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1,663 records · Page 83Linked to original sources

Hydrologic and water-quality conditions in the Horse Creek basin, west-central Florida, October 1992-February 1995

A baseline study of the 241-square-mile Horse Creek basin was undertaken from October 1992 to February 1995 to assess the hydrologic and water-quality conditions of one of the last remaining undeveloped basins in west-central Florida. During the period of the study, much of the basin remained in a natural state, except for limited areas of cattle and citrus production and phosphate mining. Rainfall in 1993 and 1994 in the Horse Creek basin was 8 and 31 percent, respectively, above the 30-year long-term average. The lowest and highest maximum instantaneous peak discharge of the six daily discharge stations occurred at the Buzzard Roost Branch and the Horse Creek near Arcadia stations with 185 to 4,180 cubic feet per second, respectively. The Horse Creek near Arcadia station had the lowest number of no-flow days with zero days and the Brushy Creek station had the highest number with 113 days. During the study, the West Fork Horse Creek subbasin had the highest daily mean discharge per square mile with 30.6 cubic feet per second per square mile, and the largest runoff coefficient of 43.7 percent. The Buzzard Roost Branch subbasin had the lowest daily mean discharge per square mile with 5.05 cubic feet per second per square mile, and Brushy Creek and Brandy Branch shared the lowest runoff coefficient of 0.6 percent. Brandy Branch had the highest monthly mean runoff in both 1993 and 1994 with 11.48 and 19.28 inches, respectively. During the high-baseflow seepage run, seepage gains were 8.87 cubic feet per second along the 43-mile Horse Creek channel. However, during the low-baseflow seepage run, seepage losses were 0.88 cubic foot per second. Three methods were used to estimate average annual ground-water recharge in the Horse Creek basin: (1) well hydrograph, (2) chloride mass balance, and (3) streamflow hydrograph. Estimated average annual recharge using these three methods ranged from 3.6 to 8.7 inches. The high percentage of carbonate plus bicarbonate analyzed at the Carlton surficial aquifer well could indicate an upward ground-water flow from the underlying intermediate aquifer system. Based on constituent concentrations in water samples from the six daily discharge stations, concentrations generally are lower in the upper three subbasins, West Fork Horse Creek, Upper Horse Creek, and Brushy Creek than in the lower three subbasins. Typically, concentrations were highest for major ions at Buzzard Roost Branch and nutrients at Brushy Creek.

Florida

Assessing nonpoint-source uranium pollution in an irrigated stream-aquifer system

Uranium (U) in rocks and soils of arid and semi-arid environments can be mobilized by irrigation and fertilization, posing environmental and health risks. Elevated U, along with selenium (Se) and nitrate (NO 3 ) co-constituents, necessitates careful monitoring and management. We developed a distributed-parameter numerical model to assess U pollution in an irrigated stream-aquifer system, applying it to a 552 km 2 region in Colorado's Lower Arkansas River Valley (LARV) over 14 years. A MODFLOW model, describing groundwater and stream flow, was coupled with an RT3D-OTIS model to portray reactive U transport. Calibration using the PESTPP-iES iterative ensemble smoother (iES) software indicated good agreement with observed U concentrations. The model revealed substantial and variable U levels across the LARV, highlighting potential hotspots and possible contributing factors, such as geological composition of the bedrock and near-surface shale and aquifer sediments derived from them, irrigation practices, and riparian landscape. U levels exceed the chronic standard (85th percentile = 30 μg/L, set by the US Environmental Protection Agency), which is the permissible regulatory threshold, in groundwater across 44 % of the region and along the river by an average factor of 2.9. Simulated average U concentrations in the non-riparian aquifer and river are 124 μg/L and 60 μg/L, respectively, compared with 112 μg/L and 62 μg/L for measured values. The average 85th percentile U concentration is 222 μg/L in the aquifer and 82 μg/L in the river. Average simulated U mass loading to the river is 0.17 kg/day per km, compared to an estimated 0.23 kg/day per km. Findings provide a baseline for comparing future simulated outcomes of alternative best management practices (BMPs) for U pollution mitigation and offer a methodology applicable to other irrigated regions.

