U.S. Department of the Interior

U.S. Geological Survey

Data Series 573

National Water-Quality Assessment Program

Prepared in cooperation with the Conservation Technology Information Center

Tillage Practices in the Conterminous United States, 

1989–2004—Datasets Aggregated by Watershed
Cover photos

Upper Left. Conservation tillage system (full width) that leaves at least 30 percent of the soil covered after 

planting with last year’s crop residue (mulch tillage). Central Iowa. Photograph by Lynn Betts, 1999, 

Natural Resources Conservation Service Photo Gallery, NRCSIA99097, http://photogallery.nrcs.usda.gov/.

Lower Left. Ridge-till and strips of corn and soybeans in northwest Iowa field. Photograph by Lynn Betts, 

1999, Natural Resources Conservation Service Photo Gallery, NRCSIA99311, http://photogallery.nrcs.usda.gov/.

Upper and Lower Center. No-till soybeans. Photos courtesy of Conservation Technology Information Center, 

Feb. 2011, http://www.ctic.org/.

Upper Right. Moldboard plowing. Stages of Bean Growth – Plowing, Michigan State University, AgBioResearch, 

http://agbioresearch.msu.edu/saginawvalley/Pic_Tour/plowing.htm accessed Feb. 2011.

Lower Right. No-till drill working in central Iowa. Photograph by Tim McCabe, 1999, Natural Resources 

Conservation Service Photo Gallery, NRCSIA99091, http://photogallery.nrcs.usda.gov/.
Tillage Practices in the Conterminous 

United States, 1989–2004—

Datasets Aggregated by Watershed

By Nancy T. Baker

National Water-Quality Assessment Program

Prepared in cooperation with the Conservation Technology Information Center

Data Series 573

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: 2011

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reproduce any copyrighted materials contained within this report.

Suggested citation:

Baker, N.T., 2011, Tillage practices in the conterminous United States, 1989–2004—Datasets Aggregated by 

Watershed: U.S. Geological Survey Data Series 573, 13 p.
iii

Foreword

The U.S. Geological Survey (USGS) is committed to providing the Nation with reliable 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 

suitable for industry, irrigation, and fish and wildlife. Population growth and increasing demands for water 

make the availability of that water, 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 quality 

of our Nation’s streams and groundwater? How are conditions changing over time? How do natural features 

and human activities affect the quality of streams and groundwater, 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. From 1991 to 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/studies/study_units.html).

National and regional assessments are ongoing in the second decade (2001–2012) of the NAWQA Program 

as 42 of the 51 Study Units are selectively reassessed. These assessments extend the findings in the 

Study Units by determining water-quality status and trends at sites that have been consistently monitored 

for more than a decade, and filling critical gaps in characterizing the quality of surface water and 

groundwater. For example, increased emphasis has been placed on assessing the quality of source water 

and finished water associated with many of the Nation’s largest community water systems. During the

second decade, NAWQA is addressing five national priority topics that build an understanding of how 

natural features and human activities affect water quality, and establish links between sources of 

contaminants, the transport of those contaminants through the hydrologic system, and the potential effects 

of contaminants on humans and aquatic ecosystems. Included are studies on the fate of agricultural 

chemicals, effects of urbanization on stream ecosystems, bioaccumulation of mercury in stream ecosystems, 

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

In addition, national syntheses of information on pesticides, volatile organic compounds (VOCs), nutrients, 

trace elements, and aquatic ecology are continuing. 

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.

 William H. Werkheiser

USGS Associate Director for Water
iv

Acknowledgments

The author thanks Karen Scanlon, Executive Director, and the staff of the Conservation Technology 

Information Center (CTIC) for providing the county-level tillage practice dataset and for providing technical 

support during the data-aggregation process. The author also expresses gratitude to two CTIC consultants: 

Dan Towery of Ag Conservation Solutions for explaining the methods used to collect the data and 

Scott Brunton of EsJay Computer Systems for providing database technical support.
v

Contents

Foreword ........................................................................................................................................................iii

Acknowledgments........................................................................................................................................iv

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

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

CTIC Data-Collection Methods....................................................................................................................1

Tillage Type Definitions ........................................................................................................................2

Data-Processing Methods ...........................................................................................................................4

Preprocessing of County-Level Tillage Data....................................................................................4

Area-Weighted Interpolation..............................................................................................................4

Tabular-Data Aggregation...................................................................................................................5

Tillage-Practice Datasets Aggregated to 8-Digit Hydrologic Unit Watersheds..................................8

Summary........................................................................................................................................................12

References Cited..........................................................................................................................................12

Appendix 1. Tillage Practices in the Conterminous United States, 

1989–2004 based on the 1992 enhanced National Land Cover Data; 

dBase file: tillage_lu92e.....................................................................................................13

Appendix 2. Tillage Practices in the Conterminous United States, 

1989–2004 based on the 2001 National Land Cover Data; 

dBase file: tillage_lu01.......................................................................................................13

Appendix 3. Companion dataset to be used with the tabular dBase tillage 

practice datasets, dBase file: tillage_lu92e and dBase file: tillage_lu01..................13

Figures

1–2. Maps showing:

1. States where tillage information was obtained by roadside-transect 

surveys for 2000, 2002 and 2004, and location of cultivated land ................................2

2. Last year for which the Crop Residue Management Survey was 

conducted, by county, for the A 1989–98, B 1998 and 2000, and 

C 2002, 2004 and 2006–08 time periods for the conterminous United States.............3

3. Land-cover weighted areal interpolation by (1) overlaying 8-digit 

hydrologic unit watersheds with (2) cultivated cropland and (3) county 

boundaries resulting in (4) the intersection of cultivated land for all the 

counties in each watershed. Examples of the process are shown for areas 

in the A western and B eastern United States ........................................................................6

4. Maps showing the comparison of the original Conservation Technology 

Information Center county-level data and 8-digit hydrologic unit 

watershed-level data for the percentage of no-till on 

A all crops, B corn, and C soybeans for the conterminous United States, 2004................9

