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Cited by 5

The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.

Beyond Water Surface Profiles: A New Iterative Methodology for 2D Model Calibration in Rivers Using Velocity Data from Multiple Cross-Sections

Rivera-Trejo, Fabian, Soto-Cortes, Gabriel, Konsoer, Kory M., Langendoen, Eddy J., Priego-Hernandez, Gaston·2025·Water
DOI 10.3390/w17030377
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Abstract

Observed longitudinal water-surface profiles are commonly used to calibrate river hydrodynamic models, relying on assumptions of lateral uniformity in water surface elevation and velocity distribution. While suitable for 1D models, this approach has limitations in regard to 2D model calibration. When 2D flow measurements are available, a more robust quantitative evaluation is necessary to assess model accuracy. This study introduces a novel methodology to improve 2D model calibration and evaluate performance. High-resolution bathymetric and hydrodynamic data collected with a multibeam echosounder (MBES) and acoustic Doppler current profiler (ADCP) were aligned to compare observed and simulated flow velocities at matching spatial locations. Statistical metrics, including relative mean absolute error and root-mean-square error, were employed to assess hydrodynamic modeling. The methodology was tested using MBES and ADCP measurements alongside TELEMAC-2D simulations of a dynamic neck cutoff on the White River, Arkansas, USA. This approach provides a 2D calibration process, enhancing model accuracy and informing parameter selection, such as channel boundary roughness and downstream boundary water surface elevation.

