Today, most water utilities in Denmark are highly digitalised, meaning that key administrative, planning and operational systems are digitised and – most importantly – the data is stored in open (non-proprietary) databases.

As of 2024, more than 80 percent of meters in Denmark are remotely read, including both drive-by and fully smart systems. This means that the data can be utilised across the water utility to increase the level of knowledge of performance.

In addition, a massive development of new communication platforms has taken place recently, and smart devices such as automated meter reading, deployed noise loggers and acoustic leak detection mean that more data is being collected than ever before. As a result, many utilities are now well placed to operate as smart water networks.

The principles of SWAN

The Smart Water Networks Forum (SWAN) has defined a five-layered model that describes best practice for any water utility seeking to transform into a smart water network, leading to improved efficiency, durability and reliability of the physical distribution network.

The top layer includes advanced data analytics that utilise historical as well as real-time data to conduct advanced reporting, forecasting and optimisation of the operations. Various algorithms (including artificial intelligence and machine learning) aid in providing input for data-driven decision-making, improving drinking water distribution and reducing water and energy consumption.

Building a smart water system

Several Danish water utilities have implemented integrated information and communication tools to support strategic rehabilitation planning of the transmission and distribution network. These tools use input from all available systems to support water utilities in executing long-term investment planning and updates on budgets, a continuous overview of rehabilitation projects and prioritisation of rehabilitation activities. In particular, they enable cost-optimised sequencing of rehabilitation efforts and provide full documentation of progress.

Using a combination of spatial data analysis, machine learning and cost optimisation enables water utilities to establish a long-term, holistic plan for their NRW interventions and improvement initiatives. The effects of these are continuously monitored and reported back to the operational management and used for prioritising the ongoing active leakage control activities in the network.

Tools for leakage monitoring and control

Using online water meters – more commonly known as smart meters – at the customer level means that the operators can monitor the water balance for each DMA with a much higher frequency and much more precisely compared to the traditional setup with manual monthly or annual readings of customer meters.

In Denmark, water utilities that have implemented smart customer metering are experiencing significant benefits, including shorter response times for leak detection and repairs, a lowered administrative workload for meter reading and invoicing, and increased customer satisfaction due to easily accessible water consumption data.

Water utilities serving areas with vulnerable pipes that are especially prone to bursts are adding permanently deployed acoustic noise loggers with automated data collection as an additional technology that allows pipe bursts to be registered, reported and localised within 24 hours.