5. Graphs showing the comparison of Economic Research Service (E) 

and Conservation Technology Information Center (C) estimates of

total planted acreages, by State, and tillage practice for corn for 

1993, 1996, 1998, and 2000..........................................................................................................10
vi

Tables

1. Example output from U.S. Geological Survey National Water-Quality 

Assessment Area Characterization, Feature Weights to Table Tool....................................7

2. Attribute labels and definitions for tillage_lu92e.dbf and tillage_lu01.dbf..........................8

Multiply By To obtain

Length

inch (in.) 2.54 centimeter (cm)

inch (in.) 25.4 millimeter (mm)

meter (m) 3.281 foot (ft)

meter (m) 1.094 kilometer (km)

mile, nautical (nmi) 1.852 kilometer (km)

yard (yd) 0.9144 yard (yd)

Area

acre 4,047 square meter (m2

)

acre 0.4047 hectare (ha)

acre 0.4047 square hectometer (hm2

) 

acre 0.004047 square kilometer (km2

)

square mile (mi2

) 259.0 hectare (ha)

square mile (mi2

) 2.590 square kilometer (km2) 

Conversion Factors and Abbreviations

Abbreviations used in this report

CTIC Conservation Technology Information Center

ERS Economic Research Service

FWT feature weights to table

HU hydrologic unit

NACT NAWQA Area Characterization Toolbox

NASS National Agricultural Statistics Service

NAWQA National Water-Quality Assessment 

NLCD National Land Cover Data

NRCS Natural Resources Conservation Service

USDA U.S. Department of Agriculture

USGS U.S. Geological Survey

WAREAF area-weighted fraction
Tillage Practices in the Conterminous United States, 

1989–2004—Datasets Aggregated by Watershed

By Nancy T. Baker

Abstract

This report documents the methods used to aggregate 

county-level tillage practices to the 8-digit hydrologic unit 

(HU) watershed. The original county-level data were collected 

by the Conservation Technology Information Center (CTIC). 

The CTIC collects tillage data by conducting surveys about 

tillage systems for all counties in the United States. Tillage 

systems include three types of conservation tillage (no-till, 

ridge-till, and mulch-till), reduced tillage, and intensive tillage. 

Total planted acreage for each tillage practice for each crop 

grown is reported to the CTIC. The dataset includes total 

planted acreage by tillage type for selected crops (corn, cotton, 

grain sorghum, soybeans, fallow, forage, newly established 

permanent pasture, spring and fall seeded small grains, and 

“other” crops) for 1989–2004.

Two tabular datasets, based on the 1992 enhanced and 

2001 National Land Cover Data (NLCD), are provided as part 

of this report and include the land-cover area-weighted interpolation and aggregation of acreage for each tillage practice in 

each 8-digit HU watershed in the conterminous United States 

for each crop. Watershed aggregations were done by overlying 

the 8-digit HU polygons with a raster of county boundaries 

and a raster of either the enhanced 1992 or the 2001 NLCD for 

cultivated land to derive a county/land-cover area weighting 

factor. The weighting factor then was applied to the countylevel tillage data for the counties within each 8-digit HU and 

summed to yield the total acreage of each tillage type within 

each 8-digit HU watershed. 

Introduction 

The Conservation Technology Information Center (CTIC) 

has made its proprietary county-level tillage survey available 

for inclusion in U.S. Geological Survey (USGS), National 

Water-Quality Assessment (NAWQA) supported analyses. 

The dataset includes planted acreage of conservation tillage 

(no-till, ridge-till, and mulch-till), reduced tillage, and intensive 

or conventional tillage for selected crops (corn, cotton, grain 

sorghum, soybeans, fallow, forage, newly established permanent pasture, spring and fall seeded small grains, and “other” 

crops), by county, for 1989–2004. The CTIC requests that 

the data not be distributed in their raw form—county acreage 

totals, by crop, for each tillage practice—because the survey 

is proprietary. To comply with the CTIC requirements, the 

dataset was aggregated by watershed for each tillage practice, 

crop, and year combination. Watershed aggregations were 

made for each 8-digit hydrologic unit (HU) in the conterminous United States by using an area-weighted interpolation for 

cultivated land in each county intersecting a HU. 

This report documents the methods used by the CTIC 

to collect tillage data and the methods used by the USGS to 

prepare the CTIC data for release for NAWQA-supported 

analyses. The prepared datasets are provided as part of this 

report and include the land-cover area-weighted interpolation 

and aggregation of acreage for each tillage practice in each 

8-digit HU watershed in the conterminous United States for 

corn, cotton, grain sorghum, soybeans, fallow, forage, newly 

established permanent pasture, spring seeded and fall seeded 

small grains, and other crops (sum of all other crops not 

listed). Land-cover area-weighted interpolations were done 

using both the 1992 (enhanced) (Nakagaki and others, 2007) 

and 2001 (LaMotte, 2008) National Land Cover Data (NLCD) 

resulting in two tabular datasets. The prepared tabular datasets include tillage practices for 1989–2004 for all counties 

(aggregated to the 8-digit HU) where data were collected in 

the conterminous United States. The CTIC did not conduct 

surveys for 1999, 2001, and 2003. In addition, surveys were 

not conducted every year for 1995–98 for several counties; 

therefore, the number of years data were collected varies by 

county. A spatial coverage of the 8-digit HUs, which can be 

related to the two tabular datasets based on the 8-digit HU 

code, also is included in this report. 

CTIC Data-Collection Methods 

The CTIC collects tillage data by conducting surveys 

about tillage systems for all counties in the United States. 

