as well as event to seasonal precipitation effects. Data such as these are greatly needed for improving our understanding of ecohydrological processes within tropical forests and for improving models of these systems in the face of changing environmental conditions.

Major components of hydrologic and elemental cycles reside underground, where their complex dynamics and linkages to surface waters are obscure. We delineated seasonal subsurface flow and transport dynamics along a hillslope in the Rocky Mountains (USA), where precipitation occurs primarily as winter snow and drainage discharges into the East River, a tributary of the Gunnison River. Hydraulic and geochemical measurements down to 10 m below ground surface supported application of transmissivity feedback of snowmelt to describe subsurface flow and transport through three zones: soil, weathering shale, and saturated fractured shale. Groundwater flow is predicted to depths of at least 176 m, although a shallower limit exists if hillslope-scale hydraulic conductivities are higher than our local measurements. Snowmelt during the high snowpack water year 2017 sustained flow along the weathering zone and downslope within the soil, while negligible downslope flow occurred along the soil during the low snowpack water year 2018. We introduce subsurface concentration-discharge (C-Q) relations for explaining hillslope contributions to C-Q observed in rivers and demonstrate their calculations based on transmissivity fluxes and measured pore water specific conductance and dissolved organic carbon. The specific conductance data show that major ions in the hillslope pore waters, primarily from the weathering and fractured shale, are about six times more concentrated than in the river, indicating hillslope solute loads are disproportionately high, while flow from this site and similar regions are relatively smaller. This methodology is applicable in different representative environments within snow-dominated watersheds for linking their subsurface exports to surface waters.

Evapotranspiration (ET) is a key component of the water balance, which influences hydrometeorology, water resources, carbon and other biogeochemical cycles, and ecosystem diversity. This study aims to investigate the spatio-temporal variations of ET at the East River watershed in Colorado and analyze the factors that control these variations. ET was acquired using the community land model (CLM) simulations and was compared with the values estimated using Fu's equation and a watershed-scale water balance equation. The simulation results showed that 55% of annual precipitation in the East River is lost to ET, in which 75% of the ET comes from the summer months (May to September). We also found that the contribution of transpiration to the total ET was ~50%, which is much larger than that of soil evaporation (32%) and canopy evaporation (18%). Spatial analysis indicated that the ET is greater at elevations of 2950-3200 m and lower along the river valley ( < 2750 m) and at the high elevations ( > 3900 m). A correlation analysis of factors affecting ET showed that the land elevation, air temperature, and vegetation are closely correlated and together they govern the ET spatial variability. The results also suggested that ET in areas with more finely textured soil is slightly larger than regions with coarse-texture soil. This study presents a promising approach to the assessment of ET with a high spatiotemporal resolution over watershed scales and investigates factors controlling ET spatiotemporal variations.

The U.S. Department of Energy's Watershed Function Scientific Focus Area (SFA), centered in the East River, Colorado, generates diverse datasets including hydrological, geological, geochemical, geophysical, ecological, microbiological and remote sensing data. The project has deployed extensive field infrastructure involving hundreds of sensors that measure highly diverse phenomena (e.g. stream and groundwater hydrology, water quality, soil moisture, weather) across the watershed. Data from the sensor network are telemetered and automatically ingested into a queryable database. The data are subsequently quality checked, integrated with the United States Geological Survey's stream monitoring network using a custom data integration broker, and published to a portal with interactive visualizations. The resulting data products are used in a variety of scientific modeling and analytical efforts. This paper describes the SFA's end-to-end infrastructure and services that support the generation of integrated datasets from a watershed sensor network. The development and maintenance of this infrastructure, presents a suite of challenges from practical field logistics to complex data processing, which are addressed through various solutions. In particular, the SFA adopts a holistic view for data collection, assessment and integration, which dramatically improves the products generated, and enables a co-design approach wherein data collection is informed by model results and vice-versa.

