Brown water accounts for a significant proportion of reports about water quality that Dutch drinking water companies receive from customers. To tackle the phenomenon, it is important to have an understanding of the movement and accumulation of particles in the distribution network. The Aquarellus tool was developed in recent years for this purpose: it can predict drinking water contamination on the basis of the settlement of particles in the distribution network. But there are several drawbacks to the current version of the tool. Accurate calculations are too time-consuming and calculations can be made only for networks with a limited length (~10 km). There is also a wish to make Aquarellus more user-friendly. This project aims to deliver the desired improvements and make the tool applicable for operational purposes.
A range of technical alterations are needed if the tool is to be used in distribution networks of the relevant size. Correct model calculations depend on an understanding of the properties of particles in mains water, such as fall velocity, particle size, bed load velocity and mobility limits. Previous projects have looked at what type of laboratory experiments can be used to determine these properties. In addition, field measurements of turbidity are needed to validate the model results.
Our first step will be to improve the technical performance of the tool so that it can be used for actual distribution areas. That involves working towards two different versions.
- The ‘laptop version’ can be used to calculate sedimentation scenarios with a limited size (up to a minimum of 200 km) and with a resolution that the user can lower to make calculations faster.
- The ‘high-performance version’ is designed to make calculations for larger areas on a computational server with maximum accuracy.
If the tool performs adequately, we will use it to determine particle properties in a laboratory array (in other words, the input parameters for Aquarellus). Here, we work with sluicing samples with the aim of establishing as complete and realistic a picture as possible of the particle properties and how these relate to the transport properties.
Preventing brown-water incidents
The ongoing development of the Aquarellus tool will provide us with a better picture of the accuracy of the predicted sedimentation patterns. This will allow network managers to make improvements in various respects in order to prevent brown-water incidents. For example, they can set up cleaning plans and determine monitoring locations in the distribution network more effectively to study sediment formation.
In the long term, Aquarellus can be used in combination with the Gondwana optimisation platform developed by KWR. This will open up new opportunities for optimising network designs with a view to reducing the risk of brown water to a minimum. This approach will also make it possible to identify measurement and sensor locations for the effective monitoring of sediments in pipeline networks.