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«International 17 Workshop th Nitrogen The was jointly organised by Teagasc and AFBI Printed by Print Depot Suggested citation Authors, 2012. Title ...»

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1. Background & Objectives Implementation of the Water Framework directive (2000/60EC) has created considerable pressure to lower nutrient losses to waterbodies. The objective of this experiment was to investigate if N concentrations and losses in shallow groundwater (5 m below ground level) on a dairy farm in south Ireland could be correlated with three dairy production systems after migration through a soil with high natural attenuation capacity.

2. Material & Methods The grass-clover based systems were: (i) ES-100N–Early spring calving with 100 kg ha-1of fertilizer N: grazed from February to November and stocked at 2.1 LU ha-1; (ii) ES-0N–Early spring calving without fertilizer N: grazed from February to November and stocked at 1.6 LU ha-1; (iii) LS-0N–Late spring calving without fertilizer N: stocked at 1.7 LU ha-1 between calving and 1st September and then 1.3 LU ha-1 until closing date at the end of January. Each system consisted of 16 plots (1 ha) on a clay-loam (clay 28%) soil with high soil organic C (4.48%) in the upper 0.3 m.

The shallow groundwater monitoring was carried out over two drainage seasons. Five screened piezometers were installed in each plot, 240 piezometers in total. The slotted screen opening interval on the lower 0.2 m of the casing was covered by a filter sock. The annulus between casing and the piezometer wall was grouted with sand and bentonite on the soil surface. Samples were taken fortnightly after purging the piezometers during the main drainage period and after periods of high rainfall during other times of the year. Sampling was conducted 19 and 12 times during drainage seasons 2008-09 and 2009-10, respectively. A 50 ml sample was then taken from each piezometer, bulked to a composite sample per plot and filtered. Total dissolved N (TDN) was measured using a Shimadzu TOC-VCPH analyzer. Total oxidised N (TON), nitrite N (NO2-N) and ammonium N (NH4-N) were analysed on a Thermo Konelab analyser. Nitrate N (NO3--N) was calculated as the difference between TON and NO2--N. Dissolved organic N (DON) was calculated as the difference between TDN and dissolved inorganic N (DIN, NO3-N + NO2-N + NH4-N).

Weather data were recorded at the meteorological station on the farm. Effective rainfall (ER) was calculated using the hybrid grassland model of Schulte et al. (2005) based on poorly drained criterion. Losses of N for each system after natural attenuation during migration through the unsaturated zone were estimated by multiplying the mean N concentrations recorded on the sampling date with the volume of ER between two sampling occasions. The vertical travel time was calculated as Fenton et al. (2011). Concentration variables were subjected to ANOVA as a repeated measure (SAS Institute, 2009) examining the effects of the system, sampling date and all their interactions. Similarly, the annual N losses were subjected to ANOVA as a repeated measure investigating the effect of the system, year and their interactions.

3. Results & Discussion Over the first sampling period, the site received a rainfall of 923 mm of which ER was 728 mm.

The amount of rainfall during the second period was higher (1291 mm) and ER was only slightly different (751 mm). Vertical travel times to the watertable ranged from 0.2 to 0.5 yr-1. Nitrate N was

Nitrogen Workshop 2012

below maximum admissible concentration (MAC) for groundwater (11.3 mg L-1) but DON and NH4+-N were high. Considering the high soil moisture content, heavy texture of the soils and high soil organic C content down to 0.9 m in the soil profile, low NO3--N is likely attributable to soil attenuation processes such dissimilatory NO3- reduction to NH4+ (DNRA) or denitrification which consequently resulted in increased NH4+-N levels. There was a significant two way interaction of system and sampling date at concentrations of DON, TON and NO3--N. In contrast, concentrations of NH4+-N and NO2--N were unaffected by the systems. All N concentrations were independent of weather variables indicating control by soil parameters and biochemical processes rather than by ER. Losses of all N species from the systems buffered by natural soil attenuation are presented in Table 1. Due to high attenuation capacity, NO3--N comprised only a small proportion of the N lost to groundwater and DON and NH4+-N represented 74 and 11% of overall losses, respectively.

