Transcript How Management Effects Nutrient and Sediment Losses

How Management Effects
Nutrient and Sediment Losses
Dennis Frame
Fred Madison
Directors
UW Discovery Farms Program
Goals of Discovery Farms
1)
2)
Evaluate farming systems effects on air,
water and soil
Understand farming systems - how they
operate
Goals – Continued
3)
4)
Work with families to identify how to
modify farming systems while insuring
economic viability
Insure fairness of environmental
regulations
Questions To Address
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How much water really runs off of farm fields?
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When does this runoff occur?
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What is the magnitude of the losses associated with this
runoff?
When do these losses occur?
Discovery Farm Locations
Buffalo County
• Two paired basin sites (stream)
Iowa County
• Up/down stream and one field site
LaFayette County
• Three paired basin sites (field)
Kewaunee County
• Three paired basin sites (field)
• Two tile line sites
Discovery Farms
Special Projects
Manitowoc County
• Up / down stream sites
• One small basin site
• One tile site
• One large basin site
Waukesha County
• One small basin site
• Two tile monitoring sites
What are we analyzing for?
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Suspended Sediment
Total Dissolved Solids
TKN
Ammonium
Nitrate
Total P
Dissolved Reactive P
Chloride
Total Nitrogen
Organic Nitrogen
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Why did we choose
these constituents to
look at?
What is the
significance of these
constituents?
What is a runoff event or storm?
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There are two types of
runoff events: Those that
derive from rainfall on nonfrozen ground and those
that are the combination of
rain and melting snow on
frozen ground.
To fully understand the
relationships between the
landscape and its practices
to the water quality, both
types of runoff events are
important to analyze.
Sample Overview - 2004
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At the three sites we had
in operation, samples
representing 98% of the
annual storm volume
were collected.
This means, 2% of the
annual storm volume was
unsampled or “missed”
and concentrations were
estimated.
Sample Overview - 2005
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Samples representing 84% of
the total runoff volume were
collected in Kewaunee County.
Samples representing 95% of
the total runoff volume were
collected in Manitowoc County.
There were 524 discrete
samples taken so far in
Kewaunee County and 695
discrete samples (not including
the tile) in Manitowoc County.
M o n th ly P re c ip ita tio n a n d S u rfa c e W a te r R u n o ff T o ta ls fo r F a rm A a n d B
No v e m b e r 2 0 0 3 - A p ril 2 0 0 5
3.00
F arm A 3-B as in Average R unoff
R u n o ff, in in c h e s
2.50
F arm B 3-B as in Average R unoff
2.00
1.50
1.00
0.50
0.00
A pr-05
M ar-05
F eb-05
J an-05
D ec -04
N ov -04
O c t-04
S ep-04
A ug-04
J ul-04
J un-04
M ay -04
A pr-04
M ar-04
F eb-04
J an-04
D ec -03
N ov -03
When does runoff occur?
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Runoff during frozen
ground periods make
up a significant
portion of the yearly
runoff.
Farm A
Frozen Ground
50%
50%
Non-Frozen
Ground
Farm B
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Most studies don’t
capture snowmelt.
Frozen Ground
41%
59%
Non-Frozen
Ground
Snowmelt
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Snowmelt is labor
intensive.
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Freezing conditions
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State-wide event
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Weeks of runoff
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Expensive!
P re c ip ita tio n v s . R u n o ff D e p th , F ie ld Ye a r 2 0 0 4
F a rm A v s . F a rm B
40
P recip itatio n an d R u n o ff D ep th , in in ch es
P re cip ita tio n
Runo ff
35
30
25
34
40
20
15
10
5
8 - F ro z e n G ro u n d
2 1 - N o n -F ro z e n
5 - F ro z e n G ro u n d
G ro u n d
1 0 - N o n -F ro z e n
13%
0
G ro u n d
4%
13%
F arm A
F arm B
V a lu e s fo r p re c ip ita tio n s b a rs a re th e n u m b e r o f e v e n ts g re a te r th a n 0 .2 5 "
V a lu e s fo r ru n o ff b a rs a re th e n u m b e r o f ru n o ff e v e n ts (fro z e n g ro u n d v s . n o n -fro z e n g ro u n d )
2004 Suspended Sediment
Discovery Farms A & B
900
Suspended Sediment
(lbs/acre)
800
700
600
500
400
300
200
100
0
A1
A2
A3
B1
Site
B2
B3
Pounds/Acre
Suspended Sediment 2004
Discovery Farms A & B
900
800
700
600
500
400
300
200
100
0
Frozen Ground
Non-Frozen Ground
A1
A2
A3
B1
Sites
B2
B3
FY05 Sediment Loss Highlights
Suspended Watershed
Sediment
Size
Load (lbs)
(acres)
P1
278
20.5
Suspended
Sediment
Yield
(lbs/acre)
13.6
Suspended
Sediment
(Wheelbarrows)
0.51
P2
495.8
22.1
22.4
0.90
P3
405.8
13.2
30.8
0.74
K1
4489
495
9.0
8.16
K2
4381
641
6.8
7.97
K3
3718
14.7
253
6.76
Surface-Water Nutrient Losses FY04
FY04 Kewaunee Farm
Total Phosphorus Losses
FY04 Kewaunee Farm
Total Nitrogen Losses
1.6
Total Phosphorus, lbs/acre
Total Nitrogen, lbs/acre
18
Non-Frozen Ground
16
Frozen Ground
14
12
10
8
6
4
2
1.4
Non-Frozen Ground
Frozen Ground
1.2
1.0
0.8
0.6
0.4
0.2
0.0
0
1
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2
3
1
2
A large portion of the total nutrient losses
occurred during the period of frozen ground.
