United States Environmental Protection Agency
CBP/TRS 2/87
August 1987
Vegetated Filter Strips
for Agricultural
Runoff Treatment
esapeake
Bay
Program
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EPA
February 1987
VEGETATED FILTER STRIPS FOR AGRICULTURAL RUNOFF TREATMENT
William L. Magette
Russell B. Brinsfield
Robert E. Palmer
James D. Wood
Agricultural Engineering Dept.
The University of Maryland
College Park, MD 20742
and
Theo A. Dillaha
Agricultural Engineering Oept.
Raymond B. Reneau
Agronomy Dept.
Virginia Polytechnic Institute and State University
Blacksburg, VA 24061
Assistance No. X-003314-01
Project Officer
Joseph Macknis
Region III, Chesapeake Bay Laison Office
Annapolis, MD 21403
REGION -III
U.S. ENVIRONMENTAL PROTECTION AGENCY
PHILADEPHIA, PA 19107
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DISCLAIMER
The information in this document has been funded wholly or
in part by the United States Environmental Protection Agency
under Assistance No. -X—003314—Ol to The University of Maryland,
College Park. It has been subject to the Agency’s peer and
administrative review, and it has been approved for publication
as an EPA document. Mention of trade names or commercial
products does not constitute endorsement or recommendation for
use.
•11
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PREFACE
The U. S. Environmental Protection Agency’s Chesapeake Bay
Study identified nonpoint source contributions of pollutants from
agricultural and urban areas as partial reasons for water quality
deterioration in the bay and its tributaries. The study also
outlined a “framework for action” designed to help restore water
quality bay—wide to its once high level. In a spirit of
determined institutional cooperation, the State of Maryland, the
Commonwealths of Virginia and Pennsylvania, the District of
Columbia, and the Environmental Protection Agency joined in
implementing a variety of programs to reduce both point and
noripoint pollution of the bay.
In Maryland and Virginia, much support has been given to
protecting shoreline around the bay by vegetation, in an effort
to “buffer” sensitive receiving waters from the effects of man’s
activities. Grassed (or vegetated) buffer strips have been
promoted on the assumption that they could “filter” sediment and
nutrients from naturally occurring runoff, thereby preventing
entry of these pollutants into bay waters.
While this strategy seemed logical from a practical
standpoint, little information existed to document how well
actual vegetated filter strips (VFS) of limited width might
remove dissolved pollutants, primarily nitrogen, from
agricultural runoff. A key objective of this study was to
provide such documentation.
The Agricultural Engineering Departments at both The
University of Maryland, College Park and Virginia Polytechnic
Institute and State University, Blacksburg participated in the
study. This report, however, contains only results from the
University of Maryland experiments. Results from the Virginia
Tech portion of the study can be found in a separate EPA
publication.
111.
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ABSTRACT
Nine 0.01 ha (0.03 ac) runoff plots and artificially
created rainfall were utilized to evaluate the removal by
vegetated filter strips (VFS) of suspended solids, nitrogen, and
phosphorus from runoff leaving agricultural production areas.
Filters 4.6 m and 9.2 m (15 ft and 30 ft) wide (in the downslope
direction) received runoff from bare “source” 22 m long and 5.5 m
wide (72.6 ft by 18 ft). Nitrogen as a 30% urea—ammonium—nitrate
solution and as broiler litter was applied to the plots in
separate experiments.
The ability of VFS to reduce the amount of suspended solids,
nitrogen and phosphorus was highly variable and seemed to depend
especially on the extent to which runoff concentrated into
discrete channels through the vegetated filters. Channelization,
in turn, appeared to depend on both topographic features as well
as the quality of the stand of vegetation in the filters.
When data from all tests were averaged, mass losses of total
suspended solids, nitrogen and phosphorus from bare source areas
were reduced by 72%, 17%, and 41%, respectively, by 4.6 m (15 ft)
wide filters. TSS, N, and P reductions by 9.2 m (30 ft) wide VFS
were 86%, 51%, and 53% respectively. Percentage mass reductions
for individual storm events deviated widely from these averages,
however, prompting the conclusion that VFS of the size studied
should not be relied upon by themselves to reduce nutrients
transported in runoff from agricultural areas.
This report was submitted in fulfillment of Grant #X—0033l4—
01 by the Agricultural Engineering Department, University of
Maryland, College Park Campus under the partial sponsorship of
the U.S. Environmental Protection Agency. This report covers a
period from October 1, 1984 to May 31, 1986, and work was
completed as of February 23, 1987.
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CONTENTS
Preface . . . . . . . . . .
Ab St r act
Figures . . . . . . . . . . . . . .
Tables . . . . . . . . . . . . . .
Abbreviations and Symbols . . . .
Acknowledgments . . . . . . . . . .
1. Introduction . . . . . . .
2. Conclusions . . . . . . .
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3. Summary and Recommendations
4. Review of Literature . • • . •
Highlights of previous research
Summary and perspective •
5. Study Objectives
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S • • S S S
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6 . P r o c ed u r e s . . . . . • . . . . • . . •
Experimental design at Maryland .
Runoff plots . . . • . . . . .
Soils description • • • • . • .
Rainfall simulation • • • • • •
Nutrient additions • • • • • •
Plot preparation • • • • • • • •
Soil sampling • • .
Runoff measurement and sampling
Analytical procedures • . . . . . .
Total kjeldahl nitrogen • • • •
Ammonium nitrogen • • . • . • . .
Nitrate—nitrite nitrogen
Total phosphorus . • • • • • • • •
Ortho phosphorus • • • • . . • . .
Total suspended solids
Volatile suspended solids • • . •
Extractable soil inorganic nitrogen
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A. Soils description
B. Simulator performance, raw chemical data
VFS performance, test of VFS models
C. Pollutant reduction & nitrogen leaching
g r aph s
bare plots
• . . . .
• . . . .
• . . S •
• S S S S
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7. Results and Discussion . . . • . . •
Manure analysis
Simulator performance
Hydrologic response • . . . . . . . .
Expected performance . . . . . . .
Observed results
Surface losses of nutrients
General trends . . . .
Plots 4, 5, & 6 . . .
Plots 1, 2, 3, 7, 8, & 9
Suspended solids losses • . . . . . .
Relative surface losses from vegetated vs.
Subsurface losses of inorganic nitrogen
Combined surface and subsurface N losses
Mathematical modeling of VFS performance
Test of existing models . . . . . .
Development of linear model
Investigation of existing VFS . • . . .
8. References . . . . . . .
Appendices
• S S S • S S • S S S S
S • S S S S S S S S S S
• S S S •
• S S S S
S S S S S
S S S
S S S S
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FIGURES
Number Page
1 Site layout of University of Maryland
vegetated filter strip research plots,
Queenstown, MD . . . . . . . . . . . . . . . . . . . 11
2 Schematic diagram of one set of experimental
runoff plots showing relationship of VFS
to bare source areas and arrangement of
controlpiot 12
3 Schematic diagram of instrumentation used to
measure and sample runoff from runoff
plots . . . . . . . . . . . . . . . . . 16
C— 1 Mass losses of TP from Plot 1 (with 9.2 in
VFS) and Plot 2 (with 4.6 m VFS),
expressed as a percentage of Plot 3 (with
no VFS) losses 99
C— 2 Mass losses of TN from Plot 1 (with 9.2 in
VFS) and Plot 2 (with 4.6 m VFS),
expressed as a percentage of Plot 3 (with
no VFS) losses . . . . . . . . . . . . . . . . . . . 100
C— 3 Mass losses of TSS from Plot 1 (with 9.2 m
VFS) and Plot 2 (with 4.6 m VFS),
expressed as a percentage of Plot 3 (with
no VFS) losses . . . . . . . . . . . . . . . . . . . 101
C— 4 Mass losses of TP from Plot 4 (with 9.2 in
VFS) and Plot 5 (with 4.6 m VFS),
expressed as a percentage of Plot 6 (with
no VFS) losses 102
C— 5 Mass losses of TN from Plot 4 (with 9.2 in
VFS) and Plot 5 (with 4.6 in VFS),
expressed as a percentage of Plot 6 (with
no VFS) losses . . . . . . . . . . . . . 103
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Number Page
C— 6 Mass losses of TSS from Plot 4 (with 9.2 m
VFS) and Plot 5 (with 4.6 m VFS),
expressed as a percentage of Plot 6 (with
no VFS) losses . . . . . . . . . . . . . . . . . . . 104
C— 7 Mass losses of TP from Plot 7 (with 9.2 m
VFS) and Plot 8 (with 4.6 m VFS),
expressed as a percentage of Plot 9 (with
no VFS) losses . . . . . . . . . . . . . . . . . . . 105
C— 8 Mass losses of TN from Plot 7 (with 9.2 m
VFS) and Plot 8 (with 4.6 m VFS),
expressed as a percentage of Plot 9 (with
no VFS) losses . . . . . . . . . . . . . . . . . . . 106
C— 9 Mass losses of TSS from Plot 7 (with 9.2 m
VFS) and Plot 8 (with 4.6 m VFS),
expressed as a percentage of Plot 9 (with
no VFS) losses . . . . . . . . . . . . . . . . . . . 107
C—lO Comparison of aminonium—N in soil profile of
bare portion (Pre—B) and VFS (Pre—F) of
Plot 1 before (JAN tests and after (JAN
tests (Post—B and Post—F) 108
C—il Comparison of ammonium—N in soil profile of
bare portion (Pre—B) and VFS (Pre—F) of
Plot 2 before (JAN tests and after (JAN
tests (Post—B and Post—F) 109
C—12 Comparison of ammonium—N in soil profile of
Plot 3 before (JAN tests (Pre—B) and after
(JAN tests (Post—B) . . . . . . . . . . . . . . . . . 110
C—13 Comparison of ammonium—N in soil profile of
bare portion (Pre—B) and VFS (Pre—F) of
Plot 4 before (JAN tests and after (JAN
tests (Post—B and Post—F) 111
C—14 Comparison of ammonium—N in soil profile of
bare portion (Pre—B) and VFS (Pre—F) of
Plot 5 before (JAN tests and after (JAN
tests (Post—B and Post—F) 112
C—l5 Comparison of ammonium—N in soil profile of
Plot 6 before ( JAN tests (Pre—B) and after
(JAN tests (Post—B) . . . . . . . . . . . . . . . . . 113
viii
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Number Page
C—16 Comparison of ammonium—N in soil profile of
bare portion (Pre—B) and VFS (Pre—F) of
Plot 7 before UAN tests and after UAN
tests (Post—B and Post—F) . . . . . . . 114
C—17 Comparison of ammonium—N in soil profile of
bare portion (Pre—B) and VFS (Pre—F) of
Plot 8 before tIAN tests and after UAN
tests (Post—B and Post—F) . . . . . . . . . . . . . . 115
C—18 Comparison of amxnonium—N in soil profile of
Plot 9 before UAN tests (Pre—B) and after
UAN tests (Post—B) . . . . . . . . . . . 116
C—19 Comparison of nitrate—N in soil profile of
bare portion (Pre—B) and VFS (Pre—F) of
Plot 1 before JAN tests and after UAN
tests (Post—B and Post—F) . . . . . . . . . . . . . . 117
C—20 Comparison of nitrate—N in soil profile of
bare portion (Pre—B) and VFS (Pre—F) of
Plot 2 before (JAN tests and after (JAN
tests (Post—B and Post—F) . . . . . . 118
C—21 Comparison of nitrate—N in soil profile of
Plot 3 before (JAN tests (Pre—B) and after
(JAN tests (Post—B) 119
C—22 Comparison of nitrate—N in soil profile of
bare portion (Pre—B) and ‘IFS (Pre—F) of
Plot 4 before ( JAN tests and after (JAN
tests (Post—B and Post—F) . . . . . . . . . . . . . . 120
C—23 Comparison of nitrate—N in soil profile of
bare portion (Pre—B) and ‘IFS (Pre—F) of
Plot 5 before UAN tests and after UAN
tests (Post—B and Post—F) . . . . . . . . . . . . . . 121
C—24 Comparison of nitrate—N in soil profile of
Plot 6 before (JAN tests (Pre—B) and after
(JAN tests (Post—B) . . . . . . . . . . . 122
C—25 Comparison of nitrate—N in soil profile of
bare portion (Pre—B) and ‘IFS (Pre—F) of
Plot 7 before (JAN tests and after (JAN
tests (Post—B and Post—F) . . . . . . . 123
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Number Pane
C—26 Comparison of nitrate—N in soil profile of
bare portion (Pre—B) and VFS (Pre—F) of
Plot 8 before UAN tests and after UAN
tests (Post—B and Post—F) . . . . . . 124
C-27 Comparison of nitrate—N in soil profile of
Plot 9 before UAN tests (Pre—B) and after
UAN tests (Post—B) . . . . . . . . . . . . . . . . . 125
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TABLES
Number Page
1 Broiler litter analysis 19
2 Mass nitrogen application from broiler litter . . . . . 20
3 Rainfall simulator performance . . . . . . 21
4 Summarized runoff characteristics . . . . . . . . . . . 23
5 Surface runoff losses of nutrients and solids . . . . . 25
6 Relative nutrient and solids losses from VFS
plots . . . . . . . . . . . . . . . . . . . . . . . . 29
7 Mass losses of nutrients and solids in runoff . 30
8 Average percentage mass reductions (PMRs) in
bare plot losses achieved by VFS . . . . . . . . . . 31
9 Mass losses (areal basis) of nutrients and
solids in runoff . . . . 32
10 Mass changes in soil inorganic nitrogen . . . . 33
11 Combined N losses, runs 1—6 . . . . . . . . . . . . . . 34
B—i Rainfall simulator performance . . . . . . . . . . . . 44
B—2 Hydrologic response of runoff plots . . . . . . . . . . 48
B—3 Basic data — chemical analyses of runoff samples . . . 53
B—4 Calculated mass losses in runoff 71
B—5 Vegetated filter strip performance as a
percentage of bare plot losses 77
B—6 Basic and computed nitrogen leaching data . . . . . . . 78
5—7 Inorganic nitrogen leaching summary (totals
for 125 cm profile) 93
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Number Page
B—8 Predicted vs. observed pollutant reductions,
NCSU model . . . . . 94
B—9 Predicted vs. observed pollutant reductions,
USDA model . . . . . . 95
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LIST OF ABBREVIATIONS AND SYMBOLS
ABBREVIATIONS
ac —— acre
AVE —— average
BL —— broiler litter
cm —— centimeter
ft —— foot
gm —— gram
gms —— grams
ha —— hectare
in —— inch
INFILT —— infiltration
kg —— kilogram
kg/ha —— kilogram per hectare
kg/t —— kilogram per metric tonne
lb -— pound
lb/ac —— pound per acre
m — — meter
mm —— millimeter
mg/i —— milligram per litre
mm —— minute
PMR —— percentage mass reduction
Post—B —— after nutrient application in bare plot area
Post—F —— after nutrient application in vegetated filter
PPT —— precipitation
PR — — performance ratio
Pre—B — — before nutrient application in bare plot area
Pre—F — — before nutrient application in vegetated filter
RT — — rate
STD DEV — — standard deviation
SD — — standard deviation
t/ac — — ton per acre
t/ha — — metric tonne per hectare
Total N —— total nitrogen
Total P — — total phosphorus
TSS —— total suspended solids
UAN —— urea—ammonium—nitrate
VAR —- variance
VFS —— vegetated filter strip
xiii
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SYMBOLS
Cd —— cadmium
Cu -= copper
KC1 —— potassium chloride
K 2 0 —— potash
N —— nitrogen
NH 4 —N -— ammonium nitrogen
N0 3 —N —— nitrate nitrogen
P -- phosphorus
-- phosphate
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ACK NOWL EDGMENTS
The guidance, encouragement, and perseverence of Mr. Joseph
Macknis, Project Officer, was very helpful in the completion of
this project.
The support of the Maryland Agricultural Experiment Station,
and especially of the Department of Agricultural Engineering,
University of Maryland, College Park, is gratefully acknowledged.
Thanks are extended to the Department of Agricultural
Engineering, Virginia Tech, for the use of field equipment
employed in this study.
Special appreciation is owed the field and laboratory staff
who helped with this project and without whose assistance the
research would not have been possible. At the Wye Research and
Education Center, thanks are given to L. Smith, M. Sultenfuss, R.
Stafford, D. Poet, M. Newell, J. Wiltbank, and, for laboratory
analyses, to K. Morrissey and J. Metz. At Virgina Tech,
appreciation is due H. Castros, Agricultural Enigneering
Department, and H. Walker, Agronomy Department, for analyses of
runoff and soil samples, respectively. Gratitude is expressed to
M. Yaramanoglu for help with computer programming.
The authors also wish to thank the scientists who peer
reviewed the draft project manuscript, and took time to make
constructive criticsms toward improving the quality of the
document: Dr. Ray Daniels, Department of Soil Science, North
Carolina State University, Raleigh; Dr. Archie McDonnell,
Institute for Research on Land and Water Resources, Pennsylvania
State University, University Park; and Mr. Lynn Shuyler, EPA
Chesapeake Bay Laison Office, Annapolis.
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SECTION 1
I NTRODUCTI ON
The EPA Chesapeake Bay Study focused attention on nonpoint
source contributions of pollutants as one reason for the general
decline in water quality bay—wide. Agriculture is one nonpoint
source of pollutants (mainly sediment and agrochemicals).
Agricultural best management practices (BMPs) are used to control
these losses of pollutants. For agrochemicals, application at
recommended rates and times using the appropriate application
techniques is a very effective combination of management
practices that helps reduce the transport of these substances to
receiving waters.
Other structural, cultural and managerial techniques also
are used to control agricultural nonpoint source pollution. A
popular practice among these is the use of close—growing
vegetation around the perimeter of fields and animal operations
to “filter” pollutants from runoff leaving these areas. Although
the ability of such vegetated filter strips (VFS) to reduce
pollutant concentrations has been demonstrated by several
researchers, not enough is known about individual treatment
mechanisms to permit routine design of reliable filters.
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SECTION 2
CONCLUSI ONS
Conclusions from this study must be kept within the context
under which the research was conducted. This is to say that a
“worst case” scenario was created to examine the ability of
vegetated filter strips of limited widths (4.6 m and 9.2 m) to
remove suspended solids, nitrogen and phosphorus from
agricultural runoff. The experimental conditions thus
established were believed to be representative of “real world”
circumstances that would provide the most severe test of VFS
commonly used in the coastal plain of Maryland.
Based on an examination of nutrient losses in surface runoff
from plots with and without vegetated filter strips, the
following conclusions are drawn:
1. The performance of vegetated filter strips in reducing
nutrient losses from agricultural lands is highly variable.
2. vegetated filter strips are more effective in removing
suspended solids from runoff than in removing nutrients.
3. Removals of runoff—transported sediment (and perhaps
chemicals attached thereto) at the interface between VFS and
upslope areas may consitute a large percentage of the total
amount of sediment prevented from leaving areas protected by ‘IFS.
4. vegetated filter strips appear to be less effective as
time goes on in reducing nutrient and suspended solids losses in
runoff.
5. The performance of vegetated filter strips generally
diminishes as the ratio of vegetated to unvegetated area
decreases.
6. The effectiveness of vegetated filter strips is highly
dependent on the condition of the filter itself.
7. Subsurface (leaching) losses can be an important
component of inorganic nitrogen movement from agricultural areas.
When these losses are considered together with surface losses,
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the relationship between VFS width and nitrogen removal is not
clear.
8. Since the ability of VFS to remove nutrients and
suspended solids in this closely controlled experiment was so
highly variable, the performance of VFS in actual use is probably
much less than expected (although no performance criteria have
been established).
9. vegetated filter strips should not be relied upon as the
sole, or even primary means of preventing nutrient movement from
agricultural management systems.
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SECTION 3
SUMMARY & RECOMMENDATIONS
This study was conducted under closely controlled
experimental conditions that were designed to be very
representative of typical farming situations in the Maryland
coastal plain. A “worst case” scenario was investigated,
however, to estimate an upper bound for pollutant losses, and
thus a lower bound for ‘IFS effectiveness.
In the upcoming months in Maryland, special attention is
expected to be directed toward vegetated filter strips as a best
management practice due to the recently passed Chesapeake Bay
Critical Area Protection Act. One requirement resulting from the
legislation is that, under certain conditions, VFS must be
provided around the borders of some agricultural operations.
This study provides timely guidance for the implementation of
that legislation. Specifically, results of this study
demonstrate that VFS performance under “real world” conditions
can be highly variable, especially as regards the ability to
remove nutrients from runoff. Vegetated filters thus should not
be considered as nutrient management BMP5 in and of themselves.
This study supports findings of other researchers that
demonstrate the ability of VFS to reduce suspended solids
(sediment) losses in runoff. The time dependent nature of these
removals was not adequately defined, nor was the areal
distribution of such removals between ‘IFS and upslope source
areas.
In addition to defining the performance of ‘IFS in removing
nutrients and sediment from agricultural runoff, a major
objective of this study was to develop more reliable design
criteria (i.e. design equations) for VFS than presently exist.
Efforts fell somewhat short of accomplishing this objective.
This occurred because the experimental design was developed under
the hypothesis that the major nutrient and sediment removal
mechanisms would occur in the VFS themselves. This research
indicated that significant removals, especially of sediment, can
occur at the interface between VFS and upsiope areas the VFS are
supposed to protect.
The significance of this observation should not be minimized
for it suggests that VFS are responsible for some removals of
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contaminants from agricultural runoff that occur rather
independently of VFS width. The extent to which such removals
occur does, of course, depend heavily on the condition of the
filter and on the surrounding topography. Removal processes at
the VFS/source area interface need much more study to determine
their significance.
This study focused on the ability of VFS to remove nutrients
and sediment from agricultural runoff. It did not investigate
the many additional benefits that may accrue from the use of
vegetated filter strips, such as stream or ditch bank
stabilization. This research thus suggests the following
recommendations:
1. VFS should not be considered as a nutrient management
technique by themselves.
2. The performance of VFS in actual use, is likely to be
highly variable due to a number of natural factors.
3. This and other research suggests that to maximize the
ability of VFS to reduce pollutants in runoff, dense stands of
vegetation should be established and maintained, and every
reasonable attempt made to promote uniform flow of runoff through
the filters.
4. Important management questions remain unanswered that
could improve VFS performance, and thus should be studied.
Answers are needed regarding how long—term VFS performance
varies, how VFS can be managed to maximize effectiveness, and how
sedimentation at the VFS interface affects total VFS performance.
These answers can be found only through continued research.
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SECTION 4
REVIEW OF LITERATURE
HIGHLIGHTS OF PREVIOUS RESEARCH
Like many of the agricultural practices now called BMPs for
pollution control, vegetated filter strips originated from soil
and water conservation practices (SWCPs), i.e. practices designed
to reduce erosion and/or manage water more effectively for
improved agricultural production. Strip cropping (which is still
a widely—used conservation practice) is the forerunner of
perimeter—based vegetated filters, and employs strips of
perennial grasses, legumes, or hay crops alternated among strips
of row crops within a given field. The close—growing vegetated
strips effectively reduce slope length, slow runoff velocity,
filter soil from runoff, and facilitate absorption of rain by the
soil (Schwab, et al., 1966). Not all of the SWCPs adapted for
pollution control function equally effectively, however,
especially in terms of removing soluble pollutants (Haith and
Loehr, 1979).
A number of research studies have investigated the use of
vegetated filters for nonpoint source pollution control. Doyle,
Stanton and Wolf (1977) applied dairy manure upsiope of both
fescue and forest buffers and concluded that filter lengths of
only 3.7 — 4.6 m (12 — 15 ft) were very effective in removing
soluble and suspended pollutants from runoff. Dickey and
Vanderhoim (1981) studied channelized and overland flow grassed
systems for treating feedlot runoff. They observed up to 80%
reductions in concentrations of nutrients, solids and oxygen
demanding material in filter lengths ranging from 91 to 262 m
(300 to 860 ft). They also developed filter design criteria
based on residence or contact time concepts.
Livingston and Hegg (1981) used terraced pasture to treat
dairy yard runoff with success except for removing nitrate.
Sievers, Gardner and Pickett (1981) also used a terraced grass
system to treat swine waste. Edwards, et al. (1981) used a
similar system for beef feedlot runoff. Norman, Edwards and
Owens (1978) presented grass filter design criteria based on
making travel time through the filter proportional to BOD
concentration in runoff and assumed a 53 m (174 ft) length
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reduced BOD concentrations by 75%. Young, Otterby and Roos
(1982) used the concept of residence time to develop empirical
relationships for evaluating pollutant reduction potentials of
grassed areas. Young, Huntrods and Anderson (1978) reported on
the ability of 24 m (80 ft) long cropped areas to remove
pollutants from feedlot runoff. Significant reductions 92%
sediment, 64% TN, 59% TP and 80% runoff) were achieved in the
Strips.
Bingham, Westerman, and Overcash (1980) and Overcash,
Bingham, and Westerman (1981) applied chicken manure to grassed
areas and measured runoff quality at numerous downslope
distances. They concluded that buffer lengths in a 1:1 ratio to
land application area were necessary to achieve background levels
of contamination in filters downslope of waste application sites.
They developed a mathematical model to predict performance,
taking into account dilution, infiltration, and pollution
potential of the waste application site. Their results are
summarized in an EPA report (Westerman, Overcash and Bingham,
1983).
Considerable effort has been placed on developing analytical
procedures to describe VFS performance in retaining sediment.
The first widely recognized work was performed at the University
of Kentucky and concerned erosion control in surface mining areas
(Barfield et al., 1977, 1979; Kao and Barfield, 1978; Tollner et
al., 1976, 1977, 1978, 1982; Hayes et al., 1979, 1983). Toliner
et al. (1976) developed exponential power functions that related
sediment trapping efficiency in simulated vegetal material to
runoff, soil, and vegetation characteristics. Barfield et al.
(1977) developed a steady state model (Kentucky filter strip
model) for determining the sediment retention capacity of grass
media as a function of flow, sediment load, particle size, slope,
and several other parameters. Hayes et al. (1979) extended the
model of Barfield to unsteady flow and non—homogeneous sediment.
Hayes and Hairston (1983) evaluated Kentucky filter strip model
predictions against field data measuring VFS performance in
retaining sediment naturally eroded by multiple storm events.
Agreement between measured and predicted performance was good.
SUMMARY AND PERSPECTIVE
As evidenced by this comprehensive review of literature,
previous studies involving vegetated filters have concentrated on
animal waste application areas or surface mined areas.
Relatively little work has been undertaken to study the
effectiveness of VFS downslope from cropped areas. Several
studies have involved sod with vegetation densities that may not
be representative of field conditions.
7
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With the exception of the study by Sievers, Garner and
Pickett (1975), research has ignored the effect of vertical
transport, either upward or downward, of pollutants beneath VFS.
Nevertheless, infiltration is almost always cited as the major
treatment mechanism operating in vegetated filters. Predictive
tools by which to design ‘IFS range from highly complex,
cumbersome deterministic models (e.g. University of Kentucky
work) to very simplistic and empirical relationships. Required
filter lengths for approximately 90—95% pollutant reductions in
runoff have ranged from 3 m (10 ft) to lengths equivalent to the
area upsiope from the filter. If the latter criterion were
followed, a square agricultural field one hectare (or one acre)
in size would require a VFS of identical size.
8
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SECTION 5
STUDY OBJECTIVES
This study forms the first phase of a comprehensive joint
investigation of nutrient and sediment movement from agricultural
lands planned by the Agricultural Experiment Stations in Maryland
and Virginia, through the Departments of Agricultural Engineering
at The University of Maryland and at Virginia Polytechnic
Institute and State University (Virginia Tech). This first phase
concerned vegetated filter strips (VFS) and had the following
objectives:
1. Determine how well VFS remove sediment and nutrients
from agricultural runoff
2. Improve design methods for VFS
3. Estimate the effectiveness of existing VFS.
By cooperating on this project, the two universities were
able to investigate a wider range of conditions than either
research unit could study effectively on its own. As an example,
slopes and soils typical of lowland regions in the Chesapeake Bay
basin coastal plain as well as residual soils and slopes found in
upland regions of the Appalachian province were studied, not just
those conditions in one physiographic region. It was also
appropriate that, since Bay restoration heavily involves both
Maryland and Virginia, both universities should work
cooperatively whenever possible. This report deals only with the
investigations conducted at the University of Maryland.
9
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SECTION 6
PROCEDURES
EXPERIMENTAL DESIGN AT MARYLAND
Hydrologic agricultural research at the University of
Maryland has a very pragmatic orientation to maximize its
immediate relevance to the agricultural community, as well as to
society at large. Consequently, the general philosophy that
governs the design of experiments concerning nonpoint source
pollution is to represent “real world” field conditions as
closely as possible without compromising the scientific value of
the experiments.
Runoff Plots
The study made use of “runoff plots”, experimental units in
which surface (and sometimes subsurface) flow is confined to a
known area. In a typical design, runoff plots utilize artificial
borders to define the origin of runoff and subsequently direct it
to a collection point for quantity and quality measurements.
Soil characteristics are assumed to be uniform within a given
plot. This experimental design provides an important
intermediate step between pure laboratory and pure “field”
experimentation in that many important variables can be held
nearly constant within an overall environment that closely
resembles “real world” conditions.
Three groups of three plots each were established in an area
formerly cropped to corn at the University of Maryland Wye
Research and Education Center near Queenstown, MD. The Center is
located in the Atlantic coastal plain physiographic province.
The plot groups, or sets, were constructed on approximately 3%,
4%, and 5% slopes, respectively (Figure 1) after careful
topographic surveying of the area. Each plot had a fallow
“source” area that served as the origin of pollutants to
vegetated filter strips at the base of each plot (Figure 2).
Source areas were 22 m (72.6 ft) long, the standard slope length
on which the Universal Soil Loss Equation is based.
Vegetated filters 4.6 m (15 ft) and 9.2 m (30 ft) wide (in
the downslope direction) were selected for study because these
10
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Figure 1.
Site layout of University of Maryland vegetated filter strip research
plots, Queenstown, MD.
CONTOUR INTERVAL O.3m
-------
Figure 2.
Schematic diagram of one set of experimental runoff
plots showing relationship of VFS to bare source areas
and arrangement of control plot.
12
RUNOFF
SAMPLING PITS
-------
dimensions bracketed widths generally being required by
agricultural cost sharing programs in each state. Kentucky—3l
fescue, a grass popular in the mid—Atlantic coastal plain, was
used for the VFS. Filter areas were seeded using standard
farming techniques after residue from the previous corn crop had
been chopped and disked. All tillage practices were accomplished
on the contour.
VFS of each width were used in each set of plots. In
addition, one plot in each group had no VFS and served as a
control by which to estimate the delivery of pollutants from
source area to filters. This experimental design is commonly
used in agricultural hydrologic research (e.g. Neibling and
Williams, 1979), however the assumption that pollutant deliveries
from different source areas are identical is a liberal one.
Recent research (e.g. Wendt, Alberts and Hjelmfelt, 1986)
suggests that erosion and runoff rates from adjacent bare plots
are variable. Source areas were purposely kept fallow to attain
a “worst case” situation for nutrient loss, i.e. the occurrence
of precipitation soon after fertilizer application but before a
crop has had time to begin nitrogen uptake.
Soils Description
Soil scientists from the University of Maryland Agronomy
Department visited the site to describe the soil profile and
identify the soil series more precisely than could be done with a
soil survey. The soil description is found in Appendix A. Based
on this description, the soils were identified as Woodstown sandy
loam (typic Hapludult, mesic, fine loamy, siliceous), an
agriculturally important soil on Maryland’s Eastern Shore.
Rainfall Simulation
Artificial rainfall was used to generate runoff from the
plots and was created using a simulator designed by Shanholtz
(1981). Water was supplied from a well on site, the pump for
which was approximately 24 m (80 ft) deep. Though this was the
only feasible means of providing good quality water for the
simulations, the supply rate was less than ideal and caused minor
problems (as discussed below).
Tests were performed according to the following schedule to
generate runoff under a variety of soil moisture conditions. The
schedule also permitted an examination of pollutant losses as
related to the length of time between nutrient application and
occurrence of precipitation.
Run 1 — “Dry soil test”, 1—hour duration; 48.25 mm
(1.9 in) rain applied
13
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Run 2 — “Wet soil test”, conducted 24 hours after Run
1; 1/2—hour duration; 24.13 mm (0.95 in) rain
applied
Run 3 — “Very wet soil test”, conducted 1 hour after
Run 2; 1/2—hour duration; 24.13 mm (0.95 in) rain
applied
Runs 4, 5 & 6 — Identical to Runs 1, 2, & 3,
respectively; conducted 1 week after Runs 1 — 3
Runs 7 — 12 identical to Runs 1—6, respectively, but
conducted approximately 1 month after Runs 1 — 6
Twelve (in the case of plots with no VFS) or 15 raingages
were placed uniformly in each plot during each run to record the
distribution of rainfall within and between plots. Except when
rain appeared imminent, plots were left uncovered between runs.
