U.S. Department of the Interior

U.S. Geological Survey

Scientific Investigations Report 2009-5132

Upper Mississippi, Illinois, and Iowa River Basins

Missouri

River

Basin

Missouri-Mississippi

River Basin

Great Lakes Basins

Ohio River

Basin

Trends in Pesticide Concentrations in

Corn-Belt Streams, 1996-2006

NATIONAL WATER-QUALITY ASSESSMENT PROGRAM
Cover: Major drainage basins and cropping patterns in corn-belt streams, 1996–2006.
Trends in Pesticide Concentrations in 

Corn-Belt Streams, 1996–2006

By Daniel J. Sullivan, Aldo V. Vecchia, David L. Lorenz, Robert J. Gilliom, and 

Jeffrey D. Martin

National Water-Quality Assessment Program

Scientific Investigations Report 2009–5132

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

KEN SALAZAR, Secretary

U.S. Geological Survey

Marcia K. McNutt, Director

U.S. Geological Survey, Reston, Virginia: 2009

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reproduce any copyrighted materials contained within this report.

Suggested reference:

Sullivan, D.J., Vecchia, A.V., Lorenz, D.L., Gilliom, R.J., and Martin, J.D., 2009, Trends in pesticide concentrations in 

corn-belt streams, 1996–2006: U.S. Geological Survey Scientific Investigations Report 2009–5132, 75 p.
iii

Foreword

The U.S. Geological Survey (USGS) is committed to providing the Nation with credible scientific information that 

helps to enhance and protect the overall quality of life and that facilitates effective management of water, biological, energy, and mineral resources (http://www.usgs.gov/). Information on the Nation’s water resources is critical to 

ensuring long-term availability of water that is safe for drinking and recreation and is suifor industry, irrigation, 

and fish and wildlife. Population growth and increasing demands for water make the availability of that water, now 

measured in terms of quantity and quality, even more essential to the long-term sustainability of our communities and 

ecosystems. 

The USGS implemented the National Water-Quality Assessment (NAWQA) Program in 1991 to support national, 

regional, State, and local information needs and decisions related to water-quality management and policy (http://

water.usgs.gov/nawqa). The NAWQA Program is designed to answer: What is the condition of our Nation’s streams 

and ground water? How are conditions changing over time? How do natural features and human activities affect 

the quality of streams and ground water, and where are those effects most pronounced? By combining information 

on water chemistry, physical characteristics, stream habitat, and aquatic life, the NAWQA Program aims to provide 

science-based insights for current and emerging water issues and priorities. During 1991-2001, the NAWQA Program 

completed interdisciplinary assessments and established a baseline understanding of water-quality conditions in 51 

of the Nation’s river basins and aquifers, referred to as Study Units (http://water.usgs.gov/nawqa/studyu.html). 

In the second decade of the Program (2001–2012), a major focus is on regional assessments of water-quality 

conditions and trends. These regional assessments are based on major river basins and principal aquifers, which 

encompass larger regions of the country than the Study Units. Regional assessments extend the findings in the Study 

Units by filling critical gaps in characterizing the quality of surface water and ground water, and by determining status 

and trends at sites that have been consistently monitored for more than a decade. In addition, the regional assessments continue to build an understanding of how natural features and human activities affect water quality. Many 

of the regional assessments employ modeling and other scientific tools, developed on the basis of data collected at 

individual sites, to help extend knowledge of water quality to unmonitored, yet comparable areas within the regions. 

The models thereby enhance the value of our existing data and our understanding of the hydrologic system. In addition, the models are useful in evaluating various resource-management scenarios and in predicting how our actions, 

such as reducing or managing nonpoint and point sources of contamination, land conversion, and altering flow and 

(or) pumping regimes, are likely to affect water conditions within a region. 

Other activities planned during the second decade include continuing national syntheses of information on pesticides, 

volatile organic compounds (VOCs), nutrients, selected trace elements, and aquatic ecology; and continuing national 

topical studies on the fate of agricultural chemicals, effects of urbanization on stream ecosystems, bioaccumulation 

of mercury in stream ecosystems, effects of nutrient enrichment on stream ecosystems, and transport of contaminants to public-supply wells. 

The USGS aims to disseminate credible, timely, and relevant science information to address practical and effective 

water-resource management and strategies that protect and restore water quality. We hope this NAWQA publication 

will provide you with insights and information to meet your needs, and will foster increased citizen awareness and 

involvement in the protection and restoration of our Nation’s waters.

The USGS recognizes that a national assessment by a single program cannot address all water-resource issues of 

interest. External coordination at all levels is critical for cost-effective management, regulation, and conservation 

of our Nation’s water resources. The NAWQA Program, therefore, depends on advice and information from other 

agencies—Federal, State, regional, interstate, Tribal, and local—as well as nongovernmental organizations, industry, 

academia, and other stakeholder groups. Your assistance and suggestions are greatly appreciated. 

Matthew C. Larsen 

Associate Director for Water
iv

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v

Contents

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

Introduction.....................................................................................................................................................2

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

Study Design and Methods..........................................................................................................................2

Pesticide Trend Sites and Major River Basins.................................................................................2

Sample Collection and Processing....................................................................................................3

Sample Analysis....................................................................................................................................6

Preparation of Concentration Data for Trend Analysis ..................................................................6

Identification of Reporting Levels .............................................................................................6

Reassignment of the Concentration Value for Routine Nondetections..............................7

Rounding of Concentrations to a Consistent Level of Precision..........................................7

Adjustment of Concentrations for Temporal Changes in Recovery ....................................7

Reduction of Samples Collected Too Frequently in Time ......................................................7

Selection of Pesticides for Trend Analysis.......................................................................................7

Statistical Methods for Analyzing Trends in Pesticide Concentrations ......................................7

Seasonal Kendall (SEAKEN) Test for Site Trends...................................................................8

Seasonal Kendall (SEAKEN) Test for Regional Trends ........................................................11

Seasonal Wave (SEAWAVE) Model........................................................................................12

Seasonal Wave with Flow Adjustment (SEAWAVE–Q) Model ...........................................13

Trend Analysis Intervals and Model Comparisons...............................................................14

Use and Properties of Pesticides..............................................................................................................14

Use Trends ...........................................................................................................................................17

Physical and Chemical Properties...................................................................................................17

Trends in Pesticide Concentrations .........................................................................................................17

Comparison of SEAKEN and SEAWAVE .........................................................................................18

Overview of Trend Results for 1996–2002 ..............................................................................18

Overview of Trend Results for 2000–2006 ..............................................................................20

Influence of Flow Adjustment: Comparison of SEAWAVE and SEAWAVE-Q............................20

Overview of Trend Results for 1996–2002 ..............................................................................20

Overview of Trend Results for 2000-2006 ...............................................................................26

Detailed Analysis of Flow-Adjusted Trends ...................................................................................29

Atrazine.................................................................................................................................................29

Ohio River and Great Lakes Basins (sites 1-13)....................................................................29

Mississippi and Missouri River Basins (sites 14–31)...........................................................34

Trends in Relation to Changes in Use Intensity ....................................................................34

Acetochlor............................................................................................................................................35

Ohio River and Great Lakes Basins (sites 1–13) ...................................................................35

Mississippi and Missouri River Basins (sites 14–31)...........................................................35

Trends in Relation to Changes in Use Intensity ....................................................................35
vi

Metolachlor..........................................................................................................................................38

Ohio River and Great Lakes Basins (sites 1–13) ...................................................................38

Mississippi and Missouri River Basins (sites 14–31)...........................................................38

Trends in Relation to Changes in Use Intensity ....................................................................40

Alachlor................................................................................................................................................42

Ohio River and Great Lakes Basins (sites 1–13) ...................................................................42

Mississippi and Missouri River Basins (sites 14–31)...........................................................42

Trends in Relation to Changes in Use Intensity ....................................................................42

Cyanazine.............................................................................................................................................46

Trends in Relation to Changes in Use Intensity ....................................................................46

EPTC ..................................................................................................................................................50

Trends in Relation to Changes in Use Intensity ....................................................................50

Simazine ...............................................................................................................................................54

Ohio River and Great Lakes Basins (sites 1–13) ..................................................................54

Mississippi and Missouri River Basins (sites 14–31)...........................................................54

Trends in Relation to Changes in Use Intensity ....................................................................54

Metribuzin ............................................................................................................................................57

Trends in Relation to Changes in Use Intensity ....................................................................57

Prometon..............................................................................................................................................60

Ohio River and Great Lakes Basins (sites 1–13) ..................................................................60

Mississippi and Missouri River Basins (sites 14–31)...........................................................60

Chlorpyrifos..........................................................................................................................................62

Trends in Relation to Changes in Use Intensity ....................................................................62

Diazinon................................................................................................................................................65

Trends in Relation to Changes in Use Intensity ....................................................................65

Conclusions...................................................................................................................................................69

References Cited..........................................................................................................................................70

Appendixes ...................................................................................................................................................73

Appendix 1. Left-Censored Seasonal Kendall Trend Test and Approach for Estimating 

Trend Slope.............................................................................................................................73

Computing Slope........................................................................................................................74

Appendix 2. Methods for Fitting SEAWAVE and SEAWAVE-Q models...................................75
vii

Figures

1. Map of trends sites, major drainage basins, and cropping patterns...................................3

2. Trends in total annual pesticide use in major river basins of the Corn Belt, 

1992–2006 .....................................................................................................................................15

3. Observed and fitted acetochlor concentrations for selected sites for the 

1996–2002 analysis period using SEAWAVE (left) and SEAWAVE-Q (right)......................27

4. Observed and fitted acetochlor concentrations for selected sites for the 

2000–2006 analysis period using SEAWAVE (left) and SEAWAVE-Q (right)......................28

5. Observed and fitted simazine concentrations for selected sites for the 

2000–2006 analysis period using SEAWAVE (left) and SEAWAVE-Q (right)......................30

6. Observed and fitted prometon concentrations for selected sites for the 

2000–2006 analysis period using SEAWAVE (left) and SEAWAVE-Q (right)......................31

7. Flow-adjusted trends in atrazine concentration for 1996–2002 and 

2000–2006 analysis periods.......................................................................................................32

8. Atrazine use intensity and stream-water concentrations for selected 

trend sites in the Corn Belt, 1996–2006 ...................................................................................33

9. Flow-adjusted trends in acetochlor concentrations for 1996–2002 and 

2000–2006 analysis periods.......................................................................................................36

10. Acetochlor use intensity and stream-water concentrations for selected 

trend sites in the Corn Belt, 1996–2006 ...................................................................................37

11. Flow-adjusted trends in metolachlor concentration for 1996–2002 and 

2000–2006 analysis periods ......................................................................................................39

12. Metolachlor use intensity and stream-water concentrations for selected 

trend sites in the Corn Belt, 1996–2006 ...................................................................................41

13. Flow-adjusted trends in alachlor concentration for 1996–2002 and 

2000–2006 analysis periods.......................................................................................................43

14. Alachlor use intensity and stream-water concentrations for selected 

trend sites in the Corn Belt, 1996–2006 ...................................................................................45

15. Flow-adjusted trends in cyanazine concentration for 1996–2002 and 

2000–2006 analysis periods.......................................................................................................47

16. Cyanazine use intensity and stream-water concentrations for selected 

trend sites in the Corn Belt, 1996–2006 ...................................................................................49

17. Flow-adjusted trends in EPTC concentration for 1996–2002 and 

2000–2006 analysis periods.......................................................................................................51

18. EPTC use intensity and stream-water concentrations for selected 

trend sites in the Corn Belt, 1996–2006 ...................................................................................52

19. Flow-adjusted trends in simazine concentration for 1996–2002 and 

2000–2006 analysis periods.......................................................................................................55

20. Simazine use intensity and stream-water concentrations for selected 

trend sites in the Corn Belt, 1996-2006 ....................................................................................56

21. Flow-adjusted trends in metribuzin concentration for 1996–2002 and 

2000–2006 analysis periods.......................................................................................................58

22. Metribuzin use intensity and stream-water concentrations for selected trend sites in 

the Corn Belt, 1996-2006 ............................................................................................................59
viii

Tables

1. Selected information for sampling sites in the study area....................................................4

2. Pesticides selected for trend analysis......................................................................................8

3. Number of uncensored samples and total number of samples for 1996–2002 and 

2000–2006 trend analysis periods ..............................................................................................9

4. Properties affecting the transport and fate of selected pesticides...................................18

5. Comparison of SEAKEN and SEAWAVE trend results for 1996–2002.................................19

6. Regional seasonal Kendall trend results for 1996–2002.......................................................21

7. Comparison of SEAKEN and SEAWAVE trend results for 2000–2006.................................22

8. Comparison of SEAWAVE and SEAWAVE-Q trend results for 1996–2002 .........................23

9. Comparison of SEAWAVE and SEAWAVE-Q trend results for 2000–2006 .........................24

10. Statistical comparison of unadjusted and flow-adjusted trend magnitudes for 

atrazine, acetochlor, and metolachlor for the 1996–2002 analysis period ........................25

11. Flow-adjusted trends in atrazine concentration and changes in atrazine 

use intensity for selected sites for the 1996–2002 and 2000–2006 trend 

analysis periods ..........................................................................................................................34

12. Flow-adjusted trends in acetochlor concentration and changes in 

acetochlor use intensity for selected sites for the 1996–2002 and 2000–2006 

trend analysis periods................................................................................................................38

13. Flow-adjusted trends in metolachlor concentration and changes in 

metolachlor use intensity for selected sites for the 1996–2002 and 2000–2006 

trend analysis periods................................................................................................................40

14. Flow-adjusted trends in alachlor concentration and changes in alachlor use 

intensity for selected sites for the 1996–2002 and 2000–2006 trend analysis 

periods..........................................................................................................................................44

15. Flow-adjusted trends in cyanazine concentration and changes in 

cyanazine use intensity for selected sites for the 1996–2002 and 2000–2006 

trend analysis periods................................................................................................................48

16. Flow-adjusted trends in EPTC concentration and changes in 

EPTC use intensity for selected sites for the 1996–2002 and 2000–2006 

trend analysis periods................................................................................................................53

23. Flow-adjusted trends in prometon concentration for 1996–2002 and 

2000–2006 analysis periods.......................................................................................................61

24. Flow-adjusted trends in chlorpyrifos concentration for 1996–2002 and 

2000–2006 analysis periods.......................................................................................................63

25. Chlorpyrifos use intensity and stream-water concentrations for selected 

trend sites in the Corn Belt, 1996–2006 ...................................................................................64

26. Flow-adjusted trends in diazinon concentration for 1996–2002 and 

2000–2006 analysis periods.......................................................................................................66

27. Diazinon use intensity and stream-water concentrations for selected 

trend sites in the Corn Belt, 1996–2006 ...................................................................................67
ix

17. Flow-adjusted trends in simazine concentration and changes in 

simazine use intensity for selected sites for the 1996–2002 and 2000–2006 

trend analysis periods................................................................................................................57

18. Flow-adjusted trends in metribuzin concentration and changes in 

metribuzin use intensity for selected sites for the 1996–2002 and 2000–2006 

trend analysis periods................................................................................................................60

19. Flow-adjusted trends in chlorpyrifos concentration and changes in 

chlorpyrifos use intensity for selected sites for the 1996–2002 and 2000–2006 

trend analysis periods................................................................................................................65

20. Flow-adjusted trends in diazinon concentration and changes in 

diazinon use intensity for selected sites for the 1996–2002 and 2000–2006 

trend analysis periods................................................................................................................68

A2-1. Choices for the input function describing seasonal variability of 

pesticide application rates (equation A2-1)...........................................................................75
x

Conversion Factors

SI to Inch/Pound

Multiply By To obtain

Length

micrometer (um) 0.00003937 inch (in)

meter (m) 3.281 foot (ft) 

meter (m) 1.094 yard (yd) 

Area

square kilometer (km2

) 247.1 acre

square kilometer (km2

) 0.3861 square mile (mi2)

Mass

gram (g) 0.03527 ounce, avoirdupois (oz)

kilogram (kg) 2.205 pound avoirdupois (lb)

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) as follows:

°F=(1.8×°C)+32

Horizontal coordinate information is referenced to the North American Datum of 1983 (NAD 83).

Specific conductance is given in microsiemens per centimeter at 25 degrees Celsius 

(μS/cm at 25 °C)

Concentrations of chemical constituents in water are given in micrograms per liter (μg/L).
Abstract

Trends in the concentrations of pesticides that commonly 

occur in streams and rivers of the Corn Belt of the United 

States were assessed, and the performance and application of 

several statistical methods for trend analysis were evaluated. 

Trends in the concentrations of 11 pesticides with sufficient 

data for trend assessment were assessed at up to 31 stream 

sites for two time periods: 1996–2002 and 2000–2006. Pesticides included in the trend analyses were atrazine, acetochlor, 

metolachlor, alachlor, cyanazine, EPTC, simazine, metribuzin, 

prometon, chlorpyrifos, and diazinon.

The statistical methods applied and compared were (1) a 

modified version of the nonparametric seasonal Kendall test 

(SEAKEN), (2) a modified version of the Regional Kendall 

test, (3) a parametric regression model with seasonal wave 

(SEAWAVE), and (4) a version of SEAWAVE with adjustment for streamflow (SEAWAVE-Q). The SEAKEN test is a 

statistical hypothesis test for detecting monotonic trends in 

seasonal time-series data, such as pesticide concentrations at a 

particular site. Trends across a region, represented by multiple 

sites, were evaluated using the regional seasonal Kendall test, 

which computes a test for an overall trend within a region by 

computing a score for each season at each site and adding the 

scores to compute the total for the region. The SEAWAVE 

model is a parametric regression model specifically designed 

for analyzing seasonal variability and trends in pesticide 

concentrations. The SEAWAVE-Q model accounts for the 

effect of changing flow conditions in order to separate changes 

caused by hydrologic trends from changes caused by other 

factors, such as pesticide use.

There was broad, general agreement between unadjusted 

trends (no adjustment for streamflow effects) identified by the 

SEAKEN and SEAWAVE methods, including the regional 

seasonal Kendall test. Only about 9 percent of the paired 

comparisons between SEAKEN and SEAWAVE indicated a 

difference in the direction of trend, and only one of these had 

differences significant at the 10-percent significance level. 

This consistency of results supports the validity and robustness 

of all three approaches as trend analysis tools. The SEAWAVE 

method is favored, however, because it has less restrictive 

data requirements, enabling analysis for more site/pesticide 

combinations, and can incorporate adjustment for streamflow 

(SEAWAVE-Q) with substantially fewer measurements than 

the flow-adjustment procedure used with SEAKEN. Analysis of flow-adjusted trends is preferable to analysis of nonadjusted trends for evaluating potential effects of changes in 

pesticide use or management practices because flow-adjusted 

trends account for the influence of flow-related variability. 

Analysis of flow-adjusted trends showed that most of the 

pesticides assessed were dominated by concentration downtrends in one or both analysis periods. Atrazine, metolachlor, 

alachlor, cyanazine, EPTC, and metribuzin—all major corn 

herbicides—showed more prevalent concentration downtrends 

during 1996–2002 compared to 2000–2006. The downtrends 

in concentrations generally correspond to regional downtrends 

in their use resulting from a variety of regulatory, market, and 

new-product forces that reduced their use in the Corn Belt 

during all or part of the study period. The insecticide diazinon 

had no clear trends during 1996–2002, but the trends were predominantly downward during 2000–2006, likely due to reductions in nonagricultural uses because of a regulatory phaseout. Simazine concentrations trended upward at most sites 

during both 1996–2002 and 2000–2006, a pattern explained 

by increasing agricultural use at some sites, but also likely by 

nonagricultural use in some of the watersheds. 

Comparisons of concentration and watershed use trends 

at 11 sites showed that concentration trends for atrazine, acetochlor, metolachlor, alachlor, cyanazine, EPTC, simazine, and 

metribuzin generally were similar to use trends for 50 percent 

or more of trend comparisons for use-trend sites evaluated. 

There were more frequent differences between concentration 

trends and agricultural use trends for chlorpyrifos and diazinon. Overall, combined study results indicate that trends in 

pesticide concentrations in Corn Belt streams and rivers during 

1996–2006 were explained largely by corresponding trends 

in annual use and that major reductions in the use of some 

pesticides resulting from regulatory actions or market forces 

generally resulted in corresponding declines in stream and 

river concentrations. Further evaluation of the causes of concentration trends will require more quantitative comparisons 

to use trends, given the uncertainty in use estimates, and more 

information is needed on the timing of changes in factors other 

than annual use, such as conservation tillage and buffer strips.

Trends in Pesticide Concentrations in Corn-Belt Streams, 

1996–2006

By Daniel J. Sullivan, Aldo V. Vecchia, David L. Lorenz, Robert J. Gilliom, and Jeffrey D. Martin
2 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

Introduction

More than 450 million kilograms (kg) of pesticides are 

used each year in the United States to control weeds, insects, 

and other pests in agricultural areas, urban areas, and a variety 

of other land-use settings. The use of pesticides has resulted 

in a range of benefits, including increased food production 

and reduction of insect-borne disease, but also raises questions about possible adverse effects on the environment, 

including water quality. Once released into the environment, 

pesticides can move through the hydrologic system to streams 

and groundwater, where they may have unintended effects 

on humans, aquatic life, or wildlife. In particular, pesticides 

frequently were detected in streams that drain agricultural and 

urban areas throughout the Nation during 1992–2001, and 

concentrations in many of these streams were greater than 

water-quality benchmarks for aquatic life (Larson and others, 

1999; Gilliom and others, 2006).

The use of pesticides has a long history and is changing 

constantly in response to such factors as regulations, market 

forces, and the development of new pesticides and genetically 

engineered crops. Pesticide use on agricultural crops began in 

the United States in the late 1800s, accelerated during the late 

1940s with the introduction of synthetic organic pesticides, 

such as 2, 4-D for weed control and DDT for insect control, 

and has evolved constantly to the present time (Timmons, 

2005). The annual use of pesticides in the United States was 

about 227 million kg in the 1930s, increased to nearly 454 

million kg by the late 1940s, peaked at nearly 680 million kg 

in the late 1970s, and was relatively steady in the range of 544 

million kg during the 1990s (Aspelin, 2003). Although total 

use has been relatively constant during the past 10–20 years, 

major changes have occurred in the use of many individual 

pesticides, as some have been reduced or phased out and 

others have been introduced. Evaluation of the effects of 

these changes in use on trends in pesticide concentrations in 

streams, as well as the additional influences of other changes, 

such as changes in management practices or streamflow conditions, is vital to understanding how the potential effects of 

pesticides on water quality may be changing over time.

Assessment of long-term trends in pesticide concentrations in stream water is difficult because there are relatively 

few streams with long-term records of concentrations, most 

such streams have had data gaps and sporadic sampling intensities over time, and most data on pesticide concentrations 

have high proportions of nondetections, resulting in highly 

censored data sets. These characteristics present unique challenges for statistical analysis. There is a need for methods that 

can be applied to these types of data in a statistically rigorous 

manner and that allow a balance of flexibility in application to 

sites with different types of monitoring data, thereby enabling 

consistent comparisons of trends among pesticides, streams, 

and regions.

Purpose and Scope

The purpose of this report is (1) to assess trends in the 

concentrations of commonly occurring pesticides in selected 

streams in the Corn Belt, an agricultural region that accounts 

for a major portion of national pesticide use, and (2) to evaluate the performance and application of statistical trend-assessment methods for subsequent application to other regions. 

Trends in the concentrations of 11 pesticides with sufficient 

data for trend analysis were assessed at 31 stream sites for two 

time periods: 1996–2002 and 2000–2006. The 31 sites have 

drainage areas that range from about 45 to 1,840,000 square 

kilometers (km2), and the percentage of land used for rowcrop 

production in the basins ranges from 4.3 to 91 percent. All 

water-quality data were collected as part of the USGS National 

Water-Quality Assessment (NAWQA) Program (U.S. Geological Survey, 2006a) or the USGS National Stream Quality 

Accounting Network (NASQAN) (U.S. Geological Survey, 

2006b). The statistical methods applied and compared were 

(1) a modified version of the nonparametric seasonal Kendall 

test described by Hirsch and Slack (1984), including a seasonal Kendall test for regional trends, and (2) the parametric 

SEAWAVE regression model specifically designed for analyzing seasonal variability and trends in pesticide concentrations 

(Vecchia and others, 2008), including a version of SEAWAVE 

with adjustment for streamflow.

Study Design and Methods

The combined objectives of providing a comprehensive 

analysis of trends in Corn Belt streams and developing a prototype of an approach that can be used more broadly required 

a systematic approach to site selection, data preparation, and 

statistical analysis. Each part of the approach is described 

below.

Pesticide Trend Sites and Major River Basins

Stream sites sampled for this study are distributed among 

five major drainages that include most of the Corn Belt (fig. 1). 

The Corn Belt is an intensively farmed agricultural region of 

the central United States that includes Iowa, Illinois, and parts 

of Indiana, Minnesota, South Dakota, Nebraska, Kansas, Missouri, and Ohio (Pickett and others, 2000). 

Corn and soybeans are the primary crops in the Corn 

Belt and are two of the most important crops produced in 

the United States, with estimated values of $15.1 and $12.5 

billion, respectively, in 2000 (U.S. Environmental Protection 

Agency, 2005). As of 1996, more than 80 percent of national 

corn acreage was in the Corn Belt and the top three soybeanproducing states in 1996—Iowa, Illinois, and Minnesota—

accounted for 44 percent of the total U.S. production of 

soybeans (U.S. Department of Agriculture, 1997).
Study Design and Methods 3

Figure 1. Map of trends sites, major drainage basins, and cropping patterns.

The 31 stream sites analyzed in this study are a subset 

of 201 sites that were sampled as part of the USGS National 

Water-Quality Assessment Program and/or the National 

Stream Quality Accounting Network, which were selected as 

part of a national effort to identify stream-monitoring sites that 

have adequate pesticide data for trend analysis (Martin, 2009). 

For the national screening, sites were required to have had 

samples analyzed at the USGS National Water Quality Laboratory (NWQL) by Gas Chromatography/Mass Spectrometry 

(GCMS), a minimum of 3 water years of data, and at least six 

samples per year. Of the 201 sites nationally, 49 were located 

within the Corn Belt. For this report, 31 sites with at least 

5 years of pesticide data and associated daily streamflow data 

were selected for trend analysis (table 1). Sites in the Corn 

Belt were partitioned into major drainage basins for regional 

trend analysis: the Ohio River Basin; the Upper Mississippi, 

Illinois, and Iowa River Basins; the Great Lakes Basins; the 

Missouri River Basin; and the combined Upper Mississippi 

and Missouri River Basin (fig. 1).

Sample Collection and Processing

Sampling strategies varied by site and among some years, 

but followed guidelines established by NAWQA or NASQAN. 

Samples were collected using a combination of fixed-interval 

and high-flow sampling procedures. The fixed-interval sampling was more frequent during the growing season when 

pesticide concentrations usually are greatest. In general, small 

streams were sampled more frequently than large streams and 

rivers. The typical frequency of sampling during the growing 

season was one to four samples per month and commonly was 

once a month or once every other month during other times of 

the year.

