Publications
This list of Water Resources Mission Area publications includes both official USGS publications and journal articles authored by our scientists. A searchable database of all USGS publications can be accessed at the USGS Publications Warehouse.
Filter Total Items: 18995
Computing discharge using the entropy-based probability concept Computing discharge using the entropy-based probability concept
This report describes the techniques and methods for computing the mean-channel velocity and discharge using the entropy-based probability concept (probability concept). The method is an alternative to or augments standard streamgaging methods adopted by the U.S. Geological Survey (USGS). Although sensor technology for measuring the mean velocity and discharge has advanced, standard...
Authors
John Fulton, Frank Engel, Jack R. Eggleston, Chao-Lin Chiu
Multidecadal change in pesticide concentrations relative to human health benchmarks in the Nation’s groundwater Multidecadal change in pesticide concentrations relative to human health benchmarks in the Nation’s groundwater
Groundwater-quality trend assessments identify aquifers that are responding to changes in pesticide use and the compounds that may pose a threat to water availability. The U.S. Geological Survey has been monitoring pesticide concentrations in groundwater for 25 principal aquifers across the conterminous United States since 1993. The groundwater well locations represent a range of soils...
Authors
Sarah Stackpoole, Bruce Lindsey, Cee Nell
Quantifying groundwater response and uncertainty in beaver-influenced mountainous floodplains using machine learning-based model calibration Quantifying groundwater response and uncertainty in beaver-influenced mountainous floodplains using machine learning-based model calibration
Beavers (Castor canadensis) alter river corridor hydrology by creating ponds and inundating floodplains, and thereby improving surface water storage. However, the impact of inundation on groundwater, particularly in mountainous alluvial floodplains with permeable gravel/cobble layers overlain by a soil layer, remains uncertain. Numerical modeling across various floodplain structures...
Authors
Lijing Wang, Tristan Babey, Zach Perzan, Samuel Pierce, Martin Briggs, Kristin Boye, Kate Maher
PFAS sampling activities in the U.S. Geological Survey national networks PFAS sampling activities in the U.S. Geological Survey national networks
Per- and polyfluoroalkyl substances (PFAS), frequently called “forever chemicals,” are used for a wide variety of industrial purposes and are often found in common household and industrial items such as firefighting foams, non-stick cookware, and water-resistant materials. The contamination of water, air, and soil by PFAS is a national and global issue due to their widespread occurrence...
Authors
Melissa Riskin, Bruce Lindsey, Ryan McCammon
Sundial: A method for inferring image acquisition time from shadow orientation Sundial: A method for inferring image acquisition time from shadow orientation
Aerial photography and satellite imagery can be used to characterize landscape change over time and help to understand how these changes are related to climate and hydrology. Publicly available optical imagery from sources such as the United States National Agricultural Imagery Program (NAIP) is particularly valuable in this context due to its high temporal and spatial resolution...
Authors
Inhyeok Bae, Carl Legleiter, Elowyn Yager
Hyperspectral imaging of river bathymetry using an ensemble of regression trees Hyperspectral imaging of river bathymetry using an ensemble of regression trees
Remote sensing has emerged as an effective tool for characterizing river systems, and machine learning (ML) techniques could make this approach even more powerful. To explore this possibility, we developed an ML-based workflow for hyperspectral imaging of river bathymetry using an ensemble of regression trees (HIRBERT). This approach involves using paired observations of depth and...
Authors
Carl Legleiter, Paul Kinzel, Brandon Overstreet, Lee Harrison
The influence of scale in modeling social vulnerability and disaster assistance The influence of scale in modeling social vulnerability and disaster assistance
Understanding how social vulnerability relates to disaster impacts is critical for addressing social equity, yet the role of spatial scale in this relationship is often overlooked. Most studies use aggregated data, risking ecological fallacy—misinterpreting individual outcomes from group-level data. This study examines how spatial scale influences the relationship between social...
Authors
Sina Razzaghi Asl, Oronde Drakes, Eric Tate, Samuel Brody, Wesley Highfield, Kayode Atoba
A spatiotemporal deep learning approach for predicting daily air-water temperature signal coupling and identification of key watershed physical parameters in a montane watershed A spatiotemporal deep learning approach for predicting daily air-water temperature signal coupling and identification of key watershed physical parameters in a montane watershed
Seasonal shifts from runoff to groundwater dominance influence daily headwater stream temperatures, especially where local groundwater input is strong. This input buffers temperature during hot periods, supporting cold-water habitats. Recent studies use air–water temperature signal metrics to identify zones of strong stream–groundwater connectivity. While Previous studies used air–water...
Authors
Mohammad Reza Behbahani, David M. Rey, Martin Briggs, Amvrossios Bagtzoglou
Projecting stream water quality using Weighted Regression on Time, Discharge, and Season (WRTDS): An example with drought conditions in the Delaware River Basin Projecting stream water quality using Weighted Regression on Time, Discharge, and Season (WRTDS): An example with drought conditions in the Delaware River Basin
Future water availability depends on understanding the responses of constituent concentrations to hydrologic change. Projecting future water quality remains a methodological challenge, particularly when using discrete observations with limited temporal resolution. This study introduces Weighted Regression on Time, Discharge, and Season for Projection (WRTDS-P), a novel, computationally...
Authors
Christopher Green, Robert Hirsch, Hedeff Essaid, Ward Sanford
U.S. Geological Survey monitoring milestones—Chagrin River at Willoughby, OH (04209000) U.S. Geological Survey monitoring milestones—Chagrin River at Willoughby, OH (04209000)
The Chagrin River at Willoughby, OH (04209000), streamgage is the 1,000th U.S. Geological Survey (USGS) streamgage to reach Centennial status. Centennial Streamgages are USGS streamgages that have been in operation for 100 years or more. Collecting water data since 1925, it celebrated its 100th birthday on August 1, 2025.
Authors
Claire Bunch
Monitoring cyanobacteria temporal trends in a hypereutrophic lake using remote sensing: From multispectral to hyperspectral Monitoring cyanobacteria temporal trends in a hypereutrophic lake using remote sensing: From multispectral to hyperspectral
Cyanobacterial harmful algal blooms (cyanoHABs) and associated cyanotoxins are a concern for inland waters. Due to the extensive spatial coverage and frequent availability of satellite images, multispectral remote sensing tools demonstrate utility for monitoring these blooms. The next frontier for remote sensing of cyanoHABs in inland waters is hyperspectral data. Recent and upcoming...
Authors
Samantha Sharp, Alicia Cortes, Alexander Forrest, Carl Legleiter, Liane Guild, Yufang Jin, S. Schladow
Evaluation of daily stream temperature predictions (1979-2021) across the contiguous United States using a spatiotemporal aware machine learning algorithm Evaluation of daily stream temperature predictions (1979-2021) across the contiguous United States using a spatiotemporal aware machine learning algorithm
Stream temperature controls a variety of physical and biological processes that affect ecosystems, human health, and economic activities. We used 42 years (1979–2021) of data to predict daily summary statistics of stream temperature across >50,000 stream reaches in the contiguous United States using a recurrent graph convolution network. We comprehensively documented the performance –...
Authors
Jeremy Diaz, Samantha Oliver, Galen Gorski