OCDA United States ^CW—mEnvironimentaJ Protection Agency · OCDA United States...
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Ground Water Modeling Calibration Report OCDA United States ^CW—mEnvironimentaJ Protection Agency Popile, Inc. Superfund Site March 1999 El Dorado. Arkansas Total Environmental Restoration Contract Contract No. DACA56-94-D-0021 Prepared bv: Morrison Knudsen Corporation Englewood, Colorado Preparedfor: U.S. Army Corps of Engineers New Orleans District New Orleans, Louisiana MORRISON KNUDSEN CORPORATION
Transcript of OCDA United States ^CW—mEnvironimentaJ Protection Agency · OCDA United States...
Ground Water ModelingCalibration Report
OCDA United States^CW—mEnvironimentaJ Protection Agency
Popile, Inc. Superfund Site
March 1999
El Dorado. Arkansas
Total Environmental Restoration ContractContract No. DACA56-94-D-0021
Prepared bv:Morrison Knudsen CorporationEnglewood, Colorado
Preparedfor:U.S. Army Corps of Engineers
New Orleans DistrictNew Orleans, Louisiana
MORRISON KNUDSEN CORPORATION
^
s
Ground Water Modeling Calibration ReportPopile Site, El Dorado Arkansas
Table of Contents
Acronym List . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vi
1.0 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-11.1 Purpose of Ground Water Modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-11.2 Model Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-21.3 Processes and Parameters Affecting Model Calibration . . . . . . . . . . . . . . . . . . 1-3
1.3.1 Heads In Aquifer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-31.3.2 PCP and Naphthalene Plumes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1-4
2.0 BIOPLUME m Model Setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-12.1 Overview of BIOPLUME m . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-12.2 Concept of Two Dimensional Areal Modeling . . . . . . . . . . . . . . . . . . . . . . . . . 2-12.3 Model Domain and Grid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-22.4 Steady State Condition for Flow . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2-32.5 Transient Conditions for Contaminant Transport . . . . . . . . . . . . . . . . . . . . . . . 2-42.6 Boundary and Initial Conditions for Flow and Transport . . . . . . . . . . . . . . . . . 2-4
3.0 Head Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-13.1 Objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-13.2 Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-13.3 Fixed Input Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3-1
4.0 Head Calibration Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-14.1 Hydraulic Conductivity Distribution Selected . . . . . . . . . . . . . . . . . . . . . . . . . . 4-14.2 Resultant Head Match . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-14.3 Flux and Pore Velocities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4-1
5.0 Contaminant Calibration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-15.1 Objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-15.2 Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-25.3 Fixed Input Parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5-3
6.0 Contaminant Calibration Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6-16.1 Calibrated BIOPLUME III Model Parameters . . . . . . . . . . . . . . . . . . . . . . . . . 6-16.2 Resultant PCP and Naphthalene Concentration Contour Match . . . . . . . . . . . . 6-1
7.0 Sensitivity Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-17.1 Aquifer Thickness . . . . . . . ~ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-17.2 Hydraulic Conductivity/ Effective Porosity . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-37.3 Secondary Contaminant Source Flux . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-57.4 Effect of Each Attenuation Parameter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-6
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7.5 Dispersion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-77.6 Retardation Factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-87.7 Biodegradation Rate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-97.8 Simulation Time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7-11
8.0 Summary and Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-18.1 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-18.2 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8-1
9.0 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9-1
List of Figures
1-1 Potentiometric Surface in the Cockfield Sands, September 19981-2 Dissolved PCP in Concentrations in Ground Water of Upper Cockfield Sands1-3 Dissolved Naphthalene in Concentrations in Ground Water of Upper Cockfield Sands1 -4 Dissolved Oxygen in the Cockfield Sands
2-1 Simplified Cross Section of Flow2-2 Model Grid and Kriged Head Boundaries2-3 Storage Coefficient Zoning2-4 Top of Aquifer Zoning2-5 Top of Carbonaceous Layer Zoning :•;2-6 Thickness of Aquifer Zoning
4-1 Zoned Hydraulic Conductivity Pattern for Calibrated Model4-2 Modeled vs. Observed Steady State Potentiometric Surfaces4-3 Regression Plot of Data Pairs - Modeled vs Observed Heads in Flow Domain
