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1. Orchard Emergence date 23 4 Harvest date 18 9 Freezing date 20 10 Legumes Emergence date 10 5 Harvest date 20 8 The selection of crop and management factors is an essential component of the derivation of input parameters FOCUS 2001 For instance crop interception will decrease the amount of pesticides that reach the soil surface and thus ultimately enter the surface water body via runoff or drainage Crop and management input parameters were selected for the PRZM model for each crop in the surface and groundwater scenarios from Bj rnebekk and Syverud Input parameters specific for each crop were e Maximum interception storage of crop Maximum rooting depth of crop Maximum area coverage of canopy Maximum canopy height at maturation date Runoff curve number Dates for sowing emergence maturation and harvest The remaining parameters were constant Parameter selection for each crop was based on local information table 2 the PRZM manual Carsel et al 2006 expert judgements and the FOCUS scenarios from Jokioinen When the selection of the FOCUS scenarios was made Europe was classified in different regions according to precipitation and temperature figure 2 Climate region FOCUS 1 0 5 C lt 400 mm 2 0 5 C gt 400 mm 3 5 10 C lt 400 mm 4 5 10 C gt 400 mm Figure 2 Climate regions based on air temperature and precipitation The average annual air temperature and average an
2. Graph Options z 5 Chemical Display Type Environment Number Display Results Display Results G En CE CE Print Export for Current Graph for 10th tiles ce CMe 2 Ce C F Parent ab ab2 Graph Table er Fel as Text File as Text File Graphical display of leaching concentration ug l at bottom of the core for groundwater scenarios Figure 23 Site specific results The middle panel on right side of the WISPE Grapher allows you to evaluate the results of an individual scenario You can view PRZM output using the options in the Terrestrial section and the Groundwater section of this panel The terrestrial PRZM display options are chemical mass balance Figure 16 or hydrologic balance Figure 17 Chemical mass balance includes the amount of chemical lost each year through microbial degradation uptake by plants leaching below the soil profile volatilization runoff eroded soil and remaining in the soil profile at the end of the year Hydrologic balance includes annual rainfall plus irrigation and the amount of water lost from runoff evapotranspiration and leached below the soil core The Groundwater section allows you to choose between soil pore water concentrations concentration leached either below 1 m Figure 24 or below the bottom of the soil core Figure 25 Figure 26 shows the annual average concentration of leachate at 1 m depth in tabular form 29 Concentration ug l Annual Concentratio
3. r Graph Options Display Results Display Results isplay e Environment Number for Curent Graph fr 1h Ses rane ere Em 1 C Env 2 Erv 3 Pin rot as Text File as Text File C Env 4 C Env 5 OK Cancel gt Figure 21 Tabular display of 10 percentile groundwater concentrations from groundwater scenario comparison ADAM r Chemical Parent Metabl Metab2 07 Examples of scenario comparison for concentrations in leachate are presented in Figure 22 and Figure 23 Leachate concentration is calculated as the sum of advective and dispersive flux of chemical past a specified depth either 1 meter or the bottom of the soil core divided by the water flux at the same depth The ADAM groundwater concentration is calculated daily and averaged for the year Figures 22 and 23 depict the 10 percentile annual average concentration at 1 m depth and at the bottom of the core respectively Leachate concentrations are not calculated for different exposure durations in WISPE Values associated with the figure and a key for interpreting the scenario abbreviation can be obtained by selecting the tabular output in the Display Type menu Scenario Comparison Results Aquatic Leaching Concentration at 1m ug l Chemical Parent Chemical c c 700 T ENE ye a J Groundwater r Leached Below 1m Conc PRZM C Leached Below Core Cone PRZM I Show Top 10 results on
4. ss I Show Top 10 results only 2 i Site Specific Resuks 60 00 5 Norwegian GW BjoneBekk Sprcereal x 3 50 004 Torestiel 40 004 C Mass Balance FRZM C Hydrology Balance PRZM 8 30 004 E A 20 004 Fa 10 004 c ADA 0 C Leached Below 1m Conc PRZM 1365 791 8 6 7 0 2 2B 2 Mian cee me ae Period a A PRZM AFLX DFLXJINFL ys WISPE Norway v 1 00 00 Dec 15 2012 vene Chemical Display Ty Ermironment Number p napley Type Print Oeean for 0 cass ca G Parent C Meibl C Met foh C Tee 1 C c Pm eo Tost Filo Text File E Cc OK Cancel Figure 25 Average annual soil pore water concentration leached below soil core 30 Chemical Parent Chemical Annual Average Leaching Concentration Environment Norway ADAM GW at im r Scenario Comparison Results Aquatic Year Conc ug L Mass g ha Leachate L ha C 385 16 6 57 4 0 32346E 07 C 366 122 438 0 359E 07 et amp 367 58 9 202 0 342E 07 Forks 1968 65 6 183 0 279E 07 c 1988 bl was JE LON C Leached Below 1m Conc PRZM 1970 93 aan 0 443E 07 Leached Below Core Conc PRZM 1971 84 4 202 0 313E 07 1872 80 5 286 0 838 07 I Show Top 10 results only 1973 38 8 139 0 359E 07 3 x 2 Site Specific Results 1974 35 4 519 0 544E 07 1375 44 8 235 0526 07 Norwegian GW BjorneBekk SpiCereal vi 1976 45 180 0 398E 07 Terrestrial 1977 89
5. Holten R Riise G 2009 Norwegian Scenarios Il Final Report from the period 2007 2008 Bioforsk Report Vol 4 Nr 187 2009 ISBN 978 82 17 00597 1 FOCUS 2001 FOCUS Surface Water Scenarios in the EU Evaluation Process under 91 414 EEC Report of the FOCUS Working Group on Surface Water Scenarios EC Document Reference SANCO 4802 2001 rev 2 pp 245 Forum for the Co ordination of Pesticide fate Models and their Use FOCUS 2004 About PRZM URL http viso ei jrc it focus gw models PRZM Verified October 14 2004 Forum for the Co ordination of Pesticide Fate Models and their Use FOCUS 2005 Landscape and Mitigation factors in Aquatic Risk Assessment Volume Detailed Technical Reviews Report of the FOCUS Working Group on Landscape and Mitigation Factors in Ecological Risk Assessment EC Document Reference SANCO 10422 2005 434 pp Gimsing A L Borggaard O K Bang M 2004 Influence of soil composition on adsorption of glyphosate and phosphate by contrasting Danish surface soils European Journal of Soil Science 55 183 191 Haugen Lars Egil 2005 Personal communication Pest Management Regulatory Agency PMRA 2003 Genereal Principles for Performing Aggregate Exposure and Risk Assessments Science Policy Notice SPN2003 04 Health Canada July 28 2003 http www hc sc gc ca cps spc pubs pest pol guide spn2003 04 index eng php Reichenberger S 2005 Field scale risk assessment for diffuse source pes
6. Chemical X Environment China Pond Scenario 1 Pa me m ma sm er em var meet man eon een omr oe oe mm me DE E E a E E E E a E em m m Pesticide Risk Assessment Exposure Simulation Shell v 1 00 Figure 29 RICEWQ mass balance output tabular Hydrologic balance from RICEWQ is similar to that displayed for PRZM Figure 17 EXAMS output can be selected from Aquatic panel near the bottom right of the screen Choose to view either dissolved concentrations in the water column or concentrations in sediment pore water The results appear as a probability graph see example in Figure 18 The ordinate axis Y axis provides the concentration in ug L The abscissa X axis provides an exceedance probability as percentage Each contains the annual maximum series for a specific exposure duration e g instantaneous 96 hr etc The markers or points on the curve correspond to the maximum value for each year of simulation The values on the red vertical line are the upper 10 percentile concentrations depicted in the scenario comparison Figure 14 Tabular output can be 34 selected from the Display Type menu at the bottom of the screen see example in Figure 19 The year associated with each value can be identified by clicking on the Display Results for Current Graph as Text File button at the lower left of the screen Similar results are available for concentrations in sediment por
7. Erosion is a selective process and eroded soil material tends to be lighter in texture and higher in organic carbon compared to field soils The loss of pesticides due to erosion is expressed in PRZM with factors like the MUSS equation and an enrichment ratio for soil organic matter The enrichment ratio is used to account for that eroded soils have a higher content of soil organic matter Carsel et al 2006 Glyphosate sorb strongly to soil minerals and not to organic matter The calculations may therefore lead to discrepancies between predictions and field observations since the model considers the higher content of organic matter in eroded soils Bolli R I et al Bioforsk Report vol 8 nr 172 2013 19 Bioforsk 6 2 4 Sediment loss and dissolved particle bound glyphosate from Bj rnebekk The parameters used for calibration of the Askim site regarding sediment loss and transport of glyphosate to the surface water were also used for the simulations from Bjornebekk since the soil from Askim is quite similar to the soil from Bj rnebekk The sediment data from Bj rnebekk was limited to only turbidity measurements Turbidity is a measure of water clarity i e how much the suspended particles in water decrease the light transmission in the water The more total suspended solids in the water the higher the turbidity Measured values of the amount of suspended solids present are more reliable than turbidity Since there were no data describing
8. PRZM is used for pesticide risk assessments by the U S Environmental Protection Agency s Office of Pesticide Programs USEPA 2007 and for pesticide risk assessment work in Europe and Canada FOCUS 2005 FOCUS 2004 PMRA 2003 WISPE uses Win PRZM version 4 5 April 2009 which is used for pesticide registration in Europe Win PRZM contains parts which is unavailable in the version published by the USEPA such as the Freundlich adsorption isotherm aged sorption and soil moisture dependent degradation RICEWQ The Rice Water Quality Model The RICEWQ model simulates the pesticide mass balance and water management practices in rice paddy environments Williams et al 2008 This part of the WISPE model is not activated for the Norwegian version EXAMS The Exposure Analysis Modeling System The EXAMS model is a chemical fate and transport model combined with a hydraulic model which simulates different processes in aquatic environments Burns et al 2004 For the U S Environmental Protection Agency s Office of Pesticide Programs USEPA 2007 EXAMS is the standard model used for ecological and drinking water pesticide risk assessments ADAM The Aquifer Dilution Assessment Model The ADAM model predicts chemical dilution partitioning and persistence in a shallow unconfined aquifer receiving daily recharge water and chemical flux from PRZM Williams 2010 Water displacement in the aquifer is from recharge and lateral flow Th
9. and leaching below the soil core EXAMS output can be selected from Aquatic panel near the bottom right of the screen Choose between viewing dissolved concentrations in the water column or concentrations in sediment pore water The results appear as a probability graph see example in Figure 18 The ordinate axis Y axis provides the concentration in ug L The abscissa X axis provides an exceedance probability as percentage Each contains the annual maximum series for a specific exposure duration e g instantaneous 96 hr etc The markers or points on a curve correspond to the maximum value for each year of simulation The values on the red vertical line are the upper 10 percentile concentrations depicted in the scenario comparison Figure 14 Tabular output can be selected from the Display Type menu at the bottom of the screen see example in Figure 19 The year associated with each value can be identified by clicking on the button labeled Display Results for Current Graph as Text File at the lower left of the screen 24 r Scenario Comparison Results Aqautic p n 10th tile Dissolved EXAMS Scenario SW _ Cotton _ Jiangsu Nantong Dissolved Cone hate EAE Chemical Chemical X Environment China Pond Scenario 1 Groundwater Conc PRZM y Core Conc PRZM I Show Top 10 results only r Site Specific Results sw Cotton _ Jiangsu Nantong Terrestrial Mas
