Leveraging Geospatial Data to Solve Storm Sewer Issues

7/28/2019 Leveraging Geospatial Data to Solve Storm Sewer Issues

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As presented at Map India 2006, January 30th

February 1st

2006. New Delhi, India.

Leveraging Geospatial Data to Solve Storm Sewer Issues

Sharavan Govindan, Thomas M. Walski, Robert Mankowski, Jack Cook, Malcolm Sharkey,Bentley Systems Inc, Watertown, US 06795, 1-800-727-6555, www.bentley.com/haestad

Stormwater management systems are critical to urban populations, and the consequences of

storm sewer system failures can be catastrophic

ranging from damage to property andpossessions by flooding, through to the spread of disease and even death. In recent times India sstormwater management systems have been placed under enormous strain by flooding problemsthroughout the country, and it is clear that many of these storm sewer systems require dramaticimprovement (Times of India, 2005). However the analysis and design of stormwater systems isfar from straight forward, and the planning of system improvements is further complicated by theneed to prioritize system upgrades to maximize the benefits of capital expenditure.

Fortunately, hydraulic models based on geospatial data can be leveraged as a key tool forsupporting investment decisions for storm sewer infrastructure. The advancement of strongmodeling technologies that marry rich geospatial modeling and thematic mapping environmentswith proven dynamic wave solvers is expected to dramatically upgrade the scope and value ofsystems planning and operations modeling efforts.

Hydraulic models can be built using a range of geospatial data, some of which may already beavailable to Indian cities and utilities. Information such as CAD files, GIS files, aerial photography,asset management information, digital elevation models and survey information can all be utilizedin the model building process. Then, once the model is built, the system can be analyzed and theresulting information is used to assist with the following practical applications:

a) Develop comprehensive system master plansb) Assess the impact of inflow and infiltration on sewer overflowsc) Develop sewer overflow remediation programsd) Perform system capacity evaluationse) Optimize lift station and system storage capacitiesf) Implement real-time control strategiesg) Model relief sewers, overflow diversions, and inverted siphons

h) Accurately simulate variable-speed pumping and logical controlsi) Simulate out-of-service or proposed sewers.

This paper aims to investigate in detail the steps involved in leveraging geospatial data to createhydraulic models of sewer systems, and also highlight the benefits that these models can offerthose responsible for stormwater management systems. This approach will be developed aroundthe technology embodied in Bentley Systems SewerGEMS, a geospatial-centric modelingsolution released at the end of 2004.

Geospatial DataCities and utilities may well have gathered geospatial information in various data formats over theyears. The commonly used formats include DXF or DWG drawings, DGN, Shapefiles,geodatabases, coverages, geometric networks, SDE datasets, Excel spreadsheets, ODBC and

OLEDB compliant databases, MS Access, MS SQL Server, Oracle Spatial, etc.. In addition to theabove data sources, geospatial technology offers the ability to obtain external data sources suchas customer billing records, digital elevation models and high quality base maps and extract thedata needed avoiding the error-prone manual data entry process.

A city or utility that commits to developing a geospatial hydraulic model must consider severaldriving factors including data quality, hardware resources, software availability, interdepartmentalcooperation, modeling/technical leadership, data development, and maintenance.
http://www.bentley.com/haestad


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To build an effective hydraulic model the Geospatial professional must work closely with themodeler during the process of creating and transforming the Geospatial data so that the modelbuilding process can work as seamlessly as possible. For example the Geospatial data maycontain more detailed information than is needed for modeling; for example every small serviceline and lateral. This information is typically not necessary for modeling applications and can beomitted to improve model run time, reduce file size and save cost, so the Geospatial professionalshould set up the data in such a way that the modeler can easily omit this unnecessaryinformation from the model.

Some good practices for creating Geospatial data for later use in a model include a) Snappingpipe ends to other element types b) Standardized element labeling conventions c) Customerservice lines in separate features classes from system pipes d) Wet wells, pumps and othersystem components as separate feature classes.

