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# Estimation of Upper Percentiles of Chlorpyrifos Surface Water Concentration from Yearly 

# Monitoring Program Data Paul Mosquin 1 

# G. Gordon Brown 1 

# Roy Whitmore 1 

# Nick Poletika 2

1. RTI International 2. Dow AgroSciencesRTI International 

# Overview

 

# Describe a method for obtaining point and interval estimates for ‘peak’ chlorpyrifos surface water concentrations.

– 

## Use historical datasets, possibly few samples per site

- year.

– 

## Estimate 95 th 

## , 99 th 

## , 99.9 th 

## upper centiles.

 

# Apply method to compare centile estimates among groups of sites

– 

## Change in chlorpyrifos usage due to label changes of 2001, specifically its withdrawal from household use.RTI International 

# Overview (cont)

Issues

– 

## Sampling is generally not from a probability design

– 

## Potentially few observations per year at a given site

– 

## Non

- detects are common 

# Approach

– 

## Estimate aggregate quantities across groups of site

- years of interest.

– 

## Assign weights to account for varying frequencies of sampling.

– 

## Given sampling weights, use well

- established survey design principles to find estimates and confidence intervals.

– 

## Aggregate quantities tend to be larger than averages of site

- year quantities.RTI International 

# Historical Data

1. 

# NAWQA/NASQAN data (USGS)

 National coverage

 Surrogate for drinking water intake locations 

### 2. 

# Ohio Streams Data (NCWQR)

 Regional coverage

 Targeted to storm hydrology 

### 3. 

# Pesticides in Salmonid

- bearing Streams data (WSDA)

 Regional coverage

 Endangered species assessmentRTI International 

# National Water

- Quality Assessment (NAWQA/NASQAN)

http://water.usgs.gov/nawqa/map/cyc1_browse.gifRTI International 

# National Water

- Quality Assessment (NAWQA/NASQAN)

http://water.usgs.gov/nawqa/map/cyc2_browse.gifRTI International 

# National Center for Water Quality Research

Water Quality Laboratory, Heidelberg College NCWQR Website 9/27/05RTI International

WA State Departments of Ecology and Agriculture (2010) Pesticides in Salmonid

- Bearing Streams 2006

- 2008 Triennial Report. 

# Washington Pesticides in Salmonid

- bearing StreamsRTI International 

# Data Set Summary

Program Years Total Sites Total n Median (days per year) Range

(days per year)

NAWQA/ NASQAN 1991

- 2010 2,098 27,551 3 1 to 77
NCWQR 1983

- 2008 11 13,391 111 1 to 204 Washington State 2003

- 2008 22 1,724 29 12 to 63RTI International 

# Description of Approach

 

# Survey sampling approach (finite population)

– 

## Randomness is due to sampling.

– 

## Associate sampling weights with measured values to account for varying sampling frequency:

 If a probability design (systematic sampling) then use probability weights

 If not a probability design then use time

- interval weights (ILSI, 1999; Larson et al, 2004)



###  

# Point estimates:

– 

## Directly from survey

- weighted distribution function.

– 

## Quantity estimated is upper p th 

## percentile of aggregate data.RTI International 

# Description of Approach

 

# Interval Estimates:

– 

## Standard survey weighted approach of Woodruff (1952)

– 

## Performs very well for moderate to extreme tails of distribution (Sitter and Wu, 2001).

 

# Key Assumption:

– 

## Possible pseudo

- random design.

– 

## Time

- interval weights. Give slight overestimation peak usage 

## period and high frequency monitoring period coincide.RTI International 

# Non

- Detects / Level of Quantitation

 

# PROBLEM: Non

- detects comprise majority of data, at times more than 95%

– 

## Below level of detection (LOD, MDL, LT

- MDL)

– 

## Under level of quantitation (LOQ, LRL)

 

# Approach:

– 

## Only require upper tail of estimated distribution

– 

## Estimates under LOD marked as such

– 

## Estimates under LOQ footnoted

 

# Calculated percentiles two ways:

– 

## Below LOD set equal to i ) zero, or ii) LOD

– 

## Results did not show much differenceRTI International 

# Results Using All Observations for Three Data Sets

Washington 95 th 99 th 99.9 th
Percentile (L , P, U) (0.017, 0.023, 0.032) (0.050, 0.057, 0.077) (NA, NA, NA) 

