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116 records · Page 7Linked to original sources
USGS2001

Regional curve development and selection of a reference reach in the non-urban, lowland sections of the Piedmont physiographic province, Pennsylvania and Maryland

Stream-restoration projects utilizing naturalstream designs frequently are based on the bankfull- channel characteristics of a stream reach that is accommodating streamflow and sediment transport without excessive erosion or deposition. The bankfull channel is identified by the use of field indicators and confirmed with tools such as regional curves. Channel dimensions were surveyed at six streamflow-measurement stations operated by the U.S. Geological Survey in the Gettysburg-Newark Lowlands Section and Piedmont Lowlands Section of the Piedmont Physiographic Province in Pennsylvania and Maryland. Regional curves were developed from regression analyses of the relation between drainage area and cross-sectional area, mean depth, width, and streamflow of the bankfull channel. Regional curves were used to confirm the identification of the bankfull channel at a reference reach. Stream dimensions and characteristics of the reference reach were measured for extrapolation into the design of a steam-restoration project on Bermudian Creek in Adams County, Pa. Dimensions for cross-sectional area, mean depth, width, and computed streamflow of the bankfull channel in all surveyed riffle cross sections in the reference reach were within the 95-percent confidence interval bounding the regression line representing bankfull channel geometry in the Lowland Sections of the Piedmont Physiographic Province. The average bankfull cross-sectional area, bankfull mean depth, and computed bankfull discharge for riffle cross sections in the reference reach ranged from 15.4 to 16.5 percent less than estimates determined from the lowland regional curves. Average bankfull channel width was about 2 percent greater than estimates. Cross-sectional area, mean depth, and computed streamflow corresponding to the bankfull stage at the reference reach were 31.4, 44.4, and 9.6 percent less, respectively, than estimates derived from the regional curves developed by Dunne and Leopold in 1978. Average bankfull channel width at the reference reach was 16.7 percent greater than the Dunne and Leopold estimate. The concepts of regional curves and reference reaches can be valuable tools to support efforts in stream restoration. Practitioners of stream restoration need to recognize them as such and realize their limitations. The small number of stations available for analysis is a major limiting factor in the strength of the results of this investigation. Subjective selection criteria may have unnecessarily eliminated streamflow-measurement stations that could have been included in the regional curves. A bankfull discharge with a recurrence interval within the 1- to 2-year range was used as a criteria for confirmation of the bankfull stage at each streamflow-measurement station. Many researchers accept this range for recurrence interval of the bankfull discharge; however, literature provides contradictory evidence. The use of channel-characteristics data from a reference reach without any monitoring data to document the stability of the reference reach over time is a topic of debate.

Water-Resources Investigations Report↗
USGS2017

A review of surface energy balance models for estimating actual evapotranspiration with remote sensing at high spatiotemporal resolution over large extents

Many approaches have been developed for measuring or estimating actual evapotranspiration ( ET a ), and research over many years has led to the development of remote sensing methods that are reliably reproducible and effective in estimating ET a . Several remote sensing methods can be used to estimate ET a at the high spatial resolution of agricultural fields and the large extent of river basins. More complex remote sensing methods apply an analytical approach to ET a estimation using physically based models of varied complexity that require a combination of ground-based and remote sensing data, and are grounded in the theory behind the surface energy balance model. This report, funded through cooperation with the International Joint Commission, provides an overview of selected remote sensing methods used for estimating water consumed through ET a and focuses on Mapping Evapotranspiration at High Resolution with Internalized Calibration (METRIC) and Operational Simplified Surface Energy Balance (SSEBop), two energy balance models for estimating ET a that are currently applied successfully in the United States. The METRIC model can produce maps of ET a at high spatial resolution (30 meters using Landsat data) for specific areas smaller than several hundred square kilometers in extent, an improvement in practice over methods used more generally at larger scales. Many studies validating METRIC estimates of ET a against measurements from lysimeters have shown model accuracies on daily to seasonal time scales ranging from 85 to 95 percent. The METRIC model is accurate, but the greater complexity of METRIC results in greater data requirements, and the internalized calibration of METRIC leads to greater skill required for implementation. In contrast, SSEBop is a simpler model, having reduced data requirements and greater ease of implementation without a substantial loss of accuracy in estimating ET a . The SSEBop model has been used to produce maps of ET a over very large extents (the conterminous United States) using lower spatial resolution (1 kilometer) Moderate Resolution Imaging Spectroradiometer (MODIS) data. Model accuracies ranging from 80 to 95 percent on daily to annual time scales have been shown in numerous studies that validated ET a estimates from SSEBop against eddy covariance measurements. The METRIC and SSEBop models can incorporate low and high spatial resolution data from MODIS and Landsat, but the high spatiotemporal resolution of ET a estimates using Landsat data over large extents takes immense computing power. Cloud computing is providing an opportunity for processing an increasing amount of geospatial “big data” in a decreasing period of time. For example, Google Earth Engine TM has been used to implement METRIC with automated calibration for regional-scale estimates of ET a using Landsat data. The U.S. Geological Survey also is using Google Earth Engine TM to implement SSEBop for estimating ET a in the United States at a continental scale using Landsat data.

