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At least 739 records · Page 41Linked to original sources
USGS2025

Mount Spurr volcano, August 18, 1992: The eruption heard around Alaska

The August 18, 1992, eruption of Mount Spurr volcano, Alaska, produced an impressive Vulcanian to Subplinian eruption column reaching up to 40 km above sea level that blanketed the nearby city of Anchorage with ash. At the time of the eruption, the Alaska Volcano Observatory received reports of audible sound hundreds of kilometers from the source from a variety of azimuths from the volcano and found the pattern that did not solely depend on distance. Explosions are generally inaudible to the human ear at these distances due to the attenuation of sound in the atmosphere as the energy propagates, but low-frequency sound waves (infrasound) persist and can be used to detect and characterize eruptions. Similar reports of zones of audible sounds at great distances have been observed from notable eruptions such as Krakatau 1883, Mount St. Helens 1980, Mount Pinatubo 1991, and Hunga volcano 2022. We perform infrasound propagation modeling to help understand the unique distribution of audible reports, finding that areas with favorable infrasound propagation may help explain areas in which nonlinear propagation, including energy cascading effects into higher frequencies that are audible to the human ear, may have occurred.

Alaska↗
USGS2016

Algorithms used in the Airborne Lidar Processing System (ALPS)

The Airborne Lidar Processing System (ALPS) analyzes Experimental Advanced Airborne Research Lidar (EAARL) data—digitized laser-return waveforms, position, and attitude data—to derive point clouds of target surfaces. A full-waveform airborne lidar system, the EAARL seamlessly and simultaneously collects mixed environment data, including submerged, sub-aerial bare earth, and vegetation-covered topographies. ALPS uses three waveform target-detection algorithms to determine target positions within a given waveform: centroid analysis, leading edge detection, and bottom detection using water-column backscatter modeling. The centroid analysis algorithm detects opaque hard surfaces. The leading edge algorithm detects topography beneath vegetation and shallow, submerged topography. The bottom detection algorithm uses water-column backscatter modeling for deeper submerged topography in turbid water. The report describes slant range calculations and explains how ALPS uses laser range and orientation measurements to project measurement points into the Universal Transverse Mercator coordinate system. Parameters used for coordinate transformations in ALPS are described, as are Interactive Data Language-based methods for gridding EAARL point cloud data to derive digital elevation models. Noise reduction in point clouds through use of a random consensus filter is explained, and detailed pseudocode, mathematical equations, and Yorick source code accompany the report.

Open-File Report↗
USGS2018

Conceptual model to assess water use associated with the life cycle of unconventional oil and gas development

As the demand for energy increases in the United States, so does the demand for water used to produce many forms of that energy. Technological advances, limited access to conventional oil and gas accumulations, and the rise of oil and gas prices resulted in increased development of unconventional oil and gas (UOG) accumulations. Unconventional oil and gas is developed using a method that combines directional drilling and hydraulic fracturing techniques, allowing for greater oil and gas production from previously unrecoverable reservoirs. Quantification of the water resources required for UOG development and production is difficult because of disparate data sources, variable reporting requirements across boundaries (local, State, and national), and incomplete or proprietary datasets. A topical study was started in 2015 under the U.S. Geological Survey’s Water Availability and Use Science Program, as part of the directive in the Secure Water Act for the U.S. Geological Survey to conduct a National Water Census, to better understand the relation between production of UOG resources for energy and the amount of water needed to produce and sustain this type of energy development in the United States. The Water Availability and Use Science Program goal for this topical study is to develop and apply a statistical model to better estimate the water use associated with UOG development, regardless of the location and target geologic formation. As a first step, a conceptual model has been developed to characterize the life cycle of water use in areas of UOG development. Categories of water use and the way water-use data are collected might change over time; therefore, a generic approach was used in developing the conceptual model to allow for greater flexibility in adapting to future changes or newly available data. UOG development can be summarized into four stages: predrilling construction, drilling, hydraulic fracturing, and ongoing production. The water used in UOG production can be categorized further as direct, indirect, or ancillary water use. Direct water use is defined as the water used for drilling and hydraulic fracturing a well and for maintaining the well during ongoing production. Indirect water use is defined as the water used at or near a well pad. The water used for dust abatement also is considered an indirect use but may be applied away from the well pad. Ancillary water use is defined as the additional local or regional water use resulting from a change (for example, population) directly related to UOG development throughout the life cycle that is not used directly in the well or indirectly for any other purpose at the well pad. The conceptual model presented in this report consists of five elements: (1) input data, (2) processes, (3) decisions, (4) output data, and (5) outcomes. The input data requirements for estimating water use associated with UOG development are somewhat onerous, and obtaining suitable datasets can be challenging because local, State, and Federal agencies do not collect data similarly. The quality of a water-use assessment that uses the conceptual model presented in this report is dependent on the quality and quantity of data that are available for a UOG play. The conceptual model can be used for an assessment with sparse data; however, having sparse data likely will result in greater uncertainty in the water-use estimates. The conceptual model presented in this report is designed to be robust to characterize and simulate the data processing to estimate water use associated with UOG development. Although the results of an analysis that includes missing data have greater uncertainty, the analysis still can be insightful because it can establish a baseline estimate of UOG water use that may be refined further as more data become available. Analysis of models that include missing data also could aid in identifying the data most needed for future water-use estimates. Characterizing individual model limitations is important because the conceptual model can be used in future water-use studies to facilitate data compiling, data processing, estimating, and assessing UOG activities regardless of location.

