Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.
Estimation of Phosphorus Loss From
Agricultural Land in the Southern Region of
the USA Using the APEX, TBET, and APLE
Mode...
Comparing Ratings of the Southern P
Indices: Prior Work
TX
OK
FL
AL GA
AR
LA
NC
MS
TN
KY
SC
²0 250 500125 Miles
Albers Equal-Area Conic
Southern States Involved in the USDA-NRCS
...
Southern CIG: Objectives
1. Determine pre-existing watershed or plot-scale (11) sites
where accuracy of P Indices to estim...
Locations of Data Sets
TX
OK
FL
AL GA
AR
LA
NC
MS
TN
KY
SC
²0 250 500125 Miles
Albers Equal-Area Conic
Southern Field Sites
State # Plots Date range Site-years Crop STP range (ppm)
1 2 3 4
AR 7 2009 – 2011 21 Pasture 81 - 183...
Texas BMP Evaluation Tool (TBET)
Climate
• Daily rainfall &
temperature
Soils
• Up to 3 series
Land use
• Crop system
Topo...
TBET Model Process
Calibrated
Single year simulations run on a daily time-step
• (1/1/YYYY – 12/31/YYYY)
2 years of warm-u...
TBET Baseline Results: Runoff
Overall annual observed vs predicted runoff
y = 1.1204x + 39.535
R² = 0.7099
0
200
400
600
8...
TBET Baseline Results: Sediment
Overall annual observed vs predicted sediment
y = 2.6329x + 4.6557
R² = 0.1062
0
20
40
60
...
TBET Baseline Results: Total P
Overall annual observed vs predicted total P
Site
Linear Relationship
NSE PBIAS
Intercept S...
TBET Baseline Results: Dissolved P
Overall annual observed vs predicted dissolved P
y = 0.469x + 0.2736
R² = 0.4852
0
2
4
...
TBET Preliminary Conclusions
TBET was used after being
calibrated
• Runoff predictions are satisfactory
with slight overpr...
Agricultural Policy/Environmental eXtender
(APEX)
• Underpredicted estimations
when annual Q< 100mm and
overpredicted when Q >
100mm
• Poor correlation and
performance
APEX...
APEX: North Carolina Results
(Flow, Soil Loss, TP, and DP)
APEX Preliminary Conclusion (Uncalibrated)
•Acceptable model performance predicting runoff
•Very inaccurate predictions fo...
Annual P Loss Estimator (APLE)
•User-friendly spreadsheet
•Annual time step
•Requires runoff and
erosion as inputs
•Does n...
APLE Model Process
Uncalibrated
Runoff and erosion values obtained from TBET model simulations
Does not require warm-up
Co...
APLE Results: Total P
Overall annual observed vs predicted total P
Site
Linear Relationship
NSE PBIASInterce
pt
Slop
e
R2
...
APLE Results: Dissolved P
Overall annual observed vs predicted dissolved P
Site
Linear Relationship
NSE PBIASInterce
pt
Sl...
APLE Preliminary Conclusions
• APLE is uncalibrated
• APLE uses modeled runoff and
erosion
• Dissolved P is better than to...
Conclusions
• Flow generally predicted better
than sediment, TP or DP
• Modeling was very time
consuming with uncertain
ou...
Questions
Thanks to our sponsor,
69-3A75-12-182
Upcoming SlideShare
Loading in …5
×

Estimation of phosphorus loss from agricultural land in the southern region of the usa using the apex, tbet, and aple models

545 views

Published on

Full Proceedings is available at: http://www.extension.org/72817

The purpose of our work was to determine, within the southern region (AL, AR, FL, GA, KY, LA, MS, NC, OK, SC, TN, and TX), the feasibility of using different models to determine potential phosphorus loss from agricultural fields in lieu of phosphorus indices.

Published in: Education
  • Be the first to comment

Estimation of phosphorus loss from agricultural land in the southern region of the usa using the apex, tbet, and aple models

