Agricultural Conservation
USDA Should Improve Its Process for Allocating Funds to States for the Environmental Quality Incentives Program Gao ID: GAO-06-969 September 22, 2006The Environmental Quality Incentives Program (EQIP) assists agricultural producers who install conservation practices, such as planting vegetation along streams and installing waste storage facilities, to address impairments to water, air, and soil caused by agriculture or to conserve water. EQIP is a voluntary program managed by the U.S. Department of Agriculture's (USDA) Natural Resources Conservation Service (NRCS). NRCS allocates about $1 billion in financial and technical assistance funds to states annually. About $650 million of the funds are allocated through a general financial assistance formula. As requested, GAO reviewed whether USDA's process for allocating EQIP funds to states is consistent with the program's purposes and whether USDA has developed outcome-based measures to monitor program performance. To address these issues, GAO, in part, examined the factors and weights in the general financial assistance formula
NRCS's process for providing EQIP funds to states is not clearly linked to the program's purpose of optimizing environmental benefits; as such, NRCS may not be directing funds to states with the most significant environmental concerns arising from agricultural production. To allocate most EQIP funds, NRCS uses a general financial assistance formula that consists of 31 factors, including such measures as acres of cropland, miles of impaired rivers and streams, and acres of specialty cropland. However, this formula has several weaknesses. In particular, while the 31 factors in the financial assistance formula and the weights associated with each factor give the formula an appearance of precision, NRCS does not have a specific, documented rationale for (1) why it included each factor in the formula, (2) how it assigns and adjusts the weight for each factor, and (3) how each factor contributes to accomplishing the program's purpose of optimizing environmental benefits. Factors and weights are important because a small adjustment can shift the amount of funding allocated to each state on the basis of that factor and, ultimately, the amount of money each state receives. For example, in 2006, a 1 percent increase in the weight of any factor would have resulted in $6.5 million more allocated on the basis of that factor and a reduction of 1 percent in money allocated for other factors. In addition to weaknesses in documenting the design of the formula, some data NRCS uses in the formula to make financial decisions are questionable or outdated. For example, the formula does not use the most recent data available for 6 of the 31 factors, including commercial fertilizers applied to cropland. As a result, any recent changes in a state's agricultural or environmental status are not reflected in the funding for these factors. During the course of GAO's review, NRCS announced plans to reassess its EQIP financial assistance formula. NRCS recently developed a set of long-term, outcome-based performance measures to assess changes to the environment resulting from EQIP practices. The agency is also in the process of developing computer models and other data collection methods that will allow it to assess these measures. Thus, over time, NRCS should ultimately have more complete information on which to gauge program performance and better direct EQIP funds to areas of the country that need the most improvement.
RecommendationsOur recommendations from this work are listed below with a Contact for more information. Status will change from "In process" to "Open," "Closed - implemented," or "Closed - not implemented" based on our follow up work.
Director: Team: Phone:GAO-06-969, Agricultural Conservation: USDA Should Improve Its Process for Allocating Funds to States for the Environmental Quality Incentives Program
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Report to the Ranking Democratic Member, Committee on Agriculture,
Nutrition, and Forestry, U.S. Senate:
September 2006:
Agricultural Conservation:
USDA Should Improve Its Process for Allocating Funds to States for the
Environmental Quality Incentives Program:
GAO-06-969:
GAO Highlights:
Highlights of GAO-06-969, a report to the Ranking Democratic Member,
Committee on Agriculture, Nutrition, and Forestry, U.S. Senate
Why GAO Did This Study:
The Environmental Quality Incentives Program (EQIP) assists
agricultural producers who install conservation practices, such as
planting vegetation along streams and installing waste storage
facilities, to address impairments to water, air, and soil caused by
agriculture or to conserve water. EQIP is a voluntary program managed
by the U.S. Department of Agriculture‘s (USDA) Natural Resources
Conservation Service (NRCS). NRCS allocates about $1 billion in
financial and technical assistance funds to states annually. About $650
million of the funds are allocated through a general financial
assistance formula.
As requested, GAO reviewed whether USDA‘s process for allocating EQIP
funds to states is consistent with the program‘s purposes and whether
USDA has developed outcome-based measures to monitor program
performance. To address these issues, GAO, in part, examined the
factors and weights in the general financial assistance formula.
What GAO Found:
NRCS‘s process for providing EQIP funds to states is not clearly linked
to the program‘s purpose of optimizing environmental benefits;
as such, NRCS may not be directing funds to states with the most
significant environmental concerns arising from agricultural
production. To allocate most EQIP funds, NRCS uses a general financial
assistance formula that consists of 31 factors, including such measures
as acres of cropland, miles of impaired rivers and streams, and acres
of specialty cropland. However, this formula has several weaknesses. In
particular, while the 31 factors in the financial assistance formula
and the weights associated with each factor give the formula an
appearance of precision, NRCS does not have a specific, documented
rationale for (1) why it included each factor in the formula, (2) how
it assigns and adjusts the weight for each factor, and (3) how each
factor contributes to accomplishing the program‘s purpose of optimizing
environmental benefits. Factors and weights are important because a
small adjustment can shift the amount of funding allocated to each
state on the basis of that factor and, ultimately, the amount of money
each state receives. For example, in 2006, a 1 percent increase in the
weight of any factor would have resulted in $6.5 million more allocated
on the basis of that factor and a reduction of 1 percent in money
allocated for other factors. In addition to weaknesses in documenting
the design of the formula, some data NRCS uses in the formula to make
financial decisions are questionable or outdated. For example, the
formula does not use the most recent data available for 6 of the 31
factors, including commercial fertilizers applied to cropland. As a
result, any recent changes in a state‘s agricultural or environmental
status are not reflected in the funding for these factors. During the
course of GAO‘s review, NRCS announced plans to reassess its EQIP
financial assistance formula.
NRCS recently developed a set of long-term, outcome-based performance
measures to assess changes to the environment resulting from EQIP
practices. The agency is also in the process of developing computer
models and other data collection methods that will allow it to assess
these measures. Thus, over time, NRCS should ultimately have more
complete information on which to gauge program performance and better
direct EQIP funds to areas of the country that need the most
improvement.
What GAO Recommends:
GAO recommends, among other things, that NRCS document its rationale
for the factors and weights in its general financial assistance formula
and use current and accurate data. USDA agreed with GAO that the
formula needed review. USDA did not agree with GAO‘s view that NRCS‘s
funding process does not clearly link to EQIP‘s purpose of optimizing
environmental benefits. It believes that the funding process clearly
links to EQIP‘s purpose, but it has not documented the link.
[Hyperlink, http://www.gao.gov/cgi-bin/getrpt?GAO-06-969].
To view the full product, including the scope and methodology, click on
the link above. For more information, contact Daniel Bertoni at (202)
512-3841 or bertonid@gao.gov.
[End of Section]
Contents:
Letter:
Results in Brief:
Background:
NRCS's Process for Allocating EQIP Funds to the States Does Not Clearly
Address the Program's Purpose of Optimizing Environmental Benefits:
NRCS Has Begun to Develop More Outcome-Oriented Performance Measures:
Conclusions:
Recommendations for Executive Action:
Agency Comments and Our Evaluation:
Appendixes:
Appendix I: Objectives, Scope, and Methodology:
Appendix II: EQIP 2006 Funding Allocation Formulas:
Appendix III: Statistical Techniques to Determine Influential Factors
in the 2006 EQIP Financial Allocation Formula:
Principal Components Regression:
Factor Analysis of EQIP Environmental Variables:
Appendix IV: Initial EQIP Funding Provided to the States, Fiscal Year
2006:
Appendix V: Historical EQIP Funding Levels, Fiscal Years 2001-2006:
Appendix VI: Fiscal Year 2005 EQIP Obligations by Conservation
Practice:
Appendix VII: Comments from the U. S. Department of Agriculture:
Appendix VIII: GAO Contact and Staff Acknowledgments:
Tables:
Table 1: Fiscal Year 2006 Categories of EQIP Funding:
Table 2: EQIP General Financial Assistance Formula Factors and Weights,
Fiscal Year 2006:
Table 3: EQIP Annual Performance Measures, Fiscal Year 2006:
Table 4: EQIP Long-term Measures:
Table 5: Factors, Data Sources, and Weights in the EQIP General
Financial Assistance Formula for Allocating Funding to the States in
Fiscal Year 2006:
Table 6: Fiscal Year 2006 Formula for Allocating Ground and Surface
Water Conservation Financial Assistance:
Table 7: Factors Used in the Fiscal Year 2006 Formula for Allocating
EQIP Performance Bonuses:
Table 8: Fiscal Year 2006 Formula for Allocating Klamath Basin Program
Financial Assistance:
Table 9: Standardized Principal Components Estimators of the Original
Variables and Statistical Significance:
Table 10: Rotated Factor Pattern Matrix:
Figure:
Figure 1: Initial EQIP Funding to States, Fiscal Year 2006:
Abbreviations:
CAFO: Concentrated Animal Feeding Operations:
EQIP: Environmental Quality Incentives Program:
NRCS: Natural Resources Conservation Service:
NRI: National Resources Inventory:
USDA: U.S. Department of Agriculture:
September 22, 2006:
The Honorable Tom Harkin:
Ranking Democratic Member:
Committee on Agriculture, Nutrition, and Forestry:
United States Senate:
Dear Senator Harkin:
Approximately two-thirds of the continental U.S.'s land area is used as
range, forest, crop, or pasture land. The production of food and fiber
on these lands contributes to the health of the U.S. population and the
strength of the nation's economy. If not properly managed, however,
agricultural production on these lands can damage the environment and
the nation's natural resources, as when routine agricultural activities
produce sediment, fertilizer runoff, and animal waste that can impair
the nation's waterways. Improper management of natural resources can
also reduce the productive capacity of agricultural land; for example,
excessive soil erosion may lead to soil lacking in nutrients.
