• 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.

• Magazine of the Korean Society of Agricultural Engineers
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• v.44 no.5
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• pp.54-66
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• 2002

A grid-based hydrological model, CELTHYM, capable of estimating base flow and surface runoff using only readily available data, was used to assess hydrologic impacts caused by land use change on Little Eagle Creek (LEC) in Central Indiana. Using time periods when land use data are available, the model was calibrated with two years of observed stream flow data, 1983-1984, and verified by comparison of model predictions with observed stream flow data for 1972-1974 and 1990-1992. Stream flow data were separated into direct runoff and base flow using HYSEP (USGS) to estimate the impacts of urbanization on each hydrologic component. Analysis of the ratio between direct runoff and total runoff from simulation results, and the change in these ratios with land use change, shows that the ratio of direct runoff increases proportionally with increasing urban area. The ratio of direct runoff also varies with annual rainfall, with dry year ratios larger than those for wet years shows that urbanization might be more harmful during dry years than abundant rainfall years in terms of water yield and water quality management.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1592-1596
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• 2007

Accuracy of flood forecasting is an important non-structural measure on the flood control and mitigation. Hence, combination of horologic model with real time error correction became an important issue. It is one of the efficient ways to improve the forecasting precision. In this work, an approach based on Kalman Filter (KF) is proposed to continuously revise state estimates to promote the accuracy of flood forecasting results. The case study refers to the Wi River in Korea, with the flood forecasting results of Xinanjiang model. Compared to the results, the corrected results based on the Kalman filter are more accurate. It proved that this method can take good effect on hydrologic forecasting of Wi River, Korea, although there are also flood peak discharge and flood reach time biases. The average determined coefficient and the peak discharge are quite improved, with the determined coefficient exceeding 0.95 for every year.

• Journal of Korea Water Resources Association
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• v.54 no.7
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• pp.509-522
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• 2021

In many countries, including Korea, it has been challenging to understand flood-related social dynamics due to urbanization and climate change. In this regard, socio-hydrology has been proposed to consider the interaction between hydrologic systems, land-use change, and human activities. However, there is a general lack of understanding of the interactions of socio-hydrologicsystems. This study examines the interactions between human activities and hydrologic systems from a sociological perspective using a dynamic system model. In other words, this study aims to present a conceptualization model that considers the mutual interaction of flood and community from a socio-hydrologic perspective. Depending on the construction cost of the levee for the Yangjae River, this study considered three scenarios to simulate the interaction of socio-hydrologic systems. Socio-hydrologic interactions can effectively reproduce the changes in the Yangjae River. Moreover, It is expected that the proposed model can be further used to understand possible hydrologic changes and interaction with social systems in the future as a decision-making tool in water resources management.

• Journal of Korea Water Resources Association
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• v.41 no.9
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• pp.929-941
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• 2008

The objectives of this study are to propose a system for combined use of a hydrologic and a hydraulic model for urban flood forecast model and to evaluate the system on the $300km^2$ Jungrang urban watershed area, which is relatively large area as an urban watershed and consequently composed of very complex drainage pipes and streams with different land uses. In this study, SWMM for hydrologic model and HEC-RAS for hydraulic model are used and the study area is divided into 25 subbasins. The SWMM model is used for sewer drainage analysis within each subbasin, while HEC-RAS for unstready flow analysis in the channel streams. Also, this study develops a GUI system composed of mean areal precipitation input component, hydrologic runoff analysis component, stream channel routing component, and graphical representation of model output. The proposed system was calibrated for the model parameters and verified for the model applicability by using the observation data. The correlation coefficients between simulated and observed flows at the 2 important locations were ranged on 0.83-0.98, while the coefficients of model efficiency on 0.60-0.92 for the verification periods. This study also provided the possibilities of manhole overflows and channel bank inundation through the calculated water profile of longitudinal and channel sections, respectively. It can be concluded that the proposed system can be used as a surface runoff and channel routing models for urban flood forecast over the large watershed area.

