Predicting

RAINFALL-EROSION LOSSES

FROM CROPLAND

EAST OF THE ROCKY MOUNTAINS

Guide for Selection of Practices

for Soil and Water Conservation

AGRICULTURE HANDBOOK NO. 28 2

AGRICULTURAL RESEARCH SERVICE-U.S. DEPARTMENT OF AGRICULTURE

IN COOPERATION WITH PURDUE AGRICULTURAL EXPERIMENT STATION
CONTENTS

Page

Purpose of handbook 1

History of soil-loss equations 1

Sou-loss tolerances 2

The soil-Joss equation 3

The equation model 3

The rainfaU factor (Ä) 3

The soil-erodibility factor (K) 4

Factors for slope length (L) and gradient (S) 8

The cropping-management factor (C) 10

The erosion-control practice factor (P) 36

Limitations 38

Page

Field applications of the soil-loss equation 38

Predicting field soil loss 38

Determining alternative ways in which a particular

tract of land may be used and treated to conserve

or improve it 40

Estimating source sediment from watersheds 41

Summary 43

Literature cited 44

Appendix 45

LIST OF TABLES

Page

TABLE 1.—Computed A" values for soils on erosion-research stations 5

TABLE 2.—Ratio of soil loss from cropland to corresponding loss from continuous fallow 12

TABLE 3.—Suggestions for approximating soil-loss ratios for cropping and management combinations not listed in

table 2 15

TABLE 4.—Approximations of soil-loss ratios for crop-stage periods and number of tillage operations with stubble

mulching and summer fallowing in western Plains areas 16

TABLE 5.—Working table for derivation of C value for 4-year rotation in central Indiana 35

TABLE 6.—Practice factor values for contouring 36

TABLE 7.—Length limits for contouring 37

TABLE 8.—Strip widths recommended for contours 37

TABLE 9.—Maximum permissible C values (T/RKLS) for indicated gradient and slope length with straight and

with contoured rows for sou type with K, T, and R values as listed 42

TABLE 10.—Partial list of C values for common rotations for a specific erosion-index distribution area 43

TABLE 11.—Obsei^'^ed range and 5-, 20-, and 50-percent probability value of erosion index at each of 181 key locations. 45

TABLE 12.—Expected magnitudes of single-storm erosion-index values 46

Washington, D.C. Issued May 1966

For sale by the Superintendent of Documents, U.S. Government Printing Office,

Washington, D.C. 20402 Price 30 cents

UI
PREDICTING RAINFALL-EROSION LOSSES FROM

CROPLAND EAST OF THE ROCKY MOUNTAINS

Guide for Selection of Practices for Soil and Water Conservation

By WALTER H. WISCHMEIER and DWIGHT D. SMITH, Soil and Water Conservation Research Division, Agricultural

Research Service

PURPOSE OF HANDBOOK

Scientific farm planning for sou and water

conservation requires knowledge of the relations

1 between those factors that cause loss of soil and

; water and those that help to reduce such losses

on cropland. Since 1930, controlled studies on

field plots and small watersheds have supplied

much valuable information regarding these complex factor interrelations. But the greatest possible benefits from such research efforts can be

realized only when the findings are rapidly converted to sound practice on the numerous farms

throughout the country. Specific guidelines are

needed to help select the control practices best

suited to the particular needs of each farm.

The soil-loss prediction procedure presented in

this handbook provides such guidelines. It is a

technique whereby all pertinent research information is methodically combined to provide design

data for conservation plans.

The empirical soil-loss equation underlying this

technique is applicable in any location where numerical values of the equation's factors are known

or can be determined. Research has supplied information from which at least approximate values

of these factors can be derived for any location in

the major agricultural areas of the United States.

Tables and charts make this information readily

available for field use.

Research is continuing to obtain more complete

and more precise information on the interrelations

of topography, sou, and management practices.

Additional knowledge gained can be readuy

brought into the present prediction procedure.

Experience has shown, however, that the factor

values reported herein are sufficiently accurate to

provide very valuable guidelines for conservation

farm planning and to aid in estimating gross

erosion from watersheds.

The soil-loss equation in its present form is the

result of more than 20 years of development and

has had many contributors.

HISTORY OF SOIL-LOSS EQUATIONS

Development of equations for calculating field

soil loss began about 1940 in the Com Belt

States. The soil-loss estimating procedure developed in that region between 1940 and 1956

has been generally referred to as the slope-practice

method. Zingg (38) ^ published an equation in

1940 relating soil-loss rate to length and percentage of slope. In the following year, Smith (12)

added crop and conservation-practice factors and

the concept of a specified sou-loss limit, to develop a graphical method for determining conservation practices needed on the Shelby and

associated soils of the Midwest. Browning and

coworkers (1) added soil erodibility and management factors and prepared a set of tables to

simplify field use of the equation in Iowa. Other

Ï Italic numbers in parentheses refer to Literature

Cited, p. 44.

advances and adaptations of the procedure in

the Com Belt were made by Smith and Whitt

(13, 14) and by Van Doren and Bartelli (19),

Research scientists and operations personnel in

the North Central States worked together in developing the slope-practice method for use

throughout the Corn Belt States.

In 1£46, a nationwide committee on soil-loss

prediction met in Ohio for the purpose of adaptmg the Corn Belt equation to other cropland

areas with erosion problems. This committee

reappraised the Corn Belt factor values and added

a rainfall factor (9). The resulting formula,

generally known as the Musgrave equation, has

been widely used for estimating gross erosion from

watersheds in flood abatement programs. A

graphical solution of the equation was published in

1952 by Lloyd and Eley (5) and used by the Soil

Conservation Service in the Northeastern States.
AGR. HANDBOOK 2 82, U.S. DEPARTMENT OF AGRICULTURE

Years of field experience by the Soil Conservation Service in the Com Belt and the Northeastern States proved the value of soil-loss

prediction as a tool to help guide conservation

farm planning. Extension of the usefulness of

these equations to new areas was seriously hampered by the lack of procedures and basic information for adjusting measured factor values for

differences in rainfall distribution, types of rainstorms expected, localized farming methods,

length of growing season, and other variables.

An improved soil-loss equation developed in the

latter part of the 1950's (7<S, 26) overcame many

of the limitations of the earlier equations. The

improved equation was developed at the Runoff

and Soil-Loss Data Center of the Agricultural

Research Service, established at Purdue University in 1954. Most of the basic runoff and soil-loss

data obtained in studies in the United States

since 1930 were assembled at this location for

summarization and further analyses.^ These

analyses resulted in several major improvements

that were incorporated in the new soil-loss

equation: (1) an improved rainfall-erosion index

(31); (2) a method of evaluating croppingmanagement effects on the basis of local climatic

conditions (22) ; (3) a quantitative soil-erodibility

factor; and (4) a method of accounting for effects

of interrelations of such variables as productivity

level, crop sequence, and residue management.

These developments freed the equation from

some of the generalizations and the geographic and

climatic restrictions inherent in earlier models.

Because of its general applicability, the improved

equation presented in this handbook has been

referred to in some of the literature as the '^universal'' soil-loss equation (Í0, 16, 17y 18, 26).

SOIL-LOSS TOLERANCES

The term ^^soil-loss tolerance'' is used to denote

the maximum rate of soil erosion that will permit

a high level of crop productivity to be sustained

economically and indefinitely. This rate has usually been expressed in terms of average soil loss

per acre per year. Knowledge of the expected

rate of sou erosion for each of various alternative

cropping systems and management plans on any

particular field may be obtained by use of the

erosion equation. When these predicted losses

can be compared with a soil-loss tolerance for

that field, very specific guidelines are provided

for effecting erosion control within the specified

limits. Any cropping and management combination for which the predicted erosion rate is less

than the tolerance may be expected to provide

satisfactory erosion control. From the various

satisfactory^ alternatives indicated by the soil-loss

prediction procedure, the farmer may then select

2 Data used to develop the present equation and supporting tables and charts were contributed by personnel

on Federal-State cooperative research projects at the following locations: Batesville, Ark.; Tifton and Watkinsville, Ga.; Dixon Springs, Joliet, and Urbana, 111.; Lafayette, Ind.; Clarinda, Castaña, Beaconsfield, Independence, and Seymour, Iowa; Hays, Kans.; Baton Rouge,

La.; Presque Isle, Maine; Benton Harbor and East Lansing, Mich.; Holly Springs and State College, Miss.;

Bethany and McCredie, Mo.; Hastings, Nebr.; Beemerville, Marlboro, and New Brunswick, N.J.; Ithaca,

Geneva, and Marcellus, N.Y.; Statesville and Raleigh,

N.C.; Coshocton and Zanesville, Ohio; Cherokee and

Guthrie, Okla.; State College, Pa.; Clemson and Spartanburg, S.C.; Knoxville and Greeneville, Tenn.; Temple

and Tyler, Tex.; Blacksburg, Va.; Pullman, Wash.;

LaCrosse, Madison, and Owen, Wis.; and Mayaguez, P.R.

Rainfall data for development of the iso-erodent map and

erosion-index distribution curves were supplied by the U.S.

Weather Bureau, National Records Center.

the land use and management comibination best

suited to his particular farm enterprise.

Establishment of tolerances for specific soils and

topography has been largely a matter of collective

judgment. Both physical and economic factors

are considered. For the soils in the United

States, the maximum soil-loss rates thus determined range from 1 to 5 tons per acre per year,

depending upon soil properties, soil depth, topography, and prior erosion. A deep, mediumtextured, moderately permeable soil that has subsoil characteristics favorable for plant growth has

a tolerance of 5 tons per acre. Tolerances for

soils with a shallow root zone, or with a high

percentage of shale at the surface, are usually

quite low.

Soil-loss tolerances for the major soil types were

subjectively evaluated at regional Soil-Loss Prediction Workshops, and lists were distributed in

the workshop reports.^

3 ARS-SCS Soil Loss Prediction Workshop Reports:

1959. Soil loss estimation in Tennessee. Knoxville,

Tenn.

, 1960. Soil loss estimation in the Southeast. Athens,

Ga.

1961. Soil loss prediction, North Dakota, Nebraska,

and Kansas. Lincoln, Nebr.

1961. Soil loss prediction for Arkansas, Louisiana,

Mississippi, Oklahoma, and Texas. Little Rock,

Ark.

1962. Soil loss prediction for the North Central States.

Chicago, 111.

1962. Soil loss prediction for the Northeastern States.

New York, N.Y.

These reports are mimeographed, but may be available

either from the Agricultural Research Service or the Soil

Conservation Service.
RAINFALL-EROSION LOSSES FROM CROPLAND

THE SOIL-LOSS EQUATION

The Equation Model

The soil-loss equation is

A=R K L S C P

where A is the computed soil loss per unit area.

Ä, the rainfall factor, is the number of erosion-index units in a normal ^^ear^s rain.

The erosion index is a measure of the

erosive force of specific rainfall.

Kj the soil-erodibility factor, is the erosion

rate per unit of erosion index for a specific soil in cultivated continuous fallow,

on a 9-percent slope 72.6 feet long. The

reasons for selection of these conditions

as unit values is explained in the detailed discussion of this factor.

Lj the slope-length factor, is the ratio of

soil loss from the field slope length to

that from a 72.6-foot length on the same

soil type and gradient.

S, the slope-gradient factor, is the ratio of

soil loss from the field gradient to that

from a 9-percent slope.

Cy the cropping-management factor, is the

ratio of soil loss from a field with specified cropping and management to that

from the fallow condition on which the

factor K is evaluated.

Pj the erosion-control practice factor, is

the ratio of soil loss with contouring,

stripcropping, or terracing to that with

straight-row farming, up-and-dovni slope.

Numerical values for each of the six factors

have been determined from research data. These

values differ from one field or locality to another.

The approximate numerical values for any particular field may be obtained from the figures

and tables presented herein.

The subsection entitled ''Predicting Field Soil

Loss," page 38, illustrates how to select appropriate values from the figures and tables. The

reader who has had no prior experience with the

soil-loss equation may wish first to read that

section. After he has referred to the tables and

figures and located the values used in the example,

he will be able to understand the intervening

detailed discussions of the equation's factors.

In actual practice, the equation is usually not

solved in selecting practices for each farm field.

In many locations, persons experienced in the use

of the equation have prepared reference tables

that provide the information needed for the

specific locality.

The soil-loss prediction procedure can be more

intelligently used as a guide for selection of practices 3 the user has a general knowledge of the

principles and factor interrelations on which the

equation is based. Therefore, the significance of

each factor is discussed before presenting the

ready-reference table or chart from which locational values of that factor may be obtained.

Limitations of the data available for evaluation

of some of the factors are also pointed out.

The Rainfall Factor (R)

One major difference between the universal

soil-loss equation and its predecessors is in the

manner and precision with which locational differences in rainfall are brought into the soil-loss

computations. The Com Belt slope-practice

equation was based on an overall average of the

severity and distribution of the rainfall that occurred on the plot studies in that region. This

average rainfall effect was reflected in an 8-ton

base soil-loss rate for a 3-year rotation of com,

oats, and meadow. The Musgrave equation assumed that the erosivity of annual rainfaU varied

as the 1.75 power of the 2-year maximum 30-

minute rainfall. This relation was based on

limited data taken in Wisconsin in the 1930's.

Research since 1946 has not supported the accuracy of this term as an indicator of annual

rainfall erosivity. Furthermore, its use as a

rainfall factor allowed no consideration of effects

of locational differences in the number of erosive rainstorms and in their expected distribution

within the year.

Rills and sediment deposits observed after an

unusually intense storm could lead to the conclusion that the significant soil erosion is associated with only a few rare storms. However,

more than 30 years of measurements in many

States have shown that such is not the case (24)-

The data showed that a rainfall factor used to

estimate average annual soil loss must include

the cmnulative effects of the many moderate-size

storms, as well as the effects of the occasional verysevere ones.

The rainfall factor in the soil-loss equation is

the rainfall erosion index reported by Wischmeier

in 1959 (21), Locational values of this factor

were published in 1962 in the form of an isoerodent map {23).

The Rainfall Erosion Index

Exploratory analyses of the large volume of

soil loss and rainfall data assembled at the Runoff and Soil Loss Data Center brought out a

very helpful relation between soil loss and a single rainstorm.parameter. The research data show

that when factors other than rainfall are held

constant, storm soil losses from cultivated fields

are directly proportional to the product value of

two rainstorm characteristics: total kinetic energy

of the storm times its maximum 30-minute intensity (El). This product variate is an interaction term that reflects the combined potential
AGR. HANDBOOK 2 82, U.S. DEPARTMENT OF AGRICULTURE

of raindrop impact and turbulence of runoff to

transport dislodged soil particles from the field.

The value of this statistic for any particulai rainstorm can be computed from a recording-raingage record with the help of a rainfall energy

table published in 1958 (25).

The smn of the computed storm El values for

a given time period is a numerical measure of the

erosivity of all the rainfall within that period.

The rainfall erosion index at a particular location

is the longtime-average yearly total of the storm

El values. The storm El values reflect the interrelations of significant rainstorm characteristics.

Smnming these values to compute the erosion

index adds the effect of frequency of erosive storms

within the year.

Iso-Erodent Map

Locational values of the rainfall factor, i?, may

be taken directly from the iso-erodent map reproduced in figure 1. The lines joining points

with the same erosion-index value (which implies

equally erosive average annual rainfall) are called

iso-erodents. The average number of erosionindex units per year along each iso-erodent is the

value of R in the erosion equation. Points lying

between the indicated iso-erodents may be approximated by linear interpolation.

To develop the map, the locational value of the

erosion index was computed from rainfall data for

each of about 2,000 locations fairly evenly distributed over the 37 States. The iso-erodents were

then plotted as indicated by these values (23).