Colorado

Updated three-dimensional temperature maps for the Great Basin, USA

As part of the periodic update of the geothermal energy assessments for the USA (e.g., last update by Williams and others, 2008), a new three-dimensional temperature map has been constructed for the Great Basin, USA. Williams and DeAngelo (2011) identified uncertainty in estimates of conductive heat flow near land surface as the largest contributor to uncertainty in previously published temperature maps. The new temperature maps incorporate new conductive heat flow estimates developed by DeAngelo and others (2023). Predicted temperatures at depth are compared with representative measurements (for conductively dominated conditions), showing good agreement under relatively simple uniform conditions. Inputs included radiogenic heat production for all layers of 1.89 μW/m 3 , effective bulk thermal conductivity of 2.7 W/m/°C for all rocks underlying sedimentary basins, and a previously published (Williams and DeAngelo, 2011) empirically driven estimate of increasing thermal conductivity with depth in sedimentary sequences. The resulting three-dimensional temperature model is published in a USGS data release associated with this manuscript (Burns and others, 2023).

Arizona, California, Idaho, Nevada, Oregon, Utah

Water use in Louisiana, 2020

The U.S. Geological Survey (USGS), in cooperation with the Louisiana Department of Transportation and Development, collected water-withdrawal and water-use data from a 2020 inventory of water withdrawals in Louisiana. In 2020, approximately 8,700 million gallons per day (Mgal/d) of water was withdrawn from groundwater and surface-water sources in Louisiana, which represented a 0.22-percent decrease from 2015. Total groundwater withdrawals were about 1,900 Mgal/d, an increase of 7.1 percent from 2015, and total surface-water withdrawals were about 6,800 Mgal/d, a decrease of 2.1 percent from 2015 to 2020. Total water withdrawals, in million gallons per day, in 2020 for the various categories of use were as follows: public supply, 720; industry, 2,100; power generation, 4,100; rural domestic, 39; livestock, 7.0; rice irrigation, 930; general irrigation, 250; and aquaculture, 590. From 2015 to 2020, Louisiana’s total withdrawals for public supply increased by 1.4 percent, industry decreased by 2.3 percent, power generation decreased by 4.9 percent, rural domestic decreased by 1.2 percent, livestock increased by 11 percent, rice irrigation increased by 13 percent, general irrigation increased by 12 percent, and aquaculture increased by 20 percent. About 51 percent (approximately 960 Mgal/d) of all groundwater withdrawn was from the Chicot aquifer system and 24 percent (approximately 450 Mgal/d) was withdrawn from the Mississippi River alluvial aquifer. Since 2015, withdrawals from the Chicot aquifer system increased by 13 percent, and withdrawals from the Mississippi River alluvial aquifer increased by 18 percent. About 72 percent (4,900 Mgal/d) of all surface water withdrawn was from the Mississippi River main stem. This value represents a 1.1-percent decrease in withdrawals from 2015 to 2020. All water-withdrawal and water-use data presented in this report should be considered estimates. Because of rounding, totals and percentages presented in the tables, figures, and text in the report may differ slightly from totals or percentages calculated individually.

Louisiana

Reconciling bias in moderate magnitude earthquake ground motions predicted by numerical simulations

Recent studies found a significant underprediction in ground motion intensity measures for finite-fault simulations of moderate magnitude events in southern California relative to established ground motion models. This study aims to understand the source(s) of this bias by evaluating ground motion residuals. For this, simulations have been performed for a total of 27 well-recorded earthquakes in southern California. Systematic efforts have been employed to identify the source(s) of bias by ruling out factors that are insignificant. Preliminary findings indicate that the magnitude-area scaling used in the simulations is the likely major cause of the observed bias. Adjustment in the source attributes on event-by-event basis is underway to study if the observed bias can be reconciled.

Conference Paper

Streamflow, water quality, and constituent loads and yields, Scituate Reservoir drainage area, Rhode Island, water year 2023

