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At least 289 records · Page 16Linked to original sources
USGS2012

Updates to watershed modeling in the Potholes Reservoir basin, Washington-a supplement to Scientific Investigation Report 2009-5081

A previous collaborative effort between the U.S. Geological Survey and the Bureau of Reclamation resulted in a watershed model for four watersheds that discharge into Potholes Reservoir, Washington. Since the model was constructed, two new meteorological sites have been established that provide more reliable real-time information. The Bureau of Reclamation was interested in incorporating this new information into the existing watershed model developed in 2009, and adding measured snowpack information to update simulated results and to improve forecasts of runoff. This report includes descriptions of procedures to aid a user in making model runs, including a description of the Object User Interface for the watershed model with details on specific keystrokes to generate model runs for the contributing basins. A new real-time, data-gathering computer program automates the creation of the model input files and includes the new meteorological sites. The 2009 watershed model was updated with the new sites and validated by comparing simulated results to measured data. As in the previous study, the updated model (2012 model) does a poor job of simulating individual storms, but a reasonably good job of simulating seasonal runoff volumes. At three streamflow-gaging stations, the January 1 to June 30 retrospective forecasts of runoff volume for years 2010 and 2011 were within 40 percent of the measured runoff volume for five of the six comparisons, ranging from -39.4 to 60.3 percent difference. A procedure for collecting measured snowpack data and using the data in the watershed model for forecast model runs, based on the Ensemble Streamflow Prediction method, is described, with an example that uses 2004 snow-survey data.

Washington↗
USGS2012

Computing maximum-likelihood estimates for parameters of the National Descriptive Model of Mercury in Fish

This report presents the mathematical expressions and the computational techniques required to compute maximum-likelihood estimates for the parameters of the National Descriptive Model of Mercury in Fish (NDMMF), a statistical model used to predict the concentration of methylmercury in fish tissue. The expressions and techniques reported here were prepared to support the development of custom software capable of computing NDMMF parameter estimates more quickly and using less computer memory than is currently possible with available general-purpose statistical software. Computation of maximum-likelihood estimates for the NDMMF by numerical solution of a system of simultaneous equations through repeated Newton-Raphson iterations is described. This report explains the derivation of the mathematical expressions required for computational parameter estimation in sufficient detail to facilitate future derivations for any revised versions of the NDMMF that may be developed.

Open-File Report↗
USGS1988

Selected reports that include computer programs produced by the US Geological Survey for simulation of ground-water flow and quality

A summary list of reports that document numerical models that simulate ground-water flow and quality is presented. The list documents the reference by giving a description of each model program, its numerical features, a qualitative expression of the number of past applications and where to obtain a copy. All reports included in the list have been published or developed by the U.S. Geological Survey and most contain listings of the computer programs. (Author 's abstract)

Water-Resources Investigations Report↗
USGS2023

Pardus in the press: Drivers of leopard (Panthera pardus fusca) attack occurrence on humans in Nepal

The negative impact of large carnivore presence in human-dominated landscapes manifests as livestock depredation and in extreme cases as attacks on humans. In the case of conflict with leopards in Nepal, attacks resulting in human fatality have become more frequent over time, thus creating an urgent socio-ecological and management issue. We estimated the occurrence of leopard attacks in Nepal from human-leopard conflict cases reported in the media. We used occupancy models to analyse data collected from online news reports on incidents of leopard attacks on humans to explore drivers of leopard attacks on a landscape scale. Our results suggest that the probability of occurrence of leopard attack is associated with human population density, terrain ruggedness and livestock density. The human population density effect may be indicative of a density-dependent relationship, where attacks are more likely in areas where an increased abundance of humans increases encounter rates with leopards. The positive effect of livestock density suggests that livestock may be drawing leopards into human settlements, and consequently increasing the likelihood of attacks on humans. Terrain ruggedness might be offering ideal conditions to facilitate attacks on humans, for example remoteness and high amounts of cover to launch ambush attacks. We provide inference and insights into key determinants of leopard attacks on humans on a landscape scale. These insights can be used to guide future research, inform mitigation measures to reduce leopard attacks and foster a better understanding of the interaction between people and leopards. This study demonstrates the applicability and novelty of using a hierarchical modelling framework applied to freely and publicly available media reports to inform the applied management of human-wildlife conflict at a national scale.

