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At least 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Multi-Scale Integrated Monitoring System for Enhancing Methane Emission Detection, Quantification & Prediction

This report details the progress and findings of a comprehensive study on reviewing existing solutions, identifying technology gaps, and formulating an “all-in-one” integrated strategy for developing the next-generation multiscale methane monitoring and modeling platform, conducted under grant number DE-FE0032292. Co-led by Dr. David Ebert, Dr. Binbin Weng, and Dr. Chenghao Wang at the University of Oklahoma, the project’s goal was to develop an integrated approach for building this engineering platform to detect, quantify, and mitigate methane emissions across various temporal scale, spatial scales, and sectors. The planning grant study began with an extensive review of various methane sensing and monitoring technologies and systems, surveying over 100 technology providers globally. This review revealed the prevalence of optical methods over chemical methods in commercially available sensors, with Non-Dispersive Infrared (NDIR), Tunable Diode Laser Absorption Spectroscopy (TDLAS), and Optical Gas Imaging (OGI) cameras being the most prevalent options. A trend towards more advanced optical techniques was observed, driven by increased regulatory focus and technological advancements. The technical evaluation of these sensing technologies provided crucial insights into their capabilities and limitations. The study examined emerging technologies such as Differential Absorption LiDAR (DIAL), which show promise for high-precision and long-range detection. The team then investigated the features and application bandwidth of various sensing platforms, including handheld, fixed/stationary, mobile, aerials, and spaceborne monitors. Pilot field studies were conducted to assess the capabilities of solutions for different emission scenarios. Field work with sensor deployments was conducted at three distinct site types: an oil & gas industry site, a cattle ranching operation, and a waste processing facility. The team also conducted a thorough review of methane flux inverse modeling approaches, focused on physically based methods. These approaches were categorized into simple, intermediate, and advanced methods. A realtime WRF-GHG (Weather Research and Forecasting-Greenhouse Gas) modeling system was developed and applied, incorporating multiple data sources to guide field experiments and inform methane plume detection. The project identified and analyzed numerous categories of methane data sources, including satellite measurements, ground-based sensors, and inventory databases. Key platforms examined include EDGAR, EPA GHGI, NASA TROPOMI, Carbon Mapper, and Climate TRACE, among others. The team proposed an architecture for a comprehensive methane monitoring platform. This system incorporates multi-source data acquisition, advanced data processing and assimilation, interactive visualization tools, and analytical capabilities for emissions forecasting and scenario analysis. The proposed platform aims to provide a user-friendly interface catering to various stakeholders, from researchers to policymakers. The architecture includes sophisticated data ingestion methods, a centralized data warehouse, and advanced analytical tools for data fusion and interpretation. To ensure the relevance and effectiveness of the proposed system, a comprehensive survey was conducted to gather stakeholder input on system requirements. Key findings include a strong need for integrating various data types and formats, a preference for real-time data updates and advanced visualization tools, and a demand for user-friendly interfaces catering to different expertise levels.

03 NATURAL GAS↗
DOE OSTI2025

Expansion and Update of the R&D Feedstock Carbon Intensity Calculator (FD-CIC) for R&D GREET 2025

The R&D Feedstock Carbon Intensity Calculator (R&D FD-CIC) is a transparent and easy-touse tool to estimate feedstock-specific carbon intensity (CI) of biofuel feedstocks, and to examine potential CI variations of different farming practices to grow agricultural feedstocks for biofuel production. The objective of the tool is to assess potential effects of different farming practices with underlined factors to reduce uncertainties in such assessment and help R&D activities. The original work and early versions of R&D FD-CIC were supported by Advanced Research Projects Agency–Energy (ARPA-E) of the Department of Energy, with recent support by the Bioenergy Technologies Office of the Department of Energy. The tool uses life cycle inventory (LCI) data of key farming inputs from the R&D Greenhouse gases, Regulated Emissions, and Energy use in Technologies (R&D GREET) model. The system boundary of R&D FD-CIC covers the cradle-to-farm-gate activities, including upstream emissions related to farming input manufacturing and feedstock production.