5-1 Modeled Contaminant Core and Peripheral Source Area
6-1 Calibrated PCP Plume with Biodegradation6-2 Calibrated Naphthalene Plume with Biodegradation6-3 Depressed Dissolved Oxygen Caused by PCP Biodegradation6-4 Depressed Dissolved Oxygen Caused by Naphthalene Biodegradation6-5 PCP Plume After 50 Years - Calibrated Model without Biodegradation6-6 Naphthalene Plume After 50 Years - Calibrated Model without Biodegradation
List of Tables
2-1 Hydraulic Properties Used for Spatial Distribution2-2 Hydrogeologic Data Used in Defining Aquifer Thickness2-3 Piezometric Heads Used in Defining Constant Head Boundary Conditions
4-1 Differences between Modeled and Observed Potentiometric Heads for Calibrated Model
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4-2 Simulated Velocity Map (feet/year)
6-1 Physicochemical, Biogeochemical and Biological Parameters Used for Calibrated Model
7-1 Sensitivity Model Runs Increased Aquifer Thickness7-2 Sensitivity Model Runs, Hydraulic Conductivity Variable7-3 Sensitivity Model Runs, Secondary Contaminant Source Flux7-4 Sensitivity Model Runs, Dispersion, Sorption, Biodegradation Absent and Present7-5 Sensitivity Model Runs, Dispersion Variable7-6 Sensitivity Model Runs, Retardation Factor Variable7-7 Sensitivity Model Runs for Differing Biodegradation Parameters7-8 Sensitivity Model Runs, Calibrated Model for Different Run Times
List of Appendices
A Raoult's Law Calculation
B Sensitivity Analysis MapsB. 1 Maps of Heads, PCP and Oxygen for Increased Aquifer Thickness
PCPC50FHPCPL+10HPCPL+100PCPL+10W
B.2 PCP Distribution for Varying Magnitude of Hydraulic ConductivityPCPKMTNHPCPKMN_HPCPC50FHPCPKMAXHPCPEP25H
B.3 PCP Distribution for Varying Secondary Contaminant Source FluxPCPFXO_HPPFX10%HPCPC50FHPPFX10XHPCPFXCCH
B.4 PCP Distribution for Combinations of Dispersion, Sorption, and BiodegradationPCPD__HPCPS__HPCPDS__HPCPC50FH
B.5 PCP Distribution for Varying Dispersion FactorsPPS-90%HPCPC50FHPCPD&50%H
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B.6 PCP Plume Maps for Varying Retardation FactorsPCPS-90%HPCPC50FHPCPS&5XH
B.7 PCP Plume Maps for Varying Biodegradation Factors RatesPPMT10%HPCPC50FHPPU-10XHPPU&10XH
B.8 Time Series Plots of PCP and Naphthalene Distribution - Calibrated ModelPentachlorophenol (PCP)PCPC10FHPCPC20FHPCPC30FHPCPC40FHPCPC50FHPCPSS_H
NaphthaleneNAPC10FHNAPC30FHNAPC50FHNAPSS__H
Dissolved OxygenPCPC50FONAPC50FO
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Acronym List
ADPCE Arkansas Department of Pollution Control and EcologyASTM American Society of Testing and MaterialsBaP Benzo(a)Pyrenebgs Below ground surfaceBTEX Benzene, toluene, ethyl benzene, and xyleneCDM Camp Dresser & McKee Federal Programs CompanyCERCLA Comprehensive Environmental Response, Compensation and Liabilities ActCOCs Contaminations of ConcernCPT Cone PenetrometerDQO Data Quality ObjectiveDNAPL Dense Non-aqueous Phase LiquidFSP Field Sampling PlanLNAPL Light Non-aqueous Phase LiquidLIF Laser Induced FluorescenceMK Momson Knudsen CorporationMSL Mean Sea LevelNAPL Non-aqueous Phase LiquidPAHs Polynuclear Aromatic HydrocarbonsPCP PentachlorophenolPQL Practical Quantitation LimitQA Quality AssuranceQAPP Quality Assurance Project PlanQC Quality ControlRA Removal ActionRCRA Resource Conservation and Recovery ActRD Remedial DesignRI/FS Remedial Investigation/Feasibility StudySCAPS Site Characterization and Analysis Penetrometer SystemSVOC Semi-volatile Organic CompoundTBD To be determinedTD Total DepthTOC Total Organic CarbonTPH Total Petroleum HydrocarbonsUSACE United States Army Corp of EngineersUSEPA United States Environmental Protection AgencyWES Waterways Experiment Station
(Rev. a. March 1999)
§
1.0 Introduction
Morrison Knudsen Corporation (MK) developed this Ground Water Modeling Calibration report forthe U. S. Army Corps of Engineers (USACE) - New Orleans District to describe the procedures andresults of modeling ground water flow and transport of contaminants of concern (COCs) at thePopile site in El Dorado, Arkansas. The Ground Water Data Collection Report (MK, 1999a) for thissite provides the basis for selecting soil physical, chemical, physicochemical, biological, andbiogeochemical input parameters for the model, along with their reasonable ranges. MK has alsoresearched the literature to arrive at certain modeling parameters. Work was conducted accordingto the Ground Water Modeling Work Plan (MK, 1999b) for this project.
1.1 Purpose of Ground Water ModelingThe Data Quality Objectives (DQOs) for the project posed among other questions, whether groundwater contamination is entering the Bayou de Loutre or other offsite receptors, and if not, whetherit has a chance to do so in the future. This DQO document is contained within the Final QualityAssurance Project Plan (QAPP)for Ground Water Investigation, Modeling and Remedial Design,Popile, Inc Superfund Site (MK, 1998).
Monitoring well concentration data presented in the data collection report (MK, 1999a) indicate thatsite contaminants are not migrating offsite to any significant degree or entering the Bayou. Theground water model therefore addresses the possibility that contaminants may reach the Bayou inthe future.
