a ten year study of nitrate leaching in vegetable production with winter cover crops thesis defense...
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A Ten Year Study of Nitrate A Ten Year Study of Nitrate Leaching in Vegetable Leaching in Vegetable
Production With Winter Cover Production With Winter Cover CropsCrops
Thesis DefenseThesis Defense
Jeff FeagaJeff Feaga
M.S. M.S. Bioresource EngineeringBioresource Engineering
Part 1 -Part 1 - Methods Common to the Entire Methods Common to the Entire Study.Study.
Part 2 -Part 2 - Ten years of nitrate leaching Ten years of nitrate leaching below vegetable plots with and without below vegetable plots with and without cover crops.cover crops.
Part Part 3 -3 - Spread of conservative, non- Spread of conservative, non-absorbing, and soluble tracers through absorbing, and soluble tracers through field soils.field soils.
Outline of TalkOutline of Talk
Three Key PointsThree Key Points
OneOne Winter cover crops are a successful BMP for Winter cover crops are a successful BMP for
nitrogen management in the Willamette nitrogen management in the Willamette ValleyValley
TwoTwo Variations in rainfall timing and intensity Variations in rainfall timing and intensity
greatly affect the spread of solutes.greatly affect the spread of solutes.
ThreeThree The ADE is limited as a tool for predicting The ADE is limited as a tool for predicting
the spread of chemicals in soil.the spread of chemicals in soil.
MethodsMethods Location/ClimateLocation/Climate – –
North Willamette Research and Extension Center (NWREC) North Willamette Research and Extension Center (NWREC) Aurora, Oregon Aurora, Oregon
Maritime Climate: 104 cm of rainfall/year. Maritime Climate: 104 cm of rainfall/year.
SoilsSoils – Woodburn and Willamette Variant Loam. – Woodburn and Willamette Variant Loam.
ManagementManagement – – Summer VegetablesSummer Vegetables
Cover Cropped (H) Cover Cropped (H) Fallow (C)Fallow (C)
Three Fertilizer Rates (N0, N1, N2)Three Fertilizer Rates (N0, N1, N2)
Winter
Vegetables and Cover CropsVegetables and Cover Crops
Year Spring Crop Winter Crop
1989 Wheat Cereal Rye 1990 Sweet Corn Cereal Rye 1991 Broccoli Cereal Rye 1992 Sweet Corn Cereal Rye 1993 Broccoli Cereal Rye 1994 Sweet Corn Cereal Rye 1995 Broccoli ‘Celia’ Triticale 1996 Sweet Corn ‘Celia’ Triticale 1997 Broccoli ‘Celia’ Triticale 1998 Sweet Corn Cereal Rye 1999 Snap Beans ‘Celia’ Triticale 2000 Sweet Corn Common Vetch / Cereal Rye 2001 Snap Beans Common Vetch / Cereal Rye
Mario
Florian
Jeff
Hudson
Utility Players
Jaechul
Summer Summer VegetablesVegetables
Winter Winter Cover Cover CropsCrops
Separating the cereal rye Separating the cereal rye
from the common vetchfrom the common vetch
Common vetchCommon vetch
Do legumes scavenge nitrate?Do legumes scavenge nitrate?
