Flussökosysteme basieren auf dem komplexen Zusammenspiel physikalischer und biogeochemischer Prozesse. Ein mögliches Hilfsmittel zum Verständnis dieses Zusammenspiels sind Fließgewässergütemodelle (FGM): numerische, dynamische Modelle, welche die Interaktion empirisch bekannter biogeochemischer Prozesse abbilden und eine prozessbasierte Auswertung zulassen. FGM, wie sie im Folgenden verstanden werden, betrachten deterministische, biogeochemische Prozesse, die im Gewässer ablaufen, beispielsweise das Wachstum von Algenbiomasse auf der Grundlage von verfügbaren Nährstoffen und Licht. Sie unterscheiden sich dadurch deutlich von den folgenden Modelltypen, die in diesem Artikel nicht behandelt werden: (i) Rein hydraulische Modelle, welche die Strömung, Wasserstände sowie turbulente Mischung in Fließgewässern berechnen (z. B. das Modell EFDC der amerikanischen Umweltbehörde EPA (HAMRICK 1992) oder das kommerzielle Modell Telemac (GALLAND et al. 1991)). Eine Berechnung des Abflusses ist zwar die Basis aller FGM, wird aber im Folgenden nur kurz für die eindimensionale Näherung beschrieben. (ii) Stoffflussmodelle, welche eine Berechnung der Stofffrachten zum Ziel haben und Hydraulik und Transformationsprozesse im Gewässer nicht oder stark vereinfacht abbilden. Solche Modelle erlauben eine Aggregation von Stofffrachten, die über das eigentliche Gewässer hinausgeht, beispielsweise für gesamte Einzugsgebiete (z. B. MONERIS, BEHRENDT et al. (2000), oder SWAT, NEITSCH et al. (2001)) oder für städtische Wasserkreisläufe (MÖLLER et al. 2008). (iii) Modelle, die multitrophische Interaktionen in Fließgewässern abbilden und dadurch die Auswertung von Nahrungsketten ermöglichen (z. B. WOOTTON et al. 1996). Solche „multitrophischen Modelle“ werden hauptsächlich für akademische Fragestellungen eingesetzt. Im Gegensatz zu FGM betrachten sie ausschließlich die Interaktionen zwischen Spezies ohne Berücksichtigung deterministischer, biogeochemischer Prozesse. FGM koppeln eine hydraulische Modellierung des Abflusses in Fließgewässern mit der eigentlichen Gütemodellierung. Darin sind sie eng verwandt mit Gütemodellen für Seen, die im Artikel III-5.2 „Komplexe dynamische Seenmodelle“ beschrieben werden. Der große Unterschied zur Seenmodellierung ist der Umstand, dass FGM biogeochemische Prozesse in abfließenden Wasserpaketen betrachten. Die einzelnen Wasserpakete sind dadurch weitgehend unabhängig voneinander (abgesehen von der Dispersion, s. Abschnitt 3.2). Zudem beträgt die Fließzeit dieser Wasserpakete selbst in großen Flüssen lediglich Tage bis wenige Wochen. Dadurch ist die Entwicklung der Wasserqualität in FGM meist sehr viel stärker von den Randbedingungen an den oberen Rändern abhängig als bei Seenmodellen. Ein Einfluss der zurückliegenden Wasserqualität ist in FGM über das Sediment möglich, welches durch die meist geringen Wassertiefen ganzjährig einen Effekt auf die Wasserqualität im Fließgewässer haben kann. Wie bei Seenmodellen können Fließgewässer dreidimensional oder in zwei- oder eindimensionaler Vereinfachung simuliert werden. Während dreidimensionale hydraulische Modelle oft eingesetzt werden, gibt es kaum Beispiele von dreidimensionalen Güterechnungen. Neben dem Rechenaufwand verhindern auch der große Bedarf an Messungen für Kalibrierung und Validierung der Modellergebnisse sowie der große Aufwand bei der Datenauswertung einen häufigeren Einsatz. Entsprechend wird in der Folge in erster Linie auf eindimensionale Modellanwendungen eingegangen, also auf Modelle, die eine räumliche Dimension in Fließrichtung und eine zeitliche Dimension umfassen. Die beschriebenen biogeochemischen Prozesse sind aber auf höherdimensionale Modelle übertragbar. In dem folgenden Artikel wird zunächst auf die Ziele (Abschnitt 2) sowie den grundsätzlichen Aufbau von FGM (Abschnitt 3) eingegangen, wobei die Abbildung biogeochemischer Prozesse in etwas größerer Tiefe beschrieben wird. Danach wird auf existierende Modellsoftware (Abschnitt 4) sowie praktische Empfehlungen zum Vorgehen bei deren Gebrauch (Abschnitt 5) eingegangen. Zur konkreten Anwendung folgen zwei Beispiele der Modelle QSim und AQUASIM (Abschnitt 6). Da dieser Artikel nur einen groben Überblick über FGM geben kann, wird zum Schluss auf weiterführende Literatur verwiesen, die zukünftige Modellanwender unterstützen kann.

