• Journal of Environmental Science International
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• v.17 no.4
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• pp.451-459
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• 2008

This study was carried out forecasting of pollution inflow of the Small Mountainous Catchment, namely; Seolma-cheon experimental catchment. Pollutographs of DO, BOD, T-N, Conductivity, T-p, pH. COD, SS from this catchment were obtained from in-situ data of total ten events using QUAL2E-PULS model. From the analysis results, between up stream(Sabang-bridge) and down stream (Memorial-bridge, outlet) obtained relation formula of water quality component. Determination coefficient of relation formula, Conductivity, COD, BOD, DO, pH, T-N, T-P, and SS showed high relation of $0.87{\sim}0.99$. The increases of DO, BOD, COD, and pH concentration of Memorial-bridge were associated with pollution inflow by road building far 2.25km from Sabang-bridge to down stream. The analysis results of QUAL2E-PULS simulation and up/down stream relation formula, pollution amounts of DO, BOD, COD and pH increased at Memorial-bridge and pollution source site. Therefore, pollution inflow can be forecasted exactly by up/down stream relation formula at pollution source site.

• Magazine of the Korean Society of Agricultural Engineers
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• v.43 no.2
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• pp.85-93
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• 2001

The basic concept of the model is to minimize the error range between forecasted flood inflow and actual flood inflow, and forecast accurately the flood discharge some hours in advance depending on the concentration time(Tc) and soil moisture retention storage(Sa). Simplex method that is a multi-level optimization technique was used to search for the determination of the best parameters of RETFLO (REal-Time FLOod forecasting) model. The flood forecasting model developed was applied to several strom event of Yedang reservoir during past 10 years. Model perfomance was very good with relative errors of 10% for comparison of total runoff volume and with one hour delayed peak time.

• Proceedings of the Korea Water Resources Association Conference
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• 2001.05a
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• pp.45-51
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• 2001

The daily inflow is apparently one of nonlinear and complicated phenomena. The nonlinear and complexity make it difficult to model the prediction of daily flow, but attractive to try the neural networks approach which contains inherently nonlinear schemes. The study focuses on developing the forecasting models of daily inflows to a large dam site using neural networks. In order to reduce the error caused by high or low outliers, the back propagation algorithm which is one of neural network structures is modified by combining a regression algorithm. The study indicates that continuous forecasting of a reservoir inflow in real time is possible through the use of modified neural network models. The positive effect of the modification using tole regression scheme in BP algorithm is showed in the low and high ends of inflows.

• Proceedings of the Korea Water Resources Association Conference
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• 1999.05a
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• pp.209-214
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• 1999

• Proceedings of the Korea Water Resources Association Conference
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• 1999.05a
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• pp.382-387
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• 1999

• Proceedings of the Korea Water Resources Association Conference
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• 2003.05b
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• pp.675-678
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• 2003

• Water for future
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• v.14 no.2
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• pp.22-25
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• 1981

• Proceedings of the Korea Water Resources Association Conference
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• 1992.07a
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• pp.411-418
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• 1992

The purpose of this study is to develop dynamic-stochastic models that can forecast the inflow into reservoir during low/drought periods and flood periods. For the formulation of the models, the discrete transfer function is utilized to construct the deterministic characteristics, and the ARIMA model is utilized to construct the stochastic characteristics of residuals. The stochastic variations and structures of time series on hydrological data are examined by employing the auto/cross covariance function and auto/cross correlation function. Also, general modeling processes and forecasting method are used the model building methods of Box and Jenkins. For the verifications and applications of the developed models, the Chungju multi-purpose reservoir which is located in the South Han river systems is selected. Input data required are the current and past reservoir inflow and Yungchun water levels. In order to transform the water level at Yungchon into streamflows, the water level-streamflows rating curves at low/drought periods and flood periods are estimated. The models are calibrated with the flood periods of 1988 and 1989 and hourly data for 1990 flood are analyzed. Also, for the low/drought periods, daily data of 1988 and 1989 are calibrated, and daily data for 1989 are analyzed.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2001.10a
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• pp.295-299
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• 2001

To protect the flooding damages in Medium and Small watershed, it needs to set up flood warning system and develope Flood forecasting Model in real-time basis for medium and small watershed. In this study, it was able to minimize the error range between forecasted flood inflow and actual flood inflow, and forecast accurately the flood discharge some hours in advance by using simplex method recursively for the determination of the best parameters of RETFLO model. The result of RETFLO performance applied to several storm of Yugu river during 3 past years was very good with relative errors of 10% for comparison of total runoff volume and with one hour delayed peak time.

• Magazine of the Korean Society of Agricultural Engineers
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• v.37 no.1
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• pp.65-72
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• 1995

This paper describes the applications of the SCS TR-20 hydrologic model for simula- tion of hourly inflow rates from sixty-six ungaged tributaries and subareas between the Naju station and the estuarin dam at the Yongsan River Basin. The model was tested for the ungaged conditions with fifteen storm events at Naju station. Hourly simulated run- off data were compared with the observed, and the results showed less correlationships between the two data than those from TANK model. The coefficients of correlation ranged from 0.74 to 0.87. The curve numbers and time of concentration were defined from topographic dta for each of sixty-six tributaries for the estuarine dam and used for TR-20 applications. The results were within an acceptable range of errors in simulating the inflow fluctuations for the flood forecasting at the estuarine dam.