Quantification of nonpoint source pollutants discharged from the combined sewer system in the Nakdong River Basin, Korea, using SWMM

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.

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“…A separated sewer is a method of allowing sewage and rainwater to flow separately. Rainwater flows into a separate rainwater pipeline [27].…”

Section: Analysis Of Flow and Nps Pollutatnt Loads Change Sewer Chara...mentioning

confidence: 99%

Evaluation of SWMM-LID Modeling Applicability Considering Regional Characteristics for Optimal Management of Non-Point Pollutant Sources

et al. 2022

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“…In addition, in widely used sub-catchment-based urban NPS pollution models, such as the storm water management model (SWMM) and the hydrological simulation program—FORTRAN (HSPF). The topological data, which is usually digitalized as the digital elevation model (DEM), mainly provides a reference for delineating sub-catchments and setting their average slope parameters, instead of being a direct model input [ 10 , 11 ]. Therefore, the identified terrain difference with different DEM resolutions may be easily averaged or neglected when the sub-catchment does not match the DEM raster.…”

Section: Introductionmentioning

confidence: 99%

Scaling Effects of Elevation Data on Urban Nonpoint Source Pollution Simulations

Dai

Chen

Zhang

et al. 2019

Entropy

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The scale effects of digital elevation models (DEM) on hydrology and nonpoint source (NPS) pollution simulations have been widely reported for natural watersheds but seldom studied for urban catchments. In this study, the scale effect of DEM data on the rainfall-runoff and NPS pollution was studied in a typical urban catchment in China. Models were constructed based on the DEM data of nine different resolutions. The conventional model performance indicators and the information entropy method were applied together to evaluate the scale effects. Based on the results, scaling effects and a resolution threshold of DEM data exist for urban NPS pollution simulations. Compared with natural watersheds, the urban NPS pollution simulations were primarily affected by the local terrain due to the overall flat terrain and dense sewer inlet distribution. The overland process simulation responded more sensitively than the catchment outlet, showing prolonged times of concentration for impervious areas with decreasing DEM resolution. The diverse spatial distributions and accumulation magnitudes of pollutants could lead to different simulation responses to scaling effects. This paper provides information about the specific characteristics of the scale effects of DEM data in a typical urban catchment, and these results can be extrapolated to other similar catchments as a reference for data collection.

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Effects of the spatial resolution of urban drainage data on nonpoint source pollution prediction

Dai

Lei

Hou

et al. 2018

Environ Sci Pollut Res

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Detailed urban drainage data are important for urban nonpoint source (NPS) pollution prediction. However, the difficulties in collecting complete pipeline data usually interfere with urban NPS pollution studies, especially in large-scale study areas. In this study, NPS pollution models were constructed for a typical urban catchment using the SWMM, based on five drainage datasets with different resolution levels. The influence of the data resolution on the simulation results was examined. The calibration and validation results of the higher-resolution (HR) model indicated a satisfactory model performance with relatively detailed drainage data. However, the performances of the parameter-regionalized lower-resolution (LR) models were still affected by the drainage data scale. This scale effect was due not only to the pipe routing process but also to changes in the effective impervious area, which could be limited by a scale threshold. The runoff flow and NPS pollution responded differently to changes in scale, primarily because of the difference between buildup and washoff and the more significant decrease in pollutant infiltration loss and the much greater increase of pollutant flooding loss while scaling up. Additionally, scale effects were also affected by the rainfall type. Sub-area routing between impervious and pervious areas could improve the LR model performances to an extent, and this approach is recommended to offset the influence of spatial resolution deterioration.

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Quantification of nonpoint source pollutants discharged from the combined sewer system in the Nakdong River Basin, Korea, using SWMM

Cited by 5 publications

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Evaluation of SWMM-LID Modeling Applicability Considering Regional Characteristics for Optimal Management of Non-Point Pollutant Sources

Evaluation of SWMM-LID Modeling Applicability Considering Regional Characteristics for Optimal Management of Non-Point Pollutant Sources

Scaling Effects of Elevation Data on Urban Nonpoint Source Pollution Simulations

Effects of the spatial resolution of urban drainage data on nonpoint source pollution prediction

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