AN ABSTRACT OF THE THESIS OF
JOSIAH AKINLAYO AKINSANMI for the degree of Doctor of
Philosophy in Agricultural and Resource Economics presented
on August 22, 1995.
Title: AN EVALUATION OF THE ECONOMIC
IMPACTS OF REDUCING SOIL EROSION AND GROUNDWATER POLLUTION
IN NON-IRRIGATED FARMING SYSTEMS OF NORTHEASTERN OREGON.
Redacted for Privacy
Abstract approved:
Increases in food demand, favorable commodity markets
and drive towards increasing productivity at a greater
economic efficiency have accelerated negative agricultural
externalities, particularly erosion and water quality.
The
potential impact of these externalities on environmental
quality and human health prompted an examination of current
and potential production strategies on four important
dryf armed soil associations--Walla Walla, Pilot Rock,
Ritzville and Athena Soils--in the Umatilla County area of
Oregon.
The objective was to evaluate the economic and
environmental costs of reducing soil erosion and leaching
through implementing strategies that minimize soil loss and
(or) nitrate leaching or offer somt trade-off S between the
pollutants.
Four models--the Universal Soil Loss Equation (USLE),
Micro-computer Budgeting Management System (MBMS), Nitrate
Leaching and Economic Analysis Program (NLEAP) and MultiObjective Linear programming (MOP)--were employed to
accomplish the study objectives.
The results revealed that production strategies that
focused on reducing only one pollutant generally exacerbated
the other.
The mixed objective strategies achieved a
simultaneous reduction in both soil erosion and leaching.
Once either pollutant had been substantially reduced,
further reductions certainly increased the rate of
generation of the other.
On Walla Walla soil, the most cost effective erosion
reducing strategies for winter wheat production included
those that involved use of chisel plow for primary tillage
under standard conservation practice.
Large leachate
reductions in winter wheat production were possible by using
strategies that involved use of disk plowing for primary
tilIage followed by chisel plow for secondary tillage and a
split fertilizer application.
On Pilot Rock soil, production process that involved
use of sweep plow for primary tillage with a one time spring
fertilizer application and (or) with more farm acreage in
spring barley production were least cost strategies that
reduced leaching considerably.
Soil loss and leaching rates on Ritzville soils were
very low, indicating that this soil may not be subject to
soil erosion or leaching problems.
For Athena soils, least cost strategies that greatly
reduced erosion involved use of chisel or disk plow under
conservation practices.
No strategy was identified to
reduce leaching significantly.
An Evaluation of the Economic Impacts of Reducing Soil
Erosion and Groundwater Pollution in Non-Irrigated Farming
Systems of Northeastern Oregon
by
Josiah Akinlayo Akinsanmi
A THESIS
Submitted to
Oregon State University
in partial fulfillment of
the requirement for the
degree of
Doctor of Philosophy
Completed August 22, 1995
Commencement June, 1996
Doctor of Philosophy thesis of Josiah Akinlayo Akinsanini
presented on August 22, 1995
APPROVED:
Redacted for Privacy
essor, re resenting Agricultural and Resource
Redacted for Privacy
Head of Depa ent of Agricultural and Resource Economics
Redacted for Privacy
Dean of
I understand that my thesis will become part of the
permanent collection of Oregon State University libraries.
My Signature below authorizes release of my thesis to any
reader upon request.
Redacted for Privacy
Josiah Akinlayo Akinsanmni, Author
my degree programs in the US.
Same thanks and appreciation
go to my Wife and Children for bearing with me during the
long haul.
I am very grateful to my father for putting me
on a very good foundation and showing me the right forward
step, before he died, towards this feat.
to GOD for making everything possible.
Above all, thanks
You are WONDERFUL!
TABLE OF CONTENTS
Chapter
Page
INTRODUCTION
Overview of Problem
II
1
Objectives of the Study
13
Dissertation Organization
14
ECONOMIC THEORY
16
Externalities
16
Solutions to Externality
19
Theoretical Solution
Coasian Solution
Policy/Regulatory Solutions
Input Tax
Pollution Tax
Ambient Standards
Controls
Trade-off between Soil Erosion
and Nitrate Leachate
III
1
OVERVIEW OF STUDY AREA AND FARMING PRACTICES
Description of Study Area
19
20
24
24
28
30
33
36
40
40
Climate
Soil Depth Across Agronomic Zones
42
45
Wheat Production in Umatilla County
47
Management of Soils for Crop Production
48
Tillage Systems
Conventional Tillage
Conservation Tillage
Fallowing
Fertilizer Usage in Umatilla County
49
50
51
53
54
TABLE OF CONTENTS (Continued)
Page
Chapter
IV
V
MODEL REVIEW
56
Soil Loss Estimation
Link between T-Value, Present Value Yield
Losses and Intergenerational Concerns
T-Value
Yield-Soil Depth Relationships
Technological Progress and Soil Erosion
57
Cost-Return Budgeting Using MBMS
71
Estimating Nitrate-Nitrogen Leaching
74
Model Validation
78
Multiple Objective Programming (MOP) Model
79
METHODOLOGY AND DATA SPECIFICATION
59
62
63
69
83
Sources of Information
85
Tillage Systems and Management Practices
85
Alternative Production Strategies
95
Soil Loss Estimation--The Universal Soil
Loss Equation (LISLE)
R Factor
L5 Factor
The C Factor
K and P Factors
Conversion of Soil Loss to Yield Loss
Winter Wheat
Spring Barley
Pea
Budgeting
99
99
100
102
109
109
112
113
114
115
Nitrate Leached Estimation--The Nitrate
Leaching and Economic Analysis Package
(NLEAP)
117
Multi-Objective Programming
124
TABLE OF CONTENTS (Continued)
Page
Chapter
VI
VII
RESULTS AND ANALYSES
129
Results of the USLE Model
130
T-Values
Cost of Soil Erosion
Results of the Budgeting Program
135
137
140
Results of the NLEAP Program
155
Results of the MOP
170
Walla Walla Soil
Pilot Rock Soil
Ritzville Soil
Athena Soil
172
179
184
188
SUMMARY, COMMENTS AND LIMITATIONS
General Comments
Adoption of Soil Conservation Strategies
Adoption of Leaching Control Techniques
192
200
201
202
Benefits of this Research
203
Limitations of Research
204
BIBLIOGRAPHY
207
APPENDICES
222
Appendix A
Appendix B
Appendix C
Appendix D
Precipitation, Temperature
and Pan Evaporation Data
Universal Soil Loss Equation
Factors
Soil Loss (tons/acre), Cost
of Erosion Damage, Optimal
Level of Crop Production and
Strategies
Resource Information and
Budget Details
223
230
238
271
LIST OF FIGURES
Figure
Page
1.1
Nitrate Pathway and Metabolism
10
2.1
Demand Curve for an Input of Production
26
2.2
Demand Curve for Nitrogen Fertilizer
27
2.3
Imposition of Tax on Externality
29
2.4
Limitation on the Use of an Input
34
3.1
Oregon County Map Showing Location of
Umatilla County
43
Map of Umatilla County showing the Four
Major Land Resources (MLRA)
44
4.1
Soil Erosion Processes
60
5.1
Schematic Diagram of Linkages between Models...
84
5.2
"C" Factors for Fallow-Winter Wheat,
Columbia Plateau, 15-25% Winter Vegetation
3.2
by Dec.
5.3
5.4
6.1
6.2
6.3
6.4
1.
106
"C" Factors for Fallow-Winter Wheat,
Columbia Plateau, 50% Winter Vegetation
by December 1
107
"C" Factors for Fallow-spring Grain, Less
than 15% Green Vegetation by Dec. 1
108
Iso-Abatement Cost Curves Describing the
Trade-of fs between Soil Loss from Erosion
and Nitrate-N Leached on Walla Walla Soil
175
Iso-Abatement Cost Curves Describing the
Trade-of fs between Soil Loss from Erosion
and Nitrate-N Leached on Pilot Rock Soil
182
Iso-Abatement Cost Curves Describing the
Trade-off s between Soil Loss from Erosion
and Nitrate-N Leached on Ritzville Soil
187
Iso-Abatement Cost Curves Describing the
Trade-of fs between Soil Loss from Erosion
and Nitrate-N Leached on Athena Soil
191
LIST OF TABLES
Table
Page
1.1
Estimates of Disposition for Nitrogen
4.1
Estimated Soil Tolerance to Soil Loss
According to Topsoil Depth in Columbia
Plateau, Oregon
64
4.2
Effect of Topsoil Thickness on Wheat Yields
65
4.3
Statistical Estimates of the Yield-Soil Depth
Relation for the Pacific Northwest
68
5.1
Agricultural Land Inventory
86
5.2a
Summer Fallow-Winter Wheat, Standard Tillage
Options--Walla Walla Soil
88
Summer Fallow-Spring Barley, Standard Tillage
Options--walla Walla Soil
90
Summer Fallow-Winter Wheat, Standard Tillage
Options--Ritzville and Pilot Rock Soils
91
Summer Fallow-Spring Barley, Standard Tillage
Options--Ritzville and Pilot Rock Soils
92
Winter Wheat-Green Pea, Standard Tillage
Options--Athena Soil
93
Fertilizer Timing-Application Rates on Summer
Fallow-Winter Wheat, all Tillage Systems-Walla Walla Soil
96
Fertilizer Timing-Application Rates on Summer
Fallow-Winter Wheat, all Tillage Systems-Pilot Rock and Ritzville Soils
96
Fertilizer Timing-Application Rates on Summer
Fallow-Spring Barley, all Tillage Systems-Ritzville, Pilot Rock and Walla Walla Soils
97
Fertilizer Timing-Application Rates Winter
Wheat-Green Pea Rotation, all Tillage Systems
--Athena Soil
97
5.2b
5.3a
5.3b
5.4
5.5a
5.5b
5.Sc
5.5d
5.6
Annual Precipitation (Pr), and Associated
Erosivity (R) Factors for the Columbia
Plateau, 1982-1991
7
100
LIST OF TABLES (Continued)
Table
Page
5.7
LS Values used in the Analysis
102
5.8
Estimated Residue Production
103
5.9
Estimated Residue Retention for Common
Tillage Operations
104
Conversion--Percent Cover to Pounds Residue
for Wheat, Barley, Oats and Peas
105
5.11
USLE--K, LS, C, P--Factors
110
5.l2a
Soil Test Data for Athena and Pilot Rock
Soils
119
Soil Test Data for Ritzville and Walla Walla
Soils
120
Soil Test Data, Summer Fallow-Spring Barley-Pilot Rock, Ritzville, Walla Walla Soils
120
Assumptions made for the NLEAP Analysis, by
Soil Type
125
Estimated Average Soil Loss (Tons/ac/yr), Using
USLE--Standard, Divided Slope and Strip Crop
Practices on (SF-WW) and (SF-SB) Rotations-Walla Walla Soil
131
Estimated Average Soil Loss (Tons/ac/yr), Using
USLE--Standard, Divided Slope and Strip Crop
Practices on (SF-WW) and (SF-SB) Rotations-Pilot Rock Soil
132
Estimated Average Soil Loss (Tons/ac/yr)1 Using
USLE--Standard, Divided Slope and Strip Crop
Practices on (SF-WW) and (SF-SB) Rotations-Ritzville Soil
132
Estimated Average Soil Loss (Tons/ac/yr), Using
USLE--Standard, Divided Slope and Strip Crop
Practices on (WW-GP) Rotation--Athena Soil
133
Estimated Value of Soil Loss ($/ac/yr) for
Standard, Divided Slope and Strip Crop
Practices on (SF-WW) and (SF-SB) Rotations-Walla Walla Soil
138
5.10
5.l2b
5.12c
5.13
6.1
6.2
6.3
6.4
6.5
LIST OF TABLES (Continued)
Table
6.6
6.7
6.8
6.9a
6.9b
6.lOa
6.lOb
6.11a
6.11b
6.12a
Page
Estimated Value of Soil Loss ($/ac/yr) for
Standard, Divided Slope and Strip Crop
Practices on (SF-WW) and (SF-SB) Rotations-Pilot Rock Soil
139
Estimated
Standard,
Practices
Ritzville
139
Value of Soil Loss ($/ac/yr) for
Divided Slope and Strip Crop
on (SF-WW) and (SF-SB) Rotations-Soil
Estimated Value of Soil Loss ($/ac/yr) for
Standard, Divided Slope and Strip Crop
Practices on (WW-GP) Rotation--Athena Soil
140
Budget Summary for Tillage Systems under
Standard, Divided Slope and Strip Crop
Practices in (SF-WW) Crop Rotation-Walla Walla Soil
141
Budget Summary for Tillage Systems under
Standard, Divided Slope and Strip Crop
Practices in (SF-SB) Crop Rotation-Walla Walla Soil
144
Budget Summary for Tillage Systems under
Standard, Divided Slope and Strip Crop
Practices in (SF-WW) Crop Rotation-Pilot Rock Soil
146
Budget Summary for Tillage Systems under
Standard, Divided Slope and Strip Crop
Practices in (SF-SB) Crop Rotation-Pilot Rock Soil
148
Budget Summary for Tillage Systems under
Standard, Divided Slope and Strip Crop
Practices in (SF-WW) Crop Rotation-Ritzville Soil
149
Budget Summary for Tillage Systems under
Standard, Divided Slope and Strip Crop
Practices in (SF-SB) Crop Rotation-Ritzville Soil
151
Budget Summary for Tillage Systems under
Standard, Divided Slope and Strip Crop
Practices.
Winter Wheat after Green Pea-Athena Soil
152
LIST OF TABLES (Continued)
Table
6.12b
6. 13a
6. 13b
6.13c
6.l4a
6.14b
6. 15a
6. 15b
6.16
6.17
6.18
Page
Budget Summary for Tillage Systems under
Standard, Divided Slope and Strip Crop
Practices. Green Pea after Winter Wheat-Athena Soil
153
Estimated Nitrate-N Leached (lbs/acre),
Wheat Production Year--3.5 Percent Slope,
Walla Walla Soil
157
Estimated Nitrate-N Leached (lbs/acre),
Wheat Production Year--9.5 Percent Slope,
Walla Walla Soil
158
Estimated Nitrate-N Leached (lbs/acre),
Fallow Year--3.5 or 9.5 Percent Slope,
Walla Walla Soil
159
Estimated Nitrate-N Leached (lbs/acre),
Barley Production Year--3.5 Percent Slope,
Walla Walla Soil
160
Estimated Nitrate-N Leached (lbs/acre),
Barley Production Year--9.5 Percent Slope,
Walla Walla Soil
161
Estimated Nitrate-N Leached (lbs/acre),
Wheat Production Year--3.,5 or 9.5 Percent
Slope, Pilot Rock Soil
162
Estimated Nitrate-N Leached (lbs/acre),
Fallow Year--3.5 or 9.5 Percent Slope,
Pilot Rock Soil
163
Estimated Nitrate-N Leached (lbs/acre),
Barley Production Year--3.5 or 9.5 Percent
Slope, Pilot Rock Soil
164
Estimated Nitrate-N Leached (lbs/acre),
Wheat Production Year--3.5 or 9.5 Percent
Slope, Ritzville Soil
165
Estimated Nitrate-N Leached (lbs/acre),
Barley Production Year--3.5 or 9.5 Percent
Slope, Ritzville Soil
166
LIST OF TABLES (Continued)
Table
6.19a
Page
Estimated Nitrate-N Leached (lbs/acre),
Winter Wheat after Green Pea Production-3.5 or 9.5 Percent Slope, Athena Soil
167
Estimated Nitrate-N Leached (lbs/acre),
Green Pea after Winter Wheat Production-3.5 or 9.5 Percent Slope, Athena Soil
167
Multi-Objective Programming (MOP) Optimal
Solution, Walla Walla Soil
174
Multi-Objective Programming (MOP) Optimal
Solution, for Soil Loss Less than or Equal
to 3T-Value, Pilot Rock Soil
181
Multi-Objective Programming (MOP) Optimal
Solution, Ritzville Soil
186
Multi-Objective Programming (MOP) Optimal
Solution, Athena Soil
190
Implication of directing all Resources at
Reducing either Soil Loss or Leaching Rates
Generated in the Base Scenario
195
7.2a
Trade-of fs between Pollutants--Leachate
199
7.2b
Trade-of fs between Pollutants--Soil Loss
200
6.19b
6.20
6.21
6.22
6.23
7.1
LIST OF APPENDIX TABLES
Table
A.la
Page
Monthly Precipitation, Pendleton Weather
Station (inches)
223
Monthly Average Temperature (°F), Pendleton
Weather Station
223
Monthly Pan Evaporation, Pendleton Weather
Station (in hundredth of an inch)
224
Monthly Precipitation, Pilot Rock Weather
Station (inches)
225
Monthly Average Temperature (°F), Pilot Rock
Weather Station
225
Monthly Precipitation from Moro Weather
Station (inches)
226
Monthly Average Temperature (°F)--Moro
Weather Station
226
Monthly Pan Evaporation, Moro Weather Station
(in hundredth of an inch)
227
Monthly Precipitation from Pullman Weather
Station (inches)
228
Monthly Average Temperature (°F)--Pullman
Weather Station
228
Monthly Pan Evaporation, Pullman Weather
Station (in hundredth of an inch)
229
K-Factor for Pilot Rock, Ritzville and WallaWalla Soils of Umatilla County
230
LS Values for Areas affected by Frozen Soil
Including Uivatilla County, Oregon
231
Estimated Modifying Factors for "C" in the
USLE for Oregon
235
B.4
P (supporting conservation practice) factors
237
C.la
Estimated Soil Loss (Tons/ac/yr) Using USLE,
(SF-WW) and (SF-SB) Standard Practice--Walla
Walla Soil
238
A. lb
A.lc
A.2a
A.2b
A.3a
A.3b
A.3c
A.4a
A.4b
A.4c
B.l
B.2
B.3
LIST OF APPENDIX TABLES (Continued)
Table
C.lb
C.2a
C.2b
C.3a
C.3b
C.4a
C.4b
C.5a
C.5b
C.6a
C.6b
C.7a
Page
Estimated Cost of Soil Erosion ($/ac/yr),
(SF-WW) and (SF-SB)--Standard Practice-Walla Walla Soil
239
Estimated Soil Loss (Tons/ac/yr) Using USLE,
(SF-WW) and (SF-SB), Divided slope Practice-Walla Walla Soil
240
Estimated Cost of Soil Erosion ($/ac/yr) on
(SF-WW) and (SF-SB)--Divided Slope Practice-Walla Walla Soil
241
Estimated Soil Loss (Tons/ac/yr) Using USLE,
(SF-WW) and (SF-SB), Strip Cropping--Walla
Walla Soil
242
Estimated Cost of Soil Erosion ($/ac/yr)
(SF-WW) and (SF-SB) Strip Cropping Practice-Walla Walla Soil
243
Estimated Soil Loss (Toris/ac/yr) Using USLE,
(SF-WW) and (SF-SB) Standard Practice--Pilot
Rock Soil
244
Estimated Cost of Soil Erosion ($/ac/yr),
(SF-WW) and (SF-SB), Standard Practice-Pilot Rock Soil
245
Estimated Soil Loss (Tons/ac/yr) Using USLE,
(SF-Ww) and (SF-SB), Divided Slope Practice-Pilot Rock Soil
246
Estimated Cost of Soil Erosion ($/ac/yr)
(SF-WW) and (SF-SB), Divided Slope Practice-Pilot Rock Soil
247
Estimated Soil Loss (Tons/ac/yr) Using USLE,
(SF-WW) and (SF-SB), Strip Crop Practice-Pilot Rock Soil
248
Estimated Cost of Soil Erosion ($/ac/yr),
(SF-WW) and (SF-SB), Strip Crop Practice-Pilot Rock Soil
249
Estimated Soil Loss (Tons/ac/yr) Using USLE,
(SF-WW) and (SF-SB), Standard Practice-Ritzville Soil
250
LIST OF APPENDIX TABLES (Continued)
Table
C.7b
C.8a
Page
Estimated Cost of Soil Erosion ($/ac/yr),
(SF-Ww) and (SF-SB), Standard Practice-Ritzvjlle Soil
Estimated Soil Loss (Tons/ac/yr) Using USLE,
(SF-WW) and (SF-SB), Divided Slope Practice-Ritzvi].le Soil
C.8b
C.9a
C.9b
C.lOa
C.lOb
C.11a
C.11b
C.12a
C.12b
251
252
Estimated Cost of Soil Erosion ($/ac/yr),
(SF-WW) and (SF-SB), Divided Slope Practice-Ritzvi].le Soil
253
Estimated Soil Loss (Tons/ac/yr) Using USLE,
(SF-WW) and (SF-SB), Strip Crop Practice-Ritzville Soil
254
Estimated Cost of Soil Erosion ($/ac/yr),
(SF-Ww) and (SF-SB), Strip Crop Practice-Ritzvjlle Soil
255
Estimated Soil Loss (TOns/ac/yr) Using USLE,
(WW-GP), Standard Practice--Athena Soil
256
Estimated Cost of Soil Erosion ($/ac/yr),
(ww-GP), Standard Practice--Athena Soil
257
Estimated Soil Loss (Tons/ac/yr) Using USLE,
(WW-GP), Divided slope Practice--Athena Soil
258
Estimated Cost of Soil Erosion ($/ac/yr),
(WW-GP), Divided Slope Practice--Athena Soil
259
Estimated Soil Loss (Tons/ac/yr) Using USLE,
(WW-GP), Strip Cropping--Athena Soil
260
Estimated Cost of Soil Erosion ($/ac/yr),
(WW-GP), Strip Crop Practice--Athena Soil
261
C.13
Maximum Profit, Associated Tillage System and
Practice, and Acreage under various T-Values and
NO3-N Leaching Constraints--Pilot Rock Soils
262
C.14
Multi-Objective Programming Optimal Solution
C.15
(MOP) --WALLA WALLA Soil
263
Multi-Objective Programming (MOP) Optimal
Solution for Soil loss of Less than or Equal
to 3T-Value--pjlot Rock Soil
265
LIST OF APPENDIX TABLES (Continued)
Page
Table
C. 16
C.17
D.].
D.2
D.3
D.4a
D.4b
D.4c
D.4d
D.4e
D.4f
Multi-Obj ective Programming (MOP) Optimal
Solution--Ritzville Soil
267
Multi-Objective Programming (MOP) Optimal
Solution--Athena Soil
269
All Resources, Data and Parameters used
for the Budgets
271
Wheat, Barley and Green Peas Prices for
tJmatilla County, Oregon
281
Wheat, Barley Target prices and Deficiency
Payments
281
Economic Costs and Returns for Dryland
Fallow/Winter Wheat Production, Standard
Practice, Option MBW-STD-F1W--Walla
Walla Soil
282
Economic Costs and Returns for Dryland
Fallow/Winter Wheat Production, Divided
Slope Practice Option MBW-DIV-F1W-Walla Walla Soil
284
Economic Costs and Returns for Dryland
Fallow/Winter Wheat Production, Strip
Crop Practice Option MBW-DIV-F1W- Walla Walla Soil
286
Economic Costs and Returns for Dryland
Fallow/Spring Barley Production, Standard
Practice Option CHB-STD-F1B--Walla
Walla Soil
288
Economic Costs and Returns for Dryland
Fallow/Spring Barley Production, Divided
Slope Practice Option CHB-DIV-F1B--Walla
Walla Soil
290
Economic Costs and Returns for Dryland
Fallow/Spring Barley Production, Strip
Crop Practice Option CHB-STR-F1B-Walla Walla Soil
292
AN EVALUATION OF THE ECONOMIC IMPACTS OF REDUCING SOIL
EROSION AND GROUNDWATER POLLUTION IN NON-IRRIGATED
FARMING SYSTEMS OF NORTHEASTERN OREGON
CHAPTER I
INTRODUCTION
Overview of Problem
The rapid rate of world population growth has led to a
higher demand for food.
The increase in demand, coupled
with conversion of farmland into urban and industrial uses,
have forced agriculture to expand into marginal lands and
more intensively farm existing acreage.
More intensive
farming and tillage of fragile lands have accelerated the
loss of top-soil via erosion.
In the U.S., removal of soil from agricultural land by
rainfall runoff has been recognized since colonial times
(Crosson and Stout, 1983).
Until the early 20th century,
however, little attention was given to soil erosion,
particularly its effects on productivity and water quality.
Erosion problems were ignored because land was abundant, and
incentives to preserve it were weak (Crosson and Stout,
1983).
Public concern about soil erosion began with the
Dust Bowls of the early 1930's.
Soil particles from Great
Plains dust storms were observed as far as the U.S. east
coast.
The U.S. government, recognizing the potential
adverse effects of soil erosion, created programs and
agencies (such as the Soil Conservation Service), to promote
soil conservation.
Agricultural activity accounts for about
2
60 percent of all the United States soil loss (Highf ill and
Kimberlin, 1979).
Despite government involvement in soil
conservation, soil loss in the United States still averages
about 8 tons/acre/year (Lee, 1984).
The focus of this research is on the nonirrigated areas
of Umatilla County, Oregon area.
The three major
agricultural areas in the county are (1) the Palouse and Nez
Perce Prairies, (2) the Columbia Plateau and (3) the
Columbia Basin.
All three areas extend beyond Uivatilla
County to cover most of Eastern Washington and North Central
Oregon.
This larger area is an important production area of
small grains in the United States.
The Columbia Basin
contains most of the county's irrigated acreage and was the
subject of previous research study (Johnson, 1990).
In preparing the soil for planting, tillage tools and
implements used alter the physical condition of the soil,
predisposing it to water and wind erosion.
Although wind
erosion occurs frequently in the dryland areas of
Northeastern Oregon, water erosion is typically a more
severe problem.
Consequently, the focus of this study is
water erosion.
In the northwest region, over 110 million tons of soil
are eroded annually, and substantial acreage is still losing
soil at a rate much greater than the rate of soil formation
3
(known as the T-value1)
(STEEP, 1984).
A joint study by
the USDA and Council Ofl Environmental Quality, (1981),
identified the Palouse and Nez Perce Prairies, and the
Columbia Plateau of eastern Washington, northcentra]. Oregon
and west-central Idaho as among areas in the United States
with high water erosion rates. In a later study, (USDA,
1983),
it was reported that the erosion rate is above the
regeneration rate on over 400,000 acres of cropland in the
Columbia Plateau area alone.
A soil loss rate above the
regeneration rate CT-value) may not have significant short-
run impact on productivity if it occurs on deep soils, but
can be costly on shallow soils.
Even on deep soils,
continued soil loss above the tolerance value will
eventually reduce productivity on both deep and shallow
soils to the extent that farming may become uneconomical.
(Akbari,
1986).
Soil erosion affects productivity through loss of
nutrient-rich topsoil, reduced soil base, adversely affected
soil tilth, reduced water infiltration and decreased water
holding capacity, all culminating in reduced crop yield and
increased production costs (Walker, 1982; Alt et al., 1989).
As Veseth, (1989) noted, soils that are eroded become more
vulnerable to further erosion; this is "a vicious cycle that
strongly impacts crop production" (p.9).
1T value, according to Wischmeier and Smith (1978), is
defined as the "maximum level of soil loss that will permit
a high level of crop productivity to be sustained
economically and indefinitely."
4
Off-farm impacts include deposits on roads, siltation
of rivers and dams, canals and harbors, and destruction of
wildlife habitat, especially in riparian zones.
Flood
control capabilities, hydroelectric capacity and water
storage capacity are also affected.
Chemically altered
water (from dissolved fertilizer, herbicides or pesticides)
may enhance faster degradation of equipment--turbines,
irrigation pipes and pumps--or render water unsuitable for
drinking or other household uses (McCarl, 1983).
Thus of f-
site erosion can result in higher road repair and increased
dredging costs, leading to higher costs for navigation,
trade and commerce, and increasing cost of operating water
treatment plants, (Clark et al., 1985).
Also, soil
particles carrying chemical pollutants, such as fertilizers,
promote rapid eutrophication2 of lakes and estuaries (ASA,
1982)
Sediment deposits are also hypothesized to be potential
traps for fish eggs.
For example, in a research study by
Shelton and Pollock (1966), it was found that fifteen to
thirty percent siltation of the inter-gravel spaces resulted
in about 85 percent mortality of the fish eggs and fry.
There are also other recreational impacts of off-site
effects of soil erosion.
Soil particles can cause water
turbidity, creating potential swimming and boating hazards.
2Eutrophication
is
the
excessive
increase
in
the
concentration of nutrients in surface water, resulting in
excessive growth of algae and other aquatic plants.
In the northwest region, about 30 million tons of soil are
deposited in streams, lakes, rivers and harbors annually
(STEEP, 1984).
These deposits, by adversely affecting fish
population, create problems for recreational fishermen and
the commercial fishing industry.
An often overlooked
economic implication of off-site or on-site effects of
erosion, is the inter-generational impact.
Current
producers make all the decisions concerning what crop to
grow, what production techniques to employ, and so on.
The
reduced output, increased production and environmental costs
are disproportionately experienced and paid for by future
generations.
Despite soil losses, technological changes have
permitted farmers to maintain and even increase production.
For example, increased fertilizer use has more than offset
the lost crop productivity resulting from the erosion and
exhaustion of native fertility (Walker and Young, 1986).
Other technological developments (improved weed control, and
development of more effective pesticides), favorable
commodity markets and the drive towards increasing
productivity at a greater economic efficiency have
intensified the dependence on commercial fertilizers
(Waddell and Bower,
1988).
An increase in commercial
fertilizer use has had some significant environmental
consequences in many areas, including pollution of
groundwater.
6
Since the late 1970's, there has been growing awareness
of the potential hazards that groundwater pollution
represents to human health.
The primary reason for concern
is that about 50 percent of the U.S. population (CAST, 1985;
Tietenberg, 1988), and about 98 percent of the rural
population use groundwater as the primary source of drinking
water (Solley et al., 1988).
This concern is summarized by
F.P. Miller, president of the Soil Science Society of
America (Luxmoore, 1991), who stated that:
Nitrogen (fertilizer) ranks at or among the top of
the agricultural crop production resource inputs
based on both economics and thermodynamic energy
equivalents.
This production-governing resource
coupled with its propensity to leak beyond the
rooting zone under certain conditions require
management practices and protocols that will
address the economics of its use as well as the
potential for environmental and human health
impacts (p. ix).
Globally, nitrogen fertilizer use on crops and
grassland has been on the rise since World War II.
In the
United States, nitrogen fertilizer usage rose from two and a
half million metric tons in 1960 to twelve million metric
tons in 1985 (Healy et al., 1986).
Nitrogen fertilizer is
applied on over 90 percent of corn, cotton, potato, and rice
acreage, as well as over 60 percent of wheat acres (Kellogg
et al., 1991).
Variations in soil properties and seasonal
rainfallaffect the efficiency of applied fertilizers,
Only
a portion of applied fertilizer is typically utilized by the
growing crop, with the remainder remaining in the soil,
carried off with surface runoff or leached into the vadoze
The average disposition of
zone.
nitrogen
is given in Table
(1.1).
Table (1.1):
Estimates of Disposition for Nitrogen.
Environmental Compartment
Nitrogen (Percent)
Atmosphere
On-site Storage/Decay
Plant Uptake
Off-site (surface)
Surface Water
Vadoze Zone/Groundwater
15
10 - 30
35 - 50
5 - 10
<
5 - 15
Source: Managing Agricultural Chemicals in the Environment:
The Case for a Multimedia Approach (Waddell and Bower,
1988).
According to a U.S. Public Health Service report, an
increasing number of wells are exhibiting nitrate levels
above the EPA standard of 10 parts per million (ppm)
mg N/i)3.
(or 10
Nitrate concentration in aquifers underlying
agricultural land have increased rapidly over the last two
decades (OECD, 1986).
Increase in groundwater pollution is
occurring concurrently with the increase in nitrogen use
(OECD, 1986; Patrick et al., 1987).
In northcentrai Oregon, sporadic locations of
groundwater contamination from well tests have been
reported.
The Oregon Department of Environmental Quality
35 mg N/i is the threshold for continuous monitoring by
the Department of Environmental Quality.
8
found nitrate levels of up to 80 ppm in some Columbia Basin
irrigated cropping areas.
1990, 18
Of twenty five wells tested in
were found to have levels greater than 5 ppm, and
11 had levels greater than 10 ppm (Johnson,
1990).
Leaching
of nitrate is more severe when there is no crop growing on
the field.
Greater amounts of leaching may continue through
the early part of the cropping season, especially on very
sandy soils (Williams and Kissel,
1988).
Hence, a summer
fallow crop rotation could also be more prone to nitrate
leaching.
There are other sources of agricultural groundwater
pollutants.
These include: animal wastes, pesticides, plant
residues, and salty irrigation-waste waters (Robbins and
Kriz,
1973).
Nitrates are more problematic, however,
because of their ubiquitous nature (Waddell and Bower,
1988).
synthetic nitrogenous fertilizers contain nitrogen
in three forms: nitrate, ammonium and Urea.
The nitrate ion
is the common form in which nitrogen is readily available to
crops.
Ammonia in gaseous or hydrated form rapidly
transforms into nitrate.
Urea is first transformed into
ammonia and then to nitrate.
On average, about 50 percent
of applied nitrogen is used up by the crop.
The remainder
escapes into the atmosphere in gaseous form, or is converted
into nitrate form.
Nitrogen in nitrate and nitrite forms is
not attached to the soil particles, but is solvent in soil
9
water.
A considerable proportion may leach vertically,
eventually reaching the groundwater where it becomes a
hazard to the environment (Willardson and Meek, 1969).
The health problems linked to nitrates are
methemoglobinemia (blue babies), cancer, nervous system
impairments and birth defects.
Methemoglobinemia disease
reduces the oxygen-carrying capacity of the blood; children
From 1947 to
under six months of age are most susceptible.
1950, 139 cases of infant metheinoglobineiuia resulting from
farm well-water supplies were documented.
Fourteen deaths
were reported in Minnesota (Bosch et al., 1950).
Only one
death due to high nitrate levels in public water supplies
have been reported since 1960 (Hallberg, 1986).
Few deaths
have occurred from high nitrate concentration in private
wells since the mid seventies (Patrick, et al., 1987;
Johnson, et al., 1987).
Carcinogenic N-nitroso compounds--nitrosamines and
nitrosamides--resulting from the reaction of nitrites (and
indirectly nitrates) with aluines and ainides were found to
cause tumors in experimental animals, and are suspected to
cause cancer in man (OECD, 1986).
Abortions occurred in
3100 ewes and 300 cows in a livestock operation after
drinking water with a high nitrate concentration.
Figure
(1.1) illustrates nitrate pathway into the body--through
drinking water and food--and potential consequences such as
methemoglobinemia (blue babies) and cancer.
The
10
Hineral and Organic N-Fertilizers
NO3 in Soil
j*- Biological and Chemical
Denitrification
NO3 in Groundwater
Water Treatment
NO3 in Drinking Water
NO3 in Food
NO3 in Buman Beings
NO2
in
FOOd
Microbial Reduction
.NO2 in Human Beings
------
NETHEMOGLOBINEMIA
Reaction with NitrosamineE
Nitrosainids
N. Nitroso Compounds:
Workplace, Smoking,
Pharmaceuticals
N. Nitro Compounds
-k- in
Human beings.
CANCER (?)
Figure (1.1): Nitrate Pathway and Metabolism.
Source: Conrad, 1990.
11
relationship between nitrates in water and methemoglobinemia
is well understood.
The relationship between nitrates and
cancer, however, is still unclear (Conrad, 1990).
Other environmental impacts resulting from high nitrate
concentrations include eutrophication of lakes and
reservoirs (Taylor, 1990).
Aquatic plants can limit
navigation, reduce dissolved oxygen and negatively impact
environmental aesthetic values.
Reduced dissolved oxygen
often results in dead fish and production of bad odor and
flavor in potable water supplies.
In many areas, large
nitrate levels in the waters have resulted in loss of
denitrification capability, and higher permeability for
heavy metals and pesticides (Conrad, 1990).
Limited knowledge exists concerning the amount of
pollutants that actually enter the groundwater under a
particular practice and condition.
Moreover, it is
difficult to correctly assess the source of pollution, since
it is mostly from non-point sources.
Factors influencing
groundwater pollution include the dynamics of travel or
hydro-geology of the area, rate of dilution, distance to
aquifer, and permeability of the vadoze zone.
Another important factor influencing rate of
groundwater pollution is pollutants' residence time; that
is, the time taken for the contaminants to travel from the
soil surface to the underlying aquifer.
Residence time is
usually much shorter in humid areas than in arid and semiarid areas.
A large reduction in nitrogen-fertilizer use
12
may not have impact on groundwater quality in arid areas for
many years (Libra, 1986).
In addition, nitrate-nitrogen can
be stored in the sub-surface soil water system and leach
over time into deeper aquifers (Robbins and Kriz, 1973), or
may be blocked from reaching the aquifer by an impermeable
soil layer (OECD, 1986).
Water runoff and infiltration quantities are inversely
related (Peterson and Power, 1988).
A tillage practice
meant to reduce runoffs, and hence soil erosion, may
actually enhance nitrate leaching into the aquifers (Crowder
and Young, 1988).
Although potential solutions to each
problem are similar, some may be in conflict.
Consequently,
there is a need for an economic analysis of possible tradeof fs between soil conservation and dependence on
fertilizers, while recognizing the need for continued
economic viability.
Connor and Smida (1992), investigated the trade-of fs
between leaching and soil loss under an irrigated farming
system.
Their report revealed that trade-off s between the
two pollution problems do occur and that focussing on only
one of the pollution problems may increase the severity of
the other problem.
Several strategies were available,
however, that significantly reduced both pollutants at a
modest cost to farmers.
The current study investigates
trade-of fs between nitrate leaching and erosion in a dryland
farming system.
13
Objectives of the Studv
The primary objective of this study is to identify the
trade-off s between nitrate leaching, soil erosion and farm
profitability for the major nonirrigated farming areas of
Umatilla County.
This information will be useful to farmers
as they try to identify production practices that will help
them reduce environmental degradation on their farms.
Policy makers will also benefit by understanding the
economic implications of potential regulatory policies used
to reduce erosion and (or) nitrate leaching.
The process to
be followed in achieving this objective is as follows:
Identify current and potential management practices for
non-irrigated areas of Umatilla County, as well as
potential practices that might impact nitrate leaching
and (or) soil erosion.
Link estimates of production costs, potential soil loss
and nitrate leaching, and value of yield loss from the
alternative tillage systems and management practices
together in a Multi-Objective Progranuning (MOP), and
estimate a profit maximizing set of management practices
that satisfy particular levels of leachate and erosion.
Identify the tradeoffs between erosion and ground water
pollution for major soil groups in the Columbia Plateau
and Palouse geographical areas.
Using these tradeoffs,
14
identify potential courses of action farmers may follow
on these soil groups to improve environmental quality at
minimal cost.
Dissertation Organization
Chapter II presents an overview of externality problems
of soil erosion and leaching.
Theoretical, policy and
regulatory solutions are discussed.
Chapter III provides an in-depth description of the
study area.
Soil differences across agronomic zones,
climate, management and soil conservation practices are
discussed.
Chapter IV reviews models used in this study, including
the Universal Soil Loss Equation (USLE), the Micro-computer
Budgeting Management system (MBMS), the Nitrate Leaching and
Economic Analysis Package (NLEAP) for estimating nitratenitrogen leachate, and Multi-Objective Programming (MOP)
models.
Chapter V is used to describe the data estimation
process used in this study.
Data sources, alternative
tillage practices, and associated timing and rate of
nitrogen fertilizer application options are discussed.
Also
presented is a description of the actual models used in the
analysis.
15
Chapter VI presents results of the tJSLE, MBMS, NLEAP
and MOP models.
The soil loss rates, cost-return budgets,
nitrate nitrogen leaching rates, optimal production
strategies and analysis are presented by soil type.
Chapter VII presents a summary, general comments,
limitations and future research directions.
Alternative
policy options to minimize leaching and erosion are also
discussed.
16
CHAPTER II
ECONOMIC THEORY
In this chapter, discussion focusses on the externality
problems of soil erosion and groundwater contamination as
related to crop production, solutions to the externalities
problems, and tradeoffs between environmental problems,
particularly, soil erosion and nitrate leaching.
These
issues are discussed from the economic, government policy
and regulatory perspectives.
Externalities
Agricultural production is an economic activity that
involves combining and coordinating a mix of inputs in the
production of outputs--food and or fibers (Beattie and
Taylor, 1985).
It includes complex decision making on
allocation of scarce resources among enterprises and
choice of enterprise among different alternatives.
These
production activities often yield not only the desired
outputs, but also include some undesirable outputs or byproducts.
An externality usually results, according to
Varian (1984), "when the actions of one agent affect the
environment of another agent other than affecting prices"
(p.259).
As an example, when the utility of one agent is
influenced by the consumption or production activities of
another agent (Varian, 1987).
17
Agricultural externalities may be placed into three
groups: (1) depletable and detrimental, such as sediment
deposited on another person's land, killing his (her) crops;
(2) depletable and beneficial, such as rich topsoil
transported from one farmland to another, providing
nutrients for other land's crops; and (3) undepletable and
detrimental, such as (non-point source) sediments deposited
on roads, rivers, reservoirs, and chemical contamination of
surface and groundwaters, raising repair costs for the
society (Taylor, 1990).
Soil erosion and leached nitrate are residuals of
production that are returned to the environment (Waddell and
Bower, 1988).
Because of weather, soil type, biological and
other factors, these residuals are returned in the form of
environmental pollution at a rate that can be greater than
is socially optimal.
The capacity of the environment to
serve as waste receptor at zero price encourages its
exploitation and degradation.
In this respect, the
environment is treated as an equivalence of a Common
Property resource--individuals (polluters) overuse it and
consequently impose environmental costs on current and
future users.
As stated by Bauinol and Oates (1993), costs
are imposed because "the decision maker, whose activity
affects other's utility levels or enters their production
functions, does not receive (pay) in compensation for this
activity an amount equal in value to the resulting benefits
(or costs) to otherstt (p.17).
18
Historically, producers have usually ignored the
environmental damages (externalities) such as ground and
surface water pollution, and off-site impact of soil
erosion, in the economic assessment of their production
processes (Painter, 1992).
Failure to deal with these
externalities leads to a divergence between private and
social marginal cost because, as cited in Taylor (1990),
"there is no incentive scheme in which the producer is
forced to account, in his or her decision making, the
interdependence of his action with another individual's
utility" (p. 37).
In a standard competitive market, the price system
induces producers and consumers, on basis of self-interest,
to make choices that are efficient from the point of view of
society.
In other words, both parties will attempt to
maximize their surplus.
When market conditions do not
facilitate perfect competition, or when social and private
objectives diverge, pollution externalities come into
existence (Varian, 1987).
Under such conditions, resources
will not be allocated according to their true relative
prices.
An imperfect market not only fails to generate an
efficient level of pollution control, it also penalizes
those firms that might attempt to reduce pollution to an
efficient level.
For example, firms that control their
pollution are placed at a competitive disadvantage, because
19
of increased abatement expense.
Their costs of production
become much higher than those of their competitors who do
not control pollution.
The lack of a market that fully reflects total social
costs and returns encourages overproduction (in the case of
damaging externality), or underproduction (in the case of
beneficial externality) (Taylor, 1990).
These results lead
some to conclude that government intervention is needed to
compensate for the market failure.
Solutions to Externality
Theoretical Solution
Economists have suggested several methods to resolve
the externality issue.
Some suggest that the existence of
externalities can be traced to poorly defined property
rights4 and market failure.
An efficient property right
possesses four characteristics: universality, exclusivity,
transferability and enforceability (Tietenberg, 1988).
Environmental problems will occur whenever one or more of
these properties are violated.
Ronald Coase, an advocator
of the principle of well defined property rights for
correcting externalities, proposed what is today called the
Coasian Solution.
4A property right consists of legal rules defining an
owner's rights, privileges, and limitations for use of a
resource.
20
Coasian Solution
Coase contended that, under fully defined property
rights and costless transactions, allowing bargaining
between the polluter and the polluted will produce results
akin to internalization of pollution externalities.
In
other words, barring any obstacles to bargaining, near
social optimal level of output and pollution will be
produced, regardless of whichever side has the property
rights to the environment polluted (Binger and Hoffman,
1988).
Coase's theorem can be portrayed as follows.
Assume
producers Adam and Bonnie produce q and y outputs
respectively, and employ labor as the only variable factor
of production.
Adam's production process for output q
results in production of an externality (for example,
sediment from soil loss) that adversely affects the output
of Bonnie (assuming no other producer or consumer is
affected).
The production functions for both producers and
the impact of the externality can be represented as:
(2.1)
q = q(Lq),
(2.2)
y =
(2.3)
ay
That is, more production of q reduces production of y
through the negative impact of the externality.
21
If Adam has a restricted right to produce q, Bonnie
will have to "bribe" Adam to reduce his scale of production,
relative to some initial level.
But, if Bonnie has
exclusive right to produce y without any imposed
externality, Adam will have to pay to be allowed to expand
his production, relative to some initial level.
Coase
theory stressed that, in either situation, the same level of
output and pollution will be produced.
If Adam has the right to pollute, and Bonnie pays a
bribe
(b) per unit reduction in q relative to a commonly
agreed level (say q°), Bonnie will choose a mixture of labor
and a reduction in q that maximize her profit for a given
wage rate, output price and optimal amount of bribe (w,
and b).
(2.4)
(2.5)
(2.6)
In mathematical terms:
Maximize ll, =
an
=
an
=
* y(L,q) - w*L
- b(q° - q),
= 0,
p*äY
, ._ -w=O.
Solving (2.5) for the amount of bribe (b):
(2.7)
Adam's profit maximization problem given Pq
(2.8)
(2.9)
Maximize
w and b is:
= Pq * q(Lq) - W*Lq + b*[q° - q(Lq)],
= (Pqb)*.
Solving (2.9) for b:
w0.
22
(2.10)
b= p
- MPPLq
Equating (2.7) and (2.10),
(2.11)
b = -P y ay
Pq
MPPLq'
From above equation, output price for q is:
W
Pg
(2.12a)
-
MPPLg
(2.12b)
q*
= q*(pPwb)
Suppose Bonnie has the right to production free of q's
externality, and accepts Adam's pollution for a price (t)
(determined by a "subsidiary" market in pollution), she will
choose labor input and a quantity demanded for Adam's output
that maximizes her profit, given Ps,, w and t:
(2.13)
(2.14)
(2.15)
Maximize
=
* y(L,q) - w*L
+ t*q,
an
'
W =p*Yq
an
Yp* a' -w0
From (2.14)
(2.16)
t = -
Adam's profit maximization problem given Pq, w and t is:
(2.17)
(2.18)
Maximize
aug
= Pq * q(Lq) - t*q(Lq) - W*Lqi
= (P -t)*
aq
Solving (2.18) for t:
(2.19)
t=Pg
MPPLq
23
Equating (2.16) and (2.19)
(2.20)
t =
_*4
= Pq
- MPPLq'
solving (2.20) for price of q,
(2.21a)
=
MPPi,q -
and quantity q is
(2.2lb)
q*
= q*(ppwt)
From (2.11) and (2.20), the "bribe" and tax are equal;
hence, the optimal quantities q* = q*(Ppwb) and
q*
= q*(ppwt) are the same.
The associated levels of
pollution are also identical.
Coase's theorem were quickly challenged because
although it may be possible for the government to allocate
the use of a shared resource among resource users, in
reality, pollution rights are not as easily allocated.
For
example, a group of farmers sharing an aquifer may not be
able to determine who has the right to pollute the aquifer
and the quantity of pollution allowed.
This problem is very
common in agriculture, where pollutants are usually from
non-point sources (NPS).
Moreover, when several parties are
affected by pollution, bargaining may represent a
significant cost.
The question then is: are there any
alternative policies capable of promoting optimal pollution
levels?
24
Policy/Regulatory Solutions
Four policy instruments commonly suggested by
economists to deal with externality problems are input
taxes, pollution (pigouvian) taxes, ambient standards, and
input controls (Tietenberg, 1988; FAO, 1979; Pearce and
Turner, 1990; Bauutol and Oates, 1993).
These solution
methods have been advanced using economic criteria that
include, the benefits from achieving environmental
protection, costs of adjustment in agricultural practices,
costs of implementation and enforcement of policy, and
incentives for the development and adoption of less
polluting production methods (Abler and Shortle, 1991).
Input Tax:
An input tax is used to modify behavior regarding use
of inputs, such as nitrogen fertilizer, that may lead to
creation of an externality.
Given producers' profit
maximizing behavior, a tax increases costs and discourages
use of the taxed input.
As an example, if the government
imposes a tax $t per unit of input x1 the input level that
maximizes profit, given input and output prices (P, r), can
be determined from:
(2.22)
Maximize II = P*f(x) - r.x - t*x)
= p
(2.23)
(2.24)
äf(x)
.7
ar(x)
axi
=MPPxJ'
-
.7
- t = 0
25
rj + t = P*MPP
(2.25)
or rj = P*MPPXJ - t
(assume 3f(x) > o,
a2f(x) < 0)
In the presence of this tax, the producer will use x to the
level x, where its price plus the imposed tax per unit
equals the value of the marginal product; that is,
x*j = x*(P,r,t)
(2.26)
However, in the absence of imposition of tax, a producer
will employ x3 input to the level x°, where its price (rn)
is equal to the value of its marginal product.
(2.27)
x°
That is,
= x°(Pr).
This optimal input level is shown in figure (2. 1).
Imposition of tax on the input results in a decrease in its
use by
(x*3
-
x°) units.
The input tax policy has advantages in its ease and
low-cost of enforcement, administration and implementation.
The effectiveness of excise taxes in reducing input
consumption, and hence pollution, however, depends on some
factors, especially the (input's) price elasticity of
demand.
26
Price
D-VMP
r+t
3
r
D
Input
x
J
Figure (2.1):
Demand Curve for an Input of Production.
On this point, Marshall stated5:
Within an industry, the (absolute) elasticity of
demand for a factor varies directly with: (1) the
(absolute) elasticity of demand for the product
the factor produces; (2) the share of the factor
in the cost of production; (3) the elasticity of
supply of the other factor; and (4) the elasticity
of substitution between the factor in question and
the other factor (Layard and Walters, 1978) p260.
Research findings confirm that the effectiveness of the
tax policy to reduce nitrate leaching is particularly
limited because the demand for nitrogen is very (price)
inelastic.
Consequently, only a high tax rate will induce a
5This is for a two-factor case, but the principle can be
extended to multi-factor situation.
27
significant reduction in nitrogen use (Tietenberg, 1988;
Francis, 1992).
The implication of the inelastic demand is
illustrated as follows.
By similar optimal input choice
principle illustrated in figure (2.1), in the absence of an
input tax on the demand for, say, nitrogen fertilizer, a
producer will use N lbs/ac, in Figure (2.2).
An imposition
of, say ($t1) per pound per acre results in the use of N1
lbs/ac.; a small decrease of (N - N1) lbs/ac. in the level
of fertilizer employed.
But an imposed higher tax ($t2),
however, will result in employment of N2 lbs/ac.
--a large decrease of (N - N2) lbs/ac.
Using a high tax on fertilizer to reduce nitrate
leaching may have unintended negative impacts on soil
erosion.
With lower fertilizer use producing lower yields,
Price
D-VMP
r + t2
r + ti
D
N2 Ni N
Figure (2. 2):
Fertilizer
Demand Curve for Nitrogen Fertilizer.
28
farmers may feel the need to use more intensive practices to
offset the yield loss.
These practices, in turn, may
increase soil erosion.
Leachate from a particular fertilizer application rate
will vary from farm to farm according to soil leaching
potential, climatic condition and other biological factors.
An implementation of a uniform tax on all users will not be
economically efficient in this regard, given farmers are not
penalized according to level of leachates produced (Johnson,
1990)
Pollution Tax:
Pollution tax (pollution charge or Pigouvian tax) on
nitrate leached and (or) estimated soil loss is levied on
the polluter based on his estimated externality cost.
The
addition of this tax to the private costs of production
increases marginal cost, enabling total social costs to be
reflected in fertilization and tillage decisions.
This can
be described mathematically as follows.
Suppose, for example, a tax (t) is imposed on per unit
level of the externality e(q) resulting from production of
product (q), given output price (Pq), the profit maximizing
objective, including the tax as cost is:
(2.28)
(2.29)
Maximize "g
dIT
Pg * q - C(q) - t*e(q),
Pq - C" (q) -
dq
= 0,
29
(2.30)
Pg -
= MC.
The optimal output level is
(2.31)
q*
= q*(Pt)
In (2.28), t * de/dg represents the social opportunity for
each extra unit of output and Pq - t * de/dq represents the
social price of the output.
In Figure (2.3), q° units of output maximize profit in
the absence of tax, with e(q°) level of pollution and c(q°)
amount of marginal externality cost.
However, if the
producer faces the social price for his output, he will
Price,
Costs
Mc,
q
e(q°)
MC
Output q
Figure (2.3):
Imposition of Tax on Externality.
30
reduce his output supply to
pollution e(q*).
q*,
with less amount of
This policy approach internalizes external
costs, enhancing efficient allocation of resources by
eliminating the implicit market failure.
Use of Pigouvian taxes is more applicable in situations
where the environmental damage is observable and
quantifiable (such as in soil erosion problem areas).
Economists warn, however, against extreme use and reliance
on this policy.
An appropriate tax, theoretically, is one
equal to the marginal externality cost at the optimal level
of pollution (Pearce and Turner, 1990).
