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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Growth Response of Water Hyacinth to Environmental Ranges in the California Sacramento-San Joaquin River Delta

Management of aquatic weeds in complex watersheds and river systems present many challenges to assessment, planning, and implementation of management for aquatic invasive plants. The Delta Region Areawide Aquatic Weed Project (DRAAWP), a USDA sponsored area-wide project including NASA Ames Research Center and State of California Department of Boating and Waterways, is working to enhance decision-making and operational efficiency of invasive plant management in the California Sacramento-San Joaquin Delta. Expansion of invasive aquatic plants has been detrimental to water management and the ecosystem complex in the San Francisco Bay/California Delta. The portion of DRAAWP reported here focuses on parametrizing the environmental response inputs for the Delta models for prominent invasive aquatic plants. Changing climate, long-term drought, shifts in land use, and variation in water flow and quality from input watersheds lead to wide and unique variation in environmental conditions. Environmental variability occurs across a range of time scales from long-term climate and seasonal trends to short-term water flow mediated variations. Response of invasive aquatic plants are examined using controlled environment growth facilities at time scales of weeks, day, and hours using a combination of study duration and growth assessment techniques to assess water quality, temperature, nutrient, and light effects. These provide response parameters for plant growth models in response to the variation and interact with management and economic models associated with aquatic weed management. Plant growth models are informed by remote sensing and applied spatially across the Delta to balance location and type of aquatic plant, growth response to altered environments and phenology.

Sacramento-San Joaquin River Delta.v↗
NASA NTRS1993

Mixing model analysis of telescopic lunar spectra

We have analyzed very high quality reflectance spectra of the lunar surface from the University of Hawaii lunar spectral data collection using a spectral mixing model. The spectra analyzed are those of 45 mare sites and 75 highland sites. The spectra were selected on the basis of very high signal to noise ratios based on error bars and point to point scatter, and on quality of removal of telluric water bands. The spectral mixing model used 7 components, not all of which were used in each fit. Four of the components were mineral spectra of the orthopyroxene, a clinopyroxene, an olivine and an anorthite, measured at the Brown University's RELAB. All of the minerals were 45-90 micron splits. Lunar soil contains other components which have the effect of reddening and darkening the soil as well as reducing spectral contrast. In addition, lunar soil contains spectral neutral bright material (likely very fine grained feldspar) which serves to reduce spectral contrast and brighten soils. Early attempts to fit many of the spectra pointed out the need for a component which has a very broad smooth absorption feature centered near 1.1 microns. Glass is a good candidate for this component. For the bright component we used a flat reflectance of 70 percent to represent fine grained feldspar. For the 'glass' component we used a telescopic spectrum of a pyroclastic glass present on the Aristarchus plateau which is characterized by a strong smooth band centered at 1.07 microns. In addition to exhibiting the glass band this spectrum is very red and has a low albedo. On the assumption that the dark component and the red component are agglutinates, which is reasonable but not necessarily true, we sought a dark red component. To derive its properties we modelled the spectrum of an Apollo 16 soil (16xxx) and assumed the dark red component to comprise 60 percent of the soil, appropriate to agglutinate abundance in mature soil. We adjusted the albedo and slope of a straight line representing the dark red component until the contrast and albedo of the model spectrum matched the soil spectrum. The mixing was done after conversion to a single scattering albedo.

Lucey, Paul G.↗
NASA NTRS2015

The Mars Dust and Water Cycles: Investigating the Influence of Clouds on the Vertical Distribution and Meridional Transport of Dust and Water.

