validation of best management practices on eight kansas...
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Validation of Best Management Practices on Eight Kansas Farms
By Don Huggins, Will Spotts, Steven Wang, Debbie Baker, Jeff Anderson and Niang-Choo Lim
Kansas Biological Survey and the Central Plains Center for BioAssessment
University of Kansas
KBS Technical Report 105 March 2003
Validation of Best Management Practices on Eight Kansas Farms
Dr. Donald G. Huggins, Principle Investigator Director for the Central Plains Center for BioAssessment
University of Kansas Takeru Higuchi Building 2101 Constant Avenue Lawrence, KS 66047
William W. Spotts
Graduate Research Assistant at the Kansas Biological Survey Department of Ecology and Evolutionary Biology
University of Kansas
Dr. Steven H. Wang Director of the Kansas Biological Survey Ecotoxicology Laboratory
University of Kansas
Debra S. Baker Assistant Director for the Central Plains Center for BioAssessment
Kansas Biological Survey University of Kansas
Jeffrey A. Anderson
Graduate Research Assistant at the Kansas Biological Survey Department of Civil, Environmental and Architectural Engineering
University of Kansas
Niang-Choo Lim Graduate Research Assistant at the Kansas Biological Survey
Department of Civil, Environmental and Architectural Engineering University of Kansas
This research project was funded by USEPA Section 319 grant distributed by the Kansas Department of Health and Environment (KDHE) to the Kansas Biological Survey (KBS) as a companion grant to the Clean Water Farms Project of the Kansas Rural Center (KRC). The Kansas Biological Survey is a research and service agency of the state of Kansas. Organized in 1856 and formally established with the University of Kansas in 1911, KBS conducts a variety of research programs in the fields of water quality and freshwater ecology, natural areas, aquatic ecotoxicology and plant biology. Kansas is one of the few forward-looking states that support non-regulatory biological surveys.
The Central Plains Center for BioAssessment (CPCB) is a non-regulatory and non-management research organization nested within KBS. The CPCB was established as a center of biological expertise and as a scientific resource for the Central Plains and the United States Environmental Protection Agency (USEPA) Region 7. It is the Center's goal that our work will foster the spirit of cooperation between regional scientists, States, Tribes and other public entities in USEPA Region 7 that will result in collaborative research on issues of aquatic ecology and water quality.
Technical Report Number 105 of the Kansas Biological Survey and the Central Plains Center for BioAssessment
March, 2003
Acknowledgements Clean Water Farms Project Advisory Team members and participating farmers
Scott Satterthwaite, Kansas Department of Health and Environment, Bureau of Water Mary Fund, Kansas Rural Center
Validation of Best Management Practices on Eight Kansas Farms Table of Contents Page List of Figures iii List of Tables iv List of Photographs v Abstract vi Introduction 1 Nonpoint source pollution in Kansas Clean Water Farms Project
Best Management Practices Scope and Purpose of Companion Study
Partnerships and Participants Research Methods 4 Farm Selection
Monitoring Runoff Groundwater Sampling Surface Water Sampling Soils Monitoring Laboratory Analyses Habitat Diversity Index and Aquatic Invertebrate Collection Database Management and Graphics
Results and Discussions for Eight Monitored Farms
Bartel Farm 14 Spare Farm 28 Townsend Farm 35 Burr Farm 45 Howell Farm 51 Kunard Farm 60 Peters Farm 65 Hubbard Ranch 72 Project Review and Conclusions 77
References 86 Appendices 88
List of Figures Page Figure 1: Ecoregions of Kansas map showing eight CWFP farms with KBS monitoring projects. 4
Figure 2: Representative scatter plot and box plot. 13 Figure 3: Sampling sites and field perimeter on the Bartel farm, Marion County, KS. 16
Figure 4: Nutrient concentrations in groundwater at the upper sampling site. 21
Figure 5: Nutrient concentrations in groundwater at the lower sampling site. 22
Figure 6: Spatial relationships between points where runoff enters and exits fields and wetland pools. 24
Figure 7: Nutrients and herbicides in three developing wetland sites on the Bartel farm. 25
Figure 8: Sampling sites and field perimeters on the Spare farm, Saline County, KS. 30
Figure 9: Nutrients in groundwater sampled at the eight-foot depth at three locations on the Spare farm. 33
Figure 10: Sampling sites and field perimeters on the Townsend farm, Dickinson County, KS. 37
Figure 11: Nutrients in eight-foot deep groundwater sampled at three locations on the Townsend farm. 43
Figure 12: Sampling sites and field perimeters on the Burr farm, Saline County, KS. 47
Figure 13: Sampling sites and field perimeters on the Howell farm, Marshall County, KS. 53
Figure 14: Nutrients in groundwater sampled at the eight-foot depth at three locations at the Howell’s. 55
Figure 15: Nutrients, atrazine and coliform bacteria in Corndodger Creek. 57
Figure 16: Sampling sites and field perimeters on the Kunard farm, Miami County, KS. 62
Figure 17: Nitrogen and phosphorous compounds in shallow groundwater from the Kunard farm. 64
Figure 18: Sampling sites and field perimeters at the Peters farm, Marion County, KS. 67
Figure 19: Nutrient and herbicide concentrations in shallow groundwater on the Peters farm. 70
Figure 20: Pond sites and MIG system outer perimeter at the Hubbard ranch, Pottawatomie County, KS. 73
Figure 21: Nutrients, herbicides and coliform bacteria levels found in three stock ponds and a natural
spring on the Hubbard ranch. 76
Figure 22: Nutrient boxplots for first flush runoff sampled at ten sites on seven farms. 79
Figure 23: Herbicide boxplots for first flush runoff sampled at ten sites on seven farms 80
Figure 24: Nutrient and herbicide concentrations in shallow groundwater monitored on six farms. 82
Figure 25: Nutrient and herbicide boxplots for surface water monitored on four farms. 83
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List of Tables Page Table 1: BMPs used on the eight farms participating in the CWFP monitoring project. 2
Table 2: Monitoring programs for evaluating Best Management Practices on eight Kansas farms. 5
Table 3: Timed sampling regime for runoff samplers. 6
Table 4: Stream water quality by Hydrologic Unit Code 8 watershed averages. 7
Table 5: Chemical parameters and analyses methods used by KBS Ecotoxicology Laboratory. 11 Table 6: Soil quality indicators and chemistry from the Bartel’s strip-cropped field. 15
Table 7: Mean* nutrient and herbicide concentrations in first flush runoff at the upper site on the Bartel farm. 17
Table 8: Mean* nutrient and herbicide concentrations in first flush runoff at the lower site on the Bartel farm. 19
Table 9: Water quality of runoff from two fields with different fertility management strategies. 20
Table 10: Aquatic macroinvertebrates found in the Bartel wetland. 26
Table 11: Soil quality indicators and chemistry from the Spare’s converted field. 29
Table 12: Mean* nutrient and herbicide concentrations in runoff on the Spare farm. 31
Table 13: Soils quality indicators and chemistry from Townsend's converted field. 36
Table 14: Mean* nutrient and herbicide concentrations in first flush runoff at Townsend’s field site. 39
Table 15: Mean* nutrient and herbicide concentrations in first flush runoff in Townsend’s wetland. 40
Table 16: Nutrient and herbicide concentrations from three sites in the Townsend wetland. 41
Table 17: Soil chemistry from a crop field at the Burr farm. 46
Table 18: Mean* nutrient and herbicide concentrations in runoff at the upper site on the Burr farm. 48
Table 19: Mean* nutrient and herbicide concentrations in runoff at the lower site on the Burr farm. 49
Table 20: Soils quality indicators and chemistry from Howell's converted field. 52
Table 21: Mean* nutrient and herbicide concentrations in field runoff on the Howell farm. 54
Table 22: Aquatic invertebrates found in Corndodger Creek. 58
Table 23: Soil quality indicators and chemistry from the Kunard’s converted field. 61
Table 24: Mean* nutrient and herbicide concentrations in first flush runoff on the Kunard farm. 63
Table 25: Soil chemistry and quality indicators for fields under two land management practices. 66
Table 26: Mean* nutrient and herbicide concentrations in first flush runoff on the Peters farm. 69
iv
List of Photographs Page Photo 1: Runoff sampler positioned by an isolated drainage to collect runoff from no-till fields at the Peters farm. 5
Photo 2: Bottles of runoff sit atop the sampler after a particularly intense runoff event at the Howell farm. 6
Photo 3: Cluster of 8-foot, 4-foot and 1-foot lysimeters, covers sample bottles and pressure-vacuum hand pump 8
Photo 4: Pressure-vacuum hand pump set to retrieve a shallow groundwater sample from installed lysimeters. 8
Photo 5: Sampling surface water for bacteria at a livestock pond in a MIG grazing paddock. 9
Photo 6: Sampling aquatic macroinvertebrates to investigate the relationships between land management, 12
water chemistry and stream biological community.
Photo 7: KBS researcher surveys the soybean and wheat fields in the stripped-crop rotation before collecting 14
shallow groundwater samples.
Photo 8: Composted dairy bedding was applied to areas in the monitored strip-cropped field on the Bartel farm. 18
Photo 9: Dairy bedding applications increased nutrients available for local transport via runoff and groundwater. 18
Photo 10: Runoff entering a field through a road culvert is a source of gully erosion on agricultural fields. 25
Photo 11: Installing a runoff sampler in the converted field on the Spare farm. 28
Photo 12: Former wheat field planted to cool season grasses and legumes for conversion to a management 35
intensive grazing system.
Photo 13: Cropland converted to cool season grasses and legumes for management intensive grazing near 45
Mulberry Creek.
Photo 14: A runoff sampler collects runoff in the 93-acre parcel of cropland converted to perennial grasses 51
on the Howell farm.
Photo 15: Perennial grassland converted from cropland in the foreground with go-back prairie in the background. 60
Photo 16: No-till corn and residue at the Peters farm. 65
Photo 17: During the fall and winter, crop residue is left standing on Field 2 for soil cover. In the background, 66
Field 1 is planted in spring wheat.
Photo 18: Field 3 is conventionally tilled and managed for small grains and rowcrops. 66
Photo 19: Installing a sampler to collect runoff from the Peters’ no-till fields. 68
Photo 20: Cattle are moved between grazing cells in the management intensive grazing system on the 72
Hubbard ranch.
Photo 21: Pond 1 is the largest of the monitored ponds. This rocky shoreline is the future location of a watering site. 74
Photo 22: Shoreline vegetation around Pond 2 filled in after cattle were fenced out. The one bare spot at left 74
is the dam.
Photo 23: Repairs to the spillway of Pond 3 left the shoreline exposed before vegetation was established. 74
v
Abstract Changes in field-scale agricultural nonpoint source pollution levels were assessed relative to changes in
land management practices over a five-year period. The primary objective was to quantify edge-of-field
nutrient and herbicide concentrations in first flush runoff, shallow groundwater (i.e. soilwater) and surface
water for various Kansas agricultural practices under existing weather conditions on working farms.
Additionally, attempts were made to relate the observed changes water quality to causative factors (e.g.
weather patterns, natural conditions, adoption of best management practices) associated with the study
areas and farms.
Eight farms in central and northeast Kansas were chosen for study from thirty-five farms selected to
participate in the Kansas Rural Center’s Clean Water Farms Project. The management practices on the
selected farms were (1) green manure cover crops in a stripped-crop rotation, (2) no-till procedures on
rowcrops and small grains, (3) ongoing wheat field conversion to a grazing pasture, (4) rotational grazing
systems on pasture already converted from cropland, and (5) limiting livestock access to watering ponds.
Unforeseen changes in management plans or delays in implementation of management practices
required alterations to study objectives for two of the monitoring programs to make them relevant to the
actual management activities occurring on the farm. Runoff and groundwater samples were collected
from 1996 to 2000 and analyzed for a number of constituents, most notably the major nutrients nitrogen
and phosphorus and the herbicides atrazine and metolachlor. Scatter plots and box plots were used to
organize and interpret the water quality data.
A case study was developed for each farm in which potential causes of the observed changes in water
quality were identified and related to the specific combination of weather, topography, land use and land
cover on each farm. Variations in nutrient and herbicide concentrations in runoff and groundwater from
study fields were related to weather patterns, the timing or elimination of fertilizer applications, off-site
contributions of nutrients and herbicides, and the presence or absence of groundcover during larger
runoff events. The runoff and groundwater data collected during this project serves as baseline data to
characterize edge-of-field nutrient and herbicide concentrations on Kansas farms managed with practices
intuitively beneficial to water quality.
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Introduction The United States Environmental Protection Agency has identified agricultural nonpoint source pollution
(NPSP) as the major source of stream and lake contamination preventing attainment of the water quality
goals identified in the Clean Water Act (USEPA, 1988). Agricultural NPSP is the weather-driven
transportation of nutrients, pesticides, sediment and pathogens from agricultural land into natural aquatic
and terrestrial ecosystems. Surface runoff and groundwater carry these contaminants across the land
surface and through the soil, eventually depositing them in streams, lakes and reservoirs. Agricultural
NPSP is a function of climatic factors and site-specific land characteristics such as soil type, local
topography and land management. Sources are widespread and difficult to quantify, as NPSP generally
occurs over large areas, is episodic and involves multiple pollutants of natural and anthropogenic origins.
The impacts of agricultural NPSP are important for human health considerations, the integrity of aquatic
ecosystems and the long-term sustainability of intensive agriculture.
The Clean Water Farms Project (CWFP) was initiated in 1995 by the Kansas Rural Center (KRC) and
others to help farmers and ranchers in Kansas adopt land management practices that address water
quality issues involving NPSP. Funded by United States Environmental Protection Agency (USEPA)
Nonpoint Source Section 319 Funds through the Kansas Department of Health and Environment, the
CWFP provided financial incentives to farmers to achieve environmentally sustainable and economically
practical solutions to farm and watershed-scale water quality issues. The Kansas Rural Center (KRC)
distributed grants of up to $5000 to thirty-five Kansas farms and ranches involved in cropping systems,
livestock operations and integrated systems to implement changes in land management with the eventual
goal of water quality improvement. Central to the project was the adoption of best management
practices (BMPs). The BMP concept was developed specifically to deal with NPSP problems and
includes a farm-specific combination of structural controls, source controls and land management
practices to reduce or prevent NPSP. Structural controls, like terraces, grass waterways and filter strips,
are designed to reduce pollutant transport in water by rerouting, reducing or slowing down runoff. They
are particularly effective for the control of sediment and sediment-associated pollutants in surface runoff.
Source controls, like restricting fertilizer and herbicide applications have been shown to be effective at
reducing nutrients and herbicides in shallow groundwater and streams (Logan 1990). Land management
practices include the timing and placement of nutrients and herbicides, conservation tillage, rotational
management intensive grazing (MIG) and crop rotations. Management practices do not often lead to
obvious reductions in NPSP like structural and source controls; they are instead intuitive long-term
decisions based on farmer goals, economics and farm-specific ecological conditions. The overall
effectiveness of BMPs can be rated in terms of their relative impact on water quality and pollutant loads,
cost-effectiveness, acceptability by farmers, trade-offs necessary for implementation and long-term
sustainability of the practice. Monitoring the adoption of BMPs by farmers is recognized as being an
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easier method of judging the success of on-farm conservation efforts than monitoring edge-of-field or
subsurface changes in NPSP levels.
Table 1: BMPs used on the eight farms participating in the CWFP monitoring project.
1. Conversion from cropland to perennial grasses and legumes. 2. Rotational and Management Intensive Grazing (MIG). 3. Restricting livestock access to streams and wetlands. 4. Native buffer strips between developed pasture and intermittent stream. 5. Developing alternative watering methods to extend the life of cattle-watering ponds. 6. Organic crop rotations incorporating cover crops and green manures. 7. No-till farming with intensive crop rotations including cover crops 8. Repairing field gullies by promoting a transition to a wetland environment. 9. Redesigning grass waterways to better control field runoff. 10. Controlling stream bank erosion with cedar revetements.
Since BMPs need to be designed and implemented according to site-specific and goal-specific
conditions, monitoring their effectiveness is a challenging task. As a companion project to the CWFP, the
Kansas Biological Survey (KBS) developed water quality monitoring programs on eight farms in six
counties in central and northeast Kansas to detect differences in water quality that relate to the changes
in management practices. The two primary goals of the monitoring projects were (1) to assess edge-of-
field concentrations of nutrient and herbicide compounds relative to different Kansas agricultural
management practices; and (2) to relate observed concentrations to land management practices and
weather patterns.
Programs were tailored to fit each location based on the farm’s specific water quality goals, water quality
hypotheses available for testing, local topography and opportunities for the collection of comparative
samples from different land uses in the watershed. Monitoring began in 1996 on five farms and on three
additional farms in 1998 to provide data on existing conditions and to identify sources of variation in water
quality over time and space. Runoff, shallow groundwater, surface water and soils from isolated
agricultural drainages were sampled, and analyses were performed for nitrogen and phosphorus
compounds, herbicides (atrazine and metolachlor), and fecal coliform bacteria. The more successful
monitoring programs were opportunistic, longer in duration, had multiple sampling sites and on-site
differences in land management to offer comparative data, and had higher levels of farmer involvement.
The purpose of this report is to detail the nature and goals of the monitoring programs established by the
Central Plains Center for Bioassessment and the Kansas Biological Survey and to present the water
quality data gathered by those programs.
Clean Water Farms Project Advisory Team Members The Clean Water Farms Project is an ongoing project of the Kansas Rural Center funded by the United
States Environmental Protection Agency Section 319 Nonpoint Source Funds (Contract C9007405-06-0).
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Advisory team members were selected from universities, nonprofit groups, private enterprise and
regulatory agencies to provide a broad spectrum of experience and ideas in making this project
successful. The following individuals served as CWFP advisory team members and were integral to the
success of this project and the monitoring efforts of KBS.
Lisa French, Kansas Rural Center. 8016 Long View Rd. Partridge, KS 67566 [email protected] Mary Fund, Kansas Rural Center. Rt. 2 Box 23 Goff, KS 66428 [email protected] Dr. Bill Hargrove, Kansas Center for Agricultural Resources and the Environment
Kansas State University. 44 Waters Hall, Manhattan, KS 66506 [email protected]
Dr. Don Huggins, Kansas Biological Survey and Central Plains Center for BioAssessment. Takeru Higuchi Building, 2101 Constant Ave. Lawrence, KS 66047 [email protected]
Dr. Rhonda Janke, Kansas State University. 3602 Throckmorton Hall, Manhattan, KS 66506
[email protected] Dan Nagengast, Kansas Rural Center. 966 E. 800 Rd. Lawrence, KS 66047 [email protected] Ed Reznicek, Kansas Rural Center. Rt. 2 Box 23 Goff, KS 66428 [email protected] Vic Robbins, 4532 141 St. Carbondale, KS 66414 Scott Satterthwaite, Kansas Department of Health and Environment
1000 SW Jackson St. Suite 420, Topeka, KS 66612 [email protected] Will Spotts, Kansas Biological Survey. 2101 Constant Ave. Lawrence, KS 66047 [email protected] Donn Teske, 17925 Goldenbelt Rd. Wheaton, KS 66551 [email protected] Earl Wright, PO Box 226, Council Grove, KS 66846 [email protected] Validation of the Clean Water Farms Project Participating Farmers The project would have been impossible without the cooperation and contributions of these farm families.
Herb and Patricia Bartel, Hillsboro, KS
Steve Burr, Salina, KS
Dan and Mary Howell, Frankfort, KS
Alan Hubbard, Olsburg, KS
Tim and Bridgette Kunard, Edgerton, KS
Rod Peters, Hillsboro, KS
Bruce Spare, Assaria, KS
Richard, Julia and Jim Townsend, Chapman, KS
3
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Monitoring Program Methodologies The Kansas Biological Survey established monitoring programs on eight of the thirty-five farms selected
for the Clean Water Farms Project. Programs were designed to gather data on changes in on-site water
quality relative to the best management practices implemented on the farms. Specific elements of a
monitoring program depended on the type of demonstration proposed, the availability of water for
sampling (runoff, groundwater, surface water), water quality issues being addressed and the short- and
long-term goals of the participating farmers. Farm tours and on-site evaluations were conducted to make
the final determination regarding the suitability of a farm and demonstration for monitoring.
Figure 1: Ecoregions of Kansas map showing eight CWFP farms with KBS monitoring projects.
Ka n sas E co reg ionsCe ntra l G reat P la insCe ntra l Ir reg u lar P la insCe ntra l O kla ho m a/Texas P la in sF lin t H illsOz ark H igh land sS o uthw ester n Ta b leland sW es ter n C or n B elt P la insW es ter n H ig h P la ins
S
N
EW
Source: Level 3 Ecoregions of Kansas. Omernick et al, 2000.
The eight farms monitored through this project were located in six counties in central and northeastern
Kansas. Six of the monitored farms had projects involving grazing systems. Converting cropland to
perennial grassland and developing management intensive grazing (MIG) systems were two
management strategies used by those six participants. Two farms were engaged in crop production and
addressed on-farm water quality by developing extended crop rotations including cover crops.
Monitoring was initiated on five farms in 1996; three more were added when additional resources were
made available to the monitoring project in 1998. Each farm had a specifically tailored sampling regime
designed to fit questions posed by the demonstration and often included on-site features of different land
use that could offer important contrasts in water quality as a function of land use. Opportunistic
monitoring provided some important data for comparisons and case studies. Field runoff, shallow
groundwater, surface water, soils, vegetation, aquatic habitat information and aquatic invertebrate
species were all sampled to characterize existing water quality conditions and track any changes that
might have occurred. Nutrient and herbicide concentrations in collected water samples were analyzed in
order to acquire data on baseline conditions and to observe trends in water quality over time. Sometimes
that which is intuitively beneficial to water quality does not lend itself to be quantified through monitoring,
so monitoring programs had to be creative and adaptable.
use that could offer important contrasts in water quality as a function of land use. Opportunistic
monitoring provided some important data for comparisons and case studies. Field runoff, shallow
groundwater, surface water, soils, vegetation, aquatic habitat information and aquatic invertebrate
species were all sampled to characterize existing water quality conditions and track any changes that
might have occurred. Nutrient and herbicide concentrations in collected water samples were analyzed in
order to acquire data on baseline conditions and to observe trends in water quality over time. Sometimes
that which is intuitively beneficial to water quality does not lend itself to be quantified through monitoring,
so monitoring programs had to be creative and adaptable.
Table 2: Monitoring programs for evaluating Best Management Practices on eight Kansas farms. Table 2: Monitoring programs for evaluating Best Management Practices on eight Kansas farms. Farm County Farm County Land Use Land Use Demonstration Demonstration Year Started Year Started RunoffRunoff Groundwater Groundwater Surface Water Surface Water Other1 OtherBartel Bartel Marion Marion Crop Crop Strip Crop Rotation Strip Crop Rotation 1996 1996 x x x x x x x x
1
Spare Saline Grazing Conversion to MIG 1996 x x Townsend Dickinson Grazing Conversion to MIG 1996 x x x x Burr Saline Grazing Conversion to MIG 1996 x Howell Marshall Grazing Conversion to MIG 1996 x x x x Kunard Miami Grazing Conversion to MIG 1998 x x Peters Marion Crop No-till crop rotation 1998 x x Hubbard Pottawatomie Grazing Protection of cattle
watering sites 1998 x
Other1: Wetland vegetation, aquatic Habitat Development Index (HDI), aquatic macroinvertebrates.
Monitoring Runoff Seven of the eight farms monitored by KBS were equipped with
runoff samplers. Four farms had one sampling location and
three farms had two. At the sites equipped with paired units,
samplers were placed near the up and downstream ends of an
isolated drainage or at strategic locations where measurable
changes in water quality could be a function of a change in land
use/land cover or the result of a management practice.
Photo 1: Runoff sampler positioned by an isolated drainage to collect runoff from no-till fields at the Peters farm.
Sigma Streamline 800SL Portable Samplers� were installed
and used to collect field runoff as a result of individual storm
events. The sampler was enclosed in a stilted housing unit to
protect the device from high water levels, extreme weather
conditions and damage from animals. In order to maximize
the likelihood of capturing runoff, the entire unit was placed
near a swell or other field location where surface flow might
occur. Attempts were made to isolate small field-scale agricultural drainages in order to avoid or
decrease contributions of neighboring drainages not associated with the project. Due to the diffuse nature
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of nonpoint source pollution, off-site and watershed-level contributions to local water quality must be
considered when interpreting the results of any water quality monitoring program.
To collect runoff, a five-liter sump was buried flush with the ground to capture runoff as it accumulated
and flowed from the study area. Several small holes were drilled in the bottom of the sump to allow some
water to flow through during runoff events and to permit drainage between runoff events. Surface runoff
water filling the sump activated a float switch, which in turn activated the sampler. A programmable
computerized pump initiated the sampling and controlled the timing of the sampling regime. Water was
strained and pumped through a Teflon-lined plastic tube into a series of eight two-liter clear glass bottles
contained in the main sampling unit. Since the intensity and duration of each runoff-producing storm
varied greatly, we decided to capture the initial “first flush” waters of a runoff event. The Sigma sampler
was programmed to take eight one-liter samples over a three-hour period after sampler activation. Based
on prior experience with the samplers, the sample intervals in Table 3 were thought to best characterize
the water quality of runoff events in the field-scale drainages of this project.
Table 3: Timed sampling regime for runoff samplers.
Bottle Sampling Increment Total Minutes After Activation 1 activation 0 minutes 2 20 minutes 20 minutes 3 20 minutes 40 minutes 4 20 minutes 60 minutes 5 30 minutes 90 minutes 6 30 minutes 120 minutes 7 30 minutes 150 minutes 8 30 minutes 180 minutes
Photo 2: Bottles of sampled runoff sit atop the runoff sampler after a particularly intense runoff event at the Howell farm.
After a potential runoff-generating storm event, the farms were
visited to collect the sampled runoff. Several of the laboratory
analyses had to be conducted within 48 hours of sample
collection, so it was important to retrieve the samples as soon
as possible. After each sampling event, the exact time and date of sampling program activation were
recorded. Samples in bottles were capped with Teflon-lined lids, packed in ice and transported to the
KBS Ecotoxicology laboratory for analysis. Before leaving the site, clean two-liter glass bottles were
placed in the sampler for the next round of runoff collection. Typically, samplers were programmed to
delay subsequent activation for at least a week. This allowed any lingering runoff or pooled water to
recede and thus ensured the collection of separate runoff events.
6
Mean nutrient and herbicide concentrations from runoff samples were calculated by averaging the
concentrations of the eight samples collected in the first three hours after sampler activation. Runoff
water quality data are presented and compared to the Hydrologic Unit Code 8 watershed average stream
water quality when possible. The HUC values provide a measure of comparison for the sampled water
quality but do not take into account the initial greater flush of nutrients and herbicides generated in the
first stages of a runoff event. Such “first flush” concentrations are expected to be higher than baseline or
low flow conditions. However, the HUC 8 watershed averages do provide a needed benchmark against
which to contrast first flush concentrations and the potential differences in water quality as a function of
watershed-level activities and local-level management decisions.
Table 4: Average stream water quality by Hydrologic Unit Code 8 Watershed Farm County HUC ID NO3 NH3 TP AtrazineBartel Marion 11070202 0.90 0.09 0.17 1.54 Spare Saline 10260010 0.76 0.07 0.26 0.98 Townsend Dickinson 10260008 0.87 0.08 0.31 0.89 Burr Saline 10260010 0.76 0.07 0.26 0.98 Howell Marshall 10270205 1.91 0.14 0.32 2.15 Peters Marion 11070202 0.90 0.09 0.17 1.54 Kunard Miami 10290102 0.45 0.07 0.16 1.79 Hubbard Pottawatomie 10270102 0.69 0.08 0.27 1.27 Kansas Statewide Average 1.02 0.11 0.26 1.12
Units: (NO3, NH3, TP) = mg/L; Atrazine = ug/L. Source: Appendix B, Kansas Nonpoint Source Pollution Management Plan (KDHE 2000).
As with most field sampling efforts, some problems occurred in the runoff-sampling program that directly
or indirectly affected sample quality and quantity. Communication gaps between the monitoring program
participants and KBS led to the late retrieval of sampled runoff water, which made results for several
specific nutrient analyses (NO3, NH3, PO4) questionable. Therefore, KBS analyzed those samples for TN,
TP and herbicide concentrations only. On several occasions the runoff samplers did not perform up to
expectations, collecting too small a sample volume or not collecting samples at all. Four samplers had to
be returned to the manufacturer for repairs either to the internal computer, rotating pump arm or peristaltic
pump. Rodent damage to electrical cables and intake tubes were other causes of sampler failure. KBS
estimates that the Sigma 800SL Portable Samplers� successfully sampled approximately 75% of the
possible runoff events on the seven farms equipped with the samplers.
Collecting estimates of precipitation was a necessary factor in interpreting the runoff sampling results.
Each farm was given a rain gauge and asked to supply rainfall information for the duration of the
monitoring project. In most cases, this information was provided. In the instances when it was not,
precipitation estimates were taken from the weather station closest to the monitored farms. Local
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Photo 3: Cluster of 8-foot, 4-foot and 1-foot lysimeters, covers, sample bottles and pressure-vacuum hand pump.
Photo 4: Pressure-vacuum hand pump set to retrieve a shallow groundwater sample from installed lysimeters.
differences in precipitation amounts can be pronounced, so the rainfall estimates taken from the weather
stations could be a source of experimental error in the data interpretation.
Groundwater Sampling The pressure/vacuum lysimeters used by KBS to
collect shallow groundwater were constructed from
sealed lengths of PVC pipe that collected water at the
depth of a porous porcelain end cap. Clusters of three
lysimeters, one each of one, four and eight-foot
depths, were installed on six farms. Clusters were
situated to monitor groundwater from potentially
distinct local drainages or along the length of a single
drainage. To install each lysimeter, an eight-
centimeter borehole was hand-augured down to the
desired depth using a stainless steel augur. The
bottom of the borehole was sealed with bentonite,
which limited soil water at deeper depths from being
sucked upwards into the lysimeter. Next, a three- to
five-centimeter layer of silica flour was poured on top
of the bentonite powder. The lysimeter was then put
in place and more silica flour was added to protect the
pores of the porcelain cup from getting clogged. The
borehole was then filled with the excavated soil and
another layer of bentonite was added just below
ground level to prevent surface water from infiltrating
the borehole and altering the soil water chemistry
near the collection cup of the lysimeter. The entire
assembly was covered with a capped four-inch
diameter length of PVC to prevent damage by
animals and weather to the exposed portion of the
lysimeters.
To sample the groundwater, a vacuum was applied to the lysimeter with a pressure-vacuum hand pump.
This was accomplished by attaching the hand pump to the lysimeter and pumping until a level of 60
centibars or greater of soil suction was reached. The lysimeter’s pressure and water-transport tubes were
sealed with pinch clamps to make the entire unit airtight, and the vacuum was left on the lysimeter
between seven and fourteen days. Earlier experiments that left the vacuum on for a shorter period did
8
not collect enough sample volume for the entire set of nutrient and herbicide analyses. To retrieve the
collected soil water, the lysimeter was attached to a hand pump and pressurized. Shallow groundwater
was collected from the polyethylene tube that ran the length of the lysimeter pipe. One-liter amber glass
bottles and 250-milliliter single-use sterile sampling bags were used to transport the groundwater samples
from the field to the lab. Gaps in the data resulted from a loss of vacuum pressure, animal damage to the
retrieval tubing and drought conditions that reduced the amount of groundwater (i.e. soil water) in the root
zone. Lysimeters on four farms had to be replaced during the study.
Surface Water Sampling
Photo 5: Sampling surface water for bacteria at a livestock pond in a MIG grazing paddock.
Four farms had streams, ponds or wetlands that
presented opportunities for KBS to monitor effects of the
changes in land use and land management on surface
water chemistry and aquatic ecosystems. Comparisons of
runoff and groundwater chemistry to surface water
chemistry provided an important comparison between an
individual field and its watershed. Pre-cleaned one-liter
amber bottles were used to collect grab samples for
nutrient and herbicide analyses; bottles and lids were
rinsed twice with water from the collection sight and
packed in ice for transport back to the laboratory. Samples were collected at multiple locations in the
streams, ponds and wetlands to observe differences in nutrient and herbicide concentrations within the
bodies of water.
Chemical Analyses All water samples were delivered to the KBS Ecotoxicology Laboratory for chemical analysis. Samples
were analyzed for the following compounds: total nitrogen, organic nitrogen, nitrate, ammonia, total
phosphorus, phosphate, atrazine and metolachlor. Samples that were not retrieved within 48 hours after
sampler activation were analyzed for the subset of total nitrogen, total phosphorus, and the two
herbicides. A complete list of the chemical analyses undertaken and the methods involved is presented
in Table 5.
Nitrogen Compounds For the water samples, total nitrogen (TN) is the sum of nitrate, nitrite, ammonia, and organic nitrogen
concentrations. Nitrate (NO3) is a highly soluble nutrient and is the primary form of dissolved nitrogen in
streams and groundwater. Sources include fertilizers, livestock wastes, septic tanks, and the
decomposition of organic matter (USGS, 1999). In this report, nitrate refers to the sum of nitrate plus
nitrite. Nitrite (NO2) is generally unstable in surface water and contributes little to the total nitrogen level.
9
Ammonia (NH3) is another dissolved form of nitrogen that is less common than NO3. Inorganic and
organic fertilizers are primary sources of NH3. Organic nitrogen (Org N) levels are prone to seasonal and
management-based variation and can contribute substantially to the total nitrogen levels. Sources of
organic nitrogen include decomposing plant material and fecal matter.
Phosphorus Compounds Phosphorus occurs naturally in soil at levels between 300 to 1,200 mg/kg, although amounts can vary
from 100 to 2,500 mg/kg The wide variation in soil phosphorus content is a function of parent material,
texture, and management factors such as the rate and type of phosphorus applied and soil cultivation.
Excess fertilization and manure accumulation can cause a phosphorus surplus to occur in the soil, some
of which is transported to aquatic ecosystems. Total phosphorus (TP) includes inorganic phosphates and
particulate organic phosphorus. In most soils, 50 to 90 percent of the P is inorganic phosphate
compounds. Most inorganic phosphorus forms are not very soluble, and only a small fraction is available
at any one time for plant uptake (Daniel et al, 1999). However, phosphates (PO4) are the most common
forms of phosphorus found in natural waters. Phosphates occur in solution, but they are not very mobile
in soil water and groundwater due to their strong attraction to soil particles. Phosphates can have a
significant impact on water chemistry because eroded soil can transport considerable amounts of
attached phosphates to surface waters. The majority of measured PO4 is orthophosphate.
Orthophosphate in surface water is immediately biologically available for uptake by aquatic plants and
has been shown to promote the eutrophication of surface waters at levels over 0.01 mg/L. Organic
phosphorus (Org P) is found in soil hummus and is also produced by the decomposition of organic
materials.
Herbicides: Atrazine and Metolachlor Tillage and the timing of applications relative to spring and fall rains are important determinants in the
availability of herbicides to transport via runoff and groundwater. Atrazine is a selective triazine herbicide
used to control broadleaf and grassy weeds in corn, sorghum, sugarcane, pineapple, christmas trees, and
other crops, and in conifer reforestation plantings. It is also used as a nonselective herbicide on non-
cropped industrial lands and on fallow lands. Atrazine is the most widely applied herbicide in Kansas; in
1990, 74 percent of all Kansas corn acres (1.6 million acres) was treated with an average of 1.17 pounds
of atrazine per acre (Snethen, 1993). Over 64 million acres of cropland were treated with atrazine in the
U.S. in 1990. Atrazine is highly persistent in soil and moderately soluble. Because it does not adsorb
strongly to soil particles and has a lengthy half-life (60 to >100 days), it has a high potential for
groundwater contamination despite its moderate solubility in water, and has been classified as a
restricted use pesticide (Craigmill, 1997).
10
Metolachlor is usually applied to crops before plants emerge from the soil, and is used to control certain
broadleaf and annual grassy weeds in field corn, soybeans, peanuts, grain sorghum, potatoes, cotton,
highway rights-of-way and woody ornamentals. It inhibits protein synthesis; thus, high-protein crops (e.g.
soy) can be adversely affected by excessive metolachlor application. Additives may be included in
product formulations to help protect sensitive crops (e.g. sorghum) from injury. Metolachlor is found in the
trade names Dual and Bicep, among others. Metolachlor is moderately persistent in the soil environment.
