Uncertainty assessment of spatially distributed nitrate reduction potential in groundwater using multiple geological realizations

- We predict spatially distributed nitrate reduction in groundwater.
- We evaluate uncertainty on nitrate reduction due to geological uncertainty.
- Uncertainty on model predictions decreased with increasing aggregation scale.
- Using geophysical data in combination with borehole data decreases uncertainty.
- Uncertainty levels off at scale corresponding to mean length of sand units in till.

SummarySpatially distributed nitrate reduction potential in groundwater was estimated for the clay till dominated Norsminde fjord catchment in Denmark using the distributed hydrological model MIKE SHE. The nitrate transport was simulated using particle tracking and nitrate was assumed to be instantaneously reduced at the redox interface. Spatially distributed depths of the redox interface were estimated based on the spatial patterns in groundwater recharge and sediment redox capacity. Uncertainty of the estimated nitrate reduction due to geological uncertainty was assessed using multiple geological realizations. The geological realizations were generated using the geostatistical software TProGS and either conditioned based on borehole data only or soft conditioned based on both borehole data and geophysical data. Finally an upscaling of the predicted nitrate reduction was done in order to evaluate the change in uncertainty with increasing scale. The study showed that the uncertainty (one standard deviation) of the estimated nitrate reduction potential (in percentage of nitrate input) on the original 100 m model scale was 25% if only using borehole data and 19% if combining the borehole data with geophysical data. The uncertainty on the model predictions decreased with increasing aggregation scale. The decrease in uncertainty was most apparent the first 500 m, where after the uncertainty started to level off. This scale corresponded well to the mean length of the sand units within the clay till. It is concluded that using geophysical data in combination with borehole data in generation of geological realizations can help decrease uncertainty on the estimated nitrate reduction and that the predictive capability of distributed models is constrained by the spatial resolution of key data such as geology.