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Figures

Figure 1 Field data for hydrodynamic modeling: ( a ) Streamwise velocity fi eld measured with an ADCP showing velocity magnitudes in color (red: high, blue: low) and transverse fl ow vectors with the riverbed profile (gray line); ( b ) high-resolution bathymetry captured with an MBES illustrating a detailed channel morphology, including meander bends and sedimentary features. Figure 1. Field data for hydrodynamic modeling: ( a ) Streamwise velocity field measured with an ADCP showing velocity magnitudes in color (red: high, blue: low) and transverse flow vectors with the riverbed profile (gray line); ( b ) high-resolution bathymetry captured with an MBES illustrating a detailed channel morphology, including meander bends and sedimentary features.
Figure 1 Field data for hydrodynamic modeling: ( a ) Streamwise velocity fi eld measured with an ADCP showing velocity magnitudes in color (red: high, blue: low) and transverse fl ow vectors with the riverbed profile (gray line); ( b ) high-resolution bathymetry captured with an MBES illustrating a detailed channel morphology, including meander bends and sedimentary features. Figure 1. Field data for hydrodynamic modeling: ( a ) Streamwise velocity field measured with an ADCP showing velocity magnitudes in color (red: high, blue: low) and transverse flow vectors with the riverbed profile (gray line); ( b ) high-resolution bathymetry captured with an MBES illustrating a detailed channel morphology, including meander bends and sedimentary features.CC-BY · From the PDF
Figure 2 The standard calibration procedure for 2D hydrodynamic models. Figure 2. The standard calibration procedure for 2D hydrodynamic models.
Figure 2 The standard calibration procedure for 2D hydrodynamic models. Figure 2. The standard calibration procedure for 2D hydrodynamic models.CC-BY · From the PDF
Figure 3 Bed profiles before the alignment process: ( a ) multibeam data; ( b ) ADCP data; and ( c ) alignment procedure result.
Figure 3 Bed profiles before the alignment process: ( a ) multibeam data; ( b ) ADCP data; and ( c ) alignment procedure result.CC-BY · From the PDF
Figure 4 Flow chart of the iterative alignment procedure of MBES and ADCP bed profiles. Figure 4. Flow chart of the iterative alignment procedure of MBES and ADCP bed profiles.
Figure 4 Flow chart of the iterative alignment procedure of MBES and ADCP bed profiles. Figure 4. Flow chart of the iterative alignment procedure of MBES and ADCP bed profiles.CC-BY · From the PDF
Figure 5 Evaluation of the downstream boundary condition of the hydrodynamics computer model: ( a ) schematic representation of the computational domain for a 2D hydrodynamic simulation; ( b ) comparison of the simulated water surface profile along an approximate centerline ( 𝑊𝑆𝑃஼௅ ) with the corrected, observed ADCP water level in each transect ( 𝑊𝑆𝑃ோ ) and the adjusted simulated water surface profile ( 𝑊𝑆𝑃஼௅ , ௔ ) after correction with ∆𝑧௪ . Figure 5. Evaluation of the downstream boundary condition of the hydrodynamics computer model: ( a ) schematic representation of the computational domain for a 2D hydrodynamic simulation; ( b ) comparison of the simulated water surface profile along an approximate centerline ( WSPCL ) with the corrected, observed ADCP water level in each transect ( WSPR ) and the adjusted simulated water surface profile ( WSPCL , a ) after correction with ∆ zw .
Figure 5 Evaluation of the downstream boundary condition of the hydrodynamics computer model: ( a ) schematic representation of the computational domain for a 2D hydrodynamic simulation; ( b ) comparison of the simulated water surface profile along an approximate centerline ( 𝑊𝑆𝑃஼௅ ) with the corrected, observed ADCP water level in each transect ( 𝑊𝑆𝑃ோ ) and the adjusted simulated water surface profile ( 𝑊𝑆𝑃஼௅ , ௔ ) after correction with ∆𝑧௪ . Figure 5. Evaluation of the downstream boundary condition of the hydrodynamics computer model: ( a ) schematic representation of the computational domain for a 2D hydrodynamic simulation; ( b ) comparison of the simulated water surface profile along an approximate centerline ( WSPCL ) with the corrected, observed ADCP water level in each transect ( WSPR ) and the adjusted simulated water surface profile ( WSPCL , a ) after correction with ∆ zw .CC-BY · From the PDF
Figure 6 Location of Pumps Bend on the White River, Arkansas, USA. Flow is from left to bo tt om in the inset map. Figure 6. Location of Pumps Bend on the White River, Arkansas, USA. Flow is from left to bottom in the inset map.
Figure 6 Location of Pumps Bend on the White River, Arkansas, USA. Flow is from left to bo tt om in the inset map. Figure 6. Location of Pumps Bend on the White River, Arkansas, USA. Flow is from left to bottom in the inset map.CC-BY · From the PDF
Figure 7 The 2016 maps of the model domain for Pumps Bend on the White River, AR (USA), showing ( a ) ADCP transect IDs and locations; ( b ) ADCP transect groups (cross-sections) and fl ow velocity magnitude indications; ( c ) an elevation map of the study domain, which is covered by a mesh Figure 7. The 2016 maps of the model domain for Pumps Bend on the White River, AR (USA), showing ( a ) ADCP transect IDs and locations; ( b ) ADCP transect groups (cross-sections) and flow velocity magnitude indications; ( c ) an elevation map of the study domain, which is covered by a mesh comprising 184,096 triangular elements with a mean side length of ~5 m; and ( d ) the floodplain and channel boundary roughness domains.
Figure 7 The 2016 maps of the model domain for Pumps Bend on the White River, AR (USA), showing ( a ) ADCP transect IDs and locations; ( b ) ADCP transect groups (cross-sections) and fl ow velocity magnitude indications; ( c ) an elevation map of the study domain, which is covered by a mesh Figure 7. The 2016 maps of the model domain for Pumps Bend on the White River, AR (USA), showing ( a ) ADCP transect IDs and locations; ( b ) ADCP transect groups (cross-sections) and flow velocity magnitude indications; ( c ) an elevation map of the study domain, which is covered by a mesh comprising 184,096 triangular elements with a mean side length of ~5 m; and ( d ) the floodplain and channel boundary roughness domains.CC-BY · From the PDF
Figure 8 ADCP bed profile aligned with the MBES bathymetry for ADCP cross-sections I to XV. Figure 8. ADCP bed profile aligned with the MBES bathymetry for ADCP cross-sections I to XV.
Figure 8 ADCP bed profile aligned with the MBES bathymetry for ADCP cross-sections I to XV. Figure 8. ADCP bed profile aligned with the MBES bathymetry for ADCP cross-sections I to XV.CC-BY · From the PDF
Figure 9 Comparison of the simulated and reference water surface profiles along the channel centerline. ( a ) Centerline bed profile for reference. ( b ) Comparison of 𝑊𝑆𝑃ோ and 𝑊𝑆𝑃஼௅ for the channel boundary roughness scenario with a Manning n of 0.030 s m 1/3 . Figure 9. Comparison of the simulated and reference water surface profiles along the channel centerline. ( a ) Centerline bed profile for reference. ( b ) Comparison of WSPR and WSPCL for the channel boundary roughness scenario with a Manning n of 0.030 s m 1/3 .
Figure 9 Comparison of the simulated and reference water surface profiles along the channel centerline. ( a ) Centerline bed profile for reference. ( b ) Comparison of 𝑊𝑆𝑃ோ and 𝑊𝑆𝑃஼௅ for the channel boundary roughness scenario with a Manning n of 0.030 s m 1/3 . Figure 9. Comparison of the simulated and reference water surface profiles along the channel centerline. ( a ) Centerline bed profile for reference. ( b ) Comparison of WSPR and WSPCL for the channel boundary roughness scenario with a Manning n of 0.030 s m 1/3 .CC-BY · From the PDF
Figure 10 Comparison of simulated ( vUCL , vVCL ) and measured ( vUR , vVR ) velocity components vU and vV at one arbitrary transect of each transect group. Simulated velocities are for scenario 1 ( n = 0.030 s m -1/3 ).
Figure 10 Comparison of simulated ( vUCL , vVCL ) and measured ( vUR , vVR ) velocity components vU and vV at one arbitrary transect of each transect group. Simulated velocities are for scenario 1 ( n = 0.030 s m -1/3 ).CC-BY · From the PDF
Image 11
CC-BY · From the PDF