The dust and water cycles are critical to the current Martian climate, and they interact with each other through cloud formation. Dust modulates the thermal structure of the atmosphere and thus greatly influences atmospheric circulation. Clouds provide radiative forcing and control the net hemispheric transport of water through the alteration of the vertical distributions of water and dust. Recent advancements in the quality and sophistication of both climate models and observations enable an increased understanding of how the coupling between the dust and water cycles (through cloud formation) impacts the dust and water cycles. We focus here on the effects of clouds on the vertical distributions of dust and water and how those vertical distributions control the net meridional transport of water. We utilize observations of temperature, dust and water ice from the Mars Climate Sounder (MCS) on the Mars Reconnaissance Orbiter (MRO) and the NASA ARC Mars Global Climate Model (MGCM) to show that the magnitude and nature of the hemispheric exchange of water during NH summer is sensitive to the vertical structure of the simulated aphelion cloud belt. Further, we investigate how clouds influence atmospheric temperatures and thus the vertical structure of the cloud belt. Our goal is to isolate and understand the importance of radiative/dynamic feedbacks due to the physical processes involved with cloud formation and evolution on the current climate of Mars.

NASA ARC Mars Global Climate Model (MGCM)↗
DOE OSTI2026

Theoretical model of dielectrophoretic water vapor condensation during multiphase flow of electrically charged water droplets in air

Water droplet growth in air, influenced by vapor diffusion and electrical charging, has significant implications for indoor air quality, cloud formation, and aerosol dynamics. Here, this study presents a comprehensive theoretical model that describes the growth dynamics of electrically charged water droplets under external electric fields, incorporating diffusion, electrostatic, and dielectrophoretic forces to enhance understanding and practical applications in air dehumidification and environmental control. A theoretical model was established to analyze the growth dynamics of the charged water droplets. The approach extended the thermodynamic framework of the Modified Kelvin-Thomson equation by integrating electrostatic and dielectrophoretic effects, enabling a comprehensive evaluation of vapor concentration near the surface of charged droplets. A sensitivity analysis was performed to assess the roles of droplet size, electric field intensity, surface charge, and vapor concentration on condensation rates. The study progressed beyond the classical diffusion-limited growth of neutral droplets, addressing the behavior of charged droplets in electrohydrodynamic environments. The model highlighted the significance of dielectrophoretic drift flux for dipolar vapor molecules, especially in micron-sized droplets ranging from 10 to 100 µm. Findings demonstrated that, for smaller droplets subjected to elevated electrical charge, average growth rates varied from 0.3 to 1.6 µm/s if the air relative humidity increased from 50 to 100 %. Analytical results are corroborated by numerical simulations, which exhibited strong concordance, thereby validating the proposed theoretical approach. This research introduced an innovative and scalable analytical methodology for electric field-enhanced droplet growth, offering valuable insights into the advancement of energy-efficient air dehumidification, water desalination, and atmospheric water harvesting technologies.

42 ENGINEERING↗
DOE OSTI2021

Topical Report on Water Balance Model Development and Initial Application

This topical report summarizes results from developing a generic dynamic water balance tool which can be used by coal-fired power plant operators to evaluate FGD water management strategies. EPRI is using a statistical software model created on the GoldSim platform and data from coal-fired energy plants to determine the fraction of power plant water needs that can be satisfied by electrodialysis reversal treatment and, correspondingly, the discharge volume and/or byproducts that still need to be managed. The generic model is designed to accept a number of easily obtainable process variables and generate probabilities of resultant water characteristics. The model is also constructed as a universal process flow; one that can be adjusted to accommodate most major components of an FGD blowdown handling system. The generic model is dynamic and utilizes user-inputted operational variation in water quality and quantity to best provide a probabilistic representation of potential performance outcomes. In order to account for complexities of water composition and treatment, a separate chemical modeling software is used to evaluate water chemistry and unit operation performance. The thermodynamic modeling software, OLI Studio, is employed to convert ion data from laboratory analyses into balanced molecular concentrations that are classified as dissolved and suspended solids. The dynamic water model is designed to import a total of 11 species commonly found in FGD blowdown water as molecular concentrations.Water management unit operations are used in the model and categorized by either physical unit operation blocks or chemical unit operations blocks. As the name implies, the physical water treatment blocks are unit operations that are exclusively physical changes to the system (e.g., separations and volume changes). The chemical water treatment blocks are unit operations where chemical changes occur and require the use of OLI Studio to characterize subsequent streams. Water and material balances from three unique coal-fired power plants were obtained and preliminary modeling on the dynamic water balance tool was performed using the extracted data from these power plants. These three power plants were chosen due to their unique configurations and water profiles that represented a variety of operational changes. Results from using the dynamic tool with the three plant configurations are presented and discussed in the context of the existing tool and planned future capabilities.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Linking Stream Chemistry to Subsurface Redox Architecture