Modeling results will be used to support U. S. Environmental Protection Agency (USEPA) remedialaction decisions to secure the site or prevent contamination migration to offsite receptors. Thedecision inputs to the remedial action will primarily be the model results presented here (includingsensitivity analysis and calibration), the USACE Waterways Experiment Station (WES) soilbiotreatability study (USACE, 1999), and the dissolved phase ground water data. The results willalso be used to develop a plan for data collection to confirm the processes perceived as importantin limiting future movement of dissolved phase contamination. The predictive modeling includesthe following scenarios:
(1) Non-aqueous Phase Liquid (NAPL) source materials are allowed to remain in place
(2) NAPL source materials within the aquitard layer are removed
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(3) All the NAPL source materials are removed
To perform the ground water modeling, MK conducted the following specific tasks:
(1) Reviewed and compiled data from previous site investigations for input to the BIOPLUME IIImodel.
(2) Translated the conceptual model presented in Section 8 of the Ground Water Data CollectionReport into a simulation domain, and quantified hydrogeologic and geologic conditions of theaquifer system, contaminant source and release, as well as the transport and biodegradationprocesses.
(3) Simulated the transport and biodegradation ofPentachlorophenol (PCP) and Naphthalene todetermine the state of the dissolved plume (expanding, stable, or shrinking), future impacts tothe Bayou de Loutre and/or other off-site properties, and to calculate the implied source releaserate and rate of natural attenuation.
1.2 Model CalibrationOverall preparation of an operational model for the Popile site is divided into three distinct stages:
(1) Initialization and preparation
(2) Calibration and sensitivity analysis
(3) Problem solving or scenario analysis
Inasmuch as the ground water model quantifies future flow and transport processes, there must besome confidence that the model is able to accurately simulate those same processes that haveresulted in the present conditions at the site. In calibration, two types of site measurements areattempted to be matched: the ground water flow pattern; and the contaminant concentrations, extent,and shape.
The conceptual model (MK, 1999a) provided the necessary framework to ensure that quantitativepredictions of contaminant movement are rooted in the geologic controls on flow that have beenrecognized, and estimated based on the quantitative flow, chemical concentration, and contaminanttransport data that have been obtained from the Phase II RD investigation. However, it still leaveslatitude for variation and combinations of input parameters which, when taken together, best match
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the site conditions. Calibration attempts to obtain the best match of the site potentiometric map and
plume maps by varying only very few selected key model parameters within measured or literature-reported ranges. Input parameters for which either there is greatest confidence, or for whichexperience shows that they will not greatly affect calibration, are fixed to make the process
manageable.
Calibration is still subject to non-uniqueness. Many combinations of reasonable parameters mayyield the same result. Were it not for good judgement, combinations of extreme yet negatingparameters might also yield "good" calibration. For this reason, sensitivity analysis is performedon the calibrated model. Here, a greater number of parameters are varied so that a perspective isobtained on the calibration. Sensitivity analysis is used to identify parameters which strongly affectthe calibration and hence future model predictions. If these parameters are in turn not welldocumented, post-ground water modeling data collection can be directed towards their quantification
if they are integral to future USEPA decisions.
1.3 Processes and Parameters Affecting Model CalibrationIn this section, the manner in which key parameters affect calibration are described.
1.3.1 Heads In AquiferFigure 1-1 presents the potentiometric surface in the Cockfield sands for September of 1998. Lessernumbers of well existed during prior water level monitoring event, and none before initial siteinvestigative work in 1989. Little is known of past ground water flow directions that may have beeninduced by the presence of the process ponds (shown on Figure). Therefore, potentiometric surfacematching is done in steady state. The following parameters affect the head calibration and areexplored thoroughly in Section 3.
Hydraulic Conductivity. Both the absolute range and spatial homogeneity affect the head calibration.For example, a 10 fold change in conductivity would result in a 10 fold range in the expected arrivaltime for contamination to the Bayou, all else being constant. For this reason, extensivemeasurements of hydraulic conductivity in the Phase II RD investigation were made because thereare few other calibration parameters. At a given absolute range, the spatial distribution of hydraulicconductivity affects the shape of the modeled potentiometric surface including areas of steep and softgradients, and bends when water diverges from, or converges to, a lower or higher conductivity zone,respectively.
Areas of Confinement. Confined and unconfined areas of the site affect head calibration in that asteeper hydraulic gradient is required to pass flow through a given thickness of a confined aquifer
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than an unconfined one. Without a confining layer, the flow thickness is the full height of the water
table above the flow datum. Both unconfined and confined conditions have been observed at the site.The handling of simulations of unconfined and confined conditions are discussed in Section 2.2.
1.3.2 PCP and Naphthalene PlumesFigures 1-2 and 1-3 present the PCP and Naphthalene plumes within the Cockfield sands forSeptember of 1998. The time that contaminants were introduced into the ground water system mustbe estimated from the site operational history. Modeling assumes that it took the NAPL less than10 years to reach the Cockfield sand aquifer from the wood treating process ponds and theirperipheral areas so that the sources have been present since the period between 1947 and 1957, orfor approximately 50 years. The following parameters affect the plume calibration and are exploredfully in Section 5.
Source Release Rate and Size. NAPL impacts have been delineated by both Site Characterizationand Analysis Penetrometer System (SCAPS) results and observations of visually contaminated(stained) soils on soil cores. There is no known correlation between soil concentrations and the rateat which the COCs will diffuse into the ground water. Residual contamination exists within different
soil types, from which the rates of contaminant release into the aquifer can differ. The flux ofcontaminants leaving the source area affects the dissolved concentration levels, and is a keycalibration parameter.
