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: 19021
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 J. 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 J. Legleiter, Paul J. Kinzel, Brandon Overstreet, Lee R. Harrison
Toward a new framework to evaluate process-based model configurations and quantify data worth prior to calibration Toward a new framework to evaluate process-based model configurations and quantify data worth prior to calibration
Model criticism, discrimination, and selection methods often rely on calibrated model outputs. Because calibration can be computationally expensive, model criticism can first be undertaken by assessing model outputs obtained from limited prior parameter ensembles. However, such prior-based methods are often heuristic and do not formalize the notion of balancing model consistency with...
Authors
Mark Shannon Pleasants, Michael N. Fienen, Hedeff I. Essaid, Joel D. Blomquist, Jing Yang, Ming Ye
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 Oliver Drakes, Eric Tate, Samuel D. Brody, Wesley Highfield, Kayode Atoba
Clarifying the trophic state concept to advance macroscale freshwater science and management Clarifying the trophic state concept to advance macroscale freshwater science and management
For over a century, ecologists have used the concept of trophic state (TS) to characterize an aquatic ecosystem's biological productivity. However, multiple TS classification schemes, each relying on a variety of measurable parameters as proxies for productivity, have emerged to meet use-specific needs. Frequently, chlorophyll a, phosphorus, and Secchi depth are used to classify TS based...
Authors
Michael Frederick Meyer, Benjamin M. Kraemer, Carolina C. Barbosa, Davi G.F. Cuhna, Walter Dodds, Stephanie E. Hampton, César Ordóñez, Rachel M. Pilla, Amina Pollard, Joshua A. Culpepper, Alexander K. Fremier, Tyler V. King, Robert Ladwig, Dina M. Leech, Shin-Ichiro S. Matsuzaki, Isabella Oleksy, Simon N. Topp, Richard Woolway, Ludmila S Brighenti, Kate Colleen Fickas, Brian P. Lanouette, Jianning Ren, Mortimer Werther, Xiao Yang
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 M. Behbahani, David M. Rey, Martin A. 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 M. Hirsch, Hedeff Essaid, Ward E. 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 L. Sharp, Alicia Cortes, Alexander L. Forrest, Carl J. Legleiter, Liane S. Guild, Yufang Jin, S. Geoffrey 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 Alejandro Diaz, Samantha K. Oliver, Galen Gorski
The U.S. Geological Survey National Water Quality Network—Surface Water, 2024 The U.S. Geological Survey National Water Quality Network—Surface Water, 2024
The U.S. Geological Survey (USGS) National Water Quality Network for surface water (NWQN-SW) was established in 2013 to develop long-term, comparable assessments of surface-water quality in support of national, regional, State, and local needs related to water-quality management and policy. Water-quality samples are collected at each site and measured for a variety of constituents. In...
Authors
Melissa L. Riskin
Performance mapping and weighting for the evapotranspiration models of the OpenET ensemble Performance mapping and weighting for the evapotranspiration models of the OpenET ensemble
Evapotranspiration (ET) accounts for the majority of water available from precipitation in the terrestrial water cycle, and improvements to the accuracy, resolution, and coverage of ET data can enhance hydrologic models and assessments. The OpenET collaboration of six remotely sensed ET modeling teams has demonstrated that an ensemble approach to ET estimation generally provides improved...
Authors
Meredith Reitz, J. M. Volk, T. Ott, M. Anderson, Gabriel Senay, F. Melton, A. Kilic, R. Allen, J. B. Fisher, Anderson Ruhoff, A.J. Purdy, J. Huntington