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At least 91 records · Page 5Linked to original sources
USGS1965

Quality of surface water in the Sevier Lake basin, Utah

Few data are available on the quality of surface waters in the Sevier Lake basin. Because of the need for information not only on the chemical-quality but also on the other water-quality characteristics of the basin, the U.S. Geological Survey, as part of its cooperative program with the Utah State Engineer, evaluated the available data in 1963. Based on this evaluation, a reconnaissance was designed to obtain some of the needed water-quality information. To extend the applicability of the basic information, the Utah State Engineer, the Utah State Department of Health, the Water Commissioner for the Sevier River, and the Soil Conservation Service and Forest Service of the U.S. Department of Agriculture assisted in the planning and in the selection of sampling sites. This report presents the results of the data-collection phase of the reconnaissance. A companion interpretive report will be prepared later. The data were collected primarily by the U.S. Geological Survey as part of its cooperative programs with the State Engineer of Utah and the Utah Geological and Mineralogical Survey. The work was under the supervision of R. H. Langford, district chemist of the Quality of Water Branch, Water Resources Division, U.S. Geological Survey.

Utah↗
USGS1911

Ground water in Juab, Millard, and Iron Counties, Utah

Location and extent of area - Juab, Millard, and Iron counties lie in western Utah, and, with the exception of a small part of Iron County, are entirely within the Great Basin. (See fig. 1.) They comprise about 13,650 square miles, of which approximately 3,500 belong to Juab, 6,775 to Millard, and 3,375 to Iron County. Beaver County, which lies between Millard and Iron counties, is not discussed in this paper because its water resources have been described by W. T. Lee, of the United States Geological Survey, in Water-Supply Paper 217. Purpose of investigation - The investigation was begun in the summer of 1908, under cooperative agreement between the Director of the United States Geological Survey and Caleb Tanner, State engineer of Utah, the object of the work being to obtain and disseminate information which should lead to a greater utilization of the ground-water supplies. The agricultural development of an arid section, such as this, is primarily dependent on the amount of water available. Large tracts of fertile soil remain idle year after year for lack of water for irrigation, while much water that falls as rain and snow sinks into the ground, saturates the porous materials underlying the valleys and deserts, and eventually reappears at the surface in low alkali flats, where it is dissipated by evaporation without producing useful vegetation. If the water thus lost can be applied to fertile soil it will substantially increase the agricultural yield of the region. An urgent demand for information in regard to ground-water prospects has been created in recent years by the adoption of dry farming methods in localities where water is not readily obtained. The water required for culinary purposes and for supplying the horses and traction engines used in tilling the soil on some of the dry farms is at present hauled long distances. In most of the arid parts of this region watering places of any sort are so scarce that certain sections are accessible for grazing only in the winter when sheep will depend on snow for their water supply. In some of these sections an intelligent search would probably discover ground-water supplies which would increase greatly the value of the range.

Utah↗
USGS1914

Progress report on stream measurement work carried on in cooperation with the United States Geological Survey: Section in Ninth biennial report of the State Engineer to the governor of Utah: 1913-1914

Utah, like other states in the arid region of the United States, points with just pride to her present and future agricultural developments. She proudly boasts, and no doubt justly too, that her fields of green vegetation are inexhaustible and always expanding, and with due vigilance and care on the part of her land holders these fields will bring forth the proper supplies for man for an indefinite period. But, like her neighboring sister states on the east, west, north, and south, she realizes that the precipitation over her lands, as a general rule, is insufficient for the growing and maturing of crops. As a result, her principal lands can only be made to bear crops through the assistance of irrigation. In all irrigation, next to the land itself, the most important factor to be considered is the water supply.