Agriculture is also a major user of both groundwater and surface water,
contributing, in part, to water scarcity in the western United States.
Responsible production management practices can mitigate many of these
problems.
The Environmental Quality Incentives Program (EQIP) provides financial
and technical assistance to agricultural producers who enter into
contracts with the U.S. Department of Agriculture's (USDA) Natural
Resources Conservation Service (NRCS) to install conservation practices
on their land. A primary purpose of EQIP is to optimize the
environmental benefits achieved using program funds. Managed by NRCS,
EQIP is a voluntary program established in 1996 that currently provides
about $1 billion annually in cost-share and incentive payments to
farmers and ranchers in all 50 states, as well as U.S. territories,
whose production practices may put soil, water, air, and related
natural resources at risk for environmental damage.[Footnote 1] The
program provides funds to help implement conservation practices, such
as planting vegetation along rivers and streams--known as riparian
buffers--to prevent sediment and other materials from polluting the
waters, and constructing waste storage facilities to reduce the level
of nutrients from livestock production that enter neighboring bodies of
water. The Farm Security and Rural Investment Act of 2002 (the act)
reauthorized EQIP and increased annual authorized program funding from
about $200 million in 1997 to current levels of over $1
billion.[Footnote 2]
NRCS allocates the majority of EQIP funds through a general financial
assistance formula with 31 factors related to the availability of
natural resources and the presence of environmental concerns or
problems. NRCS assigns each of the formula's factors a weight that
determines the funds to be allocated to states based on that factor.
The agency also periodically modifies factor weights. Additional funds
are distributed using a second technical assistance formula that
considers ongoing and expected future conservation work, as well as
through a performance bonus formula designed to reward states for
optimizing environmental benefits and efficient program
management.[Footnote 3] States disburse EQIP funds to producers to
install conservation practices on their land.
As requested, we assessed the extent to which (1) USDA's process for
providing funds to the states is consistent with the program's purpose
of optimizing environmental benefits and (2) USDA has developed
measures to monitor program performance.
To address these issues, we reviewed relevant statutory provisions and
NRCS's regulations and guidelines for implementing EQIP and spoke with
officials in NRCS's national headquarters. To review NRCS's efforts to
allocate EQIP funding to the states, we analyzed documents accounting
for NRCS's disbursements of EQIP funds. We examined the factors and
weights in the formula for general financial assistance and discussed
the role of the data source for each factor in the formula with NRCS's
EQIP officials. We gathered comments from stakeholders about the
strengths and weaknesses of NRCS's EQIP funding approach, selecting
stakeholders from environmental and farm organizations to obtain a
broad set of views on the effectiveness of the formula in allocating
funds. To evaluate the extent to which NRCS has developed sufficient
outcome-based measures to monitor program performance, we spoke with
representatives from the NRCS teams responsible for strategic planning
and oversight activities and representatives from the EQIP program
team. We examined documentation of EQIP performance measures and
reviewed NRCS's Performance Results System.
A more detailed description of our objectives, scope and methodology is
presented in appendix I. We performed our work between December 2005
and August 2006 in accordance with generally accepted government
auditing standards.
Results in Brief:
NRCS's funding process is not clearly linked to EQIP's purpose of
optimizing environmental benefits; as such, NRCS may not be directing
EQIP funds to states with the most significant environmental concerns
arising from agricultural production. NRCS's general financial
assistance formula has several weaknesses that raise questions about
the formula's usefulness for effectively directing funds to states.
Specifically, while the 31 factors in the financial assistance formula,
and the weights associated with each factor, give the formula an
appearance of precision, NRCS does not have a specific, documented
rationale for why it included each factor in the formula or for how it
assigns and periodically adjusts factor weights. Factors and weights
are important for ensuring that funds are distributed to states to
address the nation's most significant environmental problems arising
from agriculture. Small adjustments in the weights of the factors can
shift the amount of funding directed at a particular resource concern
and, ultimately, the amount of money each state receives. For example,
in 2006, a 1 percent increase in the weight of any of the 31 factors
would have resulted in $6.5 million more allocated on the basis of that
factor at the expense of other factors. In addition, some data in the
EQIP financial assistance formula is questionable or outdated. First, 5
of the data sources--such as acres of nonirrigated cropland and federal
grazing land--were used in the formula more than once. Using the same
data for multiple factors may result in factors being indirectly
weighted more than intended and may make the formula less reliable for
allocating state funding. Second, NRCS could not identify the source of
the data used in 10 of the 31 factors in the formula, such as livestock
animal units and animal waste generation and, therefore, we could not
verify the accuracy of the data or the basis on which the agency was
allocating funding. Finally, the formula does not use the most current
data available for at least 6 of the 31 factors. For example, the
formula uses 1995 data to measure commercial fertilizer use on
cropland, but we identified 2005 data that would have made this factor
more current. Because it was not clear how NRCS originally calculated
this data, we could not quantify the effect of using more recent data.
However, using less recent data raises questions about whether the
formula allocates funds to areas of the country that currently have the
greatest environmental needs. When we brought our concerns to NRCS's
attention, officials agreed that the formula, including weights and
data sources, needed to be reviewed. NRCS subsequently announced plans
to issue a request for proposal soliciting comments and suggested
revisions to NRCS's formulas for allocating conservation funds,
including the EQIP financial assistance formula.
As part of its 2005 strategic planning effort, NRCS developed long-
term, outcome-based measures to assess changes to the environment
resulting from EQIP practices. NRCS has developed baselines for these
measures and plans to assess and report on them once computer models
and other data collection methods that estimate environmental change
are completed. In the meantime, NRCS will continue to use the results
of its existing annual measures to assess performance. As NRCS collects
additional data about its accomplishment of long-term performance
measures, it may ultimately have more complete information on which to
gauge program performance. Such information could help the agency
refine its process for allocating funds to the states via its financial
assistance formula by directing funds toward areas of the country that
need the most improvement.
We are making recommendations to the Secretary of Agriculture to better
align NRCS's process for allocating EQIP funds with the program's
stated purpose of optimizing environmental benefits. In particular, we
are recommending that NRCS ensures that its rationale for the factors
and weights is documented and linked to program priorities, its data
sources are accurate and current, and it uses information about long-
term program performance to ensure funds are directed to areas of the
highest priority. We provided USDA with a draft of this report for
review and comment. USDA agreed that the EQIP allocation formula needs
review. USDA did not agree with our assessment that NRCS's funding
process lacks a clear link to the program's purpose of optimizing
environmental benefits. The agency stated that its use of factors
related to the natural resource base and condition of those resources
shows the general financial assistance formula is tied to the program's
purpose of optimizing environmental benefits. USDA also stated that,
while some formula data sources and weights will be updated, the types
of factors used would be needed in any process that attempts to
inventory and optimize environmental benefits. While this may in fact
be the case, USDA needs to document this connection--that is, why
factors were chosen and weights assigned. USDA could make the
connection between the formula and the program's purpose of optimizing
environmental benefits more evident if it provided additional
information describing its reasons for including or excluding factors
in the formula and its rationale for assigning and modifying weights.
Background:
The U.S. agricultural sector benefits our economy and the health of our
nation. However, if not properly managed, agricultural activities can
impair the nation's water, air, and soil; disrupt habitat for
endangered species; and constrain groundwater resources. For example,
sediment produced during routine agricultural activities may run off
the land and reach surface waters, including rivers and lakes. Sediment
can destroy or degrade aquatic habitat and can further impair water
quality by transporting into area waters both the pesticides applied to
cropland and the nutrients found in fertilizers and animal
waste.[Footnote 4] These and other water quality issues are of concern
in a number of U.S. agriculture-producing regions, including the
Midwest and along the Mississippi River. Agriculture is also a major
user of groundwater and surface water, which has led to water resource
concerns across the country, particularly in the West. In 2000,
irrigation accounted for 65 percent of the nation's consumption of
fresh water. Agricultural production can also impair air quality, when
wind carries eroded soil, odors, and smoke, and may lead to the loss of
wetlands, which provide wildlife habitat, filter pollutants, retain
sediment, and moderate hydrologic extremes.