Block I Block III
1 2 (C) 3 4 (H) 5 21 22 23 (C) 14 25
N2
N0
N2 N1
6 7 8 9 10 26 27 28 29 (H) 30
N0
N1
N2
Block II Block IV
11 12 (C) 13 14 15 31 (C) 32 33 (H) 34 35
N2
N0 N0
N1 N2
N0
N1 N2 N1
16 17 18 19 20 (H) 36 37 38 39 40
N1
N0
N2
OSU North Willamette Research and Extension Center: Cover Crop, Vegetable Rotation Trial
FLOODEDFLOODED
FLOODED
6 7
3 2
85
4 1
Sampler # Treatment 1 H2 N0 North 2 H2 N0 South 3 H 2 N 1 South 4 H 2 N 2 North 5 C4 N0 North 6 C4 N0 South 7 C4 N1 South 8 C4 N2 North 9 H4 N0 North 10 H4 N0 South 11 H4 N1 North 12 H4 N2 South 13 H3 N0 North 14 H3 N0 South 15 H3 N1 South 16 H3 N2 North 17 C3 N0 North 18 C3 N0 South 19 C3 N1 North 20 C3 N2 South 21 C1 N0 North 22 C1 N2 North 23 C2 N0 North 24 C2 N0 South 25 C2 N1 North 26 C2 N2 South
= PCAPS C fallow H Winter Cover Crop N0 No Fertilizer N1 Half Recommended N2 OSU Recommended
20
2426
21 22
23
1012
25 11 9
1613
19 17
18
14 15
N
W
S
E
99 m
18 m
9 m
99 m
N0
PCAPSPCAPS
It’s Raining Again!It’s Raining Again!
?
The Flow Weighting ProcessThe Flow Weighting Process
= Mean flow weighted concentration (M/L3) over multiple sampling events = Mean flow weighted concentration measured for multiple samplers as calculated for N sampling events = Average volume of percolation (L3) collected during each sampling event calculated for N sampling events = Number of sampling events
c
ic
iV
n
= Mean flow weighted concentration (M/L3) over multiple sampling events = Mean flow weighted concentration measured for multiple samplers as calculated for N sampling events = Average volume of percolation (L3) collected during each sampling event calculated for N sampling events = Number of sampling events
c
ic
iV
n
Total Mass Solute
Total Volume Water
________________
Soil SamplingSoil Sampling
ExtractionsExtractions
Brandi-Dohrn et al. (1996)Brandi-Dohrn et al. (1996) First two wintersFirst two winters 76% collection Efficiency76% collection Efficiency
Part II – Nitrate Leaching Part II – Nitrate Leaching Results Sampler Collection Results Sampler Collection
EfficiencyEfficiency
-40
-30
-20
-10
0
10
20
30
40
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
Rank From Sampling Dates #5 - #67
% D
ev
iati
on
Fro
m M
ea
n C
oll
ec
tio
n A
mo
un
t
Sampling dates #5 - #67
Sampling Dates #121 - #172
This AnalysisThis Analysis Winter 1993, 1999, and 2001Winter 1993, 1999, and 2001 Also a 76% collection Also a 76% collection
EfficiencyEfficiency
0
5
10
15
20
25
30
35
40
45
50
Con
cent
ratio
n N
O3- -
N (m
g/L)
0
100
200
300
400
500
600
700
800
900
Cum
ulat
ive
NO
3- -N m
ass
(kg/
ha)
Fallow (C)
Cover Crop (H)
Fallow (C) Cumulative
Cover Crop (H) Cumulative
Flow Weighted Averages: N2 PlotsFlow Weighted Averages: N2 Plots
Equal to 80 kg/ha/year or 71 lbs/acre/year
Average Concentrations:H Plots = 11.4 mg/L
C Plots = 17.1 mg/L
N0 Plots N1 Plots N2 Plots
0.0
0.1
0.2
0.3
0.4
0.5
p - V
alue
N = 10 N = 9N = 10
Concentration
N0 Plots N1 Plots N2 Plots
0.0
0.1
0.2
0.3
0.4
0.5
p - V
alue
N = 9 N = 10N = 9
One Tailed Paired T-tests: P-Value One Tailed Paired T-tests: P-Value DistributionDistribution
Mass
Mass Losses Under Legumes: Mass Losses Under Legumes: Mineralization?Mineralization?