When precipitation threatened, which occurred only once during
the two series of tests, plots were covered with plastic sheets.
Nutrient Additions
Two sources of nutrients were used in the study:
commercially supplied liquid nitrogen (a 30% N urea—amrnonium—
nitrate solution) and poultry (broiler) litter. Liquid nitrogen
was used exclusively in the first series of tests (i.e. Runs 1 —
6); broiler litter was used exclusively in Runs 7 — 12.
Supplemental nutrients were not applied to the plots (except
those inherent in the broiler litter), primarily because soil
test levels of phosphorus (P) indicated that adequate levels of P
were already present in the soil profile.
Both nutrient sources were surface applied by hand without
incorporation. Applications were made approximately two days
prior to each series of runoff tests.
Liquid nitrogen was applied before Run 1 at a rate of 112 kg
N/ha (100 lb N/ac). While the N application rate was slighty
high, experience indicated that it generally represented what
would be used as a pre—plant, starter application of N for corn
production in the Maryland coastal plain.
Broiler litter was applied before Run 7, which was
approximately 1 month after Run 1, at 8.9 wet metric tons/ha (4
wet tons/ac), the lowest rate farmers can apply with conventional
spreading equipment. After collection, manure was kept on site
in burlap bags until it was spread on the plots. Samples of the
manure were collected when the manure was applied, and again at
14
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the time of rainfall simulation, for subsequent nutrient
analysis. Approximately 287 kg N/ha (256 lb N/ac) were applied
in manure, but only about 57 kg N/ha (51 lb N/ac) would be
expected to be available to crops in the first year of
application if the manure were not immediately incorporated into
the soil.
Plot Preparation
Bare source areas were rota—tilled to a depth of
approximately 15 cm (6 in) using a hand tiller prior to Runs 1
and 6. Tillage was carried out parallel to slope to yield a
smooth, uniform surface free from major depressions. Care was
taken to prepare all plots in an identical manner.
Soil Sampling
Soil samples were taken approximately one month before any
runoff tests began, one month after Run 6 and again one month
after Run 12. Samples were collected to a depth of 125 cm (4 ft)
using a Giddings soil sampler. Cores were segregated into
individual samples according to horizon as identified in the
description of the soil profile. Four cores were collected from
each source area; two cores were collected from each VFS. Bulk
densities were determined for all segregated samples by measuring
the volume occupied in the sample tube by each segregate and
determining the moisture content of the segregate. Segregated
samples at corresponding depths from the four source area cores
in each plot were composited to yield one series of bare
segregates per plot. Likewise, segregated samples from cores
from each VFS were coinposited to yield one series of VFS
segregates per plot.
Runoff Measurement and Sampling
Runoff from each plot was collected in a gutter at the base
of each plot and directed into 15 mm (6 in) H—flumes for
measurement using FW—l type water level recorders (Figure 3).
Flumes were carefully installed and field calibrated to determine
rating curves that would assure reliable measurements.
Discrete runoff samples were hand—collected throughout each
runoff event by assistants attending the flumes. Samples were
collected 1, 2 and 3 minutes after the inception of runoff and at
3—minute intervals thereafter until the end of runoff. It was
each attendant’s responsibility to judge the inception of runoff
at his plot.
15
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VEGETATED FILTER
STRIPS
RUNOFF MEASUREMENT
SIDE VIEW
RUNOFF
PLOT
&
I ’
S
IA
-‘
COSCHOCTOFS
Figure 3. Schematic diagram of instrumentation used to measure and sample runoff
GUTTER
‘-a
a’
APPROACH
BOX
WATER LEVEL
RECORDER
V t
“H 1 FLUME
1
V.
(.
1)
1
‘I
‘1
‘I
WHEEL
I .
from runoff plots.
-------
Persons collecting samples marked the runoff chart at the
time rainfall began, when runoff began and at the time each
sample was collected so that accurate computations of mass
transport in the runoff could be made. Samples were collected in
acid—washed Nalgene bottles. Duplicate subsamples were
transferred into sterile plastic “Whiripak” baggies for
preservation by freezing. All samples were refrigerated while
transfers were being made, a process which took at most 12 hours.
ANALYTICAL PROCEDURES
Broiler litter was analyzed for nutrient content by the
University of Maryland Manure Testing Laboratory (UM-MTL).
Runoff samples were analyzed for nutrients by the Virginia Tech
Agricultural Engineering Laboratory (VPISU—AgE Lab), and for
solids by the University of Maryland Wye Research and Education
Center Laboratory (UM—WRECL). Soil samples were analyzed for
inorganic nitrogen by the Virginia Tech Agronomy Department
Nitrogen Laboratory (VPISU—Agrn Lab). Specific analytic
techniques and the analyzing laboratory are outlined below.
Total Kjeldahl Nitrogen
TKN was determined colorimetrically with an autoanalyzer on
digested, unfiltered samples using Method 351.2 in Methods for
Chemical Analysis of Water and Wastes (USEPA, 1979). VPISU — AgE
Lab.
Ammonium Nitrogen
Ammonium nitrogen was determined colorimetrically on
filtered samples using Method 350.1 in Methods for Chemical
Analysis of Water and Wastes (USEPA, 1979). VPISU — AgE Lab.
Nitrate—Nitrite Nitrogen
Nitrate—nitrite nitrogen was determined colorimetrically on
filtered samples using Method 353.2 in Methods for Chemical
Analysis of Water and Wastes (USEPA, 1979). VPISU — AgE Lab.
Total Phosphorus
Total phosphorus was determined on digested, unfiltered
samples colorimetrically using an antoanalyzer according to
Method 365.4 in Methods for Chemical Analysis of Water and Wastes
(USEPA, 1979). VPISU — AgE Lab.
17
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Ortho—Phospho rus
Otho—phosphorus was determined on undigested, unfiltered
samples using Method 365.4 in Methods for Chemical Analysis of
Water and Wastes (USEPA, 1979). VPISU — AgE Lab.
Total Suspended Solids
Total suspended solids were determined using Method 160.2 in
Methods for Chemical Analysis of Water and Wastes (USEPA, 1979).
UM—WRECL.
Volatile Suspended Solids
Volatile suspended solids were determined using Method 160.4
in Methods for Chemical Analysis of Water and Wastes (USEPA,
1979). UM—WRECL.
Extractable Soil Inorganic Nitrogen
Extractable soil N was determined from 5 g air dried soil
sam ].es shaken with 50 ml of 2M KC1 for 1 hour. Extractable soil
NHA —N was determined colorimetrically with the iriduphenol blue
pr8cedure (Keeney and Nelson, 1982). Nitrate+nitrite nitrogen
was determined by the sulfanilamide method after reduction to
nitrite in a Cd—Cu column (Kenney and Nelson, 1982). VPISU —
Agrn Lab.
18
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SECTION 7
MANURE ANALYSIS
RESULTS AND DISCUSSION
Results of the broiler litter analysis are presented in
Table 1. These data illustrate the variability that is
characteristic of an unstable nutrient source such as animal
manure. Samples 1 through 5 all came from plots comprising Set
3: sample 1 was a composite of subsamples from all three plots
at the time of manure application; samples 2, 3, and 4 were
composites of samples within individual plots collected 3 days
after application at the time of testing. Sample 5 was collected
at the time of testing, but from a small pile of manure that had
been spilled outside of the plots.
Sample 6 was a composite of subsamples from plots in Set 2
at the time of manure application. Sample 7 was also a composite
of subsamples from these plots collected one day later at the
time of rainfall simulation. Similarly, Samples 8 and 9 were
composites of samples from plots in Set 1 collected at the time
of manure application and testing, respectively.
TABLE 1. BROILER LITTER ANALYSIS
Description N P 2 0 5 K 2 0 Moisture Dry
Sample
Matter
1 Set 3 @ Application
2 Plot 7 @ Test time
3 Plot 9 @ Test time
4 Plot 8 @ Test time
5 Outside Set 3 @ Test
6 Set 2 @ Application
7 Set 2 @ Test time
8 Set 1 @ Application
9 Set 1 @ Test time
Per Cent
3.7 3.6 2.6 14.3 85.7
3.1 2.4 1.8 16.2 83.8
2.1 2.7 1.8 17.7 82.3
2.8 3.1 2.0 18.7 81.3
3.2 3.6 2.4 18.4 81.6
4.7 3.3 2.4 17.3 82.7
3.1 3.0 2.1 5.7 94.3
3.5 3.1 2.2 12.5 87.5
2.7 3.3 2.2 14.4 85.6
19
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Table 2 translates the nutrient values reported in Table 1
into mass values based on the application of 8.9 t/ha (4 t/ac),
the rate used in this study.
All samples exhibited expected behavior of surface applied
poultry litter, i.e a reduction in nitrogen content due primarily
to atmospheric volatilization of anunonia N. However, sample 5
illustrated the effect that decreased direct exposure of litter
to the atmosphere has on volatilization losses. Sample 5 came
from a small mound of litter, whereas all other samples were
composites of subsamples from litter spread thinly and uniformly
over the various plots. For computational purposes, samples 2,
3, 4, 7, and 9 were used to determine the mass of applied
nitrogen available for transport during runs 7 — 12.
TABLE 2. MASS NITROGEN APPLICATION FROM BROILER LITTER
Sample Description N Content Appl. Rate Mass N Applied
kg/t kg/ha kg
1 Set 3 @ Application 37.2 331.5 4.0
2 Plot 7 @ Test time 31.2 277.8 3.4
3 Plot 9 @ Test time 21.1 188.2 2.3
4 Plot 8 @ Test time 28.2 230.9 2.8
5 Outside Set 3 @ Test 32.2 286.7 3.5
6 Set 2 @ Application 47.3 421.1 5.1
7 Set 2 @ Test time 31.2 277.8 3.4
8 Set 1 @ Appliáation 35.2 313.6 3.8
9 Set 1 @ Test time 27.2 241.9 2.9
SIMULATOR PERFORMANCE
The rainfall simulator gave excellent performance, having
uniformity coefficients (a measure of how uniformly rainfall was
distributed over the plots) in excess of 90% the majority of the
time. The mean uniformity coefficient was 0.92, with a standard
deviation of 0.03. Table 3 summarizes performance data reported
in Table 3—1, Appendix B.
Mean amounts of applied precipitation were very near design
values for most runs, especially those of 1/2 hour duration (Runs
2, 3, 5, 6, 8, 9, 11, & 12). Data in Table 3 for runs 4 and 10
reveal what are apparently unacceptable variances in
precipitation. The apparent poor performance during run 4 was
due to difficulties encountered during tests involving Set 1 and
Set 2. On days previous to tests involving those plots a delay
in schedule prevented the simulator reservoir from being filled
20
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to a capacity that would permit a full 1—hour run. Consequently,
Run 4 for Plots 1, 2 & 3 was 45 minutes in duration, rather than
the desired 1 hour. Run 4 for Plots 4, 5, and 6 was also 45
minutes in length because of a lack of sample bottles to continue
runoff sampling for the full time that runoff would have occurred
in a 1—hour test. Run 10 for Plots 4, 5, and 6 was also only 45
minutes long due to a lack of supply water. Despite the
abbreviated duration for these tests, the rate of application was
comparable to that for full duration tests.
TABLE 3. RAINFALL SIMULATOR PERFORMANCE
Run Precipitation Applied, mm Uniformity Coefficient
Average Std. Dev. Var. Average Std. Dev. Var.
1 46.70 2.08 4.33 0.92 0.02 0.0006
2 24.31 1.28 1.63 0.90 0.05 0.0021
3 24.14 1.16 1.35 0.92 0.03 0.0008
4 39.68 7.13 50.89 0.90 0.03 0.0009
5 24.32 1.19 1.41 0.91 0.02 0.0003
6 24.19 0.94 0.89 0.93 0.02 0.0003
7 45.32 2.63 6.89 0.93 0.02 0.0005
8 25.15 2.14 4.60 0.89 0.08 0.0062
9 24.23 0.58 0.34 0.92 0.02 0.0004
10 41.86 7.06 49.91 0.92 0.02 0.0006
11 24.17 0.75 0.57 0.92 0.02 0.0005
12 24.71 0.90 0.82 0.93 0.02 0.0004
HYDROLOGIC RESPONSE
Expected Performance
Theoretically, increasing slope has the effect of increasing
runoff from a given area, if all other runoff—affecting
conditions (e.g. antecedent moisture, vegetative cover, etc.) are
the same. In addition, the presence of vegetation on all or part
of an area would be expected to decrease the volume of runoff
roughly in proportion to the percentage of area vegetated.
Longer slope lengths tend to increase runoff above that produced
with shorter slope lengths.
Soil condition, both in a physical sense and with respect to
moisture content, also affects runoff potential from an area.
For example, areas that have been freshly cultivated generally
have a larger capacity to infiltrate incident precipitation than
uncultivated areas whose surface may have become sealed (or
21
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armored) by previous storm events. Likewise, soils of any given
type with lower moisture contents have more unfilled pore space
available for infiltrating precipitation than do the same soils
with higher soil moisture. The former would thus be expected to
produce less runoff than the latter for a given amount of
precipitation.
In the study reported herein, Plots 3, 6, and 9 (bare plots)
might be expected to produce the most runoff, whereas Plots 1, 4,
and 7 (those with the most vegetation) might be expected to
produce the least, in any given slope category. Similarly, all
plots in a given slope category would be expected to produce
increasing amounts of runoff as tests proceeded through runs 1, 2
and 3; 4, 5 and 6; 7, 8 and 9; and 10, 11 and 12. A marked
decrease in runoff from all plots between runs 6 and 7 would be
expected since at this point all plots were recultivated for
initiation of experiments with the broiler litter.
Observed Results
Data describing several characteristics of runoff from the
vaious plots are presented in Table 4, as summarized from Table
B—2, Appendix B. Unfortunately, not included in these values are
results from Plot 3 (bare) during run 7, which due to an
equipment malfunction were not available.
Several trends, each of which is indicative of the effect of
filter strip width on runoff, are evident from the summary in
Table 4. Firstly, it is apparent that increasing filter width
increased lag time, i.e. slowed runoff. (Lag time was taken as
the time between initiation of rainfall and the appearance of
runoff.) This is intuitive considering that vegetation in the
strip should increase resistance to flow.
Lag time during runs using broiler litter increased in all
categories over that experienced using liquid N. This was likely
due to the mulching effect of the litter, and to the “damming” of
flow channels through the filters by wood chips contained in the
litter. (Obviously the latter effect was not important in the
plots with no filters.) The fact that all plots were
recultivated before tests involving broiler litter probably also
contributed to the increased lag times. Also evident from Table
4 is the effect that continued precipitation had in reducing lag
times; i.e. as soil moisture and surface sealing increased, the
time for runoff to occur decreased.
The same trends are demonstrated in duration times (length
of time runoff occurred) and the amount of runoff that occurred
in these tests. (To help normalize runoff data, they have been
presented in Table 4 as a fraction of the applied precipitation.)
22
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The data indicate that as filter strip width increased, duration
of runoff increased as did the proportion of rainfall that was
runoff. These trends were demonstrated during tests with both
nitrogen sources, but with broiler litter, magnitudes were
reduced from those experienced during liquid N runs.
TABLE 4. SUMMARIZED RUNOFF CHARACTERISTICS
Ave 1 Filter N Lag 2 1 min Duration ,min % of Ppt
Ppt ,mm Width,m Source Ave. S.D. Ave. S.D. Ave. S.D.
++++++++++++++++++++++ Initial 1—Hour Runs ++++++++++++++++++++++
42.85 9.2 UAN 4.88 2.09 67.17 4.52 43.26 15.08
42.73 9.2 BL 11.97 4.30 65.33 11.04 33.68 19.90
43.46 4.6 UAN 2.25 0.38 71.50 7.18 62.52 13.28
43.83 4.6 BL 7.17 4.55 70.67 12.61 40.16 20.86
43.25 0.0 UAN 1.50 0.41 72.17 9.44 73.43 20.55
44.22 0.0 BL 3.98 3.82 72.33 5.50 43.78 23.81
++++++++++++++++++++++ 1st 0.5—Hour Runs ++++++++++++++++++++++++
24.50 9.2 UAN 4.23 2.61 43.33 3.99 48.89 11.74
24.76 9.2 BL 6.25 1.46 47.67 3.04 47.34 13.45
24.79 4.6 UAN 2.72 1.56 51.50 6.08 75.34 12.14
25.15 4.6 BL 6.72 3.77 52.17 6.84 59.28 13.64
23.70 0.0 UAN 1.38 0.74 53.00 4.06 73.22 15.74
24.08 0.0 BL 2.53 1.20 44.67 6.50 60.56 13.41
++++++++++++++++++++++ 2nd 0.5-Hour Runs ++++++++++++++++++++++++
23.44 9.2 UAN 2.92 1.20 50.00 1.83 65.64 12.07
24.72 9.2 BL 5.58 1.64 51.83 1.34 64.88 11.45
24.54 4.6 UAN 1.83 0.85 56.33 6.94 88.32 9.39
24.39 4.6 BL 4.50 2.42 56.50 6.70 74.61 12.73
24.53 0.0 UAN 1.00 0.00 48.83 2.27 80.17 14.09
24.30 0.0 BL 1.25 0.38 53.83 13.73 67.06 18.09
Ave. Ppt — average amount of simulated rain
3 Lag — time between start of rain and start of runoff
4 Duration — duration of runoff
% of Ppt. — ratio of runoff amount to rainfall amount
UAN — urea—anunonium—nitrate (liquid nitrogen)
BL — broiler litter
When examining individual hydrologic responses, data in
Table B—2 indicate that Plots 4, 5 and 6 (on 3% slope) exhibited
expected runoff behavior better than the other groups of plots.
Runoff response of Plot 6 might be higher than expected (at
23
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nearly 100% of applied precipitation) during runs 1 through 6.
Progressively more runoff from Plot 6 during runs 7 through 12
would be the more “expected” response. Surface sealing and/or
soil saturation apparently occurred quickly on Plot 6 in runs 1
through 6. Perhaps the organic matter (wood chips and manure
particles) in the chicken litter acted as a mulch and helped
obscure at least the sealing effects in runs 7 through 12.
The decrease in runoff (Table B—2) from all plots on 3%
slope between runs 6 and 7 is also very evident and likely the
result of both cultivation of the bare source areas and decreased
soil moisture contents. “Recovery” of infiltration capacity
between runs 3 and 4 and between runs 9 and 10 (the one—week
waiting periods between tests) is also observable for the grassed
plots (Plots 4 and 5). As expected, runoff from plots with
vegetated filters (Plots 4 and 5) was lower than from the plot
with no filter (Plot 6).
In the other slope categories, the bare plots with no
filters (Plots 3 and 9) performed basically as expected with
increasing runoff as more and more precipitation was applied,
although trends were less clearly defined than for the 3% plots.
What is more interesting in the 4% and 5% slope categories,
however, is that the plots with filters on occasion produced as
much or more runoff as the bare plots with no filters. This
seemingly incongruous result may reflect higher soil moisture
contents in the grassed filters, effectively limiting
infiltration and increasing surface runoff above that generated
on totally bare plots.
SURFACE LOSSES OF NUTRIENTS
Although approximately 20 discrete runoff samples were
collected from each plot in a typical 1—hour test (10 for a 0.5—
hour test), laboratory constraints restricted the number of these
that could be analyzed to approximately 5 per test. Decisions
regarding which samples to analyze were made by examining the
accompanying hydrograph, and selecting samples which corresponded
to early and late in the runoff event, and at marked changes in
runoff rate at intermediate times. Table B—3 in Appendix B
contains results of all chemical analyses. Linear interpolation
was used to estimate pollutant concentrations at other times
during the runoff event for purposes of calculating mass
loadings. Observations of analyses for samples taken at a
variety of times during runoff suggest that the approach for
calculating mass losses in runoff was conservative.
Table 5 contains an abbreviated summary of data presented in
Table B—4, Appendix B for nutrient and suspended solids losses in
24
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runoff. Not included in these data are results from Plot 3, runs
7 and 8. The hydrograph was not available for run 7 because of
an equipment malfunction. Samples from run 8 for nutrient
analysis were lost at some time before analysis was performed and
thus no nutrient data were available. Nevertheless, several
trends are indicated in this summary.
TABLE 5. SURFACE RUNOFF LOSSES OF NUTRIENTS AND SOLIDS
Ave 1 Filter N Total P ,gms Total N ,gms TSS ,gms
Ppt ,mm Width,m Source Ave. S.D. Ave. S.D. Ave. S.D.
++++++++++++++++++++++ Initial 1—Hour Runs ++++++++++++++++++++++
42.85 9.2 UAN 20.23 12.02 16.38 9.56 5431 4021
42.73 9.2 BL 18.73 8.96 32.63 16.18 1870 1406
43.46 4.6 UAN 28.50 7.73 57.89 49.92 12243 8512
43.83 4.6 BL 19.88 14.11 30.23 17.83 3639 3756
43.25 0.0 UAN 44.01 12.31 42.80 14.29 70827 78676
44.22 0.0 BL 29.00 15.20 32.91 24.96 9454 5013
++++++++++++++++++++++ 1st 0.5—Hour Runs ++++++++++++++++++++++++
24.50 9.2 UAN 14.10 10.74 12.30 5.04 3157 1595
24.76 9.2 BL 13.85 10.50 20.63 11.05 1919 2426
24.79 4.6 UAN 14.74 9.60 21.97 11.61 4966 2643
25.15 4.6 BL 20.17 22.42 30.37 14.68 4195 5413
23.52 0.0 UAN 22.35 15.14 30.69 16.77 16220 6379
24.22 0.0 BL 22.50 12.59 28.35 18.09 6623 2307
++++++++++++++++++++++ 2nd 0.5—Hour Runs ++++++++++++++++++++++++
23.44 9.2 UAN 11.29 5.05 11.22 7.39 5214 4719
24.72 9.2 BL 12.94 7.63 21.79 10.30 2676 2499
24.54 4.6 UAN 12.46 6.26 13.80 5.76 13143 16205
24.39 4.6 BL 18.12 8.88 39.41 17.70 4652 4568
24.53 0.0 UAN 20.03 11.74 21.14 9.38 13654 4522
24.30 0.0 BL 24.52 4.44 40.27 27.16 8318 2569
Ave. Ppt — average amount of simulated rain
3 Total P — total phosphorus in runoff
4 Total N — total nitrogen in runoff
TSS — total suspended solids in runoff
UAN — urea—ammonium—riitrate (liquid nitrogen)
BL — broiler litter
General Trends
Losses of phosphorus were higher from the initial 1—hour and
first 0.5—hour tests involving DAN, than they were for the
25
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corresponding tests involving broiler litter (except for the 4.6
m plots). At first this might appear unusual, considering that
no phosphorus was applied with the UAN, but that the broiler
litter did contain P. The higher losses of P during the UAN
tests are probably explained by the fact that the losses of
suspended solids (and presumedly, attached P) were also much
greater for the UAN tests than for those involving broiler
litter. Total P losses for the second 0.5—hour runs were
somewhat comparable for both tJAN and broiler litter tests, with
those from the litter tests being slightly greater. Suspended
solids losses were not as different in tests with the two
nutrient sources during these runs as during the previous two
sets of runs, a fact that may have influenced the relationship
between P losses. Also evident from data in Table 5 is the fact
that P losses generally decreased with increasing filter strip
length. Losses of total P also diminished as the number of tests
progressed.
The relationship between total nitrogen losses in tests
involving UAN and broiler litter was not as clear as for total P
losses. Overall, it appeared that total N losses decreased with
increasing filter strip width, however. An exception to this
general trend occurred during the 1—hour runs involving UAN and
4.6 m (15 ft) filters. Otherwise, during UAN tests, average mass
losses from plots with 9.2 m (15 ft) filters were approximately
half those from plots with no filters. As with total P, total N
losses generally decreased as the number of tests performed
increased, indicating probably that less material was available
for transport.
For the experimental design used in this study, a mass loss
of 10 gms represented an areal loss of 0.84 kg/ha (0.75 lb/ac).
Thus total P losses from bare plots from all runs involving UAN
amounted to 7.3 kg/ha (6.5 lb/ac); total N losses were 7.9 kg/ha
(7 lb/ac). For the entire testing period (losses from UAN plus
broiler litter), total P losses for bare plots equalled 13.7
kg/ha (12.2 lb/ac) and total N losses equalled 16.4 kg/ha (14.6
lb/ac). By comparison, total P losses from plots with 9.2 m (15
ft) filter strips amounted to 7.7 kg/ha (6.8 lb/ac) and total N
losses were 9.7 kg/ha (8.6 lb/ac). These losses were produced by
approximately 1/4 of the total annual precipitation expected at
the research site. (This does not mean, however, that annual
losses would be expected to be 4 times higher than those reported
here.)
Also clearly evident in the data presented in Table 5 is the
large variability that occurred in nutrient and solids losses in
runoff. Thus, trends indicated by average values such as those
presented in Table 5 were often violated in individual
situations.
26
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Plots 4, 5, & 6
As expected, total nitrogen losses from the bare plot (Plot
6) decreased as runs 1, 2 and 3 progressed, indicating less
material was perhaps available for movement from the site.
During runs 3, 4, 5 and 6, total N losses seemed to be
approximately constant at 25—30 gms (2.1 — 2.5 kg/ha). Losses of
total N during runs 7 through 12 paralleled runoff. Values
indicated that a large amount of broiler litter was leaving the
site. Most of the nitrogen was probably in the organic form
since anunonium—N losses were decreasing.
Losses of nitrogen from plots protected by filters seemed to
be increasing as runs progressed from 1 to 3, which may have
indicated a movement of trapped material from the filter. This
observation seems to be supported by the fact that soluble
phosphorus values decreased for these plots while total
phosphorus losses remained constant.
In most cases the plots with filters appeared to be
effective in reducing total phosphorus and nitrogen losses as
compared to the bare plot control.
Plots 1, 2, 3. 7. 8. & 9
Nitrogen losses from these plots appeared more erratic that
those from the 3% plots (Table B—4). In general these losses
seemed to be a function of the filter condition. The relatively
large losses of nitrogen from the vegetated plots indicates that
surface runoff was probably “short—circuiting” the filters,
because of less—than—perfect sheet flow, and/or because of
variations in the density of the filter vegetative growth. In
fact, both conditions were observed during the tests.
Total phosphorus losses were also erratic, but in general
followed similar trends as total nitrogen losses. The weak trend
of decreasing losses as a function of increasing run number
indicated that less and less material was available for loss as
tests proceeded. Nevertheless, the vegetated plots on these two
slopes were not generally effective in reducing soluble nutrient
losses (although the magnitude of such losses was relatively
small).
SUSPENDED SOLIDS LOSSES
Also presented in Table 5 are data summarizing losses of
suspended solids. Generally there were dramatic differences in
the mass of solids lost between bare plots and plots protected by
27
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vegetated filter strips, losses from bare plots being much
greater. Except for the plots with no filters, TSS losses during
the initial 1—hour runs and the second 0.5—hour runs were
comparable. High initial losses probably reflected the fact that
all plots were in a loose, highly erodible, cultivated state at
the beginning of the 1—hour tests. High losses in the final 0.5—
hour runs were probably caused by the increased proportion of
runoff that occurred in the later runs. These patterns may also
have reflected the movement of sediment further and further into
the VFS until a portion was finally released in the final test.
That these trends were in contrast to those for total N and P
seemed logical since presumedly only larger, relatively non-
reactive soil particles were detained in the VFS.
There was also a marked difference in mass loss of solids in
tests involving JAN as opposed to broiler litter. Except for the
4.6 in filter strip plots during the first 0.5—hour runs, TSS
losses from UAN tests were 3—4 or more times as large as losses
from tests involving broiler litter. This probably reflected the
mulching effect of the litter.
RELATIVE SURFACE LOSSES FROM VEGETATED VS. BARE PLOTS
Table 6 contains summary data regarding the relative losses
of nutrients and solids in surface runoff from plots with
vegetated filters as compared to losses from plots with no
filters. Relative losses are expressed as “performance ratios”,
PRs, defined as the ratio of mass losses from a plot protected by
a VFS to losses from the bare plot on the same slope. Because
runoff data were not available for run 7, Plot 3, and no nutrient
analyses were available for run 8, Plot 3, direct comparisons
were not possible for Set 1 during runs 7 and 8. Data for
individual plots are presented in Table 8—5, Appendix B.
Data in Table 6 represent an average of individual “run—by—
run” VFS performance ratios. These data are thus an average of
12 (or in some cases 10, due to the exclusion of data for runs 7
and 8 for some plots) individual performance ratios.
Consequently, performance data in Table 6 tend to reflect test—
to—test variability in plot behavior.
Data in Table 6 suggest that plots with filter strips may
experience larger losses in surface runoff of some pollutants
than comparable areas not protected by VFS. This is certainly
true on an event—by—event basis, as shown in Table B—5, Appendix
B. As observed during the simulation runs, suspended solids were
carried into the filters, and in some cases, flushed out. When
flushing occurred, mass losses were sometimes greater than for
bare control plots. Graphs in Appendix C (e.g. Figure C—l)
28
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illustrate this phenomenon and indicate that the performance of
the grassed filter strips in reducing nutrient losses as compared
to the performance of nonvegetated plots is variable.
When evaluating data in Table 6, however, the possible
natural variation in surface losses from adjacent areas should be
kept in mind (see earlier discussion under “Experimental
Design”). One should also remember that these summary data are
somewhat biased, due to the absence of mass loss values from Plot
3 for runs 7 and 8. Since Plot 3 was a bare plot, with normally
high nutrient and sediment losses, exclusion of data regarding
that plot tends to make Plots 1 and 2 appear less effective than
they may actually have been.
TABLE 6. RELATIVE NUTRIENT AND SOLIDS LOSSES PROM ‘IFS PrJOTS 1
Average Performance Ratios 2
Filter
Plot Width, m TSS Total N Total P
1 9.2 20.39 48.59 125.04
4 9.2 10.78 53.87 41.93
7 9.2 43.69 78.41 78.99
Mean 24.95 64.62 80.12
2 4.6 35.19 177.29 200.61
5 4.6 33.62 64.36 40.69
8 4.6 75.12 112.95 66.35
Mean 47.65 115.18 94.36
‘Excludes data for runs 7 and 8, Plot 3
2 Average of PRs (e.g. ) from 12 runs
Data in Table 7 lend assistance in interpreting Table 6 and
reflect plot performances for the entire series of tests. These
data are cumulative mass losses and corresponding performance
ratios from all tests. Relative to data in Table 6, those in
Table 7 can be thought of as a representation of “long term” VFS
performance.
Additionally, Table 7 presents two different attempts to
eliminate the bias in plot performance ratios for Set 1 (Plots
29
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1,2, and 3) caused by missing data from runs 7 and 8 for Plot 3.
One technique ignores (excludes from the summation process) mass
losses measured from runs 7 and 8 for Plots 1 and 2. Thus, for
example, the reported total N and P losses for Plots 1 and 2
using this procedure were the summation of losses from runs 1 — 6
and runs 9 — 12. TSS data were treated similarly, but only
losses from run 7 were excluded (because TSS data were available
from run 8 for all plots).
TABLE 7. MASS LOSSES OF NUTRIENTS AND SOLIDS IN RUNOFF
Plot Filter
Width,m
19832 19.5
19240 a 18.9
30221 29.7
29340 a 28.8
9 . 3 c
10178?
29.6
51.5
18.1
179 a
13 . 7 c
34.6
343 a
147.2 61.8
41.2
31 . 4 c
194.1
167.0
98.5
204.8”
59.2
52.4
49 .lc
114.6
105.6
82 • 7 c
139.0 67.9
112.1 54.7
235.0 114.8
208.8 101.9
58.1
53.7
47
77.2
593 c
Ratio of filtered plot loss to that of bare plot loss in set
Exd1udih1g data from run 7, plot 3
Excluding data from run 7, plot 3 and run 8, plot 3
CAssuming plot 3 losses are average of plot 6 and plot 9 losses
The second, and probably more representative, procedure
assumes that total mass losses from Plot 3 would have been
comparable to those from Plots 6 and 9 (also bare), had data for
all 12 runs been available from Plot 3. Thus, using this
+++++Mass ost From All
TSS PR Total N
g Ins gms
Tests and PRs (%)++++++
PR Total P PR
gIns
462.5
398.8
1 9.2
2 4.6
3 0.0
4 9.2
5 4.6
6 0.0
7 9.2
8 4.6
9 0.0
Ave. 9.2
Ave. 4.6
5.3
22.7
19799
84321
372216
81979
142488
276577
231.1
246.9
475.8
311.4
452.6
462.9
48.6
51.9
389.9
67.3
97 . 8
379.9
151.1
164.4
256.7
283.8
38.8
42.2
67.6
74.7
30
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assumption, mass TSS, TN and TP losses for Plot 3 were calculated
as the average of corresponding losses from Plots 6 and 9.