Tillage systems include three types of conservation tillage 

(no-till, ridge-till, and mulch-till), reduced tillage, and 

intensive tillage. Total annually planted crop acreage for 

each tillage practice for each crop grown is reported by local 

conservationists to the CTIC. For 1989–98, surveys were 

based on local knowledge and expertise to “best estimate” 

tillage practices. Local conservation partnerships included 

Natural Resources Conservation Service (NRCS), State Soil 

and Water Conservation Districts, State extension agents, 

Farm Service Agency, and other agribusiness partners. For 
2 Tillage Practices in the Conterminous United States, 1989–2004—Datasets Aggregated by Watershed

2000, 2002, and 2004, 17 States (fig. 1) used roadside-transectsurvey procedures for counties with more than 100,000 acres 

of cropland. County conservation staff drove along a set course 

through areas dominated by cropland; staff collected data on 

approximately 480 fields in each county. Percentages of each 

crop/tillage system were calculated and applied to total county 

crop acreages based on a combination of local knowledge 

of county crop acreage (Conservation Technology Information 

Center, 2004) and acreage estimated by the U.S. Department of 

Agriculture, National Agricultural Statistics Service (NASS) 

(Carmen Sandretto, U.S. Department of Agriculture, Economic Research Service, written commun., 2010). The CTIC 

roadside-transect-survey methods are described in the 2004 

Cropland Roadside Transect Survey document (Conservation 

Technology Information Center, 2004).

Not all counties reported tillage information every year. 

Figure 2 shows the CTIC survey years and the actual years 

data were collected in each county. All counties reported 

tillage information for 1989–95. For 1996–98, most counties 

reported tillage information; exceptions include counties in 

the desert southwest, coastal northeast, West Virginia, and 

in several States throughout the U.S.—primarily in counties 

with less than 25,000 cropland acres. Most counties reported 

tillage information for 2000, 2002, and 2004; selected areas in 

the Midwest reported tillage information for 2006–08 (fig. 2). 

The 2006–08 data are not included in this report because they 

are so sparse.

Tillage Type Definitions

Tillage systems are defined based upon the amount of 

crop residue that remains on the soil after planting and resulting 

disturbance to the soil. Tillage types are defined in the CTIC 

2004 National Crop Residue Management Survey. 

Conservation tillage is any cropland system that leaves 

at least one-third of the soil covered with crop residue after planting. Conservation tillage types include 

no-till/strip-till, ridge-till, and mulch-till.

• The no-till concept has evolved as technology has 

changed. With no-till, producers disturb only the minimal 

amount of soil needed to ensure a good stand and yield. 

Variations under the no-till umbrella include the following: 

• Midwest strip-till usually involves a mole knife to till 

a zone approximately 10 inches wide and 4 to 5 inches 

high in the fall. Some combination of nutrients is usually 

applied at the same time. The following spring, planting 

occurs in the tilled strip. 

• Southeast strip-till is used on the Sandy Coastal Plain soils 

(soils that naturally compact) in the Southeast portion 

of the United States. A ripper runs about 14 inches deep 

ahead of or with the planter. 

Cultivated cropland

Transect survey States

Other land

EXPLANATION

Figure 1. States where tillage information was obtained by roadside-transect surveys for 2000, 2002 and 2004, and location of 

cultivated land. Transects were surveyed in counties with more than 100,000 acres of cropland. [Source: Conservation Technology 

Information Center, 2004]
CTIC Data-Collection Methods 3

• Vertical tillage is used with a narrow ripper about 

12 to 14 inches deep, usually in the fall, which causes 

very little surface soil disturbance. Planting occurs 

directly over the tilled strip. 

• Fluffing harrows “fluff” the residue, allowing excess 

moisture in the seedbed to evaporate and improve 

planting conditions.

Other conservation tillage practices include the following: 

• Ridge-till involves building 4- to 6-inch high ridges during row cultivation and scraping off 1 to 2 inches of the 

ridge during planting. 

• Mulch-till is a full-width (100 percent of soil surface 

disturbed) tillage system that usually involves one to 

three tillage passes. Implements such as chisel plows, 

disks, field cultivators and combination tools are used. 

No-till (including all variations mentioned), ridge-till, and 

mulch-till fall under the conservation tillage umbrella.

NOT Conservation Tillage

• Reduced-till systems are somewhat similar to mulch till in 

that they involve full-width tillage, use the same implements and may use one to three tillage trips. Reduced-till, 

however, leaves 15-30 percent residue on the soil surface 

after planting.

• Intensive-till or conventional-till involves full-width 

tillage and may involve one to three or perhaps up to 

15 tillage passes. There is less than 15 percent residue 

on the soil surface after planting. Moldboard plowing 

and/or multiple tillage trips are considered the same.

(Conservation Technology Information Center, 2004, 

http://www.ctic.purdue.edu/media/pdf/TillageDefinitions.pdf )

1995

1996

1997

1998

1998

2000

A B

C

A

B

C

Last year for which the Crop Residue

Management Survey was conducted,

by county, for the time period

All counties reported in 2002 and 2004

No counties reported in 2001 or 2003

All counties reported in 1989−95

No counties reported in 1999

2004

2006

2007

2008

1989−98 1998 and 2000

2002, 2004, and 2006−08 EXPLANATION

Figure 2. Last year for which the Crop Residue Management Survey was conducted, by county, for the A 1989–98, B 1998 and 

2000, and C 2002, 2004 and 2006–08 time periods for the conterminous United States. [Source: Conservation Technology 

Information Center, 2004]
4 Tillage Practices in the Conterminous United States, 1989–2004—Datasets Aggregated by Watershed

The CTIC collects tillage information for all annually 

planted crops and for compilation purposes sums the acreage 

into the following major crop categories: full season and 

double cropped corn, grain sorghum, and soybeans; cotton; 

forage crops; spring seeded and fall seeded small grains; fallow; newly established permanent pasture; and other crops 

including vegetables. Starting in 2000, the CTIC eliminated 

the reporting requirement for double cropping of corn and 

grain sorghum because these two categories represented a 

fairly small acreage, and there was inconsistency in reporing 

these acreages. By definition, double cropped means two 

principal row crops in one growing season. Many times corn 

or sorghum was planted after hay or wheat was harvested. 

There were few acreages that were double cropped and the 

CTIC decided to simplify the data collections where possible; 

therefore, they no longer were counted as a separate category 

and were subsequently combined with the total full-season 

acreages (Dan Towery, Conservation Technology Information 

Center, written commun., 2010). 

