“Using Modern Watershed and Cropping Data as a basis forestimating percentage crop treatment”Nathan J. SnyderAldos C. BarefootJoshua J. AmosPeggy S. LeeJuly 27, 2010Exposure Modeling Public MeetingCrystal City, VAPresentation Overview•Review of USEPA Science Policy•“Development and Use of Percent Cropped Area AdjustmentFactors in Drinking Water Exposure Assessments” April 13,2010•Percent Crop Area (PCA) use in assessments•Options for Higher Tier Assessments•Registration Defense•Monitoring Strategies•Stewardship2•Recent update to documentation•Matches the practices seen in recent reregistration assessments coming from EFED•Provides a clear procedure for Tier 2assessments that registrants can follow toassess how new products will be received3Use of PCA in USEPA Tier 2 DWA•National PCA Adjustment Factors•8-Digit HUCs intersected withCounty level Crop (1997 and 1992USDA Census of Agriculture) all agriculture•PCA Adjustment Factors for Major Crops•Same as above, but croppingspecific to target crops•Available for Corn, Wheat, Soybeans and Cotton•Method developed to combine EECs if use is on several majorcrops with similar or different timing•Regional PCA Adjustment Factors•Same methodology but identified highest PCA in each of 18regions4PCA Values•National value of 87%•Crop Specific (20 to 56%)•Regional values (7 to 87%)5Regional PCA Determination6Applying PCAs in Tier 2 Assessments•Minor (not corn, soybean, wheat, cotton)•“For minor-use crops, the SAP found that the use of PCA adjustmentfactors derived from information on 8-digit HUCs....and county-basedcrop acreages might be too coarse of an estimate.”•“SAP foundusing PCAs...potentially bias exposure estimates for minoruse crops”•“In the interim, OPP will use the default PCA adjustment factor ...formajor crops that do not yet have PCA adjustment factors and for minoruse crops.”•Crop Mixtures•“The SAP provided only minimal guidance on applying the PCAadjustment factor for multiple crop uses in a watershed. “•“They recommended that the PCA adjustment factor for multiple cropsbe based on the single watershed thathad the highest percentage ofthe combination of the crops being modeled, rather than on summingthe maximum PCA adjustment factors for the individual crops fromdifferent watersheds.”7Limitations to Current Method•Refinements to address limitations of Tier 2•“The size of the 8-digit HUC may not providereasonable estimates of actual PCAs for smallerwatersheds.....may be better represented bywatersheds defined for drinking water intakes.”•“The conversion of the county level data towatershed-based percent cropped areas assumes thedistribution of the crops within a county is uniform andhomogeneous throughout the county area”•Updating of crop data to current NASS sources8Refinements to Tier 2•Re-registration process is identifying products, whichhave been used safely for years, that may not pass thecurrent assessment process•Monitoring data is not in agreement with modelingpredictions•Registrants are being asked to make significant labelmodifications based on the modeling output using Tier 2procedures•No Tier 3 procedure endorsed by USEPA•Refinements to PCA procedure as a Tier 3 is oneavenue to explore that will build