delta rmp technical advisory committee meeting€¦ · support among technical advisors and (3)...

Delta RMP Technical Advisory Committee Meeting

Thursday, March 15, 2018; 10:00 am – 4:30 pm

Sunset Maple Room, Regional San, 10060 Goethe Road, Sacramento, CA

Remote Access: Phone number: (415) 594-5500 Access Code: 943-326-397#

Screen Sharing: https://join.me/sfei-conf-cw1

Agenda

# Agenda Item and Desired Outcomes Attachments Start & Lead

1 Introductions and Agenda Review and agree on agenda and desired outcomes. Introduce facilitator and explain role.

10:00 Stephen McCord

2 Decision: Approve TAC Meeting Summary for June 13, 2017 meeting and confirm/set future TAC meeting dates

Upcoming Scheduled Meetings (Please bring your calendar) ● Next meeting Jun 12, 2018 at Regional San. ● Schedule in-person meeting for the fall AND ● Phone meeting for mid-April to review proposals for

the pesticides interpretive report. Desired outcome:

● Approve TAC meeting summary ● Confirm future TAC/SC meeting dates

Draft TAC Meeting Summary from Dec 12, 2017

10:05 Stephen McCord

3 Information: Steering Committee Update TAC co-Chair will summarize the March 2, 2018 SC meeting including the decisions and action items relevant to the TAC. Desired Outcome:

● Inform TAC regarding SC decisions and activities. ● Explain the rationale and context for agenda items

below.

Draft SC Meeting Summary from February 5, 2018

Teleconference

(SC Meeting Summary from March 2 meeting not

yet available.)

10:15 - 10:30 Stephen McCord Matthew Heberger

Delta RMP Technical Advisory Committee Meeting Agenda Package,

https://join.me/sfei-conf-cw1

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4 Technical Subcommittee and Monitoring Updates

Brief updates on subcommittees and monitoring activities

Desired outcome: ● Review running table of past and upcoming sampling

events. ● Inform TAC of subcommittee activities and

recommendations.

Table: Samples collected and schedule of planned

sampling events

10:30 – 10:45 Mercury: Stephen McCord Nutrients: Janis Cooke

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Discussion: Ranking for monitoring proposals for FY17/18

TAC members will have an opportunity to fill in the decision grid on their own through the end of March. By having each TAC member to fill in the decision grid questionnaire, we will create a package of information to forward to the Steering Committee showing (1) strengths and weaknesses, (2) level of support among technical advisors and (3) supporting and dissenting viewpoints. During this hour, we will demo the use of the decision grid

Desired Outcome: • Demo the use of the “Decision Grid” questionnaire

• Remind committee members of the conflict of interest policy in the Delta RMP Charter (duty to disclose and to recuse)

Decision Grid for Ranking Monitoring Proposals

Delta RMP Charter,

Sections 7.B.1 and 8.E, Conflict of Interest Policy

10:45 – 11:00

6 Discussion: Review monitoring proposals for FY 2017-18 (1)

ASC has been working with the technical subcommittees this spring to craft proposed monitoring designs that help answer the Delta RMP’s management and assessment questions within the planning budgets set by the SC.

Presentations:

• Nutrients: Phil Trowbridge (30 min.) • Mercury: Jay Davis / Stephen McCord (30 min.)

Desired Outcome:

• Discuss proposed monitoring plans, and answer any questions to form the basis for scoring by TAC members.

Draft Monitoring Design proposals

11:00 – 12:00

Lunch 12:00 – 1:00

7 Discussion: Review monitoring proposals (2) • Contaminants of Emerging Concern (CECs): Brian

Laurenson Draft CEC Monitoring Plan

1:00 - 2:00

8 Discussion: Review monitoring proposals (3)

• Pesticides: Matt Heberger / Stephen McCord Draft pesticide monitoring

design concepts presentation

2:00 – 3:00


http://www.waterboards.ca.gov/centralvalley/water_issues/delta_water_quality/delta_regional_monitoring/program_docs/drmp_charter.pdf

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Break 3:00 - 3:15

9 Recruiting Science Advisors

The FY17/18 Workplan includes $10,000 to pay honoraria and travel for 2–4 independent science advisors. The advisors would be selected by the Steering Committee with input from the TAC and would commit to a 3– to 4–year term. Having advisors work with the Program over multiple years is efficient because they will become familiar with the Program and be able to help with adaptive management and review technical reports. The Bay RMP uses this approach to have ongoing, independent peer review of plans and final reports.

Desired Outcome:

• Recommendation to the Steering Committee on the top 4 advisors to select in each focus area.

Science Advisor job description

List of Science Advisor candidates who have

confirmed their availability and interest

Resumes and CV’s of

candidates

3:15– 3:45

Matt Heberger

10 Decision: Recommendation on Year 1 Mercury Data Report ASC has produced a final draft of mercury in fish and water in the Delta from August 2016 to April 2017. The report presents the methods and results for the first year of monitoring, and includes a section on data QA/QC. The report has been reviewed by the mercury subcommittee and revised to incorporating comments from several reviewers. Desired Outcome: • Recommendation from the TAC to the SC to approve and publish the report.

DRAFT Report: Mercury

and Methylmercury in Fish and Water from the

Sacramento-San Joaquin Delta: August 2016 –

April 2017 (20 pages)

Appendices (33 pages)

3:45 – 4:15

Matt Heberger

Jay Davis

11 Information: Status of Deliverables and Action Items

Desired outcomes:

● Inform TAC about the status of RMP deliverables. ● Review action items from today’s meeting.

Delta RMP Stoplight Reports

4:15 – 4:20

Matthew Heberger

12 Updates and wrap-up

Desired outcomes: ● Recap of message points (TAC to SC) ● Plan agenda items for future meetings

4:20–4:30 Stephen McCord, Joe Domagalski

Adjourn 4:30


Meeting Materials for Item 4

Delta RMP Technical Advisory Committee Meeting Agenda Package, Page 14

Past Monitoring EventsTable updated 3/1/2018

Date Monitoring Element Frequency CommentsAug 22-23, 2016 Mercury (water) - quarterly QuarterlyAug 22-23, 2016 Mercury (fish) - annual AnnuallySept 13, 2016 Mercury (fish) - annual AnnuallyNov 14-15, 2016 Mercury (water) - quarterly QuarterlyFeb 28, 2017 Mercury (water) - quarterly QuarterlyApril 25, 2017 Mercury (water) - quarterly QuarterlyAug 14-18, 2017 Mercury (fish) - annual AnnuallyOct 18-19, 2017 Mercury (water and sediment) 8x per yearAdditional dates TBD

Jul 28, 2015 Pesticides MonthlyAug 18, 2015 Pesticides MonthlySep 23, 2015 Pesticides MonthlyOct 21, 2015 Pesticides MonthlyNov 10, 2015 Pesticides MonthlyDec 15, 2015 Pesticides MonthlyJan 19, 2016 Pesticides MonthlyFeb 17, 2016 Pesticides MonthlyMar 7, 2016 Pesticides MonthlyApr 19, 2016 Pesticides MonthlyMay 18, 2016 Pesticides MonthlyJun 15, 2016 Pesticides MonthlyJul 13, 2016 Pesticides MonthlyAug 17, 2016 Pesticides MonthlySep 20, 2016 Pesticides MonthlyOct 18, 2016 Pesticides Monthly Default sampling dateNov 14, 2016 Pesticides Monthly Default sampling date


Dec 16, 2016 Pesticides Monthly Deviated from default sampling date to capture major runoff eventJan 9, 2017 Pesticides Monthly Deviated from default sampling date to capture major runoff eventFeb 28, 2017 Pesticides Monthly Deviated from default sampling date because some of the sites were inaccessible Mar 14, 2017 Pesticides Monthly Default sampling dateApr 25, 2017 Pesticides Monthly Default sampling dateMay 16, 2017 Pesticides Monthly Default sampling dateJun 13, 2017 Pesticides Monthly Default sampling dateNo sampling was scheduled for FY17/18.

April 6-8, 2015 Pathogens Monthly Default sampling dateMay 4-6, 2015 Pathogens Monthly Default sampling dateJune 1-3, 2015 Pathogens Monthly Default sampling dateJuly 6-7, 2015 Pathogens Monthly Default sampling dateAug 3-5, 2015 Pathogens Monthly Default sampling dateSept 7-9, 2015 Pathogens Monthly Default sampling dateOct 5-7, 2015 Pathogens Monthly Default sampling dateNov 2-4, 2015 Pathogens Monthly Default sampling dateDec 7-9, 2015 Pathogens Monthly Default sampling dateJan 4-6, 2016 Pathogens Monthly Default sampling dateFeb 7-9, 2016 Pathogens Monthly Default sampling dateMarch 7-10, 2016 Pathogens Monthly Default sampling dateApril 4-7, 2016 Pathogens Monthly Default sampling dateMay 2-5, 2016 Pathogens Monthly Default sampling dateJune 6-8, 2016 Pathogens Monthly Default sampling dateJuly 5-7, 2016 Pathogens Monthly Default sampling dateAug 1-3, 2016 Pathogens Monthly Default sampling dateSept 6-8, 2016 Pathogens Monthly Default sampling dateOct 3-5, 2016 Pathogens Monthly Default sampling dateNov 7-9, 2016 Pathogens Monthly Default sampling dateDec 5-7, 2016 Pathogens Monthly Default sampling dateJan 9-11, 2017 Pathogens Monthly Default sampling date


Feb 6-8, 2017 Pathogens Monthly Default sampling dateMarch 6-8, 2017 Pathogens Monthly Default sampling dateNo further pathogens monitoring planned by the Delta RMP.

Planned Monitoring Events

Date Monitoring Element Comments

Sept 19-21, 2017Nutrients High-Frequency Cruise (3 consecutive days) First of 3 planned sets of 3-day cruises

The dates for future 3-day high-frequency cruises (spring, summer and fall) will be chosen in collaboration with the nutrients subcommittee


Attachment B. Evaluation Criteria for Decision Grids Potential evaluation criteria fall into three categories: 1) Management and Assessment Questions, 2) Technical Foundation, and 3) Budget, Priority, Coordination and Other Considerations. The SC will give guidance on whether some criteria have more importance than others, whether or not some criteria can be given more weight, and/or whether some criteria are not applicable. The listed evaluation criteria are important for various reasons but may not be comprehensive. There is flexibility in this process for the SC to add new (or change) evaluation criteria for the Summary Recommendations Decision Grid and the TAC to decide on elements or the need for the Detailed Assessment Grid. Evaluation criteria should be reviewed and refined prior to soliciting and reviewing proposals. The SC can communicate priorities and offer guidance to the TAC in its review process by 1) selecting pre-proposals that address SC priorities and 2) providing the TAC with refined evaluation criteria.

I. Management and Assessment Questions

Management questions are set by the SC, and the TAC may propose assessment questions as testable study components to help answer the management questions. Assessment questions are included as part of the Monitoring Design Summary (revised June 2015); however, these may change over time depending on study needs and to build toward addressing the management questions. Prior to soliciting proposals, the Management and Assessment Questions should be prioritized by the SC to give guidance to both the entities submitting a proposal and the TAC members reviewing the proposals. A) Is the proposal responsive to the Charter management question(s) prioritized by the SC? [0

– not responsive or unclear, 1 – limited responsiveness, 2 – supporting information only, 3 – potentially responsive in later phases, 4 - moderate probability to directly address management questions, and 5 – high probability to directly address management question] 1) Status and Trends. Is there a problem or are there signs of a problem?

a) Is water quality currently, or trending towards, adversely affecting beneficial uses of the Delta?

b) Which constituents may be impairing beneficial uses in subregions of the Delta? c) Are trends similar or different across different subregions of the Delta?

2) Sources, Pathways, Loadings, and Processes. Which sources and processes are most important to understand and quantify? a) Which sources, pathways, loadings, and processes (e.g., transformations,

bioaccumulation) contribute most to identified problems? b) What is the magnitude of each source and/or pathway (e.g., municipal wastewater,

atmospheric deposition)? c) What are the magnitudes of internal sources and/or pathways (e.g. benthic flux) and

sinks in the Delta? 3) Forecasting Water Quality Under Different Management Scenarios

a) How do ambient water quality conditions respond to different management scenarios? b) What constituent loads can the Delta assimilate without impairment of beneficial

uses? c) What is the likelihood that the Delta will be water quality-impaired in the future?

4) Effectiveness Tracking


http://www.waterboards.ca.gov/centralvalley/water_issues/delta_water_quality/delta_regional_monitoring/wq_monitoring_plans/drmp_monitoring_design.pdf

a) Are water quality conditions improving as a result of management actions such that beneficial uses will be met?

b) Are loadings changing as a result of management actions? B) Does the proposal adequately state and support the prioritized Monitoring Design Summary

Assessment Questions or other assessment questions developed to address Management Questions? For example: 1) Are the assessment questions testable or otherwise provide an outcome threshold that can

be measured against? [0 – no measureable thresholds or testable assessment questions, 1 – threshold or testable assessment question is not complete or relies on inference, 5 – threshold is established beneficial use impairment indicator]

2) Does the proposal adequately demonstrate how the results will be presented and interpreted? [0 – no data product or interpretation approach provided, 3 – data product and interpretation approach is not complete, 5 – data product and interpretation approach is clearly stated and responsive to study hypothesis and objectives]

II. Technical Foundation

The technical foundation of the proposal is evaluated based on how well the proposed study answers the management and assessment questions. This evaluation is based on the USEPA Data Quality Objectives guidance, which can be used as a reference for this evaluation. This includes both the assessment of data quality, geographic and temporal characterization, and how well understood the proposed tool “outcomes” are. The following are evaluation criteria that may be modified by the SC or TAC, in consultation with the SC, to appropriately evaluate different types of proposed studies. This section also provides guidance on how to consider each of the evaluation criteria (e.g., scoring) when completing the Detailed Decision Grid (Attachment D) which is then summarized in the Summary Recommendation Decision Grid (Attachment C). Note that the Attachment D examples were developed for evaluating pesticide monitoring plans but can easily be adopted for other types of Delta RMP studies by changing some of the evaluation criteria. Alternative scoring can also be considered, as appropriate for each review. For example, each criterion could be scored on a scale of 1-3 based on the following criteria: 1 – Adequately addresses the criterion, 2 – Partially addresses the criterion, 3 – Does not address the criterion.

A. Are monitoring objectives clearly defined? [0 – not stated, 3 – not clearly stated, 5 – clearly stated]

B. Are the data sources and information inputs clearly stated? [0 – not stated, 3 – not clearly stated, 5 – clearly stated]

C. Is the geographic scope of the study well defined? Does the study characterize conditions within the Delta, tributaries into the Delta, or only a smaller assessment area? [0 – not stated, 3 – not clearly stated, 4 – clearly stated for smaller assessment area outside of Delta, 5 – clearly stated and within the Delta]

D. Is the temporal scope and resolution of the study well defined? Does the study clearly define the conditions of interest (e.g. high flows)? Can the results of the study be used to evaluate trends over the timescale of interest or target magnitude of change? [0 – not stated, 1 – not clearly defined, 3 – clearly defined but does not capture resolution or time


https://www.epa.gov/quality/guidance-systematic-planning-using-data-quality-objectives-process-epa-qag-4

period of interest, 5 – clearly stated and responsive to resolution and time period of interest]

E. Is the analytical approach adequately described and developed? [0 – no methods described, 1 – significant method omissions, 3 – methods not well established or rely on additional information, 5 – as described methods can achieve study objectives]

F. How well established and understood are the monitoring tools? [0 – tools are not described well enough to evaluate, 1 – tools require additional information or inference to draw conclusions or are known as unreliable, 3 – tools are available with inter-laboratory calibration studies, 5- tools are well-accepted methods such as EPA test procedures or the equivalent.]

i. Does the study employ standard analytical methods? How well tested are the methods?

ii. How well are outcomes from monitoring tools linked to environmental effects? iii. Are effect thresholds known that reliably characterize beneficial use impairment? iv. How well are effect end points linked to impacts on beneficial uses – if not, are

required additional studies to provide such linkage well-articulated? G. Are measurement quality objectives clearly stated to ensure that data collected are of

sufficient quality and quantity to support the study objectives? [0 - not provided, 1 – insufficient, 3 – minimum recommended to support study objective, 5 – exceeds minimum requirements and provides robust documentation to reliably quantify method performance]

H. Does the proposal clearly state how the data will be collected? [0 – not stated, 3 – not clearly stated, 5 – clearly stated]

III. Budget, Priority, Coordination, and Other Considerations

A) Does the proposal meet the budget specified by the SC? [0 – no budget provided, 1 insufficient budget information, 3 – may meet budget specified under phasing or certain conditions, 5 – meets budget specified under all scenarios]

B) Priority/timeliness - Is there urgency to conducting the monitoring, such as to inform planned policies or regulations? [0 – timeliness not clear, 1 – no urgency, 3 – moderate urgency (3-5 years), 5- high urgency (<2 years)] 1) Does the monitoring respond to a stated SC priority? 2) Is there enough lead time to generate the information needed to support upcoming

decisions? 3) Do the monitoring elements need to be completed in a certain order relative to (and

contingent upon) other ongoing or future activities? 4) Can the monitoring be coordinated with other efforts to increase data power or reduce

overall study cost or duration? C) Will the study build upon, add to, and/or compliment other studies conducted by the Delta

RMP? [0 – not stated, 1 – does not compliment Delta RMP studies, 3 – builds on previous Delta RMP work, 5 – is critical component to ongoing or needed Delta RMP work]

D) Do the monitoring objectives incorporate consideration of regulatory program requirements (TMDLs, Waste Discharge Requirements, Basin Plan monitoring and


surveillance, etc.)? [0 – not stated, 1 – not required in regulatory program, 3 – assessment information needed for evaluation of programs, 5 – required by permit or Basin Plan]

E) Can the study leverage external studies and resources for added efficiency or additional priority benefits? [0 – not stated, 1 – no external coordination benefit, 3 – some external coordination benefit, 5 - extensive external coordination benefit]

F) Is the monitoring plan complete or is additional information necessary before the study could be implemented? [0 – not stated or unclear, 1 – significant information needed, 3 – moderate information needed, 5 – no additional information needed]


Attachment C. Summary Recommendation Decision Grid Template Evaluation Criteria Score Comments

I. Management / Assessment Questions A. [Relevant Management questions listed here as

directed by the Steering Committee or as appropriate for the proposed study]

B. Are the assessment questions testable or do they otherwise provide an outcome threshold?

C. Does the proposal adequately describe how the results will be presented and interpreted?

II. Technical Foundation A. Are monitoring objectives clearly defined? B. Are the data sources and information inputs clearly

stated? C. Is the geographic scope of the study well defined?

Does the study characterize conditions within the Delta, tributaries into the Delta, or only a smaller assessment area?

D. Is the temporal scope and resolution of the study well defined? Does the study clearly define the conditions of interest (e.g. high flows)? Can the results of the study be used to evaluate trends over the timescale of interest or target magnitude of change?

E. Is the analytical approach adequately described and developed?

F. How well established and understood are the monitoring tools?

G. Are measurement quality objectives clearly stated to ensure that data collected are of sufficient quality and quantity to support the study objectives?

H. Does the proposal clearly state how the data will be collected?

III. Budget, Priority, Coordination, and Other Considerations

A. Does the proposal meet the budget specified by the SC?


Evaluation Criteria Score Comments

B. Priority/timeliness - Is there urgency to conducting the monitoring, such as to inform development of planned policies or regulations?

C. Will the study build upon, add to, and/or compliment other studies conducted by the Delta RMP?

D. Do the monitoring objectives incorporate consideration of regulatory program requirements (TMDLs, Waste Discharge Requirements, Basin Plan monitoring and surveillance, etc.)?

E. Can the study leverage external studies and resources for added efficiency or additional priority benefits?

F. Is the monitoring plan complete or is additional information necessary before the study could be implemented?

Scoring Example: Each criterion could be scored on a scale of 1-3 based on the following criteria: 1 – Adequately addresses the scoring criterion 2 – Partially addresses the scoring criterion 3 – Does not address the scoring criterion


Meeting Materials for Item 6: Nutrients Proposals


Summary of Proposals for FY18/19 Delta RMP Special Studies for Nutrients

Title Summary Funding Request

Leveraged Resources

Ranking

Merging High-Frequency Water Quality Data and Models to Gain Insights into the Factors Regulating Phytoplankton Blooms in the Delta in WY2016

For this study, we propose to combine a hydrodynamic-biogeochemical model of the Delta in WY2016 with water quality measurements in order to understand what caused large phytoplankton blooms in this year. The approach will be to apply a biogeochemical model developed for WY2011 to WY2016 and then to compare the model predictions to measurements made throughout the Delta. Comparisons between the model and observations will provide insight into important mechanisms for phytoplankton productivity including physical and other influencing factors. The study will be a first step toward implementing priority research recommendations in the Delta Nutrient Research Plan. The study design leverages $24,000 of in-kind modeling resources from the Department of Water Resources and takes advantage of $900,000 of studies that are funded by other parties. Finally, this project implements a recommendation to increase data sharing among different models and monitoring programs.

$186,000

$24,000 (in-kind)

$900,000 (related projects)

3.4 of 4

Intercalibration Study for Chlorophyll Fluorescence Sensors in the Bay-Delta, Phase II

Chlorophyll is an important water quality parameter for assessing the effects of nutrients and for fisheries management in the Bay-Delta. This study is the second phase of a multi-year effort to improve the accuracy, precision, and comparability of chlorophyll data collected in the Bay-Delta. Phase I planning has shown that variability in the methods used for measurement chlorophyll across the Bay-Delta is significant and that reducing this variance is of interest to a wide variety of monitoring agencies. In FY18/19, we propose to tackle a portion of the problem with a series of tasks to help understand and reduce the variance in the measurements of chlorophyll by in-situ sensors and laboratory methods. The proposed tasks include: (1) assessing methods used by different monitoring programs; (2) performing field intercalibration exercises between programs; (3) organizing a laboratory intercalibration study; and (4) preparing a summary report through technical workgroup discussion. Funding is requested for SFEI-ASC and USGS to lead the study. The study leverages $105,000 of in-kind support from the Department of Water Resources and the US Bureau of Reclamation.