  1. 1. Estimation of Phosphorus Loss From Agricultural Land in the Southern Region of the USA Using the APEX, TBET, and APLE Models Deanna Osmond, NC State University Adam Forsberg and David Radcliffe, University of Georgia John Ramirez, Mississippi State University Dan Storm and Aaron Mittelstet, Oklahoma State University Carl Bolster, ARS Waste to Worth Conference Seattle, WA March 30 – April 2, 2015
  2. 2. Comparing Ratings of the Southern P Indices: Prior Work
  3. 3. TX OK FL AL GA AR LA NC MS TN KY SC ²0 250 500125 Miles Albers Equal-Area Conic Southern States Involved in the USDA-NRCS Funded Conservation Innovation Grant (CIG)
  4. 4. Southern CIG: Objectives 1. Determine pre-existing watershed or plot-scale (11) sites where accuracy of P Indices to estimate site P loss potential can be evaluated. 2. Compare predictions of P-Indices to water quality data from benchmark sites. 3. Compare fate and transport models (APEX, TBET, APLE) against water quality data. Use water quality data (monitored or predicted by model) to guide refinement of P Indices. 4. Compare predictions of P Indices against fate and transport water quality models (APEX, TBET, APLE) for calibrated and uncalibrated models. 5. Refine P Indices to ensure better consistency in ratings across state boundaries and within physiographic provinces.
  5. 5. Locations of Data Sets TX OK FL AL GA AR LA NC MS TN KY SC ²0 250 500125 Miles Albers Equal-Area Conic
  6. 6. Southern Field Sites State # Plots Date range Site-years Crop STP range (ppm) 1 2 3 4 AR 7 2009 – 2011 21 Pasture 81 - 183 Captina (C) GA 6 1995 – 1998 24 Pasture 14 - 142 Cecil (B) Altavista (C) Sedgefield (C) Helena (C) NC 5 2011-2013 15 Corn with wheat cover 44-121 Delanco (C) MS 2 1996-1999 8 Cotton or soybens with wheat cover 37-79 Dubbs (B) Tensas (D) Alligator (D) Dundee (C) OK 1 1972-1976 4 Cotton 20 McLain (C) Reinach (C) OK 1 2006-2007 1.17 Pasture 50 Clarksville (B) OK 1 1977-1992 16 Native grass 15 Bethany (C) OK 1 1980-1985 6 Wheat 35 Norge (B) TX 1 1998-2001 4 Hay 435 Duffau (B) TX 1 2005-2008 4 Sorghum/Oats 34 Topsey (C) Brackett (C) Krum (D) TX 1 2005-2008 4 Native grass 10 Nuff (C) TX 1 2001-2008 7 Corn with wheat cover 51 Houston Black (D) Soil Series (hydro group)
  7. 7. Texas BMP Evaluation Tool (TBET) Climate • Daily rainfall & temperature Soils • Up to 3 series Land use • Crop system Topography • Field area • Field slope Soil Test P • Mehlich III Fertilization
  8. 8. TBET Model Process Calibrated Single year simulations run on a daily time-step • (1/1/YYYY – 12/31/YYYY) 2 years of warm-up • Initialize soil-moisture profile and nutrient pools Compared model predictions to measured values on an event-basis • Events within each year were summed for annual comparisons Runoff events greater than 0.1 mm were compared • If event-basis runoff spanned more than one day, total runoff for the entire storm (up to three days) was lumped for analysis Model evaluation • Slope, intercept, R-squared • Nash-Sutcliffe Efficiency • Percent Bias
  9. 9. TBET Baseline Results: Runoff Overall annual observed vs predicted runoff y = 1.1204x + 39.535 R² = 0.7099 0 200 400 600 800 1000 0 200 400 600 800 1000 Simulatedrunoff(mm/yr) Observed runoff (mm/yr) GA NC MS TX/OK AR Site Linear Relationship NSE PBIAS Intercept Slope R2 Overall 40 1.1 0.7 0.3 34 AR 31 2.2 0.9 -5.1 164 GA 120 0.5 0.5 0.1 30 NC 104 1.1 0.7 0.0 46 MS 39 1.3 0.9 0.1 45 TX/OK -18 0.8 0.8 0.7 -30
  10. 10. TBET Baseline Results: Sediment Overall annual observed vs predicted sediment y = 2.6329x + 4.6557 R² = 0.1062 0 20 40 60 80 100 0 20 40 60 80 100 SimulatedSS(ton/ha/yr) Observed SS (ton/ha/yr) NC MS TX/OK AR Site Linear Relationship NSE PBIAS Intercept Slope R2 Overall 4.7 2.6 0.1 -67.6 488 AR 0.0 3.8 0.3 -66.1 378 GA -- -- -- -- -- NC 20.8 7.1 0.4 -304.6 1698 MS 0.3 1.3 0.8 0.4 43 TX/OK 0.4 0.4 0.3 0.1 -40
