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Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

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At least 1,063 records · Page 59Linked to original sources

USGS1987

Microprocessor-based data-acquisition system for a borehole radar

An efficient microprocessor-based system has been implemented that permits real-time acquisition, stacking, and digital recording of data generated by a borehole radar system. Although the system digitizes, stacks, and records independently of a computer, it is interfaced to a desktop computer for program control over system parameters such as sampling interval, number of samples, number of times the data are stacked prior to recording on nine-track tape, and for graphics display of the digitized data. The data can be transferred to the desktop computer during recording, or played back from a tape at a later time. Using the desktop computer, the operator can observe results while recording data and generate hard-copy graphics in the field. Thus, the radar operator can immediately evaluate the quality of data being obtained, modify system parameters, study the radar logs before leaving the field, and re-run borehole logs if necessary. The system has proven to be reliable in the field and has increased productivity both in the field and in the laboratory.

IEEE Transactions on Geoscience and Remote Sensing↗

USGS2020

msocc: Fit and analyse computationally efficient multi‐scale occupancy models in R

Environmental DNA (eDNA) sampling is a promising tool for the detection of rare and cryptic taxa, such as aquatic pathogens, parasites and invasive species. Environmental DNA sampling workflows commonly rely on multi‐stage hierarchical sampling designs that induce complicated dependencies within the data. This complex dependence structure can be intuitively modelled with Bayesian multi‐scale occupancy models. However, current software for such models are computationally demanding, impeding their use. We present an r package, msocc , that implements a data augmentation strategy to fit fully Bayesian, computationally efficient multi‐scale occupancy models. The msocc package allows users to fit multi‐scale occupancy models, to estimate and visualize posterior summaries of site, sample and replicate‐level occupancy, and to compare different models using Bayesian information criterion. Additionally, we provide a supplemental web application that allows users to investigate study design for multi‐scale occupancy models and acts as a graphical user interface to the msocc package. The utility of the msocc package is illustrated on a published dataset and the functions in msocc are compared to the primary Bayesian toolkit for multi‐scale occupancy modelling, eDNAoccupancy , using various computational benchmarks. These benchmarks indicate that msocc is capable of fitting models 50 times faster than eDNAoccupancy . We hope that access to software that efficiently fits, analyses and conducts study design investigations for multi‐scale occupancy models facilitates their implementation by the research and wildlife management communities.

Methods in Ecology and Evolution↗

USGS2021

TrendPowerTool: A lookup tool for estimating the statistical power of a monitoring program to detect population trends

A simulation-based power analysis can be used to estimate the sample sizes needed for a successful monitoring program, but requires technical expertise and sometimes extensive computing resources. We developed a web-based lookup app, called TrendPowerTool ( https://www.usgs.gov/apps/TrendPowerTool/ ), to provide guidance for ecological monitoring programs when resources are not available for a simulation-based power analysis. TrendPowerTool is implemented through the shiny package in R, but is accessible through a webpage without the need for users to install any software. By drawing on results of 1.4 million scenarios that we simulated on a supercomputer, TrendPowerTool quickly and easily provides an estimate of the statistical power to detect a population trend of a particular magnitude with a planned monitoring program, based on user-specified parameters for the monitoring design and population of interest. TrendPowerTool provides a user-friendly interface that retrieves results instantaneously, facilitating the important step of conducting a power analysis when designing monitoring programs.

Conservation Science and Practice↗

USGS2023

Factors associated with Paddlefish (Polyodon spathula) restoration success in Oklahoma

The Paddlefish ( Polyodon spathula) has been extirpated from portions of its native range due to anthropogenic habitat degradation and fragmentation, most notably the impoundment of rivers. To mitigate some of these losses in Oklahoma, Paddlefish have been stocked into reservoirs throughout the state, with variable success in establishing self-sustaining populations. Two factors thought to contribute to success of Paddlefish stocking are spawning substrate and prey availability, which were quantified in six reservoirs and nine reservoir tributaries. Side-scan sonar and supervised classification of aerial imagery were used to classify 4517-ha of river substrate upstream of the river-reservoir interface in reservoir tributaries. Zooplankton community structure, water clarity, and nutrient availability were also assessed in the same reservoirs and tributaries. One tributary had suitable spawning substrate (>40%), and the rest had minimal (<1.5%), which suggested that availability of suitable spawning substrate was not directly correlated with Paddlefish stocking success. Reservoirs with self-sustaining Paddlefish populations had higher abundance of large zooplankton (copepods and cladocerans) than reservoirs without a reproducing population. Notably, tributaries associated with Lake Texoma, the one known example of failed restoration, were much more turbid than other rivers. We conclude that abiotic factors such as water clarity may contribute more to variable recruitment than spawning substrate or zooplankton abundance by mediating foraging success of Paddlefish post-larvae.

