Overview of TM6: Simulation of Selenium Fate and Transport in North San Francisco Bay Limin Chen, Sujoy Roy, and Tom Grieb Tetra Tech, Inc., Lafayette,

Slides:



Advertisements
Similar presentations
AN OVERVIEW Jay A. Davis San Francisco Estuary Institute.
Advertisements

Contaminant Fate WG 5 Year Plan RMP CFWG Meeting January 15, 2008.
Estimation of Mercury Bioavailability in Wastewater Treatment Plant Effluents J. David Dean San Francisco Estuary Institute Mercury Coordination Conference.
Ambient Water Toxicity in San Francisco Bay: Dr. Scott Ogle, Pacific EcoRisk Dr. Andrew Gunther, Applied Marine Sciences Paul Salop, David Bell,
Contaminants at the Estuary Interface Jon Leatherbarrow 1 Rainer Hoenicke 2 Lester McKee 1 1 San Francisco Estuary Institute 2 California Resources Agency.
Concentrations and loads of PCBs and OC pesticides in the Guadalupe River watershed Jon Leatherbarrow 1,2, Lester McKee 1, John Oram 1 1 San Francisco.
C OPPER AND N ICKEL TMDL D EVELOPMENT: L OWER S OUTH B AY.
Chesapeake Bay Environmental Model Package A coupled system of watershed, hydrodynamic and eutrophication models The same package used for the 2002 load.
TMDL Development for the Floyds Fork Watershed Louisville, KY August 30, 2011.
Selenium in North San Francisco Bay: Conceptual Model and Recommendations for Numerical Model Development Technical Memoranda 4 and 5 Prepared by Tetra.
OMSAP Public Meeting September 1999 The Utility of the Bays Eutrophication Model in the Harbor Outfall Monitoring Program James Fitzpatrick HydroQual,
Recent enhancements of the OTIS model to simulate multi-species reactive transport in stream-aquifer systems. Ryan T. Bailey 1 Department of Civil & Environmental.
Sensitivity Analysis of a Spatially Explicit Fish Population Model Applied to Everglades Restoration Ren é A. Salinas and Louis J. Gross The Institute.
Progress report: Biological mechanisms for Hg accumulation in largemouth bass Ben Greenfield San Francisco Estuary Institute Fish Mercury Project 2007.
Delta TRIM Hydrodynamic modeling in CASCaDE Nancy Monsen USGS/Menlo Park IEP Modeling Workshop Tuesday, May 26, 2009.
Hyojin Kim May 9 th 2008 California Water Symposium.
Preliminary Results No nutrients 5 psu 2 psu 0.5 psu + Nutrients 5 psu 2 psu 0.5 psu Foodweb support for the threatened Delta smelt: Salinity effects on.
The Aqutic Cycling of Mercury in the Everglades (ACME) Project: Challenges of Linking Field Data to Conceptual Models David Krabbenhoft, William Orem,
TMDL Development for the Floyds Fork Watershed Watershed Hydrology and Water Quality Calibration and Water Quality Model Calibration Technical Advisory.
Foodweb support for the threatened Delta Smelt: Summary of program objectives and preliminary results Anne Slaughter 1 and The CALFED Foodweb Research.
The effect of food composition on feeding, growth and reproduction of bivalves Sofia SARAIVA 1,3, Jaap VAN DER MEER 1,2, S.A.L.M. KOOIJMAN 2, T. SOUSA.
Foodweb support for the threatened Delta smelt: Microzooplankton dynamics in the low salinity zone of San Francisco Bay J.K. York 1, B. Costas 1, G. McManus.
Foodweb support for the threatened Delta smelt: your title here A. A. Author 1, B. B. Author 1, C. C. Author 2, D. D. Author 2 1 Romberg Tiburon Center.
NH Estuaries Project Environmental Indicators Phil Trowbridge, P.E. NHEP/DES Coastal Scientist June 15, 2006.
US Army Corps of Engineers ® Engineer Research and Development Center West Bay Diversion Evaluation 1-Dimensional Modeling CWPPRA Technical Committee and.
DR. PAUL A. BUKAVECKAS VIRGINIA COMMONWEALTH UNIVERSITY Developing water quality standards to Protect the James River against Impacts from Algal Blooms.
Chemical Aspects of GLOBEC- China Programs and Potential to GLOBEC-IMBER Study in China Jing Zhang 1. State Key Laboratory of Estuarine and Coastal Research,
1 Using Multi-temporal MODIS 250 m Data to Calibrate and Validate a Sediment Transport Model for Environmental Monitoring of Coastal Waters.
Interim Update: Preliminary Analyses of Excursions in the A.R.M. Loxahatchee National Wildlife Refuge August 18, 2009 Prepared by SFWMD and FDEP as part.
Selenium in San Francisco Bay Status: Possibly Impaired Standards: –Relevant Beneficial Uses: Fishing, wildlife habitat, rare and endangered species –Water.
A T HREE- D IMENSIONAL W ATER Q UALITY M ODEL OF S OUTHERN P UGET S OUND Greg Pelletier, P.E., Mindy Roberts, P.E., Skip Albertson, P.E., and Jan Newton,
BsysE595 Lecture Basic modeling approaches for engineering systems – Summary and Review Shulin Chen January 10, 2013.