Scientific Investigations Report↗
USGS2019

Relative prediction intervals reveal larger uncertainty in 3D approaches to predictive digital soil mapping of soil properties with legacy data

Fine scale maps of soil properties enable efficient land management and inform earth system models. Recent efforts to create soil property maps from field observations tend to use similar tree-based machine learning interpolation approaches, but often deal with depth of predictions, validation, and uncertainty differently. One of the main differences in approaches is whether to model individual depths of interest separately as ‘2D’ models, or to create models that incorporate depth as a predictor variable creating a ‘3D’ model that can make pre-dictions for all depths. It is unclear how choice of 2D or 3D approach influences model accuracy and uncertainty due to lack of direct comparison and inconsistent presentation of results in past studies. This study compares 2D and 3D methods for mapping soil electrical conductivity (salinity), pH, sum of fine and very fine sands, and organic carbon at 30 m resolution for the upper 432,000 km 2 of the Colorado River Watershed of the United States of America. A new, simple, model-agnostic relative prediction interval (RPI) approach to report un-certainty is presented that scales prediction interval width to the 95% interquantile width of the original training sample distribution. The RPI approach enables direct comparison of uncertainty between properties and depths and is easily interpretable by end users. Results indicate that 3D mapping of soil properties with strong variation with depth can result in substantial areas with much higher uncertainty that coincide with unrealistic predictions relative to 2D models, even though 3D models had slightly better global cross-validation scores. Maps and global model summaries of RPI proved helpful in identifying these issues with 3D models. These results suggest that the use of RPI or similar approaches to evaluate models can identify accuracy problems not evident in global va-lidation diagnostics.

Geoderma↗
USGS2022

Incorporating snowmelt into daily estimates of recharge using a state-space model of infiltration

A state-space model (SSM) of infiltration estimates daily groundwater recharge using time-series of groundwater-level altitude and meteorological inputs (liquid precipitation, snowmelt, and evapotranspiration). The model includes diffuse and preferential flow through the unsaturated zone, where preferential flow is a function of liquid precipitation and snowmelt rates and a threshold rate, above which there is direct recharge to the water table. Model parameters are estimated over seasonal periods and the SSM is coupled with the Kalman Filter (KF) to assimilate recent observations (hydraulic head) and meteorological inputs into recharge estimates. The approach can take advantage of real-time hydrologic and meteorological data to deliver real-time recharge estimates. The model is demonstrated on daily observations from two bedrock wells in carbonate aquifers of northwestern New York (USA) between 2013 and 2018. Meteorological inputs for liquid precipitation and snowmelt are compiled from SNODAS (2021). Results for recharge during winter and spring seasons show preferential flow events to the water table from liquid precipitation, snowmelt, or a combination of the two. Recharge estimates summed annually are consistent with previous estimates of recharge reported from groundwater flow and surface-process models. Results from the SSM and KF point to errors in meteorological inputs, such as the snowmelt rate, that are not compatible with hydraulic head observations. Whereas liquid and solid precipitation are measured at discrete stations and extrapolated to 1-km 2 grid cells, snowmelt is a meteorological modeled outcome that may not represent conditions in the vicinity of monitoring well locations.