Half-lives of 15 to 70 days in different soils have been observed. Soils with significant soil water content
may show more rapid breakdown. Breakdown is mainly dependent upon microbial activity, and thus is
temperature-dependent. Microorganism metabolism occurs by both aerobic and anaerobic processes,
and is affected by temperature, moisture, the amount of leaching, soil type, nitrification, oxygen
concentrations, and sunlight. It is slightly soluble in water. Extensive leaching is reported to occur,
especially in soils with low organic content. Metolachlor is highly persistent in water over a wide range of
water acidity. Its half-life at 20 degrees C is more than 200 days in acid waters, and is 97 days in basic
waters (Craigmill, 1997).
Table 5: Chemical parameters and analytical methods used by KBS Ecotoxicology Laboratory. Parameter Equipment and Method Method Citation Detection Limit Total Nitrogen (TN) Lachat 48 Place Digester Ebina et al., 1983 0.01 mg/L Lachat QuikCehm 4200 Flow Injection Analyzer Total Phosphorus (TP) Lachat 48 Place Digester Ebina et al., 1983 0.005 mg/L Lachat QuikCehm 4200 Flow Injection Analyzer Ammonia (NH3) Lachat QuikCehm 4200 Flow Ebina et al., 1983 0.001 mg/L Injection Analyzer Nitrate (NO3) Lachat QuikCehm 4200 Flow APHA, 1995 0.01 mg/L Injection Analyzer 4500 P Phosphate (PO4) Lachat QuikCehm 4200 Flow APHA, 1995 0.001 mg/L Injection Analyzer 4500 P Atrazine and Metolachlor Gas Chromatography Thurman et al., 1990 0.02 ug/L Mass Spectrometry Soil pH Potentiometer with 0.01M CaCl2 USEPA, 1990 - Total Kjeldahl Kjeldahl digestion Bremner et al, 1982 0.01 mg/L Nitrogen (TKN)
Dissolved Organic Beckman 915A Carbon Analyzer APHA, 1995
5310 B 0.1 mg/L Carbon (DOC) Aggregate Stability % Soil sieves Angers, 1993 1 mm < x < 2 mm Soils Characterization Soils on seven of the farms were sampled from the top ten centimeters of the A-horizon with a soil probe.
Any visible organic matter and litter were removed from the soil surface prior to sampling to avoid skewing
carbon analysis data. Under normal sampling conditions, three or four cores of soil were taken from the
11
top of the A-horizon and combined to comprise an individual sample at each site. Triplicate samples
were taken at each collection site to provide some measure of the local differences in soil characteristics.
Two or three sets of triplicate samples were taken on three farms where different land management
practices (Table 2) might affect local soil quality.
Soil samples were analyzed for pH, aggregate stability percentage, dissolved organic carbon, total
Kjeldahl nitrogen, NO3, TP and PO4. The pH is a measure of soil acidity. The pH log scale ranges from 1
to 14; a pH of 7 is neutral, while less than 7 is acidic and greater than 7 is alkaline. The aggregate
stability percentage is a measure of how well soil particles are bound together by organic materials.
Higher percentages of aggregate stability are indicative of greater water retention and better soil
structure. Aggregate stability percentages are a function of management and naturally occurring soil
characteristics (Tisdale, 1982). Dissolved organic carbon (DOC) is the soluble carbon that leaches from
plant and soil organic matter. Total Kjeldahl nitrogen (TKN) is the sum of organic nitrogen and ammonia.
Habitat Development Index and Aquatic Invertebrate Collection
Photo 6: Sampling aquatic macroinvertebrates to investigate the relationships between land management, water chemistry and stream biological community.
The Habitat Development Index (HDI) was developed in
1988 as a method to identify, quantify and compare
stream microhabitats and their influence on the local
aquatic macroinvertebrate community structure. The
HDI was calculated in conjunction with aquatic
macroinvertebrate sampling on three farms where
streams and wetlands were included in the KBS
monitoring program. The HDI is a quantitative
assessment of the macrohabitat complexity from
which the invertebrate samples were collected. Pools,
runs and riffles are scored by the characteristics of the
microhabitats’ physical features (substrate composition, depth, water velocity) and biological features
(algal masses, leaf packs, bank vegetation). The habitat available to the macroinvertebrate community is
described by the sum of the scores for each unique macrohabitat sampled.
A timed kick net method (Huggins, 1988) was used to sample the macroinvertebrate community in each
of the macrohabitats scored in the HDI. Samples were preserved in ethanol and rose bengol solution,
which aided in sorting and identifying the collected organisms. Invertebrates were sampled to assess the
biological health of the water bodies and sites associated with each farm or farm management site.
Comparing Habitat Diversity Index scores and invertebrate communities over time and at various sites in
a watershed underscores the role water quality plays in aquatic communities.
12
Statistics and Graphics The Number Cruncher Statistical Software 2000 (Hintze, 2000) was used to manage and analyze water
quality information gathered from the eight monitored farms. Runoff, groundwater and surface water
quality data were organized by farm and sampling date. For the graphical approach to data presentation,
scatter plots and box plots were chosen due to the nature of the collected data (Figure 2). Scatter plots
were used to display discrete sampling events. Samples collected on the same date from multiple sites
or depths are displayed as yellow circles, red triangles and green squares. The box plot shows three
main features about a variable: its center, its spread, and its outliers. The “box” typically appears as a
rectangle divided by a single line, which represents the median (most often occurring) value. The lower
portion of the box is the 25 percent quartile and the upper portion is the 75 percent quartile. The upper
and lower adjacent values (displayed as T-shaped lines that extend from each end of the box) are the 10-
percent and 90-percent value limits respectively. Values outside the upper and lower adjacent values are
called outlier values. They are represented as closed circles. Box plots are often used in comparison
analysis of different sampling locations. For both error bar charts and box plots, concentration data is
usually graphed with a linear vertical scale, though log rhythmic scales were necessary on several
occasions to better illustrate a wider range in concentrations and bacteria counts (Hintze, 2000).
Figure 2: Representative scatter plot and box plot
0.0 1.0 2.0 3.0 4.0 5.0 6.0
Jun 9, 98Jun 12, 98Jul 9, 98Jul 30, 98Sep 9, 98O
ct 19, 98D
ec 9, 98Jun 9, 99Jul 1, 99Jul 14, 99Jul 26, 99N
ov 11, 99D
ec 7, 99M
ay 18, 00Jul 10, 00Jul 17, 00
Total Nitrogen
Con
cent
ratio
n (m
g/L)
Pond123spring
.01
.1
1
10
100
Bartel
How
ell
Peters
Townsend
Total Phosphorus
Con
cent
ratio
n (m
g/L)
13
Herb and Pat Bartel, Marion County Watershed: French Creek, Marion Reservoir Water Quality Concerns: Impacts on Marion
Reservoir from nutrients and herbicides in shallow groundwater and runoff.
Demonstration: Implement a stripped-crop rotation incorporating cover crops to improve soil structure while reducing erosion, fertilizer and chemical use. Promote the conversion of gullies to an intermittent wetland complex to filter water and provide wildlife habitat.
Monitoring: Runoff, groundwater and soils from the crop rotation; surface water, aquatic macroinvertebrates and habitat diversity in the wetland complex. Photo 7: A KBS researcher surveys the soybean and wheat
fields in the stripped-crop rotation before collecting shallow groundwater samples.
The Bartel farm includes 340 acres of cropland and native hay meadows northeast of Hillsboro, KS, adjacent to
Marion Reservoir public land. The Bartels developed a stripped-crop rotation system on an 80-acre tract that
drains into the reservoir. This conversion was undertaken in part to decrease the need for chemical fertilizer
and herbicide applications. Green manures and legumes were incorporated in the rotation plan with soybeans
and wheat. Goals of the change in land management were to decrease soil loss by the erosive effects of runoff
and to reduce the nutrient and herbicide load in runoff and groundwater draining from the farm to Marion
Reservoir. Runoff, groundwater and soil samples were collected from the field to characterize existing
conditions and monitor trends and changes in water quality.
Another management decision that addressed water quality on the farm involved repairing field gullies by
converting them to a series of wetland pools in the midst of a native hay meadow. These gullies were formed
by a neighboring farm’s runoff flowing through a culvert under a road onto the Bartel’s fields. Gullies were
widened and deepened; excavated soil and transplanted dogwood and maple shoots were used to trap
sediment and slow the velocity of water flowing through the pools. Prairie hay meadows around the pools were
kept out of the crop rotation and acted as buffer zones between crop ground and the wetland area. Native
wetland plants including many obligate wetland species became established along the margins of the pools
and channel reaches that retained adequate water over the growing season. Water samples were periodically
collected from the developing wetland to identify the effects the conversion had on water quality. Habitat,
vegetation and aquatic invertebrate surveys were conducted to track the wetland’s physical and biological
development throughout the monitoring project.
Soil Characteristics of the Monitored Field The monitored field is moderately sloped and drains directly into the Marion Reservoir. Soils found in the field
are classified in the Rosehill and Irwin Series. These soils are deep, well drained and very slowly permeable.
They form in residuum of clayey shale and are slightly acidic. Soil samples were taken annually from the top
ten centimeters at three locations in the field to account for local variation in soil chemistry. Results of the soil
14
analyses indicated annual fluctuations in nitrogen, phosphorus and carbon levels. Field applications and cover
crops noticeably impacted soil chemistry and structure. The lowest nitrogen and phosphorus levels occurred in
1999 after the clover green manure crop planted in 1998 failed. Though Austrian field peas were planted later
in 1998, the soil-building process was interrupted and nutrient levels reacted accordingly. Without the nitrogen
fixing ability of the legume cover crops, nitrate (NO3) levels decreased. Dissolved organic carbon levels and
phosphate levels increased the first three years of sampling. The more pronounced increases in 1998
coincided with one of several partial field applications of dairy bedding, manure and silt from the gully
conversion project. Aggregate stability generally increased except when the clover crop failed. With the soil
exposed longer than under normal circumstances, soil particles were less able to bind together after tilling.
However, aggregate stability increased in 1999 after a successful spring wheat crop. Nitrogen and
phosphorus levels rebounded in 2000, with both nutrients reaching the highest recorded levels. Field
applications may have influenced the nutrient data.
Table 6: Soil quality indicators and chemistry from the Bartel’s strip-cropped field. Parameter 1996 1997 1998 1999 2000 Mean
Crop soybeans soybeans peas/wheat wheat/clover clover Total Kjeldahl N (mg Org N+NH3/kg soil) 1415 1314 1240 810 1777 1311 Nitrate (mg NO3/kg soil) 30 35 22 - - 29 Total P (mg P/kg soil) 353 341 363 275 471 361 Phosphate (mg PO4/kg soil) 24 35 84 - - 48 Dissolved Organic C (mg C/kg soil) 91 92 111 - - 98 pH 6.27 6.65 6.51 - - 6.48 Aggregate Stability % 89 90 80 99 97 91 Monitoring Runoff on the Stripped-crop Rotation Field Runoff samplers were installed at two locations in the field in September 1996 (Figure 3). The upper sampler
collected runoff as it flowed downhill to a small retention area behind a pile of timber from a felled hedgerow.
The lower sampler collected runoff as it exited the field to a county ditch leading to Marion Reservoir.
Decomposing dairy bedding (straw and manure) was applied to some areas of the field in fall 1998 to address
rill erosion and increase local fertility. These applications increased nutrient concentrations and effectively
obscured the continuing effects of field management practices that might have led to continued improvements
in runoff and groundwater quality after 1998. Samples were collected seven times at the upper site and
thirteen times at the lower site between 1996 and 2000. Rodent damage to the sampler intake hoses and
computer programming errors prevented sample collection at the upper site in 1998. Though not all runoff
events were sampled, the collected samples were sufficient to characterize seasonal and management-based
changes in water quality.
At the upper sampling site, total nitrogen (TN) concentrations fluctuated noticeably. Several trends were
apparent. Nitrogen levels were generally higher during the growing season. Rainfall patterns influenced
concentrations but were not the primary trend-determining factor. The principal nitrogen component was nitrate
(NO3), which ranged from 0.30 to 6.64 mg/L. The two highest NO3 values occurred in years when 40 lbs/acre
of nitrogen fertilizer were applied to a wheat crop that followed soybeans in the crop rotation. Wheat following
15
16
Figure 3: Sampling sites and field perimeter on the Bartel farm, Marion County, KS.
cover crops did not receive nitrogen applications. Organic nitrogen (Org N) values were consistently between
0.94 and 2.04 mg/L. Organic nitrogen analyses were not conducted for the first two sampling events.
Ammonia (NH3) concentrations decreased substantially over the course of the monitoring project. This could
be in part due to the crop rotation using legumes and cover crops and the elimination of nitrogen fertilizer
applications after wheat followed cover crops in the rotation.
Phosphorus concentrations at the upper sampling site were influenced by the dairy bedding applications.
These were largely downfield of the sampler, but some spot applications upfield were sources of phosphorus in
runoff. Total phosphorus (TP) concentrations from the first few sample sets in 1997 were below 0.40 mg/L, but
levels increased noticeably to a mean value of 2.35 mg/L by the final sample set of 2000. Phosphate (PO4)
levels increased from 0.13 to 1.97 mg/L, and organic phosphorus (Org P) levels remained consistent near 0.24
mg/L. Runoff from the last sample set was generated by a stronger storm than other sample sets, which likely
increased TP concentrations by mobilizing more PO4.
First flush runoff concentrations for the herbicides atrazine and metolachlor were relatively low. Neither
herbicide was applied to the fields during the monitoring project, and the highest levels of atrazine and
metolachlor of 0.72 ug/L and 0.60 ug/L respectively were recorded for the last sample set. Spring applications
for corn and sorghum production in the watershed were ongoing around the sampling date, and off-site runoff
likely transported dissolved and bound herbicides onto the Bartel’s fields during this relatively stronger storm.
Atrazine levels were always less than the HUC unit average of 1.54 ug/L.
Table 7: Mean* nutrient and herbicide concentrations in first flush runoff at Bartel’s upper site. Sampling Date Rain TN Org N NO3 NH3 TP Org P PO4 Atrazine Metolachlor Oct 29, 96 0.5 - - 3.91 2.98 - - 0.18 0.01 0.01 Nov 16, 96 0.9 - - 6.64 2.07 - - 0.29 0.01 0.01 Jun 23, 97 0.5 4.26 2.04 2.05 0.17 0.37 0.24 0.13 0.31 0.14 Jul 29, 97 0.7 7.27 0.94 6.27 0.05 0.33 0.10 0.22 0.14 0.04 Fall 98 Dairy bedding, manure and silt applied both above and below the sampler. Jul 17, 99 1.5 3.63 1.77 2.29 0.06 0.46 0.22 0.24 0.08 0.04 Sep 14, 99 0.9 1.94 1.44 0.30 0.20 1.42 0.22 1.20 0.06 0.01 May 26, 00 2.4 6.46 1.82 4.51 0.28 2.35 0.39 1.97 0.72 0.60 Site Mean Value 4.80 1.62 3.65 0.76 1.00 0.24 0.63 0.22 0.16 Site Median Value 5.92 1.45 2.89 0.19 0.43 0.21 0.22 0.09 0.04 HUC 8 Watershed Average1 - - 0.90 0.09 0.17 - - 1.54 - Kansas Statewide Average1 - - 1.02 0.11 0.26 - - 1.12 - Units: Rain = Inches in 48 hours prior to sampling, (TN, Org N, NO3, NH3, TP, Org P, PO4) = mg/L, Atrazine and Metolachlor = ug/L. * = Average of eight samples collected during the initial three-hour first flush runoff conditions. 1 = Values obtained from Appendix B, Kansas Nonpoint Source Pollution Management Plan – 2000 Update (KDHE 2000).
At the lower sampling site, variations and patterns in nitrogen and phosphorus concentrations in runoff were
primarily a function of rainfall and the field applications. The highest values came from heavier rains during the
growing season after the compost was applied at multiple sites in the field. Before the dairy bedding was
spread between the two sample sites, TN concentrations were similar to those at the upper site. Mean TN
values ranged from 0.31 to 5.51 mg/L, and typical levels fluctuated around 5.0 mg/L. Organic nitrogen
concentrations were higher than NO3 during the growing season, while NO3 was more prevalent than Org N
during the fall and winter when nitrogen fertilizer was applied to strips of wheat following soybeans in the crop
17
Photo 9: Dairy bedding applications increased nutrients available for local transport via runoff and groundwater.
Photo 8: Composted dairy bedding was applied to areas in the monitored strip-cropped field on the Bartel farm.
rotation. Ammonia levels decreased as liquid nitrogen fertilizer applications were gradually phased out. After
the dairy bedding applications, TN concentrations steadily increased to a high of 35.31 mg/L. Increases in
NO3, Org N and NH3 were observed. Post-application levels of NO3 ranged from 2.29 to 19.78 mg/L. Organic
nitrogen ranged from 9.08 to 13.07 mg/L and NH3 from 0.07 to 2.46 mg/L.
Trends in phosphorus concentrations further indicated that the dairy bedding applications increased the
availability of nutrients for transport off-site by runoff. Total phosphorus (TP) concentrations ranged from 0.2 to
1.5 mg/L before the application. These values were slightly higher than those from the same time span at the
upper sampler. Concentrations steadily increased to a high of 10.3 mg/L after the applications. Phosphate
was the dominant constituent, ranging from 1.7 to 6.9 mg/L. Organic phosphorus amounts also increased as
the dairy bedding decomposed further. The decision to use applications of dairy bedding on the field likely
increased productivity in the long term by healing over eroded areas and stimulating growth and ground cover
on less productive patches. The short-term water quality trade-off was an increased amount of organic and
inorganic nitrogen and phosphorus compounds in runoff draining from the strip-cropped fields.
Atrazine was not applied on the fields during the course of this study, but low levels of herbicides were detected
in runoff from both sampling sites. Concentrations were higher in runoff generated by more intense storms, but
levels did not approach the HUC 8 watershed average of 1.54 ug/L. Atrazine has been reported to have a half-
life of 60 to more than 100 days but no annual buildup or carry over effects (Craigmill, 1997). Research on
volatilization and atmospheric deposition of atrazine has indicated that this phenomenon is responsible for
small ambient levels of the herbicide. In all likelihood the monitored drainages were not totally isolated from the
effects of off-site runoff transporting nutrients, herbicides and sediment onto the Bartel farm.
18
Table 8: Mean* nutrient and herbicide concentrations in first flush runoff at Bartel’s lower site. Sampling Date Rain TN Org N NO3 NH3 TP Org P PO4 Atrazine Metolachlor Nov 16, 96 2.50 - - 5.10 0.74 - - 0.21 0.01 0.01 Jun 23, 97 3.10 4.14 2.83 1.18 0.13 1.45 1.20 0.26 0.28 0.17 Sep 24, 98 0.70 4.86 3.16 1.56 0.14 1.23 0.95 0.28 0.03 0.01 Oct 2, 98 1.50 3.86 1.60 2.22 0.04 0.74 0.11 0.64 0.03 0.01 Oct 31, 98 0.90 5.51 1.68 3.70 0.13 0.92 0.10 0.82 0.01 0.01 Nov 10, 98 2.40 0.31 - - - 0.18 - - 0.01 0.01
Fall 98 Dairy bedding, manure and silt applications above and below the sampler. Jun 18, 99 1.60 9.83 - - - 1.22 - - 0.75 0.50 Jul 16, 99 1.90 13.44 9.08 2.29 0.20 2.82 1.05 1.77 0.30 0.10 Sep 14, 99 1.70 22.06 7.45 14.54 0.07 3.39 0.41 2.98 0.01 0.01 Nov 22, 99 2.40 19.53 - - - 3.58 - - 0.18 0.01 May 26, 00 1.60 35.31 13.07 19.78 2.46 10.28 3.37 6.91 0.47 0.29 Jun 13, 00 0.90 20.67 - - - 4.71 - - 0.47 0.15 Jul 19, 00 0.80 35.09 - - - 7.98 - - 0.13 0.03 Pre-application Mean Value 3.26 2.52 1.95 0.15 0.88 0.76 0.38 0.11 0.17 Post-application Mean Value 22.28 9.87 12.83 0.91 4.86 1.61 3.87 0.39 0.22 Site Mean Value 15.10 6.27 7.28 0.25 3.28 1.21 2.10 0.33 0.21 Site Median Value 9.73 4.29 3.08 0.10 2.43 0.70 0.88 0.21 0.12 HUC 8 Watershed Average1 - - 0.90 0.09 0.17 - - 1.54 - Kansas Statewide Average1 - - 1.02 0.11 0.26 - - 1.12 - Units: Rain = Inches in 48 hours prior to sampling, (TN, Org N, NO3, NH3, TP, Org P, PO4) = mg/L, Atrazine and Metolachlor = ug/L. * = Average of eight samples collected during the initial three-hour first flush runoff conditions. 1 = Values obtained from Appendix B, Kansas Nonpoint Source Pollution Management Plan – 2000 Update (KDHE 2000).
Runoff Case Study Additional runoff grab samples were collected on December 8, 1999, two days after ammonia fertilizer was
applied at a rate of 40 lbs/acre to a recently purchased 80-acre parcel adjacent to the field with the stripped-
crop rotation (Figure 3). More than 1.6 inches of snow fell then melted during the 48 hours prior to sampling.
Samples were collected at three sites. Sites 1 and 2 were located near the lower runoff sampler in the
stripped-crop rotation field, and Site 3 was located in the adjacent field where the chemical fertilizer was
applied.
Site 3 had higher concentrations of TN, NO3, NH3 and atrazine than Sites 1 and 2. Nitrate and NH3 levels were
more than twice the concentration of the other samples from the crop rotation (Table 9). Organic nitrogen
levels were consistent among sites. The concentrations of NH3 and atrazine were nearly ten times higher in
runoff from the fertilized field than in runoff from the two sites in the crop rotation. Conversely, phosphorus
compounds were ten times higher in runoff from the crop rotation field with the applications of dairy bedding.
Assuming that both fertility strategies satisfied crop needs, it is clear that the commercial application of nitrogen
fertilizer a few days before an average winter storm led to significant losses of nitrates and ammonia via runoff.
Direct applications of decomposing dairy bedding led to increases in phosphorus compounds in runoff. This
case study indicates the importance of the timeliness of fertilizer applications in managing nonpoint source
pollution. It also reinforces the idea of realizing the intended and unintended side effects of chemical and
organic fertilizers when making fertility management decisions.
19
Table 9: Water quality of runoff from two fields with two different fertility management strategies. Site Management TN Org N NO3 NH3 TP Org P PO4 Atrazine Metolachlor
1 Crop rotation 2.35 1.30 1.02 0.03 1.72 0.04 1.68 0.09 0.01
2 Crop rotation 2.25 1.70 0.52 0.03 1.89 0.23 1.66 0.04 0.01
3 Nitrogen Addition 5.48 1.39 3.82 0.27 0.12 0.01 0.11 0.48 0.01
Units: (TN, Org N, NO3, NH3, TP, Org P, PO4) = mg/L, Atrazine and Metolachlor = ug/L
Groundwater Shallow groundwater was collected from 1996 to 2000 at three sites in the crop rotation field by lysimeters at
depths of one, four and eight feet. Clusters of lysimeters were placed near the upper and lower runoff
samplers, and the third cluster was located between the runoff samplers in the middle of the monitored field
(Figure 3). An impermeable soil layer just above the eight-foot depth made it necessary to raise the sampling
depth slightly, but sampling at the eight-foot depth was largely successful. Most of the collected groundwater
came from the four- and eight-foot lysimeters. Either the one-foot lysimeters did not retain the vacuum long
enough to collect groundwater or little if any soil water was left for sampling after plant and microbial uptake.
The lower site had saturated soil conditions more frequently than the upper site and middle sites, so more
samples from the one-foot lysimeter were available there. Lysimeters at the middle site were more subject to
damage from rodents and farm machinery and had to be replaced several times. Successful sampling at the
middle site was infrequent, and results are not graphed individually. Groundwater samples were collected
independent of runoff events, though any substantial rainfall received several days prior to groundwater
sampling likely mobilized and leached some soluble nutrients down in to the soil column. Raw concentration
data is presented in Appendix A.
Nutrient concentrations at the upper sampling site showed trends by sampling depth and over time, evidenced
by the TN data. One-foot sample collection was sporadic; the few samples had generally consistent
concentrations around 2.0 mg/L. At four feet, TN concentrations initially decreased and then leveled off around
0.7 mg/L. This trend was likely a function of the decreasing dependence on chemical fertilizer applications on
the field. A strong temporal trend was evident at eight feet, where TN concentrations decreased by over 50%
from 1997 to 2000. A strong decreasing trend in ammonia concentrations was also apparent. Rainfall did not
appear to noticeably affect TN concentrations at the upper sampling site.
Total phosphorus data also reflected trends by sample depth and over time. As expected, TP concentrations
were highest at the one-foot sampling depth and decreased as sampling depth increased. Organic phosphorus
levels were consistently lower than 0.03 mg/L at all sampling depths. Fluctuations in the more soluble PO4
were more responsible for changes in concentration over time. Total phosphorus values decreased slightly at
one foot, but not enough samples were collected at that depth for temporal trend analysis. Values at four and
eight feet ranged between 0.01 and 0.20 mg/L. Rainfall apparently affected TP levels more than it did TN.
Phosphate levels increased noticeably when more than 1.2 inches of rain fell in the 48 hours before samples
were collected on June 14, 1997 and September 7, 1999. Despite this noticeable increase in PO4, a downward
trend in TP concentration was apparent at the four-foot sampling depth. The trend was not as strong at eight
20
feet. Concentrations at eight feet appeared to decrease initially but rebounded slightly. The influences of
precipitation and seasonal differences in nutrient availability accounted for most of the observed slight variation
in TP concentrations over time and sampling depth.
Figure 4: Nutrient concentrations in groundwater at the upper sampling site.
0.0
0.5
1.0
1.5
2.0
2.5
Jul 19, 96Jun 14, 97Aug 7, 97Jul 22, 98Aug 4, 98D
ec 2, 98Jul 15, 99Sep 7, 99D
ec 8, 99M
ay 13, 00Jul 19, 00
Total Nitrogen
Con
cent
ratio
n (m
g/L)
Depth (ft)148
0.0
0.1
0.2
0.3
0.4
0.5
Jul 19, 96
Jun 14, 97
Aug 7, 97
Jul 22, 98
Aug 4, 98
Dec 2, 98
Jul 15, 99
Sep 7, 99
Dec 8, 99
May 13, 00
Jul 19, 00
Total Phosphorus
Depth (ft)
Con
cent
ratio
n (m
g/L)
148
Total nitrogen levels increased noticeably from the upper to lower cluster. Concentrations at the lower cluster
increased between five to one hundred times the corresponding amount at the upper cluster. The applications
to the field below the upper sampler are the likely explanation for this dramatic difference in concentrations.
Several early one-foot samples did not have organic nitrogen analyses carried out, but the nitrate
concentrations in one-foot samples were recorded at 107.0 mg/L (not graphed for scalar purposes) and
decreased substantially to less than 10 mg/L. A larger sample set could have validated this trend further, but
samples from one-foot were not collected as frequently as the other sample depths. Values at four feet were
also very high initially at 69.8 mg/L but decreased by over 95% at the project’s end. A less-permeable soil
layer could have prevented further downward leaching of nutrients and increased concentrations at the four
and eight-foot sampling depths. Eight-foot values did not vary as much relative to the other sampling depths
but steadily increased from 9.6 to 19.5 mg/L. Saturated soil conditions likely promoted the downward leaching
of nitrate in the soil column. This type of nutrient enrichment has been observed in other studies involving field
applications of livestock waste (Klausner et al, 1976). Concentrations of ammonia were similar between sites
and exhibited several trends over the course of the monitoring project. Usually the upper site had higher
concentrations of ammonia than the lower site. Differences were most pronounced at eight feet. The range of
values for both sites was 0.01 to 0.28 mg/L. At the upper sampler, concentrations decreased significantly at
both four and eight feet after initially high levels. Not enough one-foot data was collected for trend analysis.
Similar decreases were noted at the lower cluster, though the trend was not as strong. This decreasing trend is
similar to the trend in runoff ammonia concentrations and lends weight to the hypothesis that ammonia levels in
runoff and groundwater decreased as liquid nitrogen fertilizer applications were reduced.
Unlike the nitrogen data, TP concentrations at the lower sampler were in the same range as those from the
upper sampler. Values ranged from 0.02 to 0.40 mg/L. Rainfall in the 48 hours prior to sample collection likely
21
increased the TP concentrations at multiple depths on several sampling dates. Samples from dates
unaffected by precipitation usually had values less than 0.15 mg/L. The depth-based trend was again
apparent, with one-foot samples having the highest values and eight-foot samples the lowest. This was
expected, as organic and inorganic phosphorus often bind with sediment and do not leach as readily as some
of the nitrogen compounds do. Phosphate levels were noticeably higher at one foot and relatively similar
between four and eight feet. Levels of organic phosphorus were consistently below 0.03 mg/L and decreased
even further at eight feet.
Trace amounts of the herbicides atrazine and metolachlor were periodically found in groundwater samples.
The highest value of 0.84 ug/L was collected from the one-foot lysimeter in the upper cluster on June 14, 1997.
Over 1.2 inches of rain fell during the 48 hours prior to sampling. The vast majority of samples at all three sites
had levels below the minimum detection limit of 0.02 ug/L. These low values indicate that groundwater
contamination by herbicides was not occurring at these sites on the Bartel farm.
Figure 5: Nutrient concentrations in groundwater at the lower sampling site.
0.0
16.0
32.0
48.0
64.0
80.0
Jul 19, 96 Jun 14, 97 Aug 7, 97 Jul 22, 98 Aug 4, 98 D
ec 2, 98 Jul 15, 99 Sep 7, 99 D
ec 8, 99 M
ay 13, 00 Jul 19, 00
Total Nitrogen
Feet
Con
cent
ratio
n (m
g/L)
148
0.0
0.1
0.2
0.3
0.4
0.5
Jul 19, 96 Jun 14, 97 Aug 7, 97 Jul 22, 98 Aug 4, 98 D
ec 2, 98 Jul 15, 99 Sep 7, 99 D
ec 8, 99 M
ay 13, 00 Jul 19, 00
Total Phosphorus
Feet
Con
cent
ratio
n (m
g/L)
148
Monitoring the Development of the Wetland The Bartels promoted the conversion of the gullies to a series of wetland pools to address gully erosion from
off-site runoff while enhancing local wildlife habitat and water quality. The wetland pools were formed by
widening and then damming gullies with limbs and earth. Three of the pools were monitored to track the
physical development of the wetland, identify changes in water chemistry as it flowed through the system, and
evaluate the biological integrity of the developing wetland. In addition to water quality analyses for nutrients
and herbicides, wetland vegetation was inventoried and aquatic macroinvertebrates were collected. Areas of
active erosion were periodically checked to determine if runoff was being channeled through the wetland or
scouring new gullies. A measure of the complexity of the in-stream habitat, the Habitat Diversity Index (HDI),
was calculated at each site three times to compare the pools’ habitats and their influences on the local aquatic
macroinvertebrate community.
22
Water Chemistry Water samples were collected from three intermittent wetland pools on six separate occasions during the study
period from 1996 to 2000 (Figure 6). The maximum depth and volume of water in the pools varied over the
growing season; pools were shallower in late summer when runoff events were less frequent than during the
spring. The pools were excavated to a depth where groundwater recharge kept at least a small volume of
water in the pools over most of the year. Grab samples were taken just below the water surface of the pool as
far out as possible without disturbing the pool. Attempts were made to collect samples that represented
different seasons and precipitation patterns. Water chemistry data for the wetland is located in Appendix A.
Figure 6: Spatial relationships between points where runoff enters and exits fields and wetland pools.
Concentrations of nutrients and herbicides in the samples
function of rainfall (Figure 7). Runoff events occurred befo
dates. This served to bring additional nutrients and herbicid
higher concentrations were detected in samples taken at th
were more commonplace and nutrients were mobilized by bio
Total nitrogen levels did not fluctuate much between the thr
for the later sampling dates. This may result from the matur
time. The higher values occurred when storms sent on-site
pools a few days before sampling. Excluding these two
decrease at all sites over the course of the monitoring pr
influenced by inputs from runoff were less than 2.1 mg/L.
been related to seasonal changes in population densities of t
Total phosphorus concentrations followed a similar trend, w
runoff events. Typical values ranged between 0.06 mg/L to
mg/L. Disregarding data from the two runoff-impacted sam
Photo 10: Runoff entering a field through a road culvert is a source of gully erosion on agricultural fields.
wetland pools fluctuated between sites and as a
re the June 14, 1997 and June 3, 1999 sampling
es into the wetland pools. As would be expected,
e start of the growing season when rain showers
logical processes.
ee sites but tended to decrease in the lower sites
ation and stabilization of the wetland system over
and off-site NO3 - and NH3 -laden runoff into the
events, both NO3 and NH3 levels appeared to
oject. Typical TN values on sampling dates not
Slight fluctuations between sites may also have
he local algal community.
ith higher values appearing in June samples after
0.30 mg/L, with the highest value reaching 0.53
pling dates, TP levels were below 0.3 mg/L and
23
seemed to decrease slightly over the course of the monitoring project. Peak values at the upper and middle
sites (Sites 1 and 2) corresponded to increases in PO4 while the maximum observed TP concentration at the
lower site (Site 3) was due to increased Org P.
Atrazine was graphed using a log scale on the vertical axis to better accommodate the seasonal fluctuations in
water chemistry data. Concentrations ranged between 0.02 and 69.4 ug/L. The highest concentrations
occurred on the two dates after spring storms produced runoff that transported atrazine to the pools. Spatially,
concentrations were typically lower at the most downstream site (Site 3, Figure 6), which suggests that atrazine
was either metabolized or became incorporated in the soils or biota of the wetland systems as this herbicide
traveled through the drainage system. This point is strengthened by data from the spring rain-influenced
samples on Jun 14, 1997. Atrazine levels decreased by over 50% between Sites 1 and 2 and by over 99%
between the Sites 1 and 3 over the course of the monitoring project. The effects on atrazine levels by this
wetland complex may help reduce atrazine levels in Marion Reservoir.
Figure 7: Nutrients and herbicides in three developing wetland sites on the Bartel farm.
0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0
Jul 19, 96
Jun 14, 97
Dec 2, 98
Jun 3, 99
Aug 4, 99
May 22, 00
Total Nitrogen
Con
cent
ratio
n (m
g/L)
123
0.0
0.2
0.4
0.6
0.8
1.0
Jul 19, 96
Jun 14, 97
Dec 2, 98
Jun 3, 99
Aug 4, 99
May 22, 00
Total Phosphorus
Con
cent
ratio
n (m
g/L)
1 2 3
0.01
0.1
1
10
100
Jun 19, 96
Jun 14, 97
Dec 2, 98
Jun 3, 99
Aug 4, 99
May 22, 00
Atrazine
Con
cent
ratio
n (u
g/L)
123
24
Wetland Vegetation Wetland vegetation samples were collected on two occasions near the three pools in the wetland complex.
Five cross-channel transects were established at each of the three sites, and vegetation was classified as
dominant (D) or sub-dominant (SD). Dominance was subjectively determined from visual estimates of percent
occurrence along each transect line. Sub-dominant taxa were included when appropriate (i.e. percent
occurrence estimates were 0 to 20% less than the value for the dominant taxa). Using the Wetland Indicator
Status (WIS) approach (Monda 1993), obligate wetland (Obl) species usually (>99%) occur in wetlands under
natural conditions. Facultative wetland (FacW) species usually occur in wetlands (67% to 99%) but are
occasionally found in non-wetlands. Facultative (Fac) species are equally likely to occur in wetlands or
nonwetlands (34% to 66%), with species marked (Fac+) occurring more frequently in wetlands and those
marked (FacU) found occasionally in wetlands (1% to 33%). Those species indicated as NI (Not Inventoried)
are not listed in the National Wetlands Inventory and are thus not considered as wetland species. A complete
list of the dominant and subdominant plants is found in Appendix A.
The percent of obligate wetland species compared to all dominant/sub-dominant wetland indicator plants
collected at each site was used as a simple indicator of the site’s wetland nature. Higher percent occurrences
of obligate wetland plant species along the five transects characterizing the sites was suggestive of the wetland
nature of the general site area along the intermittent stream course. Based on this simple index, in 1997 it was
clear that the upper most site had limited wetland features with only 25 percent of the wetland plant indicators
being obligate species compared to the wetter downstream sites (both have 100% obligate species). In 1999,
the percent of obligate wetland species decreased among all sites. At the upper most site the percent obligate
species was 21%, while the middle site was composed of 49% obligates and the bottom-most site was mostly
obligate species (63%). Bartel’s efforts to enhance the wetland nature of these pool sites to increase this
stream channel’s potential to treat water flowing through it and to increase wetland habitat appeared to be
effective. Concurrent increases in the number of wetland species in the lower sites with reductions in herbicide
levels are indicative of the value of small-scale wetland enhancement efforts.
