Three watersheds in Korea (Dochoncheon, Gongjicheon, Seolseongcheon) with different land cover characteristics were selected for non-point source pollution monitoring. Event mean concentration (EMC) was calculated, and runoff characteristics were compared through first-flushing and statistical analyses. The mean of the water quality parameters was the highest in Seolseongcheon during dry days among the three watersheds. EMCs of biochemical oxygen demand (BOD) and total nitrogen (TN) were higher in Dochoncheon and Gongjicheon during rainy days, respectively. The upper Seolseongchun watershed showed overall greater values of chemical oxygen demand (COD), suspended solids (SS), total organic carbon (TOC), and total phosphorus (TP). First-flush analyses indicated that SS had the strongest and TN had the weakest effects on the first flush. BOD was the highest in Dochoncheon (urban watershed) and increased with increased number of antecedent dry days. Rainfall intensity appeared to affect SS runoff strongly in Gongjicheon and Seolseongcheon. COD showed strong correlation with SS and TOC in all watersheds, and organic matter (COD and TOC) demonstrated high factor loads during dry and rainy days. Thus, organic matter–related factors were classified as the major factors in pollutant loads. TP and TN were separately classified during dry days in Gongjicheon and Seolseongcheon, whereas these were the secondary factors during rainfall when the influence of non-point pollution was substantial. Cluster analyses showed that the monitoring sites in Dochoncheon and Gongjicheon watersheds were closer than Seolseongcheon. As a result of the comparison of non-point source pollution runoff in the three watersheds, it was difficult to explain the non-point source pollution runoff by specific characteristics such as land cover. For science-based management of non-point pollution, it is necessary to obtain additional survey data considering the climatic, geographical and major industries.

Increasing public awareness about the aesthetics and safety of water sources has shifted researchers’ attention to the adverse effects of volatile organic compounds (VOCs) on humans and aquatic organisms. A total of 17 VOCs, including 10 volatile halogenated hydrocarbons and seven volatile non-halogenated hydrocarbons, were investigated at 36 sites of the Han River Basin, which is the largest and most important drinking water source for residents of the Seoul metropolitan area and Gyeonggi province in South Korea. The VOC concentrations ranged from below detection limits to 1.813 µg L⁻¹. The most frequently detected VOC was 1,2-dichloropropane, with a detection frequency of 80.56%, as it is used as a soil fumigant, chemical intermediate, and industrial solvent. In terms of geographical trends, the sampling sites that were under the influence of sewage and industrial wastewater treatment plants were more polluted with VOCs than other areas. This observation was also supported by the results of the principal component analysis. In the present study, the detected concentrations of VOCs were much lower than that of the predicted no-effect concentrations, suggesting low ecological risk in the Han River. However, a lack of available ecotoxicity data and limited comparable studies warrants further studies on these compounds.

Inflow mixing affects the spatiotemporal heterogeneity of water quality in reservoirs. Reservoir water quality management requires accurate prediction of density flow regimes to understand the spatiotemporal distribution of dissolved and particulate nutrients and organics. This study aims to characterize the mixing and circulation of three rivers with different physicochemical properties in a run-of-the-river (ROR) reservoir, using high-frequency monitoring and three-dimensional (3D) hydrodynamic modeling. The Aquatic Ecosystem Model (AEM3D) was constructed for the reservoir and calibrated with high-frequency data obtained from May–June 2016, accurately reproducing the observed spatiotemporal variations of flow velocity, water temperature, and electrical conductivity (EC) in the reservoir. High-frequency data and 3D model results showed that mixing of the rivers in the ROR reservoir is governed by density flow regimes formed by influent water temperature differences. At the confluence, colder and warmer river influents formed underflows and surface buoyant overflows, respectively. The spatial arrangement of flow direction, water residence time, and EC concentration were largely controlled by the buoyancy-driven flow. Stagnant areas with long residence times corresponded with areas of observed algal blooms and hypoxia. High-frequency sensor technology, combined with 3D hydrodynamic modeling, is effective for understanding the complex flow regimes and associated water quality characteristics in ROR-type reservoirs.

This study evaluated the spatiotemporal variability of water quality in the Han River Basin (HRB) as well as the contributions of potential pollution sources using multivariate statistical and absolute principal component score-multiple linear regression (APCS-MLR) modeling techniques. From 2011 to 2020, data on water quality parameters were collected from 14 sites in the Ministry of Environment’s water quality monitoring network. Using spatiotemporal cluster analysis, these sites were classified into two periods over the year (dry and wet seasons) and into three regions: low pollution region (LPR), moderate pollution region (MPR), and high pollution region (HPR). Through principal component analysis, we identified four potential factors accounting for 80.1% and 74.1% of the total variance in the LPR and MPR, respectively, and three that accounted for 72.7% of the total variance in the HPR. APCS-MLR results indicated domestic sewage and phytoplankton growth (25%), domestic sewage and seasonal influence (29%), and point pollution sources caused by domestic sewage and industrial wastewater discharge (31%) as potential factors for the LPR, MPR, and HPR. These results demonstrate that the multivariate statistical techniques and the APCS-MLR model can be effectively used to monitor network design, quantitatively evaluate potential pollution sources, and establish efficient water quality management policies.

In 2012, a large concentration of geosmin was found in the Paldang reservoir, which is the primary source of drinking water in Seoul, Korea. In June and September 2012, we measured the concentrations of cyanobacteria and actinomycetes, and geosmin, to identify the source of geosmin in the Paldang reservoir. A total of 68 water samples were collected from two sampling sites (Sambong, Paldang), and used to analyze the correlation between cyanobacteria, actinomycetes, and geosmin. The cell density attained a maximum of 24,722 cells/mL on August 11, 2012 and geosmin occurred at a high concentration of 3,934 ng/L on August 13 in Sambong. After July 31, 2012 a rapid increase in growth and cell density occurred with a peak value of 11,568 cells/mL on August 6, 2012. At the same time, the geosmin concentration increased to 3,157 ng/L in Paldang. The number of cyanobacteria positively correlated with geosmin concentration (R2 = 0.84, P < 0.0001), while actinomycetes were not significantly correlated with geosmin (R2 = 0.01, P = 0.709). In addition, the number of actinomycetes was associated with increased turbidity (R = 0.507). Among the various water quality constituents, temperature affected cyanobacteria in the Paldang reservoir (R = 0.803). These results suggest that cyanobacteria are the main source of geosmin in the Paldang reservoir, which might be providing useful information for managing the unpleasant taste of its drinking water.