EQIP is one of a number of USDA conservation programs designed to
mitigate agriculture's potentially negative environmental effects. EQIP
provides cost-share funds and incentive payments for land used for
agricultural production and supports around 190 conservation practices,
including constructing facilities to temporarily store animal waste;
planting rows of trees or shrubs to reduce wind erosion and provide
food for wildlife; and planning the amount, form, placement, and timing
of the application of plant nutrients. EQIP is designed to fund
conservation practices in a manner that helps the program achieve the
following national priorities identified by NRCS:
* reducing nonpoint source pollution (nutrients, sediment, pesticides,
or excess salinity), groundwater contamination, and pollution from
point sources (such as concentrated animal feeding operations);
* conserving groundwater and surface water resources;
* reducing emissions that contribute to air quality impairment;
* reducing soil erosion from unacceptable levels on agricultural land;
and:
* promoting at-risk species habitat conservation.
The Federal Agriculture Improvement and Reform Act of 1996 created EQIP
by combining four existing conservation programs into a single
program.[Footnote 5] The Farm Security and Rural Investment Act of
2002, the farm bill, reauthorized EQIP and increased its authorized
funding from about $200 million in 1997 to current levels of over $1
billion.[Footnote 6] The 2002 act required that at least 60 percent of
EQIP funds be made available for conservation practices relating to
livestock production.[Footnote 7] In addition, it authorized EQIP funds
for specific conservation purposes--(1) funds for producers to install
water conservation practices to improve groundwater and surface water
conservation (the Ground and Surface Water Conservation component of
EQIP) and (2) funds for water conservation practices in the Klamath
Basin located on the California/Oregon border (the Klamath Basin
component of EQIP).[Footnote 8]
Annually, NRCS headquarters officials determine the amount of funding
each state receives, while state and local NRCS officials decide what
conservation practices to fund in their state and local communities.
The total amount of EQIP funding a state receives can be derived by
adding together that state's funding for all categories. Table 1
describes the different categories of funding that states received for
fiscal year 2006 and NRCS's process for allocating that funding.
Table 1: Fiscal Year 2006 Categories of EQIP Funding:
EQIP funding category: General financial assistance;
Funding purpose: Cost-share and incentive payments for installing
conservation practices;
Process for allocating funding: Funds are divided among states using a
31-factor formula that considers the presence of available natural
resources and environmental concerns in each state. Each factor is
assigned a weight, which determines the amount of money to be given to
states based on that factor;
Percentage of total funding: 65%.
EQIP funding category: General technical assistance;
Funding purpose: Funds for technical specialists' time. Among other
activities, specialists process EQIP administrative paperwork, advise
farmers about the installation of practices, and inspect installed
practices;
Process for allocating funding: Technical assistance dollars are
divided among states based on the number of ongoing EQIP contracts and
expected future technical specialist needs;
Percentage of total funding: 19.
EQIP funding category: Ground and Surface Water Conservation[A];
Funding purpose: Funds for conservation practices that improve
groundwater and surface water conservation. Practices must result in a
net savings of groundwater or surface water resources;
Process for allocating funding: Groundwater and surface water funds are
allocated to eight High Plains Aquifer states, nine western drought
states, and other states with agricultural water needs using a formula
based on groundwater, irrigation, and other agricultural water usage
factors;
Percentage of total funding: 7.
EQIP funding category: Performance incentive bonuses[A];
Funding purpose: Bonuses designed to reward states that achieve a high
level of program efficiency and optimize environmental benefits. States
can use bonuses as they do other EQIP financial and technical
assistance;
Process for allocating funding: Performance bonuses are divided among
states using a formula with seven factors;
Percentage of total funding: 4.
EQIP funding category: EQIP Colorado Salinity[A];
Funding purpose: Funds for salinity control measures in the Colorado
River Basin;
Process for allocating funding: Colorado Salinity dollars are divided
between Colorado, Utah, and Wyoming based on the amount of land in each
state needing salinity control treatment;
Percentage of total funding: 2.
EQIP funding category: EQIP regional equity[A];
Funding purpose: Funds provided to states that receive less than $12
million from NRCS conservation programs (including EQIP) in a given
fiscal year.[B] States can use funds as they do other EQIP financial
and technical assistance;
Process for allocating funding: Regional equity funds are provided to
states that receive less than $12 million from NRCS conservation
programs (including EQIP) in a given fiscal year.[B] Headquarters
officials determine the amount of funds to be provided to each state
and from which program the funds will come;
Percentage of total funding: 2.
EQIP funding category: Klamath Basin[A];
Funding purpose: Funds to carry out water conservation activities in
the Klamath Basin in California and Oregon;
Process for allocating funding: Klamath Basin funding is split evenly
between California and Oregon;
Percentage of total funding: 1%.
Source: GAO analysis of NRCS documentation.
Note: EQIP funds are also provided to producers through Conservation
Innovation Grants, funds competitively awarded for the development and
adoption of innovative conservation approaches and technologies. In
fiscal year 2006, around $20 million in grants was approved by NRCS.
Conservation Innovation Grants are awarded through national and state
competitions to producers demonstrating innovative approaches to
conservation. Because the grant money for national competitions is not
provided to states along with their initial EQIP allocations, it is not
reflected in this table.
[A] NRCS provides these funds to the states through both financial and
technical assistance; the majority of the assistance is in the form of
financial assistance.
[B] In fiscal year 2006, the threshold was lowered administratively to
$11 million.
[End of table]
As the table shows, each category of EQIP funding is allocated to the
states using a different process. For the general financial assistance
formula, the availability of natural resources accounts for
approximately half of the funds allocated, and the presence of
environmental concerns or problems accounts for the remainder.[Footnote
9] Table 2 shows the factors and weights used in the financial
assistance formula for fiscal year 2006.
Table 2: EQIP General Financial Assistance Formula Factors and Weights,
Fiscal Year 2006:
Factor[A]: Acres of nonirrigated cropland;
Weight: 3.2.
Factor[A]: Acres of irrigated cropland;
Weight: 4.3.
Factor[A]: Acres of federal grazing lands;
Weight: 0.5.
Factor[A]: Acres of nonfederal grazing lands;
Weight: 4.3.
Factor[A]: Acres of forestlands;
Weight: 1.1.
Factor[A]: Acres of specialty cropland;
Weight: 3.2.
Factor[A]: Acres of wetlands and at-risk species habitat;
Weight: 4.6.
Factor[A]: Acres of bodies of water;
Weight: 3.2.
Factor[A]: Livestock animal units[B];
Weight: 5.8.
Factor[A]: Animal waste generation;
Weight: 5.8.
Factor[A]: Waste management capital cost;
Weight: 3.5.
Factor[A]: Acres of American Indian tribal lands;
Weight: 3.3.
Factor[A]: Number of limited resource producers;
Weight: 5.0.
Factor[A]: Acres of grazing land lost to conversion;
Weight: 0.8.
Factor[A]: Air quality nonattainment areas;
Weight: 1.4.
Factor[A]: Acres of pastureland needing treatment;
Weight: 5.5.
Factor[A]: Acres of cropland eroding above T[C];
Weight: 6.2.
Factor[A]: Acres of fair and poor rangeland;
Weight: 6.2.
Factor[A]: Acres of forestlands eroding above T[C];
Weight: 1.4.
Factor[A]: Acres of cropland and pastureland soils affected by saline
and/or sodic conditions[D];
Weight: 2.6.
Factor[A]: Miles of impaired rivers and streams;
Weight: 3.6.
Factor[A]: Potential for pesticide and nitrogen leaching;
Weight: 1.3.
Factor[A]: Potential for pesticide and nitrogen runoff;
Weight: 1.7.
Factor[A]: Ratio of livestock animal units to cropland;
Weight: 1.7.
Factor[A]: Number of concentrated animal feeding operations/animal
feeding operations[E];
Weight: 2.8.
Factor[A]: Ratio of commercial fertilizers to cropland;
Weight: 0.9.
Factor[A]: Wind erosion above T[C];
Weight: 4.2.
Factor[A]: Phosphorous runoff potential;
Weight: 3.9.
Factor[A]: Riparian areas;
Weight: 0.8.
Factor[A]: Carbon sequestration;
Weight: 3.6.
Factor[A]: Coastal zone land;
Weight: 3.6.
Source: NRCS.
[A] The factor names in this chart are NRCS terminology. In certain
cases, they may not represent what is actually being measured. For
example, the factor for acres of cropland and pastureland soils
affected by saline and/or sodic conditions only measures the presence
of salts on cropland and pastureland and does not include data on the
presence of sodium on these lands.
[B] Animal units are a standard way of quantifying livestock of
different types and sizes (e.g., cattle, dairy, poultry, etc.) One
animal unit is equivalent to 1,000 pounds of live animal weight.
[C] T is a term that refers to a tolerable rate of erosion. T is the
maximum rate of annual soil loss that will permit crop productivity to
be sustained economically and indefinitely on a given soil.
[D] Saline and sodic soils are soils that contain salts and sodium.
Excess amounts of salt and sodium in soils may adversely affect soil
quality and crop productivity.
[E] Animal feeding operations are facilities where animals are raised
in confined or semiconfined situations usually with feed brought to the
animals. When large enough or when in environmentally sensitive
locations, these facilities are designated as concentrated animal
feeding operations and become subject to regulatory requirements to
prevent point source pollution.
[End of table]
In fiscal year 2006, approximately $652 million was divided among the
states through the general financial assistance formula.[Footnote 10]
For example, according to the formula, EQIP funding for nonirrigated
cropland (accounting for 3.2 percent of financial assistance) totaled
$20.9 million. The state with the most acres of nonirrigated cropland
received $1.7 million of the funds associated with this factor, and the
state with the fewest acres of nonirrigated cropland received
approximately $1,100. A state's total allocation is composed of the
funds it receives for each of the 31 factors.
