Using hydrodynamic and hydraulic modelling to study microbiological water quality issues at a backwater area of the Danube to support decision-making
Research output: Journal article (peer-reviewed) › Journal article
The alluvial backwater areas of the Danube are valuable ecological habitats containing important drinking water resources. Due to the river regulation and the construction of power plants, the river water levels and natural dynamics of the backwater areas continuously decline, threatening their typical characteristics. The aim of this study was to evaluate how an increased connectivity of the backwater branch located in a nature-protected riverine floodplain (enabled by diverting river water into the backwater system via a weir) affects the microbiological quality of groundwater resources. The defined quality criterion was that the diversion measures must not lead to an increased detection frequency of faecal indicators in groundwater. The microbiological water quality of the Danube, its backwater branch and the groundwater was analysed from 2010 to 2013. E. coli was selected as bacterial indicator for recent faecal pollution. C. perfringens (spores) was analysed as indicator for persistent faecal pollution and potentially occurring pathogenic protozoa. We simulated the microbial transport from the Danube and the backwater river into groundwater using a 3‑D unsaturated-saturated groundwater model coupled with 2‑D hydrodynamic flow simulations. Scenarios for no diversion measures were compared with scenarios for an additional discharge of 3, 20 and 80 m3/s from the Danube River into the backwater branch. While the additional discharge of 20 and 80 m3/s of Danube water into the floodplain strongly improved the ecological status according to ecological habitat models, the hydraulic transport simulations showed that this would result in a deterioration of the microbiological quality of groundwater resources. The presented approach shows how hydraulic transport modelling and microbiological analyses can be combined to support decision-making.