Univariate and Bivariate Hydrological Drought Frequency Analysis by Copula Functions
Author:
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/s11269-023-03586-x.pdf
Reference78 articles.
1. AghaKouchak A, Bárdossy A, Habib E (2010) Conditional simulation of remotely sensed rainfall data using a non-Gaussian v-transformed copula. Adv Water Resour 33:624–634. https://doi.org/10.1016/j.advwatres.2010.02.010
2. Akaike H (1976) An information criteron (AIC). Math Sci 14:5–7
3. Al-Juboori AM (2023) Prediction of hydrological drought in semi-arid regions using a novel hybrid model. Water Resour Manag 37:3657–3669. https://doi.org/10.1007/s11269-023-03520-1
4. Avsaroglu Y, Gumus V (2022) Assessment of hydrological drought return periods with bivariate copulas in the Tigris river basin. Turkey Meteorol Atmos Phys 134:95. https://doi.org/10.1007/s00703-022-00933-2
5. Ayantobo OO, Li Y, Song S (2019) Copula-based trivariate drought frequency analysis approach in seven climatic sub-regions of mainland China over 1961–2013. Theor Appl Climatol 137:2217–2237. https://doi.org/10.1007/s00704-018-2724-x
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