Although about 65 percent of EQIP funds are provided through the
general financial assistance formula, other categories of funding can
have a significant effect on the total amount of funds an individual
state receives. For example, 35 percent of Utah's fiscal year 2006
allocation was from general financial assistance. The largest category
of EQIP funds Utah received--38 percent--was Colorado Salinity funds.
Appendix II provides additional information on the 2006 funding
allocation formulas for general financial assistance, Ground and
Surface Water Conservation, performance incentive bonuses and Klamath
Basin funding categories.
Figure 1 shows the initial distribution of NRCS's fiscal year 2006 EQIP
allocations to the states in November 2005. States had to return any
unused funds by June 2006 for redistribution to states with a need for
additional funds. Appendix IV describes the amount of funding each
state initially received in fiscal year 2006.
Figure 1: Initial EQIP Funding to States, Fiscal Year 2006:
[See PDF for image] - graphic text:
Source: Art Explosion (map); GAO analysis of NRCS documentation.
[End of figure] - graphic text:
NRCS's Process for Allocating EQIP Funds to the States Does Not Clearly
Address the Program's Purpose of Optimizing Environmental Benefits:
NRCS's process for providing EQIP funds to the states is not clearly
linked to the program's purpose of optimizing environmental benefits.
In particular, NRCS's general financial assistance formula, which
accounts for approximately two-thirds of funding provided to the
states, does not have a specific, documented rationale for each of the
formula's factors and weights. In addition, the financial assistance
formula relies on some questionable and outdated data. As a result,
NRCS may not be directing EQIP funds to states with the most
significant environmental concerns arising from agricultural
production.
NRCS Does Not Have A Specific, Documented Rationale for Formula Factors
and Weights:
Although the 31 factors and weights used in the general financial
assistance formula give it an appearance of precision, NRCS does not
have a clearly documented rationale for including each factor in the
formula and assigning or modifying each weight. The original EQIP
formula was created in 1997 by an interagency task force that modified
the formula created for a different conservation program--the
Conservation Technical Assistance Program.[Footnote 11] The task force
added and deleted factors and adjusted factor weights so that the EQIP
formula better corresponded to the Federal Agriculture Improvement and
Reform Act of 1996's requirement that 50 percent of funds be targeted
at funding livestock-related practices.
Since the creation of the financial assistance formula, NRCS has
periodically modified factors and weights to emphasize different
program elements and national priorities, most recently in fiscal year
2004 following the passage of the 2002 Farm Security and Rural
Investment Act. Furthermore, NRCS officials stated that they meet
annually to review the allocation of funds to states. However,
throughout this process, NRCS has not documented the basis for its
decisions to modify factors and weights or documented how changes to
its formula achieve the program's purpose of optimizing environmental
benefits. Thus, it is not always clear whether the formula factors and
weights guide funds to the states as effectively as possible. For
example, it is unclear why NRCS includes a factor in the formula that
addresses the waste management costs of small animal feeding operations
but not a factor that addresses such costs for large operations--large
operations can also damage the environment and are eligible for EQIP
funding.[Footnote 12] By not including the costs of the larger
operations in its financial assistance formula, some states may not be
receiving funds to address their specific environmental concerns. In
addition, NRCS has not demonstrated that it has the most appropriate
water quality factors in its formula. For example, the formula includes
a factor addressing river and stream impairment but no factor for
impaired lakes and other bodies of water. Moreover, it is not certain
whether the impaired rivers and streams factor results in funds being
awarded on the basis of general water quality concerns or water
pollution specifically caused by agricultural production. As a result,
it was not certain whether the formula allocates funds as effectively
as possible to states with water quality concerns arising from
agricultural production.
While the factors in the EQIP general financial assistance formula
determine what resource and environmental characteristics are
considered when allocating funds, the weights associated with these
factors directly affect how much total funding is provided for each
factor and, thus, the amount of money each state receives. Factors and
weights are key to ensuring states with the greatest environmental
problems receive funding to address these problems. Small differences
in the weights of the factors can shift the amount of financial
assistance directed at a particular resource concern and, ultimately,
the amount of money provided to a state. In 2006, if the weight of any
of the 31 factors had increased by 1 percent, $6.5 million would have
been allocated on the basis of that factor at the expense of one or
more other factors. Such a shift could impact the amount of financial
assistance received by each state. For example, a 1 percent increase in
the weight of the specialty cropland factor with a corresponding
decrease of 1 percent in the American Indian tribal land factor could
result in large changes to the distribution of EQIP general financial
assistance. According to our analysis, the state benefiting the most
from such a change would receive $2.6 million more (a 7.2 percent
increase in that state's level of general financial assistance) and the
state benefiting least from such a change would lose $2.7 million (a
13.5 percent decrease in that state's level of general financial
assistance). The potential for the weights to significantly affect the
amount of funding a state receives underscores the importance of having
a well-founded rationale for assigning them. To date, NRCS has not
documented its rationale for choosing the weights.
Some stakeholders we spoke with questioned NRCS's assignment of weights
to certain factors in the financial assistance formula because they did
not believe NRCS's formula adequately reflected the states'
environmental priorities. For example, NRCS's general financial
assistance formula allocates 6.3 percent of EQIP funds to the states
based on factors specifically associated with animal feeding
operations.[Footnote 13] However, states spent more of their EQIP
financial assistance on related practices, which suggests that the
weights in the financial assistance formula may not reflect states'
priorities. In fiscal year 2005, states spent a total of 11 percent of
EQIP financial assistance, or $91.1 million, on one such practice--the
construction of waste storage facilities for animal feeding operations.
(App. VI outlines the practices funded in fiscal year 2005, including
other practices to control pollution from animal feeding operations.)
More generally, other stakeholders said that, as the program develops,
NRCS should give additional weight to factors related to the presence
of environmental concerns in a state and place less emphasis on factors
related to natural resources in a state. They believed this
reassignment of weights would better ensure that states contending with
the most significant environmental problems receive the most funding.
Currently, factors related to the presence of environmental concerns
account for approximately half of the total funding, while factors
relating to the availability of natural resources account for the
remainder. Factors related to the availability of natural resources
provide states that have significant amounts of a particular type of
land--such as grazing land or cropland--with more funds, regardless of
whether that land is impaired.
Although NRCS has stated that it meets annually to review its
allocation of funds to states, officials told us they had not conducted
any statistical analysis to examine the influence of factors on funding
outcomes. Statistical analyses can provide information on how the
factors in the allocation formula have affected the distribution of
funds, thereby providing information to improve program
implementation.[Footnote 14] To better understand the effect of the
factors on the allocations to states, we used two types of statistical
analysis to assess the effects of the EQIP financial assistance formula
on state funding: (1) regression analysis to show which factors are the
most influential in determining funding levels and (2) factor analysis
to understand how factors can be grouped and identified with program
priorities.
Our regression analysis for the fiscal year 2006 funding allocation
shows that the factors that were the most important in explaining the
distribution of general financial assistance to states were acres of
fair and poor rangeland, acres of nonfederal grazing lands, livestock
animal units, acres of irrigated cropland, acres of American Indian
tribal lands, and wind erosion above T. This analysis suggests that
regions of the country with these types of characteristics are more
likely to benefit from the current formula. On the other hand, a few
factors, such as acres of forestlands, potential for pesticide and
nitrogen leaching, and air quality nonattainment areas were not
significantly related to the allocation, indicating that they had
little or no impact on the formula.
Our factor analysis, which groups the data into a smaller number of
categories that actually drive the formula, found that the largest
grouping with the greatest amount of correlation, included acres of
nonfederal grazing land, acres of fair and poor rangeland, livestock
animal units, and wind erosion above T--all indicative of dryland
agriculture and livestock feeding and ranching. These results
correspond with those of our regression analysis and help to show how
the current national allocation formula prioritizes money to states. A
complete explanation of both analyses is included in appendix III.
Financial Assistance Formula Relies on Some Questionable and Outdated
Data:
Weaknesses in the financial assistance formula are compounded by NRCS's
use of questionable and outdated data. Accurate data are key to
ensuring that funds are distributed to states as intended. However, we
identified several methodological weaknesses in the data sources: (1)
data that were used more than once in the formula, (2) data sources
whose accuracy could not be verified, and (3) data that was not as
recent as possible.
First, 5 of the 29 data sources behind the factors in the financial
assistance formula were used more than once, potentially causing NRCS
to overemphasize some environmental concerns at the expense of others.
Specifically:
* NRCS uses the same data to estimate pesticide and nitrogen runoff and
phosphorous runoff in its formula. According to NRCS, because data
measuring the potential for phosphorous runoff were unavailable, it
substituted data measuring the potential for pesticide and nitrogen
runoff. The agency did so believing that similar characteristics cause
both types of runoff. However, an NRCS official responsible for
deriving the runoff and leaching indicators commented that the
substitution of one type of runoff data for another was problematic
because the mechanisms through which pesticides and nitrogen are
transported off-site to cause environmental problems are different from
those of phosphorous. A 2006 NRCS cropland report estimates that the
intensity of nitrogen and phosphorous losses may differ
geographically.[Footnote 15] For example, nitrogen dissolved in surface
water runoff in the upper Midwest accounts for 28 percent of the
national total, while phosphorous dissolved in surface water runoff in
the same region accounts for 45 percent of the national total. This
difference in the effect of these two pollutants in the same region
raises questions about the appropriateness of substituting one type of
data for the other. Until adequate data are available for a given
factor, it may not be appropriate to include that factor in the general
financial assistance formula.
