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
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
P In
dex
Num
eric
val
ues
Quantitative P loss Estimates
Can we use a model to provide these data?
Is our P‐index directionally and magnitudinally correct?
Potential uses of model‐estimated P loss
P In
dex
Num
eric
val
ues
Quantitative WQ criteria
LOW
MEDIUM
HIGH
RISK
Assist with P‐index interpretation• Can the P‐index be “calibrated” to quantifiable P loss estimates?
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
Potential uses of model‐estimated P loss
P‐index Development
TP loss = β1(STP*Rsed) + β2(STP*Q) + β3(Prate*Q) + β4(AM*Q)
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 line1:1 line
What are the minimum data set requirements for calibration and validation?
RunoffSediment lossTotal 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)
Models are calibrated to measured data by adjusting model parameters
The calibration dataset will influence the final modelSensitive parameters may change
• Management• Climate• Soils
The calibration dataset must have enough information to inform all the sensitive parameters
Heartland Regional Model Development
12 datasets at 5 locationsSize: 0.4 – 5 ha.Crops
• Corn/Soybean/SorghumTillage
• No‐till/Reduced tillFertility
• Fertilizer• Poultry litter
Structures• Grass waterways• Buffers
Research Question
We developed a regionally calibrated APEX model…
Now, how can we use this model for P‐index evaluation?
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
How can we use the Regional Model to test P‐Indices?
Model UseIs the PI directionally correct? Calibration of P‐index categories Evaluation of PI components
Runoff Erosion Application Method Application Timing Application Rate
P‐index Development
Is the Kansas PI Directionally Correct?
Regional ModelKansas Locations
• Crawford• Franklin
432 simulations• 5 cropping systems• 4 STP values• 4 to 5 P application rates
• 3 watersheds
Evaluation of Kansas PI runoff
Runoff risk is assessed as a categorical variable based on the NRCS soil runoff classification
Runoff Classification Runoff PI ratingVery Low 0
Low 2Medium 4High 8
Very High 16
Evaluation of Kansas PI runoff
Evaluation of Kansas PI runoff
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 correctKS P‐index could be improved by revising the method to account for runoff
•We express appreciation to USDA‐NRCS Conservation Innovation Grant for funding this research
Questions
Is the Kansas PI Directionally Correct?
Regional Model Location‐specific Models