1. Authors: Megan Cole, Dan Mrotek, Nick Reynolds, Mitchell Schutte, and Tyler Wildman
Prepared for: Dodge County Land Conservation Department
and Wisconsin Department of Natural Resources
December 14, 2015
of a County-wide
Riparian Buffer Ordinance
in Dodge County, WI
EVALUATING THE FEASIBILITY

2.
Table of Contents
1.0 INTRODUCTION .......................................................................................................................... 1
2.0 BACKGROUND ........................................................................................................................... 1
2.1 GOALS AND OBJECTIVES ....................................................................................................................... 2
2.2 DODGE COUNTY LAND USE ................................................................................................................... 2
2.3 TYPES OF BUFFERS ............................................................................................................................... 3
2.4 BUFFER WIDTH AND EFFECTIVENESS ...................................................................................................... 5
2.5 MANAGEMENT OF RIPARIAN BUFFERS .................................................................................................. 11
2.5.1 Headwater Streams ................................................................................................................ 11
2.5.2 Maintenance ........................................................................................................................... 12
2.5.3 Managing Invasive Species ..................................................................................................... 12
2.6 ISSUES WITH IMPLEMENTATION ........................................................................................................... 12
2.6.1 Economics: .............................................................................................................................. 12
2.6.2 Complications with Drainage .................................................................................................. 13
3.0 ALTERNATIVES ......................................................................................................................... 15
3.1 REGULATORY APPROACHES ................................................................................................................. 15
3.1.1 Conservation Agriculture Methods ........................................................................................ 15
3.1.2 Nutrient Management ........................................................................................................... 16
3.1.3 Edge‐of‐field techniques ........................................................................................................ 17
3.2 VOLUNTARY .................................................................................................................................. 21
3.3 IMPLEMENTATION ALTERNATIVES ............................................................................................... 22
3.3.1 Farmer‐led Watershed Councils .............................................................................................. 22
4.0 RECOMMENDATIONS .............................................................................................................. 24
5.0 CONCLUSIONS ......................................................................................................................... 25
6.0 APPENDIX ................................................................................................................................ 26
6.1 APPENDIX A. TABLE OF THE SOIL TYPES OF DODGE COUNTY ..................................................................... 26
6.2 APPENDIX B. SUGGESTED TREES AND SHRUBS ........................................................................................ 31
7.0 REFERENCES ............................................................................................................................ 34
Acknowledgements
The authors would like to thank the following for their assistance in the completion in this report:
Laura Stremick‐Thompson – Wisconsin Department of Natural Resources
Marc Bethke – Dodge County Land Conservation Department
Dr. Neal O’Reilly, Ph.D., PH – Professor at the University of Wisconsin‐Milwaukee
Julia Olmstead – Coordinator with the St. Croix/Red Cedar River Basin, Farmer‐led Watershed
Councils
Nathan Utt – Environmental Engineer, EcoExchange

3. 1
1.0 INTRODUCTION
Dodge County is an area with a population of 88,759 and an estimated stream length of 1,649 miles.
Non‐point source pollution in the form of agricultural runoff can cause declining water quality. This is
definitely the case in Dodge County, where more than 90% of land use is agriculture. Large amounts of
associated runoff due to fertilizer use and farming practices are central to this issue. With a history of
poor water quality, the concerns of the county's citizens have continually increased. This report is an in‐
depth review of the effectiveness of riparian buffers and their implementation on a county‐wide scale.
2.0 BACKGROUND
Due to high levels of chemical runoff from agricultural fields, Dodge County has begun to consider
mandating practices that would help contribute to the reduction of these problems. Local stakeholders
have offered criticism as water pollution made wells undrinkable, and waterways unsightly. Policy
makers have struggled to find a solution that is fair to all involved.
With more than 5,000,000 pounds of nitrogen lost per year from farmer's fields in Dodge County, much
of it ends up in the streams, lakes, and groundwater that provide the population with potable water.
When nitrate levels were tested in the wells of Dodge County, more than 15% contained levels higher
that 10 mg/l, and an additional 20% contained between 1‐10 mg/l of nitrates. According to the EPA,
ingesting nitrate levels above 10 mg/l could lead to serious illness and death in infants. Safe drinking
water has since grown as a priority for the residents of Dodge County. (Masarik, Neuendor, Mechenich,
2007)
In addition to nitrogen running from fields into streams and lakes, the county is also concerned about
the levels of phosphorus that are entering waterways in the same manner. In 2014, an aquatic
monitoring station in Dodge County found an average total phosphorus value of 0.1465 mg/L which is
nearly double the state's total phosphorus criteria of 0.075 mg/L. (Cadmus Group, 2011) These high
levels of phosphorus encourage algal growth in lakes and lead to eutrophication. Although phosphorus
is an essential nutrient for plant growth, too much can lead to a loss of biodiversity and in turn reduce
the recreational potential for a waterway. (UW‐Extension, 2014)
To combat these unsafe levels of chemical runoff, the people of the county pushed to legally require all
farms to enact riparian buffers for every stream on their property. This action was not supported by all
shareholders within the county, and garnered a tie vote from the policy‐makers. While this may be
discouraging to some, it afforded more time to gather information and research the effectiveness of
stream buffers. This paper will focus on the viability of a stream buffer mandate, and whether or not this
injunction could be successful in the county. Although stream buffers are the focal point, some attention
will be given to alternative methods of chemical reduction in runoff from agricultural land.

4. 2
2.1 Goals and Objectives
The goal of this project is to research the feasibility of implementing mandatory stream buffers within
Dodge County.
 Determine effectiveness of a buffer based on width and vegetation.
 Estimate potential cost of implementing a county wide buffer ordinance, based on different
widths (including loss of agricultural revenue).
 Provide alternative practices for meeting water quality goals.
2.2 Dodge County Land Use
Using ArcMap GIS software, a representation of Dodge County was made, displaying the different types
of land use prominent throughout the county. As expected, our results show that agriculture occupies
the majority of the land within Dodge County. With the software, we also displayed lakes and rivers
within the county. Looking at figure 1, it is quite evident that there is a high potential for agricultural
runoff into water bodies due to the proximity of agricultural land to nearly any stream.
Figure 1 showing Dodge County by Land Use

5. 3
2.3 Types of Buffers
Buffers on agricultural land have a wide distribution in their function and intended purpose. The
removal efficiencies for differing pollutants change based on what type of buffer is used. The most
common buffers being implemented are grass filter strips, grassed waterways, contour buffer strips,
vegetative barriers, field borders, terrace tile inlet buffers, and forested buffers (NRCS, 2000). These
designs vary on the site conditions and designated purpose. When water is present within a field, the
most appropriate buffer is either the grassed waterway or contour buffer strips (Figure 2). Contour
buffer strips are designed to trap pesticides of sheet flow runoff that are positioned on the contour of a
field to slow water velocity. The other types of riparian buffers are edge of field buffers, which as the
name implies, are at the end of the field adjacent to the water body. Filter strips, vegetative barriers,
and field borders are designed to act as a filter for sediment that will trap contaminants as runoff flows
over the strip. These also indirectly act as a protection against pesticide spraying, where there is a
barrier in between the stream and the cropland being sprayed.
For the purpose of this study, an emphasis will be placed on
riparian buffers and their potential to reduce the effect of
agricultural runoff. Riparian buffers have been researched
extensively over the years and their effectiveness of removing
pollutants is widely documented. The use of the word
“riparian” is often more effective when considering buffers
due to its embodiment of the “assemblage of organisms and
their environment adjacent to and near flowing water
(Wenger, 1999).” In a legal definition, “riparian buffers” are
much more effective than simply a “stream buffer”, which
would only include the water body itself and not the
surrounding land. In the most simplified form, the Natural
Resource Conservation Service (NRCS) defines riparian buffers
as an established up‐gradient system of land consisting of
trees and other vegetation. It is designed to intercept “surface
runoff, wastewater, subsurface flow, and deeper groundwater
flows from upland sources. This is done with the purpose of
removing or buffering the effects of excess nutrients and
pesticides associated with agricultural runoff before discharge
to a surface water system. Applicable sites under these
conditions are adjacent to permanent or intermittent streams,
margins of lakes or ponds, environmentally sensitive wetlands,
and areas of groundwater recharge (Welsch, 1991).
Although there are many pollutants associated with agricultural runoff and pesticide use, nitrogen and
sediment are the most widely studied in literature review. This is most likely the case due to sediment
being the largest polluter of U.S. water bodies by volume. Nitrogen and phosphorus loaded sediments
contribute to extreme pollution, habitat degradation, and loss of biodiversity in coastal water bodies
(Sweeney, Newbold, & Bernard, 2012). Non‐wooded vegetative buffer strips are effective at removing
sediments but fail at removing nitrogen due to less root uptake. Forested buffers help deter the high
channelized flow that may surpass grass strips by interrupting and distributing flow. Their roots also
penetrate into the soil much further, allowing for additional nitrogen uptake from subsurface and
groundwater flow. Sediment from agricultural fields and the associated pollutants like phosphorous,
Figure 2 an example of a contour buffer strip within
an agricultural field (top) and a grass filter strip next
to an agricultural field (bottom) (NRCS, 2000).

