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DOE OSTI2023

Peatland hydrology across scale: a probabilistic framework for confronting variability, heterogeneity, and uncertainty (Final Report)

Our project aimed to guide the representations of peatland hydrology and water-carbon feedbacks within Earth System Models, by improving process understanding and developing parsimonious models that elucidate the effects of hydroclimatic variability and spatial heterogeneity. Our research questions centered on the three key drivers of peatland hydrology: (1) seasonal and interannual hydroclimatic fluctuations, (2) spatial heterogeneity of peatland microtopography, and (3) hydrological connectivity across landscape units within a peatland watershed. Our analyses and model testing used existing long-term datasets within the Marcell Experimental Forest (MEF), with new data collected whenever necessary. To date, we have demonstrated the strong influence of water table elevations on the temperature sensitivity of CH 4 emissions, using a newly developed eddy covariance dataset spanning eleven years at MEF. Specifically, higher water tables dampen the increase in CH 4 emissions in the spring as well as their decrease in the fall, resulting in hysteresis. These results imply that any hydroclimatological changes in peatlands that shift seasonal water availability from winter to summer will increase annual CH 4 emissions, even if soil temperature remains unchanged. To further investigate water table elevation change within the peatland microtopography, we installed automated water table gauges across four bog-forest transects (the “lagg”) in two peatland watersheds at MEF, which are hotspots of intense biogeochemical activity. These measurements will give us new information about the extent of lagg expansion and contraction during snowmelt and high intensity rainfall events, as well as the directionality of water and nutrient flow into the bog from the surrounding forests. Finally, we investigated the hydrological connectivity across the peatland watershed complex during early spring – a critical period where water table is elevated from snowmelt – using extended hydrological records from MEF (e.g., snow and frost depths, water table elevations, streamflow). The importance of thermal and wintertime processes within the Energy Exascale Earth System Model (E3SM) was determined through sensitivity analyses. Results from data analyses show that (i) streamflow has decreased over decades likely due to increased evapotranspiration rates (despite no detectable trends in precipitation), (ii) spring streamflow generation is controlled by a sequence of fill-and-spill pathways from the snowpack to the stream through peatland water stores, and (iii) frost depth is a key explanatory variable for the timing and magnitude of streamflow. These results suggest that frost plays an important role in connecting surface water storage in peatlands to stream outlets, and that the hydrological connectivity across the peatland watershed complex can mediate the sensitivity of hydrological responses to climate variations.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1994

VLSI-based Video Event Triggering for Image Data Compression

Long-duration, on-orbit microgravity experiments require a combination of high resolution and high frame rate video data acquisition. The digitized high-rate video stream presents a difficult data storage problem. Data produced at rates of several hundred million bytes per second may require a total mission video data storage requirement exceeding one terabyte. A NASA-designed, VLSI-based, highly parallel digital state machine generates a digital trigger signal at the onset of a video event. High capacity random access memory storage coupled with newly available fuzzy logic devices permits the monitoring of a video image stream for long term (DC-like) or short term (AC-like) changes caused by spatial translation, dilation, appearance, disappearance, or color change in a video object. Pre-trigger and post-trigger storage techniques are then adaptable to archiving only the significant video images.

Williams, Glenn L.↗

DOE OSTI2020

Energy Storage in Long-Term System Models: A Review of Considerations, Best Practices, and Research Needs

Technological change and policy support have heightened expectations for the role of energy storage in power systems, creating a need to enhance representations of energy storage in long-term models to inform decision-making. Energy storage technologies have complex and diverse cost, value, and performance characteristics that make them challenging to model, but there is limited guidance about best practices and research gaps for energy storage analysis. This paper reviews the literature and draws upon our collective experience to provide recommendations to analysts on approaches for representing energy storage in long-term electric sector models, navigating tradeoffs in model development, and identifying research gaps for existing tools and data. The review focuses on national-scale models with technological, temporal, and regional detail given their prevalence in planning and policy, though many insights are transferable to other modeling contexts. It also offers guidance to consumers of model outputs on proper use and interpretation based on model strengths and limitations. In particular, this review demonstrates the importance of capturing how the values of energy storage and other resources change as the system composition changes (e.g. with different levels of storage, renewables deployment, and emissions outcomes). These considerations require model detail like high spatiotemporal resolutions and endogenous investments that global integrated assessment models and price-taker frameworks do not typically resolve. Research gaps include linking tools of different resolutions, developing reduced-form representations of value streams, incorporating hybrid energy storage and renewable systems, and representing longer-duration energy storage technologies.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