Performance ratios in Tables 6 and 7 indicate that plots
with vegetated filter strips generally were somewhat effective in
reducing surface losses of both nutrients and solids, as compared
to losses from plots with no filters. Additionally it appears
that greater reductions were achieved as filter strip width
increased. Assuming that Plot 3 produced mass losses comparable
to those from Plots 6 and 9, data in Table 7 suggest that
doubling the width of filter produced a twofold increase (i.e. a
twofold decrease in PRs) in the amount of suspended solids
(sediment) retained.
Percentage mass reductions (defined as PMR = 100 — PR) in
Table 8 were calculated from the average performance ratios (PRs)
in Table 7. These figures represent pollutant mass reductions
achieved by VFS using the various assumptions regarding Plot 3
losses described above. As indicated above, VFS appeared most
effective in reducing solids (i.e. sediment) losses. Presumedly
this occured as a result of the filters slowing down the velocity
of runoff and also of providing a physical impediment to the
movement of suspended material in the runoff, both actions
promoting settling of the suspended soil particles. Total P was
reduced to the next greatest degree; total N was least reduced.
Both of these trends were expected based on the assumption that P
movement is generally dependent on suspended solids transport,
whereas N, as a soluble nutrient, can move more freely in the
terrestrial environment.
TABLE 8. AVERAGE PERCENTAGE MASS REDUCTIONS (PMRs)
IN BARE PLOT LOSSES ACHIEVED BY VFS
Filter ++Percent Reductions T in Bare Plot Losses++
Width,m
TSS Total N Total P
9.2 81.9 40.8 41.9
47.6 46.3
86 3 c 509 c 525 c
4.6 65.4 —14.6 22.8
65.7 —5.6 27.1
17 . 3 c 407 c
T Percent Mass Reduction, PMR = (100 — PR), using average PR5
from Table 7
Excluding data from run 7, plot 3
Excluding data from run 7, plot 3 and run 8, plot 3
Assuming plot 3 losses are average of plot 6 and plot 9 losses
31
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Table 9 summarizes mass pollutant losses from bare plots on
an areal basis (extracted from Table 6) and the projected losses
from plots protected by VFS using PMRs from Table 8. In
calculating areal losses, the conversion (for these experimental
conditions) of 10 gms mass lost = 0.84 kg/ha (0.75 lb/ac) was
used.
TABLE 9. MASS LOSSES (AREAL BASIS) OF NUTRIENTS AND SOLIDS
IN RUNOFF
Plot Filter +++++ Mass Lost From All Tests (Bare Plots) ++++
Width,m TSS Total N Total P
kg/ha lb/ac kg/ha lb/ac kg/ha lb/ac
3 0.0 8850 a 7634 a 200 b 179 b
27249 c 24329 C 394 C 352 C
6 0.0 31266 27916 40.0 35.7 32.8 29.2
9 0.0 23233 20743 38.9 34.7 31.9 28.5
AverageC 27250 24330 39.4 35.2 32.3 28.9
+++++ Mass Lost From All Tests (VFS Plots)d ++++
9.2 3733 3333 19.3 17.3 15.3 13.7
4.6 7576 6764 32.6 29.1 19.2 17.1
Excluding data from run 7, plot 3
Excluding data from run 7, plot 3 and run 8, plot 3
Assuming plot 3 losses are average of plot 6 and plot 9 losses
Projected losses using assumption “c” and average PMRs from
Table 8
Table 9 simply presents surface losses of pollutants in more
familiar mass terms. When viewed from this perspective, VFS
appear especially effective in reducing suspended solids losses
in runoff. As indicated in in Table 9, VFS 4.6 m and 9.2 m wide
(15 ft and 30 ft) reduced suspended solids (primarily sediment)
losses from an average of 27 t/ha (12 t/ac) to approximately 7
t/ha (3.3 t/ac) and 3.7 t/ha (1.6 t/ac), respectively.
SUBSURFACE LOSSES OF INORGANIC NITROGEN
Table 10 summarizes data presented in Tables B—6 and B—7,
Appendix B concerning the movement of inorganic nitrogen into the
soil profile to a depth of 125 cm (48 in). These data reflect
leaching of nitrogen during tests involving UAN (runs 1 — 6).
32
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TABLE 10. MASS CHANGES IN SOIL INORGANIC NITROGEN
Plot Filter Total Total Plot Net Change
Width, m Infil. Inorganic N, kg kg %
mm Before After
1 9.2 101.98 2.01 2.15 0.14 6.97
2 4.6 66.44 0.59 1.75 1.16 196.61
3 0.0 73.02 0.66 1.71 1.05 159.09
4 9.2 98.33 1.41 2.19 0.78 55.32
5 4.6 52.57 1.34 3.68 2.34 174.63
6 0.0 2.86 1.95 1.66 —0.29 —14.87
7 9.2 66.22 1.60 2.75 1.15 71.87
8 4.6 32.25 1.89 2.61 0.72 38.10
9 0.0 58.94 1.31 2.50 1.19 90.84
Ave. 9.2 88.84 1.67 2.36 0.69 44.72
Ave. 4.6 50.42 1.27 2.68 1.41 136.45
Ave. 0.0 44.94 1.31 1.96 0.65 78.35
Inorganic N increased in the profile of all plots except one
(Plot 6) during tests with UAN. No obvious trends are reflected
in Table 10, however. On average, it appeared that increased ‘IFS
widths increased infiltration, yet the relationship did not
extend to increased nitrogen leaching. If such did occur,
however, the trend might have been masked by uptake of nitrogen
by the vegetation in the ‘IFS. Crop uptake of N was not measured
but data in Table B—7, Appendix B suggest that for certain plots
(Plots 1 and 2), crop uptake was significant.
Table B—7 in Appendix B also reveals that inorganic N
increases, expressed on an areal basis, were greatest in the bare
areas of each plot (up to twice the original N content).
Conversely, increases in the filter areas were a maximum of
approximately 50% of original N content. This would seem to
support the notion that VFS can help minimize subsurface losses
of nitrogen despite the fact that they do tend to increase
infiltration. Likewise, leaching losses would probably have been
less in the bare source areas had a crop been actively growing
there.
Figures C—lO through C—27 in Appendix C illustrate the
variable nature of nitrogen leaching in the different plots. A
common trend exhibited, however, was a large increase in nitrate
levels in the upper profile.
33
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COMBINED SURFACE AND SUBSURFACE N LOSSES
The combined effect of surface and subsurface nitrogen
losses from all plots during tests with UAN is presented in Table
11.
TABLE 11. COMBINED N LOSSES, RUNS 1-6
Plot Filter Runoff Infiltration Total N Lost, gms
Width,m mm mm Surface Leaching Combined
1 9.2 72.50 52.57 47.2 140.0 187.2
2 4.6 116.20 66.44 257.0 1160.0 1417.0
3 0.0 103.85 73.02 131.2 1050.0 1181.2
4 9.2 72.78 98.33 90.9 780.0 870.9
5 4.6 126.53 52.57 112.3 2340.0 2452.3
6 0.0 177.98 2.86 211.2 —290.0 — 78.8
7 9.2 132.90 66.22 101.3 1150.0 1251.3
8 4.6 162.86 32.25 192.6 720.0 912.6
9 0.0 138.06 58.94 225.4 1190.0 1415.4
Two trends are apparent from data in Table 11. Firstly,
where surface (i.e. runoff) losses of nitrogen were concerned,
increased filter width resulted in decreased losses, as compared
to losses from plots with no VFS. Secondly, and perhaps more
importantly, subsurface (i.e. leaching) losses of N far
outweighed surface losses, and did not appear to be related to
VFS width. That subsurface losses were the dominant pathway for
N transport from plots was somewhat expected, considering that
runoff occurs only after infiltration and surface detention have
been satisfied by precipitation. It is assumed that as
infiltration procedes, soluble nitrogen is taken into the
profile, reducing the amount available for surface transport.
MATHEMATICAL MODELING OF VFS PERFORMANCE
A variety of factors are presumed to influence the ability
of vegetated filter strips to remove pollutants from agricultural
runoff. Some of the more important of these include:
1. Characteristics of pollutants
2. Physical characteristics of vegetation in filter
34
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3. Hydrologic characteristics of soils and vegetation
in filter and area generating runoff (source area)
4. Topographic features of source area and filters
5. Relative sizes of source and filter areas
6. Precipitation characteristics
7. Antecedent soil moisture.
Any mathematical description of VFS performance should consider
most of these. The extent to which these variables are actually
incorporated, however, can affect the complexity of the resulting
model. A range of model formats can be adopted, extending from
simplified empirical relationships to complex deterministic
models. The simplified approach was favored in this study.
Test of Existing Models
Other researchers have attempted to develop simple models
that predict pollutant reductions in runoff moving through
vegetated strips. Westerman, Overcash and Bingham (1983) reduced
the number of variables considered in their analytically derived
model of the form:
= 100 fi — (l+K)e/+Dlfh } (Eq. 1)
where:
P = percent reduction in pollutant mass
Km = ratio of filter width (downslope) to source area slope
length
D = ratio of infiltration rate to rainfall rate.
This model was developed for animal waste application sites where
both the application (source) and filter area were vegetated.
Table 3—8 in Appendix B shows results of applying this model
in this study in which the source areas were not vegetated. The
data base used included those runs in which observed pollutant
reductions were in a believable range. On average, predicted
reductions in total P and total N matched observed reductions
fairly well. The model was not able to predict the negative
reductions (i.e. increases) that were observed during several
runs. The model did not predict observed TSS reductions very
well.
Young, Otterby, and Roos (1982) developed an empirical
relationship to predict reductions in phosphorus concentrations
in runoff from animal waste application sites as it moved through
vegetated areas. The reductions were based on the “contact time”
of runoff with the grassed area. Contact time was a function of
35
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both slope and condition of the vegetated cover. The model took
the form:
D = —49.3 + 50.5 log T (Eq. 2)
where
D = percent reduction in phosphorus concentration
T = contact time in seconds.
Table B—9, Appendix B compares predictions made with this
model to observed reductions in total N and P and in TSS. As
with the model of Westerman, Overcash and Bingham (1983), this
model predicted average reductions in total P and N that were in
the range of observed reductions. Two conditions were tested:
a) a “good” filter condition, i.e. more than 75% vegetative
cover, and b) a “fair” filter condition, which assumed between
50% and 75% vegetative cover in the filter area. As with the
Westerman model, though average reductions were similar to
observed values, increases in pollutant mass were not predicted.
Reductions in TSS were not predicted well.
Development of Linear Model
An effort was made to include more variables in an empirical
model in hopes of predicting TSS reductions better than both the
Westerman and Young models. Multiple linear regression was used
to keep the resulting relationship as simple as possible.
Independent variables considered were antecedent soil moisture in
the bare source area, ratio of filter width to source area slope
length, plot slope and runoff rate per unit width of of plot.
From the data base consisting of results from all tests,
those runs which a) had reasonable observed pollutant reductions
and b) data for all four independent variables were selected for
developing the model. The data base thus included a range of
one—hour and half—hour test results. (This same data base was
used for the Westerman and Young models.)
The analysis resulted in relationships with unacceptably low
correlation coefficients. As demonstrated by these very low
correlation coefficients, the equations were worthless for
predictive purposes. After considering that the data base used
for the analysis included results of tests in which an abnormal
amount of rainfall was applied in a very short period of time, a
more realistic data base was developed that only included data
for the 1—hour tests. These tests were made at approximately 1—
week intervals and were thought to be more representative of
natural events.
Regression equations developed using the revised data base
had much—improved, but still unacceptable, correlation
36
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coefficients. That the correlation coefficients were much
improved in the revised analysis, however, indicated that the
variables investigated became less important as the frequency of
precipitation events decreased. This may occur because of any
number of factors (such as variable hydrologic response with
increased precipitation), or because the model simply failed to
adequately represent removal mechanisms.
In contrast to Equation 1 (Westerman model) and Equation 2
(Young model), linear regressions did predict TSS removals fairly
well. Even so, correlation coefficients were not high,
indicating that, as with, Equations 1 and 2, removal mechanisms
were not adequately described. This is perhaps the most
important result of the mathematical model analysis.
Neither of the linear regressions explicitly included
variables that describe the erosion and sedimentation process.
As evidenced by visual observations during the various tests,
sediment deposition was an important removal mechanism both
within and outside the filters. For example, ponding of runoff
occurred at some point on virtually all plots at the interface
between source area and VFS. During ponding, sedimentation of
eroded soil particles occurred as indicated by changes in the
topography of the bare areas at the VFS interface.
Likely, TSS removals, and perhaps some nutrient removals,
occurring at this interface were somewhat independent of VFS
width. In addition, measurements were not made during this study
that would permit an allocation of pollutant removals to
particular sites within the plot (i.e. within VFS or elsewhere).
In retrospect, it is not surprising that regression equations
based on data that ignore where pollutant removals occurred,
would fail to adequately predict such removals. A much more
complex model format based on an improved data base might be
indicated.
INVESTIGATION OF EXISTING VFS
Vegetated filter strips are a best management practice
eligible for cost—sharing under both the state supported Maryland
Agricultural Cost Share (MACS) program at 87.5% of cost and the
federal USDA Agricultural Cost—share Program (ACP) at 75% of
cost. The estimated lifetime for VFS under both programs is 10
years.
Despite the financial incentives for implementation, very
few VFS projects have been supported under the MACS program. For
example of nearly 2,000 practices cost—shared between July, 1983
and June, 1986, only 5 were filter strips (Weismiller and
37
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Magette, 1986). Statewide, in fiscal year 1985, only 25 ha (62
ac) of filter strips were included in agricultural conservation
plans developed through Maryland soil conservation districts
(Weismiller and Magette, 1986). Due to these facts, a formal
onsite investigation of VFS in Maryland was not felt justified.
Informal surveys of vegetated filter strips on several
Maryland farms, however, indicated that a wide range of
conditions exist that would result in highly variable performance
of VFS in removing pollutants from runoff. Chief among the
conditions that would diminish VFS performance is the occurrence
of concentrated flow at some point through most existing VFS. As
discussed previously, ‘IFS will perform best when runoff moves
through the filters by sheet (thin, uniform) flow. Natural
topographic features generally prevent this from occurring in
actual practice. Variations in VFS management (e.g. mowing or no
mowing), widths, type and density of vegetative cover (e.g.
riparian or farmer—planted) were all observed and would affect
performance.
38
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SECTION 8
REF ERENCES
Barfield, B. J., E. W. Toilner and J. C. Hayes. 1977. Prediction
of sediment transport in grassed media. ASAE Paper No. 77—2023.
Presented at the 1977 Annual ASAE Meeting, June 26—29, Raleigh,
North Carolina.
Barfield, B. J., E. W. Toilner and J. C. Hayes. 1979. Filtration
of sediment by simulated vegetation, I: Steady—state flow with
homogeneous sediment. Transactions of the ASAE 22(3):540—545,
548.
Bingham, S. C., P. W. Westerman, and M. R. Overcash. 1980.
Effect of grass buffer zone length in reducing the pollution from
land application areas. Trans. ASAE 23(2): 330—336
Dickey, E. C. and D. H. Vanderholm. 1981. Performance and design
of vegetative filters for feedlot runoff treatment. Proc. 4th
International Livestock Waste Symposium, ASAE Publication 2—81,
ASAE. St. Joseph, MI 49085. pp. 357—360
Dillaha, T. A. et al. 1985. Sediment and phosphorus transport in
vegetative filter strips: phase I, field studies. ASAE Paper 85—
2043. ASAE, St. Joseph, MI 49085
Doyle, R. C., G. D. Stanton, and D. C. Wolf, 1977. Effectiveness
of forest and grass buffer strips in improving the water quality
of manure polluted runoff. ASAE Paper 77—2501. ASAE, St.
Joseph, MI 49085
Edwards, W. M., L. B. Owens, D. A. Norman and R. K. White. 1981.
A settling basin — grass filter system for managing runoff from a
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265—267, 273
Haith, D. A. and R. C. Loehr, 1979. Effectiveness of Soil and
Water Conservation Practices for Pollution Control , EPA—600/3—79—
106, tJSEPA—ERL—ORD, Athens, GA, 473 pp.
Hayes, J. C. and J. E. Bairston. 1983. Modeling the long—term
effectiveness of vegetative filters as on—site sediment controls.
39
-------
ASAE Paper No. 83—2081. Presented at the 1983 Annual ASAE
Meeting, ,June 26—29, Bozernan, Montana
Hayes, 3. C., B. J. Barfield and R. I. Barnhisel. 1979.
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Hayes, J. C., B. J. Barfield and H. I. Barnhisel. 1983.
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Neibling, W. H and E. E. Alberts. 1979. Composition and yield
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273, ASAE. St. Joseph, MI 49085. pp. 254—543, 548
40
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Toliner, E. C., B. J. Barfield, C. T. Hahn and T. Y Kao.1976.
Suspended sediment filtration capacity of simulated vegetation.
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Toilner, E. C., B. J. Barfield, C. Vachirakornwatana and C. T.
Hahn. 1977. Sediment deposition patterns in simulated
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Toliner, E. C., a. C. Hayes and B. J. Barfield. 1978. The use of
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78, Institute for Mining and Minerals Research, University of
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Toliner, E. C., B. J. Barfield and J. C. Hayes. 1982.
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Westerman, P. W., M. R. Overcash, and S. C. Bingham. 1983.
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61615, 78 pp.
41
-------
APPENDIX A
SOILS DESCRIPTION
Horizon Depth, cm Description
0—22 Dark brown (10 YR 3/3) sandy loam; weak
subangular blocky and platy structure;
firable; abrupt, smooth boundry
22—34 Dark yellowish brown (10 YR 4/6) sandy
loam; weak subangular blocky structure;
firable; clear smooth boundry
34—51 Dark yellowish brown (10 YR 4/6) sandy
clay loam; moderate subangular blocky
structure; thin continuous clay films;
friable; clear smooth boundry
Dark yellowish brown (10 YR 4/6) sandy
clay loam; moderate subarigular blocky
structure; thin discontinuous clay films;
common distinct light brownish grey (2.5
YR 6/2) mottles; friable; clear smooth
boundry
Yellowish brown (10 YR 5/6) loamy sand;
weak subangular blocky structure; few
patch clay films; many distinct light
brownish grey (10 YR 6/2) mottles; very
friable
Tentative Classification: typic hapludult, fine loamy,
siliceous, mesic
Physiographic position: upland backslope
Drainage: moderately well drained
Vegetation: grasses
Parent material: coastal plain sediments
Notes: a few rounded gravels were found
throughout the profile.
Ap
BE
Btl
Bt2
BC
51—65
65—70 +
42
-------
APPENDIX B
SIMULATOR PERFORMANCE, RAW CHEMICAL DATA, VFS PERFORMANCE, TEST
OF VFS MODELS
43
-------
TABLE B-i. RAINFALL SIMULATOR PERFORMANCE
UNIFORM MEAN APP
COEFF DEPTH
cont inued
RUN
PLOT
MO
DAY
(MM)
1
1
7
18
0.918377
45.06
1
2
7
18
0.881800
49.68
1
3
7
18
0.977424
47.82
1
4
7
18
0.923715
44.13
1
5
7
18
0.924187
44.43
1
6
7
18
0.914716
44.30
1
7
7
23
0.935117
47.46
1
8
7
23
0.914585
48.53
1
9
7
23
AVG
STD
VAR
0.927674
0.924177
0.023519
0.000553
42.97
46.70
2.08
4.33
2
1
7
19
0.942788
23.28
2
2
7
19
0.935849
25.13
2
3
7
19
0.910401
22.52
2
4
7
19
0.912034
23.64
2
5
7
19
0.896723
24.11
2
6
7
19
0.897240
23.52
2
7
7
24
0.775390
27.11
2
8
7
24
0.914010
25.18
2
9
7
24
AVG
STD
VAR
0.890925
0.897262
0.046099
0.002125
24.26
24.31
1.28
1.63
3
1
7
19
0.933911
23.47
3
2
7
19
0.915736
24.57
3
3
7
19
0.932605
23.24
3
4
7
19
0.912157
21.59
3
5
7
19
0.896063
25.81
3
6
7
19
0.852941
24.47
3
7
7
24
0.951540
24.93
3
8
7
24
0.953293
24.94
3
9
7
24
AVG
STD
VAR
0.924084
0.919147
0.029088
0.000846
24.26
24.14
1.16
1.35
44
-------
TABLE 8—1.
(continued)
UNIFORM MEAN APP
COEFF DEPTH
(MM)
cant i nued
RUN
PLOT
MO
DAY
4
1
7
25
0.871220
34.71
4
2
7
25
0.867268
33.82
4
3
7
25
0.839373
33.30
4
4
7
25
0.920195
34.80
4
5
7
25
0.904417
36.42
4
6
7
25
0.920133
35.12
4
7
7
30
0.918112
50.95
4
B
7
30
0.915641
47.85
4
9
7
30
AVG
STD
VAR
0.935529
0.899098
0.030250
0.000915
50.12
39.68
7.13
50.89
5
1
7
29
0.919599
25.89
5
2
7
29
0.915369
25.45
5
3
7
29
0.888793
24.49
5
4
7
30
0.902365
22.20
5
5
7
30
0.892784
24.64
5
6
7
30
0.898770
22.37
5
7
7
31
0.924796
24.86
5
8
7
31
0.949406
24.23
5
9
7
31
AVG
910
VAR
0.925420
0.913033
0.018191
0.000330
24.79
24.32
1.19
1.41
6
1
7
29
0.943106
22.06
6
2
7
29
0.921268
23.86
6
3
7
29
0.901245
25.51
6
4
7
30
0.924396
24.76
6
5
7
30
0.905075
23.69
6
6
7
30
0.955828
25.00
6
7
7
31
0.932195
23.81
6
8
7
31
0.939680
24.37
6
9
7
31
AVG
STD
VAR
0.945159
0.929772
0.017392
0.000302
24.70
24.19
0.94
0.89
45
-------
TABLE B—i.
(continued)
UNIFORM MEAN APP
COEFF DEPTH
continued
RUN
PLOT
MO
DAY
(MM)
7
1
9
12
0.972566
42.96
7
2
9
12
0.957760
46.77
7
3
9
12
0.909972
45.85
7
4
9
10
0.892408
40.52
7
5
9
10
0.899584
44.72
7
6
9
10
0.930535
43.12
7
7
9
9
0.932262
47.43
7
8
9
9
0.927553
46.87
7
9
9
9
AVG
STD
VAR
0.921531
0.927130
0.024337
0.000592
49.68
45.32
2.63
6.89
8
1
9
13
0.923796
23.08
8
2
9
13
0.913154
23.94
8
3
9
13
0.972509
24.64
8
4
9
ii
0.932628
23.99
8
5
9
11
0.905823
24.62
8
6
9
ii
0.962408
24.02
8
7
9
10
0.749789
28.13
8
8
9
10
0.748442
29.89
8
9
9
10
AVG
STD
VAR
0.899648
0.889799
0.078589
0.006176
24.05
25.15
2.14
4.60
9
1
9
13
0.911394
23.93
9
2
9
13
0.916129
25.20
9
3
9
13
0.965812
24.77
9
4
9
11
0.906502
23.35
9
5
9
11
0.891822
24.50
9
6
9
11
0.923885
24.19
9
7
9
10
0.926493
24.76
9
8
9
10
0.916215
23.74
9
9
9
10
AVG
STD
VAR
0.887743
0.916221
0.021467
0.000460
23.60
24.23
0.58
0.34
46
-------
TABLE 8-1.
(continued)
UNIFORM MEAN APP
COEFF DEPTH
11 1 9 20
11 2 9 20
11 3 9 20
11 4 9 18
11 5 9 18
11 6 9 18
11 7 9 17
11 8 9 17
11 9 9 17
AVG
STD
VAR
0.900842
0.93483 1
0.886343
0.921372
0.957890
0.947570
0.910273
0.892910
0.942029
0.921562
0.024058
0.000578
23.45
24. 11
23.56
25.67
24.82
24.83
24.23
23.49
23. 37
24. 17
0.75
0.57
RUN
PLOT
MO
DAY
(MM)
10
1
9
19
0.926290
46.80
10
2
9
19
0.955319
47.75
10
3
9
19
0.900295
47.84
10
4
9
17
0.944357
32.26
10
5
9
17
0.935463
30.75
10
6
9
17
0.939961
32.79
10
7
9
16
0.897080
46.40
10
8
9
16
0.876453
‘+6.14
10
9
9
19
AVG
STD
VAR
0.940230
0.923938
0.024938
0.000621
46.04
41.86
7.06
49.91
12
1
9
20
0.935436
24.16
12
2
9
20
0.955319
25.42
12
3
9
20
0.897200
24.19
12
4
9
18
0.918712
26.64
12
5
9
18
0.962491
23.66
12
6
9
18
0.945985
24.43
12
7
9
17
0.910226
25.50
12
8
9
17
0.921970
23.84
12
9
9
17
AVG
STD
VAR
0.940046
0.931931
0.020297
0.000411
24.60
24.71
0.90
0.82
47
-------
TABLE 8-2. HYDROLOGIC RESPONSE OF RUNOFF PLOTS
N FILTER DATE NEAN APP HOlE HOlE INFIL INF RT RUNOFF AS
RUN SOURCE PLOT WIDTH NO DAY DEPTH LAG OUR CONT CONT RUNOFF INFILT RATE TO I OF PPT
N CNN) (NIH) (NIH) 1 7. CNN) CNN) (NN/HR1 RAIN RT
1 UAN 1 I.E 7 18 45.06 8.00 70 9.55 11.15 9.566 35.494 30.42 0.68 21.23
1 4 7 18 44.13 2.50 69 9.67 10.35 14.368 29.760 25.88 0.59 32.56
1 7 7 23 47.46 7.00 7010.00 11.90 24.806 22.658 19.42 0.41 52.26
4 1 7 25 34.71 3.30 65 12.34 12.48 14.966 19.747 18.23 0.53 43.11
4 4 7 25 34.80 3.00 58 10.89 15.90 14.292 20.506 21.21 0.61 41.07
4 7 7 30 50 ,95 5.50 7110.79 12.91 35.310 15.642 13.22 0.26 69.30
AVG 42.85 4.88 67.17 18.88 23.97 21.40 0.51 43.26
STO 6.12 2.09 4.52 8.65 6.67 5.51 0.14 15.08
VAR 37.42 4.38 20.47 74.76 44.54 30.40 0.02 227.30
7 Broiler 1 9.2 9 12 42.96 13.00 7110.57 15.21 4.547 38.413 32.46 0.76 10.58
7 Litter 4 9 10 40.52 15.00 67 8.80 15.52 9.992 30.529 27.34 0.67 24.66
7 7 9 9 47.43 5.30 73 8.92 6.61 14.514 32.916 27.05 0.57 30.60
10 1 9 19 46.80 14.50 69 16.64 16.37 20.051 26.753 23.26 0.50 42.84
10 4 9 17 32.26 17.00 4116.19 15.18 6.745 25.513 37.34 1.16 20.91
10 7 9 16 46.40 7.00 7113.21 11.67 33.625 12.772 10.79 0.23 72.47
AVG 42.73 11.97 65.33 14.91 27.82 26.37 0.65 33.68
5Th 5.27 4.30 11.04 9.79 7.94 8.28 0.28 19.90
VAR 27.79 18.52 121.89 95.85 63.07 68.51 0.08 396.0!