6. 4
enter surface waters through overland runoff. For these to be removed, they must be intercepted. This
implies that the water running through the buffer is doing so at a velocity that allows the settling of
material into the buffer, meaning channelized flow is at a minimal. Forests serve as sediment trap and
can remove infiltrated phosphorous anions from soils. Many nutrients from nonpoint source nitrogen
enter surface waters through subsurface flows (Osmond et al. 2002). Nitrogen can be removed from the
streamside section through denitrification and plant uptake. Gaseous nitrogen (dinitrogen, nitric oxide,
and nitrous oxide) can be returned to the atmosphere by denitrification, which causes a reduction in
nitrogen oxides, NO3
‐
and NO2
‐
. Denitrification is an anaerobic bacterial process that requires relatively
low levels of oxygen and a steady organic carbon source (Sweeney and Newbold, 2014). Plant uptake of
nutrients occurs where flowing subsurface water is within the rooting depth (Welsch, 1991). Upon
consideration of implementing certain vegetation within buffer strips, it is important that the species is
one that gives a reliable amount of detritus or leaf litter back down to the surface.
NRCS has developed a three tier buffer system consisting of separate zones for different purposes. Zone
1 is undisturbed forestland closest to the stream, providing needed animal habitat and acts to regulate
water temperature through shading. Zone 2 is an upslope‐managed forest promoting infiltration,
nitrogen uptake by plant roots, and nutrients. Zone 3 converts channelized flow to sheet flow and filters
out sediment. These three areas are shown in detail in Figure 3 below (Welsch, 1991). The overall goal
of this three‐zoned system is for runoff to enter the buffer as surface runoff, infiltrate to subsurface flow,
then enter the stream as treated groundwater discharge.
Figure 3 A three‐zoned riparian forest buffer

7. 5
Zone 3: Runoff Control
Zone 3 provides room needed to convert concentrated flows from runoff to shallow sheet flow by use of
water bars or spreaders. Zone 3 should consist of perennial grasses and forbs to allow sediment filtering
and trapping. Vegetation acts as a barrier to stream from agricultural field, protecting water body from
direct pesticide spraying. In certain conditions controlled grazing of the filter strips can be allowed and
could cut mowing costs. NRCS recommends Zone 3 to be at least 20 feet wide for proper conversion to
sheet flow.
Zone 2: Managed Forests
Zone 2 is located in‐between Zones 1 & 3 primarily responsible for infiltration of filtered runoff into
subsurface flow. During high flow, trees and other vegetation act as a sediment trap by slowing
channelized flow to lower velocity sheet flow allowing for infiltration. After infiltration subsurface flow is
treated by plant uptake and anaerobic denitrification. Vegetation should include deciduous tree species
which provide adequate leaf litter to allow bacterial processes needed for denitrification and rooting
depth for nutrient uptake. NRCS recommends Zone 2 a minimum width of 60 feet.
Zone 1: Undisturbed Forest
Zone 1 is directly adjacent to the stream with the purpose of creating soil/water contact to aid buffering
of nutrients and provide needed habitat. Tall, mature trees act as a temperature regulator providing
needed shade and contributes energy source from fallen detritus. Vegetation should include
undisturbed native streamside tree species. Fallen debris should be conserved as it plays an important
role in stream ecology. NRCS recommends a width of 15 feet.
2.4 Buffer Width and Effectiveness
Riparian areas are extremely variable with differing soil types, slopes, vegetation type, and land uses. A
standard buffer size set in an ordinance would be the easiest option in terms of a regulatory approach
but would fail to address the heterogeneity of the environment. There is a wide amount of research
suggesting that a fixed width is inadequate to control agricultural runoff. A riparian buffer ordinance
would need to incorporate multiple variables to reach an adequate removal outcome. Most of the
literature available has been researching the width requirements that will reach acceptable and
predictable levels of removal efficiencies. The main argument is not if buffers are effective, but at what
width is the buffer most effective for each situation.

8. 6
Figure 4. Buffer removal efficiencies by % Removal Nitrates (blue) and % Removal Sediment (red) under certain buffer widths.
Data compiled from previous literature on buffer width studies from (Sweeney & Newbold 2014) and (Wenger, 1999).
Many studies have been done to determine if there is a way to compute buffer removal effectiveness
based off buffer width. A compiled graph of many experimental data, both nitrate and sediment
removal is graphed above in Figure 4, using data taken from (Sweeney et al., 2012[1]) and (Wenger,
1999)[2]. The above data established the percent removal of certain buffer widths, including vegetation
type of the buffer. Forested buffers showed a greater percent removal of nitrates than simply herb
1
vegetated buffers, removing in some cases up to 95‐98% nitrates. An analysis of the graph shows for
nitrate and sediment, a positive relationship between buffer width and percent removal, that is, as
buffer width increases the percent of nutrient removal also increases. Using a logarithmic analysis,
buffer widths can be for certain predicted removal. For 90% removal of nitrogen, the model shows a
buffer width of 346.15 ft., for 75%, 88.23 ft., and for 50%, 9.1 ft. For 90% removal of sediment, the
model shows a buffer width of 281.50 ft., for 75%, 41.82 ft., and for 50%, 1.75 ft. The goodness of fit for
the model was R2
= 0.1 for nitrogen and R2
= 0.13 for sediment.
An EPA study in 2005 by Mayer et al. of nitrogen removal effectiveness lead to a similar outcome of high
removal rates with a low R2
value of around 0.14, the results are shown in figure 5 below. The EPA study
relates to the data above giving a buffer width of 112 m (367.45 ft.) for 90%, 28 m (91.86 ft.) 75%, 3 m
(9.84 ft.) for 50%. Through their literature review they were able to determine that buffers can remove
large portions of nitrogen that flow through them and that nitrogen removal effectiveness is positively
related to buffer width. However, due to the extreme variability of effectiveness and low R2
values,
nitrogen removal effectiveness could not be predicted from buffer width. It is important to note that
1
Nitrate data from Sweeney and Newbold: Balestrini et al. (2011), Butturini et al. (2003), Clement et al. (2003), Cooper (1990),
Correll et al. (1997), Hanson et al. (1994), Simmons et al. (1992), Hefting et al. (2003, 2006), Heinen et al. (2012), Hoffmann et al.
(2006), Jordan et al. (1993), Lowrance et al. (1984), Lowrance (1992), Bosch et al. (1996), Maitre et al. (2003), Messer et al.
(2012), Newbold et al. (2010), Peterjohn and Correll (1984), Vellidis et al. (2003), Vidon and Hill (2004), Wigington et al. (2003).
Sediment data from Sweeney and Newbold: Arora et al. (1996), Clausen et al. (2000), Daniels and Gilliam (1996), Deletic and
Fletcher (2006), Dunn et al. (2011), Fiener and Auerswald (2003), Gharabaghi et al. (2006), Helmers et al. (2005), McKergow et
al. (2006), Newbold et al. (2010), Peterjohn and Correll (1984), Sheridan et al. (1999), Ziegler et al. (2006).
2
Nitrate data from Wegner: Osborne and Kovacic (1993), Haycock and Pinay (1994), Haycock and Pinay (1994),Mander et al
(1997), Mander et al (1997), Hubbard (1997), Hanson et al (1994), Osborne and Kovacic (1993), Jordan et al (1993), Lowrance
(1992).

