장기간연속수수량추정모형(長期間連續受水量推定模型)의 실용화(實用化) 연구(硏究) -우리나라 중소유역(中小流域)을 대상(對象)으로- = A Generalized Model on the Estimation of the Long - term Run - off Volume - with Special Reference to small and Medium Sized Catchment Areas-

다국어 초록 (Multilingual Abstract)

This study aimed at developing a generalized model on the estimation of the long - term run - off volume for practical purpose.
During the research period of last 3 years( 1986-1988), 3 types of estimation model on the long - term run - off volume(Effective rainfall model, unit hydrograph model and barne's model for dry season) had been developed by the author.
In this study, through regressional analysis between determinant factors (bi of effective rainfall model, ai of unit hydrograph model and Wi of barne's model) and catchment characteris- tics(catchment area, distance round the catchment area, massing degree coefficient, river - exte- nsion, river - slope, river - density, infiltration of Watershed) of 11 test case areas by multiple regressional method, a new methodology on the derivation of determinant factors from catchment characteristics in the watershed areas having no hydrological station was developed. Therefore, in the resulting step, estimation equations on run - off volume for practical purpose of which input facor is only rainfall were developed.
In the next stage, the derived equations were applied on the Kang - and Namgye - river catchment areas for checking of their goodness. The test results were as follows ;
1. In Kang - river area, average relative estimation errors of 72 hydrographs and of continuous daily run - off volume for 245 days( 1/5/1982 - 31/12) were calculated as 6.09%, 9.58% respectively.
2. In Namgye - river area, average relative estimation errors of 65 hydrographs and of conti-nuous daily run - off volume for 2fl days(5/4/1980-31/12) were 5.68%, 10.5% respectively.
In both cases, relative estimation error was averaged as 7.96%, and so, the methodology in this study might be hetter organized than Kaziyama's formula when comparing with the relative error of the latter, 24~54%.
However, two case studies cannot be the base materials enough for the full generalization of the model. So, in the future studies, many test case studies of this model should he carries out in the various catchment areas for making its generalization.