But apart from
problems of monitoring, setting an appropriate tax rate is
difficult and requires some experimentation.
This is
because the polluter and the government do not share the
same information base.
During the trial and error period,
polluters may face volatile charges, making subsequent
decisions difficult.
Again, in some cases, isolation of a specific pollutant
may not be feasible because of the interactions between
pollutants.
This last problem makes it difficult to
accurately estimate the pollution level, damage function and
necessary tax rate (FAO, 1979; Taylor, 1990).
Ambient Standards:
Ambient standards are legal limits placed on the
concentration levels of specified pollutant in the
environment (Tietenberg, 1988).
These limits, in most
31
cases, are set with reference to health-related criteria,
such as X micrograms per cubic meter or Y milligrams per
liter..
In the case of nitrate-nitrogen, for example, the
limit is 10 parts per million (ppm).
The ambient standard approach involves creation of a
monitoring agency that measures pollutants at strategic
locations in the receiving environment.
Pollutant (non-
uniform) from several sources is related to target
concentration at receptor (R) as:
(2.32)
N
CR
= 1=1
E a*P + K
CR
is pollutant concentration at receptor
a
is ith source transfer coefficient--the constant
increase (or decrease) in concentration at receptor R
per unit of addition (or reduction) pollution from
source i
P
is the pollutant emission level of ith source
K
is the concentration from natural or other sources
outside the area.
Given a target concentration at the receptor, a cost
effective allocation is achieved when the marginal costs of
concentration reduction are equal for all sources.
From the
marginal cost, an ambient charge t, associated with the
standard may be estimated for source i, as:
32
(2. 33)
t
where
= a
* MC
MC is the marginal cost of a unit of
concentration reduction (determined from
knowledge of hydrology and meteorology)
(See Tietenberg,
1988, for detailed discussion)
The legal limits add a constraint onto pollution
activities.
The units of monitoring (per cubic meter or per
hectare) influence the cost of monitoring and ability of
polluters to comply.
As stated in Taylor
(1990),
"the
larger the 'bubble', the greater the flexibility for the
polluter, and the better the chance of approaching
optimality" (p.42).
Standard setting is most applicable and effective in
situations where the number of pollution sources are finite
and where reductions in the polluting activities will
necessarily result in significant reductions in the
associated damages.
A stochastic weather event, such as
irregular rainfall, does not affect the least-cost method of
achieving the target.
However, a cost effective allocation
of control responsibility imputes a larger information
burden on control by the monitoring agency (Tietenberg,
1988).
The monitoring agency is hence required, at a high
cost, to actually oversee the activities of polluters.
33
Controls:
Under control scheme, polluters are required to set one
or more input or output quantities at specified levels.
For
example, farmers may be limited to a particular quantity of
fertilizer usage for a specific type of soil and crop.
The implication of this restriction can be illustrated
using the principle of cost theory.
A cost minimization
objective for a producer using two variable inputs, x1 and
x2 is as
(2.34)
Minimize C = r1*x1 + r2*x2 + b
(b is fixed cost)
subject to q° = q(x11x2)
,
In lagrangian format, (2.34) is
(2.35)
Minimize L =r1*x1 + r2*x2 + b +A(q° - q(x11x2))
(2 36'
= r1 - A *
3L
(2.37)
=
aq = 0,
- q 0 - q(x1,x2)
(2.38)
(2.39)
=r2-A*
aq
= 0,
x1
= x*(ri,r2,q0) for all i.
x
is optimal input choice that minimizes cost.
The minimum cost, given the optimal input choices, is hence,
(2.40)
C
= C*(ri,r21q0)
This cost is represented in figure (2.4) by line TC1, with
optimal input combination at point E.
34
Other
Inputs
2
x*
2
q
xo x
X Input
1
Figure (2.4):
Limitation on the Use of an Input.
Suppose the use of input x1, say fertilizer, is restricted
to x3° pounds per acre, the cost minimization problem
becomes
(2.41)
Minimize
C =r1*x1° + r2*x2
subject to q° = q(x10,x2).
Optimal solution is:
(2.42)
x1 = x10, and
-x20(r1,r21q°)
(2.43)
x2
(2.44)
C= C**(rl,r21q0,x10)
35
This cost is also represented by line TC2 in the figure,
with optimal input combination at point R.
Given r1, r2,
and q°, it can be seen that TC2 is greater than TC1; that
> C*(ri,r21q0).
is, C**(ri,r2
This method is easy to implement and is effective where
localized input use is causing the environmental problem
(Francis, 1992).
The drawback is that a particular limit is
less effective in the presence of stochastic climatic
conditions, and wide differences in soil types and
topography.
This method causes non-optimal allocation of
resources; for example, x20 larger than before may create
high externalities for non-monitored inputs.
Control
schemes are difficult to enforce, and would involve high
administrative and enforcement costs (Johnson, 1990; Fox et
al., 1991; Francis, 1992).
Research evidence leads one to
conclude that the impact of input restrictions on production
varies, depending on how other inputs adjust and the ease of
substitution with other inputs.
Fertilizer reduction may
result in substantial reduction in output and revenues, as
well as an increase in product prices.
These impacts can
make a control scheme less acceptable to producers
(Tietenberg, 1988; Helmers et al., 1990; Fox et al., 1991).
In general, the inherent uncertainties in
effectiveness, high administrative costs and numerous
informational requirements, make it difficult for a single
policy instrument to satisfactorily correct the complex
socio-economic and managerial problems of agricultural
36
pollution.
A judicious combination of complementary, more
flexible, effective and efficient instruments seem more
applicable to the externality problems.
Trade-off Between Soil Erosion and Nitrate Leachate
An aspect of externalities in agricultural crop
production that has received less attention is how to
address multiple externalities that can result from one or
more production activities.
Current environmental policies
are typically aimed at solving one particular environmental
problem.
A solution to one problem, however, sometimes
magnifies another problem.
For example, some soil
conservation practices, such as stubble mulching, are
designed to discourage runoff and erosion.
An unintended
result of reduced runoff is to cause more percolation,
increased accumulation of chemicals in the soil, and high
potential for nitrate leaching into groundwaters (Hinkle,
1985;
Taylor,
1990).
An examination of possible trade-of fs
is therefore important for several reasons.
For instance,
the Soil Conservation Service has expressed concern that
recent calls for more government involvement in the control
of groundwater pollution, may invariably create a compelling
and competing demand for resources that were formerly
directed towards reducing soil erosion (Connor and Smida,
1992).
Given the numerous choices of tillage systems and
nitrogen application levels available to farmers,
37
identifying practices that are complementary6 may be a
difficult task.
Moreover, complementary practices may not
include management strategies that are necessarily most
preferred or most commonly employed by producers.
Identifying combinations of tillage systems and nitrogen
application rates that reduce both pollutants to an
acceptable level may provide useful benchmark tools for
policy makers.
Apart from identifying the trade-off s between two
pollutants, it is also important to evaluate the inherent
conflicts between the environmental goals and potential
economies in jointly addressing the environmental
objectives.
Connor et al., used a framework that combined
knowledge about erosion and leaching process, production
methods, costs and prices to address these concepts as
follows.
Under a joint production of a vector of output q,
a primary externality x1 and secondary externality x2
(influenced by any control policy on x1), the levels of both
externalities are functions of the output as x1 = x1(q1) and
x2 =x2(q1).
If x1 is the primary focus of a regulatory
externality tax, a producer's profit maximizing objective
problem can be represented as:
(2.45)
6
Maximize
II
=
E
* q) - c(q) - t1 * x1(q)
Practices that reduce both erosion and leachate.
38
where p
represents the vector of output prices,
c(q1)
represents the cost of output production, and t1 is tax per
unit of x1 generated.
(2.46)
311
--;=Pi
The first order condition is:
3c(q)
3x1
äq
for all i
The last term in (2.46) shows the effect of the externality
tax on profit maximization choices--an increase in marginal
cost and consequently, a decrease in optimal supply of
output.
(2.47)
The optimal production choice is thus:
q.*
= q(p,t1,c(q1))
Connor et al., remarked that because there was no imposed
tax on the secondary externality, (x2), it has no impact on
producer's optimization decisions.
The level of secondary
externality, therefore, is a function of the level of
optimal output rather than a direct function of prices; that
is,
(2.48)
x2 = x2(q*(p,t1ic(qj)))
Under this situation, a comparative static analysis valid
for a single externality may not be valid when multiple
technologically interdependent externalities are involved.
The tax imposed has a direct effect on the externality that
is taxed and an indirect effect on the other externality
(jointly produced).
For example the impact of the tax on
the secondary externality is expressible as:
39
(2.49)
ax2
.
3x2
l_.iiaq.*
the term 3x2/3q* in
(2.49)
contribution of product
q1*
*
aq.*
at1
represents the marginal
in the production of the
secondary externality x2, and aq*fatj represents the
marginal change in output, q, resulting from the impact of
the taxation.
If both externalities, say soil erosion and
nitrate leaching, have a complementary relationship (decline
together), the tax incidence will cause a decrease in both.
However, if they are non-complementary, a tax on primary
externality (soil erosion). may cause an increase in the
production of the secondary externality at a significant
environmental costs.
Connor et al. stated that "if the secondary effect were
sufficiently strong, a policy to reduce erosion could thus
decrease social welfare" (p6).
Therefore "when jointness in
output production and the generation of multiple
externalities exists, meaningful analysis should consider
the full range of trade-off S between cost and externality
goals" (p 10).
40
CHAPTER III
OVERVIEW OF STUDY AREA AND FARMING PRACTICES
This chapter is in three major sections.
In the first
section, a description of the study area is provided,
including the climate, soil types and depth across the
agronomic zones.
Small grain production in Umatilla County
The last section
is summarized in the second section.
focuses on soil management practices used to produce nonThis discussion covers
irrigated crops in Umatilla County.
such production factors as tillage systems, fallowirig
methods and fertilizer use in the county.
Description of Study Area
Umatilla County is located in the northeastern part of
Oregon.
It encompasses an area of about 2.1 million acres
(Oregon State University, 1973), with population of about
60,000 people.
Most of the population is directly or
indirectly dependent on farming, ranching, food processing
or timber production (USDA, 1988).
Pendleton is the county
seat.
Umatilla County is one of the leading agricultural
counties in Oregon, and one of the major wheat-producing
counties of north-central Oregon.
In the county, there are
about 600,000 acres sown to non-irrigated small grains.
Irrigated cropland represents about 35,000 acres, part of
which is sown to grains (USDA, 1988).
In 1993, 925,000
41
Of this acreage,
acres of wheat were harvested in Oregon.
about one-third (276,600 acres) is located in Umatilla
County.
bushels.
Total Oregon wheat production was about 65 million
North central Oregon counties--Gilliam, Morrow,
Sherman, Umatilla and Wasco--produced 44.6 million bushels,
a 68.6% of the state's production.
Untatilla county
accounted for 22.1 million bushels, about one-third of
Oregon's production (Extension Economic Information Office,
1994)
Total Oregon harvested acreage of barley in 1993 was
150,000, of which 11,000 acres were harvested in Umatilla
county.
bushels.
Total Oregon barley production was 11.3 million
North central Oregon counties produced 3.0 million
bushels, or 26.5% of state production.
Umatilla County
produced 0.8 million bushels, 7% of state production
respectively (Extension Economic Information Office, 1994).
Umatilla county wheat and barley production were valued at
about $70.7 and $1.6 million respectively.
Oregon harvested
green pea acreage was 33,900 during the same period; 30,000
acres were harvested in Umatilla county.
Total Oregon
production was 51,870 tons, 43,860 tons were from Umatilla
county.
This accounted for about 85% of total state's
production, and valued at about $10.6 million.
42
The County falls within four Major Land Resource
Areas7 (MLRA): The Columbia Basin, Columbia Plateau,
Palouse and Nez Perce Prairies (foothills of the Blue
Mountains), and the Northern Rocky Mountains (Blue
Mountains)
(USDA, 1988).
The study areas, as mentioned in
the previous chapter, are the Columbia Plateau, and the
Palouse and Nez Perce Prairies.
Figures (3.1) and (3.2)
show Oregon's 36-county map, Uinatilla County and the four
Major Land Resource Areas respectively.
Climate
tJmatilla County has a temperate climate, characterized
by low annual precipitation (about 8 inches), and high
summer temperatures (about 85oF).
Average Winter
temperatures (about 230F) are colder than Western Oregon,
but winters are not severe.
The low temperature may be
accompanied by snowpack which can accumulate and go through
several melt cycles during the year.
Between 60 and 75
percent of rainfall is received between October and April.
Precipitation increases from west to east across the county.
The average annual rainfall varies from less than 10 inches
at Hermiston, to about 17 inches at the Pendleton
Agricultural Research Center, 18 inches at Weston and about
55 inches in the highest portion of the Blue Mountains.
In
7Major Land Resource Area (MLRA) is a group of land with
similar characteristics such as soil (including slope and
erosion), climate, vegetation, water resources, land use, and
type of farming.
Figure (3.1):
Oregon County Map Showing Location of Uinatilla
County.
44
colU]nbia
columbia
plateau
Basin
Pa louse
and
Nez Perce
Prairies
Norther
Rocky
Mountafl5
jorther
ROCCY
i,1ouflta1s
Figure (3.2)
Map of Umatil
Land ReSOUrc
CoUfltY
shOWi
the Four Major
45
most of the agricultural areas, annual precipitation varies
from 8 to 25 inches.
Strong winds, generally from west and
southwest, may occur at any time during the year, drift snow
in the winter and cause soil movement and excessive
evaporation during other seasons (Oregon State University,
1973)
Soil Depth Across Agronomic Zones
There are 74 identified soil series in Uinatilla County.
The principal Columbia Plateau soils included in this study
are the Shano, Ritzville, Walla Walla and Pilot Rock.
These
soils are located on hills, steep hill-slopes, and gently
sloping areas on terraces.
3,100 feet.
Elevation ranges from 500 to
Shano soils are grayish brown, deep, and well
drained with surface layer that is very fine sandy loam or
coarse silt loam.
They are formed in bess8 deposited over
lacustrine sediment (USDA, 1988).
Most areas of this soil
are used for small grain production and require at least one
fallow year to store enough moisture to make crop production
profitable.
Ritzville is a deep, well drained, light
colored soil, developed from fine floury bess and coarser
wind-laid material underlain by basaltic bedrock and lime
cemented gravel.
and silt loam.
Surface layer is of very fine sandy loam
Ritzville soils also require a grain fallow
rotation.
8A wind blown silty material.
46
Walla Walla soils are formed in bess; they are deep,
well drained, lighter in color with surface, subsoil and
substratum of silt loam.
These soils produce the largest
portion of the wheat grown in tJmatilla county.
Pilot Rock
soils are shallow, light in color, and with surface and
subsoil layers of silt loam over lime hardpan.
Pilot Rock
soils are less productive because they have less waterholding capacity.
Most of the soils are used for small
grain-fallow cropping (Oregon State University, 1973; USDA,
1988), also continuous cropping is occasionally practiced.
Most soils of the Palouse and Nez Perce Prairies
(foothills of the Blue Mountains) are classified as Athena
or Palouse.
These soils are located in gently sloping
areas, on ridge-tops and in very steep areas on hillslopes
where the elevation ranges between 1,500 to 4,500 feet.
Most Athena-Palouse soils are used for non-irrigated annual
cropping of wheat and peas.
A small portion of the soils
located on flood plains support irrigated cropping.
Athena
soils, derived from bess, are deep, dark in color with
surface, subsoil and substratum layers of silt loam.
The
Athena soils are very productive, yielding about 90 bu/ac of
winter-wheat or 20 Cwt/ac of green peas on annual basis.
The Pabouse soil is a deep, well drained soil on summits of
hills, formed in bess underlain by basaltic rocks.
dark brownish gray to nearly black color.
used for non-irrigated crop production.
It is
Most areas are
As a result of the
climatic differences, Athena and Palousé soils vary in
47
organic matter content, structural development and base
saturation. Soils that have north- and east- facing slopes
are in the leeward side of landform that barricade the
prevailing winds, resulting in deeper soils. Steep soils
that have south-facing slopes typically are shallow with
smaller amounts of bess (USDA, 1988).
Wheat Production in tJmatilla County
Agricultural land use in tJmatilla County can be grouped
into five major categories: irrigated crops, small grainfallow, annual cropping, rangeland, and forestry. This
thesis focuses on small grain cropping; specifically,
dryland Summer fallow-winter wheat9, Summer fallow-spring
barley and Winter wheat-green pea cropping systems.
The vast majority of Uxnatilla County wheat acreage is
planted to soft white varieties, such as: Stephens, Daws,
Malcolm and Dusty. These are noted for their high yields,
strong seedling stands that minimize soil erosion, high
winter hardiness, resistance to major wheat diseases (common
bunt, cephalosporiuin stripe, septoria and mildew) and high
adaptability to PNW soils and climate. Spring barley
acreage is limited in Umatilla county, with most acreage in
the non-irrigated cropping areas. When grown, spring barley
9Spring wheat is produced in some areas as a crop by
itself or as another option when winter wheat cropping fails
because of bad weather. Yields from spring wheat are
relatively low and sometimes not economical.
48
usually replaces spring wheat in the crop rotation.
Varieties of Spring barley commonly produced are Steptoe,
Lindy and Adre.
These varieties are also chosen because of
their adaptability to soil types, climate, and disease
resistance (Rasmussen et al.,
1989).
Uxnatilla County is
also the most noted pea growing area in Oregon.
Green peas
are mostly planted, in rotation with winter wheat on Palouse
and Athena soils where annual precipitation is over 15
inches.
Common pea varieties grown is Dark Skinned
Perfection (DSP) and related types (Pacific Northwest
Extension Publication,
1984).
Management of Soils for Crop Production
In the dryland areas of Umatilla county, precipitation
is the limiting factor in crop production.
The decisions
about fertilizer application rates, seeding date and depth,
types of tillage practices and crop rotation are largely
determined by the soil available water and expected
precipitation (Wysocki and Veseth, 1991).
Sixty to seventy
five percent of the precipitation occurs between October and
April, and the fallow-grain rotation system is aimed at
conserving most of it in the fallow year for use by the crop
in the following year.
The different fallow systems will be
discussed later in this chapter.
49
Winter wheat planting date is from mid-September to
mid-November.
If precipitation comes early, seeding may
When
start by mid-September and end about early October.
rains are expected to arrive late, planting typically starts
in October and ends about mid-November.
Early planted wheat
provides some ground cover protection against late fall and
early winter erosion; however, it is susceptible to pest and
disease attacks, and late spring frost damage to early
headed wheat.
Late planted wheat is less susceptible to
pests and diseases, but may not provide effective ground
protection against erosion during fall and winter rains.
Moreover, the crop may be subject to lodging during the fall
rains, because the stand is weak (Akbari, 1986).
of wheat, is done from mid-July until late August.
Harvesting
Spring
barley is planted in mid-March through late April and
harvested in July or August.
Peas are usually planted very
early in the spring season, in the non-irrigated areas, "in
order to take advantage of the cooler growing conditions and
higher moisture" (Pacific Northwest Extension Publication,
1984)
(p.3).
They are harvested from May to July, depending
on weather and harvest stage desired--green or dry pea.
Tillage Systems
Water, wind and tillage erosion commonly occur on the
nonirrigated soils included in this study.
The extent of
erosion varies according to tillage methods, soil types,
steepness and climate.
Erosion tends to be more severe on
50
steep slopes, particularly when a iuoldboard plow is used.
In the northeastern region of Oregon, more producers are
accepting soil conserving technology.
Despite the potential
for large soil losses on conventionally tilled field,
moldboard plowing is still commonly practiced in Umatilla
County (Papendick and Miller, 1977; Akbari, 1986).
Conventional Tillage:
Conventional tillage involves the use of moldboard plow
for primary tillage, followed by several secondary tillage
operations with field cultivators or cultiweeders.
The
goals of this tillage system are to pulverize the soil for a
good seedbed, bury and incorporate previous crop residue,
and aid in weed control (Akbari, 1986; Lyman and Patterson,
1991).
The disadvantage is that it leaves the soil bare,
exposing it to excessive evaporation and high rate of soil
loss from erosion, especially during heavy rainfall periods
(McNamee, 1986).
This method is particularly harmful on
steep slopes as it enhances sheet-like10 erosion of soil
from the hilltops.
The erosion may be more severe in areas
where heavier and more powerful machines had been used
(Papendick and Miller, 1977).
Also, because of little or no
soil cover, the freeze-thaw cycles during the cold weather
also contribute to the erodibility of the tilled soils
(Zuzel, Pikul and Greenwalt, 1985)
10Sheet erosion--uniform removal of thin layers of soil
without formation of observable channels.
51
Conventional tillage system is still being practiced on
two-thirds of planted acreage in the U.S., however, its use
has been on the decline over the past decade.
This decline
is attributed to the economic advantages of conservation
tillage; and of recent, due to more participation in
government programs that enhance conversion (Taylor, 1990).
Conservation Ti.11age:
Conservation tillage is a broad category of tillage
systems that are designed for maintenance and improvement of
soil fertility and productivity and to mitigate excessive
soil loss from water erosion (Winburne, 1962).
Soil
conservation can be by mechanical (structural) or cultural
(management) methods.
Mechanical methods include terracing,
divided slope, strip cropping, and other methods aimed at
reducing runoff speed, shortening slope length and
prolonging water absorption time.
Mechanical methods are
very effective but have the disadvantage of involving
expensive field operations.
Cultural methods are management oriented.
Examples are
reduced tillage, minimum tillage, no-tillage and other
techniques that involve residue management.
methods require fewer machine operations.
Reduced tillage
Minimum tillage
systems exclude primary tillage or use a chisel plow or an
offset disk instead of a moldboard plow; secondary tillage
is optional or just a single pass of a field cultivator or
harrow.
The No-tillage system eliminates primary and
52
secondary tillages.
A no-till planter, is used to seed
directly into previous crop stubble.
The goals are:
(1) to
disturb the soil less; (2) prepare a smooth seed bed; and
(3) maintain more surface residue.
Cultural methods to reduce erosion are less expensive
than mechanical methods because they require less fuel
usage, reduce labor and machinery time, reduce soil
compaction, conserve more water, reduce runoff.
The
disadvantages, however, include potential for high herbicide
and pesticide use, as well as potential for nitrate and
other chemical leaching.
Tucked-in straw may result in poor
seedbed; improper timing and placement of fertilizer can
adversely affect yield (Akbari, 1986).
In Umatilla County, mechanical conservation methods are
practiced to a limited extent.
Most conservation practices
are in form of stubble mulch or reduced tillage.
A major
concern some producers have about these practices is the
problem of residue becoming a potential haven for insects
and diseases.
These pests may inflict severe damages to
subsequent crops, especially a similar crop to that grown
previously.
No-till is less practiced because of the
increased cost for herbicides, pesticides and disease
control, and drilling equipments.
53
Fal lowing
Annual cropping is generally unprofitable in areas of
Uinatilla County that receive less than 16 inches of annual
precipitation.
Hence, fallow-cropping is the commonest crop
production pattern.
The fallow period facilitates storage
of water for the cropping season.
Stored water aids in
minimizing the year to year variation in yield (Ramig and
1988).
Ekin,
Another major benefit from summer fallow is in
participation in the government farm price and income
support programs.
The higher farm average yields from
summer fallow rotation raises a producer's proven yield,
leading to a higher deficiency
price program.
payment under the target
Other benefits from fallowing include lower
fertilizer input, less weed and disease incidence and fewer
problems associated with residue during tillage or seeding
(Hoag,
1984; Akbari, 1986).
Fallowing may involve some
additional costs, however, such as extra herbicide costs and
fixed charges on land, including interest, and taxes.
Rasmussen et al.
(1989) explained that, for fallowing to be
profitable, it must be able to reduce risk, increase yield
and (or) reduce cost of production.
Of several fallowing
techniques, the most common is chemical fallow.
A chemical fallow involves herbicide use in leu of one
or more fall or early spring tillage operations.
The
disadvantage with this method is that, in a wet year, grassy
weeds (such as goat grass and annual rye grass) and
54
volunteer wheat or barley may become difficult to eradicate.
Chemical fallow, however, has some economic advantages, such
as better moisture storage, reduced mechanical tillage
costs, and ability to retain more residue on the soil
surface.
Other forms of fallow not involving chemicals are
(1) stubble mulch fallow (associated with chisel plowing),
where low to medium amount of residues are retained on soil
surface; (2) stubble fallow (associated with one way or
tandem disk) retains heavy residue on the soil surface;
and (3) bare fallow (associated with moldboard plowing)
where almost all residues are completely buried (USDA,
1977).
Fertilizer Usage in Umatilla County
Nitrogen is the major plant nutrient constraining
dryland wheat and barley yields.
In Umatilla County, this
nutrient need is met through fertilizer application.
The
rate of application usually depends on the expected yield,
nitrogen in the soil and crop variety (Gardner and Goetze,
1980).
Eighty to 110 lbs/ac of nitrogen fertilizer is
applied to winter wheat on Walla Walla soil; 40 to 55 lbs/ac
is applied on Ritzville and Pilot Rock soils, and 60 to 90
lbs/ac is applied on Athena soils.
In general, as a rule of
thumb, farmers apply 1 - 1.25 pounds per bushel of expected
wheat yield.
Most wheat producers in the area apply all
fertilizer in May-August, prior to planting in the fall.
A
55
few split application between preplant and a side dressing
is done in February-March.
For spring barley, 20 to 65
lbs/ac is applied on all soils (except Athena).
About 100
lbs/ac of ammonium sulfate with or without 0 to about 25
lbs/ac of nitrogen fertilizer is applied for green pea.
Fertilizers are applied preplant in March or April for
Spring barley, in September and (or) March for Green peas.
Fertilizer management strategies in the county include
(1) pre-plant only application; (2) spring only application;
(3) split application; and (4) sowing of "catch crop'1"
after harvest.
Pre-plant application combined with early
sowing of winter grains allows maximum nitrogen uptake
(Pumphrey and Rasmussen, 1982; Fairchild, 1987).
Spring
only application is beneficial in increasing yield as amount
of spring precipitation increases, releasing nutrients at
the time of crop greatest uptake (Pumphrey and Rasmussen,
1982).
Split application enhances better nitrogen use and
enables producers to economically hedge on weather
factors12.
Catch crop uses up residual nitrogen or
mineralized nitrate from previous crop (Fairchild, 1987).
A quick-growing crop, planted and harvested between
two regular crops in consecutive season; or crop planted after
previous regular crop has failed.
12
Producers may decide not to implement the second
fertilizer application if the weather outlook suggests a
decreasing amount of spring precipitation.
56
CHAPTER IV
MODEL REVIEW
This chapter reviews the models used in evaluating the
economic impact of reducing soil erosion and groundwater
pollution in a non-irrigated farming system.
Examination of
the soil loss, groundwater pollution, and associated
economic costs involve: (1) Using the Universal Soil Loss
Equation (USLE) to obtain an estimate of soil loss; (2)
Cost-return budgeting of alternative tillage systems, using
the Microcomputer Budget Management System (NBMS) package;
(3) Using the Nitrate Leaching and Economic Analysis Package
(NLEAP) to estimate Nitrate-Nitrogen leached; and (4) Using
MultiObjective Program (MOP) to identify a set of optimal
strategies, given various weights on soil loss and nitratenitrogen leaching.
The effectiveness of technologies to minimize pollution
from soil erosion, nitrate leaching or other chemicals
varies by geographical area and magnitude of pollutant
occurrence.
Also, differences in soil type, nitrate
leaching potential, tillage systems, methods of production,
climate and other factors add to the problem of generalizing
one's procedures and results.
Hence, this review is
presented as it relates to conditions in the study region.
57
Soil Loss Estimation
The Universal Soil Loss Equation (USLE), is a tool
widely used for estimating soil loss from water erosion and
for evaluating the effects of soil loss on long term
productivity (McCool and George, 1983).
The USLE is:
(4.1)
A = R*K*L*S*C*P
where
A = estimated average annual soil loss, in
tons/acre
R = rainfall and runoff erosivity factor--an index
of the erosive force of specific rainfall
K = soil erodibility factor; it is the soil loss
rate per unit of erosion index for various
soils--the amount of soil loss from a unit plot
of 72.6-foot length on a 9 percent slope in
(tons/acre)
L = slope length factor; it is the ratio of soil
loss from the field slope length to that from a
72.6-foot length field of the same soil type
and gradient
S = slope steepness (gradient) factor--the ratio of
soil loss from the field gradient to that from
a 9 percent slope
C = cover and management factor; this relates the
amount of cover or residue on the soil surface
at specific intervals in the growing season to
the amount and severity of rainfall occurring
during this period. The "C" factor gives the
ratio of soil loss from a field with specified
cropping and management practices and that from
a bare fallow field, assuming same soil, slope
and climate. The "C" factor is unique for each
crop or crop rotation.
P = supporting conservation practice factor--the
ratio of soil loss with contouring,
striperopping, or terracing to that with a
straight up and down the slope farming.
58
The equation, developed by Wischmeier and Smith in
1960, was introduced for use in 1965.
It was designed
primarily for sheet and nil'3 erosion, and has performed
very well in the 37 states east of the Rocky Mountains.
However, when applied to the Northwest region, a statistical
comparison of observed and predicted values of the USLE,
particularly the dryland areas of Oregon, Washington and
Idaho, revealed a low predictive capability (Zuzel et al.,
1982b).
The poor performance happens because interrill
erosion, concentrated flows and gullies'4, add to sheet
and nil erosion problems in the Pacific Northwest region
(McCool and George, 1983).
Several other problems stemming from the application of
the tJSLE to the Northwest region necessitated further
research by agronomist, soil scientist, and engineers, to
improve the R, K, LS, C and P factors in the equation.
The
research resulted in the development, by McCool and George
(1983), of the second-generation version of the USLE for the
Pacific Northwest dry farmed acreage.
The revised USLE
"predicts long-term average annual soil losses resulting
from sheet, nil, inter-nil, gullies and concentrated flows
as influenced by specific soil conditions, land use and
management practices" (Wysocki, 1987), p12.
The K, LS, C,
13Ri11. erosion--erosion occurring along small channels
(rills), where the channels are small enough to be closed by
normal tillage implements.
'4Gully erosion--erosion occurring in channels (nills)
that are too large to be closed by normal tillage operations.
59
and P factors are in Appendix A.
Details of the revision
are contained in McCool and George (1983).
Figure (4.1)
illustrates the soil erosion processes.
Relevant to the application of the USLE are:
tolerance value (T-value) mentioned in chapter I;
(1) the
(2) Yield-
soil depth response and functional relationship; and (3)
Technological progress and soil erosion.
A background
information about the link between T-value, present value of
yield loss and intergenerational concerns is first
presented.
Link between T-Value, Present Value of Yield Losses and
Intergenerational Concerns
Conventionally, tolerance-value (T-Value) is defined as
the maximum level of soil loss that permits a high level of
crop productivity to be sustained economically and
indefinitely (Wischmeier and Smith, 1978).
This definition
implied that each generation is required to conserve the
soil so that he passes on the endowed soil resources,
uninhibited, to the next generation.
In order to ensure
this, there has to be no sustained erosion in excess of Tvalue, else productivity will fall, production costs will
rise and an unfair burden will placed on future generation
(Crosson and Stout, 1983).
60
Rainfall
Energy
Reduction of
Rainfall Energy
by Plant Canopy
Soil
Characteristics
Jj
Runoff Volume
Detachment of
Soil Particles
J
Soil
Characteristics
Length of
Run
Energy of
Flowing Water
2
.1
1
Roughness
of Soil
ansport and
Further Detachment
Soil Particles
-J
Extentof
Plant Cover
K
I!
(
SOIL EROSION
-/
Figure (4.1):
Soil Erosion Processes.
Source: McCarl, 1983.
61
This concept of T-value, though is a well accepted
standard approach of relating soil erosion to peoples
problems, the definition has been argued by several
economists as vague and less specific as there are
differences in physical or economic definition of tolerable
(McCarl, 1983).
Moreover, the concept ignores employment of
cost effective alternatives to erosion control, which do not
necessarily involve cost increases, such as fertilizer and
organic matter application to soil and future technology
that may replace productivity losses to erosion.
Farmers may not conserve soil now, and thus impose
costs on future generation.
The problem then is how to
balance the welfare of current and future generation.
The
net present value (NPV) criterion is a common approach to
solving this problem.
The present value of annual yield
loss over a period of time depends on the annual value of
the losses, interest rate used for discounting the losses,
time distribution of the losses and when in time the soil
loss occurs.
The lack of a unique interest rate for
discounting makes this approach less appealing.
For
example, when several parties such as the government,
lending agency and producers are involved in soil
conservation project, differences in time preference or
discount rates usually lead to a relegation of the
importance of the yield losses.
Moreover, discount rate
usually do not take into account the uncertainties about
future value of food, land and other input resources.
All
62
these make any choice of discount rate subjective-influencing how the welfare of current generation is
weighted against welfare of future generation in the NPV
computation.
A positive discount rate often favors welfare
of current generation over future generation's.
Farmers
have incentive to control erosion only when they view the
present value of yield loss to exceed the present value
control costs.
T-Value
Soil loss rate for a particular site, as predicted by
the USLE, is compared with the associated T-value.
A
cropping and management system for which associated erosion
rate is less than the T-value is considered adequate for
minimizing erosion (Akbari, 1986).
Management systems
resulting in an erosion rate much higher than the soil's Tvalue are considered erosive, and would require a soil
conservation technique to prevent productivity from being
adversely affected in the long-run.
The Food Security Act (SAC) of 1985 emphasized the
importance of the T-value as yardstick for soil loss from
agricultural production.
The act contained a Conservation
Compliance provision that required producers to have by
1990, and implemented by 1995, a conservation plan for
highly erodible lands (HEL), if they are to remain eligible
for farm program benefits (Wysocki, 1987).
Specifically,
soil loss rates on HEL are required to be controlled to
63
between 2 and 3 times the soil's T-value.
This should be
accomplished through adoption of best management practices
or modification of current tillage systems and practices.
Soils in the U.S. have assigned T-values between 1 and
5 tons per acre per year.
A T-value associated with a soil
type depends on soil depth, nature and magnitude of external
effects on productivities (Tiinmons and Amos, 1982).
Deep,
well drained soils and soils with high rate of regeneration
have higher T-values than shallow soils or soils with poor
subsoil (Wischmeier and Smith, 1978).
The tolerance values
for soils in the Columbia Plateau of Oregon, are shown in
Table (4.1).
Yield-Soil Depth Relationships
The long-term consequence of soil erosion is loss in
soil productivity.
Understanding the relationship between
yield and topsoil depth enhances a better assessment of the
economic impact of soil erosion.
The relationship enables
conversion of soil loss to an associated yield loss.
Knowledge of the yield loss estimate enables growers to
evaluate future crop yield reductions or costs of erosion
associated with their production system.
The yield loss
estimate may serve as signal for a grower to re-evaluate his
optimal cropping decision rule (Young, 1986).
64
Table (4.1):
Estimated Soil Tolerance to Soil Loss
according to Topsoil Depth in Columbia
Plateau, Oregon.
Tolerance Soil Loss (T)
Soil
Depth
Renewable
Above 60"
40 - 60"
20 - 40"
10 - 20"
10" or less
5
4
3
2
1
Soil16
tons/acre/year
tons/acre/year
tons/acre/year
tons/acre/year
ton/acre/year
Nonrenewable Soil15
Soil Depth above
Rock Hardpan, Caliche
5
4
3
2
1
tons/acre/year
tons/acre/year
tons/acre/year
tons/acre/year
ton/acre/year
Where: T = maximum level of soil loss that permits a high
level of crop productivity to be sustained economically.
Source:
Akbari.
Early studies that described the relationship between
yield and soil depth utilized experimental plots and fields
where varying level of topsoil had been removed.
Yields
obtained were found to be lower than those from undisturbed
soil cultivated similarly.
The findings, summarized in
Table (4.2), suggested that yield declines as soil depth
decreases.
15soils with unfavorable substrata such as rock that
cannot be renewed by economical means.
16Soil with favorable substrata that can be renewed by
tillage, fertilizer, organic material, and other management
practices.
65
Table (4.2). Effect of Topsoil Thickness on Wheat Yields
Yield Reduction Per
Inch of Topsoil
Bushels/
Percent
Acre
Location
Wooster, Ohio
Wooster, Ohio
Columbus, Ohio
Oregon
Oregon
Oregon
Geary County, Kansas
Palouse Area, Washington
Palouse Area, Washington
Pullman, Washington
Manhattan, Kansas
1.7
1.5
1.3
1.0
2.5
2.0
1.3
1.6
1.8
1.4
1.1
9.5
6.2
5.3
2.2
5.8
6.4
6.2
6.9
5.3
2.9
4.3
Akron, Colorado
0.5
2.0
Remarks
virgin soil
cropped soil
deep soil
thin soil
thin soil
loss of top 5"
loss of top 11"
Sinolan silty
clay loam
Weld silt loam
Source: Crosson and Stout
Studies by Stallings (1957) and Pawson et al. (1961),
demonstrated that crop growth was positively correlated with
soil depth.
Several other studies reported a correlation
between topsoil depth and soil type, slope, slope length and
direction (Hoag, 1984).
Early studies presumed that a linear and positively
sloped production function accurately represented the yielddepth relationship (Krauss, 1979).
The presumption of a
constant yield increase with an increase in soil depth runs
contrary to the law of diminishing returns--crops have a
finite rooting depth (Taylor, 1982; Pierce et al., 1983).
Pagoulatos, (1987), suggested that a more appropriate
66
functional form, based on economic and agronomic principle,
should exhibit: (1) non-negative but diminishing marginal
returns to topsoil; (2) a non-zero intercept (positive yield
even when topsoil is depleted); and (3), an attainable
maximum yield approached asymptotically as soil depth
increases.
Currently, extensive research on the relationship
between soil depth and yield is still limited because the
effects of erosion are gradual and often insidious; such
research projects would be time consuming and expensive to
conduct (USDA, 1981).
Recent studies in the dryland areas
of the Northwest include those by Walker (1982); Taylor
(1982); Hoag and Young (1983); Adelman (1984); Young, Taylor
and Papendick (1985); and Papendick et al., (1985).
Crops
studied include wheat, barley, dry beans, sweet corn,
potatoes and sugar beets.
Their findings support earlier
studies demonstrating a direct correlation between topsoil
depth and crop yield.
Walker and Young (1981); Walker
(1982) and Taylor (1982) in estimating a more appropriate
yield-depth functional relationship, employed the
Mitscherlich-Spillinan (N-S) functional form.
The (M-S)
function produces an asymptotic functional relationship in
accord with the above economic criteria.
(Thomas et al., 1986) is of the form:
The M-S function
67
Y = N
Y = crop yield;
the theoretical maximum yield
N
obtainable from an additional units
of input x;
A = the sum of the declining geometric
yield increment series to infinity;
the constant ratio between
R
consecutive terms of the declining
geometric yield increment series;
X = the level of input.
(4.2)
Where:
Carter et al., investigated similar relationships for
wheat and barley under furrow irrigation systems.
They
found that "the crops exhibited greatest yield response per
unit change in soil depth,...and the relationship followed
reasonably wel1 the log function" of the form (Carter et al.
1985), p.210:
Y=a+blnx
(4.3)
where
Y = Percent of maximum yield
x = topsoil depth (cm)
The estimated functions for wheat, pea and barley are shown
in Table (4.3).
Hoag and Young (1983), compared linear functional
relationships with the M-S models, based on theoretical
agreement and goodness of fit criteria.
N-S models performed better.
They found that the
In Table (4.3), the general
asymptotic functional form is:
= a + b(1_RDt); a, the intercept term, represents the
crop yield at zero topsoil depth or on subsoil; b is the
maximum increase above subsoil yields that can be obtained
68
Table (4.3):
Statistical Estimates of the Yield-Soil Depth
Relation for the Pacific Northwest.
Citation
Crop
Function Estimated
Goodness
of Fit
Location
Walker
and
Young
Wheat
Y = 36.44 +
47.0l(l_eO9864D)
Y = wheat yield,
D = soil depth
R2 = 0.59
Palouse
Dryland
R2 = 0.38
Palouse
Dryland
None
given
Eastern
Palouse,
Dryland
(Based on
Taylor's
work)
Camas
Prairie,
(inches)
Walker
and
Young
Pea
I = 6.96 +
l5.03(l_e3567D)
Y = pea yield
cwt / ac
D = soil depth
(inches)
Bauer
Wheat
It = 38.92 +
= wheat yield
at time t
Dt = soil depth
at time t
ID.
Bauer
Spring
barley
It = 28.34 +
2919(1.9Dt)
R2 =
.68
= Barley
yield
at time t
Dt = soil depth
at time t
Carter
et al.,
Wheat
Y=-57.17+37.23 mx
ID;
Dryland
R2
0.52
1= % max yield
x= topsoil depth
Barley
Y= -2.90+23.59 mx
On-farm
station,
ID;
Irrigated
(cm)
Carter
et. al.,
Camas
Prairie,
R2 = 0.77
Y= % max yield
x= topsoil depth
(inches)
Source: Walker and Young; Bauer; and Hanrahan.
On-farm
station,
ID;
irrigated
69
on infinitely deep topsoil; (a + b) is equivalent to M in
equation 2 and (1 - RDt) is the proportion of the maximum
yield increase, b, attained at topsoil depth Dt.
Hence,
b(l _RDt) is the amount of the maximum yield increase, b,
attained at topsoil depth Dt, while R is (marginal product
of the (Dth + 1) inch of topsoil)/(marginal product of the
Dth inch of topsoil); t is index of time, t = 0 means start
of analysis period for t = 0,1,2,
.
.,n years.
Technological Progress and Soil Erosion
Increased fertilizer use, planting genetically improved
seeds, application of improved agricultural chemicals for
weed and pests control, use of improved farm machinery and
implements, and other technological advances have helped to
raise wheat yields over time.
For instance, technological
change is responsible for a doubling of wheat yields in the
Palouse area of Southeastern Washington-Northern Idaho,
despite high erosion levels (Pawson, 1961; Walker and Young,
1982).
Similar events elsewhere lead some to contend that
concern for soil erosion is excessive, that technological
advances will continue to more than offset the effects of
topsoil erosion.
Several economists disagree with the implied notion
that technology and soil may always function as substitute
inputs in crop production.
They argue that technological
progress actually masks the observable effects of soil
erosion on productivity rather than rectifying it (Thomas et
70
al., 1986).
A relevant comparison is yield in the presence
of technological progress and continued soil loss versus
yield with same level of technology and no erosion.
A
related issue concerns whether technological progress raises
yields evenly across different soil depths.
The current view, given existing research, is that:
(1)
yield with erosion and technological advances is less than
yield with no erosion and same level of technological
advances; (2) technology boosts yield more on deeper soil,
making conservation economically important in terms of
future farm income; (3) technology becomes a poorer and
poorer substitute for soil loss as soil depth declines; (4)
as cumulative erosion reduces topsoil, the cost of another
year of erosion increases because of higher yield damage
from soil loss on shallow soil; (5) because of the nonlinear
nature of the yield-soil depth relationship, and the
declining impact of technology on shallower soils, damage
from erosion might exceed the technologically-induced yield
boost at some point in the future; (6) on deeper soils,
technology may not be able to curb yield declines
indefinitely; and (7) general agricultural technology and
soil conservation are complements--not substitutes--towards
maintaining and enhancing future crop yields (Walker and
Young, 1982).
Detailed discussion of technical progress and
soil erosion are contained in Walker and Young (1982), Bauer
(1984), Young et al., (1984a), Hanrahan (1986), Walker and
Young (1986) and Thomas et al., (1986).
71
Cost-Return Budgeting Using MBMS
Budgeting is a tool widely used in economic research,
policy evaluation,
planning
and decision making.
In
agricultural production, a budget provides the physical,
financial
and other economic information about the whole
farm plan or individual enterprise for a specific time
period.
It lists all expenses (fixed and variable costs,
cash and
non-cash
costs) and revenue projection--an estimate
of the expected total yield and output price (McNamee,
1986)
Cost-return budgeting assists in the planning,
implementing and control phases of the farm management.
Other purposes of budgeting include: (1) to assist the
farmer in identifying possible
combinations
of available
resources for crop and (or) livestock production; (2) to
force the manager to develop a production and marketing
plan;
(3) to allow potential outcomes of changes in resource
availabilities and (or) prices to be evaluated before plans
are actually implemented; and (4) to serve as means of
developing and
organizing
information for lending
institutions when the farm operation needs loans (Kay, 1981;
Olson, 1985).
In studies analyzing the economics of soil conservation
practices, cost-return budgeting has been employed
extensively to identify the relative profitability of
72
alternative production technologies and management
strategies.
For example, conventional tillage is known to
be more erosive than conservation tillage; moreover,
conservation
tillage disturbs the soil less, substitutes
chemical control for mechanical control of weeds.
Cost-
return budgets for alternative tillage scenarios structured
in the form of conventional versus conservation tillage
systems reflect tradeoffs between profit and soil loss, and
differences in cost of production due to fewer machinery
operations and more chemical usage (McNamee, 1986).
Researchers in the Pacific Northwest often prepare and
use cost-return budgets to evaluate different tillage
systems for dryland and irrigated crops (Mohasci and Hinman
(1981); Maxwell et al. (1984); Young et al. (1984b); Cross
et al. (1991); Seavert et al. (1991); Hinman et al. (1991);
and Hinxnan and Schirman (1991)).
These prepared budgets are
usually beneficial for producers as guidelines in making
their budgetary decisions.
The usefulness of any budget in farm planning is,
however, dependent on the accuracy of the data used.
Source
and date of data are essential as technology, resource
availability and prices change regularly.
Assumptions about
the size of production, level of technology, and management
efficiency in the production processes are pertinent to the
budget.
These factors influence average fixed costs,
utilization of inputs and crop yields.
73
In this research, enterprise budgets were generated
using components from the Microcomputer Budget Management
System (MBMS) program package.
MBMS was designed in 1986 by
J.N. McGrann, K.D. Olson, T.A. Powell and
T.R. Nelson, at
Texas A&M University, for use by extension staff,
researchers, crop producers and ranchers in enterprise
analysis and planning (McGrann et al., 1986).
Developing a cost-return budget using MBMS involves
four major steps: (1) describing the resources, inputs,
potential crops and yield;
(2) describing how these
resources fit together; (3) calculating receipts and costs;
and (4) reporting of the enterprise budget.
The budget
details the elements of the gross income, variable cost,
fixed cost and net return.
The gross return value includes
items like government payments and sales from crops.
Variable costs include machinery repairs, machinery
lubricants, labor, seed, fertilizers, herbicides,
lubricants, fuel and other energy.
These costs vary
according to the level or size of production.
Fixed costs
include depreciation, interest on investments, insurance,
and taxes on equipment and land.
Net return is gross income
minus total costs.
MBMS is menu driven, capable of being used to generate
large, detailed budgets.
The program is flexible, with
built-in error checking ability to minimize undetected user
errors.
The high degree of capability, however, requires
that users be truly knowledgeable about computer usage and
74
enterprise budgeting (McGrann, 1986).
The details and
procedures of the cost-return budgeting in this study are
discussed in the methodology and data specification chapter.
The weakness of the budgeting approach in economic
analysis of soil conservation or agricultural pollution lies
in the partial, static nature of the cost-return budget.
Economic costs of environmental damages resulting from of f-
site impacts of soil erosion and nitrate leaching associated
with different production systems are difficult to quantify,
and hence are often unaccounted for in budgetings.
Also,
cost-return budgets are developed for a production period,
usually one year.
However, soil erosion affects long-term
potential productivity of the soil, and nitrate leachate
affects groundwater quality for an indefinite period of
time.
These damages ought to be included in any analysis.
Estimating Nitrate-Nitrogen Leaching
The study objectives necessitated an estimate of the
nitrate-nitrogen (NO3-N) leached from the various tillage
system and fertilizer level combinations.
This estimation
is essential when examining current practices and in
evaluating alternative production strategies that minimize
nitrate leaching; environmental consequences of
overfertilization can also be better understood.
75
Previous researchers have utilized several models to
estimate the amount of NO3-N leached from different tillage
practices.
These models include Attenuation Factor (AF)
(Painter, 1992), Erosion-Productivity Impact Calculator
(EPIC) (Williams et al., 1989), Crop-Environment Resource
Synthesis (CERES) (Ritchie et al., 1986), and Chemicals,
Runoffs, and erosion from Agricultural Management Systems
(CREAMS) (USDA-ARS, 1980).
their leaching potential.
AF ranks chemicals according to
Values range from 0 to 1, with 0
representing very low leaching potential and 1 being a
chemical with high leaching potential.
The amount of
leachate reaching groundwater is obtained by multiplying AF
by the amount of chemical (fertilizer) applied.
EPIC and
CERES mathematically simulate crop growth, estimate nutrient
use, crop yield and leachate.
CREAMS is used for evaluating
alternative management practices and the impacts on sediment
yield and chemical pollutants.
Although AF provides moderately good estimates of NO3-N
leached based on soil water content and depth to water
table, it does not take into consideration other important
factors that affect leaching, such as initial soil nitrate
level, crop residue incorporated, timing of fertilizer
application and crop planting date.
Shortage of empirical
data on solar radiation, relative humidity and wind, usually
limit the use of EPIC or CERES.
Moreover, researchers to
date have not focused on accurately calibrating EPIC or
CERES for use in predicting nitrate movements.
Another
76
issue is that CERES was not designed to evaluate production
practices involving crop rotations.
CREAMS utilizes the SCS
runoff curve number, tJSLE parameters and other engineering
parameters for its predictions.
Research evidence indicates
that, given complete and accurate input parameters, CREAMS
provides much better estimates of soil erosion and leaching
potentials.
erosion.
However, CREAMS is weak in predicting gully
The lack of certain soil and engineering input
parameters limits CREAMS applicability in predicting
leachates (Line and Meyer, 1988).
This study utilizes NLEAP to estimate leached NO3-N
associated with the alternative tillage system-fertilizer
level combinations.
NLEAP was developed in 1991 by a group
of tJSDA-ARS researchers at Fort Collins, Colorado State
(Shaffer et al., 1991).
NLEAP is a "computer
program that is user oriented and designed for use by
farmers, extension agents and other government agencies
(such as the SCS)"
(Shaffer et al., 1991) p.285.
NLEAP does not simulate crop yields.
It uses site
specific information such as crop yield, farm management
practices, soils, and climate to rapidly and efficiently
determine the potential NO3-N leaching, evapotranspiration,
Ammoniuin-nitrogen nitrification17, denitrification18,
17Nitrification is the biological oxidation of ammonia to
nitrite and finally to nitrate.
18Denitrification is the anaerobic decomposition
nitrites and nitrates to nitrogen and nitrous oxide.
of
77
ammonia volatilization19, soil organic matter and crop
residue mineralization20, water and temperature stress
factors, crop nitrogen uptake, and potential impacts of NO3N
leaching on associated aquifers.
NLEAP is menu driven with ability for error and range
checking on input parameters.
The program is very flexible
and capable of providing estimates of potential NO3-N
leaching on an annual, monthly or event-by event time basis.
NLEAP has the ability to be used in sequential analyses for
scenarios involving crop rotations.
conditions
In effect, soil
at the end of first analysis (crop) are
internally reset as initial data for the second analysis,
involving the next crop in the rotation.
A qualitative analysis of risks associated with
leaching of NO3-N (if any) based on soil, climate, and
management condition and groundwater resources is provided
in the analysis report.
Alternative management systems that
minimize NO3-N leaching,
including
aspects of field
operations contributing the most and the least to the
leaching, are often suggested in the analysis.
19Aiumonia volatilization is loss of gaseous ammonia into
the atmosphere.
20Residue mineralization is the conversion of organic
nitrogen into mineral form (NH4, NO2, NO3).
78
Model Validation
The choice of NLEAP in this study was based on its
general useability, explicit and readily available data
input requirements, little or no program parameter recalibration, consistency and high performance under
conditions in which it has been applied and validated.
For
example, NLEAP was validated against lysimeter and
groundwater data in Ohio and Iowa; it was found to be 86 and
87 percent accurate, respectively (Shaffer et al., 1991).
Other models such as CERES (Ritchie et al.), EPIC
(Williams et al.) and CREANS (Knisel and Foster) have been
used in several parts of the country and found to have
performed adequately; however, users reported inherent
problem of re-calibrations of internal program parameters
and input data to make the program perform well.
They
further emphasized the problems and necessity of staying in
frequent contact with the program developers, throughout the
period the program is in use.
As with any other model, the reliability of NLEAP in
predicting the NO3-N leachate depends on the accuracy of
input data.
NLEAP is weak in predicting NO3-N leaching
accurately in soil with complex layering or where a shallow
water table supplies water for the crop.
It is also weak in
situation where water and solute transportation in the
aquifer are key subjects under consideration (Shaffer et.
al., 1991).
79
Multiple Obiective Programminq (MOP) Model
Traditionally, in agriculture, linear programming (LP)
techniques are employed to solve problems involving
optimization of an objective function--net farm income or
cost of production--given a set of scarce resources
available to the producer (Kay,
1981).
Several researchers have investigated farm level
economic and environmental impacts of farm policy proposals
such as effluent charges, pollution standard, input tax and
input control (Taylor,
1990;
Johnson,
1990; Painter, 1992).
These researchers have used LP to attempt to answer the
general question of how the policies can best promote
economically and environmentally optimal farming practices.