9. 7
due to the statement above, there are other factors playing a significant role in the buffer effectiveness.
These most likely are slope, soil type, and buffer
vegetation type.
Out of all the factors other than buffer width that
contribute to buffer sediment trapping effectiveness, the
most important would be the slope. Since riparian buffers
require a slowed sheet flow for infiltration, increased
slope will lead to less infiltration, requiring more focus on
high‐sloped areas than low sloped. Therefore, buffer
width will need to increase as the slope of the land area
increases, implying a fixed buffer width to be inadequate
for sediment removal. Many studies have produced
various equations to determine width using fixed length
and incorporation of slope.
An example from Trimble and Sartz's 1957 study of how
erosion on logging roads impact local streams set a buffer
system using a set width of 25 feet and increasing width 2
feet for every 1% slope. The equation looked as follows, buffer width = 25 ft. + (2.0 ft.)(% slope) (Wegner,
1999). Equations that include multiple variables, like the one above, could account for the inability to
determine buffer widths from percent removal.
Figure 6 below represents the soils of Dodge County by soil category. GIS files were obtained from the
NRCS and a description table is located at the end of this document in Appendix A. Most common soil
types are SdA, a St. Charles silt loam, moderately well drained, 0 to 2 percent slopes, areas of prime
farmland, and Hu, Houghton muck, areas of farmland of statewide importance. Figure 5 shows a soil
map of Dodge County categorized by the slope of the land area. With slope being a necessary factor in
determining width, it is important to differentiate areas that are of higher or lower slope. Soils with high
slope (red) and medium slope (yellow) require a larger buffer width than that of the low slope (green)
soils.
When considering a plan to implement buffers it would be optimal to include each variable to account
for each specific site near a riparian boundary. In terms of regulation this can be very difficult to fit each
location's average slope of field, soil type, average rainfall, and cropping management factors. For this
purpose it may be more appropriate to focus on the most important factors that attribute to the
erodibility of a soil. Manning’s formula states that water velocity is related to the square root of slope
(S1/2
) and the potential for a soil particle to be moved depends on this velocity and the erodibility of the
surface. Thus, Brown and Schaefer et al. created a simplistic but rational equation to determine buffer
width based off of slope (Brown et al., 1987).
Figure 4. EPA combined study results of Nitrogen
removal effectiveness by buffer width in meters
(Mayer et al., 2005).

10. 8
Figure 6. A map showing the 117 soil types of Dodge County. Appendix A gives a descriptive table of each specific soil type and
properties.

11. 9
Figure 7. A map of Dodge County Soils separated into low slopes (0‐6%), medium slopes (6‐12%), high slopes (12‐30%), and
miscellaneous slopes. Miscellaneous are those of unknown slopes or that of wetlands and water bodies.

12. 10
Brown et al. Buffer Width Equation:
Bw = S1/2
/E
Bw = the width of the buffer in ft.
S = average slope of the land in ft. per 100 ft.
E = erodibility factor; SCS erosion factors: 4 = k factors of 0.1, 3 = k factors of 0.15, 2 = k factors
of 0.17, and 1 = k factors > 0.17.
Soil data on Dodge County was obtained from the U.S. Department of Agriculture, Natural Resources
Conservation Service Soil Survey of Dodge County Wisconsin (Fox, 1937). Erosion factors (k) can be
found using the above source and are defined as the rate at which a soil will erode (Brown et al., 1987).
Slopes in the county ranged from 0‐2, 2‐6, 6‐12, 12‐18, 12‐25, and 18‐30 percent. For example, a "palms
muck" (Pa) 0‐2 percent slopes, farmland of statewide importance, has an erosion factor (k) of 0.1. Using
the above equation, buffer width can be calculated and graphed (Figure 3) using the erodibility factor of
4, giving an efficient buffer length of 35.36 ft. Figure 8 shows the width of buffer needed for each
erodibility factor and the slope attributed to the specific soil type. As shown in the graph, the lower the
soil erosion factor, the higher the erodibility factor (it takes more energy to erode the soil), leading to a
smaller buffer width requirement. There is a positive relationship between buffer width and slope, the
higher the slope percent, the larger the buffer needed in this area.
Figure 8. Erodibility factors by slope vs. buffer widths. Shows the required buffer widths for certain soil types based on erosion
factors of soil and slope. Soil with high erosion factors is given a lower erodibility factor to account for a larger buffer width.
This equation is meant to be used as a general reference from which a more detailed, specific formula
can be developed for conditions within Dodge County. At a very site‐specific level, the Universal Soil Loss
Equation (USLE) may be more appropriate for determining buffer widths if adequate knowledge can be
obtained (Brown et al., 1987). The USLE could be used in conjunction with the previous equation to find
better site specific buffer widths by including rainfall erosivity, soil erodibility factor, topographic factors,
and cropping management factors. Brown’s equation addresses the sediment runoff of a field but fails
to address the other main pollutant nitrogen. The shorter buffer widths derived from this formula are

13. 11
due to the focus of sediment removal but does not take into account the large space needed to achieve
nitrate removals through larger trees and vegetation. The equation can be modified to include space
needed for nitrogen removal by using the NRCS recommended a zone 2 width of 60 feet. This modified
equation would then be interpreted as Bw = 60 + S1/2
/E, giving our previous soil type a buffer width of
95.36 feet. This would the buffer width within the modeled experimental range of around 75% removal
from figure 4.
There was a concern whether grass buffers were worth the trouble of creating. Research provides
evidence that wider buffers with wooded vegetation have better capability of removing nonpoint source
pollution more than grass buffers. However, the results from a 1997‐98 study find that grass buffers still
catch significant runoff. The experiment used a cropland source with an area of 14 x 73ft, a switchgrass
(Pancium vigratum) buffer with a width of 23ft, a switchgrass/woody buffer with a width of 53.5ft, and
an area with no buffer to calculate results. The switchgrass/woody buffer was 23.3ft of switchgrass and
30.2ft wooded. The mean data was collected over 19 precipitation events. The switchgrass/woody
treatment increased the removal efficiency by 20%. Based off of the findings of this experiment, wooded
buffers perform better than grass buffers, but it appears that a grass buffer would be better than
nothing at all (Lee, 2003). Results are shown in Figure 9 below.
Figure 9. Differences between grassed filter strips and forested buffers (Lee, 2003)
2.5 Management of Riparian Buffers
2.5.1 Headwater Streams
Research has been conducted that explains the necessity that there are no gaps in the riparian buffer
zone (Wegner, 1991). Headwater streams make up many of the stream length in most basins, and have
the most land‐water interaction (more time to transport sediment) making them extremely important to
establish buffer zones in these areas. Smaller streams in the county require just as large of a buffer
width as the Rock River. Previous studies suggest that the more headwater streams that are buffered,
the greater the benefits for the basin as a whole (Osborne and Kovavic 1993). Buffers could be

14. 12
implemented into the smaller stream sections leaving the already forested areas of some larger streams
untouched to minimize the cost of the project.
2.5.2 Maintenance
Sound nutrient management plans and erosion control systems can lead to less maintenance costs.
Yearly and following large storms, inspections for buffers are needed to address the potential sediment
build up or erosion from channelized flow (Welsch, 1991). Grass buffer strips may also need to be
occasionally mowed if no controlled grazing activities are in place.
2.5.3 Managing Invasive Species
Due to a lack of a native seedbank in the soil and a long period with no natural vegetation, it is highly
likely that invasive species will have to be addressed. Young, growing vegetation next to riparian areas
are susceptible to invasives transported by the stream. It is not recommended to plant non‐native
species but to instead plant young seedlings or larger plants transplanted from other local sites (Correll,
2005). Herbicide use is not recommended unless extreme action is needed. A management plan for
invasive species is a necessary step in any riparian buffer ordinance.
2.6 Issues with Implementation
2.6.1 Economics:
Estimating the cost of implementing a county‐wide stream buffer ordinance is imperative to determine
its feasibility. By utilizing previous corn and soybean prices, the two most commonly grown crops in
Dodge County, its possible to gain an idea of the economic commitment required to go forward with a
stream buffer ordinance.
In 2012 the average corn yield for Wisconsin was 121 bushels per acre and one bushel of corn was
selling for an average of $6.90 (USDA). On average for all of Wisconsin, if one acre of corn were
harvested, it would equate to gross revenue of $834.90 per acre. Dodge County in particular had an
average yield of 141.4 bushels per acre in 2012 (USDA). In turn, farmers in Dodge County were averaging
gross revenue around $972.90 per acre of corn. On average, the input cost to maintain a cornfield is
around $743, according to the University of Illinois‐Urbana‐Champaign. When considering the input
costs, in 2012 Wisconsin averaged a profit of $91.90 per acre of corn. For Dodge County, 1 acre of corn
constituted an average of $229 per acre.
In 2012 the average soybean yield for Wisconsin was 41.5 bushels per acre and soybeans were selling
for an average of $13.90 per bushel (USDA). Cumulatively, Wisconsin was averaging a yield of 41.5
bushels per acre. Dodge County in particular had an average yield of 47.2 Bushels per acre in 2012
(USDA). Consequently, farmers in Dodge County were averaging gross revenue around $656.08 per acre
of soybeans. The total input cost to maintain an acre of soybeans is about $531. When considering the
input costs, Wisconsin averaged a profit of $45.85 per acre of soybeans. Dodge County in particular
averaged a profit of $125.08 per acre of soybeans.
Based on the 2012 data and GIS mapping of total stream length we were able to estimate the loss in
profit per year when adopting buffers with different widths. It important to keep in mind the fluctuation
of market price per bushel of corn, ever‐changing weather conditions, and growing season conditions,
which is why we are only able to make a rough estimate as to how much money farmers, would lose by
converting farmland into stream buffers.

