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Research on the impact of a typhoon on the accretion-erosion of mudflats: Based on UAV photogrammetry and in situ hydrodynamic measurements
Received date: 2023-03-08
Accepted date: 2023-04-20
Online published: 2024-07-23
Extreme events such as typhoons can change mudflats by tens of centimeters. It is important for coastal management and ecosystem maintenance to recognize changes in accretion-erosion during typhoons and to understand the mechanisms driving it. In this study, Unmanned Aerial Vehicle (UAV) photogrammetry based on the Structure-from-Motion (SfM) algorithm was used to generate Digital Elevation Models (DEM) of a mudflat in Eastern Chongming, Yangtze Estuary, before and after the passage of Typhoon “In-Fa” (July 2021). Hydrodynamic measurements were conducted from bare flats to marshes to explore the mechanisms of DEM changes. Changes in accretion-erosion observed by UAV photogrammetry presented an obvious zonation of eroded bare flats and accreted marshes. The accuracy of the DEMs is 4.1 cm. Under the impact of the typhoon, the erosion of the bare flat and the accretion of the marsh have a amplitude of ±32 cm. During typhoons, the wave height and water depth in the bare flat increases to the condition of wave breaking, and the surface sediment is eroded and carried by rising tides. But in marshes, the sediment carrying capacity of water columns decreases, and the sediments are deposited. Consequently, the mudflat presents an obvious zonation of accretion-erosion. This study provides a new perspective for deeply understanding the impact of typhoons on the accretion-erosion of mudflats by combining UAV photogrammetry and hydrodynamic measurements.
Xinmiao ZHANG , Liming XUE , Benwei SHI , Wenxiang ZHANG , Tianyou LI , Biaobiao PENG , Xiuzhen LI , Yaping WANG . Research on the impact of a typhoon on the accretion-erosion of mudflats: Based on UAV photogrammetry and in situ hydrodynamic measurements[J]. Journal of East China Normal University(Natural Science), 2024 , 2024(4) : 150 -160 . DOI: 10.3969/j.issn.1000-5641.2024.04.014
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