* NRCS's formula uses nonirrigated cropland, federal grazing land,
nonfederal grazing land, and forestland once for estimating acreage and
then again for estimating carbon sequestration.[Footnote 16] According
to NRCS, the agency did not have good source data to measure potential
areas where management practices could improve levels of carbon
sequestration so it substituted these other data sources. While we
could not fully assess the soundness of NRCS's estimate of carbon
sequestration, some academic stakeholders we spoke with questioned
whether NRCS had estimated carbon sequestration as effectively as
possible and noted that alternate data sources were available. In
discussing these alternate sources with NRCS, the EQIP Manager said the
agency had not previously considered using these sources for the EQIP
formula, but that they could prove relevant.
Using the same data for multiple factors may result in factors being
indirectly weighted higher than intended. For example, the effective
weight of the pesticide nitrogen runoff factor is 5.6 percent--the sum
of the original pesticide nitrogen runoff weight (1.7 percent) and the
phosphorous runoff weight (3.9 percent). Using data created for one
factor for a second factor also makes the formula less transparent and
potentially less reliable for allocating state funding.
Second, NRCS could not confirm the source of data used in 10 factors in
the formula; as such, we could not determine the accuracy of the data,
verify how NRCS generated the data, or fully understand the basis on
which the agency allocates funding. Specifically, we could not confirm
the source of data for acres of federal grazing land, livestock animal
units, animal waste generation, acres of cropland eroding above T,
acres of forestlands eroding above T, ratio of animal units to
cropland, miles of impaired rivers and streams, ratio of commercial
fertilizers to cropland, riparian areas, and coastal zone
land.[Footnote 17] For example, we could not verify how data for the
livestock animal units and animal waste factors were generated, and
NRCS said it had not retained documentation of how the data for these
factors were calculated. As a result, it was uncertain whether NRCS had
chosen the most appropriate data as its basis for allocating funds to
states with pollution problems from livestock and animal waste or
whether the data were accurately calculated. EQIP officials told us
that, in most cases, the data sources had been chosen and incorporated
into the formula before they were involved with EQIP and that
documentation had not been kept to identify how data sources were used.
In addition, for one factor--the number of limited resource producers
in a state--we found that the data did not measure what its factor name
indicated. NRCS defines a limited resource producer as one who had, for
the last 2 years, (1) farm sales not more than $100,000 and (2) a
household income at or below the poverty level, or less than 50 percent
of the county median household income.[Footnote 18] However, the data
NRCS uses in the general financial assistance formula only captures
farms with low sales, which does not necessarily indicate whether
producers on those farms have limited means. As a result, NRCS may not
be directing funds to states having farmers with the most limited
resources. A description of each factor in the fiscal year 2006 general
financial assistance formula can be found in appendix II.
Third, NRCS does not use the most current data for six factors in the
formula--livestock animal units, animal waste generation, number of
limited resource producers, miles of impaired rivers and streams, ratio
of livestock animal units to cropland, and ratio of commercial
fertilizers to cropland.[Footnote 19] According to NRCS, the source of
data on the ratio of commercial fertilizers to cropland was a 1995
report by the Association of American Plant Food Control Officials;
we found a 2005 version of the same report with more current data. In
other cases, we identified more current, alternate sources of data. For
example, the formula currently uses 1996 EPA data for its waste
management capital cost factor but could use 2003 NRCS data that
estimates waste management costs.[Footnote 20] Not using recent data
raises questions about whether the formula allocates funds to areas of
the country that currently have the greatest environmental needs,
because recent changes in a state's agricultural or environmental
status may not be reflected. According to our analysis, by using more
current data for the number of limited resource producers factor, one
state would have received approximately $151,000 more in fiscal year
2006 (a 0.2 percent increase in that state's general financial
assistance), and another state would have received approximately
$138,000 less (a 1.3 percent decrease in that state's general financial
assistance).[Footnote 21] Because we were unable to determine how NRCS
used the data for developing the remaining five factors, we could not
determine what impact using more current data for those factors would
have on financial assistance provided to states. According to NRCS, the
alternate sources we identified appeared to be acceptable for use in
the formula, and the agency is in the process of updating the formula's
livestock data.
In addition to these six factors, data used to measure acres of
riparian areas, fair and poor rangeland, and forestland eroding above T
are about 20 years old and will likely become more inappropriate over
time.
When we brought our concerns to NRCS's attention, officials agreed that
the formula, including weights and data sources, needed to be
reexamined. NRCS subsequently announced plans to issue a request for
proposal soliciting comments and suggested revisions to NRCS's formulas
for allocating conservation funds, including the EQIP financial
assistance formula. In addition, according to NRCS's EQIP Manager, the
agency is in the process of consolidating the data used in the
financial assistance formulas for its conservation programs into a
single database. As a part of this process, the agency plans to review
its data sources for the formula factors and update them with more
relevant and current data when possible.
NRCS Has Begun to Develop More Outcome-Oriented Performance Measures:
NRCS has recently begun to develop program-specific, long-term measures
to monitor EQIP's outcomes. In 2000, we reported that performance
measures tied to outcomes would better communicate the results NRCS
intended its conservation programs to achieve.[Footnote 22] As part of
its 2005 strategic planning effort, NRCS developed outcome-based, long-
term measures to assess changes to the environment resulting from the
installation of EQIP conservation practices.[Footnote 23] These
measures include such things as reduced sediment delivery from farms,
improved soil condition on working cropland, and increased water
conservation. Previously, in 2002, NRCS established annual measures
that primarily assess program outputs--the number and type of
conservation practices installed. Table 3 outlines NRCS's seven annual
performance measures for fiscal year 2006, and table 4 describes its
seven long-term EQIP performance measures approved in 2005.
Table 3: EQIP Annual Performance Measures, Fiscal Year 2006:
Performance measure: Comprehensive nutrient management plans applied;
Measure unit: Number of plans;
Progress as of September 1, 2006: 2,189;
Fiscal year target as of September 1, 2006[A]: 2,488.
Performance measure: Comprehensive nutrient management plans written;
Measure unit: Number of plans;
Progress as of September 1, 2006: 2,231;
Fiscal year target as of September 1, 2006[A]: 2,435.
Performance measure: Grazing land with conservation practices to
protect the resource base;
Measure unit: Acres;
Progress as of September 1, 2006: 11,640,329;
Fiscal year target as of September 1, 2006[A]: 10,454,337.
Performance measure: Improved irrigation efficiency;
Measure unit: Acre-feet;
Progress as of September 1, 2006: 641,158[B];
Fiscal year target as of September 1, 2006[A]: 543,204[C].
Performance measure: Nonfederal land managed to protect species with
declining populations;
Measure unit: Acres;
Progress as of September 1, 2006: 1,163,850;
Fiscal year target as of September 1, 2006[A]: 381,124.
Performance measure: Reduction of cropland soils damaged by erosion;
Measure unit: Acres;
Progress as of September 1, 2006: 1,345,101;
Fiscal year target as of September 1, 2006[A]: 1,360,622.
Performance measure: Soil erosion reduced;
Measure unit: Tons;
Progress as of September 1, 2006: 16,230,336;
Fiscal year target as of September 1, 2006[A]: 9,912,788.
Source: NRCS.
[A] According to NRCS, performance targets may change as additional
funds are provided to the states and as states return unused funds to
headquarters.
[B] This figure represents combined progress for EQIP, Ground and
Surface Water Conservation, and Klamath Basin.
[C] This figure represents a combined target for EQIP, Ground and
Surface Water Conservation, and Klamath Basin.
[End of table]
Table 4: EQIP Long-term Measures:
Performance measure: Improve soil condition on working cropland;
Measure unit: Millions of acres moved to a soil conditioning index
level > than 0.[A];
Baseline year: .5 in 2005;
Proposed target: 2.7 by 2010.
Performance measure: Reduce potential sediment delivery from
agricultural operations;
Measure unit: Million tons per year;
Baseline year: 2.4 in 2004;
Proposed target: 18.5 by 2010.
Performance measure: Reduce potential nitrogen delivery from
agriculture;
Measure unit: Tons;
Baseline year: 18,200 in 2005;
Proposed target: 100,000 by 2010.
Performance measure: Reduce potential phosphorus delivery from
agriculture;
Measure unit: Tons;
Baseline year: 2,700 in 2005;
Proposed target: 14,000 by 2010.
Performance measure: Increase water conservation;
Measure unit: Acre- feet;
Baseline year: 600,000 in 2005;
Proposed target: 4,200,000 by 2010.
Performance measure: Improve grassland condition, health, and
productivity;
Measure unit: Million acres;
Baseline year: 10.3 in 2005;
Proposed target: 52 by 2010.
