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

1. Using agri‐environmental indicators to
track changes in the risk of nutrient and
sediment losses in the Lake Erie basin:
II. Application from watershed scale to
the Lake Erie Basin
Pamela Joosse, Natalie Feisthauer, Jillian Smith and Donna Speranzini
Science and Technology Branch
Agriculture and Agri‐Food Canada
69th SWCS Conference, Lombard, IL July 27‐30th 2014

2. AAFC Lake Erie Project Goals
• To identify agricultural production systems and
landscapes where there is capacity to make
improvements in nutrient and soil management
• To conduct historical analyses to put future
capacity for change in context with what has
already occurred
– This presentation focusses on components of the
project that analyze existing agri‐environmental
indicators and production system types for the Lake
Erie basin

3. I. Grand River Case Study
• Provided background on the National Agri‐
Environmental Health Analysis and Reporting
Program (NAHARP) indicators used in this
analysis
• Presented our Risk = Source x Transport model
• Provided results for risk of particulate and
dissolved reactive phosphorus loss for soils of
the Grand River watershed using this model
• Proof‐of‐concept pilot for application to the
entire Canadian Lake Erie basin
www.grandriver.ca

4. National Agri‐Environmental Health Analysis
and Reporting Program (NAHARP)
IROWC‐P: Indicator of Risk of Water Contamination by Phosphorus (van Bochove et al., 2009, 2010)
• Temporal & spatial trends for risk of surface water contamination by P from Canadian ag land
• Estimates phosphorus in the soil after crop harvest (P‐balance)
• Estimates partitioning of water (field scale) between surface runoff and soil leaching (VSMB)
• Hydrological connectivity factors used to estimate transport of P from field to surface water
RSN: Residual Soil Nitrogen (Drury et al., 2010)
• Estimates the inorganic nitrogen in the soil after crop harvest (N‐balance)
SoilERI: Soil Erosion Risk Indicator (Lobb et al., 2010; Li et al., 2008)
• Determines the risk of soil erosion by water (WatERI), tillage (TillERI), and wind (WindERI)
WatERI (McConkey et al., 2010, Li et al., 2008)
• Determines soil loss accounting for rainfall erosivity, crop and tillage type, and inherent erodibilty
of soil (Revised Universal Soil Loss Equation 2 equivalent)
• Includes inherent erodibility of each soil (k) and slope steepness (s) and slope length (L) factors

5. van Bochove et al., in: Eiler et al., 2010. Environmental Sustainability of Canadian Agriculture, Report #3.
National Agri‐Environmental Health Analysis
and Reporting Program (NAHARP)
• Geospatial framework for the NAHARP indicator models is the Soil
Landscapes of Canada (1:1 million scale)
– Model assumptions have to apply under all agricultural regions

6. Soil Landscapes of the Canadian Lake Erie Basin
• Data sources for NAHARP
models interpolated to SLCs
• Provides geospatially referenced
data that follows landforms and
ecological land classification
• Rural crop area illustrated

7. Our approach
• Source: nutrient balance =
• Transport Pathway: conduit by which nutrients/sediment are transported
from the field [to surface or groundwater]; depends on nutrient form, soil
type, and landscape features
http://peakwater.org/2012/04/protecting-water-at-the-source/
nutrient input (fertilizer, manure addition)
− nutrient removal (removal with crop harvest)
nutrient balance (nutrients remaining that year)
Risk = Source x Transport Pathway
K. Reid/
X

8. Risk
of Loss
= Source X
Dominant
Transport Pathway
=
Source
X
Transport Pathway
NAHARP
Model Surrogate
NAHARP Model Component
PP = Soil P X
Water erosion
towards surface water
=
Cumulative P*
(kg P/ha) IROWC‐P
X
Inherent erodibility of soil
(k*L*S) WatERI
DRP = Soil P X
Runoff
towards surface water
=
Cumulative P*
( kg P/ha) IROWC‐P
X
Surface runoff (R, mm)§
IROWC‐P VSMB
Soil = Soil X
Water erosion
towards surface water
=
k (erodibility of soil)
WatERI
X
L*S (length, slope of landscape)
WatERI
NO3
‐ = Soil N X
Leaching
through soil
=
Average§ N‐balance
(kg N/ha) RSN
X
Deep drainage (D, mm)§
IROWC‐P VSMB
Soil = Soil X
Water erosion
towards surface water
= Average§ WatERI (t soil/ha/year)
Our approach
• Risk determined for each SLC in the watershed
* Because P is conserved from year to year a cumulative P parameter for 2006 was developed by linear interpolation of the P‐
balance values of each of the six Census years (1981‐2006)
§ Average value of each of the six Census year data (1981‐2006)

