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1 Modeling Water and Sediment Contamination of Lake Pontchartrain following Pump-out of Hurricane Katrina Floodwater Mark S. Dortch, PhD, PE, D.WRE Retired.

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Presentation on theme: "1 Modeling Water and Sediment Contamination of Lake Pontchartrain following Pump-out of Hurricane Katrina Floodwater Mark S. Dortch, PhD, PE, D.WRE Retired."— Presentation transcript:

1 1 Modeling Water and Sediment Contamination of Lake Pontchartrain following Pump-out of Hurricane Katrina Floodwater Mark S. Dortch, PhD, PE, D.WRE Retired Research Civil Engineer, Environmental Laboratory, ERDC, USACE Senior Water Resources Engineer, Moffatt & Nichol Dortch, M.S., Zakikhani, M., Kim, S.C., and Steevens, J.A. 2008, in J. Env. Mgt, 87,

2 2 Background Interagency Performance Evaluation Task force (IPET) was commissioned by Congress following Hurricane Katrina to evaluate the reasons and consequences of failed protection of New Orleans Interagency Performance Evaluation Task force (IPET) was commissioned by Congress following Hurricane Katrina to evaluate the reasons and consequences of failed protection of New Orleans IPET Task 9 focused on socio-economic and environmental consequences IPET Task 9 focused on socio-economic and environmental consequences A major environmental questions was, what were the environmental impacts to Lake Pontchartrain as a result of pumping out contaminated flood water from New Orleans following Hurricanes Katrina and Rita. A major environmental questions was, what were the environmental impacts to Lake Pontchartrain as a result of pumping out contaminated flood water from New Orleans following Hurricanes Katrina and Rita.

3 3 Study Objective As part of IPET Task 9, model the fate and transport of contaminants pumped into Lake Pontchartrain following the actual events to evaluate the environmental impacts as contrasted against conditions that would have occurred without levee failures and overtopping Constraint: study had to be done in a few months Funding: USACE/IWR to USACE/ERDC-EL

4 4 Approach A 3D numerical hydrodynamic (CH3D-WES/Z) and water quality model (CE-QUAL-ICM) were applied A 3D numerical hydrodynamic (CH3D-WES/Z) and water quality model (CE-QUAL-ICM) were applied Modeled constituents included: Modeled constituents included: water column and bottom sediment concentrations of: – – Arsenic (As) – – Lead (Pb) – – Benzo(a)pyrene (BaP) – – DDE – – Fecal Coliform bacteria (FCB), water concentration only Compared actual versus base – – Actual – as occurred with levee failures and overtopping – – Base – without levee failures and overtopping Compared water and sediment concentrations with protective eco and human health criteria

5 5 CH3D-WES 3D, time-varying, baroclinic, free surface Hydro model, sigma and Z-plane versions (used Z-plane version) 3D, time-varying, baroclinic, free surface Hydro model, sigma and Z-plane versions (used Z-plane version) Transports salinity and temperature for density coupling and baroclinic forcing (not used in this study due to minor salinity differences resulting from the storm) Transports salinity and temperature for density coupling and baroclinic forcing (not used in this study due to minor salinity differences resulting from the storm) Structured, curvilinear, non-orthogonal, boundary-fitted coordinates, finite difference method Structured, curvilinear, non-orthogonal, boundary-fitted coordinates, finite difference method Block grid structure for sub-grid resolution and parallelization (not used in this study) Block grid structure for sub-grid resolution and parallelization (not used in this study)

6 6 CE-QUAL-ICM Multi-dimensional, unstructured, finite volume, surface water quality, eutrophication, and contaminant model Multi-dimensional, unstructured, finite volume, surface water quality, eutrophication, and contaminant model Must provide Hydro to ICM Must provide Hydro to ICM Developed on Chesapeake Bay (circa 1990), but has been applied to many other systems Developed on Chesapeake Bay (circa 1990), but has been applied to many other systems Over 35 state variables ranging from temperature, salinity, and nutrients to sea grass and lower food chain, plus fate/transport of trace toxic substances Over 35 state variables ranging from temperature, salinity, and nutrients to sea grass and lower food chain, plus fate/transport of trace toxic substances Benthic diagenesis sub-model for predicting bed- water column nutrient and DO fluxes Benthic diagenesis sub-model for predicting bed- water column nutrient and DO fluxes Domain decomposition with MPI for parallelization (not used for this study) Domain decomposition with MPI for parallelization (not used for this study)

