LCFR Water Quality Modeling Project Report Jim Bowen, UNC Charlotte LCFRP Advisory Board/Tech. Comm....

LCFR Water Quality ModelingProject Report

Jim Bowen, UNC Charlotte

LCFRP Advisory Board/Tech. Comm. Meeting, October 30, 2008

Raleigh, NC

Outline of Presentation

• A Quick Review of the LCFR Model

• Summary of Model Report

• Questions/Suggestions

Basis of Presentation

TechnicalReportDraft

(available on web)

LCFR Dissolved Oxygen ModelThe big picture

Estuary PhysicalCharacteristics: e.g. length,width, depth,roughness

EFDC SoftwareAdjustable Parameters:(e.g. BOD decay, SOD, reaeration)

Hydrologic Conditions

RiverFlows,Temp’s,Conc’sTides Time

“Met” DataAir temps,precip,wind,cloudiness

Time

State Variables

nutrientsDO, organic C

Time

Dissolved Oxygen Conceptual ModelBOD Sources

Sediment

Cape Fear, Black & NECF BOD Load

Muni & Ind. BOD Load

decaying phytopl.

Estuary Inflow BOD Load

Dissolved Oxygen Conceptual ModelBOD Sources, DO Sources

Sediment


Ocean Inflows

SurfaceReaeration

Phytoplank. ProductivityMuni & Ind.

BOD Load

decaying phytopl.

MCFR Inflows


BOD Consumption

Dissolved Oxygen Conceptual ModelBOD Sources, DO Sources & Sinks

Sediment Sediment O2 Demand


Ocean Inflows

SurfaceReaeration

Input of NECF & Black R. Low DO Water

Phytoplank. ProductivityMuni & Ind.

BOD Load

decaying phytopl.

MCFR Inflows


Steps in Applying a Mechanistic Model

1. Decide on What to Model

2. Decide on Questions to be Answered

3. Choose Model

4. Collect Data for Inputs, Calibration

5. Create Input Files

6. Create Initial Test Application

7. Perform Qualitative “Reality Check” Calibration & Debugging

Steps in Applying a Mechanistic Model, continued

8. Perform quantitative calibration & model verification

9. Design model scenario testing procedure (endpoints, scenarios, etc.)

10. Perform scenario tests

11. Assess model reliability

12. Document results

Description of Model Application

Open BoundaryElevation Cond.

Lower Cape Fear RiverEstuary Schematic

Black River FlowBoundary Cond.

Cape Fear R. FlowBoundary Cond.

NE Cape FearFlow Boundary Cond.

Description of Model Application

• Flow boundary condition upstream (3 rivers)

• Elevation boundary condition downstream

• 20 lateral point sources (WWTPs)

• Extra lateral sources add water from tidal creeks, marshes (14 additional sources)

• 37 total freshwater sources

Model State Variables• Water Properties

– Temperature, salinities

• Circulation– Velocities, water surface elevations

• Nutrients– Organic and inorganic nitrogen, phosphorus, silica

• Organic Matter– Organic carbon (labile particulate, labile and

refractory dissolved), phytoplankton (3 groups)

• Other– Dissolved oxygen, total active metal, fecal coliform

bacteria

Water Quality Model Schematic

Data Collected to Support Model

• Data Collected from 8 sources– US ACoE, NC DWQ, LCFRP, US NOAA, US

NWS, USGS, Wilmington wastewater authority, International Paper

• Nearly 1 TB of original data collected

• File management system created to save and protect original data

Observed Data Used to Create Model Input Files• Meteorological forcings (from NWS)

• Freshwater inflows (from USGS)

• Elevations at Estuary mouth (from NOAA)

• Quality, temperature of freshwater inflows and at estuary mouth (from LCFRP, USGS, DWQ)

• Other discharges (from DWQ)

EFDC Input Files & Data Sources

Lower Cape Fear

River Program

Sites Used

USGS Continuous Monitoring and DWQ

Special Study

Stations Used

New Cross- Sections Surveyed

by NC DWQ

SOD Monitoring

Stations Performed

by NC DWQ

LCFR Grid• Channel

Cells in Blue• Wetland

Cells in White

• Marsh and Swamp Forest in Green, Purple

LCFR Grid Characteristics• Grid based on NOAA bathymetry and previous

work by TetraTech• Off-channel storage locations (wetland cells)

based on wetland delineations done by NC DCM• 1050 total horizontal cells (809 channel cells,

