Subaqueous dunes are the building blocks of sand-bedded rivers, affecting flood risk, navigation and the stability of infrastructure (

Abstract. Systematic identification and characterization of bedforms from bathymetric data are crucial in many studies of fluvial processes. Automated and accurate processing of bed elevation data is challenging where dune fields are complex or irregular and (especially) where multiple scales co-exist. Here, we introduce a new tool to quantify dune properties from bathymetric data representing large primary and smaller superimposed secondary dunes. A first step in the procedure is to decompose the bathymetric data using a LOESS algorithm. Steep lee-side slopes of primary dunes are preserved by implementing objective breaks in the algorithm, accounting for discontinuities in the bed elevation profiles at the toe of the lee-side slope. The steep lee slopes are then approximated by fitting a sigmoid function. Following the decomposition of the bathymetric data, bedforms are identified based on a zero crossing, and morphological properties are calculated. The approach to bedform decomposition presented herein is particularly applicable where secondary dunes are large and filtering using conventional continuously differentiable functions could thus easily lead to undesired smoothing of the primary morphology. Application of the tool to two bathymetric maps demonstrates that it successfully decomposes bathymetric data, identifies primary and secondary dunes, and preserves steeper lee-side slopes of primary dunes.

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