Conversely, the following are some of the possible errors in data that need attention (and may bedriven by the capabilities of the numerical solver): Missing attributes, features not properlyconnected, features digitized backwards, GIS feature type has no model counterpart, GISidentifiers incompatible with the model, GIS contains hydraulically insignificant or short pipesegments. Haestad et al (2004)

Other publications have described similar techniques on developing Geospatial information forthe water and wastewater industries, including Orne, Hammond, and Cattran (2001), Przybyla(2002), Haestad et al (2004) and Manual of Practice titled Implementing Geographic InformationSystems (WEF, 2004).

Shamsi (2002) has presented two case studies on the application of GIS technology to sewersystems. Greene, Agbenowoshi, and Loganathan (1999) discuss a program that was used toautomatically integrate GIS data a new sewer network design. New opportunities pose newchallenges for the smooth integration of the modeling process. Newer objects can be morecomplex, with more-complicated connectivity, compared to older GIS data types (points, lines,polygons). The data-modeling effort in an object world is more time consuming (Zeiler, 1999) andrequires that the hydraulic modeler pay more attention to the process at the design stage whenusing an object-relational GIS.

Papers on modeling (such as Deagle and Ancel, 2002) typically discuss the use of GIS byhydraulic models but few describe the incorporation of model information in the GIS. An exceptionto this common approach is Indianapolis Water Company (Schatzlein and Dieterlein, 2002),which has a separate section in its GIS for proposed projects.

Building a Hydraulic Model from Geospatial Data Sources.Hydraulic analysis of sewer systems requires a great deal of data on hydrology, piping systems,wastewater loading and topography. As discussed earlier, much of this information already existsin the hands of many cities and utilities. The key is to utilize this data without the need tomanually reenter it. This requires the hydraulic model to be able to communicate with a widevariety of data sources.

Automated model building tools give the user the ability to build complete modeling datasetsusing shapefiles, coverages, geodatabases, geometric networks, SDE datasets, spreadsheetsand databases (Bentley, 2005). The modeler can map the tables and fields contained within thedata source(s) to element types and attributes in the Sewer model.

For example, storm sewer pipe information may exist in a shapefile containing line features. Theshapefile may include fields containing information such as pipe label, pipe material, pipediameter, pipe levels and roughness information. These fields are all mapped to the appropriatefield in the sewer hydraulic analysis model (for example, pipe diameter in the shapefile is mappedto pipe diameter in the model) using automated model building tools. Numeric fields, like


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diameter, also require a unit of measure to be specified (i.e. does the 100 in the shapefilerepresent inches or millimeters) so that the model can perform the appropriate conversions duringanalysis. The pipe label is typically the most important field during this process, since there mustbe a common key between the different features in the source and target files and a label isoften the best choice for this common key. However, if necessary, automated model buildingtools will create a unique key/label field for this purpose.

This data mapping process can be repeated for additional data sources and model features, andthen automated model building tools are run to create the model topology. The steps taken at theoutset will impact how the rest of the process is developed, so the modeler must spend the timeto ensure that this process goes as smoothly and efficiently as possible. However, if theGeospatial data is detailed and accurate, and the data mapping complete, then automated modelbuilding tools will create a comprehensive sewer network. If not, it is still possible to construct amodel, but considerable manual data entry will be required.

Loadings.The next step in the creation of the hydraulic model is to add the loadings, which are simply theflows that enter the sewer system.

An accurate estimation of the flows entering your sewer system is one of the most important

steps towards trusting a model that truly reflects your real world sewer system. For most sewersystems, there are two overall types of loading: 1. dry weather which includes sanitary andindustrial flows and dry weather infiltration, and 2. wet weather which comprises rainfall derivedinfiltration and inflow. Purely stormwater systems should have virtually no dry weather flow whilepurely sanitary systems should have very little wet weather induced flow. However, most realsystems have some combination of both types of flow and any hydraulic analysis model must beable to deal with both.