DOE OSTI2021

SPECs Early-Stage Decision Model: User Manual

The SPECs Early-Stage Decision (ESD) model is central to the SPECs procurement solutions toolkit. The ESD model is an Excel-based spreadsheet model, which provides information about the economic and strategic value of a proposed battery-storage project or solar-plus-storage (solar-plus) project. The model can be used to explore combinations of storage-related project value streams in order to define a potential project, while educating co-op decision-makers about project benefits and costs. A sensitivity analysis function speeds the development of "what-if" scenarios. A gap analysis function solves for top-priority metrics and supports the inclusion of hard-to-monetize strategic values, such as the value of storage to defer costly system upgrades in light of increasing distributed solar and other distributed energy resources (DERs). Model outputs include the utility data, assumptions, and use-case scenarios that are recommended content for the requests for proposals (RFPs). The model may also provide an initial "sanity check" for RFP responses, supporting further discussions among utility staff, vendors and stakeholders. The ESD is not a "finance-grade" modeling tool, and users are cautioned to be mindful of its limitations, but the model has been reviewed by users, who recommend it as a way to drive faster and better project design and planning, as well as to facilitate better communications with vendors, grid partners, and stakeholders.

14 SOLAR ENERGY↗

DOE OSTI2021

On the Representation of Hyporheic Exchange in Models for Reactive Transport in Stream and River Corridors

Efforts to include more detailed representations of biogeochemical processes in basin-scale water quality simulation tools face the challenge of how to tractably represent mass exchange between the flowing channels of streams and rivers and biogeochemical hotspots in the hyporheic zones. Multiscale models that use relatively coarse representations of the channel network with subgrid models for mass exchange and reactions in the hyporheic zone have started to emerge to address that challenge. Two such multiscale models are considered here, one based on a stochastic Lagrangian travel time representation of advective pumping and one on multirate diffusive exchange. The two models are formally equivalent to well-established integrodifferential representations for transport of non-reacting tracers in steady stream flow, which have been very successful in reproducing stream tracer tests. Despite that equivalence, the two models are based on very different model structures and produce significantly different results in reactive transport. In a simple denitrification example, denitrification is two to three times greater for the advection-based model because the multirate diffusive model has direct connections between the stream channel and transient storage zones and an assumption of mixing in the transient storage zones that prevent oxygen levels from dropping to the point where denitrification can progress uninhibited. By contrast, the advection-based model produces distinct redox zonation, allowing for denitrification to proceed uninhibited on part of the hyporheic flowpaths. These results demonstrate that conservative tracer tests alone are inadequate for constraining representation of mass transfer in models for reactive transport in streams and rivers.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Evaluation of Material Balance Approaches for Hanford Direct-Feed Low Activity Waste Processing - 20022

The Hanford Site has accumulated millions of gallons of tank waste from reprocessing spent fuel to recover plutonium, uranium, cesium, and strontium. The supernatant from the accumulated tank waste will be treated using a Direct Feed Low-Activity Waste approach. The supernatant will be treated to remove solids and cesium in the Tank-Side Cesium Removal process in the Hanford tank farm, then vitrified in a semi-batch process in the Hanford Waste Treatment and Immobilization Plant (WTP). Currently, each batch of feed is sampled at three locations prior to being fed to the melter: the feed qualification tank in the Hanford tank farm as well as the concentrate receipt vessel (CRV) and melter feed preparation vessel (MFPV) in the WTP. The feed qualification sample is taken from a large batch of accumulated feed, only two to three samples are expected each year. Approximately 275 samples from the CRVs and 1100 samples from the MFPV are expected each year. An evaluation was performed to determine if a material balance based on the feed qualification sample could replace most of the sampling in the CRVs and MFPVs. The evaluation consisted of three elements: (1) determination of the practicality of using a material balance to estimate the stream composition of the CRV and MFPV contents, (2) evaluation of whether the material balance could be automated using the existing process control system, and (3) determination of the uncertainty in glass composition using the material balance approach. It is assumed that periodic sampling at the CRV and MFPV would be performed periodically to re-baseline the material balance, evaluations are in progress to determine the frequency of this periodic sampling. Process sample locations downstream of the melter were reviewed as well, but the partitioning of semi-volatile species in the melter was determined to preclude extending the material balance approach past the melter. It was determined that replacement of the CRV sample location was feasible and did not increase process uncertainty or significantly impact waste loading. Replacement of the MFPV sample was also determined to be feasible, but that measurement of the glass former chemical addition may be needed prior to addition of these chemicals to the MFPV. This measurement could be performed by an in situ laser-induced breakdown spectroscopy (LIBS) system. Limited tests were performed to evaluate LIBS for direct measurements of the low-activity waste melter feed. The use of a material balance would eliminate over 1200 samples each year if only 10% of the CRV and MFPV batches are sampled and could likely allow the WTP laboratory to operate on days only versus 24/7 operation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Groundwater and Surface Water Flow (GSFLOW) model files for the East River, Colorado

