Dataset of Monitoring Water Quality Parameters Using Multi-source Data-driven Machine Learning Models

DOI:10.4121/d866419b-60fe-4fff-b2e3-104e2cc37381.v1
The DOI displayed 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/d866419b-60fe-4fff-b2e3-104e2cc37381

Datacite citation style

Zhao, Yubo (2025): Dataset of Monitoring Water Quality Parameters Using Multi-source Data-driven Machine Learning Models. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/d866419b-60fe-4fff-b2e3-104e2cc37381.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite

Dataset

Geolocation

The Yangtze River Basin in Hubei and Hunan provinces, China
lat (N): 28°–31.6°
lon (E): 110°–115°

Time coverage

2024-02-13

Licence

CC BY 4.0

The data is sourced from China's National Surface Water Quality Automatic Monitoring Real time Data Release System（ https://earthengine.google.com/ ）The data range is the water quality data of 74 monitoring stations in the Yangtze River Basin of Hubei Province, Hunan Province, China (longitude 110 ° -115 °, Latitude 28 ° -31.6 °), data types include water temperature, PH， Dissolved oxygen, chemical oxygen demand, total phosphorus, total nitrogen, ammonia nitrogen, turbidity, conductivity. The data collection time is February 13th, 2024.

History

  • 2025-04-23 first online, published, posted

Publisher

4TU.ResearchData

Format

CSV

Organizations

Heilongjiang University, Institute of water conservancy and electric power

DATA

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