期刊
HYDROLOGICAL PROCESSES
卷 32, 期 11, 页码 1635-1647出版社
WILEY
DOI: 10.1002/hyp.11516
关键词
Bayesian estimation; extreme precipitation; IDF curves; model selection; multiscaling
资金
- EU's H2020 Research and Innovation Program [690462]
- H2020 Societal Challenges Programme [690462] Funding Source: H2020 Societal Challenges Programme
Rainfall intensity-duration-frequency (IDF) curves are a standard tool in urban water resources engineering and management. They express how return levels of extreme rainfall intensity vary with duration. The simple scaling property of extreme rainfall intensity, with respect to duration, determines the form of IDF relationships. It is supposed that the annual maximum intensity follows the generalized extreme value (GEV) distribution. As well known, for simple scaling processes, the location parameter and scale parameter of the GEV distribution obey a power law with the same exponent. Although, the simple scaling hypothesis is commonly used as a suitable working assumption, the multiscaling approach provides a more general framework. We present a new IDF relationship that has been formulated on the basis of the multiscaling property. It turns out that the GEV parameters (location and scale) have a different scaling exponent. Next, we apply a Bayesian framework to estimate the multiscaling GEV model and to choose the most appropriate model. It is shown that the model performance increases when using the multiscaling approach. The new model for IDF curves reproduces the data very well and has a reasonable degree of complexity without overfitting on the data.
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