• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1491-1494
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• 2010

2000년 이후 국지성 호우로 인한 지역별 홍수량의 차이가 현저히 많이 나고 있다. 때문에 유역 내 주요시설물 및 인명피해를 줄이기 위해서는 유역의 특성을 최대한 반영한 홍수 분석이 필요하다. 본 연구에서는 충주댐 유역의 실측 강우량 및 유입량 자료를 이용하여 단위도를 유도하였다. 단위도 산정 방법은 강우자료의 모의기능을 추가한 Modified Clark 방법을 이용하였다. 단위도 관련 직접유출의 형태를 결정하는 주요 매개변수는 도달시간 $T_c$와 저류상수 K에 의하여 결정되며, 홍수량 산정 시 가장 중요한 매개변수라고 할 수 있다. 충주댐 유역의 2002년부터 2007년까지의 강우자료 중 대표 강우사상을 분리하여 강우사상별 매개변수를 추정하였다. 추정 결과 강우 사상별 형태에 따라 매개변수가 다르게 나타났다. 이는 강우의 패턴에 따라 댐에 유입되는 매개변수가 다르기 때문인 것으로 보인다.

• Journal of Korea Water Resources Association
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• v.35 no.1
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• pp.1-12
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• 2002

This study was intended to investigate the rainfall-runoff relationship with spatially distributed rainfall data, and then, to analyze and quantify the uncertainty induced by spatially averaging rainfall data. For constructing spatially distributed rainfall data, several historical rainfall events were extended spatially by simple kriging method based on the semivariogram as a function of the relative distance. Runoff was computed by two models; one was the modified Clark model with spatially distributed rainfall data and the other was the conventional Clark model with spatially averaged rainfall data. Rainfall errors and discharge errors occurred through this process were defined and analyzed with respect to various rain-gage network densities. The following conclusions were derived as the results of this work; 1) The conventional Clark parameters could be appropriate for translating spatially distributed rainfall data. 2) The parameters estimated by the modified Clark model are more stable than those of the conventional Clark model. 3) Rainfall and discharge errors are shown to be reduced exponentially as the density of rain-gage network is increased. 4) It was found that discharge errors were affected largely by rainfall errors as the rain-gage network density was small.

• Journal of Korea Water Resources Association
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• v.35 no.3
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• pp.307-319
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• 2002

This study used the WGR model to generate the rainfall input and the modified Clark method to estimate the runoff with the aim of investigating how the errors from the areal average rainfall propagates to runoff estimates. This was done for several cases of raingauge density and also by considering several storm directions. Summarizing the study results are as follows. (1) Rainfall and runoff errors decrease exponentially as the raingauge density increases. However, the error stagnates after a threshold density of raingauges. (2) Rainfall errors more affect to runoff estimates when the density of raingauges is relatively low. Generally, the ratio between estimation errors of rainfall and runoff volumes was found much less than one, which indicates that there is a smoothing effect of the basin. However, the ratio between estimation errors of rainfall to peak flow becomes greater than one to indicate the amplification of rainfall effect to peak flow. (3) For the study basin in this studs no significant effect of storm direction could be found. However, the runoff error becomes higher when the storm and drainage directions are identical. Also, the error was found higher for the peak flow than for the overall runoff hydrograph.

• Journal of The Korean Society of Agricultural Engineers
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• v.47 no.6
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• pp.3-14
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• 2005

Accurate estimation of the spatial distribution of rainfall is critical to the successful modeling of hydrologic processes. The objective of this study is to evaluate the applicability of spatially distributed rainfall data. Spatially distributed rainfall was calculated using Kriging method and Thiessen method. The application of spatially distributed rainfall was appreciated to the runoff response from the watershed. The results showed that for each method the coefficient of determination for observed hydrograph was $0.92\~0.95$ and root mean square error was $9.78\~10.89$ CMS. Ordinary Kriging method showed more exact results than Simple Kriging, Universal Kriging and Thiessen method, based on comparison of observed and simulated hydrograph. The coefncient of determination for the observed peak flow was 0.9991 and runoff volume was 0.9982. The accuracy of rainfall-runoff prediction depends on the extent of spatial rainfall variability.