on existing proceduresand answer limitations to current procedures highlightedby USEPA and SAP9Need for Tier 3•A process to combine localized knowledge of drinking watersupplies and labeled crops should enable the development ofconservative yet refined PCA values•Use actual watersheds used for drinking water rather than surrogateHUC-8 watersheds•Use publically available source information•NHDPlus catchments can be used to hidespecific LAT/LON of intakes whileproviding needed watershedsto produce refined PCAs•Use spatially distributed cropping datarather than “All Agriculture” at acounty scale•Additional scenarios/weather stations to address regional concerns(not addressed in this talk)•Represent distribution and timingof applications where diverse landuse exists in watersheds (not addressed in this talk)10Options for Tier 3•SDWIS identifies Water Supplies and the Source of theirWater•USEPA Source Water Assessment Plans (SWAP)available for many water supplies•State programs generally are providing adequateinformation to identify source locations•NHDPlus provides clear standard basis for delineatingwatersheds•Catchments (identified by “COMID”) can be used to delineatewatersheds while hiding specific locations of intakes•EPAs Office of Water programs may be a resource11HUC-8 Watershed vs. Actual SurfaceWater Watersheds•DWMA seems to be the tool that couldstandardize the process•“ABSTRACT: The Drinking Water Mapping Application (DWMA)provides a secure application EPAstaff can use to obtain reportsand maps that help manage programs under the Safe DrinkingWater Act. The DWMA makes extensive use of the enhancedNational Hydrography Dataset (theNHDPlus) to locate drinkingwater surface intake locationswithin the NHD network and todefine source water areas relative to the intake facilities.”12Surface Water Intakes13DWMA•Until a Tier 3 is adopted, regional refinements ofinterest to registrants to design focusedmonitoring and explore label modifications toaddress concerns•Focus efforts to where Tier 2 analysis indicatesa regional problem•Public information and tools can be utilized inmost states14Regional Surface Water SuppliesMN (Region 9)PWSIDPWSNameEPA_Region Geography_type State PCountyStatus_id PWSType GwSw PSource Owner SizeCat5_ptMN5160330Temperance River State Park/Upper Cpgrd. 05 State MN Cook 1 TNCWS sw SW State_Govt 1_Very_SmallMN5160404Judge C.R. Magney State Park 05 State MN Cook 1 TNCWS sw SW State_Govt 1_Very_SmallMN5690953Big Lake Wilderness Lodge 05 State MN St. Louis 1 TNCWS sw SW Private 1_Very_SmallMN5690244Lodge of Whispering Pines 05 State MN St. Louis 1 TNCWS sw SW Private 1_Very_SmallMN5160137Adventurous Christians Covenant 05 State MN Cook 1 TNCWS sw SW Public/Private 1_Very_SmallMN1460003Fairmont 05 State MN Martin 1 CWS sw SW Local_Govt 4_LargeMN5690950YMCA Camp Widjiwagan 05 State MN St. Louis 1 TNCWS sw SW Private 1_Very_SmallMN5690204Burntside Lodge 05 State MN St. Louis 1 TNCWS sw SW Private 1_Very_SmallMN5690951Tamarack Resort 05 State MN St. Louis 1 TNCWS sw SW Private 1_Very_SmallMN1690014Ely 05 State MN St. Louis 1 CWS sw SW Local_Govt 3_MediumMN1690004Biwabik 05 State MN St. Louis 1 CWS sw SW Local_Govt 2_SmallMN5160328Clearwater Canoe