Performance measure: Improve the quality of habitat for at-risk
species;
Measure unit: Million acres;
Baseline year: .45 million in 2005;
Proposed target: 2.4 by 2010.
Source: NRCS.
[A] The National Resources Inventory (NRI) includes data on soil type,
soil characteristics, and soil interpretations, in addition to
historical information on land use, management practices, and erosion.
These data, along with historical climate data, are being used to
assess soil quality by deriving a Soil Conditioning Index value for
each NRI sample site. This index quantifies the effects of cropping
sequences, tillage, and other management inputs on soil organic matter
content, which serves as an indicator of soil quality.
[End of table]
According to NRCS, it has developed baselines for its long-term,
outcome-based performance measures and plans to assess and report on
them once computer models and other data collection methods that
estimate environmental change are completed. The Director of the NRCS
Strategic Planning and Performance Division said NRCS expects to assess
and report on the status of all measures by 2010 but will be able to
assess the results of some measures, such as improved soil condition on
working land, sooner. In the meantime, the agency will continue to
utilize its existing annual measures to assess performance. The
Director of NRCS's Strategic Planning and Performance Division
acknowledged that the long-term measures were not as comprehensive as
needed but represented measures NRCS could reasonably assess using
modeling and data collection methods that would soon become available.
NRCS plans to continue to improve its performance measures going
forward.
Although we did not assess the comprehensiveness of the EQIP
performance measures, the additional information they provide about the
results of EQIP outcomes should allow NRCS to better gauge program
performance. Such information could also help the agency refine its
process for allocating funds to the states via its financial assistance
formula by directing funds toward practices that address unrealized
performance measures and areas of the country that need the most
improvement. The Chief of NRCS's Environmental Improvement Programs
Branch agreed that information about program performance might
eventually be linked back to the EQIP funding allocation process.
However, the agency does not yet have plans to do so.
Conclusions:
As a key NRCS conservation program with over $1 billion in annual
funding, EQIP was designed to help producers mitigate the potentially
negative environmental impacts of agricultural production. However, the
program may not be fully optimizing the environmental benefits
resulting from practices installed using EQIP dollars because of
weaknesses in NRCS's process for allocating funds to the states.
Moreover, outdated and duplicate formula data sources may further
compromise EQIP's effectiveness in allocating funds. Currently, it is
not clear that factors, weights, and data sources in the general
financial assistance formula help the agency direct funding to the
areas of the nation with the greatest environmental threats arising
from agricultural production. NRCS has an opportunity to address this
issue as it moves forward on its plans to reexamine its conservation
funding formulas. Furthermore, the agency may be able to use
information gathered from the results of its outcome-based performance
measures to refine the financial assistance formula, making it easier
for NRCS to direct EQIP funds at the most pressing environmental
problems related to agriculture production.
Recommendations for Executive Action:
To achieve EQIP's purpose of optimizing environmental benefits, we
recommend that the Secretary of Agriculture direct the Chief of the
Natural Resources Conservation Service to take the following two
actions:
* ensure that the rationale for the factors and weights used in the
general financial assistance formula are documented and linked to
program priorities, and data sources used in the formula are accurate
and current; and:
* continue to analyze current and newly developed long-term performance
measures for the EQIP program and use this information to make any
further revisions to the financial assistance formula to ensure funds
are directed to areas of highest priority.
Agency Comments and Our Evaluation:
We provided USDA with a draft of this report for review and comment.
USDA agreed that the EQIP allocation formula needs review. USDA did not
agree with our assessment that NRCS's funding process lacks a clear
link to the program's purpose of optimizing environmental benefits. The
agency stated that its use of factors related to the natural resource
base and condition of those resources shows the general financial
assistance formula is tied to the program's purpose of optimizing
environmental benefits. USDA stated that, while some formula data
sources and weights will be updated, the types of factors used would be
needed in any process that attempts to inventory and optimize
environmental benefits. While this may in fact be the case, USDA needs
to document this connection--that is, why factors were chosen and
weights assigned. USDA could make the connection between the formula
and the program's purpose of optimizing environmental benefits more
evident if it provided additional information describing its reasons
for including or excluding factors in the formula and its rationale for
assigning and modifying weights.
Appendix VII presents USDA's comments.
We are sending copies of this report to interested congressional
committees, the Secretary of Agriculture, the Director of the Office of
Management and Budget, and other interested parties. We also will make
copies available to others upon request. In addition, the report will
be available at no charge on the GAO Web site at [Hyperlink,
http://www.gao.gov].
If you or your staff have any questions about this report, please
contact me at (202) 512-3841 or bertonid@gao.gov. Contact points for
our Offices of Congressional Relations and of Public Affairs may be
found on the last page of this report. GAO staff who made major
contributions to this report are listed in appendix VIII.
Sincerely yours,
Signed by:
Daniel Bertoni:
Acting Director, Natural Resources and Environment:
[End of section]
Appendix I: Objectives, Scope, and Methodology:
At the request of the Ranking Democratic Member, Senate Committee on
Agriculture, Nutrition, and Forestry, we reviewed the extent to which
(1) the U.S. Department of Agriculture's (USDA) process for allocating
Environmental Quality Incentives Program (EQIP) funds to states is
consistent with the program's purpose of optimizing environmental
benefits and (2) USDA has developed measures to monitor program
performance.
To review the Natural Resources Conservation Service's (NRCS) process
for allocating EQIP funding to the states, we examined EQIP funding
documents and spoke with NRCS officials from the Financial Assistance
Program Division, Budget Planning and Analysis Division, and Financial
Management Division. Our analysis considered each of the different
categories of EQIP funding, including EQIP general financial
assistance, EQIP technical assistance, regional equity funds,
performance bonuses, Conservation Innovation Grants, Colorado Salinity
funds, Ground and Surface Water Conservation funds, and Klamath Basin
funds. We gathered comments from stakeholders about the strengths and
weaknesses of NRCS's EQIP funding approach. We selected stakeholders
from environmental and farm organizations to get a broad set of views
on the effectiveness of the formula in allocating funds. Specifically,
we spoke with representatives from environmental organizations,
including Environmental Defense, the National Association of
Conservation Districts, the Soil and Water Conservation Society, and
the Sustainable Agriculture Coalition, as well as farm organizations,
including the American Farm Bureau and the National Pork Producers
Council. We also discussed the EQIP funding allocation process with
selected participants on state technical committees--the Iowa
Department of Natural Resources, Iowa Farm Bureau, and Nebraska
Department of Environmental Quality; academic stakeholders; and former
NRCS employees who participated in the development of the original
formula.[Footnote 24] We examined the factors and weights in the
financial assistance formula and discussed their purpose with EQIP
program officials. We performed statistical analysis of the financial
assistance formula to determine what impact the different factors had
on overall funding. A discussion of the analysis we performed can be
found in appendix III. We searched for information about the source of
data for each factor in the formula in order to formulate an
understanding of what each factor measured and verify the accuracy of
the data being used by NRCS. NRCS did not retain documentation of the
source data for 10 factors and, as a result, we were unable to verify
all data used in the financial assistance formula. To estimate the
number of factors using outdated data, we searched for more updated
versions of the same data sources NRCS said it used in its formula. We
did not include more updated, but different, sources of data in our
count.
To understand Congress's and NRCS's goals for EQIP, we reviewed the
Federal Agriculture Improvement and Reform Act of 1996, Farm Security
and Rural Investment Act of 2002, associated regulations, and related
appropriations laws. We reviewed program documentation describing the
purpose and priorities of EQIP and discussed the documentation with
EQIP officials. To understand agency conservation priorities, we
analyzed a 2005 database of conservation practices funded using EQIP,
Ground and Surface Water Conservation, and Klamath Basin funds.
To determine how the factors and weights in the formula aligned with
resource concerns across the nation, we conducted research on the
impact agricultural production has on the environment. We spoke with
NRCS officials from selected states--Iowa, Maryland, Mississippi,
Missouri, Montana, Nebraska, New Mexico, Rhode Island, and Texas--to
better understand resource concerns important to their state and how
they used funds received from headquarters to address those concerns.
We also spoke with officials from three county offices within these
states. This geographically diverse group included states that received
varying amounts of EQIP funding and engaged in a range of types of
agricultural production.
To review what measures are in place to monitor EQIP program
performance, we spoke with representatives from the NRCS teams
responsible for strategic planning and oversight activities--the
Operations Management and Oversight Division, Oversight and Evaluation
staff, and Strategic and Performance Planning Division--and
representatives from the Financial Assistance Program Division. We
examined agency strategic planning and performance documents. We
reviewed documentation of agency and EQIP goals and performance
measures and reviewed the Web-based NRCS Performance Results
System.[Footnote 25] We also spoke with representatives from NRCS and
nongovernmental organizations working on the Conservation Effects
Assessment Project and reviewed related documentation to determine how
that initiative might influence the development of future EQIP goals.
Our analysis did not include an independent verification of NRCS's
compliance with internal controls.[Footnote 26]
We performed our work between December 2005 and August 2006 in
accordance with generally accepted government auditing standards.