$84,800 $105,000 (in-kind) 3.3 of 4

TOTAL $270,800 $129,000

Two other projects were considered by the Nutrients Subcommittee. These projects are not recommended for FY18/19 but remain on the multi-year plan (see next page).

• Sediment Nutrient Inventories, Availability, and Fluxes in the Delta. $113,000-$200,000. Rank 2.3 of 4. • Nutrients Workshop and Summary Article. $46,000. Rank 0.8 of 4.


Multi-Year Plan for Delta RMP Nutrients Subcommittee Projects

Project Type Project FY16/17 FY17/18 FY18/19 FY19/20 FY20/21

Status and Trends

Status and Trends Synthesis Reports

$120k

High Frequency Monitoring $195k

Chlorophyll Intercalibration Phase I: $15k Phase II: $85k Phase III: $50k

Workshop & Summary Article $50k

Sources, Pathways, Loadings, and Processes

WY2016 Water Quality Modeling $186k $60k

Model parameter characterization $150k TBD

Special Studies for Delta Nutrient Research Plan

$100k $300k

Forecasting Scenarios1

Total $120 $210k $271k2 $410k $300k

1. Modeling work for SPLP is building capacity for forecasting scenarios. 2. Actual funding request can be $27k lower ($244k) if the SC agrees to apply $27k left over from the FY16/17 Status and

Trends Synthesis Reports to the FY18/19 projects.


Revision Date: 3/6/18

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Delta RMP Special Study Proposal Merging High-Frequency Water Quality Data and Models to Gain Insights into the Factors Regulating Phytoplankton Blooms in the Delta in WY2016 Summary: For this study, we propose to combine a hydrodynamic-biogeochemical model of the Delta in WY2016 with water quality measurements in order to understand what caused large phytoplankton blooms in this year. The approach will be to apply a biogeochemical model developed for WY2011 to WY2016 and then to compare the model predictions to measurements made throughout the Delta. Comparisons between the model and observations will provide insight into important mechanisms for phytoplankton productivity including physical and other influencing factors. The study will be a first step toward implementing priority research recommendations in the Delta Nutrient Research Plan. The study design leverages $24,000 of in-kind modeling resources from the Department of Water Resources and takes advantage of $900,000 of studies that are funded by other parties. Finally, this project implements a recommendation to increase data sharing among different models and monitoring programs. Estimated Cost: $186,000 Oversight Group: Delta RMP Nutrients Technical Subcommittee Proposed by: SFEI-ASC, USGS, DWR

Background Nutrient management is high-profile issue in the Delta. Nutrients are among the first-order factors that shape phytoplankton productivity, which is important for understanding pelagic organism decline. The Sacramento Regional County Sanitation District is already investing over $1 billion in wastewater treatment upgrades to manage nutrients. The Central Valley Regional Board recently completed a draft Delta Nutrient Research Plan which listed harmful algal blooms, increased aquatic macrophytes, and low dissolved oxygen as other water quality concerns associated with nutrients (Cooke et al., in review). For this study, we are proposing a synthesis of monitoring and modeling tools to better understand the linkage between nutrients and the phytoplankton blooms that occurred in WY2016 taking into account physical and other factors. The approach is directly relevant to Research Recommendation MON1 from the Delta Nutrient Research Plan. This recommendation calls for monitoring to assess “physical, chemical, and biological factors affecting phytoplankton abundance and growth” (Cooke et al., in review). The combination of data synthesis and modeling proposed for this project will provide insight



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into all of these factors. The proposed project is designed to take advantage of two existing efforts that are funded by other parties. The Regional Water Control Boards (RB2 and RB5), Sacramento Regional County Sanitation District, Delta Stewardship Council, and Central Contra Costa Sanitary District are funding a project to develop, calibrate, and validate a biogeochemistry model for the Delta-Suisun in WY2011 (a year with low productivity). SFCWA is funding a project to synthesize data related to phytoplankton blooms in the Delta in WY2016 (a year with higher productivity) and prior years. The total investment for these two projects is nearly $900,000. The study design is to apply the WY2011 biogeochemical model to WY2016 to allow for comparison between model predictions and observations of phytoplankton during this year of higher productivity. The comparison between the model and observations will provide insight into important mechanisms for phytoplankton productivity. Finding a mutual set of model parameters that work for both ends of the spectrum in terms of productivity (i.e., years with low or high productivity) will also help to narrow down the choice of biogeochemical model parameters for the Delta, from which the WY2011 Delta-Suisun modeling effort can also benefit. Finally, this project implements a recommendation from the white paper on modeling that was prepared for the Delta Nutrient Research Plan (Trowbridge et al, 2016). One concept from that report was that being able to share information between different modeling groups “would be economical, lead to more efficient model applications (shorter project timelines), and increase opportunities innovation because more resources would be available for modeling” (p.24-25). This study will put this concept into action by using hydrodynamics from DWR’s SCHISM finite element platform and biogeochemistry from the Deltares Flexible Mesh finite volume platform. The project will develop code to facilitate future data sharing across these two platforms. Further, it will promote the sharing of information between modeling efforts, monitoring and research to help streamline the integration of new findings in biogeochemical models.



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Study Objectives and Applicable RMP Management Questions The objectives of the project and how the information will be used relative to the RMP’s high-level management questions are shown in Table 1. Table 1. Study objectives and questions relevant to RMP management questions.

Delta RMP Management Question & Assessment Question

Study Objectives Example Information Application

Management Question: Which sources and processes are most important to understand and quantify? Assessment Questions: SPLP1- “Which sources, pathways, and processes contribute most to observed levels of nutrients?” SPLP2 - “How are nutrients linked to water quality concerns such as harmful algal blooms, low dissolved oxygen, invasive aquatic macrophytes, low phytoplankton productivity, and drinking water issues?” A. “Which factors in the Delta influence the effects of nutrients on the water quality concerns listed above?”

Set up and run a coupled hydrodynamic and biogeochemical model to simulate the nutrients and phytoplankton in the Delta in WY2016 by combining WY2016 hydrodynamics with a biogeochemical model developed for WY2011. Compare the modeled results for nutrient concentrations and phytoplankton with the measured observations for WY2016. Synthesize important differences between the model and observations to understand the processes that need to be improved in the model. Analyze the modeled results for WY2016 to identify the major factors that caused the observed phytoplankton blooms in that year. Demonstrate data sharing between different model platforms.

This project will accelerate biogeochemical model development in the Delta. If predictions match reality, then modelers will have confidence that the model parameterization is broadly applicable. If not, then modelers will have insights into what processes need to be improved in the model. Managers and researchers will know more about process and factors (especially physical factors) that resulted in the large algae blooms in WY2016. Data collection agencies and modelers will know more about which monitoring stations are useful for validating models. Managers and modelers will gain experience and know the pros/cons of sharing data between model platforms.



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Approach Task 1: Obtain hydrodynamic model input and output files for the Delta in WY2016. DWR will provide input and output files for WY2016 hydrodynamics from the SCHISM model. The hydrodynamics will be validated at multiple locations in the Delta for the following parameters: flow, water level, temperature and salinity. SFEI will work with Deltares to write code to translate the output files to match the requirement of Deltares DWAQ model input. This code is an investment because it can later be used to translate SCHISM output files for other water years. This approach combines the extensive expertise from DWR on Delta hydrodynamic modeling as well as the power of Deltares Water Quality model (DWAQ) to predict sophisticated biogeochemical cycling processes in aquatic systems. Developing systems for sharing data across model platforms is consistent with the “community modeling” approach outlined in the Modeling Strategy White Paper (Trowbridge et al., 2016). Due to the differences in the model platforms, there is a small amount of risk that the SCHISM model output cannot be translated to the Deltares DWAQ format. As a backup, if it is not possible to use the SCHISM model output, the funds can be redirected to a subcontractor to develop the WY2016 hydrodynamics for the Deltares Flexible Mesh model. Therefore, a first step for this task will be for DWR to provide the SCHISM model output for an earlier year (e.g., WY2011) so that Deltares can identify any major barriers right away. Task 2: Prepare boundary condition and validation data for the WY2016 biogeochemical model Measurements of nutrients and nutrient-related parameters in WY2016 are needed to evaluate the model predictions for this year. Fortunately, with funding from SFCWA, USGS is already compiling much of the data that are needed for the modeling. Therefore, for this task, USGS will provide the WY2016 data from USGS and DWR stations that they have compiled for their other project and SFEI will gather other relevant data not already in the USGS database. These data will be formatted to match the input needs for the model and reconciled among data sources, which is not part of the SFCWA effort. The parameters of interest for discrete grab samples include: chlorophyll-a, ammonia, nitrate, phosphate, turbidity, and dissolved oxygen (and potentially others such as zooplankton biomass, benthic grazer data, silica, and organic nitrogen if available). These data will be formatted and incorporated into the database for Delta/Suisun Bay modeling. The parameters of interest for high frequency, in-situ sensor data are: nitrate, turbidity, chlorophyll fluorescence, and dissolved oxygen. High frequency data collected by the USGS, DWR, USBR, and other agencies will be compiled. The quality of the high frequency data will be checked by comparing the measured high frequency data with the discrete sampling data at the same or nearby location or reviewing metadata on datasets that have already gone through this step.



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The geographic focus of this project is the whole Delta. Much of the data needed, especially in the North Delta, including Cache Slough, and the Central Delta, are already being compiled by USGS through the SFCWA-funded study. For that study, data will be aggregated from the following sources: (a) USGS continuous monitoring stations and underway measurements; (b) DWR continuous monitoring stations; (c) discrete sampling and analysis programs of USGS, IEP, DWR, USBR and RTC; (d) other data as suggested by the community. Data types include temperature, conductivity, pH, turbidity, dissolved oxygen nutrients, chlorophyll fluorescence, chlorophyll concentration, dissolved organic matter fluorescence, phytoplankton abundance, zooplankton abundance, stage, discharge, velocity, precipitation, PAR, Kd and others. Task 3: Apply the biogeochemical model that has been calibrated/validated for WY2011 to hydrodynamics in WY2016. A complete biogeochemical model1 for WY2011 will be developed with funding from other sources by December 2018 (see timeline in Table 3). This model can be applied to WY2016 using the SCHISM hydrodynamic output (Task 1) and data prepared in Tasks 2. This application will not attempt to fully validate2 the model for WY16 but rather provide some initial evaluation on the performance of the model by comparing the model results to what was observed (see Task 4). Task 4: Compare model predictions of biogeochemistry in WY2016 to observations. The water quality data compiled in Task 2 will be compared to the model predictions for WY2016 (Task 3). The comparisons will be made at stations in all areas of the Delta using a similar approach as the Delta-Suisun modeling project but there will be a focus on the North Delta, including the Cache Slough Complex, and the Central Delta because these are areas of higher productivity and regions where a large amount of high-frequency data have been collected. The deliverable for this task will be a technical report with:

● Plots of the performance of the model compared to the observations for dissolved nutrient concentrations and chlorophyll concentrations at various locations throughout the Delta, such as:

○ Concentrations of dissolved nutrients and chlorophyll ○ Spatial distribution of dissolved nutrients and chlorophyll ○ Zones of bloom inception ○ Timing of bloom inception and senescence

● Hypotheses to explain the differences between the biogeochemical model output and observed water quality. The explanations will consider mechanistic relationships between physical factors (such as flow), nutrients, grazers, and chlorophyll. The topics on this list can be investigated in more depth with scenario tests using a fully calibrated model in a second phase of the study.

● Insights from the model about processes and factors (especially physical factors) that resulted in the large algae blooms in WY2016 as well as inferred rates of

1 Including all the modules for biogeochemical cycling (nutrient cycling, phytoplankton dynamics, benthic grazing, zooplankton, mineralization, and sediment fluxes, and empirical light field). 2 Data from the boundary conditions will be used to initialize the model; data from interior Delta stations will be used to evaluate and validate the model performance.



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nutrient transformation and uptake. ● The monitoring stations that appear to be especially useful for validating

biogeochemical models. ● Lessons learned and the advantages and disadvantages of sharing data

between model platforms.

The final report for this study will benefit from, not overlap with, the related SFCWA-funded effort. The SFCWA-funded report (due in February 2019) will contain insights into factors that caused the WY2016 phytoplankton blooms based on statistical relationships between phytoplankton abundance and community structure with (a) nutrient concentrations, forms and ratios; (b) temperature; (c) light availability; (d) water source and history; (e) water velocity and wind (as a proxy for turbulence) and discharge; (e) estimated residence time; and (d) events such as stormflows, Yolo bypass outflows and water releases. In practical terms, these insights will give direction on where to look and what to look for in terms of model validation and dominant processes (Tasks 3 and 4). Similarly, the mechanistic modeling work will provide insights into processes that could not be determined from the statistical analysis. In this way, the two projects are complementary and synergistic. In addition to the written report, progress reports to Delta RMP stakeholders will be provided at semi-annual meetings for the Delta-Suisun modeling project, which Delta RMP stakeholders will also be invited. Proposed Deliverables and Timeline Table 2. Deliverables

Deliverable Due Date

Obtain and format WY2016 Hydrodynamics input and output files December 31, 2018

Final Technical Report/Manuscript March 31, 2020 (draft) June 30, 2020 (final)



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Table 3. Timeline

2018 2019 2020

Task J F M A M J J A S O N D J F M A M J J A S O N D J F M A M J

Task 1 - Hydrodynamics X

Task 2 - Model Set Up

Task 3 - Model Application

Task 4 - Reporting X X X X X X

Related Studies

SFCWA Study

Data aggregation

Data analysis

Reporting

Delta-Suisun WY2011 Modeling

Stage 2

Stage 3

Stage 4

Stage 5

Stage 6

X = Deliverable due = Activity Delta-Suisun Modeling Stages Stage 2: Building a complete biogeochemical modeling framework that includes nitrogen cycling, phytoplankton dynamics, grazing behavior, mineralization, and benthic processes. Stage 3: Test runs with Stage 2 model. Identifying dominant processes. Refining input data and model structure. Stage 4: Improve model performance by tuning biogeochemical coefficients. Stage 5: Adding dissolved oxygen. Scenario testing to answer management questions. Stage 6: Final reporting.



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Budget Table 4 shows the estimated costs for this proposed special study. Table 4. Proposed Budget

Task Funding

Requested for USGS

Funding Requested

for SFEI-ASC

Funding for Contractors

Total Funding Requested

In-Kind Contributions

Task 1 - Hydrodynamics $0 $5,000 $35,000 $40,000 $24,000

Tasks 2 & 3 - Biogeochemical Model Set Up and Application

$20,000 $66,000 $0 $86,000 $0

Task 4 - Report $20,000 $30,000 $10,000 $60,000 $0

Total Funding Requested $40,000 $101,000 $45,000 $186,000

Leveraged In-Kind Contributions

$24,000

Budget Justification Task 1

● DWR will provide the WY2016 hydrodynamics model in-kind. ● The funding requested is for a $35,000 subcontract with Deltares to write code to

convert DWR’s SCHISM model output to the Deltares Flexible Mesh (DFM) format and $5,000 SFEI-ASC labor (40 hours of SFEI-ASC modeler time) to handle data transfers and contribute to the coding.

Tasks 2 & 3

● For SFEI-ASC: The funding requested is for 3 months of SFEI modeler time ($51,000) and 1 month of Environmental Analyst time ($15,000) to initialize and run the biogeochemical model for WY2016. This step will also include generating plots of model output versus observations.

● For USGS: The funding requested includes $20,000 to support participation in meetings to plan and evaluate integration of high-frequency data with model output, trouble shoot WY2016 data transfer issues, and assist with additional data compilation.

Task 4

● The final report will be a collaboration between SFEI, USGS, and DWR. SFEI-ASC will be the lead author.

● For SFEI: $30,000 is requested for 130 hours of SFEI-ASC technical staff time and 75 hours of Program Manager/Senior Scientist time.

● For USGS: $20,000 is requested for analysis of modeled versus monitored data, and co-authorship of the final report including time to present the findings to Delta RMP committees and respond to up to two rounds of comments. Funding



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will also support USGS participation in two project meetings: (1) Meeting to compare monitored and modeled results and plan final steps; and (2) Meeting to finalize main conclusions for final report.

● An additional $10,000 is requested for honoraria for consultants and external reviewers of the final report. The specific expertise needed to evaluate the results of this study is not known at this time. These funds would make it possible to bring in experts in phytoplankton, zooplankton, benthic grazers, or another discipline on an as-needed basis. In addition, the funds could be used for expert reviewers of the final report. Potential reviewers could be: Stephen Monismith from Stanford University, Jim Cloern from USGS, Fei Chai from University of Maine, Wim Kimmerer from San Francisco State University, and Lisa Lucas from USGS. Obtaining an in-kind peer-review through CWEMF will also be pursued. Plans for the use of these funds will be discussed with the Delta RMP Nutrients Subcommittee in advance.

Leveraged Funds and In-Kind Contributions Leveraged funds are cash contributions from another source that pay for a part of the scope of work. In-kind contributions are staff time or resources (e.g., boat time, lab analyses) that are contributed to the project to complete the scope of work.

• DWR will contribute the WY2016 hydrodynamic model output from SCHISM as well as input files with an approximate value of $24,000.

While not strictly “leveraging”, the project will use outputs from two other highly-complementary and well-timed studies as an effective launch pad to maximize the impact of this work.

● Delta-Suisun Modeling with funding from Regional Boards (RB2 and RB5), Central Contra Costa Sanitary District, Sacramento Regional County Sanitary District, and Delta Science Program ($800,000 in total).

● WY2016 Algal Bloom Analysis with funding from the State and Federal Contractors Water Agency ($83,700).

Optional Tasks for Future Funding The proposed project will initiate the process of gaining understanding on the mechanisms behind phytoplankton productivity in the Delta. For FY19/20, a second phase of the study could be conducted to:

● Fully validate the WY16 biogeoechemistry model. ● Perform alternative hypothetical scenario runs to isolate the contribution from

each forcing factor on causing the bloom event in 2016.



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Reporting The final report will be prepared in a format such that it can be submitted for publication as a manuscript. This manuscript will be reviewed by the Delta RMP committees following the protocols in the Delta RMP Communications Plan. If the manuscript is delayed, a stand-alone technical report will be prepared for the Delta RMP. Progress reports to Delta RMP stakeholders will be provided at semi-annual meetings for the Delta-Suisun modeling project.

References Cooke, J., C. Joab, and Z. Lu. In review. Delta Nutrient Research Plan, Draft Report.

Central Valley Regional Water Quality Control Board, Rancho Cordova, CA. January 2018.

Trowbridge, P.R, M. Deas, E. Ateljevich, E. Danner, J. Domagalski, C. Enright, W.

Fleenor, C. Foe, M. Guerin, D. Senn, and L. Thompson. 2016. Recommendations for a Modeling Framework to Answer Nutrient Management Questions in the Sacramento-San Joaquin Delta. Report prepared for: Central Valley Regional Water Quality Control Board, Rancho Cordova, CA. San Francisco Estuary Institute-Aquatic Science Center, Richmond, CA. Published online: https://www.waterboards.ca.gov/centralvalley/water_issues/delta_water_quality/delta_nutrient_research_plan/science_work_groups/2016_0301_final_modwp_w_appb.pdf.


https://www.waterboards.ca.gov/centralvalley/water_issues/delta_water_quality/delta_nutrient_research_plan/science_work_groups/2016_0301_final_modwp_w_appb.pdf




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Delta RMP Special Study Proposal Intercalibration Study for Chlorophyll Fluorescence Sensors in the Bay-Delta, Phase II Summary: Chlorophyll is an important water quality parameter for assessing the effects of nutrients and for fisheries management in the Bay-Delta. This study is the second phase of a multi-year effort to improve the accuracy, precision, and comparability of chlorophyll data collected in the Bay-Delta. Phase I planning has shown that variability in the methods used for measurement chlorophyll across the Bay-Delta is significant and that reducing this variance is of interest to a wide variety of monitoring agencies. In FY18/19, we propose to tackle a portion of the problem with a series of tasks to help understand and reduce the variance in the measurements of chlorophyll by in-situ sensors and laboratory methods. The proposed tasks include: (1) assessing methods used by different monitoring programs; (2) performing field intercalibration exercises between programs; (3) organizing a laboratory intercalibration study; and (4) preparing a summary report through technical workgroup discussion. Funding is requested for SFEI-ASC and USGS to lead the study. The study leverages $105,000 of in-kind support from the Department of Water Resources and the US Bureau of Reclamation. Estimated Cost: $84,800 Oversight Group: Delta RMP Nutrients Technical Subcommittee Proposed by: SFEI-ASC, USGS, DWR, and USBR

Background Accurate, precise measurements of phytoplankton biomass are critical to inform important management questions about productivity, nutrient management, and fisheries. Chlorophyll concentration is a widely-accepted proxy for phytoplankton biomass. There are presently more than 40 moored chlorophyll sensors using in-situ fluorescence in the Bay-Delta, belonging to networks maintained by the U.S. Geological Survey (USGS), Department of Water Resources (DWR), and others (Figures 1 and 2). Prior to now there has been no effort to ensure that the groups making these measurements are using calibrations, sampling methods, and data processing techniques that ensure comparable results. Ensuring data comparability will save money and time, and will provide managers with better, high-resolution data for the entire estuary. Therefore, to increase the utility and improve our return on the considerable effort to produce these data, the Delta Regional Monitoring Program and the San Francisco Bay Nutrient Management Strategy Science Program are jointly funding a project with the



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goal of improving the comparability of the chlorophyll data collected by different programs across the region. While a seemingly simple task, achieving this goal requires overcoming several technical barriers to apply common approaches for sensor acceptance and performance criteria, sensor calibration, performance validation, data collection, data quality assurance, data management, and data access. In FY17/18, the Delta RMP and the Nutrient Management Strategy each contributed $15,000 for SFEI-ASC to organize the stakeholders, conduct some initial analyses, and to develop a detailed workplan for FY18/19. The stakeholder outreach process revealed a broad interest from many agencies in:

● Standardizing, improving processes ● Having data from different programs be interoperable ● Improving relationship between in-situ and lab chlorophyll-a ● Coordination ● Improving data accessibility

The survey of 13 monitoring programs found that a variety of methods are being used by the different programs especially in the areas of sensor settings, calibration procedures, sensor cleaning, and QA/post-processing. The method differences were significant enough to make comparing data from different programs difficult. For example, some of the programs conduct 2-point calibrations, others perform a single point test at zero, and others do no calibration check. The laboratories performing extracted chlorophyll-a analyses use two fundamentally different methods (spectrophotometry and fluorometry). Finally, analysis of measurements from the different programs data showed a large amount of variability in chlorophyll fluorescence response (differences as much as a factor of two) between regions of the Bay-Delta and between programs (Figure 3). Variability of this magnitude impedes synthesis of data from across the Bay-Delta without using site-specific calibrations. Overall, the effort in FY17/18 has shown that variability in the methods used for measurement chlorophyll across the Bay-Delta is significant and that reducing this variance is of interest to a wide variety of monitoring agencies. A conceptual model for variability in the chlorophyll fluorescence (Figure 4) provides a way to break this challenging problem into smaller tasks. In FY18/19, we propose to tackle a portion of the problem with a series of tasks to help understand and reduce the variance in the measurements of chlorophyll by in-situ sensors and laboratory methods. This proposal was developed and reviewed by a workgroup with representatives from SFEI-ASC, USGS, DWR, US Bureau of Reclamation (USBR), and the Central Valley Regional Water Quality Control Board.



