• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2002.10a
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• pp.457-460
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• 2002

Development and application of nonpoint pollutant source model need pertinent runoff simulation for expecting good simulation result of yield of nonpont pollutant and it's move. this study purpose was compare to runoff height among Observed of Regression, HSPF and SWAT in hukchun basis loacated Gyeonggi province yangpeong-gun in two years($1998{\sim}1999$). Result, runoff height were Regression, SWAT, HSPF is 2578.96, 2526.44, 2547.21mm respectively, Nash-Schutcliff' simulation efficiency, compare to observed, was 70.22, 73.71% respectively so two simulation run off height was pertinent. If Regression method use excess observed arrange, it include error. so it's importance using pertinent arrange of observed runoff height.

• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.4
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• pp.1-10
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• 2010

In this study, two estimation equations for preparing stream data for distributed storm runoff model were developed by analyzing the nonlinear relation between upstream flow-length and stream width, and between upstream flow-length and stream bed-slope. The equations for stream cell were tested in Chungjudam watershed (6,661 $km^2$) using KIMSTORM. Six storm events occurring between 2003 and 2008 were selected for the model calibration and verification before the test of equations. The average values of the Nash-Sutcliffe model efficiency (ME), the volume conservation index (VCI), the relative error of peak runoff rate (EQp), and the difference of time to peak runoff (DTp) were 0.929, 1.035, 0.037, and -0.406 hr for the calibrated four storm events and 0.956, 0.939, 0.055, and 0.729 hr for the two verified storm events respectively. The estimation equations were tested to the storm events, and compared the flood hydrograph. The test result showed that the estimation equation of stream width reduced the peak runoff and delaying the time to peak runoff, and the estimation equation of stream bed-slope showed the opposite results.

• Journal of The Korean Society of Agricultural Engineers
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• v.54 no.4
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• pp.65-71
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• 2012

The objective of this study was to estimate surface runoff from rice paddy plots using an artificial neural network (ANN). A field experiment with three treatment levels was conducted in the NICS saemangum experimental field located in Iksan, Korea. The ANN model with the optimal network architectures, named Paddy1901 with 19 input nodes, 1 hidden layer with 16 neurons nodes, and 1 output node, was adopted to predict surface runoff from the plots. The model consisted of 7 parameters of precipitation, irrigation rate, ponding depth, average temperature, relative humidity, wind speed, and solar radiation on the daily basis. Daily runoff, as the target simulation value, was computed using a water balance equation. The field data collected in 2011 were used for training and validation of the model. The model was trained based on the error back propagation algorithm with sigmoid activation function. Simulation results for the independent training and testing data series showed that the model can perform well in simulating surface runoff from the study plots. The developed model has a main advantage that there is no requirement for any prior assumptions regarding the processes involved. ANN model thus can be a good tool to predict surface runoff from rice paddy fields.

• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.1
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• pp.13-18
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• 2010

In this study the validities of runoff prediction methods are reviewed around ESP (Ensemble Streamflow Prediction) techniques. The improvements of runoff predictions on Yongdam river basin are evaluated by the comparison of different prediction methods including ESP incorporated with qualitative meteorological outlooks provided by meteorological agency as well as the runoff forecasting based on the analysis of the historical rainfall scenarios. As a result it is assessed that runoff predictions with ESP may give rise to more accurate results than the ordinary historical average runoffs. In deed the latter gave the mean of yearly absolute error as to be 60.86 MCM while the errors of the former ones amounted to 44.12 MCM (ESP) and 42.83 MCM (ESP incorporated with qualitative meteorological outlooks) respectively. In addition it is confirmed that ESP incorporated with qualitative meteorological outlooks could improve the accuracy of the results more and more. Especially the degree of improvement of ESP with meteorological outlooks shows rising by 10.8% in flood season and 8% in drought season. Therefore the methods of runoff predictions with ESP can be further used as the basic forecasting information tool for the purpose of the effective watershed management.

• Journal of Environmental Science International
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• v.24 no.4
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• pp.437-447
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• 2015

Estimation of runoff peak is needed to assess water availability, in order to support the multifaceted water uses and functions, hence to underscore the modalities for efficient water utilization. The magnitude of storm rainfall acts as a primary input for basin level runoff computation. The rainfall-runoff linkage plays a pivotal role in water resource system management and feasibility level planning for resource distribution. Considering this importance, a case study has been carried out in the Hancheon basin of Jeju Island where distinctive hydrological characteristics are investigated for continuous storm rainfall and high permeable geological features. The study aims to estimate unit hydrograph parameters, peak runoff and peak time of storm rainfalls based on Clark unit hydrograph method. For analyzing observed runoff, five storm rainfall events were selected randomly from recent years' rainfall and HEC-hydrologic modeling system (HMS) model was used for rainfall-runoff data processing. The simulation results showed that the peak runoff varies from 164 to 548 m3/sec and peak time (onset) varies from 8 to 27 hours. A comprehensive relationship between Clark unit hydrograph parameters (time of concentration and storage coefficient) has also been derived in this study. The optimized values of the two parameters were verified by the analysis of variance (ANOVA) and runoff comparison performance were analyzed by root mean square error (RMSE) and Nash-Sutcliffe efficiency (NSE) estimation. After statistical analysis of the Clark parameters significance level was found in 5% and runoff performances were found as 3.97 RMSE and 0.99 NSE, respectively. The calibration and validation results indicated strong coherence of unit hydrograph model responses to the actual situation of historical storm runoff events.

