epa swmm manual

epa swmm manual

EPA and its employees do not endorse commercial products, services, or enterprises. It is open source public software and is free for use worldwide. SWMM 5 was produced in a joint development effort with CDM, Inc., a global consulting, engineering, construction, and operations firm. SWMM provides an integrated environment for editing study area input data, running hydrologic, hydraulic and water quality simulations, and viewing the results in a variety of formats. These include color-coded drainage area and conveyance system maps, time series graphs and tables, profile plots, and statistical frequency analyses. These include the ability to do the following: Runoff reduction via LID controls. Each of the areas contains its own fraction of pervious and impervious sub-areas. Overland flow can be routed between sub-areas, between sub-catchments, or between entry points of a drainage system. The following processes can be modeled for any number of user-defined water quality constituents: Reduction in dry-weather buildup due to street cleaning. The SWMM Climate Adjustment Tool (SWMM-CAT) provides a set of location-specific adjustments derived from World Climate Research Programme global climate change models. SWMM-CAT accepts monthly adjustment factors for climate-related variables that could represent the potential impact of future climate changes. Although some of these practices can also provide significant pollutant reduction benefits, at this time, SWMM only models the reduction in runoff mass load resulting from the reduction in runoff flow volume. More complex rain gardens are often referred to as bioretention cells. They provide storage volume and additional time for captured runoff to infiltrate the native soil below They contain vegetation that enable rainfall infiltration and evapotranspiration of stored water. Cisterns may be located above or below ground and have a greater storage capacity than a rain barrel.http://buyanycarnow.com/uploadedfiles/dodge-nitro-chilton-manual.xml

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In block paver systems, rainfall is captured in the open spaces between the blocks and conveyed to the storage zone and native soil below. It contains nine worked-out examples addressing common stormwater management and design problems encountered in practice. The manual will be especially useful for new SWMM users who need additional guidance in applying this powerful tool to urban drainage design and analysis. Published by Elsevier Ltd. All rights reserved. Recommended articles No articles found. Citing articles Article Metrics View article metrics About ScienceDirect Remote access Shopping cart Advertise Contact and support Terms and conditions Privacy policy We use cookies to help provide and enhance our service and tailor content and ads. By continuing you agree to the use of cookies. Unfortunately looks like your browser either doesn't support Javascript or Javascript is disabled. Please enable Javascript to continue browsing.Expand your knowledge, get insights and discover new approaches that let you work more effectively.Meet your colleagues, share your experiences and be on the forefront of advances in our profession.Put our experience, knowledge, and innovation to work for you. In contrast, urban drainage systems have very low interception and groundwater recharge capacity and are designed to capture runoff from impervious surfaces and pipe it through a distributed network away from people, roads, and other urban infrastructure. Soil moisture is replenished by irrigation usually using potable water supply. Because urban pollutants are also found on impervious surfaces, pollutants are also inadvertently conveyed into collection systems and away from the urban system without treatment during rain storms (or due to irrigation overflows) leading to the pollution of urban creeks and rivers and nearby lakes, estuaries and coastal water bodies.http://asbazainville.org/userfiles/dodge-nitro-manual-2007.xml

This is achieved through slowing, spreading, and infiltrating (sinking) urban stormwater run-off thus reducing stormwater peak flow and volume and potentially providing effective treatment of urban pollutants. There are different kinds of GI that incorporate mechanisms for slowing, spreading, and helping stormwater to soak into the ground. These mechanisms include slowing water velocities (adding roughness), detaining stormwater in vaults, ponds or depressed areas, retaining stormwater allowing sedimentation and reuse of captured volume (landscape irrigation or toilet flushing are examples), filtering stormwater through porous media (e.g. sand or other man-made filters and pervious pavement), infiltrating stormwater into the ground, and methods to treat stormwater such as the addition of activated carbon or the harvest of vegetation that is primarily nourished from nutrients in stormwater. Since GI is now included in many stormwater permits for both flow and water quality control, it is important to place it in the urban landscape in the most beneficial locations with the least cost. These features help to connect the public with natural environmental processes leading to greater community involvement and caring for the cityscape. In many cases, it is these features, rather than water quantity and quality benefits, that primarily drive the community decision making process around inclusion of GI into redevelopment projects. The output from the tool can be used by municipal staff and their consultants as the basis for determining the most cost effective and worthwhile locations for GI placement. Outputs can be included in various planning documents such as parks and recreations plans, capital improvement plans, redevelopment plans, or re-envisioning documents in relation to “ complete streets ”.

