Phytoplankton blooms compromise the quality of freshwater ecosystems and the efficient processing of water by treatment works worldwide. This research aims to determine whether in-situ filamentous biofiltration processes mediated by living roots and synthetic filters as media can reduce or remove the phytoplankton loading (micro-algae and cyanobacteria) prior to a potable water treatment works intake. The underlying biofiltration mechanisms were investigated using field and laboratory studies. A novel macroscale biofilter with three plant species, named the "Living-Filter", installed in Farmoor II reservoir, UK, was surveyed weekly for physicochemical and biological variables under continuous flow conditions during 17 weeks. The efficiency of a mesoscale biofilter using the aquatic plant Phalaris arundinacea and synthetic filters, was tested with Microcystis aeruginosa under continuous flow conditions and in batch experiments. The 'simultaneous allelochemical method' was developed for quantifying allelochemicals from Phalaris in aqueous samples. Microscale studies were used to investigate biofilter allelochemical release in response to environmental stressors and Microcystis growth inhibition in filtered and unfiltered aqueous root exudate. Results demonstrate that the removal of phytoplankton biomass by physical mechanisms has a removal efficiency of ≤45% in the "Living-Filter" (filamentous biofilter plus synthetic fabric) and that the removal of Microcystis biomass using only biofilters was 25%. Chemical mechanisms that reduce Microcystis cell numbers are mediated by allelochemicals released from biofilter roots. Root exudate treatments on Microcystis revealed that Microcystis growth is inhibited by allelochemicals, not by nutrient competition, and that protists and invertebrates play a role in removing Microcystis. Filamentous biofilters can remove phytoplankton biomass by physical, chemical and biological mechanisms. Biofilters and synthetic filters in combination improve removal efficiency. Application of macroscale biofilters prior to potable water treatment works benefits the ecosystem. Plant properties, biofilter size to surface water ratio, and retention time must be considered to maximise the benefits of biofiltration processes.

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Indiana University-Purdue University Indianapolis (IUPUI) / In this research, Environmental Fluid Dynamic Code (EFDC) and Adaptive- Networkbased Fuzzy Inference System Models (ANFIS) were developed and implemented to determine the spatial-temporal distribution of cyanobacterial metabolites: 2-MIB and geosmin, in Eagle Creek Reservoir, IN. The research is based on the current need for understanding algae dynamics and developing prediction methods for algal taste and odor release events. In this research the methodology for prediction of 2-MIB and geosmin production was explored. The approach incorporated a combination of numerical and heuristic modeling to show its capabilities in prediction of cyanobacteria metabolites. The reservoir’s variable data measured at monitoring stations and consisting of chemical/physical and biological parameters with the addition of calculated mixing conditions within the reservoir were used to train and validate the models. The Adaptive – Network based Fuzzy Inference System performed satisfactorily in predicting the metabolites, in spite of multiple model constraints. The predictions followed the generally observed trends of algal metabolites during the three seasons over three years (2008-2010). The randomly selected data pairs for geosmin for validation achieved coefficient of determination of 0.78, while 2-MIB validation was not accepted due to large differences between two observations and their model prediction. Although, these ANFIS results were accepted, the further application of the ANFIS model coupled with the numerical models to predict spatio-temporal distribution of metabolites showed serious limitations, due to numerical model calibration errors. The EFDC-ANFIS model over-predicted Pseudanabaena spp. biovolumes for selected stations. The predicted value was 18,386,540 mm3/m3, while observed values were 942,478 mm3/m3. The model simulating Planktothrix agardhii gave negative biovolumes, which were assumed to represent zero values observed at the station. The taste and odor metabolite, geosmin, was under-predicted as the predicted v concentration was 3.43 ng/L in comparison to observed value of 11.35 ng/l. The 2-MIB model did not validate during EFDC to ANFIS model evaluation. The proposed approach and developed methodology could be used for future applications if the limitations are appropriately addressed.

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