### Washington: Pesticides in Salmonid

- bearing Streams Heidelberg 95 th 99 th 99.9 th Percentile (L, P, U) (<LOD, <LOD, 0.023) (0.049, 0.090, 0.191) (NA, NA, NA) NAWQA 95 th 99 th 99.9 th Percentile (L, P, U) (0.007, 0.008, 0.009) (0.026, 0.030, 0.037) (0.129 , 0.237, 0.366)



### Heidelberg, NCWQR 

### NAWQA/NASQAN

The 95 th and 99 th h percentiles are below LOQ.RTI International 

# Example Using NAWQA/NASQAN

 

# Changes regarding use of chlorpyrifos in urban settings

 

# Use covariates to group sites

– 

## Land Use: Agricultural or Urban

– 

## Time Period: 1991

- 2001 or 2002

- 2010

Type Period 95 th 99 th 99.9 th 

### Ag 1991

- 2001 ( 0.009, 0.011 , 0.014) ( 0.034, 0.047 , 0.086) (0.265, 0.265 , 0.270)
2002

- 2010 ( 0.008, 0.011 , 0.032) ( 0.008, 0.049 , 0.196) (0.129, 0.209 , 0.338) 

### Ur 1991

- 2001 ( 0.013, 

## 0.017 , 0.024) ( 0.038, 

## 0.079 , 0.196) (0.168, 

## 0.295 , 0.570) 2002

- 2010 (<LOD, 

## <LOD , <LOD) ( 0.008, 

## 0.009 , 0.012) (0.015, 

## 0.021 , 0.024) 

### Comparison of Agriculture / Urban

Non

- detects set to 0.000 95 th and Urban 2002

- 2010 are below LOQRTI International 

# Example Using NCWQR

 

# Groups are:

– 

## Agricultural, Drainage area <1000 sq. mi. [2 sites]

– 

## Agricultural, Drainage area ≥1000 sq. mi. [6 sites]

– 

## Mixed (Agricultural use above station <60%) [3 sites]
Comparison of Agriculture / Mixed

. Type 95 th 99 th 99.9 th 

### Ag <1000 mi 2 (<LOD, <LOD , 0.007) 0.043, 0.071 , 0.087) (NA, NA , NA) 

### Ag ≥ 1000 mi 2 (<LOD, <LOD , 0.004) ( 0.044, 0.085 , 0.143) (NA, NA , NA) 

### Mixed (<LOD, 0.025 ,0.058) (0.042, 0.189 ,0.50) (NA, NA , NA)

Non

- detects set to 0.000RTI International 

# Example Using Washington State

 

# Comparison agricultural vs urban watershed land use

Agricultural: 4 watersheds, 18 sites Urban: 1 watershed, 4 sites Non

- detects set to 0.000 

### Type 95 th 99 th 99.9 th 

### Agricultural ( 0.023, 0.034 , 0.059) ( 0.059, 0.085 , 0.400) (NA, NA , NA) 

### Urban (<LOD, <LOD , <LOD) (<LOD, <LOD , <LOD) (NA, NA , NA)RTI International 

# Concluding Remarks

 

# A tool for estimation with large sample sizes but relatively few samples per year.

 

# Method provides point and interval estimates of upper percentiles at aggregate level.

 

# No parametric modeling assumptions.

 

# May assume pseudo

- random sampling.

 

# Identified differences due to historical changes in usage pattern.RTI International 

# References

 

## ILSI, (1999) A framework for estimating pesticide concentrations in drinking water for aggregate exposures. An ILSI Risk Science Institute Working Group Report. Washington D.C.

 

## Larson, S.J., Crawford, C.G., and Gilliom, R.J., (2004) Development 

## and application of watershed regressions for pesticides (WARP) for estimating atrazine concentration distributions in streams: U.S. Geological Survey Water

- Resources Investigations Report 03

- 4047, 68 p.

 

## Sitter, R.S., and Wu, C. (2001) A note on Woodruff confidence intervals for quantiles. Statist. Prob. Lett ., 52:353

- 358

 

## Woodruff, R.S. (1952) Confidence Intervals for medians and other position measures. J. Amer. Statist. Assoc.RTI International 

# More Information
Paul Mosquin Research Statistician 919.294.6105 mosquin@rti.org 

# G. Gordon Brown Research Statistician 919.485.5647 ggbrown@rti.orgRTI International