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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Application of MODIS Products to Infer Possible Relationships Between Basin Land Cover and Coastal Waters Turbidity Using the Magdalena River, Colombia, as a Case Study

Basin development and consequent change in basin land cover have been often associated with an increased turbidity in coastal waters because of sediment yield and nutrients loading. The later leads to phytoplankton abundance further exacerbating water turbidity. This subsequently affects biological and physical processes in coastal estuaries by interfering with sun light penetration to coral reefs and sea grass, and even affecting public health. Therefore, consistent estimation of land cover changes and turbidity trend lines is crucial to design environmental and restoration management plans, to predict fate of possible pollutants, and to estimate sedimentary fluxes into the ocean. Ground solely methods to estimate land cover change would be unpractical and traditional methods of monitoring in situ water turbidity can be very expensive and time consuming. Accurate monitoring on the status and trends of basin land cover as well as the water quality of the receiving water bodies are required for analysis of relationships between the two variables. Use of remote sensing (RS) technology provides a great benefit for both fields of study, facilitating monitoring of changes in a timely and cost effective manner and covering wide areas with long term measurements. In this study, the Magdalena River basin and fixed geographical locations in the estuarine waters of its delta are used as a case to study the temporal trend lines of both, land cover change and the reflectance of the water turbidity using satellite technology. Land cover data from a combined product between sensors Terra and Aqua (MCD12Q1) from MODIS will be adapted to the conditions in the Magdalena basin to estimate changes in land cover since year 2000 to 2009. Surface reflectance data from a MODIS, Terra (MOD09GQ), band 1, will be used in lieu of in situ water turbidity for the time period between 2000 and present. Results will be compared with available existing data.

Madrinan, Max Jacobo Moreno↗
NASA NTRS2013

Groundwater Depletion in the Middle East from GRACE with Implications for Transboundary Water Management in the Tigris-Euphrates-Western Iran Region

In this study, we use observations from the Gravity Recovery and Climate Experiment (GRACE) satellite mission to evaluate freshwater storage trends in the north-central Middle East, including portions of the Tigris and Euphrates River Basins and western Iran, from January 2003 to December 2009. GRACE data show an alarming rate of decrease in total water storage of approximately -27.2 plus or minus 0.6 mm per yr equivalent water height, equal to a volume of 143.6 cubic kilometers during the course of the study period. Additional remote-sensing information and output from land surface models were used to identify that groundwater losses are the major source of this trend. The approach used in this study provides an example of ''best current capabilities'' in regions like the Middle East, where data access can be severely limited. Results indicate that the region lost 17.3 plus or minus 2.1 mm per yr equivalent water height of groundwater during the study period, or 91.3 plus or minus 10.9 cubic kilometers in volume. Furthermore, results raise important issues regarding water use in transboundary river basins and aquifers, including the necessity of international water use treaties and resolving discrepancies in international water law, while amplifying the need for increased monitoring for core components of the water budget

remote sensing↗
NASA NTRS2013

Groundwater Depletion in the Middle East from GRACE with Implications for Transboundary Water Management in the Tigris-Euphrates-Western Iran Region

In this study, we use observations from the Gravity Recovery and Climate Experiment (GRACE) satellite mission to evaluate freshwater storage trends in the north-central Middle East, including portions of the Tigris and Euphrates River Basins and western Iran, from January 2003 to December 2009. GRACE data show an alarming rate of decrease in total water storage of approximately -27.2 plus or minus 0.6 millimeters per year equivalent water height, equal to a volume of 143.6 cubic kimometers during the course of the study period. Additional remote-sensing information and output from land surface models were used to identify that groundwater losses are the major source of this trend. The approach used in this study provides an example of ''best current capabilities'' in regions like the Middle East, where data access can be severely limited. Results indicate that the region lost 17.3 plus or minus 2.1 millimeters per year equivalent water height of groundwater during the study period, or 91.3 plus or minus 10.9 cubic kilometers in volume. Furthermore, results raise important issues regarding water use in transboundary river basins and aquifers, including the necessity of international water use treaties and resolving discrepancies in international water law, while amplifying the need for increased monitoring for core components of the water budget.