2 VAN 1 9.2 7 19 23.28 3.oO 47 16.73 16.73 10.592 12.691 16.20 0.70 45.49
2 4 7 19 23.64 3.50 42 18.10 16.50 9.683 13.956 19.94 0.84 40.96
2 7 7 24 27.11 4.00 42 13.69 14.87 14.788 12.322 17.60 0.65 54.55
5 1 7 29 25.89 3.00 4514.13 13.24 10.252 15.639 20.85 0.81 39.60
5 4 7 30 22.20 9.90 36 11.55 14.62 8.924 13.276 22.13 1.00 40.20
5 7 7 31 24.86 2.00 48 13.15 14.40 18.031 6.827 8.53 0.34 72.54
AVG 24.50 4.23 43.33 12.05 12.45 17.54 0.72 48.89
5Th 1.65 2.61 3.99 3.27 2.73 4.48 0.20 11.74
VAR 2.73 6.79 15.89 10.67 7.47 20.11 0.04 137.90
8 Broiler 1 9.2 9 13 23.08 6.00 4622.19 16.74 8.229 14.851 19.37 0.84 35.65
GLitter 4 9 I I 23.99 9.00 4721.54 17.56 9.384 14.611 18.65 0.78 39.11
8 7 9 10 28.13 5.00 52 22.18 16.58 17.146 10.980 12.67 0.45 60.96
11 1 9 20 23.45 7.00 4319.70 16.49 9.449 14.004 19.54 0.83 40.29
11 4 9 18 25.67 4.50 4719.04 17.66 9.590 16.081 20.53 0.80 37.36
11 7 9 17 24.23 6.00 5116.96 22.39 17.131 7.101 8.35 0.34 70.70
AVG 24.76 6.25 47.67 11.82 12.94 16.52 0.67 47.34
STD 1.71 1.46 3.04 3.79 3.0k 4.46 0.20 13.45
VAR 2.93 2.15 9.22 14.33 9.23 19.90 0.04 180.79
continued
48
-------
TABLE B—2. (continued)
N FILTER DATE MEAN APP MOIS MOIS INFIL INF RI RUNOFF AS
RUN SOURCE PLOT WIDTH NO DAY DEPTH LAG OUR CONT CDI II RUNOFF INFILT RATE TO 11 OF PPT
N (MM) (MIII) (MIII) X (MM) CMI I) (NM/HR) RAIN RI
3 UAN 1 9.2 7 19 23.4? 2.00 53 * * 13.479 9.991 11.31 0.48 57.43
3 4 7 19 21.59 1.00 51 * * 12.888 8.702 10.24 0.47 59.69
3 7 7 24 24.93 4.50 50 * * 20.973 3.953 4.74 0.19 84.14
6 1 7 29 22.06 2.50 49 * 14.64 13.646 8.418 10.31 0.47 6L85
6 4 7 30 24.76 4.00 47 e * 12.622 12.135 15.49 0.63 50.98
6 7 7 31 23.81 3.50 50 * * 18.990 4.818 5.78 0.24 79.76
AVG 23.44 2.92 50.00 15.43 8.00 9.65 0.41 65.64
STD 1.25 1.20 1.83 3.28 2.84 3.58 0.15 12.07
VAR 1.57 1.45 3.33 10.79 8.04 12.78 0.02 145.61
9 Broiler 1 9.2 9 13 23.93 6.00 5321.05 25.87 14.446 9.481 10.73 0.45 60.38
9 Litter 4 9 11 23.35 8.00 51 22.88 20.06 12.439 10.912 12.84 0.55 53.27
9 7 9 10 24.76 3.00 54 * * 19.648 5.109 5.68 0.23 79.36
12 1 9 20 24.16 6.00 52 21.47 17.99 15.352 8.812 10.17 0.42 63.53
12 4 9 18 26.64 6.50 5119.73 18.13 13.839 12.797 15.06 0.57 51.96
12 7 9 17 25.50 4.00 5017.90 18.68 20.604 4.898 5.88 0.23 80.79
AVG 24.72 5.58 51.83 16.05 8.67 10.06 0.41 64.88
SIB 1.09 1.64 1.34 3.02 2.88 3.41 0.14 11.45
VAR 1.18 2.70 1.81 9.11 8.28 11.64 0.02 131.17
I UAN 2 4.6 7 18 49.68 2.00 84 9.74 9.99 21.035 23.647 20.46 0.41 42.34
1 5 7 18 44.43 3.00 74 9.29 11.16 27.402 17.031 13.81 0.31 61.67
1 8 7 23 48.53 2.50 76 11.53 9.23 32.530 16.001 12.63 0.26 67.03
4 2 7 25 33.82 2.00 6510.91 13.00 18.085 15.731 14.52 0.43 53.48
4 5 7 25 36.42 2.00 6518.06 12.00 23.583 12.841 11.85 0.33 64.75
4 8 7 30 47.85 2.00 65 11.34 14.13 41.072 6.782 6.26 0.13 85.83
AVB 43.46 2.25 71.50 27.28 16.17 13.26 0.31 62.52
BID 6.15 0.38 7.18 7.69 6.53 4.19 0.10 13.28
VAR 37.87 0.15 51.58 59,17 42.65 17.52 0.01 176.38
7 Broiler 2 4.6 9 12 46.77 6.00 7710.48 17.59 7.519 39.251 30.59 0.65 16.08
7 Litter 5 9 10 44.72 3.00 68 8.25 13.48 8.171 36.550 32.25 0.72 18.27
7 8 9 9 46.87 4.50 8514.97 14.97 17.851 29.020 20.49 0.44 38.09
10 2 9 19 47.75 6.00 7716.63 15.23 24.452 23.300 18.16 0.38 51.21
10 5 9 17 30.75 17.00 4513.74 15.08 12.130 18.621 24.83 0.81 39.45
10 8 9 16 46.14 6.50 72 14.23 13.08 35.944 10.199 8.50 0.18 77.90
AVG 43.83 7.17 70.67 17.68 26.16 22.47 0.53 40.16
BID 5.92 4.55 12.61 10.03 10.06 8.01 0.22 20.86
VAR 35.08 20.72 158.89 100.66 101.21 64.13 0.05 435.00
continued
49
-------
TABLE 9—2. (continued)
N FILTER DATE MEAN APP MOIS HOIS INFIL INF PT RUNOFF AS
RUN SOURCE PLOT WIDTH MO DAY DEPTH LAG DUP CONT CONT RUNOFF INFILT RATE TO I OF PPT
H (MM) (MIN) (MINi I 1 (MM) (MM) (MM/HP) RAIN RI
2 UAN 2 4.6 7 19 25.13 5.50 5116.79 14.38 14.987 10.142 11.93 0.47 59.64
2 5 7 19 24.11 3.30 4416.13 16.78 19.133 4.980 6.79 0.28 79.35
2 8 7 24 25.18 1.00 64 17.82 16.24 19.661 5.519 5.17 0.21 78.08
5 2 7 29 25.45 1.50 5114.63 17.42 18.943 6.508 7.66 0.30 74.43
5 5 7 30 24.64 3.50 4910.95 14.17 15.634 9.004 11.03 0.45 63.45
5 8 7 31 24.23 1.50 50 12.78 15.61 23.521 0.711 0.85 0.04 97.07
AVG 24.79 2.72 51.50 18.65 6.14 7.24 0.29 75.34
STD 0.50 1.56 6.08 2.82 3.04 3.69 0.15 12.14
VAR 0.25 2.43 36.92 7.93 9.26 13.63 0.02 147.37
0 Broiler 2 4.6 9 13 23.94 5.00 65 21.55 19.17 13.036 10.908 10.07 0.42 54.44
9 Litter 5 9 11 24.62 12.00 45 20.44 18.28 13.148 11.473 15.30 0.62 53.40
8 8 9 10 29.89 3.30 49 19.97 19.52 19.071 10.816 13.24 0.44 63.01
11 2 9 20 24.11 4.00 47 18.56 17.54 13.500 10.613 13.55 0.56 55.99
11 5 9 18 24.82 12.00 5718.84 17.66 10.394 14.430 15.19 0.61 41.97
11 8 9 17 23.49 4.00 5017.22 11.18 20.239 3.248 3.90 0.17 86.17
AVG 25.15 6.12 52.17 14.90 10.25 11.87 0.47 59.28
STD 2.17 3.77 6.84 3.53 3.39 3.96 0.16 13.64
VAR 4.69 14.20 46.81 12.45 11.48 15.71 0.02 185.94
3 UAN 2 4.6 7 19 24.57 3.50 54 * 19.156 5.414 6.02 0.24 77.96
3 5 7 19 25.81 2.00 55 * * 22.583 3.223 3.52 0.14 87.51
3 8 7 24 24.94 1.00 70 * f 21.708 3.235 2.77 0.11 87.03
6 2 7 29 23.86 1.50 54 I * 23.998 0.000 0.00 0.00 100.58
6 5 7 30 23.69 2.00 58 * I 18.195 5.495 5.68 0.24 76.81
6 8 7 31 24.37 1.00 47 ‘ e 24.369 0.000 0.00 0.00 100.00
AV6 24.54 1.83 56.33 21.67 2.89 3.00 0.12 88.32
STD 0.71 0.85 6.94 2.31 2.24 2.40 0.10 9.39
VAR 0.50 0.72 48.22 5.32 5.02 5.77 0.01 88.16
9 Broiler 2 4.6 9 13 25.20 3.00 64 23.19 22.34 18.671 6.526 6.12 0.24 74.10
9 Litter 5 9 11 24.50 9.00 4520.58 19.88 16.954 7.549 10.06 0.41 69.19
9 8 9 10 23.74 2.50 54 e * 20.803 2.938 3.26 0.14 87.63
12 2 9 20 25.42 3.00 5520.37 18.26 17.704 7.633 8.33 0.33 69.97
12 5 9 18 23.66 6.50 6519.73 18.13 12.780 10.876 10.04 0.42 54.02
12 8 9 17 23.84 3.00 56 18.37 20.97 22.108 1.734 1.86 0.08 92.73
AVG 24.39 4.50 56.50 18.18 6.21 6.61 0.27 74.61
STD 0.70 2.42 6.70 2.98 3.07 3.18 0.13 12.73
VAR 0.50 5.83 44.92 8.90 9.40 10.11 0.02 162.09
continued
50
-------
TABLE B—2. (continued)
N FILTER DATE MEAN APP MOIS MOIS INFIL INF RT RUNOFF AS
RUN SOURCE PLOT WIDTH MO DAY DEPTH LA6 DUR CONT CONT RUNOFF INFILT RATE TO % OF PPT
N (MM) (NIN) (fIN) % % (MM) (NM) (NM/HR) RAIN RI
I UAN 3 0.0 7 18 47.82 1.50 8310.70 NA 18.883 28.933 20.92 0.44 39.49
1 6 7 18 44.30 1.00 80 3.62 NA 43.114 1.188 0.89 0.02 97.32
1 9 7 23 48.87 1.00 76 10.58 NA 32.747 16.127 12.73 0.26 67.00
4 3 7 25 33.30 2.00 5411.02 NA 21.880 11.415 12.68 0.38 65.72
4 6 7 25 35.12 2.00 69 18.17 NA 35.250 0.000 0.00 0.00 100.00
4 9 7 30 50.12 1.50 71 12.82 NA 35.627 14.496 12.25 0.24 71.08
AV6 43.25 1.50 72.17 31.25 12.03 9.91 0.22 73.43
BID 6.66 0.41 9.44 8.36 9.76 7.32 0.17 20.55
VAR 44.35 0.17 89.14 69.82 95.20 53.63 0.03 422.47
7 Broiler 3 0.0 9 12 45.85 3.00 64 9.36 NA * 45.847 42.98 0.94 0.00
7 Litter 6 9 10 43.12 12.30 76 6.95 NA 17.530 25.586 20.20 0.47 40.66
7 9 9 9 49.68 1.00 7110.29 NA 15.576 34.102 28.82 0.58 31.35
10 3 9 19 47.84 3.00 8117.09 NA 26.592 21.245 15.74 0.33 55.59
10 6 9 17 32.79 3.30 68 12.66 NA 23.846 8.941 7.89 0.24 72.73
10 9 9 19 46.04 1.30 74 15.99 NA 28.700 17.337 14.06 0.31 62.34
AVG 44.22 3.98 72.33 18.71 25.51 21.61 0.48 43.78
510 5.49 3.82 5.50 9.57 11.88 11.48 0.23 23.91
VAR 30.12 14.61 30.22 91.60 141.16 131.75 0.06 567.15
2 UAN 3 0.0 7 19 22.52 2.50 50 16.90 NA 15.217 7.304 8.77 0.39 67.57
2 6 7 19 23.52 1.50 5715.33 NA 29.423 0.000 0.00 0.00 100.00
2 9 7 24 24.26 0.50 57 15.42 NA 15.935 8.322 8.76 0.36 65.69
5 3 7 29 24.49 1.00 48 16.17 NA 14.601 9.889 12.36 0.50 59.62
5 6 7 30 22.37 1.30 3910.12 NA 21.162 1.211 1.86 0.08 94.59
5 9 7 31 24.79 0.50 4412.98 NA 18.036 6.750 9.20 0.37 72.77
AVG 23.70 1.38 53.00 18.79 6.38 7.47 0.31 73.22
SIB 0.77 0.74 4.06 6.15 3.80 4.56 0.19 15.74
VAR 0.59 0.55 16.50 37.88 14.41 20.77 0.04 247.68
8 Broiler 3 0.0 9 13 24.64 5.00 37 21.01 NA 11.161 13.477 21.85 0.89 45.30
8 Litter 6 9 11 24.02 3.00 36 17.56 NA 13.036 10.988 18.31 0.76 54.26
8 9 9 10 24.05 2.00 4920.20 NA 13.950 10.095 12.36 0.51 58.02
11 3 9 20 23.56 2.00 50 19.84 NA 12.107 11.452 13.74 0.58 51.39
11 6 9 18 24.83 1.50 5315.67 NA 21.400 3.428 3.88 0.16 86.19
11 9 9 17 23.37 1.70 4318.37 NA 15.937 7.431 10.37 0.44 68.20
AVG 24.08 2.53 44.67 14.60 9.48 13.42 0.56 60.56
SIB 0.53 1.20 6.50 3.39 3.25 5.72 0.23 13.41
VAR 0.28 1.44 42.22 11.49 10.56 32.77 0.05 179.73
continued
51
-------
TABLE 8—2. (continued)
N FILTER DATE MEAN APP MOIS 11015 INFIL INF RI RUNOFF AS
RUN SOURCE PLOT WIDTH (10 DAY DEPTH LAG OUR CONI CONT RUNOFF INFILT RATE 10 1 OF PPT
11 (MM) (MINI (11(N) 1 1 (MM) (11 (1) (MM/KR) RAIN RI
3 VAN 3 0.0 7 19 23.24 1.00 45 • NA 17.323 5.918 7.89 0.34 74.54
3 6 7 19 24.47 1.00 50 * NA 24.012 0.457 0.55 0.02 98.13
3 9 7 24 24.26 1.00 49 * NA 16.810 7.447 9.12 0.38 69.30
6 3 7 29 25.51 1.00 47 • NA 15.947 9.559 12.20 0.48 62.52
6 6 7 30 25.00 1.00 52 * NA 25.020 0.000 0.00 0.00 100.00
6 9 7 31 24.70 1.00 50 • NA 18.906 5.796 6.95 0.28 76.54
AVG 24.53 1.00 48.83 19.67 4.86 6.12 0.25 80.17
5Th 0.70 0.00 2.27 3.55 3.51 .44 0.18 14.09
VAR 0.49 0.00 5.14 12.60 12.30 19.72 0.03 198.41
9 Broiler 3 0.0 9 13 24.77 1.50 81 23.88 NA 18.771 5.994 4.44 0.18 75.80
9 Litter 6 9 11 24.19 1.00 3718.77 NA 15.590 8.604 13.95 0.58 64.44
9 9 9 10 23.60 1.00 48 * NA 12.096 11.505 14.38 0.61 51.25
12 3 9 20 24.19 2.00 5020.59 NA 10.437 13.756 16.51 0.68 43.14
12 6 9 18 24.43 1.00 5916.50 NA 24.325 0.101 0.10 .00 99.59
12 9 9 17 24.60 1.00 48 19.42 NA 16.761 7.835 9.79 0.40 68.15
AVG 24.30 1.25 53.83 16.33 7.97 9.86 0.41 67.06
STD 0.37 0.38 13.73 4.53 4.32 5.86 0.24 18.09
VAR 0.14 0.15 188.47 20.54 18.70 34.33 0.06 327.39
52
-------
TABLE 8—3. BASIC DATA - CHEMICAL ANALYSES OF RUNOFF SAMPLES
Time Run ID Plot ID NH4—N N03-N
m m mg/I mall
IKN P204—P
mg/i mg/i
TP ORGN lOIN
mo/i ma/l mg/i
159 VSS
mg/i mg/I
2 1
15 1
27 1
30 1
48 1
60 1
63 1
1 1.070
1 0.973
1 2.720
1 3.160
3 3 1 0.353
6 3 1 0.550
21 3 1 0.290
30 3 1 1.122
3 4 1*
6 4 1
9 4 1
27 4 1
54 4 1
0.879 15.500 2.560 13.200
0.349 1.610 0.360 ‘
0.070 2.910 0.160 4.510
0.856 4 1.700 I
0.035 +
0.638 3.930
0.521 4.330
0.416 1.970
0.311 1.440
0.800 4.510
0.250 5.580
0.210 2.320
0.180 2.160
0.000
11.811
0.000
2.320
0.117
0.000
6.740
10.670
8.7 10
7.940
4.019
1.771
0.000
0.000
1.420 * *
12.418 4407.0 519.0
0.000 4 I
3.968 1540.0 125.0
1.523 1682.0 148.0
2.693 721.0 83.0
10.313 *
12.610 3795.0 453.0
10.868 1453.0 144.0
9.300 1685.0 164.0
4.831 491.0 57.0
2.268 4 *
0.001 488.0 63.0
0.214 * 4
16.379 3549.0 435.0
1.959 1636.0 135.0
2.980 1369.0 123.0
0.856 1484.0 130.0
0.035 * 4
4.568 3483.0 424.0
4.851 1241.0 117.0
2.386 1419.0 153.0
1.751 403.0 58.0
continued
1 1.840 1.420 * * *
1 0.389 0.218 12.200 0.750 5.850
1* 4 4 14.000
6 2 1 1.130
9 2 1 1.690
21 2 1 0.860
33 2 1 0.281
36 2 1 0.189
39 2 1*
42 2 1 29.600
0.578 3.390 0.530 *
0.433 1.090 0.430 I
0.093 2.600 0.380 3.910
0.413 9.900 0.400 2.960
0.810 11.900 0.730 7.160
0.468 10.400 0.280 4.600
0.500 8.800 0.550 5.290
0.531 4.300 0.240 *
0.308 1.960 0.240 4.190
0.001* * +
0.214* * I
t 4
0.236
0.701
0.234
0.157
15. 147
1.060
2.620
0.000
0. uu o
3.694
3.629
1.736
1.283
2.502
2.340
1.584
1.249
2.717
0.000
0.000
4.184
1.410
3 5 1 0.118
6 5 1 0.200
18 5 1 0.146
30 5 1 0.271
33 5 1 0.193
3 6 1 0.126
6 6 1 0.412
18 6 1 0.516
30 6 1 0.110
0.278 2.620
0.290 2.540
0.102 1.730
0.069 1.520
0.079 2.910
0.342 *
0.415 *
0.479 4.700
0.089 1.520
2.898 2409.0
2.830 785.0
1.832 * *
1.589 605.0
2.989 502.0
0.220 I
0.310 0.010
0.240 0.967
0.260 0.887
0.190 0.610
0.290 *
0.410 *
0.260 4.670
0.370 11.500
195.0
77.0
67.0
49.0
0.342 3255.0 400.0
0.415 1171.0 105.0
5.179 876.0 88.0
1.609 722.0 66.0
53
-------
TABLE 8-3. (continued)
Time Run ID Plot ID NH4-N N03—n TKN P204—P TP ORG—N TOT N 159 YSS
mm mg/i mg/i mg/i gii mg/i mg/i mg/i mg/i mo/i
3 7 1 0.529 0.170 2.800 2.100 4.950 2.271 2.970 169.0 27.0
18 7 1 0.297 0.001 3.500 1.200 6.140 3.203 3.501 390.0 118.0
27 7 1 ‘ 1.490 * 6.750 ‘ 0.000 1.490 279.0 55.0
42 7 1 * 25.900 I 29.600 25.900 25.900 1095.0 238.0
51 7 1 3.510 m 128.000 * 22.500 124.490 128.000 651.0 128.0
57 7 1 14.100 0.260 21.700 5.900 14.000 7.600 21.960 653.0 153.0
60 7 1 m 0.732 * * * 0.000 0.732 * 4
3 8 1 ‘ 2.050 4 5.290 2.050 2.050 369.0 65.0
9 8 1 * 0.186 9.270 2.600 * 9.270 9.456 498.0 11.0
18 8 1 9.220 0.076 10.200 2.200 7.250 0.980 10.276 351.0 73.0
30 8 1 7.320 0.390 8.860 2.500 5.180 1.540 9.250 ‘ *
33 8 1 9.360 0.041 9.390 2.200 1.330 0.030 9.431 4 I
36 8 1 8.410 0.720 9.880 2.000 6.100 1.470 10.600 202.0 52.0
3 9 1 0.294 0.027 6.500 0.370 2.080 6.206 6.527 641.0 91.0
15 9 1 6.230 0.034 6.820 2.300 13.000 0.590 6.854 480.0 96.0
27 9 1 4.660 0.039 7.190 1.500 3.590 2.530 7.229 ‘
2 10 1 0.240 0.166 3.270 0.430 * 3.030 3.436 409.0 65.0
9 10 1 0.292 0.129 6.940 1.900 9.600 6.648 7.069 314.0 68.0
39 10 1 1.500 0.132 3.850 1.000 1.590 2.350 3.982 337.0 75.0
51 10 1 1.710 0.330 4.950 0.860 4.930 3.240 5.280 263.0 55.0
57 10 1 1.920 0.081 6.220 0.940 2.270 4.300 6.301 170.0 43.0
1 11 1 7.29 2.870 * 0.900 1 0.000 2.870 •
3 11 1 0.45 1.210 6.900 0.810 7.850 6.450 8.110 445.0 72.0
18 11 1 4.27 0.434 3.520 0.900 3.270 0.000 3.954 1 *
27 11 1 1.6 0.511 4.890 1.600 * 3.290 5.401 231.0 52.0
33 11 1 0.49 0.234 4.170 1.000 1 3.680 4.404 161.0 42.0
1 12 I * 0.518 ‘ 0.720 I 0.000 0.518 584.0 97.0
3 12 I 3.190 0.358 4.210 0.940 2.160 1.020 4.568 1221.0 232.0
15 12 1 0.451 0.142 2.300 0.680 3.610 1.849 2.442 297.0 62.0
27 L2 1 0.451 0.065 2.700 0.600 4.860 2.249 2.765 I *
36 12 1 2.770 0.070 2.790 0.680 3.070 0.020 2.860 110.0 49.0
continued
54
-------
TABLE 8-3. (continumd)
Time Run ID Plot ID NH4-N N03-N TKN P204—P TP ORG N TOT N ISS VSS
m m mg/i mg/i mg/i mg/i mg/i mg/I mg/i mg/i mg/i
6 1 2 0.990 1.310 6.200 1.400 3.050 5.210 7.510 5786.0 472.0
IS 1 2 ’ * * * * 0.000 0.000*
27 1 2 1.860 0.173 8.810 0.450 3.710 6.950 8.983 1785.0 180.0
48 1 2 1.870 0.801 86.500 0.200 8.910 84.630 87.301 1838.0 179.0
54 1 2 • 0.710 * * 0.000 0.710 m *
63 1 2 0.505 0.576 ‘ 0.170 3.210 0.000 0.576 1418.0 144.0
69 I 2 0.210 0.410 1.430 0.110 3.160 1.220 1.840 597.0 62.0
3 2 2 0.318 0.080 10.000 0.530 9.340 9.682 10.080 12279.0 1042.0
6 2 2 0.448 0.352 7.400 0.270 13.700 6.952 7.752 1830.0 185.0
15 2 2 0.338 0.274 7.100 0.710 10.300 6.762 7.374 1280.0 152.0
3 3 2 1.838 0.122 6.330 0,970 4.490 4.492 6.452 5378.0 402.0
6 3 2 1.69! 0.108 3.110 0.280 2.490 1.419 3.218 1489.0 96.0
18 3 2 1.810 0.022 3.390 0.270 8.210 1.580 3.412 1364.0 98.0
30 3 2 2.320 m 3.800 0.270 8.550 1.480 3.800 (343.0 110.0
6 4 2 0.118 ‘ 7.750 0.400 4.670 7.632 7.750 6948.0 52.0
9 1* 2 0.197 0.193 24.100 0.330 20.500 23.903 24.293 881.0 101.0
30 4 2 0.197 0.237 6.520 0.150 6.550 6.323 6.757 1968.0 223.0
48 4 2 0.412 0.109 6.230 0.140 4.170 5.818 6.339 *
54 4 2 1.230 0.133 5.950 0.140 7.260 4.720 6.083 856.0 109.0
2 5 2 0.038 8.530 0.270 5.000 8.530 8.568 4528.0 530.0
6 5 2 0.952 0.161 3.690 0.580 4.290 2.738 3.851 622.0 60.0
18 5 2 0.134 0.170 5.560 0.190 3.000 5.426 5.730 579.0 54.0
33 5 2 0.261 0.201 7.400 0.240 3.220 7.139 7.601 725.0 72.0
39 5 2 0.244 0.447 8.210 0.330 3.620 7.966 8.657 266.0 37.0
6 6 2 1.960 0.064 8.040 0.160 4.330 6.080 8.104 m *
12 6 2 3.430 0.005 7.720 0.160 5.170 4.290 7.725 1029.0 93.0
21 6 2 2.150 0.034 6.160 0.120 5.590 4.010 6.194 1020.0 94.0
33 6 2 0.811 0.005 6.090 0,170 7.550 S.279 6.095 726.0 80.0
42 6 2 0.150 0.173 15.500 0.350 4.920 15.350 15.673 180.0 20.0
continued
55
-------
TABLE 8—3. (continued)
ISS VSS
mg/i mg/i
4.700 1.642 2.183 537.0 60.0
6.040 0.641 2.345 483.0 62.0
6.580 0.000 5.740 *
7.710 9.490 13.610 794.0 97.0
12.100 22.320 26.940 924.0 145.0
12.700 10.910 17.130 601.0 95.0
10.100 20.090 26.503 * *
9.800 20.260 25.597 359.0 72.0
1.370 0.000 0.005 528.0 63.0
7.790 0.000 0.580 915.0 122.0
6.930 21.030 27.829 819.0 103.0
9.360 5.523 6.091 531.0 79.0
4.050 5.200 19.640 202.0 47.0
2 9 2 0.322
6 9 2 1.970
18 9 2 1.010
33 9 2 2.510
39 9 2 3.680
0.064 3.800
0.040 29.900
2 10 2*
12 10
33 10 2*
57 10 2 0.506
66 10 2 3.200
0.111 1.480 t
0.484 8.170 *
0.377 8.370
0.072 6.900
0.126 13.400
0.717 1.480 1.591 657.0 80.0
o.450 8.170 6.654 861.0 117.0
0.970 3.920 8.370 8.747 781.0 117.0
0.620 11.000 6.394 6.972 750.0 98.0
0.350 14.400 10.200 13.526 ft I
2 12 2 0.212 0.300 1.075
6 12 2 0.760 0.051 17.500
21 12 2 0.803 0.080 17.500
30 12 2 0.326 ft 10.100
39 12 2 0.682 ft 4.500
Time Run ID
Plot ID NH4-N
N03—N
TKN
P204—P
TP
ORG N
TOT N
mm
mg/i
mg/i
mg/I
mg/i
mg/i
mg/I
mall
3
7
2
0.438
0.103
2.080
0.780
21
7
2
0.999
0.705
1.640
0.490
27
7
2
4.024
5.740 1
2.700
36
7
2
3.710
0.410
13.200
1.500
51
7
2
4.580
0.040
26.900
2.900
60
7
2
6.190
0.030
17.100
2.600
63
7
2
6.210
0.203
26.300
9.300
66
7
2
4.840
0.497
25.100
10.400
3
8
2
11.300
0.005 1
0.200
9
8
2
18.300
0.580 *
2.700
18
8
2
6.270
0,529
27.300
2.100
30
8
2
0.537
0.031
6.060
0.510
39
8
2
14.200
0.240
19.400
2.700
0.390 2.660 3.478 3.864 1314.0 157.0
0.530 21.500 27.930 29.940 1024.0 160.0
0.176 17.000 4 7.800 15.990 17.176 829.0 97.0
0.046 15.300 0.160 4.500 12.790 15.346 2247.0 348.0
0.217 12.000 1.200 5.920 8.320 12.217 I ft
2 11
6 Ii
21 11
30 11
39 11
2 0.910
2 1.180
2 0.396
2 1.030
2 0.040 4
0.150 3.090 0.190 4.500 2.180 3.240 952.0 125.0
1.440 11.000 0.860 3.580 9.820 12.440 930.0 148.0
0.077 8.600 0.660 6.300 8.204 8.677 ft ft
0.072 11.400 0.850 3.960 10.370 11.472 * *
6.600 1.100 6.630 6.560 6.600 253.0 62.0
0.110 6.000 0.863 1.375 4 ft
0.690 11.000 16.740 17.551 955.0 143.0
0.590 7.260 16.697 17.580 685.0 99.0
0.540 13.400 9.774 10.100 828.0 118.0
0.560 2.750 3.813 4.500 204.0 55.0
continued
56
-------
TABLE 8-3. (continued)
2 7 3 3.343 17.900 4.800 11.200 17.900 21.243 3778.0 422.0
6 7 3 1.900 5.390 6.200 13.200 5.390 7.190 ‘
21 7 3 0.620 109.000 9.700 14.400 109.000 109.620 * *
39 7 3 5.860 0.686 75.900 30.000 15.000 70.040 76.586 4660.0 1120.0
57 7 3 7.840 0.266 68.200 31.000 * 60.360 68.466 4426.0 686.0
60 7 3 4.300 0.044 9.220 32.000 ‘ 4.920 9.264 1067.0 173.0
2 8 3* *
3 8 3* *
15 8 3’ *
27 8 3* *
30 8 3*
* * *
* * *
* I *
* * *
* * *
2564.0
3911.0
3191.0
1818.0
479.0
399.0
536.0
422.0
184.0
84.0
1 9 3 6.900
3 9 3 7.250
18 9 3 5.920
30 9 3 6.620
36 9 3 6.510
0.831 8.780 3.200 7.690
0.169 9.590 2.800 3.350
0.078 • 2.000 8.840
0.115 24.000 3.600 7.480
0.142 * 3.200 i
1.880 9.611 2664.0
2.340 9.759 4361.0
0.000 0.078 3402.0
17.380 24.115 1388.0
0.000 0.142 379.0
346.0
579.0
347.0
149.0
53.0
2 tO 3 3.570
9 10 3 2.420
36 10 3 4.770
60 10 3 0.287
63 10 3*
Time Run ID Plot ID NH4-N N03-N
TKN P204—P
mm mg/I mg/i mg/i m /l mg/I mg/i mg/i mg/i ma/I
IP ORGN lOIN
TSS YSS
* *
* *
* *
* *
8.020 0.930
14.000 1.300
12.400 1.300
10.900 2.200
8.110 *
4.450 8.411 611.0
11.580 14.140 4354.0
7.630 12.500 3616.0
10.613 10.990 774.0
8.110 8.212 303.0
105.0
509.0
497.0
107.0
42.0
0.39 1
0.140
0.100
0.090
0.102
1.990
0.245
1.610
0.435
0.135
0.347
1.130
0.880
0.137
0.140
0.166
2 11 3 5.800
3 11 3 2.360
6 11 3 4.150
15 11 3 2.510
30 11 3 0.517
33 11 3*
2 12 3 2.420
3 12 3 3.560
15 12 3 2.850
30 12 3 3.340
36 12 3 1.250
3.390
9.980
11.90v
10.000
1 .380
3.230
12.300
13. 100
16.600
11.800
4.94
22.000
27.400
18.800
4.860
4.190
9.270
9.110
8.900
6.940
6.210
5.39
19.100
12.200
7.680
11. 300
3.440
1.400
2.000
1.700
0.680
0.950
0.86
0.930
1.000
1.000
1.100
0.410
3.470 11.260 *
6.750 9.355 5235.0 650.0
4.750 10.510 ‘ *
4.430 7.375 * I
5.693 6,345 *
5.390 5.737 406.0 88.0
15.680 19.230 7444.0 622.0
8.640 13.080 * I
4.830 7.817 2871.0 334.0
7.960 11.440 1287.0 177.0
2.190 3.606 * *
continued
57
-------
TABLE 8—3. (continued)
Time Run ID Plot ID NH4-N N03-N T N P204-P TP ORG N TOT N TSS VSS
mg/i ma/I mg/i mg/I mg/I mg/i mo/I mg/i mg/i
2 7 3*
6 7 3*
21 7 3 ’
39 7 3 5.860
57 7 3 7.840
60 7 3 4.300
1 9 3 6.900
3 9 3 7.250
18 9 3 5.920
30 9 3 6.620
36 9 3 6.510
2 tO 3 3.570
9 10 3 2.420
36 10 3 4.770
60 10 3 0.287
63 10 3’
3.343 17.900 4.800 11.200 17.900 21.243 3778.0 422.0
1.800 5.390 6.200 13.200 5.390 7.190 * *
0.620 109.000 9.700 14.400 109.000 109.620 m
0.686 75.900 30.000 15.000 70.040 76.586 4660.0 1120.0
0.266 68.200 31.000 * 60.360 68.466 4426.0 686.0
0.044 9.220 32.000 ‘ 4.920 9.264 1067.0 173.0
* *
* *
* *
* *
* *
2564.0
3911.0
3191.0
1818.0
479.0
399.0
536.0
422.0
184.0
84.0
2 8 3* *
3 8 3* * *
15 8 3’ * * *
27 8 3 * * * *
30 8 3* * * * *
0.831 8.780
0.169 9.590
0.078 m
0.115 24.000
0.142 *
3.200 7.690
2.800 3.350
2.000 8.840
3.600 7.480
3.200 *
1.880 9.611 2664.0
2.340 9.759 4361.0
0.000 0.078 3402.0
17.380 24.115 1388.0
0.000 0.142 379.0
4.450 8.411 611.0
11.500 14.140 4354.0
7.630 12.500 3616.0
10.613 10.990 774.0
8.110 8.212 303.0
8.020 0.930
14.000 1.300
12.400 1.300
10.900 2.200
8.110 *
346.0
579.0
347.0
149.0
53.0
105.0
509.0
497.0
107.0
42.0
2 11 3
3 I I 3
6 11 3
15 11 3
30 LI 3
33 11 3*
5.800
2.360
4.150
2.510
0.517
0.391
0.140
0.100
0.090
0.102
1.990
0.245
1.610
0.435
0.135
0.347
1.130
0.880
0.137
0.140
0.166
3.390
9.980
11.900
10.000
1.380
3.230
12.300
13.100
16.600
11. 800
4.94
22.000
27.400
18. 800
4.860
4.190
9.270
9.110
8.900
6.940
6.210
5.39
18. 100
12.200
7.680
11 .300
3.440
1.400
2.000
1.700
0.680
0.950
0.86
0.930
1.000
1.000
1.100
0.4 10
2 12 3 2.420
3 12 3 3.560
15 12 3 2.850
30 12 3 3.340
36 12 3 1.250
3.470 11.260 * *
6.750 9.355 5235.0 650.0
4.750 10.510 *
4.430 7.375 * *
5.693 6.345 m
5.390 5.737 406.0 88.0
15.680 19.230 7444.0 622.0
9.640 13.080 I
4.830 7.817 2871.0 334.0
7.960 11.440 1287.0 177.0
2.190 3.606 •
continued
58
-------
TABLE 8-3. (continued)
Time Run ID Plot ID NH4-N N03-N TKN P204—P TP ORB N TOT N TSS YSS
m m mg/i ma/i mg/i mg/i mg/I mqII mg/i mg/i ma/i
4 1.030 0.065 5.270 0.270 2.880
6 2 4 1.720 0.597
9 2 4 0.334 0.185
21 2 4 0.516 0.159
36 2 4 0.640 0.059
39 2 4 0.769 0.060
3 1
9 1
18 1
39 1
48 1
63 1
4 0.204 0.537 16.900 * 14.700
4 0.330 0.089 * 0.390 *
4 2.390 0.176 ‘
4 1.740 0.158 5.970 0.290 9.200
4* * * * 15.300
16.696
0.000
0.000
4.230
0.000
4.240
3.240
8.226
12.444
8.660
2.22 1
17.437 3968.0 430.0
0.089 2624.0 330.0
0.176 1599.0 118.0
6.128 * *
0.000 * *
5.335 1442.0 148.0
5.557 3002.0 390.0
8.745 * *
13.119 1895.0 235.0
9.359 1196.0 145.0
3.050 742.0 93.0
4.960 1.700 4.610
3.560 2.700 11.600
12.960 0.350 8.340
9.300 0.580 5.590
2.990 0.300 ‘
3 3 4 0.710
6 3 4 1.410
21 3 4 1.330
36 3 4 0.911
42 3 4 0.563
0.485
0.078
0.20 1
0.306
0.072
7.880 3.500
0.340 6.340 14.790
0.200 3.730 10.480
0.210 5.780 9.209
0.210 0.424 0.917
4.210 I
16.200
11.810
10. 120
1.480
3.480
4.200
4.540
3.190
4.740
3.150
3.890
4.200
4.480
1.240
2.700
2.130
1.970
4.330
2.070
4.695 2468.0
16.278 2459.0
12.011 942.0
10.426 1061.0
1.552 531.0
4.126 2126.0
4.200 1408.0
6.660 1659.0
3.524 1149.0
5.453 438.0
8.500 909.0
7.540 1143.0
5.057 1125.0
4.690 991.0
1.976 *
6 4 4 0.403 0.646
9 4 4 0.435*
15 4 4 0.471 2.120
30 4 4 0.504 0.334
48 4 4 0.549 0.713
1 5 4 1.840 5.350
3 5 4 1.610 3.650
12 5 4 1.120 0.857
24 5 4 9.560 0.210
30 5 4 0.818 0.736
3 6 4 0.563 0.079
6 6 4 0.604 0.291
18 6 4 0.243 0.065
33 6 4 0.444 0.088
39 6 4 0.243 0.102
302.0
231.0
89.0
105.0
77.0
246.0
I 1.1.
