UV/Vis spectrophotometers have been used for one decade to monitor water quality in various locations: sewers, rivers, wastewater treatment plants (WWTPs), tap water networks, etc. Resulting equivalent concentrations of interest can be estimated by three ways: i) by manufacturer global calibration; ii) by local calibration based on the provided global calibration and grab sampling; iii) by advanced calibration looking for relations between UV/Vis spectra and corresponding concentrations from grab sampling. However, no study has compared the applied methods so far. This collaborative work presents a comparison between five different methods. A Linear Regression (LR), Support Vector Machine (SVM), EVOlutionary algorithm method (EVO) and Partial Least Squares (PLS) have been applied on various data sets (sewers, rivers, WWTPs under dry, wet and all weather conditions) and for three water quality parameters: TSS, COD total and dissolved. Two criteria (r2 and Root Mean Square Error RMSE) have been calculated - on calibration and verification data subsets - to evaluate accuracy and robustness of the applied methods. Values of criteria have then been statistically analysed for all and separated data sets. Non-consistent outcomes come through this study. According to the Kruskal-Wallis test and RMSEs, PLS and SVM seem to be the best methods. According to uncertainties in laboratory analysis and ranking of methods, LR and EVO appear more robust and sustainable for concentration estimations. Conclusions are mostly independent of water matrices, weather conditions or concentrations investigated.

To support decision makers in planning effective combined sewer overflow (CSO) management strategies an integrated modelling and impact assessment approach has been developed and applied for a large urban area in Berlin, Germany. It consists of an urban drainage model, a river water quality model and a tool for the quantification of adverse dissolved oxygen (DO) conditions in the river, one of the main stressors for urban lowland rivers. The coupled model was calibrated successfully with average Nash- Sutcliffe-efficiencies for DO in the river of 0.61 and 0.70 for two validation years. Moreover, the whole range of observed DO concentrations after CSO down to 0 mg L-1 is simulated by the model. A local sensitivity analysis revealed that in the absence of CSO dissolved oxygen principally depends on phytoplankton dynamics. Regarding CSO impacts, it was shown that 97% of the observed DO deficit can be explained by the three processes (i) mixing of river water with CSO spill water poor in DO, (ii) reduced phytoplankton activity due to CSO-induced turbidity and (iii) degradation of organic matter by heterotrophic bacteria. As expected, process (iii) turned out to be the most important one. However depending on the time lag after CSO the other processes can become dominant. Given the different involved processes, we found that different mitigation schemes tested in a scenario analysis can reduce the occurrence of critical DO deficits in the river by 30-70%. Overall, the study demonstrates that integrated sewer-river-models can be set up to represent CSO impacts under complex urban conditions. However, a significant effort in monitoring and modelling is a requisite for achieving reliable results.

Deterioration modelling has been developed in the last decades to support operators and municipalities in defining mid-long term asset management strategies with limited availability of sewer condition data (CCTV). Modelling can help validating and showing the viability of current strategies or provide information to justify the relevance of additional investments and expenditures. Several modelling approaches are now available but not commonly used by sewer operators and municipalities to support strategies mainly because of the lack of real scale demonstration of the tangible benefits provided. Indeed, most of these models fail to show that they can adequately forecast future conditions (Ana and Bauwens, 2010; Scheidegger et al., 2011; WERF, 2012).

We investigate water quality of a small urban river during dry and wet weather conditions, including both standard parameters and trace organics. The monitored river stretch receives both effluents from WWTP as well as (separate) stormwater runoff of an impervious area of 11 km2. Results show increases in concentrations in the river during rain events with a factor > 20 for zinc, polycyclic aromatic hydrocarbons, two herbicides and one flame retardant. Also, substances which are expected both in WWTP effluent and in stormwater effluents were detected at important concentrations in the river during wet weather, such as the corrosion inhibitor Benzotriazole (0.8 µg/L on average) and the plasticizer Diisodecyl phthalate (4.0 µg/L on average). The presented results are preliminary and will be complemented by more results and substances as well as an assessment of the relevance of the findings.

A study is conducted to determine the relevance of micropollutants in urban stormwater runoff. To evaluate for the first time city-wide annual loads of stormwater-based micropollutants entering urban surface waters, an event-based, one-year monitoring program was set up in separate storm sewers in Berlin. Monitoring points were selected in 5 catchments of different urban structures (old building areas <1930, newer building areas >1950, single houses with gardens, roads >7500 vehicles/day and commercial areas) to consider catchment-specific differences. Storm events of different characteristics were sampled up to four hours during different seasons by automatic samplers triggered by flow meters. Volume-proportional samples (one composite sample per event) were analysed for a set of 100 parameters including 85 organic micropollutants (e.g. flame retardants, phthalates, pesticides/biocides, PAH), heavy metals and standard parameters. So far (70/88 samples), 60 organic micropollutants were at least once detected in stormwater runoff of the investigated catchment types. Concentrations were highest for phthalates with average concentrations of 13 µg/L for diisodecyl phthalate. For heavy metals, concentrations were highest for zinc (average: 950 µg/L). Results also showed catchment-specific differences for many compounds as well as seasonal differences for selected pollutants which can be used to improve micropollutant strategies and potentially prevent loads at the source.