To understand how redox processes influence carbon, nitrogen, and iron cycling within the intrameander hyporheic zone, we developed a biotic and abiotic reaction network and incorporated it into the reactive transport simulator PFLOTRAN. Two-dimensional reactive flow and transport simulations were performed (1) to evaluate how transient hydrological conditions control the lateral redox zonation within an intrameander region of the East River in Colorado and (2) to quantify the impact of a single meander on subsurface exports of carbon and other geochemical species to the river. The meander's overall contribution to the river was quantified by integrating geochemical outfluxes along the outside of the meander bend. The model was able to capture the field-observed trends of dissolved oxygen, nitrate, iron, pH, and total inorganic carbon along a 2-D transect. Consistent with field observations, simulated dissolved oxygen and nitrate decreased along the intrameander flow paths while iron (Fe2+) concentration increased. The simulation results further demonstrated that the reductive potential of the lateral redox zonation was controlled by groundwater velocities resulting from river stage fluctuations, with low-water conditions promoting reducing conditions. The sensitivity analysis results showed that permeability had a more significant impact on biogeochemical zonation compared to the reaction pathways under transient hydrologic conditions. The simulation results further indicated that the meander acted as a sink for organic and inorganic carbon as well as iron during the extended baseflow and high-water conditions; however, these geochemical species were released into the river during the falling limb of the hydrograph.

Accurate estimates of infiltration and groundwater recharge are critical for many hydrologic, agricultural and environmental applications. Anticipated climate change in many regions of the world, especially in tropical areas, is expected to increase the frequency of high-intensity, short-duration precipitation events, which in turn will affect the groundwater recharge rate. Estimates of recharge are often obtained using monthly or even annually averaged meteorological time series data. In this study we employed the HYDRUS-1D software package to assess the sensitivity of groundwater recharge calculations to using meteorological time series of different temporal resolutions (i.e., hourly, daily, weekly, monthly and yearly averaged precipitation and potential evaporation rates). Calculations were applied to three sites in Brazil having different climatological conditions: a tropical savanna (the Cerrado), a humid subtropical area (the temperate southern part of Brazil), and a very wet tropical area (Amazonia). To simplify our current analysis, we did not consider any land use effects by ignoring root water uptake. Temporal averaging of meteorological data was found to lead to significant bias in predictions of groundwater recharge, with much greater estimated recharge rates in case of very uneven temporal rainfall distributions during the year involving distinct wet and dry seasons. For example, at the Cerrado site, using daily averaged data produced recharge rates of up to 9 times greater than using yearly averaged data. In all cases, an increase in the time of averaging of meteorological data led to lower estimates of groundwater recharge, especially at sites having coarse-textured soils. Our results show that temporal averaging limits the ability of simulations to predict deep penetration of moisture in response to precipitation, so that water remains in the upper part of the vadose zone subject to upward flow and evaporation.

Extreme weather, fires, and land use and climate change are significantly reshaping interactions within watersheds throughout the world. Although hydrological–biogeochemical interactions within watersheds can impact many services valued by society, uncertainty associated with predicting hydrologydriven biogeochemical watershed dynamics remains high. With an aim to reduce this uncertainty, an approximately 300-km2 mountainous headwater observatory has been developed at the East River, CO, watershed of the Upper Colorado River Basin. The site is being used as a testbed for the Department of Energy supported Watershed Function Project and collaborative efforts. Building on insights gained from research at the “sister” Rifle, CO, site, coordinated studies are underway at the East River site to gain a predictive understanding of how the mountainous watershed retains and releases water, nutrients, carbon, and metals. In particular, the project is exploring how early snowmelt, drought, and other disturbances influence hydrological–biogeochemical watershed dynamics at seasonal to decadal timescales. A system-of-systems perspective and a scale-adaptive simulation approach, involving the combined use of archetypal watershed subsystem “intensive sites” are being tested at the site to inform aggregated watershed predictions of downgradient exports. Complementing intensive site hydrological, geochemical, geophysical, microbiological, geological, and vegetation datasets are long-term, distributed measurement stations and specialized experimental and observational campaigns. Several recent research advances provide insights about the intensive sites as well as aggregated watershed behavior. The East River “community testbed” is currently hosting scientists from more than 30 institutions to advance mountainous watershed methods and understanding.

Data quality control is one of the most time consuming activities within Research Infrastructures (RIs), especially when involving observational data and multiple data providers. In this work we report on our ongoing development of data rogues, a scalable approach to manage data quality issues for observational data within RIs. The motivation for this work started with the creation of the FLUXNET2015 dataset, which includes carbon, water, and energy fluxes plus micrometeorological and ancillary data measured in over 200 sites around the world. To create an uniform dataset, including derived data products, extensive work on data quality control was needed. The unpredictable nature of observational data quality issues makes the automation of data quality control inherently difficult. Developed based on this experience, the data rogues methodology allows for increased automation of quality control activities by systematically identifying, cataloging, and documenting implementations of solutions to data issues. We believe this methodology can be extended and applied to others domains and types of data, making the automation of data quality control a more tractable problem.