As drinking-water scarcity grows worldwide, we need to improve predictions of the quantity and quality of our water resources. An overarching problem for model improvement is that we do not know the geological structure of aquifers in sufficient detail. In this work, we demonstrate that mineral-water reactions imprint structure in the subsurface that impacts the flow and transport of some chemical species. Specifically, pyrite, a ubiquitous mineral, commonly oxidizes and depletes in the upper layers of the weathering profile in most humid watersheds, only remaining at depths of meters. We hypothesize that variations in concentrations (C) of pyrite-derived sulfate released into rivers as a function of discharge (q) reflect the rate-limiting step and depth of pyrite-oxidizing layers. We found that log C - log q behaviors thus differ in small and large watersheds in the Susquehanna River Basin as well as in selected watersheds in the Western United States. Although coal mining changes pyrite oxidation from closed to open system with respect to O 2 , patterns in stream chemistry as a function of discharge are consistent with deep and shallow pyrite oxidation zones in small and large watersheds respectively. Therefore, understanding the subsurface patterns of mineral reactions and how they affect the architecture of aquifers will elucidate patterns of changing river chemistry and our ability to manage water resources in the future under accelerated land use and climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Water Network Tool for Resilience (WNTR)

The Water Network Tool for Resilience (WNTR) is an open source Python package designed to simulate and analyze resilience of water distribution networks. The United States Environmental Protection Agency, in partnership with Sandia National Laboratories, developed WNTR to integrate critical aspects of resilience modeling for water distribution networks into a single software framework. The software includes capability to: • Generate water network models • Modify network structure and operations • Assign fragility and survival curves to network components • Model disruptive events such as power outages, earthquakes, fires, pipe breaks, and contamination incidents • Model response and repair strategies • Simulate hydraulics and water quality • Evaluate resilience using a wide range of metrics • Integrate dependency with other critical infrastructure and supply chains • Analyze results and generate graphics SAND2019-450 M

Villa, Daniel↗
NASA NTRS2002

Technical Report Series on Global Modeling and Data Assimilation: A Coupled Ocean-Atmosphere Radiative Model for Global Ocean Biogeochemical Models - Volume 22

An ocean-atmosphere radiative model (OARM) evaluates irradiance availability and quality in the water column to support phytoplankton growth and drive ocean thermodynamics. An atmospheric component incorporates spectral and directional effects of clear and cloudy skies as a function of atmospheric optical constituents, and spectral reflectance across the air-sea interface. An oceanic component evaluates the propagation of spectral and directional irradiance through the water column as a function of water, five phytoplankton groups, and chromophoric dissolved organic matter. It tracks the direct and diffuse streams from the atmospheric component, and a third stream, upwelling diffuse irradiance. The atmospheric component of OARM was compared to data sources at the ocean surface with a coefficient of determination (r2) of 0.97 and a root mean square of 12.1%.

