International audienceIn common with most infrastructure systems, sewers are often inspected visually. Currently, the results from these inspections inform decisions for significant investments regarding sewer rehabilitation or replacement. In practice, the quality of the data and its analysis are not questioned although psychological research indicates that, as a consequence of the use of subjective analysis of the collected images, errors are inevitable. This article assesses the quality of the analysis of visual sewer inspection data by analysing data reproducibility; three types of capabilities to subjectively assess data are distinguished: the recognition of defects, the description of defects according to a prescribed coding system and the interpretation of sewer inspection reports. The introduced uncertainty is studied using three types of data: inspector examination results of sewer inspection courses, data gathered in day-to-day practice, and the results of repetitive interpretation of the inspection results. After a thorough analysis of the data it can be concluded that for all cases visual sewer inspection data proved poorly reproducible. For the recognition of defects, it was found that the probability of a false positive is in the order of a few percent, the probability of a false negative is in the order of 25%

Wastewater heat recovery via heat exchangers and heat pumps constitutes an environmentally friendly, approved and economically competitive, but often underestimated technology. By introducing the spatial dimension in feasibility studies, the results of calculations change considerably. This paper presents a methodology to estimate thermal energy resource potentials of wastewater treatment plants taking spatial contexts into account. In close proximity to settlement areas, wastewater energy can ideally be applied for heating in mixed-function areas, which very likely have a continuous heat demand and allow for an increased amount of full-load hours compared to most single-use areas. For the Austrian case, it is demonstrated that the proposed methodology leads to feasible results and that the suggested technology might reduce up to 17% of the Austrian global warming potential of room heating. The method is transferrable to other countries as the input data and calculation formula are made available. A broad application of wastewater energy with regard to spatial structures and spatial development potentials can lead to (1) increasing OPEN ACCESSSustainability 2015, 7 12989 energy efficiency by using a maximum of waste heat and (2) a significant reduction of (fossil) energy consumption which results in a considerable reduction of the global warming potential of the heat supply (GWP) if electricity from renewables is used for the operation of heat pumps.

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From a scientific point of view, it is unquestioned that numerical models for technical systems need to be calibrated. However, in sufficiently calibrated models are still used in engineering practice. Case studies in the scientific literature that deal with urban water management are mostly large cities, while little attention is paid to the differing boundary conditions of smaller municipalities. Consequently, the aim of this paper is to discuss the calibration of a hydrodynamic model of a small municipality (15,000 inhabitants). To represent the spatial distribution of precipitation, three distributed rain gauges were used for model calibration. To show the uncertainties imminent to the calibration process, 17 scenarios, differing in assumptions for calibration, were distinguished. To compare the impact of the different calibration scenarios on actual design values, design rainfall events were applied. The comparison of the model results using the different typical design storm events from all the surrounding data points showed substantial differences for the assessment of the sewers regarding urban flooding, emphasizing the necessity of uncertainty analysis for hydrodynamic models. Furthermore, model calibration is of the utmost importance, because uncalibrated models tend to overestimate flooding volume and therefore result in larger diameters and retention volumes.