Iso-erodents in the mountainous States west

of the 104th meridian were not included because

of the sporadic rainfall pattern of the mountains.

In this area, one weather station may average

fewer than 10 inches of rain per year, whereas

another station less than 100 miles away averages

more than 25 inches. Locational erosion-index

values are probably equallj' sporadic, but are not

directly proportional to rain amounts. A verylarge number of locational rain-intensity records

would be required to establish iso-erodents in the

mountainous States. In the scattered agricultural areas where rainfall is sufficient to pose an

erosion hazard, locational values of the erosion

index can be computed from rainfall records

within those specific areas, but a few spot values

of the index should not be considered representative of a large geographic area.

The iso-erodent map shows that erosion-index

values in the 37 States range from 50 to 600. The

erosion index measures only the effect of rainfall

when separated from all other factors that influence erosion. If the soil and topography were

exactly the same everywhere, average annual soil

losses from plots maintained in continuous fallow

would differ in direct proportion to the erosionindex values. This potential difference is, however, partially offset by differences in soil, topography, vegetal cover, and residues. On fertile

sods in the high rainfall areas of the Southern

States, good vegetal cover protects the soil surface throughout most of the year and heavy plant

residues may provide excellent cover also during

the dormant season. In the regions where the

erosion index is extremely low, rainfall is seldom

adequate for establishment of meadows and good

cover provided by other crops is often limited to

only a relatively short period. Hence, serious

soil-erosion hazards exist in semiarid regions as

well as in humid.

In areas such as the Pacific Northwest, where

snowmelt causes a large part of the field erosion,

the practical value of the rainfall-erosion equation

in its present form has not been established.

Probability Values of the Erosion Index

When the erosion equation is used to estimate

average annual soil loss, the value of the factor R \

must equal the average annual value of the ero- <

sion index at that location as obtained from the

iso-erodent map. If desired, however, some

specific probability value of the erosion index,

other than annual averages, may be substituted

for R in the equation. For example, the quantity of soil loss that will be exceeded 1 year in 5,

on the average, may be estimated by assigning to

R the 20-percent probability of the erosion index.

The 50-percent, 20-percent, and 5-percent

probability values of the index at 181 key locations are shown in appendix table 11.

To approximate the amount of soil loss from

a single storm that wiU probably be exceeded

once in 1, 2, 5, 10, or 20 years, the factor R may

be assigned a value selected from appendix table

12. For this purpose, however, the value of C

should be determined as indicated under ^'Individual-Storm Sou Losses.''

The Soü-Erodibility Factor (K)

The meaning of the term "soil erodibility" is

distinctly different from that of the term ''soil

erosion.'' The rate of sou erosion on any area

may be influenced more by land slope, rainstorm

characteristics, cover, and management than by

properties of the soil itself. The total rate of

soil loss is designated by the symbol A in the

equation. But some soils erode more readily

than others even when slope, rainfall, cover, and

management are the same. This difference, due

to properties of the soil itself, is referred to as the

soil erodibility.

Soil properties that influence erodibility by

water are (1) those that affect the infiltration

rate, permeability, and total water capacity, and

(2) those that resist the dispersion, splashing,

abrasion, and transporting forces of the rainfall

and runoff. A number of attempts have been

made to determine criteria for scientific class-
RAINFALL-EROSION LOSSES FROM CROPLAND

ification of soils according to erodibility (4, 6, 7,

11, 16), Generally, however, soil classijRcations

used for erosion prediction have been largely

subjective and have been only relative rankings.

The relative erodibility of different soils is

difficult to judge from field observations. Even

a soil with a relatively low erodibility factor may

show signs of serious erosion when the soil occurs

on long or steep slopes or in localities having

numerous high-intensity rainstorms. A soil with

a high natural erodibility factor, on the other

hand, may show little evidence of actual erosion

under gentle rainfall when it occurs on short and

gentle slopes or when the best possible management is practiced. The effects of rainfall differences, slope, cover, and management are

accounted for in the prediction equation by the

symbols Ä, i, S, C and P. Therefore, the

soil-erodibility factor, K, must be evaluated independently of the effects of the other factors.

Definition of the Factor K

The soil-erodibility factor, iC, in the soil-loss

equation is a quantitative value, experimentally

determined. For a particular soil, it is the rate

of erosion per unit of erosion index from unit

plots on that soil.

A unit plot is 72.6 feet long, with a uniform

lengthwise slope of 9 percent, in continuous

fallow, tilled up and down the slope. Continuous fallow, for this purpose, is land that has

been tiUed and kept free of vegetation for a

period of at least 2 years or until prior crop

residues have decomposed. During the period of

soil-loss measurements, the plot is plowed and

placed in conventional com seedbed condition

each spring and is tilled as needed to prevent

vegetal growth or serious surface crusting.

When all of these conditions are met, each of

the factors Z, S, (7, and P has a value of 1.0

and K equals AjEL

The conditions Usted above were selected as

unit values in the soil-loss equation because they

represent the predominant slope length and the

median gradient on which past erosion measurements in the United States have been made, and

the designated management provides the surface

condition least influenced by differences in climate and local cropping systems.

Direct measurements of K on well replicated

unit plots as described should reflect the combined effects of all the variables that significantly

influence the ease with which a soil is eroded by

rainfall and runoff. To evaluate K for soils that

do not usually occur on a 9-percent slope, soil-loss

data from plots that meet aU the other specified

conditions are adjusted to 9-percent slope by

means of the slope factor.

760-705 O—05 2

Values of K

yalues of K determined for 23 major soils on

which erosion plot studies were conducted since

1930 are listed in table 1. Seven of these values

are from continuous fallow. The others are from

row crops averaging 20 plot-years of record per

location and requiring a minimum of adjustment

for management effects {10).

TABLE 1.—Computed K values for soils on erosionresearch stations

Soil Source of data

Computed

K

Dunkirk silt loam

Keene silt loam

Geneva, N.Y

Zanesville, Ohio

Bethany, Mo

Blacksburg, Va

LaCrosse, Wis

Watkinsville, Ga

Clarinda, Iowa

Castaña, Iowa

Hays, Kans

10. 69

48

Shelby loam. _ 41

Lodi loam . 39

Fayette silt loam. 1 . 38

Cecil sandy clay loam

Marshall silt loam

Ida silt loam

.36

.33

. 33

Mansic clay loam _ __ _ . 32

Hagerstown silty clay loam.

Austin clay_ _.

State College, Pa

Temple, Tex

McCredie, Mo

Marcellus, N.Y

Clemson, S.C

Geneva, N.Y

Watkinsville, Ga

Tyler, Tex

1 .31

. 29

Mexico silt loam _ . 28

Honeoye silt loam

Cecil sandV loam _

1.28

1. 28

Ontario loam 1. 27

Cecil clay loam _ _ _ __ . 26

Boswell fine sandy loam _. . 25

Cecil sandy loam

Zaneis fine sandy loam

Tifton loamy sand

Watkinsville, Ga

Guthrie, Okla

Tifton, Ga

.23

.22

. 10

Freehold loamy sand

Bath ñaggy silt loam with

Marlboro, N.J

Arnot, N.Y

.08

1 . 05

surface stones >2 inches

removed.

Albia gravelly loam Beemerville, N.J .03

1 Evaluated from continuous fallow. All others were

computed from row-crop data.

Other soils on which valuable erosion studies

have been conducted (see footnote 2, p. 2) were

not included in the table because of uncertainties

involved in adjustments of the data for effects of

cropping and management. Short periods of

record from plots cropped to rotations that provide good canopy or residue protection most of

the time cannot presently serve for authentic

evaluation of X, even though the studies were

well designed and provided valuable data for

evaluation of other factors in the equation.

Soil-erodibihty values for numerous other soils

have been approximated by considering a soil's

characteristics and tempering the estimate of its

erodibility against the estabhshed values for the

23 soils listed in table 1. Such estimated values

for all the major soils in the several major geographic regions were prepared at joint ARS-SCS

Regional Soil-Loss Prediction Workshops.^

* See footnote 3, p. 2.
6 AGE. HANDBOOK 282, U.S. DEPARTMENT OF AGRICULTURE

106* 104« 102* 100' 96* 94- 90* ee* 8Z* 80«

FIGURE 1.—Average annual
RAINFALL-EROSION LOSSES FROM CROPLAND

values of the rainfall factor, R.
8 AGR. HANDBOOK 2 82, U.S. DEPARTMENT OF AGRICULTURE

Increased research efforts, begun in 1961 at

several locations, are designed to identify and

evaluate the various soil properties that influence

erodibility. Additional benchmark values are also

being obtained by direct measurement of K on

imit plots.

Factors for Slope Length (L) and

Gradient (S)

The rate of soil erosion by water is very much

affected by both slope length and gradient (percent slope). The two effects have been evaluated

separately in research and are represented in the

erosion equation by L and S, respectively. In

field application of the equation, however, it

is convenient to consider the two as a single

topographic factor, LS.

The Slope-Effect Chart

The factor LS is the expected ratio of soil loss

per unit area on a field slope to corresponding loss

from the basic 9-percent slope, 72.6 feet long.

This ratio, for specific combinations of slope length

and gradient, may usually be taken directly from

the slope-effect chart (fig. 2). For example, a 10-

percent slope, 360 feet long, would have an LS

ratio of 2.6.

When the equation is used as a guide for selection of practices on an area where several slopes

are combined into a single field, the slope characteristics of the most erosive significant segment

of the field should be used for figure 2. Use of

field averages on such slope complexes would

imderestimate soil movement on significant parts

of the field.

The slope-effect chart assumes essentially uniform slopes. Field slopes are often either convex

(steepening substantially toward the lower end)

or concave (flattening toward the lower end).

The effect of convexity or concavity of slopes on

soil-erosion rates has not been fully evaluated.

However, limited data indicate that use of the

average gradient of the entire slope length would

substantially imderestimate soil loss from the con6

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___„ — - - - - — — —- - — "^

^ "— —

2 %

A

— ____ _

100 200 300 400 500

Slope Length (Feet)

600 700 800

FIGURE 2.—Slope-effect chart (topographic factor, LS).
RAINFALL-EROSION LOSSES FROM CROPLAND

vex slopes and would overestimate the loss from

concave slopes. When the lower end of the slope

is steeper than the upper end, the gradient of the

steeper segment should be used with the overall

slope length to enter the slope-effect chart. On

a concave slope, deposition may occur on the

lower end of the field. In such cases, the appropriate length and gradient are those of that segment of the slope that is above the point where it

flattens enough for deposition to occur.

The broken-line portions of the curves on the

chart were extrapolated to provide the best

estimates now available for slopes longer than

those measured in plot studies. Subsequent

investigations on slopes longer than 300 feet may

show need for revision of these segments of the

curves.

Values of LS for slope percentages not shown

on the chart may be computed by solving the

following equation:

I:ä=VX(0.0076+0.00535+0.000765 ')

where X is the field slope length in feet, and s

is the gradient expressed as slope percent.

Slope Length

Slope length is defined as the distance from

the point of origii;i of overland flow to either of

the following, whichever is limiting for the major

part of the area under consideration: (1) the pomt

where the slope decreases to the extent that

deposition begins or (2) the point where runoff

enters a well-defined channel that may be part

of a drainage network or a constructed channel

such as a terrace or diversion (15).

Numerous plot studies have shown that the

soil loss per unit area is proportional to some

power of slope length. Since the factor L is the

ratio of field soil loss to that from a 72.6-foot

(—Y V72.6/ slope, the value of L may be expressed as

where X is field slope length in feet and the exponent m is determined from field data. The

magnitude of the exponent m in this expression

is not the same for all locations or for all conditions at a given location (27). Its average

value in past investigations under natural rainfall has been about 0.5. This is the value used

for development of the slope-effect chart (fig. 2).

The value of m is significantly infiuenced by

the interaction of slope length with gradient and

may also be influenced by soil properties, type

of vegetation, and management practices. On

slopes steeper than 10 percent, a value of 0.6

for m is recommended. A value of 0.3 appears

applicable to the very long slopes of less than

one-haK percent gradient encountered in the

furrow-irrigated sections of the High Plains of

western Texas. Data from gently sloping

Houston clay and Mansic clay loam soils that

were frequently dry and deeply cracked showed

a decrease in runoff with increased slope length

and indicated a value of m=0.3 for these particular soils. Other than for these special cases,

use of the 0.5-power relation reflected in figure 2

is presently recommended. However, further research investigation may soon provide a basis

for recommending other deviations from this overall average.

Figure 3 provides a graphical method for deter-

^8001-

Ö

f 600

z

; 400

i

o 200

UJ

~^ Vnnr

y m = r>ß /

i-

/ ^

/ y —-

/

/ y

y

/ ^ ^ y

/

y ' ^__^ —'— / y

" ^^ îï= 03 - —— /

^ ^

/

, ^

Y ^^ ^

¿^ /

v\

200 400 600 800

SLOPE LENGTH (feet)

1000 1200

FIGURE 3.—Equivalent slope lengths for use of slopeefifect chart when the value of the pertinent lengthexponent is not 0.5.

mining the value of LS when conditions indicate

that a length exponent other than 0.5 is applicable. For example, assume a 600-foot slope

length on Houston clay with 4-percent gradient

and an exponent of 0.3. Entering figure 2 with

the 260 found in figure 3, the LS value for the

assumed situation is about 0.68. A 600-foot slope

length under conditions where the applicable exponent is 0.4 is shown to be equivalent to a 390-

foot length under conditions where the exponent

is 0.5.

Slope Gradient ^¿r^',

A. W. Zingg, in 1940, concluded that soil loss varies

as the 1.4 power of percent slope (28). In 1946,

the Musgrave Committee (9) recommended use

of the 1.35 power of percent slope. Based on

analyses of the data assembled at the Runoff and

Soil-Loss Data Center Smith and Wischmeier

(15) in 1957 proposed the relation:

S-- 0.43+0.30g+0.043s^

6.613

where s is the gradient expressed as percent slope

and S is the slope factor in the erosion equation.

The latter relation was used to derive figure 2.

The relation of soil loss to gradient is influenced

by density of vegetal cover and by soil particle

size. However, research data are presently not

adequate to determine the specific conditions
10 AGR. HANDBOOK 2 82, U.S. DEPARTMENT OF AGRICULTURE

under which deviations from the expressed average relation would be significant.

The Cropping-Management Factor (C)

The effects of cropping and management variables cannot be evaluated independently because

of the many interre ations involved. Almost any

crop can be grown continuously, or it can be grown

in any one of numerous rotations. The sequences

of crops within a system can be varied. Crop

residues can be removed, left on the surface, incorporated near the surface, or plowed under.

When left on the surface, they can be chopped or

they can be allowed to remain as left by the

harvesting operation. Seedbeds can be left rough,

with much available capacity for surface storage

of rainfall, or they can be left smooth. Different

combinations of these variables are likely to have

different effects on soil loss.

In addition, the effectiveness of crop-residue

management will depend on how much residue

there is. This, in turn, depends on rainfall distribution, on the fertility level, and on various

management decisions made by the farmer. Similarly, the erosion-control effectiveness of meadow

sod turned under before corn or other rowcrops

depends on the type and quality of the meadow

and on the length of time elapsed since the sod

was turned under.

The canopy protection of crops not only depends on the type of vegetation, the stand, and

the quality of growth, but it also varies greatly

in different months or seasons. Therefore, the

overall erosion-reducing effectiveness of a crop

depends largely on how much of the erosive rain

occurs during those periods when the crop or

management practice provides the least protection.