15. 13
Total Buffer width (ft2
) Potential loss in profit ($177/acre)
20 $707,731
40 $1,415,463
60 $2,123,194
80 $2,830,926
100 $3,538,657
Figure 11: A table estimating the potential loss in profit for Dodge County per year corresponding to theoretical stream buffer
areas.
Yet another monetary cost to consider is how much it would cost to install the riparian buffers along the
streams in Dodge Country. The U.S Fish and Wildlife Service Sates that on the high end to seed a riparian
buffer it would cost $1000 per acre. By computing the total stream length by different buffer widths we
are able to gauge how much it would cost to implement these buffers.
Total buffer width (ft2
) Potential cost to create riparian buffer
($1000/acre)
20 $3,998,482
40 $7,996,960
60 $11,995,447
80 $15,993,929
100 $19,992,412
Figure 12: A table estimating the potential cost for Dodge County to construct different stream buffer areas around every
stream in the county. This table does not take into account the existing stream buffers in Dodge County; instead it assumes
there are currently no existing buffers.
2.6.2 Complications with Drainage
Further complications arise when considering that not all of Dodge County’s land is naturally drained.
Drain tile systems are common in farms throughout the county, and in many cases reduce or negate
natural surface runoff that would otherwise be addressed by a riparian buffer. Rain and irrigation water
(along with excess nutrients) are drained via subsurface pipes that bypass the buffer and lead straight to
a stream or ditch, rendering the buffer useless. Figure 13 shows that a full 25% of Dodge County land is
only considered “prime” for farming if it is in some way drained. We may also speculate that due to the
undeniable agricultural advantages provided to farmers, drain tiles likely exist in lands within the
category of “prime farmland” as well. While the exact percentage and acreage of drain‐tiled farmland is
not quantified here, it is a large enough “unknown” to give pause when designing a blanket ordinance.

16. 14
Figure 13. Farmland Classification Map. Farmland classification identifies the location and extent of the most suitable land for
producing food, feed, fiber, forage, and oilseed crops. NRCS.

17. 15
3.0 ALTERNATIVES
As previously illustrated, there are scenarios where riparian buffers are not an appropriate solution.
There are other practices that can reduce agricultural runoff from polluting water systems. For the
purpose of this report, select alternatives have been divided into 3 categories: regulatory, voluntary, and
implementation strategies.
Regulatory alternatives are categorized as such due to their non‐incentivized nature ‐‐ they may be
"enforced" by a governing body. These methods may be used in that capacity. Voluntary alternatives are
incentive‐based, and farmers may elect to participate if desired. Implementation strategies do not
strictly fall into either category, and may contain a mix of methods and incentives.
3.1 Regulatory approaches
3.1.1 Conservation Agriculture Methods
Conservation Tillage
Tillage practices are used in agriculture as a way to prepare a soil for planting crops in the growing
season; this is done by turning up the top horizons of a soil. Farmers have a variety of reasons why they
till their soil, but primarily it is a way to make their soils less compacted, by breaking up the structure of
the soil, allowing water and air to infiltrate it. This is often performed by heavy machinery (plows). There
are no cover crops and crop residue is removed from the surface of the soil.
Soil erosion on agricultural fields is a problem intensified by tillage. This is a problem that should
concern farmers, as increased erosion in their fields will decrease productivity of their soils, requiring
additional application of fertilizers. The erosion off of agricultural land can develop into runoff carrying
sediments containing fertilizer and pesticides, affecting water quality of nearby waterways. Thinking
from this perspective, it would be wise to reform tillage practices to a more conservational approach to
reduce soil erosion (Al‐Kaisi, 2004).
Conservation Tillage, or “no‐till” removes the process of tilling on the field. This allows the soils to retain
their structure and continue to develop, whereas tillage will eliminate on‐going internal soil processes.
Conservation tillage practices have multiple benefits for the soil, farmers, and surrounding environment.
For the purpose of this study, the reduction in soil erosion is most relevant. Leftover crop residue and
reduction in tillage can hold the soil in place, resulting in a decrease of the amount of runoff from
leaving the site. Although this practice is listed as an alternative in this report, it would be wise to use
conservation tillage in addition to implementing a riparian buffer. Any reduction in runoff from leaving
the field would benefit water quality (Conservation Technology Information Center, 2015).
Cover Crops
In addition to conservation tillage, the inclusion of cover crops on agricultural land will also reduce
erosion and runoff. Runoff can decrease as much as 80%, and sediment loss can be from 40‐96%. The
amount of erosion and runoff reduction coincides with the amount of biomass a cover crop produces.
The more biomass produced, the more runoff is contained. In addition to reducing the amount of runoff
flowing off of the field, cover crops can also prevent dissolved nutrient loss. During precipitation events,

18. 16
the impact of raindrops on soil increases erosion. The canopy above the soil surface provided by cover
crops greatly reduces the affect of this. Runoff velocity is decreased when passing through cover crops.
A mix of legume and grass species of cover crops can cover more ground and provide more benefits
than a single species (Blanco‐Canqui, 2015).
Legumes are beneficial as a cover crop because they have the ability to fix nitrogen from the
atmosphere. This characteristic allows organic nitrogen into the soil, which cuts the need for commercial
fertilizers. Depending on growing conditions, legumes fix between 50‐150 pounds of nitrogen per acre.
The low carbon content of legumes will allow them to break down quickly, which allows the crop to
spread their nitrogen at a considerable rate. According to Sustainable Agriculture Research and
Education, crops that are grown in fields with cover crops will take in 30 to 60 percent of the nitrogen
produced by the cover crop (SARE). The organic nitrogen created by cover crops will reduce fertilizer
needs, which in turn reduces excess nitrogen on fields.
Non‐legumes are useful in their ability to convert excess nutrients in the soil to organic matter. By
soaking up excess nitrogen, this class of cover crop prevents nitrogen from leaching into ground water
and running off into nearby streams. Non‐legumes are known to hold on to leftover nitrogen found in
the soil until the next growing season. In the spring, the nitrogen stored in their tissues can be worked
back into the land. Due to their high carbon content, these types of cover crops will break down more
slowly and will result in mass amounts of long‐lasting residue. This residue enhances their ability to
prevent erosion and suppress weeds, both while they are growing and when they are used as mulch.
Legumes can also be living mulches when planted with corn or soybeans. Living mulches are, “an
extension of cover crops used to decrease soil erosion, suppress weeds, improve soil structure, and
nutrient cycling” (Singer, 2005). What sets living mulch apart from other cover crops is that they can
grow alongside agricultural crops throughout the growing season, rather than needing to be eradicated
before the growing season starts. Living mulch also has the ability to continue to grow once the
agricultural crop has been harvested. When using legumes as living mulches, they will provide the same
benefits as a simple cover crop. Using legumes as living mulch reduces the amount of work that is put
into maintaining a cover crop (Singer, 2005).
Farmers that utilize cover crops or living mulches as an environmental practice will reap additional
agricultural benefits. These practices have been shown to increase crop yields. According to SARE, the
benefit of an increased yield when using cover crops can be seen after one year. Corn yields were seen
to increase by 9.6 percent while soybean yields increased by 11.6 percent. Cover crops have also been
shown to improve the soil quality. Additionally, cover crops provide shade in agricultural fields, which
impedes weed growth.
3.1.2 Nutrient Management
A nutrient management plan is a tool that farmers can use to ensure their fields are receiving the proper
amounts of nutrients at an environmentally sustainable rate. With the help of professionals or alone,
farmers can devise a nutrient management plan that fits their fields' individual needs with the end goal
of maximizing yields, while minimizing cost and nutrient loss. These plans are based on soil type, slope,
and crop rotations. According to the Wisconsin Department of Agriculture, over a quarter of Wisconsin's
farmland is currently using nutrient management plans. A nutrient management plan is a requirement
for any farmer choosing to receive benefits from the Farmland Preservation Program. (The Farmland
Preservation Program is designed to retain prime agricultural land for the use, education, and
enjoyment of future generations.)

