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At least 901 records · Page 50Linked to original sources
USGS2005

Inventory of ground-water resources in the Kabul Basin, Afghanistan

In 2004, the U.S. Geological Survey began working with engineers at the Afghanistan Geological Survey to provide hydrologic training and equipment and to apply these tools to build an inventory of water wells in the Kabul Basin of Afghanistan. An inventory of 148 wells now includes information on well location, depth, and access. Water-level and water-quality measurements have been made at most of these wells. A water-level elevation map has been constructed, and general directions of ground-water flow have been defined. Ground-water flow in the Kabul Basin is primarily through saturated alluvium and other basin-fill sediments. The water-table surface generally mirrors topography, and ground water generally flows in the directions of surface-water discharge. The quality of ground water in the Kabul Basin varies widely. In some areas, ground-water quality is excellent, with low concentrations of dissolved solids and no problematic constituents. In other areas, however, high concentrations of dissolved solids and the presence of some constituents at concentrations deemed harmful to humans and crops render untreated ground water marginal or unsuitable for public supply and/or agricultural use. Of particular concern are elevated concentrations of nitrate, boron, and dissolved solids, and an indication of fecal pollution in some parts of the basin. As Afghanistan emerges from years of conflict, as institutional capacities rejuvenate and grow, and as the need for wise water-management decisions continues, adequate data and a fuller understanding of the ground-water resource in the Kabul Basin will be imperative. The work described in this report represents only a modest beginning in what will be a long-term data-collection and interpretive effort.

Scientific Investigations Report↗
USGS2007

Long-Term Ground-Water Levels and Transmissivity in the Blackstone River Basin, Northern Rhode Island

Ground water provides about 7.7 million gallons per day, or 28 percent of total water use in the Rhode Island part of the Blackstone River Basin. Primary aquifers in the basin are stratified glacial deposits, composed mostly of sand and gravel along valley bottoms. The ground-water and surface-water system in the Blackstone River Basin is under stress due to population growth, out-of-basin water transfers, industrialization, and changing land-use patterns. Streamflow periodically drops below the Aquatic Base Flow standard, and ground-water withdrawals add to stress on aquatic habitat during low-flow periods. Existing hydrogeologic data were reviewed to examine historical water-level trends and to generate contour maps of water-table altitudes and transmissivity of the sand and gravel aquifer in the Blackstone River Basin in Rhode Island. On the basis of data from four long-term observation wells, water levels appear to have risen slightly in the study area during the past 55 years. Analysis of available data indicates that increased rainfall during the same period is a likely contributor to the water-level rise. Spatial patterns of transmissivity are shown over larger areas and have been refined on the basis of more detailed data coverage as compared to previous mapping studies.

Scientific Investigations Report↗
USGS2007

Flood of June 22-24, 2006, in North-Central Ohio, With Emphasis on the Cuyahoga River Near Independence

Heavy rains caused severe flooding on June 22-24, 2006, and damaged approximately 4,580 homes and 48 businesses in Cuyahoga County. Damage estimates in Cuyahoga County for the two days of flooding exceed $47 million; statewide damage estimates exceed $150 million. Six counties (Cuyahoga, Erie, Huron, Lucas, Sandusky, and Stark) in northeast Ohio were declared Federal disaster areas. One death, in Lorain County, was attributed to the flooding. The peak streamflow of 25,400 cubic feet per second and corresponding peak gage height of 23.29 feet were the highest recorded at the U.S. Geological Survey (USGS) streamflow-gaging station Cuyahoga River at Independence (04208000) since the gaging station began operation in 1922, exceeding the previous peak streamflow of 24,800 cubic feet per second that occurred on January 22, 1959. An indirect calculation of the peak streamflow was made by use of a step-backwater model because all roads leading to the gaging station were inundated during the flood and field crews could not reach the station to make a direct measurement. Because of a statistically significant and persistent positive trend in the annual-peak-streamflow time series for the Cuyahoga River at Independence, a method was developed and applied to detrend the annual-peak-streamflow time series prior to the traditional log-Pearson Type III flood-frequency analysis. Based on this analysis, the recurrence interval of the computed peak streamflow was estimated to be slightly less than 100 years. Peak-gage-height data, peak-streamflow data, and recurrence-interval estimates for the June 22-24, 2006, flood are tabulated for the Cuyahoga River at Independence and 10 other USGS gaging stations in north-central Ohio. Because flooding along the Cuyahoga River near Independence and Valley View was particularly severe, a study was done to document the peak water-surface profile during the flood from approximately 2 miles downstream from the USGS streamflow-gaging station at Independence to approximately 2 miles upstream from the gaging station. High-water marks were identified and flagged in the field. Third-order-accuracy surveys were used to determine elevations of the high-water marks, and the data were tabulated and plotted.

