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.

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.

It was the aim of the EU funded research project TECHNEAU to investigate the relevance and feasibility of bank filtration (BF) plus post-treatment for newly industrialised and developing countries. Field studies at BF sites in Delhi (India) were supplemented by literature studies and modelling in order to investigate if this natural drinking water (pre-) treatment is a sustainable option to provide safe drinking water for countries like India. The results showed that especially for those substances that are of relevance in newly industrialised and developing countries subsurface passage can represent an efficient barrier. However, certain limiting factors for BF application also need to be considered: high ammonium levels in surface water, usually associated with high shares of poorly or un-treated sewage, will not be mitigated during subsurface passage and require extensive post-treatment. In order to support decision makers in the difficult task of assessing the feasibility of BF systems at a certain site a simple decision support system was developed. This simple tool enables to assess a range of abstraction rates and well locations for a specific field site that could fit with their needs (e.g. minimum required travel time or share of BF).

Bank filtration, i.e. the abstraction of groundwater from wells along a river or lake, thus inducing infiltration has a long history as (pre-) treatment step for drinking water production in Europe. The goal of this study is to assess whether groundwater waterworks using BF have a cost advantage compared to SWTPs if both, water abstraction and treatment processes are considered.

Work package WP 5.2 “Combination of Managed Aquifer Recharge (MAR) and adjusted conventional treatment processes for an Integrated Water Resources Management“ within the European Project TECHNEAU (“Technology enabled universal access to safe water”) investigates bank filtration (BF) + post-treatment as a MAR technique to provide sustainable and safe drinking water supply to developing and newly industrialised countries. One of the tasks within the project is the development of a Decision Support System (DSS) to assess the feasibility of BF systems under varying boundary conditions such as: (i) quality of surface and ambient groundwater, (ii) local hydrological and hydrogeological properties (e.g. clogging layer) and (iii) well field design (distance to bank) and operation (pumping rates). Since the successful, cost-effective implementation of BF systems requires the optimization of different objectives such as (i) optimizing the BF share in order to maintain a predefined raw water quality or (ii) maintaining a predefined minimum travel time between bank and production well, both aspects are addressed within the DSS. As an example for a practical application the DSS is tested with data from the Palla well field in Delhi/India. As a result optimal shares of bank filtrate were calculated for the monsoon and non-monsoon season. By simulating different pumping and clogging scenarios with the BF Simulator optimal pumping rates were derived. The DSS proved to be a good qualitative tool to identify and learn about the trade-offs a decision maker has to make due to the (i) inherently competing nature of different objectives (e.g. high BF share and minimum travel time > 50 d) and the (ii) inherent uncertainty due to the large natural variability of boundary conditions (e.g. clogging layer). Since both characteristics can be addressed within the DSS it helps to add transparency and reproducibility to the decision making process. An additional advantage is that its application requires only low effort concerning time, money, and manpower. Thus the application of the DSS is recommended to accompany decision making processes especially in developing and newly industrialised countries where data availability and low financial budgets are usually the major burden for the application of more complex, data-demanding decision support tools. However, it needs to be considered that in practice additional parameters like water availability, energy efficiency and cost-benefit need to be taken into account.

