N-Map: High-resolution groundwater N-retention mapping and modelling by integration of geophysical, geological, geochemical, and hydrological data

Assessing groundwater denitrification spatially is the key to targeted agricultural nitrogen regulation

Globally, food production for an ever-growing population is a well-known threat to the environment due to losses of excess reactive nitrogen (N) from agriculture. Since the 1980s, many countries of the Global North, such as Denmark, have successfully combatted N pollution in the aquatic environment by regulation and introduction of national agricultural one-size-fits-all mitigation measures. Despite this success, further reduction of the N load is required to meet the EU water directives demands, and implementation of additional targeted N regulation of agriculture has scientifically and politically been found to be a way forward. In this paper, we present a comprehensive concept to make future targeted N regulation successful environmentally and economically. The concept focus is on how and where to establish detailed maps of the groundwater denitrification potential (N retention) in areas, such as Denmark, covered by Quaternary deposits. Quaternary deposits are abundant in many parts of the world, and often feature very complex geological and geochemical architectures. We show that this subsurface complexity results in large local differences in groundwater N retention. Prioritization of the most complex areas for implementation of the new concept can be a cost-efficient way to achieve lower N impact on the aquatic environment.

Importance of different factors for modeling nitrate transport and retention in a tile-drained agricultural catchment with distance-based generalized sensitivity analysis

Modeling of nitrate transport and retention in agricultural land use areas provides useful information to support water quality assessment and management. The accuracy and precision of model simulations are highly dependent on model input factors for which the appropriate values are generally difficult to determine and from which various uncertainties are induced into the modeling procedure. In this study, we applied a Distance-based Generalized Sensitivity Analysis (DGSA) to a high-resolution (25 × 25 m) nitrate transport and retention model for a tile-drained agricultural catchment (4.4 km2) to investigate the extent to which model input factors affect the spatially distributed nitrate retention. The input factors included the nitrate leaching from the root zone, the partitioning of nitrate into tile drainage and groundwater flux, the groundwater flux out of the catchment, the hydrogeological properties, and the denitrification rates in groundwater. The DGSA results were examined in both spatially lumped and distributed perspective. We found that the partitioning of nitrate into tile drainage and groundwater flux was the most important factor for modeling nitrate retention while the hydrogeological properties were secondary but also important. Conversely, the nitrate leaching from the root zone and denitrification rates in groundwater were noninfluential. By increasing the resolution of the DGSA analysis from catchment to model pixel, we found that input factors noninfluential on catchment scale were influential on pixel scale in discrete areas, and, as a general take-home-message, input factors influential on nitrate retention in at least 25 % of the model pixels were sensitive on catchment scale as well. Improved understanding of sensitivity of modelling nitrate retention may help the modelers and water managers to decide which input factors to prioritize in the modelling and data collection to improve the accuracy and precision of the model responses.