Evaluating the Impact of Large-Scale Climatic Indices as Inputs for Forecasting Monthly River Flow in Mazandaran Province, Iran
Author:
Funder
Bu-Ali Sina University
Publisher
Springer Science and Business Media LLC
Subject
Geochemistry and Petrology,Geophysics
Link
https://link.springer.com/content/pdf/10.1007/s00024-022-02970-9.pdf
Reference68 articles.
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2. Aghelpour, P., Guan, Y., Bahrami-Pichaghchi, H., Mohammadi, B., Kisi, O., & Zhang, D. (2020). Using the MODIS sensor for snow cover modeling and the assessment of drought effects on snow cover in a mountainous area. Remote Sensing, 12(20), 3437. https://doi.org/10.3390/rs12203437
3. Aghelpour, P., Kisi, O., & Varshavian, V. (2021a). Multivariate drought forecasting in short-and long-term horizons using MSPI and data-driven approaches. Journal of Hydrologic Engineering, 26(4), 04021006. https://doi.org/10.1061/(ASCE)HE.1943-5584.0002059
4. Aghelpour, P., Singh, V. P., & Varshavian, V. (2021b). Time series prediction of seasonal precipitation in Iran, using data-driven models: A comparison under different climatic conditions. Arabian Journal of Geosciences, 14(7), 1–14. https://doi.org/10.1007/s12517-021-06910-0
5. Aghelpour, P., & Varshavian, V. (2020). Evaluation of stochastic and artificial intelligence models in modeling and predicting of river daily flow time series. Stochastic Environmental Research and Risk Assessment, 34(1), 33–50. https://doi.org/10.1007/s00477-019-01761-4
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