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Figure 1: Chlorophyll fluorescence sensors in the Delta (from Bergamaschi et al., 2017)



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Figure 2: Chlorophyll fluorescence monitoring stations in the Bay. Continuous monitoring with moored sensors is performed at the red stations. Discrete measurements with sensors are made at ship-based monitoring sites (yellow) and mussel sites (orange). The graphic does not show all stations where chlorophyll fluorescence is monitored in the Delta, the Bay, and the coastal ocean.



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Figure 3: Ratio of sonde relative fluorescence units (RFU) from YSI EXO sondes to extracted chlorophyll measured in the laboratory across multiple programs and multiple locations in the Bay-Delta. The variance shown on this figure is from a combination of factors (see Figure 4). Natural variability among sites is evident when comparing different sites monitored by the same program. There can be natural differences between stations due to differences in salinity, tidal influence, and phytoplankton community. However, this graphic illustrates that some of the variance observed could be due to different protocols used by different programs.



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Figure 4: Conceptual model developed in FY17/18 for variance in extracted chlorophyll-a, in-situ chlorophyll fluorescence, algal biomass, and the relationships between these related parameters.



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Study Objectives and Applicable RMP Management Questions The objectives of the project and how the information will be used relative to the Delta RMP’s management and assessment questions are shown in Table 1. Table 1. Study objectives and questions relevant to Delta RMP management questions

Delta RMP Management Questions & Assessment Questions


Management Question: Is there a problem or are there signs of a problem? Assessment Question: How do concentrations of nutrients (and nutrient-associated parameters) vary spatially and temporally? (S&T1) This study is relevant to these questions because it will improve our ability to discern spatial and temporal trends in chlorophyll using data from multiple programs operating in the Bay-Delta.

Assess the differences in methods used by each program to measure chlorophyll. Determine whether differences in methods between programs result in significant variability in sensor and lab results for chlorophyll.

Water quality and resource managers will know the comparability of chlorophyll-a data from the major monitoring programs in the Bay-Delta. Data collection agencies will know which methods are important to address to improve the accuracy and precision of sensor and lab chlorophyll-a data in the Bay-Delta.



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Approach Task 1: Assessment methods used to measure in-situ chlorophyll fluorescence by different monitoring programs in the Bay-Delta A small group of experts from the major programs (USGS, DWR, USBR, and SFEI-ASC) will summarize current practices for chlorophyll fluorescence measurements. At a minimum, the assessment will cover the following topic areas:

● Types of sensors and sonde equipment used ● Sensor settings ● Calibration ● Deployment and retrieval protocols ● Sensor servicing and cleaning ● Quality assurance ● Post-processing and data correction ● Reporting

The assessment will only cover current methods in use by programs; it will not survey past methods. Understanding the comparability of past methods to current methods is a priority for some agencies (e.g., DWR that has been monitoring since the 1980s) but it is beyond the scope of this effort. A brief literature review will be conducted to ensure that this regional effort is informed by national and other relevant guidance. This review will not be exhaustive. It will focus on reports such as recent guidance/protocols for chlorophyll fluorescence sensors, previous intercalibration exercises with chlorophyll fluorescence sensors, and key foundational literature. The deliverable for this task will be a short report on the results of the assessment, highlighting differences in methods for in-situ chlorophyll fluorescence between the major monitoring programs in the Bay-Delta, and the literature review. The report will become part of the final report for the overall project to be completed by the workgroup (Task 5) For a schedule, the first step of this task will be prioritized to occur in July 2018. DWR has plans to deploy multiple new chlorophyll fluorescence sensors in the summer of 2018. Having initial information from the first step of this task will be helpful for setting up these sensors to be compatible with other major programs. The rest of the task will be completed during the first six months of the project. Task 2: Coordinate intercalibration exercises that can be used to show the effects of different methods on sensor results USGS will organize a series of field tests to measure chlorophyll fluorescence using different equipment and methods. Participants in these field tests will include at a minimum USGS, SFEI-ASC, DWR and USBR. The deliverable for this task will be a presentation to the workgroup.



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Proposed Field Tests ● Side-by-side deployments by all programs that want to participate. Deployments

would be in two locations that span a range of chlorophyll fluorescence and fDOM conditions (Mossdale and Montezuma Slough tentatively). Deployments would be during the summer and fall bloom period in 2018. A minimum of 4-6 weeks of side-by-side data will be collected. All sondes would be installed at the same depth in a common location and, at a minimum, will collect data on water temperature, specific conductance, dissolved oxygen, pH, turbidity, and chlorophyll fluorescence (and BGA and fDOM, if possible). The sondes will be serviced at whatever frequency each program normally uses. At the conclusion of the first side-by-side deployment, the organizers will decide if additional side-by-side deployments or a reproducibility study (described below) should be performed next.

Other Possible Field Studies

● Reproducibility study. This type of study tests for how much variance is due to operator, sonde type, or program protocols. Each program will send up to three technicians with their own calibrated sondes out on a boat together (USGS vessel). The boat will stop at a variety of sites. At each site, each technician will measure chlorophyll fluorescence (averaged over a duration of 10 minutes to reduce noise). Statistical analysis will be used to estimate the 95% confidence intervals (error bars) within and between technicians and programs.

Task 3: Intercalibration study for laboratory chlorophyll-a measurements Laboratory measurements of extracted chlorophyll-a are used to calibrate and validate in-situ chlorophyll fluorescence measurements. Therefore, any effort to improve comparability in chlorophyll data needs to address variance in both in-situ and laboratory measurements. The proposed intercalibration study would show whether the laboratories in the region report similar results when given a split sample of the same water. Significant differences in the results between labs would trigger troubleshooting by chemists to find and fix the source of the variance.

A. Inventory of the methods used by the major laboratories measuring chlorophyll-a in the Bay-Delta and secure their participation.

a. The known laboratories for major programs are DWR’s Bryte Lab, USGS National Lab, SFSU Romberg Tiburon Center, and UC Davis. All laboratories will be allowed to be anonymous for the purposes of the study.

b. A standardized survey instrument will be used to capture information on the field and analytical methods used and quality assurance procedures.

B. Implement a “pre-coordination” round of analysis by participating laboratories.

a. For intercalibration study, the field samples will be collected by USGS during an opportunistic cruise.

b. Samples will be collected during the summer growth period (July-Oct) at stations where chlorophyll-a concentrations are expected to exceed 5 ug/L.



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c. A total three sampling rounds will be conducted. For each sampling round, one large sample will be collected by peristaltic pump from 1 meter below the surface. This large sample will be delivered to DWR to be split between the participating laboratories using a churn splitter. Each laboratory will receive triplicates of the sample in whatever format they usually require (e.g., a filter, a whole water sample, or something else). Each participating laboratory will receive three replicates of each sample.

d. For quality assurance, laboratories will also receive samples spiked with known concentrations of an algal culture. This process of “standard addition” will provide information on the accuracy of the methods used.

C. Analyze and report the results of the “pre-coordination” sampling round.

a. Results of the study will be evaluated by comparing the mean and range of the triplicate samples from each laboratory. For a statistical evaluation of all the data across the three sampling days, the overall mean of all chlorophyll-a measurements from the same day will be subtracted from each individual result from the same day as a measure of deviation from the expected result. One-Way ANOVA will be used to determine whether there are any laboratories with statistically significant differences in the deviations.

b. Quality Assurance. The measurement quality objectives for chlorophyll-a results by a single lab is presumed to be +/-30%. The goal of the study is to have the between-laboratory variance in this same range. A power analysis indicates that a sample size of 8 for each laboratory is needed to detect 50% differences between laboratories (e.g., for lab means of 10, 10, 10, and 5 ug/L with assumed error of 3 ug/L). Therefore, collecting 3 rounds of triplicate samples (9 samples total for each lab) will have sufficient sample size to detect between laboratory differences of management interest.

D. Organize coordination meeting with laboratories. Hold a meeting with

representatives from the participating laboratories to discuss the results and coordinate regarding methods.

E. Prepare final report. The final report will summarize the results of the test,

lessons learned, and recommendations. Task 4: Convene a workgroup to summarize findings and recommendations A workgroup of key practitioners will meet quarterly in FY18/19 to review the findings from the field and laboratory intercalibration studies. The workgroup meetings in FY17/18 have been highly productive and valued by the participants as a forum to learn from each other and to discuss important issues. The workgroup will review outcomes from the Tasks 1-3 and be responsible for developing a short report with conclusions and recommendations for next steps. Participants in the workgroup will include USGS-WSC, DWR, USBR, and SFEI/ASC at a minimum. At least one person who also sits on the Delta RMP Nutrients Subcommittee will be part of the workgroup. Participation will be open to any other interested parties.



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The deliverable for this task will be a summary report with recommendations for next steps taking into account results from Tasks 1-4. The report will be submitted to the Delta RMP committees but is expected to be shared widely among Bay-Delta monitoring program once it is published. Proposed Deliverables and Timeline Table 2. Deliverables

Deliverable Due Date

Task 1: Assessment of in-situ chlorophyll methods in use Dec. 31, 2018 (final)

Task 2: Presentation to workgroup on field intercalibration exercises Dec. 31, 2018

Task 3: Report on laboratory intercalibration study March. 31, 2019

Task 4: Summary report with recommendations for next steps April 30, 2019 (draft) June 30, 2019 (final)

Table 3. Timeline

2018 2019

Task J A S O N D J F M A M J

Task 1 - Assessment of Methods X

Task 2 - Field IC Exercises X

Task 3 - Lab IC study X

Task 4 - Workgroup Meetings X X X X

Task 4 - Summary Report X X

X = Deliverable due = Activity



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Budget Table 4 shows the estimated costs for this proposed special study. Table 4. Proposed Budget

Task Funding Requested for USGS

Funding Requested

for SFEI-ASC

Total Funding

Requested

In-Kind Contributions

(details in justification)

Task 1 - Assessment of Methods $5,000 $0 $5,000 DWR, USBR

Task 2 - Field IC Exercises $6,750 $5,250 $12,000 DWR, USBR

Task 3 - Lab IC Study $4,300 $13,500 $17,800 DWR, USBR

Task 4 - Workgroup Meetings $10,000 $20,000 $30,000 DWR, USBR

Task 4 – Summary Report $10,000 $10,000 $20,000 DWR, USBR

Total Funding Requested $36,050 $48,750 $84,800

Leveraged In-Kind Contributions $104,927

Budget Justification Project Costs Task 1

• USGS will manage this task and prepare a summary report. The cost for this effort is $5,000 (60 hours, mostly project manager time).

Task 2

• USGS will manage the field data collection for this task. The cost for this effort is: $5,750 (56 hours, mostly technician time) + $1,000 for boat, vehicle, and fuel expenses.

• SFEI-ASC will analyze the data from the field exercises and prepare a presentation with the results. The cost for this effort is $5,250 (48 hours of effort, mostly technician time).

Task 3

• SFEI-ASC will coordinate the laboratory intercalibration study and prepare a short summary report with the results. The cost for this effort is $10,000 (70 hours of effort, mostly technician time).

• Up to $3,500 of direct costs are budgeted for sample shipping, supplies, and lab fees. If laboratories agree to participate for free, costs will be reduced.



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• USGS will collect the field samples for the field study and be responsible for shipments to the laboratories. The cost for their participation is $3,300 (40 hours mostly project manager time) +$1,000 for boat, vehicle, and fuel expenses.

Task 4

• SFEI-ASC will organize and facilitate 4 quarterly meetings of the workgroup. Assuming 20 hours to prepare and run each meeting (80 hours) plus 40 hours for project management for a total cost of $20,000.

• SFEI-ASC will also contribute to, edit, and ensure completion of the final report (40 hours) for a total cost of $10,000.

• USGS will participate in 4 quarterly meetings and be the lead author in the final report. Total funding required for these tasks is $20,000 (combination of senior scientist and project manager time). This total cost has been split as $10,000 for the workgroup meetings and $10,000 for the report.

Leveraged Funds and In-Kind Contributions Leveraged funds are cash contributions from another source that pay for a part of the scope of work. In-kind contributions are staff time or resources (e.g., boat time, lab analyses) that are contributed to the project to complete the scope of work.

• The DWR Office of Water Quality and Estuarine Ecology has authorized 6 staff to participate in the study, which is an in-kind contribution of $33,939.

• The DWR North Central Regional Office has authorized 2 staff to participate in the study, which is an in-kind contribution of $19,400.

• The DWR Bryte Lab will analyze 9 water samples for Task 4. Each analysis has a value of $150/sample. Therefore, this service is an in-kind contribution of $1,350.

• The USBR Bay Delta Office has authorized 2 staff to participate in this study and purchase of needed equipment/supplies. This is an in-kind contribution of $20,238.

USGS is also funding a laboratory study on “Developing corrections for observed biases on in situ chlorophyll fluorometers used in real time monitoring”. This study is directly related to the objectives of this study. Therefore, its value of $30,000 is also considered leveraged funds. In FY17/18, the Nutrient Management Strategy for San Francisco Bay contributed $15,000 to Phase I of this effort. This program will likely be willing to contribute a similar amount in FY18/19 but the amount and the type of tasks it will choose to fund are not yet known. The Steering Committee will decide on budgets for FY18/19 in June.

Reporting The final deliverable from this project will be a technical report to the Delta RMP with the results from FY18/19 tasks and recommendations for future work. The lead author for



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the study will be USGS but the report will be published by SFEI-ASC. Representatives from other participating organizations will be co-authors. The report will be prepared in the form of a manuscript to facilitate publication of some or all of the findings in the peer-reviewed literature. Optional Tasks for Future Funding Achieving the high level goals of this study is expected to take several years. Accordingly, the proposed tasks for FY18/19 do not cover the full range of effort that is needed. The FY18/19 tasks will be useful to understand the scope of the problem, not necessarily to diagnose its causes. The project team anticipates the following tasks will be needed in FY19/20 plus recommendations that come out of the FY18/19 tasks. Furthermore, maintaining consistency and compatibility of water quality monitoring methods in the Delta must be an ongoing effort if it is to succeed. We envision an annual “Bay-Delta Monitoring Training Academy” where technicians can maintain proficiency in standard methods and share innovations. Extension of Task 2: Coordinate intercalibration exercises that can be used to show the effects of different methods on sensor results

● Share equipment between programs, e.g., exchange of sensors and calibration check standards.

● Embed field crews from different programs to help identify where field methods differ and to share knowledge.

● Purchase 3 probes (sequential serial numbers) for all programs to check for variance in identical sensors and to remove variance from sensors of different ages.

Extension of Task 3: Intercalibration study for laboratory chlorophyll-a measurements

● Implement a “post-coordination” round of analysis by participating laboratories. The approach for this study would be the same as for the “pre-coordination” round. The samples will be collected in April and May 2019. The purpose of the post-coordination sampling round is to show improved correspondence between laboratories after coordination.

Analyze existing data to understand the magnitude of factors affecting chlorophyll fluorescence measurements

• For this task, existing data will be analyzed to understand the magnitude of the impact of other factors on chlorophyll fluorescence measurements. The effects that will be investigated are deployment depth, non-photochemical quenching, fDOM, and turbidity. The deliverable for this task will be a presentation to the workgroup.

● To understand if there is a large offset in chlorophyll fluorescence depending on the depth of the sensor, analyze profile data at sonde locations collected by USBR in the Deep Water Ship Channel (5 years of data). This dataset spans the range of vertical mixing conditions that are likely to be encountered in the Delta. The question to be addressed is: Do measurements of chlorophyll fluorescence at the surface or at the bottom need to be adjusted to be representative of the



15

overall water column in Bay-Delta channels? At all sites? At certain types of sites?

● To understand if non-photochemical quenching (NPQ) is an important factor, analyze data collected during the day and the night (including grab samples for laboratory analysis from USBR) within the same 24-hour period and with tidal correction. The question to be addressed is: Does NPQ cause enough of an effect in the Bay-Delta that chlorophyll fluorescence data needs to be correct for this factor? If there is an important effect, one solution is to only use data collected at night.

● Analyze historic datasets where fDOM and turbidity have been measured to determine the size of the effect that these water quality parameters have on the measurement of chlorophyll fluorescence. It has already been established that these parameters do affect chlorophyll fluorescence measurements. In some cases, fDOM sensors have direct interference with fluorometers. However, the magnitude of this effect and recommendations for correcting for it need to be determined. The question to be addressed is: How large of an effect do fDOM and turbidity have on chlorophyll fluorescence measurements in the Bay-Delta? Laboratory experiments are needed to investigate direct “cross talk” between fluorometers and fDOM sensors. That type of experiment is not proposed for this study.

Develop standardized methods for in-situ fluorometers

• Standardized methods would improve the consistency of data collection across the Bay-Delta. If the methods assessment (Task 1) and side-by-side deployments (Task 2) indicate the need for standardization and the major monitoring programs are willing to change their protocols, then a methods manual could be developed.

Training for water quality monitoring technicians

● Hold a training for larger audience of technicians to disseminate the lessons learned and common field protocols.

Analyze and collect data to relate chlorophyll fluorescence data to phytoplankton biomass

● A long-term goal is to be able to use chlorophyll measurements to make accurate assessments of phytoplankton biomass to inform important management questions about productivity, nutrient management, and fisheries. The FY18/19 workplan is focused on improving the comparability of just the chlorophyll measurements. In order to be ready for the next phase of the study, data to relate chlorophyll to actual phytoplankton biomass should be analyzed. Some data are already being collected as part of other studies (e.g., picoplankton and taxonomy at some USGS stations). Additional data may need to be collected in other locations to round out the dataset. Adding more sensors to some moored stations to create “superstations” where the relationships between these sensors and chlorophyll fluorescence is another option. Interpretation of phytoplankton taxonomy data will require expanding the expertise in the workgroup to cover this discipline.



16

References Bergamaschi, B.A., Downing, B.D., Kraus, T.E.C., and Pellerin, B.A., 2017, Designing a

high-frequency nutrient and biogeochemical monitoring network for the Sacramento–San Joaquin Delta, northern California: U.S. Geological Survey Scientific Investigations Report 2017–5058, 40 p., https://doi.org/10.3133/sir20175058.


https://doi.org/10.3133/sir20175058

Meeting Materials for Item 6: Mercury Proposal


Summary of Proposal for FY18/19 Delta RMP Monitoring for Mercury

Title Summary Funding Request

Leveraged Resources

Ranking

Monitoring to Support Implementation of the Methylmercury TMDL

Continued monitoring of sport fish and water is proposed to address the highest priority information needs related to implementation and revision of the Methylmercury TMDL (re-opening of the TMDL is tentatively scheduled for 2020). Annual monitoring of sport fish will firmly establish baseline concentrations and interannual variation in support of monitoring of long-term trends as a critical performance measure for the TMDL. Monitoring of water on a near-monthly basis will solidify the linkage analysis (the quantitative relationship between methylmercury in water and methylmercury in sport fish) in the TMDL and be valuable in verifying trends and patterns predicted by a numerical model of methylmercury transport and cycling being developed for the Delta and Yolo Bypass by the California Department of Water Resources (DWR) - this model will allow testing of various water management scenarios.

$314,000 $30,000 (in-kind)


Multi-Year Plan for Delta RMP Mercury Monitoring Amounts in thousands of dollars.

Approved Approved Proposed Planned Planned Element Scope FY16/17 FY17/18 FY18/19 FY19/20 FY20/21

Fish Monitoring 6 sites $46 $52 7 sites $61 $63 $65

Water Monitoring 5 sites, 4 months $65 6 sites, 8 months $153 8 sites, 10 months $258 $266 $274

Sediment Monitoring 6 sites, 4 months $29

Coordination, data management, QA, reporting $18 $25 $25 $46 $27

Total $119 $259 $344 $374 $365

In-kind Match $21 25 $30 $30 $30

Total from RMP $108 234 $314 $344 $335


DRAFT

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Summary of Mercury Proposal for FY18/19 Workplan

Continued monitoring of sport fish and water is proposed to address the highest

priority information needs related to implementation and revision of the

Methylmercury TMDL (re-opening of the TMDL is tentatively scheduled for 2020).

Annual monitoring of sport fish will firmly establish baseline concentrations and

interannual variation in support of monitoring of long-term trends as a critical

performance measure for the TMDL. Monitoring of water on a near-monthly basis will

solidify the linkage analysis (the quantitative relationship between methylmercury in

water and methylmercury in sport fish) in the TMDL and be valuable in verifying

trends and patterns predicted by a numerical model of methylmercury transport and

cycling being developed for the Delta and Yolo Bypass by the California Department of

Water Resources (DWR) - this model will allow testing of various water management

scenarios.

The estimated cost to the Delta RMP for the proposed mercury monitoring is $314,000.

