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.

Approximately 70% of the drinking water in Germany (BGR) and about 50% worldwide (IGREC 2011) are abstracted from groundwater using filter wells. Their implementation, operation and maintenance are major factors contributing to the costs of drinking water production. According to an international survey (Howsam, Misstear & Jones 1995 ), 40% of worldwide used water abstraction wells work inefficiently in terms of well performance or water quality. This implies high costs and a great potential for improvement, both for the (re-) construction of new wells (capital investment) and well operation (energy consumption, maintenance needs). The main reason for inefficient well performance is so-called well ageing, i.e. the decrease in performance due to biological, chemical and / or physical processes in and around the well. Dominant factors determining type, extension and location of deposits are the geology of the exploited aquifer together with the qualitative properties of the abstracted water, the well design (dimensions and materials), construction (drilling method) and operation. The project WellMa, initiated and financed by the Berliner Wasserbetriebe (BWB) and Veolia Eau, and coordinated at the Berlin Centre of Competence for Water (KWB), aimed at improving the efficiency of drinking water abstraction wells by identifying, evaluating and testing methods of well management including design, operation and maintenance to slow down well ageing. Set into relation to ranges, in which ageing processes are known to occur, the initial data of well sites were used to differentiate a low, medium or high potential for the occurrence of well ageing and to define the monitoring needs accordingly. Well ageing processes were distinguished into six types, each of them implying different pre-requisites and site conditions and leading to different monitoring and/ or maintenance requirements. For carbonate scaling, iron ochre formation, biofouling, corrosion, colmation and sand intake pre-requisites, triggers and threshold conditions were identified and implemented in a decision support system enabling well operators to prioritize the needs for monitoring, diagnosis or maintenance action taking into account the specific well and site characteristics.

Managed Aquifer Recharge (MAR) comprises a wide variety of systems in which water is intentionally introduced into an aquifer and subsequently recovered, e.g. for drinking water or irrigation purposes. The objective is i) to store excess water for times of less water availability and / or ii) to introduce an additional barrier for purification of water from different sources (e.g. surface water, treated waste water) for a specific use. Common MAR techniques in Europe are (Figure 1): river bank filtration (RBF) and artificial groundwater recharge – usually via ponded infiltration (AR). Riverbank filtration (RBF) has a long history as a process for generating safe water for human consumption in Europe. During industrialization in the 19th century drinking water facilities in England, the Netherlands and Germany started using bank filtered water due to the increasing pollution of the rivers. The systematic production of bank filtrates started around 1870-1890 (BMI 1975, 1985). Since then, RBF and in case of insufficient quantity, artificial groundwater recharge (AR) have been generally applied as a first barrier within the drinking water treatment chain. The most common and widely used method for artificial groundwater recharge (AR) are infiltration ponds (Asano, 2007). These simple surface spreading basins provide added benefits of treatment in the vadoze zone and subsequently in the aquifer. Advanced pretreatment of the infiltration water by coagulation, and advanced post-treatment of the recharged water, e.g. with activated carbon or ozonation became necessary in many cases after the 1960’s as the quality of the source water further decreased. Today the water supply of many European cities and densely populated areas relies on riverbank filtration or artificial recharge. Following Castany (1985), in France, the proportion of bank-filtered water reaches approximately 50% of the total drinking water production (Doussan et al., 1997). In the Netherlands 13% of drinking water is produced from infiltration of surface water, such as bank filtration and dune infiltration (Hiemstra et al., 2003). In Germany riverbank filtration and artificial groundwater recharge are used in the valleys of the rivers Rhein, Main, Elbe, Neckar, Ruhr, and in Berlin along the Havel and Spree (Grischek et al., 2002). In Berlin 75% of the drinking water is derived from riverbank filtration and artificially recharged groundwater (Schulze, 1977). Riverbank filtration is also applied in the United States as an efficient and low cost drinking water pre-treatment technology (Ray et al., 2002), also to improve the removal of surface water contaminating protozoa. In most applications, MAR is intended to act as a buffer in terms of water availability (quantity) and water quality. In general, the