10. click on the Scenario Generator icon The input generator Figure 6 allows the specification of the necessary input data in six steps 1 Selection of one of the predefined location and crop specific scenarios 2 Definition of the compound specific physical chemical and terrestrial e fate properties and activation of some major processes like foliar application biphasic degradation or aged sorption A separate e fate screen is used for parent and each metabolite max three as well as aged sorption 3 Definition of the compound specific aquatic e fate properties 4 Definition of irrigation drainage schedule 5 Definition of the compound application scenario 6 Creation of the input files in the specified working directory Write Figure 6 WISPE Input Generator All the functions of the WISPE Input Generator can be selected simply by clicking on the specific menu points The scenario e fate and application windows should be closed by clicking on OK All six input steps should be completed in the given consecutive order Scenario E fate Terrestrial E fate Aquatic Irrigation Drainage Application Write to allow everything to work properly WISPE users are expected to be familiar with the use of simulation models for environmental risk assessments in general The creation of the input files should be then self explanatory For the most part the metabolite properties can be defined independently from the parent pro
11. 44 99 1 9 Vereecken Harry 2005 Mobility and leaching of glyphosate a review Pest Management Science 61 1139 1151 Wauchope R D 1978 The pesticide content of surface water draining from agricultural fields J Environ Qual 7 459 472 Williams W M Ritter A M Cheplick J M Zdinak C E 2008 RICEWQ Pesticide Runoff Model for Rice Crops User s Manual and Program Documentation Version 1 7 3 Waterborne Environmental Inc Williams W M 2010 ADAM Aquifer Dilution Advection Model User s Manual and Program Documentation Version 1 12 Waterborne Environmental Inc Bolli R I et al Bioforsk Report vol 8 nr 172 2013 23 Biofbrsk 9 Appendix R WISPE user manual Bolli R I et al Bioforsk Report vol 8 nr 172 2013 24 WISPE USER MANUAL WORLD INTEGRATED SYSTEM FOR PESTICIDE EXPOSURE Version 1 00 00 December 2012 Prepared by J Mark Cheplick Amy M Ritter Megan L White W Martin Williams Waterborne Environmental Inc 897 B Harrison St SE Leesburg VA 20175 USA Disclaimer The user manual includes instructions for surface water and rice scenarios These are not currently available in the WISPE model but will be added in the future Introduction to WISPE The World Integrated System for Pesticide Exposure WISPE was developed to evaluate the potential impact of crop protection chemicals on the environment throughout the world WISPE currently has been configured w
12. C Table bn as Text File as Text File G oO OK Cancel Figure 27 Probability analysis of concentrations in groundwater predicted by Similar results are available for concentrations in sediment pore water using the menu at the lower right of the screen Results for other receiving water environments e g pond or river can be viewed by selecting from the Environment Number menu at the bottom of the screen Evaluation of the RICEWQ EXAMS simulation Scenario comparison results The panel in the upper right of the Grapher program allows you to view a comparison of surface water scenarios by either 10 percentile dissolved concentration or 10 percentile concentration in sediment pore water Figure 14 presents the scenario comparison summary for dissolved concentrations in the aquatic environment Each scenario is represented as a stacked bar and each section of the bar displays the 10 percentile estimated environmental concentration EEC for specific exposure durations including peak 96 hr 21 day 90 day and annual The data can also be displayed in tabular form A scenario legend is contained within the 295 tabular display The selection of graphical or tabular output can be made at the bottom of the Display Type menu at the bottom of the screen Site Specific Results You can evaluate the results of an individual scenario from the middle panel on right side of the WISPE Grapher RICEWQ output is available for viewing a
13. Metab Graph C Table ig ny OG as Test File as Text File Env 4 C Env 5 Print Export OK Cancel Figure 14 Graphical display of dissolved concentrations in the surface water 10th tile EEC s in Surface Water Sediment Pore Water Chemical FOCUS Dummy Chem A r Scenario Comparison Results Aquatic 10th tile Dissolved EXAMS 10th tile Sed Porewater EXAMS PECsw PECsed TOXS WA Groundwater C Gro IT Show Top 10 results only Scenario s F var Peak D tar 96 Hour ff war 210ay Bua sona Mar 90 da Bua Anua PRAESS v 10004 Ma 07 2012 r Site Specific Results DSW Cotton _ Jiangsu Nantong X Tenesta C Mass Balance PRZM Hydrology Balance PRZM Aquatic C Dissolved Conc EXAMS C Sed Porewater Conc EX4MS PECsw PECsed TOXSWA Graph Options Chemical Display Type r Environment Number Display Results Display Results G c C Env 3 for Current Graph for 10th tiles Parent C Metab C Metab2 Graph C Table Ene SEn bas as Text File as Text File C Env 4 Env 5 Print Export OK Cancel Figure 15 Graphical display of sediment pore water concentrations in surface water scenarios SVD Site Specific Results To evaluate the results of an indivi
14. Pesticide Risk Assessment Exposure Simulation Shell v 1 00 r Graph Options Chemical Display Type Display Results Display Results for Current Graph for 10th tiles as Text File as Text File r Environment Number Print Export Parent Metab C Metab Graph C Table DE Or 2 BES ma etab Metab C Ew os eree Figure 20 Graphical display of 10 percentile exposure groundwater concentrations from groundwater scenario comparison ADAM p Scenario Comparison Results 10th tile Groundwater Concntration ug l Aqai Chemical Chemical X 10th tile Dissolved EXAMS 10th tile S rewater EXAMS Instantaneous Hour 21 Day 60 Day 90 N Annual RUN 10 M20084 390 38 387 348 3 174 J RUN ID CTOOEA asmen oasen cessor v48en 0 413E 01 asen Groundwater Pesticide Rist Assessment Exposure Simulation Shell v 1 00 Groundwater Conc ADAM C Leached Below 1m Conc PRZM C Leached Below Core Conc PRZM I Show Top 10 results only r Site Specific Results GW _ Cotton _ Jiangsu Nantong X I r Terestrial Mass Balance PRZM Hydrology Balance PRZM la EWOQ Scenario Key Bie Ea Scenario Emironment PCA Applied Groundwater C Groundwater Conc ADAM Leached Below Im Conc PRAM Leached Below Core Conc PRZM r Aqautic Dissol C Se MS
15. middle panel of the right side of the screen The panel on the right side of the screen contains options for different outputs The top section of the panel allows you to select aquatic or groundwater output The middle 20 panel allows you to select annual results for individual scenarios i e site specific results If individual scenarios are selected the results from all years of simulation are presented The panel at the bottom of the screen switches the view from parent chemical to metabolite The results can be displayed by the Grapher as tables or as graphics All figures can be exported as Windows Meta Files or ASCII files or printed directly To do so simply select the table or graphic and click on Print or Export The tab files may be also used for easy reporting or for further data analysis Evaluation of the PRZM EXAMS simulation Scenario comparison results The panel in the upper right of the Grapher program allows you to view a comparison of surface water scenarios by either 10 percentile dissolved concentration or 10 percentile concentration in sediment pore water Figure 14 presents the scenario comparison summary for dissolved concentrations in the aquatic environment Each scenario is represented as a stacked bar and each section of the bar displays the 10 percentile estimated environmental concentration EEC for specific exposure durations including the peak 96 hr 21 day 90 day and annu
16. recharge water and chemical flux from PRZM Williams 2010 Water displacement in the aquifer is from recharge and lateral flow with lateral flow calculated using Darcy s law The linkage of PRZM to ADAM has been validated to prospective groundwater monitoring studies conducted for pesticide registration in the United States Setup project Chemical properties directory terrestrial environment Add modify Chemical properties standard scenarios aquatic environment Specify simulation W Water management input values rice scenarios Pesticide applications Produce simulation input files PRZM EXAMS Run simulations PRZM ADAM View export results RICEWQ EXAMS Figure 1 WISPE organizational structure Installing and starting the shell WISPE can be installed on any standard PC with a Windows 95 XP Vista or Windows 7 operating system To install the shell follow the instructions given during the set up 6 procedure All required files will be installed automatically in the default installation path CAWISPEN WISPE requires 50 MB hard disk space for the installation plus additional 50 MB for temporary files In very few cases it may be necessary to adjust the automatic installation by following amendment The ASCII file pfdrv ini created during the installation in the directory CAWISPE is also required in the directory C WINDOWS this path is fixed and NOT dependant on the Windows insta
17. som ofte er karakterisert av frossen jord frysing tining og stor overflateavrenning under sn smeltingen Eklo et al 2008 Eklo et al 2009 Bolli et al 2011 Glyfosat kan tapes i b de l st og partikul r form Tidspunkt og intensitet av nedb rsepisoder i forhold til spr ytetidspunktet er av stor betydning for hvordan plantevernmidlene transporteres Det var god tilpassing mellom total mengde l st glyfosat 34 mg og de observerte verdiene 24 mg Simuleringen viste at modellen hadde problemer med tidspunktet for avrenningen noe som kan skyldes at daglige verdier blir brukt i klimafilen Modellen overestimerte avrenningen av partikkelbundet glyfosat Erosjon er en selektiv prosess og erodert jord best r ofte av mindre partikler og et h yere innhold av organisk karbon Adsorpsjon av glyfosat skjer hovedsakelig til mineraldelen av jorda og ikke til organisk materiale Siden erodert jord ofte har et h yere innhold av organisk karbon enn utgangsmaterialet bruker PRZM en faktor enrichment ratio for ta hensyn til dette i beregningene av mengde partikkelbundet glyfosat noe som kan gi et avvik mellom simulerte og observerte verdier Jordegenskapene for Askim er ganske lik jorda p Bj rnebekk og derfor ble parameterne som ble brukt for kalibrering av jordtapet p Askim ogs brukt for Bj rnebekk Simuleringene viste at de kumulative predikerte verdiene var h ye sammenlignet med de beregnede observerte verdiene henholdsvis 91 kg og 3 k
18. tab These files can be used for further data analysis About the models The following simulation models have been incorporated into WISPE PRZM The Pesticide Root Zone Model PRZM is a dynamic compartmental model for use in simulating water and chemical movement in unsaturated soil systems within and below the plant root zone Su rez 2005 PRZM is the standard model used for ecological and drinking water risk assessments for pesticides by the U S Environmental Protection Agency s Office of Pesticide Programs USEPA 2004 and has been integrated into pesticide risk assessment procedures in Europe and Canada FOCUS 2005 FOCUS 2004 PMRA 2003 PRZM simulates time varying hydrologic behavior on a daily time step including physical processes of runoff infiltration erosion and evapotranspiration The chemical transport component of PRZM calculates pesticide uptake by plants surface runoff erosion decay vertical movement foliar loss dispersion and retardation PRZM includes the ability to simulate metabolites irrigation and hydraulic transport below the root zone WISPE utilizes Win PRZM version 4 5 April 2009 which is supported for pesticide registration in Europe and contains features unavailable in the version distributed by the U S Environmental Protection Agency including Freundlich adsorption isotherm aged sorption and soil moisture dependent degradation RICEWQ The Rice Water Quality RICEWQ model simulates
19. the amount of suspended solids from Bjornebekk data from Askim was used to calculate the amount of suspended solids in the surface water The simulation indicated high values compared to the calculated values 91 kg and 3 kg respectively This exercise confirms that the transfer of data from one site to another is not recommended as the properties of soil and topography strongly influence the model simulations Thus the model has to be calibrated with the field properties soil topography etc that are found at each site pers comm Cheplick 2013 Based on this experience Syverud was not calibrated as values for suspended solids were lacking and the soil properties were different compared to Askim Bolli R I et al Bioforsk Report vol 8 nr 172 2013 20 Biofbrsk 7 Conclusion Pesticide losses from agricultural fields can pose a significant threat to water bodies and one has seen the need for tools which can predict the exposure of pesticides in both surface and groundwater WISPE is a computer modelling tool developed to evaluate the potential for pesticides to occur in aquatic environments The model has been extended to eleven different crops taking into consideration the effect of the climate on the plant growth development including sowing emergence and harvest WISPE has been extended with EXAMS which is the U S standard model used as an aquatic fate model to calculate the PEC values of pesticide discharge into a standa
