Multi‐Sensor Airborne Remote Sensing for Calibrating Hydrodynamic and Sediment Transport Models in Coastal Louisiana Wetlands (Atchafalaya–Terrebonne).
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| Title: | Multi‐Sensor Airborne Remote Sensing for Calibrating Hydrodynamic and Sediment Transport Models in Coastal Louisiana Wetlands (Atchafalaya–Terrebonne). |
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| Authors: | Payandeh, Ali Reza1 (AUTHOR) ali.reza.payandeh@jpl.nasa.gov, Simard, Marc1 (AUTHOR), Jones, Cathleen E.1 (AUTHOR), Christensen, Alexandra1 (AUTHOR), Jensen, Daniel1 (AUTHOR), Denbina, Michael1 (AUTHOR), Oliver‐Cabrera, Talib1 (AUTHOR) |
| Source: | Water Resources Research. Apr2026, Vol. 62 Issue 4, p1-21. 21p. |
| Subjects: | Calibration, Sediment transport, United States. National Aeronautics & Space Administration, Remote sensing, Hydrodynamics, Ground vegetation cover, Remote sensing by radar, Coastal wetlands |
| Geographic Terms: | United States, Louisiana, Mississippi River Delta (La.) |
| Abstract: | This study integrates high resolution remote sensing data from NASA's Delta‐X mission with a process based hydrodynamic and sediment transport model to improve predictions of water levels and suspended sediment dynamics in the Mississippi River Delta, in coastal Louisiana, USA, focusing on Atchafalaya and Terrebonne basins. A two dimensional Delft3D Flexible Mesh model was implemented using spatially variable bottom friction maps derived from optical imagery (AVIRIS‐NG and Sentinel‐2) to represent vegetation heterogeneity. Hydrodynamic calibration leveraged airborne interferometric radar measurements (Airborne Surface Water and Ocean Topography (AirSWOT) and Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR)) of water surface elevations and water level changes, while validation used in situ tide gauge records from spring and fall 2021. Model comparison with AirSWOT measurements in channels showed that spatially explicit roughness parameterizations substantially improved performance. Results were notably better for the spring acquisitions (root mean square error = 0.09 m; R2 = 0.82), likely due to higher wind speeds and steeper water surface slopes that increased surface roughness and improved radar retrieval performance. UAVSAR provided additional spatial constraints on transient water level changes across wetlands at ∼30‐min intervals, further informing roughness calibration. Model deviation from UAVSAR were typically within ± $\pm $4 cm, although performance degraded in forested and densely vegetated areas due to reduced radar coherence. Validation with in situ tide gauges confirmed model performance for tidal and subtidal variability. Sediment transport calibration using AVIRIS‐NG total suspended solids allowed refinement of settling velocity and critical shear stress. Overall, the integration of remote sensing data into model calibration and parameterization led to measurable improvements in hydrodynamic and sediment predictions. Key Points: Radar‐based water‐surface measurements constrain calibration best when wind/flow create sufficient roughness and water‐level gradientsInterferometric radar measurements degrade in dense vegetation (e.g., forested wetlands and aquatic‐vegetation zones) raising uncertaintyIn frictional wetlands like coastal Louisiana, vegetation‐based spatial roughness improves hydrodynamic skill over simple friction models [ABSTRACT FROM AUTHOR] |
| Copyright of Water Resources Research is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 193320894 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Multi‐Sensor Airborne Remote Sensing for Calibrating Hydrodynamic and Sediment Transport Models in Coastal Louisiana Wetlands (Atchafalaya–Terrebonne). – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Payandeh%2C+Ali+Reza%22">Payandeh, Ali Reza</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> ali.reza.payandeh@jpl.nasa.gov</i><br /><searchLink fieldCode="AR" term="%22Simard%2C+Marc%22">Simard, Marc</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Jones%2C+Cathleen+E%2E%22">Jones, Cathleen E.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Christensen%2C+Alexandra%22">Christensen, Alexandra</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Jensen%2C+Daniel%22">Jensen, Daniel</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Denbina%2C+Michael%22">Denbina, Michael</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Oliver‐Cabrera%2C+Talib%22">Oliver‐Cabrera, Talib</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Water+Resources+Research%22">Water Resources Research</searchLink>. Apr2026, Vol. 62 Issue 4, p1-21. 