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At least 127 records · Page 7Linked to original sources

Augmented normalized difference water index for improved monitoring of surface water

We present a comprehensive critical review of well-established satellite remote sensing water indices and offer a novel, robust Augmented Normalized Difference Water Index (ANDWI). ANDWI employs an expanded set of spectral bands, RGB, NIR, and SWIR 1-2 , to maximize the contrast between water and non-water pixels. Further, we implement a dynamic thresholding method, the Otsu algorithm, to enhance ANDWI's performance. Applied to a variety of environmental conditions, ANDWI with Otsu-thresholding offered the highest overall accuracy (accuracy = 0.98, F1 = 0.98, and Kappa = 0.96) compared to other indices (NDWI, MNDWI, AWEI, WI). We also propose a novel cloud filtering algorithm that substantially increases the number of useable images compared to the conventional cloud-free composites (124% increased observations in the studied area) and resolves inappropriate masking of water bodies and hot sands as clouds by conventional methods. Finally, we develop a Google Earth Engine App to readily delineate 16-day surface water bodies across the globe.

Environmental Modeling and Software↗

Online-coupling of widely-ranged timescales to model coral reef development

The increasing pressure on Earth's ecosystems due to climate change is becoming more and more evident and the impacts of climate change are especially visible on coral reefs. Understanding how climate change interacts with the physical environment of reefs to impact coral growth and reef development is critically important to predicting the persistence of reefs into the future. In this study, a biophysical model was developed including four environmental factors in a feedback loop with the coral's biology: (1) light; (2) hydrodynamics; (3) temperature; and (4) pH. The submodels are online coupled, i.e. regularly exchanging information and feedbacks while the model runs. This ensures computational efficiency despite the widely-ranged timescales. The composed biophysical model provides a significant step forward in understanding the processes that modulate the evolution of coral reefs, as it is the first construction of a model in which the hydrodynamics are included in the feedback loop.

Environmental Modeling and Software↗

A machine learning approach to predicting equilibrium ripple wavelength

Sand ripples are geomorphic features on the seafloor that affect bottom boundary layer dynamics including wave attenuation and sediment transport. We present a new equilibrium ripple predictor using a machine learning approach that outputs a probability distribution of wave-generated equilibrium wavelengths and statistics including an estimate of ripple height, the most probable ripple wavelength, and sediment and flow parameterizations. The Bayesian Optimal Model System (BOMS) is an ensemble machine learning system that combines two machine learning algorithms and two deterministic empirical ripple predictors with a Bayesian meta-learner to produce probabilistic wave-generated equilibrium ripple wavelength estimates in sandy locations. A ten-fold cross validation of BOMS resulted in an adjusted R-squared value of 0.93 and an average root mean square error (RMSE) of 8.0 cm. During both cross validation and testing on three unique field datasets, BOMS provided more accurate wavelength predictions than each individual base model and other common ripple predictors.

Environmental Modeling and Software↗

Generating a reference flow network with improved connectivity to support durable data integration and reproducibility in the coterminous US

This report presents a reference flow network for the conterminous United States that is built from the best available information from the U.S. Geological Survey, the National Oceanic and Atmospheric Administration National Weather Service, and the U.S. Environmental Protection Agency. The work is intended to support durable data integration and reproducibility. Originating from the National Hydrography Dataset Plus (NHDPlus) V2.1, the reference flow network incorporates network connectivity enhancements from federal agency efforts. After incorporating these network improvements, many original NHDPlus attributes were regenerated to enable network navigation and related operations. After introducing the motivation and background for this work, this report describes the attribute generation workflow and data quality checks that were performed in preparation of the dataset. The reference flow network follows the NHDPlus data model and is described using terms defined in the Mainstem and Drainage Basin logical model and WaterML2 Part3: Surface Hydrology Features conceptual model.

Environmental Modelling and Software↗

Leveraging machine learning to automate regression model evaluations for large multi-site water-quality trend studies

Large multi-site trend studies provide an opportunity to evaluate progress of waterbodies towards water-quality goals across broad geographic areas. Such studies often aggregate the results of site-specific models and thus contend with evaluating each model for appropriate fit and statistical assumptions. We explored the use of four traditional machine learning models (logistic regression, linear and quadratic discriminant analysis, and k-nearest neighbors) to perform these checks and estimate probabilities that an analyst would publish or reject a site-specific trend model from a multi-site study. We trained these “model-checking models” (MCMs) using a national study of over 6000 trend models and tested the MCMs using a smaller set of novel trend models. Although the MCMs did not perform well enough to bypass analyst review entirely, we found incorporating an MCM into a larger evaluation workflow can reduce the number of trend models needing an analyst review by more than half.