Management Drivers Addressed

Mercury monitoring addresses the Delta Methylmercury TMDL, which establishes

goals for cleanup and calls for a variety of control studies and actions.

Assessment Questions Addressed

Two tiers of assessment questions have been defined for the mercury monitoring

program. Primary assessment questions are those that are explicitly addressed by the

monitoring and drive the monitoring design. Secondary assessment questions are

addressed to some extent by the monitoring, but are not drivers of the monitoring

design. The monitoring will contribute some information on but will not fully answer

the secondary assessment questions.


DRAFT

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Primary Assessment Questions

Status and Trends

ST1. What are the status and trends in ambient concentrations of

methylmercury and total mercury in sport fish and water, particularly in

subareas likely to be affected by major existing or new sources (e.g., large-

scale restoration projects)?

ST1.A. Do trends over time in methylmercury in sport fish vary among

Delta subareas?

Sources, Pathways, Loadings & Processes

SPLP1. Which sources, pathways and processes contribute most to observed levels

of methylmercury in fish?

SPLP1.A. What are the loads from tributaries to the Delta (measured at the

point where tributaries cross the boundary of the legal Delta)?

Fish-Water Linkage Analysis

(new priority question articulated by Mercury Subcommittee)

FWLA1. Are there key datasets needed to strengthen the technical foundation of

contaminant control programs?

Secondary Assessment Questions

Status and Trends

ST1. What are the status and trends in ambient concentrations of

methylmercury and total mercury in sport fish and water, particularly in

subareas likely to be affected by major existing or new sources (e.g., large-

scale restoration projects)?

ST1.B. How are ambient levels and trends affected by variability in climate,

hydrology, and ecology?


DRAFT

3

Sources, Pathways, Loadings & Processes

SPLP1. Which sources, pathways and processes contribute most to observed

levels of methylmercury in fish?

SPLP1.B. How do internal sources and processes influence methylmercury

levels in fish in the Delta?

SPLP1.C. How do currently uncontrollable sources (e.g., atmospheric

deposition, both as direct deposition to Delta surface waters and as

a contribution to nonpoint runoff) influence methylmercury levels

in fish in the Delta?

Forecasting Scenarios

FS1. What will be the effects of in-progress and planned source controls,

restoration projects, and water management changes on ambient

methylmercury concentrations in fish in the Delta?

Data Quality Objectives/Null Hypothesis

The initial and preliminary data quality objective (DQO) is the ability to detect a trend

of mercury in fish tissue of 0.040 ppm/yr. This DQO can be refined when additional

data are available. The null hypothesis is that there is no trend. MQOs are identical to

those used in other mercury studies throughout the state and the country for

determinations of impairment and trend detection. These MQOs generally call for

indices of accuracy and precision to be within 25% to 30% of expected values.


DRAFT

4

Monitoring to Support Implementation of the Methylmercury TMDL

Executive Summary

Continued monitoring of sport fish and water is proposed to address the highest priority

information needs related to implementation and revision of the Methylmercury TMDL (re-

opening of the TMDL is tentatively scheduled for 2020). Annual monitoring of sport fish will

firmly establish baseline concentrations and interannual variation in support of monitoring of

long-term trends as a critical performance measure for the TMDL. Monitoring of water on a

near-monthly basis will solidify the linkage analysis (the quantitative relationship between

methylmercury in water and mercury in sport fish) in the TMDL and be valuable in verifying

trends and patterns predicted by a numerical model of methylmercury transport and cycling

being developed for the Delta and Yolo Bypass by the California Department of Water

Resources (DWR) - this model will allow testing of various land and water management

scenarios.

Background and Motivation

Concentrations of methylmercury in fish from the Delta exceed thresholds for protection of

human and wildlife health. The Methylmercury TMDL (Wood et al. 2010) is the driver of

actions to control methylmercury in the Delta, establishing water quality goals and directing

various discharger groups to conduct monitoring and implement measures to minimize

methylmercury impairment of beneficial uses.

The TMDL established three water quality objectives for methylmercury in fish tissue: 0.24 ppm

in muscle of large, trophic level four (TL4) fish such as black bass; 0.08 ppm in muscle of large

TL3 fish such as carp; and 0.03 ppm in whole TL2 and TL3 fish less than 50 mm in length.

Furthermore, the TMDL established an implementation goal of 0.24 ppm in largemouth bass at

a standard size of 350 mm as a means of ensuring that all of the fish tissue objectives are met.

Largemouth bass are widely distributed throughout the Delta and are excellent indicators of

spatial variation due to their small home ranges. Past data for largemouth bass were a

foundation for the development of the TMDL, including the division of the Delta into eight

subareas. Monitoring of largemouth bass in these subareas therefore provides the most critical

performance measure of progress in addressing methylmercury impairment in the Delta.


DRAFT

5

The TMDL describes a statistically significant relationship between the annual average

concentration of methylmercury in unfiltered water and average mercury in 350 mm

largemouth bass when data are organized by subarea. This linkage provides a connection,

essential for management, between methylmercury inputs from various pathways (e.g.,

municipal wastewater, municipal stormwater, agricultural drainage, sediment flux in open

waters, and wetland restoration projects) and impairment of beneficial uses. Because of this

linkage, the TMDL established an implementation goal of 0.06 ng/L of unfiltered aqueous

methylmercury. In response to TMDL control study requirements, the Department of Water

Resources (DWR) is leading development of numerical methylmercury transport and cycling

simulation models for the Delta and Yolo Bypass. Monitoring of aqueous methylmercury is

therefore needed to:

1) better quantify the fish-water linkage that is the foundation of the TMDL,

2) evaluate attainment of the TMDL implementation goal,

3) support calculations of mercury and methylmercury loads and mass balances,

4) support development of mercury models for the Delta and Yolo Bypass, and

5) support evaluation of the fish data by providing information on processes and trends.

In FY 2016/2017 the Delta RMP initiated a methylmercury monitoring program for fish and

water. Largemouth bass were collected in late summer 2016 (September) from six locations

distributed across the subareas. Quarterly sampling of methylmercury and mercury (and

ancillary parameters) in water at five locations began in August 2016.

In FY 2017/2018, methylmercury monitoring of fish and water continued. Funding was

allocated to sample fish at six locations and water at six locations for eight months. The eight

months to be sampled were to be the March-October period used for the linkage analysis in the

TMDL. In late 2017, the Mercury Subcommittee decided that a more optimal use of the

available funds would be to shift to sampling water at eight locations (adding locations in the

West Delta and at the export pumps) and to add sampling in January and February (Table 1).

The FY 2017/2018 plan also included funds for quarterly sediment sampling to support the

DWR methylmercury modeling effort, and any future methylmercury modeling.


DRAFT

6

Applicable Management Decisions and Assessment Questions

The Delta Methylmercury TMDL is the embodiment of management decisions for

methylmercury in the Delta, establishing goals for cleanup and calling for a variety of control

studies and actions. With providing information to support TMDL implementation in mind, the

Mercury Subcommittee carefully considered, refined, and prioritized the assessment questions

articulated by the Steering Committee and Technical Advisory Committee for mercury.

Two tiers of assessment questions have been defined for the mercury monitoring program.

Primary assessment questions are those that are explicitly addressed by the monitoring and

drive the monitoring design. Secondary assessment questions are addressed to some extent by

the monitoring, but are not drivers of the monitoring design. The monitoring will contribute

some information but will not fully answer the secondary assessment questions.


DRAFT

7

Primary Assessment Questions

One priority question for this initial phase of methylmercury monitoring is from the Status and

Trends category of the DRMP management and assessment questions:

Status and Trends

ST1. What are the status and trends in ambient concentrations of methylmercury and

total mercury in sport fish and water, particularly in subareas likely to be

affected by major existing or new sources (e.g., large-scale restoration projects)?

ST1.A. Do trends over time in methylmercury in sport fish vary among Delta

subareas?

Question 1A is a high priority for managers that relates to the TMDL, and is a primary driver of

the sampling design for fish monitoring. Annual monitoring of fish mercury is urgently needed

to 1) firmly establish a baseline for each Delta subarea and 2) to characterize the degree of

interannual variation, which is essential to designing an efficient monitoring program for

detection of long-term trends. In addition to addressing status and trends, this monitoring will

establish a foundation for tracking the effectiveness of management actions - another category

of the Delta RMP core management questions.

Sources, Pathways, Loadings and Processes

SPLP1. Which sources, pathways and processes contribute most to observed levels of

methylmercury in fish?

SPLP1.A. What are the loads from tributaries to the Delta (measured at the

point where tributaries cross the boundary of the legal Delta)?

A mass budget for methylmercury in the Delta is a critical element of the TMDL. The mass

budget provides essential context for understanding the importance of inputs from discharges

and internal sources and processes. Obtaining data to expand and update the dataset on

methylmercury inputs to the Delta is a high priority to support TMDL refinement and

implementation. Methylmercury export from the Delta is similarly an important component of

the mass budget and a high priority information need.

Fish-Water Linkage Analysis

(new priority question articulated by Mercury Subcommittee)

FWLA1. Are there key datasets needed to strengthen the technical foundation of

contaminant control programs?


DRAFT

8

Another priority question that will be addressed by this proposal relates to the linkage analysis

discussed in the previous section, which is a key element of the technical basis for the TMDL.

This question was not articulated in the core management questions and assessment questions

established by the Steering Committee, but was nevertheless identified as a priority by the

Mercury Subcommittee. Additional data on methylmercury in water is one of the key datasets

needed to strengthen the technical foundation of the TMDL.

Secondary Assessment Questions

ST1. What are the status and trends in ambient concentrations of methylmercury and

total mercury in sport fish and water, particularly in subareas likely to be

affected by major existing or new sources (e.g., large-scale restoration projects)?

ST1.B. How are ambient levels and trends affected by variability in climate,

hydrology, and ecology?

The time series for methylmercury in fish and water that are created to answer the primary

assessment questions will also be influenced by variation in climate, hydrology, and ecology,

and will provide information on the role of these factors. For example, the first two years of

monitoring have already spanned the end of a prolonged drought and a high flow year,

providing an opportunity to examine the impact of extreme variation in flow on methylmercury

concentrations in fish and water.

Sources, Pathways, Loadings and Processes

SPLP1. Which sources, pathways and processes contribute most to observed levels of

methylmercury in fish?

SPLP1.B. How do internal sources and processes influence methylmercury

levels in fish in the Delta?

SPLP1.C. How do currently uncontrollable sources (e.g., atmospheric

deposition, both as direct deposition to Delta surface waters and as a

contribution to nonpoint runoff) influence methylmercury levels in

fish in the Delta?

Forecasting Scenarios


DRAFT

9

FS1. What will be the effects of in-progress and planned source controls, restoration

projects, and water management changes on ambient methylmercury

concentrations in fish in the Delta?

These secondary assessment questions relating to Sources, Pathways, Loadings, and Processes

and Forecasting Scenarios for this initial phase of methylmercury monitoring relate to one of the

major control studies called for in the TMDL: an effort to combine modeling, field data, and

laboratory studies to evaluate the potential effects of water project operational changes on

methylmercury in Delta channels. The Department of Water Resources (DWR) is currently

developing two mathematical models, one each for the Delta and Yolo Bypass, that will allow

testing of various water management scenarios (DiGiorgio et al. 2016). These models will be

useful in addressing this set of Delta RMP management questions. The opportunity to inform

these models, which are being developed with a considerable investment of funding from the

California Department of Water Resources (DWR), makes monitoring to address these

questions a near-term priority for the Delta RMP. The water monitoring included in this

proposal will generate data that are valuable for verifying trends and patterns predicted by the

methylmercury models.

Approach

Fish Sampling Design 7 fixed sites (Figure 1), largemouth bass only - adding a site in the West

Delta in this round

Key Indicator Annual average methylmercury in muscle fillet of 350 mm largemouth

bass (or similar predator species), derived through analysis of 16

individual bass or other predator species at each location

Parameters Total mercury*, Total length, Fork length, Weight, Sex, Moisture,

Estimated age

Frequency Annual

Schedule Monitor through 2025 and then re-evaluate. Sample in summer or early

fall.

Co-location Water MeHg and Hg

Other water parameters

Contractors SFEI (design, data management, reporting), MLML (sample collection,

chemical analysis, reporting)

Coordination DWR, USGS (sampling of flow monitoring stations)


DRAFT

10

* Total mercury measured as proxy of methylmercury because methylmercury comprises more

than 90% of the total mercury in fish.

Summary of Results to Date

Results from the first year of DRMP methylmercury monitoring are presented in the Year One

Data Report (Davis et al. 2018). The report provides details on the sample collection and

processing, chemical analysis, quality assurance, and the results. Highlights of the results are

briefly discussed here.

Results from the first round of DRMP fish monitoring are presented in Figure 2, with data

from prior fish sampling in or near these stations provided for context. Time series with more

than three observations are available for four of the six locations. The existing time series are

characterized by a high degree of inconsistency in locations, species, and sampling approach

over time, highlighting the need to build a consistent dataset for trend evaluation. The data do

suggest a preliminary answer to management question 1A. The data suggest a decline in

concentrations at the San Joaquin River at Vernalis over the period of record, while

concentrations appeared to be stable at the other three locations. Therefore, the data give a

preliminary indication that trends do vary among the Delta subareas. Additional rounds of

consistent sampling are needed to confirm this preliminary interpretation.

Water Sampling Design 8 fixed sites (Figure 1) - adding sites for export from the Delta in this

round (Mallard Island in the west Delta and the Delta Mendota Canal

for a water project export site)

Key Indicator March-October average total (unfiltered) methylmercury at each

location

Parameters Total (unfiltered) methylmercury, filtered methylmercury, unfiltered

total mercury, filtered total mercury, suspended solids, chlorophyll a,

dissolved organic carbon (field filtered), volatile suspended solids.

Field measurements will include dissolved oxygen, pH, and specific

conductance.

Other Important

Parameters

Nutrients (ALK, NH3, CL, DOC, HARD, NO3/NO2, N (total), OPO4,

TPHOS, SiO2, SO4, TDS, TOC), grain size. Budget assumes these are

covered by other studies.

Frequency 10 events per year (8 monthly events + 2 storm or winter events)

Schedule Monitor through 2020 and then re-evaluate

Co-location Sport fish sampling (at 7 of the sites, excluding Delta Mendota Canal)

Other water parameters


DRAFT

11

Coordination DWR, USGS (sampling of flow monitoring stations)

Summary of Results to Date

Results for March-October average total (unfiltered) methylmercury at each location for the first

year of sampling are briefly summarized here. Data for the other water parameters are

presented in the Year One Data Report (Davis et al. 2018).

Figure 3 presents long-term time series of March to October annual averages of total unfiltered

MeHg concentrations for Delta RMP sites. Sacramento River concentrations have remained

constant with good agreement between historic data and current data. Cache Slough 2016

concentration was lower than what was reported previously but the 2017 concentration was

within historic ranges. No historic data are available for Little Potato Slough. Middle River

MeHg concentrations were highly variable with 2016–17 concentrations within the range of

historic data. The San Joaquin River 2016 MeHg concentration was lower than previously

reported values. However, the 2017 measurement was the highest concentration ever reported

for this site.

Data Quality

The measurement quality objectives (MQOs) for measurements of methylmercury and mercury

in fish and water are shown in Appendix 1. These MQOs are the same as MQOs used in

mercury studies throughout California, with statewide fish monitoring by the Surface Water

Ambient Monitoring Program as a prominent example. The MQOs generally call for indices of

accuracy and precision to be within 25% to 30% of expected values. Data of this quality are

routinely used for determinations of impairment and trend detection throughout the state and

the country. The variance attributable to the analytical process is one of the contributors to the

overall variance observed in the data. This variance is therefore accounted for in the power

estimates provided in the next section.

Power to Detect Long-term Trends - Fish Sampling

The power to detect interannual trends in largemouth bass mercury on a per site basis was

evaluated using existing data. Even the best existing time series for the Delta have low statistical

power to detect trends due to infrequent sampling and varying sampling designs of studies

performed over the years (Figure 2). One of the goals of the initial phase of Delta RMP fish

mercury monitoring is to obtain robust information on interannual variation to support future


DRAFT

12

power analysis. As part of the mercury proposal for FY 2017/2018 we conducted a power

analysis on the small amount of information presently on hand. Appendix 2 provides the

methods and details on the results. This analysis will be updated after a few years of new data

have accumulated.

Power analysis summary

Power for trend detection at a single site based on grand mean estimates of observed variance

across sites. Pink shading indicates scenarios with greater than 80% power.

These preliminary results indicate that increasing the number of fish per site would be effective

in increasing power. With 16 fish per site and annual sampling, 80% power would be expected

for several of the 20-year scenarios. Beginning with year 2 (FY 2017/2018) the design for fish

monitoring was therefore being modified to include 16 fish per site. The monitoring results for

the San Joaquin at Vernalis suggest that trends of up to 0.040 ppm/yr are possible. The results

highlight the importance of initiating consistent time series.

Power Analysis - Water Sampling

Not applicable. The primary objectives of the water sampling are to strengthen the linkage

analysis and support model development. The water monitoring is not intended as a tool for

long-term trend monitoring.


DRAFT

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Reporting/Deliverables Deliverable Due Date

Draft Data Report on Year 2 (FY 17/18) December 2018

Final Data Report on Year 2 (FY 17/18) February 2019

Draft Data Report on Year 3 (FY 18/19) December 2019

Final Data Report on Year 3 (FY 18/19) February 2020


DRAFT

14

Budget


DRAFT

1

Table 1. Sampling schedule for Delta RMP mercury monitoring. The March-October period used for the linkage

analysis in the TMDL is indicated in bold font.


DRAFT

1

Figure 1. Planned sampling sites for methylmercury in FY18/19.


DRAFT

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Figure 2. Long-term time series of mean mercury (ppm wet weight) in black bass for Delta

RMP stations and nearby stations sampled historically. Details on following

page.

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1995 2000 2005 2010 2015 2020

Sacramento River at Freeport (RM44)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1995 2000 2005 2010 2015 2020

Lower Mokelumne River 6 (I5/Lost Slough/ds Cosumnes)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1995 2000 2005 2010 2015 2020

Cache Slough at Liberty Island Mouth (Prospect Slough)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1995 2000 2005 2010 2015 2020

Little Potato Slough(Potato Slough)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1995 2000 2005 2010 2015 2020

Middle River at Borden Hwy (Hwy 4)(Empire/Bullfrog)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1995 2000 2005 2010 2015 2020

San Joaquin River at Vernalis


DRAFT

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Figure 2 Details

Points generally show 350 mm length-adjusted means (exceptions to this noted in plot details

below) and error bars indicate two times the standard error. Filled symbols indicate 350 mm

length-adjusted means, hollow symbols indicate individual composite samples or arithmetic

means when the station did not have a significant length:mercury correlation. Diamonds

indicate largemouth bass; squares are spotted bass; circles are smallmouth bass. Data sources:

Delta RMP - 2016; the Surface Water Ambient Monitoring Program (Davis et al. 2013) - 2011; the

Fish Mercury Project (Melwani et al. 2009) - 2005-2007; the CALFED Mercury Project (Davis et

al. 2003) - 1999-2000; the Delta Fish Study (Davis et al. 2000) - 1998; and the Sacramento River

Watershed Program (2002) - 1998.

Sacramento River at Freeport Stations - Freeport: 2016; RM44: All other years Statistics - Individual composite results: 1998; 350 mm length adjusted mean: all other years Lower Mokelumne River 6 Stations - Lower Mokelumne River 6: 2016; Mokelumne River near I-5: 2011; Lost Slough: 2005; Mokelumne River downstream of the Cosumnes River: 1999, 2000 Cache Slough at Liberty Island Mouth Stations - Cache Slough at Liberty Island Mouth: 2016; Prospect Slough: 2005, 2007 Little Potato Slough Stations - Little Potato Slough: 2016; Potato Slough (aka San Joaquin River at Potato Slough): 2005, 2007 Middle River at Borden Hwy (Hwy 4) Stations - Middle River at Borden Hwy (Hwy 4): 2016; Middle River near Empire Cut: 2011; Middle River at Bullfrog: 1998, 1999, 2007; Middle River at HWY 4: 2005 Statistics - Individual composite result: 1998; 350 mm length adjusted mean: all other years San Joaquin River at Vernalis Stations - Same station all years


DRAFT

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Figure 3. Annual mean aqueous unfiltered methylmercury concentration at each Delta

RMP monitoring station sampled from August 2016 through April 2017. Plots

based on March-October data.


DRAFT

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References DiGiorgio, Carol, Helen Amos, Jamie Anderson, Maninder Bahia, Cody Beals, Don Beals, David

Bosworth, et al. “Creation of Mercury Models for the Delta and Yolo Bypass: Linking

Modeling and Delta Regulatory Decisions.” Sacramento, California, 2016.

http://scienceconf2016.deltacouncil.ca.gov/content/creation-mercury-models-delta-and-

yolo-bypass-linking-modeling-and-delta-regulatory.