Scientific Investigations Report↗
USGS2011

Summary of the Georgia Agricultural Water Conservation and Metering Program and evaluation of methods used to collect and analyze irrigation data in the middle and lower Chattahoochee and Flint River basins, 2004-2010

Since receiving jurisdiction from the State Legislature in June 2003 to implement the Georgia Agricultural Water Conservation and Metering Program, the Georgia Soil and Water Conservation Commission (Commission) by year-end 2010 installed more than 10,000 annually read water meters and nearly 200 daily reporting, satellite-transmitted, telemetry sites on irrigation systems located primarily in southern Georgia. More than 3,000 annually reported meters and 50 telemetry sites were installed during 2010 alone. The Commission monitored rates and volumes of agricultural irrigation supplied by groundwater, surface-water, and well-to-pond sources to inform water managers on the patterns and amounts of such water use and to determine effective and efficient resource utilization. Summary analyses of 4 complete years of irrigation data collected from annually read water meters in the middle and lower Chattahoochee and Flint River basins during 2007-2010 indicated that groundwater-supplied fields received slightly more irrigation depth per acre than surface-water-supplied fields. Year 2007 yielded the largest disparity between irrigation depth supplied by groundwater and surface-water sources as farmers responded to severe-to-exceptional drought conditions with increased irrigation. Groundwater sources (wells and well-to-pond systems) outnumbered surface-water sources by a factor of five; each groundwater source applied a third more irrigation volume than surface water; and, total irrigation volume from groundwater exceeded that of surface water by a factor of 6.7. Metered irrigation volume indicated a pattern of low-to-high water use from northwest to southeast that could point to relations between agricultural water use, water-resource potential and availability, soil type, and crop patterns. Normalizing metered irrigation-volume data by factoring out irrigated acres allowed irrigation water use to be expressed as an irrigation depth and nearly eliminated the disparity between volumes of applied irrigation derived from groundwater and surface water. Analysis of per-acre irrigation depths provided a commonality for comparing irrigation practices across the entire range of field sizes in southern Georgia and indicated underreporting of irrigated acres for some systems. Well-to-pond systems supplied irrigation at depths similar to groundwater and can be combined with groundwater irrigation data for subsequent analyses. Average irrigation depths during 2010 indicated an increase from average irrigation depths during 2008 and 2009, most likely the result of relatively dry conditions during 2010 compared to conditions in 2008 and 2009. Geostatistical models facilitated estimation of irrigation water use for unmetered systems and demonstrated usefulness in redesigning the telemetry network. Geospatial analysis evaluated the ability of the telemetry network to represent annually reported water-meter data and presented an objective, unbiased method for revising the network.

Georgia↗
USGS2020

A system design for implementing advanced feature descriptions for a map knowledge base

A prototype system to explore Linked Data that semantically integrates geospatial data in various formats from different publication sources with data from The National Map of the U.S. Geological Survey is presented. The focus is on accessing advanced feature descriptions for data from The National Map with data coreferenced from other sources. The prototype uses Geoserver to access The National Map data, which are converted to Resource Description Framework triples using Karma and stored in the Marmotta triplestore. Marmotta uses a Postgres relational database as a backend for the project and queries to the Marmotta triplestore are converted to structured query language and executed by Postgres. Triples retrieved are linked with same_as relationships to external data sources. The links to these sources provide additional attributes and relationships of the data from The National Map. Visualization of the results is provided using Leaflet and workflows for all parts of the system are defined. A use case for the system is provided to access structures and names information from The National Map for the Washington, D.C., area and link these to Geonames data, with visualization of the graphical and tabular results.