People and Nature↗
USGS1995

Two-year simulation of the Great Lakes region with a coupled modeling system

In this paper, we report on an experiment aimed at evaluating the feasibility of the application of our coupled regional climate modeling system to long-term climate simulations over the Great Lakes region. The simulation analyzed covers a continuous 24-month period beginning 1 September 1990 and extending to 1 September 1992. Many aspects of this simulation agreed well with observations. Compared with European Centre for Medium-Range Weather Forecasts (ECMWF) analyses, area-averaged atmospheric temperature and moisture biases were generally small. The largest temperature biases were found in the simulated boundary layer, up to 1–1.5 K colder than observed in most months. Atmospheric moisture biases were of both signs and small in magnitude, almost universally less than 0.5 g kg −1 . Comparison of simulated surface air temperatures with station observations also indicated that model simulated temperatures generally display a cold bias. Simulated precipitation values agreed well with observations during the cold portions of the year while during warm months precipitation was overpredicted by 10%–50%. Spatial patterns of precipitation over the model domain agreed well with observations during the winter months but were not as well simulated during the other seasons. A one-dimensional lake model was coupled to the atmospheric component of the model to capture the effects of the Great Lakes on regional climate. Lake surface temperatures were generally well simulated by the lake model in the summer and fall seasons, and lake ice extent agreed well with the analysis over at least three of the five lakes. The greatest shortcomings in lake temperature simulation were the earlier-than-observed warm-up in the spring and warmer than observed peak temperatures in the summer over the northern portions of the lakes. Also, lake ice extent was generally overpredicted over Lake Superior and underpredicted over Lake Erie. In summary, the coupled modeling system described in this paper shows promise for use in climate simulators over regions where lakes are important such as the Great Lakes. It has been shown that many aspects of the simulation are in good agreement with available observations. Areas in which the results point to the need for further work are the model's convective parameterization, the eddy diffusivities in the lake model, and the treatment of clouds in the radiation package.

