Tomer - Monitoring Choices Affect our Discernment of Watershed Processes

Monitoring Choices
Affect Our Discernment
of Watershed Processes
and Weather Controls on
Conservation Effectiveness
Mark Tomer
USDA/ARS
National Laboratory for Agriculture
and the Environment

Driving questions
 How can monitoring designs be chosen to provide the right information?
 How do we manage tradeoffs among contaminants (e.g., NO3-N vs. P)? Can
monitoring of multiple contaminants help answer this, or must we always
choose the lesser of two pollutants?
 Along what key pathways are contaminants being transported? How can
monitoring efforts help identify transport pathways and sources?
 Can monitoring results indicate what types of conservation practices could
achieve water quality improvement and where to place them?
 What is the role of (so called) extreme events in transport of agricultural
pollutants? What monitoring duration do we need to discern this?
 Can we use monitoring data to characterize conservation performance
beyond a simple ‘% removal’ metric?

Elevation
384m
285m
10 Km
Gauge Grab
station site
Stream
Tile
Field
South Fork Iowa River
Watershed
Two Case Studies

Upper Tipton watershed - Tile
drained, farmed wetlands (potholes)

Phosphorus
concentrations in
two tiles and
Tipton Cr. outlet,
2005-2007
Tipton Creek
0
0.5
1
1.5
2
2.5
3
3.5
4
Jan-05 Jul-05 Jan-06 Jul-06 Jan-07 Jul-07 Jan-08
Date
TotalP,mgL-1
0
0.5
1
1.5
2
2.5
3
3.5
4
Jan-05 Jul-05 Jan-06 Jul-06 Jan-07 Jul-07 Jan-08
Date
TotalP,mg/L
Large tile Small tile

Monitoring Sept. 2006 event
 Three scales – field runoff, two tile outfalls,
watershed outlet.
 Automated sampling
 Samples measured for NO3-N, Total P,
and E. coli and monitoring of hydrologic
discharge at all three scales.
 Sediment at the watershed outlet with
7Be:210Pb nuclide analyses to estimate
sediment source (channel vs. sheet & rill)

Context of event
 Dry antecedent conditions
 Late summer, full cover of mature crops
 Large event, but small hydrologic
response
 Peak discharge was about one half of
bank full discharge

"
"
Rainfall (mm)
47.9 - 57.6
57.7 - 67.2
67.3 - 76.9
77.0 - 86.6
" Rain gauge
Tile
Field
Rainfall event, Sept. 10-11 2006
0
20
40
60
80
100
120
140
9/10/06
0:00
9/10/06
12:00
9/11/06
0:00
9/11/06
12:00
9/12/06
0:00
Date & time
Rainfall,mm
Tile Field

Hydrologic response to rainfall
event at three scales
0.0001
0.001
0.01
0.1
1
10
10-Sep 11-Sep 12-Sep 13-Sep 14-Sep 15-Sep 16-Sep 17-Sep
Date (2006)
Q,mmhr-1
Stream Field Tile
Note double peak;
First for runoff, then
for tile flow

Field flume: discharge, nutrients,
and E. coli
0.0
2.0
4.0
6.0
8.0
10.0
12.0
10-Sep 11-Sep 12-Sep
Date (2006)
NO3-N&totalP,mgL
-1
ln(E.coli),mpn100mL
-1
0
10
20
30
40
50
60
Q,Ls
-1
NO3-N total P ln E. coli Q

Tile outfalls:
discharge,
nutrients,
and E. coli
0
5
10
15
20
25
Date (2006)
NO3-N&totalP,mgL
-1
lnE.colimpn100mL
-1
0
100
200
300
400
500
600
700
Q,Ls
-1
NO -N total P ln E. coli Q
0
5
10
15
20
Date (2006)
NO3-N&totalP,mgL
-1
lnE.colimpn100mL
-1
0
5
10
15
20
25
30
35
Q,Ls
-1
Nitrate-N Total P ln E. coli Outlet Q
Large tile (TC240)
Small tile (TC242)

