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.

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.

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

A key aspect of protecting aquatic ecosystems from agricultural nitrogen (N) is to locate (i) farmlands where nitrate leaches from the bottom of the root zone and (ii) denitrifying zones in the aquifers where nitrate is removed before entering the surface water (N-retention). N-retention affects the choice of field mitigation measures to reduce delivered N to surface water. Farmland parcels associated with high N-retention gives the lowest impact of the targeted field measures and vice versa.