Abstract. Systematic identification and characterization of bedforms from bathymetric data are crucial in many studies focused on fluvial processes. Automated and accurate processing of bed elevation data is challenging where dune fields are complex, irregular and, especially, where multiple scales co-exist. Here, we introduce a new tool to quantify dune properties from bathymetric data representing multiple dune scales. A first step in the procedure is to decompose the bathymetric data based on a LOESS algorithm. Steep dune lee side slopes are accounted for by implementing objective breaks in the algorithm, accounting for discontinuities in the bed level profiles, often occurring at the toe of the lee side slope of dunes. The steep lee slopes are then approximated by fitting a sigmoid function. Following the decomposition of the bathymetric data, bedforms are identified based on zero-crossing, and the relevant properties are calculated. The approach to decompose bedforms adopted in the presented tool is particularly applicable where secondary dunes are large and thus filtering could easily lead to undesired smoothing of the primary morphology. Application of the tool to two bathymetric maps demonstrates that the decomposition and identification are successful, as the lee side slopes are better preserved.
Identification and Characterization of CYP2C18 in the Cynomolgus Macaque (Macaca fascicularis)
