Data underlying the research on the Prediction of dissolved oxygen in rivers based on a fusion model with multiple data sources and algorithms, and discussion of the correlation of dissolved oxygen in rivers. (dataset)

Data underlying the research on the Prediction of dissolved oxygen in rivers based on a fusion model with multiple data sources and algorithms, and discussion of the correlation of dissolved oxygen in rivers.

doi:10.4121/0a570f87-e533-4d69-894e-b4f73f95ab42.v1

The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/0a570f87-e533-4d69-894e-b4f73f95ab42

Datacite citation style:

Zhao, Yubo (2024): Data underlying the research on the Prediction of dissolved oxygen in rivers based on a fusion model with multiple data sources and algorithms, and discussion of the correlation of dissolved oxygen in rivers. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/0a570f87-e533-4d69-894e-b4f73f95ab42.v1

Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

categories

keywords

dissolved oxygen (DO), DO water predicted, Multi-source data fusion, water quality monitoring

geolocation

The names of stations 1-5 are Gujiaqiao, Lucheng, Wangjiangjing, Wangting Upstream, and Xinfeng Town，the Grand Canal, China

licence

CC BY 4.0

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by Yubo Zhao

Dissolved oxygen data for 1-5 sites along the Beijing Hangzhou Grand Canal. Meteorological and water quality data for station 1. The latitude and longitude of stations 1-5 are (120.219575, 30.285611), (119.74962, 31.902095), (120.707958, 30.885265), (120.428448, 31.463612), and (119.571925, 32.126514), respectively.

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