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At least 145 records · Page 8

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NASA NTRS1973

Water quality parameters of harbors of Charlotte Amalie, St. Thomas, Virgin Islands: Acquisition of in situ water data, intercorrelation of selected water parameters, and initial correlation of these in situ biological, chemical and physical data with ERTS-1 bulk CCT MSS band 5 data

The author has identified the following significant results. Remote sensing by the ERTS-1 satellite was compared with selected water quality parameters including pH, salinity, conductivity, dissolved oxygen, water depth, water temperature, turbidity, plankton concentration, current variables, chlorophylla, total carotenoids, and species diversity of the benthic community. Strong correlation between turbidity and MSS-sensed radiance was recorded and less strong correlations between the two plankton pigments and radiance. Turbidity and benthic species diversity were highly correlated furnishing an inferential tie between an easily sensed water quality variable and a sensitive indicator of average water quality conditions.

Coulbourn, W. C.↗

NASA NTRS1974

Aircraft and satellite monitoring of water quality in Lake Superior near Duluth

Satellite images and low altitude aerial photographs often show vivid discolorations in water bodies. Extensive laboratory analysis shows that water reflectance, which causes brightness on aerial images, positively correlates to the water quality parameter of turbidity, which on a particular day correlates to suspended solids. Work with low altitude photography on three overcast days and with ERTS images on five clear days provides positive correlation of image brightness to the high turbidity and solids which are present in Lake Superior near Duluth over 50% of the time. Proper use of aerial images would have shown that an $8,000,000 drinking water intake constructed in the midst of this unpotable, turbid water should have been located 6 miles north in clear, usable water. Noise effects such as skylight reflection, atmospheric effects, and depth penetration also must be understood for operational use of remote sensing for water quality monitoring and are considered in the paper.

Scherz, J. P.↗

NASA NTRS2014

Improved Algorithms for Accurate Retrieval of UV - Visible Diffuse Attenuation Coefficients in Optically Complex, Inshore Waters

Photochemical processes driven by high-energy ultraviolet radiation (UVR) in inshore, estuarine, and coastal waters play an important role in global bio geochemical cycles and biological systems. A key to modeling photochemical processes in these optically complex waters is an accurate description of the vertical distribution of UVR in the water column which can be obtained using the diffuse attenuation coefficients of down welling irradiance (Kd()). The Sea UV Sea UVc algorithms (Fichot et al., 2008) can accurately retrieve Kd ( 320, 340, 380,412, 443 and 490 nm) in oceanic and coastal waters using multispectral remote sensing reflectances (Rrs(), Sea WiFS bands). However, SeaUVSeaUVc algorithms are currently not optimized for use in optically complex, inshore waters, where they tend to severely underestimate Kd(). Here, a new training data set of optical properties collected in optically complex, inshore waters was used to re-parameterize the published SeaUVSeaUVc algorithms, resulting in improved Kd() retrievals for turbid, estuarine waters. Although the updated SeaUVSeaUVc algorithms perform best in optically complex waters, the published SeaUVSeaUVc models still perform well in most coastal and oceanic waters. Therefore, we propose a composite set of SeaUVSeaUVc algorithms, optimized for Kd() retrieval in almost all marine systems, ranging from oceanic to inshore waters. The composite algorithm set can retrieve Kd from ocean color with good accuracy across this wide range of water types (e.g., within 13 mean relative error for Kd(340)). A validation step using three independent, in situ data sets indicates that the composite SeaUVSeaUVc can generate accurate Kd values from 320 490 nm using satellite imagery on a global scale. Taking advantage of the inherent benefits of our statistical methods, we pooled the validation data with the training set, obtaining an optimized composite model for estimating Kd() in UV wavelengths for almost all marine waters. This optimized composite set of SeaUVSeaUVc algorithms will provide the optical community with improved ability to quantify the role of solar UV radiation in photochemical and photobiological processes in the ocean.

