Water resources planning and management are, more and more, becoming important issue for water use and flood control due to the population increase, urbanization, and climate change. In particular, the estimating and the forecasting inflow of dam is the most important hydrologic issue for flood control and reliable water supply. Therefore, this study forecasted monthly inflow of Soyang river dam using VARMA model and 3 machine learning models. The forecasting models were constructed using monthly inflow data in the period of 1974 to 2016 and then the inflows were forecasted at 12- and 24-month ahead lead times. As a result, the forecasted monthly inflows by the models mostly were less than the observed ones, but the peak time and the variation pattern were well forecasted. Especially, the VARMA model showed very good performance in the forecasting. Therefore, the result of this study indicates that the VARMA model can be used efficiently to forecast hydrologic data and also used to establish water supply and management plan.

In this study, when seawall or harbor gate is installed for coastal disaster prevention, a two-dimensional water analysis in the bay is carried out to consider the flood amount of river inflow and effect of harbor gate. The Yeongsan river and the port Mokpo area are selcected for the study region. Then, by analyzing the hydraulic characteristics of flood flow of the Yeongsan river, we analysed the compatibility of the results in the two-dimensional hydrodynamic model. A twodimensional water analysis were conducted for the four cases considering whether a arbor gate is installed or not, and whether the inland water boundary condition is considered or not, also with open sea boundary condition. The results of the two-dimensional water analysis shows that water level change near the port Mokpo area is mainly caused by the discharge of the estuary barrage of the Yeongsan river because the harbor gate was installed. In addition, it is revealed that the volume of reservoir created by the harbor gate and the estuary barrage is too much small compared to the volume of the discharge from the Yeongsan river. Therefore, when the harbor gate is installed in the open sea, we concluded that a flexible management between the harbor gate and the estuary barrage of the Yeongsan river is required. A initial water level of the bay and outflow from the harbor gate are proposed for disaster prevention in the coastal area of port Mokpo.

본 연구에서는 하상변동 및 하상유지공 유실 문제가 발생했던 남한강과 금당천 합류부 지점을 대상으로 지류에서 유입되는 유량의 변화에 따른 흐름특성 및 하상변동 특성을 2차원 수치모형을 이용하여 분석하였다. 대상 구간의 수치모의 분석결과, 본류에서는 흐름집중 현상에 의해 지류 유입유량에 관계없이 합류 전에 비해 합류 후 유속이 더 큰 것으로 나타났다. 그러나 지류 유입유량이 클수록 지류하천의 하도 침식이 가속화되고 따라서 주하도가 형성되어 지류에서의 마름영역이 더 크게 나타났다. 이로 인한 지류에서의 하도 침식은 지류에서의 유사발생량을 증가시키고 침식된 유사는 합류부 구간에 퇴적되는 것으로 나타났다. 합류부 구간에서의 지류 유입부 퇴적은 본류 흐름을 좌안으로 집중시키고 좌안의 하상이 저하되는 현상을 야기하였다.

The influence of the point source inflow on the water quality variation in the downstream of Hyeongsan River was investigated. As the results of seasonal variation, the pollutant concentrations of dry season were 1.5~4 times higher than those of wet season. The increase rate of BOD5, CODMn, T-N, T-P due to point source were ranged to 8.1~42.6%, 7.3~41.9% and 17.1~207% as the inflow of P1, P2 and P3, respectively. After P1, P2 and P3 inflow, the accumulated increase rate were 64.3%, 32.6%, 93.1% and 258.9% in BOD5, CODMn, T-N, T-P, respectively. It was found that the influence of point source inflow on the water quality in the downstream of Hyeongsan River is severe.

This study focuses on analyzing the inflow characteristic of contaminants of city water that flows into a main water system like a reservoir, and intends to provide basic data which can be efficiently reflected on water quality management policy and decision making of a reservoir. The conclusion obtained from the analysis of the inflow of a main water system by analyzing the inflow property of city water contaminants is as follows. In the case of Chungju-cheon stream which is the city water, pollution load from the basic outflow is low when it rains, and with high load of basic outflow during the dry season, due to the discharge of pollutants from the city, the quality of water becomes worse. In the case of Chungju-cheon stream, average BOD is 4.53mg/ℓ when it rains, and the contaminants increase and flow in about 7.8% compared to the average BOD during the average ‧ droughty season. The average SS concentration in water is 798.67mg/ℓ and increased 97.2% compared to the average ‧ droughty season.

본 연구에서는 홍수시 다목적댐의 효율적 운영을 위하여 상류로부터 유입되는 홍수유입량을 실시간으로 예측하기 위해 역전파 신경망 모형을 사용하여 댐유입량 예측모형(Neural Dam Inflow Forecasting Model; NDIFM)을 개발하였다. NDIFM은 다목적댐에 의한 하류의 홍수조절 비중이 큰 낙동강의 남강댐 유역에 적용하였으며, 입력자료로는 댐유역 평균강우량, 실측 댐유입량, 예측 댐유입량 통을 사용하여 실시간 댐유입량 예측의 가능성을 검