Claire Baffaut

Nutrient Management and Edge of Field monitoring: from the Great Lakes to the Gulf

Memphis, TN 2015

Multi-scale Monitoring for Improved Nutrient Management

Challenges of tracking progress

in streams

Additional processes

Lack of targeting

Lack of control:

Conflicting factors

Lack of spatial and temporal

information

No replication

Data interpretation

is difficult.

Changes are small and difficult to

detect.

Goodwater Creek Experimental Watershed

• Stream bank erosion

• Subsurface and ground water contributions.

• Nutrient storage in and resuspension from the streambed sediment.

• Filtering and nutrient uptake by riparian buffers.

Multiple processes

Bank sediment

87%

Overland sediment

13%

Instream sediment in Otter and Crooked Creek

Bank nitrogen

23%

Overland nitrogen

77%

Instream nitrogen in Otter and Crooked Creek

Willett et al., JSWC 2012.

Replication

Relatively easy at the plot scale:- Same soils- Same slope- Same initial conditions- Same weather- Same size and shape- Same orientation

Repeated treatments on several plots allow statistical analysis to

detect significant differences

Other monitoring and analysis strategies

• Before and after analysis: difficult because change in land agricultural practices is gradual.

• Trend analysis.

• Multiple regression analysis.

• Multiple scale monitoring.

BMPs in Goodwater Creek Experimental Watershed

15% of the watershed in

17 years !

• Before and after analysis.

• Trend analysis:

– Issues with conflicting factors.

– Effect of a strong random component

• Multiple regression analysis.

• Multiple scale monitoring.

Other monitoring and analysis strategies

Trend Analysis of Flow in GCEW

Year peak flow : 8 mm more per decadeNumber of flooded days: 2 more days per decade

Agricultural Land use

1967 Row crop (corn and soybean)

Small grain (wheat)

Hay and pasture

2006

Soil erosion and water storage capacity

• 13 cm (5.1 in) in 150 years

• 3.5 cm (1.4 in) in 40 years

• 14% of water storage capacity.

Top soil loss (cm)

-45 -20 0 20 45

(Lerch et al. 2005, JSWC)

1967 2009

Tributary crossing in Centralia

Urbanization

• 11% more people• 71% more houses

Conservation Practices

0

2

4

6

8

10

12

14

16

18

0

50

100

150

200

250

% w

ate

rsh

ed

pro

tect

ed

Are

a p

rote

cte

d (

he

ctar

es)

Grassed waterway

Terraces

Seeding

Sod busting

Grazing system

Lagoon

Filter Strip

Diversion

CP33,CRP

Buffer

Cumulative % landprotected

• Before and after analysis.

• Trend analysis.

• Multiple regression analysis: requires good spatial and temporal knowledge of what is happening in the watershed.

• Multiple scale monitoring.

Other monitoring and analysis strategies

Multiple regression analysis

• Requires good spatial and temporal information of:– Weather

– Land use

– Crop distribution

– Land management, including• Cropland management and best management practices

• Sanitary sewage treatment

• Management of urban areas

• Management of pastures

Multiple regression

• No trend of nitrate loads over 92-06 in GCEW (O’Donnell, 2010).

• Decreasing trend over 1992-2010 (Lerch et al., 2015), possibly linked to decrease in wheat production.

• No BMP linked variable found significant.

• Not the right BMPs?• Not the right location?

Crop land

Pasture & grass

Impervious areas

Critical areas

Conservation practices

Time needed to detect change

• Mean Square Error of model was used to estimate the monitoring period needed to detect a future change

Predicted number of years needed to detect load reduction

Nitrate load reduction

Season 5% 10% 20% 25%

Year 92 24 7 4

Spring 185 49 13 9

O’Donnell, 2010

• Before and after analysis.

• Trend analysis.

• Multiple regression analysis: requires good spatial and temporal knowledge of what is happening in the watershed.

• Multiple scale monitoring.

Other monitoring and analysis strategies

Multiple scale monitoring

Stream Weir W1

Field

1993-2002Mulch tilled

corn-soybean

2004-2014Precision

Agricultural System (PAS)

Field 1

Pre-PAS 1993-2002 PAS 2004-2013South 40 acres North 52 acres

Odd year Corn (sorghum in 95)

N: pre-plant UAN,

incorporated

P: 1993, 1995, 2001

incorporated

Cultivation

Corn / Cover Crop

N: at planting + top

dress early summer

No-till

Wheat / Cover Crop

N: top dress in April

No-till

Even

year

Soybean

Cultivation

Soybean / Cover Crop

P: 2004, 2006, 2008

broadcast

No-till

Soybean / wheat

N: at wheat planting

P: 2004, 2006, 2008

broadcast

No-till

Effect of no-till and cover cropsFlow

Effect of no-till and cover cropDissolved P loss

Effect of no-till and cover cropNitrate-N loss

Effect of no-till and cover cropSediment

Annual Sediment losses

Summary• No-till and cover crops did: Reduce sediment

Did not change Nitrate-N transport

Did increase Dissolved P transport

• Agronomic practices, land use change, urbanization,

stream processes and climate all contribute to

modifying the runoff/sediment/nutrient yield regime of a watershed and make it difficult to:

detect a trend,

discern whether detected trends are due to any one factor.

Implications

To improve detection of water quality trends resulting from management changes, these changes should be:

• Implemented within a short time.

• Spatially targeted.• Of large magnitude.

• Addressing the processes that cause the problem

documented by the monitoring. Scale matters!

Data Management

• Equipment fails data gaps fill in the gaps

• Sediment loss measurements

• Inaccurate data

– Flow > Precipitation

– Issues with small events

• Meta data

AcknowledgementsCropping Systems and Water Quality Research Unit

Newell Kitchen, Ken Sudduth, Bob Lerch

Matt Volkmann, Kurt Holiman, Mark Olson, Aaron Beshears,

Teri Oster, Scott Drummond, Bettina Coggeshall.

ARS CEAP LTAR