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: 19111
Remote sensing of river discharge based on critical flow theory 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 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 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 R. Magee, Michael Frederick Meyer, Eric Anderson, Christoper D. Arp, Sarah Cooley, Wayana Dolan, Hilary A. 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
Characterization of DOC in riparian wetland pore water and its interference in stable water isotope analysis of δ2H and δ18O Characterization of DOC in riparian wetland pore water and its interference in stable water isotope analysis of δ2H and δ18O
Wetlands play an important role in carbon retention, which is greatly dependent on hydrological conditions. Therefore, the interest in wetland hydrology has increased over recent decades. In wetland hydrology, stable water isotopes (δ2H, δ18O) have found increasing use, as laser-based instruments have become readily available and allow for faster analysis and lower costs. However, the...
Authors
F. Fredriksson, K. T. Martinsen, K.-T. Liao, Tyler B. Coplen, R. Jakobsen, O. Batelaan, S. Jessen
Flow heterogeneity controls dissolution dynamics in topologically complex rocks Flow heterogeneity controls dissolution dynamics in topologically complex rocks
Rock dissolution is a common subsurface geochemical reaction affecting pore space properties, crucial for reservoir stimulation, carbon storage, and geothermal energy. Predictive models for dissolution remain limited due to incomplete understanding of the mechanisms involved. We examine the influence of flow, transport, and reaction regimes on mineral dissolution using 29 time-resolved...
Authors
Z. Kanavas, J. Jimenez-Martinez, F. Miele, John R. Nimmo, V.L. Morales
Gaps in water quality modeling of hydrologic systems 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 V. Lucas, Craig J. Brown, Dale M. Robertson, Nancy T. Baker, Zachary C. Johnson, Christopher Green, Jong Cho, Melinda L. 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 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, Jack R. Eggleston
Multi-Scale Graph Learning for anti-sparse downscaling Multi-Scale Graph Learning for anti-sparse downscaling
Water temperature can vary substantially even across short distances within the same sub-watershed. Accurate prediction of stream water temperature at fine spatial resolutions (i.e., fine scales, ≤ 1 km) enables precise interventions to maintain water quality and protect aquatic habitats. Although spatiotemporal models have made substantial progress in spatially coarse time series...
Authors
Yingda Fan, Runlong Yu, Janet R. Barclay, Alison P. Appling, Yiming Sun, Yiqun Xie, X. Jia
Physics-guided fair graph sampling for water temperature prediction in river networks Physics-guided fair graph sampling for water temperature prediction in river networks
This work introduces a novel graph neural networks (GNNs)-based method to predict stream water temperature and reduce model bias across locations of different income and education levels. Traditional physics-based models often have limited accuracy because they are necessarily approximations of reality. Recently, there has been an increasing interest of using GNNs in modeling complex...
Authors
Erhu He, Declan Kutscher, Yiqun Xie, Jacob Aaron Zwart, Zhe Jiang, Huaxiu Yao, X. Jia
Identifying preferential flow from soil moisture time series: Review of methodologies 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 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 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