Predicting the ecological status of rivers and streams under different climatic and socioeconomic scenarios using Bayesian Belief Networks

Freshwater systems have increasingly been subjected to a multitude of human pressures and the re-establishment of their ecological integrity is currently a major worldwide challenge. Expected future climate and socioeconomic changes will most probably further exacerbate such challenges. Modelling techniques may provide useful tools to help facing these demands, but their use is still limited within ecological quality assessment of water resources due to its technical complexity. We developed a Bayesian Belief Network (BBN) framework for modelling the ecological quality of rivers and streams in two European river basins located in two distinct European climatic regions: the Odense Fjord basin (Denmark) and the Sorraia basin (Portugal). This method enabled us to integrate different data sources into a single framework to model the effect of multiple stressors on several biological indicators of river water quality and, subsequently, on their ecological status. The BBN provided a simple interactive user interface with which we simulated combined climate and socioeconomic changes scenarios to assess their impacts on river ecological status. According to the resulting BBNs the scenarios demonstrated small impacts of climate and socioeconomic changes on the biological quality elements analysed. This yield a final ecological status similar to the baseline in the Odense case, and slightly worse in Sorraia. Since the present situation already depicts a high percentage of rivers and streams with moderate or worse ecological status in both basins, this means that many of them would not fulfil the Water Framework Directive target in the future. Results also showed that macrophytes and fish indices were mainly responsible for a non-desirable overall ecological status in Odense and Sorraia, respectively. The approach followed in this study is novel, since BBN modelling is used for the first time for assessing the ecological status of rivers and streams under future scenarios, using an ensemble of biological quality elements. An important advantage of this tool is that it may easily be updated with new knowledge on the nature of relationships already established in the BBN or even by introducing new causal links. By encompassing two case studies of very different characteristics, these BBN may be more easily adapted as decision-making tools for water management of other river basins