• Water Engineering Research
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• v.5 no.2
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• pp.55-68
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• 2004

The GLEAMS (Groundwater Loading Effects of Agricultural Management System, version 3.0) water quality model was used to predict hydrology and water quality and to evaluate the effects of soil types from a cattle-grazed pasture field of Bermuda-Rye grass rotation with poultry litter application as a fertilizer in North Alabama. The model was applied and evaluated by using four years (1999-2002) of field-measured data to compare the simulated results for the 2.71- ha Summerford watershed. $R^2$ values between observed and simulated runoff, sediment yields, TN, and TP were 0.91, 0.86, 0.95, and 0.69, respectively. EI (Efficiency Index) of these parameters were 0.86, 0.67, 0.70, and 0.48, respectively. The statistical parameters indicated that GLEAMS provided a reasonable estimation of the runoff, sediment yield, and nutrient losses at the studied watershed. The soil infiltration rates were compared with the rainfall events. Only high intensity rainfall events generated runoff from the watershed. The measured and predicted infiltration rates were higher during dry soil conditions than wet soil conditions. The ratio of runoff to precipitation was ranging from 2.2% to 8.8% with average of 4.3%. This shows that the project site had high infiltration and evapotranspiration which generated the low runoff. The ratio of runoff to precipitation according to soil types by the GLEAMS model appeared that Sa (Sequatchie fine sandy loam) soil type was higher and Wc (Waynesboro fine sandy loam, severely eroded rolling phase) soil type relatively lower than the weighted average of the soil types in the watershed. The model under-predicted runoff, sediment yields, TN, and TP in Wb (Waynesboro fine sandy loam, eroded undulating phase) and Wc soil types. General tendency of the predicted data was similar for all soil types. The model predicted the highest runoff in Sa soil type by 105% of the weighted average and the lowest runoff in Wc soil type by 87% of the weighted average

• Magazine of the Korean Society of Agricultural Engineers
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• v.42
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• pp.38-49
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• 2000

Two application rates (9 and 18 t/ha) of poultry litter and a recommended rate of commercial fertilizer were studied to determine their effects on nutrient (N and P) losses in surface and subsurface runoff and loadings in soil layers from conventionally-tilled com by the treatments. The model predicted higher sediment losses than observed data from all treatments. The overpredicted sediment losses resulted in overprediction of organic-N and sediment-P losses in surface runoff. Simulated soluble-P losses in surface runoff were close to observed data, while NO3-N losses in surface runoff were underpredicted from all treatments. Observed NO3-N concentrations in leachate at 1.0-m depth from commercial fertilizer treatment were fairly well predicted. But the concentratins were overpredicted from poultry litter treatments due to high simulation of organic-N mineralization simulated by the model.

• Journal of Korea Water Resources Association
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• v.41 no.6
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• pp.565-574
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• 2008

Fire-enhanced soil hydrophobicity often increases runoff and erosion in the mountain hillslope following severe wildfires. Estimation techniques for WEPP's parameters were studied in burnt mountain slopes. In burnt mountain slopes, the model over-predicted runoff in the small runoff and under-predicted runoff in the great runoff, and in the lower sediment runoff it had a tendency to over-predict soil loss. The effective hydraulic conductivity was most sensitive in the WEPP's runoff and its sediment runoff was mainly effected by the effective hydraulic conductivity, initial saturation, rill erodibility, and interrill erodibility. To improve the applicability of the WEPP, the adjustment coefficient of effective hydraulic conductivity was defined for runoff and the adjustment coefficient of rill erodibility and interrill erodibility was presented for sediment runoff. The adjustment coefficient of effective hydraulic conductivity in wildfire mountain slopes increased with maximum rainfall intensity of single storm and the vegetation height index. The adjustment coefficients of rill erodibility depended on soil components of size distribution curve and total rainfall depths in single storm. The adjustment coefficients of interrill erodibility decreased with increases of maximum rainfall intensity and vegetation height index. These results may be used in the application of WEPP model for wildfire mountain slopes.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 2001.10a
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• pp.93-98
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• 2001

This study was performed to analyse the rainfall and the rainfall-runoff characteristics of a rural watershed. The Sangwha basin($105.9km^{2}$) in the Geum river system was selected for this study. The arithmetic mean method, the Thiessen's weighing method, and the isohyetal method were used to analyse areal rainfall distribution and the Huff's quartile method was used to analyse temporal rainfall distribution. In addition, daily runoff analyses were peformed using the DAWAST and tank model. In the model calibration, the data from June through November, 1999 were used. In the model calibration, the observed runoff depth was 513.7mm and runoff rate was 45.2%, and the DAWAST model simulated runoff depth was 608.6mm and runoff rate was 53.5%, and the tank model runoff depth was 596.5mm and runoff rate was 52.5%, respectively. In the model test, the data from June through November, 2000 were used. In the model test, the observed runoff depth was 1032.3mm and runoff rate was 72.5%, and the DAWAST model simulated runoff depth was 871.6mm and runoff rate was 61.3%, and the tank model runoff depth was 825.4mm and runoff rate was 58%, respectively. The DAWAST and tank model's $R^{2}$ and RMSE were 0.85, 3.61mm, and 0.85, 2.77mm in 1999, and 0.83, 5.73mm, and 0.87, 5.39mm in 2000, respectively. Both models predicted low flow runoff better than flood runoff.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1880-1884
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• 2007