Scientific Investigations Report↗
USGS2020

Evaluation of legacy and emerging organic chemicals using passive sampling devices on the North Branch Au Sable River near Lovells, Michigan, June 2018

The North Branch Au Sable River, located in the northern lower peninsula of Michigan near Lovells, Michigan, has historically been known for its brook trout ( Salvelinus fontinalis ) and its status as a blue ribbon trout stream; however, within the past few decades, there has been a decline in fish population. The objectives of this study were to assess if concentrations of organic chemicals were present in quantities in the North Branch Au Sable River that may potentially harm aquatic species and to establish current baseline concentrations of organic chemicals against which future data can be compared. Passive sampling technology was used to collect information on the concentration, occurrence, transport, and fate of organic chemicals; these samplers absorb dissolved organic chemicals in the river over several weeks, as the timing and intensity of pesticide applications and the frequency of storm events and irrigation can cause fluctuations in organic chemical loading to surface waters. The chemical classes investigated as part of this study included pesticides (both legacy [organochlorine] and current use), polychlorinated biphenyls, polybrominated diphenyl ethers (PBDEs), and polycyclic aromatic hydrocarbons (PAHs). Passive samplers, including semipermeable membrane devices and polar organic chemical integrative samplers, were deployed at four locations along the North Branch Au Sable River, near Lovells, Mich., in June 2018 for a total of 28 days. Several organic chemicals were detected in the North Branch Au Sable River at low concentrations. Organic chemicals were detected at every sampling location on the North Branch Au Sable River; however, not all chemicals were detected at every location. The highest number of organic chemicals were detected at the most downstream sampling site (North Branch Au Sable River at Kellogg's Bridge), and the lowest number of organic chemicals were detected at the next site upstream (North Branch Au Sable River at Twin Bridge Road). The organic contaminants most frequently detected at all sampling locations include the legacy pesticides pentachloroanisole, trans -chlordane, p,p'-dichlorodiphenyldichloroethylene, and p,p'-dichlorodiphenyltrichloroethane; the PBDE PBDE-28; and the PAHs 2-methylphenanthrene and perylene. Organic chemical concentrations detected on the North Branch Au Sable River were below almost all water-quality benchmarks included in this report. However, low concentrations of organic chemicals may still pose a risk to aquatic organisms and throughout the trophic hierarchy because of low-dose additive and synergistic mixture effects, transgenerational effects, and a lack of established water-quality benchmarks for many organic chemicals. This report provides data on the current (2018) state of the North Branch Au Sable River and provided a baseline of organic contaminant data against which future data on the North Branch Au Sable River can be evaluated.

Michigan↗
USGS2021

Documentation of methods and inventory of irrigation information collected for the 2015 U.S. Geological Survey estimated use of water in the United States

The U.S. Geological Survey (USGS) National Water-Use Science Project strives to report water-use estimates using the best available information for the period of the estimates. The information available on water used for irrigation activities varies from State to State and in some areas from county to county within a State, which results in many information sources and methods being used to estimate water withdrawals and consumption for the Nation. The variety of estimation methods makes it difficult to compare information across States and makes it difficult to understand how different methods or data sources bias irrigation water-use estimates and trends over time. The sources of information and methods used by USGS Water Science Centers to estimate irrigation water use (the number of irrigated acres by irrigation system type, withdrawal values by water source type, and consumed-water values) for 2015 are compiled and described herein to assist with interpreting the water-use estimates. State-level summaries of information sources and methods are compiled in appendix 1, and a dataset of calendar-year, county-level estimates of actual evapotranspiration for the conterminous United States and Hawaii is provided in an associated USGS data release.