As part of a long-term cooperative program to monitor water quality within the Scituate Reservoir drainage area, the U.S. Geological Survey, in cooperation with Providence Water (formerly the Providence Water Supply Board), collected streamflow and water-quality data in tributaries to the Scituate Reservoir, Rhode Island. Streamflow and concentrations of chloride and sodium estimated from records of specific conductance for 16 tributaries were used to calculate loads of chloride and sodium during water year 2023 (October 1, 2022, through September 30, 2023). Water-quality samples were collected by Providence Water at 38 sampling stations on tributaries to the Scituate Reservoir during water year 2023. These water-quality data are summarized by using values of central tendency and are used, in combination with measured (or estimated) streamflows, to calculate loads and yields of selected water-quality constituents for water year 2023. Annual mean streamflows for monitoring stations in this study ranged from 0.47 to 34.4 cubic feet per second during water year 2023. At the 16 continuous-record streamgages, tributaries transported about 3,000 metric tons of chloride and 1,900 metric tons of sodium to the Scituate Reservoir; annual chloride yields for the tributaries ranged from 19 to 200 metric tons per square mile, and annual sodium yields ranged from 13 to 120 metric tons per square mile. At the stations where water-quality samples were collected by Providence Water, the medians of the median daily loads were 65,000 million colony forming units per day for coliform bacteria, 870 million colony forming units per day for Escherichia coli , 200 kilograms per day for chloride, 8.2 grams per day as nitrogen for nitrite, 520 grams per day as nitrogen for nitrate, and 300 grams per day as orthophosphate for phosphate. The medians of the median yields were 25,000 million colony forming units per day per square mile for coliform bacteria, 600 million colony forming units per day per square mile for Escherichia coli , 65 kilograms per day per square mile for chloride, 4.6 grams per day per square mile as nitrogen for nitrite, 180 grams per day per square mile as nitrogen for nitrate, and 180 grams per day per square mile as orthophosphate for phosphate.

Rhode Island

The U.S. Geological Survey National Water Quality Network—Groundwater, 2024

The U.S. Geological Survey (USGS) operates a National Water Quality Network (NWQN) to monitor trends in groundwater quality and assess emerging contaminants of concern. It is a “network of networks” with 81 subnetworks being sampled on a decadal time scale. Each year, 8 of the subnetworks are sampled. Subnetworks have 20–30 wells each and include studies of domestic supply wells or shallow groundwater (20–50 feet deep) underlying urban land use or agricultural land use. Currently there are 2,089 wells in the network. All wells are sampled for physical properties, nutrients, major ions, trace elements, per- and polyfluoroalkyl substances (PFAS), and a subset of wells are sampled for pesticides, volatile organic compounds, radionuclides, and microbiological contaminants.

Contiguous United States

Connecting flood-related fluvial erosion and deposition with vulnerable downstream road-stream crossings

Fluvial erosion is increasingly responsible for infrastructure and building damages associated with floods as the intensity of extreme rainfalls hit rural and urban rivers in a variety of climate settings across the United States. Extreme floods in 2016 and 2018 caused widespread culvert blockages and road failures, including extensive damage along steep tributaries and ravines in the Marengo River, Wisconsin, watershed during 2016 and 2018. A study conducted by the U.S. Geological Survey (USGS), Wisconsin Wetlands Association (WWA), Ashland County, and the Northwest Wisconsin Regional Planning Commission (NWRPC) investigated the special concern of fluvial erosion hazards (FEHs) associated with gullying, streamside landslides, and the loss of wetland storage in headwaters. In 2019, a pilot study was begun to map and classify ephemeral and perennial streams and wetlands in terms of their sensitivity to FEHs. This study combined data from field-based rapid geomorphic assessments (RGAs) coupled with a stream network-wide geographic information system (GIS) approach for mapping stream segments, referred to as fluvial process zones (FPZ), sensitive to erosion, deposition, and channel change. The GIS approach used nationally available 10-meter (m) resolution topology and an extended stream network to map FPZs based on Strahler stream order, stream power, channel slope, presence of adjacent steep valley sides and headwater flats, and adjacent landform setting. Bankfull channel widths derived from RGA-based hydraulic geometry curves combined with drainage areas, an estimate of bankfull flow, and channel slope were used to calculate specific stream power for the FPZs. Lastly, the FPZs were characterized by their location within three major landform settings that affect erosion potential. The resulting vulnerability maps provided a screening framework to identify FPZs that are sensitive to incision, gullying and mass wasting along steep headwater ephemeral channels, as well as downstream perennial channels that have the potential for valley-side landslides, coarse sediment deposition, and channel change. Lastly, each FPZ was characterized in terms of hydrologic alteration associated with ditching. The vulnerability mapping products and rankings of sensitivity of FPZs will ultimately be used by Ashland County and their collaborators to prioritize natural flood management projects that mitigate FEHs, restore hydrology, and reconnect channels with adjacent wetlands and floodplains.