Can we assume this is the same for all years?
3
Total Nitrogen Yield 2004
Discovery Farms A & B
10.0
Pounds/Acre
8.0
6.0
Frozen Ground
4.0
Non-Frozen Ground
2.0
0.0
A1
A2
A3
B1
Sites
B2
B3
Frozen Ground Comparisons
2004 vs. 2005
D isco v e ry F arm B - F ro z e n G ro u n d b y Y e ar
T o tal N Y ie ld
7.0
2004
P o u n d s / A cre
6.0
2005
5.0
4.0
3.0
2.0
1.0
0.0
B1
B2
B3
11/5/03 7,0000 gallons
9/19/03 6,000 gallons
2/13/04 4,300 gallons
10/6/04~ 3.7 T pen m anure
10/19/04 4,100 gallons
10/29/04~ 143 T pen m anure
1/5/05~ 39 T, 1/28/05~ 52T,
2/12/05~ 65T, 2/19/05~ 78 T pen m anure
Total Phosphorus Yield 2004
Discovery Farms A & B
3.5
Pounds/Acre
3.0
2.5
2.0
Frozen Ground
1.5
Non-Frozen Ground
1.0
0.5
0.0
A1
A2
A3
B1
Sites
B2
B3
Frozen Ground Comparisons
2004 vs. 2005
D isco v e ry F arm B - F ro z e n G ro u n d b y Y e ar
T o tal P Y ie ld
4.0
2004
P o u n d s / A cre
3.5
2005
3.0
2.5
2.0
1.5
1.0
0.5
0.0
B1
B2
B3
11/5/03 7,0000 gallons
9/19/03 6,000 gallons
2/13/04 4,300 gallons
10/6/04~ 3.7 T pen m anure
10/19/04 4,100 gallons
10/29/04~ 143 T pen m anure
1/5/05~ 39 T, 1/28/05~ 52T,
2/12/05~ 65T, 2/19/05~ 78 T pen m anure
How is phosphorus lost?
2 0 0 4 D is c o v e ry F a rm B T o ta l P h o s p h o ru s
100%
90%
80%
70%
60%
P artic ulate P hos phorus
50%
D is s olved P hs phorus
40%
30%
20%
10%
0%
B1
B2
S ite
B3
Phosphorus Losses (Stream)
distribution during a storm?
Distribution of P during a storm
100%
100%
18%
90%
80%
18%
23%
87%
26%
37%
78%
70%
69%
Percent
60%
60%
% Dissolved P
% Particulate P
Cumulative % Particulate P
Cumulative % Total P
50%
47%
82%
40%
30%
82%
77%
63%
74%
32%
24%
20%
10%
9%
6%
0%
0-20%
20-40%
40-60%
60-80%
% of Total Storm Volume
80-100%
Surface-Water Nutrient Losses FY05
FY05 Total Nitrogen Losses
Kewaunee and Manitowoc Counties
FY05 Total Phosphorus Losses
Kewaunee and Manitowoc Counties
1.6
Total Phosphorus, lbs/acre
Total Nitrogen, lbs/acre
18.0
16.0
14.0
12.0
10.0
8.0
6.0
4.0
2.0
0.0
1.4
1.2
1.0
0.8
0.6
0.4
0.2
0.0
P1
P2
P3
K1
K2
K3
P1
P2
P3
K1
K2
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All the nutrient losses are associated with snowmelt.
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Some P1 losses are possibly due to wintertime manure applications.
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Some P3 losses are possibly due to alfalfa winter kill.
K3
Take Home Points Rainfall/Runoff
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It doesn’t run off every
time it rains.
The landscape plays a
role in the surface-water
runoff.
Frozen ground runoff is
significant in volume and
nutrient loss
Take Home Points Magnitude/Loss
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Sediment loss occurs
during non-frozen events
Sediment losses on these
farms are much less than
“T”
With proper management
farmers can achieve very
low rates of soil loss
Take Home Points Magnitude/Loss
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N & P loss is present
during both frozen and
non-frozen events
Most of the phosphorus
loss is in the dissolved
form
Take Home Points: Manure
Management
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Manure spread on
melting snow (imminent)
impacts water quality
Type of manure may or
may not matter
Timing of application is
important
Conclusions
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Our sites are well below tolerable soil loss levels.
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Farms can achieve tolerable soil loss and be profitable
Phosphorus loss may be different on a farm with significant soil loss
These farms are doing an excellent job of
harvesting rain (88 – 96%)
Applications of manure on melting snow result
in significant loss of both nitrogen and
phosphorus
Conclusions
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Manure applications in the late winter (when
snow melt is eminent) should be done on fields
which are internally drained and pose little risk
of runoff reaching surface waters
Conclusions
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Stream data and edge of field data are
different.
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Soil loss
Nutrient concentrations
We need more data to improve existing models.