Utah↗
USGS2018

Accuracies achieved in classifying five leading world crop types and their growth stages using optimal Earth Observing-1 Hyperion hyperspectral narrowbands on Google Earth Engine

As the global population increases, we face increasing demand for food and nutrition. Remote sensing can help monitor food availability to assess global food security rapidly and accurately enough to inform decision-making. However, advances in remote sensing technology are still often limited to multispectral broadband sensors. Although these sensors have many applications, they can be limited in studying agricultural crop characteristics such as differentiating crop types and their growth stages with a high degree of accuracy and detail. In contrast, hyperspectral data contain continuous narrowbands that provide data in terms of spectral signatures rather than a few data points along the spectrum, and hence can help advance the study of crop characteristics. To better understand and advance this idea, we conducted a detailed study of five leading world crops (corn, soybean, winter wheat, rice, and cotton) that occupy 75% and 54% of principal crop areas in the United States and the world respectively. The study was conducted in seven agroecological zones of the United States using 99 Earth Observing-1 (EO-1) Hyperion hyperspectral images from 2008–2015 at 30 m resolution. The authors first developed a first-of-its-kind comprehensive Hyperion-derived Hyperspectral Imaging Spectral Library of Agricultural crops (HISA) of these crops in the US based on USDA Cropland Data Layer (CDL) reference data. Principal Component Analysis was used to eliminate redundant bands by using factor loadings to determine which bands most influenced the first few principal components. This resulted in the establishment of 30 optimal hyperspectral narrowbands (OHNBs) for the study of agricultural crops. The rest of the 242 Hyperion HNBs were redundant, uncalibrated, or noisy. Crop types and crop growth stages were classified using linear discriminant analysis (LDA) and support vector machines (SVM) in the Google Earth Engine cloud computing platform using the 30 optimal HNBs (OHNBs). The best overall accuracies were between 75% to 95% in classifying crop types and their growth stages, which were achieved using 15–20 HNBs in the majority of cases. However, in complex cases (e.g., 4 or more crops in a Hyperion image) 25–30 HNBs were required to achieve optimal accuracies. Beyond 25–30 bands, accuracies asymptote. This research makes a significant contribution towards understanding modeling, mapping, and monitoring agricultural crops using data from upcoming hyperspectral satellites, such as NASA’s Surface Biology and Geology mission (formerly HyspIRI mission) and the recently launched HysIS (Indian Hyperspectral Imaging Satellite, 55 bands over 400–950 nm in VNIR and 165 bands over 900–2500 nm in SWIR), and contributions in advancing the building of a novel, first-of-its-kind global hyperspectral imaging spectral-library of agricultural crops (GHISA: www.usgs.gov/WGSC/GHISA).

Remote Sensing↗
USGS2010

Fluvial sediment in the environment: a national challenge

Sediment and sediment-associated constituents can contribute substantially to water-quality impairment. In the past, sediment was viewed mainly as an engineering problem that affected reservoir storage capacity, shipping channel maintenance, and bridge scour, as well as the loss of agricultural soil. Sediment is now recognized as a major cause of aquatic system degradation in many rivers and streams as a result of light attenuation, loss of spawning substrate due to fine-grained sediment infilling, reduction in primary productivity, decreases in biotic diversity, and effects from sediment-associated chemical constituents. Recent advances in sediment measurement, assessment, source-identification, and analytical protocols provide new capabilities to quantify sediment and solid-phase chemical fluxes in aquatic systems. Developing, maintaining, and augmenting current sediment- and water-quality-monitoring networks is essential for determining the health of U.S. waterways and for evaluating the effectiveness of management actions in reducing sediment-related problems. The application of new scientific capabilities that address the adverse effects of sediment and sediment- associated constituents represents a major step in managing the Nation’s water quality. A robust Federal, national-scale eff rt, in collaboration with vested stakeholders, is needed to address these sediment-related water-quality issues across the United States.

