• Journal of Korean Society on Water Environment
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• v.25 no.2
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• pp.212-220
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• 2009

In many studies, the Numeric Integration (NI) method has been widely used to calculate pollutant loads from the watershed because it is easy to apply. However, there have been many needs for more accurate pollutant loads estimation method with the restricted number of water quality samples. However, the ESTIMATOR model does not allow the users to define the regression model to explain the measured flow and water quality relationship, indicating the ESTIMATOR model is not flexible. The LOADEST model allows the user to choose the model type from 11 predefined general forms of regression equations. Annual loads of T-N and T-P with the LOADEST model were 0.70 times and 0.84 times of those by NI method, respectively. The coefficient of determination ($R^2$) of the LOADEST regression for the T-N and T-P were 0.92 and 0.72, respectively. This indicates that the load estimation regression model with the LOADEST for the study watershed explains the relationship between the observed flow and water quality data well reasonably well. Based on these findings, we suggest that the LOADEST model estimated regression equation could be used to estimate pollutant loads using the measured flow data for the study watershed.

• Journal of Korean Society on Water Environment
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• v.32 no.2
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• pp.149-162
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• 2016

In recent years, there has been demand for precise estimations of pollutant loads on nationwide scale for the development of appropriate site specific (watershed specific) policies to reduce the negative impact of pollutant loads. River flow data and water quality data that were previously collected by various research institutes and universities for specific research purposes for a limited period was utilized in this study. However, only TMDL 8-day interval flow and water quality data were available in national scale. Three watersheds were selected and pollutant loads were calculated by two methods i.e., Numeric Integration (NI) method and Soil and Water Assessment Tool (SWAT). Subsequently, the results were compared to determine the appropriate method for monitoring nonpoint source networks nationwide. The SWAT model was calibrated and its estimated daily flow data were used in the NI method with estimated sediment data for 8-day monitoring data for three watersheds. The results indicated that the quantity of pollutant loads estimated with the NI and SWAT are different to some degrees especially during the summer season for all the three study watersheds. Thus, more frequent sampling of water quality is needed for nonpoint source pollutant estimation.