Small grains are grouped into spring seeded and fall 

seeded. Spring seeded small grains include rice, spring wheat, 

oats, and barley. Fall seeded small grains include winter wheat 

and rye. All acreages of small grains are counted in the year 

they are seeded. Forage crops also are reported in the seeding 

year only (Dan Towery, Conservation Technology Information 

Center, written commun., 2010). 

Other crops include other vegetable crops, truck crops, 

peanuts, potatoes, tobacco, beans, canola, sugar beets, sugarcane, sunflowers, and any other crop not included in the major 

crop categories (Conservation Technology Information Center, 

2004). Tillage practices also were reported for fallow land 

and newly established permanent pasture. Ridge-tillage is not 

applicable to either of these planting practices.

Data-Processing Methods 

The USGS may not distribute the CTIC tillage data in its 

raw form—a tabular dataset of county acreage totals, by crop, 

for each tillage practice—because the data are proprietary. The 

following steps were taken to prepare the tillage data for distribution and analysis. First, the original tabular county-level 

dataset was preprocessed to check for outliers. Next, landcover area-weighting factors were generated to determine the 

area of cultivated land within each county/8-digit HU watershed combination. Finally, the land-cover weighting factors 

were applied to the CTIC reported acreages of tilled land for 

each crop and tillage practice and aggregated to the 8-digit HU 

watershed by summing the acreage for each county portion 

that falls within each watershed. 

Preprocessing of County-Level Tillage Data

Prior to land-cover weighting and data aggregation, 

the original CTIC dataset was checked for data values that 

were outside the range of probable values. Initially, the entire 

dataset was checked for negative values. Eleven cases were 

found and brought to the attention of the CTIC, who then supplied corrected values (Scott Brunton, Conservation Technology 

Information Center, written commun., 2009). The data also 

were checked to see if, for any given year, the total acreage for 

all tillage practices for each crop in each county was greater 

or less than three times the standard deviation of the values 

for the entire period of record. A small percentage of the data 

(109 cases out of 445,248) were greater or less than three times 

the standard deviation. These outliers were evaluated on an 

individual basis to determine whether to keep the original data 

value or to replace the original data value with an interpolated 

data value from previous and subsequent years. There were 

57 cases where the data values were suspect enough to warrant 

replacing the original data values. 

Area-Weighted Interpolation

A land-cover area-weighted interpolation for cultivated 

land was done to determine the weighting factors needed to 

aggregate county-level tillage data to the 8-digit HU watershed. Weighting factors were generated based on the area 

of cultivated land within each county/8-digit HU watershed 

combination. The spatial datasets used to perform the interpolation include the Water Boundary Dataset (U.S. Geological 

Survey and U.S. Department of Agriculture–Natural Resources 

Conservation Service, 2009), the enhanced NLCD for 1992 

(Nakagaki and others, 2007) and NLCD 2001 (LaMotte, 2008), 

and the 30-m resolution grid of the 1990 county boundaries 

(JoAnn Gronberg, U.S. Geological Survey, written commun., 

2005) (fig. 3). Land-cover weighting is used so that countylevel tillage data are proportioned to the agricultural areas in 

each county/8-digit HU watershed. With a simple area-weighted 

interpolation, the tillage data would be proportioned equally 

throughout the county; therefore, it is not the best method for 

counties where the majority of cultivated land may be concentrated in a small portion of the county.

The 8-digit HU watershed boundaries used for this aggregation were derived from the Water Boundary Dataset–12-digit 

HU (U.S. Geological Survey and Natural Resources Conservation Service, 2009). The 12-digit HU subwatershed polygons 

were dissolved to the 8-digit HU watershed level for the conterminous United States. The average size of a HU is 40 mi2

 for 

a 12-digit watershed and 700 mi2 for an 8-digit watershed 

(U.S. Geological Survey and U.S. Department of Agriculture–

Natural Resources Conservation Service, 2009). 

Land-cover areal weighting was done using both the 

1992 (enhanced) and 2001 NLCD 30-m resolution raster data 

(NLCDe 92 and NLCD01, respectively), resulting in two 

separate sets of area-weighting factors. The CTIC tillage data 

span from 1989 through 2004, and the generation of the two 

datasets allows users to decide which land-cover aggregation—NLCDe 92 or NLCD01—is appropriate for their particular analysis. Users are cautioned that direct comparison of 

NLCDe 92 and NLCD01 is not recommended because these 

two independently created land-cover products were developed using different methodologies and sources of input data 
Data-Processing Methods 5

(U.S. Geological Survey, 2008a). For example, using NLCDe 92 

for areal weighting for earlier years of tillage data and using 

NLCD01 for the remaining years of tillage data may introduce 

bias unrelated to changes in tillage practices. 

Cultivated land is defined differently for NLCDe 92 and 

NLCD01. For NLCDe 92, cultivated land includes the following 

land-cover codes (U.S. Geological Survey, 2010): 61 and 62 classified as Orchards/Vineyards/Other–Orchards, vineyards, and 

other areas planted or maintained for the production of fruits, 

nuts, berries, or ornamentals (both 61 and 62 indicate the same 

land cover—62 is derived from other data sources and is part 

of the enhancements made to NLCD92); 82 classified as Row 

Crops–Areas used for the production of crops such as corn, soybeans, vegetables, tobacco, and cotton; 83 Classified as Small 

Grains–Areas used for the production of graminoid crops such 

as wheat, barley, oats, and rice; and 84 Classified as Fallow–

Areas used for the production of crops that do not exhibit visible 

vegetation as a result of being tilled in a management practice 

that incorporates prescribed alternation between cropping and 

tillage. The rational for including fallow land is that the NLCD 

is a snapshot of land cover for a single year. An assumption was 

made that fallow land will alternate in and out of production 

and will be actively managed some of the time. In addition, the 

CTIC tillage data include acreage for fallow land that has been 

tilled. For NLCD01, cultivated land includes land cover code 

82 Cultivated Crops–Areas used for the production of annual 

crops such as corn, soybeans, vegetables, tobacco, and cotton, 

and also perennial woody crops such as orchards and vineyards. 

