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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| Main Authors: | , , , , |
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| 格式: | Article |
| 語言: | English |
| 出版: |
Elsevier Ltd.
2024
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| 主題: | |
| 在線閱讀: | 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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