Scientific Investigations Report↗
USGS2010

Method for calculating self-noise spectra and operating ranges for seismographic inertial sensors and recorders

Understanding the performance of sensors and recorders is prerequisite to making appropriate use of them in seismology and earthquake engineering. This paper explores a critical aspect of instrument performance, the “self” noise level of the device and the amplitude range it can usefully record. Self noise limits the smallest signals, while instrument clipping level creates the upper limit (above which it either cannot produce signals or becomes unacceptably nonlinear). Where these levels fall, and the “operating range” between them, determines much of the instrument's viability and the applications for which it is appropriate. The representation of seismic-instrument self-noise levels and their effective operating ranges (cf., dynamic range) for seismological inertial sensors, recorders (data acquisition units, or DAUs), and integrated systems of sensors and recorders (data acquisition systems, or DASs) forces one to address an unnatural comparison between transient finite-bandwidth signals, such as earthquake records, and the instrument's self noise, an effectively stationary signal of infinite duration. In addition to being transient, earthquakes and other records of interest are characterized by a peak amplitude and generally a narrow, peaked spectral shape. Unfortunately, any power spectrum computed for such transient signals is ill defined, since the maximum of that spectrum depends strongly upon signal and record durations. In contrast, the noise floor of an instrument is approximately stationary and properly described by a power spectral density (PSD) or its root (rPSD). Put another way, earthquake records have units of amplitude ( e.g. , m/s 2 ) while PSDs have units of amplitude-squared per hertz ( e.g. , (m/s 2 ) 2 /Hz) and the rPSD has units of amplitude per root of hertz ( e.g. , (m/s 2 )/Hz 1/2 ). Thus, this incompatability is a conflict between earthquake (amplitude) and PSD (spectral density) units that requires one to make various assumptions before they can be compared. For purposes of instrument operational performance, we provide a means of evaluating signal and noise and the range between them in a manner representative of time-domain instrument performance. We call these “operating range diagrams” (ORDs), plots of instrument self noise and clipping level; the “operating range” is the range between these values. For frequency-domain performance we elect to show self noise as an rPSD that may be compared to another instrument's noise or to ambient Earth noise ( e.g. , Peterson 1993); however, to limit the number of arbitrary choices required to merge transient and stationary signals we do not compare the rPSD to transient signals in the frequency domain. Our solution for a time-domain comparison is not new but rather builds upon the consensus of the first and second Guidelines for Seismometer Testing workshops (Hutt et al. 2009) and long established practice in acoustics. We propose this method as a standard for characterizing seismic instruments, and it has been endorsed by the second workshop (Hutt et al. 2009, 2010) and the Advanced National Seismic System (ANSS) Working Group (2008) and recent ANSS procurement specifications.

