Stefan Kroll

Cost-efficiency of RTC for CSO impact mitigation

In spite of considerable uncertainty reported on the impact of Combined Sewer Overflows (CSO), it is generally acknowledged to not be negligible. Not surprisingly CSO impact is considered – although indirectly – in driving European legislations regarding the wastewater pollution and treatment. Still, when looking at impact reduction, policy makers tend to resort rather to static solutions such as disconnection or the building of storage tanks. On the other hand they often seem to be put off by dynamic measures such as Real Time Control (RTC) of sewage systems because of its perceived complexity. This paper describes a cost-benefit analysis of several static and dynamic solutions to mitigate CSO impact, based on the case-study of the Kessel-Lo catchment in Flanders/Belgium. RTC turned out to be not only the most cost efficient measure for CSO impact mitigation but also the solution offering the most flexibility for further system upgrade.

Modelling real-time control of WWTP influent flow under data scarcity

In order to comply with effluent standards, wastewater operators need to avoid hydraulic overloading of the wastewater treatment plant (WWTP), as this can result in the washout of activated sludge from secondary settling tanks. Hydraulic overloading can occur in a systematic way, for instance when sewer network connections are extended without increasing the WWTPs capacity accordingly. This study demonstrates the use of rule-based real-time control (RTC) to reduce the load to the WWTP while restricting the overall overflow volume of the sewer system to a minimum. Further, it shows the added value of RTC despite the limited availability of monitoring data and information on the catchment through a parsimonious simulation approach, using relocation of spatial system boundaries and creating required input data through reverse modelling. Focus was hereby on the accurate modelling of pump hydraulics and control. Finally, two different methods of global sensitivity analysis were employed to verify the influence of parameters of both the model and the implemented control algorithm. Both methods show the importance of good knowledge of the system properties, but that monitoring errors play a minor role.

Global sensitivity analysis of an in-sewer process model for the study of sulfide-induced corrosion of concrete.

The presence of high concentrations of hydrogen sulfide in the sewer system can result in corrosion of the concrete sewer pipes. The formation and fate of hydrogen sulfide in the sewer system is governed by a complex system of biological, chemical and physical processes. Therefore, mechanistic models have been developed to describe the underlying processes. In this work, global sensitivity analysis was applied to an in-sewer process model (aqua3S) to determine the most important model input factors with regard to sulfide formation in rising mains and the concrete corrosion rate downstream of a rising main. The results of the sensitivity analysis revealed the most influential model parameters, but also the importance of the characteristics of the organic matter, the alkalinity of the concrete and the movement of the sewer gas phase.

Possibilities of sewer model simplifications

With increased computer performance and data-processing functionalities, there has been a tendency in the last few years to apply detailed hydrodynamic sewer modelling for long-term simulations, with long time series of rainfall. Although this is now fairly realistic for small networks, there is still a clear limit as to what can be done in the case of running bigger models for a long time, which need a lot more computational effort. Therefore, the idea has grown to investigate the possibilities of hybrid sewer modelling, a combination of conceptual and mechanistic modelling approaches to combine the advantages of both models, the speed of conceptual models and the accuracy of mechanistic models. Suggestions for hybrid model simplifications are presented in this paper within their application for two case studies.

Semi-automated buildup and calibration of conceptual sewer models

Building conceptual sewer models can be a time-consuming task, especially for large or complex models or models that require input data that might be difficult/tedious to obtain manually.This paper presents a semi-automated procedure for the buildup and calibration of one conceptual model that requires detailed input data such as throttle dimensions, pump curves or water level-storage relations. The procedure uses a hydrodynamic model as basis for sewer network data to create the model layout. A standardised series of composite rainfall events is applied to the hydrodynamic model in order to obtain the necessary reference data for the automated calibration of the conceptual model.Both model buildup and calibration are illustrated by means of a case study. Comparison of results of the hydrodynamic and conceptual model for a 1 year long-term series shows that the automated buildup and calibration can lead to an accurate conceptual model in short time. An automated buildup and calibration routine for conceptual sewer models is proposed.Hydrodynamic models are used as a basis for the model buildup.The routine can handle complex data such as required for modelling of backwater at throttle structures.The automatically built and calibrated model delivers highly accurate results.

Modelling the potential for multi-location in-sewer heat recovery at a city scale under different seasonal scenarios

A computational network heat transfer model was utilised to model the potential of heat energy recovery at multiple locations from a city scale combined sewer network. The uniqueness of this network model lies in its whole system validation and implementation for seasonal scenarios in a large sewer network. The network model was developed, on the basis of a previous single pipe heat transfer model, to make it suitable for application in large sewer networks and its performance was validated in this study by predicting the wastewater temperature variation across the network. Since heat energy recovery in sewers may impact negatively on wastewater treatment processes, the viability of large scale heat recovery was assessed by examining the distribution of the wastewater temperatures throughout a 3000 pipe network, serving a population equivalent of 79500, and at the wastewater treatment plant inlet. Three scenarios; winter, spring and summer were modelled to reflect seasonal variations. The model was run on an hourly basis during dry weather. The modelling results indicated that potential heat energy recovery of around 116, 160 & 207 MWh/day may be obtained in January, March and May respectively, without causing wastewater temperature either in the network or at the inlet of the wastewater treatment plant to reach a level that was unacceptable to the water utility.