9. Source: Phosphorus Balance 1981
• Nutrient balance =
• A positive P balance means there is more P
available to be applied in the area than crops
are removing
nutrient input (fertilizer, manure addition)
− nutrient removal (removal with crop harvest)
nutrient balance (nutrients remaining that year)

10. Source: Phosphorus Balance 2006
• A large portion of the basin had a negative P
balance
• A negative P balance means there is not
enough P available to be applied in the area to
replace what crops are removing

11. Source: Phosphorus Balance Trend
Source: E. Van Bochove, K. Reid, AAFC
• P‐balance (kg P/ha/year) from each Census year
data was used to calculate a linear trend over a
25‐year period (1981‐2006)
• Significantly declining P‐balance trends in some
SLCs in the basin
• No increasing trends in P‐balance in any SLCs

12. Source: Cumulative Phosphorus
• The capacity of P to bind to soil means there is potential for
it to accumulate over time with successive positive P‐
balances
• Cumulative P (kg P/ha) calculated for each SLC via linear
interpolation from P‐balance data from 1981 to 2006
• SLCs with higher cumulative P generally have more livestock
• Significant portion of the basin has a negative P
accumulation

13. Transport Pathway for PP: Erosion
Source: S. Li, AAFC
• Potential for soil erosion represented by
inherent characteristics of soil erodibility (k)
and slope length and steepness (LS) factors
from mid‐slope soils in a given SLC
• Represents the “inherent” relative risk of soil
erosion among the SLCs in the basin; does not
take into consideration crop type and tillage
practices

14. Relative Risk: Phosphorus (PP)
• Relative risk of loss of particulate
phosphorus among SLCs in basin
• Equal weighting of source (cumulative P)
and transport pathway (k x LS)
• Risk of loss from agricultural landscape

15. Transport Pathway for DRP: Water Runoff
• Average runoff (mm water/year) for each SLC in
the basin for six Census years (1981‐2006)
• Runoff estimate incorporates soil characteristics,
as well as precipitation and crop
evapotranspiration
• Runoff is excess water that can travel via surface
or tile drain pathways
• More runoff in areas dominated by till plains
Source: E. Van Bochove, AAFC

16. Relative Risk: Phosphorus (DRP)
• Relative risk of loss of dissolved
reactive phosphorus among SLCs in
basin
• Equal weighting of source (cumulative
P) and transport pathway (runoff)

17. Challenge with Current Indicators
• NAHARP models provide aggregate values for
all agricultural production in an SLC
– Provide relative idea of where practice change
could likely make improvements for a particular
issue
– Who and how much change they can make is
missing from current NAHARP models

18. Production System Component
• Recognition that practice change occurs within a
production system
• Conducted a pilot project in 2013‐14 with Census
of Agriculture 2011 micro‐data
• Apply production system typology rules to “label”
each farm as a type of production system
• Ended up with a hierarchy that facilitates “rolling
up” of output data if there is suppression

