71st SWCS International Annual Conference July 24-27, 2016 Louisville, KY

1. Phosphorus Loss Estimation
and P‐Index Evaluation
with the APEX model
SWCS Annual Meeting – July 24‐27, 2016
Nathan Nelson, John Lory, Claire Baffaut, Anomaa Senaviratne, Ammar Bhandari,
Antonio Mallarino, Matthew Helmers, Ranjith Udawatta, Daniel Sweeney, and
Charles Wortmann

2. Why use a model to evaluate P‐indices?
 Need long‐term average annual P‐loss
 Need an independent method of evaluating a P‐ index
 Need estimates of P‐loss from many different
management, soil, and climate scenarios
PIndexNumericvalues
Quantitative P loss Estimates
Can we use a model to
provide these data?
Is our P‐index directionally
and magnitudinally correct?

3. Potential uses of model‐estimated P loss
PIndexNumericvalues
Quantitative WQ criteria
LOW
MEDIUM
HIGH
RISK
Assist with P‐index interpretation
• Can the P‐index be “calibrated” to quantifiable P loss estimates?

4. Potential uses of model‐estimated P loss
Evaluate P‐Index components
• Runoff
• Erosion
Evaluate specific scenarios
• Effect of Soil test P
• Effect of P application rate
• Effect of P‐application method
• Specific interactions
Preliminary Evaluation

5. Potential uses of model‐estimated P loss
P‐index
Development
TP loss = β1(STP*Rsed) + β2(STP*Q) + β3(Prate*Q) + β4(AM*Q)

6. What confidence level do we need to use a model
for P‐index evaluation?
How do we know how good a model is?
How good does a model need to be?
CALIBRATION VALIDATION
1:1 line
1:1 line

7. What are the minimum data set requirements for
calibration and validation?
Runoff
Sediment loss
Total P loss (and concentration?)
Dissolved P loss (and concentration?)
Crop growth (biomass or crop yield)
Short‐term P flux (fertilizer/manure P adsorption to soil,
P loss directly from applied sources)

8. Models are calibrated to measured data by
adjusting model parameters
The calibration dataset will influence the final model
Sensitive parameters may change
• Management
• Climate
• Soils
The calibration dataset must have enough information
to inform all the sensitive parameters

9. Heartland Regional Model Development
12 datasets at 5 locations
Size: 0.4 – 5 ha.
Crops
• Corn/Soybean/Sorghum
Tillage
• No‐till/Reduced till
Fertility
• Fertilizer
• Poultry litter
Structures
• Grass waterways
• Buffers

10. Research Question
We developed a regionally calibrated APEX model…
Now, how can we use this model for P‐index evaluation?

11. Regional Model Summary
Water Quality
Parameter
Overall Nash‐Sutcliffe
Model Efficiency
(validation)
Number of
sites passing
(out of 12)
Runoff 0.75 11 to 12 Pass
Sediment Loss ‐1.36 4 to 5 Fail
Total P loss 0.74 10 to 12 Pass (??)
Dissolved P loss Not evaluated Not evaluated Not evaluated
Short‐term P flux in soils Not evaluated Not evaluated Not evaluated
Regional model should be applied to soils and managements
similar to the datasets used for calibration and validation

12. How can we use the Regional Model to test P‐
Indices?
Model Use
Is the PI directionally correct? 
Calibration of P‐index categories 
Evaluation of PI components
Runoff 
Erosion 
Application Method 
Application Timing 
Application Rate 
P‐index Development 

13. Is the Kansas PI Directionally Correct?
Regional Model
Kansas Locations
• Crawford
• Franklin
432 simulations
• 5 cropping systems
• 4 STP values
• 4 to 5 P application
rates
• 3 watersheds

14. Evaluation of Kansas PI runoff
Runoff risk is assessed as a categorical variable based on
the NRCS soil runoff classification
Runoff Classification Runoff PI rating
Very Low 0
Low 2
Medium 4
High 8
Very High 16

15. Evaluation of Kansas PI runoff

16. Evaluation of Kansas PI runoff

17. Conclusions
Heartland Regional model can be used to evaluate P
indices for soils and managements similar to that used
for development
• Evaluation should focus on general P loss (not specific practice
comparisons)
• Can be used for evaluation of runoff component of PI
KS P‐index is directionally correct
KS P‐index could be improved by revising the method to
account for runoff

18. •We express appreciation to USDA‐NRCS Conservation
Innovation Grant for funding this research
Questions

19. Is the Kansas PI Directionally Correct?
Regional Model Location‐specific Models