241 wetland cells) • 8 vertical layers for each horizontal cell• Used a sensitivity analysis to locate and size

wetland cells

Model Grid

Showing Location and Size

of Wetland

Cells

Riverine Swamps

and Saltwater

Marshes in Estuary

(NC DCM)

Input File Specification

• Inflows

• Temperatures and Water Quality Concentrations at Boundaries

• Water quality mass loads for point sources

• Benthic fluxes

• Meteorological data

Riverine Inflow Specification

• Flows based on USGS flow data

• Flows scaled based upon drainage area ratios

• 17 total inflows– 3 rivers, 14 estuary sources

Subwatersheds Draining Directly to the Estuary

Temperature and Concentration Specification

• 5 stations used (3 boundaries, 2 in estuary)

• Combined USGS and LCFRP data

• Point source specification tied to closest available data

Procedure for creating water quality mass load file (WQPSL.INP)

• Used an automated procedure based upon available data (LCFRP, DMR’s)

Use data interpolation and estimation to create a monitoring data set with no data gaps, enter data into Excel spreadsheet, one spreadsheet for each source

Use data interpolation and estimation to create a monitoring data set with no data gaps, enter data into Excel spreadsheet, one spreadsheet for each source

For each source, create a data conversion matrix to estimate each model constituent from the available parameters in the source dataFor each source, create a data conversion matrix to estimate each

model constituent from the available parameters in the source data

For source data given as a concentration time history, multiply concentrations by flows to get mass loads

For source data given as a concentration time history, multiply concentrations by flows to get mass loads

Collect mass load time histories and reformat, then write into WQPSL.INP file using Matlab script

Collect mass load time histories and reformat, then write into WQPSL.INP file using Matlab script

An Example Conversion Matrix (Cape Fear River Inflow)

Benthic fluxes and meteorological data• Used a prescriptive benthic flux model

• SODs time varying, but constant across estuary

• SOD values based upon monitoring data

• Met data constant across estuary

• Met data taken from Wilmington airport

Model Calibration and Confirmation• 2004 calendar year used for model

calibration

• Nov 1, 2003 to Jan. 1 2004 used for model startup

• 2005 calendar year used for confirmation run (a.k.a. verification, validation run)

Streamflows during Model Runs

• 2004 dry until October

• Early 2005 had some high flows

• Summer 2005 was dry

Hydrodynamic Model Calibration

• Examined water surface elevations, temperatures, salinities

• Used LCFRP and USGS data for model/data comparisons of salinity temperature

• Used USGS and NOAA data for model/data comparisons of water surface elevation

• USGS data based on pressure measurements not corrected for barometric changes

Monitoring Stations Used

for Hydrodynamic

Calibration

Simulation of Tidal Attenuation in Estuary

• Varied wetland cell widths to determine effect on attenuation of tidal amplitude

• Wider wetland cells gave more attenuation, as expected

• Also tried different distribution of wetland cells within estuary

M2 Tidal Amplitude for Various Cell Width Scenarios

M2 Tidal Amplitude for Various Cell Distribution Scenarios

M2 Tidal Amplitude for Various Cell Distribution Scenarios

Width * 2, v1 chosen as best overall (in green)

Example Time Series Comparison – Black at Currie (upstream), 2004

Example Time Series Comparison – NECF at Wilmington, 2004

Example Time Series Comparison – Cape Fear at Marker 12, 2004

Example Time Series Comparison – Black at Currie (upstream), Jan. 04

Example Time Series Comparison – Wilm. Tide Gage, Jan. 04

Example Time Series Comparison – Cape Fear at Marker 12, Jan. 04

Example Time Series Comparison – Salinities at Navassa, 2004

Example Time Series Comparison – Salinities at NECF Wilm., 2004

Example Time Series Comparison – Salinities at Marker 12, 2004

Calibration Statistics, Salinity

Salinity Scatter Plot

Temperature Scatter Plot

Calibration Statistics, Temperature

Water Quality Calibration

• Added a second category of dissolved organic matter (refractory C, N, P)

• Split between labile and refractory based upon longer-term BOD measurements from LCFRP, IP, Wilmington wastewater authority

• Accounted for effects of NBOD in these tests


State Variables UsuallyUsed to Simulate Organic Matter Load


State Variables UsuallyUsed to Simulate Organic Matter Load

Additional State Variables Used (settling velocity = 0.0)

Partitioning Organic Matter into Labile and Refractory Parts• Fit data to 2 component model for BOD

exertion, using equation

€

CBOD(t)= rBODu(1− e−kdrt )+ rBODukdr

kdr − kdl(e−kdl t − e−kdrt )+ lBODu(1− e−kdl t )