In studies dealing with soil erosion and groundwater
pollution from agricultural land, LP is utilized to evaluate
the economic consequences of alternative production
strategies that offer to minimize these externalities
(McNamee,
1986).
Despite the wide application of conventional LP, its
shortcomings cannot be ignored.
These include assumptions
of a single-criterion objective function, linear
relationships between variables, comparative static
framework, and exogenously determined parameters.
Attempts
to minimize the problem imposed by the assumption of singlecriterion objective have been made difficult by the
multifaceted nature of natural resource problems (Atwood et
80
al., 1990).
For example, solutions to erosion problems and
groundwater pollution are sometimes similar, and sometimes
different to the extent that they even conflict.
Agencies
charged with the responsibility to proposing policies that
achieve two different environmental objectives, may find
these objectives in conflict with the producer's profit
maximization goal.
Attempts to overcome the other LP
problems stated above include non-linear and dynamic
programming.
Multi-Objective Programming (MOP) offers a
better approach to address issues of multiple externalities.
Multi-Objective Programming (MOP) is a tool that has
recently been used in analyses of agricultural planning
problems involving optimal compromise amongst several
objectives--some of which may be in conflict.
al.,
Apland et
(1984) examined alternative leasing methods under risk
for an owner-tenant and a landlord in Kentucky.
Lee and
Lovejoy (1991), performed an integrated assessment of
environmental effects from agricultural production.
Connor,
Perry and Adams (1994), identified efficient pollution
abatement with multiple competing environmental objectives
and limited resources in the irrigated area of Treasure
valley, in eastern Oregon.
Multi-Objective Programming involves an iterative
procedure in which several objectives, subject to some
constraints, are optimized simultaneously.
Optimum
solutions for these simultaneous objectives, however, cannot
be defined; MOP attempts to identify an approximation for a
81
set of non-dominated or Pareto-optimal solutions (Roinero et
al.,
1987).
From the set of optimal solutions, tradeoffs
between alternative levels of the competing objectives can
be mapped out (Atwood et al.,
1990).
There are four ways efficient solutions can be
generated: (1) weighting technique; (2) constraint method;
(3) multi-objectives simplex algorithm and (4) the noninferior set estimation (NISE).
The NISE generating
technique was employed in this study, because it offers
greater efficiency than the alternatives.
The MOP technique has advantages over other
lexicographic goal programming approaches in that it does
not require the user to have a-priori information about
decision maker's preferences regarding the relative values
or importance of the objectives (Connor, Perry and Adams,
1994).
The algorithm converges quickly to identify an
efficient set of solutions.
The desired accuracy for the
set of approximated non-inferior solutions can be easily
attained because MOP enhances the analyst's capability to
control maximum possible error, based on some pre-specified
error criteria (Cohon, 1978).
Another outstanding feature
of MOP is that in making it easy to elicit possible
tradeoffs between objectives and the range of alternative
solutions, producers' perception of problems in question are
made more realistic.
82
Although MOP provides increased information about
alternative choices for resource use policy, it is weak in
its ability to suggest appropriate incentives and
compensation for a move from status quo to another
alternative (Romero and Rehman, 1984).
Also, MOP cannot
give a clear choice of strategy or option to adopt.
Details
of the procedure in applying the MOP-NISE technique are
discussed in the methodology.
83
CHAPTER V
METHODOLOGY AND DATA SPECIFICATION
The preceding chapter presented general overviews of
the models used in this study.
This chapter contains the
details about each inodel--tJSLE, MBMS, NLEAP and MOP--as they
were used in this study.
The data used in these models
differ somewhat for each soil location considered in this
study.
The first part of this chapter focuses on the
sources of soil data, common tillage systems used in the
area under study and sequence of field operations in each
system.
Next, each model is presented in detail, in the
order they are evaluated in the study.
At relevant points,
other data and information are provided, including sources
and underlying assumptions.
Figure (5.1) below illustrates
the data flow and links between the models.
Most economic evaluations of agricultural
(environmental) pollution focus on irrigated farming
systems.
Water management (timing and quantity applied) is
identified as the key variable for controlling soil erosion
and (or) nitrate leaching.
Under non-irrigated system,
however, rainfall and weather systems are stochastic and
uncontrollable.
These unpredictabilities present the
farmers several alternative combinations of tillage systems,
fertilization, and soil conservation practices to use in
controlling erosion and leaching.
Given the number and
complexities of the possible scenarios, a multi-faceted
84
(Topography
Weather Data
Soil Data
Crop Data
Tillage Systems
i\anagement Practices
[USLE
Farm Data
Fertilizer Data
[NLEAPJ
3
Topsoil Loss ) (Nitrate_N
Leached
Cost of Erosion
Damage
Til].age Systems
MOP
Hanagement Practices
Farm Size,
Equipment, Crop
and Other Input
Price Data
Net
Returns
MBMS
'p
Optimal Tillage & Fertilizer Application
Rate Strategies
Figure (5.1):
Schematic Diagram of Linkages
between Models.
85
framework is required to examine these combinations, from
both physical and economical perspectives, for their soil
erosion and nitrate-nitrogen leaching potentials.
Sources of Information
To obtain data on current farming practices and costs,
a panel consisting of wheat, barley and green pea producers
in the !Jmatilla County area, an agricultural extension agent
and a research scientist from the Columbia Basin
Agricultural Research Center in Pendleton, Oregon, was
assembled.
This panel also provided information on soil
characteristics, alternative tillage systems, conservation
practices, and alternative fertilizer application rates and
timings.
Additional data were obtained from the Soil survey
of uxnatilla County, Oregon, published research papers and
other bulletins related to the study area.
General
descriptive information for the four soil groups considered
in the study is given in Table (5.1).
Tillage Systems and Management Practices
The soils considered in this study vary by location,
composition, depth, precipitation zone, weather, crops and
cropping system supported.
Summer fallow-Winter wheat is
the most common rotational system on Pilot Rock, Ritzville
and Walla Walla soils, with a Winter wheat-Green pea
rotation system prevailing on Athena soils.
Few areas
86
Table (5.1):
Agricultural Land Inventory.
WALLA WALLA SOIL
Soil Definition
Main Crops
Rotations
Avg. Yield
Avg. Farm Size
Avg. Topsoil Depth
Silt Loam 1 - 7% slope 117,400 Acres
7 - 12% slope 37,572 Acres
12 - 25% slope 40,225 Acres
Winter wheat, Spring Barley
(SF-WW), (SF-SB)
75 bu/Ac. (WW); 4,000 lbs/Ac. (SB)'
2,000 Acres (SF-WW)
2,000 Acres (SF-SB)
16 inches
PILOT ROCK SOIL
Soil Definition
Main Crops
Rotations
Avg. Yield
Avg. Farm Size
Avg. Topsoil Depth
Silt loam: 1 - 7% slope 30 ,905 Acres
7 - 12% slope 5 ,660 Acres
12 - 25% slope 4 ,l65 Acres
Winter wheat, Spring Barley
(SF-WW), (SF-SB)'
40 bu/Ac. (WW); 3000 lbs/Ac
(SB)'
2,000 Acres (SF-WW)
2,000 Acres (SF-SB)
10 inches
RITZVILLE SOIL
Soil Definition
Main Crops
Rotations
Avg. Yield
Avg. Farm Size
Avg. Topsoil Depth
Silt Loam: 1 - 7% slope 33 ,410 Acres
7 - 12% slope 13 ,8l5 Acres
12 - 25% slope 22 ,635 Acres
Winter wheat, Spring Barley
(SF-WW), (SF-SB)
(SB)'
50 bu/Ac. (WW); 3500 lbs/Ac
2,500 Acres (SF-WW),
2,500 Acres (SF-SB)
9 inches
ATHENA SOIL
Soil Definition
Silt loam: 1 - 7% slope 45,110 Acres
7 - 12% slope 9,775 Acres
Main
Avg.
Avg.
Avg.
Winter wheat, Green peas; (WW-GP'
Crops
Yield
Farm Size
Topsoil Depth
90 bu./Ac. (WW); 20 Cwt/Ac. (GP)-'
2,000 Acres
22 inches
a/ SF=Suinmer Fallow, WW=Winter Wheat, SB=Spring Barley and
GP=Green Pea. b/ yield may not be realizable by all farmers
87
practice Summer fallow-Spring Barley rotation.
Four common
tillage methods were identified on Pilot Rock and Ritzville,
five on Walla Walla and three on Athena soils.
The tillage
systems and sequence of operations are presented in Tables
(5.2) to (5.4).
Conventional tillage uses moldboard plow for primary
tillage; this is followed by four or more passes of
secondary tillage.
The objective is to provide fine tilth
seedbed for the crop, bury and incorporate previous crop
residue into the soil, and aid in weed control (Lyman and
Patterson, 1991).
Tillage systems using Chisel plow for primary tillage
followed by other secondary tillages leave 30-35% wheat or
barley residue cover on the soil.
Chisel plowing is
commonly used on fairly steep fields or where soil frost is
prevalent--to enhance water infiltration and conservation.
The residues incorporated help reduce depth or duration of
soil frost (Wysocki and Veseth, 1991).
Disking, followed by
a few secondary tillages, is used in place of moldboard
plowing on very loose soil, hard ground or land covered with
much crop residues (Wysocki and Veseth, 1991).
A strategy that includes residue burning results in low
amount of crop residue on the surface or incorporated with
the soil.
Although this method may help eradicate diseases,
it exposes soil to excessive evaporation and soil loss
through erosion (Rasmussen et al., 1989).
88
Table (5.2a):
Crop
Summer Fallow-Winter Wheat, Standard Tillage
Options--Walla Walla Soil.
Month Year
Tillage Alternatives
OPTION 1
SEP
MAR
YrO
In
MAR
MAY
MAY
MAY
In
Yrl
In
Yrl
MOLD BOARD
OPTION 2
OPTION 3
CHISEL
DISK
HERBICIDE
HERB I CIDE
SPRAY
FALLOW
YEAR
CROP
YEAR
APPLICATION
SWEEPPLOW
CULTIVATE
FERTILIZER
APPLICATION
APPLICATION
CULTI WEED
CULTI WEED
CULTIVATE
CULTIVATE
FERTILI ZER
JUN
JUN
JUL
In
In
In
CULTI WEED
AUG
Ynl
In
In
CULTIWEED
In].
DRILL SEED
Yr2
HERB I CIDE
SEP
SEP
OCT
FEB
JUL
FERTILI ZER
CULTIWEED
CULTI WEED
SPRAY
FEB
SPRAY1
CULTIVATE
CULTIVATE
CULTIWEED
CULTIWEED
DRILL SEED
CULTIWEED
CULTIWEED
DRILL SEED
HERBICIDE
SPRAY
HERBICIDE
SPRAY
FERTILI ZER
Yr2
FERTILI ZER
FERTILI ZER
Yr2
APPLICATION
HARVEST
APPLICATION APPLICATION
HARVEST
HARVEST
89
Table (5.2a) Continued: Sunmer Fallow-Winter Wheat,
Standard Tillage Options--Walla Walla Soil.
Crop
FALLOW
YEAR
CROP
YEAR
Month Year
SEP
YrO
MAR
MAR
MAY
MAY
MAY
Yr].
Tillage Alternatives
OPTION 4
OPTION 5
DISK
BURN RESIDUE
DISK
CHISEL CHOPPER
Yrl
Yri.
DISK2
Yrl
Yri.
FERTILIZER
APPLICATION
CULTIWEED
APPLICATION
CULTIWEED
CULTIWEED
CULTIWEED
CULT IWEED
CULTIWEED
CULTIWEED
DRILL SEED
JUN
JUN
JUL
Yrl
Yrl
Yrl
AUG
SEP
SEP
OCT
FEB
Yrl
Yrl
Yrl
Yrl
Yrl
FEB
Yr2
FERT ILl ZER
Yr2
APPLICATION
HARVEST
JUL
DRILL SEED
HERBICIDE
SPRAY
FERTILI ZER
HERBICIDE
SPRAY
FERTILIZER
APPLI CATION
HARVEST
The tillage systems are denoted, respectively, as MBW, CHW,
DIW, DIBW, AND DICHW; W stands for Winter Wheat cropping.
1Round up herbicide; 2spray FINESE + MCPA, ADD SENCOR (OR
LEXONE) for Options 2 AND 3.
90
Table (5.2b):
Crop
Summer Fallow-spring Barley, Standard Tillage
Options--Walla Walla Soil.
Month Year
Tillage Alternatives
OPTION 1
SEP
FALLOW
YEAR
CROP
YEAR
FALLOW
YEAR
CROP
YEAR
MAR
YrO
Yrl
MAR
MAY
MAY
JUN
JUN
JUL
Yrl
Yrl
Yrl
In
Yrl
Yrl
SEP
MAR
APR
In
Yr2
Yr2
APR
APR
MAY
Yr2
Yr2
Yr2
JUL
Yr2
SEPT
MAR
MAR
MAY
MAY
JUN
JUN
JUL
YrO
Ynl
Yrl
Yrl
AUG
MAR
APR
APR
APR
MAY
JUL
In
In
-
MOLD BOARD
OPTION 2
OPTION 3
CHISEL
HERBICIDE
SPRAY
DISK
HERBICIDE
SPRAY
CULTIVATE
CULTIVATE
-
CULTIVATE
CULTIVATE
CULTIWEED
-
SWEEPPLOW
CULTIVATE
CULTI WEED
CULTIWEED
-
CULTIWEED
CULTIWEED
FERTILIZER
APPLICATION
CULTIWEED
DRILL SEED
HERBICIDE
SPRAY
HARVEST
CULTI WEED
CULTI WEED
CULTI WEED
FERTILI ZER
CULTI WEED
CULTI WEED
FERTILI ZER
APPLICATION
APPLICATION
CULTIWEED
DRILL SEED
HERBICIDE
SPRAY
HARVEST
CULTI WEED
DRILL SEED
HERBI CIDE
SPRAY
HARVEST
OPTION 4
OPTION 5
DISK
BURN RESIDUE
DISK
CHISEL CHOPPER
DISK
CULTIWEED
CULTI WEED
In
CULTI WEED
CULTI WEED
Yrl
Yr2
Yr2
CULTIWEED
FERTILIZER
CULTIWEED
APPLI CATI ON
APPLICATION
CULTI WEED
CULTI WEED
DRILL SEED
HERBICIDE SPRAY
HARVEST
DRILL SEED
HERBICIDE SPRAY
HARVEST
Ynl
Yr2
Yr2
Yr2
Yr2
CULT I WEED
FERTILI ZER
The tillage systems are denoted in the text, respectively,
as MBB, CHB, DIB, DIBB, DICHB; B stands for Spring barley
cropping.
91
Table (5.3a):
Crop
Summer Fallow-Winter Wheat, Standard Tillage
Option--Rjtzvjlle and Pilot Rock Soils.
Month Year
Tillage Alternatives
OPTION 11
SEP
FALLOW
YEAR
CROP
YEAR
FALLOW
YEAR
MAR
MAR
MAY
MAY
MAY
YrO
In?
In
Ynl
Yrl
Ynl
JUN
JUN
JUL
In
In?
Yrl
AUG
SEP
SEP
FEB3
FEB
Yrl
Yrl
Yrl
Yrl
Yr2
JUL
Yr2
SEPT
MAR
MAR
MAY
MAY
JUNE
JUNE
YrO
Yrl
Yrl
In
Ynl
Yrl
Ynl
JULY Yrl
CROP
YEAR
-
HERBICIDE SPRAY2
-
SWEEPPLOW
JUL
Yr2
SWEEPPLOW
SWEEPPLOW
CULTI WEED
-
FERTILIZER
APPLICATION
FERTILI ZER
APPLICATION
CULTI WEED
-
CULTI WEED
CULTIWEED
-
DRILL SEED
HERBICIDE SPRAY
FERTILIZER
APPLICATION
HARVEST
DRILL SEED
HERBICIDE SPRAY
FERTILIZER
APPLICATION
HARVEST
OPTION 31
OPTION 4
HERBICIDE SPRAY2
CHISEL
HERBICIDE SPRAY
SWEEPPLOW
CULTIWEED
FERTILIZER
APPLICATION
CULTIWEED
AUG
SEP
Ynl
Yrl
SEP Ynl
FEB3 Yr2
FEB Yr2
OPTION 21
DRILL SEED
HERBICIDE SPRAY
FERTILIZER
APPLICATION
HARVEST
SWEEPPLOW
CULTIVATE
CULTIWEED
CULTIWEED
CULTIWEED
DRILL SEED
HERBICIDE SPRAY
FERTILI ZER
APPLICATION
HARVEST
The tillage systems are denoted,respectively, as SPRW, SWPW,
SSCUW AND CHIW. W stands for Winter wheat.
1Options 1, 2,
and 3 are reduced tillage practices. 2Round up herbicide
5spray FINESE + MCPA
92
Table (5.3b):
Crop
Sununer Fallow-Spring Barley, Standard Tillage
Options--Ritzville and Pilot Rock Soils
Month Year
Tillage Alternatives
OPTION 1
SEP
FALLOW
YEAR
CROP
YEAR
JUN
JUN
JUL
YrO
Yrl
Yrl
Yrl
Yrl
Yrl
Yrl
Yrl
AUG
MAR
APR
Yrl
Yr2
Yr2
CULTI WEED
APR
APR
MAY
JUL
Yr2
Yr2
Yr2
Yr2
CULTI WEED
MAR
MAR
MAY
MAY
OPTION 2
-
HERBICIDE SPRAY
SWEEPPLOW
SWEEPPLOW
SWEEPPLOW
CULTIWEED
CULTIWEED
CULTIWEED
FERTILIZER
APPLICATION
DRILL SEED
HERBICIDE SPRAY
HARVEST
CULTIWEED
CULTIWEED
FERTILI ZER
APPLICATION
CULTIWEED
DRILL SEED
HERBICIDE SPRAY
HARVEST
OPTION 3
MAR
MAR
MAY
MAY
JUN
JUN
JUL
YrO
Yrl
Yrl
Yrl
Yrl
Yrl
Yrl
Yrl
CHISEL
HERBICIDE SPRAY
AUG
MAR
APR
Yrl
Yr2
Yr2
CULTI WEED
APR
APR
MAY
JUL
Yr2
Yr2
Yr2
Yr2
SEP
FALLOW
YEAR
CROP
YEAR
-
SWEEPPLOW
CULTIVATE
CULTIWEED
-
CULTIWEED
FERTILIZER
APPLICATION
CULTIWEED
DRILL SEED
HERBICIDE SPRAY
HARVEST
The tillage systems are denoted, respectively, as SPRB,
SWPB, AND CHIB. B is Spring barley cropping.
93
Table (5.4):
Crop
Winter Wheat-Green Pea, Standard Tillage
Options--Athena Soil.
Month
JUL
JUL
AUG
WINTER
WHEAT
YrO
YrO
YrO
Tillage Alternatives
OPTION 1
OPTION 2
OPTION 3
CHISEL
CULTIVATE
DISK
CULTIVATE
DISK
CHISEL
SEP
YrO
FERTILIZER
APPLICATION
OCT
OCT
FEB
MAR
YrO
YrO
Yrl
Yrl
CULTI WEED
MAR
GREEN
PEA
Year
Yrl
JUL
Yrl
AUG
AUG
SEP
Yrl
Yrl
Yrl
OCT
NOV
Yrl
Yrl
NOV
FEB
MAR
MAR
Yrl
Yr2
Yr2
Yr2
APR
Yr2
APR
Yr2
APR
APR
JUN
Yr2
Yr2
Yr2
DRILL SEED
HERBICIDE
SPRAY
FERTILIZER
APPLICATION
HARVEST
DISK
CULTIVATE
FERTILIZER
APPLICATION
MOLD BOARD
FERTILI ZER
FERTILI ZER
APPLICATION
CULTIVATE
APPLICATION
CULTIVATE
HARROW
DRILL SEED
SPRAY HERB
CULTIVATE
DRILL SEED
SPRAY HERB
FERTILI ZER
APPLICATION
FERTILI ZER
HARVEST
DISK
CULTIVATE
FERTILIZER
APPLICATION
CULTIVATE
APPLICATION
HARVEST
HARROW
DISK
FERTILI ZER
APPLICATION
MOLDBOARD
CULTIVATE
CULTIVATE
CULTIVATE
FERTILI ZER
HERBICIDE
SPRAY
FERTILIZER
APPLICATION
CULTIVATE
DRILL SEED
HARVEST
HERBICIDE
SPRAY
APPLICATION
DRILL SEED
FERTILI ZER
APPLICATION
HARROW
DRILL SEED
HARVEST
PACK
HARVEST
The tillage systems are denoted, respectively: as CHIMBD,
DICUL AND DISMBD.
94
To minimize excessive evaporation and soil loss, farmers in
the study area combine burning with other tillage
operations; that is, they incorporate some residues into the
soil before the field burning (Wysocki and Veseth, 1991).
Reduced or minimum tillage operations, disturb the soil
less and maintain at least 30% of crop residues on the soil
surface.
This tillage regime reduces erosion by about 36
percent (Waddell and Bower, 1988).
Aside from standard
tillage practices, divided slope and strip-crop practices
are used in some areas.
Standard practice is a tillage system that does not
Divided
involve any structural method of soil conservation.
slope involves dividing a short, steep-sloped farm into two
(across the slope).
One half is planted into close-growing
crops, such as wheat, the other half is fallowed or planted
into another crop that provides less protection from
erosion,
Strip-cropping involves dividing a long, steep-
sloped farm into several strips.
The strips are planted
into crops of high and low level of erosion protection, or
fallow, alternating with crops providing soil erosion
protection.
Divided slope and strip crop practices are...
"used to better manage land to reduce erosion on long, steep
slopes.
They reduce soil losses 50 to 75 percent, depending
on slope length and steepness" (McDole, 1984) p.1.
The
choice of a tillage system often depends on production
costs, and the decision concerning choice of soil
95
conservation method is influenced by the product price
(Walker, 1982)
Fertilizer application rates and timing strategies vary
from farmer to farmer.
The decision is often based on
expected weather, type of crop, rotational system, soil NO3N test and knowledge of field history.
Most growers (about
80%) in the area prefer pre-plant application only, while
very few (about 20%) practice split application21.
The
common fertilizer application rate-timing combinations
options for each tillage practice on the soils are shown in
Table (5.5).
In Table (5.5a), the options are denoted in
the analysis, respectively, as F1W, F2W, F3W, F4W, F5W and
F6W.
W indicates Winter wheat cropping.
F1W is the most
common option on moderate to deep soils and F3W is usually
practiced on shallow soils.
F6W is practiced in conjunction
with soil (nitrogen) test.
Alternative Production Strategies
Alternative production strategies (activities),
involving combinations of tillage system, fertilizer
application rate and timing, were examined under weather and
soil slope scenarios.
Ten crop-weather years--August 1982
to July 1992--and field slope categories 0 to 7 and 7 to 12
percent were considered in this study.
21
growers.
Personal
communication with the panel
of
grain
96
Table (5.5a):
Fertilizer Timing-Application Rates on Summer
Fallow-Winter Wheat, all Tillage Systems-Walla Walla Soil.
OPTION 1
APPLY FERT: PRE-PLANT/SPRING
ANNT APPLY: llO#(SPLIT 80/1,30/I)
OPTION 3
FERT APPLY: PRE-PLANT/SPRING
ANNT APPLY: lOO#(SPLIT 50#, 50#)
OPTION 5
FERT APPLY: PRE-PLANT/SPRING
AMNT APPLY: 95#(SPLIT 65#,30#)
Table (5.5b):
OPTION 2
PRE-PLANT/ SPRING
95#(SPLIT 30#,65#)
OPTION 4
APPLY SPRING
110#
OPTION 6
PRE-PLANT ONLY
80/I
Fertilizer Timing-Application Rates Summer
Fallow-Winter Wheat, all Tillage Systems-Pilot Rock and Ritzville Soils.
OPTION 1
APPLY FERT: PRE-PLANT/SPRING
ANNT APPLY: 55#(SPLIT 40#,15#)
OPTION 3
FERT APPLY: PRE-PLANT/SPRING
ANNT APPLY: 50#(SPLIT 25#, 25#)
OPTION 5
FERT APPLY: PRE-PLANT/SPRING
ANNT APPLY: 50#(SPLIT 35#,15#)
OPTION 2
PRE-PLANT/ SPRING
50/I (SPLIT 15#,35#)
OPTION 4
APPLY SPRING
55#
OPTION 6
PRE-PLANT ONLY
4 0#
Options are denoted in the analysis, respectively, as: F1W,
F2W, F3W, F4W, F5W and F6W. W denotes Winter wheat
cropping.
97
Table (5.5c):
Fertilizer Timing-Application Rates Summer
Fallow-Spring Barley, all Tillage Systems-Ritzville, Pilot Rock and Walla Walla Soils.
OPTION 1
FERT APPLY: PRE-PLANT
ANNT APPLY: 25#
OPTION 2
OPTION 3
PRE-PLANT
45#
PRE-PLANT
65#
Options are denoted, respectively, as: FiB, F2B, and F3B.
B denotes Spring barley cropping.
Table (5.5d):
Fertilizer Timing-Application Rates Winter
Wheat-Green Pea Rotation, all Tillage
Systems--Athena Soil.
OPTION 1
FERT APPLY: PRE-PLANT (WW, GP)
ANNT APPLY: 60/I (WW), 25/I (GP)
OPTION 2
PRE-PLANT (WW)
60# (WW), 0/I (GP)
OPTION 3
FERT APPLY: PRE-PLANT (WW); PRE-PLANT/SPRING (GP)
AMNT APPLY: 90/I (WW);
lO0# ANMONIUN SULPH, 25# N (GP)
OPTION 4
FERT APPLY: PRE-PLANT/SPRING (WW, GP)
ANNT APPLY: 60/I, 30/I (WW); 100/I ANMONItJM SULPH, 25# N (GP)
Options are denoted, respectively, as: Fl, F2, F3, and F4.
WW denotes Winter wheat and GP represents Green peas
cropping.
98
The average slope in each category, that is, 3.5 and 9.5
percent, were used to represent each category in this study.
The proportion of an acre in a slope category on each soil
was assumed equal to the ratio of land area under that slope
type to total land area in both 0 to 7 percent and 7 to 12
percent slopes.
Fields with more than 12 percent slope were
not considered because land in this slope category is used
mostly as rangeland (USDA, 1988).
Weather data used were daily rainfall, average monthly
temperature and pan evaporation (see Appendix A).
These
weather data were from stations located on or near each soil
type22.
Weather data for Ritzville and Athena soils were
from Moro and Pullman respectively; weather data for the
Pilot Rock soil were from Pilot Rock weather recording site
and data for scenarios on Walla Walla soil were from the
Columbia Basin Agricultural Research Center.
These data
were compiled from the Climatological Data Bulletin of
Oregon, a monthly publication of the National Oceanic and
Atmospheric Administration.
Given the weather years and slope types, 90 Summer
fallow-winter wheat and 45 Summer fallow-spring barley
production alternatives on Walla Walla soil type were
investigated.
On Pilot Rock and Ritzville soil types, 72
22Where
data
are
unavailable
or
are
missing,
information from the nearest weather station were used.
99
Summer fallow-winter wheat and 27 Summer fallow-spring
barley production techniques were examined.
On Athena soil,
36 Winter wheat-green pea production options were analyzed.
Soil Loss Estimation--The Universal Soil Loss Ecivation
(USLE)
The USLE (as given in equation 4.1) consists of six
factors.
In this section, each factor is explained and
values reported for each alternative management practice.
R Factor
The R factor (rainfall erosivity) is an indicator of
rainfall energy available, at a particular site, to cause
Of critical importance is the rate or intensity of
erosion.
the applied energy (Wysocki, 1987).
The R factor values
used in this study reflect interrill erosion, gully erosion,
winter conditions--precipitation, frozen soil, low
infiltration--and occasional spring and summer thunderstorms
that influence erosion on summer fallow.
The value is
calculated from:
R
= - 71.97 + 10.31 (Pr) - 0.1881 (Pr)2
R
= annual erosivity,
(5.1)
where
Pr
(lO
of ft_toni-inch)
acre. hr.yr
annual precipitation, inches
Using equation (5.1) and rainfall data from the weather
sites, the Pr and R values are as presented in Table (5.6):
100
Annual Precipitation (Pr), and Associated
Erosivity (R) Factors for the Columbia
Plateau, 1982-1991.
Table (5.6):
Pendleton
Exp. Stat.
Year
(Pr)' (R)'
1982/83
1983/84
1984/85
1985/86
1986/87
1987/88
1988/89
1989/90
1990/91
1991/92
23.74
21.73
14.87
16.37
16.23
13.02
17.03
13.14
16.87
13.59
Pul livan
Pilot Rock
Moro
(Pr)
66.78
63.25
39.75
46.40
45.81
30.38
49.06
31.03
48.43
33.40
(Pr)
(R)
(R)
19.64 57.96
16.93 48.66
10.61 16.24
14.11 36.05
12.15 5.53
11.43 21.30
12.98 30.16
7.55 -4.85'17.45 50.66
10.02 12.45 14.69 38.89
11.41 21.18 10.51 15.61
17.53
13.48
8.86
11.15
11.04
10.96
9.26
50.96
32.83
4.61
19.60
18.95
18.43
7.37
Exp. Stat.
(Pr)
(R)
25.35
23.65
17.88
20.01
19.50
16.16
19.20
23.37
21.24
15.63
68.51
66.65
52.24
59.02
57.55
45.52
56.64
66.24
62.16
43.22
/ Pr is annual precipitation, inches.
b/ R is the annual rain erosivity factor,
(100 of ft-tonf -inch)
acre.hr.yr
c/ Value of 0 was used for the analysis
LS factor
The influence of slope length and steepness are
combined into a single factor, LS.
The LS values developed
and shown below follow the research work of McCool, (1982);
and NcCool and George, (1983):
The slope length-steepness factor LS (McCool, 1982) is
of the form:
LS =
(5.2)
(
)m* (
22.13
sinO
sin 5.1430
)fl
101
where LS is slope length-steepness factor relative to a
22.13 neters slope length on a uniform 9
percent (5.143°) slope,
A is horizontal slope length (in meters),
0 is slope steepness (in degrees),
m and n are exponential constants.
From equation (4.1),
(5.3)
A
K*C*P
R*LS
Substituting equation (5.2) into (5.3) yields
(5.4)
A
KCP
A
)( sinO
-R( 22.13
sin 5.143°
'
taking the logarithm of both sides of equation 5 yields
(5.5)
in
KCP
- in
R + m in
A
22 .
13
+
in
sinO
sin 5. 143°
McCool and George used data from Palouse, Northcentral
Oregon and Southeastern Idaho to fit equation (5.5).
resulting values,
in =
0.5
The
and n = 0.7, were stated to be
applicable to all slopes in the dryfarined cropland of the
northwest region (McCool and George, 1983).
Equation (5.2) becomes
102
(5.6)
A
LS=
)O.5
22.13
(
sinO
)O.7
sin 5.143°
The LS values used in this study are as in Table (5.7);
other LS values for the study area are shown in Table (B.2)
in Appendix (B).
LS Values used in the Analysis.
Table (5.7):
Slope Length (ft)
3.5 Percent Slope
9.5 Percent Slope
100
0.61
1.22
300
1.05
2. 11
600
1.49
2.98
The C Factor
Computing the general C factor associated with each
crop rotation and tillage system requires a knowledge of:
(1) the historical average crop yield on the soils (see
Table 5.1),
(2) the amount of residue produced by the crop
after harvest,
(3) surface residue retention of a tillage
system, and (4) percent residue and ground cover.
Estimates
of residue production by crop yield and residue retention by
management practice are shown in Tables (5.8) to (5.10)
103
below.
After obtaining an estimate of residue retained for
a tillage system, the C factor is read of f a corresponding
chart in Figures (5.2) to (5.4)23
The C factors obtained in this manner are for normal
crop growing condition and not site specific.
McCool
suggested that the C factor should reflect in the USLE site
conditions such as: soil structure, clod, pressure pan, plow
pan, and tillage system.
He developed multipliers for the C
value in order to make it a more site specific factors,
making possible the use of TJSLE in the Pacific Northwest.
Details of the multipliers are provided in Appendix (B).
Table (5.8):
Estimated Residue Production'
Pounds of Residue per Unit of Yield
80
70
1.0
.85
.85
.85
40
Winter Wheat
Spring Wheat
Winter Barley
Spring Barley
Spring Peas
Lentils
Oats
-
110
100
1.7
1.5
1.4
1.4
60
lbs/bu.
lbs/bu.
lbs/lb.
lbs/lb.
lbs/lb.
lbs/lb.
lbs/bu.
a/ Amount of residue produced by a crop depends on yield per
acre, timing and amount of precipitation, temperature,
stored soil water, soil depth, variety and pest problems.
Source: Small Grain Residue in the Pacific Northwest. In:
Residue Management Guide.
are from Akbari, (5.4) is from
the state Natural Resource Conservation Service office; C
value for spring grain (spring barley) was suggested for
23Figures
green pea.
(5.2)-(5.3)
104
Table (5.9):
Estimated Residue Retention for Common Tillage
Operations/
Operation
Chaff and Awn deduction
Over-winter Residue decomposition
Burning
Tandem disc, one-way & offset
4" - 6" deep
6" + deep
4" deep, pea, bean, lentil residue
Chisel Plow
straight points, 12-inch spacing
straight points, 18-inch spacing
twisted points, 18-inch spacing
Moldboard Plow
8"+deep
% Residue Remaining
70
70 - 80
20
60 - 75
40 - 60
10 - 30
70 - 80
75 - 85
50 - 70
0-15
20 - 30
6" - 8" deep no trash boards
30 - 40
uphill furrow, 6-8 inches deep
45 - 65
Chisel-disc or cultimulcher
Secondary Tillage
75 - 85
field cultivator
75 - 85
16-inch sweep with shovels
field cultivate with sweeps, 8
100 -120
inches deep after moldboard plow
85 - 95
rodweeder
75 - 85
rodweeder with sweeps
80 - 90
harrow, 10 bar spike
85 - 95
harrow, 10 bar tine
Drills
80 - 90
double disc
75 - 85
double furrow or hoe
75 - 90
no-till, light double disc
50 - 75
no-till, heavy double disc
no till, heavy double disc, pea,bean,
30 - 50
and lentil residue
50 - 75
chisel point or air seeder
Fertilizer and Herbicide Application
80 - 90
fertilizer shank applicator
100
herbicide application
40 - 80
Grazing stubble
a/ For spring grain, spring pea and lentil residues which
are less resistant to tillage and disappear rapidly, select
lower residue retention value in the table.
Source: Small Grain Residue in the PNW. In: Residue
Management Guide.
105
Table (5.10):
Conversion--Percent Cover to Pounds Residue
for Wheat, Barley, Oats and Peas.
Percent Residue Cover
10%
15%
20%
25%
30%
35%
40%
45%
50%
55%
60%
65%
70%
75%
80%
85%
90%
95%
Pounds Residue
164
252
346
446
554
669
793
928
1076
1239
1384
1629
1868
2151
2498
2944
3773
4649
Source: Small Grain Residue in the Pacific Northwest. In:
Residue Management Guide.
:_
C Factor
1.
.5OI1__
Primary Till Fall
0
Till Spring
.40
A
.35
iii.
.30
No Till
.25
.20
.15
I iI!T
.00
0
500
1000
1500
2b00
2500
3000
3500
4000
Pounds of Residue Per Acre After
Seeding
Figure (5.2):
"C" Factors for Fallow-Winter Wheat,
Columbia
Plateau, 15-25% Winter Vegetation
by Dec. 1.
4500
C Factor
.40
.35
.30
Priirary Till Fall
0
.25
Till Spring
A
.20
No Till
.15
.10
.05
.00
0
500
1000
1500
2000
2500
3000
3500
4000
Pounds of Residue Per Iore After Seeding
Figure (5.3):
"C" Factors for Fallow-Winter Wheat,
Columbia
Plateau, 50% Winter Vegetatjo
by December i.
4500
108
C Factor
0.60
0.4
0.20
0.10
0.00
0
.
250
500
750
J
1000
1250
1500
Pounds of Residue Per Acre After
Dec 1.
Figure (5.4):
"C" Factors for Fallow-spring Grain,
Less than 15% Green Vegetation by
Dec. 1.
Source: USDA-SCS Heppner Field Office.
109
K and P Factors
The K- (soil erodibility) factor measures soil's
susceptibility to erosion; its value indicates soil loss
rate per unit of R factor.
A soil with K of 0.37 loses soil
at a rate of 0.37 tons per unit of R.
The P-factor
(supporting conservation) measures the influence of
conservation practices such as divided slope, strip cropping
and cross slope farming.
Standard practice without
conservation practices is assigned a value of 2. (Wysocki,
1987).
The K- and P-factors for Columbia Plateau, Oregon,
are in Tables (B.].) and (B.4) in Appendix (B).
A summary of
the USLE factors used in this analysis is presented in Table
(5.11) below:
Conversion of soil loss to Yield loss
When soil is eroded, soil depth decreases.
Over time,
this soil loss translates into productivity decline.
Given
an initial or current average topsoil depth and average
annual soil loss rate from a particular set of management
practices, an associated yield loss can be computed using
the soil depth-yield functional relationship.
The value of
soil loss, from a tillage system, is obtained by multiplying
the resultant yield loss by the average crop price.
110
Table (5.11):
USLE--K, LS, C, P--Factors
Tillage Systems
3.5% Slope
1
K
LS
2
3
4
0.37 0.37 0.37
1.49 1.49 1.49
LS/l.05 1.05 1.05
LSb/0.6]. 0.61
0.20 0.18
1.00 1.00
0.44 0.44
ATHENA C
WW-GP P
Pa/
Pb/
0.61
0.21
1.00
0.44
0.38 0.38 0.38
K
0.43 0.43 0.43
PILOT- LS 1.49 1.49 1.49
ROCK
LSa/1.05 1.05 1.05
SF-WW LSb/0.61 0.61 0.61
C
0.10 0.10 0.10
P
1.00 1.00 1.00
Pa/ 0.44 0.44 0.44
P/ 0.38 0.38 0.38
K
0.43
PILOT- LS 1.49
ROCK
LSa/1.05
SF-SB LSb/0.61
C
0.24
P
1.00
0.43
1.49
1.05
0.61
0.24
1.00
0.43
1.49
1.05
0.61
0.24
1.00
P/ 0.44 0.44 0.44
Pb/ 0.38 0.38 0.38
0.43
1.49
1.05
0.61
0.21
1.00
0.44
0.38
Tillage Systems
9.5% Slope
5
1
2
3
0.37
2.98
2.11
1.22
0.20
1.00
0.52
0.45
0.37
2.98
2.11
1.22
0.18
1.00
0.52
0.45
0.37
2.98
2.11
1.22
0.21
1.00
0.52
0.45
0.43
2.98
2.11
1.22
0.10
1.00
0.52
0.45
0.43
2.98
2.11
1.22
0.10
1.00
0.52
0.45
0.43
2.98
2.11
1.22
0.10
1.00
0.52
0.45
0.43
2.98
2.11
1.22
0.24
1.00
0.52
0.45
0.43
2.98
2.11
1.22
0.24
1.00
0.52
0.45
0.43
2.98
2.11
1.22
0.24
1.00
0.52
0.45
4
5
0.43
2.98
2.11
1.22
0.21
1.00
0.52
0.45
/LS (300 ft slope length) and P Values--Divided Slope
Farming System.
/LS (100 ft slope length) and P Values-Strip Cropping Farming System.
111
Table (5.11) Continued:
USLE--K, LS, C, P--Factors
3.5% Slope
Tillage Systems
1
K
RITZVILLE
S F-WW
2
3
4
0.43 0.43 0.43 0.43
LS 1.49 1.49 1.49 1.49
LSa/1. 05 1.05 1.05 1.05
LSb/0. 61 0.61 0.61 0.61
C
0.10 0.10 0. 10 0. 18
P
1.00 1.00 1.00 1.00
P/ 0.44 0.44 0.44 0.44
P/ 0.38 0.38 0.38 0.38
K
0.43
RITZLS
1.49
VILLE LS/1. 05
SF-SB LS/ 0. 61
C
0.24
P
1.00
0.43
1.49
1.05
0.61
0.24
1.00
0.43
1.49
1.05
0.61
0.25
1.00
P/ 0.44 0.44 0.44
P/ 0.38 0.38 0.38
9.5% Slope
Tillage Systems
5
1
2
3
4
5
0.43 0.43 0.43 0.43
2 . 98 2.98 2.98 2.98
2. 11 2.11 2.11 2 . 11
1.22
0.10
1.00
0.52
0.45
1.22
0.10
1.00
0.52
0.45
1.22
0.10
1.00
0.52
0.45
1.22
0.18
1.00
0.52
0.45
0.43 0.43 0.43
2.98 2.98 2 .98
2. 11 2. 11 2. 11
1.22
0.24
1.00
0.52
0.45
1.22
0.24
1.00
0.52
0.45
1.22
0.25
1.00
0.52
0.45
K
0.43 0.43 0.43 0.43 0.43 0.43 0.43 0.43 0.43 0.43
WALLA- LS 1.49 1.49 1.49 1.49 1.49 2.98 2.98 2.98 2. 98 2.98
WALLA LSa/1.05 1.05 1.05 1.05 1.05 2 . 11 2.11 2 . 11 2. 11 2.11
SF-WW LSb/0.61 0.61 0.61 0.61 0.61 1.22 1.22 1.22 1.22 1.22
C
0.30 0. 12 0. 19 0.36 0.21 0.30 0.12 0.19 0.36 0.21
P
1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
Pa/ 0.44 0.44 0.44 0.44 0.40 0. 52 0.52 0.52 0.52 0.52
P/ 0.38 0.38 0.38 0.38 0.30 0.45 0.45 Ô. 45 0.45 0.45
K
0.43 0.43 0.43 0.43 0.43 0.43 0.43 0.43 0.43 0.43
WALLA- LS 1.49 1.49 1.49 1.49 1.49 2.98 2.98 2.98 2.98 2.98
WALLA LSa/1.05 1.05 1.05 1.05 1.05 2.11 2. 11 2 . 11 2. 11 2.11
SF-SB LSb/0.61 0.61 0.61 0.61 0.61 1.22 1.22 1.22 1.22 1.22
C
0.70 0.37 0.46 0.74 0.50 0.70 0.37 0.46 0.74 0.50
P
1.00 1.00 1.00 1. 00 1.00 1.00 1.00 1.00 1.00 1.00
P/ 0.44 0.44 0.44 0.44 0.44 0.52 0.52 0.52 0.52 0.52
P/ 0.38 0.38 0.38 0.38 0.38 0.45 0.45 0.45 0.45 0.45
/LS (300 ft slope length) and P Values--Divided Slope
system. k/LS (100 ft slope length) and P Values for Strip
Crop farming system.
112
The soil loss rate obtained from USLE was converted
from tons/acre to inches/acre using the following method:
At = A/W,
(5.7)
where At is soil loss in inches per acre,
A
is soil loss in tons per acre (from USLE),
W
is weight of an acre-inch of soil.
W was obtained using the soil's moist bulk density (USDA,
1988)
Athena soil: 1.20 grams/cc = 136 tons/ac-in;
Pilot rock:
1.40 grams/cc = 163 tons/ac-in;
Ritzville:
1.20 grams/cc = 136 tons/ac-in;
Walla Walla: 1.20 grams/cc = 136 tons/ac-in.
The soil depth, in inches, was applied to the soil depthcrop yield relationship, developed by Walker and Young
(1986), to obtain estimates of yield loss.
The soil depth-
crop yield relationship used were as follows:
Winter-Wheat
Y = 36.44 + 47.Ol(l_e_9B64(Dtt))
(5.8)
where
I
is yield in bu./ac,
Dt
is beginning topsoil depth in year t,
At
is average annual soil loss (in inches) in
year t,
t =
01,2,...T years; t=0 is the start of this
analysis. Dt=Do, and At=0.
113
The ntode1 was evaluated given initial average topsoil depth
of 10, 9, 16 and 22 inches, for Pilot Rock, Ritzville, Walla
Walla and Athena soils respectively, (see Table 5.1); yields
of 65.92, 64.10, 73.75 and 78.08 bushels per acre were
obtained.
The historical average winter wheat yield
corresponding to these soils, respectively, are 40, 50, 75
and 95 bushels per acre (see Table 5.1).
It was necessary
to calibrate this equation, to reflect Umatilla county wheat
yield.
(5.9)
The yield models became:
Y
22.11 + 28.53(l_e 09864(DtAt))
(Pilot rock soil)
(5.10) Y
28.42 + 36.67(l_eO9B64(Dtt)) (Ritzville soil)
(5.11) 1
37.06 + 47.8l(l_e 09864(DtAt))
(5.12) 1
42.05 + S4.00(l_eO98G4(Dtt)) (Athena soil)
(Walla Walla soil)
Spring Barley
The topsoil depth-yield relationship for spring barley
(Bauer, 1984) is:
(5.13)
1t = 28.34 + 29l9(l...9(Dt_At))
For beginning average topsoil depth of 10, 9, and 16 inches
for Pilot rock, Ritzville, and Walla Walla soils,
respectively, yields of 47.35, 46.22 and 52.12 bushels per
acre were obtained.
The historical average spring barley
yield corresponding to the soils, are 63, 73 and 83 bushels
per acre (calculated at 48 lbs./bu, see Table 5.1).
It was
114
also necessary to calibrate this equation to Umatilla county
spring barley yield.
The yield-depth projection models
become:
(5.14)
It =
(5.15)
Y
= 44.76 + 46.lO(l._.9(1t_?t))
for Ritzville soil
(5.16)
1
= 45.13 + 4648(l_9(Dt_At))
for Walla-Walla soil
37.71 + 38.84(l._.g(Dt_At))
for Pilot rock soil
Pea
The yield-topsoil depth relationship for Green pea
(Walker and Young, 1986) is:
(5.17)
I = 6.96 + l5.O3(l_e356l(Dtt))
Given beginning topsoil depth of 22 inches on Athena soil,
21.98 cwt. per acre crop yield was obtained.
The historical
average green pea yield is 20 cwt. per acre.
Multiplying
equation (5.17) by 0.9097 generated the calibrated yield
projection model:
(5.18)
1 = 6.33 + l3.67(l_e3567(Dtt))
In this study, the present value of yield loss over a
25-year planning horizon, at 6 percent real rate of
interest, was computed for each of the 10-crop years.
These
values were used to represent the on-site cost of soil loss.
A 25-year time horizon was assumed as the economic
productive life of a soil24.
Other assumptions were:
(1)
24 Soil productivity can, of course, extend beyond 25
years but its value after discounting is small enough that
it can be ignored in an analysis.
115
that soil was removed uniformly over the field by erosion
and was not redeposited on the farm; (2) the rate of soil
regeneration was not significant; and (3) technology
remained constant over the study period.
The calculation is
as follows:
25
(5.19)
1
Pc*c
(1 +
where:
D is cost of erosion damage ($/ac/yr)
is crop price ($/bu)
C is crop yield loss (bu/ac)
r is real interest rate.
Budgeting
Budgets were estimated by soil type for each crop and
production technology.
Each
budget (estimated on per acre
basis) is composed of gross revenue, total cost and net
return.
The gross revenue consists of revenues from crop
sale plus deficiency payments (where applicable).
Total
cost is sum of the variable and fixed costs incurred in the
fallow and crop years.
Variable costs vary according to the level of
production.
The variable costs were itemized according to
farm operations and various stages of production--summer
fallow, crop production, harvesting and marketing.
For each
operation, costs include payments for labor, machinery use,
and materials.
Owner and operator's labor was valued at
$9.00/hr, and hired labor at $8/hr.
Labor hours were
116
calculated based on machine hours times a multiplier (1.1 in
most cases), to account for setting up, adjustment and
putting away machinery and equipment.
Machinery costs
include payments for fuel, lubricants, repairs and
maintenance.
herbicides.
Materials include, seed, fertilizer and
Quantities and prices of these materials are
supplied for the cost calculation.
Interest on operating
capital at 6%25 was charged to reflect opportunity cost of
short-term capital investment in the crop production.
Fixed costs include machinery and equipment
depreciation, opportunity cost of capital investment, taxes
and insurance on equipments.
Fixed costs associated with
machinery were based on machinery value, age, annual use,
interest rate and use per acre.
A miscellaneous charge was added in the budget to
account for crop insurance, accounting fees, other machinery
and labor costs, and other expenses.
The before tax net
return, calculated as return to management, unpaid family
labor, overhead and land, was used as the objective function
value in the mathematical programming model.
Data input such as crop yield, input rates, and prices
were obtained locally from the committee of growers.
Machinery prices and other information were obtained from
25There
economists.
concensus
discount rate value among
It is suggested that private opportunity cost
of investment may serve as an upper bound, and return from
riskiess investments such as government bond could be used
as a lower bound (Castle et al., 1981).
is
no
117
published farm machinery and equipment guides, local dealer
and farm operators.
These are shown in Appendix D.
Details
of technical and cost calculation involved in the MBMS
program are contained in McGrann et al.,
(1986).
In developing the budgets, the following assumptions
were made:
The average farm sizes (see Table 5.1) were
2,000-acre farms on Walla Walla, Pilot Rock and Athena
soils and 2,500 acres for the farms on Ritzville soil.
Summer fallow (SF) represented 50% of total acreage on
Pilot Rock, Ritzville soil and Walla Walla soils.
Machinery was valued at new replacement price.
Each farm is owned, managed and operated by the
farmer (tJmatilla county farms typically are owner-
operator businesses).
Average crop prices (averaged over a 5-year period)
were used in calculating returns.
The farm owner participates in the government farm
programs for 1994, meeting the set-aside provisions
and receiving deficiency payments.
Nitrate Leached Estimation--The Nitrate Leaching and
Economic Analysis Package (NLEAP)
The NLEAP program required three pieces of information
to estimate NO3-N leached: (1) soil data;
and (3) on-farm management practices.
(2) climatic data
Pertinent soil data
for all US soil series are included with the program
118
software.
Specific soil data used in the analysis include
surface texture, hydrologic group, moist bulk density, water
holding capacity, and organic matter content.
This soil
information was modified to reflect site specific conditions
of the soils examined.
Climatic data used are the daily
precipitation, monthly average temperature and pan
evaporation (see Appendix B) for the study area.
The major
on-farm management practice data required are field soil
test information (including nitrate nitrogen), moisture
content of each foot of soil layer to a depth of 5 feet,
available moisture, and moisture content at wilting point.
Other on-farm management data include cropping history, type
and time of primary tillage, fertilizer rate and timing,
amount of residue buried in the soil, crop planting date,
expected crop yield under a range of weather conditions
(wet, dry and average) and other general site information
concerning the deep vadoze zone, watershed and underlying
aquifer.
Soil test data used are shown in Table (5.12).
NLEAP uses the data input to "develop a nitrogen budget
and water balance for the varying time increments" (Deichert
and Hainlett, 1992) p5.
The event-by-event-analysis approach
was followed in this study.
This method "uses event-based
time steps to calculate water and nitrogen budget, ...and
provides the most detailed analysis available in the NLEAP
model" (Shaffer, et al., 1991) p53.
To capture the impact
119
of crop rotations, the technique of sequential runs-discussed in the model review chapter--was implemented for
all scenarios investigated.
Table (5.12a):
Soil Test data for Athena and Pilot Rock
Soil
Depth
ATHENA
PILOT ROCK
(WW-GP)
(SF-WW)
Soils.26
(in.)
Moisture--in/ft
Moisture--in/ft
NO3-N
Lb/ac-ft
Total
Avail.
0-12
12-24
24-36
36-48
8-6O
1.22
1.27
1.40
1.32
1.51
0.42
0.42
0.50
0.32
0.31
12
rotal
6.72
1.97
32
9
6
2
3
Total
Avail.
NO3-N
Lb/ac-ft
2.24
1.92
1.75
1.39
1.07
0.90
16
13
13
5.91
3.36
42
26Soii, tests were taken in July of fallow year on Pilot
Rock, Ritzville and Walla Walla soils, and in July after pea
harvest on Athena soil.
120
Table (5.l2b):
Soil Test data--Ritzville and Walla Walla
Soils.
Soil
Depth
RITZVILLE
WALLA WALLA
(SF-WW)
(SF-WW)
(in.)
Moisture--in/ft
Moisture--in/ft
NO3-N
Lb/ac-ft
Total
Avail.
0-12
12-24
24-36
36-48
8-60
2.06
2.01
1.84
1.67
1.35
1.46
1.40
1.24
1.07
0.75
10
Potal
8.93
5.92
Table (5.12c):
NO3-N
Lb/ac-ft
Total
Avail.
4
2.33
2.24
2.18
2.21
2.09
1.63
1.44
1.33
1.31
1.09
4
2
5
6
35
11.05
6.80
24
5
9
7
7
Soil Test data, Summer Fallow-Spring Barley
--Pilot Rock, Ritzville, Walla Walla Soils.
Soil PILOT ROCK
Depth (SF-SB)
RITZVILLE
WALLA-WALLA
(SF-SB)
(SF-SB)
(in)
NO3-N
Moisture
(in/ft)
Total
Lbs/
ac-ft
NO3-N
Moisture
(in/ft)
Total Avail
Avail.
Lbs/
ac-ft
NO3-l'
Moisture
(in/ft)
Lbs/
ac-ft
Total Avail.
.