19. 17
3.1.3 Edge‐of‐field techniques
Drain Water Management
“Drain Water Management” is dynamic manipulation of the water table in accordance with seasonal
events using a drain tile system. Traditional drain tiles lower the water table to the pipe’s buried depth,
allowing only for a static lowered state. With the addition of control structures that employ PVC “stop
logs,” water table depth can be altered at will. This means that lowering can still take place before
planting and harvesting, when heavy machinery poses a major soil compaction threat, but can be raised
to levels throughout the rest of the season that complement the growth stage of the crops
(Frankenberger et al., 2006). This may actually reduce the need for irrigation in some heavily tiled fields.
From an ecological perspective, this may allow a greater amount of crop uptake and denitrification in
soils that would otherwise be discharged straight away (in a static system). It also allows for off‐season
raising of the water table back to natural levels (basically, stop draining). Saturation or flooding of soils
in autumn and winter (after growing season) may result in denitrification ‐‐ granted, at a reduced rate in
colder temperatures – of residual nitrates leftover from the growing season.
Recent Research:
As a stand‐alone strategy for nitrate reduction, The “Iowa Nutrient Reduction Strategy” Report of 2013
found extremely varied results in their literature review. While the average was a 33% reduction and the
high was 98%, the lowest value actually reflected an 11% addition of nitrates, rather any reduction at all.
Figure 14. A conceptual rendering of a control structure in action. (Graphic from www.extension.purdue.edu)

20. 18
Benefits:
 Can be retrofitted to many existing tile systems
 Potential savings on irrigation water in drier parts of growing season
 New technology allows control of structures remotely
 Allows for future utilization of other tile drain technologies (bioreactors, saturated buffers, etc.)
Challenges:
 As with all end‐of‐field methods, some maintenance is required
 Funding: Technical and financial assistance does exist through EQIP.
Saturated Buffers
“Saturated buffers” modify the traditional riparian buffer to work with tile drainage systems.
(Kjaersgaard et al, 2011). Applied to a conventional tile‐drained field, the underground pipes would
bypass the traditional buffer and discharge into a nearby stream or ditch, rendering it useless. A
saturated buffer would require placement of an additional control structure intercepting the tile main
coming from the field, and additional length of pipe to run parallel to the stream (at a distance from the
buffer, based on its width).
The control structure would divert a chosen percentage of the water from the main into the newly
placed parallel pipe, thereby discharging water into the soils of the buffer zone and saturating it (Jaynes
and Isenhart, 2014). At this point the saturated buffer would serve the same purpose as a traditional
buffer – with a portion of the nitrates and water being directly uptaken by plants, and a portion of the
nitrates being dealt with via denitrifying microorganisms in the saturated soil. The water continues to
percolate through the soil in its downhill gradient toward the stream where it is naturally discharged
(Jaynes and Isenhart, 2014).
The control structure can be set to divert differing amounts of flow into the saturated buffer. In the case
of unexpected heavy rains, there is still an overflow pipe that leads out from the control structure
directly to the stream and will prevent back‐ups on the field side of the structure.
As with other end‐of‐field techniques, research is ongoing. “Best practices” have not sufficiently evolved
to give solid recommendations on dimensions of saturated buffer width and length, or exact length of
pipe. However, the results are encouraging.

21. 19
Figure 15 on the left shows how a traditional riparian buffer is bypassed as a subsurface drain outlet travels from the field
straight to the steam. The figure on the right shows the location of the additional control structure and diversion of flow into the
additional parallel pipe, allowing seepage into the buffer. (Graphics by D. Jaynes, USDA ARS, Ames Iowa.)
Recent Research:
In a two‐year study, Jaynes and Isenhart (2014) found that 55% of flow was diverted from the main field
outlet of a 10 ha corn/soybean field into the saturated buffer (18,000 m3). This flow contained 228 kg of
nitrate, all of which is believed to have been dealt with (via plant uptake, denitrification, or
immobilization). This particular field already had riparian buffers in place, so it was only a matter of
adding the diversion pipe and control structure. Throughout the estimated 20‐year life span of this set
up, the total cost is estimated at $4,960 or annually, at $248/year. The per‐unit cost of nitrate removal is
therefore estimated at $2.17 per kg.
Benefits:
 Saturated buffers would potentially address a glaring shortcoming of a would‐be buffer
regulations – simply that tile‐drained farmland would bypass the active zone entirely
 Addresses heterogeneity of farm land and weather events, by accommodating more than 1
drainage type and accounting for overflow in heavy rain events
 Leverages existing infrastructure ‐‐ buffers and drain tiles exist in many places already (link them)
 Depending on width, buffers may provide (limited) corridors for wildlife
Challenges:
 One study suggests a minimum 30ft width of saturated buffers, so similar costs would be
associated in imposing this as a regulation for lands that do not currently have buffers. (Utt,
2014)
 The saturated zone still deals specifically with nitrogen loading, not phosphorus or sediment
 Potential complications with especially ‘meandering’ streams and the installation of parallel
pipes
 As with all end‐of‐field methods, some maintenance is required
Funding: Technical and financial assistance does exist through EQIP.

22. 20
Bioreactors
“Bioreactors” are artificially constructed, intensive denitrifying environments aimed at reducing nitrate
loads from specific point‐source pipes (Cooke and Bell, 2014). They are typically in the form of a buried
ditch, and filled with an organic carbon source (most often wood chips). The chips act as a substrate and
carbon source for denitrifying bacteria that colonize the bioreactor. In a tile‐drained field, excess
nitrates are carried via water in the pipes that are directed into the bioreactor, rather than discharged
directly into a stream or ditch. Saturation is key – the use of control structures allows water to be
temporarily sequestered, long enough for reduction of excess nitrates. N2 gas is the final product, and
water continues on its way out of the pipe into the stream.
Flow rate obviously changes with weather, and the bioreactor allows excess water to overflow/bypass in
order to prevent any unwanted rise in the water table on the field (Cooke and Bell, 2014). While a larger
bioreactor can accommodate higher flows (thus avoid discharge of nitrate‐laden water) a bioreactor can
be designed “too large,” and may create such a reductive internal environment that the formation of
methylmercury is possible. To prevent this, bioreactors are typically planned for no greater than 80%
nitrate reduction.
Optimizing dimensions of the bioreactor and size of the substrate depend on many factors, including the
acreage of the field being drained, the design flow rate (based on known hydrology of the fields),
probability of exceeding the design flow, etc. Current best practice design guidelines (including cost
estimation) are available in the 2014 article by Cooke and Bell.
Figure 16. An illustration of a subsurface bioreactor. (Graphic from Cooke and Bell 2014).

23. 21
Recent research:
Cooke and Bell (2014) design an example bioreactor at a cost of $13,000 for a 69% nitrate reduction in a
65.7‐acre field, with a 15‐year lifespan. This result is an estimated per‐unit reduction cost of $3.52/kg of
nitrate.
The “Iowa Nutrient Reduction Strategy” Report of 2013 found an average 43% reduction of nitrates by
bioreactors in their own literature review (with a high of 75% and low of 12%).
Benefits:
 Best practices evolving, but thorough design guidelines do exist currently
 Can be retrofitted to many existing tile systems
 Does not reduce arable acreage (as in the case with buffers)
 Once installed, very simple operation (with drain tile control structures)
 Estimated 10‐20 year lifespan of woodchips as carbon medium (before replacement)
Challenges:
 Overly large bioreactors may create a hyper reductive environment where methylmercury can
(potentially) be formed which is toxic humans and wildlife
 Addresses N loading specifically, does not really address P or sediment loading
 “Too many drains” to be a large‐scale solution? May not be useful in a strict regulatory capacity
 As with all end‐of‐field methods, some maintenance is required
Funding: Technical and financial assistance does exist through EQIP.
3.2 VOLUNTARY

