Bedload transport analysis using image processing techniques

• Autorzy: Ermilov Alexander A , Fleit Gábor , Conevski Slaven , Guerrero Massimo , Baranya Sándor , Rüther Nils

Identyfikatory

DOI

10.1007/s11600-022-00791-x

• Języki publikacji: EN

Abstrakty

EN

Bedload transport is an important factor to describe the hydromorphological processes of fluvial systems. However, conventional bedload sampling methods have large uncertainty, making it harder to understand this notoriously complex phenomenon. In this study, a novel, image-based approach, the Video-based Bedload Tracker (VBT), is implemented to quantify gravel bedload transport by combining two different techniques: Statistical Background Model and Large-Scale Particle Image Velocimetry. For testing purposes, we use underwater videos, captured in a laboratory fume, with future field adaptation as an overall goal. VBT offers a full statistics of the individual velocity and grainsize data for the moving particles. The paper introduces the testing of the method which requires minimal preprocessing (a simple and quick 2D Gaussian filter) to retrieve and calculate bedload transport rate. A detailed sensitivity analysis is also carried out to introduce the parameters of the method, during which it was found that by simply relying on literature and the visual evaluation of the resulting segmented videos, it is simple to set them to the correct values. Practical aspects of the applicability of VBT in the field are also discussed and a statistical filter, accounting for the suspended sediment and air bubbles, is provided.

Słowa kluczowe

EN

bedload transport; image processing; Statistical Background Model; Large-Scale Particle Image Velocimetry; Video-based Bedload Tracker

PL

transport ładunków; przetwarzanie obrazu

• Wydawca: Instytut Geofizyki PAN ; Springer
• Czasopismo: Acta Geophysica
• Rocznik: 2022
• Tom: Vol. 70, no 5
• Strony: 2341--2360
• Opis fizyczny: Bibliogr. 59 poz.

Twórcy

autor

Ermilov Alexander A

• Department of Hydraulic and Water Resources Engineering, Faculty of Civil Engineering, Budapest University of Technology and Economics, Budapest, Hungary

• https://orcid.org/0000-0002-2650-5870

autor

Fleit Gábor

• Department of Hydraulic and Water Resources Engineering, Faculty of Civil Engineering, Budapest University of Technology and Economics, Budapest, Hungary
• Water Management Research Group of the Eötvös Lóránd Research Network, Budapest, Hungary

autor

Conevski Slaven

• Department of Civil and Environmental Engineering, Norwegian University of Science and Technology, Trondheim, Norway

autor

Guerrero Massimo

• Department of Civil, Chemical, Environmental, and Materials Engineering, University of Bologna, Bologna, Italy

autor

Baranya Sándor

• Department of Hydraulic and Water Resources Engineering, Faculty of Civil Engineering, Budapest University of Technology and Economics, Budapest, Hungary

autor

Rüther Nils

• Department of Civil and Environmental Engineering, Norwegian University of Science and Technology, Trondheim, Norway

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Uwagi

PL

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).