Groundwater↗
USGS1998

Optimization of ground-water withdrawal in the lower Fox River communities, Wisconsin

Pumping from closely spaced wells in the Central Brown County area and the Fox Cities area near the north shore of Lake Winnebago has resulted in the formation of deep cones of depression in the vicinity of the two pumping centers. Water-level measurements indicate there has been a steady decline in water levels in the vicinity of these two pumping centers for the past 50 years. This report describes the use of ground-water optimization modeling to efficiently allocate the ground-water resources in the Lower Fox River Valley. A 3-dimensional ground-water flow model was used along with optimization techniques to determine the optimal withdrawal rates for a variety of management alternatives. The simulations were conducted separately for the Central Brown County area and the Fox Cities area. For all simulations, the objective of the optimization was to maximize total ground-water withdrawals. The results indicate that ground water can supply nearly all of the projected 2030 demand for Central Brown County municipalities if all of the wells are managed (including the city of Green Bay), 8 new wells are installed, and the water-levels are allowed to decline to 100 ft below the bottom of the confining unit. Ground water can supply nearly all of the projected 2030 demand for the Fox Cities if the municipalities in Central Brown County convert to surface water; if Central Brown County municipalities follow the optimized strategy described above, there will be a considerable shortfall of available ground water for the Fox Cities communities. Relaxing the water-level constraint in a few wells, however, would likely result in increased availability of water. In all cases examined, optimization alternatives result in a rebound of the steady-state water levels due to projected 2030 withdrawal rates to levels at or near the bottom of the confining unit, resulting in increased well capacity. Because the simulations are steady-state, if all of the conditions of the model remain the same these withdrawal rates would be sustainable in perpetuity.

Wisconsin↗
USGS2007

Surface-source downhole seismic analysis in R

This report discusses a method for interpreting a layered slowness or velocity model from surface-source downhole seismic data originally presented by Boore (2003). I have implemented this method in the statistical computing language R (R Development Core Team, 2007), so that it is freely and easily available to researchers and practitioners that may find it useful. I originally applied an early version of these routines to seismic cone penetration test data (SCPT) to analyze the horizontal variability of shear-wave velocity within the sediments in the San Francisco Bay area (Thompson et al., 2006). A more recent version of these codes was used to analyze the influence of interface-selection and model assumptions on velocity/slowness estimates and the resulting differences in site amplification (Boore and Thompson, 2007). The R environment has many benefits for scientific and statistical computation; I have chosen R to disseminate these routines because it is versatile enough to program specialized routines, is highly interactive which aids in the analysis of data, and is freely and conveniently available to install on a wide variety of computer platforms. These scripts are useful for the interpretation of layered velocity models from surface-source downhole seismic data such as deep boreholes and SCPT data. The inputs are the travel-time data and the offset of the source at the surface. The travel-time arrivals for the P- and S-waves must already be picked from the original data. An option in the inversion is to include estimates of the standard deviation of the travel-time picks for a weighted inversion of the velocity profile. The standard deviation of each travel-time pick is defined relative to the standard deviation of the best pick in a profile and is based on the accuracy with which the travel-time measurement could be determined from the seismogram. The analysis of the travel-time data consists of two parts: the identification of layer-interfaces, and the inversion for the velocity of each layer. The analyst usually picks layer-interfaces by visual inspection of the travel-time data. I have also developed an algorithm that automatically finds boundaries which can save a significant amount of the time when analyzing a large number of sites. The results of the automatic routines should be reviewed to check that they are reasonable. The interactivity of these scripts allows the user to add and to remove layers quickly, thus allowing rapid feedback on how the residuals are affected by each additional parameter in the inversion. In addition, the script allows many models to be compared at the same time.

Open-File Report↗
USGS2004

Climate change: Conflict of observational science, theory, and politics

Debate over whether human activity causes Earth climate change obscures the immensity of the dynamic systems that create and maintain climate on the planet. Anthropocentric debate leads people to believe that they can alter these planetary dynamic systems to prevent that they perceive as negative climate impacts on human civilization. Although politicians offer simplistic remedies, such as the Kyoto Protocol, global climate continues to change naturally. Better planning for the inevitable dislocations that have followed natural global climate changes throughout human history requires us to accept the fact that climate will change, and that human society must adapt to the changes. Over the last decade, the scientific literature reported a shift in emphasis from attempting to build theoretical models of putative human impacts on climate to understanding the planetwide dynamic processes that are the natural climate drivers. The current scientific literature is beginning to report the history of past climate change, the extent of natural climate variability, natural system drivers, and the episodicity of many climate changes. The scientific arguments have broadened from focus upon human effects on climate to include the array of natural phenomena that have driven global climate change for eons. However, significant political issues with long-term social consequences continue their advance. This paper summarizes recent scientific progress in climate science and arguments about human influence on climate. ?? 2004. The American Association of Petroleum Geologists. All rights reserved.

