Influence of Natural Factors on the Quality of Midwestern Streams and Rivers

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Influence of Natural Factors on the Quality of Midwestern Streams and Rivers Influence of Natural Factors on the Quality of Midwestern Streams and Rivers —Stephen D. Porter, Mitchell A. Harris, and Stephen J. Kalkhoff Streams flowing through cropland in the Midwestern Corn Belt differ considerably in their chemical and ecological characteristics, even though agricultural land use is highly intensive throughout the entire region. These differences likely are attributable to differences in riparian vegetation, soil properties, and hydrology. This conclusion is based on results from a study of the upper Contents Midwest region conducted during seasonally low-flow conditions in Introduction. 1 August 1997 by the U.S. Geological Natural Factors Influence Chemical Indicators Survey (USGS) National Water of Water Quality . 4 Quality Assessment (NAWQA) Natural Factors Influence Biological Indicators Program. This report summarizes of Water Quality . 8 significant results from the study and presents some implications for the Implications for Water-Quality Monitoring and design and interpretation of water- Assessment . 12 quality monitoring and assessment References Cited . 13 studies based on these results. Introduction The U.S. Geological Survey percentage of trees in buffer zones (USGS) National Water-Quality along riparian segments. Census data The Midwestern Corn Belt is Assessment (NAWQA) Program from the U.S. Department of Agri- one of the most productive agricul- conducted a water-quality study in culture (USDA) for 1997 were used tural regions in the world. Nearly the upper Midwest region during in this study to quantify cropland, 80 percent of the Nation’s corn and seasonally low-flow conditions in livestock, and chemical application soybeans is grown in the region. August 1997. Chemical and biologi- in each basin. A complete descrip- More than 6 million metric tons cal samples were collected from 70 tion of the study design, methods, of nitrogen fertilizer and over streams and rivers in the Minnesota, and data can be found in Sorenson 100,000 metric tons of pesticides are Wapsipinicon, Cedar, Iowa, Skunk, and others (1999). This report sum- applied to cropland in the Midwest and lower Illinois River basins of marizes significant results from the annually (Goolsby and others, southern Minnesota, eastern Iowa, study and presents some implica- 1993). The 1997 growing season and western Illinois (fig. 1). Sam- tions for the design and interpreta- produced the largest soybean crop pling locations were chosen to tion of water-quality monitoring and and second-largest corn crop represent a range of soil-drainage assessment studies based on these recorded in the Midwest. conditions in stream basins and the results. Area of map 95° 90° 3.5 50° 3.0 WESTERN LAKE Minnesota 2.5 River Basin BASE (STATSGO) SCORE MINNESOTA STATE SOIL GEOGRAPHIC DATA 2.0 Lake Western Till Plains Dissected Southern extent of Till Plains Wisconsinan PHYSIOGRAPHIC SECTION Minneapolis glacial advance M in ne so ta Ri ver M is s i s s i p p i WISCONSIN R 45° i v e r Eastern Iowa W a Basins p s i p in ic on R iv Chicago er ILLINOIS Cedar River IOWA Io wa River DISSECTED TILL PLAINS S kunk R. EXPLANATION Soil hydrologic group classification r of stream basins e v Ri is Moderately well drained soils o n i l 40° l Poorly drained soils I Very poorly drained soils TILL MISSOURI PLAINS 0 100 MILES 0 100 KILOMETERS Lower Illinois River Basin Figure 1. Soil drainage in basins for the 70 streams and rivers sampled during August 1997 varied from very poor in the Western Lake physiographic section to moderately well drained in the Dissected Till Plains section. 2 best management practice. These “riparian buffer zones” are thought to intercept runoff of sediment and chemicals from fields, promote bank stability, and provide shading and habitat for aquatic life (Osborne and Kovacic, 1993). For this study, riparian vegetation density, referred to hereinafter as “tree density,” was determined at two spatial scales: segment and reach. At the segment scale, tree density was classified based on the percentage of trees in a 100-meter-wide zone on each side of the stream for a distance of 2 to 3 miles upstream from the sam- pling location (Sorenson and others, 1999). Tree density was considered Differences in landscape terrain depth to water table, and related “low” if 35 percent or less of the and soil characteristics among drain- characteristics. Stream basins with area was forested and “high” if more age basins in the upper Midwest STATSGO scores of 2.6 or less than 35 percent was forested. At region are associated with historical were characterized as having “mod- the reach scale (refer to Fitzpatrick patterns of glacial advance and erately well drained” soils; basins and others, 1998), tree density retreat. The spatial distribution of with scores exceeding 2.6, “poorly was the percentage of the land sur- soils corresponds generally with drained;” and basins with scores face covered by trees in replicate physiographic sections (Fenneman exceeding 3.0, “very poorly 20-square-meter vegetation plots and Johnson, 1946) in the upper drained” (fig. 1). along transects at the sampling loca- Midwest region (fig. 1). For exam- ple, soils generally are moderately Resource agencies such as the tion (Sorenson and others, 1999). well drained in the Dissected Till USDA encourage maintenance of Tree density was considered low if Plains section of eastern Iowa, and strips of trees or grass between the percentage was less than 5 and the proportion of stream water that is agricultural fields and streams as a high if 5 percent or more. derived from ground-water inflow is substantially greater than in adjacent sections (Winter and others, 1998). In contrast, soils with poor drainage, high runoff potential, and relatively higher organic nitrogen content are found in the Western Lake section of southern Minnesota and northern Iowa. Agricultural drainage systems (tiles and ditches) are prevalent throughout the study area. The USDA State Soil Geographic data base (STATSGO) was used to calcu- late Soil Hydrologic Group scores for each basin (Sorenson and others, 1999). Soil Hydrologic Groups are classified on the basis of drainage, runoff potential, permeability, 3.
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