Habitat Diversity Index (HDI) and Macroinvertebrate Samples The Habitat Diversity Index was calculated seven times between 1996 and 2000 at the three pools in the
developing wetland. As expected, higher cumulative scores were calculated during the growing season
and after several years of conversion. The difference between scores was due primarily to increases in
established macrophytes, bank vegetation and organic detritus and debris. The increasing scores of the
HDI over time are also evidence that the enlarged pool environments were becoming more complex and
developing wetland features (i.e. obligate wetland plants). In addition to enhanced habitat for aquatic
species, the Bartels noticed an increased presence of deer and ground nesting birds that depended
heavily on the wetland during dry periods. The macroinvertebrate community was sampled in conjunction
with the HDI calculation. The one-minute timed kick-net method (Huggins and Moffet 1988) was used to
sample invertebrates at each macrohabitat included in the HDI score. The samples were very typical of
25
the invertebrate fauna associated with ephemeral wetlands. In fact, several present taxa including the
dragonflies and damselflies require one year to complete their life cycle, suggesting that some wetland
areas retained water throughout the year. Table 10: Aquatic macroinvertebrates found in the Bartel wetland. Common Name and Order Group Common Name and Order Group Order Ephemeroptera: Mayflies 1 Order Diptera: Craneflies 2 Caenis Limonia Callibaetis Tipula Order Odonata: Dragonflies 2 Limnophora Anax Order Decopoda: Crayfish 2 Libellela Cambaridae Plathemis Order Mollusca: Gastropd Snails 2 Order Odonata: Damselflies 2 Ancylidae Ischnura Lymnaeidae Lestes Physidae Order Heteroptera: Water Striders 2 Order Diptera: Mosquitoes 3 Gerris Culex Order Hemiptera: Water Boatmen 2 Anopheles Ramphocorixa Order Diptera: Biting Midges 3 Sigara Cbezzia Trichocorixa Dixella Order Hemiptera: Backswimmer 2 Culicoides Mesovelia Dasyhela Order Coleoptera: Beetles 2 Order Diptera: Midges 3 Agabus Chaoborus Copelatus Chronimidae Dytiscus Order Diptera: Flies 3 Hydroporus Limnophora Hygrotus Notophila Laccophilus Tetanocera Peltodytes Diptera Tropisternus Tabanus Berosus Pericoma Cyphonb Odontomyia Enochru7s Dolichopus Haliplus Tabanus Helophorus Order Clitellata: Aquatic Worms 3 Hydrobiomorpha Branchiobdellida Hydrobius Oligochae Order Megaloptera: Fish Flies 2 Chauliodes Corydalus Group 1 Taxa: Pollutant-sensitive organisms found in good quality water (USDA, 1998). Group 2 Taxa: Somewhat pollutant-tolerant organisms can be in good or fair quality water. Group 3 Taxa: Pollutant-tolerant organisms that can be found in any quality of water.
26
Discussions and Conclusions Monitoring the Bartel’s strip crop rotation and wetland was both challenging and rewarding. The high level of
personal involvement from the Bartels contributed to the overall success of the monitoring project. Soil building
aspects of the strip crop rotation were observed. Residue management and cover crops resulted in an
increase in aggregate stability, which indicates increased water holding capacity and better soil tilth.
Determining the effects of the strip crop rotation itself on nutrient levels was effectively masked by field
applications, and the data illustrated several important points. Runoff collected at the upper site was less
impacted by the applications and had water chemistry similar to other farms in the study. Total nitrogen and
total phosphorus concentrations in runoff increased substantially at the lower sampling site after the
applications. Either incorporating field applications of dairy bedding and manure to increase the rate of
decomposition, or physically containing runoff on-site could have reduced the amount of nutrients leaving the
site via runoff. Quickly establishing vegetation on areas with field applications could help reduce the amount of
nutrients that are mobilized and transported through runoff and those that could leach down through the soil
column to the groundwater.
Total nitrogen levels in shallow groundwater at the lower sampling site were higher than sites at other
monitored farms. Soluble NO3 was the primary nitrogen constituent in the shallow groundwater. The field’s
location near the Marion Reservoir was likely responsible for increased downward leaching potential for soluble
nutrients. Despite the apparent heavy contribution of nitrogen constituents from the monitored field to the
reservoir via subsurface flow, it is unlikely that the groundwater contributed greatly to algae problems in the
reservoir. Algae communities in inland surface waters are limited by the amount of phosphorus available for
uptake, and little phosphorus was exported from the monitored field via groundwater. Phosphorus constituents
tend to bind with soil particles and therefore don’t move down the soil column as readily as nitrogen
constituents can. Total phosphorus concentrations at both groundwater sampling sites were similar to TP
concentrations in groundwater on other farms monitored by KBS. When samples were collected by the one-
foot lysimeters, TP concentrations were higher than in concurrent samples from four-foot and eight-foot
lysimeters. Herbicides were virtually undetected in groundwater samples from the Bartel farm.
The gully restoration was quite successful in achieving its established goals. Maintaining the wetland and
surrounding prairie hay meadow addressed the Bartel’s erosion problem, increased local habitat diversity for
wildlife and provided a mechanism for positively impacting water quality as water moved through and exited the
system. This wetland appeared to be effective at removing atrazine from water before it went into Marion
Reservoir. The Bartels did not need to take land out of production or create concrete structures to address
their erosion problem. Instead, they used innovative ideas and common sense to restore and enhance their
part of the agricultural landscape.
27
Bruce and Cheryl Spare, Saline County Watershed: Smoky Hill River Water Quality Concerns: Erosion of
highly erodible cropland. Runoff carrying excess nutrients and herbicides from cropland into intermittent stream.
Demonstration: Convert cropland to perennial grass and legume cover and implement a management intensive grazing system.
Monitoring: Runoff, groundwater and soils in the converted cropland.
Photo 11:Installing a runoff sampler in the converted field on the Spare farm.
On the Spare farm, a management
transition from conventional rowcrops to
cool-season grasses and legume cover has been ongoing since 1995. The farm included 900 acres of
cropland, native grasses and managed pastures southeast of Assaria, KS. The Spare’s Clean Water
Farms demonstration involved an eighty-acre tract of predominantly highly erodible land (HEL) crossed
by an intermittent stream. The Spares were concerned about soil erosion and runoff removing nutrients,
herbicides and sediment from the land. To keep the land in production while reducing runoff and erosion,
the eighty-acre tract was converted from wheat and sorghum rowcrops to managed grassland, and a
management intensive grazing (MIG) system was established. A combination of fescue, alfalfa and vetch
was seeded in fall of 1995. Two wells for an innovative watering system were dug during the winter of
1995-96. Portable high-tensile steel fencing was used to divide the converted land into 36 grazing
paddocks. Fescue was reseeded in fall 1996 after the initial stand did not establish well. The topography
and water availability affected forage diversity in several areas. The wetter lowlands near the intermittent
creek were dominated by the fescue, while the uplands and slopes had more abundant legumes.
The goal of this conversion was to keep the highly erodible land in production while reducing the
economic costs associated with chemical fertilizers, herbicide applications and farm machinery rentals
and the environmental costs of nonpoint source pollution. The Kansas Biological Survey designed the
monitoring program on the Spare farm to provide data on changes in runoff and groundwater chemistry
and to identify trends that might relate water quality to the change in land use and land cover from
rowcrops to grasses and legumes. The monitoring program was established in 1996 and included the
sampling of soils, field runoff and shallow groundwater.
28
Soil Characteristics of the Converted Field The monitored eighty-acre tract of highly erodible land encompasses a moderately sloping upland ridge
and accompanying side slopes that drains to the intermittent creek and eventually to the Smoky Hill River.
Soils in the converted field are classified as Crete and Longford silt loams, which are deep and well-
drained soils found on side slopes of ridges dissected by small drainages. Crete soils, formed in
alluvium, are found in the lowlands in the floodplain, while Longford soils result from loess deposits and
are located in the uplands (Palmer et al, 1992). Soil samples were collected from three locations within a
fescue-dominated grazing paddock in the floodplain of the intermittent creek. Results of the soil sample
analyses indicated slight annual variations in nitrogen and phosphorus levels. Total nitrogen and total
phosphorus levels increased consistently for the first three years before both decreased sharply in 1999.
Levels then rebounded in 2000. Carbon levels increased the first three years of monitoring, and the
aggregate stability percentage increased consistently over the course of the project. This particular trend
in aggregate stability is indicative of increased resistance to erosion, hummus development in the soil,
and a greater soil moisture retention capacity. Similar increases in aggregate stability were found in soils
on other farms monitored by KBS that converted cropland to cool season grasses and legumes.
Table 11: Soil quality indicators and chemistry from the Spare’s converted field. Parameter 1996 1997 1998 1999 2000 Mean Total Kjehldahl N (mg Org N+NH3/kg soil) 1723 2110 2213 1088 1992 1825 Nitrate (mg NO3/kg soil) 38 57 19 - - 38 Total P (mg P/kg soil) 359 392 456 302 435 389 Phosphate (mg PO4/kg soil) 33 28 73 - - 45 Dissolved Organic C (mg C/kg soil) 152 169 226 - - 182 pH 5.89 5.25 6.06 - - 5.73 Aggregate Stability % 80 82 83 94 99 88 Monitoring Runoff in the Converted Field The runoff sampler was positioned to collect water as it flowed through the managed grass and legume
paddocks to the intermittent stream (Figure 8). The studied drainage was topographically isolated, so
runoff contributions from neighboring fields with different land cover management plans were originally
thought to be limited. Runoff from upstream conventional rowcropped fields was the source of the
majority of the water in the intermittent stream. Observed changes in herbicide concentrations over the
first flush period during one sampling event led researchers to believe that the creek had overflowed its
banks and influenced water chemistry in the runoff samples. After this was determined, the sampler was
moved farther inland in spring 1999, but it is possible that at least some of the runoff collected before the
sampler was moved came not from the converted field but from the overflowing intermittent stream.
Runoff samples were collected five times from 1997 to 2000.
Total nitrogen concentrations in runoff fluctuated between 2.86 and 12.69 mg/L (Table 12). These values
are slightly higher than other grazing projects monitored by KBS. Organic nitrogen was the
29
25
Figure 8: Sampling sites and field perimeter on the Spare farm, Saline County, KS.
greater constituent by percentage in the late summer and fall when warm season grasses began
dormancy and the harvesting of rowcrops in the watershed was ongoing. Increases in sediment from
cultivated fields upstream are another possible source for higher levels of Org N. Nitrate levels fluctuated
independently of Org N values and increased with heavier rainfall. Levels of NO3, which is highly soluble,
increased in samples generated by more intense storms on other KBS-monitored farms.
Total phosphorus concentrations were similar to values from other grazing systems monitored by KBS,
ranging between 0.88 mg/L and 2.57 mg/L. Organic phosphorus and PO4 were both prominent in the TP
concentrations. Rainfall intensity was not the primary determining factor behind phosphorus
concentrations; the highest and lowest recorded Org P concentrations came from samples generated by
the two highest recorded rainfalls.
Herbicide concentrations were relatively low, considering that neither atrazine nor metolachlor were
applied on the Spare’s fields since the last sorghum crop was planted in 1992. Atrazine values ranged
from 0.06 ug/L to 0.38 ug/L. Levels were expected to remain consistently low or even decline over the
course of the monitoring project. The unexpected fluctuations in herbicide levels, slight as they may be,
led KBS to conclude that the intermittent stream overflowing its banks could influence the runoff samples,
and that earlier results of the runoff monitoring program may better characterize water quality of the
rowcrop-dominated watershed than of the converted field. The complete raw data set is located in
Appendix B.
Table 12: Mean* nutrient and herbicide concentrations in first flush runoff on the Spare farm.
Sampling Date Rain TN Org N NO3 NH3 TP Org P PO4 Atrazine MetolachlorJul 29, 97 1.60 2.86 2.03 0.43 0.40 1.88 0.32 1.56 0.06 0.02 Aug 31, 98 0.60 9.49 7.41 0.19 2.02 2.57 1.33 1.27 0.25 0.01 Oct 31, 98 3.70 8.36 6.28 2.01 0.06 2.37 2.13 0.24 0.38 0.22 Jun 18, 99 0.50 7.50 - - - 1.83 - - 0.24 0.21 Jul 16, 99 3.80 12.69 1.64 10.65 0.39 0.88 0.27 0.61 0.16 0.03 Site Mean Value 8.80 4.34 4.05 0.72 2.62 1.01 0.92 0.22 0.12 Site Median Value 8.76 3.11 1.66 0.13 2.23 0.68 0.97 0.20 0.03 HUC 8 Watershed Average1 - - 0.76 0.07 0.26 - - 0.98 - Kansas Statewide Average1 - - 1.02 0.11 0.26 - - 1.12 - Units: Rain = inches in 48 hours prior to sampling, (TN, Org N, NO3, NH3, TP, Org P, PO4) = mg/L, Atrazine and Metolachlor = ug/L. * = Average of eight samples collected during the initial three-hour first flush runoff conditions. 1 = Values obtained from Appendix B, Kansas Nonpoint Source Pollution Management Plan – 2000 Update (KDHE 2000). Monitoring Groundwater in the Converted Field Groundwater samples were collected ten times from 1996 to 2000 on the Spare farm. Clusters of
lysimeters were installed at three locations within the converted field to collect shallow groundwater
(Figure 8). The positions of the clusters were determined by the local topography, which dictated the
directional flow of groundwater. Cluster 1 was installed nearest to the intermittent stream. Most of the
31
drainage contributing groundwater to this cluster was included in the grazing system, but lateral flow of
groundwater from the stream may have influenced groundwater chemistry at this site. Cluster 2 was
placed on the western edge of the uppermost grazing cell. Groundwater samples from this cluster flowed
through fallow land to the west and from several of the Spare’s grazing cells to the south. Cluster 3 was
installed on a ridge between the other two clusters near one of the two wells drilled for the watering
system. Most of the groundwater data came from the eight-foot lysimeters, and that data set is used in
trend analysis. The groundwater concentration data table is found in Appendix B.
Groundwater chemistry was notably consistent over time at Clusters 1 and 2. Samples from Cluster 3
displayed a wider range of variability. Total nitrogen concentrations at Clusters 1 and 2 typically ranged
from 0.2 to 1.0 mg/L (Figure 9). Concentrations were frequently slightly higher at Cluster 1. Nitrate was
the primary nitrogen constituent at the eight-foot depth at both sites. Organic nitrogen was more
prevalent in the few samples collected at four feet. Analysis over time showed that TN levels appeared to
decrease at Cluster 1 but not at Cluster 2. This was an expected result, as groundwater sampled by
Cluster 1 was more likely impacted by the changes in land management. The drainage contributing
groundwater to Cluster 2 was primarily fallow land over the duration of the monitoring project. Total
nitrogen concentrations at Cluster 3 were much more variable through time than at the other two sites.
Values were initially high at 5.7 mg/L but decreased to levels more consistent with the other two sample
sites as the planted grasses and legumes became more stabilized. Organic nitrogen was the primary
constituent for the first two years of the monitoring project, but NO3 was the more abundant form of
nitrogen in samples from 1999 and 2000. Nitrate concentrations at eight feet were consistently ten to one
hundred times less than the HUC 8 watershed average for NO3 in groundwater, 2.34 mg/L (KDHE, 2000).
Phosphorus concentrations in shallow groundwater followed a trend similar to the nitrogen data. At
Cluster 1, TP values ranged from 0.01 to 0.17 mg/L at four feet. Concentrations generally decreased with
sampling depth and were more consistent at eight feet, ranging from 0.01 to 0.04 (Figure 9). Maximum
values at four feet came from spring and early summer samples, while maximum values at eight feet
came from late fall and winter samples. Cluster 2 had a narrower range of values from both sampling
depths, 0.01 to 0.07 mg/L. Values were more consistent between depths than at Cluster 1. The highest
concentrations at both four and eight feet came from spring and early summer samples. Both organic
phosphorus and phosphate were prevalent in shallow groundwater at Cluster 2. Data from Cluster 3
followed a slightly different trend than the other two sampling locations. Concentrations in samples at this
site were higher than the other two, ranging from 0.05 to 0.19 mg/L. The timing of maximum values per
sampling depth was similar to Cluster 1. Maximum values at four feet came from spring and early
summer samples, while maximum values at eight feet came from late fall and winter samples. Phosphate
was the primary constituent in samples from this location. The proximity of Cluster 3 to one of two wells
installed for cattle watering purposes might have influenced the data.
32
Herbicides were not applied on the demonstration acreage after the last wheat crop was harvested in
1994. Atrazine and metolachlor concentrations greater than the detection limit of 0.02 ug/L were rarely
found at the eight-foot depth at any of the groundwater sampling sites on the Spare farm. On a few
occasions, higher concentrations were found at Cluster 1. Shallow groundwater sampled at Cluster 1
could have been influenced by lateral flow of stream water.
Figure 9: Nutrients in groundwater sampled at the eight-foot depth at three locations on the Spare farm.
0.0 1.0 2.0 3.0 4.0 5.0 6.0
Jul 19, 96Jun 14, 97Aug 7, 97Jul 22, 98Aug 4, 98Jul 15, 99O
ct 3, 99D
ec 9, 99M
ay 24, 00Jul 19, 00
Total Nitrogen
Con
cent
ratio
n (m
g/L)
Cluster123
0.0
0.1
0.2
0.3
Jul 19, 96Jun 14, 97Aug 7, 97Jul 22, 98Aug 4, 98Jul 15, 99O
ct 3, 99D
ec 9, 99M
ay 24, 00Jul 19, 00
Total Phosphorus
(mg/
L)
Cluster 1 2 3
Discussion and Conclusions The Spares succeeded in reaching their set goals of keeping the 80 acres of highly erodible land in
production and reducing chemical inputs and machinery needs. Establishing the MIG resulted in the
elimination of over 10 tons of nitrogen fertilizer and over 500 pounds of atrazine that would have been
applied had the ground been kept in sorghum and wheat production. The Spares observed less runoff
leaving the land after the perennial groundcover was established, and the mixes of grass and legume
crops exhibited a higher drought tolerance. Increases in soil aggregate stability and dissolved organic
carbon in the converted field point to better soil tilth and greater water holding capacity. Results of the
runoff monitoring were possibly compromised by the intermittent stream, which was fed by runoff from
conventional cropland in the upstream watershed. The mean first flush runoff concentrations for nitrogen
and phosphorus compounds were slightly higher than at the other converted MIG pastures monitored by
KBS.
A trend based on the conversion from cropland to perennial grassland was evident based on the
groundwater data from all three locations. Cluster 1 showed slight decreases in TN concentrations and
consistently low TP concentrations at eight feet. Cluster 2, positioned to sample groundwater influenced
by the neighboring fallow land, had consistently low TN concentration: TP concentrations were more
similar to values from Cluster 3. Values for TN and TP varied more both seasonally and annually at
33
Cluster 3. The site’s proximity to the well dug for the water system may have influenced nutrient
concentrations for two reasons. First, livestock seeking water were more frequently congregated near
Cluster 3 than by the other two clusters, increasing the likelihood of urine and manure being effectively
applied near the lysimeters. Secondly, the spilling of water by the cattle around the watering system
could have increased leaching of nutrients downward in the soil column. Despite this potential for
increased leaching, results of the monitoring program on the converted field show that the Spare’s
management did not contribute to increased contributions of agricultural NPSP in runoff or groundwater
pollution in the watershed.
34
Richard, Julia and Jim Townsend, Dickinson County Watershed: Smoky Hill River Water Quality Concerns: Nutrients and
herbicides in runoff from cropland Demonstration: Convert most cropland to
perennial grasses and legumes and implement a management intensive grazing system.
Monitoring: Runoff, groundwater and soils from a 65-acre converted field; runoff, groundwater, surface water from on-site wooded wetland.
Photo 12: Former wheat field planted to cool season grasses and legumes for conversion to a management intensive grazing system.
The Townsend farm included 313 acres of
cropland, native and brome pastures,
prairie hay meadows and a wooded wetland southwest of Chapman, KS. The Townsends applied to the
Clean Water Farms Project to convert cropland to cool season grasses and legumes with the eventual
goal of establishing a management intensive grazing (MIG) system. Despite conventional conservation
practices, runoff from neighboring fields washed across highly erodible cropland, transporting sediment,
nutrients and herbicides off of the Townsend’s fields. The water quality benefits of the change in land
management included reducing the amount of runoff crossing highly erodible land, retaining soil with
perennial groundcover, reducing the need for fertilizer and herbicide applications and restoring the soil
quality on land that had been continuously planted in wheat by the previous landowner. The Townsends
seeded 65 acres of cropland to alfalfa and fescue. Additional grass and legume seedings and weed
control measures were necessary, as neither the fescue nor the alfalfa did well at first. Eventually a
thriving stand of alfalfa interspersed with fescue was established. The Townsends plan to eventually
convert nearly all of their acreage to perennial grassland and establish a herd of 150-175 animal units
(cattle and possibly hogs).
The Kansas Biological Survey included the Townsend farm in the monitoring project for two main
reasons. First, the Townsend’s demonstration would ideally provide data associated with the effects on
water quality by the change in land management from annual to perennial cover, followed by the effects
on water quality by cattle in a MIG system. The change in land management was still in the planning
stage when the Townsend’s CWFP application was received, making the collection of pre-conversion
data possible. Secondly, the farm and several neighboring farms drain to a 10-acre perennial wooded
wetland adjacent to the Townsend’s monitored field. This wetland serves as the headwaters for Deer
Creek. Water quality data from the wetland provides a valuable comparison between the field scale and
the watershed scale. These comparisons offer insight to the Townsend farm’s relative contribution to
wetland’s water quality and to the role the wetland itself might have in influencing the water quality of
35
adjacent drainages. The monitoring program was established in 1996 and included soil, runoff,
groundwater and wetland surface water sampling.
Soil Characteristics of the Monitored Field The converted field is slightly sloped and drains to the wetland via a grassed waterway. Soils found in the
field are classified in the Irwin Series, which are deep, well drained and found parallel to creeks and
intermittent drainages (Jantz, 1980). Soil samples were taken annually from the top ten centimeters at
three locations in the field. All samples were collected in the late spring and early summer. Results of
the soils analyses (Table 13) suggested annual fluctuations in nitrogen, phosphorus and carbon levels.
Total Kjeldahl nitrogen levels increased annually four of five years from 1996 to 2000. Nitrate levels were
similar to crop fields monitored by KBS. The aggregate stability percentage increased noticeably after
1998 when the switch from wheat to forage crops was made. The highest values for total Kjeldahl
nitrogen, total phosphorus and aggregate stability came in 2000, after the alfalfa was well established.
Table 13: Soils quality indicators and chemistry from Townsend's converted field. Parameter 1996 1997 1998 1999 2000 Mean
Crop Wheat Wheat Wheat Alfalfa/Fescue Alfalfa - Total Kjeldahl N (mg Org N+NH3/kg soil) 1685 1787 1901 1625 2180 1836 Nitrate (mg NO3/kg soil) 8 8 7 - - 100 Total P (mg P/kg soil) 379 409 480 377 506 430 Phosphate (mg PO4/kg soil) 100 40 80 - - 73 Dissolved Organic C (mg C/kg soil) 105 125 70 - - 100 pH 5.92 5.47 5.40 - - 5.60 Aggregate % 81 82 87 96 94 88
Monitoring Runoff on the Converted Field A runoff sampler was installed on the edge of the converted field to collect runoff as it exited the field to a
grass waterway. Runoff was collected eleven times from 1996 to 1999 at the sampler on the converted
field. Seven of the sampling events occurred during the summer and fall of 1998. This was the most
heavily sampled location during one year on any of the farms monitored by KBS. The data subset for
1998 (Table 14) in particular illustrates short-term changes in water quality as a function of groundcover,
tillage and fertilizer applications. The drainage contributing runoff to the sampler was small and relatively
isolated, so the nutrient and herbicide concentrations in sampled runoff were predominantly a function of
the current and historical land management practices on the 65-acre parcel of land and adjacent small
grain fields to the south and east. Water quality data did indicate that some off-site runoff contributed to
the sampled runoff water quality.
Water quality results of the field runoff varied primarily as a function of the establishment of perennial
ground cover and timing of field applications and tilling relative to runoff events. Total nitrogen (TN)
36
37
Figure 10: Sampling sites and field perimeter on the Townsend farm, Dickinson County, KS.
concentrations ranged from 1.4 to over 9.7 mg/L (Table 14). Total nitrogen and organic nitrogen (Org N)
data were not available for the first sampling date, but the nitrate (NO3) and ammonia (NH3) values
indicated a TN concentration over 12.3 mg/L. These high NO3 and NH3 concentrations were probably
related to the fertilizer applications for the fall wheat crop prior to sample collection. Subsequent TN
concentrations were below 4.1 mg/L for nine of the ten sample events; these levels are similar to
concentrations from other grazing systems monitored by KBS. Ammonia levels in runoff increased
noticeably during the summer of 1998 after ammonium sulfate fertilizer was applied in July to stimulate
herbicide intake by field weeds. Total nitrogen levels on August 26, 1998 were higher than the previous
sampling on August 4, 1998. The field was tilled and reseeded in alfalfa between the two sampling dates,
and exposed soil increased the amount of Org N available for transport in runoff. Subsequent sample
events in 1998 after groundcover was better established had decreased concentrations of Org N.
Overall, nitrogen levels in runoff leaving the converted field, especially NO3, appeared to decrease slightly
over the course of the project.
Nine of the eleven sample events had mean TP concentrations less than 1.20 mg/L. Normally TP
concentrations were highest during the first hour of sampling and decreased for the remaining first flush
period. The 1998 data set again provided insight to the role of groundcover in retaining nutrients. The
two 1998 samples collected prior to the tilling had mean TP levels of 0.79 and 0.68 mg/L. Levels
increased to 2.39 mg/L in the first sampling after the field was tilled for alfalfa planting (Figure 14), and
then decreased over the course of the 1998 season as the alfalfa became more established. Organic
phosphorus and PO4 levels fluctuated to a small degree and followed a trend based on rainfall and the
groundcover. Samples from runoff events generated by heavier storms had a noticeably higher ratio of
the more soluble PO4 to the sediment-bound Org P.
Herbicide concentrations also followed a pattern based on rainfall and the timing of runoff events relative
to field applications in contributing drainages. Metolachlor concentrations were consistently low. Mean
atrazine levels in runoff leaving the converted field were well below the HUC 8 Watershed Average of
0.89 ug/L for ten of the eleven sampled runoff events. The highest atrazine concentrations occurred in
runoff from November 1, 1998. This runoff event was generated by a more intense storm (4.90 inches),
but nutrient levels from the November 1, 1998 storm were similar to levels from earlier storms that year.
Some applications of atrazine might have occurred on neighboring crop fields that contribute runoff to the
Townsend’s farm; runoff from neighboring fields is a possible source of the herbicide.
38
Table 14: Mean* nutrient and herbicide concentrations in first flush runoff at Townsend’s field site. Sampling Date Rain TN Org N NO3 NH3 TP Org P PO4 Atrazine Metolachlor Nov 16, 96 2.5 - - 10.33 1.99 - - 0.27 0.01 0.01 Jul 28, 97 0.8 3.72 2.83 0.83 0.05 1.19 1.00 0.20 0.01 0.01 Jul 7, 98 0.5 2.81 2.15 0.53 0.13 0.79 0.45 0.34 0.42 0.06 Jul 30, 98 3.7 3.14 1.50 1.11 0.54 0.68 0.12 0.57 0.16 0.05 Aug 26, 98 0.8 9.73 8.26 1.04 0.43 2.39 1.74 0.65 0.05 0.01 Sep 24, 98 1.1 3.50 2.02 1.17 0.32 1.13 0.67 0.46 0.03 0.01 Sep 30, 98 1.3 4.09 2.32 1.65 0.12 1.02 0.80 0.18 0.03 0.01 Oct 17, 98 1.4 2.66 2.19 0.39 0.09 0.81 0.63 0.23 1.00 0.01 Nov 1, 98 4.9 1.56 1.47 0.03 0.06 0.43 0.11 0.32 0.21 0.01 Jun 18, 99 0.8 2.91 - - - 1.04 - - 0.21 0.10 Aug 2, 99 3.6 1.41 1.23 0.19 0.10 0.94 0.31 0.63 0.26 0.19 Site Mean Value 3.55 2.66 1.71 0.36 1.04 0.65 0.38 0.14 0.08 Site Median Value 2.63 1.82 0.8 0.15 0.86 0.45 0.32 0.07 0.05 HUC 8 Watershed Average1 - - 0.87 0.08 0.31 - - 0.89 - Kansas Statewide Average1 - - 1.02 0.11 0.26 - - 1.12 - Units: Rain = inches in 48 hours prior to sampling, (TN, Org N, NO3, NH3, TP, Org P, PO4) = mg/L, Atrazine and Metolachlor = ug/L. * = Average of eight samples collected during the initial three-hour first flush runoff conditions. 1 = Values obtained from Appendix B, Kansas Nonpoint Source Pollution Management Plan – 2000 Update (KDHE 2000). Monitoring Runoff in the Wetland A runoff sampler was installed in the wetland to compare water quality data to the converted field and to
investigate the wetland’s role in influencing nutrient and herbicide levels in surface water. Fields to the
south, east and west of the monitored field all drain into the wetland. Visual estimates of which drainage
areas contribute water to the runoff sampler determined that 80% of the water likely came from the spring
that fed the wetland and from runoff from neighboring farms to the south. The other 20% likely came from
the area that contributed water to the Townsend’s grass waterway that drained directly into the wetland.
Heavier rains were necessary to activate the wetland runoff sampler than the field runoff sampler. The
four runoff events that were sampled in the wetland were also sampled from the converted field, providing
a set of matching samples. Analysis of this data subset is of interest because samples were produced by
similar conditions on these dates. Climatic factors such as storm intensity, storm duration and pre-
existing moisture levels were reduced as sources of variation in determining nutrient and herbicide
concentrations when samples were generated by the same runoff event.
For the first three sampling dates, nutrient concentrations in wetland runoff samples were largely similar
to concentrations from the converted field (Table 15). Nitrate, NH3 and PO4 constituted a greater portion
of the TN and TP values for the first and last runoff events, which were generated by heavier storms.
Organic nitrogen and Org P were more prevalent in the second and third sample sets, which were
generated by storms of lesser magnitude. Wetland runoff samples from the final sampling event were 10
to 100 times greater for NO3, NH3, atrazine and metolachlor than the matching sample concentrations in
runoff from the field samples. Total nitrogen levels in runoff samples from the field site were 1.41 mg/L for
this last event, compared to 22.48 mg/L for the wetland runoff samples. These increases resulted from a
combination of the larger land area contributing nutrients and herbicides to the wetland and the
39
mobilization of nutrients and herbicides in runoff during and after the particularly intense storm. On the
final sampling date, the atrazine concentration in runoff from the field was 0.26 ug/L, while the wetland
runoff sample was 14.39 ug/L; clearly watershed-level contributions are evident. Possible sources of the
increase in the wetland herbicide levels include applications of herbicides in the watershed prior to
sampling, and a greater suspended sediment load generated by the more intense storm. Herbicides
bound chemically to sediment particles were transported to and collected by the sampler in addition to
herbicides dissolved in the runoff.
Table 15: Mean* nutrient and herbicide concentrations in first flush runoff in Townsend’s wetland. Sampling Date Rain TN Org N NO3 NH3 TP Org P PO4 Atrazine Metolachlor Jul 30, 98 3.7 3.06 0.45 1.02 1.59 0.68 0.15 0.53 3.37 3.17 Sep 30, 98 1.3 2.24 1.39 0.70 0.17 0.69 0.40 0.29 0.07 0.02 Oct 17, 98 1.4 2.48 2.35 0.03 0.10 0.78 0.40 0.38 0.03 0.22 Aug 2, 99 3.6 22.48 1.42 19.15 1.91 1.17 0.51 0.66 14.39 16.43 Site Mean Value 7.56 1.40 5.39 0.94 0.83 0.36 0.47 4.71 4.96 Site Median Value 2.80 1.34 1.00 0.68 0.69 0.35 0.39 1.29 0.64 HUC 8 Watershed Average1 - - 0.87 0.08 0.31 - - 0.89 - Kansas Statewide Average1 - - 1.02 0.11 0.26 - - 1.12 - Units: Rain = inches in 48 hours prior to sampling, (TN, Org N, NO3, NH3, TP, Org P, PO4) = mg/L, Atrazine and Metolachlor = ug/L. * = Average of eight samples collected during the initial three-hour first flush runoff conditions. 1 = Values obtained from Appendix B, Kansas Nonpoint Source Pollution Management Plan – 2000 Update (KDHE 2000). Surface Water in the Wetland Wetland surface water was monitored to determine what effects the wetland had on water chemistry as
water entered, passed through and exited the system. Samples were collected eight times from 1996 to
2000 at three sites in the wooded wetland on the Townsend farm. Samples were collected independent
of runoff events, though rainfall did impact two of the sample sets. Wetland samples were collected at
three locations in the wetland (Figure 10) to compare nutrient and herbicide concentrations in water
flowing into the wetland (Site 1) water carried into the wetland from series of grass waterways (Site 2) and
in water exiting the wetland system (Site 3).
Results from the surface water samples are largely indicative of base-flow concentrations (Table 15).
Samples were not collected at the uppermost and middle sites for all of 1996 and part of 1997 due to low
flow conditions. During normal base flow conditions, nutrient and herbicide concentrations appeared to
fluctuate only slightly as water flowed through the system. Seasonal differences in concentrations from
the groundwater sources of the wetland were partially responsible for these fluctuations. The complex
wetland vegetation community influenced concentrations through the uptake and release of nutrients and
herbicides in repeated seasonal cycles of growth and decay. Values for TN, TP and NH3 in wetland grab
samples were generally lower than those in samples collected after substantial rainfall by the runoff
sampler. Nitrate and PO4 levels were lower probably due to intake of these essential compounds by
wetland plant community.
40
The concentration data from two sampling events influenced by runoff events reflects inputs of nutrients
and herbicides from the surrounding land into the wetland system. Increases in Org N were responsible
for the ten-fold increase in TN on July 28, 1997. Compared to concentrations in runoff collected by the
automatic sampler on August 2, 1999, wetland grab samples had markedly lower concentrations of TN,
TP, NO3, Org P, atrazine and metolachlor. By the time surface water grab samples were collected on
August 4, 1999, nutrient and herbicide concentrations in the wetland had decreased to expected levels at
all three sites. These data further characterize the water quality of first flush runoff as having higher
concentrations of nutrients and herbicides than surface water sampled days after a runoff event.
Table 16: Nutrient and herbicide concentrations from three sites in the Townsend wetland. Sampling Date Site Rain TN Org N NO3 NH3 TP Org P PO4 Atrazine MetolachlorJul 19, 96 3 0 0.63 0.26 0.33 0.04 0.04 0.02 0.02 0.01 0.01 Oct 22, 96 3 0 0.69 0.10 0.57 0.02 0.05 0.04 0.02 0.08 0.01 Jun 11, 97 3 0 0.81 0.34 0.44 0.03 0.03 0.01 0.02 0.19 0.22 Jul 28, 97 2 0.8 9.80 9.57 0.10 0.13 1.04 1.01 0.03 0.40 0.10 3 10.60 10.14 0.39 0.87 0.83 0.83 0.07 0.33 0.08 Oct 28, 98 1 0 0.50 0.50 0.00 0.06 0.00 0.00 0.00 0.01 0.01 2 0.86 0.35 0.45 0.06 0.05 0.05 0.06 0.01 0.01 3 1.16 0.21 0.95 0.01 0.00 0.00 0.00 0.01 0.01 Aug 4, 99 1 3.6 2.00 0.37 1.59 0.16 0.08 0.08 0.04 0.64 0.09 2 0.90 0.36 0.52 0.07 0.05 0.05 0.02 0.73 0.07 3 1.11 0.35 0.70 0.13 0.09 0.09 0.06 0.95 0.29 May 18, 00 1 0 0.32 0.28 0.01 0.03 0.07 0.06 0.02 0.03 0.01 2 0.83 0.75 0.02 0.06 0.12 0.09 0.03 0.06 0.01 3 0.87 0.30 0.54 0.03 0.08 0.06 0.02 0.01 0.01 Jun 15, 00 1 0.3 0.77 0.54 0.01 0.22 0.21 0.21 0.01 0.11 0.04 2 0.38 0.34 0.02 0.02 0.01 0.01 0.01 0.14 0.04 3 2.03 0.44 1.50 0.09 0.11 0.09 0.02 0.30 0.06 HUC 8 Watershed Average1 - - 0.87 0.08 0.31 - - 0.89 - Kansas Statewide Average1 - - 1.02 0.11 0.26 - - 1.12 -
Units: Rain = inches in 48 hours prior to sampling, (TN, Org N, NO3, NH3, TP, Org P, PO4) = mg/L, Atrazine and Metolachlor = ug/L.1 = Values obtained from Appendix B, Kansas Nonpoint Source P llution Management Plan – 2000 Update (KDHE 2000). o Monitoring Groundwater Shallow groundwater was collected eleven times from 1996 to 2000 at three sites on the Townsend farm.