Gregg, Watson W.↗
DOE OSTI2023

PV Stormwater Management Research and Testing (PV-SMaRT) (Final Technical Report)

The objective of the Photovoltaic Stormwater Management Research and Testing (PV-SMaRT) project was to develop and disseminate research-based, solar-specific resources for estimating stormwater runoff at ground-mounted PV facilities and detail stormwater management and water quality best practices. The intended use of stormwater management and water quality best practices and stormwater runoff estimation resources is to reduce balance of system soft costs associated with stormwater infrastructure requirements and improve water quality through research-tested best practices. Currently, stormwater regulations and guidelines vary by jurisdiction and can lead to regulatory uncertainty and increased compliance costs for managing stormwater runoff at solar sites. To address these concerns, the NREL team and its partners (University of Minnesota, Great Plains Institute, and Fresh Energy) established and engaged an advisory Water Quality Task Force (WQTF); conducted field research on stormwater infiltration and runoff at five ground-mounted PV sites; validated a 3-D hydrologic model to predict water runoff and generate stormwater runoff coefficients for a range of site conditions and PV designs; developed a stormwater management and water quality best practices document; and engaged with local jurisdictions and other stakeholders to disseminate best practices, stormwater runoff coefficients, and other tools. Key outputs of this project were a PV-SMaRT Runoff Calculator developed by University of Minnesota, a webinar detailing project outcomes and how to use the PV-SMaRT runoff calculator, and a document on Best Practices for regulators and developers regarding stormwater runoff at PV sites.

14 SOLAR ENERGY↗
DOE OSTI2023

Temperature outweighs light and flow as the predominant driver of dissolved oxygen in US rivers

The concentration of dissolved oxygen (DO), an important measure of water quality and river metabolism, varies tremendously in time and space. Riverine DO is commonly perceived as regulated by interacting and competing drivers (light, temperature and flow) that define rivers’ climate. Its continental-scale drivers, however, have remained elusive, partly due to the scarcity and spatio-temporal inconsistency of water quality data. Here we show, via a deep learning model (long short-term memory) trained using data from 580 rivers, that temperature predominantly drives daily DO dynamics in the contiguous United States. Light comes a close second, whereas flow imparts minimal influence. This work showcases the promise of using deep learning models for data filling that enables large-scale systematic analysis of patterns and drivers. Results show fairly accurate prediction of DO by temperature alone, and declining DO in warming rivers, which has important implications for water security and ecosystem health in the future climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Potential of water quality wetlands to mitigate habitat losses from agricultural drainage modernization

Given widespread biodiversity declines, a growing global human population, and demands to improve water quality, there is an immediate need to explore land management solutions that support multiple ecosystem services. Agricultural water quality wetlands designed to provide both water quality benefits and wetland and grassland habitat are an emerging restoration solution that may reverse habitat declines in intensive agricultural areas. Installation of water quality wetlands in the Upper Midwest, USA, when considered alongside the repair and modification of aging agricultural tile drainage infrastructure, is a likely scenario that may mitigate nutrient pollution exported from agricultural systems and improve crop yields. The capacity of water quality wetlands to provide habitat within the wetland pool and the surrounding grassland is not well-studied, particularly with respect to potential habitat changes resulting from drainage infrastructure upgrades. For the current study, we produced spatially explicit models of 37 catchments distributed throughout an important region for agriculture and biodiversity, the Des Moines Lobe of Iowa. Four scenarios were considered - with and without improved drainage and with and without water quality wetlands - to estimate the net potential habitat implications of these scenarios for amphibians, grassland birds, and wild bees. Model results indicate that drainage modification alone will likely result in moderate direct losses of suitable amphibian habitat and large declines in overall habitat quality. However, inclusion of water quality wetlands at the catchment scale may mitigate these amphibian habitat losses while also increasing grassland bird and pollinator habitat. In conclusion, the impacts of water quality wetlands and drainage modernization on waterfowl in the region require additional study.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Applications of GIS and remote sensing in public participation and stakeholder engagement for watershed management