This class also includes all land being actively tilled (U.S. Geological Survey, 2008b). 

A 30-m resolution grid of the 1990 county boundaries 

(JoAnn Gronberg, U.S. Geological Survey, written commun., 

2005) was used as the third component for performing the landcover area-weighted interpolation. The dataset was generated 

from the 1:100,000-scale polygon coverage of county boundaries for the conterminous United States and was created to 

generate county statistics such as county weighting factors by 

land-cover classifications. County weighting factors are used 

with county data to estimate, for instance, basin-level pesticide 

application, fertilizer use, and conservation-tillage acres (Naomi 

Nakagaki, U.S. Geological Survey, written commun., 2010).

Although the size of 8-digit HU watersheds is fairly 

consistent across the United States, county sizes generally are 

larger in western states (fig. 3). The disparity in county size in 

relation to 8-digit HUs across the country means that the results 

of aggregating county data to the 8-digit level are different in 

different areas of the country. In the east, where counties usually are smaller than 8-digit HUs, the resulting acreage for each 

8-digit HU will be the sum of the cultivated land from portions 

of several counties. Conversely in the west, the resulting acreage 

for several 8-digit HUs simply may be a proportion of cultivated 

land in a single county (fig. 3).

Cultivated-land area-weighted interpolation was done 

within the ArcGIS desktop environment (version 9.3.1). 

A detailed description of the method for calculating landcover area-weighted interpolation is documented in (Naomi 

Nakagaki, U.S. Geological Survey, written commun., 2010). 

The NAWQA Area Characterization Toolbox (NACT) (Price 

and others, 2010), an add-on toolbox for ArcGIS desktop that 

automates area-weighted interpolations, was used to obtain the 

cultivated-land area weights for this report. Using NACT for 

calculating the interpolation ensures that the steps are performed 

in a manner consistent with other NAWQA area-weighted interpolations and that standard methods and tolerances for overlaying spatial data are used (Price and others, 2010).

Area weights were calculated using the NACT, Feature 

Weights to Table (FWT) tool, which calculates the area-weight 

between the overlapping areas of each feature class against a 

weight raster and outputs the results to a weight table (table 1) 

(Price and others, 2010). The FWT tool requires user input for 

Input Features and associated Input Field, Weight Raster, and 

Zone Raster. For this interpolation, the Input Features are the 

8-digit HU watershed boundary polygons and the associated 

Input Field is the numeric 8-digit HU code. The Weight Raster 

is the 30-m resolution grid of the 1990 county boundaries; the 

Zone Raster is the NLCD. Area-weighting factors are output 

for each unique 8-digit HU code. For each unique 8-digit HU, a 

row in the resulting weight table is generated for every county 

that overlaps each 8-digit HU. Separate weight tables were generated for the NLCDe 92 and NLCD01. The output-weight table 

entries are split by creating a row for each unique land cover 

(value of Zone Raster cells) found within the area delineated by 

each input feature (table 1). The results of the weight table then 

can be used to proportion tillage acreage for each county/HU 

based on cultivated land and aggregated for each 8-digit HU.

Tabular-Data Aggregation

Aggregation of the county-level tillage practice data to the 

8-digit HU was done by merging the CTIC county-level data 

table with the weight table from the land-cover area-weighted 

interpolation, then multiplying the area-weighted fraction 

(WAREAF) from the weight table by the acreages for each crop 

and tillage practice in the county-level data table, and finally 

summing the resulting acreages for each 8-digit HU. 

Aggregation applies to cultivated land, and that data was 

extracted from the weight tables. For NLCDe 92, this included 

land-cover codes 61, 62, 81, 82, 83, and 84. For NLCD01, this 

included land-cover codes 81 and 82. For most counties for 

NLCDe 92, area-weighting factors for 61, 62, 82, 83, and 84 

for each county/HU combination were summed before multiplying by the CTIC county-tillage acreages. For NLCD01, 

the area-weighting factor for land-cover code 82 was used. 

A small number of counties reported crop acreage and associated tillage practices to CTIC, but there is no NLCD-identified 

cultivated land in those counties. In those cases, reported crop 

acreage is weighted by land-cover code 81. Land-cover code 

81 includes Pasture/Hay–Areas of grasses, legumes, or grasslegume mixtures planted for livestock grazing or the production of seed or hay crops. In counties where there was also no 

NLCD-identified land-cover code 81, the reported crop acreage 

was proportioned equally throughout the county. 
A B AB (1) 8-digit hydrologic unit watershed boundaries (2) Cultivated cropland; National Land Cover Data 2001 land-cover code 82 (3) County boundaries + + + + == EXPLANATION 8-digit hydrologic unit boundary Cultivated cropland

County boundary

(4) Boundarie

land-cov

areal in

Other land

Figure 3. Land-cover weighted areal interpolation by (1) overlaying 8-digit hydrologic unit watersheds with (2) cultivated cropland aboundaries resulting in (4) the intersection of cultivated land for all the counties in each watershed. Examples of the process are showthe A western and B eastern United States.
Data-Processing Methods 7

Table 1. Example output from U.S. Geological Survey National Water-Quality Assessment Area Characterization, 

Feature Weights to Table Tool

[AREAID, 8-digit hydrologic unit code; ZONE, land cover code; WTZONE, state and county FIPS code; NCELLS, the number of 

30m X 30m cells with the same AREAID, ZONE, and WTZONE; AREA, the total area of land with the same AREAID, ZONE, and 

WTZONE (NCELLS X 900); AREAF, area fraction (total area of the unique AREAID—for 3,150,507 total area = 5,082,517,800 m2 

and for 3,150,201 total area = 6,193,173,600 m2); WAREA, weighted area (total area of the unique WTZONE); WAREAF, weighted 

area fraction (AREA / WAREA); highlighted cells indicate cultivated land (land-cover codes 62 and 82].