GRACE↗
NASA NTRS2018

Developing Land Use Land Cover Maps for the Lower Mekong Basin to Aid Hydrologic Modeling and Basin Planning

This paper discusses research methodology to develop Land Use Land Cover (LULC) mapsfor the Lower Mekong Basin (LMB) for basin planning, using both MODIS and Landsat satellitedata. The 2010 MODIS MOD09 and MYD09 8-day reflectance data was processed into monthlyNDVI maps with the Time Series Product Tool software package and then used to classify regionallycommon forest and agricultural LULC types. Dry season circa 2010 Landsat top of atmosphere reflectance mosaics were classified to map locally common LULC types. Unsupervised ISODATAclustering was used to derive most LULC classifications. MODIS and Landsat classifications werecombined with GIS methods to derive final 250-m LULC maps for Sub-basins (SBs) 1–8 of the LMB.The SB 7 LULC map with 14 classes was assessed for accuracy. This assessment compared randomlocations for sampled types on the SB 7 LULC map to geospatial reference data such as Landsat RGBs,MODIS NDVI phenologic profiles, high resolution satellite data, and Mekong River Commissiondata (e.g., crop calendars). The SB 7 LULC map showed an overall agreement to reference data of~81%. By grouping three deciduous forest classes into one, the overall agreement improved to ~87%.The project enabled updated regional LULC maps that included more detailed agriculture LULCtypes. LULC maps were supplied to project partners to improve use of Soil andWater AssessmentTool for modeling hydrology and water use, plus enhance LMB water and disaster managementin a region vulnerable to flooding, droughts, and anthropogenic change as part of basin planningand assessment.

land use land cover mapping; SWAT hydrologic model↗
NASA NTRS2020

Remote monitoring of agricultural systems using NDVI time series and machine learning methods: a tool for an adaptive agricultural policy

This study aims to provide accurate information about changes in agricultural systems (AS) using phenological metrics derived from the NDVI time series. Use of such information could help land managers optimize land use choices and monitor the status of agricultural lands, under a variety of environmental and socioeconomic conditions. For this purpose, the Moderate Resolution Imaging Spectroradiometer (MODIS) NDVI data were used to derive phenological metrics over the Oum Er-Rbia basin (central Morocco). Random forest (RF), support vector machine (SVM), and K-nearest neighbor (KNN) classifiers were explored and compared on their ability to classify AS classes over the study area. Four main AS classes have been considered: (1) irrigated annual crop (IAC), (2) irrigated perennial crop (IPC), (3) rainfed area (RA), and (4) fallow (FA). By comparing the accuracy of the three classifiers, the RF method showed the best performance with an overall accuracy of 0.97 and kappa coefficient of 0.96.The RF method was then chosen to examine time variations in AS over a 16-year period (2000–2016). The AS main variations were detected and evaluated for the four AS classes. These variations have been found to be linked well with other indicators of local agricultural land management, as well as the historical agricultural drought changes over the study area. Overall, the results present a tool for decision makers to improve agricultural management and provide a different perspective in understanding the spatiotemporal dynamics of agricultural systems.

Youssef Lebrini↗
NASA NTRS1973

Digital analysis of Potomac River Basin ERTS imagery: Sedimentation levels at the Potomac-Anacostia confluence and strip mining in Allegheny County, Maryland

Two simple algorithms for classification of sedimentation levels in water and for delineation of active strip mines are in use as part of the development of a more general resource management information system. ERTS MSS CCT's are processed so that each pixel in each channel is geographically referenced and can be accessed individually during whole frame, multi-channel analysis or partial frame analysis. The sedimentation analysis clearly separates classes representing the turbid Anacostia water, the less disturbed Potomac (really), and mud flats resulting from effluent of a major sewage treatment plant. Mud flats of organic or mineral origin are easily distinguished.

