• Magazine of the Korean Society of Agricultural Engineers
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• v.39 no.1
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• pp.41-47
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• 1997

A geographical resource analysis support system (GRASS) was incorporated to an input and output processor for the agricultural nonpoint source pollution (AGNPS) model. The resulting interface system, GIS-AGNPS was a user-friendly, menu-driven system. GIS-AGNPS was developed to automatically process the input and output data from GIS-based data using GRASS and Motif routines. GIS-AGNPS was consisted of GISAGIN which was an input processor for the AGNPS model, GISAGOUT a output processor for the AGNPS and management submodel. The system defines an input data set for AGNPS from attributes of basic and thematic maps. It also provides with editing modes so that users can adjust and detail the values for selected input parameters, if needed. The post-processor at the system displays graphically the outputs from AGNPS, which may he used to identify areas significantly contributing nonpoint source pollution loads.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.1
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• pp.102-114
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• 2003

The objectives of the paper are to evaluate cell based pollutant loadings for different storm events, to monitor the hydrology and water quality of the Baran HP#6 watershed, and to validate AGNPS with the field data. Simplification was made to AGNPS in estimating storm erosivity factors from a triangular rainfall distribution. GIS-AGNPS interface model consists of three subsystems; the input data processor based on a geographic information system. the models. and the post processor Land use patten at the tested watershed was classified from the Landsat TM data using the artificial neural network model that adopts an error back propagation algorithm. AGNPS model parameters were obtained from the GIS databases, and additional parameters calibrated with field data. It was then tested with ungauged conditions. The simulated runoff was reasonably in good agreement as compared with the observed data. And simulated water quality parameters appear to be reasonably comparable to the field data.

• Proceedings of the Korea Water Resources Association Conference
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• 2007.05a
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• pp.1008-1013
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• 2007

The objectives of the paper were to identify appropriate best management practices (BMPs) for reducing nonpoint source (NPS) pollutant loadings and to simulate the effects of the application of the several BMP scenarios on the study watershed using Agricultural Nonpoint Source (AGNPS) model. AGNPS model was calibrated and validated for runoff, sediment yield, and nutrient components using the observed hydrologic and water quality data. The simulated runoff, sediment, and nutrient components were well agreed with observed data. The validated AGNPS was applied to estimate the NPS pollution removal efficiency for BMP scenarios which were selected considering the pollutant characteristics of the study watershed.

• Journal of Environmental Impact Assessment
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• v.3 no.2
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• pp.47-56
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• 1994

AGNPS model is an event-based model to analyze nonpoint-source and to examine potential water quality problems from agricultural watershed. This model uses a square grid-cell system to represent the spatial variability of watershed conditions, and simulates runoff, sediment, and nutrient transport for each cell. AGNPS model was applied on Yeonwha watershed, and the test results were compared with the measured data for runoff volume, peak runoff rate, suspended solids, and phosphorus concentration. The watershed of 278.8 ha was divided into 278 cells, each of which was 1 ha in size. The coefficients of determination for runoff volume and peak flow were (0.893 and 0.801 respectively from regression of the estimated values on the measured values. The concentration of suspendid solid was increased but decreased that of phosphate with runoff volume.

• Magazine of the Korean Society of Agricultural Engineers
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• v.39 no.2
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• pp.53-61
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• 1997

The interface system, GIS-AGNPS was to be validated with field data from six tested small watersheds ranging from 0.7 to 4.7$km^2$ in size which have steep topography and complex landuses. The model validation involved the calibration of input parameters and component modifications, in efforts to develop a model applicable to general uses for identifying and controlling nonpoint source pollution loads from agricultural watersheds. The simulated direct runoff from AGNPS was in good agreement with the field data for the averaged antecedent moisture conditions or AMC- II. The results differed, however, from the observed for AMC- I or III. A simple empirical relationship was proposed to estimate the curve number for AMC- I or m from AMC- II, which was found to result in simulated runoff close to the observed. The peak runoff relationship at AGNPS was also modified to reflect the watershed conditions and tested satisfactorily with the field data. The simulated sediment yields from the watersheds were fair as compared to the observed. Nutrient loads simulated from the model were different from the observed data. It appeared that the model was incapable of adequate depicting nutrient transport processes at paddy field and other landuses of the tested watersheds. Some modifications may be needed for the accurate representing the processes at paddy field.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.9 no.5
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• pp.22-31
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• 2006