0
50
100
150
200
N m
ass
(kg
/ha)
Fallow Cover Crop Fallow Cover Crop Fallow Cover Crop
Cereal Years (1992-1999) 1st Legume Year (2000) 2nd legume year (2001)
N0
N1
N2
Fertilizer Treatment
Mass N03-N
May 2001May 2001 Soil Sampling: Chemical Soil Sampling: Chemical Profiles Profiles
0
20
40
60
80
100
120
0 20 40 60 80
NO3--N Concentration (ppm)
Dep
th (c
m)
Cover
Fallow
0
20
40
60
80
100
120
0 20 40 60 80
Br- Concentration (ppm)
De
pth
(c
m)
Cover
Fallow
Residual Nitrate From Summer 2000
Br- from Dec 2000 Application
Crop Treatment and Br- Tracer Crop Treatment and Br- Tracer RecoveryRecovery
0
400
800
1200
1600
2000
Br-
Mas
s (m
g)
C Cumulative massH Cumulative mass
0
5
10
15
20
25
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0Pore Volumes
Br-
Con
cent
ratio
n (m
g/L)
C average concentration
H average concentration
C fitted concentration
H fitted concentration
C Plots 42% H Plots 32%
385 days
Cover Crops Are Effective Nitrate Cover Crops Are Effective Nitrate ScavengersScavengers
Concentration Concentration - 34% lower under N2 cover cropped plots than fallow - 34% lower under N2 cover cropped plots than fallow
plots during cereal years , (p = 0.05)plots during cereal years , (p = 0.05)
Mass losses Mass losses - 43% lower under N2 cover cropped plots than fallow - 43% lower under N2 cover cropped plots than fallow
plots during cereal years , (p = 0.05)plots during cereal years , (p = 0.05)
Rainfall timing and amount Rainfall timing and amount - influence concentrations, especially on the following - influence concentrations, especially on the following
year’s results.year’s results.
Legumes assimilated NOLegumes assimilated NO33 and Br and Br - More data needed to test ability for long-term - More data needed to test ability for long-term
scavengingscavenging
Switching FocusSwitching Focus
Part 3 –Part 3 – Transport of conservative, non-absorbing, Transport of conservative, non-absorbing,
and soluble tracers through field soils.and soluble tracers through field soils. Three applicationsThree applications
How is this study different?How is this study different? Structured field soilsStructured field soils Natural rainfallNatural rainfall Sampling methods – PCAPS enable measurement Sampling methods – PCAPS enable measurement
of flux concentrations, don’t require positive or of flux concentrations, don’t require positive or applied pressure for sampling.applied pressure for sampling.
ADEADE
RtD
RtVz
RtD
RtVz
RtDAR
MtzC
hd
w
hd
w
hd/4
/exp
/4
/exp
/4,
22
Which Parameters to Focus On?
C (z, t) = Concentration (mg/L)
Dhd = Hydrodynamic Dispersion: Molecular Diffusion + Mechanical Dispersion (Both in cm2/s)
Vw = Pore Water Velocity
The Three D’sThe Three D’s
mhd DDD 0
wm VD
whd VDD 0
Dhd = Hydrodynamic dispersion (cm2/s) D0 = Molecular diffusion of bromide (cm2/s) Dm = Mechanical dispersion (cm2/s) = Dispersivity (cm) Vw = Pore water velocity (cm/s)
Note*D0 is a
constant
Solving for the real dispersivitySolving for the real dispersivity
w
hd
V
DD 0
D0* = Diffusion coefficient for bromide with tortuosity constant (cm2/s)
k = 0.4, Tortuosity coefficient
whd VDD 0
3 Average Breakthrough 3 Average Breakthrough CurvesCurves
1992 Br -
1995 Cl-
2000 Br-
0
4
8
12
16
20
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8
Co
nc
en
tra
tio
n B
r- (m
g/L
)MeasuredFitted
0
2
4
6
8
10
12
0.0 0.4 0.8 1.2 1.6 2.0 2.4
Co
nc
en
tra
tio
n C
l- (
mg
/L)
MeasuredFitted
0
4
8
12
16
20
0.0 0.4 0.8 1.2 1.6 2.0
Time (relative pore volumes)
Co
nc
en
tra
tio
n B
r- (
mg
/L)
MeasuredFitted
0
4
8
12
16
20
0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8
Co
nc
en
tra
tio
n B
r- (m
g/L
)
0
2
4
6
8
10
12
0.0 0.4 0.8 1.2 1.6 2.0 2.4
Co
nc
en
trati
on
Cl- (
mg
/L)
0
4
8
12
16
20
0.0 0.4 0.8 1.2 1.6 2.0
Time (relative pore volumes)
Co
nc
en
tra
tio
n B
r- (m
g/L
)
= 3.74 cm
= 20.6 cm
= 15.8 cm
1992 Br- 1995 Cl- 2000 Br-
0
20
40
60
80
Disp
ersiv
ity (c
m)
Distribution of Values
They definitelydo not appear to be constant!