Illinois, Indiana, Michigan, Minnesota, New York, ↗
USGS2013

Estimating irrigation water use in the humid eastern United States

Accurate accounting of irrigation water use is an important part of the U.S. Geological Survey National Water-Use Information Program and the WaterSMART initiative to help maintain sustainable water resources in the Nation. Irrigation water use in the humid eastern United States is not well characterized because of inadequate reporting and wide variability associated with climate, soils, crops, and farming practices. To better understand irrigation water use in the eastern United States, two types of predictive models were developed and compared by using metered irrigation water-use data for corn, cotton, peanut, and soybean crops in Georgia and turf farms in Rhode Island. Reliable metered irrigation data were limited to these areas. The first predictive model that was developed uses logistic regression to predict the occurrence of irrigation on the basis of antecedent climate conditions. Logistic regression equations were developed for corn, cotton, peanut, and soybean crops by using weekly irrigation water-use data from 36 metered sites in Georgia in 2009 and 2010 and turf farms in Rhode Island from 2000 to 2004. For the weeks when irrigation was predicted to take place, the irrigation water-use volume was estimated by multiplying the average metered irrigation application rate by the irrigated acreage for a given crop. The second predictive model that was developed is a crop-water-demand model that uses a daily soil water balance to estimate the water needs of a crop on a given day based on climate, soil, and plant properties. Crop-water-demand models were developed independently of reported irrigation water-use practices and relied on knowledge of plant properties that are available in the literature. Both modeling approaches require accurate accounting of irrigated area and crop type to estimate total irrigation water use. Water-use estimates from both modeling methods were compared to the metered irrigation data from Rhode Island and Georgia that were used to develop the models as well as two independent validation datasets from Georgia and Virginia that were not used in model development. Irrigation water-use estimates from the logistic regression method more closely matched mean reported irrigation rates than estimates from the crop-water-demand model when compared to the irrigation data used to develop the equations. The root mean squared errors (RMSEs) for the logistic regression estimates of mean annual irrigation ranged from 0.3 to 2.0 inches (in.) for the five crop types; RMSEs for the crop-water-demand models ranged from 1.4 to 3.9 in. However, when the models were applied and compared to the independent validation datasets from southwest Georgia from 2010, and from Virginia from 1999 to 2007, the crop-water-demand model estimates were as good as or better at predicting the mean irrigation volume than the logistic regression models for most crop types. RMSEs for logistic regression estimates of mean annual irrigation ranged from 1.0 to 7.0 in. for validation data from Georgia and from 1.8 to 4.9 in. for validation data from Virginia; RMSEs for crop-water-demand model estimates ranged from 2.1 to 5.8 in. for Georgia data and from 2.0 to 3.9 in. for Virginia data. In general, regression-based models performed better in areas that had quality daily or weekly irrigation data from which the regression equations were developed; however, the regression models were less reliable than the crop-water-demand models when applied outside the area for which they were developed. In most eastern coastal states that do not have quality irrigation data, the crop-water-demand model can be used more reliably. The development of predictive models of irrigation water use in this study was hindered by a lack of quality irrigation data. Many mid-Atlantic and New England states do not require irrigation water use to be reported. A survey of irrigation data from 14 eastern coastal states from Maine to Georgia indicated that, with the exception of the data in Georgia, irrigation data in the states that do require reporting commonly did not contain requisite ancillary information such as irrigated area or crop type, lacked precision, or were at an aggregated temporal scale making them unsuitable for use in the development of predictive models. Confidence in the reliability of either modeling method is affected by uncertainty in the reported data from which the models were developed or validated. Only through additional collection of quality data and further study can the accuracy and uncertainty of irrigation water-use estimates be improved in the humid eastern United States.

Eastern United States↗
USGS2010

Recent (2001-09) hydrologic history and regionalization studies in Texas-Statistical characterization of storms, floods, and rainfall-runoff relations

As part of numerous cooperative studies investigating rainfall and streamflow during 1991-2009 with the Texas Department of Transportation and Texas Commission on Environmental Quality, the U.S. Geological Survey (USGS) published about 20 reports describing either historical streamflow conditions (hydrologic history) in Texas or the results of studies involving regional rainfall and streamflow statistics (regionalization studies). Both types of studies are widely used in engineering and scientific applications. Long-term rainfall and streamflow records are essential for deriving reliable rainfall and streamflow statistics. Whereas the need for such records is regionwide, rainfall and streamflow records are site-specific. The USGS has pioneered ways to mathematically transfer site-specific rainfall and streamflow information to provide regional statistical models. In addition to publishing reports describing historical hydrologic data at many monitored locations throughout Texas, the USGS has published reports describing regional models for estimating rainfall and streamflow statistics at unmonitored locations. The primary objectives of these regionalization studies were to provide historical perspectives of streamflow conditions in Texas or estimates of specific statistics of rainfall or streamflow. Statistics such as 6-hour, 1-percent annual exceedance rainfall (a large storm) or 2-percent annual exceedance streamflow (a substantial flood) can be estimated for locations lacking sufficient direct observations of rainfall and streamflow data. This fact sheet provides a brief synopsis of 12 recent (2001-09) USGS hydrologic history and regionalization studies in Texas organized thematically and chronologically.