UV↗

DOE OSTI2024

Surface water geochemistry along St. Louis River Estuary (Duluth/Superior, MN/WI)

This dataset is aimed at understanding changes in surface water chemistry associated with urbanization in the Great Lakes region. Surface water chemistry including cations, anions, organic and inorganic carbon, and nitrogen were collected from six locations along St. Louis River – a freshwater estuary entering Lake Superior (Duluth/Superior, MN/WI). The Duluth/Superior, MN/WI metropolitan area is the largest port on the United States side of Lake Superior. Samples were collected near different land uses every two weeks from late July 2023 to the onset of ice cover in November 2023. Water samples were analyzed using In-Situ AquaTroll 500 Multiparameter Sonde with Ammonium Ion Selective Electrode and Chlorophyll-a sensor (unfiltered), METTLER TOLEDO FiveEasy Plus FP20 and METTLER TOLEDO LE407 probe (unfiltered); HACH DR300 Pocket Colorimeter Iron FerroVer (filtered 0.22 μm in field); Shimadzu TOC-L Total Organic Carbon Analyzer with TNM-L Total Nitrogen Unit (filtered 0.22 μm in field); Agilent 8900 triple quadrupole ICP-MS (ICP-QQQ) (filtered 0.22 μm in field); and Dionex ICS-6000 HPIC System (filtered 0.22 μm in field).The data package is comprised of 5 files. dd.csv contains the description of columns in Geochemistry_LSNERR_water.csv and Sampling_sites.csv. flmd.csv contains descriptions of each file in the dataset. README.txt contains description of the dataset structure and file content. Geochemistry_LSNERR_water.csv contains geochemistry data for six sampling locations along the St. Louis River. Sampling_sites.csv contains latitude and longitude coordinates for each of the six sampling site locations along the St. Louis River.This data has not been previously published.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

The Application of Remote Sensing and Machine Learning to Improve Early Warning Systems for Harmful Algal Events in the Highland Lake Chain, TX

Beginning in 2019, harmful algal events have caused canine deaths in both Lady Bird Lake and Lake Travis located near Austin, Texas. These two reservoirs are part of the larger Highland Lakes chain, managed by the City of Austin Department of Watershed Protection (COA DWP) and the Lower Colorado River Authority (LCRA), which fulfill municipal, commercial, and agricultural water demands. Given the recent increase in favorable environmental conditions for algal events in central Texas, NASA DEVELOP partnered with LCRA and COA DWP to improve monitoring and early detection of algal events, utilizing satellite remote sensing and machine learning. Spatially and temporally varied chlorophyll a concentrations, cyanobacteria detections, turbidity, and water surface temperature products are used as environmental proxies. Landsat 8 Operational Land Imager (OLI) and the Sentinel-2 MultiSpectral Instrument (MSI) data were used to provide a combined revisit time of up to ~3 days and < 30 m per pixel products. Chlorophyll a concentrations were estimated using a pre-trained Mixture Density Network, and cyanobacteria detection was accomplished using the Broad Wavelength Algae Index, which can differentiate algal blooms from algal proliferations (mats). In situ data were used to validate remotely sensed measurements and quantify uncertainties. Preliminary results show a good fit between the modeled output and in situ observations, suggesting that remote sensing data can be used to retrieve biogeochemical properties and/or inherent optical properties (IOPs) of water columns in these inland human-made lakes. Uncertainties were introduced from the sensitivity to atmospheric correction, inherent mismatch between satellite and sampling data, and a relatively lower signal-to-noise ratio over water. The resulting products enable near real-time monitoring of environmental proxies relevant to algal event presence in the Highland Lakes chain, and will ultimately support water management, decision making, and risk communication.

