United States Environmental Protection Agency
CBP/TRS 4/87
August 1987
Evaluating Nutrient and
Sediment Losses from
Agricultural Lands:
Vegetative Filter Strips
Chesapeake
Bay
Program
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EVALUATING NUTRIENT AND SEDIMENT LOSSES
FROM AGRICULTURAL LANDS: VEGETATIVE FILTER STRIPS
by
T. A. Dillaha
Department of Agricultural Engineering
R. B. Reneau
Department of Agronomy
S. Mostaghimi
V. 0. Shanholtz
Department of Agricultural Engineering
Virginia Polytechnic Institute and State University
and
W. L. Magette
Department of Agricultural Engineering
University of Maryland
Project Number X-00315-01-0
Project Officer
Joseph Macknis
Chesapeak Bay Liaison Office
Annapolis, MD 21403
This study was conducted in cooperation with the
Virginia Polytechnic Institute and State University
Departments of Agricultural Engineering and Agronomy
and the Virginia Agricultural Experiment Station
U.S. Environmental Protection Agency
Region III
Chesapeake Bay Liaison Office
Annapolis, MD 21403
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DISCLAIMER
This report has been reviewed by the Chesapeake Bay Liaison Office, U.S. Envi-
ronmental Protection Agency, and approved for publication. Mention of trade
names or commercial products does not constitute endorsement or recommendation
for use.
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PREFACE
This report is part of a bi-state research effort funded by the EPA
Chesapeake Bay program between the states of Maryland and Virginia. This report
describes the Virginia project. The Maryland project is described in another
publication.
The Virginia project (EPA grant # X-00315-01-0) evaluates soils and slopes
characteristic of the ridge and valley province. The Maryland project (EPA
grant # X-00314-01-0) evaluates soils and slopes characteristic of the mid-
Atlantic coastal plain. Together these projects provide an assessment of the
effectiveness of vegetated filter strips in removing pollutants from surface
water under different environmental conditions.
Each project used their own results to develop a empirical model that will
assist in determining optimum applications and design requirements for vege-
tated filter strips.
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ABSTRACT
A rainfall simulator was used to evaluate the effectiveness of vegetative
filter strips (VFS) for the removal of sediment, nitrogen (N), and phosphorus
(P) from feedlot and cropland runoff. Simulated rainfall was applied to nine
experimental field plots on an eroded Groseclose silt loam soil (clayey, mixed,
mesic Typic Hapludalt) with a 5.5 by 18.3 m bare source area (simulated feedlot
or cropland) and either a 0, 4.6, or 9.1 m VFS located at the lower end of each
plot. Fresh dairy manure was applied and compacted into the bare portions of
the plots at rates of 7,500 and 15,000 kg/ha during the feedlot simulations and
222 kg/ha of liquid (N) and 112 kg/ha of P205 and K20 were applied to the plots
during the cropland simulations. Water samples were collected from the base
of each plot and analyzed for sediment and nutrient content. One set of plots
was constructed so that flow through the filters was concentrated rather than
shallow and uniform.
The 9.1 and 4.6 m VFS with shallow uniform flow removed 87 and 75% of the
incoming suspended solids, 69 and 57% of the incoming P, and 72 and 61% of the
incoming N, respectively. Soluble nutrients in the filter effluent were some-
times greater than the incoming soluble nutrient load, presumably due to lower
removal efficiencies for soluble nutrients and the release of nutrients previ-
ously trapped in the filters. Vegetative filters with concentrated flow were
much less effective than the shallow uniform flow plots, with percent reductions
in sediment and nutrient loadings averaging 23 to 37% less for sediment, 46 to
53% less for N, and 43 to 46% less for P. The cropland filters were much more
effective than the feedlot filters, but this increased effectiveness was due
to reduced inflow of sediment, nutrients, and runoff into the filters because
of higher infiltration rates in the cropland source areas.
Observation of existing cropland filter strips showed that in-field filter
strips were not likely to be as effective as experimental field plots because
of problems with flow concentrations.
Key Words: grass filters, filter strips, buffer strips, vegetative filters,
sediment removal, feedlots, phosphorus removal, nitrogen removal
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TABLE OF CONTENTS
TITLE PAGE i
PREFACE iii
ABSTRACT iv
TABLE OF CONTENTS v
LIST OF FIGURES vii
LIST OF TABLES ix
ACKNOWLEDGEMENTS xi
INTRODUCTION 1
LITERATURE REVIEW 4
RUNOFF CONTROL FOR FEEDLOTS 5
SEDIMENT TRANSPORT THROUGH VFS 7
NUTRIENT TRANSPORT THROUGH VFS 9
SUMMARY 11
EXPERIMENTAL PROCEDURES 12
SCOPE OF STUDY 12
PLOT DESIGN AND LOCATION 12
PLOT CONSTRUCTION 16
PLOT PREPARATION FOR FEEDLOT SIMULATION 16
Manure Application 16
PLOT PREPARATION FOR CROPLAND SIMULATION 17
RAINFALL SIMULATOR 18
SAMPLING PROCEDURE 19
ANALYTICAL TECHNIQUES 20
Total Suspended Solids 20
Total Kjeldahl Nitrogen 20
Ammonia 20
Nitrate-Nitrite Nitrogen 20
Total Phosphorus 21
Ortho-Phosphorus 21
Chemical Oxygen Demand 21
Extractable Soil Nitrogen 21
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RESULTS AND DISCUSSION 22
FEEDLOT SIMULATIONS 22
Rainfall Simulator Performance 22
Sediment Yield 22
Phosphorus Yield 31
Nitrogen Yield 40
CROPLAND SIMULATIONS 42
Rainfall Simulator Performance 42
Sediment Yield 42
Phosphorus Yield 49
Nitrogen Yield 52
Soil Inroganic Nitrogen 52
Concentration of Inorganic No 52
Nitrogen balance 55
COMBINED FEEDLOT AND CROPLAND SIMULATIONS 59
EXISTING VEGETATIVE FILTER STRIP SURVEY 59
SUMMARY AND CONCLUSIONS 64
BIBLIOGRAPHY 67
APPENDIX A 71
APPENDIX B - VEGETATIVE FILTER STRIP DESIGN AND EVALUATION PROCEDURE 87
PROGRESSION EQUATION 87
RECOMMENDED DESIGN/EVALUATION PROCEDURE 88
DESIGN EXAMPLE 89
SUMMARY 90
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LIST OF FIGURES
Figure 1. Schematic diagram of experimental field
plots 14
Figure 2. Sediment yields for plots QF4-6, Test 1
(feedlot simulation) 28
Figure 3. Sediment yields for plots QF4-6, Test 2
(feedlot simulation) 29
Figure 4. Sediment concentrations for plots QF7-9,
Test 1 (concentrated flow plots), Run 1
(feedlot simulation) 32
Figure 5. Sediment concentrations for plots QF4-6,
Test 1 (uniform flow plots) Run 1
(feedlot simulation) 33
Figure 6. Ortho-phosphorus loss from plots QF1-3
(feedlot simulation) 36
Figure 7. Ortho-phosphorus loss from plots QF4-6
(feedlot simulation) 37
Figure 8. Ortho-phosphorus loss from plots QF7-9
(feedlot simulation) 38
Figure 9. Sediment loss from plots QF4-6, Test 2,
(feedlot simulation) 39
Figure 10. Total nitrogen loss from plots QF4-6,
Tests 1 and 2 (feedlot simulation) 41
Figure 11. Percent reduction in sediment yield for
plots QF1-9 (cropland simulation) 48
Figure 12. Sediment yield and percent reduction in sediment
loss for plots QF5 and 6, T3R1-T4R3
(cropland simulation) 51
Figure 13. Nitrate nitrogen in the bare soil profile before
(B—B) and after (A A) cropland simulation 53
Figure 14. Ammonium nitrogen in the bare soil profile before
(B B) and after (A A) cropland simulation 54
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Figure 15.
Nitrate nitrogen in the filter strip soil profile
before (B B) and after (A A) cropland
simulation
56
Figure 16. Ammonium nitrogen in the filter strip soil profile
before (B B) and after (A A) cropland
simulation 57
Figure 17. Inorganic nitrogen (kg/ha) present in selected
soil layers for the bare portion of the plots
before and after application of nitrogen and
simulated rainfall 58
Figure 18. Inorganic nitrogen (kg/ha) present in selected
soil layers for the filter strip portion of the
plots before and after application of nitrogen
and simulated rainfall 60
Figure A-l. Sample filter strip evaluation form 71
Figure B-l. Design Example 91
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15
23
24
25
26
31
34
43
44
,45
,46
,49
.50
.61
.62
.72
LIST OF TABLES
Plot characteristics and operating
conditions
Rainfall simulator performance
Sediment, nutrient, and water yields from feedlot
simulations by plot
Sediment, nutrient, and water yields from feedlot
simulations by plot and test
Sediment, nutrient, and water yields from feedlot
simulations by plot, test and run
Percent reduction in simulated feedlot sediment,
nutrient, and water yields by plot
Percent reduction in simulated feedlot sediment,
nutrient, and water yeild by plot and test
Rainfall simulator performance (cropland
simulations)
Sediment, nutrient, and water yields from
cropland simulations by plot
Sediment, nutrient, and water yields for cropland
simulations by plot and test
Sediment, nutrient, and water yields from
cropland simulations by plot, test and run
Percent reduction in simulated cropland
sediment, nutrient, and water yield by plot
Percent reduction in simulated cropland
sediment, nutrient, and water yield by plot
and test
Sediment, nutrient, and water yields for all
simulations
Percent reduction in sediment, nutrient, and
water yields for all simulations
Water quality concentration and runoff data
for feedlot simulations
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Table A-2. Water quality concentration and runoff data
for cropland simulations 80
Table B-l. VFS data for regression equations 92
Table B-2. Design Example 93
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ACKNOWLEDGEMENTS
This research is a contributing project to Southern Regional Research Project
S-164, "Application of Water Quality Models for Agriculture and Forested
Watersheds." Special acknowledgement is made to the following, who generously
assisted in constructing and conducting the experimental plot studies: Rebecca
Caldwell, Jan Carr, Eldridge Collins, Dexter Davis, Louise Howard, Zeena Ishie,
Seow Loong, Phil McClellan, Patty Noyes, Blake Ross, Jenny Schwanke, and others.
Acknowledgement also is made to Helen Castros, Jenny Schwanke, and Lenore
Oosterhuis for analyzing the water quality samples, Louise Howard and Jan Carr
for analysis of the flow data, Dan Storm for preparation of the figures, and
Sharon Akers and Diane Beckwith for typing the manuscript.
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INTRODUCTION
The Environmental Protection Agency's Chesapeake Bay Program identified
agriculture as the major source of sediment and nitrogen (N) and a significant
source of phosphorus (P) in the Chesapeake Bay drainage basin (USEPA, 1983).
To help reduce agricultural nonpoint source (NPS) pollutant inputs to the Bay
system, the Commonwealth of Virginia implemented cost sharing programs to en-
courage the adoption of Best Management Practices (BMPs) by farmers. Vegetated
filter strips (VFS) are one practice which is being promoted. Vegetative filter
strips are bands of planted or indigeneous vegetation situated downslope of
cropland or animal production facilities. Their purpose is to provide localized
erosion protection and to filter nutrients, sediment, organics, pathogens, and
pesticides from agricultural runoff before it can reach receiving waters. Due
to their low installation and maintenance costs and perceived effectiveness in
removing pollutants, conservation and regulatory agencies have encouraged their
use.
Vegetated filter strips have been shown to be an effective BMP for the
control of some NPS pollutants, especially sediment and sediment-bound contam-
inants. Their effectiveness for controlling pathogens, fine sediment, and
soluble nutrients such as nitrate (N03) or ortho-phosphorus (0-P), however, is
much less certain, and has not been addressed sufficiently. Although consid-
erable research on VFS has been conducted over the past 10 years, efforts have
focused almost exclusively on either sediment removal from strip mine runoff
or nutrient and solids removal from feedlot runoff. Design procedures for the
removal of sediment from runoff have been developed from the strip mine work
but these procedures have not received widespread verification for cropland
situations and do not consider nutrient transport. Research involving VFS and
feedlot runoff has not produced any widely accepted design procedures other than
those based on the premise that the VFS should be large enough to infiltrate
all the runoff from a design storm.
Considerable research has also been conducted concerning the design of
overland flow systems for the treatment of municipal wastewaters but their de-
sign is still based more on past experience than design formulas relating filter
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characteristics, influent loadings, and effluent requirements. Treated munic-
ipal wastewaters which have been applied to overland flow systems generally have
low suspended solids concentrations and predominately soluble nutrients as op-
posed to agricultural runoff which typically has high suspended solid concen-
trations and nutrients which are predominately sediment-bound. These physical
and chemical differences reduce the usefulness of overland flow research for
agricultural design purposes.
Because of a lack of research and verified design procedures, VFS design
is generally based on past experience and there have been many system failures.
Inadequate knowledge of VFS dynamics has resulted in recommendations for their
use in many areas where they are inappropriate because of topographic limita-
tions. Before VFS can be effectively used for reducing agricultural NPS pol-
lution, sound design procedures must be developed that relate sediment and
soluble and sediment-bound pollutant transport with site and VFS character-
istics. Without these procedures, VFS will not be used effectively and water
quality improvement will be reduced.
The major goal of this research was to evaluate the circumstances under
which VFS are effective in reducing sediment and nutrient losses from cropland
and areas of confined livestock activity in Virginia. To achieve the above
goal, the following specific objectives were undertaken:
1. To conduct field plot experiments designed to investigate sediment, N, and
P transport as influenced by type of runoff (cropland or feedlot), runoff
rates, and filter strip length, slope, and hydraulic properties. Of special
interest was the effect of concentrated flow on VFS performance as opposed
to shallow uniform flow.
2. To conduct a survey of existing VSF located in the Commonwealth of Virginia
and to qualitatively evaluate VFS performance in field situations.
3. To develop a VFS design model which considers the transport of sediment,
P, and N.
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The results of the experimental plot studies and field surveys of existing
VFS are presented in the main body of this report and covers investigations
performed in Virginia. A simplified procedure for VFS design based upon re-
search conducted at Virginia Tech is presented in Appendix B. A separate report
by the University of Maryland will present the results of a parallel and coop-
erative study conducted in Maryland. A comprehensive model derived from both
the Virginia and Maryland plot studies will be presented in a latter report.
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LITERATURE REVIEW
Sediment, N, and P are three of the primary pollutants associated with
surface runoff from feedlots or areas of confined livestock activity and
cropland. One technique for removing these pollutants that is receiving in-
creased interest is the use of VFS. The major pollutant removal mechanisms
associated with VFS are thought to involve changes in flow hydraulics which
enhance the opportunity for the infiltration of runoff and pollutants into the
soil profile, deposition of total suspended solids (TSS), filtration of sus-
pended sediment by vegetation, adsorption on soil and plant surfaces, and ab-
sorption of soluble pollutants by plants. For these mechanisms to be effective,
it is essential that the surface runoff pass slowly through the filter to pro-
vide sufficient contact time for the removal mechanisms to function.
Infiltration is one of the most significant removal mechanisms affecting
VFS performance. Infiltration is important since many pollutants associated
with surface runoff enter the soil profile in the filter area as infiltration
takes place. Once in the soil profile, many pollutants, particularly N and P,
are removed by a combination of physical, chemical, and biological processes.
Infiltration is important also because it decreases the amount of surface runoff
which reduces the ability of runoff to transport pollutants. Since infiltration
is one of the more easily quantifiable mechanisms affecting VFS performance,
many filter strips for feedlot runoff control have been designed to allow all
runoff from a design storm to infiltrate into the VFS. This approach results
in large land requirements because it ignores other removal mechanisms.
Vegetative filter strips also purify runoff through the process of depo-
sition. Because VFS are usually composed of grasses and other types of dense
vegetation which offer high resistance to shallow overland flow, they decrease
the velocity of overland flow immediately upslope and within the filter causing
significant decreases in sediment transport capacity. If the transport capacity
is less than the incoming load of suspended solids, then the excess suspended
solids may be deposited and trapped within the VFS. Presumably, sediment-bound
pollutants will also be removed during this deposition process.
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The filtration of solid particles by vegetation during overland flow and
the absorption process are not as well understood as the infiltration and de-
position processes. Filtration is probably most significant for the larger soil
particles, aggregates, and manure particles while absorption is thought to be
a significant factor with respect to the removal of soluble pollutants.
The use of VFS for removing pollutants from cropland runoff is a relatively
new practice. Historically, pollution control efforts on cropland were designed
to minimize offsite pollution by reducing erosion and surface runoff within the
field. Vegetative filter strips on the other hand are designed to remove
pollutants from runoff once it has left the field and reaches filter strips on
the downslope boundaries of the field.
RUNOFF CONTROL FOR FEEDLOTS
Runoff control systems for feedlots are, or soon will be, mandatory in most
states. Runoff control systems generally consist of a clean water diversion
system, a runoff collection system, settling basins, holding basins, and a land
application system. The clean water diversion system is used to minimize the
amount of water which must be handled by the runoff collection system by ex-
cluding unpolluted outside surface water from the feedlot area. This is ac-
complished by diverting surface runoff from adjacent areas and feedlot building
roofs away from the feedlot. These diversions are usually accomplished with
diversion ditches and roof gutters. Runoff from the feedlot is transported to
the settling basins and holding ponds by the runoff collection system.
Settling basins are used to remove settleable solids from feedlot runoff
before it enters holding ponds or VFS. Settling basins typically remove 50-85%
of the manure solids from runoff (Vanderholm et al., 1978). This prevents
solids from reducing holding pond storage capacity or from being deposited in
VFS. Settling basins are generally less than 1 m deep and usually have a de-
tention time of 30 minutes. Designs are normally based upon a desired storage
volume for solids plus temporary storage for the design storm runoff. Solids
removed from the settling basins are generally applied directly to the land.
Settling basin capacities commonly range from 1.5-3.0 m3 per 100 m2 of feedlot
area.
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Holding ponds are designed for temporary storage of runoff before final
disposal on land. Wastes in ponds are purified somewhat by a combination of
physical, chemical, and biological processes, but the ponds are not designed
as a treatment facility. Holding ponds are generally designed to provide 2-3
months of storage so that liquid removal can be scheduled to avoid winter pe-
riods when the ground is frozen and to make use of the stored water and nutrients
during the crop growing season. In general, ponds should be dewatered whenever
land conditions permit applications without excessive runoff or damage to the
land and crops.
For feedlot operations in which the possibility of pollutant discharge to
receiving water is remote (small operations or operations far from receiving
water), holding ponds may not be necessary. In these situations, direct land
disposal to vegetative filter areas may be more appropriate. With this method,
lot runoff flows directly from the settling basin during runoff events to a
carefully graded VFS or infiltration areas. These systems are more appropriate
for smaller feedlot operations (less than 100 head) which do not generate large
volumes of runoff. The filter area may be either a channel similar to a long
grassed waterway with 1% slope or less or a broad flat overland flow area with
little slope.
Several approaches for designing VFS have been recommended by Vanderholm
et al. (1978). One method calculates the quantity of runoff expected from a
design storm, or series of storms, and sizes the VFS based upon the time re-
quired to infiltrate all the runoff. A second method bases the size of the
filter on a desired long-term hydraulic loading rate such as the average ap-
plication in cm per week or year. A third approach uses the estimated water
holding capacity of the filter area and sizes the filter so that infiltration
from a design storm will not exceed the water holding capacity.
Vanderholm et al. (1978) recommended that filter vegetation be harvested
regularly for nutrient removal and to maintain a thick grass cover. Livestock
also should be excluded from the VFS to minimize soil compaction and damage.
Additional details concerning the design, construction, and maintenance of
feedlot runoff control systems are available in the "Livestock Waste Facilities
Handbook" by the Midwest Plan Service (MWPS-18, 1985).
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SEDIMENT TRANSPORT THROUGH VFS
Historically, the design of VFS has been based almost entirely upon local
custom. Wilson (1967) presented the results of a sediment trapping study which
gave optimum distances required to trap sand, silt, and clay in flood waters
on flat slopes. He concluded that filter length, sediment load, flow rate,
slope, grass height and density, and degree of submergence all affect sediment
removal. A method for estimating the relationship between the parameters and
filter performance was not presented. Neibling and Alberts (1979) used exper-
imental field plots with a slope of 7% and a rainfall simulator to show that
0.6, 1.2, 2.4, and 4.9 m long grass filters all reduced total sediment discharge
by more than 90% from a 6.1 m long bare soil area. Discharge rates for the clay
size fraction were reduced by 37, 78, 82, and 83%, for the 0.6, 1.2, 2.4, and
4.9 m filters, respectively. Significant deposition of solids was observed to
occur just upslope of the leading edge of the VFS and 91% of the incoming
sediment load was removed within the first 0.6 m of the filter. Sediment dis-
charge of clay sized particles (<0.002 mm) was reduced 37% by the 0.6 m strip.
No equations were presented to estimate the influence of parameters on sediment
yield.
The most comprehensive research to date on sediment transport in VFS has
been conducted by a group of researchers at the University of Kentucky working
on erosion control in surface mining areas (Barfield et al., 1977; 1979; Kao
and Barfield, 1978; Tollner et al., 1976; 1978; 1982; Hayes et al., 1979; 1983).
Tollner et al. (1976) presented design equations relating the fraction of
sediment trapped in simulated vegetal media to the mean flow velocity, flow
depth, particle fall velocity, filter length, and the spacing hydraulic radius
(a parameter similar to the hydraulic radius in open channel flow which is used
to account for the effect of media spacing on flow hydraulics) of the simulated
media. Barfield et al. (1979) developed a steady state model, the Kentucky
filter strip model, for determining the sediment filtration capacity of grass
media as a function of flow, sediment load, particle size, flow duration, slope,
and media density. Outflow concentrations were primarily a function of slope
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and media spacing for a given flow condition. The Kentucky filter strip model
was extended for unsteady flow and non-homogeneous sediment by Hayes et al.
(1979). These investigators presented methods for determining the values of
the hydraulic parameters required by the Kentucky model for real grasses. Using
three different types of grasses, model predictions were reported to be in close
agreement with laboratory data. Hayes and Hairston (1983) used field data to
evaluate the Kentucky model for multiple storm events. Eroded material from
fallow cropland was used as a sediment source for the first time. 'Kentucky
311 (Festuca arundinacea) tall fescue trimmed to 10 cm was used and the model
predictions agreed well with the measured sediment discharge values. The
Kentucky researchers, like Neibling and Alberts (1979), observed that the ma-
jority of sediment deposition occurred just upslope of the filter and within
the first meter of the filter, until the upper portions of the filter were
buried in sediment. Subsequent flow of sediment into the filter resulted in
the advance of a wedge shaped deposit of sediment down through the filter. The
Kentucky research reported high trapping efficiencies as long as the vegetal
media was not submerged, but trapping efficiency decreased dramatically at
higher runoff rates which inundated the media.
Kao et al. (1975) proposed a VFS arrangement in which grass strips were
alternated with strips of bare ground to solve the problems associated with
sediment inundation of the filter and the killing of vegetation. Kao et al.
(1975) results indicated that with the proper VFS to bare ground strip width
ratio, most of the trapped sediment would be retained in the bare area just
upslope of the filter as reported by Neibling and Alberts (1979). This main-
tained high filter efficiencies and allowed the sediment trapped in the bare
strips to be removed periodically without damaging the systems. Kao's results
were based upon laboratory studies with artificial media and have not been
tested in the field.
