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At least 37 records · Page 2Linked to original sources
USGS2017

Probabilistic tsunami hazard analysis: Multiple sources and global applications

Applying probabilistic methods to infrequent but devastating natural events is intrinsically challenging. For tsunami analyses, a suite of geophysical assessments should be in principle evaluated because of the different causes generating tsunamis (earthquakes, landslides, volcanic activity, meteorological events, and asteroid impacts) with varying mean recurrence rates. Probabilistic Tsunami Hazard Analyses (PTHAs) are conducted in different areas of the world at global, regional, and local scales with the aim of understanding tsunami hazard to inform tsunami risk reduction activities. PTHAs enhance knowledge of the potential tsunamigenic threat by estimating the probability of exceeding specific levels of tsunami intensity metrics (e.g., run-up or maximum inundation heights) within a certain period of time (exposure time) at given locations (target sites); these estimates can be summarized in hazard maps or hazard curves. This discussion presents a broad overview of PTHA, including (i) sources and mechanisms of tsunami generation, emphasizing the variety and complexity of the tsunami sources and their generation mechanisms, (ii) developments in modeling the propagation and impact of tsunami waves, and (iii) statistical procedures for tsunami hazard estimates that include the associated epistemic and aleatoric uncertainties. Key elements in understanding the potential tsunami hazard are discussed, in light of the rapid development of PTHA methods during the last decade and the globally distributed applications, including the importance of considering multiple sources, their relative intensities, probabilities of occurrence, and uncertainties in an integrated and consistent probabilistic framework.

Reviews of Geophysics↗
USGS1998

Intercomparison of principal hydrometric instruments; Third phase, Evaluation of ultrasonic velocity meters for flow measurement in streams, canals, and estuaries

As part of the World Meteorological Organization ( WMO ) project Intercomparison of Principal Hydrometric Instruments , Third Phase , a questionnaire was prepared by the U.S. Geological Survey (USGS) on the application of Ultrasonic Velocity Meters (UVM's) for flow measurement in streams , canals , and estuaries . In 1996, this questionnaire was distributed internationally by the WMO and USGS, and distributed within the United States by the USGS. Completed questionnaires were returned by 26 agencies in 7 countries (Canada, France, Germany, The Netherlands, Switzerland, the United Kingdom, and the United States). The completed questionnaires described geometric and streamflow conditions, system configurations, and reasons for applying UVM systems for 260 sites, thus providing information on the applicability of UVM systems throughout the world. The completed questionnaires also provided information on operational issues such as (1) methods used to determine and verify UVM ratings, (2) methods used to determine the mean flow velocity for UVM systems, (3) operational reliability of UVM systems, (4) methods to estimate missing data, (5) common problems with UVM systems and guidelines to mitigate these problems, and (6) personnel training issues. The completed questionnaires also described a few unique or novel applications of UVM systems. In addition to summarizing the completed questionnaires, this report includes a brief overview of UVM application and operation, and a short summary of current (1998) information from UVM system manufacturers regarding system cost and capabilities. On the basis of the information from the completed questionnaires and provided by the manufacturers, the general applicability of UVM systems is discussed. In the finalisation of this report the financial support provided by the US National Committee for Scientific Hydrology is gratefully acknowledged.

Report↗
USGS2016

Assessing the role of climate and resource management on groundwater dependent ecosystem changes in arid environments with the Landsat archive