The use of Geographic Information Systems (GIS) and remote sensing technologies for the development of water quality management programs and for post-implementation assessments has increased dramatically in the past decade. This increase in adoption has been made more accessible through the interfaces of many popular software tools used in the regulation and assessment of water quality. Customized applications of these tools will increase, as ease of access and affordability of directly monitored and remotely sensed datasets improve over time. Concurrently, there is a need for inclusive participatory engagement with stakeholders to achieve solutions to current watershed management challenges. This paper explores the potential of these GIS and remote sensing datasets, tools, models, and immersive engagement technologies from other domains, for improving public participation and stakeholder engagement throughout the watershed planning process. To do so, an initial review is presented about the use of GIS and remote sensing in watershed management and its role in impairment identification, model development, and planning and implementation. Then, ways in which GIS and remote sensing can be integrated with stakeholder engagement through (1) leveraging GIS and remote sensing datasets, and (2) stakeholder engagement approaches including outreach and education, modeler-led development, and stakeholder-led involvement and feedback, are discussed. Finally, future perspectives on the potential for transforming public participation and stakeholder engagement in the watershed management process through applications of GIS and remote sensing are presented.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

Measurement of Cyanobacterial Bloom Magnitude Using Satellite Remote Sensing

Cyanobacterial harmful algal blooms (cyano HABs) are a serious environmental, water quality and public health issue worldwide because of their ability to form dense biomass and produce toxins. Models and algorithms have been developed to detect and quantify cyanoHABs biomass using remotely sensed data but not for quantifying bloom magnitude,information that would guide water quality management decisions. We propose a method to quantify seasonal and annual cyanoHAB magnitude in lakes and reservoirs. The magnitude is the spatio temporal mean of weekly or biweekly maximum cyanobacteria biomass for the season or year. CyanoHAB biomass is quantified using a standard reflectance spectral shape based algorithm that uses data from Medium Resolution Imaging Spectrometer (MERIS). We demonstrate the method to quantify annual and seasonal cyanoHAB magnitude in Florida and Ohio (USA) respectively during 2003-2011 and rank the lakes based on median magnitude over the study period. The new method can be applied to Sentinel-3 Ocean Land Color Imager (OLCI) data for assessment of cyanoHABs and the change over time, even with issues such as variable data acquisition frequency or sensor calibration uncertainties between satellites. CyanoHAB magnitude can support monitoring and management decision making for recreational and drinking water sources.

Sachidananda Mishra↗
DOE OSTI2025

National Energy Water Treatment & Speciation (NEWTS): A Water & Critical Mineral Database and Dashboard

The scarcity of water resources, the need for beneficial water reuse, and the challenges of wastewater treatment are becoming increasingly pressing in economic, social, and environmental domains. Addressing these concerns requires effective treatment strategies to manage wastewater streams and tackle environmental and economic issues. Furthermore, the recovery of critical minerals from the waste streams associated with energy production holds the promise of offsetting treatment costs and securing local sources of valuable minerals. However, relevant data on these waste streams are dispersed and challenging to locate. The process of ingesting such data into modeling software often involves multiple steps, requiring data restructuring to meet software-input requirements. The non-standardized reporting of water data makes data aggregation and reformatting a time-consuming process. Additionally, essential attributes necessary for modeling water treatment and mineral scale formation are frequently missing. Moreover, data gaps vary depending on the region of interest. Consequently, there is a pressing need for high-quality energy-water composition data that can be easily imported into water chemistry modeling software. To address this need, the National Energy Technology Laboratory has created the National Energy Water Treatment and Speciation (NEWTS) Database and Dashboard—a free online tool catering to community leaders and water researchers. NEWTS facilitates a comprehensive understanding of the composition of energy-related wastewater streams in the United States. The datasets provide detailed concentrations and speciation of major and minor aqueous compounds in energy-related wastewater streams, including power plant leachate, acid mine drainage, brackish water, and oil and gas produced water across the United States. Many of the aqueous species are critical minerals (Li, REEs) in high demand to modernize the world’s energy infrastructure. Many of the datasets also contain volumetric flow-rates needed to model the treatment and reuse scenarios in advanced aqueous chemistry software programs. The NEWTS Database and Dashboard offer public access to hitherto challenging-to-access datasets, presented in a standardized format that is tailored for easy input into aqueous chemistry modeling software. By performing the work needed to transform dispersed, disparate data sources into unified, model-ready datasets, NEWTS serves as an essential resource in advancing water treatment research and sustainable water resource management.

produced water management↗
NASA NTRS1978

Simplified multiple scattering model for radiative transfer in turbid water

Quantitative analytical procedures for relating selected water quality parameters to the characteristics of the backscattered signals, measured by remote sensors, require the solution of the radiative transport equation in turbid media. Presented is an approximate closed form solution of this equation and based on this solution, the remote sensing of sediments is discussed. The results are compared with other standard closed form solutions such as quasi-single scattering approximations.