Schubert, J. S.↗
NASA NTRS2019

Utilizing Satellite Based Observations and Physical Hydrological Modeling for Freshwater Ecosystem Health in the Lower Mekong River Basin

Freshwater availability is necessary to promote economic growth through agriculture, fisheries, transport, environmental health, and social equity.The National Aeronautics and Space Administration (NASA) and the Conservation International (CI) are partnering to use remote sensing Earth observations to improve regional efforts that assess natural resources for conservation and sustainable management. (Vollmer et al.,2018) have presented the social-ecological framework named the Freshwater Health Index (FHI), which takes account of the interplay between governance, stakeholders, freshwater ecosystems and the ecosystem services they provide.In this work, we develop decision support and making tools for natural resources conservation in the Lower Mekong by leveraging the FHI framework, multiple data products, and hydrological modeling capabilities (Mohammed et al., 2018). Modeling capabilities enable the integration of satellite-based daily gridded precipitation, air temperature, digital elevation model, soil characteristics, and land cover and land use information to simulate water flux framework.

Mohammed, Ibrahim N.↗
NASA NTRS1983

Integration of Landsat data into the Saginaw River Basin geographic information system

One of the objectives of the Saginaw River Basin study is related to the development of a computer model to predict flood damages. The computer model is to be operational in June 1985. In order to achieve this objective, the input of land-use data into a data base consisting of 198,000 grid cells will be required. A planning technique using Spatial Analysis Methodology (SAM) was developed by the Corps of Engineers Hydrologic Engineering Center (HEC) to systematically handle these data. The HEC-SAM system uses the spatially oriented map data in a series of data management and analysis software programs for input to the Corps hydrologic and environmental models. Attention is given to data base development, Landsat digital data, the placement of the Landsat data into the grid cell data base, and the development of the land cover classification. The Landsat-2 MSS scene covering 85 percent of the Saginaw River Basin was geometrically corrected to a UTM coordinate system.

Mckim, H. L.↗
NASA NTRS2020

Land management and climate change determine second‐generation bioenergy potential of the US Northern Great Plains

Bioenergy with carbon capture and storage (BECCS) has been proposed as a potential climate mitigation strategy raising concerns over trade‐offs with existing ecosystem services. We evaluate the feasibility of BECCS in the Upper Missouri River Basin (UMRB), a landscape with diverse land use, ownership, and bioenergy potential. We develop land‐use change scenarios and a switchgrass (Panicum virgatum L.) crop functional type to use in a land‐surface model to simulate second‐generation bioenergy production. By the end of this century, average annual switchgrass production over the UMRB ranges from 60 to 210 Tg dry mass/year and is dependent on the Representative Concentration Pathway for greenhouse gas emissions and on land‐use change assumptions. Under our simple phase‐in assumptions this results in a cumulative total production of 2,000–6,000 Tg C over the study period with the upper estimates only possible in the absence of climate change. Switchgrass yields decreased as average CO2 concentrations and temperatures increased, suggesting the effect of elevated atmospheric CO2 was small because of its C4 photosynthetic pathway. By the end of the 21st century, the potential energy stored annually in harvested switchgrass averaged between 1 and 4 EJ/year assuming perfect conversion efficiency, or an annual electrical generation capacity of 7,000–28,000 MW assuming current bioenergy efficiency rates. Trade‐offs between bioenergy and ecosystem services were identified, including cumulative direct losses of 1,000–2,600 Tg C stored in natural ecosystems from land‐use change by 2090. Total cumulative losses of ecosystem carbon stocks were higher than the potential ~300 Tg C in fossil fuel emissions from the single largest power plant in the region over the same time period, and equivalent to potential carbon removal from the atmosphere from using biofuels grown in the same region. Numerous trade‐offs from BECCS expansion in the UMRB must be balanced against the potential benefits of a carbon‐negative energy system.

climate change↗
NASA NTRS1981

Identifying environmental features for land management decisions

The benefits of changes in management organization and facilities for the Center for Remote Sensing and Cartography in Utah are reported as well as interactions with and outreach to state and local agencies. Completed projects are described which studied (1) Unita Basin wetland/land use; (2) Davis County foothill development; (3) Farmington Bay shoreline fluctuation; (4) irrigation detection; and (5) satellite investigation of snow cover/mule deer relationships. Techniques developed for composite computer mapping, contrast enhancement, U-2 CIR/LANDSAT digital interface; factor analysis, and multivariate statistical analysis are described.