Environmental Modeling and Software↗

Design and calibration of a nitrate decision support tool for groundwater wells in Wisconsin, USA

This paper describes development of a nitrate decision support tool for groundwater wells (GW-NDST) that combines nitrate leaching and groundwater lag-times to compute well concentrations. The GW-NDST uses output from support models that simulate leached nitrate, groundwater age distributions, and nitrate reduction rates. The support models are linked through convolution to simulate nitrate transport to wells. Spatially distributed parameters were adjusted through calibration to 34,255 nitrate sample targets. Prediction uncertainty is illustrated via Monte Carlo realizations informed during calibration. Over 78% of target concentrations were within the simulated range of results from 450 realizations. An example forecasting scenario illustrates that a range of feasible outcomes exist and should be considered when interpreting forecasts for decision making. Uncertainty in forecasting is unavoidable; the intent of characterizing uncertainty in the GW-NDST is to facilitate decision making by increasing insight into the response of nitrate contamination to physical and chemical processes.

Wisconsin↗

Transfer learning with convolutional neural networks for hydrological streamline delineation

Hydrological streamline delineation is critical for effective environmental management, influencing agriculture sustainability, river dynamics, watershed planning, and more. This study develops a novel approach to combining transfer learning with convolutional neural networks that capitalize on image-based pre-trained models to improve the accuracy and transferability of streamline delineation. We evaluate the performance of eleven image-based pre-trained models and a baseline model using datasets from Rowan County, North Carolina, and Covington River, Virginia in the USA. Our results demonstrate that when models are adapted to a new area, the fine-tuned ImageNet pre-trained model exhibits superior predictive accuracy, markedly higher than the models trained from scratch or those only fine-tuned on the same area. Moreover, the pre-trained model achieves better smoothness and connectivity between classified streamline channels. These findings underline the effectiveness of transfer learning in enhancing the delineation of hydrological streamlines across varied geographies, offering a scalable solution for accurate and efficient environmental modelling.

North Carolina, Virginia↗

Automating physics-based models to estimate thermoelectric-power water use

Thermoelectric (TE) power plants withdraw more water than any other sector of water use in the United States and consume water at rates that can be significant especially in water-stressed regions. Historical TE water-use data have been inconsistent, incomplete, or discrepant, resulting in an increased research focus on improving the accuracy and availability of TE water-use data using modeling approaches. This paper describes and benchmarks new code that was developed to automate and update a physics-based TE water use model that was previously published. Utilizing the automated physics-based model, monthly TE-power water withdrawal and consumption were calculated for a total of 1341 TE power plants for the 2008–2020 historical reanalysis. The updated and automated physics-based thermoelectric-power water-use model provides spatially and temporally relevant TE water-use estimates that are consistent, reproducible, transparent, and can be generated efficiently for water-using, utility-scale TE-power plants across conterminous United States (CONUS).

Environmental Modelling and Software↗

A catalogue of Do's and Don'ts in the modeling of environmental systems

Modeling plays a vital role in understanding and managing complex environmental systems, but its credibility and quality depend heavily on a comprehensive set of defensible model activities and practices, especially when the system of interest is plagued with uncertainties and conflicting stakeholder perspectives. This paper proposes a catalogue of Do's and Don'ts to guide modelers in addressing the many pertinent considerations through the whole modeling cycle. This practical tool provides advice on approaching modeling effectively through adhering to good modeling practice. It emphasizes model choices that align with the model purpose and context, and the justification and documentation of modeling decisions and assumptions. Managing uncertainty is a core consideration. The identification, assessment and reporting of these uncertainties is important across the entire modeling process, which spans problem framing, technical design, implementation and application phases. Such good practices are critical for transparency and reliability of the modeling.

