project

Robustness of the drinking water infrastructure

Expert(s):
Claudia Agudelo-Vera PhD MSc, Mirjam Blokker PhD

  • Start date
    01 Jan 2013
  • End date
    31 Dec 2013
  • Principal
    Waternet en WML
  • collaborating partners
    Waternet en WML

Drinking water consumption and the functionality of the drinking water infrastructure are subject to the influence of external developments, such as new sanitation concepts or decreased population levels. These factors can influence both the drinking water demand (quantity) and water quality. How drinking water demand will evolve over the next 25 years is very unclear. This is why water companies require tools to determine how robust their current systems are under changing circumstances.

The objective of this project is to study the robustness of today’s drinking water infrastructure under changing drinking water demand.

Stress test with 12 possible future scenarios

In this study the robustness of the network in two pilot areas (at WML and Waternet) was tested to determine how network performance changes under extreme stress. In a stress test that takes into account a wide variation of future water demand, SIMDEUM was used to simulate short time-interval patterns for 12 possible future scenarios, ranging from eco-sanitation to more luxurious forms of water consumption, to sharply higher water loss. Then, five indicators were used to quantify and compare the outcomes of the scenarios: 1) water demand, 2) peak demand, 3) head loss, 4) residence time and 5) maximum velocity (self-cleaning capability).

Stress test methode voor toekomstbestendigheid analyse van netwerken

Stress test for the analysis of network robustness

Robust drinking water mains

The WML and Waternet pilot areas were sufficiently robust under all the scenarios: the outcome of the scenarios – more significant head loss and residence times – can be dealt with through operational management measures. The stress test is a useful means of analysing the functionality of the network under changing water demand.

Water companies that want to test the robustness of their own networks or of a new design – whether for a new area or one requiring a new network – can themselves apply the method developed. It is sufficient to calculate four extreme scenarios, with preferably seven patterns and a time interval of one minute. These consumption patterns can be easily generated with the Simdeum Pattern Generator (SPG). By monitoring, the water companies can anticipate future water consumption, and quantify the implications for water abstraction and treatment.