Definition of Factor C

The factor C in the soil-loss equation is the

ratio of soil loss from land cropped under specified conditions to the corresponding loss from

tilled, continuous fallow. This factor measures

the combined effect of all the interrelated cover

and management variables listed in the preceding

three paragraphs.

The loss that would occur on a particular field

if it were continuously in fallow condition is computed by the four-factor product, RKLS, in the

erosion equation. Actual loss from the cropped

field is usually much less than this amount. Just

how much less depends on the particular combination of cover, crop sequence, and management

practices. It also depends on the particular stage

of growth and development of the vegetal cover

at the time of the rain. The factor C adjusts the

soil-loss estimate to suit these conditions.

The correspondence of periods of expected

highly erosive rainfall with periods of poor or

good plant cover differs between regions or

locations. Therefore, the value of C for a particular cropping system will not be the same in

all parts of the country. In order to derive the

appropriate C values for a given locality, it is

necessary to know how the erosive rainfall in

that locality is likely to be distributed through

the 12 months of the year. It is also necessary

to know how much erosion-control protection the

gro\ving plants, the prior-crop residues, and

various tillage operations will provide at the time

when erosive rains are likely to occur. A procedure has been developed for deriving locational

values of the factor C on the basis of available

weather records and research data that reflect

effects of crops and management. The cropping

and weather data needed for this purpose appear

in ready-reference form in the subsections entitled '^Soil-Loss Ratios'' and '^Erosion-Index

Distribution Curves.''

The change in effectiveness of plant cover

within the crop year is gradual. For practical

purposes, it was necessary to divide the year

into a series of crop stage periods so defined that

cover and management effects may be considered

approximately uniform within each period.

Crop Stage Periods

The five crop stage periods that are used for

computation of locational C values are defined

as follows :

Period F.—Rough fallow. Turn plowing to

seeding.

Period 1.—Seedling. Seedbed preparation to

1 month after planting.

Period 2.—Establishment. From 1 to 2

months a^ter spring or summer seeding.

For fall-seeded grain, period 2 includes the

winter months, ending about May 1 in

the Northern States, April 15 in the

Central States, and April 1 in the Southern States.

Period 3.—Growing and maturing crop. End

of period 2 to crop harvest.

Period 4.—Residue or stubble. Crop harvest

to plowing or new seeding. (When

meadow was established in small grain,

grain period 4 was assumed to extend 2

months beyond the grain harvest date.

After that time, the vegetation was classified as established meadow.)

Some adjustment in length of periods 1

through 3 may be necessary for vegetable crops.

Effects of Cropping System and Management

on Soil Loss

About 10,000 plot-years of runoff and soil-loss

data assembled from 47 research stations in 24

States {20) were analyzed to obtain empirical

measurements of the effects of cropping system

and management on soil loss within each cropstage period. Several significant factor relations

that became apparent from the analyses provide
RAINFALL-EROSION LOSSES FROM CROPLAND 11

background information for interpretation of the

soil-loss ratio table.

Erosion From Fallow Soil.—The rate at which

fallow soil eroded depended on cropping history

and the nature and quantity of residues turned

under as well as on inherent characteristics of the

soil itself. Brief periods of fallow in a rotation

were not comparable in erodibUity to continuous

clean-tilled fallow on similar soil and slope.

Plant residues incorporated in fallow soil were very

effective in reducing both rimoff and erosion.

Effects of cropping history are a part of the factor

Cin the erosion equation.

Productivity Level and Soil Loss.—In general,

soil losses decreased as crop yields increased.

Since good grain yields are usually associated with

good stands and good forage growth, the canopy

cover is better and more residues are returned to

the soil. Both help to decrease erosion losses.

However, the added erosion-reducing benefit of

each additional unit of crop yield becomes less as

yields become higher.

Crop-Residue Management.—The soil-loss reduction resulting from prior crop residues left on the

field depended on the type and quantity of residues produced and the method of handling. Residues were most effective when left at the surface.

But after several years of turning heavy crop residues under with a moldboard plow before rowcrop seeding, both runoff and soil loss from the

row crop were much less than from similar plots

from which cornstalks and grain straw were removed at harvesttime. The effectiveness of incorporated residues was greatest during the fallow and seedling periods.

Erosion From Row Crop After Meadow.—Specific-year erosion losses from com after meadow

ranged from 14 to 68 percent of corresponding

losses from continuous corn on adjacent plots.

Mixtures of grass and legume were more effective

than legumes alone. In general, the effectiveness

of grass-and-legume meadow sod plowed under

before com in reducing soil loss from the com was

directly proportional to meadow yields. Its erosion-control effectiveness was greatest during the

rough fallow and corn-seedling periods and decreased as the com year moved along. The total

reduction in soil loss effected by the meadow

depended, therefore, largely upon the stage of

development of the com when the erosive rains

occurred. The length of the period during which

the turned sod remained effective in reducing erosion was also directly related to meadow yields.

Efect oj I^ength oj Meadow Periods.—Direct

comparisons of corn after first, second, and third

years of meadow were very limited, and the data

were too sporadic for overall differences to be

statistically significant. When second-year meadow was allowed to deteriorate under poor management, it was less effective than 1 year of meadow.

When succeeding meadows were more productive

than first-year, they were usually more effective in

reducing erosion from corn after the meadow.

The effectiveness of virgin sod and of long periods

of continuous alfalfa in which grass became well

established was longer lasting than that of 1 or 2

years of rotation meadow.

Grass-and-legume catch crops established in

spring-seeded small grain and plowed under at

corn planting time in the following year effected

significant reduction in soil erosion during the corn

seedling period, but their effectiveness was shorter

lived than that of a full year of meadow.

Winter-Cover Seedings.—The erosion control

attained with winter-cover seedings depended

upon time and method of seeding, time of plowing, rainfall distribution, and type of cover seeded.

Covers such as vetch and ryegrass seeded between

the corn or cotton rows before harvest and turned

under in April were effective in reducing erosion

not only in the winter months but also during the

seedling and establishment periods of the following

crop. Small grain alone seeded in corn or cotton

residues and plowed under in spring was of some

value during the winter period but showed no

residual erosion-reducing effect after the next

yearns corn or cotton planting. Very limited data

indicated crimson clover alone to be of doubtful

value as a winter cover, but when it was combined

with a quick-starting grass, effective protection

was provided. Small grain or vetch seeded in the

fall on plowed cottonland and turned under in

spring for another cotton seeding lost about 20

percent more soil than adjacent plots with undisturbed cotton residues on the surface.

Soil-Loss Ratios

Humid Areas.—An empirical measure of the

erosion-control effectiveness of each crop, grown

in various sequences, was obtained from the assembled plot data. Ratios of soil losses from the

cropped plots to corresponding losses from continuous fallow were computed. This ratio was

computed for each of the five crop-stage periods

previously defined, for each particular crop, in

various combinations of crop sequence and productivity level.

A lO-column, 100-line table of the computed

soil-loss ratios was published in 1960 by Wischmeier (22). This table was not as comprehensive as would be desirable from an application

viewpoint. Some combinations of conditions encountered in field soil-loss estimation in various

parts of the United States were omitted from the

table, because not enough research data were available to make sound evaluations of these particular combinations. Nevertheless, the table was

comprehensive enough to test the^ validity and

value of the new procedure for deriving rotation

C values on a locational basis. It also provided
12 AGR. HANDBOOK 28 2, U.S. DEPARTMENT OF AGRICULTURE

a broad set of benchmark values from which other

ratios could be estimated by subjective comparisons.

Table 2 is an expansion of the previously published soil-loss ratio table. It lists, for each cropstage period, the expected ratio of soil loss from

the designated crop and practice combination to

corresponding loss from the base fallow condition.

The table is entered on the basis of crop, crop

sequence, residue management, and crop productivity level, in that order. The soil-loss ratio

for each crop-stage period is taken from the seven

columns at the right. Three columns are needed

for corn-period 4, in order to reflect effects of

different ways of managing the field during that

period. Suggestions for estimating soil-loss ratios

under some of the conditions not directly listed

in this table are shown in table 3.

TABLE 2.—Ratio of soil loss from cropland to corresponding lossfrom continuousfallow

Cover, sequence,

and management ^

Productivity 2

Hay

yield

Corn

yield

Soil-loss ratio for

crop-stage period ^

34 4L 4R 4L + WC

CORN IN ROTATION

Ist-year C after gr & Ig hay:

'Spg TP, convtill

Do

Do

Do

Do

Do

Do

Spg TP, min till

Do

Do

Do

Do

2d-year C after gr & Ig hay:

' RdL, spg TP, conv till

Do

Do

Do

Do

Do

RdL, spg TP, min tiU

Do

Do

Do

Do

RdL, WC in prec C, conv till.

Do

Do.

Do.

Do.

Do.

RdR, WC in prec C, conv till

Do

Do

RdR, no WC, convtill

Do

Do

3d or 4th year C after gr & Ig hay, or

2d-year C after SO, red cl, or sw cl:

RdL, conv till

Do

Do

Do

RdL, min till

Do

Do

RdL + WC in prec C

Do

Do

See footnotes at end of table.

Tons

3-5

2-3

2-3

1-2

1-2

<1

<1

3-5

2-3

2-3

1-2

1-2

3-5

2-3

2-3

1-2

<1

<1

3-5

2-3

2-3

1-2

<1

3-5

2-3

2-3

1-2

<1

<1

3-5

2-3

1-2

3-5

2-3

1-2

3-5

2-3

1-2

<1

3-5

2-3

1-2

3-5

2-3

1-2

Bu.

75+

75 +

60-74

60-74

40-59

40-59

20-35

75+

75 +

60-74

60-74

40-59

75+

75 +

60-74

40-59

40-59

20-35

75+

75+

60-74

40-59

40-59

75+

75+

60-74

40-59

40-59

20-35

75+

60-74

40-59

75+

60-74

40-59

75+

60-74

40-59

20-35

75 +

60-74

40-59

75+

60-74

40-59

Pet.

8

10

12

15

15

23

23

25

32

35

42

46

55

18

20

21

25

28

33

30

35

42

55

60

65

36

45

55

70

22

26

33

Pet.

25

28

29

30

32

40

40

8

10

12

15

15

48

51

54

57

62

66

25

32

35

42

46

35

37

39

42

45

48

52

55

60

62

65

72

63

66

70

76

36

45

55

46

48

51

Pet.

17

19

23

27

30

38

43

8

10

12

15

15

37

41

45

49

54

60

25

32

35

42

46

30

33

36

40

44

49

40

45

53

47

51

57

50

54

58

64

36

45

55

41

44

47

Pet.

10

12

14

15

19

25

30

6

7

8

9

11

20

22

24

28

30

35

12

13

14

17

18

20

22

24

28

30

35

22

24

30

22

24

30

26

29

32

38

16

17

19

26

29

32

Pet.

15

18

20

22

30

35

45

15

18

20

22

30

24

26

28

42

50

65

24

26

28

42

50

24

26

28

42

50

65

30

40

50

65

30

40

50

30

40

50

Pet.

35

40

43

45

50

60

65

35

40

43

45

50

60

60

65

70

75

60

60

65

70

75

80

60

65

75

60

65

70
RAINFALL-EROSION LOSSES FROM CROPLAND 13

TABLE 2.—Ratio oj soil lossfrom cropland to corresponding loss from continuousfallow—Continued

Line

No.

Cover, sequence,

and management i

Productivity

Hay

yield

Corn

yield

Soil-loss ratio for

crop-stage period ^

34 4L 4R

46

47

48

49

50

51

52

53

54

55

56

57

58

59

60

61

62

63

64

65

66

67

68

69

70

71

72

73

74

75

76

77

78

79

80

81

82

83

84

85

86

87

88

89

90

91

92

93

94

95

96

97

CORN IN ROTATION—Continued

RdL-fWC in prec C

RdR, conv till

Do

Do

RdR, 8 tons manure added

Ist-year C after cl hay

Ist-year C after sw cl

Ist-year C after lesp hay

Do

C after 1 year cot after gr & Ig hay.

Do

Corn in meadowless systems:

Aiter S G wintercrop, spg TP._.

Do :

Do

After SG, no intercrop, RdL

COTTON IN ROTATION

Ist-vear cot after gr & ]g hay

Do

Do

Do

Do

2d-year cot after gr & Ig hay:

RdL, no WC seeding

Do

Do

Do

RdL + WC in prec cot

Do

Do

Do

Cot after cot, 3d or more year after M :

RdL, no WC seeding

Do

RdL+WC in prec cot

Do

Cot after 1 year C (RdL) after M

Do

Do__:

Cot after 1 year C C RdR

Cot after 2 years C (RdL) after M

Do

Do

Cot in cot (V)-C (crot) system

Cot in cot-0-lesp seed, RdL

Do

Cot in cot-SG-sw cl

SMALL GRAIN IN ROTATION

With meadow seeding:

In disked row-crop residue—

After 1 year C after M

Do

Do

Do

After 2d or 3d year C after M_

Do

Do

Do

After 1 or more C after SG

Tons

<1

3-5

2-3

1-2

1-2

1-2

2-ri

1-2

3-5

2-3

1-2

1-2

<1

3-5

2-3

1-2

<1

3-5

2-3

1-2

<1

3-5

2-3

1-2

2-3

3-5

2-3

1-2

3-5

2-3

1-2

<1

3-5

2-3

1-2

<1

Bu.

20-35

75 +

60-74

40-59

60-74

40-55

40-55

60-70

40-55

60-70

40-59

75 +

60-70

40-55

HP

HP

HP

MP

MP

HP

HP

MP

MP

HP

HP

MP

MP

HP

MP

HP

IMP

75 +

60-75

40-59

40-59

75 +

60-75

40-59

HP

HP

MP

MP

75 +

60-74

40-59

25-39

75 +

60-74

40-59

25-39

Pet.

42

70

75

75

60

21

23

55

55

30

35

22

25

30

8

10

15

15

23

30

34

40

45

20

23

23

27

42

45

32

35

25

32

35

60

36

45

55

28

23

25

25

Pet.

56

78

80

80

70

35

45

70

70

58

65

37

40

45

25

30

34

34

40

54

58

65

70

40

42

47

51

70

80

51

58

48

51

54

65

63

66

70

40

34

40

45

20

30

41

60

32

40

58

75

Pet.

52

54

60

70

52

32

38

55

60

46

54

35

38

42

30

35

40

45

54

12

18

25

36

19

24

35

45

Pet.

38

27

30

35

28

25

28

30

32

24

29

22

24

30

20

25

30

35

45

56 38

62 44

68 46

70 50

46 38

50 44

55 46

57 50

70 48

80 52

57 48

65 52

49 32

51 35

56 38

63 40

62 39

68 45

73 50

45 35

40 30

45 37

48 35

Pet.

65

Pet.

35

35

40

50

28

42

27

30

40

22

25

30

33

42

38

40

42

48

38

40

42

48

42

48

42

48

38

40

45

48

45

48

48

2 2

3 2

4-15 2

5-15 3

5 3

5 3

5-15 3

6-15 3

{') («)

62

70

75

62

60

60

65

75

65

70

See footnotes at end of table.

7160-705 O— 65-
14 AGR. HANDBOOK 282, U.S. DEPARTMENT OF AGRICULTURE

TABLE 2.—Ratio oj soil lossfrom cropland to corresponding loss from continuousfallow—Continued

Line Cover, sequence,

and management ^

Productivity 2 Soil-loss ratio for

crop-stage period ^

No.

Hay

yield

Corn

yield

F 1 2 3* 4L 4R 4L+WC

Q8

SMALL GRAIN IN ROTATION—Continued

With meadow seeding—Continued

In disked row-crop residue—Con.

After Ist-year cot after M

After 2d-year cot after M

In cot middles after sw cl or lesp

Tons

2-3

2-3

Bu. Pet. Pet.