Wood, Michelle L., Chris G. Foe, Janis Cooke, and Stephen J. Louie. “Sacramento – San Joaquin

Delta Estuary TMDL for Methylmercury: Staff Report.” Sacramento, California: Central

Valley Regional Water Quality Control Board, 2010.

http://www.waterboards.ca.gov/rwqcb5/water_issues/tmdl/central_valley_projects/delta_h

g/april_2010_hg_tmdl_hearing/apr2010_tmdl_staffrpt_final.pdf.


http://scienceconf2016.deltacouncil.ca.gov/content/creation-mercury-models-delta-and-yolo-bypass-linking-modeling-and-delta-regulatory

http://scienceconf2016.deltacouncil.ca.gov/content/creation-mercury-models-delta-and-yolo-bypass-linking-modeling-and-delta-regulatory

http://www.waterboards.ca.gov/rwqcb5/water_issues/tmdl/central_valley_projects/delta_hg/april_2010_hg_tmdl_hearing/apr2010_tmdl_staffrpt_final.pdf

http://www.waterboards.ca.gov/rwqcb5/water_issues/tmdl/central_valley_projects/delta_hg/april_2010_hg_tmdl_hearing/apr2010_tmdl_staffrpt_final.pdf

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Central Valley Pilot Study for Monitoring Constituents of Emerging Concern (CECs) Work Plan January 10, 2018

INTRODUCTION

At the request of the Central Valley Regional Water Quality Control Board (Central Valley Water Board) and the State Water Resources Control Board (State Water Board), the Central Valley Clean Water Association (CVCWA) and several1 Central Valley Municipal Separate Storm Sewer System (MS4) representatives (MS4 representatives) have developed this integrated work plan, to be implemented through the Delta Regional Monitoring Program (Delta RMP), to monitor Constituents of Emerging Concern (CECs) in the Central Valley on a pilot basis, primarily in and around the Sacramento-San Joaquin Delta. This work plan has been developed to address the targeted CEC study elements as described in the CECs Statewide Pilot Study Monitoring Plan developed by the State Water Board (2016 Statewide Monitoring Plan)2. The 2016 Statewide Monitoring Plan was created as part of a statewide effort to address CEC monitoring needs in reaction to public interest in this topic and employs a beneficial use protection assessment approach. CEC monitoring has already been implemented differently in several regions through regional monitoring programs, Surface Water Ambient Monitoring Program (SWAMP) funding, and individual discharger funded programs. In addition to requests from the State Water Board and the Central Valley Water Board, the development and implementation of a pilot CEC monitoring program in the Delta will also address one of the Priority Science Actions recommended in the 2017 Science Action Agenda of the Delta Stewardship Council3. A suggested list of CECs is described in the 2016 Statewide Monitoring Plan. This work plan has been adapted for the Central Valley to address most of the key CECs identified by the State Water Board. Exceptions include those CECs that are currently monitored in the Central Valley under separate programs or regulations, including a number of current-use pesticides, among them pyrethroids. While the analytical methods necessary for this work plan can be performed by research laboratories and a select few commercial laboratories, any data collected in the program should be specifically evaluated to demonstrate or measure the extent the data are reliable (accuracy against a known standard), reproducible (precision of duplicates between multiple laboratories), and repeatable (precision by primary laboratory) before they are used for source management

1 Approximately nine (9) out of a total of 143 MS4 agencies voluntarily participated in the work plan development that is intended to satisfy the Central Valley region-wide effort. 2 Dawitt Tadesse, Office of Information Management and Analysis, State Water Resources Control Board. “Statewide Monitoring Plan. Constituents of Emerging Concern (CECs) Statewide Pilot Study Monitoring Plan.” January 2016. https://www.waterboards.ca.gov/water_issues/programs/swamp/cec_aquatic/docs/oima_sw_cec_mon_plan.pdf

3 “Delta Stewardship Council, Delta Science Program. 2017. 2017-2021 Science Action Agenda” (Delta Stewardship Council Delta Science Program, September 2017. http://scienceactionagenda.deltacouncil.ca.gov/sites/default/files/2017-2021-SAA-final-Sept2017.pdf


https://www.waterboards.ca.gov/water_issues/programs/swamp/cec_aquatic/docs/oima_sw_cec_mon_plan.pdf

http://scienceactionagenda.deltacouncil.ca.gov/sites/default/files/2017-2021-SAA-final-Sept2017.pdf

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and regulatory enforcement decision making. Moreover, effects thresholds are not well known for these low concentration constituents with respect to additive or mitigating effects, and an established process should be developed when assessing beneficial use protection. Based on discussions with Central Valley Water Board staff (during the coordination meeting held on September 18, 2017), the data gathered during the pilot study will be used to inform the statewide and Central Valley Water Board’s CEC programs and will not be used for regulatory purposes. During early discussions, the use of the Delta RMP to implement the pilot study was favored and supported by publicly owned treatment works (POTW) and MS4 representatives and Central Valley Water Board management for numerous reasons, including the following:

• It capitalizes on the ongoing Delta RMP stakeholder-based process, including technical and peer review;

• It provides a better sense of CEC presence in Central Valley waters than isolated receiving water data;

• It is consistent with the stated mission of the Delta RMP; • It supports the growth of the Delta RMP, including enhancement of data assessment and

communications; and • It addresses one of the Delta Stewardship Council’s Priority Science Actions to improve

understanding of interactions between stressors and managed species and their communities (Action 4). Specifically, the CEC pilot monitoring program will provide the opportunity to develop information on the potential impacts of CECs on aquatic species in the Central Valley.

It is proposed that the Central Valley CEC pilot monitoring program begin in fiscal year 2018-2019, after July 1, 2018. This work plan should be implemented as a Delta RMP “Special Study” without extensive revision. While the Delta RMP does not have a specific process for approving special studies, the previously performed Pathogen Study4 is an analogous approach whereby a specific monitoring and assessment need was identified through a stakeholder process which was then addressed through the Delta RMP with oversight by the stakeholder group. The State Water Board, Central Valley Water Board, and other California Regional Water Quality Control Boards convened a workshop on May 1 and 2, 2017 to share information regarding CEC monitoring completed to date in other regions in the State. Information presented and discussed at this workshop aided in the development of the proposed pilot study work plan.

PURPOSE

The proposed Central Valley CEC pilot study would provide preliminary information to begin to address the Delta RMP management question, “Is there a problem or are there signs of a problem” through the stated question5, “Are CECs impacting Beneficial Uses in the Central Valley?”. This work plan will not directly answer this question, which would require significant science development and consideration of factors not included in this work plan. However, this 4https://www.waterboards.ca.gov/centralvalley/water_issues/delta_water_quality/delta_regional_monitoring/wq_monitoring_plans/drmp_monitoring_design.pdf 5 Assessment question as stated at the December 7, 2017 Central Valley Regional Water Quality Control Board hearing by Regional Water Board staff.


https://www.waterboards.ca.gov/centralvalley/water_issues/delta_water_quality/delta_regional_monitoring/wq_monitoring_plans/drmp_monitoring_design.pdf

https://www.waterboards.ca.gov/centralvalley/water_issues/delta_water_quality/delta_regional_monitoring/wq_monitoring_plans/drmp_monitoring_design.pdf

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work plan will provide incremental assessment of conditions through consideration of the 2016 Statewide Monitoring Plan monitoring questions that are compiled in Table 1. Consistent with the current direction of the Delta RMP, the proposed Central Valley CEC pilot study is focused on development of information to understand the status of a specific list of CECs in ambient waters, sediments, and, to a limited extent, tissues of locally gathered fish and bivalves. Evaluation of contributions from urban sources is also consistent with the “Sources and Pathways” Delta RMP Management Question. A clear need exists to develop an understanding of the presence/absence and potential risks (i.e., a need for water quality standards for determination of beneficial use impairment) posed by CECs in the Central Valley. This will require significant expansion of effects research. This is best addressed at a national or statewide level and is not recommended as an element of the Central Valley CEC pilot monitoring effort.

PILOT STUDY SCOPE

The Central Valley CEC pilot study is proposed to occur in three phases over a three-year period. The first year (Phase 1) would consist of ambient monitoring to assess the presence of the targeted CECs at specific locations. Table 1 summarizes the technical approaches to respond to the 2016 Statewide Monitoring Plan monitoring questions. After the first year of ambient monitoring, subsequent elements of the proposed CEC monitoring plan would include continued ambient monitoring and source monitoring (POTW effluent and urban runoff characterization) during Phase 2 (Year 2), and continuation of Year 2 source monitoring plus gradient studies upstream and downstream of POTWs and other identified sources during Phase 3 (Year 3), with studies focused on those CECs detected at levels of interest. Sample collection during Year 3 may be modified to better address information needs based on the first two years of monitoring, but will at least include the second year of source monitoring. The candidate ambient sampling locations are proposed to include entry points into the Delta, in-Delta waters, as well as ambient locations in the vicinity of POTW discharges and influence from urban runoff. Ambient monitoring to characterize background conditions was suggested in the State Water Board’s 2016 Statewide Monitoring Plan. The proposed Central Valley CEC pilot study will not address several other elements of the 2016 Statewide Monitoring Plan, including non-targeted assessment, bioanalytical or toxicity components. These components may be added to the proposed pilot study work plan if additional external funding is developed to support this work. During the development of this work plan, preliminary evaluations were performed to identify and confirm appropriate sampling, sample extraction, analytical, sample handling, and quality assurance/quality control (QA/QC) methods to be used for each of the CECs on the target list to maintain consistency with other elements of the 2016 Statewide Monitoring Plan. The Delta RMP Quality Assurance Project Plan (QAPP) should be updated to evaluate data quality and provide data usage qualification for the constituents included in this proposed pilot study. A sample collection plan should also be developed as an attachment to the QAPP or as a standalone Delta RMP document.


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Target CECs

The following list of CECs will be monitored as part of this work plan, consistent with the list proposed in the State Water Board’s 2016 Statewide Monitoring Plan.

• Estrone; • Ibuprofen; • Bisphenol A; • 17-beta estradiol; • Galaxolide (HHCB), as allowed by available funding6; • Diclofenac; • Triclosan; • Triclocarban; • PBDE-47 (sediment and tissue only); • PBDE-99 (sediment and tissue only); • PFOS & PFOA (sediment and tissue only); and

Ambient Monitoring – Years 1, 2 and 3

The targeted list of CECs will be monitored at six (6) to eight (8) ambient sites located in the Delta and vicinity in water column, sediment and/or tissue matrices, according to the matrix shown in Table 2 of this work plan. Tissues used in the Central Valley pilot study will either be fish and bivalve tissue samples obtained as part of the Delta RMP mercury monitoring effort in 2018 or will be fish and bivalve tissues available from other tissue collection efforts in the Delta in the vicinity of the selected water column or sediment sampling sites. Proposed in-Delta ambient monitoring sites are a subset of monitoring sites monitored by the Delta RMP for other parameters, consistent with Delta RMP efforts to leverage ongoing sampling efforts wherever possible. Proposed in-Delta sites include the Sacramento River at Hood and San Joaquin River at Vernalis. Should funds allow, the San Joaquin River at Buckley Cove and Sacramento River at Freeport sites are also recommended as lower priority in-Delta locations. The Sacramento River at Veterans Bridge, San Joaquin River at Vernalis, and American River at Discovery Park sites will be used to provide information on “background” levels of CECs in waters entering the Delta. The locations of proposed ambient sites are shown in Figure 1. Monitoring of ambient sites will be performed for three years, during the wet season and dry season. The proposed frequency of ambient monitoring during each year is described in Table 3 of this work plan. The frequency of ambient monitoring during Year 3 is contingent on interpretation of detected results and priority information needs from the first two years of monitoring.

6 Some laboratories can analyze chlorinated phosphates with the same method as Galaxolide. Addition of chlorinated phosphates will be evaluated for potential cost impacts and the available funding level depending on final sampling and analysis plan.


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POTW Effluent and Urban Runoff Characterization Monitoring – Years 2 and 3

In Year 2, in addition to ambient monitoring, two POTW effluent(s) and two urban runoff characterization locations will be monitored. Selection of the CECs to be monitored in Year 3 will be based on Year 1 and Year 2 ambient monitoring results (i.e. CECs detected in samples collected in Year 1). Because of the limited urban area within the Delta, upstream out-of-Delta urban runoff and POTW characterization locations may be monitored.

Gradient Studies – Year 3

In Year 3, two POTW gradients will be monitored. CECs monitored in the gradients will depend on those CECs detected in Year 2 POTW source monitoring. The gradient monitoring will consist of one upstream station and up to five downstream stations, as suggested in the State Water Board’s 2016 Statewide Monitoring Plan. The decisions on the specific locations and number and spacing of gradient sites will be made during Year 2. The gradient study may be reduced in scope or omitted if other information needs are higher priority given the available Delta RMP funding.

Methods

Research and commercial analytical methods are available for the list of CECs in this work plan. Because of the low concentrations and potentially low effect levels, sample collection and analysis methods must be robust to avoid or otherwise quantify contamination and other systematic method biases. It is recommended that the stakeholders establish a CEC Technical Workgroup to implement the work plan through the Delta RMP.

Analytical The analytical methods for the targeted CECs included in this proposed pilot study are provided in Table 4.

Sampling and Handling The sampling methods, sample containers, holding times, and sample preservation methods for the proposed Central Valley CEC pilot study will follow the recommendations provided in the 2015 Southern California Coastal Water Research Project (SCCWRP) QA/QC guidance document7. The CEC Technical Workgroup will consider and implement recommendations and request input from the Delta RMP Technical Advisory Committee (TAC) when necessary.

Quality Assurance/Quality Control The CEC Technical Workgroup will implement the QA/QC methods for the proposed Central Valley CEC pilot study that will follow the methods outlined in the SCCWRP QA/QC guidance document. Field blank, field duplicate, and inter-laboratory duplicate samples will be included in the quality control sample collection schedule.

7 Nathan G. Dodder, Alvine C. Mehinto, and Keith A. Maruya, “Monitoring of Constituents of Emerging Concern (CECs)in Aquatic Ecosystems – QA/QC Guidance” (Southern California Coastal Water Research Project Authority, 2015), https://www.waterboards.ca.gov/water_issues/programs/swamp/cec_aquatic/docs/qaqc_guidance_final.pdf.


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COMMUNICATION PLAN – DATA ANALYSIS AND REPORTING

Data collected through work plan implementation will be evaluated according to the Delta RMP Communication Plan and associated schedule. Pilot study ambient data (along with its associated QA/QC data) will be uploaded to the California Environmental Data Exchange Network (CEDEN). Source monitoring locations (POTW effluent and urban runoff characterization) will be identified within reports as based on latitude and longitude, but will not be specifically designated as characterization of a specific POTW or MS4. The interpretation of results by the Delta RMP will be performed only when a process is established that considers the adequacy of the work plan technical assessment tools and known system variability to determine appropriate threshold values to assess beneficial use impacts. A draft interpretive report summarizing the work performed, methods, data analysis and conclusions will be prepared after the completion of the proposed pilot study. The draft report will follow adopted Delta RMP processes for report preparation. A final interpretive report will be prepared which addresses comments received by the Delta RMP TAC and Steering Committee on the draft report. The ability to interpret data developed under the proposed pilot study is limited by the lack of available information for the target CECs regarding environmental effects. Threshold values in water, sediment and/or tissues largely do not exist or are not of sufficient quality to determine answers to the management question, “Is there a problem or signs of a problem?” This limitation must be clearly stated in the communication plan for the work plan monitoring effort. Care must be taken to avoid the use of “detection” as an indication of “problems” in the aquatic environment. During and following Year 2 of this pilot study, the overall scope of Year 3 efforts will be determined based on a prioritization of information needs.

FUNDING AND ESTIMATED COSTS

It is expected that the Delta RMP will fund the sample collection and analysis effort for all ambient waters, sediments, and tissues through existing participation fees and the addition of new ongoing and special study participating Delta RMP members. The Delta RMP may leverage in-kind services from other monitoring programs. The scope of this proposed pilot study will be reduced, as necessary, to match available funding. The estimated costs for the proposed CEC pilot monitoring program are detailed in Table 5 and Table 6 of this work plan.


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Tables and Figure

Table 1. Technical Approaches to Address Assessment Questions

2016 Statewide Monitoring Plan Monitoring Questions Technical Approach to Address Monitoring Questions

POTWs 1. Which CECs are detected in freshwaters and in which California

watersheds are they detected? • Monitor to determine detection of CECs at boundaries and within the

legal Delta over multiple years and conditions. 2. Can the CECs be shown to originate from the inland WWTP, or are they

present at background concentrations? • Comparison of upstream and downstream location concentrations.

3. How quickly (i.e., at what distance) do the CECs attenuate once discharged?

• Perform gradient study to evaluate concentration at multiple locations downstream from discharge to evaluate CEC attenuation over distance.

4. What are the concentrations and loadings of target CECs in the dry vs. wet seasons?

• Comparison of wet and dry season concentrations and loadings at individual source characterization and ambient sites.

5. Do the new occurrence data change the estimated monitoring trigger quotients (MTQs)?

• Compare maximum detected ambient values to determine if site-specific MTQ is greater than or less than unity (1).

6. Which detected CECs have been found to accumulate in sediments and fish tissue?

• Comparison of detected water column concentrations to paired sediment and tissue samples. Calculation of average accumulation ratios.

MS4s 1. Which CECs are detected in waterways dominated by stormwater? • Monitor to determine detection at American River at Discovery Park

during wet weather conditions 2. What are their concentrations and loadings in the dry vs. wet seasons? • Comparison of wet and dry season concentrations and loadings at

individual source characterization sites. 3. What is the relative contribution of CECs in WWTP effluent vs.

stormwater? • Comparison of wet and dry weather source characterization loading

estimates for urban area runoff and POTW discharge relative to ambient flux.

4. What is the spatial and temporal variability in loadings and concentration (e.g. between storm variability during the wet season; in stream attenuation rate during low flow, dry season conditions)?

• There is insufficient sample collection included in the work plan to perform a robust variability assessment; however, significant trends may be detectable when evaluated with other (external) data and work by MS4s (e.g. statistical loading models).


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Table 2. Proposed Target CECs and Matrices to Be Monitored During the Central Valley CEC Pilot Study

Analyte1

Matrix

Water Sediment2 Tissue3

Estrone --- --- Ibuprofen --- --- Bisphenol A --- --- 17-beta-estradiol --- --- Galaxolide (HHCB)4 --- --- Diclofenac --- --- Triclosan --- --- Triclocarban --- --- PBDE-47 ---

PBDE-99 ---

PFOS ---

PFOA ---

Notes: 1. The list of analytes sampled at a site during Year 3 of the pilot study may be reduced based on monitoring results obtained during Years 1 and 2 of the pilot study. 2. Sediment sample collection to be coordinated with the State Water Board’s Stream Pollution Trends Monitoring Program (SPoT). 3. Tissue sample collection to be coordinated with Delta RMP mercury monitoring effort. 4. Pending available funding for laboratories and quality control samples.


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Table 3. Monitoring Frequency Proposed for Central Valley CEC Pilot Study

Year Matrix No. of Monitoring Sites Samples/Year Total Samples1

1

Water (receiving) 6-8 4 24-32 Water (effluent) 0 --- --- Water (stormwater source) 0 --- --- Sediment (receiving) 6-8 4 24-32 Tissue (fish) 4 2 8 Tissue (bivalve) 4 2 8

2

Water (receiving) 6-8 4 24-32 Water (effluent) 2 4 8 Water (stormwater source) 2 4 8 Sediment (receiving) 6-8 2 12-16 Tissue (fish) 4 2 8 Tissue (bivalve) 4 2 8

3

Water (receiving2) 10-18 2 20-36 Water (effluent) 2 2 4 Water (stormwater source) 2 2 4 Sediment (receiving) 0 --- --- Tissue (fish) 0 --- --- Tissue (bivalve) 0 --- ---

1. Total samples shown in this table do not include field-collected QA/QC samples (i.e., field blanks, field duplicates, and inter-laboratory split samples) that will be collected at some frequency for each monitoring event during the 3-year pilot study. 2. Receiving water monitoring includes gradient monitoring at one location upstream and up to five locations downstream of two POTW discharges.


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Figure 1. Central Valley CEC Pilot Study Ambient Monitoring Locations


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Table 4. Analytical Methods Proposed for Measuring Concentrations of Target CECs in Various Matrices

Analyte Matrix Method Analytical

Laboratory [1]

Estrone, 17-beta-estradiol

Water

AXYS MLA-075: HM-Aneg (EPA Method 1698) AXYS

EPA 1694M-APCI Weck

Ibuprofen, Bisphenol A, Triclosan, Triclocarban

AXYS MLA-075: PPCP List 3 (EPA Method 1694, Table 7) AXYS

EPA 1694M-ESI- (no Triclorcarban) Weck Galaxolide (HHCB) LS1433 USGS NWQL Galaxolide (HHCB) EPA 1694M-ESI+ Weck [2]

Diclofenac AXYS MLA-104: PPCP List SA AXYS EPA 1694M-ESI- Weck

TCEP, TCPP, TDCPP Sediment

AXYS MLA-101 AXYS Galaxolide (HHCB) EPA 1694M-ESI+ Weck PBDE-47, PBDE-99 Sediment,

Tissue AXYS MLA-033 (EPA Method 1614A) AXYS EPA 1614M Weck

PFOS, PFOA

Sediment AXYS MLA-041 AXYS EPA 537M Weck

Tissue AXYS MLA-043 AXYS EPA 537M Weck

Notes: [1] AXYS Analytical Services, Sidney, British Columbia. Weck Laboratories, Inc., City of Industry, CA. USGS National Water Quality Laboratory (NWQL), Denver, CO. [2] TCEP, TCPP, TDCPP are chlorinated phosphates that could be analyzed with this method


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Table 5. Estimated Analytical Costs for Central Valley CEC Pilot Study

Constituents Matrix Total Cost/

Sample

Total Cost/ Sample

Augmented

Estrone, Ibuprofen, Bisphenol A, 17-beta-estradiol, Galaxolide (HHCB)*, Diclofenac, Triclosan*, PBDE-47*, PBDE-99*, PFOS*

Water (receiving) $1,510 $2,560

Water (effluent) $1,510 $2,560

Sediment (receiving)* $1,650 $2,325

PBDE-47, PBDE-99, PFOS, PFOA

Tissue (fish) $1,350 $1,350

Tissue (bivalve) $1,350 $1,350 Notes: •Costs based on AXYS estimates, however chlorinated phosphates are not included and AXYS cannot perform Galaxolide •Weck Analytical can perform all analyses including Galaxolide and chlorinated phosphates analysis, but cannot readily perform Triclocarban analysis


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Table 6. Estimated Annual and Total Monitoring Costs for Central Valley CEC Pilot Study

Notes: •Costs are estimates are planning level only and are based on expected level of effort and interpretation of work plan and document

guidance. •Estimate assumes some level of coordination with the SWAMP SPoT sediment and Delta RMP MeHg fish tissue and includes only

incremental labor required for additional sample collection. •Costs include total program costs, and some labor may be provided in-kind or as part of other programs. •Cost estimate worksheet is intended as a tool to evaluate the relative effect of changes to program assumptions. •Cost based on initial AXYS estimate, however, other labs are under consideration and may alter overall cost.


