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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Modeling the effect of habitat availability and quality on endangered winter-run Chinook salmon ( Oncorhynchus tshawytscha ) production in the Sacramento Valley

Reconciliation between water uses and sustaining aquatic species populations requires an effort to identify and quantify essential habitat characteristics for ecosystem health and valuation methods to predict ecosystem response to restoration actions. This process is particularly challenging for anadromous fish species such as California's Sacramento River winter-run Chinook salmon, due to their limited geographic range and diverse life history habitat requirements. Tools, such as life-cycle models, are needed to manage population dynamics and quantify the composite effects of processes across space and time. Nevertheless, complex institutions can hinder result interpretation and communication, and limit model use in decision-making. This paper focuses on the federally endangered and endemic Sacramento River winter-run Chinook (Oncorhynchus tshawytscha) by developing a Winter-Run Habitat-based Population Model (WRHAP). Additionally, WRHAP is a conceptual, freshwater rearing stage model that includes alternative rearing habitats reported in the literature (e.g., floodplains, off-channel and tributaries), defines rules of habitat use based on instream conditions, and incorporates a juvenile growth module that combines bioenergetics modeling with empirical growth rates. Model outputs reasonably follow observed out-migration patterns and provide a realistic smolt size distribution arriving at the San Francisco Bay. This effort demonstrates the importance of currently “non-critical” habitats (as defined by the Endangered Species Act) for juvenile development, with floodplain habitat contributing to a quarter of out-migrating biomass (despite < 18% availability and <10% of total rearing days), and off-channel growth being one of the most sensitive parameters (explaining ~13% of average juvenile weight variance). The model shows the utility of a simple population model to explore relationships between habitat quality/quantity and juvenile development, and to assist water/environmental management and decision-making processes focused on species recovery.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

CTF Theory Manual: Version 4.4

Coolant-Boiling in Rod Arrays – Two Fluids (COBRA-TF) is a thermal/hydraulic (T/H) simulation code designed for light-water reactor (LWR) vessel analysis. It uses a two-fluid, three-field (i.e., fluid film, fluid drops, and vapor) modeling approach. Both subchannel and 3D Cartesian forms of its governing equations are available for the solution. The code was originally developed by Pacific Northwest Laboratory in 1980 and has been used and modified by several institutions over the last few decades. COBRA-TF also found use at the Pennsylvania State University (PSU) by the Reactor Dynamics and Fuel Modeling Group (RDFMG) and has been improved, updated, and subsequently rebranded as CTF. CTF was later adopted in the early 2010s by Oak Ridge National Laboratory (ORNL) for use in the Consortium for Advanced Simulation of Light Water Reactors (CASL) program, which led to a significant advancement of the code’s software quality, modeling accuracy, testing systems, and capabilities for improved support in modeling common LWR nominal and transient behavior. As part of the improvement process, it was necessary to generate sufficient documentation for the public domain code which had lacked such material upon being adopted by RDFMG. This document serves as a theory manual for CTF, detailing the many two-phase heat transfer, drag, and important accident scenario models contained in the code, as well as the numerical solution process utilized. Additional documents available in the CTF documentation suite include the user manual and the verification and validation manual.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRSDate not supplied

Validation of Machine Learning Algorithms for Hyperspectral Inversion of Common Water Quality Indicators

The upcoming transition to a diverse suite hyperspectral airborne and orbiting optical sensors will provide an unprecedented opportunity to measure inland water quality characteristics at a fidelity not previously achievable. This presentation will assess prototype deep learning models trained on synthetic hyperspectral data and validated with collocated in-situ measurements. Synthesized data is becoming increasingly popular for use in data-driven approaches to complex problems, and can compliment real data to increase performance on complex and unusual phenomenon, reduce or test bias, and experiment to demonstrate explainability. We will present insights from hyperspectral inversions of Chlorophyl-a, Phycocyanin, and concentration of non-algal particles using selected orbiting and airborne sensors over diverse, optically complex aquatic scenarios. We analyze how various optical water types affect fidelity of results and where improvements can be made as we prototype for globally operational water quality algorithms which can be leveraged by upcoming hyperspectral missions such as the Surface Biology and Geology (SBG) mission.