20. tipping bucket system were collected from both surface and drainage water figure 4 The sampling frequency varied from one to five weeks depending on volume of runoff Analyses of glyphosate and AMPA were conducted at Bioforsk Plant Health and Plant Protection Measurements of suspended solids SS and turbidity was done by the Norwegian University of Life Sciences Stenr d et al 2007 Experimental plot Sampling house Drainage water Figure 4 Illustration of the sampling of water proportional samples Source Riise et al 2012 6 1 3 Model and parameter estimation PRZM was used for calibration of sediment loss and particle bound pesticides from the experimental fields A detailed description of PRZM can be achieved from the manual Carsel et al 2006 and from earlier reports Eklo et al 2008 Eklo et al 2009 and Bolli et al 2011 The parameter estimation was performed at two stages an uncalibrated simulation followed by a simulation with calibration using the sensitive parameters The hydrology module is always calibrated first and the pesticide module last This is important as water is the carrier of pesticides through the soil Knowledge of the water flow is therefore a prerequisite of a valid description of the movement of pesticides in soil This is a suggested procedure of Good Modelling Practice GMP obtained in the Cost Action 66 project Vanclooster et al 2000 There were three main sources for the paramet
21. 110000000000000000000 330 QIBTS 25 000 us CROP Tier 2 0000000000000000 0000000000000000000 331 QTBAS 2 000 8 CROP Tier 2 00000000000000000000000000000000000000000000000000 332 KPHT 0 000 9 CROP Tier 2 00000000000000000000000000000000000000000000000000 333 OF HYDROL 3 10 REGION 00000000000 334 HYDROL TEMP 25 000 11 CROP MUSCRAT 1 335 HYDROLYSIS C1 0 00 0 00 0 00 12 CHEMICAL 11 0010103100 336 PH HYDROL Ci 0 00 0 00 0 00 13 MANAGEMENT PRAC 000 337 MELT PT 99 000 14 Chemical Name Parent Chemical 338 RICENQ DATA 15 Molecular Wgt 0 000 339 RCQMET1 0 000 16 Plant Upt Fet 0 500 340 RCQMET2 0 000 17 Part Cff Mth 1 341 ADAM DATA 18 Part Cff Fct 0 000 342 Part Cff Mth 1 19 Freund Exp 0 900 343 Part Coeff 0 000 20 Vapor Pres 0 0000E 00 344 ADMMET 0 000 21 Solubility 0 1000E 03 345 OF RICEWQ o 22 Degr PH1 L 0 000 23 Degr PH1 S 0 000 24 Degr PH1 52 0 000 25 Degr PH2 0 000 26 Degr PH1 0 000 0 000 0 000 27 Degr PH2 0 000 0 000 0 000 28 Bi Phase o 29 Q10 FAC 2 580 30 Q10 Temp 20 000 31 Moisture Exp 0 700 32 Moisture Cnt 100 000 33 Moisture Type 2 999 999 34 Foliar 1 2 0 000 35 Foliar Wash 0 000 36 MLT APPLICATION 2 37 APPLICATION 1121 0 38 Days Rel 1 39 Month 999 40 CAM 1 41 Depi 4 000 42 Rate 1 0000 43 PCAs 100 000 44 Drift 0 000 45 Eff 100 000 The information Figure 4 Example of the Master Project File included in the Master Project Fil
22. 5 884 0 742E 07 C Mass Balance PRZM 1978 318 215 06776407 2 Hydrology Balance PRZM 1979 49 2 199 0 404E 07 ch g 1980 40 6 210 O 517E 07 Groundwater 1981 74 8 351 0 488 07 1982 107 516 0 484 07 San ace TA STENA Leached Below 1m Conc PRZM eis z Leached Below Core Conc PRZM 384 56 0 350 0 625E 07 1985 24 0 152 0 446E 07 1986 121 486 0 401E 07 Bae 1987 71 6 220 0 308E 07 c 988 78 4 344 0 450E 07 c c 988 84 7 571 0 674E 07 1990 602 0 847E 07 WISPE No 1 00 00 Dee Graph Options Chemical Display Type Environment Number Display Results Display Results Gent C Print Export for Current Graph for 10th tiles Parent C M 2 C Graph Table BY as Text File as Text File c OK Cancel Figure 26 Tabular display of annual average leaching concentrations at 1 m Groundwater concentrations predicted by ADAM are also available from this menu The results appear as a probability graph Figure 27 The ordinate axis Y axis provides the concentration in ug L The abscissa X axis provides an exceedance probability as percentage Each contains the annual maximum series for a specific exposure duration e g instantaneous 96 hr etc The markers or points on the curve correspond to the maximum value for each year of simulation The values on the red vertical line are the upper 10 percentile concentrations depicted in the scenario comparison Figure 20 and Figure 21 Tabular output can be selected from the Di
23. Biorsk Bioforsk Rapport Bioforsk Report Vol 8 Nr 172 2013 National Scenarios Norway Development of WISPE for surface and groundwater modelling of pesticides in major crops Randi Iren Bolli Ole Martin Eklo Roger Holten Paulien Mulder Bioforsk Plant Health and Plant Protection Division Norwegian Food Safety Authority www bioforsk no Biofbrsk Head office Bioforsk Frederik A Dahls vei 20 Plant Health and Plant Protection N 1430 As Division Tel 47 40 60 41 00 H gskoleveien 7 amp B IO Orsk post bioforsk no Lee ee 40 60 41 00 plantehelse bioforsk no Title National Scenarios Norway Development of WISPE for surface and groundwater modelling of pesticides in major crops Author s Randi Iren Bolli Ole Martin Eklo Roger Holten Paulien Mulder Date Availability Project No Archive No 16 12 2013 Open 1110330 2007 118 Report No ISBN no Number of pages Number of appendices 8 172 2013 978 82 17 01184 2 61 1 Employer Contact person Norwegian Food Safety Authority Roger Holten Keywords Field of work WISPE pesticides modelling national scenarios Pesticide fate Sammendrag Dette arbeidet er en videref ring av prosjektet Norske Scenarier Form let med prosjektet var inkludere de mest utbredte jordbrukskulturene til modellverkt yet WISPE utvide modellen med en funksjon som beregner eksponering av plant
24. Master Project File View results of PRZM EXAMS View simulation s Figure 3 WISPE shell giving different options for use of the Master Project File It should be noted that the Master Project File contains all parameter information necessary to characterize a complete WISPE run The MPF can be easily used to exchange simulation scenarios between different persons or bodies involved A MPF from a different source only needs to be copied to a path that is valid to be used as an active working directory By employing the MPF it is possible to validate and re create each scenario compound and application specific model input used to generate a particular scenario Format of the Master Project File The definition of the scenario compound and application specific parameters is done by corresponding to the formats used in the PRZM parameter file inp A typical example for a Master Project File is given below in Figure 4 The depicted Master Project File was created for a parent compound a single application scenario modified bio degradation factors biphasic degradation aged sorption and multiple flood drain events MASTER FPI al Project File Created 2012 12 12 9 3 22 325 EXAMS DATA 03 22 1 2 WISPE Norway v 1 00 00 Dec 15 2012 326 AERMET 0 000 3 Parent Compound Parent Chemical 327 QIBIw 25 000 4 GROUP 1 allscenl grp 328 QTBAW 2 000 5 SCENARIO TYPE 300111 329 ANAERM 0 000 6 CROP Tier 2 11 1 1
25. Root and Unsaturated Soil Zones Users Manual for Release 3 12 2 EPA 600 R 05 111 U S Environmental Protection Agency Office of Research and Development Center for Exposure Assessment Modeling CEAM National Exposure Research Laboratory Ecosystems Research Division U S Environmental Protection Agency USEPA 2007 Water Exposure Models Used by the Office of Pesticide Programs Science and Policy Updated on Wednesday October 10 2007 http Awww epa gov oppefed1 models water models4 htm Jackson S H P Henley and J M Cheplick 2007 PLUS A Regional Groundwater Assessment and Ranking Tool J Agric Food Chem 2007 55 14 5408 5415 35 MED Rice 2003 Guidance document for the environmental risk assessments of active substances used on rice in the EU for Annex inclusion Document prepared by working group on MED Rice EU document reference SANCO 1090 2000 rev 1 Brussels June 2003 108 pp Ritter A M W M Williams J Tang T S Ramanarayanan D Desmarteau and S Anderson 2010 Comparison of aquatic exposure assessment models for pesticide use on rice SCI International Conference Pesticide Behavior in Soils Water and Air September 14 16 2009 York U K Williams W M 2010 ADAM Aquifer Dilution Advection Model User s Manual and Program Documentation Version 1 12 Waterborne Environmental Inc Williams W M A M Ritter J M Cheplick and C E Zdinak 2008 RICEWQ Pesticide Runoff Mode
26. al Figure 15 shows the 10 percentile estimated environmental concentrations in sediment pore water for each scenario and exposure duration The corresponding data can be displayed in tabular form A scenario legend is contained within the tabular display The selection of graphical or tabular output can be made at the bottom of the Display Type menu at the bottom of the screen 21 10th tile EEC s in Surface Water Dissolved Chgmical FOCUS Dummy Chem A 7000 004 6000 004 ppb 000 004 lon 4000 00 4 oo 000 004 Concentrat 2000 00 4 1000 004 0 Scenario s var Peat E Wax 96 Hour H ma 2i0ay H masona max 90 Day ua Anna PRAESS v 1 00 04 Ma 07 2012 r Scenario Comparison Results Aquatic 10th tile Dissolved EXAMS 10th tile Sed Porewater EXAMS PECsw PECsed TO I Groundwater CG j PRZM I Show Top 10 results only r Site Specific Results DSW _Cotton _ Jiangsu Nantong r Terrestrial C Mass Balance PRZM Hydrology Balance PRZM Aquatic Dissolved Cone EXAMS Sed Porewater Conc EXAMS C PECsw PECsed TOXSWA Graph Options Chemical r Display Type Environment Number Display Results Display Results G Env 1 C Env 2 Env for Cunent Graph for 10th tles Parent C Metab C
27. days 50000 00000 Degradation Non Eq Sorbed Phase days 5 0000 0 0000 m Stepwise Chemical 1 Chemical 2 NOTE Days C1 C2 C3 refers to the number of days after an application The first set of parameters will always be Days 0 Factor 1 0 r Bi Phase Degradation Simulate Bi Phase Degradation Chemical 1 Chemical 2 Chemical 3 Degradation Rate Phase 2 0 0000 0 0000 0 0000 Days after Initial Rate Figure 9 Definition of aged sorption and biphasic degradation parameters 16 Aquatic Efate Input Parameters I Override database values for RICEWOQ water management Chemical 1 Chemical 2 Chemical 3 Pathways m Half lifes m Bacterial Biolysis in Water Column Bacterial Biolysis in Benthic Sediment EXAMS Aerobic Metabolism days 30 00 EXAMS Anaerobic Metabolism days 60 00 RICEWG Aerobic Metabolism days 30 00 RICEWO Anaerobic Metabolism days 60 00 010 Base Temperature C 25 000 Q10 Base Temperature C 25 000 010 value 2 000 Q10 value 2 000 Hydrolysis Test Temperature C 25 00 Number of Tested pH s 3 X Team Hate or ow om 2 om om s om om Direct Photolysis days 0 00 Note Molecular weight solubility Koc Kd previously 99 000 entered on terrestrial efate screen are also used aqautic environment Melting Point C Figure 10 Definition o
28. describing the amount of suspended solids from Bj rnebekk and Syverud data from Askim was used to calculate the amount of suspended solids in surface water using turbidity measurements from the other sites Information about Bj rnebekk and Syverud are thoroughly described in earlier reports Eklo et al 2008 Eklo et al 2009 and Bolli et al 2011 The field experiment at Askim was conducted by the Norwegian University of Life Sciences Stenr d et al 2007 6 1 1 Field description Runoff of the pesticide glyphosate and its metabolite AMPA aminomethylphosphonic acid has been investigated in plot studies in an agricultural field at Askim The field was artificially levelled tile drained and established in 1986 The experimental plots are 26 m long and 6 2 m wide with a slope of 13 figure 3 The soil is a silty clay loam with a low content of organic carbon poor aggregate stability and high erodibility Stenr d et al 2007 k Figure 3 The experimental field at Askim Source Riise et al 2012 Bolli R I et al Bioforsk Report vol 8 nr 172 2013 14 Biofbrsk 6 1 2 Treatment of sites sampling procedure and analysis The plots at Askim were subject to autumn ploughing and spring ploughing All plots were subject to harrowing in spring The pesticide glyphosate were applied in September and the tracer kaliumbromide KBr was applied at the same time to follow the transport of water Water proportional samples with a