0-12
2.28
1.41
6
2.04
1.45
5
2.16
1.55
7
12-24
1.70
0.90
5
1.95
1.35
3
2.10
1.30
2
24-36
1.90
0.85
7
1.81
1.20
6
2.14
1.30
2
36-48
1.63
1.04
3
2.17
1.25
2
48-60
1.33
0.73
3
2.05
1.08
3
8.76
5.77
20
10.62
6.48
16
Total
5.88
3.16
18
121
The NLEAP output reports projected
N
budgets, potential
NO3-N leached below the root zone, potential off-site
effects of NO3-N leached and suggested changes in management
practices that may minimize NO3-N leaching.
Nitrate-Nitrogen (NO3-N) available for leaching (NAL) is
estimated by accounting for all nitrogen and sources:
Nplt -
(5.20)
NAL
= Nf + N
where:
NAL
is Nitrate-N available for leaching (lb/ac.)
Nf
is NO3-N in soil from fertilizer (lb/ac.)
+ Nrsd + N
-
Ndet
- Noth
is NO3-N from precipitation and irrigation
(lb/ac.)
Nrsd
is residual NO3-N in soil profile (lb/ac.)
N
is NO3-N from NH4-N nitrification (lb/ac.)
Nit
is NO3-N crop uptake (lb/ac.)
Ndet
is NO3-N lost to denitrification (lb/ac.)
Noth
is NO3-N lost to runoff and erosion (lb/ac.)
NO3-N leached from the top foot of soil (NL1), and beyond
the top foot to the bottom of root zone or root restricting
layer (NL2) are estimated as:
(5.21)
NL
= (NAL){1 - EXP[(-K)(WAL)/POR]},
I = 1,2.
where for example,
NL1
is NO3-N leached from soil top foot (lb/ac.)
NAL1 is NO3-N available for leaching from the top
foot (lb/ac.)
K
is leaching coefficient (unitless)
122
WALl is water available for leaching from the top
foot (in.)
POR1 is porosity of the top foot (in.)
NAL2 is obtained as above, using information from
from below the top foot to the bottom of root
root zone or root restricting layer.
Total NAL
is NAL1 + NAL2, the sum of NO3-N available
available for leaching in the root zone.
NAL values of 0 - 80 lb/ac are rated low, 80 - 160
lb/ac are rated moderate and above 160 lb/ac
are rated high.
The NO3-N (NL) leached beyond root zone is calculated as:
(5. 22)
NL
= (NAL) {l - EXP[(-K) (WAL)/POR2]}
NL
is NO3-N leached from the bottom of the root
where
zone (lb/ac.)
POR2 is porosity of the lower horizon (in.)
WAL
is water available for leaching from the
bottom of soil profile (in.)
Respectively, NL values of 0 - 40 lb/ac, 40 - 80 lb/ac,
and above 80 lb/ac are rated low, moderate and high.
The movement risk index (MRI) associated with leaching
of NO3-N is defined as:
(5.23)
NRI
= 1 - EXP[ (-K) (WAL) /POR1 + POR2)
3
123
MRI reflects general solute movement risks associated
with soil, climate and management conditions.
It measures
water management and climate impacts on general leaching;
that is, an indicator of the risk of NO3-N movement below
the root zone.
MRI values range between 0 and 1.
A value
of 0 indicates little or no risk, while a value equal to
1
indicates a high risk of all NO3-N available for leaching
(NAL) in the root zone moving out of the region.
The risk of moving recently leached NO3-N and deep
residual NO3-N in the vadoze zone out to an underlying
aquifer is estimated using information about the maximum
depth of water penetration below the root zone (ft)
(5.24)
Depth = WAL/AWHCa /12
AWHCa is water holding capacity of the material
underlying the root zone (in./in.); 12 is
conversion factor from inches to feet.
The potential effects of nitrogen leached (NL) on
groundwater depends on "NL travel time to aquifer, presence
or absence of confining layer, initial concentration of NO3N in aquifer, volume of water moving with the NL, volume and
quality of water moving into the aquifer and volume of water
moving out of the aquifer." (Shaffer et al., 1991) p294.
The impact of NL on groundwater is measured by the Aquifer
risk index (ARI) thus:
124
(5.25)
ARI
= 0.369 (N0 + (NL) (A)
where:
ARI
is
Aquifer risk index
N0
is
initial NO3-N content of AMV (lb.);
-N1J/AMV
value depends on initial NO3-N
concentration in the AMy (ib), surface
area of aquifer (acre), and thickness of
aquifer (ft)
N81
is
NO3-N entering AMy from sources outside
the field
N1
is
NO3-N leaving ANV (lb.)
ANV
is
Aquifer mixing volume (lb.)
An aquifer supplying drinking water (class I) with an ARI
value equal to or greater than 10 requires increased
monitoring.
Other aquifer classes are less susceptible to
the effects of NL (Shaffer et al., 1991).
Some assumptions were made in the program about the
soils under investigation.
These are presented in Table
(5.13).
Multi-Objective Programmincj
The non-inferior set estimation (NISE) algorithm of
Multi-Objective Programming (MOP) employed in this research
is a variant of the weighting technique.
The objective
functions were weighted to obtain a set of non-dominated
solutions.
This weighting technique is mostly applied to
problems involving two objectives.
125
Table (5.13):
Assumption made for the NLEAP Analysis, by
Soil Type.
Pilot Rock
Ritzville
Walla Walla
Soil Series
Silt Loam
Silt Loam
Silt Loam
Silt Loam
Soil Type
Condition
Homogenous
Homogenous
Homogenous
Homogenous
Hydrologic
Group
C
B
Athena
B
B
Drainage
Class
Well
Well
Well
Well
Landscape
Position
Sideslope
Sideslope
Sideslope
Summit
Slopes
3.5%, 9.5%
3.5%, 9.5%
3.5%, 9.5%
3.5, 9.5%
Underlying
Material
Alluvium
Bedrock
Bedrock
Loess
Depth to
Water Table
> 100 ft
> 100 ft
> 100 ft
> 100 ft
Water Flow
Restriction
None
None
None
None
28 inches
60 inches
60 inches
60 inches
Rooting
Depth
Restriction
The problem under study involves a simultaneous
minimization of soil erosion and NO3-N leaching, subject to
resource and net return constraints.
The problem
formulation is:
(la)
Maximize
(lb)
Minimize V = EE0 (Wh*Zhsc + We*Yesc),
r = E2E nr3,
126
EEnr'(sc)< 71,
X(sc)
0.
scO.
NH(SC) + TH(SC)
L.
71 is the net return associated with level of crop production
activity in solution.
V is the value of weighted objective
function; Z and Y are NO3-N leaching and soil erosion
objectives respectively; w and We are corresponding weights
or level of emphasis on the objectives; S is a vector of
alternative production strategies (combinations of tillage
system, fertilizer application rate and timing), associated
with per acre production of crop vector c.
winter wheat, spring barley and green peas.
The crops c are
NH(SC) and
TH(SC) represent acreages on 3.5 and 9.5% slopes.
The production strategies are differentiated by:
tillage system (j), erosion control practice (k), field
slope (1)
(a producer's acreages on a slope type is
proportional to overall soil type acreages on that slope),
and fertilizer application rate and timing (n); that is,
5j,k,1,n (see Table 5.1).
X
is a vector of pollutants
associated with per acre of crop c, using strategy S.
In
this study erosion and nitrate leaching are the pollutants
under consideration.
The vector nr represents net returns
(per acre total revenue, less cost of production and present
value of future yield loss resulting from soil loss)
associated with sc.
127
Constraint (2) restricts the net revenue from
activities in solution to values less than or equal to a
specified minimum level
it.
Constraints (3) and (4),
respectively, restrict the per acre production externality
level and acres of crops to values greater than or equal to
zero.
Constraint (5) restricts total acreages on both slope
types to a producer's average farm size.
The data were organized and computer analysis conducted
using the General Algebraic Modeling System (GANS) software.
GANS uses data entered in a summation notation format to
create a mathematical programming model, which is then
solved by one of several algorithms within GANS.
In
implementing the MOP, the net revenue objective function
(la) was maximized subject to unrestricted leachate and soil
loss levels (constraints 3 and 4), and producer's farm size
(constraint 5).
The solution identified optimal crop
production activities, soil loss and leaching rates, and
corresponding total net revenue.
This total net revenue was
represented as it° for the next step of the solution.
Next,
for a pre-specif led maximum level of total expenditure, P
on abatement of soil loss and NO3-N leaching, It in
constraint (2) was set equal to
it° -
P.
Following this
step, the objective functions in (ib) were individually
minimized, by setting
we = 1, Wh = 0 and We = 0, wh = 1,
subject to constraints (2) through (5).
The solution
obtained were crop production levels assuming all emphasis
128
was directed solely at minimizing, respectively, soil loss
and nitrate leachate.
The solutions yielded two points in
the objective space.
This problem solving procedure continued in an
iterative fashion by varying the value of P.
While holding
P at its current value, the weights Wh and We, were
parameterized (following the NISE technique in Cohon et al.,
1979) to obtain the efficient set of optimal production
strategies.
Solutions obtained at each iteration were
mapped out in the objective space, and the slope of a line
segment connecting two points was used to compute the
weights for the objective function in the next minimization
problem.
At each solution step, the algorithm minimizes the
error of approximation of the solution set; the procedure
continues until the maximum possible error in all parts of
the non-inferior set is as small as possible (Cohon,
1978).
The solution technique is enhanced by MOP's assumption
that the objective function is linear, and the
non-inferior
set of solution forms the boundary of a convex set of
feasible region (Cohon et al.,
1979).
The non-inferior set
estimation (NISE) method exploited these assumptions in
generating the assigned weights from the slopes of the
segments connecting extreme points (Romero et al.,
Cohon,
soils.
1978).
1987;
This solution procedure was applied to all
129
CHAPTER VI
RESULTS AND ANALYSES
This chapter focuses on the empirical results for the
study area and is divided into four sections.
Each section
focuses on the results and analysis of the models
corresponding to the USLE (soil loss estimation), MBMS
(production cost estimation), NLEAP (potential NO3-N
leached) and MOP (identification of optimal strategy)
models.
The final section, in addition to presentation and
discussion of the optimal production strategies, also
examines the tradeoffs between soil erosion and nitrate
leaching for the four soil types.
An important initial step in this type of research is
to validate the results, that is, compare the predicted
values with research findings or actual experience.
Validation is particularly important when using models to
predict environmental impacts.
The soil loss rates, and
potential NO3-N leached were examined by a group of research
scientists at the Columbia Basin Agricultural Research
center in Pendleton.
were
consistent
They concluded that soil loss rates
with research conducted on the different
soil types considered here.
Unfortunately, no known studies
in the Western U.S. have researched into Nitrate-N leaching
under non-irrigated conditions.
The group stated, however,
130
that leachate values obtained seemed reasonable,
particularly in making ordinal rankings among soils and
production alternatives.
Results of the USLE Model.
The Universal Soil Loss Equation (USLE) provided
estimates of soil loss rates (tons/acre/year) from current
and potential alternative tillage systems and practices on
Summer Fallow-Winter Wheat (SF-WW) and Summer Fallow-Spring
Barley (SF-SB) rotations on Walla Walla, Pilot Rock and
Ritzville soils; and on Winter Wheat-Green Pea (WW-GP)
rotation on Athena soils.
The estimates were obtained for
each of the 10-crop years; however, the analysis focused on
the 10-year average.
The tillage systems (see Table 5.2), average soil loss
rates and associated value of yield loss or cost of erosion
damage on each soil type are shown in Tables (6.1) to (6.4).
Detailed annual values are reported in Tables (C.l) (C.l2), Appendix C.
Abbreviations for tillage systems can
be found in Tables (5.2) - (5.4).
As expected, soil losses were much higher on steeper
slope (9.5 percent) fields.
More soil eroded on spring
barley fields as farms in (SF-SB) rotation are usually
fallowed longer, hence exposed to more weather events than
farms in (SF-WW) rotation.
The standard tillage practices
were generally most erosive on all soils, because they do
131
not involve mechanical techniques for retarding sediment
movement in soil erosion.
Soil loss rates from tillage
systems implementing soil conservation methods were
relatively much lower.
Table (6.1):
Estimated Average Soil Loss (Tons/ac/yr)1
Using Standard, Divided Slope, Strip Crop
Practices on (SF-WW) and (SF-SB) Rotations
--Walla Walla Soil.
SUMNER FALLOW-WINTER WHEAT (SF-WW)
3.5% SLOPE
TILLAGE
SYSTEMS
MB
CM
DI
DIB
DICH
STANDARD
8.73
3.49
5.53
10.48
6.11
DIVIDED
SLOPE
2.71
1.08
1.71
3.25
1.90
9.5% SLOPE
STRIP
CROP
STANDARD
1.36
0.54
0.86
1.63
0.95
17.46
6.99
11.06
20.96
12.22
DIVIDED
SLOPE
6.43
2.57
4.07
7.72
4.50
STRIP
CROP
3.22
1.29
2.04
3.86
2.25
SUMNER FALLOW-SPRING BARLEY (SF-SB)
MB
CM
DI
DIB
DICH
20.37
10.77
13.39
21.54
14.55
6.32
3.34
4.15
6.68
4.51
3.17
1.68
2.08
3.35
2.26
40.75
21.54
26.78
43.08
29.11
15.00
7.93
9.86
15.86
10.72
7.51
3.97
4.93
7.94
5.36
132
Table (6.2):
Estimated Average Soil Loss (Tons/ac/yr)1
Using Standard, Divided Slope, Strip Crop
Practices on (SF-WW) and (SF-SB) Rotations
---Pilot Rock Soil.
SUMMER FALLOW-WINTER WHEAT (SF-WW)
3.5% SLOPE
TILLAGE
SYSTEMS
SPR
SWP
SSCU
CHI
STANDARD
2.19
2.19
2.19
4.59
DIVIDED
SLOPE
0.68
0.68
0.68
1.42
9.5% SLOPE
STRIP
CROP
0.34
0.34
0.34
0.71
STANDARD
4.37
4.37
4.37
9.18
DIVIDED
SLOPE
1.61
1.61
1.61
3.38
STRIP
CROP
0.81
0.81
0.81
1.69
SUMNER FALLOW-SPRING BARLEY (SF-SB)
SPR
SWP
CHI
5.24
5.24
5.24
Table (6.3):
1.63
1.63
1.63
0.82
0.82
0.82
10.49
10.49
10.49
3.86
3.86
3.86
1.93
1.93
1.93
Estimated Average Soil Loss (Tons/ac/yr)1
Using Standard, Divided Slope, Strip Crop
Practices on (SF-WW) and (SF-SB) Rotations
---Ritzville Soil.
SUMMER FALLOW-WINTER WHEAT (SF-WW)
3.5% SLOPE
TILLAGE
SYSTEMS
SPR
SWP
SSCU
CHI
STANDARD
1.19
1.19
1.19
2.15
DIVIDED
SLOPE
0.37
0.37
0.37
0.67
9.5% SLOPE
STRIP
CROP
0.19
0.19
0.19
0.33
STANDARD
2.39
2.39
2.39
4.30
DIVIDED
SLOPE
0.88
0.88
0.88
1.58
STRIP
CROP
0.44
0.44
0.44
0.79
SUMMER FALLOW-SPRING BARLEY (SF-SB)
SPR
SWP
CHI
2.87
2.87
2.99
0.89
0.89
0.93
0.45
0.45
0.46
5.73
5.73
5.97
2.11
2.11
2.20
1.06
1.06
1.10
133
Table (6.4):
Estimated Average Soil Loss (Tons/ac/yr)1
Using Standard, Divided Slope, Strip Crop
Practices on (WW-GP) Rotation--Athena Soil.
WINTER WHEAT-GREEN PEAS ROTATION (WW-GP)
3.5% SLOPE
TILLAGE
SYSTEMS
CHINBD
DICUL
DISMBD
STANDARD
6.37
5.73
6.69
DIVIDED
SLOPE
1.98
1.78
2.07
9.5% SLOPE
STRIP
CROP
STANDARD
0.99
0.89
1.04
12.74
11.47
13.38
DIVIDED
SLOPE
4.69
4.22
4.93
STRIP
CROP
2.35
2.11
2.46
On Walla Walla, Pilot Rock and Ritzville soils and for
both winter wheat and spring barley rotations, shifting from
standard practice to divided slope and strip crop practices
reduced soil loss by as much as 69 and 85 percent,
respectively.
Strip cropping reduced soil loss by an
additional 50 percent, on both rotations and slope
categories, over divided slope.
On Athena soils, adoption of divided slope practice
reduced soil loss rate by about 69 percent on 3.5 percent
slope and about 63 percent on 9.5 percent slope.
Strip
cropping was even more effective, generating as 86 and 82
percent soil loss reductions on 3.5 and 9.5 percent slopes.
Strip cropping generated 50 to 54 percent less soil loss
than divided slope practice.
134
In general, soil losses on Walla Walla soil were much
higher than on other soils.
The greater erosion can be
attributed to the tillage practices, relatively deep soil
and higher rainfall zone.
Across all tillage systems,
conservation practices, slopes and crop rotations, tillage
system 4 (disking followed by residue burning) generated the
largest losses, followed by the conventional tillage system
(option 1, moldboard plow).
The reduced tillage system,
(option 2), utilizing chisel plow followed by herbicide
spray produced the lowest soil loss rates.
This low soil
loss rate, characterizing systems involving cultural soil
conservation techniques, is enhanced by more surface residue
remaining after primary tillage operations.
Soil losses are much lower on Pilot Rock soil than on
Walla Walla soil.
Tillage system 4 (chisel plow followed by
herbicide spray) produced the largest soil loss rates on
soils planted to winter wheat.
The other tillage systems
produced identical soil losses for a given slope and soil
conservation practice.
In spring barley production, all
tillage systems generated identical soil loss rates for each
slope and soil conservation practice.
These resulting
identical soil loss rates were due to field operations,
under the different tillage system, retaining approximately
the same level of residues on the soil surface.
Average soil loss rates on Ritzville soil are the
lowest of all the soils considered.
Across all tillage
systems and practices, a system utilizing chisel plowing
135
followed by a herbicide spray generated the largest soil
loss rates on winter wheat fields.
Soil losses from spring
barley and winter wheat fields were also roughly the same,
for each slope and production practice.
Lower soil losses
on Pilot Rock and Ritzville soils may be attributed to
relatively shallower soil, reduced tillage systems and
occurrence of much lower annual rainfall.
Soil loss rates on Athena soil, though higher than on
Pilot Rock and Ritzville soils, were much lower than on
Walla Walla soil despite use of moldboard plow and being
located in a higher rainfall zone.
This may also be due to
much higher residue from previous crop, much deeper soil,
type of rotation and tillage systems.
As expected, average
soil losses were highest for tillage systems involving
moldboard plow (tillage systems (1) and (3)).
Tillage
system (2), involving disk plowing for primary tillage,
produced the lowest soil losses.
T-Values
The soils under investigation--Walla Walla, Pilot Rock,
Ritzville and Athena soils have associated T-values of 5, 2,
5 and 5 tons/ac/yr.
Under the provision of the Food
Security Act (SAC) of 1985, Pilot Rock is the only soil
classified as highly erodible land (HEL).
The maximum
allowable soil loss rate for Pilot Rock soil, under this
Act, is 6 tons/ac/yr.
Tillage systems on both slope
categories for Winter Wheat and on 3.5 percent slope for
136
spring barley under divided slope practice consistently
produced annual soil loss rates below the maximum allowable
requirement.
Tillage systems under strip cropping, for both
slope type and crop rotation, also consistently produced
very low soil loss rates.
Tillage systems under standard
practice, on Walla Walla and Athena soils, generated soil
loss rates exceeding the soil's T-value in some weather
production years, particularly on the 9.5 percent slope.
On
Walla Walla and Pilot Rock soils, soil loss rates in spring
barley production years greatly exceeded the allowable level
for tillage systems under standard and divided slope
practices.
Only the standard practice tillage system
exceeded the allowable soil loss rate on Athena soils.
Under the current farm program, annual soil loss rates that
exceed the maximum allowed on an HEL, will result in the
loss of deficiency payments to farm operators.
Loss of
deficiency payments often results in a negative profit
situation.
The annual soil loss rates (determined from
equation 4.1) and associated cost of erosion damages
(calculated using equations 5.7 - 5.19) for all soils,
tillage systems and
conservation
- C.12 in Appendix C.
practices are in Tables C.1
137
Cost of Soil Erosion
Tables (6.5) - (6.8) show the cost of soil lost through
erosion for Walla Walla soil, Pilot Rock, Ritzville and
Athena soils, respectively.
Detailed results are in Table
(C.1) - (C.12), in Appendix C.
On Walla Walla soil, erosion cost was as large as
$7.39/ac/yr for fallow-wheat crop rotations, and $9.25/ac/yr
for fallow-barley rotations.
In production systems
implementing the divided slope practice, the value of soil
loss was reduced to $2.55, and $3.42/ac/yr for wheat and
barley rotations.
The largest erosion costs from strip
cropping were only $1.15/ac/yr and $1.75/ac/yr1
respectively, for (SF-WW) and (SF-SB) crop rotations.
Because soil loss rates were low for Pilot Rock and
Ritzville soils, the corresponding erosion costs were also
low.
The largest erosion cost ($2.96/ac/yr) occurred under
standard practice and lowest cost ($0.04/ac/yr) associated
with strip cropping.
On Athena soil, more erosion occurred during the green
pea production year than during winter wheat production.
Erosion damage cost was as large as $16.27 and $3.33/ac/yr,
for green pea and winter wheat under standard practices.
Erosion damage under divided slope and strip crop practices
were much smaller, with costs below $2.00.
138
Table (6.5):
Estimated Value of Soil Loss ($/ac/yr) for
Standard, Divided Slope and Strip Crop
Practices on (SF-WW) and (SF-SB) Rotations-Walla Walla Soil.
SUMMER FALLOW-WINTER WHEAT (SF-WW)
9.5% SLOPE
3.5% SLOPE
TILLAGE
SYSTEMS
MB
CH
DI
DIB
DICH
STANDARD
2.92
1.01
1.75
3.55
1.96
DIVIDED
SLOPE
0.73
0.14
0.37
0.92
0.43
STRIP
CROP
0.24
0.01
0.07
0.34
0.10
STANDARD
6.11
2.28
3.77
7.39
4.19
DIVIDED
SLOPE
2.08
0.68
1.22
2.55
1.38
STRIP
CROP
0.91
0.21
0.49
1.15
0.56
SUMMER FALLOW-SPRING BARLEY (SF-SB)
MB
CH
DI
DIB
DICH
4.38
2.35
2.90
4.63
3.15
1.41
0.79
0.96
1.49
1.03
0.75
0.44
0.52
0.79
0.56
8.74
4.63
5.74
9.25
6.24
3.24
1.75
2.16
3.42
2.34
1.66
0.92
1.12
1.75
1.21
139
Table (6.6):
Estimated Value of Soil Loss ($/ac/yr) for
Standard, Divided Slope and Strip Crop
Practices on (SF-WW) and (SF-SB) Rotations-Pilot Rock Soil.
SUMNER FALLOW-WINTER WHEAT (SF-WW)
9.5% SLOPE
3.5% SLOPE
TILLAGE
SYSTEMS
SPR
SWP
SSCU
CHI
STANDARD
DIVIDED
SLOPE
0.19
0.19
0.19
0.43
0.68
0.68
0.68
1.46
STRIP
CROP
0.08
0.08
0.08
0.20
STANDARD
DIVIDED
SLOPE
0.49
0.49
0.49
1.07
1.39
1.39
1.39
2.96
STRIP
CROP
0.23
0.23
0.23
0.52
SUMNER FALLOW-SPRING BARLEY (SF-SB)
SPR
SWP
CHI
0.22
0.22
0.22
1.21
1.21
1.21
Table (6.7):
Estimated
Standard,
Practices
Ritzville
0.04
0.04
0.04
0.83
0.83
0.83
2.66
2.66
2.66
0.30
0.30
0.30
Value of Soil Loss ($/ac/yr) for
Divided Slope and Strip Crop
on (SF-WW) and (SF-SB) Rotations-Soil.
SUMNER FALLOW-WINTER WHEAT (SF-WW)
9.5% SLOPE
3.5% SLOPE
TILLAGE
SYSTEMS
SPR
SWP
SSCU
CHI
STANDARD
0.79
0.79
0.79
1.32
DIVIDED
SLOPE
0.33
0.33
0.33
0.50
STRIP
CROP
0.23
0.23
0.23
0.31
STANDARD
1.45
1.45
1.45
2.51
DIVIDED
SLOPE
0.61
0.61
0.61
1.00
STRIP
CROP
0.37
0.37
0.37
0.57
SUMMER FALLOW-SPRING BARLEY (SF-SB)
SPR
SWP
CHI
1.25
1.25
1.30
0.39
0.39
0.40
0.20
0.20
0.20
2.49
2.49
2.60
0.92
0.92
0.96
0.46
0.46
0.48
140
Table (6.8):
Estimated Value of Soil Loss ($/ac/yr) for
Standard, Divided Slope and Strip Crop
Practices on (WW-GP) Rotation--Athena Soil.
WINTER WHEAT AFTER GREEN PEA
3.5% SLOPE
TILLAGE
SYSTEMS
CHIMBD
DICUL
DISMBD
STANDARD
1.73
1.59
1.81
DIVIDED
SLOPE
0.73
0.69
0.76
9.5% SLOPE
STRIP
CROP
0.51
0.49
0.52
STANDARD
3.19
2.90
3.33
DIVIDED
SLOPE
STRIP
CROP
1.35
1.24
1.40
0.82
0.76
0.84
15.90
15.88
15.91
15.80
15.79
15.81
GREEN PEA AFTER WINTER WHEAT
CHIMBD
DICUL
DISMBD
15.97
15.94
15.98
15.79
15.78
15.79
15.75
15.74
15.75
16.24
16.19
16.27
Results of the Budgeting program
Tables (6.9) - (6.12) present a partial enterprise
budget results for winter wheat, spring barley and green pea
production under alternative tillage systems, implementing
standard, divided slope and strip crop practices.
Example
detailed budgets for SF-WW and SF-SB rotations in
conventional tillage systems under standard, divided slope
and strip crop practices on Walla Walla soil are shown in
Table (D.4), Appendix D.
141
Table (69a):
TILLAGE
SYSTEMS
MB-STD-Fl
MB-STD-F2
MB-STD--F3
MB-STD-F4
NB-STD-F5
MB-STD-F6
CH-STD-Fl
CH-STD-F2
CH-STD-F3
CH-STD-F4
CH-STD-F5
CH-STD-F6
DI-STD--Fl
DI-STD-F2
DI-STD-F3
DI-STD-F4
DI-STD-F5
DI-STD-F6
DIB-STD-Fl
DIB-STD-F2
DIB-STD-F3
DIB-STD-F4
DIB-STD-F5
DIB-STD-F6
DICH-STD-Fl
DICH-STD-F2
DICH-STD-F3
DICH-STD-F4
DICH-STD-F5
DICH-STD-F6
Budget Summary for Tillage Systems under
Standard, Divided Slope and Strip Crop
Practices in (SF-WW) Crop Rotation-Walla Walla Soil.
VARIABLE
COST
FIXED
COST
TOTAL
COST
NET
RETURN
141.87
139.19
140.01
143.73
138.38
129.06
143.15
140.46
141.27
145.00
139.64
130.32
141.74
139.05
139.87
143.59
138.24
128.92
147.70
145.01
145.83
149.55
144.20
134.88
138.33
135.64
136.46
140.18
134.83
125.51
34.23
34.23
34.23
34.23
34.23
34.23
31.22
31.22
31.22
31.22
31.22
31.22
30.58
30.58
30.58
30.58
30.58
30.58
28.83
28.83
28.83
28.83
28.83
28.83
30.81
30.81
30.81
30.81
30.81
30.81
176.10
173.42
174.24
177.96
172.61
163.29
174.37
171.68
172.49
176.22
170.86
161.54
172.32
169.63
170.45
174.17
168.82
159.50
176.53
173.84
174.66
178.38
173.03
163.71
169.14
166.45
167.27
170.99
165.64
156.32
129.15
131.83
131.01
127.29
132.64
141.96
130.88
133.57
132.76
129.03
134.39
143.71
132.93
135.62
134.80
131.08
136.43
145.75
128.72
131.41
130.59
126.87
132.22
141.54
136.11
138.80
137.98
134.26
139.61
148.93
MB, CH, DI, DIB, AND DICH CORRESPONDTO TILLAGE SYSTEM 1 TO
5.
STD, DIV AND STR MEAN STANDARD, DIVIDED SLOPE AND STRIPCROP PRACTICES RESPECTIVELY. F/I, WHERE # = 1,2,3,4,5,6,
CORRESPOND TO FERTILIZER APPLICATION RATE AND TIMING
STRATEGIES. SEE TABLES (5.2) - (5.5).
142
Table (6.9a) Continued: Budget Summary for Tillage Systems
under Standard, Divided Slope and Strip Crop
Practices in (SF-WW) Crop Rotation-Walla Walla Soil.
TILLAGE
SYSTEMS
MB-DIV-Fl
MB-DIV-F2
MB-DIV-F3
MB-DIV-F4
MB-DIV-F5
MB-DIV-F6
CH-DIV-F1
CH-DIV-F2
CH-DIV-F3
CH-DIV-F4
CH-DIV-F5
CH-DIV-F6
DI-DIV-F1
DI-DIV-F2
DI-DIV-F3
DI-DIV-F4
DI-DIV-F5
DI-DIV-F6
DIE-DIV-Fl
DIB-DIV-F2
DIB-DIV-F3
DIB-DIV-F4
DIB-DIV-F5
DIB-DIV-F6
DICH-DIV-F1
DICH-DIV-F2
DICH-DIV-F3
DICH-DIV-F4
DICH-DIV-F5
DICH-DIV-F6
VARIABLE
COST
FIXED
COST
TOTAL
COST
NET
RETURN
167.51
164.60
165.48
169.61
163.68
153.45
173.33
170.42
171.30
175.43
169.50
159.26
171.68
168.77
169.65
173.78
167.85
157.61
173.35
170.44
171.33
175.45
169.58
159.29
163.31
160.40
161.28
165.40
159.48
149.24
36.92
36.92
36.92
36.92
36.92
36.92
33.61
33.61
33.61
33.61
33.61
33.61
32.90
32.90
32.90
32.90
32.90
32.90
30.98
30.98
30.98
30.98
30.98
30.98
33.16
33.16
33.16
33.16
33.16
33.16
204.43
201.52
202.40
206.53
200.60
190.37
206.94
204.03
204.91
209.04
203.11
192.87
204.58
201.67
202.55
206.68
200.75
190.51
204.33
201.42
202.31
206.43
200.56
190.27
196.47
193.56
194.44
198.56
192.64
182.40
100.82
103.73
102.85
98.72
104.65
114.88
98.31
101.22
100.34
96.21
102.14
112.38
100.67
103.58
102.70
98.57
104.50
114.74
100.92
103.83
102.94
98.82
104.69
114.98
108.78
111.69
110.81
106.69
112.61
122.85
MB, CH, DI, DIB, AND DICH CORRESPOND TO TILLAGE SYSTEM 1 TO
STD, DIV AND STR MEAN STANDARD, DIVIDED SLOPE AND STRIP5.
CROP PRACTICES RESPECTIVELY. F#, WHERE # = 1,2,3,4,5,6,
CORRESPOND TO FERTILIZER APPLICATION RATE AND TIMING
STRATEGIES. SEE TABLES (5.2) - (5.5).
143
Table (6.9a) Continued:
Budget Suiinary for Tillage Systems
under Standard, Divided Slope and Strip Crop
Practices in (SF-WW) Crop Rotation-Walla Walla Soil.
TILLAGE
SYSTEMS
MB-STR-Fl
MB-STR-F2
MB-STR-F3
MB-STR-F4
MB-STR-F5
MB-STR-F6
CH-STR-F1
CH-STR-F2
CH-STR-F3
CH-STR-F4
CH-STR-F5
CH-STR-F6
DI-STR-F1
DI-STR-F2
DI-STR-F3
DI-STR-F4
DI-STR-F5
DI-STR-F6
DIB-STR-Fl
DIB-STR-F2
DIB-STR-F3
DIB-STR-F4
DIB-STR-F5
DIB-STR-F6
DICH-STR-F].
DICH-STR-F2
DICH-STR-F3
DICH-STR-F4
DICH-STR-F5
DICH-STR-F6
VARIABLE
COST
FIXED
COST
TOTAL
COST
NET
RETURN
188.36
185.23
186.18
190.70
184.21
173.05
195.06
191.93
192.88
197.40
190.91
179.75
193.47
190.33
191.28
195.80
189.31
178.15
195.42
192.28
193.23
197.76
191.26
180.10
184.21
181.13
182.07
186.60
180.10
168.95
37.44
37.44
37.44
37.44
37.44
37.44
34.43
34.43
34.43
34.43
34.43
34.43
33.79
33.79
33.79
33.79
33.79
33.79
32.04
32.04
32.04
32.04
32.04
32.04
34.02
34.02
34.02
34.02
34.02
34.02
225.80
222.67
223.62
228.14
221.65
210.49
229.49
226.36
227.31
231.83
225.34
214.18
227.26
224.12
225.07
229.59
223.10
211.94
227.46
224.32
225.27
229.80
223.30
212.14
218.23
215.15
216.09
220.62
214.12
202.97
79.45
82.58
81.63
77.11
83.60
94.76
75.76
78.89
77.94
73.42
79.91
91.07
77.99
81.13
80.18
75.66
82.15
93.31
77.79
80.93
79.98
75.45
81.95
93.11
87.02
90.10
89.16
84.63
91.13
102.28
MB, CH, DI, DIB, AND DICH CORRESPOND TO TILLAGE SYSTEM 1 TO
5.
STD, DIV AND STR MEAN STANDARD, DIVIDED SLOPE AND STRIPCROP PRACTICES RESPECTIVELY.
F#, WHERE # = 1,2,3,4,5,6,
CORRESPOND TO FERTILIZER APPLICATION RATE AND TIMING
STRATEGIES. SEE TABLES (5.2) - (5.5).
144
Table (6.9b):
TILLAGE
SYSTEMS
MB-STD-Fl
MB-STD-F2
MB-STD-F3
CH-STD-Fl
CH-STD-F2
CH-STD-F3
DI-STD-F1
DI-STD-F2
DI-STD-F3
DIB-STD-F1
DIB-STD-F2
DIB-STD-F3
DICH-STD-Fl
DICH-STD-F2
DICH-STD-F3
MB-DIV-Fl
MB-DIV-F2
MB-DIV-F3
CH-DIV-F1
CH-DIV-F2
CH-DIV-F3
DI-DIV-F1
DI-DIV-F2
DI-DIV-F3
DIB-DIV-F1
DIB-DIV-F2
DIB-DIV-F3
DICH-DIV-F1
DICH-DIV-F2
DICH-DIV-F3
Budget Sununary for Tillage Systems under
Standard, Divided Slope and Strip Crop
Practices in (SF-SB) Crop Rotation-Walla Walla Soil.
VARIABLE
COST
FIXED
COST
TOTAL
COST
NET
RETURN
105.08
109.55
114.02
106.35
110.82
115.29
104.94
109.41
113.89
110.90
115.38
119.85
101.58
106.01
110.48
119.75
124.67
129.58
125.43
130.34
135.25
124.40
129.32
134.23
134.70
139.62
144.53
142.44
129.35
134.27
35.68
35.68
35.68
32.67
32.67
32.67
32.03
32.03
32.03
30.28
30.28
30.28
32.26
32.26
32.26
37.13
37.13
37.13
33.99
33.99
33.99
33.47
33.47
33.47
31.49
31.49
31.49
33.47
33.47
33.47
140.76
145.23
149.70
139.02
143.49
147.96
136.97
141.44
145.92
141.18
145.66
150.13
133.84
138.27
142.74
156.88
161.80
166.71
159.42
164.33
169.24
157.87
162.79
167.70
166.19
171.11
176.02
175.91
162.82
167.74
60.93
56.46
51.99
62.67
58.20
53.73
64.72
60.25
55.77
60.51
56.03
51.56
67.85
63.42
58.95
44.81
39.89
34.98
42.27
37.36
32.45
43.82
38.90
33.99
35.50
30.58
25.67
25.78
38.87
33.95
MB, CH, DI, DIB, AND DICH CORRESPOND TO TILLAGE SYSTEM 1 TO
5.
STD, DIV AND STR MEAN STANDARD, DIVIDED SLOPE AND STRIPCROP PRACTICES RESPECTIVELY.
F#, WHERE # = 1,2,3,
CORRESPOND TO FERTILIZER APPLICATION RATE AND TIMING
STRATEGIES. SEE TABLES (5.2) - (5.5).
145
Table (6.9b) Continued: Budget Summary for Tillage Systems
under Standard, Divided Slope and Strip Crop
Practices in (SF-SB) Crop Rotation-Walla Walla Soil.
TILLAGE
SYSTEMS
MB-STR-F].
MB-STR-F2
MB-STR-F3
CH-STR-F1
CH-STR-F2
CH-STR-F3
DI-STR-F1
DI-STR-F2
DI-STR-F3
DIB-STR-F1
DIB-STR-F2
DIB-STR-F3
DICH-STR-F1
DICH-STR-F2
DICH-STR-F3
VARIABLE
COST
FIXED
COST
TOTAL
COST
NET
RETURN
136.82
142.18
147.53
143.53
148.88
154.23
141.93
147.28
152.63
143.14
149.23
154.58
132.72
138.04
143.43
38.60
38.60
38.60
35.59
35.59
35.59
34.94
34.94
34.94
33.20
33.20
33.20
35.18
35.18
35.18
175.42
180.78
186.13
179.12
184.47
189.82
176.87
182.22
187.57
176.34
182.43
187.78
167.90
173.22
178.61
26.27
20.91
15.56
22.57
17.22
11.87
24.82
19.47
14.12
25.35
19.26
13.91
33.79
28.47
23.08
MB, CH, DI, DIB, AND DICH CORRESPOND TO TILLAGE SYSTEM 1 TO
5.
STD, DIV AND STR MEAN STANDARD, DIVIDED SLOPE AND STRIPCROP PRACTICES RESPECTIVELY. F#, WHERE # = 1,2,3,
CORRESPOND TO FERTILIZER APPLICATION RATE AND TIMING
STRATEGIES. SEE TABLES (5.2) - (5.5).
146
Table (6.lOa):
Budget Summary for Tillage Systems under
Standard, Divided Slope and Strip Crop
Practices in (SF-WW) Crop Rotation,
Pilot Rock Soil.
TILLAGE
SYSTEMS
SPR-STD-Fl
SPR-STD-F2
SPR-STD-F3
SPR-STD-F4
SPR-STD-F5
SPR-STD-F6
SWP-STD-F1
SWP-STD-F2
SWP-STD-F3
SWP-STD-F4
SWP-STD-F5
SWP-STD-F6
SSCtJ-STD-F1
SSCU-STD-F2
SSCIJ-STD-F3
SSCU-STD-F4
SSCtJ-STD-F5
SSCTJ-STD-F6
CHI-STD-F1
CHI-STD-F2
CHI-STD-F3
CHI-STD-F4
CHI-STD-F5
CHI-STD-F6
SPR-DIV-F1
SPR-DIV--F2
SPR-DIV-F3
SPR-DIV-F4
SPR-DIV-F5
SPR-DIV-F6
SWP-DIV-F1
SWP-DIV-F2
SWP-DIV-F3
SWP-DIV-F4
SWP-DIV-F5
SWP-DIV-F6
VARIABLE
COST
FIXED
COST
TOTAL
COST
NET
RETURN
86.79
86.09
85.85
87.72
85.62
79.21
83.77
83.06
82.83
84.69
82.60
76.08
86.90
86.19
85.96
87.82
85.73
79.21
87.87
87.17
86.94
88.80
86.70
80.18
101.54
100.79
100.53
102.59
100.27
93.10
98.01
97.25
96.99
99.05
96.73
89.57
17.63
17.63
17.63
17.63
17.63
17.63
19.37
19.37
19.37
19.37
19.37
19.37
17.63
17.63
17.63
17.63
17.63
17.63
20.53
20.53
20.53
20.53
20.53
20.53
23.72
23.72
23.72
23.72
23.72
23.72
25.45
25.45
25.45
25.45
25.45
25.45
104.42
103.72
103.48
105.35
103.25
96.84
103.14
102.43
102.20
104.06
101.97
95.45
104.53
103.82
103.59
105.45
103.36
96.84
108.40
107.70
107.47
109.33
107.23
100.71
125.26
124.51
124.25
126.31
123.99
116.82
123.46
122.70
122.44
124.50
122.18
115.02
58.38
59.08
59.32
57.45
59.55
65.96
59.66
60.37
60.60
58.74
60.83
67.35
58.27
58.98
59.21
57.35
59.44
65.96
54.40
55.10
55.33
53.47
55.57
62.09
37.54
38.29
38.55
36.49
38.81
45.98
39.34
40.10
40.36
38.30
40.62
47.78
SPR, SWP, SSCU, AND CHI CORRESPOND TO TILLAGE SYSTEM 1 TO 4.
STD, DIV AND STR MEAN STANDARD, DIVIDED SLOPE AND STRIP-CROP
PRACTICES RESPECTIVELY. F#, WHERE # = 1,2,3,4,5,6,
CORRESPOND TO FERTILIZER APPLICATION RATE AND TIMING
STRATEGIES. SEE TABLES (5.2) - (5.5).
147
Table (6.lOa) Continued: Budget Summary for Tillage Systems
under Standard, Divided Slope and Strip Crop
Practices in (SF-WW) Crop Rotation-Pilot Rock Soil.
TILLAGE
SYSTEMS
SSCtJ-DIV-F1
SSCtJ-DIV-F2
SSCU-DIV-F3
SSCtJ-DIV-F4
SSCtJ-DIV-F5
SSCU-DIV-F6
CHI-DIV-F1
CHI-DIV-F2
CHI-DIV-F3
CHI-DIV-F4
CHI-DIV-F5
CHI-DIV-F6
SPR-STR-F1
SPR-STR-F2
SPR-STR-F3
SPR-STR-F4
SPR-STR-F5
SPR-STR-F6
SWP-STR-F1
SWP-STR-F2
SWP-STR-F3
SWP-STR-F4
SWP-STR-F5
SWP-STR-F6
SSCU-STR-F1
SSCtJ-STR-F2
SSCtJ-STR-F3
SSCU-STR-F4
SSCU-STR-F5
SSCU-STR-F6
CHI-STR-F1
CHI-STR-F2
CHI-STR-F3
CHI-STR-F4
CHI-STR-F5
CHI-STR-F6
VARIABLE
COST
FIXED
COST
TOTAL
COST
NET
RETURN
101.54
100.79
100.53
102.59
100.27
93.10
105.74
104.99
104.73
106.79
104.47
97.30
112.36
111.58
111.31
113.47
111.03
103.55
108.64
107.87
107.59
109.75
107.31
99.83
113.71
112.93
112.66
114.82
112.38
104.90
118.04
117.27
116.99
119.15
116.71
109.23
23.72
23.72
23.72
23.72
23.72
23.72
26.62
26.62
26.62
26.62
26.62
26.62
25.60
25.60
25.60
25.60
25.60
25.60
27.33
27.33
27.33
27.33
27.33
27.33
25.60
25.60
25.60
25.60
25.60
25.60
28.50
28.50
28.50
28.50
28.50
28.50
125.26
124.51
124.25
126.31
123.99
116.82
132.36
131.61
131.35
133.41
131.09
123.92
137.96
137.18
136.91
139.07
136.63
129.15
135.97
135.20
134.92
137.08
134.64
127.16
139.31
138.53
138.26
140.42
137.98
130.50
146.54
145.77
145.49
147.65
145.21
137.73
37.54
38.29
38.55
36.49
38.81
45.98
30.44
31.19
31.45
29.39
31.71
38.88
24.84
25.62
25.89
23.73
26.17
33.65
26.83
27.60
27.88
25.72
28.16
35.64
23.49
24.27
24.54
22.38
24.82
32.30
16.26
17.03
17.31
15.15
17.59
25.07
SPR, SWP, SSCU, AND CHI CORRESPOND TO TILLAGE SYSTEM 1 TO 4.
STD, DIV AND STR MEAN STANDARD, DIVIDED SLOPE AND STRIP-CROP
PRACTICES RESPECTIVELY. F#, WHERE # = 1,2,..,6, CORRESPOND
TO FERTILIZER APPLICATION RATE AND TIMING STRATEGIES. SEE
TABLES (5.2) - (5.5).
148
Table (6.lob):
TILLAGE
SYSTEMS
Budget Summary for Tillage Systems under
Standard, Divided Slope and Strip Crop
Practices in (SF-SB) Crop Rotation-Pilot Rock Soil.
VARIABLE
COST
FIXED
COST
TOTAL
COST
NET
RETURN
SPR-STD-F1
SPR-STD-F2
SPR-STD-F3
83.43
87.90
92.37
22.13
22.13
22.13
105.56
110.03
114.50
40.24
35.77
31.30
SWP-STD-Fl
SWP-STD-F2
SWP-STD-F3
80.33
84.81
89.28
24.15
24.15
24.15
104.48
108.96
113.43
41.32
36.84
32.37
CHI-STD-F1
CHI-STD-F2
CHI-STD-F3
83.74
88.21
92.68
24.49
24.49
24.49
108.23
112.70
117.17
37.57
33.10
28.63
SPR-DIV-F1
SPR-DIV-F2
SPR-DIV-F3
94.12
99.04
103.95
26.34
26.34
26.34
120.46
125.38
130.29
25.34
20.42
15.51
SWP-DIV-F1
SWP-DIV-F2
SWP-DIV-F3
91.08
95.99
100.90
28.36
28.36
28.36
119.44
124.35
129.26
26.36
21.45
16.54
CHI-DIV-F1
CHI-DIV-F2
CHI-DIV-F3
97.82
102.73
107.64
28.70
28.70
28.70
126.52
131.43
136.34
19.28
14.37
9.46
SPR-STR-F1
SPR-STR-F2
SPR-STR-F3
100.29
105.42
110.55
27.05
27.05
27.05
127.34
132.47
137.60
18.46
13.33
8.20
SWP-STR-F1
SWP-STR-F2
SWP-STR-F3
96.57
101.71
106.84
28.78
28.78
28.78
125.35
130.49
135.62
20.45
15.31
10.18
CHI-STR-F1
CHI-STR-F2
CHI-STR-F3
99.50
104.63
109.77
29.08
29.08
29.08
128.58
133.71
138.85
17.22
12.09
6.95
SPR, SWP, AND CHI CORRESPOND TO TILLAGE SYSTEM 1 TO 3. STD,
DIV AND STR MEAN STANDARD, DIVIDED SLOPE AND STRIP-CROP
PRACTICES RESPECTIVELY. F#, WHERE # = 1,2,3, CORRESPOND TO
FERTILIZER APPLICATION RATE AND TIMING STRATEGIES. SEE
TABLES (5.2) - (5.5).
149
Table (6.11a):
TILLAGE
SYSTEMS
SPR-STD-Fl
SPR-STD-F2
SPR-STD-F3
SPR-STD-F4
SPR-STD-F5
SPR-STD-F6
SWP-STD-Fl
SWP-STD-F2
SWP-STD-F3
SWP-STD-F4
SWP-STD-F5
SWP-STD-F6
SSCU-STD-Fl
SSCtJ-STD-F2
SSCU-STD-F3
SSCU-STD-F4
SSCtJ-STD-F5
SSCU-STD-F6
CHI-STD-F1
CHI-STD-F2
CHI-STD-F3
CHI-STD-F4
CHI-STD-F5
CHI-STD-F6
SPR-DIV-F1
SPR-DIV-F2
SPR-DIV-F3
SPR-DIV-F4
SPR-DIV-F5
SPR-DIV-F6
SWP-DIV-F1
SWP-DIV-F2
SWP-DIV-F3
SWP-DIV-F4
SWP-DIV-F5
SWP-DIV-F6
Budget Sununary for Tillage Systems under
Standard, Divided Slope and Strip Crop
Practices in (SF-WW) Crop Rotation-Ritzville Soil.
VARIABLE
COST
FIXED
COST
TOTAL
COST
95.98
95.27
95.04
96.90
94.81
88.29
92.88
92.18
91.95
93.81
91.71
85.19
95.98
95.27
95.04
96.90
94.81
88.29
100.57
99.87
99.64
101.50
99.41
92.88
116.74
115.98
115.72
117.78
115.46
108.30
109.94
109.19
108.93
110.99
108.66
101.50
19.40
19.40
19.40
19.40
19.40
19.40
21.42
21.42
21.42
21.42
21.42
21.42
19.40
19.40
19.40
19.40
19.40
19.40
22.78
22.78
22.78
22.78
22.78
22.78
24.30
24.30
24.30
24.30
24.30
24.30
26.32
26.32
26.32
26.32
26.32
26.32
115.38
114.67
114.44
116.30
114.21
107.69
114.30
113.60
113.37
115.23
113.13
106.61
115.38
114.67
114.44
116.30
114.21
107.69
123.35
122.65
122.42
124.28
122.19
115.66
141.04
140.28
140.02
142.08
139.76
132.60
136.26
135.51
135.25
137.31
134.98
127.82
NET
RETURN
88.12
88.83
89.06
87.20
89.29
95.81
89.20
89.90
90.13
88.27
90.37
96.89
88.12
88.83
89.06
87.20
89.29
95.81
80.15
80.85
81.08
79.22
81.31
87.84
62.46
63.22
63.48
61.42
63.74
70.90
67.24
67.99
68.25
66.19
68.52
75.68
SPR, SWP, SSCU, AND CHI CORRESPOND TO TILLAGE SYSTEM 1 TO 4.
STD, DIV AND STR MEAN STANDARD, DIVIDED SLOPE AND STRIP-CROP
PRACTICES RESPECTIVELY. F#, WHERE # = 1,2,3,4,5,6,
CORRESPOND TO FERTILIZER APPLICATION RATE AND TIMING
STRATEGIES. SEE TABLES (5.2) - (5.5).
150
Table (6.11a) Continued: Budget Summary for Tillage Systems
under Standard, Divided Slope and Strip Crop
Practices in (SF-WW) Crop Rotation-Ritzville Soil.
TILLAGE
SYSTEMS
SSCU-DIV--Fl
SSCtJ-DIV-F2
SSCTJ-DIV-F3
SSCU-DIV-F4
SSCtJ-DIV-F5
SSCU-DIV-F6
CHI-DIV-Fl
CHI-DIV-F2
CHI-DIV-F3
CHI-DIV-F4
CHI-DIV-F5
CHI-DIV-F6
SPR-STR-F1
SPR-STR-F2
SPR-STR-F3
SPR-STR-F4
SPR-STR-F5
SPR-STR-F6
SWP-STR-F1
SWP-STR-F2
SWP-STR-F3
SWP-STR-F4
SWP-STR-F5
SWP-STR-F6
SSCU-STR-F1
SSCU-STR-F2
SSCU-STR-F3
SSCU-STR-F4
SSCU-STR-F5
SSCU-STR-F6
CHI-STR-F1
CHI-STR--F2
CHI-STR-F3
CHI-STR-F4
CHI-STR-F5
CHI-STR-F6
VARIABLE
COST
FIXED
COST
TOTAL
COST
116.74
115.98
115.72
117.78
115.46
108.30
121.64
120.89
120.62
122.69
120.36
113.20
128.75
127.97
127.70
129.86
127.42
119.93
121.63
120.85
120.58
122.74
120.30
112.82
128.75
127.97
127.70
129.86
127.42
119.93
133.81
133.03
132.75
134.91
132.48
124.99
24.30
24.30
24.30
24.30
24.30
24.30
27.68
27.68
27.68
27.68
27.68
27.68
26.18
26.18
26.18
26.18
26.18
26.18
28.20
28.20
28.20
28.20
28.20
28.20
26.18
26.18
26.18
26.18
26.18
26.18
29.56
29.56
29.56
29.56
29.56
29.56
141.04
140.28
140.02
142.08
139.76
132.60
149.32
148.57
148.30
150.37
148.04
140.88
154.93
154.15
153.88
156.04
153.60
146.11
149.83
149.05
148.78
150.94
148.50
141.02
154.93
154.15
153.88
156.04
153.60
146.11
163.37
162.59
162.31
164.47
162.04
154.55
NET
RETURN
62.46
63.22
63.48
61.42
63.74
70.90
54.18
54.93
55.20
53.13
55.46
62.62
48.57
49.35
49.62
47.46
49.90
57.39
53.67
54.45
54.72
52.56
55.00
62.48
48.57
49.35
49.62
47.46
49.90
57.39
40.13
40.91
41.19
39.03
41.46
48.95
SPR, SWP, SSCU, AND CHI CORRESPOND TO TILLAGE SYSTEM 1 TO 4.
STD, DIV AND STR MEAN STANDARD, DIVIDED SLOPE AND STRIP-CROP
PRACTICES RESPECTIVELY. F#, WHERE # = 12,..,6, CORRESPOND
TO FERTILIZER APPLICATION RATE AND TIMING STRATEGIES. SEE
TABLES (5.2) - (5.5).
151
Table (6.11b):
TILLAGE
SYSTEMS
Budget Summary for Tillage Systems under
Standard, Divided Slope and Strip Crop
Practices in (SF-SB) Crop Rotation-Ritzville Soil.
