• Journal of Environmental Science International
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• v.18 no.3
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• pp.309-314
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• 2009

A accurate reservoir inflow is very important as providing information for decision making about the water balance and the flood control, as well as for dam safety. The methods to calculate the inflow were divided by the directed method to measure streamflow from upstream reservoirs and the indirected method to estimate using the correlation of reservoir water level and release. Currently, the inflow of multi-purpose dam is being calculated by the indirect method and the reservoir water level to calculate the storage capacity is being used by centimeters(cm) units. Corresponding to the storage volume of 1cm according to scale and water level of multi-purpose dam comes up to from several 10 thousand tons to several million tons. If it converts to inflow during 1 hour, and it comes to several hundred $m^3/sec$(CMS). Therefore, the inflow calculated on the hourly is largely deviated along the water level changes and is occurred minus value as the case. In this research, the water level gage has been developed so that it can measure a accurate water level for the improvement for the error and derivation of inflow, even though there might be various hydrology and meteorologic considerations to analyse the water balance of reservoir. Also, it is confirmed that the error and the standard derivation of data observed by the new gage is decreased by 89,6% and 1/3 & 87% and 2/3 compared to that observed by the existing gage of Daecheong and Juam multi-purpose dam.

• The Journal of Engineering Geology
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• v.27 no.4
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• pp.377-382
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• 2017

Field experiments were conducted to estimate streambed hydraulic conductivity at 15 sites in the Anseongcheon watershed, Korea. Seepage meters and piezometers were installed in the streambed at each site to measure the amount of stream water-groundwater exchange and the hydraulic gradient. The vertical hydraulic conductivity was then calculated using Darcy's formula. The measured stream water-groundwater exchange rates were $4.08{\times}10^{-6}$ to $1.49{\times}10^{-5}m/s$, and the vertical hydraulic gradients were 0.005 to 0.145. The data suggest the streambed hydraulic conductivity to be $7.80{\times}10^{-5}$ to $1.58{\times}10^{-3}m/s$. The results show significant differences in connectivity between stream and aquifer. Quantification of the hydraulic interconnection between stream and aquifer, and evaluation of the effects of groundwater development and utilization on the streamflow require hydrogeological investigations of the connection between stream and aquifer, including the hydraulic conductivity of the streambed. Various field testing and analysis methods for hydrogeological assessment also require further improvement.

• Journal of Korea Water Resources Association
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• v.42 no.10
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• pp.773-783
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• 2009

The effects of rainfall input uncertainty on predictions of stream flow are studied based extended GLUE (Generalized Likelihood Uncertainty Estimation) approach. The uncertainty in the rainfall data is implemented by systematic/non-systematic rainfall measurement analysis in Weida catchment, Germany. PDM (Probability Distribution Model) rainfall runoff model is selected for hydrological representation of the catchment. Using general correction procedure and DUE(Data Uncertainty Engine), feasible rainfall time series are generated. These series are applied to PDM in MC(Monte Carlo) and GLUE method; Posterior distributions of the model parameters are examined and behavioural model parameters are selected for simplified GLUE prediction of stream flow. All predictions are combined to develop ensemble prediction and 90 percentile of ensemble prediction, which are used to show the effects of uncertainty sources of input data and model parameters. The results show acceptable performances in all flow regime, except underestimation of the peak flows. These results are not definite proof of the effects of rainfall uncertainty on parameter estimation; however, extended GLUE approach in this study is a potential method which can include major uncertainty in the rainfall-runoff modelling.