Step 4: Having established the USLE factors for the post-
mining land use conditions, the predicted soil loss
can be calculated on a tons-per-acre-per-year basis.
Using acreage values, the annual tons per year from
the mine area can then be tabulated (Exhibit 5).

Having calculated the predicted soil loss from the
mine area under the pre- and post-mining condi-
tions, a comparison of the soil loss between the two
land use conditions can be made. The tabulated
information in Exhibits 4 and 5 shows:

Pre-Mining Condition
Predicted Annual

Land Area — Soil Loss from Area Area
Pastureland 1,239.4 T/Yr 4,190 Ac

Cropland 1,656.4 T/Yr 940 Ac
TOTAL
SOIL LOSS 2,895.8 T/Yr

Post-Mining Condition
Predicted Annual

Land Area — Soil Loss from Area Area
Pastureland 1,415.5 T/Yr 4,490 Ac

Cropland 302.4 T/Yr 640 Ac
TOTAL
SOIL LOSS 1,717.9 T/Yr

Under the assumptions and constraints of this
example, a reduction in predicted average soil loss
of 1,177.9 T/Yr would be realized.

It must be recognized that this projected reduction
in soil loss between pre- and post-mining land use is
the result of multiple changes in the USLE factors
that are assumed to be variable, i.e., LS, C, and P.
To ideally and fully utilize the USLE, the influence
of a change of any one factor would have on the
predicted soil loss and its relationship to changes in
the other factors should be examined, i.e., a change
in X units of *‘C’' is comparable to Y units of any
other variable. Thus; by knowing the factor-to-
factor relationships and having cost information
relating to the manipulation necessary to affect a
unit parameter change, a post-mining land use
scheme could be optimized in terms of economics
within the constraints of applicable reclamation
laws, standards, and physical constraints.

The establishment of the factor-to-factor relation-
ships is beyond the scope of this publication, but it
is felt that a brief example showing the influence of
changing one variable factor versus changing
another variable factor is important.

In the previous pre- and post-mining land use example,
it has been noted that in some instances several variables
changed for each sub-area. In order to see the influence a
change in variable factors can have on the predicted soil loss,
sub-area 2A will be examined.

The pre-mining land use condition for sub-area 2A in
Exhibit 4 are shown in Exhibit 6, Item I. The post-mining
land use conditions for the same sub-area from Exhibit 6,
[tem II.

A comparison of this information shows that the pre-
dicted annual soil loss from cropland sub-area 2A changes
from 598.4 T/Yr under pre-mining conditions, or a reduction
in soil loss of 396 T/Yr. This change is influenced by a
change in both the ‘*L"’ factor and the ‘*P’’ factor. To
examine the relative impact the changes of these two factors
have on the predicted soil loss, each factor shall be consi-
dered separately. First looking at only a change in the ‘*L””
factor, while maintaining the same **P"* factor (Item III), the
predicted soil loss becomes 404.4 T/Yr, indicating a 194.0
T/Yr reduction in predicting soil loss.

Secondly, looking at a change only in the ‘‘P"’ factor
while holding the ‘‘L** factor constant (Exhibit 6, Item IV)
shows the predicted soil loss would be 298.9 T/Yr or a 299.5
T/Yr reduction. It is readily seen that in this particular
example, the assumed change in ‘‘P’’ has a much more
significant affect on reducing the predicted soil loss than the
assumed changes in ‘‘L’’. It is also seen that the calculated
changes, as dictated by the individual factors, are not addi-
tive. The predicted annual average soil loss reduction from
sub-area 2A when both factors are changes, 396 T/Yr reduc-
tion, does not equal the sum of the individual change, 194.0
+ 299.5 T/Yr or 493.5 T/Yr reduction. | T/Yr reduction in
predicted soil loss obtained by a change in one variable, say
““L"’, and a | T/Yr reduction obtained by a change in another
variable, say **P’*, does not equal a 2 T/Yr change obtained if
both factors are changed. Being aware of the above and the
applicable laws, standards, and physical constraints, the land
manager can utilize the available information to maximize
those variables which lend themselves to manipulation most
economically and/or conveniently, putting lesser emphasis
on the more ‘‘difficult’’ factors in order to bring ‘*A’’ to the
desired level.


Appendix A—Continued

SOIL
SERIES

HYATTVILLE
HYDRO

HYRUM

HYSHAM
IGNACIO
ILDEFONSO

ILIAD
ILIFF

IMA

IMLAY

INAVALE

TNCHAU

INDART

INGA

TPAGE

PANO

IRIM

ROCK

TRONTON

ISBELL

TSMAY

Isom

IVES

WIE

IVINS

JACKS FSL,ST-FSL

L,cBHL

€B-CL,ST-CL

JACQUES L

cL

JAL

JAMES

JANSEN

SARITA
JARRE

AVA
JAYEM
JEKLEY
JELM
JENKINS
JENKINSON
JERAG
JERAULD
JERRY

gocrTy sic
SL

gocKo

JODERO
JOPLIN
JORDAN

JORNADA
JUDITH

DEPTH
INCHES

0-6
ond
44-21
24-60
0-17
17-42
42-57
0-60
0-25
0-9
9-60
0-6
6-13
13-66
0-8
8-22
22-34
0-10
10-60

0-8

12-60

0-10
10-26
26-44
44-60

183

+15

eon

SOIL
SERIES

JuDY
JUGET
JULESBURG
JUNCTION
Jupson
JURA

JUVAN
KADE,

KADOKA
KALISPELL

KAMACK

KANOSH

KAPOD

KARDE
KARRO

KASSLER
KATHER

KEARNS

KEBLER

KECH
KEELDAR

KEIGLEY
KEISER

KEITH
KELVIN

KEMMERER
KENNEBEC
KENO

KENSAL
KENSPUR
KEOTA
KERMIT
KERMO
KERRICK
KERSICK

KERWIN
KESSLER

KETTLE
KETINER
XEVIN
xEYA
KEYNER
KEZAR
KIDMAN
KIEV
XILBURN

KILDOR
KILFOIL

KILLPACK
KILN
KIM

KIMBROUGH
KTMNONS

KINESATA

0-60
0-10

10-30
30-42

0-8

4-16
0-10

12-50

0-13
13-60

4-24

10-31

CBV-L 0-3

26-40
40-60
0-17
0-30
30-60

0-6

6-18
18-60

0-10

232

+20
AT
128

17
+28
+32
243,
+28
37

+28
124

+28
+20

Riana

SOIL,
SERIES

KINKEAD
KINNEAR

KINREAD
KIPPEN

KIRKHAM
KIRTLEY
KISSICK
KITCHELL
KETTREDGE

KITTSON

KIWANTS

KJAR
KLONDIKE,
-KLOTEN
KAUTSEN
KOBAR
KOKAN
KOLLS
KOLOB
KOONICH
KORCHEA
KORNMAN
KOVICH
KRANZBURG

KRATKA
KRAUSE

REM
KREMLIN
KRENTZ

KUBE
KUBLER

KURO
KUTCH

KUTLER
KYLE

LABARGE

SA BRIER
LACHAPELLA
LACTTA
LADDER

LADELLE
LADNER

LAFONDA
LAHRITY
LAIL
LAJARA
LAKE CREEK

LAKEHELEN

LAKE JANEE
LAKEPORT
LAKESHORE

33-60

0-60

0-10
10-52
0-23
23-40
40-60
0-60
0-12
12-60
0-29
29-60

0-21

0-5
5-16
16-60
0-49
49-77
0-5
0-72

o-16
5-60
0-60
0-6
6-60
0-8
8-60

Onna
11-38
38-60
0-22
22-60
0-6
6-20
20-30
0-20
20-50
0-66

132

224.

10

128
49

28
437
+28
17
+28
+43,
“37

432
+28
37
+24

228
128

+32
+28
+32
+28
+28

49

Rowe


Appendix A—Continued

sot
SERIES

DEER CREEK

DEERTRAIL

DEGREY
DEVARES

DELL
DELECO
DELMONT
DELNORTE
DELPHILE
DEMAR
DEMERS

DEMKY
DEMPSEY

DEMPSTER

DENMARK
DENVER

DEPEW
DERRICK
DESART

DESERET

DES MOINES

DESPAIN

DETRA
DEV

DEVOE
DEWVILLE
DIAMONDVTLLE.
DICKEY
DILLINGER
DILTS
DIMercK

DIM

DIMYAW
DINNEN

DIOXICE

DIPMAN

DISTERHEFF

DIVIDE
DIX
DIXIE
DOAK

DOBENT
DOBROW

DOBY
Doct

DOGER
DOLLARD

DOLORES

DOMINGUEZ

DOMINIC

DEPTH
INCHES

0-14
14-34
34-60
0-5
5-23
23-60

o-10
10-60

25-48

18-36
36-48

10-30
30-60

9-30
0-6
6-25
o-12
12-26
24-60
0-9
9-60
0-5
5-11
11-60

43

sore DEPTH
SERIES Inches
DOWINSON ona
32-60
OWA AWA 0-6
6-39
39-60
DONALD 0-5
5-15
415-60
Doxey oz
DONWARDO 0-60
DONNER L 06
CB-L,GRL 0-6
5-34
poouey 0-6
6-24
24-60
DORAN 0-20
20-60
DORAZLON ons
DORNA
DOUBLETOP 0-8
8-60
poucity 0-7
7-30
30-86
Doveat 0-60
DOWDEN 0-5
560
bovce 0-20
20-60
DRAKE 0-60
DRAPER 0-21
21-60
DREXEL 0-60
DRUM 0-60
DRY CREEK 0-8
9-26
26-48
DucHESNE 0-9
3-02
DuDA
DUDLEY -
DUFFSON 0-8
8-20
20-30
purr 0-8
8-20
20-38
pucerws 0-60
DUMAS 0-7
7780
DUNCAN 0-5
Saas
38-40
40-60
uncou 0-8
ana
Dunpay
DUNTON 0-27
27-98
DUNUL 0-8
DUPREE S80
DURANGO 0-8
9-60
DURFEE 0-16
16-60
uroc 0-60
DURRSTEIN
DURST o-10
30-25
DuTsoN 0-8
8-36
36-60
vurTox 0-6
5-35
DwvER 0-6
6-60
OYE one
pany
DYRENG 0-60
EACHUSTON 0-8
8-60
EAGER = GRL 0-30
RCL 0-30
30-50
EaKaW
EARP 0-2
2225
25-60
EASTCAN 0-28
28-60
EASTONVILLE 0-40
10-98

A6

SOIL
SERIES

EBA
ESBS
EBON

ECCLES
ECHARD
ECHEKOOR

ECKLEY

ECKMAN
ECTOR
EDGAR
EOGELEY
EDGEWATER

EDLOE

EFFINGTON

EGAN

EAS
EGELAND

EICKS

EKAK

EKALAKA

ELBETH

ELDER HOLLOW

ELEPHANT
ELFRIDA _L,SIL

cL,SICL
ELK HOLLOW

ELK MOUNTAIN

ELKNER

ELKOL

ELLEDGE © CB-SL, SL

CBL,L

ELLETT
ELLICOTT
ELLOAM
ELPAM

EL RANCHO
ELS
ELSMERE
ELTSAC

ELWOOD

ELZINGA

EMBARGO

EMBDEN
EMBLEM

EMBLEM CLAYLOAM

EMBRY
EMBUDO

DEPTH
INCHES

0-2
2-50
0-60
0-2
0-38
38-60

19-60

o-48
ya-60
0-3
3-45
18-25
25-08

0-6
6-26
o-1t
11-26
26-38
0-22
22-48
48-62
o-12
12-34
0-60
0-3
3-20
20-31
31-60
0-3
3-20
20-31
31-60
0-60
0-20
20-60

3-2


Appendix A—Continued

att DEPTH
SERIES INCHES
reRsAYO on1u
PESCAR 0-22
130 9-32
POTEETNEET
PerRIE 0-60
aorTow 0-9
9-13
13-29
23-60
raAGE L 0-13
CB-L 0-13
13-60
uARO 0-8
8-29
29-60
PAIFERSON 0-8
8-30
PyILDER 0-12
12-18
PAILLIPS. 0-7
TAS
15-78
PATLLTPSBURG 0-8
9-20
20-60
PICAYUNE 0-53
PICKRELL, 0-19
rictou on
4-14
14-60
PIERTAN 0-6
6-60
PIERRE on
4-33
PIMA 0-8
0-26
26-60
PMA 0-9
Sandy clay loam 19-40
subsoil 40-60
PIMER CL,SICL 0-15
sic 0-15
15-60
PINAL 0-12
12-60
PINAL 0-30
Yoderately deep variant34—¥5
PINALENO 0-34
31-60
PINANT 0-22
22-60
PINATA 0-10
10-45
PINAVETES 0-60
PINEDALE 0-5
5-23
23-60
Prieur 0-3
3-60
PINequest 0-2
2-60
0-60
0-43
13-30
0-10
10-16
16-40
Prion 0-16
PLITLAR 0-7
7-80
PRITURA 0-65
PISHRUN 0-10
10-48
Pure 0-9
Ptack 0-8
PALWIEW 0-6
6-28
28-60
PLATHER 0-10
10-18
18-25
PLATORO
PLAYWOOR
PLEASANT
MEASANT GROVE

SOIL
SERIES

PLEASANT VALE

PLEASANT VIEW

PLOME

POGAL
POGANEAB
POJOAQUE
POINSETT
POKEMAN
POKER
POLELINE

LEO

POLEY

POLICH
POLSON

POLVADERA
POMAT

PONCHA

PONTL

POPPLETON
PORTALES

POSANT
POST
POTTER
POTTS
POUDRE
POVERTY

POWDERHORN

PREATORSON

PRESTON
PREWITT

PRIDHAM

PRIETA
PRING
PRINGLE
PRITCHETT
PROGRESSO
PROMISE

PROMO
PROMONTORY

PROSPER
PROVO
PROVO BAY
PROW
PTARMIGAN

PUERCO

oR.
L

GR-S
Ls

sc.
GR-SL

DEPTH
INCHES

0-17
0-17
17-60
9-25
25-38
34-67
0-16
16-35
35-60
L 0-6
0-6
6-20
O-4
4-60
0-8
8-60
0-60

0-3
3-10
10-30
0-10
10-30
O-uis
0-7
7-38
38-60
0-6
0-8
6-24
24-60

14-60

25-54

o-t4

10-26
24-30

7

+28
232
220

224
+28

+10
224
37
+20

37

SOIL
SERIES

PUGSLEY
PULLMAN
PULTNEY
PURGATORY
PURNER
PYLON
PYOTE

QUAKER
QUAMON

QUANDER
quay
quazo
QUEALMAN
OUEALY

QueRe

quietus

QUIGLEY
qursey
QUINNEY

QUIVERA

RABER
RACHERT

RADERSBURG

RADNOR
RAFAEL
RAGO

RATRDENT

RAKE

RALLOD

RALPH
RAMBLER

RANCE
PANDMAN
RANSLO

RAPELJE

RAPHO
RAPLEE
RARICK
RASBAND
RATAKE
RATON
RATTLER
RAUVILLE

RAUZI

RAVALLI

RAVOLA
RAWAH

RAYADO
RAYNESFORD

GRV-L

GR-L

DEPTH
INCHES

10-15

14-35
0-3
AL
11-27

50-60

0-8
8-21

10-15

0-7
7-55
0-27
27-60
0-8
8-24
24-60
0-8
4-15
15-60
0-60
0-7
7-30

0-16
16-28
28-66

232
43

237
+28

+32
143
“17

228
-32
+28
232
49
+15
237
+32
37
+20

49
+20

+32
+15
+17
+15

+20
37
+28
-28
243
+32
+28
+26
243
+32
37
“49
28
+28

28
+32
+24


Table 3. ‘**C’’ Factors for Woodland

V/ 2/ 3/
Forest
Tree Canopy Litter ic a
% of Area % of Area Undergrowth Factor
100-75 100-90 Managed 4/ 001
Unmanaged 4/ 003-.011
70-40 85-75 Managed .022-.004
Unmanaged O1-.04
35-20 70-40 Managed 003-.009
Unmanaged 5/

1) When tree canopy is less than 20%, the area will be considered as grassland for estimating soil loss. See Table 4
2) Forest litter is assumed to be at least two inches deep over the percent ground surface area covered

3) Undergrowth is defined as shrubs, weeds, grasses, vines, etc., on the surface area not protected by forest litter. Usually
found within canopy openings.

4) Managed—grazing and fires are controlled.
Unmanaged—stands that are overgrazed or subjected to fires from natural causes.

5) For unmanaged woodland with litter cover of less than 75%, C values should be derived by taking 0.7 of the appropriate
values in Table 4. The factor of 0.7 adjusts for the much higher soil organic matter on permanent woodland.

Figure 5: Methodologies for restoring vegetative cover on severely disturbed land are presently being developed and evaluated
The Interior Western U.S. climate is often the limiting factor.


Further, the factors listed in tables 4 and 5, when plugged into the equation
will result in conservative estimates. Initial erosion and sedimation research
on mined lands has indicated much higher rates of soil loss than those occurring
on "natural" or nondisturbed sites. (Lusby and Toy, 1976; Gee et al, 1976). Thus,
I recommend that all factors be weighted towards what would be considered liberal

estimates. Based on the current accuracy of the equation for this situation it
is better to overdesign than underdesign.

Re: Section 3.5, table 6, page 19 (Draft).

Enclosed as Table 2 are values I have encountered and adjusted to utilize
for a "P" factor on surface mined lands. Note the terracing factor in column 4
Although the terracing factor in the table has limited usefulness in actual
design, the following equation (1) can be utilized to break exceedingly long
slope lengths down into acceptable lengths by terraces, level benches etc.:

Land Slope (%) Number of Equally Spaced Intervals
215 n= (1/uy 18? q)
Where:

n = number of approximately equal-length intervals into which the field
slope is divided.

5
u

permissable soil loss ratio (permissable soil loss colaclye) /exiser).

Terracing may become an important tool for reclamation of exceedingly long
and relatively steep slopes.

I have adjusted the contour furrowing factors (column 3 of enclosed table)
for 19-24 and > 25 percent slope upward to enable more liberal estimates for the
steeper slope condition.

Is "contour stripcropping" an applicable erosion control treatment in surface
mine reclamation? To my knowledge I do not know of it being a viable treatment.
If you should question its useability then I would suggest you leave it out so as
to not confuse the user with extraneous information.


APPENDIX C
COMMENTS MADE BY
TRANSCRIPT REVIEWERS

OF WYOMING ED HERSCHLER
GOVERNOR

HESTATE

Department of Enecronmentad Quatity

LAND QUALITY DIVISION

STATE OFFICE BUILDING TELEPHONE 307-777-7756 CHEYENNE, WYOMING 82002

June 10, 1977

Mr. Arnold King

USDA, Soil Conservation Service
P.0. Box 17107

Denver, CO 80217

Dear Mr. King:

I appreciate the opportunity to review the draft copy of your anticipated
publication. I shall be anxious to see this material published so that it shall
be available for industry use.

I made numerous comments on the manuscript as I read through it. It is
probably to late in the review process for many of my comments or recommendations
to be given much consideration, however, I felt they should be made. I feel that
use of this document, as it exists, may allow for conservative estimates and possible
undesign of erosion treatments on surface mined lands. Many of my commments are
directed toward developing more liberal estimates so that the trend will be to
overdesign. I feel this is especially important when the accuracy of the equation
results on surface mined lands has not been proven.

Keep up the fine work.

Sincerely,

ey Lowe

Gary Beach
Soil Scientist

GB/fs
Enclosure

¢.c.: Dan Kimball
U.S.E.P.A., Region VIII
Office of Energy Activities
1860 Lincoln St.
Denver, CO 80295


Comments: "Preliminary Guidance for Estimating Erosion on Areas
Disturbed by Surface Mining Activities in the Interior Western
United States"

1) Numerous references are made in the text to research apparently in
progress or in the planning stages. Inasmuch as a summary work of this
type is only current as of a given manuscript date, it would be advan-
tageous to the reader if the studies referred to are specifically described
such that future readers will have an idea of when and where they were
completed. If you and the SCS are involved in any of this research, it
should be so stated.

A specific need is for the quantification of the K factor for
surface mine reclamation areas. To a lesser extent, other factors of
the USLE are also unquantified insofar as the mining process is concerned.
As noted by researchers in North Dakota, "The applicability of the
equation for mine spoil areas appears sound, but the coefficients K, C
and S are not known with confidence at mine sites, since virtually no
work has been done as yet to evaluate these factors on drastically
disturbed lands." (Gee, et al., 1976). Research is in progress by
Forest Service personnel involved with the SEAM Project in Bozeman,
Montana, to derive the limits of K for surface mining situations.

I suspect that quantification of the K factor in the West will
prove to be difficult, especially for topsoil salvaged from surface
mining operations. Soil pH, salts, sodium concentrations, etc. are all
substantially different in western soils than in the soils indigenous to
the Midwest where the USLE was derived.

The accuracy of the R factor is subject to more than, as you state,
",..upon how close the actual precipitation events match the yearly
averages."" The concept you mention is itself dependent upon both the
length of record at the weather stations considered and the density of
these stations over the area being mapped. Distribution of weather
stations and records in the West is relatively sparse; therefore, the
accuracy of R factor determinations is suspect when mapped at a small
scale. Regional generalizations based on sparsely distributed data
points tend to ignore significant local variaticns, such as orographic
influences.

I see no easy way around the problem of inaccurate or misleading R
factors, for solutions are always only as good as the data used.
Nonetheless, it should be made very clear to the reader that R factors
in the West are subject to regional error.

2) In the example problem on predicting soil loss, the assumption that
K "may remain relatively constant if the surface soil is redistributed
in the approximate vicinity where it was removed," is without basis in
light of Montana experience. Until more definitive methods of defining
post-mining K values are developed, and for the purposes of simplifi-
cation if not accuracy, one might assume that pre-mining and post-mining
K values are equal. However, it does not follow that topsoil will be
redistributed over the recontoured spoils in the same general vicinities


Appendix A—Continued

SOIL
SERIES

WAUKON
WAYBE
WAYDEN
WEBER
weED

WEISER
WELD

WELLSVILLE

WELTON

WEMINUCHE.