Outfitters 05 State MN Cook 1 TNCWS sw SW Private 1_Very_SmallMN1690028Hoyt Lakes 05 State MN St. Louis 1 CWS sw SW Local_Govt 2_SmallMN1690033McKinley 05 State MN St. Louis 1 CWS sw SW Local_Govt 1_Very_SmallMN5160108Bearskin Lodge 05 State MN Cook 1 TNCWS sw SW Private 1_Very_SmallMN5380074Timber Trail Lodge LLC 05 State MN Lake 1 TNCWS sw SW Private 1_Very_SmallMN5690988Fenske Lake Cabins 05 State MN St. Louis 1 TNCWS sw SW Private 1_Very_SmallMN5160042Golden Eagle Lodge 05 State MN Cook 1 TNCWS sw SW Public/Private 1_Very_SmallMN1690007Chisholm 05 State MN St. Louis 1 CWS sw SW Local_Govt 3_MediumMN5160062Gunflint Lodge 05 State MN Cook 1 TNCWS sw SW Private 1_Very_SmallMN5160107Moosehorn Lodge 05 State MN Cook 1 TNCWS sw SW Public/Private 1_Very_SmallMN5160303Gunflint Pines Resort 05 State MN Cook 1 TNCWS sw SW Private 1_Very_SmallMN5160318Hungry Jack Outfitters 05 State MN Cook 1 TNCWS sw SW Public/Private 1_Very_SmallMN5690229North Star Resort 05 State MN St. Louis 1 TNCWS sw SW Private 1_Very_SmallMN5690113Deer Horn Resort 05 State MN St. Louis 1 TNCWS sw SW Private 1_Very_Small16ND (Region 9)PWSID PWSNameEPA_Regio Geography_type State PCounty Status_idPWSType GwSwPSourceOwner SizeCat5_ptND0800080BISMARCK CITY OF8 StateND Burleigh 1 CWS sw SW Local_Govt 4_LargeND0900336FARGO CITY OF8 StateND Cass1 CWS sw SW Local_Govt 4_LargeND0900336FARGO CITY OF8 StateND Cass1 CWS sw SW Local_Govt 4_LargeND1000543LANGDON CITY OF8 StateND Cavalier 1 CWS sw SW Local_Govt 2_SmallND1000543LANGDON CITY OF8 StateND Cavalier 1 CWS sw SW Local_Govt 2_SmallND1800410GRAND FORKS CITY OF8 StateND Grand Fork1 CWS sw SW Local_Govt 4_LargeND2800389GARRISON CITY OF8 StateND McLean 1 CWS sw SW Local_Govt 2_Small17FL (Region 3)18NHDPlus “COMID” Identified•A list of COMIDs is passed to a custom “NHDPluswatershed delineation tool”,which can be called usingESRI’s ArcGIS-ArcMap.•The tool is built over “VAACOMObjectNavigator” that isdistributed by the NHDPlus team along with theNHDPlus dataset. It usesa COMID as input,navigates upstream ofthe NHDPlus network andhydrologically identifies allrelated watersheds that arepart of the network and goes all the way till theheadwater watersheds.•The custom tool uses anautomated process of goingthrough the list of COMIDs, and creates upstreamwatersheds for each one ofthem separately using theNHDPlus data.•Each COMID may have one or more watersheds,depending on its location onthe NHDPlus network. Anintake location close tothe headwater stream mayhave one or two upstream watersheds, where as anintake location on a river will have several upstreamwatersheds. If the COMIDhas several watersheds,they are all spatially dissolved to create a single largewatershed19Watersheds - NHDPlus20Watersheds21Intake Locations•USEPA Assessment utilized county level NASSCensus of Agriculture from 1997 (or 1992 ifmissing)•Used “Cropped Area” for default and “Corn”,“Soybean”, “Cotton”, or “Wheat” for major crops•Distributed county acreage to HUC-8Watersheds•Did not utilize minor crop data•Cropland Data Layer (CDL) now seamless forContinental US22LanduseNASS CDL Data2324Watershed Land-use Description25PCA Calculations•Summarize CDL for eachWatershed•Accuracy assessment