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Section 1: Publication
Publication Type
Journal Article
Authorship
Costa D., Liu J., Roste J., Elliott J
Title
Temporal Dynamics of Snowmelt Nutrient Release from Snow–Plant Residue Mixtures: An Experimental Analysis and Mathematical Model Development
Year
2019
Publication Outlet
Journal of Environmental Quality
DOI
ISBN
ISSN
Citation
Costa D, Liu J, Roste J, Elliott J. Temporal Dynamics of Snowmelt Nutrient Release from Snow–Plant Residue Mixtures: An Experimental Analysis and Mathematical Model Development. J Environ Qual. 2019 Jul;48(4):869-879. doi: 10.2134/jeq2018.12.0440. PMID: 31589691.
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.
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