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Implementing generative adversarial network (GAN) as a data-driven multi-site stochastic weather generator for flood frequency estimation

Precipitation is a key driving factor of hydrologic modeling for impact studies. However, there are challenges due to limited long-term data availability and complex parameterizations of existing stochastic weather generators (SWGs) due to spatiotemporal uncertainty. We introduced state-of-the-art...

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Bibliographic Details
Main Authors:	Ji, Hong Kang, Majid, Mirzaei, Lai, Sai Hin, Adnan, Dehghani, Amin, Dehghani
Format:	Article
Language:	English
Published:	Elsevier Ltd. 2024
Subjects:	TA Engineering (General). Civil engineering (General)
Online Access:	http://ir.unimas.my/id/eprint/44860/2/Implementing%20generative.pdf http://ir.unimas.my/id/eprint/44860/ https://www.sciencedirect.com/science/article/pii/S1364815223002827 https://doi.org/10.1016/j.envsoft.2023.105896
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