Conference Paper↗
USGS2006

Denitrification potential of different land-use types in an agricultural watershed, lower Mississippi valley

Expansion of agricultural land and excessive nitrogen (N) fertilizer use in the Mississippi River watershed has resulted in a three-fold increase in the nitrate load of the river since the early 1950s. One way to reduce this nitrate load is to restore wetlands at suitable locations between croplands and receiving waters to remove run-off nitrate through denitrification. This research investigated denitrification potential (DP) of different land uses and its controlling factors in an agricultural watershed in the lower Mississippi valley (LMV) to help identify sites with high DP for reducing run-off nitrate. Soil samples collected from seven land-use types of an agricultural watershed during spring, summer, fall and winter were incubated in the laboratory for DP determination. Low-elevation clay soils in wetlands exhibited 6.3 and 2.5 times greater DP compared to high-elevation silt loam and low-elevation clay soils in croplands, respectively. DP of vegetated-ditches was 1.3 and 4.2 times that of un-vegetated ditches and cultivated soils, respectively. Soil carbon and nitrogen availability, bulk density, and soil moisture significantly affected DP. These factors were significantly influenced in turn by landscape position and land-use type of the watershed. It is evident from these results that low-elevation, fine-textured soils under natural wetlands are the best locations for mediating nitrate loss from agricultural watersheds in the LMV. Landscape position and land-use types can be used as indices for the assessment/modeling of denitrification potential and identification of sites for restoration for nitrate removal in agricultural watersheds. ?? 2006 Elsevier B.V. All rights reserved.

Ecological Engineering↗
USGS2020

Using NASA Earth observations and Google Earth Engine to map winter cover crop conservation performance in the Chesapeake Bay watershed

Winter cover crops such as barley, rye, and wheat help to improve soil structure by increasing porosity, aggregate stability, and organic matter, while reducing the loss of agricultural nutrients and sediments into waterways. The environmental performance of cover crops is affected by choice of species, planting date, planting method, nutrient inputs, temperature, and precipitation. The Maryland Department of Agriculture (MDA) oversees an agricultural cost-share program that provides farmers with funding to cover costs associated with planting winter cover crops, and the U.S. Geological Survey (USGS) and the U.S. Department of Agriculture-Agricultural Research Service (USDA-ARS) have partnered with the MDA to develop satellite remote sensing techniques for measuring cover crop performance. The MDA has developed the capacity to digitize field boundaries for all fields enrolled in their cover crop programs (>26,000 fields per year) to support a remote sensing performance analysis at a statewide scal,e and has requested assistance with the associated imagery processing from the National Aeronautics and Space Administration (NASA). Using the Google Earth Engine (GEE) cloud computing platform, scripts were developed to process Landsat 5/7/8 and Harmonized Sentinel-2 imagery to measure winter cover crop performance. We calibrated cover crop performance models using linear regression between satellite vegetation indices and USGS / USDA-ARS field sampling data collected on Maryland farms between 2006 and 2012 (1298 samples). Satellite-derived Normalized Difference Vegetation Index (NDVI) values showed significant correlation with the natural logarithm of cover crop biomass ( p ≤0.01, R 2 = 0.56) and with observed percent vegetative ground cover (p ≤0.01, R 2 = 0.68). The GEE scripts were used to composite seasonal maximum NDVI values for each enrolled cover crop field and calculate performance metrics for the winter and spring seasons of three enrollment years (2014–15, 2015–16, and 2017–18) for four Maryland counties. Results from winter 2017–18 demonstrate that rye and barley fields had higher biomass than wheat fields, and that early planting, along with planting methods that increase seed-soil contact, increased performance. The processing capabilities of GEE will support the MDA in scaling up remote sensing performance analysis statewide, providing information to evaluate the environmental outcomes associated with various agronomic management strategies. The tool can be modified for different seasonal cutoffs, utilize new sensors to capture phenology in winter and spring, and scale to larger regions for use in adaptive management of winter cover crops planted for environmental benefit.