35

50

30

50

80

80

92

45

51

60

60

70

60

65

70

70

25

25

50

Pet.

25

35

22

40

45

50

55

30

34

40

40

45

40

42

45

45

0

25

25

18

Pet.

5-15

5-15

10-15

5-15

7-15

6-15

7-15

5

5

7

5

7

5

6

7

7

8

10

12

5

12

5

Pet.

3

3

3

3

3

3

3

3

3

4

3

4

3

3

4

4

8

10

12

5

6

5

0.4

. 6

1.0

2.0

2. 0

1. 5

2. 0

LO

2.5

Pet. Pet.

99

TOO

101

On disked row-crop stubble, RdR—

After 1 year C after M

Do

2-3

1-2

2-3

60 +

40-59

60 +

lOi^

103 After 2 years C after M

104 After C, 3d year after M

105

On plowed seedbed, RdL—

After 1 year C or SG after M ..

Do

3-5

2-5

1-2

3-5

2-3

3-5

2-3

1-2

2-3

75 +

60-74

40-59

75 +

40-59

75 +

60-74

40-59

60-74

25

35

42

36

55

55

60

65

65

Q)

106

107 Do __

108

109

After 2 years C or SG after M _

Do

110

On plowed seedbed, RdR—

After 1 year C or SG after M ._

111 Do -

112 Do

113 After 2 years C after M

Without meadow seeding:

Sequences and yields of lines 89-90 _

Sequences and yields of lines 91-99,

101, 105, 106', 108-110 _

114 16

20

25

115

116 Sequences and yields of lines 102-

104, 107, 111-113-

117

DOUBLE-CROPPED ROTATIONS

Wheat (grain) and lesp (hay)

118 Wheat and lesp, both grazed _

119 Spg oats (hay) and lesp (hay) ^_

120

ESTABLISHED MEADOWS ^

Grass and legume mix 3 +

2

1

2.5 +

121 Do

122 Do

123 Alfalfa

124 Lespedeza

125 Red clover__

126 Sericea, 2d year _

127 Sericea, after 2d year

128 Sweetclover _

^ Symbols: C, corn; conv till, conventional tillage; cot,

cotton; crot, crotolaria; gr & Ig, grass and legume; lesp,

lespedeza; M, grass and legume meadow, at least 1 full

year; min till, minimum tillage; O, oats; prec, preceding;

RdL, residue of prior crop left; RdR, residue of prior crop

removed; spg, spring; SG, small grain; sw cl, sweetclover;

TP, turn plow; V, vetch; WC, grass or grass-and-legume

winter cover seeded early.

2 For cotton, HP = high crop productivity; MP =moderate crop productivity.

Small-grain cover is assumed commensurate with the

indicated productivity level of corn or cotton.

3 Crop-stage periods are as defined on p. 10. Period 4

ratios are taken from column 4L when crop residues

remain on field but without winter cover seeding; from

column 4R when corn stover, straw, and similar residues

are removed; and from column 4L + WC when earlyseeded grass and legume winter cover is established in

addition to leaving crop residues.

* Where two period 3 values appear, the first is for

high-yielding grain and the second is for grain yielding

less than 30 bushels of oats or 15 bushels of wheat per

acre.

^ Use data from lines 36 to 42, selecting line on basis

of productivity level.

^ Use data from lines 93 to 96, selecting line on basis of

productivity level.

7 Use data from lines 89 to 113.

8 Ratio for winter months is 12 percent.

* Ratios shown are the yearly averages.
RAINFALL-EROSION LOSSES FROM CROPLAND 15

TABLE 3.—Suggestions for approximating soil4oss ratios for cropping and management combinations not

listed in table 2

Cover, sequence, and management

Corn:

After fall turnplowing in northern

half of United States.

After 2 or more full years of meadow.

With small-grain seeding for win

ter cover.

Grain sorghum

Meadow:

New

Established

Peanuts

Potatoes:

After potatoes or truck crop

After grass-and-legume hay yielding more than 2 tons per acre.

After corn or small grain

Soybeans:

After grass-and-legume hay or af

ter corn.

After soybeans

Late-planted

Sweet corn

Truck crops

Soil loss ratios

To compensate for effect of freezing and thawing and for high early-spring

soil moisture content, add 7 to each period-F and period-1 value in Hnes

1 to 7, 13 to 18, 33 to 39, and 47 to 50 of table 2.

Table 2 assumed at least 1 full year of estabHshed grass-and-legume meadow.

Additional credit for 2-year meadows may be considered if meadows are

high yielding and are not permitted to deteriorate: Reduce by 10 percent the

values for periods F, 1, 2, 3 and 4L in lines 13, 14, 15, 33, 34, 66, 67, 78, and

Small grain turned early in spring does not significantly reduce soil loss from

following corn crop. Select lines from table 2 that do not specify WC seeding

and substitute small-grain periods 1 and 2 for corn period 4L or 4R.

Same as ratios for corn in similar rotations where canopy cover and quantities of residue are comparable. Under irrigation, the values for grain

sorghum may equal those for high-yielding corn.

When seeded without a nurse crop, use values listed for spring-seeded small

grain. The lengths of periods 1 and 2 should be adjusted if necessary so

that cover in each period will be comparable to corresponding grain periods.

Apply values of hnes 120 to 128.

For comparable crop sequence, values in lines 5, 6, 16, 17, 27, 28, 32, 35, 38,

45, 49, 52, and 56 are recommended.

In similar crop sequence, select values from periods F, 1, 2, and 4 of lines 18,

29, 39, 46. For period 3, use values from hne 16, 17, 27, 28, 38, or 45.

Select values for periods F to 3 from lines 1, 3, 5, 7 on basis of hay yield; period

4 from line 7.

Select values for periods F to 3 on basis of preceding crop and yield; period

4 from hne 7.

Use values for comparable corn rotations: Periods F to 3 from lines 3 to 7,

15 to 18, 26 to 29, 37 to 39, 48, 49; period 4 from hnes 7, 18, 29, 39.

Select lines representing corn residues equivalent to soybean residues: Lines

15 to 18, 37 to 39.

Select values from comparable crop sequences in lines 5, 6, 16, 17, 27, 28, 32,

35, 38, 45, 49.

Do.

For low-residue truck crops after grass-and-legume hay or high-residue crops,

select periods F and 1 values from comparable corn rotations; periods 2, 3,

and 4 values from hnes 7, 18, 29, 39, 46. For second or more year of truck

crop, use values from line 39 or 46 for all periods.

Other combinations of crops and management

variables are being included in studies as rapidly

as possible. Rainfall simulators have been developed to decrease the time required to obtain data.

In the meantime, the data in table 2 will be helpful for estimating the effectiveness of covers or

management practices that have not been measured directly. Such estimates are facilitated by

the fact that the table values are given for each

crop-stage period separately. Cover and surface

conditions as they occur in each crop-stage period

of an untested crop or with a new tillage practice

may usually be compared with the conditions

reflected in one of the lines of soil-loss ratio table.

This procedure is illustrated in table 3, which

suggests a number of specific comparisons.

Semiarid Areas —Water erosion is a serious

problem also in most semiarid regions. Inadequate moisture and periodic droughts reduce the

periods when growing plants provide good soil

cover and hmit the total quantities of plant

residues produced. Erosive rainstorms are not

uncommon, and they are concentrated within the

season when cropland is least protected. Because of the difficulty of establishing meadows

and the competition for available soil moisture,

sod-based rotations are often impractical.

Proper management of available residues offers

one of the most important opportunities for a

higher level of soil and moisture conservation.

However, accurate soil-loss ratios for stubble

mulching and summer fallowing practices on the

western Plains are not yet available from research data. The ratios given in table 4 are

approximations based on observations of experi-
16 AGR. HANDBOOK 2 82, U.S. DEPARTMENT OF AGRICULTURE

TABLE 4.—Approximations of soil-loss ratios for crop-stage periods and nuraher of tillage operations with

stubble mulching and summerfallowing in western Plains areas

Cover, sequence, and management Residue on surface

at seeding time

Soil-loss ratios for crop-stage period—

1 2 3 4L 4R

Small grain without meadow seeding:

After small grain _ _ _

Pounds

200-500

500-1, 000

1, 000-1, 500

1, 500-2, 000

0-200

200-500

500-1, 000

1, 000-1, 500

1, 500-2, 000

0-200

200-500

500-1, 000

1, 000-1, 500

1, 500-2, 000

2, 000-2, 500

0-200

200-500

500-1, 000

1,000-1,500

1, 500-2, 000

0-200

200-500

50O-1, 000

1, 000-1, 500

1, 500-2, 000

2, 000-2, 500

Pet.

70

42

25

15

90

70

42

25

15

90

85

70

50

40

30

Pet,

45

25

17

10

55

45

25

17

10

55

50

45

35

30

25

Pet.

6

6

6

6

6

6

6

6

6

6

6

6

6

6

6

Pet.

10

10

10

10

10

10

10

10

10

10

10

10

10

10

10

Pet.

20

Do -

20

Do --. - - - -

20

Do -- --- -.. -

20

After summer fallow of—

Small-grain residues __

20

Do -

20

Do _____

20

Do .

20

Do 20

Row crop residues— _

20

Do ___ -_.

20

Do 20

Do _

20

Do 20

Do 20

Soil-loss ratios for following number of tillage operations after grain harvest—

1 2 3 4 5

Summer fallow:

After small grain _ _ 53

25

25

10

4

68

50

50

26

20

15

60

49

29

14

6

72

55

55

35

25

20

70

55

34

19

8

80

63

60

40

30

25

80

63

39

22

11

85

75

65

45

35

28

90

Do --_ -

70

Do -

42

Do 25

Do 13

After row crop - _ _ 90

Do _

85

Do 70

Do _ - . _ -

50

Do -_ 40

Do 30

enced field personnel,^ guided by very limited

data on the erosion-control effectiveness of various amounts of surface mulch and by the experimentally determined values of table 2. These

approximations appear to be consistent with

present knowledge of erosion research and runoff

and will provide valuable guides until more precise

evaluations can be obtained through additional

research.

Erosion-Index Distribution Curves

The rainfall factor, i?, in the erosion equation

does not completely describe the effects of lo-

^ The authors are indebted to D. G. Craig, W. A. Hays,

J. J. Pierre, and J. W. Turelle, Soil Conservation Service,

for substantial contributions toward expanding the scope

and usability of the soil-loss ratio data from which table

2 was derived. Table 4 was taken from unpublished material developed by J. W. TurelJe and D. G. Craig, in

cooperation with the Agricultural Research Service's

runoff and soil loss data center.

cational differences in rainfall pattern on soil

erosion. On cropped fields, rainstorm distribution within the year is also important. The

erosion-control effectiveness of a cropping system

on some particular field depends, in part, on how

the year's erosive rainfall is distributed among

the five crop-stage periods of each crop included

in the system. Therefore, expected monthly distribution of erosive rainfall at a particular location

is an element in deriving the applicable value

of the cropping-management factor, C

It was previously pointed out that a location's

erosion index is computed by sununing El values

of individual storms. Thus, the monthly distribution of the erosion index can also be determined

from long-time rainfall data. This was done for

all the station rainfall records abstracted for

development of the iso-erodent map.

On the basis of monthly distribution of the

erosion index, the 37 States of figure 1 were
RAINFALL-EROSION LOSSES FROM CROPLAND 17

divided into 33 geographic areas shown in figure

4. For practical purposes, its monthly distribution may be considered uniform throughout any

one of these areas but different from monthly

distribution in any of the other 32 areas. Actually, the changes in distribution are usually

gradual transitions from one area to another

rather than abrupt changes at the area boimdaries. Therefore, wide differences between average distributions within two adjacent areas are

often not apparent. However, at some part of

the distribution curve, the difference is sufficient

to affect C-value derivations for some cropping

systems. For widely separated geographic areas,

differences in the erosion-index distributions are

much more apparent.

The erosion-index distribution curve applicable

in each of the 33 subareas of figure 4 is shown in

figures 5 to 21, respectively. The numbers of the

plotted curves in these figures correspond with

the area numbers shown on the key map, figure

4. Average monthly erosion-index values were

expressed as percentages of average annual values and plotted cumulatively against time. Thus,

the percentage of the annual erosion index that

is to be expected within any particular crop stage

period may be found by reading the curve at the

last and first date of the period and subtracting.

Procedure for Deriving Rotation C-Values for

a Particular Locality

To compute the value of C for any particular

rotation on a given field, one needs first to determine the most likely seeding and harvest dates

..•..- . .. .^'A'

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FIGURE 4.—Key map for selection of applicable erosion-index distribution curve.
18 AGR. HANDBOOK 2 82, U.S. DEPARTMENT OF AGRICULTURE

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FIGURE 5.—Erosion-index distribution curves 1 and 2 : the Dakotas and parts of Minnesota, Nebraska, and Iowa.
RAINFALL-EROSION LOSSES FROM CROPLAND 19

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FIGURE 6.—Erosion-index distribution curves 3 and 4: parts of Nebraska, Kansas, and Oklahoma.
20 AGR. HANDBOOK 2 82, U.S. DEPARTMENT OF AGRICULTURE

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FIGURE 7.—Erosion-index distribution curves 5 and 6: parts of Oklahoma and Texas.
RAINFALL-EKOSION LOSSES FROM CROPLAND 21

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FIGURE 8.—Erosion-index distribution curves 7 and 8: parts of Texas.

I7O0-7O5O—65 i
22 AGR. HANDBOOK 2 82, U.S. DEPARTMENT OF AGRICULTURE

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RAINFALL-EROSION LOSSES FROM CROPLAND 23

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FIGURE 10.—Erosion-index distribution curves 11 and 12: parts of Texas, Minnesota, Iowa, Wisconsin, and Michigan.
24 AGR. HANDBOOK 2 82, U.S. DEPARTMENT OF AGRICULTURE

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FIGURE 11. Erosion-index distribution curves 13 and 14: parts of Nebraska, Kansas,Missouri, Iowa, Illinois,'and

Wisconsin.
RAINFALL-EROSION LOSSES FROM CROPLAND 25

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FIGURE 12.—Erosion-index distribution curves 15 and 16: parts of Michigan, Missouri, Illinois, Indiana, and Ohio.
26 AGR. HANDBOOK 2 82, U.S. DEPARTMENT OF AGRICULTURE

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FIGURE 13.—Erosion-index distribution curves 17 and 18: parts of Ohio, Pennsylvania, West Virginia, Missouri, and

Arkansas.
RAINFALL-EROSION LOSSES FROM CROPLAND 27

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DATE

FIGURE 14.—Erosion-index distribution curves 19 and 20: parts of Missouri, Illinois, Indiana, and Kentucky.
28 AGR. HANDBOOK 2 82, U.S. DEPARTMEJSTT OF AGRICULTURE

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Alabama. ' ^ '
RAINFALL-EROSION LOSSES FROM CROPLAND 29

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FIGURE 16.—Erosion-index distribution curves 23 and 24: parts of Mississippi, Alabama, Florida, and Georgia.
30 AGR. HANDBOOK 2 82, U.S. DEPARTMENT OF AGRICULTURE

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RAINFALL-EROSION LOSSES FROM CROPLAND 31

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32 AGR. HANDBOOK 2 82, U.S. DEPARTMENT OF AGRICULTURE

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RAINFALL-EROSION LOSSES FROM CROPLAND 33

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and Massachusetts.
34

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FIGURE 21.—Erosion-index distribution curve 33: Connecticut, Rhode Island and parts of Massachusetts, New

Hampshire, and Maine.

method of seedbed preparation and residue management, and average crop yields including ha}'

expected with this system on the soil involved and

with the contemplated management. Tables 2 to

4 and figures 4 to 21 then supply the research

data needed to complete the computation. The

procedure will be explained by means of an

example.

