Synergistic approach for streamflow forecasting in a glacierized catchment of western Himalaya using earth observation and machine learning techniques
Author:
Funder
National Centre for Polar and Ocean Research, Goa, India
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s12145-024-01322-6.pdf
Reference116 articles.
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2. Abro MI, Wei M, Zhu D, Elahi E, Ali G, Khaskheli MA, Shah AR, Nkunzimana A (2020) Hydrological evaluation of satellite and reanalysis precipitation products in the glacier-fed river basin (Gilgit). Arab J Geosci 13 (631):1–13. https://doi.org/10.1007/s12517-020-05621-2
3. Adnan RM, Liang Z, Trajkovic S, Zounemat-Kermani M, Li B, Kisi O (2019) Daily streamflow prediction using optimally pruned extreme learning machine. J Hydrol 577:123981. https://doi.org/10.1016/j.jhydrol.2019.123981
4. Adnan, R.M., Zounemat-Kermani, M., Kuriqi, A., Kisi, O., 2021. Machine Learning Method in Prediction Streamflow Considering Periodicity Component. https://doi.org/10.1007/978-981-15-5772-9_18
5. Akpovi BA, Zhu D, Abro MI, Lawin AE, Houngnibo M, Bessou J (2022) Hydrological appraisal using multi-source rainfall data in PDM model over the Qinhuai River basin in China. Arab J Geosci 15:1–14. https://doi.org/10.1007/s12517-022-09545-x
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