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USGS1987

Phytoplankton productivity in relation to light intensity: A simple equation

A simple exponential equation is used to describe photosynthetic rate as a function of light intensity for a variety of unicellular algae and higher plants where photosynthesis is proportional to (1-e −β1 ). The parameter β ( =I k −1 "> =I k −1 ) is derived by a simultaneous curve-fitting method, where I is incident quantum-flux density. The exponential equation is tested against a wide range of data and is found to adequately describe P vs. I curves. The errors associated with photosynthetic parameters are calculated. A simplified statistical model (Poisson) of photon capture provides a biophysical basis for the equation and for its ability to fit a range of light intensities. The exponential equation provides a non-subjective simultaneous curve fitting estimate for photosynthetic efficiency ( a ) which is less ambiguous than subjective methods: subjective methods assume that a linear region of the P vs. I curve is readily identifiable. Photosynthetic parameters β and a are used widely in aquatic studies to define photosynthesis at low quantum flux. These parameters are particularly important in estuarine environments where high suspended-material concentrations and high diffuse-light extinction coefficients are commonly encountered.

Estuarine, Coastal and Shelf Science↗

USGS2012

Advances in the simulation and automated measurement of well-sorted granular material: 1. Simulation

1. In this, the first of a pair of papers which address the simulation and automated measurement of well-sorted natural granular material, a method is presented for simulation of two-phase (solid, void) assemblages of discrete non-cohesive particles. The purpose is to have a flexible, yet computationally and theoretically simple, suite of tools with well constrained and well known statistical properties, in order to simulate realistic granular material as a discrete element model with realistic size and shape distributions, for a variety of purposes. The stochastic modeling framework is based on three-dimensional tessellations with variable degrees of order in particle-packing arrangement. Examples of sediments with a variety of particle size distributions and spatial variability in grain size are presented. The relationship between particle shape and porosity conforms to published data. The immediate application is testing new algorithms for automated measurements of particle properties (mean and standard deviation of particle sizes, and apparent porosity) from images of natural sediment, as detailed in the second of this pair of papers. The model could also prove useful for simulating specific depositional structures found in natural sediments, the result of physical alterations to packing and grain fabric, using discrete particle flow models. While the principal focus here is on naturally occurring sediment and sedimentary rock, the methods presented might also be useful for simulations of similar granular or cellular material encountered in engineering, industrial and life sciences.

Journal of Geophysical Research F: Earth Surface↗

USGS2024

Leveraging natural capital accounting to support businesses with nature-related risk assessments and disclosures

Nature loss threatens businesses, the global economy and financial stability. Understanding and addressing these risks for business will require credible measurement approaches and data. This paper explores how natural capital accounting (NCA) can support business data and information needs related to nature, including disclosures aligned with the Taskforce on Nature-related Financial Disclosures recommendations. As businesses seek to measure, manage and disclose their nature-related risks and opportunities, they will need well-organized, consistent and high-quality information regarding their dependencies and impacts on nature, which few businesses currently collect or track in-house. NCA may be useful for these purposes but has not been widely used or applied by businesses. National NCA guided by the U.N. System of Environmental-Economic Accounting may provide: (i) a useful framework for businesses in conceptualizing, organizing and managing nature-related data and statistics; and (ii) data and information that can directly support business disclosures, corporate NCA and other business applications. This paper explores these opportunities as well as synergies between national and corporate natural capital accounts. In addition, the paper discusses key barriers to advancing the wider use and benefits of NCA for business, including: awareness of NCA, data access, business capabilities related to NCA, spatial and temporal scales of data, audit and assurance considerations, potential risks, and costs and incentives.

Philosophical Transactions of the Royal Society B:↗

USGS2001

A geostatistical approach to predicting sulfur content in the Pittsburgh coal bed

