Stretch Water System Dollars With Data Analysis

April 24, 2020

Using data to efficiently manage water distribution systems

About the author:

Barbara Leigh Shields is a writer for Esri. Shields can be reached at [email protected].


While growing cities struggle with water infrastructure built in the last century, they must plan new projects to accommodate growing populations. 

Enhancing Efficiency

Data is critical for improving efficiency. Information technologies process data and create water system intelligence that drive sound decisions. Utilities that diligently digitize their data and tag it with location can transform it into operational intelligence. If they do not, they lose revenue dollars and miss opportunities to reduce costs. 

Location intelligence technology uses digitized data to build smart maps that show entire pipeline networks. As networks change, utilities keep these maps current by editing features and adding new asset data to the database. Mapping valve data, for example, is as simple as importing a spreadsheet of valve information into a geospatial system. Mapping assets is fundamental to intelligent operations management. 

Paper-Free in Pennsylvania

Crews working at one utility authority in Pennsylvania, annually flush 1,500 hydrants. The authority dropped its paper-based workflow, in which data was used just once, and replaced it with a digital workflow. Crews now use mobile devices to capture data and instantly stream it from the field to the office. The authority’s geographic information system (GIS) software processes the data and shows task status on an operation dashboard map so that managers have a real-time view of the program’s progress. 

Using geospatial analytic tools, managers combine flushing data with water main data and identify areas that should be prioritized for leak investigation. By using location intelligence, this Pennsylvania authority annually saves $3,500 in labor costs and around $500 in vehicle and equipment expenses on just this one project. 

GIS software, which maps asset locations, also maps asset performance. It ingests data streaming from sensors and creates live maps showing what is happening along the pipeline network and where. The utility monitors the system in real-time by using operation dashboards. 

If GIS detects that a threshold—such as water pressure—is too high or too low, it sends a notification. The operation dashboard maps an event’s location and details. Operation managers then decide whether to dispatch a repair crew. In the meantime, location information streams from repair crews’ onboard GPS to GIS. Because the platform manages data streaming from different sources, GIS shows both the incident and repair crews’ locations on the same real-time map. The dispatch office sees nearby field crews and sends a work order to the appropriate unit.   

Dashboards accesses data that meets the specific needs of whoever uses them. Engineering dashboards monitor sensor data, such as pipe pressure and other operational measurements. Executives gain intelligence from dashboards that track business performance indicators such as service completion rates and fleet overtime costs. Customer service operators also use them to track call-ins. All utility data has value for someone, and, if stored in a connected GIS database, someone else can get additional insight from it. 

Monitoring Meters in Alabama

An Alabama water company could not accurately bill customers for their water usage because some meters were nonoperational. Each month, employees sifted through 14,000 meter readings to find dead meters. To improve efficiency, staff imported billing department data, work order data, and SCADA data into GIS. It then used geospatial analytic tools to estimate normal consumption rates by area and look for billing data anomalies that fell below an acceptable water usage range. Based on parameters set by analysts, the system identified hundreds of dead meters, which, in turn, resulted in a monthly revenue gain of $25,000. 

Augmenting utility data with data from outside resources adds greater context to water analysis. NOAA climate predictions help utilities prepare for a new normal in climate trends. Layering the local planning department’s project data onto the water asset map highlights where new development will need water services and increase demand on the water supply. The U.S. Census’ population clusters also indicate where demand will likely increase or decrease. Layering USGS soil types data on a pipeline network map reveals where corrosive soil might be distressing pipes. 

These types of data analysis help companies proactively mitigate problems and predict change. By understanding operational and business intelligence derived from data, utilities make water-wise decisions and can better manage costs. 

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