Surface Biology and Geology (SBG)↗
DOE OSTI2021

Using Machine Learning to Develop a Predictive Understanding of the Impacts of Extreme Water Cycle Perturbations on River Water Quality

This whitepaper addresses to two focal areas – (3) Insight gleaned from complex data using Artificial Intelligence (AI), and other advanced techniques (primary), and (2) Predictive modeling through the use of AI techniques and AI-derived model components (secondary). This topic is directly relevant to four DOE Earth and Environmental Systems Science Division Grand Challenges: integrated water cycle, biogeochemistry, drivers and responses in the Earth system, and data-model integration.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

CY2019 Annual Closure Monitoring Report for Corrective Action Unit 98, Frenchman Flat, Underground Test Area, Nevada National Security Site, Nevada (January 2019–December 2019), Revision 1

Three types of monitoring are performed for CAU 98: water quality, water level, and institutional control. These are monitored to determine whether the URs remain protective of human health and the environment, and to ensure that the regulatory boundary objectives are being met. Monitoring data will be used in the future, once multiple years of data are available, to evaluate consistency with the groundwater flow and contaminant transport models because the contaminant boundaries calculated with the models are the primary basis of the UR boundaries. Six wells were sampled for water-quality monitoring in 2019. Contaminants of concern were detected only in the two source/plume wells already known to contain contamination as a result of a radionuclide migration experiment. Tritium concentrations in both of these wells, RNM-2S and UE-5n, remain above the Safe Drinking Water Act maximum contaminant level of 20,000 picocuries per liter but declined in 2019 as compared to measurements in 2018. All other contaminants of concern are below the minimum detection level plus analytical error. The water-level monitoring network includes 16 wells. Depth to water measured in 2019 is generally consistent with recent measurements for all wells. Many wells continue to exhibit a long-term downward trend in water level, though changes from 2018 to 2019 are minimal. The sharp 2016 decline in water level in Well ER-5-3-2 remains unexplained, with the lower level persisting through 2019. Rising water-level trends continue to be observed in Well ER-5-3 deep piezometer and former water supply Well WW-5A. Water supply Well WW-5B experienced a rise in water level as a result of an absence of pumping in the first part of the year (due to a mechanical problem), whereas water levels declined in WW-4 and WW-4A in response to greater pumping in 2019. Institutional control monitoring confirmed the URs are recorded in U.S. Department of Energy and U.S. Air Force land management systems, and that no activities within Frenchman Flat basin are occurring that could potentially affect the contaminant boundaries. Survey of groundwater resources in basins surrounding Frenchman Flat similarly identify no current or pending development that would indicate the need to increase monitoring activities or would otherwise cause concern for the closure decision. The URs continue to prevent exposure of the public, workers, and the environment to contaminants of concern by preventing use of potentially contaminated groundwater.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1999

Retrieval Assimilation and Modeling of Atmospheric Water Vapor from Ground- and Space-Based GPS Networks: Investigation of the Global and Regional Hydrological Cycles

Uncertainty over the response of the atmospheric hydrological cycle (particularly the distribution of water vapor and cloudiness) to anthropogenic forcing is a primary source of doubt in current estimates of global climate sensitivity, which raises severe difficulties in evaluating its likely societal impact. Fortunately, a variety of advanced techniques and sensors are beginning to shed new light on the atmospheric hydrological cycle. One of the most promising makes use of the sensitivity of the Global Positioning System (GPS) to the thermodynamic state, and in particular the water vapor content, of the atmosphere through which the radio signals propagate. Our strategy to derive the maximum benefit for hydrological studies from the rapidly increasing GPS data stream will proceed in three stages: (1) systematically analyze and archive quality-controlled retrievals using state-of-the-art techniques; (2) employ both currently available and innovative assimilation procedures to incorporate these determinations into advanced regional and global atmospheric models and assess their effects; and (3) apply the results to investigate selected scientific issues of relevance to regional and global hydrological studies. An archive of GPS-based estimation of total zenith delay (TZD) data and water vapor where applicable has been established with expanded automated quality control. The accuracy of the GPS estimates is being monitored; the investigation of systematic errors is ongoing using comparisons with water vapor radiometers. Meteorological packages have been implemented. The accuracy and utilization of the TZD estimates has been improved by implementing a troposphere gradient model. GPS-based gradients have been validated as real atmospheric moisture gradients, establishing a link between the estimated gradients and the passage of weather fronts. We have developed a generalized ray tracing inversion scheme that can be used to analyze occultation data acquired from space- or land-based receivers. The National Center for Atmospheric Research mesoscale model (version MM5) has been adapted for Southern California, and assimilation studies are underway. Additional information is contained in the original.