  11. 11. TBET Baseline Results: Total P Overall annual observed vs predicted total P Site Linear Relationship NSE PBIAS Intercept Slope R2 Overall 3.5 1.7 0.1 -26.6 166 AR 0.7 0.8 0.5 0.1 39 GA 2.1 0.3 0.1 -0.4 -43 NC 21.7 5.9 0.5 -158.3 961 MS 1.0 0.4 0.4 0.4 -16 TX/OK 0.6 0.4 0.2 0.1 -36 y = 1.6941x + 3.5249 R² = 0.1028 0 50 100 150 0 50 100 150 SimulatedTP(kg/ha/yr) Observed TP (kg/ha/yr) GA NC MS TX/OK AR
  12. 12. TBET Baseline Results: Dissolved P Overall annual observed vs predicted dissolved P y = 0.469x + 0.2736 R² = 0.4852 0 2 4 6 8 10 12 14 16 18 20 0 5 10 15 20 SimulatedDP(kg/ha/yr) Observed DP (kg/ha/yr) GA NC MS TX/OK AR Site Linear Relationship NSE PBIASInterce pt Slop e R2 Overall 0.3 0.5 0.5 0.4 -41 AR 0.4 0.5 0.4 0.4 -10 GA 1.6 0.3 0.2 -0.2 -40 NC 0.2 0.3 0.5 0.4 -36 MS 0.0 0.3 0.9 -0.7 -72 TX/OK 0.0 0.2 0.2 -0.5 -77
  13. 13. TBET Preliminary Conclusions TBET was used after being calibrated • Runoff predictions are satisfactory with slight overprediction • Sediment for AR & NC is overpredicted • Total P is affected by overprediction of sediment and underprediction of dissolved P, which is systematically underpredicted • Modeling TBET was very time consuming with uncertain outcomes thus it may not be an appropriate field-based tool for predicting P loss especially if it is uncalibrated R2 NSE PBIAS Runoff 0.74 0.42 22 Sediment 0.07 -77.61 489 Total P 0.08 -30.53 176 Dissolved P 0.49 0.40 -44
  14. 14. Agricultural Policy/Environmental eXtender (APEX)
  15. 15. • Underpredicted estimations when annual Q< 100mm and overpredicted when Q > 100mm • Poor correlation and performance APEX: Georgia Results (Flow, TP, and DP)
  16. 16. APEX: North Carolina Results (Flow, Soil Loss, TP, and DP)
  17. 17. APEX Preliminary Conclusion (Uncalibrated) •Acceptable model performance predicting runoff •Very inaccurate predictions for phosphorus losses •Inaccurate soil erosion prediction in small plots •Tillage practices appears to be a factor that determines model performance (e.g. overprediction or underprediction) •Model setup required additional information that was not available in the southern databases and most producers would not have this information either •Modeling APEX was very time consuming with uncertain outcomes thus it may not be an appropriate field-based tool for predicting P loss especially if it is uncalibrated
  18. 18. Annual P Loss Estimator (APLE) •User-friendly spreadsheet •Annual time step •Requires runoff and erosion as inputs •Does not require calibration •Has most up-to-date fertilizer and manure application algorithm
  19. 19. APLE Model Process Uncalibrated Runoff and erosion values obtained from TBET model simulations Does not require warm-up Compared model predictions to measured values on an annual basis • Events within each year were summed for annual comparisons Model evaluation • Slope, intercept, R2 • Nash-Sutcliffe Efficiency (NSE) • Percent Bias (PBIAS)
  20. 20. APLE Results: Total P Overall annual observed vs predicted total P Site Linear Relationship NSE PBIASInterce pt Slop e R2 Overall 3.4 1.5 0.2 -18 -140 AR 0.7 1.0 0.6 0.3 -64 GA 1.5 0.4 0.3 0.1 37 NC 15 4.4 0.4 -3 -670 MS -0.4 1.4 0.8 -18 -24 TX/OK 0.3 0.2 0.4 -0.1 66 Measured TP loss (kg/ha) 0 5 10 15 20 25 PredictedTPloss(kg/ha) 0 20 40 60 80 100 120 NC MS GA AR TX/OK
  21. 21. APLE Results: Dissolved P Overall annual observed vs predicted dissolved P Site Linear Relationship NSE PBIASInterce pt Slop e R2 Overall 0.99 0.6 0.5 0.5 4.3 AR 0.5 1.0 0.7 0.3 -51 GA 1.2 0.5 0.4 0.1 28 NC 1.6 0.5 0.1 -3 -180 MS 0.3 2.0 0.3 -18 -160 TX/OK 0.3 -0.1 0.03 -1.4 49 Measured DRP loss (kg/ha) 0 5 10 15 PredictedDRPloss(kg/ha) 0 2 4 6 8 10 12 14 16 NC MS GA AR TX/OK
  22. 22. APLE Preliminary Conclusions • APLE is uncalibrated • APLE uses modeled runoff and erosion • Dissolved P is better than total P R2 NSE PBIAS Runoff -- -- -- Sediment -- --- -- Total P 0.2 -18 -140 Dissolved P 0.5 0.5 4.3
  23. 23. Conclusions • Flow generally predicted better than sediment, TP or DP • Modeling was very time consuming with uncertain outcomes thus it may not be an appropriate field-based tool for predicting P loss
  24. 24. Questions Thanks to our sponsor, 69-3A75-12-182

×