Three lysimeter clusters were installed along a transect to sample shallow groundwater from two distinct
land covers. Cluster 1 was placed to collect groundwater in the wetland complex (Figure 10). Cluster 2
and Cluster 3 were positioned to collect groundwater coming from the converted field, with Cluster 3
being closer to the boundary of the managed field. Samples were collected independent of runoff events,
though rainfall may have influenced water chemistry in some samples. The majority of samples were
collected from eight feet, though the more frequently saturated soils in the wetland also provided samples
from one and four feet. Data from the eight-foot groundwater samples are used in trend analyses.
41
Total nitrogen concentrations in shallow groundwater from all three sampling locations were relatively
consistent after initially higher concentrations (Figure 12). The majority of the samples ranged between
1.5 and 5.0 mg/L. Nitrate was the principal groundwater nitrogen constituent at the eight-foot depth.
Organic nitrogen concentrations were usually less than 1.0 mg/L at all three sites. Comparing nitrogen
levels at all three clusters, TN levels at Cluster 3 varied over a larger range than at Clusters 1 and 2. This
could be a function of the Cluster 3’s closer proximity to neighboring conventional rowcropped fields;
neighboring management practices had a greater chance at contributing nutrients to Cluster 3 than
Cluster 2. Groundwater from Clusters 1 and 2 followed similar seasonal and annual trends and had
similar TN concentrations after the first sampling event. Concentrations in both field sites increased
slightly in fall samples. Reduced nitrogen intake by vegetation in the non-growing season probably
allowed more nitrogen to leach down to the eight-foot depth. Total nitrogen concentrations were lower at
all three sites at the completion of the monitoring project compared to initial values.
As with TN, TP levels were highest in the beginning of the project before the conversion from wheat to
grasses and legumes. Total phosphorus levels at eight feet at all clusters ranged from 0.01 to 0.18 mg/L
(Figure 12). The Cluster 1 (wetland) and Cluster 2 (lower field) had TP levels consistently less than 0.06
mg/L after the first sampling event, while Cluster 3 (upper field) had more varied TP levels ranging from
0.01 to 0.15 mg/L. Concentrations at the upper field sampler decreased over the course of the monitoring
project, perhaps due to the establishment of permanent groundcover that incorporated more of the PO4
before it could leach downward past the root zone and into the shallow groundwater.
Groundwater sampled at the Townsend’s farm was not adversely impacted by atrazine and metolachlor.
Those herbicides were rarely detected above 0.10 ug/L in groundwater at any sampling location. This
was expected, as atrazine applications on the converted field ceased after the grass and legumes were
established in 1998. Some seasonal variation was observed. Fall samples rarely had levels above the
laboratory detection limit of 0.02 ug/L, while summer samples were often detected, once reaching 0.28
ug/L. The highest recorded concentration for atrazine was in a rain-impacted wetland groundwater
sample. Saturated soil conditions in the wetland and herbicide applications earlier in the season
upstream of the wetland lysimeter cluster created conditions suitable for increased downward leaching of
dissolved atrazine. The complete concentration data is found in Appendix C.
42
Figure 11: Nutrients in eight-foot deep groundwater sampled at three locations on the Townsend farm.
0.0
3.0
6.0
9.0
12.0
Jul 19, 96 Jun 14, 97 Aug 7, 97 Jun 22, 98 Aug 4, 98 Jul 15, 99 O
ct 3, 99 D
ec 9, 99 M
ay 31, 00 Jul 19, 00
Con
cent
ratio
n (m
g/L)
Cluster
Wetland Lower field Upper field
Total Nitrogen
0.0
0.1
0.2
Jul 19, 96 Jun 14, 97 Aug 7, 97 Jun 22, 98 Aug 4, 98 Jul 15, 99 O
ct 3, 99 D
ec 9, 99 M
ay 31, 00 Jul 19, 00
Con
cent
ratio
n (m
g/L)
Cluster
Wetland Lower field Upper field
Total Phosphorus
Discussion and Conclusions The Townsend farm provided an excellent data set on the relationship between field conditions and
nutrient and herbicide concentrations in runoff and groundwater. The concentration information collected
in the summer and fall 1998 was one of the more illuminating data sets gathered in any of the KBS on-
farm monitoring projects. The combination of soils, runoff, groundwater and wetland surface water
sampling allowed KBS to better interpret each single data set. The Townsends reduced the applications
of nitrogen fertilizers on the converted field by over 7000 pounds and eliminated the need for herbicides
used in wheat production. By communicating with the Townsends about past management decisions
and future management plans, relationships between concentration data and specific management
practices were made.
Though the Townsends experienced some initial difficulties establishing their cool season grasses and
legumes, this project allowed KBS to gather and interpret data on the land-use conversion from grains to
forages. The soil aggregate stability increased over the duration of the project. Higher aggregate stability
percentages are indicative of better water-holding capacity, and the Townsends observed less runoff
flowing over their land after the perennial ground cover was established. Nutrient concentrations in field
runoff seemed to be related to the management practices. Results from the 1998 sampling season
illustrated the role that fertilizer applications and establishing ground cover can have in the nutrient
concentrations in runoff flowing over and off of that field. Comparing the four matching events sampled
at both the field and wetland sites showed the influence of the land-use in an entire watershed on local
water quality after particularly intense storms.
Groundwater nutrient and herbicide concentrations at the eight-foot depth were relatively similar among
the sampling sites, and results were similar to other farms monitored by KBS. Minute differences among
the sampling sites are likely related to off-site contributions. Groundwater from Cluster 1, with its
43
saturated wetland soil, had a more consistent TN concentration that fluctuated slightly seasonally and a
consistently low TP concentration. Clusters 2 and 3 in the grassed waterway were more likely influenced
by both on-site and neighboring land management. Some seasonal variation was observed, and
concentrations for TN and TP seemed to stabilize in the latter stages of the monitoring project. This
decrease is attributed to consistent land cover and fewer chemical applications to the monitored field.
Watershed-level contributions were noticeable in wetland runoff and wetland surface water samples.
Comparing the August 2, 1999 wetland runoff samples with wetland surface water collected two days
later illustrated the water quality relationship between first flush runoff and surface water. Total nitrogen,
TP and atrazine levels were all over ten times higher in the first flush runoff compared to the surface
water sampled from the wetland two days later. Baseline water quality conditions in the wetland were
dramatically different than rain-influenced conditions. The wetland provided a buffering effect for the
runoff coming from the Townsend’s and surrounding farms. Though spatial differences in nutrient and
herbicide concentrations between the upper, middle and lower sampling sites were unpredictable, the
wetland appeared to lessen the potential impact of the more highly concentrated first flush by absorbing
the nutrient pulses in runoff and gradually releasing the nutrients downstream through biological
processes. Preserving the wetland on the Townsend farm had a positive impact on the local and
downstream waters of Deer Creek.
44
Steve and Jenny Burr, Saline County Watershed: Mulberry Water Quality Concerns: Nutrients and
herbicides in runoff from cropland influencing water quality in creek.
Demonstration: Convert cropland to grass and establish a year-round grazing system.
Monitoring: Runoff from cropland converted to grasses and legumes; soils from unconverted cropland.
The Burr farm has developed 700 acres of
cropland and native grasses in a rotational
grazing system northwest of Salina, KS. Three
hundred acres were planted in wheat, milo, sudan
were in native grasses and managed pastures. In o
and free of confinement lots, the Burrs converted
season grasses and installed underground wate
management intensive grazing (MIG) system. W
included reducing the need for fertilizers and herb
farm. Additional benefits of the switch in managem
perennial groundcover and reducing impacts assoc
wastes, denudation of groundcover, compacted soils
Much of the conversion from crop to perennial gras
the KBS monitoring plan. Despite the lack of pre-co
the MIG practice for several reasons. While the
grasses, the change in land use and management w
monitoring period were expected to be high. Seco
program. Points where runoff entered and exited th
installing sampling equipment was relatively straigh
that the perennial forage and grass waterways could
reduce nutrient and herbicide concentrations in that
Soil Characteristics of an Unconverted GSoil samples were taken from a crop field south of
This field was originally slated for conversion to pere
plans changed when weather conditions were unfa
grown in the field during the monitoring project. Th
grain field and not any conversion process from cro
Photo 13: Cropland converted to cool season grasses and legumes for management intensive grazing near Mulberry Creek.
grass and alfalfa in rotation, and another 400 acres
rder to expand their grazing system to be year-round
43 more acres of their cropland to native and cool
r lines and high tensile fencing to implement a
ater quality goals associated with the conversion
icides and decreasing volume of runoff crossing the
ent included enhancing soil structure by establishing
iated with over-wintering feedlots (i.e. concentrated
).
s was near completion prior to the implementation of
nversion water quality data, KBS decided to monitor
fields had already been converted from grains to
as recent and chances of observing trends over the
nd, the local topography was ideal for a monitoring
e managed MIG paddocks were easily identified, and
tforward. Finally, KBS wanted to test the hypothesis
reduce the volume of runoff coming off the land and
runoff.
rain Field the converted fields from 1996 to 2000 (Figure 13).
nnial grasses, but the Burr’s immediate management
vorable for seeding. Instead, wheat and milo were
ese samples thus represent a conventionally grown
pland to perennial grass cover. Soils data from this
45
grain field contrasts trends from converted fields in other farms monitored by KBS. The field where the
soil samples were taken has soils in the Bavaria Series. These soils are deep, nearly level and
moderately well drained. Found on stream terraces, Bavaria soils are subject to episodic flooding and
are formed from silty alluvium (Palmer et al, 1992). Results of the soils analyses from the sampled crop
field differed from expected results from a converted field. Total Kjeldahl nitrogen levels were less than
converted fields in the same general vicinity, but those differences might reflect natural variation in soil
chemistry and organic matter content. Total phosphorus levels were similar to other monitored fields, but
the aggregate stability percentage was noticeably lower in the cropped field than in perennial grass fields.
This trend indicates the effects of tillage and perennial ground cover on soil structure.
Table 17: Soil chemistry from a crop field at the Burr Farm. Parameter 1996 1997 1998 1999 2000 Mean Crop milo wheat milo wheat wheat - Total Kjeldahl N (mg Org N+NH3/kg soil) 1092 1018 924 1191 969 1039 Nitrate (mg NO3/kg soil) 14 16 21 - - 17 Total P (mg P/kg soil) 303 284 341 458 325 342 Phosphate (mg PO4/kg soil) 27 24 55 - - 35 Dissolved Organic C (mg C/kg soil) 120 92 68 - - 93 pH 5.12 5.61 5.12 - - 5.28 Aggregate Stability % 72 91 75 77 88 81
Monitoring Runoff in the Burr’s Converted Fields The monitoring program at the Burr farm was designed to collect surface runoff as it entered and exited
the farm. Between the entrance and exit points, runoff flowed through two converted fields. Fescue,
alfalfa and Eastern gamma grass had already become well established before monitoring equipment was
installed in 1996. The upper sampler was positioned in a cedar hedgerow to collect runoff as it first
entered the upper converted field. The lower sampler was placed in a wooded riparian area by a tributary
of Mulberry Creek to capture runoff as it exited a second converted field to the creek. Field runoff was
collected nine times between 1997 and 2000, four times at the upper sampler and five times at the lower
sampler. Dramatic changes in nutrient and herbicide concentrations between sampling increments on
the first date indicate that rising creek waters might have contributed water to the collected samples. The
complete set of raw water quality data is found in Appendix D.
The water chemistry of runoff entering the Burr farm reflected the management of land contributing over
which it flowed to the sampling site. Total nitrogen concentrations at the upper runoff sampler fluctuated
seasonally and with changes in rainfall (Table 17). Three sample sets were all collected in the month of
July from 1997 to 1999 and consistently had TN values less than 3.0 mg/L and low concentrations of Org
N, NO3 and NH3. The highest recorded TN concentration occurred on November 1, 1998 and resulted
from increased NO3 and NH3, presumably elevated by fertilizer applications for spring wheat crops in the
watershed. Organic nitrogen values were similar to the other samples. Fall runoff samples generated by
46
47
Figure 12: Sampling sites and field perimeters on the Burr farm, Saline County, KS.
heavy storms on other farms monitored by KBS also had elevated NO3 and NH3 concentrations from fall
fertilizer applications in the surrounding watershed.
Total phosphorus concentrations at the upper sampler were always less than 2.0 mg/L for the four
sample sets, similar to levels from other grazing systems monitored by KBS. Increases in PO4 levels
were responsible for the higher TP concentrations on November 1, 1998 and July 24, 1999. Organic
phosphorus levels were highest in July 29, 1997 samples. This sample set was generated by an intense
storm that probably mobilized Org P both in solution and attached to sediment transported by the runoff.
Herbicide levels fluctuated slightly within a low range of concentration. The fallow land immediately north
of the runoff sampler could function as a buffer between rowcropped and wheat fields in the watershed
and the Burr’s converted fields. Atrazine exceeded the HUC 8 watershed average of 0.98 ug/L once.
Table 18: Mean* nutrient and herbicide concentrations in runoff at the Burr’s upper site.
Sampling Date Rain TN Org N NO3 NH3 TP Org P PO4 Atrazine Metolachlor Jul 29, 972 4.7 2.99 2.01 0.88 0.10 0.93 0.80 0.13 0.59 0.40 Jul 24, 98 1.7 2.71 1.30 1.33 0.08 0.98 0.24 0.74 2.05 0.07 Nov 1, 982 3.2 6.62 1.42 4.68 0.52 1.88 0.29 1.59 0.04 0.04 Jul 24, 992 1.3 2.84 1.02 1.30 0.52 1.57 0.10 1.47 0.47 0.03
Site Mean Value 4.15 1.46 2.05 0.31 1.43 0.79 0.98 0.37 0.14 Site Median Value 3.37 1.34 1.33 0.24 1.49 0.18 0.84 0.43 0.05 HUC 8 Watershed Average1 - - 0.76 0.07 0.26 - - 0.98 - Kansas Statewide Average1 - - 1.02 0.11 0.26 - - 1.12 -
Units: Rain = Inches in 48 hours prior to sampling, (TN, Org N, NO3, NH3, TP, Org P, PO4) = mg/L, Atrazine and Metolachlor = ug/L.* = Average of eight samples collected during the initial three-hour first flush runoff conditions. 1 = Values obtained from Appendix B, Kansas Nonpoint Source Pollution Management Plan – 2000 Update (KDHE 2000). 2 = Matching samples collected at the Burr’s lower sampling site.
Runoff samples from the lower site were influenced by the intermittent tributary of Mulberry Creek, by the
continuous grass waterway between the two sampler sites, and by the land use immediately upstream of
the runoff sampler. The first sample on June 23, 1997 was likely influenced by the overflowing tributary of
Mulberry Creek (Table 18). Increased levels of Org N and Org P were responsible for the highest
recorded concentrations of TN and TP collected in runoff on this farm. The sources for these nutrients
were probably a combination of exposed soils and residue created by the wheat harvest in the
watershed. Rainfall also influenced the data. Similar to the upper site, the increase in the November 1,
1998 TN concentration is due to increases in NO3 mobilized by the 3.2 inches of rain that fell on that
date. Both NO3 and Org N values increased over the sample taken earlier that year. Mean NO3 levels
increased slightly over the project at this site but did not fluctuate very much overall, ranging from 1.1 to
2.5 mg/L. Organic nitrogen varied from 0.9 to 16.8 mg/L and was the primary nitrogen constituent in the
majority of the samples. Organic phosphorus values were usually below 0.5 mg/L. Phosphate levels
varied with rainfall amounts and ranged from 0.14 to 2.80 mg/L. Herbicide levels were initially quite high;
it’s likely that the tributary of Mulberry Creek overflowed its banks and influenced the first sample set.
48
Concentrations of atrazine and metolachlor decreased to levels similar to other KBS-monitored grazing
systems after that initial high.
Table 19: Mean* nutrient and herbicide concentrations in runoff at the Burr’s lower site.
Sampling Date Rain TN Org N NO3 NH3 TP Org P PO4 Atrazine Metolachlor Jun 23, 97 1.6 19.10 16.84 1.06 1.20 4.57 4.43 0.14 64.95 267.21 Jul 29, 972 4.7 4.69 3.46 1.15 0.07 0.97 0.32 0.65 0.65 1.62 Aug 4, 98 1.5 2.73 0.88 1.65 0.16 0.82 0.18 0.64 0.59 0.77 Nov 1, 982 3.2 5.45 2.80 2.53 0.17 3.03 0.23 2.80 0.06 0.06 Jul 24, 992 1.3 3.51 1.18 1.90 0.43 1.27 0.10 1.17 0.13 0.02 Site Mean Value 6.46 4.40 1.69 0.24 2.03 0.79 1.16 11.64 52.34 Site Median Value 4.48 1.52 1.20 0.19 1.41 0.18 0.90 0.13 0.08 HUC 8 Watershed Average1 - - 0.76 0.07 0.26 - - 0.98 - Kansas Statewide Average1 - - 1.02 0.11 0.26 - - 1.12 - Units: Rain = Inches in 48 hours prior to sampling, (TN, Org N, NO3, NH3, TP, Org P, PO4) = mg/L, Atrazine and Metolachlor = ug/L. * = Average of eight samples collected during the initial three-hour first flush runoff conditions. 1 = Values obtained from Appendix B, Kansas Nonpoint Source Pollution Management Plan – 2000 Update (KDHE 2000). 2 = Matching samples collected at the Burr’s upper sampling site.
Discussions and Conclusions
The change in land management on the Burr farm enhanced their grazing system by adding additional
grazing land with quality forage. The enhancement of the MIG system allowed the Burrs to achieve their
economic and environmental goals to reduce machinery and input costs associated with grain production
and to eliminate animal concentration lots from their grazing system. The Burrs were able to use their
grazing system year-round without confining their cattle in wintering lots. Converting the forty-three acres
to cool season grasses and legumes eliminated the need for herbicides associated with wheat and over
four tons of nitrogen fertilizer on that land. Data from the upper sampler was indicative of watershed-level
contributions of nutrients and herbicides to the runoff flowing onto the Burr’s fields. Observations by the
Burrs indicated less runoff flowed over and off of the converted fields compared to when the land was
devoted to rowcrops. The reduced volume and velocity of runoff flowing over the land with year-round
ground cover resulted in greater sediment retention and helped prevent rills from forming in the fields.
The monitoring program on the Burr farm provided data on runoff entering and leaving the farm.
Samples were compromised on one occasion by the rising waters of the tributary of Mulberry Creek.
Matching samples were collected on July 29, 1997; November 1, 1998; and July 24, 1999. The three
sets of matching samples (collected from both locations and generated by a single storm) indicated
similarities and inconsistencies in water quality in runoff entering and exiting the farm. Levels of NH3 and
Org P were reduced as runoff moved from the inflow to outflow sampler through the grass waterways. In
this case, the switch in land management seemed to have a buffering effect on water quality. Interpreting
the NO3 and PO4 was complicated by the differing intensities of the sampled storms. Concentrations of
these two nutrients levels did not change in a similar fashion to NH3 and Org P. The NO3 may have
rapidly traveled between the two sampling sites via sheet flow, unaffected by physical or biological
49
reduction processes. Organic nitrogen levels actually increased slightly in each set, perhaps due to an
increased amount of vegetation in varying states of decay in the riparian area where the sampler was
located. The increase in Org N and the unpredictability of the NO3 and PO4 may have resulted from the
influences of livestock in and upstream of the grazing paddocks. However, the observed changes in
concentrations were slight and could result from natural background variation.
50
51
Photo 14: A runoff sampler collects runoff in the 93-acre parcel of cropland converted to perennial grasses on the Howell farm.
Dan and Mary Howell, Marshall County Watershed: Lower Black Vermillion Water Quality Concerns: Erosion of flood-prone
cropland by Corndodger Creek; nutrients and herbicides in runoff
Demonstration: Convert cropland to perennial grass and implement a management intensive grazing system.
Monitoring: Runoff and groundwater from cropland converted to grazing system; surface water, aquatic habitat diversity and aquatic macroinvertebrates from adjacent Corndodger Creek.
The Howell farm included 1600 acres of cropland,
native grazing land and pasture in multiple locations
southwest of Frankfort, KS. Small grains and
grasses are grown as feed for 220 head of cattle. Corndodger Creek runs the western border of the
home farm site, and fields in the floodplain were periodically flooded, leading to crop and soil losses
and increased nutrients and herbicides in runoff. The Howells converted a 93-acre parcel of flood-
prone cropland to perennial grass cover and incorporated this parcel in their management intensive
grazing (MIG) system. The goal of the conversion from cropland to perennial forage was to keep the
land in production while reducing losses from the periodic flooding and to eventually eliminate the
need for fertilizer, herbicides and specialized equipment on that land. Prior to the conversion, alfalfa,
wheat, soybeans, oats and rye were grown on that parcel. Water lines were trenched in 1996, and
Martin fescue was planted in 1997 with a cover crop of oats. No fertilizer or herbicides were applied
after September 1997, and cattle were first introduced to the parcel in the summer of 1998.
The Kansas Biological Survey included the Howell farm in the monitoring project for several reasons.
First, the change in land management was still in the first stages when the Howells applied for a
Clean Water Farms grant. This provided the opportunity for KBS to collect data from the field during
several stages of the conversion process. Secondly, the farm’s location adjacent to Corndodger
Creek provided the opportunity to examine local water quality on both the field and watershed scales.
Aquatic invertebrate community sampling and habitat analysis on Corndodger Creek offered the
opportunity to investigate the effects of agricultural nonpoint pollution on stream biota. Finally, the
Howell family was interested in taking an active role in the monitoring process. They offered KBS
access to their extensive records detailing crop histories and applications to the 93-acre field and
welcomed the opportunity to participate in the monitoring program.
Soils in the Converted Field The Howell’s converted field occupies the floodplain of Corndodger Creek and the side slopes of a
ridge. Periodic flooding by Corndodger Creek influenced the soil types on the Howell farm. Soils in
the Kennebuc and Muir series were found on the Howell farm (Kutnink et al, 1980). Both soils are
nearly level and moderately well drained in or near the flood plains of streams. Soil samples were
collected in 1996, 1998, 1999 and 2000. Nitrogen, phosphorus and carbon levels all fluctuated
annually, but no strong trends in soil chemistry were observed (Table 19). One positive trend in soil
structure quality was evident. Laboratory analysis of aggregate stability revealed that the conversion
of the rowcropped parcel to perennial grassland resulted in a consistent increase in soil aggregate
values in the converted field. High values in this measure are indicative of increased soil moisture
retention and overall soil tilth. Similar trends in increasing aggregate stability were observed on other
farms monitored by KBS that had converted cropland to grasses and legumes.
Table 20: Soils quality indicators and chemistry from Howell's converted field. Parameter 1996 1998 1999 2000 Mean
Total Kjeldahl N (mg Org N+NH3/kg soil) 1793 1588 1433 1453 1567 Nitrate (mg NO3/kg soil) 47 18 - - 33 Total P (mg P/kg soil) 495 454 408 411 442 Phosphate (mg PO4/kg soil) 58 70 - - 64 Dissolved Organic C (mg C/kg soil) 144 86 - - 115 pH 6.48 6.35 - - 6.42 Aggregate Stability % 76 82 93 96 87
Monitoring the Converted Field The Kansas Biological Survey sampled runoff, groundwater and soils in the 93-acre field to monitor
changes in water quality that resulted from the conversion of the cropland to perennial grass cover.
In 1996, a runoff sampler was placed in an existing grass waterway to collect runoff as it exited the
converted field into a gully that drained into Corndodger Creek. Samples were collected six times
from 1998 to 2000. A railroad trestle and sloping topography to the north of the farm funneled runoff
from several neighboring parcels of cropland and pasture onto the monitored field.
Results of the runoff water quality analyses varied primarily as a function of rainfall and of the
different seasonal agricultural activities occurring in the watershed (Table 20). Total nitrogen and TP
values were consistent with runoff concentrations from grazing systems on other farms monitored by
KBS. Event mean TN values ranged from 1.6 to 6.6 mg/L. Organic nitrogen was the more prominent
dissolved nitrogen constituent in spring and summer samples, but NO3 and NH3 were more prevalent
than Org N in the November 10, 1998 sample. This seasonal change in water chemistry likely
resulted from late autumn nitrogen fertilizer applications in the watershed for spring wheat crops.
52
Figure 13: Sampling sites and field perimeter on the Howell farm, Marshall County, KS.
53
Another potential factor involved in the observed variation in the ammonia levels is the process of
mineralization, whereby bacteria and fungi transform Org N into inorganic forms including NH3.
Total phosphorus values ranged from 0.4 to 2.5 mg/L followed a seasonal pattern similar to TN. The
highest concentration was recorded on the earliest sampling date and resulted from the highest
recorded Org P concentration. Organic phosphorus levels declined and were consistently less than
0.3 mg/L after the first sampling date. The lowest TP value occurred on June 22, 1999. Precipitation
records from the nearest weather stations and physical evidence from the study site indicated that a
large runoff event occurred in the ten days prior to sampling while the sampler was on a programmed
delay. It is likely that this unsampled runoff event reduced the amount of phosphorus available for
transport in the runoff collected on June 22, 1999 and that the values do not accurately represent
concentrations of the first flush of total phosphorus. This data furthers the distinction between
expected first flush and baseline nutrient concentrations.
No herbicides were applied to the converted land after 1997. Thus, atrazine and metolachlor detected
in the runoff came from upslope parcels of land primarily engaged in rowcrop production. The
atrazine data followed a similar pattern to TN and TP with a seasonal trend and higher concentrations
recorded early in the study. As expected, atrazine concentrations were higher in the late spring and
early summer sample dates due to the timing of herbicide applications for corn and sorghum in the
watershed. Detectable levels of both herbicides were present in five of the six runoff sample sets.
However, metolachlor concentrations remained steady around 0.10 ug/L throughout the study, and
the mean atrazine concentration for all runoff events was less than one-tenth the HUC 8 watershed
average.
Table 21: Mean* nutrient and herbicide concentrations in first flush runoff on the Howell farm. Sampling Date Rain TN Org N NO3 NH3 TP Org P PO4 Atrazine Metolachlor
Jun 11, 98 1.20 6.61 6.01 0.52 0.15 2.46 2.19 0.27 0.25 0.09 Sep 28, 98 7.40 1.92 1.78 0.06 0.08 1.65 0.09 1.55 0.12 0.12 Nov 10, 98 3.20 3.34 0.22 1.10 2.52 1.83 0.15 1.67 0.01 0.01 Jun 22, 99 0.80 4.09 - - - 0.41 - - 0.20 0.09 Jun 2, 00 0.80 2.53 - - - 2.42 - - 0.26 0.09 Jul 17, 00 1.80 1.63 1.28 0.31 0.04 1.43 0.28 1.15 0.05 0.01
Site Mean Value 3.99 2.65 0.51 0.72 1.58 0.70 1.15 0.19 0.10 Site Median Value 3.54 1.71 0.44 0.12 1.65 0.15 1.30 0.19 0.10 HUC 8 Watershed Average1 - - 1.91 0.14 0.32 - - 2.15 - Kansas Statewide Average1 - - 1.02 0.11 0.26 - - 1.12 - Units: Rain = Inches in 48 hours prior to sampling, (TN, Org N, NO3, NH3, TP, Org P, PO4) = mg/L, Atrazine and Metolachlor = ug/L. * = Average of eight samples collected during the initial three-hour “first flush” runoff conditions. 1 = Values obtained from Appendix B, Kansas Nonpoint Source Pollution Management Plan – 2000 Update (KDHE 2000).
54
Monitoring Groundwater in the Converted Field Shallow groundwater was collected ten times from 1996 to 2000 at three sites: in the field (Cluster 1),
on the edge of the field (Cluster 2), and in the riparian area of Corndodger Creek (Cluster 3) at depths
of one, four and eight feet (Figure 14). The majority of the samples were collected by the eight–foot
lysimeters on this farm, and this eight-foot data set is the primary focus of groundwater trend analysis
(Figure 15). Measurable rainfall occurred in the 48 hours prior to groundwater sampling on eight of
the ten sampling dates, but no consistent trend in concentration data was related to the occurrence or
nonoccurrence of rainfall. The complete set of concentration data is located in Appendix E.
At Cluster 1, TN concentrations decreased steadily from over 1.5 mg/L to less than 0.20 mg/L.
Declines in NO3 and NH3 levels were largely responsible for this trend and corresponded with the
elimination of chemical fertilizer applications on the field after September 1997. Concentrations at
Cluster 2 also appeared to decrease, though not as dramatically as the first site. Nitrogen
concentrations at Clusters 3 did not follow a similar pattern. Fluctuations in NH3 concentrations were
largely responsible for the variation at Cluster 2. Variation at Cluster 3 was due to changes in Org N
levels, reflecting the seasonal growth and decomposition of vegetation in the riparian zone.
Total phosphorus concentrations differed noticeably among the sampling sites. Cluster 1 and Cluster
2 followed similar trends. Values at both sites ranged from 0.12 mg/L to 0.28 mg/L. As grazing on
the converted field increased, TP concentrations increased slightly. In comparison, samples from
Cluster 3 in the ungrazed riparian area were consistently below 0.10 mg/L. The dominant dissolved
component of the TP levels was PO4, averaging about 0.18 mg/L, while Org P values were rarely
above 0.05 mg/L. Most of the observed fluctuations were due to changes in PO4. Analyses for
atrazine and metolachlor detected small amounts of both herbicides, though the concentrations were
rarely above the laboratory minimum detection limit of 0.02 ug/L.
Figure 14:Nutrients in groundwater sampled at eight feet at three sites on the Howell farm.
0.0
0.5
1.0
1.5
2.0
Sep 7, 96
Jun 11, 98
Sep 23, 98
Jul 13, 99
Sep 9, 99
Dec 13, 99
Jul 6, 00
Jul 17, 00
Total Nitrogen
Con
cent
ratio
n (m
g/L)
Cluster123
0.0
0.1
0.2
0.3
Sep 7, 96
Jun 11, 98
Sep 23, 98
Jul 13, 99
Sep 9, 99
Dec 13, 99
Jul 6, 00
Jul 17, 00
Total Phosphorus
Con
cent
ratio
n (m
g/L)
Cluster123
55
Monitoring Surface Water: Corndodger Creek The periodic flooding of the Corndodger Creek and accompanying damage to crops and soils were
the primary influences behind the Howell’s decision to convert the cropland to perennial forage cover.
The Kansas Biological Survey collected water samples, calculated the Habitat Diversity Index (HDI)
and inventoried the aquatic macroinvertebrate community in Corndodger Creek. In addition to water
chemistry, surface water samples were analyzed for fecal coliform bacteria. Water samples were
collected at three locations on the creek (Figure 14). Site 1 was approximately 0.75 miles upstream
of the farm and was bordered by rowcropped fields. Site 2 was located closest to the groundwater
sampling sites in the converted field, and Site 3 was just downstream of where the gully that
channeled runoff from the Howell’s converted field drained into the creek. The complete set of water
quality data is found in Appendix E.
Water quality in Corndodger Creek was strongly influenced by both season and precipitation. Higher
concentrations of nutrients, herbicides and bacteria were typically found in samples from spring and
summer collected within forty-eight hours after a runoff event. The August 13, 1999; July 17, 2000
and August 7, 2000 samples were influenced by runoff events that transported nutrients, herbicides
and sediment from the watershed to the creek. During low flow conditions, concentrations of TN
ranged from 0.22 mg/L to 1.50 mg/L (Figure 16). Concentrations increased to a range of 0.58 to
2.48 mg/L when influenced by a rain event. Organic nitrogen levels remained consistent around 0.04
mg/L while NO3 concentrations ranged from 0.03 to 1.70 mg/L. This was below the HUC 8 watershed
average for NO3 of 1.91 mg/L. Ammonia levels did not change dramatically as a function of
precipitation levels. Concentrations were less than the HUC 8 watershed average of 0.14 mg/L.
except for one rain-influenced sample.
Total phosphorus concentrations were typically less than 0.20 mg/L, but rose to over 0.40 mg/L when
surface water from the creek was sampled shortly after precipitation events. Increases in PO4 were
largely responsible for the observed fluctuations in TP concentrations. Atrazine levels were usually
less than 0.5 ug/L. The only concentrations of atrazine over 0.50 ug/L came from rain-influenced
sampling events in late spring and summer. Fecal coliform bacteria counts in Corndodger Creek
varied greatly over the course of the monitoring project. Precipitation patterns and seasonal grazing
in the watershed were sources of the variation. Concentrations were often higher than the Kansas
water quality standard for primary contact recreation (swimming, mussel harvesting, boating, etc) of
200 colonies/100 mL. The standard for secondary contact (wading, fishing, hunting) of 2000
colonies/100 mL was exceeded on one occasion after a summer storm. The average concentration
of all samples from all dates was 407 colonies/100mL, which was substantially lower than both the
Kansas state average stream water quality count of 1422 colonies/100mL and the HUC 8 watershed
average of 3,236 colonies/100 mL (KDHE 2000). Studies on livestock performance and fecal coliform
56
bacteria in drinking water suggested a water quality standard of less than 1,000 colonies/100 mL for
adult livestock drinking water (A&L Great Lakes Laboratories, 2002).
Figure 15: Nutrients, atrazine and coliform bacteria in Corndodger Creek.
0.0
1.0
2.0
3.0
Jun 12, 98
Sep 9, 98
Dec 31, 98
Jun 9, 99
Aug 13, 99
Nov 11, 99
May 17, 00
Jul 6, 00
Jul 17, 00
Aug 7, 00
Total Nitrogen
Con
cent
ratio
n (m
g/L)
Site123
0.0
0.1
0.2
0.3
0.4
0.5
Jun 12, 98Sep 9, 98
Dec 31, 98
Jun 9, 99Aug 13, 99
Nov 11, 99
May 17, 00
Jul 6, 00Jul 17, 00
Aug 7, 00Total Phosphorus
Con
cent
ratio
n (m
g/L)
Site123
0.01
0.1
1.0
10.0
Oct 22, 96
Nov 25, 96
Jun 12, 98Sep 9, 98 D
ec 31, 98Jun 9, 99 Aug 13, 99N
ov 11, 99M
ay 17, 00Jul 6, 00 Jul 17, 00
Atrazine
Con
cent
ratio
n (u
g/L)
Site123
1
10
100
1000
Oct 22, 96
Jun 12, 98 Sep 9, 98 D
ec 31, 98Jun 9, 99Aug 13, 99N
ov 11, 99M
ay 17, 00Jul 6, 00 Jul 17, 00 Aug 7, 00
Coliform Bacteria Count
Col
onie
s/10
0 m
L Site123
Habitat Diversity Index and Macroinvertebrate Samples The Habitat Diversity Index (HDI) was calculated yearly in 1996,1998, 1999 and 2000 on three 50-
meter transects in Corndodger Creek. Each transect had a dominant macrohabitat of either a pool,
run or riffle. HDI scores for Corndodger Creek were comparable to HDI scores for other streams in
the same ecoregion that were considered as reference-quality streams in other studies. The
Corndodger Creek scores indicated the presence of a complex aquatic environment with many
different habitat types available to stream fauna. Cumulative scores varied slightly as a function of the
time of year of the calculation. The variation was largely due to fluctuations in stream depth, the
presence or absence of algal masses, and seasonal differences in bank vegetation. Using the one-
minute timed kick-net method, the aquatic macroinvertebrate community was sampled at each
macrohabitat included in the HDI score (Huggins and Moffet 1981). Samples were preserved and
57
identified by KBS entomologists (Table 21). The macroinvertebrate survey indicated a typical
perennial stream fauna with at least eighteen families of aquatic macroinvertebrates present.
Members of insect orders that are sensitive to pollution were found in all three stream sites on multiple
sampling occasions. Together, the HDI and macroinvertebrate sampling indicated that nonpoint
source pollution is not adversely impacting the aquatic macroinvertebrate community.