29. dual scenario use the controls on the middle panel on right side of the WISPE Grapher Example output from PRZM is available for viewing under the Terrestrial Section of this panel Select either chemical mass balance Figure 16 or hydrologic balance Figure 17 r Scenario Comparison Results r Aquatic 8 C tot Annual Mass Balance at Bottom of Soil Core aie a e G C PE Scenario Norwegian GW BjorneBekk SprCereal Chemical Parent Chemical Environment Norway ADAM GW Env 1 Groundwater G ate 24004 i eee C Leached Below Im Cone PRZM 2200 Leached Below Core Cone PRZM 20005 I Show Top 10 results only 18004 16004 Site Specific Results 14004 Nonwegian GW BjorneBekk SprCereal v a 12004 Terrestrial 8 10004 Mass Balance PRZM Hydrology Balance PRZM 800 4 C Mass Balance If 6004 CH 4004 Groundwater 2004 E adwatet I i 0 C Leached Below 1m Cone PRZM 1 p 7 9 11 8 15 17 19 4 2 2 C Leached Below Core Conc PRZM Period ENES C G rewate Bl Decayed ff Uptake ff Leaches Remaining J Runoff f Volatilized fj Erode c c WISPE Norway v 1 00 00 Dec 152012 Graph Options eee NEE Chemical gt r Display T nvironment Number Display Results Display Results sais rp a e c a Print Export for Curent Graph for 10th Ztiles Parent C Metab C Meta G Graph C Table Bee 1 as Text File as Text File CE CE OK Cancel i Figure 16 Chemical mass bala
30. e connection between PRZM and ADAM has been validated to groundwater monitoring studies conducted for pesticide registration in the United States WISPE has had some changes since the User Manual was made in December 2012 Cheplick et al 2012 One of the changes is the Scenario Manager which allows us to implement our own scenarios into the WISPE software This is a very useful tool which makes us capable to do this work ourselves in an easy way Waterborne Environmental Inc has included the Norwegian surface and groundwater scenarios from Bj rnebekk and Syverud Eklo et al 2008 Eklo et al 2009 Bolli et al 2011 into WISPE which makes it possible to do pesticide exposure assessments in surface and groundwater resources considering Norwegian conditions A part of this project was to include the major crops into WISPE to make it more representative for Norway The crop Bolli R I et al Bioforsk Report vol 8 nr 172 2013 7 Biofbrsk grown at each scenario and the practices used to manage the soil contribute to a potential exposure of pesticides to surface water bodies The size of the crop canopy influences the amount of pesticides reaching the soil and the depth and distribution of root systems together with soil management practices affect the soil water balance and therefore indirectly the amount of runoff and drain flow FOCUS 2001 The major transport pathway for soil particles and particle bound pesticides is surface ru
31. e contribution of runoff and TOXSWA for the estimation of the final predicted environmental concentration PEC in surface waters FOCUS 2001 TOXSWA TOXic substances in Surface Waters is an aquatic fate model and does not simulate the drainage or runoff erosion processes itself but uses the fluxes calculated by other models as entries into the water body system TOXSWA uses these output files as input to calculate exposure in water and in sediment at the downstream end of a ditch stream or pond neighboring a treated field TOXSWA considers the transport processes advection dispersion transformation hydrolysis photolysis biodegradation sorption and volatilization figure 1 FOCUS 2001 FOCUS Pond scena rio Eroded sediment pesticide Pond outflow input from a 20 m contributing regulated by a broad margin along one side of pond FOCUS Ditch Scenariocresied weir with a runoff scenarios only 5 height of 1 0 m FOCUS Stream Scenario Minimum water depth of 0 3 m maintained by a weir Eroded sediment pesticide input from a 1 ha field treated with pesticide Input from drainage or runoff Minimum water depth of 0 3 m maintained by a weir contributing margin along stream runoff scenarios only Figure 1 Conceptual outline of the FOCUS surface water bodies FOCUS 2001 Bolli R I et al Bioforsk Report vol 8 nr 172 2013 9 Biofbrsk Because of problems with coupling WISPE a
32. e further investigated to give increased knowledge on the behaviour of glyphosate in a soil sediment water system Bolli R I et al Bioforsk Report vol 8 nr 172 2013 21 Biofbrsk 8 References Bolli R I Haraldsen T Haugen L E Holten R Eklo O M 2011 National Scenarios Norway Introduction of national scenarios for approval of new pesticides in Norway Bioforsk Report Vol 6 Nr 34 2011 ISNB 978 82 17 00764 7 Burns Lawrence 2004 Exposure Analysis Modeling System EXAMS User manual and system documentation Version 2 98 04 06 EPA 600 R 00 081 Ecologist Ecosystems Research Division U S Environmental Protection Agency Athens GA 197 pp Carsel R F Imhoff J C Hummel P R et al 2006 PRZM 3 A Model for Predicting Pesticide and Nitrogen Fate in the Crop Root and Unsaturated Soil Zones Users Manual for Release 3 12 2 U S EPA Athens GA 30605 2700 Cheplick J M Ritter A M White M L Williams W M 2012 WISPE User Manual World Integrated System for Pesticide Exposure Waterborne Environmental Inc USA Cheplick Mark 2013 Personal communication Eklo O M Almvik M Bolli R I Haraldsen T Haugen L E Holten R Lundekvam H Riise G Stenr d M Tveit C W 2008 Norske Scenarier Il Sluttrapport for prosjektperioden 2005 2006 Bioforsk Rapport Vol 3 Nr 11 2008 ISBN 978 82 17 00325 0 Eklo O M Almvik M Bolli R I B rresen T Haraldsen T Haugen L E
33. e is complete but minimized with regard to the FOCUS default settings Information about metabolites aging factors or modified biodegradation factors are only included if relevant The following information is coded in the individual lines of the Master Project File Line 1 Line 2 Line 3 Line 4 Line 5 Line 6 9 Line 10 Line 11 Line 12 Line 13 Line 14 35 Line 36 99 Line 100 102 Line 103 115 Line 116 118 Line 119 122 Line 123 124 Date on which the file was created by WISPE Version of WISPE Name of the parent compound Identification of Group File Scenario type 3 Standard Tier II Index of selected scenarios 1 used 0 not used for the simulation Region Crop Rotation 1 no crop rotation 26 year met file Relationship between parent and metabolites e g 2 parent with metabolite Management practice Chemical properties parent and metabolites Application scenario here six applications relative to emergence Aging factors for parent and metabolites EXAMS input RICEWQ input ADAM input Number of RICEWQ events 10 Line 125 143 Drainage events Scenario Manager The Scenario Manager seen in Figure 5 allows the maintenance of conducted scenarios You can enter an identifier or short help text as annotation for each conducted scenario It is also possible to delete individual project directories Scenario Manager Chem Name Status Location Tyre Date C
34. e run the groundwater scenario comparison menu can be made active by selecting any available groundwater scenario in the pull down menu under Site specific Comparisons in the middle section on the right of the screen An example scenario comparison of groundwater concentrations is presented in Figures 20 and 21 These figures display the 10 percentile peak 96 hr 21 day 90 day and annual groundwater concentration calculated from ADAM The Display Type menu at the bottom of the screen allows you to switch between graphical Figure 22 and tabular Figure 21 displays The tabular output includes a key for interpreting the scenario abbreviation that is displayed at the bottom of the graph in Figure 21 26 r Scenario Comparison Results Aqautic 10th tile Di 10th tile 5 Groundwater Concentration ug l Chemical Chemical X IZM 3504 J Leached Below Core Conc PRZM Q IOW results onl 2 I Show Top 10 results only amp 3004 J 250 Site Specific Results T i GW _ Cotton _ Jiangsu Nantong v 2 004 Terrestrial oO C Mass Balance PRZM 5 150 4 ai Hydrology Balance PRZM oO Mass B RICEWO 1 004 RICEWOQ Groundwater Groundwater Conc ADAM Leached Below 1m Cone PRZM Leached Below Core Cone PRZM Aqautic Disso Scenario s Fe BP vape ff Max 96 Hour ff wax 2t0ay ff Masona M ma 90 day mar Annual
35. e water using the menu at the lower right of the screen Results for other receiving water environments e g pond or river can be viewed by selecting from the Environment Number menu at the bottom of the screen Program exit Exit the WISPE Tool by clicking on the x button in the upper right hand corner of the starting screen References Burns Lawrence 2004 Exposure Analysis Modeling System EXAMS User manual and system documentation Version 2 98 04 06 EPA 600 R 00 081 Ecologist Ecosystems Research Division U S Environmental Protection Agency Athens GA 197 pp Forum for the Co ordination of Pesticide Fate Models and their Use FOCUS 2005 Landscape and Mitigation Factors in Aquatic Risk Assessment Volume Detailed Technical Reviews Report of the FOCUS Working Group on Landscape and Mitigation Factors in Ecological Risk Assessment EC Document Reference SANCO 10422 2005 434 pp Forum for the Co ordination of Pesticide Fate Models and their Use FOCUS 2004 About PRZM URL http viso ei jrc it focus gw models PRZM Verified October 14 2004 Pest Management Regulatory Agency PMRA 2003 General Principles for Performing Aggregate Exposure and Risk Assessments Science Policy Notice SPN2003 04 Health Canada July 28 2003 http Avww hc sc gc ca cps spc pubs pest _pol guide spn2003 04 index eng php Suarez L 2005 PRZM 3 a Model for Predicting Pesticide and Nitrogen Fate in the Crop
36. eeeeeeeeeeeeeees 16 62 1 Sut ace Water Lassa vid wacisectversiesivecdiveesaseiinivecieveaxavess 16 6 2 2 Sediment l SS suavveasvasseaemreauroaask rand eder 16 6 2 3 Dissolved and particle bound glyphosate in surface water awvnnnanvnvner 17 6 2 4 Sediment loss and dissolved particle bound glyphosate from Bj rnebekk 20 COMGUIGION SEERE EE EE NE 21 REGLENE eek diddd des 22 9 APPENA susen badene e dan 24 Bolli R I et al Bioforsk Report vol 8 nr 172 2013 4 Biofbrsk 1 Summary Waterborne Environmental Inc has together with Bioforsk as an assignment from the Norwegian Food Safety Authorities developed the risk assessment tool WISPE The World Integrated System for Pesticide Exposure which includes several environmental fate and transport models WISPE is a computer modelling tool developed to evaluate the potential for pesticides to occur in aquatic environments The scenarios Bj rnebekk and Syverud are included in WISPE which makes it possible to estimate pesticide exposure in surface and groundwater resources considering Norwegian conditions The first sub goal has been to include an aquatic fate model into WISPE to predict exposure to aquatic living organisms WISPE has been extended with EXAMS The Exposure Analysis Modeling System which is the U S standard model used to calculate the PEC predicted environmental concentrations values of pesticide discharge into a standard water body pond ditch or stream T
37. er estimations measurements or calculation based on measurements the PRZM manual other literature sources and expert judgement Bolli R I et al Bioforsk Report vol 8 nr 172 2013 15 Biofbrsk 6 2 Results and discussion from the model simulations Measurements of water flow from both the drainage system and surface runoff were measured at the plot For calibration of sediment loss and particle bound pesticides only data from surface runoff were used 6 2 1 Surface water Various strategies were attempted in order to get a good adaption of the runoff figure 5 The parameter which had the biggest influence on the water flow was the rainfall intensity 80 FG e Simulated 0G Observed o E60 50 5 40 Y 30 20 10 Aug 06 Sep 06 Oct 06 Nov 06 Dec 06 Jan 07 Feb 07 Mar 07 Apr 07 Figure 5 Cumulative calibrated simulation of surface water at Askim 2006 2007 The difference between the total amount of simulated water and observed values were about 25 According to Resseler et al 1996 a satisfactory simulation occurs when the difference between the simulated and observed amount of water do not exceed 25 during a year Reichenberger 2005 did some considerations about the acceptability limit for the deviation between simulated and measured values and according to this surface runoff was set to a factor of 10 PRZM predicts the surface water flow adequately but there were some problem