The US Geological Survey (USGS) is completing a national assessment of coal resources in the five top coal-producing regions in the US. Point-located data provide measurements on coal thickness and sulfur content. The sample data and their geologic interpretation represent the most regionally complete and up-to-date assessment of what is known about top-producing US coal beds. The sample data are analyzed using a combination of geologic and Geographic Information System (GIS) models to estimate tonnages and qualities of the coal beds. Traditionally, GIS practitioners use contouring to represent geographical patterns of "similar" data values. The tonnage and grade of coal resources are then assessed by using the contour lines as references for interpolation. An assessment taken to this point is only indicative of resource quantity and quality. Data users may benefit from a statistical approach that would allow them to better understand the uncertainty and limitations of the sample data. To develop a quantitative approach, geostatistics were applied to the data on coal sulfur content from samples taken in the Pittsburgh coal bed (located in the eastern US, in the southwestern part of the state of Pennsylvania, and in adjoining areas in the states of Ohio and West Virginia). Geostatistical methods that account for regional and local trends were applied to blocks 2.7 mi (4.3 km) on a side. The data and geostatistics support conclusions concerning the average sulfur content and its degree of reliability at regional- and economic-block scale over the large, contiguous part of the Pittsburgh outcrop, but not to a mine scale. To validate the method, a comparison was made with the sulfur contents in sample data taken from 53 coal mines located in the study area. The comparison showed a high degree of similarity between the sulfur content in the mine samples and the sulfur content represented by the geostatistically derived contours. Published by Elsevier Science B.V.

International Journal of Coal Geology↗

USGS2025

Characterizing pyrethroid and fipronil concentrations in biosolids

Pesticides are prevalent in wastewater, yet few studies have measured pesticides in biosolids and aqueous media from samples collected concurrently. Seventeen California wastewater treatment plants (WWTPs) were sampled in May 2020. Biosolids samples were analyzed for 27 analytes, and paired aqueous samples (influent and effluent) were analyzed for 23 analytes. Analytes included fipronil and its transformation products (fiproles), pyrethroids, novaluron, and several other pesticides with down-the-drain transport potential. Of the 27 compounds analyzed in biosolids samples, 16 were detected in at least one sample, and 10 had a detection frequency (DF) of at least 25 %. Fipronil sulfone, fipronil sulfide, and fipronil were the most frequently detected fiproles (DF = 100 %, 94 %, and 67 %, respectively); permethrin was the most frequently detected pyrethroid (DF = 100 %), followed by bifenthrin (DF = 94 %), cyhalothrin (DF = 89 %), and etofenprox (DF = 78 %). To elucidate fipronil transformation pathways within the treatment system, data from the three sample types were compared; findings were generally consistent with transformation pathways reported previously (e.g., some fiproles were rarely detected in influent or biosolids, but frequently detected in effluent, indicating their formation during the treatment process). No correlations were found between WWTP characteristics and pesticide concentrations in biosolids. The fraction of organic carbon ( f OC ) of each biosolids sample was measured, and a statistically significant negative correlation was observed between f OC and some fiproles, but not fipronil; possible explanations are discussed. Additional analysis for two major agricultural pesticides (bifenthrin and permethrin) indicated that estimated mass loads of these pesticides in biosolids applied to land as a soil amendment are minimal (approximately 2 to 3 orders of magnitude lower) compared to inputs from agricultural applications. This study provides insight on the magnitude of pesticides entering the environment via land-applied biosolids; existing regulations surrounding agricultural pesticide applications are expected to also be protective of the relatively low inputs from biosolids.

Science of the Total Environment↗

USGS2017

Extracting accurate and precise topography from LROC narrow angle camera stereo observations

The Lunar Reconnaissance Orbiter Camera (LROC) includes two identical Narrow Angle Cameras (NAC) that each provide 0.5 to 2.0 m scale images of the lunar surface. Although not designed as a stereo system, LROC can acquire NAC stereo observations over two or more orbits using at least one off-nadir slew. Digital terrain models (DTMs) are generated from sets of stereo images and registered to profiles from the Lunar Orbiter Laser Altimeter (LOLA) to improve absolute accuracy. With current processing methods, DTMs have absolute accuracies better than the uncertainties of the LOLA profiles and relative vertical and horizontal precisions less than the pixel scale of the DTMs (2–5 m). We computed slope statistics from 81 highland and 31 mare DTMs across a range of baselines. For a baseline of 15 m the highland mean slope parameters are: median = 9.1°, mean = 11.0°, standard deviation = 7.0°. For the mare the mean slope parameters are: median = 3.5°, mean = 4.9°, standard deviation = 4.5°. The slope values for the highland terrain are steeper than previously reported, likely due to a bias in targeting of the NAC DTMs toward higher relief features in the highland terrain. Overlapping DTMs of single stereo sets were also combined to form larger area DTM mosaics that enable detailed characterization of large geomorphic features. From one DTM mosaic we mapped a large viscous flow related to the Orientale basin ejecta and estimated its thickness and volume to exceed 300 m and 500 km 3 , respectively. Despite its ∼3.8 billion year age the flow still exhibits unconfined margin slopes above 30°, in some cases exceeding the angle of repose, consistent with deposition of material rich in impact melt. We show that the NAC stereo pairs and derived DTMs represent an invaluable tool for science and exploration purposes. At this date about 2% of the lunar surface is imaged in high-resolution stereo, and continued acquisition of stereo observations will serve to strengthen our knowledge of the Moon and geologic processes that occur across all of the terrestrial planets.

