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http://dx.doi.org/10.3741/JKWRA.2022.55.7.545

Evaluation of extreme rainfall estimation obtained from NSRP model based on the objective function with statistical third moment  

Cho, Hemie (Department of Civil and Environmental Engineering, Sejong University)
Kim, Yong-Tak (Department of Civil and Environmental Engineering, Hong Kong University of Science and Technology)
Yu, Jae-Ung (Department of Civil and Environmental Engineering, Sejong University)
Kwon, Hyun-Han (Department of Civil & Environmental Engineering, Sejong University)
Publication Information
Journal of Korea Water Resources Association / v.55, no.7, 2022 , pp. 545-556 More about this Journal
Abstract
It is recommended to use long-term hydrometeorological data for more than the service life of the hydraulic structures and water resource planning. For the purpose of expanding rainfall data, stochastic simulation models, such as Modified Bartlett-Lewis Rectangular Pulse (BLRP) and Neyman-Scott Rectangular Pulse (NSRP) models, have been widely used. The optimal parameters of the model can be estimated by repeatedly comparing the statistical moments defined through a combination of parameters of the probability distribution in the optimization context. However, parameter estimation using relatively small observed rainfall statistics corresponds to an ill-posed problem, leading to an increase in uncertainty in the parameter estimation process. In addition, as shown in previous studies, extreme values are underestimated because objective functions are typically defined by the first and second statistical moments (i.e., mean and variance). In this regard, this study estimated the parameters of the NSRP model using the objective function with the third moment and compared it with the existing approach based on the first and second moments in terms of estimation of extreme rainfall. It was found that the first and second moments did not show a significant difference depending on whether or not the skewness was considered in the objective function. However, the proposed model showed significantly improved performance in terms of estimation of design rainfalls.
Keywords
NSRP; Extreme rainfall; Objective function; Stochastic precipitation model; Poisson process;
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Times Cited By KSCI : 2  (Citation Analysis)
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