31 7

6

5

2

3

4

1

12

11 13

10

8

9

22

21

23

24

25

30 26

20

16 19

18 17

15

14

27

28

29

Alfalfa > 50

Corn > 20; Alfalfa > 20

Corn > 20; Soybeans > 20

Corn > 20; Wheat & other grains > 20

Corn > 50

Corn > 20; Alfalfa > 20; Soybeans > 20

Corn > 20; Alfalfa > 20; Wheat & other grains > 20

Corn > 20; Soybeans > 20; Wheat & other grains > 20

Soybeans > 50

 ( > is greater than)

Other crops or use

EXPLANATION

State boundary

Major rivers

Major river basins

Reporting site

 and identifier 0 100 200 400 Miles

0 200 400 100 Kilometers

Upper Mississippi, Illinois, and Iowa River Basins

Missouri

River

Basin

Missouri-Mississippi

River Basin

Great Lakes Basins

Ohio River

Basin

20

IP003821_Figure 01

Land use, in percent of indicated row crop

 (Nakagaki and others, 2007)
4 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006 Map num- ber Site short name USGS station number Site name Drainage area (km2

)

Percent land use1

Period of record

Number 

years 

sampled Cropland Pasture Urban Undevel- oped

Ohio River Basin

1 MAD 03267900 Mad River at St. Paris Pike at Eagle City, 

Ohio

802 64 10 9.4 16 1999 2004 6

2 OHIO-CA 03303280 Ohio River at Cannelton Dam at 

Cannelton, Indiana

250,000 13 19 3.8 62 1996 2005 10

3 LBUCK 03353637 Little Buck Creek near Indianapolis, 

Indiana

44.6 8.1 0.9 87 3.9 1992 2004 9

4 SUG-NP 394340085524601 Sugar Creek at County Road 400 South at 

New Palestine, Indiana

246 82 2.4 7.6 7.3 1992 2004 11

5 WHITE 03374100 White River at Hazleton, Indiana 29,300 48 7.9 11 32 1992 2006 11

6 WABASH 03378500 Wabash River at New Harmony, Indiana 75,800 59 18 3.4 18 1996 2005 10

7 OHIO-GRCH 03612500 Ohio River at Dam 53 near Grand Chain, 

Illinois

527,000 22 20 3.4 52 1996 2005 10

Great Lakes Basins

8 DUCK 04072050 Duck Creek at Seminary Road near 

Oneida, Wisconsin

247 56 20 5.4 19 1993 2004 8

9 MILW 04087000 Milwaukee River at Milwaukee, 

Wisconsin

1,800 35 18 16 29 1993 2004 9

10 CLINT 04161820 Clinton River at Sterling Heights, 

Michigan

803 4.3 5.6 48 36 1996 2006 9

11 STJOS 04178000 St. Joseph River near Newville, Indiana 1,600 45 25 7.2 22 1996 2004 8

12 AUGL 04186500 Auglaize River near Fort Jennings, Ohio 858 76 5.7 9.6 8.5 1996 2006 9

13 MAUM 04193500 Maumee River at Waterville, Ohio 16,400 73 5.4 10 9.9 1996 2006 11

Table 1. Selected information for sampling sites in the study area.[Number years sampled, number of years samples were collected during the 1996–2006 period; USGS, U.S. Geological Survey; km2, square kilometers]
Study Design and Methods

5

Map 

number Site short name USGS station number Site name Drainage area (km2) Percent land use1 Period of record Number years sam- pled Cropland Pasture Urban Undevel- oped

Upper Mississippi, Illinois, and Iowa River Basins

14 LCOBB 05320270 Little Cobb River near Beauford, 

Minnesota

336 87 0.6 5.8 5.5 1996 2006 11

15 MSSP-HA 05331580 Mississippi River below Lock and Dam 2 

at Hastings, Minnesota

96,000 43 17 2.5 32 1995 2004 9

16 MSSP-CL 05420500 Mississippi River at Clinton, Iowa 239,000 34 19 1.8 40 1996 2005 10

17 WAPS-TR 05420680 Wapsipinicon River near Tripoli, Iowa 897 74 4.6 7.2 14 1996 2004 8

18 IOWA-ROW 05449500 Iowa River near Rowan, Iowa 1,080 86 1.7 6.8 4.9 1996 2004 7

19 SFIOWA 05451210 South Fork Iowa River near New Providence, Iowa 580 86 3 6.7 4.4 1996 2006 11

20 IOWA-WAP 05465500 Iowa River at Wapello, Iowa 32,400 73 6.1 8.6 11 1996 2006 11

21 SUG-MIL 05525500 Sugar Creek at Milford, Illinois 1,160 91 1.9 5.6 1.4 1999 2004 6

22 DPLAI 05532500 Des Plaines River at Riverside, Illinois 1,630 16 2.1 63 16 1999 2004 6

23 ILLI-OTT 05553500 Illinois River at Ottawa, Illinois 28,300 58 3.4 23 14 1996 2004 9

24 SANG 05572000 Sangamon River at Monticello, Illinois 1,430 87 1.8 8.4 3 1996 2006 9

25 ILLI-VC 05586100 Illinois River at Valley City, Illinois 69,200 66 4.6 15 14 1996 2006 11

26 MSSP-GR 05587455 Mississippi River below Grafton, Illinois 447,000 48 18 2.8 13 1997 2005 8

Missouri River Basin

27 MIZZ-OM 06610000 Missouri River at Omaha, Nebraska 831,000 19 50 0.3 20 1996 2005 10

28 MAPLE 06800000 Maple Creek near Nickerson, Nebraska 954 81 0.5 4.6 14 1992 2006 10

29 PLATTE 06805500 Platte River at Louisville, Nebraska 221,000 21 1.3 3.4 73 1992 2006 11

30 MIZZ-HE 06934500 Missouri River at Hermann, Missouri 1,350,000 23 51 0.7 19 1995 2005 10

Combined Upper Mississippi and Missouri River Basin

31 MSSP-TH 07022000 Mississippi River at Thebes, Illinois 1,840,000 30 12 1.3 21 1995 2005 10

1Nakagaki and others, 2007. 

Table 1. Selected information for sampling sites in the study area.—Continued[Number years sampled, number of years samples were collected during the 1996–2006 period; USGS, U.S. Geological Survey; km2, square kilometers] 
6 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

Flow-weighted, depth- and width-integrated water 

samples for the analysis of pesticides were collected using 

Teflon-coated isokinetic samplers and processed following 

standard USGS methods (Shelton, 1994; Edwards and Glysson, 1999). Most water samples were collected from bridges 

or by wading, but samples from large rivers were collected 

from boats or cableways. All sample collection and processing 

equipment that came in contact with sample water was constructed of Teflon, glass, aluminum, or stainless steel. Equipment was cleaned with a dilute solution of phosphate-free 

detergent and rinsed with deionized water and pesticide-grade 

methanol. Water samples were filtered using pre-combusted 

glass-fiber filters with a nominal 0.7-micrometer (μm) pore 

diameter to remove suspended particulate matter and collected 

in baked amber glass bottles. Filtered samples were placed on 

ice in coolers and shipped to the NWQL in Denver, Colorado, 

for pesticide analysis. 

The quality of the stream-water pesticide data was evaluated using quality-control procedures presented in Mueller and 

others (1997). The field quality-control program included the 

collection of field blank water samples to asses potential contamination, replicate water samples to assess variability, and 

field matrix spikes to assess bias from the analytical method, 

potential pesticide degradation, or matrix effects.

Sample Analysis

Although various analytical techniques have been used 

to analyze samples for pesticide concentrations as part of 

the NAWQA Program, data for samples reported herein 

were analyzed solely at the NWQL by gas chromatography/

mass spectrometry (GCMS) with selected-ion monitoring 

(Zaugg and others, 1995; Lindley and others, 1996). In this 

method, solid-phase extraction is used to extract pesticides 

from filtered water samples. This method is available from 

the National Environmental Methods Index (http://www.nemi.

gov/) as USGS-NWQL method O–1126–95.

The GCMS analytical method does not have specified 

“detection limits” for each pesticide analyte. All detections 

conclusively identified by retention time and spectral characteristics are quantified (Zaugg and others, 1995, p. 19–21). 

Nondetections of pesticides (analyses that do not meet identification criteria based on retention time or spectral characteristics) are reported as less than a “reporting level” (for example: 

<0.005 micrograms per liter [μg/L]). The types and numerical 

values of reporting levels used to report nondetections of pesticides analyzed by GCMS have changed through time. 

See Martin (2009) for additional information on reporting 

procedures for GCMS analytical data.

Preparation of Concentration Data for 

Trend Analysis

Pesticide concentration data were prepared for trend 

analysis using the approach presented in Martin (2009). The 

principal data-preparation steps were to (1) identify routine 

reporting levels used to report nondetections for each sample; 

(2) reassign the concentration value for routine nondetections 

to the maximum value of the long-term method detection 

level; (3) round concentrations to a consistent level of precision for the concentration range; (4) adjust concentrations to 

compensate for temporal changes in bias of recovery of the 

GCMS analytical method; and (5) identify and remove samples collected too frequently in time for trend analysis. These 

steps are described briefly below. In addition to procedures 

applied by Martin (2009), low-level pesticide detections below 

the maximum long-term method detection level (maxLTMDL) were treated as nondetections at the maxLT-MDL.

Identification of Reporting Levels

Two types of reporting levels were identified for the 

purposes of trend analysis: routine and raised. Nondetections 

of pesticides (analyses that do not meet identification criteria based on retention time and spectral characteristics) are 

reported as less than the “routine” reporting level (for example: <0.005 μg/L). A small number of samples have “matrix 

effects” or other analytical difficulties that interfere with the 

measurement of pesticide retention time or spectral characteristics. Under conditions of interference, pesticides (1) cannot 

be identified/detected if they are present at concentrations less 

than the level of interference, and (2) are reported as nondetections less than a “raised” reporting level (for example: 

<0.03 μg/L; six times greater than the routine reporting level). 

Nondetections at raised reporting levels indicate the maximum 

possible concentration of the pesticide on the basis of the magnitude of the interference. Raised reporting levels always are 

greater than routine reporting levels (for a given time period). 

Raised reporting levels are sample-specific and determined by 

the magnitude of the interference. Routine reporting levels are 

the same for all samples (for a given time period) that are not 

affected by interference. 

The types and numerical values of routine reporting 

levels used to report nondetections analyzed by GCMS have 

changed over time. The value of the routine reporting level in 

effect for a given time period was determined from NWQL 

records and from review of the data set (Martin, 2009).
Study Design and Methods 7

Reassignment of the Concentration Value for 

Routine Nondetections

Temporal changes in the magnitude of reporting levels 

used to report routine nondetections have the potential to 

adversely affect trend analysis because they introduce a temporal “structure” to the timeseries of routine nondetections. 

The temporal structure of routine nondetections was removed 

for trend analysis by “reassigning” the temporally inconsistent concentration value to a uniform, temporally consistent 

concentration value. The concentration value of all pesticide 

nondetections at routine reporting levels was assumed to be 

less than the maximum value of the long-term method detection level for water years 1994–2006 (maxLT-MDL). As noted 

earlier, the detections at concentrations below maxLT-MDL 

were also treated as censored values at the maxLT-MDL.

Pesticide nondetections at raised reporting levels were not 

reassigned to maxLT-MDL. The maxLT-MDL is used in this 

report as a temporally consistent, conservatively high, estimate 

of the detection limit.

Rounding of Concentrations to a Consistent Level 

of Precision

The precision of pesticide data compiled for trend analysis changed through time. Concentration data were rounded 

consistently for trend analysis (Martin, 2009).

Adjustment of Concentrations for Temporal 

Changes in Recovery

Recovery of a pesticide compound in the analytical 

process is measured by analysis of “spiked” quality-control 

samples. “Spikes” are water samples to which a known 

amount of pesticide is added. Recovery is the measured concentration of the pesticide, divided by the expected concentration, then expressed as a percentage. Recovery measures 

bias in the analytical method. Bias is the systematic error in 

the measurement process and results in measurements that 

differ from the true (or expected) value in the same direction. 

Procedures used to adjust pesticide concentrations for temporal changes in recovery are presented by Martin and others 

(2009). Lowess smooths (Cleveland and McGill, 1985, p. 

833; Helsel and Hirsch, 2002, p. 45–47) were used to model 

recovery as a function of time. Temporal changes in lowessmodeled recovery of more than 50 percent were observed 

for some pesticides during 1992–2006 (Martin and others, 

2009). Measured concentrations of pesticides were adjusted 

to 100-percent recovery to compensate for changes in recovery through time. Concentrations were adjusted by dividing 

the measured concentration by the modeled recovery; where 

recovery was expressed as a fraction (Martin, 2009, p. 17).

Reduction of Samples Collected Too Frequently 

in Time

Samples collected too frequently in time typically have 

highly correlated, redundant information that is inappropriate 

for use in trend analyses. A weekly sampling frequency was 

considered to be the maximum frequency for trend analysis. 

All samples at a site were assigned to calendar weeks (Sunday 

through Saturday) and if two or more samples were collected 

during the same week, only the sample collected closest in 

time to noon Wednesday was retained for trend analysis.

Selection of Pesticides for Trend Analysis

Pesticides considered for trend analysis were all of 

the 52 compounds included in the USGS GCMS method 

described above. For a pesticide to be selected for trend analysis (table 2), data were required to be available for at least 

10 of the 31 sites, with 10 or more uncensored values (detections at or above maxLT-MDL) at each site during either of 

the trend assessment time periods (table 3). In addition, waterquality samples without streamflow data were not used in 

trend analysis by SEAWAVE or SEAWAVE-Q. The two trend 

assessment periods, which are explained in the section of this 

report, “Trend Analysis Intervals and Model Comparisons,” 

were partially overlapping 7-year periods: 1996–2002 and 

2000–2006. 

Statistical Methods for Analyzing Trends in 

Pesticide Concentrations

The statistical methods applied and compared for the 

selected sites and pesticides were (1) a modified version of 

the nonparametric seasonal Kendall test described by Hirsch 

and Slack (1984), herein referred to as SEAKEN; (2) a modified version of the Regional Kendall test (Helsel and Frans, 

2006); (3) a parametric regression model designed for analyzing seasonal variability and trends in pesticide concentrations 

(Vecchia and others, 2008), herein referred to as SEAWAVE; 

and (4) a version of SEAWAVE with adjustment for 

streamflow (SEAWAVE-Q).
8 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

Two related concepts—statistical significance and 

p-values—will be used to discuss and compare the trends 

results from the various methods. The less likely the obtained 

value of a particular trend statistic (such as the SEAKEN test 

statistic or the estimated trend slope from the SEAWAVE 

model) could have occurred by chance (that is, even if there 

was no trend), the more confidence we have that the trend is 

real and not an artifact of random variation. The p-value is the 

probability the trend statistic could have been as extreme, or 

more extreme, than the value obtained simply by chance. All 

p-values in this report are two-sided p-values, which means 

they do not distinguish between negative values (downtrends) 

or positive values (uptrends). Thus, the p-value is the probability that the absolute value of the trend statistic could have been 

as large, or larger than, the obtained value simply by chance. 

A significance level often is specified, which is the p-value 

below which a trend is deemed to be “statistically significant.” 

For this report, two significance levels—1 percent and 

10 percent—are used. A trend is significant at the 1-percent 

level if the p-value is less than or equal to 0.01 and significant 

at the 10-percent level if the p-value is less than or equal to 

0.10. The p-value sometimes is referred to as the “attained 

significance level,” because it is the smallest significance level 

for which the trend can be deemed significant.

Seasonal Kendall (SEAKEN) Test for Site Trends

The SEAKEN test is a statistical hypothesis test for 

detecting monotonic trends in seasonal time-series data, such 

as unadjusted pesticide concentrations at a particular site. The 

data requirements and assumptions of the test are described 

briefly in this section, and more detail is provided in 

Appendix 1 of this report.

The data requirements for applying the SEAKEN test 

in this report are similar to those described by Schertz and 

others (1991), with some modifications to accommodate high 

censoring rates that are typical of pesticides. The first consideration is to fix the number and length of the seasons that can 

be analyzed, on the basis of the sampling frequencies of the 

available data. Approximately monthly or higher sampling 

frequencies were maintained for most pesticide/site combinations during 1996–2002. However, sampling frequencies 

generally decreased to 6–12 samples per year after 2002. To 

facilitate comparisons between pesticides and sites as well as 

to maintain a balance between the power of the trend test and 

the number of stations that could be analyzed; a monthly sampling frequency was used for all the SEAKEN results. Data 

for some sites were thinned if necessary, particularly during 

1996–2002, to at most one sample per month and some sites 

were not analyzed, particularly for the 2000–2006 analysis 

period, because too many monthly values were missing to 

apply the SEAKEN test. For months with multiple samples, 

the sample closest to the middle of the month was used for 

analysis.

Pesticide CAS number Pesticide class Type of pesticide Maximum LT-MDL 

(μg/L)

Atrazine 1912-24-9 Triazine Herbicide 0.004

Acetochlor 34256-82-1 Acetanilide Herbicide 0.003

Metolachlor 51218-45-2 Acetanilide Herbicide 0.006

Alachlor 15972-60-8 Acetanilide Herbicide 0.002

Cyanazine 21725-46-2 Triazine Herbicide 0.009

EPTC 759-94-4 Thiocarbamate Herbicide 0.002

Simazine 122-34-9 Triazine Herbicide 0.006

Metribuzin 21087-64-9 Triazine Herbicide 0.014

Prometon 1610-18-0 Triazine Herbicide 0.007

Chlorpyrifos 2921-88-2 Organothiophosphate Insecticide 0.003

Diazinon 333-41-5 Organothiophosphate Insecticide 0.003

Table 2. Pesticides selected for trend analysis.

[Pesticides are listed in order of average use over the study period, from most to least. Other pesticides and pesticide degradation products for which results were 

available, but were not included in trend analyses due to insufficient uncensored data, include azinphos-methyl, benfluralin, butylate, carbaryl, carbofuran, dacthal, p,p′-DDE, deethylatrazine, desulfinylfipronil, desulfinylfipronil amide, dieldrin, 2,6-diethylaniline, disulfoton, ethalfluralin, ethoprophos, fipronil, fipronil 

sulfide, fipronil sulfone, fonofos, alpha-HCH, gamma-HCH, linuron, malathion, molinate, napropamide, parathion, parathion-methyl, pebulate, pendimethalin, 

cis-permethrin, phorate, propachlor, propanil, propargite, propyzamide, tebuthiuron, terbacil, terbufos, thiobencarb, triallate, and trifluralin. CAS, Chemical 

Abstracts Service; LT-MDL, long-term method detection level; μg/L, micrograms per liter]
Study Design and Methods

9

Table 3. Number of uncensored samples (detected concentrations at or greater than maxLT-MDL) and total number of samples for 1996–2002 and 2000–2006 trend analysis 

periods.—Continued

[maxLT-MDL, maximum value of the long-term method detection level]

Map 

number Site Time period

Number of uncensored samples/Total number of samples 

Atrazine Acetochlor Metolachlor Alachlor Cyanazine EPTC Simazine Metribuzin Prometon Chlorpyrifos Diazinon

1 MAD 1996–2002 77/80 25/80 62/80 3/80 2/80 0/81 37/80 5/80 8/80 1/81 8/81

1 MAD 2000–2006 78/79 27/79 62/79 3/79 2/79 0/80 50/79 5/79 9/79 2/80 6/80

2 OHIO-CA 1996–2002 93/93 63/93 92/93 36/93 43/93 0/93 86/93 19/93 54/93 15/93 43/93

2 OHIO-CA 2000–2006 82/82 60/82 80/82 21/82 4/82 0/82 73/82 9/82 44/82 2/82 32/82

3 LBUCK 1996–2002 95/95 45/95 82/95 9/95 12/95 2/95 73/95 4/95 95/95 18/95 92/95

3 LBUCK 2000–2006 75/75 36/75 59/75 4/75 1/75 1/75 50/75 1/75 75/75 5/75 71/75

4 SUG-NP 1996–2002 127/127 94/127 125/127 45/127 48/127 2/127 90/127 29/127 80/127 2/126 32/127

4 SUG-NP 2000–2006 101/101 72/101 98/100 20/101 9/86 0/86 86/101 17/101 58/100 4/100 15/100

5 WHITE 1996–2002 176/176 148/176 176/176 126/176 115/176 10/176 173/176 57/176 167/176 10/175 105/176

5 WHITE 2000–2006 108/108 95/108 108/108 58/108 17/103 3/103 108/108 23/108 98/108 5/107 69/108

6 WABASH 1996–2002 82/82 74/82 82/82 54/82 55/82 6/82 82/82 35/82 67/82 18/81 30/82

6 WABASH 2000–2006 81/81 73/81 81/81 36/81 12/81 3/81 81/81 24/81 57/81 11/81 24/81

7 OHIO-GRCH 1996–2002 91/91 70/91 91/91 48/91 48/91 2/91 91/91 23/91 54/91 25/90 35/91

7 OHIO-GRCH 2000–2006 83/83 66/83 83/83 27/83 4/83 1/83 83/83 8/83 44/83 8/83 25/83

8 DUCK 1996–2002 87/87 31/87 86/87 14/87 34/87 19/87 76/87 8/87 22/87 0/87 9/87

8 DUCK 2000–2006 77/77 31/77 77/77 12/77 16/77 17/77 66/77 2/77 22/77 0/77 8/77

9 MILW 1996–2002 72/72 18/72 38/72 5/72 22/72 4/72 60/72 1/72 38/72 1/72 27/72

9 MILW 2000–2006 64/64 19/64 36/64 3/64 8/64 1/64 56/64 1/64 33/64 1/64 34/64

10 CLINT 1996–2002 53/53 13/53 39/53 13/53 8/53 0/53 47/53 3/53 47/53 8/53 41/53

10 CLINT 2000–2006 47/47 15/47 36/47 4/47 0/42 0/42 32/47 0/47 40/47 1/47 28/47

11 STJOS 1996–2002 64/64 50/64 64/64 52/64 55/64 2/64 64/64 36/64 34/64 9/63 9/64

11 STJOS 2000–2006 29/29 24/29 29/29 12/29 7/29 1/29 29/29 11/29 18/29 2/29 2/29

12 AUGL 1996–2002 51/51 45/51 51/51 43/51 41/51 0/53 50/51 31/51 46/51 10/51 18/53

12 AUGL 2000–2006 51/52 49/52 50/51 19/52 10/48 0/50 51/52 18/52 48/51 5/53 9/53

13 MAUM 1996–2002 88/88 81/88 88/88 77/88 77/88 5/88 87/88 62/88 75/88 19/87 49/88

13 MAUM 2000–2006 64/64 64/64 64/64 48/64 25/60 2/60 64/64 45/64 57/64 11/64 26/6414 LCOBB 1996–2002 77/77 66/77 77/77 39/77 12/77 19/77 2/77 3/77 24/77 0/77 0/77

14 LCOBB 2000–2006 47/48 40/47 46/47 6/47 0/45 4/45 2/48 0/48 7/48 7/48 1/48

15 MSSP-HA 1996–2002 72/73 42/73 69/73 25/73 29/73 18/73 12/73 1/73 38/73 2/73 17/73

15 MSSP-HA 2000–2006 42/42 28/42 39/42 8/42 3/42 6/42 4/42 0/42 22/42 1/42 15/42

16 MSSP-CL 1996–2002 90/90 62/90 87/90 43/90 39/90 16/90 56/90 2/90 18/90 9/90 1/90

16 MSSP-CL 2000–2006 72/72 55/72 69/72 17/72 4/72 6/72 46/72 2/72 9/72 3/72 3/72

Table 3. Number of uncensored samples (detected concentrations at or greater than maxLT-MDL) and total number of samples for 1996–2002 and 2000–2006 trend analysis periods.[maxLT-MDL, maximum value of the long-term method detection level]
10 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006 Table 3. Number of uncensored samples (detected concentrations at or greater than maxLT-MDL) and total number of samples for 1996–2002 and 2000–2006 trend analysis periods.—Continued [maxLT-MDL, maximum value of the long-term method detection level] Map num- ber Site Time period Number of uncensored samples/Total number of samples Atrazine Acetochlor Metolachlor Alachlor Cyanazine EPTC Simazine Metribuzin Prometon Chlorpyrifos Diazinon 17 WAPS-TR 1996–2002 44/44 39/44 44/44 38/44 15/44 6/44 17/44 3/43 19/44 2/44 0/44 17 WAPS-TR 2000–2006 36/36 34/36 36/36 31/36 2/36 1/36 14/36 0/36 15/36 1/36 0/36 18 IOWA-ROW 1996–2002 71/71 53/71 71/71 41/71 11/71 9/71 5/71 3/71 46/71 0/71 1/71 18 IOWA-ROW 2000–2006 36/36 21/36 36/36 8/36 0/36 4/36 1/36 1/36 12/36 1/36 0/36 19 SFIOWA 1996–2002 66/66 40/66 66/66 18/66 6/66 6/66 24/66 2/66 22/66 1/66 0/66 19 SFIOWA 2000–2006 71/71 47/71 70/70 6/71 1/67 2/67 31/71 2/70 12/70 1/70 0/70 20 IOWA-WAP 1996–2002 98/98 66/98 98/98 52/98 48/98 10/98 37/98 6/98 62/98 3/98 12/98 20 IOWA-WAP 2000–2006 69/69 53/69 69/69 18/69 7/65 3/65 31/69 2/69 38/69 3/69 5/69 21 SUG-MIL 1996–2002 49/49 32/49 49/49 5/49 31/49 3/49 27/49 5/49 30/49 11/49 0/49 21 SUG-MIL 2000–2006 45/45 35/45 45/45 4/45 15/45 3/45 32/45 8/45 22/45 8/45 0/45 22 DPLAI 1996–2002 39/39 14/39 35/39 6/39 6/39 0/39 22/39 1/39 37/39 0/39 31/35 22 DPLAI 2000–2006 38/38 15/38 34/38 6/38 2/38 0/38 23/38 1/38 36/38 1/38 33/38 23 ILLI-OTT 1996–2002 76/76 58/76 76/76 61/76 51/76 9/76 68/76 10/76 74/76 16/75 75/76 23 ILLI-OTT 2000–2006 38/38 36/38 38/38 25/38 8/38 2/38 38/38 3/38 36/38 3/38 38/38 24 SANG 1996–2002 82/82 64/82 82/82 45/82 58/82 8/82 32/82 6/82 55/82 10/82 7/82 24 SANG 2000–2006 58/58 50/58 58/58 15/58 1/54 0/54 40/58 3/58 38/58 2/58 6/58 25 ILLI-VC 1996–2002 90/90 76/90 90/90 57/90 65/90 10/90 77/90 15/90 79/90 9/87 76/90

25 ILLI-VC 2000–2006 61/61 58/61 61/61 33/61 8/57 4/57 60/61 6/61 54/61 6/61 41/61

26 MSSP-GR 1996–2002 79/79 70/78 79/79 55/79 34/79 6/79 58/79 8/79 35/79 1/78 35/79

26 MSSP-GR 2000–2006 57/57 53/57 57/57 24/57 7/57 0/57 49/57 2/57 22/57 0/57 15/57

27 MIZZ-OM 1996–2002 103/103 80/103 96/103 42/103 43/103 57/103 22/103 8/103 20/103 4/103 6/103

27 MIZZ-OM 2000–2006 86/86 66/86 75/86 24/86 10/86 38/86 17/86 7/86 14/86 6/86 6/86

28 MAPLE 1996–2002 104/104 69/104 97/104 51/104 67/104 8/104 27/104 17/104 41/104 15/103 7/104

28 MAPLE 2000–2006 121/121 107/121 114/121 56/121 22/85 6/85 32/121 20/121 53/121 30/121 11/121

29 PLATTE 1996–2002 93/94 54/94 89/94 48/94 44/94 10/94 48/94 14/94 61/94 7/94 29/94

29 PLATTE 2000–2006 79/79 56/79 74/79 33/79 14/75 5/75 34/79 6/79 43/79 4/79 25/79

30 MIZZ-HE 1996–2002 99/99 81/99 99/99 68/99 59/99 13/99 56/99 25/99 44/99 4/98 32/99

30 MIZZ-HE 2000–2006 82/82 68/82 82/82 42/82 10/82 3/82 60/82 11/82 41/82 1/82 18/82

31 MSSP-TH 1996–2002 99/99 91/99 99/99 78/99 53/99 8/99 78/99 15/99 53/98 9/98 44/99

31 MSSP-TH 2000–2006 82/82 75/82 82/82 47/82 8/82 0/82 73/82 6/82 42/82 0/82 24/82
Study Design and Methods 11

The second consideration for applying the SEAKEN test 

is the amount of censored data. Although censored data easily 

can be accommodated in the SEAKEN test by assuming data 

below the maxLT-MDL are all equal to the maxLT-MDL, 

Schertz and others (1991) recommend that a maximum of 

50 percent of the data be censored for applying the SEAKEN 

test. However, given that data for many of the site-pesticide 

combinations considered here were highly censored, a more 

lenient requirement was applied to the data for this report. 