Seismological Research Letters↗
USGS2021

Assessing cyanobacterial frequency and abundance at surface waters near drinking water intakes across the United States

This study presents the first large-scale assessment of cyanobacterial frequency and abundance of surface water near drinking water intakes across the United States. Public water systems serve drinking water to nearly 90% of the United States population. Cyanobacteria and their toxins may degrade the quality of finished drinking water and can lead to negative health consequences. Satellite imagery can serve as a cost-effective and consistent monitoring technique for surface cyanobacterial blooms in source waters and can provide drinking water treatment operators information for managing their systems. This study uses satellite imagery from the European Space Agency's Ocean and Land Colour Instrument (OLCI) spanning June 2016 through April 2020. At 300-m spatial resolution, OLCI imagery can be used to monitor cyanobacteria in 685 drinking water sources across 285 lakes in 44 states, referred to here as resolvable drinking water sources. First, a subset of satellite data was compared to a subset of responses ( n = 84) submitted as part of the U.S. Environmental Protection Agency's fourth Unregulated Contaminant Monitoring Rule (UCMR 4). These UCMR 4 qualitative responses included visual observations of algal bloom presence and absence near drinking water intakes from March 2018 through November 2019. Overall agreement between satellite imagery and UCMR 4 qualitative responses was 94% with a Kappa coefficient of 0.70. Next, temporal frequency of cyanobacterial blooms at all resolvable drinking water sources was assessed. In 2019, bloom frequency averaged 2% and peaked at 100%, where 100% indicated a bloom was always present at the source waters when satellite imagery was available. Monthly cyanobacterial abundances were used to assess short-term trends across all resolvable drinking water sources and effect size was computed to provide insight on the number of years of data that must be obtained to increase confidence in an observed change. Generally, 2016 through 2020 was an insufficient time period for confidently observing changes at these source waters; on average, a decade of satellite imagery would be required for observed environmental trends to outweigh variability in the data. However, five source waters did demonstrate a sustained short-term trend, with one increasing in cyanobacterial abundance from June 2016 to April 2020 and four decreasing.

Water Research↗
USGS2009

Atmospheric correction at AERONET locations: A new science and validation data set

This paper describes an Aerosol Robotic Network (AERONET)-based Surface Reflectance Validation Network (ASRVN) and its data set of spectral surface bidirectional reflectance and albedo based on Moderate Resolution Imaging Spectroradiometer (MODIS) TERRA and AQUA data. The ASRVN is an operational data collection and processing system. It receives 50 ?? 50 km 2 ; subsets of MODIS level 1B (L1B) data from MODIS adaptive processing system and AERONET aerosol and water-vapor information. Then, it performs an atmospheric correction (AC) for about 100 AERONET sites based on accurate radiative-transfer theory with complex quality control of the input data. The ASRVN processing software consists of an L1B data gridding algorithm, a new cloud-mask (CM) algorithm based on a time-series analysis, and an AC algorithm using ancillary AERONET aerosol and water-vapor data. The AC is achieved by fitting the MODIS top-of-atmosphere measurements, accumulated for a 16-day interval, with theoretical reflectance parameterized in terms of the coefficients of the Li SparseRoss Thick (LSRT) model of the bidirectional reflectance factor (BRF). The ASRVN takes several steps to ensure high quality of results: 1) the filtering of opaque clouds by a CM algorithm; 2) the development of an aerosol filter to filter residual semitransparent and subpixel clouds, as well as cases with high inhomogeneity of aerosols in the processing area; 3) imposing the requirement of the consistency of the new solution with previously retrieved BRF and albedo; 4) rapid adjustment of the 16-day retrieval to the surface changes using the last day of measurements; and 5) development of a seasonal backup spectral BRF database to increase data coverage. The ASRVN provides a gapless or near-gapless coverage for the processing area. The gaps, caused by clouds, are filled most naturally with the latest solution for a given pixel. The ASRVN products include three parameters of the LSRT model (kL, kG, and kV), surface albedo, normalized BRF (computed for a standard viewing geometry, VZA = 0, SZA = 45??), and instantaneous BRF (or one-angle BRF value derived from the last day of MODIS measurement for specific viewing geometry) for the MODIS 500-m bands 17. The results are produced daily at a resolution of 1 km in gridded format. We also provide a cloud mask, a quality flag, and a browse bitmap image. The ASRVN data set, including 6 years of MODIS TERRA and 1.5 years of MODIS AQUA data, is available now as a standard MODIS product (MODASRVN) which can be accessed through the Level 1 and Atmosphere Archive and Distribution System website ( http://ladsweb.nascom.nasa.gov/data/search.html). It can be used for a wide range of applications including validation analysis and science research. ?? 2006 IEEE.

