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http://dx.doi.org/10.3741/JKWRA.2020.53.5.383

Bayesian parameter estimation of Clark unit hydrograph using multiple rainfall-runoff data  

Kim, Jin-Young (Department of Civil and Environmental Engineering, Sejong University)
Kwon, Duk-Soon (ISAN Corporation)
Bae, Deg-Hyo (Department of Civil and Environmental Engineering, Sejong University)
Kwon, Hyun-Han (Department of Civil and Environmental Engineering, Sejong University)
Publication Information
Journal of Korea Water Resources Association / v.53, no.5, 2020 , pp. 383-393 More about this Journal
Abstract
The main objective of this study is to provide a robust model for estimating parameters of the Clark unit hydrograph (UH) using the observed rainfall-runoff data in the Soyangang dam basin. In general, HEC-1 and HEC-HMS models, developed by the Hydrologic Engineering Center, have been widely used to optimize the parameters in Korea. However, these models are heavily reliant on the objective function and sample size during the optimization process. Moreover, the optimization process is carried out on the basis of single rainfall-runoff data, and the process is repeated for other events. Their averaged values over different parameter sets are usually used for practical purposes, leading to difficulties in the accurate simulation of discharge. In this sense, this paper proposed a hierarchical Bayesian model for estimating parameters of the Clark UH model. The proposed model clearly showed better performance in terms of Bayesian inference criterion (BIC). Furthermore, the result of this study reveals that the proposed model can also be applied to different hydrologic fields such as dam design and design flood estimation, including parameter estimation for the probable maximum flood (PMF).
Keywords
Single event rainfall-runoff; Clark unit hydrograph model; Basin characteristic; Hierarchical bayesian; Parameter optimization;
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