Improving the benefits of sewer condition deterioration modelling through information content analysis.

As urban sewer infrastructures age, it becomes increasingly important to make effective decisions to maintain the structural condition of the sewers at an acceptable level. To support the decision-making process, the utility manager can apply sewer deterioration models. However, the quality of the decision support from such models is dependent on the accuracy and reliability of the predictions, and previous research has shown that sewer deterioration predictions can be unreliable. In this paper it is shown, by numerical experiment and analysis of information content, how the accuracy of sewer deterioration models is inhibited by data heterogeneity. The data heterogeneity arises when the condition class is used as a response variable, because the condition class is an aggregation of different failure modes, and contains information that does not describe structural deterioration. Based on these findings, the paper suggests changes to be implemented in the condition classification standard, which can mitigate heterogeneity and improve prediction reliability. The suggestions for improvement include distinguishing between structural and functional defect codes, defining new condition metrics better suited for deterioration modelling, and registration of detailed defect codes to allow distinction of different failure mechanisms.

The hydraulic capacity of deteriorating sewer systems.

Sewer and wastewater systems suffer from insufficient capacity, construction flaws and pipe deterioration. Consequences are structural failures, local floods, surface erosion and pollution of receiving waters bodies. European cities spend in the order of five billion Euro per year for wastewater network rehabilitation. This amount is estimated to increase due to network ageing. The project CARE-S (Computer Aided RE-habilitation of Sewer Networks) deals with sewer and storm water networks. The final project goal is to develop integrated software, which provides the most cost-efficient system of maintenance, repair and rehabilitation of sewer networks. Decisions on investments in rehabilitation often have to be made with uncertain information about the structural condition and the hydraulic performance of a sewer system. Because of this, decision-making involves considerable risks. This paper presents the results of research focused on the study of hydraulic effects caused by failures due to temporal decline of sewer systems. Hydraulic simulations are usually carried out by running commercial models that apply, as input, default values of parameters that strongly influence results. Using CCTV inspections information as dataset to catalogue principal types of failures affecting pipes, a 3D model was used to evaluate their hydraulic consequences. The translation of failures effects in parameters values producing the same hydraulic conditions caused by failures was carried out through the comparison of laboratory experiences and 3D simulations results. Those parameters could be the input of 1D commercial models instead of the default values commonly inserted.