Scientific Investigations Report↗
USGS2023

Surrogate regression models estimating nitrate concentrations at six springs in Gooding County, south-central Idaho, 2018–22

Populations of endangered Banbury Springs limpet ( Idaholanx fresti ) and threatened Bliss Rapids snail ( Taylorconcha serpenticola ) are declining in springs north of the Snake River along the southern Gooding County boundary, in south-central Idaho. One hypothesis for the decline is that increased macrophyte growth, associated with elevated nitrate concentrations in the springs, is decreasing aquatic habitat for the limpet and snail populations. In support of U.S. Fish and Wildlife Service efforts to understand the population declines, the U.S. Geological Survey developed surrogate regression models to estimate nitrate concentrations at six springs influenced by upgradient agriculture, which results in an increase and decrease each year of streamflow, specific conductance, and nitrate concentrations. The surrogate regression models use continuous specific conductance data and streamflow data (available at two springs from existing U.S. Geological Survey streamgages). The spring surrogate regression models showed that specific conductance can be an effective surrogate for nitrate in springs affected by agriculture and that the model results improved when streamflow data were included. Four of the six springs had surrogate regression models (using specific conductance and day of the year as explanatory variables) that performed well based on model summary statistics, and these models improved further with the inclusion of streamflow as an explanatory variable. The surrogate regression models at four springs had coefficient of determination (R 2 ) values ranging from 0.79 to 0.94. The root mean squared error of the four models ranged from 0.07 to 0.11 milligrams per liter. Two of the six springs were not well modeled, with adjusted R 2 values of 0.15 and 0.80. The surrogate regression models for these two springs also did not meet the required assumption of linearity between explanatory and response variables for linear regression. The surrogate regression models show that specific conductance can be an effective surrogate for nitrate in springs affected by agriculture and that models are improved where streamflow data are included. These surrogates improve understanding of nitrate concentration variability in the springs.

Idaho↗
USGS2024

Novel data in recreation monitoring—Summary proceedings from interagency workshops in 2019 and 2023

Two interagency workshops were held in 2019 and 2023 in Fort Collins, Colorado, to discuss the use of novel data in recreation monitoring. During the workshops, the phrase “novel data in recreation monitoring” was primarily used to refer to data from social media, mobile device applications, and other online secondary sources. The goals of these workshops were to share information across agencies and researchers on the state of the science and applications for using novel data and to collectively discuss best practices for using novel data for understanding recreation on public lands and waters. Presentations during the workshops focused on use-cases, current applications, and the current state of research (as of the time of the workshops) for using novel data in recreation monitoring. Group discussions during the workshops focused on the strengths and limitations of novel data sources, potential approaches for integrating new and emerging data sources and methods with traditional approaches, and research and management needs. This report provides the proceedings of the 2019 and 2023 interagency workshops on novel data in recreation monitoring.

Scientific Investigations Report↗
USGS2026

Comparison of two precipitation gage networks in Cook County, Illinois

The Cook County Precipitation Network is a set of 25 precipitation gages established within Cook County, Illinois, on approximately a 5- to 7-mile square grid and used by the U.S. Army Corps of Engineers to help account for diversions of water from Lake Michigan to the State of Illinois. The transition from the precipitation gage network operated by the Illinois State Water Survey to the precipitation gage network operated by the U.S. Geological Survey (USGS) was compared for periods of overlapping data. This transition took place from May through September during the 2019 water year. The USGS was able to establish replacement precipitation gages at 17 of the 25 sites by the conclusion of the overlapping operational period. The double-mass curve method was used to compare the two networks by creating a graph of the cumulated data collected by the Illinois State Water Survey and the comparable data collected by the USGS. Breaks in the double-mass curve method are caused by a change in the relation between variables. The eight sites that were installed following the overlapping period have a gap in the recorded data; however, the slope of the line for each of the eight sites is nearly equivalent to the previous data. In general, the cumulated precipitation data from the two networks were similar. Three sites had greater than 8-percent difference in their cumulative data ratios, located at Cicero, Ping Tom Park at Chicago, and South Shore, Ill.