Work package WP 5.2 “Combination of Managed Aquifer Recharge (MAR) and adjusted conventional treatment processes for an Integrated Water Resources Management“ within the European Project TECHNEAU (“Technology enabled universal access to safe water”) investigates bank filtration (BF) + post-treatment as a MAR technique to provide sustainable and safe drinking water supply. One of the tasks within the project is the testing of a data-driven approach for the identification (pattern recognition) and quantification of the key processes that drive the groundwater (GW) dynamics in observation wells (OW) near well fields of a BF waterworks. For this BUSSE (2010) used a multivariate statistical method (principal component analysis - PCA) with daily GW level time series of 41 OWs and was able to identify four processes that explained 95% of the total variance in the data set. On the one hand GW recharge (58.9%) and its temporal delay (3.3%) explain 62% of the GW level fluctuations within the study period. On the other hand any discernible impact of waterworks abstractions is limited to one of the three well fields with the highest production rate (29.8% of explained variance). In addition the infiltration of a marshy ditch into the GW accounts for another 2.9% of the GW level fluctuations. Regarding the ability to identify driving forces for GW level fluctuations the main advantage for using PCA compared to process-driven GW flow modelling is that the driving forces for GW level fluctuations can be identified and quantified without requiring exact knowledge about the structural properties of the subsurface (e.g. aquifer transmissivities) and its input parameters (e.g. GW recharge, production rates). Note that the latter do not enter the PCA directly but are used for spatiotemporal interpretation of the results, which also requires some expertise. In addition, it is recommended to perform a sensitivity analysis of the PCA results in a next step, so that it can be tested whether the processes identified above are robust in case of changing input parameters such as: - Reduced spatiotemporal resolution - Study period with different boundary conditions (e.g. pumping regime). The contents of this report were presented to the involved experts from the Berliner Wasserbetriebe (BWB). In agreement with their recommendations it was decided to focus further research within follow-up projects on the (i) sensitivity analysis of the PCA results and (ii) to apply nonlinear approaches for identification and quantification of processes that drive GW quality dynamics within the study area.

Work package WP 5.2 “Combination of Managed Aquifer Recharge (MAR) and adjusted conventional treatment processes for an Integrated Water Resources Management“ within the European Project TECHNEAU (“Technology enabled universal access to safe water”) investigates bank filtration (BF) + post-treatment as a MAR technique to provide sustainable and safe drinking water supply to developing and newly industrialised countries. One of the tasks within this work package is to assess the costefficiency of BF systems. For this a comparative cost analysis (CCA) between groundwater waterworks using BF as natural pre-treatment step and surface water treatment plants (SWTPs) is performed. The CCA yielded that, under the assumption of equally low surface water quality, BF systems are more cost-efficient than SWTPs. This result is in line with the general water source priority of water suppliers, which prefer resources with the best water quality and security under the constraint of guaranteeing sufficient water availability. Furthermore the sensitivity analysis confirmed that the natural boundary condition 'pumping rate per production well' has a major impact on the specific total costs of BF systems. Lower pumping rates lead to increasing capital costs for the additional production wells, which are not fully compensated through pumping cost savings and thus lead to increasing total costs. In addition the result of the monitoring scenario clearly confirmed that for this aspect groundwater waterworks have a structural disadvantage compared to surface waterworks. Subsequently, if monitoring costs are taken into account, a higher critical pumping rate per production well is required to exceed the break-even-point. In a nutshell the CCA shall support water supply managers in the complex process of making rational investment decisions. However, since within this analysis only water abstraction and treatment process costs are considered, the CCA does not cover the total cost structure of a waterworks (e.g. costs of building sites). Thus the application of the CCA is only valid if both (i) neglected costs and (ii) benefits are in the same order of magnitude for all alternatives (exception: most cost-efficient alternative provides excess benefits). In case that the above stated prerequisites are not fulfilled, the CCA is only a first step in the economic assessment and more powerful evaluation methods (e.g. cost-benefit analysis) are needed.

Within the European project TECHNEAU (www.techneau.org) the Berlin Center of Competence for Water (KWB) is investigating bank filtration (BF) and adjusted post-treatment as a managed aquifer recharge (MAR) technique to provide sustainable and safe drinking water supply to developing and newly industrialised countries. One of the tasks within the project is the development of a Decision Support System (DSS) to assess the feasibility of BF systems under varying boundary conditions such as: (i) quality of surface and ambient groundwater, (ii) local hydrological and hydrogeological properties (e.g. clogging layer) and (iii) well field design (distance to bank) and operation (pumping rates). Since the successful, cost-effective implementation of BF systems requires the optimization of multiple objectives such as (i) optimizing the BF share in order to maintain a predefined raw water quality, (ii) maintaining a predefined minimum travel time between bank and production well and (iii) achieving cost-efficiency of different well field design and operation schemes, all these objectives need to be addressed within the DSS.