monitoring and modeling nitrate fate in subbasins

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Monitoring and Modeling Nitrate Fate in Subbasins with the Choptank River Watershed, Maryland, USA Greg McCarty USDA ARS

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69th SWCS International Annual Conference July 27-30, 2014 Lombard, IL

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Page 1: Monitoring and modeling nitrate fate in subbasins

Monitoring and Modeling Nitrate Fate in Subbasins with the Choptank River Watershed, 

Maryland, USA

Greg McCartyUSDA ARS

Page 2: Monitoring and modeling nitrate fate in subbasins

1

2

3

4

7

8 9

1011

13146

5

15

Page 3: Monitoring and modeling nitrate fate in subbasins

Metolachlor Fate

N

O

OS

O

OH

O

MESA {2‐[(2‐ethyl‐6‐methylphenyl) (2‐methoxy‐1‐methylethyl)amino]‐2‐oxoethanesulfonic acid} is a metabolite of metolachlor, which is a widely‐used pre‐emergent herbicide 

Glutathione conjugation is the common detoxification method for metolachlor in plants and its microbial degradation pathway in soil unsaturated zones 

MESA is like nitrate‐N very  water soluble, 2.12*105 g/L low sorption coefficient (calculated log Koc = 

1.13)  classified as highly mobile 

MESA is also very stable; its half‐life for all MESA processing has been estimated at 100 – 200 days

Metolachlor

MESA

Page 4: Monitoring and modeling nitrate fate in subbasins

Co‐movement of nitrate and MESA in Croplands

Page 5: Monitoring and modeling nitrate fate in subbasins

Drainage Condition of Subwatersheds

Page 6: Monitoring and modeling nitrate fate in subbasins

Sub‐watershed sampling• Samples (events = 12) were collected at the mouth of 15 sub‐watersheds within the Upper Choptank River and Tuckahoe Creek sub‐basins

• Spatial and temporal variation in biogeochemical processes and source water mixing will cause complex relationships between solute concentrations in stream and river waters

Page 7: Monitoring and modeling nitrate fate in subbasins

Subwatershed and Estuary SamplingBas

eflo

w (m

3 /s)

0

20

40

60

80

100

120

Tota

l flo

w (m

3 /s)

0

20

40

60

80

100

120

Baseflow Total flowSubwatershed samplingRiver sampling

03/01

/2005

06

/01/20

05

09/01

/2005

12

/01/20

05

03/01

/2006

06

/01/20

06

09/01

/2006

12

/01/20

06

03/01

/2007

06

/01/20

07

09/01

/2007

12

/01/20

07

03/01

/2008

06

/01/20

08

Bas

eflo

w (m

3 /s)

0

20

40

60

80

100

120

Tota

l flo

w (m

3 /s)

0

20

40

60

80

100

120

Tuckahoe USGS Gauge (01491500)

Greensboro USGS Gauge (01491000)

Page 8: Monitoring and modeling nitrate fate in subbasins

Variance of Nitrate and MESA in Sub‐watersheds

Nitra

te‐N (m

g/L)

CO NO DO BL KC PB OL

GB SF LM NF

BD BW OT0

3

6

9

12

Subwatershed

MESA ( g

/L)

CO NO DO BL KC PB OL

GB SF LM NF

BD BW OT0

3

6

WDUSFPDU

Page 9: Monitoring and modeling nitrate fate in subbasins

Collinearity of subwatershedproperties 

% Hydric Soils in Subwatershed

20 40 60 80

% C

ropl

and

in S

ubw

ater

shed

40

50

60

70

80

90

Page 10: Monitoring and modeling nitrate fate in subbasins

Nitrate concentration vs. Percentage Cropland

% Cropland in Subwatershed

40 50 60 70 80 90

Mea

n N

itrat

e-N

(mg/

L)

0

2

4

6

8

10

Page 11: Monitoring and modeling nitrate fate in subbasins

• Collinearity confounds interpretation of nitrate‐N fate as influenced by land use and land condition

• No correlation was found between MESA concentration and percentage cropland in the sub‐watersheds.