The first step in determining loading would be to first understand the current year dry weatherflows and then add the complexities of wet weather and future conditions. Loading data can beobtained manually from customer or flow meter data or automatically using software import tools.

Automated model loading tools can take loading information from a variety of GIS based sources

such as customer meter data, system flow meter or polygons with known population or land useand assign those flows to elements. Automated model loading tools are oriented to the types ofdata available to describe dry weather flows while other methods in SewerGEMS are moreamenable to wet weather flows (Bentley, 2005). Some of the loading options include

a) Water Consumption Data Loading can be leveraged in developed countries where theflow data from each customer meter can be assigned by automatically assigning geocodedcustomer water consumption data to the nearest manhole in the sewer network, instantlyallocating consumption data to the nearest pipe and then specifying how the demand will be splitamong the bounding manholes, aggregating consumption data for individual service polygons(meter routes or drainage basins) and then assigning the aggregated loading to the associatedmanhole.

b) Flow Monitoring Data Loading where the flow data from the monitors can be assigned bydistributing the flow from each monitor equally across all elements in a specified area (polygon),usually a drainage basin or sub-basin, proportionally distributing the flow to elements in aspecified area based on the actual service area(s) of the elements involved and distributing theflow based on the population in the service area.

c) Land Use Parcel and Census Data Loading which is based on requirements, user-definedrule-of-thumb flows are developed for each type of land use or per capita. LoadBuilder candistribute the loads either equally or proportionally to the elements located within the polygonscontained in Land Use and Census Maps.


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Figure 1: Load builder technology allows the user to allocate loads based on flow monitoring, waterconsumption records, land use polygons, and other GIS sources.

For master planning, users can project future loadings quickly and accurately based on data suchas phased land use projections and population projections. This allows modelers to efficientlycreate multiple loading alternatives by intersecting any combination of future service area layerswith different land use and population forecast layers.

Wet weather flows that are caused by precipitation should be characterized based on the stormevent or by using hydrographs. In addition, flow from stormwater runoff should be computed atthe catchment elements based on different characteristics including catchment size, catchmentland use, loss method and hydrograph method, coupled with the hyetograph from the storm eventof interest.

There is no single "correct" method for converting precipitation events into sewer wet weatherloadings. Some methods such as the Green-ampt infiltration equation or the SCS runoff methodare more appropriate for pervious surfaces, while methods such as the RTK method are best formore urbanized areas. The most general method would consist of a calibrated unit hydrograph fora catchment. Storm sewer hydraulic analysis models can convert rainfall into wet weather sewerflow using any one of a wide variety of methods selected by the user. (Haestad et al. 2004)


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Sewer System Hydraulic Model Analysis.Storm Sewer system models calculate flow, velocities, depths, and hydraulic grade line insystems and much more, given loading data and network hydraulic characteristic such as invertelevations and pipe diameters. These can be used in system design and analysis of existingsystems.

Storm sewer systems can be modeled using Bentley s SewerGEMS in a stand alone interface orinside AutoCAD, ArcGIS or MicroStation environments allowing interoperability, geospatialanalysis, hydraulic and hydrologic calculations. The modeler is given the option to leverage thepower of the modeling application and the modelers favorite drafting/mapping applicationsimultaneously. Figure 2 illustrates a storm sewer thematic map with property-based symbologyand annotation, inside MicroStation.

Figure 2: SewerGEMS thematic map with property-based symbology and annotation, insideMicroStation

Storm sewer analysis models have the ability to support the wide variety of elements found in thereal world. The storm sewer structures supported range from manholes, inlets, pipe networks,channels, pumps, detention structures, control structures, and stormwater watersheds.