192.0
130.0
48.0
113.0
124.0
143.0
101.0
0.210 0.247
0.220 4.940
0.190 1.670
0.170 1.670
0.210 *
0.430 2.100
0.310 6.000
0.240 6.410
0.350 6.750
0.310 e
0.210 6.480
0.320 *
0.240 *
0.270 I
0.160 1.350
3.077
3.765
4.069
2.686
4.191
1.310
2.280
3.080
0.000
0.422
2.137
1.526
1.727
3.886
1.827
*
2.779 2587.0 210.0
2.421 1074.0 115.0
2.035 1055.0 l13.0
4.418 771.0 91.0
2.172 *
continued
59
-------
TABLE 8—3. (continued)
flee Run ID Plot ID NH4—N N03-N TKN P204—P IP 0R6 N TOT N 188 VSS
eq/i eq/i eq/I ing/1 eq/I ugh mg/I eq /i eq/i
1 7 4 0.298 0.000 0.679 1.300 1.380 0.381 0.679 279.0 37.0
18 7 4 0.240 0.003 1.750 1.300 1.320 1.510 1.753 161.0 39.0
30 7 4 1.179 0.001 3.250 3.200 4.130 2.071 3.251 118.0 32.0
42 7 4 e 0.018 35.500 7.900 23.000 35.500 35.518 3497.0 798.0
54 7 4 1.700 0.133 40.200 7.800 24.700 38.500 40.333 350.0 96.0
60 7 4 1.680 0.270 45.900 * 24.600 44.220 46.170 336.0 105.0
2 8 4 2.220 0.066 1.560 0.040 e 0.000 1.626 206.0 39.0
6 8 4 • * 8.030 • 8.030 8.030 8.030 222.0 55.0
15 8 4 24.600 0.232 33.900 5.400 7.060 9.300 34.132 224.0 60.0
27 8 4 6.860 0.111 13.300 2.700 7.750 6.440 13.411 181.0 56.0
33 8 4 3.690 0.114 6.910 4.200 3.270 3.220 7.024 183.0 58.0
1 9 4 2.360 0.113 5.600 0.780 1.220 3.240 5.713 227.0 52.0
3 9 4 6.040 0.320 13.700 0.210 7.160 7.660 14.020 362.0 98.0
18 9 4 5.450 0.294 14.400 1.100 6.270 8.950 14.694 221.0 60.0
30 9 4 11.900 0.251 20.200 2.400 14.900 8.300 20.451 220.0 59.0
36 9 4 9.090 0.103 * 2.500 5.720 0.000 0.103 161.0 50.0
2 10 4 1.080 0.017 2.580 0.360 * 1.500 2.597 238.0 32.0
6 10 4 2.380 1.360 7.040 0.650 0.717 4.660 8.400 360.0 75.0
21 10 4 1.370 0.116 4.660 (‘.970 3.520 3.290 4.776 422.0 65.0
30 10 4 6.300 0.299 7.960 0.410 9.890 1.660 8.259 217.0 44.0
36 10 4 1.170 0.302 5.230 0.480 e 4.060 5.532 264.0 56.0
2 11 4 0.991 0.191 4.040 0.350 0.606 3.049 4.231 219.0 36.0
3 11 4 0.289 0.043 2.130 0.150 0.531 1.841 2.173 ‘
6 11 4 0.290 0.160 9.870 0.250 2.110 9.580 10.030 371.0 57.0
18 11 4 1.750 0.290 5.720 1.300 3.490 3.970 6.010 * *
21 11 4 1.800 0.352 12.400 0.690 5.860 10.600 12.752 ‘ *
24 11 4 1.620 0.224 3.190 0.760 5.900 1.570 3.414 e
27 11 1 , 1.260 0.181 3.830 0.810 4.150 2.570 4.011 * *
33 11 4 1.220 0.155 3.780 0.830 2.930 2.560 3.935 * *
2 12 4 1.580 0.046 1.910 0.270 e 0.330 1.956 350.0 52.0
6 12 4 1.540 0.201 13.100 1.100 * 11.560 13.301 595.0 94.0
18 12 4 1.100 0.092 2.560 0.510 2.770 1.460 2.652 353.0 59.0
30 12 4 1.200 0.065 3.600 0.970 5.900 2.400 3.665 351.0 75.0
36 12 4 0.952 0.154 5.100 0.700 1.310 4.148 5.254 232.0 57.0
continued
60
-------
TABLE 8-3. (continued)
Time Run ID Plot ID NH4—N N03—N
mm mg/i mgii
TKU P204-P
mg/i mg/i
TP ORG N TOT N 195 VSS
mg/i mg/I mg/i mg/i mg/i
2 3 5 0.366
18 3 5 0.760
33 3 5 0.798
45 3 5 0.818
4.740 0.430 t 4.374
5.390 0.480 * 4.630
3.400 0.450 4.000 2.602
2.890 0.520 4.060 2.072
5.648 7679.0 937.0
5.818 3351.0 322.0
3.465 *
3.045 1765.0 224.0
2 6 5 1.730 0.087 5.020 0.270
3 6 5 0.785 0.067 3.740 0.630
9 7 5 1.270
21 7 5 3.370
36 7 5 4.100
51 7 5 28.800
60 7 5 17.700
63 7 5 7.600
5.510 3.290 5.107 1285.0 147.0
4.540 2.955 3.807 2198.0 204.0
3
1
5
0.149
0.723
7.100
0.860
2.090
6.951
7.823
2319.0
294.0
18
1
5
0.439
0.089
8.200
0.320
5.720
7.761
8.289
1232.0
106.0
39
1
5 ‘
0.930 *
0.490
12.600
0.000
0.930
4299.0
434.0
57
1
5
2.600
0.078
4.720
0.460
8.160
2.120
4.798
1738.0
149.0
66
1
5
0.949
0.451 *
0.370
14.400
0.000
0.451
804.0
103.0
2
2
5
0.393 m
8.380
0.220
8.100
7.987
8.380
2546.0
251.0
6
2
5
0.542
3.100
0.230
5.990
2.558
4.736
2328.0
239.0
18
2
5
0.829
3.460
0.240
6.240
2.631
3.848
2138.0
209.0
33
2
5
1.620
3.490
0.270
9.260
1.870
3.571 +
+
42
2
5
1.320
3.630
0.390
3.730
2.310
3.777
843.0
104.0
1.636
0.388
0.081
0.147
0.908
0.428
0.065
0.155
0.460
1.370
0.249
0.230
0.086
0.118
0.934
0.471
0.319
5.100
14.600
10.000
4.600
6 4 5 0.197
9 4 5 0.618
27 4 5 1.040
48 4 5 0.498
2 5 5 0.157
3 5 5 0.420
15 5 5 1.620
30 5 5 0.910
36 5 5 0.341
0.320
0.450
0.260
0.200
5.560 2769.0 262.0
15.970 *
10.249 m
4.830 * I
3.440
17.400
5.020
3.090
1.400
1.900
2.060
1.710
1.670
4.903
13. 982
8.960
4.102
2.163
2.950
4.600
1.680
2.399
2.320 0.250
3.370 0.130
6.220 0.320
.590 I
2.740 0.160
2.406 643.0
3.488 1031.0
7.154 1273.0
3.061 1105.0
3.059 *
71.0
95.0
106.0
114.0
*
0.719
2.040 *
1.960
0.770
2.759
74.0
13.0
0.021
2.700
0.410
2.090
0.000
2.721
91.0
20.0
0.034
13.400
1.600
6.900
9.300
13.434
522.0
95.0
0.193
25.600
5.300
9.110
0.000
25.793 ‘
*
0.015
30.800
2.800
10.000
13.100
30.815
325.0
76.0
0.010
29.600
6.200
18.500
22.000
29.610
314.0
77.0
continued
61
-------
TABLE 8-3. (continued)
Time Run ID Plot ID l H4-N N03-N TKN P204-P IP 0R6 N TOT N TSS VSS
m m mg/i ma/i ma/i 1mg/i mg/i me/I mg/I mg/i mo/i
3 8 5 4.080 0.344 12.100 1.200 4.260 8.020 12.444 267.0 58.0
12 8 5 10.800 0.046 22.200 1.300 5.010 11.400 22.246 *
24 8 5 9.090 0.262 33.400 3.000 7.710 24.310 33.662 272.0 56.0
36 8 5 15.500 1 32.800 4.900 8.680 17.300 32.800 192.0 82.0
9 5 5.640 0.035 ‘ 1.200 3.240 0.000 0.035 332.0 58.0
3 9 5 7.220 0.046 6.810 0.960 3.610 0.000 6.856 316.0 67.0
15 9 5 10.500 0.378 25.700 2.200 7.530 15.200 26.078 264.0 35.0
30 9 5 2.900 0.056 14.700 0.460 3.800 11.800 14.756 225.0 48.0
1 10 5 1.780 1.310 3.680 * 1.050 1.900 4.990 300.0 50.0
6 10 5 3.590 0.955 7.600 0.960 2.600 4.010 8.555 307.0 63.0
lB 10 5 1.740 0.426 6.540 0.920 8.640 4.800 6.966 277.0 52.0
33 10 5 3.960 0.250 4.290 0.840 1.050 0.330 4.540 273.0 55.0
42 10 5 3.150 0.421 6.170 1.100 1.160 3.020 6.591 484.0 104.0
1 11 5 1.430 0.472 3.590 0.640 1.910 2.160 4.062 ‘
2 11 5 0.696 0.327 5.040 0.690 2.600 4.344 5.367 *
3 11 5 2.960 0.991 4.330 0.630 2.840 1.370 5.321 * *
6 11 5 1.300 1.114 4.290 0.640 2.810 2.990 5.404 ‘ *
9 11 5 1.380 0.957 4.910 0.650 2.220 3.530 5.867 *
15 11 5 ‘ 0.000 0.000 871.0 136.0
24 11 5 1.240 0.179 2.350 0.970 2.250 1.110 2.529 337.0 63.0
36 ii 5 0.991 0.152 6.060 0.810 2.270 5.069 6.212
39 11 5 1.190 0.141 4.990 0.610 2.760 3.800 5.131 172.0 37.0
1 12 5 0.334 0.156 5.490 0.230 2.950 5.156 5.646 ‘
2 12 5 2.170 0.076 4.810 0.620 1.710 2.640 4.886 4 4
3 12 5 0.138 0.036 4.020 0.520 1.490 3.882 4.056 *
6 12 5 2.870 0.154 3.830 0.680 2.640 0.960 3.984 *
9 12 5 2.310 0.094 3.440 1.300 3.420 1.130 3.534 *
18 12 5 2.540 0.103 4.900 0.710 3.070 2.360 5.003 * *
21 12 5 2.810 0.124 11.100 0.520 4.040 8.290 11.224 *
24 12 5 2.860 0.129 4.020 0.800 2.990 1.160 4.149 ‘ (
27 12 5 0.800 0.094 4.060 0.630 3.880 3.260 4.144 I
33 12 5 1.000 0.096 3.470 0.610 4.850 2.470 3.566 * *
36 12 5 2.920 0.030 3.480 0.650 3.900 0.560 3.510 *
39 12 5 1.460 0.052 3.140 0.550 0.162 1.680 3.192 172.0 37.0
conti nued
62
-------
TABLE 8-3. (continued)
Time Run ID Plot ID
m i tt
1*14—4 N03—N TKN P204-P
mg/i mg/i mg/i mg/i
TP ORGN 1014
mg/I mg/I mg/i
TSS YSS
mg/i mg/i
3 I 6 1.020
9 I 6 1.000
36 1 6 1.010
54 1 6 (.480
60 1 6 1.880
2.740 4.740 0.880 10.700 3.720 7.480 t *
0.899 8.980 0.400 15.200 7.980 9.879 * *
0.534 8.290 0.260 11.000 7.280 8.824 10059.0 1035.0
0.169 24.900 0.440 9.230 23.320 24.969 6411.0 457.0
0.153 4.300 1.200 6.700 2.420 4.453 1544.0 150 ,0
2 6 2.120
2 2 6 2.370
18 2 6 1.460
30 2 6 1.120
39 2 6 0.949
0.233 14.500 +
0.743 *
0.493 11.500
4.840 5.800
0.648 2.780
23.100 12.380 14.733 10161.0 852.0
1.300 * 0.000 0.743 10941.0 766.0
0.600 11.200 10.040 11.993 6911.0 355.0
0.610 9.060 4.680 10.640 378.0 55.0
0.630 3.550 1.831 3.428 475.0 34.0
1 3 6 2.280
2 3 6 (.660
l B 3 6 1.470
30 3 6 1.460
33 3 6 2.360
1.010 14.200
1.030 11.600
0.267 5.880
0.349 3.790
0.147 2.500
0.660 12.800 11.920 15.210 8876.0 737.0
0.750 14.300 9.940 12.630 *
0.390 17.100 4.410 6.147 6770.0 472.0
1.600 10.200 2.330 4.139 3591.0 268.0
0.370 1.710 0.140 2.647 748.0 81.0
2 4 6 2.390
6 4 6 +
27 4 6 1.110
45 4 6 0.224
48 4 6 0.696
5.140 8.330
2.400 7.210
0.313 3.270
0.276 2.990
0.084 7.110
0.170 * 5.940 13.470 29289.0 2047.0
0.230 12.100 7.210 9.610 7536.0 518.0
0.410 11.900 2.160 3.593 4348.0 299.0
0.310 6.030 2.766 3.266 1417.0 (07.0
0.990 7.110 6.414 7.194 315.0 36.0
1 5 6 2.260
3 5 6 3.940
18 5 6 1.350
30 5 6 0.603
33 5 6 0.200
16.400 18.900
6.710 (4.800
1.080 4.990
0.446 8.350
0.399 2.090
0.250 7.170 16.640 35.300 5200.0 466.0
0.410 7.160 10.860 21.510 6337.0 473.0
0.230 4.790 3.640 6.070 12139.0 823.0
0.100 5.760 7.747 8.796 1893.0 151.0
0.180 3.160 1.890 2.489 436.0 51.0
1 6 a 1.180
2 6 6 1.110
18 6 6 2.000
30 6 6 2.100
33 6 6 2.000
3.230 11.100
2.330 9.800
0.333 7.240
0.298 5.440
0.290 1.110
0.360 8.940 9.920 14.330 6589.0 1682.0
0.230 7.150 9.690 12.130 4726.0 341.0
0.860 5.300 5.240 7.573 6154.0 314.0
0.250 8.130 3.340 5.738 4731.0 249.0
0.980 * 0.000 1.400 * *
continued
63
-------
TABLE 8—3. (continued)
Time Run ID Plot ID NH4-N N03-N TKN P264-P IP ORG N TOT N TSS VSS
mg/i mg/I mg/i mg/I 09/i mg/i ogil mg/I mg/i
2 7 6 9.880 0.958 17.400 * 3.730 7.520 18.358 2498.0
l8 7 6 3.140 0.127 9.200 1.900 8.120 6.060 9.327 1125.0
33 7 6 8.720 * 53.200 7.200 * 44.480 53.200 3590.0
45 7 6 17.500 0.200 I 11.100 I 0.000 0.200 3578.0
57 7 6 6.030 * 3.900 19.500 0.000 0.000 8317.0
3 8 6 12.200 0.085 20.400 9.300 4.970 8.200 20.485 4307.0
6 8 6 m 20.700 I * 20.700 20.700 4831.0
18 8 6 9.870 0.228 46.000 2.100 16.700 36.130 46.228 3706.0
30 8 6 8.710 0.384 23.300 5.500 11.800 14.590 23.684 1199.0
33 8 6 23.500 0.239 11.100 5.300 12.700 0.000 11.339 334.0
2 9 6 0.988 0.270 24.900 0.960 15.300 23.912 25.170 5025.0
3 9 6 14.600 0.239 34.200 3.500 18.800 19.600 34.439 5560.0
18 9 6 3.880 0.001 31.800 1.900 16.700 27.920 31.901 4196.0
30 9 6 * * 106.000 • 8.560 106.000 106.000 1841.0
1 12 6 0.463
3 12 6 3.170
18 12 6 2.690
33 12 6 2.320
36 12 6 0.216
5.410 24.300
0.331 20.000
0.243 16.900
0.208 7.680
0.197 12.000
0.128 14.100
0.109 15.200
0.369 10.400
8.250 *
1.320 8.250
0.290 20.200
0.423 15.900
0.580 5.200
0.796 6.200
1.300 5.740 20.420
1.100 11.000 17.020
1.400 12.500 14.740
1.800 3.930 4.500
0.800 10.500 8.420
0.930 9.430 12.120
0.650 9.480 10.960
0.640 8.100 6.200
7.050 8.250
0.870 11.300 7.787
0.950 18.300 17.030
0.750 9.310 13.210
0.620 3.130 2.880
0.850 4.920 5.994
29.710 m
20.331 4473.0 515.0
17.143 *
7.888 3427.0 332.0
12.197 * *
14.228 I
15.309 I *
10.769 *
8.250 321.0 69.0
9.570 2817.0 403.0
20.490 4839.0 650.0
16.323 3169.0 415.0
5.780 507.0 81.0
6.994 233.0 65.0
continued
274.0
128.0
503.0
553.0
980.0
552.0
495.0
348.0
134.0
67.0
511.0
927.0
625.0
138.0
998.0
583.0
452.0
53.0
3 10 6 0.774*
9 10 6 6.200
27 10 6*
36 10 6 1.690
39 10 6 1.380
45 10 6 2.360
14.700
2.340 21.300
0.102 9.230
0.131 3.760
0.257 11.900
0.742 5.540
0.390 21.700 13.926
2.900 14.600 15.100
1.700 8.160 9.230
1.200 6.240 2.070
1.500 10.700 10.520
1.500 1.160 3.180
14.700 7794.0
23.640 3990.0
9.332 3549.0
3.891 *
12.157 *
6.282 290.0
2 11 6
3 11 6
15 ii 6
18 11 6
21 ii 6
24 11 6
27 11 6
30 11 6
33 Ii 6*
3.880
2.980
2.160
3.180
3.580
1.980
4.240
4.200
*
64
-------
TABLE 8—3. (continued)
Time Run ID Plot ID NH4—N N03—N
m m mg/i mg/i
TKN P204-P
mg/i mg/i
TP OR6N TOTN
mg/i mm/i mg/i
TSS VSS
mg/i mg/I
3 1 7 2.280 0.380 2.780 1.400 * 0.500 3.160 5230.0
6 1 7 * 0.482 3.320 1.900 6.600 3.320 3.802 2591.0
33 1 7 3.820 m 5.610 * 7.770 1.790 5.610 2884.0
54 I 7 3.790 * 13.300 0.860 10.900 9.510 13.300 2046.0
60 1 7 1.550 0.019 6.040 0.410 * 4.490 6.059 1128.0
2 2 7*
3 2 7*
18 2 7
30 2 7*
33 2 7*
* * *
* * *
1.210 0.296 4.660 •
* * *
* * *
* I *
* * *
5.790 3.450 4.956 *
* * *
* I *
5088.0 351.0
1846.0 165.0
*
1879.0 152.0
1296.0 117.0
2 3 7 1.720
3 3 7 2.790
18 3 7 0.502
27.300 27.682 1155.0
34.400 34.407 1213.0
8.730 8.768 999.0
142 .0
159.0
127,0
294.0
222.0
246.0
210.0
136.0
0.610
0.352
0.270
3.760
3.110
2.170
0.870
0.460
0.250
4.670
4.520
4.310
2.040
0.320
1.668
4.370
3.462
2.440
3150.0
1662.0
2698.0
281.0
160.0
231.0
2
3
33
60
6m
4
4
4
4
4
7
7 m
7
7 *
7 *
0.623
0.471
0.952
0.877
0.494
0.478
0.387
6.940 *
4.090
3.150
3.270
5,100
0.930
0.350
0.180
0.300
0.933
1.180
7.260
4.410
3.420
6.317
4.090
2.679
3,270
5.100
7.892
4.967
3.644
3.748
5.487
1340.0
1299.0
2270.0
1573.0
846.0
115.0
144.0
206.0
132.0
94.0
3
6
18
33
39
5
5
5
5
5
7 •
7
7
7 m
7
0.955
0.592
0.569
0.297
0.781
0.304
0.044
0.256
3.800
4.090
6.090
1.640
3.800 *
0.260 t
0.270
0.290
0.180 *
14.800
12.900
2.910
3.800
3.135
5.498
1.640
3.231
4.097
4.871
6.394
1.684
4.056
4609.0
1842.0
2116.0
1828.0
1002.0
378.0
162.0
194.0
169.0
97.0
2
3
33
36
6
6
6
6
7 •
7
7 *
7
0.271
0.725
0.382
0.379
0.364
0.381 *
1.560 *
2.740
1.320
0.420
0.230
0.260 *
0.081
0.857
0.076
1.560
2.469
1.320
0.000
1.942
3.119
1.684
0.381
6436.0
2280.0
1846.0
1028.0
491.0
63.0
183.0
118.0
3
15
27
45
60
63
7
7
7
7
7
7
7
7
7
7 m
7 *
7 *
0.746 *
0.919
0.565
0.876
0.333
0.382
0.007
0.038
15.450
5.600
4.510
27.300
34.400
8.730
0.550
0.760 m
3.400
4.200
4.500
3.600 *
7.890
3.530
16.900
15.600
14.704
4.681
3.945
15.450
6.476
4.843
544.0
110,0
136.0
57.0
20.0
23.0
continued
65
-------
TABLE 9-3. (continued)
flee Run ID P1Dt ID NH4—N
em eq/i
2 8 7*
6 8 7 5.080
18 8 7 5.080
30 8 7 11.100
39 8 7 10.700
1 9 7 7.560
2 9 7 7.040
15 9 7 6.480
30 9 7 7.880
39 9 7 9.360
3 10 7 2.810
6 10 7 3.480
30 10 7 0.603
60 10 7 1.820
66 10 7 0.478
N03-N TkN P204-P TP 0R8 N TOT N 188 VSS
eq/i eq/i eq/I eq/I eq/I eq/I eq/i eq/I
0.284
0.092
0.422
0.217
0.243
0.185
0.187
0.389
0.202
0.200
0.773
0.764
0.241
0.428
0.128
4.210
5.150
12.700
17.700
24.400
17.400
8.940
11.700
8.570
8.860
10. 300
12.700
3.930
4.530
2.660
0.220 6.990
1.500 *
3.600 5.330
2.800 5.670
2.300 5.200
3.200 25.300
2.800 3.000
0.340 11.100
0.980 1.320
2.600 5.590
1.100 7.470
1.000 8.370
0.900 0.892
1.500 0.672
0.490 0.502
4.494 474.0 48.0
5.242 351.0 40.0
13.122 993.0 84.0
17.917 1165.0 116.0
24.643 331.0 52.0
17.585 2533.0 266.0
9.127 1489.0 154.0
12.089 2359.0 213.0
8.772 1787.0 186.0
9.060 * *
11.073 1093.0 121.0
13.464 1061.0 115.0
4.171 * *
4.958 503.0 59.0
2.788 435.0 63.0
7.470 26990.0 2598.0
13.900 1267.0 130.0
4.820 1698.0 125.0
3.977 1824.0 183.0
3.359 e
1 11 7*
3 11 7*
15 Il 7 0.721 0.390
30 11 7 2.230 0.187
36 11 7 1.320 0.279
4.210
0.070
7.620
6.600
13.700
9.840
1.900
5.220
0.690
0.000
7.490
9.220
3.327
2.710
2.182
7.470
13.900
3.709
1.560
1.760
3.130
7.260
4.480
2.870
1.590
0.000
13 .6 10
0.000
14.640
1.108
7.470 * *
13.900 * 17.800
4.430 0.620 11.900
3.790 0.910 4.950
3.080 1.000 7.170
1 12 7 2.610
2 12 7 1.400
15 12 7 1.480
30 12 7 1.160
36 12 7 1.300
0.713
5.740
1.800 *
0.822
8.660
1.400 *
0.563
5.960
2.400 •
0.396
4.030
1.300 •
0.326
2.890
1.100 *
12 1 8 0.457 0.151 * 0.870 •
15 1 8 1.800 0.482 15.410 1.930 9.150
39 1 8* 0.100* * *
60 1 8 1.150 0.222 15.790 0.140 7.580
63 1 8 0.412 * 1.520 0.250 0.892
6.453 2249.0
9.482 1484.0
6.523 1879.0
4.426 1089.0
3.216 477.0
0.151 2816.0
15.892 4760.0
0.100 5459.0
16.012 3406.0
1.520 2136.0
194.0
137.0
134.0
106.0
66.0
296.0
416.0
383.0
285.0
161.0
continued
66
-------
TABLE 8—3. (continued)
TKN P204—P TP 0R6 N TOT N
mg/i mg/i mg/i mg/i mg/i mg/i mg/i
TsS vss
mg/i mg/I
3 3 8 3.930 0.548 9.350
6 3 8 2.040 0.307 2.340
21 3 8 1.970 0.158 3.320
33 3 8 2.240 0.155 5.190
36 3 8 0.502 0.262 *
39 3 8 1.450 0.055 2.210
1.686
14.739
0.000
6.880
0.000
2.409 * *
15.959 2959.0 241.0
0.141 2948.0 201.0
8.120 *
0.133 * *
3.690
0.000
3.323
7.338
7.620 2842.0 232.0
0.363 3347.0 234.0
4.122 5478.0 353.0
7.999 904.0 91.0
2 7 8
3 7 8
15 7 8
27 7 8
45 7 8
60 7 8
66 7 8
14.327 * *
5.650 988.0
8.670 720.0
9.933 1641.0
97.0
76.0
205.0
317.0
304.0
109.0
mm
Time Run ID Plot ID NH4—N N03—N
3 2 8 0,204 0.519 1.890 0.210 0.395
6 2 8 0.261 0.959 15.000 0.940 13.100
18 2 8 2.980 0.141 * 0.270 *
36 2 8 * 1.240 6.880 0.930 5.710
39 2 8 1.920 0.133 m 0.170 *
0.330 15.700
0.320 0.431
0.320 2.790
0.490 4.370
0.250 *
0.320 1.320
5.420
0.300
1,350
2.950
0.000
0.760
9.898 5008.0 347.0
2.647 2297.0 178.0
3.478 4381.0 333.0
5.345 * *
0.262 1607.0 139.0
2.265 m *
6 4 8 1.090 2.850 4.780 * 1.490
9 4 8 0.958 0.363 * 0.310 ‘
42 4 8 0.357 0.442 3.680 0.270 6.890
66 4 8 0.502 0.159 7.840 0.270 1.250
2 5 8 0.060 0.856 1.600
3 5 8 0.877 1.300 2.620
18 5 8 0.909 * 12.000
33 5 8 0.451 0.148 19.200
39 5 8 0.465 0.508 2.620
2 6 8 0.524 0.087 7.020
3 6 8 1.810 * 4.540
18 6 8 0.283 0.305 1.240
33 6 8 0.334 0.154 1.810
39 6 8 0.384* *
0.250 0.276
0.210 0.247
0.260 0.644
0.280 1.210
0.260 20.000
0.380 *
0.220 *
0.260 0.502
0.200 0.005
0.310 1.640
1.540
1.743
11. 091
18.749
2.155
6.496
2.730
0.957
1.476
0.000
2.456 4542.0 292.0
3.920 2566.0 168.0
12.000 2347.0 172.0
19.348 t
3.128 * i
7.107 4942.0 333.0
4.540 2632.0 205.0
1.545 2750.0 231.0
1.964 1529.0 138.0
0.000 532.0 70.0
3.550 0.627 13.700 * 6.140 10. 150
1.420 0.150 5.500 0.540 3.760 4.080
4.720 0.480 8.190 4.100 6.270 3.470
8.580 0.123 9.810 2.700 9.430 1.230
2.610 0.014 31.200 * 22.100 28.590 31.214 3240.0
12.400 0.220 29.700 6.600 16.600 17.300 29.920 2793.0
18.300 0.416 43.300 6.600 12.100 25.000 43.716 748.0
continued
67
-------
TABLE 8-3. (continued)
lime Run ID P1 t ID NH4-N N03-N aN P204-P TP ORG N TOT N TSS YSS
m m ma/i mg/I mg/I mg/i ma/l mg/i ma/l mg/i mg/i
5.300
5.080
5.320
2.100
1.390
2.979
4.590
22.150
2.790
4.770
1. 60
1.920
3.920
1.310
15.800
0.950
0.000
0.000
17.870
0.000
[ 8.320
17.050
47.910
0.000
4.810
3.707 m
10.600 2080.0 185.0
24.707 11082.0 865.0
4.936 1251.0 108.0
4.770 1290.0 158.0
3.996 ‘
3.560 *
6.390 3727.0 289.0
3.030 2972.0 181.0
17.742 1645.0 104.0
3.309 387.0 61.0
1.878 4638.0 421.0
0.093 10527.0 692.0
21.370 * *
0.122 1868.0 131.0
26.630 5932.0 515.0
21.720 8271.0 586.0
50.249 9957.0 614.0
2.776 *
4.828 1371.0 132.0
continued
5.320 7.337 976.0 108.0
3.450 9.596 *
7.720* * *
7.760 7.817 2406.0 208.0
7.534 8.093 m
10.773 10919.0 676.0
47.754 5556.0 400.0
6.040 4101.0 305.0
22.950 3126.0 263.0
22.211 860.0 101.0
10. 700
47 • 700
6.010
19.130
12. 320
5.330
4.730
3.320
3.443
7.801 1059.0
7.744 1723.0
5.290 1181.0
4.457 446.0
113.0
170.0
127.0
69.0
2 8 8 1.910 0.107 7,230 0.890
3 8 8 6.060 0.086 9.510 2.500
18 8 8 ‘ 0.152 7.720 2.100
30 8 8 * 0.057 7.760 *
36 8 8 0.506 0.053 8.040 *
1 9 8 * 0.073 10.700 + 8.270
2 9 8 • 0.054 47.700 * 19.500
18 9 8 * 0.030 6.010 1.100 2.130
30 9 8 3.470 0.350 22,600 1.500 13.700
36 9 8 9.780 0.111 22.100 4.400 6.950
1 10 8 1.410 1.061 6.740 1.800 2.490
6 10 8 2.500 0.514 7.230 1.200 3.490
57 10 8 1.970 * 5.290 1.200 1.490
63 10 8 0.877 0.137 4.320 0.820 0.717
1 11 8 0.591 0.137 3.570 0.150 32.670
3 11 8 3.270 2.740 7.860 0.580 •
15 11 8 2.05 0.507 24.2 2.5 22.34
30 11 8 2.110 0.036 4.900 0.550 *
33 11 8 m * 4.770 ‘ 18.700
36 U 8 1.700 0.636 3.360 0.720 u.349
1 12 8 1,640 * 3.560 0.720 2.420
2 12 8 1.230 [ .240 5.150 0.680 1.250
15 12 8 1.720 * 3.030 0.630 0.040
30 12 8 1.800 0.142 17.600 0.740 8.110
39 12 8 1.590 0.769 2.540 0.860 6.250
3 1 9 4.410 0.698 1.180 0.740 15.900
39 1 9 4.180 0.093 * 0.320 3.230
60 1 9 3.430 0.070 21.300 * 24.000
63 1 9 0.651 0.122 * 0.240 4.110
1 2 9 5.480 2.830 23.800 0,470 14.000
3 2 9 3.650 1.020 20.700 0.930 14.200
18 2 9 2.090 0.249 50.000 0.820 m
30 2 9 3.650 0.236 2.540 * *
33 2 9 * 0.018 4.810 0.390 28.oOO
68
-------
TABLE 9-3. (continued)
Time Run ID Plot ID
elm
NH4-N P103-N
mg/I mg/i
TKN P204-P
mg/I mg/i
TP ORG N TOT N TSS VSS
mg/i mg/i mg/i mg/i mg/I
I 3 9
3 3 9
18 3 9
30 3 9
33 3 9
1 4 9 1.330
2 4 9 1.880
33 4 9 0.875
63 4 9 1.180
5 9 1.950
3 5 9 2.330
15 5 9 0.589
30 5 9 0.337
33 5 9 0.452
5.690 7.430 0.300 5.900
0.106 14.400 0.340 13.700
0.134 9.350 0.500 13.100
0.068 3.800 0.530 3.880
1.910 0.085 25.700 0.340 13.600
1.320 m 8.040 0.470 5.930
1.560
2.170
1.970
0.556 30.800 1.700 *
0.649 6.030 0.330 9.770
0.040 3.760 0.490 5.050
I 6 9 0.707
3 6 9 0.774
15 6 9 0.591
30 6 9 1.550
33 6 9 0.320
7.220 13.500 0.340 10.500
5.050 5.440 * 7.180
1.090 5.560 • 5.820
0.313 3.230 0.380 2.480
0.092 m 0.240 •
1.231 6.740 1.100 6.850
0.548 6.780 0.860 9.490
0.049 8.080 * 12.200
0.592 * 0.350 *
0.142 2.790 0.250 3.190
0.801 * 1.300 4.370
0.140 3.530 0.860 3.640
1.150 4.380 * *
23.790
6.720
29.240
3.860
1.790
6.100
12.520
8.475
2.620
11 .550
3.110
4.97 1
2.993
0.000
6.033
6.006
7.489
0.000
2.470
0.000
3.530
4.390
53.200
0.960
51. 650
5.060
12.270
10.780
6.760
8.7 10
8.960
25. 180
17. 140
10.000
9*
94
9*
2 7
15 7
27 7
45 7
60 7
63 7
25.785 10540.0
8.040 7839.0
31.356 10415.0
6.679 3417.0
3.800 1561.0
13.120 2533.0
14.506 6832.0
9.484 7096.0
3.868 1510.0
20.720 6491.0
10.490 6462.0
6.650 *
3.543 4011.0
0.092 1184.0
7.971 7694.0
7.328 6892.0
9.129 7010.0
0.592 4505.0
2.932 1165.0
0.801 1438.0
3.670 1249.0
5.530 11427.0
53.200 9860.0
2.907 4224.0
54.435 1427.0
7.775 2224.0
13.359 7060.0
17.439 7277.0
12.902 1334.0
15.408 3419.0
17.492 10255.0
28.883 9459.0
26.152 6238.0
21.291 1311.0
771.0
486.0
616.0
226.0
137.0
299.0
688.0
451.0
170.0
458.0
387.0
270.0
114.0
663.0
411.0
356.0
259.0
109.0
123.0
159.0
1374.0
910.0
404.0
162.0
245.0
644.0
545.0
129.0
315.0
620.0
65L.0
392.0
120.0
9 * 53.200 * 34.800
9 1.540 0.407 2.500 8.800 23.200
9 2.050 0.735 53.700 9.300 23.600
8 9 2.620 0.095 7.680 0.340 3.910
3 8 9 1.030 0.059 13.300 3.700 6.570
18 8 9 6.620 0.039 17.400 3.200 21.300
33 8 9 6.140 0.002 12.900 3.900 10.900
1 9 9 6.590 0.108 15.300 2.100 13.600
2 9 9 8.440 0.092 17.400 1.800 7.760
18 9 9 3.620 0.083 28.800 2.800 22.300
30 9 9 9.860 0.152 26.000 2.600 18.600
33 9 9 11.100 0.191 21.100 1.500 10.100
continued
69
-------
TABLE 8-3. (conhnued)
*qil
ffigil mg/i mg/i mg/I mg/i
2 10 9 2.060 0.285 12.200 0.980 12.000 10.140 12.485 1521.0 184.0
6 10 9 4.520 1.270 29.700 1.200 * 25.180 30.970 6078.0 509.0
36 10 9 * * * ‘ 0.000 0.000 5710.0 410.0
60 10 9 1.730 0.574 5.840 0.580 5.860 4.110 6.414 2347.0 195.0
63 10 9 2.100 0.205 6.490 ‘ 6.220 4.390 6.695 886.0 114.0
1 11 9 1.120 7.700 10.500 0.760 0.328 9.380 18.200 3581.0 318.0
2 11 9 1.080 4.840 9.860 * 0.936 8.780 14.700 6145.0 444.0
18 11 9 1.280 0.132 31.200 0.570 45.600 29.920 31.332 5161.0 395.0
30 11 9 * * 10.100 0.730 1.380 10.100 10.100 2912.0 231.0
1 12 9* 8.410*
2 12 9 7.260 0.113 10.800
18 12 9 1.810 0.162 1.640 *
33 12 9’ ‘ *
36 12 9 1.180 0.218 12.100 *
12.600 8.410 8.410 5389.0 453.0
1.800 12.900 3.540 10.913 7294.0 502.0
11.900 0.000 1.802 6339.0 412.0
0.720 * 0.000 0.000 928.0 77.0
15.800 10.920 12.318 737.0 86.0
Time Run ID Plot ID NH4-N N03—N
*0/1
TKN P204-P
mg/i
TP ORGN TOTN
189 V9S
1118 / I
70
-------
TABLE 8-4. CALCULATED NASS LOSSES IN RUNOFF
FILTER
RUN NITROGEN PLOT WIDTH NH4 N03 TKN £205 TP ORB-N TN TSS VSS
SOURCE g s qes g s gms g s q s gms ps qms
1 VAN 1 9.2 2.034 0.710 3.990 0.763 14.573 1.956 4.700 2605.382 234.93
1 4 4.270 0.354 18.293 0.748 27.609 14.023 18.647 1935.16 160.103
1 7 14.919 1.000 31.400 5.392 36.287 18.315 31.767 10863.49 973.757
4 1 0.785 1.064 5.934 0.548 7.472 5.149 6.998 3139.856 348.397
4 4 1.234 2.211 9.708 0.460 4.555 8.474 11.919 2718.528 302.888
4 7 1.504 3.545 20.725 2.756 30.907 19.221 24.270 11322.16 1051.736
AVG 4.12 1.48 15.01 1.78 20.23 11.19 16.38 5430.76 511.97
STD 4.95 1.08 9.52 1.80 12.02 6.49 9.56 4021.39 359.54
VAR 24.55 1.18 90.67 3.23 144.46 42.07 91.42 16171595.50 129271.25
7 Broiler 1 9.2 2.144 0.684 34.471 4.771 17.954 32.327 35.155 591.738 126.449
7 Litter 4 2.110 0.082 41.032 9.711 26.523 38.922 41.114 2314.63 536.88
7 7 0.000 0.762 56.716 9.752 32.902 56.716 57.478 2244.055 285.771
10 1 4.046 0.564 17.153 4.266 15.776 13.107 17.717 1071.29 233.723
10 4 3.046 0.550 6.888 0.880 4.927 3.842 7.438 443.957 79.27
10 7 8.834 2.319 34.531 6.172 14.274 25.697 36.850 4557.706 506.884
AVG 3.36 0.83 31.80 5.93 18.73 28.44 32.63 1870.56 294.83
510 2.73 0.70 16.10 3.12 8.96 17.19 16.18 1406.35 174.26
VAR 7.48 0.49 259.30 9.76 80.21 295.37 261.77 1977810.78 30364.92
2 UAN I 9.2 1.775 0.903 14.843 0.747 8.910 13.068 15.746 2499.944 248.854
2 4 0.849 0.242 18.403 1.550 14.024 17.554 18.645 3229.105 404.739
2 7 3.070 0.751 11.824 0.000 14.692 8.754 12.575 4749.64 40 .036
5 1 0.343 0.214 3.266 0.449 1.354 2.923 3.480 1185.037 123.529
5 4 5.701 2.134 6.258 0.453 9.600 0.557 8.392 1648.166 190.411
5 7 2.126 1.109 13.823 0.796 36.042 11.697 14.932 5631.47 520.762
AVG 2.31 0.89 I1.4& 0.67 14.10 9.09 12.30 3157.23 315.39
STD 1.75 0.64 5.16 0.47 10.74 5.85 5.04 1594.87 138.37
VAR 3.07 0.42 26.59 0.22 115.24 34.20 25.37 2543607.25 19146.07
continued
-------
TABLE 8-4. (continued)