The data package contains model input files and executables for the East River, Colorado (750 km2) located in the headwaters of the Upper Colorado River Basin. The code applied is the U.S. Geological Survey (USGS) Groundwater and Surface Water Flow (GSFLOW) model. The model contains a 100-m grid resolution to represent topographic complexity and a daily timestep accounts for energy and water partitioning between the snowpack, vegetation, soil zone and bedrock. The land surface model is dynamically linked to a three-dimensional groundwater flow model that allows for streamflow gaining and losing conditions. The groundwater model accounts for nine stratigraphic units and extends 400 m below land surface. Using this modeling framework we explore historical water budgets (water year 1987-2022) and the influence of seasonal warming and associated mechanisms driving groundwater declines and streamflow loss. A Readme_062424.txt file provides instructions on how to download all files. Input and output files are provided for the historical simulation representative of water years 1987 to 2022 (i.e. baseline) and the all-year +4C warming scenario. Instructions are provided to run the seasonal warming scenarios with warming applied only to the autumn, winter, spring or summer months. Modeled output used in figures for Carroll et al., 2024 are also provided with metadata describing where these data were obtained. This dataset additionally includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata; and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.Updated on 06-24-2024: The dataset was updated to include model outputs (updated base.zip and 4C.zip files), figure source files (Figure_Source_Files.zip), an updated Readme file (Readme_062424.txt), climate input files (climate_input_files.zip), and the adoption of ESS-DIVE File Level Metadata and CSV reporting formats (inclusion of flmd.csv and dd.csv files).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Grid Operator Analytics and Assessment Tools for Inverter- Based Resources Dominated Grid (GOAAT-IBR) Project Update

This presentation provides an update on the OPTIMA GOAAT project, with emphasis on the cloud-native data platform developed in-house to ingest, manage, and operationalize high-resolution power system data. Since our last NASPI presentation, accessible via OSTI ID #2671437, the project team advanced the design and deployment of a scalable architecture capable of handling both synchronized and non-synchronized streams, including PMU, point-on-wave (POW), COMTRADE, and SCADA data. These materials review the project status, recent progress, and key lessons learned. The core of the presentation examines the architecture and engineering of our cloud-native ingestion and data management platform. We then explain how pipelines were designed to collect, normalize, time-align, store, and serve heterogeneous data at scale. We will discuss design choices such as data models, streaming versus batch ingestion, storage tiers, and interoperability with analytics applications. Practical experiences with cloud-native technologies were shared during the event, including benefits, limitations, and integration challenges in a utility environment, along with methods used to improve performance, reduce latency, and optimize resource usage. The presentation also showcases user interface designs and visualization tools that convert raw measurements and analytics results into intuitive, actionable insights for operators and engineers. During the presentation examples were provided demonstrating how visualization, event views, and summarized analytics enhance situational awareness and support operational decision-making. These use cases illustrate how a well-designed data infrastructure can bridge the gap between high-volume measurements and practical grid operations.

Aminifar, Farrokh↗

DOE OSTI2021

Storage Futures Study: Economic Potential of Diurnal Storage in the U.S. Power Sector

We model the evolution of the U.S. electricity sector from 2020 through 2050 and find significant market potential (>125 GW) for diurnal energy storage across all 19 scenarios considered. Most of this storage has 4-6 hours of duration. We find that storage deployment is driven primarily by the combination of capacity value and energy time-shifting value, and that the combination of these value streams is needed for optimal storage deployment to be realized. We also find a strong correlation of PV penetration and storage market potential. Cost and performance metrics in this study focus on Li-ion batteries because the technology has more market maturity than other emerging technologies but results from this study can be generalized to any technologies that meet the cost and performance projections assumed.

