TU Delft agrees collaboration with IBM on smarter water

06 Oct 2010 | Network Updates

TU Delft is partnering with IBM to develop models of water systems that will support efforts in water conservation and flood prevention.

The results are expected to be relevant both to the Dutch water system and other regions with similar complex water systems, such as the Sacramento River Delta in the US, the South-North Water Transfer Project in China, and for reservoir management in the Alps.

The Dutch water system consists of an extensive network of rivers, canals, pumps, pumping stations, locks, dams and reservoirs, spread around a total length of 2,200 kilometres of waterway, transporting roughly 120 trillion litres of river and rain water each year.

By applying analytics to the vast amounts of data gathered from across this system, researchers expect to identify patterns and trends that will enable improvements in overall water management, with benefits including reduced flooding and improved water quality.

Through linking together and analysing disparate information flows, water managers will be able to gain real-time insight into the water system. For example, information from sensors in rivers and dikes can be linked to meteorological information. Advanced algorithms and analysis software will then calculate the impact of events such as extreme rainfall. This information will enable water boards, municipalities and the Directorate-General for Public Works and Water Management in the Netherlands to model the results of different interventions into the system, thereby aiding the decision-making process.  IBM’s collaboration with TU Delft builds on its portfolio of water management applications, developed since it set up its Global Centre of Excellence for Water Management in the Netherlands in 2008.

In the Netherlands, IBM is collaborating in the Flood Control 2015 programme with public and private partners to develop the next-generation operational flood management technologies to enable real-time monitoring, improved forecasting and decision support systems.

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