09 BIOMASS FUELS↗
NASA NTRS1975

A comparative interregional analysis of selected data from LANDSAT-1 and EREP for the inventory and monitoring of natural ecosystems

Comparative statistics were presented on the capability of LANDSAT-1 and three of the Skylab remote sensing systems (S-190A, S-190B, S-192) for the recognition and inventory of analogous natural vegetations and landscape features important in resource allocation and management. Two analogous regions presenting vegetational zonation from salt desert to alpine conditions above the timberline were observed, emphasizing the visual interpretation mode in the investigation. An hierarchical legend system was used as the basic classification of all land surface features. Comparative tests were run on image identifiability with the different sensor systems, and mapping and interpretation tests were made both in monocular and stereo interpretation with all systems except the S-192. Significant advantage was found in the use of stereo from space when image analysis is by visual or visual-machine-aided interactive systems. Some cost factors in mapping from space are identified. The various image types are compared and an operational system is postulated.

Poulton, C. E.↗
NASA NTRS2022

Canadian and Alaskan Wildfire Smoke Particle Properties, Their Evolution and Controlling Factors, From Satellite Observations

The optical and chemical properties of biomass burning (BB) smoke particles greatly affect the impact that wildfires have on climate and air quality. Previous work has demonstrated some links between smoke properties and factors such as fuel type and meteorology. However, the factors controlling BB particle speciation at emission are not adequately understood nor are the factors driving particle aging during atmospheric transport. As such, modeling wildfire smoke impacts on climate and air quality remains challenging. The potential to provide robust, statistical characterizations of BB particles based on ecosystem type and ambient environmental conditions with remote sensing data is investigated here. Space-based Multi-angle Imaging SpectroRadiometer (MISR) observations, combined with the MISR Research Aerosol (RA) algorithm and the MISR Interactive Explorer (MINX) tool, are used to retrieve smoke plume aerosol optical depth (AOD) and to provide constraints on plume vertical extent; smoke age; and particle size, shape, light-absorption properties, and absorption spectral dependence. These tools are applied to numerous wildfire plumes in Canada and Alaska, across a range of conditions, to create a regional inventory of BB particle-type temporal and spatial distribution. We then statistically compare these results with satellite measurements of fire radiative power (FRP) and land cover characteristics, as well as short-term climate, meteorological, and drought information from the Modern-Era Retrospective analysis for Research and Applications (MERRA-2) reanalysis and the North American Drought Monitor. We find statistically significant differences in the retrieved smoke properties based on land cover type, with fires in forests producing the thickest plumes containing the largest, brightest particles and fires in savannas and grasslands exhibiting the opposite. Additionally, the inferred dominant aging mechanisms and the timescales over which they occur vary systematically between land types. This work demonstrates the potential of remote sensing to constrain BB particle properties and the mechanisms governing their evolution over entire ecosystems. It also begins to realize this potential, as a means of improving regional and global climate and air quality modeling in a rapidly changing world.

Katherine T. Junghenn Noyes↗
NASA NTRS1982

The structure and evolution of ancient impact basins on Mars

It is pointed out that characteristic styles of degradation and modification of obvious Martian basins make it possible to recognize more subtle expressions. This approach is seen as providing not only additional basins to the existing inventory but also fundamental clues for initial impact basin structure and stratigraphy. It also reveals the long-lasting influence of basin formation on the crust of Mars in spite of extensive erosion and resurfacing. Consideration is given to five clear examples of modified impact basins, and regions around each that have undergone similar processes (fracturing, collapse, channeling) are delineated. These processes among the different basins are then compared, and similar zones of modification are correlated with concentric basin rings. Consideration is then given to the implications of these observations for current models of basin formation and to the role of impact basins in controlling regional tectonics. The results indicate that large multiring impact scars leave a major but sometimes subtle imprint on the geologic structure of stable crustal regions on Mars.

