Abstract
AbstractKnowledge of the static and morphodynamic components of the river bed is important for the maintenance of waterways. Under the action of a current, parts of the river bed sediments can move in the form of dunes. Recordings of the river bed by multibeam echosounding are used as input data within a morphological analysis in order to compute the bedload transport rate using detected dune shape and migration. Before the morphological analysis, a suitable processing of the measurement data is essential to minimize inherent uncertainties. This paper presents a simulation-based evaluation of suitable data processing concepts for vertical sections of bed forms based on a case study at the river Rhine. For the presented spatial approaches, suitable parameter sets are found, which allow the reproduction of nominal dune parameters in the range of a few centimetres. However, if parameter sets are chosen inadequately, the subsequently derived dune parameters can deviate by several decimetres from the simulated truth. A simulation-based workflow is presented, to find the optimal hydrographic data processing strategy for a given dune geometry.
Funder
Bundesministerium für Verkehr und Digitale Infrastruktur
Bundesanstalt für Gewässerkunde
Publisher
Springer Science and Business Media LLC
Subject
Earth and Planetary Sciences (miscellaneous),Instrumentation,Geography, Planning and Development
Reference24 articles.
1. Akima H (1969) A method of smooth curve fitting. Tech. Rep, ESSA Research Laboratories
2. Artz T, Willersin D (2020) Hydrographische maßnahmen für eine smart-bwastr. Interdisziplinärer Wasserbau im digitalen Wandel 63:225–234
3. Bechteler W (2006) Sedimentquellen und Transportprozesse, Sustainable Sediment Management in Alpine Reservoirs considering ecological and economical aspects, vol 2. Universität der Bundeswehr München, Institut für Wasserwesen, Munchen
4. Bradley RW, Venditti JG (2019) Transport scaling of dune dimensions in shallow flows. J Geophys Res Earth Surf 124(2):526–547. https://doi.org/10.1029/2018JF004832
5. Chicco D, Jurman G (2020) The advantages of the Matthews correlation coefficient (mcc) over f1 score and accuracy in binary classification evaluation. BMC Genom. https://doi.org/10.1186/s12864-019-6413-7
Cited by
1 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献