Icarus↗

USGS2025

Streamflow regime characterization in the changing boreal ecosystem: Wildfire impacts from stream-to-regional scales

The boreal ecosystem has experienced significant changes over recent decades as wildfires become more frequent, intense, and severe. As streams are highly prevalent and ecologically relevant, understanding interactions among wildfire and hydrologic patterns is important for effective aquatic ecosystem management. This study used a Bayesian mixture model to classify streamflow regimes from modeled streamflow data for 32,730 stream reaches (totaling 295,880 km) across the Yukon and Kuskokwim basins and the Northwestern Boreal Ecosystem in Alaska, USA, and Yukon Territory, Canada. We assessed time since burn and calculated the total length of stream (km) within burn perimeters for each streamflow class from 1985 to 2015. Additionally, we used field observations (2018–2022) to compare streamflow regimes in four burned and four unburned headwater streams (drainage basins ≤150 km 2 ) in interior Alaska. Modeled stream reaches were grouped into twenty-two classes and reduced to eleven metaclasses based on similarities in streamflow statistics. These metaclasses formed two broad groups: 1) large rivers with lower variability and strong seasonal signals, and 2) mid- to small-sized tributaries with high variability, frequent high flow events, and weaker seasonal signals. The stream length burned analysis indicated an average increase of 47 km per year with first- and second-order streams experiencing more frequent fire. Empirical streamflow metrics from headwater stream gages revealed additional differences in streamflow patterns between burned and unburned streams. This streamflow classification establishes a baseline for understanding boreal stream responses to wildfire, detecting climate-induced regime shifts, and facilitating management and conservation of important boreal aquatic species.

Alaska↗

USGS2017

Expanded target-chemical analysis reveals extensive mixed-organic-contaminant exposure in USA streams

Surface water from 38 streams nationwide was assessed using 14 target-organic methods (719 compounds). Designed-bioactive anthropogenic contaminants (biocides, pharmaceuticals) comprised 57% of 406 organics detected at least once. The 10 most-frequently detected anthropogenic-organics included eight pesticides (desulfinylfipronil, AMPA, chlorpyrifos, dieldrin, metolachlor, atrazine, CIAT, glyphosate) and two pharmaceuticals (caffeine, metformin) with detection frequencies ranging 66–84% of all sites. Detected contaminant concentrations varied from less than 1 ng L –1 to greater than 10 μg L –1 , with 77 and 278 having median detected concentrations greater than 100 ng L –1 and 10 ng L –1 , respectively. Cumulative detections and concentrations ranged 4–161 compounds (median 70) and 8.5–102 847 ng L –1 , respectively, and correlated significantly with wastewater discharge, watershed development, and toxic release inventory metrics. Log 10 concentrations of widely monitored HHCB, triclosan, and carbamazepine explained 71–82% of the variability in the total number of compounds detected (linear regression; p -values: < 0.001–0.012), providing a statistical inference tool for unmonitored contaminants. Due to multiple modes of action, high bioactivity, biorecalcitrance, and direct environment application (pesticides), designed-bioactive organics (median 41 per site at μg L –1 cumulative concentrations) in developed watersheds present aquatic health concerns, given their acknowledged potential for sublethal effects to sensitive species and lifecycle stages at low ng L –1 .

