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Closed Drainage Systems
Published in Saeid Eslamian, Faezeh Eslamian, Flood Handbook, 2022
SWMM is the stormwater management model developed by the US Environmental Protection Agency (EPA) (Rossman et al., 2004; Huber et al., 2010). It is a dynamic rainfall-runoff simulation model using the one-dimensional well-known Saint Venant equation (SVE) through the drainage networks. It can be applied for planning, analysis, and design of infrastructure related to stormwater runoff, combined and sanitary sewers, and other drainage systems in urban areas (Huber et al., 2010). The platform consists of an interface, in which a drainage network can be created by using the elements such as pipes, canals, storage units, and sub-catchments, among others, and has been equipped with dynamic controls, such as orifices and gates, and static control elements, such as weirs and outlets (Riano-Briceno et al., 2016). Additionally, the local public infrastructure department can manage the water levels, cumulative volumes, and flow directions by setting operation points for valves and gates.
Riverine and Flood Modeling Software
Published in Saeid Eslamian, Faezeh Eslamian, Flood Handbook, 2022
Mustafa Goodarzi, Saeid Eslamian
The SWMM model or Storm Water Management Model was developed by the US Environmental Protection Agency. The SWMM model is a dynamic rainfall-runoff simulation model with the ability to consider different hydrological phenomena, including evaporation, snowmelt, infiltration, deep percolation, interception, depression storage, and subsurface flow. This model can be used for a single event or continuous simulation of runoff quantity and quality from urban areas. In this model, flood estimation is carried out using the kinematic and dynamic wave method and the combination of ground and channel flow elements. Also, this model has the ability to be linked with the other models and provides satisfactory results in small basins (Rossman, 2009). The SWMM has been widely used throughout the world for planning, analysis, and design related to stormwater runoff, combined sewers, sanitary sewers, and other drainage systems in urban areas (Rossman, 2009).
Framework for Optimum Design and Control of Urban Wastewater Systems
Published in Carlos Alberto Vélez Quintero, Optimization of Urban Wastewater Systems using Model Based Design and Control, 2020
SWMM is a dynamic rainfall-runoff simulation model used for single event or long-term (continuous) simulation of runoff quantity and quality from primarily urban areas. The runoff component of SWMM operates on a collection of sub-catchment areas that receive precipitation and generate runoff and pollutant loads. The main hydrological processes are represented in SWMM: rainfall interception, infiltration, percolation into groundwater, snow accumulation and evaporation. The model uses a nonlinear reservoir approach for routing the overland flow. The pollutants load is generated using the build-up and wash-off approach. Different particle sizes can be represented in the model and these are associated with the common water quality parameters (i.e. chemical oxygen demand, suspended solids, etc).
Exploring near-optimal locations for bioretention systems in catchment scale using many-objective evolutionary optimization
Published in Urban Water Journal, 2023
Abtin Shahrokh Hamedani, Cesar Do Lago, Marcio H. Giacomoni
The near-optimal location of bioretention systems within the French Creek watershed were identified by solving a many-objective optimization problem to maximize the bioretention control benefits. The objective functions of the optimization problem (Equation 2) were defined to minimize the (1) peak flow and (2) runoff volume, and pollutant loads of (3) TSS and (4) TN, while the installation and maintenance (5) cost is kept to a minimum. The runoff volume, peak flow, TSS and TN loading are the outputs of the SWMM model. Total cost is the sum of bioretention costs of all subcatchment (N), where is the number of BRs in subcatchment i and A is the unit area (. is the unit construction cost and is the unit annual maintenance cost, divided by yearly discount factor () to apply the inflation rate (4%) on annual maintenance costs. , , and are the outlet peak flow, runoff volume, TSS and TN load after BR placement, respectively.
Modelling and assessment of sustainable urban drainage systems in dense precarious settlements subject to flash floods
Published in LHB, 2022
Luma Gabriela Fonseca Alves, Carlos de Oliveira Galvão, Bervylly Lianne de Farias Santos, Eldson Fernandes de Oliveira, Demóstenes Andrade de Moraes
SWMM is a well-known dynamic rainfall-runoff and hydraulic simulation model developed by the US Environmental Protection Agency, frequently used for simulating urban flooding (Rossman, 2008). The successful use of this model depends on the accuracy and efficiency of its parameterisation (Baiti et al., 2017). SWMM only considers flow within closed or open pipes. Thus, to model Ramadinha catchment, the streets were assumed to be rectangular open canals, and junctions as points scattered along them, since the runoff propagation in the study area occurs over the roads, until reaching the concrete canal, due to the absence of micro drainage infrastructure. The parameterisation of the current land use and occupation, representing the patterns of lots and streets that determine runoff propagation, took into account several physical characteristics of the catchment.
Exploring trade-offs between cost and peak flow reduction toward identifying optimal LID designs combining green roof and permeable pavement
Published in Urban Water Journal, 2022
Roanny Viana de Barros, Ely Ewerton Amorim Lopes, Gustavo Barbosa Lima da Silva
The input parameters required by SWMM encompass hydrologic and physical characteristics of the soil, drainage network, and subcatchments. Areas (A) of the subcatchments were determined directly from Google Earth imagery. Roof and ground slopes (S) were defined as 0.5% based on information surveyed in situ. Manning’s roughness coefficient for stormwater runoff was adopted based on Rossman and Huber (2016) with a value of 0.011 assigned to the subcatchments and pipes. Subcatchments were assigned 100% imperviousness (which do not allow for infiltration) and null storage depression (dp = 0). Although the parameter flow width (W) is usually obtained by calibration, there are methods for estimating this value. Through the Equation (1), using the A (m2), the parameter W (m) for each subcatchment was determined. Based on Krebs et al. (2014), which suggested the value k = 0.7 considering the analysis of the distribution of k for 2,652 subcatchments, and Li et al. (2016) that recommend values of k between 0.2 and 5.0. In this study, k was defined as 0.7. Table 1 shows the parameters of the model.