38. evernmidler til ulike vannmilj og kalibrere modellen med hensyn p transport av partikler og partikkelbundne plantevernmidler Prosjektet har v rt et samarbeid mellom Bioforsk Plantehelse Waterborne Environmental Inc og Mattilsynet Summary This work is a continuation of the project Norwegian Scenarios The aim of this project was to include the major crops in Norway to the model tool WISPE to extend the model with an aquatic fate model and to make a better model adaption regarding transport of soil particles and particle bound pesticides This project has been a cooperation between Bioforsk Plant Health and Plant Protection Division Waterborne Environmental Inc and Norwegian Food Safety Authority Approved Project leader Lie Holen Ok Mati Cte Borge Holen Ole Martin Eklo Preface This project has been a cooperation between Bioforsk Plant Health and Plant Protection Division Waterborne Environmental Inc and Norwegian Food Safety Authority The project has been carried out as an assignment from the Norwegian Food Safety Authority The aim of the project was to include the major crops in Norway into the scenarios from Bj rnebekk and Syverud to the model tool WISPE to extend the model with an aquatic fate model EXAMS and to make a better model adaption regarding transport of soil particles and particle bound pesticides Bioforsk Plant Health and Plant Protection Division have been responsible for the coordinati
39. f aquatic e fate parameters 247 sten X Select Current Scenario wE Current Scenario and Status 1 Norwegian GW BjorneBekk SprCereal Total Number of Scenario 3 Total Unmodified Scenario 31 Environments Associated with Selected Scenario C ee bin ene Fa Application Inputs Number of Applications 3 Application Timing Relative to Emergence v Application Units Application Type Aerial Spray vi C oana oo Moth CAM Inco ton Pee ooy Cuert Appeaion Parameters to ait 1 1 0 100 A Scenaos Help CAM Definitions OK Cancel Figure 11 Definition of the application parameters After all the scenarios e fate and application data have been specified the input files have to be written in the project directory by clicking on the Write button A click on Exit will close the WISPE Input Generator and return you to the WISPE starting screen Handling of degradation rates in WISPE For ease in specifying degradation rates the degradation kinetics is specified in the new PRZM 3 21 differently than in the former DOS versions of PRZM WISPE will automatically do the necessary calculations to produce the parameters as required in the PRZM 3 21 input file according to the User Input Each compound to be used in the simulation scenario must be characterized by the total first order degradation half life regardless of whether the d
40. from the Askim field were used together with results for dissolved glyphosate and Kd to calculate the amount of particle bound glyphosate The model simulates too much loss of particle bound glyphosate according to the calculated values figure 10 It is difficult to decide whether the calculations of particle bound glyphosate is better than the simulations or not due to inaccurate Kd values v 100 e Simulated 3 Observed fe a gt on zm SE a v U D Cj a vo oo oO o OD N NN OR o 0909 9 v a 22 gt c A S amp 3 Yy OO WO 63 a lt AS 5 2453 Pez a Figure 10 Calibrated simulation of particle bound glyphosate in surface water at Askim 2006 2007 Stenr d et al 2007 documents that the transport of glyphosate is closely connected to the transport of soil particles Adsorption of glyphosate is mainly governed by the mineral phase of the soil matrix especially aluminium and iron oxides Soil organic matter seems to play an indirect role Vereecken 2005 The soil pH determines the electrical charge of glyphosate and therefore its adsorption on the mineral phase Gimsing et al 2004 found through several experiments that the soil s pH strongly influenced the adsorption of glyphosate The soil pH is not added into the model as a separate parameter but is indirectly taken into account in the Kd value since the pH for many pesticides influences the sorption
41. g Disse simuleringene har bekreftet at overf ring av data fra et sted til et annet ikke er anbefale siden jordegenskapene og topografien p virker modellsimuleringene Modellen m derfor kalibreres med data for hvert enkelt felt pers med Cheplick 2013 Bolli R I et al Bioforsk Report vol 8 nr 172 2013 6 Biofbrsk 3 Introduction The contamination of surface water bodies with agricultural pesticides can pose a significant threat to aquatic ecosystems and has increased the need for tools which can predict the behaviour of chemicals entering the environment Such a tool is The World Integrated System for Pesticide Exposure WISPE which is a modelling platform designed to evaluate the potential for pesticides to occur in surface and groundwater resources The structure of the model allows seamless executions of several environmental fate and transport models in the Windows environment and it also has the flexibility for the user to create update and maintain databases on pesticides environmental fate properties and exposure scenarios Cheplick et al 2012 The following simulation models have been implemented into WISPE PRZM Pesticide Root Zone Model Surface and groundwater scenarios for different crops require simulations of PRZM for the terrestrial field PRZM is a dynamic compartment model which can be used to simulate chemical movement in unsaturated soil systems within and below the root zone Carsel et al 2006
42. gian scenarios from Bj rnebekk and Syverud have been calibrated for spring barley which is one of the most common crops in Norway An important part of this project was to implement other major crops into WISPE to make it more relevant for Norway Table 2 shows the most widespread crops in Norway with dates for sowing emergence and harvest The collection of data regarding plant growth development for the main crops were received from the Norwegian Agricultural Extension Service department Hedmark potatoes onion SouthEast cereals oilseed legumes and Viken vegetables fruit berries Eklo et al 2008 Table 2 An overview over the main crops in Norway Cereals winter Sowing date 8 9 Emergence date 15 9 Harvest date 15 8 Spring oilseed Sowing date 1 5 Emergence date 10 5 Harvest date 4 9 Potatoes Sowing date 20 5 Emergence date 10 6 Harvest date 20 9 Vegetables root Carrots Sowing date 10 5 Emergence date 25 5 Harvest date 5 10 Vegetables leafy Cabbage Sowing date 15 5 Emergence date 30 5 Harvest date 15 9 Vegetables bulb Onions Sowing date 28 4 Emergence date 17 5 Harvest date 28 8 Strawberries Emergence date 23 4 Harvest date 8 7 Freezing date 20 10 Bush berries Emergence date 23 4 Harvest date 15 8 Freezing date 20 10 Bolli R I et al Bioforsk Report vol 8 nr 172 2013 11 Biofbrsk
43. his is similar to TOXSWA TOXic substances in Surface Waters which is a part of the FOCUS surface water exposure assessment The second sub goal has been to extend the model to major crops in Norway taking into consideration the effect of the climate on the plant growth development including sowing emergence and harvest The third sub goal was to calibrate PRZM Pesticide Root Zone Model according to transport of particles and particle bound pesticides especially glyphosate with existing field data PRZM simulates the amount of surface water and soil loss from the Askim field adequately and the results are within the acceptability limit for the deviation between simulated and observed values Similar to earlier simulations with PRZM also here there were problems in periods characterized by frozen soil freezing and thawing cycles and high surface runoff during snowmelt events Eklo et al 2008 Eklo et al 2009 Bolli et al 2011 Glyphosate can be transported into water bodies both as dissolved and bound to particles Pesticide losses in surface runoff are event driven and therefore very strongly dependent on the weather conditions especially rainfall immediately after application There was a good correlation between the total simulated amount of dissolved glyphosate 34 mg and the observed values 24 mg The simulation indicated that the model did not time the runoff events well which can be related to the daily resolution of
44. iangsu Nantong Ea Terrestrial Mass Balance PRZM Hydrology Balance PRZM e RICEWOQ Pesticide Rist assessment Exposure Simulation Shell 1 00 Chemical r Display Type Environment Number G Env 1 C Env 2 En 3 Pit Emo Graph Options Display Results for Current Graph as Text File Display Results for 10th tiles as Text File G C Metabl CM c G Parent Metab1 h Graph Table CEOE Cancel Figure 19 EXAMS output tabular Similar results are available for concentrations in sediment pore water using the menu at the lower left of the screen Results for other receiving water environments e g pond 25 or river can be viewed by selecting from the Environment Number menu at the bottom of the screen Evaluation of the PRZM ADAM simulation Scenario comparison results The panel in the upper right of the Grapher program allows you to compare groundwater scenarios Scenarios can be compared by either 10 percentile dissolved concentration in groundwater 10 percentile concentration in leachate at a depth of 1 meter or 10 percentile concentration in leachate at the bottom of the soil core If this panel is grayed out either groundwater scenarios were not included in selected simulations or surface water scenario comparisons have been activated If groundwater scenarios wer
45. issipation is to a specified or unspecified metabolite to CO or to bound residues In addition to this the formation percentage in the FOCUS report also called transformation fraction going from the 18 parent to a metabolite or from one metabolite to another has to be defined for each metabolite used in the simulation The shell automatically uses the affiliated molecular weights to adjust the PRZM input formation fraction by the molecular weight relation In doing so the correct mass flow and output concentrations are guaranteed Starting a simulation To start the simulation of the defined scenario s simply click on the Run button Then the shell will automatically start the executable WINPRZM EXE RICEWQ EXE EXAMS EXE and or ADAM EXE as applicable During the simulation run WISPE is not able to conduct other actions It is impossible to run two simulations at the same time Example execution windows during a simulation run of WISPE are given in Figure 12 and Figure 13 TET T Win PRZM PESTICIDE ROOT ZONE MODEL V4 5 Apr 2009 Scenario MZ0024 INP Status Running PRZM from 1 Aug 58 to 31 Aug 58 for zone 1 Trace Percent Complete Current Scenario il DUE EH NY WATERBORNE All Scenarios GERDSRRRRES i Terminate Simulation s Figure 12 Execution window during a PRZM simulation 19 R RER Running RICEWQ EXAMS simulation Please Wait Figure 13 Execution wi
46. ith scenarios containing crop soil and weather conditions for major agricultural areas in Brazil Canada Colombia the European Union Norway the People s Republic of China and the United States The architecture of WISPE allows seamless executions of several environmental fate and transport models including PRZM RICEWQ EXAMS and ADAM operating under the Windows environment A shared model input structure provides the flexibility for the user to create update and maintain databases on pesticide environmental fate properties and exposure scenarios As of the date of this manual the following exposure scenarios have been incorporated into WISPE Table 1 Standard scenarios currently available in WISPE Endpoint 07 fo 0 Location Receiving Water Groundwater Onions Hamburg Aquer Groundwater Peas Hamburg Aquer Groundwater Onions Jokioinen Aquer Groundwater Peas Jokioinen Aquifer WISPE has the ability to simulate multiple chemicals and metabolites within a single model execution and the flexibility to specify unique pesticide application conditions for different scenarios Simulations are conducted using 30 years of historical meteorological data in order to evaluate pesticide transport under a variety of weather conditions A statistical analysis is performed on model output to produce peak 24 hour 4 day 21 day 60 day 90 day and annual exposure durations Tabular and graphical out
47. kg e Simulated G Observed O N MA NN 0 O N Sediment loss kg Ne Oo Ne Ne N N N N oO Oo o oO oO oO a gt U a U Oo uU Qa A 2 3 lt so 2 on 53 lt Figure 6 Calibrated simulation of sediment loss at Askim 2006 2007 Simulated Observed Sediment loss cumulative Aug 06 Sep 06 Oct 06 Nov 06 Dec 06 Jan 07 Feb 07 Mar 07 Apr 07 Figure 7 Cumulative calibrated simulation of sediment loss at Askim 2006 2007 6 2 3 Dissolved and particle bound glyphosate in surface water Glyphosate is quite easily soluble in water but the risk of leaching has been regarded as low due to its relatively fast degradation in soil and strong sorption to soil particles Particle bound pesticides are generally believed to have a lower potential to leakage to watercourses than pesticides with lower affinity to soil Wauchope 1978 Sorption of pesticides to soil is an equilibrium reaction which is dependent on the soil water ratio and the contact time between pesticide and soil During transport of glyphosate with soil particles to surface and drainage water a major change of soil water ratio occurs and the glyphosate molecules might be released from the soil particles The total amount of simulated dissolved glyphosate 34 mg lost to the surface water is quite similar to the observed amount 28 mg figure 8 and 9 The simulated pesticide runoff losses are affec