Table 22: Aquatic invertebrates found in Corndodger Creek Common Name and Order Group Order Ephemeroptera: Mayflies 1
Baetis Caenis Choroterpes Heptagenia Isonychia Leucrocuta Stenacron Stenonema Order Odonata: Dragonflies/Damselflies 1 Argia Calopteryz Enallagma Order Plecoptera: Stoneflies 1 Neoperla Perlesta Order Trichoptera: Caddisflies 1 Cernotina Cheumatopsyche Chimarra
Helicopsyche Hydropsyche Hydroptila Neotrichia Order Heteroptera: Water Striders 2 Gerris Order Hemiptera: Riffle Bugs 2 Rhagovelia Order Hemiptera: Water Boatmen 2 Corixidae Order Megaloptera: Alderflies 2 Sialis
Common Name and Order Group Order Coleoptera: Beetles 2 Cyphon Dineutus Stenelmis
Tropisternus Staphylinidae
Order Diptera: Mosquitos 2 Aedes Order Diptera: Biting Midges 2 Bezzia
Caloparyphus Dixella
Tabanus Tipula Pericoma
Order Diptera: Craneflies 2 Hemerodromia Hexatoma Limnophora
Tipula Order Amphipoda: Sideswimmers 2 Hyalella Order Decopoda: Crayfish 2 Cambaridae Order Mollusca: Gastropod Snails 2 Ancylidae
Lymnaeidiae Physidae
Order Mollusca: Bivalve Clams 2 Pelecypoda Order Clitellata: Aquatic Worms 3 Branchiobdellida Order Tricladida: Flatworms 3 Turbellari
Group 1 Taxa: Pollutant-sensitive organisms found in good quality water. Group 2 Taxa: Somewhat pollutant-tolerant organisms can be found in good or fair quality water. Group 3 Taxa: Pollutant-tolerant organisms that can be found in any quality of water. Discussion and Conclusions By changing their land use from rowcrops to pasture, the Howells were able to keep flood-prone land in
production and enhance their grazing program. Their management goals of decreasing inputs and need
for machinery were met, as livestock essentially harvested the grass and legume crop. Nitrogen
concentrations in runoff at the Howell farm appeared to decrease over the monitoring project. Total
phosphorus concentrations stayed consistent. Phosphate was more prevalent than Org P, which
suggests that sediment and livestock manure were not the only sources of phosphorus loading in runoff.
58
Upstream fertilizer applications transported onto the Howell’s fields via runoff and soluble PO4 from the
soil upslope from the sampler are likely sources. The November 10, 1998 sample set was also probably
influenced by ongoing agricultural activities in the watershed. This particular set of results reinforces the
notion that local water chemistry is determined by a number of factors, including local and upstream land
use, land management and conservation practices, and precipitation patterns.
Results of the groundwater monitoring indicated there was a persistent trend from high to low values as
one moved from the cropped and grazed field conditions to a woody riparian buffer zone. Changing from
cropland to grazing reduced the amount of nitrate and ammonia and slightly increased the amount of
phosphate in shallow groundwater in the converted field. Total phosphorus decreased from Cluster 1 to
Cluster 3 as the land cover went from forages to the riparian area. Cluster 1 did show the most changes
in water quality, which was expected due to its location in the middle of the converted field. The land
management immediately around Cluster 2 and Cluster 3 did not change as dramatically as Cluster 1.
Future monitoring of the groundwater might indicate a lag time between the change in land management
and the change in nutrient concentrations. It is estimated that The Howells avoided applying over seven
tons of nitrogen fertilizer on the converted land in the four years after the conversion to grasses and
legumes was completed. This source reduction intuitively contributed to less nutrients being transported
off of the Howell’s land to Corndodger Creek via runoff and groundwater.
59
Tim and Bridget Kunard, Miami County Watershed: Hillsdale Lake Water Quality Concerns: Nutrients and herbicides in
runoff from cropland into Hillsdale Lake. Demonstration: Convert cropland to perennial
grassland and implement a management-intensive grazing system.
Monitoring: Runoff, groundwater and soils from converted cropland.
Photo 15: Perennial grassland converted from cropland in the foreground with go-back prairie in the background.
The Kunard farm includes 112 acres of cropland and
go-back land (refers to cropland allowed to “go back”
to more native set of grasses, legumes and forbes)
near Hillsdale Lake in Miami County, KS. Increasing
expenses associated with farming small grains and
concerns about runoff, erosion and water quality led the Kunards to adopt a change in land management.
The goal of the conversion was to reduce and eventually eliminate the need for fertilizer and herbicide
inputs while keeping the land in production. Seventy-five acres of cropland were planted to a mixture of
grasses and legumes and a management intensive grazing (MIG) system was established. The
remaining land was separated into grazing paddocks by high tensile electric fence, and water line was
trenched in spring 2000. The grasses and legumes established well enough to put thirty head of cattle
into the system by the following summer.
A monitoring program was established on the Kunard farm for two reasons. First, the farm’s location near
Hillsdale Lake was advantageous, as other KBS monitoring projects that involved Hillsdale could tie in
land use and nutrient concentration data from the Kunard farm. Secondly, the conversion process was
not yet underway when the Kunards applied for their Clean Water Farms grant, making the collection of
pre-conversion data possible. The monitoring project on the Kunard farm was designed to provide data
on the effects of conversion of cropland to perennial grasses and legumes on runoff and groundwater
quality. Some difficulties were encountered during the monitoring project, and the number of sample sets
was limited compared to the other farms monitored by KBS. However, the data provides valuable
information about nutrient and herbicide concentrations in runoff and groundwater during the land
conversion and the role of buffer strips in filtering nutrients and herbicides from runoff and groundwater.
Soil Characteristics of the Monitored Field The field that the Kunards converted to perennial grass cover was relatively level and drained to an
intermittent stream. Soils found in that field are from the Woodson and Summit series (Penner 1981).
The Woodson silt loam is deep, nearly level and somewhat poorly drained and is found on uplands.
Permeability is very slow, Most areas of Woodson silt loam are dedicated to cultivated crops and
perennial grasses. The Summit silty clay loam is more sloped and better drained than the Woodson soil.
60
Most areas of these soils in Miami County are used for cultivated crops. Soil samples were taken during
the fall of 1998 and 1999 and the following spring 2000 (Table 22). Results of the soils analyses
indicated seasonal differences in nitrogen and phosphorus levels. Total Kjeldahl Nitrogen and TP both
increased noticeably between the Fall 1999 and Spring 2000 samples. Since no fertilizer was applied
after the grass was established, the observed increases in TKN and TP are more likely related to
increases in organic matter due to the interseeding of grasses and legumes. Aggregate stability values
dropped slightly but are still in the same range as values from other converted fields monitored by KBS.
Comparative values from the go-back prairie were higher for TKN, TP and aggregate stability than from
the managed field samples taken on the same data in Spring 2000.
Table 23: Soil quality indicators and chemistry from the Kunard’s converted field. Parameter Fall 1998 Fall 1999 Spring 2000 Spring 2000 Managed Field Mean Cover wheat/clover fescue/clover fescue/clover go-back prairie Total Kjeldahl N (mg Org N+NH3/kg soil) 1540 1577 1746 3125 1621 Nitrate (mg NO3/kg soil) 9 - - - - Total P (mg P/kg soil) 372 373 414 449 386 Phosphate (mg PO4/kg soil) 18 - - - - Dissolved Organic C (mg C/ kg soil) 183 - - - - pH 5.93 - - - - Aggregate % 99 98 92 95 96 Monitoring Runoff from the Converted Field The runoff sampler at the Kunard farm was situated in an intermittent stream to collect runoff from the
converted field and surrounding unconverted area. Both runoff and groundwater samplers were installed
early on in the conversion process, so data reflected the majority of the conversion. The Kunard farm
turned out to be the most challenging of the eight farms monitored by KBS. Rodents damaged the runoff
sampler and lysimeters by gnawing through the intake tubes. Three sets of runoff samples from fall 1999
and spring 2000 were missed entirely as holes in the intake tubing prevented the peristaltic pump from
generating enough suction to collect sample. Runoff was successfully sampled three times in two years.
Total nitrogen values were consistently low among the three runoff sampling sets, ranging from 2.4 to 2.7
mg/L (Table 23). Organic levels increased from spring to fall, probably as a function of increased plant
biomass. The observed decrease in NO3 levels and the minute changes ammonia levels were likely
related to the elimination of chemical fertilizer inputs after the initiation of the conversion from rowcrops to
perennial grass cover.
Total phosphorus concentrations decreased over the course of the monitoring project. Values ranged
between 0.6 and 0.8 mg/L. Organic phosphorus levels were consistent between the first two sample sets
while phosphate levels decreased. The June 28, 1999 samples were not collected within the allocated
holding time for organic and inorganic constituent analyses to take place. Herbicide concentrations were
61
62
Figure 16: Sampling sites and field perimeters on the Kunard farm, Miami County, KS.
quite low at the Kunard farm. Atrazine data varied seasonally. June samples for both 1998 and 1999
had mean concentrations of 0.12 ug/L. Values from the October sample were lower than the minimum
detection level of 0.02 ug/L.
Table 24: Mean* nutrient and herbicide concentrations in first flush runoff on the Kunard farm. Sampling Date Rain TN Org N NO3 NH3 TP Org P PO4 Atrazine Metolachlor Jun 22, 98 1.5 2.51 1.76 0.71 0.04 0.80 0.32 0.48 0.12 0.01 Oct 5, 98 2.2 2.43 2.22 0.16 0.06 0.67 0.33 0.34 0.02 0.01 Jun 28, 99 3.6 2.65 - - - 0.56 - - 0.12 0.08 Site Mean Value 2.53 1.99 0.43 0.05 0.68 0.32 0.41 0.09 0.08 Site Median Value 2.30 1.89 0.44 0.04 0.67 0.30 0.42 0.12 0.08 HUC 8 Watershed Average1 - - 0.45 0.07 0.16 - - 1.79 - Kansas Statewide Average1 - - 1.02 0.11 0.26 - - 1.12 - Units: Rain = inches in 48 hours prior to sampling, (TN, Org N, NO3, NH3, TP, Org P, PO4) = mg/L, Atrazine and Metolachlor = ug/L.* = Average of eight samples collected during the initial three-hour “first flush” runoff conditions. 1 = Values obtained from Appendix B, Kansas Nonpoint Source Pollution Management Plan – 2000 Update (KDHE 2000). Monitoring Groundwater in the Converted Field One cluster of lysimeters was placed in a section of go-back land adjacent to the converted field and near
the intermittent stream. An impervious clay layer six feet below ground level prevented the installation of
the eight-foot lysimeter, so a pair of four-foot lysimeters and a single one-foot lysimeter was installed.
The area that contributed groundwater to the samples was mostly converted cropland, but nearly 40
acres of go-back land were directly around the cluster. Samples were collected six times from the four-
foot lysimeters. As with other farms monitored by KBS, the one-foot lysimeters did not collect enough
sample volume for nutrient and herbicide analyses, and the groundwater data presented here is taken
exclusively from the four-foot lysimeters.
Several trends were apparent in the nitrogen and phosphorus data from groundwater samples. Total
nitrogen concentrations ranged from 0.14 to 0.69 mg/L. Nitrate levels steadily decreased over the course
of the project. Organic nitrogen was the primary nitrogen constituent in groundwater in most samples.
Most values were between 0.2 and 0.4 mg/L. Ammonia levels were usually less than 0.02 mg/L.
Phosphorus concentrations ranged from 0.02 to 0.09 mg/L. Organic phosphorus values were
consistently around 0.01 mg/L, while phosphate levels showed more variation. Phosphate was the
primary phosphorus constituent in groundwater and ranged from 0.01 to 0.08 mg/L.
63
Figure 17: Nitrogen and phosphorus compounds in shallow groundwater from the Kunard farm
0.0
0.2
0.4
0.6
0.8
Aug 4, 98
Sep 16, 98
Jul 2, 99
Dec 14, 99
May 3, 00
Jul 12, 00
Nitrogen Compounds C
once
ntra
tion
(mg/
L)
TNOrg NNO3NH3
0.0
0.1
0.2
0.3
Aug 4, 98
Sep 16, 98
Jul 2, 99
Dec 14, 99
May 3, 00
Jul 12, 00
Phosphorus Com pounds
Con
cent
ratio
n (m
g/L)
TPOrg PPO 4
Discussions and Conclusions The monitoring program established on the Kunard farm supplied a small set of runoff and groundwater
data on the conversion process from grain crops to forage crops. The Kunard farm is a good candidate
for continued monitoring, as the collected data is more representative of baseline conditions for converted
cropland than of a rotational grazing system. Cattle were seldom on the converted land until after the
monitoring program was completed. Unfortunately, several sets of runoff samples were missed due to
rodent damage and equipment failure. A larger sample set would have lent more credibility to the notion
that the conversion from cropland to pasture was responsible for the low levels of TN, TP and atrazine
sampled in the runoff and groundwater.
Concentrations of TN and TP in runoff and groundwater were lower than other converted fields monitored
by KBS. Though it is difficult to generalize about water quality from small sample sets, one possible
factor behind the low concentrations was the filtering of nutrients from runoff and groundwater by the
undisturbed go-back land around the runoff sample and lysimeter cluster. In essence that land acts as a
buffer, slowing down runoff velocity, absorbing dissolved nutrients and settling suspended sediment out of
the runoff. Groundwater concentrations of TN and NO3 appeared to decrease in over the course of the
monitoring project. This is most likely related to the elimination of chemical fertilizers to the converted
land. Detectable herbicide levels were rarely found in groundwater samples.
The Kunard’s conversion from rowcrops to rotational grazing contributed to a reduction of nitrogen
fertilizer applications on the 75 converted acres by over three tons. Results from the monitoring program
suggested that the Kunard farm contributed very little nonpoint source pollution to area surface waters
such as Hillsdale Lake and to shallow ground water.
64
Rod and Linda Peters, Marion County
Watershed: South Cottonwood River Water Quality Concerns: Nutrients and herbicides in
runoff from no-till crop fields. Demonstration: Incorporate legumes and cover
crops into a no-till crop rotation and redesign bermless grassed waterway to control runoff from crop fields.
Monitoring: Runoff and groundwater from no-till fields, soils from two no-till fields and one tilled field.
Photo 16: No-till corn and residue at the Peters farm.
The Peters operate a 1,300-acre farm with cropland
and cattle in Marion County, KS and have used no-till
practices since 1995. Crops included wheat, grain
sorghum, soybeans, corn, cotton and sunflowers.
The Peters combined no-till principles, long-term crop
rotations, high crop residue maintenance and cover
cropping to promote soil conservation on their farm. Water quality benefits of this management plan
include increased permeability and water storage capacity in the soil, reduced velocity and volume of
runoff flowing across fields, perennial ground cover in the form of residue and stubble, and decreased
amounts of sediment available for transport in runoff. As another water protection measure, a bermless
waterway was shaped and extended to decrease runoff flowing across the fields and to better control
overflow from a small pond off the fields to the creek.
The Kansas Biological Survey set up a monitoring program for two no-till fields on the Peters farm in
1998. Though the monitored fields were not part of the crop rotation plan implemented through this
study, they offered KBS several opportunities unique among the eight studied farms. KBS wanted to
monitor recently converted no-till fields to better compare conversion effects from the switch in
management practices on water quality and soil development with different land conversion practices (i.e
cropland to grassland or stripped crop rotations) on other monitored farms.
Soil Characteristics of the Monitored Fields One of the desired results of the Peters’ switch to no-till farming was soil enhancement and conservation.
Increases in soil health and stability positively affect natural soil fertility and decrease competition from
weeds. Soil samples were taken from three locations in and around the Peters farm (Figure 19). Fields 1
and 2 were no-till fields, and Field 3 was a neighboring conventionally tilled field. Multiple samples were
taken at each site and then combined into a single sample per site to account for local variability in soil
chemistry. The soils from the three fields are classified in the Wells and Verdigris Series (Horsch et al,
1983). Fields 1 and 3 have a Wells loam, a deep, well-drained soil found on side slopes near drainage
65
ways. The Wells soils are upland soils and are not as prone to flooding as the Verdigris soils. Field 2 has
a Verdigris silt loam, which is a deep, nearly level and moderately well drained soil found on flood plains.
The Verdigris soils are periodically flooded for brief periods and are siltier than the Wells soils. Results of
the soil analyses indicated annual fluctuations for nitrogen and phosphorus compounds at all three sites.
Nitrate levels in Fields 1 and 2 were among the highest recorded in the monitoring project and reflected
spring nitrogen fertilizer applications. Phosphate values contrasted greatly between the no-till fields and
the tilled field, with values from the tilled field less than one percent of the no-till fields. The no-till fields
also and higher dissolved organic carbon, TKN and aggregate stability values than the neighboring field.
These higher values point to the soil-building benefits of no-till farming.
Table 25: Soil chemistry and quality indicators for fields under two land management practices.
Field One: No-till side slope 1998 1999 2000 Crop milo milo soybeans Total Kjeldahl N (mg Org N+NH3/kg soil) 2032 1229 1708 Nitrate (mg NO3/kg soil) 157 - - Total P (mg P/kg soil) 569 360 398 Phosphate (mg PO4/kg soil) 130 - - Dissolved Organic C (mg C/kg soil) 78 - - pH 5.30 - -
Aggregate (%) 88 98 92
Field Two: No-till flood plain 1998 1999 2000
Crop corn beans corn Total Kjeldahl N (mg Org N+NH3/kg soil) 2023 1528 1932
Nitrate (mg NO3/kg soil) 155 - - Total P (mg P/kg soil) 584 496 565 Phosphate (mg PO4/kg soil) 140 - - Dissolved Organic C (mg C/kg soil) 76 - - pH 4.97 -
Aggregate (%) 82 98 98
Field Three: Conventional tillage 1998 1999 2000 Crop wheat wheat wheat Total Kjeldahl N (mg Org N+NH3/kg soil) 811 996 1277 Nitrate (mg NO3/kg soil) 71 - - Total P (mg P/kg soil) 390 491 567 Phosphate (mg PO4/kg soil) 1 - - Dissolved Organic C (mg C/kg soil) 43 - - pH 7.13 - - Aggregate (%) 91 97 81
Photo 18: Field 3 is conventionally tilled and managed for small grains and rowcrops.
Photo 17: During the fall and winter, crop residue is left standing on Field 2 for soil cover. In the background, Field 1 is planted in spring wheat.
66
67
Figure 18: Sampling sites and field perimeters at the Peters farm, Marion County, KS.
Monitoring Runoff from the No-Till Fields The runoff sampler was positioned in a low area in Field Two to
collect water after it flowed over the two no-till fields to the grassed
waterway before exiting the farm to the creek. The grading and
extension of the grassed waterway were completed in October
1999. Samples were collected seven times from spring 1998 to
winter 1999. Several other sets were collected, but insufficient
sample volume and rodent damage compromised these sets and
prevented their inclusion in the water quality analyses. No storms
activated the runoff sampler during the spring and summer of 2000,
so comparisons of runoff from before and after the work on the
grassed waterway are unavailable. Photo 19: Installing a sampler to collect runoff from the Peters no-till fields.
Though ranges of values for each of the nutrients and herbicides are wide, apparent trends help explain
those ranges (Table 25). Total nitrogen values ranged from 0.3 mg/L to 8.5 mg/L. Organic nitrogen was
frequently more prominent than the NO3 component in the TN value. Lower values appeared on October
2 and October 11, 1998. On these dates the sampling unit was programmed to start at a certain time
instead of by float switch activation. This was done to allow existing runoff from previous storms to
subside. Unsampled first flush runoff that flowed through the sample site before the programmed delay
allowed sampler activation likely decreased the amount of organic nitrogen available for transport in
runoff waters on those three dates. The highest mean TN values appeared on August 1, 1999 and
November 22, 1999. These two runoff events occurred after earthwork for the bermless waterway
extension was started, which exposed soil just upfield of the runoff sampler. Samples not influenced by a
delay on the sampler program activation or earthwork associated with the waterway extension had a
much tighter range of values, 2.5 to 5.6 mg/L. Runoff from the final sampling event was generated by
melting snow and was not as forceful as a thunderstorm would have been. As such, runoff leaving the
fields was essentially free of sediment.
Ammonia concentrations ranged from 0.03 mg/L to 0.12 mg/L. The lowest values came from the time-
activated samples. Unsampled runoff events occurring while the sampler was waiting for water levels to
recede decreased potential soluble nutrients available for sampling. Samples collected on dates
unaffected by the programmed delay had NH3 levels between 0.10 and 0.12 mg/L.
Some trends were also apparent in the phosphorus data. Values for TP ranged from 0.01 mg/L to 3.5
mg/L. Similar to trend in TN, the highest value came from samples taken after the earthwork for the
waterway exposed more soil to erosion. The range of TP values tightened, 0.5 mg/L to 1.7 mg/L when
68
only non-delayed sample events before the waterway extension were considered. Phosphate was
usually the more prominent constituent of the TP levels on the Peters farm.
A persistent seasonal trend was readily apparent in atrazine and metolachlor concentrations. Annually,
concentrations were higher in spring samples and decreased over the growing season in both 1998 and
1999. Atrazine concentrations in first flush runoff did exceed the HUC 8 watershed average of 1.54 ug/L.
Runoff samples collected in June of each year had concentrations over one hundred times that of
corresponding fall samples. Herbicide levels were expected to be higher than the other farms in the
study, since chemical weed control is one important component of no-till practices. The Peters hope to
continue reducing the need for herbicides on their farm.
Table 26: Mean* nutrient and herbicide concentrations in first flush runoff on the Peters farm. Sampling Date Rain TN Org N NO3 NH3 TP Org P PO4 Atrazine Metolachlor Jun 22, 98 2.20 3.06 1.99 0.95 0.12 0.49 0.35 0.14 2.45 0.65 Oct 2, 981 4.10 1.46 1.03 0.40 0.03 1.30 0.07 0.98 0.10 0.16 Oct 11, 981 1.50 0.32 0.12 0.16 0.03 0.01 0.00 0.01 0.02 0.03 Nov 10, 981 5.80 0.79 - - - 0.26 - - - - Jun 16, 99 0.50 3.37 - - - 0.34 - - 45.36 0.77 Aug 1, 99 0.40 5.79 0.45 5.24 0.10 0.44 0.14 0.30 27.66 0.09 Nov 22, 99 2.40 19.53 - - - 3.53 - - - - Site Mean Value2 7.25 1.56 2.22 0.11 1.29 0.25 0.56 21.11 0.54 Site Median Value2 4.35 1.36 0.93 0.09 0.56 0.16 0.27 2.77 0.57 HUC 8 Watershed Average3 - - 0.90 0.09 0.17 - - 1.54 - Kansas Statewide Average3 - - 1.02 0.11 0.26 - - 1.12 - Units: Rain = Inches in 48 hours prior to sampling, (TN, Org N, NO3, NH3, TP, Org P, PO4) = mg/L, Atrazine and Metolachlor = ug/L. * = Average of eight runoff samples collected during initial three-hour first flush conditions. 1 = Sampler programmed for delayed activation; values not representative of true first flush concentrations. 2 = Only true first flush concentrations (e.g. no delayed-activation samples) used to calculate site mean and median values 3 = Values obtained from Appendix B, Kansas Nonpoint Source Pollution Management Plan – 2000 Update (KDHE 2000).
Groundwater Shallow groundwater was collected eight times from 1998 to 2000 by one cluster of lysimeters at depths
of one, four and eight feet. The cluster was installed at the edge of the no-till field near the runoff
sampler. As on the other farms, most groundwater samples came from the four-foot and eight-foot
lysimeters. Normally the lysimeters were left under a vacuum for 10-14 days before sample retrieval.
Raw concentration data is presented in Appendix G.
Total nitrogen in groundwater ranged from 0.04 mg/L to 1.5 mg/L, and most of the samples had
concentrations less than 0.3 mg/L (Figure 20). Values at eight feet were frequently greater than
corresponding values at four feet. The two highest TN values were sampled at eight feet on December 2,
1998 and September 7, 1999 and resulted from spikes in NH3 and NO3 respectively. This could be due to
the nutrients’ downward movement in the soil column driven by gentle storms that occurred while the
lysimeters were pressurized. An increase in soil moisture available for collection on December 2, 1998 is
also supported by the fact that the lone sample from the one-foot depth was taken on that date.
69
Ammonia concentrations were higher at the four-foot depth compared to the eight-foot sampling depth in
four out of five events where both depths were sampled. Typical values for NH3 were lower than 0.04
mg/L ranged from less than 0.01 mg/L to 0.8 mg/L.
Total phosphorus values ranged from 0.02 mg/L to 0.13 mg/L. Nearly all the samples had values lower
than 0.06 mg/L. Phosphate, which is more soluble than Org P, was by far the dominant component of the
TP values. The highest value for TP on December 2, 1998 was most likely affected by rain leaching
soluble phosphate down the soil column to the collecting cup of the lysimeter. On this and subsequent
sampling dates, TP concentrations were highest in the shallower samples and decreased with depth.
Atrazine concentrations fluctuated on a seasonal basis from an off-season low of 0.02 ug/L to a July high
of 1.29 ug/L. Most values were below 0.10 ug/L. Atrazine concentrations were higher at four feet than
eight feet on every sampling date when both depths were sampled. Precipitation patterns were not as
influential on atrazine concentrations as they were on nutrient concentrations.
Figure 19: Nutrient and herbicide concentrations in shallow groundwater on the Peters farm.
0.0
0.5
1.0
1.5
Jul 22, 98
Aug 4, 98
Dec 2, 98
Jul 15, 99
Sep 7, 99
Dec 8, 99
May 31, 00
Jul 19, 00Total Nitrogen
Con
cent
ratio
n (m
g/L)
Feet148
0.0
0.02
0.04
0.06
0.08
0.10
0.12
0.14
Jul 22, 98
Aug 4, 98
Dec 2, 98
Jul 15, 99
Sep 7, 99
Dec 8, 99
May 31, 00
Jul 19, 00
Total Phosphorus
Con
cent
ratio
n (m
g/L)
Feet148
.001
0.01
0.1
1.0
Jul 22, 98
Aug 4, 98
Dec 2, 98
Jul 15, 99
Sep 7, 99
Dec 8, 99
May 31, 00
Am m onia
Con
cent
ratio
n (m
g/L)
Feet
48
1
0.01
0.10
1.00
10.00
Jul 22, 98
Aug 4, 98
Dec 2, 98
Jul 15, 99
Sep 7, 99
Dec 8, 99
May 31, 00
Jul 19, 00
Atrazine
Con
cent
ratio
n (u
g/L)
Feet48
70
Discussion and Conclusions The Peters farm was included in the Kansas Biological Survey monitoring efforts due to the unique nature
of the project. The Peters’ high level of involvement in the monitoring project was key to successful
monitoring. Observational data included a decrease in runoff leaving the farm after the no-till system was
established. Water leaving the farm carried less sediment than prior to the conversion to no-till. Soil was
kept in place by the regimented crop rotations and residue maintenance. Soil organic matter and
aggregate stability percentage increased over the course of the monitoring project.
There were no major differences in nutrient levels in runoff and groundwater between Peters and other
farms. Total nitrogen and TP concentrations were consistently low, though noticeable increases occurred
in runoff samples when the grassed waterway was under construction. The delayed samples had lower
TN and TP levels and were indicative of the expected baseline levels of TN and TP in surface water in the
area. As expected, higher levels of herbicide were found in the first flush runoff samples compared to
other farms that eliminated herbicide applications, but the shallow groundwater did not appear to be
contaminated by herbicides. Following recommended application procedures and timing applications
helped the Peters minimize the amount of fertilizer and herbicide leaving the farm in runoff and shallow
groundwater.
71
72
Photo 20: A rancher counts cattle before transferring them to another grazing paddock.
Alan and Sharon Hubbard, Pottawatomie County Watershed: Blue River, Tuttle Reservoir Water Quality Concerns: Shoreline erosion and
physical degradation of cattle watering sites.
Demonstration: Develop watering system including storage tanks and underground lines to limit livestock access to ponds and streams
Monitoring: Three cattle-watering ponds and one developed spring
Located in the Flint Hills near Olsburg, KS, the
Hubbard ranch included nearly 5,300 acres of
leased land and another 800 acres of managed brome and go-back grass. The management shift from
total continuous grazing to a rotational grazing system was made in 1981 after the Hubbards determined
they could effectively and profitably manage the complex schedules of rotations necessary to make such
a management intensive grazing (MIG) system work. The 910 acres devoted entirely to the MIG system
were divided into thirty-four paddocks with permanent and temporary fence. Paddock size ranged from
17 to 40 acres. Forage was mainly native grasses, but several paddocks were in managed brome. Each
paddock has access to a watering point. To prevent overgrazing, cattle were kept in each paddock from
one to three days, depending on the condition of the forage, to prevent overgrazing. Currently, the MIG
rotation system supports approximately 300 beef cattle year round and another 1,500 custom-grazed
steers from early May through August.
The Hubbard’s Clean Water Farms Project demonstration involved developing alternatives to pond and
stream use as water supplies in the MIG system. Rotating hundreds of cattle through paddocks with
ponds and streams had deleterious effects on cattle-watering sites. Even though cattle were present in
most paddocks for only several days in each grazing season, pond and stream banks suffered episodic
physical damage from hoof action, and livestock waste impacted the water quality. To prevent further
damage while providing clean water to all the MIG paddocks, the Hubbards limited access to the ponds
and streams and developed a gravity-supply watering system to tanks in the MIG paddocks. A 10,000
gallon storage tank was put in place in 1998. Water line was laid from the storage tank to three watering
sites in the pasture. Each site was situated to provide water for four to six grazing paddocks. Other
components to the Hubbard’s new watering system included a developed spring and a cattle ramp that
restricted access to one pond to a rocky shoreline less vulnerable to erosion.
Monitoring livestock watering ponds on the Hubbard ranch The monitoring project established by the Kansas Biological Survey on the Hubbard ranch involved
collecting grab samples from three of the ponds in MIG paddocks (Figure 21). The ponds were selected
73
Figure 20: Pond sites and MIG system outer perimeter at the Hubbard ranch, Pottawatomie County, KS.
based on differences in surface area and watershed size and their close proximities to one another. The
rocky soil of the Flint Hills prevented the installation of lysimeters for shallow groundwater sampling, so
KBS collected samples from a developed spring starting in winter 1999.
Photo 21: Pond 1 is the largest of the monitored ponds. This rocky shoreline if the future location of a watering site.
With a surface area of nearly four acres, Pond 1
was the largest monitored pond and the only one
large enough to ecologically function as a natural
pond. Constructed in 1964, it drained an area that
includes former cropland to the east. Most of the
shoreline was exposed soil, but one particularly
rocky area was slated to have a cattle-access-
limiting ramp installed. Three sampling sites were
established on Pond 1, and the water quality
information presented in this pond’s profile is the
average of those three sites. This pond was not fenced off before or during the monitoring project.
Just upslope from Pond 1 was Pond 2, which
originally served as a settling basin for runoff flowing
into Pond 1. The water in Pond 2 was noticeably
turbid during the sampling project, and only a few
macrophytes became established in the littoral zone.
With steep banks and a shallow average depth,
Pond 2 was considered too small to serve as a
primary watering supply for cattle, and it was
cordoned off with electric fence after the storage tank
and waterlines were installed. Now that the watering
system has been established, it is likely that Pond 2
either will silt in naturally or will be bulldozed in to
provide more grazing area in that paddock.
Photo 22: Shoreline vegetation around Pond 2 filled in after cattle were fenced out. The one bare spot at left is the dam.
Pond 3 was slightly less than one acre in size and
received water from a different drainage basin than
the other two monitored ponds. Constructed in the
1940’s, Pond 3 was usually quite turbid and silted in
noticeably over the course of the monitoring project.
Photo 23: Repairs to the spillway of Pond 3 left the bank exposed before shoreline vegetation was established.
74
Total nitrogen levels in all three ponds typically ranged from 0.90 to 3.50 mg/L with several outliers
(Figure 22). In most sample sets, Pond 1 had slightly higher TN concentrations than Ponds 2 and 3.
Data outliers for Ponds 2 and 3 corresponded with cattle moving through the paddocks containing those
ponds around the time samples were gathered. Increases in NH3 levels were partly responsible for the
increases in TN. Detectable levels of NO3 were rare for Ponds 2 and 3, but samples from Pond 1
frequently had detectable amounts of NO3. Organic nitrogen was proportionally a greater nitrogen
constituent than NO3 in all three ponds. Sources of Org N were likely fine particulate organic matter
(FPOM) and algae suspended in the ponds. Nitrate concentrations in samples from the developed spring
were higher, between 4.0 and 5.0 mg/L, reflecting the concentration of NO3 associated with the
groundwater that fed the spring. These values were similar to NO3 concentrations in groundwater
sampled from the Townsend farm.
Total phosphorus levels were more scattered than TN concentrations and differed more among the
ponds. Concentrations of TP at all three ponds ranged from 0.05 to 0.60 mg/L. Ponds 2 and 3 contained
detectable levels of PO4 on several occasions, but Org P was the dominant TP constituent. Similar to
Org N, this trend is attributed to FPOM suspended in the water column. Pond 1 had relatively consistent
levels of Org P, but the trend for PO4 was not similar to the other ponds. Phosphate levels increased
from the October 19, 1998 sampling date to the July 14, 1999 sampling date. The Hubbard’s year-round
cattle were confined to the paddock around Pond 1 during the winter season, but the minor impacts
expected from a small herd of cattle do not explain this seasonal increase in nutrient concentration by
themselves. Decreased phosphate uptake by algal communities could also explain the winter season
increase in PO4 in pond 1, but PO4 levels did not similarly increase in the winter of 1999. Rainfall records
imply that rainfall events before the sampling events were sources of nutrient loading, and variation in
nutrient concentration are likely a function of the combination of cattle being present in the watershed and
a storm carrying sediment and fecal matter to the ponds. Increases in both Org P and PO4 were noticed
in Ponds 2 and 3 after cattle had been rotated through the paddocks containing those ponds and after
storms stirred up the pond water.
Atrazine was detected in small amounts in each of the three ponds, but levels never approached the HUC
8 watershed average of 1.27 ug/L. Only three of the forty-eight samples had levels higher than 0.25 ug/L.
Since no atrazine was applied in the immediate watershed in the 20 years prior to monitoring, the small
amount of atrazine present in the ponds most likely came from atmospheric deposition of atrazine applied
to rowcropped fields upwind of the ranch.
Fecal coliform analyses were conducted on pond and spring samples. No bacteria colonies were found
in samples from the developed spring. Bacteria counts for each of the ponds displayed variation as a
function of rainfall and the timing of the sampling relative to cattle access to the ponds. It is important to
note that cattle are not the only source of fecal coliform bacteria in surface water, as waterfowl and native
75
mammals that visit the ponds release the bacteria in their feces. On four occasions, the bacteria levels
were higher than the HUC 8 watershed average of 1,289 colonies/100 mL. Studies on livestock
performance and fecal coliform bacteria in drinking water suggested a water quality standard of less than
1,000 colonies/100 mL for adult livestock drinking water (A&L Great Lakes Laboratories, 2002).
Figure 21: Nutrients, herbicides and coliform bacteria levels found in three stock ponds and a natural spring on the Hubbard ranch.
0.0 1.0 2.0 3.0 4.0 5.0 6.0
Jun 9, 98Jun 12, 98Jul 9, 98Jul 30, 98Sep 9, 98O
ct 19, 98D
ec 9, 98Jun 9, 99Jul 1, 99Jul 14, 99Jul 26, 99N
ov 11, 99D
ec 7, 99M
ay 18, 00Jul 10, 00Jul 17, 00
Total Nitrogen
Con
cent
ratio
n (m
g/L)
Pond123spring
0 .0
0 .1
0 .2
0 .3
0 .4
0 .5
0 .6
Jun 9, 98Jun 12, 98Jul 9, 98Jul 30, 98Sep 9, 98O
ct 19, 98D
ec 9, 98Jun 9, 99Jul 1, 99Jul 14, 99Jul 26, 99N
ov 11, 99D
ec 7, 99M
ay 18, 00Jul 10, 00Jul 17, 00
T o ta l P ho s p h oru s
Con
cent
ratio
n (m
g/L)
P o n d123s p rin g
0.0
0.1
0.2
0.3
0.4
Jun 9, 98Jun 12, 98Jul 9, 98Jul 30, 98Sep 9, 98O
ct 19, 98Jun 9, 99Jul 1, 99Jul 14, 99Jul 26, 99N
ov 11, 99D
ec 7, 99M
ay 18, 00Jul 10, 00Jul 17, 00
A trazine
Con
cent
ratio
n (u
g/L)
P ond123spring
1
10
100
1000
10000
Jun 9, 98Jun 12, 98Jul 9, 98Jul 30, 98Sep 9, 98O
ct 19, 98D
ec 9, 99Jun 9, 99Jul 1, 99Jul 14, 99Jul 26, 99N
ov 11, 99D
ec 7, 99M
ay 18, 00Jul 1, 00Jul 17, 00
Fecal C oliform Bacteria
Col
onie
s/10
0 m
L
Pond123
Discussion and Conclusions Converting to a management intensive grazing system allowed the Hubbards to increase their stocking
rates and obtain a higher return of pounds per acre in their cattle. The modifications and additions to the
MIG watering system permitted an increase in the number of grazing paddocks; in return, the Hubbards
dropped several conventionally grazed pastures from the rotation. Results of the monitoring program
indicated that cattle rotations release episodic pulses of NPSP in the form of pathogens, TN and TP.