Maryland↗
USGS1981

The role of remotely sensed and other spatial data for predictive modeling: the Umatilla, Oregon example

The U. S. Geological Survey's Earth Resources Observations Systems Data Center, in cooperation with the U.S. Army Corps of Engineers, Portland District, developed and tested techniques that used remotely sensed and other spatial data in predictive models to evaluate irrigation agriculture in the Umatilla River Basin of north-central Oregon. Landsat data and 1:24,000-scale aerial photographs were initially used to map he expansion of irrigate from 1973 to 1979 and to identify crops under irrigation in 1979. The crop data were then used with historical water requirement figures and digital topographic and hydrographic data to estimate water and power use for the 1979 irrigation season. The final project task involved production of a composite map of land suitability for irrigation development based on land cover (from Landsat), land-ownership, soil irrigability, slope gradient, and potential energy costs. The methods and data used in the study demonstrated the flexibility of remotely sensed and other spatial data as input for predictive models. When combined, they provided useful answers to complex questions facing resource managers.

Oregon↗
USGS2021

American and Sacramento Rivers, California, erodibility measurements and model

Executive Summary A previous report by the authors described sediment sampling and drilling by the U.S. Geological Survey (USGS) beside the American and Sacramento Rivers near Sacramento, California, in support of a U.S. Army Corps of Engineers project focused on regional flood control. The drilling was performed to define lithology, extract samples for laboratory testing, and perform borehole erosion tests (BETs). The U.S. Department of Agriculture (USDA) performed jet erodibility tests (JETs) near each drilling site, and a team from Texas A&M University performed laboratory tests with an erosion function apparatus (EFA). Collectively, the effort was intended to reveal spatial variations in sediment erodibility and provide data for use in a model to simulate morphological response to a major flood. The data collected by the USGS are available in a public data release. This report, developed in cooperation with the U.S. Army Corps of Engineers, provides comparisons of the three types of measurements of the erodibility of riverbed sediments. The BET is performed in the field and reveals erodibility of sediments below the bed surface. The JET is likewise performed in the field but reveals only erodibility of exposed sediments. The EFA test is done in the laboratory and was performed on soils extracted from different depths beneath the bed surface, in many cases reconstituted for laboratory testing. Tests were performed at nominally similar locations but differed by meters to tens of meters in horizontal locations. The comparison was undertaken to investigate differences among results obtained by the individual measurement approaches and to elucidate pros and cons of each method. The critical shear stress to initiate erosion and the rate of change of erosion rate per unit increase of excess shear stress, sometimes referred to as the erosion coefficient, served as the primary basis for comparison. The three test methods in some cases resulted in order of magnitude differences in estimates of these parameters. Some differences could be attributed to variances in site location or result from testing surface sediment versus a deeper layer, but systematic differences are also evident in the results. The tests performed in the laboratory using the EFA resulted in much lower values of critical shear stress and much higher values of the erosion coefficient compared to the JET tests performed by the USDA team on surface sediments. Critical shear stress was poorly resolved in the BET results because of the limited number of results per site, but the erosion coefficients derived from BET results were systematically lower than those obtained using the EFA. A new, simplified approach is also proposed to estimate the increase in channel cross-sectional area during a large flood, given data describing the initial river cross section, riverbed erodibility parameters, and peak flood discharge and duration. The model runs until the cross section erodes to an equilibrium condition or the flood ends. Output describes the area of the cross section at the end of the simulation and the time required to reach equilibrium if it was reached within the simulated period. The model assumes unique, constant values for both the critical shear stress and the erosion coefficient and represents the fluid mechanics in a simplified way, making it of limited value for quantitative predictions. It does, however, provide an indication of which cross sections are most likely to undergo the greatest change in the design event and can be used to investigate sensitivity of erosion predictions to variability in sediment erodibility measurements.

California↗
USGS2000

Sleepers River, Vermont: a Water, Energy, and Biogeochemical Budgets Program site

The Sleepers River Research Watershed in northeastern Vermont was established by the Agricultural Research Service (ARS) of the U.S. Department of Agriculture in 1959 and is now operated jointly by the U.S. Geological Survey (USGS) and the U.S. Army Cold Regions Research and Engineering Laboratory (CRREL), will collaboration from several other Federal Agencies and Universities. The USGS has contributed to the understanding of hydrological processes and added a major biogeochemical cycling research component in the last 10 years of Sleepers River's 40-year history as a field laboratory. The USGS uses hydrologic measurements and chemical and isotopic tracing techniques to determine how water moves from the hillslope to the stream, and what processes cause chemical changes, such as neutralization of acid rain. Research results provide insights on how pollutants move through ecosystems, and how ecosystems may respond to climatic change.