Shuyu Chang↗

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 NTRS1999

Wind Induced Sediment Resuspension in a Microtidal Estuary

Bottom sediment resuspension frequency, duration and extent (% of bottom sediments affected) were characterized for the fifteen month period from September 1995 to January 1997 for the Barataria Basin, LA. An empirical model of sediment resuspension as a function of wind speed, direction, fetch and water depth was derived from wave theory. Water column turbidity was examined by processing remotely sensed radiance information from visible and near-IR AVHRR imagery. Based on model predictions, wind induced resuspension occurred during all seasons of this study. Seasonal characteristics for resuspension reveal that late fall, winter and early spring are the periods of most frequent and intense resuspension. Model predictions of the critical wind speed required to induce resuspension indicate that winds of 4 m/s (averaged over all wind directions resuspend approximately 50% of bottom sediments in the water bodies examined. Winds of this magnitude (4 m/s) occurred for 80% of the time during the late fall, winter and early spring and for approximately 30% of the time during the summer. More than 50% of the bottom sedimets are resuspended throughout the year, indicating the importance of resuspension as a process affecting sediment and biogeochemical fluxes in the Barataria Basin.

Booth, J. G.↗

DOE OSTI2020

Real-time monitoring and prediction of water quality parameters and algae concentrations using microbial potentiometric sensor signals and machine learning tools

We report the overarching hypothesis of this study was that temporal microbial potentiometric sensor (MPS) signal patterns could be used to predict changes in commonly monitored water quality parameters by using artificial intelligence/machine learning tools. To test this hypothesis, the study first examines a proof of concept by correlating between MPS's signals and high algae concentrations in an algal cultivation pond. Then, the study expanded upon these findings and examined if multiple water quality parameters could be predicted in real surface waters, like irrigation canals. Signals generated between the MPS sensors and other water quality sensors maintained by an Arizona utility company, including algae and chlorophyll, were collected in real time at time intervals of 30 min over a period of 9 months. Data from the MPS system and data collected by the utility company were used to train the ML/AI algorithms and compare the predicted with actual water quality parameters and algae concentrations. Based on the composite signal obtained from the MPS, the ML/AI was used to predict the canal surface water's turbidity, conductivity, chlorophyll, and blue-green algae (BGA), dissolved oxygen (DO), and pH, and predicted values were compared to the measured values. Initial testing in the algal cultivation pond revealed a strong linear correlation (R 2 = 0.87) between mixed liquor suspended solids (MLSS) and the MPSs' composite signals. The Normalized Root Mean Square Error (NRMSE) between the predicted values and measured values were <6.5%, except for the DO, which was 10.45%. The results demonstrate the usefulness of MPSs to predict key surface water quality parameters through a single composite signal, when the ML/AI tools are used conjunctively to disaggregate these signal components. The maintenance-free MPS offers a novel and cost-effective approach to monitor numerous water quality parameters at once with relatively high accuracy.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2021

Highland Lakes Water Resources: Using NASA Earth Observations to Improve Detection Systems for Harmful Algal Events in the Highland Lakes in Central Texas

Beginning in 2019, harmful algal events in Austin, Texas, caused canine deaths in the Lady Bird Lake and Lake Travis reservoirs. These reservoirs are part of the larger Highland Lakes chain, managed by the Lower Colorado River Authority (LCRA) and the City of Austin Department of Watershed Protection (CoA DWP), which fulfill municipal, commercial, and agricultural water demands. Given the recent increase in favorable algal event conditions in central Texas, the LCRA and CoA DWP partnered with NASA DEVELOP to improve algal event early-warning systems through the application of remote sensing and machine learning. An Earth observation-based algal monitoring system will assist the responsible agencies in predicting algal conditions and communicating hazards to the public. The NASA DEVELOP team utilized Landsat 8 Operational Land Imager (OLI) and Sentinel-2 Multispectral Instrument (MSI) data to produce products including chlorophyll-a concentrations, cyanobacteria detections, turbidity, and water surface temperature. Chlorophyll-a concentrations were retrieved with a pre-trained machine learning model (mixture density network) and spectral indices, while the other products were derived from spectral indices. In situ field data were used to validate and quantify uncertainties for each product. The validations show strong correlations for chlorophyll-a and water surface temperature. Time series analyses of chlorophyll-a concentrations show peaks in the severe drought years (2015 and 2016). This project's resulting products enable monitoring of environmental proxies relevant to algal event presence in the Highland Lakes chain and will ultimately support water management, decision making, and risk communication.