Wisconsin

Only very strong shaking can break a tree

A handful of credible accounts, both recent and historical, describe trees being broken during earthquakes. Apart from landslides and tsunamis, such accounts are uncommon, suggesting that trees break only when ground acceleration is extreme or when trees are especially vulnerable to breakage. Here, I consider the question: what ground acceleration is required to break a living tree? I present simplified first‐principles calculations, considering the properties of common trees, focusing on tall, thin trees that can be approximated as uniform vertical cantilevers. The results suggest that, possibly excepting tall trees with heavy canopies, standing trees can only be broken by shaking approaching or exceeding 1 g , as anticipated by the rarity of documented accounts of snapped trees. I briefly consider several well‐documented instances of tree damage during strong earthquakes, drawing inferences about local ground motions.

The Seismic Record

Mapping bedrock outcrops in the Sierra Nevada Mountains (California, USA) using machine learning

Accurate, high-resolution maps of bedrock outcrops can be valuable for applications such as models of land–atmosphere interactions, mineral assessments, ecosystem mapping, and hazard mapping. The increasing availability of high-resolution imagery can be coupled with machine learning techniques to improve regional bedrock outcrop maps. In the United States, the existing 30 m U.S. Geological Survey (USGS) National Land Cover Database (NLCD) tends to misestimate extents of barren land, which includes bedrock outcrops. This impacts many calculations beyond bedrock mapping, including soil carbon storage, hydrologic modeling, and erosion susceptibility. Here, we tested if a machine learning (ML) model could more accurately map exposed bedrock than NLCD across the entire Sierra Nevada Mountains (California, USA). The ML model was trained to identify pixels that are likely bedrock from 0.6 m imagery from the National Agriculture Imagery Program (NAIP). First, we labeled exposed bedrock at twenty sites covering more than 83 km 2 (0.13%) of the Sierra Nevada region. These labels were then used to train and test the model, which gave 83% precision and 78% recall, with a 90% overall accuracy of correctly predicting bedrock. We used the trained model to map bedrock outcrops across the entire Sierra Nevada region and compared the ML map with the NLCD map. At the twenty labeled sites, we found the NLCD barren land class, even though it includes more than just bedrock outcrops, accounted for only 41% and 40% of mapped bedrock from our labels and ML predictions, respectively. This substantial difference illustrates that ML bedrock models can have a role in improving land-cover maps, like NLCD, for a range of science applications.

California

Young explosive eruptions from the Clear Lake volcanic field

The Clear Lake volcanic field is the northernmost and youngest field in a chain of volcanic fields in and near the California Coast Range mountains. For 2 million years, numerous eruptions have happened around (and through) Clear Lake. The most recent period of activity in the Clear Lake volcanic field probably started around 40,000 years ago and was mainly explosive eruptions concentrated on and near faults in and around the lake. The combination of hot magma and groundwater created explosive releases of hot steam. The craters, called maars, threw out volcanic ash, pumice, and lava fragments, which fell back to the ground and draped the surrounding landscape. The deposits are visible in many places around the southeast end of the lake.

California

HyFlood: A surrogate-model-based framework for compound coastal flooding

Compound coastal flooding is a major threat to low-lying coastal regions and is expected to intensify under future climate change projections. However, modeling the joint interaction of waves, storm surge, tides, and rainfall remains computationally demanding, limiting the development of fast and reliable forecast tools. Here we present HyFlood, a hybrid statistical-numerical downscaling framework capable of computing and mapping high-resolution compound flood hazards while substantially reducing the computational cost compared with fully process-based hydrodynamic modeling. HyFlood combines statistical sampling and selection algorithms with a cascade of reduced-complexity surrogate models that emulate nearshore wave transformation, surf-zone hydrodynamics, and coastal, fluvial, and pluvial flooding. The surrogate models employ machine-learning and regression algorithms applied to a low-dimensional representation of the flooding outputs, obtained through statistical dimensionality reduction. The framework is demonstrated in southern O'ahu, Hawai'i, a region exposed to elevated sea levels driven by tides, waves, and storm surge along with frequent precipitation-driven flash flooding. Validation of the surrogates against the physics-based model outputs demonstrates that HyFlood accurately reproduces daily maxima of spatially distributed flooding depths. This hybrid approach offers a scalable and efficient tool to better quantify how changes in flooding drivers translate into hazard and impact assessments, and to support compound-flood risk assessments and climate-change adaptation planning.