Metadata describe the ancillary information needed for data preservation and independent interpretation, comparison across heterogeneous datasets, and quality assessment and quality control (QA/QC). Environmental observations are vastly diverse in type and structure, can be taken across a wide range of spatiotemporal scales in a variety of measurement settings and approaches, and saved in multiple formats. Thus, well-organized, consistent metadata are required to produce usable data products from diverse environmental observations collected across field sites. However, existing metadata reporting protocols do not support the complex data synthesis and model-data integration needs of interdisciplinary earth system research. We developed a metadata reporting framework (FRAMES) to enable management and synthesis of observational data that are essential in advancing a predictive understanding of earth systems. FRAMES utilizes best practices for data and metadata organization enabling consistent data reporting and compatibility with a variety of standardized data protocols. We used an iterative scientist-centered design process to develop FRAMES, resulting in a data reporting format that incorporates existing field practices to maximize data-entry efficiency. Thus, FRAMES has a modular organization that streamlines metadata reporting and can be expanded to incorporate additional data types. With FRAMES's multi-scale measurement position hierarchy, data can be reported at observed spatial resolutions and then easily aggregated and linked across measurement types to support model-data integration. FRAMES is in early use by both data originators (persons generating data) and consumers (persons using data and metadata). In this paper, we describe FRAMES, identify lessons learned, and discuss areas of future development.

Data quality control is one of the most time consuming activities within Research Infrastructures (RIs), especially when involving observational data and multiple data providers. In this work we report on our ongoing development of data rogues, a scalable approach to manage data quality issues for observational data within RIs. The motivation for this work started with the creation of the FLUXNET2015 dataset, which includes carbon, water, and energy fluxes plus micrometeorological and ancillary data measured in over 200 sites around the world. To create an uniform dataset, including derived data products, extensive work on data quality control was needed. The unpredictable nature of observational data quality issues makes the automation of data quality control inherently difficult. Developed based on this experience, the data rogues methodology allows for increased automation of quality control activities by systematically identifying, cataloging, and documenting implementations of solutions to data issues. We believe this methodology can be extended and applied to others domains and types of data, making the automation of data quality control a more tractable problem.

Identifying dynamic causal inference involved in flow and transport processes in complex fractured-porous media is generally a challenging task, because nonlinear and chaotic variables may be positively coupled or correlated for some periods of time, but can then become spontaneously decoupled or non-correlated. In his 2002 paper (Faybishenko, 2002), the author performed a nonlinear dynamical and chaotic analysis of time-series data obtained from the fracture flow experiment conducted by Persoff and Pruess (1995), and, based on the visual examination of time series data, hypothesized that the observed pressure oscillations at both inlet and outlet edges of the fracture result from a superposition of both forward and return waves of pressure propagation through the fracture. In the current paper, the author explores an application of a combination of methods for detecting nonlinear chaotic dynamics behavior along with the multivariate Granger Causality (G-causality) time series test. Based on the G-causality test, the author infers that his hypothesis is correct, and presents a causation loop diagram of the spatial-temporal distribution of gas, liquid, and capillary pressures measured at the inlet and outlet of the fracture. The causal modeling approach can be used for the analysis of other hydrological processes, for example, infiltration and pumping tests in heterogeneous subsurface media, and climatic processes, for example, to find correlations between various meteorological parameters, such as temperature, solar radiation, barometric pressure, etc.

Soil depth tends to vary from a few centimeters to several meters, depending on many natural and environmental factors. We hypothesize that the cumulative effect of these factors on soil depth, which is chiefly dependent on the process of biogeochemical weathering, is particularly affected by soil porewater (i.e., solute) transport and infiltration from the land surface. Taking into account evidence for a non-Gaussian distribution of rock weathering rates, we propose a simple mathematical model to describe the relationship between soil depth and infiltration flux. The model was tested using several areas in mostly semi-arid climate zones. The application of this model demonstrates the use of fundamental principles of physics to quantify the coupled effects of the five principal soil-forming factors of Dokuchaev.