[End of section]
Appendix II: EQIP 2006 Funding Allocation Formulas:
Tables 5, 6, 7, and 8, respectively, describe the formulas for
allocating general financial assistance, Ground and Surface Water
Conservation funds, performance bonuses, and Klamath Basin funds. In
the case of the general financial assistance formula, we have
identified the source of data for each factor and described what each
factor measures.
Table 5: Factors, Data Sources, and Weights in the EQIP General
Financial Assistance Formula for Allocating Funding to the States in
Fiscal Year 2006:
Factor: Acres of nonirrigated cropland;
Source: 1997 National Resources Inventory (Revised December 2000);
Description: Nonirrigated cultivated and noncultivated cropland acres;
Weight: 3.2%.
Factor: Acres of irrigated cropland;
Source: 1997 National Resources Inventory (Revised December 2000);
Description: Irrigated cultivated and noncultivated cropland acres;
Weight: 4.3.
Factor: Acres of federal grazing lands;
Source: [A];
Description: [B];
Weight: 0.5.
Factor: Acres of nonfederal grazing lands;
Source: 1997 National Resources Inventory (Revised December 2000);
Description: Nonfederal, rural acres of pastureland, rangeland, and
grazed forestland;
Weight: 4.3.
Factor: Acres of forestlands;
Source: 1997 National Resources Inventory (Revised December 2000);
Description: Nonfederal, rural acres of forestland;
Weight: 1.1.
Factor: Acres of specialty cropland;
Source: 1997 National Resources Inventory (Revised December 2000);
Description: Acres of land used as vineyards or to grow fruits, nuts,
berries, bush fruit, or other specialty crops;
Weight: 3.2.
Factor: Acres of wetlands and at-risk species habitat;
Source: 1997 National Resources Inventory (Revised December 2000);
Description: Acres of wetlands and deepwater habitats on water areas
and nonfederal land;
Weight: 4.6.
Factor: Acres of bodies of water;
Source: 1997 National Resources Inventory (Revised December 2000);
Description: Surface area (in acres) of water areas;
Weight: 3.2.
Factor: Livestock animal units;
Source: 1997 NRCS calculation based on data gathered prior to 1997
(exact year unknown)[C];
Description: [B];
Weight: 5.8.
Factor: Animal waste generation;
Source: NRCS calculation based on 1987 Census of Agriculture and other
data[C];
Description: [B];
Weight: 5.8.
Factor: Waste management capital cost;
Source: 1996 Environmental Protection Agency Clean Water Needs Survey
Report to Congress;
Description: Modeled estimates of state needs for controlling nonpoint
source pollution from confined animal facilities with fewer than 1,000
animal units;
Weight: 3.5.
Factor: Acres of American Indian tribal lands;
Source: 1997 Bureau of Indian Affairs data;
Description: Acres of American Indian reservations and Tribal Trust
Land;
Weight: 3.3.
Factor: Number of limited resource producers;
Source: 1997 Census of Agriculture;
Description: Number of farms with sales under $100,000;
Weight: 5.0.
Factor: Acres of grazing land lost to conversion;
Source: 1997 National Resources Inventory (Revised December 2000);
Description: Acres of grazing and pastureland converted to another form
of land or development between 1982 and 1997;
Weight: 0.8.
Factor: Air quality nonattainment areas;
Source: NRCS analysis of 2005 Environmental Protection Agency air
quality data;
Description: Measure of air quality nonattainment based on the percent
of a state affected by certain air quality pollutants and the number of
air quality standards not met by that state;
Weight: 1.4.
Factor: Acres of pastureland needing treatment;
Source: 1992 National Resources Inventory;
Description: Acres of pastureland needing conservation treatment;
Weight: 5.5.
Factor: Acres of cropland eroding above T;
Source: 1992 National Resources Inventory[C];
Description: [D];
Weight: 6.2.
Factor: Acres of fair and poor rangeland;
Source: 1987 National Resources Inventory;
Description: Acres of rangeland in fair and poor condition;
Weight: 6.2.
Factor: Acres of forestlands eroding above T;
Source: 1987 National Resources Inventory[E];
Description: [F];
Weight: 1.4.
Factor: Acres of cropland and pastureland soils affected by saline and/
or sodic conditions;
Source: 1997 National Resources Inventory (Revised December 2000);
Description: Acres of cultivated and noncultivated cropland and
pastureland with the presence of salts;
Weight: 2.6.
Factor: Miles of impaired rivers and streams;
Source: Environmental Protection Agency 1994 National Water Quality
Inventory[C];
Description: [B];
Weight: 3.6.
Factor: Potential for pesticide and nitrogen leaching;
Source: 1997 NRCS analysis[G];
Description: NRCS formula based on data about land vulnerability to
manure nitrogen, commercial nitrogen, and pesticide leaching;
Weight: 1.3.
Factor: Potential for pesticide and nitrogen runoff;
Source: 1997 NRCS analysis[G];
Description: NRCS formula based on data about land vulnerability to
manure nitrogen, commercial nitrogen, and pesticide runoff;
Weight: 1.7.
Factor: Ratio of livestock animal units to cropland;
Source: [A];
Description: [B];
Weight: 1.7.
Factor: Number of concentrated animal feeding operations/animal feeding
operations;
Source: 2003 NRCS report based on 1997 Census of Agriculture data[H];
Description: Number of farms needing a comprehensive nutrient
management plan;
Weight: 2.8.
Factor: Ratio of commercial fertilizers to cropland;
Source: NRCS calculation based on 1995 data from the Association of
American Plant Food Control Officials and 1997 NRI cropland data[C];
Description: [B];
Weight: 0.9.
Factor: Wind erosion above T;
Source: 1997 National Resources Inventory (Revised December 2000);
Description: Cultivated and noncultivated cropland with a 4-year
average rate of estimated soil loss due to wind erosion greater than T--
a tolerable rate of erosion above which soil productivity is believed
to decrease;
Weight: 4.2.
Factor: Phosphorous runoff potential;
Source: 1997 NRCS analysis[G];
Description: Same data used for factor measuring potential for
pesticide and nitrogen runoff;
Weight: 3.9.
Factor: Riparian areas;
Source: 1982 National Resources Inventory[C];
Description: [I];
Weight: 0.8.
Factor: Carbon sequestration;
Source: 1997 National Resources Inventory (Revised December 2000) and
unknown data source;
Description: Sum of data from other factors in the financial assistance
formula-- nonirrigated cropland, federal grazing lands, nonfederal
grazing lands and forestlands;
Weight: 3.6.
Factor: Coastal zone land;
Source: NRCS calculation based on 1992 National Oceanic and Atmospheric
Administration and unknown data[C];
Description: [J];
Weight: 3.6%.
Sources: GAO analysis of NRCS and USDA data.
Note: We used NRCS's own terminology for the factor names in this
chart. In some instances, names do not precisely capture what is being
measured.
AWe were unable to verify the source of data for this factor.
[B] Because we could not verify certain data sources, we were unable to
provide an accurate description of what each factor measured. Blank
cells indicate that we were unable to accurately describe what the
factor measured.
[C] Data source as reported by NRCS. We were unable to verify the
source of data for this factor.
[D] According to an NRI official, cropland eroding above T could have
been estimated in one of two ways--(1) acres of cropland where the
total wind, sheet and rill erosion rates exceeded T or (2) acres of
cropland where either wind erosion, sheet and rill erosion, or both,
exceeded T. We were not able to confirm how the data was estimated.
[E] NRCS could not confirm the source or date of this data. The
National Resources Inventory believed this data was from work NRI
performed in 1987.
[F] According to an NRI official, this factor measures acres of
nonfederal, rural forestland with estimated average annual sheet and
rill erosion above T. We were not able to obtain documentation to
confirm this definition.
[G] "Potential Priority Watersheds for Protection of Water Quality from
Nonpoint Sources Related to Agriculture." Poster Presentation at the
52nd Annual SWCS Conference Toronto, Ontario, Canada, July 22-25, 1997
(Revised October 7, 1997).
[H] Costs Associated with Development and Implementation of
Comprehensive Nutrient Management Plans Part I--Nutrient Management,
Land Treatment, Manure and Wastewater Handling and Storage, and
Recordkeeping (NRCS, June 2003).
[I] According to NRCS, the definition for riparian areas in the 1982
National Resources Inventory was acres of riparian areas--the banks,
shorelines, or edges of the rising ground bordering a natural or
manmade watercourse or water area (riparian areas are not limited to
natural areas).
[J] According to NRCS, this factor considers data on square miles of
coastlines.
[End of table]
Table 6: Fiscal Year 2006 Formula for Allocating Ground and Surface
Water Conservation Financial Assistance:
Targeted area: High Plains Aquifer states--Colorado, Kansas, Nebraska,
New Mexico, Oklahoma, South Dakota, Texas, and Wyoming; Allocation
methodology: Percentage of state's acreage in the High Plains Aquifer;
Weight: 40.6%.
Targeted area: Western drought states--Arizona, California, Idaho,
Montana, Nevada, North Dakota, Oregon, Utah, and Washington;
Allocation methodology: Amount of irrigated acreage in each state;
Weight: 41.5%.
Targeted area: Additional states with agricultural water needs--
Alabama, Arkansas, Delaware, Florida, Georgia, Hawaii, Iowa, Louisiana,
Maine, Minnesota, Mississippi, Missouri, North Carolina, Puerto Rico,
Wisconsin;
Allocation methodology: Proportional comparison of agriculture to
nonagricultural use of water;
Weight: 17.9%.