Fact Sheet↗
USGS1983

Effects of sanitary sewers on ground-water levels and streams in Nassau and Suffolk Counties, New York, part 1: Geohydrology, modeling strategy, and regional evaluation

A computer simulation of Long Island 's regional groundwater system has been used to evaluate the effects that new-installed sewers will have on ground-water levels. Results indicate maximum water-table decliners of as much as up to 18 feet in central Nassau County and about 9 feet in Suffolk County. Total stream base flows and freshwater outflow to the south shore bay system will decrease by 22%. The regional scale of the model does not permit detailed predictions for individual streams. To quantify the effects of lowered ground-water levels on individual streams, two fine-scale sub-regional models have been designed. This report, the first in a three-part series describing the simulated effects of sewers in southern Nassau and southwestern Suffolk Counties, presents the hydrogeologic setting, pertinent literature, modeling strategy, subregional model design, and the results obtained to date from the regional ground-water model. The regional model results described will be used in the later reports to generate flux boundary conditions for the subregional models.

New York↗
USGS2022

Updates to models of streamflow and water temperature for 2011, 2015, and 2016 in rivers of the Willamette River Basin, Oregon

Mechanistic river models capable of simulating hydrodynamics and stream temperature are valuable tools for investigating thermal conditions and their relation to streamflow in river basins where upstream water storage and management decisions have an important influence on river reaches with threatened fish populations. In the Willamette River Basin in northwestern Oregon, a two-dimensional, hydrodynamic water-quality model (CE ‑ QUAL ‑ W2) has been used to investigate the downstream effects of dam operations and other anthropogenic influences on stream temperature. By simulating the managed releases of water and various temperatures from the large Willamette Valley Project dams upstream of the modeling domain, these models can be used to investigate riverine temperature conditions and their relation to streamflow to determine where and when conditions are most challenging for threatened fish populations and how dam operations and flow management can affect and optimize thermal conditions in the river. The original models were initially developed to simulate conditions in spring–autumn of 2001 and 2002. This report documents (1) the upgrade of the river models to CE‑QUAL‑W2 version 4.2 and (2) the update of those models to simulate conditions that occurred from March through October of 2011, 2015, and 2016. These years were selected to represent a range of climatic and hydrologic conditions in the Willamette River Basin, including a “cool, wet” year (2011), a “hot, dry” year (2015), and a “normal” year (2016). Six submodels comprise the modeling system updated in this report; each submodel can be run independently or run with the others as a system. These models include the Coast Fork and Middle Fork Willamette River submodel, which includes the Coast Fork and Middle Fork Willamette Rivers, the Row River, and Fall Creek; the McKenzie River submodel, which includes the South Fork McKenzie River downstream of Cougar Dam and the McKenzie River from its confluence with the South Fork McKenzie River to its mouth; the South Santiam River submodel, which comprises the South Santiam River from Foster Dam to the Santiam River; the North Santiam and Santiam River submodel, which includes the Santiam River and the North Santiam River downstream of Big Cliff Dam; the Upper Willamette River submodel, which includes the Willamette River from Eugene to Salem; and the Middle Willamette River submodel, which includes the Willamette River from Salem to Willamette Falls near Oregon City. The models included in this report were originally developed, calibrated, and documented by other researchers. As part of the model updates described here, some model parameters were adjusted to improve stability and decrease runtime. Boundary conditions including meteorological, hydrologic, and thermal parameters were developed and updated for model years 2011, 2015, and 2016. In many cases, the data sources used to drive the 2001 and 2002 models were no longer available, which required the use of new data sources, the determination of a proxy record, or the development of appropriate estimation techniques. Goodness-of-fit statistics for the updated models show a good model fit, with the models simulating subdaily water temperatures at most comparable locations with a mean absolute error of generally less than 1 °C and often nearing 0.5 °C, depending on the individual submodel, and a reasonably low bias. The subdaily mean error for the South Santiam River submodel produced the highest bias of any of the submodels. Goodness-of-fit statistics indicate that the results may be biased cool (ranging from -0.43 °C in 2016 to -0.80 °C in 2011 for subdaily results), but the only water temperature data available for comparison on the South Santiam River is itself estimated, and those estimates are known to be too high in summer. Depending on future modeling needs, that submodel may warrant further refinement, along with additional data collection to properly define and minimize any model bias.

