Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 149

The DOI matches its Crossref record.

Inference of effective river properties from remotely sensed observations of water surface

Garambois, Pierre-André, Monnier, Jérôme·2015·Advances in Water Resources

Overview

Integrity signals

Registry

Crossref · 10.1016/j.advwatres.2015.02.007

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

No references could be resolved yet.

Research works printed but not linked: 34

  1. Han, 2005, High-resolution continental water storage recovery from low-low satellite-to-satellite tracking, J Geodyn, 39, 11, 10.1016/j.jog.2004.08.002 · doi:10.1016/j.jog.2004.08.002
  2. Munier, 2012, Global runoff anomalies over 1993–2009 estimated from coupled Land–Ocean–Atmosphere water budgets and its relation with climate variability, Hydrol Earth Syst Sci., 16, 3647, 10.5194/hess-16-3647-2012 · doi:10.5194/hess-16-3647-2012
  3. Frappart, 2006, Preliminary results of ENVISAT RA-2-derived water levels validation over the Amazon basin, Remote Sens Environ, 100, 252, 10.1016/j.rse.2005.10.027 · DOI
  4. Jung, 2010, Characterization of complex fluvial systems using remote sensing of spatial and temporal water level variations in the Amazon, Congo, and Brahmaputra Rivers, Earth Surf Process Landforms, 35, 294, 10.1002/esp.1914 · doi:10.1002/esp.1914
  5. Biancamaria, 2010, Preliminary characterization of SWOT hydrology error budget and global capabilities, IEEE J Sel Top Appl Earth Obs Remote Sens, 3, 6, 10.1109/JSTARS.2009.2034614 · DOI
  6. Bjerklie, 2003, Evaluating the potential for measuring river discharge from space, J Hydrol, 278, 17, 10.1016/S0022-1694(03)00129-X · DOI · Paper page
  7. Bjerklie, 2005, Estimating discharge in rivers using remotely sensed hydraulic information, J Hydrol, 309, 191, 10.1016/j.jhydrol.2004.11.022 · DOI · Paper page
  8. Birkinshaw, 2014, Daily discharge estimation at ungauged river sites using remote sensing, Hydrol Process, 28, 1043, 10.1002/hyp.9647 · DOI
  9. Aronica, 1998, Uncertainty and equifinality in calibrating distributed roughness coefficients in a flood propagation model with limited data, Adv Water Res, 22, 349, 10.1016/S0309-1708(98)00017-7 · DOI · Paper page
  10. Roux, 2005, Parameter identification using optimization techniques in open-channel inverse problems, J Hydraul Res, 43, 311, 10.1080/00221680509500125 · doi:10.1080/00221680509500125
  11. Roux, 2006, Use of parameter optimization to estimate a flood wave: potential applications to remote sensing of rivers, J Hydrol, 328, 258, 10.1016/j.jhydrol.2005.12.025 · doi:10.1016/j.jhydrol.2005.12.025
  12. Bélanger, 2005, Data assimilation (4D-VAR) to forecast flood in shallow-waters with sediment erosion, J Hydrol, 300, 114, 10.1016/j.jhydrol.2004.06.009 · DOI
  13. Honnorat M. Assimilation de données lagrangiennes pour la simulation numTrique en hydraulique fluviale [PhD thesis]. INPG, Grenoble, France; 2007. http://www-ljk.imag.fr/membres/Marc.Honnorat/these/index.html
  14. Lai, 2009, Assimilation of spatially distributed water levels into a shallow-water flood model. Part I: Mathematical method and test case, J Hydrol, 377, 1, 10.1016/j.jhydrol.2009.07.058 · doi:10.1016/j.jhydrol.2009.07.058
  15. Hostache, 2010, Assimilation of spatially distributed water levels into a shallow-water flood model. Part II: Use of a remote sensing image of Mosel River, J Hydrol, 390, 257, 10.1016/j.jhydrol.2010.07.003 · doi:10.1016/j.jhydrol.2010.07.003
  16. Durand, 2010, Estimating river depth from remote sensing swath interferometry measurements of river height, slope, and width, IEEE J Sel Top Appl Earth Obs Remote Sens, 3, 20, 10.1109/JSTARS.2009.2033453 · DOI
  17. Biancamaria, 2011, Assimilation of virtual wide swath altimetry to improve Arctic river modeling, Remote Sens Environ, 115, 373, 10.1016/j.rse.2010.09.008 · DOI · Paper page