Page 12: Monitoring and modeling nitrate fate in subbasins

Conceptual ModelLand use/ condition Land management Local hydrology Impact on water fate

Cropland on well drained soils (high permeability soils)  

Low intensity ditch network and incised streams provide drainage required for crop production 

Predominant movement of precipitation into shallow groundwater due to high soil permeability

Oxic groundwater flow paths to local streams through surficial aquifers; deeper flow paths to regional groundwater via high permeability sediments

Cropland with low permeability soils  (prior converted wetlands)

High intensity ditch network provides drainage required for crop production 

Predominant movement of precipitation by vadose zone interflow to drainage ditches; low percolation potential 

Preferential ditch flow through landscape provides rapid transport  to the local stream network, impacting water chemistry

Page 13: Monitoring and modeling nitrate fate in subbasins

A more sensitive metric

% Cropland on Hydric Soils in Subwatershed

20 40 60 80

Mea

n N

itrat

e-N

/(Mea

n M

ESA*

1000

)

0.0

0.5

1.0

1.5

2.0

2.5

3.0

Page 14: Monitoring and modeling nitrate fate in subbasins

Conclusion

A more sensitive metric is percent cropland on hydric soil MESA leaches into groundwater with nitrate‐N and acts as a conserved transport analogRatio of nitrate‐N:MESA is correlated with percent cropland on hydric soils (R2 = 0.54***)Thus, croplands on well‐drained soils are the predominant source of nitrate‐N in streamsMitigation strategies should target these well‐drained area

Page 15: Monitoring and modeling nitrate fate in subbasins

Estuary  Sampling Transect

Station Median Salinity(range)

Water Depth (m)

1 9.5 (9.0 ‐ 12.3) 10

2 8.7 (6.6 ‐ 11.1) 7

3 5.0 (3.4 ‐7.8) 4

4 0.80 (0.17 ‐ 2.6) 12

5 0.12 (0.06 ‐ 0.53) 5

6 0.15 (0.06 ‐ 0.44) 2

7 0.10 (0.07 ‐ 0.17) 6

Eight synoptic  sampling campaigns were performance along the transect

Page 16: Monitoring and modeling nitrate fate in subbasins

Temporal and Spatial Variance

Whiskers represent minimum and maximum values, the box encloses the interquartile range, and the line within the box represents the median

River Site

Nitrat

e‐N (m

g/L)

1 2 3 4 5 6 70

1

2

3

4

aa

b

b b b

b

Nitrat

e‐N (m

g/L)

30 Mar 2005

2 Dec 2005

6 Apr 2006

11 Jul 2006

24 Aug 2006

25 Sep 2006

11 Apr 2007

16 Apr 2008

0

1

2

3

4

River Site

MESA

 ( g/L

)

1 2 3 4 5 6 70

2

4

6

MESA

 ( g/L

)

30 Mar 2005

2 Dec 2005

6 Apr 2006

11 Jul 2006

24 Aug 2006

25 Sep 2006

11 Apr 2007

16 Apr 2008

0

2

4

6

Page 17: Monitoring and modeling nitrate fate in subbasins

Nitrate‐N concentrations relative to MESA concentrations along the transect were linear for all eight sampling events (0.95 ≤ R2≤ 0.99 for all events except 25‐Sep‐2006, where R2 = 0.91; p ranged from < 0.001 to 0.044) 

MESA (g/L)

0 1 2 3 4 5

Nitr

ate-

N (m

g/L)

0

1

2

3

4

Page 18: Monitoring and modeling nitrate fate in subbasins

Conclusions

The strong correlation of nitrate‐N with MESA indicates that nitrate‐N was conserved in much of the Choptank River estuary and that dilution is responsible for the changes in nitrate‐N and MESA concentrations

An alternative mechanism, yet highly improbable, is that the processing rates in the river for nitrate‐N and MESA are exactly the same