Specifically, the SEAKEN test was applied if at least 10 

detections were at or above above the maxLT-MDL, regardless of the percentage of censored values. This requirement 

was selected to conform to the SEAWAVE trend analysis, 

described later in this report, in order to increase the number 

of comparisons that could be made between the two methods.

To define the assumptions of the SEAKEN test, let 

XM={CM(1), CM(2), ...} be the set of all pesticide concentration 

values for a designated pesticide/site combination and a designated month M (Jan, Feb, ... Dec). The null hypothesis of 

the SEAKEN test is that XM constitutes a random sample from 

a fixed distribution – that is, the probability distribution of all 

values within a given month is the same year after year. The 

SEAKEN test is called a nonparametric procedure because 

the form of the distribution (as determined by its parameters) 

does not need to be specified. The test statistic is computed 

by examining all pairwise-differences between values within 

the same month (CM(j) and CM(k) with j<k), subtracting the 

total number of negative differences from the total number of 

positive differences, and combining the resulting values for all 

months,

S

S

PPD NPD M M M * = ∑{ − = ; , ,..., 1 2 12}

where 

* is the SEAKEN test statistic;

is the number of positive pairwise-differences 

f

PPDM

or month M; and 

NPD is the number of negative pairwise-dif M ferences 

for month M.

(1)

If there is no trend in any of the months, then the number of 

positive differences will balance the number of negative differences and the test statistic is close to zero. The null distribution of the test statistic (its probability distribution under the 

assumption that no trend occurs in any of the months) is given 

by Hirsch and Slack (1984), along with provisions for dealing 

with ties, censored values, missing values, and potential serial 

correlation between values from different months. An unusually large positive value of the test statistic (as determined by 

comparing it to the null distribution) indicates an uptrend in 

one or more months, and an unusually large negative value 

indicates a downtrend.

Although the SEAKEN test can determine if a significant 

trend exists, it cannot be used to estimate the magnitude of 

the trend. For site-pesticide combinations with few censored 

values (less than 5 percent, according to Schertz and others [1991]), the slope of the trend can be estimated using the 

techniques of Hirsch and others (1982). A new approach for 

estimating the slope of the trend that can be used with 

censored data was developed for this report (Appendix 1).

Seasonal Kendall (SEAKEN) Test for 

Regional Trends

Consistent trends in pesticide concentrations may be 

present across a region represented by multiple sites. The 

regions evaluated in this study were the major drainages 

described earlier. Regional unadjusted trends in concentration 

were examined using the regional seasonal Kendall test—the 

Regional Kendall test (Helsel and Frans, 2006) modified to 

account for seasonality. The data requirements and assumptions of the test are described briefly in this section, and more 

detail is provided in Sprague and Lorenz (2009).

The regional seasonal Kendall test computes a test for 

an overall trend for all sites within a region by computing a 

score for each season at each site and adding the scores to 

compute the total for the region. To define the assumptions of 

the regional seasonal Kendall test, let XMi={CMi(1), CMi(2), ...}

be the set all pesticide concentration values for the designated 

pesticide at site i and a designated month M (Jan, Feb, ... 

Dec). The null hypothesis of the SEAKEN test is that XMi constitutes a random sample from a fixed distribution—that is, the 

probability distribution of all values within a given month and 

site is the same year after year. The test statistic is computed 

by examining all pairwise-differences between values within 

the same month and site [CMi(j) and CMi(k) with j<k], subtracting the total number of negative differences from the total 

number of positive differences, and combining the resulting 

values for all months and sites,

S PPD NPD M R Mi Mi

* ; , ,...,

,

= (∑∑ { − = 1 2 12 ; }

i=1, 2, total number ... of sites

where 

is the regional seasonal Kendall test st

)

SR

* atistic;

PPD is the number of positive pairwise-difference Mi s 

for month M and site i; and 

NPD is the number of negati Mi ve pairwise-differences 

for month M and site i.

(2)
12 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

If there is no regional trend in any of the months, then the 

number of positive differences should balance the number of 

negative differences and the test statistic should be close to 

zero. The null distribution of the test statistic (its probability 

distribution under the assumption that no trend occurs in any 

of the months) is given by Sprague and Lorenz (2009). An 

unusually large positive value of the test statistic (as determined by comparing it to the null distribution) indicates a 

regional uptrend in one or more months, and an unusually 

large negative value indicates a regional downtrend.

For the purposes of this report, an arbitrary value of 

one-half the maxLT-MDL (or for results with elevated censoring levels, one-half the reported value) was substituted for 

censored data for the Regional seasonal Kendall test. For 

singly-censored data, there is no bias in the computation of 

SR (Hirsch and Slack, 1984). There were very few elevated 

censoring limits in the pesticide data interpreted in this report 

and it was assumed that any bias in the computation of SR was 

very small and could be ignored. The pesticide data with the 

most elevated censoring levels was chlorpyrifos (3.1 percent 

of samples). The data requirements for the regional seasonal 

Kendall test basically are the same as for SEAKEN, except 

that because all censored data are recoded, there are no system 

limits on the number of censored data. However, there is a 

practical limit to the number of tied values caused by recoding censored data that affect the ability to detect a trend. The 

regional seasonal Kendall trend test does not compute an estimate of the magnitude of the trend, but only an indication of 

whether the trend is upward or downward and an attained level 

of significance. A key characteristic of the regional seasonal 

Kendall test is that effects from highly cross-correlated sites 

are down weighted. For example, strong trends at a subset of 

sites, such as small agricultural streams in a limited area, do 

not have a substantial effect on the test results. When closely 

spaced sites repeatedly sample a limited geographic area, the 

sites may not be independent and the regional seasonal Kendall test accounts for that lack of independence by reducing the 

effect of the sites on the overall test statistic.

Seasonal Wave (SEAWAVE) Model

The SEAWAVE model is a parametric regression model 

specifically designed for analyzing seasonal variability and 

trends in pesticide concentrations (Vecchia and others, 2008). 

In its simplest form, the model can be expressed as

Log C(t) = + W(t) + t + (t) β β β ε 0 1 2

where 

Log denotes the base-10 logarithm; 

t is decimal time, in years, with respect to an 

arbitrary time origin;

C(t) is pesticide concentration, in micrograms 

per liter; 

W(t) is a seasonal wave representing intra- annual 

variability in concentration 

(Appendix 2); 

, , and are regression coefficients; and β β β 0 1 2

ε (t) is the model error.

(3)

The seasonal wave is a periodic function of time with a period 

of 1 year, similar to mixtures of sine and cosine functions 

often used to model seasonality in concentration data. However, the seasonal wave differs from a trigonometric function 

in that it is specifically designed to mimic the behavior of 

pesticide concentrations in response to seasonal application 

rates, basin accumulation, and removal from processes such as 

degradation and runoff (Vecchia and others, 2008). The methodology used to estimate the seasonal wave and the regression 

coefficients, given a sample of censored pesticide concentration data, is given in Appendix 2.

Data requirements for the SEAWAVE model are less 

restrictive than those given previously for the SEAKEN 

test. Unlike SEAKEN, there was no need to assume a fixed 

monthly sampling frequency for the SEAWAVE model. The 

model could be applied with as few as six samples per year 

during a period of at least 3 years and as few as a total of ten 

uncensored values. Also, unlike SEAKEN, in which the magnitude of the trend is estimated using a separate method, the 

magnitude of the trend for SEAWAVE (the regression coefficient β2

) is obtained directly from the SEAWAVE model. 

The SEAWAVE model for each site-pesticide combination is fitted by maximizing the likelihood function of the 

log-transformed data, assuming the model errors are independent, normally distributed random variables with a mean of 

zero and a constant variance. Intra-annual changes in the mean 

and variance of the pesticide data are modeled by a combination of the logarithmic transformation, which helps stabilize 

seasonal differences in the variance, and the seasonal wave, 

which models seasonality in the mean of the log-transformed 

concentration data. In contrast, the SEAKEN test does not 

assume a distribution for the pesticide concentration data, and 

seasonality in the mean is handled by comparing values only 

within like seasons. The null distribution of the SEAKEN test 
Study Design and Methods 13

statistic (S*, eq. 1), however, depends on cross-products of 

the pairwise-differences both within and between seasons, and 

needs to be approximated using a relatively complex formula 

that may not be accurate for small sample sizes, especially 

when there is a high percentage of censored data (Hirsch and 

Slack, 1984). The SEAKEN test, which has few assumptions, 

and the SEAWAVE model, which has more assumptions but 

can be applied to more limited data (provided the assumptions 

hold), are compared in a later section to help evaluate their 

applicability for analyzing trends in pesticide concentrations.

Seasonal Wave with Flow Adjustment 

(SEAWAVE–Q) Model

When analyzing trends in concentration data, the effect of 

changing flow conditions on those trends needs to be considered if it is desired to separate changes caused by hydrologic 

trends from changes caused by other factors, such as pesticide 

use. This often is done by regressing concentration (or logtransformed concentration) on concurrent flow (or log-transformed flow), subtracting the fitted concentration values from 

the observed values to obtain residuals (flow-adjusted concentrations), and analyzing trends in flow-adjusted concentrations 

using an established technique such as SEAKEN (Hirsch and 

others, 1982). However, flow-adjusted concentrations cannot 

be computed for censored data without substituting arbitrary 

fixed values for the censored concentrations. Therefore, a different approach was used for this study in which flow-related 

variables were added to the SEAWAVE model. This section 

describes adjustments that were made to the SEAWAVE model 

to account for flow-related variability in pesticide concentrations and to separate flow-related trends from trends due to 

other factors such as changes in pesticide use.

Changing flow conditions can affect pesticide concentrations in subtle ways that may not be removed easily by simply 

regressing concentration on concurrent flow (Vecchia and others, 2008). The seasonal hydrologic cycle, though often a large 

component of the variability in flow, may not be correlated 

in any meaningful way with pesticide concentrations because 

the timing and length of the pesticide application season is 

the dominant factor controlling seasonality of concentrations. 

However, short-term flow anomalies resulting from rainfallrunoff events during or after the application season can have a 

substantial effect on pesticide concentrations. Long-term flow 

anomalies resulting from changes in climate or stream regulation also would be expected to affect pesticide concentrations 

by changing the amount of dilution of pesticide runoff by 

ground water or ambient streamflow.

Three dimensionless flow variables were added to the 

SEAWAVE model to help account for flow-related variability in pesticide concentrations. The variables are computed 

by using log-transformed flow aggregated over various time 

scales, including daily, monthly and yearly time scales. The 

first variable represents short-term (day-to-day) flow variability, and is defined as

STFA(t) = X(t) X (t) M

where

STFA is the short- term flow anomaly (dimensionless);

X(t) Log Q(t) = is log- transformed daily flow; and

is the average of 

log

X (t) = Ave{X(u), t (1/12) < u t} M − ≤

- transformed daily flow for 1 / 12 of a year 

(about 1 month) up to and including time . t

(4)

Reasons for using STFA as a predictor of pesticide concentration are given by Vecchia and others (2008). Large positive 

values of STFA and associated increases in pesticide concentrations tend to occur near the beginning of a substantial 

rainfall-runoff event, whereas negative values of STFA and 

associated decreases in pesticide concentrations tend to occur 

after the event passes. The second flow variable added to the 

SEAWAVE model represents mid-term (month-to-month) flow 

variability and is defined as

MTFA(t) = X (t) X (t)

MTFA

M A

where

 is the mid- term flow anomaly 

(dimensionless); and

X (t) = Ave{X(u), t 1<u t} is the A ≤ average of 

log- transformed daily flow for 1 year up to 

and including time t.

(5)

The third flow variable added to the SEAWAVE model represents long-term (year-to-year) flow variability, and is defined 

as

LTFA(t) = X (t) X A − *

where 

LTFA is the long- term flow anomaly (dimensionless); and

X is the average of log- transformed d * aily flow for 

a specified trend analysis period (either 

1996 2002 or 2000 2006). − −

(6)
14 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

Unlike STFA, which tends to affect pesticide concentrations 

in a relatively consistent manner among different sites and 

pesticides, MTFA and LTFA can affect pesticide concentrations in different ways and to different degrees, depending on 

the type of pesticide, the size of the basin being analyzed, the 

climatic and hydrologic properties of the basin, and the degree 

of streamflow regulation. For example, for a large basin with 

substantial non-agricultural runoff, higher-than-normal annual 

flow conditions (as indicated by a positive value for LTFA) 

may lead to decreased pesticide concentrations because of 

more dilution from non-agricultural runoff. 

Adding the flow anomalies to eq. 3 and changing the 

notation for the regression coefficients and error term yields 

Log C(t) = + W(t) + LTFA(t) + 

 MTFA(t) + STF

0 1 2

3 4

γ γ γ

γ γ A(t) + t + (t). 5 γ η

(7)

The regression model without the flow terms (eq. 3) will be 

referred to as SEAWAVE and the model with the flow terms 

(eq. 7) as SEAWAVE-Q. The estimated value of β2 from SEAWAVE will be referred to as a trend in concentration and the 

estimated value of γ5 from SEAWAVE-Q will be referred to as 

a flow-adjusted trend in concentration.

Trend Analysis Intervals and Model Comparisons

One of the primary objectives of this report is to interpret 

trends in pesticide concentrations in relation to spatially and 

temporally varying flow conditions and pesticide-use patterns. 

When making these interpretations, it is important to have 

comparable sampling intervals among the sites. Most sites 

had either no samples or few samples collected before 1996. 

Therefore, the trend analysis for this report is based on data 

collected from 1996–2006. Initially, trends were evaluated 

for this entire interval. However, examination of the residuals from the SEAWAVE model indicated that trends for most 

pesticide-site combinations were not uniform in magnitude 

during 1996–2006. Rather, most trends tended to either occur 

from the mid 1990s to the early 2000s, or, in some cases, 

during 2000–2006. In still other cases, there appeared to be 

substantial changes in the seasonal concentration patterns from 

the mid- to late 1990s to the early to mid-2000s (presumably 

from changes in seasonal-use patterns), making difficult the 

selection of a single seasonal wave for 1996–2006. 

Because of the potential problems with assessing monotonic trends over the entire 1996–2006 period, trends in this 

report are analyzed for both an early (1996–2002) and late 

(2000–2006) time period, as stated earlier. This approach 

also facilitated comparison of trend-analysis results from the 

SEAKEN and SEAWAVE models, because the 1996–2002 

analysis period resulted in the most complete set of sites that 

could be analyzed using SEAKEN. Trends from SEAKEN and 

SEAWAVE (both for unadjusted concentrations) are comparatively evaluated in a later section for both time periods. 

Subsequently, trends from SEAWAVE and SEAWAVE-Q 

are compared and contrasted for both time intervals to help 

separate flow-related trends from trends due to other causes. 

Finally, flow-adjusted trends from SEAWAVE-Q are evaluated 

in relation to changing use patterns or other potential causes of 

the trends. In these evaluations of flow-adjusted trends, rough 

estimates of average annual pesticide fluxes for the 1996–2002 

and 2000–2006 periods are used to help interpret the fitted 

trends. The flux estimates were obtained using the fitted daily 

concentrations from the SEAWAVE-Q model along with 

observed daily flows. The fitted daily log-transformed concentrations were untransformed, multiplied by a bias correction 

factor based on a normal distribution for the model errors 

(Appendix 2), multiplied by the daily flows (with the appropriate conversion factor), and aggregated to obtain annual flux 

estimates. The flux estimates are approximations intended 

primarily for relative comparisons, and should not be relied 

upon as final quantitative estimates of actual fluxes.

Use and Properties of Pesticides

Trends in the use of a pesticide (fig. 2) and its physical 

and chemical properties (table 4) are important influences on 

changes in stream concentrations over time and how they may 

change as water passes through stream drainage systems. In 

particular, pesticide use generally is the single most important 

influence on pesticide concentrations in streams (Gilliom and 

others, 2006). 

Annual estimates of agricultural use of each pesticide 

during 1996–2006 were developed for all counties in the 

conterminous U.S. using proprietary data (DMRKynetec, Inc.) 

on the mass of pesticides applied to agricultural crops each 

year and data on county-harvested crop acreage. Pesticide use 

estimates, which were based on surveys of major row crops 

and specialty crops, were reported for multi-county areas referred to as “Crop Reporting Districts” (CRDs). The estimates 

were combined with annual harvested acres available from 

the 1992, 1997, 2002, and 2007 Census of Agriculture and 

NASS annual crop acreage to calculate pesticide application 

rates for individual crops. The CRD-level use estimates were 

disaggregated to county-level application rates by dividing the 

mass of pesticides applied to a crop by the acres of that crop in 

the CRD to yield a rate per harvested acre. Pesticide estimates 

were not available for all of the 304 CRDs in the conterminous U.S., nor for every crop or year; in such cases a crop 

application rate was estimated from median surveyed rates for 

surrounding CRDs. Pesticide-crop application rates were then 

applied to crop acreages for each county. Annual pesticide-use 

intensities for individual watersheds were calculated on the 

basis of county-level pesticide use estimates and information 

on the proportion of agricultural land use in each of the watersheds. Using a geographic information system, mapped land 

cover was combined with the digital maps of drainage basins 

and county boundaries to compute the basin’s areal weights of 

agricultural land in each intersecting county. 
Study Design and Methods 15

IP003821_Figure 02A

A

Atrazine

Acetochlor

Metolachlor

Alachlor

Cyanazine

1992 1994 1996 1998

YEAR

2000 2002 2004 2006

TOTAL USE, IN MILLIONS OF KILOGRAMS

0

10

20

0

4

8

10

0

5

15

0

5

10

15

5

15

25

12

20

0

4

8

12 1996-2002 analysis period 2000-2006 analysis period

Figure 2. Trends in total annual pesticide use in major river basins of the Corn Belt, 1992–2006. A. Atrazine, acetochlor, metolachlor, 

alachlor, and cyanazine. B. EPTC, simazine, metribuzin, chlorpyrifos, and diazinon.
16 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

IP003821_Figure 02B

B

EPTC

Simazine

Metribuzin

Chlorpyrifos

Diazinon

1992 1994 1996 1998

YEAR

2000 2002 2004 2006

TOTAL USE, IN MILLIONS OF KILOGRAMS

0

2

0

0.4

0.8

0.4

0

0.2

0.6

0

1

2

3

4

6

1.2

0.8

0

0.3

0.2

0.1

1996-2002 analysis period 2000-2006 analysis period

Figure 2. Continued.
Trends in Pesticide Concentrations 17

The basin’s areal weights, or “weighting factors” of agricultural land, were computed such that a county entirely within 

the basin had a weighting factor of 1.0; a county entirely 

consisting of agricultural land and intersected half-way into 

the basin had a value of 0.5; and so forth. The estimated pesticide use for a basin was computed by multiplying the basin’s 

county weighting factors by the total county pesticide use and 

summing the results. The source for mapped agricultural land 

for 1996 and 1997 pesticide estimates was U.S. Geological 

Survey’s National Land Cover Dataset 1992 (Vogelmann and 

others, 2001), as enhanced by Nakagaki and others (2007); 

for 1998 through 2006 pesticide estimates, the source was 

U.S. Geological Survey’s National Land Cover Database 2001 

(Homer and others, 2004).

Use Trends

Regional trends in annual use for agricultural purposes 

during 1992–2006 are shown in figure 2 for the pesticides 

assessed in this study (prometon is registered only for noncrop 

uses and is not included). Corn Belt agricultural use during 

1996–2006 generally decreased for metolachlor, alachlor, 

cyanazine, metribuzin, EPTC, chlorpyrifos, and diazinon, 

increased somewhat for simazine, and stayed relatively constant for atrazine and acetochlor. The use within individual 

drainage basins may not follow these regional trends, however, 

and estimates of use for some of the study sites are different 

in direction or degree. It also is important to note that, while 

the use data in this report are believed to be the best estimates 

available, they are based on user surveys and, as such, are 

subject to error.

Most of the agricultural pesticides assessed in this study 

primarily were used on corn during the study period, with 

the exceptions of metribuzin and alachlor, which were used 

on both corn and soybeans. Nonagricultural uses were most 

important for the herbicides simazine (used for both agricultural and industrial weed control in roughly equivalent total 

amounts, although it generally is applied at a higher rate for 

nonagricultural uses [EXTOXNET, accessed June 16, 2008]) 

and prometon (right-of-ways and construction sites), and for 

the insecticides diazinon and chlorpyrifos. 

Physical and Chemical Properties

The occurrence and transport of pesticides in the environment are influenced strongly by the chemical and physical properties that affect their persistence and partitioning 

(Gilliom and others, 2006). Of the 11 pesticides assessed in 

this study, five are triazine herbicides (atrazine, cyanazine, 

metribuzin, prometon, and simazine), three are chloroacetanilide herbicides (acetochlor, alachlor, and metolachlor), two are 

organophosphorus insecticides (chlorpyrifos and diazinon), 

and one is a thiocarbamate herbicide (EPTC).

Pesticides with high persistence remain in their original 

chemical form in the environment for long periods, whereas 

those with low persistence more rapidly transform following their application. The tendency of a pesticide to partition 

into water, sediment, or other media determines where it most 

likely is to be detected in the environment, and how it is transported through the hydrologic system. Pesticides with relatively low soil adsorption coefficients (Koc) and high water 

solubility are more mobile than those with high soil adsorption 

and low solubility.

With the exception of chlorpyrifos, the pesticides in this 

report have moderate to high water solubility and relatively 

low soil-adsorption coefficients (table 4), resulting in relatively similar and high mobility in water and moderate-tostrong potential for transport from fields by surface runoff, 

primarily in the dissolved phase. Chlorpyrifos has the highest 

soil adsorption coefficient and the lowest water solubility and, 

thus, is the least mobile when dissolved in water and has the 

greatest tendency to adsorb to soil. None of the 11 pesticides 

is highly volatile. Seven of the pesticides have half-lives in 

the range of 1–6 weeks, three are in the range of 3–6 months, 

and prometon has a half-life of more than 2 years. Overall, 

the relatively high mobilities (except for chlorpyrifos) and 

half-lives of less than a year (except for prometon) indicate 

that stream concentrations of most of the pesticides assessed 

should respond to year-to-year changes in use and not be much 

affected by use in past years. Some of the pesticides with the 

shortest half-lives, such as EPTC, may not show consistent 

trends among upstream to downstream locations if sites are far 

apart.

Trends in Pesticide Concentrations 

Results of trend analysis are presented and evaluated in 

three main parts:

1. The first analysis focuses on a regional overview that 

comparatively evaluates results from SEAKEN (both 

site and regional applications) and SEAWAVE for 

both 1996–2002 and, to the extent possible, 

2000–2006 (data constraints limited SEAKEN 

applications during this period).

2. The second analysis compares and evaluates results 

from SEAWAVE and SEAWAVE-Q for all sitepesticide combinations, for both 1996–2002 and 

2000–2006, in order to assess the overall influence 

and potential importance of flow adjustment.

3. The third analysis is comprised of more detailed 

assessments of individual pesticides (using SEAWAVE-Q), with an emphasis on interpreting 

the inter-relations among sites in a hydrologic 

framework and more detailed interpretation of 

concentration trends in relation to changes in use.
18 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

Comparison of SEAKEN and SEAWAVE 

Comparison of SEAKEN (both site and regional applications) with SEAWAVE results serves to evaluate the similarity 

of results for nonparametric and parametric methods, computed with no adjustments for flow. Most of these comparisons 

focus on the 1996–2002 analysis period because of more 

complete data during those years.

Overview of Trend Results for 1996–2002

There is broad, general agreement between trends identified by the SEAKEN and SEAWAVE methods during 1996–

2002 (table 5). Less than 10 percent of the paired comparisons 

(15 of 175 site-pesticide combinations) between the methods 

indicated a difference in the direction of the trend, and only 

one of the 15 site-pesticide combinations with differences had 

trends significant at the 10-percent level (p < 0.10). For some 

pesticide/site combinations with many censored values, the 

SEAKEN method was unable to produce a reliable estimate 

of the trend (Appendix 1), but the direction of the trend could 

be determined from Kendall’s tau. These cases are indicated 

by “‘– –” for a downtrend and “++” for an uptrend. The broad, 

general agreement between trends indicates that the methods 

produce similar results when adequate data are available for 

both, and that they reinforce each other for interpretation of 

results.

Most of the trends identified during 1996–2002 were 

downtrends, including all of the trends that could be quantified for alachlor, cyanazine, metribuzin, and chlorpyrifos. All 

trends for metolachlor and EPTC were downward except at 

MILW, CLINT, SUG-MIL, and DPLAI (metolachlor) and 

DUCK (EPTC). Most trends for atrazine were downward, and 

only LCOBB had a significant uptrend at the 10-percent significance level. Trends for acetochlor, simazine, prometon, and 

diazinon were mixed. Many sites had downtrends identified 

Pesticide name log Koc

(Koc in mL/g)

Sw

(mg/L)

log KH

(KH in Pa•m3

/mol)

Half-life for 

transformation 

in aerobic soil 

(days)

Atrazine 2 30 –3.54 146

Acetochlor 1

2.38 2223 3–5.26 411

Metolachlor 2.26 430 –2.63 26

Alachlor 2.23 240 –2.7 5

20.4

Cyanazine 2.3 171 –6.52 6

17

EPTC 2.3 370 0.00988 7

7

Simazine 2.11 5 –3.46 6

91

Metribuzin 8

1.72 8,91,000 8,10–5.31 172

Prometon 2.54 750 –4.05 932

Chlorpyrifos 3.78 0.73 0.0374 30.5

Diazinon 2.76 60 –1.39 39

1

Median among five values reported by U.S. Environmental Protection Agency (1994). 

2

Source: Shiu and others (1990).

3

KH value computed by dividing vapor pressure reported by Ma and others (2004a) by Sw value reported by Shiu and others (1990).

4

Computed for 25°C by interpolation using data reported by Ma and others (2004b).

5

Half-life interpolated to 25°C from rates of alachlor disappearance from a sandy loam soil (0.7 percent organic carbon) at 10, 20 and 30°C reported by Zimdahl and Clark (1982).

6

Sole value reported by the U.S. Department of Agriculture (2005) database authors, but not “selected.”

7

“[H]alf-life in moist loam soil at 21 to 27°C is approximately 1 week” (Mackay and others, 1997). 

8

Source: U.S. Department of Agriculture (2005). 

9

Measured at 20°C. 

10Adjusted from value measured at 20°C to 25°C using equation 13 from Mackay and others (2000), and an enthalpy of vaporization (ΔHv

) of 46.8 kJ/mol, 

based on KH data from 197 compounds (Staudinger and Roberts, 2001). 

Table 4. Properties affecting the transport and fate of selected pesticides.