48. l Name Chemical X I Use Non linear Adsorption Freundlich Exponent 1 n Molecular Weight 264 00 Solubility mg l 0 1000E 03 Plant Uptake Factor 0 50 Partition Coefficient Method Koc X Partition Value 100 000 Degradation days 30 00 I Use Temperature and or Moisture Corrected Half life Q10 Factor 25 Moisture Q10 Temp C Abs Moisture Exponent e p el FC Moisture Content C Off Vapor Pressure or Henry s K 0 0000E 00 Units of VP or Kh ve Torr I Use Foliar Processes I Simulate ET using crop coefficients Foliar Half life days Foliar Washoff Coefficient Simulate Volatilization Aquatic Only Groundwater Zone Specific Inputs ADAM model 60 0000 Partition Coefficient Method Koc v Partition Value 0 0000 Degradation days I Simulate Aged Adsorption Bi Phase Degradation Cancel Help Figure 8 Definition of the chemical parameters here chemical 1 parent 15 Enter Terrestrial EFATE Chemic Chemical 1 Chemical 2 Chemical 3 Aged Sorption m Aged Sorption Simulate Aged Sorption Select Kd Aging Method Continuous v Continuous Method for Equilibrium fraction PRZM direct FEQ v Chemical 1 Chemical 2 Chemical 3 Fraction at equillibrium 0 50000 0 0000 Desorption Rate 1 days 0 20000E 0 0000 Degradation Eq Sorbed Phase 9 99 to dissolved phase
49. l for Rice Crops User s Manual and Program Documentation Version 1 7 3 Waterborne Environmental Inc 362 Appendix A Calculations of Temporal Probability of Occurrence The simulation models incorporated into WISPE i e PRZM RICEWQ EXAMS and ADAM produce output on a daily time step Daily output is converted into an annual series for tabular and graphical presentation in the model shell The user can view the annual output for an individual scenario or compare the results for the upper 10 percentile year across scenarios Daily output can be obtained from output files created by the individual models To determine the 10 percentile values a probability analysis is performed on the annual maximum series of predicted concentrations for a given exposure duration The annual maximum series represents the maximum concentration for each year of simulation determined from a rolling average For example to calculate the maximum 21 day series for each year of simulation the average concentration is calculated for days 1 to 21 2 to 22 3 to 23 345 to 365 and the highest value from that year is assigned to the annual maximum series The Weibull plotting position Haan 1977 is used to calculate the 10 percentile concentrations The Weibull plotting position allows concentrations to be expressed in a temporal probability context i e frequency of occurrence For example concentrations of a 10 percentile are estimated to occ
50. llation The file pfdrv ini contains only two lines one with the drive letter of the Windows drive e g C and another with the drive letter of the CD ROM e g G The drive letters may be adjusted manually After a successful installation the shell is started by double clicking on WISPE EXE or by starting any shortcut WISPE to the executable The starting screen should appear including a picture of a rice paddy WISPE is optimized for a screen resolution of 1024x768 pixels The starting window of WISPE is shown in Figure 2 miske an k ao x WISPE Norway v 1 00 00 Dec 15 2012 Select Create Project Directory Scenario Manager Help TA tu O WISPE Current Project Directory momsen Figure 2 WISPE opening display screen The functions available from WISPE s initial screen are Select Create Project Directory Start a new project directory or navigate to an existing project directory Scenario Manager Scenario Manager Maintain all saved scenarios Prepare chemical and agronomic input data p Start model simulations Analyze and display model results ES Project directory and the Master Project File Directly after starting WISPE specify the active project directory in order to create the pesticide input data files for Win PRZM All relevant input output data of a simulation run is saved under this working directory Therefore WISPE needs to have full read w
51. ly an S gt Site Specific Results Norwegian GW BjorneBekk SpiCereal Tenesttial C Mass Balance PRZM C Hydrology Balance PRZM ce Concentration ppb c Groundwater al Leached Below Im Cone PRZM Leached Below Core Conc PRZM Aquatic i C Scenario s a C PE C PEC Banna WISPE Norway v 1 0000 Dec 152012 Graph Options ES Chemical Display Type nvironment Number Display Results Display Results FA Fr a Print Export for Curent Graph for 10th tiles Parent C Metab C Meta G Graph C Table ne as Text File as Text File C Er E OK Cancel Figure 22 Graphical display of leaching concentration at 1m yg I for groundwater scenarios 28 m Scenario Comparison Results Aqautic Leaching Concentration at Bottom of Core ug l Chemical Chemical X Groundwater C Groundwater Conc ADAM C Leached Below 1m Conc PRZM Leached Below Core Cone PRZM I Show Top 10 results only Site Specific Results GW _ Cotton _ Jiangsu Nantong p Terrestrial C Mass Balance PRZM Hydrology Balance PRZM CM Concentration ppb E p Groundwater Groundwater Conc ADAM Leached Below 1m Conc PRZM Leached Below Core Conc PRZM r Aqautic Scenario s eee am Pesticide Risk Assessment Exposure Simulation Shell v 1 00
52. n Leached Below 1m Scenario Norwegian GW BjorneBekk SprCereal Chemical Parent Chemical Environment Norway ADAM GW Env Period I PRZM AFLX DFLX VINFL r Graph Options WISPE Norway v 1 00 00 Dec 15 2012 Scenario Comparison Results Aquatic C 10th C 10th C PEC Groundwater C Groundwater Conc ADAM Leached Below 1m Conc PRZM Leached Below Core Conc PRZM I Show Top 10 results only Site Specific Results Norwegian GW BjorneBekk SpiCereal _ v m Terrestrial t_ Mass Balance PRZM Hydrology Balance PRZM Groundwater Conc ADAM Leached Below 1m Conc PRZM C Leached Below Cote Conc PRZM 7 Aquatie Ap gt p p pA C Dis Sed Pi C PECsw Display Results for Current Graph as Text File Chemical for 10th tiles as Text File Display Results Parent Metab Metab2 Display Type Environment Number G Env 1 Env 2 Eny 3 Ce 9 mah Table k Env 4 C Eny 5 Print Export OK Cancel p x l Scenano Componson Results Aquasc Annual Concentration Leached Below Soil Core sale c r Scenario Norwegian GW BjorneBekk SprCereal Chemical Parent Chemical Environment Norway ADAM GW Env 1 Groundwater A 90 004 Leached Below Im Conc PRZM Loachod Below Core Conc PRZM
53. nce output screen Chemical mass balance includes the amount of chemical lost each year through microbial degradation uptake by plants leaching below the soil profile volatilization runoff eroded soil and remaining in the soil profile at the end of the year 598 Scenario Comparison Results Aquatic Annual Hydrology Summary at Bottom of Soil Core c B G Scenario Norwegian GW BjorneBekk SprCereal _ Chemical Parent Chemical Environment Norway ADAM GW Env 1 Groundwater c C Leached Below 1m Conc PRZM Leached Below Core Cone PRZM I Show Top 10 results only Site Specific Results Precip Irrig cm Norwegian GW BjorneBekk SpiCereal 0 4 Terrestrial C Mass Balance PRZM amp Hydrology Balance PRZM c c Groundwater E C Leached Below 1m Conc PRZM C Leached Below Core Conc PRZM Water Balance cm 9 7 9 48 1 7 19 NB 25 Aquatic Period C e 6 e fleet fe f Runoff WISPE Norway v 1 00 00 Dec 152012 Graph Options Chemical Display Type Environment Number si Display Results Display Results G Enw 1 C C Print Export for Current Graph for 10th tiles Parent C c Graph Table ON as Text File as Text File i C OK Cancel Figure 17 Hydrologic balance output screen Hydrologic balance includes annual rainfall plus irrigation and the amount of water lost from runoff evapotranspiration
54. nd TOXSWA it was decided to combine the field scale runoff leaching model PRZM with the surface model EXAMS in WISPE EXAMS is the U S equivalent to TOXSWA with similar capabilities USEPA 2007 Like TOXSWA EXAMS calculates the pesticide exposure in three different aquatic environments pond stream and ditch figure 1 PRZM connected with EXAMS are the standard models used for ecological and drinking water risk assessment for pesticides by the U S Environmental Protection Agency s Office of Pesticide Programs USEPA 2007 PRZM produces runoff and erosion values that represent volumes and concentrations that are likely to be observed at the edge of the agricultural field Each PRZM modelling scenario represents a combination of climatic conditions crop specific management practices soil specific properties site specific hydrology and pesticide specific application and dissipation processes Each PRZM simulation is conducted using multiple years of rainfall data to cover year to year variability in runoff Daily edge of field loadings of pesticides dissolved in runoff waters and sorbed to entrained sediment are discharged into a standard water body pond stream or ditch simulated by the EXAMS model EXAMS simulates the processes that occur in the water body rather than on the agricultural field The EXAMS model accounts for hydrologic transport volatilization sorption hydrolysis biodegradation and photolysis of the pesticide EXAMS takes
55. ndow during a RICEWQ EXAMS simulation Evaluating model output After the selected simulations have finished i e the execution windows have been automatically closed you may wish to evaluate the results of the conducted simulation Clicking on the WISPE Grapher button will start the Grapher and automatically generate tables and figures required for risk assessment The simulation models incorporated into WISPE i e PRZM RICEWQ EXAMS and ADAM produce output on a daily time step Daily output is converted into an annual series for tabular and graphical presentation You can view the annual output for an individual scenario or compare the results for upper 10 percentile year across scenarios The upper 10 percentile results correspond to a 10 year return period Additional discussion on the derivation of the 10 percentile results is provided in Appendix A If the selected simulations contain surface water scenarios the initial image in Grapher will default to a comparison of the upper 10 percentile concentrations in the water column across all surface water scenarios row crop and rice as a bar chart If the selected simulations only contain groundwater scenarios the initial image will be the upper 10 percentile concentrations in groundwater across all groundwater scenarios To switch between surface water and groundwater scenario comparisons you must have a surface or groundwater scenario respectively highlighted in the
56. noff which to a large extent depends of soil properties and hydrological characteristics Transport of particles and particle bound pesticides like glyphosate is particularly affected by tillage rainfall intensity timing of rainfall in relation to spraying and the interval between two rainfall events The transport of pesticides is also affected by pesticide properties such as solubility sorption and degradation Uneven soil surface soil with high content of organic carbon high aggregate stability and porosity as well as crop residues covering the soil will reduce erosion and losses of pesticides to surface waters In the south eastern part of Norway the erosion and transport of particle bound pesticides are highest during winter and spring These transport processes are heavily dependent on climatic conditions and especially precipitation events shortly after application and melting freezing episodes during winter Bolli R I et al Bioforsk Report vol 8 nr 172 2013 8 Biofbrsk 4 Exposure of pesticides in aquatic systems There are many models available that are able to estimate the fate of a substance in different environmental compartments after its application in agriculture The FOCUS Working Group on Surface Water Scenarios has chosen a specific set of models to account for the different contamination routes of surface waters The models chosen are MACRO for estimating the contribution of drainage PRZM for the estimation of th