Dispersion is a function of Dispersion is a function of scalescale
Blue = Bromide 2000 Red = Chloride 1995 Green = Bromide 1992
Rainfall VariedRainfall Varied
0
5
10
15
201992 Bromide
0
5
10
15
20
25
30
35
40
1995 Chloride
0
5
10
15
20
25
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
2000 Bromide
Months Passed Since Tracer Application
Rai
nfa
ll (c
m)
November1992
November1995
December2000
1992 Br-: = 0.02 cmSampler # 17
1995 Cl- = 49.9 cmSampler #6
0
8
16
24
32
40
0.0 0.5 1.0 1.5Time (relative pore volumes)
Co
nce
ntr
atio
n B
r- (m
g/L
)
MeasuredFitted
0
2
4
6
8
10
0.0 0.4 0.8 1.2 1.6 2.0 2.4 2.8
Time (relative pore volumes)
Co
nce
ntra
tion
Cl
- (m
g/L
)
MeasuredFitted
131 days
440 days
0
5
10
15
20 1992 Bromide
0
5
10
15
20
25
30
35
40
1995 Chloride
Months Passed Since Tracer ApplicationR
ainf
all (
cm)
1 Pore Volume
1 Pore Volume
How Important is Molecular Diffusion? How Important is Molecular Diffusion? Peclet Number Analysis Peclet Number Analysis
Typically, DTypically, D00 is not considered: True? is not considered: True?
0D
dV
diffusion
dispersionPe
w d = characteristic length controlling transport
Characteristic LengthCharacteristic Length Peclet Number**Peclet Number**Silt Grain Size (0.001 cm)Silt Grain Size (0.001 cm) 6.9 x 106.9 x 10-4-4
Ped Size of 1 cmPed Size of 1 cm 0.690.69
Ped Size of 5 cmPed Size of 5 cm 3.473.47
**Using Average Velocity Calculated From PCAPS Flux
Distribution of Experimental
Peclet #’s
Characteristic lengthIS at Ped Scale!
0D
DPe hd Bear (1972)
1992 Br- 1995 Cl- 2000 Br-
100
101
102
2
34568
2
34567
2
34568
Pec
let N
umbe
r
1 cm Ped Controlled
5 cm Ped Controlled
10 cm Ped Controlled
Can PCAPS Can PCAPS Values Predict the Values Predict the Spatial Concentration Profile?Spatial Concentration Profile?
0
20
40
60
80
100
120
0 10 20 30 40 50
Concentration Br- (mg/L)
Dep
th
Spatially f it ADE
Field Measured
PCAPS Parameters
0
4
8
12
16
20
Dec-00
Feb-01
Apr-01
Jun-01
Aug-01
Oct-01
Dec-01
Feb-02
Apr-02
Mo
nth
ly R
ain
fall
(cm
)0
30
60
90
120
150
Cu
mu
lati
ve
Ra
infa
ll (c
m)Monthly Rainfall (cm)
Cumulative Rainfall (cm)
Soil Sampling Event
Sampler #20
PCAPS PCAPS Values Were Much Higher Values Were Much Higher Than Spatial Than Spatial Values Values
-5
0
5
10
15
20
25
30
5 7 8 17 19 20 23 25 26Sampler Number (Fallow Plots Only)
Dis
per
sivi
ty (
cm)
PCAPS Parameters
May 2001 Soil Sampling
Sep 2001 Soil Sampling
48 cm
Temporal Correlation of Temporal Correlation of
Do Samplers Consistently Fit Do Samplers Consistently Fit Values Above or Values Above or Below the Mean?Below the Mean?