IEEE Transactions on Geoscience and Remote Sensing↗
USGS1985

Effects of flood control alternatives on fish and wildlife resources of the Malheur-Harney lakes basin

Malheur Lake is the largest freshwater marsh in the western contiguous United States and is one of the main management units of the Malheur National Wildlife Refuge in southeastern Oregon. The marsh provides excellent waterfowl production habitat as well as vital migration habitats for birds in the Pacific flyway. Water shortages have typically been a problem in this semiarid area; however, record snowfalls and cool summers have recently caused Malheur Lake to rise to its highest level in recorded history. This has resulted in the loss of approximately 57,000 acres of important wildlife habitat as well as extensive flooding of local ranches, roads, and railroad lines. Because of the importance of the Refuge, any water management plan for the Malheur-Harney Lakes Basin needs to consider the impact of management alternatives on the hydrology of Malheur Lake. The facilitated modeling workshop described in this report was conducted January 14-18, 1985, under the joint sponsorship of the Portland Ecological Services Field Office and the Malheur National Wildlife Refuge, Region 1, U.S. Fish and Wildlife Service (FWS). The Portland Field Office is responsible for FWS reporting requirements on Federal water resource projects while the Refuge staff has management responsibility for much of the land affected by high water levels in the Malheur-Harney Lakes Basin. The primary objective of the workshop was to begin gathering and analyzing information concerning potential fish and wildlife impacts, needs, and opportunities associated with proposed U.S. Army Corps of Engineers (COE) flood control alternatives for Malheur Lake. The workshop was structured around the formulation of a computer model that would simulate the hydrologic effects of the various alternatives and any concommitant changes in vegetation communities and wildlife use patterns. The simulation model is composed of three connected submodels. The Hydrology submodel calculates changes in lake volume, elevation, and surface area, as well as changes in water quality, that result from the proposed water management projects (upstream storage, upstream diversions, drainage canals) and the no action alternative. The Vegetation submodel determines associated changes in the areal extent of wetland and upland vegetation communities. Finally, the Wildlife submodel calculates indices of abundance or habitat suitability for colonial nesting birds (great egret, double-crested cormorant, white-faced ibis), greater sandhill crane, diving ducks, tundra swan, dabbling ducks, and Canada goose based on hydrologic and vegetation conditions. The model represents the Malheur-Harney Lakes Basin, but provides water quantity and quality indicators associated with additional flows that might occur in the Malheur River Basin. Several management scenarios, representing various flood control alternatives and assumptions concerning future runoff, were run to analyze model behavior. Scenario results are not intended as an analysis of all potential management actions or assumptions concerning future runoff. Rather, they demonstrate the type of analysis that could be conducted if the model was sufficiently refined and tested. Early in a model development project, the process of building the model is usually of greater benefit than the model itself. The model building process stimulates interaction among agencies, assists in integrating existing information, and helps identify research needs. These benefits usually accrue even in the absence of real predictive power in the resulting model. This workshop initiated interaction among the primary State and Federal resource and development agencies in a nonadversarial forum. The exchange of information and expertise among agencies provided the FWS with the best information currently available for use in the Planning Aid Letter it will develop at the Reconnaissance state of the COE study. If the COE subsequently initiates a Feasability Study, this information will be refined further and will aid the FWS in preparing its Coordination Act Report on any flood control alternative proposed by the COE. The model building and testing process also helped identify model limitations and more general information needs that should be evaluated for further study prior to preparation of an FWS Coordination Act Report. Major needs associated with the Hydrology submodel include a more detailed representation of hydrologic units (separately consider Harney Lake, Mud Lake, and Malheur Lake or the three hydrological units within Malheur Lake, rather than a combined lake system) and explicitly representation of groundwater storage and discharge in water budget calculations. A better representation of the hydrological units will require more detailed topographic data for the basin, capacity-elevation and elevation-surface area curves for each unit, and better water flow data between the units. Additional water quality parameters and constraints on proposed canal operation due to conditions in the Malheur River might also be added. Key Vegetation submodel needs include fine-tuning existing vegetation relationships in the model and adding relationships to address the influence of historical conditions on vegetation development, effects of very rapid changes in lake level, effects of wildlife populations (e.g., carp, muskrat), responses of vegetation to habitat management actions (e.g, haying, grazing, burning), and better representation of sago pondweed dynamics. A complementary geographic information system might also be developed for spatial analyses. Major needs that should be evaluated for the Wildlife submodel include addition of other wildlife species that have important effects on habitat on the Refuge (e.g., carp, muskrat) and consideration of additional life-cycle requisites and controlling variable for species presently in the model. Some of these limitations could perhaps be overcome if historical data on habitat conditions were developed to use with historical data on wildlife populations.