Environmental Science & Technology↗

USGS2011

Macondo-1 well oil in sediment and tarballs from the northern Gulf of Mexico shoreline

From April 20 through July 15, 2010, an estimated 4.4 million barrels (1 barrel = 42 gallons [~700,000 cu m]) of crude oil spilled into the northern Gulf of Mexico (nGOM) from the ruptured British Petroleum (BP) Macondo-1 (M-1) well after the explosion of the drilling platform Deepwater Horizon. In addition, ~1.84 million gallons (~7,000 cu m) of hydrocarbon-based Corexit dispersants were applied to the oil both on and below the sea surface (Operational Science Advisory Team, 2010). An estimate of the total extent of the surface oil slick, derived from wind, ocean currents, aerial photography, and satellite imagery, was 68,000 square miles (~180,000 sq km; Amos and Norse, 2010). Spilled oil from this event impacted sensitive habitat along the shores of the nGOM. In response to this environmental catastrophe, the U.S. Geological Survey (USGS) collected coastal sediment and tarball samples along the shores of the nGOM from Texas to Florida before and after oil made landfall. These sites included priority areas of the nGOM at highest risk for oil contamination. These areas included coastal wetlands, shorelines, and barrier islands that could suffer severe environmental damage if a significant amount of oil came ashore. Samples were collected before oil reached land from 69 sites; 49 were revisited to collect samples after oil landfall. This poster focuses on the samples from locations that were sampled on both occasions. The USGS samples and one M-1 well-oil sample provided by BP were analyzed for a suite of diagnostic geochemical biomarkers. Aided by multivariate statistical analysis, the M-1 well oil was not detected in the samples collected before landfall but have been identified in sediment and tarballs collected from Louisiana, Alabama, Mississippi, and Florida after landfall. None of the sediment hydrocarbon extracts from Texas correlated with the M-1 well oil. Oil-impacted sediment is confined to the shoreline adjacent to the cumulative oil slick of the Deepwater Horizon oil spill and no impact was observed outside of this area. Incorporation of the analytical data in geographical information systems (GIS) offers querying capabilities and visualizations such as those demonstrated here.

Open-File Report↗

USGS2014

Factors affecting temporal variability of arsenic in groundwater used for drinking water supply in the United States

The occurrence of arsenic in groundwater is a recognized environmental hazard with worldwide importance and much effort has been focused on surveying and predicting where arsenic occurs. Temporal variability is one aspect of this environmental hazard that has until recently received less attention than other aspects. For this study, we analyzed 1245 wells with two samples per well. We suggest that temporal variability, often reported as affecting very few wells, is perhaps a larger issue than it appears and has been masked by datasets with large numbers of non-detect data. Although there was only a slight difference in arsenic concentration variability among samples from public and private wells (p = 0.0452), the range of variability was larger for public than for private wells. Further, we relate the variability we see to geochemical factors—primarily variability in redox—but also variability in pH and major-ion chemistry. We also show that in New England there is a weak but statistically significant indication that seasonality may have an effect on concentrations, whereby concentrations in the first two quarters of the year (January–June) are significantly lower than in the second two quarters (July–December) (p < 0.0001). In the Central Valley of California, though not statistically significant (p = 0.4169), arsenic concentration is lower in the first quarter of the year but increases in subsequent quarters. In both regions, these changes appear to follow groundwater levels. It is possible that this difference in arsenic concentrations is related to groundwater level changes, pumping stresses, evapotranspiration effects, or perhaps mixing of more oxidizing, lower pH recharge water in wetter months. Focusing on the understanding the geochemical conditions in aquifers where arsenic concentrations are concerns and causes of geochemical changes in the groundwater environment may lead to a better understanding of where and by how much arsenic will vary over time.

Science of the Total Environment↗

USGS2025

Regenerable membrane sensors for ultrasensitive nanoplastic quantification enabled by a data-driven Raman spectral processing algorithm

The detection of nanoplastics (NPs) in complex natural water systems is hindered by matrix interferences and limitations in current analytical techniques. This study presents Pre_seg, a Raman spectral processing algorithm integrated with regenerable anodic aluminum oxide (AAO) membrane sensors, for ultrasensitive, rapid, and quantitative NP detection at the single-particle level. The AAO membranes function as both filtration substrates and Raman sensors, reducing sample loss and contamination. Pre_seg incorporates statistically determined thresholds for signal-to-noise ratios (SNRs) and full width at half maximums (fwhms) across segmented spectral ranges, effectively minimizing noise and enhancing accuracy and sensitivity of NP detection. Pre_seg achieved 93.5% prediction accuracy of NPs and ≥90.4% rejection accuracy for non-NP entries. Mixed NPs were quantified at the lowest concentration of 0.5 μg L –1 . The robustness of Pre_seg was validated in eutrophic and oligotrophic lake matrices following oxidation digestion pretreatment to mitigate organic interferences. Furthermore, the AAO membrane sensors demonstrated stability through multiple regeneration and reuse cycles. This innovative approach advances NP detection by enabling scalable, customizable, and environmentally relevant monitoring.