Illinois↗
USGS2008

Remote-controlled pan, tilt, zoom cameras at Kilauea and Mauna Loa Volcanoes, Hawai'i

Lists of important volcano-monitoring disciplines usually include seismology, geodesy, and gas geochemistry. Visual monitoring - the essence of volcanology - is usually not mentioned. Yet, observations of the outward appearance of a volcano provide data that is equally as important as that provided by the other disciplines. The eye was almost certainly the first volcano monitoring-tool used by early man. Early volcanology was mostly descriptive and was based on careful visual observations of volcanoes. There is still no substitute for the eye of an experienced volcanologist. Today, scientific instruments replace or augment our senses as monitoring tools because instruments are faster and more sensitive, work tirelessly day and night, keep better records, operate in hazardous environments, do not generate lawsuits when damaged or destroyed, and in most cases are cheaper. Furthermore, instruments are capable of detecting phenomena that are outside the reach of our senses. The human eye is now augmented by the camera. Sequences of timed images provide a record of visual phenomena that occur on and above the surface of volcanoes. Photographic monitoring is a fundamental monitoring tool; image sequences can often provide the basis for interpreting other data streams. Monitoring data are most useful when they are generated and are available for analysis in real-time or near real-time. This report describes the current (as of 2006) system for real-time photograph acquisition and transmission from remote sites on Kilauea and Mauna Loa volcanoes to the U.S. Geological Survey Hawaiian Volcano Observatory (HVO). It also describes how the photographs are archived and analyzed. In addition to providing system documentation for HVO, we hope that the report will prove useful as a practical guide to the construction of a high-bandwidth network for the telemetry of real-time data from remote locations.

Hawai'i↗
USGS2017

Spatial variability of harmful algal blooms in Milford Lake, Kansas, July and August 2015

Cyanobacterial harmful algal blooms (CyanoHABs) tend to be spatially variable vertically in the water column and horizontally across the lake surface because of in-lake and weather-driven processes and can vary by orders of magnitude in concentration across relatively short distances (meters or less). Extreme spatial variability in cyanobacteria and associated compounds poses unique challenges to collecting representative samples for scientific study and public-health protection. The objective of this study was to assess the spatial variability of cyanobacteria and microcystin in Milford Lake, Kansas, using data collected on July 27 and August 31, 2015. Spatially dense near-surface data were collected by the U.S. Geological Survey, nearshore data were collected by the Kansas Department of Health and Environment, and open-water data were collected by U.S. Army Corps of Engineers. CyanoHABs are known to be spatially variable, but that variability is rarely quantified. A better understanding of the spatial variability of cyanobacteria and microcystin will inform sampling and management strategies for Milford Lake and for other lakes with CyanoHAB issues throughout the Nation. The CyanoHABs in Milford Lake during July and August 2015 displayed the extreme spatial variability characteristic of cyanobacterial blooms. The phytoplankton community was almost exclusively cyanobacteria (greater than 90 percent) during July and August. Cyanobacteria (measured directly by cell counts and indirectly by regression-estimated chlorophyll) and microcystin (measured directly by enzyme-linked immunosorbent assay [ELISA] and indirectly by regression estimates) concentrations varied by orders of magnitude throughout the lake. During July and August 2015, cyanobacteria and microcystin concentrations decreased in the downlake (towards the outlet) direction. Nearshore and open-water surface grabs were collected and analyzed for microcystin as part of this study. Samples were collected in the uplake (Zone C), midlake (Zone B), and downlake (Zone A) parts of the lake. Overall, no consistent pattern was indicated as to which sample location (nearshore or open water) had the highest microcystin concentrations. In July, the maximum microcystin concentration observed in each zone was detected at a nearshore site, and in August, maximum microcystin concentrations in each zone were detected at an open-water site. The Kansas Department of Health and Environment uses two guidance levels (a watch and a warning level) to issue recreational public-health advisories for CyanoHABs in Kansas lakes. The levels are based on concentrations of microcystin and numbers of cyanobacteria. In July and August, discrete water-quality samples were predominantly indicative of warning status in Zone C, watch status in Zone B, and no advisories in Zone A. Regression-estimated microcystin concentrations, which provided more thorough coverage of Milford Lake ( n =683–720) than discrete samples ( n =21–24), generally indicated the same overall pattern. Regardless of the individual agencies sampling approach, the overall public-health advisory status of each zone in Milford Lake was similar according to the Kansas Department of Health and Environment guidance levels.