Retardation (total organic carbon). This is a measure of how contaminants will move relative tothe mean ground water flow. Whereas source flux and size factor into the concentration ranges andshape of the dissolved plume, retardation will also control how fast the plume will spread. TOCmeasurements were obtained for many samples in the upper and lower portions of the Cockfieldsands for input to the ground water model.
Dispersion. Dispersion is the process whereby contaminant plumes spread out in the longitudinaldirection along the direction of ground water flow, and transversely perpendicular to ground waterflow due to the mechanical mixing in the aquifer and chemical diffusion. The dispersivities for inputto the ground water model were estimated based on empirical equations using plume lengthsobserved during the Phase II RD investigation.
Biogeochemical Environments. The key factor to revealing characteristics that indicate biologicalactivity is to compare field data from the contaminated zone with data from an upgradient, cleanarea. Dissolved oxygen level measurements and total heterotrophic plate counts show sufficientoxygen and aerobic organisms present in most of the ground water samples to validate the
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assumption that any biodegradation of hydrocarbon contaminants is an aerobic process. It is also
most likely true that anaerobic degradation is occurring in zones where dissolved oxygen levels are
very low. However, anaerobic processes are much slower than aerobic, and unless aerobic
metabolism can be ruled out completely, the effects of anaerobic degradation would beovershadowed by aerobic processes in a site model. Figure 1-4 shows the dissolved oxygenconcentration in the Cockfield sands.
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REFERENCE DRAWINGS"QUAKINC NO. | nni
_______LEGEND________
•MW-33 MONITORING WELL (MW) WITH186.79 WATER LEVEL ELEVATION
M SVE-1 SURFACE WATER ELEVATIONLOCATION WITH WATER SURF-ACEELEVATION
—»»lgS.>_. PIEZOMDRIC SURFACE ELEV." ^ ^ ''•-i. CONTOUR (DASHED WHERE
APPROXIMATE)
"-''•-"-"-- TREELINE—^,-,^_. FENCE (WIRE STRAND)
——————— RAILROAD—— — —— EDGE OF ROAD
——B.aw— RIGHT OP WAY (ROW)L...... ~~3 BUILDING
IS-sfeiSsfeS&ri RIPRAP
.....in »-•> PROPERTY BOUNDARY
NOTES
1. ZS WELLS SCREENED IN me 20-30 FT. BGS INTERVAL WERECHOSEN TO CONTOUR PIE20ME7RIC SURFACE.NELLS POETRATE UPPER PORTION OF THE COCKFIELD SAND.
2. •H1ER LEVELS FRQU SHALLOW PIEZOMETERS WB1E NOT USEDSINCE PIEZOMETERS ARE GEtfRAli.Y SCREENED IN LfAKYMUITARD OVERLYIN6 COCKnELO SAMOS AND ARE NOTREPRESENTATIVE OF PIEZDME1RIC SURFACE IN UNDERLYINGSANDS (SEE TEXT FOR DISCUSSION)
1 WMER LfVELS IN WELLS SCREENED IN DEEPER POSITIONS OFCOCKFIELD SANDS (LE. NEAfi TOP OF COOK MOUNTAIN FM.) WERENOT USED DUE TO VERTICAL GRADIENTS OBSERVES AT WELLCLUSTERS. (SEE TEXT FOR DISCUSSION)
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Figure 1-1
«M} POTENTIOMETRIC SURFACE WITHIN~ THE COCKFIELD AQUIFER
______(SEPTEMBER 1998)_______
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OF UPPER COCKFIELD SANDS©
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_________LEGEND_________
• BOREHOl£ (BH)
. SEDIMENT OR SURFACEWATER LOCATION (SD/SW)
1-2C SCAPS LOCATION
• MONITORING HEU. (MW) OR PIEZOMETER (PZ)0 ABANDONED WELL OR PIEZOMETER
-^—2000—— ISO CONCENTRATION CONTOUR IN iigfl.
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2.0 BIOPLUME III Model Setup
2.1 Overview of BIOPLUME mThe ground water model selected for use at Popile was presented by MK (1999b), and isBIOPLUME m (USEPA, 1998). BIOPLUME m was developed through collaboration between theAir Force Center for Environmental Excellence, the EPA's National Risk Management ResearchLaboratory, and EPA's Robert S. Kerr Environmental Research Center. The program is a two-dimensional finite difference model, specifically designed for simulating the natural attenuation oforganic contaminants in ground water due to the processes ofadvection, dispersion, sorption, andbiodegradation. All of these processes are of interest in evaluating contaminant plume movementand attenuation at the Popile site.
The model simulates the aerobic and anaerobic biodegradation of organic contaminants usingoxygen, nitrate, iron (ffl), sulfate, and carbon dioxide as electron acceptors. Detailed theory onelectron receptors and how they are treated in BIOPLUME in is contained in the Ground WaterModeling Work Plan (MK, 1999b) and in the BIOPLUME ffl user manual. The program is publicdomain, and runs in a Windows95/NT environment. It has been integrated with a graphical userinterface (GUI) by contractors of the Air Force. The typical run time for the 35 by 35 node modelin this study was five minutes on a Pentium II-based, 400 MHZ PC.
