Statistical analysis to characterize transport of nutrients in groundwater near an abandoned feedlot

Surface water from a lagoon and groundwater samples from 17 wells within and near an abandoned feedlot in northwestern Minnesota, USA, were analyzed for carbon, nutrients, and field parameters. The feedlot is surrounded by wetlands that act as receptors of nutrients from the feedlot. Q- and R-mode m...

Full description

Bibliographic Details
Main Authors: P. Gbolo, P. Gerla
Format: Article
Language:English
Published: Copernicus Publications 2013-12-01
Series:Hydrology and Earth System Sciences
Online Access:http://www.hydrol-earth-syst-sci.net/17/4897/2013/hess-17-4897-2013.pdf
Description
Summary:Surface water from a lagoon and groundwater samples from 17 wells within and near an abandoned feedlot in northwestern Minnesota, USA, were analyzed for carbon, nutrients, and field parameters. The feedlot is surrounded by wetlands that act as receptors of nutrients from the feedlot. Q- and R-mode multivariate analyses performed on total carbon (TC), inorganic carbon (IC), total organic carbon (TOC), nitrite-nitrogen (NO<sub>2</sub>-N), nitrate-nitrogen (NO<sub>3</sub>-N), ammonium-nitrogen (NH<sub>4</sub>-N), soluble or dissolved reactive phosphorus (DRP), and total phosphorus (TP) indicated three groups of the chemical species, which reflected variability in groundwater chemistry. Factor analysis indicated approximately 82% of the variability in factor 1 was caused by TC, IC, TOC, and DRP, while in factor 2 approximately 79% of the variability was caused by NO<sub>2</sub>-N, NO<sub>3</sub>-N, and TP. In factor 3, only NH<sub>4</sub>-N contributed 31% of the variability. Groundwater isotope and spatial distribution analysis indicated reduced nitrate concentration from the source to the wetlands, with variation in NO<sub>2</sub>-N, NO<sub>3</sub>-N, and NH<sub>4</sub>-N concentrations attributed to the plant nutrient uptake, high rate of denitrification and/or the dissimilatory nitrate reduction to ammonium. This study indicated the value of multivariate analyses in characterizing variability in groundwater quality.
ISSN:1027-5606
1607-7938