Potential of Support Vector Machine Fed by ERA5 for Predicting Daily Discharge in the High Atlas of Morocco
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-47079-0_18
Reference10 articles.
1. Boudhar, A., Hanich, L., Boulet, G., Duchemin, B., Berjamy, B., & Chehbouni, A. (2009). Evaluation of the Snowmelt Runoff model in the Moroccan High Atlas Mountains using two snow-cover estimates. Hydrological Sciences Journal, 54(6), 1094–1113. https://doi.org/10.1623/hysj.54.6.1094
2. Chaponnière, A., Boulet, G., Chehbouni, A., & Aresmouk, M. (2008). Understanding hydrological processes with scarce data in a mountain environment. Hydrological Processes, 22(12), 1908–1921. https://doi.org/10.1002/hyp.6775
3. Giorgi, F., & Lionello, P. (2008). Climate change projections for the Mediterranean region. Global and Planetary Change, 63(2–3), 90–104. https://doi.org/10.1016/j.gloplacha.2007.09.005
4. Lange, H., & Sippel, S. (2020). Machine learning applications in hydrology (pp. 233–257). Springer. https://doi.org/10.1007/978-3-030-26086-6_10
5. Liu, D., Zhang, Y., Zhang, J., Xiong, L., Liu, P., Chen, H., & Yin, J. (2021). Rainfall estimation using measurement report data from time-division long term evolution networks. Journal of Hydrology, 600, 126530. https://doi.org/10.1016/j.jhydrol.2021.126530
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