2.2 Concept of Two Dimensional Areal ModelingA conceptual model of the site was developed and presented in the Ground Water Data CollectionReport (MK, 1999a). Based on the conceptual model and observed contaminant patterns, a two-dimensional plan view model was proposed as relevant because the Cockfield sands are homogenouswith depth. It was proposed that a great deal of insight would be developed of fate and transportattenuation mechanisms in having to reproduce the plumes' shapes as being essentially the same asthe former excavation area, with little obvious movement (Figures 1-2 and 1-3).
Figure 2-1 shows a schematic geologic model of the site containing the essential features of flow andcontaminant transport processes. Along side the geologic domain is a representation of the depth-averaged flow domain which is input to the numerical model. The cross section does not mean thatmodeling is along a vertical section. On the contrary, the cross section shows how the flow domainis simplified on any vertical prism whose top and bottom surfaces are rectangles. The modeling istwo dimensional in the horizontal plane (i.e., between the tops and bottoms of the prisms).
F:\Koaiig\TBRC\T018\CalibrationRq»rt\calibtplwpd 2-1 (Rev. a, March 1999)
2.3 Model Domain and Grid
The ground water model is of the shallow ground water aquifer located at the Popile site. The aquifer
is vertically bounded by the water table or an upper confining layer in places, and the top of the
carbonaceous layer within the Cockfield sand aquifer. The flow domain of interest includes
upstream and downstream limits of the Bayou that could be affected by site ground water.
In application of numerical models, one of the elements critical to the accuracy of the computationalresults is the spatial and temporal discretization chosen. Spatial discretization is represented by thegrid overlaying the aquifer, and formed by cells defined by interconnected nodes. The discretizationin time is represented by the sequence of time steps selected for the simulations.
Taking into consideration the hydrogeology and the ground water flow boundaries, a grid wasconstructed over the site to model the flow domain. Figure 2-2 presents the grid used for the model.The grid covers a width of 1,400 feet in the x (approximate southwest-northeast) direction and alength of 1,400 feet in the y (approximate southeast-northwest) direction. Spacing of the nodes inboth directions was constant, at 40 feet. MK. confirmed through the authors of the code that thevariable spacing option was not allowed. Thirty-five nodal blocks were used in both the x- and y-directions. The total number of nodes used in each simulation was 1,225. Ninety-three time stepswere required to simulate 50 years of contaminant movement, with a time increment multiplier of1.05 and an initial time step of 10 days.
The grid orientation was selected to coincide with the direction of flow. The x-axis was rotated 30
degrees from east (counterclockwise).
BIOPLUME III requires input of spatially distributed parameters such as hydraulic conductivity,storativity, effective porosity, dispersivity, and aquifer top and bottom elevations. The modelaccepts the input values at control points (termed "log points" in the manual), consisting ofcoordinates and the input values, for geostatistical kriging. Four sets of parameters were krigedwithin the model grids for the calibrated model, including:
• Hydraulic conductivity• Storativity• Aquifer top elevation• Aquifer bottom elevation
Table 2-1 shows the hydraulic property values assigned to the model log points for kriging. Thesehydraulic conductivity and storativity values were obtained by slug tests and pumping tests,
F:\Koeiiig\TERC\T018\C«libr«tionRepon\c»librpl.wpil 2-2 (RCV. 3, March 1999)
respectively, during the Phase n RD site investigation. The aquifer top and bottom elevations used
in the log points for kriging are presented in Table 2-2 where the confined and unconfined conditionsof the aquifer are also indicated. However, effective porosity and contaminant dispersivity wereassumed to be constant throughout the entire aquifer.
Figure 2-3 shows the distribution ofstorativity within the ground water model after kriging. Thoughmany numerical ranges are shown, two primary ranges represent unconfined conditions (storagecoefficient = effective porosity = 0.30), and confined conditions (storage coefficient = order of0.001). The zoning is reflective of the unconfined and confined conditions encountered at the site(MK, 1999a), and values representative of the aquifer for those conditions. Storativity is not relevantto steady state simulation and was set to zero in the head calibration runs.
Figures 2-4,2-5 and 2-6 show the contours of the top and bottom elevations of the aquifer and thethickness of the simulated layer. The hydrogeologic values in Table 2-2 were chosen based onjudgement in grouping material types into one of two classifications for modeling: aquitard oraquifer. The modeling layer top and bottom were identified based on lithologic control at all boring
locations from the SCAPS data and Phase II RD investigation.
For this model, the material grouped into the aquifer designation are the sand facies of the finegrained unit, upper silty and clayey sands of the Carbonaceous rich sand unit, and the cleaner sandsof the carbonaceous rich sand unit down to where the carbonaceous layers appear. This resulted inan average aquifer thickness of 17 feet. Sensitivity analysis does assess aquifer thickness (Section7), because the lower two thirds of the carbonaceous sand unit was not modeled. This zone's largecontent of carbonaceous layers and slightly larger permeability is believed to have resulted in nocontamination at depth. The effective bottom of the flow domain (i.e., top of the carbonaceouslayers) does, however, affect how much contaminant mass can be absorbed over the model layerthickness.
