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Title:A spatial analysis of phosphorus in the Mississippi River Basin
Author(s):Jacobson, Linda M.
Advisor(s):David, Mark B.
Department / Program:Natural Res & Env Sci
Discipline:Natural Res & Env Sciences
Degree Granting Institution:University of Illinois at Urbana-Champaign
Abstract:Phosphorus (P) in rivers and streams in the Mississippi River Basin (MRB) is a contributing nutrient to hypoxia in the Gulf of Mexico and impacts local water quality. Although nitrogen has been extensively studied and attributed to be the main nutrient causing the Gulf hypoxic zone, P has increasingly been recognized as having more of an effect than was previously thought. The primary inputs of P to rivers and streams are through surface runoff or tile drainage from agricultural fields and from point sources, primarily sewage effluent. The objective of this study was to analyze the spatial pattern of P inputs and outputs in the MRB as they relate to riverine P yields to the Gulf of Mexico and to determine the counties in the MRB that have the highest yields of P and the most critical factors causing this P loss. A database of factors contributing P to the environment was constructed for each county in the MRB from 1997 through 2006 including data on fertilizer application, major crop acreage and harvest, animal numbers for manure inputs and human population. Landscape and climate characteristics of tile drainage, soil characteristics, slope and precipitation were also included. Riverine yields of total P (TP), dissolved reactive P (DRP) and particulate P (PP) for 113 watersheds within the MRB were related to these factors to create multiple regression and spatial error regression models to predict P yields throughout the basin. The fraction of the land planted in crops, sewage effluent P inputs and precipitation were found to best predict TP yields with a spatial error model (R2=0.47). Dissolved reactive P yields were predicted by fertilizer P inputs, sewage effluent P inputs and precipitation in a multiple regression model (R2=0.46), whereas PP yields were explained by crop fraction, sewage effluent P inputs and soil bulk density in a spatial error regression model (R2=0.499). Inputs of P from animal manure were not found to be significant in any model predicting P yields, which contrasts with the results of the USGS SPARROW model. Overall, the Cornbelt region of the upper Midwest, where there is a large amount of cropland and fertilizer application, had the counties with the greatest P yields. This analysis of P in the MRB helps to point out specific areas where P reductions are needed to limit the occurrence of Gulf hypoxia and improve local water quality.
Issue Date:2010-05-19
Rights Information:Copyright 2010 Linda M. Jacobson
Date Available in IDEALS:2010-05-19
Date Deposited:May 2010

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