This report presents practical field aspects gained during two years of monitoring with state-of-the-art spectrometers and ion-selective sensors, combining (i) continuous measurements of the quality and flow rates of combined sewer overflows (CSO) with (ii) continuous measurements of water quality parameters within the urban stretch of the River Spree. It describes the set-up and the implementation of the monitoring and evaluates the outcomes and experiences towards “lessons learnt”. The challenge of CSO monitoring is their event-based and highly dynamic nature during rain events. Applied online sensors allow dynamic measurements of CSO and water quality impacts for a wide range of parameters. However, the success of online monitoring campaigns depends highly on three main considerations. Firstly, the representativity of the measurement station. The location of the probe must be representative of the concentration over the entire cross section of the sewer or the river. Further criteria have to be considered for the selection of the monitoring sites (e.g. easy access to the probes for maintenance) (chapter 2). Secondly, the quality of the raw measurements. External conditions can influence the quality of measurements and lead to wrong values or outliers. – To avoid drifts, probes need to be cleaned and checked regularly. We found that monitoring stations must be visited at least once a week for functional check-ups. During the two years of monitoring, the maintenance methodology have been continously improved to ensure the best measurement conditions (chapter 3). – But even under state-of-the-art operation of the probes, some values can be affected by errors and lead to misinterpretation. Thus, a validation step is required to detect wrong values and separate them from valid values. Given the large amount of data, an Access-based tool has been developed to support semi-automatic validation of monitoring data (chapter 4). Lastly, the calibration of raw measuments and the determination of uncertainties is critical. Online probes were not able to provide accurate measurements without being calibrated to local conditions with parallel laboratory measurements (online probe refers in this document to spectrometer and ISE-Probe). A Monte-Carlo method was adapted to perform regressions between raw measurement and lab values, which allows considering both uncertainties of sensor and lab chain. For instance, total uncertainty of the UV/VIS probe was between 15 and 30% for chemical oxygen demand (COD), accounting for errors from sensor, laboratory and field (representativity of site). The uncertainties in concentration and flow measurements lead to an uncertainty in CSO COD load between 20 and 70%, depending on the average concentration and flow of the event (chapter 5). In order to gain grab samples and provide high quality calibration, an automatic sampler has been installed at the sewer monitoring. However, for operational purposes, a sewer operator will expect to gain quality online data without the effort and costs of sampling each CSO. In order to estimate the optimal sampling effort, we investigated how many events (or how many lab measurements) are necessary for calibration depending on aimed at uncertainty. From a set of 12 sampled CSO events, we simulate all possible random combinations of events and calculated each time the resulting measurement uncertainty (chapter 5.5). Results shown in Figure A indicate that at least 7 random events need to be sampled to calibrate the probe reducing uncertainties of COD measurement under 30%. It has to be noted that the concentration range of the grab samples has a high influence on the quality of the calibration. A similar analysis considering only events with high lab variations (range > 500 mg/l) showed that then only 4 events must be sampled to reduce uncertainty under 30%. Considering these results, we recommend parallel short sampling campaigns with autosamplers (grab sampling) for application of spectrometers for CSO monitoring. If the lab measurements cover the entire range of water quality variations, a minimum of 3-4 rain events should be sampled to build an accurate calibration function with acceptable uncertainty. If sampled concentration range is exceeded by later measurements, new sampling campaigns should be planned. Since both sensor and autosampling results were available, CSO COD loads have been calculated using both spectrometer and lab values (chapter 6). Results indicate that load calculated with lab samples are within the error range of the loads calculated with spectrometer values. However, the frequency of grab sampling should be less than 10 minutes, to match concentration peaks and quick quality variations in our case. For the purpose of CSO load calculation, autosampler-based monitoring remains a cost-effective alternative to online probes. For a dynamic description of CSO (pollutant sources, mass/flow balance, etc.), autosampler-based data are limited by the minimal sample frequency and the sampling capacity. Investment and effort of online monitoring can overcome these limitations. For river monitoring, online probes enable measuring water quality variations with an acceptable uncertainty, if the probes are properly calibrated. Here, autosamplers are clearly limited by their sampling capacity as the impacts are spread on several days in the case of the River Spree. Since no autosampler was available during the two monitoring years no clear correlation could be established for the spectrometer parameters (TSS, COD, BOD). As the manual approach often fails to catch CSO impacts, an autosampler has been purchased for the last monitoring year in 2012. For NH4 + measurement, the ISE probe has been successfully calibrated performing monthly NH4 measurements in a bucket of river water spiked with ammonium standard solution to reach values in the range expected during CSO (1-2 mg/l).