  18. Gessese, 2011, Reconstruction of river bed topography from free surface data using a direct numerical approach in one-dimensional shallow water flow, Inverse Prob, 27, 025001, 10.1088/0266-5611/27/2/025001 · doi:10.1088/0266-5611/27/2/025001
  19. Gessese A. Algorithms for bed topography reconstruction in geophysical flows [Ph.D. thesis]. University of Canterbury. Mechanical Engineering; 2013. <http://ir.canterbury.ac.nz/handle/10092/8673>
  20. Gessese, 2013, Bathymetry reconstruction based on the zero-inertia shallow water approximation, Theor Comput Fluid Dyn, 27, 721, 10.1007/s00162-012-0287-5 · doi:10.1007/s00162-012-0287-5
  21. Yoon, 2012, Estimating river bathymetry from data assimilation of synthetic SWOT measurements, J Hydrol, 464–465, 363, 10.1016/j.jhydrol.2012.07.028 · DOI
  22. Honnorat, 2009, Lagrangian data assimilation for river hydraulics simulations, Comput Visual Sci, 12, 235, 10.1007/s00791-008-0089-x · doi:10.1007/s00791-008-0089-x
  23. Honnorat, 2010, Identification of equivalent topography in an open channel flow using Lagrangian data assimilation, Comput Visual Sci, 13, 111, 10.1007/s00791-009-0130-8 · doi:10.1007/s00791-009-0130-8
  24. Roux, 2008, Sensitivity analysis and predictive uncertainty using inundation observations for parameter estimation in open-channel inverse problem, J Hydrol Eng ASCE, 134, 541, 10.1061/(ASCE)0733-9429(2008)134:5(541) · doi:10.1061/(asce)0733-9429(2008)134:5(541
  25. Negrel, 2011, Estimating river discharge from earth observation measurements of river surface hydraulic variables, Hydrol Earth Syst Sci, 15, 2049, 10.5194/hess-15-2049-2011 · doi:10.5194/hess-15-2049-2011
  26. Romeiser, 2007, Current measurements in rivers by spaceborne along-track InSAR, IEEE Trans Geosci Remote Sens, 45, 4019, 10.1109/TGRS.2007.904837 · doi:10.1109/tgrs.2007.904837
  27. Tarpanelli, 2013, Hydraulic modelling calibration in small rivers by using coarse resolution synthetic aperture radar imagery, Hydrol Process, 27, 1321, 10.1002/hyp.9550 · doi:10.1002/hyp.9550
  28. Durand, 2014, Estimating reach-averaged discharge for the River Severn from measurements of river water surface elevation and slope, J Hydrol, 10.1016/j.jhydrol.2013.12.050 · DOI · Paper page
  29. Strelkoff, 2000, Approximating wetted perimeter in power-law cross section, J Irrig Drain Eng, 126, 98, 10.1061/(ASCE)0733-9437(2000)126:2(98) · doi:10.1061/(asce)0733-9437(2000)126:2(98
  30. Jowett, 1993, A method for objectively identifying pool, run, and riffle habitats from physical measurements, N Z J Mar Freshwater Res, 27, 241, 10.1080/00288330.1993.9516563 · doi:10.1080/00288330.1993.9516563
  31. Simeoni-Sauvage S. Modélisation hydrobiogéochimique de la Garonne a l’étiage estival : cas de l’azote entre Toulouse et Agen (120 kilomètres) [Ph.D. thesis]. Toulouse, INPT; 1999.
  32. Larnier K. Modélisation thermohydraulique d’un tronton de Garonne en lien avec l’habitat piscicole: approches statistique et déterministe [Ph.D. thesis]. Toulouse; 2010.
  33. Moré, 1983, Computing a trust region step, SIAM J Sci Stat Comput, 4, 553, 10.1137/0904038 · DOI · Paper page
  34. Chow V. Handbook of applied hydrology. New-York: McGraw-Hill Book Co.; 1467p.

Cited by

See all 149

Metadata

Authors
Garambois, P.-A., & Monnier, J.
Venue
Advances in Water Resources
Publisher
Elsevier BV
Published
2015-05
Volume
79
Pages
103-120
ISSN
0309-1708
Cited by
149
References
0
Language
en
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)

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: Inference of effective river properties from remotely sensed observations of water surface. https://app.cochat.ai/papers/10.1016/j.advwatres.2015.02.007
The paper
Garambois, P.-A., & Monnier, J. (2015). Inference of effective river properties from remotely sensed observations of water surface. Advances in Water Resources. https://doi.org/10.1016/j.advwatres.2015.02.007

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.