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. In Denmark, a targeted N-regulation approach is currently implemented on small catchment scale (approx. 15 km2). Although this regulatory scale is much more detailed than what has been used previously, it is still so large that regulation for most individual fields will be either over- or under-regulated due to large spatial variation in the N-retention. The potential cost reduction for farmers is of up to 20-30% from detailed retention mapping at the field scale compared to the current small catchment scale. In this study, we present a mapping framework (N-Map) for differentiating farmland according to their N-retention, which can be used for improving the effectiveness of targeted N-regulation. The framework currently only includes N-retention in the groundwater. The framework benefits from the incorporation of innovative geophysics in hydrogeological and geochemical mapping and modelling. To capture and describe relevant uncertainties a large number of equally probable realizations are created through Multiple Point Statistical (MPS) methods. This allows relevant descriptions of uncertainties of parts of the model structure and includes other relevant uncertainty measures that affects the obtained N-retention. The output is data-driven high-resolution groundwater N-retention maps, to be used by the individual farmers to manage their cropping systems due to the given regulatory boundary conditions. The detailed mapping allows farmers to use this information in the farm planning in order to optimize the use of field measures to reduce delivered agricultural N to the surface water and thereby lower the costs of the field measures. From farmer interviews, however, it is clear that not all farms will have an economic gain from the detailed mapping as the mapping costs will exceed the potential economic gains for the farmers. The costs of N-Map is here estimated to 5-7 €/ha/year plus implementation costs at the farm. At the society level, the N-retention maps allow authorities to point out opportunities for a more targeted implementation of field measures to efficiently reduce the delivered N-load to surface waters.

Optimized number of suction cups required to predict annual nitrate leaching under varying conditions in Denmark.

Nitrate concentrations in soil water leaving the root zone measured by suction cups combined with water transport modeling is a commonly used practice in Denmark for calculating nitrate leaching. Two suction cups installed in one plot giving one water sample and replicated four times, (eight total suction cups) to reduce variability between samples. For practical reasons, it would be beneficial to minimize the number of suction cups used yet maintain reliable predictions. To assess the variability in reducing suction replicates, this study analyzed data from five research sites across Denmark representing annual field nitrate leaching predictions for different combinations of soil, weather conditions, crops, N-fertilizer rates, and winter soil cover, covering a total of 173 annual nitrate leaching experiments. The analysis was conducted having different nitrate leaching predictions using different numbers of replicates of suction cup measurements. Linear regression was used to identify the different influences of leaching year (hydrological year), N rate applied, soil characteristics, and crop sequence on nitrate leaching. The analyses were set up on three 2-yr and two 3-yr field experiments in five different sites. Crop effects showed that cereals and winter cover sown in autumn 2017 had significantly more nitrate leaching than in 2015 and 2016 leaching years due to high precipitation rates in the autumn. Furthermore, decreasing the number of suction cup replicates from four (eight total) to three replicates (six total) did not have a significant effect on nitrate leaching prediction. In contrast, decreasing replicates from four to two (four total) and one (two total) replicates did show a significant difference. Therefore, using three replicates is a viable solution for future sampling strategies and a good trade-off between costs and accuracy.

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.

Controlled Drainage as a Targeted Mitigation Measure for Nitrogen and Phosphorus.

Drainage systems provide a more or less direct conduit for excess water and nutrients from fields to surface water. High nutrient loads to streams and lakes are known to adversely affect water quality and may potentially cause algae blooms. Therefore, in-field as well as edge-of-field mitigation measures that can assist in reducing the loss of nutrients are needed. The aim of this study was to investigate the effectiveness and possibility of using controlled drainage during the drainage season to reduce nutrient losses while growing a winter crop in a temperate climate. The 3-yr-long (2012-2015) study was conducted on four experimental field plots on loamy soil. The impacts of controlled drainage on groundwater levels, drain flow, and water quality at regulation levels of 50 and 70 cm above the conventional drain pipe level were determined by using a before-after control-impact study design. A regulation level of 70 cm was required to significantly elevate groundwater levels and reduce the drain outflow and N and P loss, which decreased by 37 to 54%, 38 to 51%, and 43 to 46%, respectively, relative to conventional drainage levels. Denitrification in the root zone, as measured with stable isotopes, was not markedly enhanced at the plots with controlled drainage, except on a few occasions. Resetting the groundwater level to conventional levels in early spring only had a marginal influence on water and nutrient losses. Thus, potential water quality tradeoffs (e.g., increased N loss to groundwater) need to be more thoroughly investigated before implementing controlled drainage as a mitigation measure in Denmark.

