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안승섭,이증석,도준현 한국환경과학회 2003 한국환경과학회지 Vol.12 No.9
The subject basin of the research was the basin of Yeongcheon Dam located in the upper reaches of the Kumho River. The parameters of the model were derived from the results of abstracting topological properties out of rainfall-runoff observation data about heavy rains and Digital Elevation Modeling(DEM) materials. This research aimed at suggesting the applicability of the CELLMOD Model. a distribution-type model, in interpreting runoff based on the topological properties of a river basin, by carrying out runoff interpretation for heavy rains using the model. To examine the applicability of the model, the calculated peaking characteristics in the hydrograph was analyzed in comparison with observed values and interpretation results by the Clark Model. According to the result of analysis using the CELLMOD Model proposed in the present research for interpreting the rainfall-runoff process, the model reduced the physical uncertainty in the rainfall-runoff process, and consequently, generated improved results in forecasting river runoff. Therefore it was concluded that the algorithm is appropriate for interpreting rainfall-runoff in river basins. However, to enhance accuracy in interpreting rainfall-runoff. it is necessary to supplement heavy rain patterns in subject basins and to subdivide a basin into minor basins for analysis. In addition, it is necessary to apply the model to basins that have sufficient observation data, and to identify the correlation between model parameters and the basin characteristics(channel characteristics).
안승섭,박노삼,이수식,이관영,박상현 한국환경과학회 2000 한국환경과학회지 Vol.9 No.5
In this study, the removal possibility of nutrients of T-P, NH_3-N, NO_3-N, and T-N is examined through a positive experimental study using submerged biofilter of media packing channel method. From the analysis of nutrients removal efficiency for each run of the collected sample, following results are obtained. Firstly, the result of N/P surveying for inflow shows serious value that excess the limit value of 20 as the values are in the range of 12.0∼42.7 and the average is 25.73. Secondly, the highest concentration of the incoming NH_3-N reaches double of the standard since the concentrations of NH_3-N, and NO_3-N for inflow shows 0.06㎎/ℓ , and 2.5∼3.8㎎/ℓ respectively, and the average removal rate which passed the submerged biofilter adopted in this study is a satisfactory level. Next, the average removal rate of T-P of 51.5% shows the possibility of entrophication removal since the removal rate of T-P of 66.8∼68.8% in relative low temperature period of RUN 1∼2 appeared higher than in RUN 3∼6, and T-N shows relatively poor result with the average removal rate of 34.1%. And it is known that the bigger BOD/P and BOD/N are, the more removal rate increases from the examination result of the relation between BOD/P and BOD/N, and the treatment water T-P and T-N to decide the relation with the concentration of organic matters, and thought that the appropriate proportion is necessary for effective removal of nitrogen and phosphorus.
안승섭,신성일,정순돌 한국환경과학회 2004 한국환경과학회지 Vol.13 No.7
The Neural Network Models which mathematically interpret human thought processes were applied to resolve the uncertainty of model parameters and to increase the model's output for the streamflow forecast model. In order to test and verify the flood discharge forecast model eight flood events observed at Kumho station located on the midstream of Kumho river were chosen. Six events of them were used as test data and two events for verification. In order to make an analysis the Levengerg-Marquart method was used to estimate the best parameter for the Neural Network model. The structure of the model was composed of five types of models by varying the number of hidden layers and the number of nodes of hidden layers. Moreover, a logarithmic-sigmoid varying function was used in first and second hidden layers, and a linear function was used for the output. As a result of applying Neural Networks models for the five models, the N10-6model was considered suitable when there is one hidden layer, and the N10-9-5model when there are two hidden layers. In addition, when all the Neural Network models were reviewed, the N10-9-5model, which has two hidden layers, gave the most preferable results in an actual hydro-event.