Comparison of Models forEstimating the Removal ofPesticides by Vegetative BufferStripsMichael Winchell1, Russell Jones2, Tammara Estes11. Stone Environmental,Montpelier, Vermont2. Bayer CropScience, Stilwell, KansasEMPM MeetingJuly 27, 20102Contents1 Background2 Models Evaluated3 Case Studies4 Conclusions3■Vegetated filter strips (VFSs) have longbeen recommended as a BestManagement Practice (BMP) to reducesediment, nutrients, and pesticidesentering water bodies.■VFSs have been mandated asrequirements on labels for crop protectionproducts in North America and the EU.Background: Motivation■The use of physically-based models to estimate the effectiveness ofVFSs is a cost-effective supplement(or alternative) to field studies.4■Objective 1: To test the ability of four models (APEX, PRZM-BUFF,REMM, and VFSMOD) in simulating VFS effectiveness on threecommon datasets in anuncalibratedsimulation mode.20 runoff data points20 sediment data points33 pesticide data points■Objective 2: To understand the sensitivity of model predictions tothe uncertainty in key model input parameters.■Objective 3: To provide an analysis that will aide in the selection ofappropriate models for use as decision-making tools in estimatingVFS effectiveness at reducing pesticides in runoff and sediment.Background: Study Objectives5■Developers: Texas Blackland Research and Extension Center / USDA■Model Scale: Farm, small watershed, field: Continuous, daily time step■Primary Use: Agricultural non-point source, crop growth, nutrientmanagement■Model Structure:Agricultural fields and buffers aresimulated as independent subareasFlow, sediment, nutrient, andpesticide are routed todownstream subareas via overlandflow and channel flowAgricultural Policy EnvironmentalExtender Model (APEX)6■Developers: Waterborne Environmental■Model Scale: Field plus buffer: Continuous, daily time step■Primary Use: Pesticide exposure, agricultural non-point source■Model Structure:Agricultural fields and buffersare simulated as independentPRZM runs.Flow, sediment, andpesticide loads from field areaare added directly to bufferareas, simulated throughadditional PRZM runs.Pesticide Root Zone Buffer Model(PRZM-BUFF)7■Developers: USDA / ARS■Model Scale: Multi-zone buffer: Continuous, daily time step■Primary Use: Nutrient trapping and management of managed andunmanaged riparian buffers■Model Structure:A three-zone buffer system issimulated with REMM (grassfilter, managed riparian,unmanaged riparian).Flow, sediment, and pesticidefield loads are provided as inputto the model and routed downstreamthrough the 3 zones.Riparian Ecosystem ManagementModel (REMM)8■Developers: University of Florida■Model Scale: Buffer: Sub-hourly, event-based■Primary Use: Non-point source water quality, buffer design/optimization■Model Structure:Flow and sediment field loads areprovided as input to the model.Infiltration and sedimentdeposition are simulated in asingle buffer zone.Pesticide reduction is calculatedas a function of infiltration,deposition chemical characteristics,and soil clay.Vegetated Filter Strip Model:(VFSMOD)9■Location: Part of USDA experimental watershed near Tifton, GA■Buffer Characteristics:Length x Width: 120 m x 8 m.Field to Buffer Area Ratio: 11.5Slope: 2.5%Soil: Tifton loamy sand■Monitoring:3 years continuous (1992 – 1994)■Pesticides Simulated:Alachlor: Koc = 54 mL/gCase Study: Gibbs Farm, Georgia10Results: Gibbs Farm, Long-TermPesticide ReductionsTotal Alachlor Mass Reduction in Buffer, 1992 - 19940102030405060708090100Full Year After Applications Between ApplicationsPesticide

Percent Reduction (%)ObservedAPEXPRZM-BUFFREMMVFSMOD■After applications representsapp date through June 30th(or 25 cm rainfall)■Between applications represents June 30th(or 25 cm rainfall) thru following year’s app11■Location: In the north Rhine-Westphalia region of Germany■Buffer Characteristics:Length x Width: 1.5 m. x 3 m.Field to Buffer Area Ratio: 2.3Slope: 10%Soil: Silty loam■Monitoring:6 simulated rainfall events (1998 - 1999)■Pesticide Simulated:Pendimethalin: Koc = 12,495 mL/gCase Study:Velbert-Neviges, Germany12Results: Germany, Event-BasedPendimethalin ReductionsTotal Pendimethalin Mass Reduction in Buffer01020304050607080901005/28/98 6/5/98 6/8/98 5/27/99 6/1/99 6/16/99Event