VARIABLE
COST
FIXED
COST
TOTAL
COST
NET
RETURN
SPR-STD-F1
SPR-STD-F2
SPR-STD-F3
90.47
94.95
99.42
23.49
23.49
23.49
113.96
118.44
122.91
56.14
51.66
47.19
SWP-STD-Fl
SWP-STD-F2
SWP-STD-F3
87.46
91.93
96.40
25.80
25.80
25.80
113.26
117.73
122.20
56.84
52.37
47.90
CHI-STD-Fl
CHI-STD-F2
CHI-STD-F3
91.09
95.56
100.03
26.19
26.19
26.19
117.28
121.75
126.22
52.82
48.35
43.88
SPR-DIV-F1
SPR-DIV-F2
SPR-DIV-F3
103.52
108.43
113.34
27.21
27.21
130.73
135.64
140.55
39.37
34.46
29.55
SWP-DIV-F].
SWP-DIV-F2
SWP-DIV-F3
100.13
105.04
109.96
29.52
29.52
29.52
129.65
134.56
139.48
40.45
35.54
30.62
CHI-DIV-Fl
CHI-DIV-F2
CHI-DIV-F3
107.73
112.65
117.56
29.91
29.91
29.91
137.64
142.56
147.47
32.46
27.54
22.63
SPR-STR-F1
SPR-STR-F2
SPR-STR-F3
111.14
116.44
121.57
28.79
28.79
28.79
139.93
145.23
150.36
30.17
24.87.
19.74
SWP-STR-F1
SWP-STR-F2
SWP-STR-F3
107.74
112.87
118.00
31.10
31.10
31.10
138.84
143.97
149.10
31.26
26.13
21.00
CHI-STR-F1
CHI-STR-F2
CHI-STR-F3
115.65
120.78
125.92
31.49
31.49
31.49
147.14
152.27
157.41
22.96
17.83
12.69
27.2].
SPR, SWP, AND CHI CORRESPOND TO TILLAGE SYSTEM 1 TO 3. STD,
DIV AND STR MEAN STANDARD, DIVIDED SLOPE AND STRIP-CROP
PRACTICES RESPECTIVELY. F#, WHERE # = 1,2,3, CORRESPOND TO
FERTILIZER APPLICATION RATE AND TIMING STRATEGIES. SEE
TABLES (5.2) - (5.5).
152
Table (6.12a): Budget Summary for Tillage Systems under
Standard, Divided Slope and Strip Crop
Practices. Winter Wheat after Green Pea-Athena Soil.
TILLAGE
SYSTEMS
CHIMBD-STD-F1
CHIMBD-STD-F2
CHIMBD-STD-F3
CHIMBD-STD-F4
DICUL-STD-Fl
DICUL-STD-F2
DICtJL-STD-F3
DICUL-STD-F4
DISMBD-STD-F1
DISMBD-STD-F2
DISMBD-STD-F3
DISMBD-5TD-F4
CHIMBD-DIV-F].
CHIMBD-DIV-F2
CHIMBD-DIV-F3
CHIMBD-DIV-F4
DICtJL-DIV-F1
DICUL-DIV-F2
DICUL-DIV-F3
DICUL-DIV-F4
DISMBD-DIV-F1
DISMBD-DIV-F2
DISMBD-DIV-F3
DISMBD-DIV-F4
CHIMBD-STR-F1
CHIMBD-STR-F2
CHIMBD-STR-F3
CHIMBD-STR-F4
DICUL-STR-F].
DICtJL-STR-F2
DICtJL-STR-F3
DICUL-STR-F4
DISMBD-STR-F1
DISMBD-STR-F2
DISMBD-STR-F3
DISMBD-STR-F4
VARIABLE
COST
COST
TOTAL
COST
NET
RETURN
128.17
128.17
135.13
140.96
129.44
129.44
136.39
142.22
132.13
132.13
139.08
144.91
144.02
144.02
151.64
158.06
147.74
147.74
155.35
161.77
150.89
150.89
158.50
164.92
167.06
167.06
175.33
182.34
168.86
168.86
177.13
184.14
172.83
172.83
181.14
188.12
26.44
26.44
26.44
26.44
26.61
26.61
26.61
26.61
28.38
28.38
28.38
28.38
28.02
28.02
28.02
28.02
30.12
30.12
30.12
30.12
32.05
32.05
32.05
32.05
32.63
32.63
32.63
32.63
32.85
32.85
32.85
32.85
35.11
35.11
35.11
35.11
154.61
154.61
161.57
167.40
156.05
156.05
163.00
168.83
160.51
160.51
167.47
173.30
171.74
171.74
179.66
186.08
177.86
177.86
185.47
191.89
182.94
182.94
190.55
196.97
199.69
199.69
207.96
214.97
201.71
201.71
209.98
216.99
207.94
207.94
216.25
223.23
211.69
211.69
204.73
198.90
210.25
210.25
203.30
197.47
205.79
205.79
198.83
193.00
194.26
194.26
186.64
180.22
188.44
188.44
180.83
174.41
183.36
183.36
175.75
169.33
166.61
166.61
158.34
151.33
164.59
164.59
156.32
149.31
158.36
158.36
150.05
143.07
FIXED
CHIMBD, DICUL, AND DISMBD CORRESPOND TO TILLAGE SYSTEMS 1 TO
3. STD, DIV AND STR MEAN STANDARD, DIVIDED SLOPE AND STRIPCROP PRACTICES RESPECTIVELY. F#, WHERE # = 1,2,3,4,
CORRESPOND TO FERTILIZER APPLICATION RATE AND TIMING
STRATEGIES. SEE TABLES (5.2) - (5.5).
153
Table (6.12b): Budget Summary for Tillage Systems under
Standard, Divided Slope and Strip Crop
Practices. Green Pea after Winter Wheat-Athena Soil.
TILLAGE
FIXED
SYSTEMS
VARIABLE
COST
COST
TOTAL
COST
NET
RETURN
CHIMBD-STD-F1
CHIMBD-STD-F2
CHIMBD-STD-F3
120.86
115.29
139.74
33.10
33.10
33.10
153.96
148.39
172.84
63.04
68.61
44.16
DICUL-STD-F1
DICUL-STD-F2
DICUL-STD-F3
111.03
105.46
129.90
25.66
25.66
25.66
136.69
131.12
155.56
80.31
85.88
61.44
DISMBD-STD-F1
DISMBD-STD-F2
DISMBD-STD-F3
106.04
100.46
124.91
35.37
35.37
35.37
141.41
135.83
160.28
75.60
81.17
56.72
CHIMBD-DIV-Fl
CHIMBD-DIV-F2
CHIMBD-DIV-F3
134.37
128.25
155.05
34.59
34.59
34.59
168.96
162.84
189.64
48.04
54.16
27.36
DICUL-DIV-F1
DICtJL-DIV-F2
DICTJL-DIV-F3
124.23
118.11
144.91
28.59
28.59
28.59
152.82
146.70
173.50
64.18
70.30
43.50
DISMBD-DIV-F1
DISMBD-DIV-F2
DISMBD-DIV-F3
119.19
113.07
139.87
38.76
38.76
38.76
157.95
151.83
178.63
59.05
65.17
38.37
CHIMBD-STR-F1
CHIMBD-STR-F2
CHIMBD-STR-F3
153.46
146.79
175.94
38.70
38.70
38.70
192.16
185.49
214.64
24.84
31.51
2.36
DICUL-STR-F1
DICUL-STR-F2
DICtJL-STR-F3
142.26
135.59
164.74
31.31
31.31
31.31
173.57
166.90
196.05
43.43
50.10
20.95
DISMBD-STR-F1
DISMBD-STR-F2
DISMBD-STR-F3
134.71
128.04
157.19
41.48
41.48
41.48
176.19
169.52
198.67
40.81
47.48
18.33
CHIMBD, DICIJL, AND DISMBD CORRESPOND TO TILLAGE SYSTEMS 1 TO
3. STD, DIV AND STR MEAN STANDARD, DIVIDED SLOPE AND STRIPCROP PRACTICES RESPECTIVELY. F#, WHERE # = 1,2,3,
CORRESPOND TO FERTILIZER APPLICATION RATE AND TIMING
STRATEGIES. SEE TABLES (5.2) - (5.5).
154
On each soil type and crop rotation, tillage systems
using the mechanical conservation methods (divided slope and
strip cropping) were most expensive.
Strip cropping systems
cost between 25 and 35 percent more than standard practices,
while divided slope costs between 10 and 25 percent more.
Fixed costs did not vary significantly across tillage
practices on each soil.
Large differences occurred,
however, in the variable costs, reflecting differences in
the level of resource inputs used; that is, herbicides,
fertilizer and secondary tillages.
In divided slope and
strip crop practices, additional costs were incurred for
labor required to demarcate strips and cultivate boundaries,
and for additional operations in farming these strips during
the crop year27.
Thus, net returns were largest for
standard practices and lowest for strip cropping.
Costs of production for (SF-SB) rotation are lower than
for (SF-WW) rotation, a result of lower fertilizer
application rates; lower storage, marketing, handling and
other miscellaneous charges.
Net returns were also much
lower in spring barley production because of lower barley
price and yield, particularly on shallower Pilot Rock and
Ritzville soils.
On Athena soil, fixed costs are higher for
green pea production than winter wheat production because
more field operations are involved in preparing the soil for
pea planting.
Net returns from winter wheat production were
27Suggested by Hal Gordon, USDA-Soil Conservation
Service Economist, Oregon State Office, Portland.
155
much higher than from green peas, because of:
(1) higher
winter wheat yield on Athena soil, and (2) the deficiency
payment received for wheat production.
Results of the NLEAP Program
The NLEAP provided detailed estimates of potential and
actual crop nitrogen uptake, risk of moving nitrate-N
(NO3-N) below root zone (NRI), aquifer leaching risk
potential (ALRP), potential impact of nitrate-N leaching on
aquifer (Mu), nitrate-N available for leaching (NAL)
(NO3-N) actually leached beyond the root zone (NL).
and
Each
NLEAP report also included estimates of N losses through
runoffs/erosion, volatilization, nitrification and
mineralization.
On Walla Walla, Pilot Rock and Ritzville soils, the
largest MRI values were 0.48, 0.56 and 0.20.
These indices
indicated a 48, 56 and 20 percent chance of NO3-N moving
below the root zone that year.
were below 0.31.
low as 0.11.
Other reported MRI values
Dry years, in particular, had values as
On Athena soil, most NRI values obtained were
about 0.50, but much higher in very wet years.
The largest
value (0.88) obtained in the 1989/90 wheat production year,
implied an 88 percent chance of NO3-N moving below the root
zone that year.
In this same 1989/90 crop year, almost all
156
precipitation days were wet days (days with precipitation
greater than or equal to 0.20 inch), and annual
precipitation was well above average (23.37 inches).
The ALRP values were reported qualitatively as either
low or very low for all soils.
The Aquifer Risk Index (ARI)
projected beyond 10 years suggested the impact of NO3-N
leached on the aquifer will be very low.
All NO3-N losses
from runoffs/erosion reported were less than 3 lbs/acre for
all soils.
The most relevant NLEAP report for this research, were
the predicted nitrate leached each year, by production
practice and soil.
These can be found in Tables (6.13)
(6.19).
Across soils, NO3-N leached was influenced by type of
soil, type of tillage system, fertilizer application rate
and timing, and amount and distribution of precipitation.
Field slope had a small impact on annual leaching rates and
losses through runoffs/erosion in wet years.
On the
average, however, the impact was not noticeable.
This
latter result reflects the inability of NLEAP to
sufficiently monitor lateral flow of pollutant in the soil.
On Walla Walla soil, a significant amount of NO3-N
leaching occurred in wet years (crop years with annual
precipitation greater than or equal to 16 inches) for
winter wheat (Table 6.13).
Leaching occurred in only 3 of
the 10 years for the spring barley (SB) rotation (Table
157
6.14).
The highest leaching rate for wheat or barley
occurred in the 1982-83 and 1983-84 crop years when
precipitation exceeded 22.7 inches per year.
Table (6.13a):
CROP
YEAR
8283
Estimated Nitrate-N Leached (lbs/acre),
Wheat Production Year--3.5 percent Slope,
Walla Walla Soil.
83- 84- 85- 8684
85 86
87
87- 88- 89- 90- 9188 89
90
91 92
TILLAGE
SYSTEMS
MB-Fl
MB-F2
MB-F3
MB-F4
MB-F5
MB-F6
CH-F1
CH-F2
CH-F3
CH-F4
CH-F5
CH-F6
DI-F1
DI-F2
DI-F3
DI-F4
DI-F5
DI-F6
DIB-Fl
DIB-F2
DIB-F3
DIB-F4
DIB-F5
DIB-F6
DICH-F1
DICH-F2
DICH-F3
DICH-F4
DICH-F5
DICH-F6
10-YR
AVG
20
8
11
10
13
16
22
9
12
11
16
16
22
9
13
11
15
17
20
8
12
11
16
18
19
8
10
11
14
15
32
21
25
19
27
28
34
23
27
21
29
30
34
23
27
21
29
30
33
22
26
19
28
29
32
22
25
20
28
28
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
1
1
2
2
1
1
1
1
1
1
2
1
2
2
2
1
2
1
2
2
2
1
2
1
2
2
2
1
2
1
2
1
2
1
1
1
1
1
2
1
1
1
1
1
2
1
1
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
4
3
4
3
4
4
5
4
5
4
5
5
5
4
5
4
5
5
4
3
4
3
4
4
5
4
5
4
5
5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0'O
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
6
3
4
3
5
5
7
4
5
4
5
5
7
4
5
4
5
6
6
4
5
4
5
5
6
4
4
4
5
5
158
Table (6.13b):
CROP
YEAR
Estimated Nitrate-N Leached (lbs/acre),
Wheat Production Year--9.5 Percent Slope,
Walla Walla Soil.
82-
83- 84- 85- 86-
83
84
85
86
87
87- 88- 89- 90- 9188
89 90
91 92
TILLAGE
SYSTEMS
10-YR
AVG
MB-Fl
MB-F2
MB-F3
MB-F4
MB-F5
MB-F6
20
33
22
0
0
11
10
13
16
26
0
19
28
29
0
CH-F1
CH-F2
CH-F3
CH-F4
CH-F5
CH-F6
22
10
13
11
17
18
35
24
28
21
30
31
0
0
2
0
0
0
0
2
DI-Fi
DI-F2
DI-F3
DI-F4
DI-F5
DI-F6
22
10
35
24
DIB-F1
DIB-F2
DIB-F3
DIB-F4
DIB-F5
DIB-F6
21
DICH-Fi
DICH-F2
DICH-F3
DICH-F4
DICH-F5
DICH-F6
20
8
13
12
16
18
8
13
11
17
19
8
11
11
15
16
0
0
1
1
1
1
1
1
1
1
1
1
1
1
0
0
0
0
0
0
4
3
4
3
4
4
5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
6
4
4
3
5
5
0
0
0
2
2
1
1
1
1
1
0
4
5
4
5
5
0
2
2
0
5
0
0
0
0
0
0
1
2
1
1
4
1
1
1
1
0
0
0
0
0
0
0
0
5
34
23
27
19
29
30
0
0
0
2
1
2
2
0
0
0
0
0
0
4
0
0
0
2
1
1
1
1
1
4
4
0
0
0
0
0
0
33
23
0
0
0
2
1
2
2
0
0
0
5
4
5
0
0
0
0
0
0
0
0
0
6
0
1
1
4
0
0
0
4
0
2
1
1
0
0
0
5
5
0
0
0
0
0
0
5
5
28
21
30
31
26
20
29
29
0
1
1
2
2
2
1
2
1
1
1
0
0
5
4
5
3
4
3
0
0
0
0
7
4
5
4
6
6
7
4
5
4
5
6
6
4
5
4
5
6
4
5
159
Table (6.13c):
CROP
YEAR
Estimated Nitrate-N Leached (lbs/acre),
Fallow Year--3.5 or 9.5 Percent Slope,
Walla Walla Soil.
82-
83- 84- 85- 86-
83
84
85
86
87
87- 88- 89- 90- 9188
89 90
91 92
TILLAGE
SYSTEMS
10-YR
AVG
MB-Fl
MB-F2
MB-F3
MB-F4
MB-F5
MB-F6
3
2
2
1
1
1
2
2
2
9
2
2
12
1
1
3
3
CH-F1
CH-F2
CH-F3
CH-F4
CH-F5
CH-F6
0
0
0
8
0
0
0
2
2
2
0
0
0
0
2
1
DI-Fi
DI-F2
DI-F3
DI-F4
DI-F5
DI-F6
0
0
0
0
0
0
1
1
1
9
0
0
0
0
1
0
0
0
0
0
1
0
0
0
0
1
1
1
0
0
1
1
0
0
0
0
0
0
0
0
1
1
1
0
0
1
1
2
DIB-F1
DIB-F2
DIB-F3
DIB-F4
DIB-F5
DIB-F6
0
0
DICH-Fl
DICH-F2
DICH-F3
DICH-F4
DICH-F5
DICH-F6
0
0
0
0
9
0
0
9
0
0
014
112
111
112
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
2
1
1
0
0
0
2
0
0
0
0
0
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
0
0
2
0
0
160
Table (6.14a):
CROP
YEAR
8283
Estimated Nitrate-N Leached (lbs/acre),
Barley Production Year--3.5 Percent Slope,
Walla Walla Soil.
83- 84- 85- 8684
85 86
87
87- 88- 89- 90- 9188
89
90
91
92
TILLAGE
SYSTEMS
10-YR
AVG
MB-Fl
MB-F2
MB-F3
4
4
4
0
0
0
0
5
5
CH-F].
CH-F2
CH-F3
4
4
4
5
6
6
0
0
0
DI-Fl
DI-F2
DI-F3
4
4
4
5
6
6
DIB-F1
DIB-F2
DIB-F3
4
4
4
DICH-Fl
DICH-F2
DICH-F3
4
4
4
5
0
0
0
0
0
0
0
0
0
0
0
0
0
5
6
6
0
0
5
6
6
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
0
0
0
0
1
1
1
0
0
0
0
0
0
0
0
0
1
1
1
0
0
0
0
0
0
0
0
0
1
1
1
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
0
0
0
0
0
0
0
1
1
1
0
0
0
0
0
0
0
1
1
1
0
0
0
0
0
0
1
1
161
Estimated Nitrate-N Leached (lbs/acre),
Barley Production Year--9.5 Percent Slope,
Walla Walla Soil.
Table (6.l4b):
CROP
YEAR
8283
83- 84- 85- 8684 85
86 87
87- 88- 89- 90- 9188
89
90
91
92
10-YR
AVG
TILLAGE -.
SYSTEMS
MB-Fl
MB-F2
MB-13
4
4
4
5
5
6
0
0
0
CH-F1
CH-F2
CH-F3
5
5
5
5
6
6
DI-Fl
DI-F2
DI-F3
5
5
5
DIB-F1
DIB-F2
DIB-F3
5
DICH-Fi
DICH-F2
DICH-F3
0
0
0
0
0
0
0
1
1
1
1
1
1
0
0
0
0
0
0
0
0
0
1
1
1
0
1
1
1
0
0
0
0
0
0
0
0
0
1
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
0
0
0
0
0
0
1
1
1
0
0
0
0
0
0
0
1
1
1
0
0
0
0
0
0
0
0
0
5
6
6
0
0
0
0
5
5
5
6
6
5
5
5
5
6
6
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0-0
0
0
0
162
Table (6.15a):
CROP
YEAR
Estimated Nitrate-N Leached (lbs/acre),
Wheat Production Year--3.5 or 9.5 Percent
Slope, Pilot Rock Soil.
82-
83- 84- 85- 86-
83
84
85
86
87
87- 88- 89- 90- 9188
89 90
91 92
TILLAGE
SYSTEMS
SPR-Fl
SPR-F2
SPR-F3
SPR-F4
SPR-F5
SPR-F6
10-YR
AVG
26
20
2
15
25
23
29
24
26
22
28
28
SWP-Fl
SWP-F2
SWP-F3
SWP-F4
SWP-F5
SWP-F6
25
19
21
14
24
22
28
23
25
21
26
26
2
2
2
1
2
2
0
0
0
0
0
SSCtJ-Fl
SSCtJ-F2
29
24
26
22
28
28
2
2
2
2
2
2
1
1
SSCU-F3
SSCU-F4
SSCU-F5
SSCU-F6
26
20
22
15
25
23
CHI-Fl
CHI-F2
CHI-F3
CHI-F4
CHI-F5
CHI-F6
26
20
22
15
25
23
29
24
26
22
28
28
2
1
1
1
1
1
1
22
2
2
2
2
2
2
2
2
2
2
1
1
1
1
1
1
0
1
1
1
1
0
6
0
0
0
0
0
0
0
0
0
4
5
3
5
5
5
4
4
3
5
5
0
0
0
0
0
0
0
0
0
0
0
0
6
5
6
6
6
0
0
0
0
0
0
0
0
0
0
0
0
6
4
5
0
0
8
7
7
6
7
7
0
0
0
0
0
0
8
7
7
6
7
7
6
5
6
5
6
6
0
0
0
0
0
0
0
0
0
0
0
0
6
4
5
8
7
7
6
7
6
5
6
5
6
7
6
0
0
0
0
0
0
7
0
0
0
0
0
0
0
0
0
0
6
6
5
6
6
5
0
0
5
4
5
2
5
5
3
5
5
3
5
5
8
8
7
5
7
7
7
6
6
5
7
7
8
6
7
5
7
7
8
6
7
5
7
7
163
Table (6.15b):
CROP
YEAR
Estimated Nitrate-N Leached (lbs/acre),
Fallow Year--3.5 or 9.5 Percent Slope,
Pilot Rock Soil.
82-
83- 84- 85- 86-
87- 88- 89- 90- 91-
83
84
88
85
86
87
89
90
91
92
TILLAGE
SYSTEMS
10-YR
AVG
SPR-F1
SPR-F2
SPR-F3
SPR-F4
SPR-F5
SPR-F6
8
7
7
6
7
6
10
SWP-F1
SWP-F2
SWP-F3
SWP-F4
SWP-F5
SWP-F6
7
6
6
5
6
5
SSCU-F1
SSCU-F2
SSCU-F3
SSCU-F4
SSCU-F5
SSCU-F6
8
7
7
10
6
7
6
4
5
4
CHI-Fi
CHI-F2
CHI-F3
CHI-F4
CHI-F5
CHI-F6
7
6
6
5
6
5
6
5
5
5
4
4
4
4
3
7
6
5
4
4
5
0
0
0
0
4
3
0
0
7
6
6
5
0
0
0
7
5
6
4
3
6
6
7
6
4
4
6
6
6
5
3
4
4
5
4
4
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
0
0
0
0
0
0
2
2
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
2
2
2
2
1
2
2
2
2
1
2
2
1
2
2
2
2
2
1
164
Table (6.16):
CROP
YEAR
Estimated Nitrate-N Leached (lbs/acre),
Barley Production Year--3.5 or 9.5 Percent
Slope, Pilot Rock Soil.
82-
83- 84- 85- 86-
83
84
85
86
87
87- 88- 89- 90- 9188
89 90
91 92
TILLAGE
SYSTEMS
10-YR
AVG
SPR-Fl
SPR-F2
SPR-F3
12
12
12
11
11
11
0
0
0
0
0
0
0
0
SWP-Fl
SWP-F2
SWP-F3
10
10
10
10
10
10
0
0
0
CHI-Fl
CHI-F2
CHI-F3
12
12
12
11
11
11
0
0
0
3
3
3
0
0
0
0
0
3
3
3
3
0
0
0
0
3
3
3
0
0
0
0
0
0
0
0
0
2
2
2
0
0
0
0
0
0
3
3
3
3
3
0
0
0
0
0
0
0
0
0
3
0
0
0
0
0
0
3
3
3
3
3
3
3
3
3
165
Table (6.17):
CROP
YEAR
Estimated Nitrate-N Leached (lbs/acre),
Wheat Production Year--3.5 or 9.5 Percent
Slope, Ritzville Soil.
82-
83- 84- 85- 86-
83
84
85
86
87
87- 88- 89- 90- 9188
89 90
91 92
TILLAGE
SYSTEMS
10-YR
AVG
SPR-Fl
SPR-F2
SPR-F3
SPR-F4
SPR-F5
SPR-F6
9
7
8
8
8
8
5
5
5
5
5
SWP-F1
SWP-F2
SWP-F3
SWP-F4
SWP-F5
SWP-F6
8
6
7
6
7
5
4
4
4
5
7
5
SSCU-Fl
SSCU-F2
SSCU-F3
SSCU-F4
SSCU-F5
SSCU-F6
9
7
8
8
8
6
5
5
CHI-Fl
CHI-F2
CHI-F3
CHI-F4
CHI-F5
CHI-F6
9
7
8
8
8
8
8
6
5
5
5
6
5
5
5
5
5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
1
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
0
0
0
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
2
1
1
1
1
1
166
Table (6.18):
CROP
YEAR
Estimated Nitrate-N Leached (lbs/acre),
Barley Production Year--3.5 or 9.5 Percent,
Slope, Ritzville Soil.
82-
83- 84- 85- 86-
83
84
85
86
87
87- 88- 89- 90- 9188 89
90 91 92
TILLAGE
SYSTEMS
10-YR
AVG
SPR-Fl
SPR-F2
SPR-F3
3
SWP-Fl
SWP-F2
SWP-F3
CHI-Fi
CHI-F2
CHI-F3
2
2
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
2
2
2
2
2
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3
3
3
2
2
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
1
1
3
3
0
167
Table (6.19a):
CROP
YEAR
8283
Estimated Nitrate-N Leached (lbs/acre),
Winter Wheat after Green Pea Production
--3.5 or 9.5 Percent slope, Athena Soil.
83- 84- 85- 8685 86 87
84
87- 88- 89- 90- 9188
89
90
91
92
TILLAGE
SYSTEMS
CHIMBD-F1
CHINBD-F2
CHIMBD-F3
CHIMBD-F4
DICUL-Fi
DICUL-F2
DICUL-F3
DICUL-F4
DISMBD-Fl
DISNBD-F2
DISNBD-F3
DISMBD-F4
10-YR
AVG
0
0
0
0
0
0
0
0
0
0
0
0
Table (6.19b):
CROP
YEAR
8283
13
13
16
14
13
13
16
14
13
13
16
14
11
11
15
13
1].
11
14
13
1].
11
15
13
0
0
0
0
0
0
0
0
0
0
0
0
5
5
5
5
6
0
0
0
0
0
0
0
0
0
0
0
5
0
6
5
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
51
51
60
53
51
51
59
53
52
52
60
54
0
0
0
0
0
0
0
0
0
0
0
0
Estimated Nitrate-N Leached (lb/ac), Green
Pea after Winter Wheat Production--3.5 or
9.5 Percent Slope, Athena Soil.
83- 84- 85- 8684
85 86
87
87- 88- 89- 90- 9188
89
90
91
92
TILLAGE
SYSTEMS
CHIMBD-F].
8.00
8.00
9.70
8.50
8.00
8.00
9.50
8.50
8.10
8.10
9.70
8.60
10-YR
AVG
CHIMBD-F2
CHIMBD-F3
CHIMBD-F4
DICUL-Fi
DICUL-F2
DICUL-F3
0
0
0
0
7
7
1
0
8
23
23
DICtJL-F4
8
DISMBD-F1
DISMBD-F2
DISMBD-F3
DISMBD-F4
0
0
7
7
0
0
0
0
0
0
0
0
0
0
0
0
23
23
0
0
1
0
24
24
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
2
0
0
0
0
28
28
11
11
15
15
5
5
1
0
1
1
31
31
13
13
17
17
2
2
0
0
0
0
28
28
11
11
15
15
0.20
0.20
8.40
8.40
0.90
0.60
9.30
9.30
0.20
0.20
8.40
8.40
168
The combined fallow-crop average leaching rates, for
all tillage systems, varied between 15 and 28 lbs/ac/yr in
winter wheat production and about 5 lbs/ac/yr for spring
barley.
The 10-year average leaching rates in winter wheat
production varied between 3 and 7 ib/ac/yr, and less than
lb/acre in spring barley production.
2
Fertilization options
2 (split application of 30 lb/acre pre-plant and 65 lb/acre
topdress) and 4 (spring application at 110 lb/acre) produced
the lowest leaching rates.
Average leaching rates in all
fallow years but one were generally very low (less than 1
lb/ac/yr).
This was because the soil profile generally
contained insufficient moisture to leach.
The fallow period
preceded by fertilization option 4 (spring application at
110 lb/ac), consistently produced substantially higher
leachate levels than other production options.
This was
probably caused by high nitrate residual levels carried over
from the previous year.
On Pilot Rock soil, NO3-N leaching occurred in 7 of the
10 years on Summer fallow-winter wheat rotation; 40 to 47
percent of fertilizer applied in wet years leached beyond
the root zone.
Average leaching rates varied between 5 and
8 lb/ac/yr in the cropping season and less than 3 lb/ac/yr
in the fallow period in all tillage systems.
As expected,
average leaching rates from spring barley production were
much lower, (about 3 lb/ac/yr)1 with zero leaching in the
fallow period.
Leaching rates were similar on both 3.5 and
9.5 percent slopes and did not vary significantly with the
169
level of fertilizer application and timing.
Higher leaching
rates on this soil can be attributed to lower yield,
shallower soil, and fewer alternative tillage systems.
Winter wheat production on Ritzville soil produced the
lowest leaching rate.
Even in a wet year (1982/83),
leachate was less than or equal to 9 lb/acre in winter wheat
and less than or equal to 3 lb/acre in spring barley
production.
On the average, most tillage systems on
Ritzville soil had leaching rates of about 1 lb/acre for
both crop rotations.
Relative to Pilot Rock, with similar
tillage systems and fertilizer application rates/timing,
average leaching rates were less by as much as 86 percent in
winter wheat production, and by as much as 100 percent in
spring barley production.
This low leaching rate may be due
to deeper root zone and less rainfall than on Pilot Rock
soil, as soil moisture level usually does not reach
saturation for the entire root zone in most years.
On Athena Soil, a significant amount of NO3-N leaching
occurred in 4 of the 10 years for winter wheat production.
An equivalent of sixty to eighty five percent (about 51 to
60 lbs/ac) of fertilizer applied leached out in 1989/90 crop
year.
This was probably caused by greater number of wet
days prior to proper crop stand establishment.
Annually,
and on an average basis, the fertilizer application rate and
timing option (3)
(one time pre-application of 90 lbs/acre
of fertilizer) resulted in the most leaching.
rates were almost identical for other options.
Leaching
In green pea
170
production, leaching occurred in 5 of 10 years.
The highest
leaching rate occurred from fertilizer application and
timing option (3)
(100 lbs/acre pre-application of Anuuonium
Sulphate followed by topdressing with 25 lbs/acre Ammoniuin
nitrate fertilizer).
Leaching during pea production was
also greatest in the 1989/90 crop year.
Results of the MOP
The MOP solutions for the unrestricted soil loss and
NO3-N leaching rates (base scenario solution) represent the
most profitable production strategy given soil, resources
and other production methods available to the producers.
Under this scenario, farmers are assumed to ignore the
environmental consequences of their management decisions.
The levels of soil loss and nitrate leachate per acre
represent the environmental consequences of the profit
maximizing solution.
The maximum profit obtained from solution to the
unconstrained soil loss and leaching rate problem (base
scenario) served as the "bench-mark" for identifying
alternative production strategies that generated lower
erosion and (or) leachate at a given profit level.
The alternative production strategies represent the
optimal tillage systems, conservation practices, fertilizer
application rates and timing, land reallocation and
associated minimum pollution levels that occur when profit
171
is allowed to fall by $5, $10, $20, $30, $40 and
$50/acre28 below that achieved for the profit maximization
case.
These values are costs to producers of adopting
least-cost abatement techniques or implementing best
management practices (BMP).
A summary of these results are
presented in Tables (6.20) to (6.23).
The non-inferior
frontiers of soil loss and Nitrate-N leaching holding
abatement expenditure level constant (or "iso-abatement
curves"), are illustrated in Figures (6.1) to (6.4) for each
soil type.
Each frontier describes the locus of optimal
production strategies given different levels of importance
assigned to the two agricultural environmental pollutants.
Points p1 in each figure represents the optimal
solution when nitrate leaching reduction is the sole
environmental goal.
On the other hand, points p4 (including
p3 on the $10/acre abatement expenditure frontier for Athena
soil in Figure 6.4) represent solutions when all resources
are directed solely at minimizing soil loss.
Solution for
points between P1 and P4 (p3 on the $10/acre abatement
expenditure frontier for Athena soil), obtained by varying
the level of emphasizes on the two environmental objectives,
are also shown in the figures.
28These values were arbitrarily chosen.
A producer may
be reluctant to spend a high amount of money on abatement,
especially where crop yield and (or) net return is very low.
An alternative is using values that are percentage of the
maximum net return.
172
Although the results have similar implications across
soils, some useful insights can be obtained specific to each
soil situation.
The unregulated soil loss and nitrate
leaching rates associated with current practices vary from
farm to farm and across soils.
As a result, the
effectiveness of abatement measures and optimal responses by
producers also vary.
On all soils and all abatement expenditure levels, it
was possible to achieve a simultaneous reduction in soil
loss and nitrate-nitrogen leaching rates using the mixed
objective strategies.
Given a level of abatement
expenditure, once a certain low level of either pollutant
was achieved, the environmental cost (trade-off) of further
reducing a pollutant, increased.
This increase varied by
soil and level of abatement expenditure.
Walla Walla Soil
When environmental concerns were not a factor in the
decision process, the optimal (or base scenario) solution
was DICHW-STD-F6W (see Tables 5.2 and 5.5).
This solution
involved winter wheat production under standard practice,
using disk plow for primary tillage, followed by chisel
chopper and several secondary tillage operations.
The
fertilization strategy was a one time 80 lbs/acre nitrogen
fertilizer application, applied pre-plant.
The production
strategy produced an average soil loss rate of 7.18
tons/acre, an average NO3-N leaching rate of 5.02 lbs/acre,
173
and a potential maximum return to land and management of
$146.58/acre.
This return became the foundation on which
subsequent abatement expenditures were based.
A summary of the base solution and the set of noninferior solutions for 3 levels of abatement expenditures
($10, $30, and $50/ac), given varying weights on the
environmental objectives, are presented in Table (6.20), and
represented graphically in Figure (6.1).
Full results are
provided in Table (C.14), Appendix C.
Given an abatement expenditure level of $10/acre, point
p1 showed a minimum NO3-N leached of 3.64 lbs/acre,
representing a 27.5 percent leachate reduction from the
unconstrained (base scenario) solution.
The associated soil
loss rate of 7.18 tons/acre was the same as in the
unconstrained solution.
The production strategies (see
Table 6.20), used to generate these environmental outcomes
are similar to the base scenario, but employed split
fertilizer application (30 lbs/acre pre-plant, 65 lbs/acre
top-dressed) on 99 percent of farm acreage.
Although this
strategy reduced profit, it had a neutral effect on erosion
and a positive benefit in reducing leaching.
Point p4 for the same abatement expenditure level of
$10/acre represented a soil loss rate of 3.56 tons/acre,
accompanied by a 5.54 lbs/acre NO3-N leaching rate.
This
solution produced a 50.4 percent reduction in soil loss
rate, but a 10.4 percent increase in leaching over the base
scenario.
174
Table (6.20):
Abatement
Expense
Multi-Objective Programming (MOP) Optimal
Solution, Walla Walla Soil.
Weights
Soil loss
NO3-N
Leached
(tons/ac)
(lbs/ac)
Production System
in Solution and
Percentage of
Farm Acreage.
(S/acre)
Wh
0 (BASE)
0.00
0.00
7.18
5.02
DICHW-STD-F6W
100.0
10
1.00
0.00
7.18
3.64
3.08
1.01
5.01
4.31
3.62
1.90
4.10
4.65
0.00
1.00
3.56
5.54
DICHW-STD-F2W
DICHW-STD-F6W
CHW-STD-F2W
DICHW-STD-F6W
CHW-STD-F2W
CHW-STD-F6W
CHW-STD-F6W
CHW-DIV-F6W
98.7
1.3
70.4
29.6
58.6
41.4
80.4
19.6
1.00
0.00
9.91
2.90
7.11
0.82
6.55
3.07
8.16
2.64
2.80
3.72
0.00
1.00
1.75
5.54
DICHW-STD-F2W
DICHB-STD-F1B
DICHW-STD-F2W
CHB-DIV-F1B
CHW-STD-F2W
DICHW-DIV-F2W
CHW-STD-F6W
CHW-DIV-F6W
72.5
27.5
79.1
20.9
25.7
74.3
14.6
85.4
1.00
0.00
12.65
2.17
44.8
55.2
10.21
0.96
5.91
2.52
11.80
3.37
2.44
3.13
0.00
1.00
0.85
5.54
DICHW-STD-F2W
DICHB-STD-F1B
DICHW-STD-F2W
CHB-DIV-F1B
DICHW-DIV-F2W
DICHB-STR-F1B
CHW-DIV-F6W
CHW-STR-F6W
30
50
We
58.].
41.9
81.4
18.6
26.3
73.7
STD = standard tillage, DIV = divided slope, STR = strip
cropping.
F#W and F#B (# = 1,2...6) = fertilizer
application rate and timing option #, in SF-WW and SF-SB
respectively.
Tillage systems are: DICHW = disking followed
by chiselling in SF-WW; DICHB = disking followed by
chiselling in SF-SB; CHW = chiselling in SF-WW; CHB =
chiselling in SF-SB
175
15
Abatement
Expenditure = $50/Ac
p1
Abatement
Expenditure = $30/Ac
-I
p1
IAbatement.
5/
Expenditure = $10/Ac
I
Base Scenario
p2
p2
p4
p3
p4
p4
0
I
I
1
2
3
-I
I
I
I
4
5
6
7
8
9
Nitrate-N Leached (Lbs/Ac/Yr)
Figure (6. 1):
Iso-Abatement Cost Curves Describing the
Trade-off s between Soil Loss from Erosion and
Nitrate-N Leached on Walla Walla Soil.
176
The optimal production technique (associated with p4) was a
chisel plow tillage system on all acreage, with about 20
percent of acreage also farmed using divided slope. The
fertilizer application strategy remained the same as in the
base scenario.
When the sole focus was on nitrate leaching
(p1), reductions were achieved without increasing erosion.
But when the sole focus was on reducing erosion, leaching
increased.
Mixed objective optimal strategies (for $10/acre
expenditure), such as those associated with points p2 and
p3, resulted in a reduction of both leaching and soil loss
rates.
The strategies at P2 and P3 reduced leaching by 14.1
and 7.4 percent and soil loss rate 30.2 and 42.9 percent,
respectively, over the base scenario.
For an abatement expenditure of $30/acre, the optimal
strategy generated minimum leachate of 2.90 lbs/acre, or a
42.3 percent reduction over the base scenario.
This
strategy generated an increase in soil loss (over the base
scenario) of 38 percent or a loss of 9.91 tons/acre.
Holding abatement expenditures to $30/acre and shifting all
emphasis to reducing soil erosion (point p4) resulted in a
strategy that reduced erosion to 1.75 tons/acre and
increased leaching to 5.54 lbs/acre.
These rates represent
a 75.6 percent reduction in soil loss and 10.4 percent more
leaching than in the base scenario.
177
An abatement expenditure of $50/acre resulted in a
strategy (p1) that had a minimum leachate of 2.17 lbs/acre
and an associated soil loss of 12.65 tons/acre.
For the
$50/acre expenditure, the strategy that minimized soil loss
(p4) produced 0.85 ton/acre of erosion and 5.54 lbs/acre of
nitrate leached.
The strategies resulting from mixed objectives on all
abatement expenditure frontiers, were complementary as they
allowed a reduction in both NO3-N leaching and soil loss.
Across frontiers, when emphasis was placed solely on solving
soil loss problem, the optimal strategies shifted to chisel
plow for primary tillage and reduced the proportion of total
farm acreage under standard practice.
Beyond $30/acre
abatement expenditure, farm operation mostly under divided
and strip crop practices accomplished a large reduction in
soil loss.
Increase in spring barley acreage and use of
different (from base scenario) fertilization option (2) for
winter wheat crop, reduced leachate significantly.
The production strategy p1 on $50/acre abatement
expenditure frontier was most successful in reducing
leachate, but at a relatively high average cost ($17.54 per
pound of NO3-N leachate reduced).
Nitrate minimizing for
the $10 and $30 abatement expenditure frontiers reduced
leachate at a lower average cost ($7.25 and $14.15, per
pound per acre).
These average costs also fail to account
178
for the environmental costs associated with increased soil
erosion under the $30/acre and $50/acre abatement
expenditures.
The strategies associated with point p4 on the $50/acre
abatement expenditure frontier had the greatest effect on
reducing erosion, but at the highest average cost ($7.90 per
ton).
By comparison, lower expenditure of $10/acre and
$30/acre generated soil erosion benefits that cost only a
$2.76 and $5.52 per ton.
These costs did not include the
environmental cost of a slight increase (0.52 lb/acre) in
NO3-N leaching rate.
By comparison of the average costs of
reducing only either pollutant, it seemed more economical to
target a reduction in soil loss, on Walla Walla soil, than a
reduction in leachate.
The slope of a line segment connecting two adjacent
optimal points on a frontier represents something akin to
the marginal rate of technical substitution, with tradeoffs
occurring between pollutants rather than production inputs.
We will call this slope the Marginal rate of Externality
Substitution (MRES).
Mathematically, MRES is calculated as
3 erosion
3 leachate, abatement cost = constant
For example, for $10/acre abatement expenditure frontier,
the slope of the line segment connecting p1 and p2 indicated
that, a reduction in NO3-N leaching rate from 4.31 lbs/acre
to 3.64 lbs/acre, was accompanied by an increase in soil
179
loss rate of 2.17 tons/acre (from 5.01 tons/acre to 7.18
tons/acre), an MRES of 3.24.
Similarly, the slope of the
line segment p3 and p4 indicated a reduction in soil loss
from 4.10 tons/acre to 3.56 tons/acre accompanied by a 0.89
lb/acre increase in NO3-N leaching (from 4.65 to 5.54
lbs/acre) for an MRES of 0.61.
Hence, along the $10/acre
abatement expenditure frontier, the MRES varied between 0.60
and 3.24 tons/acre.
For $30 and $50/acre expenditures
frontiers, the NRES varied between 0.58 and 19.61 tons/acre,
and between 0.66 and 19.26 tons/acre respectively.
Pilot Rock Soil
As mentioned earlier, Pilot Rock is among soils
classified as highly erodible (HEL).
Consequently the MOP
constraints were formulated differently to meet or exceed
the standard of less than or equal to 3 times the T-value,
or an acceptable erosion level of 6 tons/acre.
The profit
maximizing production strategy was SWPW-STD-F6W, which
involved planting winterwheat only, using sweep plow for
primary tillage and a single, pre-plant fertilizer
application.
This base solution produced an average soil
loss rate of 2.52 tons/acre, an average NO3-N leaching rate
of 7.80 lbs/acre,and a potential return to labor and
management of $66.56/acre.
The base solution and the set of
non-inferior solution strategies for $10, $30 and $50/acre
levels of abatement expenditures are summarized in Table
180
(6.21).
The maximum attainable profit and associated
optimal tillage practices for the various T-values are in
shown in Table (C.13), in Appendix C.
The frontiers of the set of non-inferior solutions for
the three abatement expenditure levels, are shown in Figure
(6.2).
C.
Full results are provided in Table (C.l5), Appendix
The production strategies, associated soil loss and
NO3-N leaching rates associated with points p1 - p4 on all
abatement expenditure frontiers can be interpreted similarly
as with Walla Walla soil.
Some differences existed between
results for these two soils.
When emphasis was focused solely on reducing leachate,
strategies at p1 on $10, $30 and $50/acre abatement
expenditure frontiers generated 24.7, 59.5 and 68 percent
leachate reductions over the base scenario.
These
reductions occurred at average costs of $5.18, $6.47 and
$9.40 per pound, a 28 to 54 percent lower than for Walla
Walla soil.
The average costs associated with these nitrate
leachate reductions excluded the environmental cost of an
increase of 1.01 tons/acre or a benefit of 1.13 tons
decrease in soil loss.
Production strategies involving sweep plow tillage were
predominant in optimal solutions for Pilot Rock soil.
The
Sweep plow tillage system under standard practice, combined
with other fertilization options remained in solution until
abatement expenditure reached $50/acre.
181
Table (6.21):
Abatement
Expense
(S/acre)
Multi-Objective Programming (MOP) Optimal
Solution for Soil Loss Less than or Equal to
3T-Value, Pilot Rock Soil.
Weights
Wh
We
Soil loss
NO3-N
Leached
(tons/ac)
(lbs/ac)
Production System
in Solution and
Percentage of
Farm Acreage.
0 (BASE)
0.00
0.00
2.52
7.80
SWPW-STD-F6W 100.0
10
1.00
0.00
3.53
5.87
1.90
1.93
2.47
6.16
0.84
1.64
2.19
6.65
SWPW-STD-F6W
SWPW-STD-F4W
SWPB-STD-F1B
SWPW-STD-F4W
SWPB-STR-F1B
SWPW-STD-F6W
SWPB-STR-F1B
0.00
1.00
1.63
7.80
30
50
1.00
0.00
3.53
3.16
1.88
0.98
2.15
3.75
3.08
4.64
1.65
4.14
0.00
1.00
0.45
7.80
1.00
0.00
1.39
2.50
0.74
3.10
0.99
2.50
0.34
3.10
0.75
4.08
0.00
1.00
0.65
5.60
SWPW-DIV-F6W
43.7
27.7
28.6
96.3
3.7
78.4
21.6
47.4
52.6
SWPW-STD-F4W
SWPB-STD-F1B
SWPB-DIV-F1B
SWPW-STD-F4W
SWPB-DIV-F1B
SWPW-STD-F4W
SWPB-STR-F1B
SWPW-DIV-F6W
SWPW-STR-F6W
17.4
35.8
46.8
33.0
67.0
43.1
56.9
8.5
91.5
SWPB-DIV-F1B
SWPB-STR-F2B
SWPB-STR-F1B
SWPB-STR-F3B
SWPW-STR-F4W
SWPB-STR-F3B
SSCUW-STR-F4W
CHIB-STR-F3B
40.5
59.5
63.0
37.0
41.7
58.3
62.9
37.1
SWPW-STD--F6W
STD = standard tillage, DIV = divided slope, STR = strip
cropping.
F#W and F#B (1/ = 1,2. ..6) = fertilizer
application rate and timing option #, in SF-WW and SF-SB
Tillage systems are: SWPW = sweep plowing in
respectively.
SF-WW; SWPB = sweep plowing in SF-SB; SSCUW = herbicide
spray followed by sweep plow and cultiweeding in SF-WW and
CHIB = chiselling in SF-SB.
182
15
Abatement
Expenditure = $30/Ac
I-
Abatement
Expenditure = $50/Ac
-\
Abatement
Expenditure = $10/Ac
J
tp
p1
Base Scenario
I
p2
p
p1
p2
p4
p3
P4
1
0
1
1
2
3
p4
I
I
I
I
4
5
6
7
8
9
Nitrate-N Leached (Lbs/Ac/Yr)
Figure (6.2):
Iso-Abatement Cost Curves Describing the
Trade-of fs between Soil Loss from Erosion and
Nitrate-N Leached on Pilot Rock Soil.
183
Spring barley production was optimal at abatement
expenditure of $10/acre or more.
Acreage planted into wheat
decreased as abatement expenditure increase.
At $50/acre,
all farm acreage was devoted to spring barley using sweep
plow tillage system, divided slope and strip crop practices,
with spring barley fertilization options (1) and (2)
(pre-
plant application of 25 and 45 lbs/acre of fertilizer,
respectively).
These strategies had a complementary impact
on soil loss and NO3-N leaching.
When all emphasis was placed solely on reducing soil
erosion, more winter wheat acreage was produced under
divided slope and (or) strip crop practices.
At the
$50/acre abatement expenditure, production shifted to a
combination of tillage systems involving the use of
herbicide prior to sweep plow for winter wheat production on
most acreage, with spring barley production using chisel
plow on remaining acreage.
cropping.
All acreage was devoted to strip
Production of spring barley enable a reduction
also in leaching rate.
The average costs per ton of soil loss were $11.24,
14.49 and $26.74/acre corresponding to $10, $30 and $50
abatement expenditure levels.
These costs, which were one
and a half to three times greater than in Walla Walla soil
also ignored the benefit of a 2.20 lbs/acre reduction
soil loss.
in
At abatement expenditure of $50/acre, all pure
and mixed objective strategies caused a significant
reductions in both leachate and soil loss.
This expenditure
184
level may not be acceptable or economical to all producers
because it is a great percentage (75 percent) of the net
earning, especially on a marginal land such as Pilot Rock.
On the abatement frontiers, the Marginal Rate of
Externality Substitution (NRES) varied from very low to very
high as 0.49 - 3.65 tons/acre, 0.32 - 2.33 tons/acre and
0.07 - very large amount of soil loss, respectively.
A comparison of the soil loss rates with the maximum
tolerance rate of 6 tons/acre, indicated that soil loss is
within acceptable level.
The relatively high leaching rate
showed that Pilot Rock soil may be prone to excessive
leaching, and emphasis should be focused on leaching only.
Abatement expenditure of $10/acre achieved only a 25 percent
reduction, whereas $30/acre accomplished about 60 percent
reduction in leaching with no impact on erosion.
Ritzville Soil
Ritzville soils were characterized by very low levels
of both soil erosion and NO3-N leaching.
The profit
maximizing solution for this soil was to plant entire farm
acreage to winter wheat, employing sweep plow for primary
tillage, no special field layout and applying 40 lbs/acre
nitrogen fertilizer at the pre-plant production stage (SWPWSTD-F6W).
This strategy generated an average soil loss rate
and NO3-N leaching rate of 1.54 tons/acre and 1.20 lbs/acre,
respectively, with a potential maximum profit of
$95.91/acre.
Table (6.22) contains a summary of the base
185
solution and the set of non-inferior solutions for abatement
expenditure levels of $10/acre,$30/acre and $50/acre. The
abatement expenditure frontiers for the Ritzville soils, are
shown in Figure (6.3).
The full results are provided in
Table (C.16), Appendix C.
The optimal tillage systems and practices were almost
identical to those in Pilot Rock soil, but varied slightly
in the fertilization option.
Again, spring barley became a
more preferred option as abatement expenditure levels
increased.
At (p1), where emphasis was placed exclusively on NO3-N
leaching, reductions were achieved at average costs of $40,
$49 and $63 per pound on $10, $30 and $50/acre abatement
expenditure frontiers.
These costs were many times greater
than those incurred on the Walla Walla and Pilot Rock soils.
The average costs of reducing soil erosion only were
also relatively high at $20, $24.79 and $39.37 per ton.
One
should recognize, however, that the environmental
degradation levels were lower on Ritzville soils than any
other soil series considered in the study.
Because there
was relatively little room for improvement, the cost of
achieving any improvements was relatively high.
The NRES
along the abatement expenditure frontiers, were 1.70 - 6.80,
1.93 - 12.46 and 0.50 - 17.70 tons of soil loss,
respectively.
The mixed objective strategies allowed a
reduction in both leaching and soil loss rate while all the
pure strategies were non-complementary.
186
Table (6.22):
Abatement
Expense
Multi-Objective Programming (MOP) Optimal
Solution, Ritzville Soil.
Weights
Soil loss
NO3-N
Leached
(tons/ac)
(lbs/ac)
Production System
in Solution and
Percentage of
Farm Acreage.
($/acre)
Wh
We
0 (BASE)
0.00
0.00
1.54
1.20
SWPW-STD-F6W 100.0
10
1.00
0.00
1.74
0.95
91.1
0.69
0.25
1.40
1.00
0.35
0.20
1.32
1.04
0.00
1.00
1.05
1.20
SWPW-STD-F2W
SWPB-STD-F1B
SWPW-STD-F2W
SWPW-DIV-F2W
SWPW-STD-F2W
SWPW-DIV-F6W
SWPW-STD-F6W
SWPW-DIV-F6W
1.00
0.00
3.02
0.59
1.84
0.17
1.40
0.72
2.69
0.61
1.18
0.76
0.00
1.00
0.33
1.20
SWPW-STD-F2W
SWPB-STD-F1B
SWPW-STD-F2W
SWPB-DIV-F1B
SWPW-STD-F2W
SWPW-STR-F2W
SWPW-DIV-F6W
SWPW-STR-F6W
31.7
68.3
53.0
47.0
60.2
39.8
28.3
71.7
1.00
0.00
2.52
0.40
1.94
0.24
1.28
0.47
2.25
0.87
0.58
0.64
0.00
1.00
0.27
1.27
SWPB-STD-F1B
SWPB-STR-F1B
SWPW-STD-F2W
SWPB-DIV-F1B
SWPW-DIV-F2W
SWPB-STR-F1B
SSCUW-STR-F4W
CHIB-STR-F3B
61.5
38.5
12.2
87.8
40.7
59.3
96.3
3.7
30
50
8.9
85.9
14.1
78.0
21.0
51.6
48.4
STD = standard tillage, DIV = divided slope, STR = strip
cropping.
F#W and F#B (# = 1,2...6) = fertilizer
application rate and timing option #, in SF-WW and SF-SB
respectively. Tillage systems are: SWPW = sweep plowing in
SF-WW; SWPB = sweep plowing in SF-SB; CHIB = chiselling in
SF-SB; SSCUW = herbicide spray followed by sweep plow and
cultiweeding in SF-WW.