At the present time, the Kentucky model is the only comprehensive model
available for VFS design with respect to sediment removal, but further field
testing and verification is required before it can be recommended for widespread
use. The model also will require modifications if organics or nutrient trans-
port is a design constraint.
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NUTRIENT TRANSPORT THROUGH VFS
Nutrient movement through VFS has been investigated by several researchers
but no comprehensive design methods have been presented. Doyle et al. (1977)
applied dairy manure to 7 x 5 m fescue plots on a Chester silt loam (fine-loamy,
mixed, thermic, Typic Hapludult) soil with a slope of 10%. Soluble nutrient
concentrations were measured after passing through 0.5, 1.5, and 4.0 m of fescue
filter strips. Soluble P (filtered runoff samples) was reduced by 9, 8, and
62% after passage through the 0.5, 1.5, and 4.0 m filters, respectively. Sol-
uble N03 losses decreased by 0, 57, and 68%, respectively, but NH4 concen-
trations increased with increasing filter length presumably due to the release
of NH4 from decomposing organic N, which was trapped in the filter previously.
Westerman and Overcash (1980) investigated runoff from an earthen open dairy
lot or loafing area and reported that 4.8 and 12.0% of the applied N and P,
respectively, appeared in runoff. They also observed that the largest storms
were responsible for most of the pollutant transport even though these storms
were responsible for only 17% of the total precipitation. Soil compaction in
the dairy lot also was investigated and runoff, as a percent of rainfall, was
21% for the open dairy lot and 10% for neighboring pastures over a 30 month
period.
Young et al. (1980) used a rainfall simulator to study the ability of VFS
to control pollution from feedlot runoff. Field plots were constructed on a
4% slope with the upper 13.7 m in an active feedlot and the lower 27.4 m planted
in either corn (Zea mavs) , oats (Auena sativa) , orchardgrass, (Dactvlis
alomerata) or a sorghum- (Sorahum vulaare) sudangrass (Sorahum sudanensis)
mixture. Water was applied to the plots to simulate a 25-year, 24-hour duration
storm. Total runoff, sediment, T-P, and total nitrogen (T-N) were reduced by
81, 66, 88, and 87%, respectively, by the orchardgrass and by 61, 82, 81, and
84%, respectively, with the sorghum-sudangrass mixture. The authors concluded
that VFS were a promising treatment alternative.
Thompson et al. (1978) studied the effectiveness of orchardgrass filter
strips on a sandy loam soil in reducing nutrient loss from the application of
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dairy manure to frozen or snow covered orchardgrass plots. Fresh dairy manure
was applied to 24 m orchardgrass plots and runoff quality determined after
traveling through 12 and 30 m of additional orchardgrass during natural runoff
events. Total P, total Kjeldahal nitrogen (TKN), and T-N were reduced by an
average of 55, 46, 41, and 45%, respectively, after passing through 12 m of
filter. A 36 m filter resulted in T-P, N03, TKN, and T-N reductions of 61, 62,
57, and 69%, respectively. Nutrient concentrations in the runoff from the 36
m filters approached that from control plots to which no manure had been added.
Bingham et al. (1978) applied poultry manure to 13 m long fescue grass
plots on an eroded Cecil clay loam (clayey, kaolinitic, thermic Typic Hapludult)
with 6-8% slopes and reported that filter strip length/waste area length ratios
of about 1.0 reduced pollutant loads to near background concentrations. Total
P, TKN, N03, and T-N were reduced 25, 6, 28, and 28%, respectively.
Edwards et al. (1983) monitored storm runoff for 3 years from a paved
feedlot. Storm runoff was measured and sampled as it left the feedlot, after
passing through a shallow concrete settling basin, and after passing through
two consecutive 30.5 m long fescue filter strips. Runoff, TSS, T-P, and T-N
were reduced by -2, 50, 49, and 48%, respectively, after passing through the
first filter and by an additional -6, 45, 52, and 49%, respectively, after
passing through the second filter. Total runoff from the filters was greater
than the incoming runoff because rainfall rates during runoff events exceeded
the infiltration capacity of the filters. This rainfall excess coupled with
the added area of the filters resulted in increased runoff. Removal efficien-
cies would have been higher if the settling basin located upslope of the VFS
had not removed 54, 41, and 35% of the TSS, T-P, and T-N, respectively. Most
of these solids and nutrients would have been removed in the filters because
they were either settleable solids or nutrients bound to settleable solids.
Patterson et al. (1977) applied liquid dairy waste via a gated pipe to a
fescue plot on Hosmer silt loam (fine-silty, mixed, mesic Fragiudalf) on a 3.4%
slope. After applying dairy waste to the filter for one year, pollutant re-
ductions averaged 42, 38, 7, and 71% for B0D5, NH4, 0-P, and TSS, respectively,
after passage through the 35 m fescue filter strip. Nitrate loss from the
filter was greater than N03 loading to the filter from the dairy waste, pre-
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sum ably due to mineralization of TKN and nitrification of NH4 which had been
trapped in the filter previously. Paterson et al. (1977) also noted problems
with maintaining a good grass cover on the filter area. They recommended that
several filter areas should be utilized and rotated on a weekly basis to main-
tain good grass cover.
Procedures for the design of VFS with respect to organics removal have been
presented by Norman et al. (1978) and Young et al. (1982). However, these
procedures were based primarily on infiltration or limited organics removal
data. Regression type design equations for P reduction were presented by Young
et al. (1982), but details of their development were not presented and they
have not been verified.
SUMMARY
In summary, insufficient research data currently are available concerning
VFS processes and performance to develop a reliable design procedure for VFS
in Virginia if nutrient removal is a design constraint. The Kentucky filter
strip model is presently the only available comprehensive design model but it
only considers sediment transport. The model is structured, however, such that
incorporation of sediment-bound nutrient transport sub-models are possible.
Development of soluble nutrient transport models will be more difficult as
previous research into VFS pollutant removal mechanisms has not been conducted.
To develop a VFS design model, which considers nutrient transport, it is
essential that additional research be conducted concerning both the short and
long-term dynamics of sediment, organics, and nutrient buildup in VFS. Sig-
nificant issues which must be addressed include the ability of filter strip
vegetation to recover after inundation with sediment, the effects of the buildup
of degradable organics in the filters, and the ultimate fate of nutrients
trapped within filters. Since N, P, and sediment loss from cropland and
feedlots are the NPS pollutants of concern in Virginia with respect to water
quality, the research presented herein will deal exclusively with these
pollutants and their transport in VFS.
11
-------
EXPERIMENTAL PROCEDURES
SCOPE OF STUDY
To accomplish the objectives of this project, a series of nine experimental
plots were constructed, with a source area (simulated cattle feedlot, 1984;
cropland, 1985) and a VFS of known length. The field plots were constructed
on three different slopes to assess the influence of slope on nutrient and
sediment transport. A rainfall simulator was used to apply artificial rainfall
to each plot three different times at each of two different manure loading rates
and six times after application of commercial fertilizer to the cropland plots.
Runoff was collected at the base of each VFS and transported through a flume
equipped with a stage recorder for flow measurement. Runoff samples were col-
lected manually at 3-min time intervals during the course of a rainfall-runoff
event, frozen, and later analyzed. Analyses were conducted for the determi-
nation of TSS, T-P, 0-P, N03, TKN, chemical oxygen demand (COD), filtered T-P
(TP-F), filtered TKN (TKN-F) and total ammonia (NH3 + NH4) which will be re-
presented as, NH4, because it is the dominate species present at pH values
normally encountered in surface runoff.
After completion of the field experiments, existing filter strips located
throughout the Commonwealth of Virginia were visited to qualitatively evaluate
their effectiveness. Filter strips chosen for inspection were selected at
random, although all were within the drainage areas of the Chesapeake Bay and
the Chowan River. Over 24 km of VFS were inspected on 18 farms. The VFS in-
spected represented approximately 10% of the total of those in existence at the
time in the Commonwealth (Virginia Soil and Water Conservation Commission,
1984).
PLOT DESIGN AND LOCATION
Experimental plot studies on VFS were conducted during the fall of 1984
and spring of 1985 on an eroded Groseclose silt loam (clayey, mixed, mesic Typic
12
-------
Hapludult) soil. A series of nine experimental field plots were established
for VFS research. The plots were located at the Prices Fork Agricultural Re-
search Farm, 10 km west of Blacksburg, Virginia. Figure 1 is a sketch of one
set of
experimental plots. The lower edge of each plot was bounded by a gutter which
was designed to collect surface runoff and transport it to a 150 mm H-flume
equipped with a FW-1 stage recorder for flow measurement. Each plot had a
simulated feedlot or cropland area which was 5.5 m wide and 18.3 m long. One
plot in each set had no VFS, another a 4.5 m VFS and the third a 9.1 m VFS.
For experimental purposes, the discharge from the plot with no VFS was assumed
to be the input to the VFS of the adjacent two plots in the same set. This
assumption is a potential source of error in the present study as soil
erodibility is spatially variable even within the same contiguous soil units.
The present study assumes that this error is not significant. In future
studies, flow from the bare areas should be concentrated, sampled and then re-
distributed with a flow spreader to the upper end of the VFS to minimize this
potential error.
Table 1 is a summary of the physical characteristics of each field
plot. As shown in Table 1, the first two sets of plots,' QF1-QF3 and QF4-QF6
had negligible cross slope and longitudinal slopes of 11 and 16%, respectively.
The third set of plots (QF7-QF9) had a longitudinal slope of 5% and a cross slope
of 4%. The cross slope in these plots was used to cause runoff to accumulate
and flow along the border on one side of each plot. This resulted in concen-
trated flow which could be used to evaluate the effects of flow concentration
on VFS performance. This was a major concern in the present study because ex-
perimental field plots generally are designed and constructed so that flow will
be shallow and uniform. "Real world" VFS, however, tend to have more fully
developed drainageways which encourage concentrated flow, filter inundation,
and poor performance. Also summarized in Table 1 are manure and commercial
fertilizer loading rates, simulated rainfall intensities and durations, and the
coding scheme used to differentiate between plots, manure and commercial
fertilizer loading rates, and simulated runoff events.
13
-------
T
I-
5.5m
5.5m
•5.5m
"I
Figure 1. Schematic diagram of experimental field plots.
14
-------
TABLE 1. PLOT CHARACTERISTICS AND OPERATING CONDITIONS
Plot
QF1
QF2
QF3
QF4
QF5
QF6
QF7
gF8
QF9
Filter length, m
9.1
4.6
0.0
9.1
4.6
0.0
0.0
9.1
4.6
Slope, %
11
11
11
16
16
16
5
5
5
Cross Slope, %
<1
<1
<1
<1
<1
<1
4*
4*
4
Filter strip vegetation - Orchard grass (trimmed to 10 cm)
Soil type
Feedlot simulation
Cropland simulation
Simulated rainfall
Intensity
Simulated rainfall
duration
- Groseclose silt loam
- Test 1 (Tl) 7500 kq/ha dairy manure
(moist weight)
- Test 2 (T2) 15,000 kg/ha dairy manure
- Test 3 (T3) 222 kg/ha N, 112 kg/ha K?0
112 kg/ha P205 c
- Test 4 (T4) no additional fertilizer
- 50 mm/hr
- Run 1
- Run 2
- Run 3
60 mln
30 mln
30 mln
*cross slope allowed to simulate effects of concentrated flow In "real world"
filters
-------
PLOT CONSTRUCTION
The experimental field plots were initially constructed during the summer
of 1984. The plots were installed so that the "feedlot" or "cropland" (source
area) portions of the plots were located in an area that had previously been
planted in no-till corn while the VFS portions of the plots were located in
previously established orchardgrass strips which had been part of the normal
contour strip farming rotation.
Plots were prepared by installing metal borders to a depth of 150 mm along
the boundaries of the plots and a gutter with a pipe outlet at the base of each
plot. All border and gutter joints were sealed with caulking compounds to
prevent leakage into or out of the plots. The gutters were installed so that
their upper edge was level with the soil surface. The interface between the
soil surface and the gutter was sealed with cement grout and caulking to mini-
mize leakage.
PLOT PREPARATION FOR FEEDLOT SIMULATION
After the borders and gutters were installed, crop residue and weeds were
removed from the "feedlot" portions of the plots by hand. The bare area was
then tilled to a depth of 20 to 30 cm with a PTO driven tiller. After tillage,
the bare areas were compacted with smooth and sheepsfoot rollers to simulate
feedlot soil densities. The plot preparation procedure described above ap-
proximates actual feedlot soil conditions and sediment losses from "real
feedlots" will undoubtedly vary significantly from those simulated here. This
should not be of major concern in this study, however, as the present investi-
gation is concerned with the fate of sediment and nutrients within the VFS
rather than within the source area.
Manure Application
Fresh dairy manure scraped from a paved feedlot at the Virginia Tech Dairy
Center was applied to the bare portions of each plot 24 to 48 before each set
of simulated runoff events. Manure was applied to the plots at a rate of 7500
16
-------
kg/ha (moist weight), during the first set of simulations and at 15,000 kg/ha
during the second set. These manure applications were the estimated manure
accumulations within a feedlot after 7 and 14 days, respectively, and were ob-
tained by assuming that: a) the cows spent 8 per day in the feedlot, b) half
of the manure production in the feedlot occured near the feeders where it was
not subject to runoff, c) manure production for the dairy cattle was 52 kg/day
(moist weight), and d) 80 m2 of space is required per cow in a good feedlot.
(E. R. Collins, Extension Agricultural Engineer, VPI & SU, personal communi-
cation)
The nutrient content of the manure was 0.65% for T-N, 0.15% for NH4, and
0.1% for T-P with a solids content of 17.1%. These values compare favorably
with those estimated by the Midwest Plan Service (1985) of 0.5% for T-N and 0.1%
for T-P for fresh dairy manure. With these nutrient contents, approximately
80 of P and 490 of N were applied to each plot during the first set of simu-
lations (Test 1) and double these amounts during the second set (Test 2).
Manure was distributed uniformly over the plots by subdividing the bare
portions of each plot into either 4 or 8 equal sized areas and applying either
1/4 or 1/8, respectively, of the total manure required for each plot to each
sub area. Manure was then spread manually with rakes within each sub area as
uniformly as possible. The plots were then compacted again with the sheepsfoot
roller to simulate the action of animal hoofs which compact and grind manure
into the soil of earthen feedlots.
PLOT PREPARATION FOR CROPLAND SIMULATIONS
After the feedlot simulations were completed in November, 1984, the plots
were covered with clear plastic to protect them from further erosion during the
winter. In early April, 1985, the plots were uncovered and prepared for the
cropland simulations. The bare portions of the plots were tilled to a depth
of 20 to 30 cm with a PTO driven tiller. Granular P205 and K20 fertilizer were
applied to the plots uniformly by hand at rates of 112 kg/ha. The plots were
then tilled again to incorporate the granular fertilizer into the upper 20 to
30 cm of the soil profile.
17
-------
Two to three days before the simulations began, non-pressurized N solution
(7% NH4, 7% N03> 14% urea) was applied to the plots at a rate of 222 kg N/ha
with a precision liquid application system developed for plot research. After
the N was applied, the plots were raked lightly to remove footprints made during
the N application process.
RAINFALL SIMULATOR
The Department of Agricultural Engineering's rainfall simulator (Shanholtz
et al., 1981) was used to apply artificial rainfall to each set of plots. The
rainfall simulator consisted of six rows of seven sprinklers each spaced 6.1 m
apart. The sprinkler heads are Rain Jet Model 78C placed on 3.4 m risers each
equipped with a 190 kPa, 34 L/s flow control valve. Water is provided to supply
lines for each sprinkler by pumping from a 110 m3 storage tank. Uniformity of
application with the simulator is excellent for wind speeds less than 10-13
km/h. Drops produced by the simulator are approximately 50% smaller than those
produced by natural rainfall at the same rainfall intensity (50 mm/h). The
kinetic energy produced by the simulator at 50 mm/h is therefore only about 40%
of that produced by natural rainfall at the same intensity (E. L. Neff, 1979).
Approximately 100 mm of rainfall was applied to each plot over a two day
period during each test. Each test consisted of a 1 h "dry" run (Rl) which was
followed 24 h later by a 0.5 h "wet" run (R2) and an additional 0.5 h "very wet"
run (R3) after a 0.5 h rest interval. A rainfall intensity of approximately
50 mm/h was used during all simulations. The first simulated rainfall event
(Rl) closely approximates a 2 year recurrence interval 1 h duration storm in
Virginia (Hershfield, 1961) and should approximate a worse case condition as
manure or commercial fertilizer had just been applied to the plots. The three
run sequence of dry, wet, and very wet was selected because it is a commonly
used artificial rainfall sequence for erosion research in the United States.
The 50 mm/h rate of application is a standard research rate, which is used to
allow for direct comparison of results from one location to another.
18
-------
The plots were protected from natural precipitation during the study period
by covering them with plastic when rain appeared imminent. The plots were left
uncovered at all other times so that the soils could dry normally.
Rainfall simulator application rates and uniformity were measured for each
simulation by placing 9 to 15 rain gages within each plot. The rain gages were
read after each simulation to determine the total amount of rainfall and the
coefficient of uniformity for each run.
SAMPLING PROCEDURE
Water quality samples were collected manually from the plot discharges at
3-min intervals throughout the runoff process and a tick made on the stage re-
corder charts to precisely record the time and flow rate at which each sample
was collected. This procedure greatly simplified mass flow calculations and
minimized timing errors. Water quality samples were frozen immediately after
collection and stored for up to 3 months before analysis.
Soil samples were collected from both the bare and VFS portions of each
plot before each simulation for soil moisture analysis and before and after each
set of runs for nutrient analyses. Before application of fertilizer and after
the completion of the cropland simulations, the plots were sampled with a
Giddings soil sampler to a depth of 100 cm to measure nutrient movement through
the soil profile during the test and to determine bulk density for N balance
techniques.
Grass samples were collected from the VFS after the runs were completed
to estimate the hydraulic parameters required by the Kentucky filter strip
model. Overland flow velocities were determined in the bare portion of each
plot and within the VFS by timing the advance of a dye front. Sediment movement
and accumulation within and upslope of the VFS were estimated using a network
of sediment pins.
19
-------
ANALYTICAL TECHNIQUES
Total Suspended Solids
Total suspended solids concentration was determined in accordance with
Method 160.2 contained in Methods for Chemical Analysis of Water and Wastes
(1979). Sample volumes of 100 ml were filtered through pre-weighed 0.45 micron
glass fiber filters. Filters and residue were then dried for approximately 24
h at 103-105 C, transferred to a dessicator until cool and then reweighed on
an analytical balance. The change in dry weight divided by the sample volume
was then determined and expressed in terms of mg/L.
Total Kieldahl Nitrogen
Total Kjeldahl Nitrogen was determined on filtered and non-filtered samples
in accordance with Method 351.2 in Methods for Chemical Analysis of Water and
Wastes (1979). Samples to be analyzed were heated for 2.5 h in the presence
of sulfuric acid, K2S04, and HgS04. Next the residue remaining was diluted to
50 ml and placed in an autoanalyzer for NH3 determination. A 99% recovery for
this analysis has been reported.
Ammonia.
Method 350.1 described in Methods for Chemical Analysis of Water and Wastes
(1979) was used for total NH3 determinations. Samples filtered through 0.45
micron glass fiber filters were analyzed colorimetrically at 660 nm in a 50 mm
tubular flow cell. Ammonia concentrations were determined by comparing sample
readings with a standard curve.
Nitrate-Nitrite Nitrogen.
The cadmium reduction method was used to determine combined N03 and N02
concentrations. A filtered sample was passed through a column containing
granulated copper-cadmium to reduce N03 to N02. The N02 (originally present
plus reduced N03) was determined by diazotizing with sulfanilamide and coupling
with N- (1-naphthyl) - ethylenediamine dihydrochloride to form a highly colored
azo dye that was measured colorimetrically at 520 nm. This procedure is defined
in Method 353.2 contained in Methods for Chemical Analysis of Water and Wastes
(1979).
20
-------
Total Phosphorus
Total P for both filtered and non-filtered samples was determined by fol-
lowing the procedures outlined in Method 365.4 described in Methods for Chemical
Analysis of Water and Wastes (1979). Samples were digested for 2.5 h in the
presence of sulfuric acid, K2S04, and HgS04 The resulting residue was cooled
and diluted to 50 ml. Concentration of T-P was measured with an autoanalyzer.
Ortho-Phosphorus
Ortho-phosphorus was determined in a similar manner with the procedure used
to obtain T-P with the exception that acid digestion was not utilized and
therefore organic P was not mineralized.
Chemical Oxygen Demand
Chemical Oxygen Demand (COD) was determined spectrophotometrically at 600
nm after sealed samples were placed in an oven in the presence of dichromate
at 150 C for 2 h. Method 410.4 listed in Methods for Chemical Analysis for Water
and Wastes was followed and a spectrophotometer was used in place of an
autoanalyzer.
Extractable Soil Nitrogen
Extractable soil N was determined from 5 g soil samples (oven dried basis,
but soil used was field moist) shaken with 50 mL of 2 M KCl for 1 h. Extractable
NH4 was determined colorimetrically with the indophenol blue procedure (Keeney
and Nelson, 1982) and N03 + N02 was determined by the sulfanilamide method
following reduction to N02 with a Cd-Cu column (Keeney and Nelson, 1982).
21
-------
RESULTS AND DISCUSSION
FEEDLOT SIMULATIONS
The Appendix (Table A-l) contains the sediment and nutrient concentrations
of the 415 water quality samples analyzed during the feedlot simulations along
with the plot discharge rate at the time each sample was collected. The results
of the simulated feedlot study with respect to rainfall, sediment, nutrient,
and water yield are presented in Tables 2 through 7. Table 2 summarizes the
performance of
the rainfall simulator while Tables 3 through 7 present water quality and flow
data. Tables 3 through 7 and all other water quality and flow data from the
feedlot simulations were derived from Table A-l.
Rainfall Simulator Performance
As shown in Table 2, the rainfall simulator performed quite remarkably with
respect to rainfall amounts and uniformity coefficients. The mean application
rate during all simulations was 50.1 mm/h and ranged from a low of 44.2 mm/h
(QF1T2R3 0.5-h run) to a high of 56.8 mm/h (QF4T2R3 0.5-h run). Uniformity
coefficients, which are a measure of the uniformity of simulated rainfall ap-
plication, were excellent, averaging 93.4% and ranging from 80.6 to 96.4%, with
only 5 out of 54 measurements having values less than 90%.
Sediment Yield
As shown in Tables 3 and 6, the VFS were effective in removing TSS.
Total sediment loss from the plots without filters for the six rainfall simu-
lations were 105, 235, and 54 kg TSS, or on a per hectare basis, 10500, 23400,
and 5400 kg/ha for plots QF3, QF6, and QF7, respectively. The longer 9.1 m
filters on the uniform flow plots (QF1 and QF4) reduced sediment loss by an
average of 91% while the shorter 4.6 m filters (QF2 and QF5) reduced sediment
loss by 81%. The upper portions of the VFS were the most effective for sediment
removal. This observation is supported by field observations of sediment ac-
22
-------
Table 2. Rainfall simulator performance.
Plot
QF1
QF2
QF3
Mean QF1-3
TEST
RUN
DATE 1
RAINFALL U.C.
RAINFALL U.C.
RAINFALL U.C.
RAINFALL U.C.
