Credit: EID

With geospatial time series management, El Dorado (Calif.) Irrigation District information support technician III Timothy Hance, left, and Guy Barritt, GIS/drafting/graphics unit supervisor, could forecast and model trends in drinking water supplies over their entire watershed.

Credit: EID

For an agency with multiple responsibilities, such as managing drinking water supplies and providing hydro-electric power generation and recreation functions, GTSM could help manage demands and temporarily shift resources to hot spots, such as EID's 21 MW powerhouse.

Geographic information systems (GIS) and supervisory control and data acquisition (SCADA) are often part of an agency's standard operating equipment. When the technologies were first introduced, however, many viewed them as specialty products.

GIS offered accurate maps in rich detail, but how often would such an elaborate map be needed? SCADA removed the human error element from collecting operating data, but what would an agency do with all that data except store it? How would these applications be of practical use, day to day?

Today, GIS and SCADA have been so thoroughly built in to functions from environmental and construction permitting to billing and customer service that public works managers may not remember how their agencies functioned without them. A new technology, geospatial time series management (GTSM), is at the same stage as GIS was in the 1980s and SCADAwas in the 1990s.

In simple terms, GTSM transforms data points collected by GIS and SCADA into a predictive tool by relating the data for a specific location to changes over time. Anything that moves or changes through time—rainfall, reservoir levels, construction site runoff, power demands, and numerous other parameters—can be considered using GTSM.

The growing numbers of engineers and information technology professionals introduced to GTSM are impressed. They view it as the next logical progression from GIS and SCADA. But is GTSM more than another “cool” technology? If so, how will it benefit agencies in a profound way, every day?

“It is becoming clear that the walls between control systems and GIS are finally coming down,” said David Henry, P.E., Metropolitan Water District of Southern California's program manager for water system automation. “Products that integrate the operational and business data of SCADA systems with the geospatial and graphical relevance of GIS enable utilities to better respond to emergency situations, operate more efficiently on a day-to-day basis, and better visualize long-term needs.”


Public works agencies have made significant investments in “must-have” tools and applications. As-builts, maps, and service area grids have been digitized and made accessible using GIS. SCADA is the gold standard for collecting real-time operating data for pump stations and other facilities, and for operations control.

Yet, in spite of their sophistication, neither GIS nor SCADA is a predictive tool. GIS is only a spatial frame of reference. SCADAdata offers only a snapshot in time, a report of what has already happened. GTSM offers the next step by integrating spatial data collected by GIS and real-time data collected by SCADA to frame data points to a particular time and space. By generating geospatial time series data, GTSM transforms data into a decision-making tool.

Why is geospatial time series data so important? Human beings inherently relate space and time to make a variety of decisions. For example, a police department reallocating officers to better fight crime needs to know more than where crimes occur. The department must also know when the most crimes occur in those locations. With both space and time information, officers can be assigned to appropriate places at the most cost-effective times.


In the same way, agencies need to relate data to both time and space. For example, managing distribution from a particular drinking water reservoir requires more than a map of the reservoir location and a stack of hour-by-hour water level readings. A compilation of reservoir levels over a period of time to represent wet, dry, and average rainfall years, however, provides the right mix of information. Using this geospatial time series, an agency can decide how much water to distribute from the reservoir.