Groundwater dependent ecosystems (GDEs) rely on near-surface groundwater. These systems are receiving more attention with rising air temperature, prolonged drought, and where groundwater pumping captures natural groundwater discharge for anthropogenic use. Phreatophyte shrublands, meadows, and riparian areas are GDEs that provide critical habitat for many sensitive species, especially in arid and semi-arid environments. While GDEs are vital for ecosystem services and function, their long-term (i.e. ~ 30 years) spatial and temporal variability is poorly understood with respect to local and regional scale climate, groundwater, and rangeland management. In this work, we compute time series of NDVI derived from sensors of the Landsat TM, ETM +, and OLI lineage for assessing GDEs in a variety of land and water management contexts. Changes in vegetation vigor based on climate, groundwater availability, and land management in arid landscapes are detectable with Landsat. However, the effective quantification of these ecosystem changes can be undermined if changes in spectral bandwidths between different Landsat sensors introduce biases in derived vegetation indices, and if climate, and land and water management histories are not well understood. The objective of this work is to 1) use the Landsat 8 under-fly dataset to quantify differences in spectral reflectance and NDVI between Landsat 7 ETM + and Landsat 8 OLI for a range of vegetation communities in arid and semiarid regions of the southwestern United States, and 2) demonstrate the value of 30-year historical vegetation index and climate datasets for assessing GDEs. Specific study areas were chosen to represent a range of GDEs and environmental conditions important for three scenarios: baseline monitoring of vegetation and climate, riparian restoration, and groundwater level changes. Google's Earth Engine cloud computing and environmental monitoring platform is used to rapidly access and analyze the Landsat archive along with downscaled North American Land Data Assimilation System gridded meteorological data, which are used for both atmospheric correction and correlation analysis. Results from the cross-sensor comparison indicate a benefit from the application of a consistent atmospheric correction method, and that NDVI derived from Landsat 7 and 8 are very similar within the study area. Results from continuous Landsat time series analysis clearly illustrate that there are strong correlations between changes in vegetation vigor, precipitation, evaporative demand, depth to groundwater, and riparian restoration. Trends in summer NDVI associated with riparian restoration and groundwater level changes were found to be statistically significant, and interannual summer NDVI was found to be moderately correlated to interannual water-year precipitation for baseline study sites. Results clearly highlight the complementary relationship between water-year PPT, NDVI, and evaporative demand, and are consistent with regional vegetation index and complementary relationship studies. This work is supporting land and water managers for evaluation of GDEs with respect to climate, groundwater, and resource management.

Remote Sensing of Environment↗
USGS2020

The assessment and remediation of mercury contaminated sites: A review of current approaches

Remediation of mercury (Hg) contaminated sites has long relied on traditional approaches, such as removal and containment/capping. Here we review contemporary practices in the assessment and remediation of industrial-scale Hg contaminated sites and discuss recent advances. Significant improvements have been made in site assessment, including the use of XRF to rapidly identify the spatial extent of contamination, Hg stable isotope fractionation to identify sources and transformation processes, and solid-phase characterization (XAFS) to evaluate Hg forms. The understanding of Hg bioavailability for methylation has been improved by methods such as sequential chemical extractions and porewater measurements, including the use of diffuse gradient in thin-film (DGT) samplers. These approaches have shown varying success in identifying bioavailable Hg fractions and further study and field applications are needed. The downstream accumulation of methylmercury (MeHg) in biota is a concern at many contaminated sites. Identifying the variables limiting/controlling MeHg production—such as bioavailable inorganic Hg, organic carbon, and/or terminal electron acceptors (e.g. sulfate, iron) is critical. Mercury can be released from contaminated sites to the air and water, both of which are influenced by meteorological and hydrological conditions. Mercury mobilized from contaminated sites is predominantly bound to particles, highly correlated with total sediment solids (TSS), and elevated during stormflow. Remediation techniques to address Hg contamination can include the removal or containment of Hg contaminated materials, the application of amendments to reduce mobility and bioavailability, landscape/waterbody manipulations to reduce MeHg production, and food web manipulations through stocking or extirpation to reduce MeHg accumulated in desired species. These approaches often rely on knowledge of the Hg forms/speciation at the site, and utilize physical, chemical, thermal and biological methods to achieve remediation goals. Overall, the complexity of Hg cycling allows many different opportunities to reduce/mitigate impacts, which creates flexibility in determining suitable and logistically feasible remedies.

Science of the Total Environment↗
USGS2018

Defining “atmospheric river”: How the Glossary of Meteorology helped resolve a debate

Since the term “atmospheric river” (AR) first appeared in modern scientific literature in the early 1990s, it has generated debate about the meaning of the concept. A common popular definition is something along the lines of a “river in the sky,” albeit as a river of water vapor rather than of liquid. This general concept has come into regular use in the western United States and in some other regions affected by ARs, partly due to its use by media, and due to the intuitive nature of the concept. However, over the last 20 years there have been varying perspectives on the term in the technical community. These perspectives range roughly from considering it duplicative of preexisting concepts, such as the warm conveyor belt (WCB), to arguments that the analogy to terrestrial rivers is inappropriate, to being a primary topic of focused research, applications, and usage by water managers.