OF RUN
(MM)
(%)
(MM)
(%)
(MM)
(%)
(MM)
(%)
1
1
10/17/84
47.7
94.5
47.4
94.5
47.5
95.4
47.5
94.8
2
10/18/84
24.2
95.3
24.8
92.7
24.8
94.2
24.7
94.1
3
10/18/84
24.5
94.0
24.5
93.6
24.4
96.4
24.5
95.0
2
1
11/06/84
47.5
94.9
48.7
94.9
45.9
95.8
47.4
95.2
2
11/07/84
23.8
95.1
24.4
95.1
23.8
96.1
24.0
95.4
3
11/07/84
22.1
94.2
23.4
95.5
22.7
95.8
22.7
95.2
QF4
QF5
QF6
MEAN
QF4-6
1
1
10/19/84
54.8
94.2
52.5
95.8
48.2
94.7
51.8
94.9
2
10/20/84
28.1
93.0
27.3
94.8
25.5
91.8
27.0
93.2
3
10/20/84
28.6
93.0
25.8
92.2
25.2
90.0
26.5
92.0
2
1
11/01/84
55.4
87.8
50.3
95.1
52.3
95.3
52.7
92.7
2
11/02/84
25.9
89.4
26.9
93.3
24.8
94.9
25.9
92.5
3
11/02/84
24.8
90.5
28.4
80.6
23.3
95.5
25.5
88.9
QF7
QF8
QF9
MEAN
QF7-9
1
1
10/23/84
50.0
92.6
48.1
94.1
52.2
95.3
50.1
94.0
2
10/24/84
23.9
93.9
25.2
94.6
25.4
93.9
24.8
94.1
3
10/24/84
25.1
91.7
24.9
93.6
25.7
93.2
25.2
92.8
2
1
10/30/84
51.3
94.6
50.7
92.6
52.1
94.1
51.4
93.8
2
10/31/84
25.5
94.1
26.3
90.4
26.6
91.3
26.1
91.9
3
10/31/84
24.8
94.3
26.2
89.2
26.7
89.6
25.9
91.0
WHERE: U.C. = UNIFORMITY COEFFICIENT
cumulations in the VFS and by the fact that doubling VFS length from 4.6 to 9.1
m resulted in only an additional 10% reduction in sediment yield.
Observation of the filter strips during and after simulated runoff events
supported the conclusion of Neibling and Alberts (1979) and the Kentucky re-
searchers, that sediment removal is most effective just upslope and within the
23
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Table 3. Sediment, nutrient, and water yields from cropland simulations
by plot.
PLOT/
FILTER
TSS
NH4
N03
TKN
T-N
T-P
0-P
TKN-F
TP-F
RUNOFF
LENGTH
(M)
(KG)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(MM)
QF1
9.1
5.
22.
25.
133.
157.
49.
17.
40.
18.
121.7
QF2
4.6
14.
45.
35.
234.
269.
91.
29.
59.
19.
171.2
QF3
0.0
105.
69.
26.
655.
682.
248.
24.
122.
28.
161.3
QF4
9.1
29.
46.
19.
256.
267.
112.
19.
10.
5.
147.1
QF5
4.6
56.
41.
22.
280.
302.
123.
26.
17.
11.
124.7
QF6
0.0
235.
34.
22.
907.
922.
257.
13.
41.
7.
148.1
QF8
9.1
32.
119.
20.
346.
363.
146.
22.
•
152.2
QF9
4.6
54.
107.
14.
375.
389.
177.
32.
•
130.0
QF7
0.0
77.
108.
8.
380.
389.
181.
31.
•
141.2
first few meters of the VFS. Sediment was first observed to deposit at the front
edge of the filters where overland flow depths increased due to flow resistance
caused by vegetation. Flow resistance decreased flow velocity which resulted
in runoff ponding in and upslope of the VFS. This decreased sediment transport
capacity resulted in deposition of the heavier soil particles and aggregates.
As runoff and sediment delivery to the VFS continued, the ponded area upslope
of the filter gradually filled with sediment until a steady state situation was
reached. After the ponded area upslope of the filter was filled, sediment began
to gradually move down through the filter. Typically, the sediment would fill
a half meter wide strip of the filter until a substantial portion of the vege-
tation was buried. As more vegetation was buried, resistance to flow by the
vegetation decreased, transport capacity increased, and sediment began to flow
into the adjacent "virgin" area of the filter. This process was observed to
continue in one plot until sediment filled the entire filter, at which time the
VFS failed.
These observations are supported by data from plot QF5 in particular. Plot
QF5 had a short filter (4.6 m) and the highest slope (16%). Intuitively, it
24
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Table 4. Sediment, nutrient, and water yields from cropland simulations
by plot and test.
PLOT/ FILTER TSS NH4 N03 TKN T-N T-P 0-P TKN-F TP-F RUNOFF
TEST
LENGTH
(M)
(KG)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(MM)
QF1T1
QF2T1
QF3T1
9.1
4.6
0.0
2.2
9.9
75.8
7.6
14.3
34.7
10.5
15.6
11.5
61.4
88.5
443.5
71.9
104.0
455.8
19.4
31.8
166.2
5.1
9.8
10.8
20.8
29.2
62.2
5.8
8.7
13.1
52.8
76.7
84.8
QF4T1
QF5T1
QF6T1
9.1
4.6
0.0
13.9
27.9
153.4
5.1
8.8
20.5
13.4
12.5
16.4
46.6
93.1
463.1
60.0
105.7
472.2
18.0
31.7
150.6
3.1
3.8
5.8
10.0
16.5
41.1
4.6
10.9
7.3
53.1
50.5
69.6
QF8T1
QF9T1
QF7T1
9.1
4.6
0.0
20.0
32.1
50.3
12.9
15.7
14.2
9.9
8.6
7.3
137.9
115.3
164.6
147.9
124.0
172.0
56.2
46.3
68.8
7.6
8.8
6.3
•
«
•
•
•
•
64.0
60.5
63.6
QF1T2
QF2T2
QF3T2
9.1
4.6
0.0
2.9
3.7
28.7
13.9
30.9
34.1
14.3
19.6
14.4
71.1
145.2
211.8
85.4
164.8
226.2
29.6
59.3
81.5
12.1
19.5
13.6
19.6
29.9
59.5
12.3
9.8
14.6
68.8
94.5
76.2
QF4T2
QF5T2
QF6T2
9.1
4.6
0.0
15.4
28.5
81.3
40.9
32.3
13.5
5.2
9.2
6.0
209.5
187.3
443.7
207.4
196.5
449.7
93.8
90.9
106.7
16.1
22.6
6.9
•
»
•
•
•
•
94.0
74.2
78.5
QF8T2
QF9T2
QF7T2
9.1
4.6
0.0
12.1
21.4
26.7
106.2
91.1
93.3
10.5
5.8
0.6
208.5
259.9
214.9
215.5
264.7
216.7
90.0
131.1
111.7
14.1
23.5
25.1
•
•
«
•
•
78.5
69.6
77.5
would be expected that this would be the first plot to fill with sediment and
would consequently have the poorest performance.
Observation of the plot during the simulations showed a steady advance of the
sediment front through the filter until it reached the trough during the last
two simulations. As shown in Table 5 and Figures 2 and 3, the sediment yield
reduction
for plot QF5 decreased from 90% during the first simulation (QF5T1R1) to 77,
66, 74, 41, and 53% during the second (QF5T1R2) to sixth simulations (QF5T2R3),
respectively. Sediment reductions would have been poorer if sediment delivery
25
-------
Table 5. Sediment, nutrient, and water yields from cropland simulations
by plot, test and run.
PLOT/ FILTER
TSS
NH4
N03
TKN
T-N
T-P
0-P
TKN-F
TP-F
runof:
TEST/ LENGTH
RUN
(M)
(KG)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(M3)
QF1T1R1
9.1
0.8
3.9
4.3
30.2
34.5
9.3
2.9
10.2
3.2
18.8
QF2T1R1
4.6
1.5
8.3
7.5
53.0
60.5
16.5
6.5
20.2
6.1
31.2
QF3T1R1
0.0
42.7
27.0
7.3
297.7
305.7
113.0
9.1
50.1
10.8
44.2
QF1T1R2
9.1
0.6
1.6
2.5
13.5
16.1
3.5
0.9
4.7
0.9
12.7
QF2T1R2
4.6
2.5
3.2
4.3
15.7
20.0
7.4
1.7
6.0
1.7
21.3
QF3T1R2
0.0
15.2
4.2
2.1
89.4
91.6
32.8
0.8
6.9
1.1
19.8
QF1T1R3
9.1
0.8
2.1
3.7
17.7
21.3
6.6
1.4
5.9
1.7
21.3
QF2T1R3
4.6
5.9
2.8
3.8
19.8
23.5
7.9
1.6
3.0
1.0
24.1
QF3T1R3
0.0
17.9
3.5
2.1
56.4
58.5
20.4
0.9
5.3
1.2
20.8
QF1T2R1
9.1
1.5
8.4
6.3
49.2
55.5
21.1
6.8
10.7
6.5
34.0
QF2T2R1
4.6
1.2
19.6
10.7
82.6
93.4
30.9
12.4
29.9
9.8
49.3
QF3T2R1
0.0
12.8
21.1
7.6
114.1
121.7
45.1
8.1
40.4
9.0
39.6
QF1T2R2
9.1
0.1
2.1
2.2
6.5
8.7
3.4
2.3
1.1
2.8
14.5
QF2T2R2
4.6
0.7
5.8
5.6
32.6
38.2
13.1
3.4
•
«
20.8
QF3T2R2
0.0
6.9
6.9
4.1
46.2
50.3
16.3
2.7
10.9
2.8
1767
QF1T2R3
9.1
1.3
3.4
5.8
15.4
21.2
5.1
3.0
7.8
3.0
20.3
QF2T2R3
4.6
1.8
5.5
3.3
30.0
33.2
15.3
3.8
•
•
24.1
QF3T2R3
0.0
9.1
6.2
2.7
51.5
54.2
20.1
2.8
8.2
2.7
19.6
QF4T1R1
9.1
1.0
1.4
2.6
5.0
7.6
2.3
0.6
1.9
1.0
9.939
QF5T1R1
4.6
8.5
4.2
4.7
36.9
41.6
12.3
1.5
8.1
1.8
16.5
QF6T1R1
0.0
84.8
14.7
7.9
304.8
312.7
102.5
3.1
28.9
4.3
37.1
QF4T1R2
9.1
2.7
1.6
5.3
12.5
17.8
4.9
0.9
3.8
1.4
17.5
QF5T1R2
4.6
8.2
2.5
4.5
22.5
27.0
8.0
1.1
5.5
1.5
16.3
QF6T1R2
0.0
35.4
3.1
4.9
81.6
86.4
24.6
1.1
6.4
1.3
15.0
QF4T1R3
9.1
10.2
2.1
5.6
29.1
34.6
10.8
1.7
4.3
2.2
25.7
QF5T1R3
4.6
11.2
2.1
3.4
33.7
37.1
11.4
1.2
2.9
7.5
17.8
QF6T1R3
0.0
33.3
2.7
3.7
76.7
73.1
23.5
1.5
5.7
1.7
17.8
QF4T2R1
9.1
8.9
28.0
1.2
160.0
154.0
72.3
11.2
•
•
46.7
QF5T2R1
4.6
13.9
24.4
4.1
122.3
126.3
59.8
14.3
•
•
34.8
QF6T2R1
0.0
53.5
10.4
4.1
307.6
311.6
73.7
5.5
•
•
40.1
...continued
26
-------
100
U 25
0.00
1.57
9.14
FILTER LENGTH ( M )
Figure 2. Sediment yields for plots QF4-6, Test 1 (feedlot simulation)
28
-------
100
Li 25
0.00 4.57 d.m
FILTER LENGTH ( M )
Figure 3. Sediment yields for plots QF4-6, Test 2 (feedlot simulation)
29
-------
Plots QF7-9, which had cross slopes of 4%, were included in this study to
assess the potential impact of concentrated flow (as opposed to the desired
shallow overland flow) on VFS performance. Observations during the simulations
confirmed that the cross slopes caused runoff from both the bare and filtered
portions of the plots to flow to one side of the plots where it concentrated
and then flowed down the side of the plot as deeper channel flow. Flow in the
VFS was generally through a 0.5 to 1 m wide strip along one side (down slope
with respect to cross slope) of each filter. Little flow was observed to enter
the other portions of the filters and most rainfall falling on the non channel
portions of the plots appeared to infiltrate into the VFS rather than running
off.
Observations during the simulations showed that the area through which
concentrated flow was occuring accumulated considerable sediment along its en-
tire length after the first two simulations but not as much as the upper areas
of the shallow uniform flow plots. Presumably, this resulted from the concen-
trated flow which submerged and bent the grass over, thus minimizing flow re-
sistance and increasing sediment transport capacity. As shown in Table 6,
sediment yield reductions
were 58 and 31% for the long and short VFS, respectively. These plots were 1/2
and 1/3 as steep as the first two sets of plots and would have been expected
to be more efficient since sediment transport capacity is directly proportional
to slope. The decreased effectiveness of the concentrated flow plots therefore
is most likely the result of concentrated flow.
Figures 4 and 5 also demonstrate this effect. The incoming sediment
concentration (8 mg/L) of the concentrated flow plot (QF7) was less than that
of the uniform flow plot QF6 (20 mg/L). In spite of this, the sediment con-
centrations leaving the uniform flow filters were considerably less than those
from the concentrated flow plots. As shown in Table 5, the concentrated flow
plots had gross sediment losses of 16.1 (QF9T1R1) and 7.4 kg (QF8T1R1) for the
short and long filters, respectively, while sediment losses from the uniform
flow plots (QF4T1R1 and QF5T1R1) were only 8.5 and 1.0 kg, respectively. This
occurred even though the sediment loading to the uniform flow plots was 3.7
times as great.
30
-------
Table 6. Percent reduction in simulated feedlot sediment, nutrient, and
water yields by plot.
PLOT/
FILTER
TSS
NH4
N03
TKN
T-N
T-P
0-P
TKN-F
TP-F
RUNOFF
LENGTH
(M)
(KG)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(M3)
QF1
9.1
95.
69.
4.
80.
77.
80.
30.
67.
35.
25.
QF2
4.6
87.
34.
-36.
64.
61.
63.
-20.
51.
33.
-6.
QF3
0.0
-
-
-
-
-
-
-
-
-
-
QF4
9.1
88.
-35.
17.
72.
71.
57.
-51.
76.
37.
1.
QF5
4.6
76.
-21.
3.
69.
67.
52.
-108.
60.
-49.
16.
QF6
0.0
-
-
-
-
-
-
-
-
-
-
QF8
9.1
58.
-11.
-158.
9.
7.
19.
31.
-
-
-1.
QF9
4.6
31.
1.
-82.
1.
0.
2.
-3.
-
-
8.
QF7
0.0
"
"
"
"
While the present study was not designed to investigate the effect of slope
on VFS performance, several general observations can be made concerning slope
effects based upon the data. As shown in Tables 6 and 7, the sediment yield
reductions
for the plots with a slope of 11% (QF1 and QF2) were greater than those for the
16% slope plots (QF4 and QF5). The 11% slope plots had sediment reductions of
95 and 87% for the long and short filters, respectively, while sediment re-
ductions were only 88 and 76% for the long and short filters of the 16% slope
plots, respectively. These differences, however, were not statistically sig-
nificant at the 5% level.
Phosphorus Yield
Total phosphorus loss from the plots during the first 3 simulations (Test
1) followed the same general trends as sediment loss except that the percent
reductions in P were generally smaller. This was expected because P in the
runoff was present in both soluble and sediment-bound forms. Sediment-bound P
was presumed to be removed by the deposition of sediment and the filtration of
31
-------
QF7
QF9
QF8
0
17
51
O TIME ( MIN )
Figure 4. Sediment concentrations for plots QF7-9 Test 1 (concentrated
flow plots) Run 1 (feedlot simulation)
32
-------
15 30 45
TIME C MIN )
Figure 5. Sediment concentrations for plots QF4-6 Test 1 (uniform flow
plots) Run 1 (feedlot simulation)
33
-------
Table 7. Percent reduction in simulated feedlot sediment, nutrient, and
water yield by plot and test.
PLOT/ FILTER TSS NH4 N03 TKN T-N T-P O-P TKN-F TP-F RUNOFF
TEST/
LENGTH
(M)
QF1T1
QF2T1
QF3T1
9.1
4.6
0.0
97.
87.
78.
59.
9.
-36.
86.
80.
84.
77.
88.
81.
53.
9.
67.
53.
56.
34.
38.
10.
QF4T1
QF5T1
QF6T1
9.1
4.6
0.0
91.
82.
75.
57.
18.
24.
90.
60.
87.
78.
88.
79.
47.
34.
76.
60.
37.
-49.
24.
27.
QF8T1
QF9T1
QF7T1
9.1
4.6
0.0
60.
36.
9.
-11.
-36.
-18.
16.
30.
14.
28.
18.
33.
-21.
-40.
-
-
0.
5.
QF1T2
QF2T2
QF3T2
9.1
4.6
0.0
90.
87.
59.
9.
1.
-36.
66.
31.
62.
27.
64.
27.
11.
-43.
67.
50.
16.
33.
10.
-24.
QF4T2
QF5T2
QF6T2
9.1
4.6
0.0
81.
65.
-203.
-139.
13.
-53.
53.
58.
54.
56.
12.
15.
-133.
-228.
' -
-20.
5.
QF8T2
QF9T2
QF7T2
9.1
4.6
0.0
55.
20.
-14.
2.
-1650.
-867.
3.
-21.
1.
-22.
19.
-17.
44.
6.
-
-
-1.
-10.
sediment from the flow. Soluble P, however, is much more difficult to remove
as it moves in solution independently of suspended sediment and its primary
removal mechanisms probably involve infiltration, absorption, and soil
•sorption'. If this is the case, then soluble P removal should decrease with
time as infiltration decreases, the absorption capacity of the vegetation is
satisfied, and the surface soil P 'sorption' sites become occupied.
As shown in Table 6, reductions in T-P for all simulations were 80 and 63%
for plots QF1 and 2, and 57 and 52% for plots QF4 and 5, respectively. The cross
34
-------
slope plots had considerably lower reductions, 19 and 2% for plots QF8 and 9,
respectively.
Reductions in soluble P as measured by 0-P, soluble T-P, and TP-F, were
not consistent. As shown in Figures 6 and 7, the filter strips with shallow
uniform
flow were only moderately successful in removing 0-P during the first set of
simulations (Test 1) with reductions in the long VFS of 53% for QF1 and 47% for
QF4. During test 2, the percent reduction in QF1 decreased to 11% and the
outflow from QF4 was greater than the inflow. The concentrated flow plots were
completely unsuccessful in removing 0-P as shown in Figure 8.
Inspection of Tables 3 thru 7 and Figures 6 thru 8 show many instances
where the effluent from the filters contained more 0-P and TP-F than the inflow.
This is probably attributable to the release of P that was previously trapped
in the filters. Presumably, this sediment-bound P was converted to soluble
forms which were "leached" from the filters during subsequent events. The ex-
perimental design followed in the present study was not designed to identify
the exact P removal mechanisms and transformations involved. Future research
in this area is highly recommended.
One of the common assumptions concerning P transport in runoff is that P
is predominantly sediment-bound and that conservation practices which remove
sediment, such as VFS, should be nearly as effective for P removal as for
sediment. This was definitely not the case in the present study where extreme
rainfall occurred shortly after manure applications. As shown in Figures 3 and
9, substantial sediment reductions
are achieved while P reductions are relatively minor. As discussed earlier,
this may be the result of the release of previously trapped P or it may be re-
lated to the size of sediment and manure particles which transport sediment-
bound P. Also, P present in manure is primarily organic as opposed to inorganic
P which is normally associated with soil particles. Manure P also becomes more
mobile as degradation occurs and soluble P forms are released.
If deposition and filtration of suspended solids are the predominate
mechanisms controlling VFS performance, then filters will be more effective in
removing larger particles such as soil aggregates, sand, and larger manure
35
-------
32
Z
ID
211
if)
Z)
O
tt
O
X
CL
in
o
16
8
Q:
o
fc>$:Wg
l¥x^:
TEST 1
TEST 2
0.00 4.57 9.14
FILTER LENGTH ( M )
Figure 6. Ortho-phosphorus loss from plots QF1-3 (feedlot simulation)
36
-------
0.00
<1.57
9.11
FILTER LENGTH ( M )
Figure 7. Ortho-phosphorus loss from plots QF4-6 (feedlot simulation)
37
-------
s
Wm
0.00 4.57 9.14
FILTER LENGTH ( M )
Figure 8. Ortho-phosphorus loss from plots QF7-9 (feedlot simulation)
38
-------
100
z
ID
in
3
O
CE
O
X
Q.
to
O
75
50
25
CE
I-
o
I-
m
l|:
'Mi
m
p
§&
•
Sgg.
frsjpl
m
ma
0.00
Ssii
j
k
K
/.w:
4.57
Rl
I I R2
MM R3
«*;*
tm
|p
m
m
s*
m
¦XvX
'!,X,X
W$.
$£
9. m
FILTER LENGTH ( M )
Figure 9. Sediment loss from plots QF4-6, Test 2 (feedlot simulation)
39
-------
particles. The filter effluent will then be enriched with smaller, more easily
transported particles such as primary clay, silt, and small manure particles.
Since these small particles may have a much higher capacity for the P sorption
than the original soil mass, the passage of significant amounts of these par-
ticles through the filter may result in significant P transport in spite of a
large decrease in gross sediment transport. The effects of effluent particle
size distribution on VFS performance are currently being investigated.
Nitrogen Yield
Nitrogen loss from the simulated feedlot plots followed the same general
trends as the soluble and sediment-bound P losses discussed previously. As
shown in Tables 3 and 4, the 4.6 and 9.1 m filters on the uniform flow plots
reduced T-N by 67 and 74%, respectively. Total Kjeldahl nitrogen accounted for
approximately 97% of the N leaving the plots with no filters and about 85% of
this TKN was in a filterable or sediment-bound form. This means that 82% of
the N entering the filters was associated with sediment or manure particles.
After passage through the 4.6 and 9.1 m filters, filterable TKN accounted for
67 and 59% of the N leaving the filters, respectively, indicating that the
filters were not as effective in removing soluble N as they were sediment-bound
N. This observation is further supported by Table 7 which shows that soluble
N loss (NH4, N03 and soluble TKN, (TKN-F)) was reduced much less than
sediment-bound N.
As with P, the effectiveness of the filters decreased with time as sediment
and nutrients built up in the filters. As shown in Figure 10, plots QF4 and 5
were more effective for
N removal during the first three runs (Test 1) than the second set of runs (Test
2). This was also influenced by higher runoff rates during Test 2 due to lower
infiltration in the plots caused by higher soil moisture contents and possibly
surface sealing.
The filter strips were ineffective for removing soluble forms of N such
as N03. As shown in Table 7, the highest percent reduction in N03 achieved by
any uniform flow plot was 24% by plot QF5 during Test 1. During Test 2, N03
loss from this plot exceeded its influent loading by 53% indicating that N
40
-------
600
~I
3 TEST 1
1 TEST 2
450
O
U
LD 300
O
Q:
I-
150
CE
I-
O
H
M
56%
78%
54%
87%
0.00 4.5? 9.14
FILTER LENGTH ( M )
Figure 10. Total nitrogen loss from plots QF4-6, Tests 1 and 2 (feedlot
simulation)
41
-------
trapped in the filter during earlier runs was probably being mineralized and
transported through the VFS as N03. The other plots had much higher N03 losses.