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Metadata

Authors
Rivera-Trejo, F., Soto-Cortes, G., Konsoer, K. M., Langendoen, E. J., & Priego-Hernandez, G.
Affiliations
  • Division of Engineering and Architecture, Juarez Autonomous University of Tabasco, Tabasco 86040, Mexico
  • Department of Earth Resources, Autonomous Metropolitan University, Lerma 52005, Mexico
  • Department of Geography and Anthropology, Louisiana State University, Baton Rouge, LA 70802, USA
  • National Sedimentation Laboratory, US Department of Agriculture, Oxford, MS 38655, USA
  • Division of Basic Sciences, Juarez Autonomous University of Tabasco, Tabasco 86690, Mexico
ORCID
Venue
Water
Publisher
MDPI AG
Published
2025-01-30
Volume
17
Issue
3
Pages
377
ISSN
2073-4441
DOI
10.3390/w17030377
Cited by
5
References
34
Language
en
Licence
creativecommons.org/licenses/by/4.0/ (vor)
Funders
Ministry of Public Education (PRODEP-IDCA 30509, PRODEP 511-6/18-9789)

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CoChat. (2026). Citation check: Beyond Water Surface Profiles: A New Iterative Methodology for 2D Model Calibration in Rivers Using Velocity Data from Multiple Cross-Sections. https://app.cochat.ai/papers/10.3390/w17030377
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Rivera-Trejo, F., Soto-Cortes, G., Konsoer, K. M., Langendoen, E. J., & Priego-Hernandez, G. (2025). Beyond Water Surface Profiles: A New Iterative Methodology for 2D Model Calibration in Rivers Using Velocity Data from Multiple Cross-Sections. Water. https://doi.org/10.3390/w17030377

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