In situ measurements of deformations, stresses, and closure of fractures, affecting water inflow following coal mining, are challenging due to the inaccessibility of fractured rock. In this paper, the authors studied the closure process of the fractured rock mass with the cover stress re-establishment based on a theoretical analysis and a scale model testing. A quantitative analysis is used to study the fracture distribution in the fractured zone. A function to describe a fracture aperture distribution in the fractured zone is proposed, which takes into account the curvature and thickness of the fractured rock. The theoretical analysis and a scale model testing both indicate that the cover stress re-establishment with mining distance increasing and the relationship between the fracture closure and cover stress re-establishment both satisfy a logarithmic function. The scale model test also shows the following features: (1) the fracture ratio (which is the fracture area divided by the total area of fracture and intact rock with a unit width in the vertical or horizontal direction) in the lower part of the fractured rock mass is greater than that in the upper part; (2) the initially fast decreased of fracture ratios is then followed by a slower decrease during the cover stress re-establishment process; (3) in the upper part of the rock mass, the vertical directional fractures with small apertures are being closed with cover stress re-establishment, which indicates an increase in the water resistance reducing the seepage from these parts of the fractured zone. This study improves the general understanding of the fracture closure process and cover stress re-establishment in the fractured rock mass after coal mining ceased, and provides a theoretical basis for water resource protection in case of underground coal mining.

The objective of the current paper is to extend the theoretical approach and an analytical solution, which was proposed by Babchin and Faybishenko (2014), for the evaluation of a capillary pressure (Pc) curve in porous media based on the apparent specific surface area, using an explicit combination of the relative permeability functions for the wetting and nonwetting phases. Specifically, in the current paper, the authors extended this approach by the application of two types of capillary bundle models with different formulations of effective capillary radius formulae. The application of the new models allowed the authors to improve the results of calculations of the effective average contact angle given in the paper by Babchin and Faybishenko (2014). The validation of the new models for calculations of the Pc curve is also given in this paper using the results of a specifically designed core experiment, which was originally conducted by Ayub and Bentsen (2001).

Although CO2 fluxes from soils are often assumed to originate within shallow soil horizons (

Science data gateways are effective in providing complex science data collections to the world-wide user communities. In this paper we describe a gateway for the Advanced Simulation Capability for Environmental Management (ASCEM) framework. Built on top of established web service technologies, the ASCEM data gateway is specifically designed for environmental modeling applications. Its key distinguishing features include (1) handling of complex spatiotemporal data, (2) offering a variety of selective data access mechanisms, (3) providing state-of-the-art plotting and visualization of spatiotemporal data records, and (4) integrating seamlessly with a distributed workflow system using a RESTful interface. ASCEM project scientists have been using this data gateway since 2011.

This paper is concerned with the evaluation of permeability of fractured rock mass due to the cover stress re-establishment, which is a major factor in controlling water and gas flow rate induced by mining operations in fractured rock. The case study considered in this paper is based on the results of observations of groundwater inrush and a decrease in water inflow from the fractured roof strata due to mining advancing in the Taiping Coalmine, Shandong Province, China. A conceptual model of an effective porous media was used to assess the permeability distribution in the fractured zone induced by coal mining. The cover stress re-establishment in gob fractured rock mass was evaluated using an empirical formula based on the surface subsidence. A simplified conceptual model of the fractured zone was used to evaluate the deformation of fractured zone along with the evaluation of changes in the rock permeability above the gob due to the cover stress re-establishment. These data were then used to calculate the water inflow rate into the panel. Predicted water inflow rates have been found to be in good agreement with those from monitoring data. This study improved the understanding of the mechanisms of the post-mining cover stress re-establishment on permeability change of the overburden fracture rock strata. These results can then be applied for numerical simulations of the process of overburden failure and consequent groundwater inrush due to coal mining.