The Natural Resource Conservation Service Curve Number(NRCS-CN) method is one of the widely used methods for computation of runoff from a basin. However, NRCS-CN method has weak point in that the spatial land use distribution characteristics are ignored by using area weighted CN value. This study developed a program which can estimate runoff by considering spatial distribution of CN and flow accumulation at the outlet of the watershed by appling Moglen's method. Comparisons between the results from NRCS-CN method and this study showed good agreement with measured data of experimental watersheds. The developed program predicted lower runoff than the conventional NRCS-CN method. As a conclusion, this study proposes a new design direction which can simulate real runoff phenomena. And the developed program could be applied into runoff minimization design for a basin development.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.7
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• pp.83-93
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• 2003

This research compared the observed and model predicted results that include; runoff, sediment yield, and nutrient losses from a 2.71 ha cattle grazing pasture field in North Alabama. Application of water quality computer simulation models can inexpensively and quickly assess the impact of pasture management practices on water quality. AGNPS single storm based model was applied to the three pasture species; Bermudagrass, fescue, and Ryegrass. While comparing model predicted results with observed data, it showed that model can reasonably predict the runoff, sediment yield and nutrient losses from the watershed. Over-prediction and under-prediction by the model occurred during very high and low rainfall events, respectively. The study concluded that AGNPS model can be reasonably applied to assess the impacts of pasture management practices and chicken litter application on water quality.

• Journal of Environmental Impact Assessment
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• v.19 no.3
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• pp.247-257
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• 2010

Watershed runoff and turbid water dynamics were simulated in the Youngju Dam, being constructed. The runoff flow and suspended solids were simulated and then thermal stratification and turbid water current in the reservoir were predicted by HSPF and CE-QUAL-W2 model, respectively. Considering selective withdrawal, we hypothesized 3 withdrawal types from the dam, i.e. surface layer, middle layer and the lowest layer. The maximum concentration of SS was 400mg/L in reservoir and it was decreased by the withdrawal. The inflowed turbid water fell to 30 NTU after 12 days regardless of the withdrawal types, but the surface layer withdrawal was a better type at turbid water discharge than the others. In current environmental impact assessment(EIA), we concluded that runoff and reservoir water quality predicted by HSPF and CE-QUAL-W2 was desirable, and appropriate parameters were selected by continous monitoring after EIA.

• Magazine of the Korean Society of Agricultural Engineers
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• v.39 no.6
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• pp.54-66
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• 1997

The objectives of this study is to introduce and apply neural network theory to real hydrologic systems for stochastic nonlinear predicting of daily runoff discharge in the river catchment. Back propagation algorithm of neural network model is applied for the estimation of daily stochastic runoff discharge using historical daily rainfall and observed runoff discharge. For the fitness and efficiency analysis of models, the statistical analysis is carried out between observed discharge and predicted discharge in the chosen runoff periods. As the result of statistical analysis, method 3 which has much processing elements of input layer is more prominent model than other models(method 1, method 2) in this study.Therefore, on the basis of this study, further research activities are needed for the development of neural network algorithm for the flood prediction including real-time forecasting and for the optimal operation system of dams and so forth.

• Journal of Environmental Impact Assessment
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• v.18 no.2
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• pp.59-67
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• 2009

Water quality of the Lake Youngrang in the Sokcho City is eutrophic. Jangcheon is the largest inflow source to the lake. Major pollutant sources are stormwater runoff from resort areas and various land uses in the Jangcheon watershed. A storm sewer on the southern end of the lake is also an important pollution source. In this study, water quality modelling for Lake Youngrang was carried out considering the rainfall-runoff pollution loads from the watershed. The rainfall-runoff curves and the rainfall-runoff pollutant load curves were derived from the rainfall-runoff survey data during the recent 4 years. The rainfall-runoff pollution loads and flow from the Jangcheon watershed and the storm sewer were estimated using the two kinds of curves, and they were used as the flow and the boundary data of the WASP model. With the measured water quality data of the year 2005 and 2006, WASP model was calibrated. Non-point pollution control measures such as wet pond and infiltration trench were considered as the alternative for water quality management of the lake. The predicted water quality were compared with those under the present condition, and the improvement effect of the lake water quality were analyzed.

• Journal of Environmental Science International
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• v.24 no.12
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• pp.1649-1656
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• 2015

Jeju Island is the highest rain-prone area in Korea that possesses affluent water resources, but future climate changes are predicted to further increase vulnerabilities as resultant of increasing of extreme events and creating spatial-temporal imbalance in water resources. Therefore, this study aimed to provide basic information to establish a proper water resources management plan by evaluating the effects of climate change on water resources using climate change scenario. Direct runoff ratio for 15 years (2000~2014) was analyzed to be 11~32% (average of 23%), and average direct runoff ratio for the next 86 years (2015~2100) was found as 28%, showing an increase of about 22% compared to the present average direct runoff ratio (23%). To assess the effects of climate change on long-term runoff, monthly runoff variation of future Gangjeong watershed was analyzed by dividing three time periods as follows: Present (2000~2030), Future 1 (2031~2070) and Future 2 (2071~2100). The estimated results showed that average monthly runoff increases in the future and the highest runoff is shown by Future 2. Extreme values has been expected to occur more frequently in the future as compared to the present.