Null Hypothesis: Three normalized Null Hypothesis: Three normalized Values Values came from a population with a mean of 1.came from a population with a mean of 1.
Only six samplers fit the alternative hypothesis.Only six samplers fit the alternative hypothesis.
Result: The group of Result: The group of Values Have No Correlation Values Have No Correlation in Timein Time
Exceptions: Samplers measuring the lowest and Exceptions: Samplers measuring the lowest and highest highest valuesvalues
Spatial Spatial DistributionDistribution
Filliben test:Filliben test: Significant Log-Normal Distribution of Values in Space
0
2
4
6
8
10
12
14
16
-1 to -0.9
-0.8 to -0.7
-0.6 to -0.5
-0.4 to -0.3
-0.2 to -0.1
0 to 0.10.2 to 0.3
0.4 to 0.5
Range of Log10 Dispersivity Values (normalized)
Fre
qu
en
cy
Tracer Transport ConclusionsTracer Transport Conclusions
Variation in Variation in not explained by velocity: rainfall cycles and not explained by velocity: rainfall cycles and
periods between diffusion and dispersion periods between diffusion and dispersion dominated transport.dominated transport.
Soil StructureSoil Structure Transport processes reflect the soil ped Transport processes reflect the soil ped
structure, not grain size.structure, not grain size.
Prediction of tracer spreadPrediction of tracer spread The main parameter of the ADE controlling The main parameter of the ADE controlling
solute spread is not constant in time and solute spread is not constant in time and space. As we implement it, the ADE is not space. As we implement it, the ADE is not capable of accurate transport predictions in capable of accurate transport predictions in natural conditions.natural conditions.
The Scientific Value of Long The Scientific Value of Long Term Experiments:Term Experiments:
10 Years of NWREC experiments were the 10 Years of NWREC experiments were the minimum to understand this soil system.minimum to understand this soil system.
Nature is highly variable, so cover crop Nature is highly variable, so cover crop experiments of a couple of years may not experiments of a couple of years may not lead to the true conclusions.lead to the true conclusions.
Laboratory and fast breakthrough tracer Laboratory and fast breakthrough tracer experiments rarely represent field experiments rarely represent field conditions.conditions.
How can we measure temporal aspects of How can we measure temporal aspects of model parameters if long-term studies are model parameters if long-term studies are not funded?not funded?
Thanks!Thanks!My major professor John Selker for his devotion to his students, his My major professor John Selker for his devotion to his students, his
intense interest in hydrology, and his love of practical solutions.intense interest in hydrology, and his love of practical solutions.
My committee: Richard Dick, Marshal English and Mike GamrothMy committee: Richard Dick, Marshal English and Mike Gamroth
USDA, USGS, EPA and the ODA for funding contributionsUSDA, USGS, EPA and the ODA for funding contributions
The ODA for funding this particular analysis.The ODA for funding this particular analysis.
All of the former students and Bob Christ that worked collecting All of the former students and Bob Christ that worked collecting datadata
Joan Sandeno for all the chromatographic analysis and organizing Joan Sandeno for all the chromatographic analysis and organizing the harveststhe harvests
Del Hemphill for doing all the farmin’ and welcoming new members Del Hemphill for doing all the farmin’ and welcoming new members into the PCAPS club at the NWREC.into the PCAPS club at the NWREC.
Yutaka Hagimoto for his help FINDING the PCAPS and soil samplingYutaka Hagimoto for his help FINDING the PCAPS and soil sampling..
All of the folks in Gilmore hall, especially Dave and Kristy, who All of the folks in Gilmore hall, especially Dave and Kristy, who make work far better than bearable.make work far better than bearable.
Surface FloodingSurface Flooding