Abstract

Computer simulation models of urban drainage systems represent the most effective and viable means for evaluating system response to various management strategies. To be effective, these models require extensive spatial utility infrastructure data readily available from a Geographic Information System (GIS). Indeed, a utility’s database contains the objects that make up the network and information about these objects. The GIS is used to link this information to the digital map. Used as a spatial database, GIS can greatly assist in various modeling and analysis applications through the development of automated tools for constructing and maintaining reliable network models of urban drainage systems. This chapter presents a comprehensive GIS-based decision support system that integrates several technologies for use in the effective management of urban stormwater collection systems. It explicitly integrates ESRI ArcGIS geospatial model with advanced hydrologic, hydraulic, and water quality simulation algorithms based on the USEPA SWMM5 urban drainage network solver, global optimization techniques based on fast messy genetic algorithms for calibration and design, automated dry weather flow generation and allocation, and automated subcatchment delineation and parameter extraction to address every facet of urban drainage infrastructure management.

Comprehensive modeling of sewer collection systems is essential to develop reliable and cost-effective remedial solutions for enhancing system integrity and performance, restoring and maintaining needed capacity, avoiding backups and overflows and meeting environmental regulations to improve public health and safety. However, modeling of urban stormwater and sewer collection systems requires extensive spatial and temporal data due to the complexity of the governing processes and the heterogeneity of watershed properties and flow paths and conduits found in developed and undeveloped urban areas. These features are geographic in nature and suggest the need for an efficient spatial data management and analysis tool such as a GIS. A GIS is both a database system with specific capabilities for spatially referenced data, as well as a set of operations for working with the data (Poku and Arditi, 2006). It provides functions for development and preparation of accurate spatial information for input (pre-processing) to urban drainage system models. It also facilitates post-processing spatial analysis and graphical output display for evaluating results. Therefore, the marriage of mathematical stormwater models and GIS ensures that sound engineering solutions are drawn efficiently and effectively in the planning, design, operation, and maintenance of wastewater collection systems (Miles and Ho, 1999). These benefits are being realized by wastewater utilities and municipalities in managing their sanitary, storm and combined sewer system infrastructures.

Shamsi (2002) distinguishes three different methods to link a GIS to simulation (mathematical) models: interchange, interface, and integration, listed in order of complexity and versatility. The interchange method employs a batch process to transfer data between the GIS and simulation model. Both GIS and the simulation model are run separately and no direct link exists between the two systems. The interface method provides a direct link to exchange information between the GIS and the simulation model with customized pre- and post-processing functions added to the GIS. However, the interface method also requires the simulation model to run independently from the GIS. The integration method represents the closest relationship between the GIS and the simulation model. The method combines both the GIS and the modeling functions in one complete seamlessly integrated package. It provides the basis for a comprehensive decision support system for the effective management of urban drainage systems.

In addition to ensuring seamless integration of GIS with a mathematical model that simulates the hydrology, hydraulics and water quality of urban drainage systems, a comprehensive decision support model should have: tools that facilitate watershed delineation and extraction of input parameters from digital topographic, soil and land use data; a calibration model that adjusts parameter values so that model predictions closely match observed data; a design model that determines cost-effective solutions to eliminate flooding and associated pollution problems; a load allocation tool that computes wastewater loads entering the collection system at various locations; and the capability to analyze important water quality parameters whose improper management could cause serious problems including loss of life (Nicklow et al., 2004, 2006).

This chapter presents an integration of the USEPA storm water management model (SWMM5) for hydrologic, hydraulic, and water quality simulation with GIS (ArcGIS, ESRI, Redlands, California) and an efficient variation of genetic algorithms (GA) optimization technology to address every facet of urban wastewater management activities. The resulting integrated system effortlessly reads GIS data, extracts necessary modeling information such as subcatchment parameters, and automatically constructs, loads, calibrates, designs, analyzes and optimizes a representative model considering hydraulic, water quality and hydrologic management and operational requirements. It also makes it easy to simulate various scenarios, identify deficiencies, and determine cost-effective improvements for optimum performance. It is a single software platform that addresses the requirements of both wastewater utility engineers and GIS professionals and provides an informative structured framework for complete sewer model construction, analysis, optimization, and results presentation. These combined capabilities provide a consistent geospatial environment to assist wastewater utilities in planning, designing, and operating reliable systems, evaluating the effectiveness of best management practices (BMPs), and in optimizing their capital improvement programs. The benefits of the proposed decision support system are illustrated by application to an example stormwater collection system and conclusions are stated.

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