Background: During a field-scale chromium treatability study, a single dose of a slow release electron donor (HRC) was applied to a contaminated aquifer to stimulate microbial reductive precipitation of hexavalent chromium Cr(VI). Here we present analysis of microarray-based prokaryotic population dynamics and correlations with geochemical and geophysical observations following this application over two years. Methods: A high-density 168 rRNA phylogenetic microarray (PhyloChip) and a functional gene array (FGA) were used to analyze groundwater samples from multiple depths in injection and monitoring wells taken at intervals pre-and postHRC injection. Following filtration, genomic DNA was extracted and PCR amplicons or MDA amplified community-DNA were analyzed by microarray hybridization. A range of geochemical and geophysical parameters were also monitored. Results: Following HRC injection reducing conditions had rapidly established with a corresponding decline in DO, Eh and nitrate. Cr(VI) concentrations declined steadily over 6 weeks and remained below upgradient concentrations. PhyloChip data demonstrated depth stratified microbial communities with temporal shifts in composition corresponding with observed geochemistry. A sustained enrichment of iron and sulfate reducing bacteria was observed over 2 years, suggesting indirect chromium immobilization through interaction with reactive iron or sulfide by-products. Nitrate reducers such as Pseudomonas also remained elevated over the two years and FGA array data demonstrated a sustained enrichment of Pseudomonas chromate reductase genes suggesting direct reduction of chromate may also be significant in chromium immobilization. Based on this data, organisms representing each of these functional groups have been isolated and characterized. Conclusions: The combination of phylogenetic and functional gene arrays represents a complementary highthroughput approach to elucidating mechanisms responsible for contaminant immobilization in the subsurface.

The overall objective of this presentation is to demonstrate a conceptual multiscale, multidomain model of coupling of biogeochemical and hydrogeological processes during bioremediation of Cr(VI) contaminated groundwater at Hanford 100H site. A slow release polylactate, Hydrogen Release Compound (HRCTM), was injected in Hanford sediments to stimulate immobilization of Cr(VI). The HRC injection induced a 2-order-of-magnitude increase in biomass and the onset of reducing biogeochemical conditions [e.g., redox potential decreased from +240 to -130 mV and dissolved oxygen (DO) was completely removed]. A three-well system, comprised of an injection well and upgradient and downgradient monitoring wells, was used for conducting the in situ biostimulation, one regional flow (no-pumping) tracer test, and five pumping tests along with the Br-tracer injection. Field measurements were conducted using a Br ion-selective electrode and a multiparameter flow cell to collect hourly data on temperature, pH, redox potential, electrical conductivity, and DO. Groundwater sampling was conducted by pumping through specially designed borehole water samplers. Cross-borehole radar tomography and seismic measurements were carried out to assess the site background lithological heterogeneity and the migration pathways of HRC byproducts through groundwater after the HRC injection.

To improve understanding of the physics of dynamic instabilities in unsaturated flow processes within the Paintbrush nonwelded unit (PTn) and the middle nonlithophysal portion of the Topopah Spring welded tuff unit (TSw) of Yucca Mountain, we analyzed data from a series of infiltration tests carried out at two sites (Alcove 4 and Alcove 6) in the Exploratory Studies Facility, using analytical and empirical functions. The analysis of infiltration rates measured at both sites showed three temporal scales of infiltration rate: (1) a macro-scale trend of overall decreasing flow, (2) a meso-scale trend of fast and slow motion exhibiting three-stage variations of the flow rate (decreasing, increasing, and [again] decreasing flow rate, as observed in soils in the presence of entrapped air), and (3) micro-scale (high frequency) fluctuations. Infiltration tests in the nonwelded unit at Alcove 4 indicate that this unit may effectively dampen episodic fast infiltration events; however, well-known Kostyakov, Horton, and Philip equations do not satisfactorily describe the observed trends of the infiltration rate. Instead, a Weibull distribution model can most accurately describe experimentally determined time trends of the infiltration rate. Infiltration tests in highly permeable, fractured, welded tuff at Alcove 6 indicate that the infiltration rate exhibits pulsation, which may have been caused by multiple threshold effects and water-air redistribution between fractures and matrix. The empirical relationships between the extrinsic seepage from fractures, matrix imbibition, and gravity drainage versus the infiltration rate, as well as scaling and self-similarity for the leading edge of the water front, are the hallmark of the nonlinear dynamic processes in water flow (under episodic infiltration through fractured tuff). Based on the analysis of experimental data, we propose a conceptual model of a dynamic fracture flow and fracture-matrix interaction in fractured tuff, incorporating the time-dependent processes of water redistribution in the fracture-matrix system.