Although the present version focuses quantitatively on water quality and quantity, the other ancillary benefits can be qualitatively included through the ranking components described below and discussed in the individual case studies sections. It is hoped that future iterations of the Toolkit will include quantitative modules for these other benefits. Until that time, the present version of the GreenPlan-IT tool includes the following nine (9) GI feature types: Pollutants are removed from stormwater through adsorption, microbial activity, plant uptake, sedimentation, and filtration. Bioretention with out underdrains are more suitable to areas with higher soil filtration rates. Runoff is collected during storm events and stored in the void spaces of the gravel before being released back into the soil by infiltration. It reduces runoff volume, peak discharge rates, pollutant loading, and runoff temperature. Stormwater runoff drains into these wetlands and the plants and soils act as a filter for the stormwater. They are designed to slow stormwater runoff and filter out particulate pollutants, and promote infiltration before reaching the stormwater drain. A wet pond provides similar benefits to stormwater wetlands, except they are typically deeper and may increase the temperature of runoff. Water stored in the planter box is disharged through a pipe not through infiltration of native soils. Tree wells are designed to collect runoff to allowing excess water to infiltrate into native soil or be collected by an underdrain. This analysis has been more recently run to create regional suitability layers for the additional GI types.These rankings were then weighted and used in a Categorical Weighted Overlay to identify locations that were suitable for each GI type.

For example, incorporating the base analysis in the initial screening process provides a more refined (but exclusive) output since only locations that were deemed to be most suitable by the base analysis are included. Incorporating the base analysis in the ranking process provides a final output that is more inclusive of potential GI locations, and the results will not be limited to locations deemed suitable by the base analysis; rather, locations within the base analysis will receive a higher ranking than those not specified in the base analysis. This may be more desirable as many of the factors that were used to create the base analysis layer can be addressed by engineering and or design. That is, locations outside of the base analysis may still be possible locations for GI, however they may be more costly to install in those locations due to additional engineering and installation requirements (terracing due to slope, underdrain due to non-ideal soil type etc.). A city or county interested in saving costs by installing regionally applicable standard GI designs may need to take these issues into account when running the tool. As with any simple model of a complex landscape, the scale and accuracy of input data will largely determine the scale and accuracy of the interpretative outputs. Therefore, when local higher quality data are available, we recommend these be incorporated. There are four (4) modules that may be used to facilitate a more refined analysis using available local data to improve the scale and accuracy (and relevance) of the tool outputs. These are: If using local datasets, the user should reference the folder schema to determine the locations and formats of any compiled data. This will be described in detail in Tool Preparations. As a best practice, we recommend projecting any local datasets to this spatial reference; however, this is not a requirement.

The user may select any combination of refined analyses when running the GreenPlan-IT Site Locator Tool (i.e. any combination of 0 - 4 analyses). An example of a completed locations.csv table is here: Example locations.csv. An example of a completed locations.csv table is here: Example ownership.csv. If it is negative, type “-1” under “rank” if positive then type “1”. Provide this value to each layer row that the factor applies to. If there is only one factor within that layer then the weight of that layer as 1. Note, you may choose to edit the opportunities and constraints table after viewing results. This is often an iterative process in order to create the most useful output for a user. Or you could purposely run it different ways for each neighborhood if there are specific local interests that are more or less important. An example of a completed knockouts.csv table is here: Example knockouts.csv. When running the Site Locator Tool, the GI Size Table is used to remove GI locations that do not meet the minimum area specified. This table is also required if the user plans on running the Optimization Precursor Tool to generate inputs for the GreenPlan-IT Optimization Tool. This tool identifies (and ranks, when Opportunities and Constraints Analysis is used) feasible locations for GI development. We recommend that the character length of the output directory be Check to restrict the final outputs to only areas that overlap the regional suitability layer for each GI type.You may still include the base analysis layer in the Opportunities and Constraints module and run the tool for that type of GI only, in order to rank locations that fall within the base analysis areas as higher. This second option may be the preferable method. See Preparing Analysis Tables. Any analysis should be performed using the feature classes in the file geodatabase. The legend provided with the tool will have to be added manually.

The legend provided with the tool will have to be added manually. Many of these are projected copies of the input data or intermediate analyses; however, the final GI locations for each selected GI Type will be saved in the following format: Each KMZ represents a geographic quadrant of the area of interest. A set of KMZ quadrants is made for each selected GI type (one set each for all locations, and private locations and public locations, where applicable). This tool calculates the total area of each GI type within each sub-basin (produced during hydrologic modeling of the area). Additionally, the Optimization Precursor Tool calculates the number of possible GI locations within each sub-basin based on the minimum GI areas defined in the GI Size Table. In this way, total area is conserved. If a unique ID field does not exist, use the Object ID field. In this way, total area is conserved. The tool is built upon the publicly available EPA Storm Water Management Model (SWMM) (Rossman, 2010), a dynamic rainfall-runoff simulation model used for single event or long-term (continuous) simulation of runoff quantity and quality and is used for planning, analysis and design related to stormwater runoff management, combined and sanitary sewers, and other drainage systems in urban areas. Within the toolkit, this tool is used to establish the baseline hydrology and water quality conditions through the characterization of the modeled watershed before any new management activities are implemented; identify high-yield runoff and pollution areas; and evaluate relative effectiveness of implementing GIs across different areas within a watershed, based on their potential for reducing runoff volume or contaminant loads. The hydrologic and pollutant modules are used to simulate the generation, transport, and fate of stormwater runoff and associated pollutants from the landscape.