As shown in Tables 6 and 7, the concentrated flow plots were totally in-
effective for N removal. Overall, the 9.1 m concentrated flow plot (QF8) re-
duced influent T-N by only 9% and the 4.6 m filter achieved no net reduction
in T-N. Effluent N03 generally exceeded influent loadings indicating that the
filters trapped very little influent N03 and released previously trapped N as
N03.
CROPLAND SIMULATIONS
Sediment and nutrient concentrations of the 352 water quality samples
collected during the cropland simulation portion of this project are presented
in Table A-2 in conjunction with the plot discharges at the times each sample
was collected. Tables 9 to 13, which summarize the results of the cropland
simulations were derived from the data presented in Table A-2.
Rainfall Simulator Performance
Table 8 summarizes the performance of the rainfall simulator during the
cropland simulations. As shown in Table 8, the mean application rate was 47.9
mm/h and ranged from a low of 41.2 mm/h (QF9T3R2) to a high of 52.4 mm/h
(QF1T3R2). Uniformity coefficients averaged 93.3% with only 4 of 54 coeffi-
cients having values less than 90%. As with the feedlot simulations, the
rainfall simulator performed quite well. The only major difference between the
cropland and feedlot simulations was that the simulated rainfall intensity av-
eraged 2.2 mm/h less during the cropland tests than the feedlot tests. This
would be expected to reduce runoff by about 4% and erosion approximately 5%,
relative to the 50.1 mm/h rainfall intensity produced during the feedlot tests.
Sediment Yield
As shown in Tables 9 to 13 and Figure 11, the VFS
were very effective for sediment removal during the cropland simulations for
both the shallow flow (QF1-6) and concentrated flow (QF7-9) plots. Sediment
losses from the plots without filters were 39.3, 84.4, and 21.0 kg or 3.9, 8.9,
42
-------
Table 8. Rainfall simulator performance (cropland simulations)
Plot
QF1 QF2 QF3 Mean QF1-3
TEST
RUN
DATE
RAINFALLU.C.
RAINFALLU.C.
RAINFALLU.C.
RAINFALLU.C.
OF RUN
(MM)
(%)
(MM)
(%)
(MM)
(%)
(MM)
<%)
3
1
04/22/85
48.5
88.0
47.8
91.8
48.6
94.6
48.3
90.9
3
2
04/23/85
26.2
93.9
24.6
93.6
24.1
94.7
25.1
92.8
3
3
04/23/85
25.7
94.5
24.5
91.2
23.9
95.8
24.8
93.3
4
1
04/27/85
50.5
93.9
47.7
94.8
46.8
92.9
48.6
93.4
4
2
04/28/85
25.9
91.6
24.8
92.1
24.1
87.4
25.1
90.9
4
3
04/28/85
26.5
93.1
24.7
94.4
24.2
91.6
25.3
92.7
QF4
QF5
QF6
MEAN
QF4-6
3
1
04/20/85
49.8
93.9
48.4
94.8
47.9
92.3
48.9
93.9
3
2
04/21/85
24.3
96.0
24.1
95.4
24.3
96.0
24.2
95.7
3
3
04//8585
24.9
90.6
24.5
94.2
24.1
89.6
24.6
91.5
4
1
04/27/85
52.7
89.9
50.4
93.9
44.9
96.2
50.0
90.7
4
2
04/28/85
24.4
95.0
23.9
96.1
22.3
97.3
23.7
94.9
4
3
04/28/85
24.9
95.5
25.3
94.7
22.8
95.0
24.5
94.2
QF7
QF8
QF9
MEAN
QF7-9
3
1
04/24/85
46.9
94.9
47.9
95.7
47.8
96.8
47.6
95.9
3
2
04/25/85
21.4
96.7
21.3
93.2
20.6
93.9
21.1
94.3
3
3
04/25/85
22.3
96.4
22.1
92.8
20.9
96.2
21.8
93.8
3
1
04/29/85
47.0
92.9
45.9
91.7
47.0
91.8
46.6
92.0
4
2
04/30/85
24.0
96.3
21.2
92.7
22.3
96.5
22.3
93.7
4
3
04/30/85
24.2
96.0
21.9
94.6
23.2
97.6
22.9
95.0
WHERE: U.C. = UNIFORMITY COEFFICIENT
and 2.1 Mg/ha for plots QF3, QF6, and QF7, respectively. These bare plot
sediment yields are 61 to 63% less than those from the same plots during the
feedlot simulations. Reduced soil loss was expected during the cropland simu-
lations because of decreased runoff due to higher infiltration rates in the bare
portions of the cropland plots. Infiltration was higher because the cropland
43
-------
Table 9. Sediment, nutrient, and water yields from cropland simulations
by plot.
PLOT/
FILTER
TSS
NH4
N03
TKN
T-N
T-P
O-P
TKN-F
TP-F
RUNOFF
LENGTH
(M)
(KG)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(M3)
QF1
9.1
1.0
1.7
3.6
9.5
13.2
3.3
0.5
4.7
0.8
2.7
QF2
4.6
5.6
6.6
16.1
35.6
51.8
11.8
1.6
9.6
2.7
8.2
QF3
0.0
39.3
15.3
16.5
132.6
149.1
43.4
0.9
21.4
1.8
7.1
QF4
9.1
27.1
24.9
15.5
125.9
141.4
29.6
1.4
27.9
2.5
8.0
QF5
4.6
42.2
38.8
18.5
163.2
181.7
43.1
1.0
35.6
1.8
7.0
QF6
0.0
89.4
42.9
19.8
308.5
319.8
84.2
1.1
47.5
1.7
5.6
QF8
9.1
1.4
1.2
3.4
14.5
17.9
3.0
0.3
2.7
0.4
2.5
QF9
4.6
3.6
1.9
3.4
12.3
15.7
3.5
0.2
2.7
0.4
2.0
QF7
0.0
21.0
7.5
12.2
76.8
89.0
22.7
0.5
11.3
1.0
5.9
plots were tilled prior to storm events compared to the compacted feedlot plots.
The higher infiltration rates and initial soil moisture differences resulted
in average runoff reductions of 59, 68, and 74% for the cropland plots relative
to the feedlot plots for the 0, 4.6, and 9.1 m filter plots, respectively.
As shown in Table 12, the 4.6 m VFS of plots QF2, 5, and 9 reduced
sediment losses by 86, 53, and 83%, respectively, and the 9.1 m plots, QF1, 4,
and 8, reduced sediment loss by 98, 70, and 93%, respectively. Doubling the
filter lengths from 4.6 to 9.1 m reduced sediment loss by only an additional
12, 23, and 10% for the 11 and 16% slope uniform flow plots and the 5% slope
concentrated flow plot, respectively. These results are similar to those from
the feedlot simulations and indicate that the first few meters of the VFS are
responsible for most sediment removal until the filters become inundated with
sediment. After inundation, the lower portions of the VFS start trapping
sediment which is not trapped by the upper buried portions.
It is interesting to note, as shown in Tables 12 and 13 and Figure 12,
that the concentrated flow plots were more effective with respect to sediment
and nutrient removal than the 16% slope uniform flow plots (QF4 and 5) and only
44
-------
Table 10. Sediment, nutrient, and water yields from cropland simulations
by plot and test.
PLOT/ FILTER TSS NH4 N03 TKN T-N T-P O-P TKN-F TP-F RUNOFF
TEST/ LENGTH
(M)
(KG)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(M3)
QF1T3
9.1
0.2
0.8
1.0
4.9
5.9
1.2
0.1
1.9
0.3
0.6
QF2T3
4.6
1.8
2.9
3.7
14.1
17.7
4.4
0.5
3.5
1.2
2.5
QF3T3
0.0
18.7
9.0
5.4
69.1
74.5
22.3
0.4
12.9
0.9
2.5
QF4T3
9.1
7.3
10.7
3.6
42.0
45.6
10.4
0.5
12.4
0.7
2.3
QF5T3
4.6
11.4
16.3
3.5
50.3
53.8
12.2
0.5
14.3
0.6
2.1
QF6T3
0.0
42.5
23.2
7.5
145.7
153.2
36.8
0.8
26.6
1.1
2.3
QF8T3
9.1
0.5
0.3
0.8
2.4
3.2
0.8
0.1
1.0
0.1
0.6
QF9T3
4.6
0.9
0.4
0.7
2.8
3.5
1.0
0.1
0.8
0.1
0.5
QF7T3
0.0
6.6
2.7
4.3
24.3
28.6
7.1
0.2
4.9
0.4
1.8
QF1T4
9.1
0.8
0.9
2.6
4.6
7.3
2.0
0.4
2.9
0.6
2.1
QF2T4
4.6
3.7
3.6
12.5
21.5
34.0
7.4
1.2
6.0
1.5
5.8
QF3T4
0.0
20.5
6.3
11.1
63.5
74.6
21.1
0.5
8.5
1.0
4.6
QF4T4
9.1
19.9
14.1
11.9
83.9
95.8
19.1
0.9
15.5
1.8
5.7
QF5T4
4.6
30.8
22.6
15.0
112.9
127.9
31.0
0.5
21.3
1.1
4.9
QF6T4
0.0
46.9
19.6
12.3
162.8
166.6
47.3
0.3
20.9
0.6
3.3
QF8T4
9.1
1.0
0.8
2.6
12.1
14.8
2.3
0.2
1.7
0.3
1.9
QF9T4
4.6
2.7
1.5
2.7
9.5
12.2
2.5
0.1
1.8
0.3
1.5
QF7T4
0.0
14.4
4.8
7.9
52.5
60.4
15.6
0.3
6.4
0.6
4.2
slightly less effective than the 11% slope uniform flow plots (QF1 and 2). The
increased effectiveness of the concentrated flow plots is the result of the 59%
reduction in runoff from the bare portions of the plots during the cropland
simulations relative to the feedlot simulations. With these reduced flows,
surface runoff was shallow, less concentrated and more like shallow overland
flow. Sediment and manure which were trapped in the filters during the earlier
feedlot simulations may also have contributed to improved performance by filling
in part of the previous concentrated flow area. When vegetation became rees-
tablished in this area in the spring, the capacity of the previous channelized
45
-------
Table 11. Sediment, nutrient, and water yields from cropland simulations
by plot, test, and run.
PLOT/ FILTER TSS NH4 N03 TKN T-N T-P O-P TKN-F TP-F RUNOFF
TEST/ LENGTH
RUN
(M)
(KG)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(M3)
QF1T3R1
QF2T3R1
QF3T3R1
9.1
4.6
0.0
0.00
0.02
2.01
0.00
0.17
2.52
0.00
0.30
1.69
0.00
0.64
19.60
0.00
0.93
21.29
0.00
0.15
4.64
0.00
0.06
0.05
0.00
0.38
4.17
0.00
0.10
0.20
0.00
0.16
0.48
QF1T3R2 9.1
QF2T3R2 4.6
QF3T3R2 0.0
QF1T3R3 9.1
QF2T3R3 4.6
QF3T3R3 0.0
QF1T4R1 9.1
QF2T4R1 4.6
QF3T4R1 0.0
QF1T4R2 9.1
QF2T4R2 4.6
QF3T4R2 0.0
QF1T4R3 9.1
QF2T4R3 4.6
QF3T4R3 0.0
QF4T3R1 9.1
QF5T3R1 4.6
QF6T3R1 0.0
QF4T3R2 9.1
QF5T3R2 4.6
QF6T3R2 0.0
QF4T3R3 9.1
QF5T3R3 4.6
QF6T3R3 0.0
QF4T4R1 9.1
QF5T4R1 4.6
QF6T4R1 0.0
0.05 0.26
0.53 1.24
5.79 3.75
0.11 0.51
1.26 1.52
10.90 2.73
0.11 0.22
1.15 1.85
9.49 3.94
0.15 0.34
0.96 0.86
4.13 1.23
0.54 0.36
1.63 0.91
6.93 1.12
0.89 1.00
1.43 2.73
14.41 8.64
2.27 3.40
3.50- 5.31
11.40 7.19
4.10 6.34
6.44 8.23
16.66 7.38
6.66 5.02
10.46 9.94
23.89 9.05
0.27 1.67
1.37 5.12
1.78 19.76
0.75 3.19
1.99 8.34
1.93 29.72
0.67 1.05
4.07 10.35
4.30 34.27
0.65 0.99
2.14 4.31
1.75 11.57
1.30 2.61
6.28 6.87
5.04 17.66
0.50 4.95
0.59 7.96
1.64 52.93
0.86 13.18
1.31 16.11
2.33 41.70
2.25 23.92
1.59 26.25
3.55 51.07
5.37 31.18
6.46 41.01
5.86 86.56
1.94 0.33
6.49 1.38
21.55 6.65
3.94 0.88
10.33 2.92
31.66 11.06
1.72 0.35
14.43 2.86
38.57 11.29
1.64 0.48
6.45 1.62
13.33 3.83
3.91 1.21
13.15 2.90
22.71 5.97
5.44 1.03
8.55 1.82
54.57 13.54
14.04 3.20
17.42 3.62
44.02 10.11
26.17 6.22
27.84 6.74
54.62 13.16
36.55 5.05
47.47 10.78
92.43 24.99
0.02 0.51
0.19 2.30
0.15 4.20
0.06 1.35
0.22 0.84
0.16 4.55
0.13 0.57
0.62 2.97
0.23 4.50
0.09 0.29
0.26 1.47
0.14 2.00
0.17 2.01
0.28 1.59
0.16 1.96
0.06 1.75
0.09 2.77
0.36 10.53
0.15 4.05
0.15 4.53
0.21 7.07
0.25 6.60
0.22 7.04
0.23 8.99
0.38 6.55
0.24 8.33
0.11 10.82
0.07 0.14
0.41 0.87
0.25 0.85
0.19 0.50
0.66 1.43
0.43 1.17
0.13 0.53
0.83 2.46
0.46 2.08
0.13 0.50
0.33 1.49
0.24 1.10
0.30 1.04
0.37 1.80
0.26 1.44
0.11 0.28
0.12 0.34
0.44 0.71
0.22 0.68
0.20 0.62
0.29 0.67
0.36 1.36
0.33 1.14
0.38 0.94
0.51 2.22
0.58 1.91
0.25 1.40
continued
46
-------
PLOT/ FILTER TSS NH4 N03 TKN T-N T-P O-P TKN-F TP-F RUNOFF
TEST/ LENGTH
RUN (M) (KG) (GM) (GM) (GM) (GM) (GM) (GM) (GH) (GM) (M3)
QF4T4R2
QF5T4R2
QF6T4R2
9.1
4.6
0.0
QF4T4R3
QF5T4R3
QF6T4R3
9.1
4.6
0.0
QF8T3R1
QF9T3R1
QF7T3R1
9.1
4.6
0.0
QF8T3R2
QF9T3R2
QF7T3R2
9.1
4.6
0.0
QF8T3R3
QF9T3R3
QF7T3R3
9.1
4.6
0.0
QF8T4R1
QF9T4R1
QF7T4R1
9.1
4.6
0.0
QF8T4R2
QF9T4R2
QF7T4R2
9.1
4.6
0.0
QF8T4R3
QF9T4R3
QF7T4R3
9.1
4.6
0.0
4.51 2.94
8.25 6.36
10.27 5.69
8.70 6.19
12.12 6.26
12.73 4.90
0.00 0.00
0.02 0.01
0.24 0.12
0.03 0.03
0.25 0.18
1.66 0.99
0.46 0.31
0.67 0.25
4.73 1.61
0.27 0.30
0.96 0.62
5.59 2.30
0.15 0.18
0.71 0.43
3.99 1.34
0.54 0.35
1.01 0.45
4.77 1.15
3.12 18.06
4.91 28.99
3.56 37.80
3.43 34.63
3.63 42.87
2.87 38.48
0.00 0.00
0.02 0.09
0.20 1.09
0.06 0.23
0.22 0.90
1.42 7.06
0.74 2.15
0.47 1.82
2.69 16.16
0.92 2.48
1.07 2.90
3.60 22.90
0.57 2.15
0.77 2.26
2.08 14.72
1.14 7.51
0.84 4.32
2.20 14.86
21.18 4.26
33.90 7.45
32.80 10.61
38.06 9.79
46.50 12.74
41.35 11.75
0.00 0.00
0.12 0.03
1.29 0.26
0.30 0.06
1.12 0.27
8.48 1.88
2.89 0.71
2.29 0.67
18.84 4.98
3.39 0.90
3.97 0.84
26.51 7.08
2.72 0.53
3.04 0.83
16.80 4.49
8.65 0.83
5.17 0.87
17.06 4.02
0.24 3.54
0.16 6.11
0.07 5.45
0.31 5.39
0.12 6.86
0.08 4.65
0.00 0.00
0.00 0.04
0.01 0.32
0.01 0.11
0.02 0.31
0.07 1.58
0.06 0.87
0.03 0.49
0.16 2.99
0.08 0.62
0.05 0.75
0.16 3.02
0.05 0.34
0.03 0.52
0.06 1.74
0.08 0.72
0.04 0.57
0.08 1.62
0.44 1.26
0.28 1.26
0.18 0.90
0.83 2.17
0.28 1.69
0.18 0.99
0.00 0.00
0.00 0.01
0.02 0.07
0.01 0.05
0.03 0.13
0.11 0.47
0.06 0.56
0.05 0.35
0.26 1.21
0.14 0.66
0.09 0.55
0.35 1.78
0.07 0.38
0.07 0.38
0.13 1.12
0.13 0.84
0.13 0.60
0.16 1.28
flow area would have been reduced forcing runoff to spread out over a wider
portion of the filter strip. Assumptions concerning the filling in of the
channel area are speculative because insufficient sediment deposition informa-
tion was collected to quantify this presumed effect.
Like the feedlot simulations, the effectiveness of the VFS decreased with
time as sediment accumulated in the filters. This is demonstrated in Table 11
47
-------
100
80
— 20
.y.v.v.*.*
iX'X'Xv!
60
r* 40
III!
QFl QF2
QF4 QF5
PLOT
QF8
QF9
9.1 m filter
4.6 m filter
Figure 11. Percent reduction in sediment yield for plots QF1-9 (cropland
simulation)
48
-------
Table 12. Percent reduction in simulated cropland sediment, nutrient, and
water yield by plot.
PLOT/
FILTER
TSS
NH4
N03
TKN
T-N
T-P
0-P
TKN-F
TP-F
RUNOFF
LENGTH
(M)
(KG)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(M3)
QF1
9.1
98.
89.
78.
93.
91.
93.
47.
78.
55.
62.
QF2
4.6
86.
57.
2.
73.
65.
73.
-83.
55.
-47.
-15.
QF3
0.0
-
-
-
-
-
-
-
-
-
-
QF4
9.1
70.
42.
22.
59.
56.
65.
-31.
41.
-44.
-42.
QF5
4.6
53.
9.
7.
47.
43.
49.
8.
25.
-4.
-24.
QF6
0.0
-
-
-
-
-
-
-
-
-
-
QF8
9.1
93.
84.
72.
81.
80.
87.
48.
76.
60.
58.
QF9
4.6
83.
74.
72.
84.
82.
85.
69.
76.
64.
66.
QF7
0.0
"
"
and Figure 12 where the effectiveness of the 4.6 m filter of plot QF5 is shown
to decrease from 90% during first run (T3R1) to 5% during the sixth run (T4R3).
As with the feedlot simulations, slope dramatically affected VFS perform-
ance. As shown in Figure 11 and Tables 9-11, the steepest plots (QF4 and 5,
16% slope) had the lowest percent reductions and highest sediment yields. Plots
QF1 and 2 (11% slope) had the highest percent reductions and lowest sediment
yields. The concentrated flow plots (5% slope) were intermediate in effec-
tiveness but cannot be compared with the other plots in determining slope ef-
fects because of the masking effects of concentrated flow.
Phosphorus Yield
Total phosphorus loss from the plots followed the same trends as sediment
loss except that percent reductions in T-P were usually slightly less than the
sediment yield reductions as shown in Tables 12 and 13 (0-17% less). Phosphorus
was predominantly sediment-bound as 97, 92, and 90% of the P leaving the 0.0,
4.6 and 9.1 m filter strips, respectively, was sediment-bound (T-P minus TP-F
49
-------
Table 13. Percent reduction in simulated cropland sediment, nutrient and
water yield by plot and test.
PLOT/ FILTER TSS NH4 N03 TKN T-N T-P 0-P TKN-F TP-F RUNOFF
TEST/
LENGTH
(M)
(KG)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(M3)
QF1T3
9.1
99.
91.
81.
93.
92.
95.
78.
86.
70.
74.
QF2T3
4.6
90.
67.
32.
80.
76.
80.
-31.
73.
-33.
2.
QF3T3
0.0
-
-
-
-
-
-
-
-
-
-
QF4T3
9.1
83.
54.
52.
71.
70.
72.
43.
53.
38.
0.
QF5T3
4.6
73.
30.
54.
65.
65.
67.
43.
46.
41.
9.
QF6T3
0.0
-
-
-
-
-
-
-
-
-
-
QF8T3
9.1
93.
88.
81.
90.
89.
89.
71.
80.
82.
65.
QF9T3
4.6
86.
84.
84.
88.
88.
86.
79.
83.
79.
72.
QF7T3
0.0
-
-
-
-
-
• -
-
-
-
-
QF1T4
9.1
96.
85.
76.
93.
90.
90.
26.
66.
42.
55.
QF2T4
4.6
82.
42.
-13.
66.
54.
65.
-119.
29.
-59.
-24.
QF3T4
0.0
-
-
-
-
-
-
-
-
-
-
QF4T4
9.1
58.
28.
3.
48.
42.
60.
-258.
26.
-192.
-72.
QF5T4
4-.6
34.
-15.
-22.
31.
23.
35.
-100.
-2.
-87.
-48.
QF6T4
0.0
-
-
-
-
—
-
-
—
-
-
QF8T4
9.1
93.
83.
67.
77.
76.
86.
30.
74.
47.
55.
QF9T4
4.6
81.
69.
66.
82.
80.
84.
60.
71.
55.
63.
QF7T4
0.0
-
-
-
-
-
-
-
-
-
-
in Table 9). Since the filters were effective for sediment removal, they were
also effective for P removal. The cropland VFS were much more effective than
the feedlot plots for P removal for the same reasons that they were more ef-
fective for sediment removal, namely, reduced runoff and sediment transport
capacity.
As shown in Table 13, the effectiveness of the filters in removing T-P
decreased with time from 2 to 32% from Test 3 to Test 4. Like the feedlot
simulations, there was a tendency for previously trapped P to be re-released
during latter runs as 0-P. Consequently, yields of soluble P (®-P) from the
50
-------
25.0
20.0
Q
_J 15.0
hJ
10.0 -
5.0
0.0
j.v.v
Xv!1!'
J.V.V,
90%
.~Xv;
•».v.v
\v'v!
£ii£
69%
i'Jv.v!
X'X*,'*
::::Xv
'.V.V/
61%
&¦
»v,v.
.•.•.v.'
56%
•v.'.'.*
.vi'M'
•!v!v!
j.
'.ViV.
'.vXv
Xvlvi
'.'vXv
• I
» ••
ixc:
.•.v.*.*.
.sV.V.
5%
T3R1 T3R2 T3R3 T4R1 T4R2
SIMULATION
T4R3
QF6, Bare
JqF5,
4. 6m
Figure 12. Sediment yield and percent reduction in sediment loss for plots
QF5 and 6, T3R1-T4R3 (cropland simulation)
51
-------
VFS were often higher than the inflows, especially during the last set of runs
(Test 4) as shown in Table 13.