Problem.—Evaluate C for a 4-year rotation of

wheat-with-meadow-seeding, meadow, corn, corn

in central Indiana: (1) with conventional tillage

and average production of 45 bushels of wheat, 4

tons of hay, and 100 bushels of corn per acre; (2)

with minimum tillage and similar crop yields; and

(3) with conventional tillage and yield averages of

only 12 to 15 bushels of wheat, 2 tons of hay, and

40 to 55 bushels of corn. Assume that the meadow is a mixture of grass and legume, such as alfalfa

and brome or timothy and clover; that crop residues are left on the field; that cornstalks are

plowed under about May 1 for corn planting or

disked for wheat seeding about October 10; and

that wheat is harvested about July 10.

Procedure.—Set up a working table such as that

illustrated in table 5, obtaining the needed

information as follows:

Column 1 lists in chronological sequence all

seeding and harvest dates (other than hay)

involved in the rotation.

Column 2 lists the beginning date of each

successive crop-stage period. A seeding date

begins crop stage period 1. By definition, period

2 begins 1 month later, period 3 begins 2 months

after seeding (except for winter grain), period 4

begins with crop harvest, and period F with the

date of moldboard plowing. The meadow period

begins 2 months after wheat harvest and extends

to plowing date. Thus, all the dates in column 2

are determined by the locational seeding and

harvest dates.

Column 3 records values read from the appropriate erosion-index distribution curve. Figure

4 shows that the curve applicable in central

Indiana is No. 16. This curve appears in figure 12.

The curve is read for each successive date listed

in column 2, adding one to the ''hundreds''

column each time January 1 is passed.

Column 4 identifies the crop-stage period

ending with the date shown on that line.
RAINFALL-EROSION LOSSES FROM CROPLAND 35

Column 5 lists the percentage of the erosion

index applicable to each successive crop-stage

period. The values are differences between

successive ciu*ve readings recorded in column 3.

Column 6 Usts the soil-loss ratio indicated in

table 2, page 12, for the specific conditions and

crop-stage period represented by each line in the

working table. The numbers in parentheses

indicate the Unes in table 2 from which the values

were taken.

The crop yield figm-e for entering table 2 is the

expected average yield, not the yield attainable in

the most favorable years. If the likeUhood of

meadow failure is significant, a yield figure well

below the expected average is appropriate. From

an erosion viewpoint, the adverse effects of a

meadow failure in a rotation far outweigh the

gains from occasional exceptionally good meadows.

All row-crop values in the table that are not

otherwise identified assume moldboard plowing,

smoothing for seedbed, and cultivation after

emergence.

The F period precedes the crop year with which

it is associated in the table. For example, the

value for rough fallow after first-year corn appears

in the line for second-year corn.

Column 7 is self-explanatory. (The decimals

in this column derive from the percentage values

in columns 5 and 6.)

Column 8 subtotals for the different crops indicate where in the rotation most of the erosion

is occurring and help to suggest where additional

conservation measures could be most helpful in

reducing erosion. The total for this column,

divided by the number of years in the rotation,

is the (7 value for this rotation under the conditions

assumed in columns 1 to 6.

Columns 9 and 10 replace column 6 when

solving parts 2 and 3 of the problem.

The first eight columns complete part 1 of the

problem. Only the addition of columns 9 and

10 is needed to derive C values for the management levels specified in parts 2 and 3. Wheeltrack planting (part 2) reduced the value of C

from 0.119 to 0.075, a 37-percent reduction.

A productivity level as low as that specified in

part 3 would increase the C value for the rotation

to 0.186, an increase of 56 percent. Expected

TABLE 5.—Working table Jor derivation of C value for Jf^-year rotation in central Indiana

(1)

Operation

(2)

Date

(3)

Readings

from curve

No. 16

(4)

Cropstage

period

(5)

El

in

period

(6)

Soil-loss

ratio 12

(7)

Column

5 times

col. 6

(8)

Value

of C

(9)

Soil-loss

ratio 2 3

(10)

Soil-loss

ratio 2 4

PI W 10/10

11/10

5/1

7/10

9/10

9/10

5/1

5/20

6/20

7/20

10/15

5/1

5/20

6/20

7/20

10/10

Pet.

91

96

114

153

183

283

314

321

339

359

392

414

421

439

459

491

Pet. Pet.

G. 0787

.0052

. 1176

.0330

.2419

Pet. Pet.

Hv W

Wl

W2

W3

W4

M

M

F

Cl

C2

C3

C4

F

Cl

C2

C3

5

18

39

30

100

31

7

18

20

33

22

7

18

20

32

32(93)

19

5

3

.4(122)

. 4

8(1)

25

17

10

15

25(13)

48

37

20

0. 0160

.0342

.0195

.0090

32(93)

19

5

3

. 4

. 4

58(95)

35

15

3

TP

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.0012

. 6(121)

.6

PI C .0056

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.0340

.0330

15(5)

Hv C

8(8)

8

6

15

32

30

19

TP --

.0330

.0175

.0864

.0740

.0640

30

PI C 42(16)

PI W _ - - -- - -

25(19)

25

12

57

49

28

Rotation total,

4 years 400 .4764

. 119

6. 3005

6.075

5. 7438

Annual average C

value for rotation 6. 186

1 For 45 bu. wheat, 4 tons hay, 100 bu. corn per acre,

conventional seedbed and tillage.

2 Numbers in parentheses refer to line numbers in

table 2.

3 Same yields as for column 6, except minimum tillage

for the corn.

^ For 12 to 15 bu. wheat, 2 tons hay, 40 to 55 bu. corn,

conventional tillage.

5 Sum of the products of El increments (col. 5) and

corresponding soil-loss ratios.

6 Rotation total divided by number of years in the

rotation.
36 AGR. HANDBOOK 2 82, U.S. DEPARTMENT OF AGRICULTURE

soil loss from the field would be increased by the

same percentage.

The C values computed for the rotation in

the example are directly applicable only within

area 16 of figure 4. For other areas or other

seeding dates, the values in columns 3 and 5 of

table 5 are different and the C value for the same

rotation in other areas may be either larger or

smaller.

It should be pointed out here that all these

detailed computations are not required of each

farm field. The procedure and basic data for derivation of the C values are provided primarily

to enable computation of ready-reference handbook tables of values applicable in specific States

or geographic areas. Knowledge of the procedure

will, however, lead to a better understanding of

the significance of such tables and will permit

field computation of values for unusual situations.

The Erosion-Control Practice

Factor (P)

In general, whenever sloping soil is to be cultivated and exposed to erosive rains, the protection offered by sod or close-growing crops in the

system needs to be supported by practices that

will slow the runoff water and thus reduce the

amount of soil it can carry. The most important

of these supporting practices for cropland are contour tillage, stripcropping on the contour, terrace systems, and stabilized waterways. The factor P in the erosion equation is the ratio of soil

loss with the supporting practice to the soil loss

with up-and-down-hill cultiu'e. Improved tillage

practices, sod-based rotations, fertility treatments,

and greater quantities of crop residues left on

the field contribute materially to erosion control

and frequently provide the major control in a

farmer's field. However, these are considered conservation cropping and management practices, and

the benefits derived from them are included in

the factor C,

Contouring

The practice of tillage and planting on the contour have been, in general, effective in reducing

erosion. In limited field studies, the practice provided almost complete protection against erosion

from individual storms of moderate to low intensity, but it provided little or no protection

against the occasional severe storms that caused

extensive breakovers of the contoured rows. Contouring appears to produce its maximum average

effect on slopes in the 3- to 7-percent range. As

land slope decreases, it approaches equality with

the contour row slope, and the soil-loss ratio approaches 1.0. As slope increases, contour row

capacity decreases and the soil-loss ratio again

approaches 1.0.

Practice-Factor Values for Contouring—Aix.^

avaüable data and observations were considered,

a joint ARS-SCS-AES slope-practice workshop

group meeting at Purdue University m 1956

adopted the values of P shown in table 6.

TABLE 6.—Practice factor values for contouring

Land slope (percent)

1.1 to 2...

2.1 to 7...

7.1 to 12..

12.1 to 18

18.1 to 24.

P value

0.60

.50

.60

.80

.90

These are average values for the factor. Location values may vary with soil type, cropping,

residue management, and rainfall pattern.

The full benefits of contouring are obtained only

on fields relatively free from gullies and depressions other than grassed waterways. The effectiveness of this practice is reduced if a field contains numerous small gullies and rills that are not

obUterated by normal tillage operations. In such

instances, land smoothing should be considered

before contouring. Otherwise, a judgment value

greater than shown in table 6 should be used when

computing the benefits for contouring.

Contour Listing,—Contour listing, with the corn

planted in the furrows, has been more effective

than surface planting on the contour (5). However, the additional effectiveness of this practice

is limited to the time from the date of listing

to that of the second corn cultivation. The

soil-loss ratios (table 2) that apply to this

period may be reduced 50 percent in addition to

reduction supplied by the contour factor. The

additional credit does not apply after the lister

ridges have been largely obliterated by two corn

cultivations.

A similar analysis would apply to commercial

potato production where the potato rows are on

the contour, except that in this case the 50-percent reduction would be applied only from layby time to potato harvest.

Slope-Length Limits for Elective Contouring,—

When rainfall exceeds infiltration and surface

detention in large storms, breakovers of contour

rows often result in concentrations of runoff that

tend to become progressively greater with increases in slope length. Therefore, on slopes

exceeding some critical length the amount of

soil moved from a contoured field may approach

or exceed that from a field on which each row

carries its own runoff water down the slope.

At what slope length this could be expected to

occur would depend to some extent on gradient,

soil properties, management, and storm characteristics. Terraces or the sod strips in a contour

stripcrop system function to prevent serious
RAINFALL-EROSION LOSSES FROM CROPLAND 37

arosion damage when excessive row breakage

occurs.

After the 1956 slope-practice workshop, the

Soil Conservation Service prepared ready-reference tables for use with the Corn Belt slopepractice procedure. The values shown in table 7

were given as guides to slope-length limits for

eflFective contouring. These are judgment values.

Research data are not now available to verify

or correct them. It is important to bear in

naind, however, that the contour factor values

given in table 6 assume slope lengths short

enough for full eflFectiveness of the practice. Use

of these values for estimating soil loss on unterraced slopes that are several terrace intervals in

length is speculative.

TABLE 7.—Length limitsjor contouring

Slope (percent)

Maximum

slope

length

2

Feet

400

4 to 6 300

8 200

10 100

12 80

14 to 24 60

Contour Stripcropping

Stripcropping, a practice in which contour

strips of sod are alternated with strips of row

crop or small grain, has proved to be a more

eflFective practice than contouring alone. A good

example is found in the Mormon Coulee near

LaCrosse, Wis., where some fields are reported to

have been cropped in strips for more than 70

years. Where the strips were on the contour, or

nearly so, good erosion control was accomplished.

Where the strips were 5 percent or more oflF

contour, very high soil losses have occurred due

to the flow of runoflF down the rows at high

velocities.

Observations from stripcrop studies indicated

that much of the soil washed from a cultivated

strip was filtered out of the runoflF as it spread

within the first several feet of the adjacent sod

strip. Thus, the stripcrop factor, derived from

soil-loss measurements at the foot of the slope,

accounts for oflF-the-field movement of soil but

not for all movement within the field.

Practice Factor jor Contour Stripcropping.—^After review of available data and field observations,

the ARS-SCS Workshop group meeting at Purdue in 1956 decided to compute the contourstripcrop factor as one-half of that for contouring

alone (table 6). This value was to apply with

the alternate grain-and-meadow strip system possible with a 4-year rotation of corn, small-grain.

meadow, meadow, with the meadow established in

the small grain. Strip guideUnes were to be level.

With less eflFective stripcrop systems, larger factor values are recommended.

With a cropping system such as a 4-year system

of small grain, meadow, and 2 years of row crop,

the contour factor value should probably be about

75 percent of the value in table 6 for contouring

alone. Alternate strips of /aiZ-seeded grain and

row crop were eflFective on relatively flat slopes

in Texas (5), but alternate strips of spring-seeá^á

grain and corn on moderate to steep slopes have

not appeared to provide significant erosion control benefits beyond those attained with contouring

alone. For such "systems the contour values are

recommended.

Buffer stripcropping consists of narrow protective strips alternated with wide cultivated

strips. The location of the protective strips is

determined largely by the width and arrangement

of adjoining strips to be cropped in the rotation

and by the location of steep, severely eroded areas

on slopes. BuflFer strips usually occupy the correction areas on sloping land and are seeded to perennial grasses and legumes. This type of stripcropping is not so effective as contour stripcropping {2).

Width oj Strips With Contour Stripcropping.—

The strip widths shown in table 8 were recommended by the 1956 slope-practice workshop.

TABLE 8.—Strip widths recommended for contours

Slope group (percent) Width of

strip

2 to 7

Feet

88 to 100

7 to 12 _ --- -- - 74 to 88

12tol8-- --- 60 to 74

18 to 24 ._.___-_ 50 to 60

Terracing

Terracing with contour farming is more effective

as an erosion-control practice than stripcropping,

because it positively divides the slope into

segments equal to the horizontal terrace spacing.

With terracing, the slope length is this terrace

interval; with stripcropping or contouring alone,

it is the entire field slope length. Dividing a slope

length into four equal segments cuts the expected

rate of soil loss per acre in half. Dividing it into

six equal segments divides the sou-loss rate by 2.45.

These reductions are reflected in the erosion

equation by changes in the LS factor value.

Both with terracing and with contour stripcropping, measured soil losses have included

only soil moved completely off the field. The

soil saved with contour stripcropping is largely

that deposited in the sod strip. With terracing,
38 AGR. HANDBOOK 2 82, U.S. DEPARTMENT OF AGRICULTURE

the deposit is in the terrace channel and may

equal 90 percent of the soil moved to the channel

(38). The slope-practice workshop group in

1956 decided to use neither the off-the-field soilloss rate nor that for soil movement within the

terrace interval, but a rate that shows a part of

the soil deposited in the channels as not lost.

The group recommended a terracing practice

factor value equal to the one for contour stripcropping.

If all furrow shces between the terraces were

turned up slope periodically with a two-way plow,

most or all of the soil washed into the terrace

channel would be eflFectively moved back up the

slope and a factor value based on the off-thefield rate of loss could be safely applied. Limited

data indicate the terrace factor in this case should

be about 20 percent of that for contouring. But in

most farming operations, conventional plows are

used and the soil deposited in the terrace channel

is not returned to the interterrace interval to

help maintain soil productivity.

It is logical to assume that the total movement

of soil within a terrace interval is equal to that

with contouring alone on the same length and

percentage of slope. Erosion control between

terraces depends upon the crop rotation and other

management practices. Therefore, if a control

level is desired that will maintain soil movement

between terraces within the soil-loss tolerance

Hmit, the practice factor for terracing should equal

the contour practice factor.

However, if the erosion equation is used to

compute gross erosion for estimates of reservoir

sedimentation rates, a terracing practice factor

equal to 20 percent of the contour factor values

shown in table 6 is recommended. The reason

for this lower value is that the soil deposited in

the terrace channels, although lost from the terrace

interval, does not leave the field completely to

enter into the established drainageways.

Limitations

The rainfall-erosion index measures only the

erosivity of rainfall and associated runoff. Therefore, the equation does not predict soil loss that

is due solely to thaw, snowmelt, or wind. In

areas where such losses are significant, they must

be estimated separately and combined with those

predicted by the equation for comparison with

soil-loss tolerances.