7 7 Lake Pontchartrain Computational Grid 6,038 surface cells Max of 6 layers, 1.52 m thick except surface 21,018 total cells Rigolets Inlet

8 8 Pump Stations Included in Model Orleans Metro Orleans East

9 9 Pump Hydrographs for Actual Conditions 5-10% of lake volume pumped out (2005) Flows estimated from another IPET task Started 9/11 and stopped Oct 17, 37 days

10 10 Pumped Flow for Base Condition Assumed no levee failures or overtopping Assumed no levee failures or overtopping Used measured rainfalls at Slidell (Katrina had 20 cm) and NO A/P (Rita had 5.84 cm) and NO metro & east basin area (2.8E8 m 2 ), yielding 5.7E7 and 1.7E7 m 3 (Katrina and Rita, respectively) Used measured rainfalls at Slidell (Katrina had 20 cm) and NO A/P (Rita had 5.84 cm) and NO metro & east basin area (2.8E8 m 2 ), yielding 5.7E7 and 1.7E7 m 3 (Katrina and Rita, respectively) Base pumped volume (collected rainfall) 10% Actual pumped volume for Katrina Base pumped volume (collected rainfall) 10% Actual pumped volume for Katrina These volumes can be pumped out in a day or less (0.6 days for Katrina at total pump capacities) These volumes can be pumped out in a day or less (0.6 days for Katrina at total pump capacities) Flow per pump = 0.6 * pump capacity Flow per pump = 0.6 * pump capacity Duration = 1 day due to model requirement of daily flows Duration = 1 day due to model requirement of daily flows

11 11 Other Hydro Model Inputs 90 day simulation starting on Sep 1, day simulation starting on Sep 1, 2005 Winds from NO Int. Airport (no data from 9/1 to 9/7, so linearly ramped up from 0, spin-up) Winds from NO Int. Airport (no data from 9/1 to 9/7, so linearly ramped up from 0, spin-up) Seaward water level boundary at Rigolets (Waveland, MS gage was blown out) – used sum of: Seaward water level boundary at Rigolets (Waveland, MS gage was blown out) – used sum of: – Astronomical based on NOAA predictions at Waveland, MS – Meteorological based on Norco, Bayou LaBranche, LA gage with 48 hour filter and 24 hour shift forward Tributary flows were not included Tributary flows were not included

12 12 Hydrodynamic Model Calibration At the Norco tide gage Hurricane Rita Model spin-up Katrina hit on August 29

13 13 Hydrodynamic Animation Sep 9-13, before and during 2 days of pump-out

14 14 Contaminant Model Fate Processes Equilibrium sorption to suspended solids Equilibrium sorption to suspended solids Settling of adsorbed particulate contam. Settling of adsorbed particulate contam. Volatilization of dissolved organic contam. Volatilization of dissolved organic contam. Surficial benthic sediment mass balance due to settling, resuspension, and burial Surficial benthic sediment mass balance due to settling, resuspension, and burial FCB die off FCB die off

15 15 Contaminant Model Inputs Lake total suspended solids, TSS = 19.2 mg/L (based on NTU regression and observed lake-wide median NTU following Katrina) Lake total suspended solids, TSS = 19.2 mg/L (based on NTU regression and observed lake-wide median NTU following Katrina) TSS settling rate = 1 m/d based on Corps IHNC DMMU study TSS settling rate = 1 m/d based on Corps IHNC DMMU study Sediment fraction TOC for water column and bed, foc = 0.02 based on DMMU study Sediment fraction TOC for water column and bed, foc = 0.02 based on DMMU study Surficial benthic sediment porosity = 0.9 Surficial benthic sediment porosity = 0.9 Sediment burial rate = m/yr based on steady- state solids balance with 0 resuspension Sediment burial rate = m/yr based on steady- state solids balance with 0 resuspension FCB die off rate = 1 per day (conservative value) FCB die off rate = 1 per day (conservative value) Degradation rate of metals and organics = 0.0 Degradation rate of metals and organics = 0.0

16 16 Model Inputs (cont.) Kd Input Values for Model, L/kg Pb: 4,000 Pb: 4,000 As: 500 As: 500 BaP: 0.3 E6 BaP: 0.3 E6 DDE: 0.6 E6 DDE: 0.6 E6 Values are close to literature (metals) and Kow computed values (organics), but they were adjusted slightly using observed benthic sediment and water column data from NO flood waters to back out Kd