ofCounties•Conservative CDLgroupings based onCounty Census ofAgriculture•CDL offers a completespatial view at a 56mresolution•CDL has 130 classes,including some from theNLCD•Census of Agriculture issummarized at a countyresolution•Includes only agriculturalareas•Includes >200 cropcategories•A comparison of the 2NASS sources is neededto identify groupingsneeded for detailed PCAcalculations26CDL versus Censusof Agriculture27CDL Crop GroupingNLCD‐BarrenBarleyNLCD‐BarrenAlfalfaNLCD‐DeciduousForestBlueberryNLCD‐DeciduousForestBarleyNLCD‐Developed/HighIntensityCamelinaNLCD‐Developed/HighBlueberryNLCD‐Developed/LowIntensityCanolaNLCD‐Developed/LowCamelinaNLCD‐Developed/MediumIntensitCeleryNLCD‐Developed/MediumCanolaNLCD‐Developed/OpenSpaceCitrusNLCD‐Developed/OpenSpaceCeleryNLCD‐EvergreenForestDryBeansNLCD‐EvergreenForestCitrusNLCD‐GrasslandHerbaceousFlaxseedNLCD‐HerbaceousWetlandsClover/WildflowersNLCD‐HerbaceousWetlandsHerbsNLCD‐MixedForestDryBeansNLCD‐MixedForestLentilsNLCD‐OpenWaterFallow/IdleCroplandNLCD‐OpenWaterMilletNLCD‐ShrublandFlaxseedNLCD‐ShrublandMisc.Vegs.&FruitsNLCD‐WoodyWetlandsHerbsNLCD‐WoodyWetlandsOatsWetlandsLentilsWetlandsOrangesWoodlandMilletWoodlandOtherCropsCornMisc.Vegs.&FruitsCornOtherSmallGrainsCottonNLCD‐GrasslandHerbaceousCottonOtherTreeFruitsDurumWheatNLCD‐Pasture/HayDurumWheatPeanutsSoybeansOatsSoybeansPeasSpringWheatOrangesSpringWheatPotatoesSweetCornOtherCropsSweetCornRiceWinterWheatOtherHaysWinterWheatRyeOtherSmallGrainsSeed/SodGrassOtherTreeFruitsSorghumPasture/GrassStrawberriesPeanutsSugarbeetsPeasSugarcanePotatoesSunflowersRiceWatermelonRyeAlfalfaSeed/SodGrassClover/WildflowersSorghumFallow/IdleCroplandStrawberriesNLCD‐Pasture/HaySugarbeetsOtherHaysSugarcanePasture/GrassSunflowersWatermelon

Minor Crop and Pasture\Hay

Major Crops Non

‐ AgFloridaCDLGroupings Region9CDLGroupings

Pasture/Hay Minor Crop

Non

‐ Ag Major Crops•County review of CDL versus Census of Agriculture•Neither dataset is perfect (omissions, border effects,incorrect categorizations, under/over reporting, cropdamage)28CDL versus Census of AgricultureCategoryCensusofAg CDL CDL%ofCensusNon‐AgricultureNA 9,506,731.12TotalCropland3,796,669.01 3,673,464.2196.8%‐MajorCrops4,733.14 4,995.15105.5%‐ForageandPasture 2,453,258.04 2,434,969.9399.3%‐MinorCrops1,338,677.83 1,233,499.1392.1%Florida(CountieswithDrinkingWaterIntakes)CategoryCensusofAg CDLCDL%ofCensusNon‐AgricultureNA21,553,679.82TotalCropland24,912,617.02 24,277,202.9897.4%‐MajorCrops13,061,637.04 13,728,937.31105.1%‐MinorandForage/Pasture 11,850,979.98 10,548,265.6889.0%‐ForageandPasture4,626,551.06 NA‐MinorCrops7,224,428.92 NAMN,ND,SD(Region9CoutnieswithIntakes)•Tabular summary of All Ag, Major Crops, OtherCrops – Conservative view of using CDL foridentified watersheds•Highlights many watersheds that are notagricultural•Major groupings could be divided further ifcounty and CDL comparison in small groups ofspecific counties support•Specific crop composition can be used to identifyappropriate standard scenarios and properweighting29Final PCA Summary30Florida Specific PCAsCOMID TotalArea Non‐Ag MajorCrop Pasture/hay MinorCrop %Non‐Ag %MajorCrop %Pasture/Hay %MinorCrop10247733 558,771 322,044 0 133,304 103,423 58% 0% 24% 