2.4 Steady State Condition for FlowGround water levels are known to have fluctuated within the last two years (MK, 1999a), and flowpatterns may have shifted in the long term (decades) owing to the placement and subsequent removalof the process ponds and construction of low permeability soil and debris cells. The flow portionof the model is nevertheless run in steady state. The head pattern presently observed is thereforeassumed to have existed for all time before and subsequent to wood treating operations, to thepresent, and into the future.
F:VKocnit\TERC\T01»\C«libralionRcpon\calibrpl.wpd 2-3 (Rev a, March 1999)
2.5 Transient Conditions for Contaminant TransportThe contaminant transport simulations were run in transient mode, even though the flow field withinwhich contaminants move is in steady state. The process of calibration questions whether current
conditions can be replicated given likely timing of past releases. A simulation time of 50 years was
used for model calibration.
2.6 Boundary and Initial Conditions for Flow and TransportBoundary conditions are normally employed in a model so that the impact of known externalcontrols on the ground water system are applied at the appropriate locations within the flow domainand then force ground water levels to respond to the stress. In river systems connected to shallowground water, the river stage is represented as control on the ground water in contact with the river.Because the Phase II RD site investigation reported no known connection between the Cockfieldaquifer and the Bayou de Loutre, head boundaries were not prescribed along the Bayou. The aquiferwas vertically bounded by the water table (or upper confinement as appropriate) and the top of thecarbonaceous layer.
Constant head boundary cells were placed along the four sides of the model domain far enough fromthe flow domain of interest for calibration so as to allow the head pattern to freely develop as a resultof both the hydraulic conductivity distribution, and variations in the aquifer thickness. Theseconstant head boundaries were set from the workings of the BIOPLUME in model and are shownon Figure 2-2. Briefly, this includes:
• Measured piezometric heads were assigned at a limited number of nodes representing waterlevels in wells at the site.
• The model interpolated/extrapolated a potentiometric surface by kriging with the internalgeostatistical routine and then assigned head values to all the boundary cells. This occurredbefore the model was run.
• The controlling heads in the well locations originally used for kriging were removed, allowingthe finite-difference nodes to react to the boundary heads and other simulation controls.
Table 2-3 shows the observed piezometric heads that were used in defining the constant headboundary conditions for the calibrated model.
Because of the dual source release mechanisms as discussed in the conceptual model (MK, 1999a),boundary conditions for contaminant transport and biodegradation included constant concentration
F;\KoCTiB\TERC\T018\C«librationRepon'mlibn)lwpd 2-4 (Rev. a, March 1999)
and source flux of a contaminant and constant concentration of dissolved oxygen. For example, PCP
concentration at its equilibrium solubility was assigned to cells where residual NAPL was identifiedwithin the Cockfield sand aquifer. PCP fluxes were also assigned to cells where residual NAPLexisted in the fine-grained unit within 5 feet above the underlying aquifer. Dissolved oxygen wasassumed to be replenished due to the aquifer recharge in the high land area in the western part of thesite, oxygen diffusion recharge downward from the upper fine-grained unit, and mechanical mixingof the flows from offsite areas. A constant concentration of oxygen at 4,500 j^g/L was placed to thecells along the four sides of the simulation domain. Details regarding the dual source releasemechanisms and their corresponding boundary conditions are discussed in Section 5.2.
Concentrations at the start of the simulation were also specified in the BIOPLUME HI input.Ground water was assumed to be clean before the contaminants reached the aquifer. Therefore,initial concentrations of PCP and Naphthalene were set to be zero within the aquifer while initialconcentration of dissolved oxygen was set to equal to the background concentration.
F:\Kotnig\TERC\T01 Calibration Rcpon\calilMpt.wpd 2-5 (Rev. a, March 1999)
Table 2-1 Hydraulic Properties Used for Spatial Distribution
WellID
MW-24
MW-25
MW-26
MW-27
MW-28
MW-29
MW-31
MW-32
MW-33
MW-34
MW-35
MW-37
MW-40
MW-43
OW-01
OW-02
ScreenInterval(ft-bgs)
20-30
56-66
18-28
23-28
25-35
42-52
29.5-32
20-30
23-33
20-30
20-30
20-30
20-30
20-30
30-35
19-24
HydraulicConductivity
(cm/sec)
2xl0-4
4xl0"1
8x10-4
3xl0-3
6xl0-4
2xl0-4
7xl0-4
8xl0-4
9xl0-4
2xl0-4
StorageCoefficient
2xl0-3,6xl0-3
2xl0-3,6xl0-3
2xl0-4.8xl0-4
3xl0-4,lxl0-3
2xl0-4,8xl0-4
2.0x10-3
2-6 (Rev. a, March 1999)
Tab)* 2-2 Hydrogcologic Data U*»d In Defining Aquifer Thicknw
Loctton
10
tK*.***' :BH.22
BH-23
BH-24
BH-25
BH47
BH.2B
BH-2C
«^^W
MW-1
MW-CMW-7
MW-12
MW-23A
MW-25
MW.2t
MW-27
MW-2B
MW-29
MW-31
MW-32
MW-33
MW-34
MW.38
MW-38
MW-41
MW-43
PW01
PW02
Nothing
1800878.7
1800488.8
1500580.5
1800884.2
15008U.61500741.4
1600836.4
W;:;;:;;1;;
1501104.6
1800831.7
1500823.1
1800117.3
1501028.6
1SOia3T3.4
1S00451.0
1600M7.5
1500(81 £
1500106.0
1800(22.8
150112« .5
15007M.1
isoowfi.elB002t7J
15007C2.4
15007«44
1500480.8
1SOMSSX
1500302.6
EMttng
110B32t.t
11083M.S
1108831.5
H0»»14.i
110134.7
1108BH.7
1107004.7
110831N.1
iioew*.?110B801.4
nwew.«nogiig.f1101275.1
110MW.O
1108528.3
IKHTOT.B
110W73.7
110BT82.8
1108784.4
1108483.3
11073»0.»
