In the Netherlands, drinking water is produced by purifying ground- or surface water during sand filtration to remove macro and micro pollutants from the source waters, mainly iron, manganese, methane and nitrogen compounds. A wide range of different, often fluctuating and difficult to predict biological and chemical processes are involved in this removal. The filter function of sand beds is also strongly influenced by operational parameters, such as the flow rate and regular cleaning procedures.
However, we currently lack the fundamental insights and models required to accurately forecast filter behaviour during normal operation and especially after disturbances, which for instance can occur after cleaning or following changes in the chemical composition of the incoming water.
Objectives
In this project, we aim to obtain a mechanistic and quantitative understanding of the underlying microbial and geochemical processes occurring in sand filters. We will identify the key microbial players, determine their interactions, assess their impact on the removal of iron, manganese, methane and nitrogen, and study their response to disturbance.
Methods
We will do this by a complementary array of state-of-the-art methods, combining novel sequencing techniques that determine which microorganisms are present and active with detailed biogeochemical measurements of the distribution and rate of conversion of a range of chemical compounds in sand beds. Combined with monitoring data of sand filter performance obtained from the drinking water companies, this will provide unprecedented insights in the cycling of the key elements of interest and their (bio)geochemical transformation. The sequencing and biogeochemical data will provide critical information on the nature of these transformation processes and will allow us to determine which reactions are biotic (i.e. microbially driven) and which are abiotic. This crucial information will be used to optimize the model regarding the cycling of elements. Taken together, the data obtained and analysed in this project will make it possible to predict which conversions take place in the filter material and which processes and microorganisms are involved.
Predictive model
Our ultimate goal is to contribute to the development of a predictive model that can be used in optimized management of sand filters.