Oregon↗
USGS1965

A final report on computed magneto-telluric curves for hypothetical models of crustal structure

Several mathematical models were investigated to determine the capa-bilities of the magneto-telluric method for determining the resistivity structure of the earth's crust. The model parameters were based on the crust model proposed by Keller (1963). The mathematical technique used was developed by Cagniard (1953). The investigations indicate that a three-layer model approximation of the crust and mantle is the most detailed model warranted in inter-preting the information provided by the magneto-telluric method about the lower crust. Only the thickness of the lower crust can be determined, and not the resistivity.

Crustal Studies Technical Letters↗
USGS2023

Parameter estimation at the conterminous United States scale and streamflow routing enhancements for the National Hydrologic Model infrastructure application of the Precipitation-Runoff Modeling System (NHM-PRMS)

This report documents a three-part continental-scale calibration procedure and a new streamflow routing algorithm using the U.S. Geological Survey National Hydrologic Model (NHM) infrastructure along with an application of the Precipitation-Runoff Modeling System (PRMS). The traditional approach to hydrologic model calibration and evaluation, which relies on comparing observed and simulated streamflow, is not sufficient for accurately representing the non-streamflow parts of the water budget. If intermediate process variables computed by the hydrologic model are not examined, the variables could be characterized by parameter values that do not replicate those hydrological processes present in the physical system. In answer to this potential problem, alternative hydrologic process variables from the model (in addition to streamflow) are included in a calibration procedure applied to the conterminous United States (CONUS) domain. The three-part calibration procedure presented in this report considers volume (calibration by hydrologic response unit [byHRU]), timing (calibration by headwater watershed [byHW]), and measured streamflow [byHWobs]). The first part, byHRU, is considered a water-balance volume calibration that uses five alternative (non-streamflow) hydrologic quantities (runoff, actual evapotranspiration, recharge, soil moisture, and snow-covered area) as calibration targets for each hydrologic response unit (HRU). These alternative data products were derived, with error bounds, from multiple sources for each of the 109,951 HRUs in the NHM on time scales varying from annual to daily. The second part of the calibration, byHW, is considered a streamflow timing calibration that uses statistically based streamflow simulations developed using ordinary kriging for 7,265 headwater watersheds that had drainage areas of less than 3,000 square kilometers (1,158 square miles) across the CONUS. Two streamflow routing algorithms were tested in this byHW calibration: (1) continuity without attenuation of the flood pulse and (2) a new formulation of the Muskingum routing method, which was added to the PRMS as part of this study. The third part of the calibration, byHWobs, refines the model parameters using available measured streamflow using 1,417 streamgage locations. A multiple-objective, stepwise, automated calibration procedure was used to identify the optimal set of parameters for each calibration procedure. Using a variety of alternative datasets for calibration of the water budget provides users of the NHM-PRMS with improved initial parameters and helps alleviate the equifinality problem (getting the right answer for the wrong reason). Through a community effort, these alternative data products, with error bounds, can be used to improve and expand our understanding of hydrologic-process representation in models. The broader modeling community can use these data products, with error bounds, to calibrate and evaluate hydrologic models using more than streamflow.

Conterminous United States↗
USGS2025

Science needs for determining the effects of climate change on harmful algal blooms in the southeastern United States