KBS observed decreased cattle trailing, hoof damage and erosion on pond and stream banks that
restricted from access to livestock. Developing alternative watering sources and restricting access to
natural aquatic systems improved the farmers’ economic return through increased stocking without the
concurrent damage to natural aquatic systems by the increased numbers of livestock.
76
Project Review and Conclusions This NPSP monitoring project assessed the impacts of the implementation of agricultural best
management practices on water quality at the individual field scale on eight Kansas farms. Goals of the
project were twofold: 1) quantify edge-of-field concentrations of nutrients and selected herbicides in field
runoff, shallow groundwater and surface water; and 2) identify weather and management factors that
influence field losses of specific nutrient and herbicide constituents of consequence to water quality.
Initial objectives were modified to ensure collection of appropriate data relative to the relevant water
quality and land management issues. Hypotheses testing included both temporal and spatial factors that
were thought to affect water quality variables. Three different temporal scales were examined to assess
differences in water quality: multiple years, seasons and single management or weather events (i.e. field
applications of fertilizers, tillage). Spatial hypotheses included tests related to changes in runoff water
quality entering and exiting specific fields, groundwater quality at different depths, and water quality
changes associated with various land uses. The results of this study built on the knowledge base of
edge-of-field water quality data under different land management conditions in Kansas and the
surrounding region.
Monitoring Nonpoint Source Pollution This small-scale monitoring effort offered opportunities to collect many distinct types of data. The Kansas
Biological Survey applied adaptive study approaches in regards to designing and installing field-scale
agricultural NPSP monitoring projects. Defining the hypotheses relevant to the specific water quality
issues and identifying the types of data necessary to support or challenge those hypotheses were
necessary to fit the monitoring goals with the proper sampling instrumentation. The initial experimental
designs of several projects were altered to take advantage of new opportunities that emerged during the
study. Additionally, on several farms, the original goals were also modified to respond to changes in
expected management and delays in BMP implementation. Involving the farmer in all stages of the
monitoring project increased the likelihood of successful sample collection and insightful data
interpretation.
Once monitoring objectives and water quality hypotheses were identified, development of experimental
designs and appropriate instrumentation of each farm was critical to the successful sampling of runoff and
groundwater. Sampling regimes were designed to incorporate stochastic events (i.e. runoff-generating
storms) within a more seasonal sampling framework for shallow groundwater and surface water. The
placement of semi-permanent sampling equipment was limited by topography, land use and on-going
daily farm operations; sites also had to be accessible in wet weather. Additionally installing multiple
runoff samplers and/or lysimeter clusters on a farm provided valuable comparative data for spatial
hypotheses testing.
77
Runoff Sampling and Results As one major pathway for NPSP to be transported from individual fields to downstream water bodies,
surface runoff has been a primary focus of monitoring projects in both field and laboratory NPSP studies.
Monitored runoff events generally occurred several times during each sampling season (May through
November) and were generated by precipitation amounts ranging from 0.5 to 4.7 inches. This project
used an event mean concentration (EMC), calculated by averaging the concentrations of six to eight
discrete samples collected in the initial three-hour runoff period of a runoff event, as the representative
quantity for each runoff event. Typically, EMCs are flow-weighted averages determined by compositing
(in proportion to flow rate) a set of samples, taken at various points in time during a runoff event, into a
single sample for analysis (Lehner et al, 1999). The flow-weighted EMC is multiplied by the measured
flow volume to arrive at loading values for individual runoff events and yearly loading contributions
(Owens et al, 1991). However, in this project, the largely undefined drainage channels, shallow flow
characteristics and the inability to install permanent weirs prohibited the measurement of discharge and
flow. Furthermore, the flow-weighted EMC does not take into account variability in runoff quality, and it
was not uncommon during this monitoring project for samples collected during a given runoff event to
differ in concentration by a factor of 10 or more. Pulses of higher concentrations of nutrients and
herbicides, whose significance is limited when samples are composited for flow-weighted EMCs, can
have adverse effects on aquatic biological communities, especially fish and pollution-sensitive
macroinvertebrates (USEPA, 1976). For these reasons, the EMC in this project was calculated for each
runoff event as the average concentration of six to eight flush runoff samples. On all farms, the EMCs for
TN in first flush runoff events fell within a range of 2.5 to 15.1 mg/L; TP values ranged from 0.6 to 3.3
mg/L. The EMCs calculated using the first flush runoff concentration data were expected to be higher
than flow-weighted EMCs calculated for the same runoff events.
Median values for each runoff sampling site were statistically identified and then illustrated in box plot
comparisons by using all first flush runoff concentrations sampled on each farm over the course of the
monitoring projects. Box plots allowed runoff values between farms to be assessed while lessening the
statistical influence of runoff events with higher EMCs (Hintze, 2000). Median TN concentrations in first
flush runoff events ranged between 2.3 mg/L (on the Kunard farm) to 9.8 mg/L (at the lower sampler on
the Bartel farm) (Figure 22). The high and low median TP values, 0.4 mg/L and 2.5 mg/L, came from the
upper and lower samplers at the Bartel farm. Mean and median atrazine and metolachlor levels were
less than 1.0 ug/L for five of the seven farms equipped with runoff samplers (Figure 23).
78
Figure 22: Nutrient boxplots for first flush runoff sampled at ten sites on seven farms. Log scales are used to better display the entire range of concentration data.
.1
1
10
100
Bartel: Lower
Bartel: Upper
Burr: Lower
Burr: Upper
How
ell
Kunard
Peters
Spare
Townsend: Field
Townsend: W
etlandTotal Nitrogen
Con
cent
ratio
n (m
g/L)
.1
1
10
100
Bartel: Lower
Bartel: Upper
Burr: Lower
Burr: Upper
How
ell
Kunard
Peters
Spare
Townsend: Field
Townsend: W
etland
Total Phosphorus
Con
cent
ratio
n (m
g/L)
79
Figure 23: Herbicide boxplots for first flush runoff sampled at ten sites on seven farms. Log scales are used to better display the entire range of concentration data.
.01
.1
1
10
100
1000
Bartel: Lower
Bartel: Upper
Burr: Lower
Burr: Upper
How
ell
Kunard
Peters
Spare
Townsend: Field
Townsend: W
etland
AtrazineC
once
ntra
tion
(ug/
L)
.01
.1
1
10
100
1000
Bartel: Lower
Bartel: Upper
Burr: Lower
Burr: Upper
How
ell
Kunard
Peters
Spare
Townsend: Field
Townsend: W
etland
Metolachlor
Con
cent
ratio
n (u
g/L)
80
Groundwater Sampling and Results Shallow groundwater samples were collected several times annually on six of the eight monitored farms.
Multiple clusters of lysimeters were installed on four farms to evaluate potential spatial changes in nutrient
and herbicide concentrations within local groundwater. In addition, groundwater samples were collected
at multiple depths (one, four and eight feet) to assess changes in concentrations at different levels in the
soil column. As expected, results of the groundwater monitoring projects indicated that nutrient
concentrations in groundwater were generally lower than those in surface runoff sampled on these six
Kansas farms. Median nutrient and herbicide concentrations were determined statistically and illustrated
with box plots. Median TN levels at the eight-foot sampling depth were below 1.0 mg/L on four of six
farms (Figure 24). Concentrations on the other two farms were probably increased as a function of field
applications and tillage. Median TP concentrations ranged between 0.01 and 0.2 mg/L. Atrazine and
metolachlor were rarely detected at levels over 0.5 ug/L (one of 117 samples. Mean concentrations for
atrazine and metolchlor for each farm (all sites and depths) were lower than 0.25 ug/L. The general lack
of herbicides in local groundwater was probably related to the fact that five of the six farms had reduced
or eliminated herbicide applications as part of the implemented BMPs. The EPA-mandated drinking
water standard for atrazine is 3 ug/L for atrazine; metolachlor concentrations in drinking water are not yet
regulated (USEPA, 1995).
Surface Water and Aquatic Ecosystems Surface water was sampled at multiple locations on water bodies on four farms on a regular basis and
supplemented with additional samples collected after runoff events. Surface water from wetlands,
streams and stock ponds was collected on four farms. Samples were collected from multiple sites in each
of the water bodies to account for spatial variability in the water chemistry. Normally, samples were
collected during low-flow periods. Increases in nutrient and herbicide concentrations were noted in the
data when surface water sample collection followed a runoff event. Median values for each farm were
illustrated in boxplot comparisons by using all data from all sites on each farm. Median TN values ranged
between 0.8 mg/L at the Howell’s creek and 2.2 mg/L at the Hubbard’s stock ponds (Figure 25).
Similarly, median TP concentrations were between 0.07 and 0.3 mg/L
In addition to water chemistry, the potential aquatic habitat and macroinvertebrate populations were
assessed on two farms. Aquatic habitat was characterized quantitatively with the Habitat Development
Index (HDI), which compares in-stream habitats and their influence on the local aquatic
macroinvertebrate community. Analysis of the HDI scores typically indicated the presence of a diverse
habitat able to sustain a varied and multiple-trophic-leveled invertebrate community. The sampled
aquatic macroinvertebrate populations were representative of the expected populations (USDA, 1998).
Together, the HDI and the macroinvertebrate sample collection indicated the aquatic biota was not greatly
impaired by water quality.
81
Figure 24: Nutrient and herbicide concentrations in shallow groundwater monitored on six farms. Log scales are used to better display the entire range of concentration data.
.01
.1
1
10
100
Bartel-1
Bartel-2
How
ell-1
How
ell-2
How
ell-3
Kunard-1
Peters-1
Spare-1
Spare-2
Spare-3
Townsend-1
Townsend-2
Townsend-3
Total Nitrogen
Con
cent
ratio
n (m
g/L)
.001
.01
.1
1
Bartel-1
Bartel-2
How
ell-1
How
ell-2
How
ell-3
Kunard-1
Peters-1
Spare-1
Spare-2
Spare-3
Townsend-1
Townsend-2
Townsend-3
Total Phosphorus
Con
cent
ratio
n (m
g/L)
.001
.01
.1
1
Bartel-1
Bartel-2
How
ell-1
How
ell-2
How
ell-3
Kunard-1
Peters-1
Spare-1
Spare-2
Spare-3
Townsend-1
Townsend-2
Townsend-3
Atrazine
Con
cent
ratio
n (u
g/L)
82
Figure 25: Nutrient and herbicide boxplots for surface water monitored on four farms. Log scales are used to better display the entire range of concentration data.
.1
1
10
Bartel
How
ell
Hubbard
Townsend
Total Nitrogen
Con
cent
ratio
n (m
g/L)
.01
.1
1
Bartel
How
ell
Hubbard
Townsend
Total Phosphorus
Con
cent
ratio
n (m
g/L)
.01
.1
1
10
100
Bartel
How
ell
Hubbard
Townsend
Atrazine
Con
cent
ratio
n (u
g/L)
83
Causative Factors Variability in rainfall, soil and water chemistry as well as the probable influences of land management and
other factors associated with adjacent lands draining to the sampling points influenced edge-of-field
concentrations of nutrients and herbicides and complicated the interpretation of field data. Variation in
the defining characteristics of runoff generating storms (i.e. frequency, intensity and duration) and
differences in soil chemistry between farms did not appear to account for observed differences in water
chemistry between farms. The timing of sampling relative to fertilizer and herbicide applications and to
the seasonal presence or absence of groundcover (rowcrops, crop residue, perennial forage, freshly tilled
soil) also impacted the runoff EMCs. Multiple sources of nutrients and herbicides beyond the monitored
fields were present on each farm. Fertilizer and herbicide applications were frequently represented in
water quality data by increased concentrations in runoff, groundwater and surface water; the elimination
of field applications was also apparent in the data sets of several farms. Trends in nutrient and herbicide
concentrations were relative to watershed-scale contributions of nonpoint source pollutants. The
intuitively beneficial effects of management practices are not immediately displayed quantitatively by the
monitored agricultural ecosystem; a lag time between implementation of the BMPs and significantly
measurable changes in water quality was expected (USEPA, 1988).
On several farms, upstream and/or off-site nutrient and herbicide inputs masked the potential effects the
BMPs themselves might have had on field-scale water quality. Occasionally, management practices
used to address one water quality issue inadvertently increased the generation or transport of NPSP at
another site (Logan, 1990). The inability to truly isolate the “treatment effects” of the BMPs within the
water chemistry analyses made relating land management to water quality difficult. Obtaining
information as to what BMPs were recommended by county or state agencies was helpful in determining
what specific factors could influence water chemistry on both the field and watershed scales. However,
“pre-BMP” comparative data for the eight monitored farms was rarely available, as most of the monitoring
programs were established after the transitions in land management were already underway. Data
comparisons were limited to the time scale of the monitoring project, and the use of comparative studies
from other field NPSP studies was limited by the relative scarcity of agricultural edge-of-field
concentrations on “working” farms in the literature.
Future Studies Study results did not reveal conclusive evidence of improved water quality resulting from the
implementation of BMPs during the monitoring. However, this project accomplished its goals of
quantifying edge-of-field concentrations in field runoff, shallow groundwater and surface water through
on-farm monitoring and determining the factors that influenced the observed concentrations. Additionally,
the results of this study build on the knowledge base of edge-of-field nutrient and herbicide
concentrations under different land management and climatic conditions in eastern Kansas. Many NPSP
84
studies monitor receiving bodies of water (i.e. streams, lakes or reservoirs), use test plots, simulated
rainfall, and/or computer models to predict annual TN and TP loading values rather than concentrating on
the importance of edge-of-field concentration data (Dunigan et al, 1976; USEPA, 1985; Wang et al,
2000). Future studies of edge-of-field concentrations of NPSP related to “working” farms should
incorporate additional factors to better define and quantify these values. An experimental approach that
focuses on fluctuations in water quality and runoff volume over the course of an entire runoff event would
further build on the knowledge base of agricultural contributions of NPSP. Another possible approach is
the pairing of monitoring efforts with modeling efforts (e.g. estimations of runoff volume, roles of land
use/land cover in water quality), which could then estimate annual loading values (kg/ha/yr) from
individual fields within a watershed. The use of weirs to develop edge-of-field runoff hydrographs is
another possibility. Designing monitoring projects to support the generation of a model runoff hydrograph
and chemograph for small-scale runoff events can provide researchers the ability to better evaluate the
influences of storm intensity and duration on edge-of-field concentrations of nutrients, herbicides,
sediment and pathogens.
Monitoring agricultural nonpoint source pollution levels will continue to be an important component of
projects designed to identify time periods in the agricultural season and areas in agriculturally-dominated
watersheds that contribute a disproportionate amount of NPSP to receiving bodies of water. This will be
particularly important in developing meaningful total maximum daily loadings (TMDLs) for nutrients and
herbicides in watersheds with impaired water quality. Long-term studies must continue to incorporate
monitoring and modeling efforts on multiple spatial scales (i.e. individual fields, intermittent streams, lakes
and reservoirs) to better illustrate seasonal and temporal changes in water quality as the field-level and
watershed-level BMPs are introduced and refined. This study reinforced the ideas that NPSP
concentrations in runoff, groundwater and surface water are functions of natural conditions, weather
patterns and management decisions. Identifying the time periods with an increased likelihood of NPSP
levels, the areas most likely to contribute higher levels of NPSP, and the proper BMPs to further address
the unique temporal and spatial issues involved with reducing agricultural NPSP will be necessary to
reduce the water quality impacts of agricultural activities.
85
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87
List of Appendices Appendix A: Bartel farm Water quality data for runoff, groundwater and surface water Wetland vegetation survey Appendix B: Spare farm Water quality data for runoff and groundwater Appendix C: Townsend farm Water quality data for runoff, groundwater and surface water Appendix D: Burr farm Water quality data for runoff Appendix E: Howell farm Water quality data for runoff, groundwater and surface water Appendix F: Kunard farm Water quality data for runoff and groundwater Appendix G: Peters farm Water quality data for runoff and groundwater Appendix H: Hubbard ranch Water quality data for surface water
88
Appendix A: Nutrient and herbicide concentration statistics for Bartel runoff, upper sampler.Standard
Sampling Date Nutrient Mean Median Low High Deviation Oct 29, 1996 TN (mg/L) -Rain = 0.50 Org N (mg/L) -
NO3 (mg/L) 3.91 3.63 2.99 5.28 0.85NH3 (mg/L) 2.98 2.59 2.11 5.36 1.23TP (mg/L) -Org P (mg/L) -PO4 (mg/L) 0.18 0.20 0.09 0.24 0.06Atrazine (ug/L) 0.01 0.01 0.01 0.03 0.01Metolachlor (ug/L) -
Nov 16, 1996 TN (mg/L) -Rain = 0.90 Org N (mg/L) -
NO3 (mg/L) 6.64 6.65 6.21 6.94 0.26NH3 (mg/L) 2.07 2.11 0.83 3.63 0.96TP (mg/L) -Org P (mg/L) -PO4 (mg/L) 0.29 0.13 0.10 1.40 0.45Atrazine (ug/L) 0.01 0.01 0.01 0.01 0.00Metolachlor (ug/L) -
Jun 23, 1997 TN (mg/L) 4.26 4.23 3.92 4.70 0.24Rain = 0.50 Org N (mg/L) 2.04 2.00 1.53 2.86 0.44
NO3 (mg/L) 2.05 2.18 1.62 2.39 0.31NH3 (mg/L) 0.17 0.17 0.13 0.22 0.03TP (mg/L) 0.37 0.36 0.32 0.43 0.04Org P (mg/L) 0.24 0.23 0.17 0.31 0.05PO4 (mg/L) 0.13 0.13 0.11 0.15 0.01Atrazine (ug/L) 0.31 0.31 0.23 0.40 0.06Metolachlor (ug/L) 0.14 0.15 0.10 0.17 0.03
Jul 29, 1997 TN (mg/L) 7.27 7.28 6.85 8.05 0.41Rain = 0.70 Org N (mg/L) 0.94 1.02 0.01 1.33 0.44
NO3 (mg/L) 6.27 5.99 5.75 7.26 0.60NH3 (mg/L) 0.05 0.04 0.03 0.08 0.02TP (mg/L) 0.32 0.33 0.23 0.37 0.05Org P (mg/L) 0.10 0.12 0.02 0.15 0.05PO4 (mg/L) 0.22 0.22 0.21 0.23 0.01Atrazine (ug/L) 0.14 0.14 0.11 0.17 0.02Metolachlor (ug/L) 0.04 0.03 0.03 0.07 0.01
Jul 17, 1999 TN (mg/L) 3.63 3.23 2.90 6.30 1.11Rain = 1.50 Org N (mg/L) 1.77 1.37 1.14 4.35 1.14
NO3 (mg/L) 2.29 1.82 1.63 5.58 1.34NH3 (mg/L) 0.06 0.06 0.02 0.11 0.03TP (mg/L) 1.42 1.38 1.20 1.66 0.17Org P (mg/L) 0.22 0.18 0.07 0.56 0.15PO4 (mg/L) 0.24 0.23 0.22 0.32 0.03Atrazine (ug/L) 0.08 0.08 0.07 0.09 0.01Metolachlor (ug/L) 0.04 0.04 0.03 0.04 0.00
Sep 14, 1999 TN (mg/L) 1.94 1.90 1.60 2.45 0.30Rain = 0.90 Org N (mg/L) 1.44 1.41 1.19 1.93 0.21
NO3 (mg/L) 0.30 0.26 0.07 0.84 0.25NH3 (mg/L) 0.20 0.20 0.15 0.27 0.04TP (mg/L) 1.42 1.38 1.20 1.66 0.17Org P (mg/L) 0.22 0.22 0.12 0.33 0.06PO4 (mg/L) 1.20 1.18 1.02 1.42 0.16Atrazine (ug/L) 0.06 0.06 0.05 0.08 0.01Metolachlor (ug/L) 0.01*
May 26, 2000 TN (mg/L) 6.46 4.92 4.53 12.78 3.04Rain = 2.40 Org N (mg/L) 1.82 1.68 1.28 2.77 0.48
NO3 (mg/L) 4.51 2.92 2.32 11.11 3.27NH3 (mg/L) 0.28 0.30 0.08 0.44 0.13TP (mg/L) 2.35 2.12 1.91 3.66 0.60Org P (mg/L) 0.39 0.29 0.15 1.01 0.29PO4 (mg/L) 1.97 1.84 1.68 3.07 0.46Atrazine (ug/L) 0.72 0.70 0.63 0.94 0.10Metolachlor (ug/L) 0.59 0.63 0.43 0.67 0.08
Data from eight runoff samples collected within three hours of sampler activation.0.01* = Herbicide registered under laboratory detection limit of 0.02 ug/L- indicates results of analysis unavailable.Rain = inches in 48 hours prior to sampling
Appendix A: Nutrient and herbicide concentration statistics for Bartel runoff, lower sampler. Standard
Sampling Date Nutrient Mean Median Low High DeviationNov 16, 1996 NO3 (mg/L) 5.18 5.18 4.92 5.43 0.36Rain = 2.50 NH3 (mg/L) 0.74 0.74 0.64 0.84 0.14
PO4 (mg/L) 0.21 0.21 0.21 0.21 0.00Atrazine (ug/L) 0.01*Metolachlor (ug/L) 0.01*
Jun 23, 1997 TN (mg/L) 4.14 3.93 2.70 6.99 1.50Rain = 3.10 Org N (mg/L) 2.83 2.12 1.72 4.40 1.21
NO3 (mg/L) 1.18 0.83 0.58 2.31 0.68NH3 (mg/L) 0.13 0.11 0.07 0.28 0.07TP (mg/L) 1.45 1.05 0.86 2.75 0.70Org P (mg/L) 1.20 0.83 0.50 2.56 0.73PO4 (mg/L) 0.26 0.25 0.19 0.36 0.06Atrazine (ug/L) 0.28 0.23 0.16 0.57 0.14Metolachlor (ug/L) 0.17 0.17 0.08 0.28 0.07
Sep 24, 1998 TN (mg/L) 4.86 4.40 3.65 7.85 1.38Rain = 0.70 Org N (mg/L) 3.16 2.73 1.57 6.47 1.56
NO3 (mg/L) 1.56 1.47 0.90 2.69 0.59NH3 (mg/L) 0.14 0.09 0.05 0.38 0.11TP (mg/L) 1.23 1.07 0.66 2.56 0.61Org P (mg/L) 0.95 0.79 0.36 2.24 0.59PO4 (mg/L) 0.28 0.29 0.20 0.37 0.06Atrazine (ug/L) 0.03 0.04 0.02 0.07 0.02Metolachlor (ug/L) 0.01*
Oct 2, 1998 TN (mg/L) 3.86 4.28 1.80 5.05 1.13Rain = 1.50 Org N (mg/L) 1.60 1.68 1.17 1.92 0.26
NO3 (mg/L) 2.22 2.51 0.61 3.08 0.87NH3 (mg/L) 0.04 0.04 0.02 0.05 0.01TP (mg/L) 0.74 0.77 0.54 0.88 0.12Org P (mg/L) 0.11 0.09 0.03 0.28 0.10PO4 (mg/L) 0.64 0.70 0.26 0.88 0.22Atrazine (ug/L) 0.03 0.03 0.02 0.05 0.01Metolachlor (ug/L) 0.01*
Oct 31, 1998 TN (mg/L) 5.51 5.93 3.15 6.70 1.18Rain = 0.90 Org N (mg/L) 1.68 1.65 1.08 2.27 0.04
NO3 (mg/L) 3.70 3.93 1.99 4.51 0.84NH3 (mg/L) 0.13 0.13 0.07 0.20 0.05TP (mg/L) 0.92 0.99 0.37 1.40 0.41Org P (mg/L) 0.13 0.12 0.06 0.22 0.06PO4 (mg/L) 0.82 0.90 0.20 1.40 0.48Atrazine (ug/L) 0.01*Metolachlor (ug/L) 0.01*
Nov 10, 1998 TN (mg/L) 0.31 0.32 0.26 0.35 0.00Rain = 2.40 TP (mg/L) 0.18 0.12 0.11 0.59 0.17
Atrazine (ug/L) 0.01*Metolachlor (ug/L) 0.01*
Jun 18, 1999 TN (mg/L) 9.83 9.46 8.32 12.71 1.41Rain = 1.60 TP (mg/L) 1.22 1.18 1.15 1.45 0.10
Atrazine (ug/L) 0.75 0.73 0.60 0.97 0.13Metolachlor (ug/L) 0.50 0.53 0.21 0.59 0.12
Jul 16, 1999 TN (mg/L) 13.44 13.33 12.60 14.40 0.62Rain = 1.90 Org N (mg/L) 9.08 9.27 8.09 9.91 0.67
NO3 (mg/L) 4.17 4.00 2.71 5.84 1.03NH3 (mg/L) 2.82 2.82 2.61 3.14 0.17TP (mg/L) 2.82 2.82 2.61 3.14 0.17Org P (mg/L) 1.05 1.04 0.87 1.29 0.13PO4 (mg/L) 1.77 1.76 1.68 1.86 0.06Atrazine (ug/L) 0.30 0.21 0.15 0.84 0.23Metolachlor (ug/L) 0.09 0.05 0.02 0.35 0.11
Data from eight runoff samples collected within three hours of sampler activation.0.01* = Herbicide registered under detection limit of 0.02 ug/LRain = inches in 48 hours prior to sampling
Appendix A : Despcriptive statistics for nutrients and pesticides in Bartel's runoff, lower samplerStandard
Sampling Date Nutrient Mean Median Low High Deviation Sep 14, 1999 TN (mg/L) 22.06 18.85 12.50 46.40 11.47Rain = 1.70 Org N (mg/L) 7.45 7.43 5.09 11.74 2.08
NO3 (mg/L) 14.54 11.32 6.85 34.58 9.47NH3 (mg/L) 0.07 0.07 0.05 0.08 0.01TP (mg/L) 3.39 3.05 2.43 6.24 1.20Org P (mg/L) 0.41 0.40 0.33 0.59 0.08PO4 (mg/L) 2.98 2.65 2.08 5.64 1.12Atrazine (ug/L) 0.01*Metolachlor (ug/L) 0.01*
Nov 22, 1999 TN (mg/L) 19.53 17.25 7.30 32.40 8.67Rain = 2.40 TP (mg/L) 3.58 3.10 2.30 5.89 1.21
Atrazine (ug/L) 0.47 0.31 0.22 1.09 0.31Metolachlor (ug/L) 0.01*
May 26, 2000 TN (mg/L) 35.31 32.47 5.52 71.75 29.75Rain = 0.90 Org N (mg/L) 13.08 11.72 0.96 33.14 12.62
NO3 (mg/L) 19.78 13.96 1.40 44.10 17.78NH3 (mg/L) 2.46 2.70 0.07 5.26 2.12TP (mg/L) 10.28 10.48 2.38 17.86 7.29Org P (mg/L) 3.37 4.24 0.24 7.23 2.76PO4 (mg/L) 6.91 5.60 1.97 1.34 5.06Atrazine (ug/L) 0.47 0.07 0.04 2.48 0.86Metolachlor (ug/L) 0.29 0.19 0.07 0.62 0.24
Jun 13, 2000 TN (mg/L) 20.67 21.95 12.95 45.80 3.54Rain = 0.90 TP (mg/L) 4.71 4.98 3.42 5.14 0.59
Atrazine (ug/L) 0.47 0.46 0.30 0.66 0.11Metolachlor (ug/L) 0.15 0.14 0.10 0.23 0.05
Jul 19, 2000 TN (mg/L) 35.09 41.15 14.63 45.80 12.28Rain = 0.80 TP (mg/L) 7.98 8.95 3.94 10.54 2.48
Atrazine (ug/L) 0.13 0.13 0.11 0.17 0.02Metolachlor (ug/L) 0.03 0.03 0.02 0.03 0.00
Data from eight runoff samples collected within three hours of sampler activation.
0.01* = Herbicide registered under laboratory detection limit of 0.02 ug/L
Rain = inches in 48 hours prior to sampling
Appendix A: Nutrient and herbicide concentrations in shallow groundwater on the Bartel farm.
Sampling Date Cluster Depth (ft) TN Org N NO3 NH3 TP Org P PO4 Atrazine Metolachlor Jul 19, 1996 1 4 2.10 1.76 0.06 0.28 0.15 0.09 0.07 0.01* 0.01*Rain = 0 3 4 15.68 0.37 15.03 0.28 0.09 0.03 0.07 0.01* 0.01*
3 8 9.54 9.62 0.08 0.06 0.03 0.02 0.01* 0.01*
Oct 22, 1996 1 4 - - 0.07 0.09 - - 0.12 0.01* 0.01*Rain = 0 2 4 - - 9.70 0.07 - - 0.07 0.01* 0.01*
3 1 - - 107.00 0.06 - - 0.24 0.01* 0.01*3 4 - - 18.66 0.02 - - 0.10 0.01* 0.01*
Jun 14, 1997 1 1 1.82 1.64 0.10 0.08 0.26 0.15 0.11 0.84 0.25Rain = 1.20 1 4 1.99 1.99 - 0.00 0.10 - 0.12 0.01* 0.01*
1 8 - - 0.53 0.22 - - 0.31 0.01* 0.01*2 1 - - 8.60 - - - 0.35 0.01* 0.01*2 4 14.08 0.97 13.10 0.01 0.07 - 0.09 0.01* 0.01*3 1 - - 25.15 0.03 0.26 0.06 0.20 0.01* 0.01*3 4 69.75 22.05 47.70 0.00 0.17 0.13 0.05 0.05 0.01*3 8 9.44 0.41 9.00 0.03 0.04 0.01 0.03 0.01* 0.01*
Aug 7, 1997 1 4 0.63 0.54 0.09 0.14 0.01 0.13 0.02 0.10Rain = 0 1 8 1.06 0.64 0.20 0.22 0.06 0.01 0.05 0.04 0.06
3 4 56.00 0.01 59.70 0.07 0.04 0.00 0.04 0.02 0.01*3 8 9.76 0.61 9.08 0.07 0.02 0.00 0.02 0.01* 0.02
Jul 22, 1998 1 4 0.68 0.63 0.02 0.03 0.13 0.06 0.07 0.01* 0.01*Rain = 0.40 3 4 42.50 - 42.60 0.01 0.10 0.03 0.08 0.01* 0.01*
3 8 12.59 1.34 11.23 0.02 0.03 - 0.03 0.01* 0.01*
Aug 4, 1998 1 1Rain = 0 1 4 0.54 0.49 0.02 0.03 0.06 - 0.10 0.01* 0.01*
1 8 1.57 1.33 0.16 0.08 0.01 - 0.09 0.01* 0.01*3 4 40.90 - 41.20 0.01 0.03 - 0.11 0.01* 0.01*3 8 11.50 0.33 11.16 0.01 0.02 - 0.06 0.01* 0.01*
Dec 2, 1998 1 1 2.09 1.56 0.50 0.03 0.16 0.10 0.06 0.01* 0.01*Rain = 0.50 1 4 0.73 0.71 - 0.02 0.01 - 0.02 0.01* 0.01*
1 8 0.88 0.73 0.03 0.12 0.01 - 0.04 0.01* 0.01*2 4 8.86 0.13 8.66 0.07 0.08 - 0.10 0.01* 0.01*2 8 36.85 - 38.88 0.10 0.16 - 0.18 0.01* 0.01*3 1 3.73 2.03 1.61 0.09 0.20 - 0.22 0.01* 0.01*3 4 39.35 - 40.64 0.03 0.03 - 0.07 0.01* 0.01*3 8 12.00 0.31 11.65 0.04 - - 0.04 0.01* 0.01*
Jul 15, 1999 1 1 2.05 1.21 0.82 0.02 0.18 0.10 0.07 0.07 0.04Rain = 0 1 4 0.54 0.51 0.02 0.01 0.03 0.01 0.02 0.03 0.02
1 8 0.64 0.56 0.01 0.07 0.02 - 0.02 0.01* 0.023 1 2.79 2.69 0.10 0.00 0.18 0.00 0.18 0.01* 0.043 4 44.52 - 44.52 0.00 0.03 - 0.03 0.02 0.01*3 8 15.08 - 15.08 0.01 0.10 - 0.10 0.08 0.01*
Sep 7, 1999 1 4 0.88 0.81 0.04 0.03 0.42 - 0.42 0.01* 0.01*Rain = 1.60 1 8 0.75 0.68 - 0.07 0.04 - 0.04 0.01* 0.01*
3 1 9.38 5.24 4.07 0.07 0.43 0.03 0.40 0.01* 0.01*3 4 53.56 7.20 46.34 0.02 0.05 - 0.05 0.01* 0.01*3 8 17.34 1.57 15.75 0.02 0.07 0.00 0.07 0.01* 0.01*
Dec 8, 1999 1 4 2.34 0.80 1.52 0.02 0.06 0.01 0.04 0.01* 0.01*Rain = 0.80 1 8 0.66 0.62 - 0.04 0.07 - 0.07 0.01* 0.01*
2 8 10.90 0.98 9.82 0.10 0.14 - 0.14 0.01* 0.01*3 1 7.49 2.94 4.54 0.01 0.18 - 0.18 0.01* 0.01*3 4 30.75 3.17 27.58 0.00 0.09 - 0.09 0.01* 0.01*3 8 16.35 1.84 14.49 0.02 0.18 - 0.18 0.01* 0.01*
Jul 19, 2000 1 4 0.74 0.72 - 0.02 0.12 0.05 0.07 0.05 0.03Rain = 0 1 8 0.40 0.38 - 0.02 0.02 0.00 0.02 0.01* 0.01*
3 1 3.71 2.90 0.81 - 0.27 0.02 0.25 0.01* 0.01*3 4 1.59 0.71 0.88 - 0.05 - 0.05 0.10 0.01*3 8 19.50 2.62 16.88 - 0.05 - 0.05 0.01* 0.01*
May 13, 2000 1 4 0.66 0.35 0.26 0.05 0.06 0.02 0.04 0.01 0.01Rain = 0.80 1 8 0.38 0.34 0.01 0.03 0.03 0.01 0.02 0.01* 0.01*
2 8 2.78 0.25 2.49 0.04 0.10 0.02 0.08 0.03 0.01*3 1 2.71 2.52 0.18 0.01 0.25 0.04 0.21 0.01* 0.01*3 4 2.66 0.41 2.23 0.02 0.06 0.01 0.05 0.03 0.01*3 8 15.46 0.08 15.37 0.01 0.06 0.00 0.06 0.01* 0.01*
0.01* = Concentrations determined to be less than the sample detection limit of 0.02 u g/L. - indicates analysis for that sample not available.
Rain = inches in 48 hours prior to sampling, (TN, Org N, NO3, NH3, TP, Org P, PO4) = mg/L, Atrazine and Metolachlor = ug/L
Appendix A: Nutrient, herbicide and bacteria concentrations at three sites in the Bartel wetland.Coliform
Sampling Date Site TN Org N NO3 NH3 TP Org P PO4 Atrazine Metolachlor Bacteria Jul 19, 1996 1 1.34 1.2 0.06 0.08 0.11 0.09 0.01 0.35 0.01* -Rain = 0 2 1.36 1.13 0.01 0.22 0.13 0.11 0.01 1.1 0.01* -
3 2.07 1.93 0.02 0.12 0.27 0.22 0.05 0.08 0.01* -
Jun 14, 1997 1 6.26 2.17 4.02 0.07 0.53 0.17 0.36 69.4 0.13 -Rain = 1.20 2 3.22 1.19 1.92 0.11 0.30 0.10 0.19 29.4 0.27 -
3 1.35 0.81 0.52 0.02 0.18 0.08 0.11 0.39 0.06 -
Dec 2, 1998 1 0.51 0.33 0.15 0.03 0.06 0.00 0.06 0.04 0.01* 32Rain = 0.50 2 0.72 0.69 0 0.03 0.06 0.03 0.02 0.04 0.01* 12
3 2.58 0.39 2.16 0.03 0.12 0.02 0.10 0.03 0.01* 4
Jun 3, 1999 1 0.94 0.78 0.13 0.03 0.45 0.18 0.27 1.039 0.38 -Rain = 0 2 1.5 1.44 0.04 0.01 0.18 0.13 0.05 1.494 0.47 -
3 3.77 3.51 0.05 0.21 0.89 0.70 0.19 0.563 0.17 -
Aug 4, 1999 1 1.59 1.59 0.00 0.00 0.18 0.18 0.01 0.076 0.01* 12Rain = 2.3 2 1.21 1.19 0.00 0.02 0.17 0.16 0.01 0.048 0.01* 16
3 1.2 1.1 0.06 0.04 0.08 0.08 0.01 0.043 0.01* 32
May 22, 2000 1 0.6 0.58 0.00 0.02 0.13 0.10 0.03 0.042 0.01* 16Rain = 0.10 2 0.98 0.96 0.00 0.02 0.16 0.13 0.03 0.049 0.02 8
3 0.51 0.48 0.00 0.03 0.21 0.05 0.16 0.021 0.01* 12
Bacteria = Coliform colonies/100 mL 0.01* = Concentrations determined to be less than the sample detection limit of 0.02 u g/L. - indicates analysis for that sample not available.