As with sediment loss, Plots QF4 and 5, were least effective for P removal
because they were quickly inundated with sediment reducing their sediment and
therefore sediment-bound P trapping efficiency.
Nitrogen Yield
Percent reductions in T-N from the cropland simulations were similar to
those observed for T-P but generally 2 to 9% less. Nitrogen yield like P yield
appeared to be highly correlated with sediment yield indicating that N entering
the plots was predominantly sediment-bound. Nitrogen from the simulated
cropland plots was predominantly sediment-bound (Table 9) as 77, 65, and 66%
of the T-N leaving the plots with no filters, the 4.6 m filters and the 9.1 m
filters, respectively, was sediment-bound (total N - nitrate - soluble TKN).
As with P and sediment yield, the steepest plots (QF4-5) were least ef-
fective, the concentrated flow plots (QF8-9) were moderately effective, and the
11% slope plots (QF1-2) were the most effective for N removal.
As shown in Table 9, 93% of the T-N leaving the bare portions of the plots
and entering the filters was in the form of TKN (organic-N plus NH4). This was
expected because most of the N in the plots was residual organic N which had
built up in the soils previously and because 75% of the N fertilizer applied
to the plots was either urea or NH4. Both NH4 and urea have a tendency to bind
to and be transported along with clay particles and organic matter in the soil.
Also, most of the urea N is rapidly hydrolyzed to NH4. By the end of the tests,
most of the NH4 and urea were probably mineralized to N03 so residual organic
N in the soil was presumably the primary source of N leaving the plots.
Soil Inorganic Nitrooen
Concentration of Inorganic N; The concentrations of both N03 (Fig. 13)
and NH4 (Fig. 14)
increased, as expected, after the cropland simulation and N application to the
bare portions of the plots. The maximum N03 concentration was present in the
surface horizon and ranged from 20 kg N/ha prior to the application of N and
52
-------
0-
ioH
s
0
1 2QH
L
0 30-(
E
P
T 40-1
H
2 soH
N
C 60-1
M
70-
immu
miiiiiiiiifiif
50 73 200 223 250
N2TRATE N CMC/KC3
Figure 13. Nitrate nitrogen in the bare soil profile before (B - - B) and
after (A — A) cropland simulation.
53
-------
1EH
s
a
I 20-
L
0
E
P
T 40H
H
I
N
C 80-
M
70- *
MH| |IIH
IIIIIMMI
SO 73 100 123 ISO
AMMONIUM N CMC/KG?
Figure 14. Ammonium nitrogen in the bare soil profile before (B - - B) and
after (A — A) cropland simulation.
54
-------
the cropland simulation to 125 kg N/ha following the cropland simulation. The
NH4 concentration was much lower and ranged form a maximum of 5 kg N/ha before
to 30 kg N/ha after the cropland simulation. Even though there was a trend of
increased N03 concentration at all depths sampled, most of the N03 was present
in the upper 30 cm of the soil profile.
The concentration of N03 (Fig. 15) and NH4
(Fig. 16) in the VFS portions of the plots remained unchanged before
and after the cropland simulation. The inorganic N concentrations in the VFS
soil profile were always less than 15 kg N/ha. The surface horizon contained
slightly less N03 and slightly more NH4 before and after the cropland simu-
lation, respectively. These data show that the urea N present in the liquid N
solution applied was hydrolyzed and that most of the NH4 was nitrified prior
to collection of the last series of soil samples. Even though relatively large
and intense rainfall events were simulated during the study and even though most
of the inorganic N was present in the mobile N03 form, very limited N transport
through the bare plot soil profile was measured. Most of the inorganic N was
present in the upper 15 cm of the soil profile. The concentration of inorganic
N remained relatively constant at all depths in the VFS. This was not antic-
ipated since one of the purposes of VFS is to infiltrate runoff which has a
certain soluble N component. Increased uptake of inorganic N by the grass in
the VFS may account for the relatively stable inorganic N concentrations in the
soil.
Nitrogen Balance; When the total mass of inorganic N present in the upper
70 cm of the bare soil profile (Fig. 17) is normalized (N mass after - N mass
before)
approximately 203 kg N/ha were recovered. This recovery accounts for 91% of
the fertilizer N applied prior to the cropland simulation. The unaccounted for
N (9%) can be attributed to several different components. Ammonia
volatilization losses from surface applications of urea to clean tilled or from
incorporated urea-based fertilizers usually are less than 5% of applied N
(Nelson, 1985). The inorganic N fraction (Table 9) collected in the runoff
amounted to 1.8% of the total N applied. Because of the rapidity of the
55
-------
//
10-1
s
Q
X 20H!
L
0 30-H
E
P
T 40H
H
1 504
N
C 8QH
M
70-41
i|iMmMi|iiMiMinnmMTfpwwfyfp
50 75 100 125 150
NITRATE N CMG/KQ
Figure 15. Nitrate nitrogen in the filter strip soil profile before (B
- B) and after (A — A) cropland simulation.
56
-------
0-
r
10-i
s
0
1 20-1
L
~ 30-4
S
P
T 4CH
H
2 SQ-
N
C 80-j
M
7o4A
t"
0
SO 73 100 123 150
NITRATE N CMG/KG3
Figure 16. Ammonium nitrogen in the filter strip soil profile before (B -
- B) and after (A — A) cropland simulation.
57
-------
en
00
a
o
fe
«
TIME DEPTH
0-5
5-12
12-30
30-50
50-70
0-5
5-12
12-30
30-50
50-70
10 20 30 40 50 60 70 60
INORGANIC NITROGEN (kg/ha)
SO
100
Inorganic N
kg/ha
IS. 6
14.2
22.0
22.8
25.8
103. 4
48.8
67.3
48.5
36. 1
110
Figure 17. Inorganic nicrogen (kg/ha) present in selected soil layers in the bare soil profile
before and after cropland simulation.
-------
hydrolysis reaction much of the T-N present in runoff was probably not associ-
ated with the fertilizer N application. Even if all the total N recovered in
runoff was attributable to N applied before the cropland simulation this would
account for only 3.2% of the total applied N. When the mass of inorganic N
recovered from the VFS (Fig. 18) is considered
34 kg N/ha were present before and 35 kg N/ha were present after the cropland
simulation. Thus, inorganic N accumulation in the soil in the VFS was insig-
nificant. One source of unaccounted for N would be N uptake by the orchardgrass
in the VFS during the cropland simulation. Another possible mechanism for N
loss would be denitrification in anaerobic microsites (Cady and Bartholomew,
1961; Greenland, 1962; Gray and Williams, 1971; Martin and Focht, 1977).
COMBINED FEEDLOT AND CROPLAND SIMULATIONS
Tables 14 and 15 combine the results of both the feedlot and cropland
simulations to indicate how the filter strips performed over the 6 month simu-
lation period with respect to sediment and nutrient removal. As shown in Table
15 the 9.1 m uniform flow filters removed 83-96, 67-79, and 58-82% of the ap-
plied sediment, N, and P, respectively. The 4.6 m uniform flow filters were
only slightly less effective with percent reductions of 70-86, 61-62, and 51-65%
for sediment, N, and P, respectively. The plots characterized by concentrated
flow (QF8 and 9) were much less effective with sediment, N, and P removal ef-
ficiencies for the long filters of only 66, 20, and 27%, respectively.
Combining the results of all these simulations was originally intended as
a means of assessing the long term effectiveness of VFS subject to repeated
runoff and deposition. As indicated, the uniform flow plots were effective,
but it must be remembered that flow through real world filter strips is probably
predominantly concentrated so the percent reductions report here are undoubt-
edly very liberal.
EXISTING VEGETATIVE FILTER STRIP SURVEY
The effectiveness of existing VFS in the Commonwealth of Virginia was
qualitatively evaluated by visiting and observing filter strips on 18 farms in
Virginia. Filter strips were evaluated by talking with landowners and soil
59
-------
a*
o
a
TIME OEPTH
0-5
5-12
12-30
30-50
50-70
0-5
5-12
12-30
30-50
50-70
Trr
2
¦r
3
*1*
4
5
8
a
rrTr
10
INORGANIC NITROGEN (kg/ha)
Figure 18. Inorganic nitrogen (kg/ha) present In selected soil layers In the filter strip
soil profile before and after cropland simulation.
Inorganic N
kg/ha
9. 5
5. B
5.6
6.0
7. 1
7. 1
4.6
9. 6
7. 1
6. 5
-------
Table 14. Sediment, nutrient, and water yields for all simulations.
PLOT/
FILTER
TSS
NH4
N03
TKN
T-N
T-P
0-P
TKN-F
TP-F
RUNOFF
TEST/
LENGTH
RUN
(M)
(KG)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(MM)
QF1
9.1
6.
24.
29.
142.
171.
52.
18.
45.
19.
140.
QF2
4.6
20.
52.
51.
270.
321.
103.
31.
69.
21.
237.
QF3
0.0
144.
84.
43.
788.
831.
291.
25.
143.
30.
232.
QF4
9.1
56.
71.
34.
382.
416.
142.
20.
38.
8.
200.
QF5
4.6
98.
80.
41.
443.
484.
166.
27.
53.
13.
181.
QF6
0.0
324.
77.
42.
1216.
1258.
341.
14.
88.
9.
204.
QF8
9.1
33.
120.
23.
358.
381.
149.
22.
•
•
159.
QF9
4.6
58.
109.
17.
387.
404.
180.
32.
•
•
146.
QF7
0.0
98.
115.
20.
457.
477.
204.
31.
•
•
200.
conservationists and walking the length of the filters to evaluate potential
problems. Figure A-l of the Appendix is a copy of a survey sheet which was used
to tabulate VFS characteristics.
It is important to note that all of the VFS surveyed were used in combi-
nation with cropland because no feedlots with VFS could be found in Virginia
which were installed specifically for water quality improvement. Filter strips
were rarely used before 1983 on cropland as they had not been a recognized
conservation practice eligible for state or federal cost sharing money.
Filter strip performance was generally judged to fall into two categories
depending upon the topography of the site. In hilly areas, VFS were judged to
be ineffective for removing sediment and nutrients from surface runoff because
drainage usually concentrated in natural drainageways within the fields before
reaching the filter strips. Flow across these strips during the larger runoff
producing storms (the most significant in terms of water quality) was therefore
primarily concentrated and the filters were locally inundated and ineffective.
This assessment was confirmed by the fact that little sediment was observed to
have accumulated in the majority of the filters observed. Filter strips in
these areas, while not effective for trapping sediment and nutrients, were
61
-------
Table 15. Percent reduction in sediment, nutrient, and water yields for
all simulations.
PLOT/
TEST/
FILTER
LENGTH
TSS
NH4
N03
TKN
T-N
T-P
0-P
TKN-F
TP-F
RUNOFF
RUN
(M)
(KG)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(GM)
(M3)
QF1
QF2
QF3
9.1
4.6
0.0
96.
86.
71.
38.
33.
-19.
82.
66.
79.
61.
82.
65.
28.
-24.
69.
52.
37.
30.
10.
-27.
QF4
QF5
QF6
9.1
4.6
0.0
83.
70.
8.
-4.
19.
2.
69.
64.
67.
62.
58.
51.
-43.
-93.
57.
40.
11.
-44.
-47.
10.
QF8
QF9
QF7
9.1
4.6
0.0
66.
41.
-4.
5.
-15.
15.
22.
15.
20.
15.
27.
12.
29.
-3.
-
-
-19.
judged to be beneficial because they provide effective cover in areas imme-
diately adjacent to streams which are often susceptible to severe localized
channel and gully erosion. They also provide a narrow buffer between cropland
and streams which may reduce the aerial drift of fertilizers and pesticides to
streams during application.
In flatter areas, such as the coastal plain, VFS appeared to be more ef-
fective. Slopes were more uniform, and significant portions of stormwater
runoff entered the VFS as shallow uniform flow. This observation was supported
by the presence of significant sediment accumulations in many of the coastal
plain filters surveyed. Several one to three year old filters were observed
that had trapped so much sediment that they were higher than the fields they
were protecting. In these cases, runoff tended to flow parallel to the VFS
until a low point was reached where it flowed across as concentrated flow. In
this situation, the VFS acted more like a terrace than a filter strip.
Flow parallel to the VFS also was observed on several farms where moldboard
plowing was practiced. When soil was turn plowed away from the filter, a
shallow ditch was formed parallel to the field. If this ditch was not removed
62
-------
by careful disking later, runoff once again concentrated and flowed parallel
to the filter until it reached a low point and crossed as channel flow.
63
-------
SUMMARY AND CONCLUSIONS
Simulated rainfall was applied to a series of 5.5 by 18.3 m bare soil plots
with 4.6 and 9.1 m VFS located at the lower end of the plots as shown in Figure
1. The plots were used to evaluate the effectiveness of VFS for controlling
sediment and nutrient losses from both feedlots and cropland. For the feedlot
simulations, fresh dairy manure was applied to the bare portions of the plots
at rates of 7500 and 15,000 kg/ha and compacted with rollers to simulate feedlot
conditions. For the cropland simulations, commercial fertilizer, 112 kg/ha of
granular P205 and K20 and 222 kg-N/ha of non-pressurized N solution were applied
to bare tilled plots. Water samples were collected from H-flumes at the base
of each plot to evaluate the effectiveness of the VFS in removing sediment, N,
and P from the simulated feedlot or cropland runoff. One set of plots was
constructed with a cross slope so that flow through the filters would be deeper
or concentrated rather than shallow and uniform. Observation of existing VFS
in the Commonwealth of Virginia and analysis of the results of the plot studies
led to the following conclusions:
1. Vegetative filter strips are effective for the removal of sediment and other
suspended solids from the surface runoff of feedlots if flow is shallow and
uniform and if the VFS have not previously filled with sediment. The 9.1 and
4.6 m VFS on the uniform flow plots removed 91 and 81% of the incoming sediment
during the feedlot simulations, respectively, and 78 and 63% during the cropland
simulations, respectively.
2. The effectiveness of VFS for sediment removal appears to decrease with time
as sediment accumulates within the filter. On the average, VFS effectiveness
decreased by approximately 9% with respect to sediment removal between the first
and second set of the feedlot simulations. One set of the filters (QF4-5)
during the cropland simulations was almost totally inundated with sediment and
filter effectiveness dropped 30 to 60% between the first and second set of runs.
This may or may not be a problem in "real world" VFS because filter strip veg-
etation should normally be able to grow through most sediment accumulations.
64
-------
The success of VFS in surviving burial by sediment will be a function of random
variables associated with rainfall, runoff, vegetal recovery rate, depth of
sediment accumulation, and other factors.
3. Total N and P in runoff from the simulated feedlots was not removed by VFS
as effectively as sediment. Presumably, much of the N and P in feedlot runoff
was soluble or associated with very fine sediment which the 4.6 and 9.1 m VFS
could not remove efficiently because of high runoff rates from the bare portions
of the plots. The long and short filters of the uniform flow feedlot plots
removed only 69 and 58%, respectively, of the applied P and 74 and 64%, re-
spectively, of the applied N. The filter strips below simulated cropland were
much more effective and removed T-P nearly as effectively as sediment. This
was expected because 97% of the T-P entering the filters from the simulated
cropland was sediment-bound and because the cropland filters had about 60% less
influent runoff than the feedlot filters. This reduced inflow to the filters
reduced flow depths and sediment transport capacity resulting in more effective
filter performance.
4. The VFS lengths used in this research were not effective in removing soluble
N and P present in the runoff from simulated feedlots and cropland. Soluble P
and N in the outflow from the filters was often higher than the inflow, pre-
sumably due to the release of P and N which had been trapped in the filters
previously. Soluble N and P as percent of T-N and T-P entering the VFS were
15 and 8%, respectively. After passage through the filters, soluble N and P
increased to 26 and 19%, respectively, of the T-N and T-P.
5. Vegetative filter strips which are characterized by concentrated or deeper
channel type flow were much less effective for sediment, N, and P removal than
filters with shallow uniform flow. Filters with concentrated flow were 40 to
60%, 70 to 95%, and 61 to 70% less effective with respect to sediment, P, and
N removal than uniform flow plots. Unless VFS can be installed so that con-
centrated flow is minimized, it is unlikely that they will be very effective.
65
-------
6. Nitrogen balances for the cropland simulation indicated that 91% of the
applied fertilizer N remained in the soil profile. Assuming that the fertilizer
N applied to the cropland simulation was present in the inorganic form, then
only 1 to 3% of the applied N was lost from the source area via runoff. After
passing through the VFS, runoff losses where on the order of 0.2 to 2.5%. Soil
samples collected from the VFS before and after the cropland simulation indi-
cated that N03 did not accumulate in the VFS soil profile as a result of the
infiltration of soluble N.
7. Most on-farm VFS (cropland only) which were visited during this study were
judged to be ineffective for sediment and nutrient removal. The majority of
flow entering the filters was judged to be concentrated because runoff tended
to accumulate in natural drainageways long before reaching the VFS. This was
more of a problem in hilly areas and less of a problem in flatter areas such
as the coastal plain. The effectiveness of the experimental filter strips used
in this study should not be used as a direct indicator of real world VFS ef-
fectiveness because of the concentrated flow problems previously discussed.
Concentrated flow effects under real agricultural conditions will be orders of
magnitude greater than those measured during the experimental field studies.
66
-------
BIBLIOGRAPHY
Barfield, B. J., E. W. Tollner and J. C. Hayes. 1977. Prediction of sediment
transport in grassed media. ASAE Paper No. 77-2023. ASAE, St. Joseph, MI.
Barfield, B. J., E. W. Tollner 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., M. R. Overcash, and P. W. Westerman, 1978. Effectiveness of
grass buffer zones in eliminating pollutants in runoff from waste application
sites. ASAE Paper No. 78-2571, St. Joseph, MI.
Cady, F. B. and W. V. Bartholomew. 1961. Influence of low P02 on
denitrification processes and products. Soil Sci. Soc. Am. Proc. 25:362-365.
Doyle, R. C., G. C. Stanton and D. C. Wolf. 1977. Effectiveness of forest and
grass buffer filters in improving the water quality of manure polluted runoff.
ASAE Paper No. 77-2501. ASAE, St. Joseph, MI.
Edwards, W. M., L. B. Owens, and R. K. White. 1983. Managing runoff from a
small, paved beef feedlot. J. Environ. Qual. 12: 281-286.
Gray, T. R. G. and S. T. Williams. 1971. Soil microorganisms. Hafner Pub-
lishing CO., New York.
Greenland, D. J. 1962. Denitrification in some tropical soils. J. Agr. Sci.
58:227-233.
Hayes, J. C., B. J. Barfield, and R. I. Barnhisel. 1979. Filtration of sediment
by simulated vegetation II. Unsteady flow with non-homogeneous sediment.
TRANSACTIONS of the ASAE, 22 (5), 1063-1067.
67
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Hayes, J. C., B. J. Barfield, and R. I. Barnhisel. 1979. Performance of grass
filters under laboratory and field conditions. ASAE Paper No. 79-2530. ASAE,
St. Joseph, HI.
Hayes, J. C. and J. E. Hairston. 1983. Modeling the long-term effectiveness
of vegetative filters on on-site sediment controls. ASAE Paper No. 83-2081.
ASAE, St. Joseph, MI.
Hershfield, D. N. 1961. Rainfall frequency atlas of the United States. U.
S. Weather Bureau Tech. Paper 40.
Kao, T. Y., B. J. Barfield, and R. I. Barnhisel, 1975. On-site sediment
filtration using grass strips. National Symposium on Urban Hydrology and Ero-
sion Control, Univ. of Kentucky, Lexington, KY, 73-82.
Kao, T. Y. and B. J. Barfield. 1978. Predictions of flow hydraulics of vege-
tated channels. TRANSACTIONS of the ASAE, 21 (3): 489-494.
Keeney, D. R. and D. W. Nelson, 1982. Nitrogen-inorganic forms, p. 643-698.
In A. L. Page et al. (ed.) Methods of soil analysis part 2; Chemical and
Microbiological Properties. Am. Soc. Agrn., Inc., Madison, WI.
Martin, J. P. and D. D. Focht. 1977. Biological properties of soils. p.
115-169. In Elliott, L. F. and F. J. Stevenson (ed.) Soils for management of
organic wastes and wastewaters. SSSA, ASA, CSSA. Madison, WI.
Midwest Plan Service. 1985. Livestock waste facilities handbook. MWPS-18.
Midwest Plan Service, Iowa State Univ., Ames, Iowa.
Neibling, W. H. and E. E. Alberts. 1979. Composition and yield of soil par-
ticles transported through sod strips. ASAE Paper No. 79-2065. ASAE, St.
Joseph, MI.
68
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Tollner, E. W., B. J. Barfield, and J. C. Hayes. 1982. Sedimentology of erect
vegetal filters. Proceedings of the Hydraulics Division, ASCE, Vol. 108, HY
12, 1518-1531.
U. S. Environmental Protection Agency. 1979. Methods for the chemical analysis
of water and wastes. U. S. Environmental Protection Agency, Report No. EPA
600/4-79-020, Washington, DC.
U. S. Environmental Protection Agency, 1983. Chesapeake Bay: A Framework for
Action, U. S. Environmental Protection Agency, Chesapeake Bay Program,
Annapolis, MD.
Vanderholm, D. H. and E. C. Dickey, 1978. Design of Vegetative filters for
feedlot runoff treatment in humid areas. ASAE Paper No. 78-2570, ASAE, St.
Joseph, MI.
Virginia Soil and Water Conservation Commission. 1984. The 1983 Virginia grass
filter strip incentive program evaluation report. Virginia Soil and Water
Conservation Commission, Richmond, VA.
Westerman, P. W. and M. R. Overcash. 1980. Dairy open lot and lagoon-irrigated
pasture runoff quantity and quality. TRANSACTIONS of the ASAE, 23, 1157-1164,
1170.
Wilson, L. G. 1967. Sediment removal from flood water by grass filtration.
TRANSACTIONS of the ASAE, 19 (1): 35-37.
Young, R. A., T. Huntrods, and W. Anderson. 1980. Effectiveness of vegetative
buffer strips in controlling pollution from feedlot runoff. J. Environ. Qual.
9: 483-487.
Young, R. A., M. A. Otterby, and A. Roos. 1982. An evaluation system to rate
feedlot pollution potential. USDA-ARS, ARm-NC-17. Washington, DC.
70
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APPENDIX A
VEGETATIVE FILTER STRIP EVALUATION FORM
VFS code: Date: Evaluated by:
District: County:
Participant's names
Field number(s): Adjacent stream:
Length certified for payment (ft):
Average width (ft): Mininum: Maximum width:
Estimated age (Yrs): Distance to stream:
Cover condition: Excellent Good Fair Poor No visible VFS
(circle appropriate response and describe below)
Type of Vegetation:
Is VFS damaged or in need of maintenance? (describe)
Land use, crops, etc. above VFS:
Slope of field above VFS, % Slope across VFS, %
Estimated percent of field drainage entering VFS as concentrated flow,
% s Describe field drainage system:
Elevation of VFS with respect to field:
Owner's attitude concerning VFS (good, bad?):
Owner's opinion of effectiveness of VFS for water quality improvement:
Would owner install VFS without cost sharing? :_
Figure A-l. Sample filter strip evaluation form
71
-------
TABLE A-l. WATER QUALITY CONCENTRATION AND RUNOFF DATA FOR
FEEDLOT SIMULATIONS
PLOT/ SAMPLE TSS
NH4
N03
TKN
T-N
T-P
0-P
COD
FILTERED
DT
FLOW
TEST/
NO
TKN
T-P
RUN
GM/L
PPM
PPM
PPM
PPM
PPM
PPM
PPM
PPM
PPM MIN
L/S
QF1T1R1
1
0.118
1.12
1.68
13.60
15.30
1.10
1.10
4.65
1.10
1
0.0000
QF1T1S1
2
0.088
1.21
1.65
7.90
8.60
1.60
1.30
4.30
1.30
3
0.0028
QF1T1R1
3
0.061
1.08
1.59
6.70
8.30
1.00
1.20
142.
