This document summarizes a national project to develop phosphorus indices and assess phosphorus loss for four regions across the United States. It involved establishing benchmark watersheds, identifying agricultural practices of concern, and comparing models like APEX, APLE and Drainmod to measured water quality data. The project found that calibrating models was challenging due to limited data and issues with model codes. It also found that modeled phosphorus loss estimates did not always match measured data and that developing a single national phosphorus index framework remains difficult. Models need updates to better represent regional hydrology and subsurface phosphorus loss.

1. • Chesapeake Bay – DE, NY,
PA,VA, & WV
• Heartland – IA, KS, MO, & NE
• Southern – AL, AR, FL, GA,
LA, KY, MS, NC, OK, SC, TN,
& TX
• National synthesis project

2. Peter Kleinman
& Doug Beegle• Establish 11 benchmark watersheds
 Water quality information
 Land treatment information
• Identify practices of concern in physiographic
regions (4) using expert panels composed of
 Farmers & farm advisors
 State and local agencies & environmental groups
• Compare P Indices to water quality data & water
quality modeling data using APEX, APLE & Drainmod

3. • All fate & transport models need to be updated
to better represent
 Site-specific hydrology (dependent on region)

4. This is what we must represe
177
144 44
1
<
Soil P – mg kg-1
Runoff – liters
P loss – kg P ha-1 y
92
Buda et al. JEQ, 20
Lowest field is now a CREP buffer
that continues to yield largest P load
4620
DPDPDP
8
DPDPDP78

5. Application rate
Collick et al. JEQ, 2016
6000 gal ac-1
9000 gal ac-1
NewOld NewOld
6
3
0
Runoff total P, kg ha-1
Field 1 Field 2
P routines must be
updated in ALL MODELS
Application timing
New
Old
1/15 1/31 2/14
0.1
0
0.2
6000 gal ac-1
Runoff total P, kg ha-1

6. 0.00
0.25
0.50
0.75
1.00
1/1/2010 2/20/2010 4/11/2010
0.0
1.0
2.0
3.0
4.0
1/1/2010 2/20/2010 4/11/2010
0
10
20
30
40
50
Measured
Old
New
No manure applied
Poultry litter applied,
January (2 tons ac-1)
Runoff P, mg L-1 Rainfall,
mm

7. John Lory,
Nathan Nelson
& Claire
Baffaut
• Assess rigor required in calibrating APEX
 Use data from existing runoff
studies
 Compare “out-of-the-box”
versus fully calibrated model
• Use calibrated model to assess & modify P Indices
• Develop & assess regional P Index for state
consideration
• Work with stakeholders throughout project

8. • Team vastly under-estimated time & challenges with
 Accessing & validating available water quality data
 Fixing problems identified in model code
 Delineating boundaries where use of APEX can be trusted
based on available water quality data
 These challenges not unique to Heartland effort
• Success promoting “team” approach to problem solving
 Transdisciplinary team with different approaches learned
to work together was rewarding

9. Deanna Osmond &
David Radcliffe
• Collate water quality & land
treatment data for plots & watersheds
 7 AR, 1 GA, 4 NC, 4 OK, and 4 TX
• Compare P-Index ratings against water quality
data
 Using both measured sediment & RUSLE2 soil
loss

10. 0
20
40
60
80
• RUSLE 2 estimates of erosion were up to an order
of magnitude greater than measured values
• NRCS loss ratings
 Low < 2.2 kg ha-1 yr-1
 Moderate 2.2 to
5.5 kg ha-1 yr-1
 High > 5.5 kg ha-1 yr-1
• How did tools
compare with NRCS
P loss ratings?
Percent correspondence with
NRCS loss rating
34
61
52
48
60
64
P INDICES
TBET APLEAPEX
Added
Multiply
Comp

11. • TBET
 Modeling TBET very time consuming with uncertain
outcomes
 TBET almost always over-estimates total P loss
• APEX
 Model setup requires information not available to most
producers
 APEX use was time consuming with uncertain outcomes
 Modeled results almost always under-estimates total P loss
• APLE
 Modeling APLE less time consuming than TBET & APEX
 Modeled results almost always over-estimates total P loss
• None appropriate as field-based tool, if uncalibrated

12. •Invaluable network among NRCS, Land Grants, &
stakeholders developed
•Estimating P transport (surface & leaching) still
major limitation
•There is considerable “uncertainty” with all
models and Indices
•Variation in model estimates can be ±100%
•Soliciting expert knowledge & converting it to
models very difficult

13. •Models can arrive at the right conclusions for the
wrong reasons
•To a certain extent model calibration &
validation detracted from P Index assessment

14. • We are far from developing framework of single national
P Index
• If a field advisory tool, must be simple to use &
interpret
• If a model, then we have many nonpoint source models
• But….
• All fate & transport models need to be updated to
better represent
 Site-specific hydrology (dependent on region)
 Subsurface P loss is high priority
 4R’s of nutrient stewardship