Lee, JiyongMusa, MirkoGuala, Michele2021-02-122021-02-122021-02-12https://hdl.handle.net/11299/218358This bedform tracking tool identifies bedforms based on the sign change of the gradient of streambed profiles, dz/dx. Before fed to the bedform tracking algorithm, bed elevation profiles (BEPs) are filtered using Fast Fourier Transform (FFT) decomposition to extract large bedforms buried underneath superimposed secondary bedform features. Thereafter, characteristics (morphology and kinematics) of individual bedforms are quantified. Please refer README for more details.Quantifying bedform characteristics is crucial because bedforms are omnipresent and play an important role in fluvial environments. Bedforms induce form drag against flows and can significantly alter water depth, flow velocity, and sediment transport rate (i.e. the hydraulic roughness of channels can be parameterized with bedforms). In addition, ship navigation can be constrained by the presence and distributions of bedform crests; and localized scour within bedform troughs can deteriorate performance of fluvial infrastructures (e.g. containment walls, embedded pipes, or groynes). Despite of its importance, characterizing bedforms has been challenges due to inherent multi-scale features observed in channel bathymetries in both natural rivers and laboratory flumes. To tackle such challenges, we developed a bedform tracking tool coupled with Fast Fourier Transform (FFT) decomposition. A key advantage of the presented bedform tracking method is that bedform characteristics (morphology and kinematics) can be quantified in a wider range of scales.CC0 1.0 Universalsediment transportriver morphodynamicsbedformDatasethttps://doi.org/10.13020/e1fe-sb56