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...
| Main Authors: | , , , , |
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| Format: | Article |
| Published: |
Elsevier Ltd
2024
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| Online Access: | http://psasir.upm.edu.my/id/eprint/105818/ |