Environmental Modelling and Software↗

Simulation of nitrous oxide and nitric oxide emissions from tropical primary forests in the Costa Rican Atlantic Zone

Nitrous oxide (N 2 O) and nitric oxide (NO) are important atmospheric trace gases participating in the regulation of global climate and environment. Predictive models on the emissions of N 2 O and NO emissions from soil into the atmosphere are required. We modified the CENTURY model (Soil Sci. Soc. Am. J., 51 (1987) 1173) to simulate the emissions of N 2 O and NO from tropical primary forests in the Atlantic Zone of Costa Rica at a monthly time step. Combined fluxes of N 2 O and NO were simulated as a function of gross N mineralization and water-filled pore space (WFPS). The coefficients for partitioning N 2 O from NO were derived from field measurements (Global Biogeochem. Cycles, 8 (1994) 399). The modified CENTURY was calibrated against observations of carbon stocks in various pools of forest ecosystems of the region, and measured WFPS and emission rates of N 2 O and NO from soil to the atmosphere. WFPS is an important factor regulating nutrient cycling and emissions of N2O and NO from soils making the accuracy of the WFPS prediction central to the modeling process. To do this, we modified the hydrologic submodel and developed a new method for the prediction of WFPS at the monthly scale from daily rainfall information. The new method is based on: (1) the relationship between monthly rainfall and the number of rainfall events, and (2) the relative cumulative frequency distribution of ranked daily rainfall events. The method is generic and should be applicable to other areas. Simulated monthly average WFPS was 0.68±0.02 — identical with the field measurement average of 0.68±0.02 from the annual cycle observed by Keller and Reiners (Global Biogeochem. Cycles, 8 (1994) 399). Simulated fluxes of N 2 O and NO were 52.0±9.4 mg-N m −2 month −1 and 6.5±0.7 mg-N m −2 month −1 , respectively, compared with measured averages of 48.2±11.0 mg-N m −2 month −1 and 7.1±1.1 mg-N m −2 month −1 . The simulated N 2 O/NO ratio was 11.2±1.9 compared with the measured value of 10.9±4.7. WFPS is the dominant determinant of the fraction of gross N mineralization that is emitted from the soil as N 2 O and NO. If WFPS were not limiting during part of the year, this fraction would be 4.2%. With some periods of lower WFPS, the realized fraction is 2.2%. Because of the strong relationships between N 2 O and NO emission rates and rainfall and its derivative, WFPS, these moisture variables can be used to scale up nitrogen trace gas fluxes from sites to larger spatial scales.

Environmental Modelling and Software↗

An enhanced cluster analysis program with bootstrap significance testing for ecological community analysis

The biosphere is filled with complex living patterns and important questions about biodiversity and community and ecosystem ecology are concerned with structure and function of multispecies systems that are responsible for those patterns. Cluster analysis identifies discrete groups within multivariate data and is an effective method of coping with these complexities, but often suffers from subjective identification of groups. The bootstrap testing method greatly improves objective significance determination for cluster analysis. The BOOTCLUS program makes cluster analysis that reliably identifies real patterns within a data set more accessible and easier to use than previously available programs. A variety of analysis options and rapid re-analysis provide a means to quickly evaluate several aspects of a data set. Interpretation is influenced by sampling design and a priori designation of samples into replicate groups, and ultimately relies on the researcher's knowledge of the organisms and their environment. However, the BOOTCLUS program provides reliable, objectively determined groupings of multivariate data.

Environmental Modelling and Software↗

3D Visualization of Earthquake Focal Mechanisms Using ArcScene

We created a new tool, 3D Focal Mechanisms (3DFM), for viewing earthquake focal mechanism symbols three dimensionally. This tool operates within the Environmental Systems Research Institute (ESRI®) GIS software ArcScene® 9.x. The program requires as input a GIS point dataset of earthquake locations containing strike, dip, and rake values for a nodal plane of each earthquake. Other information, such as depth and magnitude of the earthquake, may also be included in the dataset. By default for each focal point, 3DFM will create a black and white sphere or “beach ball” that is oriented based on the strike, dip, and rake values. If depth values for each earthquake are included, the focal symbol will also be placed at its appropriate location beneath the Earth's surface. In addition to the default settings, there are several other options in 3DFM that can be adjusted. The appearance of the symbols can be changed by (1) creating rings around the fault planes that are colored based on magnitude, (2) showing only the fault planes instead of a sphere, (3) drawing a flat disc that identifies the primary nodal plane, (4) or by displaying the null, pressure, and tension axes. The size of the symbols can be changed by adjusting their diameter, scaling them based on the magnitude of the earthquake, or scaling them by the estimated size of the rupture patch based on earthquake magnitude. It is also possible to filter the data using any combination of the strike, dip, rake, magnitude, depth, null axis plunge, pressure axis plunge, tension axis plunge, or fault type values of the points. For a large dataset, these filters can be used to create different subsets of symbols. Symbols created by 3DFM are stored in graphics layers that appear in the ArcScene® table of contents. Multiple graphics layers can be created and saved to preserve the output from different symbol options.