187
15
14
0
l0
I-
0
Abatement
Expenditure = $50/Ac
0
14
0
Abatement
Expenditure
14
44
$30/Ac
-I
0
I-
0
Abatement
Expenditure = 10/Ac
p1
Wi
p1'
p2
P3
0
Base Scenario
p4
p4
I
I
T
1
2
3
4
5
6
7
8
9
Nitrate-N Leached (Lbs/Ac/Yr)
Figure (6.3):
Iso-Abatement Cost Curves Describing the
Trade-of fs between Soil Loss from Erosion and
Nitrate-N Leached on Ritzville Soil.
188
Athena Soil
Athena soils differs from the Walla Walla, Ritzville
and Pilot Rock soils in that no fallow year is included in
the rotation.
The optimal base solution strategy involved
the use of disk plow for primary tillage, cultivator for
secondary tillage and standard practice for both winter
wheat and green pea production and a 60 lbs/acre fertilizer
application for wheat (DICUL-STD-F2).
This production
strategy generated an average soil loss of 6.75 tons/acre,
average leachate of 8.60 lbs/acre, and a return to land and
management of $278.32/acre.
The results for the $10/acre,
$30/acre and $50/acre abatement expenditure levels are
summarized in Table (6.23), and represented graphically in
Figure (6.4).
The full results are in Table (C.17), in
Appendix C.
All resources directed at minimizing leachate (points
p1) achieved a mild 0.40 lb/acre (4.7 percent) reduction.
Because of the insignificant reduction in leaching, the
average cost of the 0.40 lb/acre improvement in leachate
reduction was very high at $25, $75 and $125 per pound for
abatement expenditure levels of $10, $30 and $50/acre,
respectively.
None of the optimal strategies was able to
reduce leaching significantly, even for fertilizer option
(2)
(application of 60 lbs/acre nitrogen fertilizer for
winter wheat and zero application for green pea).
The
reason for the ineffectiveness of these strategies may be
because of higher level of surface residue retained by the
189
various tillage systems.
Surface residues "trap" pools of
water on the soil surface, thus retarding soil erosion.
Very slow run-off s enhance water percolation and promote
leaching.
The associated strategies had a non-complementary
impact on soil loss at abatement expenditure of $30/acre or
less, and substitute impact above $30/acre.
When the objective was to minimize soil loss, the
strategies accomplished a significant reduction with
increased abatement expenditure.
The average costs of $8,
$8 and $10.22/ton/acre, were the lowest of any soil
considered in the study.
The mixed objective strategies had
a greater impact on reducing erosion, but did not perform
any better than the pure strategies.
The MRES along the $10/acre abatement expenditure
frontier varied between 3.67 and 5.58 tons/acre.
At maximum
leachate rates, NRES were 3.85 and 1.18 tons/acre, for $30
and $50/acre abatement expenditures; no trade-off between
soil loss and leachate was possible beyond 8.20 lbs/acre
leachate.
On Athena soils, the alternative practices were much
more effective inreducing erosion than leachate;
unfortunately, the soil seemed most capable of generating
sufficient leachate to cause groundwater quality problems.
Perhaps one positive outcome from this analysis was the lack
of strong correlation between erosion and leachate.
Thus a
farmer operating on the Athena soil could focus on reducing
erosion without worrying about an increase in leaching.
190
Table (6.23):
Abatement
Expense
Multi-Objective Programming (MOP) Optimal
Solution, Athena Soil.
Weights
Soil loss
(tons/ac)
NO3-N
Leached
(lbs/ac)
Production System
in Solution and
Percentage of
Farm Acreage.
($/acre)
Wh
We
0 (BASE)
0.00
0.00
6.75
8.60
DICUL-STD-F2
100.0
10
1.00
0.00
7.87
8.20
2.37
0.40
5.83
8.51
0.00
1.00
5.50
8.60
DICUL-STD-F2
DISMBD-STD-F2
CHIMBD-DIV-F2
DICUL-STD-F2
DICUL-STD-F2
DICUL-DIV-F2
0.4
99.6
21.5
78.5
72.4
27.6
1.00
0.00
6.86
8.20
3.87
0.40
4.92
8.20
1.93
0.40
3.99
8.34
0.00
1.00
2.99
8.60
CHIMBD-STD-F1
CHIMBD-STR-F1
CHIMBD-DIV-F2
DISMBD-STD-F2
CHIMBD-DIV-F2
DICUL-STD-F2
DICUL-STD-F2
DICUL-DIV-F2
89.7
10.3
54.7
45.3
64.5
35.5
17.0
83.0
1.00
0.00
5.32
8.20
CHIMBD-STD-F1
65.2
34.8
91.9
30
50
CHfl'IBD-STR-Fl
3.76
0.40
2.37
8.20
0.51
0.40
1.99
8.49
0.00
1.00
1.86
8.60
CHIMBD-DIV-F2
CHIMBD-STR-F2
DICUL-DIV-F2
DISMBD-STR-F2
DICUL-DIV-F2
DICUL-STR-F2
8.].
73.7
26.3
68.4
32.6
STD=standard tillage, DIV=divided slope, STR = strip
cropping. F/I (#= 1,2,3,4) = fertilizer application rate and
timing option # in WW-GP. Tillage systems are: DICUL = use
of disk plow for primary tillage followed by use of
cultivator for secondary tillage, in both WW and GP
production period; DISMBD = use of disk plow for primary
tillage in WW production period and iuoldboard plow in GP
production period; CHIMBD = use of chisel plow for primary
tillage in WW production year and moldboard plow in GP year.
191
15
0
Base Scenario
(Abatement
0
-'-4
Expenditure = $10/Ac
m
0
p1.
I
14
p1
(Abatement
Expenditure = $30/Ac.
0
J-4
'44
w
0
-'-4
0
U)
(Abatement
1.. Expenditure = $50/Ac
I
0
1
I
2
I
I
I
I
I
3
4
5
6
7
8
9
Nitrate-N Leached (Lbs/Ac/Yr)
Figure (6.4):
Iso-Abatement Cost Curves Describing the
Trade-of fs between Soil Loss from Erosion and
Nitrate-N Leached on Athena Soil.
192
CHAPTER VII
SUMMARY, COMMENTS AND LIMITATIONS
The primary objective of this study was to examine the
economic and environmental impact of reducing soil erosion
and groundwater pollution under dryland farming systems in
the Umatilla County area of Oregon.
Soil loss and nitrate leaching are bi-products of
agricultural production that result in externalities.
The
potential impact of these agricultural externalities on
environmental quality and human health prompted an
examination of current and potential production strategies.
The study objective was to identify the potential economic
costs of reducing soil erosion and leachate on four soil
associations in Umatilla County.
Four models were employed to accomplish the study
objectives:
(1) the second generation of the Universal Soil
Loss Equation (USLE), which provided estimates of annual
soil loss per acre; (2) Micro-computer Budgeting Management
System (MBMS), used to generate enterprise budgets; (3)
Nitrate Leaching and Economic Analysis Program (NLEAP),
which provided estimates of the NO3-N that leached beyond
the root zone; and (4) Multi-Objective Linear programming
(MOP) helped to identify optimal production strategies,
given limited resources (abatement expenditures), and
different levels of emphasis on the environmental objectives
of minimizing soil loss and (or) NO3-N leached.
193
The results of the USLE provided insight into the
extent of soil erosion in the study area.
On all soils,
high amounts of soil loss occurred because of one or more of
the following:
(1) use of moldboard plow tillage systems;
(2) fields in spring barley production; and (3) crop
production on relatively steep terrain.
Divided slope and
strip cropping consistently reduced soil losses by more than
50 percent over standard practice.
Walla Walla soil was the most erosive of all soils
investigated.
Tillage systems utilizing iuoldboard plow or
residue burning techniques generated largest annual soil
losses at 21 and 43 tons/acre on winter wheat and spring
barley fields, under the standard practice.
High
precipitation levels seemed to be the major factor causing
these high soil loss rates.
The highest annual erosion levels on the Pilot Rock and
Ritzville soils were 10.5 and 6 tons/acre, respectively.
Existing tillage practices tended to leave more residue on
soil surface, minimizing soil losses.
Moreover, both soils
are located in lower precipitation zones.
Very high soil loss rates were expected from Athena
soil because most of the tillage systems on the soil
involved use of moldboard plow and also because the soil is
located in a higher precipitation zone relative to Walla
Walla soil.
In fact, soil losses were much lower than on
Walla Walla soil but slightly higher than on Pilot Rock
soils.
The largest annual soil loss of 13 tons/acre came
194
from a tillage system that involved disk and moldboard
plows.
Athena soil is continuously cropped, thus always has
a crop or residue on the surface that protects the soil from
erosion.
The NLEAP provided estimates of average leaching rates.
The rates varied by soil type, crop, fertilization technique
and amount of annual precipitation.
The highest leaching
rates occurred during winter wheat production, with very
little during spring barley production or in fallow periods.
Field slope, to the extent examined in this study, had
little or no impact on leaching.
The Pilot Rock soil series
had the largest average leaching rate of about 10 lbs/acre.
Next were the Athena soils with leaching as large as 9.7
lbs/acre during winter wheat production period, and 9.3
lbs/acre in green pea production whenever ammonium sulphate
fertilizer was applied to the peas.
The leaching rate on
Walla Walla soils was smaller than on Pilot Rock or Athena
soils (about 7 lbs/acre).
Ritzville leached the least at 2
lbs/acre, with virtually no leaching during fallow period.
Multi-Objective Programming (MOP) delineated
alternative optimal production strategies, given different
levels of emphasis on reducing both pollutants.
Production
strategies that focussed on controlling only one pollutant
generally caused the other pollutant to increase.
Only at
relatively high abatement expenditure levels did strategies
aimed at reducing one pollutant also reduce the other.
This
195
pattern, however, did not hold for all situations.
The
environmental consequence of focusing solely on reducing
either pollutant is summarized in Table (7.1).
Table (7.1):
Implication of directing all Resources at
Reducing either Soil Loss or Leaching Rates
Generated in the Base Scenario.
All Resources aimed
All Resources aimed
at Reducing Soil loss at Reducing Leaching
Soils
Cost*
NO3-N
Soil loss Leached
(Tns/Acre) (Lbs/Ac)
NO3-N
Leached
Soil loss
(Lbs/Ac)
(Tns/Acre)
Walla Walla
$10
$30
$50
50% decr.
76% decr.
88% decr.
0% incr.
10% incr. 27% decr.
10% incr. 42% decr. 38% incr.
10% incr. 57% decr. 76% incr.
Pilot Rock
$10
$30
$50
35% decr.
82% decr.
74% decr.
0% incr. 25% decr. 40% incr.
0% incr. 60% decr. 40% incr.
28% decr. 68% decr. 44% decr.
Ritzville
$10
$30
$50
32% decr.
79% decr.
83% decr.
0% incr. 21% decr. 13% incr.
0% incr. 51% decr. 96% incr.
6% incr. 67% decr. 64% incr.
Athena
$10
$30
$50
19% decr.
56% decr.
72% decr.
0% incr.
0% incr.
0% incr.
*
5% decr. 17% incr.
2% incr.
5% decr.
5% decr. 21% decr.
Abatement Expenditures ($/Ac).
On Walla Walla soil, the unrestricted soil loss and
leaching rates under a profit maximization problem were 7.18
tons and 5.02 lbs/acre.
The most cost effective strategy to
reduce erosion at low abatement expenditures involved use of
chisel plowing for primary tillage under standard
conservation practice during winter wheat production.
This
196
management strategy caused a mild increase in leachate.
A
larger reduction in soil loss was achieved by operating more
of the farm acreage under divided slope and (or) strip crop
practices.
These practices involved higher abatement costs
for strip demarcation, boundary cultivation and maintenance
of the strips during the cropping season.
Large leachate reductions in winter wheat production
were achieved by using disk plow for primary tillage
followed by chisel plow for secondary tillage and a split
fertilizer application, with about two-thirds of the
fertilizer applied as top-dress.
Shifting more acres from
winter wheat to spring barley significantly reduced the
leaching rate, but at the expense of a decrease in net
returns and an increase in erosion.
Increased abatement expenditures focused solely on
reducing erosion achieved as much as an 88 percent reduction
in soil loss rate, with a 10 percent increase in leachate
rate.
Abatement expenditures directed solely at minimizing
leaching, achieved a reduction of as much as 57 percent, but
at the expense of as high as 76 percentage increase in soil
loss rate.
The unconstrained erosion and leaching profit
maximization problem on Pilot Rock soil generated very low
soil loss rates and high leaching rates (2.52 tons and 7.80
lbs/acre).
The production strategy that involved use of
197
sweep plow for primary tillage with one time spring
fertilizer application and (or) a shift of more acreage from
wheat to spring barley reduced leaching considerably.
When only soil erosion was targeted, a reduction of up
to 82 percent in soil loss was achieved without any change
in current leaching rate.
At the $50/acre abatement cost,
large soil loss reductions were accompanied by a 28 percent
decrease in leaching.
Placing sole emphasis on reducing
leachate reduced the pollutant by as much as 68 percent but
caused an increase in soil loss rate by 44 percent (a level
still below soil T-value).
The low soil loss and high
leaching rates implied that Pilot Rock soils may be more
prone to leaching problems, and control should therefore be
primarily aimed at reducing leaching rate.
Soil loss and leaching rates were generally very low on
Ritzville soils.
These low rates are an indication that
Ritzville soils may not be subject to soil erosion or
leaching problems.
Unconstrained soil loss and leaching
rates on Athena soils were 6.75 tons and 8.60 lbs/acre.
A
minimum of $30/acre abatement expenditure for chisel or disk
plow and for conservation practices (divided slope) was
necessary to reduce soil loss rate to less than 5 tons/acre
(the soil T-value).
When emphasis was solely on reducing soil loss,
significant amount of reduction was accomplished with no
change in leaching rate.
Efforts at reducing leachate
achieved only a 5 percent reduction, with a simultaneous
198
decrease in erosion at $50/acre abatement expenditure.
These results lead one to conclude that Athena soils may be
subject to both erosion and leaching problems.
None of the
optimal production strategies identified for this soil were
able to significantly reduce leachate levels.
The mixed objective strategies demonstrated that it is
possible to achieve a simultaneous reduction in both soil
erosion and leaching.
The results from the mixed strategies
revealed further that, once either pollutant has been
substantially reduced, further reductions certainly
increased the rate of generation of the other by an amount
that varied by soil type and abatement expenditure level.
This information is very useful for assessing policy
efficiency and the implications of a need for a substantial
reduction in these pollutants.
Tables (7.2a) and (7.2b)
summarize the rates of pollutant substitution associated
with each soil series and abatement levels.
For example, on
Walla Walla soil, a reduction in soil loss from 4.10 to 3.56
tons/acre (a decrease of 0.54 ton/acre) given $10/acre
abatement expenditure, was accompanied by an increase in
leaching of 0.89 lb/acre (an increase from 4.65 to 5.54
lbs/acre); that is, a marginal rate of pollutant
substitution of 1.65 lbs/acre per ton of soil loss reduction
(2.05, 0.59, 0.27 lbs/acre for Pilot Rock, Ritzville and
Athena soils).
199
Table (7.2a):
Trade-off s between Pollutants--Leachate.
At Low Rate of Leaching2
Soils
Costi
NO3-N
Leached
Soil loss
(Lb/Ac)
(Tons/Acre)
Walla Walla
$10
$30
$50
1 decrease
1 decrease
1 decrease
3.24 increase
19.76 increase
19.26 increase
Pilot Rock
$10
$30
$50
1 decrease
1 decrease
1 decrease
3.66 increase
2.34 increase
Large increase3
Ritzville
$10
$20
$30
1 decrease
1 decrease
1 decrease
6.80 increase
12.46 increase
17.71 increase
Athena
$10
$30
$50
1 decrease
1 decrease
1 decrease
6.58 increase
Large increase
Large increase
1 Abatement Expenditures ($/Ac).
2 A move from p2 to p1 in Figures (6.20-6.23).
3 Large marginal rate of pollution substitution implies the
trade-off curve is either almost vertical or horizontal.
For the same abatement expenditure level, a reduction in
leaching from 4.31 to 3.64 lbs/acre (a decrease of 0.67
lb/acre) resulted in an increase in soil loss by 2.17
tons/acre (an increase from 5.01 to 7.18 tons/acre).
That
is, a marginal rate of substitution of 3.24 tons/acre per
pound of leachate (3.66, 6.80 and 6.58 tons/acre for Pilot
Rock, Ritzville and Athena soils).
200
Table (7.2b):
Trade-of fs between Pollutants--Soil Loss.
At Low Rate of Soil loss4
Soils
Costi
Soil loss
NO3-N
Leached
(Tn/Acre)
(Lbs/Acre)
$50
1 decrease
1 decrease
1 decrease
1.65 increase
1.73 increase
1.52 increase
Pilot Rock
$10
$30
$50
1 decrease
1 decrease
1 decrease
2.05 increase
3.05 increase
15.20 increase
Ritzville
$10
$20
$30
1 decrease
1 decrease
1 decrease
0.59 increase
0.52 increase
2.03 increase
Athena
$10
$30
$50
1 decrease
1 decrease
1 decrease
0.27 increase
0.26 increase
0.85 increase
$10
Walla Walla $30
1 Abatement Expenditures (S/Ac).
4 A move from p3 to p4 in Figures (6.20-6.23).
General Comments
The results in this study showed several alternative
production systems for controlling soil erosion and (or)
nitrate leachate.
To reduce soil loss rates, preferred
production systems included tillage systems that disturb the
soil less, retain more residue on the soil surface or a
combination with mechanical soil conservation practices.
Split application fertilization techniques, different
application rates and changes in crop mix were suggested to
reduce nitrate leaching.
201
While the benefits from reducing soil loss and leaching
are obvious, the critical question is whether the
environmental benefits can justify the economic costs
incurred in implementing the production strategies that
achieved these benefits.
This and other considerations may
have a major impact on a producers' inclination to adopt a
different or "new" production system.
Adoption of Soil Conservation Strategies
The enterprise budgets showed that the most intensive
and erosive farming practices generally produced the largest
net returns.
The rate of adoption of a new tillage system
and (or) soil conserving practice by a farmer currently
employing conventional or other erosive farming practices,
would hence depend on his perceived potential impact on farm
net return (both currently and in the future years), and the
inherent risks that may be involved.
Other factors such as
the financial situation of farm owner or operator, farm
size, land quality and tenure status become important
whenever faced with implementation decision.
For instance,
a farmer in a strong financial position may be able to
absorb the additional costs of any new technology involved.
The size of farm a farmer operates is critical because
the fixed cost involved in machinery and other inputs
required in switching from current tillage system and
202
practice to another may be lower for large farms than for
small farms.
Hence, an operator of a small-sized farm may
be hesitant to adopt expensive soil conservation strategy.
Land quality is another issue of importance.
Tillage
systems and (or) soil conservation techniques that minimize
soil losses are more likely to be readily adopted by a
producer on land that is more vulnerable to excessive
erosion, particularly if such losses mean greatly reduced
farm income in the near future.
AdoTtion of Leaching Control Techniques
Under dryland conditions, techniques for minimizing
leaching focused mainly on timing and rate of application,
as well as changes in crop mix.
Split fertilizer applications better ensure that
fertilizer is made available at roughly the same time it is
needed, thus reducing leaching considerably.
The timing and
level of application a producer employs is influenced by
experience, expectation of precipitation patterns and
ability to absorb any extra cost involved in multiple
applications.
Changes in crop mix mean production of both wheat and
barley or switching entirely to either crop.
Producers
usually view such changes with suspicion because of the
risks and uncertainties involved by way of yield and (or)
203
economic returns.
In particular, farmers may be more
hesitant to include the less profitable spring barley in
their crop rotation.
Benefits of this Research
The research results should help farmers to identify
tillage systems and management practices that are less
harmful to the environment by reducing erosion and (or)
Efficient management strategies that meet
leaching.
environmental goals at minimal cost can also be easily
identified.
The abatement expenditures provided a producer
information about the potential cost for implementing
alternative strategies that accomplish certain reductions in
either or both pollutants, should he be required to do so.
Government support in form of subsidy payments or sharing of
expenditures on soil and water conservation practices may
help raise the "speed" of adoption of farming practices that
minimize environmental damage.
In essence, knowledge of the
abatement expenditures may serve a useful purpose in
formulating economic incentives that encourage
implementation of plans that reduce soil loss and (or)
nitrate leaching.
The research results revealed that Walla Walla and
Athena soils have highest soil loss rates--above their Tvalues.
Average cost of abating soil loss on Athena soil is
204
greater than on Walla Walla.
Athena soil leached the most
nitrate, followed by Pilot Rock soil.
Leaching on Walla
Walla soil is slightly lower than on Pilot Rock.
Relatively, average abatement cost on Athena soil is
highest.
It is about 3 to 7 times that of Walla Walla soil,
and 13 times that of Pilot Rock soil.
Contrary to what was
expected, leaching on Pilot Rock is the least expensive to
abate.
On both Walla Walla and Athena soils, reducing
erosion is less expensive than reducing leaching.. This
information is beneficial for policy makers attempting to
solve agricultural environmental problems without any
adverse impact on the agricultural industry.
Once a soil is
identified as prone to soil loss and (or) leaching,
pollution control policies or regulations can easily be made
more site specific.
The objective of solely reducing one pollutant may
result in strategies that cause a significant increase in
production of the other.
MOP helped illuminate these
problems and identified strategies that offered trade-of fs
between soil loss and leachate, and the approximate
abatement costs.
Limitations of Research
While the conclusions in this study are not final, it
is hoped that the strengths and limitations point to areas
of further studies or improvement in future research.
205
The data requirements for this study were quite
extensive.
Information on land resource, tillage systems
and sequence of operations, soil conservation practices,
soil loss rates determination, parameters and data for
budgeting required time, effort and multi-disciplinary best
judgement.
The reliability of the results and conclusions
depend on the accuracy of these data.
In the NLEAP model, only a single nitrate-nitrogen soil
test per soil per crop rotation was available.
Additional
soil test data may have resulted in different beginning soil
nitrate levels and hence, different leachate estimates.
There were no available data for the value of off-site
cost of erosion, inter-generational impact of erosion,
average or estimated cost of nitrogen leaching damage (in
$/lb).
If these information were available, incorporating
them with the analysis could potentially influence the net
returns and, hence, choice of optimal production strategies.
Risk attitude of producers, both economic and
environmental, pertinent to decision making process were not
addressed in this research.
For example, a farmer's
perception of risk and uncertainty influences his
willingness and readiness to switch from a current
management practice to alternatives that minimize soil loss
and (or) nitrate leaching rates.
Stochastic weather events,
input availability and use over time, price and yield risks,
206
may influence decisions within the season.
Risk issues
could be addressed using stochastic programming or other
techniques.
Suggested optimal strategies were not effective in
bringing a significant reduction in nitrate leaching on
Athena soil.
In retrospect, this indicated that other best
management practices for reducing nitrate leaching should be
investigated, including use of slow-release organic and
inorganic fertilizers, nitrification inhibitor, including
nitrogen fixing legumes or deep rooted crops in the
rotation, and adding cover crop in the rotation to absorb
residual nitrogen.
The market impact of changes in the production levels
for a crop was not treated in this thesis.
A more macro-
oriented analysis of the strategies used to reduce leaching
and (or) erosion will aid policy makers as they consider the
implication of pollution-reducing policies.
207
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APPENDICES
223
APPENDIX A
TEMPERATURE AND PAN EVAPORATION DATA--
PRECIPITATION
Table (A.la): Monthly Precipitation, Pendleton Weather
Station (inches).
CROP 82YR
83
8384
8485
8586
8687
0.68 0.80 0.98 0.19
0.82 0.98 1.54 1.87
OCT
0.91 1.18 1.34 1.02
NOV
2.79 3.43 2.66 3.41
DEC
3.17 1.96 1.27 0.95
JAN
0.99 0.69 2.38 2.08
FEB
2.56 1.49 0.94 1.31
MAR
3.23 1.33 1.94 1.85
APR
2.37 0.65 0.83 0.83
MAY
2.11 0.89 1.79 1.63
JUN
2.05 1.42 0.09 0.62
JUL
0.05 0.05 0.61 0.47
TOT 23.74 21.73 14.87 16.4 16.23
AUG
SEP
0.50
1.68
2.68
1.46
2.69
1.63
2.97
3.90
1.23
2.08
1.92
1.00
AVG 16.66
8788
88-
89
8990
9091
9192
0.06 0.00 1.19 0.76 0.24
0.04 0.40 0.24 0.00 0.03
0.00 0.08 1.00 1.37 0.89
1.44 3.65 1.65 1.73 4.18
1.61 0.93 0.49 1.18 0.97
2.58 2.86 1.43 1.15 0.96
0.32 1.55 0.28 0.86 1.34
1.65 2.95 1.89 1.71 0.85
2.59 1.94 1.76 1.01 1.29
1.79 2.19 2.14 4.73 0.20
0.94 0.33 0.70 2.22 0.90
0.00 0.15 0.37 0.15 1.74
13.0 17.0 13.14 16.9 13.59
Table (A.lb): Monthly Average Teiip (°F), Pendleton Weather
Station.
CROP
YR
8283
8384
84- 8585
86
8687
87-
88-
88
89
8990
9091
9192
AUG 69.92 71.21 70.3 66.13 72.84 67.02 67.4 67.4 70.50 72.30
SEP 59.50 57.22 58.9 54.70 57.22 62.93 60.5 60.5 65.30 62.00
OCT 48.97 49.74 47.7 48.44 51.34 50.48 56.1 49.8 49.20 50.00
NOV 36.45 45.27 41.5 25.97 41.85 41.87 43.5 43.7 44.90 40.80
DEC 35.35 21.92 29.3 19.02 31.90 32.90 33.9 32.8 24.90 36.30
JAN 40.10 33.34 25.4 35.39 29.18 32.06 36.5 38.0 31.10 38.60
FEB 43.16 39.12 31.8 38.45 39.18 38.14 24.1 37.9 44.50 42.50
MAR 46.97 45.40 42.1 48.10 45.29 43.06 42.6 44.0 41.70 45.90
APR 48.03 47.45 52.2 47.92 53.32 51.43 51.7 52.3 49.00 52.10
MAY 57.16 53.50 57.2 56.19 58.97 55.60 55.3 55.0 53.60 58.80
JUN 61.38 59.60 63.5 67.65 64.85 62.52 64.7 63.5 59.40 68.20
JUL 66.94 70.37 74.5 65.97 68.74 70.21 68.7 72.8 69.50 69.60
224
Table (A.lc):
CROP
YR
Monthly Pan Evaporation, Pendleton Weather
Station (in hundredth of an inch).
82-
83-
84-
85-
86-
83
84
85
86
87
AUG 10.24 10.02 10.66
SEP 5.63 6.55 6.30
OCT 3.36 3.34 3.64
NOV 1.30 1.00 1.40
DEC 1.10 0.90 1.18
JAN 1.50 1.35 1.18
FEB 1.50 1.35 1.20
MAR 3.41 3.15 3.33
APR 4.87 4.82 6.15
MAY 7.24 6.76 7.62
JUN 8.67 7.17 10.09
JUL 10.2 11.62 13.62
8788
8889
8990
9091
9192
9.66 11.80 11.66 11.24 9.54 10.99 11.9
4.90 5.56 8.24 8.04 7.19 8.03 8.1
3.37 3.23 4.29 4.87 4.08 4.47 5.7
1.20 1.89 1.80 1.87 1.80 1.90 1.9
0.80 1.20 1.40 1.56 1.15 0.90 1.1
1.30 1.10 1.20 1.20 1.20 1.25 1.4
1.30 1.22 1.28 1.02 1.20 1.91 1.9
2.86 2.93 3.11 2.89 3.41 4.50 2.9
4.85 5.29 4.09 4.83 5.64 5.82 4.4
6.88 6.50 6.76 6.51 6.80 7.15 8.9
9.96 9.25 7.29 9.28 9.64 8.78 10.2
10.5 11.16 12.25 11.98 12.8 12.09 10.3
225
Table (A.2a):
CROP 82YR
83
AUG
1.07
1.85
2.45
0.23
1.79
0.80
1.39
3.12
SEP
OCT
NOV
DEC
JAN
FEB
MAR
APR 1.5].
MAY 1.95
JUN 2.25
JUL 1.23
TOT 19.64
AVG 13.70
Monthly Precipitation, Pilot Rock Weather
Station (inches).
83-
84-
85-
86-
87-
88-
89-
84
85
86
87
88
89
90
0.42
0.57
0.90
2.13
3.05
0.55
1.44
2.71
1.52
1.54
2.04
0.06
16.93
Table (A. 2b):
0.89 0.57 0.08 0.33
0.69 1.58 1.11 0.01
1.11 1.07 0.73 0.02
1.82 1.63 2.51 1.34
1.01 0.74 0.52 0.64
0.72 1.50 1.90 1.81
1.33 2.43 0.60 0.43
1.13 1.38 1.48 1.30
0.37 0.58 0.27 2.76
0.44 1.66 1.79 1.46
1.10 0.17 0.70 1.28
0.00 0.80 0.46 0.05
10.6 14.11 12.15 11.43
0.01
0.41
0.12
2.46
0.78
1.63
1.24
1.94
1.39
2.06
0.60
0.34
13.0
9091
9192
1.74 0.52 0.31
0.28 0.02 0.00
0.33 0.61 0.75
1.83 1.00 3.16
0.37 1.26 0.47
1.17 0.84 0.49
0.43 0.02 0.86
1.77 2.12 1.24
1.49 1.31 1.29
1.94 4.29 0.23
1.76 2.38 0.85
0.38 0.32 0.86
13.5 14.69 10.51
Monthly Average Temp (°F), Pilot Rock Weather
Station.
CROP
YR
AUG
SEP
OCT
NOV
DEC
JAN
FEB
MAR
APR
MAY
JUN
JUL
82-
83-
84-
87-
88-
89-
85
87
88
89
90
9091
91-
84
8586
86-
83
70.6
59.0
48.0
41.9
31.3
26.8
33.5
43.2
53.1
58.4
64.6
75.5
66.50
54.98
50.37
27.72
19.90
37.82
39.25
48.44
48.23
56.21
68.43
65.53
72.77
57.27
52.27
42.27
32.53
31.58
39.02
46.69
53.50
58.97
66.90
67.87
69.7
61.9
57.3
43.7
35.0
38.5
25.7
43.3
52.0
56.2
65.6
68.5
67.9
62.1
52.0
45.1
33.8
39.3
37.8
44.7
54.4
55.9
63.3
73.5
71.60
66.60
50.70
45.70
25.70
32.40
46.10
42.50
49.60
54.40
60.00
70.30
73.20
64.80
52.40
42.20
36.80
39.50
43.00
47.00
52.10
60.10
68.40
69.90
69.79
59.45
49.23
36.98
36.44
41.40
44.04
47.10
48.47
57.63
61.00
66.16
70.60
58.25
50.32
45.42
24.66
35.85
39.97
45.69
47.25
53.18
60.20
70.24
68.50
64.57
52.89
42.82
34.39
33.02
39.88
44.02
51.48
56.16
62.68
70.02
92
226
Table (A.3a):
CROP 82YR
83
AUG
SEP
OCT
NOV
DEC
JAN
FEB
MAR
APR
MAY
JUN
JUL
TOT
AVG
83-
84-
85-
86-
87-
88-
89-
84
85
86
87
88
89
90
0.60
0.52
0.62
2.45
2.31
0.17
1.07
2.34
1.32
0.89
1.13
0.06
17.53 13.48
11.13
0.32
1.95
1.96
1.08
1.89
1.40
2.43
2.74
0.61
1.96
0.39
0.80
Table (A. 3b):
CROP
YR
AUG
SEP
OCT
NOV
DEC
JAN
FEB
MAR
APR
MAY
JUN
JUL
Monthly Precipitation from Moro Weather
Station (inches).
82-
83-
83
84
66.80
57.70
46.40
34.70
32.10
36.90
38.20
43.30
46.20
55.30
58.00
63.80
68.20
55.50
48.40
41.70
22.50
32.70
37.50
43.50
44.30
50.60
62.10
72.90
0.44 0.14 0.07 0.11
0.39 1.11 1.52 0.07
1.02 1.09 0.45 0.01
3.18 1.19 1.53 0.66
0.41 1.12 0.78 3.23
0.27 1.84 1.69 1.60
0.97 2.39 1.10 0.21
0.44 0.98 1.55 1.25
0.14 0.34 0.28 2.21
0.63 0.35 0.99 0.55
0.92 0.06 0.29 1.02
0.05 0.54 0.78 0.04
8.86 11.15 11.04 10.96
0.00 0.49
0.56 0.07
0.02 0.36
2.5]. 0.96
0.22
1.33
0.77
1.91
0.84
0.91
0.08
0.11
9.26
9091
91-
1.43
0.29
1.27
0.61
0.74
0.87
0.60
1.44
0.40
0.77
1.27
0.33
0.16
0.00
1.40
2.57
1.02
0.47
1.64
0.64
2.38
0.04
0.28
92
0.48
1.91
0.28
0.76
0.79
0.91
0.39
0.15
0.8].
7.55 10.02 11.41
Monthly Average Temp (°F) --Moro Weather
Station.
8485
8586
86-
87-
88-
89-
90-
91-
87
88
89
90
91
92
72.2
60.4
49.1
38.8
28.5
24.7
31.1
40.1
49.6
54.6
61.7
73.5
64.10
53.90
47.50
26.20
18.40
32.60
35.90
45.90
45.50
55.80
65.60
63.20
72.20
55.70
51.60
40.80
29.40
29.90
37.50
42.60
51.50
57.90
64.20
65.70
65.8
59.7
56.2
41.6
33.2
36.4
24.6
39.4
50.4
54.1
62.7
65.7
64.9
60.8
49.3
42.4
32.9
36.9
37.9
43.1
51.2
54.1
60.9
71.1
68.50
64.70
48.00
43.40
25.10
30.80
41.80
40.60
47.10
51.70
56.90
68.90
67.00
63.50
52.60
40.90
30.80
29.80
38.00
42.80
48.60
51.60
59.20
67.90
71.00
62.70
50.50
40.40
35.10
37.10
41.60
45.50
49.50
58.20
67.10
68.20
227
Table (A.3c):
CROP 82YR
83
8384
Monthly Pan Evaporation, Moro Weather Station
(in hundredth of an inch).
8485
85-
86-
87-
88-
86
87
88
89
8990
90-
91-
91
92
AUG 11.5 9.37 11.29 10.99 13.26 11.90 10.82 10.13 10.46 11.9
SEP 6.82 4.45 6.98 5.65 5.85 8.71 7.50 7.91 7.78 8.8
OCT 3.1]. 3.96 4.08
3.64
3.69 4.94 4.43
4.19 3.57 6.2
NOV 1.39 1.15 1.34 0.70 1.89 1.55 1.20 2.96 1.90 1.9
DEC 1.37 0.70 0.80 0.60 0.80 1.08 1.10 1.20 0.90 1.1
JAN 1.15 1.10 0.70 1.15 1.16 1.08 1.16 1.25 1.25 1.4
FEB 1.15 1.26 1.01 1.18 1.18 1.18 0.89 1.25 1.91 1.9
MAR 3.70 4.89 1.68 3.06 3.27 4.00 1.20 2.92 4.35 2.9
APR 6.88 6.57 7.29 5.21 6.41 4.48 5.10 5.83 5.82 4.3
MAY 9.37 8.30 11.52 8.16 8.09 6.32 7.56 6.88 7.15 8.9
JUN 8.74 8.68 12.84 11.38 11.06 7.96 10.39 8.60 8.03 10.7
JUL 10.3 8.77 15.14 10.86 11.19 11.95 11.95 12.95 12.81 10.3
228
Table (A.4a):
CROP 8283
YR
AUG
SEP
OCT
NOV
DEC
JAN
FEB
MAR
APR
MAY
JUN
JUL
0.42
1.58
2.47
2.56
2.66
2.82
3.05
3.49
0.85
1.55
2.16
1.74
Monthly Precipitation from Pullman Weather
Station (inches).
83-
84-
84
85
0.67
0.91
0.94
4.57
3.10
2.00
1.74
3.34
1.46
1.89
2.19
0.84
0.39
0.97
1.61
3.81
3.71
0.49
1.60
1.64
0.88
1.14
1.55
0.09
8586
86-
87-
88-
89-
87
88
89
90
1.21
2.14
1.45
2.28
0.54
3.35
3.64
1.58
1.09
1.62
0.21
0.90
0.90
2.45
0.60
3.29
0.75
1.90
1.40
1.79
1.03
2.23
1.57
1.59
0.18
0.00
0.00
1.22
2.98
2.15
0.89
2.56
2.00
1.76
1.43
0.99
0.04
0.91
0.75
4.30
1.42
3.27
1.37
3.45
0.77
1.93
0.86
0.13
3.81
0.48
1.40
2.10
1.46
4.40
1.46
0.90
2.81
2.55
1.22
0.78
9091
91-
0.83
0.03
2.54
3.66
1.91
2.01
0.84
2.61
1.35
3.28
1.94
0.24
0.43
0.03
0.78
3.57
1.17
2.07
2.33
0.45
2.50
0.39
0.80
1.11
92
TOT 25.5 23.65 17.88 20.01 19.50 16.16 19.20 23.37 21.2 15.6
AVG 20.20
Table (A. 4b):
CROP
YR
82
83
84
85
86
87
88
89
90
91
/
/
/
/
/
/
/
/
/
/
84
85
86
87
88
89
90
91
92
67.6
64.4
46.5
40.0
22.8
28.9
41.4
38.2
46.0
50.2
55.4
65.9
69.0
61.2
48.9
37.6
35.5
34.1
40.6
45.6
49.6
56.7
64.5
65.9
83
AUG
SEP
OCT
NOV
DEC
JAN
FEB
MAR
APR
MAY
JUN
JUL
Monthly Average Temp (°F) --Pullman Weather
Station.
65.90
58.10
46.40
32.50
30.00
36.60
39.10
43.00
44.30
54.00
57.80
62.30
68.40
54.50
49.00
39.90
21.90
31.70
35.40
41.10
44.00
50.20
57.60
66.20
67.30
55.80
44.80
37.90
25.80
21.30
26.20
37.30
48.50
55.10
59.50
70.20
63.90
52.60
45.90
24.20
19.00
34.50
34.00
44.80
45.30
53.60
63.60
61.60
70.0
54.1
50.1
35.5
29.8
27.9
37.2
41.3
51.8
56.6
62.2
65.2
64.60
61.60
50.90
40.10
28.60
28.10
37.30
39.50
47.90
52.90
59.10
65.00
65.90
58.30
55.60
38.50
29.70
30.00
23.40
38.00
48.80
52.30
60.60
65.30
63.30
60.10
48.00
40.80
32.40
33.90
32.00
41.30
49.80
51.60
58.90
68.10
229
Table (A.4c):
CROP 82YR
83
AUG
SEP
OCT
NOV
DEC
JAN
FEB
MAR
APR
MAY
JUN
JUL
9.24
5.73
2.50
1.00
1.00
1.00
1.00
3.13
3.94
6.98
7.17
7.29
8384
Monthly Pan Evaporation, Pullman Weather
Station (in hundredth of an inch).
8485
8.51 9.38
5.38 5.12
3.00 2.50
1.00 1.00
1.00 1.00
1.00 1.00
1.00 1.00
1.00 2.00
3.71 3.71
5.57 6.50
6.52
8.43
9.27 11.38
85-
8687
87-
88-
88
89
7.85 10.80
8.55
7.26
2.50
1.00
1.00
1.00
1.00
2.00
3.67
5.81
5.70
86
4.17
2.50
1.00
1.00
1.00
1.00
1.00
4.09
6.86
7.78
9.54
4.29
2.50
1.00
1.00
1.00
1.00
1.00
5.84
6.62
8.04
8.30
9.42
5.75
2.50
1.00
1.00
1.00
1.00
2.00
4.84
5.86
7.70
8.25 10.14
8990
90-
91-
91
92
7.99
5.48
2.50
1.00
1.00
1.00
1.00
2.00
4.20
5.22
6.25
8.86
8.21
6.80
2.50
1.00
1.00
1.00
1.00
2.00
4.00
4.77
5.66
8.08
9.25
6.46
2.50
1.00
1.00
1.00
1.00
2.00
3.50
7.44
7.53
6.52
230
APPENDIX B
UNIVERSAL SOIL LOSS EQUATION FACTORS
Table (B.l):
K-Factor for Pilot Rock, Ritzville and WallaWalla Soils of Umatilla County.
Soil Type
ATHENA SILT LOAMa/
PILOT ROCK SILT LOAMa/
PILOT ROCK SILT LOAN NORTH
PILOT ROCK SILT LOAN SOUTH
PILOT ROCK SILT LOAN SHALLOW
RITZVILLE SILT LOANa/
RITZVILLE SILT LOAN NORTH
RITZVILLE SILT LOAN SOUTH
RITZVILLE VERY FINE SANDY LOAN
WALLA WALLA SILT LOAMa/
WALLA WALLA SILT LOAN COARSE SOLUN
WALLA WALLA SILT LOAN COARSE SOLUM DEEP
WALLA WALLA SILT LOAN COARSE SOLUM DEEP SOUTH
WALLA WALLA SILT LOAN COARSE SOLUM DEEP NORTH
WALLA WALLA SILT LOAN COARSE SOLUM SOUTH
WALLA WALLA SILT LOAN COARSE SOLUM VERY DEEP SOUTH
WALLA WALLA SILT LOAN COARSE SOLUM VERY DEEP NORTH
WALLA WALLA SILT LOAN DEEP
WALLA WALLA SILT LOAN DEEP SOUTH
WALLA WALLA SILT LOAN DEEP NORTH
WALLA WALLA SILT LOAM DEEP TO PAN
WALLA WALLA SILT LOAN HIGH RAINFALL
WALLA WALLA SILT LOAN HIGH RAINFALL NORTH
WALLA WALLA SILT LOAN HIGH RAINFALL SOUTH
WALLA WALLA SILT LOAN LOW RAINFALL DEEP
WALLA WALLA SILT LOAN LOW RAINFALL DEEP NORTH
WALLA WALLA SILT LOAN LOW RAINFALL DEEP SOUTH
WALLA WALLA SILT LOAN LOW RAINFALL VERY DEEP
WALLA WALLA SILT LOAN LOW RAINFALL VERY DEEP NORTH
WALLA WALLA SILT LOAN NORTH
WALLA WALLA SILT LOAN SOUTH
WALLA WALLA SILT LOAN VERY DEEP
WALLA WALLA SILT LOAM VERY DEEP NORTH
WALLA WALLA SILT LOAM VERY DEEP SOUTH
WALLA WALLA SPOFFORD COMPLEX
WALLA WALLA SILT LOAM COARSE SOLUN VERY DEEP
K Factor
0.37
0.43
0.43
0.43
0.43
0.43
0.43
0.43
0.49
0.43
0.43
0.43
0.43
0.43
0.43
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.49
0.43
0.49
/ K = 0.43, 0.43, 0.43 and 0.37 were assumed for Pilot
Rock, Ritzville, Walla Walla and Athena soils, respectively.
Source: 1. Akbari 2. Soil Survey of Umatilla County.
231
Table (B.2):
LS Values for Areas affected by Frozen Soil
Including Umatilla County, Oregon.
Slope Length, in Feet
Percent Slope
0.5
12.
14.
16.
18.
20.
22.
25
50
75
100
125
150
0.08
0.13
0.21
0.22
0.33
0.39
0.44
0.49
0.54
0.59
0.63
0.71
0.79
0.87
0.94
1.01
1.07
0.11
0.18
0.29
0.39
0.47
0.55
0.63
0.70
0.76
0.83
0.89
1.01
1.12
1.23
1.33
1.42
1.51
0.13
0.22
0.36
0.47
0.50
0.67
0.77
0.85
0.93
1.01
1.09
1.24
1.39
1.50
1.62
1.74
1.85
0.16
0.25
0.41
0.55
0.67
0.78
0.88
0.90
1.08
1.17
1.26
1.43
1.58
1.73
1.88
2.01
2.14
0.17
0.28
0.46
0.61
0.75
0.87
0.99
1.10
1.21
1.31
1.41
1.60
1.77
1.94
2.10
2.25
2.39
0.19
0.31
0.50
0.67
0.82
0.95
1.00
1.21
1.32
1.43
1.54
1.75
1.94
2.12
2.30
2.46
2.62
232
Table (B.2) (Continued):
LS Values for Areas affected by
Frozen Soil Including Umatilla County, Oregon.
Slope Length, in Feet
Percent Slope 200
0.5
12.
14.
16.
18.
20.
22.
0.22
0.36
0.58
0.77
0.94
1.10
1.25
1.39
1.53
1.66
1.78
2.02
2.24
2.45
2.65
2.84
3.02
250
300
350
400
450
0.25
0.40
0.65
0.86
1.05
1.23
1.40
1.56
1.71
1.58
1.99
2.26
2.51
2.74
2.97
3.18
3.38
0.20
0.44
0.71
0.94
1.15
1.35
1.53
1.70
1.87
2.03
2.18
2.47
2.75
3.00
3.25
3.48
3.70
0.29
0.47
0.79
1.02
1.25
1.46
1.65
1.84
2.02
2.19
2.36
2.67
2.97
3.24
3.51
3.76
4.00
0.31
0.51
0.82
1.09
1.33
1.56
1.77
1.97
2.16
2.34
2.52
2.85
3.17
3.47
3.75
4.02
4.20
0.33
0.54
0.87
1.16
1.41
1.65
1.88
2.09
2.29
2.48
2.67
3.03
3.36
3.68
3.98
4.26
4.58
500
0.15
0.57
0.92
1.22
1.49
1.74
1.98
2.20
2.41
2.62
2.82
3.19
3.04
3.08
4.19
4.56
4.78
233
Table (B.2)
(Continued): LS Values for Areas affected by
Frozen Soil Including TJmatilla County, Oregon.
Slope Length, in Feet
Percent Slope
0.5
12.
14.
16.
18.
20.
22.
Source:
550
0.36
0.59
0.96
1.28
1.56
1.83
2.07
2.31
2.53
2.75
2.95
3.35
3.72
4.07
4.40
4.71
5.02
600
700
800
1000
1200
0.38
0.62
1.01
1.34
1.63
1.91
2.17
2.41
2.64
2.87
3.09
3.50
3.88
4.25
4.59
4.92
5.24
0.41
0.67
1.09
1.44
1.76
2.06
2.34
2.60
2.86
3.10
3.33
3.78
4.19
4.59
4.96
5.32
5.66
0.44
0.71
1.16
1.54
1.89
2.20
2.50
2.78
3.05
3.31
3.56
4.04
4.48
4.90
5.31
5.69
6.05
0.49
0.80
1.30
1.72
2.11
2.46
2.80
3.11
0.54
0.88
1.42
1.89
2.31
2.70
3.06
3.41
3.74
4.06
4.36
4.96
5.49
6.01
6.50
6.96
(1) Akbari, 1986.
LS =
(
m
22.13
3.4].
3.70
3.90
4.51
5.01
5.48
5.93
6.36
6.76
7.4].
(2) McCool and 1983.
Sin 0
sin 5.143°
)fl
Where LS = slope length-steepness factor relative to a
22.13m slope length on a uniform 9 percent
(5.143°) slope
A = horizontal slope length, in meters;
o = slope steepness, degrees;
m,n = exponential constant;
The LS value for the study area are obtained for 3.5 and 9.5
percent slopes and 100-, 300-, and 600-foot slope length.
234
The C Factor
The general C-factors developed for the Columbia
Plateau Summer fallow-Winter wheat (SF-WW), Summer fallowSpring Barley (SF-SB) and Winter wheat-Green pea (WW-GP)
rotations were derived from materials published by
Wischmeier, 1973, 1975; and Wischiueier and Smith, 1978,
These apply to normal condition, but not site specific
(McCool and George, 1983).
To be site specific, McCool and
George, utilized information based on the soil condition,
such as structure, clod, pressure pan and plow pan, to
modify the C-factors.
The modified C factors considered
tillage systems and their effects on surface and shallow
buried residue, residue decomposition with time, and change
in mulch or canopy cover.
The value of the modified C-
f actors can be obtained by first determining the general C-
factor from the graph and multiplying by the appropriate
site values shown in Table (B.3).
For example, suppose the
general C-factor for a conventional tillage system on a
Columbia plateau summer fallow-winter wheat, with primary
tillage done in fall and 50 percent canopy developed by
December 1 is 0.23, then the C-factor will be approximately
0.28 (0.23 * 1.20).
235
Table (B.3):
Estimated Modifying Factors for "C" in the
tJSLE for Oregon.
Well Defined
Tillage Pan and/
or Compaction,
No tillage
Fans and/or
Compaction
Weak tillage
Pans and/or
Coinpaction'
below 5" above 5"
Soils with
rough tillage,
> 15% clods
0.80
0.90
1.10
1.20
Soils with
rough tillage
5 - 15% clods
0.85
0.95
1.15
1.25
Soils with
fine surface
puddled or
crusted), < 5%
clods, massive
soil structure
0.90
1.00
1.20k'
1.30
Soils with
Platy structure
or surf. compaction
1.20
1.30
1.40
Soils with
1.10
resid. burned,
well, defined
surface structure
1.20
1.30
1.40
Soils with
1.20
resid. burned,
weak or no soil
surf. structure
1.30
1.40
1.50
Soils with
0.85
surface puddled
or crusted, very
weak with no soil
structure; pans
recently broken
by subsoiling or
chiseling
1.00
Soil site
Condition
a/ Weak tillage pans and/or compaction layers slow water
penetration or development.
/ Value of 1.20 was suggested by SCS, Pendleton.
236
Table (B.3) Continued:
Estimated Modifying Factors for "C"
in the USLE for Oregon.
Well Defined
Tillage Pan and!
or Compaction,
No tillage
Fans and/or
Compaction
Weak tillage
Pans and/or
Compaction'
below 5" above 5"
Soil with
conservation
tillage, weak
surface soil
structure
0.75
0.85
1.05
1.15
Soil with
conservation
tillage, or
green manure
incorporated,
moderate soil
structure
0.70
0.80
1.00
1.10
Soil with high 0.60
residue, conserv.
tillage, and no
till, (>2000
lbs/ac) green
manure incorp.,
well developed
soil structure
0.75
0.95
1.05
Soil with high 0.50
% organic on
surface, normal
intake rate,
very friable,
well devel. soil
surf. structure
0.70
0.90
1.00
Soil site
Condition
/ Weak tillage pans and/or compaction layers slow water
penetration or development.
Source: Akbari, (1986).
237
Table (B.4):
P (supporting conservation practice) factors.
P-Factors
Cross
Slope
Slope %
1.0
2.1
9.1
13.1
17.1
21.1
-
2.0
9.0
13.0
17.0
21 0
26.0
0.80
0.75
0.80
0.85
0.90
0.95
Non-Cross
Slope
Divided
Slopes
Strip
Cropping
Contour
Strips
1.00
1.00
1.00
1.00
1.00
1.00
0.52
0.44
0.52
0.61
0.70
0.79
0.45
0.38
0.45
0.38
0.32
0.38
0.44
0.50
0.56
Source: McCool and George (1983).
0. 52
0.60
0.68
238
APPENDIX C
SOIL LOSS (TONS/ACRE), COST OF EROSION DAMAGE. OPTIMAL
LEVEL OF CROP PRODUCTION AND STRATEGIES
Table (C.la):
YEAR
8283
8384
TILLAGE
SYSTEMS
1
2
3
4
5
Estimated Soil Loss (Tons/ac/yr) Using USLE,
(SF-WW) and (SF-SB) Standard Practice-Walla Walla Soil.
84-
85-
85
86
8687
87-
88-
88
89
8990
9091
9192
10-Yr
(SF-WW) Rotation--3.5% Slope
12.8 12.2
5.1 4.9
8.1 7.7
15.4 14.6
9.0 8.5
7.6
3.1
4.8
8.9
3.6
5.7
8.8
3.5
5.6
9.2 10.7 10.6
5.4
6.2
6.2
5.8
2.3
3.7
9.4
3.8
6.0
7.0 11.3
4.1 6.6
Avg
6.0 9.3
3.7
2.4
3.8
5.9
7.2 11.2
4.2
6.5
6.4
2.6
4.1
7.7 10.5
4.5
(SF-WW) Rotation--9.5% Slope
1
2
3
4
5
2
3
4
5
25.7 24.3 15.3 17.8 17.6 11.7 18.7 11.9 18.6 12.8 17.5
10.3
9.7
16.3 15.4
6.1 7.1 7.0
9.7 11.3 11.2
7.5 4.8 7.5 5.1 7.0
7.4 11.9 7.6 11.8 8.1 11.1
30.8 29.2 18.3 21.4 21.1 14.0 22.6 14.3 22.3 15.4 21.0
18.0 17.0 10.7 12.5 12.3 8.2 13.2 8.4 13.0 9.0 12.2
4.7
30.0
15.8
19.7
31.7
21.4
28.4
15.0
18.6
30.0
20.3
17.8
9.4
11.7
18.8
12.7
20.8
11.0
13.7
22.0
14.9
Avg
20.5 13.6 22.0 13.9 21.7 15.0 20.4
10.9 7.2 11.6 7.4 11.5 7.9 10.8
13.5 9.0 14.5 9.1 14.3 9.8 13.4
21.7 14.4 23.3 14.7 23.0 15.8 21.5
14.7 9.7 15.7 9.9 15.5 10.7 14.6
(SF-SB) Rotation--9.5% Slope
1
2
3
4
5
6.1
Avg
(SF-SB) Rotation--3.5% Slope
1
8.7
3.5
5.5
59.9
31.7
39.4
63.3
42.8
56.7
30.0
37.3
60.0
40.5
35.7
18.8
23.4
37.7
25.5
41.6
22.0
27.4
44.0
29.7
41.1
21.7
27.0
43.4
29.4
27.3
14.4
17.9
28.8
19.5
44.0
23.3
28.9
46.5
31.4
27.8
14.7
18.3
29.4
19.9
Avg
43.4
23.0
28.5
45.9
31.0
30.0
15.8
19.7
31.7
21.4
40.7
21.5
26.8
43.1
29.1
Tillage System (1,2,3,4,and 5) Correspond to MB, CH, DI, DIB
and DICH. See Tables (5.2)-(5.4).