25 ENERGY STORAGE↗

DOE OSTI2026

Mountain Basin Controls on the Snow-to-Streamflow Signal: An AIC-Weighted Multiple Linear Regression Framework

A regression-based analysis quantifies how basin characteristics modulate the snow-to-streamflow signal. First, we use the ERA5-Land reanalysis gridded product (European Centre for Medium Range Weather Forecasts reanalysis 5 -Land component) for 4,655 hydrologic unit code - 10 (HUC10) mountain basins across the western United States (US) for water years 1987–2024. Linear regressions are performed for peak snow water equivalent (SWE) and annual streamflow for each mountain basin. Models use ordinary least squares in Python’s statsmodels package. After which, an Akaike Information Criterion (AIC)–weighted ensemble multiple linear regression (MLR) framework with 47 watershed traits is used to predict the linear regression coefficient of determination (r-squared) defining the ability of peak SWE to predict annual streamflow across all mountain basin. Predictor sets are constrained to avoid multicollinearity by excluding models with variance inflation factors (VIF) greater than 5. Mountain basin traits included in the MLR include seasonal climate, topography, vegetation type and structure, and bedrock geology. Accepted models are considered if their AIC is within 2.0 of the model with the minimum AIC, or best model. To compare predictor influence across acceptable models, we computed standardized regression coefficients. To evaluate structural redundancy among models, we constructed binary inclusion vectors for each acceptable model, denoting whether a predictor was present (1) or absent (0). Core predictor variables are defined as occurring in at least 67% of the acceptable models. For this regional analysis, only one model was found acceptable, with higher snow-to-streamflow translation (higher r-squared) occurring in colder mountain basins with higher relative winter precipitation, more snow accumulation and a lower fraction of annual precipitation that falls in the spring and summer. The second component of the data package uses previously published, high-resolution output from an integrated hydrological model of the East River watershed using the U.S. Geological Survey Groundwater and Surface water Flow model (GSFLOW, doi:10.15485/1998576). East River MLR expands upon the approach described above to explore the response of five streamflow metrics—annual streamflow, runoff efficiency, 7-day minimum flow, low-flow duration, and non-perennial stream fraction to snow system indicators including peak SWE, snow-covered area, snow disappearance date, and the fraction of basin area characterized by low-to-no snow, as well as seasonal precipitation and temperature, and annual hydrologic variables representing soil moisture, evapotranspiration (ET), the partitioning of incoming precipitation to evapotranspiration (ET/P), groundwater storage, and groundwater inflow to streams. MLR was done on all water years (P0: 1987-2024) and for each period as determined in the split analysis using pooled regression techniques (P1: 1987-2011 and P2: 2012-2024) to evaluate shifting predictor variable emphasis on streamflow generation. Results indicate that since 2012, peak SWE has lost statistical strength in its prediction of annual streamflow and runoff efficiency, and the indirect influence of spring temperature has emerged as critically important. Low-flow metrics remain largely influenced by soil moisture, vegetation water use and groundwater inflows with summer precipitation becoming a direct influence on minimum summer flow. Together, these data and Python-based analysis tools provide a framework for identifying the key watershed characteristics that control how streamflow responds to snow from year to year. The package also helps quantify uncertainty in statistical models and assess how snow–streamflow relationships vary across regions and over time. This dataset contains comma-separated values files (.csv), text files (.txt), python code files (.py), figure files (.png), and shapefiles (.cpg, .dbf, .prj, .sbn, .sbx, .shp, .xml). Further details on file contents and MLR execution can be found in the readme file and the FLMD files. Work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Accelerating multigrid with streaming chiral SVD for Wilson fermions in lattice QCD

A modification to the setup algorithm for the multigrid preconditioner of Wilson fermions in lattice QCD is presented. A larger basis of test vectors than that used in regular multigrid is calculated by the smoother and truncated by singular value decomposition on the chiral components of the test vectors. The truncated basis is used to form the prolongation and restriction matrices of the multigrid hierarchy. This modification of the setup method is demonstrated to increase the convergence of linear solvers on an anisotropic lattice with m π ≈ 239 MeV from the Hadron Spectrum Collaboration and an isotropic lattice with m π ≈ 220 MeV from the MILC Collaboration. The lattice volume dependence of the method is also examined. Increasing the number of test vectors improves speedup up to a point, but storing these vectors becomes impossible in limited memory resources such as GPUs. To address storage cost, we implement a streaming singular value decomposition of the basis of test vectors on the chiral components and demonstrate a decrease in the number of fine level iterations by a factor of 1.7 for m q ≈ m crit

Iterative methods↗

NASA NTRS1978

A distributed microcomputer telemetry system for spacecraft applications

Distributed microcomputer telemetry system design difficulties are examined and solutions to these difficulties are discussed. In the telemetry system being considered, the data gathering is actually distributed among a number of computers, each with its own commutation cycle, data storage buffers, and specified set of measurements to be sampled. A computer based high level module controls the formation of the final telemetry stream by accessing individual computer's data storage buffers at the appropriate time and inserting them into the telemetry stream. Attention is given to the precise time tagging of data samples, the interconnection of several computers, the autonomous operation of science instruments, and reliability considerations.