Schultz, P. H.↗
NASA NTRS2012

Contrasting Patterns of Damage and Recovery in Logged Amazon Forests From Small Footprint LiDAR Data

Tropical forests ecosystems respond dynamically to climate variability and disturbances on time scales of minutes to millennia. To date, our knowledge of disturbance and recovery processes in tropical forests is derived almost exclusively from networks of forest inventory plots. These plots typically sample small areas (less than or equal to 1 ha) in conservation units that are protected from logging and fire. Amazon forests with frequent disturbances from human activity remain under-studied. Ongoing negotiations on REDD+ (Reducing Emissions from Deforestation and Forest Degradation plus enhancing forest carbon stocks) have placed additional emphasis on identifying degraded forests and quantifying changing carbon stocks in both degraded and intact tropical forests. We evaluated patterns of forest disturbance and recovery at four -1000 ha sites in the Brazilian Amazon using small footprint LiDAR data and coincident field measurements. Large area coverage with airborne LiDAR data in 2011-2012 included logged and unmanaged areas in Cotriguacu (Mato Grosso), Fiona do Jamari (Rondonia), and Floresta Estadual do Antimary (Acre), and unmanaged forest within Reserva Ducke (Amazonas). Logging infrastructure (skid trails, log decks, and roads) was identified using LiDAR returns from understory vegetation and validated based on field data. At each logged site, canopy gaps from logging activity and LiDAR metrics of canopy heights were used to quantify differences in forest structure between logged and unlogged areas. Contrasting patterns of harvesting operations and canopy damages at the three logged sites reflect different levels of pre-harvest planning (i.e., informal logging compared to state or national logging concessions), harvest intensity, and site conditions. Finally, we used multi-temporal LiDAR data from two sites, Reserva Ducke (2009, 2012) and Antimary (2010, 2011), to evaluate gap phase dynamics in unmanaged forest areas. The rates and patterns of canopy gap formation at these sites illustrate potential issues for separating logging damages from natural forest disturbances over longer time scales. Multi-temporal airborne LiDAR data and coincident field measurements provide complementary perspectives on disturbance and recovery processes in intact and degraded Amazon forests. Compared to forest inventory plots, the large size of each individual site permitted analyses of landscape-scale processes that would require extremely high investments to study using traditional forest inventory methods.

Morton, D. C.↗
DOE OSTI2022

Patterns and controls on island‐wide aboveground biomass accumulation in second‐growth forests of Puerto Rico

Abstract Understanding the heterogeneity of biomass accumulation in second‐growth tropical forests following land use abandonment is important for informing ecosystem carbon models and forest restoration efforts. There is an urgent need for a broad sample of second‐growth forests to enhance our knowledge of carbon accumulation in human‐dominated landscapes, especially for older forests. Puerto Rico has predominantly second‐growth forests, ranging in age from approximately 25 to more than 80 years. We used an island‐wide sample of airborne lidar from the NASA Goddard Lidar, Hyperspectral, and Thermal (G‐LiHT) Airborne Imager collected on March 2017, forest inventory data, and data on forest age, precipitation, soils, and land use to estimate aboveground biomass stocks in moist and wet, second‐growth tropical forests. Biomass accumulation rates in Puerto Rico were lower, on average, than in other Neotropical forests. Median biomass across >16,700 ha of older second‐growth forests was 105 Mg ha −1 , and sampled biomass rarely surpassed 250 Mg ha −1 . Differences in biomass by age were large and persistent across different substrates and land uses, with a plateau in the pattern of island‐wide biomass accumulation after about 33 years. A spatial regression model showed that multiple factors were related to biomass accumulation, including time since abandonment, geologic substrate, past land use as coffee or pasture, precipitation, topographic wetness index, and slope. Our findings have important consequences for the total carbon storage and expected climate mitigation benefits of large‐scale reforestation efforts, and highlight the value of airborne lidar for quantifying biomass variability in complex tropical landscapes. Abstract in Spanish is available with online material.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Battery state-of-health diagnostics during fast cycling using physics-informed deep-learning