Hydrograph
separations at
tile outlets
based on
NO3-N
mixing model
0
100
200
300
400
500
600
700
Date (2006)
Q,Ls
-1
Q Q (tile)
0
5
10
15
20
25
30
35
Date (2006)
Q,Ls
-1
Q Q (tile)
Large tile (TC240)
Small tile (TC242)

Stream outlet: discharge,
nutrients, and E. coli
0
5
10
15
20
25
Date (2006)
NO3-N&totalP,mgL
-1
ln(E.coli),mpn100mL
-1
0
1
2
3
4
5
6
Q,m
3
s
-1
NO3-N Total P ln (E. coli) Q

Hydrograph separation – Stream outlet
0
1
2
3
4
5
6
Date (2006)
Q,m
3
s
-1
Q Q (tile) Q (ground water)

Cumulative NO3-N loads at tile
and stream gauges
0
100
200
300
400
500
600
700
800
900
1000
9/10 9/11 9/12 9/13 9/14 9/15 9/16 9/17
NO3-Nload,gha-1
Stream Tile
0
100
200
300
400
500
600
700
800
900
1000
9/10 9/11 9/12 9/13 9/14 9/15 9/16 9/17
NO3-Nload,gha-1
Stream Tile

Sediment response:
78% from channel sources*
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Date (2006)
Sediment,kgm
-3
Fractionsediment
0
1
2
3
4
5
6
Discharge,m
3
s
-1
Sediment concentration
g/m3
Fraction sediment from
field erosion
Stream discharge
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
Date (2006)
Sediment,kgm
-3
Fractionsediment
0
1
2
3
4
5
6
Discharge,m
3
s
-1
Sediment concentration
g/m3
Fraction sediment from
field erosion
Stream discharge
*estimated on 7Be/210Pb nuclide ratios
Note: peak sediment concentration
occurred before hydrograph peak

Cumulative total P loads at tile,
field and stream gauges
0
10
20
30
40
50
60
70
Date (2006)
TotalPload,gha
-1
Stream Field Tile

Cumulative E. coli loads at tile, field
and stream gauges
0
2000
4000
6000
8000
10000
12000
14000
Date (2006)
E.coli-10
6
cfuha
-1
Stream Tile Field

Major
sources and
pathways:
Highly erodible crop land
Okoboji/Harps soils
Surface
Drainage districts
Sub-surface
• Subsurface (tile)
• Surface
• Channel

Study One - Conclusions
 NO3-N was dominantly sourced from tiles (>90%).
 Sediment was dominantly (78%) sourced from stream
banks.
 Surface intakes draining depressions found an important
source of P, along with stream sediments.
 E. coli was dominated by near- and in-channel sources,
although runoff and tile intake sources also contributed.
 Conservation emphases on erosion control and nutrient
management in this watershed should be expanded to
include vegetative practices that stabilize/restore
streams and buffer surface intakes that drain potholes.
 This single event analysis helped clarify source
pathways of key contaminants, helping to inform a more
comprehensive approach to water quality management.

Driving questions
 How can monitoring designs be chosen to provide the right
information?
 How do we manage tradeoffs among contaminants (e.g., NO3-N vs. P)?
Can monitoring of multiple contaminants help answer this, or must we
always choose the lesser of two evils?
 Along what key pathways are contaminants being transported? Can
 Can monitoring results indicate what types of conservation practices
could achieve water quality improvement and where to place them?

Transition to study two
 Study one comprised detailed and nested
monitoring (at 3 scales) of multiple
contaminants during a single rainfall runoff
event (seven days)
 Study two compared two fields for total P
transport and runoff amounts during
eleven years.

