The present study aims to explore the relationship between rainfall variables and water quality/quantity characteristics of combined sewer overflows (CSO), by the use of multivariate statistical methods and online measurements at a principal CSO outlet in Berlin (Germany). Canonical correlation results showed that the maximum and average rainfall intensities are the most influential variables to describe CSO water quantity and pollutant loads whereas the duration of the rainfall event and the rain depth seem to be the most influential variables to describe CSO pollutant concentrations. The analysis of Partial Least Squares (PLS) regression models confirms the findings of the canonical correlation and highlights three main influences of rainfall on CSO characteristics: (i) CSO water quantity characteristics are mainly influenced by the maximal rainfall intensities, (ii) CSO pollutants concentrations were found to be mostly associated with duration of the rainfall and (iii) pollutants loads seemed to be principally influenced by dry weather duration before the rainfall event. The prediction quality of PLS models is rather low (R² < 0.6) but results can be useful to explore qualitatively the influence of rainfall on CSO characteristics.

The present study aims at demonstrating the possibilities of on-line sensors for describing CSO emissions and river impacts. A continuous integrated monitoring, using state-of-the-art on-line sensors, was started in Berlin in 2010. It combines (i) continuous measurements of water quality and flow rates of combined sewer overflows (CSO) at one main CSO outlet and (ii) continuous measurements of water quality parameters at four sites within the urban stretch of the receiving river. UV-VIS probes provide continuous measurements of parameters such as chemical oxygen demand (COD) with relatively low uncertainties (10-30%). However, experience shows that on-line UV-VIS probes are not able to provide accurate measurements of water quality without being calibrated to local conditions. Several methodologies to analyze on-line CSO and river measurements are presented and illustrated with an exemplary event. Results show that reliable information such as the CSO load, the proportion of wastewater in CSO, the contribution of wastewater to CSO load, the first flush effect and the intensity of river impacts can be gained at high precision and temporal resolution. Given the broad range of high quality information from CSO impacts in the river to the characterization of CSO emissions, the study suggests the use of continuous integrated monitoring programs to support decisions on CSO management.

Das vorgestellte modellbasierte Werkzeug bildet Mischwasserüberläufe aus dem Berliner Mischkanalsystem und deren kurzfriste Auswirkungen im Gewässer ab. Es soll für die Maßnahmenplanung und die Berechnung von Zukunftsszenarien verwendet werden. Das Werkzeug zeigt eine gute Übereinstimmung mit Messungen bezüglich des Verlaufes der Sauerstoffkonzentration im Gewässer und des Auftretens kritischer Bedingungen für die Fischfauna. Eine Szenarienuntersuchung für ein Extremjahr zeigt, dass durch die bis zum Jahr 2020 geplante Stauraumvergrößerung die Häufigkeit fischkritischer Bedingungen im Gewässer bereits um ein Drittel reduziert werden kann. Eine Reduktion um ein zusätzliches Drittel wäre durch weitergehende Maßnahmen im Bereich der Entsiegelung möglich. Die verbleibenden fischkritischen Bedingungen sind das Ergebnis von sehr starken Regenereignissen und können kaum verhindert werden. Eine durch Klimaveränderung erhöhte oder reduzierte Regenintensität im Sommer hätte starken Einfluss auf das Auftreten fischkritischer Bedingungen; die erwartete Temperaturerhöhung würde hingegen hauptsächlich die Sauerstoffsituation bei Trockenwetter verschlechtern.

Das vorgestellte modellbasierte Werkzeug bildet Mischwasserüberläufe aus dem Berliner Mischkanalsystem und deren kurzfristige Auswirkungen im Gewässer ab. Es soll für die Massnahmenplanung und die Berechnung von Zukunftsszenarien verwendet werden. Das Werkzeug zeigt eine gute Übereinstimmung mit Messungen bezüglich des Verlaufes der Sauerstoffkonzentration im Gewässer und des Auftretens kritischer Bedingungen für die Fischfauna.

Combined sewer overflows (CSO) after heavy rainfall can cause acute depletions of dissolved oxygen (DO) in the Berlin River Spree. Further aggravation of ecological deficits can be expected from global climate change. A planning instrument for CSO impact assessment under different sewer management and climate conditions has been developed at Kompetenzzentrum Wasser Berlin. It couples the sewer model InfoWorks CS, the river water quality model Hydrax/QSim and an impact assessment tool. The planning instrument was validated for the years 2010 and 2011. Simulation results for the critical parameters discharge and DO concentrations in the Berlin River Spree agree well with measurements. Although not all observed DO deficits can be simulated accurately, the very good representation of processes related to the oxygen budget allows assessing relative changes in boundary conditions, e.g. from climate change or different CSO control strategies. The conducted scenario analysis indicates that the coupled sewer-rivermodel reacts sensitively to changes in boundary conditions (temperature, rainfall, storage volume and other CSO control strategies, etc.). Based on the simulation year 2007 – representing an extreme year with regards to CSO volume and critical conditions in the river – sewer rehabilitation measures planned to be implemented until 2020 are predicted to reduce total CSO volumes by 17% and discharged pollutant loads by 21 - 31%. The frequency of critical DO conditions for the most sensitive local fish species will decrease by one third. For a further improvement of water quality after the year 2020, the reduction of impervious surfaces emerges as a very effective management strategy where feasible. A reduction of the impervious connected area by 20% results in a decrease in the frequency of critical DO conditions by another third. The studied increase in surface air and water temperature as part of the climate change scenarios leads to a significant aggravation of DO stress due to background pollution in the Berlin River Spree, while acute DO depletions after CSO are barely affected. However, changes in rain intensity have a considerable effect on CSO volumes, pollutant loads and the frequency of critical DO concentrations. A general reduction of discharged pollutant loads by 60% based on the sewer status 2020 can prevent critical DO conditions in the Berlin River Spree, even for the exceptionally rain intense year 2007. A detailed analysis of river processes after CSO, has shown that the biodegradation of organic carbon compounds is the most important contributor to acute DO depletions in the Berlin River Spree. An additional impairment of DO conditions is caused by the inflow of oxygen free CSO spill water and suspended solids into the Berlin River Spree. In this report, CSO impacts under different management strategies or climate change conditions are assessed only for a part of the Berlin combined sewer system (although the main part) and for one exemplary year. An extension of the planning instrument to the entire combined sewer system would enable to evaluate the full impact of measures. For a robust prediction of future CSO impacts it is also recommended to test different simulation periods or conduct long-term simulations.

Theoretically the Berlin River Spree could be under pressure from depressions in dissolved oxygen (DO) and high concentration of fish toxic ammonia following overflows of the combined sewer system. However, monitoring results indicate that the Spree is only under pressure from depressions in dissolved oxygen (DO). Consequently, a sewer model, a river water quality model and an impact assessment tool were calibrated and validated for representation of DO depressions. The three elements are joined in a planning tool, which will be used to test the effect of CSO management approaches for the current situation and with altered boundary conditions to account for expected climate change.