Dickey, Jean O.↗
DOE OSTI2022

A separations and purification process for improving yields and meeting fuel contaminant specifications for high-octane gasoline produced from dimethyl-ether over a Cu/BEA catalyst

In this work, we have been developing a three-step conversion of biomass-derived syngas to methanol to dimethyl-ether (DME) to non-aromatic hydrocarbons for use as high-octane gasoline and sustainable aviation fuel. This process produces branched alkanes from DME using a Cu/BEA catalyst and is a promising alternative to other syngas conversion processes such as Fischer-Tropsch to linear alkanes and traditional ZSM-5 catalyzed methanol to aromatic gasoline. In this short article we describe some advances in our understanding related to separations and purification via the use of more detailed experimental speciation in an updated process model involving multiple phase equilibrium-based separation steps. Primary modeled reactor outlet constituents (and weight %) are: C3 and lighter hydrocarbon gases (11.1%), C4s (54.5%), H 2 (1.2%), CO 2 (2.9%), water (5.0%), unreacted DME (16.5%), methanol (2.3%), and C5+ hydrocarbons (6.4%). DME (the primary reactant) and H 2 recycle and reuse are important for the overall process efficiency, and the recycle of C4s is important to increase the C5+ yield via reactivation and homologation. Thus H 2 , C4s, and DME are targeted for recycle, while methanol and water need to be removed from the product to conform with fuel specifications. Model predictions from Aspen Plus using the NRTL-RK property method indicate a fuel composition with C5+ content of 97.1 wt%, with minor constituents: 2.4 wt% C4s, 0.3 wt% methanol, 0.1 wt% DME, 0.03 wt% water, and 0.01 wt% C3s. These ranges of minor components conform with fuel quality requirements, and the modeled product is amenable for unconstrained blending to boost gasoline octane ratings.

09 BIOMASS FUELS↗
NASA NTRS2001

Active Control of Aerodynamic Noise Sources

Aerodynamic noise sources become important when propulsion noise is relatively low, as during aircraft landing. Under these conditions, aerodynamic noise from high-lift systems can be significant. The research program and accomplishments described here are directed toward reduction of this aerodynamic noise. Progress toward this objective include correction of flow quality in the Low Turbulence Water Channel flow facility, development of a test model and traversing mechanism, and improvement of the data acquisition and flow visualization capabilities in the Aero. & Fluid Dynamics Laboratory. These developments are described in this report.

Reynolds, Gregory A.↗
NASA NTRS2012

Analysis of Water and Energy Budgets and Trends Using the NLDAS Monthly Data Sets

The North American Land Data Assimilation System (NLDAS) is a collaborative project between NASA GSFC, NOAA, Princeton University, and the University of Washington. NLDAS has created surface meteorological forcing data sets using the best-available observations and reanalyses. The forcing data sets are used to drive four separate land-surface models (LSMs), Mosaic, Noah, VIC, and SAC, to produce data sets of soil moisture, snow, runoff, and surface fluxes. NLDAS hourly data, accessible from the NASA GES DISC Hydrology Data Holdings Portal, http://disc.sci.gsfc.nasa.gov/hydrology/data-holdings, are widely used by various user communities in modeling, research, and applications, such as drought and flood monitoring, watershed and water quality management, and case studies of extreme events. More information is available at http://ldas.gsfc.nasa.gov/. To further facilitate analysis of water and energy budgets and trends, NLDAS monthly data sets have been recently released by NASA GES DISC.