Source: NRCS.
[End of table]
Table 7: Factors Used in the Fiscal Year 2006 Formula for Allocating
EQIP Performance Bonuses:
Factor: Ratio of technical assistance obligations to total obligations;
Description: Ratio of obligated EQIP funds used for technical
assistance in fiscal year 2005 to total obligated funds;
Weight: 25%.
Factor: Livestock-related contracts;
Description: Ratio between the number of EQIP contracts issued for
Comprehensive Nutrient Management Plans to the number of farms needing
such plans[A];
Weight: 15.
Factor: Cost-share obligations versus payments;
Description: Ratio of cost-share dollars obligated to cost-share
dollars paid in fiscal years 2004 and 2005;
Weight: 15.
Factor: Technical service provider obligations and disbursements;
Description: Ratio of disbursements to obligations in fiscal years 2004
and 2005 to technical service providers--contractors that help
producers install practices;
Weight: 15.
Factor: Weighted cost-share percentage;
Description: Average cost- share rate by state, excluding limited
resource farmer cost-share and incentive payments;
Weight: 10.
Factor: Limited resource farmer;
Description: Percentage of total EQIP contracts entered into with
limited resource farmers;
Weight: 10.
Factor: Program national priorities;
Description: Ratio between acres treated with conservation practices
that address the national priorities to the total agricultural base;
Weight: 10%.
Source: NRCS.
[A] Comprehensive nutrient management plans are conservation plans
unique to livestock operations. These plans document practices and
strategies adopted by livestock operations to address natural resource
concerns related to manure and organic by-products and their potential
impacts on water quality.
[End of table]
Table 8: Fiscal Year 2006 Formula for Allocating Klamath Basin Program
Financial Assistance:
State: California;
Weight: 50%.
State: Oregon;
Weight: 50%.
Source: NRCS.
[End of table]
[End of section]
Appendix III: Statistical Techniques to Determine Influential Factors
in the 2006 EQIP Financial Allocation Formula:
Using statistical techniques--that is, principal components regression
and factor analysis--we analyzed the Environmental Quality Incentives
Program (EQIP) formula used to allocate fiscal year 2006 financial
assistance to the states to identify the environmental factors that
most influenced the allocations. Sixty-five percent of the total EQIP
funds for 2006 were based on the allocation formula for financial
assistance.
Principal Components Regression:
In order to determine the relationships between the allocation and the
environmental factors (variables), we typically would apply regression
techniques to a model, expressed as:
[See PDF for image/equation]
[End of figure]
In equation (1), the dependent variable is the funding allocation for
state i, the x's are the j factors in the allocation formula, b0,
b1,—,bj are the regression coefficients, and ei is the model error for
the iTH state.
When we used this model, however, standard regression techniques were
not possible because many of the environmental factors used in the
allocation formula were highly collinear.[Footnote 27] Collinearity
occurs when variables are so highly correlated that it is difficult to
distinguish their independent influences on the dependent variable--in
this case, state allocation funding. In a regression analysis, highly
correlated independent variables cause the following effects: (1)
regression coefficients change, depending on which variables are
included or excluded in the model, (2) standard errors are large, (3)
regression coefficients are large with random signs, and (4) achieving
statistical significance of the collinear parameters is difficult.
Moreover, multicollinearity poses a problem if the purpose of the model
is to estimate, or explain, rather than predict, the individual
contributions of variables. Following Fekedulegn et al., (2002), Norton
(1984), and others, we used principal components regression analysis
since this technique is recommended when there is multicollinearity in
the data.[Footnote 28]
Before running the regression analysis, we performed the principal
components analysis.[Footnote 29] This procedure generates a set of
latent variables, called principal components--uncorrelated linear
transformations of the original variables.[Footnote 30] At this stage,
even though the new variables are not collinear, the same magnitude of
variance is retained. Therefore, the elimination of small principal
components reduces the total variance and substantially improves the
diagnostic capability of the model. In order to eliminate these small
principal components, various selection procedures are used. Following
Fekedulegn (2002), we chose the cumulative eigenvalue product rule,
which keeps the first principal components whose combined product is
greater than 1.00 (Guiot et al., 1982).[Footnote 31] The principal
components themselves are expressed as:
(2) Z = X*V.
In equation (2), Z is an (i x j) matrix of principal components, X is
an (i x j) matrix of standardized environmental factors, and V is a (j
x j) matrix of eigenvectors.[Footnote 32],[Footnote 33]
After the principal components analysis and the elimination of smaller
principal components as described above, we used the data in a cross-
sectional multivariate regression expressed as:
(3) [See PDF for image/equation]
[End of figure]
In equation (3), A is an (i x 1) vector for the allocation of funding
for the states (the dependent variable in the regression), b01 is an (i
x 1) vector of the intercept terms, Z is an (i x j) matrix of principal
components, and a is a (j x 1) vector of new coefficients of the
principal components. However, this procedure will usually leave some
principal components that are not statistically significant. Therefore,
to further eliminate the nonsignificant principal components, we used
the SAS stepwise regression procedure.[Footnote 34] Specifically, we
eliminated "r" principal components in the analysis, which consisted of
the (1) number eliminated using the eigenvalue product rule and (2)
number eliminated from the stepwise regression. We were then left with
(j - r) principal components estimators or coefficients and the reduced
form in equation 3 becomes:
(4) [See PDF for image/equation]
[End of figure]
In equation (4), a is the vector of coefficients associated with the
reduced set of (j-r) principal components and Z is an (i x (j-r))
matrix of principal components. With the r components eliminated, the
principal components estimators--in terms of the standardized
environmental factors of the allocation model--are obtained by
multiplying the new vector of coefficients by the associated vectors in
the matrix of eigenvectors:
(5) [See PDF for image]
[End of figure]
In equation (5), bSpc (subscript pc stands for principal components) is
the vector of j standardized principal component estimators of the
regression coefficients of the environmental factors, V is the (j x (j
- r)) matrix of eigenvectors, and a is the reduced vector of ((j - r) x
1) estimated coefficients as in equation 4. Once we have the
standardized coefficients of the principal components estimators of the
factors, we can transform them back into the coefficients of the
original environmental factors. For the standardized estimators, the
method for this transformation is expressed as:
(6) [See PDF for image]
[End of figure]
In equation (6), Sxj is the standard deviation of the original jTH
environmental factor, xj, bSj,pc is the jTH standardized estimator, and
bj,pc is the coefficient of the original environmental factor.
While we can obtain the regression coefficients of the original
environmental factors (the bj,pc's) that have been corrected for
multicollinearity, we cannot directly compare them because most have
different units. For instance, some environmental and resource factors
used in the formula are measured in acres, while others may be measured
in terms of animal units. In other words, the largest coefficient may
not be the most influential in the regression. Therefore, when
comparing the relative importance of the factors (variables) in the
regression, we mainly discuss the standardized estimators of the
environmental factors used in the allocation formula.[Footnote 35]
Data Used:
For the 48 contiguous states, we used a cross-section of data for the
dependent variable--the allocation variable--and the independent
variables--the environmental variables (factors). We could not
incorporate Alaska or Hawaii because we lacked complete data. We
excluded two factors--independent variables--from the regression
analysis because they were linear combinations of factors already
included in the data. For instance, we could not include the carbon
sequestration factor because it is the sum of four factors already
included in the formula allocation model: acres of nonirrigated
cropland, forestland, federal grazing land, and nonfederal grazing
land. We also excluded the factor for pesticide and nitrogen runoff
because it contains the same data as the phosphorous runoff potential
factor. Although the U.S. Department of Agriculture (USDA) weights
these factors differently, they are still linear combinations and, for
regression analysis, must be excluded. In all, we ran the regression
using the 2006 state allocations for the 48 states as our dependent
variable and the 29 environmental and resource factors in the formula
for our independent variables.
Results:
After reducing the components from the eigenvalues product rule and the
stepwise regression, we were left with 13 principal components from the
original 29. We then transformed the parameter estimates of the
stepwise regression,, back into the coefficients of the standardized
principal components of the environmental factors, the bSpc. The
results for these standardized coefficients--bSpc, the t-values, and
the probability values of t--sorted by the size of the standardized
coefficient are shown in table 9. Specifically, a standardized
coefficient of a factor measures the expected change in the dependent
variable for a one unit change in the standardized independent
variable, in this case the iTH factor, all other things being equal.
Those variables that had the largest standardized coefficient as well
as being highly statistically significant were acres of fair and poor
rangeland, acres of nonfederal grazing land, acres of irrigated
cropland, acres of American Indian tribal lands, wind erosion above T,
and livestock animal units. As table 9 shows, as one would expect with
a formula, most of the factors in the regression were highly
significant and positively related to the allocation, except the four
factors, acres of forestlands, potential for pesticide and nitrogen
leaching, air quality nonattainment areas, and acres of federal grazing
lands.
Table 9: Standardized Principal Components Estimators of the Original
Variables and Statistical Significance:
Factor: Acres of fair and poor rangeland;
Standardized coefficient: 1399095;
t-value: 35.322;
p-value:
