• Journal of Korean Society on Water Environment
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• v.23 no.4
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• pp.527-534
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• 2007

To operate scientifical and integrated management of water resources, it needs to identify clearly the quantitative variation and moving pathway of water resources in a basin. Moreover, it needs to also estimate more precisely the amount of runoff generating from the precipitation. Thus, in this study, to carry out more reliable hydrologic analyses, the runoff characteristics according to detailed runoff components and water balance in a basin are analyzed. As a result of yearly water balance analyses, during the period of drought year, the loss is bigger than that of 6-year mean loss and the return flow of groundwater is the most dominant component of runoff. During the period of flood year, the loss is smaller about 4% than that of 6-year mean loss and the subsurface water is the most dominant component of runoff. The loss due to the interception and evapotranspiration for 6-year mean loss is about 53% of the total rainfall, the mean runoff ratio is about 27% and the baseflow is about 22%.

• Journal of Korea Water Resources Association
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• v.36 no.3 s.134
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• pp.423-436
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• 2003

The objective of this study is to propose an automatic parameter estimation scheme considering runoff components of Tank model. It estimates model parameters by Powell's automatic algorithm based on the runoff component separation of the observed hydrograph by using digital filter method. The selected study areas are the 4 main dam sites on the Han River. The simulated flows are compared with the observed flows depending on whether runoff component consideration or not. As a result, the estimated model parameters from classical Powell's method only can relatively well simulate the time variation of total runoff, but gives poor runoff component simulations. Therefore, it can be concluded that the proposed automatic parameter estimation scheme in this study Is more reliable and objective.

• Proceedings of the Korea Water Resources Association Conference
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• 1997.05a
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• pp.192-198
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• 1997

The spatial variation of saturation tendency can be calculated from the Digital Elevation Model (DEM) employing the multiple flow direction algorithm on the platform of Geographic Resources Support Analysis System (GRASS). It is expected that a bettter understanding of dynamical runoff processes in hillslope hydrological scale is obtained through tracing various runoff path such as infiltration excess overland flow component, strutation excess overland flow component and subsurface runoff component. A procedure is suggested to consider the effect of a tile system on calculating the topographic index. A small agricultural subwatershed (3.4 km2) is used for this study.

• Magazine of the Korean Society of Agricultural Engineers
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• v.22 no.3
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• pp.75-87
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• 1980

Most hydro]ogic phenomena are the complex and organic products of multiple causations like climatic and hydro-geological factors. A certain significant correlation on the run-off in river basin would be expected and foreseen in advance, and the effect of each these causual and associated factors (independant variables; present-month rainfall, previous-month run-off, evapotranspiration and relative humidity etc.) upon present-month run-off(dependent variable) may be determined by multiple regression analysis. Functions between independant and dependant variables should be treated repeatedly until satisfactory and optimal combination of independant variables can be obtained. Reliability of the estimated function should be tested according to the result of statistical criterion such as analysis of variance, coefficient of determination and significance-test of regression coefficients before first estimated multiple regression model in historical sequence is determined. But some error between observed and estimated run-off is still there. The error arises because the model used is an inadequate description of the system and because the data constituting the record represent only a sample from a population of monthly discharge observation, so that estimates of model parameter will be subject to sampling errors. Since this error which is a deviation from multiple regression plane cannot be explained by first estimated multiple regression equation, it can be considered as a random error governed by law of chance in nature. This unexplained variance by multiple regression equation can be solved by stochastic approach, that is, random error can be stochastically simulated by multiplying random normal variate to standard error of estimate. Finally hybrid model on estimation of monthly run-off in nonhistorical sequence can be determined by combining the determistic component of multiple regression equation and the stochastic component of random errors. Monthly run-off in Naju station in Yong-San river basin is estimated by multiple regression model and hybrid model. And some comparisons between observed and estimated run-off and between multiple regression model and already-existing estimation methods such as Gajiyama formula, tank model and Thomas-Fiering model are done. The results are as follows. (1) The optimal function to estimate monthly run-off in historical sequence is multiple linear regression equation in overall-month unit, that is; Qn=0.788Pn+0.130Qn-1-0.273En-0.1 About 85% of total variance of monthly runoff can be explained by multiple linear regression equation and its coefficient of determination (R2) is 0.843. This means we can estimate monthly runoff in historical sequence highly significantly with short data of observation by above mentioned equation. (2) The optimal function to estimate monthly runoff in nonhistorical sequence is hybrid model combined with multiple linear regression equation in overall-month unit and stochastic component, that is; Qn=0. 788Pn+0. l30Qn-1-0. 273En-0. 10+Sy.t The rest 15% of unexplained variance of monthly runoff can be explained by addition of stochastic process and a bit more reliable results of statistical characteristics of monthly runoff in non-historical sequence are derived. This estimated monthly runoff in non-historical sequence shows up the extraordinary value (maximum, minimum value) which is not appeared in the observed runoff as a random component. (3) "Frequency best fit coefficient" (R2f) of multiple linear regression equation is 0.847 which is the same value as Gaijyama's one. This implies that multiple linear regression equation and Gajiyama formula are theoretically rather reasonable functions.