3.95
1.10
3
0.1189
QF1T1R1
5
0.320
3.33
3.16
19.80
23.00
6.30
2.10
9.40
2.20
6
0.3115
QF1T1R1
8
0.324
2.45
2.21
11.90
14.10
4.90
1.70
6.10
1.90
9
0.5465
QF1T1R1
10
0.364
1.75
1.78
11.10
12.90
3.80
1.30
4.75
1.30
6
0.6428
QF1T1R1
12
0.304
1.60
1.63
13.60
15.20
3.80
1.20
3.80
1.30
6
0.8269
QF1T1R1
16
0.268
1.28
1.56
11.60
13.20
3.40
1.00
3.35
1.10
21
1.0421
QF1T1R1
20
0.800
1.05
1.44
11.60
13.00
2.90
0.80
2.75
0.90
6
0.5748
QF1T1R2
1
0.706
1.75
2.11
11.60
13.70
3.20
0.70
4.55
0.70
1
0.0085
QF1T1S2
2
0.345
1.44
1.95
9.70
11.70
2.40
0.60
3.75
0.70
3
0.4078
QF1T1R2
4
0.453
1.11
1.65
7.60
9.30
2.10
0.60
3.80
0.70
6
1.0421
QF1T1R2
6
0.265
0.91
1.45
7.20
8.70
1.80
0.50
2.20
0.50
6
1.1213
QF1T1R2
8
0.367
0.91
1.46
9.30
10.80
2.40
0.50
2.65
0.50
9
1.2714
QF1T1S2
10
0.402
0.84
1.46
5.70
7.20
1.60
0.60
220.
2.45
0.70
6
0.3115
QF1T1R3
1
0.351
1.19
1.28
8.80
10.10
4.20
0.60
581.
3.70
0.70
2
1.2459
QF1TIR3
2
0.316
0.98
1.46
6.70
8.20
1.80
0.60
2.25
0.60
3
1.6027
QF1T1R3
4
0.200
0.73
1.32
4.50
5.70
1.80
0.50
2.05
0.60
6
1.5546
QF1T1S3
6
0.356
0.74
1.33
6.00
7.30
2.60
0.50
1.65
0.60
6
1.6990
QF1T1S3
8
0.252
0.64
1.30
7.00
8.30
2.70
0.40
2.30
0.60
9
1.6027
QF1T1R3
10
0.190
0.68
1.29
6.80
8.10
1.50
0.50
1.85
0.55
6
0.8835
QF1T2R1
1
0.455
3.38
4.48
17.80
22.30
3.80
1.60
9.50
1.80
2
0.0255
QF1T2R1
2
0.383
2.83
3.93
8.00
11.90
2-10
1.60
6.65
1.75
3
0.3993
QF1T2R1
3
0.329
2.72
3.29
11.80
15.10
3.60
2.00
5.70
2.10
3
0.8042
QF1T2R1
5
0.474
2.81
2.31
16.20
18.50
5.20
1.90
4.55
1.90
6
1.0704
QF1T2RI
8
0.266
2.65
1.56
24.80
26.40
4.30
1.70
411.
3.05
1.55
9
1.5404
QF1T2R1
10
0.264
1.57
1.26
6.00
7.30
4.40
1.50
2.20
l.SO
6
1.6027
QF1T2R1
12
0.909
1.55
1.13
11.20
12.30
5.40
1.50
1.95
1.50
6
1.5716
QF1T2S1
16'
0.185
1.42
1.02
5.30
6.30
4.90
1.30
1.40
1.20
18
1.6679
QF1T2S1
20
0.234
1.59
1.03
6.00
7.00
3.60
1.60
1.85
1.50
6
0.2633
QF1T2S2
1
0.208
1.09
1.29
5.30
6.60
2.60
1.40
1.55
1.25
1
0.4757
QF1T2R2
2
0.126
1.32
0.95
8.30
9.30
3.30
1.50
196.
1.10
3.25
3
1.0562
QF1T2S2
4
0.043
1.19
1.33
3.60
4.90
1.30
1.20
1.15
1.10
6
1.3167
QF1T2R2
6
0.070
1.06
1.13
2.40
3.50
2.20
1.20
0.40
1.10
6
1.5546
QF1T2R2
8
0.050
1.03
1.13
2.70
3.80
1.30
1.10
0.40.
1.60
6
1.6027
QF1T2R2
10
0.054
1.01
1.14
3.20
4.30
1.20
0.90
1.10
0.95
9
0.1133
QF1T2R3
1
0.056
1.59
3.37
7.20
10.60
2.00
1.10
4.45
0.75
3
1.3026
QF1T2S3
2
2.170
1.60
3.44
6.10
9.50
1.30
1.20
3.85
1.30
3
1.5886
QF1T2R3
4
0.269
1.32
2.46
5.50
8.00
2.70
1.10
3.20
1.15
6
1.6367
QF1T2R3
6
0.620
1.24
1.81
5.70
7.50
1.90
1.20
2.55
1.25
6
1.7160
QF1T2R3
8
0.147
1.00
1.52
6.00
7.50
1.50
1.00
127.
2.45
0.95
6
1.7330
QF1T2R3
10
0.113
1.21
1.56
4.40
6.00
1.60
1.20
2.05
1.30
9
0.6145
QF2T1R1
1
0.077
1.56
2.60
4.80
7.40
1.20
1.30
5.25
1.40
2
0.3879
QF2T1R1
2
0.247
1.21
2.30
4.00
6.30
1.00
0.60
3.05
0.65
3
0.7646
QF2T1R1
3
0.279
4.39
3.44
23.60
27.00
8.40
3.60
16.55
1.50
3
0.9345
QF2T1R1
5
0.296
3.82
2.55
14.20
16.70
6.20
2.70
9.15
2.70
6
1.1582
QF2T1R1
8
0.317
2.68
1.93
8.90
10.80
2.70
2.00
220.
5.90
1.95
9
1.2346
72
-------
QF2T1R1
10
0.389
QF2T131
12
0.529
QF2T121
16
0.357
QF2T151
20
1.445
QF2T1S2
1
0.430
QF2T122
2
0.580
QF2T1S2
4
2.153
QF2T1B2
6
0.570
QF2T122
8
0.625
QF2T1S2
10
0.379
QF2T1R3
1
1.463
QF2T1E3
2
0.883
QF2T1R3
4
0.935
QF2T1B3
6
4.857
QF231S3
8
0.751
QF2T1S3
10
2.355
QF2T2R1
1
0.121
QF2T2R1
2
0.138
QF2T2&1
3
0.135
q?2T2Rl
5
0.166
QF2T2R1
8
0.181
QF2T2R1
10
. 0.174
QF2T2R1
12
0.293
QF2T2H1
16
0.130
QF2T2R1
20
0.103
QF2T2B2
1
0.211
QF2T2H2
2
0.176
QF2T2S2
4
0.133
QF2T2H2
6
0.190
QF2T2S2
8
0.408
QF2T2S2
10
0.126
QF2T2S3
1
0.593
QFZT2S3
2
0.396
QF2T2S3
4
0.309
QF2T2K3
8
0.745
QF2T2S3
10
0.375
QF3T1B1
1
12.580
QF3T1S1
2
4.670
QF3T1H1
3
4.543
QF3T1H1
5
6.787
QF3T1H1
8
9.855
QF3TLR1
10
9.824
QF3T1R1
12
9.673
QF3T1S1
16
9.653
QF3T1R1
20
8.897
QF3T1S2
1
6.069
QF3T1B2
2
6.770
QF3T1S2
4
8.476
QF3T122
6
7.288
QF3T132
8
6.216
QF3T132
10
7.575
QF3T1R3
1
4.995
QF3T1S3
2
7.344
QF3T1S3
4
9.041
1.90 1.72 17.70
1.47 1.54 14.20
1.33 1.49 12.40
1.10 1.57 8.30
1.69 2.23 3.40
1.59 1.21 5.70
1.17 1.73 11.20
1.13 1.53 3.20
0.97 1.39 4.20
0.32 1.51 4.SO
1.16 1.31 7.80
1.12 1.19 5.00
0.87 1.33 3.90
0.68 0.58 5.50
0.83 1.42 7.00
0.33 1.34 9.80
4.66 6.99 22.50
4.55 5.23 22.40
4.25 4.07 21.20
3.80 2.67 10.50
3.74 1.80 11.60
2.99 1.36 17.60
2.98 1.25 17.50
2.34 1.00 9.90
2.53 1.07 6.80
2.63 4.45 10.90
2.81 4.59 11.10
2.52 2.71 7.00
1.89 1.59 9.20
1.94 1.43 18.90
1.79 1.33 5.80
2.66 1.46 9.00
2.38 1.28 9.70
1.75 1.05 11.00
1.50 0.93 9.20
1.48 0.94 7.60
13.70 12.45 91.70
14.50 1.69 136.30
11.40 0.13 118.60
6.90 0.93 76.80
5.25 0.68- 64.30
4.48 0.76 49.40
4.32 0.72 25.30
3.26 0.90 53.80
4.33 1.06 49.10
3.15 2.05 38.90
2.73 1.56 36.10
1.70 0.97 44.40
1.59 0.73 44.30
1.95 0.65 38.50
1.72 0.93 46.80
2.37 0.86 48.30
1.97 1.18 19.10
1.56 1.02 28.10
19.40 4.40 1.60
15.70 5.60 1.30
13.90 3.30 1.10
9.90 2.30 1.10
5.60 0.80 0.70
6.90 2.40 0.60
12.90 4.80 0.60
4.80 1.80 0.60
5.60 2.20 0.60
6.30 2.30 0.60
9.20 3.20 0.80
6.20 2.80 0.50
5.20 2.40 0.50
6.00 0.60
8.40 3.40 0.40
11.10 4.00 0.50
29.50 5.10 2.10
27.60 7.00 2.20
25.30 8.10 2.00
13.30 5.10 2.30
13.40 4.70 2.20
19.00 6.40 1.60
18.30 5.80 1.90
10.90 3.60 1.80
7.90 2.90 1.50
15.40 2.70 1.40
15.70 3.20 1.30
9.70 4.00 1.20
10.80 4.20 1.10
20.30 6.60 1.30
7.10 3.10 1.30
10.50 3.80 1.50
11.00 5.10 1.40
12.10 5.60 1.20
10.10 4.80 1.10
8.50 3.90 1.20
104.20 45.50 2.40
138.00 52.00 6.50
118.70 38.00 5.50
77.70 24.00 2.80
66.00 23.10 1.70
50.20 18.70 1.50
26.00 13.90 1.30
54.70 20.40 1.00
50.20 16.40 1.40
41.00 14.30 0.40
37.70 11.50 0.40
45.40 14.80 0.40
45.00 15.40 0.40
39.20 16.10 0.30
47.70 18.30 0.30
49.20 15.50 0.40
20.30 6.30 0.50
29.10 9.00, 0.40
73
4.90
1.55
6
1.3620
3.90
1.30
6
1.4272
2.75
1.10
18
•1.4923
2.60
1.05
6
0.1388
3.90
0.75
2
0.9911
3.10
0.65
3
1.5404
136.
2.05
0.55
6
1.6056
2.25
0.65
6
1.6565
1.70
0.55
9
1.7925
1.70
0.55
6
0.7447
2.00
0.50
3
1.7415
2.05
0.50
3
1.7556
1.50
0.45
6
1.7556
1.85
0.60
6
1.7925
1.80
0.60
9
1.7755
106.
0.70
0.45
6
0.8580
15.00
2.40
1
0.0510
10.50
2.35
3
1.3450
9.00
2.35
3
1.5234
345.
7.65
2.35
6
1.7075
6.45
2.25
9
1.8859
5.30
1.55
6
2.0501
5.00
1.60
6
1.9878
4.80
1.70
21
2.0105
6
0.9458
1
0.0793
3
1.4583
6
1.6056
6
1.6877
139.
9
1.7755
6
0.9005
3
1.6877
3
1.6707
6
1.7245
15
1.3378
6
0.8127
34.80
3.20
5
0.9656
29.50
6.45
3
1.2516
23.00
5.35
3
1.2233
14.40
3.05
6
1.2516
8.65
1.85
9
1.3082
7.65.
2.85
6
1.3366
5.65
1.50
6
1.3366
4.75
1.30
21
1.3082
7.40
1.45
6
0.5154
5.20
0.60
3
1.1298
3.80
0.55
3
1.1723
2.95
0.55
6
1.1978
3.05
0.50
6
1.1440
1452.
3.00
0.50
6
1.1723
2.75
0.45
6
1.1978
2.95
0.55
2
1.3649
2.90
0.65
3
1.3366
2.25
0.50
6
1.2516
-------
QF3T1R3
6
9.276
QF3T1S3
8
4.510
QF3T1S3
10
10.940
QF3T2R1
1
3.729
QF3T2H1
2
3.484
QF3T2S1
3
2.295
QF3T2R1
5
2.740
QF3T2B1
8
2.706
QF3T2H1
10
2.735
QF3T2R1
12
3.516
QF3T2R1
16
¦ 3.578
QF3T2S1
20
2.860
QF3T2H2
1
3.532
QF3T252
2
5.589
QF3T2S2
4
3.938
QF3T2K2
6
1.879
QF3T2R2
8
3.946
QF3T2R2
10
4.483
QF3T2R3
1
4.834
QF3T2R3
2
5.184
QF3T2B3
4
3.755
QF3T2S3
6
4.696
QF3T2B3
8
4.476
QF3T2R3
10
3.973
QF4T1&1
1
0.496
QF4T1S1
2
0.950
QF4T1S1
5
0.780
QF4T1S1
8
0.516
QF4T1&1
10
0.876
QF4T1B2
1
2.142
QF4T1S2
4
1.034
QF4T1S2
6
1.008
QF4T1S2
8
1.460
QF4T1B2
10
0.760
QF4T1R3
1
3.208
QF4T1S3
2
2.736
QF4T1H3
4
3.270
QF4T1S3
6
3.598
QF4T1H3
8
2.698
QF4T1R3
10
2.406
QF4T2R1
1
2.342
QF4T2H1
2
1.987
QF4T2R1
3
1.884
QF4T2R1
4
2.148
QF4T2R1
5
1.516
QF4T2R1
6
0.805
QF4T2&1
7
1.216
QF4T2R1
8
1.618
QF4T2R1
9
1.492
QF4T2R1
10
1.372
QF4T2H1
11
1.180
QF4T2R1
12
1.714
QF4T2R1
13
1.560
QF4T2R1
14
1.932
1.57 0.78 27.30
1.42 0.74 21.90
1.35 1.11 19.60
6.10 5.47 24.60
6.80 10.04 26.60
7.20 4.02 33.80
6.20 2.62 34.00
5.75 1.14 23.00
4.77 1.29 23.50
4.99 1.09 26.30
4.28 1.10 34.10
3.74 1.09 16.00
4.52 6.64 14.10
4.88 5.56 35.30
4.15 3.17 19.80
3.74 1.43 34.50
3.33 1.10 27.90
3.29 1.55 16.00
3.96 2.77 34.90
3.51 1.93 32.10
3.23 0.96 29.10
1.95 1.08 17.30
3.23 1.09 27..10
2.67 1.03 16.60
0.79 1.88 3.60
6.60 4.69 42.60
1.22 1.91 5.10
1.14 2.05 2.60
1.06 1.95 3.80
1.15 4.50 11.90
0.84 2.99 4.70
0.71 2.14 4.50
0.61 1.90 7.20
0.57 1.82 2.60
0.62 2.55 9.90
0.65 2.02 8.80
0.64 1.61 8.90
0.61 1.49 7.40
0.60 1.54 9.80
0.54 1.51 5.80
9.80 0.17 66.50
10.00 0.25 77.80
6.25 0.19 67.00
7.15 0.13 75.30
5.85 0.11 43.00
3.90 0.15 19.70
4.95 0.21 16.30
5.15 0.20 38.90
4.15 0.12 15.00
3.95 0.15 14.80
8.25 0.20 28.10
7.05 0.20 10.70
0.23 0.20 19.00
3.55 0.20 13.40
28.10 14.10 0.40
22.60 7.90 0.40
20.70 5.10 0.40
30.10 6.90 1.40
36.60 8.10 1.90
37.80 13.50 2.20
36.60 13.40 2.50
29.10 12.60 2.00
24.80 9.20 1.70
27.40 10.00 2.20
35.20 12.60 1.80
17.10 6.80 1.60
20.70 4.30 1.30
40.90 9.10 1.40
23.00 6.80 1.40
35.90 12.10 1.60
29.00 10.40 1.60
17.50 6.80 1.40
37.70 12.30 1.40
34.00 10.00 1.40
30.10 11.10 1.30
18.40 8.10 1.50
28.20 9.60 1.30
17.60 8.40 1.10
5.50 1.30 0.55
47.30 11.90 3.25
7.00 1.70 0.43
4.70 1.40 0.45
5.80 1.80 0.39
16.40 3.40 0.55
7.70 1190 0.42
6.60 2.00 0.39
9.10 2.50 0:37
4.40 1.40 0.42
12.40 2.50 0.50
10.80 2.40 0.57
10.50 2.00 0.48
8.90 2.60 0.48
11.30 4.90 0.51
7.30 3.00 0.46
66.70 32.90 2.16
78.10 33.40 5.09
67.20 33.40 3.22
75.40 19.80 2.26
43.10 20.40 1.39
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15
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16
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8
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3.726
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1.5348
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10
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6
1.3762
75
-------
QF5T2R1
12
3.360
3.88
0.98
QF5T2S1
16
2.228
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20
1.386
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6
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6
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8
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10
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5
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8
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10
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12
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16
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20
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10.240
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4
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6
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8
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8
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10
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4
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5
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6
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7
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8
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9
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10
8.552
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11
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12
12.717
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13
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16
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17
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18
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8.40 9.40 5.70 2.26
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116.50 125.60 31.80 1.19
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76.20 78.50 22.90 0.91
47.10 49.10 21.70 0.92
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65.40 66.70 18.30 0.79
115.40 116.50 40.90 0.60
54.30 66.00 15.50 0.60
50.30 55.90 13.60 0.49
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57.50 59.60 17.00 0.69
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43.10 47.30 10.30 0.84
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36.40 38.10 10.30 0.84
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123.30 125.30 28.50 2.40
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60.30 60.70 19.00 1.85
79.50 79.80 21.50 1.45
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67.30 68.60 16.50 1.65
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60.00 60.70 15.50 0.65
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6
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76
-------
QF6T231
19
10.303
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20
9.992
1.94
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21
9.946
3.38
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22
1.608
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1
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2
6.488
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3
6.228
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4
7.619
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5
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6
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7
5.710
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8
4.174
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9
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10
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11
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3
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4
6.984
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5
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6
5.724
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7
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8
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9
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10
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11
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12
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QF7T1H1
16
8.250
2.20
QF7T1B1
20
7.406
4.50
QF7T122
1
8.822
2.90
QF7T1S2
2
6.714
1.99
QF7T1B2
4
6.642
1.37
QF7T1S2
6
6.678
1.25
QF7T1R2
8
6.896
1.22
QF7T1B2
10
7.110
1.25
QF7T1B3
1
7.592
1.63
QF7T123
2
8.120
1.27
QF7T1B3
4
6.408
1.07
QF7T1S3
6
8.044
0.98
QF7T1B3
8
8.076
0.97
QF7T1R3
10
4.964
0.99
QF7T2S1
2
7.874
86.30
QF7T2S1
3
6.682
77.50
QF7T2K1
5
4.358
31.50
QF7T2R1
8
5.512
11.50
QF7T2R1
10
2.736
10.10
QF7TZR1
12
3.214
7.00
QF7T2S1
16
1.200
11.50
0.43
0.52
0.24
0.88
2.33
0.77
0.93
0.55
0.94
0.54
0.34
0.47
0.24
0.34
1.30
1.01
0.34
0.20
0.36
0.39
0.29
0.47
0.34
0.16
0.26
0.60
5.91
2.29
1.60
1.03
0.78
0.84
0.86
0.81
0.72
2.94
1.38
1.30
1.30
1.17
1.06
1.28
1.11
1.16
1.00
0.86
0.93
0.12
0.11
0.08
0.06
0.05
0.06
0.06
58.30
31.50
43.30
17.00
33.50
36.50
44.30
45.00
41.80
31.50
26.80
24.80
29.00
41.80
12.50
52.50
21.80
25.30
33.80
37.80
32.80
45.30
44.80
30.00
22.00
7.50
39.50
33.40
46.90
23.60
32.90
30.90
30.60
28.90
39.30
23.90
29.80
32.30
19.90
19.40
16.80
35.40
15.10
14.10
13.80
18.10
23.10
168.30
113.00
82.20
26.80
27.50
20.00
19.70
58.70
32.00
43.50
17.90
35.80
37.30
45.20
45.50
42.70
32.00
27.10
25.30
29.20
42.10
13.80
53.50
22.10
25.50
34.20
38.20
33.10
45.80
45.10
30.20
22.30
8.10
45.40
35.70
48.50
24.60
33.70
31.70
31.50
29.70
40.00
26.80
31.20
33.60
21.20
20.60
17.90
36.70
16.20
15.30
14.80
19.00
24.00
168.10
113.10
82.30
26.90
27.50
20.10
19.80
12.50
0.30
947.
3
1.2403
11.00
0.97
1395.
3
1.2233
11.50
1.39
1307.
3
0.2322
3.00
0.95
381.
3
0.0566
8.50
0.57
1313.
1
0.0113
7.50
0.52
1196.
3
1.1836
7.50
0.66
1284.
3
1.2516
10.50
0.30
758.
3
1.2516
14.00
0.50
802.
3
1.2120
9.50
0.20
642.
3
1.1695
7.00
0.47
1043.
3
1.2233
6.50
0.44
954.
3
1.1836
6.00
0.22
954.
3
1.1440
12.50
0.20
846.
3
1.1157
3.50
0.67
337.
3
0.4644
15.00
0.35
1167.
2
0.5522
8.50
0.47
1080.
3
1.3394
5.50
0.32
1123.
3
1.1978
5.00
0.56
895.
3
1.0902
11.50
0.15
802.
3
1.2233
4.50
0.30
1072.
3
1.1044
9.50
0.20
817.
3
1.1298
11.00
0.10
875.
3
1.1553
4.00
0.16
984.
3
1.1440
7.00
0.24
1072.
3
1.1836
1.50
0.21
43.
3
0.4134
11.60
2.67
3
0.4248
16.40
3.09
3
0.4332
17.00
3.39
1981.
3
0.4417
13.30
2.56
6
0.5239
15 .'90
2.00
9
0.6031
12.40
1.70
6
0.6683
12.80
1.-52
6
0.8212
11.90
1.05
21
1.1723
16.20
2.68
6
0.0821
7.30
0.45
1
0.0028
11.80
0.59
1320.
3
1.1723
10.40
0.58
6
1.1978
8.70
0.51
6
1.2120
8.30
0.54
6
1.2771
7.50
0.50
6
1.2120
12.90
0.52
1589.