Oklahoma↗

USGS2013

Lake shoreline in the contiguous United States: Quantity, distribution and sensitivity to observation resolution

1. Quantifying lake biogeochemical processing at broad spatial scales requires that we scale processes along with physical metrics. Past work has primarily scaled lentic processes using estimates of lake surface area. However, many processes important to lakes, such as material, energy and biological ﬂuxes and biogeochemical cycling, scale with lake perimeter. 2. We estimate the total lake perimeter for the contiguous United States (U.S.) and examine the sensitivity of this estimate to measurement resolution. At the original mapping resolution, lakes in the contiguous U.S. have a total perimeter of over 1.8 million km. 3. The change in measured perimeter versus measurement resolution for the contiguous U.S. had a log-log slope (also known as the fractal dimension) of 0.21, generally less than previously reported estimates. With changing observation resolution, total measured perimeter was most sensitive to the inclusion or exclusion of small lakes, not shoreline complexity. 4. The total aquatic–terrestrial interface in lakes is less than one-tenth that of streams and rivers, which collectively account for over 21 million km of shoreline in the contiguous U.S. This study further describes the distribution of lake perimeter and proposes a technique that can contribute to understanding continental-scale processes.

Freshwater Biology↗

USGS2015

Unifying research on the fragmentation of terrestrial and aquatic habitats: patches, connectivity and the matrix in riverscapes

While there is an increasing emphasis in terrestrial ecology on determining the influence of the area that surrounds habitat patches (the landscape ‘matrix’) relative to the characteristics of the patches themselves, research on these aspects in running waters is still rather underrepresented. Here we outline conceptual foundations of matrix ecology for stream and river ecosystems (‘riverscapes’). We discuss how a hierarchical, patch-based perspective is necessary for the delineation of habitat patches and the surrounding matrix, through which we may identify two classes of habitat edges in riverscapes (i.e. edges between the terrestrial–aquatic interface and edges within streams). Under this conceptual framework, we discuss the role of the matrix in influencing between-patch movement, and resource quality and quantity within and among habitat patches in riverscapes. We also review types of empirical and modelling approaches which may advance our understanding of fragmentation effects in these systems. We identify five key challenges for understanding fragmentation and matrix effects more completely: (i) defining populations and their status (i.e. quantifying the demographic contribution of habitat patches to metapopulation dynamics), (ii) scaling from metapopulations to metacommunities (particularly searching for generalities in species responses to landscape heterogeneity), (iii) scaling from metacommunities to metaecosystems (i.e. exploring the interactive role of the terrestrial–aquatic and within-stream matrix effects on the flow of material and energy at the network scale), (iv) understanding temporal dynamics in matrix permeability and (v) revealing the utility of different patch and matrix representations for modelling connectivity relationships. Fragmentation of habitats is a critical issue in the conservation and management of stream networks across spatial scales. Although the effects of individual barriers (e.g. dams) are well documented, we argue that a more comprehensive patch–matrix landscape model will improve our understanding of fragmentation effects and improve management in riverscapes.

Freshwater Biology↗

USGS2015

Estuarine fish communities respond to climate variability over both river and ocean basins

Estuaries are dynamic environments at the land–sea interface that are strongly affected by interannual climate variability. Ocean–atmosphere processes propagate into estuaries from the sea, and atmospheric processes over land propagate into estuaries from watersheds. We examined the effects of these two separate climate-driven processes on pelagic and demersal fish community structure along the salinity gradient in the San Francisco Estuary, California, USA. A 33-year data set (1980–2012) on pelagic and demersal fishes spanning the freshwater to marine regions of the estuary suggested the existence of five estuarine salinity fish guilds: limnetic (salinity = 0–1), oligohaline (salinity = 1–12), mesohaline (salinity = 6–19), polyhaline (salinity = 19–28), and euhaline (salinity = 29–32). Climatic effects propagating from the adjacent Pacific Ocean, indexed by the North Pacific Gyre Oscillation (NPGO), affected demersal and pelagic fish community structure in the euhaline and polyhaline guilds. Climatic effects propagating over land, indexed as freshwater outflow from the watershed (OUT), affected demersal and pelagic fish community structure in the oligohaline, mesohaline, polyhaline, and euhaline guilds. The effects of OUT propagated further down the estuary salinity gradient than the effects of NPGO that propagated up the estuary salinity gradient, exemplifying the role of variable freshwater outflow as an important driver of biotic communities in river-dominated estuaries. These results illustrate how unique sources of climate variability interact to drive biotic communities and, therefore, that climate change is likely to be an important driver in shaping the future trajectory of biotic communities in estuaries and other transitional habitats.

