Comparative performance of different probability distribution functions for maximum rainfall estimation at different time scales
Author:
Publisher
Springer Science and Business Media LLC
Subject
General Earth and Planetary Sciences,General Environmental Science
Link
https://link.springer.com/content/pdf/10.1007/s12517-021-08580-4.pdf
Reference56 articles.
1. Ahmad I, Ahmad T, Almanjahie IM (2019) Modelling of extreme rainfall in Punjab: Pakistan using bayesian and frequentist approach. Appl Ecol Environ Res 17(6):13729–13748
2. Alahmadi F (2019) Evaluation of the efficiency of conventional and unconventional probability distribution functions for rainfall frequency models in arid environments. 8th International Conference on Water Resources and Arid Environments. ICWRAE 8:76–81
3. Alam MA, Emura K, Farnham C, Yuan J (2018) Best-fit probability distributions and return periods for maximum monthly rainfall in Bangladesh. Climate 6:9. https://doi.org/10.3390/cli6010009
4. Amin TA, Rizwan M, Alazba AA (2016) A best-fit probability distribution for the estimation of rainfall in northern regions of Pakistan. Open Life Science 11:432–440
5. Asim M, Nath S (2015) Study on rainfall probability analysis at Allahabad district of Uttar Pradesh. J Biol Agric Healthc 5(11):214–222
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