Bulletin of the American Meteorological Society↗
USGS2021

OpenET: Filling a critical data gap in water management for the western United States

The lack of consistent, accurate information on evapotranspiration (ET) and consumptive use of water by irrigated agriculture is one of the most important data gaps for water managers in the western United States (U.S.) and other arid agricultural regions globally. The ability to easily access information on ET is central to improving water budgets across the West, advancing the use of data-driven irrigation management strategies, and expanding incentive-driven conservation programs. Recent advances in remote sensing of ET have led to the development of multiple approaches for field-scale ET mapping that have been used for local and regional water resource management applications by U.S. state and federal agencies. The OpenET project is a community-driven effort that is building upon these advances to develop an operational system for generating and distributing ET data at a field scale using an ensemble of six well-established satellite-based approaches for mapping ET. Key objectives of OpenET include: Increasing access to remotely sensed ET data through a web-based data explorer and data services; supporting the use of ET data for a range of water resource management applications; and development of use cases and training resources for agricultural producers and water resource managers. Here we describe the OpenET framework, including the models used in the ensemble, the satellite, meteorological, and ancillary data inputs to the system, and the OpenET data visualization and access tools. We also summarize an extensive intercomparison and accuracy assessment conducted using ground measurements of ET from 139 flux tower sites instrumented with open path eddy covariance systems. Results calculated for 24 cropland sites from Phase I of the intercomparison and accuracy assessment demonstrate strong agreement between the satellite-driven ET models and the flux tower ET data. For the six models that have been evaluated to date (ALEXI/DisALEXI, eeMETRIC, geeSEBAL, PT-JPL, SIMS, and SSEBop) and the ensemble mean, the weighted average mean absolute error (MAE) values across all sites range from 13.6 to 21.6 mm/month at a monthly timestep, and 0.74 to 1.07 mm/day at a daily timestep. At seasonal time scales, for all but one of the models the weighted mean total ET is within ±8% of both the ensemble mean and the weighted mean total ET calculated from the flux tower data. Overall, the ensemble mean performs as well as any individual model across nearly all accuracy statistics for croplands, though some individual models may perform better for specific sites and regions. We conclude with three brief use cases to illustrate current applications and benefits of increased access to ET data, and discuss key lessons learned from the development of OpenET.

western United States↗
USGS2013

A scenario and forecast model for Gulf of Mexico hypoxic area and volume

For almost three decades, the relative size of the hypoxic region on the Louisiana-Texas continental shelf has drawn scientific and policy attention. During that time, both simple and complex models have been used to explore hypoxia dynamics and to provide management guidance relating the size of the hypoxic zone to key drivers. Throughout much of that development, analyses had to accommodate an apparent change in hypoxic sensitivity to loads and often cull observations due to anomalous meteorological conditions. Here, we describe an adaptation of our earlier, simple biophysical model, calibrated to revised hypoxic area estimates and new hypoxic volume estimates through Bayesian estimation. This application eliminates the need to cull observations and provides revised hypoxic extent estimates with uncertainties, corresponding to different nutrient loading reduction scenarios. We compare guidance from this model application, suggesting an approximately 62% nutrient loading reduction is required to reduce Gulf hypoxia to the Action Plan goal of 5,000 km 2 , to that of previous applications. In addition, we describe for the first time, the corresponding response of hypoxic volume. We also analyze model results to test for increasing system sensitivity to hypoxia formation, but find no strong evidence of such change.

Environmental Science & Technology↗
USGS1995

Monthly average polar sea-ice concentration

The data contained in this CD-ROM depict monthly averages of sea-ice concentration in the modern polar oceans. These averages were derived from the Scanning Multichannel Microwave Radiometer (SMMR) and Special Sensor Microwave/Imager (SSM/I) instruments aboard satellites of the U.S. Air Force Defense Meteorological Satellite Program from 1978 through 1992. The data are provided as 8-bit images using the Hierarchical Data Format (HDF) developed by the National Center for Supercomputing Applications.