WEMPLE

WENDOVER

WENDTE
WENTWORTH.
WERLOW
WERNER
WESSELL

WESTCREEK
WESTOVER

WESTPLAIN

WETWORE
WETTERHORN

WEWELA
WHEATRIDGE
WHEATVILLE,
WHITEFISH

WHITE HOUSE

WHITELAKE

‘WHITEWOOD
WHITLOCK

WHITORE
WIBAUX

WIDTSOE

NIGTON

WILCOXSON

WILDCAT

WILEY

WILLARD
WILLHAND

WILLIAMS

WILLOUGHBY

WILLOW CREEK

DEPTH
INCHES K

0-9 2
9-60 +32
0-5 +32
5-18 37
0-3 43
3-15 43
0-9 +24
9-32 +28
32-60 10
0-5 +32
5-19 237
19-4028
0-7(1,CL).20
0-7(GR-L).17
7-20 “15
20-60 .10
0-6 +10
6-60 +15
0-20 15
20-36 = .10
36-6010
0-12 232
12-4020
uous 15
ons +24
4-10 +24
10-1817

-28

+32
0-60 +32
0-17 +28
0-8 +28
8-33 224
33-4910
0-24 +15
2-48.32
4a-60 0.15

+32
0-17 +32
17-60 .10
0-12 +10
0-20 224
20-36 © .10

+20
0-10 ra
10-3037
30-60-10
0-60 +28
0-8 24
8-40 +28
0-3 43
0-3 37
3-26 +24
26-60 .37

22h

+28
0-29 +20
29-60 10
0-7 +28
7-50 237
one +28
ya12 +24
0-3 +10
3-8 +20
8-15 224
15-42 .20
0-10 10
10-60-10
0-7 +28
74H +24
0-2 49.
0-2 w1S
2-7 +55
7-32 24
on 37
u-16 37
16-60-49
0-60 43.
o-8 +28
4-7 +32
7-20 +28
20-60-32
0-24 +28
2u-60 0.37
0-6 +28
6-30 +32
30-40 «10
0-9 +32
9-36 37
36-60-49

T

5-4

su

SOIL
SERIES

WILLOWMAN

WILLWOOD
WILTON

WINDHAM

WINDMILL

WINEG SL,GR-SL
L

WINETTI

WINTFRED
WINK

WINKEL
WINKLEMAN

WINKLER

WINN

WINWEMUCCA

WINNETT
WINONA
WINTERSBURG

WISCOW
WISHARD

WITCH
Witt
WITTEN
WOLF

WOLFORD

WOLF POINT
WOODHALL
WoODHURST
WOODLY
WOODROCK
WOODROW
WOODS CROSS
WOODSIDE
WOOLY

WOONSOCKET
WOOSLEY

WORF

WORK

WORLAND

WORMSER
WOROCK

WORTMAN
WORTHING
WRENMAN

WYARD

DEPTH
INCHES K
0-5 +28
5-13 +28
13-6015
0-5 210
5-60 +10
0-27 +28
27-60 37
0-6 +24
6-12 +28
12-60 .20
0-23 32
23-60 40
0-2 17
0-2 249
2-14 37
18-6020
0-17 +10
17-2428
2-82.20
0-36 237
0-24 +20
0-24(FSL).20
2u-60.20
0-16 +18
0-7 +32
7-60 37
0-9 +20
9-22 +24
22-80 .32
0-13 232
13-60 .43
o-n1 126
11-18 24
18-28 0.17
28-42 0.28
0-6 ary
6-30 255
0-15, 243,
0-42 37
0-12 +24
12-6049
0-9 :37
0-12 -28
12-20 .32
20-58 = .28
0-22 +10
0-47 103
47-60 .32
+28
ou +32
4-14 37
14-60 .32
on +20
4-24 +28
21-6017
0-60 +32
0-24 +10
0-12 +28
12-26 .32
- +20
0-13 a7
13-26 2
26-30 .20
0-60 03
0-37 232
37-7232
0-18 +20
18-27 10
0-9 47
9-46 -20
220
0-12 +28
12-3543
0-5 237
5-9 37
o-t4 243
ou +32
4-22 37
22-38 © .32
38-60 © .28
o-4 +20
4-30 24
0-34 +43
0-10 -32
10-26 .28
26-44 32
4-68.20
232
o-10 -32
10-32 137
0-32 -28
32-60 37

SOIL
SERIES

WYARNO

WYNDMERE
WYRENE

XAVIER

YAKI
YAMAC

YANA

YANKEE

YARDLEY

YAWDIM
YEATES HOLLOW

YECROSS
YEFULL
YEGEN
YELJACK
YENCE

YENRAB
YEOMAN

YESUM
YETULL

YousAY

YOUNGSTON

YOURAME.

YOUVIMPA

YTURBIDE
YUBA
ZAHTLL
ZAHL
ZANE
ZEESIX
ELL
ENIFF

‘ZEONA
DIEGLER

SIGWEID

‘ZILLMAN

ZITA

ZUKAN
ZUNT

DEPTH
-INCHES

o-4
4-60
0-60
0-21
21-60
0-s
5-62
0-19

5-60
0-50
0-9
9-27
27-60
0-10
10-60
0-15
o-11
11-46

0-60

34-60

0-60
0-16
16-34
0-65
0-18
15-66
o-t
1-14
0-60
0-10
10-52
52-77
O-m
4-15
15-24

8-60
0-60
0-60
90-5
5-60
0-13
13-60
0-13
13-60
o-11
11-60

6-14
14-60
0-60
0-8
6-18
18-2"
24-20

6-60
0-8
8-60
0-7
7-60
0-16
0-16
16-36
36-45

+55


EXHIBIT 3
Erosion Factor Map
Coal Field Inc.
Post-Mining Conditions

AREA 1- PASTURELAND

Phase |

Phase 2

Phase 3

Scale: 2"= | mile

Phase 8

Phase 9

eeee Erosion Area Boundaries

— Land Use Boundary

——— Mine Phase Boundaries
Gallegos


Appendix A—Continued

solb
SERIES
LAKEWEN

TAKOA
LAKOHA

LALANDE
AALLIE

LAMANGA
TAMARSH
LAMBERT

LAMBETH
LANBMAN

Ato
LANONDT

LAMOURE,
LAMPHIER

LAMPSHIRE,

SANEY

LANGHET
SANKIN

LANTIN
LANTRY
LAP

LA PALMA
LAPLATTA

LAPORTE
LAPRATRIE
ARAND

LARGO.
EARTH

LARIMER

LARKSON
LARRY
LARSON
LARVIE,

Las

LAS ANIMAS,
LASAUSES
UsIL

LAS LUCAS
LASSEL,

LATENE,

LaTon

LAUREL
LAYATE
LAVEEN

LAVERKIN
LAVINA

LAWTHER
LAZEAR

LEADVILLE.

arg

RoS LPL,
ray baht

CBV-SL,GRV-SL,GR -SL,CB~
LANE

sl
L,VFSL,SIL

FSL

DEPT!
INCHES

0-27
27-60

0-50
0-60
0-6
6-19
19-60
0-5
5-24
0-60
0-66
0-3
3-14
14-18

0-28
28-73
0-60
0-16
16-60
0-8
0-8
0-8 st

ou
4-60

0-6
6-60
0-10
10-60
0-9
9-48
O-4S

8-25
26-60
o-11
o-11
11-37
37-50
0-8
0-60
o-43
0-13
0-13
13-60
0-60
0-6
6-19
0-60
0-66
4-14
0-10
10-26

8-40
40-60

4-60

+28
+28
32
+28
+15
+28
+32
43
+32
+28
37
+28
224
+28
243,
+32
+28
+20
+55
+37
+20
+28
+32
+32
+28
=24
224
+28
ug,
+24
+10
ra
+32
+10
+10
“15
+28

132
=28
+32
BU
+15
“a7
+24
243.
+83,
i39
+32
143
10
249
28
43,
215
+2
+28
Bt
48
37
+49
+37
43
+37
+32
+20
220

+20
128

+32
+28
+10
+10
ety
+10

SOIL
SERIES

LEAPS
LEATHAM

LEAVITT.

LEAVITTVILLE

LEBO

LEBSACK

LEDGEFORK

LEDRU
LEEDS

LEETON

LEFOR
LEHMANS

LEHR
LELAND

LEMERT
LEN

LENNEP

LEOTA
LEPLEY
LESHARA
LETCHER
LEWISTON

LIBBINGS
LIBBY

LIBEG
LIck
LICK CREEK

LIHEN
LIKES
LIMBER

LIMON

LINNET
LINOYER
LINTON
LISADE
LISAM
LISMAS
LISMORE
LITIMBER
LITLE

LITTLEBEAR
LITTLE HORN

LITTLE POLE
LITTSAN

LIVOWA

LIZZANT
LOBERG

LOBERT
LOBURN
LOcKERBY
LODAR
LOFTON

DEPTH
INCHES

0-60
0-10
19-54
0-7
7-38
38-60
O-11
11-28
28-60
0-28
28-50
0-8
6-38
34-60
0-13
13-31
31-60
nu
uai7
0-15
15-60
0-9
9-36
36-72
O-15,
O-1

core 1-16

GR-CL

1-18
0-15
15-60
0-38
38-58
0-60
o-s
5-11
11-30
30-40
0-8
8-32
32-73

0-66
0-60
0-10
10-32
32-50
0-34
0-7
7-60

4-56
0-18
18-30
0-6
6-16
0-60
0-60

3-15
15-32
0-8
4-60
0-80
0-60
0-60
0-60
0-15
0-10

0-15
15-60
0-60
0-12
12-27
27-72

0-38
0-20
0-9
9-80
0-13
13-26

A112"

+24

SOIL
SERIES

LOGGERT
LOHLER
LOHMILLER
LOHNES
LOHSMAN
LOLO

LOLOW

LOMA
LOMITAS
LONE PINE

LONE ROCK
LONETREE

LONGMONT.

LONTI GR-L,CB-L
GR-SL,SL

LOS ALAMOS

LOS TANOS

LOSEE GR-L
GX-SL

LOSTWELLS
LOTHAIR

LOUP
LOUVIERS

LOVELAND
LOWRY

LOZIER
LUBRECHT

Lucky

LUCKY STAR

LUDDEN

LUHON

LULUDE

LUNA cL
cB-SIL

LUNCH

LUNDY

LUPINTO

LUTE
WwTH

LUTON
LUXOR
LUZENA

deep variant

LUZENA GR-L,CB-L
GR-CL
LYMANSOW
LYNNDYL.
LYNX FSL
L

DEPTH
TICHES

9-19
19-60
9-60

0-60
One
4-26
0-18
8-60
0-8
8-17
17-28
28-40
0-5
5-28
28-60
0-13
0-6
6-40

34-60

O-4

52-74

0-5
0-10
10-34
0-s
a5
5-20

5-30
0-4
442
42-72
0-2
0-2
0-60

243

+10

49
237


LIST OF EXHIBITS

Exhibit | Soil Map. 0 2. ek ee ee ee ee ee ee ee AT
Exhibit 2. Erosion Factor Map Pre-Mining...... 2. 0. 22.0.6 eee ee eee rrr 3
Exhibit 3 Erosion Factor Map Post-Mining 19
Exhibit 4 Erosion Calculations Pre-Mining ..........0..6.0 62 cee ce be eee ne ee ne ne eee eee 20
Exhibit 5 Erosion Calculations Post-Mining . 21
Exhibit 6 Factor Influence Calculations . 22
Exhibit 7 Erosion Calculations Reclamation in Progress... .. 26. 22022 ee ce ce eee ee ne eee 23
APPENDICES
Appendix A Factors ‘‘K"’ and ‘‘T’’. bees bb eee be ee beens be ee ee rec |
Appendix BSCS Offices in Interior Western Coal Resources Areas... 2 6. 1. 0 ee ne nee eee B-1
Appendix C Comments ..............00.0 cece ee cee te tees be ne nee Cl


Appendix A—Continued

sorb
SERIES

BUSKA
‘BURGI GR-L
L

BURNAC
BURNETT

BURNT LAKE

BUSE

BUSHVALLEY CB~SL,CB-FSL
cB-L

BUTCHE

BUTTERFIELD

BYNUM

BYRNIE

CABALLO

ABBA
CABBART

CABEZON

casin

CACHE

CACTQUE

CADOMA,

CALABASAS

cALICOTT

ALITA

CALIZA

CALKINS

CALLINGS

CAMBERN SL ,CB-SL,GR-SL
SIL.

CEL, ORL
CAMPO

CAMPSPASS
CAMPUS
CANBURN
CANELO
CANEZ
CANNINGER
CANUTIO
‘CANYON
CAPILLO

‘CAPULIN
CARALANPL
CARALAMPI

Brown Variant

CARLITO

CARBOL

CARDON

CARELESS

CARLSTROM

DEPTH
INCHES

0-5 SL
5-10

0-30

40-54

on
4-8

30-60

0-60

0-6
6-40
0-10
10-41
44-66
0-2
2-23
23-60
O-tt
11-39
39-60
On
4-8
8-60
0-7
7-14
o-tt
11-34
34-62
0-8
8-26
26-50
50-66
0-7
7-26

SOIL
SERIES

CARGILL

CARNERO

CARRACAS

CASA GRANDE

CASAIO

CASEBIER
CASHEL
CASHION
CASITO

CAPUTA
CASTELLETA

CASTELLO
CASTING
CASTLE
casTo
CASTNER
CATHAY
CATHEDRAL
CAUSEY
AVAL
CAVE
CAVELT

CAVOUR
CEBOLIA

CEBONE
CEDAR MOUNTAIN
CELESTE

CELLAR

CENTER CREEK
CENTERFIELD

CERRTLLOS

CERRO

CESTIK

CHAFFEE

CHAMA

CHAMBERINO

CHANTA

CHAPERTON

CHAPIN

CHAPPELL

CHARCOL

CHARLOS

CHASEVILLE
CHEADLE
CHECKETT
CHEDSEY

CHEESEMAN

DEPTH
TnChES

A-4

0-6
6-17
17-30

21-60

19-40
40-63

5-30
30-60

11-26
28-60

26-60

20-36

o-2t
21-54
0-6
6-17
17-30
30-62
o-14
14-60
0-8
o-t9
0-13
13-36
0-15
15-26
26-33

K

403

SOIL,
SERIES

CHEREETE
CHERTONT
CHERRY

CHEVELON

CHEYENNE
CHILSON CB-CL, ST-CL

CHILTON
CHIMAYO
‘CHINOOK
CHIPETA
CHIFMAN
CHIRICAHUA,

CHRIS

CHRISTIANBURG
CHUBBS

CHUGTER
CHURCH
CHUPADERA
CIBEQUE
CIMARRON
CIPRIANO
CIRCLEVILLE
CLAIRE
CLAPPER
CLARK FORK

CLAYSPRINGS

CLAYBURN

CLEGG

CLERGEN

CLEVERLY
CLIFTERSON

‘CLONTARF
cLoup RT

(CLOVERDALE,

CLOVER SPRINGS

cLovis

CLOUD PEAK
CLOWERS
cCLUFF

coAD

‘COALDRAW
COALMONT

COBEN

COCHETOPA

16-30
30-60
0-60
0-3
3-20
20-30
90-60
0-11
11-60
0-6
6-24
0-42
42-60
0-6
6-60
0-15
15-20
20-60

10-32
32-60
0-12
12-60
0-60
on
4-60
0-25
ont
o-14
14-60

36-84

+32


Active Reclamation

As previously stated, the USLE can be utilized to pre-
dict the average soil loss from a given area over a time period
Jess than one year. The major influence in predicting soil loss
over short time periods, as compared to predicting the annual
average soil loss, is the adjustment of the ‘‘R’’ factor and the
short-term changes in land conditions. As illustrated in Fig-
ure 2, the ‘‘R’’ factor can be modified for periods less than
12 months. Step-by-step procedures applicable to soil loss
evaluation during this period are presented below.

Step 1:

Step 2:

Identify the area of study and select the time periods
such that the USLE factors can be assumed constant
for that period. In this example, the area shall be the
area identified in Exhibit 2 as the Phase I post-
mining area. This area, 480 acres, is the first area
disturbed and subsequently reclaimed as the mining
activity progresses. The time periods (Exhibit 7)
are (1) from May 15 (5/15) to October 1 (10/1)
during which it is assumed that the area will remain
essentially bare, and (2) from 10/1 to 5/15 during
which mulching and seeding are assumed.
Prepare a chart, Exhibit 7, showing the area of study
and assign numeric values to the USLE factors. The
land condition for period | is assumed to be bare for
approximately five months, 5/15 to 10/1, while
protected by mulch for the remaining seven months,
10/1 to 5/15, period 2. The ‘‘K’’ and ‘‘P’’ factors
for both periods are assumed to remain the same as
in pre-mining. The length and slope factors, ‘‘L’’
and ‘‘S’’, are assumed to be restored after mining
has occurred and thus also remain the same. The
““C”? factor will change with respect to the stages of
cover and the ‘‘R’’ factor will change as determined
from the EI distribution curve, Figure 2, for the
appropriate time period.

The ‘‘C’’ factor values (Table 5) are 1.0 for bare
soil (5/15 to 10/1, period 1), and 0.06 for assumed
mulching and seeding at two tons of mulch per acre

(10/1 to 5/15, period 2). The adjusted ‘‘R’’ factor
values, Figure 2, are determined as follows. (Note
that the EI curve, Figure 2, is assumed to be the
appropriate curve for this mining site.)

1. Percent of annual EI at each date: 5/15 %
EI=45
10/1 %
EI=97

2. The difference, (97-45)=52, indicates 52% of
the annual ‘*R”’ factor occurs from 5/15 to 10/1.

3. The adjusted ‘‘R’’ factor is then:

“R’ (adjusted= .52(R)=.52(30)
=15.6

The EI curve is assumed to repeat each year, over
the short term, thus the adjusted *‘R’’ factor for the
period from 10/1 and 5/15 is the remaining percen-
tage, or 48%. The adjusted ‘‘R”’ factor from 10/1 to
5/15 is then:

R (adjusted) = .48R=.48(30)= 14.4

Step 3: Having assigned values to all factors, the average

soil loss can be predicted. Exhibit 7 shows that
during period | when the land is bare and 52% of the
erosion due to rainfall is anticipated, the predicted
soil loss is 1.44 tons/acre/period, indicating a total
loss of 691.2 tons from 5/15 to 10/1. During period
2, the predicted average loss is 0.08 tons/acre/
period, or 38.4 tons from the 480 acres over the
period 10/1 to 5/15. The total predicted soil loss
from 5/15 to 5/15 the following year, is thus 729.6
tons/year.

Exhibit 7 also shows the predicted soil loss during
the second year assuming that the seeding was suc-
cessful and that a 20 percent ground cover density
with no appreciable canopy is representative of the
conditions over the second year. During this
period, total predicted soil loss is 264.0 tons/year as
compared to 729.6 tons/year the first year.


EXHIBIT 6
EROSION CALCULATIONS

Project: Coal Field Inc.

Land Condition: ‘‘Factor Influence Chart’’ Date.
Est. Est.
Areas Land Universal Soil-Loss Equation Factors Soil Acres Soil Loss
of the use or Loss in from Area
Project Cond. R K L Ss Ls Cc P_T/Ac/Yr Area Tons/Yr
ITEM I Pre-Mining
2A Crop 30. 37, 6002.00.34 36 1.36 440 598.4
ITEM II Post-Mining
2A Crop 30.37, 160 2.0.23 36 50 -46 440 202.4
SUB-TOTAL
ITEM II ‘‘L”’ factor change
2A Crop 30.37, 1602.0 23.3610 92 440 404.8
ITEM IV ‘‘P”’ factor change
24 Crop 30.37 — 6002.0 34 36 —S0* 68 440 298.9
SUB-TOTAL
TOTALS
Remarks:

* Table 6 indicated contouring is not an acceptable alternative for this area due to the excessive slope length (see 1/). However,
if the area is terrace to reduce slope length, contouring will be applicable.

22


EXHIBIT 2
Erosion Factor Map
Coal Field Inc.
Present Conditions

Scale:2"= I mile

1220 Ac

(Pre- Mining)
AREA 1- PASTURELAND
A K-37
L-400
$-1.5
C-.10 1290 Ac
weteteees, ie
AREA 2- woeee 3
CROPLAND | ; Cy 94
_ K-.37 $  T-150
(600 L-300 2 §-3.0
re, S20 8-5.0 3 C-.10
a tee, C-.36 c-042 ry
K-.28°%,., 440Ac % SS0Ac
L400 “fee, 4
-36 200 c** .
* i 37 Tete teeeeed

K- .28
L-200
$- 2.0
c-.20

380A

seeeee Erosion Area Boundaries
Land Use Boundary

Goteass


Appendix A—Continued

sor
SERIES
COE
COEROCK

COGSHELL L

COHAGEN
COREL

covey

COLDCREEK
COLLARD

COLLBRAN

COLLEGIATE
COLLETT
COLLINSTON

cOLMOR
‘COLOMBO
COLONA
COLUMBINE

coLvIN
COMER

como

coODORE
coHoRO

CONATA
CONCHAS

coNcHO

CONDTE

CONGER
CONT

CONNERTON

CONTIDE

CONTINE

CONTINENTAL GR-SL
GR-SCL
COOLIDGE

COPPERTON
CORDES.

CORLETTE
CORMONT:

CORNISH
CORNVILLE SL, FSL.
L

CORPENING
CORTA,
COSTILLA

COTHA

DEPTH
INCHES

0-6
6-60
On
4-15
0-12
0-12
0-12
12-26
26-60
0-17
0-22
22-60
0-8
8-60
0.45
0-20
20-60
0-13
13-26
0-9
9-36
36-60
0-12
12-34
34-48
0-15
15-35
35-60
o-u
4-64
0-12
12-60
o-4
4-60
0-6
6-60
0-60
0-6
6-60
0-18
18-32
o-15
0-36
36-60

0-8
5-30
0-8
5-60
0-25
25-42
42-66
0-17
0-7
7-19
0-8
8-60
0-2
2-28
28-52
52-60
0-12
15-28
25-66
0-10
0-10
10-31
31-72
0-24
24-60
0-60
0-34
34-60

8-60
0-6
6-60
0-10
0-3

3-30
30-60
0-6
6-15
ou
4-60
0-6
6-24
24-60
0-30

K

-28

SOIL
SERIES

COTOPAXT
COTTIER

COTTONWOOD
COURTHOUSE.

