Temporal Dynamics of Snowmelt Nutrient Release from Snow–Plant Residue Mixtures: An Experimental Analysis and Mathematical Model Development

Diogo Costa, Jian Liu, Jennifer Roste, J. G. Elliott


Abstract
Reducing eutrophication in surface water is a major environmental challenge in many countries around the world. In cold Canadian prairie agricultural regions, part of the eutrophication challenge arises during spring snowmelt when a significant portion of the total annual nutrient export occurs, and plant residues can act as a nutrient source instead of a sink. Although the total mass of nutrients released from various crop residues has been studied before, little research has been conducted to capture fine-timescale temporal dynamics of nutrient leaching from plant residues, and the processes have not been represented in water quality models. In this study, we measured the dynamics of P and N release from a cold-hardy perennial plant species, alfalfa ( L.), to meltwater after freeze-thaw through a controlled snowmelt experiment. Various winter conditions were simulated by exposing alfalfa residues to different numbers of freeze-thaw cycles (FTCs) of uniform magnitude prior to snowmelt. The monitored P and N dynamics showed that most nutrients were released during the initial stages of snowmelt (first 5 h) and that the magnitude of nutrient release was affected by the number of FTCs. A threshold of five FTCs was identified for a greater nutrient release, with plant residue contributing between 0.29 (NO) and 9 (PO) times more nutrients than snow. The monitored temporal dynamics of nutrient release were used to develop the first process-based predictive model controlled by three potentially measurable parameters that can be integrated into catchment water quality models to improve nutrient transport simulations during snowmelt.
Cite:
Diogo Costa, Jian Liu, Jennifer Roste, and J. G. Elliott. 2019. Temporal Dynamics of Snowmelt Nutrient Release from Snow–Plant Residue Mixtures: An Experimental Analysis and Mathematical Model Development. Journal of Environmental Quality, Volume 48, Issue 4, 48(4):869–879.
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