This report concludes the first phase of the project “OptiWells”, which focuses on the optimization of drinking water well field operation with respect to energy efficiency. The purpose of this document is to provide sound answers to questions that utilities and well field operators are facing. Thus, it is built as a thematically organized sequence of main questions and answers rather than an extensive manuscript-like report. In total, 13 questions are addressed in detail, while 3 main “unanswered” questions and issues are detailed at the end of this report. The focus of this report is identical to the project’s focus: it addresses energy efficiency issues within the well field system. Thus, the main area of focus of the project lies in the interactions between the groundwater, the well, the pump and raw water pipe system. Drinking water treatment, as well as water distribution is not included in this study. This document, in combination with the other project deliverables, shall provide an overview of the potential optimizations for drinking water well fields. It shall yield both answers about saving potentials in general, and give some concrete examples from a French well field. By doing so, it shall assist the identification of solutions for an energyefficient groundwater abstraction, and provide a basis for a sound, practical methodology for well field energy audits and assessments.

This work was carried out within the framework of the project OPTIWELLS at the Kompetenzzentrum Wasser Berlin (KWB), a non-profit network society for water research and science transfer. The project addresses the modelling of a well field in order to minimise its energy demand. The first phase of the project is a feasibility study to identify the optimization possibilities of the energy demand. The first part of the study concerns the design and testing of a hydraulic model. At the beginning it was implemented on MS Excel and after with the help of Epanet, an opensource software. Data from the operator and manufacturers as well as measured data, gained during a site audit, were used to calibrate the model. Goals were to understand how the well field was working and to identify the energy demand drivers. The second part of the study concerned the choice and the implementation of scenarios with different operational conditions for the well field. Scenarios were focused on two aspects: the change of boundary conditions and the study of possible investments. A cost comparative assessment was carried out to estimate the payback times of the investigated scenarios. Results and according recommendations were communicated to the well field manager.

The optimisation of drinking water well field operation may significantly reduce the energy demand and associated costs, but is seldom applied in a systematic methodological approach. In this study, a well field was analysed using a coupled model that takes into account aquifer, wells, pumps and raw water pipes. This coupled approach enabled to identify and quantify the key energy demand drivers. The geometrical elevation was the most important driver, while pipe network losses were in the same order of magnitude as aquifer- and well losses. Using the modelling tool, the most energyefficient well field operation scheme could be derived and energy savings of up to 17% may be achieved by optimising well field operation only whereas further 5% may be saved by investing in new pump equipment. These findings show the potentials for significant energy savings in the field of drinking water abstraction.

Im Rahmen eines Forschungsprojektes wurden die Auswirkungen von Mischwasserentlastungen auf die Berliner Stadtspree untersucht und ein Planungsinstrument zur Reduzierung der Auswirkungen von Mischwasserüberläufen entwickelt.

In the city of Berlin combined sewer overflows (CSO) can lead to severe depressions in dissolved oxygen (DO) of receiving urban rivers and hence to acute stress for the local fish fauna. To quantify CSO impacts and optimize sewer management strategies, a model-based planning instrument has been developed. It couples the urban drainage model InfoWorks CS which simulates hydraulics and pollutant transport in the sewer with the river water quality model QSim which simulates hydraulics, mass transport and various biogeochemical processes in the receiving water body. To identify simulated CSO impacts, concentration-durationfrequency-thresholds for DO are applied to river model results via an impact assessment tool. Two kinds of impacts are distinguished: i) suboptimal conditions and ii) critical conditions for which acute fish kills are possible. In the case of Berlin, suboptimal conditions are observed on up to 92 days per year, predominantly during periods of low discharge and high temperatures whereas critical conditions only occur after CSO. For model calibration and validation, continuous measurements in both river and sewer are used. First simulations show good accordance between simulated and measured DO concentration in the river with Nash-Sutcliffe efficiencies between 0.70 and 0.79 for an eight-month time period at three different river monitoring points. However, to assure satisfactory model performance for adverse DO conditions in particular, impact assessment results for measured and simulated data are compared. Regarding suboptimal DO conditions simulated and measured data show good agreement. Nevertheless model representation for critical conditions is poor for some river sections and requires further improvement for CSO conditions. The results underline the importance of combining different validation approaches when dealing with complex systems.