Untreated stormwater runoff can be an important source of pollutants affecting urban surface waters. For example, in Berlin each year 78% or 54 million m³ of stormwater are discharged mostly untreated into receiving surface waters. Beside “classic” stormwater pollutants (e.g. suspended solids, COD, phosphorous or heavy metals), trace organic substances such as biocides, plasticizers, flame retardants and traffic related micropollutants (e.g. vulcanizing accelerators originating from tire wear or combustion by-products such as PAHs) started to come into focus in recent years (Zgheib et al. 2012, Gasperi et al. 2014). To evaluate for the first time city-wide annual loads of these trace organic substances entering urban surface waters through stormwater discharge, an event-based, one-year monitoring program was set up in the city of Berlin.

In recent years, the effect of urbanization on the quality of stormwater runoff gained increased attention including investigations on micropollutants. Especially in cities dominated by separated sewer systems, stormwater runoff containing micropollutants from anthropogenic origin is discharged mostly untreated into surface waters and therefore a potential source of high loads of pollutants. In a one year monitoring campaign stormwater runoff from five different catchments in Berlin is analyzed for major groups of micropollutants such as phthalates, organophosphates, organotin-compounds, biocides/pesticides, PAH’s, alkylphenols, polybrominated diphenylether, polychlorinated biphenyls and heavy metals. Sampling sites are equipped with automatic samplers, flow and water level meters in order to prepare flow proportional composite samples (recommended sampling strategy according to DIN ISO 5667-10). First results show that all groups of micropollutants were found in at least one catchment type in concentrations > 2 µg/L. Concentrations of the different micropollutant groups vary depending on the catchment types. So far, no organotin-compounds, polybrominated diphenylether or polychlorinated biphenyls were determined.

Im Rahmen des Forschungsprojekts SEMA ist die Prognosequalität eines Alterungsmodells anhand der TV-Inspektionsdaten der Stadt Braunschweig geprüft worden. Die Qualität der Prognose wurde auf der Grundlage einer Probe von 35.826 Inspektionen bewertet. Die Inspektionen wurden mittels eines substanzbasierten Modells klassifiziert. In einem zweiten Schritt wurde das statistische Modell KANEW-Z angewandt, um die Kanalalterung zu simulieren. Der Vergleich der Inspektions- mit den Simulationsergebnissen zeigt, dass das Modell in der Lage ist, die Zustandsverteilung des Systems ziemlich genau wiederzugeben. Die Ergebnisse sind auch ermutigend auf individueller Haltungsebene. Im Allgemeinen zeigt das Alterungsmodell viel bessere Ergebnisse als ein einfaches lineares Alterungsmodell. Schlussfolgernd unterstreichen die Ergebnisse das Interesse und den potentiellen Nutzen der Anwendung von Alterungsmodellen zur Unterstützung von Asset-Management-Strategien.

Micropollutant concentrations found in stormwater runoff were extrapolated to annual loads at the scale of the city of Berlin (impervious connected area of ~170 km2). Extrapolation was done by city structure, i.e., it was assumed that concentration patterns found in one of five specific city structure types is representative for every area of this structure type. Preliminary results show that micropollutants of several substance types can enter Berlin surface waters at loads in the order of kg/yr via stormwater runoff: plasticizers (e.g., sum of Di-iso-decylphthalate and Di-iso-nonylphthalate at 770 kg/yr), flame retardants (e.g., tris(2-butoxyethyl) phosphate (TBEP) at 89 kg/yr), biocides from different sources (e.g., Glyphosate at 17 kg/yr and Mecoprop at 30 kg/yr), vulcanizing accelerator benzothiazole (as sum of benzothiazole and metabolites methylthiobenzothiazole and hydroxybenzothiazole at 65 kg/yr) and combustion byproduct polycyclic aromatic hydrocarbons PAH 16 (sum of 16 EPA PAH at 107 kg/yr). These loads are in a similar order of magnitude as micropollutants that enter Berlin surface waters via (treated) sewage, such as pharmaceutical residues carbamazepine and ibuprofen with estimated annual loads of 436 kg/yr and 35 kg/yr, respectively.