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http://dx.doi.org/10.3741/JKWRA.2019.52.9.589

Assessment of variability and uncertainty in bias correction parameters for radar rainfall estimates based on topographical characteristics  

Kim, Tae-Jeong (Research & Development Division, Korea Institute of Hydrological Survey)
Ban, Woo-Sik (Hangang River Regional Division Water Resources Management Center, K-Water)
Kwon, Hyun-Han (Department of Civil & Environmental Engineering, Sejong University)
Publication Information
Journal of Korea Water Resources Association / v.52, no.9, 2019 , pp. 589-601 More about this Journal
Abstract
Various applications of radar rainfall data have been actively employed in the field of hydro-meteorology. Since radar rainfall is estimated by using predefined reflectivity-rainfall intensity relationships, they may not have sufficient reproducibility of observations. In this study, a generalized linear model is introduced to better capture the Z-R relationship in the context of bias correction within a Bayesian regression framework. The bias-corrected radar rainfall with the generalized linear model is more accurate than the widely used mean field bias correction method. In addition, we analyzed variability of the bias correction parameters under various geomorphological conditions such as the height of the weather station and the separation distance from the radar. The identified relationship is finally used to derive a regionalized formula which can provide bias correction factors over the entire watershed. It can be concluded that the bias correction parameters and regionalized method obtained from this study could be useful in the field of radar hydrology.
Keywords
Radar rainfall; Bias correction; Bayesian; Generalized linear model; Regionalization;
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Times Cited By KSCI : 4  (Citation Analysis)
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