Kaitlynn Hietpas↗

NASA NTRS1973

Correlation of ERTS multispectral imagery with suspended matter and chlorophyll in lower Chesapeake Bay

The feasibility of using multispectral satellite imagery to monitor the characteristics of estuarine waters is being investigated. Preliminary comparisons of MSS imagery with suspended matter concentrations, particle counts, chlorophyll, transmittance and bathymetry have been made. Some visual correlation of radiance with particulates and chlorophyll has been established. Effects of bathymetry are present, and their relation to transmittance and radiance is being investigated. Greatest detail in suspended matter is revealed by MSS band 5. Near-surface suspended sediment load and chlorophyll can be observed in bands 6 and 7. Images received to date have partially defined extent and location of high suspensate concentrations. Net quantity of suspended matter in the lower Bay has been decreasing since the inception of the study, and represents the diminution of turbid flood waters carried into the Bay in late September, 1972. The results so far point to the utility of MSS imagery in monitoring estuarine water character for the assessment of siltation, productivity, and water types.

Bowker, D. E.↗

NASA NTRS1973

Investigation of environmental indices from the Earth Resources Technology Satellite

The author has identified the following significant results. Land use, quality, and air quality trends are being deduced from both ERTS-1 MSS and computer compatible tapes. The data analysis plan and the preliminary data analysis phase were conducted in January 1973. Results from these two phases are: (1) Method of analysis has been selected and checked out. (2) Land use for two dates have been generated for one test site. (3) Water quality for one date has been produced partially. (4) Air quality for three has been produced and compared with ground truth. (5) One of the two DCP stations is in operation; the second station will be installed in March 1973. Land use classification exceeds pre-launch expectations. Water quality (turbidity) is not progressing as expected. Finally, mesoscale air quality results have shown correlation with NOAA/EPA turbidity network. If air quality correlations continue to show favorable results, a rapid means of global turbidity may be available from ERTS-1 MSS observations.

Greeley, R. S.↗

NASA NTRS1973

Application of ERTS-1 imagery to the harvest model of the US Menhaden fishery

Preliminary results of an experiment to demonstrate the utility of ERTS-1 imagery for providing significant information to the harvest model of the menhaden industry are reported. Fisheries and related environmental data were obtained discontinuously throughout the 1973 menhaden (a surface schooling, coastal species) fishing season in Mississippi Sound. The unexpected complexity of the physical environment in Mississippi Sound precluded simplistic analysis of fish/environment relationships. Preliminary indications are that an association does exist between fish availability and differences in water transparency (turbidity) within the Sound. A clearer relationship is developing between major turbid features, imaged by ERTS-1 and location of successful fishing attempts. On all occasions where relatively cloudfree ERTS-1 overflight days coincided with fishery activity, overlays of catch location of ERTS-1 images show an association of school position with interfaces between imaged turbid features. Analysis is currently underway to determine persistence of such associations in an attempt to define minimum satellite return time necessary to maintain continuity of associations.

Maughan, P. M.↗

NASA NTRS1974

The ERTS-1 investigation (ER-600). Volume 2: ERTS-1 coastal/estuarine analysis

The Coastal Analysis Team of the Johnson Space Center conducted a 1-year investigation of ERTS-1 MSS data to determine its usefulness in coastal zone management. Galveston Bay, Texas, was the study area for evaluating both conventional image interpretation and computer-aided techniques. There was limited success in detecting, identifying and measuring areal extent of water bodies, turbidity zones, phytoplankton blooms, salt marshes, grasslands, swamps, and low wetlands using image interpretation techniques. Computer-aided techniques were generally successful in identifying these features. Aerial measurement of salt marshes accuracies ranged from 89 to 99 percent. Overall classification accuracy of all study sites was 89 percent for Level 1 and 75 percent for Level 2.