24. 22
EQIP
The Environmental Quality Incentives Program is a voluntary program that aims to offer financial and
technical assistance to agricultural producers. The goal of these EQIP contracts is to provide help to
producers that are implementing conservation practices that will address their specific growing concerns
related to the degradation of soil, water, plant, animal, air, energy and other related resources that lie
within the agricultural land. This program also maintains federal, state, tribal, and local environmental
regulations that are applicable, so each program is specific to the producer's locale.
Eligibility for enrollment in EQIP is dependent on ownership of land, compliance with local conservation
requirements, and meeting adjusted gross income limitation provisions. While all meeting these
requirements are welcome to apply, some applicants may be eligible for increased/advanced payments.
Those that are socially disadvantaged, beginner farmers, Indian tribes, or veterans are encouraged to
apply for these added benefits.
Four EQIP Initiatives
The ‘Air Quality Initiative’ offers assistance in establishing cover crops, implementing nutrient
management practices, and applying other conservation efforts that help to mitigate current issues, as
well as preventing future occurrences.
The ‘On‐Farm Energy Initiative’ works to develop Agricultural Energy Management Plans that assess
energy consumption and helps to maximize the resourcefulness of a producer’s current energy uses.
The ‘Organic Initiative’ was designed to assist in the implementation of conservation practices that assist
in the transition process to organic and sustainable farming practices. This may include establishing
buffer zones, improving soil quality and organic matter, erosion control, as well as developing a grazing
plan that meets organic livestock practices.
The ‘High Tunnel System’ helps aims to help extend the growing season of producers by implementing
steel‐framed tunnels that not only benefit the plants and soil, but also reduces pesticides being released
into the environment.
Enrollment in EQIP is a valuable benefit that is available to those that are interested in government
assistance in implementing conservation efforts (NRCS 2014).
3.3 IMPLEMENTATION ALTERNATIVES
3.3.1 Farmer‐led Watershed Councils
Overview
It can be argued that addressing that the complexities of the water quality problems in Dodge Co.
requires the input and knowledge of many stakeholders in order to be successful. One method of
gathering and organizing such stakeholders that is showing promise in other parts of the state is the
“Farmer‐led watershed council.” These councils are formed on a sub‐watershed level (ideally HUC 12,

25. 23
from USGS) and address poor water quality by putting farmers in a position to study and solve the
problems in ways that work best for them. Some of the inherent issues with top‐down approaches are
tackled by working in this way, namely – the personal engagement by the farmers themselves, who are
sometimes seen as the “offenders” when it comes to water quality (Olmstead, 2014).
While there is a general understanding and consensus within the county that there are serious water
quality problems and that agricultural runoff is the source, farmers are often hesitant to accept personal
“blame” for this. Hot spots of pollution may exist (likely from large CAFOs), but in general it is certainly
true that no single farm or farmer is responsible for the collective problems of the county. Soil and
water quality data from an outside source (such as the DNR) are therefore met with skepticism when
used as rationale for regulations that might force behavioral change. The potential economic
repercussions of regulations on farmers may further contribute to a defensive stance on their part
(Olmstead, 2014).
Farmer‐led watershed councils consist of a group of dedicated, conservation‐minded farmers. They work
with a limited staff of skilled facilitators, coordinators, and technicians (from UW Extension) to develop
their own mission and vision (based on the farmers involved) but with the overarching goal of improving
water quality. They design their own incentives from funding procured by the staff, which ensures that
they are pertinent and attractive to farmers in their area. The objectives follow from this point and are
unique to each council. This is important to note –while the main goal is the same for each council, the
path to achieving it is determined by the group. The structure is not forced or rigid. As a result, deciding
how to monitor success must also be unique to each council (Olmstead, 2014).
Progression
The findings from four ongoing councils in western Wisconsin (St. Croix and Red Cedar River basins)
show some general trends after a couple of years. First, farmers showed an interest in updating baseline
soil data within their study area. Being part of the testing process appeared to “legitimize” the results in
the eyes of the farmers, and painted a more detailed picture of the water quality issues within the
county. It served as a launch point for the farmers’ own education, and set a mutually agreed‐upon
baseline for future monitoring. Edge‐of‐field monitors were then installed at locations specified by the
farmers (two in natural areas and three in crop fields). Eventually, the intent is for farmers to be sharing
their data with their watershed partners and council staff in order to map nutrient hotspots and begin
directing incentives to meet water quality goals (Olmstead, 2014).
In these first years, farmers have come up with incentives ranging from: cash payments for soil sampling
across their land; subsidies for the installation of grass waterways; lump sum cash payments for a “farm
walkover” with a conservation planner from the county land conservation department. Interestingly,
one of the best methods of engagement that has met with the most interest from farmers has been the
“field days” (seminars in the field, demonstrating alternative practices and ongoing results). The costs
associated with trials of alternative practices make up a portion of the funding arranged by the council
staff (Olmstead, 2014).
Creating a Farmer‐led Watershed Council
There are challenges to creating farmer‐led watershed councils, but there is no singular best practice for
recruitment. The St. Croix and Red Cedar River basin councils have shown success with two totally
different methods. In one case, initial recruitment focused of a handful of dedicated farmers that were
known leaders in the farming community. County Land Conservation Departments are invaluable in this
capacity, as they have previously existing relationships with farmers. Along with the council staff, they

26. 24
were able to encourage other farmers to come, and expand attendance and awareness. This style may
possibly lead to smaller groups, but with high levels of dedication (Olmstead, 2014).
In the other case, letters were mailed to all landowners in the county (while specifying farmers) inviting
them to an introductory meeting. Interested members of the general public had to be politely dismissed
in order to keep a supportive “all‐farmer” environment. A greater diversity of farmers and farm‐types
has been represented by this method, but there are obviously costs associated with mailings and
postage that do not exist in the first scenario, which strictly leverages existing relationships (Olmstead,
2014).
There is a minimal (but dedicated) staff that aid in the creation and facilitation of the councils as well as
the technical aspects of testing, monitoring, and reporting data. They include:
Coordinator position (full time): Tending to all the watersheds, involved in project development and
management, meeting facilitation, grant writing, data reporting and communications, etc.
(Cost: approx. $100,000/year to cover travel, equipment, meeting expenses, salary, etc.
DNR‐funded)
Conservation Planners/Technicians (multiple half‐time positions): Recruits famers, assists in meeting
planning and facilitation, provide technical advice and assistance in implementation.
(Cost: approx. $50,000/year each to cover all costs and salary; state and county funding sources)
Expectations and Challenges
Since monitoring is customized to the unique objectives of each watershed and their work is ongoing,
the results for the first couple years have focused on the successes in raising attendance and awareness
and in raising funds to secure the immediate future of the councils. Data on the reductions in nutrients
that can be attributed to the councils are not yet available. This leads to a primary criticism and
challenge of farmer‐led watershed councils. Namely, that progress is slow and difficult to monitor. While
this may be true in the limited time they’ve been in existence, we can’t speculate on the results they
may produce in the future. In defense of the councils, their proponents acknowledge that it’s a potential
long‐term strategy to address what has been a very long‐term problem. “Quick” or “easy” fixes, if they
exist, have not been shown to work thus far (Olmstead, 2014).
4.0 RECOMMENDATIONS
Buffer widths were reviewed for effectiveness using extensive literature review and experimental data.
From figure 4, the low correlation between width and removal efficiencies demonstrates the importance
of other factors that heavily impact the removal of nutrients. These include slope, soil type, buffer
vegetation type, and crop choice. Therefore, buffer widths alone are not a suitable factor for
determining nutrient removal. In relation to other factors, there is no set buffer width that will perform
at a predictable level.

27. 25
Estimated costs of implementation were calculated by buffer width, as well as estimated loss of profit by
reduction of potentially farmed land. As stated above, the uncertainty in buffer performance does not
warrant an expenditure of such magnitude, based off of findings in figures 11 and 12.
After reviewing the alternative practices to riparian buffers, early data suggests they may prove to be
more appropriate and effective on a field‐by‐field basis. If producers were to take on a more prominent
role in the decision making process, then a more appropriate approach may be devised based on their
understanding of their own field conditions. This is the foundation for Farmer‐led Watershed Councils. A
few important prerequisites have been identified from previous experience when organizing and
launching farmer‐led watershed councils. They pertain to staffing, funding, and effective scale of
implementation:
 Having known leaders in the farmer community greatly enhances the probability of successful
formation
 It’s not recommended to start with less than 2‐3 individuals who are willing to take on
leadership roles
 Staff should be from a neutral source (such as UW Extension) that is considered “non‐
threatening” to farmers
 Plan for implementation at the HUC 12 level
 It’s strongly recommended that funding and resources be in place before the formation of
councils even begins, preferably from multiple sources (state, county, private) that account for
more than 1 year
5.0 CONCLUSIONS
Concern over the poor water quality within Dodge County has gone on for decades. Recently, this has
led to discussions regarding bold actions to remedy these problems with legislation. Riparian buffer
zones can provide an excellent service in catching agricultural runoff before it reaches streams, but are
not a “one size fits all” solution for the producers in Dodge County. Thus, a county‐wide buffer
ordinance is not a recommended solution to their water quality concerns. Due to the lack of research,
variability in the efficacy of nutrient removal, and the challenges in funding the implementation of such
an ordinance, we instead suggest a multipronged approach built from the aforementioned alternatives.