Vollmer, Bruce E.↗
NASA NTRS2021

Trash Compaction and Processing System Trash Models and Evolved Gas Analysis of Trash Components

As part of the NASA Next Space Technologies for Exploration Partnerships (NextSTEP) Trash Compaction and Processing System (TCPS) program, the Generation 2 (Gen 2) Heat Melt Compactor (HMC) tests a variety of trash models (nominal, high liquid, and high cloth) in order to evaluate the technical risk associated with processing spacecraft trash. The trash components used in the trash models not only impacts the final solid trash disk quality, but also the water and gas effluent compositions. In order to better design an auxiliary system to treat the effluent streams, both the input trash components and the effluent must be characterized. Evolved gas analysis (EGA) methods are used to characterize the input trash components. The EGA results will be used to determine various HMC operational parameters, as well as to determine the optimal operation for the TCPS system.

Heat Melt Compactor↗
DOE OSTI2022

A framework for ensemble modelling of climate change impacts on lakes worldwide: the ISIMIP Lake Sector

Abstract. Empirical evidence demonstrates that lakes and reservoirs are warming across the globe. Consequently, there is an increased need to project future changes in lake thermal structure and resulting changes in lake biogeochemistry in order to plan for the likely impacts. Previous studies of the impacts of climate change on lakes have often relied on a single model forced with limited scenario-driven projections of future climate for a relatively small number of lakes. As a result, our understanding of the effects of climate change on lakes is fragmentary, based on scattered studies using different data sources and modelling protocols, and mainly focused on individual lakes or lake regions. This has precluded identification of the main impacts of climate change on lakes at global and regional scales and has likely contributed to the lack of lake water quality considerations in policy-relevant documents, such as the Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC). Here, we describe a simulation protocol developed by the Lake Sector of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) for simulating climate change impacts on lakes using an ensemble of lake models and climate change scenarios for ISIMIP phases 2 and 3. The protocol prescribes lake simulations driven by climate forcing from gridded observations and different Earth system models under various representative greenhouse gas concentration pathways (RCPs), all consistently bias-corrected on a 0.5∘ × 0.5∘ global grid. In ISIMIP phase 2, 11 lake models were forced with these data to project the thermal structure of 62 well-studied lakes where data were available for calibration under historical conditions, and using uncalibrated models for 17 500 lakes defined for all global grid cells containing lakes. In ISIMIP phase 3, this approach was expanded to consider more lakes, more models, and more processes. The ISIMIP Lake Sector is the largest international effort to project future water temperature, thermal structure, and ice phenology of lakes at local and global scales and paves the way for future simulations of the impacts of climate change on water quality and biogeochemistry in lakes.

58 GEOSCIENCES↗
DOE OSTI2024

Data-Informed Synthetic Networks of Water Distribution Systems for Resilience Analysis in Puerto Rico

The increasing potential of infrastructure disruptions calls for high-quality infrastructure models to be used in resilience analysis and decision making. Unfortunately, many utilities and communities do not have access to accurate and detailed models due to a lack of data and resources. Furthermore, security restrictions on sharing infrastructure models present roadblocks to research, analysis, and decision making. Recent advances in the development of synthetic water distribution models provide a potential solution to this problem. There is an opportunity to improve these methods by leveraging incomplete pipe datasets to aid synthetic network generation. To address this gap, we developed a methodology for synthetic network generation that incorporates partial pipe data using a modification of the minimum cost flow algorithm for network generation and pipe sizing. This methodology demonstrates how partial pipe data can be leveraged to improve site-specific synthetic network generation. For the study area of Mayagüez, Puerto Rico, a synthetic model generated using 50% of real pipe data matches the pressure of the validation system with an average error of 23.5 m of head, which improves upon the average error of 31.6 m of head produced by a synthetic model generated using no data of the real pipes. Additionally, synthetic networks are shown to replicate the pressure response under a disruption scenario of the validation network, suggesting potential use in resilience analysis.

resilience analysis↗
DOE OSTI2026

Full-scale validation gaps and opportunities for low-head hydropower: a review and perspective