57. nual precipitation are shown in the legend Lars Egil Haugen personal communication 2005 Bolli R I et al Bioforsk Report vol 8 nr 172 2013 12 Biofbrsk The classification shows that the south eastern part of Norway is in the same region as the mid part of Sweden and the main part of Finland climate region 1 The Finnish scenario Jokioinen together with Bjornebekk and Syverud is located in climate region 1 which is characterized as a relatively dry and cold climate Bolli R I et al Bioforsk Report vol 8 nr 172 2013 13 Biofbrsk 6 Transport of particles and particle bound glyphosate A part of this project was to calibrate PRZM to achieve a better adaption of the sediment loss and the loss of pesticides which sorbs strongly to soil particles i e glyphosate Glyphosate can be transported in soil as dissolved or bound to particles Results from monitoring glyphosate through the Norwegian JOVA and the Swedish pesticide monitoring programs indicate that glyphosate is mainly lost through transport with soil particles In catchments and during runoff episodes with large particle losses also large amounts of glyphosate are lost Stenr d et al 2007 6 1 Materials and methods The calibration of PRZM was performed with data from controlled plot studies at the sites Askim Bjornebekk and Syverud Data for suspended solids turbidity and dissolved glyphosate was achieved from the study at Askim Since there were no data
58. on implementing of crops and calibration of soil loss and particle bound pesticides Waterborne Environmental Inc has been responsible for the software development user manual of WISPE and the implementation of EXAMS Project associates have been Randi Bolli and Ole Martin Eklo project coordinator from Bioforsk Plant Health and Plant Protection Division Amy Ritter and Mark Cheplick from Waterborne Environmental Inc and Roger Holten and Paulien Mulder from the Norwegian Food Safety Authority Biofbrsk Contents RS EE ENE TEEN SEAN 3 Contents cies cand chde cceacddecancetds ETETE EEEE AE EATE caus ad EEEE eave choi edeseeee caus ceoeedeces 4 Ws SUIMMMANY tree esteem det veenoetewece dete weewogscwecwdeseu AR 5 Zs Sammendrag es iriiri sinen a E EE EEEE E EEEE EE EET EA 6 Se MEN ee 7 4 Exposure of pesticides in aquatic Systems onnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnneeer 9 Dy Crop EG vr k en 11 6 Transport of particles and particle bound glyphosate rrnannnnnnnvnnnnnnnnnenever 14 1 Materials and ME NO c 22ciervecdcesvee ee veentebadenevscaniwauebiuweeractweoetetoeeebeets 14 6 1 1 Field descripti miccsvdsnvavedadeiavesssdeaiesueviadedaaeiuvelassnadavesevavasansiaeees 14 6 1 2 Treatment of sites sampling procedure and analysis eeeeeeeeees 15 6 1 3 Model and parameter GstiMatiOn sssc vocseencvveesacsvenevensvacesensveevvenevenseans 15 2 Results and discussion from the model simulations cc
59. perties e g Freundlich volatilization temperature and moisture corrected degradation biphasic degradation The bio degradation factors of a metabolite are handled in the parent check box as an independent data set All compound specific parameters parent and metabolites can be saved in a chemical database provided with the shell Figure 7 This allows the use of the same compound parameters for additional simulations of different soil and crop scenarios It is possible to delete single entries and still maintain the database The whole database may be also deleted manually by starting the batch file CHM BAT found in the directory 293 CAWISPEWPIG See Figure 7 Figure 11 for screenshots of the various input screens for chemical e fate aged sorption aquatic e fate and application parameters Chemical Database Options md Sm I Chemical Name Status Comments Record1 Dummy Chemical 1 Example Chemical 1 Dummy Chemical 2 Example Chemical 2 Kinetic Sorption On Currently Selected Record 1 Save Currently Entered Values to Database Recall Currently Selected Record Browse Currently Selected Record Perform Maintenance Apply Status Change Cancel Figure 7 WISPE Chemical database manager 14 Enter Terrestrial EFATE Chemical Parameters Chemical 1 Chemical 2 Chemical 3 Aged Sorption Universal Chemical Inputs i Interface Specific Options Chemica
60. pesticide mass balance and water management practices in rice paddy environments Williams et al 2008 Water balance takes into account precipitation evaporation seepage irrigation overflow and drainage Pesticide mass balance can accommodate metabolites volatilization linear equilibrium sorption between water sediment first order or bi phase decay on foliage water and sediment and resuspension from sediment The model has been endorsed by the European community MED Rice 2003 and has been validated with a number of field and watershed applications EXAMS The Exposure Analysis Modeling System version 2 98 04 EXAMS combines a chemical fate and transport model with a steady state hydraulic model to simulate the following processes in aquatic environments advection dispersion dilution partitioning between water biota and sediment and degradation in water biota and sediment Burns et al 1997 Model geometry is based on the segment compartment approach in which the simulated system is divided into a number of discrete volumes that are connected by advective and dispersive fluxes EXAMS is the standard model used for ecological and drinking water risk assessments for pesticides by the U S Environmental Protection Agency s Office of Pesticide Programs USEPA 2004 e ADAM The Aquifer Dilution Assessment Model ADAM predicts chemical dilution partitioning and persistence in a shallow unconfined aquifer receiving daily
61. put can be exported to Windows metafile format Figure 1 displays the organizational structure for WISPE The simulation shell allows the user to create or use specific folders or directories for individual projects or assessments Model simulations can be performed for any combination of the standard scenarios Several input screens are used to provide input parameter values related to chemical properties and pesticide applications Once these properties are specified the user can create model input files and initiate model simulations Surface water scenarios for terrestrial crops e g corn and cotton require sequential simulations of PRZM for the terrestrial field and EXAMS for the pond and or river Scenarios account for pesticide loads from the agricultural field into the aquatic environment from spray drift water runoff and soil erosion and into the aquatic environment Groundwater scenarios for terrestrial crops require sequential simulations of PRZM for the terrestrial field and ADAM for aquifer system Surface water scenarios for rice involve sequential simulations of RICEWQ and EXAMS After a completed simulation is run the relevant scenario output data is given in six ASCII files of the type ann hyd cnc msb out and zts The shell will analyze those files automatically and provide the user with result tables and graphics WISPE s Grapher can also export results for each simulated scenario in an ASCII file of the type
62. rd water body pond ditch or stream This is similar to TOXSWA which is a part of the FOCUS surface water exposure assessment PRZM simulates the amount of surface water and soil loss from the Askim field adequately and the results are within the acceptability limit for the deviation between simulated and observed values As earlier simulations from Bj rnebekk and Syverud have shown the model encounters difficulties when estimating exposure in periods with frozen soil freezing and thawing cycles and high surface runoff during snowmelt events Eklo et al 2008 Eklo et al 2009 Bolli et al 2011 Glyphosate can reach water bodies both in a dissolved state and bound to particles The total simulated amount of dissolved glyphosate 34 mg lost to surface water was similar to the observed amount 24 mg The simulation showed that the model did not time runoff events well compared to the observed measurements The model simulates too much loss of particle bound glyphosate compared to calculated values due to the strong sorption of glyphosate to soil minerals and not to the organic matter Transfer of data from one site to another is not recommended since the soil properties and topography strongly influence the model simulations Thus the model has to be calibrated with the field properties that are found at each site pers comm Cheplick 2013 The effect of soil particles on transport and analytical determination of glyphosate should b
63. reated Annotation 1 Dummy Chemical 1 CAPRAESSYPROJECTS vestd Tier 2 Original 2010 04 07 17 28 Chemical X CAPRAESS PROJECTS Tier 2 Original 2070 06 08 15 56 Currently Selected Scenario 1 Recall Currently Selected Perform Selected Maintence Scenario and Perform Don t Recall Currently Cancel Selected Maintenace Selected Scenario Figure 5 WISPE Scenario Manager 11 Data files and scenario definition The information necessary to run WISPE EXE is divided into a number of input data files parameter file including the scenario definition inp climate file providing the weather data used met file with definition of the PRZM run options run file with definition of the EXAMS run options exa file with definition of the RICEWQ run options req file with definition of the ADAM run options adm The shell WISPE EXE allows you to create the required input files All scenario compound and application specific information is also stored in the Master Project File called master fpj In addition a file of the type scn is created in order to support WISPE s Grapher with necessary information for the data analysis and data visualization Note that the PRZM 3 21 parameter and weather files are not compatible with older PRZM versions Creating the data files for a WISPE simulation To start the scenario definition and begin entering the necessary pesticide input data
64. rite permission for the specified directory New directories can be created on hard disks or network drives using the shell Windows Explorer or other tools Long filenames are possible A standard working directory to be automatically used as the default directly after start of WISPE e g C WISPE PROJECTS may be defined in the first line of the file startdir ini located in C WISPE The default directory after installation of WISPE is not defined Each simulation scenario may be rerun and reanalyzed later on by choosing the specific project directory Each previously created project directory contains a special file called the Master Project File MPF file The MPF named MASTER FPJ contains all scenario specific information necessary to characterize the project By specifying an active project directory the shell returns an output window as given in Figure 3 asking for further input The directory selected already contains a previously created Master Project File Please select one of the following options Copy the Master Project File Copy to anew directory Edit the Master Project File Edit NOTE This will delete all previous results files Browse Print the Master Browse Project File Reselect Create a different Reselect project directory Email the Master Project File EMail NOTE Will be sentto code developer for software debug purposes only Rerun PRZM EXAMS Rerun simulation s using selected
65. s Balance PRZM Hydrology Balance PRZM Dissolved Concentration ug l 10 20 30 40 60 70 80 Percent of Years Exceeding the Above Concentration Key amp 10th Perci Resulis Dissolved Cone EXAMS Maximum Pek Maximum 96 Hour Matimum 21 Day Maximum 60 Day Maimum 90 Day Long Term Sed Porewater Conc EXAMS 60 6 58 2 497 34 8 253 7 86 Pesticide Risk Assessment Exposure Simulation Shell v 1 00 Graph Options Chemical Display Type Environment Number Display Results Display Results Ps el SEE Print Export for Current Graph for 10th tiles amp Parent C Metab Metab G Graph Table nv nw r as Text File as Text File C En 4 C Env 5 Figure 18 EXAMS output graphical s Scenario Comparison Results SW _ Cotton _ Jiangsu Nantong Dissolved Conc ppb Chemical Chemical X Environment China Pond Scenario 1 Agautie Web Inst 96 Hr 210 60 0 90 D C 10th Xtile Dissolved EXAMS 003 848 818 893 495 384 10th tile Sed Porewater EXAMS 008 737 708 203 25 Eg 010 625 a0 811 Eg 74 013 432 n5 370 20 219 Groundwater 018 428 41 370 EJ EH Groundwater Conc 019 384 30 23 42 165 hed Below 1r 35 37 27 159 d Below Core I Show Top 10 results only r Site Specific Results SW Cotton _ J