19%11003339 1,434 692 0 742 0 48% 0% 52% 0%11003367 7,976 7,261 0 705 9 91% 0% 9% 0%16715740 39,713 14,125 0 25,301 287 36% 0% 64% 1%16767080 6,446 6,345 0 5 95 98% 0% 0% 1%16809709 1,159,388 625,497 0 334,236 199,656 54% 0% 29% 17%16814857 218,996 91,520 0 90,915 36,561 42% 0% 42% 17%16838208 59,139 47,063 0 11,601 475 80% 0% 20% 1%16839124 68,210 38,213 0 27,853 2,144 56% 0% 41% 3%16878340 81,033 51,074 0 22,240 7,718 63% 0% 27% 10%16896620 235,138 191,343 0 32,423 11,372 81% 0% 14% 5%16907115 395,483 298,289 0 84,294 12,900 75% 0% 21% 3%16916882 9,256 8,278 0 961 17 89% 0% 10% 0%16921582 10,043 9,062 0 964 17 90% 0% 10% 0%2179191 1,571 1,558 1 9 4 99% 0% 1% 0%67182 11,575 11,538 0 15 22 100% 0% 0% 0%31Region 9 (MN, ND, SD) Specific PCAsCOMID TotalArea Non‐Ag MajorCrop OtherCrops %Non‐Ag %MajorCrop %OtherCrop14144901 614,187 116,116 365,672 132,399 19% 60% 22%14415209 20,928 2,315 8,682 9,931 11% 41% 47%14415927 30,888 3,282 13,515 14,091 11% 44% 46%14428870 430,519 68,455 181,822 180,242 16% 42% 42%14828149 3,219,902 625,848 1,269,441 1,324,614 19% 39% 41%6658333 731,514 463,029 77,423 191,063 63% 11% 26%6667833 7,149,129 1,812,604 3,285,680 2,050,846 25% 46% 29%6667867 7,126,189 1,805,159 3,273,340 2,047,690 25% 46% 29%7038041 2,077,005 1,619,844 199,025 258,135 78% 10% 12%7039505 15,701,965 5,149,688 7,005,220 3,547,057 33% 45% 23%7065884 17,307,241 5,429,108 7,790,269 4,087,863 31% 45% 24%7077518 18,765,799 5,702,757 8,447,763 4,615,279 30% 45% 25%7094291 16,397 16,391 0 5 100% 0% 0%7094301 15,452 15,447 0 5 100% 0% 0%7094305 22,201 22,191 0 9 100% 0% 0%7094455 811 811 0 0 100% 0% 0%7094459 49,856 49,852 0 4 100% 0% 0%7105265 7,246 7,239 0 6 100% 0% 0%7111417 10,936 10,919 0 18 100% 0% 0%7111443 1,204 1,203 0 1 100% 0% 0%7111483 935 934 0 1 100% 0% 0%7111509 12,689 12,689 0 1 100% 0% 0%7111709 10,479 10,467 0 12 100% 0% 0%7111777 7,483 7,478 0 5 100% 0% 0%7115443 4,078 4,075 0 2 100% 0% 0%7145072 33,484 33,389 1 94 100% 0% 0%7145080 259,320 257,642 0 1,678 99% 0% 1%7145088 27,265 27,189 1 75 100% 0% 0%7152000 11,794 11,699 0 95 99% 0% 1%7152014 211,022 209,283 0 1,740 99% 0% 1%7158314 1,274 1,270 0 4 100% 0% 0%7158454 14,852 14,813 0 39 100% 0% 0%7158468 2,896 2,890 0 5 100% 0% 0%7158574 4,650 4,609 0 40 99% 0% 1%7163988 2,805,256 2,796,356 4 8,896 100% 0% 0%7748114 5,066 5,050 3 13 100% 0% 0%7748122 6,775,728 6,601,387 52,523 121,819 97% 1% 2%9398232 15,877,315 5,182,141 7,104,099 3,591,076 33% 45% 23%•Refined PCAs are feasible as a Tier 3 assessment option•Limitations and accuracy concernsare real, but not insurmountable•Identify vulnerable monitoring locations•Analysis identifies range of land-use patterns which could be used todesign monitoring programs focused on highest potential exposure•Identify areas requiring possible stewardship activities thru refineduse patterns•Analysis may result in areas still not resulting in a safe assessmentrequiring focused use pattern adjustments•Protect important use areas that falloutside of potentially vulnerabledrinking water supplies•Focus analysis may result in important markets being protected fromunnecessary use pattern changes as they may fall outside of surfacedrinking water supplies32Conclusions33Questions?