A Study of Non-Point Pollution Sources Management in the Ian Stream Watershed Using the HSPF Model

Through the calibration and validation of the HSPF watershed model, the pollution discharge load in the Ian stream watershed, where the management of non-point pollutant sources was a problem, was simulated by modeling, and the watershed characteristics were analyzed using the actual data during rainfall for the three sub-basins of contamination estimated. As a result of the pollution discharge load by modeling, BOD was high in sub-basin 5, sub-basin 38, and sub-basin 8 in order of pollution levels. Similarly, T-N was high in sub-basin 5, sub-basin 38, and T-P was high in sub-basin 5, sub-basin 8, and sub-basin 38. In sub-basin Ian 3, no significant correlation was observed between precipitation and water pollutants. In the case of the sub-basin Ian 5, a significant positive correlation between rainfall and COD (0.942), rainfall and SS (0.967), and rainfall and T-P (0.890) was observed (p<0.05). In sub-basin Ian 32, a significant positive correlation between rainfall and BOD (0.970), rainfall and SS (0.944), and rainfall and T-P (0.952) was observed (p<0.05). The correlation in Ian stream watershed as a whole, a statistical trend between rainfall and BOD (0.404), rainfall and COD (0.402) was confirmed (0.05 < p < 0.1). The greatest Event Mean Concentration (EMC) values were 3.0 mg/L for BOD, 6.3 mg/L for COD, 502.5 mg/L for SS in sub-basin 32, 2.757 mg/L for T-N in sub-basin 32, and 0.192 mg/L for T-P in sub-basins 3. The runoff coefficients for the sub-basins that were dominated by agricultural land and forest area were 0.17 (sub-basin 3), 0.25 (sub-basin 32), and 0.38 (sub-basin 5), 0.33 (sub-basin 38), respectively. The correlation between the runoff coefficient and BOD, T-N, and T-P for each watershed was analyzed, the correlation with TN was the highest (0.937), and a statistical tendency was observed (0.05 < p < 0.1). Ian Stream watershed is a typical rural area and is largely influenced by NPS. Therefore, accurate and precise management is crucial to improve water quality and secure aquatic ecosystem safety in the future. In order to reduce non-point pollution sources in watersheds, particularly in sub-basins with high discharge loads, a strong correlation between rainfall and water pollutants, or high pollutant runoff, management options such as the construction of shallow reservoirs, buffer green areas, ecological waterways, and artificial wetlands can be suggested.

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Publication Details

Journal
Journal of the Korean Society for Environmental Technology
Published
2025-02-28
DOI
https://doi.org/10.26511/jkset.26.1.1
Primary Topic
Water Quality and Pollution Assessment
Type
article
Field-Weighted Citation Impact
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article

A Study of Non-Point Pollution Sources Management in the Ian Stream Watershed Using the HSPF Model

Yun-Young Choi, Yu-Seong Lim, Byungjoon Lee, Y. Kim
Journal of the Korean Society for Environmental Technology
Water Quality and Pollution Assessment
article

A Study of Non-Point Pollution Sources Management in the Ian Stream Watershed Using the HSPF Model

Yun-Young Choi, Yu-Seong Lim, Byungjoon Lee, Y. Kim
article en

Abstract

Through the calibration and validation of the HSPF watershed model, the pollution discharge load in the Ian stream watershed, where the management of non-point pollutant sources was a problem, was simulated by modeling, and the watershed characteristics were analyzed using the actual data during rainfall for the three sub-basins of contamination estimated. As a result of the pollution discharge load by modeling, BOD was high in sub-basin 5, sub-basin 38, and sub-basin 8 in order of pollution levels. Similarly, T-N was high in sub-basin 5, sub-basin 38, and T-P was high in sub-basin 5, sub-basin 8, and sub-basin 38. In sub-basin Ian 3, no significant correlation was observed between precipitation and water pollutants. In the case of the sub-basin Ian 5, a significant positive correlation between rainfall and COD (0.942), rainfall and SS (0.967), and rainfall and T-P (0.890) was observed (p<0.05). In sub-basin Ian 32, a significant positive correlation between rainfall and BOD (0.970), rainfall and SS (0.944), and rainfall and T-P (0.952) was observed (p<0.05). The correlation in Ian stream watershed as a whole, a statistical trend between rainfall and BOD (0.404), rainfall and COD (0.402) was confirmed (0.05 < p < 0.1). The greatest Event Mean Concentration (EMC) values were 3.0 mg/L for BOD, 6.3 mg/L for COD, 502.5 mg/L for SS in sub-basin 32, 2.757 mg/L for T-N in sub-basin 32, and 0.192 mg/L for T-P in sub-basins 3. The runoff coefficients for the sub-basins that were dominated by agricultural land and forest area were 0.17 (sub-basin 3), 0.25 (sub-basin 32), and 0.38 (sub-basin 5), 0.33 (sub-basin 38), respectively. The correlation between the runoff coefficient and BOD, T-N, and T-P for each watershed was analyzed, the correlation with TN was the highest (0.937), and a statistical tendency was observed (0.05 < p < 0.1). Ian Stream watershed is a typical rural area and is largely influenced by NPS. Therefore, accurate and precise management is crucial to improve water quality and secure aquatic ecosystem safety in the future. In order to reduce non-point pollution sources in watersheds, particularly in sub-basins with high discharge loads, a strong correlation between rainfall and water pollutants, or high pollutant runoff, management options such as the construction of shallow reservoirs, buffer green areas, ecological waterways, and artificial wetlands can be suggested.

Journal of the Korean Society for Environmental TechnologyVol. 26(1)
Climate action
Openalex Percentile: Top 91%
Water Quality and Pollution Assessment
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