The impacts of climate change on nitrogen losses to the environment in Austria: A dual model analysis across spatial and temporal scales to support policy decisions

The amounts and pathways of reactive nitrogen (Nr) losses in Austria into the surface water, soil, and atmosphere were determined under four climate change scenarios for the period 2041-2070. Two nutrient models were used to undertake the analysis at two different scales. Firstly, a semi-empirical, conceptual model (MONERIS) was setup for Austria to calculate the overall annual Nr surpluses, categorise flows of Nr, and identify regional hotspots of Nr losses. Secondly, a physically based eco-hydrological model (SWAT) was setup in three agricultural catchments to determine the hydrological processes related to Nr transport and quantify the amounts transported by various pathways in cropland at a detailed spatial and temporal resolution. The agricultural N surplus calculations for Austria were revised and used as input data for both models. The MONERIS and SWAT simulated inorganic N loads transported into waterbodies are overall similar, with average differences for the subsurface inorganic N loads of ±3 kg ha-1 yr-1 and for surface inorganic N loads of +0.4 to -0.03 kg ha-1 yr-1. Crop level N losses under future climate scenarios was contingent upon the fertilizer type, the crop grown and its accumulated biomass, as well as the type of climate scenario (wet or dry). In the SWAT model, an examination of the sensitivity of the input data (climate data and parameter values) found the dominant contribution to the sensitivity of simulated monthly discharge was from the climate data (69 % to 98 %). For simulating N loads, the climate scenarios contributed 30 % to 89 % of the sensitivity. Simulating Nr flows under climate scenarios is policy relevant to assess critical areas of N losses and identify future N transport pathways. Using a dual-model approach saves on resources required to set up a complex, data intensive model at a large scale, and can focus on critical catchments in detail.

Regional nitrogen budgets of agricultural production systems in Austria constrained by natural boundary conditions

Nitrogen (N) budgets are valuable tools to increase the understanding of causalities between agricultural production and N emissions to support agri-environmental policy instruments. However, regional agricultural N budgets for an entire country covering all major N flows across sectors and environmental compartments, which also distinguish between different N forms, are largely lacking. This study comprehensively analyses regional differences in N budgets pertainting to agricultural production and consumption in the largely alpine and spatially heterogeneous country of Austria. A special focus is on the interconnections between regional agricultural production systems, N emissions, nitrogen use efficiencies (NUE), and natural boundary conditions. Seven regional and one national balance are undertaken via material flow analysis and are analysed with regards to losses into soils, water bodies and atmosphere. Further, NUE is calculated for two conceptual systems of plant and plant-livestock production. The results reveal major differences among regions, with significant implications for agri-environmental management. The high-alpine region, characterized by alpine pastures with a low livestock density, shows consequent low N inputs, the lowest area-specific N outputs and the most inefficient NUE. In contrast, the highest NUE is achieved in a lowland region specialized in arable farming with a low livestock density and a predominance of mineral fertilizer over manure application. In this region, the N surplus is almost as low as in the high-alpine region due to both significantly higher N inputs and outputs compared to the high-alpine region. Nevertheless, due to low precipitation levels, widespread exceedances of the nitrate target level concentration take place in the groundwater. The same issue arises in another non-alpine region characterized by arable farming and high livestock densities. Here, the highest N inputs, primarily via manure, result in the highest N surplus and related nitrate groundwater exceedances despite an acceptable NUE. These examples show that NUE alone is an insufficient target and that adapted criteria are needed for different regions to consider natural constraints and specific framework conditions. In a geographically heterogeneous country like Austria, the regional circumstances strongly define and limit the scope and the potential effectiveness of agricultural N management strategies. These aspects should be integrated into the design, assessment and implementation of agri-environmental programmes.

Particulate PhozzyLogic Index for policy makers-an index for a more accurate and transparent identification of critical source areas

The identification of critical source areas (CSAs) is a key element in a cost-effective mitigation of diffuse emissions of phosphorus from agricultural soils into surface waters. One of the challenges related to CSAs is how to couple complex, data-intensive fate and transport models with easy-to-use information on field level for management purposes at the scale of large watersheds. To fill such a gap and create a bridge between the two tasks, this study puts forward the new Particulate PhozzyLogic Index (PPLI) based on the innovative combination of the results of a complex watershed model (in this case the PhosFate model) with fuzzy logic. Its main feature is the ability to transform the results of diverse scenarios or even models into a final map showing a catchment-wide ranking of the possibility of high PP emissions reaching surface waters for all agricultural fields. Further, this study enhances the PhosFate model with a new algorithm for the allocation of particulate phosphorus (PP) loads entering surface waters to their sources of origin. This is a basic requirement for the identification of critical PP source areas and in consequence for a cost-effective implementation of mitigation measures. By means of a sensitivity analysis, this study investigates the impacts of storm drains, discharge frequencies and flow directions on the designation of CSAs with the help of present-day scenarios for a case study catchment with an area of several hundred square kilometres. The upfront model calibration exhibits a Nash-Sutcliffe efficiency (NSE) of about 0.95 and a modified Nash-Sutcliffe efficiency (mNSE) of around 0.83. A core result of the sensitivity analysis is that the scenarios at least partially disagree on the identified CSAs and suggest that especially open furrows at field borders have the potential to lead to deviating outcomes. All scenario results nevertheless support the 80:20 rule, which states that about 80% of the phosphorus inputs into the surface waters of a catchment originate from only about 20% of its area.