Tracking Hotspots: Putting Sewer Cleaning on the Map
The Town of Mooresville, NC, developed a system using ESRI’s ArcGIS software to track distressed areas of the sewer system that needed frequent cleaning, giving the sewer maintenance department specific areas to target for improvement or repair.
By Alan Saine
In 2010, the Town of Mooresville, NC, began experiencing a rise in the number of sanitary overflows and sewer stoppages. The reason for the problem was evident: the town has over 6,000 manholes and 250 miles of sanitary-sewer gravity-main lines, but only 30 percent of that infrastructure was constructed in the last 20 years. The town's population has tripled in that same time period, putting more strain on the aging sanitary sewer system.
|The ESRI app on the iOS device displays the sewer cleaning data and the MHIDs, therefore the user knows if that line has been cleaned recently.|
Mooresville has permit requirements regulated by the North Carolina Department of Environment and Natural Resources Division of Water Quality. One of the requirements is that the town assess all cleaning needs, and develop and implement a program appropriately cleaning all sewer lines. The Mooresville Water Sewer Maintenance Department (WSMD) manages this requirement on a day-to-day basis and recently requested the assistance of the town's Engineering Department to help determine all the distressed spots, or "hotspots," in the system to more strategically and effectively clean and maintain the system.
Fortunately, the Engineering Department had recently finished a year-long project that employed ESRI's ArcGIS software to locate, map and input all the features of the town's sanitary sewer system.
"Economic growth kept our staff very busy for years with installing all of the water and sewer taps. Since the growth slowed due to the recession, we had to move from a reactive approach to being proactive. In the past, crews would alternate cleaning sewer lines in whatever area they wanted to and areas were being left out. By restructuring crews, we dedicated a crew to do all of the line cleaning and with this continuity we were able to grasp the needs of our wastewater collection system," said Jamie Johnson Water/Sewer Maintenance Field Supervisor.
To assist the WSMD in identifying distressed spots in the system, the Engineering Department needed to pinpoint these locations on a map and assign dates for when the sewer features (manholes, sewer main, etc.) were cleaned. The WSMD had access to monthly data from August 2009 to January 2011 showing where and when sewer cleaning had occurred. That data was stored in Microsoft Excel spreadsheets. Each spreadsheet contained the cleaning data for that month as well as a unique identifier, Manhole ID (MHID), to capture the location.
Once the spreadsheets were reviewed, the engineering staff decided to use Python scripting to process the batch of Excel format cleaning data and generate a comprehensive dataset. Python is a free and open source software programming system (www.python.org).
The first step in the process was to create the cleaning data. This was done by creating a join between the MHID in the Excel file and the MHID in the town's ArcGIS SDE database. A copy of cleaned manholes was created and all intersecting sewer lines to cleaned manholes were selected and copied. Simple reports were also created using the ArcPy function in Python.
As an example of this, the ArcGIS Analyst Frequency Tool was used to calculate the number of sewer mains and their length that were cleaned that month. Once the cleaned sewer mains were created, the process was repeated for the next month's data. After the monthly cleaned sewer mains data was created, the data was merged together into one layer and the frequency of how often that line has been cleaned was calculated and coded using a red-yellow-green scheme. Hotspots, or areas that had been cleaned seven or more times, were displayed as red so it would be evident where there were issues.
Locating the Cleaning Hotspots
Through the Python automation, it was easy to use ArcMap to display all the cleaning data. The ability to map where the sewer cleaning was occurring and how often it occurred yielded some interesting results. There were over a dozen separate areas where the sewer mains had been cleaned 7-12 times in an 18 month span. This information became a catalyst for improved interdepartmental communication between the WSMD and the Town of Mooresville Fat Oils Grease (FOG) Department.
"Our sewer cleaning map has helped us to identify those areas that require more frequent inspections and increased pumping/cleaning frequencies for food service establishments,'' said Jamie Levis, FOG Compliance Officer. "The use of ArcGIS has helped the FOG staff identify and remedy problem grease interceptors on multiple occasions. With the use of this tool, what used to take weeks now takes minutes to look up and identify."
Fixing the Hotspots
Mapping the hotspots gave the WSMD and FOG department specific areas to target and improve. Several methods were used to investigate these areas, such as closed-circuit television (CCTV) of the sewer mains and inspecting all the oil/water separators in the vicinity of the sewer cleaning hotspots. Several problems were fixed by simple root control treatments and locating grease violations by local restaurants.
Prior to this project being implemented in 2010, the WSMD did not know where the "hotspots" were and did not have a way to track areas that were being repeatedly cleaned. In 2010, the town cleaned 51 miles of sewer mains. Of those cleaned sewer mains, 58% had already been cleaned earlier that year. In 2011, after the project, the town cleaned 144 miles of sewer mains and only 32% of them were repeats. By having the ability to identify hotspots and correct issues, the town was able to clean almost three times more and cut the repeat trips by 26%.
"Since our productivity has increased, we have noticed a decrease in main-line stoppages and after-hour callbacks resulting in cost reductions, including less overtime pay for employees. This has also resulted in less service interruptions to the customer and less of an impact on surface waters caused from overflows," Johnson said.
Ryan Rase, Deputy Town Manger, also praised the results of the project: "The WSMD has not been immune to the downturn in the economy, we are constantly being asked to do more with less. Through the use of technology and teamwork we were able to provide a tangible example of how the WSMD has been able to become more efficient."
Next Steps - Going mobile
Today the town continues to map the sewer cleaning. Using the ESRI ArcGIS app, workers can now use iPads to log cleaning data directly into the system from the field. The sewer cleaning crew can instantly view where the cleaning truck has been in the past two years and be strategic in cleaning by maximizing the route of the cleaning crew and migrating to areas that need attention. Additionally, they can easily identify hotspots that show up red on the map and communicate where customer intervention may be needed.
This project has created a proactive approach to maintaining the town sewer system and has enhanced interdepartmental communication.
"This project has ended up being a model to the entire Public Services Division of how through the use of technology both time and money can be saved. The WSMD employees have recognized this and now are bringing ideas to Engineering so they can be implemented in such areas as valve exercising, CCTV, and inflow and infiltration repairs," Rase said. "We look back now and wonder how we ever survived without it."
About the Author: Alan Saine is a Civil Engineer and Engineering Intern at the Town of Mooresville in North Carolina. He is a graduate of the University of North Carolina at Charlotte and is currently pursuing his Masters in Geospatial Information Science and Technology at North Carolina State University. In Mooresville, Saine recently finished implementing an enterprise GIS system in the Public Services Division. Saine may be contacted via email at email@example.com.