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: 18960
Remote sensing of river discharge based on critical flow theory
Critical flow theory provides a physical foundation for inferring discharge from measurements of wavelength and channel width made from images. In rivers with hydraulically steep local slopes greater than∼0.01, flow velocities are high and the Froude number F r (ratio of inertial to gravitational forces) can approach 1.0 (critical flow) or greater. Under these conditions, undular...
Authors
Carl J. Legleiter, Gordon E. Grant, Inhyeok Bae, Becky Fasth, Elowyn Yager, Daniel C. White, Laura A. Hempel, Merritt Elizabeth Harlan, Christina Leonard, Robert W. Dudley
Fine-resolution satellite remote sensing improves spatially distributed snow modeling to near real time
Given the highly variable distribution of seasonal snowpacks in complex mountainous environments, the accurate snow modeling of basin-wide snow water equivalent (SWE) requires a spatially distributed approach at a sufficiently fine grid resolution (
Authors
Graham A. Sexstone, Garrett Alexander Akie, David J. Selkowitz, Theodore B. Barnhart, David M. Rey, Claudia León-Salazar, Emily Carbone, Lindsay A. Bearup
One-hundred fundamental, open questions to integrate methodological approaches in lake ice research
The rate of technological innovation within aquatic sciences outpaces the collective ability of individual scientists within the field to make appropriate use of those technologies. The process of in situ lake sampling remains the primary choice to comprehensively understand an aquatic ecosystem at local scales; however, the impact of climate change on lakes necessitates the rapid...
Authors
Joshua Culpepper, Sapna Sharma, Grant Gunn, Madeline Magee, Michael Frederick Meyer, Eric Anderson, Christoper D. Arp, Sarah Cooley, Wayana Dolan, Hilary Dugan, Claude R. Duguay, Benjamin C. Jones, Georgiy Kirillin, Robert Ladwig, Matti Lepparanta, Di Long, John J. Magnuson, Tamlin Pavelsky, Sebastiano Piccolroaz, Dale M. Robertson, Bethel Steele, Manu Tom, Gesa A. Weyhenmeyer, R. Iesytn Woolway, Marguerite A. Xenopoulos, Xiao Yang
Gaps in water quality modeling of hydrologic systems
This review assesses gaps in water quality modeling, emphasizing opportunities to improve next-generation models that are essential for managing water quality and are integral to meeting goals of scientific and management agencies. In particular, this paper identifies gaps in water quality modeling capabilities that, if addressed, could support assessments, projections, and evaluations...
Authors
Lisa Lucas, Craig J. Brown, Dale M. Robertson, Nancy T. Baker, Zachary Johnson, Christopher T. Green, Se Jong Cho, Melinda Erickson, Allen C. Gellis, Jeramy Roland Jasmann, Noah Knowles, Andreas Prein, Paul E. Stackelberg
RIce-Net: Integrating ground-based cameras and machine learning for automated river ice detection
River ice plays a critical role in controlling streamflow in cold regions. The U.S. Geological Survey (USGS) qualifies affected water-level measurements and inferred streamflow by ice conditions at a date later than the day of the actual measurements. This study introduces a novel computer vision-based framework, River Ice-Network (RIce-Net), that uses the USGS nationwide network of...
Authors
Mahmoud Ayyad, Marouane Temini, Mohamed Abdelkader, Moheb Henein, Frank L. Engel, R. Russell Lotspeich, John R. Eggleston
Identifying preferential flow from soil moisture time series: Review of methodologies
Identifying and quantifying preferential flow (PF) through soil—the rapid movement of water through spatially-distinct pathways in the subsurface—is vital to understanding how the hydrologic cycle responds to climate, land cover, and anthropogenic changes. In recent decades, methods have been developed that use measured soil moisture time series to identify PF. Because they allow for...
Authors
John R. Nimmo, Inge Wiekenkamp, Ryoko Araki, Jannis Groh, Nitin Singh, Octavia Crompton, Briana Wyatt, Hoori Ajami, Daniel Gimenez, Daniel Hirmas, Pamela L. Sullivan, Matthias Sprenger
Neural network-based temporal ensembling of water depth estimates derived from SuperDove Images
CubeSats provide a wealth of high-frequency observations at a meter-scale spatial resolution. However, most current methods of inferring water depth from satellite data consider only a single image. This approach is sensitive to the radiometric quality of the data acquired at that particular instant in time, which could be degraded by various confounding factors, such as sun glint or...
Authors
Milad Niroumand-Jadidi, Carl J. Legleiter, Francesca Bovolo
Evaluating the applicability of the generalized power-law rating curve model: With applications to paired discharge-stage data from Iceland, Sweden, and the United States
Hydrologic research and operations make extensive use of streamflow time series. In most applications, these time series are estimated from rating curves, which relate flow to some easy-to-measure surrogate, typically stage. The conventional stage-discharge rating takes the form of a segmented power law, with one segment for each hydrologic control at the stream gauge. However, these...
Authors
Rafael Daniel Vias, Birgir Hrafnkelsson, Timothy O. Hodson, Sölvi Rögnvaldsson, Axel Örn Jansson, Sigurdur M. Gardarsson
A generalized framework for inferring river bathymetry from image-derived velocity fields
Although established techniques for remote sensing of river bathymetry perform poorly in turbid water, image velocimetry can be effective under these conditions. This study describes a framework for mapping both of these attributes: Depths Inferred from Velocities Estimated by Remote Sensing, or DIVERS. The workflow involves linking image-derived velocities to depth via a flow resistance...
Authors
Carl J. Legleiter, Paul J. Kinzel
A low-cost approach to monitoring streamflow dynamics in small, headwater streams using timelapse imagery and a deep learning model
Despite their ubiquity and importance as freshwater habitat, small headwater streams are under monitored by existing stream gage networks. To address this gap, we describe a low-cost, non-contact, and low-effort method that enables organizations to monitor streamflow dynamics in small headwater streams. The method uses a camera to capture repeat images of the stream from a fixed position...
Authors
Phillip J. Goodling, Jennifer Burlingame Hoyle Fair, Amrita Gupta, Jeffrey Walker, Todd L. Dubreuil, Michael J Hayden, Benjamin Letcher
Multi-scale geophysical imaging of a hydrothermal system in Yellowstone National Park, USA
Little is known about the local plumbing systems that fuel Yellowstone’s famous hot springs, geysers and mud pots. A multi-method, multi-scale geophysical investigation was carried out in the Obsidian Pool Thermal Area (OPTA) to: (i) delineate the lateral extent of the hydrothermal area and associated surface features; (ii) estimate the dimensions of the upflow zone and identify its main...
Authors
Sylvain Pasquet, W. Steven Holbrook, Bradley J. Carr, Neil C. Terry, Martin Briggs, Carol A. Finn, Paul A. Bedrosian, Esben Auken, Jesper Pedersen, Pradip Kumar Maurya, Kenneth Sims
Fiber-optic distributed temperature sensing of hydrologic processes—Diverse deployments and new applications by the U.S. Geological Survey
Fiber-optic distributed temperature sensing instruments harness the temperature-dependent properties of glass to measure temperature continuously along optical fibers by using precise pulses of laser light. In the mid-2000s, this technology was refined for environmental monitoring purposes such as snowpack-air exchange, groundwater/surface-water exchange, and lake-water stratification...
Authors
Martin Briggs, David Matthew Rey, Chad C. Opatz, Neil C. Terry, Connor P. Newman, Lance R. Gruhn, Carole D. Johnson