A field-scale approach to estimate nitrate loading to groundwater
Citation
Malekani, F., Ryan, M.C., Zebarth, B.J., Loo, S.E., Suchy, M., Cey, E.E. (2018). A field-scale approach to estimate nitrate loading to groundwater. Journal of Environmental Quality, [online] 47(4), 795-804. http://dx.doi.org/10.2134/jeq2017.09.0369
Plain language summary
Nitrate is the most common groundwater contaminant, and agriculture is the primary source of groundwater nitrate contamination. It is important to be able to identify the loading of nitrate from individual fields to groundwater, so that the risk of contamination can be linked to specific agricultural practices, and that strategies to reduce nitrate contamination can be developed. This study used a novel approach to identify the nitrate loading to groundwater from a single red raspberry field. The method as able to accurately predict the amount of chloride loading to groundwater from a field applied tracer, confirming that the technique was robust. This method was able to quantify the annual loading of nitrate from this individual field, and may be a useful approach for estimating nitrate loading in other aquifers.
Abstract
The quantification of groundwater NO3 loading associated with a specific field or set of management practices so that groundwater quality improvements can be objectively assessed is a major challenge. The magnitude and timing of NO3 export from a single agricultural field under raspberry (Rubus idaeus L.) production were investigated by combining high-resolution groundwater NO3 concentration profiles (sampled using passive diffusion samplers) with Darcy's flux estimation at the field's downgradient edge (based on field-measured hydraulic gradients and laboratory-estimated hydraulic conductivity). Annual recharge estimated using Darcy's law (1002 mm) was similar to that obtained using two other approaches. The similarity in the rate of Cl applied to the field and the estimated export flux over the 1-yr monitoring period (51 vs. 56 kg Cl ha-1) suggested the mass flux estimation approach was robust. An estimated 80 kg NO3-N ha-1 was exported from the agricultural field over the 1-yr monitoring period. The greatest monthly groundwater mass flux exported was observed in February and March (~11 kg NO3-N ha-1), and was associated with NO3 leached from the soil zone during the onset of precipitation in the previous autumn. Provided the groundwater recharged from the field of interest can be isolated within a vertical profile, this approach is an effective method for obtaining spatially integrated estimates of the magnitude and timing of NO3 - loading to groundwater.