Water Management 2019-09-18T08:31:34+00:00

Optimizing water transport with SIWA leakage detection systems

The challenge

Optimum performance and cost-efficiency of water trans-port and distribution systems crucially depend on the early and reliable detection of leaks and their immediate localization.

The time elapsed until the detection of a leak is critical for the prevention of potential subsequent damages such as undercutting below buildings or roads. Leaks do not only lead to the loss of valuable drinking water that has been purified at high cost, but may also result in substantial economic losses.

The solution

Siemens offers the following modules for intelligent leakage detection:

  • SIWA Leak Control for complex water distribution networks
  • SIWA Leak for water transport pipelines

With SIWA Leak, large, medium and even small leaks in water pipes are reliably detected. As an extension for existing control and automation systems, SIWA Leak provides the operators with gapless information on the cur-rent state of the water pipes, building a detailed data basis for targeted decisions on the right measures to take in case of a leak

The efficiency of the municipal water distribution infra-structure, too, may be compromised by an increasing number of small and large leaks caused by corrosion or geological shifts. Without an efficient detection system, such leaks may go unnoticed for a long time. Permanent monitoring, in contrast, ensures the early detection of any leak, reducing leaking time and helping preserve the cost-efficiency of the water supply system.

SIWA Leak Control enables the plant operator to detect and locate new and existing leaks and initiate the appropriate intervention measures depending on importance and risk potential: either immediate repair or inclusion in the ongoing pipeline maintenance plan.

SIWA Leak Control is based on a three-step approach: In a first step, flow measurement is implemented for auto-mated monitoring, measuring water inflow and outflow successively in exactly defined virtual segments (DMAs) and in water reservoirs. The measured values are transmitted to the corresponding SW module of SIWA Leak Control and analyzed using statistical and model-based methods.

In a second step, these data serve as the basis for narrowing down the leak location by temporarily installing acoustic sensors in the segment in question or by opening and closing slide gates to modify the operational conditions. The third and last step uses pinpointing and a correlator to locate the leak to the nearest meter.

The benefits of SIWA Leak and SIWA LeakControl

SIWA Leak and SIWA Leak Control support the operators of water transport systems and water distribution net-works in ensuring permanent monitoring for cutting leakage times, reducing the risk of secondary damages caused by the undercutting of foundations etc.,minimizing water losses,maximizing efficiency and reducing costs in plant operation and maintenance.

Measurement Data Collection

Measurement, reconciliation and analysis of water volumes:

  1. Supplied to pumping station zone, water supply sector
  2. Consumed by utility customers
  3. Transferred through the zone to other zones/sectors
  4. Used for utility technological needs
  5. Calculated as water losses

Analysis of the data from pressure sensors, installed at the water network and consumer inlets, including:

  1. Control of the water supply quality
  2. Detection of anomalies in measurements
  3. Probable location of leak/water loss occurrence

Extended web-based User Interface

Detection of suspicious behavior

  1. Unauthorized consumption e.g. consumption without contract or consumption via firefighting or reserve lines
  2. Comparison of the collected data with statistical values and data validation

Statistics and Analysis

Quantitative and qualitative results related to objects, service delivery points and accounts

Advanced Metering Infrastructure (AMI) related information:

  1. Amount of meters in sector, zone or within particular object
  2. Correctness of AMI data
  3. Various statistical KPI’s
  4. Data collection and data transmission failures
  5. Measurements quality analysis

Support of meter history tracking including procurement, installation, replacement etc.

Meter events processing, in particular magnet, reverse rotation, cover-off, dial rollover etc.

  1. Analysis of network topology, historical consumption data, definition of water supply sectors and metering locations
  1. Formalization of goals and objectives. Technical audit of IT landscape, solution architecture design and definition of integration strategy.


  1. Required “tuning” of selected IT systems and introduction of new business processes related to technological accounting and management of water resources at Utility


  1. Provision of unique software, based on machine learning algorithms for condition monitoring and decision support for operation of water supply system


  1. Testing the system for pilot district, and spreading the suggested approach to other parts of the city in case of successful implementation

Stage 1.

Water supply sectors and key metering points.

Pilot zone is “splitted” into smaller sectors, hydrolically isolated with valves and flowmeters from rest of the network.

To estimate overall consumption and network conditions within the sectors limited amount of consumers should be equipped with smart meters and pressure sensors

Such key metering points are optimally selected based on mathematical analysis of water consumption and network topology.

The meter data from the key metering points is processed by data analytical algorithms. As a result this information becomes sufficient to provide diagnostics and monitoring of the whole water supply network in the zone.

Stage 1.

Key metering points. Selection approach

Stage 2.

Overall solution layout and goals

Solution …
– 3-layers architecture with open communication
– supporting variety of metering devices
– validation of master and metered data
– integration with utility IT systems a

– setup and support of utility business processes

… aimed to

– detect and localize losses

– forecast the consumption
– control the metering infrastructure
– increase the transparency of processes
– support decision and optimize the planning

drive effectively Utility Business.

Stage 2.

High level solution architecture and integration

Stage 3.

Automation of business processes for automation of configuration and measured data collection

Stage 3.

Business process example: installation of new communication module to metering device

Stage 4.

Data analytics as an approach to overcome challenges in water utility metering

Stage 4.

Data analytics and decision support

Stage 4.

Data analytics and decision support. Water Balance

Stage 4.

Data analytics and decision support. Leak detection.

Stage 4.

Visualization and decision support

Stage 4.

Interactive dashboards and data access

Stage 5.

Water utility of St. Petersburg “Vodokanal”