239
Table (C.lb):
YEAR
8283
Estimated Cost of Soil Erosion ($/ac/yr),
(SF-WW) and (SF-SB)--Standard Practice-Walla Walla Soil.
83-
8485
84
TILLAGE
SYSTEMS
1
2
3
4
5
4.41
1.61
2.70
5.35
3.01
8586
8687
8788
8889
8990
90-
91-
9].
92
10-Yr
(SF-wW) Rotation--3.5% Slope
4.16
1.51
2.54
5.05
2.84
2.52
0.85
1.50
3.07
1.69
2.98
1.04
1.79
3.63
2.01
2.94
1.02
1.77
3.58
1.98
1.86
0.59
1.09
2.29
1.23
3.17
1.11
1.91
3.86
2.14
1.91
0.61
1.12
2.34
1.26
Avg
3.13
1.10
1.88
3.80
2.11
2.08
0.68
1.22
2.54
1.38
(SF-WW) Rotation--95% Slope
1
2
3
4
5
9.12
3.48
5.66
8.62
3.28
5.35
11.01 10.41
6.29 5.94
5.30
1.96
3.26
6.42
3.63
6.24
2.34
3.85
7.55
4.28
6.16
2.30
3.80
7.45
4.23
3.99
1.44
2.43
4.84
2.71
6.62
2.48
4.09
8.00
4.55
4.08
1.48
2.49
4.95
2.78
Avg
6.53
2.45
4.03
7.89
4.48
4.41
1.61
2.70
5.35
3.01
(SF-SB) Rotation--3.5% Slope
1
2
3
4
5
6.42
3.42
4.23
6.78
4.59
6.08
3.24
4.01
6.43
4.35
3.84
2.06
2.55
4.05
2.76
4.47
2.40
2.96
4.72
3.21
4.41
2.37
2.92
4.66
3.17
2.95
1.60
1.97
3.11
2.13
4.72
2.53
3.13
4.99
3.39
3.01
1.63
2.01
3.18
2.17
2
3
4
5
12.89 12.20
6.78 6.43
8.44
7.99
13.64 12.91
9.17 8.69
7.64
4.05
5.03
8.08
5.46
8.92
4.72
5.86
9.44
6.37
8.81
4.66
5.79
9.32
6.29
5.84
3.11
3.85
6.17
4.18
9.44
4.99
6.20
9.98
6.73
5.97
3.18
3.94
6.30
4.27
6.11
2.28
3.77
7.39
4.19
Avg
4.66
2.50
3.09
4.93
3.35
3.24
1.75
2.15
3.42
2.33
(SF-SB) Rotation--9.5% Slope
1
2.92
1.01
1.75
3.55
1.96
4.38
2.35
2.90
4.63
3.15
Avg
9.32
4.93
6.12
9.85
6.65
6.42
3.42
4.23
6.79
4.60
8.74
4.63
5.74
9.25
6.24
Tillage System (1,2,3,4,and 5) Correspond to MB, CH, DI, DIB
and DICH. See Tables (5.2)-(5.4).
240
Table (C.2a):
YEAR
82-
83-
84-
85-
86-
87-
88-
89-
83
84
85
86
87
88
89
90
TILLAGE
SYSTEMS
1
2
3
4
5
Estimated Soil Loss (Tons/ac/yr) Using USLE,
(SF-WW) and (SF-SB), Divided slope Practice-Walla Walla Soil.
9091
9192
10-Yr
Avg
(SF-WW) Rotation--3.5% Slope
4.0
1.6
2.5
4.8
2.8
3.8
1.5
2.4
4.5
2.6
2.4
0.9
1.5
2.8
1.7
2.8
1.1
1.8
3.3
1.9
2.7
1.1
1.7
3.3
1.9
1.8
0.7
1.1
2.2
1.3
2.9
1.2
1.9
3.5
2.0
1.8
0.7
1.2
2.2
1.3
2.9
1.2
1.8
3.5
2.0
2.0
0.8
1.3
2.4
1.4
Avg
(SF-WW) Rotation--9.5% Slope
1
2
3
4
5
9.5 9.0
3.8
3.6
6.0
5.7
11.3 10.7
6.6 6.3
5.6
2.3
3.6
6.8
3.9
6.6
2.6
4.2
7.9
4.6
6.5
2.6
4.1
7.8
4.5
4.3
1.7
2.7
5.2
3.0
6.9
2.8
4.4
8.3
4.9
4.4
1.8
2.8
5.3
3.1
6.9
2.7
4.3
8.2
4.8
4.7
1.9
3.0
5.7
3.3
2
3
4
5
9.3
4.9
6.1
9.8
6.6
8.8
4.6
5.8
9.3
6.3
5.5
2.9
3.6
5.8
3.9
6.5
3.4
4.2
6.8
4.6
6.4
3.4
4.2
6.7
4.6
4.2
2.2
2.8
4.5
3.0
6.8
3.6
4.5
7.2
4.9
4.3
2.3
2.8
4.6
3.1
(SF-SB) Rotation--9.5% Slope
1
2
3
4
5
22.1
11.7
14.5
23.3
15.8
6.4
2.6
4.1
7.7
4.5
Avg
(SF-SB) Rotation--3.5% Slope
1
2.7
1.1
1.7
3.2
1.9
6.7
3.6
4.4
7.1
4.8
4.6
2.5
3.1
4.9
3.3
6.3
3.3
4.2
6.7
4.5
Avg
20.9 13.1 15.3 15.1 10.0 16.2 10.2 16.0 11.0 15.0
11.0 6.9 8.1 8.0 5.3 8.6 5.4 8.5 5.8 7.9
13.7 8.6 10.1 9.9 6.6 10.6 6.7 10.5 7.2 9.9
22.1 13.9 16.2 16.0 10.6 17.1 10.8 16.9 11.7 15.9
14.9 9.4 10.9 10.8 7.2 11.6 7.3 11.4 7.9 10.7
Tillage System (1,2,3,4,and 5) Correspond to MB, CII, DI, DIB
and DICH. See Tables (5.2)-(5.4).
241
Table (C.2b):
YEAR
Estimated Cost of Soil Erosion ($/ac/yr) on
(SF-WW) and (SF-SB)--Divided Slope Practice-Walla Walla Soil.
82-
83-
84-
83
84
85
TILLAGE
SYSTEMS
1
2
3
4
5
1.19
0.32
0.66
1.48
0.76
8586
8687
8788
8889
8990
90-
91-
91
92
10-Yr
Avg
(SF-WW) Rotation--3.5% Slope
1.11
0.29
0.61
1.39
0.70
0.61
0.09
0.29
0.78
0.35
0.75
0.15
0.38
0.95
0.45
0.74
0.14
0.37
0.93
0.44
0.40
0.01
0.16
0.53
0.21
0.81
0.17
0.42
1.02
0.49
0.42
0.02
0.17
0.55
0.22
0.79
0.17
0.41
1.00
0.48
0.47
0.04
0.20
0.61
0.25
Avg
(SF-WW) Rotation--9.5% Slope
1
2
3
4
5
3.18
1.12
1.92
3.87
2.15
3.00
1.04
1.80
3.65
2.02
1.79
0.56
1.04
2.20
1.17
2.13
0.70
1.25
2.61
1.41
2.10
0.69
1.24
2.57
1.39
1.31
0.37
0.73
1.62
0.84
2.27
0.75
1.34
2.77
1.51
1.34
0.38
0.76
1.66
0.86
2.23
0.74
1.32
2.73
1.49
1.46
0.43
0.83
1.80
0.95
2.04
1.12
1.37
2.15
1.48
1.93
1.06
1.30
2.04
1.40
1.25
0.70
0.85
1.31
0.91
1.44
0.80
0.98
1.52
1.05
1.42
0.79
0.96
1.50
1.04
0.97
0.56
0.67
1.02
0.72
1.52
0.84
1.03
1.60
1.11
0.99
0.57
0.68
1.04
0.73
1.50
0.83
1.01
1.58
1.10
1.06
0.60
0.73
1.12
0.78
4
5
4.73
2.53
3.13
5.00
3.40
4.49
2.40
2.97
4.74
3.22
2.84
1.54
1.90
3.00
2.05
3.31
1.79
2.20
3.49
2.38
3.27
1.76
2.17
3.45
2.36
2.19
1.20
1.47
2.31
1.59
3.49
1.88
2.32
3.69
2.52
2.24
1.22
1.50
2.36
1.62
1.41
0.79
0.96
1.49
1.03
Avg
(SF-SB) Rotation--9.5% Slope
1
2
3
2.08
0.68
1.22
2.55
1.38
Avg
(SF-SB) Rotation--3.5% Slope
1
2
3
4
5
0.73
0.14
0.37
0.92
0.43
3.45
1.86
2.29
3.64
2.49
2.40
1.31
1.61
2.54
1.74
3.24
1.75
2.16
3.42
2.34
Tillage System (1,2,3,4,and 5) Correspond to MB, CH, DI, DIB
and DICH. See Tables (5.2)-(5.4).
242
Table (C.3a):
YEAR
82-
83-
83
84
TILLAGE
SYSTEMS
1
2
3
4
5
Estimated Soil Loss (Tons/ac/yr) Using USLE,
(SF-WW) and (SF-SB), Strip Cropping-Walla Walla Soil.
8485
85-
86-
87-
88-
86
87
88
89
8990
9091
9192
10-Yr
Avg
-
(SF-WW) Rotation--3.5% Slope
2.0
0.8
1.3
2.4
1.4
1.9
0.8
1.2
2.3
1.3
1.2
0.5
0.8
1.4
0.8
1.4
0.6
0.9
1.7
1.0
1.4
0.5
0.9
1.6
1.0
0.9
0.4
0.6
1.1
0.6
1.5
0.6
0.9
1.8
1.0
0.9
0.4
0.6
1.1
0.6
1.4
0.6
0.9
1.7
1.0
1.0
0.4
0.6
1.2
0.7
(SF-WW) Rotation--9.5% Slope
1
2
3
4
5
4.7
1.9
3.0
5.7
3.3
4.5
1.8
2.8
5.4
3.1
2.8
1.1
1.8
3.4
2.0
3.3
1.3
2.1
3.9
2.3
3.2
1.3
2.1
3.9
2.3
2.2
0.9
1.4
2.6
1.5
3.5
1.4
2.2
4.2
2.4
2.2
0.9
1.4
2.6
1.5
Avg
3.4
1.4
2.2
4.1
2.4
2.4
0.9
1.5
2.8
1.7
(SF-SB) Rotation--3.5% Slope
1
2
3
4
5
4.7
2.5
3.1
4.9
3.3
4.4
2.3
2.9
4.7
3.2
2.8
1.5
1.8
2.9
2.0
3.2
1.7
2.1
3.4
2.3
3.2
1.7
2.1
3.4
2.3
2.1
1.1
1.4
2.2
1.5
3.4
1.8
2.2
3.6
2.4
2.2
1.1
1.4
2.3
1.5
3
4
5
11.0 10.5
5.8
7.3
5.5
6.9
11.7 11.0
7.9 7.5
6.6
3.5
4.3
6.9
4.7
7.7
4.1
5.0
8.1
5.5
7.6
4.0
5.0
8.0
5.4
5.0
2.7
3.3
5.3
3.6
8.1
4.3
5.3
8.6
5.8
5.1
2.7
3.4
5.4
3.7
3.2
1.3
2.0
3.9
2.3
Avg
3.4
1.8
2.2
3.6
2.4
2.3
1.2
1.5
2.5
1.7
(SF-SB) Rotation--9.5% Slope
1
2
1.4
0.5
0.9
1.6
1.0
3.2
1.7
2.1
3.4
2.3
Avg
8.0
4.2
5.3
8.5
5.7
5.5
2.9
3.6
5.8
3.9
7.5
4.0
4.9
7.9
5.4
Tillage System (1,2,3,4,and 5) Correspond to MB, CH, DI, DIB
and DICH. See Tables (5.2)-(5.4).
243
Table (C.3b):
YEAR
Estimated Cost of Soil Erosion ($/ac/yr)
(SF-WW) and (SF-SB) Strip Cropping Practice-Walla Walla Soil.
82-
83-
84-
83
84
85
TILLAGE
SYSTEMS
1
2
3
4
5
0.47
0.04
0.21
0.62
0.25
8586
86-
87-
88-
89-
87
88
89
90
9091
9192
10-Yr
Avg
(SF-WW) Rotation--3.5% Slope
0.43
0.02
0.18
0.57
0.23
0.18
0.00
0.02
0.26
0.05
0.25
0.00
0.07
0.35
0.10
0.24
0.00
0.06
0.34
0.10
0.08
0.00
0.00
0.14
0.00
0.28
0.00
0.08
0.39
0.12
0.08
0.00
0.00
0.15
0.00
0.27
0.00
0.08
0.38
0.11
0.11
0.00
0.00
0.18
0.00
(SF-WW) Rotation--9.5% Slope
1
2
3
4
5
1.46
0.43
0.83
1.80
0.95
1.37
0.40
0.78
1.70
0.88
0.77
0.16
0.39
0.97
0.46
0.94
0.22
0.50
1.18
0.58
0.92
0.22
0.49
1.16
0.57
0.53
0.06
0.24
0.68
0.29
1.01
0.25
0.54
1.26
0.63
0.54
0.07
0.25
0.70
0.30
Avg
0.99
0.24
0.53
1.24
0.62
0.60
0.09
0.29
0.78
0.35
(SF-SB) Rotation--3.5% Slope
1
2
3
4
5
1.06
0.60
0.73
1.12
0.78
1.01
0.58
0.70
1.06
0.75
0.67
0.40
0.47
0.70
0.50
0.77
0.45
0.53
0.80
0.57
0.76
0.44
0.53
0.80
0.57
0.53
0.32
0.38
0.56
0.41
0.80
0.47
0.56
0.85
0.60
0.54
0.33
0.39
0.57
0.41
5
2.40
1.31
1.61
2.54
1.74
2.28
1.25
1.53
2.41
1.65
1.46
0.81
0.99
1.54
1.07
1.70
0.94
1.14
1.79
1.24
1.67
0.93
1.13
1.77
1.22
1.14
0.64
0.78
1.20
0.84
1.79
0.99
1.20
1.88
1.30
1.16
0.66
0.79
1.22
0.85
0.91
0.21
0.49
1.15
0.56
Avg
0.80
0.46
0.55
0.84
0.59
0.58
0.35
0.41
0.60
0.44
(SF-SB) Rotation--9.5% Slope
1
2
3
4
0.24
0.01
0.07
0.34
0.10
0.75
0.44
0.52
0.79
0.56
Avg
1.77
0.97
1.19
1.86
1.29
1.24
0.70
0.85
1.31
0.91
1.66
0.92
1.12
1.75
1.21
Tillage System (1,2,3,4,and 5) Correspond to MB, CH, DI, DIB
and DICH. See Tables (5.2)-(5.4).
244
Table (C.4a):
YEAR
82-
83-
84-
85-
86-
87-
88-
83
84
85
86
87
88
89
TILLAGE
SYSTEMS
1
2
3
4
Estimated Soil Loss (Tons/ac/yr) Using USLE,
(SF-WW) and (SF-SB) Standard Practice-Pilot Rock Soil.
3.7
3.7
3.7
7.8
8990
9091
9192
10-Yr
Avg
(SF-WW) Rotation--3.5% Slope
3.1
3.1
3.1
6.5
1.0
1.0
1.0
2.2
2.3
2.3
2.3
4.9
1.6
1.6
1.6
3.4
1.4
1.4
1.4
2.9
1.9
1.9
1.9
4.1
3.2
3.2
3.2
6.8
2.5
2.5
2.5
5.2
1.0
1.0
1.0
2.1
Avg
(SF-WW) Rotation--9.5% Slope
1
2
3
4
7.4
7.4
7.4
6.2
6.2
6.2
15.6 13.1
2.1
2.1
2.1
4.4
4.6
4.6
4.6
9.7
3.3
3.3
3.3
6.9
2.7
6.5 5.0
6.5 5.0
3.9 6.5 5.0
8.1 13.6 10.5
3.9
27 3.9
2.7
5.7
2.0
2.0
2.0
4.2
2
3
8.9
8.9
8.9
7.5
7.5
7.5
2.5
2.5
2.5
5.5
5.5
5.5
3.9
3.9
3.9
3.3
3.3
3.3
4.6
4.6
4.6
7.8
7.8
7.8
6.0
6.0
6.0
(SF-SB) Rotation--9.5% Slope
1
2
3
17.8 15.0
17.8 15.0
17.8 15.0
5.0 11.1
5.0 11.1
5.0 11.1
7.9
7.9
7.9
6.6
6.6
6.6
4.4
4.4
4.4
9.2
Avg
(SF-SB) Rotation--3.5% Slope
1
2.2
2.2
2.2
4.6
9.3 15.6 12.0
9.3 15.6 12.0
9.3 15.6 12.0
2.4
2.4
2.4
5.2
5.2
5.2
Avg
4.8 10.5
4.8 10.5
4.8 10.5
Tillage System (1,2,3, and 4) Correspond to SPR, SWP, SSCU
and CHI. See Tables (5.2)-(5.4).
245
Table (C.4b):
YEAR
82-
83-
83
84
TILLAGE
SYSTEMS
1
2
3
4
1.18
1.18
1.18
2.51
Estimated Cost of Soil Erosion ($/ac/yr),
(SF-WW) and (SF-SB), Standard Practice-Pilot Rock Soil.
8485
8586
86-
87-
88-
89-
87
88
89
90
9091
9192
10-Yr
Avg
(SF-WW) Rotation--3.5% Slope
0.98
0.98
0.98
2.10
0.30
0.30
0.30
0.68
0.72
0.72
0.72
1.55
0.50
0.50
0.50
1.08
0.41
0.41
0.41
0.90
0.59
0.59
0.59
1.29
1.02
1.02
1.02
2.19
0.78
0.78
0.78
1.67
0.29
0.29
0.29
0.65
Avg
(SF-WW) Rotation--9.5% Slope
1
2
3
4
2.39
2.39
2.39
5.06
2.00
2.00
2.00
4.24
0.64
0.64
0.64
1.39
1.47
1.47
1.47
3.13
1.03
1.03
1.03
2.21
0.85
0.85
0.85
1.83
1.22
1.22
1.22
2.61
2.08
2.08
2.08
4.42
(SF-SB) Rotation--3.5% Slope
1
2
3
2
3
1.59
1.59
1.59
3.38
0.62
0.62
0.62
1.33
1.39
1.39
1.39
2.96
Avg
2.22 1.83 0.46 1.29 0.85 0.67 1.04 1.91 1.41 0.43 1.21
2.22 1.83 0.46 1.29 0.85 0.67 1.04 1.91 1.41 0.43 1.21
2.22 1.83 0.46 1.29 0.85 0.67 1.04 1.91 1.41 0.43 1.21
(SF-SB) Rotation--9.5% Slope
1
0.68
0.68
0.68
1.46
Avg
4.68 3.89 1.14 2.82 1.93 1.57 2.32 4.06 3.06 1.09 2.66
4.68 3.89 1.14 2.82 1.93 1.57 2.32 4.06 3.06 1.09 2.66
4.68 3.89 1.14 2.82 1.93 1.57 2.32 4.06 3.06 1.09 2.66
Tillage System (1,2,3, and 4) Correspond to SPR, SWP, SSCU
and CHI. See Tables (5.2)-(5..4).
246
Table (C.5a):
YEAR
8283
8384
TILLAGE
SYSTEMS
1
2
3
4
1.2
1.2
1.2
2.4
Estimated Soil Loss (Tons/ac/yr) Using USLE,
(SF-WW) and (SF-SB), Divided Slope Practice-Pilot Rock Soil.
8485
8586
8687
8788
8889
8990
9091
9192
10-Yr
Avg
(SF-WW) Rotation--3.5% Slope
1.0
1.0
1.0
2.0
0.3
0.3
0.3
0.7
0.7
0.7
0.7
1.5
0.5
0.5
0.5
1.1
0.4
0.4
0.4
0.9
0.6
0.6
0.6
1.3
1.0
1.0
1.0
2.1
0.8
0.8
0.8
1.6
0.3
0.3
0.3
0.7
(SF-WW) Rotation--9.5% Slope
1
2
3
4
2.7
2.7
2.7
5.7
2.3
2.3
2.3
4.8
0.8
0.8
0.8
1.6
1.7
1.7
1.7
3.6
1.2
1.2
1.2
2.5
1.0
1.0
1.0
2.1
1.4
1.4
1.4
3.0
2.4
2.4
2.4
5.0
Avg
1.8
1.8
1.8
3.9
0.7
0.7
0.7
1.5
3
2.8
2.8
2.8
2.3
2.3
2.3
0.8
0.8
0.8
1.7
1.7
1.7
1.2
1.2
1.2
1.0
1.0
1.0
1.4
1.4
1.4
2.4
2.4
2.4
1.9
1.9
1.9
0.7
0.7
0.7
(SF-SB) Rotation--9.5% Slope
1
2
3
6.6
6.6
6.6
5.5
5.5
5.5
1.8
1.8
1.8
4.1
4.1
4.1
2.9
2.9
2.9
2.4
2.4
2.4
3.4
3.4
3.4
5.7
5.7
5.7
1.6
1.6
1.6
3.4
Avg
(SF-SB) Rotation--3.5% Slope
1
2
0.7
0.7
0.7
1.4
1.6
1.6
1.6
Avg
4.4
4.4
4.4
1.8
1.8
1.8
3.9
3.9
3.9
Tillage System (1,2,3, and 4) Correspond to SPR, SWP, SSCU
and CHI. See Tables (5.2)-(5.4).
247
Table (C.5b):
YEAR
82-
83-
83
84
TILLAGE
SYSTEMS
1
2
3
4
0.34
0.34
0.34
0.75
Estimated Cost of Soil Erosion ($/ac/yr)
(SF-WW) and (SF-SB), Divided Slope Practice-Pilot Rock Soil.
8485
85-
86-
87-
88-
86
87
88
89
8990
9091
9192
10-Yr
Avg
(SF-WW) Rotation--3.5% Slope
0.28
0.28
0.28
0.63
0.07
0.07
0.07
0.19
0.20
0.20
0.20
0.46
0.13
0.13
0.13
0.31
0.10
0.10
0.10
0.25
0.16
0.16
0.16
0.38
0.29
0.29
0.29
0.65
0.22
0.22
0.22
0.49
0.07
0.07
0.07
0.18
Avg
(SF-WW) Rotation--9.5% Slope
2
3
4
0.86
0.86
0.86
1.84
0.7]. 0.21 0.52 0.36 0.29 0.43 0.74
0.71 0.21 0.52 0.36 0.29 0.43 0.74
0.71 0.21 0.52 0.36 0.29 0.43 0.74
1.54 0.49 1.13 0.79 0.65 0.94 1.60
(SF-SB) Rotation--3.5% Slope
1
2
3
0.56
0.56
0.56
1.22
0.21
0.21
0.21
0.47
0.49
0.49
0.49
1.07
Avg
0.53 0.41 0.00 0.24 0.10 0.05 0.16 0.43 0.28 0.00 0.22
0.53 0.41 0.00 0.24 0.10 0.05 0.16 0.43 0.28 0.00 0.22
0.53 0.41 0.00 0.24 0.10 0.05 0.16 0.43 0.28 0.00 0.22
(SF-SB) Rotation--9.5% Slope
1
2
3
0.19
0.19
0.19
0.43
Avg
1.57 1.28 0.27 0.89 0.56 0.43 0.71 1.35 0.98 0.26 0.83
1.57 1.28 0.27 0.89 0.56 0.43 0.71 1.35 0.98 0.26 0.83
1.57 1.28 0.27 0.89 0.56 0.43 0.71 1.35 0.98 0.26 0.83
Tillage System (1,2,3, and 4) Correspond to SPR, SWP, SSCU
and CHI. See Tables (5.2)-(5.4).
248
Table (C.6a):
YEAR
Estimated Soil Loss (Tons/ac/yr) Using USLE,
(SF-WW) and (SF-SB), Strip Crop Practice-Pilot Rock Soil.
82-
83-
84-
83
84
85
8586
86-
87-
88-
89-
87
88
89
90
9091
9192
10-Yr
Avg
TILLLAGE
SYSTEMS
1
2
3
4
0.6
0.6
0.6
1.2
(SF-WW) Rotation--3.5% Slope
0.5
0.5
0.5
1.0
0.2
0.2
0.2
0.3
0.4
0.4
0.4
0.8
0.3
0.3
0.3
0.5
0.2
0.2
0.2
0.4
0.3
0.3
0.3
0.6
0.5
0.5
0.5
1.1
0.4
0.4
0.4
0.8
0.2
0.2
0.2
0.3
Avg
(SF-WW) Rotation--9.5% Slope
1
2
3
4
1.4
1.4
1.4
2.9
1.1
1.1
1.1
2.4
0.4
0.4
0.4
0.8
0.9
0.9
0.9
1.8
0.6
0.6
0.6
1.3
0.5
0.5
0.5
1.1
0.7
0.7
0.7
1.5
1.2
1.2
1.2
2.5
0.9
0.9
0.9
1.9
0.4
0.4
0.4
0.8
1.4
1.4
1.4
1.2
1.2
1.2
0.4
0.4
0.4
0.9
0.9
0.9
0.6
0.6
0.6
0.5
0.5
0.5
0.7
0.7
0.7
1.2
1.2
1.2
0.9
0.9
0.9
0.4
0.4
0.4
3.3
3.3
3.3
2.8
2.8
2.8
0.9
0.9
0.9
2.0
2.0
2.0
1.4
1.4
1.4
1.2
1.2
1.2
1.7
1.7
1.7
2.9
2.9
2.9
0.8
0.8
0.8
Avg
(SF-SB) Rotation--9.5% Slope
1
2
3
0.8
0.8
0.8
1.7
Avg
(SF-SB) Rotation---3.5% Slope
1
2
3
0.3
0.3
0.3
0.7
2.2
2.2
2.2
0.9
0.9
0.9
1.9
1.9
1.9
Tillage System (1,2,3, and 4) Correspond to SPR, SWP, SSCU
and CHI. See Tables (5.2)-(5.4).
249
Table (C.6b):
YEAR
82-
83-
83
84
TILLAGE
SYSTEMS
1
2
3
4
0.15
0.15
0.15
0.36
Estimated Cost of Soil Erosion ($/ac/yr),
(SF-WW) and (SF-SB), Strip Crop Practice-Pilot Rock Soil.
8485
8586
8687
87-
88-
88
89
8990
9091
9192
10-Yr
Avg
(SF-WW) Rotation--3.5% Slope
0.12
0.12
0.12
0.30
0.02
0.02
0.02
0.08
0.08
0.08
0.08
0.21
0.05
0.05
0.05
0.14
0.03
0.03
0.03
0.11
0.06
0.06
0.06
0.17
0.13
0.13
0.13
0.31
0.09
0.09
0.09
0.23
0.02
0.02
0.02
0.07
Avg
(SF-WW) Rotation--9.5% Slope
1
2
3
4
0.41
0.41
0.41
0.90
0.34
0.34
0.34
0.75
0.09
0.09
0.09
0.23
0.24
0.24
0.24
0.55
0.16
0.16
0.16
0.38
0.13
0.13
0.13
0.31
0.20
0.20
0.20
0.45
0.35
0.35
0.35
0.78
(SF-SB) Rotation--3.5% Slope
1
2
3
1
0.26
0.26
0.26
0.59
0.09
0.09
0.09
0.22
0.23
0.23
0.23
0.52
Avg
0.15 0.09 0.00 0.01 0.00 0.00 0.00 0.10 0.03 0.00 0.04
0.15 0.09 0.00 0.01 0.00 0.00 0.00 0.10 0.03 0.00 0.04
0.15 0.09 0.00 0.01 0.00 0.00 0.00 0.10 0.03 0.00 0.04
(SF-SB) Rotation--9.5% Slope
2
3
0.08
0.08
0.08
0.20
Avg
0.67 0.53 0.02 0.33 0.17 0.10 0.24 0.56 0.37 0.01 0.30
0.67 0.53 0.02 0.33 0.17 0.10 0.24 0.56 0.37 0.01 0.30
0.67 0.53 0.02 0.33 0.17 0.10 0.24 0.56 0.37 0.01 0.30
Tillage System (1,2,3, and 4) Correspond to SPR, SWP, SSCU
and CHI. See Tables (5.2)-(5.4).
250
Table (C.7a):
YEAR
82-
83-
83
84
TILLAGE
SYSTEMS
1
2
3
4
Estimated Soil Loss (Tons/ac/yr) Using USLE,
(SF-WW) and (SF-SB), Standard Practice-Ritzville Soil.
8485
85-
86-
87-
88-
86
87
88
89
8990
90-
91-
9].
92
10-Yr
Avg
(SF-WW) Rotation--3.5% Slope
3.3
3.3
3.3
5.9
2.1
2.].
2.1
3.8
0.3
0.3
0.3
0.5
1.3
1.3
1.3
2.3
1.2
1.2
1.2
2.2
1.2
1.2
1.2
2.1
0.5
0.5
0.5
0.8
0.0
0.0
0.0
0.0
0.8
0.8
0.8
1.4
1.4
1.4
1.4
2.4
Avg
(SF-WW) Rotation--9.5% Slope
1
2
3
4
6.5
6.5
6.5
11.8
4.2
4.2
4.2
7.6
0.6
0.6
0.6
1.1
2.5
2.5
2.5
4.5
2.4
2.4
2.4
4.4
2.4
2.4
2.4
4.3
0.9
0.9
0.9
1.7
0.0
0.0
0.0
0.0
1.6
1.6
1.6
2.9
2.7
2.7
2.7
4.9
(SF-SB) Rotation--3.5% Slope
1
2
3
7.8
7.8
8.2
5.0
5.0
5.3
0.7
0.7
0.7
3.0
3.0
3.1
2.9
2.9
3.0
2.8
2.8
3.0
1.1
1.1
1.2
0.0
0.0
0.0
2
3
15.7 10.1
15.7 10.1
16.3 10.5
1.4
1.4
1.5
6.0
6.0
6.3
5.8
5.8
6.1
5.7
5.7
5.9
2.3
2.3
2.4
0.0
0.0
0.0
2.4
2.4
2.4
4.3
Avg
1.9
1.9
2.0
3.3
3.3
3.4
2.9
2.9
3.0
Avg
(SF-SB) Rotation--9.5% Slope
1
1.2
1.2
1.2
2.1
3.8
3.8
4.0
6.5
6.5
6.8
5.7
5.7
6.0
Tillage System (1,2,3, and 4) Correspond to SPR, SWP, SSCU
and CHI. See Tables (5.2)-(5.4).
251
Table (C.7b):
YEAR
82-
83-
83
84
Estimated Cost of Soil Erosion ($/ac/yr),
(SF-WW) and (SF-SB), Standard Practice-Ritzville Soil.
TILLAGE
SYSTEMS
1
2
3
4
1.94
1.94
1.94
3.39
8485
85-
86-
87-
88-
86
87
88
89
8990
9091
9192
10-Yr
Avg
(SF-WW) Rotation--3.5% Slope
1.29
1.29
1.29
2.22
0.29
0.29
0.29
0.42
0.82
0.82
0.82
1.38
0.80
0.80
0.80
1.34
0.78
0.78
0.78
1.30
0.39
0.39
0.39
0.60
0.13
0.13
0.13
0.13
0.57
0.57
0.57
0.92
0.88
0.88
0.88
1.48
Avg
(SF-WW) Rotation--9.5% Slope
1
2
3
4
3.75
3.75
3.75
6.66
2.46
2.46
2.46
4.33
0.45
0.45
0.45
0.72
1.52
1.52
1.52
2.63
1.47
1.47
1.47
2.55
1.43
1.43
1.43
2.48
0.65
0.65
0.65
1.07
0.13
0.13
0.13
0.13
(SF-SB) Rotation--3.5% Slope
1
2
3
3
1.01
1.01
1.01
1.72
1.63
1.63
1.63
2.83
1.45
1.45
1.45
2.51
Avg
3.41 2.19 0.31 1.31 1.27 1.23 0.49 0.00 0.83 1.41 1.25
3.41 2.19 0.31 1.31 1.27 1.23 0.49 0.00 0.83 1.41 1.25
3.55 2.28 0.32 1.36 1.32 1.28 0.51 0.00 0.87 1.47 1.30
(SF-SB) Rotation--9.5% Slope
1
2
0.79
0.79
0.79
1.32
Avg
6.83 4.39 0.62 2.62 2.53 2.46 0.99 0.00 1.66 2.83 2.49
6.83 4.39 0.62 2.62 2.53 2.46 0.99 0.00 1.66 2.83 2.49
7.12 4.58 0.64 2.73 2.64 2.57 1.03 0.00 1.73 2.95 2.60
Tillage System (1,2,3, and 4) Correspond to SPR, SWP, SSCU
and CR1. See Tables (5.2)-(5.4).
252
Table (C.8a):
YEAR
82-
83-
84-
83
84
85
TILLAGE
SYSTEMS
1
2
3
4
Estimated Soil Loss (Tons/ac/yr) Using USLE,
(SF-WW) and (SF-SB), Divided Slope Practice-Ritzville Soil.
8586
86-
87-
88-
87
88
89
8990
9091
9192
10-Yr
Avg
(SF-WW) Rotation--3.5% Slope
1.0
1.0
1.0
1.8
0.7
0.7
0.7
1.2
0.1
0.1
0.1
0.2
0.4
0.4
0.4
0.7
0.4
0.4
0.4
0.7
0.4
0.4
0.4
0.7
0.1
0.1
0.1
0.3
0.0
0.0
0.0
0.0
0.2
0.2
0.2
0.4
0.4
0.4
0.4
0.8
Avg
(SF-WW) Rotation---9.5% Slope
1
2
3
4
2.4
2.4
2.4
4.3
1.5
1.5
1.5
2.8
0.2
0.2
0.2
0.4
0.9
0.9
0.9
1.7
0.9
0.9
0.9
1.6
0.9
0.9
0.9
1.6
0.3
0.3
0.3
0.6
0.0
0.0
0.0
0.0
0.6
0.6
0.6
1.1
1.0
1.0
1.0
1.8
2.4
2.4
2.5
1.6
1.6
1.6
0.2
0.2
0.2
0.9
0.9
1.0
0.9
0.9
0.9
0.9
0.9
0.9
0.4
0.4
0.4
0.0
0.0
0.0
0.6
0.6
0.6
1.0
1.0
1.1
(SF-SB) Rotation--9.5% Slope
1
2
3
5.8
5.8
6.0
3.7
3.7
3.9
0.5
0.5
0.5
2.2
2.2
2.3
2.1
2.1
2.2
2.1
2.1
2.2
0.8
0.8
0.9
0.0
0.0
0.0
0.9
0.9
0.9
1.6
Avg
(SF-SB) Rotation--3.5% Slope
1
2
3
0.4
0.4
0.4
0.7
0.9
0.9
0.9
Avg
1.4
1.4
1.5
2.4
2.4
2.5
2.1
2.1
2.2
Tillage System (1,2,3, and 4) Correspond to SPR, SWP, SSCU
and CHI. See Tables (5.2)-(5.4).
253
Table (C.8b):
YEAR
82-
83-
83
84
TILLAGE
SYSTEMS
1
2
3
4
0.69
0.69
0.69
1.14
Estimated Cost of Soil Erosion (S/ac/yr)1
(SF-WW) and (SF-SB), Divided Slope Practice-Ritzville Soil.
8485
8586
8687
87-
88-
88
89
8990
9091
9192
10-Yr
Avg
(SF-WW) Rotation--3.5% Slope
0.49
0.49
0.49
0.78
0.18
0.18
0.18
0.22
0.34
0.34
0.34
0.52
0.34
0.34
0.34
0.50
0.33
0.33
0.33
0.49
0.21
0.21
0.21
0.27
0.13
0.13
0.13
0.13
0.26
0.26
0.26
0.37
0.36
0.36
0.36
0.55
Avg
(SF-WW) Rotation--9.5% Slope
1
2
3
4
1.46
1.46
1.46
2.53
0.98
0.98
0.98
1.67
0.25
0.25
0.25
0.34
0.64
0.64
0.64
1.05
0.62
0.62
0.62
1.02
0.61
0.61
0.61
0.99
0.32
0.32
0.32
0.47
0.13
0.13
0.13
0.13
(SF-SB) Rotation--3.5% Slope
1
2
3
0.45
0.45
0.45
0.71
0.68
0.68
0.68
1.12
0.61
0.61
0.61
1.00
Avg
1.06 0.68 0.10 0.41 0.39 0.38 0.15 0.00 0.26 0.44 0.39
1.06 0.68 0.10 0.41 0.39 0.38 0.15 0.00 0.26 0.44 0.39
1.10 0.71 0.10 0.42 0.41 0.40 0.16 0.00 0.27 0.46 0.40
(SF-SB) Rotation--9.5% Slope
1
2
3
0.33
0.33
0.33
0.50
Avg
2.51 1.61 0.23 0.96 0.93 0.91 0.36 0.00 0.61 1.04 0.92
2.51 1.61 0.23 0.96 0.93 0.91 0.36 0.00 0.61 1.04 0.92
2.61 1.68 0.24 1.00 0.97 0.94 0.38 0.00 0.64 1.09 0.96
Tillage System (1,2,3, and 4) Correspond to SPR, SW?, SSCU
and CHI. See Tables (5.2)-(5.4).
254
Table (C.9a):
YEAR
82-
83-
83
84
TILLAGE
SYSTEMS
1
2
3
4
Estimated Soil Loss (Tons/ac/yr) Using USLE,
(SF-WW) and (SF-SB), Strip Crop Practice-Ritzville Soil.
8485
85-
86-
87-
88-
86
87
88
89
8990
9091
9192
10-Yr
Avg
(SF-WW) Rotation--3.5% Slope
0.5
0.5
0.5
0.9
0.3
0.3
0.3
0.6
0.0
0.0
0.0
0.1
0.2
0.2
0.2
0.4
0.2
0.2
0.2
0.3
0.2
0.2
0.2
0.3
0.1
0.1
0.1
0.1
0.0
0.0
0.0
0.0
0.1
0.1
0.1
0.2
0.2
0.2
0.2
0.4
Avg
(SF-WW) Rotation--9.5% Slope
1
2
3
4
1.2
1.2
1.2
2.2
0.8
0.8
0.8
1.4
0.1
0.1
0.1
0.2
0.5
0.5
0.5
0.8
0.4
0.4
0.4
0.8
0.4
0.4
0.4
0.8
0.2
0.2
0.2
0.3
0.0
0.0
0.0
0.0
0.3
0.3
0.3
0.5
0.5
0.5
0.5
0.9
2
3
1.2
1.2
1.3
0.8
0.8
0.8
0.1
0.1
0.1
0.5
0.5
0.5
0.5
0.5
0.5
0.4
0.4
0.5
0.2
0.2
0.2
0.0
0.0
0.0
0.3
0.3
0.3
0.5
0.5
0.5
1
2.9
2.9
3.0
1.9
1.9
1.9
0.3
0.3
0.3
1.1
1.1
1.2
1.1
1.1
1.1
1.0
1.0
1.1
0.4
0.4
0.4
0.0
0.0
0.0
0.4
0.4
0.5
Avg
(SF-SB) Rotation--9.5% Slope
2
3
0.4
0.4
0.4
0.8
Avg
(SF-SB) Rotation--3.5% Slope
1
0.2
0.2
0.2
0.3
0.7
0.7
0.7
1.2
1.2
1.2
1.1
1.1
1.1
Tillage System (1,2,3, and 4) Correspond to SPR, SWP, SSCU
and CHI. See Tables (5.2)-(5.4).
255
Table (C.9b):
YEAR
82-
83-
83
84
TILLAGE
SYSTEMS
1
2
3
4
0.41
0.41
0.41
0.63
Estimated Cost of Soil Erosion ($/ac/yr),
(SF-WW) and (SF-SB), Strip Crop Practice-Ritzville Soil.
8485
8586
86-
87-
88-
87
88
89
8990
9091
9192
10-Yr
Avg
(SF-WW) Rotation--3.5% Slope
0.31
0.31
0.31
0.45
0.15
0.15
0.15
0.17
0.24
0.24
0.24
0.32
0.23
0.23
0.23
0.32
0.23
0.23
0.23
0.31
0.17
0.17
0.17
0.20
0.13
0.13
0.13
0.13
0.20
0.20
0.20
0.25
0.24
0.24
0.24
0.34
(SF-WW) Rotation--9.5% Slope
1
2
3
4
0.79
0.79
0.79
1.33
0.56
0.56
0.56
0.90
0.19
0.19
0.19
0.24
0.38
0.38
0.38
0.59
0.37
0.37
0.37
0.57
0.37
0.37
0.37
0.56
0.22
0.22
0.22
0.30
0.13
0.13
0.13
0.13
(SF-SB) Rotation--3.5% Slope
1
2
3
Avg
0.29
0.29
0.29
0.42
0.40
0.40
0.40
0.63
0.37
0.37
0.37
0.57
Avg
0.53 0.34 0.05 0.21 0.20 0.19 0.08 0.00 0.13 0.22 0.20
0.53 0.34 0.05 0.21 0.20 0.19 0.08 0.00 0.13 0.22 0.20
0.55 0.36 0.05 0.21 0.21 0.20 0.08 0.00 0.14 0.23 0.20
(SF-SB) Rotation--9.5% Slope
1
2
3
0.23
0.23
0.23
0.31
Avg
1.25 0.81 0.12 0.48 0.47 0.46 0.18 0.00 0.31 0.52 0.46
1.25 0.81 0.12 0.48 0.47 0.46 0.18 0.00 0.31 0.52 0.46
1.31 0.84 0.12 0.50 0.49 0.47 0.19 0.00 0.32 0.54 0.48
Tillage System (1,2,3, and 4) Correspond to SPR, SWP, SSCU
and CHI. See Tables (5.2)-(5.4).
256
Table (C.lOa):
YEAR
Estimated Soil Loss (Tons/ac/yr) Using USLE,
(WW-GP), Standard Practice--Athena Soil.
82-
83-
84-
85-
86-
87-
88-
83
84
85
86
87
88
89
TILLAGE
SYSTEMS
CHIMBD 7.6
DICUL 6.8
DISMBD 7.9
8990
9091
9192
10-Yr
(WW-GP) Rotation--3.5% Slope
7.3
6.6
7.7
5.8
5.2
6.0
6.5
5.9
6.8
6.3
5.7
6.7
5.0
4.5
5.3
6.2
5.6
6.6
7.3
6.6
7.7
(WW-GP) Rotation--9.5% SLOPE
Avg
6.9
6.2
7.2
4.8
4.3
5.0
6.4
5.7
6.7
Avg
CFIINBD 15.1 14.7 11.5 13.0 12.7 10.0 12.5 14.6 13.7 9.5 12.7
DICUL 13.6 13.2 10.4 11.7 11.4 9.0 11.2 13.1 12.3 8.6 11.5
DISMBD 15.9 15.4 12.1 13.7 13.3 10.5 13.1 15.3 14.4 10. 13.4
257
Table (C.lOb):
YEAR
8283
TILLAGE
SYSTEMS
8384
Estimated Cost of Soil Erosion (S/ac/yr)1
(WW-GP), Standard Practice--Athena Soil.
8485
8586
8687
87-
88-
89-
90-
91-
88
89
90
91
92
10-Yr
(WINTER WHEAT) Rotation--3.5% SLOPE
Avg
CHIMBD 2.00 1.96 1.59 1.76 1.73 1.43 1.70 1.95 1.84 1.37 1.7
DICIJL
1.83 1.79 1.46 1.62 1.58 1.31 1.56 1.78 1.69 1.26 1.6
DISMBD 2.09 2.04 1.66 1.84 1.80 1.48 1.78 2.03 1.92 1.42 1.8
(WINTER WHEAT) Rotation--9.5% SLOPE
Avg
CHIMBD 3.73 3.64 2.91 3.25 3.18 2.57 3.13 3.62 3.41 2.45 3.2
DICUL 3.38 3.30 2.65 2.95 2.89 2.34 2.84 3.28 3.10 2.24 2.9
DISMBD 3.90 3.80 3.04 3.40 3.32 2.68 3.27 3.78 3.57 2.56 3.3
(GREEN PEA) Rotation--3.5% SLOPE
Avg
CHIMBD 16.0 16.0 15.9 16.0 16.0 15.9 16.0 16.0 16.0 15.9 16.
DICUL 16.0 16.0 15.9 16.0 15.9 15.9 15.9 16.0 16.0 15.9 16.
DISMBD 16.0 16.0 16.0 16.0 16.0 15.9 16.0 16.0 16.0 15.9 16.
(GREEN PEA) Rotation--9.5% SLOPE
Avg
CHIMBD 16.3 16.3 16.2 16.3 16.2 16.1 16.2 16.3 16.3 16.1 16.
DICUL 16.3 16.3 16.1 16.2 16.2 16.1 16.2 16.3 16.2 16.1 16.
DISMBD 16.4 16.4 16.2 16.3 16.3 16.2 16.3 16.4 16.3 16.1 16.
258
Table (C.11a):
YEAR
Estimated Soil Loss (Tons/ac/yr) Using USLE,
(WW-GP), Divided slope Practice--Athena Soil
82-
83-
84-
83
84
85
TILLAGE
SYSTEMS
CHIMBD 2.3
DICUL 2.1
DISMBD 2.5
8586
86-
87-
88-
87
88
89
8990
9091
9192
10-Yr
Avg
(WW-GP) Rotation--3.5% SLOPE
2.3
2.1
2.4
1.8
1.6
1.9
2.0
1.8
2.1
2.0
1.8
2.1
1.6
1.4
1.6
1.9
1.7
2.0
2.3
2.0
2.4
2.1
1.9
2.2
1.5
1.3
1.6
Avg
(WW-GP) Rotation--9.5% SLOPE
CHIMBD 5.6
DICUL 5.0
DISMBD 5.8
5.4
4.9
5.7
4.2
3.8
4.5
4.8
4.3
5.0
4.7
4.2
4.9
3.7
3.3
3.9
4.6
4.1
4.8
5.4
4.8
5.6
2.0
1.8
2.1
5.0
4.5
5.3
3.5
3.2
3.7
4.7
4.2
4.9
259
Table (C.11b):
YEAR
TILLAGE
SYSTEMS
Estimated Cost of Soil Erosion ($/ac/yr),
(WW-GP), Divided Slope Practice--Athena Soil
82-
83-
84-
83
84
85
8586
86-
87-
88-
87
88
89
(WINTER WHEAT)--3.5% SLOPE
8990
9091
9192
10-Yr
Avg
CHIMBD 0.82 0.80 0.69 0.74 0.73 0.64 0.72 0.80 0.77 0.6 0.73
DICUL 0.76 0.75 0.65 0.70 0.69 0.60 0.68 0.75 0.72 0.6 0.69
DISMBD 0.84 0.83 0.71 0.77 0.75 0.66 0.75 0.83 0.79 0.6 0.76
(WINTER WHEAT)--9.5% SLOPE
Avg
CHIMBD 1.55 1.51 1.25 1.37 1.35 1.12 1.33 1.51 1.43 1.1 1.35
DICUL 1.42 1.39 1.15 1.26 1.24 1.04 1.23 1.39 1.32 1.0 1.24
DISMBD 1.61 1.58 1.30 1.43 1.40 1.17 1.38 1.57 1.49 1.1 1.40
(GREEN PEA)--3.5% SLOPE
Avg
CHIBMD 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 16. 15.8
DICUL 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 16. 15.8
DISMBD 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 16. 15.8
(GREEN PEA)--9.5% SLOPE
Avg
CHIMBD 15.9 15.9 15.9 15.9 15.9 15.9 15.9 15.9 15.9 15.9 16.
DICUL 15.9 15.9 15.9 15.9 15.9 15.8 15.9 15.9 15.9 15.8 16.
DISMBD 16.0 15.9 15.9 15.9 15.9 15.9 15.9 15.9 15.9 15.9 16.
260
Table (C.12a):
YEAR
82-
83-
83
84
TILLAGE
SYSTEMS
CHIMBD 1.2
DICUL 1.1
DISMBD 1.2
Estimated Soil Loss (Tons/ac/yr) Using USLE,
(WW-GP), Strip Cropping--Athena Soil.
8485
8586
86-
87-
88-
87
88
89
8990
9091
9192
10-Yr
Avg
(WW-GP) Rotation--3.5% SLOPE
1.1
1.0
1.2
0.9
0.8
0.9
1.0
0.9
1.1
1.0
0.9
1.0
0.8
0.7
0.8
1.0 11 1.1
0.9
1.0
1.0
1.2
1.0
1.1
0.7
0.7
0.8
Avg
(WW-GP) Rotation--9.5% SLOPE
CHIMBD 2.8
DICUL 2.5
DISMBD 2.9
2.7
2.4
2.8
2.1
1.9
2.2
2.4
2.2
2.5
2.3
2.1
2.5
1.8
1.7
1.9
2.3
2.1
2.4
2.7
2.4
2.8
1.0
0.9
1.0
2.5
2.3
2.7
1.8
1.6
1.8
2.3
2.1
2.5
261
Table (C.12b):
YEAR
TILLAGE
SYSTEMS
82-
83-
83
84
Estimated Cost of Soil Erosion (S/ac/yr)1
(WW-GP), Strip Crop Practice--Athena Soil.
8485
85-
86-
87-
86
87
88
8889
8990
9091
9192
10-Yr
(WINTER WHEAT)--3.5% SLOPE
Avg
CHIMBD .55 0.54 0.49 0.52 0.51 0.46 0.51 0.54 0.53 0.45 0.51
DICUL .53 0.52 0.47 0.49 0.49 0.44 0.48 0.52 0.50 0.44 0.49
DISMBD .57 0.56 0.50 0.53 0.52 0.47 0.52 0.56 0.54 0.46 0.52
(WINTER WHEAT)--9.5% SLOPE
Avg
CHIMBD .92 0.90 0.77 0.83 0.82 0.71 0.81 0.90 0.86 0.68 0.82
DICUL .85 0.84 0.72 0.78 0.76 0.66 0.76 0.84 0.80 0.64 0.76
DISBMD .95 0.93 0.79 0.86 0.84 0.73 0.83 0.93 0.89 0.70 0.84
(GREEN PEA)--3.5% SLOPE
Avg
CHIMBD 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 16. 15.8
DICUL 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 16. 15.8
DISMBD 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 16. 15.8
(GREEN PEA)--9.5% SLOPE
Avg
CHIMBD 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 16. 15.8
DICUL 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 16. 15.8
DISMBD 15.9 15.8 15.8 15.8 15.8 15.8 15.8 15.8 15.8 16. 15.8
262
Table (C.13):
Maximum Profit, Associated Tillage System and
Practice, and Acreage under various T-Values
and NO3-N Leaching Constraints--Pilot Rock
Soils.
Constraint
Tillage Systems
Acreage
T<=2,L>=0
z = $51,526.13
SWPW-DIV-THP-F6W
SWPW-DIV-NHP-F6W
SWPW-STD-THP-F6W
SWPW-STD-NHP-F6W
668.18
122.57
176.82
32.43
z = $64,677.98
SWPW-STD-THP-F6W
SWPW-STD-NHP-F6W
SWPW-DIV-THP-F6W
SWPW-DIV-NHP-F6W
761.25
139.64
83.75
15.36
z = $66,562.64
SWPW-STD-THP-F6W
SWPW-STD-NHP-F6W
845.00
155.00
T<=4, L>=0
T<=6,L>=O
Z = Maximum Profit, STD=standard tillage, DIV=divided slope,
STR=strip cropping. F#W and F#B (#= 1,2..6)=fertilizer
application rate and timing option #, in SF-WW and SF-SB
DICHW=disking followed by chiselling in SFrespectively.
WW, DICHB=disking followed by chiselling in SF-SB, CHW
chiselling in SF-WW, CHW=chiselling in SF-WW, CHB and
CHIB=chiselling in SF-SB, SWPW=sweep plowing in SF-WW,
SWPB=sweep plowing in SF-SB, SSCUW=herbicide spray followed
by sweep plow and cultiweeding in SF-WW.
263
Table (C.14):
Multi-Objective Programming Optimal Solution
(MOP)--WALLA WALLA Soil.
