How would water management ‘Software for Domain Experts’ work?

Here are some ideas from an IBM 2014 White Paper “Employing integrated operations for water resources management“.

Water management is a vast policy area, including managing (drinking) water quality, avoiding floods, managing underlying water infrastructure, managing overall water supply and demand, and managing the workforce which does all of the work. There may be emergency response required if there is any immediate hazard.

In particular the water supply needs to be managed – should it be diverted through hydroelectric schemes, used for agricultural irrigation, or made available for domestic or industrial consumption?

All of these systems are complex and interdependent, with many different vendors, regulators and research organisations involved, and many assets owned by different entities. There may be software systems and data, for example from sensors, going into differnet systems.

There may be large government investments required in reservoirs, tunnels and dams.

As a starting point, experts need to have a ‘single operating picture’ for the water system – showing the current risk of floods, drought, and water quality, shared between whoever needs it.

Using this ‘single operating picture’ data, experts should be able to work together with others, monitor what is happening, do modelling and simulation, and optimise operation of assets, such as pumps.

In one example, the Netherlands National Water Authority “Rijkswaterstaat” implemented a “digital delta” program, aiming to integrate data from a range of different sources, make forecasting models, do analytics and build visualisations, all aimed to help experts anticipate problems in real time.

In another example, the City of Bangalore Water Supply and Sewarage Board (BWSSB) worked with IBM do build an ‘operational dashboard’ as a command centre for monitoring, administering and managing water supply networks. It installed instrumentation in the distribution network, so it could see how water was flowing through the systems. By using ‘big data’ analytics, it could be better manage the water distribution, including modifying control valve settings remotely.

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