Prioritization Workgroup Surface Water Protection Program DPR Environmental Monitoring Branch...
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- Slide 1
- Prioritization Workgroup Surface Water Protection Program DPR
Environmental Monitoring Branch Presented by Yuzhou Luo
5/18/2015
- Slide 2
- Workgroup: Xin Deng, Robert Budd, Michael Ensminger, April
DaSilva, Yuzhou Luo Data analysis: Kimberly Osienski, Emily Lisker,
Emerson Kanawi Reviewers: Frank Spurlock, Kean Goh, Nan
Singhasemanon, David Duncan, Sheryl Gill, Janet OHara, Rich Breuer,
Tessa Fojut, Danny McClure, Terri Reeder
- Slide 3
- Project overview Phase-1 and phase-2 studies Phase 3,
watershed-scale prioritization Discussions
- Slide 4
- Where, when, and what to sample? Early efforts e.g., Assessment
of acute aquatic toxicity of current-use pesticides in California,
with monitoring recommendations (Starner, 2007)
- Slide 5
- Where, when, and what to sample? Early efforts Prioritization
workgroup Establish computer programs to integrate and facilitate
the automation of updating the agricultural and urban monitoring
priority lists (workgroup charter, 2012)
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- Where, when, and what to sample? Early efforts Prioritization
workgroup Evolution Phase 1 (use and toxicity), May 2013 Phase 2
(predicted/observed exposure), July 2014 Phase 3 (watershed), March
2015 Computer program, version 3.0
http://www.cdpr.ca.gov/docs/emon/surfwtr/monitoring_methods.htm
- Slide 7
- Executable file (
- Results for statewide agricultural uses 2010-2012 Use (lb)
-> use score (1~5) Benchmark (ppb)-> toxicity score
(1~8)
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- [priority score]=[toxicity score]*[use score] Toxicity score =1
(lower toxicity) to 8 (higher toxicity) based on the lowest
Benchmark Toxicity scoreThe lowest Benchmark value (ppb) 8
(higher)1000 (Starner, 2007; 2008)
- Slide 11
- [priority score]=[toxicity score]*[use score] Use score=1
(lower use) to 5 (higher use), dependent on user-defined regions
and seasons PercentageUse score 2%5 (higher) 4%4 8%3 16%2 70%1
(lower) default values, can be changed by users
- Slide 12
- Pesticide use data (PUR) (internal users) download from Oracle
database (external users) import from PUR website
(http://www.cdpr.ca.gov/docs/pur/purmain.htm)http://www.cdpr.ca.gov/docs/pur/purmain.htm
Model [Configuration] Check PUR data
- Slide 13
- Pesticide use data (PUR) (internal users) download from Oracle
database (external users) import from PUR website
(http://www.cdpr.ca.gov/docs/pur/purmain.htm)http://www.cdpr.ca.gov/docs/pur/purmain.htm
Saved as monthly data in the model database (data.dat), organized
by years Model [Advanced Options] Download/import PUR data
- Slide 14
- Pesticide use data (PUR) (internal users) download from Oracle
database (external users) import from PUR website
(http://www.cdpr.ca.gov/docs/pur/purmain.htm)http://www.cdpr.ca.gov/docs/pur/purmain.htm
Saved as monthly data in the model database (data.dat), organized
by years Options: user-specified use patterns, years, months,
counties, watersheds, ranking scheme, etc. Model [Advanced Options]
Options for PUR data processing
- Slide 15
- Pesticide use data (PUR) Toxicity data (Acute and chronic)
USEPA aquatic life benchmark (Acute) Benchmark equivalent, based on
FOOTPRINT PPBD (Acute and chronic) USEPA Human Health Benchmark
USEPA Drinking Water Standard, maximum contaminant level goal
(MCLG) Model [Configuration] Toxicity data
- Slide 16
- Pesticide use data (PUR) Toxicity data Chemical properties