• Journal of Environmental Science International
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• v.19 no.10
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• pp.1211-1217
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• 2010

For an accurate rainfall-runoff simulation in the river basin, it is important to consider not only evaluation of runoff model but also accurate runoff component. In this study long-term runoffs were simulated by means of watershed runoff model and the amounts of runoff components such as upstream inflow, surface runoff, return flow and dam release were evaluated based on the concept of water budget. SSARR model was applied to Daecheong basin, the upstream region of Geum river basin, and in turn the monthly runoff discharges of main control points in the basin were analyzed. In addition, for the purpose of providing the basic quantified water resources data the conceptual runoff amounts were estimated with water budget analysis and the reliability of the observations and the monthly runoff characteristics were investigated in depth. The yearly runoff ratios were also estimated and compared with the observations. From the results of the main control points, Yongdam, Hotan, Okcheon and Daecheong, the yearly runoff ratios of those points are consistent well with data reported previously.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.9 no.4
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• pp.52-59
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• 2006

This study was conducted to find end-members and tracers which are effective to be applied in the End Member Mixing Analysis (EMMA) model for runoff separation at the Gwangneung coniferous forest catchment (13.6ha), Gyeonggido, Korea. We monitored three successive rainfall events during two weeks from June 26, 2005 to July 10, 2005, and analysed chemical properties of rainfall, throughfall, stemflow, groundwater and soil water considered as main components of storm runoff. The followings are the results of analyses of each component and tracer. Groundwater, soil water and rainfall (or throughfall) were dominant runoff components. Rainfall and groundwater were selected as main components for the two components-one tracer mixing model, and groundwater, soilwater and throughfall were selected as main components for the three components-two tracers mixing model. Tracers were selected from anion ($Cl^-$ and ${SO_4}^{2-}$), cation ($Na^+$, $K^+$, $Mg^{2+}$, and $Ca^{2+}$) and Acid Neutralizing Capacity (ANC) in event 1, 2, and 3. $Na^+$, $Ca^{2+}$ and ANC were selected in the two components-one tracer mixing model and ${SO_4}^{2-}-K^+$, ${SO_4}^{2-}-Na^+$, ${SO_4}^{2-}-Ca^{2+}$, ${SO_4}^{2-}$-ANC, and $Ca^{2+}$-ANC were selected in the three components-two tracers mixing model. Selected main runoff components and tracers can provide basic information to determine the contribution rate of each runoff component and identify the runoff process in a forest watershed.

• Journal of Korea Water Resources Association
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• v.37 no.7
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• pp.599-612
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• 2004

The continuous long-term rainfall-runoff simulation model SWAT has the advantage of being able to account for various land use, however, SWAT lacks the capability of simulating the drainage characteristics of urban area. On the other hand, SWMM, which is the most popular model for runoff analysis of urban watershed, has the advantage of being capable of considering surface and drainage characteristics in urban area, but SWMM cannot easily account for land use other than urban area within a watershed. In this study, SWAT-SWMM model, which builds on the strengths of SWAT and SWMM, has been applied to the Osan River Watershed which is a tributary watershed to the Gyung-Ahn River. From the application, the results from coupled SWAT-SWMM model has been compared to the ones from SWAT for each hydrologic component such as evapotranspiration, surface runoff, groundwater flow, and watershed and channel discharge, and the runoff characteristics of two models for each hydrologic component has been discussed.

• Journal of the Korean Professional Engineers Association
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• v.18 no.2
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• pp.1-5
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• 1985

In the flood prediction research, it is pointed out that the difficulty of flood prediction is the frequently experienced overestimation of flood peak. That is caused by the rainfall prediction difficulty and the nonlinearity of hydrological phenomena. Even though the former reason will remain still unsolved, but the latter one can be possibly resolved the method of the AMRA (Auto Regressive Moving Average) model for each runoff component as developed by Dr. Hino and Dr. Hasebe. The principle of the method consists of separating though the numerical filters the total runoff time series into long-term, intermediate and short-term components, or ground water flow, interflow, and surface flow components. As a total system, a hydrological system is a non-linear one. However, once it is separated into two or three subsystems, each subsystem may be treated as a linear system. Also the rainfall components into each subsystem a estimated inversely from the runoff component which is separated from the observed flood. That is why flood prediction can be done without rainfall data. In the prediction of surface flow, the Kalman filter will be applicable but this paper shows only impulse function method.

• Magazine of the Korean Society of Agricultural Engineers
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• v.34 no.1
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• pp.100-106
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• 1992

The objective of this study is to develop a real-time runoff forecasting model considering stochastic component. The model is composed of deterministic and stochastic components. Simplified tank model was selected as a deterministic runoff forecasting model. The time series of estimation residual resulting from the tank model simulation was analyzed and was best suited to the second-order autoregressive model. ARTANK model which combined the tank model with the autoregressive process was developed. And it was applied to a BANWEOL basin for validation. The simulation results showed a good agreement with the observed field data.

• Magazine of the Korean Society of Agricultural Engineers
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• v.44 no.5
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• pp.54-66
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• 2002

A grid-based hydrological model, CELTHYM, capable of estimating base flow and surface runoff using only readily available data, was used to assess hydrologic impacts caused by land use change on Little Eagle Creek (LEC) in Central Indiana. Using time periods when land use data are available, the model was calibrated with two years of observed stream flow data, 1983-1984, and verified by comparison of model predictions with observed stream flow data for 1972-1974 and 1990-1992. Stream flow data were separated into direct runoff and base flow using HYSEP (USGS) to estimate the impacts of urbanization on each hydrologic component. Analysis of the ratio between direct runoff and total runoff from simulation results, and the change in these ratios with land use change, shows that the ratio of direct runoff increases proportionally with increasing urban area. The ratio of direct runoff also varies with annual rainfall, with dry year ratios larger than those for wet years shows that urbanization might be more harmful during dry years than abundant rainfall years in terms of water yield and water quality management.