Sophisticated Data Models to understand water consumptionShare Case Study:
For Scottish Water, Acorn is the foundation of a sophisticated model that determines expected water usage in locations across Scotland.
Martin Walton, Asset Planner at Scottish Water explains:
“There are hardly any domestic water meters in Scotland. So, we have had to find other ways to stratify our customer base. Using Acorn data, we have built and refined models over the years that give us a clear view of how water is being used.”
The insight Acorn provides helps operations and engineering teams to prioritise their activities and pinpoint key areas for investigation.
Scott Young, Leakage Delivery Team Leader at Scottish Water, describes the approach:
“In terms of water supply, Scotland is divided into over 3,000 areas, each with a district meter. We inform supply / demand analysis within these areas using our Acorn model. We compare district meter flows to those within the Acorn model to see whether actual water usage is similar to the projected household demand for that area.
When there’s a difference, we can investigate whether this is because of unrecorded usage, network anomalies or leakage.”
Martin Walton adds, “The modelled per household consumption dataset has proved to be a very accurate predictor of consumption for the domestic properties we supply.”
Acorn provides Scottish Water with an accurate usage prediction model based on data evidence
Scott Young says, “With the Acorn data, we’ve been able to break down demand by area to understand the opportunity for leakage reduction.
Using big data in the digital space is quite a radical change from the traditional mainstream approach to leakage detection. Now, we can identify areas of concern with a high degree of accuracy, even in areas with plastic pipes, where traditional soundings to find leakage are less effective.
“When I send a team out on the ground to locate and fix a problem identified via the Acorn data model, we have a very high degree of confidence that we’ll find it where we predicted. That means we can detect and stop leaks more quickly and efficiently.”
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