–  –  –

4. Conclusion Vertical travel time of approximately a drainage season due to a shallow watertable and high ER allowed correlations between nutrient losses and shallow groundwater nutrient concentrations within a small time lag period. However, the high natural attenuation capacity of the soil due to high C and anaerobic conditions ensured low concentrations of nutrients making correlations difficult. It was hypothesised that any losses from the winter grazing systems were instantaneously reduced by denitrification and DNRA, which consequently resulted in increased NH4+-N levels. For this reason, DON and NH4+-N represented the highest proportion of the N losses from the site presently migrating slowly towards receptors on site.

Acknowledgement This study was funded by the Department of Agriculture, Fisheries and Food (RSF07-511) References Directive 2000 ⁄ 60 ⁄ EC establishing a framework for community action in the field of water policy. Official Journal of the European Union, L 327, 1–73.





Fenton, O., Schulte, R.P.O., Jordan, P., Lalor, S. and Richards, K.G. 2011. Time lag: a methodology for the estimation of vertical and horizontal travel & flushing timescales to nitrate threshold concentrations in Irish aquifers.

Environmental Science & Policy 14, 419-431 Schulte, R.P.O., Diamond, J. Finkele, K,.Holden, N.M. and Breton, A.J. 2005. Predicting the soil moisture conditions of Irish grasslands. Irish Journal of Agricultural and Food Research 44, 95-110

Nitrogen Workshop 2012

Effect of ploughing and reseeding of permanent grassland on N leaching to groundwater and nitrous oxide emissions from a clay-loam soil Necpalova, M.a,b, Casey, I.b, Humphreys, J.a a Animal and Grassland Research and Innovation Centre, Teagasc Moorepark, Fermoy, Co Cork, Rep of Ireland b Department of Chemical and Life Sciences, Waterford Institute of Technology Cork Road, Waterford, Rep of Ireland

1. Background & Objectives Implementation of the Water Framework Directive (2000/60EC) and the Kyoto protocol in Ireland has constrained farmers to lower nitrogen (N) fluxes to the environment. Cultivation of permanent grassland increases the rate of mineralization of soil organic matter and thus promotes N losses via leaching and denitrification. The objective of this study was to examine the effect of ploughing and reseeding of permanent grassland on (i) N leaching to shallow groundwater (5 m below ground level) over two drainage seasons (Aug 2008-Feb 2010); and (ii) nitrous oxide (N2O) emissions over a year (Jan 2009-Dec 2009) on a dairy farm in southern Ireland.

2. Material & Methods The treatments were: (i) permanent grassland [PG] and (ii) ploughed and reseeded grassland [RG] on a clay-loam soil (28% clay) with high N (0.48%) in the top 0.3 m; replicated 18 and 4 times for leaching and denitrification experiments, respectively. The RG was introduced in June 2008. Five screened piezometers were installed in each plot (1 ha), 180 piezometers in total. The slotted screen opening interval on the lower 0.2 m of the casing was covered by a filter sock. The annulus between the casing and the piezometer wall was grouted with sand and bentonite on the soil surface.

Groundwater samples were taken fortnightly after purging the piezometers during the main drainage period and after periods of high rainfall during other times of the year. Sampling was conducted 19 and 12 times during the drainage seasons 2008-09 and 2009-10, respectively. A 50 ml sample was then taken from each piezometer, bulked to a composite sample per plot and filtered. Total dissolved N (TDN) was measured using a Shimadzu TOC-VCPH analyzer. Total oxidised N (TON), nitrite N (NO2-N) and ammonium N (NH4-N) were analysed on a Thermo Konelab analyser. Nitrate N (NO3--N) was calculated as the difference between TON and NO2--N. Dissolved organic N (DON) was calculated as the difference between TDN and dissolved inorganic N (DIN, NO3-N + NO2-N + NH4-N). Weather data were recorded at the meteorological station on the farm.

Effective rainfall (ER) was calculated using the hybrid grassland model of Schulte et al. (2005) based on the poorly drained criterion. Losses of N for each treatment after natural attenuation during migration through the unsaturated zone were estimated by multiplying the mean N concentrations recorded on the sampling date with the volume of ER between two sampling occasions. The N2O fluxes were measured fortnightly using a static chamber technique; in total 22 times. On each sampling day, ten iron chambers (diameter =11.5 cm, height = 14.5 cm) per plot were driven into the soil to a depth of 0.01 m randomly across each plot. Headspace gas samples were taken after 20 minutes incubation, and transferred to 7 ml pre-evacuated septum-sealed screwcapped glass vials using a 25 ml polypropylene syringe. At the same time two background gas samples were taken from each plot. Gas samples were analyzed using a gas chromatograph (Varian GC 450; The Netherlands) fitted with an electron capture detector at 300°C and automatic sampler.