Although somewhat unusual, nitrate conservation in estuaries has been documented elsewhere, e.g., Conwy Estuary and Waterford Harbor in Ireland (Raine and Williams, 2000) and the Delaware Bay (Fisher et al., 1988)

Page 19: Monitoring and modeling nitrate fate in subbasins

Sub‐basin Monitoring and Modeling

Page 20: Monitoring and modeling nitrate fate in subbasins

GreensboroTuckahoe

ET 5.2

Page 21: Monitoring and modeling nitrate fate in subbasins
Page 22: Monitoring and modeling nitrate fate in subbasins

Current Real Time data at the Greensboro Gage Station

Date/Time

11/1

/201

2

12/1

/201

2

1/1/

2013

2/1/

2013

3/1/

2013

4/1/

2013

Nitra

te (m

g-N/

L)

0

1

2

3

4

5

Turb

idity

(FTU

)

0

20

40

60

80

100

Stre

am d

isch

arge

(ft3

/s)

10

100

1000

NO3-N TurbidityStream Discharge

Hurricane Sandy

Page 23: Monitoring and modeling nitrate fate in subbasins

Nitrate loads

0

500

1000

1500

2000

2500

3000

3500

4000

0

1

2

3

4

5

6

7

7/6/2005

9/12/2005

11/9/2005

1/27/2006

4/18/2006

5/23/2006

7/12/2006

9/5/2006

11/7/2006

12/6/2006

1/10/2007

3/5/2007

4/17/2007

6/4/2007

7/30/2007

9/10/2007

12/3/2007

2/6/2008

3/11/2008

5/12/2008

7/8/2008

9/8/2008

11/16/2008

1/8/2009

3/12/2009

4/28/2009

6/4/2009

8/12/2009

9/28/2009

11/9/2009

12/10/2009

2/22/2010

4/8/2010

5/25/2010

7/12/2010

8/31/2010

10/2/2010

11/8/2010

1/10/2011

3/21/2011

5/23/2011

7/18/2011

8/30/2011

10/24/2011

12/5/2011

Stream

 flow

 (cms)

Nitrate (m

g/l)

TK_FLOW GSB_FLOW TK_Nitrate GSB_Nitrate

• TK_FLOW: Stream flow from the Tuckahoe watershed• GSB_FLOW: stream flow from the Greensboro watershed• TK_Nitrate: Nitrate load from the Tuckahoe watershed• GSB_Nitrate: Nitrate load from the Greensboro watershed

Page 24: Monitoring and modeling nitrate fate in subbasins

Preliminary Findings

• Both sub‐basins have similar amounts of cropland but nitrate export is twice as high in the Tuckahoe sub‐basin.

• Greensboro sub‐basin has greater percentage cropland on hydric soils.

Page 25: Monitoring and modeling nitrate fate in subbasins

Proportion of agricultural lands• Tuckahoe has higher % Agg in watershed than

Greensboro.

% Crop Forest Pasture Range Urban Water WetlandsTuckahoe 53.96 32.83 8.19 0.23 4.21 0.05 0.53

Greensboro 36.08 48.33 8.96 0.31 5.58 0.12 0.62

Page 26: Monitoring and modeling nitrate fate in subbasins

Soil properties

A B C DTuckahoe 0.99 48.09 5.58 45.33

Greensboro 4.51 24.54 12.92 58.02

Page 27: Monitoring and modeling nitrate fate in subbasins

Tuckahoe A (%) B (%) C (%) D (%)Cropland 0.39 57.10 6.58 35.92

Non‐cropland 1.70 37.54 4.41 56.35

Greensboro A (%) B (%) C (%) D (%)Cropland 3.07 33.85 19.26 43.82

Non cropland 5.33 19.29 9.35 66.04

Page 28: Monitoring and modeling nitrate fate in subbasins

Winter Cover Crop Modeling

• Currently using SWAT to model winter cover crop impacts on nitrate export.

• Difficulty calibrating the model to reflect differences in nitrate export.

• The denitrification parameter can only be set at the sub‐basin level.

• Need modification of SWAT to adjust to parameter based on drainage class for soils.