Ine Pauwels

Development and assessment of an integrated ecological modelling framework to assess the effect of investments in wastewater treatment on water quality

Worldwide, large investments in wastewater treatment are made to improve water quality. However, the impacts of these investments on river water quality are often not quantified. To assess water quality, the European Water Framework Directive (WFD) requires an integrated approach. The aim of this study was to develop an integrated ecological modelling framework for the River Drava (Croatia) that includes physical-chemical and hydromorphological characteristics as well as the ecological river water quality status. The developed submodels and the integrated model showed accurate predictions when comparing the modelled results to the observations. Dissolved oxygen and nitrogen concentrations (ammonium and organic nitrogen) were the most important variables in determining the ecological water quality (EWQ). The result of three potential investment scenarios of the wastewater treatment infrastructure in the city of Varaždin on the EWQ of the River Drava was assessed. From this scenario-based analysis, it was concluded that upgrading the existing wastewater treatment plant with nitrogen and phosphorus removal will be insufficient to reach a good EWQ. Therefore, other point and diffuse pollution sources in the area should also be monitored and remediated to meet the European WFD standards.

Development and selection of decision trees for water management: Impact of data preprocessing, algorithms and settings

In the present research, we found that different preprocessing options and parameterizations of classification and regression trees alter their model fit and have a direct effect on their applicability for end-users. We found that, in terms of applicability, classification trees react different to pruning than regression trees. Indeed, in case of high pruning levels, classification focus on the extreme values of the response variable, whereas regression tree are more likely to predict the intermediate values. Furthermore, when applying cross-validation with a high number of folds, modellers are likely to find one model that outperforms the other models in terms of reliability. Models were assessed based on the determination coefficient, the percentage of Correctly Classified Instances and the Cohens Kappa statistic for each parameterization. We found positive correlations (R-2 > 0.70) between the statistical criteria and we found a non-linear negative relation between the model fit and the level of pruning. Therefore, environmental modellers should make use of an exhaustive list of model parameterizations to develop and compare environmental models in a transparent and objective manner. General methodological guidelines derived from the present research may help modellers to efficiently select statistical and ecological relevant models that are meeting the needs of users. The validity of our conclusion should be further tested for other datasets and scientific domains as our findings are based on one set of freshwater data.

A Spatially Explicit Migration Model for Pike

Pike (Esox lucius L.) populations have been suffering from habitat degradation and the increasing number of restoration programs had only limited success. In order to set up more effective restoration programmes in the future, it is important to gain insight into the spatio-temporal dynamics of pike. Because no efforts have been spent to develop a spatially explicit model that enables a better understanding of the observed patterns of movement, and actually as a first step towards an integrated spatially explicit model for describing pike dynamics, a model mimicking the movement of pike in the river Yser, Belgium, is proposed.