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http://dx.doi.org/10.3741/JKWRA.2009.42.2.149

Parameter Regionalization of Semi-Distributed Runoff Model Using Multivariate Statistical Analysis  

Lee, Byong-Ju (Dept. of Civil and Environmental Engrg., Sejong Univ)
Jung, Il-Won (Dept. of Civil and Environmental Engrg., Sejong Univ)
Bae, Deg-Hyo (Dept. of Civil and Environmental Engrg., Sejong Univ)
Publication Information
Journal of Korea Water Resources Association / v.42, no.2, 2009 , pp. 149-160 More about this Journal
Abstract
The objective of this study is to suggest parameter regionalization scheme which is integrated two multivariate statistical methods: principal components analysis(PCA) and hierarchical cluster analysis(HCA). This technique is to apply semi-distributed rainfall-runoff model on ungauged catchments. 7 catchment characteristics (area, mean altitude, mean slope, ratio of forest, water content at saturation, field capacity and wilting point) are estimated for 109 mid-sized sub-basins. The first two components from PCA results account for 82.11% of the total variance in the dataset. Component 1 is related to the location of the catchments relevant to the altitude and Component 2 is connected with the area of these. 103 ungauged catchments are clustered using HCA as the following 6 groups: Goesan 23, Andong 6, Imha 5, Hapcheon 21, Yongdam 4, Seomjin 44. SWAT model is used to simulate runoff and the parameters of the model on the 6 gauged basins are estimated. The model parameters were regionalized for Soyang, Chungju and Daecheong dam basins which are assumed as ungauged ones. The model efficiency coefficients of the simulated inflows for these three dams were at least 0.8. These results also mean that goodness of fit is high to the observed inflows. This research will contribute to estimate and analyze hydrologic components on the ungauged catchments.
Keywords
Parameter Regionalization; Principal Component Analysis; Hierarchical Cluster analysis; SWAT;
Citations & Related Records
Times Cited By KSCI : 8  (Citation Analysis)
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