• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.151-151
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• 2018

The present study is aimed to quantifying the uncertainty in the general circulation model (GCM) selection and its impacts on hydrology studies in the basins. For this reason, 13 GCMs was selected among the 26 GCM models of the Fifth Assessment Report (AR5) scenarios. Then, the climate data and hydrologic data with two Representative Concentration Pathways (RCPs) of the best model (INMCM4) and worst model (HadGEM2-AO) were compared to understand the uncertainty associated with GCM models. In order to project the runoff, the Precipitation-Runoff Modelling System (PRMS) was driven to simulate daily river discharge by using daily precipitation, maximum and minimum temperature as inputs of this model. For simulating the discharge, the model has been calibrated and validated for daily data. Root mean square error (RMSE) and Nash-Sutcliffe Efficiency (NSE) were applied as evaluation criteria. Then parameters of the model were applied for the periods 2011-2040, and 2070-2099 to project the future discharge the five large basins of South Korea. Then, uncertainty caused by projected temperature, precipitation and runoff changes were compared in seasonal and annual time scale for two future periods and RCPs compared to the reference period (1976-2005). The findings of this study indicated that more caution will be needed for selecting the GCMs and using the results of the climate change analysis.

• Journal of Environmental Impact Assessment
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• v.32 no.1
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• pp.29-40
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• 2023

The need for improvement is raised due to limitations with environmental impact assessment, and the importance for data-based environmental impact assessment is increasing. In this study, data demand was derived by analyzing Agreed Terms and Conditions in the Water Environment field (Water Quality, Hydraulic & Hydrologic Conditions, and Marine Environment) of environmental impact assessment. Agreed Terms and Conditions on environmental impact assessment in the water environment field were classified and categorized by environmental impact assessment stage (addition to status survey, impact prediction and evaluation, establishment of reduction measures, post-environmental impact survey), and data demand for each type of consultation opinion was linked. As a result of the categorization of Agreed Terms and Conditions, it was classified into 18 types in the water quality, 15 types in the hydraulic & hydrologic conditions, and 17 types in the marine environment. As a result of linking data demand, the total number of data demand was 236 in the water quality, 98 in the hydraulic & hydrologic conditions, and 73 in the marine environment. The highest number of Agreed Terms and Conditions and data demands were found in the water quality for the evaluation item and establishment of reduction measures, specifically establishment of non-point source pollution reduction measures, for the stage. The numbers were judged to be linked to the relative importance of the items and the primary purpose of environmental impact assessment. The derivation of data demand through the analysis of Agreed Terms and Conditions in the environmental impact assessment can contribute to the advancement of the preparation of environmental impact assessment reports and is expected to increase data utilization by various decision-makers by establishing a systematic database.

• Journal of Korea Water Resources Association
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• v.36 no.6
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• pp.911-924
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• 2003

Many researches have been conducting on extracting geometry data and hydrologic parameters by using GIS technique. However, there is no clear standard on those methods yet. This study examines the changing pattern of runoff responses characteristics with applying lumped model on divided watershed. WMS is used in order to divide watershed and calculate hydrologic geometry data and parameters by GIS technique. HEC-1 is adopted as a hydrologic model to establish runoff responses. The basin is divided into small watersheds, which are approximately same size. This research conducted runoff response simulation of Pyoungchang River and Wichon River Basin. Especially, research was focused on what is the most appropriate level as a divined sub-basin, and tested the effect of size of sub-basin for the runoff response simulation. The results showed the size of sub-basin was not an important factor for the simulation results after a certain size. The results of this study can be applied as an appropriate guidance to select optimal simulation size of watershed for the lumped model in a specific watershed.

• Journal of The Korean Society of Agricultural Engineers
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• v.59 no.3
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• pp.63-70
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• 2017

The purpose of this study was to calibrate the hydrologic parameters of SWAT model and analyze the daily runoff for the study watershed using SWAT-CUP. The Hardware watershed is located in Virginia, USA. The watershed area is $356.15km^2$, and the land use accounts for 73.4 % of forest and 23.2 % of pasture. Input data for the SWAT model were obtained from the digital elevation map, landuse map, soil map and others. Water flow data from 1990 to 1994 was used for calibration and from 1997 to 2005 was for validation. The SUFI-2 module of the SWAT-CUP program was used to calibrate the hydrologic parameters. The parameters were calibrated for the highly sensitive parameters presented in previous studies. The P-factor, R-factor, $R^2$, Nash-Sutcliffe efficiency (NS), and average flow were used for the goodness-of-fit measures. The applicability of the model was evaluated by sequentially increasing the number of applied parameters from 4 to 11. In this study, 10-parameter set was accepted for calibration in consideration of goodness-of-fit measures. For the calibration period, P-factor was 0.85, R-factor was 1.76, $R^2$ was 0.51 and NS was 0.49. The model was validated using the adjusted ranges of selected parameters. For the validation period, P-factor was 0.78, R-factor was 1.60, $R^2$ was 0.60 and NS was 0.57.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.54-55
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• 2015