Hydropower is undergoing technological innovation as future development increasingly targets low-head sites (<10 m), primarily through retrofits, rehabilitation, and upgrades of existing infrastructure. This shift toward smaller systems creates a timely opportunity: unlike conventional large projects, many emerging low-head technologies may be small enough for direct full-scale validation. Full-scale testing is particularly important for environmental mitigation technologies, including fish passage, sediment continuity, and water-quality improvements, whose performance is difficult to assess reliably using reduced-scale models. Yet adoption remains constrained by the limited risk-bearing capacity of small hydropower owners, discouraging manufacturers from bringing unvalidated technologies to market. This review and perspective paper examines hydropower trends driving innovation, selected emerging technologies, conventional testing methods, and current U.S. testing capabilities as a case study. We then evaluate the gap between existing capabilities and the needs of low-head powertrains and environmental mitigation measures. Many technologies exceed existing facility flow capacities; in the U.S., the highest combined head–flow capability is limited to 5.66 m3/s, compared with median and 90th-percentile low-head turbine-unit flows of 14.3 and 60 m3/s. To mitigate this gap, we advocate repurposing large, retired, or underused hydraulic infrastructure as full-scale testing facilities to reduce first-adoption risk and support sustainable low-head hydropower deployment.

Tseng, Chien-Yung [Colorado State University, Fort↗
DOE OSTI2022

Quantifying Nitrogen Bioextraction by Seaweed Farms – A Real-time Modeling-Monitoring Case Study in Hood Canal, WA

Anthropogenic nitrogen input is the leading cause of increasing marine eutrophication. Cultivating seaweeds at large scales may provide a viable solution for mitigating eutrophication especially when nitrogen extraction is achieved as an added environmental benefit of biofuel and food production. As the first step to promoting and implementing this solution, it is critical to quantify and assess the effectiveness of nitrogen removal by existing seaweed farms. Pacific Northwest National Laboratory and Hood Canal Mariculture Inc. conducted a case study by applying a coupled modeling-monitoring approach to quantify nitrogen bioextraction by a one-hectare commercial sugar kelp farm in Hood Canal, WA. Through this two-year effort, the project team conducted intensive field monitoring of water quality parameters at the farm site and subsequent laboratory analysis. Meanwhile, the team applied a coupled hydrodynamic-macroalgal growth model to simulate kelp growth and nitrogen bioextraction over the two kelp growing seasons. The model results showed an overall good comparison with field monitoring data and showed the effectiveness of nitrogen removal by kelp farms. The established modeling-monitoring approach can also be transferable for supporting broader research activities in macroalgal farming and eutrophication mitigation.

09 BIOMASS FUELS↗
DOE OSTI2020

Simulator for Hydrologic Unstructured Domains (SHUD v1.0): numerical modeling of watershed hydrology with the finite volume method

Abstract. Hydrologic modeling is an essential strategy for understanding and predicting natural flows, particularly where observations are lacking in either space or time or where complex terrain leads to a disconnect in the characteristic time and space scales of overland and groundwater flow. However, significant difficulties remain for the development of efficient and extensible modeling systems that operate robustly across complex regions. This paper introduces the Simulator for Hydrologic Unstructured Domains (SHUD), an integrated, multiprocess, multiscale, flexible-time-step model, in which hydrologic processes are fully coupled using the finite volume method. SHUD integrates overland flow, snow accumulation/melt, evapotranspiration, subsurface flow, groundwater flow, and river routing, thus allowing physical processes in general watersheds to be realistically captured. SHUD incorporates one-dimensional unsaturated flow, two-dimensional groundwater flow, and a fully connected river channel network with hillslopes supporting overland flow and baseflow. The paper introduces the design of SHUD, from the conceptual and mathematical description of hydrologic processes in a watershed to the model's computational structures. To demonstrate and validate the model performance, we employ three hydrologic experiments: the V-catchment experiment, Vauclin's experiment, and a model study of the Cache Creek Watershed in northern California. Ongoing applications of the SHUD model include hydrologic analyses of hillslope to regional scales (1 m2 to 106 km2), water resource and stormwater management, and interdisciplinary research for questions in limnology, agriculture, geochemistry, geomorphology, water quality, ecology, climate and land-use change. The strength of SHUD is its flexibility as a scientific and resource evaluation tool where modeling and simulation are required.