AREAID ZONE WTZONE NCELLS AREA AREAF WAREA WAREAF

3150107 11 1001 7 6300.0 0.00000124 1565538300.0 0.00000402

3150107 21 1001 173 155700.0 0.00003063 1565538300.0 0.00009945

3150107 22 1001 15 13500.0 0.00000266 1565538300.0 0.00000862

3150107 23 1001 34 30600.0 0.00000602 1565538300.0 0.00001955

3150107 25 1001 13 11700.0 0.00000230 1565538300.0 0.00000747

3150107 26 1001 63 56700.0 0.00001116 1565538300.0 0.00003622

3150107 33 1001 23 20700.0 0.00000407 1565538300.0 0.00001322

3150107 41 1001 10683 9614700.0 0.00189172 1565538300.0 0.00614147

3150107 42 1001 5878 5290200.0 0.00104086 1565538300.0 0.00337916

3150107 43 1001 12418 11176200.0 0.00219895 1565538300.0 0.00713889

3150107 62 1001 68 61200.0 0.00001204 1565538300.0 0.00003909

3150107 81 1001 2846 2561400.0 0.00050396 1565538300.0 0.00163611

3150107 82 1001 4564 4107600.0 0.00080818 1565538300.0 0.00262376

3150107 85 1001 83 74700.0 0.00001470 1565538300.0 0.00004772

3150201 11 1001 23525 21172500.0 0.00341868 1565538300.0 0.01352410

3150201 21 1001 9189 8270100.0 0.00133536 1565538300.0 0.00528259

3150201 22 1001 2257 2031300.0 0.00032799 1565538300.0 0.00129751

3150201 23 1001 4054 3648600.0 0.00058913 1565538300.0 0.00233057

3150201 25 1001 475 427500.0 0.00006903 1565538300.0 0.00027307

3150201 26 1001 6630 5967000.0 0.00096348 1565538300.0 0.00381147

3150201 31 1001 257 231300.0 0.00003735 1565538300.0 0.00014774

3150201 33 1001 27254 24528600.0 0.00396059 1565538300.0 0.01566784

3150201 41 1001 388320 349488000.0 0.05643116 1565538300.0 0.22323823

3150201 42 1001 291453 262307700.0 0.04235433 1565538300.0 0.16755112

3150201 43 1001 451679 406511100.0 0.06563858 1565538300.0 0.25966219

3150201 62 1001 9272 8344800.0 0.00134742 1565538300.0 0.00533031

3150201 81 1001 130100 117090000.0 0.01890630 1565538300.0 0.07479217

3150201 82 1001 224428 201985200.0 0.03261417 1565538300.0 0.12901965

3150201 85 1001 2572 2314800.0 0.00037377 1565538300.0 0.00147860

3150201 91 1001 122314 110082600.0 0.01777483 1565538300.0 0.07031613

3150201 92 1001 8840 7956000.0 0.00128464 1565538300.0 0.00508196

A one-to-many relation exists between the county-level 

tillage data and the cultivated land 8-digit HU/county weighting factors. When the two tables are merged, the weight table 

is populated with the county-level data so that all the portions 

of an HU that falls within a single county will be populated 

with the tillage data for that particular county.

Two dBase files were generated—tillage_lu92e.dbf based 

on the NLCDe 92 (appendix 1) and tillage_lu01.dbf based on 

the NLCD01 (appendix 2). Attribute definitions for the two 

dBase files are listed in table 2. The 8-digit HU watershed 

polygon coverage, wdbhuc8, provides a spatial reference for 

the tabular tillage data. The numeric value for the 8-digit HU, 

HUC8_N, is used as the unique identifier for the relate attribute between the spatial and tabular data. In the conterminous 

United States, HU codes range from 01010001 to 18100204. 

The numeric value for the 8-digit HU does not include the 

leading zero for HUs less than 10000000. 
8 Tillage Practices in the Conterminous United States, 1989–2004—Datasets Aggregated by Watershed

Table 2. Attribute labels and definitions for tillage_lu92e.dbf and tillage_lu01.dbf.

[NA, not applicable; WDBHUC8, water-data boundary 8-digit hydrologic unit code; GIS, Geographic Information System; CTIC, Conservation Technology Information Center]

Attribute label Attribute definition Units Source

huc8_n Numeric 8-digit hydrologic unit code identifier NA WDBHUC8 GIS coverage

crop Name of crop NA CTIC county-level survey

year Year crop was planted year CTIC county-level survey

notill No-till conservation tillage, greater than 30 percent of soil covered 

with crop residue

planted acres area-weighted interpolation

ridge Ridge-till conservation tillage, greater than 30 percent of soil covered 

with crop residue

planted acres area-weighted interpolation

mulch Mulch-till conservation tillage, greater than 30percent of soil covered 

with crop residue

planted acres area-weighted interpolation

reduced Reduced tillage (not considered conservation tillage), 

15 to 30 percent of crop residue left on soil

planted acres area-weighted interpolation

intense Intensive or conventional tillage, less than 15 percent residue left 

on soil

planted acres area-weighted interpolation

totacre Total planted acres (sum of all tillage types) planted acres calculated 

pctnotil Percentage of no-till acres (no till / totacre) *100 percent calculated 

pctridge Percentage of ridge-till acres (ridge till / totacre) *100 percent calculated 

pctmulch Percentage of mulch-till acres (mulch till / totacre) *100 percent calculated 

pctreduc Percentage of reduced-till acres (reduced till / totacre) *100 percent calculated 

pctinten Percentage of intensive-till acres (intensive till / totacre) *100 percent calculated 

Tillage-Practice Datasets Aggregated 

to 8-Digit Hydrologic Unit Watersheds

In order to evaluate the results of aggregating countylevel tillage surveys to the 8-digit HUs, manual calculations of 

selected HUs were made to ensure that the automated interpolation was done correctly, and the original county-level data 

were compared to the 8-digit HU aggregation to ensure that 

the results of the aggregation reliably reflect the original data. 

In addition, the original data were compared to other independently collected data. 