California↗

USGS2015

Human activities and climate variability drive fast-paced change across the world's estuarine-coastal ecosystems

Time series of environmental measurements are essential for detecting, measuring and understanding changes in the Earth system and its biological communities. Observational series have accumulated over the past 2–5 decades from measurements across the world's estuaries, bays, lagoons, inland seas and shelf waters influenced by runoff. We synthesize information contained in these time series to develop a global view of changes occurring in marine systems influenced by connectivity to land. Our review is organized around four themes: (i) human activities as drivers of change; (ii) variability of the climate system as a driver of change; (iii) successes, disappointments and challenges of managing change at the sea-land interface; and (iv) discoveries made from observations over time. Multidecadal time series reveal that many of the world's estuarine–coastal ecosystems are in a continuing state of change, and the pace of change is faster than we could have imagined a decade ago. Some have been transformed into novel ecosystems with habitats, biogeochemistry and biological communities outside the natural range of variability. Change takes many forms including linear and nonlinear trends, abrupt state changes and oscillations. The challenge of managing change is daunting in the coastal zone where diverse human pressures are concentrated and intersect with different responses to climate variability over land and over ocean basins. The pace of change in estuarine–coastal ecosystems will likely accelerate as the human population and economies continue to grow and as global climate change accelerates. Wise stewardship of the resources upon which we depend is critically dependent upon a continuing flow of information from observations to measure, understand and anticipate future changes along the world's coastlines.

Global Change Biology↗

USGS2015

Beyond just sea-level rise: Considering macroclimatic drivers within coastal wetland vulnerability assessments to climate change

Due to their position at the land-sea interface, coastal wetlands are vulnerable to many aspects of climate change. However, climate change vulnerability assessments for coastal wetlands generally focus solely on sea-level rise without considering the effects of other facets of climate change. Across the globe and in all ecosystems, macroclimatic drivers (e.g., temperature and rainfall regimes) greatly influence ecosystem structure and function. Macroclimatic drivers have been the focus of climate-change related threat evaluations for terrestrial ecosystems, but largely ignored for coastal wetlands. In some coastal wetlands, changing macroclimatic conditions are expected to result in foundation plant species replacement, which would affect the supply of certain ecosystem goods and services and could affect ecosystem resilience. As examples, we highlight several ecological transition zones where small changes in macroclimatic conditions would result in comparatively large changes in coastal wetland ecosystem structure and function. Our intent in this communication is not to minimize the importance of sea-level rise. Rather, our overarching aim is to illustrate the need to also consider macroclimatic drivers within vulnerability assessments for coastal wetlands.

Global Change Biology↗

USGS2013

1DTempPro: analyzing temperature profiles for groundwater/surface-water exchange

A new computer program, 1DTempPro, is presented for the analysis of vertical one-dimensional (1D) temperature profiles under saturated flow conditions. 1DTempPro is a graphical user interface to the U.S. Geological Survey code Variably Saturated 2-Dimensional Heat Transport (VS2DH), which numerically solves the flow and heat-transport equations. Pre- and postprocessor features allow the user to calibrate VS2DH models to estimate vertical groundwater/surface-water exchange and also hydraulic conductivity for cases where hydraulic head is known.