Kansas↗
USGS2025

Leveraging artificial intelligence and machine learning to advance Chesapeake Bay research and management: A review of status, challenges, and opportunities

The Chesapeake Bay and its watershed (hereafter “Chesapeake Bay region”) have been the focus of extensive restoration efforts for several decades. These restoration efforts are guided by the Chesapeake Bay Watershed Agreement (Chesapeake Executive Council 2014) which outlines 10 goals and 31 measurable outcomes. The Chesapeake Bay is globally recognized as a model for coastal restoration due to long-term investments in monitoring, modeling, implementation and research by the Chesapeake Bay Program (CBP) partnership. These monitoring network spans tidal and non-tidal regions and provides data across multiple scales. Artificial intelligence (AI), particularly machine-learning (ML) and deep learning (DL), has emerged as a powerful tool for analyzing large, complex datasets. These techniques have gained widespread adoption across various disciplines, including ecology, hydrology, and environmental science. In the Bay context, AI/ML is increasingly being used to explore drivers of environmental change, analyze system dynamics, and predict conditions in areas with limited monitoring. The CBP partnership, particularly its Scientific and Technical Advisory Committee (STAC), has increasingly recognized the growing role of AI/ML in watershed and estuarine management. Recent Chesapeake Community Research Symposium sessions and initiatives such as the Chesapeake Global Collaboratory highlight increasing regional momentum to apply big data and AI/ML for environmental solutions. Together, these developments underscore the timely need to explore how AI/ML can help advance Chesapeake Bay restoration and management. This STAC workshop, titled “Leveraging Artificial Intelligence and Machine learning to Advance Chesapeake Bay Research and Management: A review of status, challenges, and opportunities,” was held from February 24-25, 2025, in Edgewater, Maryland to bring together over 50 federal, state, and academic scientists and partners to synthesize the current state of AI/ML applications and identify research gaps in Chesapeake Bay research and management. The workshop focused on three main objectives: 1. Summarize recent AI/ML applications and lessons learned in both tidal and nontidal areas of the Chesapeake Bay region. 2. Identify challenges and gaps in applying AI/ML approaches to Chesapeake Bay data. Such challenges and gaps may include data limitations, harmonization issues, ineffective communication of AI/ML insights, and a lack of coordination among research and management institutions. 3. Develop recommendations and identify opportunities for leveraging AI/ML to address issues across the Chesapeake Bay region. Key areas of focus may include generating new information to support watershed management, delivering AI/MLgenerated insights to managers in a clear and actionable way, and fostering greater collaboration among stakeholders within the CBP Partnership. Workshop participants engaged in science presentations and breakout sessions to develop recommendations for advancing the integration of AI/ML techniques into research and management across the Chesapeake Bay region. By synthesizing current applications, identifying challenges, and exploring new opportunities, the workshop has provided valuable insights and recommendations for better leveraging AI/ML approaches to support the success of Bay restoration efforts. Together, these recommendations provide a roadmap for enhancing data-driven, science-based decision making aligned with the goals and outcomes of the Chesapeake Bay Watershed Agreement.

Delaware, Maryland, Virginia↗
USGS1994

The Clementine mission to the Moon: Scientific overview

In the course of 71 days in lunar orbit, from 19 February to 3 May 1994, the Clementine spacecraft acquired just under two million digital images of the moon at visible and infrared wavelengths. These data are enabling the global mapping of the rock types of the lunar crust and the first detailed investigation of the geology of the lunar polar regions and the lunar far side. In addition, laser-ranging measurements provided the first view of the global topographic figure of the moon. The topography of many ancient impact basins has been measured, and a global map of the thickness of the lunar crust has been derived from the topography and gravity.

Science↗
USGS1996

Communicating scientific findings to the general public

The Human Induced Land Transformation project (HILT), part of the U.S. Geological Survey Global Change Research Program, has generated considerable public interest during the first two phases of the project: the data assembly and visualization phase carried out for the San Francisco Bay area; and the model building and calibration phase. The third phase, now underway for the Washington/Baltimore region, is a large scale test of the model's portability to another urban area. The modeling community has been kept informed of progress and findings of the HILT project through conventional academic outlets such as conference and journal publications as well as through more popular outlets such as newspaper, television, and a World Wide Web site. The program, sample data and documentation of the model will be available for downloading to those with an Internet connection. While recognizing that not all research has the same degree of public appeal as this project, additional effort was invested to establish contacts, publicize, and distribute the historical visualizations and model predictions generated by this work in the media, publishing, and in education. In this paper, we will cover the lessons learned in publicizing HILT, the techniques used and the criteria evolved for successful involvement of the general public in the modeling of land cover transitions.