[All values measured at (or estimated for) 25°C. Unless noted otherwise, (1) values for soil organic carbon-water partition coefficient (Koc), water solubility (Sw) 

and Henry’s law constant (KH) are from Mackay and others (1997); (2) transformation half-lives in soil and water were measured in the laboratory (rather than in 

the field) at neutral pH in the dark, and obtained from the U.S. Department of Agriculture (2005); and (3) all are recommended values selected by the compilation authors when more than one value was available from the literature. Numbers of significant figures are identical to those given in original sources. mL/g, 

milliliter per gram; mg/L, milligram per liter; Pa•m3/mol, pascal-cubic meter per mole]
Trends in Pesticide Concentrations 

19

Table 5. Comparison of SEAKEN and SEAWAVE trend results for 1996–2002.[SW, SEAWAVE; SK, SEAKEN; - -, downtrend result for SEAKEN, trend magnitude not available; ++, uptrend result for SEAKEN, trend magnitude not available; trend results in bold font are significant at p < 0.1; cells highlighted in yellow indicate trend results in opposite directions; empty cells indicate insufficient data to apply the model]

Site map 

number and 

short name

Pesticide

Atrazine Acetochlor Metolachlor Alachlor Cyanazine EPTC Simazine Metribuzin Prometon Chlorpyrifos Diazinon

Trend model

SW SK SW SK SW SK SW SK SW SK SW SK SW SK SW SK SW SK SW SK SW SK

Trend result (percent per year)

 1. MAD 20.1 45.1 –7.9 55.3

 2. OHIO–CA –1.9 –0.7 2.4 2.4 –12.8 –7.8 –37.5 – – –49.5 –44.4 4.1 2.6 –19.3 –15.5 1.5 3.1 –31.2 8.9 16.7

 3. LBUCK –20.6 –11.0 –10.5 – – –20.6 –17.6 –25.4 –13.4 –12.5 –12.2 –15.0 –38.0 –15.0 5.7 1.5

 4. SUG–NP –11.1 –10.5 –13.6 –3.1 –20.2 –13.9 –35.8 – – –58.1 – – –0.8 14.3 –36.7 – – –4.1 11.9 –7.2 –13.3

 5. WHITE –15.7 –12.8 –11.2 –10.0 –22.2 –21.0 –36.1 –25.0 –57.3 –49.0 –7.3 4.4 12.5 –16.7 –8.6 –2.8 –5.9 –64.7 5.4 16.7

 6. WABASH –13.6 –13.6 –21.1 –38.6 –63.2 23.6 –23.4 –1.3 –11.8 13.5

 7. OHIO–GRCH –7.1 –7.5 –4.9 –6.2 –17.6 –15.6 –28.6 –25.0 –53.4 –41.3 15.3 11.9 –18.4 –14.3 –2.2 –2.8 –23.3 –16.7 0.4 – –

 8. DUCK 3.3 9.4 –6.4 –19.4 –26.2 2.6 –25.8 –1.5

 9. MILW 1.8 13.1 5.0 –29.9 6.8 –10.4 33.1

10. CLINT 0.0 0.4 –3.7 –10.2 –12.5 1.3 –8.3 –3.6

11. STJOS –13.2 –22.9 –6.3 –5.0 –29.2 –20.3 –48.8 –36.7 –44.5 –47.1 7.1 5.6 –30.3 –21.4 –17.4 –14.3

12. AUGL –6.5 –5.5 2.8 –1.5 –22.7 –20.8 –40.4 –60.0 –33.5 –61.7 4.7 – – –41.1 –33.3 8.1 3.0 –27.9 –19.9 –13.913. MAUM –5.2 –4.7 4.6 3.7 –18.2 –14.8 –32.3 –27.9 –44.4 –39.8 17.3 11.6 –18.8 –12.8 2.0 –0.7 –38.8 –18.3 –4.7 8.3

14. LCOBB 24.7 2.5 7.6 – – –14.7 –3.4 –48.5 –31.7 –14.7 –12.5 –5.9 –14.3

15. MSSP–HA 4.3 – – 19.9 12.5 –14.5 –9.2 –32.5 – – –29.6 –22.2 –7.3 – – –8.5 –16.7 –6.0 –4.8 7.4 13.9

16. MSSP–CL 0.3 –0.1 14.8 16.7 –11.5 –5.6 –27.0 –33.3 –39.5 –22.2 –16.4 0.5 2.8 –4.7 –7.1

17. WAPS–TR –7.5 –4.1 9.6 2.6 –16.2 –10.5 –13.4 –11.4 –14.8 20.0 – –

18. IOWA–ROW –11.0 –6.4 –12.6 –5.6 –24.9 –22.0 –40.9 –35.4 –51.0 –14.0 –12.519. SFIOWA –27.3 –13.4 –44.2 –23.1 –32.0 –23.8 –55.4 –31.7 –24.3 –8.3 –12.7 ––21.4

20. IOWA–WAP –1.4 –3.8 –9.7 –4.5 –16.8 –14.3 –26.1 –25.0 –41.1 –32.2 –13.9 –3.8 – – –2.6 –3.1 14.0

21. SUG–MIL 14.5 54.1 11.3 –46.3 93.8 –6.6 –10.4

22. DPLAI 3.1 –5.3 5.5 7.4 –13.0 –12.6

23. ILLI–OTT 3.3 –0.2 24.9 ++ –13.8 –15.8 –19.1 –16.7 –52.0 –59.1 7.3 5.7 –25.7 –5.7 –11.1 –43.4 –5.0 –9.2

24. SANG –18.8 –9.2 –15.9 –10.4 –14.4 –7.8 –27.6 –25.0 –60.8 –37.8 13.6 ++ –7.7 –12.5 –71.2

25. ILLI–VC 1.3 2.3 8.8 3.0 –14.3 –16.6 –29.2 –16.7 –57.9 –77.8 –24.9 18.2 13.7 –24.5 –14.3 –7.2 –8.9 –4.2 –7.7

26. MSSP–GR –1.9 –6.7 –15.7 –33.4 –57.9 38.7 –12.5 –3.6

27. MIZZ–OM –3.5 – – 0.9 ++ –16.7 –7.9 –24.5 –14.6 –38.6 –13.9 –12.0 –10.0 –7.2 –13.3 –1.7 –4.8

28. MAPLE 3.8 22.1 –17.6 –25.1 –53.3 –5.6 –19.2 3.9 –12.9

29. PLATTE –15.2 –9.1 –0.1 ++ –22.9 –10.9 –36.4 –10.0 –58.0 –44.4 –18.7 –8.3 –5.6 –39.2 –10.0 –12.5 –3.8 – –

30. MIZZ–HE –6.2 –5.3 –3.8 – – –17.1 –17.0 –15.0 –8.3 –47.7 –44.4 –15.7 24.1 16.7 –4.7 –14.3 –2.1 –7.1 4.5 ++

31. MSSP–TH –3.4 –7.6 –5.8 –1.1 –16.0 –22.7 –17.1 –11.1 –47.3 –51.9 23.4 14.0 –6.5 –6.4 –7.1 –3.9 13.9
20 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

from both methods for all of the agricultural herbicides 

(atrazine, acetochlor, metolachlor, alachlor, cyanazine, EPTC, 

and metribuzin). No site had only uptrends, but MILW had 

downtrends only in cyanazine.

A regional seasonal Kendall analysis of trends was done 

for the four major river basins shown in figure 1 (table 6). A 

consistent set of sites were used in the analysis for each basin: 

the Ohio River Basin included OHIO-CA, LBUCK, SUG-NP, 

WHITE, and the OHIO-GRCH sites; the Great Lakes River 

Basins included CLINT, STJOS, AUGL, and the MAUM 

sites; the Upper Mississippi, Illinois, and Iowa River Basins 

included the LCOBB, MSSP-HA, MSSP-CL, WAPS-TR, 

IOWA-ROW, SFIOWA, ILLI-OTT, and the ILLI-VC sites; 

the Missouri River Basin included the MIZZ-OM, PLATTE, 

and the MIZZ-HE sites. A regional seasonal Kendall analysis also was done for the entire Corn Belt using all of the 

previously mentioned sites plus MSSP-TH. Downtrends in 

atrazine, metolachlor, alachlor, cyanazine, EPTC, metribuzin, 

prometon, and chlorpyrifos concentrations were indicated 

for streams in all basins as well as the Corn Belt as a whole 

and, except for EPTC, all of these constituents have at least 

one basin that had significant downtrends at the 10-percent 

significance level. The downtrends in metolachlor, alachlor, 

and cyanazine concentrations were significant at the 10-percent confidence level for all basins and for the Corn Belt as a 

whole. 

Regional trends for acetochlor, simazine, and diazinon were mixed—some basins had downtrends and some 

had uptrends. The most widespread regional uptrends were 

observed for simazine, although none of the regional trends 

for acetochlor, simazine, and diazinon were significant at the 

10-percent significance level (table 6). 

Overview of Trend Results for 2000–2006

There also is good agreement between trends identified by the SEAKEN and SEAWAVE methods for the four 

sites that could be analyzed by the SEAKEN method for 

the period from 2000 to 2006 (table 7). Only 3 of 27 of the 

paired comparisons between the methods indicated a difference in the direction of the trend, and in no case were either 

of the trends significant at the 10-percent level. The good 

agreement between trends confirms the similar results for the 

period 1996–2002, but there are not enough analyses by the 

SEAKEN method for a regional analysis. Results for SEAWAVE for 2000–2006 will be discussed in more detail in the 

following sections.

Influence of Flow Adjustment: Comparison of 

SEAWAVE and SEAWAVE-Q

Results presented in the previous section show that 

numerous statistically significant trends in pesticide concentrations occurred during both the 1996–2002 and 2000–2006 

analysis periods, and that the trends generally were in agreement using either SEAKEN or SEAWAVE. Neither of these 

methods incorporates the influence of streamflow conditions 

on trends, however, and it is important to determine if some 

of the trends (or lack of trends) may be influenced by variable 

or trending streamflow conditions. Either sampling biases 

in relation to short-term streamflow conditions, or sustained 

trends in streamflow conditions, can contribute to, or obscure, 

trends in a concentration time series. A primary goal of this 

study is to evaluate trends due to changes in such factors as 

use and management practices, which requires adjustment for 

streamflow influences. For this purpose, SEAWAVE-Q, which 

accounts for influences of flow conditions, was the primary 

method used in this study for detailed interpretation.

Before focusing on the analysis of flow-adjusted trend 

results from SEAWAVE-Q, in relation to changes in use and 

other management factors, the overall effect of flow-related 

variability and trends on pesticide concentration trends is evaluated by comparing the trends using SEAWAVE, which does 

not include flow-related variables, and SEAWAVE-Q, which 

includes flow-related variables. Detailed trend results for both 

SEAWAVE and SEAWAVE-Q are given in tables 8 and 9. This 

section gives a general overview of comparative results for 

SEAWAVE and SEAWAVE-Q, and several specific examples 

to illustrate the types of situations that arise. The purpose of 

these comparisons is not to systematically distinguish flow 

contributions to trends from use-or-management contributions 

to trends, which would require detailed site-specific analysis, 

but to provide a perspective on the degree of potential influence on results and interpretation if the influences of flow 

conditions (short, medium, and long term) are not included in 

the model.

Overview of Trend Results for 1996–2002

The trends in pesticide concentrations for the 1996–2002 

analysis period are shown in table 8. Of the 341 possible sitepesticide combinations, 251 had adequate data for application 

of both SEAWAVE and SEAWAVE-Q. Of the 251 pairs of 

results, almost half (122 pairs) had significant trends by both 

methods, and the direction of the trends were in agreement 

between the methods in every one of those 122 cases. Of the 

remaining 129 pairs, 52 were different in terms of statistical significance, with about equal numbers of cases in which 

significant unadjusted trends changed to nonsignificant flowadjusted trends (27 cases) or nonsignificant unadjusted trends 

changed to significant flow-adjusted trends (25 cases). There 

only were 26 pairs of results, or about 10 percent of cases, for 

which the direction of the unadjusted and flow-adjusted trends 

differed, and in 21 of those 26 pairs neither of the trends was 

significant.
Trends in Pesticide Concentrations 

21

Table 6. Regional seasonal Kendall trend results for 1996–2002.[down, a downtrend; up, an uptrend; trend results in bold font are significant at p < 0.1]

Region 

(see figure 1)

Number 

of sites

Pesticide

Atrazine Aceto- chlor Metola- chlor Alachlor Cyanazine EPTC Simazine Metribuzin Prometon Chlorpy- rifos Diazinon

Ohio River Basin 5 down down down down down down down down down down up

Great Lakes River 

Basins

4 down down down down down down up down down down down

Upper Mississippi, 

Illinois, and Iowa River Basins

8 down up down down down down up down down down down

Missouri River Basin 3 down up down down down down up down down down down

Corn Belt (all sites) 21 down down down down down down up down down down down
22

Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

Table 7. Comparison of SEAKEN and SEAWAVE trend results for 2000–2006.[SW, SEAWAVE; SK, SEAKEN; - -, downtrend result for SEAKEN, trend magnitude not available; trend results in bold font are significant at p < 0.1; cells highlighted in yellow indicate trend results in opposite directions; empty cells indicate insufficient data to apply the model]

Site map number 

and short name

Pesticide

Atrazine Acetochlor Metolachlor Alachlor Cyanazine EPTC Simazine Metribuzin Prometon Chlorpyrifos Diazinon

Trend model

SW SK SW SK SW SK SW SK SW SK SW SK SW SK SW SK SW SK SW SK SW SK

Trend result (percent per year)

 1. MAD 16.7 27.9 5.3 54.8

 2. OHIO–CA 1.3 14.9 –3.4 –3.5 6.1 –6.7 –25.8 3. LBUCK –8.5 –5.2 –3.8 13.3 13.9 –29.8 4. SUG–NP –3.7 6.5 16.6 –22.5 29.2 2.4 10.1 –49.9 5. WHITE 2.9 7.8 –1.7 –5.4 –69.5 23.3 7.9 0.6 –17.7 6. WABASH –1.0 2.4 –4.4 –19.8 –52.8 12.1 –22.5 –5.6 –27.2 –26.4 7. OHIO–GRCH 0.6 5.4 –2.2 –23.8 5.0 –3.6 –18.3 8. DUCK 0.3 10.9 19.9 2.0 –9.3 11.4 –13.8 –16.2 9. MILW 1.1 15.3 17.7 –2.1 –11.8 –12.410. CLINT –14.8 –23.5 4.2 –3.4 14.3 –42.511. STJOS 11.1 13.6 46.9 22.6 22.1 58.4 20.912. AUGL –7.7 2.7 –13.0 –31.3 –29.3 –14.5 9.0 –11.413. MAUM –10.4 –3.4 –4.2 – – –3.8 –2.2 –20.0 –20.8 –34.9 –22.2 1.4 – – –7.1 –1.3 –3.3 – – 1.5 –27.3 –18.314. LCOBB –19.6 3.0 –11.215. MSSP–HA 12.0 –1.9 1.8 7.2 1.616. MSSP–CL –2.2 –5.5 1.0 –39.2 2.217. WAPS–TR –5.7 –18.3 –10.5 –13.1 –2.718. IOWA–ROW –4.5 20.9 –17.8 24.419. SFIOWA –2.8 –1.8 12.8 5.6 –1.4 0.0 8.6 16.7 –10.3 –9.520. IOWA–WAP –8.4 –3.1 18.2 9.0 –6.1 –1.5 –21.0 –8.3 10.6 12.5 –2.0 –7.121. SUG–MIL 3.3 22.1 7.4 –65.0 5.9 –35.022. DPLAI –1.8 14.0 16.7 –5.5 2.3 –29.523. ILLI–OTT –6.3 9.9 –14.2 –5.9 14.3 –8.1 –26.824. SANG –5.7 –11.4 –15.0 –7.0 0.0 6.825. ILLI–VC –7.3 –4.0 0.1 1.9 –12.7 –11.0 –2.5 – – 4.5 0.0 2.3 –1.2 –33.1 –28.626. MSSP–GR –3.3 4.5 –8.2 –6.6 9.6 5.4 –45.927. MIZZ–OM 15.7 –6.2 13.2 –3.8 –37.7 –32.0 13.6 –3.928. MAPLE 22.1 50.0 9.1 31.8 –25.9 20.6 28.2 –1.9 50.8 –9.329. PLATTE 12.6 28.4 9.8 9.6 –28.8 0.8 1.1 –11.630. MIZZ–HE 3.6 11.0 –2.4 –5.7 –53.6 23.0 –12.6 3.9 –39.431. MSSP–TH –1.1 10.9 –3.6 –8.7 13.3 5.3 –44.0
Trends in Pesticide Concentrations 

23

Table 8. Comparison of SEAWAVE and SEAWAVE–Q trend results for 1996–2002.[SW, SEAWAVE; SW–Q, SEAWAVE–Q; trend results in bold font are significant at p < 0.1; cells highlighted in yellow indicate trend results in opposite directions; empty cells indicate insufficient data to apply the model]

Site map number 

and short name

Pesticide

Atrazine Acetochlor Metolachlor Alachlor Cyanazine EPTC Simazine Metribuzin Prometon Chlorpyrifos Diazinon

Trend model

SW SW–Q SW SW–Q SW SW–Q SW SW–Q SW SW–Q SW SW–Q SW SW–Q SW SW–Q SW SW–Q SW SW–Q SW SW–Q

Trend result (percent per year)

 1. MAD 20.1 3.6 45.1 –5.6 –7.9 –0.5 55.3 5.2

 2. OHIO–CA –1.9 2.4 2.4 10.5 –12.8 –6.2 –37.5 –37.7 –49.5 –49.7 4.1 8.5 –19.3 –19.5 1.5 –1.6 –31.2 –30.9 8.9 6.4

 3. LBUCK –20.6 –21.0 –10.5 –14.2 –20.6 –22.2 –25.4 –31.8 –13.4 –13.9 –12.2 –12.1 –38.0 –38.2 5.7 5.7

 4. SUG–NP –11.1 –8.4 –13.6 –10.0 –20.2 –17.4 –35.8 –30.7 –58.1 –56.6 –0.8 –0.8 –36.7 –29.4 –4.1 –0.7 –7.2 2.6

 5. WHITE –15.7 –14.8 –11.2 –7.3 –22.2 –19.6 –36.1 –33.1 –57.3 –56.1 –7.3 –2.2 4.4 8.0 –16.7 –10.6 –2.8 –4.0 –64.7 –57.3 5.4 6.4

 6. WABASH –13.6 –11.5 –13.6 –7.6 –21.1 –16.9 –38.6 –35.7 –63.2 –63.1 23.6 27.1 –23.4 –18.4 –1.3 –2.6 –11.8 –10.6 13.5 14.7

 7. OHIO–GRCH –7.1 –4.2 –4.9 –0.9 –17.6 –7.9 –28.6 –28.3 –53.4 –53.0 15.3 12.4 –18.4 –18.3 –2.2 –3.9 –23.3 –22.9 0.4 –0.3

 8. DUCK 3.3 1.9 9.4 6.7 –6.4 –4.2 –19.4 –28.7 –26.2 –24.6 2.6 1.1 –25.8 –27.0 –1.5 –4.5

 9. MILW 1.8 0.9 13.1 13.0 5.0 5.6 –29.9 –27.3 6.8 4.3 –10.4 –8.6 33.1 28.2

10. CLINT 0.4 1.3 –10.2 0.1 1.3 –0.4

11. STJOS –13.2 –8.6 –6.3 1.5 –29.2 –25.4 –48.8 –44.1 –44.5 –42.1 7.1 6.7 –30.3 –22.8 –17.4 –13.8

12. AUGL –6.5 0.6 2.8 4.0 –22.7 –8.8 –40.4 –37.0 –33.5 –32.0 4.7 3.4 –41.1 –35.4 8.1 –3.5 –27.9 –24.2 –19.9 –14.0

13. MAUM –5.2 –6.9 4.6 6.7 –18.2 –14.4 –32.3 –30.6 –44.4 –44.3 17.3 12.5 –18.8 –17.5 2.0 –4.4 –38.8 –32.9 –4.7 –3.0

14. LCOBB 24.7 1.7 7.6 –3.3 –14.7 –1.0 –48.5 –73.1 –14.7 –34.7 –5.9 –3.6

15. MSSP–HA 4.3 4.6 19.9 12.9 –14.5 –5.7 –32.5 –38.8 –29.6 –32.7 –7.3 0.3 –8.5 –4.8 –6.0 –2.0 7.4 –2.5

16. MSSP–CL 0.3 –1.4 14.8 –0.8 –11.5 –10.3 –27.0 –27.4 –39.5 –38.0 –16.4 –19.2 0.5 1.4 –4.7 –1.8

17. WAPS–TR –7.5 –0.1 9.6 –0.3 –16.2 –0.2 –13.4 –17.6

18. IOWA–ROW –11.0 –6.3 –12.6 –7.5 –24.9 –19.5 –40.9 –43.4 –51.0 –66.1 –14.0 –13.8

19. SFIOWA –27.3 –23.0 –44.2 –31.1 –32.0 –27.4 –55.4 –54.1 –24.3 –17.2 –12.7 –16.2

20. IOWA–WAP –1.4 –0.5 –9.7 –8.4 –16.8 –15.2 –26.1 –25.1 –41.1 –42.5 –13.9 –13.5 –3.8 –6.3 –2.6 –4.3 14.0 14.9

21. SUG–MIL 14.5 2.9 54.1 14.2 11.3 10.7 –46.3 –47.5 93.8 47.8 –6.6 7.6 –10.4 –11.7

22. DPLAI 3.1 7.8 –5.3 4.4 5.5 13.8 7.4 12.8 –13.0 –14.0 –12.6 –10.4

23. ILLI–OTT 3.3 3.3 24.9 29.4 –13.8 –9.4 –19.1 –18.2 –52.0 –52.1 7.3 7.6 –25.7 –9.5 –5.7 –6.3 –43.4 –45.8 –5.0 –7.5

24. SANG –18.8 –17.5 –15.9 –12.1 –14.4 –11.3 –27.6 –25.2 –60.8 –57.7 13.6 15.4 –7.7 –7.4 –71.2 –88.5

25. ILLI–VC 1.3 1.5 8.8 14.7 –14.3 –10.0 –29.2 –27.4 –57.9 –56.8 –24.9 –28.3 18.2 19.1 –24.5 –23.0 –7.2 –8.9 –4.2 –7.0

26. MSSP–GR –1.9 –0.3 –6.7 –3.9 –15.7 –14.6 –33.4 –33.3 –57.9 –62.8 38.7 36.9 –12.5 –13.0 –3.6 –5.7

27. MIZZ–OM –3.5 –0.9 0.9 –0.9 –16.7 –3.6 –24.5 –17.9 –38.6 –38.5 –12.0 –12.9 –7.2 1.0 –1.7 3.7

28. MAPLE 3.8 4.7 22.1 8.9 –17.6 –10.0 –25.1 –16.8 –53.3 –50.9 –5.6 0.6 –19.2 –8.2 3.9 –4.5 –12.9 –6.4

29. PLATTE –15.2 –8.9 –0.1 –4.1 –22.9 –6.8 –36.4 –24.3 –58.0 –52.9 –18.7 –23.9 –8.3 –10.7 –39.2 –25.1 –10.0 –2.3 –3.8 –3.6

30. MIZZ–HE –6.2 –1.3 –3.8 –0.7 –17.1 –5.0 –15.0 –15.7 –47.7 –50.5 –15.7 –18.3 24.1 9.4 –4.7 –10.5 –2.1 –1.1 4.5 –3.1

31. MSSP–TH –3.4 –2.2 –5.8 1.3 –16.0 –9.5 –17.1 –17.4 –47.3 –50.0 23.4 13.4 –6.5 –14.4 –6.4 –6.2 –3.9 –6.1
24 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006 Table 9. Comparison of SEAWAVE and SEAWAVE-Q trend results for 2000–2006. [SW, SEAWAVE; SW-Q, SEAWAVE-Q; trend results in bold font are significant at p < 0.1; cells highlighted in yellow indicate trend results in opposite directions; empty cells indicate insufficient data to apply the model] Site map number and short name Pesticide Atrazine Acetochlor Metolachlor Alachlor Cyanazine EPTC Simazine Metribuzin Prometon Chlorpyrifos Diazinon Trend model SW SW-Q SW SW-Q SW SW-Q SW SW-Q SW SW-Q SW SW-Q SW SW-Q SW SW-Q SW SW-Q SW SW-Q SW SW-Q Trend result (percent per year) 1. MAD 16.7 1.2 27.9 –7.5 5.3 0.3 54.8 2.2 2. OHIO-CA 1.3 –1.0 14.9 –4.0 –3.4 0.2 –3.5 10.2 6.1 1.7 –6.7 –2.9 –25.8 –3.7 3. LBUCK –8.5 –6.5 –5.2 –6.6 –3.8 –10.0 13.3 8.5 13.9 4.7 –29.8 –24.4 4. SUG-NP –3.7 –2.1 6.5 5.2 16.6 11.9 –22.5 –27.0 29.2 17.5 2.4 2.0 10.1 11.5 –49.9 –48.9 5. WHITE 2.9 2.4 7.8 5.8 –1.7 –0.2 –5.4 –2.9 –69.5 –73.7 23.3 1.0 7.9 10.5 0.6 0.9 –17.7 –11.2 6. WABASH –1.0 0.0 2.4 0.0 –4.4 –2.6 –19.8 –12.8 –52.8 –57.0 12.1 1.4 –22.5 –23.3 –5.6 –1.9 –27.2 –30.5 –26.4 –18.5 7. OHIO-GRCH 0.6 –0.7 5.4 –2.4 –2.2 0.2 –23.8 –16.2 5.0 –0.5 –3.6 –0.5 –18.3 –2.3 8. DUCK 0.3 –0.0 10.9 13.3 19.9 9.1 2.0 20.8 –9.3 –9.4 11.4 14.9 –13.8 3.1 –16.2 6.9 9. MILW 1.1 3.2 15.3 –1.8 17.7 7.8 –2.1 2.0 –11.8 –11.7 –12.4 –9.0 10. CLINT –14.8 –12.0 –23.5 –7.0 4.2 –9.0 –3.4 –9.6 14.3 8.6 –42.5 –17.2 11. STJOS 11.1 –0.3 13.6 2.1 46.9 27.4 22.6 11.7 22.1 12.2 58.4 29.9 20.9 13.3 12. AUGL –7.7 –4.9 2.7 0.1 –13.0 –9.0 –31.3 –28.0 –29.3 –23.4 –14.5 –9.9 9.0 11.5 –11.4 –2.3 13. MAUM –10.4 –7.7 –4.2 –2.3 –3.8 –0.9 –20.0 –17.0 –34.9 –45.4 1.4 0.7 –7.1 –2.6 –3.3 0.9 1.5 9.4 –27.3 –21.4 14. LCOBB –19.6 –11.2 3.0 6.7 –11.2 2.3 15. MSSP-HA 12.0 9.6 –1.9 7.3 1.8 12.7 7.2 4.2 1.6 –2.5

16. MSSP-CL –2.2 –3.4 –5.5 –7.2 1.0 1.1 –39.2 –38.9 2.2 0.5

17. WAPS-TR –5.7 –12.8 –18.3 –5.1 –10.5 –7.5 –13.1 –11.3 –2.7 2.6

18. IOWA-ROW –4.5 –2.1 20.9 9.7 –17.8 –13.9 24.4 15.1

19. SFIOWA –2.8 –2.8 12.8 3.8 –1.4 –4.0 8.6 8.0 –10.3 2.3

20. IOWA-WAP –8.4 –8.6 18.2 18.1 –6.1 –5.7 –21.0 –15.9 10.6 9.4 –2.0 –2.7

21. SUG-MIL 3.3 0.9 22.1 14.3 7.4 7.8 –65.0 –52.9 5.9 –11.6 –35.0 –4.8

22. DPLAI –1.8 –0.2 14.0 10.7 16.7 5.7 –5.5 –3.9 2.3 –0.4 –29.5 –31.4

23. ILLI-OTT –6.3 –3.6 9.9 9.2 –14.2 –11.6 –5.9 –8.7 14.3 12.1 –8.1 –5.1 –26.8 –22.9

24. SANG –5.7 –4.5 –11.4 –10.6 –15.0 –14.8 –7.0 –2.7 0.0 2.0 6.8 2.4

25. ILLI-VC –7.3 –5.8 0.1 –0.0 –12.7 –11.9 –2.5 –3.6 4.5 5.6 2.3 0.8 –33.1 –32.5

26. MSSP-GR –3.3 –2.3 4.5 3.8 –8.2 –8.6 –6.6 –4.3 9.6 11.5 5.4 8.7 –45.9 –43.5

27. MIZZ-OM 15.7 0.8 –6.2 –4.1 13.2 0.3 –3.8 –17.1 –37.7 –48.8 –32.0 –22.5 13.6 0.7 –3.9 3.7

28. MAPLE 22.1 4.2 50.0 7.7 9.1 –3.6 31.8 14.6 –25.9 –31.5 20.6 6.1 28.2 6.0 –1.9 –0.3 50.8 35.6 –9.3 –1.9

29. PLATTE 12.6 0.4 28.4 4.6 9.8 2.9 9.6 2.1 –28.8 –31.6 0.8 –9.7 1.1 4.0 –11.6 –5.7

30. MIZZ-HE 3.6 4.0 11.0 8.8 –2.4 –1.7 –5.7 –4.6 –53.6 –65.7 23.0 20.4 –12.6 –13.7 3.9 3.8 –39.4 –34.4

31. MSSP-TH –1.1 –1.5 10.9 7.6 –3.6 –4.6 –8.7 –7.8 13.3 11.3 5.3 6.8 –44.0 –40.2
Trends in Pesticide Concentrations 25

 Flow adjustment affected the fitted trends for atrazine, 

acetochlor, and metolachlor to varying degrees (table 8). 