1107150,5
110880B.7
110860e.1
1108488.8
1108885.7
1108885.8
ttirfEtov.
, , f t "T 1 ) , ,
187.3
202.4
11)6.2
182.4
1M.7
183.8
187.8
^^^s:;;;;:;;188.0
188.7
183.3
187.7
182.0
211.5
188.4
188.6
188.3
182.3
1B2.4
185.1
188.8
183.7
181.1
187.8
180.2
188.8
188-2
182.5
ToPOfAqu^
(bonnnolconAiknimr)
. . . I f t W , , ,
18.3
12.3
10.0
10.0
3.8
2.0
4.4
8.0
8.0
11 .0
8.0
NP
NP
14.7
18.8
8.8
8.8
8.8
11.0
8.3
8.3
5.0
8.5
7.8
8.5
10.4
7.1
TfpoftaywM)
e»boiMM«
»M
, , .ftW , , ,
31.5
27.4
28.3
28.8
18.8
18.8
30.8
NE
20.0
NE
NE
20.0
33.8
NE
21.0
20.8
28.4
18.7
24.8
22.1
20.0
NE
ND
18.0
ND
21.8
30.8
ToilDfAwHf
IIMItnnt
(II.IMI)
180.3
184.8
188.2
182.4
182.1
181.8
183.8
177.0
178.7
182.3
188.7
188.0
184.8
183.7
171.8
178.7
183.5
188.8
174.1
183.3
177.4
183.1
178.3
182.4
188.4
17S.8
188.4
TopOfliyfMl
urt>onu*ou>
BXM
, , ,ft—t , , ,
188.8
178.0
187.8
184.1
188.8
187.1
187.4
187.0
188.7
188.0
182.0
172.0
177.8
188.0
185.5
185.7
182.8
173.7
180.3
187.8
183.7
188.0
185.0
171-?
188.0
184.8
181.8
ConftMdor
unconfln«l
U
U
ccccc
i'i:!:!:!;!:!^!:ccccU
U
cccccccccccccc
•hmilMlanInrmi
.("•W,
7.0-ai.5
7.8-27.4
10.048.3
10.048.3
3.8-18.8
2.0-18.8
44-30.5
^i^i^hiiiii8.0-18.0
8.048.0
11.0-27.3
8.048.7
7.040.0
18.8-33.8
14.7-30.4
18.841.0
8.840.8 •
1.8-28.4
8.8-18.7
11.044.8
8.342.1
8.3-20.0
5.0-33.1
8.5.22.8
7.8-18.0
g.5-30.e10.441.8
7.1-10.8
Grid
X
CoofdInMw
m
187.0
188.4
448.7
888.2
781.4
78B.7
810.8
^^i^i^i;;^:
820.8
785.8
388.3
848.0
275.8
47.5
428.8
S73.8
788.2
S8S.1
»4.4
840.8
433.8
1278.0
782.8
708.0
532.2
288.0
883.7
601.5
Ortd
Y
coortkm1"> ,
830.5
887.0
888.5
14.1
782.3
8M.O
818.4
^i:^:1:!::::;;1 1 1 . 0
585.3
578.3
1285,8
58.5
812.4
811.8
277.1
443.1
7S1.0
710.0
287.2
448.8
728.1
1212.0
812.7
510.7
718.5
344.3
1083.7
htot(s:Wt«nNO|not<M«m«nabk).hE |nol>ncount»«).orNP|napiuen()vMue><nf*incounl<>W,)ixlaKiiMv>hi«w*r>MtlgnWb*
GridOrtoln- Eutlng'1105882.8: Nonhing ° 1500840.8
2-7 (Rev. B, March 1999)
Table 2-3 Piezometric Heads Used in Defining Constant Head Boundary Conditions
Well
ID
MW-2
MW-6
MW-8
MW-10
MW-11
MW-12
MW-16
MW-24
MW-26
MW-27
MW-28
MW-31
MW-32
MW-33
MW-34
MW-35
MW-37
MW-38
MW-36
MW-40
MW-41
MW-42
MW-43
PW-02
Northing
1501119.2
1500831.7
1500191.3
1500404.7
1499891.7
1500117.3
1501010.4
1500365.5
1500451.0
1500987.5
1500951.5
1500622.9
1501129.5
1500768.1
1500949.8
1500734.1
1500835.7
1500267.3
1500762.4
1500835.8
1500764.4
1500675.7
1500480.8
1500302.8
Ewang
1106403.5
1106874.7
1106385.5
1106809.1
1106777.2
1106998.6
1.106158.2
1106261.8
1106668.0
1106528.3
1106797.8
1106762.6
1106754.4
1106493.3
1107360.9
1107126.2
1106960.6
1107150.5
1106809.7
1106629.5
1106609.1
1106448.5
1106496.9
1106955.6
Top of
AquHw
(ft.mtl)
ND
176.7
NE
ND
NE
189.7
ND
ND
183.7
171,6
176.7
165.5
174,1
183.3
177.4
ND
ND
163.1
178.3
ND
182.4
ND
189.4
185.4
Conflrrmmt
C
C
U
C
C
C
C
U
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
HMKb
Ocwfvd
(n.-ri)183.4
184.4
193.6
186.5
190.9
187.2
187.0
194.2
188.9
183.5
183.8
186.3
161.3
166.8
184.7
184.7
185.8
186.0
165.3
185.4
186.1
188.4
192.1
186.7
Grid
X-Coordlnite*
(H)
531.6
795.9
52.0
612.2
241.4
546.0
264.7
49.4
426.6
573.6
789.2
504.4
840.6
433.8
1276.0
964.9
772.3
752.6
705.0
585.6
532.2
346.8
285.0
601.5
Grid
Y-CoordlnatM
W
100.6
585.3
895.3
972.3
1350.6