Data Series↗

Geologic map of the Chewelah 30' x 60' Quadrangle, Washington and Idaho

This data set maps and describes the geology of the Chewelah 30' X 60' quadrangle, Washington and Idaho. Created using Environmental Systems Research Institute's ARC/INFO software, the data base consists of the following items: (1) a map coverage containing geologic contacts and units, (2) a point coverage containing site-specific geologic structural data, (3) two coverages derived from 1:100,000 Digital Line Graphs (DLG); one of which represents topographic data, and the other, cultural data, (4) two line coverages that contain cross-section lines and unit-label leaders, respectively, and (5) attribute tables for geologic units (polygons), contacts (arcs), and site-specific data (points). In addition, the data set includes the following graphic and text products: (1) A PostScript graphic plot-file containing the geologic map, topography, cultural data, and two cross sections, and on a separate sheet, a Correlation of Map Units (CMU) diagram, an abbreviated Description of Map Units (DMU), modal diagrams for granitic rocks, an index map, a regional geologic and structure map, and a key for point and line symbols; (2) PDF files of the Readme text-file and expanded Description of Map Units (DMU), and (3) this metadata file. The geologic map database contains original U.S. Geological Survey data generated by detailed field observation and by interpretation of aerial photographs. The map was compiled from geologic maps of eight 1:48,000 15' quadrangle blocks, each of which was made by mosaicing and reducing the four constituent 7.5' quadrangles. These 15' quadrangle blocks were mapped chiefly at 1:24,000 scale, but the detail of the mapping was governed by the intention that it was to be compiled at 1:48,000 scale. The compilation at 1:100,000 scale entailed necessary simplification in some areas and combining of some geologic units. Overall, however, despite a greater than two times reduction in scale, most geologic detail found on the 1:48,000 maps is retained on the 1:100,000 map. Geologic contacts across boundaries of the eight constituent quadrangles required minor adjustments, but none significant at the final 1:100,000 scale. The geologic map was compiled on a base-stable cronoflex copy of the Chewelah 30' X 60' topographic base and then scribed. The scribe guide was used to make a 0.007 mil-thick blackline clear-film, which was scanned at 1200 DPI by Optronics Specialty Company, Northridge, California. This image was converted to vector and polygon GIS layers and minimally attributed by Optronics Specialty Company. Minor hand-digitized additions were made at the USGS. Lines, points, and polygons were subsequently edited at the USGS by using standard ARC/INFO commands. Digitizing and editing artifacts significant enough to display at a scale of 1:100,000 were corrected. Within the database, geologic contacts are represented as lines (arcs), geologic units as polygons, and site-specific data as points. Polygon, arc, and point attribute tables (.pat, .aat, and .pat, respectively) uniquely identify each geologic datum.

Miscellaneous Field Studies Map↗

Archive of chirp seismic reflection data collected during USGS cruises 00SCC02 and 00SCC04, Barataria Basin, Louisiana, May 12-31 and June 17-July 2, 2000

This archive consists of two-dimensional marine seismic reflection profile data collected in the Barataria Basin of southern Louisiana. These data were acquired in May, June, and July of 2000 aboard the R/V G.K. Gilbert. Included here are data in a variety of formats including binary, American Standard Code for Information Interchange (ASCII), Hyper-Text Markup Language (HTML), shapefiles, and Graphics Interchange Format (GIF) and Joint Photographic Experts Group (JPEG) images. Binary data are in Society of Exploration Geophysicists (SEG) SEG-Y format and may be downloaded for further processing or display. Reference maps and GIF images of the profiles may be viewed with a web browser. The Geographic Information Systems (GIS) information provided here is compatible with Environmental Systems Research Institute (ESRI) GIS software.

Louisiana↗

Archive of Boomer seismic reflection data: collected during USGS Cruise 96CCT01, nearshore south central South Carolina coast, June 26 - July 1, 1996

This archive consists of marine seismic reflection profile data collected in four survey areas from southeast of Charleston Harbor to the mouth of the North Edisto River of South Carolina. These data were acquired June 26 - July 1, 1996, aboard the R/V G.K. Gilbert. Included here are data in a variety of formats including binary, American Standard Code for Information Interchange (ASCII), Hyper Text Markup Language (HTML), Portable Document Format (PDF), Rich Text Format (RTF), Graphics Interchange Format (GIF) and Joint Photographic Experts Group (JPEG) images, and shapefiles. Binary data are in Society of Exploration Geophysicists (SEG) SEG-Y format and may be downloaded for further processing or display. Reference maps and GIF images of the profiles may be viewed with a web browser. The Geographic Information Systems (GIS) map documents provided were created with Environmental Systems Research Institute (ESRI) GIS software ArcView 3.2 and 8.1.