Data Series↗
USGS2015

Simulated runoff at many stream locations in the Methow River Basin, Washington

A collaborative Bureau of Reclamation-U.S. Geological Survey (USGS) team has been brought together to incorporate a conceptual geomorphic-habitat model with a process-based trophic model to understand the processes important to stream habitat for anadromous fish populations. The Methow River Basin was selected as a test basin for this hybrid geomorphic-habitat/trophic model, and one of the required model inputs is long-term daily runoff at reaches with potential habitat. Leveraging the existence of a watershed model that was constructed for the Methow River Basin by the USGS, the team approached the USGS at the Washington Water Science Center to resurrect the original model and to simulate runoff at many locations in the basin to test the trophic model. Thirteen new flow-routing sites were added to the model, creating a total of 61 sites in the basin where daily runoff was simulated and provided as output. The input file that contains observed meteorological data that drives the watershed model and observed runoff data for comparisons with simulated runoff was extended from water year 2001 to water year 2013 using data from 18 meteorological sites and 12 observed runoff sites. The watershed model included simulation of 16 irrigation diversions that simulated 50-percent water loss through canal seepage. Irrigation was simulated as a constant application of 0.2 inches per day to during the irrigation season, May 1–October 7. Comparisons of the simulated runoff with observed runoff at six selected long-term streamflow-gaging stations showed that the simulated annual runoff was within +15.4 to -9.6 percent of the annual observed runoff. The simulated runoff generally matched the seasonal flow patterns, with bias at some stations indicated by over-simulation of the October–November late autumn season and under-simulation of the snowmelt runoff months of May and June. Sixty-one time series of daily runoff for a 26-year period representative of the long-term runoff pattern, water years 1988–2013, were simulated and provided to the trophic modeling team.

Washington↗
USGS2006

The Short Wave Aerostat-Mounted Imager (SWAMI): A novel platform for acquiring remotely sensed data from a tethered balloon

We describe a new remote sensing system called the Short Wave Aerostat-Mounted Imager (SWAMI). The SWAMI is designed to acquire co-located video imagery and hyperspectral data to study basic remote sensing questions and to link landscape level trace gas fluxes with spatially and temporally appropriate spectral observations. The SWAMI can fly at altitudes up to 2 km above ground level to bridge the spatial gap between radiometric measurements collected near the surface and those acquired by other aircraft or satellites. The SWAMI platform consists of a dual channel hyperspectral spectroradiometer, video camera, GPS, thermal infrared sensor, and several meteorological and control sensors. All SWAMI functions (e.g. data acquisition and sensor pointing) can be controlled from the ground via wireless transmission. Sample data from the sampling platform are presented, along with several potential scientific applications of SWAMI data.

Remote Sensing of Environment↗
USGS2014

Scaling up watershed model parameters: flow and load simulations of the Edisto River Basin, South Carolina, 2007-09

As part of an ongoing effort by the U.S. Geological Survey to expand the understanding of relations among hydrologic, geochemical, and ecological processes that affect fish-tissue mercury concentrations within the Edisto River Basin, analyses and simulations of the hydrology of the Edisto River Basin were made using the topography-based hydrological model (TOPMODEL). A primary focus of the investigation was to assess the potential for scaling up a previous application of TOPMODEL for the McTier Creek watershed, which is a small headwater catchment to the Edisto River Basin. Scaling up was done in a step-wise manner, beginning with applying the calibration parameters, meteorological data, and topographic-wetness-index data from the McTier Creek TOPMODEL to the Edisto River TOPMODEL. Additional changes were made for subsequent simulations, culminating in the best simulation, which included meteorological and topographic wetness index data from the Edisto River Basin and updated calibration parameters for some of the TOPMODEL calibration parameters. The scaling-up process resulted in nine simulations being made. Simulation 7 best matched the streamflows at station 02175000, Edisto River near Givhans, SC, which was the downstream limit for the TOPMODEL setup, and was obtained by adjusting the scaling factor, including streamflow routing, and using NEXRAD precipitation data for the Edisto River Basin. The Nash-Sutcliffe coefficient of model-fit efficiency and Pearson’s correlation coefficient for simulation 7 were 0.78 and 0.89, respectively. Comparison of goodness-of-fit statistics between measured and simulated daily mean streamflow for the McTier Creek and Edisto River models showed that with calibration, the Edisto River TOPMODEL produced slightly better results than the McTier Creek model, despite the substantial difference in the drainage-area size at the outlet locations for the two models (30.7 and 2,725 square miles, respectively). Along with the TOPMODEL hydrologic simulations, a visualization tool (the Edisto River Data Viewer) was developed to help assess trends and influencing variable in the stream ecosystem. Incorporated into the visualization tool were the water-quality load models TOPLOAD, TOPLOAD–H, and LOADEST. Because the focus of this investigation was on scaling up the models from McTier Creek, water-quality concentrations that were previously collected in the McTier Creek Basin were used in the water-quality load models.