21p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Calibration%22">Calibration</searchLink><br /><searchLink fieldCode="DE" term="%22Sediment+transport%22">Sediment transport</searchLink><br /><searchLink fieldCode="DE" term="%22United+States%2E+National+Aeronautics+%26+Space+Administration%22">United States. National Aeronautics & Space Administration</searchLink><br /><searchLink fieldCode="DE" term="%22Remote+sensing%22">Remote sensing</searchLink><br /><searchLink fieldCode="DE" term="%22Hydrodynamics%22">Hydrodynamics</searchLink><br /><searchLink fieldCode="DE" term="%22Ground+vegetation+cover%22">Ground vegetation cover</searchLink><br /><searchLink fieldCode="DE" term="%22Remote+sensing+by+radar%22">Remote sensing by radar</searchLink><br /><searchLink fieldCode="DE" term="%22Coastal+wetlands%22">Coastal wetlands</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22United+States%22">United States</searchLink><br /><searchLink fieldCode="DE" term="%22Louisiana%22">Louisiana</searchLink><br /><searchLink fieldCode="DE" term="%22Mississippi+River+Delta+%28La%2E%29%22">Mississippi River Delta (La.)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: This study integrates high resolution remote sensing data from NASA's Delta‐X mission with a process based hydrodynamic and sediment transport model to improve predictions of water levels and suspended sediment dynamics in the Mississippi River Delta, in coastal Louisiana, USA, focusing on Atchafalaya and Terrebonne basins. A two dimensional Delft3D Flexible Mesh model was implemented using spatially variable bottom friction maps derived from optical imagery (AVIRIS‐NG and Sentinel‐2) to represent vegetation heterogeneity. Hydrodynamic calibration leveraged airborne interferometric radar measurements (Airborne Surface Water and Ocean Topography (AirSWOT) and Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR)) of water surface elevations and water level changes, while validation used in situ tide gauge records from spring and fall 2021. Model comparison with AirSWOT measurements in channels showed that spatially explicit roughness parameterizations substantially improved performance. Results were notably better for the spring acquisitions (root mean square error = 0.09 m; R2 = 0.82), likely due to higher wind speeds and steeper water surface slopes that increased surface roughness and improved radar retrieval performance. UAVSAR provided additional spatial constraints on transient water level changes across wetlands at ∼30‐min intervals, further informing roughness calibration. Model deviation from UAVSAR were typically within ± $\pm $4 cm, although performance degraded in forested and densely vegetated areas due to reduced radar coherence. Validation with in situ tide gauges confirmed model performance for tidal and subtidal variability. Sediment transport calibration using AVIRIS‐NG total suspended solids allowed refinement of settling velocity and critical shear stress. Overall, the integration of remote sensing data into model calibration and parameterization led to measurable improvements in hydrodynamic and sediment predictions. Key Points: Radar‐based water‐surface measurements constrain calibration best when wind/flow create sufficient roughness and water‐level gradientsInterferometric radar measurements degrade in dense vegetation (e.g., forested wetlands and aquatic‐vegetation zones) raising uncertaintyIn frictional wetlands like coastal Louisiana, vegetation‐based spatial roughness improves hydrodynamic skill over simple friction models [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Water Resources Research is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1029/2025WR042357 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 21 StartPage: 1 Subjects: – SubjectFull: Calibration Type: general – SubjectFull: Sediment transport Type: general – SubjectFull: United States. National Aeronautics & Space Administration Type: general – SubjectFull: Remote sensing Type: general – SubjectFull: Hydrodynamics Type: general – SubjectFull: Ground vegetation cover Type: general – SubjectFull: Remote sensing by radar Type: general – SubjectFull: Coastal wetlands Type: general – SubjectFull: United States Type: general – SubjectFull: Louisiana Type: general – SubjectFull: Mississippi River Delta (La.) Type: general Titles: – TitleFull: Multi‐Sensor Airborne Remote Sensing for Calibrating Hydrodynamic and Sediment Transport Models in Coastal Louisiana Wetlands (Atchafalaya–Terrebonne). Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Payandeh, Ali Reza – PersonEntity: Name: NameFull: Simard, Marc – PersonEntity: Name: NameFull: Jones, Cathleen E. – PersonEntity: Name: NameFull: Christensen, Alexandra – PersonEntity: Name: NameFull: Jensen, Daniel – PersonEntity: Name: NameFull: Denbina, Michael – PersonEntity: Name: NameFull: Oliver‐Cabrera, Talib IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 04 Text: Apr2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 00431397 Numbering: – Type: volume Value: 62 – Type: issue Value: 4 Titles: – TitleFull: Water Resources Research Type: main |
| ResultId | 1 |
