Summary of Major Analyses and Conclusions in the BLM Technical Support Document

Copper Rulemaking Advisory CommitteeMeeting 1

Dec. 17, 2015

1Presenter: James McConaghie, WQ Specialist

Environmental Solutions, Water Quality Standards and Assessment Section

Collect and assess available data. Understand the range and character of the data. Identify the most sensitive parameters. Estimate missing parameters. Generate criteria from the BLM. Compare BLM results to previous criteria.

Purpose of analyses

1. Acquire and prepare data to run the Biotic Ligand Model

2. Generate criteria using the BLM

3. Understand and apply BLM results

Topics for technical review

Part 1:Preparing data for the BLM

Part 1

Collect and assess available data

Create a BLM database for Oregon

Explore characteristics of the data

Determine sensitivity of the model to the data

Database structure

Site

Sample

Parameter

•Geographical locations where samples were collected.

•Groups of parameters collected at a specific time and location.

•Used to calculate an Instantaneous Water Quality Criterion with the BLM.

•Individual measurements of any of the 10 measured input parameters of the BLM model.

BLM Database

Existing archived data USGS-NWIS database OR-DEQ LASAR database

Current field monitoring OR-DEQ BLM \ Ambient Monitoring OR-DEQ Toxics Monitoring

Data sources

Where has data been collected?

Parameter Sample size Importance:

pH 20,827•Highly sensitive BLM parameter. •Potentially limits the number of samples for calculating BLM criteria.

DOC 4,992•Highly sensitive BLM parameter. •Limits the number of samples usable for calculating BLM criteria.

Specific conductance

21,504 •Estimator of missing geochemical cations and anions.•For filling parameter “gaps” within samples.

Copper 4,169 •To evaluate attainment of BLM criteria and the Fixed Monitoring Benchmark (FMB) procedure.

Hardness 1,957 •To compare BLM-IWQC with the existing hardness-based criteria.

Potential Samples

22,844 •Total number of samples with at least 1 of the above BLM parameters measured.

How many samples are available?

How many Samples Are Available?

# of samples suitable to calculate BLM criteria

20531

929

124

1133

114

2340

200

0

500

1000

1500

2000

2500

Cascades Coastal Eastern Willamette Valley

Region

Cou

nt (n

=)

Samples

Sites

How many samples are available?

Range of BLM parameters

10

100

1000

1.5 IQR

25th %

75th %

Median

Statistical Outliers

Min

Max

Range of BLM parameters

0.1

10.0

1,000.0

Cu DOC Na Ca Mg K Cl SO4 Alk.

Con

cent

ratio

n (m

g/L)

0

10

20

30

Temp

Deg

-C

5

6

7

8

9

10

pH

pH U

nits

10

100

1000

Cond.

Sp. C

ond.

(um

ho\c

m)

Model sensitivity to BLM parameters

1

100

0.0 0.5 1.0

DOC

1

100

0.0 0.5 1.0

pH

1

100

0.0 0.5 1.0

Temperature

1

100

0.0 0.5 1.0

Alkalinity

1

100

0.0 0.5 1.0

Sodium

1

100

0.0 0.5 1.0

Calcium

1

100

0.0 0.5 1.0

Magnesium

1

100

0.0 0.5 1.0

Potassium

1

100

0.0 0.5 1.0

Chloride

1

100

0.0 0.5 1.0Percentile

log

IWQ

C

Sulfate

*The BLM IWQC are highly sensitive to changes in DOC and pH

Sites with complete sets of measured data

164 sites361 samples

Accuracy of estimation required depends on sensitivity

Geochemical Ions less sensitive

DOC & pH more sensitive

Estimate missing parameters

Two Methods Explored:

1. Regression on Conductivity

2. Georegional estimates from summary of existing data

Estimate missing parameters

Specific conductivity is a widely collected parameter

Look at correlation between BLM parameters and specific conductivity

Develop equations to predict concentration of missing parameters

Regression on conductivity

Regression on conductivity: correlation

0

20

40

60

0 25 50 75CCC

DO

C

0

25

50

75

0 25 50 75CCC

Alk

.

