Hydraulic Model of the Belle Fourche Irrigation District Using EPA SWMM 5.0

Schoenfelder, Curtis; Kenner, Scott J.; Hoyer, Dan

doi:10.1061/40856(200)262

Cited by 5 publications

(1 citation statement)

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“…SWMM model predictions are typically found to be sensitive to parameters that are related to characteristics of impervious surfaces such as impervious percentage (Barco et al 2008;Cermola et al 1979;Chow et al 2012;Jia et al 2014;Kim et al 2011;Mancipe et al 2011;Song et al 1983;Zaghloul 1983), impervious depression storage (Barco et al 2008;Boon et al 2008;Calabrò and Maglionico 2002;Chen and Adams 2006;Obropta and Kardos 2007;Sun et al 2014a;Tsihrintzis and Hamid 1998;Xiong et al 2005;Zaghloul and Al-Shurbaji 1991;Zhao et al 2008), and Manning's roughness coefficient for impervious surfaces (Chen and Adams 2006;Chow et al 2012;Gülbaz and Kazezyılmaz-Alhan 2013;Jia et al 2014;Krebs et al 2014;Mancipe et al 2011;Schoenfelder et al 2006;Sun et al 2014a;Xiong et al 2005;Zhao et al 2008;Zhao and McEnroe 2000). Moreover, a number of studies found output to be sensitive to overland flow width (Boon et al 2008;Cermola et al 1979;Chow et al 2012;Jia et al 2014;Mancipe et al 2011;Marsalek 1983;Sun et al 2014a;Zaghloul and Al-Shurbaji 1991;…”

Section: Sensitivity Analysismentioning

confidence: 99%

Storm Water Management Model: Performance Review and Gap Analysis

Niazi

Nietch

Maghrebi

et al. 2017

J. Sustainable Water Built Environ.

175

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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.

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