Water Quality and Habitat Conditions

in Upper Midwest Streams Relative to 

Riparian Vegetation and Soil

Characteristics, August 1997: 

Study Design, Methods, and Data

U.S. Geological Survey

Open-File Report 99–202
U.S. GEOLOGICAL SURVEY

Open-File Report 99–202

Water Quality and Habitat Conditions

in Upper Midwest Streams Relative

to Riparian Vegetation and Soil

Characteristics, August 1997:

Study Design, Methods, and Data

By Stephen K. Sorenson, Stephen D. Porter, Kimberlee K.B. Akers,

Mitchell A. Harris, Stephen J. Kalkhoff, Kathy E. Lee, Linda R. Roberts,

and Paul J. Terrio

Denver, Colorado

1999
U.S. DEPARTMENT OF THE INTERIOR

BRUCE BABBITT, Secretary

U.S. GEOLOGICAL SURVEY

Charles G. Groat, Director

The use of firm, trade, and brand names in this report is for identification purposes only and does

not constitute endorsement by the U.S. Geological Survey.

For additional information write to: Copies of this report can be purchased

U.S. Geological Survey

Information Services

Box 25286

Federal Center

Denver, CO 80225

from:

Regional Hydrologist

U.S. Geological Survey

Box 25046, Mail Stop 406

Denver Federal Center

Denver, CO 80225–0046
CONTENTS III

CONTENTS

Abstract.................................................................................................................................................................................. 1

Introduction............................................................................................................................................................................ 1

Purpose and Scope....................................................................................................................................................... 2

Effects of Agricultural Intensity on Water Quality and Aquatic Life.......................................................................... 2

Effects of Wooded-Riparian Areas on Water Quality and Aquatic Life...................................................................... 3

Effects of Soil Characteristics on Water Quality and Aquatic Life ............................................................................. 5

Hypotheses Concerning Relations Between Stream Quality and Selected Factors..................................................... 5

Acknowledgments ....................................................................................................................................................... 6

Study Design and Methods.................................................................................................................................................... 6

Site Characterization.................................................................................................................................................... 7

Characterization of Wooded-Riparian Zones in Stream Segments.................................................................... 7

Characterization of Soil Drainage in Stream Basins ......................................................................................... 12

Livestock Data ................................................................................................................................................... 12

Population Data ................................................................................................................................................. 12

Rainfall Data...................................................................................................................................................... 16

Agricultural-Chemical Use and Crop Data........................................................................................................ 16

Characterization of Water Quality ............................................................................................................................... 16

Water-Sample Collection ................................................................................................................................... 16

Water-Sample Laboratory Analyses .................................................................................................................. 20

Water Clarity...................................................................................................................................................... 20

Stream Productivity and Respiration ................................................................................................................. 22

Algae.................................................................................................................................................................. 22

Sample Collection.................................................................................................................................... 22

Periphyton Subsampling and Processing................................................................................................. 22

Chlorophyll a and Ash-Free Dry Mass Analyses .................................................................................... 23

Quality-Control Samples ......................................................................................................................... 23

Benthic Invertebrates ......................................................................................................................................... 24

Characterization of Habitat Conditions ....................................................................................................................... 24

Canopy Cover .................................................................................................................................................... 24

Stream-Habitat Conditions ................................................................................................................................ 24

Streambank Characteristics ............................................................................................................................... 25

Riparian-Zone Vegetation .................................................................................................................................. 25

Quality Assurance........................................................................................................................................................ 25

Data........................................................................................................................................................................................ 25

Summary................................................................................................................................................................................ 25

References Cited.................................................................................................................................................................... 26

Appendix................................................................................................................................................................................ 31

FIGURE

1. Locations of 70 sites on Midwestern streams where water quality and habitat conditions were

characterized in August 1997...................................................................................................................................... 8

TABLES

1. Locations and basin characteristics of 70 sites on Midwestern streams and rivers where water quality

and habitat conditions were evaluated in August 1997 ........................................................................................... 9

2. Livestock, nitrogen and phosphorus content of manure, human-population density, and precedent

rainfall conditions.................................................................................................................................................... 13

3. Nitrogen and phosphorus content of manure .......................................................................................................... 16

4. Row-crop production, fertilizer application, and herbicide use .............................................................................. 17
IV CONTENTS

5. Herbicides and herbicide-degradation products analyzed by the U.S. Geological Survey Organic

Geochemistry Research Laboratory, Lawrence, Kansas......................................................................................... 21

6. Basin characteristics, discharge, and selected water-quality properties.................................................................. 33

7. Concentrations of nutrients, organic carbon, chlorophyll a in water samples, and periphyton

chlorophyll and ash-free dry mass .......................................................................................................................... 36

8. Concentrations of triazine herbicides and degradation products ............................................................................ 39

9. Concentrations of chloroacetamide herbicides and degradation products.............................................................. 42

10. Summary of continuous-monitoring data and estimates of stream productivity and respiration............................ 45

11. Average width, depth, velocity, water clarity, and canopy conditions .................................................................... 48

12. Average stream-bottom substrate, bank-stability, and riparian-vegetation cover conditions.................................. 51

CONVERSION FACTORS, ABBREVIATIONS, AND ACRONYMS

Temperature is given in degrees Celsius (°C), which can be converted to degrees Fahrenheit (°F) by the following equation:

°F = 1.8(°C) + 32.

Electrical conductivity is measured as specific electrical conductance in units of

microsiemens per centimeter (μS/cm) at 25 degrees Celsius.

Multiply By To obtain

micrometer (μm) 0.00003937 inch

centimeter (cm) 0.3937 inch

meter (m) 3.281 foot

kilometer (km) 0.6214 mile

square centimeter (cm2) 0.1550 square inch

square meter (m2) 10.76 square foot

cubic meter (m3) 1.308 cubic yards

square kilometer (km2) 0.3861 square mile

cubic meter per second (m3/s) 35.31 cubic feet per second

meters per kilometer (m/km) 5.280 feet per mile

centimeters per second (cm/s) 0.3937 inches per second

gram (g) 0.03527 ounce

milligram 0.00003527 ounce

microgram 0.00000003527 ounce

liter (L) 0.2642 gallon

milliliter (mL) 0.0002642 gallon
Abstract 1

Abstract

Water-chemistry, biological, and habitat

data were collected from 70 sites on Midwestern

streams during August 1997 as part of an integrated, regional water-quality assessment by the

U.S. Geological Survey National Water-Quality

Assessment (NAWQA) Program. The study

area includes the Corn Belt region of southern

Minnesota, eastern Iowa, and west-central

Illinois, one of the most intensive and productive

agricultural regions of the world. The focus of the

study was to evaluate the condition of woodedriparian zones and the influence of basin soildrainage characteristics on water quality and

biological-community responses. This report

includes a description of the study design and

site-characterization process, sample-collection

and processing methods, laboratory methods,

quality-assurance procedures, and summaries

of data on nutrients, herbicides and metabolites,

stream productivity and respiration, biological

communities, habitat conditions, and agriculturalchemical and land-use information.

INTRODUCTION

The Midwestern Corn Belt region of the United

States is one of the most intensive and productive agricultural regions in the world. Nearly 80 percent of the

Nation’s corn and soybeans is grown in the region, and

more than 6 million metric tons of nitrogen fertilizer

and more than 100,000 metric tons of pesticides

are applied to cropland in the Midwest annually

(Goolsby and others, 1993). Intensive use of agricultural chemicals poses potential problems of nonpointsource contamination of surface and ground waters

throughout the Midwest. Results from studies

conducted by the U.S. Geological Survey (USGS)

during the past decade indicate that large amounts

of nutrients and pesticides are flushed from cropland

and transported into tributary streams of major

Midwestern rivers during periods of rainfall in late

spring and early summer (Goolsby and others,

1991; Thurman and others, 1991, 1992; Coupe and

others, 1995; Scribner and others, 1998). Following

seasonal flushes of nutrients, sediments, and

herbicides, concentrations of contaminants in

Midwestern streams and rivers generally decline;

however, relatively little is known about the fate of

herbicide-degradation products during low-flow

conditions. In addition, the overall effects of intense

agricultural activity on biological communities and

their responses to natural landscape factors, such

as differences in surficial geology and soil drainage

among watersheds, and the abundance of woodedriparian vegetation along stream and river corridors

are poorly understood.

The USGS National Water-Quality Assessment

(NAWQA) Program builds upon the existing base

of water-quality studies in the Midwestern Corn Belt

region as part of its overall objectives to describe

water-quality conditions for a large part of the

Nation’s streams, rivers, and aquifers; to describe how

water quality is changing over time; and to improve

understanding of natural and human factors that affect

Water Quality and Habitat Conditions in Upper

Midwest Streams Relative to Riparian Vegetation

and Soil Characteristics, August 1997:

Study Design, Methods, and Data

By Stephen K. Sorenson, Stephen D. Porter, Kimberlee K.B. Akers, Mitchell A. Harris,

Stephen J. Kalkhoff, Kathy E. Lee, Linda R. Roberts, and Paul J. Terrio
2 Water Quality and Habitat Conditions in Upper Midwest Streams Relative to Riparian Vegetation and Soil Characteristics,

August 1997: Study Design, Methods, and Data

water-quality conditions (Hirsch and others, 1988;

Gilliom and others, 1995). Objectives of the NAWQA

Program are accomplished through water-quality

investigations in 59 large river basins and aquifer

systems (study units) throughout the United States,

and synthesis of results on a regional or national

basis.

As a collaborative effort by the Lower Illinois

River Basin (LIRB), Eastern Iowa Basins (EIWA),

and Upper Mississippi River Basin (UMIS) NAWQA

study units, a regional, low-flow synoptic study was

conducted during August 1997. The objectives of the

study were to:

1. Characterize chemical, biological, and habitat conditions at 70 sites on Midwestern streams and rivers

affected by high agricultural intensity during

seasonal low-flow conditions in August 1997.

2. Evaluate water-chemistry conditions and biological

responses in relation to surficial geology and

characteristics of basin soils, wooded-riparian

cover in stream segments, and regional differences in hydrologic conditions.

3. Assess algal-nutrient relations in reference to

stream productivity (“eutrophication”) and

agricultural sources of nutrients and herbicides.

Compare and contrast effects of row-crop agriculture with confined livestock practices (for

example, high-density hog-feeding operations)

on water chemistry and rates of primary productivity. Provide understanding of algal-species and

community responses to nutrients, turbidity,

herbicides, and metabolites.

4. Describe responses of benthic invertebrate communities to agricultural nonpoint sources. Provide

understanding of invertebrate-species responses

to stream eutrophication and physical habitat

conditions in a region of high agricultural

intensity.

Purpose and Scope

This report describes the study design, methods,

and quality assurance for a low-flow synoptic waterquality study conducted during August 1997 in streams

of the Illinois, Skunk, Cedar, Iowa, Wapsipinicon, and

Minnesota River watersheds and summarizes physical,

chemical, biological, and habitat data collected during

the study (objective 1 listed above). The study area

includes parts of west-central Illinois, eastern Iowa, and

southern Minnesota, including all or parts of the LIRB,

EIWA, and UMIS NAWQA study units.

Effects of Agricultural Intensity on

Water Quality and Aquatic Life

The effects of high row-crop intensity in a

stream watershed may include accelerated erosional

and depositional processes, increased water temperature resulting from the removal of riparian trees that

provide canopy shading, reduced dissolved oxygen

(DO) associated with nutrient and organic enrichment,

and toxicity associated with agricultural pesticides,

all of which can reduce or destroy habitat for fish and

other aquatic organisms and alter aquatic communities. Confined livestock operations can cause increases

in nutrient, carbon, and bacterial contamination, as

well as fish kills, in streams if wastes are accidentally

discharged or leach into streams through ground-water

discharge. However, potential adverse effects from

field application of manure slurry on stream quality

are poorly understood.

Agricultural contaminants typically enter

streams from diffuse (nonpoint) sources, such as

runoff from fields during spring and summer precipitation, and from ground-water discharge. Direct (point)

discharges from small wastewater-treatment plants

or agricultural tile drains in agricultural communities

also could contribute to water-quality degradation

during low-flow periods (Osborne and Wiley, 1988;

Wiley and others, 1990).

Excessive loads of nitrogen and phosphorus

in streams and rivers resulting from human activities

frequently result in a degraded water-quality condition

known as cultural eutrophication that is commonly

accompanied by large in-stream growths of algae

or other aquatic plants. Dense growths of algae in

streams and rivers provide visible evidence that the

waters may be polluted, which can reduce the recreational quality of the water resource and impair other

beneficial water uses such as domestic water supplies.

Natural senescence and decomposition of algae, as

well as microbial decomposition of other sources of

organic carbon, can result in the depletion of DO

to levels that cause fish to die from asphyxia. During

active growth, algal processes such as photosynthesis

and nutrient uptake can influence water-quality

dynamics over relatively short periods of time. For

example, diel changes in DO and pH can regulate
INTRODUCTION 3

the partitioning, retention, transport, and bioavailability of contaminants in stream water and bed

sediments (Fuller and Davis, 1989). Algal primary

productivity also can be viewed as a measure of the

ecological health of a stream in relation to the abundance and rate at which food-web resources are being

produced for potential consumption by invertebrates

and fish.

The effects of cultural eutrophication are

best evaluated by integrated evaluation of physical,

chemical, and biological conditions and responses.

The abundance and productivity of algal communities

are positively influenced when nutrient concentrations,

light conditions, velocity, and other factors are favorable. These conditions may be negatively affected

by some physical factors (hydrologic disturbance,

scouring and washout, water turbidity, and canopy

shading), chemical factors (contaminant toxicity),

and biological factors (grazing consumption by

invertebrates and fish, and natural senescence of

algal assemblages) (Stevenson and others, 1996).

Although previous studies frequently have determined

that nutrients are rarely limiting in agricultural streams

of the Midwest (Munn and others, 1989; Wiley

and others, 1990), the availability of light (mediated

by riparian shading and water turbidity) differs among

streams and rivers, resulting in high rates of primary

productivity where light conditions are favorable.

Soil erosion from agricultural fields to streams

could potentially affect algal production negatively by

reducing light availability (high suspended-sediment

concentrations) or positively by increasing the availability of phosphorus associated with suspended

sediments (Stevenson, 1997). However, during

stable hydrologic conditions in summer, relatively

low dissolved-nutrient concentrations have been

measured in Iowa streams and rivers that contained

substantial amounts of suspended algae, as indicated

by phytoplankton chlorophyll a (CHLa) concentrations (data on file at U.S. Geological Survey, Iowa

City, Iowa). Isenhart and Crumpton (1989) documented significant losses of nitrate in Bear Creek,

Iowa, that corresponded with increases in benthicalgal productivity. Thus, the evidence of cultural

eutrophication in Midwestern streams and rivers

during summer low-flow conditions may be indicated

more by algal production than by elevated nutrient

concentrations.

Chemical indicators of eutrophication (for

example, nutrient concentrations) may be revealed

only when in-stream rates of nutrient flux exceed

rates of nutrient uptake by algae or other aquatic plants

in combination with other biogeochemical processes

such as denitrification (Hill, 1983, 1988). Rates of

nutrient uptake by algae are expected to correspond

closely with rates of primary productivity because

nutrient uptake is an active physiological process,

requiring energy derived primarily from photosynthesis. During stable low-flow conditions, nutrients

are temporarily retained [nutrient cycling or spiraling

(Newbold and others, 1982)] in aquatic systems rather

than immediately being transported downstream.

The retention of nutrients by algae or aquatic plants

contributes to the biological health or productivity

of streams and rivers. Water turbidity in streams

with elevated suspended-sediment loads is likely to

limit primary production, adversely affecting the abundance of food resources for higher organisms in those

streams and resulting in greater transport of nutrients

downstream to larger rivers and, eventually, the Gulf

of Mexico.

Differences in soil and riparian-canopy

conditions in watersheds of the Midwest are likely

to influence eutrophication processes in major tributaries to the Mississippi River, as well as eutrophication and hypoxia issues in the Gulf of Mexico.

The Gulf of Mexico hypoxia issues are currently

being addressed by the USGS National Stream

Quality Accounting Network (NASQAN) and

Toxics Hydrology Programs (Battaglin and others,

1997; D.A. Goolsby, U.S. Geological Survey, World

Wide Web URL http://wwwrcolka.cr.usgs.gov/

midconherb/hypoxia.html), as well as many other

investigators (for example, Turner and Rabalais, 1994;

Rabalais and others, 1996). The effects of agriculture

on stream eutrophication could be moderated by the

presence of wooded-riparian areas that serve as buffer

strips to control nutrient and sediment inflows and

provide shading and habitat for aquatic communities.

Soil characteristics of stream basins also may modify

the effects of agricultural activities by influencing

the timing and processes by which nutrients and

sediments enter aquatic systems.

Effects of Wooded-Riparian Areas on

Water Quality and Aquatic Life

Wooded-riparian areas provide beneficial effects

to water quality and aquatic life. In small to midsize

streams, forested riparian zones can moderate water

temperature; reduce inputs of nutrients, herbicides,
4 Water Quality and Habitat Conditions in Upper Midwest Streams Relative to Riparian Vegetation and Soil Characteristics,

August 1997: Study Design, Methods, and Data

and sediment; provide important sources of particulate

organic matter; and stabilize streambanks (Osborne

and Kovacic, 1993). Contaminant movement through

wooded-riparian areas occurs along stream courses

and from land directly adjacent to the stream.

Wooded-riparian buffers serve as a depositional

area for runoff from the adjacent watershed and as

an area of contaminant uptake along streams, rivers,

and wetlands (Mitsch and Gosselink, 1993). Many

nutrients, sediments, and other contaminants that

would otherwise impair aquatic communities are

removed by adsorption and aggradation with sediment, microbial processes (for example, denitrification) as contaminants pass through riparian soils,

or uptake by terrestrial plants. However, the ultimate

fate of nutrients trapped by riparian vegetation is

uncertain. Osborne and Kovacic (1993) reported that

riparian buffer strips acted as nutrient sinks for much

of the growing season but released phosphorus to

shallow ground water during the non-growing season.

Streams in basins with substantial wooded-riparian

areas might be expected to contain higher concentrations of dissolved and suspended organic carbon

than streams without riparian zones. Particulate

and dissolved forms of organic carbon have been

shown to be important sources of energy for benthic

invertebrates (Merritt and Cummins, 1984).

Maintenance or enhancement of existing

wooded-riparian buffer strips between agricultural

fields and streams provides a physical barrier that may

improve water quality and aquatic habitat by reducing

nutrient and sediment inflows (Lowrance and others,

1984; Osborne and Kovacic, 1989; Puckett and others,

1993). Aquatic biological communities may benefit

from wooded-riparian cover because of reduced inputs

of sediments and contaminants to streams, increased

woody habitat within stream channels, moderation of

water-temperature ranges, and a reduction in the diel

variability of pH and DO concentrations associated

with high rates of primary production. However, rates

of herbicide degradation by photolysis and related

processes (Larson and others, 1997) and rates of

benthic primary production may be lower in densely

shaded streams than in streams with sparse riparian

vegetation.

The relative influence of riparian buffer zones

on water quality at local, stream-segment, and basin

scales is known to be variable and is poorly understood. Many studies conducted in small stream watersheds (less than 100 square miles) have concluded that

water chemistry and sediment-related habitat variables

are related closely to forested and agricultural land

cover nearest to the stream (Schlosser and Karr, 1981;

Lowrance and others, 1984; Osborne and Wiley, 1988;

Richards and others, 1996). Other investigators have

suggested that nutrient concentrations, stream habitat,

and biological community structure are strongly

related to land uses in the basin but not to land cover

near stream margins (Omernik and others, 1981; Roth

and others, 1996; Richards and others, 1997). The

relative importance of local- and basin-scale vegetation factors may vary seasonally (Johnson and others,

1997). Seasonal differences in rainfall, runoff, and

metabolic rates of riparian vegetation are likely to

influence timing and rates of contaminant delivery to

streams and the efficiency with which riparian vegetation serves as a contaminant filter.

