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      Statistical assessment of nonpoint source pollution in agricultural watersheds in the Lower Grand River watershed, MO, USA

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          Abstract

          The water quality in many Midwestern streams and lakes is negatively impacted by agricultural activities. Although the agricultural inputs that degrade water quality are well known, the impact of these inputs varies as a function of geologic and topographic parameters. To better understand how a range of land use, geologic, and topographic factors affect water quality in Midwestern watersheds, we sampled surface water quality parameters, including nitrate, phosphate, dissolved oxygen, turbidity, bacteria, pH, specific conductance, temperature, and biotic index (BI) in 35 independent sub-watersheds within the Lower Grand River Watershed in northern Missouri. For each sub-watershed, the land use/land cover, soil texture, depth to bedrock, depth to the water table, recent precipitation area, total stream length, watershed shape/relief ratio, topographic complexity, mean elevation, and slope were determined. Water quality sampling was conducted twice: in the spring and in the late summer/early fall. A pairwise comparison of water quality parameters acquired in the fall and spring showed that each of these factors varies considerably with season, suggesting that the timing is critical when comparing water quality indicators. Correlation analysis between water quality indicators and watershed characteristics revealed that both geologic and land use characteristics correlated significantly with water quality parameters. The water quality index had the highest correlation with the biotic index during the spring, implying that the lower water quality conditions observed in the spring might be more representative of the longer-term water quality conditions in these watersheds than the higher quality conditions observed in the fall. An assessment of macroinvertebrates indicated that the biotic index was primarily influenced by nutrient loading due to excessive amounts of phosphorus (P) and nitrogen (N) discharge from agricultural land uses. The PCA analysis found a correlation between turbidity, E. coli, and BI, suggesting that livestock grazing may adversely affect the water quality in this watershed. Moreover, this analysis found that N, P, and SC contribute greatly to the observed water quality variability. The results of this study can be used to improve decision-making strategies to improve water quality for the entire river basin.

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          Most cited references 52

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          Modeling the relationship between land use and surface water quality

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            Rapid Field Assessment of Organic Pollution with a Family-Level Biotic Index

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              A Biotic Index for the Southeastern United States: Derivation and List of Tolerance Values, with Criteria for Assigning Water-Quality Ratings

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                Author and article information

                Contributors
                fkj5gd@mst.edu
                Journal
                Environ Sci Pollut Res Int
                Environ Sci Pollut Res Int
                Environmental Science and Pollution Research International
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                0944-1344
                1614-7499
                14 November 2018
                14 November 2018
                2019
                : 26
                : 2
                : 1487-1506
                Affiliations
                [1 ]ISNI 0000 0000 9364 6281, GRID grid.260128.f, Department of Geosciences and Geological and Petroleum Engineering, , Missouri University of Science and Technology, ; McNutt Hall, 1400 N. Bishop Ave, Rolla, MO 65401 USA
                [2 ]ISNI 0000 0004 1788 7058, GRID grid.449919.8, College of Science, , University of Misan, ; Amarah, Iraq
                Author notes

                Responsible editor: Philippe Garrigues

                Article
                3682
                10.1007/s11356-018-3682-7
                6331747
                30430446
                © The Author(s) 2018

                Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

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                Research Article
                Custom metadata
                © Springer-Verlag GmbH Germany, part of Springer Nature 2019

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