Lord, D. D.↗

DOE OSTI2025

Experimental Characterization of High-Surface Area Thermal Energy Storage

There is growing interest in energy storage technologies due to the expansion of renewable energy sources that are inherently intermittent and the increasing frequency of extreme weather events that disturb the power grid. Power consumption in buildings makes up approximately 76% of all electricity usage on the grid and is primarily used for thermal applications such as space conditioning, hot water, and cooking. This makes thermal energy storage (TES) an ideal solution for many of these applications. Many TES technologies rely on latent energy storage, which utilizes the melting/solidification of phase change materials (PCM) to store energy. Typically, TES designs suffer from low power density due to their low inherent thermal conductivity. This limitation makes the deployment of TES in active applications difficult as the ease of access to energy is essential for effective use. Common routes for improving power density include high thermal conductivity additives or extended features such as fins that increase cost. This study presents an alternative approach to improving performance through increasing the overall surface area to volume ratio of the device, to increase the available area for convection to occur between the working fluid and PCM. In the study a commercial PCM was selected with a transition temperature ideal for space heating applications. The heat exchanger design utilizes a unique application of triply periodic minimal surfaces (TPMS) for macro-encapsulation of the PCM. The use of TPMS for heat exchangers has been growing in interest due to their high-surface area to volume ratios, which were previously unmanufacturable until the development of additive manufacturing. A modular system was designed and manufactured with a stereolithography resin printing system that is then backfilled with PCM. An experiment test set-up is designed to test the charge and discharge performance of the thermal storage using a conditioned air stream. The pressure drop of the design is tested across a variety of flow rates. When compared to existing experimental data within literature, there is excellent agreement based on the Reynolds number at similar hydraulic diameters. Several inlet temperatures are tested at consistent temperature differences from the phase change temperature for both charging and discharging. Additionally, the volumetric flow rate is varied for each temperature set point. It was found that increasing flow rate had diminishing returns in reducing the overall charge time of the TES. The temperature delta from the melting temperature was the primary contributor to the change in average heat flux with limited variation in average heat transfer rate between charging and discharging at similar inlet temperatures and flow rates. The TPMS heat exchanger design has a high air-side pressure drop but it provides high heat transfer rates. This helps maintain a high outlet temperature during discharge, which is important to thermal comfort applications. The design, manufacturing, and experimental characterization of the TES device will be presented as part of this study.

25 ENERGY STORAGE↗

DOE OSTI2020

A White Paper: Disposition Options for a High-Temperature Gas-Cooled Reactor

The high-temperature gas-cooled reactor (HTGR) is a uranium-fueled, graphite-moderated, gas-cooled nuclear reactor design concept capable of producing very high core outlet temperatures. Both types of HTGR have the tristructural isotropic (TRISO) fuel kernel at the heart of the fuel design. For the prismatic block-type HTGR, the TRISO particles are overcoated with a resinated graphitic matrix and pressed into fuel compacts, which are then heat treated and placed in the fuel channels of the prismatic-block-shaped fuel assemblies. For the pebble-bed-type HTGR, the TRISO particles are dispersed in a graphitic-matrix sphere, which is the basic unit for the reactor core. Despite having very different fuel designs, both types of HTGR are graphite-moderated, gas-cooled, thermal reactors using many of the same materials. As a result, both prismatic-block-type and pebble-bed-type HTGRs have similar radioactive waste streams, all of which require safe and secure storage and eventual disposition. Modern HTGR designs are based on a long and rich operating history of several different graphite-moderated, gas-cooled, thermal reactors. Several of these reactors have been shut down, the fuel has been placed in safe storage, and they have undergone some degree of decommissioning. As such, there is significant experience in the management of the spent nuclear fuel (SNF) and radioactive wastes associated with operating these reactors. This white paper will, (1) identify the definitions and regulations that apply to the safe and secure management, storage, and disposal of radioactive waste; and (2) identify the key radioactive waste streams from HTGRs and their characteristics. Idaho National Laboratory (INL) has significant experience in the management of SNF from HTGR predecessors. This experience should form the basis for the management and disposition efforts of the radioactive waste from any new HTGR-type small modular reactor, or microreactor intended for deployment at the INL site.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2020