FIELD APPLICATIONS OF THE SOIL-LOSS EQUATION

The primary pm*pose of the soil-loss prediction procedure described in this handbook is to

provide specific and reliable guides to help select

adequate soil and water conservation practices

for larm fields. Where agricultural lands are a

major sediment source, the procedure may also

be used to compute this phase of sediment production in predicting rates of reservoir sedimentation. Specific applications of the erosion

equation are discussed and illustrated below.

Predicting Field Soil Loss

Rotation Averages

The procedure for computing the expected

average annual soil loss from a given cropping

system on a particular field is illustrated by the

following example.

Assume a field in Fountain County, Ind., on

Russell silt loam, having an 8-percent slope about

200 feet long. The cropping system is a 4-year

rotation of wheat, meadow, corn, corn with

tillage and rows on the contour and with corn

residues disked for wheat seeding and turned

under in spring for second-year corn. Fertility

and residue management on this farm are such

that crop yields are rarely less than 85 bushels

corn, 40 bushels wheat, or 4 tons alfalfa-brome

hay, and the probability of meadow failure is

slight.

The first step is to refer to the charts and

tables discussed in the preceding section and to

select the values of i?, Ky LSy Í7, and P that

apply to the specific conditions on this particular

field.

The value of the rainfall factor, i?, is taken

from figure 1, page 6. Fountain County, in

west-central Indiana, lies between iso-erodents

175 and 200. By linear interpolation, R=il85.

The value of the soil-erodibility factor, K^ is

taken from table 1, page 5, supplemented by

Ä-value tables prepared at regional Soil-Loss

Prediction Workshops.^ Soil scientists in the

North Central States consider Russell silt loam

equal in erodibility to Fayette silt loam, for

which table 1 lists ÍL=0.38.

The slope-effect chart (fig. 2, p. 8), shows that,

for an 8-percent slope, 200 feet long, LS=1AI.

Figure 4 (p. 17), shows that Fountain County is

within the geographic area to which erosion-index

distribution curve No. 16 applies. Using curve

No. 16, figure 12, and soil-loss ratios taken from

table 2 (p. 12) or table 4 (p. 16), compute the C

value for the rotation by the procedure illustrated

in table 5 (p. 35). For the productivity level and

management practices assumed in this example,

factor C for a W-M-C-C rotation in area 16 was

shown in table 5 to equal 0.119.

Table 6 (p. 36) shows a practice-factor value of

0.6 for contouring on 8-percent slope, and table 7

See footnote 3, p. 2.
RAINFALL-EROSION LOSSES FROM CROPLAND 39

(p. 37) indicates that the 200-foot slope is not too

long for this factor to be applicable. Therefore,

under the conditions assumed in this example,

P=0.6.

The next step is to substitute the selected

numerical values for the symbols in the erosion

equation and solve for A. In this example,

^=185X0.38X1.41X0.119X0.6=7.1 tons of soil

loss per acre per year.

If planting had been up and down slope, instead

of on the contour, the factor P would have

equaled 1.0, and the predicted soU loss for this

field would have been 185X0.38X1.41X0.119X

1.0=11.8 tons per acre.

Had contour farming been combined with

minimum tillage for all corn in the rotation, the

value of the factor C would have been 0.075 (see

table 5). The predicted average annual soil loss

from the field would then have been 185 X 0.38 X

1.41X0.075X0.6=4.5 tons per acre.

Crop-Year Averages

The soil losses computed in the example are

rotation averages over a long time period. Thus,

the heavier losses experienced during the corn

years are diluted by trivial losses during the

meadow year. Please refer again to the first

solution above, in which the rotation average was

7.1 tons per acre per year. The 4-year loss from

each complete rotation cycle would average

4X7.1, or about 28.4 tons per acre.

Use of the values in column 8 of table 5 enables

one to compute the average soil loss for each of the

4 crop years. Column 8 shows a computed C

value of 0.0787 for the wheat period and a C

of 0.4764 for the entire 4-year period. The

average yearly soil loss from wheat in the above

example, with contouring, would be 28.4 X

0.079/0.476, or 4.7 tons per acre. First-year corn,

including the winter period, would average

28.4X0.151/0.476, or 9.0 tons. The second-year

com would average 28.4X0.242/0.476, or 14.4 tons,

and the 20-month meadow period would average

less than 0.5-ton soil loss per acre.

Soil-Loss Probabilities Other Than Average

Because rainfall differs from year to year, the

actual value of the tactor R also differs from year

to year at any given location. Appendix table

11 lists 50-, 20-, and 5-percent probability values

of Ä at 181 key locations. These may be used

for further characterization of soil-loss hazards.

Fountain, County, Ind. (where our example was

located), is not Hsted in the table, but figure 1

shows that the R value there is essentially the

same as the R value at IndianapoUs. Table 11

shows that, over a long period, the value of the

factor R will equal or exceed 225 at Indianapolis

in 20 percent oí the years. This is 225-^185, or

1.22 times the average value. Returning once

more to the example, soU loss from second-year

corn on the assumed field would be expected to

exceed 1.22X 14.4= 17.6 tons per acre in 20 percent

of the years. The 5-percent probability value of

R at Indianapolis is shown in table 11 to be 302,

or 1.63 times the average value of 185. Therefore,

soil loss from the second-year corn on the field

assumed for our example would be expected to

exceed 1.63X14.4 =23.5 tons per acre in 5 percent

of the years if the corn is contoured. Without

contouring it would exceed 23.5-^-0.6 =39.2 tons

per acre in 5 percent of the years.

Individual-Storm Soil Losses

The assembled plot data show conclusively that

the relation of soil loss to such major factors as

slope, cropping, management, and conservation

practices is not the same from storm to storm or

from year to year, even on the same field under a

continuing rotation. In a particular rainstorm,

the factor relations are influenced by such variables as antecedent moisture, tillage, tractor and

implement compaction, soil crusting by prior

rains, and progressive changes in plant cover.

Daily soil moisture and temperatures are more

favorable to rapid development of good protective

cover in some years than in others. The factor

values reported in the preceding section and used

in the foregoing examples represent average factor

relations derived from research measurements over

an extended period. Therefore, the erosion equation is particularly designed to predict average

annual soil loss from any specific field over an

extended period.

Predictions of individual-storm soil losses will

be less accurate, because effects of the minor

variations in antecedent conditions cannot be

precisely evaluated at this time. However, valuable estimates of single-storm losses can be computed by the following procedure.

Instead of taking the value of R from figure

1, let Ä equal the computed erosion-index value

for the specific rainstorm. Instead of the C

value for the rotation, let C in the equation

equal the soil-loss ratio shown in table 2, 3, or 4

for the specific conditions existing on the field

at the time of the rain. For example, appendix

table 12 shows that a 10-year rain at IndianapoUs

has an erosion-index value of 75 or more. Assume

that such a rain occurred about 3 weeks after

planting the second-year corn in the preceding

example. The existing condition is then described by line 13 of table 2. Since the rain

occurred within 30 days after corn planting,

the value of C at the time of this particular

rain is 48. The value of R is 75. Other values

in the equation remain the same as in the first

solution. The estimated soil loss from this

single rainstorm on the second-year corn, without

contouring, is then RKLS'C'P^löXO.SSXlAl

X0.48X 1.0= 19.3 tons per acre.
40 AGR. HANDBOOK 2 82, U.S. DEPARTMENT OF AGRICULTURE

Specific-Year Soil Losses

Soil loss from a particular field in any specific

year cannot presently be predicted in advance,

primarily because it is not presently possible to

predict the size and time of the rainstorms that

will occm* in that year. Deviations from average

are very great. Surface conditions, quality of

cover, and minor factors in tillage and management may also differ significantly from the

average for that field. However, the erosion

equation can provide reasonably reliable estimates of soil loss in a particular past year, if

detailed rainfall records were obtained. Storm

El values need to be computed from the specific

year's rainfall records, and the soil loss must be

computed for each crop-stage period separately.

This is done by letting R equal the erosion index

measured for the crop-stage period and letting

C equal the soil-loss ratio taken from table 2,

as in the example for estimating individualstorm soil losses.

Even though a particular year's precipitation

may. have been essentially equal to the average

annual rainfall in inches at that location, this

fact is not justification for selecting R and C

values from figure 1 and table 11 to estimate

the soil loss for that particular year. Even with

normal annual precipitation, the erosion index

may have been well above or below normal

because of abnormal intensities. The monthly

distribution of the erosive rains may also have

deviated significantly from normal.

Significance of Average Field Soil Loss

Knowledge of quantitative rates of erosion and

soil-loss tolerances provides specific guidelines for

effective erosion-control planning. Such values

are, however, to be looked upon as guides that

sometimes need to be tempered with judgment.

It is important to bear in mind that the accepted

expression for average rate of erosion from a

field—^tons of soil loss per acre—^is not intended

to imply imiform soil movement over the entire

field area. Since soil loss increases as the 0.5

power of slope length, the erosion rate on the upper

quarter of a field with a single uniform slope is

about half the field average and that on the lower

quarter is about IK times the field average.

Because of the erodibility of the lower ends of

long uniform or convex slopes, it may be appropriate to recommend subdividing such a slope

even though the estimated average soil loss for

the entire length is within the tolerance limit. On

irregular topography, serious erosion may occur

in some parts of a field while deposition occurs in

others. In such cases, the erodible slopes need to

be taken as the limiting factor for the field.

DeterminingAlternative Waysin Which

a Particular Tract of Land May

Be Used and Treated Successfully To

Conserve or Improve It

The soil-loss prediction procedure provides the

practicing conservationist with concise readyreference tables from which he can ascertain, for

each particular situation encountered, which

specific land use and management combinations

will provide the desired level of erosion control.

A number of possible alternatives are usually indicated. From these, the farmer will be able to

make a choice, in line with his desires and financial

resources.

Management decisions generally influence erosion losses by affecting the factor (7 or P in the

erosion equation. The factor L is modified only

by terracing. The other three factors—Ä, K, and

S—are essentially fixed so far as a particular field

is concerned. WTien erosion is to be Hmited to the

maximum allowable, or tolerance rate, the term

A in the equation is replaced by T, and the equation is rewritten in the form: CP=T/RKLS.

Substituting the locational values of the fixed

factors in this equation and solving for CP give the

maximum value that the product CP may assume

under the specified field conditions. With no

conservation practices, the most intensive cropping plan that can be safely used on the field is

one for which the factor C just equals this value.

When a conservation practice such as contouring

or stripcropping is added, the computed value of

T/RKLS is divided by the practice factor, P,

to obtain the maximum permissible croppingmanagement factor value. With terracing, the

value of T/RKLS is increased by decreasing the

value of i.

A special sHde rule recently designed in Tennessee (17) enables rapid and systematic computation of T/RKLS for any specific situation after

pertinent values of the factors have been selected

from the tables and charts.

Since a practicing conservationist usually works

within the limits of a single county or other

small geographic area, he will usually be concerned

with only one value of R, one erosion-index distribution curve, K and T values for only a few

soils, and C values for only a limited number of

cropping systems. Therefore, the R value for his

county, a hst of T and K values for the soils in his

work area, a few brief tables of pertinent T/RKLS

values, and a table of C values for pertinent rotations will provide all the information he will need

to use this procedure as a guide to selection of

conservation practices. He will rarely, if ever,

need to solve the equation or to perform computations in the field.

The T/RKLS values are the maximum allowable C values for the various soil and slope com-
RAINFALL-EROSION LOSSES FROM CROPLAND 41

binations in the conservationist's work area.

They may be included in his handbook in the form

illustrated by table 9, with a table for each major

soil type with which he is concerned.

C values for rotations may be centrally computed for all cropping systems encountered

within a given erosion-index distribution area

(fig. 4), based on average seeding and harvest

dates within that area. The factor for each

cropping system needs to be computed for each

of several crop-productivity levels and for each

of several methods of residue management and

seedbed preparation. The results are then hsted

in a table in order of decUning magnitude of

C, as illustrated in table 10.

To illustrate the selection process, we will

assume a field in a coimty having a rainfall factor

of 180, located within the erosion-index distribution area in which the C values of table 10 apply.

Assume that the soil on this field has a K value

of 0.33 and a soil-loss tolerance of 4 tons per acre

per year. Past yields on the field have been

from 2 to 3 tons hay and from 40 to 60 bushels

corn per acre, with conventional seedbed preparation and tillage.

The land slope averages about 3 percent over

the upper half of a total 400-foot slope, but the

lower half steepens considerably and ranges from

5 to 7 percent. The field is planted as a single

unit. In conservation farming, soil movement

from the most vulnerable part of the field should

be held below the tolerance limit, T. Therefore,

the gradient of the lower half of the field is the

significant percentage of slope for the soil loss

estimate. However, surface rimoflF from the

upper half passes over the lower half. Therefore,

the overall length will be the effective slope

length. Thus, a slope length of 400 feet and a

slope gradient of 6 percent would be used to

enter the ready-reference table.

For this soil and slope combination, table 9

lists a maximum CP value of 0.050. Entering

table 10 with this value, the farmer finds that with

straight rows and conventional tillage at the F2

yield level, the most intensive cropping system he

can safely use is 1 year of com in 5 years (C-O-MM-M). Any system having a C value less than

that for C-0-M-M-M should provide better

than the tolerable level of erosion control under

the conditions assimied for this example.

With contour farming, the maximum C value

would be 0.10 (table 9), and he could move up

the Ust in table 10 to a C-OO-M-M-M system.

Improvement in his general level of fertility

and residue management would enable the farmer

to use a more intensive cropping system safely or

to attain a higher level of conservation, while at

the same time increasing his crop yields. If he

were able to reach and maintain average yields

equal to F3 in table 10, he could move up to a

C-O-M-M rotation without contoming or to

C-C-0-M-M with contouring. If he then also

added wheeltrack planting and minimimi tillage

for corn, he could move up the Hst to 2 years of

corn and 1 year meadow in a C-C-O-M rotation.

Thus, the tables, show the farmer how he can

improve his erosion-control program and still

increase yields or decrease labor and tractor

costs.

A system of terraces would break the slope

length and permit a higher degree of conservation

or more intensive cropping systems. Terraces at

about 100-foot horizontal intervals would reduce

the effective slope length from 400 feet to 100

feet. For a 6-percent slope 100 feet long, contoured, table 9 shows a maximum C7 value of 0.20.

This would permit any of the cropping systems

hsted in table 10 up to 3 years of corn in 5

(C-C-C-0-M) or a 2-year system of corn and

oats with sweetclover intercrop. With wheeltrack planting, a 3-year rotation of corn, corn,

oats-and-sweetclover would also appear satisfactory.

Estimating Source Sediment From

Watersheds

Cultivated farm fields are a major sediment

source in the general agricultural area of the

humid and subhumid zones. The soil-loss prediction equation may be used effectively in making

predictions of the magnitude of this sediment

soiu*ce. Other soiKces of sediment production

that must be considered in making estimates of

total sediment loads include gullies, roadside

areas, and residential subdivisions.

The erosion equation provides a methodical

means of bringing the effects of expected rainfall

pattern, sou properties, and land use into computation of that part of the sediment production that

is attributable to sheet and rill erosion. The

drainage area may be broken down into a series

of tracts having relatively homogeneous land use

and treatment. The erosion equation is then

used to approximate the average annual rate of

soil movement from each tract.

However, sediment estimates computed in this

manner are estimates of average annual sediment

production over a period of at least 25 years or

more. Gross erosion on the watershed in any one

particular year may be at least three or four times

this average rate. In other years it will be less.