Considering atrazine, for example, both the unadjusted and 

flow-adjusted trends indicated generally stable or decreasing 

concentrations. Of the 30 sites analyzed, both approaches indicated no significant trend in atrazine concentration for 17 sites 

and both approaches indicated a significant decrease for 

9 sites. Of the remaining four sites, there was a difference in 

the significance but not the direction of the trends between the 

two methods. Of the 30 sites analyzed for acetochlor trends for 

1996–2002, both unadjusted and flow-adjusted trends indicated no significant change for 13 sites, both approaches indicated a significant decrease for 3 sites, and both approaches 

indicated a significant increase for 1 site. However, there 

were 13 sites for which the significance of the trends changed. 

Both the unadjusted and flow-adjusted trends for metolachlor 

concentration indicated significant downtrends for 19 of the 

31 sites analyzed. Of the remaining 12 sites, the directions of 

the unadjusted and flow-adjusted trends were in agreement, 

but the significance of the trends differed for 6 of those sites.

Closer examination of the model results for atrazine, 

acetochlor, and metolachlor indicated that substantial flowrelated variability existed in the pesticide concentrations for 

most sites and, despite qualitative differences in the way that 

variability affected the significance of the fitted trends, there 

was a consistent pattern in the way the flow-related variables 

affected the trend magnitudes among the three pesticides. One 

or more of the flow variables in eq. (7) were strongly related 

to atrazine, acetochlor, and metolachlor concentration for 

most sites and the coefficients for the flow anomalies (LTFA, 

MTFA, and STFA) were similar among the three pesticides. 

Summary statistics of the fitted trends in atrazine, acetochlor, 

and metolachlor concentrations for the sites analyzed for those 

pesticides (table 10) indicate the effect of the flow adjustment on the trend magnitudes. The flow-adjusted downtrends 

generally were smaller in magnitude than the unadjusted 

downtrends by an average of about 2 percent per year (pct/

yr) for atrazine (–7.7 pct/yr compared to –10.1 pct/yr), about 

4 pct/yr for acetochlor, and about 6 pct/yr for metolachlor. 

Similarly, with the exception of metolachlor (for which there 

were only four uptrends), the flow-adjusted uptrends generally were smaller in magnitude than the unadjusted uptrends 

by an average of about 4 pct/yr for atrazine and about 6 pct/yr 

for acetochlor. The large unadjusted uptrends for atrazine and 

acetochlor were particularly sensitive to flow adjustment. For 

example, the largest, unadjusted uptrend for acetochlor was 

54.1 pct/yr, compared to the largest flow-adjusted uptrend of 

29.4 pct/yr. 

There was near unanimous agreement among the direction and significance of the unadjusted and flow-adjusted 

trends for 1996–2002 for alachlor and cyanazine (table 8). 

All of the trends for these herbicides were downtrends and 

almost all were significant. Although there was significant 

flow-related variability in the pesticide concentrations for most 

sites, the variability was small, in relation to the overall pattern 

of decreasing concentrations. Similarly, most of the EPTC, 

metribuzin, and chlorpyrifos concentration trends that could 

be analyzed were downtrends as well, and most were significant. However, the high number of censored values for those 

pesticides (table 3) made it difficult to detect trends for most 

sites either with or without flow adjustment.

The fitted trends for simazine and prometon concentration for 1996–2002 were the most sensitive to flow adjustment 

of the 11 pesticides evaluated (table 8). Of the 28 sites analyzed for simazine trends, both unadjusted and flow-adjusted 

trends indicated significant uptrends for 8 sites and significant 

downtrends for 3 sites. However, either the direction or significance of the unadjusted and flow-adjusted trends differed for 

13 of the remaining 17 sites. Most of the significant trends 

were uptrends, with 9 significant unadjusted uptrends and 

14 significant flow-adjusted uptrends. For prometon, either the 

direction or significance of the unadjusted and flow-adjusted 

uptrends differed for 14 sites. However, unlike simazine, most 

of the significant trends for prometon were downtrends. Of the 

29 sites analyzed, both unadjusted and flow-adjusted trends 

for prometon indicated significant downtrends for 10 sites. 

There was only one significant unadjusted uptrend and no

significant flow-adjusted uptrends. 

Pesticide Trend type

Downward trends Upward trends

Count Average 

(pct/yr)

Largest 

(pct/yr) Count Average (pct/yr)

Largest 

(pct/yr)

Atrazine Unadjusted 19 –10.1 –27.3 11 7.3 24.7

Flow-adjusted 18 –7.7 –23.0 12 3.0 7.8

Acetochlor Unadjusted 15 –10.9 –44.2 15 16.0 54.1

Flow-adjusted 17 –7.0 –31.1 13 9.9 29.4

Metolachlor Unadjusted 27 –17.7 –32.0 4 5.6 11.3

Flow-adjusted 27 –11.2 –27.4 4 7.8 13.8

Table 10. Statistical comparison of unadjusted and flow-adjusted trend magnitudes for atrazine, acetochlor, and metolachlor for the 

1996–2002 analysis period. 

[pct/yr, percent per year]
26 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

The trends for diazinon concentration for 1996–2002 

also were affected by flow adjustment (table 8). Either the 

direction or significance of the unadjusted and flow-adjusted 

trends differed for 9 of the 18 sites analyzed. However, most 

of the trends were not significant. There were three significant 

unadjusted uptrends and one significant unadjusted downtrend, 

compared to three significant flow-adjusted uptrends and two 

significant flow-adjusted downtrends. 

A detailed examination of selected results for acetochlor 

shows the influence of flow adjustment on the significance 

and degree of trend. Model results for four sites (OHIOCA, WABASH, MSSP-CL, and IOWA-WAP) are shown in 

figure 3. The measured acetochlor concentrations are shown 

along with the fitted concentrations and trends from the 

SEAWAVE model (left-hand plots) and SEAWAVE-Q model 

(right-hand plots). For OHIO-CA, there was a small and 

nonsignificant uptrend (2.4 pct/yr, p = 0.65) without flowadjustment, compared to a significant flow-adjusted uptrend 

(10.5 pct/yr, p = 0.03). Of the three flow coefficients in the 

model (eq. 7), the coefficient for LTFA was positive and highly 

significant (0.91, p = 0.01), MTFA was negative and not 

significant (–0.26, p = 0.11), and STFA was negative and not 

significant (–0.15, p = 0.40). LTFA for this site was high during 1997 and low during 2000, which is reflected in the fitted 

concentrations from SEAWAVE-Q for those years. Without 

LTFA in the model, the slope of the unadjusted trend line was 

reduced as a result of the anomalous concentrations during 

those years. For WABASH, there was a highly significant 

unadjusted downtrend (–13.6 pct/yr, p = 0.01) compared 

to a smaller and not significant flow-adjusted downtrend 

(–7.6 pct/yr, p = 0.12). Neither LTFA nor MTFA were significant predictors of acetochlor concentration for this site. 

However, the coefficient for STFA was positive and highly 

significant (0.99, p < 0.001). The significant unadjusted 

downtrend for this site may have been caused, at least in part, 

by failure to account for short-term flow-related variability 

(because STFA is not included in SEAWAVE). For MSSP-CL, 

there was a highly significant unadjusted uptrend (14.8 pct/yr, 

p = 0.01) compared to a slight and nonsignificant flowadjusted downtrend (–0.8 pct/yr, p = 0.86). The coefficients 

for LTFA (–2.04, p = 0.03), MTFA (0.63, p = 0.02), and STFA 

(0.77, p = 0.004) all were significant for this site. The large 

negative coefficient for LTFA was particularly noteworthy. 

The unadjusted uptrend probably was caused by generally 

decreasing annual flows for this site during 1996–2000. For 

IOWA-WAP, there was a fairly large but nonsignificant unadjusted downtrend (–9.7 pct/yr, p = 0.16) compared to a similar 

but more significant flow-adjusted downtrend (–8.4 pct/yr, 

p = 0.08). The coefficients for LTFA (1.07, p = 0.003), MTFA 

(1.04, p < 0.001), and STFA (1.68, p < 0.001) all were positive 

and highly significant for this site. In this case, the flow variables were effective in explaining variability in the acetochlor 

concentration data but had little effect on the fitted trend, other 

than to increase its significance.

Overview of Trend Results for 2000-2006

The unadjusted and flow-adjusted trends for the 2000–

2006 analysis period are shown in table 9. Compared to the 

1996–2002 analysis period (table 8), there were fewer significant trends during 2000–2006. Of the 210 pairs of results for 

2000–2006, only about 25 percent (49 pairs) had significant 

trends by both methods. However, the directions of the trends 

were in agreement for all of the pairs that had significant 

trends by both methods. There were 38 pairs of results for 

2000–2006 for which the statistical significance of the trends 

differed, and in most of those (33 pairs), significant unadjusted 

trends changed to nonsignificant flow-adjusted trends. This is 

in contrast to the results for 1996–2002, in which there were 

a substantial number of pairs (26) in which nonsignificant 

unadjusted trends changed to significant flow-adjusted trends. 

However, the number of pairs in which the direction of the 

unadjusted and flow-adjusted trends changed for 2000–2006 

was similar to the earlier period—29 pairs for 2000–2006 

compared to 26 pairs for 1996–2002. 

With the exception of cyanazine and diazinon, for which 

both unadjusted and flow-adjusted trends for 2000–2006 

were predominately downtrends and significant, and EPTC, 

metribuzin, and chlorpyrifos, for which there were too few 

uncensored concentrations to draw any definitive conclusions, 

flow-adjustment was an important consideration for interpreting trends in the remaining pesticides. Careful consideration 

of flow-related variability is important for interpreting and 

analyzing trends for this latter period, especially because 

of the generally lower sampling frequencies compared to 

1996–2002.

Flow adjustment had a similar effect on the fitted trends 

for atrazine, acetochlor, and metolachlor for 2000–2006 

(table 9). There were more unadjusted uptrends than flowadjusted uptrends for those pesticides. A total of 49 of the 

93 site-pesticide combinations had unadjusted uptrends, 

16 of which were significant, compared to 43 site-pesticide 

combinations with flow-adjusted uptrends, only 4 of which 

were significant. This situation is illustrated in figure 4 for 

acetochlor concentration for several of the sites (MAD, 

STJOS, IOWA-ROW, and PLATTE). There were substantial 

unadjusted uptrends for all four of the sites, although only one 

of the trends (PLATTE) was significant. However, all of the 

flow-adjusted trends were small and nonsignificant and one 

(MAD) was downward. There was strong and highly significant flow-related variability in acetochlor concentrations for 

all four sites and that variability may have resulted in upward 

bias in the unadjusted trends. Such bias would be expected to 

be especially evident for small sample sizes, especially if the 

sampling frequencies change from year to year, as was the 

case for each of these sites.
Trends in Pesticide Concentrations 27

-4

-3

-2

-1

0

1

OHIO-CA

-3

-2

-1

0

1

2

WABASH

-5

-4

-3

-2

-1

0

1

2

MSSP-CL

1996 1997 1998 1999 2000 2001 2002

YEAR

-4

-3

-2

-1

0

1

2

IOWA-WAP

ACETOCHLOR CONCENTRATION, AS BASE-10 LOGARITHM OF MICROGRAMS PER LITER

OHIO-CA

WABASH

MSSP-CL

1996 1997 1998 1999 2000 2001 2002

IOWA-WAP

EXPLANATION

Uncensored

Censored

SEAWAVE

Trend

SEAWAVE-Q

Flow-adjusted trend

IP003821_Figure 03

Figure 3. Observed and fitted acetochlor concentrations for selected sites for the 1996–2002 analysis period using SEAWAVE (left) and 

SEAWAVE-Q (right).
28 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

Figure 4. Observed and fitted acetochlor concentrations for selected sites for the 2000–2006 analysis period using SEAWAVE (left) and 

SEAWAVE-Q (right).

MAD

STJOS

IOWA-ROW

PLATTE

MAD

STJOS

IOWA-ROW

PLATTE

2000 2001 2002 2003 2004 2005 2006 2000 2001 2002 2003 2004 2005 2006

YEAR

ACETOCHLOR CONCENTRATION, AS BASE-10 LOGARITHM OF MICROGRAMS PER LITER -4

-3

-2

-1

0

1

2

3

-5

-4

-3

-2

-1

0

1

2

-4

-3

-2

-1

0

1

2

-4

-3

-2

-1

0

1

2

EXPLANATION

Uncensored

Censored

SEAWAVE

Trend

SEAWAVE-Q

Flow-adjusted trend

IP003821_Figure 04
Trends in Pesticide Concentrations 29

Flow adjustment also affected the trends for simazine 

concentrations for the 2000–2006 analysis period (table 9). 

Either the direction or significance of the unadjusted and flowadjusted trends for simazine differed for 10 of the 27 sites 

analyzed. Examples of the trends for four of the sites (OHIOCA, WABASH, ILLI-VC, and MSSP-GR) are shown in 

figure 5. For OHIO-CA, both the unadjusted and flow-adjusted 

trends were small and nonsignificant. For WABASH, there 

was a strong and significant unadjusted uptrend but a slight 

and nonsignificant flow-adjusted uptrend. For ILLI-VC and 

MSSP-GR, the unadjusted and flow-adjusted uptrends were 

similar in magnitude. However, the significance of the trends 

increased as a result of the flow adjustment.

Flow adjustment had the most pronounced effect on 

prometon concentration trends for 2000–2006 (table 9). There 

were significant unadjusted trends in prometon concentration 

for 12 of the 28 sites analyzed, including 8 significant downtrends and 4 significant uptrends. However, there were only 2 

significant flow-adjusted downtrends and 4 significant flowadjusted uptrends. The results are shown in figure 6 for four 

of the sites (OHIO-CA, WABASH, AUGL, and SUG-MIL). 

In each case, significant unadjusted downtrends were reduced 

in both size and significance with flow adjustment. The effect 

of the flow-related variability is particularly evident for the 

AUGL and SUG-MIL sites.

Detailed Analysis of Flow-Adjusted Trends 

Analysis of flow-adjusted trends, which is the focus of 

this section, is preferable to analysis of non-adjusted trends 

for evaluating potential effects of changes in pesticide use or 

management practices because flow-adjusted trends account 

for the influence of flow-related variability. If ignored, these 

influences of flow conditions may alter or disguise trends 

caused by changes in pesticide use or management practices. 

In addition, the hydrologic connectivity between watersheds 

and the relative contributions of streamflow and pesticide 

flux from specific sites are important considerations for 

interpreting trend directions and magnitudes. 

For each pesticide, trend results are summarized with two 

figures and a table that follow a consistent format to facilitate 

comparisons. The first figure illustrates the significance level, 

magnitude, and direction of flow-adjusted trends in relation to: 

(1) site locations within the drainage network, and (2) relative 

contributions of streamflow and pesticide transport. Figure 7, 

which summarizes results for atrazine, is an example of this 

first figure. Figure 8 is an example of the second figure, a 

time-series plot of concentration and use intensity for seven 

study sites that were selected as indicators of major subareas 

of the Corn Belt, and that have large enough drainage areas 

such that reasonable use estimates are possible. Changes 

in pesticide use intensity over time were estimated for the 

watersheds of these sites, plus the four major river sites that 

are at the outlets of major drainages and that have the greatest flows (OHIO-GRCH, MSSP-GR, MIZZ-HE, and MSSPTH) by fitting a straight line to log-transformed annual use 

intensity for the specified analysis period using ordinary 

least-squares regression. Results for the 11 sites, referred to as 

“use-trend” sites, are summarized in a table for each pesticide, 

such as in table 11 for atrazine.

Atrazine

Atrazine concentrations generally were stable or decreasing during 1996–2002 (fig. 7). Of the 30 sites analyzed for this 

period, 20 had small and nonsignificant trends and the remaining 10 sites had significant or highly significant downtrends. 

Atrazine concentrations also were generally stable or decreasing during 2000–2006, but the downtrends were smaller 

and less significant than during 1996–2002. Of the 31 sites 

analyzed during the latter period, 26 had nonsignificant trends, 

4 had significant but relatively small (less than 13 pct/yr) 

downtrends, and one site had a significant uptrend. Although 

the downtrends were smaller and less significant than the 

earlier analysis period, generally there was a similar frequency 

of downtrends during 2000–2006 (21 of 31 sites) compared to 

1996–2002 (18 of 30 sites).

Ohio River and Great Lakes Basins (sites 1-13)

There was a small (about 5 pct/yr) and nonsignificant 

downtrend in atrazine concentration for the most downstream Ohio River Basin site, OHIO-GRCH (site 7) during 

1996–2002, but the four sites in the tributary Wabash River 

Basin (sites 3–6) had highly significant downtrends. The small 

downtrend for OHIO-GRCH during 1996–2002 is consistent 

with the combined influence of the downtrend for WABASH, 

which is a major source of atrazine to the Ohio River, and 

a small and nonsignificant uptrend for OHIO–CA (site 2). 

Although OHIO-CA contributed much more streamflow than 

WABASH, the Wabash River drains some of the most intensively farmed area of the Ohio River Basin and provided a 

substantially larger atrazine flux than OHIO–CA. There also 

were significant downtrends during 1996–2002 for MAUM 

(site 13), the Great Lakes Basins site with the largest drainage 

area, and for a small tributary to that site, STJOS (site 11).

During 2000–2006, trends were notably different in the 

Ohio River Basin, with only small and nonsignificant trends 

for all seven sites. In the Great Lakes Basin, however, MAUM 

still had a significant downtrend, as did CLINT (site 10), a site 

with a small watershed and substantial urban influence.
30 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

Figure 5. Observed and fitted simazine concentrations for selected sites for the 2000–2006 analysis period using SEAWAVE (left) and 

SEAWAVE-Q (right).

-3

-2

-1

0

1

OHIO-CA

WABASH

ILLI-VC

YEAR

MSSP-GR

SIMAZINE CONCENTRATION, AS BASE-10 LOGARITHM OF MICROGRAMS PER LITER

OHIO-CA

WABASH

ILLI-VC

MSSP-GR

-3

-2

-1

0

1

-3

-2

-1

0

1

-3

-2

-1

0

1

2000 2001 2002 2003 2004 2005 2006 2000 2001 2002 2003 2004 2005 2006

EXPLANATION

Uncensored

Censored

SEAWAVE

Trend

SEAWAVE-Q

Flow-adjusted trend

IP003821_Figure 05
Trends in Pesticide Concentrations 31

Figure 6. Observed and fitted prometon concentrations for selected sites for the 2000–2006 analysis period using SEAWAVE (left) and 

SEAWAVE-Q (right).

OHIO-CA

WABASH

AUGL

YEAR

SUG-MIL

PROMETON CONCENTRATION, AS BASE-10 LOGARITHM OF MICROGRAMS PER LITER

OHIO-CA

WABASH

AUGL

SUG-MIL

-3

-2

-1

0

-3

-2

-1

0

-3

-2

-1

0

1

2000 2001 2002 2003 2004 2005 2006 2000 2001 2002 2003 2004 2005 2006

-4

-3

-2

-1

0

1

EXPLANATION

Uncensored

Censored

SEAWAVE

Trend

SEAWAVE-Q

Flow-adjusted trend

IP003821_Figure 06
32 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

 1. MAD

 2. OHIO-CA

 3. LBUCK

 4. SUG-NP

 5. WHITE

 6. WABASH

 7. OHIO-GRCH

 8. DUCK

 9. MILW

10. CLINT

11. STJOS

12. AUGL

13. MAUM

14. LCOBB

15. MSSP-HA

16. MSSP-CL

17. WAPS-TR

18. IOWA-ROW

19. SFIOWA

20. IOWA-WAP

21. SUG-MIL

22. DPLAI

23. ILLI-OTT

24. SANG

25. ILLI-VC

26. MSSP-GR

27. MIZZ-OM

28. MAPLE

29. PLATTE

30. MIZZ-HE

31. MSSP-TH

-60 0 +60 -60 0 +60

TREND, IN PERCENT PER YEAR

1996-2002 2000-2006

Atrazine

Flow-adjusted trends in concentration

Estimated value

90-percent confidence limits

Nonsignificant

(p > 0.1)

Significant

(p < 0.1)

Highly significant

(p < 0.01)

Average annual

flux, 1996-2006

(kg/yr)

Average daily

flow, 1996-2006

(m3/s)

< 4,000

40,000

400,000

< 80

800

8,000

NA NA

NA is not analyzed; > is greater than;

< is less than

IP003821_Figure 07

Figure 7. Flow-adjusted trends in atrazine concentration for 1996–2002 and 2000–2006 analysis periods.
Trends in Pesticide Concentrations 33

8 20 21 12 11 10 8 7 7 7 11

13 17 14 13 13 11 7 8 8 6 11

13 14 13 13 11 13 13 12 13 10

6 14 16 14 15 11 18 17 8 6 4

12 13 14 12 12 15 15 15 14 11

11 30 13 12 12 11 9 9 9 8 11

2 15 14 12 9 16 14 14 16 12

ILLI-VC

MAUM

MSSP-CL 

PLATTE

OHIO-CA

IOWA-WAP

WABASH

ATRAZINE CONCENTRATION, IN MICROGRAMS PER LITER

1996 1998 2000 2002 2004 2006

1996 1998 2000 2002 2004 2006

0.1

0.01

0.002

0.002

0.002

0.002

1

10

0.1

0.01

1

10

0.1

0.01

1

10

0.1

0.01

1

10

50

50

50

50

ATRAZINE USE INTENSITY, IN KILOGRAMS PER SQUARE KILOMETER 

1

10

100

1

10

100

1

10

100

1

10

100

EXPLANATION

25th percentile

75th percentile

Median

Maximum observed concentration

Minimum observed concentration

12 Number of samples

Maximum long-term method detection level

Atrazine use intensity

1996-2002 analysis period

2000-2006 analysis period

Figure 8. IP003821_Figure 08 Atrazine use intensity and stream-water concentrations for selected trend sites in the Corn Belt, 1996–2006.
34 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

Table 11. Flow-adjusted trends in atrazine concentration and changes in atrazine use intensity for selected sites for the 1996–2002 and 

2000–2006 trend analysis periods.

[Bold type indicates significant (p ≤ 0.10) trends or changes in use intensity]

Site map number 

and short name

(see table 1)

1996–2002 2000–2006

Flow-adjusted trend 

(percent per year)

Change in use 

(percent per year)

Flow-adjusted trend 

(percent per year)

Change in use 

(percent per year)

 2. OHIO-CA 2.4 –2.6 –1.0 –0.7

 6. WABASH –11.5 2.5 0.0 –3.0

 7. OHIO-GRCH –4.2 0.9 –0.7 –2.7

13. MAUM –6.9 –1.6 –7.7 –0.2

16. MSSP-CL –1.4 –0.8 –3.4 –2.3

20. IOWA-WAP –0.5 –1.9 –8.6 –0.1

25. ILLI-VC 1.5 2.8 –5.8 –0.7

26. MSSP-GR -0.3 –0.4 –2.3 –0.5

29. PLATTE –8.9 –2.5 0.4 –1.4

30. MIZZ-HE –1.3 0.6 4.0 –3.6

31. MSSP-TH -2.2 0.3 –1.5 –1.9

Trends in Relation to Changes in Use Intensity

Atrazine use for all 11 use-trend sites was relatively 

stable during both analysis periods (table 11 and fig. 8). 

Estimated use trends range from a decrease of 3.6 pct/yr for 

MIZZ-HE during 2000–2006 to an increase of 2.8 pct/yr for 

ILLI-VC during 1996–2002. Consistent with stable use, 16 of 

the 22 cases analyzed for both time periods had flow-adjusted 

trends in atrazine concentration that were nonsignificant. 

However, there were two sites during 1996–2002: WABASH 

and MAUM, and three sites during 2000–2006: MAUM, 

IOWA-WAP, and ILLI-VC at which significant downtrends 

occurred despite no significant trend in use intensity. These 

downtrends may be the result of reduced transport of atrazine 

to streams due to agricultural management changes, such as 

increases in conservation tillage and application buffer strips 

along streams during the trend-assessment periods. The proportion of crop acreage with conservation tillage practices has 

increased steadily since 1990 (Fawcett, 2008) and, beginning 

in 1992, label instructions on most atrazine products called for 

20-m no-application buffers along streams, including seeded 

buffers for highly erodible land (Paul Hendley, Syngenta, 

written commun., 2008). The degree and timing of implementation of these changes in the basins of the four sites requires 

further investigation, however, in order to further evaluate this 

potential influence. Another possible explanation is inaccurate 

estimates of use trends for these sites, which have among 

the smaller watershed areas of the 11 use-trend sites. Both 

the concentration and use trends are relatively low and a 

more quantitative uncertainty analysis of differences in 

concentration and use trends is needed.

Mississippi and Missouri River Basins 

(sites 14–31)

For the 1996–2002 time period, there were small (less 

than 5 pct/yr) and nonsignificant flow-adjusted trends in 

atrazine concentration for the downstream Mississippi River 

site, MSSP-TH (site 31); both large tributaries to that site, 

MSSP-GR (site 26) and MIZZ-HE (site 30); and all three 

major tributaries to MSSP-GR, which are MSSP-CL, IOWAWAP, and ILLI-VC (sites 16, 20, and 25). There were highly 

significant downtrends for smaller tributaries in the Iowa River 

Basin (SFIOWA, site 19), the Illinois River Basin (SANG, 

site 24), and the Missouri River Basin (PLATTE, site 29), 

and a significant downtrend for another small Iowa tributary 

(IOWA-ROW, site 18). The average annual atrazine fluxes 

for the small basins were negligible compared to the larger 

downstream basins, however, and the large downtrends in the 

small basins did not substantially impact the overall stable 

concentrations at downstream sites. The trends for the remaining smaller basins, like the large downstream basins, were 

small and nonsignificant during 1996–2002.