In contrast, the effects of wooded-riparian

areas on the quality of larger streams and rivers (100-

to 1,000-mi2 drainage basins), as well as the spatial

scale of those effects, are relatively unknown. The

presence of mature riparian forest and dense tree

canopy may exert local (sampling location) control

on the distribution and abundance of benthic organisms and aquatic habitats, whereas riparian conditions

along some larger stream length (segment to basin

scale) are more likely to influence water-quality

processes such as nutrient assimilation, herbicide

degradation, and primary productivity, particularly

during summer low-flow conditions. Longitudinal

(upstream to downstream) changes in wooded-riparian

conditions in Midwestern prairie river systems differ

considerably from those described for other regions of

the United States (for example, the River Continuum

Concept; Vannote and others, 1980). The upper

portions of Midwestern watersheds generally are open

and unforested and dominated by cropland. Riparian

forests eventually develop along the drainage network

but are restricted primarily to the lower half of the

basin (Wiley and others, 1990; aerial observations by

the authors). Previous studies in the Midwest have

demonstrated that small first- to third-order (for

instance, Strahler, 1957) streams generally are

autotrophic; primary production by algae, rather than

inputs of terrestrial leaf detritus, determines energy

flow and food-resource relations in the upper portions

of stream basins. In general, beneficial effects of

wooded-riparian trees, as well as gradients of woodedriparian density, are more likely to occur in larger

fourth- to sixth-order streams and rivers.
INTRODUCTION 5

Effects of Soil Characteristics on

Water Quality and Aquatic Life

Soil permeability influences the delivery

of water and contaminants to streams and affects

runoff and base-flow conditions. Contaminants in

the dissolved phase may reach streams through runoff

or through ground-water discharge into the stream,

depending on soil texture and slope. Particulate forms

of nutrients and contaminants may reach the stream

through adsorption to sediment and transport to the

stream. Areas with well-drained soils may have a

greater potential for inputs of nutrients (Kalkhoff,

1995; Mueller and Helsel, 1996; Jordan and others,

1997) and herbicides (Squillace and others, 1993,

1996; Larson and others, 1997) entering the stream

through ground-water discharge. In contrast, areas

with poorly drained soils have limited ground-water

discharge due to low soil permeability. The poorly

drained soils are more easily eroded, however,

providing more particulate forms of contaminants and

sediments to streams. Agricultural areas with poorly

drained soils typically have tile drains to facilitate

drainage. Because most of the agriculture in this study

area is in areas of moderate to poorly drained soils, tile

drains are present throughout the region. Because tile

drains facilitate drainage from agricultural fields to the

stream, they short-circuit the mitigating effects of

subsurface drainage through riparian soils and buffer

strips and function as point sources of contaminants.

Differences in soil-drainage characteristics in

the upper Mississippi River region are associated with

historical patterns of glacial advance and retreat, as

well as other natural factors such as regional deposits

of loess. For example, soils on the Wisconsin glacial

lobe in north-central Iowa and southern Minnesota

are characterized by fine-grained materials that are

characteristic of prairie-pothole landscapes, whereas

soils in eastern Iowa and western Illinois contain relatively larger proportions of sand and coarser grained

materials in a more riverine terrain. The proportion of

stream water that is derived from ground-water inflow

is substantially less in streams on the Wisconsin lobe

(Winter and others, 1998, fig. B–2) than in streams

located to the southeast of the Wisconsinon glacial

advance. This proportion corresponds with differences, or gradients, in soil-drainage properties

between hydrologic regions.

The characteristics and composition of floodplain deposits and bottom materials in Midwestern

streams reflect soil-drainage properties and alluvial

processes in the drainage basin. Streams draining

basins with coarse well-drained soils frequently have

a well-developed hyporheic zone, the subsurface zone

where stream water flows through short reaches of its

adjacent bed and banks (Hynes, 1983; Winter and

others, 1998). Because of mixing of ground water with

surface water in the hyporheic zone, biogeochemical

processes, such as sorption-desorption and oxidationreduction reactions associated with microbial

processing, may have a significant effect on water

chemistry and biological communities. The interaction

of ground water and surface water in stream basins and

segments is influenced by the interchange of local and

regional ground-water flow systems. Rates of contaminant transport along ground-water flow paths to streams

vary considerably in relation to soil properties, rainfall,

and other factors, and range from several months to

many years. As a result, the influence of agriculture

on ground- and surface-water relations in streams

with sandy alluvial aquifers could reflect historical

fertilizer and herbicide application practices, in addition

to those used during the most recent growing season.

The 1997 growing season produced the largest soybean

crop and second-largest corn crop on record in the

Midwest.

Hypotheses Concerning Relations

Between Stream Quality and

Selected Factors

The following hypotheses were considered in

designing this study:

• Streams in basins with poorly drained soils and

significant wooded-riparian cover are expected to

contain lower concentrations of suspended sediment, nutrients, and other contaminants than

streams with sparse wooded-riparian cover. Algal

productivity is expected to be greater in streams

with low riparian cover, and dissolved-nutrient

concentrations are expected to decrease as stream

productivity increases.

• Riparian buffer zones in basins with moderately

well-drained soils may be less effective in intercepting and removing nutrients and herbicides

washed in from agricultural fields than in basins

with poorly drained soils. Riparian vegetation

may have little effect in reducing contaminant

concentrations discharged from ground-water

sources.
6 Water Quality and Habitat Conditions in Upper Midwest Streams Relative to Riparian Vegetation and Soil Characteristics,

August 1997: Study Design, Methods, and Data

• Ratios of herbicide metabolites (degradation

products) to parent herbicide concentrations in

streams are expected to be greater in watersheds

with significant riparian cover and moderately

well-drained soils than in basins with little

wooded-riparian cover and poorly drained

soils.

• Streams in basins with significant wooded-riparian

cover are expected to have lower rates of primary

production, as indicated by reduced algal biomass,

chlorophyll concentrations, and low diel variability in DO and pH. The abundance of benthic

algae also is expected to decrease as populations

of invertebrate and fish consumers of algae

increase.

• Streams in basins with moderately well-drained

soils and significant wooded-riparian cover

are expected to have more diverse invertebrate

communities, with higher numbers of invertebrate

taxa and higher EPT (mayflies, caddisflies, and

stoneflies) richness than streams in basins with

poorly drained soils and little wooded-riparian

cover.

Acknowledgments

We thank private landowners and public

agencies for permission to access and sample

many of the streams. Substantial assistance was

provided to the design and implementation of habitat

protocols used in this study by Robert Goldstein,

USGS, Minnesota District. The authors also acknowledge the contributions to the study design made by

Jeffrey Stoner and David Mueller of the USGS

NAWQA Nutrients Synthesis Team. Additional

GIS support was provided by David J. Fazio and

Timothy A. Brown in the USGS Illinois District

and Paul Hanson in the USGS Minnesota District.

Field assistance was provided by the following

USGS personnel: Phil Talmage, Joe Stauffer, and

Jesse Anderson (Minnesota District); Kent D. Becher,

Jeffrey J. Copa, Joshua D. Eash, Jeffrey W. Harms,

Patrick D. Lustgraaf, Denise L. Montgomery, and

Patrick E. Sweeney (Iowa District); and Debbie L.

Adolphson, Karen Gao, and Andrew R. Waratuke

(Illinois District). We also acknowledge assistance

in manuscript preparation, cover graphics, and editorial effort provided by Carol Anderson, John Evans,

Joy Monson, and Ed Swibas in the USGS Colorado

District. Linda Britton, Peter Dileanis, and

John Helgesen provided thoughtful technical and

editorial review comments that improved the quality

of this report.

STUDY DESIGN AND METHODS

The study was designed to examine the effects

of wooded-riparian cover on water chemistry and

biological responses in basins (watersheds) with

moderate- and low-permeability soils within a region

of high agricultural intensity. Sites were selected in

each of three NAWQA study units (LIRB, EIWA,

and UMIS) with basin areas in the range of existing

NAWQA agricultural-indicator basic fixed sites

(BFSs), generally larger than 100 mi2 and smaller than

1,000 mi2

. Land-use, land-cover, soils, and ripariantree information were determined using geographic

information system (GIS) procedures to be described

later in this report. All sites selected represent basins

with at least 75 percent of the land area in row-crop

production (corn and soybeans); the average area in

row-crop production among all basins in the study

exceeded 90 percent. All NAWQA agriculturalindicator BFSs in the region were included in the

study, and sites with existing streamflow gages and

minimal urban influence were selected when possible.

Within each study unit, sites were classified into the

following groups:

1. Good Riparian Conditions, Moderately WellDrained Soils—Riparian-tree density greater

than 35 percent within a 100-m buffer along

both banks of the upstream segment, and

more than 50 percent of the basin area in Soil

Hydrologic Groups A or B (moderately welldrained soils; Soil Conservation Service, 1993).

2. Poor Riparian Conditions, Moderately Well-Drained

Soils—Riparian-tree density less than 35 percent

within a 100-m buffer along both banks of the

upstream segment, and more than 50 percent of

the basin area in Soil Hydrologic Groups A or B

(moderately well-drained soils).

3. Good Riparian Conditions, Poorly Drained

Soils—Riparian-tree density greater than

35 percent within a 100-m buffer along both

banks of the upstream segment, and more than

50 percent of the basin area in Soil Hydrologic

Groups C or D (poorly drained soils; Soil

Conservation Service, 1993).
STUDY DESIGN AND METHODS 7

4. Poor Riparian Conditions, Poorly Drained

Soils—Riparian-tree density less than 35 percent

within a 100-m buffer along both banks of the

upstream segment, and more than 50 percent

of the basin area in Soil Hydrologic Groups C

or D (poorly drained soils).

Sites were selected in accordance with a nested

(study units within region) two-factor analysis of

variance design to test whether constituent concentrations or biological conditions differed significantly

between factors or their interactions. Review of

confined animal feeding operation (CAFO) locations

based on State permits revealed that most CAFO

facilities were located in stream basins with poorly

drained soils (Groups 3 and 4). Therefore, the study

design for the effects of confined hog and cattle

operations on the quality of Midwestern streams

is limited to the effects of riparian conditions and

water quality and biological responses to a gradient

of livestock populations resident in different stream

basins. Locations and descriptions of sites are shown

in figure 1 and listed in table 1. Site-classification

variables and study-design groups are listed in

table 1.

Site Characterization

Site characterization was primarily done

using various GIS coverages as outlined in this and

following sections. Stream sites and associated basin

boundaries were located and marked on 7.5-minute

USGS topographic maps. The exact latitude and longitude of the sampling location were obtained by using

the three-point orient function on a digitizing table.

Point coverages, representing discrete sampling locations, were created using values determined for latitude and longitude. Polygon coverages were created

to represent watershed boundaries by digitizing lines

marked on the topographic maps. The drainage-basin

area for each site was calculated from the watershed

boundary polygon coverages. Polygon coverages also

were created to quantify agricultural land uses or

natural landscape features, such as crop acreage or

soil conditions, and were defined by a series of arcs

or lines that form many-sided, closed figures. A label

point inside each polygon was used to assign attributes

to the polygon. Attributes can contain any information

that pertains to the area represented by the polygon.

For example, each basin polygon was identified by an

eight-digit USGS station identification code (table 1).

Characterization of Wooded-Riparian Zones

in Stream Segments

Digital Raster Graphics (DRG) images

(1:24,000 scale) were used to estimate the percentage

of wooded-riparian vegetation within a buffered area

of a stream segment. DRG images are raster images

of scanned USGS topographic maps and are useful

sources or background layers for GIS procedures.

Using the 7.5-minute USGS topographic maps

discussed previously, a segment of stream with adjacent flood-plain areas was digitized for each site. The

length of a “stream segment,” as defined operationally

in this study, ranges from 2 to 3 mi upstream from the

sampling location, corresponding with drainage-basin

areas that range from 100 mi2

 to about 1,000 mi2

(table 1). Automated GIS procedures were developed

for processing the sampling location (point) coverage

and the stream-segment (arc) coverage into a polygon

coverage that represents the stream segment with

length equal to the base-10 logarithm of the basin area,

and riparian buffers of 100 m on both sides of the

stream. The area of the buffered stream segment was

then clipped from the DRG coverage, and the newly

created stream-segment coverage was “cleaned”

of any roads, contour lines, or text that overlaid the

forested area, using an automated GIS procedure. The

percentage of trees (riparian-tree density; table 1) in

each stream segment was calculated as follows:

where

DRT = riparian tree density (percent),

Pf = number of forest pixels in streamsegment area,

PT = number of total pixels in streamsegment area, and

PW = number of water pixels in streamsegment area.

GIS procedures generally were coded in

Arc-Info AML (Environmental Systems Research

Institute, 1992) (procedures on file at U.S. Geological

Survey, Iowa City, Iowa). Subsequent aerial verification and photodocumentation of the stream segments

(September 1997) indicated that, with several exceptions, wooded-riparian conditions had not changed

substantially during the 10 to 20 years that had elapsed

since the preparation of the USGS topographic maps

and DRG images.

DRT

Pf

PT – PW

= -------------------- * 100
8 Water Quality and Habitat Conditions in Upper Midwest Streams Relative to Riparian Vegetation and Soil Characteristics,

August 1997: Study Design, Methods, and Data

0 100 150 KILOMETERS 50

0 100 150 MILES 50

Figure 1. Locations of 70 sites on Midwestern streams where water quality and habitat conditions were characterized

in August 1997.
STUDY DESIGN AND METHODS 9

Table 1. Locations and basin characteristics of 70 sites on Midwestern streams and rivers where water quality and habitat conditions we

August 1997

[°, degrees; ', minutes; '', seconds; STATSGO, Soil Conservation Service Soil Hydrologic Group]

Site

number

U.S. Geological

Survey station

identification

Site name Latitude Longitude

Basin

area

(mi2)

STATSGO

score1

L01 05554000 North Fork Vermilion River near Charlotte, Illinois 40°50'08'' 88°17'58'' 186 3.20 

L02 05554490 Vermilion River at McDowell, Illinois 40°49'50'' 88°34'29'' 551 3.20 

L03 05556500 Big Bureau Creek at Princeton, Illinois 41°21'55'' 89°29'55'' 196 2.40 

L04 05559500 Crow Creek near Washburn, Illinois 40°57'15'' 89°18'30'' 115 2.80 

L05 05563000 Kickapoo Creek near Kickapoo, Illinois 40°48'00'' 89°48'00'' 119 2.60 

L06 05564300 Mackinaw River near Kappa, Illinois 40°40'46'' 88°56'26'' 309 2.70 

L07 05567500 Mackinaw River near Congerville, Illinois 40°37'25'' 89°14'30'' 767 2.70 

L08 05568830 Spoon River at Elmore, Illinois 40°57'25'' 89°58'34'' 432 2.60 

L09 05569875 Cedar Creek near Avon, Illinois 40°41'25'' 90°25'15'' 271 2.50 

L10 05570910 Sangamon River at Fisher, Illinois 40°18'40'' 88°19'20'' 240 2.90 

L12 05575850 Horse Creek at Springfield, Illinois 39°41'46'' 89°34'21'' 129 2.80 

L15 05580000 Kickapoo Creek at Waynesville, Illinois 40°15'20'' 89°07'40'' 227 2.60 

L16 05583900 Sugar Creek near Ray, Illinois 40°11'45'' 90°27'16'' 118 2.60 

L17 05584500 La Moine River at Colmar, Illinois 40°19'45'' 90°53'55'' 655 2.60 

L18 05585800 McKee Creek near Versailles, Illinois 39°52'47'' 90°45'32'' 306 2.60 

L19 05586598 Apple Creek at Highway 900E near Haypress, Illinois 39°22'11'' 90°32'46'' 385 2.50 

L20 05586645 Macoupin Creek near Carlinville, Illinois 39°18'16'' 89°47'15'' 132 2.90 

L21 05587000 Macoupin Creek near Kane, Illinois 39°14'03'' 90°23'40'' 868 2.70 

L22 05567000 Panther Creek near El Paso, Illinois 40°46'05'' 89°04'30'' 93.9 2.90 

L23 05568000 Mackinaw River near Green Valley, Illinois 40°27'15'' 89°36'22'' 1,070 2.60 

L24 05568800 Indian Creek near Wyoming, Illinois 41°01'06'' 89°50'07'' 62.7 2.60 

I01 05451210 South Fork Iowa River near New Providence, Iowa 42°18'54'' 93°04'22'' 224 2.97 

I02 05469980 South Skunk River near Story City, Iowa 42°08'14'' 93°34'02'' 214 2.83 

I03 05420680 Wapsipinicon River near Tripoli, Iowa 42°50'10'' 92°15'26'' 346 2.51 

I04 05456510 Turtle Creek at Austin, Minnesota 43°40'25'' 93°01'11'' 153 2.93 

I05 05449500 Iowa River near Rowan, Iowa 42°45'36'' 93°37'23'' 418 2.98 
10 Water Quality and Habitat Conditions in Upper Midwest Streams Relative to Riparian Vegetation and Soil Characteristics,

August 1997: Study Design, Methods, and Data I06 05462770 Beaver Creek near Parkersburg, Iowa 42°35'15'' 92°48'37'' 145 2.52 

I07 05420720 East Fork Wapsipinicon River near Tripoli, Iowa 42°50'51'' 92°13'48'' 144 2.63 

I08 05420900 Little Wapsipinicon River at Littleton, Iowa 42°32'27'' 92°01'30'' 210 2.52 

I09 05471120 East Branch Indian Creek near Iowa Center, Iowa 41°57'08'' 93°24'21'' 128 2.84 

I10 05458870 Maynes Creek near Kesley, Iowa 42°41'46'' 92°54'28'' 136 2.71 

I11 05459300 Winnebago River near Fertile, Iowa 43°14'49'' 93°26'16'' 294 2.80 

I12 05449200 East Branch Iowa River at Belmond, Iowa 42°51'48'' 93°36'47'' 195 2.96 

I13 05457950 Little Cedar River near Floyd, Iowa 43°11'55'' 92°41'14'' 250 2.61 

I14 05463510 Black Hawk Creek at Waterloo, Iowa 42°27'24'' 92°25'21'' 327 2.37 

I15 05455500 English River near Kalona, Iowa 41°28'11'' 91°42'52'' 574 2.41 

I16 05421700 Buffalo Creek near Stone City, Iowa 42°08'32'' 91°20'44'' 233 2.45 

I17 05461390 Flood Creek near Powersville, Iowa 42°54'26'' 92°43'14'' 150 2.49 

I18 05473060 Crooked Creek at Coppock, Iowa 41°09'31'' 91°42'30'' 284 2.48 

I19 05473400 Cedar Creek near Oakland Mills, Iowa 40°55'20'' 91°40'10'' 533 2.81 

I20 05455100 Old Mans Creek near Iowa City, Iowa 41°36'23'' 91°36'56'' 201 2.36 

I21 05421870 Mud Creek near Donahue, Iowa 41°44'17'' 90°41'26'' 119 2.31 

I22 05464220 Wolf Creek near Dysart, Iowa 42°15'06'' 92°17'55'' 327 2.30 

I23 05473550 Big Creek near Lowell, Iowa 40°51'38'' 91°28'49'' 167 2.72 

I24 05452020 Salt Creek at Belle Plaine, Iowa 41°53'31'' 92°17'60'' 200 2.28 

I25 05465310 Long Creek near Columbus Junction, Iowa 41°13'36'' 91°16'32'' 154 2.49 