South Carolina↗
USGS2014

Scaling up watershed model parameters--Flow and load simulations of the Edisto River Basin

The Edisto River is the longest and largest river system completely contained in South Carolina and is one of the longest free flowing blackwater rivers in the United States. The Edisto River basin also has fish-tissue mercury concentrations that are some of the highest recorded in the United States. As part of an effort by the U.S. Geological Survey to expand the understanding of relations among hydrologic, geochemical, and ecological processes that affect fish-tissue mercury concentrations within the Edisto River basin, analyses and simulations of the hydrology of the Edisto River basin were made with the topography-based hydrological model (TOPMODEL). The potential for scaling up a previous application of TOPMODEL for the McTier Creek watershed, which is a small headwater catchment to the Edisto River basin, was assessed. Scaling up was done in a step-wise process beginning with applying the calibration parameters, meteorological data, and topographic wetness index data from the McTier Creek TOPMODEL to the Edisto River TOPMODEL. Additional changes were made with subsequent simulations culminating in the best simulation, which included meteorological and topographic wetness index data from the Edisto River basin and updated calibration parameters for some of the TOPMODEL calibration parameters. Comparison of goodness-of-fit statistics between measured and simulated daily mean streamflow for the two models showed that with calibration, the Edisto River TOPMODEL produced slightly better results than the McTier Creek model, despite the significant difference in the drainage-area size at the outlet locations for the two models (30.7 and 2,725 square miles, respectively). Along with the TOPMODEL hydrologic simulations, a visualization tool (the Edisto River Data Viewer) was developed to help assess trends and influencing variables in the stream ecosystem. Incorporated into the visualization tool were the water-quality load models TOPLOAD, TOPLOAD-H, and LOADEST. Because the focus of this investigation was on scaling up the models from McTier Creek, water-quality concentrations that were previously collected in the McTier Creek basin were used in the water-quality load models.

South Carolina↗
USGS2010

Global estimates of evapotranspiration and gross primary production based on MODIS and global meteorology data

The simulation of gross primary production (GPP) at various spatial and temporal scales remains a major challenge for quantifying the global carbon cycle. We developed a light use efficiency model, called EC-LUE, driven by only four variables: normalized difference vegetation index (NDVI), photosynthetically active radiation (PAR), air temperature, and the Bowen ratio of sensible to latent heat flux. The EC-LUE model may have the most potential to adequately address the spatial and temporal dynamics of GPP because its parameters (i.e., the potential light use efficiency and optimal plant growth temperature) are invariant across the various land cover types. However, the application of the previous EC-LUE model was hampered by poor prediction of Bowen ratio at the large spatial scale. In this study, we substituted the Bowen ratio with the ratio of evapotranspiration (ET) to net radiation, and revised the RS-PM (Remote Sensing-Penman Monteith) model for quantifying ET. Fifty-four eddy covariance towers, including various ecosystem types, were selected to calibrate and validate the revised RS-PM and EC-LUE models. The revised RS-PM model explained 82% and 68% of the observed variations of ET for all the calibration and validation sites, respectively. Using estimated ET as input, the EC-LUE model performed well in calibration and validation sites, explaining 75% and 61% of the observed GPP variation for calibration and validation sites respectively. Global patterns of ET and GPP at a spatial resolution of 0.5° latitude by 0.6° longitude during the years 2000–2003 were determined using the global MERRA dataset (Modern Era Retrospective-Analysis for Research and Applications) and MODIS (Moderate Resolution Imaging Spectroradiometer). The global estimates of ET and GPP agreed well with the other global models from the literature, with the highest ET and GPP over tropical forests and the lowest values in dry and high latitude areas. However, comparisons with observed GPP at eddy flux towers showed significant underestimation of ET and GPP due to lower net radiation of MERRA dataset. Applying a procedure to correct the systematic errors of global meteorological data would improve global estimates of GPP and ET. The revised RS-PM and EC-LUE models will provide the alternative approaches making it possible to map ET and GPP over large areas because (1) the model parameters are invariant across various land cover types and (2) all driving forces of the models may be derived from remote sensing data or existing climate observation networks.