For 2000–2006, as during 1996–2002, there were small 

and nonsignificant trends for the three largest basins, MSSPGR, MIZZ-HE, and MSSP-TH (sites 26, 30, and 31, respectively). However, unlike 1996–2002, there were significant 

downtrends for two of the major tributaries to MSSP-GR, 

specifically IOWA-WAP and ILLI-VC (sites 20 and 25), and a 

significant uptrend for MSSP-HA (site 15).
Trends in Pesticide Concentrations 35

Acetochlor

Trends in acetochlor concentrations for 1996–2002 were 

highly variable among sites (fig. 9). Of the 30 sites analyzed, 

20 had nonsignificant trends, 6 had significant downtrends, 

and 4 had significant uptrends. For the Ohio River Basin sites 

(sites 1–7), the upper Mississippi and Iowa River Basin sites 

(sites 14–20), and the Missouri and lower Mississippi River 

Basin sites (sites 26–31), trends in acetochlor concentration during 1996–2002 were qualitatively similar to atrazine 

(fig. 7). However, for the Great Lakes Basins sites (sites 8–13) 

and the Illinois River Basin sites (sites 21–25), there were 

more uptrends and fewer downtrends in acetochlor compared 

to atrazine. During 2000–2006, there were no significant 

downtrends and only one significant uptrend in acetochlor 

concentration. Although not individually significant, acetochlor concentrations at 19 of 31 sites showed uptrends during 

2000–2006, in contrast to atrazine, in which most (21 of 

31 sites) trends were downward.

Ohio River and Great Lakes Basins (sites 1–13)

In the highly agricultural Wabash River Basin, there were 

moderate (5–15 pct/yr) downtrends for all four sites (3–6) 

during 1996–2002, and three of the trends were significant. 

Conversely, there was a significant uptrend (about 10 pct/yr) 

for OHIO-CA (site 2) during that time. The OHIO-CA site is 

only 55 percent agricultural land use and is less intensively 

row-cropped than sites in the Wabash River Basin. During 1996–2002 the small (about 2 pct/yr) and nonsignificant 

downtrend in acetochlor concentration for OHIO-GRCH 

(site 7), the downstream-most Ohio River Basin site, reflects 

influences from both WABASH (site 6), which provided a 

large part of the flux for OHIO-GRCH, and OHIO-CA, which 

provided a smaller but still substantial part of the flux for 

OHIO-GRCH. All five Great Lakes Basins sites analyzed had 

uptrends during 1996–2002, and the uptrend at MILW (site 9) 

was significant. During 2000–2006, there were no significant 

trends in acetochlor concentration for any of the Ohio River 

Basin and Great Lakes Basins sites.

Mississippi and Missouri River Basins 

(sites 14–31)

During 1996–2002, there were small (less than 

5 pct/yr) and nonsignificant trends in acetochlor concentration for MSSP–TH (site 31, the downstream-most Mississippi River site), as well as for both major tributaries to that 

site, MSSP–GR and MIZZ–HE (sites 26 and 30). However, 

trends for the 3 main tributary sites to MSSP–GR were mixed: 

MSSP–CL (site 16) had a nonsignificant downtrend; IOWA–

WAP (site 20) had a significant downtrend; and ILLI–VC (site 

25) had a significant uptrend during 1996–2002. There also 

was a large and highly significant downtrend for SFIOWA 

(site 19), a small Iowa tributary, a large and highly significant 

uptrend at the upstream Illinois River site ILLI–OTT (site 

23), and a significant downtrend for an Illinois River tributary, 

SANG (site 24) during that time. During 2000–2006, most (13 

of 18) of the trends in acetochlor concentration for sites 14–31 

were upward, although only one, IOWA–WAP (site 20) was 

significant. 

Trends in Relation to Changes in Use Intensity

Acetochlor was registered in 1994, the same year it was 

first used for weed control in corn fields, and use of this herbicide increased rapidly during the following 2 years. During 

1996–2006, total acetochlor use for the overall Corn Belt was 

relatively constant (fig. 2). However, within the watersheds of 

the 11 use-trend sites, acetochlor use was variable (table 12, 

fig. 10) and ranged from a decrease of 6.7 pct/yr at WABASH 

during 2000–2006 to an increase of 6.9 pct/yr at ILLI-VC 

during 1996–2002. The trends in acetochlor concentration also 

were variable and, moreover, the trends were not significant 

for 18 of the 22 cases analyzed for both trend analysis periods 

for the 11 use-trend sites. A significant downtrend occurred 

at one site, IOWA–WAP, during 1996–2002, despite nonsignificantly declining use. In contrast, concentrations trended 

upward at OHIO-CA, despite nonsignificantly declining use 

(table 12). During 2000–2006, the IOWA-WAP concentration trend reversed to a significant uptrend even though use 

was significantly downward. This difference in results for the 

two periods for IOWA-WAP, which is one of the smaller of 

the use-trend watersheds, may result from inaccurate usetrend estimates. Results do not provide a consistent pattern, 

compared to atrazine, for the potential influence of non-use 

management practices. While atrazine results indicated steeper 

concentration downtrends during 1996–2002 at WABASH and 

MAUM, acetochlor, which would have been affected by many 

of the same practices, had no significant trend in either concentration or use. During 2000–2006, atrazine results indicated 

steeper concentration downtrends at MAUM, IOWA-WAP, 

and ILLI-VC, whereas acetochlor concentration trends were 

nonsignificant, upward, and nonsignificant, respectively.
36 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

Figure 9. Flow-adjusted trends in acetochlor concentrations for 1996–2002 and 2000–2006 analysis periods.

 1. MAD

 2. OHIO-CA

 3. LBUCK

 4. SUG-NP

 5. WHITE

 6. WABASH

 7. OHIO-GRCH

 8. DUCK

 9. MILW

10. CLINT

11. STJOS

12. AUGL

13. MAUM

14. LCOBB

15. MSSP-HA

16. MSSP-CL

17. WAPS-TR

18. IOWA-ROW

19. SFIOWA

20. IOWA-WAP

21. SUG-MIL

22. DPLAI

23. ILLI-OTT

24. SANG

25. ILLI-VC

26. MSSP-GR

27. MIZZ-OM

28. MAPLE

29. PLATTE

30. MIZZ-HE

31. MSSP-TH

-60 0 +60 -60 0 +60

TREND, IN PERCENT PER YEAR

1996-2002 2000-2006

Acetochlor

Flow-adjusted trends in concentration

Estimated value

90-percent confidence limits

Nonsignificant

(p > 0.1)

Significant

(p < 0.1)

Highly significant

(p < 0.01)

Average annual

flux, 1996-2006

(kg/yr)

Average daily

flow, 1996-2006

(m3/s)

< 800

8,000

80,000

< 80

800

8,000

NA NA

NA is not analyzed; > is greater than;

< is less than

IP003821_Figure 09
Trends in Pesticide Concentrations 37

8 20 21 12 11 10 8 7 7 7 11

13 17 14 13 13 11 7 8 8 6 11

13 14 13 13 11 13 13 12 13 10

6 14 16 14 15 11 18 17 8 6 4

12 13 14 12 12 15 15 15 14 11

11 30 13 12 12 11 9 9 9 8 11

2 15 14 12 9 16 14 14 16 12

ILLI-VC

MAUM

MSSP-CL 

PLATTE

OHIO-CA

IOWA-WAP

WABASH

ACETOCHLOR CONCENTRATION, IN MICROGRAMS PER LITER

1996 1998 2000 2002 2004 2006

1996 1998 2000 2002 2004 2006

0.1

0.01

0.002

0.002

0.002

0.002

1

10

0.1

0.01

1

10

0.1

0.01

1

10

0.1

0.01

1

10

20

20

20

20

ACETOCHLOR USE INTENSITY, IN KILOGRAMS PER SQUARE KILOMETER 

1

10

100

1

10

100

1

10

100

1

10

100

EXPLANATION

25th percentile

75th percentile

Median

Maximum observed concentration

Minimum observed concentration

12 Number of samples

Maximum long-term method detection level

Acetochlor use intensity

1996-2002 analysis period

2000-2006 analysis period

IP003821_Figure 10 Figure 10. Acetochlor use intensity and stream-water concentrations for selected trend sites in the Corn Belt, 1996–2006.
38 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

Site map number 

and short name

(see table 1)

1996–2002 2000–2006

Flow-adjusted trend 

(percent per year)

Change in use 

(percent per year)

Flow-adjusted trend 

(percent per year)

Change in use 

(percent per year)

 2. OHIO-CA 10.5 –3.0 –4.0 –5.5

 6. WABASH –7.6 2.6 0.0 –6.7

 7. OHIO-GRCH –0.9 0.6 –2.4 –6.1

13. MAUM 6.6 4.1 –2.3 –4.7

16. MSSP-CL –0.8 –0.9 –7.2 –3.2

20. IOWA-WAP -8.4 –2.0 18.1 –3.2

25. ILLI-VC 14.7 6.9 –0.0 –4.3

26. MSSP-GR –3.8 –0.2 3.8 –2.8

29. PLATTE –4.1 6.8 4.6 0.6

30. MIZZ-HE –0.7 0.7 8.8 –4.4

31. MSSP-TH 1.3 0.4 7.6 –3.4

Table 12. Flow-adjusted trends in acetochlor concentration and changes in acetochlor use intensity for selected sites for the 

1996–2002 and 2000–2006 trend analysis periods.

[Bold type indicates significant (p ≤ 0.10) trends or changes in use intensity]

Metolachlor

Metolachlor concentrations were broadly decreasing 

during 1996–2002 (fig. 11). Of the 31 sites analyzed, 27 had 

downtrends; of these, 14 were highly significant and 5 were 

significant. Although four sites had uptrends indicated, none 

were significant. When compared to atrazine (fig. 7) and 

especially acetochlor (fig. 9), there were many more and larger 

significant downtrends in metolachlor concentrations during 

1996–2002. Trends in metolachlor during 2000–2006 were 

somewhat mixed, although there were still more downtrends 

than uptrends. Trends were significant at only six sites during 

2000–2006; of these, four were downtrends. The significant 

downtrends for 2000–2006 were similar to trends for 1996–

2002 for the same sites, but the two significant uptrends for the 

latter period were in contrast to highly significant downtrends 

for 1996–2002 at the same sites.

Ohio River and Great Lakes Basins (sites 1–13)

Highly significant downtrends in metolachlor concentration occurred for sites in the Wabash River Basin (sites 3–6) 

and the downstream Ohio River Basin site OHIO-GRCH 

(site 7) during 1996–2002. However, since the upstream Ohio 

River site OHIO-CA (site 2) had a smaller though still significant downtrend, it effectively diluted the downtrend at 

OHIO-GRCH, which was substantially smaller in magnitude 

(8 pct/yr) than the downtrend of about 17 pct/yr at WABASH 

(site 6). Significant downtrends also occurred during 1996–

2002 for the three Maumee River Basin sites (sites 11–13), 

and those trends were similar in magnitude to the downtrends 

for the Wabash River Basin sites. There were no significant 

uptrends during 1996–2002 at any of the Ohio River or Great 

Lakes Basins sites. There were fewer significant trends in 

metolachlor concentrations during 2000–2006 in the Ohio 

River and Great Lakes Basins. A significant downtrend 

occurred at small tributary site AUGL (site 12), and significant 

uptrends occurred at SUG-NP and STJOS (sites 4 and 11, 

respectively), which also are small tributary sites. 

Mississippi and Missouri River Basins 

(sites 14–31)

There were substantial (about 10–15 pct/yr) and highly 

significant downtrends in metolachlor concentration at 

MSSP–GR and MSSP–TH (sites 26 and 31), and at all 3 

major tributaries to MSSP–GR (MSSP–CL, IOWA–WAP, and 

ILLI–VC; sites 16, 20, and 25) during 1996–2002 (fig. 11). 

There also were highly significant downtrends at IOWA–ROW 

and SFIOWA (sites 18 and 19) and significant downtrends at 

Illinois River Basin sites ILLI–OTT and SANG (sites 23 and 

24). There were uptrends at SUG-MIL and DPLAI (sites 21 

and 22), but they were not significant and both sites are small 

tributaries to the Illinois Rver without much influence on total 

flows and fluxes. Although there were downtrends for the 

Missouri River Basin sites, all were nonsignificant with the 

exception of MAPLE (site 28), and the trend for downstream 

MIZZ–HE (site 30) was small and nonsignificant, contributing to a reduction in the magnitude of the trend at MSSP–TH 

compared to MSSP–GR. During 2000–2006, there again were 

significant downtrends at MSSP–GR of about 9 pct/yr and at 

several tributary sites, including ILLI–VC and SANG, as well 

as nonsignificant downtrends at numerous other tributary sites. 

There were no significant trends for the Missouri River Basin 

sites (sites 27–30) or the downstream Mississippi River site 

(site 31) during 2000–2006. 
Trends in Pesticide Concentrations 39

 1. MAD

 2. OHIO-CA

 3. LBUCK

 4. SUG-NP

 5. WHITE

 6. WABASH

 7. OHIO-GRCH

 8. DUCK

 9. MILW

10. CLINT

11. STJOS

12. AUGL

13. MAUM

14. LCOBB

15. MSSP-HA

16. MSSP-CL

17. WAPS-TR

18. IOWA-ROW

19. SFIOWA

20. IOWA-WAP

21. SUG-MIL

22. DPLAI

23. ILLI-OTT

24. SANG

25. ILLI-VC

26. MSSP-GR

27. MIZZ-OM

28. MAPLE

29. PLATTE

30. MIZZ-HE

31. MSSP-TH

-60 0 +60 -60 0 +60

TREND, IN PERCENT PER YEAR

1996-2002 2000-2006

Metolachlor

Flow-adjusted trends in concentration

Estimated value

90-percent confidence limits

Nonsignificant

(p > 0.1)

Significant

(p < 0.1)

Highly significant

(p < 0.01)

Average annual

flux, 1996-2006

(kg/yr)

Average daily

flow, 1996-2006

(m3

/s)

< 1,600

16,000

160,000

< 80

800

8,000

NA is not analyzed; > is greater than;

< is less than

IP003821_Figure 11 Figure 11. Flow-adjusted trends in metolachlor concentration for 1996–2002 and 2000–2006 analysis periods. 
40 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

Table 13. Flow-adjusted trends in metolachlor concentration and changes in metolachlor use intensity for selected sites for the 

1996–2002 and 2000–2006 trend analysis periods.

[Bold type indicates significant (p ≤ 0.10) trends or changes in use intensity]

Site map number 

and short name 

(see table 1)

1996–2002 2000–2006

Flow-adjusted trend 

(percent per year)

Change in use 

(percent per year)

Flow-adjusted trend 

(percent per year)

Change in use 

(percent per year)

 2. OHIO-CA –6.2 –13.2 0.2 –3.3

 6. WABASH –16.8 –9.8 –2.6 –3.3

 7. OHIO-GRCH –7.9 –12.1 0.2 –4.6

13. MAUM –14.4 –15.0 –0.9 –0.1

16. MSSP-CL –10.3 –12.8 1.1 –5.0

20. IOWA-WAP –15.2 –10.1 –5.7 –12.2

25. ILLI-VC –10.0 –11.7 –11.9 –2.0

26. MSSP-GR –14.6 –11.9 –8.6 –5.3

29. PLATTE –6.8 –13.0 2.9 –2.6

30. MIZZ-HE –5.0 –11.5 –1.7 –8.2

31. MSSP-TH –9.5 –11.7 -4.6 –6.2

Trends in Relation to Changes in Use Intensity

Metolachlor use decreased at all 11 use-trend sites during 

1996–2002 (table 13, fig. 12). These decreases were due to the 

reductions in use of metolachlor mandated as part of the conditional registration for acetochlor. Part of this reduction was 

possible with the introduction of a reformulation of metolachlor (S-metolachlor) that was introduced to the market in the 

late 1990s. S-metolachlor has a 30-percent lower application 

rate than previous formulations of metolachlor because of its 

greater potency.

Stream concentrations reflected the decrease in use as 

trends generally were downward and similar to changes in use 

during 1996–2002 (table 13). All but two sites had significant 

downtrends of similar magnitude in concentration and use. 

The PLATTE and MIZZ-HE also had downtrends in both 

use and concentration, but concentration downtrends were 

nonsignificant. During 2000–2006, use intensity also generally declined, but at less that half the rate at most sites, and 

the concentration trends were not significant at 9 of the 11 

use-trend sites. The only major deviation from the pattern 

was at ILLI-VC, for which there was a significant downtrend 

of 11.9 pct/yr during 2000–2006, despite a nonsignificant 

decrease in use intensity for that site. There were nonsignificant concentration trends during 2000–2006 at MSSP-CL, 

IOWA-WAP, MIZZ-HE, and MSSP-TH despite significantly 

decreasing use, although all but one of the nonsignificant 

trends were downward. A possible explanation for the 

2000–2006 results is that as use intensity decreases below a 

certain level, concentrations become lower and proportionally 

more variable (including more nondetections) and, as a result, 

do not provide clear indications of trend.
Trends in Pesticide Concentrations 41

8 20 21 12 11 10 8 7 7 7 11

13 17 14 13 13 11 7 8 8 6 11

13 14 13 13 11 13 13 12 13 10

6 14 16 14 15 11 18 17 8 6 4

12 13 14 12 12 15 15 15 14 11

11 30 13 12 12 11 9 9 9 8 11

2 15 14 12 9 16 14 14 16 12

ILLI-VC

MAUM

MSSP-CL 

PLATTE

OHIO-CA

IOWA-WAP

WABASH

METOLACHLOR CONCENTRATION, IN MICROGRAMS PER LITER

1996 1998 2000 2002 2004 2006

1996 1998 2000 2002 2004 2006

0.1

0.01

0.002

0.002

0.002

0.002

1

10

0.1

0.01

1

10

0.1

0.01

1

10

0.1

0.01

1

10

50

50

50

50

METOLACHLOR USE INTENSITY, IN KILOGRAMS PER SQUARE KILOMETER 

0.1

1

0.1

10

100

1

10

100

1

10

100

1

0.1

10

100

EXPLANATION

25th percentile

75th percentile

Median

Maximum observed concentration

Minimum observed concentration

12 Number of samples

Maximum long-term method detection level

Metolachlor use intensity

1996-2002 analysis period

2000-2006 analysis period

Figure 12. IP003821_Figure 12 Metolachlor use intensity and stream-water concentrations for selected trend sites in the Corn Belt, 1996–2006.
42 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

Alachlor

During 1996–2002, there were downtrends in alachlor 

concentrations at all 25 sites with sufficient data to compute 

trends. Of these, most (21 of 25) were highly significant, and 

most (19 of 25) were larger than 25 pct/yr (fig. 13). During 

2000–2006, significant trends were found at only five sites 

and all were downtrends (two were significant, and three were 

highly significant). At many of the sites, the median concentration was below the LT-MDL in later years, thus further reductions in alachlor concentrations in streams may not have been 

detected at many sites. 

Ohio River and Great Lakes Basins (sites 1–13)

During 1996–2002, all nine of the trends in alachlor 

concentration for sites 1–13 that could be analyzed were 

downward, all were substantial (greater than about 28 pct/yr 

in magnitude), and all were highly significant or significant. 

During 2000–2006, downtrends still prevailed, but five of 

nine trends were nonsignificant. There still were significant 

downtrends for the downstream Ohio River Basin site OHIOGRCH (site 7) as well as SUG-NP (site 4), a small tributary in 

the Wabash River Basin, and highly significant downtrends for 

two Maumee River Basin sites, AUGL and MAUM (sites 12 

and 13). 

Mississippi and Missouri River Basins 

(sites 14–31)

Downtrends in alachlor concentrations were found at all 

16 sites with sufficient data for 1996–2002, most of which 

were highly significant (13) or significant (2) (fig. 13). The 

largest trend magnitudes (greater than 40 pct/yr) were for 

small tributaries in the upper Mississippi and Iowa River 

Basins (LCOBB, IOWA-ROW, and SFIOWA; sites 14, 18, 

and 19). Downtrends at MSSP-GR (site 26) and all three main 

tributaries to that site (MSSP-CL, IOWA-WAP, and ILLI-VC; 

sites 16, 20, and 25) were somewhat smaller, ranging from 

about 25 to 35 pct/yr (fig. 13). The downtrend magnitudes for 

the Missouri River Basin sites (sites 27–30) and the downstream site MSSP-TH (site 31) tended to be smaller than 

the other trends, ranging from about 15 to 25 pct/yr. During 

2000–2006, trends at 11 of 12 sites that could be analyzed 

were nonsignificant, although there was a highly significant 

downtrend at MSSP–CL. 

Trends in Relation to Changes in Use Intensity

In 1990, alachlor was the third most heavily used herbicide in the Corn Belt. However, because of the introduction of 

acetochlor for corn and the introduction of glyphosateresistant soybeans, the use of alachlor has steadily declined 

since 1994. Alachlor use at the 11 use-trend sites decreased 

substantially during both analysis periods at all sites, with significant downtrends for all but 3 of 22 cases (table 14, fig. 14). 

During 1996–2002, trends in stream concentrations also were 

all significant downtrends and generally similar in magnitude 

to the decreases in alachlor use during that time. During 

2000–2006, downtrends at OHIO-GRCH, MAUM, and 

MSSP-CL also were similar in magnitude to decreases in alachlor use, but concentration trends for the remaining eight usetrend sites were not significant, despite substantial decreases 

in use intensity. As discussed previously for metolachlor, there 

may be a level below which further decreases in alachlor-use 

intensity do not result in a clearly discernable decrease in 

concentration. 
Trends in Pesticide Concentrations 43

 1. MAD

 2. OHIO-CA

 3. LBUCK

 4. SUG-NP

 5. WHITE

 6. WABASH

 7. OHIO-GRCH

 8. DUCK

 9. MILW

10. CLINT

11. STJOS

12. AUGL

13. MAUM

14. LCOBB

15. MSSP-HA

16. MSSP-CL

17. WAPS-TR

18. IOWA-ROW

19. SFIOWA

20. IOWA-WAP

21. SUG-MIL

22. DPLAI

23. ILLI-OTT

24. SANG

25. ILLI-VC

26. MSSP-GR

27. MIZZ-OM

28. MAPLE

29. PLATTE

30. MIZZ-HE

31. MSSP-TH

-120 0 +120 -120 0 +120

TREND, IN PERCENT PER YEAR

1996-2002 2000-2006

Alachlor

Flow-adjusted trends in concentration

Estimated value

90-percent confidence limits

Nonsignificant

(p > 0.1)

Significant

(p < 0.1)

Highly significant

(p < 0.01)

Average annual

flux, 1996-2006

(kg/yr)

Average daily

flow, 1996-2006

(m3

/s)

< 100

1,000

10,000

< 80

800

8,000

NA NA

NA NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA is not analyzed; > is greater than;

< is less than

IP003821_Figure 13 Figure 13. Flow-adjusted trends in alachlor concentration for 1996–2002 and 2000–2006 analysis periods.
44 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

Table 14. Flow-adjusted trends in alachlor concentration and changes in alachlor use intensity for selected sites for the 1996–2002 and 

2000–2006 trend analysis periods.

[Bold type indicates significant (p ≤ 0.10) trends or changes in use intensity]

Site map number 

and short name 

(see table 1)

1996–2002 2000–2006

Flow-adjusted trend 

(percent per year)

Change in use 

(percent per year)

Flow-adjusted trend 

(percent per year)

Change in use 

(percent per year)

 2. OHIO-CA –37.7 –26.9 10.2 –16.0

 6. WABASH –35.7 –26.8 –12.8 –25.2

 7. OHIO-GRCH –28.3 –26.2 –16.2 –16.5

13. MAUM –30.6 –34.9 –17 –21.1

16. MSSP-CL –27.4 –20.8 –38.9 –27.9

20. IOWA-WAP –25.1 –15.4 –15.9 –5.6

25. ILLI-VC –27.4 –16.0 –3.6 –6.9

26. MSSP-GR –33.3 –19.5 –4.3 –14.3

29. PLATTE –24.3 –17.0 2.1 –23.6

30. MIZZ-HE –15.7 –15.3 –4.6 –15.5

31. MSSP-TH –17.4 –16.8 –7.8 –15.2
Trends in Pesticide Concentrations 45

8 20 21 12 11 10 8 7 7 7 11

13

17 14 13 13 11 7 8 8 6 11

13 14 13 13 11 13 13 12 13 10

6 14 16 14 15 11 18 17 8 6 4

12 13 14 12 12 15 15 15 14 11

11 30 13 12 12 11 9 9 9 8 11

2 15 14 12 9 16 14 14 16 12

ILLI-VC

MAUM

MSSP-CL 

PLATTE

OHIO-CA

IOWA-WAP

WABASH

ALACHLOR CONCENTRATION, IN MICROGRAMS PER LITER

1996 1998 2000 2002 2004 2006

1996 1998 2000 2002 2004 2006

0.001

0.1

0.01

1

10

0.001

0.1

0.01

1

10

0.001

0.1

0.01

1

10

0.001

0.1

0.01

1

10

ALACHLOR USE INTENSITY, IN KILOGRAMS PER SQUARE KILOMETER 

1

0.1

10

30

1

0.1

10

30

1

0.1

10

30

1

0.1

10

30

EXPLANATION

25th percentile

75th percentile

Median

Maximum observed concentration

Minimum observed concentration

12 Number of samples

Maximum long-term method detection level

Alachlor use intensity

1996-2002 analysis period

2000-2006 analysis period

IP003821_Figure 14 Figure 14. Alachlor use intensity and stream-water concentrations for selected trend sites in the Corn Belt, 1996–2006.
46 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

Cyanazine

Trends in cyanazine concentrations during 1996–2002 

were the greatest magnitude of all the pesticides evaluated 

for this study. There were highly significant downtrends at 

all 25 sites with sufficient data, and most (18 of 25) were 

larger than 40 pct/yr (fig. 15). The smallest trend magnitudes 

occurred for the Great Lakes and upper Mississippi River 

Basin sites (sites 8–16), where 5 of the downtrends were less 

than 40 pct/yr. During 2000–2006 few sites had sufficient 

detections for trend testing, but large and highly significant 

downtrends occurred at eight of the ten sites with sufficient 

data, and smaller though still significant downtrends occurred 

for the remaining two sites. 

Trends in Relation to Changes in Use Intensity

Cyanazine phaseout began in the mid-1990s as a result of 

environmental concerns about frequent detections in surface 

water and ground water. In 1992, more than 9 million kg of 

cyanazine were applied on corn acreage in the Corn Belt; by 

2002 only about 4,500 kg were reported, and none was applied 

in 2005 or thereafter (proprietary pesticide use data obtained 

from DMRKynetec, St. Louis, Missouri).

Changes in cyanazine use within watersheds of the 11 

use-trend sites (table 15, fig. l6) ranged from a decrease of 

51.2 pct/yr for PLATTE during 1996–2002 to a decrease of 

77.4 pct/yr for MAUM during 1996–2002. Because cyanazine 

use was essentially zero for the latter years, changes in use 

could not be computed for the 2000–2006 time period. There 

were strong downtrends in concentration for all of the sites 

during 1996–2002, and the trend magnitudes were similar to 

the use downtrends. 
Trends in Pesticide Concentrations 47

 1. MAD

 2. OHIO-CA

 3. LBUCK

 4. SUG-NP

 5. WHITE

 6. WABASH

 7. OHIO-GRCH

 8. DUCK

 9. MILW

10. CLINT

11. STJOS

12. AUGL

13. MAUM

14. LCOBB

15. MSSP-HA

16. MSSP-CL

17. WAPS-TR

18. IOWA-ROW

19. SFIOWA

20. IOWA-WAP

21. SUG-MIL

22. DPLAI

23. ILLI-OTT

24. SANG

25. ILLI-VC

26. MSSP-GR

27. MIZZ-OM

28. MAPLE

29. PLATTE

30. MIZZ-HE

31. MSSP-TH

-120 0 +120 -120 0 +120

TREND, IN PERCENT PER YEAR

1996-2002 2000-2006

Cyanazine

Flow-adjusted trends in concentration

Estimated value

90-percent confidence limits

Nonsignificant

(p > 0.1)

Significant

(p < 0.1)

Highly significant

(p < 0.01)

Average annual

flux, 1996-2006

(kg/yr)

Average daily

flow, 1996-2006

(m3

/s)

< 400

4,000

40,000

< 80

800

8,000

NA NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA is not analyzed; > is greater than;

< is less than

IP003821_Figure 15 Figure 15. Flow-adjusted trends in cyanazine concentration for 1996–2002 and 2000–2006 analysis periods.
48 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

Table 15. Flow-adjusted trends in cyanazine concentration and changes in cyanazine use intensity for selected sites for the 1996–2002 

and 2000–2006 trend analysis periods.