This is true for a number of reasons. Table 11

shows that in one year out of 20, the rainfall

erosion index is at least twice the average for that

location. At the same time, abnormal distribution of erosive rains may result in a greater than

average portion of the erosive rainfall occurring

when the fields are most vulnerable to rainfall

erosion. Breakover of contour rows in a severe

rainstorm may increase greatly the gross erosion

from that storm and also from succeeding storms

until the break is obhterated by tillage. Adverse
42 AGR. HANDBOOK 2 82, U.S. DEPARTMENT OF AGRICULTURE

TABLE 9,—Maximum permissible C values (T/RKLS)for indicated gradient and slope length wUh straight

and with contoured rows jor soil type with the K, T, and R values as listea

For soil type with ^-=0.33, T=4 or K=0.25, T=3, and R=m. ^_^

Gradient (percent)

2.

4-

6-

8-

10

12

14

16

18

20

2-

4.

6-

8-

10

12

14

16

18

20

60

0.45

.22

.13

.089

.064

.048

.038

.030

.025

.021

0.75

.44

.26

.15

.11

.08

.048

.038

.031

.023

Values for slope length (in feet) of—

80 100

0.58 0.57

.38 .34

.22 .20

.13 .11

.093 .083

.070 .062

.041 .036

.032 .030

.027 .024

.020 .018

150 200

STRAIGHT ROW

0.35 0.33 0.26

.19 .17 .13

.11 .10 .083

.077 .068 .055

.056 .050 .040

.042 .037 .030

.033 .029 .024

.026 .024 .019

.022 .019 .016

.018 .016 .013

0.22

.11

.072

.048

.035

.026

.020

.016

.014

.011

CONTOURED

0.43

.26

.17

.092

.067

.050

.030

.024

.020

.014

0.37

.22

.14

.080

.058

.043

.025

.020

.018

.012

250

0.20

.10

.065

.043

.030

.023

.018

.015

.012

0.33

.20

.13

.072

.050

.038

.022

.019

.015

300

0.17

.092

.058

.039

.028

.021

.017

.013

0.28

.18

.12

.065

.047

.035

.021

.016

400

0.15

.081

.050

.034

.024

.018

.014

.012

0.25

0.16

.10

.057

.040

.030

.018

.015

weather in one year may cause widespread meadow

failure within the watershed area. Gross erosion

from the first-year and second-year rotation corn

after a poor meadow will then be substantially

greater than normal and may nearly equal that

from continuous row cropping. Furthermore,

one segment of the watershed may receive a

severe rainstorm while another segment of the

same watershed receives Httle or no rain. Location of the storm center will differ from one storm

to another, so that the long-time average rainfall

may be nearly uniform. However, specific-storm

or specific-year values of both R and C may deviate

a great deal from their average values for that

location. When gross erosion is to be estimated

for a specific short-term period for evaluation of

sediment delivery rates, the specific El value and

soil-loss ratio for each successive crop-stage

period must be used in lieu of the annual erosion

index and the rotation C value. (Refer to page 39

for details.)

Correct interpretation of watershed conditions

for selection of appropriate values of the factors

L and S is also very important, but interpretation

is frequently quite difficult because of complex

topography. Complex soil and land use patterns

superimposed upon a complex topography present

problems in interpretation and factor evaluation

that need further research analysis. However,

the definition of slope length, page 9, and the

discussion of convex and concave slopes, page 8,

provide helpful guides. Slope shapes and drainage

patterns need to be carefully considered. A steep

gradient at the lower end of a slope should not

be averaged with a gentle gradient at the upper

end. A slope length does not terminate simply

because of a wire fence or a change in cropping.

If runoff from an area above a field is allowed to

enter the field as sheet flow, the upper area is

part of the slope length for computing erosion on

the field. However, sufficient flattening of the

slope to cause deposition to begin indicates the

end of a slope length.

The suna of the estimates for the individual

tracts making up the watershed approximates the

quantity of soil moved from its original general

position. This initial sediment estimate must be

adjusted downward to compensate for deposition

in terrace channels, in sod waterways, in field

boundaries, and at the toe of field slopes. Further

changes in sediment content of runoff water will

occur during the stream transport phase.

The appropriate value of the factor P for a

terraced field is considerably lower for purposes
RAINFALL-EROSION LOSSES FROM CROPLAND 43

TABLE 10.—Partial list of C values for common rotations for a specific erosion-index distribution area ^

Croppine system ^

C values for RdL, disked for small grain, spring-plowed for corn

Conventional plant and till ^ Minimum tillage ^

Rotations Limits 3 Y, Y, Fa Y, F3

Continuous corn __ 0.48

.36

.32

.25

.25

0.43

.31

. 27

0.38

.27

.24

0.33

.23

0 27

C-C-C-Ox - - - . 19

C-C-Ox i • 19 . 17

C-C-C-0-M .20

. 18

. 19

. 17

. 12

. 14

.13

. 12

C-0, - - . 12

C-C-O-M

y.

. 19

. 15

. 13

. 13

. 12

. 14 i . 10 . 082

C-C-0-M-M . 12 ! • ^^ .081

.068

. 064

.052

. 066

C-C-O-M-M-M .096

.083

.079

.082

.058

.058

.057

C-O-W-M

C-O-M _- - .

.049

.037

C-O-M-M .088

.071

.060

.060 i . 045 .040

.033

.028

.029

C-0-M-M-M

C-0-M-M-M-M

.049

.042

.036

.031

.024

.020

CL

1 Area shown in fig. 12 for curve No. 16.

2 Abbreviations: C—corn, O—oats, O,—oats with sweet

clover intercrop, W—fall-seeded grain, M—grass and

legume meadow, RdL—residues left.

' Dashed lines indicate cropping system Hmits for: a,

of watershed sediment prediction than it is for

purposes of erosion-control planning. As much

as 90 percent of the soil eroded from the area

between terraces may be deposited in the channels

{28), For sediment prediction, the important

consideration is the quantity of soil moved completely of the field. For this purpose, P values

equal to about 20 percent of the contour practice

values shown in table 6 are recommended.

When rimoff from a cropped field enters a grass

straight-row farming; 6, contomring; c, terraces. Acceptable rotations are those below the lines.

* Y\—average yields of 1 to 2 tons hay, 40 to 59 bu. corn.

Y2—average yields of 2 to 3 tons hay, 60 to 74 bu. corn.

Yz—average yields of 3 to 5 tons hay, 75 to 100 bu. corn.

waterway or crosses a sodded fence row or streambank area to enter a main drainageway, part of

the silt load is filtered out by the sod, as it is in a

cultivated field with contour stripcropping. If

the gradient decreases significantly between the

lower end of the cropped field and the point where

the runoff enters the drainageway, deposition may

occur even if the area is not sodded. Factors to

adjust gross-erosion estimates for these situations

have not been evaluated.

SUMMARY

The soil-loss prediction procedure presented

in this handbook provides a methodical means

for using all available research information to

help guide land use and management decisions

on any particular farm field where soil erosion

by rainfall and runoff is a problem. The soilloss prediction equation presented is universally

apphcable wherever locational values of the

equation's individual factors are known or can

be determined. Research data assembled from

all major agricultural areas of the United States

were analyzed and summarized in ready-reference

tables and graphs. These provide a source of

information for approximating the factor values

needed to apply the equation to the specific

conditions in the various geographic areas.

Data and procedures are presented in considerable detail, to help the user interpret the

guides suppUed by solutions of the equation.

Apphcations of the procedures are illustrated in

specific examples.

Use of the equation, tables, and figures for

predicting soil erosion losses on any particular
44 AGR. HANDBOOK 2 82, U.S. DEPARTMENT OF AGRICULTURE

field, under each of various alternative cropping

systems and management practices, is not a

complicated procedure. Comparison of the predicted erosion rates with the applicable soil-loss

tolerance provides very specific guidelines for

effecting erosion control within specified limits.

For the selection of practices on an mdividual

farm, the procedure can be reduced to use of a

few reference tables derived for the particular

geographic area.

LITERATURE CITED

(1) BROWNING, G. M., PARISH, C. L., and GLASS, J. A.

1947. A METHOD FOR DETERMINING THE USE AND

LIMITATION OF ROTATION AND CONSERVATION

PRACTICES IN CONTROL OF SOIL EROSION IN

IOWA. Amer. Soc. Agron. Jour. 39: 65-73.

(2) BLAKELY, B. D., COYLE, J. J., and STEELE, J. G.

1957. EROSION ON CULTIVATED LAND. In Soil, U.S.

Dept. Agr. Yearbook, pp. 290-306.

(3) HILL, H. O., PEEVY, W. J., MCCALL, A G., and BELL,

F. G.

1944. INVESTIGATIONS IN EROSION CONTROL AND

RECLAMATION OF ERODED LAND AT THE

BLACKLAND CONSERVATION EXPERIMENT STATION, TEMPLE, TEX., 1931-41. U.S. Dept.

Agr. Tech. Bui. 859, 109 pp.

(4) LiLLARD, J. H., ROGERS, H. T., and ELSON, JESSE.

1941. EFFECTS OF SLOPE, CHARACTER OF SOIL,

RAINFALL, AND CROPPING TREATMENTS ON

EROSION LOSSES FROM DUNMORE SILT LOAM.

Va. Agr. Expt. Sta. Tech. Bui. 72, 32 pp.

(5) LLOYD, C. H., and ELEY, G. W.

1952. GRAPHICAL SOLUTION OF PROBABLE SOIL

LOSS FORMULA FOR NORTHEASTERN REGION.

Jour. Soil and Water Conserv. 7: 189-191.

(6) MiDDLETON, H. E., SLATER, C. S., and BYERS, H. G.

1932. PHYSICAL AND CHEMICAL CHARACTERISTICS

OF THE SOILS FROM THE EROSION EXPERIMENT STATIONS. U.S. Dept. Agr. Tech.

Bui. 316, 51 pp.

(7) SLATER, C. S., and BYERS, H. G.

1934. THE PHYSICAL AND CHEMICAL CHARACTERISTICS OF THE SOILS FROM THE EROSION

EXPERIMENT STATIONS SECOND REPORT.

U.S. Dept. Agr. Tech. Bui. 430, 62 pp.

(8) MOLDENHAUER, W. C., and WiSCHMEIER, W. H.

1960. SOIL AND WATER LOSSES AND INFILTRATION

RATES ON IDA SILT LOAM AS INFLUENCED BY

CROPPING SYSTEMS, TILLAGE PRACTICES AND

RAINFALL CHARACTERISTICS. Soil Sci. SOC.

Amer. Proc. 24: 409-413.

(9) MUSGRAVE, G. W.

1947. THE QUANTITATIVE EVALUATION OF FACTORS

IN WATER EROSION, A FIRST APPROXIMATION.

Jour. Soil and Water Conserv. 2: 133-138.

(10) OLSON, T. C., and WISCHMEIER, W. H.

1963. SOIL-ERODIBILITY EVALUATIONS FOR SOILS

ON THE RUNOFF AND EROSION STATIONS.

Soil Sei. Soc. Amer. Proc. 27: 590-592.

(11) PEELE, T. C., LATHAM, E. E., and BEALE, O. W.

1945. RELATION OF THE PHYSICAL PROPERTIES OF

DIFFERENT SOIL TYPES TO ERODIBILITY.

S. C. Agr. Expt. sta. Bui. 357, 31 pp.

(12) SMITH, D. D.

1941. INTERPRETATION OF SOIL CONSERVATION DATA

FOR FIELD USE. AgT. Engin. 22: 173-175.

(13)

(14)

(15)

(16)

(17)

(18)

(19)

(20)

(21)

(22)

(23)

(24)

(25)

(26)

(27)

(28)

and WHITT, D. M.

1947. ESTIMATING SOIL LOSSES FROM FIELD AREAS OF

CLAYPAN SOILS. SoU Sci. Soc. Amcr. Proc.

12: 485-490.

and WHITT, D. M.

1948. EVALUATING SOIL LOSSES FROM FIELD AREAS.

Agr. Engin. 29: 394-396.

and WISCHMEIER, W. H.

1957. FACTORS AFFECTING SHEET AND RILL EROSION.

Amer. Geophys. Union Trans. 38: 889-896.

and WISCHMEIER, W. H.

1962. RAINFALL EROSION. Advances in Agronomy,

V. 14, pp. 109-148. Academic Press, Inc.,

New York, N.Y.

SPRINGER, D. K., BREINIG, C. B., and SPRINGER,

M. E.

1963. PREDICTING SOIL LOSSES IN TENNESSEE.

Jour. Soil and Water Conserv. 18(4): 157-

158.

U.S. AGRICULTURAL RESEARCH SERVICE.

1961. A UNIVERSAL EQUATION FOR PREDICTING

RAINFALL-EROSION LOSSES. U.S. Dept. AgT.

ARS 22-66, 11 pp.

VAN DOREN, C. A., and BARTELLI, L. J.

1956. A METHOD OF FORECASTING SOIL LOSSES.

Agr. Engin. 37: 335-341.

WISCHMEIER, W. H.

1955. PUNCHED CARDS RECORD RUNOFF AND SOILLOSS DATA. Agr. Engin. 36: 664-666.

1959. A RAINFALL EROSION INDEX FOR A UNIVERSAL

SOIL-LOSS EQUATION. SoÜ Sci. SoC. AmCF.

Proc. 23: 246-249.

1960. CROPPING-MANAGEMENT FACTOR EVALUATIONS

FOR A UNIVERSAL SOIL-LOSS EQUATION. Soil

Sci. Soc. Amer. Proc. 24: 322-326.

1962. RAINFALL EROSION POTENTIAL. Agr. Engin.

43: 212-215.

1962. STORMS AND SOIL CONSERVATION. JOUT. Soil

and Water Conserv. 17(2) : 55-59.

and SMITH, D. D.

1958. RAINFALL ENERGY AND ITS RELATIONSHIP TO

SOIL LOSS. Amer. Geophys. Union Trans.

39: 285-291.

and SMITH, D. D.

1961. A UNIVERSAL SOIL-LOSS ESTIMATING EQUATION

TO GUIDE CONSERVATION FARM PLANNING.

7th Cong. Internatl. Soil Sci. Soc. Trans, v.

1, paper 2.

SMITH, D. D., and UHLAND, R. E.

1958. EVALUATION OF FACTORS IN THE SOIL LOSS

EQUATION. Agr. Engin. 39: 458-462, 474.

ZiNGG, A. W.

1940. DEGREE AND LENGTH OF LAND SLOPE AS IT

AFFECTS SOIL LOSS IN RUNOFF. Agr. Engin.

21: 59-64.
RAINFALL-EROSION LOSSES PROM CROPLAND 45

APPENDIX

TABLE 11.—Observed range and 5-, ¡80-j and 50-percent

probability values of erosion index at each of 181 key

locations

TABLE 11.—Observed range and 5-, 20-j and 60-percent

probability values of erosion index at each of 181 key

locations—Continued

Location

Alabama:

Birmingham

Mobüe - —.

Montgomery

Arkansas:

Fort Smith.-

Little Rock

Mountain Home

Texarkana

California:

RedBlufl

San Luis Obispo

Colorado:

Akron

Pueblo

Springfield

Connecticut:

Hartford.

New Haven

District of Columbia

Florida:

Apalachicola

Jacksonville

Miami

Georgia:

Atlanta-.-

Augusta

Columbus

Macon

Savannah

Watkinsvllle ^

Illinois:

Cairo

Chicago

Dixon Springs i

Moline

RantoulSpringfield

Indiana:

Evarsvllle

Fort Wayne

Indianapolis

South Bend

Terre Haute

Iowa:

Burlington

Charles City

Clarinda i

Des Moines

Dubuque --

Sioux City

Rockwell City

Kansas:

Burlingame

Cofleyville

Concordia

Dodge City

Goodland

Haysi

Wichita

Kentucky:

Lexington

Louisville

Middlesboro

Louisiana:

Lake Charles

New Orleans

Shreveport

Maine:

Caribou

Portland

Skowhegan

Maryland, Baltimore..

