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

1. Evaluation of WEPP runoff and erosion
prediction: Goodwater Creek, Field One
Nayereh Ghazanfarpour1
Claire Baffaut2
Clark J. Gantzer1
Department of Soil, Environmental and Atmospheric Sciences1
USDA-ARS2
July 2014
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2. Introduction
 Estimating of soil loss by farmers and land managers to target BMP placement.
 “ Water Erosion Prediction Project ” WEPP (Lane and Nearing, 1989), physics-based
model for hillslopes / watersheds.
 “The Agricultural Policy/Environmental eXtender” APEX (Williams et al., 2008) -
field/watershed scale model.
 Apply the WEPP model on the Goodwater Creek Field #1 within the claypan soil
region and compare to APEX results (Mudgal et al. 2010).
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3. Claypan Soils
• Surface runoff is a main hydrologic process causing excessive losses of
NPS pollutants (Lerch et al. 2005).
• Events immediately following herbicide and/or fertilizer application are
most risky for the downstream area and water bodies.
• Characterized by a subsoil horizon with large increase in clay content
within a short vertical distance in the soil profile.
• During the winter and spring periods, the clays are swollen and causing a
high probability of runoff.
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4. Objectives
Studies have been done using WEPP model in locations across the U.S.
(Savabi, 1993; Savabi et al., 1995; Zhang et al., 1996; Baffaut et al., 1997; Laflen et al., 2004; Laflen, 2011)
 Apply the WEPP model for prediction of runoff and soil loss.
 Evaluate WEPP’s prediction compared to the APEX model (Mudgal et al. (2010) in the
same area).
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6. WEPP model advantages
 Spatial and temporal variability in topography, soil properties, cropping and management.
 Predicting spatial and temporal distributions of net soil loss or gain for any period of time.
 Capable of calculating sediment delivery to the stream channel.
 May be used both in single-event and continuous simulation mode.
 Results allow land managers and conservationists to delineate CMAs to target locations for
BMP placement.
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7. GeoWEPP
ArcGIS extension for the WEPP model
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Comparing WEPP and APEX
WEPP model APEX model
Rainfall
distribution
Breakpoints/ CLIGEN Daily precipitation
Infiltration Green– Ampt Mein Larson (GAML)
-Modification of the curve number method
-Green– Ampt infiltration equation
Runoff Solution of the kinematic wave equation Curve number (CN) equation
Erosion Steady state sediment continuity equation Modified USLE equation (Williams 1995)

9. Field Area
Field 1, a 35 ha (88 ac) agricultural field
Average annual precipitation 968 mm (38.1 in)
Average annual min and max daily temp. 6.3°C
and 16.9°C
Management in a corn–soybean annual crop
rotation.
Under mulch tillage, maintaining ~30% residue
cover
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10. Weir and automatic sampler
Weather Station
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WEPP and user inputs
1- Climate data
2- Management input
* Measured Data
(Inputs acquired from the USDA-ARS)
*

11. A soil survey (1:5,000 scale) in the field during 1997
Soil properties:
Texture, Cation Exchange Capacity (CEC), Organic
carbon content, Sum of bases, and pH in each soil
profile
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WEPP and user inputs: 3-

12. http://ned.usgs.gov/about.html (2009)
Topography: (3m)
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WEPP and user inputs: 4-

13. Tolerable value of
erosion
T = 3 t/ac
H2
H1
H3
H1 : 2.29 t/ac
H2 : 2.8 t/ac
H3 : 2.62 t/ac
1 T <=Sediment yield < 2 T
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Results
H: Hillslope