[Bold type indicates significant (p ≤ 0.10) trends or changes in use intensity; na, not analyzed]

Site map number and 

short name 

(see table 1)

1996–2002 2000–2006

Flow-adjusted trend 

(percent per year)

Change in use 

(percent per year)

Flow-adjusted trend 

(percent per year)

Change in use 

(percent per year)

 2. OHIO-CA –49.7 –62.8 na na

 6. WABASH –63.1 –68.4 –57.0 na

 7. OHIO-GRCH –53.0 –65.7 na na

13. MAUM –44.3 –77.4 –45.4 na

16. MSSP-CL –38.0 –52.2 na na

20. IOWA-WAP –42.5 –71.6 na na

25. ILLI-VC –56.8 –67.6 na na

26. MSSP-GR –62.8 –62.7 na na

29. PLATTE –52.9 –51.2 –31.6 na

30. MIZZ-HE –50.5 –51.8 –65.7 na

31. MSSP-TH –50.0 –57.8 na na
Trends in Pesticide Concentrations 49

Figure 16. Cyanazine use intensity and stream-water concentrations for selected trend sites in the Corn Belt, 1996–2006.

8 20 21 12 11 10 8 7 5 5 11

13 17 14 13 13 11 7 8 8 6 11

13 14 13 13 11 13 13 12 13 10

6 14 16 14 15 11 18 17 6 4 4

12 13 14 12 12 15 15 15 14 11

11 30 13 12 12 11 9 9 7 6 11

2 15 14 12 9 16 14 14 16 12

ILLI-VC

MAUM

MSSP-CL 

PLATTE

OHIO-CA

IOWA-WAP

WABASH

CYANAZINE CONCENTRATION, IN MICROGRAMS PER LITER

1996 1998 2000 2002 2004 2006

1996 1998 2000 2002 2004 2006

0.002

0.1

0.01

1

20

10

0.002

0.1

0.01

1

20

10

0.002

0.1

0.01

1

20

10

0.002

0.1

0.01

1

20

10

CYANAZINE USE INTENSITY, IN KILOGRAMS PER SQUARE KILOMETER 

1

0.01

0.1

10

30

1

0.01

0.1

10

30

1

0.01

0.1

10

30

1

0.01

0.1

10

30

EXPLANATION

25th percentile

75th percentile

Median

Maximum observed concentration

Minimum observed concentration

12 Number of samples

Maximum long-term method detection level

Cyanazine use intensity

1996-2002 analysis period

2000-2006 analysis period

IP003821_Figure 16
50 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

EPTC

Most of the sites had too few concentrations above detection limits to analyze trends in EPTC (table 3). Of ten sites 

that could be analyzed during the 1996–2002 period, eight 

had downtrends in EPTC concentrations, including significant 

downtrends at ILLI-VC, MIZZ-OM, and PLATTE (sites 25, 

27, and 29) and a highly significant downtrend at MSSP-CL 

(site 16) (fig. 17). During 2000–2006, of two sites that could 

be analyzed, there was a highly significant downtrend at 

MIZZ-OM (site 27). There were no significant uptrends for 

any of the sites during either analysis period. 

Trends in Relation to Changes in Use Intensity

Use of EPTC for weed control on corn fields declined 

over the study period as it was replaced by newer herbicides. 

In 1992, over 4.5 million kg of EPTC were applied in the Corn 

Belt, but this declined steadily to under 400,000 kg by 2005. 

Although use intensity for the use-trend sites generally 

declined (fig. 18), there were only five sites for which comparisons could be made between trends in EPTC concentration and use intensity, all for the 1996–2002 analysis period 

(table 16). For all five sites, the downtrends in EPTC concentration were similar in magnitude to the decreases in use 

intensity, although not all were individually significant. 
Trends in Pesticide Concentrations 51

Figure 17. Flow-adjusted trends in EPTC concentration for 1996–2002 and 2000–2006 analysis periods.

 1. MAD

 2. OHIO-CA

 3. LBUCK

 4. SUG-NP

 5. WHITE

 6. WABASH

 7. OHIO-GRCH

 8. DUCK

 9. MILW

10. CLINT

11. STJOS

12. AUGL

13. MAUM

14. LCOBB

15. MSSP-HA

16. MSSP-CL

17. WAPS-TR

18. IOWA-ROW

19. SFIOWA

20. IOWA-WAP

21. SUG-MIL

22. DPLAI

23. ILLI-OTT

24. SANG

25. ILLI-VC

26. MSSP-GR

27. MIZZ-OM

28. MAPLE

29. PLATTE

30. MIZZ-HE

31. MSSP-TH

-60 0 +60 -60 0 +60

TREND, IN PERCENT PER YEAR

1996-2002 2000-2006

EPTC

Flow-adjusted trends in concentration

Estimated value

90-percent confidence limits

Nonsignificant

(p > 0.1)

Significant

(p < 0.1)

Highly significant

(p < 0.01)

Average annual

flux, 1996-2006

(kg/yr)

Average daily

flow, 1996-2006

(m3

/s)

< 10

100

1,000

< 80

800

8,000

NA NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA is not analyzed; > is greater than;

< is less than

IP003821_Figure 17
52 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

8 20 21 12 11 10 8 7 5 5 11

13 17 14 13 13 11 7 8 8 6 11

13 14 13 13 11 13 13 12 13 10

6 14 16 14 15 11 18 17 6 4 4

12 13 14 12 12 15 15 15 14 11

11 30 13 12 12 11 9 9 7 6 11

2 15 14 12 9 16 14 14 16 12

ILLI-VC

MAUM

MSSP-CL 

PLATTE

OHIO-CA

IOWA-WAP

WABASH

EPTC CONCENTRATION, IN MICROGRAMS PER LITER

1996 1998 2000 2002 2004 2006

1996 1998 2000 2002 2004 2006

0.001

0.1

0.2

0.01

EPTC USE INTENSITY, IN KILOGRAMS PER SQUARE KILOMETER 

1

0.1

10

100

1

0.1

10

100

1

0.1

10

100

1

0.1

10

100

0.001

0.1

0.2

0.01

0.001

0.1

0.2

0.01

0.001

0.1

0.2

0.01

EXPLANATION

25th percentile

75th percentile

Median

Maximum observed concentration

Minimum observed concentration

12 Number of samples

Maximum long-term method detection level

EPTC use intensity

1996-2002 analysis period

2000-2006 analysis period

Figure 18. IP003821_Figure 18 EPTC use intensity and stream-water concentrations for selected trend sites in the Corn Belt, 1996–2006.
Trends in Pesticide Concentrations 53

Table 16. Flow-adjusted trends in EPTC concentration and changes in EPTC use intensity for selected sites for the 1996–2002 and 

2000–2006 trend analysis periods.

[Bold type indicates significant (p ≤ 0.10) trends or changes in use intensity; na, not analyzed]

Site map number 

and short name 

(see table 1)

1996–2002 2000–2006

Flow-adjusted trend 

(percent per year)

Change in use 

(percent per year)

Flow-adjusted trend 

(percent per year)

Change in use 

(percent per year)

16. MSSP-CL –19.2 –14.3 na –42.5

20. IOWA-WAP –13.5 –20.8 na –57.5

25. ILLI-VC –28.3 –26.0 na –38.4

29. PLATTE –23.9 –23.6 na –13.4

30. MIZZ-HE –18.3 –22.9 na –22.9
54 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

Simazine

Of the 28 sites analyzed, 21 had uptrends in simazine 

concentrations during 1996–2002, including 7 sites that had 

highly significant uptrends and 7 sites that had significant 

uptrends (fig. 19). There were 7 sites with downtrends during 1996–2002, four of which were significant or highly 

significant, but almost all were for sites with small basins that 

represent local conditions. Most (21 out of 27) of the trends 

for 2000–2006 also were uptrends, but the trends were smaller 

and less significant than the uptrends during the earlier time 

period. There only were five significant uptrends during the 

latter period. All 6 downtrends during 2000–2006 were relatively small (less than 12 pct/yr) and only one downtrend was 

significant.

Ohio River and Great Lakes Basins (sites 1–13) 

During 1996–2002, a highly significant uptrend in 

simazine concentration of about 12 pct/yr occurred for the 

downstream Ohio River Basin site OHIO-GRCH (site 7) 

(fig. 19). This was consistent with uptrends at two tributaries 

to OHIO-GRCH during that time: a highly significant uptrend 

of about 27 pct/yr at WABASH (site 6) and a smaller, but significant, uptrend of 8.5 pct/yr at OHIO-CA (site 2). There also 

were significant uptrends at MAUM (site 13) and a tributary 

to MAUM, STJOS (site 11) during 1996–2002. There were 

highly significant downtrends only for two small tributary 

sites: LBUCK (site 3) in the Wabash River Basin, and DUCK 

(site 8) in the Great Lakes Basins. During 2000–2006, 11 of 13 

trends were nonsignificant. 

Mississippi and Missouri River Basins 

(sites 14–31)

Uptrends in simazine concentrations were found at 11 

of 15 sites with sufficient data during 1996–2002, including 

highly significant uptrends at MSSP-GR (site 26) and a major 

tributary to MSSP-GR, ILLI-VC (site 25), as well as significant uptrends for four tributaries to ILLI-VC. However, other 

major tributaries to MSSP-GR—MSSP-CL and IOWA-WAP 

(sites 16 and 20)—had small and nonsignificant trends. The 

trend magnitude for MSSP-GR (about 37 pct/yr) was larger 

than the magnitude at ILLI-VC (about 19 pct/yr), despite the 

lack of uptrend at IOWA-WAP and a very small, nonsignificant uptrend for MSSP-CL. This may indicate that simazine 

sources from other tributaries contributed to the uptrend at 

MSSP-GR, or that the Illinois River is the major influence and 

the differences in trend magnitude primarily reflect uncertainty 

in trend estimates.

The highly significant uptrend for MSSP-TH (site 31) 

is consistent with the large uptrend for MSSP-GR, combined 

with a smaller uptrend at MIZZ-HE (site 30). Upstream of 

MIZZ-HE, there was no significant trend for MIZZ-OM 

(site 27), which contributes proportionally more streamflow 

than simazine flux, and the PLATTE (site 29) had a significant 

downtrend. The uptrend for MIZZ-HE may have been caused, 

at least in part, by sources downstream of the major tributaries 

to that site.

During 2000–2006, MSSP-GR and MIZZ-HE, as well as 

the Mississippi River site downstream of these sites (MSSPTH), continued to have significant uptrends despite relatively 

weak and variable trends in upstream tributaries. 

Trends in Relation to Changes in Use Intensity

Simazine is a commonly used herbicide that has lower 

total use and higher proportions of nonagricultural use when 

compared to the previously discussed herbicides (Gilliom and 

others, 2006). Simazine is used on a wider variety of crops 

relative to atrazine, acetochlor, alachlor, and metolachlor. 

During 1996–2002, significant uptrends occurred in both 

concentration and use for 5 of the 11 use-trend sites, three 

sites had significant concentration uptrends with nonsignifcant 

use trends, and two sites had nonsignificant trends for both 

concentration and use (table 17, fig. 20). During 2000–2006, 

6 of the 11 sites had nonsignificant trends for both concentration and use. Four sites (IOWA-WAP, MSSP-GR, MIZZ-HE, 

and MSSP-TH) had significant concentration uptrends, despite 

nonsignificant decreases in use during that time. Concentration 

uptrends at these four sites may reflect increasing nonagricultural use of simazine in these basins. 
Trends in Pesticide Concentrations 55

 1. MAD

 2. OHIO-CA

 3. LBUCK

 4. SUG-NP

 5. WHITE

 6. WABASH

 7. OHIO-GRCH

 8. DUCK

 9. MILW

10. CLINT

11. STJOS

12. AUGL

13. MAUM

14. LCOBB

15. MSSP-HA

16. MSSP-CL

17. WAPS-TR

18. IOWA-ROW

19. SFIOWA

20. IOWA-WAP

21. SUG-MIL

22. DPLAI

23. ILLI-OTT

24. SANG

25. ILLI-VC

26. MSSP-GR

27. MIZZ-OM

28. MAPLE

29. PLATTE

30. MIZZ-HE

31. MSSP-TH

-60 0 +60 -60 0 +60

TREND, IN PERCENT PER YEAR

1996-2002 2000-2006

Simazine

Flow-adjusted trends in concentration

Estimated value

90-percent confidence limits

Nonsignificant

(p > 0.1)

Significant

(p < 0.1)

Highly significant

(p < 0.01)

Average annual

flux, 1996-2006

(kg/yr)

Average daily

flow, 1996-2006

(m3

/s)

< 800

8,000

80,000

< 80

800

8,000

NA

NA

NA

NA

NA NA

NA

NA

NA

NA

NA

NA is not analyzed; > is greater than;

< is less than

IP003821_Figure 19 Figure 19. Flow-adjusted trends in simazine concentration for 1996–2002 and 2000–2006 analysis periods.
56 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

Figure 20. Simazine use intensity and stream-water concentrations for selected trend sites in the Corn Belt, 1996-2006.

8 20 21 12 11 10 8 7 7 7 11

13 17 14 13 13 11 7 8 8 6 11

13 14 13 13 11 13 13 12 13 10

6 14 16 14 15 11 18 17 8 6 4

12 13 14 12 12 15 15 15 14 11

11 30 13 12 12 11 9 9 9 8 11

2 15 14 12 9 16 14 14 16 12

ILLI-VC

MAUM

MSSP-CL 

PLATTE

OHIO-CA

IOWA-WAP

WABASH

SIMAZINE CONCENTRATION, IN MICROGRAMS PER LITER

1996 1998 2000 2002 2004 2006

1996 1998 2000 2002 2004 2006

0.002

0.1

0.01

1

10

0.001

0.1

0.01

1

10

0.001

0.1

0.01

1

10

0.001

0.1

0.01

1

10

0.001

0.1

0.01

1

10

0.002

0.1

0.01

1

10

0.002

0.1

0.01

1

10

0.002

0.1

0.01

1

10

SIMAZINE USE INTENSITY, IN KILOGRAMS PER SQUARE KILOMETER 

EXPLANATION

25th percentile

75th percentile

Median

Maximum observed concentration

Minimum observed concentration

12 Number of samples

Maximum long-term method detection level

Simazine use intensity

1996-2002 analysis period

2000-2006 analysis period

IP003821_Figure 20
Trends in Pesticide Concentrations 57

Table 17. Flow-adjusted trends in simazine concentration and changes in simazine use intensity for selected sites for the 1996–2002 

and 2000–2006 trend analysis periods.

[Bold type indicates significant (p ≤ 0.10) trends or changes in use intensity; na, not analyzed]

Site map number 

and short name

(see table 1)

1996–2002 2000–2006

Flow-adjusted trend 

(percent per year)

Change in use 

(percent per year)

Flow-adjusted trend 

(percent per year)

Change in use 

(percent per year)

 2. OHIO-CA 8.5 0.1 1.7 –3.4

 6. WABASH 27.1 29.1 1.4 0.0

 7. OHIO-GRCH 12.4 11.7 –0.5 –2.4

13. MAUM 12.5 26.2 0.7 2.3

16. MSSP-CL 1.4 –24.2 0.5 –15.0

20. IOWA-WAP –6.3 –12.7 9.4 –30.2

25. ILLI-VC 19.1 20.3 5.6 3.7

26. MSSP-GR 36.9 –1.8 11.5 –9.7

29. PLATTE –10.7 na –9.7 na

30. MIZZ-HE 9.4 12.5 20.4 –0.1

31. MSSP-TH 13.4 4.7 11.3 –4.8

Metribuzin

Analysis of metribuzin concentration trends was limited during both analysis periods due to the large number of 

censored values (table 3). During 1996–2002, 14 sites had 

sufficient data, and all 14 sites had downtrends in concentrations (fig. 21). Downtrends were significant at four sites and 

highly significant at eight sites, including SUG-NP, WABASH, 

OHIO-GRCH, STJOS, AUGL, MAUM, ILLI-VC, and MSSPTH (sites 4, 6, 7, 11, 12, 13, 25, and 31). Only eight sites could 

be analyzed during 2000–2006 and all but WABASH (site 6) 

had nonsignificant trends (fig. 21). There were no significant 

uptrends for any of the sites during either analysis period. 

Trends in Relation to Changes in Use Intensity

In the corn and soybean areas of the Midwest, metribuzin 

use was more common on soybeans than corn in the early part 

of the study period; in Wisconsin and Michigan metribuzin 

also is used on a variety of vegetable crops. Over 700,000 

kg of metribuzin was applied in 1992 (fig. 2); by 2006, use 

had decreased to just over 100,000 kg. The decrease in use 

primarily was because glyphosate became the herbicide of 

choice for soybeans. Low-level use on corn continued at similar levels throughout the study. 

Use intensity for the use-trend sites generally was 

decreasing during both analysis periods (fig. 22). During 

1996–2002, 7 of the 8 use-trend sites with adequate data for 

trend analysis had similar and significant downtrends in both 

concentration and use (table 18). The PLATTE also had a 

significant decline in concentration and the use trend was 

downward but not significant. During 2000–2006, only three 

sites had adequate data for evaluating concentration trends, 

all with significant or nonsignificant downtrends in both 

concentration and use. In all cases, downtrends in metribuzin 

concentration were similar in magnitude to decreases in use 

intensity—changes in use intensity for the 11 cases ranged 

from decreases of 9.3 to 21.6 pct/yr and the downtrends 

ranged from 2.6 to 25.1 pct/yr.
58 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

Figure 21. Flow-adjusted trends in metribuzin concentration for 1996–2002 and 2000–2006 analysis periods.

 1. MAD

 2. OHIO-CA

 3. LBUCK

 4. SUG-NP

 5. WHITE

 6. WABASH

 7. OHIO-GRCH

 8. DUCK

 9. MILW

10. CLINT

11. STJOS

12. AUGL

13. MAUM

14. LCOBB

15. MSSP-HA

16. MSSP-CL

17. WAPS-TR

18. IOWA-ROW

19. SFIOWA

20. IOWA-WAP

21. SUG-MIL

22. DPLAI

23. ILLI-OTT

24. SANG

25. ILLI-VC

26. MSSP-GR

27. MIZZ-OM

28. MAPLE

29. PLATTE

30. MIZZ-HE

31. MSSP-TH

-60 0 +60 -60 0 +60

TREND, IN PERCENT PER YEAR

1996-2002 2000-2006

Metribuzin

Flow-adjusted trends in concentration

Estimated value

90-percent confidence limits

Nonsignificant

(p > 0.1)

Significant

(p < 0.1)

Highly significant

(p < 0.01)

Average annual

flux, 1996-2006

(kg/yr)

Average daily

flow, 1996-2006

(m3

/s)

< 100

1,000

10,000

< 80

800

8,000

NA NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA is not analyzed; > is greater than;

< is less than

IP003821_Figure 21
Trends in Pesticide Concentrations 59

8 20 21 12 11 10 8 7 7 7 11

13 17

14 13 13 11 7 8 8 6 11

13 14 13 13 11 13 13 12 13 10

6 14 16 14 15 11 18 17 8 6 4

12 13 14 12 12 15 15 15 14 11

11 30 13 12 12 11 9 9 9 8 11

2 15 14 12 9 16 14 14 16 12

ILLI-VC

MAUM

MSSP-CL 

PLATTE

OHIO-CA

IOWA-WAP

WABASH

METRIBUZIN CONCENTRATION, IN MICROGRAMS PER LITER

1996 1998 2000 2002 2004 2006

1996 1998 2000 2002 2004 2006

0.002

0.1

0.01

1

20

10

0.002

0.1

0.01

1

20

10

0.002

0.1

0.01

1

20

10

0.002

0.1

0.01

1

20

10

METRIBUZIN USE INTENSITY, IN KILOGRAMS PER SQUARE KILOMETER 

1

0.01

0.1

5

1

0.01

0.1

5

1

0.01

0.1

5

1

0.01

0.1

5

EXPLANATION

25th percentile

75th percentile

Median

Maximum observed concentration

Minimum observed concentration

12 Number of samples

Maximum long-term method detection level

Metribuzin use intensity

1996-2002 analysis period

2000-2006 analysis period

Figure 22. IP003821_Figure 22 Metribuzin use intensity and stream-water concentrations for selected trend sites in the Corn Belt, 1996-2006.
60 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

Table 18. Flow-adjusted trends in metribuzin concentration and changes in metribuzin use intensity for selected sites for the 1996–

2002 and 2000–2006 trend analysis periods.

[Bold type indicates significant (p ≤ 0.10) trends or changes in use intensity; na, not analyzed]

Site map number 

and short name

(see table 1)

1996–2002 2000–2006

Flow-adjusted trend 

(percent per year)

Change in use 

(percent per year)

Flow-adjusted trend 

(percent per year)

Change in use 

(percent per year)

 2. OHIO-CA –19.5 –20.0 na –9.5

 6. WABASH –18.4 –19.5 –23.3 –16.3

 7. OHIO-GRCH –18.3 –19.9 na –12.3

13. MAUM –17.5 –21.6 –2.6 –9.3

25. ILLI-VC –23.0 –16.5 na –19.1

29. PLATTE –25.1 –9.5 na –14.4

30. MIZZ-HE –10.5 –14.7 –13.7 –14.2

31. MSSP-TH –14.4 –12.5 na –15.9

Prometon

All significant trends in prometon concentration during 

1996–2002 were downward (fig. 23). Of the 29 sites analyzed, 

27 had downtrends, including 10 sites that were highly significant and 4 sites that had significant downtrends. In contrast, 

during 2000–2006 uptrends outnumbered downtrends almost 

2 to 1 (18 uptrends, 10 downtrends), but most (22 of 28) were 

not significant. The six significant or highly significant trends 

included uptrends (4) and downtrends (2). Because prometon 

is a nonselective herbicide used primarily for nonagricultural 

purposes (but in both urban and agricultural areas), accurate 

use data are not available and it is unknown whether downtrends in stream concentrations are the result of decreased use 

or some other factor(s). 

Ohio River and Great Lakes Basins (sites 1–13) 

During 1996–2002, there was a small (about 4 pct/yr) 

but significant downtrend at OHIO-GRCH (site 7), which 

is consistent with all of the upstream sites (with sufficient 

data for analysis) also having downtrends, including a highly 

significant downtrend at LBUCK (site 3), which is a small and 

rapidly urbanizing basin. There also were highly significant 

downtrends at Great Lakes tributary sites MILW and STJOS 

(sites 9 and 11). During 2000–2006, only two significant 

trends were found; a highly significant downtrend at MILW 

and a significant uptrend at SUG-NP.

Mississippi and Missouri River Basins 

(sites 14–31)

During 1996–2002, there was a highly significant 

downtrend in prometon concentrations at MSSP-GR (site 26) 

and significant or highly significant downtrends at its major 

upstream tributaries, ILLI-VC (site 25) and IOWA-WAP 

(site 20). Significant or highly significant downtrends also 

were found at several smaller sites in the Illinois and Iowa 

River Basins (IOWA-ROW, SFIOWA, DPLAI, ILLI-OTT, and 

SANG; sites 18, 19, 22, 23, and 24). There were no significant trends for the Missouri River Basin sites (sites 27–30), 

but a highly significant downtrend at MSSP-TH (site 31) was 

consistent with the downtrend at the upstream site, MSSPGR. During 2000–2006, however, there was a highly significant uptrend in prometon concentrations at MSSP-GR, and 

a significant uptrend downstream at MSSP-TH. As during 

1996–2002, there were no significant trends at any of the four 

sites in the Missouri River Basin during 2000–2006. 
Trends in Pesticide Concentrations 61

Figure 23. Flow-adjusted trends in prometon concentration for 1996–2002 and 2000–2006 analysis periods.

 1. MAD

 2. OHIO-CA

 3. LBUCK

 4. SUG-NP

 5. WHITE

 6. WABASH

 7. OHIO-GRCH

 8. DUCK

 9. MILW

10. CLINT

11. STJOS

12. AUGL

13. MAUM

14. LCOBB

15. MSSP-HA

16. MSSP-CL

17. WAPS-TR

18. IOWA-ROW

19. SFIOWA

20. IOWA-WAP

21. SUG-MIL

22. DPLAI

23. ILLI-OTT

24. SANG

25. ILLI-VC

26. MSSP-GR

27. MIZZ-OM

28. MAPLE

29. PLATTE

30. MIZZ-HE

31. MSSP-TH

-60 0 +60 -60 0 +60

TREND, IN PERCENT PER YEAR

1996-2002 2000-2006

Prometon

Flow-adjusted trends in concentration

Estimated value

90-percent confidence limits

Nonsignificant

(p > 0.1)

Significant

(p < 0.1)

Highly significant

(p < 0.01)

Average annual

flux, 1996-2006

(kg/yr)

Average daily

flow, 1996-2006

(m3

/s)

<50

500

5,000

< 80

800

8,000

NA NA NA

NA NA

NA

NA

NA

NA

NA is not analyzed; > is greater than;

< is less than

IP003821_Figure 23
62 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

Chlorpyrifos

Most sites had too few concentrations above detection 

limits to analyze for trends in chlorpyrifos (table 3). At the 

11 sites for which flow-adjusted trends could be analyzed during 1996–2002, all had downtrends in chlorpyrifos concentrations, including significant downtrends at 2 sites and highly 

significant downtrends at 5 sites (fig. 24). Only three sites 

could be analyzed during 2000–2006, and there was a highly 

significant downtrend at WABASH (site 6) and a highly 

significant uptrend at MAPLE (site 28), a small agricultural 

stream. As indicated in table 3, MAPLE was one of few sites 

for which the percentage of uncensored chlorpyrifos concentrations was higher during 2000–2006 (25 percent) than during 

1996–2002 (15 percent). 

Trends in Relation to Changes in Use Intensity

Slightly more than half of all chlorpyrifos used for insect 

control in agriculture is on corn acreage (U.S. Environmental Protection Agency, 2002). Most residential uses were 

cancelled as of 2001. Agricultural use data (fig. 25) suggest 

that chlorpyrifos use may be declining somewhat, although 

patterns were not uniform at all sites.