Rain = inches in 48 hours prior to sampling, (TN, Org N, NO3, NH3, TP, Org P, PO4) = mg/L, Atrazine and Metolachlor = ug/L
Appendix A: Dominant wetland vascular plants occurring along five cross-channel transects on three study sites at Bartel’s gully.
Survey Date: June 12, 1997 Wetland Indicator Site 1 Dominance Scientific Name Common Name Status (WIS) Transect 1 D Eleocharis erythropoda Bald Spikerush Obl SD Scirpus pendulus Drooping Bulrush Obl SD Cyperus strigosus Straw-color Flatsedge FacW SD Carex gravida Heavy Sedge NI Transect 2 D Eleocharis erythropoda Bald Spikerush Obl SD Cyperus strigosis Straw-color Flatsedge FacW Transect 3 SD Carex molesta Troublesome Sedge NI SD Cyperus strigouis Straw-color Flatsedge FacW Transect 4 D Eleocharis erythropoda Bald Spikerush Obl SD Cyperus strigosus Straw-color Flatsedge FacW Transect 4 SD Carex brevior Short-beak Sedge NI SD Leersia virginica Whitegrass FacW
SD Carex amphibola Narrow-leaf Sedge FacW Transect 5 SD Carex brachyglossa Yellow-fruit Sedge Fac+
SD Carex gravida Heavy Sedge NI D Juncus interior Inland Rush Fac Site 2 Transect 1 D Eleocharis erythropoda Bald Spikerush Obl Transect 2 D Eleocharis erythropoda Bald Spikerush Obl Transect 3 D Eleocharis erythropoda Bald Spikerush Obl Transect 4 D Eleocharis erythropoda Bald Spikerush Obl SD Scirpus pendulus Drooping Bulrush Obl SD Typha angustifolia Narrow-leaf Cattail Obl Transect 5 D Eleocharis erythropoda Bald Spikerush Obl SD Scirpus pendulus Drooping Bulrush Obl Site 3 Transect 1 D Eleocharis erythropoda Bald Spikerush Obl Transect 2 D Salix nigra Black Willow Obl Transect 3 D Salix nigra Black Willow Obl Transect 4 D Eleocharis erythropoda Bald Spikerush Obl Transect 5 D Eleocharis erythropoda Bald Spikerush Obl SD Scirpus pendulus Drooping Bulrush Obl Survey Date: June 3, 1999 Site 1 Dominance Scientific Name Common Name WIS Transect 1 D Eleocharis erythropoda Bald Spikerush Obl SD Carex brachyglossa Yellow-fruit Sedge Fac+ SD Juncus toreyi Torrey’s Rush FacW SD Bromus inermis Smooth Brome NI SD Rumex altissimus Pale Dock Fac+ SD Scirpus pendulus Drooping Bulrush Obl SD Leersya oryzoides Rice Cutgrass Obl Transect 2 D Eleocharis erythropoda Bald Spikerush Obl SD Hordeum pusillum Little Barley Fac SD Bromus inermis Smooth Brome NI SD Galium aparine Catchweed Bedstraw FacU SD Carex fissa Thread-leaf Sedge FacW SD Tradescantia brecteata Spider Wort Fac
Appendix A: Dominant wetland vascular plants occurring along five cross-channel transects on three study sites at Bartel’s gully.
Survey Date: June 3, 1999 Site 1 Dominance Scientific Name Common Name WIS Transect 3 SD Cyperus setigerus Lean Flatsedge Fac SD Eleocharis compressa Flat-stem Spikerush FacW SD Scirpus pendulus Drooping Bulrush Obl SD Eleocharis macrostacya Creeping Spikerush Obl SD Hordium jubatum Fox-tail Barley FacW SD Juncus interior Inland Rush Fac SD Carex bicknellii Bicknell’s Sedge FacU SD Helianthus maximilliani Maximillian Sunflower NI Transect 4 D Eleocharis macrostacya Creeping Spikerush Obl SD Hordium pusillum Little Barley Fac SD Rumex crispis Curly Dock FacW SD Juncus toreyi Torrey’s Rush FacW SD Carex fissa Thread-leaf Sedge FacW Transect 5 D Bromus inermis Smooth Brome NI SD Hordium pusillum Little Barley Fac SD Carex austrina Southern Sedge NI SD Carex gravida Heavy Sedge NI SD Carex davisii Davis’ Sedge FacU SD Tradescantia brecteata Spider Wort Fac Site 2 Transect 1 D Bromus inermis Smooth Brome NI SD Helianthus maximilliani Maximillian Sunflower NI SD Carex fissa Thread-leaf Sedge FacW SD Carex austrina Southern Sedge NI SD Eleocharis erythropoda Bald Spikefush Obl SD Carex brevior Short-beak Sedge Fac SD Juncus interior Inland Rush Fac SD Scirpus pendulus Drooping Bulrush Obl Transect 2 D Eleocharis erythropoda Bald Spikefush Obl SD Hordium jubatum Fox-tail Barley Fac SD Helianthus maximilliani Maximillian Sunflower NI SD Bromus inermis Smooth Brome NI SD Carex fissa Thread-leaf Sedge FacW SD Scirpus pendulus Drooping Bulrush Obl SD Carex brevior Short-beak Sedge FacW SD Leersya oryzoides Rice Cutgrass Obl Transect 3 SD Scirpus pendulus Drooping Bulrush Obl SD Eleocharis erythropoda Bald Spikerush Obl SD Rumex altissimus Pale Dock Fac+ SD Leersya oryzoides Rice Cutgrass Obl SD Carex fissa Thread-leaf Sedge FacW SD Typha angustifolia Narrow-leaf Cattail Obl Transect 4 SD Eleocharis erythropoda Bald Spikerush Obl SD Scirpus pendulus Drooping Bulrush Obl SD Juncus toreyi Torrey’s Rush FacW SD Rumex altissima Pale Dock Fac+ SD Helianthus maximilliani Maximillian Sunflower NI SD Salix nigra Black Willow Obl SD Leersya oryzoides Rice Cutgrass Obl SD Aster praealtus Willow-leaf Aster Obl
Appendix A: Dominant wetland vascular plants occurring along five cross-channel transects on three study sites at Bartel’s gully.
Survey Date: June 3, 1999 Site 2 Dominance Scientific Name Common Name WIS Transect 5 D Eleocharis erythropoda Bald Spikerush Obl SD Rumex altissima Pale Dock Fac+ SD Helianthus maximilliani Maximillian Sunflower NI SD Eleocharis macrostacea Creeping Spikerush Obl SD Scirpus pendulus Drooping Bulrush Obl Site 3 Transect 1 D Scirpus pendulus Drooping Bulrush Obl SD Salyx nigra Black Willow Obl SD Solidago gigantea Giant Goldenrod FacW SD Aster praealtus Willow-leaf Aster Obl SD Bromus inermis Smooth Brome NI SD Eleocharis erythropoda Bald Spikerush Obl Transect 2 D Bromus inermis Smooth Brome NI D Eleocharis macrostacea Creeping Spikerush Obl SD Cyperus setigerus Lean Flatsedge Fac Transect 3 SD Eleocharis erythropoda Bald Spikerush Obl SD Salix nigra Black Willow Obl SD Bromus inermis Brome Grass NI Transect 4 D Bromus inermis Brome Grass NI SD Scirpus pendulus Drooping Bulrush Obl SD Poa pratenis Kentucky Bluegrass Fac SD Eleocharis macrostacea Creeping Spikerush Obl Transect 5 D Eleocharis macrostacea Creeping Spikerush Obl SD Poa pratenis Kentucky Bluegrass Fac SD Scirpus pendulus Drooping Bulrush Obl SD Salix nigra Black Willow Obl
Appendix B: Nutrient and herbicide concentration statisitcs for Spare runoff.Standard
Sampling Date Nutrient Mean Median Low High Deviation Jul 29, 1997 TN (mg/L) 2.86 2.58 1.20 6.40 1.57Rain = 1.60 Org N (mg/L) 2.03 1.73 0.80 4.83 1.23
NO3 (mg/L) 0.43 0.45 0.05 0.74 0.21NH3 (mg/L) 0.40 0.22 0.12 1.52 0.47TP (mg/L) 1.88 1.81 1.43 2.45 0.32Org P (mg/L) 0.32 0.30 0.13 0.62 1.23PO4 (mg/L) 1.56 1.59 1.20 1.83 0.22Atrazine (ug/L) 0.06 0.06 0.03 0.08 0.02Metolachlor (ug/L) 0.02 0.01 0.01 0.03 0.01
Aug 31, 1998 TN (mg/L) 9.49 8.63 7.55 17.75 3.37Rain = 0.60 Org N (mg/L) 7.41 6.86 5.47 13.18 2.42
NO3 (mg/L) 0.19 0.19 0.16 0.22 0.04NH3 (mg/L) 2.02 1.75 1.16 4.41 0.99TP (mg/L) 2.57 2.29 2.19 4.27 0.70Org P (mg/L) 1.33 1.13 0.76 3.20 0.78PO4 (mg/L) 1.27 1.31 0.89 1.50 0.23Atrazine (ug/L) 0.25 0.23 0.17 0.32 0.06Metolachlor (ug/L) 0.01*
Oct 31, 1998 TN (mg/L) 8.36 9.20 1.45 11.05 3.16Rain = 3.70 Org N (mg/L) 6.28 7.02 1.03 9.69 2.71
NO3 (mg/L) 2.01 2.05 0.33 3.40 1.00NH3 (mg/L) 0.06 0.06 0.04 0.09 0.02TP (mg/L) 2.37 2.55 0.74 3.61 0.89Org P (mg/L) 2.13 2.37 0.21 3.40 1.00PO4 (mg/L) 0.24 0.18 0.16 0.53 0.13Atrazine (ug/L) 0.38 0.44 <0.02 0.60 0.23Metolachlor (ug/L) 0.22 0.23 0.02 0.40 0.13
Jun 18, 1999 TN (mg/L) 7.50 7.48 6.11 9.21 1.25Rain = 0.50 TP (mg/L) 1.83 1.59 1.08 2.76 0.77
Atrazine (ug/L) 0.24 0.24 0.16 0.33 0.05Metolachlor (ug/L) 0.21 0.23 0.14 0.27 0.06
Jul 16, 1999 TN (mg/L) 12.69 12.10 10.80 16.60 1.84Rain = 3.80 Org N (mg/L) 1.64 1.60 1.11 2.36 0.51
NO3 (mg/L) 10.65 10.47 9.48 12.51 0.99NH3 (mg/L) 0.39 0.02 0.02 2.92 1.03TP (mg/L) 0.88 0.70 0.59 2.11 0.51Org P (mg/L) 0.27 0.20 0.14 0.74 0.20PO4 (mg/L) 0.61 0.50 0.45 1.37 0.31Atrazine (ug/L) 0.16 0.15 0.12 0.23 0.04Metolachlor (ug/L) 0.03 0.03 0.02 0.04 0.00
Data from eight runoff samples collected within three hours of sampler activation. Rain = inches in 48 hours prior to sampling 0.01* = Herbicide registered under laboratory detection limit of 0.02 ug/L
Sampled at the eight-foot depth at three locations in the converted field.Sampling Date Cluster TN Org N NO3 NH3 TP Org P PO4 Atrazine MetolachlorJul 19, 1996 1 0.50 0.06 0.31 0.13 0.02 0.01 0.01 0.01* 0.01*Rain = 0 2 0.44 0.24 0.11 0.09 0.05 0.02 0.03 0.01* 0.01*
Oct 22, 1996 1 - - 0.16 0.11 - - 0.13 0.08 0.01*Rain = 0 2 - - 1.46 0.2 - - 0.23 0.03 0.01*
Jun 14, 1997 1 0.62 0.20 0.41 0.01 0.03 0.01 0.02 0.02 0.05Rain = 0.50 2 0.57 0.55 0.01 0.01 0.05 0.01 0.05 0.01* 0.01*
3 5.73 1.85 3.86 0.02 0.12 0.07 0.05 0.01* 0.01*
Aug 7, 1997 1 0.64 0.07 0.48 0.09 0.01 0.00 0.01 0.01* 0.03Rain = 0.20 2 0.25 0.06 0.13 0.06 0.05 0.00 0.11 0.01* 0.01*
3 5.42 1.95 3.40 0.07 0.11 0.03 0.08 0.01* 0.05
Jul 22, 1998 1 0.74 0.16 0.57 0.01 0.02 0.00 0.02 0.01* 0.01*Rain = 0.40 2 0.29 0.26 0.00 0.03 0.03 0.05 0.03 0.01* 0.01*
3 0.77 0.49 0.27 0.01 0.08 0.09 0.08 0.01* 0.03
Aug 4, 1998 1 0.85 0.12 0.73 0.00 0.06 0.01 0.05 0.01* 0.01*Rain = 0.30 2 0.25 0.22 0.00 0.03 0.1 0.05 0.05 0.01* 0.01*
3 0.76 0.48 0.23 0.05 0.14 0.05 0.09 0.01* 0.01*
Jul 15, 1999 1 0.51 0.14 0.51 0.01 0.01 0.00 0.01 0.25 0.24Rain = 0 3 1.53 0.17 1.13 0.23 0.16 0.00 0.16 0.08 0.07
Oct 3, 1999 1 0.46 0.42 0.00 0.04 0.04 0.02 0.02 0.01* 0.01*Rain = 0 2 0.44 0.15 0.27 0.02 0.01 0.00 0.01 0.01* 0.01*
Dec 9, 1999 1 0.39 0.39 0.00 0.00 0.04 0.00 0.04 0.01* 0.01*Rain = 0 2 0.42 0.32 0.10 0.00 0.03 0.00 0.03 0.01* 0.01*
3 0.46 0.38 0.08 0.00 0.19 0.00 0.19 0.01* 0.01*
May 24, 2000 1 0.28 0.25 0.02 0.01 0.02 0.00 0.02 0.01* 0.01*Rain = 0 2 0.23 0.04 0.19 0.00 0.01 0.00 0.01 0.01* 0.01*
3 0.99 0.50 0.48 0.01 0.08 0.00 0.08 0.01* 0.01*
Jul 19, 2000 1 0.21 0.2 0.00 0.01 0.02 0.00 0.02 0.01* 0.01*Rain = 1.30 2 0.28 0.15 0.13 0.00 0.01 0.00 0.01 0.01* 0.01*
3 0.53 0.29 0.23 0.01 0.08 0.00 0.08 0.01* 0.01*
0.01* = Herbicde concentration less than detection limit of 0.02 u g/L.
- indicates analysis for that sample not available.
Appendix B: Nutrient and herbicide concentrations in shallow ground water on the Spare farm.
Rain = inches in 48 hours prior to sampling, (TN, Org N, NO 3, NH3, TP, Org P, PO4) = mg/L, Atrazine and Metolachlor = u g/L
Appendix C : Descriptive statistics for nutrients and pesticides in Townsend runoff, field sampler.Standard
Date Nutrient Mean Median Low High DeviationNov 16, 96 NO3 (mg/L) 10.33 11.44 0.15 14.64 4.81Rain = 2.50 NH3 (mg/L) 1.99 0.93 0.48 7.01 2.42
PO4 (mg/L) 0.27 0.28 0.2 0.33 0.06Atrazine (ug/L) 0.01*Metolachlor (ug/L) 0.01*
Jul 28, 97 TN (mg/L) 3.72 2.97 2.40 8.23 1.95Rain = 0.80 Org N (mg/L) 2.83 2.00 1.32 7.20 2.02
NO3 (mg/L) 0.83 0.93 0.34 1.08 0.29NH3 (mg/L) 0.05 0.04 0.03 0.15 0.04TP (mg/L) 1.19 1.00 0.76 2.50 0.55Org P (mg/L) 1.00 0.83 0.56 2.12 0.49PO4 (mg/L) 0.20 0.19 0.12 0.38 0.08Atrazine (ug/L) 0.15 0.16 0.09 0.20 0.04Metolachlor (ug/L) 0.01 0.01 0.01 0.02 0.00
Jul 7, 98 TN (mg/L) 2.81 2.68 2.30 3.60 0.52Rain = 0.50 Org N (mg/L) 2.15 2.01 1.84 2.79 0.35
NO3 (mg/L) 0.54 0.47 0.41 0.81 0.14NH3 (mg/L) 0.13 0.14 0.05 0.24 0.08TP (mg/L) 0.79 0.75 0.67 1.00 0.12Org P (mg/L) 0.45 0.44 0.39 0.58 0.06PO4 (mg/L) 0.34 0.30 0.18 0.48 0.08Atrazine (ug/L) 0.42 0.42 0.34 0.50 0.05Metolachlor (ug/L) 0.06 0.07 0.04 0.08 0.01
Jul 30, 98 TN (mg/L) 3.14 3.33 1.40 4.55 1.03Rain = 3.70 Org N (mg/L) 1.50 1.59 0.68 2.30 0.49
NO3 (mg/L) 1.11 1.16 0.52 1.51 0.37NH3 (mg/L) 0.54 0.60 0.20 0.80 0.21TP (mg/L) 0.68 0.79 0.26 0.92 0.25Org P (mg/L) 0.12 0.10 0.04 0.24 0.06PO4 (mg/L) 0.57 0.62 0.20 0.86 0.24Atrazine (ug/L) 0.16 0.16 0.07 0.20 0.05Metolachlor (ug/L) 0.05 0.05 0.03 0.08 0.02
Aug 26, 98 TN (mg/L) 9.73 8.73 6.20 19.65 4.30Rain = 0.80 Org N (mg/L) 8.26 7.21 4.34 18.65 4.59
NO3 (mg/L) 1.04 0.93 0.46 2.11 0.58NH3 (mg/L) 0.43 0.36 0.25 0.75 0.19TP (mg/L) 2.39 1.95 1.61 5.47 1.28Org P (mg/L) 1.74 1.26 0.96 5.05 1.37PO4 (mg/L) 0.65 0.68 0.42 0.70 0.09Atrazine (ug/L) 0.05 0.05 0.04 0.07 0.01Metolachlor (ug/L) 0.01*
Sep 24, 98 TN (mg/L) 3.50 3.18 2.65 6.20 1.15Rain = 1.10 Org N (mg/L) 2.02 1.70 1.19 4.23 1.02
NO3 (mg/L) 1.16 1.13 0.80 1.52 0.24NH3 (mg/L) 0.32 0.30 0.27 0.45 0.06TP (mg/L) 1.13 1.08 0.71 2.02 0.42Org P (mg/L) 0.67 0.58 0.33 1.44 0.37PO4 (mg/L) 0.46 0.47 0.38 0.58 0.06Atrazine (ug/L) 0.03 0.03 0.03 0.04 0.00Metolachlor (ug/L) 0.01*
Data from eight runoff samples collected within three hours of sampler activationRain = inches in 48 hours prior to sampling 0.01* = Herbicide registered under detection limit of 0.02 ug/L
Appendix C: Descriptive statistics for nutrients and pesticides in Townsend runoff, field samplerStandard
Date Nutrient Mean Median Low High DeviationSep 30, 98 TN (mg/L) 4.09 4.15 2.00 7.30 1.83Rain =1.30 Org N (mg/L) 2.32 1.28 0.77 6.69 2.17
NO3 (mg/L) 1.65 1.65 0.35 3.91 1.50NH3 (mg/L) 0.12 0.10 0.06 0.26 0.07TP (mg/L) 1.02 0.68 0.48 2.26 0.71Org P (mg/L) 0.80 0.80 0.19 2.10 0.74PO4 (mg/L) 0.18 0.16 0.11 0.40 0.09Atrazine (ug/L) 0.03 0.03 0.02 0.03 0.00Metolachlor (ug/L) 0.01*
Oct 17, 98 TN (mg/L) 2.66 2.43 1.80 4.35 0.87Rain = 1.40 Org N (mg/L) 2.19 2.10 1.51 3.05 0.59
NO3 (mg/L) 0.39 0.30 0.21 0.95 0.25NH3 (mg/L) 0.09 0.04 0.03 0.35 0.11TP (mg/L) 0.81 0.77 0.58 1.23 0.20Org P (mg/L) 0.63 0.62 0.40 0.83 0.14PO4 (mg/L) 0.23 0.22 0.16 0.28 0.04Atrazine (ug/L) 0.03 0.03 0.02 0.04 0.01Metolachlor (ug/L) 0.01*
Nov 1, 98 TN (mg/L) 1.56 1.54 0.98 2.05 0.34Rain = 4.90 Org N (mg/L) 1.47 1.47 0.88 1.89 0.34
NO3 (mg/L) 0.03 .02.21 0.01 0.08 0.03NH3 (mg/L) 0.06 0.06 0.05 0.08 0.01TP (mg/L) 0.43 0.43 0.38 0.49 0.03Org P (mg/L) 0.11 0.11 0.10 0.13 0.01PO4 (mg/L) 0.32 0.31 0.28 0.35 0.03Atrazine (ug/L) 1.00 1.14 0.19 1.48 0.42Metolachlor (ug/L) 0.01*
Jun 18, 99 TN (mg/L) 2.91 2.24 1.96 7.59 1.91Rain = 0.80 TP (mg/L) 1.04 0.85 0.79 2.24 0.50
Atrazine (ug/L) 0.21 0.21 0.17 0.26 0.03Metolachlor (ug/L) 0.10 0.11 0.08 0.13 0.01
Aug 2, 99 TN (mg/L) 1.41 1.30 1.00 2.25 0.42Rain = 3.60 Org N (mg/L) 1.23 1.04 0.92 2.22 0.44
NO3 (mg/L) 0.19 0.21 0.07 0.30 0.12NH3 (mg/L) 0.10 0.10 0.03 0.20 0.07TP (mg/L) 0.94 0.88 0.82 1.39 0.19Org P (mg/L) 0.31 0.27 0.25 0.59 0.12PO4 (mg/L) 0.63 0.61 0.58 0.80 0.07Atrazine (ug/L) 0.26 0.13 0.09 1.16 0.37Metolachlor (ug/L) 0.18 0.05 0.02 1.04 0.35
Data from eight runoff samples collected within three hours of sampler activationRain = inches in 48 hours prior to sampling 0.01* = Herbicide registered under detection limit of 0.02 ug/L
Appendix C: Descriptive statistics for nutrients and pesticides in Townsend runoff, wetland sampler.Standard
Date Nutrient Mean Median Low High DeviationJul 30, 1998 TN (mg/L) 3.06 2.95 2.75 3.95 0.39Rain = 3.70 Org N (mg/L) 0.45 0.33 0.12 1.45 0.44
NO3 (mg/L) 1.02 1.01 0.71 1.17 0.14NH3 (mg/L) 1.59 1.57 1.43 1.90 0.16TP (mg/L) 0.68 0.62 0.50 1.24 0.23Org P (mg/L) 0.15 0.07 0.06 0.72 0.23PO4 (mg/L) 0.53 0.54 0.42 0.61 0.06Atrazine (ug/L) 3.37 3.68 1.03 4.64 1.45Metolachlor (ug/L) 3.17 3.60 0.84 4.63 1.36
Sep 30, 1998 TN (mg/L) 2.24 2.15 1.80 2.90 0.39Rain = 1.30 Org N (mg/L) 1.38 1.28 0.90 1.97 0.45
NO3 (mg/L) 0.70 0.64 0.46 1.12 0.25NH3 (mg/L) 0.17 0.16 0.13 0.23 0.04TP (mg/L) 0.69 0.63 0.53 0.93 0.16Org P (mg/L) 0.40 0.33 0.21 0.67 0.19PO4 (mg/L) 0.29 0.29 0.26 0.32 0.02Atrazine (ug/L) 0.07 0.07 0.05 0.10 0.02Metolachlor (ug/L) 0.02 0.02 0.01 0.03 0.01
Oct 17, 1998 TN (mg/L) 2.48 2.35 2.20 3.40 0.40Rain = 1.40 Org N (mg/L) 2.35 2.31 2.10 2.89 0.26
NO3 (mg/L) 0.03 0.02 0.01 0.09 0.03NH3 (mg/L) 0.10 0.07 0.02 0.42 0.13TP (mg/L) 0.78 0.78 0.61 1.06 0.15Org P (mg/L) 0.40 0.40 0.27 0.57 0.11PO4 (mg/L) 0.38 0.37 0.34 0.49 0.05Atrazine (ug/L) 0.03 0.03 0.02 0.04 0.01Metolachlor (ug/L) 0.22 0.21 0.04 0.44 0.13
Aug 2, 1999 TN (mg/L) 22.48 23.22 17.85 26.45 3.18Rain = 3.60 Org N (mg/L) 1.42 1.22 0.62 2.76 0.70
NO3 (mg/L) 19.15 18.55 15.75 22.40 2.59NH3 (mg/L) 1.91 2.06 0.94 2.88 0.63TP (mg/L) 1.17 1.04 0.58 2.33 0.55Org P (mg/L) 0.51 0.46 0.27 0.92 0.22PO4 (mg/L) 0.66 0.61 0.30 1.41 0.34Atrazine (ug/L) 14.39 15.47 11.41 16.67 2.39Metolachlor (ug/L) 16.43 16.80 13.40 19.03 2.10
Data from eight runoff samples collected within three hours of sampler activation. Rain = inches in 48 hours prior to sampling 0.01* = Herbicide registered under detection limit of 0.02 ug/L
Appendix C: Nutrient and herbicide concentrations in shallow groundwater on the Townsend farm.Sampling Date Cluster Depth (ft) TN Org N NO3 NH3 TP Org P PO4 Atrazine Metolachlor Jul 19, 1996 1 4 2.63 0.06 2.38 0.19 0.07 0.04 0.02 0.05 0.01*Rain = 0 1 8 8.03 3.98 4.05 0.01 0.02 0.01 0.01 0.03 0.01*
2 8 11.29 0.47 10.81 0.01 0.05 0.02 0.03 0.03 0.01*
Oct 22, 1996 1 1 - - 0.06 0.05 - - 0.07 0.01* 0.01*Rain = 0 1 4 - - 3.01 0.10 - - 0.03 0.01* 0.01*
1 8 - - 4.28 0.02 - - 0.01 0.01* 0.01*2 8 - - 0.18 0.02 - - 0.06 0.03 0.01*3 1 - - 0.38 0.21 - - 0.19 - -3 4 - - 0.49 0.06 - - 0.07 0.01* 0.01*
Nov 25, 1996 1 4 - - 1.41 0.04 - - 0.06 0.01* 0.01*Rain = 0.10 1 8 - - 13.34 0.97 - - 0.15 - -
2 1 - - 0.06 0.04 - - 0.06 0.01* 0.01*2 4 - - 0.43 0.08 - - 0.09 0.01* 0.01*2 8 - - 0.07 0.05 - - 0.04 0.01* 0.01*3 1 - - 0.23 0.04 - - 0.05 0.01* 0.01*3 4 - - 3.86 0.07 - - 0.01 0.01* 0.01*3 8 - - 3.56 0.02 - - - 0.01* 0.01*
Jun 14, 1997 1 1 0.36 0.32 0.04 0.00 0.10 0.03 0.06 0.19 0.26Rain = 0.50 1 4 4.32 0.23 4.09 0.01 0.02 0.00 0.02 0.05 0.08
1 8 4.18 0.36 3.82 - 0.02 0.01 0.01 0.06 0.022 8 2.32 0.32 2.00 0.00 0.06 0.03 0.03 0.07 0.063 4 0.34 0.29 - 0.05 0.09 0.00 0.09 - -3 8 12.16 0.61 11.55 - 0.15 0.07 0.09 - -
Aug 7, 1997 1 4 3.57 0.26 3.28 0.03 0.02 0.01 0.01 0.01* 0.02Rain = 0.10 1 8 4.12 0.01 4.34 0.05 0.01 0.00 0.01 0.01* -
2 8 2.91 0.15 2.66 0.10 0.02 0.01 0.01 0.03 0.023 8 8.08 0.53 7.52 0.03 0.09 0.06 0.03 0.01* 0.02
Jun 22, 1998 1 1 0.57 0.40 0.15 0.02 0.07 0.03 0.05 - 0.04Rain = 1.30 1 4 3.10 0.39 2.70 0.01 0.04 0.03 0.01 0.01* 0.04
1 8 3.59 0.11 3.46 0.02 0.00 - 0.01 0.09 -2 8 3.02 1.07 1.93 0.02 0.18 0.15 0.03 0.03 0.01*3 8 2.09 0.45 1.63 0.01 0.13 0.09 0.04 - -
Aug 4, 1998 1 1 0.30 0.28 0.02 0.00 0.06 - - - -Rain = 0 1 4 4.27 - 4.27 0.00 0.04 - - 0.03 0.04
1 8 3.94 0.08 3.86 0.00 0.04 - - 0.072 1 1.31 0.97 0.34 0.00 0.19 - - - -2 4 0.37 0.30 0.05 0.02 0.12 - - 0.07 -2 8 1.12 0.18 0.92 0.02 0.05 - - 0.04 0.01*3 1 1.42 1.05 0.36 0.01 0.19 - - 0.04 0.01*3 4 1.04 0.49 0.55 0.00 0.09 - - - -3 8 2.51 0.37 2.14 0.00 0.09 - - 0.03 -
Oct 28, 1998 1 4 3.44 0.03 3.40 0.01 0.00 - 0.01 - -Rain = 0 2 1 0.49 0.46 0.01 0.03 0.06 0.01 0.05 0.01* 0.01*
3 1 0.67 0.65 0.02 0.06 0.02 0.05 0.01* 0.01*3 4 4.81 0.28 4.49 0.05 0.15 0.02 0.13 0.01* 0.01*
Jul 15, 1999 1 1 0.60 0.60 - - 0.07 0.01 0.05 0.21 0.17Rain = 1.10 1 4 1.68 0.58 1.10 0.00 0.22 0.02 0.21 0.28 0.23
1 8 2.18 - 2.18 0.00 0.02 0.00 0.02 0.06 0.052 1 0.95 0.90 0.04 0.01 0.35 0.02 0.34 0.14 0.112 4 0.04 0.03 0.01 - 0.02 0.00 0.02 0.02 0.012 8 1.67 0.10 1.57 0.00 0.03 0.00 0.03 0.16 0.133 1 0.22 0.17 0.04 0.01 0.01 0.00 0.01 0.05 0.033 4 3.19 0.00 3.19 - 0.01 0.00 0.01 0.06 -3 8 0.74 0.00 0.74 0.00 0.00 0.00 0.00 0.15 0.04
0.01* = Herbicde concentration less than detection limit of 0.02 u g/L.- indicates analysis for that sample not available.
Rain = inches in 48 hours prior to sampling, Depth = feet, (TN, Org N, NO 3, NH3, TP, Org P, PO4) = mg/L, Atrazine and Metolachlor = u g/L
Appendix C: Nutrient and herbicide concentrations in shallow groundwater on the Townsend farm.
Date Cluster Depth (ft) TN Org N NO3 NH3 TP Org P PO4 Atrazine Metolachlor Oct 3, 1999 1 1 0.27 0.25 - 0.02 0.02 0.00 0.02 0.01* 0.01*Rain = 0 1 4 3.00 0.04 2.94 0.02 0.02 0.00 0.02 0.01* 0.01*
1 8 2.69 0.06 2.62 0.01 0.01 - 0.01 0.01* 0.01*2 8 3.32 0.05 3.24 0.03 0.05 0.00 0.05 0.01* 0.01*3 8 4.98 0.31 4.64 0.03 0.07 0.01 0.06 0.01* 0.01*
Dec 9, 1999 1 1 0.97 0.12 0.83 0.02 0.04 0.00 0.04 0.01* 0.01*Rain = 0 1 4 2.86 0.02 2.84 0.00 0.02 0.00 0.02 0.01* 0.01*
1 8 3.65 0.00 3.65 0.00 0.02 0.00 0.02 0.01* 0.01*2 8 4.24 0.00 4.24 0.00 0.06 0.00 0.06 0.01* 0.01*3 8 4.88 0.00 4.88 0.00 0.09 0.00 0.09 0.01* 0.01*
May 31, 2000 2 1 2.34 0.92 1.37 0.05 0.32 0.03 0.29 0.01* 0.01*Rain = 0.70 2 8 2.82 0.35 2.46 0.01 0.02 - 0.02 0.03 -
3 1 2.99 0.42 2.55 0.02 0.02 0.01 0.01 0.03 0.013 4 0.22 0.10 0.11 0.01 0.04 0.03 0.02 0.02 0.01*3 8 3.76 0.49 3.26 0.01 0.01 0.00 0.00 0.01* 0.01*
Jul 19, 2000 1 1 0.63 0.35 0.28 0.00 0.02 0.00 0.02 0.06 0.01*Rain = 0.20 1 4 2.97 0.71 2.25 0.01 0.01 0.00 0.01 0.04 0.01*
1 8 4.92 1.09 3.82 0.01 0.01 0.00 0.01 0.01* 0.01*2 8 3.49 0.91 2.57 0.01 0.02 0.01 0.02 0.04 0.01*3 8 3.03 0.73 2.30 0.00 0.06 0.00 0.06 0.01* 0.01*
Rain = inches in 48 hours prior to sampling, Depth = feet, (TN, Org N, NO 3, NH3, TP, Org P, PO4) = mg/L, Atrazine and Metolachlor = u g/L
0.01* = Herbicde concentration less than detection limit of 0.02 u g/L.
- indicates analysis for that sample not available.
Sampling Date Site TN Org N NO3 NH3 TP Org P PO4 Atrazine Metolachlor Jul 19, 1996 3 0.63 0.26 0.33 0.04 0.04 0.02 0.02 0.01* 0.01*Rain = 0
Oct 22, 1996 2 0.39 0.16 0.20 0.03 0.11 0.10 0.01 0.18 0.01*Rain = 0 3 0.69 0.10 0.57 0.02 0.05 0.04 0.02 0.08 0.01*
Jun 11, 1997 2 0.49 0.24 0.22 0.03 0.04 0.02 0.02 0.21 0.06Rain = 0 3 0.81 0.34 0.44 0.03 0.03 0.01 0.02 0.19 0.22
Jul 28, 1997 2 9.80 9.57 0.10 0.13 1.04 1.01 0.03 0.40 0.10Rain = 0.80 3 10.60 10.14 0.39 0.07 0.87 0.83 0.04 0.33 0.08
Oct 28, 1998 1 0.50 0.50 0.00 0.00 0.06 0.00 0.06 0.03 0.01*Rain = 0 2 0.86 0.35 0.45 0.06 0.06 0.05 0.01 0.09 0.01*
3 1.16 0.21 0.95 0.00 0.02 0.00 0.02 0.33 0.01*
Aug 4, 1999 1 2.00 0.37 1.59 0.04 0.16 0.08 0.09 0.64 0.09Rain = 3.60 2 0.90 0.36 0.52 0.02 0.07 0.05 0.02 0.73 0.07
3 1.11 0.35 0.70 0.06 0.13 0.09 0.04 0.95 0.29
May 18, 2000 1 0.32 0.28 0.01 0.03 0.07 0.06 0.02 0.03 0.01*Rain = 0 2 0.83 0.75 0.02 0.06 0.12 0.09 0.03 0.06 0.01*
3 0.87 0.30 0.54 0.03 0.08 0.06 0.02 - -
Jun 15, 2000 1 0.77 0.54 0.01 0.22 0.21 0.21 0.01 0.11 0.04Rain = 0.30 2 0.38 0.34 0.02 0.02 0.01 0.01 0.01 0.14 0.04
3 2.03 0.44 1.50 0.09 0.11 0.09 0.02 0.30 0.06
0.01* = Herbicide registered under detection limit of 0.02 ug/L - indicates analysis for that sample not available.
Appendix C: Nutrients and herbicide concentrations at three sites in Townsend's wetland.