Oregon↗
USGS2009

Experimental Advanced Airborne Research Lidar (EAARL) Data Processing Manual

The Experimental Advanced Airborne Research Lidar (EAARL) is an example of a Light Detection and Ranging (Lidar) system that utilizes a blue-green wavelength (532 nanometers) to determine the distance to an object. The distance is determined by recording the travel time of a transmitted pulse at the speed of light (fig. 1). This system uses raster laser scanning with full-waveform (multi-peak) resolving capabilities to measure submerged topography and adjacent coastal land elevations simultaneously (Nayegandhi and others, 2009). This document reviews procedures for the post-processing of EAARL data using the custom-built Airborne Lidar Processing System (ALPS). ALPS software was developed in an open-source programming environment operated on a Linux platform. It has the ability to combine the laser return backscatter digitized at 1-nanosecond intervals with aircraft positioning information. This solution enables the exploration and processing of the EAARL data in an interactive or batch mode. ALPS also includes modules for the creation of bare earth, canopy-top, and submerged topography Digital Elevation Models (DEMs). The EAARL system uses an Earth-centered coordinate and reference system that removes the necessity to reference submerged topography data relative to water level or tide gages (Nayegandhi and others, 2006). The EAARL system can be mounted in an array of small twin-engine aircraft that operate at 300 meters above ground level (AGL) at a speed of 60 meters per second (117 knots). While other systems strive to maximize operational depth limits, EAARL has a narrow transmit beam and receiver field of view (1.5 to 2 milliradians), which improves the depth-measurement accuracy in shallow, clear water but limits the maximum depth to about 1.5 Secchi disk depth (~20 meters) in clear water. The laser transmitter [Continuum EPO-5000 yttrium aluminum garnet (YAG)] produces up to 5,000 short-duration (1.2 nanosecond), low-power (70 microjoules) pulses each second. Each pulse is focused into an illumination area that has a radius of about 20 centimeters on the ground. The pulse-repetition frequency of the EAARL transmitter varies along each across-track scan to produce equal cross-track sample spacing and near uniform density (Nayegandhi and others, 2006). Targets can have varying physical and optical characteristics that cause extreme fluctuations in laser backscatter complexity and signal strength. To accommodate this dynamic range, EAARL has the real-time ability to detect, capture, and automatically adapt to each laser return backscatter. The backscattered energy is collected by an array of four high-speed waveform digitizers connected to an array of four sub-nanosecond photodetectors. Each of the four photodetectors receives a finite range of the returning laser backscatter photons. The most sensitive channel receives 90% of the photons, the least sensitive receives 0.9%, and the middle channel receives 9% (Wright and Brock, 2002). The fourth channel is available for detection but is not currently being utilized. All four channels are digitized simultaneously into 65,536 samples for every laser pulse. Receiver optics consists of a 15-centimeter-diameter dielectric-coated Newtonian telescope, a computer-driven raster scanning mirror oscillating at 12.5 hertz (25 rasters per second), and an array of sub-nanosecond photodetectors. The signal emitted by the pulsed laser transmitter is amplified as backscatter by the optical telescope receiver. The photomultiplier tube (PMT) then converts the optical energy into electrical impulses (Nayegandhi and others, 2006). In addition to the full-waveform resolving laser, the EAARL sensor suite includes a down-looking 70-centimeter-resolution Red-Green-Blue (RGB) digital network camera, a high-resolution color infrared (CIR) multispectral camera (14-centimeter-resolution), two precision dual-frequency kinematic carrier-phase global positioning system (GPS) receivers, and an