Chlorpyrifos use for the use-trend sites generally was 

stable or decreasing during both trend analysis periods 

(fig. 25). There were only four sites and six cases for which 

comparisons could be made between trends in chlorpyrifos 

concentration and changes in use intensity (table 19). During 

1996–2002, three of four sites had significant and substantial 

downtrends in concentrations, despite nonsignificant trends in 

use (OHIO-CA, OHIO-GRCH, and MAUM). Possible explanations for the steeper downtrends in concentrations compared 

to agricultural use include improved erosion control practices, 

which could have a particularly great effect on chlorpyrifos because of its hydrophobic nature, and the possibility 

that major reductions in nonagricultural use of chlorpyrifos 

accounted for most of the concentration reduction (this would 

not be apparent in the agricultural use trends). During 2000–

2006, agricultural use trends were all downward, with three of 

the four sites significant. Three of the four sites had unassessable or nonsignificant concentration trends, while WABASH 

had a strong significant downtrend of –30.5 pct/yr.
Trends in Pesticide Concentrations 63

 1. MAD

 2. OHIO-CA

 3. LBUCK

 4. SUG-NP

 5. WHITE

 6. WABASH

 7. OHIO-GRCH

 8. DUCK

 9. MILW

10. CLINT

11. STJOS

12. AUGL

13. MAUM

14. LCOBB

15. MSSP-HA

16. MSSP-CL

17. WAPS-TR

18. IOWA-ROW

19. SFIOWA

20. IOWA-WAP

21. SUG-MIL

22. DPLAI

23. ILLI-OTT

24. SANG

25. ILLI-VC

26. MSSP-GR

27. MIZZ-OM

28. MAPLE

29. PLATTE

30. MIZZ-HE

31. MSSP-TH

-120 0 +120 -120 0 +120

TREND, IN PERCENT PER YEAR

1996-2002 2000-2006

Chlorpyrifos

Flow-adjusted trends in concentration

Estimated value

90-percent confidence limits

Nonsignificant

(p > 0.1)

Significant

(p < 0.1)

Highly significant

(p < 0.01)

Average annual

flux, 1996-2006

(kg/yr)

Average daily

flow, 1996-2006

(m3

/s)

<5

50

500

< 80

800

8,000

NA

NA

NA is not analyzed; > is greater than;

< is less than

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

IP003821_Figure 24

Figure 24. Flow-adjusted trends in chlorpyrifos concentration for 1996–2002 and 2000–2006 analysis periods.
64 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

8 20 21 12 11 10 8 7 7 7 11

13 17 14 13 13 11 7 8 8 6 11

13 14 13 13 11 13 13 12 13 10

6 14 16 14 15 11 18 17 8 6 4

12 13 14 12 12 15 15 15 14 11

11 30 13 12 12 11 9 9 9 8 11

2 15 13 12 9 16 14 14 16 12

ILLI-VC

MAUM

MSSP-CL 

PLATTE

OHIO-CA

IOWA-WAP

WABASH

CHLORPYRIFOS CONCENTRATION, IN MICROGRAMS PER LITER

1996 1998 2000 2002 2004 2006

1996 1998 2000 2002 2004 2006

0.01

0.001

0.1

1

CHLORPYRIFOS USE INTENSITY, IN KILOGRAMS PER SQUARE KILOMETER 

1

0.01

0.1

10

0.01

0.001

0.1

1

0.01

0.001

0.1

1

0.01

0.001

0.1

1

1

0.01

0.1

10

1

0.01

0.1

10

1

0.01

0.1

10

EXPLANATION

25th percentile

75th percentile

Median

Maximum observed concentration

Minimum observed concentration

12 Number of samples

Maximum long-term method detection level

Chlorpyrifos use intensity

1996-2002 analysis period

2000-2006 analysis period

Figure 25. IP003821_Figure 25 Chlorpyrifos use intensity and stream-water concentrations for selected trend sites in the Corn Belt, 1996–2006.
Trends in Pesticide Concentrations 65

Site map number and 

short name

(see table 1)

1996–2002 2000–2006

Flow-adjusted trend 

(percent per year)

Change in use 

(percent per year)

Flow-adjusted trend 

(percent per year)

Change in use 

(percent per year)

 2. OHIO-CA –30.9 2.3 na –7.0

 6. WABASH –10.6 –1.5 –30.5 –22.1

 7. OHIO-GRCH –22.9 –1.6 na –15.2

13. MAUM –32.9 –1.5 9.4 –17.3

Table 19. Flow-adjusted trends in chlorpyrifos concentration and changes in chlorpyrifos use intensity for selected sites for the 

1996–2002 and 2000–2006 trend analysis periods.

[Bold type indicates significant (p ≤ 0.10) trends or changes in use intensity; na, not analyzed]

Diazinon

Flow-adjusted trends in diazinon concentration were 

mixed for 1996–2002 and broadly downward for 2000–2006 

(fig. 26). Of 18 trends that could be analyzed for 1996–2002, 

13 sites had nonsignificant trends, two sites had significant 

downtrends and 3 sites had significant uptrends, including 

highly significant uptrends for WABASH (site 6) and MILW 

(site 9). During 2000–2006, all 18 sites that could be analyzed 

had downtrends and 11 of the downtrends were highly significant. The downtrends were particularly strong for the Wabash 

River Basin (sites 3–6) and the Illinois River Basin (sites 22, 

23, and 25). There also were large (greater than 30 pct/yr) 

and highly significant downtrends for the large Mississippi 

River and Missouri River mainstem sites, MSSP-GR (site 26), 

MIZZ-HE (site 30), and MSSP-TH (site 31). Small and 

nonsignificant downtrends for the two Ohio River mainstem 

sites (OHIO-CA and OHIO-GRCH; sites 2 and 7) were found 

during 2000–2006.

Trends in Relation to Changes in Use Intensity

A federally mandated phase out of non-agricultural uses 

of diazinon by 2004 (U.S. Environmental Protection Agency, 

2008) resulted in significant decreases in urban streams and 

rivers in the northeastern and midwestern U.S. (Phillips and 

others, 2007). However, agricultural uses of diazinon continue 

(fig. 2) and the result is a mix of responses at sites in the Corn 

Belt.

Diazinon use intensities for the use-trend sites were 

much more variable from year to year than were use intensities for any of the previous pesticides (fig. 27). This variation 

in use partly reflects the fact that insecticides are applied on 

an as-needed basis and not as routinely as herbicides and, 

thus, application can be much higher during years of insect 

infestations and lower during years when few insect pests are 

observed. In addition, the effect of urban use of diazinon, not 

reflected in the agricultural use intensity shown in figure 27, 

likely masks relations between agricultural use and stream 

concentrations (table 20).

During 1996–2002, 3 of 10 use-trend sites with adequate 

data had significant downtrends in agricultural use in the range 

of 46 to 65 percent per year. Each of these sites, plus three others with substantial but nonsignificant downtrends (MAUM, 

IOWA-WAP, and MSSP-GR), had nonsignificant, mostly 

small downtrends in concentrations (table 20). ILL-VC had a 

significant downtrend in concentration and a large, but nonsignificant, downtrend in agricultulral use. During 2000–2006, 

there were substantial, but mostly nonsigificant, uptrends in 

use at most sites, which were accompanied by mostly significant downtrends in concentrations.

This apparent “disconnect” between concentration and 

use trends may result from the large proportional contribution 

of urban uses compared to agricultural uses prior to the 2004 

phase out, such that agricultural use downtrends were offset 

or diminished by urban uses during 1996–2002. During 2000–

2006, when the phase out of urban uses occurred, concentration trends generally were downward even though estimated 

agricultural use may have increased for several sites. Most 

sites with the largest decreasing trends during 2000–2006 also 

are those with the greatest urban influence. Results indicate 

that the diazinon phase-out for nonagricultural uses was 

effective in reducing river concentrations.
66 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

 1. MAD

 2. OHIO-CA

 3. LBUCK

 4. SUG-NP

 5. WHITE

 6. WABASH

 7. OHIO-GRCH

 8. DUCK

 9. MILW

10. CLINT

11. STJOS

12. AUGL

13. MAUM

14. LCOBB

15. MSSP-HA

16. MSSP-CL

17. WAPS-TR

18. IOWA-ROW

19. SFIOWA

20. IOWA-WAP

21. SUG-MIL

22. DPLAI

23. ILLI-OTT

24. SANG

25. ILLI-VC

26. MSSP-GR

27. MIZZ-OM

28. MAPLE

29. PLATTE

30. MIZZ-HE

31. MSSP-TH

-60 0 +60 -60 0 +60

TREND, IN PERCENT PER YEAR

1996-2002 2000-2006

Diazinon

Flow-adjusted trends in concentration

Estimated value

90-percent confidence limits

Nonsignificant

(p > 0.1)

Significant

(p < 0.1)

Highly significant

(p < 0.01)

Average annual

flux, 1996-2006

(kg/yr)

Average daily

flow, 1996-2006

(m3

/s)

< 20

200

2,000

< 80

800

8,000

NA NA NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA

NA NA NA

NA

NA

NA NA NA

NA NA

NA NA NA

NA NA NA

NA

NA

NA NA

NA

NA NA NA

NA

NA

NA

NA

NA is not analyzed; > is greater than;

< is less than

IP003821_Figure 26 Figure 26. Flow-adjusted trends in diazinon concentration for 1996–2002 and 2000–2006 analysis periods.
Trends in Pesticide Concentrations 67

8 20 21 12 11 10 8 7 7 7 11

13 17 14 13 13 11 7 8 8 6 11

13 14 13 13 11 13 13 12 13 10

6 14 16 14 15 11 18 17 8 6 4

12 13 14 12 12 15 15 15 14 11

11 30 13 12 12 11 9 9 9 8 11

2 15 14 12 9 16 14 14 16 12

ILLI-VC

MAUM

MSSP-CL 

PLATTE

OHIO-CA

IOWA-WAP

WABASH

DIAZINON CONCENTRATION, IN MICROGRAMS PER LITER

1996 1998 2000 2002 2004 2006

1996 1998 2000 2002 2004 2006

0.01

0.001

0.1

DIAZINON USE INTENSITY, IN KILOGRAMS PER SQUARE KILOMETER 

0.001

0.1

0.2

0.01

0.01

0.001

0.1

0.01

0.001

0.1

0.01

0.001

0.1

0.001

0.1

0.2

0.01

0.001

0.1

0.2

0.01

0.001

0.1

0.2

0.01

EXPLANATION

25th percentile

75th percentile

Median

Maximum observed concentration

Minimum observed concentration

12 Number of samples

Maximum long-term method detection level

Diazinon use intensity

1996-2002 analysis period

2000-2006 analysis period

Figure 27. IP003821_Figure 27 Diazinon use intensity and stream-water concentrations for selected trend sites in the Corn Belt, 1996–2006.
68 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

Table 20. Flow-adjusted trends in diazinon concentration and changes in diazinon use intensity for selected sites for the 1996–2002 

and 2000–2006 trend analysis periods.

[Bold type indicates significant (p ≤ 0.10) trends or changes in use intensity; na, not analyzed]

Site map number 

and short name

(see table 1)

1996–2002 2000–2006

Flow-adjusted trend 

(percent per year)

Change in use 

(percent per year)

Flow-adjusted trend 

(percent per year)

Change in use 

(percent per year)

 2. OHIO-CA 6.4 7.9 –3.7 –22.5

 6. WABASH 14.7 8.7 –18.5 30.7

 7. OHIO-GRCH –0.3 –7.9 –2.3 –22.5

13. MAUM –3.0 –21.5 –21.4 –5.1

20. IOWA-WAP 14.9 –51.9 na 118.2

25. ILLI-VC –7.0 –30.2 –32.5 43.2

26. MSSP-GR –5.7 –13.0 –43.5 12.6

29. PLATTE –3.6 –59.4 –5.7 40.0

30. MIZZ-HE –3.1 –65.4 –34.4 33.6

31. MSSP-TH –6.1 –46.1 –40.2 13.2
Conclusions 69

Conclusions

This study assessed trends in the concentrations of commonly occurring pesticides in selected streams in the Corn 

Belt, an agricultural region that accounts for a major proportion of pesticide use in the U.S., and evaluated the performance and application of statistical trend-assessment methods 

for subsequent application to other regions. Trends in the 

concentrations of 11 pesticides with sufficient data for trend 

assessment were assessed at up to 31 stream sites for two time 

periods: 1996–2002 and 2000–2006. Eleven of the 31 sites, 

referred to as “use-trend” sites, include 7 study sites that were 

selected as indicators of major subareas of the Corn Belt, plus 

four large river sites at the outlets of major drainage basins. 

These 11 sites have large enough drainage areas that reasonable estimates of agricultural use of pesticides are possible. 

Pesticides included in trend analyses are atrazine, acetochlor, 

metolachlor, alachlor, cyanazine, EPTC, simazine, metribuzin, 

prometon, chlorpyrifos, and diazinon.

The statistical methods applied and compared were (1) a 

modified version of the nonparametric seasonal Kendall test 

(SEAKEN), (2) a modified version of the Regional Kendall 

test, (3) a parametric regression model with seasonal wave 

(SEAWAVE), and (4) a version of SEAWAVE with adjustment 

for streamflow (SEAWAVE-Q). The SEAKEN test is a statistical hypothesis test for detecting monotonic trends in seasonal 

time-series data such as pesticide concentrations at a particular 

site. Trends across a region, represented by multiple sites, are 

evaluated using the regional seasonal Kendall test, which computes a test for an overall trend within a region by computing 

a score for each season at each site and adding the scores to 

compute the total for the region. The SEAWAVE model 

is a parametric regression model specifically designed for analyzing seasonal variability and trends in pesticide concentrations. The seasonal wave differs from a trigonometric function 

in that it is specifically designed to mimic the temporal behavior of pesticide concentrations in response to seasonal application rates, basin accumulation, and removal by processes such 

as degradation and runoff. Finally, the SEAWAVE-Q model 

accounts for the effect of changing flow conditions in order to 

separate changes caused by hydrologic trends from changes 

caused by other factors, such as pesticide use.

There was broad, general agreement between unadjusted 

trends (no adjustment for streamflow effects) identified by the 

SEAKEN and SEAWAVE methods, including the regional 

seasonal Kendall test. Only about 9 percent of the paired 

comparisons between SEAKEN and SEAWAVE indicated a 

difference in the direction of trend and only one of these had 

differences significant at the 10-percent significance level. 

This consistency of results supports the validity and robustness 

of all three approaches as trend-analysis tools. The SEAWAVE 

method is favored, however, because it has less restrictive 

data requirements, enabling analysis for more site/pesticide 

combinations, and can incorporate adjustment for streamflow 

(SEAWAVE-Q) with substantially fewer measurements than 

the flow-adjustment procedure used with SEAKEN. 

 Analysis of flow-adjusted trends is preferable to analysis of non-adjusted trends for evaluating potential effects of 

changes in pesticide use or management practices because 

flow-adjusted trends account for the influence of flow-related 

variability. If ignored, these influences of flow conditions may 

alter or disguise trends caused by changes in pesticide use or 

management practices. Flow adjustment affected the fitted 

trends to varying degrees. The flow-adjusted trends generally 

were smaller in magnitude than the unadjusted trends (whether 

up or down). Fitted trends for simazine and prometon concentrations for 1996–2002 were the most sensitive to flow adjustment of the 11 pesticides evaluated and, for the 2000–2006 

period, flow adjustment had the most pronounced effect on 

prometon concentrations.

Analysis of flow-adjusted trends by SEAWAVE-Q shows 

that all of the pesticides assessed except for simazine (mostly 

uptrends) and acetochlor (mostly no trends) were dominated 

by varying degrees of concentration downtrends in one or both 

analysis periods. Atrazine, metolachlor, alachlor, cyanazine, 

EPTC, and metribuzin—all major corn herbicides—showed 

more prevalent concentration downtrends during 1996–2002 

compared to 2000–2006. The downtrends in concentrations 

of these herbicides generally correspond to varying degrees 

of regional downtrends in their use resulting from a variety of 

regulatory, market, and new-product forces that reduced their 

use in the Corn Belt during all or part of the study period. The 

insecticide diazinon had no clear trends during 1996–2002, but 

the trends were predominantly downward during 2000–2006, 

most likely due to reductions in nonagricultural uses because 

of a regulatory phase-out. Acetochlor trends were mixed during 1996–2002 and slightly upward during 2000–2006, but 

most of the trends were not significant. Simazine concentrations trended upward at most sites during both 1996–2002 and 

2000–2006, a pattern explained by increasing agricultural use 

at some sites, but also likely by extensive nonagricultural use 

in some of the watersheds. 

More detailed qualitative comparisons of concentration 

and use trends at 11 sites with relatively large watersheds 

showed that concentration trends for atrazine, acetochlor, 

metolachlor, alachlor, cyanazine, EPTC, simazine, and 

metribuzin were generally similar to use trends for 50 percent 

or more of trend comparisons for use-trend sites evaluated 

(concentration and use trends were considered similar if both 

were significant and in the same direction or if both were 

nonsignificant). There were more frequent differences between 

concentration trends and agricultural use trends for chlorpyrifos and diazinon, which had substantial nonagricultural use 

during part of the study period and which are both insecticides 

with more erratic year-to-year use than most herbicides.
70 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

Overall, combined study results indicate that trends in 

pesticide concentrations in Corn Belt streams and rivers during 1996-2006 were largely explained by corresponding trends 

in annual use and that major reductions in the use of some 

pesticides resulting from regulatory actions or market forces 

generally resulted in corresponding declines in stream and 

river concentrations. To further address the degree to which 

trends in watershed use of pesticides control concentration 

trends, more quantitative comparisons are needed that evaluate 

the significance of differences, given the uncertainty in trend 

estimates. In addition, watershed-scale information is needed 

on the timing of changes in factors other than annual use, such 

as conservation tillage and implementation of buffer strips.

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Appendixes 73

Appendixes

Appendix 1. Left-Censored Seasonal Kendall 

Trend Test and Approach for Estimating Trend 

Slope

The left-censored seasonal Kendall trend test is based 

on the seasonal Kendall trend test described in Hirsch and 

Slack (1984). The seasonal Kendall trend test described in 

Hirsch and Slack (1984) gives unbiased test results for singly 

censored data, when simple substitution is for the censored 

values, however, the estimated trend is affected by the choice 

of the substitution value. Modifications to that test to provide 

unbiased test results for multiply censored data are described 

in this appendix. Consider a sequence of observations collected at regular intervals over a period of years, with no ties 

in the values. Let the matrix

X

x x

x x

p

n np

=





















11 1

1



  



denote a sequence of observations sampled over p seasons 

for n years. The null hypothesis is that the n observations for 

each of the p seasons are ordered randomly. The alternative 

hypothesis is a monotonic trend in one or more seasons. The 

Mann-Kendall test statistic for each season is

S sgn x x g = , p g i< j = ∑ ( ) jg ig − , 1, 2,... , (1)

where the sgn function is defined for censored and uncensored 

values in equations 2 through 5. For these equations, a censored value is indicated by preceding the symbol with <, the 

upper limit is indicated by preceding the symbol with '.

If both are detected values:

sgn x x =

if x x >

if x x =

if x x <

m s

m s

m s

m s

( ) −

−

−

− −





















1 0

0 0

1 0

(2)

If both are censored:

sgn < x < x = ( ) m s − 0 (3)

If only the minuend is censored:

sgn < x x = if x x >

if x x m s

m s

m s

( ) − −

− − ≤













0 0

1 0

'

' (4)

If only the subtrahead is consored:

sgn x x =

if x x

if x x m s

m s

m s

( ) − <

− ≥

− <













1 0

0 0

'

' (5)

If either value is missing, the result is 0.

The seasonal Kendall test statistic is

S Sg g ' = ∑

and is asymptotically normal with mean 0 and variance

Var S g g gh g h gh ( ') , = + ∑ ∑  !=  2

where σ2

g is Var(Sg

) and σgh is Cov(Sg,Sh). Equations 6 to 8 

describe the proposed method for computing the adjustment to 

the p-value to account for serial dependence between seasons.

Equation 6 in Hirsch and Slack (1984) estimates the 

covariance:

gh gh = + − K n n r ( ) gh /3 /9 3 (6)

Equation 7 in Hirsch and Slack (1984) describes the 

computation of Kgh:

K sgn x x x xX gh i j jg ig jh ih = ∑ < [( ) − ( ) − ] (7)

Equation 8 in Hirsch and Slack (1984) describes the 

computation of rgh:

r n n sgn X X X X gh = − 3 ( )∑i j k ( ) jg ig jh kh − ( ) − 3 / [ ] , , (8)

The covariance can be computed using the same rules as 

for computing the variance of S.

For computational purposes, the sign of the product of 

two values is equal to the product of the signs of each value 

(eq. 9):

sgn AB sgn A sgn B ( ) ( ) ( ) = (9)
74 Trends in Pesticide Concentrations in Corn-Belt Streams, 1996–2006

This reduces the computation of equations 7 and 8 to 

a simple look-up table (eq. 2 through 5) on the basis of the 

values of minuend (Xm) and subtrahend (Xs).

For missing data, the same procedure as in Hirsch and 

Slack (1984) is used. Define sgn(A – B) to be zero if either A 

or B is missing. Equation 8 then becomes:

r n n n sgn x x x x gh = + ( ( ) g h ( ) + ) i j k ( ) jg ig jh kh − ( ) −   ∑  3 1 1 / , , (10)

and equation 6 becomes:

 gh gh = + + K n n n r / ( 3 1 1 9 ( ) g h gh ( ) + ) / (11)

The modifications described in this appendix result in no 

change for left-censored data when there is a single censoring 

value and no observed values less than the censoring value. 

There also is no difference when there are missing values. 

However, these modifications provide a method to estimate 

the significance of a trend, when there are multiple reporting 

limits.

Computing Slope

Slope is an estimate of the magnitude of the trend. The 

method used in the left-censored seasonal Kendall trend test 

modifies the procedure presented by Helsel (2005, p. 210–212) 

from a general regression between X and censored Y to a 

seasonal slope estimate. This method describes the relation 

between T and censored Y, where Y is observed on a regular 

basis throughout a given period of time (T). The estimate of 

slope is made by computing the median slope of all withinseason comparisons. For example, if water-quality samples 

were taken on a monthly basis, slopes would be computed 

for all values taken in January, but not between January and 

February, as is described in Hirsch and Slack (1984).

The key to this method is that water-quality data are 

interval-censored data. That is, a concentration that is reported 

as <Y actually is a concentration that probably lies between 0 

and Y. Thus, the slope between two observations, one censored 

and one uncensored, is expressed as a range. For example, 

assume that at time 1 the concentration is <1 and that at time 2 

the concentration is 2. The slope (rate of change in concentration between time 1 and time 2) is between (2 – 1)/1 = 1 and 

(2 – 0)/1 = 2. The median slope can be estimated using Turnbull’s method for the Kaplan–Meier survival analysis (Turnbull, 1974, 1976) using estimated seasonal slopes as input.

Turnbull’s method requires three values, a maximum 

value (Smax), a minimum value (Smin), and an indicator value 

(Sind), (1 for known event (maximum = minimum), 2 for interval censored (maximum > minimum), for example). Equations 

12–15 describe computing slope.

Yt and Yt+n are uncensored: 

S Y Y n

S S

S

t n t

ind

max

min max

= − ( )/

=

=

+

1

(12)

Yt censored and Yt+n uncensored:

S Y n

S Y Y n

S

t n

t n t

ind

max

min

( )/

( )/

= −

= −

=

+

+

0

2

(13)

Yt uncensored and Yt+n censored:

S Y Y n

S Y n

S

t n t

t

ind

max

min

( )/

( )/

= −

= −

=

+

0

2 (14)

Yt and Yt+n are censored:

S Y n

S Y n

S

t n

t

ind

max

min

( )/

( )/

= −

= −

=

+ 0

0

2 (15)

If either Yt or Yt+n are missing, no slope is computed. For 

computational purposes, if Y is censored at a value D, then a 

value of D – ε is used for that value, where ε is about 1/1000 

the resolution of the data (the smallest range between sorted 

data). All possible slopes are computed for each season and 

the median is computed for the aggregated slopes for each 

season. 
Appendixes 75

Appendix 2. Methods for Fitting SEAWAVE and 

SEAWAVE-Q models

The methods used to fit the SEAWAVE model (eq. 2) and 

SEAWAVE-Q model (eq. 3) are similar to those described in 

Vecchia and others (2008), with some minor modifications, 

described in this appendix, to accommodate the specific sites 

and pesticides analyzed in this study.

The seasonal wave, W(t), is the solution to the following 

differential equation,

d

dt

W t t W t t W W

t I kt

k k

( ) ( ) ( ) , ( ) ( )]

( )

= − [ ≤ ≤ =

= − ≤ < 



 

λ φ

λ ω

0 1 0 1

1

12 12 

 =

∑k

t

1

12

where 

is decimal time, in years, with respect to an 

arbitrary origin;

λ( )is an instantaneous input function t describing 

seasonal variability of pesticide application rates;

is a positive constant;

{ , k = 1, 2, ,12} are specif k

φ

ω ... ied non- negative constants; and 

I I t (.) = if lies in the given interval and (.) = 0 otherwise. I

(A2-1)

As described in Vecchia and others (2008), the input function 

consisted of seven choices with either 1 or 2 pesticide application periods of specified length and constant application rates 

within each period. For this report, 14 choices for the input 

function were used (table A2-1), including the 7 choices from 

Vecchia and others (2008) plus 7 additional choices. See Vecchia and others (2008) for figures that show examples of the 

seasonal waves. The parameter f controls the rate at which 

the seasonal wave decays during periods of no input. If input 

ceases at some time t* (λ(t)=0 for t>t*), W(t) decays at a rate 

of exp(–φ/12) per month, corresponding to an approximate 

half-life of (12/φ) months. In this report, four choices were 

used for φ – 3, 4, 6, and 12 – corresponding with half-lives 

of 4, 3, 2, or 1 month. In Vecchia and others (2008), only two 

choices for φ (4 or 12) were used. 

 For each pesticide/site combination, there were 56 

choices for the seasonal wave, corresponding with the 14 

choices for the input function and 4 choices for φ described 

previously. In addition, since the origin used to compute the 

seasonal wave was arbitrary, a phase shift needed to be applied 

to make the maximum of each wave line up as closely as 

possible with the timing of the maximum concentration. In 

Vecchia and others (2008), the time of the maximum concentration was selected by locating the center of the 1-month 

interval for which the mean of the log-transformed concentration data were maximized. However, for this report, a more 

robust method was used for fixing the time of the maximum 

concentration. Namely, the S-plus function, supsmu, was used 

to fit a smooth line to a plot of season (t minus the greatest 

integer in t) versus concentration and the time was selected at 

which the line reached its maximum.

The regression parameters for either eq. 3 or eq. 7 were 

estimated using Gaussian maximum likelihood estimation 

with censored data, as described in Vecchia and others (2008). 

Parameters were estimated for each of the 56 choices for the 

seasonal wave, and the wave with the highest value for the 

likelihood function for a given site/pesticide combination was 

selected as the best wave. 

Choice 

number ω1 ω2 ω3 ω4 ω5 ω6 ω7 ω8 ω9 ω10 ω11 ω12

1 0 0 1 0 0 0 0 0 0 0 0 0

2 0 0 1 1 0 0 0 0 0 0 0 0

3 0 0 1 1 1 0 0 0 0 0 0 0

4 0 0 1 1 1 1 0 0 0 0 0 0

5 0 0 1 1 1 1 1 1 0 0 0 0

6 0 0 1 1 1 1 1 1 1 1 1 0

7 0 0 1 1 1 0 0 0 1 0 0 0

8 0 0 1 1 1 0 0 0 0 1 0 0

9 0 0 1 1 1 0 0 0 0 0 1 0

10 0 0 1 1 1 0 0 0 0 0 0 1

11 0 0 1 1 1 0 0 0.75 0.75 0 0 0

12 0 0 1 1 1 0 0 0 0.75 0.75 0 0

13 0 0 1 1 1 0 0 0 0 0.75 0.75 0

14 0 0 1 1 1 0 0 0 0 0 0.75 0.75

Table A2-1. Choices for the input function describing seasonal variability of pesticide application rates (equation A2-1).
Manuscript approved for publication, June 16, 2009

Prepared by the USGS Enterprise Publishing Network,

Publishing Service Center, Sacramento, California

For more information concerning the research in this report, contact the

California Water Science Center Director,

U.S. Geological Survey, 6000 J Street

Sacramento, California 95819

http://ca.water.usgs.gov
Sullivan and others—Trends in Pesticide Concentrations in Corn-Belt Streams, 1996-2006 SIR 2009-5132

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