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Assessing nitrogen fluxes from dairy farms using a modelling approach: A case study in the Moe River catchment, Victoria, Australia

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  • Thayalakumaran, T.
  • Roberts, A.
  • Beverly, C.
  • Vigiak, O.
  • Norng, S.
  • Stott, K.

Abstract

Assessment of nitrogen (N) loss forms and pathways from farming systems is important for improved understanding of potential off-farm impacts on high value environmental assets. The objective of this study was to estimate N losses in different pathways in dairy systems across the range of climate, soil and farm management by using west Gippsland (Victoria, Australia) as case study area, and to characterise the sensitivity of the adopted model parameters. We combined the point scale models DairyMod and Howleaky to estimate dissolved N (DN) and particulate N (PN) loads in runoff, and N leaching (LN) in deep drainage from representative dairy farms in west Gippsland. Monte Carlo error propagation with Latin hypercube sampling was performed to identify sensitive model parameters and assess potential uncertainty in N load predictions. The combined model was capable of simulating climate-soil-animal-pasture management interactions and estimating DN, PN and LN at an annual scale; which were estimated at up to 18kg-Nha−1, 15kg-Nha−1 and 312kg-Nha−1, respectively. The combined model demonstrated that more intensive feeding as mixed ration, and nutrient budgeting that takes into account the fertiliser equivalent of recycled nutrients can achieve an increase in milk production by up to 13% and a decrease in N loads by up to 31% compared to the intensive system in the case study catchment. Soil type and farm management explained much of the variability (up to 76%) observed in LN and DN loads, whereas climate and soil type had significant influence on PN loads (62–77%). Year-to-year variation, particularly under dry conditions had a marked influence on N loads. Soil N, vegetation cover, rooting depth and soil maximum drainage rate must be well characterised in order to reduce potentially high uncertainty in the estimation of N losses in heterogeneous catchments.

Suggested Citation

  • Thayalakumaran, T. & Roberts, A. & Beverly, C. & Vigiak, O. & Norng, S. & Stott, K., 2016. "Assessing nitrogen fluxes from dairy farms using a modelling approach: A case study in the Moe River catchment, Victoria, Australia," Agricultural Water Management, Elsevier, vol. 178(C), pages 37-51.
  • Handle: RePEc:eee:agiwat:v:178:y:2016:i:c:p:37-51
    DOI: 10.1016/j.agwat.2016.09.008
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    References listed on IDEAS

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    1. Barnes, A.P. & Willock, J. & Hall, C. & Toma, L., 2009. "Farmer perspectives and practices regarding water pollution control programmes in Scotland," Agricultural Water Management, Elsevier, vol. 96(12), pages 1715-1722, December.
    2. Graeme J. Doole & David J. Pannell, 2012. "Empirical evaluation of nonpoint pollution policies under agent heterogeneity: regulating intensive dairy production in the Waikato region of New Zealand," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 56(1), pages 82-101, January.
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    4. Cameira, M.R. & Fernando, R.M. & Ahuja, L.R. & Ma, L., 2007. "Using RZWQM to simulate the fate of nitrogen in field soil-crop environment in the Mediterranean region," Agricultural Water Management, Elsevier, vol. 90(1-2), pages 121-136, May.
    5. Smith, Andrew P. & Western, Andrew W., 2013. "Predicting nitrogen dynamics in a dairy farming catchment using systems synthesis modelling," Agricultural Systems, Elsevier, vol. 115(C), pages 144-154.
    6. Payraudeau, Sylvain & van der Werf, Hayo M.G. & Vertes, Francoise, 2007. "Analysis of the uncertainty associated with the estimation of nitrogen losses from farming systems," Agricultural Systems, Elsevier, vol. 94(2), pages 416-430, May.
    7. Bryant, J.R. & Snow, V.O. & Cichota, R. & Jolly, B.H., 2011. "The effect of situational variability in climate and soil, choice of animal type and N fertilisation level on nitrogen leaching from pastoral farming systems around Lake Taupo, New Zealand," Agricultural Systems, Elsevier, vol. 104(3), pages 271-280, March.
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