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The self-organizing map (SOM) model was applied to elucidate heavy metal removal mechanisms and to predict heavy metal concentrations in experimental constructed wetlands treating urban runoff. A newly developed SOM map showed that nickel in constructed wetland filters is likely to leach under high conductivity in combination with low pH in winter. In contrast, influent pH and conductivity were not shown to have clear relationships with copper (Cu) concentrations in the effluent, suggesting that the mobility of Cu was not considerably affected by salt increase during winter. The accuracy of prediction with SOM was highly satisfactory, suggesting heavy metals can be efficiently estimated by applying the SOM model with input variables such as conductivity, pH, temperature and redox potential, which can be monitored in real time. Moreover, domain understanding was not required to implement the SOM model for prediction of heavy metal removal efficiencies.

This paper examines the potential of a biological activity control system (BACS) for biological activated carbon (BAC) in comparison to granular activated carbon (GAC) for the treatment of potable water. The overall objective of the project is to produce drinking water of a higher quality more economically by developing a BACS for exhausted GAC that can be transformed to BAC by the development of a natural biofilm during the bio-regeneration mode. The research therefore may be interesting for water companies and the activated carbon industry. Findings show that the lifetime of a GAC filter can be significantly extended by maintaining an active biofilm that has to be controlled in order to avoid filter clogging. The most important parameters are dissolved oxygen (DO), pH and a correct balance of nutrients, which enables a natural control of the biomass. pH control was required to maintain an optimal bacteria-protozoa level. Excessive growth of filamentous bacteria can be prevented by a decrease in DO, increase in pH and the reduction of one essential nutrient, e.g. total phosphorus (P). Total organic carbon (TOC) and chemical oxygen demand (COD) values were reduced by bioactivity. DO, turbidity and suspended solids (SS) values were kept in acceptable ranges with respect to drinking water objectives. Plants without a significant population of protozoa deliver turbid low quality effluent high on SS and biochemical oxygen demand (BOD). It was possible to control the biofilm on GAC containing a natural biofilm and BAC during the bio-regeneration mode. Natural and artificial bio-regeneration lead to similar performance characteristics.

The European Union's Flood Directive 2007/60/EC requires member states to produce flood risk maps for all river basins and coastal areas at risk of flooding by 2013. As a result, flood risk assessments have become an urgent challenge requiring a range of rapid and effective tools and approaches. The Sustainable Flood Retention Basin (SFRB) concept has evolved to provide a rapid assessment technique for impoundments, which have a pre-defined or potential role in flood defense and diffuse pollution control. A previous version of the SFRB survey method developed by the co-author Scholz in 2006 recommends gathering of over 40 variables to characterize an SFRB. Collecting all these variables is relatively time-consuming and more importantly, these variables are often correlated with each other. Therefore, the objective is to explore the correlation among these variables and find the most important variables to represent an SFRB. Three feature selection techniques (Information Gain, Mutual Information and Relief) were applied on the SFRB data set to identify the importance of the variables in terms of classification accuracy. Four benchmark classifiers (Support Vector Machine, K-Nearest Neighbours, C4.5 Decision Tree and Naive Bayes) were subsequently used to verify the effectiveness of the classification with the selected variables and automatically identify the optimal number of variables. Experimental results indicate that our proposed approach provides a simple, rapid and effective framework for variable selection and SFRB classification. Only nine important variables are sufficient to accurately classify SFRB. Finally, six typical cases were studied to verify the performance of the identified nine variables on different SFRB types. The findings provide a rapid scientific tool for SFRB assessment in practice. Moreover, the generic value of this tool allows also for its wide application in other areas.

The self-organizing map (SOM) model was applied to predict outflow nutrient concentrations for integrated constructed wetlands (ICWs) treating farmyard runoff. The SOM showed that the outflow ammonia-nitrogen concentrations were strongly correlated with water temperature and salt concentrations, indicating that ammonia-nitrogen removal is effective at low salt concentrations and comparatively high temperatures in ICWs. Soluble reactive phosphorus removal was predominantly affected by salt and dissolved oxygen concentrations. In addition, pH and temperature were weakly correlated with soluble reactive phosphorus removal, suggesting that soluble reactive phosphorus was easily removed within ICWs, if salt concentrations were low, and dissolved oxygen, temperature and pH values were high. The SOM model performed very well in predicting the nutrient concentrations with water quality variables such as temperature, conductivity and dissolved oxygen, which can be measured cost-effectively. The results indicate that the SOM model was an appropriate approach to monitor wastewater treatment processes in ICWs.

The treatment efficiencies of vertical-flow wetland filters containing macrophytes and granular media of different adsorption capacities were investigated. Different concentrations of lead and copper sulphate were added to urban stream inflow water in order to simulate pre-treated (pH adjustment assumed) mine wastewater. After 1 year of operation, the metal mass load rate was increased by a factor of approximately 4.6. No breakthrough of metals was recorded. The use of macrophytes and adsorption media did not enhance heavy metal reduction significantly after 13 months of operation. A correlation analysis indicated strong positive correlations between conductivity on one side and other variables including temperature, total solids, dissolved oxygen and the redox potential on the other side. Some expensive or time-consuming variables (e.g., biochemical oxygen demand) can be predicted with less expensive ones (e.g., dissolved oxygen and temperature). The associated absolute mean errors were