Erb, R. B.↗

NASA NTRS1975

The use of LANDSAT-1 imagery for water quality studies in southern Scandinavia

The possibilities of using LANDSAT-1 images for environmental studies, with special references to water quality studies, were investigated by selecting test areas in southern Scandinavia. The MSS images of different bands are compared under the magnification of an Interpretoscope and densitometric analyses are performed in a Schnell-photometer. The possibility of tracing pollution plumes is studied in the Oresund outside Copenhagen. The effect of different sewers and the circulation of the polluted water is analyzed in various situations. The variation in reflectivity of a great number of lakes in South and Middle Sweden is studied by means of densitometric analyses and significant regional differences are found. The correlation with in situ measurements of water quality (turbidity and secchi disc transparency) of the sampled lakes (made by the National Swedish Environment Protection Board) is fairly good.

Hellden, U.↗

NASA NTRS1976

Analysis of six broadband optical filters for measuring chlorophyll alpha and suspended solids in the Patuxent River

Kodak Wratten broadband optical filters numbered 47B (400 to 500 nm), 57 (500 to 600 nm), 58 (500 to 600 nm), 12 (500 to 700 nm), 25 (600 to 700 nm), and 89B (690 to 900 nm) were tested on October 17, 1972, to see whether each spectral band by itself could be used to quantify chlorophyll a and suspended sediment in the Patuxent River. Band 690 to 900 nm showed promise in being able to detect gross changes in chlorophyll a above 28 micrograms/l. None of the broad spectral bands seem capable of measuring chlorophyll a concentrations less than 28 micrograms/l in turbid estuarine water. Except for the 47B spectral band, the bands do show promise for measuring suspended solids.

Ohlhorst, C. W.↗

NASA NTRS1982

A parameterized model for global insolation under partially cloudy skies

A simple and efficient parameterization of insolation under partially cloudy skies is discussed and compared with a set of exact radiative transfer results for clear skies, an empirical equation and observations. The parameterization is physically based and requires, as input variables, the ozone path length, precipitable water, Angstrom turbidity, surface air pressure and albedo, fractional cloud-cover and cloud thickness. Multiple reflection between the surface and the overlying atmosphere, and clouds are considered. The albedo of the earth-atmosphere system is also formulated and compared with a set of exact radiative transfer results. As compared to the exact radiative transfer results, the errors in the insolations are generally less than 1 percent, and in the albedo of the earth-atmosphere system less than 10 percent. The errors in the calculated insolations using climatological data are 2-3 percent when compared with many years averaged observations at Maudheim (Antarctica) and at Rockville (U.S.A.). A parametric equation for calculating directly the daily total insolation is also given.

Choudhury, B.↗

NASA NTRS1976

Sensitivity of solar-cell performance to atmospheric variables. 2: Dissimilar cells at several locations

Several solar cells having dissimilar spectral response curves and cell construction were measured at various locations in the United States to determine sensitivity of cell performance to atmospheric water vapor and turbidity. The locations selected represent a broad range of summer atmospheric conditions, from clear and dry to turbid and humid. Cell short circuit current under direct normal incidence sunlight, the intensity, water vapor and turbidity were measured. Regression equations were developed from the limited data base in order to provide a single method of prediction of cell current sensitivity to the atmospheric variables.

Klucher, T. M.↗

NASA NTRS2012

Planetary Lake Lander - A Robotic Sentinel to Monitor a Remote Lake

The Planetary Lake Lander Project is studying the impact of rapid deglaciation at a high altitude alpine lake in the Andes, where disrupted environmental, physical, chemical, and biological cycles result in newly emerging natural patterns. The solar powered Lake Lander robot is designed to monitor the lake system and characterize both baseline characteristics and impacts of disturbance events such as storms and landslides. Lake Lander must use an onboard adaptive science-on-the-fly approach to return relevant data about these events to mission control without exceeding limited energy and bandwidth resources. Lake Lander carries weather sensors, cameras and a sonde that is winched up and down the water column to monitor temperature, dissolved oxygen, turbidity and other water quality parameters. Data from Lake Lander is returned via satellite and distributed to an international team of scientists via web-based ground data systems. Here, we describe the Lake Lander Project scientific goals, hardware design, ground data systems, and preliminary data from 2011. The adaptive science-on-the-fly system will be described in future papers.

Pedersen, Liam↗