66. s and large runoff erosion events Bolli et al 2011 According to Reichenberger 2005 this is probably due to the daily calculation step of PRZM and that the model does not consider actual rainfall Meteorological data used for environmental fate modelling generally consists of daily values for precipitation temperature and evapotranspiration The daily resolution of weather data is used primarily because daily data is easier to obtain than data with finer temporal resolution For transient processes such as runoff and erosion which have time scales of minutes to days the use of daily weather creates significant uncertainties FOCUS 2001 Sampling procedures from field experiments are important for the interpretation of the observed results Due to the Bolli R I et al Bioforsk Report vol 8 nr 172 2013 18 Biofbrsk methodology of water proportional sampling sudden runoff events are not taken into account Glyphosate can be lost into water bodies both as dissolved and bound to particles There are some analytical challenges associated with the analysis of glyphosate in water samples and methods used today only give a measure of dissolved glyphosate The amount of particle bound glyphosate being transported with water suspended solids is built on the assumption that there is a good correlation between the amount of suspended solids in the water and the amount of glyphosate Stenr d et al 2007 Data collected for suspended solids
67. s chemical mass balance in both graphical Figure 28 and tabular Figure 29 formats Chemical mass balance includes annual losses from degradation hydrolysis microbial degradation and photolysis volatilization drainage and overflow seepage below the benthic compartment and mass remaining in the paddy and sediment at the end of the year The benthic compartment is considered the surficial 5 cm of sediment Scenario Comparison Results Aqautic Annual Mass Balance in Rice Paddy GO oe Diestve DANS C 10th tile Sed Porewater EXAMS Scenario SW _ Rice _ Zhejiang Hangzhou Chemical Chemical X Environment China Pond Scenario 1 Groundwater C6 oC c I Show Top 10 results only Site Specific Results sw Rice _ Zhejiang Hangzhou od Terrestrial 6 Mass Balance RICEWQ p Groundwater 6 6 3 8 13 18 23 28 8 Period FAS C Dissolved Cone EXAMS Sed Porewater Conc EXAMS F Deczyet f Volatiized J Seepage ff Drainage J Remaining Pesticide Risk Assessment Exposure Simulation Shell v 1 00 Graph Options Chemical Display Type Environment Number Display Results Display Results G Env1 Cem 2 C Print Export for Current Graph for 10th tiles amp Parent C Graph Table Linge ny as Text File as Text File GC Cancel Figure 28 RICEWQ mass balance output tabular 33 SW _ Rice Jiangsu Changzhou Dissolved Conc ppb Chemical
68. s in periods characterized by frozen soil freezing and thawing cycles and high surface runoff during snowmelt events This problem was also found in earlier simulations done for Bjornebekk and Syverud Bolli et al 2011 PRZM considers the effect of snowmelt in the runoff equation but the curve numbers are not adjusted to account for the effects of snowpack or frozen ground on runoff generation Reichenberger 2005 6 2 2 Sediment loss The sediment loss is highly dependent on erosion which again depends on the soil permeability and aggregate stability Topographical conditions like the land slope and the hydraulic length is also important for the erosion Soil loss by erosion is modelled empirically in PRZM using MUSS a modification from the Modified Universal Soil Loss Equation MUSLE which is specifically designed for small watersheds After recommendations from the model developer pers comm Cheplick 2013 parameters like the topographic factor USLELS universal soil loss equation topographic factor and the hydraulic length of the field HL were changed to get a better adaption of the data The difference between the total amount of simulated and observed sediment Bolli R I et al Bioforsk Report vol 8 nr 172 2013 16 Biofbrsk loss was about 9 figures 6 and 7 The timing of the largest runoff event and the amount simulated was very good The simulated amount of sediment loss was 11 kg while the observed amount was 9
69. splay Type menu at the bottom of the screen see Figure 19 The year associated with each value can be identified by clicking on the Display Results for Current Graph as Text File button at the lower left of the screen depth 31 Scenario Comparison Results Aqautic Scenario GW _ Cotton _ Jiangsu Nantong Groundwater Conc Chemical Chemical X Environment China ADAM GW Env 1 Groundwater Groundwater Conc ADAM Leached Below 1m Cone PRZM Leached Below Core Conc PRZM I Show Top 10 results only Site Specific Results aw _ Cotton _ Jiangsu Nantong x Groundwater Concentration ug l Terrestrial 3 C Mass Balance PRZM Hydrology Balance PRZM 2 6 c Groundwater Groundwater Cone ADAM Leached Below 1m Conc PRZM Leached Below Core Conc PRZM 10 20 30 40 50 60 70 80 90 Percent of Years Exceeding the Above Concentration Agqautic Key amp 10th Percentile Results 2 Maximum Pex amp Maximum 96 Hour amp Maximum 21 Da Maimum 60 Da Maimum 90 Day Long Term 6 680E 01 669E 01 618E 01 496 01 413E 01 155E 01 Pesticide Risk Assessment Exposure Simulation Shell v 1 00 Graph Options ae aS Chemical Display T nvironment Number Display Results Display Results a alt G em 1 C c Print Export for Current Graph for 10th tiles Parent C M C Graph
70. ted by uncertainty from both water transport and chemical transport Bolli R I et al Bioforsk Report vol 8 nr 172 2013 17 Biofrsk simulation The deviation between simulated and measured values can thus be expected to be higher for pesticide runoff than for the corresponding runoff water volumes However for the purpose of aquatic risk assessment an under or over prediction of pesticide inputs into a surface water body by more than a factor of 10 cannot be considered as acceptable Reichenberger et al 2005 N UT e Simulated G Observed N oO ul oO UT Dissolved glyphosate mg Aug 06 Sep 06 Oct 06 Nov 06 Dec 06 Jan 07 Feb 07 Mar 07 Apr 07 Figure 8 Calibrated simulation of dissolved glyphosate in surface water at Askim 2006 2007 Simulated ETETETT Observed KR gt NN ou ou oO u Dissolved glyphosate cumulative mg Aug 06 Sep 06 Oct 06 Nov 06 Dec 06 Jan 07 Feb 07 Mar 07 Apr 07 Figure 9 Cumulative calibrated simulation of dissolved glyphosate in surface water at Askim 2006 2007 The timing of the runoff events do not fit well with the observed measurements figure 8 Pesticide losses in surface runoff are event driven and therefore very strongly dependent on the weather conditions immediately after application in particular the rainfall pattern Earlier simulations have showed that the model has the tendency to under predict for high intensity rainfall
71. the runoff and spray drift loading generated by PRZM and estimates the concentration of pesticides in the water body on a day to day basis The combination of substance specific data scenario specific data and crop specific data result in an estimated environmental concentration EEC in surface water that is used for the risk assessment processes More information can be obtained in the manuals for PRZM EXAMS and WISPE Carsel et al 2006 Burns 2004 Cheplick et al 2012 In order to run the TOXSWA in FOCUS model a set range of characteristics relating to the dimensions sediment and organic components and hydrology of each water body are required to parameterize each scenario It was important that the definitions in EXAMS were similar to the definitions in TOXSWA Table 1 gives an overview over some important parameters that are similar between EXAMS and TOXSWA Table 1 Parameters in EXAMS that is similar to TOXSWA Ditch Pond Stream Width m 1 30 1 Total length m 100 30 100 Average water depth m 0 3 1 0 3 Concentration of suspended solids mg L 15 15 15 Organic carbon content 5 5 5 Dry bulk density kg m3 800 800 800 More information about the parameters in EXAMS and TOXSWA can be found in the EXAMS manual Burns et al 2004 and the FOCUS document FOCUS 2001 Bolli R I et al Bioforsk Report vol 8 nr 172 2013 10 Biofbrsk 5 Crop scenarios In WISPE the Norwe
72. the meteorological data The model simulates too much loss of particle bound glyphosate compared to the calculated values Erosion is a selective process and eroded soil materials tend to consist of smaller particles and higher content of organic carbon Adsorption of glyphosate is mainly governed by the mineral phase of the soil matrix and not to the organic matter PRZM uses an enrichment ratio to account for that eroded soils have a higher content of soil organic matter which can lead to more inaccurate simulations of particle bound glyphosate due to the strong sorption to soil minerals The soil properties for the Askim site are quite similar to the soil from Bj rnebekk and the parameters used for the sediment loss calibration at Askim were also used for Bj rnebekk The simulation showed that the cumulative simulated values were high compared to the calculated values 91 kg and 3 kg respectively These simulations confirmed that transfer of data from one site to another is not recommended since the soil properties and topography strongly influence the model simulations Thus the model has to be calibrated with the field properties that are found at each site pers comm Cheplick 2013 Bolli R I et al Bioforsk Report vol 8 nr 172 2013 5 Biofbrsk 2 Sammendrag Waterborne Environmental Inc har sammen med Bioforsk og pa oppdrag fra Mattilsynet utviklet risikovurderingsverkt yet WISPE The World Integrated System for Pesticide E
73. ticide inputs into German surface waters Phd Thesis 228 p Giessen Germany Bolli R I et al Bioforsk Report vol 8 nr 172 2013 22 Biofbrsk Resseler H Schafer H Gampp H Gorlitz G Klein M Kloskowski R Mani J Moede J Muller M Sarafin R Stein B Winkler R 1996 Recommendations to conduct and assess model calculations for the validation of simulation models In Nachrichtenblatt des Deutschen Pflanzenschutzdienstes 48 no 1 4 9 Riise G and B rresen T 2012 Sluttseminar i Reduce prosjektet Tap av glyfosat og nedbrytingsproduktet AMPA Feltfors k p et erosjonsutsatt omr de Askim Presentasjon Stenr d M Ludvigsen G H Riise G Lundekvam H Almvik M T rresen K S ygarden L 2007 Redusert jordarbeiding og glyfosat En sammenstilling av norske og internasjonale forsknings og overv kingsresultater samt en sm skala feltstudie av avrenning av glyfosat ved ulik jordarbeiding Bioforsk Rapport Vol 2 Nr 145 2007 ISBN 978 82 17 00297 0 U S Environmental Protection Agency USEPA 2007 Water Exposure Models Used by the Office of Pesticide Programs Science and Policy 2007 http www epa gov oppefed1 models water models4 htm Vanclooster M Boesten J T T I Trevisan M Brown C Capri E Eklo O M Gottesburen B Gouy V van der Linden A M A 2000 A European test of pesticide leaching models methodology and major recommendations Agric Water Mgmt Vol
74. ur on average once in a 10 year period The Weibull plotting position represents the probability that a specific event will be equaled or exceeded in any given year under the hydrologic and agronomic conditions simulated in the model for the scenario Annual concentrations are ranked in descending order from 1 to 30 corresponding to 30 years of simulation For the annual values n 30 the highest value ranked from high to low has a rank of 1 and the lowest value has a rank of 30 The equation for the Weibull plotting position is shown below Rank Weibull plotting position 2 100 1 n The 10 percentile Weibull plotting position is then determined by interpolation 7872
75. xposure som inkluderer bade transportmodeller og modeller som beregner eksponeringen av plantevernmidler i ulike vannmilj De norske scenariene fra Bj rnebekk og Syverud er inkludert i WISPE noe som gj r det mulig gj re risikovurderinger i overflate og grunnvannsressurser med hensyn p norske forhold Det f rste delm let i prosjektet var inkludere en modell som kunne beregne plantevernmiddel eksponeringen for vannlevende organismer WISPE har blitt utvidet med EXAMS The Exposure Analysis Modeling System som er standard modellen i USA for beregning av PEC predicted environmental concentrations verdier til plantevernmidler sluppet ut i et standard vannmilj pond ditch stream EXAMS har de samme egenskapene som modellen TOXSWA TOXic substances in Surface Waters som brukes i risikovurderingsarbeidet i Europa Det andre delm let i prosjektet var inkludere i modellen de mest utbredte jordbrukskulturene i Norge slik at det norske klimaet blir tatt hensyn til i forhold til planteutvikling noe som inkluderer s ing modning og h sting Det tredje delm let var bruke eksisterende norske feltdata fra Askim til kalibrere PRZM Pesticide Root Zone Model med hensyn p transport av partikler og partikkelbundne plantevernmidler glyfosat Modellen viste god tilpassing mellom predikerte og observerte verdier b de av overflatevann og jordtap Som tidligere simuleringer med PRZM har vist var det ogs her problemer i perioder

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