South Carolina↗

Preliminary geologic map of the Big Bear City 7.5' Quadrangle, San Bernardino County, California

This data set maps and describes the geology of the Big Bear City 7.5' quadrangle, San Bernardino County, California. Created using Environmental Systems Research Institute's ARC/INFO software, the data base consists of the following items: (1) a rock-unit coverage and attribute tables (polygon and arc) containing geologic contacts, units and rock-unit labels as annotation which are also included in a separate annotation coverage, bbc_anno (2) a point coverage containing structural point data and (3) a coverage containing fold axes. In addition, the data set includes the following graphic and text products: (1) A PostScript graphic plot-file containing the geologic map, topography, cultural data, a Correlation of Map Units (CMU) diagram, a Description of Map Units (DMU), an index map, a regional geologic and structure map, and an explanation for point and line symbols; (2) PDF files of the Readme (including the metadata file as an appendix), and a screen graphic of the plot produced by the PostScript plot file. The geologic map describes a geologically complex area on the north side of the San Bernardino Mountains. Bedrock units in the Big Bear City quadrangle are dominated by (1) large Cretaceous granitic bodies ranging in composition from monzogranite to gabbro, (2) metamorphosed sedimentary rocks ranging in age from late Paleozoic to late Proterozoic, and (3) Middle Proterozoic gneiss. These rocks are complexly deformed by normal, reverse, and thrust faults, and in places are tightly folded. The geologic map database contains original U.S. Geological Survey data generated by detailed field observation and by interpretation of aerial photographs. The map data was compiled on base-stable cronoflex copies of the Big Bear City 7.5' topographic map, transferred to a scribe-guide and subsequently digitized. Lines, points, and polygons were edited at the USGS using standard ARC/INFO commands. Digitizing and editing artifacts significant enough to display at a scale of 1:24,000 were corrected. Within the database, geologic contacts are represented as lines (arcs), geologic units as polygons, and site-specific data as points. Polygon, arc, and point attribute tables (.pat, .aat, and .pat, respectively) uniquely identify each geologic datum.

Open-File Report↗

Digital geologic and geophysical data of Bangladesh

This CD-ROM was compiled according to the methodology developed by the U.S. Geological Survey's World Energy Project . The goal of the project was to assess the undiscovered, technically recoverable oil and gas resources of the world and report these results by the year 2000. A worldwide series of geologic maps, published on CD-ROMs, was released by the U.S. Geological Survey's World Energy Project during 1997 - 2000. Specific details of the data sources and map compilation are given in the metadata files on this CD-ROM. These maps were compiled using Environmental Systems Research Institute Inc. (ESRI) ARC/INFO software. Political boundaries and cartographic representations on this map are with permission from ESRI's ArcWorld 1:3M digital coverage: they have no political significance and are displayed as general reference only. Portions of this database covering the coastline and country boundaries contain proprietary property of ESRI. (© 1992 and 1996, Environmental Systems Research Institute Inc. All rights reserved.)

Open-File Report↗

Maps showing geology, oil and gas fields and geological provinces of Africa

The CD-ROM was compiled according to the methodology developed by the U.S. Geological Survey's World Energy Project . The goal of the project was to assess the undiscovered, technically recoverable oil and gas resources of the world and report these results by the year 2000. A worldwide series of geologic maps, published on CD-ROMs, was released by the U.S. Geological Survey's World Energy Project during 1997-2000. Specific details of the data sources and map compilation are given in the metadata files on this CD-ROM. These maps were compiled using Environmental Systems Research Institute Inc. (ESRI) ARC/INFO software. Political boundaries and cartographic representations on this map are shown (with permission) from ESRI's ArcWorld 1:3M digital coverage: they have no political significance and are displayed as general reference only. Portions of this database covering the coastline and country boundaries contain proprietary property of ESRI. (Copyright 1992 and 1996, Environmental Systems Research Institute Inc. All rights reserved.)

Open-File Report↗