Nitrate leaching losses from two Baltic Sea catchments under scenarios of changes in land use, land management and climate.

Pollution with excess nutrients deteriorate the water quality of the Baltic Sea. The effect of combined land use and climate scenarios on nitrate leaching and nitrogen (N) loads to surface waters from two Baltic Sea catchments (Norsminde in Denmark and Kocinka in Poland) was explored using different models; the NLES and Daisy models for nitrate leaching, and MIKE SHE or MODFLOW/MT3DMS for N transport. Three Shared Socioeconomic Pathways (SSP1, SSP2 and SSP5) defined change in land use and agricultural activities. The climate change scenarios covered 2041-2060 compared with 1991-2010 under RCP8.5, applying four different climate models. Increases in predicted N-load from climate change vary from 20 to 60% depending on climate model. SSPs moderate these N-load changes with small changes for SSP1 to large increases for SSP5, with greater increases for Norsminde than Kocinka due to land use differences. This stresses needs for new measures and governing schemes to meet sustainability targets.

Spatially differentiated regulation: Can it save the Baltic Sea from excessive N-loads?

The Baltic Sea Action Plan and the EU Water Framework Directive both require substantial additional reductions of nutrient loads (N and P) to the marine environment. Focusing on nitrogen, we present a widely applicable concept for spatially differentiated regulation, exploiting the large spatial variations in the natural removal of nitrate in groundwater and surface water. By targeting mitigation measures towards areas where nature's own capacity for removal is low, spatially differentiated regulation can be more cost-effective than the traditional uniform regulation. We present a methodology for upscaling local modelling results on targeted measures at field scale to Baltic Sea drainage basin scale. The paper assesses the potential gain and discusses key challenges related to implementation of spatially differentiated regulation, including the need for more scientific knowledge, handling of uncertainties, practical constraints related to agricultural practice and introduction of co-governance regimes.

Reducing uncertainty of estimated nitrogen load reductions to aquatic systems through spatially targeting agricultural mitigation measures using groundwater nitrogen reduction.

The need to further abate agricultural nitrate (N)-loadings to coastal waters in Denmark represents the main driver for development of a new spatially targeted regulation that focus on locating N-mitigation measures in agricultural areas with high N-load. This targeting makes use of the spatial variation across the landscape in natural N-reduction (denitrification) of leached nitrate in the groundwater and surface water systems. A critical basis for including spatial targeting in regulation of N-load in Denmark is the uncertainty associated with the effect of spatially targeting measures, since the effect will be critically affected by uncertainty in the quantification of the spatial variation in N-reduction. In this study, we used 30 equally plausible N-reduction maps, at 100 m grid and sub-catchment resolutions, for the 85-km2 groundwater dominated Norsminde catchment in Denmark, applying set-aside as the measure on high N-load areas to reach a N-load reduction target of 20%. The uncertainty on these N-reduction maps resulted in uncertainty on the estimated N-load and on the required set-aside area. We tested several methods for spatially targeting set-aside that took into account the uncertainty on set-aside area and developed methods to reduce uncertainty on the estimated N-load reductions. These methods includes application of set-aside based on each individual N-reduction map compared to a mean N-reduction map, using spatial frequency of high N-load and using spatial frequency of low N-reduction. The results revealed that increasing the ensemble size for averaging the N-reduction maps would decrease the uncertainty on the estimated set-aside area with a stable effect when using an ensemble of 15 or more maps. The spatial resolution of the groundwater N-reduction map is essential for the effectiveness of set-aside, but uncertainty of the finer spatial resolution of N-reduction is greater compared to sub-catchment scale, and application of a spatially targeted strategy with uncertain N-reduction maps will result in incorrect set-aside area and uncertain estimations of N-load reductions. To reduce the uncertainty on estimated N-load reductions, this study finds the method of set-aside application based on spatial frequency of high N-load to be more effective than other methods tested.

Spatially differentiated strategies for reducing nitrate loads from agriculture in two Danish catchments.

Nutrient loss from agriculture is the largest source of diffuse water pollution in Denmark. To reduce nutrient loads a number of solutions have been implemented, but this has been insufficient to achieve the environmental objectives without unacceptable repercussions for agricultural production. This has substantiated the need to develop a new approach to achieve nitrogen (N) load reduction to the aquatic environments with lower costs to farmers. The new approach imply targeting N leaching mitigation to those parts of the landscape which contribute most to the N-loadings. This would involve either reducing the source loading or enhancing the natural reduction (denitrification) of N after it is leached from the root zone of agricultural crops. In this study, a new method of spatially differentiated analysis for two Danish catchments (Odense and Norsminde) was conducted that reach across the individual farms to achieve selected N-load reduction targets. It includes application of cover crops within current crop rotations, set-a-side application on high N-load areas, and changes in agricultural management based on maps of N-reduction available for two different spatial scales, considering soil type and farm boundaries as spatial constraints. In summary, the results revealed that considering spatial constraints for changes in agricultural management will affect the effectiveness of N-load reduction, and the highest N-load reduction was achieved where less constraints were considered. The results also showed that the range of variation in land use, soil types, and N-reduction potential influence the reduction of N-loadings that can originate from critical source areas. The greater the spatial variation the greater the potential for N load reduction through targeting of measures. Therefore, the effectiveness of spatially differentiated measures in term of set-a-side area in Odense catchment were relatively greater compared to Norsminde catchment. The results also showed that using a fine spatial N-reduction map provides greater potential for N load reductions compared to using sub-catchment scale N-reduction maps.