Rain = inches in 48 hours prior to sampling, (TN, Org N, NO 3, NH3, TP, Org P, PO4) = mg/L, Atrazine and Metolachlor = u g/L
Appendix D: Nutrients and herbicide concentration statistics for Burr runoff: lower sampler.Standard
Sampling Date Nutrient Mean Median Low High Deviation 23 Jun, 1997 TN (mg/L) 19.10 19.80 15.40 20.80 2.12Rain = 1.60 Org N (mg/L) 16.84 17.11 13.65 19.29 2.11
NO3 (mg/L) 1.06 1.20 0.07 1.52 0.50NH3 (mg/L) 1.20 0.34 0.31 5.40 2.06TP (mg/L) 4.57 4.65 3.55 5.34 0.59Org P (mg/L) 4.36 4.34 3.28 5.29 0.73PO4 (mg/L) 0.14 0.06 0.05 0.32 0.12Atrazine (ug/L) 64.95 75.44 1.25 120.40 53.17Metolachlor (ug/L) 267.21 348.96 2.71 447.38 205.97
29 Jul, 1997 TN (mg/L) 4.69 3.34 0.70 12.35 4.33Rain = 4.70 Org N (mg/L) 3.46 1.97 0.22 10.71 3.73
NO3 (mg/L) 1.15 0.70 0.39 2.75 0.88NH3 (mg/L) 0.07 0.06 0.04 0.14 0.04TP (mg/L) 0.97 0.90 0.53 1.95 0.46Org P (mg/L) 0.43 0.16 0.02 1.55 0.54PO4 (mg/L) 0.65 0.60 0.18 1.42 0.43Atrazine (ug/L) 1.43 0.21 0.06 6.96 2.50Metolachlor (ug/L) 1.62 0.16 0.03 7.85 2.86
4 Aug, 1998 TN (mg/L) 2.73 1.85 1.35 8.55 2.41Rain = 1.50 Org N (mg/L) 1.12 0.87 0.42 1.55 0.40
NO3 (mg/L) 1.65 1.03 0.28 7.14 2.26NH3 (mg/L) 0.16 0.15 0.02 0.33 0.11TP (mg/L) 0.82 0.76 0.48 1.27 0.32Org P (mg/L) 0.18 0.14 0.00 0.46 0.17PO4 (mg/L) 0.64 0.62 0.24 1.18 0.38Atrazine (ug/L) 0.88 0.41 0.54 1.40 0.28Metolachlor (ug/L) 0.77 0.23 0.04 2.31 0.92
1 Nov, 1998 TN (mg/L) 5.45 5.30 4.40 6.95 0.94Rain = 3.20 Org N (mg/L) 2.81 2.76 2.54 3.16 0.25
NO3 (mg/L) 2.53 2.43 1.77 3.66 0.67NH3 (mg/L) 0.17 0.17 0.15 0.19 0.02TP (mg/L) 3.03 3.15 2.08 3.60 0.48Org P (mg/L) 0.23 0.23 0.13 0.37 0.07PO4 (mg/L) 2.80 2.92 1.82 3.39 0.52Atrazine (ug/L) 0.06 0.06 0.03 0.10 0.03Metolachlor (ug/L) 0.06 0.06 0.06 0.06 0.00
24 Jul, 1999 TN (mg/L) 3.51 2.65 2.05 10.20 2.72Rain = 1.30 Org N (mg/L) 1.12 1.22 0.42 1.55 0.40
NO3 (mg/L) 1.90 0.82 0.75 8.78 2.79NH3 (mg/L) 0.49 0.43 0.36 1.00 0.21TP (mg/L) 1.27 1.37 0.85 1.55 0.26Org P (mg/L) 0.11 0.10 0.06 0.18 0.05PO4 (mg/L) 1.16 1.22 0.79 1.44 0.25Atrazine (ug/L) 0.13 0.12 0.10 0.19 0.04Metolachlor (ug/L) 0.02 0.02 0.01 0.07 0.02
Data from eight runoff samples collected within three hours of sampler activation. Rain = inches in 48 hours prior to sampling
Appendix D: Nutrients and herbicide concentration statistics for Burr runoff: upper sampler.Standard
Sampling Date Nutrient Mean Median Low High Deviation 29 Jul, 1997 TN (mg/L) 2.99 3.03 1.28 5.63 1.38Rain = 4.70 Org N (mg/L) 2.01 1.99 0.58 4.15 1.10
NO3 (mg/L) 0.88 0.95 0.44 1.33 0.31NH3 (mg/L) 0.10 0.10 0.06 0.14 0.03TP (mg/L) 0.93 0.93 0.44 1.40 0.31Org P (mg/L) 0.8 0.79 0.28 1.34 0.37PO4 (mg/L) 0.13 0.08 0.05 0.45 0.13Atrazine (ug/L) 0.59 0.53 0.19 1.09 0.32Metolachlor (ug/L) 0.40 0.45 0.03 0.55 0.16
24 Jul, 1998 TN (mg/L) 2.71 2.65 2.40 3.20 0.24Rain = 1.70 Org N (mg/L) 1.38 1.35 1.03 1.85 0.24
NO3 (mg/L) 1.33 1.38 1.13 1.44 0.11NH3 (mg/L) 0.08 0.04 0.00 0.27 0.09TP (mg/L) 0.98 0.99 0.89 1.08 0.06Org P (mg/L) 0.24 0.21 0.15 0.41 0.09PO4 (mg/L) 0.74 0.71 0.65 0.85 0.08Atrazine (ug/L) 2.05 1.97 1.73 2.47 0.30Metolachlor (ug/L) 0.07 0.07 0.05 0.08 0.01
1 Nov, 1998 TN (mg/L) 6.62 7.35 2.15 8.70 2.21Rain = 3.20 Org N (mg/L) 1.44 1.33 0.92 2.15 0.45
NO3 (mg/L) 4.69 4.94 0.71 6.70 1.97NH3 (mg/L) 0.52 0.57 0.21 0.65 0.14TP (mg/L) 1.88 1.98 0.90 2.19 0.42Org P (mg/L) 0.29 0.29 0.24 0.37 0.05PO4 (mg/L) 1.59 1.69 0.64 1.94 0.14Atrazine (ug/L) 0.04 0.04 0.03 0.05 0.01Metolachlor (ug/L) 0.04 0.04 0.03 0.05 0.01
24 Jul, 1999 TN (mg/L) 2.84 2.60 2.30 3.70 0.56Rain = 1.30 Org N (mg/L) 1.02 0.94 0.68 1.43 0.29
NO3 (mg/L) 1.30 1.30 1.07 1.54 0.18NH3 (mg/L) 0.52 0.45 0.37 0.82 0.18TP (mg/L) 1.57 1.54 1.15 1.99 0.25Org P (mg/L) 0.1 0.08 0.03 0.21 0.06PO4 (mg/L) 1.47 1.48 0.95 1.87 0.27Atrazine (ug/L) 0.47 0.51 0.09 0.61 0.16Metolachlor (ug/L) 0.03 0.03 0.01 0.03 0.01
Data from eight runoff samples collected within three hours of sampler activation. Rain = inches in 48 hours prior to sampling
Appendix E: Nutrient and herbicide concentration statistics for Howell runoff.Standard
Sampling Date Nutrient Mean Median Low High Deviation Jun 11, 1998 TN (mg/L) 6.61 6.18 3.40 11.35 2.77Rain = 0.70 Org N (mg/L) 6.01 5.56 3.27 10.52 2.62
NO3 (mg/L) 0.53 0.53 0.44 0.66 0.09NH3 (mg/L) 0.15 0.13 0.11 0.19 0.03TP (mg/L) 2.46 1.89 1.37 5.82 1.48Org P (mg/L) 2.19 1.60 1.13 5.62 1.49PO4 (mg/L) 0.27 0.25 0.20 0.32 0.04Atrazine (ug/L) 0.25 0.22 0.19 0.40 0.08Metolachlor (ug/L) 0.09 0.07 0.06 0.16 0.04
Sep 28, 1998 TN (mg/L) 1.90 1.90 1.75 2.05 0.11Rain = 4.40 Org N (mg/L) 1.78 1.71 1.62 1.97 0.13
NO3 (mg/L) 0.06 0.05 0.01 0.17 0.06NH3 (mg/L) 0.08 0.07 0.06 0.11 0.02TP (mg/L) 1.65 1.65 1.62 1.66 0.01Org P (mg/L) 0.10 0.10 0.06 0.15 0.03PO4 (mg/L) 1.55 1.56 1.49 1.58 0.03Atrazine (ug/L) 0.11 0.04 0.04 0.34 0.14Metolachlor (ug/L) 0.12 0.12 0.10 0.15 0.01
Nov 10, 1998 TN (mg/L) 3.34 3.25 3.05 3.75 0.27Rain = 0.70 Org N (mg/L) 0.22 0.09 0.05 0.66 0.29
NO3 (mg/L) 1.10 1.05 0.96 1.56 0.19NH3 (mg/L) 2.52 2.51 1.43 3.40 0.66TP (mg/L) 1.83 1.81 1.60 2.11 0.16Org P (mg/L) 0.15 0.16 0.01 0.32 0.10PO4 (mg/L) 1.67 1.66 1.59 1.79 0.07Atrazine (ug/L) 0.01*Metolachlor (ug/L) 0.01*
Jun 22, 1999 TN (mg/L) 4.09 3.88 3.19 4.98 0.61Rain = 0.80 TP (mg/L) 0.41 0.40 0.38 0.46 0.03
Atrazine (ug/L) 0.20 0.19 0.18 0.23 0.02Metolachlor (ug/L) 0.09 0.1 0.08 0.1 0.01
Jun 2, 2000 TN (mg/L) 2.53 2.11 1.73 5.02 1.12Rain = 0.80 TP (mg/L) 2.42 2.38 2.09 2.74 0.02
Atrazine (ug/L) 0.26 0.27 0.19 0.31 0.05Metolachlor (ug/L) 0.09 0.09 0.08 0.11 0.01
Jul 17, 2000 TN (mg/L) 1.63 1.45 1.27 3.17 0.63Rain = 1.50 Org N (mg/L) 1.28 1.09 0.97 2.70 0.58
NO3 (mg/L) 0.31 0.31 0.27 0.35 0.03NH3 (mg/L) 0.04 0.03 0.02 0.12 0.04TP (mg/L) 1.43 1.30 1.26 2.28 0.35Org P (mg/L) 0.28 0.15 0.12 1.13 0.35PO4 (mg/L) 1.15 1.14 1.07 1.30 0.07Atrazine (ug/L) 0.05 0.05 0.03 0.08 0.02Metolachlor (ug/L) 0.01*
Rain = inches in 48 hours prior to sampling Data from eight runoff samples collected within three hours of sampler activation. 0.01* = Herbicide concentrations less than detection limit of 0.02 u g/L .
Sampled at eight feet at three locations in the converted field.Sampling Date Cluster TN Org N NO3 NH3 TP Org P PO4 Atrazine Metolachlor Sep 7, 1996 1 1.52 0.01 1.40 0.11 0.11 0.03 0.09 0.01* 0.01*
Rain = 0.40
Oct 22, 1996 1 - - 1.43 0.03 - - 0.17 0.01* 0.01*Rain = 0.20 2 - - 0.67 0.06 - - 0.17 0.01* 0.01*
3 - - 0.14 0.02 - - 0.12 0.01* 0.01*
Nov 25, 1996 1 - - 1.68 0.03 - - 0.17 0.01* 0.01*Rain = 0 2 - - 0.41 0.05 - - 0.17 0.01* 0.01*
3 - - 0.32 0.02 - - 0.11 0.01* 0.01*
Jun 11, 1998 1 1.33 - 1.38 0.01 0.19 - 0.20 0.01* 0.01*Rain = 1.20 2 0.61 0.02 0.58 0.01 0.19 - 0.19 0.01* 0.01*
3 0.19 0.16 0.02 0.01 0.09 0.01 0.07 0.01* 0.01*
Sep 23, 1998 1 0.37 0.01 0.35 0.01 0.22 - 0.22 0.01* 0.01*Rain = 3.50 2 0.05 0.04 0.01 0.00 0.21 0.00 0.21 0.01* 0.01*
3 0.50 0.48 0.01 0.01 0.09 0.07 0.02 0.01* 0.01*
Jul 13, 1999 1 - - - 0.01 0.19 0.02 0.18 0.04 0.03Rain = 0.10 2 0.81 0.22 0.02 0.57 0.21 0.04 0.17 0.03 0.02
3 0.11 0.11 0.00 0.00 0.03 0.00 0.03 0.03 0.03
Sep 9, 1999 1 - - 0.01 0.01 0.27 - 0.27 0.01* 0.01*Rain = 0.20 2 - - - 0.05 0.25 - 0.25 0.01* 0.01*
3 0.08 0.08 - - 0.07 - 0.07 0.01* 0.01*
Dec 13, 1999 1 0.11 0.04 0.07 - 0.28 - 0.28 0.01* 0.01*Rain = 0 2 0.16 0.07 0.09 0.00 0.26 - 0.26 0.01* 0.01*
3 0.39 0.29 0.06 0.04 0.07 - 0.07 0.01* 0.01*
Jul 6, 2000 1 0.19 0.06 0.12 0.01 0.24 0.06 0.18 0.01* 0.01*Rain = 1.70 2 0.18 0.06 0.11 0.01 0.19 0.05 0.14 0.01* 0.01*
3 0.66 0.23 0.10 0.33 0.06 0.04 - 0.01* 0.01*
Jul 17, 2000 1 0.12 0.05 0.07 - 0.26 0.00 0.25 0.01* 0.01*Rain = 1.80 2 0.04 0.03 0.01 - 0.20 - 0.20 0.01* 0.01*
0.01* = Herbicde concentration less than detection limit of 0.02 u g/L.
- indicates analysis for that sample not available.
Appendix E: Nutrient and herbicide concentrations in shallow ground water on the Howell farm.
Rain = inches in 48 hours prior to sampling, (TN, Org N, NO3, NH3, TP, Org P, PO4) = mg/L, Atrazine and Metolachlor = u g/L
Date Site TN Org N NO3 NH3 TP Org P PO4 Atrazine Metolachlor Bacteria Oct 22, 1996 1 - - 0.65 0.03 - - 0.30 0.05 0.01* 330Rain = 0.20 2 - - 0.14 0.02 - - 0.20 0.08 0.01* 740
3 - - 0.09 0.02 - - 0.20 0.05 0.01* 280
Nov 25, 1996 1 - - 1.24 0.07 - - 0.09 0.18 0.01* -Rain = 0 2 - - 1.24 0.08 - - 0.10 0.10 0.01* -
3 - - 1.26 0.08 - - 0.09 0.10 0.01* -
Jun 12, 1998 1 1.31 0.56 0.71 0.04 0.20 0.13 0.08 0.14 0.01* 584Rain = 0.20 2 1.02 0.23 0.74 0.05 0.10 0.03 0.08 0.14 0.05 532
3 0.96 0.29 0.64 0.03 0.09 0.02 0.07 0.14 0.01* 748
Sep 9, 1998 1 0.50 0.27 0.17 0.06 0.08 0.03 0.05 0.07 0.05 164Rain = 0 2 0.82 0.28 0.49 0.05 0.04 0.01 0.03 0.07 0.06 68
3 0.39 0.17 0.16 0.06 0.06 0.01 0.05 0.07 0.02 244
Dec 31, 1998 1 1.43 0.30 1.12 0.01 0.03 0.01 0.02 0.01* 0.01* 18Rain = 0 2 1.36 0.15 1.20 0.01 0.03 0 0.02 0.01* 0.01* 14
3 1.51 0.23 1.27 0.01 0.03 0 0.03 0.01* 0.01* 10
Jun 9, 1999 1 1.23 0.18 0.99 0.06 0.08 0.01 0.07 0.51 0.11 670Rain = 0 2 1.19 0.14 1.03 0.02 0.10 0.04 0.06 0.50 0.11 860
3 1.18 0.15 0.97 0.06 0.08 0.01 0.07 0.45 0.11 1040
Aug 13, 1999 1 2.09 0.35 1.73 0.01 0.13 0.03 0.10 1.22 1.19 24Rain = 1.60 2 2.29 0.47 1.81 0.01 0.15 0.04 0.11 2.38 1.71 708
3 2.18 0.39 1.78 0.01 0.16 0.05 0.11 2.17 2.54 24
Nov 11, 1999 1 0.24 0.22 0.01 0.01 0.14 0.02 0.13 0.07 0.01* 176Rain = 0 2 0.31 0.26 0.04 0.01 0.15 0.01 0.13 0.08 0.01* 88
3 0.30 0.29 0.01 0.17 0.02 0.15 0.07 0.02 0
May 17, 2000 1 0.60 0.26 0.28 0.06 0.14 0.03 0.11 0.25 0.15 0Rain = 0 2 0.77 0.32 0.35 0.10 0.17 0.03 0.14 0.31 0.20 0
3 0.70 0.29 0.33 0.08 0.19 0.05 0.14 0.32 0.22 340
Jul 6, 2000 1 0.58 0.30 0.23 0.05 0.21 0.07 0.14 2.81 0.05 276Rain = 1.15 2 0.93 0.50 0.37 0.06 0.25 0.08 0.17 7.86 0.06 186
3 0.70 0.42 0.21 0.07 0.27 0.09 0.18 7.34 0.07 369
Jul 17, 2000 1 2.48 0.90 1.53 0.05 0.44 0.22 0.22 0.85 0.22 >> 2000Rain = 1.70 2 2.01 0.92 1.03 0.06 0.39 0.21 0.18 1.24 0.15 >> 2000
3 1.99 0.93 1.01 0.05 0.41 0.22 0.18 1.11 0.15 >> 2000
Aug 7, 2000 1 0.22 0.11 0.07 0.04 0.15 0.06 0.09 0.27 0.02 168Rain = 0.10 2 0.65 0.26 0.20 0.19 0.37 0.08 0.28 0.24 0.03 296
3 0.45 0.41 0.03 0.01 0.27 0.10 0.17 0.33 0.03 440
0.01* = Herbicde concentration less than detection limit of 0.02 u g/L. - indicates analysis for that sample not available.
Appendix E: Nutrients and herbicide concentrations at three sites on Corndodger Creek
Rain = inches in 48 hours prior to sampling, (TN, Org N, NO 3, NH3, TP, Org P, PO4) = mg/L, Atrazine and Metolachlor = u g/L Bacteria = Coliform colonies/100 mL; 1 = much greater than 2000 colonies/100 mL.
Appendix F: Descriptive statistics for nutrients and pesticides in Kunard runoff. Standard Date Nutrient Mean Median Low High Deviation 2 Jun, 1998 TN (mg/L) 2.51 2.50 2.20 3.10 0.28 Rain = 1.50 Org N (mg/L) 1.76 1.74 1.53 2.18 0.21 NO3 (mg/L) 0.71 0.70 0.65 0.85 0.06 NH3 (mg/L) 0.04 0.04 0.02 0.07 0.02 TP (mg/L) 0.80 0.81 0.71 0.94 0.07 Org P (mg/L) 0.32 0.30 0.29 0.38 0.03 PO4 (mg/L) 0.48 0.48 0.41 0.56 0.06 Atrazine (ug/L) 0.13 0.12 0.11 0.14 0.01 Metolachlor (ug/L) 0.01* 5 Oct, 1998 TN (mg/L) 2.44 2.30 2.05 2.90 0.36 Rain = 2.20 Org N (mg/L) 2.22 2.17 1.78 2.65 0.36 NO3 (mg/L) 0.16 0.16 0.10 0.23 0.05 NH3 (mg/L) 0.06 0.05 0.02 0.14 0.04 TP (mg/L) 0.67 0.65 0.56 0.82 0.08 Org P (mg/L) 0.33 0.31 0.23 0.44 0.08 PO4 (mg/L) 0.34 0.34 0.24 0.46 0.07 Atrazine (ug/L) 0.02 0.02 0.01 0.03 0.01 Metolachlor (ug/L) 0.01* 28 Jun, 1999 TN (mg/L) 2.65 2.00 1.17 7.20 1.93 Rain = 3.60 TP (mg/L) 0.56 0.51 0.35 0.99 0.19 Atrazine (ug/L) 0.12 0.13 0.09 0.14 0.02 Metolachlor (ug/L) 0.08 0.08 0.07 0.09 0.01 Data from eight runoff samples collected within three hours of sampler activation. Rain = inches in 48 hours prior to sampling 0.01* = Herbicide registered under detection limit of 0.02 ug/L Appendix F: Nutrient and herbicide concentrations in shallow groundwater on the Kunard farm. Sampling Date Cluster Depth (ft) TN Org N NO3 NH3 TP Org P PO4 Atrazine Metolachlor Aug 4, 1998 1 4 0.69 0.32 0.36 0.01 0.05 0.00 0.05 0.03 0.01* Sep 16, 1998 1 4 0.43 0.38 0.04 0.01 0.09 0.01 0.08 0.03 0.01* Jul 2,1999 1 4 0.29 0.18 0.10 0.01 0.02 0.01 0.01 0.17 0.04 2 4 0.64 0.00 0.63 0.00 0.08 0.02 0.06 0.01* 0.01* Dec 14, 1999 1 4 0.29 0.21 0.07 0.01 0.06 0.01 0.05 0.01* 0.01* 2 4 0.23 0.20 0.03 0.00 0.06 0.00 0.06 0.01* 0.01* May 3, 2000 1 4 0.14 0.09 0.04 0.01 0.03 0.01 0.02 0.02 0.01* 2 4 0.16 0.03 0.09 0.04 0.06 0.01 0.05 0.01* 0.01* Jul 12, 2000 1 4 0.25 0.23 0.02 0.00 0.04 0.00 0.04 0.04 0.01* 2 4 0.29 0.18 0.04 0.07 0.06 0.01 0.05 0.01* 0.01* Rain = inches in 48 hours prior to sampling, Depth = feet, (TN, Org N, NO3, NH3, TP, Org P, PO4) = mg/L, Atrazine and Metolachlor = ug/L
0.01* = Herbicde concentration less than detection limit of 0.02 ug/L.
Appendix G: Descriptive statistics for nutrients and herbicides in Peters' runoff. Standard
Sampling Date Nutrient Mean Median Low High DeviationJun 22, 1998 TN (mg/L) 3.06 2.50 2.10 5.50 1.19Rain = 2.20 Org N (mg/L) 1.99 1.42 1.02 4.59 1.18
NO3 (mg/L) 0.95 0.87 0.74 1.54 0.26NH3 (mg/L) 0.12 0.09 0.06 0.26 0.07TP (mg/L) 0.49 0.36 0.28 1.16 0.30Org P (mg/L) 0.35 0.23 0.13 1.12 0.34PO4 (mg/L) 0.14 0.15 0.04 0.18 0.04Atrazine (ug/L) 2.45 2.38 1.51 3.26 0.66Metolachlor (ug/L) 0.65 0.64 0.56 0.74 0.07
Jul 30, 1998 TN (mg/L) 3.08 3.08 2.90 3.25 0.25Rain = 2.00 Org N (mg/L) 1.94 0.19 1.79 2.08 0.21
NO3 (mg/L) 0.66 0.66 0.65 0.67 0.01NH3 (mg/L) 0.48 0.48 0.46 0.50 0.03TP (mg/L) 0.71 0.71 0.65 0.78 0.07Org P (mg/L) 0.59 0.59 0.53 0.65 0.09PO4 (mg/L) 0.13 0.13 0.13 0.13 0.00Atrazine (ug/L) 0.13 0.13 0.12 0.13 0.01Metolachlor (ug/L) 0.07 0.07 0.05 0.09 0.03
Sep 20, 1998 TN (mg/L) 2.53 2.40 2.20 2.95 0.29Rain = 4.20 Org N (mg/L) 2.41 2.37 1.98 2.67 0.28
NO3 (mg/L) 0.03 0.02 0.01 0.06 0.02NH3 (mg/L) 0.10 0.02 0.02 0.27 0.12TP (mg/L) 1.69 1.88 0.85 2.12 0.49Org P (mg/L) 0.25 0.25 0.04 0.46 0.29PO4 (mg/L) 1.60 1.88 0.39 2.12 0.70Atrazine (ug/L) 0.13 0.15 0.05 0.20 0.07Metolachlor (ug/L) 0.01*
Oct 2,1998 TN (mg/L) 1.46 1.45 1.05 2.00 0.28Rain = 4.1 Org N (mg/L) 1.03 1.27 0.33 1.33 0.40
NO3 (mg/L) 0.40 0.22 0.16 0.90 0.31NH3 (mg/L) 0.03 0.02 0.01 0.10 0.03TP (mg/L) 1.03 1.08 0.41 1.38 0.35Org P (mg/L) 0.07 0.05 0.01 0.21 0.07PO4 (mg/L) 0.98 1.07 0.35 1.36 0.40Atrazine (ug/L) 0.10 0.11 0.05 0.14 0.04Metolachlor (ug/L) 0.16 0.18 0.04 0.28 0.10
Oct 11, 1998 TN (mg/L) 0.32 0.29 0.25 0.47 0.01Rain = 1.50 Org N (mg/L) 0.12 0.13 0.08 0.15 0.02
NO3 (mg/L) 0.16 0.13 0.12 0.23 0.05NH3 (mg/L) 0.03 0.03 0.02 0.11 0.03TP (mg/L) 0.01 0.01 0.01 0.01 0.00Org P (mg/L) 0.00 0.00 0.00 0.00 0.00PO4 (mg/L) 0.01 0.01 0.01 0.01 0.00Atrazine (ug/L) 0.02 0.01 0.01 0.03 0.01Metolachlor (ug/L) 0.03 0.03 0.03 0.04 0.01
Nov 10, 1998 TN (mg/L) 0.79 0.44 0.21 1.70 0.61Rain = 5.80 TP (mg/L) 0.26 0.14 0.05 0.64 0.22
Atrazine (ug/L) -Metolachlor (ug/L) -
Jun 16, 1999 TN (mg/L) 3.37 3.06 1.85 5.06 1.10Rain = 0.50 TP (mg/L) 0.34 0.21 0.12 0.65 0.24
Atrazine (ug/L) 45.36 23.87 0.63 134.07 52.75Metolachlor (ug/L) 0.77 0.52 0.23 1.88 0.65
Data from eight runoff samples collected within three hours of sampler activation, except Jul 30, 98 (n=2). 0.01* = Herbicide registered under detection limit of 0.02 ug/L
Appendix G: Descriptive statistics for nutrients and herbicides in Peters' runoff. StandardSampling Date Nutrient Mean Median Low High DeviationAug 1 1999 TN (mg/L) 5 79 4 95 4 55 8 10 1 46Rain = 0.40 Org N (mg/L) 0.45 0.45 0.19 0.84 0.21
NO3 (mg/L) 5.42 4.68 3.92 7.72 1.41NH3 (mg/L) 0.10 0.09 0.08 0.15 0.03TP (mg/L) 0.44 0.40 0.38 0.53 0.07Org P (mg/L) 0.14 0.12 0.1 0.17 0.03PO4 (mg/L) 0.30 0.29 0.25 0.39 0.05Atrazine (ug/L) 27.66 28.94 22.93 31.57 3.85Metolachlor (ug/L) 0.09 0.07 0.05 0.17 0.05
Nov 22, 1999 TN (mg/L) 19.53 17.25 7.30 32.40 8.67Rain = 2.40 TP (mg/L) 3.53 3.10 2.30 5.89 1.18
Atrazine (ug/L) -Metolachlor (ug/L) -
Dec 8, 1999 TN (mg/L) 1.75Rain = 1.60 Org N (mg/L) 1.12
NO3 (mg/L) 0.58 grab sample collected from snowmeltNH3 (mg/L) 0.05TP (mg/L) 0.61Org P (mg/L) 0.06PO4 (mg/L) 0.55Atrazine (ug/L) 0.21Metolachlor (ug/L) 0.05
Data from eight runoff samples collected within three hours of sampler activation, except Dec 8, 1999 (n=1). - indicates results of analysis unavailable. Appendix G: Nutrient and herbicide concentrations in groundwater for two depths on Peters farm. Sampling Date Depth (ft) TN Org N NO3 NH3 TP Org P PO4 Atrazine Metolachlor 22 Jul 1998 4 0.27 0.23 0.00 0.04 0.02 0.00 0.02 0.14 0.02 Rain = 0.50 8 0.31 0.30 0.00 0.01 0.03 0.01 0.02 0.08 0.03 4 Aug 1998 4 0.20 0.17 0.00 0.03 0.05 0.00 0.05 0.01* 0.03 Rain = 0.50 8 0.30 0.02 0.28 0.00 0.04 0.00 0.04 0.09 0.04 2 Dec 1998 1 1.05 0.97 0.01 0.07 0.13 0.08 0.05 0.01* 0.13 Rain = 0.50 4 1.46 0.63 0.03 0.80 0.10 0.00 0.10 0.01* 0.10 8 0.27 0.17 0.05 0.05 0.02 0.00 0.02 0.03 0.02 15 Jul 1999 4 0.12 0.11 0.01 0.00 0.02 0.00 0.02 1.29 0.02 Rain = 0.40 8 0.58 0.00 0.58 0.02 0.02 0.00 0.02 0.40 0.02 7 Sep 1999 8 0.98 0.32 0.64 0.02 0.03 0.00 0.03 0.03 0.03 Rain = 0.60 8 Dec 1999 4 0.21 0.20 0.00 0.01 0.04 0.00 0.04 0.02 0.04 Rain = 1.60 8 0.24 0.17 0.07 0.00 0.03 0.00 0.03 0.03 0.03 31 May 2000 4 0.05 0.02 0.01 0.02 0.06 0.02 0.04 0.02 0.06 Rain = 2.40 8 0.29 0.06 0.22 0.01 0.03 0.01 0.02 0.02 0.03 19 Jul 2000 4 0.13 0.13 0.00 0.00 0.01 0.00 0.01 0.04 0.01 Rain = 0.60 8 0.04 0.04 0.00 0.00 0.01 0.00 0.01 0.01* 0.01 Rain = inches in 48 hours prior to sampling, Depth = feet, (TN, Org N, NO3, NH3, TP, Org P, PO4) = mg/L, Atrazine and Metolachlor = ug/L 0.01* = Concentrations determined to be less than the laboratory detection limit of 0.02 ug/L.
ColiformSampling Date Pond TN Org N NO3 NH3 TP Org P PO4 Atrazine Metolachlor BacteriaJun 9, 1998 1* 3.35 1.93 1.33 0.09 0.48 0.31 0.17 0.12 0.02 95Rain = 0.30 2 2.15 2.10 0.03 0.02 0.18 0.18 0.00 0.14 0.01* 0
3 3.50 3.14 0.05 0.31 0.15 0.14 0.01 0.17 0.01* 30Jun 12, 1998 1* 2.75 1.26 1.41 0.09 0.49 0.32 0.17 0.12 0.02 61Rain = 0.30 2 2.30 2.26 0.03 0.01 0.20 0.20 0.00 0.14 0.01* 0
3 2.20 1.79 0.06 0.35 0.20 0.20 0.00 0.17 0.01* 30Jul 9, 1998 1* 2.68 2.59 0.08 0.02 0.22 0.20 0.02 0.13 0.04 565Rain = 0.10 2 2.60 2.60 0.00 0.00 0.19 0.19 0.00 0.22 0.03 >> 20001
3 4.65 4.60 0.03 0.02 0.45 0.43 0.01 0.20 0.03 388Jul 30, 1998 1* 1.68 1.41 0.13 0.21 0.25 0.12 0.08 0.09 0.02 773Rain = 1.70 2 1.52 2.20 0.03 0.05 0.09 0.18 0.00 0.05 0.01* 880
3 1.82 2.83 0.16 0.23 0.13 0.29 0.01 0.04 0.01* >> 20001
Sep 9, 1998 1* 1.68 1.68 0.01 0.21 0.25 0.17 0.08 0.05 0.01* 0Rain = 0 2 1.52 1.52 0.00 0.05 0.09 0.09 0.00 0.03 0.01* 10
3 1.82 1.82 0.02 0.23 0.13 0.12 0.01 0.03 0.01* 20Oct 19, 1998 1* 2.35 2.35 0.34 0.77 0.56 0.25 0.31 0.05 0.01* 1059Rain = 1.30 2 3.70 3.70 0.00 0.01 0.20 0.14 0.06 0.03 0.01* 76
3 1.08 1.08 0.12 0.02 0.13 0.11 0.02 0.03 0.01* 452Dec 9, 1998 1* 2.15 2.15 0.61 0.36 0.59 0.25 0.34 0.01* 0.01* 60Rain = 0.40 2 1.65 1.65 0.00 0.08 0.15 0.14 0.01 0.01* 0.01* 0
3 1.00 1.00 0.00 0.05 0.15 0.14 0.01 0.01* 0.01* 40Jun 9, 1999 1* 2.14 2.14 0.59 0.28 0.54 0.23 0.31 0.15 0.06 370Rain = 0 2 1.48 1.48 0.00 0.03 0.13 0.12 0.00 0.18 0.06 180
3 1.46 1.46 0.15 0.09 0.26 0.22 0.03 0.14 0.07 280Jul 1, 1999 1* 1.79 1.79 0.27 0.27 0.47 0.18 0.29 0.09 0.03 20Rain = 0.90 2 1.38 1.38 0.00 0.14 0.22 0.12 0.10 0.08 0.03 64
3 0.91 0.91 0.00 0.07 0.19 0.10 0.08 0.05 0.03 108Jul 14, 1999 1* 1.41 1.41 0.22 0.08 0.42 0.18 0.25 0.38 0.20 16Rain = 0.30 2 1.57 1.57 0.09 0.05 0.18 0.16 0.02 0.23 0.12 0
3 1.05 1.05 0.05 0.01 0.12 0.11 0.01 0.21 0.17 4Jul 26, 1999 1* 1.30 1.30 0.01 0.04 0.28 0.21 0.07 0.15 0.05 60Rain = 0 2 1.55 1.55 0.02 0.01 0.18 0.16 0.01 0.09 0.03 0
3 0.87 0.87 0.00 0.00 0.08 0.07 0.01 0.12 0.04 0Nov 11, 1999 1* 2.15 2.15 0.01 0.89 0.15 0.10 0.05 0.07 0.01* 0Rain = 0 2 1.99 1.99 0.00 0.01 0.18 0.17 0.01 0.06 0.01* 0
3 0.85 0.85 0.00 0.01 0.06 0.05 0.01 0.05 0.01* 0Dec 7, 1999 1* 2.78 2.78 0.16 1.42 0.12 0.10 0.02 0.06 0.01* 17Rain = 0.20 2 1.93 1.93 0.00 0.09 0.15 0.14 0.01 0.05 0.01* 0
3 0.95 0.95 0.10 0.13 0.05 0.05 0.01 0.04 0.01* 8Spring 5.03 0.56 4.46 0.01 0.05 0.00 0.05 0.01* 0.01* 0
May 18, 2000 1* 3.64 3.64 0.00 0.03 0.21 0.21 0.00 0.08 0.03 0Rain = 0.30 2 3.47 3.47 0.00 0.11 0.41 0.41 0.00 0.16 0.05 10
3 2.43 2.43 0.00 0.05 0.33 0.33 0.00 0.13 0.04 20Jul 1, 2000 1* 1.98 1.98 0.00 0.16 0.28 0.24 0.04 0.18 0.04 70Rain = 0.30 2 2.64 2.64 0.02 0.08 0.21 0.20 0.01 0.32 0.01* 20
3 2.18 2.18 0.00 0.02 0.22 0.21 0.01 0.21 0.01* 0Spring 5.24 0.26 4.97 0.01 0.09 0.08 0.01 0.01* 0.01* 0
Jul 17, 2000 1* 2.87 2.87 2.32 0.55 0.31 0.27 0.04 0.15 0.02 133Rain = 1.30 2 2.87 2.87 2.77 0.09 0.18 0.17 0.01 0.26 0.01* 50
3 2.56 2.56 2.24 0.30 0.28 0.27 0.01 0.12 0.01* >> 20001
Spring 4.65 0.27 4.38 0 0.04 0.01 0.03 0.01* 0.01* 0P1 mean value 2.29 2.09 0.47 0.34 0.35 0.21 0.14 0.13 0.05 206P2 mean value 2.10 2.14 0.01 0.05 0.18 0.17 0.02 0.13 0.05 284P3 mean value 1.83 1.85 0.19 0.12 0.18 0.18 0.01 0.11 0.06 634HUC 8 Watershed Average2 - - 0.69 0.08 0.27 - - - 1.27 1298Kansas Statewide Average2 - - 1.02 0.11 0.26 - - - 1.02 1422
Units: Atrazine and Metolachlor = ug/L, Bacteria = Coliform colonies/100 mL1* = Concentrations for Pond One are averaged from grab samples collected at three distinct sites on the pond.0.01* = Herbicide registered under detection limit of 0.02 ug/L>>20001 = much greater than 2000 Coliform bacteria colonies/100 mL.
2 = Values obtained from Appendix B, Kansas Nonpoint Source Pollution Management Plan - 2000 Update.
Appendix H: Nutrient, herbicide and bacteria concentrations in three ponds at the Hubbard ranch.
Units: Rain = inches in 48 hours prior to sampling, (TN, Org N, NO 3, NH3, TP, Org P, PO4) = mg/L