Percent Reduction (%)ObservedAPEXPRZM-BUFFREMMVFSMOD13■For several groups of simulations, model performance wasevaluated based upon the Mean Absolute Error (MAE).■This is calculated as follows:■Where: Robsi= Observed mass/volume reduction by buffer, forevent i (%)Rsimi= Simulated mass/volume reduction by buffer, forevent i (%)n = number of events in groupResults: Evaluation of Model ErrorniiiRsimRobsnMAE1114Results: Germany, Absolute Error inBuffer Reduction EfficiencyMean Absolute Error in Buffer Reductions Over 6 Events020406080100120APEX PRZM-BUFF REMM VFSMODModel

Absolute Error (%)RunoffSedimentPesticidePrimary bar represents the mean of 6 events.Error bars represent min and max of 6 events.15■Location: In western Sioux County Iowa■Buffer Characteristics:Length x Width: 4.6 m. x4.6 m; 0.46 m. x 4.6 mField to Buffer Area Ratio: 15:1; 30:1Slope: 5.25%Soil: Silty clay loam■Monitoring:4 simulated run-on events, 3 replicates■Pesticides Simulated:Chlorpyrifos: Koc = 9,930 mL/gAtrazine: Koc = 171 mL/gCase Study:Western Sioux County, Iowa16Results: Sioux County, Event-BasedAtrazine ReductionTotal Atrazine Reduction in Buffer12 Plots SimulatedR2= 0.84R2= 0.84R2= 0.84R2= 0.8201020304050607080901000 20 40 60 80 100Observed Reduction (%)

Simulated Reduction (%)APEXPRZM-BUFFREMMVFSMOD17Results: Sioux County, Event-BasedChlorpyrifos ReductionTotal Chlorpyrifos Reduction in Buffer12 Plots SimulatedR2= 0.84R2= 0.88R2= 0.74R2= 0.8501020304050607080901000 20 40 60 80 100Observed Reduction (%)

Simulated Reduction (%)APEXPRZM-BUFFREMMVFSMOD18Results: Sioux County, AbsoluteError in Buffer Reduction EfficiencyMean Absolute Error in Buffer Reductions Over 12 Plots0102030405060708090APEX PRZM-BUFF REMM VFSMODModel

Absolute Error (%)RunoffSedimentAtrazineChlorpyrifosPrimary bar represents the mean of 12 trials.Error bars represent min and max of 12 trials.19■Based on previous studies and experience, three sensitive parameterswith higher uncertainty were selected for each model.■Parameter mean values were set equal to the cold run values.■Saturated Conductivity (Ksat): lognormal distribution.■Curve Number (CN): lognormal distribution.■Manning’s N: triangular distribution.■Initial soil moisture (theta): Uniform distribution.Model Sensitivity and Uncertainty:ApproachParameter Value 1st 10th 50th 90th 99thKsat (cm/hr) 0.8 2 5.7 16.7 39.9CN 82 74 61 46 34Manning's N 0.4 0.43 0.47 0.56 0.61Theta (%) 0.01 0.1 0.5 0.9 0.99Parameter Percentile20Results: Atrazine ReductionSensitivity to Ksat/CN, Sheet FlowSensitivity of Atrazine Reduction to Ksat/Curve NumberBlock 1 Treatment 2 (Sheet Flow Conditions)01020304050607080901000 20 40 60 80 100Ksat/CN Percentile

Percent Reduction (%)ObsAPEXPRZM-BUFFREMMVFSMOD21Results: Atrazine ReductionSensitivity to Ksat/CN, Conc. FlowSensitivity of Atrazine Reduction to Ksat/Curve NumberBlock 1 Treatment 4 (Concentrated Flow Conditions)01020304050607080901000 20 40 60 80 100Ksat/CN Percentile

Percent Reduction (%)ObsAPEXPRZM-BUFFREMMVFSMOD22Results: Chlorpyrifos ReductionSensitivity to Manning’s N, Sheet FlowSensitivity of Chlorpyrifos Reduction to Manning's NBlock 1 Treatment 2 (Sheet Flow Conditions)01020304050607080901000 20 40 60 80 100Manning's N Percentile

