The natural and ecological wastewater treatment system (NEWS) was developed to target organic pollutants and nutrients for decentralized rural communities. The system was installed in Sangwang-dong, Gongju-si, Chungcheongnam-do, South Korea, and operated for about nine months. It consisted of three parts: the anaerobic septic tank, the absorbent-biofilter system (ABS), and the up- and down-flow constructed wetland. The respective nitrogen (N), phosphorus (P), and chemical oxygen demand removal rates of the NEWS were 45.94, 48.65, and 98.47% in the growing season and 27.93, 23.78, and 86.45% in the winter season. The significantly low N and P removal rates could have been caused by microorganism vitality in the ABS, as most of the nutrients occurred in an organic form. Average water temperature of the ABS was 18.13°C in the growing season and 8.289°C in the winter season, which might have influenced the low overall removal rate during the winter season. Performance of the NEWS was efficient, independent of the influent concentration within the study period, except a short term clogging. Considering its high performance, low maintenance, and cost-effectiveness, the NEWS is an effective, feasible alternative for sewage treatment in decentralized communities in South Korea.

Objectives:Since the enactment of the 「Han-River Watershed Act」, comprehensive analysis about direct and indirect contributions and effects of various environmental policies and water quality improvement projects for the preservation of water quality in the Han-River watershed is insufficient. Especially, effect of pollutant source location regulation should be inferred and estimated through model prediction because it does not exist unregulated conditions. As development pressure in non-urban areas near the metropolitan area is increasing, it is necessary to analyze the effects of pollutant source location regulation.Methods:In this study, average pollutant density of Gangwon-do, Gyeonggi-do, and Chungcheongbuk-do, where the regulation areas located, and average pollutant density of water source management areas were compared and analyzed. After that changes in pollutant sources in regulation areas were estimated by assuming load of pollutant sources in unregulated areas that load of pollutant sources in regulation areas. Since many reservoirs are located in Han-river watershed, it is difficult to simulate the water quality of Paldang reservoir using only watershed model, BASINS/WinHSPF and EFDC-WASP were linked. Through this, change in water quality of Paldang Lake was tried to predict when the pollutant location regulation was not implemented, and to analyze the effect of the pollutant location regulation.Results and Discussion:Water quality improvement of Paldang reservoir was evaluated by applying the discharge load when the pollution source location regulation was not implemented to the calibrated model. As a result of the pollution source location regulation, discharge load in the location regulation area was analyzed to reduce by 53.90% and T-P by 48.58%, and the BOD and T-P improvement effect of Paldang Dam was analyzed 6.77% and T-P 6.62%. Since the water quality improvement effect of Paldang Lake is accumulated to the entire upstream, it is evaluated relatively less than pollutant load reducing effect.Conclusion:It was analyzed that pollutiont source location regulation has water quality improvement effect, despite the small area which only located in near Paldang reservoir compared to the total area of the Han-River watershed.

This study developed an algorithm to predict algal blooms in river systems by integrating the two-dimensional CE-QUAL-W2 water quality model with optimization techniques. The study area was the Nakdong River system in South Korea, and the model was constructed for eight multipurpose weir sections. Sensitivity analysis was used to identify key parameters influencing algal concentrations, and an optimization algorithm was developed using the bagging ensemble method. The algorithm aimed to minimize the relative error (%Difference) between simulated and observed chlorophyll-a concentrations, which served as the target variable. The model achieved a "Very Good" rating in the overall efficiency assessment across all target weir sections. Furthermore, a separate evaluation of temporal algal trends was conducted, which showed that while some sections received a 'Poor' rating during low-concentration periods, most sections achieved a 'Good' or higher rating overall. In addition, the model effectively captured temporal patterns and spatial heterogeneity, demonstrating its adaptability to complex hydrodynamic conditions. By integrating machine learning techniques into the physically-based modeling framework, the proposed algorithm is expected to enhance model reliability and improve optimization efficiency. These improvements are applicable to water quality prediction and management systems.

Sustaining the long-term operation of decentralized wastewater treatment facilities remains a challenge in resource-limited settings. This study evaluated an integrated biofilter-constructed wetland system installed at Eswatini Christian University in Mbabane, Eswatini, through a field monitoring campaign in 2015 and a qualitative operational follow-up in 2026. During the 2015 field campaign, the system reduced chemical oxygen demand, total nitrogen, and total phosphorus by 87.1%, 73.3%, and 79.0%, respectively. A 2026 follow-up documented continued use of one biofilter and the wetland, while other installed units were no longer operating. This follow-up provided the reported operational status but did not verify treatment performance after 2015. These findings highlight the need to distinguish continued operation from verified treatment performance when assessing the long-term sustainability of decentralized wastewater treatment. Based on this evidence, we propose a sustainability framework in which modular sustainable engineering, institutional and technical support, and financing act as practical enablers of long-term operation, while preventive public health and social welfare value provide the rationale for maintaining treatment service over time. The Eswatini case therefore supports a broader perspective in which decentralized wastewater systems are designed, financed, and monitored as environmental health infrastructure rather than one-time technology installations.

Three-dimensional (3D) hydrodynamic and water-quality models can represent spatial heterogeneity in stratified reservoirs, but their routine operational application is limited because calibration requires repeated model runs. To address this limitation, this study proposes a calibration-assistance optimization framework for 3D water-quality models that reduces the number of runs needed to reach an acceptable parameter set. The framework was implemented using the Estuary, Lake and Coastal Ocean Model (ELCOM) coupled with the Computational Aquatic Ecosystem Dynamics Model (CAEDYM). Unlike conventional approaches that rely on many separate runs during calibration, the proposed method compares simulated and observed values from each run across multiple stations and sampling dates and combines those differences to guide the next parameter update. This allows each run to provide multiple pieces of calibration information while reducing repeated executions. Chlorophyll-a (Chl-a) was used as the primary calibration target for evaluating the proposed framework. Application to Daecheong Dam and Namgang Dam showed convergence within 3–7 optimization iterations (i.e., 3–7 model runs), with total turnaround times of approximately 17–24 h. These results indicate that the proposed workflow can support reproducible calibration adjustment for computationally expensive 3D models.