A review on the scaling properties in maximum rainfall marginal distributions: theoretical background, probabilistic modeling, and recent developments-Reference-Cited by-同舟云学术

A review on the scaling properties in maximum rainfall marginal distributions: theoretical background, probabilistic modeling, and recent developments

Published:2023-09-14 Issue:12 Volume:37 Page:4541-4553
ISSN:1436-3240
Container-title:Stochastic Environmental Research and Risk Assessment
language:en
Short-container-title:Stoch Environ Res Risk Assess

Author:

Barbosa Alan de Gois^ORCID,Costa Veber A. F.^ORCID

Publisher

Springer Science and Business Media LLC

Subject

General Environmental Science,Safety, Risk, Reliability and Quality,Water Science and Technology,Environmental Chemistry,Environmental Engineering

Link

https://link.springer.com/content/pdf/10.1007/s00477-023-02546-6.pdf

Reference102 articles.

1. Avanzi F, De Michele C, Gabriele S, Ghezzi A, Rosso R (2015) Orographic signature on extreme precipitation of short durations. J Hydrometeorol 16(1):278–294. https://doi.org/10.1175/JHM-D-14-0063.1

2. Bairwa AK, Khosa R, Maheswaran R (2016) Developing intensity duration frequency curves based on scaling theory using linear probability weighted moments: a case study from India. J Hydrol 542:850–859. https://doi.org/10.1016/j.jhydrol.2016.09.056

3. Blanchet J, Ceresetti D, Molinié G, Creutin J-D (2016) A regional GEV scale-invariant framework for intensity–duration–frequency analysis. J Hydrol 540:82–95. https://doi.org/10.1016/j.jhydrol.2016.06.007

4. Bonaccorso B, Brigandì G, Aronica GT (2020) Regional sub-hourly extreme rainfall estimates in Sicily under a scale invariance framework. Water Resour Manag 34(14):4363–4380. https://doi.org/10.1007/s11269-020-02667-5

5. Boni G, Parodi A, Rudari R (2006) Extreme rainfall events: learning from raingauge time series. J Hydrol 327(3–4):304–314. https://doi.org/10.1016/j.jhydrol.2005.11.050