The Most Powerful and Comprehensive ArcGIS™-Centric Urban Drainage Management Solution
InfoSWMM RDII Analyst
Excessive wet weather flow resulting from rainfall-derived inflow and infiltration (RDII) is a major source of sanitary sewer overflows (SSOs). SSOs pose serious problems to the public and the environment by causing back up into basements and sewer overflows to streets and rivers. Control of sewer overflows is, therefore, vital to reducing risks to public health and protecting the environment from water pollution. Computer modeling of sewer collection systems plays an important role in determining sound and economical remedial solutions that reduce RDII, improve system integrity, reliability and performance, and avoid overflows.
Mathematical drainage modeling can be used to analyze existing sewer collection systems, to identify potential problems, and to design optimal remedial solutions. For sanitary sewer systems in particular, the ability to determine RDII flows reliably is critical for developing SSO control plans. The processes that convert rainfall to RDII flow in sanitary sewer systems are very complicated. Various factors control RDII responses in addition to the rainfall and antecedent moisture conditions, including depth to groundwater, depth to bedrock, land slope, number and size of sewer system defects, type of storm drainage system, soil characteristics, and type of sewer backfill. Furthermore, RDII responses can vary greatly due to spatial rainfall distributions over a sewershed. Given this degree of complexity, if not supplemented by flow monitoring data, mathematical modeling of RDII inflows may not yield the degree of reliability desired to identify existing problems and to make sound and economical decisions to correct those problems.
The wastewater flow monitoring data collected at sewer collection systems consists of dry-weather flow components and RDII flow components. A crucial step towards successful modeling of sewer collection systems is the ability to decompose the flow monitoring data into the RDII flow and the dry-weather flow. The dry-weather flow component can be further classified into ground water flow and base flow. Groundwater flow represents the groundwater infiltration that enters the collection system through defective pipes, pipe joints, and leaking manhole walls irrespective of rainfall availability. Base wastewater flow represents sewage from residential, commercial, and industrial areas released to the sanitary sewer system. RDII is the rainfall-driven flow that makes its way to the collection system. The decomposition process can then be used to understand the sources of flow and the relative quantities of each flow components for the sewer system. Additionally, it determines if RDII and groundwater flow components are excessive to cause SSOs and other operational problems.
A significant improvement over the EPA SSOAP program, RDII Analyst performs QA/QC of rainfall and flow monitoring data and decomposes the flow data into distinct dry-weather flow (DWF) and wet-weather flow (RDII) components using criteria such as rainfall threshold. The DWF component is further analyzed to construct a DWF pattern that can be used to simulate the collection system using InfoSWMM. The DWF pattern is then assigned to the source nodes that contribute DWF to the meter location in proportion to sewershed areas or based on other criteria. The RDII component is then analyzed to determine RDII events and to calibrate parameters of the RTK synthetic unit hydrograph so that the RDII flow simulated by the RTK method closely matches the RDII flow obtained by the decomposition process. The RTK unit hydrograph parameters are calibrated with genetic algorithm optimization. The calibrated RTK parameters and the DWF patterns are then passed to InfoSWMM to carry out detailed dynamic flow routing through the sewer system and evaluate system response to support development of an optimal capital improvement program. Click here for a complete description and validation of the RDII Analyst workflow process.
Discover some of the key features of InfoSWMM RDII Analyst:
|• Performs QA/QC of flow monitoring data and rainfall data|
|• Identifies dry day flows and wet day flows|
|• Determines hourly dry weather flow (DWF) patterns for weekend and weekdays|
|• Assigns the hourly DWF patterns to the nodes that contribute flow to the flow monitoring site proportional to sewershed area or other criteria|
|• Determines groundwater flow component of dry day flows|
|• Assigns the groundwater flow time series to the nodes that contribute flow to the flow monitoring site proportional to sewershed area or other criteria|
|• Determines the RDII component of the flow monitoring data|
|• Performs linear regression between RDII volume and rainfall volume identified for the RDII events to determine optimal R (i.e., fraction of the rainfall that becomes RDII )|
|• Uses genetic Algorithms optimization to calibrate parameters of the RTK hydrograph to closely match the RDII flow simulated by InfoSWMM with the RDII time series determined by decomposing the flow monitoring data|
|• Export the hourly DWF patterns, the groundwater flow time series, and the RDII time series or the calibrated RTK parameters determined by RDII Analyst to InfoSWMM|
|• Direct connection between Simulation Options and RDII Analyst|
|• RDII Hydrograph Editable from the RDII Analyst|
|• Allow editing of DWF data|
|• Calculate Predicted RDII event values in an expanded RDII Table|
|• Create Run Once command using the existing RTK parameters|
|• Save the import profile data for the RDII Analyst per RDII Inflow Node|
|• Improvement in the evaluation of the T and K parameters for the 3 Unit Hydrographs|
Application Dependent - InfoSWMM Suite.