Data-driven artificial intelligence-based streamflow forecasting, a review of methods, applications, and tools

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Jahanbani, Heerbod ORCID: 0000-0003-1599-9147, Ahmed, Khandakar ORCID: 0000-0003-1043-2029 and Gu, Bruce ORCID: 0000-0002-3008-6285 (2024) Data-driven artificial intelligence-based streamflow forecasting, a review of methods, applications, and tools. Journal of the American Water Resources Association, 60 (6). pp. 1095-1119. ISSN 1093-474X

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Item type Article
URI https://vuir.vu.edu.au/id/eprint/49324
DOI 10.1111/1752-1688.13229
Official URL https://onlinelibrary.wiley.com/doi/10.1111/1752-1...
Subjects Current > FOR (2020) Classification > 3707 Hydrology
Current > FOR (2020) Classification > 4005 Civil engineering
Current > FOR (2020) Classification > 4602 Artificial intelligence
Current > Division/Research > Institute for Sustainable Industries and Liveable Cities
Keywords streamflow forecasting; data-driven; artificial intelligence (AI); machine learning; stochastic data
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