2005, Vol.14, No.2

Journal of Environmental Impact Assessment 2023 KCI Impact Factor : 0.51

pISSN : 1225-7184
https://journal.kci.go.kr/kseia

노은 매립지는 사용종료된지 5년이 경과된 비위생매립지로 최종복토는 되어 있으나 침출수차집시설 및 매립가스 포집설비가 제대로 갖추어지지 않은 상태이다. 환경부의 사용종료 매립지 정비지침에 의하면 침출수의 BOD/CODcr 비율이 1/10 수준임으로 침출수의 안정화 과정이거의 완결상태로 진행되고 있는 것으로 판단된다. 매립지 가스의 안정화 측면에서는 CH4의 비율이 5%정도이기 때문에 안정화가 거의 이루어진 것으로 볼 수 있다. 매립된 쓰레기 중에서 플라스틱을 제외한 가연물 함량이 3.97 - 9.34%이기 때문에 매립폐기물은 안정화 기준에 미흡한상태이다. 그리고 지하수는 대장균 항목이 지하수 수질기준 생활용수 기준에 미흡하여 안정화기준을 충족시키지 못하고 있다. 노은매립지는 매립지 안정화의 속도가 평가 대상별로 상이하게 진행되는 것으로 평가된다.

This study applied the Neural Network and Fuzzy theory to show water-purity control andpreventive measure in water quality forecasting of the future river. This study picked out NAJUand HAMPYUNG as the subject of investigation and used monthly the water quality and theoutflow data of KWANGJU2, NAJU, YOUNGSANNPO and HAMPYUNG from 1995 to 1999to forecast BOD, COD, T-N, T-P water density. The datum from 1995 to 1999 are used for studyand that of 2000 are used for verification. To develop model of water quality forecasting, firstly,this research formed Neural Network model and divided Neural Network model into two case- the case of considering lag and not considering. And this study selected optimal NeuralNetwork model through changing the number of hidden layer based on input layer(n) from nto 3n. Through forecasting result, the case without considering lag showed more precisesimulated result. Accordingly, this study intended to compare, analyse that Fuzzy model usingthe method without considering lag with Neural Network model. As a result, this study found that the model without considering lag in Neural Network Network shows the most excellent outcome. Thus this study examined a forecasting accuracy, analyzed result and verified propriety through appling the method of water quality forecasting using Neural Network and Fuzzy Algorithms to the actual case.

This study was performed to characterize stormwater runoff of pollution material fromnonpoint sources during rainfall in drainage basins of Hongjechun watershed, and to suggestmanagement methods to control the first flush of nonpoint sources. We conducted 4 times offield surveys including 3 times of wet period and 1 times of dry period for 5 stations, whichconsist of 3 stations in main stream of Hongjechun and 1 station in tributaries of Sinyoungchunand Gukichun, respectively. The variation of pollutant concentrations in terms of BOD, COD, SSand TP was large depending on the flow rate of stormwater, while a little change of TNconcentration was investigated. Depending on the rainfall event, the difference of flowrates, andrunoff loadings was large, while the difference of those for dry wether period was not noticeablefor various sub-basins. In the results of unit load calculation, the range of 153-277 kg/ha/yr forBOD, 222-422 kg/ha/yr for COD, 264-432 kg/ha/yr for SS, 40-70kg/ha/yr for TN, and 13-25kg/ha/yr for TP was obtained for Hongjechun, Sinyoungchun, and Gukichun sub-basins.Compared with the previous studies, the result of this study was founded to be acceptable.