Alexander Ahring

Combining Ecohydrological Catchment Modelling and Water Quality Monitoring to Assess Surface Water Pollution in the Swist River Basin

Inland surface waters like rivers, streams, lakes and reservoirs are subject to anthropogenic pollutant emissions from various sources. These emissions can have severe negative impacts on surface water ecology, as well as human well-being when surface waters are used for recreational activities, irrigation of cropland or drinking water production. In order to protect aquatic ecosystems and freshwater resources, the European Water Framework Directive (WFD) sets specific quality requirements which the EU member states must meet until 2027 for every water body.

Implementing effective measures and emission control strategies requires knowledge about the important emission pathways in a given river basin. However, due to the abundance of pollution sources and the heterogeneity of emissions in time and space, it is not feasible to gain this knowledge via water quality monitoring alone. SWAT (short for Soil and Water Assessment Tool) is a semi-distributed, dynamic and process-driven watershed model capable of simulating long term hydrology as well as nutrient fluxes on a daily time step. My thesis aims to combine SWAT ecohydrological modelling and long term water quality monitoring data to quantify Nitrogen emissions into surface waters and identify the principal pollution pathways for the Swist river basin in North Rhine-Westphalia (Germany).

The Swist is the largest tributary of the Erft River and drains a basin area of approximately 290 km². As part of its legal obligations and research activities, the Erftverband waterboard collects a large variety of long term monitoring data in the Swist river catchment,  which is available for the thesis. This includes streamflow data from four online gauging stations in the catchment, operational data from the wastewater treatment plants in the watershed as well as data from diverse water quality monitoring activities.