Environmental Science and Technology↗

USGS2026

Decadal trends and occurrence of geogenic constituents and mixtures in groundwater across the continental United States

Worldwide, about 50% of the population is served by groundwater-sourced drinking water. Numerous groundwater quality assessments have found that geogenic constituents are among the most common contaminants in drinking-water aquifers. Documenting changing groundwater quality is a crucial aspect of water availability assessments. We assess trends and occurrence of geogenic constituent concentrations in groundwater across the continental United States using 3 decades of data from the U.S. Geological Survey’s National Water Quality Network. Thousands of groundwater wells were grouped into agricultural, urban, or domestic supply network types. Although most networks and constituents had no statistically significant change in concentration, many had increasing concentration trends, elevated concentrations, or both. Lithium, sodium, radium, sulfate, and uranium had increasing trends in more than 10% of the study networks. Urban and domestic well networks had increasing lithium and sodium trends more often than agricultural networks. Manganese most commonly increased in domestic well networks; uranium more commonly increased in agricultural and urban networks. Elevated concentration mixtures were widespread, and mixture complexities appeared to increase over time. Our results indicate that more than 2.3 million domestic-well users may be affected by elevated concentrations of one or more geogenic constituents.

continental United States↗

USGS2020

2,200-Year tree-ring and lake-sediment based snowpack reconstruction for the northern Rocky Mountains highlights the historic magnitude of recent snow drought

In recent decades, Rocky Mountain accumulated snowpack levels have experienced rapid declines, yet long-term records of snowpack prior to the installation of snowpack observation stations in the early and mid 20th century are limited. To date, a small number of tree-ring based reconstructions of April 1 Snow Water Equivalent (SWE) in the northern Rocky Mountains have extended modern records of snowpack variability to ∼1200 C.E. Carbonate isotope lake sediment records, provide an opportunity to further extend tree-ring based reconstructions through the Holocene, providing a millennial-scale temporal record that allows for an evaluation of multi-scale drivers of snowpack variability, from internal climate dynamics to orbital-scale forcings. Here we present a ∼2200 year preliminary reconstruction of northern Rockies snowpack based on δ 18 O measurements of sediment carbonates collected from Foy Lake, Montana. We explore the statistical calibration of lake sediment δ 18 O to an annually resolved snowpack reconstruction from tree rings, and develop an approach to assess and quantify potential sources of error in this reconstruction approach. The sediment-based snowpack reconstruction shows strong low-frequency variability in snowpack over the last two millennia with few snow droughts approaching the magnitude of recent snowpack declines. Given the growing availability of high-resolution, carbonate-rich lake sediment records, such reconstructions could help improve our understanding of how snowpack conditions varied under previous climatic events (mid-Holocene climate optimum ca. 9−6 ka), providing critical insights for anticipating future snowpack conditions.

Alberta, British Columbia, Idaho, Montana, Nevada,↗

USGS2015

East versus West: organic contaminant differences in brown pelican ( Pelecanus occidentalis ) eggs from South Carolina, USA and the Gulf of California, Mexico

Brown pelicans ( Pelecanus occidentalis ) were listed as endangered in the United States in 1970, largely due to reproductive failure and mortality caused by organochlorine contaminants, such as DDT. The southeast population, P.o. carolinensis , was delisted in 1985, while the west coast population, P.o. californicus , was not delisted until 2009. As fish-eating coastal seabirds, brown pelicans may serve as a biomonitors. Organic contaminants were examined in brown pelican eggs collected from the Gulf of California in 2004 and South Carolina in 2005 using gas chromatography/mass spectrometry (GC/MS). Contaminants were compared using all individual data as well as statistically pooled samples to provide similar sample sizes with little difference in results. Principal components analysis separated the Gulf of California brown pelican eggs from the South Carolina eggs based on contaminant patterns. The South Carolina population had significantly ( P < 0.05) higher levels of polychlorinated biphenyls (PCBs), chlordanes, dieldrin and mirex, while the Gulf of California eggs had higher levels of dichlorodiphenyltrichloroethanes (DDTs) and hexachlorocyclohexanes (HCHs). With the exception of dieldrin and brominated diphenyl ether (BDE) 47, this pattern was observed for mussel and oyster tissues from these regions, indicating the need for further study into the differences between east and west coast brown pelican populations and ecosystem contamination patterns.