‘COURTLAND

COWAN

COWDREY
COWERS
cowooD
CRADDOCK

cRAGO

CRAGOLA
CREEDMAN
CREIGHTON
CRESBARD
CRESPIN
CREST
CRESTLINE

RESTON
CREWS

cRIsTo

CRITCHELL

CROOKED CREEK
CROOKSTON

‘CROSS

cROT cL

SL, PSL
L, StL

CROW
CROW CRERK

CROW FLATS
CROWFOOT

CROWHEART
CROWSHAW

CROYDEN
CRUCES
CRUCKTON

CRYSTOLA

‘CUDAHY
CUEVA

‘CUEVOLAND

‘CUMBRES

cunpicK
CUNDIYO

14-50
50-66
0-4

43-21
21-35

7-20
20-60
0-60
o-18
14-27
27-56

0-5

47-60

SOIL

SERIES
CURBERANT
CURDLI
CURECANTI
CURHOLLOW
CURTIS CREEK
CURTIS SIDING
CUSHMAN
CUSHOOL
CUTTER
CYPHER

DACONO

OAGFLAT
DAGLUM
DAGOR
DAHLQUIST

DAILEY
DALBY

DALCAN
DALHART

DALIAN
DALLAM

DANDREA

DANKO

DANVERS

DARGOL

DARLING

DARNEN

DARRET

DAST
DATELAND

DATEMAN

DATINO

DATWYLER

DAVIS

DAVISON

DAYBEL

DAZE

DEACON

DEAMA

DEAN

DEAVER

DEBONE

DECCA

DECKER

DECROSS

DEPTH
INCHES. K

0-20 17
20-36 «24
0-60 oy
0-7 +10
7-20 10
20-60 20
o-15 +15
0-8 +2
8-18 +32
0-60 210
0-28 +32
on 224
0-60 +32
o-4 +20
uo “17
0-9 226
9-20 +28
20-26 15
26-60 «10
0-30 +10
O-u5 32
0-60.37
0-7 15
7-14 20
14-2815
28-60 10
0-16 15
16-60 «15
0-60 +32
9-27 224
0-9 224
9-38 +32
38-72 «32
0-42 7
0-8(FSL) .24
O-8(LFS) .20
a-80 232
0-7 203
7-2 232
12-2900 .17
o-12 :37
o-4u 37
wu-60 28
0-6 +24
6-35, 228
0-5 -20
5-21 +10
21-60 «10
0-38 +28
34-6037
0-8 237
8-13 243
13-28 .32
0-30 +20
0-17 +20
17-3349
33-60-37
0-24 224
24-34 20
0-7 +24
7-50 +28
o-t4 +20
11-28 «10
28-3515
+24

- +28
0-16 +32
16-31 32
31-90 .10
0-2 143
2-20 +32
0-10 +24
10-26 «24
26-60 20
0-13 17
0-7 +32
7-60 +28
o-4 43
4-24 237
0-8 +32
8-26 37
26-60 .32
0-15 +32
15-60 .10
0-12 +32
12-35 .32
35-60 0.43
0-9 +28
9-30 37
30-60 43

a


Section 6.0
APPLICATION OF THE USLE

The information presented in previous sections of this
publication was developed to provide background informa-
tion on the USLE and provide pertinent data needed to apply
the equation.

This section is devoted to giving an illustrative example
of an erosion study for lands disturbed by surface mining. It
should be noted that the methodology and exhibits shown in
this section of the publication provide general guidance and
examples for illustrative purposes. The guidance is not
meant to imply a specific method or procedure for conduct-
ing an erosion study.

It must be noted that the sample soil loss calculations
presented in this publication are only examples. The pre- and
post-mining land uses specified herein present a hypothetical
situation and do not suggest that specific land productivity
nor reclaimed land use or configuration are attainable and
recommended. A site-specific, demonstration study will fol-
low the effort represented by this publication. This study will
attempt to assess the influences of physical manipulation on
soil loss and investigate the potential change in *‘K*’ values
for pre- and post-mining conditions.

6.1 DEVELOPING AN EROSION STUDY

An erosion evaluation project should be carried out with
specific objectives in mind. Soil loss or erosion information
can be of value for a number of purposes. [n many cases the
primary purpose may be the evaluation of various alternative
plans or components to plans. For example, it may be of
concer to determine quantitatively the effects diversions or
terraces may have on erosion. If the objective is to determine
off-site sediment yield, additional surveys will be necessary
to arrive at a sediment delivery ratio(s) representative of the
drainage area(s).

Erosion is an environmental impact that should be ad-
dressed in plans involving land disturbance resulting from
surface mining activities. It is possible, by using information
in this publication to predict soil loss for pre-mining condi-
tions and to predict what the soil loss will be at completion of
the reclamation plan, or at any stage during reclamation.
Again, it should be emphasized that the USLE utilizes long-
term average rainfall intensities, and deviation from average
intensity, amount, or distribution will affect the answers
arrived at by use of the USLE. In spite of this restriction, the
USLE is recognized by most conservationists as the best
method available to calculate soil loss from sheet and rill
erosion

Certain-site specific resource information will be neces-
sary for an erosion study, including soil survey information,
topographic information, vegetative analysis, and climatic
data. Other material may include aerial photography, forms
and procedure for recording erosion factors, and as much
information as possible concerning the planned mining ac-
tivities and reclamation work.

6.2. DETERMINING EROSION FACTORS

To predict the soil loss from a given land area, a value
must be assigned to each of the five factors in the USLE. The
correlation between the chosen factor values and actual site
conditions will determine the accuracy of the soul loss pre-
diction. Values for some of the factors may be taken directly
from the tables, figures, and Appendix A presented in this
report, while values for other factors will require a site survey
and measurement.

Determination of Erosion Factors

Rainfall Factor ‘*RTM: The ‘*R’’ factor value can be
taken directly from Figure 1 by selecting the value
assigned to the location of the project area.

Soil Erodibility Factor **K"': Determination of the ‘*K**
factor requires that the soil type be known. Soil
type information is acquired through a soil survey.
Exhibit | is an example of the mapping output from
such a survey. The various soil types and extent
within the use area boundary are identified by
three-letter codes and mapping units. Having iden-
tified the soil series, the ‘*K"" value for each can be
determined from Appendix A. Appendix A lists all
known soil series for the eight Interior Westem
states of Arizona, Colorado, Montana, New
Mexico, North Dakota, South Dakota, Utah, and
Wyoming.

The question of whether the ‘*K"’ value remains
the same for disturbed and reclaimed lands as for
pre-mining lands remains specifically un-
answered. Follow-up investigations to this publi-
cation hope to address this question, but until such
time and for simplification of this example, the
same pre- and post-mining *‘K’* values will be
used.

Length-Slope Factor ‘‘LS**: The user of this publication
should be thoroughly familiar with the section dis-
cussing factors **L"’, ‘*S'', and ‘*LS"’ In most
cases, field investigation and reference to the re-
clamation plan will be necessary to determine the
length and degree of slope. After determining the
“L" and **S’’, refer to Table | for the ‘‘LS"" factor
used in the USLE.

Crop Management Factor ‘*C’’: This factor relates to
vegetative soil protection. Refer to Tables 2, 3, 4,
or 5, depending on the land use, to determine the
appropriate erosion factor based on information
from field investigation or information contained
in the reclamation plan. Additional information on
cropland **C’" factors is available at local SCS
offices (Appendix B) if the planned cropping sys-
tem does not fit one list in Tables 2 through 5.


-3+

An additional point should be clarified, and that is your defini-
tion of gross erosion in the Glossary: "The total amount of water
erosion occurring on a site. Includes sheet and rill and gulley (?)
erosion." I have two observations. First, the use of the word gross
implies an all-inclusive context, whereas your definition includes only
water erosion, to the exclusion of wind and gravity, which may be equally
as important. Second, your use of the term gross erosion in the text in
Section 5.0 apparently is not intended to include gully erosion. (Sec-
tion 4.0: the USLE, "...does not account for gully erosion, which

cannot be predicted by any known formula.”) I suggest that the defini-
tion be reworded.

I want to emphasize that my intent is not to disparage the possible
value of a quantifiable method of comparing reclamation plans. I realize
full well that it is frequently too easy to criticize without making
suggestions for improvement. In this case, however, such suggestions
may not he possible because science simply has not advanced sufficiently.
Application of the USLE, however lacking and inappropriate in many
cases, may be all we have. Nonetheless, I want to impress upon the non-
technical reader that this application of the USLE should be used within
very strict and well-defined limits. Too frequently, individuals use
equations without an understanding of its inherent limitations. I wish
to state those limitations at the outset.

Reference: Gee, G.W., Gilley, J.E., and Bauer, Armand, 1976, "Use of
Soil Properties to Estimate Soil Loss by Water Erosion on Surface-
Mined Lands of Western North Dakota", North Dakota Farm Research,
vol. 34 (2), pp. 40-43.


0 VA 74 70 # very fine gronulor
FF 2-tine granulor
7 or coorse gronulor
to 30 60 ty, OF massive
7
%0M:0, .
\\ N 4 4 * SOIL STRUCTURE
20 \ 30 * 7
Xda 8 “4
N \ 3 whe
5° 0 i Z
WN N 7 3
o (Y WS Ns 7 S 7
z \ NN =
<z40 a
z NS ao ;
c > ira
350 z i 50 .20 Z
$ CAROLS § “ft
= 7 <N TNA 7 4
t CAT +P OK TA YA
a 60 i. ~ 40 10 7
a y XN tfy
b Pek NS XR YS 7 i L497
% 70 uN \ 0 H oy, Z
ra \vy 30 H Vy i,
v\Is t x 7 H 4
80 PERCENT sano ke © 40 i a6 66) PERMEABILITY
(0.10-2.0mm) Ns J2° 2° OA
NL) t g t x
. z j
90 NS so > 304: 0s
Dag FA 7 yy AY, © 6. very 1
I~ o 0/72 - very slow
100 $4 + n } } i A A 8 20 zZ 4 5- slow
PROCEDURE: With appropriate data, enter scale at left and proceed to points reoreseting & 7, 4 4 slow to moa.
the sofl's % sand (0.10-2.0 mm), T organic matter, structure, and permeability, {n that sequence, " fr 4
Interpotate between plotted curves. The dotted Tine ‘Ilustrates procedure for sot} having: 2 GA
sie ty and St, On sire Pe pemmnly fe eltlns Oo 8 10 U7
m4
fe)

Figure 3. Nomograph for Determining Soil Erodibility—Factor ‘‘K’”

Wischmeier, et al, 1971



Appendix A—Continued

SOIL
SERIES

ARNY

AROSA

ARP

ARROW

ARTESIA
ARVADA
ARVANA
ARVESON
ARUILLA

ASCALON

ASHBON

ASHCROFT

ASHLEY

ASHUELOT

Aso

ASPERSON

Ls
SL, FSL

FSL, Lb
sT-L

FSL
cL

ASSTNNTBOINE

ATASCOSA
ATENCIO

ATEPIC

ATHELWOLD

ATHERLY

ATHMAR

ATOKA

ATON

ATTEWAN

AUT

auzqui

AVALANCHE
AVALON

AVAMAN.
AVON

AVONDA

AVONDALE

AYLMER

AYON

AZAAR

AZELTINE

L
SCL

DEPTH
INCHES.

0-8
9-22
22-60
0-10
10-39
39-62
0-2
2-18
O68
6-22
22-32
0-3
3-25
on
4-60
0-8
8-24
0-34
34-60
0-16
16-60
0-7
0-7
7-18
18-25
25-60
o-w
4-13
0-6
6-26
26-60
0-3
0-9
9-18
15-72
0-8

20-60

10-20
20-30
30-60
0-17

0-8
6-60
part
11-36
36-60
0-6
6-19
19-30
0-10
10-29
23-72

7-18
18-26
28-60
0-12
12-26
0-12
12-60
0-60
Ont
onan
31-42

0-9
9-27
27-60
0-13
13-27
27-60
0-12
12-60
0-60
O-12
12-19
19-60
0-23
13-22
22-32
0-16
16-60

228

SOIL
SERIES

AZETELD
BABB
BACA

BACHUS

BADUS
BAGARD

BAGCOTT
BAGLEY

BAINVILLE

BAIRD HOLLOW CB-L.
L

BAKER PASS

BALDY

BALLER

BALMORHEA

BALON GR-SCL,GR-CL
GR-SL, SL

BALTIC
BAMFORTH
BANDERA

BANGSTON SL
is, FS
BANKARD

BANKS

BARCUS

BARELA

BARFUSS

BARISHMAN
BARKERVILLE
BARNES
aR

BARRETT
BARTON
BARVON
BASCOM
BASS
BASSEL

BATA

BATTERSON

BATTLE CREEK
BAYERTON

BEAD

BEADLE
BEAMTON

BEAR BASIN

A-2

39-60

0-3

23-60

19-27
27-40

0-36
0-19
19-31
0-44
10-38
34-42
0-18
16-36
96-72
0-18
18-26
26-40
0-7
7-15
15-60
0-7
7-28
25-60
o-4
4-45,
0-10
10-37
37-64

SOTL
SERIES

BEARDALL
BEARDEN
BEARDSLEY
BEARMOUTH
BEARPAW
BEARS4IN
BEAUVOIS

BEAVERELL
BEAVERTON
BECKS
BECKTON

BEEBE
BEEK
DEENON
BEGAY
BEHANIN
BELEN
BELFIELD

BELLAMY
BELMEAR

BELTON

BENCLARE

BENJAMIN
BENOIT

BENTEEN
BENZ
BEOTIA
BERCAIL

BERENT
BERINO

BERMESA
BERNAL
BERNARDINO

BERTAG STL

-L

BERTELSON
BERTHOUD
BERYL
BESSEMER

BETTS
BEW

BEZZANT
BICKMORE

BIDMAN

BIG BLUE

BIGETTY

DEPTH
INCHES

0-15
18-34
9-28
28-60
0-10
10-36
0-10
10-60
0-6
6-50
50-86
0-10
0-30
30-60
0-3
3-17
17-60
0-9
9-18
14-60
o-15
18-19
19-37
0-6
6-38
34-60
0-60
9-60
o-
7-18
0-50

27-40

0-60

4-17
17-29

20-60

15-60

24-60

20-34

22-60

0-6
6-22
22-60
0-60
0-16
16-28
24-37
cs
5-18
18-80

10-18
18-80
0-3
3-60
60-71


Soil Map: A map showing the distribution of soil types or other soil mapping units in relation to the prominent physical and
cultural features of the earth's surface. The following kinds of soil maps are recognized in the U.S.: detailed, detailed
reconnaissance, reconnaissance, generalized, and schematic.

Soil Organic Matter: The organic fraction of the soil that includes plant and animal residues at various stages of decomposition,
cells and tissues of soil population. Commonly determined as the amount of organic material contained in a soil sample
passed through a two-millimeter sieve.

Soil Profile: A vertical cross-section of the soil from the surface into the underlying unweathered material.

Soil Series: The soil series is a group of soil having horizons similar to differentiating characteristics and arrangement in the soil
profile, except for texture of the surface portion, or if genetic horizons are thin or absent, a group of soils that, within
defined depth limits, is uniform in all soil characteristics diagnostic for series.

Soil Survey: A general term for the systematic examination of soils in the field and in laboratories; their description and
classification; the mapping of kinds of soil, the interpretation of soils according to their adaptability for various crops,
grasses, and trees; their behavior under use or treatment for plant production of for other purposes; and their productivity
under different management systems.

Stripcropping: Growing crops in a systematic arrangement of strips or bands which serve as barriers to wind and water erosion.

Subble: The basal portion of the plants remaining after the top portion has been harvested; also, the portion of the plants,
principally grasses, remaining after grazing is completed.

Subsoil: The B horizons of soils with distinct profiles. In soils with weak profile development, the subsoil can be defined as the
soil below the plowed soil (or its equivalent of surface soil), in which roots normally grow. Although a common term, it
cannot be defined accurately. It has been carried over from early days when ‘‘soil’’ was conceived only as the plowed soil
and that under it as the ‘‘subsoil’’

Surface Mining: A process in which rock and topsoil strata overlying ore or fuel deposits are scrapped away by mechanical
shovels. Also known as strip mining.

Terrace: An embankment or combination of an embankment and channel constructed across a slope to control erosion by
diverting or storing surface runoff instead of permitting it to flow uninterrupted down the slope.

Tillage: The operation of implements through the soil to prepare seedbeds and root beds.

Topsoil: The original or present dark-colored upper soil that ranges from a mere fraction of an inch to two or three feet thick on
different kinds of soil.

25


Section 3.0
THE UNIVERSAL SOIL LOSS EQUATION

The Universal Soil Loss Equation (USLE) is an empiri-
cally developed formula historically used to estimate soil loss
on agricultural lands.

The soil loss equation is A = R K L S C P, where:

Ais the computed soil loss expressed in tons/acre/year.

R, the rainfall factor, is the number of erosion index

units in a normal year’s rain. The erosion index is a

measure of the erosive force of specific rainfall.

the soil erodibility factor, is the erosion rate per unit
of erosion index for a specific soil in cultivated

continuous fallow, on a nine percent slope, 72.6

feet long. The reasons for specifying these condi-

tions as unit values are presented in Section 3.2, the
detailed discussion of this factor.

L, 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 nine percent
slope.

C, the cover or 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.

P, the erosion control practice factor, is the ratio of soil
loss under specified soil management practices, to
that with straight rows, up and down the slope.

‘a

Numerical values for each of the six factors have been
determined from field experience and research data. These
values differ from one field or locality to another. The
approximate numerical values of the erosion factors can be
obtained from the tables and figures presented in this report.

Ongoing and future investigations will establish and
verify numerical values for the above factors with respect to
lands disturbed by surface mining in the Interior Western
U.S.

Section 6.0, ‘‘Application of the USLE,”” illustrates
how to select applicable values from the tables and charts,
and how to predict soil loss before, during and after reclama-
tion. Assistance in the application of the USLE can be
obtained at the SCS offices listed in Appendix B.

3.1 THE RAINFALL FACTOR *‘R”

The energy of moving water detaches soil and causes
erosion. The rainfall factor ‘‘R’’ is a measurement of the
kinetic energy of the expected rainstorms of a specific geo-
graphical area. Locational values of the rainfall factor ‘*R’”
can be taken directly from the map titled ‘‘Average Annual
Values of the Rainfall Factor ‘R’ ’’, Figure 1. The informa-
tion presented in this figure was developed using rainfall data
furnished by the National Weather Bureau and a conversion
chart from Soil Conservation Service Technical Note No. 32
(Brooks, et al. 1974).

The values of the factor *‘R’’ were computed from
rainfall data expressed in tenths of inches received from a
two-year frequency, six-hour duration rainstorm. The data
was converted to factor ‘‘R’’ by use of a modification curve
to better conform to specific climatic characteristics occur-
ring in various area(s). The iso-erodents, or ‘‘R’’ factors, in
the mountainous states west of the 104th meridian are not as
accurate as data developed in the eastern states because of the
highly localized rainfall patterns in the mountain regions
(Wischmeier, 1974). There simply are not enough weather
monitoring stations in the mountainous regions to record
adequate rainfall information. However, most of the westem
coal resources are located in areas where the iso-erodent
information is relatively accurate for the long term average.

Other parameters of factor ‘‘R’’ include rainfall prob-
abilities expressed in terms of percentage and soil loss from
individual storms. However, this information has been de-
veloped for only a few locations, most of which are in the
eastern states (Wischmeier, et al. 1965). Additional efforts
are needed in developing this climatic data for the Interior
Wester states. If and when this rainfall information be-
comes available, it can be used in the Universal Soil Loss
Equation.

It should be understood that ‘‘R’’ factors presented in
Figure 1 are based on long term average precipitation re-
cords. Therefore, the accuracy of soil loss predictions de-
pends upon how close the actual precipitation events match
the yearly averages.

The use of an erosion index distribution curve that
represents a given area permits factor ‘‘R’’ to be modified to
indicate the number of erosion units for any period of time
within a year. This concept makes it possible to estimate
erosion for periods of less than twelve months during the
year. Figure 2 illustrates how this concept can be used.

The precedure for developing erosion index distribution
curves is thoroughly discussed in SCS Technical Note 32
(Brooks, et al. 1974). Erosion index distribution curves that
represent specific areas of a state are available through the
Soil Conservation Service state offices listed in Appendix B.



Section 1.0
INTRODUCTION

Surface mining activity in the Interior Western U.S. is
increasing due to the energy demands of the Nation. As
disruption of surface lands increase, a tool is needed to
evaluate alternative mitigating measures needed in reclama-
tion of disturbed areas. This publication is directed toward
application of the Universal Soil Loss Equation (USLE) on
surface mined lands and is an effort to provide guidance to
those responsible for evaluating erosion control practices
included in mine reclamation plans. Erosion and sedimenta-
tion are environmental impacts that can be mitigated through
proper planning and implementation of conservation prac-
tices on disturbed areas.

The USLE is a tool developed initially for use in
evaluating conservation practices on the Nation's croplands.
Recent developments in the soil loss equation have made it a
potentially valuable tool for planning conservation practices
on disturbed areas resulting from construction and surface
mining activities. It is an empirical formula based on many
years of experience and research. The information gained by
application of the USLE can be used as a basis for comparing
alternative conservation practices used in reclamation plan-
ning.

Section 2.0
HISTORY OF THE SOIL LOSS EQUATION

An equation that related soil loss to length and percent
of slope was published in 1940. This equation utilized all
available rainfall data and was based upon the erosion data
then available in the United States. It is usually considered
the pioneering effort to put soil conservation practices for
cropland on a firm, quantitative basis.

Factors were developed to express the influences of
cropping and conservation practices on certain soils of the
Midwest during 1941. This became known as the Com Belt
equation. Between 1941 and 1946, further improvements
were made in the equation for use throughout Iowa by adding
factors to express the influence of soil type and quality of
management of soil loss. Continuing research and opera-
tional conservationists of the Soil Conservation Service, in
eight northcentral states, led to the development of the sys-
tem referred to as ‘‘slope practice for use in farm planning"’
(ARS, 1966).

In 1946, a nationwide committee on soil loss prediction
met in Ohio for the purpose of adapting the Corn Belt equa-
tion to other cropland areas with erosion problems. This
committee reappraised the Corn Belt factor values and added
arainfall factor. 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
and was used by the Soil Conservation Service in the north-
eastern states (Lloyd, et al. 1952).

An improved soil loss equation, developed in the late
1950’s, 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 Re-
search Service, Purdue University. 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 resulting in several
major improvements that were incorporated in the new soil
loss equation (Wischmeier, et al. 1971).

Wischmeier’s work in developing simplified relation-
ships of soil characteristics for estimating the soil erodibility
factor (or ‘‘K’’ value) was a major breakthrough and allowed
widespread use of the Universal Soil Loss Equation (USLE).
These relationships, addressed in Section 3.2 and on Figure 3
of this publication, have lifted many of the previous restric-
tions of the USLE.

The USLE has generally been limited until recently to
use on croplands of the eastern United States. It is now
potentially useful as a technique for estimating soil loss from
lands of the Interior Western U.S. disturbed by mining and
construction activities.


The line intercept methods should be used to de-
termine percent ground cover and canopy cover for
use in Tables 4 and 5. A 100-foot tape that mea-
sures in tenths of feet will permit easy conversion
to percent ground cover and canopy cover. (Can-
field, 1941.)

Control Practice Factor **P’’: The ‘*P”’ factor is ordinar-
ily applicable to cropland management systems,
however, research is underway to determine the
effects of contour pitting and furrowing on range-
land and pastureland. A follow-up investigation to
this report will consider the effects of pitting and
furrowing on mine reclaimed lands on the USLE.
Refer to Table 6 to select the appropriate ‘‘P’’
factor.

6.3 PREDICTING SOIL LOSS

The following represent examples of how the USLE
may be used to predict soil loss on lands which have been or
may be disturbed by surface mining activities. The primary
area of application of the USLE is anticipated to be with
regard to predicting any change in soil loss between the pre-
and post-mining land use conditions. Thus, step-by-step
procedures applicable to the situation are presented below.