Ground Water↗

USGS2014

Geophysical and hydrologic studies of lake seepage variability

Variations in lake seepage were studied along a 130 m shoreline of Mirror Lake NH. Seepage was downward from the lake to groundwater; rates measured from 28 seepage meters varied from 0 to −282 cm/d. Causes of this variation were investigated using electrical resistivity surveys and lakebed sediment characterization. Two-dimensional (2D) resistivity surveys showed a transition in lakebed sediments from outwash to till that correlated with high- and low-seepage zones, respectively. However, the 2D survey was not able to predict smaller scale variations within these facies. In the outwash, fast seepage was associated with permeability variations in a thin (2 cm) layer of sediments at the top of the lakebed. In the till, where seepage was slower than that in the outwash, a three-dimensional resistivity survey mapped a point of high seepage associated with heterogeneity (lower resistivity and likely higher permeability). Points of focused flow across the sediment–water interface are difficult to detect and can transmit a large percentage of total exchange. Using a series of electrical resistivity geophysical methods in combination with hydrologic data to locate heterogeneities that affect seepage rates can help guide seepage meter placement. Improving our understanding of the causes and types of heterogeneity in lake seepage will provide better data for lake budgets and prediction of mass transfer of solutes or contaminants between lakes and groundwater.

Groundwater↗

USGS2015

1DTempPro V2: new features for inferring groundwater/surface-water exchange

A new version of the computer program 1DTempPro extends the original code to include new capabilities for (1) automated parameter estimation, (2) layer heterogeneity, and (3) time-varying specific discharge. The code serves as an interface to the U.S. Geological Survey model VS2DH and supports analysis of vertical one-dimensional temperature profiles under saturated flow conditions to assess groundwater/surface-water exchange and estimate hydraulic conductivity for cases where hydraulic head is known.

Groundwater Monitoring & Remediation↗

USGS2016

Scripting MODFLOW model development using Python and FloPy

Graphical user interfaces (GUIs) are commonly used to construct and postprocess numerical groundwater flow and transport models. Scripting model development with the programming language Python is presented here as an alternative approach. One advantage of Python is that there are many packages available to facilitate the model development process, including packages for plotting, array manipulation, optimization, and data analysis. For MODFLOW-based models, the FloPy package was developed by the authors to construct model input files, run the model, and read and plot simulation results. Use of Python with the available scientific packages and FloPy facilitates data exploration, alternative model evaluations, and model analyses that can be difficult to perform with GUIs. Furthermore, Python scripts are a complete, transparent, and repeatable record of the modeling process. The approach is introduced with a simple FloPy example to create and postprocess a MODFLOW model. A more complicated capture-fraction analysis with a real-world model is presented to demonstrate the types of analyses that can be performed using Python and FloPy.

Groundwater↗

USGS2017

Scenario Evaluator for Electrical Resistivity survey pre-modeling tool

Geophysical tools have much to offer users in environmental, water resource, and geotechnical fields; however, techniques such as electrical resistivity imaging (ERI) are often oversold and/or overinterpreted due to a lack of understanding of the limitations of the techniques, such as the appropriate depth intervals or resolution of the methods. The relationship between ERI data and resistivity is nonlinear; therefore, these limitations depend on site conditions and survey design and are best assessed through forward and inverse modeling exercises prior to field investigations. In this approach, proposed field surveys are first numerically simulated given the expected electrical properties of the site, and the resulting hypothetical data are then analyzed using inverse models. Performing ERI forward/inverse modeling, however, requires substantial expertise and can take many hours to implement. We present a new spreadsheet-based tool, the Scenario Evaluator for Electrical Resistivity (SEER), which features a graphical user interface that allows users to manipulate a resistivity model and instantly view how that model would likely be interpreted by an ERI survey. The SEER tool is intended for use by those who wish to determine the value of including ERI to achieve project goals, and is designed to have broad utility in industry, teaching, and research.

Groundwater↗

USGS2018

VS2DRTI: Simulating heat and reactive solute transport in variably saturated porous media

Variably saturated groundwater flow, heat transport, and solute transport are important processes in environmental phenomena, such as the natural evolution of water chemistry of aquifers and streams, the storage of radioactive waste in a geologic repository, the contamination of water resources from acid-rock drainage, and the geologic sequestration of carbon dioxide. Up to now, our ability to simulate these processes simultaneously with fully coupled reactive transport models has been limited to complex and often difficult-to-use models. To address the need for a simple and easy-to-use model, the VS2DRTI software package has been developed for simulating water flow, heat transport, and reactive solute transport through variably saturated porous media. The underlying numerical model, VS2DRT, was created by coupling the flow and transport capabilities of the VS2DT and VS2DH models with the equilibrium and kinetic reaction capabilities of PhreeqcRM. Flow capabilities include two-dimensional, constant-density, variably saturated flow; transport capabilities include both heat and multicomponent solute transport; and the reaction capabilities are a complete implementation of geochemical reactions of PHREEQC. The graphical user interface includes a preprocessor for building simulations and a postprocessor for visual display of simulation results. To demonstrate the simulation of multiple processes, the model is applied to a hypothetical example of injection of heated waste water to an aquifer with temperature-dependent cation exchange. VS2DRTI is freely available public domain software.