Rapid, in-situ Li-ion battery state-of-health (SOH) quantification is challenging. Li-ion battery aging can vary significantly with chemistry, operating conditions, cycling demands, electrode design, and operation history. As a cell ages, optimal and safe operating conditions need to be adapted to account for battery degradation by tracking critical aging modes such as loss-of-lithium-inventory (LLI), loss-of-active-material (LAM) in either electrode, and/or impedance rise. This manuscript describes a framework for identifying battery aging modes in-operando using fast-rate voltage charge/discharge responses. The framework uses a physically based Li-ion battery model to produce synthetic high-rate responses at aged states. The aging model is calibrated against experimental data from cells with different electrode loadings and cycled under a variety of fast-charging conditions (1 h, 15 min, 10 min, and 7 min charging). The synthetically generated high-rate responses at aged states are then used to train a deep-learning model to identify real cell state-of-health from fast charge/discharge battery voltage responses. The synthetically trained deep-learning model performance is validated by comparing to standard incremental capacity analysis and half-cell measurements. Finally, the framework demonstrates the benefits of using high-rate physics-based models to generate synthetic data for training deep-learning models.

25 ENERGY STORAGE↗
DOE OSTI2021

Multi-fidelity kinetic theory-based approach for the prediction of particle attrition: Application to jet cup attrition system

The timescale difference between the “fast” flow dynamics of fluidized bed reactors and the relatively “slow” rate of particle degradation makes the direct computational prediction of attrition challenging. An approach to this challenge is a multi-fidelity strategy where a high fidelity model for the flow dynamics is coupled with a lower fidelity model for the long-time resolution of the bulk attrition of the reactor inventory. We implement this approach using high-fidelity kinetic theory simulations to calculate the flow dynamics which are post-processed to calculate the frequency and intensity of the particle-particle and particle-wall collisions (e.g. collision energy spectra). This is combined with the particle breakage properties to construct the coefficients for a low-fidelity model [e.g. Monazam et al., 2018, Powder Technology 340, p. 528-536]. Simulations are performed of a jet cup attrition system containing Canadian hematite (Monazam et al. 2018). Furthermore, these are first analyzed using the collision energy spectra. Quantitative predictions of the mass loss are made using a low-fidelity model derived from the collision-spectra and a calibrated material breakage coefficient. The results are found to compare favorably with the experimental measurements.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2026

WholeTraveler Anonymized Data Phase 1

Phase 1 of the WholeTraveler Study data collection consisted of an online-only survey. This survey captured data on three categories of observable variation in the population relevant to transportation decisions. First, the survey collected traditional demographic data such as age, gender, income, and education level. Second, it collected data across personality, psychological, and preference categories. This included: 1. The "Big Five" inventory personality traits: openness to new experience, conscientiousness, extroversion, agreeableness, and neuroticism; 2. Risk and time preferences; and 3. Environmental preferences. Third, the survey collected data on historical behavior patterns including: 1. Adoption of (as well as interest in) new technologies or innovations (e.g., smartphones, PEVs, solar panels, adaptive cruise control [ACC]); 2. Car ownership history and current car ownership status; 3. Recent mode use across different time scales (e.g., previous week, previous month, previous year); and 4. Timing of major life events such as starting a family as well as overall lifecycle trajectory patterns. Data from Phase 1 and Phase 2 are linked by a unique respondent identifier. Anonymized versions of the Phase 1 and Phase 2 data are both available on Livewire.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Decontamination of Irradiated Nuclear Graphite Using High Temperature Molten Salt - 17447