FILTER
RUN NITROGEN PLOT WIDTH NH4 N03 TKN P205 TP 0R6-N TN 155 ‘JSS
SOURCE g s qes qm5 g s q s g s q s q s ges
B Broiler 1 9.2 12.258 0.265 13.637 3.305 8.953 1.379 13.902 ‘*79.749 104.387
B Litter 4 24.622 0.269 34.043 6.026 11.752 9.421 34.312 337.557 92.949
8 7 19.544 0.829 35.362 8.194 16.947 15.818 36.191 2503.188 233.632
11 1 4.62 0.998 7.353 1.646 3.568 2.733 8.351 499.714 107.836
11 4 2.299 0.380 9.864 1.428 6.494 7.565 10.244 610.39 93.782
11 7 3.068 1.018 19.735 2.011 35.383 16.667 20.753 7083.781 635.585
AVG 11.07 0.63 20.00 3.77 13.85 8.93 20.63 1919.06 211.36
STD 8.56 0.33 ll.08 2.52 10.50 5.84 11.05 2426.09 195.99
VAR 73.24 0.11 122.74 6.33 110.25 34.14 122.21 5885912.78 38411.51
3 UAN 1 9.2 1.382 0.854 5.972 1.523 14.681 4.590 6.826 3400.853 296.32?
3 4 2.736 0.436 27.012 0.516 10.476 24.276 27.448 2867.249 273.599
3 7 4.011 1.063 0.759 1.122 15.724 4.748 9.822 15513.16 811.318
6 I 0.852 0.798 8.635 0.766 16.022 7.783 9.433 2096.278 199.738
6 4 0.837 0.276 5.584 0.574 9.250 4.747 5.860 2213.625 238.5
6 7 1.510 1.213 6.701 1.082 1.560 5.191 7.914 5194.232 520.728
AV6 1.89 0.77 10.44 0.93 11.29 8.56 11.22 5214.23 390.04
STD 1.14 0.33 7.51 0.35 5.05 7.12 7.39 4718.59 214.50
VAR 1.30 0.11 56.37 0.12 25.51 50.63 54.58 22265045.01 46012.39
9 Broiler 1 9.2 12.164 0.087 17.177 4.350 19.776 5.013 17.264 1233.348 236.631
9 Litter 4 15.179 0.602 33.487 2.594 17.628 18.308 34.089 540.667 141.475
9 7 23.876 0.984 34.342 3.397 22.024 10.466 35.326 6808.553 653.974
12 1 2.592 0.382 7.236 1.824 9.963 4.644 7.618 1028.703 222.358
12 4 2.885 0.269 12.675 1.773 8.246 9.791 12.944 939.677 167.719
12 7 4.895 2.052 21.445 6.524 0.000 16.550 23.497 5507.705 448.39
AVG 10.27 0.73 21.06 3.41 12.94 10.80 21.79 2676.44 311.76
Sb 7.69 0.66 10.06 1.66 7.63 5.20 10.30 2498.86 182.19
VAR 59.20 0.43 101.25 2.74 58.26 26.99 106.16 6244307.19 33193.34
continued
-------
TABLE 8-4. (continued)
FILTER
RUN NITROGEN PLOT UIDTH NH4 1103 11(11 P205 TP ORG-N TN 155 VSS
SOURCE a gas gas gas gas gas gas gas gas gas
I UAN 2 4.738 1.845 160.638 0.824 19.303 155.900 162.483 1839.771 191.065
1 5 5.952 2.017 25.834 1.769 38.849 19.882 27.851 11254.39 1098.318
1 8 6.816 1.070 73.215 4.440 39.115 66.399 74.285 22335.85 1721.809
4 2 0.731 0.506 25.532 0.477 22.359 24.801 26.038 4019.37 462.734
4 5 2.724 1.728 32.912 0.993 25.173 30.188 34.640 9567.381 905.256
4 8 3.552 2.813 27.880 1.708 26.174 17.432 22.026 24443.7 1648.603
AVG 4.09 1.66 57.67 1.70 28.50 52.43 57.89 12243.41 1004.63
STO 2.03 0.73 48.97 1.31 7.73 49.06 49.92 8511.90 563.21
VAR 4.13 0.53 2398.47 1.71 59.76 2407.25 2492.03 72452375.23 317206.48
7 Broiler 2 4.6 4.955 0.359 22.372 2.911 11.664 17.417 22.731 880.676 129.502
7 Litter 5 11.337 0.100 16.150 2.555 7.407 4.813 16.250 348.231 68.094
7 8 16.829 0.277 66.033 12.318 45.047 49.204 66.310 6936.278 724.833
10 2 1.952 1.046 28.351 3.036 33.068 26.399 29.397 2820.648 398.129
tO 5 4.854 0.947 11.032 1.625 9.113 6.178 11.979 509.277 99.563
10 8 11.648 1.849 32.864 6.347 12.982 21.216 34.713 10338.42 925.557
AVG 8.60 0.76 29.47 4.80 19.88 20.87 30.23 3638.92 390.95
STD 5.10 0.60 17.88 3.67 14.11 14.83 17.83 3756.25 330.36
VAR 26.00 0.36 319.56 13.45 198.98 219.85 317.89 14109441.41 109138.58
2 UAN 2 0.791 0.628 15.857 1.352 24.105 15.066 16.485 3279.297 356.789
2 5 2.785 1.572 9.571 0.702 19.400 6.786 11.143 5279.094 527.962
2 8 6.088 1.621 32.540 1.611 27.991 26.452 34.161 8499.428 607.337
5 2 0.908 0.514 16.219 0.779 9.230 15.311 16.733 1755.122 170.122
5 5 2.680 1.478 10.327 0.573 4.372 7.647 11.805 2698.455 245.934
5 8 2.702 2.482 39.036 0.872 3.359 36.334 41.518 8286.637 590.654
AVG 2.66 1.38 20.59 0.98 14.74 17.93 21.97 4966.34 416.47
STD 1.75 0.6o 11.19 0.37 9.60 10.46 11.61 2642.80 169.57
VAR 3.06 0.44 125.22 0.14 92.07 109.39 134.80 6984372.59 28755.40
continued
-------
TABLE 8—4. (continued)
FILTER
RUN NITROGEN PLOT WIDTH NH4 N03 TI(N P205 TP ORG-N TN TSS ‘16 5
SOURCE - in gins gins gms gins gins gins gins gins ges
B Broiler 2 4.6 14.155 0.732 40.229 3.373 14.586 26.074 40.961 1404.707 187.087
B litter 5 17.295 0.349 44.956 3.615 11.004 27.661 45.305 513.334 111.685
8 8 9.604 0.310 22.635 2.165 12.072 13.031 22.945 5073.461 465.852
11 2 1.454 0.873 19.323 1.497 10.051 17.869 20.196 1310.848 225.33
ii 5 2.101 0.902 5.911 1.191 3.586 3.810 6.813 1036.049 167.412
II 8 6.77? 2.558 43.429 4.368 69.738 36.652 45.987 15831.09 1273.23
AVG 8.56 0.95 29.41 2.70 20.17 20.85 30.37 4194.91 405.10
STD 5.83 0.75 14.46 1.16 22.42 10.68 14.68 5413.07 4’)4.1
VAR 34.01 0.57 209.19 1.35 502.53 113.96 215.45 29301331.32 163295.90
3 UAN 2 4.6 5.389 0.130 9.844 0.816 18.982 4.455 9.974 4189.771 304.7u1
3 5 2.331 1.331 15.418 1.536 13.240 13.087 16.749 48839.38 4332.258
3 8 6.655 0.685 11.361 1.114 8.977 4.706 12.046 10627.2 815.471
6 2 7.382 0.105 25.190 0.545 20.059 17.808 25.295 3262.71 308.215
6 5 2.093 0.179 9.970 1.679 12.102 7.877 10.149 3286.547 320.183
6 8 2.360 0.775 7.802 0.846 1.417 5.442 8.577 8652.021 736.288
AVG 4.37 0.53 13.26 1.09 12.46 8.90 13.80 13142.94 1136.19
SIB 2.19 0.45 5.81 0.40 6.26 4.95 5.76 16205.24 1444.55
VAR 4.79 0.20 33.81 0.16 39.18 24.54 33.19 262609965.48 2086736.15
9 Broiler 2 4.6 4.484 0.319 52.325 1.014 26.839 47.841 52.644 3421.8Th 485.772
9 litter 5 19.258 0.525 44.713 3.609 13.846 25.455 45.238 667.543 115.491
9 8 10.969 0.339 63.139 3.838 28.332 52.170 63.478 12767.96 962.456
12 2 1.755 0.0 )0 39.518 1.562 24.764 37.763 39.518 2036.061 299.703
12 5 3.953 0.189 8.774 1.459 6.298 4.821 8.963 322.057 69.28
12 8 5.291 2.210 24.379 2.189 8.611 19.088 26.589 8696.561 589.671
AVG 7.62 0.60 38.81 2.28 18.12 31.19 39.41 4652.01 420.40
SID 5.91 0.74 17.89 1.08 8.88 16.51 17.70 4568.15 304.84
VAR 34.96 0.55 320.05 1.17 78.82 272.55 313.30 20867987.71 92928.90
continued
-------
TABLE 8-4. (continued)
FILTER
RUM NITRO6EN PLOT WIDTH MH4 N03 1KM P205 TP ORG-N TN TSS YSS
SOURCE m gms qes gm5 g s gos g s gms qes q s
I VAN 3 0.0 7.953 0.498 32.758 1.560 50.177 24.805 33.256 17036.48 1393.583
6 6.065 2.704 64.920 1.961 59.448 58.855 67.624 224404.8 25019.18
9 15.442 0.824 53.453 1.520 41.487 38.011 54.277 123561.7 8848.5
4 3 1.309 1.017 35.676 1.458 19.360 34.367 36.693 10854.51 1039.077
4 6 5.435 4.687 19.555 1.436 45.617 14.120 24.242 24356.66 1690.554
4 9 5.164 0.508 40.227 2.022 47.993 35.063 40.735 24748.59 1919.698
AVG 6.89 1.71 41.10 1.66 44.01 34.20 42.80 70827.12 6651.77
STO 4.30 1.53 14.63 0.24 12.31 13.63 14.29 78676.47 8644.31
VAR 18.53 2.34 213.99 0.06 151.47 185.77 204.17 6189986867.23 74724065.94
7Broi ler 3 0.0 * * * *
7 Litter 6 22.569 0.488 0.000 14.529 29.117 0.000 0.488 8329.139 1118.418
7 9 2.931 1.416 55.259 11.574 51.562 52.328 56.675 16246.98 1644.046
10 3 9.994 0.356 39.974 4.801 34.853 29.980 40.330 9993.926 13u1.455
10 6 10.052 2.171 33.630 5.448 28.256 23.578 35.801 9022.269 1215.803
10 9 10.783 3.169 60.986 3.080 30.222 50.203 64.155 13133.97 1021.995
AVG 9.39 1.27 31.64 6.59 29.00 26.01 32.91 9454.38 1050.29
510 7.15 1.12 24.13 4.96 15.20 21.03 24.96 5013.45 508.52
VAR 51.05 1.25 582.44 24.64 231.06 442.11 623.12 25134682.60 258595.95
2 VAN 3 0.0 1.504 0.617 23.066 1.442 7.222 0.825 24.508 23730.29 2 !5.383
2 6 5.604 5.923 37.024 2.762 46.600 31.420 42.947 21224.79 1305.482
2 9 5.641 0.943 59.705 1.480 40.058 54.064 60.648 15196.07 997.575
5 3 2.332 0.257 11.328 0.510 14.152 8.996 11.585 5333.999 401.948
5 6 4.843 6.884 22.162 0.638 14.607 17.319 29.046 20553.39 1439.396
5 9 2.043 4.189 11.190 0.785 11.479 9.147 15.379 11283.88 715.373
AVG 3.66 3.14 27.41 1.27 22.35 20.30 30.69 16220.40 1212.53
STO 1.74 2.66 16.85 0.77 15.14 17.81 16.77 6378.99 639.97
VAR 3.02 7.06 283.92 0.59 229.31 317.33 281.34 40691562.97 409562.92
continued
-------
TABLE 8—4. (continued)
FILTER
RON NITROGEN PLOT NIUTH NH4 N03 TKN P205 TP 0R6-N TN 195 VSS
SOURCE m gs5 gis gms gms q s q s 9s5 ge
8 Broiler 3 0.0 I * * * * 3778.077 4B3.51
8 Litter 6 16.583 0.386 52.430 6.963 20.842 35.847 52.816 5009.241 497.005
8 9 8.947 0.057 25.818 5.916 25.657 16.971 25.875 9345.451 795.13
Il 3 3.402 0.912 10.68 1.548 20.281 7.278 (1.592 4414.955 573.714
II 6 7.954 0.682 37.558 2.841 25.286 29.604 38.240 7824.399 825.941
I l 9 2.369 2.839 38.763 1.276 42.963 36.394 41.602 9363.434 707.45
AVG 6.53 0.81 27.54 3.09 22.50 21.02 28.35 6622.59 645.46
510 5.45 0.96 17.76 2.53 12.59 14.01 18.09 2307.18 (34.99
VAR 29.70 0.92 315.25 6.38 158.40 196.16 327.12 5323057.37 18223.01
3 VAN 3 0.0 1.764 0.668 (5.149 1.608 18.662 13.385 15.817 10012.13 821.9a8
3 6 4.519 (.489 20.771 2.252 42.168 16.252 22.260 19139.7? 1443.381
3 9 3.352 0.911 37.907 2.059 16.246 34.555 38.818 16437.92 (003.7
6 3 1.461 0.138 9.187 0.751 2.161 7.726 9.325 5672.716 457.618
6 6 5.413 2.660 22.405 1.645 19.971 16.992 25.065 16396.86 953.u69
6 9 2.076 0.821 14.729 .1.410 20.993 12.653 15.550 14262.44 799.308
AV6 3.10 1.11 20.02 1.62 20.03 16.93 21.14 13653.64 913.17
910 1.47 0.80 9.09 0.48 11.74 8.43 9.38 4522.19 294.31
VAR 2.16 0.63 82.55 0.23 137.75 71.11 88.06 20450245.65 86620.29
9 Broiler 3 0.0 14.680 0.262 41.444 6.164 (6.410 26.764 41.706 6348.467 719.631
9 Litter 6 12.690 0.131 94.259 4.379 29.006 81.569 94.390 7546.513 11(2.31
9 9 9.599 0.159 36.215 3.545 24.878 26.616 36.374 12239.63 802.42
12 3 3.938 0.459 12.980 (.290 21.497 9.042 13.439 4606.28 444.611
12 6 7.760 1.316 41.578 2.272 20.989 33.818 42.094 8408.526 1125.679
12 9 6.364 0.326 12.507 2.575 26.341 6.143 (2.833 10756.96 723.283
AVG 9.17 0.44 39.83 3.37 24.52 30.66 40.27 8317.73 824.66
510 3.66 0.41 27.23 1.58 ‘i.44 24.84 27.16 2568.63 232.6o
VAR 13.36 0.16 741.45 2.50 19.74 616.94 737.63 6597836.67 54132.21
-------
TABLE B-S. VE6ETATED FILTER STRIP PERFORNANCE AS A PERCENTAGE OF BARE PLOT LOSSES
RUN 1 2 3 4 5 6 7 8 9 10 II 12 Average
PLOT Filter Paraaeter
1 9.2 a TSS 15.29 10.53 33.87 28.93 22.22 36.95 * 12.70 19.43 10.72 11.32 22.33 20.39
Total N 14.13 64.25 43.16 19.07 30.04 101.16 * 4 41.39 43.93 72.04 56.69 48.59
Total P 29.04 123.37 78.67 38.60 9.57 741.41 * * 120.51 45.26 17.59 46.35 125.04
4 9.2 a TSS 0.86 15.21 14.98 11.16 8.02 13.50 27.79 6.74 7.16 4.92 7.80 11.18 1 ( 1.78
Total N 27.57 43.41 123.31 49.17 28.89 23.40 200.00 64.97 8.00 20.78 26.79 30.18 53.87
Total P 46.44 30.09 24.84 9.99 65.72 46.32 91.09 56.39 60.77 17.44 25.68 28.44 41.93
7 9.2 a TSS 8.79 31.26 94.37 45.75 49.91 36.42 13.81 26.79 55.63 34.70 75.65 51.20 43.69
Total N 58.53 20.73 25.30 59.58 97.09 50.89 101.42 139.86 97.12 57.44 49.88 183.10 78.41
Total P 87.47 36.68 96.79 64.40 313.98 7.43 63.81 66.05 88.53 47.23 82.36 * 78.99
Average TSS 8.31 19.00 47.74 20.61 26.72 28.96 20.80 15.41 27.41 16.78 31.59 28.24 24.96
—i Total N 33.41 42.80 63.92 42.61 52.01 58.48 150.71 102.42 48.84 40.72 49.57 89.99 64.62
Total P 54.32 63.38 66.77 37.66 129.76 265.05 77.45 61.22 89.94 36.64 41.88 37.40 80.12
2 4.6 a TSS 10.80 13.82 41.85 37.02 32.90 57.52 4 37.18 53.90 28.22 29.69 44.20 35.19
Total N 488.58 67.26 63.06 70.96 144.43 271.26 * a 126.23 72.89 174.22 294.05 177.29
Total P 38.46 333.77 101.71 115.49 65.22 928.23 a * 163.55 94.88 49.56 115.20 200.61
5 4.6 a TSS 5.01 24.87 255.17 39.28 13.13 20.04 4.18 10.25 8.85 5.64 13.24 3.83 33.62
Total N 41.19 25.95 75.24 142.89 40.64 40.49 200.00 85.78 47.93 33.46 17.82 20.89 64.36
Total P 65.35 41.63 31.40 55.18 29.93 60.60 25.44 52.80 47.73 42.25 14.18 21.73 40.69
8 4.6 a 155 18.08 55.93 64.65 98.77 73.44 60.66 42.69 54.29 104.32 78.72 169.07 80.85 75.12
Total N 136.86 56.33 31.03 54.07 269.96 55.16 117.00 88.68 174.52 S4.11 110.54 207.19 112.95
Total P 94.28 69.87 S5.26 54.54 29.26 6.75 87.36 47.05 113.88 42.96 162.32 32.69 bb.35
Average 155 11.30 31.54 120.56 58.36 39.82 ‘*6.07 23.44 33.91 55.69 37.53 70.67 42.96 47.65
Total N 222.21 49.85 56.1*4 89.31 151.68 122.30 158.50 87.23 116.23 53.49 100.86 174.04 115.18
Total P 66.03 148.42 62.79 75.07 41.47 331.86 56.40 49.93 108.39 60.03 75.3S 56.54 94.36
-------
TABLE 8-6. BASIC AND COMPUTED NITROGEN LEACHING DATA
PLOT SAMPLE DEPTH TOTAL BULK PORTION PIH-4 NH—4 NH—4
TIME INCREMENT DEPTH DENSITY SAMPLED ppm ag/kg kg/ha
cm cm gm/cc
NO-3 NO-3 ND—3 Inorg-N Inorg-N Inorg-N
ppm mg/kg kg/ha kg/ha kg Plot
kg
-J
1
Pre-Appli
cation
11
11
Ii
22
0.980 Bare
1.140
0.392
0.387
3.92
3.87
4.23
4.85
0.379
0.194
3.79
1.94
4.09
2.43
8.311
7.286
6
28
1.160
0.477
4.77
3.32
0.275
2.75
1.91
5.234
6
34
1.380
0.361
3.61
2.99
0.206
2.06
1.71
4.695
9
43
1.680
0.220
2.20
3.33
0.932
9.32
14.09
17.418
9
51
1.450
0.159
1.59
2.07
0.343
3.43
4.48
6.551
7
58
1.530
0.195
1.95
2.09
0.160
1.60
1.71
3.802
7
65
1.540
0.235
2.35
2.53
0.206
2.06
2.22
4.754
20
85
1.640
0.090
0.90
2.95
0.191
1.91
6.26
9.217
20
105
1.540
0.512
5.12
15.77
0.286
2.86
8.81
24.578
20
125
1.410
0.225
2.25
6.35
0.935
9.35
26.37
32.712
Profile
Total
50.40
74.08
124.56
1
Pre—Appli
cation
ii
11
6
6
9
8
7
7
20
20
20
Ii
22
28
34
43
51
58
65
85
105
125
0.980 Filter
1.140
1.160
1.160
1.680
1.450
1.530
1.540
1.640
1.540
1.410
0.338
0.422
0.235
0.260
0.191
0.373
0.179
0.289
0.324
0.336
0.498
Profile
3.38
4.22
2.35
2.68
1.91
3.73
1.79
2.89
3.24
3.36
4.98
Total
3.64
5.29
1.64
1.87
2.89
4.33
1.92
3.12
10.63
10.35
14.04
59.70
0.114
0.137
0.314
0.114
0.171
0.090
0.192
0.079
0.632
0.079
0.114
1.14
1.37
3.14
1.14
1.71
0.9
1.92
0.79
6.32
0.79
1.14
1.23
1.72
2.19
0.79
2.59
1.04
2.06
0.85
20.73
2.43
3.21
38.84
4.873
7.010
3.821
2.659
5.473
5.371
3.973
3.967
31 .357
12.782
17.258
98.54
1.51
0.49 2.01
coot nued
-------
TABLE 8—6. (continued)
PLOT SAMPLE DEPTH TOTAL BULK PORTION IIH-4 NH-4 NH—4 NO—3 NO—3 NO—3 Inorg-N Inorg-N Inorg-N
TIME INCREMENT DEPTH DENSITY SAMPLED ppm mg/kg kg/ha ppm mg/kg kg/ha kg/ha kg Plot
cm cm gm/cc kg
Post App— 11 II 0.980 Bare 0.277 2.77 2.99 2.742 27.42 29.56 32.545
lication I I 22 1.140 0.540 5.40 6.77 0.874 8.74 10.96 17.732
6 28 1.160 0.564 5.64 3.93 0.125 1.25 0.87 4.795
6 34 1.160 0.206 2.06 1.43 0.451 4.51 3.14 4.573
9 43 1.680 0.218 2.18 3.30 0.761 7.61 11.51 14.802
8 51 1.450 0.314 3.14 3.64 0.411 4.11 4.77 8.410
7 58 1.530 0.462 4.62 4.95 0.310 3.1 3.32 8.268
7 65 1.540 0.775 7.75 8.35 0.436 4.36 4.70 13.055
20 85 1.640 0.242 2.42 7.94 0.183 1.83 6.00 13.940
20 105 1.540 0.277 2.77 8.53 0.402 4.02 12.38 20.913
20 125 1.410 0.356 3.56 10.04 0.171 1.71 4.82 14.861
Profile Total 61.87 92.03 153.89 1.87
Post App— 11 I i 0.980 Filter 0.420 4.20 4.53 0.067 0.67 0.72 5.250
lication 11 22 1.140 0.222 2.22 2.78 0.194 1.94 2.43 5.217
6 28 1.160 0.155 1.55 1.08 0.114 1.14 0.79 1.872
6 34 1.160 0.155 1.55 1.08 0.017 0.17 0.12 1.197
9 43 1.680 0.324 3.24 4.90 0.114 1.14 1.72 6.623
B 51 1.450 0.303 3.03 3.51 0.114 1.14 1.32 4.837
7 58 1.530 0.213 2.13 2.28 0.114 1.14 1.22 3.502
7 65 1.540 0.269 2.69 2.90 0.148 1.48 1.60 4.495
20 85 1.640 0.193 1.93 6.33 0.079 0.79 2.59 8.922
20 105 1.540 0.168 1.68 5.17 0.067 0.67 2.06 7.238
20 125 1.410 0.156 1.56 4.40 0.090 0.9 2.54 6.937
Profile Total 38.97 17.12 56.09 0.28 2.15
continued
-------
TABLE 8—6. (continued)
PLOT SAMPLE DEPTH TOTAL BULK PORTION NH-4 NH-4 NH—4 NO—3 P10-3 P10—3 Inorg-N Inorg-N Inorg-N
TINE INCREMENT DEPTH DENSITY SAMPLED ppm mg/kg kg/ha ppm mg/kg kg/ha kg/ha kg Plot
cm cm gm/cc kg
cc
0
2
Pre-Appli
I l
Il
0.980 Bare
0.527
5.27
5.68
0.380
3.80
4.10
9.777
cation
11
22
1.140
0.114
1.14
1.43
0.208
2.08
2.61
4.038
6
28
1.600
0.059
0.59
0.57
0.092
0.92
0.88
1.450
6
34
1.380
0.022
0.22
0.18
0.087
0.87
0.72
0.903
9
43
1.680
0.284
2.84
4.29
0.126
1.26
1.91
6.199
8
51
1.450
0.035
0.35
0.41
0.059
0.59
0.68
1.090
7
58
1.530
0.028
0.28
0.30
0.070
0.70
0.75
1.050
7
65
1.540
0.050
0.50
0.54
0.264
2.64
2.85
3.385
20
85
1.640
0.002
0.02
0.06
0.229
2.29
7.51
7.574
20
lO S
1.540
0.0u4
0.04
0.12
0.109
1.09
3.36
3.480
20
125
1.540
0.004
0.04
0.12
0.109
(.09
3.36
3.480
Profile
Total
13.71
28.72
42.43
0.52
2
Pre—Appli
11
11
0.980 Filter
0.0 07
0.07
0.08
0.254
2.54
2.74
2.814
cation
I I
6
6
9
8
7
7
20
20
20
22
28
34
43
SI
58
65
85
105
125
1.140
1.600
1.380
1.680
1.450
(.530
1.540
1.640
1.540
1.410
0.274
0.059
v.021
0.110
0.004
0.0)6
v.032
0.021
0.004
0.v07
Profile
2.74
0.59
0.21
1.10
0.04
0.06
0.32
0.21
0.04
0.07
Total
3.44
0.57
0.17
1.66
0.05
0.06
0.34
0.69
0.12
0.20
7.38
0.293
0.070
0.024
0.024
0.088
0.075
0.062
0.024
0.139
0.224
2.93
0.70
0.24
0.24
0.88
0.75
0.62
0.24
1.39
2.24
3.67
0.67
0.20
0.36
1.02
0.80
0.67
0.79
4.28
6.32
21.52
7.1(0
1.238
0.373
2.026
1.067
0.868
1.013
1.476
4.404
6.514
28.90
0.07 0.59
continued
-------
TABLE 8-6. (continued)
PLOT SAMPLE DEPTH TOTAL BULK PORTION NH-4 NH-4 1111-4 110-3 110-3 110-3 Inorg-N Inorq-N Inc’rg-N
TIME INCREMENT DEPTH DENSITY SAMPLED ppm mg/kg kg/ha ppm mg/kg kg/ha kg/ha kg Plot
2 Post App-
licat ion
2 Po5t App—
licat ion
cm cm go/cc
1.7)
kg
11
II
0.980 Bare
0.155
1.55
1.67
11
22
1.140
0.051
0.51
0.64
2.557
25.57
32.06
32.704
6
28
1.600
0.015
0.15
0.14
1.188
11.88
11.40
11.549
6
34
1.380
0.024
0.24
0.20
0.275
2.75
2.28
2.476
9
1*3
1.680
0.009
0.09
0.14
0.159
1.59
2.40
2.540
8
51
1.450
0.018
0.18
0.21
0.198
1.98
2.30
2.506
7
58
1.530
0.028
0.28
0.30
0.440
4.4
4.71
5.012
7
65
1.540
0.153
1.53
1.65
0.638
6.38
6.98
8.527
20
85
1.640
0.055
0.55
1.80
0.331
3.31
10.86
12.661
20
105
1.540
0.046
0.46
1.42
0.395
3.95
12.17
13.583
20
125
1.410
0.049
Profile
0.49
Total
1.38
9.55
0.253
2.53
7.13
131.07
8.516
140.62
11
11
0.980 Filter
0.192
1.92
2.07
0.013
0.13
0.14
2.210
I I
22
1.140
0.147
1.47
1.84
0.089
0.89
1.12
2.959
6
28
1.600
0.008
0.08
0.08
0.054
0.54
0.52
0.595
6
34
1.380
0.014
0.14
0.12
0.024
0.24
0.20
0.315
9
43
1.680
u.035
0.35
0.53
0.043
0.43
0.65
1.179
8
51
1.450
0.032
0.32
0.37
0.043
0.43
0.50
0.870
7
58
1.530
0.005
0.05
0.05
0.037
