The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Prospects for river discharge and depth estimation through assimilation of swath‐altimetry into a raster‐based hydrodynamics model
Open accessAbstract
Surface water elevation profiles for a reach of the Ohio River were produced by the Jet Propulsion Laboratory Instrument Simulator to represent satellite measurements representative of those that would be observed by a wide swath altimeter being considered jointly by U.S. and European space agencies. The Ensemble Kalman filter with a river hydrodynamics model as its dynamical core was used to assimilate the water elevation synthetic observations, and to estimate river discharge. The filter was able to recover water depth and discharge, reducing the discharge RMSE from 23.2% to 10.0% over an 84‐day simulation period, relative to a simulation without assimilation. An autoregressive error model was instrumental in correcting boundary inflows, and increasing the persistence of error reductions between times of observations. The nominal 8‐day satellite overpass produced discharge relative errors of 10.0%, while 16‐day and 32‐day overpass frequencies resulted in errors of 12.1% and 16.9% respectively.
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
Evensen, G. (1994) · Journal of Geophysical Research: Oceans · doi:10.1029/94jc00572 · Cited by 5,371
Cited by
Neal, J., Schumann, G., & Bates, P. (2012) · Water Resources Research · doi:10.1029/2012wr012514 · Cited by 517
The SWOT Mission and Its Capabilities for Land Hydrology
Biancamaria, S., Lettenmaier, D. P., & Pavelsky, T. M. (2016) · Surveys in Geophysics · doi:10.1007/s10712-015-9346-y · Cited by 458
Self-citation
Metadata
- Authors
- Andreadis, K. M., Clark, E. A., Lettenmaier, D. P., & Alsdorf, D. E.
- Venue
- Geophysical Research Letters
- Publisher
- American Geophysical Union (AGU)
- Published
- 2007-05
- Volume
- 34
- Issue
- 10
- ISSN
- 0094-8276 (ISSN-L)
- 1944-8007
- OpenAlex
- W2023020665
- Cited by
- 249
- References
- 1
- FWCI
- 7.99
- Type
- journal article
- Language
- en
- Open access
- bronze
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: Prospects for river discharge and depth estimation through assimilation of swath‐altimetry into a raster‐based hydrodynamics model. https://app.cochat.ai/papers/10.1029/2007gl029721
- The paper
- Andreadis, K. M., Clark, E. A., Lettenmaier, D. P., & Alsdorf, D. E. (2007). Prospects for river discharge and depth estimation through assimilation of swath‐altimetry into a raster‐based hydrodynamics model. Geophysical Research Letters. https://doi.org/10.1029/2007gl029721
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.