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EUR 22245 EN (2006) Bio-Bio Project Modelling nutrient fate from agriculture: an integrated framework FAYÇAL BOURAOUI, BRUNA GRIZZETTI, ALBERTO ALOE European Commission, Joint Research Centre, Institute for Environment and Sustainability 21020 Ispra, Italy Many European countries face high nutrient loadings and the scientific community is asked to provide tool sand methodologies to alleviate the pressure on the environment originating from agriculture. This paper presents a tiered approach for addressing nutrient fate at various scales that makes best use of readily available data at EU level. A statistical approach is used at large-river basin to identify areas with highest nutrient losses. A physically-based model is then used to identify within those areas, the major processes and pathways controlling nutrient losses. Finally, a farm-scale model is used to elaborate appropriate farming practices. 1. Introduction Although nutrients are essential for plant and animal populations, high concentrations can degrade water and soil quality. To control and reduce pollution coming from nutrients, the EC has been setting stringent regulations: • The Nitrates Directive (91/676/EEC, 1991) requires Member States to designate Nitrate Vulnerable Zones (NVZ), and imposes to implement various action programs for reducing water pollution generated by agriculture; • The Water Framework Directive (2000/60/EC, 2000) required Member States to identify sources of pollution, evaluate their impacts on the ecological status of surface and subsurface waters and implement river basins management plans Agriculture is one of the main sources of nutrient loading to water bodies, with contribution to nitrogen loading ranging from more than 80% in Denmark to less than 30% in Finland (OECD, 2001). Italian’s agriculture contributes to more than 60% of the nitrogen measured in the streams (OECD, 2001). Combating diffuse pollution from agriculture is complicated due to the temporal and spatial lag between the management actions taken at the farm level and the environmental response (Schröder et al., 2004). Appropriate farming practices are among the most efficient way of reducing nutrient losses. In Italy, the nitrogen efficiency (ratio of nitrogen application and nitrogen uptake) is slightly 26 higher than 70% (OECD, 2001), indicating that better fertiliser use could be achieved through appropriate management. Nutrient management (single versus split application, timing), appropriate crop rotation (introducing nitrogen fixing crop in the crop sequence) are among the various options available to reduce the amount of nitrogen lost to the environment. This paper presents a tiered approach for addressing nutrient fate at various scales that makes best use of readily available data at EU level taking into account the policy requirements of various Directives. Firstly (tier 1) a statistical approach (Grizzetti et al., 2005) is used at large-river basin to identify areas with highest nutrient losses. In a subsequent step (tier 2), the physically-based SWAT (Arnold et al., 1998) model is used to identify within those areas, the major processes and pathways controlling and contributing to nutrient losses. The third step (tier 3) involves the use of the farm-scale model EPIC (William, 1995) to elaborate appropriate farming practices that could reduce pollution load without endangering the farm economic sustainability. The last step consists in field measurement to validate the results of the farm scale model. This paper will focus primarily on steps 1 and 3. The statistical tool is used to calculate the diffuse emission of nitrogen for Italy. EPIC is then used to illustrate the potential impact of nutrient management on nitrogen leaching. The field work was performed in the context of the Pavia Project (Cenci et al., 2006) in the area of Pavia to study the effect of various farming practices including traditional farming, organic farming, and sludge-application type of farming on nitrogen cycling
and leaching. However, the results are still under analysis. The paper will present only the modelling results. 2. Materials and methods 2.1 Modelling Approach 2.1.1 STATISTICAL MODEL The statistical modelling approach consists of a simplified conceptual model, considering two different pathways in nutrient transfer from sources to the catchment outlet. Diffuse sources (DS), include applied fertiliser (artificial and manure), atmospheric deposition, and scattered dwellings, are first reduced in the soil and then retained partially in the streams, while point sources (PS) which include discharges from sewers, waste water treatment plants, industries, and paved areas are only retained in the streams (Grizzetti et al., 2005). 2.1.2 EPIC MODEL The EPIC (Erosion-Productivity Impact Calculator; Williams et al., 1995) is a field scale model, originally developed to simulate the long-term effects of soil erosion on soil productivity. A nutrient cycling and pesticide fate routines were added later on. The various developments of EPIC are given by Gassman et al. (2005). 2.2 EU Database The data used in this study was derived from a harmonized database developed for EU15. Three major data sets are being used which include a soil map, a land-cover land use map, and a climatic database. Pan- European soil data collected for this research includes the European Soil Bureau Database (ESBD) v1.0, which provides an important source of information for the EC in the monitoring of soil quality, soil organic matter, degradation, contamination, and for assistance in the formation and evaluation of policies towards sustainable agriculture (ESB, 1998). Landover data are available from the Corine (Coordination of information on the environment) database. Meteorological data for the years 1990 to 2003 were obtained from the Monitoring Agriculture and Regional Information Systems (MARS) Unit of the JRC. The MARS meteorological database contains daily data spatially interpolated on a 50 km x 50 km grid-cell. In addition, atmospheric N deposition data was derived from the Precipitation Chemistry Database of the Co- EUR 22245 EN (2006) Bio-Bio Project 27 operative Programme for the Monitoring and Evaluation of the Long-Range Transmission of Air Pollutants in Europe (EMEP). Nitrogen and phosphorous input data for both mineral and manure fertiliser was taken at NUTS level 2 from the Capri (Common Agricultural Policy Regional Impact Analysis economic) model (Heckelei and Britz, 2000). 3. Results The tier 1 approach was applied to the whole Italian territory. The map of the diffuse emission is shown in Figure 1. Figure 1. Calculated nitrogen diffuse emission (kg N/ha) for Italy. The highest emission of nitrate occurs in the Po valley, the area of intensive agriculture in Italy. Agriculture is indeed predicted to be the major source of nitrate in the Po River (Figure 2) with local contribution ranging from 50 to 70% of the total nitrogen load. This value is in agreement with the OECD that estimates the contribution of agriculture to total nitrogen loading to be around 60% (OECD, 2001).
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Pavia. In each sites one field was
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3.2 Nematodes 3.2.1 Density and tax
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Rhabditidae. In the biological-mana
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positive aspect must be pondered on
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In summary, the simulations depicte
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Figure 2-Extracted specimens for th
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2.8 AChE evaluation Acetylcholinest
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The Bio-Bio project proposes to com
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The sites were very different in te
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Fertilized management Within fertil
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species. So, the agricultural manag
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Texier C. (1995)- Etat de l’art c
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interfere with restriction endonucl
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similar level of polymorphism was d
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The analysis has been carried out i
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Table 4. Summary of Hazard Quotient
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Klemens EKSCHMITT Justus Liebig Uni
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