0.37
0.40
0.450
7
65
1.540
0.059
0.59
0.64
0.234
2.34
2.52
3.159
20
85
1.640
0.004
0.04
0.13
0.087
0.87
2.85
2.985
20
1o5
1.540
0.005
0.05
0.15
0.032
0.32
0.99
1.140
20
125
1.410
0.002
0.02
0.06
0.054
0.54
1.52
1.579
0.04 1.75
continued
-------
TABLE 8-6. (continued)
PLOT SAMPLE DEPTH TOTAL BULK PORTION NH-4 NH- li NH—4 NO—3 NO-3 NO—3 Inorg-N Inorg—F4 Iriorq—N
TIME INCREMENT DEPTH DENSITY SAMPLED ppm mglkg kg/ha ppm mg(kg kg/ha kg/ha kg Plot
cm c m gm/cc kg
Is )
3
Pre-Appli
11
11
0.980
Bare
0.378
3.78
4.07
0.463
4.63
4.99
9.066
cation
11
22
1.140
0.481
4.81
6.03
0.174
1.74
2.18
8.214
6
28
1.600
0.035
0.35
0.34
0.153
1.53
1.47
1.805
6
34
1.680
0.070
0.70
0.71
0.197
1.97
1.99
2.691
9
43
1.680
0.070
0.70
1.06
0.197
1.97
2.98
4.037
8
51
1.450
0.024
0.24
0.28
0.109
1.09
1.26
1.543
7
58
1.530
0.133
1.33
1.42
0.334
3.34
3.50
5.002
7
65
1.540
0.035
0.35
0.38
0.229
2.29
2.47
2.846
20
85
1.640
0.090
0.90
2.95
0.229
2.29
7.51
10.463
20
105
1.540
0.020
0.20
0.62
0.120
1.20
3.70
4.312
20
125
1.410
0.035
0.35
0.99
0.121
1.21
3.41
4.399
Profile
Total
18.84
35.54
54.38
0.6
0.66
3
Post App-
11
11
0.980
Bare
0.337
3.37
3.63
4.074
40.74
43.92
47.551
lication
11
6
6
9
8
7
7
20
20
20
22
28
34
43
51
58
65
85
loS
125
1.140
1.680
1.680
1.680
1.450
1.530
1.540
1.640
1.540
1.410
u.316
0.048
0.048
0.048
0.028
0.051
0.0u5
0.048
0.o32
0.o24
Profile
3.16
0.48
0.48
0.48
0.28
0.51
0.05
0.48
0.32
0.24
Total
3.96
0.48
0.48
0.73
0.32
0.55
0.05
1.57
0.99
0.68
13.45
1.132
0.435
0.435
0.435
0.740
0.286
0.523
0.264
0.472
0.459
11.32
4.35
4.35
4.35
7.40
2.86
5.23
2.64
4.72
4.59
14.20
4.38
4.38
6.58
8.58
3.06
5.64
8.66
14.54
12.94
126.89
18.158
4.869
4.869
7.303
8.909
3.609
5.692
10.234
15.523
13.621
140.34
1.71
1.71
continued
-------
TABLE 8—6. Icontinued)
PLOT SAMPLE DEPTH TOTAL BULK PORTION NH-4 NH-4 NH-4 NO-3 NU—3 NU-3 Inorq-N Inorg-N Inorq—N
TitlE INCREMENT DEPTH DENSITY SAMPLED ppm mg/kg kg/ha ppm mg/kg kg/ha kg/ha kg Plot
4 Pre—Appli
cation
cm cm gm/cc
kg
4 Pre-Appli
Ii
11
1.190 Bare
0.436
4.36
5.71
0.472
4.72
6.18
11.886
cation
11
22
1.410
0.220
2.20
3.41
0.281
2.81
4.36
7.771
6
28
1.540
0.134
1.34
1.24
0.256
2.56
2.37
3.604
6
34
1.430
0.118
1.18
1.01
0.386
3.86
3.31
4.324
9
43
1.550
0.076
0.76
1.06
0.182
1.82
2.54
3.599
8
51
1.620
0.085
0.85
1.10
0.711
7.11
9.21
10.316
7
58
1.690
0.241
2.41
2.85
0.166
1.66
1.96
4.815
7
65
1.690
0.241
2.41
2.85
0.166
1.66
1.96
4.815
20
85
1.680
0.253
2.53
8.50
0.158
1.58
5.31
13.810
20
105
1.500
0.214
2.14
6.42
0.157
1.57
4.71
11.130
20
125
1.500
0.453
4.53
13.59
0.100
1.00
3.00
16.590
11
11
6
6
9
8
7
7
20
20
20
Profile
Total
47.74
44.91
92.66
1.13
Ii
1.190 Filter
0.158
1.58
2.07
0.364
3.64
4.76
6.833
22
1.410
0.430
4.30
6.67
0.043
0.43
0.67
7.336
28
1.540
0.184
1.84
1.70
0.083
0.83
0.77
2.467
34
1.430
0.176
1.76
1.51
0.240
2.40
2.06
3.569
43
1.550
0.221
2.21
3.08
0.038
0.38
0.53
3.613
51
1.620
0.222
2.22
2.88
0.035
0.35
0.45
3.331
58
1.690
0.158
1.58
1.87
0.091
0.91
1.08
2.946
65
1.690
0.158
1.58
1.87
0.091
0.91
1.08
2.946
85
1.680
0.055
0.55
1.85
0.124
1.24
4.17
6.014
105
1.500
0.171
1.71
5.13
0.079
0.79
2.37
7.500
125
1.500
0.225
2.25
6.75
0.092
0.92
2.76
9.510
Profile
Total
35.37
20.69
56.07
0.28 1.41
continued
-------
TABLE 8-6. (continued)
PLOT SAMPLE DEPTH TOTAL BULK PORTION NH-4 NH-4 NH—4 NO-3 NO—3 NO—3 Inorg-N lnorg-N Inorg-N
TIME INCREMENT DEPTH DENSITY SAMPLED ppm mg/kg kg/ha ppm mg/kg kg/ha kg/ha kg Plot
cm cm gm/cc kg
4 Post App- I i 11 1.190 Bare 0.201 2.01 2.63 2.065 20.65 27.03 29.662
lication 11 22 1.410 0.125 1.25 1.94 0.752 7.52 11.66 13.602
6 28 1.540 0.103 1.03 0.95 0.510 5.10 4.71 5.664
6 34 1.430 0.128 1.28 1.10 0.447 4.47 3.84 4.934
9 43 1.550 0.210 2.10 2.93 0.305 3.05 4.25 7.184
8 51 1.620 0.230 2.30 2.98 0.397 3.97 5.15 8.126
7 58 1.580 0.307 3.07 3.40 0.626 6.26 6.92 10.319
7 65 1.690 0.363 3.63 4.29 0.403 4.03 4.77 9.062
20 85 1.680 0.262 2.62 8.80 0.255 2.55 8.57 17.371
2 20 105 1.500 0.269 2.69 8.07 0.281 2.81 8.43 16.500
20 125 1.500 0.442 4.42 13.26 0.665 6.65 19.95 33.210
Profile Total 50.35 105.28 155.63 1.89
4 Post App— II I I 1.190 Filter 0.329 3.29 4.31 0.132 1.32 1.73 6.034
lication 11 22 1.410 0.217 2.17 3.37 0.076 0.76 1.18 4.544
6 28 1.540 0.196 1.96 1.81 0.048 0.48 0.44 2.255
6 34 1.430 0.186 1.86 1.60 0.076 0.76 0.65 2.248
9 43 1.550 0.241 2.41 3.36 0.048 0.48 0.67 4.032
8 51 1.620 0.221 2.21 2.86 0.131 1.31 1.70 4.562
7 58 1.580 0.326 3.26 3.61 0.068 0.68 0.75 4.358
7 65 1.690 0.204 2.04 2.41 0.038 0.38 0.45 2.863
20 85 1.680 0.155 1.55 5.21 0.116 1.16 3.90 9.106
20 105 1.500 0.155 1.55 4.65 0.132 1.32 3.96 8.610
20 125 1.500 0.254 2.54 7.62 0.110 1.10 3.30 10.920
Profile Total 40.80 18.73 59.53 0.3’ ) 2.19
continued
-------
TABLE 8—6. (continued)
PLOT SAMPLE DEPTH TOTAL BULK PORTION NH-4 NH-4 NH—4 NO—3 NO—3 NO—3 lnorg—N Inorg-N lriorg—N
TIME INCREMENT DEPTH DENSITY SAMPLED ppm mg/kg kg/ha ppm mg/kg kg/ha kg/ha kg Plot
cm cm gm/cc kg
5 Pre-Appli 11 11 1.190 Bare 0.411 4.11 5.38 0.402 4.02 5.26 10.642
cation 11 22 1.410 0.469 4.69 7.27 0.402 4.02 6.24 13.509
6 28 1.540 0.303 3.03 2.80 0.298 2.98 2.75 5.553
6 34 1.500 0.460 4.60 4.14 0.423 4.23 3.81 7.947
9 43 1.550 0.260 2.60 3.63 0.350 3.50 4.88 8.510
8 51 1.620 0.118 1.18 1.53 0.198 1.98 2.57 4.095
7 58 1.580 0.315 3.15 3.48 0.647 6.47 7.16 10.640
7 65 1.690 0.235 2.35 2.78 0.206 2.06 2.44 5.217
20 85 1.680 0.201 2.01 6.75 0.240 2.40 8.06 14.818
U i 20 105 1.500 0.217 2.17 6.51 0.109 1.09 3.27 9.780
20 125 1.500 0.123 1.23 3.69 0.174 1.74 5.22 8.910
Profile Total 47.97 51.65 99.62 1.21
5 Pre—Appli 11 11 1.190 Filter 0.321 3.21 4.20 0.148 1.48 1.94 6.139
cation Il 22 1.410 0.242 2.42 3.75 0.171 1.71 2.65 6.406
6 28 1.540 0.097 0.97 0.90 0.108 1.08 1.00 1.894
6 34 1.430 0.232 2.32 1.99 0.148 1.48 1.27 3.260
9 43 1.550 0.247 2.47 3.45 0.048 0.48 0.67 4.115
8 51 1.620 0.18! 1.81 2.35 0.048 0.48 0.62 2.968
7 58 1.580 0.198 1.98 2.19 0.131 1.31 1.45 3.639
7 65 1.690 0.086 0.86 1.02 0.091 0.91 1.08 2.094
20 85 1.680 0.230 2.30 7.73 0.051 0.51 1.71 9.442
20 105 1.500 0.055 0.55 1.65 0.099 0.99 2.97 4.620
20 125 1.500 0.081 0.81 2.43 0.132 1.32 3.96 6.390
Profile Total 31.65 19.32 50.97 0.13 1.34
continued
-------
TABLE 8—6. (continued)
PLOT SAMPLE DEPTH TOTAL BULK PORTION NH—4 NH—4 NH-4 NO-3 NO—3 NO—3 Inorg—N Inorq—N borg-N
TIME INCREMENI DEPTH DENSITY SAMPLED ppm ag/kg kg/ha ppm my/kg kg/ha kg/ha kg Plot
cm cm go/cc kg
5 Post App— II 11 1.190 Bare 1.233 12.33 16.14 5.895 58.95 77.17 93.306
lication 11 22 1.410 0.241 2.41 3.74 5.358 53.58 83.10 86.840
6 28 1.540 0.509 5.09 4.70 0.461 4.61 4.26 8.963
6 34 1.430 0.390 3.90 3.35 0.460 4.60 3.95 7.293
9 43 1.550 0.277 2.77 3.86 0.252 2.52 3.52 7.380
8 51 1.620 0.176 1.76 2.28 0.158 1.58 2.05 4.329
7 58 1.580 0.218 2.18 2.41 0.544 5.44 6.02 8.428
7 65 1.690 1.504 15.04 17.79 0.263 2.63 3.11 20.904
20 85 1.680 0.2u5 2.05 6.89 0.207 2.07 6.96 13.843
20 105 1.500 0.234 2.34 7.02 0.402 4.02 12.06 19.080
20 125 1.500 0.208 2.08 6.24 u.363 3.63 10.89 17.130
Profile Total 74.42 213.07 287.49 3.49
5 Post App- 11 11 1.190 Filter 0.387 3.87 5.07 0.114 1.14 1.49 6.558
lication 11 22 1.410 0.337 3.37 5.23 0.234 2.34 3.63 8.856
6 28 1.540 0.201 2.01 1.86 0.035 0.35 0.32 2.181
6 34 1.430 0.219 2.19 1.88 0.092 0.92 0.79 2.668
9 43 1.550 0.256 2.56 3.57 0.125 1.25 1.74 5.315
8 51 1.620 0.085 0.85 1.10 0.091 0.91 1.18 2.281
7 58 1.580 0.184 1.84 2.04 0.091 0.91 1.01 3.042
7 65 1.690 0.233 2.33 2.76 0.100 1.00 1.18 3.939
20 85 1.680 0.39k) 3.90 13.10 0.137 1.37 4.60 17.707
20 105 1.500 0.373 3.73 11.19 0.125 1.25 3.75 14.940
20 125 1.500 0.189 1.89 5.67 0.048 0.48 1.44 7.110
Profile Total 53.46 21.14 74.60 0.19 3.68
continued
-------
TABLE 84. (continued)
PLOT SAMPLE DEPTH TOTAL BULK PORTION NH-4 NH—4 NH-4 N0-3 NO—3 NO-3 Inorg-N Inorg-N Inorg-N
TIME INCREMENT DEPTH DENSITY SAMPLED ppm mg/kg kg/ha ppm mg/kg kg ha kg/ha kg Plot
cm cm gm/cc kg
-J
6
Pre-Appli
11
11
1.190
Rare
0.512
5.12
6.70
5.117
51.17
66.98
73.684
cation
11
22
1.410
0.295
2.95
4.58
0.240
2.40
3.72
8.298
6
28
1.540
0.268
2.68
2.48
0.448
4.48
4.14
6.616
6
34
1.430
0.266
2.66
2.28
0.018
0.18
0.15
2.437
9
43
1.550
0.184
1.84
2.57
0.035
0.35
0.49
3.055
8
51
1.620
0.206
2.06
2.67
0.606
6.06
7.85
10.524
7
58
1.580
0.369
3.69
4.08
0.200
2.00
2.21
6.293
7
65
1.690
0.521
5.21
6.16
0.356
3.56
4.21
10.375
20
85
1.680
0.235
2.35
7.90
0.194
1.94
6.52
14.414
20
105
1.500
0.276
2.76
8.28
0.183
1.83
5.49
13.770
20
125
1.500
v.229
2.29
6.87
0.151
1.51
4.53
11.400
Profile
Total
54.56
106.30
160.87
1.95
1.95
6
Post App-
11
Il
1.190
Bare
0.567
5.67
7.42
2.041
20.41
26.72
34.139
lication
11
6
6
9
8
7
7
20
20
20
22
28
34
43
5!
58
65
85
105
125
1.410
1.540
1.430
1.550
1.620
1.580
1.690
1.680
1.500
1.500
0.413
0.321
0.142
v.087
0.169
0.072
0.321
0.181
0.271
0.213
4.13
3.21
1.42
0.87
1.69
0.72
3.21
1.81
2.71
2.13
6.41
2.97
1.22
1.21
2.19
0.80
3.80
6.08
8.13
6.39
1.347
0.764
0.470
0.121
0.084
0.794
0.436
0.229
0.13!
0.109
13.47
7.64
4.70
1.21
0.84
7.94
4.36
2.29
1.31
1.09
20.89
7.06
4.03
1.69
1.09
8.78
5.16
7.69
3.93
3.27
27.298
10.025
5.251
2.902
3.279
9.578
8.955
13.776
12.060
9.660
continued
-------
TABLE B-h. (continued)
PLOT SAIIPLE DEPTH TOTAL BULK PORTION NH-4 NH—4 tIH—4 NO—3 110—3 110—3 lnorg—N Inorg-N Inorg-N
TIME INCREIIENT DEPTH DENSITY SAMPLED ppm mg/kg kg/ha ppm mg/kg kg/ha kg/ha kg Plot
cm cm gm/cc kg
7 Pre-Appli 11 11 1.420 Bare 0.306 3.06 4.78 0.733 7.33 11.45 16.229
cation 11 22 1.670 0.172 1.72 3.16 0.143 1.43 2.63 5.787
6 28 1.340 0.233 2.33 1.87 0.125 1.25 1.01 2.878
6 34 1.490 0.215 2.15 1.92 0.316 3.16 2.83 4.747
9 43 1.640 0.063 0.63 0.93 0.460 4.60 6.79 7.719
8 51 1.540 0.214 2.14 2.64 0.198 1.98 2.44 5.076
7 58 1.740 0.300 3.00 3.65 0.150 1.50 1.83 5.481
7 65 1.340 0.082 0.82 0.77 0.606 6.06 5.68 6.453
20 85 1.570 u.208 2.08 6.53 0.229 2.29 7.19 13.722
20 105 1.550 0.234 2.34 7.25 0.229 2.29 7.10 14.353
20 125 1.560 0.312 3.12 9.73 0.171 1.71 5.34 15.070
Profile Total 43.24 54.27 97.52 1.18
7 Pre-Appli Ii 11 1.420 Filter 0.528 5.28 8.25 0.018 0.18 0.28 8.529
cation 11 22 1.670 0.384 3.84 7.05 0.256 2.56 4.70 11.757
6 28 1.340 0.316 3.16 2.54 0.115 1.15 0.92 3.465
6 34 1.640 0.546 5.46 5.37 0.035 0.35 0.34 5.717
9 43 1.640 0.546 5.46 8.06 0.035 0.35 0.52 8.576
8 51 1.540 0.459 4.59 5.65 0.129 1.29 1.59 7.244
7 58 1.740 0.374 3.74 4.56 0.114 1.14 1.39 5.944
7 65 1.340 0.096 0.96 0.90 0.169 1.69 1.59 2.486
20 85 1.570 0.101 1.01 3.17 0.145 1.45 4.55 7.724
20 105 1.550 0.124 1.24 3.84 0.104 1.04 3.22 7.068
20 125 1.560 0.o78 0.78 2.43 0.363 3.63 11.33 13.759
Profile Total 51.83 30.44 82.27 0.41 1.60
continued
-------
TABLE 8—6. (continued)
¼0
PLOT SAMPLE DEPTH TOTAL BULK PORTION NH-4 NH-4 NH-4 NO—3
TIME INCREMENT DEPTH DENSITY SAMPLED ppm mg/kg kg/ha ppm
cm cm gm/cc
110-3 110—3 lnorg—N Inorg—tl Inorg-N
mg/kg kg/ha kg/ha kg Plot
kg
7 Post App-
lication
11 11 1.420 Filter 0.394 3.94
i i 22 1.670 0.108 1.08
6 28 1.340 0.394 3.94
6 34 1.640 0.409 4.09
9 43 1.640 0.409 4.09
8 51 1.540 0.692 6.92
7 58 1.740 0.690 6.90
7 65 1.340 0.063 0.63
20 85 1.570 0.059 0.59
20 105 1.550 0.196 1.96
20 125 1.560 0.734 7.34
Profile Total
6.15 0.173
1.98 0.423
3.17 0.018
4.02 0.125
6.04 0.125
8.53 0.814
8.40 0.423
0.59 0.326
1.85 0.350
6.08 0.131
22.90 0.399
69.72
1.73 2.70 8.857
4.23 7.77 9.75
0.18 0.14 3.312
1.25 1.23 5.255
1.25 1.85 7.882
8.14 10.03 18.554
4.23 5.15 13.556
3.26 3.06 3.649
3.50 10.99 12.843
1.31 4.06 10.137
3.99 12.45 35.350
59.43 129.15
0.65 2.75
7 Post App-
LI
I I
1.420 Bare 0.457
4.57
7.14
0.978
9.78
15.28
22.415
lication
11
6
6
9
8
7
7
20
20
20
22
28
34
43
51
58
65
85
105
125
1.670
1.340
1.490
1.640
1.540
1.740
1.340
1.570
1.550
1.560
0.270
0.868
0.205
0.223
0.059
0.267
0.085
0.347
0.196
0.190
Profile
2.70
8.68
2.05
2.23
0.59
2.67
0.85
3.47
1.96
1.90
Total
4.96
6.98
1.83
3.29
0.73
3.25
0.80
10.90
6.08
5.93
51.88
2.220
1.909
1.215
0.316
0.715
0. 117
0.533
0.240
0.172
0.194
22.20
19.09
12.15
3.16
7.15
1.17
5.33
2.40
1.72
1.94
40.78
15.35
10.86
4.66
8.81
1.43
5.00
7.54
5.33
6.05
121.09
45.741
22.327
12.695
7.956
9.536
4.677
5.797
18.432
11.408
11.981
172.96
2.10
continued
-------
TABLE 8—6. (continued)
PLOT SAMPLE DEPTH TOTAL BULK PORTION HH-4 NH—4 NH—4 NO-3 110-3 110—3 Inorg-N Inorg—N Inorg—N
TIME INCREMENT DEPTH DENSITY SAMPLED ppm ag/kg kg/ha ppm ag/kg kg/ha kg/ha kg Plot
cm cm gm/cc
kg
0.29 1.89
D
8
Pre-Appli
11
11
1.420 Bare
0.608
6.08
9.50
0.728
7.28
11.37
20.868
cation
11
22
1.670
0.569
5.64
10.36
0.035
0.35
0.64
11.004
6
28
1.340
0.485
4.85
3.90
1.011
10.11
8.13
12.028
6
34
1.490
0.346
3.46
3.09
0.035
0.35
0.31
3.406
9
43
1.640
0.322
3.22
4.75
0.286
2.86
4.22
8.974
8
51
1.540
0.408
4.09
5.03
0.134
1.34
1.65
6.677
7
58
1.740
0.400
4.00
4.87
0.184
1.84
2.24
7.113
7
65
1.340
0.295
2.95
2.77
0.223
2.23
2.09
4.859
20
85
1.570
0.462
4.62
14.51
0.068
0.68
2.14
16.642
20
105
1.550
0.532
5.32
16.49
0.162
1.62
5.02
21.514
20
125
1.560
0.082
0.82
2.56
0.521
5.21
16.26
18.814
Profile
Total
77.83
54.07
131.90
B
Pre-Appli
11
11
1.420 Filter
0.736
7.36
11.50
0.139
1.39
2.17
13.668
cation
II
6
6
9
8
7
7
20
20
20
11
28
34
43
51
58
65
85
205
225
1.420
1.340
1.540
1.540
1.540
1.740
1.340
1.570
1.560
1.560
0.736
0.294
0.642
0.642
0.6q2
0.550
0.357
0.347
0.312
0.312
7.36
2.94
6.42
6.42
6.42
5.50
3.57
3.47
3.12
3.12
11.50
2.36
5.93
8.90
7.91
6.70
3.35
10.90
9.73
9.73
0.139
0.399
0.018
0.018
0.018
0.102
0.139
0.092
0.226
0.226
1.39
3.99
0.18
0.18
0.18
1.02
1.39
0.92
2.26
2.26
2.17
3.21
0.17
0.25
0.22
1.24
1.30
2.89
7.05
7.05
13.668
5.572
6.098
9.148
8.131
7.941
4.652
13.785
16.786
16.786
I .60
continued
-------
TABLE B— h. (continued)
PLOT SAMPLE DEPTH TOTAL BULK PORTION NH-4 NH-4 NH-4 NO-3 NO—a NO-3 Inorg-N Inorg-N Inorg-N
TINE INCREMENT DEPTH DENSITY SAMPLED ppm mg/kg kg/ha ppm mg/kg kg/ha kg/ha kg Plot
cm cm gm/cc kg
8 Post App-
lication
B Post App-
lication
0
I .- ’
11
II
1.420 Bare
0.347
3.47
5.42
0.119
1.19
1.86
7.279
I i
22
1.670
0.353
3.53
6.48
3.316
33.16
60.91
67.400
6
28
1.340
0.288
2.88
2.32
1.605
16.05
12.90
15.220
6
34
1.490
0.420
4.20
3.75
1.099
10.99
9.83
13.580
9
43
1.640
0.301
3.01
4.44
0.893
8.93
13.18
17.623
8
51
1.540
0.492
4.92
6.06
0.257
2.57
3.17
9.228
7
58
1.740
0.868
8.68
10.57
0.224
2.24
2.73
13.301
7
65
1.340
0.423
4.23
3.97
0.233
2.33
2.19
6.153
20
85
1.570
0.353
3.53
11.08
0.125
1.25
3.93
15.009
20
lO S
1.550
0.119
1.19
3.69
0.035
0.35
1.09
4.774
20
125
1.560
0.281
Profile
2.81
Total
8.77
66.56
0.347
3.47
10.83
122.60
19.594
189.16
2.30
11
11
1.420 Filter
0.823
8.23
12.86
0.228
2.28
3.56
16.417
11
22
1.670
0.103
1.03
1.89
0.399
3.99
7.33
9.222
6
28
1.340
0.569
5.69
4.57
0.131
1.31
1.05
5.628
6
34
1.540
0.779
7.79
7.20
0.149
1.49
1.38
8.575
9
43
1.540
0.779
7.79
10.80
0.149
1.49
2.07
12.862
8
51
1.540
0.779
7.79
9.60
0.149
1.49
1.84
11.433
7
58
1.740
0.343
3.43
4.18
0.228
2.28
2.78
6.955
7
65
1.340
0.249
2.49
2.34
0.092
0.92
0.86
3.199
20
85
1.570
0.394
3.94
12.37
0.149
1.49
4.68
17.050
20
lOS
1.570
0.394
3.94
12.37
0.149
1.49
4.68
17.050
20
125
1.570
0.394
Profile
3.94
Total
12.37
90.54
0.149
1.49
4.68
34.90
17.050
125.44
0.31 2.61
continued
-------
TABLE B— b. (continued)
PLOT SAMPLE DEPTH TOTAL BULK PORTION NH-4 NH-4 NH—4 NO—3 NO—3 NO-3 Inorg-N Inorg-N Inorg—N
TIME INCREMENT DEPTH DENSITY SAMPLED ppm mg/kg kg/ha ppm mg/kg kg/ha kg/ha kg Plot
c m cm gm/cc kg
hO
9
Pre-Appli
11
Il
1.420
Bare
0.477
4.77
7.45
0.459
4.59
7.17
14.620
cation
11
22
1.670
0.362
3.62
6.65
0.224
2.24
4.11
10.765
6
28
1.340
0.214
2.14
1.72
1.257
12.57
10.11
11.827
6
34
1.490
0.206
2.06
1.84
0.117
1.17
1.05
2.888
9
43
1.740
0.235
2.35
3.68
0.124
1.24
1.94
5.622
B
51
1.740
0.235
2.35
3.27
0.124
1.24
1.73
4.997
7
58
1.740
0.235
2.35
2.86
0.124
1.24
1.51
4.373
7
65
1.340
0.556
5.56
5.22
0.217
2.17
2.04
7.251
20
85
1.570
0.237
2.37
7.44
0.290
2.90
9.11
16.548
20
lO S
1.550
0.364
3.64
11.28
0.114
1.14
3.53
14.818
20
125
1.560
0.279
2.79
8.70
0.169
1.69
5.27
13.978
Profile
Total
60.12
47.56
107.69
1.31
1.31
9
Post App—
II
I I
1.420
Bare
0.364
3.64
5.69
1.347
13.47
21.04
26.726
lication
I I
6
6
9
8
7
7
20
20
20
22
28
34
43
51
58
65
85
lOS
125
1.670
1.340
1.490
1.740
1.740
1.740
1.340
1.570
1.550
1.560
0.229
0.210
0.217
0.260
0 ,260
0.260
0.554
0.846
0.543
‘).266
Profile
2.29
2.10
2.17
2.60
2.60
2.60
5.54
8.46
5.43
2.66
Total
4.21
1.69
1.94
4.07
3.62
3.17
5.20
26.56
16.83
8.30
81.27
1.803
1.342
1.508
0.324
0.324
0.324
0.557
0.402
0.184
0.298
18.03
13.42
15.08
3.24
3.24
3.24
5.57
4.02
1.84
2.98
33.12
10.79
13.48
5.07
4.51
3.95
5.22
12.62
5.70
9.30
124.81
37.328
12.478
15.422
9.145
8.129
7.113
10.421
39.187
22.537
17.597
206.08
2.50
2.50
-------
TABLE B-7. 1NORGMNIC NITROGEN LEACHING SU UI IARY (TOTALS FOR 125 cm PROFILE)
PLOT FILTER BARE AREA % FILTER AREA TOTAL PLOT NET
LENGTH kg/ha CHANGE kg/ha CHANGE kg CHANGE
m Before After Before After Before After kg
1 9.2 124.56 153.89 23.55 98.54 56.09 -43.08 2.01 2.15 0.14 6.97
2 4.6 42.43 140.62 231.42 28.90 17.44 —39.65 0.59 1.75 1.16 196.61
3 0 54.68 140.34 156.66 0.66 1.7! 1.05 159.09
4 9.2 92.66 155.63 67.96 56.07 59.53 6.17 1.41 2.19 0.78 55.32
5 4.6 99.62 287.49 188.59 50.97 74.60 46.36 1.34 3.68 2.34 174.63
6 U 160.87 136.92 -14.89 1.95 1.66 -0.29 —14.87
7 9.2 97.52 172.96 77.36 82.27 129.15 56.98 1.60 2.75 1.15 71.87
8 4.6 131.90 189.16 43.41 116.23 125.44 7.92 1.89 2.61 0.72 38.10
9 0 107.69 206.08 91.36 1.31 2.50 1.19 90.84
Average 1.42 2.33 0.92
Vartance 0.24 0.37 0.48
Std. Dee. 0.49 0.61 0.70
93
-------
TABLE B—B. PREDICTED VS. OBSERVED POLLUTANT REDUCTIONS 1 NCSU MODEL
FILTER! INFIL to
RUN PLOT SLOPE FIL lER SOURCE PRECIP I!1+K 1!1—D REDUC
RATIO Cpred ct) REDUC REDUC REDUC
D
WIDTH RATIO
i n K
IP TN TSS
I !