M01 05319050 South Fork Watonwan near St. James, Minnesota 43°58'45'' 94°30'49'' 192 3.07 

M02 05320270 Little Cobb River near Beauford, Minnesota 43°59'48'' 93°54'30'' 130 3.38 

M03 05317828 Coon Creek at Highway 169 near Blue Earth, Minnesota 43°36'38'' 94°05'14'' 99 3.19 

M04 05326150 Middle Branch Rush River near New Rome, Minnesota 44°30'54'' 94°02'59'' 190 3.10 

M05 05320450 Maple River near Sterling Center, Minnesota 43°56'06'' 94°04'15'' 317 3.42 

M06 05319360 Perch Creek below Vernon Center, Minnesota 43°59'46'' 94°16'38'' 133 3.07 

Table 1. Locations and basin characteristics of 70 sites on Midwestern streams and rivers where water quality and habitat conditions weAugust 1997—Continued

[°, degrees; ', minutes; '', seconds; STATSGO, Soil Conservation Service Soil Hydrologic Group]

Site

number

U.S. Geological

Survey station

identification

Site name Latitude Longitude

Basin

area

(mi2)

STATSGO

score1
STUDY DESIGN AND METHODS 11

M07 05326250 South Branch Rush River near Rush River, Minnesota 44°29'08'' 94°02'10'' 180 2.99 

M08 05318050 East Branch Blue Earth River below Bricelyn, Minnesota 43°35'09'' 93°50'52'' 186 2.87 

M09 05318240 Elm Creek near Northrap, Minnesota 43°46'01'' 94°22'57'' 232 2.88 

M10 05320080 Le Sueur River near Wilton, Minnesota 44°01'38'' 93°32'47'' 173 2.86 

M11 05317170 Little Cottonwood River near Searles, Minnesota 44°14'19'' 94°26'05'' 162 2.88 

M12 05304795 Dry Weather Creek near Watson, Minnesota 45°02'33'' 95°45'33'' 105 2.88 

M13 05316985 Sleepy Eye Creek near Springfield, Minnesota 44°16'33'' 94°54'22'' 250 3.20 

M14 05326700 High Island Creek near Arlington, Minnesota 44°37'22'' 94°05'29'' 163 3.11 

M15 05312000 Spring Creek near Spring Creek, Minnesota 44°42'38'' 95°47'16'' 112 3.20 

M18 05320230 Cobb River near Mapleton, Minnesota 43°53'56'' 93°52'14'' 111 3.30 

M19 05303900 Shakopee Creek near Louriston, Minnesota 45°08'16'' 95°28'12'' 149 2.84 

M20 05318630 Wantonwan River near St. James, Minnesota 44°03'03'' 94°39'56'' 100 3.05 

M21 05317800 West Branch Blue Earth River above Elmore, Minnesota 43°30'56'' 94°07'41'' 150 2.96 

M22 05318178 Center Creek at Huntley, Minnesota 43°43'28'' 94°13'20'' 111 2.80 

M23 05314500 Hawk Creek near Maynard, Minnesota 44°52'11'' 95°28'59'' 315 2.99 

M24 05318138 South Creek near Huntley, Minnesota 43°41'39'' 94°14'52'' 104 2.84 

M25 05318800 St. James Creek near LaSalle, Minnesota 44°03'03'' 94°33'25'' 60 2.95 

M27 05314510 Chetomba Creek near Renville, Minnesota 44°50'24'' 95°14'20'' 120 3.22 

1STATSGO scores were calculated by weighted averaging of the spatial distribution of Soil Hydrologic Groups in each stream basin, as explained in “Characteriza

Basins” subsection.

2The percentage of trees in a 100-meter buffer zone on both streambanks was calculated for stream segments using digital raster graphic images from 7.5-minute U.

maps. The length of a stream segment in miles was defined as the base-10 logarithm of the basin area.

3Study design groups: 1, good riparian conditions, moderately well-drained soils; 2, poor riparian conditions, moderately well-drained soils; 3, good riparian condit

riparian conditions, poorly drained soils.

Table 1. Locations and basin characteristics of 70 sites on Midwestern streams and rivers where water quality and habitat conditions we

August 1997—Continued

[°, degrees; ', minutes; '', seconds; STATSGO, Soil Conservation Service Soil Hydrologic Group]

Site

number

U.S. Geological

Survey station

identification

Site name Latitude Longitude

Basin

area

(mi2)

STATSGO

score1
12 Water Quality and Habitat Conditions in Upper Midwest Streams Relative to Riparian Vegetation and Soil Characteristics,

August 1997: Study Design, Methods, and Data

Characterization of Soil Drainage in

Stream Basins

Soil-drainage conditions were classified for

each basin using U.S. Department of Agriculture

STATSGO Soil Hydrologic Groups, based primarily

on drainage characteristics, but including and integrating several other factors including runoff potential,

permeability, depth to water table, depth to impervious

layer, water capacity, and shrink-swell potential (Soil

Conservation Service, 1993). Soil Hydrologic Groups

define groups of soils with the same runoff potential

under similar storm and vegetative-cover conditions,

varying from Group A (well-drained soils through

which water moves rapidly) to Group D (very poorly

drained soils through which water moves slowly).

Streams that drain basins with well-drained soils

would be expected to receive greater contributions

from ground-water discharge during seasonal lowflow periods than streams that drain basins with poorly

drained soils. Tile drains or ditches are used more

commonly in poorly drained agricultural fields than

in well-drained fields, to remove excess water from

the soil.

Basin-boundary GIS polygon coverages were

used to clip information from STATSGO coverages

developed within the NAWQA Program (data on file

at U.S. Geological Survey, Lakewood, Colorado).

For the purpose of site classification, moderately

well-drained basins were defined as those where

the percentage of Soil Hydrologic Groups A or B

exceeded 50 percent; poorly drained basins were

defined as those where the percentage of Soil

Hydrologic Groups C or D exceeded 50 percent.

For subsequent analyses, a STATSGO score was

calculated for each site by weighted averaging of Soil

Hydrologic Groups found in each basin. To process

STATSGO data into a continuous theme of hydrologic

groups (HYDGRPs) for use in statistical water-quality

models, a simple numeric scheme was developed

to simplify the generalization (weighted-average

transfer) of soil component HYDGRP data to average

HYDGRP values for associations. Assignment of

values for mixed-group soil classes (for example, A/D

and B/D) was based on discussions with soil experts

and review of literature. Possible scores range from

near 1 (basin dominated by Group A soils) to 4 (basin

dominated by Group D soils). STATSGO scores in this

study ranged from 2.28 (moderately well drained) in

eastern Iowa to 3.42 (poorly drained) in southern

Minnesota (table 1).

Livestock Data

The county boundary polygon coverage

was used as the base coverage for estimating the

numbers of livestock in each stream basin (table 2).

Numbers of livestock present in 1995 or 1996 are

given because the 1997 data were not available in

time for inclusion in this report. For Illinois and

Minnesota, livestock numbers for 1996 were

obtained from U.S. Department of Agriculture data

at URL http://jan.mannlib.cornell.edu/data-sets/

livestock/93105/. For Iowa, the Iowa Poultry

Association provided estimated numbers of cattle,

sheep, and poultry by county for 1995. This was the

most recent data available. The number of hogs and

pigs estimated for each county, for 1996, was obtained

from URL http://www.econ.iastate.edu/faculty/

lawrence/COUNTY.htm (John Lawrence, livestock

economist, Iowa State University).

The nitrogen and phosphorus content of manure

was calculated from the number of cattle, sheep, hogs,

and poultry estimated in each stream basin. Computations were based on formulas provided in an AML

(R. Alexander, U.S. Geological Survey, written

commun., 1992). The computations are based on estimates of the nutrient content of wastes produced per

1,000 pounds of animal weight per day (table 3). The

estimates were obtained from the Soil Conservation

Service Agricultural Waste Management Field

Handbook (Soil Conservation Service, 1992). In some

cases, estimates of nitrogen and phosphorus content

represent an average of the reported range of values, or

are assumed values.

Population Data

Human-population density per square mile in

each basin was estimated using GIS polygon coverages of census-block groups processed from the

U.S. Department of Commerce, Bureau of Census

1990 TIGER/Line files (Hitt, 1994) (table 2). The

census-block group coverage was intersected with

the basin coverages, and the percentage of area of each

census-block group that was located within each basin

was multiplied by the total number of people in that

block group. The total population in all census-block

groups within each basin was summed, and population

density was estimated by dividing the total population

by the basin area.
STUDY DESIGN AND METHODS 13

Table 2. Livestock, nitrogen and phosphorus content of manure, human-population density, and precedent rainfall conditions

Site

number

U.S. Geological

Survey station

identification

Hogs

and pigs,

estimated

number

in basin1

Cattle,

estimated

number

in basin1

Sheep,

estimated

number

in basin1

Nitrogen

content of

manure

(metric tons)

Phosphorus

content of

manure

(metric tons)

Humanpopulation

density per

square mile,

1990

Rainfall

in basin,

May 1997

(centimeters)

L01 05554000 14,100 3,120 0 294 131 18.6 7.6 L02 05554490 50,700 8,230 22 931 429 18.6 6.8 L03 05556500 16,600 5,960 14 441 186 39.9 8.9 L04 05559500 9,800 3,950 0 278 116 39.9 6.0 L05 05563000 4,880 4,010 0 224 86 54.2 8.4 L06 05564300 17,400 5,770 455 448 189 19.2 7.8 L07 05567500 77,600 17,400 683 1,640 726 19.2 7.1 L08 05568830 48,900 12,200 168 1,080 473 14.7 8.0 L09 05569875 30,373 16,500 1,230 1,060 421 14.7 11 L10 05570910 11,200 3,330 119 270 116 41 14 L12 05575850 13,700 3,720 27 314 137 37.7 6.1 L15 05580000 10,200 4,060 265 291 120 34.2 11 L16 05583900 5,060 6,010 0 309 115 54.2 8.9 L17 05584500 48,100 37,400 118 2,120 819 13.8 13 L18 05585800 30,400 18,200 0 1,110 442 13 8.4 L19 05586598 43,200 20,800 97 1,370 558 13 7.8 L20 05586645 18,000 5,490 191 441 189 13.1 7.1 L21 05587000 11,000 40,700 1,430 2,990 1,250 13.1 7.3 L22 05567000 14,100 2,480 14 267 122 19.2 6.2 L23 05568000 122,000 24,600 751 2,450 1,100 19.2 6.9 L24 05568800 12,400 2,560 102 252 113 14.7 8.1 I01 05451210 170,000 5,560 904 2,380 1,200 9.56 10 I02 05469980 96,800 2,730 619 1,540 748 28.2 9.6 I03 05420680 89,600 12,900 2,190 1,940 798 13.3 12 I04 05456510 33,300 4,960 502 662 286 17.8 10 I05 05449500 138,000 6,900 1,350 2,120 1,030 9.56 11 
14 Water Quality and Habitat Conditions in Upper Midwest Streams Relative to Riparian Vegetation and Soil Characteristics,

August 1997: Study Design, Methods, and Data I06 05462770 34,700 3,360 933 605 276 41.3 8.3 

I07 05420720 35,800 5,500 1,280 818 327 13.3 12 I08 05420900 39,600 5,040 968 912 355 13.3 11 I09 05471120 31,500 2,560 763 503 237 28.2 10 I10 05458870 25,400 2,710 776 457 207 8.4 9.0 I11 05459300 52,300 4,480 1,030 877 402 29.4 10 I12 05449200 49,100 3,390 644 784 376 9.56 10 I13 05457950 87,900 9,440 719 1,610 720 17.8 12 I14 05463510 65,700 12,500 3,070 1,460 627 41.3 9.7 I15 05455500 132,000 29,900 4,740 3,000 1,290 27.9 14 I16 05421700 72,000 9,500 883 1,530 624 13.3 11 I17 05461390 23,900 3,010 438 427 195 15.7 12 I18 05473060 119,000 9,340 2,710 2,050 961 12.5 15 I19 05473400 86,300 22,100 6,100 2,130 891 12.5 12 I20 05455100 36,700 10,700 1,630 958 393 27.9 15 I21 05421870 27,800 3,860 510 534 234 13.5 16 I22 05464220 44,100 11,600 3,180 1,100 457 41.3 13 I23 05473550 31,700 4,290 884 707 312 12.5 8.4 I24 05452020 28,200 9,610 2,170 794 319 17.5 15 I25 05465310 68,300 5,650 1,200 1,140 537 27.9 15 M01 05319050 546 3,720 0 121 118 8.64 10 M02 05320270 8 96 0 3 3 10.3 11 M03 05317828 1,210 6,570 0 216 210 9.92 11 M04 05326150 10,900 10,800 222 536 335 89.3 6.1 M05 05320450 4,560 20,400 0 681 657 10.3 12 M06 05319360 488 3,480 0 113 110 8.64 12 M07 05326250 11,000 11,300 95 519 382 89.3 6.1 

Table 2. Livestock, nitrogen and phosphorus content of manure, human-population density, and precedent rainfall conditions—Continue

Site

number

U.S. Geological

Survey station

identification

Hogs

and pigs,

estimated

number

in basin1

Cattle,

estimated

number

in basin1

Sheep,

estimated

number

in basin1

Nitrogen

content of

manure

(metric tons)

Phosphorus

content of

manure

(metric tons)

Humanpopulation

density per

square mile,

1990

Rainfall

in basin,

May 1997

(centimeters)
STUDY DESIGN AND METHODS 15

M08 05318050 2,920 15,800 0 521 506 9.92 11 M09 05318240 582 5,710 0 183 180 9.92 11 M10 05320080 362 5,050 0 160 158 10.3 11 M11 05317170 15,000 8,270 397 479 305 27.7 6.9 M12 05304795 30,500 11,300 494 772 472 12.8 3.1 M13 05316985 10,400 33,600 846 1,550 913 7.82 3.9 M14 05326700 7,930 13,800 203 654 394 89.3 5.0 M15 05312000 2,520 2,990 76 144 91 10.5 2.9 M18 05320230 755 6,200 0 200 196 10.3 11 M19 05303900 21,600 9,150 320 619 365 12.8 5.3 M20 05318630 82 510 0 17 16 8.64 8.3 M21 05317800 88 1,640 0 51 51 9.92 9.7 M22 05318178 469 3,760 0 121 119 9.92 12 M23 05314500 56,800 27,600 1,040 1,730 1,050 10.5 3.4 M24 05318138 479 5,040 0 161 158 9.92 11 M25 05318800 287 1,780 0 58 57 8.64 10 M27 05314510 9,350 10,700 219 563 328 12.8 2.9 

1Illinois and Minnesota data (sites L01–L24 and M01–M27) are for 1996; Iowa data (sites I01–I25) are for 1995.

Table 2. Livestock, nitrogen and phosphorus content of manure, human-population density, and precedent rainfall conditions—Continue

Site

number

U.S. Geological

Survey station

identification

Hogs

and pigs,

estimated

number

in basin1

Cattle,

estimated

number

in basin1

Sheep,

estimated

number

in basin1

Nitrogen

content of

manure

(metric tons)

Phosphorus

content of

manure

(metric tons)

Humanpopulation

density per

square mile,

1990

Rainfall

in basin,

May 1997

(centimeters)
16 Water Quality and Habitat Conditions in Upper Midwest Streams Relative to Riparian Vegetation and Soil Characteristics,

August 1997: Study Design, Methods, and Data

Rainfall Data

The locations (latitude and longitude) of precipitation stations in and near the regional study area

were obtained from climatological data reports for

Minnesota, Iowa, and Illinois published monthly by

the National Oceanic and Atmospheric Administration

(NOAA), National Climatic Data Center (NCDC)

(NOAA-NCDC, 1997a–i). A GIS point coverage

representing the location of NOAA-NCDC precipitation stations was created. Rainfall amounts for the

months of May, June, and July 1997 (table 2) were

obtained from NOAA-NCDC (1997a–i). Precipitation

values were attributed to the point coverage. A master

grid was created by generating a precipitation value

for each cell based on the location of points in the

point coverage. Maximum and minimum precipitation

values were determined for all cells, and mean values

for the basin were determined by a kriging process

after the basin was clipped from the master grid

coverage.

Agricultural-Chemical Use and Crop Data

A polygon coverage representing county boundaries in the States of Illinois, Iowa, and Minnesota was

used as the base coverage for determining agriculturalchemical usage and crop acreage for each stream

basin. The county coverages were obtained from the

U.S. Bureau of Census TIGER/line files using an AML

program (D. Nebert and M. Negri, U.S. Geological

Survey, written commun., 1997). These coverages

were retrieved from URL http://water.usgs.gov/lookup/

getspatial?county100. The scale of the county coverages is 1:100,000. Each county polygon is identified by

a five-digit Federal Information Processing Standard

Table 3. Nitrogen and phosphorus content of manure

Animal

Average

weight

of animal

(pounds)

Nitrogen

content

in pounds

per day per

1,000 pounds

of animal

Phosphorus

content

in pounds

per day per

1,000 pounds

of animal

Beef cows 800 0.315 0.105

Milk cows 1,200 0.400 0.060

Steers-calves 800 0.315 0.105

Hogs-pigs 250 0.280 0.150

Sheep 175 0.450 0.070

Pullets 2 0.620 0.240

Broilers 3 1.100 0.340

Turkeys 3 0.740 0.280

(FIPS) code. Basin boundaries were attributed to

county coverages using an ARC/INFO command that

computes the geometric intersection of two polygon

coverages.

County-level crop data for Illinois, Iowa,

and Minnesota were obtained from the U.S. Department of Agriculture, National Agricultural Statistical Service (USDA-NASS), from URL http://

jan.mannlib.cornell.edu/data-sets/crops/9X100/.

The number of acres in corn, soybean, and sugar

beet production was determined by calculating the

percentage of all counties present in each stream

watershed, then multiplying each county percentage

by the total acreage of crops grown in that county,

and summing results for all counties in the watershed

(table 4). Computations for agricultural-chemical use

in each basin (table 4) were based on estimates of

fertilizer and herbicide use for each crop reported in

the 1997 Agricultural Chemical Use Estimates for

Field Crops (USDA-NASS, 1999). Specific rates of

application on individual crops are reviewed within

and among States to promote regional consistency in

reporting; however, recommended application rates

differ for Illinois, Iowa, and Minnesota.

Characterization of Water Quality

Water-Sample Collection

Samples for chemical analyses were collected

from 70 sites in west-central Illinois, eastern Iowa,

and southern Minnesota (fig. 1; table 1) during

August 1997. Generally, water samples were collected

on the same day that biological samples were collected,

or within 48 hours. To integrate vertical and horizontal

variability in water chemistry, samples were collected

using a depth-integrated sampler at 5 to 10 verticals,

equally spaced across the stream (Edwards and

Glysson, 1988; Ward and Harr, 1990; Shelton, 1994).

A cone splitter (Capel and Larson, 1996) was used

to divide the collected sample into subsamples for

determinations of total nutrients, dissolved nutrients,

dissolved herbicides, total and dissolved organic

carbon, and total suspended sediment. Subsamples also

were obtained for seston (phytoplankton) analyses (see

“Algae” subsection). Samples requiring filtration were

processed using procedures described by Shelton

(1994). Following field processing, all samples were

immediately chilled (placed in a cooler with wet ice)

for shipment to the analytical laboratories. Samples

for total and filtered nutrients and organic carbon
STUDY DESIGN AND METHODS 17

Table 4. Row-crop production, fertilizer application, and herbicide use[kg, kilograms; --, no data]

Site

number

U.S.

Geological

Survey

station

identification

Corn

(acres

planted

in 1997)

Soy

beans

(acres

planted

in 1997)

Corn,

percent

of total

crop in

1997

Soy

beans,

percent

of total

crop in

1997

Corn,

percent

of total

basin

area

Soy

beans,

percent

of total

basin

area

Nitrogen

applied to

corn and

soybeans

in 1997

(metric

tons)

Phosphorus

applied to

corn and

soybeans

in 1997

(metric

tons)

Acetochlor

use in

1997

(kg)

Alachlor

use in

1997

(kg)

Atrazine

use in

1997

(kg)

Cya

us

1

(

L01 05554000 54,000 51,600 50 48 45 43 3,740 660 14,700 561 22,600 8L02 05554490 158,000 153,000 50 48 45 43 10,900 1,930 43,000 1,640 66,200 24L03 05556500 57,700 36,500 59 37 46 29 3,990 660 15,700 600 24,200 8L04 05559500 26,700 23,400 50 44 36 32 1,850 320 7,270 277 11,200 4L05 05563000 19,600 16,400 47 40 26 22 1,360 230 5,350 204 8,240 3L06 05564300 86,400 82,300 50 48 44 42 5,980 1,050 23,500 897 36,200 13L07 05567500 206,000 190,000 50 46 42 39 14,200 2,500 56,000 2,130 86,200 31L08 05568830 122,000 84,400 57 39 44 31 8,440 1,410 33,300 1,270 51,200 18L09 05569875 64,600 53,200 52 43 37 31 4460 768 17,600 670 27,100 9L10 05570910 61,300 58,700 50 48 40 38 4,240 749 16,700 636 25,700 9L12 05575850 28,700 27,000 48 45 35 33 1,990 350 7,820 298 12,000 4L15 05580000 61,200 58,500 50 48 42 40 4,240 748 16,700 636 25,700 9L16 05583900 17,500 18,500 42 44 23 24 1,220 218 4,780 182 7,350 2L17 05584500 140,000 134,000 46 44 33 32 9,680 1,710 38,100 1,450 58,600 21L18 05585800 14,000 42,500 19 57 7 22 983 241 3,800 145 5,850 2L19 05586598 78,600 72,400 47 43 32 29 5,440 954 21,400 817 33,000 12L20 05586645 25,500 24,500 45 44 30 29 1,760 312 6,940 265 10,700 3L21 05587000 153,000 147,000 45 43 28 26 10,600 1,870 41,700 1,590 64,300 23L22 05567000 24,300 21,800 50 45 40 36 1,680 294 6,630 253 10,200 3L23 05568000 276,000 253,000 50 46 40 37 19,100 3,350 75,200 2,870 116,000 42L24 05568800 18,800 12,500 57 38 47 31 1,300 217 5,130 196 7,900 2I01 05451210 62,000 54,300 52 45 43 38 3,440 532 15,000 5,720 19,800 10I02 05469980 61,200 56,800 51 47 45 41 3,400 530 14,800 5,900 19,600 10I03 05420680 86,500 75,200 49 42 39 34 4,800 740 20,900 7,930 27,700 15
18 Water Quality and Habitat Conditions in Upper Midwest Streams Relative to Riparian Vegetation and Soil Characteristics,

August 1997: Study Design, Methods, and Data I04 05456510 37,900 35,300 48 45 39 36 2,100 328 9,140 3,670 12,100 6

I05 05449500 120,000 101,000 53 45 45 38 6,660 1,020 29,000 10,800 38,500 21I06 05462770 40,200 34,100 52 44 43 37 2,230 343 9,710 3,620 12,900 7I07 05420720 36,600 30,700 49 41 40 33 2,030 311 8,840 3,270 11,700 6I08 05420900 38,800 27,400 51 36 29 20 2,140 320 9,360 3,040 12,400 6I09 05471120 33,700 31,800 50 47 41 39 1,870 293 8,140 3,300 10,800 5I10 05458870 39,400 32,900 53 44 45 38 2,190 335 9,520 3,500 12,600 6I11 05459300 86,500 70,800 53 44 46 38 4,790 732 20,900 7,570 27,700 15I12 05449200 55,600 45,700 54 44 45 37 3,080 471 13,400 4,880 17,800 9I13 05457950 61,600 53,100 50 44 39 33 3,420 527 14,900 5,620 19,700 10I14 05463510 98,100 85,200 53 45 47 41 5,440 839 23,700 8,990 31,400 17I15 05455500 111,000 89,200 46 37 30 24 6,150 936 26,800 9,580 35,500 19I16 05421700 60,900 37,300 54 33 41 25 3,360 493 14,700 4,300 19,500 10I17 05461390 33,200 28,400 51 44 35 30 1,840 283 8,010 301 10,600 5I18 05473060 57,100 50,800 47 41 31 28 3,170 491 13,800 5,330 18,300 10I19 05473400 78,700 78,100 41 40 23 23 4,380 691 19,000 8,010 25,200 13I20 05455100 37,600 26,500 46 33 29 21 2,080 310 9,070 2,940 12,000 6I21 05421870 29,400 18,500 57 36 39 24 1,620 239 7,090 2,120 9,410 5I22 05464220 70,900 60,800 50 43 34 29 3,930 605 17,100 6,440 22,700 12I23 05473550 32,000 27,700 48 41 30 26 1,770 274 7,720 2,930 10,200 5I24 05452020 47,300 40,600 48 41 37 32 2,620 404 11,400 4,300 15,100 8I25 05465310 31,200 28,000 47 42 32 28 1,730 269 7,540 2,930 10,000 5M01 05319050 52,300 54,500 48 50 43 44 2,590 366 9,840 3,170 5,400 1M02 05320270 33,700 31,500 49 45 41 38 1,660 231 6,340 1,860 3,480 1M03 05317828 28,600 24,300 53 45 45 38 1,410 193 5,380 1,460 2,950 

Table 4. Row-crop production, fertilizer application, and herbicide use—Continued

[kg, kilograms; --, no data]

Site

number

U.S.

Geological

Survey

station

identification

Corn

(acres

planted

in 1997)

Soy

beans

(acres

planted

in 1997)

Corn,

percent

of total

crop in

1997

Soy

beans,

percent

of total

crop in

1997

Corn,

percent

of total

basin

area

Soy

beans,

percent

of total

basin

area

Nitrogen

applied to

corn and

soybeans

in 1997

(metric

tons)

Phosphorus

applied to

corn and

soybeans

in 1997

(metric

tons)

Acetochlor

use in

1997

(kg)

Alachlor

use in

1997

(kg)

Atrazine

use in

1997

(kg)

Cya

us

1

(
STUDY DESIGN AND METHODS 19

M04 05326150 40,400 42,000 43 45 33 35 2,000 282 7,600 2,450 4,170 1M05 05320450 81,700 76,400 51 48 40 38 4,030 560 15,400 4,520 8,430 2M06 05319360 36,800 37,300 48 49 43 44 1,820 256 6,920 2,180 3,800 1M07 05326250 40,700 41,600 44 45 35 36 2,010 284 7,660 2,430 4,200 1M08 05318050 49,300 44,500 51 46 41 37 2,430 336 9,280 2,650 5,090 1M09 05318240 64,500 65,100 48 49 43 44 3,190 448 12,100 3,810 6,660 2M10 05320080 45,500 40,900 48 43 41 37 2,240 310 8,560 2,440 4,690 1M11 05317170 39,000 40,600 45 47 38 39 1,930 273 7,340 2,360 4,030 1M12 05304795 24,300 25,100 41 43 36 37 1,200 170 4,570 1,460 2,510 M13 05316985 62,800 69,000 45 50 39 43 3,110 443 11,800 3,980 6,480 1M14 05326700 34,200 35,300 42 44 33 34 1,690 238 6,420 2,060 3,520 1M15 05312000 25,800 28,500 43 48 36 40 1,280 182 4,850 1,640 2,660 M18 05320230 28,500 26,400 49 45 40 37 1,400 195 5,360 1,570 2,940 M19 05303900 27,000 24,300 42 38 28 25 1,330 184 5,080 1,450 2,790 M20 05318630 26,000 27,800 47 50 41 43 1,290 183 4,900 1,610 2,690 M21 05317800 46,200 37,700 54 44 48 39 2,270 310 8,690 2,280 4,770 1M22 05318178 32,900 32,000 49 48 46 45 1,620 227 6,180 1,880 3,390 1M23 05314500 63,900 60,800 42 40 32 30 3,150 440 12,000 3,590 6,590 1M24 05318138 30,800 29,200 50 47 46 44 1,520 212 5,800 1,720 3,180 M25 05318800 16,800 17,500 48 50 44 46 829 117 3,150 1,020 1,730 M27 05314510 21,500 19,000 42 37 28 25 1,060 146 4,050 1,140 2,220 

Table 4. Row-crop production, fertilizer application, and herbicide use—Continued

[kg, kilograms; --, no data]

Site

number

U.S.

Geological

Survey

station

identification

Corn

(acres

planted

in 1997)

Soy

beans

(acres

planted

in 1997)

Corn,

percent

of total

crop in

1997

Soy

beans,

percent

of total

crop in

1997

Corn,

percent

of total

basin

area

Soy

beans,

percent

of total

basin

area

Nitrogen

applied to

corn and

soybeans

in 1997

(metric

tons)

Phosphorus

applied to

corn and

soybeans

in 1997

(metric

tons)

Acetochlor

use in

1997

(kg)

Alachlor

use in

1997

(kg)

Atrazine

use in

1997

(kg)

Cya

us

1

(
20 Water Quality and Habitat Conditions in Upper Midwest Streams Relative to Riparian Vegetation and Soil Characteristics,

August 1997: Study Design, Methods, and Data

were shipped to the USGS National Water Quality

Laboratory (NWQL) in Arvada, Colorado. Samples for

herbicide and degradate analyses were shipped to the

USGS Organic Geochemistry Research Laboratory

(OGRL) in Lawrence, Kansas. Samples for total

suspended sediment were shipped to the USGS Iowa

District Sediment Laboratory (IDSL) in Iowa City,

Iowa. Seston subsamples were filtered onto glass-fiber

filters, and the filters were shipped on dry ice to the

USGS Stable Isotope Laboratory in Menlo Park,

California, for determinations of δ15N and δ12C

(Battaglin and others, 1997) and the USGS Iowa

District laboratory for CHLa determinations. Approximately 15 percent of samples collected for seston

CHLa determinations were split from the original

sample volume and submitted to the NWQL for

quality-control purposes. Field measurements of water

temperature, specific conductance, pH, DO, and alkalinity were made in accordance with protocols established by Shelton (1994). Results of field measurements

and chemical determinations are listed in tables 6

through 9 in the Appendix.

Water-Sample Laboratory Analyses

The NWQL performed analyses for nutrients,

organic carbon, and chlorophyll (quality-control

comparison samples only) concentrations in water

samples. Analytical methods for nutrient determinations are presented by Fishman and Friedman (1989),

Patton and Truitt (1992), and Fishman (1993). Methods

for determining total and dissolved organic carbon in

water samples are given by Wershaw and others (1987)

and Brenton and Arnett (1993). Chlorophyll was determined by the high-pressure liquid chromatography

(HPLC) method described by Britton and Greeson

(1989). Quality-control practices employed by the

NWQL are presented by Pritt and Raese (1995).

The IDSL performed analyses for total suspendedsediment concentrations in water samples. Samples

were analyzed in accordance with methods presented

by Guy (1969).

The OGRL performed analyses of herbicide and

herbicide-metabolite concentrations in water samples

(table 5) using gas chromatography/mass spectrometry

(GC/MS) following extraction on C18 cartridges

(Thurman and others, 1990; Meyer and others, 1993).

The analytical reporting limit for this method was

0.05 μg/L for all compounds. Additional analyses for

six chloroacetanilide herbicide metabolites—acetochlor

ethanesulfonic acid (ESA), acetochlor oxanilic acid

(OA), alachlor ESA, alachlor OA, metolachlor ESA,

and metolachlor OA—and the atrazine metabolite,

hydroxy-atrazine (table 5), were analyzed by HPLC

following solid-phase extraction on C18 cartridges

(Meyer and others, 1993). Quantification of the

analytes was achieved by dividing the peak height of

the analyte by the peak height of the internal standard

(2,4–D) and substituting the peak height into the

respective linear regression equation. Complete separation of all analytes was achieved with this method. The

analytical reporting limit for this method was 0.2 μg/L

for all metabolite compounds. Relative standard deviation for the method is ±10 percent. Standards were run

with each sample set at concentrations of 0.25, 0.5, 1.0,

and 2.0 μg/L. Confirmation by HPLC-MS negative ion

electrospray (Ferrer and others, 1997) was achieved for

metolachlor ESA and acetochlor, alachlor, and metolachlor OA. Complete separation of alachlor ESA and

acetochlor ESA was not possible by HPLC-MS negative ion electrospray. Tables 8 and 9 list results for all

herbicide compounds that were detected.

Water Clarity

Water clarity was quantified by determining

or estimating the depth of the euphotic zone,

which is the depth at which 1 percent of subsurface photosynthetically-active radiation (PAR)

remains (Hutchinson, 1967). Light meters with

Li-CorTM underwater quantum sensors were used to

determine PAR approximately 1 cm below the water

surface; the sensor was then lowered to a depth where

1 percent of subsurface PAR remained or to the bottom

of the deepest pool in the stream reach. When greater

than 1 percent of subsurface PAR (PCTPAR) was

detected at the stream bottom, the depth and PCTPAR

were recorded. The depth of the euphotic zone in

meters (EUPHOTIC) was estimated by linear regression, with the concentration of total suspended sediment (TSS), in mg/L, and PCTPAR, using the

following relation:

Log (EUPHOTIC) = 0.427 – 0.396 (Log TSS)

– 0.005 (PCTPAR)

(adjusted R2

= 0.548; F = 27.036; p < 0.001)
STUDY DESIGN AND METHODS 21

Table 5. Herbicides and herbicide-degradation products analyzed by the U.S. Geological Survey Organic Geochemistry

Research Laboratory, Lawrence, Kansas

[GC/MS, gas chromatography/mass spectrometry; HPLC, high-performance liquid chromatography; MCL, maximum contaminant level,

U.S. Environmental Protection Agency (Nowell and Resek, 1994); HA, health advisory level, U.S. Environmental Protection Agency (Nowell

and Resek, 1994); --, not applicable]

Common name Chemical name Use or

origin

Method of

analysis

MCL

or HA

Acetochlor 2-chloro-N-(ethoxymethyl)-N-(2-ethyl-6-

methylphenyl)acetamide

herbicide GC/MS --

Acetochlor ethanesulfonic

acid (acetochlor ESA)

2-[(2-ethyl-6-methylphenyl)(ethoxymethyl)amino]-

2-oxoethane sulfonic acid

herbicide degradate

(acetochlor)

HPLC --

Acetochlor oxanilic acid

(acetochlor OA)

2-[(2-ethyl-6-methylphenyl)(ethoxymethyl)amino]-

2-oxoacetic acid

herbicide degradate

(acetochlor)

HPLC --

Alachlor 2-chloro-2'-6'-diethyl-N-(methoxymethyl)-

acetanilide

herbicide GC/MS 2

Alachlor ethanesulfonic

acid (alachlor ESA)

2-[(2,6-diethylphenyl)(methoxymethyl)amino]-

2-oxoethane sulfonic acid

herbicide degradate

(alachlor)

HPLC --

Alachlor oxanilic acid

(alachlor OA)

2-[(2,6-diethylphenyl)(methoxymethyl)amino]-

2-oxoacetic acid

herbicide degradate

(alachlor)

HPLC --

Ametryn 2-(ethylamino)-4-isopropylamino-6-methylthio-s-triazine

herbicide GC/MS 2,000

Atrazine 2-chloro-4-ethylamino-6-isopropylaminos-triazine

herbicide GC/MS 3

Cyanazine 2-[[4-chloro-6-(ethylamino)-1,3,5-triazine2-yl]amino]-2-methyl propionitrile

herbicide GC/MS 1

Cyanazine amide 2-chloro-4-(1-carbamoyl-1-methyl-ethylamino6-ethylamino-s-triazine

herbicide degradate

(cyanazine)

GC/MS --

Deethylatrazine 2-amino-4-chloro-6-(isopropylamino)-s-triazine herbicide degradate

(atrazine, propazine)

GC/MS --

Deisopropylatrazine 2-amino-4-chloro-6-(ethylamino)-s-triazine herbicide degradate

(atrazine, cyanazine,

simazine)

GC/MS --

Hydroxyatrazine 2-hydroxy-4-(ethylamino)-6-(isopropylamino)-

s-triazine

herbicide degradate

(atrazine)

HPLC --

Metolachlor 2-chloro-N-(2-ethyl-6-methylphenyl)-N-

(2-methoxy-1-methyl ethyl)acetamide

herbicide GC/MS 100

Metolachlor ethanesulfonic acid

(metolachlor ESA)

2-[(2-ethyl-6-methylphenyl)(2-methoxy-1-

methylethyl)amino]-2-oxoethanesulfonic acid

herbicide degradate

(metolachlor)

HPLC --

Metolachlor oxanilic acid

(metolachlor OA)

2-[(2-ethyl-6-methylphenyl)(2-methoxy1-methylethyl)amino]-2-oxoacetic acid

herbicide degradate

(metolachlor)

HPLC --

Metribuzin 4-amino-6-(1,1-dimethylethyl)-3-(methylthio)-

1,2,4-triazine-5(4H)-one

herbicide GC/MS 200

Prometon 2,4-bis(isopropylamino)-6-methyoxy-s-triazine herbicide GC/MS 100

Prometryn 2,4-bis(isopropylamino)-6-(methylthio)-s-triazine herbicide GC/MS --

Propachlor 2-chloro-N-isopropylacetanilide herbicide GC/MS 90

Propazine 2-chloro-4,6-bis(isopropylamino)-s-triazine herbicide GC/MS 10

Simazine 2-chloro-4,6-bis(ethylamino)-s-triazine herbicide GC/MS 4

Terbutryn 2-tert-butylamino-4-ethylamino-6-methylthios-triazine

herbicide GC/MS --
22 Water Quality and Habitat Conditions in Upper Midwest Streams Relative to Riparian Vegetation and Soil Characteristics,

August 1997: Study Design, Methods, and Data

The depth of the euphotic zone in streams with high

water clarity was estimated by setting PCTPAR equal

to 1 percent and calculating EUPHOTIC using the

regression relation. Results for euphotic-zone depth

are listed in table 11 in the Appendix.

Stream Productivity and Respiration

Measurements of water temperature, specific

conductance, pH, and DO were recorded at 15-minute

intervals over a period of 48 hours using submersible

data recorders (HydroLabTM DataSondeTM units)

suspended with the probes positioned in the euphotic

zone. Data recorder probes were calibrated in accordance with manufacturer’s instructions before installation at a site and following retrieval. New batteries and

DO sensor membranes were installed each time a unit

was deployed. Data recorder values were compared

with measurements made independently during the

collection of chemical and biological samples.

Stream productivity and respiration were estimated using diel DO and pH curves. Examination of

diel DO and pH curves revealed minima and maxima

about 8 a.m. and 3 p.m., respectively. Rapid rates

of change were linear, increasing between 9 a.m.

and 3 p.m. due to algal photosynthesis, and decreasing

from midnight to 8 a.m. because of biological respiration. Stream productivity (Pmax) was quantified by

subtracting the DO concentration at 8 a.m. from the

concentration at 3 p.m. and calculating the net rate

of oxygen accrual in milligrams of O2 per liter per

hour (mg O2/L/hr), which is equivalent to grams of

O2 per cubic meter per hour (g O2/m3

/hr). Stream

respiration (Rmax) was quantified by subtracting the

DO concentration at midnight from the concentration

at 8 a.m. and calculating the rate of oxygen loss in

the same manner. Similar calculations for productivity

(daylight, rate of increase) and respiration (night, rate

of decrease) were made using pH as the response

variable. When differences in productivity and respiration estimates were determined between 24-hour

cycles due to cloudy weather, the larger of the two

estimates was retained. Estimates of Pmax and Rmax

do not account for rates of oxygen diffusion that are

a function of water temperature and the difference in

oxygen saturation between water and air (Odum,

1956). Selected summary statistics for the 48-hour

period are listed in table 10 in the Appendix.