28. 26
6.0 Appendix
6.1 Appendix A. Table of the soil types of Dodge County
AcA Ackmore silt loam, 0 to 3 percent
slopes
Consociation Prime farmland if drained
Ar Adrian variant muck Consociation Not prime farmland
AsA Ashippun silt loam, 0 to 2 percent
slopes
Consociation All areas are prime farmland
AsB Ashippun silt loam, 2 to 6 percent
slopes
Consociation Prime farmland if drained
BsA Brookston silt loam, 0 to 3
percent slopes
Consociation Prime farmland if drained
CcB Casco loam, 2 to 6 percent slopes Consociation Farmland of statewide importance
CcC2 Casco loam, 6 to 12 percent
slopes, eroded
Consociation Not prime farmland
CcD2 Casco loam, 12 to 20 percent
slopes, eroded
Consociation Not prime farmland
CdB Channahon silt loam, 1 to 6
percent slopes
Consociation Farmland of statewide importance
CdC2 Channahon silt loam, 6 to 12
percent slopes, eroded
Consociation Not prime farmland
CdD2 Channahon silt loam, 12 to 25
percent slopes, eroded
Consociation Not prime farmland
ChB Chelsea loamy fine sand, 2 to 6
percent slopes
Consociation Not prime farmland
ChC Chelsea loamy fine sand, 6 to 18
percent slopes
Consociation Not prime farmland
Co Colwood silty clay loam Consociation Prime farmland if drained
DdA Dodge silt loam, 0 to 2 percent
slopes
Consociation All areas are prime farmland
DdB Dodge silt loam, 2 to 6 percent
slopes
Consociation All areas are prime farmland
DdC2 Dodge silt loam, 6 to 12 percent
slopes, eroded
Consociation Farmland of statewide importance
EbA Elburn silt loam, 0 to 3 percent
slopes
Consociation All areas are prime farmland
Ev Elvers silt loam Consociation Prime farmland if drained and either
protected from flooding or not
frequently flooded during the growing
season
FoE2 Fox loam, 18 to 30 percent
slopes, eroded
Consociation Not prime farmland
FsA Fox silt loam, 0 to 2 percent
slopes
Consociation All areas are prime farmland

29. 27
FsB Fox silt loam, 2 to 6 percent
slopes
Consociation All areas are prime farmland
FsC2 Fox silt loam, 6 to 12 percent
slopes, eroded
Consociation Farmland of statewide importance
FsD2 Fox silt loam, 12 to 18 percent
slopes, eroded
Consociation Not prime farmland
Fu Fluvaquents Consociation Not prime farmland
FxC3 Fox soils, 6 to 12 percent slopes,
severely eroded
Consociation Farmland of statewide importance
Gb Granby variant fine sandy loam Consociation Not prime farmland
HnB Hochheim silt loam, 2 to 6
percent slopes, eroded
Consociation All areas are prime farmland
HnC2 Hochheim silt loam, 6 to 12
percent slopes, eroded
Consociation Farmland of statewide importance
HnD2 Hochheim silt loam, 12 to 20
percent slopes, eroded
Consociation Not prime farmland
HnE2 Hochheim silt loam, 18 to 30
percent slopes, eroded
Consociation Not prime farmland
HoD3 Hochheim soils, 12 to 18 percent
slopes, severely eroded
Consociation Not prime farmland
Hu Houghton muck Consociation Farmland of statewide importance
Hw Houghton muck, ponded Consociation Not prime farmland
IoA Ionia silt loam, 0 to 3 percent
slopes
Consociation All areas are prime farmland
JuA Juneau silt loam, 0 to 2 percent
slopes
Consociation All areas are prime farmland
JuB Juneau silt loam, 2 to 6 percent
slopes
Consociation All areas are prime farmland
Ke Keowns silt loam Consociation Prime farmland if drained
KlA Kibbie loam, 0 to 2 percent slopes Consociation Prime farmland if drained
KlB Kibbie loam, 2 to 6 percent slopes Consociation Prime farmland if drained
KrB Kidder loam, 2 to 6 percent slopes Consociation All areas are prime farmland
KrC2 Kidder loam, 6 to 12 percent
slopes, eroded
Consociation Farmland of statewide importance
KrD2 Kidder loam, 12 to 18 percent
slopes, eroded
Consociation Not prime farmland
KrE2 Kidder loam, 18 to 30 percent
slopes, eroded
Consociation Not prime farmland
KwA Knowles silt loam, 0 to 2 percent
slopes
Consociation All areas are prime farmland
KwB Knowles silt loam, 2 to 6 percent
slopes
Consociation All areas are prime farmland
KwC2 Knowles silt loam, 6 to 12 percent
slopes, eroded
Consociation Farmland of statewide importance
KxA Knowles variant silt loam, 0 to 2
percent slopes
Consociation All areas are prime farmland

30. 28
KxB Knowles variant silt loam, 2 to 6
percent slopes
Consociation All areas are prime farmland
LmA Lamartine silt loam, 0 to 2
percent slopes
Consociation Prime farmland if drained
LmB Lamartine silt loam, 2 to 6
percent slopes
Consociation Prime farmland if drained
LrB LeRoy silt loam, 2 to 6 percent
slopes
Consociation All areas are prime farmland
LrC2 LeRoy silt loam, 6 to 12 percent
slopes, eroded
Consociation Farmland of statewide importance
LrD2 LeRoy silt loam, 12 to 18 percent
slopes, eroded
Consociation Not prime farmland
LrE2 LeRoy silt loam, 18 to 30 percent
slopes, eroded
Consociation Not prime farmland
LvB Lomira silt loam, 2 to 6 percent
slopes
Consociation All areas are prime farmland
LvC2 Lomira silt loam, 6 to 12 percent
slopes, eroded
Consociation Farmland of statewide importance
MdB Markesan silt loam, 2 to 6 percent
slopes
Consociation All areas are prime farmland
MdC2 Markesan silt loam, 6 to 12
percent slopes, eroded
Consociation Farmland of statewide importance
MoA Mayville silt loam, 0 to 2 percent
slopes
Consociation All areas are prime farmland
MoB Mayville silt loam, 2 to 6 percent
slopes
Consociation All areas are prime farmland
MoC Mayville silt loam, 6 to 12 percent
slopes
Consociation Farmland of statewide importance
MrB McHenry silt loam, 2 to 6 percent
slopes
Consociation All areas are prime farmland
MrC2 McHenry silt loam, 6 to 12
percent slopes, eroded
Consociation Farmland of statewide importance
MrD2 McHenry silt loam, 12 to 18
percent slopes, eroded
Consociation Not prime farmland
MsB Mendota silt loam, 2 to 6 percent
slopes
Consociation All areas are prime farmland
MsC2 Mendota silt loam, 6 to 12
percent slopes, eroded
Consociation Farmland of statewide importance
MyB Miami silt loam, 2 to 6 percent
slopes
Consociation All areas are prime farmland
MyC2 Miami silt loam, 6 to 12 percent
slopes, eroded
Consociation Farmland of statewide importance
MyD2 Miami silt loam, 12 to 18 percent
slopes, eroded
Consociation Not prime farmland
MzD3 Miami soils, 12 to 18 percent
slopes, severely eroded
Consociation Not prime farmland
MzE3 Miami soils, 18 to 30 percent Consociation Not prime farmland