Hourly N2O fluxes for each chamber were estimated from the slope of the linear increase between background level and concentration after incubation. All N concentrations and N2O fluxes were subjected to ANOVA as a repeated measure (SAS Institute, 2009) examining the effects of cultivation, sampling date and their interaction. Similarly, the annual losses were subjected to ANOVA as a repeated measure investigating the effect of cultivation, year and their interaction.

3. Results & Discussion The ER during the first and second sampling periods was 728 and 751 mm, respectively. All concentrations of N species in shallow groundwater exhibited high temporal variation (P0.001).

Cultivation increased concentrations of TON, NO3--N, NO2-N (P0.0001) and C:N ratio (P0.05) as a result of accelerated mineralisation of soil organic matter. The DON was affected by two way interaction between cultivation and sampling date (P0.05) and NH4-N was not affected by ploughing. Annual losses of oxidised N species buffered by natural soil attenuation were affected by interaction between cultivation and year (P0.05). This indicated that the increase in TON leaching was more pronounced during first year after cultivation (Table 1). Since ER caused similar recharge during both sampling periods, year to year variation in the DON (P0.0001) and NH4-N (0.05) losses may be caused by enhanced mineralization of dissolved organic matter to NH4-N in the second year. Cultivation also increased N2O emissions (P0.001). The instantaneous fluxes ranged between -72 to 382 μg N2O m-2 h-1 from PG and between -72 to 788 μg N2O m-2 h-1 from RG (Fig.1) and the annual fluxes of N2O from PG and RG were 1.32 ± 3.90 and 2.49 ± 6.04 kg N ha-1.

permanent N2O flux (ug m-2h-2)

–  –  –

4. Conclusion Ploughing and reseeding of PG increased TON leaching and N2O emissions from the soil surface;

however, the overall N losses were quite low. Due to high soil organic C and anaerobic status of heavy textured soils on site, it was assumed that N losses caused by cultivation were reduced by complete denitrification and consequently resulted in molecular N emissions.

Acknowledgement This study was funded by the Department of Agriculture, Fisheries and Food (RSF07-511) References Directive 2000 ⁄ 60 ⁄ EC establishing a framework for community action in the field of water policy. Official Journal of the European Union, L 327, 1–73.

Schulte, R.P.O,.Diamond, J., Finkele, K,.Holden, N.M. and Breton, A.J. 2005. Predicting the soil moisture conditions of Irish grasslands. Irish Journal of Agricultural and Food Research 44, 95-110

Nitrogen Workshop 2012

Evaluating innovative farming systems to limit nitrogen diffuse pollution in catchments:

development and application of the CASIMOD’N model Durand, P.a,b,Moreau, P.a,b, Baratte, C.d,b, Faverdin, P.d,b, Gascuel-Odoux, C. a,b, Ramat, E.c, Ruiz, L. a,b, Salmon-Monviola, J.a,b, a INRA, UMR1069 Sol Agro et hydrosystème Spatialisation, F-35000 Rennes, France b Agrocampus Ouest, UMR1069 Sol Agro et hydrosystème Spatialisation, F-35000 Rennes, France c ULCO, UPRES EA 4029 Laboratoire d’Informatique du Littoral, F-62228 Calais, France d INRA, UMR1080 Production du Lait, F-35590 St-Gilles, France

1. Background & Objectives The European Union (EU) states that all water bodies need to recover a “good and nondeteriorating” ecological status by 2015. The catchment is the scale where both (i) the impacts of nitrogen diffuse pollution from agriculture are visible and (ii) the territorial policies are discussed and implemented. On the other hand, the farming system is the scale where management practices are decided by the farmers. The farming system can be defined as a combination of the anthropogenic decision system and the biotechnical system (Gouttenoire et al., 2010). The management practices express and materialize the farmer decisions which can be modulated by the feedbacks from the biotechnical system. Integrating farm and catchment scales and the interactions between decisional, biotechnical and biophysical systems can provide powerful tools to build and evaluate innovative farming systems aiming at reducing nitrogen losses. The objective of this paper is to present the newly-developed integrative tool CASIMOD’N (Catchment and Agricultural System Integrated MODel for Nitrogen). Its validation and application on a 60 km² catchment, in which cattle production dominates, will be discussed.



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