Algae

Sample Collection

Two quantitative algal samples were collected

at each site: periphyton (algae attached to submerged

surfaces such as wood) and seston (phytoplankton

suspended in the water column). Periphyton samples

were collected in accordance with the NAWQA algal

protocol for richest targeted habitat (RTH) samples

(Porter and others, 1993). All samples were collected

from snags (submerged woody debris) that were

entirely submerged in the euphotic zone of the stream.

Snag samples were collected from a minimum of

10 locations in each stream reach. Snags were gently

removed from the water to minimize disturbance of

the periphyton community; an 8- to 10-cm cylindrical

section was cut from each snag with lopping shears;

and the snag sections were retained in a plastic bag

prior to processing. After periphyton was removed

from the snag sections, the length and diameter of

each section was measured, and the surface area of

each snag segment was calculated using the following

formula:

Surface area (cm2) = 3.1416 * average diameter * length

The areas of all snag sections were summed,

and the total surface area was recorded on the field

data sheets and sample labels. Periphyton was

removed from each snag section using a stiff-bristled

toothbrush and de-ionized water from a rinse bottle.

The algal suspension was washed into a small, plastic

processing pan. Snag sections were processed until

about 150 to 200 mL of water had accumulated in

the processing pan. The process water was then

used to rinse periphyton removed from the remaining

snag sections. After all snag sections were processed,

each section was rinsed with additional water, and

the combined periphyton-water suspension was

poured into a labeled 500-mL plastic sample

container.

Periphyton Subsampling and Processing

Periphyton samples were subsampled to

provide aliquots for determinations of CHLa, ashfree dry mass (AFDM), taxonomic analysis, and stable

isotope ratios. Results of stable isotope values are not

in this report. The sample was homogenized for about

30 seconds, or until the sample appeared to be well
STUDY DESIGN AND METHODS 23

mixed, using a hand-held, battery-operated mixer.

When algal filaments became wound about the slotted

tip of the mixer, they were cut into smaller fragments

using small dissecting scissors. This process was

repeated until most of the algal filaments were

dispersed and the sample appeared to be relatively

homogeneous. Two subsamples (generally 10 mL)

were withdrawn from each periphyton sample and

filtered onto Whatman GF/F glass-fiber filters using

procedures described by Porter and others (1993). The

filters were wrapped with aluminum foil, placed into

labeled plastic bags or disposable petri dishes, and

shipped to analytical laboratories in a cooler with dry

ice. A subsample of sufficient volume to produce

about 10 mg of solid material was withdrawn and

delivered into a 20-mL scintillation vial. This

subsample was shipped to the USGS National

Research Program stable isotope laboratory in Menlo

Park, California, for determinations of stable-isotope

ratios of nitrogen, carbon, and sulfur. The remainder

of the original periphyton sample was preserved and

shipped to the NWQL Biological Unit for identification and enumeration of algal taxa using the standard

NAWQA RTH 600-cell count method (protocol on file

at U.S. Geological Survey, Lakewood, Colorado). The

volume of this taxonomic-sample component was

determined using a graduated cylinder. After the

volume of the taxonomic-sample component was

recorded on the field data sheet and sample label, the

resulting sample was preserved with sufficient concentrated buffered formalin to result in a final concentration of 5 percent (Porter and others, 1993). The total

volume of the original periphyton sample was determined by summing the volumes withdrawn for CHLa,

AFDM, stable isotopes, and algal taxonomy; the total

sample volume was recorded on field data sheets and

sample labels.

Seston (phytoplankton) samples for CHLa analysis were split from the water sample collected for

nutrient and herbicide analyses. Sample volumes,

ranging from 50 to 100 mL, depending on water clarity,

were recorded on field data sheets, and the sample was

filtered onto Whatman GF/F glass-fiber filters for

seston CHLa analysis using procedures described

by Porter and others (1993). The filters were wrapped

with aluminum foil, placed into labeled plastic bags or

disposable petri dishes, and shipped to the analytical

laboratory in a cooler with dry ice. Filters used during

the processing of water-chemistry samples were

retained, placed into labeled plastic bags, and shipped

to the USGS stable isotope laboratory for processing,

as described previously.

Chlorophyll a and Ash-Free Dry Mass Analyses

Chlorophyll a was determined in the Iowa

District laboratory using the U.S. Environmental

Protection Agency fluorometric method (Arar and

Collins, 1992; Eaton and others, 1995). Filters were

thawed and extracted in 90 percent aqueous acetone

solution by grinding, and then steeping for 24 hours

at 4°C. Fluorescence of chlorophyll extracts was

determined with a Turner 111 fluorometer that had

been calibrated previously with chlorophyll standards

provided by the NWQL. Results for periphyton

CHLa (mg/m2

) and seston CHLa (μg/L) (table 7) are

corrected for the presence of phaeophytin pigments,

corresponding with the U.S. Environmental Protection

Agency STORET code 32229. Ash-free dry mass was

determined in the USGS Illinois District laboratory

using the U.S. Environmental Protection Agency standard method (Weber, 1973; Eaton and others, 1995).

Filters were dried to a constant mass at 105°C; the dry

weight was determined on an analytical balance; the

filters were ashed at 500°C for 1 hour, re-hydrated,

dried to a constant mass, and the mass of the residue

(ash weight) was determined. Ash-free dry mass

(g/m2

) was calculated by subtracting the ash weight

from the dry weight of the sample and dividing by the

periphyton sample area. Results correspond with

STORET code 00572.

Quality-Control Samples

Quality-control samples included filter blanks,

triplicate split samples, and replicate samples split with

the NWQL. No fluorescence attributable to chlorophyll

was detected in repeated analyses of blank filters. Triplicate periphyton filters were analyzed from 12 sites.

The average coefficient of variation was 6 percent

over a large range of CHLa concentrations (13.2 to

80.2 mg/m2). Results from samples split with the

NWQL were highly correlated (r > 0.99; p < 0.001),

but concentrations differed significantly between laboratories. These results are attributable to differences in

CHLa values determined by fluorometric and HPLC

methods (for example, Millie and others, 1993). Values

determined by the HPLC method were slightly less than

half of those determined by the fluorometric method for

the same sample.
24 Water Quality and Habitat Conditions in Upper Midwest Streams Relative to Riparian Vegetation and Soil Characteristics,

August 1997: Study Design, Methods, and Data

Benthic Invertebrates

Benthic invertebrate samples were collected

in accordance with the NAWQA protocol for RTH

samples (sampler code 27) (Cuffney and others, 1993).

All samples were collected from snags that appeared to

have been submerged for an extended period of time in

areas of flowing water. Snag samples were collected

from 5 to 10 locations in each stream reach. A sampling

net (Slack sampler) was placed downstream from the

snag to retain any organisms dislodged during the

collection process. The top portion of the branch was

cut underwater with lopping shears. A 12- to 20-in

section of the snag was then cut underwater and

allowed to flow into the Slack sampler. The snag

section was scraped gently with a brush inside the

net, then removed and placed into a 5-gal plastic

bucket. Organisms clinging to the inside of the net, and

those retained in the net-sample bottle, were removed

and placed into another plastic bucket containing a

small amount of stream water. Contents of the bucket

containing organisms were poured into a 425-μm mesh

sieve, and invertebrates were removed and placed into a

500-mL plastic container. Snag sections were examined

and picked repeatedly, as the sections dried, until no

additional organisms were found. The total area associated with each invertebrate sample was calculated using

the same formula described for the periphyton samples.

Samples were labeled and preserved with 10-percent

buffered formalin. All samples were submitted to the

NWQL Biology Unit for taxonomic analysis using the

standard NAWQA RTH 500-organism count method

(S. Moulton, U.S. Geological Survey, written commun.,

1998).

Characterization of Habitat Conditions

Stream-habitat conditions were assessed

using methods adapted from the NAWQA Level 1

habitat-assessment protocol (Meador and others, 1993;

Fitzpatrick and others, 1998). The lower boundary of

the sampling reach was established and marked temporarily. Three to six transects were established upstream

from the lower reach boundary at intervals of two

channel widths. If the site was an existing NAWQA

basic fixed site, the existing marked transects were

used. Information was collected to quantify ripariantree canopy cover, stream-habitat conditions (substrate,

channel width and depth, velocity, and discharge),

stream-bank conditions, and riparian-zone vegetation

on the stream flood plain or terrace (tables 11 and 12

in the Appendix).

Canopy Cover

Measurements of canopy shading were made

(and presented in table 11) using three different procedures: (1) Solar Pathfinder—measurements were taken

in accordance with procedures recommended by the

manufacturer (Solar Pathways, Glenwood Springs,

Colorado). Canopy shading reflected by the plastic

dome of the Solar Pathfinder was quantified in relation

to stream latitude and the month of sample collection.

Results are presented as the average percentage

of canopy shading in the stream reach; (2) spherical

densiometer—measurements of riparian-canopy

closure were made with a concave spherical densiometer, as described by Fitzpatrick and others (1998).

Results are presented as the average percentage of

canopy shading in the stream reach; and (3) open

canopy angle—the left and right canopy angles were

measured with a hand-held clinometer. The left and

right angles were subtracted from 180 degrees to give

the open canopy angle (in degrees). Percent shading

(CANSHADE) was calculated by summing left and

right canopy angles, dividing by 180, and multiplying

by 100.

Stream-Habitat Conditions

Stream width, depth, velocity, and bottom

substrate measurements were made along a minimum

of three transects; depth, velocity, and substrate were

measured at the stream thalweg (or the center of the

stream) and two equidistant points between that first

point and the right and left streambanks. Velocity,

reported in centimeters per second (cm/s), was determined at a depth equivalent to 0.6 times the measured

stream depth. Similarly, the percentage of clay, silt,

sand, gravel, and cobble was estimated visually (when

greater than 25 percent) at three points along a

minimum of three transects. Stream bankfull width

(Fitzpatrick and others, 1998) was measured, where

possible. Results are presented as the mean and

maximum velocity (centimeters per second), width

and depth (meters) (table 11), and average percentages

of substrate materials in the stream reach (table 12).

Stream discharge (in cubic feet per second) was

measured at the time of water-sample collection

(table 6).
DATA 25

Streambank Characteristics

Bank erosion was classified qualitatively at the

ends of stream transects, as described by Meador and

others (1993). Bank angle, vegetative cover, height,

and material composition were measured, and a Bank

Stability Index (BSI), modified from Simon and Hupp

(1992), was calculated, as given by Fitzpatrick and

others (1998). Values of the BSI are presented in

table 12.

Riparian-Zone Vegetation

Temporary, semiquantitative vegetation plots

were established at both ends of each stream transect,

extending onto the flood plain for 10 m. The percentage

ground cover of trees, shrubs, grasses, forbs, and bare

soil was estimated visually in a 20-m2 vegetation plot,

1 m on either side of the 10-m flood-plain transect. The

diameter at breast height (dbh) was measured from

trees for which at least half of the trunk was present in

the vegetation plot. Results are presented as the average

percent ground cover of vegetation categories in the

stream reach (table 12). The width of the woodedriparian corridor was measured from the ends of each

stream transect onto the flood plain. Distances greater

than 50 m were not measured but recorded as greater

than 50 m. Results are presented in table 11 as the

average wooded-riparian-zone width for the stream

reach. Quantification of wooded-riparian zones in

stream segments was discussed in a previous section.

Quality Assurance

Written field-sampling procedures for the study

were provided to all personnel prior to commencement

of field activities (protocol on file at U.S. Geological

Survey, Lakewood, Colorado). Additional training

was provided during practice field sessions prior to

the study and during the first week of sampling activities. Preprinted field data forms and sample labels

were prepared to ensure consistency of data collection

and sample integrity. Sample-identification codes

for biological samples were preassigned to facilitate

transmittal of information required for the laboratory

analytical-service request process and to ensure

accuracy of site and sample information. Field meters

were maintained and calibrated in accordance with

manufacturer recommendations. Submersible data

recorders used for productivity and respiration

estimates were calibrated in accordance with manufacturer (HydrolabTM Corporation, Austin, Texas) recommendations prior to deployment and following

retrieval. Batteries and DO membranes were replaced

in the data recorders at the end of each 48-hour

recording period. Quality-control samples included

blanks and replicate samples for water chemistry and

split samples and filter blanks for CHLa and AFDM.

Photodocumentation of stream reaches was supplemented by low-altitude aerial photography and video

footage of stream segments, as defined in this report.

DATA

The analytical results of this study are presented

in tables 6–12 in the Appendix. Table 6 lists field properties and suspended sediment. Table 7 lists results of

nutrient analyses and chlorophyll a and ash-free dry

mass. Tables 8 and 9 list all triazine and chloroacetamide herbicides and degradation products that were

detected in water samples. Table 10 lists summaries of

continuous data collected over a 48-hour period at each

site. Tables 11 and 12 list measurements of instream,

bank, and riparian-zone habitat. Results of periphyton

identification and quantification can be found at URL

http://wwwrcolka.cr.usgs.gov/nawqa. Results for

benthic invertebrate identification and quantification

can be found at URL http://wwwrcolka.cr.usgs.gov/

nawqa.

SUMMARY

Study design, methods, quality assurance,

and results are reported from a low-flow waterquality and habitat characterization study conducted

in August 1997 in a region of high agricultural intensity. The study represents a collaborative regional

synthesis effort among three NAWQA study units

(LIRB, EIWA, and UMIS) in the upper Mississippi

River Basin. The objectives of the study were to characterize chemical, biological, and habitat conditions

for 70 sites on Midwestern streams and rivers; to relate

results to regional differences in soil drainage and

wooded riparian conditions; to assess algal-nutrient

relations in reference to stream eutrophication; and to

describe responses of algal and invertebrate communities to agricultural nonpoint sources of contamination.

Methods are described for the collection and analysis
26 Water Quality and Habitat Conditions in Upper Midwest Streams Relative to Riparian Vegetation and Soil Characteristics,

August 1997: Study Design, Methods, and Data

of water-chemistry data, stream productivity and respiration, biological communities, habitat conditions,

agricultural land-use and landscape information, and

quality-assurance/quality-control procedures. With the

exception of algal and invertebrate community and

isotope data, data are summarized in tables 6 through

12 of the report. Biological-community data are

reported on the World Wide Web.

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APPENDIX

APPENDIX 33

Table 6. Basin characteristics, discharge, and selected water-quality properties

[mi2, square miles; STATSGO, Soil Conservation Service Soil Hydrologic Group; ft3/s, cubic feet per second; s.u., standard units; μS/cm, microsiemens per centimeter at 25 degrees Celsius;

mg/L, milligrams per liter; --, no data]

Site

number

U.S. Geological

Survey station

identification

Basin

area

(mi2)

STATSGO

score1

Riparian

tree density

(percent)2

Study

design

group3

Date in 1997

when water

and biological

samples were

collected

Discharge

(ft3/s)

pH

(s.u.)

Specific

conductance

(μS/cm)

Alkalinity

(mg/L)

Suspended

sediment,

total

(mg/L)

L01 05554000 186 3.20 3.4 4 15-Aug 4.8 8.2 619 184 224

L02 05554490 551 3.20 41.7 3 11-Aug 14 8.2 626 198 158

L03 05556500 196 2.40 24.2 1 11-Aug 18 7.8 466 134 95

L04 05559500 115 2.80 35.0 4 12-Aug 6.0 7.9 1,090 218 46

L05 05563000 119 2.60 23.6 1 12-Aug 26 7.9 681 150 157

L06 05564300 309 2.70 55.2 1 14-Aug 14 8.6 613 220 74

L07 05567500 767 2.70 45.9 3 13-Aug 47 8.1 558 212 55

L08 05568830 432 2.60 49.4 3 4-Aug 50 8.2 585 354 169

L09 05569875 271 2.50 38.0 1 5-Aug 60 7.4 467 162 43

L10 05570910 240 2.90 41.3 3 15-Aug 9.2 7.7 774 204 92

L12 05575850 129 2.80 55.0 3 8-Aug 0.0 7.4 654 240 252

L15 05580000 227 2.60 28.3 4 14-Aug 16 7.9 589 236 72

L16 05583900 118 2.60 61.0 1 6-Aug 0.21 7.7 581 272 53

L17 05584500 655 2.60 51.6 1 5-Aug 22 8.0 542 232 59

L18 05585800 306 2.60 43.5 1 6-Aug 2.0 7.9 618 282 104

L19 05586598 385 2.50 22.1 1 7-Aug 3.2 7.7 614 282 136

L20 05586645 132 2.90 43.4 3 7-Aug 0.0 7.9 616 250 63

L21 05587000 868 2.70 29.1 1 7-Aug 9.8 7.8 601 250 86

L22 05567000 93.9 2.90 35.7 3 14-Aug 2.1 7.9 815 210 40

L23 05568000 1,070 2.60 65.4 3 13-Aug 96 7.7 553 180 67

L24 05568800 62.7 2.60 25.2 2 4-Aug 9.3 8.0 663 228 135

I01 05451210 224 2.97 43.0 3 19-Aug 20 7.9 528 142 30.1

I02 05469980 214 2.83 49.0 3 18-Aug 15 8.3 645 261 14.9

I03 05420680 346 2.51 63.0 3 28-Aug 54 7.9 396 104 7.6

I04 05456510 153 2.93 11.0 4 27-Aug 74 7.5 683 255 258
34 Water Quality and Habitat Conditions in Upper Midwest Streams Relative to Riparian Vegetation and Soil Characteristics,

August 1997: Study Design, Methods, and Data I05 05449500 418 2.98 26.0 4 11-Aug 89 8.2 593 

I06 05462770 145 2.52 15.0 4 19-Aug 41 8.0 611 

I07 05420720 144 2.63 66.0 3 28-Aug 20 7.8 579 

I08 05420900 210 2.52 62.0 3 20-Aug 34 8.2 458 

I09 05471120 128 2.84 33.0 4 18-Aug 3.9 7.9 533 

I10 05458870 136 2.71 27.0 4 25-Aug 28 8.1 582 I11 05459300 294 2.80 19.0 4 26-Aug 75 8.4 593 I12 05449200 195 2.96 13.0 4 26-Aug 20 8.0 627 I13 05457950 250 2.61 57.0 1 27-Aug 36 8.0 457 I14 05463510 327 2.37 50.0 1 20-Aug 42 8.0 537 I15 05455500 574 2.41 45.0 1 11-Aug 37 7.8 473 I16 05421700 233 2.45 32.0 2 14-Aug 42 8.3 471 I17 05461390 150 2.49 4.0 2 25-Aug 22 7.9 488 I18 05473060 284 2.48 26.0 2 12-Aug 13 7.7 661 I19 05473400 533 2.81 25.0 2 13-Aug 7.9 8.3 569 I20 05455100 201 2.36 46.0 1 11-Aug 5.9 7.6 498 I21 05421870 119 2.31 54.0 1 14-Aug 6.2 7.8 579 I22 05464220 327 2.30 34.0 2 21-Aug 33 7.9 587 I23 05473550 167 2.72 16.0 2 13-Aug 7.0 7.8 1,220 I24 05452020 200 2.28 10.0 2 21-Aug 32 8.1 573 I25 05465310 154 2.49 26.0 2 12-Aug 6.5 8.0 442 M01 05319050 192 3.07 28.0 4 19-Aug 28 8.2 735 M02 05320270 130 3.38 31.0 4 18-Aug 35 8.3 539 M03 05317828 99 3.19 44.0 3 20-Aug 21 8.1 645 M04 05326150 190 3.10 59.0 3 28-Aug 97 8.0 751 

Table 6. Basin characteristics, discharge, and selected water-quality properties—Continued

[mi2, square miles; STATSGO, Soil Conservation Service Soil Hydrologic Group; ft3/s, cubic feet per second; s.u., standard units; μS/cm, microsiemens per centimeter a

mg/L, milligrams per liter; --, no data]

Site

number

U.S. Geological

Survey station

identification

Basin

area

(mi2)

STATSGO

score1

Riparian

tree density

(percent)2

Study

design

group3

Date in 1997

when water

and biological

samples were

collected

Discharge

(ft3/s)

pH

(s.u.)

