The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Large‐scale particle image velocimetry for measurements in riverine environments
Abstract
Large‐scale particle image velocimetry (LSPIV) is a nonintrusive approach to measure velocities at the free surface of a water body. The raw LSPIV results are instantaneous water surface velocity fields, spanning flow areas up to hundreds of square meters. Measurements conducted in typical conditions in conjunction with appropriate selections of parameters for image processing resulted in mean velocity errors of less than 3.5%. The current article reviews the background of LSPIV and the work of three research teams spanning over a decade. Implementation examples using various LSPIV configurations are then described to illustrate the capability of the technique to characterize spatially distributed two‐ and three‐dimensional flow kinematic features that can be related to important morphologic and hydrodynamic aspects of natural rivers. Finally, results and a critique of research methods are discussed to encourage LSPIV use and to improve its capabilities to collect field data needed to better understand complex geomorphic, hydrologic, and ecologic river processes and interactions under normal and extreme conditions.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Particle-Imaging Techniques for Experimental Fluid Mechanics
Adrian, R. J. (1991) · Annual Review of Fluid Mechanics · doi:10.1146/annurev.fl.23.010191.001401 · Cited by 3,405 · cited 5×
“The first image-based quantitative instruments, generically labeled as particle image velocimetry (PIV), have greatly enhanced measurement techniques of instantaneous velocity vectors in a variety of laboratory flows [e.g., Adrian, 1991; Raffel et al., 1998].”
BackgroundMethodInfluential
Cited by
Benchmarking observational uncertainties for hydrology: rainfall, river discharge and water quality
McMillan, H., Krueger, T., & Freer, J. (2012) · Hydrological Processes · doi:10.1002/hyp.9384 · Cited by 522
Masafu, C., Williams, R., Shi, X., Yuan, Q., & Trigg, M. (2022) · Journal of Hydrology · doi:10.1016/j.jhydrol.2022.128217 · Cited by 28
Metadata
- Authors
- Muste, M., Fujita, I., & Hauet, A.
- Venue
- Water Resources Research
- Publisher
- American Geophysical Union (AGU)
- Published
- 2008-04
- Volume
- 44
- Issue
- 4
- ISSN
- 0043-1397 (ISSN-L)
- 1944-7973
- OpenAlex
- W1504073505
- Cited by
- 425
- References
- 1
- FWCI
- 5.37
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Large‐scale particle image velocimetry for measurements in riverine environments. https://app.cochat.ai/papers/10.1029/2008wr006950
- The paper
- Muste, M., Fujita, I., & Hauet, A. (2008). Large‐scale particle image velocimetry for measurements in riverine environments. Water Resources Research. https://doi.org/10.1029/2008wr006950
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.