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• W3206717460 endingPage "113957" @default.
• W3206717460 startingPage "113957" @default.
• W3206717460 abstract "Coastal wetlands are the most valuable ecosystems on the earth but facing severe degradation and losses owing to climate change and anthropogenic activities. Many ecological engineering projects (EEP) have been conducted to mitigate the degradation of coastal wetlands. However, the geomorphological impacts of EEP on coastal wetlands have not been well documented. In this study, a method employed a process-based hydrodynamic model and remote sensing (RS) was developed to evaluate the impacts of EEP on the geomorphological change of a prototype Ramsar site. Results demonstrated that RS can improve the quality of bathymetry data for the numerical model with a decrease of RMSE of bathymetry data from 0.52 m to 0.3 m. RS data also showed good capacity in trend detection of geomorphological change spatially. Results showed the Chongming Dongtan wetland experienced erosion with an annual rate of -0.035 m/yr from 2013 to 2016 after the implementation of EEP. The deposition rate changed significantly in the area within 200 m of the EEP. It is found that the EEP modified the composition of vegetation, sediment transportation, as well as substrate stability, affecting the geomorphological change of coastal wetlands. The study suggested that the EEP is a direct and effective way to restore the coastal habitats for waterbirds from moderate anthropogenic disturbance. However, the modification of the coastal wetland ecosystem by EEP will potentially increase the vulnerability to global climate change. Therefore, Future studies are needed to further evaluate the advantages and disadvantages of EEP and identify a more sustainable approach for coastal management." @default.
• W3206717460 created "2021-10-25" @default.
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• W3206717460 date "2022-01-01" @default.
• W3206717460 modified "2023-10-18" @default.
• W3206717460 title "Tracking the environmental impacts of ecological engineering on coastal wetlands with numerical modeling and remote sensing" @default.
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• W3206717460 doi "https://doi.org/10.1016/j.jenvman.2021.113957" @default.
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