Specific

conductance

(μS/cm)
APPENDIX 35

M05 05320450 317 3.42 35.0 3 19-Aug 50 8.1 657 M06 05319360 133 3.07 40.0 3 19-Aug 22 8.4 758 M07 05326250 180 2.99 54.0 1 21-Aug 240 7.6 781 M08 05318050 186 2.87 31.0 2 20-Aug 47 8.1 594 M09 05318240 232 2.88 37.0 1 14-Aug 24 8.2 591 M10 05320080 173 2.86 40.0 1 18-Aug 230 8.1 714 M11 05317170 162 2.88 50.0 1 13-Aug 49 8.2 785 M12 05304795 105 2.88 30.0 2 12-Aug 6.7 7.6 1,500 M13 05316985 250 3.20 0.0 4 13-Aug 89 8.0 1,060 M14 05326700 163 3.11 2.0 4 28-Aug 190 7.7 698 M15 05312000 112 3.20 9.0 4 12-Aug 14 8.0 1,750 M18 05320230 111 3.30 27.0 4 20-Aug 48 8.2 675 M19 05303900 149 2.84 9.0 2 11-Aug 100 8.1 512 M20 05318630 100 3.05 10.0 2 15-Aug 33 8.1 824 M21 05317800 150 2.96 6.0 2 20-Aug 26 8.1 746 M22 05318178 111 2.80 0.0 2 14-Aug 10 8.7 616 M23 05314500 315 2.99 3.0 2 11-Aug 81 8.3 959 M24 05318138 104 2.84 3.0 2 14-Aug 12 8.1 433 M25 05318800 60 2.95 0.0 2 21-Aug 63 7.6 806 M27 05314510 120 3.22 0.0 4 25-Aug 28 8.1 1,360 

1STATSGO scores were calculated by weighted averaging of the spatial distribution of Soil Hydrologic Groups in each stream basin, as explained in “Characterizat

Basins” subsection.

2The percentage of trees in a 100-meter buffer zone on both streambanks was calculated for stream segments using digital raster graphic images from 7.5-minute U

graphic maps. The length of a stream segment in miles was defined as the base-10 logarithm of the basin area.

3Study design groups: 1, good riparian conditions, moderately well-drained soils; 2, poor riparian conditions, moderately well-drained soils; 3, good riparian cond

4, poor riparian conditions, poorly drained soils.

Table 6. Basin characteristics, discharge, and selected water-quality properties—Continued[mi2, square miles; STATSGO, Soil Conservation Service Soil Hydrologic Group; ft3/s, cubic feet per second; s.u., standard units; μS/cm, microsiemens per centimeter amg/L, milligrams per liter; --, no data]

Site

number

U.S. Geological

Survey station

identification

Basin

area

(mi2)

STATSGO

score1

Riparian

tree density

(percent)2

Study

design

group3

Date in 1997

when water

and biological

samples were

collected

Discharge

(ft3/s)

pH

(s.u.)

Specific

conductance

(μS/cm)
36

August 1997: Study Design, Methods, and DataWater Quality and Habitat Conditions in Upper Midwest Streams Relative to Riparian Vegetation and Soil Characteristics,

Table 7. Concentrations of nutrients, organic carbon, chlorophyll a in water samples, and periphyton chlorophyll and ash-free dry mass

[mg/L, milligrams per liter; N, nitrogen; NO2, nitrite; NO3, nitrate; P, phosphorus; μg/L, micrograms per liter; mg/m2, milligrams per square meter; g/m2, grams per square meter; <, less than; --, no data]

Site

number

U.S.

Geological

Survey

station

identification

Nitrogen,

ammonia,

dissolved

(mg/L

as N)

Nitrogen,

ammonia

plus

organic,

dissolved

(mg/L

as N)

Nitrogen,

ammonia

plus

organic,

total

(mg/L

as N)

Nitrogen,

nitrite,

dissolved

(mg/L

as N)

Nitrogen,

NO2 plus

NO3,

dissolved

(mg/L

as N)

Phosphorus,

total

(mg/L

as P)

Phosphorus,

dissolved

(mg/L

as P)

Phosphorus,

ortho,

dissolved

(mg/L

as P)

Carbon,

organic,

dissolved

(mg/L)

Carbon,

organic,

suspended

(mg/L)

Chlorophyll a,

seston

(μg/L)

Chlorophyll a,

periphyton

(mg/m2)

Ash-free

dry mass,

periphyton

(g/m2)

L01 05554000 0.03 0.41 1.1 0.02 0.11 0.18 0.01 0.02 4.4 2.5 27.9 25.5 19.5

L02 05554490 0.02 0.33 0.87 <0.01 0.08 0.10 <0.01 0.02 7.2 2.3 27.0 13.1 20.6

L03 05556500 0.32 0.78 1.3 0.07 0.94 0.62 0.41 0.41 4.5 3.0 11.1 85.0 27.4

L04 05559500 0.03 0.26 0.61 <0.01 0.17 0.06 <0.01 0.02 2.9 1.0 16.3 34.3 18.2

L05 05563000 0.06 0.39 0.85 0.02 0.72 0.17 0.03 0.04 4.1 2.2 9.89 15.5 19.5

L06 05564300 <0.02 0.33 1.3 <0.01 <0.05 0.15 0.01 0.02 4.0 5.0 70.2 27.6 22.8

L07 05567500 0.02 0.37 0.81 0.02 0.55 0.13 0.05 0.06 3.9 1.9 24.3 40.1 21.0

L08 05568830 0.03 0.40 1.5 0.06 0.60 0.22 <0.01 0.01 6.1 5.0 125 12.9 31.5

L09 05569875 0.08 0.67 1.0 0.05 2.5 0.16 0.06 0.07 5.8 1.1 31.5 40.5 29.8

L10 05570910 0.08 0.49 0.86 0.02 0.24 0.15 0.07 0.07 3.8 1.4 14.0 9.96 17.8

L12 05575850 0.11 0.48 1.1 0.02 0.18 0.38 0.12 0.14 -- 1.1 6.4 8.35 11.2

L15 05580000 <0.02 0.30 0.23 0.02 0.69 0.03 0.02 0.02 2.6 1.3 7.0 15.3 19.1

L16 05583900 0.06 <0.20 0.53 <0.01 0.08 0.03 <0.01 0.01 3.6 0.70 12.2 51.5 43.5

L17 05584500 <0.02 0.32 0.80 0.02 0.52 0.12 0.02 0.03 4.1 1.2 48.6 33.3 29.0

L18 05585800 0.02 0.22 0.91 0.01 <0.05 0.10 0.02 0.02 4.2 2.1 17.4 16.6 18.6

L19 05586598 0.06 0.21 0.50 0.04 2.2 0.07 0.04 0.06 3.0 1.1 9.8 25.9 24.8

L20 05586645 0.06 0.53 0.95 0.02 0.10 0.10 0.04 0.05 7.1 3.6 38.7 48.5 32.3

L21 05587000 0.03 0.21 0.86 0.01 <0.05 0.13 0.02 0.03 4.3 1.3 27.0 32.3 39.5

L22 05567000 0.15 0.87 1.2 0.08 1.3 0.21 0.14 0.13 5.9 1.3 21.6 12.3 17.2

L23 05568000 0.06 0.32 1.1 0.04 1.0 0.28 0.11 0.11 3.3 2.6 73.4 19.8 14.3

L24 05568800 0.11 0.54 0.89 0.08 2.2 0.16 0.07 0.08 4.1 0.90 15.7 24.7 26.1

I01 05451210 0.02 0.35 0.52 0.02 1.5 0.05 0.04 0.03 3.9 0.40 11.0 51.9 20.1

I02 05469980 0.03 0.44 0.45 0.03 2.7 0.18 0.17 0.16 3.7 0.30 9.8 29.4 22.7

I03 05420680 <0.02 0.52 0.53 0.15 0.17 0.03 0.02 <0.01 3.1 0.9 15.5 37.0 34.1
APPENDIX 37

I04 05456510 <0.02 0.74 1.1 0.08 3.7 0.16 <0.01 <0.01 7.2 4.5 3I05 05449500 0.05 0.31 1.8 0.02 1.7 0.24 <0.01 <0.01 3.7 5.0 7I06 05462770 0.03 0.23 0.54 0.04 6.0 0.07 0.04 <0.05 2.1 0.60 1I07 05420720 <0.02 0.98 1.0 0.06 1.2 0.19 0.16 0.02 3.5 1.0 I08 05420900 <0.02 0.23 0.37 0.04 2.7 0.03 0.02 0.01 3.0 0.30 1I09 05471120 0.04 0.33 1.1 0.02 0.29 0.12 0.04 0.04 5.6 0.60 8I10 05458870 <0.02 0.22 0.33 0.04 3.4 0.04 0.03 0.02 2.1 1.9 3I11 05459300 <0.02 0.44 2.1 0.02 0.44 0.20 <0.01 <0.01 5.0 2.8 17I12 05449200 <0.02 0.39 1.4 0.04 0.82 0.18 0.01 <0.01 4.1 2.1 12I13 05457950 <0.02 0.29 0.33 0.21 2.0 <0.01 0.01 <0.01 2.4 0.80 I14 05463510 <0.02 <0.20 0.28 0.03 3.5 0.09 0.07 0.06 2.6 0.50 1I15 05455500 0.81 1.4 2.1 0.05 0.27 0.46 0.17 0.18 5.2 2.5 6I16 05421700 <0.02 <0.20 0.31 0.05 3.5 0.03 0.04 0.03 2.1 0.50 1I17 05461390 <0.02 <0.20 0.26 0.07 8.3 0.05 0.04 0.05 1.6 0.40 2I18 05473060 1.3 2.0 3.5 0.03 0.17 0.78 0.31 0.31 7.5 4.4 10I19 05473400 <0.02 0.41 1.0 <0.01 <0.05 0.14 0.02 0.02 5.5 2.6 4I20 05455100 0.02 0.43 0.39 0.01 0.14 0.04 0.04 0.04 4.2 1.1 2I21 05421870 <0.02 0.94 1.2 0.36 0.72 0.17 0.09 <0.01 4.0 0.80 1I22 05464220 <0.02 0.20 0.57 0.05 3.8 0.05 0.05 0.04 2.4 0.50 1I23 05473550 0.08 0.52 1.4 0.01 0.14 0.53 0.23 0.25 5.9 2.7 8I24 05452020 <0.02 <0.20 0.56 0.03 2.6 0.06 0.05 0.06 2.4 0.50 1I25 05465310 0.14 0.53 1.0 0.02 0.68 0.18 0.05 0.06 4.6 2.0 3M01 05319050 <0.02 0.57 1.7 0.01 1.6 0.12 <0.01 <0.01 4.3 4.0 8M02 05320270 <0.02 0.74 1.2 0.03 2.9 0.17 0.05 0.05 8.0 3.1 5M03 05317828 <0.02 0.31 0.58 0.04 6.4 0.06 0.03 0.04 3.7 0.50 

Table 7. Concentrations of nutrients, organic carbon, chlorophyll a in water samples, and periphyton chlorophyll and ash-free dry mass—

[mg/L, milligrams per liter; N, nitrogen; NO2, nitrite; NO3, nitrate; P, phosphorus; μg/L, micrograms per liter; mg/m2, milligrams per square meter; g/m2, grams per square 

Site

number

U.S.

Geological

Survey

station

identification

Nitrogen,

ammonia,

dissolved

(mg/L

as N)

Nitrogen,

ammonia

plus

organic,

dissolved

(mg/L

as N)

Nitrogen,

ammonia

plus

organic,

total

(mg/L

as N)

Nitrogen,

nitrite,

dissolved

(mg/L

as N)

Nitrogen,

NO2 plus

NO3,

dissolved

(mg/L

as N)

Phosphorus,

total

(mg/L

as P)

Phosphorus,

dissolved

(mg/L

as P)

Phosphorus,

ortho,

dissolved

(mg/L

as P)

Carbon,

organic,

dissolved

(mg/L)

Carbon,

organic,

suspended

(mg/L)

C

ph

se

(
38 Water Quality and Habitat Conditions in Upper Midwest Streams Relative to Riparian Vegetation and Soil Characteristics,

August 1997: Study Design, Methods, and Data M04 05326150 <0.02 0.80 1.3 0.08 8.6 0.40 0.27 0.24 6.9 0.80 

M05 05320450 <0.02 0.53 1.2 0.02 2.6 0.16 0.06 0.07 5.6 1.4 M06 05319360 <0.02 0.50 0.89 0.02 7.6 0.08 0.04 0.05 4.6 0.50 M07 05326250 0.02 0.75 1.1 0.04 12 0.24 0.16 0.15 7.1 0.50 M08 05318050 0.08 0.58 1.1 0.04 3.2 0.13 0.05 0.05 5.3 1.5 M09 05318240 0.03 0.64 1.6 0.04 2.1 0.13 <0.01 0.01 5.8 1.6 M10 05320080 0.02 0.70 1.1 0.02 10 0.14 0.09 0.09 6.6 0.70 M11 05317170 <0.02 0.50 0.59 0.02 4.6 0.11 0.07 0.09 4.2 0.90 M12 05304795 0.03 0.53 1.0 0.01 0.21 0.08 <0.01 <0.01 6.2 1.6 M13 05316985 0.02 0.52 0.7 0.03 10 0.06 0.03 0.04 4.3 0.60 M14 05326700 <0.02 0.25 1.2 <0.01 0.64 0.16 0.01 <0.01 9.5 2.1 M15 05312000 <0.02 0.91 1.5 0.07 0.97 0.18 0.14 0.13 8.9 0.60 M18 05320230 <0.02 0.29 1.4 0.03 9.5 0.17 0.03 0.03 5.3 1.0 M19 05303900 <0.02 0.94 1.9 0.02 0.68 0.36 0.07 0.07 11 2.5 M20 05318630 <0.02 0.38 0.68 0.02 5.7 0.09 0.03 0.04 3.8 1.5 M21 05317800 0.02 0.46 0.9 0.05 3.2 0.06 0.02 0.02 4.9 0.70 M22 05318178 <0.02 0.58 1.5 0.02 2.3 0.23 0.10 0.11 5.6 3.2 M23 05314500 0.02 0.64 1.9 0.04 3.8 0.44 0.21 0.23 8.5 5.0 M24 05318138 0.78 2.3 3.7 0.1 0.62 0.19 0.03 0.03 11 1.7 M25 05318800 0.04 0.50 1.4 0.03 8.1 0.44 0.27 0.28 4.8 2.7 M27 05314510 <0.02 0.73 0.95 0.05 13 0.10 0.08 0.06 5.9 0.60 

Table 7. Concentrations of nutrients, organic carbon, chlorophyll

a in water samples, and periphyton chlorophyll and ash-free dry mass—

[mg/L, milligrams per liter; N, nitrogen; NO2, nitrite; NO3, nitrate; P, phosphorus; μg/L, micrograms per liter; mg/m2, milligrams per square meter; g/m2, grams per squar

Site

number

U.S.

Geological

Survey

station

identification

Nitrogen,

ammonia,

dissolved

(mg/L

as N)

Nitrogen,

ammonia

plus

organic,

dissolved

(mg/L

as N)

Nitrogen,

ammonia

plus

organic,

total

(mg/L

as N)

Nitrogen,

nitrite,

dissolved

(mg/L

as N)

Nitrogen,

NO2 plus

NO3,

dissolved

(mg/L

as N)

Phosphorus,

total

(mg/L

as P)

Phosphorus,

dissolved

(mg/L

as P)

Phosphorus,

ortho,

dissolved

(mg/L

as P)

Carbon,

organic,

dissolved

(mg/L)

Carbon,

organic,

suspended

(mg/L)

C

p

s
APPENDIX 39

Table 8. Concentrations of triazine herbicides and degradation products[μg/L, micrograms per liter; <, less than]

Site

number

U.S. Geological

Survey station

identification

Atrazine

(μg/L)

Deethylatrazine

(μg/L)

Deisopropylatrazine

(μg/L)

Cyanazine

(μg/L)

Cyanazine amide

(μg/L)

Hydroxyatrazine

(μg/L)

L01 05554000 0.95 0.13 0.14 0.64 0.24 0.50 L02 05554490 0.22 0.05 0.08 0.13 0.12 0.50 L03 05556500 0.73 0.10 0.36 0.57 0.06 0.92 L04 05559500 0.08 <0.05 <0.05 <0.05 <0.05 0.48 L05 05563000 0.40 0.10 0.10 0.14 0.12 1.5 L06 05564300 0.09 <0.05 0.05 <0.05 0.05 0.24 L07 05567500 0.19 0.07 0.07 0.20 0.07 0.25 L08 05568830 0.37 0.13 0.11 0.09 0.09 1.8 L09 05569875 0.30 0.13 0.14 0.10 0.10 0.69 L10 05570910 0.13 0.05 0.05 0.12 0.15 0.42 L12 05575850 0.34 0.18 0.15 <0.05 0.11 7.3 L15 05580000 0.56 0.11 0.07 <0.05 0.10 0.46 L16 05583900 0.56 0.11 0.09 0.17 0.31 3.2 L17 05584500 0.56 0.21 0.20 0.14 0.19 1.2 L18 05585800 1.5 0.39 0.33 0.62 1.2 7.2 L19 05586598 0.26 0.18 0.17 <0.05 0.18 2.2 L20 05586645 0.60 0.23 0.15 0.09 0.20 8.8 L21 05587000 0.28 0.08 0.09 <0.05 <0.05 2.1 L22 05567000 0.35 0.09 <0.05 0.54 0.15 0.57 L23 05568000 0.33 <0.05 0.05 0.05 <0.05 <0.20 L24 05568800 0.19 0.10 0.07 <0.05 0.07 0.84 I01 05451210 0.17 0.13 0.08 <0.05 <0.05 <0.20 I02 05469980 0.17 0.11 0.07 <0.05 <0.05 <0.20 I03 05420680 0.14 0.12 <0.05 <0.05 <0.05 0.27 I04 05456510 0.09 0.06 <0.05 <0.05 <0.05 0.24 I05 05449500 0.05 <0.05 <0.05 <0.05 <0.05 <0.20 I06 05462770 0.16 0.12 0.05 <0.05 <0.05 <0.20 
40 Water Quality and Habitat Conditions in Upper Midwest Streams Relative to Riparian Vegetation and Soil Characteristics,

August 1997: Study Design, Methods, and Data I07 05420720 0.13 0.12 <0.05 <0.05 <0.05 <0.20 