It is also conceivable however that soil loss predictions
during active reclamation, i.e., between pre- and post-
mining, may be useful with respect to timing of reclamation
procedures such as mulching, seeding, sedimentation basin
design (assuming a soil loss-sediment yield relationship has
been established), etc., and thus, step-by-step procedures
applicable during this period are also presented.

Pre- and Post-Mining Land Use

Step 1: Develop an erosion factor map of the pre-mining
project area (Exhibit 2). Because topography prob-
ably will change, land use may change, and sub-
Strate characteristics may change, a post-mining
erosion factor map is necessary (Exhibit 3). Vari-
ous erosion sub-areas may occur within a single
land use area due to a change in one or more of the
erosion factors. Erosion areas can be delineated by
drainage patterns, land use, or various physical
differences. Field investigation will be necessary to
determine erosion factors for each designated area
or sub-area. A soils map of the area will be neces-
sary in all cases (Exhibit 1).

Step 2: Develop a chart to record the pre-mining condition

erosion factors for each erosion area (Exhibit 4).

Each sub-area/area delineated on the pre-mining
erosion factor map (Exhibit 2) is listed in Exhibit 4,
as are the USLE factors as determined from the soil
survey mapping effort (Exhibit 1) and information
from Tables, Figures and Appendix A presented in
this report. The information in Exhibit 4 is then
tabulated to give the average tons per acre per year
soil loss for each sub-area. Sub-area 1A for exam-
ple:

A=R

K Ls C P

Step 3:

A=(30) (0.37) (0.25) (0.10) (1);

where the topographic LS factor is determined

from Table 1 by interpolation:
A=0.28 tons per acre per year.
Knowing the number of acres involved, 1,290 for
sub-area 1A, the predicted tons per year soil loss
from sub-area LA is calculated to be 361.2. The soil
loss from the individual sub-areas/areas can be cal-
culated and summed to yield the total estimated
annual average soil loss from the mine area under
pre-mining conditions. Exhibit 4 shows a total pre-
dicted soil loss of 2,895.8 tons per year from the
mine area under pre-mining conditions. This
should not be mistaken for sediment yield.

Using the post-mining erosion factor map (Exhibit
3) a chart (Exhibit 5) similar to Exhibit 4 can be
developed. In the development of this chart, it is
reasonable to assume that some of the USLE factors
will remain constant for both pre- and post-mining
land use conditions. ‘*R’’ will always remain con-
stant. ‘*K’’ may remain relatively constant if the
surface soil is redistributed in the approximate vic-
inity where it was removed, but this constancy
cannot be confirmed nor denied with presently
available information. For calculation purposes in
this example a constant pre- and post-mining **K”’
value will be assumed. Future investigations will
address this issue. The remaining factors L, S, C,
and P may change depending upon any change in
the post-mining land use and topography variables.
that influence those factors. In this example, and as
shown in the factor values in Exhibit 5, several
changes have been assumed between pre- and
post-mining land use. A summary of changes is
presented below:

Post-Mining
Sub-Areas

1A, 1B,
IC, 1E

Assumed Changes

Change in ‘‘C’’ factor—assumes
50% post-mining ground cover den-
sity.

ID Same as above; plus includes pre-
mining area 3A, Cropland, assum-
ing it is changed to pastureland in-

creasing area by 300 acres.

2A, 2B Change in the ‘‘L”’ factor to 160 as
the result of terracing which is re-
flected in a change in the topo-
graphic ‘‘LS"’ factor. The practice
of contouring is also initiated for
post-mining land use resulting in a
“*P? factor of 0.50 (Table 6).

Post-mining land use change to pas-
tureland having the same factors as
area 1D and thus is included in 1D
for calculation purposes.

3A


3.2. THE SOIL ERODIBILITY FACTOR ‘‘K’’

The rate of soil erosion on any area is usually influenced
more by land slope, rainstorms characteristics, cover, and
management than by properties of the soil itself. Some soils,
however, erode more readily than others even when slope,
rainfall, cover and management are the same. This differ-
ence is due to properties of the soil itself and is referred to as
the soil erodibility.

Soil properties that influence erodibility by water are
those that affect the infiltration rate, permeability, and total
water holding capacity, and those that resist the dispersion,
splashing, abrasion, and transporting forces of the rainfall
and runoff. A number of attempts have been made to deter-
mine criteria for scientific classification of soils according to
erodibility. Generally, however, soil classification used for
erosion prediction have been largely subjective and have
only relative rankings.

The relative erodibility of different soils is difficult to
judge from field observations. Even a soil with a relative low
erodibility factor may slow signs of serious erosion when the
soil occurs on long or steep slopes or in localities having
numerous high-intensity rainstorms. On the other hand, a
soil with a high natural erodibility factor 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 (Wischmeier, et al. 1965).

Until recently, the lack of a simplified method to deter-
mine the erodibility of any given soil without actual soil loss
measurements has created problems in determining ‘‘K’’
values. Although soil loss on different sites may vary more
than tenfold just because of basic soil differences, the erodi-
bility factor has been directly measured for only a few soils.
A new method was developed under the leadership of W. H.
Wischmeier, of the Agricultural Research Service, U.S.
Department of Agriculture. The use of a relatively simple
nomograph (Figure 3) is of great value in determining ‘‘K’’
values, and thus, in planning conservation practices on se-
verely disturbed areas (Wischmeier, et al. 1971).

As shown in the nomograph, five soil parameters are
necessary to predict soil erodibility. These consist of percent
silt plus very fine sand, percent sand greater than 0.10 mil-
limeter, organic matter content, soil structure and permeabil-
ity.

Soil erodibility generally tends to increase with greater
silt content and decrease with greater sand, clay, and organic
matter content. Early studies concluded that within a range
from 0 to 4 percent organic matter, soil erodibility tends to
decrease appreciably as organic matter increase and mag-
nitude of change is related to soil texture (Wischmeier, et al.
1969). The effects of organic matter is excess of 4.0 percent
has not yet been determined.

The soil structure parameter reflects average relation-
ships between structure type and size. There are indications
that the magnitude of these relationships may be influenced
by structure strength and soil pH, but these affects are appa-
rently too small to be concemed with in-field application
(Wischmeier, et al. 1971).

The relative permeability classes coded on the nomo-
graph refer to the soil profile as a whole. Usually these can be
determined from routine profile descriptions. The control-
ling soil layer most often is below the surface layer. Includ-
ing the permeability parameter should not necessitate
laboratory determinations because general permeability clas-
sification guides are given in the USDA Soil Survey Manual
(USDA Soil Survey Staff, 1951).

The procedure for using the soil erodibility nomograph
is shown on Figure 3. For many agricultural soils having a
fine granular structure and moderate permeability, the value
of ‘‘K’’ can be read directly from the first approximation of
“*K’? scale on the right hand edge of the first section of the
nomograph, and the procedure can terminate there (Wis-
chmeier, et al. 1971). However, for purposes of determining
“*K’’ factors on lands disturbed by surface mining, it will
ordinarily be necessary to continue the procedure through the
structure and permeability curves.

Soil scientists with the Soil Conservation Service have
determined ‘‘K’’ factors for all established soil series in the
states included in this publication. Refer to Appendix A to
determine factor ‘‘K’’ for a given soil.

Soil profiles that have been moved, mixed, or otherwise
distributed are expected to experience a change in erodibility
(i.e., ‘“K’’ value). However, the magnitude of a change in
“*K”’ and varying relationships with time have not been
quantified. Even in cases where topsoil is preserved and
replaced, there may be changes in ‘‘K’’ values, due primarily
to structural changes. Future research efforts will be directed
toward studying the parameters of disturbed soils as they
relate to soil erodibility.


EXHIBIT 4

EROSION CALCULATIONS
Project: Coal Field Inc. Land Condition: Pre-mining Date.
Est. Est.
Areas Land Universal Soil-Loss Equation Factors Soil Acres Soil Loss
of the use or Loss in from Area
Project Cond. R K L s Ls Cc P__T/Ac/Yr Area Tons/Yr
1A Past. 30 37. 400) s15 25.10 1.0 -28 1290 361.2
1B Past. 30.37, 3005.0 9304210 43 1220 524.6
Ic Past. 30.24 150 3.032101. 23 550 “126.5
1D Past. 30. 37150042100 09 750 67.5
1E Past. 30.28 = 2002.0 = 25 20100 42 380 159.6
SUB-TOTAL (Pastureland) 4190 1239.4
2A Crop. 30. 37 — 600 2.034 36* = 1.0 1.36 440 598.4
2B Crop. 30. 28 = 400 3.044 86* 1.0 1.33 200 266.0
3A Crop. 30. 37,150 5.0.66 —36* 1.0 2.64 300 792.0
SUB-TOTAL (Cropland) 940 1656.4
TOTALS 5130 2895.8
Remarks:

* Present farming program is wheat-fallow with approximately 200 Ibs. of residue at planting time (see table 2).

20


EPA-908/4-77-005
July 1977

PRELIMINARY GUIDANCE
FOR
ESTIMATING EROSION ON AREAS DISTURBED
BY ;
SURFACE MINING ACTIVITIES
IN THE
INTERIOR WESTERN UNITED STATES

INTERIM FINAL REPORT

U.S. Department of Agriculture U.S. Environmental Protection Agency
Soil Conservation Service . Region VIII
we STA,

fh
SZ

‘ay prove

ee a
Y
()

% acenct

YW

‘SOR CONSERVATION SERVICE



Appendix A—Continued

sot
SERIES

SADDLE
SADDLEBACK

SAGE
SAGECREEK
SASUACHE,
SALADON
SALAS
SALIX
SALMO
SALTAIR
SALT LAKE
SAMBRITO
SAMPSON

SANSTL
SAN ARCACIO

SANBORN
SANCHEZ
SANDALL
SANDTA
SANDLAKE
SANDLEE
SANELT.
SANFORD

SANGREY
SAN ISABEL

SAN JON
SAN JOSE
SAN LUIS
SAN MATEO
SANPETE
SANPITCH
SANSARC
SANSON

SANTA FE
SANTANA

SAPINERO

SAPPHIRE

SAPPINGTON

SARATON

SANTAQUIN
SANTO TOMAS
SARPY
SATANKA,

SATANTA

SAVAGE
SAVENAC

savO
SAVOTA

SAWATCH
SAWCREEK

DEPTH
LHCHES

oni
uate
14-30
Q-10
10-60

on

11-30
30-50
0-5
5-60
0-72
0-40

4-35

0-60
o-4
4-16
16-27
27-48
48-63

0-12

0-21

+20

SOIL
SERIES
SAWPIT
SAYLES
SAXBY

SCAVE

SCHAMBER
SCHMUTZ
SCHNEBLY
SCHOFIELD

SCHOLLE
SCHOONER

SCHRADER

SCHRAP

SCHUSTER

SCOBEY

SCORUP

SCRAVO

ScoTT
SCOUT

SCROGGIN
SEARING
SEBUD

SEDILLO
SEDWELL
SEEDSKADEE

SEELEZ
SEIS
SEITZ
SELON
SEN
SERDEN
SERNA
SEROCO
SESSIONS
SEVY

SHAAK

SHALEY
SHAM
SHAMBO
SHANE
SHANTA

‘HARLAND

‘SHARPS

SHARROTT

SHARVANA

SHAVANO

SHAWA
SHAWMUT

DEPTH
THCHES

14-25

17-30

0-18
18-32
32-62
0-28
0-28
o-4
4-22
22-49
49-62
0-60
0-47

4-12
12-16
0-68
0-30
o-14
14-32
32-60
0-30
30-60
0-6
6-34
0-60

0-60

46-60

50-60
o-8
4-12
12-16
16-60
0-9
9-25
25-30
0-7
TAT

6-18
om
4-26
0-60
0-16
16-28
28-60

SOIL
SERIES
SHAY
SHEAR

SHEDADO
SHEEP CREEK

SHEEPROCK
SHENA
SHEPPARD
SHERBURNE

SHERLOCK

SHERM

SHEPRYL

SHINBARA

SHINDLER
SHINGLE

SHIPMAN

SHIPROCK
SHIRK

‘SHONKIN
‘SHOOF

SHOOFLIN
‘SHOOK
‘SHOSHONE

SHOTWELL
‘SHOWALTER

SHOWLOW

SHRINE
SHUE
SHUGE
SHULE
SHUPERT
SHUMWAY
SHURTLEFF
SIBYLEE

SICKLESTEETS

SIEBERT

SIECHE
STELO

SIESTA

SIGNAL

STGURD
SILI
SILVER
STMMONT

SIMONA
SINAT

SINGAAS
SINNIGAM

cB-SIL
SIL

6-26

0-26
26-60
0-12

12-51
9-16

16-28
28-40

0-12
0-10
10-30
30-56
0-3
3-31
31-44
44-52
0-60

0-17
0-16
16-36

2-43,
49-72
0-60
o-8
4-18
TAO

15

24
+20

+28
43
243

137
132
7

+28
+28

37
49
:28
17
+20
15,
132
37

224
+28
+24
10
+10
228
-32
+24
249
55,
224
232
43
+20
+28
24

+32
+20
+28
37
224
+28
43
+28
+24
+20


Tabte 1. Values of the Topographic Factor "LS"

Length
of Percent Slope (S)
Slope (L)
Ft. 0.2.0.3 0.4 0.5 1.0 2.0 3.0 4.0 5.0 6.0 8.0 10.0 12.0 14.0 16.0 18.0 20.0 25.0 30.0 40.0 50.0 60.0
20 05.05 = 06 06 608) 12) 18272480 wT 1.0 1.3 1.6 1.8 2.6 4 6 8 10
40 +06 07 ‘.07 08 6100.15 22,28 3443 6387 ,2 1.41.8 2.2 2.6 3.5 5 8 n 15
60 .07 08.08 608.1117 25 338A 52 77.00 1.8 2.2 2.6 3.0 4.5 6 10 14 18
80 .08 =.08 = .09 09.12, «19 27,37 4860 B92 16 2.1 2.6 3.0 3.6 5.5 7 Rf 16 21
100 08 = 609.09 +10 .13 «620,29 40 5467998 2.4 2.9 3.5 4.2 6.0 8 13 18 23
110 08 09 10 10.13 21 30 42 56 7161.0 41.6 2.0 2.5 3.0 3.7 4.5 6 9 14 19 25
120 09.09.10 100.14 6273043 59) 7410 7.0627 2.6 3.3 4.0 4.6 7 9 14 20 26
130 09.09.10 WT .14 0 2237446771216 22 2.8 3.4 4.1 4.9 7 9 15 20 27
140 09 10 10 Wo 14 22 32 46 63 80 1.2 1.7 2.3 2.9 3.6 4.3 5.1 7 10 15 2 29
150 09 10 W WTS 23 32 47 66 82 61.2 «1.8 2.4 3.0 3.7 4.5 5.3 8 10 16 23 30
160 09 10 n Wo .15 23 33 48 68 85 1.2 1.9 2.5 3.1 3.9 4.7 5.5 8 10 7 24 31
180 10 10 V1 W415 24 34 51 72 90 1.4 1.9 2.6 3.300 4.1 5.0 6.0 9 12 18 26 33
200 10 VW n 120.16 25 35 53 76 95 1.4 2.1 2.8 3.6 4.4 5.3 6.3 9 12 18 27 35
300 WW 12 13 4 18 28 40 62 93 1.2 1.8 2.7 3.6 4.5 5.6 6.8 8 12 16 25 35 45
400 12 13 4 .15 -.20 v 44 70 1.0 4 2.0 3.2 4.2 5.4 6.7 8.0 10 14 19 30 42 54
500 13 14 15 16.21 33 47.76 1 1.6 2.2 3.7 4.9 6.2 7.6 9.2 n 16 2l 34 47 61
600 4 15 16 17.22 34 49.82 1.4 1.6 2.4 4.1 5.4 6.9 8.5 10.3 12 16 24 38 53 68
700 15 16 V7 18 £23 36 $2 87 1.4 «21,8 2.6 4.5 6.0 7.5 9.3 11.3 13 18 26 4 58 75
800 15 416 Ww +18 24 38 54.92 1.6 2.0 28 4.9 6.4 8.2 10.1 12.2 14 20 28 45 58 81
900 16 7 18 +19 .25 39 66 .96 1.6 2.0 3.0 5.2 6.9 8.8 10.8 13.1 16 22 30 48 67 87
1000 16 18 19 +20 26 40 67 1.0 1.6 2,2 3.0 5.6 7.4 9.3, 11.6 14.0 V7 24 32 51 72 93
1100 V7 18.19 20 27 41 59 1.0 1.8 2.2 3.5 5.9 7.8 9.9 12.2 14.8 18 25 34 54 76 98
1200 W7 18 20 221 27 42 81.10.18 2.4 3.5 6.2 8.2) 10.4 13.0 15.6 18 27 36 57 80 104
1300 18 19.20 21 28 43 82 1.2 2.0 2.4 3.5 6.5 8.6 11.0 13.5 16.4 19 28 38 60 84° 109
1400 18 19.21 22 29 44 63 +2 2.0 2.6 3.5 6.8 9.0 11.4 14.1 17.1 20 30 40 63 88 114
1500 19 20.2) 22 29 45 65 1.2 2.0 2.6 4.0 7.1 9.4 12.0 14.7 17.8 ral uv 41 65 920 119
1600 19 20, «421 23 30 46 66 1.2 2.2 2.6 4.0 7.4 9.8 12.4 14.8 18.5 22 32 43 68 95 123
1700 «19.21.22 +2300 -.300 647) 67.20 2.2) 2.8 «64.0 7.6 10.1 12.9 15.9 19.2 23 33 44 70 97 (128
2000 +20, 622.23 +240 63200-49714 204 3.00 465 864 1714.70 «17205 ra) 25 36 49 77-108 (141

Contour limits - 2 percent 400 feet, 8 percent 200 feet, 10 percent 100 feet, 14 - 24 percent 60 feet. The effectiveness
of contouring beyond these limits is speculative

When the length of slope exceeds 400 feet and (or) percent of slope exceeds 24 percent, soil loss estimates are speculative
as these values are beyond the range of research data.


3.3. FACTORS FOR SLOPE LENGTH “‘L"’ AND
GRADIENT *‘S””

Soil erosion by overland flow of water is significantly
affected by both slope length and percent slope. For con-
venience and use in the field, the factors have been combined
into a single factor expressed as **LS"* (Wischmeier, 1974).

The factor **LS"’ is the expected ratio of soil loss per
unit area on a field slope to corresponding loss from the basic
nine percent slope, 72.6 feet long. Notice in Table | that by
interpolation a nine percent slope 72.6 feet long has an ‘‘LS’”
factor of 1.0.

The ‘‘LS"’ factor for gradients up to 60% and slope
lengths up to 2000 feet can be obtained from the slope effect
chart (Table 1). Research supports values up to 20% slope
and about 400 feet lengths. Values of ‘‘LS’* beyond these
limits are extrapolations beyond the range of field research
Slopes occurring on areas disturbed by mining activities will
rarely exceed 400 foot lengths, but will commonly exceed
20% gradient. Further efforts should be directed toward
research to substantiate ‘‘LS"’ values beyond the range of
400 foot lengths and 20% slopes.

In order to use this guide effectively, it is necessary to
have a good understanding of what constitutes slope length.
It is defined as the distance in feet from the point of origin of
overland flow to either of the following, whichever applies to
the major part of the area:

1. The point where the slope decreases to the extent that
visible deposition begins. The presence of alluvial
fans is a good indication of a significant slope
change.

2. The point where runoff enters an area of concentra-
tion that may be part of a drainage network or a con-
structed channel such as a waterway, terrace, or
diversion (Wischmeier, et al. 1965).

Refer to the slope effects, Table 1, to arrive at the factor
“*LS"*. For example, a 30% slope, 90 feet long, would have
an ‘‘LS"' value of 7.5 by interpolation.

Figure 4: Approximate original topography or contour can
be restored on most surface mined lands. Efforts should be
made to establish acceptable slope lengths and gradients on
restored lands.


-2-

as where it was initially collected. Topsoil salvaging operations, as
practiced in Montana and much of Wyoming, involve operators scraping
approximate surface thicknesses of all soil units and stockpiling every-
thing together. Such being the case, it is impossible for the operator
to redistribute the stockpiled soils in the same manner as they origi-
nally formed. Perhaps a better method of deriving a post-mining K
value, until current studies are completed, may be to use a weighted
average of K for all soil types found on the pre-mining site.

You also assume that major portions of reclaimed surface will be
returned immediately to pastureland. I am not aware of how other states
handle the matter, but Montana requires a minimum of a 5 year bond and
reclamation period before the regulatory agency can release the surface
for customary land uses. Put differently, no private grazing occurs for
at least 5 years following initial reclamation and revegetation attempts.
If other western states have similar practices you might consider them
to make the text example representative of current techniques.

3) I find sections 4.0 and 5.0 to contain the most interesting mate-
rial. In the first paragraph of the former, the rationale and practical
limit of the USLE is stated: "The USLE was developed to predict soil
loss from agricultural lands due to sheet and rill erosion. It does not
account for gully erosion, which cannot be predicted by any known formula."
You have accurately noted the original intent of the USLE, and you have
cautioned the reader that at least one other geomorphic process may be
unaccounted for in the equation. The potential user, especially if
technically unfamiliar with the scope of erosion/deposition phenomena,
must be made aware that sheet and rill erosion may account for only a
minor portion of the erosion occurring on reclaimed slopes. It may te
said that the primary difference between a rill and a gully is one of
size; making the distinction between a large rill and a small gully may
be difficult. For that matter, when does a rill become a gully?

Additional erosive processes also occur on reclaimed slopes in the
West, none of which are measured by the USLE. These include, but are
not limited to: wind action, piping, saturated flow, and soil creep.
The relative magnitude of these processes, degree of interaction, and
how they tie in with the channel processes which ultimately attempt to
remove slope-deposited sediments from the basin are al] virtually
unknown. Indeed, to quantify all of the above would probably tax an
innovative computer modeller. I doubt that the formulators of the USLE
ever intended their equation to cover the above phenomena.

You state in Section 5.0 that, "Gross erosion can be estimated by
use of the Universal Soil Loss Equation". I must take exception to this
statement. Sheet and rill wash are only a few of the erosive activites
operating on slopes in attempted reclamation areas. Likewise, it should
be clear that the USLE only covers two processes and excludes the others.
Until a comprehensive analysis is undertaken of the relative magnitude
of all processes operating on post-mining slopes, I consider it pre-
mature to equate gross erosion with sheet and rill wash. Inasmuch as
different processes may account for more sediment moved on post-mining
slopes than in the undisturbed state, using the USLE as an estimate of
gross erosion may provide estimates off by several orders of magnitude.


