Optimizing farmyard manure and cattle slurry applications for intensively managed grasslands based on UK-DNDC model simulations

Abstract

Fertilizer applications can enhance soil fertility, pasture growth and thereby increase production. Nitrogen fertilizer has, however, been identified as a significant source of nitrous oxide (N2O) emissions from agriculture if not used correctly and can thereby increase the environmental damage costs associated with agricultural production. The optimum use of organic fertilizers requires an improved understanding of nutrient cycles and their controls. Against this context, the objective of this research was to evaluate the scope for reducing N2O emissions from grassland using a number of manure management practices including more frequent applications of smaller doses and different methods of application. We used a modified UK-DNDC model and N2O emissions from grasslands at Pwllpeiran (PW), UK during the calibration period in autumn, were 1.35 kg N/ha/y (cattle slurry) and 0.95 kg N/ha/y (farmyard manure), and 2.31 kg N/ha/y (cattle slurry) and 1.08 kg N/ha/y (farmyard manure) during validation period in spring, compared to 1.43 kg N/ha/y (cattle slurry) and 0.29 kg N/ha/y (farmyard manure) during spring at North Wyke (NW), UK. The modelling results suggested that the time period between fertilizing and sampling (TPFA), rainfall and the daily average air temperature are key factors for N2O emissions. Also, the emission factor (EF) varies spatio-temporally (0–2%) compared to uniform 1% EF assumption of IPCC. Predicted N2O emissions were positively and linearly (R2 ≈ 1) related with N loadings under all scenarios. During the scenario analysis, the use of high frequency, low dose fertilizer applications compared to a single one off application was predicted to reduce N2O peak fluxes and overall emissions for cattle slurry during the autumn and spring seasons at the PW and NW experimental sites by 17% and 15%, respectively. These results demonstrated that an optimized application regime using outputs from the modelling approach is a promising tool for supporting environmentally-friendly precision agriculture.