Massachusetts:

Boston -

Washington

Michigan:

Alpena

Detroit

East LansingGrand Rapids

Values of erosion index {El)

Observed

22-year

range

179-601

279-926

164-780

116-818

103-€25

9^-441

137-^64

11-240

5-147

8-247

&-291

4-246

60-percent

probability

354

673

359

254

308

206

325

54

43

72

44

79

20-percent

probability

461

799

482

400

422

301

445

70

129

93

138

6-percent

probability

692

940

638

614

569

432

600

171

113

225

189

233

65-356 133 188 263

66-373 157 222 310

84-334 183 250 336

271-944 629 663 820

283-900 640 693 876

197-1225 529 784 1136

116-549 286 377 488

14&-476 229 308 408

215-514 336 400 473

117-493 282 357 447

197-886 412 671 780

182-544 278 362 441

126-575 231 349 618

50-379 140 212 316

89-581 225 326 465

80-369 158 221 303

73-286 162 201 263

38-316 164 210 283

104-417 188 263 362

60-276 127 183 259

60-349 166 225 302

43-374 137 204 298

81-413 190 273 389

65-286 162 216 284

39-308 140 206 295

76-376 162 220 296

30-319 136 198 284

64-389 176 261 366

66-336 135 205 308

40-391 137 216 335

67-447 176 267 398

66-546 234 339 483

38-669 131 241 427

16-421 98 175 303

10-166 76 116 171

66-373 116 182 279

42-440 188 292 445

64-396 178 248 340

84-296 168 221 286

107-301 164 197 248

200-1019 672 786 1063

27a-1366 721 1007 1384

143-707 321 446 609

26-120 68 79 106

36-241 91 131 186

39-149 78 108 148

60-388 178 263 381

39-366 99 169 262

66-229 116 163 198

14-124 67 86 124

66-179 100 134 177

36-161 86 121 166

33-203 84 123 178

Values of erosion index {El)

Location

Observed

22-year

range

50-percent

probability

20-percent

probability

6-percent

probabiUty

Minnesota:

AlexATidiia. 33-301

7-227

22-205

19-173

46-338

37-290

216-820

131-670

165-786

98-419

28-361

64-410

105-415

97-333

50-359

59-737

2-82

3-62

1-101

18-131

44-289

34-217

14-236

69-312

4-169

52-212

71-318

58-331

37-382

0^6

5-159

40-172

20-151

20-148

33-180

24-241

22-180

31-202

8-219

76-238

113-526

102-357

152-569

196-701

9-189

21-171

5-213

4-71

66-352

21-186

29-188

45-228

72^26

56-245

32-189

100-678

49-320

69-441

105-741

19-684

2-28

16-80

11-634

60-228

48-232

72-361

88

84

62

94

142

96

416

310

365

214

170

189

209

199

178

168

12

13

21

60

133

96

81

154

64

91

166

186

149

10

41

81

76

66

73

74

66

70

83

135

229

184

280

358

43

56

62

30

146

93

96

113

158

125

83

263

167

210

272

247

4

40

96

97

105

156

147

127

108

135

207

154

557

413

493

297

248

271

287

266

257

290

26

24

40

86

201

142

136

205

100

131

229

254

216

19

73

114

106

96

106

112

101

106

129

175

322

244

379

497

73

90

113

46

211

132

129

158

235

175

120

395

242

316

411

347

8

66

181

136

146

210

240

Duluth 189

Fosston... 184

MlTiTieftpf^Hs 190

Rochester 297

Springfield - 243

Mississippi:

MftridiftTi . _ 737

Oxford -- 643

Vicksburg 668

Missouri:

Columbia 406

ITansas Citv 356

McCredie^ 383

Rolla 387

Sürinefleld .. . 352

St Joseph 366

St. Louis 488

Montana:

Billlnes 50

Great Falls .

44

Miles City 72

Nebraska:

Antioch 120

lilno-olTi - - - 299

Lynch 206

North Platte 224

Scribner .-

269

Valentine . - 163

New Hampshire, Concord -

187

New Jersey:

Atlantic Citv 311

Marlboro ^ 343

Trenton 308

New Mexico:

AlbuQueraue 36

Roswell 128

New York:

Albany ---

169

Binghamton 146

Buffalo -

139

Geneva ^ 152

Marcellus ^ 167

Rochester 151

Salamanca 157

S37Tacuse 197

North Carolina:

AsheviUe 223

Charlotte ..-

443

Greensboro -

320

Raleieh 506

Wilmincrton 677

North Dakota:

Bismarck 120

Devils Lake 142

Fargo 200

Williston 67

Ohio:

Cincinnati 29S

Cleveland 18£

Columbiana 172

Columbus 2ie

Coshocton *

34:

Dayton 24(

Toledo 17(

Oklahoma:

Ardmore 58Í

Cherokee ^ 34Í

Guthrie 1

46'

McAlester -

601

Tulsa 47Í

Oregon:

Pendleton .

1

Portland 7

Pennsylvania:

Erie 33

Franklin 18

Harrisbure 19

Philadelphia 28

See footnote at end of table.
46 AGR. HANDBOOK 2 82, U.S. DEPARTMENT OF AGRICULTURE

TABLE 11.—Observed range and 5-, 20-, and SO-percent

probability value of erosion index at each of 181 key

locations—Continued

TABLE 12.—Expected magnitudes of single-storm erosion

index values

Location

Pennsylvania—Con.

Pittsburgh

Reading

Scranton

Puerto Rico, San Juan. __

Rhode Island, Providence.

South Carolina:

Charleston

Clemson i

Columbia

Greenville

South Dakota:

Aberdeen

Huron

Isabel

Rapid City

Tennessee:

Chattanooga __

Knoxville.-

Memphis

Nashville

Texas:

Abilene.

Amarillo

Austin

Brownsville

Corpus Christi

Dallas

Del Rio

El Paso

Houston

Lubbock

Midland

Nacogdoches

San Antonio

Temple 1

Victoria

Wichita Falls

Vermont, Burlington

Virginia:

Blacksburg »

L3mchburg

Richmond.-

Roanoke

Washington:

Pullman i

Spokane

West Virginia:

Elkins

Huntington

Parkersburg

Wisconsin:

Oreen Bay

LaCrosse » Madison

Milwaukee

Rice Lake

Wyomüig:

Casper

Cheyenne

Values of erosion index {El)

Observed

22-year

range

43-201

84-308

52-198

203-577

63-225

174-1037

138-624

81-461

130-589

19-295

18-145

16-141

10-140

163-468

64-370

139-695

116-381

27-554

33-340

69-669

46-652

124-569

93-630

19^06

4-85

176-1171

17-416

35-260

163-769

77-636

81-644

108-609

79-668

33-270

81-245

64-366

102-373

78-283

1-30

1-19

43-223

66-228

69-303

17-148

61-385

38-261

31-193

24-334

1-24

8-66

60-percent

probability

111

144

104

345

119

387

280

213

249

74

60

48

37

269

173

272

198

146

110

270

267

237

263

121

18

444

82

82

401

220

261

265

196

72

126

164

208

129

118

127

120

77

153

118

93

122

9

28

20-percent

probability

148

204

140

446

167

559

384

298

350

129

91

78

64

348

239

384

262

263

184

414

386

330

396

216

36

674

168

139

671

353

379

385

298

114

168

232

276

176

12

11

168

173

165

107

228

171

139

202

15

43

6-percent

probability

194

285

188

666

232

796

519

410

487

219

136

125

108

445

325

636

339

427

299

624

649

451

586

374

67

1003

296

228

801

556

542

561

447

178

221

324

361

237

21

17

209

233

226

147

331

245

202

327

26

66

Í Computations based on ARS-SWC rainfall records,

based on Weather Bureau records.

All others are

Index values normally exceeded once In—

Location

1

year

2

years

6

years

10

years

20

years

Alabama:

Birminsham 54

97

62

43

41

33

51

13

11

22

17

31

23

31

39

87

92

93

49

34

61

63

82

52

39

33

39

39

27

36

26

24

29

26

42

37

33

36

31

43

31

40

37

47

33

31

26

35

41

28

31

28

104

66

77

122

86

66

69

46

73

21

15

36

31

61

33

47

67

124

123

134

67

60

81

72

128

71

63

49

56

69

39

52

38

33

41

41

67

48

47

48

45

63

49

68

61

69

63

47

37

51

61

46

43

38

149

73

110

151

118

101

115

68

105

36

22

63

60

84

60

73

86

180

166

200

92

74

108

99

203

98

101

77

82

89

66

75

56

45

60

65

78

62

68

66

67

91

76

84

69

101

86

76

53

76

93

80

69

62

214

99

140

172

146

132

168

87

132

49

28

87

88

112

64

96

108

224

201

253

112

94

131

122

272

120

135

101

106

116

69

94

71

66

75

86

96

72

86

79

86

114

101

106

83

128

116

97

67

97

121

114

72

63

270

121

170

Mobile 194

Monteomerv 172

Arkansas:

Fort Smith 167

Little Rock 211

Mountain Home 106

Texarkana 163

California:

Red Bluff 66

San Luis Obispo 34

Colorado:

Akron 118

Pueblo _ 127

Springfield 162

Connecticut:

Hartford 79

New Haven 122

District of Columbia 136

Florida:

Apalachicola 272

Jacksonville 236

Miami — 308

Georgia:

Atlanta 134

Augusta -- 118

Columbus 162

Macon _ ._ 146

Savannah. 358

Watkinsville ... 142

Illinois:

Cairo 173

Chicago 129

Dixon Springs 130

Moline 145

Rantoul 82

Springfield 117

Indiana:

Evansville 86

Fort Wayne. 66

Indianapolis 90

South Bend _ 111

Terre Haute 113

Iowa:

Burlington 81

Charles City _ 103

Ciarinda 94

Des Moines . 105

Dubuque . _ _. 140

Rockwell City 129

Sioux City _ 131

Kansas:

Burlingame _ 100

Cofleyville 169

Concordia _. 164

Dodge City 124

Goodland 80

Hays 121

Wichita 160

Kentucky:

Lexington 161

Louisville 86

Middlesboro 73

Louisiana:

New Orleans 330

Shreveport... 141
RAINFALL-EROSION LOSSES FROM CROPLAND 47

TABLE 12.—Expected magnitudes of single-storm erosion

index values—Continued

TABLE 12.—Expected magnitudes of single-storm erosion

index values—Continued

Location

Maine:

Caribou

Portland

Skowhegan

Maryland, Baltimore

Massachusetts:

Boston

Washington

Michigan:

Alpena

Detroit

East Lansing

Grand Rapids

Minnesota:

Duluth

Fosston

Minneapolis

Rochester

Springfield --

Mississippi:

Meridian

Oxford

Vicksburg

Missouri:

Columbia

Kansas City —

McCredie _ —

Rolla _—

Springfield

St. Joseph

Montana:

Great Falls -.

Mues City

Nebraska:

Antioch

Lincoln -

Lynch

North Platte. _

Scribner

Valentine.

New Hampshire, Concord.

New Jersey:

Atlantic City

Marlboro

Trenton.

New Mexico:

Albuquerque

Roswell

New York:

Albany

Binghamton

Buffalo — —

Marcellus -

Rochester -

SaJamanca

Syracuse .- --

North Carolina:

Asheville

Charlotte

Greensboro

Ralei^i

Wilnüngton..- —

North Dakota:

Devils Lake

Index values normally exceeded once in—

1

year yesirs

Fargo

Williston.

Ohio:

Cincinnati---

Cleveland

Columbiana.

Columbus

Coshocton...

Dayton

Toledo

14

16

18

41

17

29

14

21

19

24

21

17

25

41

24

48

57

43

30

35

43

37

45

4

7

19

36

26

25

38

18

18

39

39

29

4

10

18

16

15

16

5

years

10

years

35

21

31

26

28

34

26

35

58

37

92

64

78

58

43

55

63

51

62

8

12

26

51

37

38

53

28

27

55

57

13 22

15 21

15 24

28 40

41 63

37 51

53 77

59 87

19 27

20 31

11 16

27 36

22 35

20 26

27 40

27 45

21 30

16 26

28

48

40

86

43

41

32

45

36

34

53

39

51

85

60

125

86

111

77

63

89

91

70

66

51

109

57

45

41

56

43

38

72

51

65

105

151

103

136

93

78

117

115

87

106

20

years

44

88

63

133

73

50

50

68

51

42

93

63

78

129

102

176

120

161

107

93

151

140

102

126

14 20 26

21 29 38

36 45 52

74 92 112

54 67 82

59 78 99

76 96 116

45 61 77

45 62 79

77 97 117

85 111 136

76 102 131

11 15 21

34 45 53

38 47 56

36 47 58

36 49 61

38 49 62

38 54 75

32 40 49

38 51 65

58 72 87

100 131 164

74 92 113

110 137 168

129 167 206

39 49 59

54 77 103

25 33 41

48 59 69

53 71 86

35 41 48

60 77 94

77 108 143

44 57 70

42 57 74

Location

Oklahoma:

Ardmore

Cherokee

Guthrie..

McAlester _

Tulsa

Oregon, Portland

Pennsylvania:

Franklin

Harrisburg

Philadelphia

Pittsburgh.. -

Reading

Seranton

Puerto Rico, San Juan

Rhode Island, Providence..

South Carolina:

Charleston

Clemson

Columbia

Greenville

South Dakota:

Aberdeen _

Huron

Isabel

Rapid City

Tennessee:

Chattanooga

Knoxville

Memphis

Nashville

Texas:

Abilene

Amarillo

Austin

Brownsville.-- -

Corpus Christi

Dallas

Del Rio

El Paso

Houston. __ _

Lubbock

Midland

Nacogdoches

San Antonio

Temple

Victoria

Wichita Falls

Vermont, Burlington

Virginia:

Blacksburg

Lynchburg

Richmond

Roanoke

Washington, Spokane

West Virginia:

Elkins

Huntington

Parkersburg

Wisconsin:

Green Bay

LaCrosse

Madison

Milwaukee

Rice Lake

Wyoming:

Casper

Cheyenne

Index values normally exceeded once in1

year

2

years

17

19

28

23

28

23

57

23

74

51

41

44

23

19

15

12

34

25

43

35

31

27

51

73

57

53

44

6

82

17

23

77

57

53

59

47

15

23

31

46

23

3

23

18

20

18

46

29

25

29

5

years

24

25

39

32

39

32

87

34

106

73

59

65

35

27

24

20

49

41

55

49

49

47

80

113

79

82

67

9

127

29

35

103

82

78

83

63

22

31

45

63

33

4

31

29

31

26

67

42

35

45

7

14

10

years

107

80

105

127

100

13

35

35

55

45

55

44

131

52

154

106

85

96

55

40

38

34

72

68

70

68

79

80

125

181

114

126

108

15

208

53

52

138

122

123

116

86

35

41

66

86

48

7

42

49

46

38

99

61

50

70

21

141

97

134

165

127

15

45

43

69

67

68

63

169

68

196

133

106

124

73

60

62

48

93

93

82

83

103

112

169

246

146

166

144

19

275

77

69

164

155

162

146

106

47

48

83

102

61

51

69

61

49

125

77

62

92

11

27

20

years

179

113

163

209

154

18

54

51

81

67

81

63

216

83

240

163

132

153

92

61

67

64

114

122

91

138

160

218

312

171

213

182

24

359

103

85

194

193

206

178

123

58

U.S. GOVERNMENT PRINTING OFFICE: 1965 O—760-705