The Southeastern United States has many lakes, streams, and reservoirs that serve as important drinking water sources with recreational, agricultural, and ecological uses. However, harmful algal blooms (HABs) are becoming more common in these waters, causing health issues for humans and animals. HABs have been listed as a contaminant of emerging concern, and the magnitude, frequency, and duration of HABs appear to be increasing at the global scale. While it is well known that nutrients stimulate algae growth, it is not clear how climate change and other parameters stimulate the development of toxin production by HABs. The scientific literature describes parameters, such as storm occurrence, temperature, dissolved metals, erosion of soils, increasing length of growing season, discharge, and hydroperiod, that may affect algae growth and toxin production. Climate and hydrologic models address many of the physical and environmental parameters that influence HABs, but no climate models directly address HABs. This report compiles information from the existing literature pertaining to HABs and the modeling and forecasting of HABS. This compilation is done through the incorporation of climate change models. HAB research that involves climate change will require multiple disciplines that bring together ecologists, hydrologists, climatologists, engineers, economists, and new technology. Resource managers could use geographic data about the occurrence and distribution of HABs to develop models that identify waterbodies more vulnerable to HAB events. Development of such models will require teams capable of integrating biological, chemical, and physical factors. Model development will require additional research that can resolve anthropogenic and climate-related environmental factors to identify trends in freshwater HABs. The complexity and interconnectedness of the parameters that influence HAB occurrences will make model development challenging and require rigorous regional calibration.

Open-File Report↗
USGS2014

Numerical simulation of groundwater flow in the Columbia Plateau Regional Aquifer System, Idaho, Oregon, and Washington

A three-dimensional numerical model of groundwater flow was constructed for the Columbia Plateau Regional Aquifer System (CPRAS), Idaho, Oregon, and Washington, to evaluate and test the conceptual model of the system and to evaluate groundwater availability. The model described in this report can be used as a tool by water-resource managers and other stakeholders to quantitatively evaluate proposed alternative management strategies and assess the long‑term availability of groundwater. The numerical simulation of groundwater flow in the CPRAS was completed with support from the Groundwater Resources Program of the U.S. Geological Survey Office of Groundwater. The model was constructed using the U.S. Geological Survey modular three-dimensional finite-difference groundwater-flow model, MODFLOW-NWT. The model uses 3-kilometer (9,842.5 feet) grid cells that subdivide the model domain by 126 rows and 131 columns. Vertically, the model domain was subdivided into six geologic model units. From youngest to oldest, the units are the Overburden, the Saddle Mountains Basalt, the Mabton Interbed, the Wanapum Basalt, the Vantage Interbed, and the Grande Ronde Basalt. Natural recharge was estimated using gridded historical estimates of annual precipitation for the period 1895–2007. Pre-development recharge was estimated to be the average natural recharge for this period. Irrigation recharge and irrigation pumping were estimated using a remote-sensing based soil-water balance model for the period 1985–2007. Pre-1985 irrigation recharge and pumping were estimated using previously published compilation maps and the history of large-scale irrigation projects. Pumping estimates for municipal, industrial, rural, residential, and all other uses were estimated using reported values and census data. Pumping was assumed to be negligible prior to 1920. Two models were constructed to simulate groundwater flow in the CPRAS: a steady-state predevelopment model representing conditions before large-scale pumping and irrigation altered the system, and a transient model representing the period 1900–2007. Automated parameter-estimation techniques (steady-state predevelopment model) and traditional trial-and-error (transient model) methods were used for calibration. To calibrate the steady-state and transient models, 10,525 and 46,460 water level measurements, respectively, and 50 base-flow estimates were used. The steady-state model simulated the shape, slope, and trends of a potentiometric surface that was generally consistent with mapped water levels. For the transient model, the mean and median difference between simulated and measured hydraulic heads is -10 and 4 ft, respectively, with a standard deviation of 164 ft over a 5,648 ft range of measured heads. The residuals for the simulation period show that 52 percent of the simulated heads exceeded measured heads with a median residual value of 43 ft, and 48 percent were less than measured heads with a median residual value of -76 ft. The CPRAS model was constructed to derive components of the groundwater budget and help understand the interactions of stresses, such as recharge, groundwater pumping, and commingling wells on the groundwater and surface-water system. Through these applications, the model can be used to identify trends in groundwater storage and use, and quantify groundwater availability. The annual groundwater budgets showed several patterns of change over the simulation period. Groundwater pumping was negligible until the 1950s and began to increase significantly during the 1970s and 1980s. Recharge was highly variable due to the interannual variability of precipitation, but began to increase in the late 1940s due to the increase in surface-water irrigation projects. Groundwater contributions to streamflow (base flow) followed recharge closely. However, in areas of significant groundwater-level decline, base flow is reduced. Groundwater pumping had the greatest effect on water levels, followed by irrigation enhanced recharge. Commingling was a larger factor in structurally complex upland areas where hydraulic-head gradients are naturally high. Groundwater pumping has increased substantially over the past 40–50 years; this increase resulted in declining water levels at depth and decreased base flows over much of the study area. The effects of pumping are mitigated somewhat by the increase of surface-water irrigation, especially in the shallow Overburden unit, and commingling wells in some areas. During dry to average years, groundwater pumping causes a net loss of groundwater in storage and current condition (2000–2007) groundwater pumping exceeds recharge in all but the wettest of years.