A
Cobs) Cobs) Cobs)
I
1
4
9.2
0.413
0.79
0.71
4.71
72.27 70.96 85.87
84.71
2
1
4
9.2
0.413
0.55
0.71
2.20
33.92 -23.37 35.75
89.47
3
1
4
9.2
0.413
0.43
0.71
1.74
22.60 21.33 56.84
66.03
4
1
4
9.2
0.413
0.57
0.71
2.32
36.63 61.40 80.93
71.07
5
1
4
9.2
0.413
0.60
0.71
2.53
40.98 90.43 69.96
77.78
6
1
4
9.2
0.413
0.38
0.71
1.62
19.21 -641.42 -1.16
63.05
9
1
4
9.2
0.413
0.40
0.71
1.66
20.30 —20.51 58.61
80.57
10
I
4
9.2
0.413
0.57
0.71
2.33
36.95 54.74 56.07
89.28
11
1
4
9.2
0.413
0.60
0.71
2.48
40.09 82.41 27.96
88.68
12
1
4
9.2
0.413
0.36
0.71
1.57
18.Ofl 53.65 43.31
77.67
1
2
4
4.6
0.207
0.58
0.83
2.36
22.60 61.53 -388.58
89.20
2
2
4
4.6
0.207
0.40
0.83
1.68
11.95 -233.77 32.74
86.18
3
2
4
4.6
0.207
0.22
0.83
1.28
5.18 -1.71 36.94
58.15
4
2
4
4.6
0.207
0.47
0.83
1.87
15.10 —15.49 29.04
62.97
5
2
4
4.6
0.207
0.26
0.83
1.34
6.26 34.78 -44.44
67.10
6
2
4
4.6
0.207
0.00
0.83
1.00
0.00 -828.23 -171.26
42.48
9
2
4
4.6
0.207
0.26
0.83
1.35
6.36 -63.55 —26.23
46.10
10
2
4
4.6
0.207
0.49
u.83
1.95
16.41 5.12 27.11
71.78
11
2
4
4.6
0.207
0.44
0.83
1.79
13.75 50.44 -74.22
70.31
12
2
4
4.6
0.207
0.30
0.83
1.43
7.76 —15.20 -194.05
55.80
1
4
3
9.2
0.413
0.67
0.71
3.07
51.13 53.56 72.43
99.14
2
4
3
9.2
0.413
0 59
0.71
2.44
39.24 69.91 56.59
84.79
3
4
3
9.2
0.413
0.40
0.71
1.68
20.82 75.16 -23.31
85.02
4
4
3
9.2
0.413
0.59
0.71
2.43
39.11 90.01 50.83
88.84
5
4
3
9.2
0.413
0.60
0.71
2.49
40.21 34.28 71.11
91.98
6
4
3
9.2
0.413
0.49
0.71
1.96
28.28 53.68 76.62
86.50
8
4
3
9.2
0.413
0.61
0.71
2.56
41,62 43.61 35.03
93.26
9
4
3
9.2
0.413
0.47
0.71
1.88
26.16 39.23 63.88
92.84
10
4
3
9.2
0.413
0.79
0.71
4.78
72.96 32.56 79.22
95.08
11
4
3
9.2
0.413
0.63
0.71
2;68
43.99 74.32 73.21
92.20
12
4
3
9.2
0.413
0.48
0.71
1.92
27.36 71.55 69.82
88.82
continued
94
-------
TABLE 8-B. (continued)
FILTER! INFIL to
RUN PLOT SLOPE FILTER SOURCE PRECIP 111+K 1/1-D REDUC
WIDTH RATIO RATIO
K 0
0.38
0.21
0.12
0.35
0.37
0.23
0.47
0.31
0.61
0.58
0.46
0.48
0.45
0.16
0.31
0.27
0.20
0.69
0.39
0.21
0.28
0.29
0.19
0.33
0.22
0.13
0.14
0.03
0.00
0.62
0.36
0.12
0.22
0.14
0.07
0.83
0.83
0.83
0.83
0.83
0.83
0.83
0.83
0.83
0.83
0.83
0.71
0.71
0.71
0.71
0.71
0.71
0.71
0.71
0.71
0.7!
0.71
0.71
0.83
0.83
0.83
0.83
0.83
0.83
0.83
0.83
0.83
0.83
0.83
0.83
1.62
1.26
1.14
1.54
1.58
1.30
1.87
1.45
2.54
2.39
1.85
1.9!
1.83
1.19
1.44
1.38
1.25
3.27
1 .64
1.26
1 .38
1.41
1.24
1.49
1.28
1.15
1.17
1.03
1 • 00
2.63
1.57
1.14
1.28
1.16
1.08
TP TN TSS
I2 ‘1
(predict) REDUC P.EDUC REDIJC
Cobs) Cobs) Cobs)
AVE 19.48 11.03 15.12 62.30
810 16.53 144.78 79.96 40.48
1 5 3 4.6 0.207
2 5 3 4.6 0.207
3 5 3 4.6 0.207
4 5 3 4.6 0.207
5 5 3 4.6 0.207
6 5 3 4.6 0.207
8 5 3 4.6 0.207
9 5 3 4,6 0.207
10 5 3 4.6 0.207
11 5 3 4.6 0.207
12 5 3 4.6 0.207
1 7 5 9.2 0.413
2 7 5 9.2 0.413
3 7 5 9.2 0.413
4 7 5 9.2 0.413
5 7 5 9.2 0.413
6 7 5 9.2 0.413
7 7 5 9.2 0.413
8 7 5 9.2 0.413
9 7 5 9.2 0.413
10 7 5 9.2 0.413
11 7 5 9.2 0.413
12 7 5 9.2 0.413
1 8 5 4.6 0.207
2 8 5 4.6 0.207
3 8 5 4.6 0.207
4 8 5 4.6 0.207
5 8 5 4.6 0.207
6 8 5 4.6 0.207
7 9 5 4.6 0.207
8 8 5 4.6 0.207
9 8 5 4.6 0.207
10 8 5 4.6 0.207
Ii 8 5 4.6 0.207
12 8 5 4.6 0.207
11.04 34.65 58.81 94.98
4.78 58.37 74.05 75.13
2.65 68.60 24.76 -155.17
9.74 44.02 -42.89 60.72
10.27 70.07 59.36 86.87
5.52 39.40 59.51 79.96
15.14 47.20 14.22 89.75
8.04 52.27 52.07 91.15
25.08 67.75 66.54 94.36
22.99 85.82 82.18 86.76
14.79 78.27 79.10 96.17
27.08 12.53 41.47 91.21
25.03 63.32 79.27 68.74
6.31 3.21 74.70 5.63
14.20 35.60 40.42 54.25
12.27 -213.98 2.91 50.09
8.40 92.57 49.11 63.59
54.34 36.19 -1.42 86.19
19.86 33.95 —39.87 73.21
8. 0 11.q7 2.88 44.37
12.31 52.77 42.56 65.30
13.35 17.64 50.12 24.35
7.89 100.00 -83.10 48.80
8.84 5.72 —36.86 81.92
5.14 30.12 43.67 44.07
2.76 44.74 68.97 35.35
3.06 45.46 45.93 1.23
0.57 70.74 -169.97 26.56
0.00 93.25 44.84 39.34
26.35 12.64 —17.00 57.31
10.12 52.95 11.32 45.7!
2.62 —13.88 -74.51 -4.32
5.20 57.04 45.89 21.28
2.97 -62.32 -10.54 -69.07
1.46 67.31 —107.19 19.15
95
-------
TABLE B—9. PREDICTED VS. OBSERVED POLLUTANT REDUCTIONS, USDA MODEL
V V
I I
RUN PLOT SLOPE FILTER COCITACT CONTACT REDUC REDUC
TP TN TSS
1
WIDTH TIr E TIME GOOD FAIR REDUC REDUC REDUC
I in )600D) (FAIR) (predict)(predict) Cobs) Cobs) Cobs)
1 1 4 9.2 25.03
2 1 4 9.2 25.03
3 1 4 9.2 25.03
4 1 4 9.2 25.03
5 1 4 9.2 25.03
6 1 4 9.2 25.03
9 1 4 9.2 25.03
10 1 4 9.2 25.03
11 I 4 9.2 25.03
12 1 4 9.2 25.03
I 2 4 4.6
2 2 4 4.6
3 2 4 4.6
4 2 4 4.6
5 2 4 4.6
6 2 4 4.6
9 2 4 4.6
10 2 4 4.6
11 2 4 4.6
12 2 4 4.6
1 4 3 9.2 28.90
2 4 3 9.2 28.90
3 4 3 9.2 28.90
4 4 3 9.2 28.90
5 4 3 9.2 28.90
6 4 3 9.2 28.90
8 4 3 9.2 28.90
9 4 3 9.2 28.90
10 4 3 9.2 29.90
Il 4 3 9.2 28.90
12 4 3 9.2 28.90
17.79 70.96 85.87 84.71
17.79 -23.37 35.75 89.47
17.79 21.33 56.84 66.03
17.79 61.40 80.93 71.07
17.79 90.43 69.96 77.78
17.79 -641.42 -1.16 63.05
17.79 -20.51 58.61 80.57
17.79 54.74 56.07 89.28
17.79 02.41 27.96 88.68
17.79 53.65 43.31 77.67
2.59 61.53 -388.58 89.20
2.59 -233.77 32.74 86.18
2.59 —1.71 36.94 58.15
2.59 -15.49 29.04 62.97
2.59 34.78 -44.44 67.10
2.59 -928.23 -171.26 42.48
2.59 -63.55 -26.23 46.10
2.59 5.12 27.11 71.78
2.59 50.44 -74.22 70.31
2.59 —15.20 -194.oS 55.80
20.94 53.56 72.43 99.14
20.94 69.91 56.59 84.79
20.94 75.16 -23.31 85.02
20.94 90.01 50.83 88.84
20.94 34.28 71.11 91.98
20.94 53.68 76.62 86.50
20.94 43.61 35.03 93.26
20.94 39.23 63.88 92.84
20.94 82.56 79.22 95.08
20.94 74.32 73.21 92.20
20.94 71.55 69.82 88.82
continued
12.51
12.51
12.51
12.51
12.51
12.51
12.51
12.51
12.51
21.30
21 .30
21.30
21.30
21.30
21.30
21.30
21.30
21.30
21 .30
10.65
10.65
10.65
10.65
10.65
10.65
10.65
10.65
10.65
10.65
24.60
24.60
24.60
24.60
24.60
24.60
24.60
24.60
24.60
24.60
24.60
21.32
21.32
21.32
21.32
21.32
21.32
21.32
21.32
21.32
21.32
6.12
6.12
6.12
6.12
6.12
6.12
6.12
6.12
6.12
6.12
24.48
24.48
24.48
24.48
24.48
24.48
24.48
24.48
24.48
24.48
24,48
96
-------
TABLE 8—9. (continued)
I. I I
RUN PLOT SLOPE FILTER CONTACT CONTACT REDUC REDUC
1 5 3 4.6 14.45
2 5 3 4.6 14.45
3 5 3 4.6 14.45
4 5 3 4.6 14.45
5 5 3 4.6 14.45
6 5 3 4.6 14.45
8 5 3 4.6 14.45
9 5 3 4.6 14.45
10 5 3 4.6 14.45
11 5 3 4.6 14.45
12 5 3 4.6 14.45
1 7 5 9.2 22.39
2 7 5 9.2 22.39
3 7 5 9.2 22.39
4 7 5 9.2 22.39
5 7 5 9.2 22.39
6 7 5 9.2 22.39
7 7 5 9.2 22.39
8 7 5 9.2 22.39
9 7 5 9.2 22.39
10 7 5 9.2 22.39
11 7 5 9.2 22.39
12 7 5 9.2 22.39
8 5 4.6 11.19
2 8 5 4.6 11.19
3 8 5 4.6 11.19
4 8 5 4.6 11.19
5 8 5 4.6 11.19
6 8 5 4.6 11.19
7 8 5 4.6 11.19
8 8 5 4.6 11.19
9 8 5 4.6 11.19
10 8 5 4.6 11.19
11 8 5 4.6 11.19
12 8 5 4.6 11.19
5.74 34.65 58.81 94.98
5.74 58.37 74.05 75.13
5.74 68.60 24.76 —155.17
5.74 44.82 -42.89 60.72
5.74 70.07 59.36 86.87
5.74 39.40 59.5! 79.96
5.74 47.20 14.22 89.75
5.74 52.27 52.07 91.15
5.74 67.75 66.54 94.36
5.74 85.82 82.18 86.76
5.74 78.27 79.10 96.17
15.34 12.53 41.47 91.21
15.34 63.32 79.27 68.74
15.34 3.21 74.70 5.63
15.34 35.60 40.42 54.25
15.34 -213.98 2.91 50.09
15.34 92.57 49.11 63.58
15.34 36.19 —1.42 86.19
15.34 33.95 -39.87 73.21
15.34 11.47 2.88 44.37
15.34 52.77 42.56 65.30
15.34 17.64 50.12 24.35
15.34 100.00 -83.10 48.80
0.14 5.72 -36.86 81.92
0.14 30.12 43.67 44.07
0.14 44.74 68.97 35.35
0.14 45.46 45.93 1.23
0.14 70.74 —169.97 26.56
0.14 93.25 44.84 39.34
0.14 12.64 —17.00 57.31
0.14 52.95 11.32 45.71
0.14 —13.88 -74.51 —4.32
0.14 57.04 45.89 21.28
0.14 —62.32 -10.54 —69.07
0.14 67.31 —107.19 19.15
AYE 13.88 10.35 11.03 15.12 62.30
SID 7.95 7.95 144.78 79.96 40.48
WIDTH TINE TINE GOOD FAIR REDUC REDUC REDUC
m (600D} (FAIR) (predict)(predict) (obs) lobs) (obs)
IP TN 198
12.30
12.30
12.30
12.30
12.30
12.30
12.30
12.30
12.30
12.30
12.30
19.05
19.05
19.05
19.05
19.05
19.05
19.05
19.05
19.05
19.05
19.05
19.05
9.53
9.53
9.53
9.53
9.53
9.53
9.53
9.53
9.53
9.53
9 • 53
9.53
9.27
9.27
9.27
9.27
9.27
9.27
9.27
9.27
9.27
9.27
9.27
18.88
18.88
18.88
18.88
18.88
18.88
18.88
18.88
18.88
18.88
18.88
18.88
3.67
3.67
3.67
3.67
3.67
3.67
3.67
3.67
3.67
3.67
3.67
3.67
97
-------
APPENDIX C
POLLUTANT REDUCTION & NITROGEN LEACHING GRAPHS
98
-------
% BARE PLOT PHOSPHORUS LOSSES
Plots 1. 2 & 3 Slope = 4%
1-
0.9 -
0.8
(n
0
;L ::::
cn 0.5-
0.4 -
0.3-
Run
9.2 m Filter 4.6 m Filter No Filter
Figure c—i. Mass losses of TP from Plot 1 (with 9.2 m VFS) arid
Plot 2 (with 4.6 m VFS), expressed as a percentag.e
of Plot 3 (with no VFS) losses.
99
-------
% BARE PLOT NITROGEN LOSSES
Plots 1, 2 & 3 Slope = 4%
500 -.
4-00 -
f r i
0
-J
0
300-
o IN
m
Li
0
200-
z
\
io: ddjJ I 1d E
9.2 rn Filter 4.6 m T?ter No Filter
Figure C—2. Mass losses of TN from Plot 1 (with 9.2 m VFS) and
Plot 2 (with 4.6 m VFS), expressed as a percentage
of Plot 3 (with no VFS) losses.
100
-------
‘U
U)
0
-J
0
V
L
0
‘4-
0•
c i )
(J)
I-
100
90
80
70
60
50
40
30
20
10
0
] 9.2 m Filter
RUN
4.6 m Filter
____ No Filter
Figure C—3.
Mass losses of TSS
Plot 2 (with 4.6 in
of Plot 3 (with no
Plots 1, 2, & 3
BARE PLOT TSS LOSSES
Slope 4%
1 2 3 4 5 6 7 8 9 10 11 12
from Plot 1 (with 9.2 in VFS) and
VFS), expressed as a percentage
VFS) losses.
101
-------
% BARE PLOT
Plots
PHOSPHORUS
4, 5 & 6 Slope = 3%
Run
4;6 rn Filter
No Filter
Figure C—4.
Mass losses of TP from Plot 4 (with 9.2.m VFS) and
Plot 5 (with 4.6 m VFS), expressed as a. percentage
of Plot 6 (with no VFS) losses.
LOSSES
100
go
80
70
60
50
40
30
20
10
U)
U)
0
-J
0
0
V
L
0
‘4-
0
0
0
0
1 2 3 4
92 rn Filter
5
6
7
8
9 10
11 12
102
-------
% BARE PLOT NITROGEN LOSSES
Plots 4, 5 & 6 Slope = 3%
200 - ____________________________ -
190-
180-
170-
160-
150-
-j 140-
2 130-
120-
U
l _ l1/
o . .
o
— ‘ — r
‘4— / -. f f / ? I /
o 9Q_ l I I I I I. I I
/ / I I I I I I I
Xe I I . ‘ I ‘SI I I I
80—
/ ,. / / / , I I / I
z— 7/ I I I / I . ‘ I I
S. ., — I I I I I / I I
/ .‘ /
— 60 — i / , I r .‘ ‘ s 7 . / /
o / / / , 1 / ‘I /
So- ; ‘ ;: 2
I. — / I I / I 1 5 / / I
40— cI I /I’ / /
I Ii - ‘ I I 7 1 7 I /
/ vI I I I I 1 / 7
r E / / / I /
20- k1:;I;
L/l I I I I I I I I I
10— , ii / / /
i,’r — — — / /
— _—-T ’-1 .r
1 2. 3 4 5 6 7 8 9 10 11 12
Run
ZZJ 9.2 m Filter 4.6 m Filter No Filter
Figure C—5. Mass losses of TN from Plot 4 (with 9.2 m VFS) and
Plot5 (with 4.6 m VFS), expressed as a percentage
of Plot 6 (with no VFS) losses.
103
-------
% BARE PLOT TSS LOSSES
Plots 4, 5, & 6 Slope = 3%
0
VZI 0.2 m Filter
RU N
] 4.6 m Filter
‘ / No Filter
Figure C—6. Mass losses of TSS from Plot 4 (with 9.2 m VFS) and
Plot 5 (with 4.6 m VFS), expressed as a percentage
of Plot 6 (with no VFS) losses.
260
240
220
200
180
160
140
120
100
80
60
40
20
U I
‘V
UI
UI
0
-J
-4 ..
0
c i.
‘V
L
0
0
w
c / i
I-
1 2 3 4 5 6 7 8 9 10 11 12
104
-------
% BARE PLOT PHOSPHORUS LOSSES
Plots 7, 8 & 9 Slope = 5%
320 -
300
280
260
240
-J
220
o
200
180
o
I r
IQ’ P
140
• 120
0
100 171 ; / ; P1 ‘. \/ K
o / / /
::
40
20 ‘!7O 1 2
Run
92 m Filter 4.6 m Filter No Filter
Figure C—7. Mass losses of TP from Plot 7 (with 9.2 in VFS) and
Plot 8 (with 4.6 in VFS), expressed as a percentage
of Plot 9 (with no VFS) losses.
105
-------
% BARE PLOT NITROGEN LOSSES
Plots 7. 8 & 9 Slope = 5%
280
260
240
220
. 200
180
ii
160
0
140
120 -
60 / /
/ ‘,
I / I I
40 / , / , , \ I ¼ I
I / I I T_t 1 /
— 1 r,—i —————S /
2, / I Til / — /
I S I I S I S
I I P 1
I I I I ‘ / “1 I
0- •—T-—i .—r --i -’.i
1 2 3 4 5 6 7 8 9 10 11 12
Run
9.2 m Filter 4.6 m Filter No Filter
Figure C—8. Mass losses of TN from Plot 7 (with 9.2 m VFS) and
Plot 8 (with 4.6 m VFS), expressed as apercentage
of Plot 9 (with no VFS) losses.
106
-------
% BAPE PLOT 155 LOSSES
Plots 7, 8, & 9. Slope = 5%
170 -
160-
150 -
140-
130-
V
120-
0
-J 110-
2 100-
— ; 1/i /
90 — r,i ,
, r i — — —
L d # r,’i ‘ S “
o — . ‘ , “ “
— — / ,‘1 S S
/ / — I LtJ / — 0’ 9
‘4— 70 — — 9 , — ‘ i L’J — — ‘ ‘ /
o “ / [ i ”J / 0’ 9
‘ s r,ci ‘ ‘1
60 — I
9 ‘ 9 ‘ — I\ [ ,’J 9 \ ‘9 9 \ 9 .
I / i IT/ i / — I .‘ — ,
i1 50- - ‘ hf ‘ ‘
- - , Nr-i / - ‘ ‘‘-i
40- / 0’ 1t -i - / ‘ . /
/ 0” “5/ 0’ ....J’\r/i 0/ I , ‘ / I
0’ 0’ PIT/I , - ‘J / ‘ - /
30- ; : /
20— riti
9 S/ , / ‘ I, I.J,J ‘ — ‘s/ ‘ — ‘ —
, 11T/i . - —
10— — — i,’i’s ,r,’j
rir i
, , / ‘ , i,’r—.r,i ‘ , — / —
‘-i
1 2 3 4 5 6 7 8 9 10 11 12
RUN
9.2 rn Filter • 4.6 m Filter No Filter
Figure C—9. Mass losses of TSS from Plot 7 (with 9.2 m VFS) and
Plot 8 (with 4.6 in VFS), expressed as a percentage
of Plot 9 (with no VFS) losses.
107
-------
Nitrogen Leaching, Plot 1 — 9.2rn Filter
Arnmonium N
16-
15 -
14-
13 -
12 -
11 —
a
4,-’
—
9-
j
4- . ..‘,
h
11 22 28 34 43 51 58 65 85 105 125
Depth r tGrvaL cm
Pre—B Post—B Pre—F Post—F
Figure C—10. Comparison of ammonium—N in soil profiie.of bare
portion(Pre—B) and VFS (Pre—F) of Plot 1 before
UAN tests and after UAN tests (Post—B and Post-F).
108
-------
Nitrogen Leaching, Plot 2, 4.6m Filter
Arnmonium N
6-
5
o 4
-c
-z
I
z
0
_I.._
11 22 28 34 43 51 58 65 85 105 125
Depth Interval, cm
ZI Pre—’B Post—B Pre—F Post—F
Figure C—li. Comparison of ammonium—N in soil profile of bare
portion (Pre—B) and VFS (Pre—F) of Plot 2 before
• UAN tests and after UAN tests (Post—B and Post—F).
109
-------
Nitrogen Leaching, Plot 3 — No Filter
Arnrnoniurn N
7-
6- 7
/
/
5- /
0 /
-C /
/
4-7 /-
/_. /\
/\ /\
3 /\ /N
— /\ /N 7
/\ /\ /
/\ /\ /
2-/ /\ /
/\ /\
/\\ ,/\ /\
/\\ /\ /\
1-/\ /\ L7
/\/\
11 22 28 34 43 51 58 65 85 105 125
Depth Interval. cm
Pre—B Post—B
Figure C—12. Comparison of ammonium—N in soil profile of Plot 3
before UAN tests (Pre—B) and after UAN tests (Post—
B).
110
-------
Nitrogen Leaching, Plot 4, 9.2m Filter
Arnmonium N
14-
13
12
11 - I
10 -
0
-c 9-
I
z 6-
5- - -
. -
11 22 28. 34 43 51 58 65 85 105 125
Depth Interval. cm
Pre—B Post—B Pre—F Post—F
Figure C—13. Comparison of ammonium—N in soil profile of bare
portion (Pre—B) and VFS (Pre—F) of Plot 4 before
UAN tests and after UAN tests (Post—B and Post—F).
111
-------
Nitrogen Leaching, Plot 5, L1 .6m Filter
Arnrnonium N
18 -
17
16
15
14
13
o 12
N
- 10
9
8
z
= 7
0
( I) 5
• ! LhLU __
11 22 28 34 43 51 58 65 85 105 125
Depth Interval. cm
Pre—B Post—B Pi-e—F Post—F
Figure C—14. Comparlsonof.ammoniuin—N in soil profile of bare
portion (Pre—B) and VFS (P.re—F) of Plot 5 before
UAN tests and after tJAN tests (Post—B and Post—F).
112
-------
Nitrogen Leaching, Plot 6 — No Filter
Arnmcnium N
9-
8-
/ /\
/ /N
7 N /
— / /N /_
6 - /s \ /_ /\ /\
-c /\ N / /\ /\ /\
/\ N / /\ ,‘N /\
• 5 /\ N / /\ /N /\
J\ _\ / /N /\ /\
/\ /\ / /N /\ /\
4-/N /\ 7 / /N /N /\
/\ /\ / / /N /\ /\
/\ /\ / /\ /N /\ /\
W 3-/\ /\ / /N /N /\ /\
/\ /\ _\ 7 / /N /\ /\ /\
/ \ / / N / / / / N / N / ‘N / \
2-/\ /\ /\ / / /\ / //\ J\ /\
/\/N /\ / / /\ / / / ./\/\
/\ /\ /\ / / /\ / /N /\ /\ /N
1 /\ /\ /\ / / /\ / /N ,/N /\ /\
/\ /N /\ / / /\ / /N /N /\ /\
11 22 28 34 43 51 58 65 85 105 125
Depth Interval, cm
Pre—B Post—B
Figure C—15. Comparison of ammonium—N in soil profile of Plot 6
before UAN tests (Pre—B) and after UAN tests (Post—
B).
113
-------
Nitrogen Leaching, Plot 7, 9.2m Filter
Ammonium
24 -
22
20
18
o 16
14
12
10
: L [ kJ ILLJ..I_ ,ji k
11 22 28 34 43 51 58 65 85 105 125
Depth Interval. cm
Pre—B Post—B Pre—F Post—F
Figure C—16. Comparison of ámrnonium—N in soil profile of. bare
portion (Pre—B) and VFS (Pre—F) of Plot 7 before
UAN tests and afterUAN tests (Post—B and Post—F).
114
-------
Nitrogen Leaching, Plot 8,
Arnmonium N
17
16
15
14
13
12
0
cr 10
9
8
I
7
6
U)
5
4
3
2
0
4.6m Filter
11 22 28 34 43 51 58 65 85 105 125
Pre—B
Depth ntervaI. cm
Post—B Pre—F
Figure C—l7.
Comparison of ammoniuin—N in soil profile of bare
portion (Pre—B) and VFS (Pre—F) of Plot 8 before
UAN tests and after UAN tests (Post—B and Post—F).
Post—F
115
-------
Nitrogen
28
26
24
22
20
18
16
14
12
10
8
6
4
2
0
Leaching, Plot 9
Arnmonium N
— No FHter
11 22 28 34 43 51 58 65 85 105 125
Depth Interval. cm
Pre—B Post—B
Figure C ]8.
Comparison of. anunoniuTn—N in soil profile of Plot 9
before UAN tests (Pre—B) and after UAN tests (Post—
B).
0
-c
I
z
0
(1)
116
-------
Nitrogen. Leaching, Plot 1 — 9.2m Filter
Nitrate N
30 -
28 -
26 -
24 -
22 -
o 20-
-c
0 ”
16-
14
_ LL
11 22 28 34 43 51 58 65 85 105 125
Depth Interval, cm
Era—B Poet—B Pre—F Post—F
Figure C—19. Comparison of nitrate—N in soil profile of bare
portion (Pre—B) and VFS (Pre—F) of Plot 1 befOre
UAN tests and after UAN tests (Post-B and Post—F).
117
-------
Nitrogen Leaching, Plot 2, 4.6m Filter.
Nitrate N
40-
35 -
30 -
0
-c
F
20-
a
z
15-
. _____
11 22 28 34 43 51 58 65 85 105 125
Depth Interval. cm
Pre—B Post—B Pre—F Post—F
Figure C—20. Comparison of nitrate—N in soil profile of. bare
portion (Pre—B) and ‘IFS (Pre—F) of Plot 2 before
UAN tests and after UAN tests (Post—B and Post—F).
118
-------
Nitroen Leach.inq, Plot 3 —. No Filter
Nitrate N
45 -
40-
o 30-
-c N
N
25- N
N
N
20- N
N
N
15- N —
N N -S
N N
10- N
11 22 28 34 43 51 58 65 85 105 125
Depth Interval, cm
Pre—B Post—B
Figure C—21. Comparison of nitrate—N in soil profile of Plot 3
before UAN tests (Pre—B) and after tJAN tests (Post—
B).
119
-------
Nitrogen Leaching, Plot 4, 9.2m Filter
Nitrate N
28-
26 -
24 -
22 -
20 -
a
-c 18-
o ).
- 16-
14-
0
z 12-
___H_
11 22 28 34 43 51 58 65 85 105 125
Depth Interval. cm
• Pre—B Post—B Pre—F Post—F
Figure C—22. Comparison of nitrate—N in soil profile of bare
portion (Pre--B) and VFS (Pre—F) of Plot 4 befOre
UAN tests and after UAN tests (Post—B and Post—F).
120
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Leaching, Plot
Nitrate N
5, 4.6m Filter
0
ZI Pre—B
Post—F
Figure C—23.
Comparison of nitrate—N in soil profile of bare
portion (Pre—B) and VFS (Pre—F) of Plot 5 before
UAN tests and after UAN tests (Post—B and Post—F).
Nitrogen
90
80
70
60
50
40
30
20
10
C
-c
C . .
F ’)
z
0
U )
11 22 28 34 43 51 58
Depth Interval. cm
Post—B Pre—F
65 85 105 125
121
-------
• Nitrogen Leaching, Flot 6 — No Filter
Nitrate N
70 -
/
60
/
/
50 /
0 /
/
‘N. /
40- /
/
/
20-/\
/\ \
/\
11 22 28 34 43 51 58 65 85 105 125
Depth IntervaL crri
Pre—B Post—B
Figure C—24; Comparison of nitrate—N in sojI profile of Plot 6
before UAN tests (Pre—B) and after UANtests (Post—
B).
122
-------
Nitrogen Leaching, PIot7, 9.2m FHter
Nitrote N
45 -
40-
35 -
o 30-
-c
0 ’
- 25-
F)
20-
0
11 22 28 34 43 51 58 65 85 105 125
Depth Interval. cm
Pre—B Post—B Pre—F Post—F
Figure C—25. Comparison of nitrate—N in soil profile of bare
portion (Pre—B) and VFS (Pre—F) of Plot 7 before
UAN tests and after UAN tests (Post—B and Post—F).
123
-------
Nitrogen Leaching, Plot 8, 4.6m Filter
Nitrate N
70 -.
60
50 -
C
-c
- 40-
30 -
C
1 L
11 22:’ 28 34 43 51 58 65 85 105 125
____ Depth IntervaL cm
VLI •Pre—B ‘ : Post—B Pre—F Post—F
Figure C—26. Compaiisón of nitrate—N in soil profile of bare
portion (Pre—B) and VFS (Pre—F) of Plot 8 befOre
UAN tests and after UAN tests (Post—B and Post—F).
124
-------
• Nitrogen Leaching, Plot 9 :— No Filter
Nitrate N
34 -
32-
N
30-
28-
26-
24-
N
22-
20-
N N
18- \
16-
‘0
Z 14 \ —
12- N
U. )
10- \ \ 7 —
8-
rN N / N /\ N
\ / /N
i
2-/\ N / 1 4N -1N /\ V1N ’\
0 - — - — JZ -. 1 N’ 1 ’T ’ “N’ 1 ”N’ . /N1 1 ,
11 22 28 34 43 51 58 65 .85 105 125
Depth Interval, cm
Pre—B Post -B
Figure C—27. Comparison of nitrate—N In soil profile ,of.P,lot 9
before UAN tests (Pre—B) and.’ ‘after UAN tests ‘(Post—
B).
125
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