South Carolina↗

USGS2018

Increased scientific rigor will improve reliability of research and effectiveness of management

Rigorous science that produces reliable knowledge is critical to wildlife management because it increases accurate understanding of the natural world and informs management decisions effectively. Application of a rigorous scientific method based on hypothesis testing minimizes unreliable knowledge produced by research. To evaluate the prevalence of scientific rigor in wildlife research, we examined 24 issues of the Journal of Wildlife Management from August 2013 through July 2016. We found 43.9% of studies did not state or imply a priori hypotheses, which are necessary to produce reliable knowledge. We posit that this is due, at least in part, to a lack of common understanding of what rigorous science entails, how it produces more reliable knowledge than other forms of interpreting observations, and how research should be designed to maximize inferential strength and usefulness of application. Current primary literature does not provide succinct explanations of the logic behind a rigorous scientific method or readily applicable guidance for employing it, particularly in wildlife biology; we therefore synthesized an overview of the history, philosophy, and logic that define scientific rigor for biological studies. A rigorous scientific method includes 1) generating a research question from theory and prior observations, 2) developing hypotheses (i.e., plausible biological answers to the question), 3) formulating predictions (i.e., facts that must be true if the hypothesis is true), 4) designing and implementing research to collect data potentially consistent with predictions, 5) evaluating whether predictions are consistent with collected data, and 6) drawing inferences based on the evaluation. Explicitly testing a priori hypotheses reduces overall uncertainty by reducing the number of plausible biological explanations to only those that are logically well supported. Such research also draws inferences that are robust to idiosyncratic observations and unavoidable human biases. Offering only post hoc interpretations of statistical patterns (i.e., a posteriori hypotheses) adds to uncertainty because it increases the number of plausible biological explanations without determining which have the greatest support. Further, post hoc interpretations are strongly subject to human biases. Testing hypotheses maximizes the credibility of research findings, makes the strongest contributions to theory and management, and improves reproducibility of research. Management decisions based on rigorous research are most likely to result in effective conservation of wildlife resources.

Journal of Wildlife Management↗

USGS2007

Consistency of L4 TM absolute calibration with respect to the L5 TM sensor based on near-simultaneous image acquisition

The Landsat archive provides more than 35 years of uninterrupted multispectral remotely sensed data of Earth observations. Since 1972, Landsat missions have carried different types of sensors, from the Return Beam Vidicon (RBV) camera to the Enhanced Thematic Mapper Plus (ETM+). However, the Thematic Mapper (TM) sensors on Landsat 4 (L4) and Landsat 5 (L5), launched in 1982 and 1984 respectively, are the backbone of an extensive archive. Effective April 2, 2007, the radiometric calibration of L5 TM data processed and distributed by the U.S. Geological Survey (USGS) Center for Earth Resources Observation and Science (EROS) was updated to use an improved lifetime gain model, based on the instrument's detector response to pseudo-invariant desert site data and cross-calibration with the L7 ETM+. However, no modifications were ever made to the radiometric calibration procedure of the Landsat 4 (L4) TM data. The L4 TM radiometric calibration procedure has continued to use the Internal Calibrator (IC) based calibration algorithms and the post calibration dynamic ranges, as previously defined. To evaluate the "current" absolute accuracy of these two sensors, image pairs from the L5 TM and L4 TM sensors were compared. The number of coincident image pairs in the USGS EROS archive is limited, so the scene selection for the cross-calibration studies proved to be a challenge. Additionally, because of the lack of near-simultaneous images available over well-characterized and traditionally used calibration sites, alternate sites that have high reflectance, large dynamic range, high spatial uniformity, high sun elevation, and minimal cloud cover were investigated. The alternate sites were identified in Yuma, Iraq, Egypt, Libya, and Algeria. The cross-calibration approach involved comparing image statistics derived from large common areas observed eight days apart by the two sensors. This paper summarizes the average percent differences in reflectance estimates obtained between the two sensors. The work presented in this paper is a first step in understanding the current performance of L4 TM absolute calibration and potentially serves as a platform to revise and improve the radiometric calibration procedures implemented for the processing of L4 TM data.