In addition the modeling engine supports the modeling of looped pipe networks, flow splits,overflows, and storage capacity. Storm sewer analysis models can be used to perform capacityand overflow analysis of existing systems over an extended period of, say, 24 hours.SewerGEMS has a stable implicit finite difference numerical algorithm that solves the full St.Venant equations.

Understanding Results.


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Digesting and comprehending the volume and complexity of raw numerical results from ahydraulic model can be challenging. Reporting, visualization, and thematic mapping tools areused to present the results to users in a variety of useful ways. Some of these tools includetabular results, profiles, map annotations, color coding, and graphs. Tabular results arecustomizable giving the user the option to view computed data selectively, sort and filter databased on constraints.

Profiles help visualize how selected attributes, such as hydraulic grade, energy grade, groundelevation vary along an interconnected series of pipes over time. Element annotation is used fordynamic presentation of the values of user-selected variables in the plan view. Color codingallows to perform quick diagnostics on the network by assigning colors to a range of attributevalues. Element sizing enables the modeler to change the line width (of pipes, channels etc) andelement size (of manhole, inlets etc) based on any attribute of interest (such as flow rate, velocity,diameter etc) to the modeler.

Figure 3: Hydrographs for different storm events (back image) and Storm Sewer Line profiles (frontimage to the right) create using SewerGEMS can be compared simultaneously for all time steps.

Once the model is running successfully, it is important to realize that the model is just a tool foranalysis, not the end in itself. The engineer or modeling professional should continue to spendmore time engineering after efficiently building, loading, editing, running, and understanding thestorm sewer model. In most studies, the engineer will run a large number of scenarios to analyzea wide range of alternative designs and operating strategies to optimize system performance.


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Continuing improvements include detecting and addressing system bottlenecks, optimization ofcontrol strategies, limit overflow occurrences, and more.

Summary.Advances in the application of geospatial data in sewer modeling, analysis, and design keepincreasing with each new development in geospatial technology and data availability. Modelersmay not be aware of these geospatial advancements, and CAD/GIS professionals may not beaware that such tools could be applied to hydraulic modeling. Thus, modeling and CAD/GISprofessionals must communicate regularly, constantly refining techniques to apply geospatialtechnology to storm sewer modeling. (Haestad et al, 2004)

REFERENCES

Bentley Systems Incorporated, 2005, SewerGEMS Users Manual, 2005, Haestad PressWatertown, Conn.

Deagle, G., and S. Ancel. 2002. Development and maintenance of hydraulic models. KansasCity, MO: AWWA IMTech.

Greene, R., N. Agbenowoshi, and G. F. Loganathan. 1999. GIS based approach to sewer system

design. Journal of Surveying Engineering 125, no. 1: 3657.

Orne, W., R. Hammond, and S. Cattran. 2001. Building better water models. Public Works,October.

Przybyla, J. 2002. What stops folks cold from pursuing GIS. Public Works, April.

Schatzlein, M. and J. Dieterlein. 2002. Finding Needles in a Haystack: IWCs Experience

Optimizing Integration with Hydraulic Models. Kansas City, Missouri: AWWA IMTech.

Shamsi, U. M. 2002. GIS Tools for Water, Wastewater and Stormwater Systems. Alexandria, VA:American Society of Civil Engineers Press.

Times of India, July 28 2005. After the Flood news article

Water Environment Federation. 2004. Implementing Geographical Information Systems,Alexandria, VA Water Environment Federation.

Haestad et al. 2004. Wastewater Collection System Modeling and Design, Haestad Press

Zeiler, M. 1999. Modeling Our World. Redlands, CA: ESRI Press.

Author Information:

Sharavan Govindan [email protected] M. Walski [email protected] Mankowski [email protected] Cook [email protected] Sharkey [email protected]

Bentley Systems Inc27 Siemon Company Drive - Suite 200WWatertown CT US 06795http://www.bentley.com/haestad.com
http://www.bentley.com/haestad.commailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]

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Leveraging Geospatial Data to Solve Storm Sewer Issues