19. Production Systems Pilot Typology
• Consolidated Census Subdivisions (CCS) for Lake Erie

20. Livestock
(7,849)
Poultry (716)
Layer poultry (111)
Meat poultry (556)
Mixed Poultry (49)
Dairy (1,486)
Beef (2,456)
Hog (700)
Sheep/Goat (372)
Mixed/Other Livestock (2,119)
Crop
(11,846)
Specialty
(1,102)
1) Sod (27) 2) Mushroom (20) 3) Ginseng (159) 4) Tobacco (126)
5) Nursery (239) 6) Greenhouse flowers (202)
7) Greenhouse vegetables (223) 8) Mixed Specialty (106)
Fruit
(252)
1) Grape (42) 2) Tender fruit (22)
3) Berries (42) 4) Apples and Pears (61) 5) Mixed Fruit (85)
Other Cropland
(9,786)
Potatoes (73)
Fresh field vegetables (263)
Mixed vegetables with field crops (704)
Forage Based System (837)
Corn‐soybean dominant (2,559)
Soybean – W Wheat dominant (1,593)
Corn‐ soybean‐ W Wheat dominant (1,624)
Field crops of regional interest (832)
1) Dry Beans (201) 2) Sugar Beets (33)
3) Canola (51) 4) Spring grain (547)
Mixed/other cropping systems (1,301)
1) With AU (277)
2) Without AU (1,024)
Other Farm (706)
Number of Census Farms by Production System Lake Erie Basin = 19,695
For Discussion Only – Do not Distribute

21. Livestock
(7,849)
Poultry (716)
Layer poultry (111)
Meat poultry (556)
Mixed Poultry (49)
Dairy (1,486)
Beef (2,456)
Hog (700)
Sheep/Goat (372)
Mixed/Other Livestock (2,119)
Crop
(11,846)
Specialty
(1,102)
1) Sod (27) 2) Mushroom (20) 3) Ginseng (159) 4) Tobacco (126)
5) Nursery (239) 6) Greenhouse flowers (202)
7) Greenhouse vegetables (223) 8) Mixed Specialty (106)
Fruit
(252)
1) Grape (42) 2) Tender fruit (22)
3) Berries (42) 4) Apples and Pears (61) 5) Mixed Fruit (85)
Field Crops
(9,786)
Potatoes (73)
Fresh field vegetables (263)
Mixed vegetables with field crops (704)
Forage Based System (837)
Corn‐soybean dominant (2,559)
Soybean – W Wheat dominant (1,593)
Corn‐ soybean‐ W Wheat dominant (1,624)
Field crops of regional interest (832)
1) Dry Beans (201) 2) Sugar Beets (33)
3) Canola (51) 4) Spring grain (547)
Mixed/other cropping systems (1,301)
1) With AU (277)
2) Without AU (1,024)
Other Farm (706)
Number of Census Farms by Production System Lake Erie Basin = 19,695

22. Livestock
(7,849)
Poultry (716)
Layer poultry (111)
Meat poultry (556)
Mixed Poultry (49)
Dairy (1,486)
Beef (2,456)
Hog (700)
Sheep/Goat (372)
Mixed/Other Livestock (2,119)
Crop
(11,846)
Specialty
(1,102)
1) Sod (27) 2) Mushroom (20) 3) Ginseng (159) 4) Tobacco (126)
5) Nursery (239) 6) Greenhouse flowers (202)
7) Greenhouse vegetables (223) 8) Mixed Specialty (106)
Fruit
(252)
1) Grape (42) 2) Tender fruit (22)
3) Berries (42) 4) Apples and Pears (61) 5) Mixed Fruit (85)
Field Crops
(9,786)
Potatoes (73)
Fresh field vegetables (263)
Mixed vegetables with field crops (704)
Forage Based System (837)
Corn‐soybean dominant (2,559)
Soybean – W Wheat dominant (1,593)
Corn‐ soybean‐ W Wheat dominant (1,624)
Field crops of regional interest (832)
1) Dry Beans (201) 2) Sugar Beets (33)
3) Canola (51) 4) Spring grain (547)
Mixed/other cropping systems (1,301)
1) With AU (277)
2) Without AU (1,024)
Other Farm (706)
Number of Census Farms by Production System Lake Erie Basin = 19,695