IUPAC FOOTPRINT Pesticide Property Data Base (PPDB) Invisible to
users, no options in the GUI Monitoring data DPRs Surface Water
Database (SURF,
http://www.cdpr.ca.gov/docs/emon/surfwtr/surfcont.htm). Latest
public version April 2014
http://www.cdpr.ca.gov/docs/emon/surfwtr/surfcont.htm Model
[Advanced Options] Monitoring
- Slide 17
- DPR surface water monitoring in Imperial County Imperial County
(CA County Code=13), agricultural use, Jan-Mar Data analysis for
historical monitoring results: for all sites in this county
- Slide 18
- Slide 19
- Phase 2: Monitoring recommendation
- Slide 20
- Objective: to classify pesticides with relatively exposure
potentials to surface water, and make recommendations for
monitoring Approach Observed exposure potentials: based on
monitoring data Predicted exposure potentials: based on chemical
properties, use patterns, and application methods, similar to SWPP
Registration Evaluation (RegEval) Model
- Slide 21
- Objective Approach Results Monitoring recommendations TRUE:
this pesticide potentially causes surface water toxicity, is
recommended to be included for monitoring FALSE: excluded for
monitoring Phase-2 notes: reasons to exclude
- Slide 22
- PUR Every year (last updated: May 2015) Also, can be updated by
users USEPA Aquatic life benchmark Every year (last updated: Feb.
2015) SURF When a new version is released (last updated: April
2014)
- Slide 23
- Spatial resolution, from county to watershed
- Slide 24
- Watershed: area draining to a stream Outlet (pour point): one
Inlet: zero (headwater) to multiple Within a watershed: Main stream
vs. tributaries Time of travel Between watersheds Flow direction
Flow accumulation
- Slide 25
- Hydrologic Region (by 2-digit Hydrologic Unit Code, or HUC2):
HUC2=18: California USGS National Map Viewer
- Slide 26
- Hydrologic Region (by 2-digit Hydrologic Unit Code, or HUC2)
HUC2=18: California Hydrologic Sub-region (HUC4) HUC4=1801:
Klamath-Northern California Coast HUC4=1810: Southern Mojave-Salton
Sea HUC6, HUC8, HUC10, HUC12
- Slide 27
- # of HUs 1 10 16 126 1,009 4,415 (USGS, Techniques and Methods
11A3, 2009) HUC2=18
- Slide 28
- Scale ~1:9M
- Slide 29
- HUC12: the minimal spatial unit for modeling No sub-HUC12
spatial variability Monitoring sites: mainstream vs. tributary
Drainage area, including 1 or more HUC12s Water connectivity
(From-to relationship) Scale ~1:0.3M
- Slide 30
- Aggregation from PUR data at section (1x1mi 2 ) level
Applicable for ag. use only
- Slide 31
- Assumption: urban PUR data can be down-scaled by population
density in a county Urban use(HUC12) = f 1 %*PUR(CO1)+f 2
%*PUR(CO2)+ Approach County (58) US Census County Subdivision (397)
HUC12 (4,415)
- Slide 32
- Site Drainage area contributing HUC12s For tributary sites, PUR
data for the base HUC12 (where the site is located) For mainstream
sites, PUR data for the entire drainage area (the base HUC12 and
all upstream ones) User-input data for a monitoring site: the base
HUC12, and whether the site is located on a mainstream or not Model
[Watershed] HUC12-based prioritization
- Slide 33
- Simple sum Total USE=USE(0)+USE(1)++USE(n), where 0 is the base
HUC12 and 1~n are upstream HUC12s With time of travel (T), from
treated HUC12 to the site Total USE=d 0 USE(0)+d 1 USE(1)++d n
USE(n) d i =exp(-kT i ) NHDPlus2NHDPlus2 for T
- Slide 34
- Settings (DPR study #297) Example: Salinas River @ Del Monte,
DPR site code #27_14, [36.7319 -121.7824] Ag. uses; April to
September Input data Base HUC12=180600051509 ArcGIS USGS National
Map Viewer Mainstream site? Yes
- Slide 35
- DPR Study #279 Protocol, Table 4 (Deng, 2015)
