Land use impact on long term nitrogen trends and stream network nitrate uptake

Uunderstanding of the effect of land use and agriculture practices on in-stream nitrogen fluxes is still not fully achieved. Primarily land use controls nitrogen losses from land to water. Long term land us effects can be evaluated by data driven time series analyses if detailed spatial analyses are not in the focus. New findings suggest that additionally land use can modify nitrogen removal from stream networks. To fully understand the spatial distribution and temporal dynamics of nitrate losses to and uptake in river networks distributed grid-based hydrological water quality models are required. Our new findings reveal that dynamic harmonic regression time series analysis of long term river water quality data allow to detect changes from chemodynamic to more chemostatic behavior over several decades and we suggest that this seems to be a general trend in long term heavily anthropogenically used agricultural catchments in central Europe. This is a sign of long-term homogenisation of nitrate concentrations distribution over depth of the soil and subsoil. We show that detailed physical understanding of nitrate dynamics across time scales can be obtained only through combined analysis of long-term records including also high-resolution sensor data. New experimental analyses indicate that land use can modify in-stream assimilatory uptake through riparian vegetation induced changes of light regime. Furthermore straitening of streams and rivers due to increasing land use pressure may also change in-stream nitrogen removal through reduced stream benthic area and increased flow velocity. We introduce a new modelling approach based on the multi-scale Hydrological Model (mHM) which allows considering both spatially distributed nitrogen leaching as well as high spatial resolution river network uptake including the impact of riparian vegetation and stream bottom area. We compare seasonal variation of model in-stream nitrate uptake predictions with calculated values using a nitrate assimilatory uptake approach generated from high frequency sensor measurements. Our findings suggest that using new experimental data for parameterizing stream network models will allow to substantially improve continues modelling of in-stream nitrogen fluxes.