Abatement
Expense
Weights
Soil loss
($/ac)
(Tons/ac)
Wh
We
Production System
in Solution and
(lbs/ac) Percentage
NO3-N
Leached
0 (BASE)
0.00
0.00
7.18
5.02
DICHW-STD-F6W
100.0
5
1.00
0.00
7.18
4.33
0.00
1.00
4.02
5.54
3.16
1.21
4.10
5.40
3.08
1.06
6.10
4.67
DICHW-STD-F2W
DICHW-STD-F6W
CHW-STD-F6W
CHW-DIV-F6W
CHW-STD-F2W
CHW-STD-F6W
CHW-STD-F2W
DICHW-STD-F6W
49.4
50.6
96.1
3.9
9.2
90.8
35.2
64.8
1.00
0.00
7.18
3.64
98.7
0.00
1.00
3.56
5.54
3.62
1.90
4.10
4.65
3.08
1.01
5.01
4.31
DICHW-STD-F2W
DICHW-STD-F6W
CHW-STD-F6W
CHW-DIV-F6W
CHW-STD-F2W
CHW-STD-F6W
CHW-STD-F2W
DICHW-STD-F6W
80.4
19.6
58.6
41.4
70.4
29.6
1.00
0.00
8.54
3.26
0.00
1.00
2.66
5.54
5.88
2.28
3.63
3.91
4.91
0.65
6.87
3.35
DICHW-STD-F2W
DICHB-STD-F1B
CHW-STD-F6W
CHW-DIV-F6W
CHW-STD-F2W
DICHW-DIV-F2W
DICHW-STD-F2W
CHB-DIV-F1B
86.3
13.7
47.5
52.5
72.8
27.2
89.6
10.4
1.00
0.00
9.91
2.90
0.00
1.00
1.75
5.54
8.16
2.64
2.80
3.72
7.11
0.82
6.55
3.07
DICHW-STD-F2W
DICHB-STD-F1B
CHW-STD-F6W
CHW-DIV-F6W
CHW-STD-F2W
DICHW-DIV-F2W
DICHW-STD-F2W
CHB-DIV-F1B
72.5
27.5
14.6
85.4
25.7
74.3
79.1
20.9
10
20
30
1.3
264
Table (C.14) Continued: Multi-Objective Programming Optimal
(MOP) Solution --WALLA WALLA Soil.
Abatement
Expense
Weights
Soil loss
($/ac)
Wh
(Tons/ac)
40
1.00
0.00
11.28
2.54
0.00
1.00
1.17
5.54
10.11
3.00
2.38
3.47
8.90
0.93
6.23
2.80
1.00
0.00
12.65
2.17
0.00
1.00
0.85
5.54
11.80
3.37
2.44
3.13
10.21
0.96
5.91
2.52
50
We
Production System
NO3-N
Leached in Solution and
(lbs/ac) Percentage
DICHW-STD-F2W
DICHB-STD-F1B
CHW-DIV-F6W
CHW-STR-F6W
DICHW-DIV-F2W
DICHB-STR-F1B
DICHW-STD-F2W
CHB-DIV-F1B
58.7
41.3
73.6
26.4
94.2
5.8
68.6
31.4
DICHW-STD-F2W
DICHB-STD-F1B
CHW-DIV-F6W
44.8
55.2
26.3
73.7
81.4
18.6
58.1
41.9
CHW-STR--F6W
DICHW-DIV-F2W
DICHB-STR-F1B
DICHW-STD-F2W
CHB-DIV-F1B
STDstandard tillage, DIV=divided slope, STR=strip cropping.
F#W and F#B (#= 1,2.. .6)=fertilizer application rate and
timing option #, in SF-WW and SF-SB respectively. Tillage
systems are: DICHW=disking followed by chiselling in SF-WW;
DICHB=disking followed by chiselling in SF-SB;
CHW=chiselling in SF-WW; CHW=chiselling in SF-WW; CHB and
CHIB=chiselling in SF-SB; SWPW=sweep plowing in SF-WW;
SWPB=sweep plowing in SF-SB; SSCUW=herbicide spray followed
by sweep plow and cultiweeding in SF-WW.
265
Table (C.15):
Multi-Objective Programming (MOP) Optimal
Solution for Soil loss of Less than or Equal
to 3T-Value--Pilot Rock Soil.
Abatement
Expense
Weights
Soil loss
NO3-N
Leached
($/ac)
Wh
(Tons/ac)
(lbs/ac)
O (BASE)
0.00
0.00
2.52
7.80
SWPW-STD--F6W 100.0
5
1.00
0.00
3.19
6.81
0.00
1.00
2.08
7.80
1.11
0.99
2.52
6.93
0.44
0.87
2.36
7.23
SWPW-STD-F6W
SWPB-STD-F1B
SWPW-STD-F6W
SWPW-DIV-F6W
SWPW-STD-F4W
SWPW-STD-F6W
SWPW-STD-F6W
SWPB-STD-F1B
81.3
18.7
73.7
26.3
58.1
41.9
89.2
10.8
1.00
0.00
3.53
5.87
0.00
1.00
1.63
7.80
0.84
1.64
2.19
6.65
1.90
1.93
2.47
6.16
SWPW-STD-F4W
SWPW-STD-F6W
SWPB-STD-F1B
SWPW-STD-F6W
SWPW-DIV-F6W
SWPW-STD-F6W
SWPB-STR-F1B
SWPW-STD-F4W
SWPB-STR-F1B
27.7
43.7
28.6
47.4
52.6
78.4
21.6
96.3
SWPW-STD-F4W
SWPB-STD-F1B
SWPB-DIV-F1B
SWPW-STD-F4W
SWPB-STR-F1B
SWPW-DIV-F6W
SWPB-STR-F1B
SWPW-DIV-F6W
SWPW-STR-F6W
50.7
31.3
18.0
69.7
30.3
96.4
3.6
91.8
8.2
SWPW-STD-F4W
SWPB-STD-F1B
SWPB-DIV-F1B
SWPW-STD-F4W
SWPB-DIV-F1B
SWPW-STD-F4W
SWPB-STR-F1B
SWPW-DIV-F6W
SWPW-STR-F6W
17.4
35.8
46.8
33.0
67.0
43.1
56.9
8.5
91.5
10
20
30
We
1.00
0.00
3.53
4.43
2.74
3.37
2.06
5.15
1.27
2.65
0.83
7.61
0.00
1.00
0.79
7.80
1.00
0.00
3.53
3.16
1.88
0.98
2.15
3.75
3.08
4.64
1.65
4.14
0.00
1.00
0.45
7.80
Production System
in Solution and
Percentage
3.7
266
Table (C.15) Continued: Multi-Objective Programming (MOP)
Optimal Solution for Soil loss of Less than or
Equal to 3T-Value--Pilot Rock Soil.
Abatement
Expense
Weights
W
($/ac)
Wh
40
50
Soil loss
(Tons/ac)
Production System
in Solution and
(lbs/ac) Percentage
NO3-N
Leached
1.00
0.00
3.53
2.50
2.29
0.63
2.12
2.25
0.00
1.00
0.41
7.69
3.12
5.19
1.24
3.13
0.83
4.56
0.41
6.44
1.00
0.00
1.39
2.50
0.74
3.10
0.99
2.50
0.34
3.10
0.75
4.08
0.00
1.00
0.65
5.60
SWPB-STD-F1B
SWPB-STD-F3B
SWPB-DIV-F1B
SWPB-DIV-F6W
SWPB-STD-F1B
SPRW-STR-F6W
SSCUW-STR-F4W
SWPW-STD-F4W
SWPB-STR-F1B
SWPW-STR-F4W
SWPW-STR-F6W
10.0
40.2
49.8
96.3
3.7
38.0
62.0
16.5
83.5
90.5
9.5
SWPB-DIV-F1B
SWPB-STR-F2B
SWPB-STR-F1B
SWPB-STR-F3B
SWPW-STR-F4W
SWPB-STR-F3B
40.5
59.5
63.0
37.0
41.7
58.3
62.9
37.1
SSCtIW-STR-F4W
CHIB-STR-F3B
STD=standard tillage, DIV=divided slope, STR=strip cropping.
F#W and F#B (/1= 1,2...6)=fertilizer application rate and
timing option #, in SF-WW and SF-SB respectively. Tillage
systems are: DICHW=disking followed by chiselling in SF-WW;
DICHB=disking followed by chiselling in SF-SB;
CHW=chiselling in SF-WW; CHW=chiselling in SF-WW; CHB and
CHI.B=chiselling in SF-SB; SWPW=sweep plowing in SF-WW;
SWPB=sweep plowing in SF-SB; SSCTJW=herbicide spray followed
by sweep plow and cultiweeding in SF-WW.
267
Table (C.16):
Multi-Objective Programming (MOP) Optimal
Solution---Ritzville Soil.
Abatement
Cost
Weights
($/ac)*
Wh
We
Soil loss
(Tons/ac)
Production System
in Solution and
(lbs/ac) Percentage
NO3-N
Leached
0 (BASE)
0.00
0.00
1.54
1.20
SWPW-STD--F6W 100.0
5
1.00
0.00
1.54
1.06
0.00
1.00
1.30
1.20
SWPW-STD-F2W
SWPW-STD-F6W
SWPW-STD-F6W
SWPW-DIV-F6W
71.5
28.5
75.7
24.3
1.00
0.00
1.74
0.95
SWPW-STD--F2W
91.1
SWPW-DIV-F6W
8.9
51.6
48.4
85.9
14.1
78.0
21.0
SWPW-STD-F2W
SWPB-STD-F1B
SWPW-STD-F6W
SWPW-DIV-F6W
SWPW-STD-F2W
SWPB-STR-F1B
SWPW-STD-F2W
SWPB-DIV-F1B
61.4
38.6
3.1
96.9
77.5
22.5
39.0
61.0
SWPW-STD-F2W
SWPB-STD-F1B
SWPW-DIV-F6W
SWPW-STR-F6W
SWPW-STD-F2W
SWPW-STR-F2W
SWPW-STD-F2W
SWPB-DIV-F1B
31.7
68.3
28.3
71.7
60.2
39.8
53.0
47.0
SWPW-STD-F2W
SWPB-STD-F1B
SWPW-STR-F6W
SSCUW-STR-F4W
SWPW-STD-F2W
SWPB-STR-F1B
SWPW-STD-F2W
SWPB-DIV-F1B
2.0
98.0
58.1
41.9
43.0
57.0
32.6
67.4
10
0.00
1.00
1.05
1.20
SWPB-STD-F1B
SWPW-STD-F6W
SWPW-DIV-F6W
0.69
0.25
1.40
1.00
SWPW-STD--F2W
0.35
0.20
1.32
1.04
SWPW-DIV-F2W
20
30
40
1.00
0.00
2.38
0.77
0.00
1.00
0.55
1.20
1.83
0.43
1.34
0.87
0.79
0.33
0.92
1.00
1.00
0.00
3.02
0.59
0.00
1.00
0.33
1.20
2.69
0.61
1.18
0.76
1.84
0.17
1.40
0.72
1.00
0.00
3.66
0.41
0.00
1.00
0.26
1.24
3.40
0.83
1.02
0.66
2.64
0.25
1.34
0.60
SWPW-STD--F2W
268
Table (C.16) Continued: Multi-Objective Programming (MOP)
Optimal Solution--Ritzville Soil.
Abatement
Weights
Cost
($/ac)*
50
Wh
We
Soil loss
(Tons/ac)
Production System
in Solution and
(lbs/ac) Percentage
NO3-N
Leached
1.00
0.00
2.52
0.40
SWPB-STD-F1B
SWPB-STR-F1B
0.00
1.00
0.27
1.27
SSCtJW-STR-F4W
2.25
0.87
0.58
0.64
1.94
0.24
1.28
0.47
CHIB-STR-F3B
SWPW-DIV-F2W
SWPB-STR-F1B
SWPW-STD-F2W
SWPB-DIV-F1B
61.5
38.5
96.3
3.7
40.7
59.3
12.2
87.8
STD=standard tillage, DIV=divided slope, STR=strip crop,
F#W, F#B (#= 1,2..6)=fertilizer application rate and timing
option #, in SF-WW and SF-SB respectively. Tillage: DICHW=
disking followed by chiselling in SF-WW; DICHB=disking
followed by chiselling in SF-SB; CHW=chiselling in SF-WW;
CHW=chiselling in SF-WW; CHB and CHIB=chiselling in SF-SB;
SWPW=sweep plowing in SF-WW; SWPB=sweep plowing in SF-SB;
SSCUW=herbicide spray followed by sweep plow and
cultiweeding in SF-WW.
269
Table (C.17):
Multi-Objective Programming (MOP) Optimal
Solution--Athena Soil.
Abatement
Expense
Weights
We
Soil loss
(Tons/ac)
NO3-N
Leached
Production System
in Solution and
Percentage
(lbs/ac)
($/ac)
Wh
0 (BASE)
0.00
0.00
6.75
8.60
DICUL-STD-F2
100.0
5
1.00
0.00
7.31
8.40
0.00
1.00
6.13
8.60
DICUL-STD-F2
DISMBD-STD-F2
DICUL-STD-F2
DICUL-DIV-F2
50.2
49.8
86.2
13.8
1.00
0.00
7.87
8.20
2.37
0.40
5.83
8.51
0.00
1.00
5.50
8.60
DICUL-STD-F2
DISMBD-STD-F2
CHIMBD-DIV-F2
DICUL-STD-F2
DICUL-STD-F2
0.4
99.6
21.5
78.5
72.4
27.6
10
DICTJL-DIV-F2
20
1.00
0.00
7.56
8.20
3.32
0.40
6.40
8.20
2.16
0.40
4.91
8.43
CHIMBD-STD-F2
DISMBD-STD-F2
CHIMBD-DIV-F2
DISMBD-STD-F2
CHIMBD-DIV-F2
DICUL-STD--F2
30
0.00
1.00
4.24
8.60
DICUL-STD-F2
DICUL-DIV-F2
1.00
0.00
6.86
8.20
1.93
0.40
3.99
8.34
CHINBD-STD-F1
CHIMBD-STR-F1
CHIMBD-DIV-F2
DICTJL-STD-F2
3.87
0.40
4.92
8.20
0.00
1.00
2.99
8.60
CHIMBD-DIV-F2
DISMBD-STD-F2
DICUL-STD-F2
DICUL-DIV-F2
86.1
13 9
27.3
72.7
43.0
57.0
44.7
55.3
89.7
10.3
64.5
35.5
54.7
45.3
17.0
83.0
270
Table (C.17) Continued: Multi-Objective Programming (MOP)
Optimal Solution--Athena Soil.
Abatement
Expense
Weights
Soil loss
($/ac)
Wh
We
(Tons/ac)
40
1.00
0.00
6.09
8.20
1.22
0.40
2.30
8.45
3.97
0.40
3.34
8.20
0.00
1.00
2.12
8.60
1.00
0.00
5.32
50
Production System
in Solution and
(lbs/ac) Percentage
NO3-N
Leached
CHIMBD-STD-F1
CHIMBD-STR-F1
CHIMBD-DIV-F2
DICUL-DIV-F2
CHIMBD-DIV-F2
DISMBD-STD-F2
DICUL-DIV-F2
DICUL-STR-F2
77.5
22.5
36.9
63.1
82.1
17.9
91.2
09.8
8.20
CHfl4BD-STD-F].
CHINBD-STR-F1
CHIMBD-DIV-F2
65.2
34.8
91.9
8.1
73.7
26.3
68.4
32.6
3.76
0.40
2.37
8.20
0.51
0.40
1.99
8.49
0.00
1.00
1.86
8.60
CHII4BD-STR-F2
DICUL-DIV-F2
DISMBD-STR-F2
DICUL-DIV-F2
DICUL-STR-F2
STD=standard tillage, DIV=divided slope, STR=strip cropping.
F# (#= 1,2,3,4)=fertilizer application rate and timing
option # in WW-GP.
Tillage systems are: CHIMBD=use of
chisel plow for primary tillage in WW production year and
moldboard plow in GP year; DICUL=use of disk plow for
primary tillage followed by use of cultivator for secondary
tillage, in both WW and GP production period; DISMBD=use of
disk plow for primary tillage during WW period and iuoldboard
plow in GP.
271
APPENDIX D
RESOURCE INFORMATION AND BUDGET DETAILS
Table (D.1):
Showing all resources, data and parameters
used for the budgets.
Des cr ipt ion
Tractor
Propelled
Propelled
First Name
TRACTOR
CRAWLER
200HP
COMBINE
HILLSIDE
COMBINE
HILLSIDE
BARLEY
Qualifying Name
Horsepower Rating
(Hp)
Useful Life
(Hr or Mi)
Fuel Type
Remaining Life
(Hr or Mi)
Fuel Con. (Unit/Hr or /141)
Annual Use
(Hr or Mi)
Speed
(Mi/h)
Width
(Ft)
Field Efficiency
(%)
Capacity
(Ac/Hr)
Power Unit Multiplier
Labor Multiplier
Current List Price
($)
Salvage Value
(%)
Current Market Value
($)
($)
Lease Payment
Annual License & Tax
($)
Annual Insurance
($)
On Farm Hired Labor
(Hr)
200
16000
DI
4000
8.8
800
124000
25
77500
24 'WHEAT
75
24
70
75
3000
DI
1200
5.8
300
3.0
24
70
6
6
1.0
1.1
149000
41.23
105217
1.0
1.1
149000
41.23
105217
.040
.64
.040
64
3000
DI
1200
5.8
300
3.0
Of f Farm Parts & Labor ($)
On Farm Owner Labor
(Hr)
Annual Use Base (Hr or Mi)
Repair Coefficient #1
Depreciation Factor #1
Years Owned
Repair Coefficient #2
Depreciation Factor #2
Capacity
(Def. ,Calc.)
Fuel Use
(Def.,Calc.)
R & M Caic.
(#1,#2)
Lease Caic.
(Hour,Year)
.003
.68
15
2.0
.92
6
2.0
.885
D
6
2.0
.885
D
D
D
D
2
2
2.
272
Table (D.l) Continued:
Showing all resources, data and
parameters used for the budgets.
Description
Implement
Implement
Implement
First Name
BANK-OUT
WAGON
CHISEL
CHOPPER
CHISEL
PLOW
24'
150
25'
150
2000
2000
700
5.8
130
4.5
24
85
11
1.1
1.1
24000
25
15000
1000
5.8
100
4.5
.6
6
.28
.6
10
.28
.6
10
1.3
.885
D
C
1.4
.885
D
C
1.4
.885
D
C
2
2
2
Qualifying Name
Horsepower Rating
(Hp)
Useful Life
(Hr or Mi)
Fuel Type
Remaining Life (Hr or Mi)
Fuel Con. (Unit/Hr or /Mi)
Annual Use
(Hr or Mi)
Speed
(Mi/hr)
Width
(Ft)
Field Efficiency
(%)
Capacity
(Ac/Hr)
Power Unit Multiplier
Labor Multiplier
Current List Price
(5)
Salvage Value
(%)
Current Market Value
Cs)
(5)
Lease Payment
Annual License & Tax
(5)
Annual Insurance
($)
On Farm Hired Labor
(Hr)
50
3000
1800
8.8
200
100
8.6
1.1
1.1
17500
20
10500
85
11.5
1.1
1.1
17000
25
10625
Of f Farm Parts & Labor ($)
On Farm Owner Labor
(Hr)
Annual Use Base (Hr or Mi)
Repair Coefficient #1
Depreciation Factor #1
Years Owned
Repair Coefficient #2
Depreciation Factor #2
Capacity
(Def.,Calc.)
(Def.,Calc.)
Fuel Use
R & M Calc.
(#l,#2)
(Hour,Year)
Lease Calc.
.19
273
Table (D.1) Continued: Showing all resources, data and
parameters used for the budgets.
Implement
Description
Implement
First Name
CHISEL PLOW CULTIVATOR CULTIVATOR
DIV. SLOPE
PLOW STRIP
48'TOOTH
48'TOOTH
25'
Qualifying Name
Horsepower Rating
(Hp)
(Hr or Mi)
Useful Life
Fuel Type
Remaining Life (Hr or Mi)
Fuel Con. (Unit/Hr or /Mi)
Annual Use
(Hr or Mi)
Speed
(Mi/h)
Width
(Ft)
Field Efficiency
(%)
(Ac/Hr)
Capacity
Power Unit Multiplier
Labor Multiplier
Current List Price
($)
Salvage Value
(%)
Current Market Value
Cs)
Lease Payment
(5)
Annual License & Tax
($)
Annual Insurance
(5)
(Hr)
On Farm Hired Labor
Of f Farm Parts & Labor (5)
(Hr)
On Farm Owner Labor
Annual Use Base (Hr or Mi)
Repair Coefficient #1
Depreciation Factor #1
Years Owned
Repair Coefficient #2
Depreciation Factor #2
(Def.,Calc.)
Capacity
(Def.,Calc.)
Fuel Use
(#1,#2)
R & M Calc.
(Hour,Year)
Lease Caic.
liupleinent
150
2000
180
2000
180
2000
1000
1000
1000
100
4.5
100
5.5
85
48
85
27
100
5.5
48
85
25
1.1
1.1
10.0
1.4
1.4
17000
25
10625
1.1
1.1
22000
13750
22000
25
13750
.28
.27
.27
.6
.6
.6
10
1.4
.885
10
1.4
.885
10
1.4
.885
D
C
2
D
C
D
C
2
2
25
274
Table (D.1) Continued: Showing all resources, data and
parameters used for the budgets.
Description
Implement
Implement Implement
First Name
CULTIWEEDER
DISK
PLOW
GRAIN
DRILL
Qualifying Name
(Hp)
Horsepower Rating
(Hr or Mi)
Useful Life
Fuel Type
Remaining Life (Hr or Mi)
Fuel Con. (Unit/Hr or /Mi)
Annual Use
(Hr or Mi)
Speed
(Mi/h)
(Ft)
Width
(%)
Field Efficiency
Capacity
(Ac/Hr)
Power Unit Multiplier
Labor Multiplier
Current List Price
($)
Salvage Value
(%)
Current Market Value
($)
Lease Payment
($)
Annual License & Tax
($)
Annual Insurance
($)
On Farm Hired Labor
(Hr)
48'
180
24'
100
2000
2000
4-12'
60
1500
1000
1000
750
100
5.5
48
85
27
1.1
1.1
30000
35
20250
200
4.5
100
4.0
.270
.18
.6
.320
10
1.4
.885
D
C
5.0
1.7
.885
7.5
2.0
.885
D
C
D
C
2
2
2
24
85
11.0
1.1
1.1
18200
25
11375
70
16
1.1
1.].
33000
25
20625
Of f Farm Parts & Labor ($)
(Hr)
On Farm Owner Labor
Annual Use Base (Hr or Mi)
Repair Coefficient #1
Depreciation Factor #1
Years Owned
Repair Coefficient #2
Depreciation Factor #2
(Def.,Calc.)
Capacity
(Def.,Calc.)
Fuel Use
(#1,#2)
R & M Calc.
(Hour,Year)
Lease Caic.
.6
.6
275
Table (D.1) Continued: Showing all resources, data and
parameters used for the budgets.
Implement
Description
Implement
Implement
First Name
HARROW
MOLDBOARD
PLOW
SWEEP
PLOW
Qualifying Name
Horsepower Rating
(Hp)
Useful Life
(Hr or Mi)
Fuel Type
Remaining Life (Hr or Mi)
Fuel Con. (Unit/Hr or /Mi)
(Hr or Mi)
Annual Use
Speed
(Mi/h)
Width
(Ft)
Field Efficiency
(%)
(Ac/Hr)
Capacity
Power Unit Multiplier
Labor Multiplier
Current List Price
($)
Salvage Value
(%)
Current Market Value
($)
Lease Payment
($)
Annual License & Tax
($)
Annual Insurance
($)
On Farm Hired Labor
(Hr)
60'
10-16"
150
2000
25'
165
2000
1200
1000
1000
80
5.0
100
4.5
100
4.0
80
80
29.0
1.1
1.1
13000
25
8125
5.00
1.1
1.1
28000
80
9.0
1.1
1.1
.18
.29
.6
.6
.6
10
1.7
.885
10
10
C
1.8
.885
D
C
1.8
.885
D
C
2
2
2
150
2000
17000
25
10625
25
17500
Of f Farm Parts & Labor ($)
(Hr)
On Farm Owner Labor
Annual Use Base (Hr or Mi)
Repair Coefficient #1
Depreciation Factor #1
Years Owned
Repair Coefficient #2
Depreciation Factor #2
(Def.,Calc.)
Capacity
(Def.,Calc.)
Fuel Use
R & M Caic.
(#1,#2)
(Hour,Year)
Lease Caic.
D
.29
276
Table (D.l) Continued: Showing all resources, data and
parameters used for the budgets.
Description
Implement Implement
First Name
PACKER
Qualifying Name
Horsepower Rating
(Hp)
Useful Life
(Hr or Mi)
Fuel Type
Remaining Life (Hr or Mi)
Fuel Con. (Unit/Hr or /Mi)
Annual Use
(Hr or Mi)
Speed
(Mi/h)
Width
(Ft)
Field Efficiency
(%)
Capacity
(Ac/Hr)
Power Unit Multiplier
Labor Multiplier
Current List Price
($)
Salvage Value
(%)
Current Market Value
($)
($)
Lease Payment
Annual License & Tax
($)
Annual Insurance
($)
On Farm Hired Labor
(Hr)
Self Propel
GREEN PEA
DRILL
GREEN PEA
COMBINE
40'
150
36'
60
22'
75
2000
1500
1200
750
40
6.0
40'
85
25
1.1
1.1
80
4.0
36
75
2000
DI
1000
5.8
200
3.5
13
13000
25
8125
1.1
1.1
24000
25
15000
.16
.320
.6
.6
10
1.3
.885
D
C
7.5
2.0
.885
2
2
22
80
7.5
1.0
1.1
100000
41.23
70615
Of f Farm Parts & Labor ($)
On Farm Owner Labor
(Hr)
Annual Use Base (Hr or Mi)
Repair Coefficient #1
Depreciation Factor #1
Years Owned
Repair Coefficient #2
Depreciation Factor #2
Capacity
(Def.,Calc.)
Fuel Use
(Def.,Calc.)
R & M Caic.
(#1,#2)
Lease Caic.
(Hour,Year)
D
C
.20
.64
5
1.6
.885
D
D
2
277
Table (D.l) Continued: Showing all resources, data and
parameters used for the budgets.
Description
Auto or Truck
Auto or Truck
First Name
Horsepower Rating
(Hp)
Useful Life
(Hr or Mi)
Fuel Type
Remaining Life
(Hr or Mi)
Fuel Con. (Unit/Hr or /Mi)
Annual Use
(Hr or Mi)
Speed
(Mi/h)
Width
(Ft)
Field Efficiency
(%)
Capacity
(Ac/Hr)
Power Unit Multiplier
Labor Multiplier
Current List Price
($)
Salvage Value
(%)
Current Market Value
($)
Lease Payment
($)
Annual License & Tax
($)
Annual Insurance
($)
On Farm Hired Labor
(Hr)
2-TON TRUCK
PICKUP -4WD
65000
GA
32500
60000
GA
30000
5
8
6500
25
10000
30000
15000
35
30
20250
9750
20
455
20
290
780
190
6500
10000
D
D
D
D
1
1
Of f Farm Parts & Labor ($)
On Farm Owner Labor
(Hr)
Annual Use Base (Hr or Mi)
Repair Coefficient #1
Depreciation Factor #1
Years Owned
Repair Coefficient #2
Depreciation Factor #2
(Def.,Calc.)
Capacity
(Def.,Calc.)
Fuel Use
R & M Caic.
(#1,#2)
Lease Caic.
(Hour,Year)
25
278
Table (D.1) Continued:
Showing all resources, data and
parameters used for the budgets.
Price/Unit
Operating Input
ACCOUNTING COSTS WHEAT
ACCOUNTING COSTS BARLEY
BARLEY COMMISSION
BARLEY SEED
BURN RESIDUE
CONSERVATION PRACTICES
CROP INSURANCE
WHEAT
CROP INSURANCE
BARLEY
PEA
CROP INSURANCE
DIV. SLOPE LABOR WHEAT
FERTILIZER
APPLIED
FERTILIZER EQUIP TOPDRESS
FERTILIZER PEA
FIRST
FERTILIZER PEA
SECOND
HANDLING
WHEAT
HANDLING BARLEY
HANDLING
PEA
HAUL BARLEY SEED
HAUL WHEAT
MACHINERY: WHEAT OR BARLEY
WHEAT
OTHER LABOR
OTHER LABOR
PEA AND BARLEY
PEA SEED
STORAGE
WHEAT
STORAGE BARLEY
WHEAT
STRIP LABOR
STRIP LABOR
PEA
TRANSPORTATION
BARLEY
TRANSPORTATION
WHEAT
PEA
TRANSPORTATION
WHEAT COMMISSION
WHEAT SEED
Custom Operation
.02
.10
10.5
.25
.08
.03
.125
.4
.22
ACRE
ACRE
BU.
LB.
ACRE
ACRE
BU.
BU.
cwt
ACRE
LB.
5
ACRE
.18
.22
.12
.09
.10
LB.
LB.
BU.
BU.
CWT.
.9
1.6
1
5
4
.20
.12
.08
.6
.75
.20
.24
.22
.03
.115
ACRE
ACRE
ACRE
ACRE
ACRE
LB.
BU.
BU.
ACRE
ACRE
BU.
BU.
CWT.
BU.
LB.
Price/Unit
Unit
4.50
ACRE
CUSTOM APPLIER
.25
FERTILI ZER
FERTILIZER EQUIP
HERBICIDE
HERBICIDE AERIAL
HERBICIDES
HERBICIDE PEA
HERBICIDE PEA
5*
4
Unit of Measure
TOPDRES S
APPLIER
APPLIED
APPLI ER
*Value varies by Soil type.
5
1.50
3.50
9.50
12.5
2.00
lb.
ACRE
ACRE
ACRE
ACRE
ACRE
ACRE
279
Showing all resources, data and
Table (D.1) Continued:
parameters used for the budgets.
Description
Other Labor
Other Labor
Other Labor
First Name
HIRED LABOR
DIV. SLOPE
HIRED LABOR
STRIP CROP
HIRED LABOR
Cost or value
($/Hr)
Total Wage Benefits (%)
Labor Type
(A,B)
8
8
8
A
A
A
Description
Other Labor
First Name
OPERATOR
LABOR
Cost or value ($/Hr)
Total Wage Benefits (%)
Labor Type
(A,B)
9
B
Description
Land
Land
First Name
Qualifying Name
Market Value
Property Tax
Appreciation Rate
Interest Rate
Annual Lease
App. Calculations
CROPLAND
BARLEY
CROPLAND
WHEAT
(S/Ac)
(S/Ac)
(%)
(%)
(5/Ac)
(Y,N)
N
N
Description
Management
Management
First Name
DIV SLOPE
COST INCREASE
STRIP CROP
COST INCREASE
% of Total Gross
(%)
% of Total Variable
(%)
Cost per Budget Unit
(5)
Management Option (3,4,5)
*Value varies by Soil Type
10*
20*
4
4
280
Table (D.l) Continued: Showing all resources, data and
parameters used for the budgets.
Parameter Name
Value
Unit
Description
DIESEL
0.87
135250.00
0.10
3410.00
1.30
124100.00
8.00
GAL.
BTU
KWH
BTU
GAL.
BTU
HOUR
Cost of Diesel Fuel
Energy of Diesel Fuel
Cost of Electricity
Electricity energy
Cost of Gasoline
Energy of Gasoline
Hired Repair and
Maintenance Labor Rate
Hired Irrigation Operation
Labor
Insurance Rate, % of Market
value
Interest Rate, Intermediate
Term Borrow
Interest Rate, Intermediate
Term Equity
Interest Rate, Operating
Capital Borrow
Interest Rate, Operating
Capital Equity
Interest Rate, Positive
Cash Flow
Interest Rate, Investment
Capital
Cost of LP Gas
Energy of LP Gas
Lube Multiplier
Cost of Natural Gas
Energy of Nat. Gas per
100 ft3 or Therm
Owner Repair and
Maintenance Labor Rate
Personal Property Tax Rate
DIESEL BTtJ
ELECTRICITY
ELECTRICITY BTU
GASOLINE
GASOLINE BTU
HIRED LABOR
HIRED LABOR IRR
7.50 HOUR
INR
0.50 %
IRITB
9.00 %
IRITE
6.00 %
IRO C B
9.00 %
IROCE
6.00 %
IRP C F
0.00 %
ITI
10.00 %
0.70
LP GAS
92140.00
LP GAS BTU
0.05
LUBE MULTI
4.00
NATURAL GAS
NATURAL GAS BTU 1000000.00
GAL.
BTU
NONE
MCF
BTU
OWNER LABOR
9.00 HOUR
PTR
0.00 %
281
Table (D.2):
Wheat, Barley and Green Peas prices for
Umatilla County, Oregon.
Wheat
Barley
Green Peas
Crop Year
($/bu.)
($/bu.)
(S/ton)
1987/88
1988/89
1989/90
1990/91
1991/92
Average
4.24
4.06
2.83
3.65
3.87
3.73
2.45
2.22
2.47
2.25
2.17
2.31
183.50
210.50
229.70
234.40
226.80
216.98
Source:
Extension Economic Information Office,
AREC Department, Oregon State University, 1993.
Table (D.3):
Wheat, Barley Target prices and Deficiency29
Payments.
Barley
Wheat
Target
Price
Deficiency
Payment
Target
Price
Crop Year
($/bu.)
($/bu.)
($/bu.)
($/bu.)
1987/88
1988/89
1989/90
1990/91
1991/92
Average
4.38
4.23
4.10
4.00
4.00
2.60
2.51
2.43
2.36
2.36
0.24
0.17
0.10
0.04
0.04
0.12
Source:
0.53
0.41
0.30
0.22
0.22
0.34
Deficiency
Payment
USDA-ERS, 1993.
29
Wheat Deficiency Payment = (Target Price - Maximum
The 1990 Farm Bill allows
planting on 85 percent of Wheat base acres and limits
deficiency payments to 70 percent of this base (0.82 =
70/85). Barley Deficiency payment = (Target price - Maximum
The 1990 Farm Bill allows
(Crop price, Loan rate)) * 0.84.
planting on 92.5 percent of Barley base acres and limits
(Crop price, Loan rate)) * 0.82.
deficiency payment to 77.5 percent of the base (0.84 =
77.5/92.5). Wheat and Barley prices are greater than loan
rate during the 5 year period.
282
Table (D.4a):
Economic Costs and Returns for Dryland
Fallow/Winter Wheat Production, Standard
Practice, Option MBW-STD-F1W-Walla Walla Soil.
GROSS INCOME Description
Quantity Unit
$I
DEFICIENCY PMT
WHEAT
75.000
75.000
0.3400
3.7300
WHEAT
BU.
BU.
Unit
Total GROSS Income
Total FALLOW
PLANTING
DRILL SEED Operation
WHEAT SEED
Operation
HAUL SEED
Total PLANTING
PREHARVEST
FERTILIZER Operation
FERTILIZER EQUIP
FERTILIZER
Total PREHARVEST
PLANTING
HERBICIDE Operation
HERBICIDES
HERBICIDE
Total PREHARVEST
25.50
279.75
305.25
VARIABLE COST Description Labor
Interest - OC Equity
PICKUP -4WD
Fuel
Lube
R & M (Off-Farm)
FALLOW
MOLDBOARD Operation
CULTIVATE Operation
CULTIWEED Operation
FERTILIZE Operation
FERTILIZER
Total
Machinery
Materials Total
3.35
2.43
0.12
0.28
2.18
0.81
1.21
0.00
80.000
6.84
2.03
3.39
0.00
LB. x
0.00
0.00
0.00
17.60
0.220 =
9.02
2.84
4.60
17.60
17.60
34.06
2.47
0.75
73.700 LB.
x
0.36
0.39
8.48
0.115 =
0.00
11.69
8.47
0.75
12.44
0.00
0.00
1.000 ACRE x
30.000 lb. x
12.50
5.000 =
0.250 =
12.50
5.00
7.50
12.50
0.00
0.00
1.000 ACRE x
1.000 ACRE x
11.00
9.500 =
1.500 =
11.00
9.50
1.50
11.00
283
HARVESTING WHEAT
COMBINE
Operation
LOAD
Operation
1.65
1.27
4.76
2.75
Total HARVESTING WHEAT
MISCELLANEOUS
OTHER COSTS Operation 0.00
0.00
MACHINERY
1.000 ACRE x
ACCOUNTING COSTS
1.000 ACRE x
CROP INSURANCE
75.000 BU.
x
OTHER LABOR
1.000 ACRE x
0.00
0.00
10.42
17.00
1.000 =
5.000 =
0.080 =
5.000 =
Total MISCELLANEOUS
MARKETING WHEAT
MARKETING Operation
HANDLING
STORAGE
TRANSPORTATION
WHEAT COMMISSION
6.41
4.02
17.00
1.00
5.00
6.00
5.00
17.00
0.00
75.000
75.000
75.000
75.000
0.00
BU.
x
BU.
x
BU.
x
BU.
x
Total MARKETING WHEAT
38.25
0.120 =
0.120 =
0.240 =
0.030 =
38.25
9.00
9.00
18.00
2.25
38.25
Total VARIABLE COST
141.87
GROSS INCOME minus VARIABLE COST
163.38
FIXED COST Description
Unit
Total
Machinery and Equipment
Acre
34.23
Total FIXED Cost
34.23
Total of ALL Cost
176.11
NET PROJECTED RETURNS
129.15
284
Table (D.4b).
Economic Costs and Returns for Dryland
Fallow/Winter Wheat Production, Divided
Slope Practice Option MBW-DIV-F1W-Walla WaJla Soil.
GROSS INCOME Description
Quantity
DEFICIENCY PMT
WHEAT
75.000
75.000
WHEAT
Unit
$ / Unit
BU.
BU.
0.3400
3.7300
Total GROSS Income
Machinery
Materials Total
Interest - OC Equity
4.12
DIV STRP INSTALL Operation 0.43
FERT ILl Z ER
Total FALLOW
PLANTING
DRILL SEED Operation
WHEAT SEED
HAUL SEED Operation
1.21
0.00
FERTILI ZER
Total PREHARVEST
1.63
2.43
0.12
0.28
2.40
0.89
1.33
0.00
80.000
7.52
2.24
3.73
0.00
LB.
x
0.00
0.00
0.00
17.60
0.220 =
9.92
3.12
5.06
17.60
17.60
35.70
0.75
2.47
73.700 LB.
x
0.36
0.39
8 . 48
0.115 =
0.00
Total PLANTING
PREHARVEST
HERBICIDE
Operation
HERBICIDES
HERBICIDE
FERTILIZER Operation
FERTILIZER EQUIP
25.50
279.75
305.25
VARIABLE COST Description Labor
PICKUP -4WD
Fuel
Lube
R & M (Off-Farm)
FALLOW
MOLDBOARD
Operation
CULTIVATE
Operation
CULTIWEED
Operation
FERTILIZE
Operation
Total
11.69
8.47
0.75
12.44
0.00
2.000 ACRE x
2.000 ACRE x
0.00
0.00
0.00
1.000 ACRE x
0.000 lb. x
22.00
9.500 =
1.500 =
12.50
5.000 =
0.250 =
22.00
19.00
3.00
12.50
5.00
7.50
34.50
285
HARVESTING WHEAT
COMBINE
Operation
LOAD
Operation
1.65
1.27
4.76
2.75
0.00
0.00
6.41
4.02
Total HARVESTING WHEAT
10.42
MISCELLANEOUS
OTHER COSTS Operation 0.00
0.00
MACHINERY
1.000 ACRE x
ACCOUNTING COSTS
1.000 ACRE x
CROP INSURANCE
x
75.000 BU.
OTHER LABOR
1.000 ACRE x
17.00
1.000
5.000
0.080
5.000
=
=
=
=
17.00
1.00
5.00
6.00
5.00
Total MISCELLANEOUS
DIV COST INCREASE
DIV COST INCREASE
17.00
Total DIV COST INCREASE
10.59
MARKETING WHEAT
MARKETING Operation
HANDLING
STORAGE
TRANSPORTATION
WHEAT COMMISSION
10.59
0.00
75.000
75.000
75.000
75.000
0.00
BU. x
BU. x
BU.
x
BU.
x
Total MARKETING WHEAT
38.25
0.120
0.120
0.240
0.030
=
=
=
=
38.25
9.00
9.00
18.00
2.25
38.25
Total VARIABLE COST
167.51
GROSS INCOME minus VARIABLE COST
137.74
FIXED COST Description
Unit
Total
Machinery and Equipment
Acre
36.92
Total FIXED Cost
36.92
Total of ALL Cost
204.43
NET PROJECTED RETURNS
100.82
286
Table (D.4c):
Economic Costs and Returns for Dryland
Fallow/Winter Wheat Production, Strip Crop
Practice Option MBW-DIV-F1W--Walla Walla Soil
GROSS INCOME Description
DEFICIENCY PMT
WHEAT
WHEAT
Quantity
Unit
75.000
75.000
$ / Unit
0.3400
3.7300
BU.
BU.
Total GROSS Income
Machinery
Materials Total
Interest - OC Equity
4.42
1.72
3.41
PICKUP -4WD
Fuel
Lube
R & M (Off-Farm)
FALLOW
6.84
MOLDBOARD Operation 2.18
2.03
CULTIVATE Operation 0.81
3.39
CULTIWEED Operation 1.21
0.00
0.00
FERTILIZE Operation
80.000
LB.
x
FERTILIZER
Total FALLOW
PLANTING
2.47
DRILL SEED Operation 0.75
x
73.700 LB.
WHEAT SEED
0.36
0.39
HAUL SEED Operation
Total PLANTING
PREHARVEST
HERBICIDE Operation 0.00
2.000
HERBICIDES
2.000
HERBICIDE
FERTILIZER Operation 0.00
1.000
FERTILIZER EQUIP
30.000
FERTILIZER
Total PREHARVEST
25.50
279.75
305.25
VARIABLE COST Description Labor
STRIP INSTALL Operation
Total
0.00
5.13
2.43
0.12
0.28
0.00
0.00
0.00
17.60
0.220 =
9.02
2.84
4.60
17.60
17.60
34.06
8.48
0.115 =
0.00
11.69
8.47
0.75
12.44
0.00
ACRE x
ACRE x
000
ACRE x
lb.
x
22.00
9.500 =
1.500 =
12.50
5.000 =
0.250 =
22.00
19.00
3.00
12.50
5.00
7.50
34.50
287
HARVESTING WHEAT
Operation
COMBINE
LOAD
Operation
4.76
2.75
1.65
1.27
6.41
4.02
0.00
0.00
Total HARVESTING WHEAT
10.42
MISCELLANEOUS
OTHER COSTS Operation 0.00
0.00
MACHINERY
1.000 ACRE x
ACCOUNTING COSTS
1.000 ACRE x
75.000 BU.
x
CROP INSURANCE
OTHER LABOR
1.000 ACRE x
17.00
1.000
5.000
0.080
5.000
=
=
=
=
17.00
Total MISCELLANEOUS
MARKETING WHEAT
MARKETING Operation
HANDLING
STORAGE
TRANSPORTATION
WHEAT COMMISSION
17.00
1.00
5.00
6.00
5.00
0.00
0.00
75.000 BU.
x
75.000 BU. x
x
75.000 BU.
38.25
0.120 =
0.120 =
0.240 =
38.25
9.00
9.00
18.00
x
0.030 =
2.25
75.000 BU.
Total MARKETING WHEAT
38.25
PROD COST INCREASE
STRP COST INCREASE
29.28
Total PROD COST INCREASE
29.29
Total VARIABLE COST
188.36
GROSS INCOME minus VARIABLE COST
116.89
FIXED COST Description
Unit
Total
Machinery and Equipment
Acre
37.44
Total FIXED Cost
Total of ALL Cost
NET PROJECTED RETURNS
37.44
225.80
79.45
288
Table (D.4d):
Economic Costs and Returns for Dryland
Fallow/Spring Barley Production, Standard
Practice Option CHB-STD-F1B--Walla Walla Soil
GROSS INCOME Description
BARLEY
DEFICIENCY PMT
BARLEY
Quantity
83.000
83.000
Unit
BU.
BtJ.
$ / Unit
2.3100
0.1200
Total GROSS Income
VARIABLE COST Description Labor
Total
191.73
9.96
201.69
Machinery Materials Total
Interest - OC Equity
1.95
PICKUP -4WD
Fuel
Lube
R & M (Off-Farm)
FALLOW
CHISEL PLOWING
Operation
0.95
HERBICIDE
Operation
0.00
CUSTOM APPLIER
0.500 ACRE
0.500 ACRE
HERBICIDE AERIAL
SWEEP PLOWING
1.2].
Operation
0.40
CULTIVATE
Operation
1.61
CULTIWEED
Operation
Total FALLOW
PLANTING
DRILL BARLEY
Operation
0.75
BARLEY SEED
77.000 LB.
0.36
HAUL BARLEY SEED Operation
2.43
0.12
0.28
2.24
0.00
0.00
4.00
4.500 =
x
3.500 =
x
3.14
0.00
1.02
0.00
4.53
0.00
3.19
4.00
2.25
1.75
4.34
1.42
6.14
19.09
2.47
7.70
0.100 =
x
0.39
0.00
10.92
7.70
0.75
Total PLANTING
PREHARVEST
0.00
0.00
5.50
FERTILIZE BARLEY Operation
0.220 =
FERTILI ZER
25.000 LB. x
0.00 11.00
0.00
HERB I CIDE
Operation
9.500 =
1.000 ACRE x
HERB I C IDES
1.500 =
1.000 ACRE x
HERBICIDE
11.67
Total PREHARVEST
16.50
5.50
5.50
11.00
9.50
1.50
289
HARVESTING BARLEY
LOAD BARLEY
COMBINE BARLEY
Operation
Operation
1.27
1.65
2.75
4.76
Total HARVESTING BARLEY
0.00
0.00
4.02
6.41
10.42
MISCELLANEOUS
OTHER COSTS
Operation
0.00
CROP INSURANCE
83.000 BU.
OTHER LABOR
1.000 ACRE
ACCOUNTING COSTS
1.000 ACRE
MACHINERY BARLEY
1.000 ACRE
0.00
11.49 11.49
0.030 =
2.49
x
4.000 =
4.00
x
4.000 =
4.00
x
1.000 =
1.00
x
Total MISCELLANEOUS
11.49
MARKETING BARLEY
MARKETING BARLEY Operation
0.00
HANDLING BARLEY
83.000 BU.
STORAGE BARLEY
83.000 BU.
BARLEY COMMISSION
83.000 BU.
TRANSPORTATION
83.000 BU.
Total MARKETING BARLEY
0.00
32.37 32.37
0.090 =
7.47
x
0.080 =
6.64
x
0.020 =
1.66
x
0.200 =
16.60
x
32.37
Total VARIABLE COST
106.35
GROSS INCOME minus VARIABLE COST
95.34
FIXED COST Description
Unit
Total
Machinery and Equipment
Acre
32.67
Total FIXED Cost
Total of ALL Cost
NET PROJECTED RETURNS
32.67
139.01
62.68
290
Table (D.4e):
Economic Costs and Returns for Dryland
Fallow/spring Barley Production, Divided
Slope Practice Option CHB-DIV-F1B
Walla Walla Soil.
GROSS INCOME Description
BARLEY
DEFICIENCY PMT
BARLEY
Quantity
83.000
83.000
Unit
$ / Unit
Total
BU.
BU.
2.3100
0.1200
191.73
9.96
Total GROSS Income
VARIABLE COST Description
201.69
Labor Machinery
Materials Total
Interest - OC Equity
DIV STRP INSTALL Operation
2.50
0.39
1.10
0.00
PICKUP -4WD
Fuel
Lube
R & M (Off-Farm)
FALLOW
CHISEL PLOWING
Operation
0.95 2.24
0.00
8.00
HERBICIDE
Operation
0.00 0.00
1.000 ACRE x
4.500 =
CUSTOM APPLIER
HERBICIDE AERIAL
3.500 =
1.000 ACRE x
0.00
SWEEP PLOWING
Operation
1.21 3.14
0.00
CULTIVATE
Operation
0.65 1.21
0.00
CULTIWEED
Operation
1.61 4.53
1.49
2.43
0.12
0.28
3.19
8.00
4.50
3.50
4.34
1.86
6.14
Total FALLOW
PLANTING
7.70
DRILL BARLEY
Operation
0.75 2.47
0.100 =
BARLEY SEED
77.000 LB. x
0.00
HAUL BARLEY SEED Operation
0.36 0.39
23.53
Total PLANTING
PREHARVEST
0.00
FERTILIZE BARLEY Operation
25.000 LB.
FERTILIZER
0.00
HERBICIDE
Operation
1.200 ACRE
HERBICIDES
HERBICIDE
1.200 ACRE
11.67
Total PREHARVEST
0.00 5.50
0.220 =
x
0.00 13.20
9.500 =
x
1.500 =
x
10.92
7.70
0.75
5.50
5.50
13.20
11.40
1.80
18.70
291
HARVESTING BARLEY
LOAD BARLEY
COMBINE BARLEY
Operation
Operation
1.27
1.65
2.75
4.76
0.00
0.00
Total HARVESTING BARLEY
4.02
6.41
10.42
MISCELLANEOUS
OTHER COSTS
Operation
0.00
CROP INSURANCE
83.000 BU.
OTHER LABOR
1.000 ACRE
ACCOUNTING COSTS
1.000 ACRE
MACHINERY BARLEY
1.000 ACRE
0.00 11.49
0.030 =
x
x
x
x
4.000 =
4.000 =
1.000 =
Total MISCELLANEOUS
11.49
2.49
4.00
4.00
1.00
11.49
MARKETING BARLEY
MARKETING BARLEY Operation
0.00
HANDLING BARLEY
83.000 BU.
STORAGE BARLEY
83.000 BU.
BARLEY COMMISSION
83.000 BU.
TRANSPORTATION
83.000 BU.
0.00 32.37
0.090 =
0.080 =
x
0.020 =
x
0.200
x
x
32.37
7.47
6.64
1.66
16.60
Total MARKETING BARLEY
DIV COST INCREASE
DIV COST INCREASE
32.37
Total DIV COST INCREASE
10.41
10.41
125.43
Total VARIABLE COST
76.26
GROSS INCOME minus VARIABLE COST
FIXED COST Description
Unit
Total
Machinery and Equipment
Acre
33.99
Total FIXED Cost
Total of ALL Cost
NET PROJECTED RETURNS
33.99
159.42
42.27
292
Table (D.4f):
Economic Costs and Returns for Dryland
Fallow/spring Barley Production, Strip Crop
Practice Option CHB-STR-F1B-Walla Walla Soil.
GROSS INCOME Description
BARLEY
DEFICIENCY PMT
BARLEY
Quantity
Unit
$ / Unit
83.000
83.000
BU.
BU.
2.3100
0.1200
Total GROSS Income
Total
191.73
9.96
201.69
VARIABLE COST Description
Labor Machinery
Interest - OC Equity
STRIP INSTALL
Operation 1.57
3.10
Materials Total
0.00
PICKUP -4WD
Fuel
Lube
R & M (Off-Farm)
FALLOW
0.95 2.24 0.00
CHISEL PLOWING
Operation
0.00 0.00 8.00
HERBICIDE
Operation
4.500 =
1.000 ACRE x
CUSTOM APPLIER
3.500 =
1.000 ACRE x
HERBICIDE AERIAL
Operation
1.21 3.14 0.00
SWEEP PLOWING
0.00
0.40 1.02
CULTIVATE
Operation
1.61 4.53 0.00
CULTIWEED
Operation
2.90
4.66
2.43
0.12
0.28
3.19
8.00
4.50
3.50
4.34
1.42
6.14
Total FALLOW
PLANTING
0.75 2.47 7.70
Operation
DRILL BARLEY
0.100 =
77.000 LB.
x
BARLEY SEED
0.36 0.39 0.00
HAUL BARLEY SEED Operation
23.09
Total PLANTING
PREHARVEST
FERTILIZE BARLEY Operation
11.67
FERTILI ZER
HERBICIDE
HERBICIDES
HERBICIDE
Total PREHARVEST
0.00 0.00
x
25.000 LB.
0.00 0.00
Operation
1.500 ACRE x
1.500 ACRE x
5.50
0.220 =
16.50
9.500 =
1.500 =
10.92
7.70
0.75
5.50
5.50
16.50
14.25
2.25
22.00
293
HARVESTING BARLEY
LOAD BARLEY
COMBINE BARLEY
Operation
Operation
1.27
1.65
2.75
4.76
4.02
0.00
0.00
6.4].
Total HARVESTING BARLEY
10.42
MISCELLANEOUS
0.00 0.00
Operation
OTHER COSTS
x
.000
BU.
CROP INSURANCE
83
.000
ACRE
x
OTHER LABOR
1
1 .000 ACRE x
ACCOUNTING COSTS
MACHINERY BARLEY
1 .000 ACRE x
11.49
0.030
4.000
4.000
1.000
11.49
=
=
=
=
2 . 49
Total MISCELLANEOUS
MARKETING BARLEY
0.00 32.37
MARKETING BARLEY Operation
0. 00
0.090 =
83.000 BU.
x
HANDLING BARLEY
0.080 =
STORAGE BARLEY
83.000 BU. x
x
0.020 =
BARLEY COMMISSION
83.000 BU.
x
0.200 =
TRANSPORTATION
83.000 BU.
11.49
Total MARKETING BARLEY
STRP COST INCREASE
STRP COST INCREASE
32.37
Total STRP COST INCREASE
22.07
4.00
4.00
1.00
32.37
7.47
6.64
1.66
16.60
22.07
143 53
Total VARIABLE COST
GROSS INCOME minus VARIABLE COST
58.16
FIXED COST Description
Unit
Total
Machinery and Equipment
Acre
35.59
Total FIXED Cost
Total of ALL Cost
NET PROJECTED RETURNS
35.59
179.11
22.58