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- Title
River/stream water temperature forecasting using artificial intelligence models: a systematic review.
- Authors
Zhu, Senlin; Piotrowski, Adam P.
- Abstract
Water temperature is one of the most important indicators of aquatic system, and accurate forecasting of water temperature is crucial for rivers. It is a complex process to accurately predict stream water temperature as it is impacted by a lot of factors (e.g., meteorological, hydrological, and morphological parameters). In recent years, with the development of computational capacity and artificial intelligence (AI), AI models have been gradually applied for river water temperature (RWT) forecasting. The current survey aims to provide a systematic review of the AI applications for modeling RWT. The review is to show the progression of advances in AI models. The pros and cons of the established AI models are discussed in detail. Overall, this research will provide references for hydrologists and water resources engineers and planners to better forecast RWT, which will benefit river ecosystem management.
- Subjects
ARTIFICIAL intelligence; META-analysis; ECOSYSTEM management; WATER supply; RIVERS; WATER temperature; EPHEMERAL streams
- Publication
Acta Geophysica, 2020, Vol 68, Issue 5, p1433
- ISSN
1895-6572
- Publication type
Article
- DOI
10.1007/s11600-020-00480-7