Proven Technologies for the Solidification of Complex Liquid Radioactive Waste (LRW): Global Case Studies of Applications and Disposal Options - 20424

Legacy radioactive waste streams from the Cold War still exist and newly generated waste streams from nuclear power plants and research institutes go untreated and expose environmental hazards at many nuclear sites. The nature of the waste is diverse, depending upon the source or the process from which it originated. The most problematic waste streams include complex liquids such as organic (tri-butyl-phosphate TBP) solutions contaminated with Pu and U isotopes, mixed sludge types, high acid radioactive waste, H-3 contaminated organic and aqueous streams, etc. Technological, environmental and economic challenges exist for the treatment and disposal of such waste streams. A proven technology that has been applied to LRW on a global basis provides one option as a low-cost solution to legacy streams and small volume, highly complex LRW frequently found during decommissioning at nuclear power plants and weapons sites. The engineered polymer technology from Nochar, USA, is capable of solidifying standard and highly complex LLW and ILW waste streams for interim or final storage, or for incineration. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Updated Baseline Cost Model for Hydropower (2023)

The "Updated Baseline Cost Model (BCM) for Hydropower" is an empirical model for estimating the costs of US hydropower projects in six categories (Non-Powered Dam (NPD), New Stream Development (NSD), Canal/Conduit, Pumped Storage Hydro (PSH), Capacity Expansion, Generator Rewind). The model equations have been estimated with data on existing or planned projects obtained from various sources. NOTE: This is a macro-enabled workbook, so Excel may block it on the first opening. In that case: 1. Save the workbook to a local directory 2. Right-click on the workbook in the local directory and select “Properties” 3. Then check “Unblock” at the bottom of the “General” tab.

13 HYDRO ENERGY↗

NASA NTRS1998

Evaluating the feasibility of biological waste processing for long term space missions

Recycling waste products during orbital (e.g., International Space Station) and planetary missions (e.g., lunar base, Mars transit mission, Martian base) will reduce storage and resupply costs. Wastes streams on the space station will include human hygiene water, urine, faeces, and trash. Longer term missions will contain human waste and inedible plant material from plant growth systems used for atmospheric regeneration, food production, and water recycling. The feasibility of biological and physical-chemical waste recycling is being investigated as part of National Aeronautics and Space Administration's (NASA) Advanced Life Support (ALS) Program. In-vessel composting has lower manpower requirements, lower water and volume requirements, and greater potential for sanitization of human waste compared to alternative bioreactor designs such as continuously stirred tank reactors (CSTR). Residual solids from the process (i.e. compost) could be used a biological air filter, a plant nutrient source, and a carbon sink. Potential in-vessel composting designs for both near- and long-term space missions are presented and discussed with respect to the unique aspects of space-based systems.

NASA Discipline Life Support Systems↗

NASA NTRS2022

Mississippi Embayment Water Resources: Utilizing NASA Earth Observations to Understand Groundwater Recharge in the Mississippi Regional Aquifer System

The Memphis Sand Aquifer (MSA) is located in the Mississippi Embayment which extends 250,000 square kilometers across nine states. Groundwater recharge factors that influence the narrow recharge zone of the MSA include precipitation, potential evapotranspiration, and landcover changes. The unsustainable water practices and increasing landcover change from urban development in the MSA's narrow recharge zone threaten the aquifer’s groundwater storage. In partnership with Protect Our Aquifer, the team used data from Terra Moderate Resolution Imaging Spectroradiometer (MODIS), Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (GPM IMERG), National Land Cover Dataset (NLCD), and Gravity Recovery and Climate Experiment (GRACE). These datasets included annually-averaged precipitation, evapotranspiration, potential evapotranspiration, biannual landcover change, and monthly total water storage which were used to create groundwater recharge factors maps and timeseries. The evaporative stress index map, water balance map, and landcover change maps were used to identify thriving areas. The team found precipitation did not express a strong linear trend and showed high precipitation years in 2017 and 2018, and a drought year in 2011. The potential evapotranspiration showed a weak negative linear trend. The landcover change showed shifts in forested areas and urban development. The team identified four thriving areas in the western side of Tennessee that successfully contribute to aquifer recharge due to increased forest area, sufficient water use, low changes in total water storage, and lateral positioning to streams. These end products allowed our partners to make informed decisions about areas that are thriving in the Mississippi Embayment recharge zone for conservation efforts of the aquifer.

Lauren Mahoney↗