Conference Paper↗

USGS2008

Decadal-scale changes of nitrate in ground water of the United States, 1988-2004

This study evaluated decadal-scale changes of nitrate concentrations in groundwater samples collected by the USGS National Water-Quality Assessment Program from 495 wells in 24 well networks across the USA in predominantly agricultural areas. Each well network was sampled once during 1988-1995 and resampled once during 2000-2004. Statistical tests of decadal-scale changes of nitrate concentrations in water from all 495 wells combined indicate there is a significant increase in nitrate concentrations in the data set as a whole. Eight out of the 24 well networks, or about 33%, had significant changes of nitrate concentrations. Of the eight well networks with significant decadal-scale changes of nitrate, all except one, the Willamette Valley of Oregon, had increasing nitrate concentrations. Median nitrate concentrations of three of those eight well networks increased above the USEPA maximum contaminant level of 10 mg L-1. Nitrate in water from wells with reduced conditions had significantly smaller decadal-scale changes in nitrate concentrations than oxidized and mixed waters. A subset of wells had data on ground water recharge date; nitrate concentrations increased in response to the increase of N fertilizer use since about 1950. Determining ground water recharge dates is an important component of a ground water trends investigation because recharge dates provide a link between changes in ground water quality and changes in land-use practices. Copyright ?? 2008 by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America. All rights reserved.

Journal of Environmental Quality↗

USGS1985

Study and interpretation of the chemical characteristics of natural water

The chemical composition of natural water is derived from many different sources of solutes, including gases and aerosols from the atmosphere, weathering and erosion of rocks and soil, solution or precipitation reactions occurring below the land surface, and cultural effects resulting from human activities. Broad interrelationships among these processes and their effects can be discerned by application of principles of chemical thermodynamics. Some of the processes of solution or precipitation of minerals can be closely evaluated by means of principles of chemical equilibrium, including the law of mass action and the Nernst equation. Other processes are irreversible and require consideration of reaction mechanisms and rates. The chemical composition of the crustal rocks of the Earth and the composition of the ocean and the atmosphere are significant in evaluating sources of solutes in natural freshwater. The ways in which solutes are taken up or precipitated and the amounts present in solution are influenced by many environmental factors, especially climate, structure and position of rock strata, and biochemical effects associated with life cycles of plants and animals, both microscopic and macroscopic. Taken together and in application with the further influence of the general circulation of all water in the hydrologic cycle, the chemical principles and environmental factors form a basis for the developing science of natural-water chemistry. Fundamental data used in the determination of water quality are obtained by the chemical analysis of water samples in the laboratory or onsite sensing of chemical properties in the field. Sampling is complicated by changes in the composition of moving water and by the effects of particulate suspended material. Some constituents are unstable and require onsite determination or sample preservation. Most of the constituents determined are reported in gravimetric units, usually milligrams per liter or milliequivalents per liter. More than 60 constituents and properties are included in water analyses frequently enough to provide a basis for consideration of the sources from which each is generally derived, the most probable forms of elements and ions in solution, solubilitycontrols, expected concentration ranges, and other chemical factors. Mechanisms that control concentrations of elements commonly present in amounts less than a few tens of micrograms per liter cannot always be easily ascertained, but present information suggests that many are controlled by solubility of their hydroxides or carbonates or by sorption on solid particles. Many dissolved organic compounds can now be specifically determined. Chemical analyses may be grouped and statistically evaluated by means, medians, frequency distributions, or ion correlations to summarize large volumes of data. Graphing of analyses or of groups of analyses aids in showing chemical relationships among water, probable sources of solutes, areal water-quality regimen, temporal and spatial variation, and water-resources evaluation. Graphs may show water type based on chemical composition, relationships among ions, or groups of ions in individual waters or many waters considered simultaneously. The relationships of water quality to hydrogeologic characteristics, such as stream discharge rate or ground-water flow patterns, can be shown by mathematical equations, graphs, and maps. About 80 water analyses selected from the literature are tabulated to illustrate the relationships described, and some of these, along with many others that are not tabulated, are also used in demonstrating graphing and mapping techniques. Relationships of water composition to source rock type are illustrated by graphs of some of the tabulated analyses. Human activities may modify water composition extensively through direct effects of pollution and indirect results of water development, such as intrusion of seawater in groundwater aquifers. Water-quality standards for domestic, agricultural, and industrial use have been published by various agencies. Irrigation project requirements for water quality are particularly intricate. Fundamental knowledge of processes that control natural-water composition is required for rational management of water quality.

Water Supply Paper↗