Bathymetric modeling of sediments and organic carbon of polluted rivers in southeastern China
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Rivers in low plains in the subtropical regions of China, where the population is dense and economies are active and well-developed, might be a large terrestrial carbon pool. This present study of the Sanyang wetlands in Wenzhou, southeastern China, aims to quantitatively estimate the volume of sediments in this region’s polluted river systems and their carbon storage.
Materials and methods
The bathymetry of river sections were surveyed using an echo sounder equipped with a differential GPS. An underwater digital elevation model (DEM) was then developed using the anisotropic ordinary Kriging method. Sediment samples were collected and analyzed for carbon content and sediment properties. Carbon storage in sediments was calculated using bathymetric and sediment analysis data.
Results and discussion
The studied rivers have been receiving organic pollutants from local residences and industries for decades. Results from a river network of 1.2 km2 revealed a total carbon storage of 46.7 million kg in the sediments which had a volume of 1.4 million m3, with the upper 20 cm depth of sediments contributing about one third of this carbon storage.
The present work demonstrated that GIS technologies can be used to create digital river sediment surfaces and assess sediment amounts as well as determine the spatial distribution of sediments and their components. This could provide further insight into river restoration planning and other options from a carbon-balance perspective.
KeywordsBathymetric surface Carbon storage Sediment
We wish to thank the students (Wang Ting, Wang Qian, Zhu Shenwu, Wu Chunjie, to name a few) from the Environmental Sciences Program of Wenzhou University who were involved in the sampling, field measurements, and laboratory analysis. This study was funded by the Science and Technology Department of Zhejiang Province (Project No. 2012C23023), Zhejiang Environmental Protection Bureau (Project No. 2011B26), and Wenzhou Science and Technology Bureau (Project No. S20150022). We are also grateful for the support provided by the Wenzhou Municipal Government, Wenzhou University, and Foreign Experts program to undertake this study. The authors would also like to acknowledge the Idaho EPSCoR NSF funding (IIA-1301792).
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