The urban stretch of the River Spree is a regulated lowland-river, which is affected by a number of anthropogenic pressures, most notably impacts from combined sewer overflows (CSO) of the Berlin sewer system. Collected data show that occurrence of CSO can be detected in the river through a combination of continuous monitoring data, such as specific conductivity, ammonium (NH4), chemical oxygen demand and dissolved oxygen (DO). Comparison with stormwater guidelines indicates that drops in DO from CSO lead to regular problematic conditions for the fish fauna. In contrast, observed NH4 peaks never reach fish-toxic levels. Mitigation measures are currently implemented to reduce these negative impacts during storm events. The effect of past and potential future CSO measures can be studied with a model tool, which has been tested and is currently calibrated based on the above monitoring data.

The oxygen-consuming processes in the hypolimnia of freshwater lakes leading to deep-water anoxia are still not well understood, thereby constraining suitable management concepts. This study presents data obtained from 11 eutrophic lakes and suggests a model describing the consumption of dissolved oxygen (O2) in the hypolimnia of eutrophic lakes as a result of only two fundamental processes: O2 is consumed (i) by settled organic material at the sediment surface and (ii) by reduced substances diffusing from the sediment. Apart from a lake’s productivity, its benthic O2 consumption depends on the O2 concentration in the water overlying the sediment and the molecular O2 diffusion to the sediment. On the basis of observational evidence of long-term monitoring data from 11 eutrophic lakes, we found that the areal hypolimnetic mineralization rate ranging from 0.47 to 1.31 g ofO2 m-2 d-1 (average 0.90 ± 0.30) is a function of (i) a benthic flux of reduced substances (0.37 ± 0.12 g ofO2 m-2 d-1) and (ii) an O2 consumption which linearly increases with the mean hypolimnion thickness (zH)upto ~25 m. This model has important implications for predicting and interpreting the response of lakes and reservoirs to restoration measures.

In agricultural watersheds affected by diffuse pollution, limitation of fertilizer and pesticide application may not be sufficient to achieve good river water quality. After waterworks had to be closed in Brittany due to elevated nitrate concentrations in the river Ic (> 50 mg-NO3 L-1), the project Aquisafe has been initiated. The objective of Aquisafe is to reduce pollutant loads (nitrate and pesticides) from agricultural fields by implementation of near-natural mitigation zones at diffuse pollution hotspots at the head of watersheds. Simple and small solutions have to be designed in order to more efficiently reduce nitrate and pesticide concentrations in receiving rivers. In addition, a planning tool has to be developed to determine optimal locations to construct these systems. Finally, a tool to assess the effectiveness of these reactive zones on watershed water quality will be implemented. In order to reach the first objective, design features are tested on three scales: 1) laboratory scale, 2) technical scale and 3) field scale. 1) In the laboratory, column experiments were conducted with different organic substrates at short hydraulic residence times (HRT). The efficiency for parallel reduction of nitrate and two common herbicides in Europe, Bentazon and Isoproturon, was explored (Krause Camilo, 2012). 2) In technical scale, two parallel swales were filled with the most suitable material determined in (1) for a one year test. The influence of HRT and temperature was investigated. For nitrate, high reduction could be achieved at short HRT; results for herbicides still have to be confirmed. 3) One infiltration ditch and two simple wetlands were constructed in Brittany (France), taking into account experiences from other scales. These systems are now monitored to investigate the effects of upscaling. Site locations were chosen based on a validated and repeatable GIS-based overlay method that prioritises zones of potential contribution to nitrate pollution (Orlikowski et al, 2011). Additionally, a new wetland module is being developed for the Soil and Water Assessment Tool (SWAT). It allows to predict impacts of wetland constructions on nitrate concentrations in receiving rivers; the module is now implemented but still has to be calibrated with in situ monitoring results. The presentation will focus on results of the up-scaling approach, and will show how the tools of Aquisafe can be used for supporting the development of strategies at catchment scale.