Elevation
384m
285m
10 Km
Gauge Grab
station site
Stream
Tile
Field
South Fork Iowa River
Watershed
SF101
SF102
Second Case Study

A tale of two fields:
HOW DO RUNOFF AND NUTRIENT LOADS DIFFER BETWEEN THEM?
one manured: SF101 one not: SF102

SF101
(manured)
SF102
(not manured)

Rainfall /
runoff
record
(daily)
0
20
40
60
80
100
120
140
160
180
2000
5
10
15
20
25
30
35
40
45
50
Jan-00
Jul-00
Jan-01
Jul-01
Jan-02
Jul-02
Jan-03
Jul-03
Jan-04
Jul-04
Jan-05
Jul-05
Jan-06
Jul-06
Jan-07
Jul-07
Jan-08
Jul-08
Jan-09
Jul-09
Jan-10
Jul-10
Runoff-producingprecipitation,mm
Surfacerunoff,mm
Date
Runoff Rainfall
0
20
40
60
80
100
120
140
160
180
2000
5
10
15
20
25
30
35
40
45
50
Jan-00
Jul-00
Jan-01
Jul-01
Jan-02
Jul-02
Jan-03
Jul-03
Jan-04
Jul-04
Jan-05
Jul-05
Jan-06
Jul-06
Jan-07
Jul-07
Jan-08
Jul-08
Jan-09
Jul-09
Jan-10
Jul-10
Runoff-producingprecipitation,mm
Surfacerunoff,mm
Date
Runoff Rainfall
SF101
SF102

Similarity in amounts of
rainfall and runoff per event
y = 1.01x
R² = 0.83
0
20
40
60
80
100
120
0 20 40 60 80 100 120
SF102rain(mm)
SF101 rain (mm)
y = 1.16x
R² = 0.77
0
5
10
15
20
25
30
35
40
0 5 10 15 20 25 30
SF102runoff(mm)
SF101 runoff(mm)

Significant difference in runoff – P load relationship
y = 0.018x0.947
R² = 0.870
y = 0.018x1.118
R² = 0.858
0.001
0.01
0.1
1
10
0 10 20 30 40
Plossduringevent(kg/ha)
Amount of runoff (mm/event)
Not Manured Manured

In-Field Conservation Practices Impact on
Runoff-P Load Relationship Could Improve
Effectiveness of Edge of Field Practices
0.001
0.01
0.1
1
10
0.01 0.1 1 10 100
Plossduringevent(kg/ha)
Amount of runoff (mm/event)
Reduce runoff amounts
PL = aQb

Study two: Conclusions
 Eleven years of monitoring provided data for >90 rainfall
runoff events in two field-sized watersheds differing in
manure application.
 Long periods with little or no runoff were punctuated with
flashy runoff events.
 Half the cumulative runoff observed in 11 yrs occurred in
<48 hours.
 The two watersheds were similar in rainfall and runoff
amounts.

Study Two Conclusions: P losses
 P losses characterized:
 P losses averaged about 1.80 kg/ha.yr in the manured watershed
and 1.05 kg/ha.yr in the non-manured watershed.
 Differences in the relationship between runoff and P losses were
observed – implications for assessment of practices, and on the
performance of additional practices placed below the field edge.
 Large events placed in context:
 Storms <60 mm resulted in 84-88% of the observed P load; more
than half the P load was associated with 30-60 mm rainfall events
in both watersheds.
 Conservation practices that limit runoff from <60 mm storms should
also limit P losses from these soils.

Driving questions
 Can monitoring designs be chosen to provide the right information?
Yes, consider goals and options for TIMING, FREQUENCY, NESTING
and DURATION of monitoring.
 How do we manage tradeoffs among contaminants (e.g., NO3-N vs. P)? Can
monitoring of multiple contaminants help answer this, or must we always
choose the lesser of two pollutants?
 Along what key pathways are contaminants being transported? Can
Contaminants may have unique sources and pathways, which nested,
detailed monitoring can help to characterize.
 Can monitoring results indicate what types of conservation practices could
achieve water quality improvement and where to place them?
YES, information on contaminant sources and pathways can help
identify appropriate practices to address multiple contaminants, at least
in a general way.
Decade or more of monitoring needed to place large events in context.
Suggestion to characterize runoff – nutrient load relationship when
evaluating practice effectiveness.

Thanks
Co-Authors
Kevin Cole
Tom Moorman
Tom Isenhart
John Kovar
Dave Heer
Chris Wilson
Technical support
Kelly Barnett
Beth Douglass
Amy Morrow
Jeff Nichols
Partners
Southfork Watershed Alliance
USDA-NRCS

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