31. 29
slopes, severely eroded
NeB Neda silt loam, 2 to 6 percent
slopes
Consociation All areas are prime farmland
NeC2 Neda silt loam, 6 to 12 percent
slopes, eroded
Consociation Farmland of statewide importance
NeD2 Neda silt loam, 12 to 18 percent
slopes, eroded
Consociation Not prime farmland
NeE2 Neda silt loam, 18 to 30 percent
slopes, eroded
Consociation Not prime farmland
NvB Neda variant silt loam, 2 to 6
percent slopes
Consociation All areas are prime farmland
NvC2 Neda variant silt loam, 6 to 18
percent slopes, eroded
Consociation Farmland of statewide importance
NxA Nenno silt loam, 0 to 2 percent
slopes
Consociation Prime farmland if drained
NxB Nenno silt loam, 2 to 6 percent
slopes
Consociation Prime farmland if drained
Ot Otter silt loam Consociation Prime farmland if drained and either
protected from flooding or not
frequently flooded during the growing
season
Pa Palms muck, 0 to 2 percent slopes Consociation Farmland of statewide importance
Ph Pella silty clay loam, cool, 0 to 2
percent slopes
Consociation Prime farmland if drained
Pk Pella variant silt loam Consociation Prime farmland if drained
Pn Pits Consociation Not prime farmland
PsA Plano silt loam, till substratum, 0
to 2 percent slopes
Consociation All areas are prime farmland
PsB Plano silt loam, till substratum, 2
to 6 percent slopes
Consociation All areas are prime farmland
PtA Plano silt loam, moderately well
drained, 0 to 3 percent slopes
Consociation All areas are prime farmland
PuB Puchyan loamy fine sand, 2 to 6
percent slopes
Consociation All areas are prime farmland
RcE Rock outcrop‐Channahon
complex, 5 to 30 percent slopes
Complex Not prime farmland
RxC2 Rodman‐Casco complex, 6 to 12
percent slopes, eroded
Complex Not prime farmland
RxD2 Rodman‐Casco complex, 12 to 30
percent slopes, eroded
Complex Not prime farmland
ScA St. Charles silt loam, 0 to 2
percent slopes
Consociation All areas are prime farmland
ScB St. Charles silt loam, 2 to 6
percent slopes
Consociation All areas are prime farmland
ScC2 St. Charles silt loam, 6 to 12
percent slopes, eroded
Consociation Farmland of statewide importance

32. 30
SdA St. Charles silt loam, moderately
well drained, 0 to 2 percent
slopes
Consociation All areas are prime farmland
SeA St. Charles silt loam, gravelly
subtratum, 0 to 2 percent slopes
Consociation All areas are prime farmland
SeB St. Charles silt loam, gravelly
subtratum, 2 to 6 percent slopes
Consociation All areas are prime farmland
Sk Saprists and Aquents Undifferentiate
d group
Not prime farmland
Sm Sebewa silt loam Consociation Prime farmland if drained
SuA Sisson fine sandy loam, 0 to 2
percent slopes
Consociation All areas are prime farmland
SuB Sisson fine sandy loam, 2 to 6
percent slopes
Consociation All areas are prime farmland
SuC2 Sisson fine sandy loam, 6 to 12
percent slopes, eroded
Consociation Farmland of statewide importance
SuD2 Sisson fine sandy loam, 12 to 25
percent slopes, eroded
Consociation Not prime farmland
ThB Theresa silt loam, 2 to 6 percent
slopes
Consociation All areas are prime farmland
ThC2 Theresa silt loam, 6 to 12 percent
slopes, eroded
Consociation Farmland of statewide importance
ThD2 Theresa silt loam, 12 to 18
percent slopes, eroded
Consociation Not prime farmland
ThE2 Theresa silt loam, 18 to 30
percent slopes, eroded
Consociation Not prime farmland
TrD3 Theresa soils, 12 to 25 percent
slopes, severely eroded
Consociation Not prime farmland
Ud Udorthents, loamy Consociation Not prime farmland
Uf Udifluvents Consociation Not prime farmland
W Water Consociation Not prime farmland
M‐W Miscellaneous water Consociation Not prime farmland
LDF Landfill Consociation Not prime farmland

33. 31
6.2 Appendix B. Suggested trees and shrubs
The DNR has divided the state into different zones that
indicate what type of vegetation is appropriate to plant
depending on the location within the state. Dodge
County located within Zone 4 (NE), Zone 5 (SW). The
NW corner of the county is also located within a
“Tension Zone Boundary”, where the Prairie province
overlaps with the Hardwoods province.
Listed below are suggestions for proper species of trees
and shrubs for zones 4 and 5, as well as species that are
acceptable in both zones. This is intended to summarize
possible shrubs and trees to be planted within buffer
zones; more extensive evaluation and research will be
necessary before planting.
Zone 4 Shrubs
 Blackberry (Rubus allegheniensis)
 Black Raspberry (Rubus occidentalis)
 Thimbleberry (Rubus parviflorus)
 Gray Dogwood (Cornus racemosa)
 American Hazelnut (Corylus americana)
 Beaked Hazelnut (Corylus cornuta)
 Arrowwood (Viburnum dentatum)
 Staghorn Sumac (Rhus typhina)
 Smooth Sumac (Rhus glabra)
 Fragrant Sumac (Rhus aromatica)
Zone 4 Trees (Fruit‐bearing)
 Black Cherry (Prunus serotina)
 Pin Cherry (Prunus pensylvanica)
 Choke Cherry (Prunus virginiana)
Zone 4 Trees (Deciduous)
 Big‐Toothed Aspen (Populus grandidentata)
 Quaking Aspen (Populus tremuloides)
 Yellow Birch (Betula alleghaniensis)
 Paper Birch (Betula papyrifera)
 River Birch (Betula nigra)
 Sugar Maple (Acer saccharum)
 Red Maple (Acer rubrum)
 Silver Maple (Acer saccharinum)
 Green Ash (Fraxinus pennsylvancia)
Figure 17. Vegetative zones of Wisconsin

34. 32
 White Ash (Fraxinus americana)
 Black Ash (Freaxinus nigra)
Zone 4 Trees (Evergreen)
 Eastern Red Cedar (Juniperus virginiana)
 Hemlock (Tsuga canadensis)
Zone 5 Shrubs
 Silky Dogwood (Conrus amomum)
 Common Elderberry (Sambucus canadensis)
Zone 5 Trees (Fruit‐bearing)
 Prairie Crabapple (Pyrus ioensis)
 Sweet Crabapple (Pyrus coronaria)
 Hawthorn (Crataegus)
 Red Mulberry (Morus rubra)
Zone 5 Trees (Nut‐bearing)
 Shagbark Hickory (Carya ovata)
 Bitternut Hickory (Carya cordiformis)
Zone 5 Trees (Deciduous)
 Hackberry (Celtis occidentalis)
Zone 4 & 5 Shrubs
 Green Alder (Alnus viridis)
 Speckled Alder (Alnus incana)
 Smooth Alder (Alnus serrulata)
 Red‐osier Dogwood (Cornus sericea)
 American Highbush Cranberry (Viburnum trilobum)
 Ninebark (Physocarpus opulifolius)
 Wild Rose (Rosa)
Zone 4 & 5 Trees (Fruit‐bearing)
 Wild Plum (Prunus americana)
 Eastern Serviceberry (Amelanchier canandesis)
 Downy Serviceberry (Amelanchier arborea)
 Smooth Serviceberry (Amelanchier laevis)
Zone 4 & 5 Trees (Nut‐bearing)
 Butternut (Juglans cinerea)
 Black Walnut (Juglans nigra)
 White Oak (Quercus alba)

35. 33
 Bur Oak (Quercus macrocarpa)
 Swamp White Oak (Quercus bicolar)
 Red Oak (Quercus rubra)
 Black Oak (Quercus velutina)
 Northern Pin Oak (Quercus ellipsoidalis)
Zone 4 & 5 Trees (Deciduous)
 Basswood (Tilia americana)
 Boxelder (Acer negundo)
 Willow (Salix)
Zone 4 & 5 (Evergreen)
 Jack Pine (Pinus banksiana)
 White Pine (Pinus strobus)
 Red Pine (Pinus resinosa)
 Tamarack (Larix laricina)
When selecting species of vegetation to plant in a buffer zone, it is important to avoid plants that have
the potential to out‐compete native species. The DNR has provided a list of trees and shrubs to avoid.
Trees to avoid
 Common buckthorn (Rhamnus cathartica, Rhamnus frangula)
 European Mountain Ash (Sorbus aucuparia)
 Amur maple (Acer ginnala)
 Norway maple (Acer platanoides)
 Black locust (Robinia pseudoacacia)
 Chinese elm (Ulmus parciflora)
 Siberian elm (Ulmus pumila)
 European or black alder (Alnus glutinosa)
 White poplar (Populus alba)
 Lombardy poplar (Populus nigra italica)
Shrubs to avoid
 Honeysuckles (Lonicera tatarica, Lonicera x bella, Lonicera morrowii, Lonicera aackii)
 Japanese barberry (Berberis thunbergii)
 European barberry (Berberis vulgaris)
 Multiflora rose (Rosa multiflora)
 European cranberry bush (Vibernum opulus)
 Common privet (Lingustrum vulgare)
 Burning bush (Euonymus alatus)
 Autumn olive (Elaeagnus umbellate)
 Russian olive (Elaeagnus angustifolia)
 Smooth sumac (Rhus glabra)

36. 34
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