Source record↗
NASA NTRS1990

Space Station Freedom - Technology R&D and test facility for the 21st century

Development of the SSF is considered in terms of a primary stimulus for technology research and development activities in the early 21st century. The utilization and operations management organization, the ground facilities, and the associated international agreements will form the basis for all future major space projects, including lunar and Mars missions and outposts. Problems discussed include SSF technology R&D accommodations, Pacific Basin cooperative R&D opportunities, Pacific Basin cooperative R&D candidates, and space infrastructure cooperative projects.

Holt, Alan C.↗
NASA NTRS2011

Combining Space-Based and In-Situ Measurements to Track Flooding in Thailand

We describe efforts to integrate in-situ sensing, space-borne sensing, hydrological modeling, active control of sensing, and automatic data product generation to enhance monitoring and management of flooding. In our approach, broad coverage sensors and missions such as MODIS, TRMM, and weather satellite information and in-situ weather and river gauging information are all inputs to track flooding via river basin and sub-basin hydrological models. While these inputs can provide significant information as to the major flooding, targetable space measurements can provide better spatial resolution measurements of flooding extent. In order to leverage such assets we automatically task observations in response to automated analysis indications of major flooding. These new measurements are automatically processed and assimilated with the other flooding data. We describe our ongoing efforts to deploy this system to track major flooding events in Thailand.

Flooding↗
NASA NTRS1975

An ERTS-1 investigation for Lake Ontario and its basin

The author has identified the following significant results. Methods of manual, semi-automatic, and automatic (computer) data processing were evaluated, as were the requirements for spatial physiographic and limnological information. The coupling of specially processed ERTS data with simulation models of the watershed precipitation/runoff process provides potential for water resources management. Optimal and full use of the data requires a mix of data processing and analysis techniques, including single band editing, two band ratios, and multiband combinations. A combination of maximum likelihood ratio and near-IR/red band ratio processing was found to be particularly useful.

Polcyn, F. C.↗
NASA NTRS2022

Tracking the Impacts of Precipitation Phase Changes Through the Hydrologic Cycle in Snowy Regions: From Precipitation to Reservoir Storage

Cool season precipitation plays a critical role in regional water resource management in the western United States. Throughout the twenty-first century, regional precipitation will be impacted by rising temperatures and changing circulation patterns. Changes to precipitation magnitude remain challenging to project; however, precipitation phase is largely dependent on temperature, and temperature predictions from global climate models are generally in agreement. To understand the implications of this dependence, we investigate projected patterns in changing precipitation phase for mountain areas of the western United States over the twenty-first century and how shifts from snow to rain may impact runoff. We downscale two bias-corrected global climate models for historical and end-century decades with the Weather Research and Forecasting (WRF) regional climate model to estimate precipitation phase and spatial patterns at high spatial resolution (9 km). For future decades, we use the RCP 8.5 scenario, which may be considered a very high baseline emissions scenario to quantify snow season differences over major mountain chains in the western U.S. Under this scenario, the average annual snowfall fraction over the Sierra Nevada decreases by >45% by the end of the century. In contrast, for the colder Rocky Mountains, the snowfall fraction decreases by 29%. Streamflow peaks in basins draining the Sierra Nevada are projected to arrive nearly a month earlier by the end of the century. By coupling WRF with a water resources model, we estimate that California reservoirs will shift towards earlier maximum storage by 1–2 months, suggesting that water management strategies will need to adapt to changes in streamflow magnitude and timing.

Melissa L. Wrzesien↗
NASA NTRS2017

Automated Mapping of Flood Events in the Mississippi River Basin Utilizing NASA Earth Observations

The Mississippi River Basin is the fourth largest drainage basin in the world, and is susceptible to multi-level flood events caused by heavy precipitation, snow melt, and changes in water table levels. Conducting flood analysis during periods of disaster is a challenging endeavor for NASA's Short-term Prediction Research and Transition Center (SPoRT), Federal Emergency Management Agency (FEMA), and the U.S. Geological Survey's Hazards Data Distribution Systems (USGS HDDS) due to heavily-involved research and lack of manpower. During this project, an automated script was generated that performs high-level flood analysis to relieve the workload for end-users. The script incorporated Landsat 8 Operational Land Imager (OLI) tiles and utilized computer-learning techniques to generate accurate water extent maps. The script referenced the Moderate Resolution Imaging Spectroradiometer (MODIS) land-water mask to isolate areas of flood induced waters. These areas were overlaid onto the National Land Cover Database's (NLCD) land cover data, the Oak Ridge National Laboratory's LandScan data, and Homeland Infrastructure Foundation-Level Data (HIFLD) to determine the classification of areas impacted and the population density affected by flooding. The automated algorithm was initially tested on the September 2016 flood event that occurred in Upper Mississippi River Basin, and was then further tested on multiple flood events within the Mississippi River Basin. This script allows end users to create their own flood probability and impact maps for disaster mitigation and recovery efforts.