Vermont↗
USGS1999

Response of the Rio Grande and shallow ground water in the Mesilla Bolson to irrigation, climate stress, and pumping

The El Paso-Ciudad Juarez metropolitan area obtains its water from the Rio Grande and intermontane-basin aquifers. Shallow ground water in this region is in close communication with the surface water system. A major problem with both systems is salinity. Upstream usage of the water in the Rio Grande for irrigation and municipalities has led to concentration of soluble salts to the point where the surface water commonly exceeds drinking water standards. Shallow ground water is recharged by surface water (primarily irrigation canals and agricultural fields) and discharges to surface water (agricultural drains) and deeper ground water.

Environmental & Engineering Geoscience↗
USGS2017

Nominal 30-m cropland extent map of continental Africa by integrating pixel-based and object-based algorithms using Sentinel-2 and Landsat-8 Data on Google Earth Engine

A satellite-derived cropland extent map at high spatial resolution (30-m or better) is a must for food and water security analysis. Precise and accurate global cropland extent maps, indicating cropland and non-cropland areas, are starting points to develop higher-level products such as crop watering methods (irrigated or rainfed), cropping intensities (e.g., single, double, or continuous cropping), crop types, cropland fallows, as well as for assessment of cropland productivity (productivity per unit of land), and crop water productivity (productivity per unit of water). Uncertainties associated with the cropland extent map have cascading effects on all higher-level cropland products. However, precise and accurate cropland extent maps at high spatial resolution over large areas (e.g., continents or the globe) are challenging to produce due to the small-holder dominant agricultural systems like those found in most of Africa and Asia. Cloud-based geospatial computing platforms and multi-date, multi-sensor satellite image inventories on Google Earth Engine offer opportunities for mapping croplands with precision and accuracy over large areas that satisfy the requirements of broad range of applications. Such maps are expected to provide highly significant improvements compared to existing products, which tend to be coarser in resolution, and often fail to capture fragmented small-holder farms especially in regions with high dynamic change within and across years. To overcome these limitations, in this research we present an approach for cropland extent mapping at high spatial resolution (30-m or better) using the 10-day, 10 to 20-m, Sentinel-2 data in combination with 16-day, 30-m, Landsat-8 data on Google Earth Engine (GEE). First, nominal 30-m resolution satellite imagery composites were created from 36,924 scenes of Sentinel-2 and Landsat-8 images for the entire African continent in 2015–2016.

Remote Sensing↗
USGS2000

Use of Argon, Corona, and Landsat imagery to assess 30 years of land resource changes in west-central Senegal

Over the past 35 years, an agricultural area of west-central Senegal has experienced rapid population growth, fast expansion of agricultural lands, a decline in rainfall, and degradation of vegetative and soil resources. Although such changes have not escaped the attention of Senegal's people, its government, and the scientific community the ability to monitor and quantify land resource trends of recent decades has been difficult. Recently available high-resolution satellite photographs from the American Argon and Corona Programs provide coverage of Senegal back to 1963. The photographs make it possible to study and map land resources at the beginning of the Space Age. In this study, we characterize the changes that have occurred in the region from the early 1960s to the mid-1 990s. Early Argon and Corona photographs are used to reconstruct the historical land use and land cover; comparisons are made with assessments from recent Landsat images. Field studies and aerial surveys provide additional insight. The forces of change, driven primarily by population growth and unsustainable agricultural practices, are examined

Photogrammetric Engineering and Remote Sensing↗
USGS2022

Wildlife associates of nine-banded armadillo (Dasypus novemcinctus) burrows in Arkansas