0

25

50

75

0 25 50 75CCC

Ca

0

25

50

75

0 25 50 75CCC

Na

0

25

50

75

0 25 50 75CCC

Mg

0

25

50

75

0 25 50 75CCC

K

0

25

50

75

0 25 50 75CCC

Cl

0

25

50

75

0 25 50 75CCC

SO

4

Chronic IWQC from Measured Parameters (μg/L)

Chronic IW

QC from

 Estim

ated

 Param

eters (μg

/L)

DOC Alkalinity Calcium

Sodium Magnesium Potassium

Chloride Sulfate

Regression on conductivity: accuracy

y 0.075 0.97 x ,r2=0.999

RMSE 0.53

0

20

40

60

80

0 25 50 75Measured Chronic IWQC (ug/L)

Estim

ated

Chr

onic

IWQ

C (u

g/L)

Regression on conductivity: accuracy

Substitution of ALL Geochemical Ions in Measured Samples

*IWQC calculated by estimating geochemical parameters from conductivity regression were accurate.

Regression on conductivity: conclusions

Model input data for geochemical ions can be estimated using specific conductivity

Given poor correlation and high model sensitivity to DOC and pH, specific conductance should not be used to estimate DOC or pH values.

To calculate accurate IWQC, use measured values of DOC and pH parameters.

Where measured DOC and pH are not available, it may be necessary to use conservative estimates from best available measured data.

Estimate data for a location based on geography

Regions based on sites that share similar water chemistry: Climate Geology Land Cover Natural communities

Physiographic region estimates

Physiographic regions for BLM

Physiographic regions

DOC

pH

a b c dGroups:

n = 240 n = 930 n = 1146 n = 2372

0.1

1.0

10.0

100.0

DO

C (m

g/L)

n = 369 n = 1159 n = 1562 n = 17665

6

7

8

9

10

Casca

des

Coasta

l

Easter

n

Willa

mette V

alley

pH

a b c dGroups:

*Distribution of DOC and pH data is statistically different in each region

DEQ proposes using four physiographic geo-regions for evaluating estimates of BLM parameters

Using larger regions provides more data for each region, therefore improving accuracy of estimates.

These physiographic regions have statistically different data for specific conductance, DOC and pH.

Therefore, estimates using regional data, rather than statewide data, will be more accurate.

Specific conductance, DOC, and pH data was not statistically different among sites grouped by EPA Level-III Ecoregions

Physiographic regions: conclusions

Physiographic regions: conclusions

In order to calculate accurate IWQC, the BLM should use measured values of DOC and pH parameters

Where measured values are not available, it may be necessary to use a conservative estimate based on the best available measured data for each region.

Part 2:Deriving criteria with the BLM

Part 2

Biotic Ligand Model

Data Inputs Outputs IWQC

Deriving criteria with the BLM

How do we determine criteria for sites missing data?

Two Methods:1. Estimate Missing Input Parameters 2. Assign Defaults based on Model Outputs From sites where there is sufficient data Regional basis

Biotic Ligand Model

Data Inputs Outputs IWQC

Estimate missing ions with conductivity data Estimate DOC using regional estimates Estimate pH and temperature from regions or

nearby stations

1. Estimate model inputs for missing parameters

Biotic Ligand Model

Data Inputs Outputs IWQC

1. Physiographic region estimates

n = 343 n = 343 n = 343

0.1

1.0

10.0

100.0

Actual

IWQC

OR med

ian

OR 10th%

DOC Estimates

log1

0 IW

QC

(ug/

L)

Estimates need to be protective over a wide range of spatial and temporal variability in the data.

The estimates are meant to be conservative, not accurate.

1. Physiographic region DOC estimates: conclusions

Calculate IWQC for all samples with sufficient data

Apply a percentile of the population of measured criteria to use as default criteria

2. Default criteria from model outputs

Biotic Ligand Model

Data Inputs Outputs IWQC

n = 205 n = 929 n = 1133 n = 2340

DL (0.05 ug/L)

QL (1.5 ug/L)

0.1

0.5

1.0

5.0

10.0

25.0

50.0

100.0

Cascades Coastal Eastern Willamette ValleyRegions

Chr

onic

IWQ

C2. Default criteria from model outputs

10th%

25thth%

75thth%

95th %

Median

Copper IWQC for the different physiographic regions have statistically different sample medians

Median and 10th % IWQC values were near or below quantification limits for copper

IWQC values can vary widely within and among sites.

