“…Nevertheless, a quasi-linear relationship emerges between C and both the mean and upper values of the M R distributions, pointing to a strong first-order control of C on meandering river morphodynamics 37 , 38 , 44 . This proportionality typically only holds for mildly curved channel reaches (i.e., for width-adjusted curvature values smaller than 0.25–0.5, taken here as C < 0.3 for convenience) and breaks down at higher curvatures ( C > 0.3) where M R saturates due to the growth of hydrodynamic nonlinearities that effectively limit bank erosion, such as saturation of centrifugally driven secondary flows, enhanced secondary outer bank cells, and flow separation at the outer bank 1 , 38 , 46 , 53 , 54 (Supplementary Method 2 ). Fig.…”
Stabilization of riverbanks by vegetation has long been considered necessary to sustain single-thread meandering rivers. However, observation of active meandering in modern barren landscapes challenges this assumption. Here, we investigate a globally distributed set of modern meandering rivers with varying riparian vegetation densities, using satellite imagery and statistical analyses of meander-form descriptors and migration rates. We show that vegetation enhances the coefficient of proportionality between channel curvature and migration rates at low curvatures, and that this effect wanes in curvier channels irrespective of vegetation density. By stabilizing low-curvature reaches and allowing meanders to gain sinuosity as channels migrate laterally, vegetation quantifiably affects river morphodynamics. Any causality between denser vegetation and higher meander sinuosity, however, cannot be inferred owing to more frequent avulsions in modern non-vegetated environments. By illustrating how vegetation affects channel mobility and floodplain reworking, our findings have implications for assessing carbon stocks and fluxes in river floodplains.
“…Nevertheless, a quasi-linear relationship emerges between C and both the mean and upper values of the M R distributions, pointing to a strong first-order control of C on meandering river morphodynamics 37 , 38 , 44 . This proportionality typically only holds for mildly curved channel reaches (i.e., for width-adjusted curvature values smaller than 0.25–0.5, taken here as C < 0.3 for convenience) and breaks down at higher curvatures ( C > 0.3) where M R saturates due to the growth of hydrodynamic nonlinearities that effectively limit bank erosion, such as saturation of centrifugally driven secondary flows, enhanced secondary outer bank cells, and flow separation at the outer bank 1 , 38 , 46 , 53 , 54 (Supplementary Method 2 ). Fig.…”
Stabilization of riverbanks by vegetation has long been considered necessary to sustain single-thread meandering rivers. However, observation of active meandering in modern barren landscapes challenges this assumption. Here, we investigate a globally distributed set of modern meandering rivers with varying riparian vegetation densities, using satellite imagery and statistical analyses of meander-form descriptors and migration rates. We show that vegetation enhances the coefficient of proportionality between channel curvature and migration rates at low curvatures, and that this effect wanes in curvier channels irrespective of vegetation density. By stabilizing low-curvature reaches and allowing meanders to gain sinuosity as channels migrate laterally, vegetation quantifiably affects river morphodynamics. Any causality between denser vegetation and higher meander sinuosity, however, cannot be inferred owing to more frequent avulsions in modern non-vegetated environments. By illustrating how vegetation affects channel mobility and floodplain reworking, our findings have implications for assessing carbon stocks and fluxes in river floodplains.
“…The hazard scenario is derived using the two-dimensional (2-D) hydrodynamic model 2DEF [44,[77][78][79][80][81], which allows for a physics-based description of the flood routing within the Piave River, of the formation of levee failures, and of the flooding of adjacent areas in a coupled fashion. The numerical approach, the model effectiveness in reproducing the river flow, the levee failure, and the subsequent flooding processes have been described in Viero et al [80].…”
Section: Hydrodynamic Model For Hazard Assessmentmentioning
The present work is aimed at assessing the change in time of flood risk as a consequence of landscape modifications. The town of San Donà di Piave (Italy) is taken as a representative case study because, as most parts of the North Italy floodplains, it was strongly urbanized and anthropized in the last several decades. As a proxy for flood risk, we use flood damage to residential buildings. The analysis is carried out at the local scale, accounting for changes to single buildings; GIS data such as high-resolution topography, technical maps, and aerial images taken over time are used to track how the landscape evolves over time, both in terms of urbanized areas and of hydraulically relevant structures (e.g., embankments). Flood hazard is determined using a physics-based, finite element hydrodynamic code that models in a coupled way the flood routing within the Piave River, the formation of levee failures, and the flooding of adjacent areas. The expected flood damage to residential buildings is estimated using an innovative method, recently proposed in the literature, which allows estimating how the damage evolves during a single flood event. The decade-scale change in the expected flood damage reveals the detrimental effect of urbanization, with flood risk growing at the pace of a fraction of urbanized areas. The within-event time evolution of the flood damage, i.e., how it progresses in the course of past or recent flood events, reflects changes in the hydrodynamic process of flooding. The general methodology used in the present work can be viewed as a promising technique to analyze the effects on the flood risk of past landscape evolution and, more importantly, a valuable tool toward an improved, well-informed, and sustainable land planning.
“…counter-clockwise rotating secondary current generated by the upstream right-handed bend. Indeed, rotational inertia makes these curvature-induced helical flow structures to propagate downstream for relatively long distances (Dominguez Ruben et al, 2021;Lazzarin and Viero, 2023;Thorne et al, 1985). The distribution of the velocity at the free surface for the cross-section 4 (200 m downstream of the bridge) is presented in Figure 9 for the moderate peak flow condition of the 2022 event.…”
Section: Entropy Model Forced With a Single Value Of Free-surface Vel...mentioning
confidence: 99%
“…However, plenty of factors contributes in making the velocity distribution irregular. For instance, channel bends and deformed bathymetry produce large-scale secondary currents (Constantinescu et al, 2011;Lazzarin and Viero, 2023;Yang et al, 2012), and the presence of banks and of discontinuities of bed elevation in the spanwise directions can generate secondary currents of the second kind (Nikora and Roy, 2011;Proust and Nikora, 2020), which all increase the three-dimensionality of the flow field and alter the vertical and spanwise distribution of the flow velocity.…”
Abstract. Estimating the flow velocity and discharge in rivers is of particular interest for monitoring, modelling, and research purposes. Instruments for measuring water level and surface velocity are generally mounted on bridge decks, and this poses a challenge because the bridge structure (e.g., piers and abutments) can lead to perturbated flow fields. The current research aims to investigate the applicability of the entropy theory to estimate the velocity distribution and the discharge in the vicinity of river bridges. To this purpose, a Computational Fluid Dynamics (CFD) model is used to obtain three-dimensional flow fields along a stretch of the Paglia River (central Italy), where a historical multi-arch bridge strongly affects flood flows. The input data for the entropy model include the cross-sectional bathymetry and the surface velocity provided by the numerical simulations. Different flow conditions and cross-sections, either upstream and downstream of the bridge, are considered. It is found that the entropy model can be applied safely upstream of the bridge, also when forced with a single (i.e., the maximum) value of the surface velocity, with errors on total discharge below 13 % in the considered case. On the contrary, downstream the bridge, the wakes generated by the bridge piers strongly affect the velocity distribution, both in the spanwise and in the vertical directions, and for very long distances. Here, notwithstanding the complex and multimodal spanwise distribution of flow velocity, the entropy model estimates the discharge with error lower than 8 % if forced with the river-wide distribution of the surface velocity. The present study has important implications for the optimal positioning of sensors and suggest the potential of using CFD modelling and entropy theory jointly to foster the knowledge of river systems.
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