Hawaii

Stratigraphic notes—Volume 2, 2025

This is the second volume in the U.S. Geological Survey (USGS) series of reports on stratigraphy entitled “Stratigraphic Notes,” which consists of short papers that highlight stratigraphic studies, changes in stratigraphic nomenclature, and explanations of stratigraphic names and concepts used on published geologic maps. “Stratigraphic Notes” is a long-term (multiyear), multivolume publication containing articles that address updates or revisions to stratigraphic nomenclature (and whose content ultimately will be incorporated by National Geologic Map Database personnel into Geolex, https://ngmdb.usgs.gov/Geolex/ ). We welcome papers for the “Stratigraphic Notes” series from geoscientists of the USGS, of State Geological Surveys, and from academicians. Papers can be submitted for publication in “Stratigraphic Notes” by contacting the USGS Geologic Names Committee ( gnc@usgs.gov ). As new “Stratigraphic Notes” volumes are published, links to the volumes will be posted at https://doi.org/10.3133/pp1879 .

Professional Paper

Stratigraphic notes—Volume 3, 2026

This is the third volume in the U.S. Geological Survey (USGS) series of reports on stratigraphy entitled “Stratigraphic Notes,” which consists of short papers that highlight stratigraphic studies, changes in stratigraphic nomenclature, and explanations of stratigraphic names and concepts used on published geologic maps. “Stratigraphic Notes” is a long-term (multiyear), multivolume publication containing articles that address updates or revisions to stratigraphic nomenclature (and whose content ultimately will be incorporated by National Geologic Map Database personnel into Geolex, https://ngmdb.usgs.gov/Geolex/ ). We welcome papers for the “Stratigraphic Notes” series from geoscientists of the USGS, of State Geological Surveys, and from academicians. Papers can be submitted for publication in “Stratigraphic Notes” by contacting the USGS Geologic Names Committee ( gnc@usgs.gov ). As new “Stratigraphic Notes” volumes are published, links to the volumes will be posted at https://doi.org/10.3133/pp1879 .

Professional Paper

Salinas Valley integrated hydrologic and reservoir operations models, Monterey and San Luis Obispo Counties, California

The area surrounding the Salinas Valley groundwater basin in Monterey and San Luis Obispo Counties of California is a highly productive agricultural area, contributes substantially to the local economy, and provides a substantial portion of vegetables and other agricultural commodities to the Nation. This region of California provides about half of the Nation’s lettuce, celery, broccoli, and spinach each year. Thus, this agricultural area provides substantial volumes of agricultural products not just for California but for the United States. Changes in population and increased agricultural development, which includes a shift toward more water-intensive crops, and climate variability, have put increasing demand on both surface-water and groundwater resources in the valley. This situation has resulted in water management challenges in the Salinas Valley that generally relate to the distribution of the water supply throughout the basin. Where and when the water is present in the surface and subsurface does not coincide with where and when the water is needed. Historically, to deal with the distribution issue, water has been used conjunctively in the valley. Conjunctive use is a water management strategy that coordinates surface-water and groundwater use to maximize water availability. Groundwater is used throughout the Salinas Valley to meet water demands when surface-water supplies are insufficient. The availability of surface water is constrained by climate. Precipitation and streamflow vary seasonally and year to year. Although there are two reservoirs in the Salinas Valley to capture and store water during wet periods, the only conveyance of reservoir water to coastal agricultural areas is the Salinas River. Increasing demand for groundwater and surface-water resources throughout the Salinas Valley has resulted in undesirable effects from unsustainable water use, such as surface-water depletion, groundwater-level declines, storage depletion in the principal aquifers, and seawater intrusion. To address these escalating issues, local communities, water management agencies, and groundwater sustainability agencies are evaluating how to sustainably manage both their surface-water and groundwater resources. To meet water demands and reduce the undesirable effects of unsustainable water use, continued conjunctive management of surface water and groundwater would ideally incorporate strategies to deal with increases in demand and climate variability. To evaluate the challenging water management issues in the Salinas Valley, the U.S. Geological Survey, Monterey County Water Resources Agency, and the Salinas Valley Basin Groundwater Sustainability Agency developed a comprehensive suite of models that represent the Salinas Valley hydrogeologic system called the Salinas Valley System Model. The geologic framework is known as the Salinas Valley Geologic Framework and was developed to characterize the subsurface using various topographic and geologic data sources, including information on hydrogeologic units, their surfaces and extents, geologic structures, lithology, and elevations from borehole data and cross sections, as well as details on faults and existing models. The surface-water model is called the Salinas Valley Watershed Model and simulates the Salinas River watershed. Monthly surface-water inflows into the integrated hydrologic model domain were simulated using the Salinas Valley Watershed Model. The historical model uses historical climate data, water and land use data, and reservoir releases to simulate agricultural operations, including landscape water demands, diversions, and reclaimed wastewater. The operational model adds an embedded reservoir operations framework to the simulation of the historical model that allows specified operational rules to simulate reservoir releases and changes in reservoir storage. The operational model assumes current reservoir operations and constant land use, which differs from historical conditions. Thus, the operational model is a hypothetical baseline model that can be used by local water managers to evaluate and quantify potential benefits of water supply projects. Together, the geologic framework, watershed, historical, and operational models form a tool that can be used to simulate irrigated agriculture and associated reservoir operations of the integrated hydrologic system of the Salinas Valley.