American Association of Petroleum Geologists Bulle↗
USGS2018

SWB Version 2.0—A soil-water-balance code for estimating net infiltration and other water-budget components

The U.S. Geological Survey’s Soil-Water-Balance (SWB) code was developed as a tool to estimate distribution and timing of net infiltration out of the root zone by means of an approach that uses readily available data and minimizes user effort required to begin a SWB application. SWB calculates other components of the water balance, including soil moisture, reference and actual evapotranspiration, snowfall, snowmelt, canopy interception, and crop-water demand. SWB is based on a modified Thornthwaite-Mather soil-water-balance approach, with components of the soil-water balance calculated at a daily time step. Net-infiltration calculations are computed by means of a rectangular grid of computational elements, which allows the calculated infiltration rates to be imported into grid-based regional groundwater-flow models. SWB makes use of gridded datasets, including datasets describing hydrologic soil groups, moisture-retaining capacity, flow direction, and land use. Climate data may be supplied in gridded or tabular form. The SWB 2.0 code described in this report extends capabilities of the original SWB version 1.0 model by adding new options for representing physical processes and additional data input and output capabilities. New methods included in SWB 2.0 allow for direct gridded input of externally calculated water-budget components (fog, septic, and storm-sewer leakage), simulation of canopy interception by several alternative processes, and a crop-water demand method for estimating irrigation amounts. New input and output capabilities allow for grids with differing spatial extents and projections to be combined without requiring the user to resample and resize the grids before use.

Techniques and Methods↗
USGS2025

Pre-eruptive characteristics of “suspect” silicic magmas in Carlin-type Au-forming systems

World-class Carlin-type Au deposits hosted in sedimentary rock were formed when profuse Eocene silicic magmatism swept across northern Nevada in response to arc migration. Carlin-type Au deposits formed along with porphyry/skarn Cu-Mo-W-Au deposits, epithermal Ag-Au deposits, and distal disseminated Ag-Au deposits. But unlike these other Au-bearing deposits that have clear associations with igneous intrusions, Carlin-type ore deposits appear to have formed distant from concealed plutons, and their origin remains controversial. Despite decades of abundant geophysical, geochronological, and geochemical studies suggesting the involvement of magmas, concrete evidence for magmatic involvement is still lacking. Consequently, the involvement of contemporaneous igneous systems remains inferred based on age, proximity, and variable isotopic, geochemical, and geophysical clues. A recent synthesis of deposit models postulates that Carlin-type Au deposits are intrusion-related, but that the causative magmas reside deeper (∼6–12 km) than in typical porphyry and peripheral systems (∼3–5 km), meaning that Carlin-type deposits are perhaps more distal expressions of igneous intrusions. We investigate a collection of “suspect” magmatic systems over a ∼7 m.y. timespan (∼41–34 Ma) that are contemporaneous with and near known Carlin-type ore deposits. We report results of a multifaceted array of in situ geochemical analyses (FTIR, EMP, SHRIMP-RG, LA-ICP-MS) of quartz-hosted melt inclusions, biotite, and quartz to better characterize the pre-eruptive characteristics of these magmas. We also report results of thermobarometry and thermodynamic phase equilibria modeling to help place constraints on magmatic reservoir depths and processes. Rather than a single “flavor” of silicic magma, we observe a surprisingly broad compositional spectrum of rhyolites, with one end of the spectrum exhibiting more arc-like (I-type) characteristics and the other end displaying more post-subduction, thick-crust extensional (A-type) characteristics. This broad compositional spectrum suggests a more complex picture of silicic crustal magmatism operating over a narrow span of time during slab rollback. Despite this spectrum, magmatic systems in this study are consistently ferroan and generally peraluminous, which we interpret as an expression of the relatively elevated geotherm at the time and incorporation of variable amounts of highly peraluminous metasedimentary crustal components. The silicic magma spectrum encompasses a range of mineralization associations, including subduction-related Cu-Mo-W-Au-Ag and post-subduction, thick-crust extensional rare-metal Mo-Sn-W-F-Be-Ag-Au, consistent with the prolific and diverse array of ore deposits that formed during this time. Carlin-type Au deposition appears to be associated with nearly the entire magmatic spectrum. This apparent indifference to silicic magma “flavor” would seem to imply that if magmas are involved in Carlin-type Au deposit genesis, they perhaps do not need to be compositionally specialized and/or possibly are only relevant as heat sources driving circulation to remobilize and redistribute metals.

Nevada↗