Elevated nitrate concentrations are a thread for water supply and ecological integrity in surface water. Nitrate fluxes obtained by standard monitoring protocols at the catchment outlet strongly integrate spatially and temporally variable processes such as mobilization and turnover. Consequently, inference of dominant nitrate sources is often problematic and challenging in terms of effective river management and prioritization of measures. Here, we combine a spatially highly resolved assessment of nitrate concentration and fluxes along a mesoscale catchment with four years of monitoring data at two representative sites. The catchment is characterized by a strong land use gradient from pristine headwaters to lowland sub-catchments with intense agricultural land use and wastewater sources. We use nitrate concentrations in combination with hydrograph separation and isotopic fingerprinting methods to characterize and quantify nitrate source contribution.

The hydrological analysis revealed a clear dominance of base flow during both campaigns. However, the absolute amounts of discharge differed considerably from one another (outlet: 1.42 m³ s^− 1 in 2014, 0.43 m³ s^− 1 in 2015). Nitrate concentrations are generally low in the pristine headwaters (< 3 mg L^− 1) and increase downstream (15 to 16 mg L^− 1) due to the contribution of agricultural and wastewater sources. While the agricultural contribution did not vary in terms of nitrate concentration and isotopic signature between the years, the wastewater contribution strongly increased with decreasing discharge. Wastewater-borne nitrate load in the entire catchment ranged between 19% (2014) and 39% (2015). Long-term monitoring of nitrate concentration and isotopic composition in two sub-catchment exhibits a good agreement with findings from spatially monitoring. In both datasets, isotopic composition indicates that denitrification plays only a minor role. The spatially highly resolved monitoring approach helped to pinpoint hot spots of nitrate inputs into the stream while the long-term information allowed to place results into the context of intra-annual variability.