Increase of impervious areas due to expansion of housing area, commercial and business building of urban is resulting in property change of stormwater runoff. Also, rapid urbanization and heavy rain due to climate change lead to urban flood and debris flow damage. In 2010 and 2011, Seoul had experienced shocking flooding damages by heavy rain. All these have led to increased interest in applying LID and decentralized rainwater management as a means of urban hydrologic cycle restoration and Natural Disaster Prevention such as flooding and so on. Urban development is a cause of expansion of impervious area. It reduces infiltration of rain water and may increase runoff volume from storms. Low Impact Development (LID) methods is to mimic the predevelopment site hydrology by using site design techniques that store, infiltrate, evaporate, detain runoff, and reduction flooding. Use of these techniques helps to reduce off-site runoff and ensure adequate groundwater recharge. The contents of this paper include a hydrologic analysis on a site and an evaluation of flooding reduction effect of LID practice facilities planned on the site. The region of this Case study is LID Rainwater Management Demonstration District in A-new town and P-new town, Korea. LID Practice facilities were designed on the area of rainwater management demonstration district in new town. We performed analysis of reduction effect about flood discharge. SWMM5 has been developed as a model to analyze the hydrologic impacts of LID facilities. For this study, we used weather data for around 38 years from January 1973 to August 2014 collected from the new town City Observatory near the district. Using the weather data, we performed continuous simulation of urban runoff in order to analyze impacts on the Stream from the development of the district and the installation of LID facilities. This is a new approach to stormwater management system which is different from existing end-of-pipe type management system. We suggest that LID should be discussed as a efficient method of urban disasters and climate change control in future land use, sewer and stormwater management planning.

• Water Engineering Research
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• v.5 no.4
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• pp.157-176
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• 2004

This research presents a prototype development and implementation of Decision Support System (DSS) for integrated river basin water management for the flood control. The DSS consists of Relational Database Management System, Hydrologic Data Monitoring System, Spatial Analysis Module, Spatial and Temporal Analysis for Rainfall Event Tool, Flood Forecasting Module, Real-Time Operation of Multi Reservoir System, and Dialog Module with Graphical User Interface and Graphic Display Systems. The developed DSS provides an automated process of alternative evaluation and selection within a flexible, fully integrated, interactive, centered relational database management system in a user-friendly computer environment. The river basin decision-maker for the flood control should expect that she or he could manage the flood events more effectively by fully grasping the hydrologic situation throughout the basin.

• Journal of the Korean Solar Energy Society
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• v.27 no.3
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• pp.135-142
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• 2007

The model to predict flow duration characteristics and performance for small scale hydro power(SSHP) plants is studied to analyze the effects of rainfall condition. One existing SSHP plant was selected and performance characteristics was analyzed by using the developed model. The predicted results from the model developed show that the data were in good agreement with operational results of existing SSHP plant. The results show that both the scale parameter and the shape parameter have large effects on the performance of SSHP sites. And also it was found that the model developed in this study can be a useful tool to predict the performance of SSHP sites.

• Korean Journal of Hydrosciences
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• v.4
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• pp.1-9
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• 1993

It is a major objective for the management and operation of water resources system to forecast streamflows. The applicability of artificial neural network model to hydrologic system is analyzed and the performance is compared by statistical method with observed. Multi-layered perception was used to model rainfall-runoff process at Pyung Chang River Basin in Korea. The neural network model has the function of learning the process which can be trained with the error backpropagation (EBP) algorithm in two phases; (1) learning phase permits to find the best parameters(weight matrix) between input and output. (2) adaptive phase use the EBP algorithm in order to learn from the provided data. The generalization results have been obtained on forecasting the daily and hourly streamflows by assuming them with the structure of ARMA model. The results show validities in applying to hydrologic forecasting system.

• Journal of Korea Water Resources Association
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• v.30 no.6
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• pp.641-648
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• 1997

Mutual information is useful for analyzing nonlinear dependence in time series in much the same way as correlation is used to characterize linear dependence. We use multivariate kernel density estimators for the estimation of mutual information at different time lags for single and multiple time series. This approach is tested on a variety of hydrologic data sets, and suggested an appropriate delay time $ au$ at which the mutual information is almost zerothen multi-dimensional phase portraits could be constructed from measurements of a single scalar time series.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1998.10a
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• pp.349-352
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• 1998

In many circumstances, it is infeasible to simulate the daily water yield in every land use or soil type of the watershed or river basin. These situations can be simulated in“Soil and Water Assessment Tool”(SWAT) using a concept called“hydrologic response units”(HRU's) within a topographically-defined subbasin. Soil water balance, crop growth, nutrient cycling management, etc., are simulated for each HRU For the watershed of Bok-ha river, the effect of HRU's in SWAT has been studied in respect to water yield. The optimum number of HRU's was 23 based in data capacity and correlation coefficient.