A model of PCBs bioaccumulation in the blue mussel (Mytilus edulis) from the Bay of Seine C:/gemco/textes/meeting/setac/poster.ppt Véronique Loizeau and.
Collaborative Monitoring in the Great Lakes: Revisiting the Lake Michigan Mass Balance Project Collaborative Monitoring in the Great Lakes: Revisiting.
PART-2 Geochemical Equilibrium Models CASE STUDY: MINEQL+ An interactive data management system for chemical equilibrium modeling.
Courtney K. Harris Virginia Institute of Marine Sciences In collaboration with Katja Fennel and Robin Wilson (Dalhousie), Rob Hetland (TAMU), Kevin Xu.
Update on Chesapeake Bay Model Upgrade Projects Blue Plains Regional Committee Briefing November 30, 2004 Presented by: Steve Bieber Metropolitan Washington.
WQSTM Shallow-Water Simulation We received the shallow-water database from CBP circa autumn These are grab samples and measures collected when continuous.
Inputs to shelf seas- an overview Materials are introduced into coastal and shelf seas primarily through: rivers, atmosphere, groundwaters, ice processes.
Modeling Copper Runoff in San Francisco Bay Area Watersheds Jim Carleton US EPA.
NorCal SETAC 2001 Seafood Contamination and Consumption.
Benefits of the Redesigned RMP to Regional Board Decision Making Karen Taberski Regional Water Quality Control Board San Francisco Bay Region.
Value of Mass Balance Modeling in Formulating a PTS Reduction Strategy for the Great Lakes Joseph V. DePinto Limno-Tech, Inc. Ann Arbor, MI GLRC PBS Strategy.
Potential Impacts of Climate Change on Water Quality in the New York City Water Supply System Watershed Science and Technical Conference West Point, New.
Urban Environmental Biogeochemsitry Laboratory Chemical and Biological Impacts of Roadway Derived Contaminants Entering Stormwater Retention Systems S.
Role of the Texas Water Development Board in Environmental Flow studies Barney Austin Surface Water Resources Division Texas Water Development Board May.
Application of the CMAQ Particle and Precursor Tagging Methodology (PPTM) to Support Water Quality Planning for the Virginia Mercury Study 6 th Annual.
Impact of Watershed Characteristics on Surface Water Transport of Terrestrial Matter into Coastal Waters and the Resulting Optical Variability:An example.
Digital Map from Dr. William Bowen California State University Northridge Sacramento- San Joaquin Delta San Joaquin River Sacramento River Suisun Bay San.
BASINS 2.0 and The Trinity River Basin By Jóna Finndís Jónsdóttir.
Estimating future scenarios for farm-watershed nutrient fluxes using dynamic simulation modelling – Can on-farm BMPs really do the job at the watershed.
Development of the Neuse Estuary Eutrophication Model: Background and Calibration By James D. Bowen UNC Charlotte.
Estimating the Volume of Fine-Grained Sediments Behind Four Low-Head Dams, Kalamazoo River, Michigan. In cooperation with the Michigan Department of Environmental.
1. Digital Map from Dr. William Bowen California State University Northridge Sacramento- San Joaquin Delta San Joaquin River Sacramento River Suisun Bay.
The GEMCO PROJECT -2- The foodweb model The GEMCO project (Generic Estuarine Modelling system to evaluate transport, fate and impact of COntaminants) aims.
Abstract Man-made dams influence more than just the flow of water in a river. The build up of sediments and organic matter, increased residence times,
Copper Source Loading Estimates (Process Profiles) Physical & Chemical Characterization of Wear Debris (Clemson University) Water Quality Monitoring (ACCWP)
Selenium Aquatic Life Criteria and Implementation ORSANCO Technical Committee Meeting October 21, 2009 Holly Green, USEPA Office of Science and Technology.
1 Dynamic modeling in a representative watershed (Guadalupe) Michelle Lent, John Oram, and Lester McKee Sources Pathways and Loadings Workgroup May 6 th.
Nitrogen loading from forested catchments Marie Korppoo VEMALA catchment meeting, 25/09/2012 Marie Korppoo, Markus Huttunen 12/02/2015 Open DATA: Nutrient.
Model Description Sample Results Next Steps Monitoring Data (Initial Conditions) Hydrodynamics Water Quality USGS; DWR Monitoring Data (Initial Conditions)
Dave Clark and Michael Kasch
AQUATOX v. 3.1 Host Institution/URL
San Luis Drain Shutoff Simulations and Link-Node Recalibration
The Long Term Fate of PCBs in San Francisco Bay Jay A. Davis
Elizabeth River PCB TMDL Study: Numerical Modeling Approach
James River PCB TMDL Study: Numerical Modeling Approach
Cain, DJ, Carter, JL, Buchwalter, DB, and Luoma, SN
Introduction to the WASP Interface
Modeling Water Treatment Using the Contaminant Transport Module
Presentation transcript:

Overview of TM6: Simulation of Selenium Fate and Transport in North San Francisco Bay Limin Chen, Sujoy Roy, and Tom Grieb Tetra Tech, Inc., Lafayette, CA Presentation to TMDL Advisory Committee April 28, 2010

Overview Goal: Develop tool to calculate selenium in water and biota in response to different loads of selenium entering North San Francisco Bay  Technical Review Process  Modeling Approach  Selenium Loads  Example Calibration Results  Predicted Loads and Concentrations  Role of Boundary Conditions  Model Scenarios

Technical Review Committee ( ) Dr. Nicholas S. Fisher, State University of New York, Stony Brook Dr. Regina G. Linville, California State Office of Environmental Health Hazard Assessment Dr. Samuel N. Luoma, Emeritus, U.S. Geological Survey Dr. John J. Oram, San Francisco Estuary Institute The role of the Technical Review Committee was to provide expert reviews of the modeling process as well as credible technical advice on specific issues arising during the review. Final TM-6 report includes their comments and our responses.

Model Structure ECoS = Fate and transport modeling framework for selenium species DYMBAM = Dynamic Bioaccumulation Model for estimating bivalve concentrations TTF = Trophic Transfer Factor, ratio between food and predator tissue concentration

Red dots: approximate locations of model segments Yellow pins: sampling stations in Cutter and Cutter (2004) survey Model domain starts at Sacramento River at Rio Vista and extends to Golden Gate Study Domain

Model Components and Steps in Calibration 1. Salinity: relatively conservative (advection and dispersion) 2. Total Suspended Material: three components of PSP, BEPS and phytoplankton, result of advection, dispersion 3. Phytoplankton (Chl a): result of advection, dispersion, growth, respiration, and grazing 4. Dissolved selenium: selenite (SeIV), organic selenide (SeII), selenate (SeVI) 5. Particulate selenium: particulate elemental, particulate organic selenide, particulate adsorbed selenite + selenate Transformation modeled as first order reactions; transformations include: uptake by phytoplankton, adsorption/desorption, oxidation, mineralization