17 17 Model Inputs (cont.) Volatilization Rates BaP: m/d BaP: m/d DDE: 0.19 m/d DDE: 0.19 m/d Computed using wind speed of 5 mph, Henrys constants, and molecular weights

18 18 Contaminant Model Loadings (Q*C) Actual conditions Actual conditions – Based on measurements in NO floodwaters for total concentrations (EPA database of values monitored by EPA, USGS, LSU, LaDEQ) – Computed median and 95UCL of concentrations for NO East and NO Metro Base conditions Base conditions – Assumed to be same concentrations as Actual conditions; based on literature – concentrations in Katrina flood waters were typical for storm water

19 Contaminant Loading Concentrations ConstituentMedian, ug/L95UCL, ug/L Orleans Metro Arsenic20 BaP55 DDE0.05 Lead544 Fecal coliform bacteria2,200*70,041* Orleans East Arsenic2026 BaP55 DDE Lead2.512 Fecal coliform bacteria200*32,869* * MPN/100 ml

20 20 Contaminant Model Validation There were some observations for FCB and lake benthic sediment contamination following Katrina There were some observations for FCB and lake benthic sediment contamination following Katrina Computed and observed FCB were same order of magnitude, but observations were spotty Computed and observed FCB were same order of magnitude, but observations were spotty Sediment contamination values not really comparable since there is a long-term sediment memory and model only had a brief loading history compared with many years in prototype Sediment contamination values not really comparable since there is a long-term sediment memory and model only had a brief loading history compared with many years in prototype There was qualitative confirmation in that events had very little impact on lake sediment metal concentrations for predicted and observed There was qualitative confirmation in that events had very little impact on lake sediment metal concentrations for predicted and observed

21 21 Arsenic Animation, Water Surface 90 days starting Sep 1, 2005

22 22 Maximum Incremental Arsenic Water Surface Concentrations ActualBase Max of about mg/L in both cases

23 23 Maximum Incremental Arsenic Sediment Concentrations ActualBase Max of about 0.05 mg/kgMax of about mg/kg

24 Computed maximum incremental water (ug/L) and sediment (mg/kg) concentrations (total) for Lake Pontchartrain for Actual and Baseline conditions and median and 95UCL loading concentrations ConditionAs water As sedBaP water BaP sedDDE water DDE sedPb wat. Pb sed FCB water* Actual ,055 Actual , 214 Base ,413 Base ,780 *Units for FCB are MPN/100ml Note: water concentrations about the same for both conditions, but sediment about 10X for Actual compared to Base

25 25 Lake Contaminant Incremental Concentration Conclusions Water column – increases were about the same or less for actual versus base conditions Water column – increases were about the same or less for actual versus base conditions Surficial sediment – increases for actual conditions were about 10 times those for base Surficial sediment – increases for actual conditions were about 10 times those for base Increases in sediment for metals were small (<1%) compared with pre-Katrina concentrations Increases in sediment for metals were small (<1%) compared with pre-Katrina concentrations Increase in sediment BaP concentrations were about the same as post-Katrina measurements Increase in sediment BaP concentrations were about the same as post-Katrina measurements Sediment increase in DDE was much lower than other contaminants Sediment increase in DDE was much lower than other contaminants

26 26 Exceedence of Protective Water and Sediment Screening Benchmarks Water Pb for Actual95 and Base95 Water Pb for Actual95 and Base95 Sediment BaP for Actual and Actual95 Sediment BaP for Actual and Actual95 Sediment DDE for Actual and Actual95 Sediment DDE for Actual and Actual95 Water FCB for both conditions and both loadings (the norm for NO storm water removal) Water FCB for both conditions and both loadings (the norm for NO storm water removal)

27 27 Overall Conclusions Flood water contamination is thought to be due primarily to pre-Katrina-contaminated urban soils (typical urban storm-water), but a much greater water volume was pumped with levee failures, thus greater loadings Flood water contamination is thought to be due primarily to pre-Katrina-contaminated urban soils (typical urban storm-water), but a much greater water volume was pumped with levee failures, thus greater loadings Lake water column concentrations about the same with/without levee failures Lake water column concentrations about the same with/without levee failures Sediment concentrations for BaP and DDE under actual conditions with levee failures exceeded eco screening guidelines close to south shore, but both degrade over time Sediment concentrations for BaP and DDE under actual conditions with levee failures exceeded eco screening guidelines close to south shore, but both degrade over time Water Pb and FCB are a concern with/without levee failures Water Pb and FCB are a concern with/without levee failures


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