Monthly hydraulic geometry relationship quantification with environmental LAI by utilizing sentinel data: A case in Jingjiang reach of the Yangtze River

•Innovative ODE model integrates hydraulic geometry and remotely sensed LAI data.•Captures dynamic influences of riparian vegetation on channel morphology and stability.•Calibrated/verified model outperforms constant-parameter approaches for normal climate.•Limited predictive ability under extreme d...

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Veröffentlicht in:Journal of hydrology (Amsterdam) 2024-06, Vol.636, p.131322, Article 131322
Hauptverfasser: Huang, Hai, Song, Xiaolong, Zhang, Lei, Xu, Haijue, Bai, Yuchuan
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Sprache:eng
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Zusammenfassung:•Innovative ODE model integrates hydraulic geometry and remotely sensed LAI data.•Captures dynamic influences of riparian vegetation on channel morphology and stability.•Calibrated/verified model outperforms constant-parameter approaches for normal climate.•Limited predictive ability under extreme drought due to data limitations, assumptions.•Framework shows potential for broader application with appropriate adjustments. This study presents a novel approach for quantifying the dynamics of monthly hydraulic geometry relationships in the Jingjiang reach of the Yangtze River by integrating leaf area index (LAI) data as an indicator of riparian vegetation. A comprehensive system of ordinary differential equations (ODEs) couples traditional power-law hydraulic geometry equations with LAI, capturing the influence of erosion control on channel morphology. The periodic delayed response theory and automatic differentiation techniques are employed to enhance the modeling framework’s capabilities. Calibration and verification demonstrate the models’ effectiveness in capturing overall trends in discharge, width, and depth dynamics, outperforming traditional constant-parameter approaches. However, model predictive abilities are limited under extreme climate conditions due to training on normal climate data. Key assumptions, including the periodic delayed response theory’s neglect of peak discharges, simplified representation of artificial cut-offs, and reliance on remotely sensed data with limited local validation, introduce uncertainties. The proposed modeling framework shows potential for broader application to other river systems with appropriate adjustments. Future research could incorporate additional environmental factors, integrate models across scales, couple with advanced simulation techniques, and expand stability assessments beyond the riverbed index. By addressing related challenges, this integrated approach lays a foundation for enhancing understanding of river morphodynamics and channel stability.
ISSN:0022-1694
1879-2707
DOI:10.1016/j.jhydrol.2024.131322