Artificial structures installed in rivers can change the natural physical, physiochemical, and biological characteristics of the rivers. Coliform bacteria are important water quality indicators, related to human health. This study investigated the relationship between coliform bacteria and water quality factors at eight weir stations constructed in the Nakdong River, a major river in South Korea. Fifteen water quality factors were analyzed at these sites from 2012 to 2016 using correlation and multiple regression analyses. The results for all stations confirmed the analytical validity, with high adjusted R² values of approximately 0.6 and 0.8 on average for total and fecal coliforms, respectively. The results showed influential water quality factors affecting the concentration of coliform bacteria at weir stations. Specifically, total coliforms were mostly affected by organic matter and fecal coliforms were mostly affected by phosphate phosphorus and suspended solids. Rainfall was the most influential factor affecting both coliforms. Further, both coliforms were negatively affected by organic matter below the Dalseong weir in the mid- to downstream area of the Nakdong River. A positive relationship with phosphate phosphorus was indicated at all weir stations. To the authors’ knowledge, this kind of study has never been attempted so far. Thus, the study results can provide important information on influential water quality factors related to coliform bacteria, especially in the Nakdong River, creating a foundation for future water quality management.

Identifying critical source areas (CSAs) is the first step to effectively managing nonpoint source (NPS) pollution. Increasing variability in climate can affect identification of CSAs. In this study, we identified present and future CSAs of NPS pollution in the Nakdong River watershed and examined how climate change will influence the identification of CSAs. Nine NPS pollution-related factors affecting the watershed environment and water quality were considered. These factors were rescaled through a min-max normalization to propose an index system that ranks basins based on the sensitivity of basins to climate change on identifying CSAs. For analyses, past rainfall was replaced with future rainfall under two RCP scenarios, RCP 2.6 and RCP 8.5. Results showed insignificant differences in the spatial distribution of CSAs between the present and the future and between the future scenarios. Basins that are on or adjacent to the Nakdong River mainstream were mainly identified as CSAs, in addition to many basins of the Geumho and Nam rivers. Highly ranked CSAs including the level 1 CSAs, were mainly distributed in the mid- and downstream areas of the Nakdong River, indicating high need of NPS pollution management. This study can provide a foundation for the effective management of NPS pollution in the present and the future.

To assess distribution of metal contamination and grain size in the sediments of Nakdong River (South Korea), surface sediments were collected from 21 sites and analyzed. Within the study area, sand was typically the dominant grain size. However, because of the reduced flow rate and flow velocity, sites adjacent to weirs were composed of relatively fine sediments. A comparison of sediment metal concentrations with sediment quality guidelines proposed by the USA, Canada, and South Korea revealed that sites adjacent to weirs had concentrations that exceeded the standard values. The enrichment factor, index of geo-accumulation, and pollution load index calculation results that the sites adjacent to weirs showed high contamination, with Cd accounting for the highest contamination levels. The metals in the study area varies due to the effect of fine sediments; therefore, high concentrations of metals accumulated adjacent to weirs where fine sediments were distributed in greater proportions. Furthermore, Cd exhibited the greatest contribution to metal contamination in the study area and the highest contamination levels were found at NS19 (adjacent to the Haman weir). Thus, the accumulation of fine sediment increased due to the influence of the weirs, thereby increasing the overall amount of metal contamination.

This study aimed to estimate pollutant unit loads for different landuses and pollutants that reflected long-term runoff characteristics of nonpoint source (NPS) pollutants and recent environmental changes. During 2008–2014, 2026 rainfall events were monitored. The average values of antecedent dry days, total rainfall, rainfall intensity, rainfall duration, runoff duration, and runoff coefficient for each landuse were 3.8–5.9 d, 35.2–65.0 mm, 2.9–4.1 mm/h, 12.5–20.4 h, 12.4–27.9 h, and 0.24–0.45, respectively. Uplands (UL) exhibited high suspended solids (SS, 606.2 mg/L), total nitrogen (TN, 7.38 mg/L), and total phosphorous (TP, 2.27 mg/L) levels, whereas the runoff coefficient was high in the building sites (BS), with a high impervious surface ratio. The event mean concentration (EMC) for biological oxygen demand (BOD) was the highest in BS (8.0 mg/L), while the EMC was the highest in BS (in the rainfall range 50 mm). The unit loads for BOD (1.49–17.76 kg/km²·d), TN (1.462–10.147 kg/km²·d), TP (0.094–1.435 kg/km²·d), and SS (15.20–327.70 kg/km²·d) were calculated. The findings can be used to manage NPS pollutants and watershed environments and implement relevant associated management systems.

Process-based numerical models developed to perform hydraulic/hydrologic/water quality analysis of watersheds and rivers have become highly sophisticated, with a corresponding increase in their computation time. However, for incidents such as water pollution, rapid analysis and decision-making are critical. This paper proposes an optimized parallelization scheme to reduce the computation time of the Environmental Fluid Dynamics Code-National Institute of Environmental Research (EFDC-NIER) model, which has been continuously developed for water pollution or algal bloom prediction in rivers. An existing source code and a parallel computational code with open multi-processing (OpenMP) and a message passing interface (MPI) were optimized, and their computation times compared. Subsequently, the simulation results for the existing EFDC model and the model with the parallel computation code were compared. Furthermore, the optimal parallel combination for hybrid parallel computation was evaluated by comparing the simulation time based on the number of cores and threads. When code parallelization was applied, the performance improved by a factor of approximately five compared to the existing source code. Thus, if the parallel computational source code applied in this study is used, urgent decision-making will be easier for events such as water pollution incidents.