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 to developing and newly industrialised countries. One of the tasks within the project was the identification of state-of-the-art tools in the field of well field optimization modelling. Most of the currently used tools are process-driven simulation models like MODFLOW or FEFLOW. These are sometimes also combined with optimization models to reduce the computational demand and are utilized as strategic planning tools for water supply managers. However, in case of optimizing well field operation (i) under relatively constant boundary conditions and (ii) enough field data (temporal and spatial resolution dependent of the dynamics of the state parameter of interest, e.g. groundwater table, contaminant concentrations) data-driven approaches like support vector machines (SVM) can be used instead. If the water manager’s key interest is only a good predictive capability in combination with low computational demand, the application of this approach is more goal-orientated to simulate the dynamics of well field performance indicators efficiently. The contents of this report were presented to possible end-users, experts from Berliner Wasserbetriebe and Veolia. In agreement with their recommendations it was decided to focus further research within TECHNEAU on the empirical, data driven modelling approach. The selected approach is currently tested in the framework of a diploma thesis for a Berlin waterworks with the objective to analyse available production and observation well hydrographs by using modern statistical methods like principal component analysis and SVM (www.support-vector-machines.org).

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 of WP 5.2 is to develop a Decision Support System (DSS) as a first qualitative tool to assess the feasibility of bank filtration for drinking water supply in developing countries. The Bank Filtration Simulator (BFS), which is the subject of this report, is a sub-model used within the DSS to compute steady-state solutions for a two dimensional groundwater flow field in the horizontal plane for BF settings. Input parameters are required for aquifer, bank and well characteristics to calculate the BF share analytically. In addition the minimum travel time between bank and well is computed numerically. The sensitivity analysis yielded that the analytical calculated BF share is the most reliable output parameter, since its value is grid-independent. The most sensitive input parameters for the BF share calculation are the hydraulic conductivity of the aquifer and the clogging parameter, which both are the most uncertain ones to estimate. The accuracy of the numerically computed minimum traveltime of the BFS was cross-checked against a MODFLOW model, which produced only a very small discrepancy below 5%. Due to the lacking time-dependency of the BFS model its application is only appropriate on a management horizon for which the system’s boundary conditions (e.g. baseflow, clogging parameter and pumping rates) do not change significantly over time. In a nutshell it is therefore highly recommended to use the BFS only as a qualitative assessment tool in a first planning step to evaluate the feasibility of BF systems. Nevertheless the qualitative outputs give a valuable physically based insight of the system’s behaviour for distinct operational scenarios (e.g. minimal/maximum pumping rates) in order to add transparency and reproducibility to the decision making process.