Irradiated graphite is one of the most significant, large volume waste streams in the UK. After shut down of gas cooled reactors there will be ∼96,000 tonnes of nuclear graphite arising from pressure vessels, sealed or unsealed stacks, temporary surface storage and in silos, which may account for up to 30% by ILW volume of any future UK geological disposal facility. High temperature molten salt treatment (HMST) could be considered as a partitioning process of the activation and fission products from irradiated graphite. The main objective of the research is to optimize a specific graphite treatment technology compatible with older, current and future reactors to provide a safe and effective process to decontaminate graphite and reduce the waste inventory. In order to reach that purpose principal radionuclides contained in irradiated samples from Magnox reactors were investigated by germanium (Ge) gamma spectrometry. The next key tasks were to employ treatment at 450 deg. C in LiCl-KCl eutectic which included the following procedures: electrochemical cleaning of the salt, initial cyclic voltammetry (CV) of graphite followed by several steps of chrono-potentiometry (CP) with different current applied and CV was taken after each step. Once the treatment was established, experiments investigating the electro-refinement of the resultant salt mixtures were conducted as well as the comparison of gamma spectroscopy results of graphite before and after the treatment providing the result of total activity reduction of around 60%. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
NASA NTRS1972

Inventory of forest and rangeland and detection of forest stress

There are no author-identified significant results in this report. Some ERTS-1 imagery has been received for each of the test sites: Black Hills, Atlanta, and Manitou. Only small portions of each site are covered and clouds have precluded capturing good imagery over the center of each site. Discoloration infestations of ponderosa pine are being located and sized on CIR transparencies. A computer program was completed from microdensitometer scans of CIR photos which maps areas of an image which are spectrally similar. Decided differences between forest types are present as well as differences between forest and other vegetative and nonvegetative land classes.

Heller, R. C.↗
NASA NTRS1973

Analysis of ERTS imagery using special electronic viewing/measuring equipment

An electronic satellite image analysis console (ESIAC) is being employed to process imagery for use by USGS investigators in several different disciplines studying dynamic hydrologic conditions. The ESIAC provides facilities for storing registered image sequences in a magnetic video disc memory for subsequent recall, enhancement, and animated display in monochrome or color. Quantitative measurements of distances, areas, and brightness profiles can be extracted digitally under operator supervision. Initial results are presented for the display and measurement of snowfield extent, glacier development, sediment plumes from estuary discharge, playa inventory, phreatophyte and other vegetative changes.

Evans, W. E.↗
NASA NTRS2022

Patterns and Controls on Island-Wide Aboveground Biomass Accumulation in Second-Growth Forests of Puerto Rico

Understanding the heterogeneity of biomass accumulation in second-growth tropical forests following land use abandonment is important for informing ecosystem carbon models and forest restoration efforts. There is an urgent need for a broad sample of second-growth forests to enhance our knowledge of carbon accumulation in human-dominated landscapes, especially for older forests. Puerto Rico has predominantly second-growth forests, ranging in age from approximately 25 to more than 80 years. We used an island-wide sample of airborne lidar from the NASA Goddard Lidar, Hyperspectral, and Thermal (G-LiHT) Airborne Imager collected on March 2017, forest inventory data, and data on forest age, precipitation, soils, and land use to estimate aboveground biomass stocks in moist and wet, second-growth tropical forests. Biomass accumulation rates in Puerto Rico were lower, on average, than in other Neotropical forests. Median biomass across >16,700 ha of older second-growth forests was 105 Mg ha−1, and sampled biomass rarely surpassed 250 Mg ha−1. Differences in biomass by age were large and persistent across different substrates and land uses, with a plateau in the pattern of island-wide biomass accumulation after about 33 years. A spatial regression model showed that multiple factors were related to biomass accumulation, including time since abandonment, geologic substrate, past land use as coffee or pasture, precipitation, topographic wetness index, and slope. Our findings have important consequences for the total carbon storage and expected climate mitigation benefits of large-scale reforestation efforts, and highlight the value of airborne lidar for quantifying biomass variability in complex tropical landscapes.