2
0.2492
6.70
0.55
3
1.2374
6.80
0.49
6
1.2374
6.70
0.42
6
1.2233
8.20
0.40
6
1.1865
8.20
0.41
6
1.1723
53.80
34.00
1301.
3
1.2120
49.40
23.30
1338.
3
1.2120
35.80
10.70
1221.
6
1.2120
21.60
2.65
1192.
9
1.2120
15.50
1.60
1526.
6
1.2120
14.10
2.40
1328.
6
1.2120
12.00
1.65
1144.
12
1.2120
77
-------
QF7T2R1
20
2.714
7.80
0.06
QF7T2H2
1
3.730
7.60
2.98
QF7T2B2
2
3.536
5.80
0.10
QF7T2H2
4
2.466
2.90
0.10
QF7T2R2
6
1.920
2.40
0.04
QF7T2R2
8
3.312
3.25
0.04
QF7T2H2
10
2.248
2.90
0.05
QF7T2H3
1
2.874
6.35
0.04
QF7T2H3
2
3.718
2.60
0.10
QF7T2R3
4
3.200
3.50
0.10
QF7T2R3
6
2.782
2.75
0.12
QF7T2B3
8
2.928
1.85
0.09
QF7T2H3
10
3.926
2.00
0.05
QF8T1E1
1
3.120
6.20
5.04
QF8T1R1
2
2.588
6.10
3.37
QF8T1E1
3
2.614
4.80
2.07
QF8T1H1
5
1.932
3.70
1.28
QF8T1R1
8
2.106
3.05
1.04
QF8T1R1
10
2.330
3.00
1.04
QF8T1R1
12
2.148
1.91
0.95
QF8T1R1
16
2.038
1.61
0.87
QF8T1X1
20
2.996
1.71
1.19
QF8TLR2
1
3.536
1.59
2.04
QF8T1H2
2
2.154
1.29
1.78
QF8T1S2
4
2.286
1.02
1.35
QF8T1E2
6
2.568
0.86
1.32
QF8T1B2
8
2.150
0.77
0.96
QF8T1H2
10
1.060
0.72
1.21
QF8T1H3
1
2.876
0.94
1.28
QF8T1H3
2
2.802
0.80
1.15
QF8T1B3
4
3.428
0.68
1.05
QFST1S3
6
2.642
0.63
1.03
QF8T1H3
8
2.538
0.59
1.02
QF8T1S3
10
1.380
0.55
1.06
QF8T2S1
1
4.638
64.50
0.05
QF8T2S1
2
2.760
73.50
0.05
QF8T2H1
3
3.258
60.50
0.03
QF8T2E1
5
2.488
32.00
0.02
QF3T2R1
8
1.914
9.80
0.01
QF8T2H1
10
1.634
18.80
0.01
QF8T2R1
12
1.538
7.30
0.01
QF8T2S1
16
1.616
9.90
0.01
QF8T2R1
20
0.694
8.35
0.01
QF8T2S2
1
1.146
7.35
4.79
QF8T2S2
2
0.376
5.25—2.91
QF8T2B2
3
0.514
3.35
2.58
QF8T2H2
6
0.672
2.60
2.41
QF8T2X2
8
0.366
2.85
1.84
QF8T2S2
10
0.368
3.70
2.46
QF8T2S3
1
0.582
5.60
0.08
QF8T2R3
2
0.768
4.15
1.92
QF8T2B3
3
0.570
3.45
2.22
QF8T2S3
4
0.528
3.00
2.00
QF8T2B3
6
0.648
2.60
2.00
35.30 35.40 14.40 1.10
15.00 15.00 5.80 0.95
8.80 15.00 4.50 0.74
10.00 10.10 5.40 0.43
4.20 4.20 4.50 0.64
7.60 7.60 4.90 0.52
8.50 8.50 6.70 0.40
8.10 8.10 5.50 0.46
6.00 6.00 6.00 0.55
4.60 4.70 6.60 0.69
4.10 4.20 4.50 0.41
10.80 10.90 6.80 0.28
11.70 11.70 6.90 0.41
44.00 49.00 11.90 2.44
33.40 36.80 14.20 2.76
31.30 33.40 14.10 2.67
71.50 72.80 20.00 2.11
23.20 24.20 10.40 1.74
32.60 33.60 11.30 1.90
12.40 13.30 5.50 1.25
16.50 17.40 6.70 1.02
42.00 43.20 17.50 2.22
10.80 12.80 4.20 0.52
10.30 12.10 3.80 0.51
12.90 14.30 5.10 0.51
12.10 13.40 6.20 0.49
9.80 10.80 5.00 0.47
6.30 7.50 3.90 0.50
18.20 19.50 6.80 0.53
8.00 9.10 4.80 0.46
7.50 8.60 3.30 0.43
5.20 6.20 3.90 0.43
8.90 9.90 3.80 0^39
3.50 4.60 3.00 0.43
109.60 109.60 59.40 6.70
112.60 112.60 47.40 6.10
143.10 143.10 46.40 5.78
44.50 44.50 28.40 3.15
39.60 39.60 14.70 1.10
21.10 21.10 12.20 2.20
19.60 19.60 9.90 0.98
19.90 19.90 8.40 1.60
12.80 12.80 7.10 1.06
10.50 15.30 1.00 1.11
8.10 11.00 2.00 1.12
3.10 5.70 0.70 1.06
5.70 8.10 1.80 0.58
6.20 8.00 1.50 0.75
7.30 9.80 3.20 0.57
6.40 6.50 2.90 1.65
11.00 12.90 3.50 0.66
8.00 6.00 2.80 0.86
6.80 6.00 2.10 0.60
5.70 5.80 2.20 0.45
847.
12
1.2120
733.
2
0.1189
434.
3
1.2374
273.
6
1.2233
272.
6
1.2374
368.
6
1.2488
794.
6
1.2488
432.
2
0.3256
613.
3
1.2374
592.
6
1.3309
383.
6
1.2374
709.
6
1.2374
625.
6
1.1865
3
0.4842
3
0.7136
3
0.7787
6
0.9260
9
0.9854
6
1.0619
6
1.0987
294.
18
1.2205
6
0.2039
2
0.6739
3
1.1667
6
1.3734
355.
6
1.5065
9
1.4611
6
0.3143
3
1.2884
3
1.5518
6
1.6480
6
1.5829
9
1.5999
404.
6
0.6513
3293.
0
0.0000
2311.
3
1.0109
2232.
3
1.2063
912.
6
1.4923
606.
9
1.5688
1076.
6
1.5829
1628.
6
1.6311
755.
21
1.6311
255.
6
1.0619
257.
1
0.0170
• 166.
3
0.9146
223.
3
1.1525
164.
9
1.4611
285.
9
1.5518
200.
3
1.0506
541.
2
0.6938
356.
3
1.5688
150.
3
1.7273
200.
3
1.7103
205.
6
1.7443
78
-------
QF8T2R3
8
0.436
3.05
QF8T2S3
10
0.206
3.80
QF9T1R1-
1
10.950
6.95
QF9T1R1
2
6.600
6.65
QF9T1S1
3
5.236
5.60
QF9T1B1
5
4.760
5.10
QF9T1R1
8
4.536
3.70
QF9T1R1
10
3.824
3.20
QF9T1R1
12
3.638
2.65
QF9T1R1
16
4.108
1.90
QF9T1E1
20
1.718
1.61
QF9T1S2
1
2.468
1.35
QF9T1E2
2
4.294
1.96
QF9T1S2
4
3.678
1.31
QF9T1R2
6
4.346
1.11
QF9T1R2
8
4.314
1.03
QF9T1H2
10
3.940
0.96
QF9T1H3
1
8.868
1.70
QF9T1B3
2
4.986
1.37
QF9T1R3
4
3.552
0.91
QF9T1S3
6
3.958
0.89
QF9T153
8
3.982
0.85
QF9T1R3
10
3.754
0.63
QF9T2R1
1
6.150
64.00
QF9T2R1
2
5.164
60.50
QF9T2S1
3
3.996
46.75
QF9T2R1
5
4.966
29.00
QF9T2R1
8
2.024
16.57
QF9T2R1
10
3.038
13.75
QF9T221
12
3.498
9.30
QF9T2R1
16
2.962
6.30
QF9T2R1
20
2.532
9.45
qgywq?
1
3.752
7.20
QF9T2H2
2
1.258
2.95
QF9T2H2
4
1.096
2.15
QF9T222
6
1.200
2.20
QF9T2B2
8
0.924
2.00
QF9T2H2
10
1.178
1.80
QF9T2R3
1
3.654
4.20
QF9T2S3
2
2.444
2.75
4
0.818
1.60
QF9T2H3
6
0.879
1.45
QF9T2R3
8
3.038
1.15
QF9T2B3
10
0.498
1.40
2.01 4.40 6.40 2.50 0.77
2.79 4.70 7.SO 2.20 0.80
6.99 30.90 37.90 10.10 1.83
S.13 39.10 44.20 13.10 2.33
1.92 27.50 29.40 10.70 2.47
1.17 35.40 36.60 14.80 2.39
0.86 13.60 14.50 8.70 1.87
0.79 23.10 23.90 9.40 1.69
0.82 29.80 30.60 8.70 1.57
0.92 19.40 20.30 6.90 1.49
1.07 4.00 5.10 1.10 1.28
1.71 13.00 14.70 3.10 0.53
1.94 13.60 15.50 4.30 0.58
1.41 15.40 16.80 5.30 0.56
1.16 8.70 9.90 3.60 0.54
1.08 6.40 7.50 2.30 0.56
1.08 12.60 13.70 4.90 0.53
0.94 16.70 17.60 5.60 0.40
1.00 7.90 8.90 3.20 0.57
1.01 8.00 9.00 3.00 0.58
0.97 6.90 7.90 2.10 0.51
0.88 3.50 4.40 3.90 0.44
0.95 4.50 5.40 4.00 0.40
0.10 166.30 166.40 63.10 21.80
0.06 137.00 137.10 56.20 18.50
0.02 98.50 98.50 50.40 11.50
0.05 61.10 61.10 32.80 4.85
0.05 33.20 33.20 21.10 3.55
0.05 36.50 36.60 18.80 2.20
0.06 22.70 22.80 15.60 2.00
0.05 32.90 33.00 14.40 1.95
0.06 15.80 15.90 9.60 1.70
6.80 18.40 25.20 6.20 ll08
5.25 15.00 18.00 5.80 0.76
3.53 10.00 12.00 3.70 0.60
1.25 5.50 6.80 4.80 1.04
1.12 20.40 21.50 8.20 1.01
1.01 15.70 16.70 7.10 0.94
0.74 7.30 8.00 5.10 1.80
0.65 6.90 7.50 4.30 0.96
0.66 12.90 13.60 6.50 0.76
1.04 3.10 4.10 3.50 1.15
0.37 3.00 3.40 3.20 0.85
0.54 7.00 7.50 4.30 0.27
232.
9
1.6764
83.
3
1.1383
1
0.0000
1072.
3
0.5975
3
0.7872
6
1.0052
9
1.1383
6
1.1780
6
1.2063
21
1.2346
6
0.7872
2
0.6088
3
1.0052
229.
6
1.0845
6
1.2091
9
1.1383
3
0.6881
759.
1
0.0057
3
1.1921
6
1.3989
6
1.4130
6
1.3507
6
1.3224
2175.
2
0.5210
2002.
3
1.3507
1950.
3
1.3507
1837.
6
1.3989
1695.
9
1.4583
1424.
6
1.4272
1661.
6
1.4725
1310.
21
1.4130
700.
6
0.7108
1118.
1
O'.OOOO
215.
3
1.0449
373.
6
1.1921
407.
6
1.3366
526.
6
1.3366
488.
6
1.3989
1291.
1
0.0623
575.
3
0.9316
363.
6
1.3819
387.
6
1.3507
233.
6
1.3366
406.
6
1.3989
79
-------
TABLE A-2 WATER QUALITY CONCENTRATION AND RUNOFF DATA FOR CROPLAND
SIMULATIONS
PLOT/ SAMPLE TSS
NH4
N03
TKN
T-N
T-P
0-P
COD
FILTERED
DT
FLOW
TEST/
NO.
TKN
T-P
RUN
GM/L
PPM
PPM
PPM
PPM
PPM
PPM
PPM
PPM
PPM MIN
L/S
QF1T3R2
1
0.630
3.10
2.41
18.20
20.61
6.70
0.17
169.
5.27
0.55
1
0.5663
QF1T3R2
2
0.310
2.00
2.00
14.90
16.90
3.00
0.13
3.57
0.45
4
1.1327
QF1T3R2
3
0.356
1.77
1.94
13.50
15.44
3.10
0.16
3.25
0.50
7
1.7840
QF1T3R2
4
0.204
1.74
1.93
10.30
12.23
2.70
0.15
4.12
0.50
10
2.1521
QF1T3R2
5
0.458
1.67
1.95
12.70
14.65
0.90
0.18
4.12
0.55
13
2.2653
QF1T3R2
6
0.345
2.07
2.13
11.80
13.93
2.70
0.17
3.47
0.45
16
2.2087
QF1T3R3
1
0.110
1.05
1.38
15.20
16.58
3.60
0.15
116.
2.15
0.40
1
2.2653
QF1T3R3
2
0.150
0.89
1.31
6.20
7.51
1.50
0.13
2.75
0.40
4
3.0299
QF1T3R3
3
0.242
0.86
1.31
8.00
9.31
2.10
0.12
3.42
0.40
7
3.1715
QF1T3R3
4
0.178
0.84
2.00
8.60
10.60
2.50
0.11
1.70
0.40
10
3.1715
QF1T3R3
6
0.304
1.02
1.36
3.80
5.16
1.10
0.12
2.25
0.40
16
3.1715
QF1T3R3
8
0.182
1.18
1.40
4.60
6.00
1.40
0.10
4.82
0.45
22
3.2564
QF1T3R3
9
0.193
1.50
1.54
5.20
6.74
1.50
0.12
25
1.9822
QF1T4R1
1
0.246
0.80
1.81
6.10
7.91
0.90
0.52
1.70
0.40
1
0.2832
QF1T4R1
2
0.174
0.63
1.92
5.50
7.42
0.90
0.58
3.20
0.55
4
1.1327
QF1T4R1
3
0.208
0.55
1.71
2.60
4.31
0.50
0.35
2.00
0.40
7
1.8406
QF1T4R1
5
0.220
0.47
1.47
2.60
4.07
0.60
0.39
1.50
0.40
13
2.4069
QF1T4R1
8
0.220
0.40
1.31
3.30
4.61
0.60
0.27
0.70
0.10
21
2.5485
QF1T4R1
10
0.246
0.34
1.25
0.90
2.15
0.70
0.22
0.60
0.10
27
2.8317
QF1T4R1
12
0.152
0.33
1.14
1.70
2.84
-0.70
0.17
86.
0.70
0.28
33
2.8317
QF1T4R1
14
0.204
0.44
0.84
1.00
1.84
0.70
0.17
1.40
0.28
40
2.8317
QF1T4R1
16
0.172
0.66
1.25
1.10
2.35
0.70
0.18
1.40
0.35
42
1.6990
QF1T4R2
1
0.140
1.06
1.11
3.50
4.61
1.10
0.32
134.
2.30
0.43
1
0.2832
QF1T4R2
2
0.206
0.79
1.36
3.00
4.36
0.80
0.21
0.80
0.38
4
2.9733
QF1T4R2
4
0.326
0.66
1.31
1.50
2.81
0.60
0.17
0.40
0.25
10
3.3980
QF1T4R2
6
0.336
0.59
1.25
1.70
2.95
1.40
0.18
0.40
0.25
16
3.5396
QF1T4R2
7
0.323
0.51
1.40
2.20
3.60
1.20
0.17
0.30
0.18
20
3.5396
QF1T4R2
8
0.304
0.99
1.22
1.90
3.12
0.80
0.16
1.40
0.25
22
2.5485
QF1T4R3
1
1.060
0.65
1.44
6.20
7.64
2.10
0.22
2.00
0.20
1
0.2832
QF1T4R3
2
0.444
0.65
1.38
2.90
4.28
1.00
0.20
136.
1.90
0.15
4
4.3042
QF1T4R3
4
0.576
0.26
1.14
2.30
3.44
1.10
0.16
1.40
0.15
10
4.4174
QF1T4R3
6
0.544
0.26
1.29
2.10
3.39
1.10
0.15
3.50
0.63
16
4.4457
QF1T4R3
8
0.430
0.26
1.25
2.90
4.15
1.30
0.15
1.10
0.20
22
4.3891
QF1T4R3
9
0.488
0.26
1.18
2.30
3.48
1.30
0.15
1.20
0.18
25
4.4741
QF1T4R3
10
0.476
0.82
1.33
1.70
3.03
1.20
0.15
1.20
0.20
28
2.8317
QF2T3R1
1
0.016
1.14
2.40
4.50
6.90
0.60
0.30
58.
4.72
0.55
12
0.4248
QF2T3R1
2
0.016
1.42
2.44
5.20
7.64
1.10
0.30
1.68
0.65
15
0.7079
QF2T3RI
3
0.052
1.13
1.94
4.30
6.24
0.90
0.37
2.04
0.65
18
1.6990
QF2T3R1
4
0.180
1.04
1.77
3.70
5.47
1.00
0.40
2.12
0.60
21
2.7184
QF2T3R1
5
0.132
1.00
1.77
3.40
5.17
0.90
0.36
2.15
0.60
25
3.0016
QF2T3R1
6
0.170
1.13
1.88
5.10
6.98
1.00
0.41
3.18
0.60
27
1.8406
QF2T3S2
1
0.300
2.05
2.16
12.30
14.46
2.00
0.48
206.
7.38
0.75
1
0.2832
QF2T3R2
2
0.389
1.60
1.78
7.80
9.58
1.80
0.37
4.18
0.60
4
3.7378
QF2T3R2
3
0.334
1.48
1.67
6.60
8.27
1.80
0.23
3.38
0.50
7
4.0210
QF2T3R2
4
0.625
1.51
1.61
5.10
6.71
1.40
0.23
1.40
0.45
10
4.4741
QF2T3R2
6
0.776
1.41
1.54
5.90
7.44
1.70
0.19
2.96
0.40
16
4.4457
QF2T3R2
7
0.844
1.30
1.47
6.10
7.57
1.70
0.19
2.44
0.50
20
4.5873
80
-------
8
1
2
3
4
6
a
9
10
1
2
3
5
8
QF2T3R2
QF2T3R3
QF2T3R3
QF2T3R3
QF2T3R3
QF2T3R3
QF2T3R3
QF2T3H3
QF2T3H3
QF2T4S1
QF2T4R1
QF2T4R1
QF2T4R1
QF2T4RI
QF2T4R1 10
QP2T4S2 12
QF2T4R1 16
QF2T4R1 17
QF2T4R2
QP2T4S2
QF2T482
QF2T4R2
QF2T4R2
QF2T4R2
QF2T4R3
QF2T4R3
QF2T4R3
QF2T4R3
QF2T4B3
QF2T4R3
QF3T3S1
QF3T3R1
QF3T3R1
QF3T3S1
QF3T3R1
QF3T3R1
QF3T3R1
QF3T3R1
QF3T3R2
QF3T3R2
QF3T3R2
QF3T3R2
QF3T3R2
QF3T3R2
QF3T3R3
QF3T3S3
QF3T3R3
QF3T3R3
QF3T3R3
1
2
4
6
8
9
1
2
4
6
8
10
1
2
3
4
5
6
8
10
1
2
4
6
8
9
1
2
4
6
8
QF3T3R3 10
QF3T4R1
QF3T4R1
QF3T4R1
QF3T4R1
0.466
0.640
0.646
0.810
0.676
1.080
1.082
0.944
0.612
0.256
0.310
0.348
0.380
0.524
0.572
0.460
0.570
0.216
0.366
0.639
0.620
0.784
0.700
0.344
0.882
0.936
0.900
0.878
1.130
0.550
5.556
4.528
3.268
4.370
4.150
4.320
4.340
3.870
4.370
5.140
5.200
7.840
7.000
7.910
7.980
8.450
9.220
9.260
8.950
10.700
2.980
3.480
3.480
4.780
1.27.
0.96
0.90
0.90
1.08
1.11
1.11
1.09
1.24
1.07
0.67
0.67
0.62
0.51
0.81
0.87
0.93
0.75
0.99
1.08
0.52
0.48
0.47
0.48
0.06
0.42
0.57
0.60
0.53
0,54
13.90
9.10
6.80
6.40
5.60
5.00
4.40
3.70
9.40
6.10
4.70
4.30
3.70
3.75
3.84
2.80
2.76
1.27
2.32
2.28
2.94
3.18
3.03
2.49
1.48
1.31
1.32
1.39
1.37
1.40
1.40
1.46
1.41
3.26
2.58
2.56
2.17
1.44
1.47
1.38
1.40
1.64
1.71
1.51
1.44
1.38
1.37
1.55
1.47
1.42
1.31
1.34
8.54
6.46
8.66
6.34
4.70
3.61
3.76
3.45
3.01
2.60
4.50
3.15
2.29
1.94
1.77
1.73
2.59
1.91
1.63
1.57
1.53
1.47
4.63
3.13
2.15
1.76
4.50
7.10
5.70
5.20
5.30
6.30
5.70
6.20
5.20
9.40
6.80
2.90
4.50
2.90
3.80
4.80
5.80
1.30
5.00
3.30
2.60
3.30
3.20
1.20
4.50
4.40
3.80
4.00
3.70
2.50
83.40
52.90
47.40
43.20
42.30
39.40
35.80
35.70
30.90
24.00
24.00
21.10
23.30
23.60
28.20
22.70
23.30
20.70
29.90
28.60
24.90
17.50
18.30
17.60
5.98
8.41
7.02
6.59
6.67
7.70
7.10
7.66
6.61
12.66
9.38
5.46
6.67
4.34
5.27
6.18
7.20
2.94
6.71
4.81
4.04
4.68
4.57
2.75
5.97
5.82
5.11
5.34
12.24
8.96
92.06
59.24
52.10
46.81
46.06
42.85
38.81
38.30
35.40
27.15
26.29
23.04
25.57
25.33
30.79
24.61
24.93
22.27
31.43
30.07
29.53
20.63
20.45
19.36
1.20
1.90
1.80
1.80
2.00
2.20
2.00
2.40
1.80
2.70
2.10
1.30
1.70
0.80
0.80
0.90
1.70
0.40
1.10
1.00
1.20
1.20
1.30
0.40
1.70
1.80
1.60
1.70
1.70
1.00
7.00
10.80
10.20
10.20
10.40
9.30
9.00
10.40
6.50
6.80
7.60
7.10
8.40
8.90
11.50
7.80
8.30
7.80
10.70
11.70
4.80
4.90
4.90
5.10
0.18
0.21
0.19
0.14
0.14
0.18
0.14
0.13
0.12
1.09
0.49
0.37
0.28
0.26
0.22
0.22
0.22
0.16
0.30
0.22
0.20
0.16
0.14
0.16
0.20
0.19
0.15
0.15
0.15
0.13
0.09
0.09
0-.10
0.10
0.11
0.10
0.13
0.10
0.38
0.26
0.17
0.20
0.10
0.15
0.15
0.15
0.14
0.14
0.12
0.15
0.21
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0.16
0.15
183.
155.
71.
143.
88.