California

Trimming the UCERF3-TD logic tree: Model order reduction for an earthquake rupture forecast considering loss exceedance

The Uniform California Earthquake Rupture Forecast version 3-Time Dependent depicts California’s seismic faults and their activity. Its logic tree has 5760 leaves. Considering 30 more model combinations related to ground motion produces 172,800 distinct models representing so-called epistemic uncertainties. To calculate risk to a portfolio of buildings, one also considers millions of earthquakes and spatially correlated ground-motion variability. We offer a tree-trimming technique that retains the probability distribution of portfolio loss and identifies the leading sources of uncertainty for further study. We applied it to a California statewide building portfolio and various levels of nonexceedance probability between one in 100 and one in 2500. We trimmed the logic tree from 172,800 leaves to as few as 15. The result: a supercomputer that would otherwise run 24 h to estimate the distribution of one-in-250-year loss can calculate it in moments with the reduced-order model. Others can use the reduced-order model to calculate risk to different California portfolios, and scientists can prioritize study to reduce the remaining epistemic uncertainty.

Earthquake Spectra

A methodology to estimate CO2 and energy gas storage resources in depleted conventional gas reservoirs

Depleted hydrocarbon reservoirs are subsurface geological structures capable of sequestering vast quantities of carbon dioxide (CO 2 ) as well as storing other energy gases for later usage, such as natural gas, and potentially hydrogen (H 2 ). Here we outline a methodology to quantify multi-gas storage resources in depleted conventional gas reservoirs for usage in assessments by the United States Geological Survey (USGS) at the scale of sedimentary basins. The methodology consists first of quantifying accessible pore volume in a depleted reservoir for natural gas storage using up to three equations. Input data are derived from commonly reported or estimated reservoir parameters and natural gas production volumes, and equations may be combined in linear models to improve pore volume estimates. Storage estimates from these equations are tested and validated for 31 reservoirs in the Michigan Basin Province, USA that were previously converted to underground gas storage facilities and have known (federally reported) natural gas storage capacities. Secondly, natural gas storage capacities can be transformed via fluid substitution calculations to estimate the storage resources for non-native fluids, applied here for, CO 2 , H 2 , and methane-H 2 blends, accounting for molecule-specific deviations from ideal gas behavior at reservoir pressures and temperatures as well as differing storage efficiencies. Importantly, the storage of non-native fluids may not be appropriate in all depleted gas reservoir settings due to potential risks like leakage, in particular in the case of H 2 storage, requiring additional knowledge of caprock sealing capacity. Given this caveat, we demonstrate the fluid substitution method for natural gas reservoirs of the Northern Niagaran Reef and Southern Niagaran Reef USGS plays in the Michigan Basin Province, as these trends of Silurian pinnacle reefs are capped with tight-sealing evaporite facies. The deterministic equations outlined from this methodology can be incorporated into future probabilistic USGS gas storage assessments for CO 2 , H 2 , and natural gas resources in the United States.

Michigan

Distribution functions for statistics derived from bivariate normal and bivariate two-parameter log-normal populations

The distribution functions for statistics that may be used to assess the significance of differences between sample means, standard deviations, coefficients of skewness, and coefficients of variation are obtained by Monte Carlo experiments. The distributions are expressed as functions of sample size, cross correlation, and skewness. In general, the distributions are more sensitive to cross correlation than to skewness. As sample size increases, however, the distributions tend to become more sensitive to skewness.

Open-File Report