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An investigation into remote sensing techniques and field observations for modeling of dynamic hydraulic roughness from riparian vegetation
  • +3
  • Smriti Chaulagain,
  • Mark Stone,
  • Daniel Dombroski,
  • Tyler Gillihan,
  • Li Chen,
  • Su Zhang
Smriti Chaulagain
The University of New Mexico

Corresponding Author:schaulagain@unm.edu

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Mark Stone
The University of New Mexico
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Daniel Dombroski
US Bureau of Reclamation Denver Federal Center
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Tyler Gillihan
The University of New Mexico
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Li Chen
Nanjing University of Information Science and Technology
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Su Zhang
The University of New Mexico
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Riparian vegetation provides many noteworthy functions in river and floodplain systems including its influence on hydrodynamic processes. Traditional methods for predicting hydrodynamic characteristics in the presence of vegetation involve the application of static roughness ( ns) values, which neglect changes in roughness due to local flow characteristics. The objectives of this study were to: (1) implement numerical routines for simulating dynamic hydraulic roughness ( nd) in a two-dimensional (2D) hydrodynamic model; (2) evaluate the performance of two dynamic roughness approaches; and (3) compare vegetation parameters and hydrodynamic model results based on field-based and remote sensing acquisition methods. A coupled vegetation-hydraulic solver was developed for a 2D hydraulics model using two dynamic approaches, which required vegetation parameters to calculate spatially distributed, dynamic roughness coefficients. Vegetation parameters were determined by field survey and using airborne LiDAR data. Water surface elevations modeled using conventional and the proposed dynamic approaches produced similar profiles. The method demonstrates the suitability in modeling the system where there is no calibration data. Substantial spatial variations in both n and hydraulic parameters were observed when comparing the static and dynamic approaches. Thus, the method proposed here is beneficial for describing the hydraulic conditions for the area having huge variation of vegetation. The proposed methods have the potential to improve our ability to simulate the spatial and temporal heterogeneity of vegetated floodplain surfaces with an approach that is more physically-based and reproducible than conventional “look up” approaches. However, additional research is needed to quantify model performance with respect to spatially distributed flow properties and parameterization of vegetation characteristics.
02 Nov 2021Submitted to River Research and Applications
02 Nov 2021Submission Checks Completed
02 Nov 2021Assigned to Editor
10 Nov 2021Review(s) Completed, Editorial Evaluation Pending
23 Nov 2021Reviewer(s) Assigned
20 Apr 2022Editorial Decision: Revise Major
21 Jul 20221st Revision Received
21 Jul 2022Submission Checks Completed
21 Jul 2022Assigned to Editor
21 Jul 2022Review(s) Completed, Editorial Evaluation Pending
26 Jul 2022Reviewer(s) Assigned
23 Aug 2022Editorial Decision: Accept