14. Results
y = 1.0286x ‐ 46.69
R² = 0.78
NSE= 0.69
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
0 10000 20000 30000 40000 50000
Simulated runoff (m3)
Measured runoff (m3)
Period: 1993‐2002
y = 0.67x + 2.13
R² = 0.80
NSE= 0.78
Pbias= 5.6 %
RSR= 0.47
0
50
100
150
0 50 100 150
Simulated runoff (mm)
Measured Runoff (mm)
Calibration period (1993‐1997)
y = 0.58x + 3.43
R² = 0.79
NSE= 0.72
Pbias= 22.7 %
RSR= 0.53
0
50
100
150
0 50 100 150
Simulated runoff (mm)
Measured runoff (mm)
Validation period (1998‐2002)
Runoff – Event based from WEPP
Runoff – Event based from APEX 0604
Not having a calibration and a validation period.
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15. Runoff – Monthly (total) by WEPP
y = 0.9605x + 411.92
R² = 0.84
NSE= 0.83
0
10000
20000
30000
40000
50000
60000
70000
80000
0 20000 40000 60000 80000
Simulated runoff (m3)
Measured runoff (m3)
Period: 1993‐2002
y = 0.7938x + 15364
R² = 0.89
NSE= 0.88
0
50000
100000
150000
0 50000 100000 150000
Simulated runoff (m3)
Measured runoff (m3)
Period: 1993‐2002
Results
Runoff –Yearly (total) by WEPP
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16. y = 0.4522x + 0.2197
R² = 0.50
NSE= 0.53
Pbias= 2 %
RSR= 0.69
0
5
10
0 5 10
Simulated sediment yield (t ha‐1)
Measured sediment yield (t ha‐1)
Calibration period (1993‐1997)
Sediment yield –event based by WEPP
y = 0.143x + 0.4101
R² = 0.01
NSE= 1.7
Pbias= ‐140 %
RSR= 1.65
0
1
2
3
0 1 2 3
Simulated sediment yield (t ha‐1)
Measured sediment yield (t ha‐1)
Validation period (1998‐2002)
Results
Sediment yield –event based by APEX 0604
y = 0.4962x + 0.17
R² = 0.38
NSE= 0.34
0
1
2
3
4
5
6
7
8
9
0 1 2 3 4 5 6 7 8 9
Simulated sediment yield (t ha‐1)
Measured sediment yield (t ha‐1)
All data (1993‐2002)
Dates: X: 26 Feb 97/ Y: 29 Jun 98
y = 0.583x + 0.142
R² = 0.61
NSE= 0.6
0
1
2
3
4
5
6
7
8
9
0 1 2 3 4 5 6 7 8 9
Simulated sediment yield (t ha‐
1)
Measured sediment yield (t ha‐1)
removed 2 points (1993‐2002)
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17. Sediment yield –monthly (total) by WEPP
y = 0.6231x + 3.2089
R² = 0.59
NSE= 0.48
2
4
6
8
10
12
14
0 2 4 6 8 10 12 14
Simulated sediment yield (t ha‐1)
Measured sediment yield (t ha‐1)
All data (1993‐2002)
y = 0.7688x + 2.3873
R² = 0.86
NSE= 0.75
0
2
4
6
8
10
12
14
0 2 4 6 8 10 12 14
Simulated sediment yield (t ha‐1)
Measured sediment yield (t ha‐1)
removed 2 points (1993‐2002)
y = 0.6129x + 0.3536
R² = 0.57
NSE= 0.55
0
2
4
6
8
10
12
0 2 4 6 8 10 12
Simulated sediment yield (t ha‐1)
Measured sediment yield (t ha‐1)
removed 2 points (1993‐2002)
Results
Sediment yield– yearly (total) by WEPP
y = 0.5614x + 0.4098
R² = 0.42
NSE= 0.36
0
2
4
6
8
10
12
0 2 4 6 8 10 12
Simulated sediment yield (t ha‐1)
Measured sediment yield (t ha‐1)
All data (1993‐2002)
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18. * Reasonably high R2 and NSE values for the simulation of runoff by WEPP (without
calibration process & considering slope of regression).
 An important reason: methods in the models; GAML equation for the WEPP model
and curve number for APEX.
 Green–Ampt model performs better than SCS (Chahinian et al. 2005; Shen, 2010).
 The main criticism of the SCS CN method: The amount of simulated runoff is not
sensitive to rainfall intensity and is independent of event duration or rainfall intensity.
Discussion- Runoff
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Discussion- Sediment yield
The analysis showed that WEPP simulated sediment yield better than APEX.
R2=0.61, NSE= 0.60
One important reason is the different methods used in the models.
WEPP uses the Steady-state sediment continuity equation to predict soil loss.
APEX sediment yield simulation is the MUSLE module. In MUSLE, the rainfall
energy factor is replaced with a runoff factor that allows to simulate individual
storm events.

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Discussion- WEPP & APEX
 It seems difficult to reproduce low sediment yields (<2 T/ha) with WEPP or with APEX.
 Uncertainty of the measurement of low sediment yields. The weir always causes some
amount of backwater and slowing down of the flow. When velocities are low (small
events), soil particles tend to precipitate and are not picked up by the sampler. So
simulated values being greater than measured ones (points along the y axis).
 In addition, the sampling is proportional to flow, i.e. water samples are collected
according to flow. Thus when flow is low, samples are collected with lower frequency
and there is greater error in the “measured” sediment load.

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Conclusion & Summary
 Reasonably high R2 and NSE values for the simulation of runoff and sediment yield (0.78
and 0.69, and 0.61 and 0.6, respectively) showed that the WEPP model performed
satisfactorily.
 Overall predictions of event-based runoff by the WEPP (without calibration) and APEX
(after calibration) models during simulation period were satisfactory.
 On the basis of R2 and NSE, the WEPP model provided better predictions than the APEX
model for event- based sediment yield.

22.  WEPP performed good: Information have significant implications for management
and could allow land managers and conservationists to delineate critical areas based
on them.
 Evaluation and comparison of the WEPP and APEX model will help to select a
model that meet needs based on the amount of available input information and the
capabilities of the personnel in the organizations.
Conclusion & Summary
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23. Next Goals
Scenario: No tillage with a winter cover crops.
Following soybean in rotation with corn:
1.Overseeded when soybean leaves begin to turn yellow and drop: cereal rye (rye)
2.The cover crop can be controlled in early/mid April.
Following corn in continuous corn or in rotation with soybean:
1.Overseeded: late August/early September one month before harvest - cereal rye (rye)
2.The cover crop can be controlled in early/mid April.
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Acknowledgment
• University of Missouri Experiment Station
• USDA- NRCS, Conservation Innovation Grant
• USDA- ARS, Cropping Systems and Water Quality Research
Nayereh Ghazanfarpour
Phone: 573-823-6830
E-mail: ghazanfarpourn@missouri.edu
Thank you

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