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Delta RMP Pesticides Monitoring Options for

FY18/19for discussion by the Delta RMP Technical Advisory Committee

March 15, 2018

BackgroundIn fall of 2017, SC allocated a planning budget of ~ $250,000

In addition, funds are available via SWAMP to support toxicity testing, up to $315,040 per year over next two fiscal years (July 2018 to June 2020.)

Pesticides Subcommittee has met 4 times this spring

Considered 2 main options, and possibly a “hybrid” of these – each answers a different set of management questions

SC has indicated interest/support in option 2 (which samples in more locations with lower frequency) while possibly maintaining montly sampling at 2 locations where toxicity has been observed during the first 2 years of monitoring.


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Where we are at in the proposal development process● Contracted with a professional statistician – advising and developing on

power analysis. This will tell us how many samples (and how long) it will take to answer the study’s questions with a reasonable level of confidence and statistical power (i.e. that observed effects did not occur by random chance)

● Proposal(s) to be finalized in March, reviewed and ranked by TAC in April (special meeting by phone/online?)

● Package to SC will indicate technical feasibility, desirability, and level of support among TAC members for each proposal, highlighting any dissenting opinions.

● ASC recommendation: Monitoring to begin in new water year, Oct 1, 2018. (Syncs with other programs, allows additional 2 months for developing Quality Assurance Program Plan, QAPP)

Designing in response to External Review critiqueInvolving a professional statistician in monitoring design

Developing Data Quality Objectives for each design, systematic planning process with 7 steps:

1. State the problem2. Identify management decisions and goals of the study3. Identify the inputs to the decision

a. Target Parametersb. Sources of Information

4. Boundaries of the Study5. Develop analytical approach and decision rule6. Specify tolerable limits on decision errors (i.e., Data Quality Objectives)7. Optimize the design for obtaining data


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Common ElementsBoth proposed studies would collect samples to be analyzed for toxicity and a suite of current use pesticides

Propose to continue using USGS lab at Sacramento State for its unique capability to test 170+ analytes, low detection limits, competitive cost

Toxicity testing at UC Davis Aquatic Health Program Laboratory – 4 species used in first 2 years (fathead minnow, single-cell algae, Hyalella, Ceriodaphnia)

Add an additional test species, Chironomus riparius (larvae of freshwater midges : More sensitive to fipronil and more sensitive in chronic exposures to imidacloprid than Ceriodaphnia dubia. Fipronil is recognized as a concern in the Delta, may be present in POTW discharges or urban runoff, no widespread ag. use.

Option 2. Delta-wide random samplingSplit the Delta into basins and select random sites within each basin

One or more of these areas is assessed each year over the rotation cycle. A rotation cycle is commonly five or more years in length.

Typically 20-30 samples allow you to characterize a resource with ±12% error.

Simple random Systematic Stratified random


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Questions it can answerPercent of the basin where aquatic toxicity is observed.

Percent of basin where pesticide concentrations exceed a water quality standard or benchmark during the monitoring season.

Identify spatial patterns in aquatic toxicity and pesticide concentrations within the basin to inform decisions about sensitive habitats, sources, and strata for future designs.

Less statistical power for analyzing the linkage between pesticide concentration and toxicity, but still possible to some extent.

Possibility of detecting higher chemical concentrations, greater toxicity in smaller tributaries; Toxicity Identification Evaluations (TIEs) may yield more results.

Option 1. Monthly Sampling at Key LocationsSimilar to monitoring design during first 2 years of sampling. However, we would only monitor at locations where toxicity has been observed in the past.

● San Joaquin River at Vernalis● Sacramento River at Hood ● San Joaquin River at Buckley Cove● Ulatis Creek at Brown Road● Liberty Island or Cache Slough


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Questions the study can answer● Test for the co-occurrence of aquatic toxicity and pesticide concentrations.● Determine when and where pesticide concentrations exceed water quality

standards or other numeric thresholds. ● After several years, ability to detect trends

Pros and Cons of (1) monitoring at fixed sitesPros:

● Supports conclusions about conditions at specific sites or areas of concern.● Increases statistical power for trend detection● Assists in determining

○ - Frequency of criteria exceedance○ - How conditions vary by seasons/flow○ - Processes○ - If regulatory actions are effective

Cons:

● Does not give insight into conditions in rest of the Delta.


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Pros and Cons of (2) Random SamplingPros:

● More robust characterization of a smaller area● Generates more granular data at smaller spatial scales

Cons:

● Would take 5+ years to cover the whole Delta

● Increased field sampling costs (requires a boat, increased travel)● Difficult to compare conditions between basins because of annual differences

in weather, hydrology● Difficult to determine trends because of infrequent surveys of same basin

Pros and Cons of running 2 studies in parallel● Overall: Allows for greater geographic coverage while maintaining some

continuity.● Con: for random sampling, reduced number of samples each year● Pro: continuing monthly monitoring at certain sites maintains continuity of

historical record● Con: monthly sampling not the best experimental design for follow-up

investigation of causes of toxicity – a special study may be preferable. ● Con: Lower statistical power means it will take more years of monitoring

before we can answer management questions with confidence.


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Management and Assessment QuestionsStatus and Trends

1. To what extent do current use pesticides contribute to observed toxicity in the Delta? 1. Which pesticides or degradates have the highest potential to be causing toxicity in the Delta and therefore should be the

priority for monitoring and management?A. If samples are toxic, do detected pesticides explain the toxicity?B. If samples are not toxic, do detected pesticide concentrations exceed other thresholds of concern (e.g., water quality

objectives or Office of Pesticide Programs aquatic toxicity benchmarks)?2. What are the spatial and temporal extents of lethal and sublethal aquatic and sediment toxicity observed in the Delta?

A. Do aquatic or sediment toxicity tests at targeted sites indicate a toxic response?B. If answer to A is yes, which other toxicity indicator(s) should guide monitoring and management of pesticides in Years

2+?1. What are the spatial/temporal distributions of concentrations of currently used pesticides identified as likely causes of observed

toxicity?2. Which pesticides have the highest risk potential (based on DPR’s risk prioritization model) and should be included in chemical

analyses?A. Is the list of pesticides included in USGS pesticide scan sufficient for Delta RMP monitoring design?B. Are methods available to monitor pesticides with high-risk potential not included in USGS pesticide scan?

1. How do concentrations of the pesticides with the highest risk potential vary seasonally and spatially?

Management Questions (contd.)Sources, Pathways, Loadings, and Processes

1. What are the principal sources and pathways responsible for aquatic and sediment toxicity observed in the Delta? 2. What are the fates of prioritized pesticides and degradates in the environment?

3. Do physical/chemical properties of priority pesticides, application rates and processes, and ambient conditions influence thedegree of toxicity observed?

4. What are the spatial/temporal use patterns of priority pesticides?

Forecasting Scenarios1. How do pesticide concentrations respond to different management scenarios?2. What current use pesticide loads can the Delta assimilate without exceeding water quality criteria established to protect

beneficial uses?3. How will climate change affect concentrations and/or loadings of pesticides and impacts to aquatic species?

Effectiveness Tracking1. Are pesticide-related toxicity impacts decreasing over time?


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Delta RMP Pesticides Monitoring Proposal 1 Monitoring Aquatic Toxicity and Current Use Pesticides at Five Fixed-Station Integrator Sites

Data Quality Objectives/Systematic Planning Steps

Step 1 State the Problem A better understanding of the effects of contaminants on the aquatic resources and beneficial uses of the Delta is a priority for regulators and stakeholders. Pesticide use in the Delta and Central Valley is constantly changing, presenting a challenge for resource managers and policy makers trying to understand the fate and effects of these contaminants. Therefore, baseline monitoring of water samples for both aquatic toxicity and a broad list of current use pesticides is needed to understand whether current use pesticides contribute to observed toxicity in the Delta. Step 2 – Identify the management decisions to be informed by Delta RMP pesticide data

Delta RMP Management Questions and Assessment Questions


Management Question:

“Is water quality currently, or trending towards,* adversely affecting beneficial uses of the Delta?”

*Note that this proposal is focused on current conditions, and has limited power to assess trends, and detecting trends is not among the main objectives. Assessment Questions:

Collect monthly data for one year on aquatic toxicity and pesticide concentrations in water samples at fixed input stations.

Data can be used to test for the co-occurrence of aquatic toxicity and pesticide concentrations. Determine when and where pesticide concentrations exceed water quality standards or other numeric thresholds.


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S&T 1 - “To what extent do current use pesticides contribute to observed toxicity in the Delta?” S&T 1.1A - “If samples are toxic, do detected pesticides explain the toxicity?”


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Step 3: Identify the inputs to the decision

Data and Information Sources

Information Source Water column chemistry Conventional parameters + panel of 174 current use pesticides

and degradates monitored by USGS (not listed). Water column toxicity 4-5 species, acute and chronic endpoints, plus water quality

parameters required by testing (See table below) Proposed Thresholds of concern (to be determined as part of forthcoming Interpretive Report analysis)

− Adopted Basin Plan Objectives − California Toxics Rule Objectives; − OW Aquatic Life Criteria − OPP Aquatic Life Benchmarks − OPP Benchmark Equivalents (DPR) − Basin Plan Lowest LC50 / 10

Water Column Toxicity Testing Parameters

Constituent Rational

Alkalinity as CaCO3 Ammonium as N Electrical Conductivity Hardness as CaCO3 Oxygen, Dissolved pH Specific Conductivity Temperature

Measurements required by the toxicity testing methods;

Ceriodaphnia dubia (Reproduction) (Survival)

More sensitive to the presence of organophosphorus (OP) pesticides.


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Hyalella azteca (Survival) Most sensitive to low levels of pyrethroid pesticides

Pimephales promelas (Larval biomass) (Larval survival)

Representative for fish toxicity, which is an important management concern in the Delta.

Selenastrum capricornutum (Growth) Herbicide toxicity

Chironomus

More sensitive to fipronil and more sensitive in chronic exposures to imidacloprid than C. dubia Fipronil is recognized as a concern in the Delta, may be present in POTW discharges or urban runoff, no widespread ag. use

Step 4: Boundaries of the Study

Property Definition Spatial boundaries 5 fixed input locations in the Delta

- San Joaquin River at Vernalis - Sacramento River at Hood - Buckley Cove - Ulatis Creek at Brown Road - Liberty Island

We have chosen 5 sites to maximize spatial coverage with available budget while continuing monthly sampling. 4 of the 5 sites have been monitored by the Delta RMP in the past, and toxicity has been observed, along with detections of dozens of priority current use pesticides. No toxicity has been observed at the Mokelumne R. site, hence we propose dropping it. Liberty Island is a good candidate for monitoring, as little pesticides and toxicity monitoring has been done there, and it


5

is important site for fish habitat and investments in ecological restoration, while also being adjacent to agricultural land uses.

Temporal boundaries Monitoring will be approved for one Water Year (October 1, 2018-September 30, 2019). Add information about monthly sampling plus opportunistic storm and runoff. Ideally, the study would be conducted for X years in order to answer the management question Y above. (Information to be added pending power analysis.) If additional funding is approved, the end date of the project may be extended.


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Step 5: Develop analytical approach and decision rule See column 2 and 3 in the table below. Step 6: Specify tolerable limits on decision errors (i.e., Data Quality Objectives) See column 4 in the table below.


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Questions to Answer with Delta RMP Pesticide Data

Analytic Approach Decision Rule Data Quality Objectives Power Analysis


8

Causes of toxicity 1. Evaluate the co-

occurrence of aquatic toxicity and pesticides

2. Evaluate whether pesticides are present at levels greater than risk thresholds

Metrics for toxicity: 1. Binary variable (0/1, or

True/False) indicating whether significant toxicity was observed (stratified by species, and possibly by endpoint)

2. Continuous variable - Percent effect observed for individual toxicity tests: reduction in organism survival, reproduction, or growth compared to control.

Metrics for pesticides: 1. Continuous variable: Observed

concentration of individual pesticides, in ng/L

2. Binary variable (0/1 or True/False) Individual pesticide observations exceeding a risk threshold

3. Frequency with which individual pesticides exceed a threshold.

4. Cumulative frequency of

exceedance (for one or all pesticides)

5. Cumulative frequency of

exceedance for classes of pesticides grouped by type or mode of action (organophosphate and pyrethroids)

6. Pesticide Toxicity Index*

Statistical Test: -Logistic Regression All data from all sites will be pooled for the test? Analyze individual sites if there is sufficient statistical power? Null hypothesis: 1. Ho: Toxicity is not

related to exposure to pesticides. (There is no relationship between pesticide levels and toxicity.) Ha: There exists a relationship between pesticide exposure and the toxicity.

2. Ho: Frequency of toxicity no different in “exposed population” vs. unexposed populations. Ha: Exposed populations are more likely to exhibit a toxic response, i.e. reduction in one or more endpoint). (Note: it is critical that we define what exposure is.)

1. The test should be able to detect a 25% effect1 of pesticide exposure with a Type 1 error of <0.1 and a Type 2 error of <0.2 (80% power).

2. The test should be able to detect a 25% effect size (whether a pesticide is greater than 75% of a threshold value) with a Type 1 error of <0.1 and a Type 2 error of <0.2 (80% power).

Note: Power analysis is pending. Power analysis will show: How many samples are needed to determine whether concentrations exceed relevant regulatory or risk-based thresholds? Dataset to use for evaluation: Delta RMP FY15/16 and FY16/17 CUP Monitoring.


9



3. Ho: Average pesticide concentrations is less than risk threshold(s). Ha: Pesticide concentration is greater than or equal to the threshold.

*The Pesticide Toxicity Index is a screening tool to assess potential aquatic toxicity of complex pesticide mixtures by combining measures of pesticide exposure and acute toxicity in an additive toxic-unit model. See:

Nowell, Lisa H., Julia E. Norman, Patrick W. Moran, Jeffrey D. Martin, and Wesley W. Stone. “Pesticide Toxicity Index—A Tool for Assessing Potential Toxicity of Pesticide Mixtures to Freshwater Aquatic Organisms.” Science of The Total Environment 476–477 (April 2014): 144–57. https://doi.org/10.1016/j.scitotenv.2013.12.088.

Step 7: Optimize the design for obtaining data The proposed study design, repeated monitoring at fixed stations, is acceptable for the purpose of evaluating co-occurrence of toxicity and pesticide exposure (essentially a comparisons to thresholds). The only designs that rank higher for this category of test are probabilistic. Probabilistic designs offer better spatial coverage for these comparisons but they can miss short term events that repeated monitored would capture. Therefore, the fixed station design offers an acceptable alternative to achieve the study

1 *Note: We are working with our consulting statistician to put into words what a 25% effect size means in the context of the chosen hypothesis test. E.g.: An effect size of 25% means that exposure to a pesticide results in a 25% reduction in reproduction, survival, or growth. In general, large effect sizes (e.g. 80% reduction in survival) are easier to detect with smaller sample sizes, while small effect sizes (10% reduction in survival) are more difficult to differentiate from random chance and need a much larger number of samples to detect.)


https://doi.org/10.1016/j.scitotenv.2013.12.088

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objectives. While the design is acceptable, the fixed stations chosen for this study are integrator sites which risk dilution of upstream sources and do not provide information on interior sites. Alternative Sampling Designs ***Recommended. ** Good alternative. * May provide relevant information. (No stars) Not likely to provide useful information.

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Probabilistic *** ** ** ** • Supports conclusions about conditions across the entire Delta, and about any strata or subpopulations defined through poststratification in the data analysis (e.g. by waterbody type/size, land use, or subregion)

• Best suited for sediments

• Would represent a snapshot in time that may not represent typical conditions = limited temporal analysis

• Difficult to identify causal relationships and assess influence of flow and other factors

• Reduced power to detect small changes over time

Stratified Random, e.g. by land use

** ** ** ** ** • Stratified designs generally increase accuracy • Provides spatial balance • Enables standard statistical methods to be

used (with assumptions) • Precision/power a direct function of sample

size and metric variability

• Difficult to replace dropped sites and maintain spatial balance

• Requires additional information to stratify, e.g. land uses

• No exact estimator for variances; there are only approximations

Rotating Basin Probabilistic

*** * *** ** • More robust characterization of a smaller area • Generates more granular data at smaller

spatial scales • Reduced field sampling costs (less travel time) • Better power to detect small changes than full

probabilistic design.

• Takes 5+ years to cover the whole area • Difficult to compare conditions between

basins because of annual weather changes • Difficult to determine trends because of

infrequent surveys of same basin


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Sampling Design

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Pros Cons

Trends monitoring at fixed/targeted individual sites

*** ** ** * * • Supports conclusions about conditions at specific sites or areas of concern.

• Increases statistical power for trend detection • Assists in determining

− Frequency of criteria exceedance − How conditions vary by seasons/flow − Processes − If regulatory actions are effective

• Transferability of data to unmonitored locations is limited

Fixed/targeted sites located at important inflows

** ** * * Supports • Limited characterization of spatial and

temporal variations in loadings • Assessment of yields to inform the

placement of best management practices for pesticide loading reductions.

• Relating of results to changes upstream

• Not informative about interior locations • No ability to identify hotspots or sources.

Define areas of special interest

** * * ** ** • Allows to judiciously define either strata or areas to sample with higher probability

• Risk of inherent bias


1

Delta RMP Pesticides Monitoring Proposal 2 Monitoring Aquatic Toxicity and Current Use Pesticides Using a Rotating Basin Probabilistic Design

Data Quality Objectives/Systematic Planning Steps

Step 1 State the Problem A better understanding of the effects of contaminants in the apparent decline in fish populations in the Delta is a priority for regulators and stakeholders. Pesticide use in the Delta and Central Valley is constantly changing, presenting a challenge for resource managers and policy makers trying to understand the fate and effects of these contaminants. Less than half of the pesticides currently applied in the watershed are routinely analyzed in monitoring studies and new pesticides are continually being registered for use. Therefore, baseline monitoring of water samples for both aquatic toxicity and a broad list of current use pesticides is needed to understand whether current use pesticides contribute to observed toxicity in the Delta. Step 2 – Identify the management decisions to be informed by Delta RMP pesticide data

Delta RMP Management Questions and Assessment Questions


Management Question:

“Is water quality currently, or trending towards, adversely affecting beneficial uses of the Delta?” Assessment Questions: S&T 1 ‐ “To what extent do current use pesticides contribute to observed toxicity in the Delta?” (Note: with lower statistical power.) S&T 1.1A ‐ “If samples are toxic, do detected pesticides explain the toxicity?”

Collect data for one season on aquatic toxicity and pesticide concentrations in water samples at multiple probabilistically‐determined sampling locations within a subarea or basin of the Delta. One or more of these areas is assessed each year over the rotation cycle. A rotation cycle is commonly five or more years in length.

Data can be used to report the percent of the basin where aquatic toxicity and co‐occurrence of pesticides greater than risk‐based thresholds were observed during the index season. Data can be used to identify spatial patterns in aquatic toxicity and pesticide concentrations within the basin to inform decisions about sensitive habitats, sources, and strata for future designs.


2

S&T 1.2. What are the spatial and temporal extents of lethal and sublethal aquatic and sediment toxicity observed in the Delta? S&T 2 ‐ What are the spatial/temporal distributions of concentrations of currently used pesticides identified as likely causes of observed toxicity?


3

Step 3: Identify the inputs to the decision

Data and Information Sources

Information Source Water column chemistry Conventional parameters + panel of 154 current use pesticides

and degradates. Water column toxicity 4-5 species, acute and chronic endpoints, plus water quality

parameters required by testing (See table below) Thresholds of concern − Adopted Basin Plan Objectives

− California Toxics Rule Objectives; − OW Aquatic Life Criteria − OPP Aquatic Life Benchmarks − OPP Benchmark Equivalents (DPR)

Water Column Toxicity Testing Parameters

Constituent Rational

Alkalinity as CaCO3 Ammonium as N* Electrical Conductivity* Hardness as CaCO3* Oxygen, Dissolved pH Specific Conductivity Temperature

Measurements required by the toxicity testing methods; *required for ILRP compliance reporting

Ceriodaphnia dubia (Reproduction) (Survival)

More sensitive to the presence of organophosphorus (OP) pesticides.

Hyalella azteca (Survival) Most sensitive to low levels of pyrethroid pesticides


4

Pimephales promelas (Larval biomass) (Larval survival)

Representative for fish toxicity, which is an important management concern in the Delta.

Selenastrum capricornutum (Growth) Herbicide toxicity/compliance requirement for ag coalitions

Chironomus

More sensitive to fipronil and more sensitive in chronic exposures to imidacloprid than C. dubia Fipronil is recognized as a concern in the Delta, may be present in POTW discharges or urban runoff, no widespread ag. use


5

Step 4: Boundaries of the Study Property Definition Spatial boundaries For each year, the geographic extent would be one or more of

the Delta sub‐areas (“basins”) delineated in Delta RMP’s 2018 nutrients modeling report.1 Over a 5‐year period, the whole Delta would be sampled. Sample locations within a basin will be selected at random using the method Generalized Random Tesselation Stratified (GRTS).2 Initially, the GRTS design would not be stratified (such as by habitat type) but such stratification may be added later. The probabilistic design could be customized to include a few historic Delta RMP sampling sites to maintain continuity for trends. However, the power to detect trends with repeat samples once every 5 years would be extremely low.

Temporal boundaries Samples will be collected from all the sites in the basin during an index season.

• Summer, irrigation season? • Spring runoff? • Critical time for target species (such as breeding of

Delta smelt)?

Step 5: Develop analytical approach and decision rule See column 2 and 3 in the table on the next page. Step 6: Specify tolerable limits on decision errors (i.e., Data Quality Objectives) See column 4 in the table on the next page.

1 Delta RMP FY 2016–17 Nutrients Synthesis: Modeling to Assist Identification of Temporal and Spatial Data Gaps for Nutrient Monitoring 2 https://science.nature.nps.gov/im/datamgmt/statistics/r/advanced/grts.cfm


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Spatial extent of pesticide, toxicity occurrence

Report the percent of the basin where aquatic toxicity and co‐occurrence of pesticides greater than risk‐based thresholds were observed during the index season. What is the average pesticide concentration in the basin? Over what percentage of the basin does a pesticide concentration exceed a threshold?