AnnAGNPS model would be applied to simulate the pollutant removal capacity with the buffer strip in the Deachung reservoir watershed. In 2002, 2,270 tons of TN and 221 tons of TP were discharged from the nonpoint source pollutants in this watershed. During the rainy season, from June to September, 66.4% of TN and 71.9% of TP resulted from nonpoint source loads. AnnAGNPS model was also used to simulate the nutrients removal capacity from the buffer strip under the condition that the present landuse would be changed to forest. As the result of simulation, the removal rates of nutrients from the buffer strip of Daecheong reservoir watershed are 406 tons of TN, 39 tons of TP, which means reduction rates are TN 17.9%, TP 17.8%, respectively.

• Journal of the Korean Association of Geographic Information Studies
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• v.3 no.4
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• pp.63-72
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• 2000

The objective of this study was to identify the applicability of AGNPS(Agricultural Nonpoint Source Pollution) model using RS data; Landsat TM merged by KOMPSAT EOC and GIS data. AGNPS model which is well-known distributed nonpoint source pollution model was used as the assessment tool. This model has the capability to adjust the level of pollutant load from farmstead and the fertilization level of upland field. A small agricultural watershed($4.12km^2$) which has 20 livestock farmhouses located in Gosan-myun, Ansung-gun was selected. AGNPS data were prepared by using Arc/Info, GRASS, ER-Mapper and Idrisi. Four storm events in 1999 were used for runoff calibration, and 2 storm events which were measured in hourly-base at 4 locations along the stream were used for water quality(TN, TP) calibration.

• 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 the Korean Association of Geographic Information Studies
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• v.8 no.2
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• pp.125-135
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• 2005

Generation and transport of nonpoint source pollution, especially sediment-associated pollutants, are profoundly influenced by hydrologic features of runoff. In order to identify pollutant export rates, hence, clear knowledge of rainfall-runoff relationship is a pre-requisition. In this study, performance of AnnAGNPS model was assessed based on the ability of the model to predict rainfall-runoff relationship. Three catchments, each under different nearly single land use, were simulated. From the results, it was found that the model was likely to produce better predictions for larger catchments than smaller catchments. Because of using the daily time scale, the model could not account for short durations less than 24 hours, especially high intensity events with multiple peak flow that significantly contribute to the generation and transport of pollutants. Since CN information for regional areas has not been built up, a careful selection of CN is needed to achieve accurate prediction of runoff volume. Storm distribution also found to be considered as an important calibration parameter for the hydrologic simulation.

• Journal of The Korean Society of Agricultural Engineers
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• v.47 no.4
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• pp.65-74
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• 2005

AnnAGNPS model was applied to a catchment mainly occupied with bushland for modeling non-point source pollution. Since the single event model cannot handle events longer than 24 hours duration, the event-based calibration was carried out using the continuous mode. As event flows affect sediment and nutrient generation and transport, the calibration of the model was performed in three steps: Hydrologic, Sediment and Nutrient calibrations. The results from hydrologic calibration for the catchment indicate a good prediction of the model with average ARE(Absolute Relative Error) of $24.6\%$ fur the runoff volume and $12\%$ for the peak flow. For the sediment calibration, the average ARE was $198.8\%$ indicating acceptable model performance for the sediment prediction. The predicted TN(Total Nitrogen) and TP(Total Phosphorus) were also found to be acceptable as the average ARE for TN and TP were $175.5\%\;and\;126.5\%$, respectively. The AnnAGNPS model was therefore approved to be appropriate to model non-point source pollution in bushland catchments. In general, the model was likely to result in underestimation for the larger events and overestimation fur the smaller events for the water quality predictions. It was also observed that the large errors in the hydrologic prediction also produced high errors in sediment and nutrient prediction. This was probably due to error propagation in which the error in the hydrologic prediction influenced the generation of error in the water quality prediction. Accurate hydrologic calibration should be hence obtained for a reliable water quality prediction.