23. Livestock
(7,849)
Poultry (716) 51%
Layer poultry (111)
Meat poultry (556)
Mixed Poultry (49)
Dairy (1,486)
Beef (2,456)
Hog (700) 62%
Sheep/Goat (372)
Mixed/Other Livestock (2,119)
Crop
(11,846)
Specialty
(1,102)
1) Sod (27) 2) Mushroom (20) 3) Ginseng (159) 4) Tobacco (126)
5) Nursery (239) 6) Greenhouse flowers (202)
7) Greenhouse vegetables (223) 63% 8) Mixed Specialty (106)
Fruit
(252)
1) Grape (42) 2) Tender fruit (22)
3) Berries (42) 4) Apples and Pears (61) 5) Mixed Fruit (85)
Field Crops
(9,786)
Potatoes (73) 53%
Fresh field vegetables (263)
Mixed vegetables with field crops (704) 54%
Forage Based System (837)
Corn‐soybean dominant (2,559) 63%
Soybean – W Wheat dominant (1,593) 74%
Corn‐ soybean‐ W Wheat dominant (1,624)
69%
Field crops of regional interest (832)
1) Dry Beans (201) 2) Sugar Beets (33) 72%
3) Canola (51) 4) Spring grain (547)
Mixed/other cropping systems (1,301)
1) With AU (277)
2) Without AU (1,024)
Other Farm (706)
Number of Census Farms by Production System Lake Erie Basin = 19,695 38%
% of provincial farms in basin

24. Production System Approach
• Use production system characteristics to calculate
system level nutrient balances, soil cover, and
erosion risks
• Look at vulnerability of soil landscapes where
systems are located to determine relative risk of
issues within and among production systems
• Complemented by Horticulture Environmental
Vulnerability project (Donna Speranzini)

25. Summary
• AAFC agri‐environmental indicators and their components can
be utilized to illustrate relative risk of nutrient and soil loss
among geospatially explicit landscapes within the Lake Erie
basin
• Identifying and characterizing production systems using
census of agriculture data will aid in determining inputs for
similar models at a production system scale
• These are just two lines of evidence to help determine the
capacity for nutrient and soil management improvements
among production systems in the Lake Erie basin

26. Acknowledgements:
• Agriculture and Agri‐Food Canada (AAFC): Keith Reid, Sheng Li, Ted
Huffman, Bahram Daneshfar, Ruibo Han and Jean Gordon
• Statistics Canada: Alessandro Alasia, Anne Munro

27. Citations:
Eilers, W., R. MacKay, L. Graham and A. Lefebvre (eds). 2010. Environmental Sustainability of Canadian Agriculture: Agri‐Environmental
Indicator Report Series — Report #3. Agriculture and Agri‐Food Canada, Ottawa, Ontario.
• Drury, C.F., J. Yang, R. De Jong, T. Huffman, X. Yang, K. Reid and C.A. Campbell. 2010. Residual Soil Nitrogen. Pages 74 – 80 in Eilers, W., R.
MacKay, L. Graham and A. Lefebvre (eds). 2010.
• Lobb, D.A., S. Li and B.G. McConkey. 2010. Soil Erosion Risk (integration the risks of wind, water and tillage erosion). Pages 46 – 53 in
Eilers, W., R. MacKay, L. Graham and A. Lefebvre (eds). 2010.
• McConkey, S. Li, M.W. Black and D.A. Lobb. 2010. Water Erosion Risk Indicator. Page 48 in Eilers, W., R. MacKay, L. Graham and A.
Lefebvre (eds). 2010.
• van Bochove, E., G. Thériault, J.‐T. Denault, F. Dechmi, A.N Rousseau and S.E. Allaire. 2010. Risk of Water Contamination by Phosphorus.
Pages 87 – 93 in Eilers, W., R. MacKay, L. Graham and A. Lefebvre (eds). 2010.
Li., S., B.G. McConkey, M.W. Black and D.A. Lobb. 2008. Water Erosion Risk Indicator (WatERI) Methodology in Soil erosion risk indicators,
Technical Supplement. Ottawa, ON, Canada:Agriculture and Agri‐Food Canada
van Bochove, E. and J.‐T. Denault (editors). 2009. Indicator of Risk of Water Contamination by Phosphorus (IROWC‐P). A Handbook for
presenting the IROWC‐P Algorithms. Research Branch. Agriculture and Agri‐Food Canada. Quebec. Contribution No. AAFC/AAC, 94 pp.