Asset Management Strategies for Sewer Systems
Asset management is an increasing concern for wastewater utilities and municipalities. In the last 30 years, most cities have invested in sewer system expansion and treatment plant upgrade but a relatively small component has been allocated to the improvement of sewer system condition. In order to avoid the general deterioration of sewer system and the risk reversing public health, environment and increasing costs, tools are needed to develop long term cost-effective strategies.
The definition of sustainable rehabilitation and inspection strategies is limited by the lack of information about sewer system condition. Therefore, sewer deterioration models have been developed (i) to simulate the condition of non-inspected sewers and (ii) forecast the evolution of the system according to his current and past condition. Simulation results can be used by sewer operators to support the definition of cost-effective inspection and rehabilitation programs. Since the confidence in deterioration models depends highly on their ability to predict accurately future sewer condition, research is needed to assess their performance and define their relevant specifications.
The project SEMA aims
to investigate the suitability of sewer deterioration model to predict sewer condition state and
to identify the relevant specifications of sewer deterioration models and input data in respect to a successful utilisation.
Sewer deterioration models will be applied in the cities of Braunschweig and Montbéliard, in close collaboration with the engineering company 3S Consult GmbH (3SC). Model precision and sensitivity will be tested using several configurations of input data.
Considering the project results, a second project (SEMA 2) will be developed to assess the pertinence of sewer deterioration models to support the definition of inspection and rehabilitation strategies.
- Bewertung verschiedener Modellansätze zur Vorhersage des Zustands von Abwasserkanälen am Beispiel von Berlin
- Practical benchmarking of statistical and machine learning models for predicting the condition of sewer pipes in Berlin, Germany
- Sewer deterioration modeling for asset management strategies – state-of-the-art and perspectives
- Sewer deterioration modeling for asset management strategies
- Review of available technologies and methodologies for sewer condition evaluation