Conference Paper↗
USGS2025

Improving hydroacoustic methods for monitoring suspended-sand flux and grain size in sediment-laden rivers

Suspended-sand concentration and grain-size data in rivers provide valuable information on the catchment's dynamics for scientists and river managers. Producing continuous measurements of suspended-sand concentrations remains a scientific challenge due to their high spatial and temporal variability. Traditional methods such as sediment-rating curves may be highly uncertain, and optical turbidity is insensitive to coarse particles when there are many fine particles. Surrogate hydroacoustic methods aim to improve sand concentration measurements. These single- or dual-frequency acoustic methods use acoustic attenuation and/or backscatter to estimate fine-sediment (i.e., silt and clay) and/or sand concentration and possibly grain size. New methods have recently been developed and applied in rivers exhibiting a wide range of sediment conditions in North America but not independently tested elsewhere by other researchers. In this article, we apply, adapt and evaluate hydroacoustic methods to continuously estimate suspended-sand concentration and grain size in an Alpine river with high suspended-sediment concentrations. From the example of the River Isère at Grenoble Campus, France, we show that the hydroacoustic methods adapted to local conditions may yield valuable sand concentration estimates consistent with traditional measurements. Compared with prior knowledge, limited additional information on the grain size can be obtained due to high uncertainties. Hydroacoustic concentration estimates are more sensitive to real changes in concentration at the event scale than traditional rating-curve methods that relate concentration to discharge only. These findings open the perspective for facilitated sand concentration monitoring at a higher temporal resolution with decreased field work.

Grenoble Campus↗
USGS2006

An integrated chronostratigraphic data system for the twenty-first century

Research in stratigraphy is increasingly multidisciplinary and conducted by diverse research teams whose members can be widely separated. This developing distributed-research process, facilitated by the availability of the Internet, promises tremendous future benefits to researchers. However, its full potential is hindered by the absence of a development strategy for the necessary infrastructure. At a National Science Foundation workshop convened in November 2001, thirty quantitative stratigraphers and database specialists from both academia and industry met to discuss how best to integrate their respective chronostratigraphic databases. The main goal was to develop a strategy that would allow efficient distribution and integration of existing data relevant to the study of geologic time. Discussions concentrated on three major themes: database standards and compatibility, strategies and tools for information retrieval and analysis of all types of global and regional stratigraphic data, and future directions for database integration and centralization of currently distributed depositories. The result was a recommendation to establish an integrated chronostratigraphic database, to be called Chronos, which would facilitate greater efficiency in stratigraphic studies (http://www.chronos.org/) . The Chronos system will both provide greater ease of data gathering and allow for multidisciplinary synergies, functions of fundamental importance in a variety of research, including time scale construction, paleoenvironmental analysis, paleoclimatology and paleoceanography. Beyond scientific research, Chronos will also provide educational and societal benefits by providing an accessible source of information of general interest (e.g., mass extinctions) and concern (e.g., climatic change). The National Science Foundation has currently funded a three-year program for implementing Chronos.. ?? 2006 Geological Society of America. All rights reserved.

Special Paper of the Geological Society of America↗
USGS2011

Classification tree models for predicting distributions of michigan stream fish from landscape variables

Traditionally, fish habitat requirements have been described from local-scale environmental variables. However, recent studies have shown that studying landscape-scale processes improves our understanding of what drives species assemblages and distribution patterns across the landscape. Our goal was to learn more about constraints on the distribution of Michigan stream fish by examining landscape-scale habitat variables. We used classification trees and landscape-scale habitat variables to create and validate presence-absence models and relative abundance models for Michigan stream fishes. We developed 93 presence-absence models that on average were 72% correct in making predictions for an independent data set, and we developed 46 relative abundance models that were 76% correct in making predictions for independent data. The models were used to create statewide predictive distribution and abundance maps that have the potential to be used for a variety of conservation and scientific purposes. ?? Copyright by the American Fisheries Society 2008.

Transactions of the American Fisheries Society↗