Idaho, Oregon, Washington↗
USGS2026

Logical data model for hydrographic data based on HY_Features concepts

This report describes background and design of the “hydrofabric data model” which defines logic for implementation of data schemas and software that deals with hydrologic geospatial data. As a “logical” data model, the hydrofabric data model specifies details necessary to support compatibility of data and software that satisfy diverse needs without unnecessarily restricting implementation details. The logic presented in this report is based on concepts defined in WaterML2 Part 3 Surface Hydrology Features Concepts and is designed to serve the needs of a range of hydroscience use cases. Development of international community standards applicable to hydrofabrics began, prompted by the World Meteorological Organization Commission for Hydrology, in 2012 [5] . More than 10 years later, this report documents one aspect of a long-term research and development activity that traces its roots back that far. This report describes terminology, use cases, and background as context preceding presentation of the logical model and discussion of its design. Three appendices document related data models, an example encoding of the hydrofabric data model, and an artificial schematic and tabular data example. The sections of the report can be accessed in the Clause 5 section.

OCG Public Engineering Report↗
USGS2024

Water-quality indicators of surface-water-influenced groundwater supplies in the Ohio River alluvial aquifer of West Virginia

The U.S. Geological Survey, in cooperation with the West Virginia Department of Health and Human Resources, studied surface-water-influenced groundwater supplies in the Ohio River alluvial aquifer of West Virginia for the purpose of understanding the influence of surface water on groundwater chemistry. Public groundwater supplies obtained from these aquifers receive substantial recharge from surface-water sources and are highly susceptible to degradation from water-soluble contaminants. Water samples were collected from 4 sites in the Ohio River and 23 groundwater wells in the alluvial aquifer from June 2019 to January 2020. Surface-water influence was assessed through characterization of groundwater quality, determination of recharge sources, estimation of groundwater age, and estimation of the fraction of Ohio River water entering groundwater pumped by wells in the alluvial aquifers. Hydrogeochemical processes controlling solute concentrations in the Ohio River alluvial aquifer were evaluated with multivariate statistical analysis and identified to be primarily controlled by redox processes, input from sources of salinity, and carbonate dissolution. Meteoric recharge from the Ohio River and precipitation on the alluvium are the main sources of water entering the aquifer. The age of groundwater in the system was determined to be primarily from a modern source. Groundwater samples from every well included in this study had detections for at least one geochemical indicator of surface-water influence, and every well was determined to be susceptible and vulnerable to contamination from surface sources. Results from binary mixing models and inverse geochemical models showed that sulfate, silica, and bicarbonate concentrations predict the fraction of Ohio River water entering alluvial wells for preliminary determination of surface-water influence when compared to fractions predicted using a numerical groundwater-flow model. In the absence of extensive analytes and geochemical or groundwater modeling capabilities, preliminary assessment of the fraction of Ohio River water entering groundwater wells in the Ohio River alluvium can be estimated for most sites using a linear relation between the equivalent ratio of bicarbonate to sulfate and the fraction of water computed by the average of the three geochemical models presented in this report. This approximation of the fraction of Ohio River water, coupled with information on the hydrogeological framework and geochemical indicators of surface-water influence, may be sufficient for preliminary assessment of surface-water influence in the absence of more detailed site information or reaction-transport models.