Aggregated data for selected HUs were compared to values manually calculated for the associated CTIC county and 

crop acreages. Manual calculation of weighting factors and 

application to CTIC tillage-practice acreages for the counties 

within selected HUs shows that the automated procedures for 

the cultivated-land area-weighted interpolation performed the 

interpolation and aggregation correctly.

Visually comparing the results of the original countylevel data with the aggregated data indicates that the aggregation to an 8-digit HU watershed reliably reflects the original 

data (fig. 4). Slight differences exist between the county-level 

and HU-level data. In the west where counties generally are 

larger than 8-digit HU watersheds, the shaded areas on the 

county map may extend to a larger area than that shown on 

the watershed map. Conversely, in areas where the counties 

are smaller than 8-digit HU watersheds, the shaded areas on 

the watershed map cover a larger extent than on the county 

map (fig. 4).

Comparisons were made of the original CTIC 

data to independently collected State-level tillage data. 

The U.S. Department of Agriculture (USDA)–Economic 

Research Service (ERS) compiles limited State-level tillage 

data for selected states and crops from 1990 through 2000 

(fig. 5). The ERS conducts farm surveys from a representative sample of farms to estimate the percentage of tillage 

practices for the State and then multiplies the percentage 

of each tillage practice by NASS estimates of crop acreage 

(U.S. Department of Agriculture–Economic Research Service, 

1997 and 2010). The CTIC uses a similar method but conducts their surveys independently from the ERS. A graphical 

comparison for selected crops and years between the CTIC 

and ERS tillage data shows good agreement between the two 

datasets at the State level (fig. 5). 
Tillage-Practice Datasets Aggregated to 8-Digit Hydrologic Unit Watersheds 9

Percent no-till

 0 −10 

10 − 25 

25 − 50 

50 − 100 

A. All crops

B. Corn

C. Soybeans

County 8-digit hydrologic unit watershed

Percent no-till

 0 −10 

10 − 30 

30 − 50 

50 − 100 

White areas represent

counties with less than

10,000 cropland acres

White areas represent

counties with less than

10,000 cropland acres

Percent no-till

White areas represent

counties with less than

10,000 cropland acres

 0 −10 

10 − 50 

50 − 75 

75 − 100 

Figure 4. Comparison of the original Conservation Technology Information Center county-level data and 8-digit hydrologic unit 

watershed-level data for the percentage of no-till on A all crops, B corn, and C soybeans for the conterminous United States, 2004
0 2,000 4,000 6,000 8,000 10,000 12,000 14,000

Planted acreage, in thousand acres

E C E C E C E C E C

Illinois Indiana Iowa Michigan Minnesota

Corn, 1993

0

2,000

4,0006,000

8,000

10,00012,00014,000

E C E C E C E C E C E C E C E C E C E C 

Planted acreage, in thousand acres

Illinois IndianaIowaKansas Kentucky Michigan Minnesota Missouri Nebraska North CarolinaO

P

0

2,0004,0006,0008,000

10,00012,00014,000

E C E C E C E C E C E C E C E C E C E C E C E C E C E C E C E C

Planted acreage, in thousand acres

Illinois IndianaIowaKansas Kentucky Michigan Minnesota Missouri Nebraska North CarolinaOhio South DakotaTexas Wisconsin

Corn, 1998

Colorado Pennsylvania

0

2,0004,0006,0008,000

10,00012,00014,000

Planted acreage, in thousand acres

E C E C E C E C E C E C E C E C E C E C E C E 

Illinois IndianaIowa Kansas Kentucky Michigan Minnesota Missouri Nebraska North Carolin

Colorado

New York Nort

Conventional

ReducedRidge

MulchNo till 

Tillage practice

EXPLANATION

Data source E Economic Research

 Service

C Conservation Technology

 Information Center

Figure 5. Comparison of Economic Research Service (E) and Conservation Technology Information Center (C) estimates of total planted acreages, by 

for corn for 1993, 1996, 1998, and 2000. [Source: U.S. Department of Agriculture-Economic Research Service, 1997 and 2010; Karen Scanlon, Executive D

Technology Information Center, written commun., 2010]
0

2,0004,0006,0008,000

10,00012,000

E C E C E C E C E C

Arkansas Indiana Iowa Illinois Minnesota

Soybeans, 1993

E C

Missouri

0

2,000

4,0006,0008,000

10,000

12,000

E C E C E C

Arkansas Indiana Iowa Illinois Minnesota

Missouri

E C E C E C E C E C 

LouisianaMississippi N

E C E C E C E C E C E C E C E C E C E C E C E C E C E C

Illinois IndianaIowaKansas KentuckyMichigan MinnesotaMissouri Nebraska North CarolinaOhio South Dakota Tennessee Arkansas

E C E C

0

2,0004,0006,0008,000

10,00012,000

Soybeans, 1998

Louisiana Mississippi

E C E C E C E C E C E C E C E C E C E C E C E 

Illinois IndianaIowa Kansas KentuckyMichigan MinnesotaMissouri Nebraska North 

Arkansas 

0

2,0004,0006,0008,000

10,000

12,000

Planted acreage, in thousand acres

LouisianaMississippi

Planted acreage, in thousand acres

Planted acreage, in thousand acres Planted acreage, in thousand acres

Conventional

ReducedRidge

MulchNo till 

Tillage practice

EXPLANATION

Data source E Economic Research

 Service

C Conservation Technology

 Information Center

Figure 5 (cont). Comparison of Economic Research Service (E) and Conservation Technology Information Center (C) estimates of total planted acreagpractice for soybeans for 1993, 1996, 1998, and 2000. [Source: U.S. Department of Agriculture-Economic Research Service, 1997 and 2010; Karen ScanloConservation Technology Information Center, written commun., 2010]
12 Tillage Practices in the Conterminous United States, 1989–2004—Datasets Aggregated by Watershed

Summary

The Conservation Technology Information Center (CTIC) 

proprietary county-level tillage data were aggregated to 

8-digit hydrologic unit (HU) watersheds and made available 

for inclusion in U.S. Geological Survey (USGS), National 

Water-Quality Assessment (NAWQA) supported analyses. A 

cultivated-land area-weighted interpolation, based on the 1992 

enhanced and 2001 National Land Cover Data (NLCDe 92) 

and (NLCD01), respectively, was done to calculate weighting 

factors for each county/HU combination. Weighting factors 

then were multiplied by county-level tillage data and aggregated by HU to yield tillage-practice acreages for selected 

crops for each 8-digit HU in the conterminous United States. 