Effects of changes in land use and climate on aquatic ecosystems: Coupling of models and decomposition of uncertainties.

To analyse the potential future ecological state of estuaries located in the temperate climate (here exemplified with the Odense Fjord estuary, Denmark), we combined end-of-the-century climate change projections from four different climate models, four contrasting land use scenarios ("Agriculture for nature", "Extensive agriculture", "High-tech agriculture" and "Market driven agriculture") and two different eco-hydrological models. By decomposing the variance of the model-simulated output from all scenario and model combinations, we identified the key sources of uncertainties of these future projections. There was generally a decline in the ecological state of the estuary in scenarios with a warmer climate. Strikingly, even the most nature-friendly land use scenario, where a proportion of the intensive agricultural area was converted to forest, may not be enough to counteract the negative effects of a future warmer climate on the ecological state of the estuary. The different land use scenarios were the most significant sources of uncertainty in the projections of future ecological state, followed, in order, by eco-hydrological models and climate models, albeit all three sources caused high variability in the simulated outputs. Therefore, when projecting the future state of aquatic ecosystems in a global warming context, one should at the very least consider to evaluate an ensemble of land use scenarios (nutrient loads) but ideally also include multiple eco-hydrological models and climate change projections. Our study may set precedence for future attempts to predict and quantify uncertainties of model and model input ensembles, as this will likely be key elements in future tools for decision-making processes.

Simulation of Soil Organic Carbon Effects on Long-Term Winter Wheat (Triticum aestivum) Production Under Varying Fertilizer Inputs.

Soil organic carbon (SOC) has a vital role to enhance agricultural productivity and for mitigation of climate change. To quantify SOC effects on productivity, process models serve as a robust tool to keep track of multiple plant and soil factors and their interactions affecting SOC dynamics. We used soil-plant-atmospheric model viz. DAISY, to assess effects of SOC on nitrogen (N) supply and plant available water (PAW) under varying N fertilizer rates in winter wheat (Triticum aestivum) in Denmark. The study objective was assessment of SOC effects on winter wheat grain and aboveground biomass accumulation at three SOC levels (low: 0.7% SOC; reference: 1.3% SOC; and high: 2% SOC) with five nitrogen rates (0-200 kg N ha-1) and PAW at low, reference, and high SOC levels. The three SOC levels had significant effects on grain yields and aboveground biomass accumulation at only 0-100 kg N ha-1 and the SOC effects decreased with increasing N rates until no effects at 150-200 kg N ha-1. PAW had significant positive correlation with SOC content, with high SOC retaining higher PAW compared to low and reference SOC. The mean PAW and SOC correlation was given by PAW% = 1.0073 × SOC% + 15.641. For the 0.7-2% SOC range, the PAW increase was small with no significant effects on grain yields and aboveground biomass accumulation. The higher winter wheat grain and aboveground biomass was attributed to higher N supply in N deficient wheat production system. Our study suggested that building SOC enhances agronomic productivity at only 0-100 kg N ha-1. Maintenance of SOC stock will require regular replenishment of SOC, to compensate for the mineralization process degrading SOC over time. Hence, management can maximize realization of SOC benefits by building up SOC and maintaining N rates in the range 0-100 kg N ha-1, to reduce the off-farm N losses depending on the environmental zones, land use and the production system.

Potential benefits of farm scale measures versus landscape measures for reducing nitrate loads in a Danish catchment.

To comply with the EU Water Framework Directive, Denmark must further reduce the nitrate (N)-load to marine ecosystems from agricultural areas. Under the anticipated future spatially targeted regulation, the required N-load reductions will differ between catchments, and these are expected to be mitigated by a combination of land and water management measures. Here, we explored how the expected N-load reduction target of 38% for a Danish catchment (River Odense) could be achieved through a combination of farm and landscape measures. These include: (a) N-leaching reduction through changing the crop rotation and applying cover crops, (b) enhancing N-reduction through (re)establishment of wetlands, and (c) reducing N-leaching through spatially targeting of set-aside to high N-load areas. Changes in crop rotations were effective in reducing N-leaching by growing crops with a longer growing season and by allowing a higher use of cover crops. A combination of wetlands and changes in crop rotations were needed for reaching the N-load reduction target without use of set-aside. However, not all combinations of wetlands and crop rotation changes achieved the required N-load reduction, resulting in a need for targeted set-aside, implying a need for balancing measures at farm and landscape scale to maximize N load reduction while minimizing loss of productive land. The effectiveness of farm scale measures is affected by farm and soil types as well as by N-reduction in groundwater, while the possibilities for using wetlands for decreasing the N-load depends on landscape features, allowing the establishment of wetlands connected to streams and rivers.

