KWR conducts research into the drinking water distribution network with an eye to the quality and quantity of the drinking water provision. Our research themes include the building blocks of optimal asset management, water quality during distribution, and models for water use and water delivery.
Asset management of the distribution network
Our experts provide water companies with the building blocks for the optimal asset management of their distribution network. We develop knowledge about the optimal design of drinking water networks (material, diameter, valves), degradation of mains material and mains inspection. Using GIS techniques, we make predictions of the impact on mains of environmental factors, such as soil type and the presence of roads. We analyse failure data to understand the failure behaviour of mains and its causes. Based on this knowledge, we advise water companies on the maintenance and prioritisation in the replacement and renovation of distribution networks.
Water quality in the drinking water network
Between the treatment station and the client’s tap, the quality of the water can decrease because of the influence of the mains material or the stagnation of the water, for instance. We research how we can keep degradation in the distribution network to a minimum by studying the optimal composition of the drinking water, the optimal design of the distribution network (self-cleaning networks), and cleaning techniques. We have developed models to predict the temperature and brown-water risk in the distribution network, and can define where the water quality monitors can best be positioned.
Water quantity: water use and delivery
We have developed another model which we use to describe and predict drinking water use. The model gives us more insight into the real flows in the distribution network. Water companies use this knowledge for the design and maintenance of their networks, but also to track and remedy water main failures. Besides differences in water use, there are also anomalies in water delivery, which the water companies would obviously like explained. Our experts have developed a model with which we can identify these anomalies, resulting for instance from water losses.