Appendix A—Continued

so
SERIES

MINERAL MOUNTAIN

MINNEOSA
NINNEQUA
MINNEWAUKAN
ION

MIRABEL
MIRACLE

MIRANDA
MIRROR LAKE

TRROR

WISHAK

WITCH

MITCHELL
WOANO
WOREETIE

NOBRIDGE
NODALE
MODENA

WOEN

SIL
SL

WOENKOPIE SL,LS
GR-LS ,GRV-LS

NOEPITZ
MOFFAT
MOGOLLON

WOGOTE

HOHALL

MOHAVE

MOLESE

WOKIAK.
OLAS

WOLLMAN
ona
HONDAMIN
WONDEY
MONROE
HONTE,

WONTEROSA
HONTICELLO

HoNTOSA
woHTOYA
MONTVALE
NONTWEL

SoHE
soopy

woRD

woREAU
NORENO

L

SL

cL

(L,cL)

DEPTH
TNCHES K
0-8 20
B-3u 32
34-6043
= 7
yu-60 237
0-4 232
4-30 32
0-60 0.15
on14 43
0-23 “17
o-4 128
4-30.28
0-60.32
0-16 32
16-70 117
0-8 “1S
8-30 +10
o-12 +10
12-30 .10
30-60 «10
0-36.24
0-26 = .10
26-60 143
243

0-9 143
O10 24
10-60-24
+32

0-6 143
6-54 243
0-5 +32
5-23 37
0-9 AS
0-9 +10
0-3 243
0-30.49
0-60.32
0-13.28
13-60 .37
0-8 +32
8-37 237
37-4520
45-60 «10
o-10 20
0-109
O-10 128
10-3532
35-60 .20
0-12 (SL).49
ont 248
11-55-43
58-60 .37
0-6 232
6-11 +28
41-18 .20
18-60-10
0-38 10
o-18 20
18-3324
0-34 +32
34-6032
o-14 37
14-ug9 37
ug-74 32
:37

0-9 -20
9-31 +32
31-60 132
0-6 -28
6-60.37
0-7 +24
7-60.24
o-12 017
0-8 37
8-56 3
0-6 37
6-18-20
18-60-10
0-60-37
0-18 17
0-12 «49
12-3737
0-52 49
+32

- +32
0-16 0.37
16-70-32
232

224

+28

1u-60 «20

rer

wee new

we

SOIL
SERIES

MORET

MORGALA

MORTARTY
MORLING
MORONT
MOROP

MORSET

MORTENSON
MORTON
MORVAL

MOSCA

MosBY
MOSHER
MOSIDA
MOSLANDER
MOTA
MOTOQUA
MOTT

MOUNTAINVILLE
MOUNT HOME
MOWEBA

MOYERSON
MUCET
MUDRAY

HUD SPRINGS
MUGGINS

MUGHOUSE
MULT

MUNDOS
MULLGULLO
MULLINVILLE

MUNJOR
MUNK

MURDO
MURDOCK
MUSINIA

MUSSEL

MUSSELSHELL

MYSTEN
MYTON SLL
ST-SL,ST-S

NAGEEST

NAHON

NAKAT

NAMBE

NAMON

NAPA

NAPALTO

NAPLENE

NAPLES, L

NARROWS
NASER
A-13

DEPTH
INCHES

0-6
6-15
Onu
4-29
29-60
0-60
o-14
0-60
9-10
10-25
25-60

21-87

0-30

0-60
9-60
0-60
0-16
0-46
46-60
0-11
11-60
0-17
17-60
0-30
30-55
0-18
0-17
0-2
2-12
12-17
0-25
0-12
12-18
18-50
50-60
o-u
4-24
o-14
14-24
0-8
8-28
28-60
0-2
2-18
18-60
o-u
u12
12-60

0-17
17-32

0-60
0-60

0-48

0-60
0-60
0-20
0-20
20-72

0-60

SOIL
SERIES

NATHROP
NATRONA
NATURITA
NAVAJO
NEBEKER
NECHE

NEDERLAND

NEESOPAH

NEHAR
ELMAN

NELSON
NEMOTE
EOLA
NEPALTO
NEPESTA

NEPHI

HESDA
HESKAHT
NETO

NETTLETON

NEVEE
NEVILLE

NEVINE
NEWCASTLE
NEWCOMB

NEWFORK
NEWKIRK

NEWLIN

NIBLEY
NICKEL
NIELSEN
NIRTLL
NIKEY
NIMBRO
NIOBELL
NIPPT
NIRADA
NISHNA
NISHON
NIWOT
NOBE
NODEN

NOEL
NOKHU

NOLAM
NOONAN
NORA
NORBERT
NORCAN

SL
STV-SL

vEPTH
INCHES,

0-8
8-15
15-28

ow
0-60
0-18
14-55
55-70
0-10
10-60
0-7
7-20
20-60
0-14
16-60
0-47
0-10
10-26
0-9
9-30
0-3
3-80
0-12
0-60
0-15
15-60
0-10
10-33
33-70
0-8
8-60
0-69
90-13
13-38
38-58
o-18
18-30
30-50
50-86

0-10
10-60
0-17
17-32
32-60
0-60
0-15,
15-60

0-7
TAT
0-8
8-17
17-22
22
0-13
13-43
43-58
o-11
11-19
19-60
0-19
0-8
8-60
0-26
0-26
26-60

0-60
0-9
o-44
14-40
0-13
13-60

o-14
14-60

0-5
5-20
20-60

o-14
14-32
32-60
0-9
0-60

0-27
0-15
15-60

224
232
+43

24
243
37
+28
243,
232
43
+10
+10
+10
+24
+24
+10
15
215
+20
+20
215
+10
+28
49

37
232
43

+32
+10
249
220

+15
143
37
+32
+17

+28
37
232
228
a7
+28
+24
210

24

+10

224
+28
37

+28
+28
224

+32
232
+32
237
2H
332

Be ewe


SoTL
SERIES

AABERG
AASTAD
BAC
ABAJO

ABARCA

agBorT

KBCAL,

ABCLA

ABERDEEN

BES.

‘BOR

BRA GR-L, L.
GR-SL, SL

‘ABRAHAM

ABREU

ABSAROKEE

ABSHER

ABSTED

ABSTON

AcACTO

‘ACASCO

ACEL

ACKMAN
ACREE
ADEL.

ADELINO

ADENA

ADGER

ADILIS GR-SL, GR-L

L, St

ADIV

ACAR
AGASSIZ

AGNER

AGNESTON
AGUA
AGUA FRIA

AGUALT FSL
L

DEPTH
INCHES

o-8
4-30
onta
16-19
0-19
0-10
10-20
20-50
o-u
4-30
30-60
0-6
0-60
0-28
28-60
0-26
26-60
0-15,
15-21

12-60
1-60

o-8
4-20
20-60
0-3
3-60

0-7
7-18
0-7
7-33
33-60
0-6
6-25
0-27
27-60
0-21
21-30
30-60
0-12
0-12
12-27
27-60

+28

49

+10

210

APPENDIX A

Factors ‘*K’’ and ‘“

SOIL
SERIES

AGUSTIN
AHLSTROM
AIRPORT
AsO
AKASKA
AKELA

ALADDIN
ALAMA

ALAMOSA

ALBATON
ALBINAS

ALCESTER
ALCOA

ALDER

ALEMEDA

ALGERITA

ALICE
ALICIA
ALLENS PARK

ALLENTINE

ALLESSIO

ALMONT

ALY

ALOVAR
ALPINE LOOP

ALTA

ALTVAN
AMARILLO

AMBRANT
AMESHA
AMHERST

AMOR
AMOS

AMSDEN
AMSTERDAM
ANTOFT
ANAMITE
ANAPRA
ANASAZI
ANCHO

ANCO
ANDREEN

DEPTH
INCHES K
0-60 17
0-7 232
7-40 37
0-19 228
19-60 443
0-2 +28
2-24 224
-28
0-18 a7
0-60 224
0-3 43
3-28 43
28-60 .u3
0-12 +28
12-40 «28
W0-60 0.28
28
0-3 232
3-25 128
25-60 43
28
0-7 224
7-25 22
25-60 .2u
0-6 232
6-11 237
31-30 43
0-9 224
9-13 224
13-26 0.17
0-5 +24
5-37 :28
37-66 32
0-60 +20
0-60 “49
0-10 +20
10-26 .20
0-3 283
3-42 249,
42-60 64
0-8 24
8-25 17
25-60 .10
0-8 228
8-60
0-6 +28
6-25 237
25-60 137
0-60.37
0-18 232
19-33 443
33-64 .37
0-12 128
12-36 143
36-54 137
+32

A-l

0-11 (FSL).24
0-11(LFS).20

11-80 .32
0-39 a7
0-28 +32
28-74 = .37
0-2 =32
2-10 28
0-31 +28
0-3 37
3-41 24
0-12 +32
12-60 ug
0-8 37
8-28 +03
28-60 .28
0-20.28
0-3 249
3-56 255
0-26 243
26-60 .17
0-24 ug
0-60 37
0-60.37
0-9 15
9-20 0.15
20-60 .10

SoIL
SERIES

ANDREESON = L

ST-L,ST-CL

ANDREWS
ANETH
ANGOSTURA
ANIMAS

ANNABELLA SL

DEPTH
INCHES

CB-SL,GR-SLO-10

ANSEL

ANSELMO
ANT TLAT LCL
ST-L

ANTELOPE SPRINGS

ANTEPO

ANTHO
ANTHONY SL,GR-SL.
L

ANTLER
ANTROR!S
aNTY
AMWAY SL
L
SICL

ANVIK
ANZTANO

APACHE
APISHAPA
APRON

ARAPIEN

ARAVE
ARCH

ARCHERSON

ARCHIN
ARENA
ARIZO
ARLE
ARMIJO
ARMINGTON
ARNEGARD
ARNHART

‘ARNO

10-60
0-12

12-36
36-60

o-11
o-14
11-32
32-60
0-3
3-13
13-48
0-7
7-60
0-60
9-10
0-10
10-60
0-16
16-60
o-158
15-60
0-8
8-40

18-42
42-60

12-30
30-60
9-16
0-8
8-60
0-6
6-60
0-13
13-38
38-60

20-60
0-60


Appendix A—Continued

SOIL
SERIES

SIPPLE

SIOUX

SISSETON
SIXMILE

SIZER SILL
GR-SIL,GR-L

GRV-SIL,GRV-L

SKAGGS

SKUMPAH

‘SKUTUM

SKYLICK

SKYWAY

SLAUGHTER

SLIPMAN

sLocuM

SLUICE

SMARTS
sMoor
SMUGGLER
SNAKE HOLLOW
SNOMO

SNOWILLE

SOLDIER CBV-L ,GRV-L
CB-L,GR-L

SOFIA

SOGZIE
SOLOMON
SOMERS

SONOTTA
SONTAG

SORDO

SORUM,

SOTELLA
soriM

SOUTHFORK

SOUTHACE
SPAA

SPACE CITY
SPANGLER
SPEARFISH
SPEARMAN
‘SPENLO
SPICERTON
SPLITRO
SPONSELLER
SPOOL

SPOON BUTTE

DEPTH

INCHES

0-7

11-27
27-50

14-40

11-19
19-62

SOIL
SERIES

SPOTTSWOOD

SPRINGER

SPRINGERVILLE

SPUR

‘SPURLOCK

STADY
STAGECOACH

STAPLETON
STARLEY

‘STARMAN
STECUM
STEED
STEGALL
‘STEINAUER
STELLAR
ST. ELMO
STERLING
STETTER
STEWART

STICKNEY
STINGAL

ST GEORGE
STILLMAN

STIRK
STIRUM

ST MARYS

STODA

STOKES

STONEHAM

ST ONGE
STORLA

STORNITT

STORY

sTouT
STOVHO
STRAIN

STRAUSS
STRAW
STROUPE
STRYKER
STUBBS

STUKEY

STUMBLE

STUMPP

STUNNER

STUTZMAN

DEPTH
INCHES

0-25
25-60

K

+28
:10

O-16(LFS).17
0-16(FSL).20

A-18

16-80 .20
o-u 220
4-39 +20
0-15 +28
0-15(FSL).24
18-60 .28
0-7 224

(L,cL) 0-7 +28
0-28 232
0-29 +28
29-60 .10
0-16 -10
16-60 .10
0-60 © 40
0-9 22
9-15 +20
On 228
4-8 228
0-5 +20
5-28 215
0-17 232
17-60 .10
0-7 +32
7-28 132
- +32
0-60 +28
0-10 215
10-30 .10
30-60 10
0-16 126
16-48 .20

+28
L 0-9 +55

SL,FSL 0-9 +20

9-22 -

37
0-6 “43
6-48 +55
4e-74 6
0-60 243

FSL 0-40 255

GR-FSL 0-10.43.
10-60 10

+28
0-7 22
TH 232
44-6017
0-50 +20
O-t1 +28
11-6755
o-t1 249
11-24 37
24-68 55,
O-4(L) £20
o-u(SL) .17
uo +20
9-60 +20

228

+28

228
0-6 +28
6-14 +37
14-28 © .32
28-72 .28
0-6 +32
6-36 237
36-60 10
0-16 226

37
0-7 +28
7-14 ay
14-60 .37
0-60 +32
0-24 17
0-6 +32
6-34 243
0-29 +32
29-60 .32
0-3 4.32
3-32 +32
32-60 .10
0-7 “15
1-28 224
25-60 .28
0-60 37

SOIL
SERIES

SUBLETTE

SUDDATH

SUGARDEE

SUGARLOAF
SUGLO

‘SULA

SULLY
SUNBURST
SUNCITY
SUNSET
SUNSHINE
SUNUP
SUPERSTITION
SUPERVISOR
SVEA
SVERDRUP

SWANBOY
SWAPPS

SWASEY

SWASTIKA

SWEETGRASS

‘SWENODA
SWIFT CREEK

SWIFTON
SHINS

SWINT
SYRACUSE
SYRENE

SYRETT

‘TABERNASH

‘TABIONA

‘TABLE MOUNTAIN

TACAN

TACNA

TAFOYA

TAO
TALAG
TALLY
TALMO
‘TAMBIONA
‘TANELY
TAMPICO
TANNA
TANSEM
TAOS

TAPIA

0-60

24-60

0-15
19-23

4-27
o-14
11-30

47
17-26
26-32
32-60
0-29
29-60
0-8
8-60
0-72
ont
4-25
25-54
54-60

0-60
0-17
17-60
0-12
12-23
23-38
0-6
6-34
34-60
0-7
7-60
0-24
24-60
0-60

2-u4
41-60
o-t4
14-39
39-46
0-3
3-28
0-8
5-22
22-49
0-60

0-15
15-62
0-6
6-50
0-6
6-27
27-31
0-60
0-22
22-60
0-24

24-60

+43

+20

+20

28
15,
+32
+28
37
43
+24
+28
+24
15,
+28

24


()
(2

(3)
(4)
(5)
(6)
(7

(8)
(9)

(10)

(0))
(12)

(13)
(4)

(15)
(16)

Section 8.0
BIBLIOGRAPHY

Brooks, Frank L. and Turelle, Joseph W., 1974. Universal Soil Loss Equation. Technical Note No. 32. West Technical
Service Center, Portland, Oregon.

Canfield, R. H., 1941. Application of the Line Interception Method in Sampling Range Vegetation. Journal Forestry
39:388-394,

Dendy, F. E. and G. C. Bolton, 1976. Sediment Yield-Runoff-Drainage Area Relationships in the United States, Journal
of Soil and Water Conservation. Volume 31, No. 6.

Dollhopf, D. J., J. B. Jensen, and R. C. Hodder. Effects of Surface Configuration in Water Pollution Control on Semiarid
Mined Lands. U.S. Environmental Protection Agency, Demonstration Grant No. R-803079-01-0.

Holeman, John; Turelle, Joseph W.; and Barnes, R. C., 1975. Procedure for Computing Sheet and Rill Erosion on Project
Area. Technical Release No. 51, Washington, D.C.

Lloyd, C. H., and Eley, G. W., 1952. Graphical Solution of Probable Soil Loss Formula for Northeastern Region. Journal
of Soil and Water Conservation 7:189-191.

Mannering, J. V., 1967. The Relationship of Some Physical and Chemical Properties of Soils to Surface Sealing. Ph.D.
thesis, Purdue University, Lafayette, Indiana.

SCS National Engineering Handbook; Section 3, Sedimentation; Chapter 6, Sediment Sources, Yields, and Delivery
Ratios; Washington, D.C., 1971.

Soil Taxonomy, December 1975. A Basic System of Soil Classification for Making and Interpreting Soil Surveys.
Agricultural Handbook 436. USDA—Soil Conservation Service.

Soil and Water Research Division, Agriculture Research Service, 1966. A Universal Equation for Predicting Rainfall-
Erosion Losses. ARS Special Report.

USDA Soil Survey Staff, Soil Survey Manual, USDA Handbook No. 18, August 1951.

Wischmeier, W. H., and D. D. Smith, 1965. Predicting Rainfall-Erosion Losses from Cropland East of the Rocky
Mountains. Agriculture Handbook No. 282. U.S. Government Printing Office, Washington, D.C.

and J. V. Mannering, 1969. Relation of Soil Properties to Its Erodibility. Soil Science Society AM. Proc. 33(1): 131-137.
C. B. Johnson and B. V. Cross, 1971. A Soil Nomograph for Farmland and Construction Sites. Journal of Soil and Water
Conservation. September-October 1971. Volume 26, No. 5.

1974. New Developments in Estimating Water Erosion, Proceedings of the 29th Annual Meeting of the Soil Conservation
Society of America, August 11-14, 1974, Syracuse, New York.

1976. Use and Misuse of the Universal Soil Loss Equation. Journal of Soil and Water Conservation. January-February
1976. Volume 31, No. 1.

26


FIGURE 2

Erosion Index Distribution Curve
for Computing Factor ‘R’’ for Less than 12 Months

100 “ayaate rT)
~*~
a
a 80
g
3
60 4
Pp j
g H
& 40 iy =
& Western |
a A Colorado ‘a
a 20 7
B ?

0 wteejentecl

W aw 4. SA Of WA 8/1 91 10/1 11 12AN

DATE

Example

Earth work will be completed on a project area on or about June ist. It is estimated that mulching and seeding will be
accomplished by October 15th. What will be the adjusted ‘R’’ factor during this stage of reclamation given R=30?

Factor “‘R’’ will be adjusted to indicate only the Erosion Index (EI) units that occur during the period from June 1 to October
15th. This is accomplished as follows:

Determine the percent of annual EI at each date. June 1 %EI=65

October %EI=98
The difference, (98~65=) 33, indicates 33% of the annual ‘‘R’’ factor occurs during the specified time period.
Determine the adjusted ‘‘R”’ factor: R(Adjusted)=.33R=.33(30)=9.9


EXHIBIT 1

SOIL MAP
Owner Coal Field Inc. Operator Same
County Diablo State Colorado

Soil survey sheet (s) or code nos. page 29 Approximate scale 2" - 1 mile

Prepared by U. S. Department of Agriculture, Soil Conservation Service
cooperating with Conservation District

Soil Legend

AsB - Ascalon fine sandy loam
0-1% slopes
1 PoB
HeB - Heldt Clay Loam, 1-3% slopes
HoB - Holderness loam, 1-3% slopes
PoB - Potts loam, 1-3% slopes

Pot - P > 3-5% slopes
otts loam pe Ass

—

7


State of AHMontana
Office of Che Governar
Helena 9401
Northern Powder River Basin EIS
Power Block Bldg., Rm. 221

THOMAS L JUDGE

30. ERNOR

July 8, 1977

Mr. Arnold C. King
scs, USDA

P.O. Box 17107

Denver, Colorado 80217

Near Mr. King:

Through Messrs. Dan Kimball and Gary Parker of the EPA, Denver, I
received a copy of your draft report on the application of the Universal
Soil Loss Equation to surface mined lands in the West. I was asked to
submit substantive comments directly to you. My comments are enclosed.

I necessarily view all slope erosion studies and applications as
part of a larger picture, that of the drainage basin. Slope and channel
processes are interrelated to the extent that generally only the basin
unit provides a comprehensive perspective of erosion/deposition phenom-
ena. Accordingly, I consider an application of the USLE to the reclama-
tion process to be of limited utility. However, I concur with you in
that it apparently is the best thing we have going at present which
attempts to quantify even a portion of the action.

I must also point out that my experience primarily derives from
Montana, and to a lesser extent, Wyoming. Therefore, my comments are
biased towards this experience.

I hope the enclosed comments will be of some use to you. If you
have any questions, please feel free to contact me.

Regards,
David Stiller

Eydrologist-Geologist
NPRB EIS State Team

DS:gs

Enclosure

cc: Dan Kimball, EPA
Gary Parker, EPA

C-2


Appendix A—Continued

Sor
SERIES

GACHADO

GADDES

GADSDEN c

GAINES

GALATA

GALCHUTT
GALETON

GALISTEO

GALLATIN

GALLEGOS

GALLINA

GAMBLER

GANNETT
GAPO

GAPPMAYER
GARBER

GARDENA
GARDNER'S. FORK
GARITA

GARLAND

GARLET

GARO

GARRETT

GARSID

GARZA

GAS CREEK

GATESON

GATEVIEW
GATEWAY
GAVINS
GAYLORD
GAYNOR

GAYVILLE
GEERTSEN

GELKIE
GENDA
GERBER
‘GERRARD
GETTYS
GIBBLER

GILA

GILBY

GILCREST

GILISPIE

(1,SIL)
(FSL)
(cL)

DEPTH
INCHES

0-2
2-8
8-13

14-60

34-50
50-60
0-21

21-50
0-10

10-24,
21-60
0-13

13-20
20-45

0-10
10-60
8-60
0-22
22-60

20-60

30-60

T

SOIL
SERIES

GILKON

GILLAND
GILMAN

GILT EDGE

GIRARDOT
GIRD
GLADEL
GLASSNER

GLENBAR

GLENBERG
GLENDALE
GLENDIVE
GLENDERSON
LENDING
GLENHAM
GLENROSS
GLENTON

GLYNDOW
GOLDCREEK

GOLDFIELD
GOLDVALE

GOLvA

GOMEZ

coock
GORDO

GORING

orus
GOSHEN
GOSHUTE

GOSLIN
GOTHARD

GorHIC

GorHo

GOURLEY

GRABE

GRABLE
GRACEVILLE,
GRAFEN

GRAHAM

GRAIL
GRAMM,

GRANATH

GRANER

DEPTH

1

FSL

cL

L, SIL
CL,SICL

(Fst)
(LFS)

(SL,GR-SL)
(L, SIC)

INCHES

0-42
42-60
0-28
0-13
0-13
0-13
13-60

40-60

40-66

+28
“49

+32

+32
132

128
+32
22
+28

SOIL
SERIES

GRANILE

GRANO
GRANTSDALE
GRASSNA
GRAYPOINT
RAT

GREAT BEND

GREEN CANYON

GREENOUGH
GREENLAW
GREEN RIVER
GREENSON

GRENADIER

GREYBACK

GREYBULL
GREYCLIFF
GRIFFY

GRINSTAD
GRINSTONE.

