Cause and effect oriented sewer degradation evaluation to support scheduled inspection planning.

Managing the subsurface urban infrastructure, while facing limited budgets, is one of the main challenges wastewater utilities currently face. In this context targeted planning of inspection and maintenance measures plays a crucial role. This paper introduces a cause and effect oriented sewer degradation evaluation approach to support decisions on inspection frequencies and priorities. Therefore, the application of logistic regression models, to predict the probability of failure categories as an alternative to the prediction of sewer condition classes, was introduced. We assume that analysing the negative effects resulting from different failure categories in extension to a condition class-based planning approach offers new possibilities for targeted inspection planning. In addition, a cross validation process was described to allow for a more accurate prediction of sewer degradation. The described approach was applied to an Austrian sewer system. The results show that the failure category-based regression models perform better than the conventional condition class-oriented models. The results of the failure category predictions are presented with respect to negative effects the failure may have on the hydraulic performance of the system. Finally, suggestions are given for how this performance-oriented sewer section evaluation can support scheduled inspection planning.

The HSG procedure for modelling integrated urban wastewater systems.

Whilst the importance of integrated modelling of urban wastewater systems is ever increasing, there is still no concise procedure regarding how to carry out such modelling studies. After briefly discussing some earlier approaches, the guideline for integrated modelling developed by the Central European Simulation Research Group (HSG - Hochschulgruppe) is presented. This contribution suggests a six-step standardised procedure to integrated modelling. This commences with an analysis of the system and definition of objectives and criteria, covers selection of modelling approaches, analysis of data availability, calibration and validation and also includes the steps of scenario analysis and reporting. Recent research findings as well as experience gained from several application projects from Central Europe have been integrated in this guideline.

Basin-wide integrated modelling via OpenMI considering multiple urban catchments.

Integrated modelling is currently receiving a lot of attention in the field of urban hydrology. This paper describes a method for carrying out integrated modelling of sewer systems and rivers, where the constituent models are linked to each other using the European OpenMI interface. This has the advantage that, once the necessary software extensions have been carried out, the data sets describing the subsystems can be used as they are without any need for adaptation.

Pollution load modelling in sewer systems: an approach of combining long term online sensor data with multi-objective auto-calibration schemes.

Pollutant load modelling for sewer systems is state-of-the-art, especially for the estimation of discharged pollutant loads and development of sewer management strategies. However, conventionally obtained calibration data sets are often not exhaustive and have significant drawbacks. In the Graz West catchment area (Graz, Austria), continuous high-resolution long-term online measurements for discharge and pollutant concentration have been carried out since 2002.In this paper, the application of single- and multi-objective auto-calibration schemes based on evolution strategies for a deterministic hydrological pollutant load model will be discussed. Three approaches for pollutant load modelling are examined and compared: using a constant storm weather concentration and two surface accumulation-wash-off approaches with basic respectively extended wash-off equations. It is shown that the applied auto-calibration method leads to very satisfying results for both the calibration and the validation data set, and also for the dry and the storm weather runoff. Results from multi-objective calibration show better robustness in validation events than single-objective calibration. The build-up wash-off approach using the basic wash-off equation gives the best correlations between measured data and simulation results.

Sewer modelling based on highly distributed calibration data sets and multi-objective auto-calibration schemes.

Pollutant load modelling for sewer systems is state-of-the-art, especially for the estimation of discharged pollutant loads and development of sewer management strategies. However, conventionally obtained calibration data sets are often not exhaustive and have significant drawbacks. In the Graz West catchment area (Graz, Austria), continuous high-resolution long-term online measurements for discharge and pollutant concentration have been carried out since 2002. In this paper, the application of single- and multi-objective auto-calibration schemes based on evolution strategies for a deterministic hydrological pollutant load model will be discussed. Three approaches for pollutant load modelling are examined and compared: using a constant storm weather concentration and two build-up wash-off approaches with basic respectively extended wash-off equations. It is shown that the applied auto-calibration method leads to very satisfying results for both the calibration and the validation data set, and also for the dry and the storm weather runoff. However, until now, convective storms have not been convincingly represented. The build-up wash-off approach using the basic wash-off equation shows the best correlations between measured data and simulation results. As one of the chosen objectives for the multi-objective optimisation reacted highly sensitively to measurement errors, additional improvements can be expected after refining the criteria used in this algorithm.