Cyanobacterial Harmful Algal Blooms (CyanoHABs) produce toxins and odors in public water bodies and drinking water. Current process-based models predict algal blooms by modeling chlorophyll-a concentrations. However, chlorophyll-a concentrations represent all algae and hence, a method for predicting the proportion of harmful cyanobacteria is required. We proposed a technique to predict harmful cyanobacteria concentrations based on the source codes of the Environmental Fluid Dynamics Code from the National Institute of Environmental Research. A graphical user interface was developed to generate information about general water quality and algae which was subsequently used in the model to predict harmful cyanobacteria concentrations. Predictive modeling was performed for the Hapcheon-Changnyeong Weir–Changnyeong-Haman Weir section of the Nakdong River, South Korea, from May to October 2019, the season in which CyanoHABs predominantly occur. To evaluate the success rate of the proposed model, a detailed five-step classification of harmful cyanobacteria levels was proposed. The modeling results demonstrated high prediction accuracy (62%) for harmful cyanobacteria. For the management of CyanoHABs, rather than chlorophyll-a, harmful cyanobacteria should be used as the index, to allow for a direct inference of their cell densities (cells/mL). The proposed method may help improve the existing Harmful Algae Alert System in South Korea.

The negative changes in the hydrological cycle are increasing due to climate change and urbanization, resulting in deterioration of water quality and environmental issues. Although Low-Impact Development (LID) techniques studies have been conducted to solve this problem, the spatial distribution of LID facilities and sewer types has received less attention. In this study, it is proposed to analyze the effects of sewer type, the spatial distribution of LID facilities, and LID type on runoff and water quality using the Storm Water Management Model and to identify effective ways of improving the hydrological cycle and Non-Point Source (NPS) pollution associated with urbanization. As a result of the runoff reduction analysis, 68% of the rainfall was discharged at the outlet for separate sewers, 79% for combined sewers without storage tank, and 49% for combined sewers with storage tank. The LID scenario results showed the distributed LID application method has higher reduction efficiency of runoff and NPS pollution than the intensive application method. Moreover, intensive application of LID in downstream areas resulted in higher runoff reduction efficiency than the application of LID in upstream areas. It will be used not only in the hydrological cycle plan but also in NPS pollution management.

Changes in land use and climate can affect both the surface runoff and baseflow of streamflow. Baseflow significantly contributes to stream function in regions where climatic characteristics are seasonally distinct. Baseflow estimation depends on the observed streamflow in gauge water sheds, but baseflow estimations in data-poor or gauged watersheds depend solely on streamflow predicted from the hydrologic model. To accurately predict base runoff through the model, it is necessary to apply proper hydrological parameters. Accordingly, the objectives of this study are to (1) improve predictions of SWAT by applying the alpha factor estimated using BFLOW for calibration, and (2) evaluate streamflow and baseflow the effects of changes in land use and climate. The results show the alpha factor estimated using BFLOW in SWAT calibration improves the prediction for streamflow and recessions in the baseflow. In this study, streamflow increased due to land use change (impervious urban and agricultural areas), while baseflow decreased. The baseflow was more significant in the dry season than in the wet season, and the baseflow fluctuation was significant from February to May. Moreover, the changes in land use in the study area lead to differences in the seasonal characteristics observed for the temporal distribution of streamflow and baseflow.

Land use changes, specifically the growth of impervious areas due to urbanization, exacerbate non-point-source pollutants in stormwater runoff, surpassing discharge from point sources in Korea. The application of nature-based solutions, such as constructed wetlands (CWs), is becoming popular for stormwater treatment, but challenges arise when background concentrations are overlooked, leading to reduced pollutant removal efficiency. This study aims to propose a plan for the sustainability of CWs by evaluating design appropriateness and utilizing existing monitoring results. The evaluation of 63 CWs reveals that meteorological factors, specifically antecedent dry days and rainfall depth, have significant impacts on urban stormwater runoff quality in various land uses, affecting the performance of CWs. Designing CWs considering land use is crucial due to the considerable concentration variations across different land uses. Improving CW performance requires proper maintenance strategies to ensure effective pollutant removal mechanisms, especially for poorly degradable organic substances post treatment. Rainfall characteristics play a pivotal role in CW design and operation, affecting capacity, efficiency estimation, and maintenance frequency. Considering various factors such as land use, watershed characteristics, and ease of maintenance is essential when utilizing CWs. This study’s findings contribute to the design and operation of future CWs, emphasizing the need for continuous performance analyses through long-term monitoring.

It is difficult to accurately identify and manage the paths of nonpoint source (NPS) pollution in rural watersheds because their discharge patterns vary depending on season, region, and agricultural characteristics. In this study, flow and water quality during rainfall events were monitored in Songya watershed, an impaired, rural area in South Korea. A method of identifying priority management areas was proposed through scientific objectification and quantification of key factors controlling NPS, such as land use, agricultural type, and load. For the load calculation, a watershed model was developed using Hydrological Simulation Program Fortran (HSPF). Three priority management areas—Mulhan Stream, Osan Stream, and the upstream area of Songya Stream—were selected. Using the developed model, constructed wetlands with the capacity of 1000 m³ were applied at the lower reach of each priority management subbasin and the impacts on NPS pollution reduction were tested. The simulated results showed that BOD and TP concentrations at the outlet of Songya watershed were lowered by 9.2% and 6.0%, respectively. It is expected that the method proposed in this study for identifying priority management areas and implementing best management practice in agricultural watersheds can be applied to similar areas which struggled with NPS pollution.

Urbanization and climate change have deteriorated the runoff water circulation and quality in urban areas worldwide. Consequently, low-impact development (LID) and green infrastructure (GI) techniques have been applied to manage impermeable land and non-point source pollutants. Herein, the impacts of urban characteristics, sewer system type, and precipitation intensity on surface runoff were analyzed using the Storm Water Management Model (SWMM) to derive an effective water circulation strategy for urban and complex areas through the optimal allocation of LID/GI strategies. The runoff rates were estimated to be 77.9%, 37.8%, and 61.7% for urban areas with separated and combined sewer systems and complex areas with combined sewer systems, respectively. During low rainfall, runoff was intercepted in areas with combined sewer systems, and runoff and pollutant load were lower than that in areas with separated sewer system. In contrast, wastewater was diluted during heavy rainfall; however, the total pollutant load was higher than in separated areas. The analysis of scenarios according to the regional distribution of each LID type resulted in high efficiency when combined sewers were applied during the distributed placement of catchment areas. Additionally, LID infrastructure was applied in areas with separated sewers when the placement was concentrated at the end of the basin.