Ghovanlou, A. H.↗
DOE OSTI2024

Uncertainty characterization in a coupled human-natural system: Modeling agricultural adaptation in the Great Lakes Region

The Great Lakes Region's water quality and ecological health are threatened by the export of nutrients from agricultural lands, which causes eutrophication, hypoxia, and destructive algal blooms. The intensification of hydrologic cycles brought about by climate change is expected to exacerbate nutrient loading in the region, and, at the same time, agricultural adaptation to changing conditions is also expected to affect loading through shifting amounts and timing of fertilization. Quantifying these future effects and their interactions necessitates modeling both the human and natural processes as a coupled system, by pairing land use and agricultural management with hydrologic modeling. At the same time, compounding uncertainties arising from the complex interactions in both systems significantly limit our predictive understanding of the region's impacts. This study utilizes the Soil and Water Assessment Tool (SWAT), developed for simulating the impact of various farmer decisions on watershed functions in Western Lake Erie watersheds, and an under-development agent-based model (ABM) for agricultural management decisions. The aim of this study is to use global sensitivity analysis on the coupled ABM and SWAT models to quantify how uncertainty in both models interactively affects nutrient loading. To do so, we will conduct Sobol sensitivity analysis experiments at different levels of coupling assumptions to quantify how various uncertain factors (e.g., soil moisture and crop choice) and their interactions affect our estimates of nutrient loading. The results of this analysis will allow us to quantify how complex interactions and dependencies between both systems amplify the effect of uncertainties. Insights gained from this study will have broader implications for modeling the adaptive co-evolution of human and natural systems under climate change and can inform effective management of nutrient loading in the Great Lakes Region.

Climate Change↗
NASA NTRS2013

Higher Surface Ozone Concentrations Over the Chesapeake Bay than Over the Adjacent Land: Observations and Models from the DISCOVER-AQ and CBODAQ Campaigns

Air quality models, such as the Community Multiscale Air Quality (CMAQ) model, indicate decidedly higher ozone near the surface of large interior water bodies, such as the Great Lakes and Chesapeake Bay. In order to test the validity of the model output, we performed surface measurements of ozone (O3) and total reactive nitrogen (NOy) on the 26-m Delaware II NOAA Small Research Vessel experimental (SRVx), deployed in the Chesapeake Bay for 10 daytime cruises in July 2011 as part of NASA's GEO-CAPE CBODAQ oceanographic field campaign in conjunction with NASA's DISCOVER-AQ air quality field campaign. During this 10-day period, the EPA O3 regulatory standard of 75 ppbv averaged over an 8-h period was exceeded four times over water while ground stations in the area only exceeded the standard at most twice. This suggests that on days when the Baltimore/Washington region is in compliance with the EPA standard, air quality over the Chesapeake Bay might exceed the EPA standard. Ozone observations over the bay during the afternoon were consistently 10-20% higher than the closest upwind ground sites during the 10-day campaign; this pattern persisted during good and poor air quality days. A lower boundary layer, reduced cloud cover, slower dry deposition rates, and other lesser mechanisms, contribute to the local maximum of ozone over the Chesapeake Bay. Observations from this campaign were compared to a CMAQ simulation at 1.33 km resolution. The model is able to predict the regional maximum of ozone over the Chesapeake Bay accurately, but NOy concentrations are significantly overestimated. Explanations for the overestimation of NOy in the model simulations are also explored

boundary layer↗