• Journal of the Korean Association of Geographic Information Studies
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• v.7 no.1
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• pp.28-38
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• 2004

The purpose of this study is to analyze the urban hydrologic state by the use of GIS, resolution and interpolation. The determination coefficient($R^2$) and Regression Formula were derived from the contour of digital map for the accuracy, and DEM data was made by using TIN interpolation by the size of the grid. By using the observed DEM data, topographical factors were extracted from the small basin, size, the width of a basin and the slope, and were applied in the urban runoff model. Through the model, we tried to find out the most suitable runoff model in a small basin of Yosu-Munsu area. As a result of applying models to the drainage considered, the runoff hydrograph estimated by SWMM model was closer to the observed one than that estimated by ILLUDAS model. The difference between the runoff hydrograph by SWMM and the observed one is maximum error of 19%, minimum error of 5% and average error of 13%. The influence of duration in contrast to pick time is insignificant in a urban small basin. As a conclusion of this study, SWMM model was more suitable and applicable for the urban runoff model than ILLUDAS model due to its accuracy and various abilities.

• Journal of The Korean Society of Agricultural Engineers
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• v.46 no.5
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• pp.107-116
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• 2004

A GIS-based paddy inundation simulation system which is capable of simulating temporal and spatial inundation processes was established and applied in this paper. The system is composed of HEC-GeoHMS, and HEC-GeoRAS modules which interface the GIS and flood runoff models, and HEC-HMS, and HEC-RAS models which estimate the flood runoff. It was used to simulate storm runoff and inundation for a small rural watershed, the Baran HP#7, which is 10.69 $km^2$ in size. The simulated peak runoff, time to peak, and total direct runoff for eight storms were compared with the observed data. The results showed that the coefficient of determination ($R^2$) for the observed peak runoff was 0.99 and an error, RMSE, 11.862 $m^3$/s for calibration stages. In the model verification, $R^2$ was 0.99 and RMSE 1.296 $m^3$/s. Paddy inundation for each paddy growing stages in study watershed were estimated using verified inundation simulation system when probability rainfall was applied.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.6
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• pp.119-127
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• 2003

This paper documents recent efforts to validate the GIS-based hydrologic models, HEC-HMS and HEC-GeoHMS by the US Army Corps of Engineers. HMS and Geo-HMS were used to simulate storm runoff from a small rural watershed, the Balan HS#6. The watershed is 3.85 $\textrm{km}^2$ in size. The watershed topographic, soils, and land use data were processed using the GIS tool fur the models. Input parameters were retrieved and calibrated with the field data. The simulated peak runoff, time to peak, and total direct runoff fer twenty three storms were compared with the observed data. The results showed that the coefficient of determination($R^2$) for the observed peak runoff was 0.95 and an error, RMSE, 3.08 $\textrm{m}^3$/s for calibration stages. In the model verifications, $R^2$ was 0.89 and RMSE 6.79 $\textrm{m}^3$/s, which were slightly less accurate than the calibrated data. The simulated flood hydrographs were well compared to the observed. It was concluded that HMS and GeoHMS are applicable to flood analyses for rural watersheds.

• Journal of The Korean Society of Agricultural Engineers
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• v.46 no.1
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• pp.87-97
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• 2004

The paper presents the results from the applications of the Water Erosion Prediction Project (WEPP) model to a single plot, and also a small watershed in the Mid Korean Peninsula which is comprised of hillslopes and channels along the water courses. Field monitoring was carried out to obtain total runoff, peak runoff and sediment yield data from research sites. For the plot of 0.63 ha in size, cultivated with com, the relative error of the simulated total runoff, peak runoff rates, and sediment yields using WEPP ranged from -16.6 to 22％, from -15.6 to 6.0％, and from 23.9 to 356.4％ compared to the observed data, respectively. The relative errors for the upland watershed of 5.1 ha ranged from -0.7 to 11.1 ％ for the total runoff, from -6.6 to 35.0 ％ for the sediment yields. The simulation results seem to justify that WEPP is applicable to the Korean dry croplands if the parameters are correctly defined. The results from WEPP applications showed that the major source areas contributing sediment yield most are downstream parts of the watershed where runoff concentrated. It was suggested that cultural practice be managed in such a way that the soil surface could be fully covered by crop during rainy season to minimize sediment yield. And also, best management practices were recommended based on WEPP simulations.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2001.10a
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• pp.45-50
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• 2001

The purpose of this study was to estimate of soil loss form hillslope using WEPP(Water Erosion Prediction Project) model. WEPP model was developed for predicting soil erosion and deposition, fundamentally based on soil erosion prediction technology. The model for predicting sediment yields from single storms was applied to a tested watershed. Surface runoff is calculated by kinematic wave equation and infiltration is based on the Green and Ampt equation. Governing equations for sediment continuity, detachment, deposition, shear stress in rills, and transport capacity are presented. Tested watershed has an area of 0.6ha, where the runoff and sediment data were collected. The relative error between predicted and measured runoff was $-16.6{\sim}2.2%$, peak runoff was $-15.6{\sim}2.2%$ and soil loss was $-23.9{\sim}356.5%$.