Abstract
Riparian vegetation imposes complex flow resistance, influencing hydraulics and morphodynamics of meandering rivers. Analytical characterizations remain limited regarding flexible foliage reconfiguration and leaf area index (LAI) impacts. We advance process-based resistance representations using LAI-integrated extensions alongside machine learning regressions of key parameters. Assessments against flume measurements demonstrate significant performance improvements, confirming suitability across varied immersion conditions. Integrations with a meander model reveal reconfiguration-moderated LAI effects in governing progressive planform displacement. Increased inundation and spatial density attenuate/reverse intrinsic trajectory based on width-depth regimes. The innovations establish an adaptable modeling template for remote sensing-assisted simulations, revealing shifting riparian controls on lowland river resilience.
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