Secondary objective that can be evaluated qualitatively: Identify spatial patterns in aquatic toxicity and pesticide concentrations within the basin to inform decisions about sensitive habitats, sources, and strata for future designs.

1. Metric for toxicity: Binary variable (0/1 or True/False) indicating whether significant toxicity was observed (can be stratified by species) 2. Metric for pesticides: ‐Individual pesticide concentrations ‐ Individual pesticide frequency of exceedance ‐ Cumulative frequency of exceedance 3. Metric for determining cause of toxicity: outcome of Toxicity Identification Evaluations (TIEs)

Population estimates will be made using open source R software (‘spsurvey’).3 Population estimates are not a statistical test. There is no null hypothesis. The result will be a percent of basin water area meeting a certain condition such as: ‐Percent of basin with significant aquatic toxicity ‐Percent of basin with pesticide concentrations above risk based thresholds ‐Percent of basin with significant toxicity AND pesticide concentrations above risk based thresholds Each estimate will have known error bars which can be used to test for differences between years or basins if the effects of weather in different years is controlled.

The sample size for each basins should be large enough to be able to estimate the percent of basin water area with a certain condition with error bars of ±10% Assume a Type 1 error of <0.1 and a Type 2 error of <0.2 (80% power).

TBD. Power analysis will be performed after details in columns 2, 3, and 4 are decided. Dataset to use for evaluation: ‐Delta RMP FY15/16 and FY6/17 CUP Monitoring. ‐Other datasets with better spatial coverage?

3 https://cran.r-project.org/web/packages/spsurvey/spsurvey.pdf


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Step 7: Optimize the design for obtaining data The proposed study design, rotating basin probabilistic, is excellent for the purpose of understanding the spatial extent of toxicity and pesticide concentrations. The rotating basin approach will allow for enough samples in each basin to characterize the variance of concentrations in the basin. A weakness of the approach is that basins will be sampled in different years under different weather conditions. Therefore, comparisons between basins will be compromised. It will also take 5 years to collect data for the whole Delta. Alternative Sampling Designs ***Recommended. ** Good alternative. * May provide relevant information. (No stars) Not likely to provide useful information.

Sampling Design

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Pros Cons

Probabilistic *** ** ** ** • Supports conclusions about conditions across the basin, and about any strata or subpopulations defined through poststratification in the data analysis (e.g. by waterbody type/size, land use, or subregion

• Best suited for sediments

• Would represent a snapshot in time that may not represent typical conditions = limited temporal analysis

• Difficult to identify causal relationships and assess influence of flow and other factors

• Reduced power to detect small changes over time

Stratified Random, e.g. by land use

** ** ** ** ** • Stratified designs generally increase accuracy • Provides spatial balance • Enables standard statistical methods to be

used (with assumptions) • Precision/power a direct function of sample

size and metric variability

• Difficult to replace dropped sites and maintain spatial balance

• Requires additional information to stratify, e.g. land uses

• No exact estimator for variances; there are only approximations


8

Sampling Design

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Pros Cons

Rotating Basin Probabilistic

*** * *** ** • More robust characterization of a smaller area • Generates more granular data at smaller

spatial scales • Reduced field sampling costs (less travel time) • Better power to detect small changes than full

probabilistic design.

• Takes 5+ years to cover the whole area • Difficult to compare conditions

between basins because of annual weather changes

• Difficult to determine trends because of infrequent surveys of same basin

Trends monitoring at fixed/targeted individual sites

*** ** ** * * • Supports conclusions about conditions at specific sites or areas of concern.

• Increases statistical power for trend detection • Assists in determining

− Frequency of criteria exceedance − How conditions vary by seasons/flow − Processes − If regulatory actions are effective

• Transferability of data to unmonitored locations is limited

Fixed/targeted sites located at important inflows

** ** * * Supports • Limited characterization of spatial and

temporal variations in loadings • Assessment of yields to inform the

placement of best management practices for pesticide loading reductions.

• Relating of results to changes upstream

• Not informative about interior

locations • No ability to identify hotspots or

sources.

Define areas of special interest

** * * ** ** • Allows to judiciously define either strata or areas to sample with higher probability

• Risk of inherent bias


1

DATE: March 1, 2018

TO: Delta RMP Steering Committee

FROM: Matthew Heberger, Program Manager, Aquatic Science Center

RE: Science Advisor Job Description

At the fall 2017 joint meeting, Steering Committee members requested a brief “job description” for science advisors.

Background: The FY17/18 Workplan included a $10,000 budget to cover honoraria and travel for up to 4 independent science advisors. The advisors would be selected by the Steering Committee with input from the TAC and would commit to a 3-4 year term. Having advisors work with the Program over multiple years is efficient because they will become familiar with the Program and be able to help with adaptive management and review technical reports. The Bay RMP uses this approach to have ongoing, independent peer review of plans and final reports. However, the Bay RMP does not have a formal agreement or written job description for science advisors.

Job Description: The Delta RMP seeks to work with scientists who can lend their expertise according to our needs and their skills and interest. This includes reviewing proposed monitoring plans, draft reports, and other program documents and giving comments on how these documents can be improved. We would like to have advisors attend one meeting per year in person; it could be a meeting of our Technical Advisory Committee, which is a single day usually from 10 am to 4, or a technical subcommittee meeting, which are typically a maximum of 3 to 4 hours long. Further, we would also expect advisors to be available for infrequent, informal, consultations with program staff to answer questions or discuss technical matters by phone and email. It is difficult to give an exact estimate for time commitment, but will likely be on the order of 5 – 15 hours per quarter.

The science advisor program is not a formal program review. Nor do we expect a great deal of written material in the form of reports or papers.


Science Advisor List Pesticides

Interested Title FirstName LastName Expertise Affiliation Email Phone Notes WebsiteNo Mr. Brian Anderson Toxicology, Pesticides, Contaminant Effects UC Davis [email protected] 831-254-4791 www.granitecanyon.org/

Yes Dr. Gary Cherr Toxicology, Pesticides, Contaminant Effects UCD [email protected] (707) 875-2051http://bml.ucdavis.edu/research/faculty/gary-cherr/

Dr. Richard Connon Toxicology, Pesticides, Contaminant Effects UCD [email protected]+1 530 752 3141

http://www.vetmed.ucdavis.edu/faculty/results.cfm?fid=19083

Yes Dr. Jerry Diamond Toxicology, Pesticides, Contaminant Effects Tetra [email protected]

Jerry is an expert in ecological risk assessment, monitoring designs, and environmental assessments in addition to ecotox

http://www.tetratech.com/en/experts/dr-jerry-diamond-ecotoxicology-and-risk-management-expert

maybe-follow up Dr. Ed Furlong pesticides, CECs USGS [email protected] 303-236-3941 suggested by Jay Davis

https://www.usgs.gov/staff-profiles/edward-furlong?qt-staff_profile_science_products=3#qt-staff_profile_science_products

Yes Mr. Gregory Goodwin pesticides, nutrients [email protected]

nominated by Rich Breuer. "We have worked with Waterborne on the central valley CoPST pesticide modeling project with CALFED and DWR. They suggested Greg Goodwin, who has expertise in pesticide and nutrient monitoring in the Central Valley and an expert in sensors and data."

Ms. Kathryn Kuivila Toxicology, Pesticides, Contaminant EffectsUSGS Oregon Water Science Center [email protected] (503) 251-3257 historic local knowledge

Dr. Jeff Miller Toxicology AQUA-Science [email protected] (530) 753-5456over 4 decades of toxicity pesticide expertise. Based in Davis, CA. Suggested by staff of USEPA.

Yes Dr. Justin Miller-Schulze Toxicology, Pesticides, Contaminant Effects CSUS [email protected] 916-278-7409http://www.csus.edu/chem/bios/miller-schulze.html

No Dr. Kelly Moran chemistry, CECs TDC [email protected] Suggested by Phil Trowbridge

http://www.tdcenvironmental.com/styled-2/styled-4/index.html

Yes Mr. Patrick Moran Toxicology, Pesticides, Contaminant Effects USGS [email protected] (253) 552-1646Expert in ecotoxicology and pesticide monitoring programs https://water.usgs.gov/nawqa/pnsp/

Yes Dr. Lisa Nowell Toxicology, Pesticides, Contaminant EffectsUSGS California Water Science Center [email protected] 916-278-3096

primary focus is to track, interpret and model the occurrence of pesticides in stream water and sediment at the regional scale; and to interpret data on sediment toxicity and ecological condition in relation to chemical stressors

https://www.usgs.gov/staff-profiles/lisa-nowell?qt-staff_profile_science_products=3#qt-staff_profile_science_products

Yes Dr. Christopher Salice Toxicology, Pesticides, Contaminant Effects Towson University [email protected] 410-704-2083Ecotoxicity (including pesticides), ecological modeling, bioenergetic markers

https://www.towson.edu/fcsm/departments/biology/facultystaff/csalice.html

Yes Dr. Daniel Schlenk Toxicology UC Riverside [email protected] (951) 827-2018

Already an advisor to the Bay RMP. Nominated by Jay Davis. From his web page: "His research focuses on understanding the biochemical factors that influence susceptibility to environmental and natural chemicals. Four specific projects involve the impact of climate change on environmental factors that influence detoxification strategies in aquatic organisms; mechanistic investigations of the effects of salinity on pesticide toxicity in fish; the role of biotransformation as a mechanism of tolerance to natural and man-made toxic agents; impacts of endocrine disrupting chemicals on aquatic organisms; and mechanisms of PAH developmental toxicity in fish."

https://envisci.ucr.edu/faculty/schlenk.html

Yes Dr. Shane Snyder Toxicology, Pesticides, Contaminant Effects University of Arizona [email protected] 520-621-2573http://snyderlab.arizona.edu/content/dr-shane-snyder

Mr. Donald P. Weston Toxicology, Pesticides, Contaminant Effects UCB [email protected] (510) 665-3421 local experiencehttps://vcresearch.berkeley.edu/faculty/donald-p-weston

Yes Dr. Thomas Young Toxicology, Pesticides, Contaminant Effects UCD [email protected] (530) 754-9399 environmental chemistry and non-target analyseshttps://faculty.engineering.ucdavis.edu/young/

Mr. Marty Williams pesticides, hydrology [email protected]

http://www.waterborne-env.com/bio/marty-williams/








Science Advisor List Statistics

Interested Title FirstName LastName Expertise Affiliation Email Phone Website Notes

Dr. Elizabeth BoyerEnvironmental Statistics, Monitoring Design Penn State University [email protected] 814-865-8830

http://ecosystems.psu.edu/directory/ewb100

Environmental Statistics, Environmental Chemistry, Biogeochemistry, Water Quality, Algae Blooms, Nutrient Cycling, Nutrient Pollution, Trace Metals, Hydrology, Environmental Education

Yes Dr. Tom GriebEnvironmental Statistics, Monitoring Design Tetra Tech, Inc. [email protected]

Expertise: Behavior of metals in the aquatic environment and the application of statistical methods to characterize uncertainty in simulation models and environmental data sets. Has worked with the San Francisco Bay Clean Estuary Partnership to develop the conceptual model for mercury in San Francisco Bay. Has served as technical lead and project manager for several other TMDL projects in the Bay-Delta including the Copperand Nickel TMDL project for South San Francisco Bay and the Guadalupe River Watershed Mercury TMDL. Is currently the project manager for the technical studies supporting the development of the Selenium TMDL in North San Francisco Bay.

Interested, but may not be available. Will let us know.Dr. Dennis HelselEnvironmental Statistics, Monitoring Design USGS and private [email protected]

http://www.practicalstats.com/consulting/credentials.html

Dennis and Ed Gilroy (USGS) specialize in water resources and environmental data. Both are very knowledgeable and helpful.

No Dr. James LimbrunnerEnvironmental Statistics, Monitoring Design Tufts University [email protected]

http://engineering.tufts.edu/cee/people/limbrunner/

Hydrologist and environmental statisitician. Useful perspective from outside the watershed.

Yes Dr. Ramzi MahmoodEnvironmental Statistics, Monitoring Design CSUS [email protected] 916-278-6127

http://www.ecs.csus.edu/wcm/ce/people/mahmood.html

Dr. Ganapati PatilEnvironmental Statistics, Monitoring Design Pennsylvania State University [email protected]

814-883-2814 or 814-865-9442 http://stat.psu.edu/people/gpp

Statistical ecology, environmental statistics, risk analysis, multiscale advanced raster map analysis, and surveillance geoinformatics

Yes Mr. Steve SaizEnvironmental Statistics, Monitoring Design Water Boards [email protected] (805) 549-3879

We have a staff person at our Central Valley Board (Steve Saiz) who has also helped Dr. Helsel develop training, peer reviewed his books, etc. But Steve is busy working on stuff for RB3 most of the time, but perhaps we could figure out a way to borrow some of his time.

Yes Dr. Ken SchiffEnvironmental Statistics, Monitoring Design SCCWRP [email protected] 714-755-3202 www.sccwrp.org I spoke with him and he confirmed his interest & availability. - Stephen McCord

Dr. Donald WellerEnvironmental Statistics, Monitoring Design Smithsonian Environmental Research [email protected] 443-482-2214

http://serc.si.edu/labs/ecological-modeling

Ecological Modeling, mathematical modeling, statistics, and spatial analysis to explore the ecological health of wetlands, streams, and estuaries and nutrients

Yes Dr. Neil WillitsEnvironmental Statistics, Monitoring Design UCD [email protected]

https://www.stat.ucdavis.edu/stat-lab/staff.html




http://stat.psu.edu/people/gpp

Science Advisor List Other

Name Expertise Affiliation Email Phone Website Notes

Steve Balogh MercuryMetropolitan Council Environmental Services, St. Paul, MN [email protected]

Expertise: Served as project leader on a number of studies regarding the fate and transport of Hg and MeHgwithin wastewater treatment plants, and on the relative contributions of wastewater treatment plants to loads ofHg and MeHg in receiving streams. Has directed projects addressing diffuse (nonpoint) sources of Hg andMeHg in rivers and streams. Since 1992, has operated an analytical laboratory for the trace determination of Hgand MeHg in environmental matrices.

Brian Branfireun MercuryProfessor, University of Western Ontario, London, Ontario, Canada [email protected]

Expertise: Studies hydrology, ecology and biogeochemistry of wetland-dominated environments from theCanadian sub-arctic to the sub-tropics of Mexico. Areas of research address mercury cycling and transport,particularly as it pertains to methylation and association with organic matter, as well as controls on mercurymethylation and demethylation processes. Has expertise in wetland hydrology, and has published research oncontaminant fate and transport in urban environments.

John Cain Mercury

Conservation Director for California Floodplain Management, American Rivers, Berkeley, CA [email protected]

Expertise: Has 15 years experience with the interrelated issues of river restoration, water supply management,water quality, and flood risk reduction in California’s Central Valley and the Bay-Delta ecosystem. Has plannedor actively participated in the planning of several large scale efforts that could affect the fate and transport ofmethylmercury in the Bay Delta ecosystem, including the 1200 acre Dutch Slough tidal marsh restorationproject, increasing the frequency of inundation on the Yolo Bypass, restoring flow to the San Joaquin River,subsidence reversal ponds on Twitchel island, management of the Marsh Creek watershed, geomorphicanalysis of Cache Creek, reservoir re-operation, the Bay Delta Conservation Plan, and the Central Valley FloodProtection Plan. 2

Dave Krabbenhoft MercuryResearch Hydrologist & Geochemist, US Geological Survey, Middleton, WI [email protected]

Expertise: Has 24 years experience in environmental mercury research, with specific expertise on thebiogeochemistry of important processes that control transport, bioaccumulation and toxicity. Has worked on awide range of environments across the United States, including several projects in the Bay-Delta system. Hasbeen directly involved with three of the largest ecosystem restoration efforts ever undertaken in the US,including the Everglades, Great Lakes, and San Francisco Bay, all of which have significant mercurycontamination concerns.

Carol Kelly Mercury R&K Research, Canada [email protected]

Expertise: Mercury and carbon biogeochemistry in lakes, wetlands and estuaries, mercury methylation,bioavailability of mercury for methylation, mercury transport, field-based investigations, and whole ecosystem10 Charge to Delta Mercury TAC, 2/01/12; updated 3/22/2017manipulations including mercury additions and wetland flooding. Also familiar with QA/QC programs for mercuryanalyses in water, sediment, and biota. Tangential areas: nitrogen and sulfur cycling in lakes, acid rain, primaryproduction, methanogenesis, anaerobic and aerobic decomposition.

Mark Grismer Hydrology

Professor of Hydrology and Biological and Agricultural Engineering, UC Davis, Davis, CA [email protected]

Expertise: Wetland design, hydrology and transport, urban runoff and irrigation, drainage management or wateruse. Also studies soil erosion and runoff processes on agricultural lands, water movement in the watershed andshallow subsurface and associated water quality problems, water quality in wetland systems, and managementsolutions.


Meeting Materials for Item 10: sent separately to TAC members


Delta RMP Deliverables Stoplight Report

Delta RMP Deliverables Scorecard Report

Key to Status Colors:Green indicates greater than 90 days until the deliverable is due.Yellow indicates a deliverable due within 90 days.Red indicates a deliverable that is overdue.

Project Primary Deliverable Assigned To Due Date Status Comments

1

Cross-Delta MonitoringUsing High-Frequency Tools

Report from USGS on Cross-Delta High FrequencyMonitoring Project

Philip Trowbridge 03/31/19 Will consist of three cruises conducted three timeson three successive days in May, August andOctober corresponding to periods of high nutrienttransformation. The product will be a final technicalreport.In Sept 2017, USGS met with the NutrientsSubcommittee and finalized the 3 cruise tracks.In Sept 2017, USGS attempted one cruise but raninto technical problems. The NutrientsSubcommittee decided to postpone the project so all3 cruises will happen in Water Year 2018,commencing in spring, once flows recede. This willput the final report due in early 2019 as a draft.Final report should include a discussion of how theHF data should be used in the context of othermonitoring data.

2 Delta RMP (FY15/16) CUP Monitoring Annual Monitoring Report forFY15/16 CUP Monitoring

Thomas Jabusch 02/28/17 Complete Data need to be uploaded to CEDEN by 2/1/17.

3

Delta RMP (FY15/16) Pathogens Study - Year 2 Sample Collection and DataManagement of Year 2Pathogens Data

Amy Franz 07/31/17 Complete Data from BioVir and Eurofins. Formatting,transcribing field collection information, performingQA/QC review, and uploading field and analyticalresults to SFEI's RDC database and replicating toCEDEN. Expected to be complete by June 15, 2017.

4 Delta RMP (FY15/16) Pathogens Study - Year 2 Quality Assurance Report onYear 2 Pathogens Data

Don Yee 07/31/17 Complete QAO report. Funded from Data Managementbudget.

5 Delta RMP (FY16/17) Governance Financial Subcommittee reportand conference call

Philip Trowbridge 01/05/17 Complete

6 Delta RMP (FY16/17) Governance Steering Committee Meeting #3and Summary


7 Delta RMP (FY16/17) Program Management FY17/18 Annual Workplan andBudget

Philip Trowbridge 02/10/17 Complete Draft for Finance Subcommittee sent 4/19/17. Finalby 6/30/16.

8

Delta RMP (FY16/17) Program Management Updated Monitoring Design Philip Trowbridge 02/15/17 Complete Deliverable not relevant for this fiscal year. Followingthe External Review, the Monitoring Design isexpected to need a major revision, which is morethan was planned for FY16/17. Minor revisions, suchas updating the target analyte lists, would be awaste of effort at this point. The update to theMonitoring Design will have its own budget line forFY17/18.

9 Delta RMP (FY16/17) Governance TAC Meeting #3 and Summary Thomas Jabusch 03/15/17 Complete

10 Delta RMP (FY16/17) Governance Steering Committee Meeting #4and Summary

Matthew Heberger 05/05/17 Complete

11 Delta RMP (FY16/17) Governance TAC Meeting #4 and Summary Matthew Heberger 06/14/17 Complete

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12

Delta RMP (FY16/17) Quality Assurance QAPP Update Thomas Jabusch 06/14/17 As of March 2018, we have resolved all commentsand suggestions made by the SWAMP QA officer.We have received provisional approval and areworking to draft a new requested element: aStandard Operating Procedures (SOP) document ondata review, verification, and validation.

13Delta RMP (FY16/17) Communications Preparation of a Factsheet Thomas Jabusch 06/30/17 Complete The draft factsheet was discussed at SC meetings in

Jan and May 2017. The final draft is out forcomments now and will be presented for approval atthe Jul 28 meeting.

14 Delta RMP (FY16/17) Communications Technical Workshop / summarymemorandum of findings

Philip Trowbridge 06/30/17 Complete SC decided not to hold a technical workshop inFY16/17.

15Delta RMP (FY16/17) CUP Monitoring 6. Field Sampling Report for

FY16/17 CUP MonitoringPhilip Trowbridge 09/29/17 Complete The Steering Committee decided at its July 28, 2017

meeting that this report was not necessary andshould be cancelled.

16Delta RMP (FY16/17) CUP Monitoring 6. Data Management of

FY16/17 CUP DataAmy Franz 12/31/17 Complete Electronic data delivered by USGS in October 2017.

ASC staff have finalized provisional data upload butdata will not be made public until reviewed by TACand approved by SC.

17Delta RMP (FY16/17) CUP Monitoring 6. Quality Assurance Report for

FY16/17 CUP MonitoringDon Yee 12/31/17 As of 2/28/2018, this is in progress. We are following

up with the labs on some missing recordsdiscovered in the course of reviewing the data.

18Delta RMP (FY16/17) Mercury 8. Mercury YR1 report

summarizing fish and wateranalyses

Matthew Heberger 12/31/17 Draft report distributed to Mercury Subcommittee inDecember 2017.

19Delta RMP (FY16/17) Nutrients Synthesis 7A1.3 Status and Trends

Synthesis Report - Preparesynthesis report

Thomas Jabusch 01/31/18 Complete Draft report has been distributed to the NutrientsSubcommittee and the TAC. We will be requestingapproval from SC to publish at Jan 2018 meeting.