West Virginia↗
USGS2024

Three-dimensional geologic framework model of the Rio San Jose groundwater basin and adjacent areas, New Mexico

As part of a U.S. Geological Survey study in cooperation with the Bureau of Reclamation and the Pueblo of Acoma, New Mexico, and the Pueblo of Laguna, New Mexico, a digital three-dimensional geologic framework model was constructed for the Rio San Jose and its surface-water drainage basin in west-central New Mexico. This three-dimensional model defines the altitude, thickness, and extent of 18 geologic units for use in a regional numerical hydrologic model. The model included an undifferentiated Proterozoic basement layer, 13 consolidated Paleozoic and Mesozoic rock units, and 4 Cenozoic units. Model input data were compiled from published cross sections, well data, structure contour maps, selected geophysical data, and data derived from geologic maps and structural features in the study area. These data were used to construct faulted surfaces that represent the upper and lower subsurface geologic unit boundaries. The digital three-dimensional geologic framework model combines faults, the altitude of the tops of each geologic unit, and boundary lines depicting the subsurface extent of each geologic unit. The digital three-dimensional geologic model described in this report and the corresponding data release represents the generalized geometry of the subsurface geologic units; it reproduces with reasonable accuracy the input geologic data and is consistent with previously published subsurface conceptualizations of the region. The geologic framework model is at a scale and resolution appropriate for use as the foundation for a numerical hydrologic model of the study area.

New Mexico↗
USGS2012

Analytical resource assessment method for continuous (unconventional) oil and gas accumulations - The "ACCESS" Method

The U.S. Geological Survey (USGS) periodically assesses petroleum resources of areas within the United States and the world. The purpose of this report is to explain the development of an analytic probabilistic method and spreadsheet software system called Analytic Cell-Based Continuous Energy Spreadsheet System (ACCESS). The ACCESS method is based upon mathematical equations derived from probability theory. The ACCESS spreadsheet can be used to calculate estimates of the undeveloped oil, gas, and NGL (natural gas liquids) resources in a continuous-type assessment unit. An assessment unit is a mappable volume of rock in a total petroleum system. In this report, the geologic assessment model is defined first, the analytic probabilistic method is described second, and the spreadsheet ACCESS is described third. In this revised version of Open-File Report 00-044 , the text has been updated to reflect modifications that were made to the ACCESS program. Two versions of the program are added as appendixes.

Open-File Report↗
USGS2021

A numerical model for the cooling of a lava sill with heat pipe effects

Understanding the cooling process of volcanic intrusions into wet sediments is a difficult but important problem, given the presence of extremely large temperature gradients and potentially complex water-magma interactions. This report presents a numerical model to study such interactions, including the effect of heat pipes on the cooling of volcanic intrusions. Udell (1985) has shown that heat pipes may develop in heated saturated granular media under laboratory conditions. In previous work, Baker and others (2015) calculated temperatures in the vicinity of a volcanic sill that intruded into wet sediment, showing an unexpected temperature profile in which peak temperatures remained near constant over a region extending a meter above and below the sill. This is challenging to explain with conduction or convection heating methods but is predicted if the heat transfer is performed primarily by a heat pipe. We have numerically modeled the cooling of a lava sill under similar circumstances, using the experimental findings of Udell (1985) to estimate the characteristics of the heat pipe. We have constructed a model using Microsoft C#.NET, complete with an intuitive graphical user interface. The model is available from the U.S. Geological Survey and is capable of being run on Microsoft Windows 7 and higher with modest hardware. We find that the resulting overall temperature profile has some key similarities to the profile inferred by Baker and others (2015). Future models including more detailed convective heat transfer physics will be necessary to fully reproduce the effects of boiling in sediments.

Techniques and Methods↗