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LCFR Water Quality Modeling Project Report Jim Bowen, UNC Charlotte LCFRP Advisory Board/Tech. Comm. Meeting, October 30, 2008 Raleigh, NC.

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Presentation on theme: "LCFR Water Quality Modeling Project Report Jim Bowen, UNC Charlotte LCFRP Advisory Board/Tech. Comm. Meeting, October 30, 2008 Raleigh, NC."— Presentation transcript:

1 LCFR Water Quality Modeling Project Report Jim Bowen, UNC Charlotte LCFRP Advisory Board/Tech. Comm. Meeting, October 30, 2008 Raleigh, NC

2 Outline of Presentation A Quick Review of the LCFR Model Summary of Model Report Questions/Suggestions

3 Basis of Presentation Technical Report Draft (available on web)

4 LCFR Dissolved Oxygen Model The big picture Estuary Physical Characteristics: e.g. length, width, depth, roughness EFDC Software Adjustable Parameters: (e.g. BOD decay, SOD, reaeration) Hydrologic Conditions River Flows, Temp’s, Conc’s Tides Time “Met” Data Air temps, precip, wind, cloudiness Time State Variables nutrients DO, organic C Time

5 Dissolved Oxygen Conceptual Model BOD Sources Sediment Cape Fear, Black & NECF BOD Load Muni & Ind. BOD Load decaying phytopl. Estuary Inflow BOD Load

6 Dissolved Oxygen Conceptual Model BOD Sources, DO Sources Sediment Cape Fear, Black & NECF BOD Load Ocean Inflows Surface Reaeration Phytoplank. Productivity Muni & Ind. BOD Load decaying phytopl. MCFR Inflows Estuary Inflow BOD Load

7 BOD Consumption Dissolved Oxygen Conceptual Model BOD Sources, DO Sources & Sinks Sediment Sediment O 2 Demand Cape Fear, Black & NECF BOD Load Ocean Inflows Surface Reaeration Input of NECF & Black R. Low DO Water Phytoplank. Productivity Muni & Ind. BOD Load decaying phytopl. MCFR Inflows Estuary Inflow BOD Load

8 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

9 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

10 Description of Model Application Open Boundary Elevation Cond. Lower Cape Fear River Estuary Schematic Black River Flow Boundary Cond. Cape Fear R. Flow Boundary Cond. NE Cape Fear Flow Boundary Cond.

11 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

12 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

13 Water Quality Model Schematic

14 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

15 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)

16 EFDC Input Files & Data Sources

17 Lower Cape Fear River Program Sites Used

18 USGS Continuous Monitoring and DWQ Special Study Stations Used

19 New Cross- Sections Surveyed by NC DWQ

20 SOD Monitoring Stations Performed by NC DWQ

21 LCFR Grid Channel Cells in Blue Wetland Cells in White Marsh and Swamp Forest in Green, Purple

22 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

23 Model Grid Showing Location and Size of Wetland Cells

24 Riverine Swamps and Saltwater Marshes in Estuary (NC DCM)

25 Input File Specification Inflows Temperatures and Water Quality Concentrations at Boundaries Water quality mass loads for point sources Benthic fluxes Meteorological data

26 Riverine Inflow Specification Flows based on USGS flow data Flows scaled based upon drainage area ratios 17 total inflows –3 rivers, 14 estuary sources

27 Subwatersheds Draining Directly to the Estuary

28

29 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

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

31 An Example Conversion Matrix (Cape Fear River Inflow)

32 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

33 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)

34 Streamflows during Model Runs 2004 dry until October Early 2005 had some high flows Summer 2005 was dry

35 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

36 Monitoring Stations Used for Hydrodynamic Calibration

37 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

38 M2 Tidal Amplitude for Various Cell Width Scenarios

39 M2 Tidal Amplitude for Various Cell Distribution Scenarios

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

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

42 Example Time Series Comparison – NECF at Wilmington, 2004

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

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

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

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

47 Example Time Series Comparison – Salinities at Navassa, 2004

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

49 Example Time Series Comparison – Salinities at Marker 12, 2004

50 Calibration Statistics, Salinity

51 Salinity Scatter Plot

52 Temperature Scatter Plot

53 Calibration Statistics, Temperature

54 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

55 Water Quality Model Schematic

56 State Variables Usually Used to Simulate Organic Matter Load

57 Water Quality Model Schematic State Variables Usually Used to Simulate Organic Matter Load Additional State Variables Used (settling velocity = 0.0)

58 Partitioning Organic Matter into Labile and Refractory Parts Fit data to 2 component model for BOD exertion, using equation

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

60 Partitioning Organic Matter into Labile and Refractory Parts Fit data to 2 component model for BOD exertion, using equation

61 Loading Breakdown for DOC

62 Loading Breakdown for Refractory DOC

63 Loading Breakdown for NH4

64 Also implemented time variable SOD (varies w/ temperature)

65 Example Time Series Comparison – DO at Navassa, 2004

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

67 Example Time Series Comparison – DO at Marker 12, 2004

68 Calibration Statistics, DO

69 DO Scatter Plot

70 DO Percentile Plot

71 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

72 Example Time Series Comparison – Ammonia at Navassa, 2004

73 Example Time Series Comparison – NOx at Navassa, 2004

74 Example Time Series Comparison – TP at Navassa, 2004

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

76 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)

77 Example Time Series Comparison – Salinities at Navassa, 2005

78 Example Time Series Comparison – Temperatures at Navassa, 2005

79 Example Time Series Comparison – DO at Navassa, 2005

80 Model Fit Statistics, DO, 2005 Confirmation Run

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

82 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)

83 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

84 Six Scenario Tests Done so Far 1.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

85 1. Changes in Flow (and load) of Brunswick Co. WWTP Base case flow = 0.38 MGD Three increased flows 1.4.3 times base 2.12.1 times base 3.39.1 times base

86 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

87 3. Removal of Ammonia load from all WWTPs Removed ammonia load from all 20 WWTP inputs No changes to CBOD load

88 4. Increase all WWTPs to maximum permitted load Increased all flows and loads to maximum permitted values Assumed constant load at maximum permitted value

89 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%

90 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

91 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

92 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

93 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 Questions?

94 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 Additional analyses done that are not in report

95 Effect on DO of deepening navigation channel Entrance channel deepened from 40 to 44 feet Remainder of channel (up to CF Mem. Br.) deepened from 38 to 42 feet

96 Effect of Changing River Load and SOD Considers possible cleanup of sediments SOD lowered by same percentages (30% and 50%) as riverine loading

97 Analysis of DO deficit in the impaired region Examined summer average DOs (surface) at 3 sites in impaired region Used linear sensitivity analysis to attribute deficit to either WWTPs, SOD, or river loads


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