The GI module utilizes stormwater runoff from the hydrologic module as the forcing function for GI simulation to estimate any reduction made from GI implementation by performing without and then with the GI scenarios simulation. As such, this manual will not provide a detailed description of SWMM, its strengths and weaknesses, or software and hardware requirements, nor step by step instructions on model setup as a regular user manual would do. Rather, it will focus on providing guidance on model development and application. Before running GreenPlan-IT, users should familiarize themselves with the SWMM user guidance. In particular, users will need to download: Once the model development is completed, the model can then be used to answer management questions by simulating various management scenarios. In the case of this project, the developed modeling tool is used to drive GI simulation. The data collection process involves a thorough compilation and review of information available for the study area. It generally includes gathering applicable regional and site-scale GIS data layers, digital elevation model (DEM) data, stream networks, soil, land use, critical source information, and monitoring data for calibration and validation. A summary of typical data needs for SWMM development is provided in Table 3-1. Consistent with the lumped nature of the model, each sub-basin is modeled as a homogeneous unit with spatially averaged descriptive properties. Watershed delineation is normally done by GIS analysis using topographical data. The watershed delineation will establish a representation of the study area, and ideally, locally derived higher-resolution site scale data should be used. The proper spatial scale of a modeling project is usually determined through professional judgment and needs to take into account important factors such as the project goals, size of the study area, spatial scale of crucial input data, and model run time.

For a stormwater management project, watershed delineation should strike a balance between a meaningful size of sub-basins for guiding GI implementation and demand on computer run time. A hydrologic calibration is typically done by means of an iterative process of trial and error, by adjusting the parameters within the established range until modeled flow rates match the timing, magnitude, and total volume of the field-observed streamflow data. The model calibration is necessary to ensure that a representative baseline condition is established with a high degree of confidence in its applicability to form the basis for comparative assessment of various management scenarios. A subset of the model parameters associated with frequent storm events (impervious percentage, subcatchment width, Manning’s roughness, depression storage, and soil infiltration parameters) are most sensitive and typically used as hydrologic calibration parameters. A brief discussion of each parameter follows. This is an abstract basin parameter and is commonly used as a “tuning parameter” for model calibration because of the uncertainty associated with determining the travel length of stormwater runoff. Increasing the travel length decreases the subcatchment width which creates a more attenuated response to storm events. Separate roughness coefficients are applied to pervious versus impervious surfaces. Typical values are as follows: The potential depression storage is related to the surface roughness coefficient; thus, separate values are required for pervious and impervious surfaces. Typical values are as follows: Adjusting this parameter could improve model performance, but the improvement is often limited. Regardless of the method used, the infiltration parameters are closely correlated to hydrologic characteristics of the soil groups.

Regional data available from the NRCS in the State Soil Geographic Database (STATSGO) is commonly used in lieu of local soil information to determine the default values and allowable ranges for each parameter. The calibration process then involves varying the parameters within their defined bounds in an effort to optimize the model. The model is capable of analyzing the buildup, washoff, transport and treatment of a variety of water quality constituents such as sediment, heavy metals, and nutrient. Because the SWMM uses the buildup-washoff formulation that assumes urban runoff quality constituents behaving in some manner similar to “sediment” of sediment transport theory, it works well for constituents that are transported in solid form, either as particulates or by adsorption onto soil particles, but not for constituents that are transported primarily in a dissolved state, e.g., NO3. Water quality parameters are defined for buildup and washoff of each pollutant and include maximum surface build-up, surface build-up rate and wash-off coefficients. These parameters are land use specific and are primary parameters used for water quality calibration. The water quality calibration has often proved more difficult than the hydrology calibration, due largely to the lack of high resolution calibration data, both temporally and spatially. Therefore, the calibration procedure should also incorporate the comparison of the outcomes with a reasonable conceptual understanding of the likely variation of pollutant sources, erosion, and transport processes in the landscape that is water quality parameter specific. The outcome of the water quality simulation should at least compare closely with this conceptual model and follow the reasonable likelihood that pollutant production should vary more between each sub-basin than flow production.

For example, flow production between sub-basins normally varies by 2-4-fold between the least to the most imperious sub-basins whereas it is not uncommon for pollutant loads to vary by any magnitude between sub-basins by 5-100-fold. The GI simulation is usually performed after SWMM is developed for a watershed using local data, to quantify any runoff reduction associated with GI implementation. The types of GI compartments are: storage, underdrain, surface, pavement and soil. GI controls are represented by a combination of these vertical layers whose properties are defined on a per-unit-area basis. These compartments are GI specific and the SWMM5 user manual (Rossman, 2010) provides a detailed description on the configuration of each GI type. The model does not contain mechanisms for sediment deposition and transport within a river channel. The mechanistic simulation of pollution reduction is not built into the model. Additional programing by the user is required for simulating load reduction within the GI types. Office of Research and Development.