The Nine-banded Armadillo ( Dasypus novemcinctus ) is a widespread burrowing species with an expanding geographic range across the southeastern and midwestern United States. Armadillos dig numerous, large burrows within their home ranges and these burrows are likely used by a diverse suite of wildlife species as has been reported for other burrowing ecosystem engineers such as Gopher Tortoises ( Gopherus polyphemus ), Desert Tortoises ( Gopherus agassizi ), and Black-tailed Prairie Dogs ( Cynomys ludovicianus ). We used motion-triggered game cameras at 35 armadillo burrows in 4 ecoregions of Arkansas and documented 19 species of mammals, 4 species of reptile, 1 species of amphibian, and 40 species of bird interacting with burrows. Bobcat ( Lynx rufus ), Coyote ( Canis latrans ), Eastern Cottontail ( Sylvilagus floridanus ), Gray Fox ( Urocyon cinereoargenteus ), Gray Squirrel ( Sciurus carolinensis ), Northern Raccoon ( Procyon lotor ), Virginia Opossum ( Didelphis virginiana ), and unidentified rodents (mice and rats) were documented using burrows in all four ecoregions. We documented wildlife hunting, seeking shelter, rearing young in, and taking over and modifying armadillo burrows. The rate of use was highest in the Mississippi Alluvial Valley, a landscape dominated by agriculture, where natural refugia may be limited and rodents are abundant. Armadillo burrows are clearly visited and used by numerous wildlife species to fulfill various life stage requirements, and this list will likely expand if more attention is devoted to understanding the role of armadillos burrows. Armadillos are important ecosystem engineers, and their ecological role warrants more investigation and attention as opposed to only being viewed and managed as agricultural and garden pests.

Arkansas↗
USGS2016

Basin scale controls on CO 2 and CH 4 emissions from the Upper Mississippi River

The Upper Mississippi River, engineered for river navigation in the 1930s, includes a series of low-head dams and navigation pools receiving elevated sediment and nutrient loads from the mostly agricultural basin. Using high-resolution, spatially resolved water quality sensor measurements along 1385 river kilometers, we show that primary productivity and organic matter accumulation affect river carbon dioxide and methane emissions to the atmosphere. Phytoplankton drive CO 2 to near or below atmospheric equilibrium during the growing season, while anaerobic carbon oxidation supports a large proportion of the CO 2 and CH 4 production. Reductions of suspended sediment load, absent of dramatic reductions in nutrients, will likely further reduce net CO 2 emissions from the river. Large river pools, like Lake Pepin, which removes the majority of upstream sediments, and large agricultural tributaries downstream that deliver significant quantities of sediments and nutrients, are likely to persist as major geographical drivers of greenhouse gas emissions.

Upper Mississippi River↗
USGS2002

Land use and flow regime effects on phosphorus chemical dynamics in the fluvial sediment of the Winooski River, Vermont

In the last century, fourfold increase in phosphorus (P) loadings to Lake Champlain, Vermont (VT), USA, have led to nuisance levels of algal growth occurring more often. To better understand the transport, storage, and cycling of P within the lake's catchment, we examined the chemistry, bioavailability and processes controlling sediment P release to waters of the Winooski River, VT, the largest tributary to Lake Champlain. Iron-oxide strip P (algal-bioavailable P) of the river sediments adjacent to agricultural land (3.6 mg kg-1) was greater (P < 0.05) than adjacent to forested land (2.4 mg kg-1). When compared among flow regimes, impoundment (731 mg kg-1) and reservoir sediments (803 mg kg-1) had greater total P concentrations than river sediment (462 mg kg-1). This was attributed to more fines (< 63 ??m) in impoundments and reservoirs (64%) than in river sediments (33%), which also decreased the ability of impoundment sediments to release P to solution and thereby be a sink for P. Although land use and flow regime influenced whether Winooski River sediments acted as a sink or source of P to Lake Champlain, long-term remedial strategies for the catchment should continue to focus on decreasing P losses in agricultural and urban runoff. ?? 2002 Elsevier Science B.V. All rights reserved.

Ecological Engineering↗