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2.23
0.45
22
3.1149
2.42
0.55
1
3.9644
0.56
0.60
4
4.7289
0.50
0.45
7
4.8139
0.53
0.50
10
4.9271
0.48
0.45
16
4.9554
0.42
0.40
22
4.9838
0.46
0.40
25
5.1537
0.46
0.40
28
2.8317
5.40
1.33
2
0.7079
2.10
0.55
5
3.1149
1.90
0.43
8
4.1059
1.50
0.35
14
4.6440
1.30
0.33
23
4.9271
0.90
0.30
29
5.0970
1.00
0.30
35
5.1253
1.00
0.33
47
5.1537
0.90
0.30
50
3.3980
1.80
0.45
1
2.2653
1.40
0.38
4
4.5307
1.10
0.20
10
5.0970
0.70
0.18
16
5.3802
0.90
0.18
23
5.5218
1.00
0.20
25
3.6812
1.30
0.28
2
5.1537
1.20
0.25
5
5.3519
0.80
0.20
9
5.3802
0.80
0.20
15
5.4368
0.70
0.18
24
5.4368
0.90
0.18
27
3.6812
25.20
0.30
14
1.1327
16.00
0.30
17
1.5574
11.90
0.45
20
1.9822
10.30
0.45
23
2.2653
7.92
0.40
26
2.5485
6.87
0.40
29
2.6901
6.37
0.45
35
3.0665
7.47
0.45
42
3.0865
2.45
0.55
2
1.6990
7.37
0.40
5
2.8317
5.72
0.30
11
3.6312
4.87
0.30
17
4.0776
3.66
0.25
23
4.0210
4.67
0.25
26
3.9644
6.57
0.45
2
2.8317
4.42
0.40
5
4.1059
3.41
0.35
11
4.3891
4.12
0.40
17
4.2475
3.37
0.30
23
4.2475
3.70
0.40
30
4.2475
6.50
0.33
2
1.1327
4.70
0.25
5
2.6901
3.90
0.23
8
3.2348
2.90
0.20
14
3.9644
81
-------
QF3T4R1 8
QF374R1 10
QF374R1 12
QF3T4R1 16
QF3T4R1 19
QF3T4R2
QF3T4H2
QF3T4R2
QF3T4H2
QF3T4R2
QF3T4R2 10
QF3T4R3
QF3T4R3
QF3T4S3
QF3T4R3
QF3T4R3
QF3T4R3
QF4T3S1
QF4T3R1
QF4T3R1
QF4T3R1
QF4T3R1
QF4T3R1
QF4T3R1
QF4T3R2
QF4T3R2
QF4T3R2
QF4T3R2
QF4T3R2
QF4T3R2
QF4T3R3
QF4T3R3
QF4T3R3
QF4T3R3
QF4T3R3
QF4T3R3
QF4T3R3
QF4T4R1
QF4T4R1
QF4T4R1
QF4T4R1
QF4T4R1
QF4T4R1 10
QF4T4R1 12
QF4T4R1 16
QF4T4R1 18
QF4T432
QF4T432
QF474R2
QF4T4R2
QF4T432
QF4T432
QF4T422
QF4T4H3
1
2
4
6
8
10
1
2
3
5
7
9
10
1
2
4
6
7
8
1
2
4
6
8
9
10
1
2
3
5
8
1
2
4
6
8
9
10
1
4.310
4.860
5.130
4.590
4.320
2.710
3.690
3.760
3.590
3.820
3.970
4.600
5.140
4.380
4.640
4.750
5.220
1.020
0.956
1.090
1.940
2.890
4.230
3.770
1.570
3.320
3.470
3.430
3.310
3.330
5.120
3.230
2.080
2.840
3.160
3.840
2.480
0.182
1.210
2.160
2.540
3.050
3.380
3.130
3.010
2.630
2.670
2.740
3.020
3.610
4.010
4.030
3.190
8.780
2.00
1.44
1.67
1.71
1.57
2.21
1.67
1.31
1.08
0.93
0.83
1.05
1.05
0.62
0.70
0.75
0.75
1.50
1.20
2.97
3.67
3.07
3.18
6.80
2.98
4.70
4.98
5.13
5.08
5.37
6.29
5.25
4.70
4.19
4.34
4.33
5.27
0.56
1.92
2.72
2.73
2.57
2.38
2.16
1.89
2.18
1.89
2.67
2.52
2.43
2.15
2.10
2.29
1.48
1.69
1.45
3.28
1.93
1.71
1.54
1.54
1.47
1.89
1.60
1.45
1.47
1.38
1.32
1.91
6.50
6.12
1.32
1.35
1.40
1.30
1.73
1.85
2.51
1.50
1.30
1.30
1.30
1.11
1.26
4.00
1.76
1.43
1.63
1.35
1.44
1.57
4.44
2.20
5.26
4.00
2.41
2.42
2.19
1.74
1.80
5.11
6.01
3.44
2.42
1.98
0.93
1.57
1.06
13.10
15.70
16.50
18.00
16.00
17.30
12.00
11.30
10.60
9.70
9.40
13.50
12.70
12.10
11.50
11.90
12.70
7.90
7.50
9.90
11.90
17.30
20.70
22.60
17.80
13.50
20.40
21.20
21.30
17.40
28.30
20.10
18.00
12.70
17.90
18.80
15.70
15.20
13.70
16.50
15.60
12.30
13.50
12.90
15.30
17.60
14.30
15.40
13.80
13.20
14.60
16.10
14.20
25.40
14.79
17.15
19.78
19.93
17.71
18.84
13.54
12.77
12.49
11.30
10.85
14.97
14.08
13.42
13.41
18.40
18.82
9.22
8.85
11.30
13.20
19.03
22.55
25.11
19.30
14.80
21.70
22.50
22.41
18.66
32.30
21.86
19.43
14.33
19.25
20.24
17.27
19.64
15.90
21.76
19.60
14.71
15.92
15.09
17.04
19.40
19.41
21.41
17.24
15.62
16.58
17.03
15.77
26.46
4.30
4.90
5.10
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83
-------
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84
-------
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QF7T4R1 2 2.400 3.46 6.09 16.90 22.99 4.00 0.12
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QF7T4R1 16 3.060 0.78 1.78 12.80 14.58 3.80 0.10
QF7T4R1 19 3.290 i.79 1.41 13.80 15.21 4.20 0.13
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QF7T4R2 2 3.720 1.74 2.29 14.55 16.84 4.60 0.05 589.
QF7T4R2 4 3.790 1.31 1.66 13.69 15.35 2.40 0.06
QF7T4R2 6 2.820 0.86 1.82 14.60 16.42 4.60 0.07
QF7T4R2 8 3.660 0.99 1.68 12.90 14.58 4.33 0.04
QF7T4R2 9 3.850 0.97 1.73 12.90 14.63 3.93 0.03
QF7T4R3 1 5.000 1.66 2.06 15.70 17.76 4.12 0.05
QF7T4R3 2 3.800 1.29 1.75 14.90 16.65 4.74 0.08
QF7T4R3 4 4.000 0.98 1.61 10.40 12.01 2.18 0.05
QF7T4R3 6 3.840 0.80 1.65 10.30 11.95 2.69 0.05 404.
QF7T4R3 8 3.590 0.79 1.67 9.33 11.00 2.27 0.07
QF7T4R3 10 3.730 0.74 1.83 15.50 17.33 4.90 0.07
QF7T3R1 ll 1.120 0.70 2.03 9.07 11.10 2.48 0.09 262.
QF8T3R2 1 0.684 0.85 1.55 5.00 6.55 2.10 0.16
QF8T3R2 2 0.686 0.58 1.45 4.30 5.75 1.30 0.12
QF8T3R2 3 0.676 0.74 1.26 6.60 7.86 1.40 0.13
QF8T3R2 4 0.598 0.58 1.32 2.90 4.22 1.00 0.12 175.
QF8T3R3 1 0.604 0.28 1.27 3.30 4.57 1.10 0.11 163.
QF8T3R3 2 0.690 0.48 1.41 2.90 4.31 1.10 0.14
QF8T3R3 3 0.902 0.56 1.20 3.20 4.40 1.30 0.13
QF8T3R3 4 0.884 0.58 1.28 3.70 4.98 1.40 0.12
QF8T3R3 6 0.904 0.58 1.47 4.70 6.17 1.30 0.09
QF8T3R3 8 0.678 0.64 1.27 4.40 5.67 1.10 0.09
QF8T4R1 1 0.842 1.36 1.58 7.61 9.19 1.35 0.'24
QF8T4R1 2 0.558 0.99 1.76 4.53 6.29 1.41 0.19 160.
QF8T4R1 3 0.414 0.80 1.67 6.50 8.17 1.47 0.18
QF8T4R1 5 0.570 0.57 1.50 2.39 3.89 1.08 0.16
QF8T4R1 8 0.292 0.32 1.43 3.16 4.59 1.32 0.12 82.
QF8T4R1 12 0.378 0.43 1.33 3.76 5.09 1.24 0.09
QF8T4R1 14 0.474 0.38 1.15 4.53 5.68 1.23 0.08
QF8T4R1 15 0.364 0.29 1.37 4.53 5.90 3.71 0.12
QF8T4R2 1 0.482 0.52 1.56 4.88 6.44 1.47 0.11
QF8T4R2 4 0.408 0.58 1.52 4.78 6.30 1.29 0.12 134.
QF8T4R2 6 0.356 0.32 1.43 4.19 5.62 1.65 0.13
QF8T4R2 7 0.404 0.31 1.42 12.92 14.34 1.13 0.11
QF8T4R3 1 1.480 1.50 1.54 5.90 7.44 4.69 0.13
QF8T4R3 2 0.728 0.57 1.48 4.70 6.18 1.63 0.11
QF8T4R3 6 0.692 0.37 1.31 17.96 19.27 0.67 0.09 210.
QF8T4R3 8 0.508 0.34 1.30 3.42 4.72 0.71 0.07
QF8T4R3 9 0.600 0.40 1.32 2.48 3.80 1.10 0.08
QF8T4R3 10 0.592 0.37 1.37 2.68 4.05 0.97 0.12
QF8T4R3 11 0.258 0.34 1.31 2.01 3.32 0.51 0.09
QF9T3R1 1 1.350 1.01 1.62 7.10 8.72 2.00 0.27
QF9T3R1 2 1.630 0.92 1.78 7.30 9.08 1.90 0.26 266.
QF9T3R1 3 1.480 0.88 1.69 6.60 8.29 1.80 0.24
24.40
0.48
1
0.2832
5.40
0.20
4
1.8406
3.50
0.18
7
2.6901
2.50
0.20
13
3.3980
1.80
0.20
22
3.9644
1.60
0.15
28
4.0493
1.40
0.18
34
4.0493
1.40
0.20
46
4.2475
1.00
0.23
55
4.2475
2.70
0.15
3
3.1149
2.00
0.10
6
3.6812
1.60
0.13
12
4.1059
1.40
0.15
18
4.3891
1.30
0.10
24
4.5307
1.30
0.08
29
4.5307
2.20
0.10
2
3.1149
1.60
0.15
5
3.8228
1.30
0.13
11
3.8228
1.20
0.10
17
4.8705
1.20
0.13
23
4.6723
1.00
0.15
30
4.7289
1.10
0.15
32
2.2653
2.70
0.25
2
0.2832
2.40
0.15
5
1.4158
2.80
0.20
9
1.9255
1.80
0.20
11
1.2743
1.40
0.20
2
2.6901
1.30
0.20
5
3.1149
1.60
0.20
8
3.4830
1.40
0.10
11
3.5396
1.80
0.05
21
3.5396
1.70
0.05
23
2.5485
4.00
0.45
2
0.5663
1.80
0.28
5
1.5574
1.40
0.28
8
1.9822
1.10
0.25
14
2.5485
0.90
0.20
23
2.8317
0.80
0.20
35
3.0582
0.70
0.18
42
3.3980
0.80
0.20
44
2.2653
1.30
0.20
3
1.4158
0.90
0.20
12
3.3980
0.80
0.20
19
3.3980
0.70
0.15
21
2.6901
2.30
0.23
1
0.2832
1.00
0.20
4
3.1149
0.80
0.13
16
4.1626
0.70
0.13
22
3.9644
0.90
0.13
26
4.1626
0.60
0.18
28
3.2564
2.60
0.30
31
0.8495
2.80
0.35
5
0.5097
2.60
0.35
8
0.6230
2.70
0.30
11
0.7646
-------
4
1
2
3
4
5
6
1
2
4
6
8
9
10
1
2
3
8
10
12
16
17
1
2
4
6
8
9
1
2
4
6
3
9
1.630 0.76 1.64 7.40 9.04 1.90 0.22
2.380 1.62 1.81 9.80 11.61 2.60 0.18
1.910 1.48 1.78 7.20 8.98 2.10 0.16
1.760 1.27 1.54 6.60 8.14 2.00 0.15 313.
1.790 1.32 1.60 6.10 7.70 1.90 0.15
1.760 1.04 1.54 5.90 7.44 1.80 0.10
1.140 1.52 1.62 4.20 5.82 1.40 0.09
1.910 1.09 1.54 6.50 8.04 2.20 0.10
1.800 0.93 1.47 5.30 6.77 1.90 0.09
1.920 0.66 1.29 5.00 6.29 1.90 0.09
2.120 0.69 1.26 5.70 6.96 2.00 0.09 318.
2.090 0.65 1.35 5.20 6.55 2.00 0.08
1.430 0.41 1.33 '3.50 4.83 1.40 0.08
0.776 0.30 1.33 2.00 3.33 1.10 0.07
1.940 2.74 3.58 2.82 6.40 3.03 0.15
2.050 2.23 2.70 6.76 9.46 2.93 0.12
1.940 1.79 2.54 8.13 10.67 1.98 0.13 284.
1.840 1.09 1.94 4.53 6.47 1.02 0.10
1.740 1.00 1.77 2.99 4.76 1.82 0.10
1.390 0.91 1.74 4.11 5.85 1.35 0.10
1.890 0.75 1.64 7.36 9.00 1.46 0.07
1.430 0.73 1.62 3.68 5.30 1.97 0.10
1.920 1.82 3.41 16.26 19.67 2.47 0.10
2.010 1.54 2.92 4.19 7.11 2.38 0.08
1.960 1.28 2.12 4.11 6.23 2.34 0.07 356.
1.920 1.01 1.77 7.19 8.96 2.15 0.09
1.730 0.78 1.61 5.20 6.81 2.00 0.07
1.190 0.82 1.66 3.25 4.91 1.13 0.07 338.
1.990 1.14 2.03 10.10 12.13 2.40 0.06
1.560 1.04 1.74 . 8.66 10.40 1.80 0.07
1.750 0.81 1.22 8.00 9.22 1.40 0.07
1.700 0.63 1.36 6.68 8.04 1.20 0.09
1.580 0.59 1.37 6.12 7.49 1.20 0l07
1.730 0.64 1.30 6.01 7.31 1.50 0.05
2.60
0.40
14
0.9628
2.80
0.25
3
1.6990
2.60
0.25
6
1.7840
2.20
0.23
9
1.9539
2.20
0.23
12
2.0671
2.20
0.28
17
2.1804
2.10
0.20
18
1.2743
1.90
0.18
2
2.1238
2.00
0.18
5
2.4352
1.50
0.18
11
2.6335
1.60
0.15
17
2.6335
0.60
0.08
23
2.6335
1.10
0.18
27
1.6990
0.30
0.05
30
0.2832
2.80
0.23
3
1.1327
2.60
0.18
6
1.6141
2.40
0.25
9
1.9822
1.30
0.15
24
2.5485
1.10
0.15
30
2.4069
1.10
0.13
36
2.5485
0.90
0.13
48
2.5768
0.90
0.15
51
1.1327
2.40
0.15
2
1.6990
1.90
0.15
5
2.2653
1.50
0.18
11
2.5768
1.20
0.20
17
3.2564
1.00
0.18
24
2.8317
0.80
0.13
26
1.5574
1.40
0.18
2
2.2653
1.20
0.43
5
2.9450
1.00
0.18
11
3.3414
0.90
0.20
17
3.1715
0.80
0.18
23
3.1149
0.80
0.15
27
3.3980
86
-------
APPENDIX B - VEGETATIVE FILTER STRIP DESIGN AND EVALUATION PROCEDURE
REGRESSION EQUATIONS
The equations and procedures presented herein were developed to assist in
the design of new VFS and in the evaluation of existing VFS. The empirically
derived equations were developed from the experimental plot studies discussed
in the main body of this report. Because of the limited database from which
these equations were derived, they must be used with caution and sound engi-
neering judgment as conditions at other sites may differ considerably from those
for which these equations were developed.
The following equations, describing percent reductions in TSS (RTSS), T-N
(RTN), and T-P (RTP), were developed using multiple regression techniques. Data
used in the regressions included filter slope (s) and length (L), average plot
discharge per unit width (Q), and percent reductions in TSS, T-N, and T-P.
These equations were developed from data obtained from the first set of runs
during the feedlot simulations (Test 1) and cropland simulations (Test 3) only.
Data from Tests 2 and 4 were not used to avoid problems associated with exces-
sive sediment accumulation in the VFS. Use of all the plot data was undesirable
because simualted rainfall amounts over the period of application (100 mm/h for
2-1 h periods and 4-30 min periods in 2 weeks) had an extremely high recurrence
interval which is inappropriate for design purposes. Also, in the real world,
the temporal distribution of natural precipitation would allow regrowth of
inundated vegetation and some recovery of sediment and nutrient removal capa-
bilities.
Table B.l is a summary of the data which was used in the development of
the regression equations. As indicated in the table, the flow width used in
defining Q was 5.5m for the uniform flow plots (QF1, 2, 4, and 5) and either
0.75 m (QF8 and 9, Test 1) or 1.0 m (QF8 and 9, Test 3) for the concentrated
flow plots. The flow rate per unit width was obtained by dividing the total
discharge of the bare plot in the set (Runs 1, 2, and 3) by the rainfall duration
and the filter width through which flow was occurring.
The following 3 equations were developed to describe filter strip per-
formance :
87
-------
RTSS=71.41-29.23Q2+2.55L, r2=0.87 (Bl)
RTN=70.38+88.26Q-110.26Q2, r2=0.91 (B2)
RTP=74.03+74.47Q-97.96Q2, r2=0.90 (B3)
where: RTSS, RTN, and RTP are the percent reductions in TSS, T-N, and T-P,
respectively, Q is the flow rate into the filter, L/s-m, and L is the filter
length, m. Filter slope was not statistically significant in the regressed
equations.
Equation Bl describing the percent reduction in sediment is appropriate
for filters less than 11.2 m length and for flow rates less than 1.8 L/s-m.
At higher flow rates, RTSS is assumed negligible.
Equations B2 and B3, describing the percent reductions in T-N and T-P, can
be used for flow rates between 0.4 and 1.3 L/s-m. At higher flows, RTN and RTP
are assumed to be negligible. For flows less than 0.4 L/s-m, RTN, and RTP are
assumed to be 90%.
RECOMMENDED DESIGN/EVALUATION PROCEDURE
1. Obtain topographic map of area proposed for protection by VFS.
2. Delineate subwatersheds on the topographic map which will discharge to the
VFS and determine the drainage area for each.
3. Estimate the total volume of runoff which will be discharged from each
subwatershed using the Soil Conservation Service total runoff volume method
or some other appropriate method for the desired design storm.
4. Estimate the VFS width through which flow will pass for each subwatershed,
filter strip longitudinal length through which shallow uniform flow occurs
or channel width through VFS in subwatersheds with developed drainageways.
88
-------
5. Determine flow rate per unit width through filter strip for each
subwatershed.
6. Estimate percent reduction in desired pollutant for each subwatershed using
regression equations.
7. Area weight percent reductions obtained to determine if VFS is an appro-
priate BMP for the field under investigation.
DESIGN EXAMPLE
A 9.1 m VFS is proposed as a BMP for the contoured corn field shown in
Figure Bl. As shown in Figure Bl, the watershed has been divided into 6
subwatersheds, all of which except one, subwatershed F, drain through the VFS
below the field.
The area of each subwatershed along with assumed soil groups, land use,
curve numbers (N), and S and Q values as determined by the SCS total runoff
volume method (SCS, 1972) for a 2-year 1-hour duration storm in central Virginia
(I = 40.6 mm/h) are shown in Table B2 for the hypothetical watershed. In this
example, antecedent rainfall condition II is assumed.
If the effects of drainageways in the subwatersheds are neglected and all
flow from the field is assumed to flow across the VFS as shallow uniform flow,
RTSS is found to be 78% as shown in the last row of Table B2. A value of this
magnitude would normally indicate that a VFS was an excellent BMP for this
particular field but this is a false conclusion because the effects of concen-
trated flow and filter inundation were not considered.
A better method for evaluating VFS which was outlined in the previous
section also is presented in Table Bl. As shown in Table B2, RTSS ranges from
Q to 94% for individual subwatersheds. If these subwatershed values are area
weighted for the area draining through the VFS, an effective RTSS value of 17%
is obtained indicating that the VFS is only partially successful in removing
suspended solids from the field's runoff. In a similar manner, the percent
reduction in T-N and T-P were both approximately 16%.
89
-------
SUMMARY
As indicated in the design example, the effects of natural drainageways
and concentrated flow can have a significant impact on the design and evaluation
of VFS. The use of the design equations presented in this report were demon-
strated for a hypothetical watershed. They should be used with caution because
of the limited database from which they were derived. They should also be used
only within the flow ranges specified and in conjunction with the Recommended
Design/Evaluation Procedure presented in this report.
90
-------
V0
. Scale .
0 100 m
Figure B-l Design Example
-------
TABLE Bl.
VFS DATA FOR REGRESSION EQUATIONS
PLOT/
FILTER
TSS
T-N
T-P
FILTER
FILTER
FLOW
TEST
LENGTH
SLOPE
WIDTH
RATE
(M)
(%
REDUCTION)
(%)
(M)
(L/S-M)
QF1T1
9.1
97.
84.
88.
11.
5.5
0.215
QF2T1
4.6
87.
77.
81.
11.
5.5
0.215
QF4T1
9.1
91.
87.
88.
16.
5.5
0. 176
QF5T1
4.6
82.
78.
79.
16.
5.5
0.176
QF8T1
9.1
60.
14.
18.
5.
.75
1. 18
QF9T1
4.6
36.
28.
33 .
5.
.75
1. 18
QF1T3
9.1
99.
92.
95.
11.
5.5
0.063
QF2T3
4.6
90.
76.
80.
11.
5.5
0.063
QF4T3
9.1
83.
70.
72.
16.
5.5
0.058
QF5T3
4.6
73.
65.
67.
16.
5.5
0.058
QF8T3
9.1
93.
89.
89.
5.
1.0
0.250
QF9T3
4.6
86.
88.
86.
5.
1.0
0.250
92
-------
TABLE B-2. DESIGN EXAMPLE
vo
CjJ
Subarea Area, Soil Land Use, Treatment,
(ha) Group and Condition
B
1.7
12.6
1.3
10.4
2.1
B
B
row crop, contoured,
good
row crop, contoured,
good
row crop, contoured,
good
row crop, contoured,
good
row crop, contoured,
good
Curve S Q
No, N (mm) (mm)
82 55.8 10.2
82 55.8 10.2
82 55.8 10.2
75 84.7 5.2
75 84.7 5.2
Active
Filter
Width,
(m)
190
230
345
0,
(L/s-m)
0.25
119.0
0.14
50.1
0.09
RTSS"
(«)
92
94
94
Does not drain across VFS
Total Area 28.1
78.9 67.9 7.69 800
0.75
78
S = 25400/N-254
2 Q = (I-0.2s)2
1+0.85
From Equation Bl
------- |