“…Two studies looked in a more in-depth manner at water quality in combined sewers. In one study, Park et al (2010) sought to characterize the discharge of storm runoff pollution (COD, TSS, total nitrogen, and total phosphorus) from urban catchments with combined sewers in Korea, and to estimate the probability of mass first flush (MFFn) by using SWMM and probability density functions. The authors found that the most reliable MFFn could be achieved when the representative rainfall characteristics including rainfall depth and duration are statistically representative.…”
Section: Combined Sewer System Overflowsmentioning
The storm water management model (SWMM) is a widely used tool for urban drainage design and planning. Hundreds of peerreviewed articles and conference proceedings have been written describing applications of SWMM. This review focuses on collecting information on model performance with respect to calibration and validation in the peer-reviewed literature. The major developmental history and applications of the model are also presented. The results provide utility to others looking for a quick reference to gauge the integrity of their own unique SWMM application. A gap analysis assesses the model's ability to perform water-quality simulations considering green infrastructure (GI)/low impact development (LID) designs and effectiveness. It is concluded that the level of detail underlying the conceptual model of SWMM versus its overall computational parsimony is well balanced-making it an adequate model for large and medium-scale hydrologic applications. However, embedding a new mechanistic algorithm or providing user guidance for coupling with other models will be necessary to realistically simulate diffuse pollutant sources, their fate and transport, and the effectiveness of GI/LID implementation scenarios.
“…Two studies looked in a more in-depth manner at water quality in combined sewers. In one study, Park et al (2010) sought to characterize the discharge of storm runoff pollution (COD, TSS, total nitrogen, and total phosphorus) from urban catchments with combined sewers in Korea, and to estimate the probability of mass first flush (MFFn) by using SWMM and probability density functions. The authors found that the most reliable MFFn could be achieved when the representative rainfall characteristics including rainfall depth and duration are statistically representative.…”
Section: Combined Sewer System Overflowsmentioning
The storm water management model (SWMM) is a widely used tool for urban drainage design and planning. Hundreds of peerreviewed articles and conference proceedings have been written describing applications of SWMM. This review focuses on collecting information on model performance with respect to calibration and validation in the peer-reviewed literature. The major developmental history and applications of the model are also presented. The results provide utility to others looking for a quick reference to gauge the integrity of their own unique SWMM application. A gap analysis assesses the model's ability to perform water-quality simulations considering green infrastructure (GI)/low impact development (LID) designs and effectiveness. It is concluded that the level of detail underlying the conceptual model of SWMM versus its overall computational parsimony is well balanced-making it an adequate model for large and medium-scale hydrologic applications. However, embedding a new mechanistic algorithm or providing user guidance for coupling with other models will be necessary to realistically simulate diffuse pollutant sources, their fate and transport, and the effectiveness of GI/LID implementation scenarios.
“…2. The M(V) curves were plotted to represent the normalized cumulated runoff volume for each storm event and each water quality index 14 . If the curve is close to the diagonal line, it indicates that the pollutant concentration changed little during the early stage of runoff or that the load distribution is comparatively uniform 15 .Figure 2M (V) curves of different pollutions…”
Section: Resultsmentioning
confidence: 99%
“…Park et al . 9 estimated the probability of the mass first flush ratio (MFF n ) by using the Storm Water Management Model (SWMM) to analyze the characteristics of the first flush.…”
To study the first flush effect of nonpoint source pollution in the Guangzhou community unit, runoff from roads, roofs, and green spaces during three rainfall events was collected and analyzed for pollutants. Nine runoff pollution indices were considered. The dimensionless cumulative curve of pollutant mass vs. volume, the first flush coefficient (b) and the mass first flush ratio (MFFn) were used to assess the first flush effect of different underlying surfaces. The assessment results pointed out that the roof was most prone to first flush effect. And ammonia nitrogen and phosphorus were the main pollutants in the first flush in the study area. For a quantitative analysis of the first flush, the Storm Water Management Model (SWMM) was used to simulate the hydrological effect of low impact development (LID) implementation in the community. The results showed that the first flush strength was reduced after setting LID. And LID measures, such as green roofs and sunken green spaces, contribute to flood control and rainwater purification. This research can be relevant regarding for constructing sponge cities and reducing the pollution caused by the first flush.
“…The MFF ratio quantifies the mass of emitted pollutants as a storm progresses, thereby determining the mass first flush for (Kayhanian and Stenstrom, 2005). Park et al (2010) suggested that the MFF can be a useful index for first flush intensity, because various storm and water quality data can be optimized as indicators through statistical analysis. This can be defined mathematically as follow:…”
The monitoring of stormwater runoff from Light Rail Transit (LRT) facilities is insufficient in many regions around the world. In this study, runoff quality and quantity were monitored during operational and non-operational LRT phases during 2010-2013. The event mean concentration (EMC) of pollutants showed little statistical variability during both phases. The antecedent dry day (ADD) showed a strong to moderate positive correlation with most pollutant EMCs during the non-operational phase. The existence and magnitude of the first flush from LRT runoff was found to be similar to those from other transportation land uses. The comparison of LRT runoff data with an adjacent road bridge site showed that the pollutant EMC and unit load were 2 to 9 times higher from the road bridge. It was suggested that LRT automated operation and the elevated track makes this transportation mode a viable option for the management of non-point source pollution.
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