Remote Sensing of Environment↗
USGS2023

Assessing snowpack stratigraphy accuracy based on different input data: Insights for operations avalanche forecasting

Avalanche forecasters and snow scientists use physically based snow stratigraphy models to fill spatial and temporal gaps in field-based snow profile observations. These models generate stratigraphy predictions using meteorological input from automated weather stations (AWS) or numerical weather prediction (NWP) models. The choice of input data is often determined by data availability or convenience instead of giving full consideration to the most appropriate source for a particular application. For example, while AWS may provide weather observations that better represent a particular site, they have large up-front costs and require specialized personnel to service and maintain. The goal of this study is to quantify the accuracy of snow stratigraphy produced by the SNOWPACK model driven by different input data, with a particular focus on cost-benefit analysis for operational avalanche forecasting. We generate modeled snow profiles at a field site in the Bridger Range of southwestern Montana, USA, using a) observations from an AWS at the field site and b) NWP output from the NOAA High-Resolution Rapid Refresh (HRRR) model. Validation data consist of a season-long time series of 10 manual snow profiles. We use dynamic time-warping (DTW) to quantify the overall and grain-type categorized similarities between modeled and in-situ observed profiles that are collocated in time and in space. Based on the similarity results, we present a cost-benefit analysis that considers the cost of installing and maintaining an AWS alongside the improved representation of snow depth, grain size, and weak layer types.

Montana↗
USGS1969

Satellite imagery of the earth

Photography of the Earth from spacecraft has application to both atmospheric and Earth sciences. Gemini and Apollo photographs have furnished information on sea surface roughness, areas of potential upwelling and oceanic current systems. Regional geologic structures and geomorphologic features are also recorded in orbital photographs. Infrared satellite imagery provides meteorological and hydrological data and is potentially useful for locating fresh water springs along coastal areas, sources of geothermal power and volcanic activity. Ground and airborne surveys are being undertaken to create a basis for the interpretation of data obtained from future satellite systems.

Photogrammetric Engineering↗
USGS1979

The brightness of lights on Earth at night, digitally recorded by DMSP satellite

The U.S. Air Force has operated its Defense Meteorological Satellite Program (DMSP) for nearly a decade, and film images from the system have been openly available since 1973. Films are well suited for the study of weather, and users of such films have derived much useful data. For many potential remote sensing applications, however, a quantitative measurement of the brightness of the imaged light patterns is needed, and it cannot be extracted with adequte accuracy from the films. Such information is contained in the telemetry from the spacecraft and is retained on digital tapes, which store the images for a few days while they await filming. For practical reasons, it has not heretofore been feasible for the Air Force to provide a remote-sensing user with these digital data, and the quantitative brightness information has been lost with the erasure of tapes for re-use. For the purpose of evaluation of tapes as a means for remote sensing, the Air Force recently did provide to the author six examples containing records of nighttime DMSP imagery similar to that which has previously 1 been evaluated by SRI International in a film format. The digital data create many new applications for these images, owing to a combination of several factors, the most important of which are the preservation of photometric information and of full spatial resolution. In this evaluation, stress has been placed upon determination of the broad potential value of the data rather than the full exploitation of any one aspect of it. The effort was guided by an objective to develop handling methods for the vast body of numbers--methods which will be practical for use in a research or engineering environment where budgets are limited, and specialized capabilities and image reproduction equipment has not already been developed. We report the degree of success obtained in this effort, pointing out the relative strengths and the relative limitations, as compared to the sophisticated, weather-oriented data processing which is well suited for the Air Force requirements. Both geometric and photometric calibration methods are evaluated. An image can be considered as a 3-dimensional array, X, Y, Z, in which X and Y are the coordinates of a picture element (pixel) and Z is the brightness at that location. A method of approach to handling these parameters, particularly Y and Z, is developed in a form quite different from that which serves the operational applications. The user of digital data will need the film images which are generated by the Air Force from the same data as is provided on digital tape. In the first stages of analysis, the films provide both a convenient index and a guide to identification of large patterns in the data. Additionally, the infrared (8 to 13 0 film provides a valuable indicator of cloud cover. Two general conclusions are drawn from this study. Firstly, the digital DMSP data have great potential value but their cost, in terms of the interruption of the present operational routine, is quite high. Therefore, if a program is undertaken to provide for the open availability of an archive of digital records, great care must be exercised in selecting only those records which have unusually high value in order that the effort will be cost-effective. Secondly, it is concluded that several aspects of the program, well designed for Air Force operational purposes, are not adapted to earth-sensing needs. This is probably inevitable, since the two applications are largely different and in some ways incompatible. For example, the nighttime visual sensor saturates in the center of major cities and in moderately large fires (such as gas flares). This saturation prevents the analyst from integrating photometric parameters. For weather observation, this inability is unimportant, and acceptance of such saturation makes feasible a decrease in the data rate. Such limitations in the data will probably be overcome only through modifying the existing system or the implementation of a similar system designed specifically to serve earth-sensing needs.

