An Adaptive Ensemble Framework for Flood Forecasting and Its Application in a Small Watershed Using Distinct Rainfall Interpolation Methods
Author:
Funder
Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Water Science and Technology,Civil and Structural Engineering
Link
https://link.springer.com/content/pdf/10.1007/s11269-023-03489-x.pdf
Reference56 articles.
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3. Chao L, Zhang K, Li Z, Wang J, Yao C, Li Q (2019) Applicability assessment of the CASCade Two Dimensional SEDiment (CASC2D-SED) distributed hydrological model for flood forecasting across four typical medium and small watersheds in China. J Flood Risk Manag 12(S1):e12518. https://doi.org/10.1111/jfr3.12518
4. Charalambous J, Rahman A, Carroll D (2013) Application of Monte Carlo simulation technique to design flood estimation: A case study for North Johnstone River in Queensland, Australia. Water Resour Manag 27(11):4099–4111. https://doi.org/10.1007/s11269-013-0398-9
5. Cheng M, Fang F, Kinouchi T, Navon IM, Pain CC (2020) Long lead-time daily and monthly streamflow forecasting using machine learning methods. J Hydrol 590:125376. https://doi.org/10.1016/j.jhydrol.2020.125376
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