58 GEOSCIENCES↗
NASA NTRS2004

NASA Data for Water Resources Applications

Water Management Applications is one of twelve elements in the Earth Science Enterprise National Applications Program. NASA Goddard Space Flight Center is supporting the Applications Program through partnering with other organizations to use NASA project results, such as from satellite instruments and Earth system models to enhance the organizations critical needs. The focus thus far has been: 1) estimating water storage including snowpack and soil moisture, 2) modeling and predicting water fluxes such as evapotranspiration (ET), precipitation and river runoff, and 3) remote sensing of water quality, including both point source (e.g., turbidity and productivity) and non-point source (e.g., land cover conversion such as forest to agriculture yielding higher nutrient runoff). The objectives of the partnering cover three steps of: 1) Evaluation, 2) Verification and Validation, and 3) Benchmark Report. We are working with the U.S. federal agencies including the Environmental Protection Agency (EPA), the Bureau of Reclamation (USBR) and the Department of Agriculture (USDA). We are using several of their Decision Support Systems (DSS) tools. This includes the DSS support tools BASINS used by EPA, Riverware and AWARDS ET ToolBox by USBR and SWAT by USDA and EPA. Regional application sites using NASA data across the US. are currently being eliminated for the DSS tools. The current NASA data emphasized thus far are from the Land Data Assimilation Systems WAS) and MODIS satellite products. We are currently in the first two steps of evaluation and verification validation. Water Management Applications is one of twelve elements in the Earth Science Enterprise s National Applications Program. NASA Goddard Space Flight Center is supporting the Applications Program through partnering with other organizations to use NASA project results, such as from satellite instruments and Earth system models to enhance the organizations critical needs. The focus thus far has been: 1) estimating water storage including snowpack and soil moisture, 2) modeling and predicting water fluxes such as evapotranspiration (ET), precipitation and river runoff, and 3) remote sensing of water quality, including both point source (e.g., turbidity and productivity) and non-point source (e.g., land cover conversion such as forest to agriculture yielding higher nutrient runoff). The objectives of the partnering cover three steps of 1) Evaluation, 2) Verification and Validation, and 3) Benchmark Report. We are working with the U.S. federal agencies the Environmental Protection Agency (EPA), the Bureau of Reclamation (USBR) and the Department of Agriculture (USDA). We are using several of their Decision Support Systems (DSS) tools. T us includes the DSS support tools BASINS used by EPA, Riverware and AWARDS ET ToolBox by USBR and SWAT by USDA and EPA. Regional application sites using NASA data across the US. are currently being evaluated for the DSS tools. The current NASA data emphasized thus far are from the Land Data Assimilation Systems (LDAS) and MODIS satellite products. We are currently in the first two steps of evaluation and verification and validation.

Toll, David↗
DOE OSTI2024

Data from "A Bayesian Record Linkage Approach to Applications in Tree Demography Using Overlapping LiDAR Scans"

Processed LiDAR data and environmental covariates from 2015 and 2019 LiDAR scans in the Vicinity of Snodgrass Mountain (Western Colorado, USA), in a geographic subset used in primary analysis for the research paper.This package contains LiDAR-derived canopy height maps for 2015 and 2019, crown polygons derived from the height maps using a segmentation algorithm, and environmental covariates supporting the model of forest growth. Source datasets include August 2015 and August 2019 discrete-return LiDAR point clouds collected by Quantum Geospatial for terrain mapping purposes on behalf of the Colorado Hazard Mapping Program and the Colorado Water Conservation Board. Both datasets adhere to the USGS QL2 quality standard. The point cloud data were processed using the R package lidR to generate a canopy height model representing maximum vegetation height above the ground surface, using a pit-free algorithm.This dataset was compiled to assess how spatial patterns of tree growth in montane and subalpine forests are influenced by water and energy availability. Understanding these growth patterns can provide insight into forest dynamics in the Southern Rocky Mountains under changing climatic conditions.This dataset contains .tif, .csv, and .txt files. 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.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1975

The use of satellite data for regional planning

The experience of the Ohio-Kentucky-Indiana Regional Council of Governments in its development of a regional land use inventory from computer processing of LANDSAT 1 digital tapes and the use of those data in the OKI water quality planning program are discussed. A major part of the planning program is the prediction of water quality in rivers and lakes resulting from existing and future land uses. A model has been developed that can predict the flow of sediment, total phosphorus, total nitrogen, and organic wastes into major streams. An essential input to this model is an accurate map of land use derived from LANDSAT 1 digital tapes.

Hessling, A. H.↗