Sebastián Martinuzzi↗
NASA NTRS1980

Stratification of forest vegetation for timber inventory using Landsat and collateral data

An automated forest stratification procedure based on Landsat and digital terrain data is reviewed. The system uses Landsat multispectral brightness values, a spatial texture channel, and digital terrain data information to divide Klamath National Forest vegetation into timber volume-homogeneous strata. The stratification process involves analyst-supervised class pooling editing, and the modeling of the regional type in a spatial manner using the digital terrain data. It is noted that for a given size and density class, the timber volume will change when the regional type changes, reflecting differences in growth potential.

Woodcock, C. E.↗
DOE OSTI2015

Nitrous oxide and methane emissions and nitrous oxide isotopic composition from waste incineration in Switzerland

Highlights: • N{sub 2}O emissions from waste incineration with SNCR NO{sub x} removal are 51.5 ± 10.6 g t{sup −1}. • This is significantly lower than the reported Swiss emission factor of 120 g t{sup −1} (FOEN, 2013). • N{sub 2}O contributes <0.3% and ≈2.5% of GHG emissions from SCR and SNCR plants. • Measured isotopic SP of 17.7‰ is likely characteristic for N{sub 2}O emissions from SNCR. • CH{sub 4} emitted by waste incineration is negligible, contributing <0.01% to total GHGs. - Abstract: Solid waste incineration accounts for a growing proportion of waste disposal in both developed and developing countries, therefore it is important to constrain emissions of greenhouse gases from these facilities. At five Swiss waste incineration facilities with grate firing, emission factors for N{sub 2}O and CH{sub 4} were determined based on measurements of representative flue gas samples, which were collected in Tedlar bags over a one year period (September 2010–August 2011) and analysed with FTIR spectroscopy. All five plants burn a mixture of household and industrial waste, and two of the plants employ NO{sub x} removal through selective non-catalytic reduction (SNCR) while three plants use selective catalytic reduction (SCR) for NO{sub x} removal. N{sub 2}O emissions from incineration plants with NO{sub x} removal through selective catalytic reduction were 4.3 ± 4.0 g N{sub 2}O tonne{sup −1} waste (wet) (hereafter abbreviated as t{sup −1}) (0.4 ± 0.4 g N{sub 2}O GJ{sup −1}), ten times lower than from plants with selective non-catalytic reduction (51.5 ± 10.6 g N{sub 2}O t{sup −1}; 4.5 ± 0.9 g N{sub 2}O GJ{sup −1}). These emission factors, which are much lower than the value of 120 g N{sub 2}O t{sup −1} (10.4 g N{sub 2}O GJ{sup −1}) used in the 2013 Swiss national greenhouse gas emission inventory, have been implemented in the most recent Swiss emission inventory. In addition, the isotopic composition of N{sub 2}O emitted from the two plants with SNCR, which had considerable N{sub 2}O emissions, was measured using quantum cascade laser spectroscopy. The isotopic site preference of N{sub 2}O – the enrichment of {sup 14}N{sup 15}NO relative to {sup 15}N{sup 14}NO – was found to be 17.6 ± 0.8‰, with no significant difference between the two plants. Comparison to previous studies suggests SP of 17–19‰ may be characteristic for N{sub 2}O produced from SNCR. Methane emissions were found to be insignificant, with a maximum emission factor of 2.5 ± 5.6 g CH{sub 4} t{sup −1} (0.2 ± 0.5 g CH{sub 4} GJ{sup −1}), which is expected due to high incinerator temperatures and efficient combustion.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Thermal Performance Analysis of a Geologic Borehole Repository