Example: Long-term BOD, IP discharge, 7/20/2003

Partitioning Organic Matter into Labile and Refractory Parts• Fit data to 2 component model for BOD

exertion, using equation

€

CBOD(t)= rBODu(1− e−kdrt )+ rBODukdr

kdr − kdl(e−kdl t − e−kdrt )+ lBODu(1− e−kdl t )

Loading Breakdown for DOC

Loading Breakdown for Refractory DOC

Loading Breakdown for NH4

Also implemented time variable SOD (varies w/ temperature)

Example Time Series Comparison – DO at Navassa, 2004

Example Time Series Comparison – DO at NECF Wilm., 2004

Example Time Series Comparison – DO at Marker 12, 2004

Calibration Statistics, DO

DO Scatter Plot

DO Percentile Plot

Calibration of Other WQ Constituents• Show some key constituents

– Ammonia, nitrate+nitrite, total phosphorus, chlorophyll-a

• Show only at Navassa (more plots in report)

• Overall, water quality model predicts each of the constituents well

Example Time Series Comparison – Ammonia at Navassa, 2004

Example Time Series Comparison – NOx at Navassa, 2004

Example Time Series Comparison – TP at Navassa, 2004

Example Time Series Comparison – Chl-a at Navassa, 2004

Confirmation Run Results

• Ran model for calendar year 2005, with parameters determined from calibration

• USGS continuous monitoring data ended by then, used LCFRP data instead

• Show time histories only at Navassa (more in report)

Example Time Series Comparison – Salinities at Navassa, 2005

Example Time Series Comparison – Temperatures at Navassa, 2005

Example Time Series Comparison – DO at Navassa, 2005

Model Fit Statistics, DO, 2005 Confirmation Run

DO Percentile Plot, Predicted vs. Observed, 2005 Confirmation Run

Sensitivity Testing

• Examined effect of varying SOD on model DO predictions and sensitivity of system to changes in organic matter loading

• SOD had an significant impact on model predictions

• Effect of changing SOD on effect of load changes shown in next section (scenario testing)

Scenario Tests - Methods

• In general, test effect of changing wastewater input on water quality of system

• Changed loads only for oxygen demanding constituents (DOC, RDOC, Ammonia

• Examine DOs during warm weather period (April 1 – November 1) at 18 stations spread across impaired area

• Look at predicted DOs in each layer

• 6 scenario tests done so far

Six Scenario Tests Done so Far1. Changes in Flow (and load) of Brunswick Co.

WWTP

2. Removal of load from all WWTPs, and from 3 (IP, Wilm NS & SS)

3. Removal of Ammonia load from all WWTPs

4. Increase all WWTPs to maximum permitted load

5. Reduction in load from rivers, tidal creeks, wetlands

6. Reduction in loads for various SOD values

1. Changes in Flow (and load) of Brunswick Co. WWTP • Base case flow = 0.38 MGD

• Three increased flows1. 4.3 times

base

2. 12.1 times base

3. 39.1 times base

2. Removal of load from all WWTPs, and from 3 (IP, Wilm NS & SS) • Completely removed CBOD & ammonia load from all WWPTS

• Tried turning off just IP, just Wilm NS & SS

3. Removal of Ammonia load from all WWTPs • Removed ammonia load from all 20 WWTP inputs

• No changes to CBOD load

4. Increase all WWTPs to maximum permitted load • Increased all flows and loads to maximum permitted values

• Assumed constant load at maximum permitted value

5. Reduction in load from rivers, tidal creeks, wetlands • Manipulated concentrations (& loads) of all 17 freshwater inputs (3 rivers, 14 estuary sources)

• Reduced loads by 30% and 50%

6. Reduction in loads for various SOD values • Varied SOD above and below calibrated value

• Observed effect of turning all WWTP loads off for each SOD case

Summary & Conclusions• Successfully created a simulation model of

dissolved oxygen in Lower Cape Fear River Estuary• Model testing included calibration, confirmation,

and sensitivity analyses• Scenario tests used to investigate system sensitivity

to changes in organic matter and ammonia load• System found to be only moderately sensitive to

changes in WWTP load

Additional Work Ongoing• Working to finalize modeling report and

other publications

• Will work with DWQ personnel to incorporate model results into TMDL

• Training DWQ personnel to run LCFR model and analyze additional scenarios

LCFR Water Quality Modeling Project Report Jim Bowen, UNC Charlotte LCFRP Advisory Board/Tech. Comm....

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