J.W. Reijs

Use of long-term monitoring data to derive a relationship between nitrogen surplus and nitrate leaching for grassland and arable land on well-drained sandy soils in the Netherlands

The decrease in nitrogen (N) use in agriculture led to improvement of upper groundwater quality in the Sand region of the Netherlands in the 1991–2009 period. However, still half of the farms exceeded the European nitrate standard for groundwater of 50 mg/l in the 2008–2011 period. To assure that farms will comply with the quality standard, an empirical model is used to derive environmentally sound N use standards for sandy soils for different crops and soil drainage conditions. Key parameters in this model are the nitrate-N leaching fractions (NLFs) for arable land and grassland on deep, well-drained sandy soils. NLFs quantify the fraction of the N surplus on the soil balance that leaches from the root zone to groundwater and this fraction represents N available for leaching and denitrification. The aim of this study was to develop a method for calculating these NLFs by using data from a random sample of commercial arable farms and dairy farms that were monitored in the 1991–2009 period. Only mean data per farm were available, which blocked a direct derivation of NLFs for unique combinations of crop type, soil type and natural soil drainage conditions. Results showed that N surplus leached almost completely from the root zone of arable land on the most vulnerable soils, that is, deep, well-drained sandy soils (95% confidence interval of NLF 0.80–0.99), while for grassland only half of the N surplus leached from the root zone of grassland (0.39–0.49). The NLF for grassland decreased with 0.015 units/year, which is postulated to be due to a decreased grazing and increased year-round housing of dairy cows. NLFs are positively correlated with precipitation surplus (0.05 units/100 mm for dairy farms and 0.10 units/100 mm for arable farms). Therefore, an increase in precipitation due to climate change may lead to an increase in leaching of nitrate.

Modeling the Effect of Nutritional Strategies for Dairy Cows on the Composition of Excreta Nitrogen

For an integrated evaluation of the effect of nutritional strategies on the utilization and losses of N at dairy farms, reliable estimates of excreta production and composition are indispensable. An extant, dynamic, mechanistic model of rumen functioning was extended with static equations that describe intestinal digestion to simulate the composition of dairy cow faeces and urine as a function of diet composition. The extended model predicts organic matter (OM), carbon (C) and nitrogen (N) output of both faeces and urine, classified in different components. Total N excretion was partitioned in three fractions based on the C:N ratio of individual components representing their availability of N following manure application to crops, viz. NM (immediately available), NE (easily decomposable) and NR (resistant). Forty nutritional strategies for stall-fed dairy cows, covering diets with a wide range in protein content and OM digestibility, were evaluated. The simulated ranges in faecal and urinary composition were largely in line with values reported in literature. Diet intake and composition had a substantial effect on simulated total N excretion and excreta composition, mainly because of differences in the level of NM excretion and the C:N ratio of the NR fraction. Furthermore, it was shown that the type of OM excreted varies considerably between different diets. A simplified simulation of degradation processes during the first four months of excreta storage produced average values and ranges of slurry characteristics that were in line with values reported in literature. The simulated variation in slurry characteristics suggested a strong variability in ammonia N losses from the slurry pit and a moderate variability in plant availability of slurry N. Further efforts are required to integrate effects of manure storage conditions on the storage processes. In conclusion, the model can be a tool to predict faecal and urinary composition of cattle, and ultimately to improve the utilization of N from field applied manure as well as to evaluate the effects of different nutritional strategies on the whole-farm N balance.