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Çѱ¹¼öÀÚ¿øÇÐȸ / v.25, no.1, 1992³â, pp.93-100
´ÙÁßȸ±Í¸ðÇüÀ¸·Î ÃßÁ¤µÈ ¸ð¼ö¿¡ ÀÇÇÑ ÃÖÀû´ÜÀ§À¯·®µµÀÇ À¯µµ¿¡ °üÇÑ ¿¬±¸
( A Study on the Derivation of the Unit Hydrograph using Multiple Regression Model )
ÀÌÁ¾³²;±èä¿ø;ȲâÇö; °æÈñ´ëÇб³;ÀδöÀü¹®´ëÇÐ;¿ìº¸±â¼ú´Ü;
 
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Abstract A study on the Derivation of the Unit Hydrograph using Multiple Regression MoeÀÌ. The purpose of this study is to deriver an optimal unit hydrograph suing the multiple regression model, particularly when only small amount of data is available. The presence of multicollinearity among the input data can cause serious oscillations in the derivation of the unit hydrograph. In this case, the oscillations in the unit hydrograph ordinate are eliminated by combining the data. The data used in this study are based upon the collection and arrangement of rainfall-runoff data(1977-1989) at the Soyang-river Dam site. When the matrix X is the rainfall series, the condition number and the reciprocal of the minimum eigenvalue of XTX are calculated by the Jacobi an method, and are compared with the oscillation in the unit hydrograph. The optimal unit hydrograph is derived by combining the numerous rainfall-runoff data. The conclusions are as follows; 1)The oscillations in the derived unit hydrograph are reduced by combining the data from each flood event. 2) The reciprocals of the minimum eigenvalue of XTX, 1/k and the condition number CN are increased when the oscillations are active in the derived unit hydrograph. 3)The parameter estimates are validated by extending the model to the Soyang river Dam site with elimination of the autocorrelation in the disturbances. Finally, this paper illustrates the application of the multiple regression model to drive an optimal unit hydrograph dealing with the multicollinearity and the autocorrelation which cause some problems.
A study on the Derivation of the Unit Hydrograph using Multiple Regression MoeÀÌ. The purpose of this study is to deriver an optimal unit hydrograph suing the multiple regression model, particularly when only small amount of data is available. The presence of multicollinearity among the input data can cause serious oscillations in the derivation of the unit hydrograph. In this case, the oscillations in the unit hydrograph ordinate are eliminated by combining the data. The data used in this study are based upon the collection and arrangement of rainfall-runoff data(1977-1989) at the Soyang-river Dam site. When the matrix X is the rainfall series, the condition number and the reciprocal of the minimum eigenvalue of XTX are calculated by the Jacobi an method, and are compared with the oscillation in the unit hydrograph. The optimal unit hydrograph is derived by combining the numerous rainfall-runoff data. The conclusions are as follows; 1)The oscillations in the derived unit hydrograph are reduced by combining the data from each flood event. 2) The reciprocals of the minimum eigenvalue of XTX, 1/k and the condition number CN are increased when the oscillations are active in the derived unit hydrograph. 3)The parameter estimates are validated by extending the model to the Soyang river Dam site with elimination of the autocorrelation in the disturbances. Finally, this paper illustrates the application of the multiple regression model to drive an optimal unit hydrograph dealing with the multicollinearity and the autocorrelation which cause some problems.
 
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Çѱ¹¼öÀÚ¿øÇÐȸÁö / v.25, no.1, 1992³â, pp.93-100
Çѱ¹¼öÀÚ¿øÇÐȸ
ISSN : 1738-9488
UCI : G100:I100-KOI(KISTI1.1003/JNL.JAKO199211920093924)
¾ð¾î : Çѱ¹¾î
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