Modeling Steps During model calibration, adjustable parameters were varied to obtain a best fit to the data; for evaluation, the model was run with the fitted parameters and compared with new data sets Model calibrated to data from 1999, and tested against datasets from 2001, 2005, 1998 and 1986 Model applied in a predictive mode using historical hydrology and different load scenarios Tetra Tech worked with model developers (Shannon Meseck, John Harris) over the course of this work

Model Schematic 1-D model with 33 well-mixed cells representing the bay.

Selenium Transformations Represented by first-order rate constants.

Uptake by Bivalves Cmss is selenium concentration in tissue (μg/g), ku is the dissolved metal uptake rate constant (L/g/d), Cw is the dissolved metal concentration (µg/L), AE is the assimilation efficiency (%), IR is the ingestion rate (g/g/d), Cf is the metal concentration in food (e.g. phytoplankton, suspended particulate matter, sediment) (µg/g), and ke is the efflux rate (d -1 ).

Boundary Conditions are Important C, on the y-axis, represents a constituent being modeled. The model framework shown on the preceding slides involves the solution of a set of differential equations. These explain the shape of the curve. However, the boundary conditions also have an important effect on determining the actual magnitudes of C.

Annual Selenium Loads

Dissolved Loads for Water Year 1999

Particulate Loads for Water Year 1999

Example Calibration 1: Salinity (1999)

Example Calibration 2: Chlorophyll a (1999)

Example Calibration 3: Dissolved Selenium (1999)

Example Calibration 4: Particulate Selenium (1999)

TSM Long-Term Evaluation at USGS Stations

Evaluation of Chlorophyll a Suisun Bay San Pablo Bay Central Bay

Predicted Particulate Selenium Concentrations (1999)

Bivalve (C. amurensis) Concentrations

White Sturgeon Concentrations TTF = 1.7

Effect of Changing Boundary Conditions

Scenarios Examined ScenarioDescription 1Base case 2Removal of all point source loads (refineries, POTWs), and local tributary loads 330% reduction in refinery and San Joaquin River loads, dissolved only 450% reduction in all point sources (refineries, POTWs), local tributaries and San Joaquin River loads, dissolved only 5Increase dissolved selenium loads from San Joaquin River by a factor of 3, particulate loads remain the same as the base case 6Decrease dissolved selenium loads from San Joaquin River by a factor of 50%, particulate loads remain the same as the base case 7Increase particulate selenium loads associated with PSP, BEPS, and phytoplankton from Sacramento River by a factor of 3, dissolved loads remain the same as the base case 8Decrease particulate selenium loads associated with PSP, BEPS, and phytoplankton from Sacramento River by a factor of 50%, dissolved loads remain the same as the base case 9Increase San Joaquin River particulate loads by 3x, other loads stay the same 10A natural load scenario, where the point sources are zero, the local tributary loads and speciation are at Sacramento River values, and the San Joaquin River is at 0.2 µg/l, at current speciation

Impact on Dissolved Se

Impact on Particulate Se

Summary of Model Results The model is able to simulate key aspects of physical and biological constituents that affect selenium concentrations. During calibration, the model was able to fit the patterns in concentrations of dissolved and particulate selenate and selenite well, although it performed less well for the organic fractions. The model was also able to represent the observed variation in biota concentrations. The model is a valuable tool to explore selenium transport, fate, and bioaccumulation in the bay, and can be applied in analyses in support of the TMDL, as demonstrated through a set of example scenarios. A modeling study provides an opportunity to synthesize information from the system, and in doing so, highlights unknowns that may have a bearing on model predictions. This report presents a set of data needs for further evaluation such as characterization of boundary conditions, selenium loads from major sources, recent water column concentrations and speciation, as well as biota concentrations.

Impact on Bivalve Se