level of knowledge of natural treatment systems, notably in aquifers, is not as high as in engineered systems, because the biogeochemical environment in aquifers that modify water quality for sure, will vary in space and time (Dillon et al. 2008). The heterogeneity of the system, strengthens its buffer potential on the one hand, but makes it more difficult to describe and control on the other hand. Key parameters that determine the quantitative storage capacity of the system are the specific hydrogeology of the aquifer (e.g. transmissivity and porosity) and the clogging potential at the entry point of the recharge water (infiltration pond, well or river bank). Clogging occurs due to physical, chemical and biochemical processes and needs to be regarded carefully as it may reduce the systems performance substantially. From literature it is known, that increased clogging reduces the oxidation state of the clogging layer. At a bank filtration site at Lake Tegel, Berlin, it was observed that intensity and spatial distribution of clogging strongly depends on the extent and thickness of the unsaturated zone. Geochemical observations suggest, that atmosperic oxygen induces redox processes which lead to a reduction of the clogging layer (Wiese & Nützmann 2008). This is possibly due to the complex interaction of hydrochemical and biological processes within the uppermost centimetres of the aquifer (Hoffmann et al., 2006). If these processes are likewise found in AR system, they may be influenced as to minimize basin-cleaning efforts. This needs to be further investigated. Water quality aspects of MAR are governed by i) the quality of the infiltrated / injected water ii) physical straining of particulate and particle-bound substances, iii) adsorption and desorption, iv) biogeochemical degradation / deactivation processes within the aquifer, iv) the geochemical composition of the aquifer, and v) the quality of the ambient groundwater. The process most important for MAR applications is usually the physical straining of particulate and particlebound substances, lessening the effort for subsequent drinking water treatment. In Berlin, e.g. disinfection of drinking water can usually be avoided due to complete removal of pathogens during underground passage of up to 6 months. Cyanobacterial toxins (e.g. microcystins) that are primarily cell-bound are efficiently removed as well (Grützmacher et al. 2007). On the other hand there is still a lack of understanding under which circumstances microcystins or other cyanobacterial toxins like cylindrospermopsin (currently observed in growing quantities in Germany) are released, thus becoming potentially more mobile in the subsurface. Adsorption to the aquifer matrix contributes to the elimination of organic substances and heavy metals. Although this does not remove the substances completely, peak loads – e.g. from oil spills – are retarded and maximum concentrations reduced. In addition, sorption prolongs the detention time in the aquifer which multiplies the time for biodegradation. Biological degradation in the subsurface is responsible for the elimination of dissolved organic carbon (usually resulting from natural organic matter, NOM) and organic trace substances that occur at varying extent. Investigations have shown that the redox potential in the aquifer is decisive for the degree of elimination (Stuyfzand, 1998; Massmann et al. 2007). Due to increasingly sensitive analytical methods trace organics present in surface waters (e.g. pharmaceutical residues) have been detected in many MAR systems e.g in Berlin and the Netherlands (Massmann et al, 2007, Stuyfzand et al. 2007). Advanced numerical models including reactive flow and transport can simulate the complex interactions between the hydrogeochemical environment and degradation of trace organics (Greskowiak et al. 2006). However, so far this has only been applied for a limited number of compounds at very few sites. Further research is needed to apply these methods for risk assessment. A second method for predicting the removal of organic micropollutants is the more statistically based approach of linking substance properties (molecular weight, number of double bonds, number of aromatic rings, etc.) to biodegradation via quantitative structure-activity relationship (QSAR) type models. This has been applied successfully to other water treatment methods – a transfer to MAR is lacking so far. As MAR is a technology that relies on the interaction of natural processes framework conditions like climate and hydrogeology play an important role. There is a need for testing the transferability from central European conditions to other regions, and for an assessment, how temperature changes affect the system’s elimination capacity. With ongoing climate change, reducing precipitation in some regions of Europe and increasing peak flow events in others, MAR is the ideal technology to act as a buffer for quantity and quality. The European Water Supply and Sanitation Platform (www.wsstp.org) for example has identified MAR as a technology potentially fit for future challenges.