GRIZZLY
GROWLER

GRUMMIT
GRUVER
GUADALUPE

GUAJE
GUBEN

cuEsT

GUILDER

GULNARE

GUNBARREL,
GUNSIGHT

GUNSONE
cuy

GYPNEVEE
GYSTRUM

HACCKE
HADES

HAGGA

HAGERMAN
HAGGERTY

HAGSTADT

HATLMAN
HALFORD

HALE MOON
HALGATTOH

GRV-L
GReL

DEPTH
INCHES

0-9
9-18
18-44,
41-60
0-48
48-60
0-32
32-36
0-60
4-16
16-60
o-4

0-13
13-60
0-9
9-18
16-42
0-40
40-48
0-14
14-42
42-60
0-60
0-16
16-75
0-3
3-18
18-40
0-18
18-28
28-60
o-4
4-28
0-60
o-4
4-19
19-60
0-28
0-12
12-20
20-27

0-7
7-13
13-60
0-8
8-80
0-38
38-60
o-14
ony
0-14,
24-4
44-54
0-10
0-28
28-60

18-60
0-60

15-60

19-39

0-48

+15

249
43
+24
+73
32
+32
37
+32
37
+28
+32
+28
17
+10
237
“49


Appendix A—Continued

SOIL SERIES
SERIES

HALL
WALLECK

HAMAR
HAMERLY

HAMILTON
HAMLEY
HANAKER
HAND
HANDRAN
HANLY
HANS
HANSEL
HANSON
HANTZ
HAP
HAPNEY
HARBORD

HARDING

HARDSCRABBLE
HARDY

HARGREAVE

HARKERS

HARKEY
HARLAN

HARLEM
HARMONY
HARQUA
HARRIET
HARRISBURG
HARRISVILLE.

HARVEY
ASK
HASKILL
HASSELL
RAT

HATCH BL

HATERHUS
HATERTON

HATHAWAY

HATTIE
HAUGAN

DEPTH
INCHES

0-16
6-60
0-60
0-8
8-60
0-48
0-60
0-60
+28
0-9
9-60
0-60
0-7
7-34

20-60

0-60
0-60
0-35

8-60
0-50
0-60
0-27
27-32
32-72
0-7
7-32
0-5
5-60

0-2
2-23
23-36
0-18

214
0-24
24-60
0-60
0-15
15-35
35-49
49-66
0-12
0-24

6-60

kK

32
+20
a7
17
+28
:37
37
-32
37

+10
15
7
37
243
+43
37
243,
49
132

+28
+24
+32
+28
232
+15
220
+20
+20
28
+28
+20
+24
+24

+43
49

37
43
232
22h
+49
243
49
+55

28

37

+28

32
+32
115
+20
28
+20

+10
10

4
232
4

SOIL
SERIES

HAYFORD

HAYNESS:

HAZTON
HEADQUARTERS

HEATH

HEBER
HEBGEN

HECHT

HECLA
HEFLIN

HEGNE
HEIL

HETMDAL
HEINSAW

HEIST

HELDT
HENDRICKS:
HENEFER
HENHOIT

HENKIN
HERD

HEREFORD

HERMERING
HESPER

HESPERUS

HIERRO

HIGGINS
HIGHLAND

HIGHMORE
HIGH PARK

HIGHPOINT
HIIBNER

HIKO PEAK
HIKO SPRINGS

HILGER
HILLERY

HILLFIELD
HILLIARD

HILLON
HINMAN

HISEGA
HISLE
HITCHEN
HOBACKER
HOBOG
HOFFMANVILLE

HOGELAND

DEPTH
INCHES

0-5
5-19
19-29
29-60
0-15
15-60
0-17
0-29
29-51
0-5
5-22
22-60
0-60
0-7
To14
14-24
24-60
on
4-9
9-32
0-72
O-8
4-36
36-56
0-60
0-60
0-19
19-60
0-8
8-60
0-12
12-42
42-60
0-8
6-60
0-15
15-66
0-20
20-60
0-10
10-60

0-20
20-70
0-13
0-13
0-13
13-60
0-3
3-60
ony
44-60
0-11
11-44
44-60
0-10
10-29
29-60

0-13
19-28
28-72

0-6
6-60
0-8
0-6
6-52
0-34
3u-60
0-14
14-60
0-60
0-18
18-60
0-21
21-60

0-60
0-7
7-18
18-60

sort DEPTH
SERIES INCHES
oce 0-3
3-52
HOGRIS 0-60
HOLDAWAY 0-20
HOLDEN 0-13
13-43
43-72
HOLDERNESS o-12
11-40
40-60
HOLLOMAN 0-9
HOLLOWAY 0-9
9-64
HOLMES 0-21
21-60
HOLROYD 0-3
3-60
HOLT
HOMELAKE 0-12
12-60
HONDALE (L,SIL) 0-8
(SSL) 0-5
(SICL) 0-5
Sua
41-60
HONDO 0-5
5-57
HONEYVILLE o-13
13-64
HOODLE 0-13
43-42
HOOPER 0-5
5-18
18-32
32-60
HOPKINS 0-16
HOPLEY 0-42
HORATIO o-u
u-19
HORD
HORROCKS 0-42
HORSLEY 0-6
HOSKIN 0-7
7-28
HOSKINNINA 0-12
HOSSICK 0-18
18-23,
HOUDEK
HOURGLASS 0-10
10-50
HOUSE MOUYTALYLGRY-L,CBV- 0-12
8 a1
pover  ORV-CL, CBY-cL
HOVENWEEP 0-10
10-32
HOVERT
HOYE LOH
GR-SL 0-4
4-60
HUB 0-6
6-14
14-60
HUBERT 0-15
15-48
4e-105
HUECO 0-5
5-30
HUFFINE 0-5
5-24
24-35
35-60
HUGGINS
HUGHESVILLE 0-12
12-27
HUGUSTON 0-3
3-16
HUME 0-6
6-60
HUNCHBACK o-14
14-60
HUNTING 0-60
HUPP 0-18
18-60
HURLEY
HUTT o-4
4-66
HYANNIS 0-3
3-42
12-30
HYAT on
11-25
25-28
28-60

15

+24

+24

“37

43
37
+28
+20
+24
+32
137



Re:

Re:

Re:

Comments on Draft "Preliminary Guidance for Estimating Erosion
on Areas Disturbed by Surface Mining Activities - Interior Western U.S.".

Section 3.2, para. 11, page 10, (Draft Copy).

It should be noted that the soils listed in Appendix A are of Established
Series. There are numerous soils in Wyoming for which a series name has not
been developed. Thus, not all soils mapped by the SCS in the interior states
can be found in Appendix A.

Section 3.3, para. 3, page 11, (Draft Copy).

In Wyoming there are many proposed final slope conditions that will exceed
400 feet horizontal distance (HI). We have accepted in mountainous or hogback
terrain slopes as great as 1,200' HI. So, I feel it is untrue to make the
statement that slopes in the Interior States will rarely exceed 400' in
length, for in rough terrain it is quite customary to realize slopes of this
length or slightly greater.

Section 3.4, para. 4, page 13, and table 4, page 17.

The reported "C" values in table 4, are not applicable to conditions
initially existing on retopsoiled surface mined lands. As indicated in the
table title these are factors for permanent pasture and rangeland. The factors
were derived to include a "type III - soil residual effect" (Wischmeier,1972).
However, on retopsoiled surface mined lands the soil residual effect will be
minimal, thus the factors for "Type III effect" would approach 1.0.

With omission of the soil residual effect a "C" factor for a site having
"No appreciable canopy", "no canopy cover %", and no mulch or residue cover
(column 3, table 4) would be near 1.0. This value differs significantly from
the 9.45 value reported in column 4 -- table 4, which is the only value that
a user could use for the site conditions listed in the previous sentence.
Clyde et al (1976) list factors for bare soil conditions on construction sites
ranging from 1.0 to 0.8. In my judgment these values more accurately repre-
sent "C" values for bare totally disturbed surface mine topsoil conditions
during the initial year.

To make the "C" values more applicable to reclamation conditions their
derivation should be basic to the anticipated minesoil - cover conditions.
I suggest that "C" values which do not account for "Type III residue effect"
(report in Wischmeier, 1972) be established for bare recently redistributed
topsoil conditions, Primary emphasis in erosion control design will be in the
initial years of revegetation.


EXHIBIT 7
EROSION CALCULATIONS

Project: Coal Field Inc. Land Condition: Active Reclamation Date.
Est. Est.

Areas Land Universal Soil-Loss Equation Factors Soil Acres Soil Loss
of the use or Loss in from Area
Project Cond. R K L Ss LS c P TIAc Area Tons/Period
(Time Period 1)

Ist year 5/15-10/1

Phase I bare 15.6*  .37, 400 1.5 25 10 1.0 1.44 480 691.2

(Time Period 2)
Ist year 10/1-5/15 Mulch and

Phase I Seed 14.4 37 400) =1.5 25 06 1.0 -08 480 38.4
SUB-TOTAL (lst year) 480 729.6
and year 5/15-5/15
Phase I estab. 30.37, «400 1S 2520120 55 480 264.0
SUB-TOTAL (2nd year) 480 264.0
TOTALS 480 993.6
Remarks:

* Factor ‘*R"* has been adjusted to reflect total erosion index units from May 15 to Oct. 1 (See figure 2). Target date for
mulching and seeding is October Ist. From October Ist to May 15th the 2 tons of mulch (See table 5) should remain effective.
The second year should be the establishment year with a ‘‘C’’ of approximately .20 (See table 4).

23


Re: Section 3.3, table 1, page 12.

As was stated earlier in the comments, we encounter numerous occasions
in a reclamation contour map where final proposed slopes exceed 20% and are
> 400'. Thus, regardless of how speculative "LS" factors may be at this
magnitude of slope conditions, it is important that "LS" values reported for
these conditions are the best available and should be liberal rather than
conservative,

Many of the values reported in table 1 for the greater slope - length
conditions appear to be less than what has recently been accepted as more
accurate,

Example:

Table 1 reports for 20% slope and 400 foot length a "LS" value of 8.0.

By the following equation where slope length (n) = 400' and
% slope (S) = 20:

-43 + .3(20) + -=43(207) ) -400 0.8 10,000

Us =( 6.613 726  ‘T,000+(207)

) = 9.6

The above modified equation is from Clyde et al (1976) anda
nomograph for "LS" values is shown in enclosed Figure 5-ll.

It appears that the reported value of 8.0 in Table 1 was calculated using
an exponent of 0.5 on thelength fraction of the equation:

43 + .3(20) + .043(20? 400 an 10,000
6.613 726 10, 000+(20°)
Clyde et al (1976) and Fuster (personal communications, 1976) indicated

that for slopes > 10% an exponent of 0.6 should be utilized on the length
fraction of the equation.

d5¢

LS = ) = 8.1

I suggest that these changes be considered for Table 1.

feferences Cited

yde, C.G. et al. 1975. "Erosion Control During Highway Construction." Natl. Coop.
High. Res. Program, Proj. 16-3, Transp. Res. Board. Natl. Res. Counc.,
Vol. II, 103p.

bster, George. 1976. (Personal Communications). Purdue University.

he, G.W. et al. 1976. "Use of Soil Properties to Estimate Soil Loss by Water Erosion
“on Surface-Mined Lands of Western North Dakota." North Dakota Farm Research
Vol. 34 (2).

lsby, G.c. and T.J. Toy. 1976. "An Evaluation of Surface-mine Spoils Area Restoration
in Wyoming Using Rainfall Simulation." Earth Surface Processes, Vol.1:375-386

lischmeier, W.H. 1975. "Estimating the Soil Loss Equation's Cover and Management Factor
for Undisturbed Areas." Proc. Sediment~Yield Workshop, 1972.


TABLE OF CONTENTS

Page

1.0 Introduction ..... 2.6.0 foe ek eect teen bee cen beeen bene eee teens 1

2.0 History of the Soil Loss Equation !

3.0 The Universal Soil Loss Equation 2

3.1 The Rainfall Factor ‘‘R”’ 2

3.2 The Soil Erodibility Factor ‘‘K’” 4

3.3 Factors for Slope Length ‘‘L’’ and Gradient “‘S"" 6

3.4 Cover or Crop Management Factor ‘*C’’ 8

3.5 The Erosion Control Practice Factor ** 0)

4.0 Uses and Limitations of the USLE ..........0 10. c cece cece neces tenet nett eee en es eee 12

5.0 Soil Loss vs. Sediment Yield....... 0.0... cece ese eee eee ete beeen nee en cnet nent eens 12

6.0 Application of the USLE .................. 6... Pee eee cen n en een ent e eens 13

6.1 Developing an Erosion Study . . 13

6.2 Determining Erosion Factors 13

6.3 Predicting Soil Loss 14

7.0 Glossary... 2... cece ee ete nee ene nee renee nee eee nent e nent en ee nea 24

8.0 Bibliography .. 2.2.2... cece cece etn nee nner e ene t tent e teeta 26

LIST OF FIGURES

Figure 1 Map Showing Average Values of Factor *‘R'’ (See envelope inside back cover)...........0..00.00es0e 28

Figure 2. Erosion Index Distribution Curve . . 3
Figure 3 Nomograph for Determining Soil Erodibility Factor ‘*K’’ .

Figure 4 Approximate Original Topography 6

Figure 5 Vegetative Cover 9

Figure 6 Surface Mined Land Reclaimed for Cropland ........... 00.00 ese cece cece ence ete ee eeseneeae UL

LIST OF TABLES

Table 1 Values of the Topographic Factor “LS” 0... 26.0 e cece eee eee tee e cece eee cece veee veueneee 7

Table 2. Crop Management Factor ‘*‘C’’ for Cropland 8

Table 3. Factor ‘‘C’’ for Woodland ... 9

Table 4 Factor ‘‘C’’ for Permanent Pasture and Rangeland . 10

Table 5 Factor ‘‘C’’ for Various Quantities of Mulch ..... 10

Table 6 Determining Factor “*P’?... 1... ieee eee reece eee eee eee e een eens .



Appendix A—Continued

SOIL
SERIES

RAZOR
REAGEN

REAKOR
RECLUSE

REDBANK

RED BUTTE

REDCAN
REDCHIEF

REDCLOUD
REDCREEK
REDFEATHER

REDFIELD
REDIG
REDLANDS

REDLODGE
REDMANSON

REDNUN

REDOLA

REDONA

REDRIDGE

REDROB
RED ROCK

REDSTOE
RED SPUR

REDSTONE
REDTHAYNE
REDTOM

REDVALE

REDVIEW
REDWASH
REE
RFEDER
REEVES
REFUGE

REGAN
REGENT

REGNTER
REKOP

RELAN

RELIANCE

RELSOB

REMIT
REMUNDO
RENBAC
RENCALSON
RENCOT

RENNER
RENOHILL

DEPTH
INCHES

0-28
0-30
30-60
0-65
o-4
4-30
0-5
5-60
0-8
8-16
16-60
0-15
0-7
7-13
13-34
34- 60
0-60
0-15
0-8
8-12
12-17
0-60

0-7
7-18
18-60

0-5

10-42
42-60

0-9
37-84

0-26
26-48
48-56

47-61
0-60

10-40

o-4
4-16
0-13
13-26
28-62

14-18

0-7
7-14
14-30

+28

SOIL
SERIES

RENSHAW

RENTILL
RENTSAC

REPP
REPPART
RESERVE
RETRIEVER
REYAB
RHAME
RHOADES
RHOAME
RHOAMETT
RICHEAU
RICHEN

RICHEY

RICHFIELD
RICHLIE
RICHMOND
RICHVILLE
RICKHAN

RICKMORE

RICKS

RIcoT

RIDD

RIDGELAWN

RIDGEVIEW
RILLINO GR-L

DEPTH
INCHES

GR-SL,GR-FSL
GR-FSL,GR-SL

GR-L

RILLITO

RILLOSO
RIMROCK
RIMTON
RING
RINGLING
RISTA
RIVRA
RIZOZO
ROB ROY

ROBANA

ROBLEDO
ROCK RIVER

ROCKWELL,

ROCKY FORD

ROGER?
ROLETTE

A-16

0-15
15-60
0-7
7-18
0-25
25-65
0-10
10-39
39-57
0-40
o-8
8-14
0-60
1-34
0-49

16-34
34-60

K

28
+10
+28
228
224
22
+28
+28
+32
+28
237
243
3-32
249
220
232
+28
224
137
+32
232

10

SOIL
SERIES

ROLTSS
ROLLA
ROMBERG
ROMBO
RONAN
ROND

RONSON
ROOSET

ROTEL
ROSAMOND
ROSANE
ROSEBUD
ROSEGLEN
ROSHE SPRINGS

ROSWELL
ROTHIEMAY

ROTTULEE

ROUBIDEAU
ROUND BUTTE
ROUNDLEY

ROUNDTOP

ROUNDUP

ROUNDY
ROUTT

ROXAL

ROXBURY
ROY

ROZLEE
RUBY

RUDD
RUKO

RULE

RUNE

RUSO

RUSSLER
RYAN
RYAN PARK

RYARK

RYEGATE
RYELL

RYORP

L
CL, SICL

DEPTH
INCHES K
os 28
16-60 137
0-60 232
0-9 132
3-29 628
29-60 +32
0-20 132
20-30 124
om lua
4-60 137
0-3 lag
ay 132
q-se 128
20
o-7 le
qin 128
11-60 +20
0-23 128
0-8(SL,FSL)
0-B(L,CL)
8-60
0-28 «30
28-60 110
‘2
0-60 132
0-20 124
20-52 143
0-88 115
o-4B 132
48-60 128
0-15 37
15-22 332
on 128
4-8 128
a2 143
12-32 37
0-7) lar
Ti 132
au-67 13
0-2 132
32137
32-28 137
0-3 lug
‘a2
au
a2
‘a7
+32
au
24
‘a8
128
tar
oe
‘32
+32
0-6 632
6-60 128
one 128
38-30 124
0-6 12e
6-13 10
ons 1a
ou lau
wig lau
oe 11s
18-32 15
0-2 lug
o-2 lar
aa 187
23-60 124
0-22 +20
22-60 10
o-38 la
0-60 +28
ou 132
uso 12
0-2 las
peau
18-30 117
30-60 +10
0-824
9-17 132
17-32 +28
0-8 +28
e202
2e-60 to
o-34 20

we


Appendix A—Continued

SOIL
SERIES

NORDIC

NORKA

NORREST
NORRISTON
NORTE
NORTHDALE
NORTONVILLE
NORWAY FLAT

NOVARY
NUCLA

nusceT

NUTLEY
NUTRAS

NUTRIOSO cL

OAHE
OAKDEN
OAK LAKE
OASIS

OBRAST
OBRAY

OBURN

OCEANET

OGLALA
OHAYST

OUATA

OKATON
OKO

OKREEK
OLDHAM

OLGA

OLJETO
OLNEY

oLTON

OMADE
ONASON

Onova
ONAWA
ONEILL
ONITA
ONITE
ONRAY

OPAL

ORCHARD

‘ORDNANCE

ORDWAY

ORELLA
OREM

DEPTH
INCHES

0-15
15-40
40-70
0-7
7-13
13-60

0-9
9-16
16-60
0-30
30-60
0-8
8-31
0-12
12-60
0-12
12-60

o-10
10-60
0-6
6-21
21-50
0-12
12-30
30-60
0-10
10-47
47-60
0-60
0-8
9-60
o-47
0-17
17-36
36-44
44-60

0-13
13-48
48-60
0-60
0-7
7-60

7-36
36-60

Sai

0-27
27-60
nat
11-60
0-69
0-8
8-16
26-22
22-60
0-8
8-80

0-3
3-11

+20

SOIL DEPTH
SERIES INCHES
ORO GRANDE o-10
10-16
OROFINO on
4-23
23-48
ORSA 0-20
20-60
ORTIZ 0-28
ORTON
ORWET
OSAKIS o-14
14-60
OSCURA 0-60
scoop 0-30
OSHA 0-32
32-50
OsMUND 0-10
10-30
30-60
OSORTDGE 0-5
5-23
sore 0-33
33-55
OSTLER 0-18
18-60
OTERO (SL,FSL)0-14
(GR-SL) 0-14
14-60
‘OUARD 0-2
2-46
OURAY 0-20
20-60
OVERGAARD —GR-L 0-10
LFS 0-10
PSL 0-10
GR-SL,GR-FSL 0-10
10-42
42-52
OVERLY 0-60
OWEN CREEK 0-6
6-36
PACK 0-60
PACTOLA
PAGODA 0-16
16-46
46-60
PAGOSA 90-22
22-44
PAHREAH 0-12
12-38
PAICE 0-31
PAINTROCK ony
4-42
12-30
PASARITG 0-5
5-60
PAKA
PALA 0-3
3-18
18-40
PALACIO o-4
4-22
22-44
PALISADE 0-16
16-72
PALMA 0-7
7-60
PALMER CANYON O-4
4-28
28-60
PALOMAS o-16
16-66
PALOMENO L 0-9
FSL 0-9
STX-FSL 0-9
STK-L 0-9
9-15
PALOS VERDES GR-SL 0-1
GRV-SL (0-4
GR-L Ont
10-21
21-60
PANGUITCH Ont
14-47
47-56
PANKY 0-6
6-24
24-60
PAOLT 0-20
20-25
25-60
PARCHTF

SOIL
SERIES

PARIETTE

PARKAY

PARLEYS

PARLIN

PARLO

PARNELL.
PARSHALL,
PARTRI
PASSAR

PASS CANYON
PASSCREEK

PASTURA
PATENT
PATIO

PATRICIA

PAULSON

PAUNSAUGUNT

PAVANT
PAVILLION

PAYMASTER
PAYSON
PECOS
PEDRICK

PEELER

PEETZ

PEEVER
PENA

PENASCO
PENDERGRASS

PENDROY

PENINSULA
PENISTAJA

PENITENTE
PENNEL
PENO
PENROSE

(cn-L)
PENSORE

PENTHOUSE — §T-L
CB-CL
PERCETON

PERCIVAL
PERELLA

PERITSA
PERMA

PERRY PARK

PERRYVILLE = GR-L
SL

DEPTH
INCHES K
0-8 +43
8-24 37
21-30 .32
0-8 12
8-60 +20
0-15 232
15-33 .32
33-6049
ontt +24
11-310 415
31-60 .10
o-t4 .37
11-30 143
30-4015
0-60 +28
0-60 +20
0-15 232
15-28 28
28-60 .28
0-12 17
12-60 .37
ont4 +15
0-8 +32
rer 37
14-23 .28
0-10 +32
0-60 +32
0-13 +15
13-26 20

0-17 (FSL). 24
0-47(LFS).10

17-8024
0-5 137
5-10.49
10-34 632
34-6049
0-3 £20
3-15.17
o-19 128
0-3 24
3-32.28
ou “49
4-24 137
24-30 155
0-56.32
O17 lH
37-6017
o-16 18
16-3215
32-60 115
0-9 210
9-28 10
28-60 10
0-49.28
49-60 137
0-18 12H
18-60 117
0-12.20
0-5 124
S14 24
0-02.37
42-70 143
0-7 132
o-4 124
4-28 132
28-60 24
0-60.15
0-60.32

128
0-32 (L) 115
0-42.40
0-3 132
3-12.28
0-3 :37
0-3 232
3-27 128
27-60 24
0-200 145
20-34 148
0-18.28
18-60 143
0-31 137
0-15 fag
15-60 115
0-12 110
12-60 140
o-9 249
0-8 a7
838149
38-60 20


Table 4. ‘‘C’’ Factors for Permanent Pasture and Rangeland

Vegetative Canopy Cover That Contacts the Surface 1/
Type and Height Canopy Percent Ground Cover
of Raised Canopy 2/ Cover 3/ Type 4/

my 0 10 20 40 60 80 95-100
No appreciable canopy G 1.0 45 20.10 042.013. .003
WwW 1.0 45 24 AS 090.043 OL
Canopy of tall forbs 25 G 1.0 36 17.09 038 =.012 003
or short brush Ww 1.0 36 200.13 082.041 OL
(0.5 m fall ht.) 50 G 1.0 26 13.07 035.012, .003
Ww 1.0 26 160 AL 075.039 OIL
75 G 1.0 17 10.06 031 011.003
WwW 1.0 17 12.07 067, 038 — 01
Appreciable brush 25 G 1.0 .40 18.09 040.013, .003
or brushes WwW 1.0 40 22 «14 085 =.042,— 011
(2 m fall ht.) 50 G 1.0 34 16.085 .038 012.003
WwW 1.0 34 A913 081.041 O11
75 G 1.0 28 14.08 036 =.012,—.003
WwW 1.0 28 AT 12 077, 04011
Trees but no appreciable 25 G 1.0 42 A910 041 013.003
low brush Ww 1.0 42 23 14 -087 042 O11
(4 m fall ht.) 50 G 1.0 39 18.09 040.013. .003
Ww 1.0 39 210 14 085.042, 01
75 G 1.0 36 17.09 039 012.003

1/ All values shown assume: (1) random distribution of mulch or vegetation, and (2) mulch of appreciable depth where it exists.
2/ Average fall height of waterdrops from canopy to soil surface: m=meters.