• Journal of Wetlands Research
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• v.21 no.spc
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• pp.61-68
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• 2019

Recently, climate indices represented by quantifying atmospheric-ocean circulation patterns have been widely used to predict hydrologic variables for considering long-term climate variability. Hydrologic forecasting models based on artificial neural networks have been developed to provide accurate and stable forecasting performance. Forecasts of hydrologic variables considering climate variability can be effectively used for long-term management of water resources and environmental preservation. Therefore, identifying significant indicators for hydrologic variables and applying forecasting models still remains as a challenge. In this study, we selected representative climate indices that have significant relationships with dam inflow time series in the Han-River basin, South Korea for applying the dam inflow forecasting model. For this purpose, the ensemble empirical mode decomposition(EEMD) method was used to identify a significance between dam inflow and climate indices and an artificial neural network(ANN) ensemble model was applied to overcome the limitation of a single ANN model. As a result, the forecasting performances showed that the mean correlation coefficient of the five dams in the training period is 0.88, and the test period is 0.68. It can be expected to come out various applications using the relationship between hydrologic variables and climate variability in South Korea.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2002.10a
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• pp.281-284
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• 2002

Geographic Information System (GIS) has advantage of analyzing spatial distributed data and handling spatial data for hydrologic analysis. Hydrologic Engineering Center's Hydrologic Modeling System(HEC-HMS) with HEC-GeoHMS was used to analyze flood runoff at agricultural small watershed. HEC-GeoHMS, which is an ArcView GIS extension designed to process geospatial data for HEC-HMS, is a useful tool for storing, managing, analyzing, and displaying spatially distributed data. Hydroligical component including peak discharge, time to peak, direct runoff, baseflow for Balhan study watershed, which is located in Whasung city, Kyunggi province, having an area of $29.79km^2$, were calculated using the HEC-HMS model with HEC-GeoHMS.

• 한국방재학회:학술대회논문집
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• 2008.02a
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• pp.683-686
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• 2008

Flood damage has been increased due to the abnormal climate and extreme rainfall. So, quantitative and qualitative hydrologic data should be improved in oder to enhance accuracy of hydrologic forecast. However, research regarding hydrologic data have not been thorough enough. Therefore, in this study, monte carlo simulation was applied to rainfall runoff model to improve the reliability of runoff analysis and risk analysis. Rainfall-Stage-Discharge curve was developed as a consequence of MCS and it is possible to get correct rating curve for high water level.

• 한국신재생에너지학회:학술대회논문집
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• 2010.06a
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• pp.193.1-193.1
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• 2010

Small hydropower resources for five major river systems have been studied. The model, which can predict flow duration characteristic of stream, was developed to analyze the variation of inflow caused from rainfall condition. And another model to predict hydrologic performance for small hydropower(SHP) plants is established. Monthly inflow data measured at Andong dam were analyzed. The predicted results from the developed models in this study showed that the data were in good agreement with measured results of long term inflow at Andong dam. It was found that the models developed in this study can be used to predict the available potential and technical potential of SHP sites effectively. Based on the models developed in this study, the hydrologic performance for small hydropower sites located in river systems have been analyzed. The results show that the hydrologic performance characteristics of SHP sites have some difference between the river systems. Especially, the specific design flowrate and specific output of SHP sites located on North Han river and Nakdong river systems have large difference compared with other river systems.

• Journal of The Korean Society of Agricultural Engineers
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• v.57 no.2
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• pp.15-26
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• 2015

The purpose of this paper is to develop a software tool, PGA-CC (Projection of hydrology via Grid-based Assessment for Climate Change) to evaluate the present hydrologic cycle and the future watershed hydrology by climate change. PGA-CC is composed of grid-based input data pre-processing module, hydrologic cycle calculation module, output analysis module, and output data post-processing module. The grid-based hydrological model was coded by Fortran and compiled using Compaq Fortran 6.6c, and the Graphic User Interface was developed by using Visual C#. Other most elements viz. Table and Graph, and GIS functions were implemented by MapWindow. The applicability of PGA-CC was tested by assessing the future hydrology of South Korea by HadCM3 SRES B1 and A2 climate change scenarios. For the whole country, the tool successfully assessed the future hydrological components including input data and evapotranspiration, soil moisture, surface runoff, lateral flow, base flow etc. From the spatial outputs, we could understand the hydrological changes both seasonally and regionally.