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.

Delay in catchment nitrogen load to streams following restrictions on fertilizer application.

A MIKE SHE hydrological-solute transport model including nitrate reduction is employed to evaluate the delayed response in nitrogen loads in catchment streams following the implementation of nitrogen mitigation measures since the 1980s. The nitrate transport lag times between the root zone and the streams for the period 1950-2011 were simulated for two catchments in Denmark and compared with observational data. Results include nitrogen concentration and mass discharge to streams. By automated baseflow separation, stream discharge was separated into baseflow and drain flow components, and the nitrogen concentration and mass discharge in baseflow and drain flow were determined. This provided insight on the development of stream nitrogen loads, with a short average lag time in drain flow and a long average lag time in baseflow. The long term effect of nitrogen mitigation measures was determined, with results showing that there is a 15 years long delay in the appearance of peak nitrogen loads in streams. This means that real time stream monitoring data cannot be used alone to assess the effect of nitrogen mitigation measures.

Review of scenario analyses to reduce agricultural nitrogen and phosphorus loading to the aquatic environment.

Nutrient loadings of nitrogen (N) and phosphorus (P) to aquatic environments are of increasing concern globally for managing ecosystems, drinking water supply and food production. There are often multiple sources of these nutrients in the landscape, and the different hydrological flow patterns within stream or river catchments have considerable influence on nutrient transport, transformation and retention processes that all eventually affect loadings to vulnerable aquatic environments. Therefore, in order to address options to reduce nutrient loadings, quantitative assessment of their effects in real catchments need to be undertaken. This involves setting up scenarios of the possible nutrient load reduction measures and quantifying their impacts via modelling. Over the recent two decades there has been a great increase in the use of scenario-based analyses of strategies to combat excessive nutrient loadings. Here we review 130 published papers extracted from Web of Science for 1995 to 2014 that have applied models to analyse scenarios of agricultural impacts on nutrients loadings at catchment scale. The review shows that scenario studies have been performed over a broad range of climatic conditions, with a large focus on measures targeting land cover/use and land management for reducing the source load of N and P in the landscape. Some of the studies considered how to manage the flows of nutrients, or how changes in the landscape may be used to influence both flows and transformation processes. Few studies have considered spatially targeting measures in the landscape, and such studies are more recent. Spatially differentiated options include land cover/use modification and application of different land management options based on catchments characteristics, cropping conditions and climatic conditions. Most of the studies used existing catchment models such as SWAT and INCA, and the choice of the models may also have influenced the setup of the scenarios. The use of stakeholders for designing scenarios and for communication of results does not seem to be a widespread practice, and it would be recommendable for future scenario studies to have a more in-depth involvement of stakeholders for the elaboration and interpretation of scenarios, in particular to enhance their relevance for farm and catchment management and to foster better policies and incentives.

Integrated modelling of crop production and nitrate leaching with the Daisy model.

An integrated modelling strategy was designed and applied to the Soil-Vegetation-Atmosphere Transfer model Daisy for simulation of crop production and nitrate leaching under pedo-climatic and agronomic environment different than that of model original parameterisation. The points of significance and caution in the strategy are: •Model preparation should include field data in detail due to the high complexity of the soil and the crop processes simulated with process-based model, and should reflect the study objectives. Inclusion of interactions between parameters in a sensitivity analysis results in better account for impacts on outputs of measured variables.•Model evaluation on several independent data sets increases robustness, at least on coarser time scales such as month or year. It produces a valuable platform for adaptation of the model to new crops or for the improvement of the existing parameters set. On daily time scale, validation for highly dynamic variables such as soil water transport remains challenging. •Model application is demonstrated with relevance for scientists and regional managers. The integrated modelling strategy is applicable for other process-based models similar to Daisy. It is envisaged that the strategy establishes model capability as a useful research/decision-making, and it increases knowledge transferability, reproducibility and traceability.