3/ Portion of total-area surface that would be hidden from view by canopy in a vertical projection, (a bird’s-eye view).
4/ G: Cover at surface is grass, grasslike plants, decaying compacted duff, or litter.

W: Cover at surface is mostly broadleaf herbaceous plants (as weeds with little lateral-root network near the surface, and/or
undecayed residue.)

Table 5. Factor ‘‘C’’ for Various Quantities of Mulch

Mulch—adequately crimped into soil “C”’ Factor
bare areas 1.0
Y ton straw mulch per acre 52
Vermeer ” om 35
4” ” now 34
Deo ” now 18
mon” ” noon “10
pe o# ” noon 06
ZH ” noon 03
4a" ” noon ‘02


Re:

Re:

Section 4.0, para. 4, page 20.

Enclosed as Appendix A is a discussion on the "TI" value or permissable
soil loss level (PSL). Paragraph 3 of this appendix relates our attitude
towards establishing a PSL for predictive measurements. We generally utilize
15T/ac/yr as a PSL for the initial years of reclamation. This value is
utilized on construction sites for water qulaity control and control of
sediment delivery to sediment traps, (Personal communications, George Foster,
Hydraulic Engineer, Purdue University.

Section 4.0, para. 6, page 21

Gee et al (1976) measured soil erosion using a rainfall simulator on
a Flaxton sandy loam spread over mine spoil. They measured a 35% increase
in the "K" value over that listed by the SCS or calculated by the Wischmeier
nomograph. Because of these early results I suggest that the SCS K values
be skewed upward to enable more liberal calculations or when estimating the
"K" by the Wischmeier nomograph the mine soil be considered massive or
structureless and the permeability reduced.


Section 4.0

LIMITATIONS AND USES OF THE UNIVERSAL
SOIL LOSS EQUATION

The USLE was developed to predict soil loss from
agricultural lands due to sheet and rill erosion. It does not
account for gully erosion, which cannot be predicted by any
known formula. Neither does it predict sediment yield or
stream loading (see Section 5.0).

The USLE has not found wide use to date as a tool for
evaluating the potential and adequacy of proposed surface
mining reclamation activities, but consideration of such ap-
plication is receiving wider acceptance. The USLE can pro-
vide a basis for comparison of the impacts and long-term
productivity of pre-minded land conditions with those pro-
posed for post-mine reclamation. As more information is
acquired and substantiated by investigative efforts, both the
precision and accuracy of the quantitative predictions of soil
loss with respect to Interior Western mine lands will be
established.

A value known as soil loss tolerance, ‘‘T’’, is used as an
indicator of the adequacy of soil resource management prac-
tices on agricultural lands under continuing production con-
ditions. The ‘‘T’’ value is the amount of soil that can be lost
in a year from a particular soil series, while at the same time
supporting sustained long-term agricultural productivity of
that land.

Soil loss tolerances, or “‘T’’ factors, are included in
Appendix A for all soil series occurring in the eight-state
area included in this publication. It is thought that ‘‘T’’
factors may provide some comparative value for estimated
soil loss for a particular soil series on reclaimed mined lands.
However, it must be recognized that ‘‘T”’ factors shown in
Appendix A were developed for use in planning and evaluat-
ing conservation plans on cropland. Most of the areas of land
where this guide applies in the Western United States will be
reclaimed following mining for grazing or wildlife usage. In
addition, such areas will be severely disturbed where mining
takes place, and in many cases, high rates of erosion will
occur on these disturbed areas until permanent cover is estab-
lished. Additional efforts need to be directed toward quan-
tifying ‘‘T’’ factors for both overburden material and top-
soiled areas in conjunction with mined land reclamation.
Until additional guidance is available, the applicability of the
“*T”’ factors shown in Appendix A may be of limited utility.

A potential source of significant error in the accuracy of
soil loss prediction by the USLE is in selecting and assigning
the factor values. The conditions to be evaluated must be
clearly defined.

The accuracy of the USLE when applied to land dis-
turbed by surface mining is dependent upon the relationship
between the assumed factor values and the actual conditions
that determine the factor. The accuracy of the ‘‘K’’ value is

of particular concern. In many instances and for purposes of
sample calculations in this report, the *‘K’’ value has been
assumed constant for pre-mining and post-mining condi-
tions. The actual characteristics and the potential changes in
the ‘K’’ value with respect to field application are presently
unknowns. Due to severe disturbance of the soil between
pre- and post-mining, some change in the **K’’ value bet-
ween pre- and post-mining conditions may be variable with
time and continuously change until stable conditions are
established.

Soil, cover, and management conditions may not match
specific guidelines shown in the tables and charts, and inter-
polated values guided by judgment and experience may often
be necessary. Interpolation and assumptions should not
however diminish the usefulness of this publication if the
outputs and conclusions reached are put into proper perspec-
tive. It should be kept in mind that the primary value of the
USLE lies in its ability to compare alternative reclamation
practices quantitatively.

Section 5.0
SOIL LOSS vs. SEDIMENT YIELD

Sediment yield is equivalent to the gross erosion minus
what is deposited en route to a given point. Sediment yield
estimates are needed to evaluate sediment loading to streams
and to determine sediment design requirements for sediment
control structures. The yield of a given area varies with the
changing patterns of precipitation, soil, cover, drainage pat-
terns, topography, and size of the drainage area.

A method of determining sediment yield has been used
for many years by the Soil Conservation Service. The esti-
mate of sediment yield is made by use of the following
equation:

Y=E(DR)
where
Y=sediment yield (tons/unit area/year)
E=gross erosion (tons/unit area/year)
DR=sediment delivery ration (always less than 1)

Gross erosion can be estimated by use of the Universal
Soil Loss Equation. The sediment delivery ratio should be
determined by a sedimentation geologist or engineer. Many
interrelationships of watershed characteristics must be con-
sidered in order to determine accurate sediment delivery
ratios (SCS Engineering Handbook, 1971).


REVIEW NOTICE

This report was prepared for the U. S. Environmental Protection Agency by the U. S. Department of Agriculture, Soil
Conservation Service, Denver, Colorado, under Interagency Agreement EPA-IAG-D6-F 154. This report has been reviewed by
the Region VIII Office of Energy Activities, EPA, and approved for publication in interim final form. Approval does not signify
that the contents necessarily reflect the views and policies of the Environmental Protection Agency, nor does mention of trade
names or commercial products constitute endorsement or recommendation for use.

A field investigative phase by the Soil Conservation Service will follow this preliminary guidance effort.

FOREWORD

This publication describes the appliction of the Universal Soil Loss Equation (USLE) to the task of estimating sheet and rill
erosion from lands of the Interior Western United States that have been or may be disturbed by surface mining.

This work has been accomplished under an interagency agreement, EPA-IAG-D6-F071, between the Soil Conservation
Service and the Environmental Protection Agency, Region VIII, Office of Energy Activities. Mr. Amold D. King, State
Conservation Agronomist, and Mr. Tommie J. Holder, State Soil Scientist, both members of the Soil Conservation Service
staff, directed and performed the work in preparation of this document. Mr. Dan Kimball and Mr. Gary Parker of the EPA were
project officers for this study.

Acknowledgment is given to the personnel of the respective State Soil Conservation Service offices who provided valuable
assistance during the data development phase of this project and to Ms. Shirley Lindsay of the EPA, Office of Energy Activities
for her critical review and recommended changes.

ABSTRACT

Increasing demands are being placed on the coal resources of the Interior Western United States. This publication provides
guidance on use of the Universal Soil Loss Equation (USLE) to predict water-related erosion on areas distributed by surface
Mining activities. The information should prove to be useful in developing and evaluating mining plans, as well as in evaluating
the environmental impacts of various surface mining projects.

The USLE is a method of estimating soil loss from sheet and rill erosion as a function of rainfall intensity, soil erodibility,
length/percent slope, vegetative protection and erosion control practices (contour tillage and stripcripping).


Appendix A—Continued

sorb
SERIES

EMERALD

EMIGRANT

EAIGRATION

MONS = L,FSL.
SIC

EAPEDRADO

DARICK
ENCIERRO

ENDLICH
ENET

ENGLEWOOD
ENLOE
ENNING
NOS
ENTENTE
EPHRAIM
EPPING
ERSTE
ERCAN

ERD

ERNEM
ERRAMOUSPE.
ERVIDE,
ESCABOSA
ESCALANTE
ESHOND
ESPLIN
Ess
ESTELLINE
ESTERBROOK
ESTRELLA
ETCHEN

ETHAN
ETHELMAN

ETHETE

ETHRIDGE

bath

ETTA
EVANSTON

EVARO

EQUINE,
ATH

EAIRDALE
TAIRFIELD

FALCON

DEPTH
INCHES

0-12
12-60
0-7
7-13
13-30
0-18
0-7
0-7
7-49
0-10
10-24
24-40
0-20
20-60
0-5
5-14
0-22
0-24
24-60
0-9
9-34.
34-60
0-60

21-36
36-50
0-8
8-32
32-38
38-60
0-9
9-60

ani6
0-60
o-14
14-40
40-60
0-60

7-36
36-60
0-7
7-14

Fen aNne

5-4

SOIL
SERIES

FALFA

FALKIRK
FALLSAM
FANNO

FANNO
acid variant
FARAWAY
FARB
FARGO
FARISTA

FARLAND

FARNUF

FARSON

FASKIN (FSL)
(urs)

ATTIC

FEATHERLEGS

FEDORA
FELAN
FELOR
FELTNER

FERDIG

FERGUS

FERNANDO
PERN CLIFF

FERROW
FIELDING
FIFER
FINNERTY
FIRESTEEL,

FIRMAGE
FIRO

FISHERS
FITZGERALD
FIVEMILE
FIVEOH
FLANDREAU
FLASHER
FLATHEAD
FLAXTON
FLECHADO
FLEER
FLEAK

FLOM
FLORISSANT

FLOWELL

FLOWEREE

FLUETSCH

DEPTH
INCHES

0-12
12-36
36-64
64-70
0-34
34-60
0-9
9-46
0-25
0-13
13-40
0-8
0-10
0-60

unt?
nu
4-18
18-60
0-7
7-60
0-3
3-10
10-60
0-8
0-8

0-60
0-3
3-45

0-12
12-60
0-26

26-60

49
235
37
132

+32
+28
+28
+32

“15
15
+28
+10

0-5(SICL).43
0-5(SCL) .32

5-60
0-60

0-10
0-24
2u-44
usu
0-22
22-60
0-8
9-60
0-30
30-60
0-17
0-60
ow
4-22
22-31
0-12
12-38
38-72
0-6
6-60
0-10
19-30
30-60

A-7

:37
+32
+28
17

sou

SOIL
SERIES

FLYGARE

FLYNN
FOLA

FONDIS
FONTREEN
FORD
FORDVILLE
FORELLE
FORESTBURG
FORMAN

FORNEY
FORREST

FORSEY
FORSGREN

FORT COLLINS
FORTWINGATE
FOSSILON
FOSSUM
FOURLOG
FOURMILE,
FOXPARK
FOXTON
FOXOL

FOY

FRADDLE
FRAM
FRANCIS
FRAZER

FRIANA

PREECE
FREEDOM

FRISCO
FRIDLO

FROLIC

FRONTON

FRUITA

FRUITLAND

(cold variant)

FRYE

FULCHER

FULDA
GABALDON

st.
L
scl

DEPTH
INCHES

0-17
17-36
36-60

0-6
6-16
16-60
0-7
7-23
23-60
0-60
0-16
16-34
0-26
24-60
on
4-15
15-60

o-8
4-29

29-60
29-60

16-60

2-40

9-10
10-26
0-7
TAT
o-1a
11-60
ow
4-33
0-18
18-60
0-23
23-73
0-60
0-3
3-39
39-54

0-60
0-16
16-80
0-29
29-43
43-60
0-35
35-42
412-66
0-3
3-16

4-20
20-60
0-26
28-39
39-58
0-12
0-12
0-12
12-26
26-38
38-60
0-15
18-31
31-64
O-11
41-82
42-60
0-60

0-60

K

249

+28
37


EXHIBIT 5
EROSION CALCULATIONS

Project: Coal Field Inc. Land Condition: Post mining Date.
Est. Est.
Areas Land Universal Soil-Loss Equation Factors Soil Acres Soil Loss
of the use or Loss in from Area
Project Cond. R K L s LS c P__T/Ac/Yr Area Tons/Yr
1A Past. 30 37 400 1.5 25 07 1.0 19 1290 245.1
1B Past. 30 37 300 50 93.07 1.0 72 1220 878.4
IC Past. 30 24 = 150 3.0 32 07 1.0 16 550 88.0
ID Past. 30 37. 150 1.51907 1.0 AS 1050 157.5
IE Past. 30 28 200 20 25 07 1.0 15 380 57.0
SUB-TOTAL (Pastureland) 4490 1426.0
2A Crop 30 -37—:160* 2.0.23. 36 ——.50* 46 440 202.4
2B Crop 30 28 160* 3.0  .33 36 —.50* -50 200 100.0
3A Included in area 1D

* The cropland will be terraced to reduce slope length and farmed on the contour (See table 6).

SUB-TOTAL (Cropland) 640 302.4

TOTALS 5130 1728.4

Remarks: The following assumptions were necessary.

1. Mined areas will be restored to approximately original topography.

2. Introduced plant species plus improved management will result in approximately 50% ground cover.

3. Topsoil will be redistributed over approximately the same area where it was removed. If this is accomplished, ‘*K’’ factors
will remain relatively constant.

21


2 SOF IWND

EPA-908/4-77-005
July 1977

PRELIMINARY GUIDANCE
FOR
ESTIMATING EROSION ON AREAS DISTURBED
BY
SURFACE MINING ACTIVITIES
IN THE
INTERIOR WESTERN UNITED STATES

INTERIM FINAL REPORT

Prepared for:

U.S. Environmental Protection Agency
Region VIII
Office of Energy Activities
Denver, Colorado

By:

U.S. Department of Agriculture
Soil Conservation Service


Appendix A—Continued

soll DEPTH
SERIES INCHES
TARKTO 0-9
5-60
TARRETE 0-60
TARRYALL 0-10
10-30
TASSEL
TASSELMAN, 0-3
3-18
TATIYEE 0-12
12-30
30-60
TAYLORSFLAT 0-20
20-72
TAYLORSVILLE 0-7
7-59
TEAPO 0-3
9-30
TEALSON 0-10
10-16
TECOLOTE 0-20
20-60
TEELER o-4
4-10
10-23,
23-60
TEEMAT 0-3
3-60
TELEFONO 0-14
14-26
26-36
TELEPHONE CBV-SL,STV-SL 0-17
CBSL,ST-SL_ 0-17
GR-SL 0-17
TELFER 0-60
TELLMAN 0-8
8-30
30-60
TELLURA o-14
14-36
36-60
TELSTAD 0-5
5-38
38-62
TENVIK 0-6
6-60
TENCEE 0-7
TENEX O-1t
11-23
23-70
TENTBAC 0-12
12-36
36-48
TENORIO 0-6
6-22
22-60
TENRAG 0-21
21-53
‘TENSLEEP 0-2
2-7
7-60
TEOCULLI 0-60
TEPEE
TERADA 0-3
3-29
TERINO 0-15
TERMINAL, 0-10
10-22
TERRAD 0-7
1
TERRERA 0-15
TERRY 0-5
s-14
14-26
TESAJO 0-60
TESUQUE
TETON 0-6
6-32
32-38
TETONKA
Tex
TEXLINE
TEZUMA
THAYNE
THEBO
‘THEDALUND,

4-20

215

24

+32

+24

+24

SOIL
SERIES

‘THERMOPOLIS

THESS
THIEL

THIOKOL

THOENY

‘THOROUGHFARE.

‘THORREL

‘THREEMILE
THUNDERBIRD (7B-CL)
(ST-CL)

‘THURLONI
THURLOW

THURMAN
TIAGOS

TIBAN
TICELL
TIDWELL SL

TIFFANY
TIGERON

TIGIWON

TIGON
TIJERAS

TILFORD
TILTON

‘TIMBERG

‘TIMPANOGOS

‘TIMPOONEKE
TINAJA
TINE
TINGEY
TINSLEY
TINYTOWN

TIPPER
TIPPERARY

TISWORTH

TIVOLI
TOBLER
‘TOBISH
TOBY
TODDLER
‘TOEHEAD
‘TOHONA
TOLBY
TOLMAN
TOLNA
TOLTEC

TOLTEC
variant

DEPTH
TICHES

o-8
4-15

0-20
20-60
0-5
5-36
36-60
0-6
6-20
20-60
0-4
4-60
0-5
5-20
20-30
30-60

13-25
28-66

3-13
13-60
0-2
2-15
0-19
19-40

0-12
12-60

15-27
27-60

10-18
18-60
0-60

4-60
0-12
12-60
0-28

5-60
0-3

8-24
24-60
0-7
7-60
0-13
0-13
13-60
0-35,
0-60

SOIL
SERIES

TOLUCA

TOLVAR

TOMAH

TOMAS
TOME

TOMICHT
TONCAN

TONGUE RIVER

TONKA
TONRA

TONUCO
TOOLE

TOONE
TOQUOP
TOQUERVILLE
TORCHLIGHT
TOREX
‘TOPREOM
TORRINGTON

TORSIDO

TORTUGAS

TOSTON

TOTELAKE

TOTTEN

TOURS
TOWNER

TOYAH

TOE
TRAIL

‘TRAIL CREEK
‘TRAPPER
TRAPPS
‘TRAVELERS
TRAVESSILLA
TREBOR
‘TRELONA
‘TREMANT
‘TREMBLES
‘TRENT
‘TRENTON

‘TRES HERMANOS
‘TRESANO
TRICON

‘TRIDELL

‘TRINCHERA
TRIPIT

TRIPP

cBV-L
GRV-L

27-60

0-16
o-u
4-60

24-60

12-60

0-6
6-23
23-46
0-6
6-59
0-16
0-8

0-7
7-14
0-23
23-60
0-60

0-8
8-60
0-40
40-60
0-3
3-60

7-33
0-8
0-8
8-38
38-50

o-u
4-12
12-30

243

28

17

143,

a7

32


Appendix A—Continued

sor
SERIES

BIG HORN

BIG TIMBER

s1J0U

BIGNELL
BILLINGS
BINCD
BINTORD
BINGHAM OL

GR-L
CB-L

BINNA

BINTON

BIPPUS

BIRCH

BIRDOW
BIRDSLEY
BITTERROOT

BITTON
BLACKBURN

BLACKHALL
BLACKETT
BLACKLEED
BLACKMAN
BLACKPIPE

BLACK RIDGE,
BLACKROCK

BLACKSTON
BLACKWATER
BLAINE,

BLAKE
BLAKELAND
BLAMER
BLANCA

BLANCHARD
BLANDING
BLANYON

BLAZON
ALENCOE

BLENDON
SLEVINTON
SLODGETT
BLOOK

SLUEPOINT
BLUERIM

BLUE STAR
BLUFFDALE,

ArBuRG

DEPTH
INCHES K
o-4 49
4-26 .37
26-60 137
0-6 232
6-18 +28
0-15, +10
0-18 +10
18-33 .10
33-60 10
o-11 232
11-1528
15-60 20
0-60 143
0-7 +28
7-60 228
0-18 220
16-60 10
0-10 +28
0-10 224
0-10 226
10-18 24
18-60 © .10
0-24 :37
24-2817
28-60 10
0-6 237
6-60 243
o-14 243
0-28(L) 28
0-28(FSL). 24
28-60 .28
0-16 120
14-2215
22-38 = .10
0-60 228
0-14 143
o-tt 232
11-36 .37
0-21 132
21-86 624
ue-6u 128
o-12 37
1-42.28
42-60 149
o-12 232
0-60 224
o-14 “17
14-4015
0-30 37
30-60 .37
232
0-16 +20
0-8 117
8-39 24
39-52 .28
ont4 10
14-28 10
28-60 © .10
0-22 228
0-16 +28
16-35 .32
0-12 +10
12-60 .10
0-30 “17
0-16 +28
16-40 17
Yo-s4 410
0-60 15
0-60 249
0-10 37
10-2543
25-60 «43
o-14 243
.20
0-30 =20
30-60 «24
0-16 17
16-44 15
on :37
4-60 37
0-9 “17
o-u1 a7
ui-8000 17
0-3 15
3-18 124
18-29 .20
0-19 .15
19-60 10
0-16 =32
16-60 32
32

Sor
SERIES

BLYTHE
BOBTAIL

BODORUMPE,

BOEL
BOHNLY
BOHNSACK
BOETTCHER

BOGAN
BOLTUS

BON
BOND

BONDURANT

BONEEK

BONILLA
BONITA

BORACHO
BORDEAUX

BORKY

BORO
BORREGO

BoRUP
BORVANT
BOSLER

BOSTWICK L,GR-L,FSL,
ST-L
BOTTINEAU

BOULDER

BOTTLE

BOWBAC

BOWBELLS

BowOISH

BOWDLE

BOWEN

BOX ELDER L
cL.