Open-File Report↗
USGS1981

Significant results from using earth observation satellites for mineral and energy resource exploration

A large number of Earth-observation satellites orbit our world several times each day, providing new information about the land and sea surfaces and the overlying thin layer of atmosphere that makes our planet unique. Meteorological satellites have had the longest history of experimental use and most are now considered operational. The geologic information collected by the Landsat, Polar Orbiting Geophysical Observatory (POGO), Magsat, Heat Capacity Mapping Mission (HCMM) and Seasat land and ocean observation systems is being thoroughly tested, and some of these systems are now approaching operational use. Landsat multispectral images provide views of large areas of the Earth under uniform lighting conditions and can be obtained at a variety of scales and formats. Not only do the Landsat data provide highly useful images showing surficial materials and structures such as folds and faults, but also measurements and computer-derived ratios of the brightness of different rock types, alteration zones, and mineral associations. These data have led to the finding of a variety of new ore deposits. In addition, the combination of Landsat digital data and aeromagnetic data has extended the use of Landsat as an exploration tool which can be used to readily relate surface features to subsurface anomalies. Magsat data, now being collected, are helping refine information on major crustal anomalies that were first recognized during the analysis of POGO data. The more nearly circular orbit, lower altitude, and increased sophistication of its vector magnetometer enable Magsat to provide more precise information than POGO. Information of this type is required to develop crustal models. Although Magsat is designed to operate for only 4–8 months, the number of orbits that it should be able to make will be sufficient to accomplish its mission and to record a major magnetic storm expected in 1980. HCMM is a two-band visible to near-IR (0.55–1.1 μm) and thermal infrared (10.2–12.5 μm) system designed to measure reflected solar energy, determine the heat capacity of rocks and to monitor soil moisture, thermal effluents, plant canopy temperatures and snow cover. Launched in April 1978, it is in sun-synchronous, circular orbit at an altitude of 620 km. It is a relatively low-resolution system with an instantaneous field of view (IFOV) of 500–600 m and a swath width of 716 km. However, the system is designed to detect objects in the range of 260°–340° K with a sensitivity (NEδT) of 0.4°K at 280°. Recording the thermal radiation of urban heat islands and high thermal inertia of quartzite strata in the Appalachian region are two examples of its land applications. Launched in June 1978, Seasat operated for only 100 days, but successfully acquired much information over both sea and land. The collection of synthetic aperture radar (SAR) imagery and radar altimetry was particularly important to geologists. Although there are difficulties in processing and distributing these data in a timely manner, initial evaluations indicate that the radar imagery supplements Landsat data by increasing the spectral range and offering a different look angle. The radar altimeter provides accurate profiles over narrow strips of land (1 km wide) and has demonstrated usefulness in measuring icecap surfaces (Greenland, Iceland, and Antarctica). The Salar of Uyuni in southern Bolivia served as a calibration site for the altimeter and has enabled investigators to develop a land-based smoothing algorithm that is believed to increase the accuracy of the system to 10 cm. Data from the altimeter are currently being used to measure subsidence resulting from ground water withdrawal in the Phoenix-Tucson area.

Advances in Space Research↗