Articles | Volume 16, issue 2
https://doi.org/10.5194/essd-16-1137-2024
© Author(s) 2024. This work is distributed under the Creative Commons Attribution 4.0 License.
Data description paper
| 
27 Feb 2024
Data description paper |
| 27 Feb 2024
| 27 Feb 2024
An extensive spatiotemporal water quality dataset covering four decades (1980–2022) in China
Related authors
Geosci. Model Dev., 16, 2583–2606, 2023
Hydrol. Earth Syst. Sci., 27, 1627–1644, 2023
Hydrol. Earth Syst. Sci., 27, 647–671, 2023
Cited articles
Allen, C.: A review of scientific advancements in datasets derived from big data for monitoring the Sustainable Development Goals, Sustain. Sci., 16, 1701–1716, https://doi.org/10.1007/s11625-021-00982-3, 2021.
Bowes, M. J., Armstrong, L. K., Harman, S. A., Wickham, H. D., Nicholls, D. J. E., Scarlett, P. M., Roberts, C., Jarvie, H. P., Old, G. H., Gozzard, E., Bachiller-Jareno, N., and Read, D. S.: Weekly water quality monitoring data for the River Thames (UK) and its major tributaries (2009–2013): the Thames Initiative research platform, Earth Syst. Sci. Data, 10, 1637–1653, https://doi.org/10.5194/essd-10-1637-2018, 2018.
Cai, L. and Zhu, Y.: The challenges of data quality and data quality assessment in the big data era, Data Sci. J., 14, 2, https://doi.org/10.5334/dsj-2015-002, 2015.
Chen, J., Zheng, T., Garg, A., Xu, L., Li, S., and Fei, Y.: Alternative maritime power application as a green port strategy: barriers in China, J. Clean. Prod., 213, 825–837, https://doi.org/10.1016/j.jclepro.2018.12.177, 2019.
Crochemore, L., Isberg, K., Pimentel, R., Pineda, L., Hasan, A., and Arheimer, B.: Lessons learnt from checking the quality of openly accessible river flow data worldwide, Hydrol. Sci. J., 65, 699–711, https://doi.org/10.1080/02626667.2019.1659509, 2020.
