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

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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 G...

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Bibliographic Details
Main Authors:	Ji, Hong Kang, Mirzaei, Majid, Lai, Sai Hin, Dehghani, Adnan, Dehghani, Amin
Format:	Article
Published:	Elsevier Ltd 2024
Online Access:	http://psasir.upm.edu.my/id/eprint/105818/

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