20Delta RMP (FY16/17) Nutrients Synthesis 7B2.5 Modeling Synthesis

Report - Prepare technicalreport.

Thomas Jabusch 01/31/18 Complete Draft report has been distributed to the NutrientsSubcommittee and the TAC. We will be requestingapproval from SC to publish at Jan 2018 meeting.

21

Delta RMP (FY16/17) Nutrients Synthesis 7C3.1 Nutrients- AdvancedStatistical Modeling

Thomas Jabusch 01/31/18 Marcus Beck of SCCWRP (formerly USEPA) ispreparing this manuscript in-kind. Funding allocatedis for ASC review of the manuscript. The manuscriptwas submitted to ES&T in May 2017, but it wasrejected. The manuscript has been revised andresubmitted to ECSS. The submitted manuscriptwas shared with the Nutrients Subcommittee.

22 Delta RMP (FY16/17) CUP Monitoring 6. Permit Compliance Data forILRP

Amy Franz 02/01/18 Complete Not necessary in FY18, per agreement with agcoalitions

23Delta RMP (FY16/17) CUP Monitoring 6. Annual Monitoring Report for

FY16/17 CUP MonitoringThomas Jabusch 02/28/18 Complete The SC voted on 7/28 that this was no longer

necessary, and that funds for this task should bereallocated to the Interpretive Report.

24 Delta RMP (FY17/18) Contract and FinancialManagement

Quarterly Financial Update #1 Matthew Heberger 07/15/17 Complete

25 Delta RMP (FY17/18) SC Meetings Steering Committee Meeting #1and Summary


26Delta RMP (FY17/18) Continued Nutrient Data

Analysis and BiennialReporting

Design additional statisticalanalyses to be completed inFY17/18


27 Delta RMP (FY17/18) TAC Meetings TAC Meeting #1 and Summary Matthew Heberger 10/06/17 Complete





30 Delta RMP (FY17/18) TAC Meetings TAC Meeting #2 and Summary Matthew Heberger 11/07/17 Complete

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31 Delta RMP (FY17/18) Technical Reports RFP for Pesticides/ToxicityInterpretive Report

Matthew Heberger 11/15/17 Complete RFP issued in in spring 2018, proposals due March16.

32Delta RMP (FY17/18) Science Advisors Recruit 2-4 science advisors Matthew Heberger 12/31/17 CVs have been collected and candidates screened

based on qualifications and willingness to volunteer.For discussion by the TAC in spring 2018 thenapproval by SC.



Complete additional statisticalanalyses and prepare technicalreport

Philip Trowbridge 12/31/17 Complete $27,000 of funds are available for this task.





36 Delta RMP (FY17/18) TAC Meetings TAC Meeting #3 and Summary Matthew Heberger 04/15/18


Quarterly Financial Update #4 Matthew Heberger 05/15/18


Matthew Heberger 05/15/18

39 Delta RMP (FY17/18) Program Planning FY18/19 Workplan and Budget Matthew Heberger 06/30/18

40 Delta RMP (FY17/18) Quality Assurance Revised QAPP for FY18/19 Matthew Heberger 06/30/18

41 Delta RMP (FY17/18) Communications "Pulse of the Delta" Draft Matthew Heberger 06/30/18

42

Delta RMP (FY17/18) Continued Nutrient DataAnalysis and BiennialReporting

Prepare, coordinate, andprovide technical support to upto 4nutrient subcommittee meetings

Philip Trowbridge 06/30/18 Meetings set for 9/29/17, 12/1/17, 1/18/18, 2/15/18.Desired outcomes: a) review and discuss completedstudies and reports, b) assess data needs relative toDelta RMP assessment questions, and c) developstudy designs and project plans for monitoring toaddress data gaps.



Outline for biennial synthesisreport to be completed inFY18/19

Philip Trowbridge 06/30/18

44Delta RMP (FY17/18) Chlorophyll Sensor

IntercalibrationPrepare, coordinate, andfacilitate Phase 1 TechnicalTeam Meetings

Philip Trowbridge 06/30/18 4 meetings are anticipated between 10/1/17 and6/30/18. Meetings held on 9/28/17 and 12/5/17.

45Delta RMP (FY17/18) Chlorophyll Sensor

IntercalibrationDevelop Phase 2 Project Plan,including study design, logistics,and institutional coordination

Philip Trowbridge 06/30/18

46 Delta RMP (FY17/18) TAC Meetings TAC Meeting #4 and Summary Matthew Heberger 07/31/18

47 Delta RMP (FY17/18) Mercury Monitoring Mercury Data Management Amy Franz 07/31/18

48 Delta RMP (FY17/18) Mercury Monitoring Mercury QA Memo Don Yee 07/31/18

49 Delta RMP (FY17/18) Program Planning Amended Charter (if necessary) Matthew Heberger 12/31/18

50 Delta RMP (FY17/18) Program Planning Amended Communication Plan(if necessary)

Matthew Heberger 12/31/18

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Delta RMP Action Items Stoplight Report

Key to Status Colors:Green indicates greater than 90 days until the deliverable is due.Yellow indicates a deliverable is due within 90 days.Red indicates a deliverable that is overdue.

Primary Meeting Date Deliverable Assigned To Due Date Status Comments

1

TAC Action Items from12/12/2017

12/12/17 Data Assessment Framework Workshop: Greg Gearheartwill have OIMA staff draft a white paper. The ad hocworkgroup will hold a conference call in mid-January andthe item will be included in the January 23, 2018 SteeringCommittee agenda, with a workshop tentatively plannedfor February.

Greg Gearheart 01/23/18 Update: Some initial planning had been done,but OIMA has informed us that they are nolonger willing to pay for this workshop. To bediscussed by the SC to determine whetherthis is still a priority, and whether they wish toallocate funding to cover it.

2 TAC Action Items from12/12/2017

12/12/17 Schedule a Pesticides Subcommittee meeting in the firsthalf of January



12/12/17 Edit the proposed changes to Delta RMP AssessmentQuestions for Nutrients memo as described above


4


12/12/17 Re: Science Advisors, Screen CVs based on the abovecriteria and bring results back to the March 15, 2018 TACMeeting; (2) draft the job description, including $2K/yearstipend, one in-person meeting (with expenses paid),review reports, and provide guidance on monitoringdesigns.


5TAC Action Items from12/12/2017

12/12/17 Summarize the committee’s understanding of the use ofReporting Limits and Method Detection Limits for inclusionin the Reporting Section of the QAPP

Matthew Heberger 07/31/18 To be done for the FY18/19 QAPP

6 SC Action Items 10/24/2017 10/24/17 Finalize the 7/28/17 Meeting Summary and post to the Matthew Heberger 11/30/17 Complete

7SC Action Items 10/24/2017 10/24/17 Email the Science Advisor Form to Steering Committee

members, as well as a reminder to TAC members tocontinue to submit additional nominations by the end ofthe year


8SC Action Items 10/24/2017 10/24/17 Forward the Delta Science Plan questionnaire to Steering

Committee members in advance of the January 23, 2018meeting

Matthew Heberger 01/15/18 Complete Included in agenda package.

9SC Action Items 10/24/2017 10/24/17 Tom Grovhoug will work with Linda Dorn and Greg

Gearheart to fund and host a half-day workshop to furtherdevelop the Assessment Framework.

Tom Grovhaug 02/28/18 Initial planning meetings have taken place.Coordinating Committee directed ASC to helpfacilitate and to budget up to $5K for this task.

10 SC Action Items 10/24/2017 10/24/17 evised grid and trial run results will be reviewed at theDecember TAC meeting

Brian Lauerson 12/12/17 Complete

11 SC Action Items 10/24/2017 10/24/17 Decision grid results should be presented to the SC in itsJanuary 2018 meeting

Brian Lauerson 01/23/17 Complete Pre-proposal for CECs is on the agenda.

12SC Action Items 10/24/2017 10/24/17 Greg Gearheart and Adam Laputz will work on the

clarifying language on Conflict of Interest for inclusion inthe Charter, consulting State Board legal counsel asneeded.

Adam Laputz 12/31/17 Email reminder sent March 2018.

13SC Action Items 10/24/2017 10/24/17 A workgroup will be formed to support Greg’s staff to draft

data visualization products for TAC and SC reviewMatthew Heberger 12/31/17 Complete Team participants include: Selina Cole,

Melissa Turner, Vyomini Upadhyay, StephenMcCord, and Matthew Heberger.


09/21/17 Prepare draft summary for 9/21 TAC meeting anddistribute to TAC members for comments



09/21/17 Set 3/15/18 meeting location and announce to TAC Matthew Heberger 10/15/17 Complete


09/21/17 Add a presentation on USGS high frequency monitoring to12/12/17 TAC Agenda


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09/21/17 Include a last updated time stamp on monitoring tabledata in future reports



09/21/17 Revise the Year 1 CUP data report incorporating TACcomments and distribute final draft to TAC members forapproval

Matthew Heberger 10/15/17 Complete September discussion was tabled pendingfurther review. To be discussed by TAC on12/12/2017.


09/21/17 Decision Grid Small Group: Revise the grid per discussionand conduct trial run and provide feedback on the process



09/21/17 Design an online form for collecting potential scienceadvisors



09/21/17 Send comments or suggested edits to the draft NutrientsSynthesis reports to ASC

TAC members 10/05/17 Complete

22 SC Action Items 7/28/2017 07/28/17 Finalize the 5/3/2017 SC Meeting Summary and post tothe program website


23SC Action Items 7/28/2017 07/28/17 Check on how TAC meetings are staffed and determine

whether ASC hours are warrantedMatthew Heberger 10/01/17 Complete We will be bringing fewer ASC staff to

meetings going forward. For example, onlywhen necessary to present on a special topic.Having a note-taker

24

SC Action Items 7/28/2017 07/28/17 Revise the charter to require Finance Committee approvalfor switching money between tasks. Up to $5,000 atdiscretion of the Implementing Entity, more than $5,000shall require FC approval, and more than $25,000 shallrequire approval by the Steering Committee.

Matthew Heberger 10/01/17 Complete Draft charter language to be voted on inOctober

25SC Action Items 7/28/2017 07/28/17 OIMA staff to prepare a visualization of Delta RMP

pesticides/toxicity data using Tableau, to include variouswater quality standards, benchmarks and thresholds foraquatic toxicity...

Greg Gearhart 10/24/17 Complete Greg will present the data viz at the10/24/2017 SC meeting.

26SC Action Items 7/28/2017 07/28/17 For the Decision Grid for ranking monitoring proposals,

consider (1) assigning points, (2) assigning weights, and(3) adding something related to statistical expertise in theexperimental design.

Matthew Heberger 09/21/17 Complete Two Workgroup meetings have been held. Tobe discussed at the 9/21 TAC meeting.

27

SC Action Items 7/28/2017 07/28/17 Provide comments on the Year 1 Pesticides Data Reportby end of August. Any suggestions that are interpretive innature will NOT be included in this report, but ratherforwarded to the authors of the forthcoming InterpretiveReport.

Steering Committee 08/31/17 Complete

28SC Action Items 7/28/2017 07/28/17 Put together SEP proposal for CEC monitoring Matthew Heberger 11/30/17 Complete ASC has provided expert review of the draft

monitoring plan jointly developed by theCentral Valley Regional Water Quality ControlBoard and the POTW and MS4 communities.


06/13/17 Draft and distribute for review “Highlights” with the mostimportant outcomes (action items, recommendations, etc.)of the meeting that would be presented to the SteeringCommittee.

Stephen McCord 06/30/17 Complete


06/13/17 Set 12/12/17 meeting location and announce to TAC Matthew Heberger 07/14/17 Complete

31


06/13/17 Review the revised pesticides data report and submit anyfinal comments by June 30 to Thomas Jabusch (ASC).Email the TAC ([email protected]) if you have majorconcerns that would prevent recommending to theSteering Committee that the report be approved

TAC members 06/30/17 Complete


06/13/17 Send out the next version of the FY15/16 Pesticides DataReport when any remaining comments and edits areincorporated, including both “clean” and “tracked changes”versions

Thomas Jabusch 07/10/17 Complete


06/13/17 Convene a meeting of the Pesticides Subcommittee forthe week of July 12



06/13/17 Develop a “strawman” set of options for the report,including staffing and cost


Page 2 of 5




06/13/17 Work with the permittees subgroup to further develop theevaluation criteria, and distribute it to TAC members forcomments/editing



06/13/17 Pesticides Subcommittee: Discuss the draft evaluationcriteria



06/13/17 With Brian Laurenson (LWA), compile optional processesfor the TAC to make consensus decisions


38 SC Action Items 5/3/2017 05/03/17 Finalize the 1/26/2017 SC Meeting Summary and post tothe program website


39 SC Action Items 5/3/2017 05/03/17 Determine the date and location for the Fall 2017 SteeringCommittee meeting and send invitation to the SC

Matthew Heberger 05/25/17 Complete Set for Oct 24

40 SC Action Items 5/3/2017 05/03/17 Update the Financial Memo with minor edits Matthew Heberger 05/11/17 Complete

41 SC Action Items 5/3/2017 05/03/17 Send out revised draft Fact Sheet to the SC to review withdeadline for comments


42SC Action Items 5/3/2017 05/03/17 Finalize minor portions of the FY17/18 Workplan that

require changes in response to input received at themeeting and the decision of the Steering Committee

Matthew Heberger 05/15/17 Complete Pesticides question still outstanding.

43

SC Action Items 5/3/2017 05/03/17 Present the SC with information from the TAC related tothe pesticides proposals: TAC meeting summary,pros/cons of the two approaches, slides showing how datafrom the proposed approaches would be interpreted toanswer management questions, and how the costs of theDelta RMP might change with external funding for certainaspects of the projects

Matthew Heberger 07/21/17 Complete The TAC requested additional guidance onhow to evaluate competing proposals, andhas begun a process for developing this, withthe approval of SC co-chairs.

44SC Action Items 5/3/2017 05/03/17 Prepare a revised scope and budget for the CUP/Toxicity

Year 1-2 Interpretative Report that includes synthesis ofreadily available information in the Delta, not just DeltaRMP data


45SC Action Items 5/3/2017 05/03/17 Regarding the Chlorophyll-a Intercalibration Study for

FY17/18, provide Gregg Gearheart with the specificsabout how partner agencies can participate



03/14/17 Reserve meeting room for 9/21 TAC meeting; send emailinvitation



03/14/17 Follow up with SFWCA and SWAMP regardingcontribution matching funds to support the chlorophyllsensor intercalibration effort


48


03/14/17 Look into whether a Delta RMP HABs monitoring projectwould be eligible for Water Board grant funding

Thomas Jabusch 03/31/17 Complete Talked to R. Breuer: Answer: Probably not atthis point. Very limited funding allocated toanother project for Delta satellite surveillanceand response. Another complication is theclosing of WPCL. There is currently no lab todo the analyses.


03/14/17 Revise Pesticides proposal 1 to include only one site,Sacramento River at Hood

Debra Denton 03/31/17 Complete

50


03/14/17 Revise pesticide proposal 2A with the trends option for alonger list of pesticides from the DPR model (removeother options) and add draft site selection criteria. Makesure the planning budget is sufficient for 3 meetingsbetween July 1 and September 30


51


03/14/17 In nutrients proposal package, increase the funding listedfor FY18/19 for the chlorophyll intercalibration study toindicate that we are embarking on a multi-year effort andlist other likely collaborators: USGS, SWAMP, DWR,NMS, Bay RMP, SFCWA


52


03/14/17 Prepare high-level summary of TAC-recommendedproposals for nutrients, Hg, and pesticides. To include thefollowing topics: 1) Management Drivers Addressed, 2)Assessment Questions Answered, 3) External ReviewComments Addressed, 4) Data Quality Objectives/NullHypothesis

Thomas Jabusch 04/15/17 Complete Add abstracts to each proposal with thisinformation.

Page 3 of 5




03/14/17 Prepare memo on power analysis for Pesticide Proposal 2to share with interested TAC members, including caveatsrelated to using a priori estimates of variance


54


03/14/17 Schedule a pesticide subcommittee meeting for the 2ndweek of April to discuss: data evaluation process andQAPP for Proposal 1, site selection criteria for Proposal 2,target analytes for Proposal 2, bullets on pros/cons of TACrecommendation to SC



03/14/17 Ask Regional Board staff to figure out if dropping PesticideProposal 3 will reduce the total revenue for FY17/18(because Ag coalitions may reduce their contribution).



03/14/17 Send draft CUP report to TAC as a Word document Thomas Jabusch 03/17/17 Complete


03/14/17 Schedule a webinar to present and discuss the CurrentUse Pesticides draft report



03/14/17 Schedule a webinar to present CD3 visualization, datadownload and metadata

Matthew Heberger 04/15/17 Currently in parking lot. Schedule forforthcoming TAC meeting?

59 SC Action Items 1/26/2017 01/26/17 Finalize the 10/18/16 Meeting Summary and post to thewebsite


60 SC Action Items 1/26/2017 01/26/17 Determine the location for the 7/28/17 meeting and sendan invitation to the SC


61

SC Action Items 1/26/2017 01/26/17 Confirm whether Delta RMP measurement methods formercury and ancillary parameters are compatible withother programs, to ensure that the data we collect can bereadily combined with data collected by others.

Thomas Jabusch 02/28/17 Complete Thomas has talked to USGS and MLML andconfirmed that the data collection andanalysis methods are the same, and there isno concern with comparing and combiningmercury data.

62SC Action Items 1/26/2017 01/26/17 Add an agenda for the next SC Meeting on the

Communications Plan and access topreliminary/provisional data. Use the technicalpowerpoints presented as a case study.

Philip Trowbridge 04/30/17 Complete Topic added to list of items for next SCmeeting.

63

SC Action Items 1/26/2017 01/26/17 ASC to discuss with State Board (Greg Gearheart andJanis Cooke) on developing options for HABs monitoring.Questions include: where does the Delta RMP fit in, howmight we complement other programs, what kind ofoptions are there for projects in the FY17/18 budget orSEP funds? ASC to work with Greg Gearheart (StateBoard) on this.


64 SC Action Items 1/26/2017 01/26/17 Nutrients subcommittee to discuss HABs at a futuremeeting, and to come up with options to present to the SC


65SC Action Items 1/26/2017 01/26/17 Organize a debrief meeting with State Board staff, USGS,

and ASC to develop lessons learned which might makethe CEDEN upload easier next time.

Matthew Heberger 02/28/17 Complete Meeting is scheduled for 3/6/17.

66

SC Action Items 1/26/2017 01/26/17 ASC will look into hiring administrative staff to performcertain roles, such as invoicing, taking meeting notes.

Matthew Heberger 02/28/17 Complete We have contacted Ms. Daphne Orzalli, whohas confirmed her interest and given us aquote for professional services at $40/hour.The finance committee will discuss the prosand cons at their next meeting.

67

SC Action Items 1/26/2017 01/26/17 Beginning July 2017, all financials will be reported forcurrent fiscal year only. Remaining funds from prior yearswill be rolled over to the current year.

Matthew Heberger 07/31/17 Complete We have looked into this issue and discussedit with our accountant and financial managerand concluded we can make a seamlesstransition without any issues. Frameworkpresented to Finance Subcommittee on4/25/2017, and approved.

68SC Action Items 1/26/2017 01/26/17 Prepare a memo for the next SC meeting with options for

setting fees with pros and consPhilip Trowbridge 04/30/17 Complete Slides discussing the options and preferred

alternative were prepared for the May 3meeting but the discussion was tabled andwill be presented on July 28.

69SC Action Items 1/26/2017 01/26/17 Create a 1- to 2-page factsheet about Delta RMP to help

with fundraising. Describe the purpose, accomplishments,and benefits.

Matthew Heberger 03/31/17 Complete Draft factsheet to be presented at the May 3Steering Committee meeting.

Page 4 of 5



70 SC Action Items 1/26/2017 01/26/17 Convene a meeting of the Revenue Subcommittee. Val Connor 04/30/17 Complete The Revenue Committee has met and isplanning future meetings.

71 SC Action Items 1/26/2017 01/26/17 Send a PDF of the nutrients presentations and links to the Matthew Heberger 02/01/17 Complete

72

SC Action Items 1/26/2017 01/26/17 Revise the response to the External Review Committee.Committee members to submit proposed language toASC. Following revisions, ASC will re-send the responseto the SC showing the edits in track changes. SCmembers will have one week to respond. If no commentsare received, the letter will be finalized and sent to thereviewers.


73 SC Action Items 1/26/2017 01/26/17 Schedule a meeting between Planning Committee and theIndependent Reviewers for March.

Yumiko Henneberry 02/10/17 Complete

74

SC Action Items 1/26/2017 01/26/17 Develop new text for Attachment 3 (the flowchart) to bediscussed at the fall SC-TAC meeting.

Matthew Heberger 09/30/17 Complete At the Jan 26, 2017 meeting, it wasdiscussed that the flowchart had served auseful purpose at the beginning of theprogram, allowing dischargers and regulatorsto come to a common understanding of howdata collected by the program would (andwould not) be used. However, it no longerreflects current policy or procedures. WaterBoard staff suggested replacing it with acouple of paragraphs.

Update October 2017: The flowchart will bereplaced by the Data Assessment Framework(under development).

75 SC Action Items 1/26/2017 01/26/17 Accept approved edits and post new Charter to website. Matthew Heberger 02/28/17 Complete

76SC Action Items 1/26/2017 01/26/17 Put on the agenda for a future SC meeting: How we will

be interacting with the Delta Science Program, especiallyas it regards the findings of the recent report State of Bay-Delta Science, 2016, which concerns us directly.

Philip Trowbridge 02/01/17 Complete Item added to agenda item parking lot.

77 SC Action Items 1/26/2017 01/26/17 Put on the agenda for a future SC meeting: CECworkshop and State Board CEC Guidance.

Philip Trowbridge 02/01/17 Complete Item added to agenda item parking lot.

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delta rmp technical advisory committee meeting€¦ · support among technical advisors and (3)...

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