2. Default criteria from outputs: conclusions

Part 3:Applying Criteria from the BLM

Part 3

Comparing BLM criteria to HB criteria

Compare BLM Criteria to Hardness-Based Criteria

Assess changes in attainability

Identify vulnerable conditions where HBC are not protective

Identify vulnerable regions / locations

0

25

50

75

5 10 15 20

Chronic Hardness Criteria (ug/L)

Chr

onic

BLM

IWQ

C (u

g/L)

NMFSProposed Default:

1.45 ug/L

Comparison of hardness-based and BLM derived chronic criteria

Comparing BLM criteria to HB criteria

BLM less stringentn=164

BLM more stringentn=178

Totaln=342

LOOKOUT CREEK NEAR BLUE RIVER, OR

LITTLE ABIQUA CREEK NEAR SCOTTS MILLS, OR

Siuslaw River at Tide boat ramp

COLUMBIA RIVER @ BEAVER ARMY TERMINAL NR QUINCY,OR

Umatilla River at Westland Road (Hermiston)

WILLAMETTE RIVER AT PORTLAND, OR

ZOLLNER CREEK NEAR MT ANGEL, OR

123

1.62.02.4

510

510

01020304050

05

1015

5101520

2001 2003 2005 2007 2009 2011 2013 2015

Chr

onic

Cu

Crit

eria

(ug\

L)

Criteria HBC BLM-IWQC

Comparing BLM criteria to HB criteria

Comparing BLM criteria to HB Criteria

Comparing BLM and HBC: conclusions

BLM criteria generally less stringent than HBC• BLM expected to more accurately measure Cu toxicity

Temporal variability of BLM > HBC

HBC not protective for some locations• Low DOC , <1.5mg/L• Neutral pH, <7.4, and below

Depends on sample chemistry, not location

Comparing BLM criteria to copper

Calculate criteria for sites with sufficient data

How does copper concentration in the environment compare to criteria developed by the BLM?

Comparing BLM criteria to copper

Where:TU > 1 = exceeds the water quality criteria TU ≤ 1 = meets the water quality criteria

i

ii IWQC

CuTU

Comparing BLM criteria to copperChronic Toxic Units

BLM criteria and copper: conclusions

Region Samples (n) [Cu] > IWQC %

Cascades 205 15 7.3

Coastal 929 5 0.5

Eastern 1133 8 0.7

Willamette Valley 2340 64 2.7

The BLM predicts a relatively low rate of samples currently exceed criteria Cascades: low DOC? Willamette: more copper sources?

Key conclusions of the technical review

Biotic Ligand Model

Data Inputs Outputs IWQC

DEQ developed a database of existing archived and current monitoring data that could be used to calculate BLM-based criteria.

The BLM is most sensitive to DOC and pH, and this sensitivity was verified in Oregon’s dataset.

The derivation of BLM-based criteria for most locations requires estimation of some missing parameters

Measurements of specific conductance were found to provide strong correlation to geochemical ions and alkalinity

Regional observations of DOC may provide an estimation method where measured DOC data are insufficient.

Key conclusions: acquiring data

DOC estimates derived from EPA and DEQ databases are generally conservative in order to ensure they are protective over the potential range of conditions at a site.

Given the high spatial and temporal variability of DOC, collection of sufficient DOC is necessary to establish accurate:

Water Quality CriteriaWater Quality Based Effluent LimitsAssessment of copper water body impairmentsSensitive environmental conditions

Key conclusions: generating criteria

BLM-derived criteria were frequently higher than Oregon’s hardness-based criteria (total recoverable copper)

Existing hardness-based criteria may not be protective of aquatic life in locations with very low DOC and low pH.

Temporal variation in criteria must be considered when applying BLM results.

Key conclusions: applying criteria

The median and 10th percentile of statewide IWQCs are near or below typical quantification limits (QL) of ~1.5-2 μg/L for copper.

The number of samples where copper concentrations exceed BLM criteria generated for sites where DEQ had sufficient data to derived BLM criteria is relatively low.

BLM-derived criteria can vary widely across / within waterbodies.

Key conclusions: applying criteria

AcknowledgementsExternal Review PanelKathleen Collins EPA, Region 10Luis CruzJoe Beaman EPA, Headquarters

Jeff Lockwood National Marine Fisheries Service, NOAAChris Mebane U.S. Geologic Survey, USGSDianne Barton Columbia River Intertribal Fish CommissionDr. Bill Stubblefield Oregon State UniversityDr. Jeff Louch,Dr. Barry Malmberg

National Council for Air and Stream Improvement, Inc.

Bob Baumgartner Clean Water ServicesDr. Robert Gensemer,John GondekAmanda Kovach

GEI Consultants, Inc.

Scott TobiasonRobert SantoreDave DeForest

Windward Environmental, LLC

Oregon DEQ Internal Review PanelDebra Sturdevant Water Quality Standards and AssessmentsJames Bloom Watershed ManagementErich Brandstetter Surface Water ManagementGreg Coffeen Water Quality MonitoringSteve Schnurbusch Permits and Compliance – DEQ Western Region

Karla Urbanowicz Water Quality Standards and Assessments

Questions?

Windward Environmental, LLC