Two tabular datasets were generated and included planted 

acreage of conservation tillage (includes no-till, ridge-till, 

and mulch-till), reduced tillage, and intensive or conventional 

tillage for selected crops (corn, cotton, grain sorghum, soybeans, fallow, forage, newly established permanent pasture, 

spring and fall seeded small grains, and “other” crops) by 

HU for 1989–2004. 

The 8-digit HU watershed polygon coverage is the spatial 

reference for the two tabular datasets. The tabular datasets can 

be related to the watershed polygons by the numeric value of 

the unique 8-digit HU code (HUC8_N). 

Comparison of results for 8-digit HU watershed 

aggregation and the original county-level data shows that the 

aggregation reliably reflects the original data. Manual calculations of weighting factors for selected HUs were done to 

ensure the automated calculations were done correctly. Comparison of the original data with tillage data independently 

collected by the Economic Research Service also was done.

References Cited 

Conservation Technology Information Center, 2004, 

2004 National crop residue management survey: 

Conservation Technology Information Center, 

West Lafayette, Ind., accessed September 2009 at 

www.ctic.purdue.edu.

Conservation Technology Information Center, 2007, Tillage 

type definitions: Conservation Technology Information 

Center, West Lafayette, Ind., accessed September 2009 at 

http://www.ctic.purdue.edu/media/pdf/TillageDefinitions.pdf

LaMotte, Andrew, 2008, National land cover database 2001 

(NLCD01), Tiles 1–4: U.S. Geological Survey Data Series 

383a, accessed November 2008 at http://water.usgs.gov/

GIS/metadata/usgswrd/XML/nlcd01_1.xml.

Nakagaki, Naomi, Price, C.V., Falcone, J.A., Hitt, K.J., and 

Ruddy, B.C., 2007, Enhanced national land cover data 1992 

(NLCDe 92), Tiles 1–4: U.S. Geological Survey digital 

raster data, accessed June 2010 at http://water.usgs.gov/GIS/

metadata/usgswrd/XML/nlcde92.xml.

Price, C.V., Nakagaki, Naomi., and Hitt, K.J., 2010, 

The National Water-Quality Assessment (NAWQA) 

Area-Characterization Toolbox, Release 1.0: 

U.S. Geological Survey Open-File Report 2010–1268, 

accessed June 2010 at http://pubs.usgs.gov/of/2010/1268.

U.S. Department of Agriculture, Economic Research Service, 

1997, Cropping practices, 1990–95, accessed September 

2010 at http://www.ers.usda.gov/data/archive/93018/.

U.S. Department of Agriculture, Economic Research 

Service, 2010, Farm Business and Household Survey 

data: Customized Data Summaries from ARMS, Tailored 

Reports, Crop Production Practices, accessed September 

2010 at http://www.ers.usda.gov/Data/ARMS/app/default.

aspx?survey=CROP#startForm 

U.S. Geological Survey, 2008a, (NLCD) 1992/2001 retrofit land cover change product multi-zone download 

site, Multi-Resolution Land Characteristics Consortium (MRLC), National Land Cover Database, accessed 

September 2010 at http://www.mrlc.gov/multizone.php.

U.S. Geological Survey, 2008b, NLCD 2001 land cover class 

definitions, Multi-Resolution Land Characteristics Consortium (MRLC), National Land Cover Database, accessed 

September 2010 at http://www.mrlc.gov/nlcd_definitions.php.

U.S. Geological Survey, 2010, NLCD land cover class 

definitions, The USGS Land Cover Institute, accessed 

September 2010 at http://landcover.usgs.gov/classes.php. 

U.S. Geological Survey and U.S. Department of Agriculture–

Natural Resources Conservation Service, 2009, Federal 

guidelines, requirements, and procedures for the national 

Watershed Boundary Dataset: U.S. Geological Survey 

Techniques and Methods 11–A3, 55 p., report available at 

http://pubs.usgs.gov/tm/tm11a3/ ; geospatial data accessed 

November 2009 at http://www.ncgc.nrcs.usda.gov/products/

datasets/watershed/. 
Appendixes 1–3. Tillage Practices 

in the Conterminous United States, 1989–2004—

Datasets Aggregated by Watershed

1. This dBase tabular dataset is based on the 1992 enhanced National Land Cover Data. This 

dataset is intended to be used with the 8-digit watershed boundary data (WBDHUC8, provided 

below) which shares the common attribute HUC8_N. This tabular data can be linked (joined or 

related) to the WBDHUC8 dataset by the HUC8_N attribute. 

Download data here: http://water.usgs.gov/GIS/metadata/usgswrd/XML/ds573_tillage_lu92e.xml

2. This dBase tabular dataset is based on the 2001 National Land Cover Data. This dataset is 

intended to be used with the 8-digit watershed boundary data (WBDHUC8, provided below) which 

shares the common attribute HUC8_N. This tabular data can be linked (joined or related) to the 

WBDHUC8 dataset by the HUC8_N attribute. 

Download data here: http://water.usgs.gov/GIS/metadata/usgswrd/XML/ds573_tillage_lu01.xml

3. This is the companion dataset to be used with the tabular dBase tillage practice datasets 

above. The WBDHUC8 is derived from the 12-digit Watershed Boundary Data and includes the 

attribute HUC8_N. HUC8_N is the common attribute used to link the tabular dBase data files above 

to this geospatial dataset. 

Download the WBDHUC8 here: http://water.usgs.gov/GIS/metadata/usgswrd/XML/ds573_wbdhuc8.xml
Baker—Tillage Practices in the Conterminous United States, 1989–2004—Datasets Aggregated by Watershed—Data Series 573