Groundwater↗

USGS2018

MoisturEC: a new R program for moisture content estimation from electrical conductivity data

Noninvasive geophysical estimation of soil moisture has potential to improve understanding of flow in the unsaturated zone for problems involving agricultural management, aquifer recharge, and optimization of landfill design and operations. In principle, several geophysical techniques (e.g., electrical resistivity, electromagnetic induction, and nuclear magnetic resonance) offer insight into soil moisture, but data‐analysis tools are needed to “translate” geophysical results into estimates of soil moisture, consistent with (1) the uncertainty of this translation and (2) direct measurements of moisture. Although geostatistical frameworks exist for this purpose, straightforward and user‐friendly tools are required to fully capitalize on the potential of geophysical information for soil‐moisture estimation. Here, we present MoisturEC, a simple R program with a graphical user interface to convert measurements or images of electrical conductivity (EC) to soil moisture. Input includes EC values, point moisture estimates, and definition of either Archie parameters (based on experimental or literature values) or empirical data of moisture vs. EC. The program produces two‐ and three‐dimensional images of moisture based on available EC and direct measurements of moisture, interpolating between measurement locations using a Tikhonov regularization approach.

Groundwater↗

USGS2025

A new groundwater energy transport model for the MODFLOW hydrologic simulator

Heat transport in the subsurface is an important aspect of research related to the effects of a warming climate on ecological services (i.e., cold-water refugia); the development of geothermal resources for energy banking schemes (i.e., aquifer thermal energy storage [ATES]); and the effects of temperature on other aspects of groundwater quality, such as nutrient cycling. Historically, simulation of heat transport using the MODFLOW groundwater simulator and related codes was performed by scaling the input parameters of a solute-transport model to emulate heat transport. However, that approach required additional pre- and post-processing of input and output and could not account for the variation in effective thermal storage and transport properties during transient, unsaturated flow, for example. True heat-transport capabilities in the context of MODFLOW were first introduced in a variant called USG-Transport. More recently, a new groundwater energy-transport (GWE) model type has been added to MODFLOW 6, the core version of the MODFLOW hydrologic simulator. GWE supports the simulation of heat transport on structured or unstructured grids as well as within and between features of advanced packages that represent streams, lakes, multi-aquifer wells, and the unsaturated zone. GWE is integrated within MODFLOW 6 and is accessible through the FloPy Python package and the MODFLOW 6 application programming interface (API). An example simulation demonstrates conduction between grid cells through both the water and the solid aquifer material, including thermal bleeding from saturated overburden cells into a groundwater flow field.

Groundwater↗

USGS2025

ARCHI: A new R package for automated imputation of regionally correlated hydrologic records

Missing data in hydrological records can limit resource assessment, process understanding, and predictive modeling. Here, we present ARCHI (Automated Regional Correlation Analysis for Hydrologic Record Imputation), a new, open-source software package in R designed to aggregate, impute, cluster, and visualize regionally correlated hydrologic records. ARCHI imputes missing data in “target” records by linear regression using more complete “reference” records as predictors. Automated imputation is implemented using a novel, iterative algorithm that allows each site to be considered a target or reference for regression, growing the pool of complete references with each imputed record until viable gap-filling ceases. Users can limit artifacts from spurious correlations by specifying model-acceptance criteria and applying geospatial, correlation, and group-based filters to control reference selection. ARCHI provides additional functions for visualizing results, clustering records with similar correlation structures, evaluating holdout data, and interactive parameterization with an accessible and intuitive graphical user interface (GUI). This methods brief provides an overview of the ARCHI package, modeling guidelines, and benchmarking on two regional groundwater-level datasets from the Central Valley, CA and Long Island, NY. We evaluate ARCHI alongside widely used multivariate imputation software to highlight and contextualize its computational efficiency, imputation accuracy, and model transparency when applied to large, groundwater-level datasets.

California, New York↗