The Brazilian Nuclear Research Institute (IPEN) proposed a design for the disposal of Disused Sealed Radioactive Sources (DSRS) based on the IAEA Borehole Disposal of Sealed Radioactive Sources (BOSS) design that would allow the entirety of Brazil’s inventory of DSRS to be disposed in a single borehole. The proposed IPEN design allows for 170 waste packages (WPs) containing DSRS (such as Co-60 and Cs-137) to be stacked on top of each other inside the borehole. The primary objective of this work was to evaluate the thermal performance of a conservative approach to the IPEN proposal with the equivalent of two WPs and two different inside configurations using Co-60 as the radioactive heat source. The current WP configuration (heterogeneous) for the IPEN proposal has 60% of the WP volume being occupied by a nuclear radioactive heat source and the remaining 40% as vacant space. The second configuration (homogeneous) considered for this project was a homogeneous case where 100% of the WP volume was occupied by a nuclear radioactive heat source. The computational models for the thermal analyses of the WP configurations with the Co-60 heat source considered three different cooling mechanisms (conduction, radiation, and convection) and the effect of mesh size on the results from the thermal analysis. The results of the analyses yielded maximum temperatures inside the WPs for both of the WP configurations and various mesh sizes. The heterogeneous WP considered the cooling mechanisms of conduction, convection, and radiation. The temperature results from the heterogeneous WP analysis suggest that the model is cooled predominantly by conduction with effect of radiation and natural convection on cooling being negligible. From the thermal analysis comparing the two WP configurations, the results suggest that either WP configuration could be used for the design. The mesh sensitivity results verify the meshes used, and results obtained from the thermal analyses were close to being independent of mesh size. The results from the computational case and analytically-calculated case for the homogeneous WP in benchmarking were almost identical, which indicates that the computational approach used here was successfully verified by the analytical solution.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2021

Mixing Cell Model: A One-Dimensional Numerical Model for Assessment of Water Flow and Contaminant Transport in the Unsaturated Zone

This report describes the Mixing Cell Model code, a one dimensional model for water flow and solute transport in the unsaturated zone under steady state or transient flow conditions. The model is based on the principles and assumptions underlying mixing-cell model formulations. The unsaturated zone is discretized into a series of independent mixing cells. Each cell may have unique hydrologic, lithologic, and sorptive properties. Ordinary differential equations describe the material (water and solute) balance within each cell. Water-flow equations are derived from the continuity equation, assuming that unit gradient conditions exist at all times in each cell. Pressure gradients are considered implicitly through model discretization. Unsaturated hydraulic conductivity and moisture contents are determined by the material specific moisture-characteristic curves. Solute-transport processes include explicit treatment of advective processes, first order chain decay, and linear sorption reactions. Dispersion is addressed through implicit and explicit dispersion. Implicit dispersion is an inherent feature of all mixing-cell models and originates from the formulation of the problem in terms of mass balance around fully mixed volume elements. Expressions are provided that relate implicit dispersion to the physical dispersion of the system. Two FORTRAN codes were developed to solve the water flow and solute-transport equations: (1) the Mixing Cell Model for Flow (MCMF) solves transient water-flow problems and (2) the Mixing Cell Model for Transport (MCMT) solves the solute-transport problem. The transient water-flow problem is typically solved first by estimating the water flux through each cell in the model domain as a function of time using the MCMF code. These data are stored in either ASCII or binary files that are later read by the solute transport code (MCMT). Code output includes solute pore water concentrations, water and solute inventories in each cell and at each specified output time, and water and solute fluxes through each cell and specified output time. Computer run times for coupled transient water flow and solute transport were typically several seconds on a 2 GHz Intel Pentium IV desktop computer. The model was benchmarked against analytical solutions and finite element approximations to the partial differential equations (PDE) describing unsaturated flow and transport. Differences between the maximum solute flux estimated by the mixing cell model and the PDE models were typically less than two percent. This revision includes an option for a fixed concentration lower boundary condition for diffusive fluxes for versions 020321 and later.

54 ENVIRONMENTAL SCIENCES↗