Bartkovich, Mercedes↗
NASA NTRS1981

Irrigated lands assessment for water management: Technique test

A procedure for estimating irrigated land using full frame LANDSAT imagery was demonstrated. Relatively inexpensive interpretation of multidate LANDSAT photographic enlargements was used to produce a map of irrigated land in California. The LANDSAT and ground maps were then linked by regression equations to enable precise estimation of irrigated land area by county, basin, and statewide. Land irrigated at least once in California in 1979 was estimated to be 9.86 million acres, with an expected error of less than 1.75% at the 99% level of confidence. To achieve the same level of error with a ground-only sample would have required 3 to 5 times as many ground sample units statewide. A procedure for relatively inexpensive computer classification of LANDSAT digital data to irrigated land categories was also developed. This procedure is based on ratios of MSS band 7 and 5, and gave good results for several counties in the Central Valley.

Wall, S. L.↗
NASA NTRS2007

Assimilation of GRACE Terrestrial Water Storage Data into a Land Surface Model: Results for the Mississippi River Basin

NASA's GRACE mission has the potential to be extremely valuable for water resources applications and global water cycle research. What makes GRACE unique among Earth Science satellite systems is that it is able to monitor variations in water stored in all forms, from snow and surface water to soil moisture to groundwater in the deepest aquifers. However, the space and time resolutions of GRACE observations are coarse. GRACE typically resolves water storage changes over regions the size of Nebraska on a monthly basis, while city-scale, daily observations would be more useful for water management, agriculture, and weather prediction. High resolution numerical (computer) hydrology models have been developed, which predict the fates of water and energy after they strike the land surface as precipitation and sunlight. These are similar to weather and climate forecast models, which simulate atmospheric processes. We integrated the GRACE observations into a hydrology model using an advanced technique called data assimilation. The results were new estimates of groundwater, soil moisture, and snow variations, which combined the veracity of GRACE with the high resolution of the model. We tested the technique over the Mississippi River basin, but it will be even more valuable in parts of the world which lack reliable data on water availability.

Zaitchik, Benjamin F.↗
NASA NTRS2016

Measuring Global Water Security Towards Sustainable Development Goals

Water plays an important role in underpinning equitable, stable and productive societies and ecosystems. Hence, United Nations recognized ensuring water security as one (Goal 6) of the seventeen sustainable development goals (SDGs). Many international river basins are likely to experience 'low water security' over the coming decades. Water security is rooted not only in the physical availability of freshwater resources relative to water demand, but also on social and economic factors (e.g. sound water planning and management approaches, institutional capacity to provide water services, sustainable economic policies). Until recently, advanced tools and methods are available for the assessment of water scarcity. However, quantitative and integrated-physical and socio-economic-approaches for spatial analysis of water security at global level are not available yet. In this study, we present a spatial multi-criteria analysis framework to provide a global assessment of water security. The selected indicators are based on Goal 6 of SDGs. The term 'security' is conceptualized as a function of 'availability', 'accessibility to services', 'safety and quality', and 'management'. The proposed global water security index (GWSI) is calculated by aggregating indicator values on a pixel-by-pixel basis, using the ordered weighted average method, which allows for the exploration of the sensitivity of final maps to different attitudes of hypothetical policy makers. Our assessment suggests that countries of Africa, South Asia and Middle East experience very low water security. Other areas of high water scarcity, such as some parts of United States, Australia and Southern Europe, show better GWSI values, due to good performance of management, safety and quality, and accessibility. The GWSI maps show the areas of the world in which integrated strategies are needed to achieve water related targets of the SDGs particularly in the African and Asian continents.

sustainable-development goals↗