I08 05420900 0.21 0.17 0.09 <0.05 <0.05 0.61 I09 05471120 0.23 0.12 0.05 0.14 <0.05 <0.20 I10 05458870 0.17 0.11 0.07 <0.05 <0.05 <0.20 I11 05459300 0.05 <0.05 <0.05 <0.05 <0.05 <0.20 I12 05449200 0.71 <0.05 <0.05 <0.05 <0.05 <0.20 I13 05457950 0.11 0.11 0.06 <0.05 <0.05 <0.20 I14 05463510 0.13 0.08 0.06 <0.05 <0.05 0.56 I15 05455500 0.15 0.12 0.10 <0.05 <0.05 0.75 I16 05421700 0.13 0.16 0.05 <0.05 <0.05 0.36 I17 05461390 0.19 0.18 0.06 <0.05 <0.05 <0.20 I18 05473060 0.77 0.17 0.21 0.16 0.14 1.0 I19 05473400 1.1 0.15 0.16 0.19 0.34 2.6 I20 05455100 0.18 0.09 0.07 <0.05 0.07 2.2 I21 05421870 0.25 0.08 0.05 <0.05 <0.05 1.6 I22 05464220 0.18 0.12 0.08 <0.05 <0.05 0.51 I23 05473550 0.24 0.10 0.12 <0.05 0.07 0.68 I24 05452020 0.08 0.10 0.13 <0.05 <0.05 0.51 I25 05465310 0.45 0.17 0.20 0.09 0.23 0.72 M01 05319050 0.05 <0.05 0.05 <0.05 <0.05 <0.20 M02 05320270 0.11 0.06 <0.05 <0.05 <0.05 0.36 M03 05317828 0.05 0.05 <0.05 <0.05 <0.05 <0.20 M04 05326150 0.23 0.08 0.09 <0.05 <0.05 0.35 M05 05320450 0.05 <0.05 <0.05 <0.05 <0.05 0.26 M06 05319360 <0.05 <0.05 <0.05 <0.05 <0.05 <0.20 M07 05326250 0.19 0.13 0.08 <0.05 <0.05 0.35 M08 05318050 0.07 0.06 0.07 <0.05 <0.05 0.21 

Table 8. Concentrations of triazine herbicides and degradation products—Continued

[μg/L, micrograms per liter; <, less than]

Site

number

U.S. Geological

Survey station

identification

Atrazine

(μg/L)

Deethylatrazine

(μg/L)

Deisopropylatrazine

(μg/L)

Cyanazine

(μg/L)

Cyanazine amide

(μg/L)

Hydroxyatrazine

(μg/L)
APPENDIX 41

M09 05318240 <0.05 0.05 <0.05 <0.05 <0.05 <0.20 M10 05320080 0.24 0.26 0.08 0.05 <0.05 0.33 M11 05317170 0.17 0.05 0.11 0.05 0.10 <0.20 M12 05304795 <0.05 <0.05 <0.05 <0.05 <0.05 <0.20 M13 05316985 0.17 0.06 0.34 0.07 0.22 <0.20 M14 05326700 0.17 0.06 <0.05 <0.05 <0.05 <0.20 M15 05312000 0.12 0.06 0.22 0.06 0.08 <0.20 M18 05320230 0.08 0.08 <0.05 <0.05 <0.05 <0.20 M19 05303900 0.12 0.05 0.06 0.13 0.05 0.23 M20 05318630 0.10 0.07 0.15 0.12 <0.05 <0.20 M21 05317800 0.06 <0.05 0.10 <0.05 <0.05 <0.20 M22 05318178 0.06 <0.05 <0.05 <0.05 <0.05 0.25 M23 05314500 0.13 0.06 0.14 0.06 0.06 <0.20 M24 05318138 0.05 0.05 0.05 <0.05 <0.05 <0.20 M25 05318800 0.10 0.09 <0.05 <0.05 <0.05 <0.20 M27 05314510 0.10 0.12 0.33 0.06 0.18 0.30 

Table 8. Concentrations of triazine herbicides and degradation products—Continued

[μg/L, micrograms per liter; <, less than]

Site

number

U.S. Geological

Survey station

identification

Atrazine

(μg/L)

Deethylatrazine

(μg/L)

Deisopropylatrazine

(μg/L)

Cyanazine

(μg/L)

Cyanazine amide

(μg/L)

Hydroxyatrazine

(μg/L)
42

August 1997: Study Design, Methods, and DataWater Quality and Habitat Conditions in Upper Midwest Streams Relative to Riparian Vegetation and Soil Characteristics,

Table 9. Concentrations of chloroacetamide herbicides and degradation products

[μg/L, micrograms per liter; ESA, ethanesulfonic acid; <, less than]

Site

number

U.S. Geological

Survey station

identification

Acetochlor

(μg/L)

Acetochlor

ESA

(μg/L)

Acetochlor

oxanilic acid

(μg/L)

Alachlor

ESA

(μg/L)

Alachlor

oxanilic acid

(μg/L)

Metolachlor

(μg/L)

Metolachlor

ESA

(μg/L)

Metolachlor

oxanilic acid

(μg/L)

L01 05554000 <0.05 <0.20 <0.20 0.31 0.22 0.41 1.3 0.53

L02 05554490 <0.05 <0.20 <0.20 0.24 <0.20 0.05 1.1 0.26

L03 05556500 0.06 0.47 <0.20 0.47 0.45 0.16 1.2 0.47

L04 05559500 <0.05 <0.20 <0.20 <0.20 <0.20 <0.05 0.76 <0.20

L05 05563000 <0.05 0.35 0.72 <0.20 <0.20 0.19 0.82 0.35

L06 05564300 <0.05 <0.20 <0.20 0.22 <0.20 <0.05 1.0 0.24

L07 05567500 <0.05 <0.20 <0.20 <0.20 <0.20 0.06 0.78 <0.20

L08 05568830 <0.05 0.46 0.60 0.26 <0.20 0.14 1.9 0.34

L09 05569875 <0.05 <0.20 0.35 0.23 <0.20 0.11 1.5 0.29

L10 05570910 <0.05 0.21 <0.20 0.39 0.22 0.06 1.1 0.31

L12 05575850 <0.05 0.26 <0.20 0.21 <0.20 0.08 1.7 0.36

L15 05580000 <0.05 <0.20 <0.20 <0.20 <0.20 0.08 1.4 0.29

L16 05583900 <0.05 <0.20 <0.20 0.26 <0.20 0.10 0.99 0.31

L17 05584500 <0.05 0.25 0.29 <0.20 <0.20 <0.05 0.61 <0.20

L18 05585800 <0.05 0.53 0.95 0.27 <0.20 0.16 0.59 0.64

L19 05586598 <0.05 <0.20 <0.20 0.20 <0.20 <0.05 0.40 0.25

L20 05586645 <0.05 0.30 <0.20 0.44 <0.20 0.08 2.6 0.69

L21 05587000 <0.05 <0.20 <0.20 <0.20 <0.20 <0.05 0.39 0.20

L22 05567000 <0.05 <0.20 <0.20 0.29 0.24 <0.05 0.87 0.23

L23 05568000 <0.05 <0.20 <0.20 <0.20 <0.20 0.42 0.37 <0.20

L24 05568800 <0.05 <0.20 0.45 <0.20 <0.20 0.05 2.3 <0.20

I01 05451210 <0.05 0.49 0.28 0.62 0.21 0.09 4.7 0.92

I02 05469980 <0.05 0.41 <0.20 0.70 0.41 0.19 4.0 0.86

I03 05420680 <0.05 0.27 <0.20 2.1 <0.20 0.11 2.3 0.45

I04 05456510 <0.05 0.38 <0.20 1.4 <0.20 0.06 1.8 0.76

I05 05449500 <0.05 <0.20 0.24 1.8 <0.20 <0.05 4.1 0.71

I06 05462770 <0.05 0.82 0.21 3.5 0.28 0.33 6.2 1.1
APPENDIX 43

I07 05420720 <0.05 0.31 <0.20 2.3 0.54 0.06 2.3 I08 05420900 0.14 0.55 <0.20 3.2 <0.20 0.12 2.1 I09 05471120 <0.05 0.59 <0.20 0.23 <0.20 0.06 3.3 I10 05458870 <0.05 0.37 <0.20 1.3 <0.20 <0.05 3.1 I11 05459300 <0.05 0.42 <0.20 1.4 <0.20 <0.05 1.2 I12 05449200 <0.05 0.21 <0.20 3.0 <0.20 <0.05 4.0 I13 05457950 <0.05 <0.20 <0.20 1.2 <0.20 <0.05 2.5 I14 05463510 <0.05 <0.20 <0.20 2.2 0.31 0.11 6.7 I15 05455500 <0.05 <0.20 0.35 1.1 <0.20 0.06 1.3 I16 05421700 <0.05 0.21 <0.20 1.88 <0.20 <0.05 2.4 I17 05461390 <0.05 0.37 <0.20 1.09 <0.20 <0.05 3.4 I18 05473060 <0.05 0.69 0.87 0.66 0.24 0.18 2.8 I19 05473400 <0.05 0.45 0.53 0.86 0.30 0.11 1.4 I20 05455100 <0.05 0.34 0.40 1.3 0.29 <0.05 1.6 I21 05421870 <0.05 0.2 <0.20 1.42 <0.20 0.07 3.1 I22 05464220 <0.05 <0.20 <0.20 1.40 <0.20 <0.05 3.7 I23 05473550 <0.05 0.51 0.55 0.48 <0.20 0.06 1.2 I24 05452020 <0.05 <0.20 <0.20 1.2 <0.20 <0.05 2.2 I25 05465310 <0.05 0.8 0.61 0.90 <0.20 0.08 1.0 M01 05319050 <0.05 0.63 0.33 0.54 0.21 <0.05 1.6 M02 05320270 <0.05 1.3 0.60 1.0 0.21 0.09 3.8 M03 05317828 0.21 0.50 <0.20 0.82 <0.20 0.12 4.9 M04 05326150 <0.05 0.87 0.38 1.5 <0.20 0.12 2.8 M05 05320450 0.07 0.65 0.31 0.55 0.24 0.24 2.9 M06 05319360 <0.05 0.84 <0.20 0.45 <0.20 <0.05 2.5 M07 05326250 <0.05 1.2 0.42 2.0 <0.20 0.12 4.4 

Table 9. Concentrations of chloroacetamide herbicides and degradation products—Continued

[μg/L, micrograms per liter; ESA, ethanesulfonic acid; <, less than]

Site

number

U.S. Geological

Survey station

identification

Acetochlor

(μg/L)

Acetochlor

ESA

(μg/L)

Acetochlor

oxanilic acid

(μg/L)

Alachlor

ESA

(μg/L)

Alachlor

oxanilic acid

(μg/L)

Metolachlor

(μg/L)

Metolac

ESA

(μg/
44 Water Quality and Habitat Conditions in Upper Midwest Streams Relative to Riparian Vegetation and Soil Characteristics,

August 1997: Study Design, Methods, and Data M08 05318050 <0.05 0.68 0.26 0.82 <0.20 <0.05 1.6 

M09 05318240 <0.05 0.39 <0.20 0.27 <0.20 <0.05 2.7 M10 05320080 <0.05 1.6 0.55 1.2 <0.20 0.10 3.8 M11 05317170 <0.05 0.33 <0.20 0.75 <0.20 0.07 1.4 M12 05304795 <0.05 <0.20 1.4 0.39 <0.20 <0.05 0.2M13 05316985 <0.05 0.31 <0.20 0.41 <0.20 <0.05 0.9M14 05326700 <0.05 0.48 0.36 1.2 <0.20 0.09 1.7 M15 05312000 <0.05 0.42 0.59 <0.20 <0.20 <0.05 0.6M18 05320230 <0.05 0.73 0.23 1.0 <0.20 <0.05 3.5 M19 05303900 <0.05 <0.20 <0.20 <0.20 <0.20 <0.05 <0.2M20 05318630 <0.05 0.43 <0.20 0.21 <0.20 <0.05 1.0 M21 05317800 <0.05 0.27 <0.20 0.60 <0.20 0.10 2.6 M22 05318178 <0.05 0.22 <0.20 0.28 <0.20 0.07 1.4 M23 05314500 <0.05 <0.20 <0.20 0.64 <0.20 <0.05 <0.2M24 05318138 <0.05 0.33 <0.20 0.38 <0.20 <0.05 1.1 M25 05318800 <0.05 1.4 0.32 0.96 <0.20 0.09 3.1 M27 05314510 <0.05 0.38 0.21 2.4 0.35 0.11 3.4 

Table 9. Concentrations of chloroacetamide herbicides and degradation products—Continued

[μg/L, micrograms per liter; ESA, ethanesulfonic acid; <, less than]

Site

number

U.S. Geological

Survey station

identification

Acetochlor

(μg/L)

Acetochlor

ESA

(μg/L)

Acetochlor

oxanilic acid

(μg/L)

Alachlor

ESA

(μg/L)

Alachlor

oxanilic acid

(μg/L)

Metolachlor

(μg/L)

Metola

ESA

(μg/
APPENDIX 45

Table 10. Summary of continuous-monitoring data and estimates of stream productivity and respiration

[°C, degrees Celsius; μS/cm, microsiemens per centimeter at 25 degrees Celsius; s.u., standard units; mg/L, milligrams per liter; gO2/m3/hr, grams of oxygen per cubic meter per hour; s.u./hr, standard

units per hour; --, no data]

Site

number

U.S.

Geological

Survey

station

identification

Date in

1997 when

continuous

measurements

were taken

Water

temperature,

minimum

(°C )

Water

temperature,

maximum

(°C )

Specific

conductance,

median

(μS/cm)

pH,

median

(s.u.)

Dissolved

oxygen,

minimum

(mg/L)

Dissolved

oxygen,

maximum

(mg/L)

Dissolved

oxygen,

median

(mg/L)

Dissolved

oxygen,

saturation,

maximum

(percent)

Productivity,

maximum

(gO2/m3/hr)

Respiration,

maximum

(gO2/m3/hr)

pH,

daylight,

rate of

increase

(s.u./hr)

pH,

night,

rate of

decrease

(s.u./hr)

L01 05554000 10-Aug 19.7 28.1 714 8.2 3.8 7.9 6.1 94.9 0.34 0.06 0.077 0.014

L02 05554490 10-Aug 21.2 27.1 665 8.3 6.5 13 8 167 0.72 0.20 0.047 0.016

L03 05556500 13-Aug 20.3 25.2 562 7.8 3.5 7.0 5.2 87.7 0.48 0.20 0.048 0.022

L04 05559500 13-Aug 20.9 25.2 744 8.2 4.1 9.3 6.2 114 0.37 0.21 0.053 0.030

L05 05563000 13-Aug 19.5 25.5 564 8.0 6.0 7.8 6.6 93.9 0.12 0.00 0.037 0.006

L06 05564300 16-Aug 22.2 27.7 608 8.6 5.5 14 10 178 0.98 0.36 0.083 0.038

L07 05567500 14-Aug 20.8 24.5 557 8.2 3.4 6.3 4.8 75.6 0.32 0.19 0.038 0.036

L08 05568830 5-Aug 23.0 28.0 529 8.4 1.7 14 6.7 179 1.0 0.18 0.083 0.025

L09 05569875 4-Aug 22.9 28.7 445 8.8 3.5 15 6.7 198 1.0 0.80 0.075 0.078

L10 05570910 16-Aug 21.1 26.5 836 7.7 2.7 5.5 3.9 66.7 0.23 0.11 0.045 0.006

L12 05575850 8-Aug 18.4 21.1 659 7.6 1.2 3.8 2.3 42.7 0.02 0.13 0.002 0.005

L15 05580000 24-Aug 20.5 25.2 604 8.1 5.6 8.7 6.8 104 0.33 0.09 0.042 0.012

L16 05583900 5-Aug 17.4 24.0 573 7.6 4.9 8.5 6 99.5 0.57 0.04 0.025 0.008

L17 05584500 4-Aug 21.6 27.2 550 7.7 5.3 11 6.7 139 0.46 0.07 0.060 0.002

L18 05585800 5-Aug 21.3 29.8 641 8.0 4.3 7.7 6.3 102 0.44 0.27 0.027 0.021

L19 05586598 7-Aug 20.5 24.0 633 7.8 5.0 6.1 5.3 71.9 0.11 0.01 0.012 0.001

L20 05586645 8-Aug 20.9 22.7 644 8.1 3.8 8.6 6 101 0.14 0.26 0.005 0.019

L21 05587000 6-Aug 19.4 29.0 610 7.9 5.3 12 7.6 161 0.73 0.03 0.080 0.009

L22 05567000 15-Aug 21.2 25.5 751 7.9 4.6 7.3 5.3 87.9 0.32 0.01 0.022 0.001

L23 05568000 14-Aug 21.1 24.3 546 8.4 5.0 13 8 161 0.95 0.19 0.018 0.039

L24 05568800 3-Aug 23.4 30.0 665 8.2 3.4 7.6 4.5 101 0.63 0.15 0.033 0.021

I01 05451210 18-Aug 18.8 21.6 -- 8.1 8.8 12 9.2 104 0.53 0.05 0.043 0.015

I02 05469980 18-Aug 19.0 22.0 678 8.2 6.6 12 8.1 140 0.69 0.13 0.082 0.019

I03 05420680 28-Aug 20.3 24.5 389 8.0 5.8 8.3 6.4 103 0.32 0.00 0.057 0.009

I04 05456510 27-Aug 19.2 23.6 685 7.6 6.8 9.1 7.9 111 0.28 0.16 0.017 0.010

I05 05449500 13-Aug 17.1 21.3 -- 8.2 9.0 16 11 187 0.89 0.13 0.038 0.022

I06 05462770 20-Aug 16.4 23.7 605 8.1 7.5 9.7 8.2 117 0.24 0.00 0.025 0.004

I07 05420720 28-Aug 19.5 23.5 564 7.9 5.2 8.1 6.2 95.8 0.32 0.00 0.045 0.021
46 Water Quality and Habitat Conditions in Upper Midwest Streams Relative to Riparian Vegetation and Soil Characteristics,

August 1997: Study Design, Methods, and Data I08 05420900 20-Aug 17.2 23.3 449 8.2 7.0 10 7.8 124 0.44 0

I09 05471120 19-Aug 19.5 24.3 505 8.2 6.0 11 7.9 130 0.70 0I10 05458870 25-Aug 19.2 26.6 589 8.1 7.1 8.9 7.8 105 0.10 0I11 05459300 26-Aug 19.9 25.9 603 8.2 6.2 15 8.4 189 1.2 0I12 05449200 26-Aug 20 28.9 616 8.3 6.2 17 9 221 1.5 0I13 05457950 26-Aug 19.5 22.8 445 8.2 6.8 9.9 7.6 117 0.40 0I14 05463510 20-Aug 17.4 22.2 530 8.1 7.4 10 8 117 0.34 0I15 05455500 16-Aug 21.7 29.0 493 8.1 5.2 14 8.1 185 1.3 0I16 05421700 15-Aug 17.7 27.5 480 8.0 6.1 10 7.2 128 0.34 0I17 05461390 26-Aug 14.7 20.9 490 7.9 8.2 11 8.8 120 0.34 0

I18 05473060 13-Aug 20.4 25.8 624 8.2 4.8 15 7.8 182 1.2 0

I19 05473400 16-Aug 25.4 30.7 546 8.3 6.0 20 10 248 0.99 0

I20 05455100 11-Aug 18.7 21.2 494 7.8 7.2 9.7 7.6 108 0.24 0

I21 05421870 15-Aug 19.2 25.9 549 8.0 5.8 8.7 6.8 106 0.36 0

I22 05464220 22-Aug 17.0 25.5 576 8.2 6.5 13 7.9 164 0.78 0

I23 05473550 21-Aug 19.4 24.0 649 7.7 5.1 8.5 6.4 103 0.42 0

I24 05452020 22-Aug 17.8 23.6 518 8.1 7.2 11 7.9 128 0.38 0

I25 05465310 13-Aug 19.2 16.8 475 7.8 5.3 12 7.1 145 0.86 0

M01 05319050 27-Aug 21.4 23.6 756 8.3 7.2 8.6 7.7 105 0.16 0

M02 05320270 20-Aug 18.3 22.9 604 8.1 4.9 8.7 7.4 97.7 0.20 0

M03 05317828 29-Aug 19.4 23.0 677 8.1 6.8 9.2 7.5 107 0.18 0

M04 05326150 29-Aug 18.1 28.0 648 7.9 5.5 12 7.1 159 0.69 0

M05 05320450 23-Aug 18.3 22.9 675 8.3 7.5 12 8.5 140 0.56 0

M06 05319360 23-Aug 17.6 22.0 752 8.2 8.0 9.4 8.3 110 0.18 0

M07 05326250 3-Sep 16.9 23.0 844 8.2 7.8 10 8.6 117 0.28 0

M08 05318050 1-Sep 17.2 23.1 610 8.3 6.2 11 7.3 138 0.65 0

M09 05318240 26-Aug 21.2 24.7 710 7.7 6.6 10 7.6 129 0.53 0

M10 05320080 28-Aug 16.7 18.1 723 7.2 8.4 9.0 8.6 96.2 0.08 0

Table 10. Summary of continuous-monitoring data and estimates of stream productivity and respiration—Continued

[°C, degrees Celsius; μS/cm, microsiemens per centimeter at 25 degrees Celsius; s.u., standard units; mg/L, milligrams per liter; gO2/m3/hr, grams of oxygen per cubic met

units per hour; --, no data]

Site

number

U.S.