http://www.cdpr.ca.gov/docs/emon/pubs/protocol/study297_surface_water.pdf
- Slide 36
- Settings MCC040 (South San Ramon Creek), urban receiving water,
DPR site_code #01_15, [37.70641 -121.92669] Base HUC12=
180500040502 Mainstream site? No Results top-10 model-suggested:
bifenthrin, fipronil, diuron, bromacil, permethrin, cyfluthrin,
pendimethalin, cypermethrin, -cyhalothrin, deltamethrin ALL of the
top-10 have been included in the previous DPR monitoring (DPR Study
#249, #264)
- Slide 37
- Standard watershed delineation (HUC12) Customized watershed (by
sections, ag. only) Drainage area of a site is significantly
smaller than the base HUC12 (e.g., sites for small creeks, see the
next Demo) Improved watershed delineation with local survey data
(e.g., sites in valley floors) Sites in the State of California,
but out of HUC2=18 (e.g.,DPR sites in Palo Verde Outfall Drain in
Imperial and Riverside) Model [Watershed] Customized watershed
- Slide 38
- Alisal Slough @ Hartnell Rd. (DPR site code 27_70) Prepare a
text file by listing all sections in the customized watershed
- Slide 39
- Factors: site location, water body type, drainage area
description, sampling schedule, budget Model settings Years: recent
3 years with PUR data Months: by sampling schedules Water body type
of the monitoring siteOptions for watershed prioritization Drainage
ditch (agriculture)Preferred: customized drainage area Alternative:
prioritization for tributary site Storm drain outfall
(urban)Preferred: none Alternative: prioritization for tributary
site Receiving water, tributary in watershed (agriculture or urban)
Prioritization for tributary site Receiving water, mainstream
(agriculture, urban, or mixed landuse) Prioritization for
mainstream site
- Slide 40
- Objective: to compare statewide spatial distribution of one
chemical (or one chemical group) Priority mapping index = [USE, lb]
/ [TOX, ppb] / [FLOW, cfs], OR [USE, lb] / [TOX, ppb] / [AREA, mi 2
] ChemicalLocation Spatially continuous mappingOneMultiple Regular
prioritizationMultipleOne
- Slide 41
- Mapping for chlorpyrifos (DPR Chem_code=253) Results: priority
mapping index in each HUC12 Excel format JSON (JavaScript Object
Notation) format
- Slide 42
- (a) Tributaries(b) Main streams
- Slide 43
- PURwebGISPURwebGIS as an example
- Slide 44
- To compare relative importance of pesticides for surface water
monitoring, NOT predict concentrations Chemical parameters are
considered, but fate/transport processes are not explicitly
simulated Spatially distributed modeling framework first
Field-specific modeling (future development) Limitations of input
data PUR for pesticide use data FOOTPRINT for pesticide property
data USGS watershed delineation and HUC12 characterizations
- Slide 45
- A tool for PUR query and mapping e.g., urban fipronil use in LA
County, May to August of 2010 Top-10 ag. pesticides in Salinas
River watershed in each year Compiled, up-to-date toxicity database
(aquatic toxicity, drinking water, human health) Monitoring data
analysis (detection frequency and benchmark exceedance, in the
user-defined domain)
- Slide 46
- SWPP modeling approach Registration evaluation Phase 1 initial
screening Phase 2 refined modeling Post-use evaluation Monitoring
prioritization (phases 1,2,3) Probabilistic risk assessment Label
rate based, Scenario based PUR based, Spatially distributed USEPA
Spatial Aquatic Model (SAM) USGS Monitoring Prioritization Rough
estimation of risk quotient (RQ) or exposure potential Detailed
modeling of RQ
- Slide 47
- Yuzhou Luo, Ph.D. Research Scientist III CDPR/EM/SWPP
yuzhou.luo@cdpr.ca.gov (916) 445-2090