BOXWELL

BOYD

BOYSAG FSi,
GR=1 SESE
SL

BOYLE

BOYSEN

BOZEMAN

BRAD
‘BRADSHAW
BRAMER
BRANDENBURG

BRANTFORD
BRAZITO

REECE
BRENDA

BRESSER st
Ls

DEPTH
INCHES

ont
11-36
0-2
2-26
0-36

9-60

4-29
9-12
12-24
0-3
3-12

0-8
4-17
9-12
12-60

o-34
31-60
o-10
0-18
18-60
nw
4-32

0-6

10-60
o-u
u-10

37
+32
-10
10
+28
+20

sor DEPTH
SERIES INCHES

BRIBUTTE
BRIDGE

BRIDGER

BRIDGEPORT
BRIDGET

BRIDGEWATER
BRIGCSDALE SL,FSt.

L, cL
BRINKERT
BRIOS SL,LS
L
BROAD
BROAD CANYON GR-L,CB-L

ST-L,GRV-L

BROADHEAD L

BROADHURST
BROADMOOR

BROCKO

BROCKWAY

BROLLIAR

BROOKINGS
BROOMPIELD

BROSS
BROWNFIELD

BROWWLEE
BROWNRIGG
BROWNSTO

BRUSSETT

BRYANT
BRYCAN
BUCHHOUSE
BUCKLON

BUCKLEBAR

BUDMAYR

BUELL
BUEWA VISTA

BUFF INGTON
BUFFMEYER

BUFORD

BLETON
BUICK

BULLION

BULLNEL,

UNDO

BUNDYMAN

BURGESS

0-3
3-12

ont?
12-37
37-62
0-23
23-72
9-18
a2
2-25
25-60
0-5
5-15
18-28
28-60

18-35

30-56

6-25,
0-9
9-30



Appendix A—Continued

SOIL
SERIES

MERCBS CBKE GRY
MACAR

MACFARLANE,

MACK

MaDDOCK
MAGNUS
MACKEN
vADDOCK
MADUREZ
MAGGTN
MAGINNIS
MAGNA

MaGOTSU
MAIDEN

MAITLAND
MAJADA
MAKOTI
MALJAMAR

MALPOSA
MALSTROM

MANASSA
MANBURN

MANDAN
MANDERFIELD = L
a

MANPRIED
MANKATTEN

MANILA

MANNING
MANSKER

MANTER

MANVEL
MANT2.
MANWOOD
MANZANO
MANZANOLA

MAPLE MOUNTAIN
MARCETTA

MARCIAL
MARIAS
MARICOPA
MARTPO
MARMARTH
MARRIOTT

MARSELL

MARSHDALE

MARTINSDALE

DEPTH

INCHES

STV- 0-12
STL 0-12

0-38
38-62
0-18

4-18
18-36
36-60
0-60
0-60

0-10
10-22
22-60
0-3
3-36
O-8
4-16
0-70
0-17
0-6
6-13
13-36

0-7

0-7
7-14
0-29
29-47
0-18
0-16
16-20
0-60
0-9
9-21
21-29
29-60

30-60

10-33
33-70
0-52
0-74
0-26
26-60
0-34
34-60
0-7
7-35
0-22
22-61
0-10
10-33
33-56
0-30
30-60
0-6
6-14
14-66

K

37
243
232
37
+10
+10
210
+20
+28
228
210
7
17
228
17
+20
232
+37
+32
+28
+28
224
128
224
237
228
+28
+28
+24
“17
+32
+43
“47
228
17
+28
239
210
+10
+32
143
224
+20
+10
+32
220
24
215
+20
43
:37
143
228
a7
+28
228
-18
115
+15
37
43
:37
243
+55,

SOIL
SERIES

MARTINEZ
MARTINI
MARVAN
MARY ELLEN
MARYSLAND

MASCHETAH
MATCHER

MATHERS

MATHIS
MAUGHAN

MAUKEY

MAURICE

MAWER
MAX

MAXVILLE
MAY DAY
MAYPTELD
MAYFLOWER

MAYLAND

MAYOWORTH

MAYSDORF

MCALLISTER

MCBETH
HCCAFFERY
MCCLAVE

ccooK
MCCORMICK

MccoRT

MCDONALD

MCDONALDSVILLE
MCFADDIN

NCGAFFEY
MCGINTY

MCILWAINE

MCINTYRE

MCKENZIE
MCKINNEY

MCMURDIE

MCNARY

8

MCPAUL
MCPHIE

MCQUARRIE

MCRAE

MCVICKERS FSL
VFSL

19-60

14-33
33-58
o-4

4-56

0-12
12-60

49

SOIL
SERIES

MEAD
MEADIN
MEANDER
MEDANO
MEETEETSE
MELLENTHIN
MELLAR
MELOCHE

MELVILLE

MENDENHALL
MENDON
MENEFEE
MENOKEN
MERDEN
MEREDITH
MERGEL
MERNA
MERINO
MESA
MESCAL
MESCALERO
MESITA

MESPUN
METIGOSHE

METRE
MICHELBON
MIDDLE
MIDDLEWOOD
MIDESSA
MIDNIGHT

MIDWAY
MIKESELL

MILL
MILLARD L
GR-L

MILLBORO
MILLBURNE

MILLERLAKE

NILLETT GR-SL,GR-LS.
GR-L

MILL HOLLOW

MILLIKEN

MILLVILLE

MILREN

MINBRES

MINATARE
MINCHEY

MINE

DEPTH
INCHES

0-6
6-60

0-12
12-60
0-3
3-24
24-60
0-15
0-60
0-9
9-56
0-5
5-23
23-30
30-60
0-10
10-60
0-7
7-28
28-48
o-1H
0-30

0-30

42-56

0-20
20-48
0-6
6-60

28

+2
10
243
49
243,
17
+85
+32
+37
+28
-32
+28
+20
:37
+28
+32
+32
237
+32
243

.10

132

+10
10

Fee

eee


Section 7.0
GLOSSARY

Arid: Regions or climates that lack sufficient moisture for crop production without irrigation. The limits of precipitation vary
considerably according to temperature conditions, with an upper annual limit for cool regions of ten inches or less and for
tropical regions as much as fifteen to twenty inches.

Brush: A growth of shrubs or small trees.

Bunchgrass: A grass that does not have rhizomes or stolons and forms a bunch of tuft.

Canopy: The cover of leaves and branches formed by the tops or crowns of plants as viewed from above the cover.

Clean Tillage: Cultivation of a field so as to cover all plant residues and to prevent the growth of all vegetation except the
particular crop desired.

Contour: 1. An imaginary line on the surface of the earth connecting points of the same elevation; 2. A line drawn on a map
connecting points of the same elevation.

Contour Farming: Conducting field operations, such as plowing, planting, cultivating, and harvesting, on the contour.

Contour Furrows: Furrows plowed approximately on the contour on pasture and rangeland to prevent runoff and increase
infiltration. Also, furrows laid out approximately on the contour for irrigation purposes.

Contour Stripcropping: Layout of crops in comparatively narrow strips in which the farming operations are performed
approximately on the contour. Usually strips of grass, close-growing crops, or fallow are alternated with those in cultivated
crops.

Contour Stripping: The removal of overburden and mining from a coal seam that outcrops or approaches the surface at
approximately the same elevation. In steep or mountainous areas.

Cover (Ground Cover): Vegetation or other material providing protection to the soil.

Cover Crop: A close-growing crop grown primarily for the purpose of protecting and improving soil between periods of regular
crop production or between trees and vines in orchards and vineyards.

Cropland: Land used primarily for the production of adapted, cultivated, close-growing fruit or nut crops for harvest, alone or in
association with sod crops.

Crop Residue: The portion of a plant or crop left in the field after harvest.

Crop Residue Management: Use of that portion of the plant or crop left in the field after harvest for protection or improvement of
the soil.

Deposition: The accumulation of material dropped because of a slackening movement of the transporting agent (water or wind).

Diversion Terrace: Diversions, which differ from terraces in that they consist of individually designed channels across a
hillside; may be used to protect bottomland from hillside runoff or may be needed above a terrace system for protection
against runoff from an unterraced area; may also divert water out of active gullies, protect farm buildings from runoff,
reduce the number of waterways, and sometimes used in connection with stripcropping to shorten the length of slope so that
the strips can effectively control erosion. See terrace.

Duff: The more or less firm organic layer on top of mineral soil, consisting of fallen vegetative matter in the process of
decomposition, including everything from pure humus below to the litter on the surface; a general, non-specific term.

Erosion: 1. The wearing away of the land surface by running water, wind, ice, or other geologic agents, including such
processes as gravitational creep; 2, Detachment and movement of soil or rock fragments by water, wind, ice, or gravity.
The following terms are used to describe different types of water erosion.

Gross Erosion: The total amount of water erosion occurring on a site. Includes sheet and rill and gulley erosion.

Permeability Soil: The quality of a soil horizon that enables water or air to move through it. The permeability of a soil may be
limited by the presence of one nearly impermeable horizon even though the others are permeable.

Pitting: Making shallow pits of suitable capacity and distribution to retain water from rainfall or snowmelt on rangeland or
pasture.

Plant Residue: See crop residue, mulch, soil organic matter.

Reclamation: The process of reconverting disturbed lands to their former uses or other productive uses.

Runoff (Hydraulics); That portion of the precipitation on a drainage area that is discharged from the area in stream channels.

Sediment: Solid material, both mineral and organic, that is in suspension, is being transported, or has been moved from its site or
origin by air, water, gravity, or ice and has come to rest on the earth’s surface either above or below sea level.

Slope: The degree of deviation of a surface from horizontal, measured in a numerical ratio, percent, or degrees. Expressed as a
ratio or percentage, the first number is the vertical distance (rise) and the second is the horizontal distance (run), as 2:1 or
200 percent. Expressed in degrees, it is the angle of the slope from the horizontal plane with a 90% slope being vertical
(maximum) and 45% being a 1:1 slope.

Slope Characteristics: Slopes may be characterized as concave (decrease in steepness in lower portion), uniform, or convex
(increase in steepness at base). Erosion is strongly affected by shape, ranked in order of increasing erodibility from concave
to uniform to convex.

Soil Erosion: The detachment and movement of soil from the land surface by wind or water.

24


3.4 COVER OR CROP MANAGEMENT FACTOR
“er

The factor ‘*C’’ values relate to the effects various
ground covers have on erosion. The basic soil loss is the rate
at which the soil would erode if the field were continuously
clean tilled. The ‘‘C’’ factor in the USLE indicates the
percentage of this potential soil loss that would occur if the
surface were partially protected by some particular combina-
tion of cover and management (Holeman, et al. 1975).

In order to apply the factor **C’’ to land uses other than
cropland, three zones of influence are considered. These
three influence zones are shown in Tables 3 and 4 and can be
grouped into general categories of canopy cover, weeds or
undecayed organic residue, and sod or decaying organic
matter. Canopy cover, as the name implies, is an overhang-
ing protective cover standing sufficiently above other vegeta-
tive growth as to be readily distinguishable and to provide
shielding from direct rainfall inpingement. Weeds or unde-
cayed organic residue is the vegetative growth, either viable
or dead but undecayed, that provides some protection from
rainfall impact, but does not serve to significantly retard
runoff by holding the water that reaches the surface. Sod or
decaying organic matter is that material directly on the soil
surface and serves to retard rainfall runoff by holding the
water.

Vegetative residue in contact with the soil surface is
extremely effective against erosion (Mannering, 1967). A
thick layer of organic litter is often present under woodland
situations. Therefore, very little erosion occurs unless the
soil has been disturbed or exposed. Croplands often erode

severely because of the soil disturbance necessary for weed
control, seedbed preparation, and planting operations.
Likewise, surface mined areas are generally bare for a period
of time from pre-winter (i.e., before surface freezing) re-
moval of topsoil until mining and from final grading to the
mulching and seeding of regraded and topsoiled areas.

Reclamation plans are ordinarily directed toward re-
habilitating affected lands to a designated land use. Tables 2,
3, and 4 provide guidance for determining **C’’ factors for
cropland, pastureland, rangeland, and woodland.

Refer to Table 5 to determine factor ‘*C’’ for various
rates of mulch. It should be noted that two tons of straw
mulch per acre provides approximately the same ‘‘C’’ factor
as 44% ground cover of grass with no appreciable canopy
cover. The mulch material, however, is only temporary and
begins to lose its effectiveness soon after application. The
durability of the mulch depends on the amount of material
applied, quality of material, and method of application.
Various kinds of organic mulch decay at different rates.
Also, the method of application is important due to the high
wind velocities occurring in parts of the Interior Western
United States. Ordinarily, the higher the quantity of mulch
applied, the longer it lasts and the more protection the mulch
provides against erosion; however, if too much is applied, it
has a smothering effect on grass seedlings.

If the post mining land use is recreation or wildlife
habitat, the “*C’’ factor will be selected from the chart that
best describes the vegetative condition of the area.

Table 2. Crop Management Factor ‘‘C’’

Cropland

Residue at “C’* Values/State

Crop Rotations Planting AZ CO MT NM _ ND _ SD WY _ UT
Ibs/Ac

Winter wheat-fallow 0 55.47 43 56 43841894
or 0-500 360.3600 3137 3637383
Spring wheat-fallow 500-1000 2200 2100 21 2723827222
1000-1500 A4 1S AB AS 14 17 (13.16
Continuous spring 0 3300 340 303584843388
or 0-500 300.310.2424 27) .27 si
Winter wheat- 500-100 AT 18 IS 182002001817
occasional fallow 1000-1500 AZ 13 UL BS ASA

For cropping systems not included in this chart, additional information can be obtained through the local Soil Conservation

Service office (see Appendix B).


Appendix A—Continued

SOIL
SERIES

‘TRIK
TROJAN +

‘TROOK

‘TROUT CREEK

‘TROUTDALE

‘TROUTVILLE

‘TRUCKTON

‘TRUEFISSURE
TRULL

TRULON

TRUMP

TSCHICOMA

TUBAC GR-SL,SL

E,GR-L

‘TUCSON L

TUCUMCART
‘TUFFIT

‘TULAROSA
TULLOCK

TURK
‘TURKEYSPRINGS

TURLEY
TURNER

‘TURRAH

‘TURNERVILLE
TURNEY

TURRET

TURSON

TUSLER
TUTRELL
‘TWILIGHT
TWIN CREEK
‘THO DOT
‘THOTOP
TYRONE
UBAR

UCOLA

UFFENS
UINTA

ULa

ULEN

DEPTH
THCHES

0-60
o-tt
11-50
0-7
7-12
12-27
27-60
0-8
8-24
24-30
0-9
9-28
24-32
0-3
3-60

4g-52

14-31
31-60
ety
o-14
14-36
36-85
0-60

412
12-29
29-48
0-60
0-28
0-7
7-24
0-45
0-60

1-26
26-30
30-60
0-4
4-22
22-38
38-42
42-60
0-3
3-60
o-2t
21-48

9-18
18-24
24-60
0-10

10-24
24-60
0-12

12-26

0-7
7-30
30-66
7-60
0-7

27-60

12-60

17-37
0-60

sor
SERIES

ULM
uLRIC
ULYSSES
UNAWEEP
UNCOMPAGRE
UNSON
UPSATA
UPSON

UPTON
URACCA

USHAR

UTABA

UTALINE

ure

urica

UVADA

VABEM

ADO

VALE

VALENCIA

VALENCIA
saline-alkali

VALENT

VALENTINE
VALLE

VALLEONO

VALLERS
VALMONT

VAMER
VANAJO
VANANDA
VANDA
VANET
VANG
VANOCKER
VAN WAGONER
VASQUEZ
VASTINE
VEBAR
VECONT
VEGA
VEKOL
VELA
VENABLE
VENEZIA
VENLO

VERHALEN

DEPTH
INCHES

A-20

0-9
9-60
0-9
g-2t
21-42

0-10
10-60
o-14
14-60
0-3
3-60
o-14,
14-60
0-33
33-36
0-13
om
4-13
19-17
17-60
0-9
0-9
9-31
31-60
0-10
10-46
46-60
on
4-60

8-36
36-60

6-19
19-72
0-8
S48
on
4-16
0-60
0-60
0-26
26-60
0-28
26-60
Onn
4-60
0-72
0-28
28-60
0-9
9-24
24-30
30-60
0-60
on
4-26
24-60
0-46
0-60
0-60
0-60
o-14
14-21
21-32
0-25
28-60

0-20
o-11
11-24
24-60
0-30
30-60
0-32
o-1y
yaad
44-60
0-15,
15-52
0-3
3-33
33-60
0-60
0-23
23-60
0-2
2-10
0-13
13-60
0-60

K

32
37
+32
224
228
+32
15
115
224
224
+28
+32
17
-10
17
+15
228
“17
215,
210
210
232
228
37
210
224
232
+43
-10
+10
224
232
228
128
7
-10
255.
137
232
243
“17
+32
7
:37
47
37
215
215
+10
249
228
237
+32
+32
10
232
+26
+32
10
+28
+28
12
+24
224
+28
+32
228
+10
224
224
+10
+10
+10
+28
210
220
1:37
224
132

SOIL
SERIES

VERMEJO
VERNAL

VERNON
VETAL
VEYO
VIBLE
VIBORG
VICTOR
VIDA
VIENNA

VIKING
VILLA GROVE

VILLY
VINGO

vINT LFS, LS
FSL.

VINTON

VIRKULA

VOLGA

VOLIN
VONA

VULCAN

WABEK

WAGES

WAHPETON
WAITS

WAKONDA
WALCOTT

WALDEN

WALDROUP

WALKE
WALL

WALLIS
WALLROCK
WALLSON
WALSH

WALSTEAD

WALTERS
WALUM

WANBLEE
WANETTA

WANN
WARSING

WASA
WASHOE
WATERINO
WATERS

WATROUS
WAUBAY

DEPTH
INCHES

0-60
Onn
4-24
2-60
o-21,

0-19
0-16
18-60

0-26
26-36
36-60
0-5
5-60

0-60
0-8
8-34

Bub
44-60

0-18
18-48
48-80
0-12
0-12
12-60
0-60

0-8
8-30
30-60
0-8
8-16
16-36
36-60
0-5
5-60
on
4-14,
14-60
0-60
0-17
17-23
23-60

8-29
o-24

37

+32

22
+20
+10
+32
+32
37
+28
10

+28
215
+28

-32
37
+32
+20
132
+28
+28

s-4

3-2


APPENDIX B

The following are Soil Conservation Service State Office
Locations of the U.S. Interior West:

Soil Conservation Service
P O. Box 17107
Denver, Colorado 80217

Soil Conservation Service
3008 Federal Bidg.

230 No. First Ave.
Phoenix, Arizona 85025

Soil Conservation Service

517 Gold Ave. S.W.

Rm 3301 Box 2007
Albuquerque, New Mexico 87103

Soil Conservation Service
Rm 4012 Federal Bldg.
125 So. State Street

Salt Lake City, Utah 84138

Soil Conservation Service
Federal Bldg. Rm 270
Rosser Ave. & Third St.

P. O. Box 1458

Bismarck, North Dakota 58501

Soil Conservation Service
239 Wisconsin Ave. S.W.
Huron, South Dakota 57350

Soil Conservation Service
Federal Bldg.

P.O. 970

Bozeman, Montana 59715

Soil Conservation Service
Federal Bldg.

100 E. “‘B”’ St.

P. O. Box 2440

Casper, Wyoming 82601

B-]


3.5 THE EROSION CONTROL PRACTICE FAC-
TOR "*P”’

In conventional application of the USLE, the erosion
control practice factor *‘P’’ relates to erosion control on
cropland fields. This would include contour tillage, and
contour stripcropping. Typically, if erosion is being calcu-
lated on land uses other than cropland, the factor ‘*P"’ will be
1.0. The exception is where physical manipulation of the
land is used such as contour pitting, gouging, or furrowing
during a reclamation process.

When sloping soil is disturbed and exposed to erosive
rains, the protection offered by mulch, sparse grass stands, or
close-growing crops can be supported by practices that will
slow the runoff water and thus reduce the amount of soil it
can carry. The supporting practices include contour tillage
and stripcropping on the contour. The factor **P"’ in the
erosion equation is the ratio of soil loss with the supporting
practice to the soil loss up-and-downhill culture. Improved
tillage practices, fertility treatments, and greater quantities of
residues left on the area contribute materially to erosion
control and frequently provide the major control in a field.
However, these are considered conservation cropping and
management practices, and the benefits derived from them
are included in the factor **C** (Wischmeier, et al. 1965).

Tillage and planting operations performed on the con-
tour are very effective in reducing erosion from storms of low
to moderate intensity. Storms of high intensity however are
common to many areas of the Interior Western United States,
and contouring provides little protection against such high
intensity rainstorms.

Terracing in combination with contouring is more effec-
tive as an erosion control practice than just contouring and
stripcropping. The beneficial effects of terracing is reflected

in the factor ‘‘LS*" since the length of slope is directly
affected by terracing. Off-field sediment load is affected by
terracing from both the shorter slope lengths and sediment
storage in the terrace channels. Sediment yield is further
discussed in Section 5.

Contour furrowing and pitting is being evaluated for use
in reclamation plans. These practices demonstrate benefits
from moisture conservation, as well as erosion control (Dol-
lhopf, et al. 1976). Table 6 gives relative guidance on factor
““PTM for erosion control practices related to contouring.

Figure 6: Reclaimed surface mined land can sometimes be

utilized for croplands. Climate often restricts the post-
mining land use to grassland.

Table 6. Determining Factor **P"’
Contour 3/
Land Slope Contour 2/ ditches
% Contouring 1/ Furrows or Pits (wide spacing)

2.007 0.50 0.25 3/

8.0-12 0.60 0.30 3/
13.0-18 0.80 0.40 3/
19.0-24 0.90 0.45 3/
25.0-30 1.0 0.65 3

1/ Topsoil spreading, tillage, and seeding on the contour. Contour Limits—2 percent 400 feet, 8 percent 200 feet, 10 percent
100 feet, 14-30 percent 60 feet. The effectiveness of contouring beyond these limits is speculative.

2/ Estimating values for surface manipulation of reclaimed land disturbed by surface mining. Furrows or pits installed on the
contour. Spacing between furrows 40-60 inches with a minimum 6 inch depth. Pits equal or exceed 12 inch width 36 inch
length and 6 inch depth. Pit spacing is dependent on pit size, but generally the pits should occupy 50% of the surface area

3/ Factor values for this practice are not established