Geological

Survey

station

identification

Date in

1997 when

continuous

measurements

were taken

Water

temperature,

minimum

(°C )

Water

temperature,

maximum

(°C )

Specific

conductance,

median

(μS/cm)

pH,

median

(s.u.)

Dissolved

oxygen,

minimum

(mg/L)

Dissolved

oxygen,

maximum

(mg/L)

Dissolved

oxygen,

median

(mg/L)

Dissolved

oxygen,

saturation,

maximum

(percent)

Productivity,

maximum

(gO2/m3/hr)

Resp

max

(gO2/
APPENDIX 47

M11 05317170 20-Aug 17.6 21.9 789 8.2 8.1 9.4 8.6 109 0.11 0.

M12 05304795 25-Aug 17.5 22.6 1,510 7.5 5.4 10 6.9 121 0.70 0.

M13 05316985 22-Aug 17.5 22.4 1,210 7.3 7.5 10 8.5 119 0.27 0.

M14 05326700 No Data -- -- -- -- -- -- -- -- -- -

M15 05312000 No Data -- -- -- -- -- -- -- -- -- -M18 05320230 20-Aug 17.6 21.1 706 8.1 7.2 8.8 7.8 102 0.20 0.

M19 05303900 16-Aug 18.5 23.0 518 8.1 6.9 7.7 7.4 93.4 0.07 0.

M20 05318630 27-Aug 19.9 24.3 805 8.1 7.1 9.1 7.8 109 0.11 0.

M21 05317800 29-Aug 19.8 26.5 845 7.4 4.5 8.9 6.9 111 0.48 0.

M22 05318178 27-Aug 19.8 27.0 660 8.2 5.8 16 8.2 197 0.66 0.

M23 05314500 25-Aug 18.3 24.3 917 8.3 6.9 11 8.6 135 0.47 0.

M24 05318138 30-Aug 21.4 27.8 522 8.2 4.8 15 6.3 198 1.3 0.

M25 05318800 26-Aug 20.5 25.3 807 8.0 6.8 10 7.7 129 0.36 0.

M27 05314510 3-Sep 16.8 24.3 1,110 8.1 6.5 16 9.7 190 1.2 0.

Table 10. Summary of continuous-monitoring data and estimates of stream productivity and respiration—Continued

[°C, degrees Celsius; μS/cm, microsiemens per centimeter at 25 degrees Celsius; s.u., standard units; mg/L, milligrams per liter; gO2/m3/hr, grams of oxygen per cubic met

units per hour; --, no data]

Site

number

U.S.

Geological

Survey

station

identification

Date in

1997 when

continuous

measurements

were taken

Water

temperature,

minimum

(°C )

Water

temperature,

maximum

(°C )

Specific

conductance,

median

(μS/cm)

pH,

median

(s.u.)

Dissolved

oxygen,

minimum

(mg/L)

Dissolved

oxygen,

maximum

(mg/L)

Dissolved

oxygen,

median

(mg/L)

Dissolved

oxygen,

saturation,

maximum

(percent)

Productivity,

maximum

(gO2/m3/hr)

Respi

max

(gO2/
48 Water Quality and Habitat Conditions in Upper Midwest Streams Relative to Riparian Vegetation and Soil Characteristics,

August 1997: Study Design, Methods, and Data Table 11. Average width, depth, velocity, water clarity, and canopy conditions [m, meters; cm/s, centimeters per second; --, no data; >, greater than] Site number U.S. Geological Survey station identification Stream width, wetted channel (m) Stream width, bankfull (m) Stream depth, mean (m) Stream depth, maximum (m) Velocity, mean (cm/s) Velocity, maximum (cm/s) Euphotic- zone depth (m) Secchi depth (m) Open canopy angle (degrees) Cano

shad

Sol

Pathfi

(perc

L01 05554000 20 45 0.10 0.24 4.9 12 0.24 0.13 155 0 L02 05554490 45 61 0.66 0.79 1.2 4.0 0.32 0.21 122 9 L03 05556500 15 35 0.48 1.04 14 58 0.37 0.26 83 23 L04 05559500 9 30 0.31 0.91 15 58 0.67 0.50 80 41 L05 05563000 11 34 0.32 0.61 40 83 0.36 0.22 104 23 L06 05564300 27 31 0.44 0.76 5.2 13 0.58 0.36 87 16 L07 05567500 27 47 0.42 0.94 34 86 0.61 0.30 90 25 L08 05568830 15 27 0.50 0.70 27 45 0.35 0.17 79 30 L09 05569875 21 28 1.16 1.28 6.4 9.1 0.57 0.38 52 70 L10 05570910 17 22 0.41 0.82 7.3 15 0.60 0.38 40 53 L12 05575850 7 15 0.16 0.24 0.0 0.0 0.37 0.27 0 97 L15 05580000 11 22 0.28 0.49 24 61 0.54 0.34 58 51 L16 05583900 11 23 0.36 1.00 0.0 0.0 0.50 0.44 84 38 L17 05584500 18 33 1.05 1.22 0.0 0.0 0.44 0.31 45 29 L18 05585800 19 38 0.41 0.85 2.4 11 0.39 0.31 67 34 L19 05586598 8 25 0.37 1.07 13 36 0.61 0.37 17 86 L20 05586645 17 22 0.46 0.80 0.0 0.0 0.51 0.27 90 30 L21 05587000 13 40 0.13 0.27 18 36 0.32 -- 74 13 L22 05567000 9 17 0.29 0.49 5.2 27 0.61 -- 3 80 L23 05568000 32 57 0.64 1.20 26 47 0.54 0.29 137 4 L24 05568800 9 17 0.24 0.43 35 150 0.38 0.28 62 51 I01 05451210 11 21 0.17 0.30 30 51 0.69 -- 107 9 I02 05469980 12 17 0.43 0.66 12 39 0.91 -- 54 62 I03 05420680 18 21 0.51 1.16 19 33 1.20 -- 53 71 I04 05456510 17 21 0.82 0.98 15 18 0.91 0.18 116 14 I05 05449500 27 -- 0.50 0.75 18 37 0.52 -- 79 -- 
APPENDIX 49

I06 05462770 11 24 0.32 0.65 37 51 0.54 -- 107 3 I07 05420720 20 25 0.52 0.85 16 39 0.78 -- 29 77 I08 05420900 18 30 0.21 0.49 26 49 0.86 -- 88 39 I09 05471120 7 26 0.10 0.27 20 35 0.63 0.61 66 47 I10 05458870 10 16 0.29 0.73 34 45 0.54 0.43 104 19 I11 05459300 18 23 0.48 0.66 27 46 0.49 0.27 82 29 I12 05449200 14 21 0.36 0.61 21 38 0.39 0.18 104 25 I13 05457950 15 23 0.26 0.43 38 56 1.30 -- 77 27 I14 05463510 18 24 0.48 0.98 17 38 0.82 0.82 75 31 I15 05455500 26 29 0.40 0.70 12 18 0.70 0.32 61 23 I16 05421700 17 24 0.26 0.53 36 59 1.00 -- 66 70 I17 05461390 9 12 0.32 0.46 26 38 0.77 -- 30 61 I18 05473060 12 18 0.29 0.44 22 49 0.50 0.23 114 56 I19 05473400 21 31 0.25 0.41 17 33 0.57 0.34 86 41 I20 05455100 15 23 0.11 0.16 17 35 0.67 -- 59 80 I21 05421870 12 18 0.34 0.45 15 27 0.61 0.40 27 78 I22 05464220 24 33 0.20 0.43 31 42 0.61 -- 152 3 I23 05473550 10 17 0.16 0.36 20 40 0.27 0.21 53 57 I24 05452020 12 21 0.39 0.90 28 48 0.66 0.61 18 99 I25 05465310 13 16 0.28 0.67 9.2 30 0.48 0.30 100 19 M01 05319050 10 -- 0.31 0.58 17 25 0.76 -- 10 88 M02 05320270 16 -- 0.31 0.52 43 66 0.84 -- 8 86 M03 05317828 10 -- 0.37 0.55 31 51 0.30 -- 30 80 M04 05326150 12 -- 0.61 1.04 31 51 0.51 -- 33 65 M05 05320450 18 -- 0.63 0.85 10 20 0.56 -- 105 12 M06 05319360 13 -- 0.34 0.49 19 27 0.51 -- 78 17 

Table 11. Average width, depth, velocity, water clarity, and canopy conditions—Continued

[m, meters; cm/s, centimeters per second; --, no data; >, greater than]

Site

number

U.S. Geological

Survey station

identification

Stream

width,

wetted

channel

(m)

Stream

width,

bankfull

(m)

Stream

depth,

mean

(m)

Stream

depth,

maximum

(m)

Velocity,

mean

(cm/s)

Velocity,

maximum

(cm/s)

Euphoticzone

depth

(m)

Secchi

depth

(m)

Open

canopy

angle

(degrees)

Cano

shad

Sol

Pathfi

(perc
50 Water Quality and Habitat Conditions in Upper Midwest Streams Relative to Riparian Vegetation and Soil Characteristics,

August 1997: Study Design, Methods, and Data M07 05326250 13 -- 0.53 1.07 17 36 0.74 -- 30 34 

M08 05318050 11 -- 0.40 0.55 37 51 0.76 -- 23 62 M09 05318240 12 -- 0.34 0.76 27 45 0.72 -- 65 60 M10 05320080 15 -- 0.51 0.73 58 82 1.40 -- 52 25 M11 05317170 11 -- 0.44 0.76 27 58 0.41 -- 58 47 M12 05304795 8 -- 0.41 0.76 0.0 0.0 0.56 -- 52 49 M13 05316985 13 -- 0.54 0.73 50 61 0.61 -- 150 0 M14 05326700 9 -- 0.32 0.43 36 50 0.46 -- 146 0 M15 05312000 12 -- 0.42 0.79 9.4 15 0.56 -- 108 16 M18 05320230 13 -- 0.29 0.43 0.0 0.0 0.63 -- 159 1 M19 05303900 16 -- 0.75 0.98 22 37 0.66 -- 158 0 M20 05318630 10 -- 0.35 0.46 40 52 0.51 -- 142 7 M21 05317800 10 -- 0.34 0.44 22 48 0.25 -- 123 16 M22 05318178 12 -- 0.29 0.58 20 42 0.38 -- 158 4 M23 05314500 15 -- 0.56 0.91 28 47 0.36 -- 142 24 M24 05318138 9 -- 0.17 0.40 26 53 0.28 -- 172 0 M25 05318800 7 -- 0.70 0.82 43 59 0.61 -- 150 2 M27 05314510 10 -- 0.32 0.43 41 62 0.76 -- 148 0 

Table 11. Average width, depth, velocity, water clarity, and canopy conditions—Continued

[m, meters; cm/s, centimeters per second; --, no data; >, greater than]

Site

number

U.S. Geological

Survey station

identification

Stream

width,

wetted

channel

(m)

Stream

width,

bankfull

(m)

Stream

depth,

mean

(m)

Stream

depth,

maximum

(m)

Velocity,

mean

(cm/s)

Velocity,

maximum

(cm/s)

Euphoticzone

depth

(m)

Secchi

depth

(m)

Open

canopy

angle

(degrees)

Cano

shad

Sol

Pathfi

(perc
APPENDIX 51

Table 12. Average stream-bottom substrate, bank-stability, and riparian-vegetation cover conditions[--, no data]

Site

number

U.S.

Geological

Survey station

identification

Bottom

material,

percent

clay

Bottom

material,

percent

silt

Bottom

material,

percent

sand

Bottom

material,

percent

gravel

Bottom

material,

percent

cobble

Bottom

material,

percent

boulder

Bank

stability

index

Riparianzone

cover,

percent

trees

Riparianzone

cover,

percent

shrubs

Riparianzone

cover,

percent

grass

Ripari

zon

cove

perce

forb

L01 05554000 50 19 30 1 0 0 13 0 0 39 1 L02 05554490 14 46 17 13 10 0 13 8 12 39 33 L03 05556500 1 10 42 20 21 7 14 6 8 47 28 L04 05559500 0 10 31 29 30 0 14 5 1 2 89 L05 05563000 2 17 44 34 4 0 15 5 8 5 50 L06 05564300 0 4 54 23 5 13 14 9 8 20 54 L07 05567500 0 3 47 22 28 0 14 3 7 30 37 L08 05568830 0 8 48 28 17 0 12 18 6 18 40 L09 05569875 8 83 10 0 0 0 16 8 8 23 52 L10 05570910 15 10 23 31 21 0 12 9 8 29 34 L12 05575850 13 84 4 0 0 0 15 5 0 40 46 L15 05580000 0 6 41 46 8 0 15 8 4 12 63 L16 05583900 8 3 79 12 0 0 14 5 9 25 53 L17 05584500 3 33 39 10 15 0 17 4 10 21 43 L18 05585800 0 8 60 5 26 1 16 1 7 18 54 L19 05586598 0 29 14 28 30 0 15 9 7 19 59 L20 05586645 0 28 63 8 0 0 14 3 3 47 15 L21 05587000 3 17 55 26 0 0 15 6 4 43 34 L22 05567000 0 35 26 39 1 0 12 5 3 35 54 L23 05568000 0 12 82 5 1 0 16 8 3 52 33 L24 05568800 7 47 29 16 2 0 14 6 6 37 24 I01 05451210 1 0 71 24 5 0 14 6 29 23 30 I02 05469980 1 22 29 19 28 0 12 9 7 23 41 I03 05420680 1 7 84 9 0 0 14 6 3 32 32 I04 05456510 7 35 20 28 9 0 10 3 3 51 29 
52 Water Quality and Habitat Conditions in Upper Midwest Streams Relative to Riparian Vegetation and Soil Characteristics,

August 1997: Study Design, Methods, and Data I05 05449500 0 63 25 12 0 0 10 -- -- -- -- 

I06 05462770 0 2 93 2 2 0 13 3 7 74 16 I07 05420720 0 19 80 1 0 0 12 6 8 31 42 I08 05420900 0 0 98 2 0 0 12 6 10 23 35 I09 05471120 0 0 75 20 5 0 12 12 5 34 21 I10 05458870 0 8 85 8 0 0 13 4 1 32 52 I11 05459300 0 2 32 20 47 0 12 3 8 19 51 I12 05449200 28 28 44 0 0 0 10 6 8 22 54 I13 05457950 0 4 76 19 1 0 14 5 6 15 52 I14 05463510 0 13 65 14 7 0 12 6 3 16 68 I15 05455500 0 30 59 10 0 0 15 7 0 35 48 I16 05421700 0 3 38 11 47 0 14 4 22 9 46 I17 05461390 35 12 46 5 1 0 10 6 5 22 48 I18 05473060 0 11 48 7 35 0 12 6 10 28 38 I19 05473400 11 35 44 8 2 0 11 13 18 21 32 I20 05455100 0 28 72 0 0 0 15 10 3 36 29 I21 05421870 26 38 37 0 0 0 11 6 2 52 27 I22 05464220 0 2 91 4 3 0 11 1 1 86 11 I23 05473550 0 18 52 14 16 0 10 8 10 8 49 I24 05452020 0 14 73 12 0 0 11 6 2 9 56 I25 05465310 7 23 66 4 0 0 12 4 4 23 39 M01 05319050 0 22 72 0 0 6 14 8 1 -- 79 M02 05320270 0 44 12 34 9 0 13 4 0 -- 54 M03 05317828 0 33 16 49 1 1 13 5 10 -- 80 M04 05326150 0 1 46 17 17 19 12 6 5 -- 57 M05 05320450 0 53 25 22 0 0 12 3 7 -- 90 

Table 12. Average stream-bottom substrate, bank-stability, and riparian-vegetation cover conditions—Continued

[--, no data]

Site

number

U.S.

Geological

Survey station

identification

Bottom

material,

percent

clay

Bottom

material,

percent

silt

Bottom

material,

percent

sand

Bottom

material,

percent

gravel

Bottom

material,

percent

cobble

Bottom

material,

percent

boulder

Bank

stability

index

Riparianzone

cover,

percent

trees

Riparianzone

cover,

percent

shrubs

Riparianzone

cover,

percent

grass

Ripari

zon

cove

perce

forb
APPENDIX 53

M06 05319360 0 1 38 38 24 0 12 8 27 -- 62 0 5

M07 05326250 0 12 10 31 28 19 13 6 39 -- 22 17 16

M08 05318050 0 53 44 3 0 0 12 1 0 -- 92 0 7

M09 05318240 0 10 88 0 0 2 12 3 10 -- 73 0 13

M10 05320080 0 16 31 44 3 6 12 4 2 -- 83 0 10

M11 05317170 0 37 9 44 9 0 12 5 15 -- 72 0 8

M12 05304795 0 11 29 28 11 21 14 0 27 -- 73 0 0

M13 05316985 0 22 59 16 0 3 14 0 0 -- 100 0 0

M14 05326700 0 35 58 6 1 0 12 0 17 -- 83 0 0

M15 05312000 0 100 0 0 0 0 10 1 1 -- 98 0 0

M18 05320230 0 100 0 0 0 0 12 0 0 -- 100 0 0

M19 05303900 0 100 0 0 0 0 11 0 0 -- 78 5 17

M20 05318630 0 13 78 6 0 3 14 2 2 -- 91 0 5

M21 05317800 0 47 22 31 0 0 12 4 21 -- 66 5 2

M22 05318178 0 13 20 61 6 0 12 7 0 -- 83 0 10

M23 05314500 0 25 31 18 3 25 14 1 0 -- 98 0 1

M24 05318138 0 38 44 14 3 0 12 0 0 -- 100 0 0

M25 05318800 0 72 28 0 0 0 11 0 1 -- 99 0 0

M27 05314510 0 0 56 44 0 0 12 0 0 -- 100 0 0

Table 12. Average stream-bottom substrate, bank-stability, and riparian-vegetation cover conditions—Continued

[--, no data]

Site

number

U.S.

Geological

Survey station

identification

Bottom

material,

percent

clay

Bottom

material,

percent

silt

Bottom

material,

percent

sand

Bottom

material,

percent

gravel

Bottom

material,

percent

cobble

Bottom

material,

percent

boulder

Bank

stability

index

Riparianzone

cover,

percent

trees

Riparianzone

cover,

percent

shrubs

Riparianzone

cover,

percent

grass

Riparianzone

cover,

percent

forbs

Riparianzone

cover,

percent

crops

Riparianzone

cover,

percent

bare soil

or other
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