Open-File Report↗
USGS2010

Analysis and simulation of water-level, specific conductance, and total phosphorus dynamics of the Loxahatchee National Wildlife Refuge, Florida, 1995-2006

The Arthur R. Marshall Loxahatchee Wildlife Refuge (Refuge) was established in 1951 through a license agreement between the South Florida Water Management District and the U.S. Fish and Wildlife Service (USFWS) as part of the Migratory Bird Conservation Act. Under the license agreement, the State of Florida owns the land of the Refuge and the USFWS manages the land. Fifty-seven miles of levees and borrow canals surround the Refuge. Water in the canals surrounding the marsh is controlled by inflows and outflows through control structures. The transport of canal water with higher specific conductance and nutrient concentrations to the interior marsh has the potential to alter critical ecosystem functions of the marsh. Data-mining techniques were applied to 12 years (1995-2006) of historical data to systematically synthesize and analyze the dataset to enhance the understanding of the hydrology and water quality of the Refuge. From the analysis, empirical models, including artificial neural network (ANN) models, were developed to answer critical questions related to the relative effects of controlled releases, precipitation, and meteorological forcing on water levels, specific conductance, and phosphorous concentrations of the interior marsh. Data mining is a powerful tool for converting large databases into information to solve complex problems resulting from large numbers of explanatory variables or poorly understood process physics. For the application of the linear regression and ANN models to the Refuge, data-mining methods were applied to maximize the information content in the raw data. Signal processing techniques used in the data analysis and model development included signal decomposition, digital filtering, time derivatives, time delays, and running averages. Inputs to the empirical models included time series, or signals, of inflows and outflows from the control structures, precipitation, and evapotranspiration. For a complex hydrologic system like the Refuge, the statistical accuracy of the models and predictive capability were good. The water-level models have coefficient of determination (R 2 values ranging from 0.90 to 0.98. The R 2 for the specific conductance model is 0.82, and the R2 for the total phosphorus model is 0.51. The accuracy of the models was attributable to the quantity and quality of the available data. To make the models directly available to all stakeholders, an easy-to-use decision support system (DSS) called the Loxahatchee Artificial Neural Network Model (LOXANN) DSS was developed as a spreadsheet application that integrates the historical database, linear regression and ANN models, model controls, streaming graphics, and model output. The LOXANN DSS allows Refuge managers and other users to easily execute the water level, specific conductance, and phosphorous models to evaluate various water-resource management scenarios. The user is able to choose from three options in setting the control-structure flows: as a percentage of historical flow, as a constant flow, or as a user-defined hydrograph. Output from the LOXANN DSS includes tabular time series of predictions of the measured data and predictions of the user-specified conditions. A three-dimensional visualization routine also was developed that displays longitudinal specific conductance conditions. Two scenarios were simulated with the LOXANN DSS. One scenario increased the historical flows at four control structures by 40 percent. The second scenario used a user-defined hydrograph to set the outflow from the Refuge to the weekly average inflow to the Refuge delayed by 2 days. Both scenarios decreased the potential of canal water intruding into the marsh by decreasing the slope of the water level between the canals and the marsh.

Scientific Investigations Report↗
USGS1980

Thermal modeling of flow in the San Diego Aqueduct, California, and its relation to evaporation

The thermal balance of the 26-kilometer long concrete-lined San Diego Aqueduct, a canal in southern California, was studied to determine the coefficients in a Dalton type evaporation formula. Meteorologic and hydraulic variables, as well as water temperature, were monitored continuously for a 1-year period. A thermal model was calibrated by use of data obtained during a 28-day period to determine the coefficients which best described the thermal balance of the canal. The coefficients applicable to the San Diego Aqueduct are similar to those commonly obtained from lake evaporation studies except that a greater evaporation at low windspeeds is indicated. The model was verified by use of data obtained during 113 days which did not include the calibration data. These data verified that the derived wind function realistically represents the canal evaporation. An annual evaporation of 2.08 meters was computed which is about 91 percent of the amount of water evaporated annually from nearby class A evaporation pans. (Kosco-USGS)

Professional Paper↗