Articles | Volume 24, issue 2
https://doi.org/10.5194/hess-24-827-2020
https://doi.org/10.5194/hess-24-827-2020
Research article
 | 
24 Feb 2020
Research article |  | 24 Feb 2020

A data-based predictive model for spatiotemporal variability in stream water quality

Danlu Guo, Anna Lintern, J. Angus Webb, Dongryeol Ryu, Ulrike Bende-Michl, Shuci Liu, and Andrew William Western

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Latest update: 26 Sep 2023
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Short summary
This study developed predictive models to represent the spatial and temporal variation of stream water quality across Victoria, Australia. The model structures were informed by a data-driven approach, which identified the key controls of water quality variations from long-term records. These models are helpful to identify likely future changes in water quality and, in turn, provide critical information for developing management strategies to improve stream water quality.