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Improving Channel Hydrological Connectivity in Coastal Hydrodynamic Models With Remotely Sensed Channel Networks

Zhang, Xiaohe and Wright, Kyle and Passalacqua, Paola and Simard, Marc and Fagherazzi, Sergio (2022) Improving Channel Hydrological Connectivity in Coastal Hydrodynamic Models With Remotely Sensed Channel Networks. Journal of Geophysical Research. Earth Surface, 127 (3). Art. No. e2021JF006294. ISSN 2169-9003. doi:10.1029/2021jf006294. https://resolver.caltech.edu/CaltechAUTHORS:20220224-285161300

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Abstract

Coastal wetlands are nourished by rivers and periodical tidal flows through complex, interconnected channels. However, in hydrodynamic models, channel dimensions with respect to model grid size and uncertainties in topography preclude the correct propagation of tidal and riverine signals. It is therefore crucial to enhance channel geomorphic connectivity and simplify sub-channel features based on remotely sensed networks for practical computational applications. Here, we utilize channel networks derived from diverse remote sensing imagery as a baseline to build a ∼10 m resolution hydrodynamic model that covers the Wax Lake Delta and adjacent wetlands (∼360 km2) in coastal Louisiana, USA. In this richly gauged system, intensive calibrations are conducted with 18 synchronous field-observations of water levels taken in 2016, and discharge data taken in 2021. We modify channel geometry, targeting realism in channel connectivity. The results show that a minimum channel depth of 2 m and a width of four grid elements (approximatively 40 m) are required to enable a realistic tidal propagation in wetland channels. The optimal depth for tidal propagation can be determined by a simplified cost function method that evaluates the competition between flow travel time and alteration of the volume of the channels. The integration of high spatial-resolution models and remote sensing imagery provides a general framework to improve models performance in salt marshes, mangroves, deltaic wetlands, and tidal flats.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1029/2021jf006294DOIArticle
https://deltax.jpl.nasa.gov/data/MRD/final/2022-02-delft3D-model/Related ItemSimulations data and codes
ORCID:
AuthorORCID
Zhang, Xiaohe0000-0002-7324-0529
Wright, Kyle0000-0001-5142-1786
Passalacqua, Paola0000-0002-4763-7231
Simard, Marc0000-0002-9442-4562
Fagherazzi, Sergio0000-0002-4048-5968
Additional Information:© 2022 American Geophysical Union. Issue Online: 06 March 2022; Version of Record online: 06 March 2022; Accepted manuscript online: 23 February 2022; Manuscript accepted: 17 February 2022; Manuscript revised: 11 February 2022; Manuscript received: 01 June 2021. The NASA Delta-X project is funded by the Science Mission Directorate's Earth Science Division through the Earth Venture Suborbital-3 Program NNH17ZDA001N-EVS3. This work was partly conducted by the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration. Sergio Fagherazzi was also partially funded by NSF grants DEB-1832221 to the Virginia Coast Reserve Long-Term Ecological Research project and OCE-1637630 to the Plum Island Ecosystems Long-Term Ecological Research project. The authors declare no conflicts of interest relevant to this study. Data Availability Statement: The simulations data and codes of cost-function surrogate model are available at https://deltax.jpl.nasa.gov/data/MRD/final/2022-02-delft3D-model/.
Funders:
Funding AgencyGrant Number
NASANNH17ZDA001N-EVS3
NASA/JPL/CaltechUNSPECIFIED
NSFDEB-1832221
NSFOCE-1637630
Subject Keywords:Coastal numerical model; Flow propagation; Remote-sensed channel network; Channel geometry; Model performance; Cost function
Issue or Number:3
DOI:10.1029/2021jf006294
Record Number:CaltechAUTHORS:20220224-285161300
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20220224-285161300
Official Citation:Zhang, X., Wright, K., Passalacqua, P., Simard, M., & Fagherazzi, S. (2022). Improving channel hydrological connectivity in coastal hydrodynamic models with remotely sensed channel networks. Journal of Geophysical Research: Earth Surface, 127, e2021JF006294. https://doi.org/10.1029/2021JF006294
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:113609
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:24 Feb 2022 22:55
Last Modified:22 Mar 2022 20:34

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