Percent Reduction (%)ObsAPEXPRZM-BUFFREMMVFSMOD23Results: Chlorpyrifos ReductionSensitivity to Manning’s N, Conc. FlowSensitivity of Chlorpyrifos Reduction to Manning's NBlock 1 Treatment 4 (Concentrated Flow Conditions)01020304050607080901000 20 40 60 80 100Manning's N Percentile

Percent Reduction (%)ObsAPEXPRZM-BUFFREMMVFSMOD24Results: Atrazine ReductionSensitivity to Initial Soil MoistureSensitivity of Atrazine Reduction to Initial Soil MositureBlock 1 Treatment 2 (Sheet Flow Conditions)01020304050607080901000 20 40 60 80 100Initial Soil Mositure Percentile

Percent Reduction (%)ObsAPEXPRZM-BUFFREMMVFSMOD25Results: Chlorpyrifos ReductionSensitivity to Initial Soil MoistureSensitivity of Chlorpyrifos Reduction to Initial Soil MositureBlock 1 Treatment 2 (Sheet Flow Conditions)01020304050607080901000 20 40 60 80 100Initial Soil Mositure Percentile

Percent Reduction (%)ObsAPEXPRZM-BUFFREMMVFSMOD26Results: Chlorpyrifos ReductionDistribution, Sheet FlowCumulative Distribution of Simulated Chlorpyrifos Reduction30:1 Field-to-Buffer Area Ratio, Sheet Flow Conditions01020304050607080901000 20 40 60 80 100Reduction (%)

PercentileObsAPEXPRZM-BUFFREMMVFSMOD■1 observation■20 simulations, Ksat, N, and theta varied concurrently27Results: Chlorpyrifos ReductionDistribution, Concentrated FlowCumulative Distribution of Simulated Chlorpyrifos Reduction30:1 Field-to-Buffer Area Ratio,Concentrated Flow Conditions01020304050607080901000 20 40 60 80 100Reduction (%)

PercentileObsAPEXPRZM-BUFFREMMVFSMOD■1 observation■20 simulations, Ksat, N, and theta varied concurrently28■Criteria: Absolute error in runoff, sediment, and pesticidereduction■Data Points: 73 TotalGibbs Farm: 2 runoff, 2 sediment, 3 pesticideVelbert-Neviges, Germany: 6runoff, 6 sediment, 6 pesticideSioux County, Iowa: 12 runoff, 12 sediment, 24 pesticide■Mean of absolute error calculated for runoff, sediment, andpesticide simulations independentlyResults: Model PerformanceEvaluation29■Mean absolute error in runoff,sediment, and pesticide reductionshown in (%)■Number in parentheses is the standard deviation of theabsolute error in (%)Results: Model PerformanceSummary12.2 (17)30.3 (24)31.0 (31)19.4 (17)Sediment12.3 (9)34.5 (32)36.9 (28)30.4 (20)Runoff8.5 (8)31.2 (31)16.3 (14)15.6 (10)PesticideVSFMODREMMPRZMBUFFAPEXModel30■Encouraging results from this study support the use of these physicallybased models to estimate buffer effectiveness.■The models, as parameterized here, were generally conservative in theirpredictions, especially for events with a high observed removal efficiency.■All four models were much more sensitive to Ksat/curve number ascompared to Manning’s N and initialsoil moisture. The sensitivity toManning’s N and initial soil moisture was less than expected.■Following standard parameter estimation procedures, the average error in% reduction of runoff, sediment, and pesticide for all 4 models rangedbetween 9% and 37%.Summary, Conclusions, andRecommendations31■Funding for this research was provided by the European Crop ProtectionAssociation, Bayer CropScience, Syngenta Crop Protection, andMonsanto Company.■PRZM-BUFF modeling was conducted byAmy Ritter and Mark Cheplickof Waterborne Environmental.■VFSMOD modeling was conducted by George Sabbagh of BayerCropScience.■Addition information on the study datasets was provided by:Gibbs Farm: Richard Lowranceand Randy Williams, USDA/ARSVelbert-Neviges: Christine Klein, SCC Scientific ConsultingSioux County: Nick Poletika, Dow AgroSciencesAcknowledgements