1265.9
72.2
692.5
811.6
277.1
443.1
710.0
267.2
449.6
726.1
795.6
797.6
1212.0
612.7
459.1
510.7
507.2
718.5
1083.7
Notes: C - Confined; U - Unconflned; ND - Not Detanranable; NE - Not Encountered
2-8
LEGEND
PHYSICAL DOMAIN
W
MODELING DOMAIN
E
EXTENT OF HESBUAL SOURCE
SILTT 0« CLAYEY S»lt>
SILT; SANDY Olt CLAW SILT; ClAT
sue
NOOCLED SATOKAIED SAMP SOUKCC
MODBH1SC.TY OB CLAYEY SWD;OR AOUITMO SOURCE
BSOUfB WATER FLO*
FEATURE CHARACTERISTICS
FUM
HYDRAULICCOIBUCTIWTY
AQUIFiRTHICKNESS
POROSITY
AQUITWO
BESIOUAL SOURCE
ORGANIC CARBONCONTENT
Verticol and horizontal on any given vertical saclion. External stresses (recharge,chemical input) propagate vertically through the section. Flow vectors refract atinterface of materials having contrasting hydraulic conductivity.
Up to two principal values in o vertical section, reflective of lower sond unit (K1 "5 x 10-3 cm/sec), and upper fine grained unit (K2 — 5 x 10-4 cm/sec).
From water table or bottom of confining layer to top of Cook Mountain formation.
Total porosity measured by laboratory for sand materials on the order of 30 percent.
Leaky. Vertical gradients create flux through aquitard into and out of aquiferdepending on boundary conditions.
Diffusion of contaminants out of NAPL, wherever NAPL exists, into whatever geologicmaterial is present.
Variable. Two primary values within the lower carbonaceous rich sand unit- one fordisseminated organic carbon (foe = 0.001), another for the depths below which thereis on abundance of carbonaceous layers.
Horizontal only in any given vertical pram (model node). Recharge, chemical input.etc. ore distributed instantaneously and uniformly through the vertical section. Flowvector (arrow) density proportional to flux.
One value in a given node, reflective of the dominant material type over the aquiferthickness. May vary in plan view.
From water table or bottom of confining layer to depth at which carbonaceous layersappear. Flow calibration will proportion flux through reduced section as compared tothe fun aquifer thickness.
Effective porosity for sand materials is used to account for dead end pore space.Estimated at 25 percent.
Impermeable. Leakage / contaminant flux through oquitard into or out of aquifer oreprescribed rather than computed, modeled by addition or removal of water /contaminant mass directly within the nodes.
Dud source, one representing contaminated soil within carbonaceous sand unit. theother representing contaminated sol in fine groined unit Different rates of release toreflect relative Impact on carbonaceous sand unit
Constant. One primary value within the carbonaceous sand unit, for disseminated organiccarbon (foe » 0.001).
DATE: 02/10/88 [TIME: 5:40 PU]
POPILE. INC. SUPERFUND SITEEL DORADO, ARKANSAS
_ REMEDIAL DESIGN PHASEUSACE TULSA DISTRICT
Figure 2-1
SIMPLIFIEDCROSS SECTION OF FLOW
dORRISON KNUDSEN CORPORATION' 7100 E. M——w AM., Englnood. CO 8011' 7«1.(:!M)7»3-5000
SCALE
DRAWN: S-SCHMITT
CHECKED: J.SIECEL
DATE
02/10/M
v- inning02/12/M
KM Item
WORK ORDER NUMBER
4423-1801MAKING NUMBER
17x
22REV
0
_________LEGEND__________
__.151_— STORATIVITY (DIMENSIONLESS)
|H| INACTIVE CELLS
/^a, STORATXVITr PREDOMINANTLYy^ 7.3 x 1(r4 (CONFINED)
NOTE:
1. EFFECTIVE PCROSITY - 0.30 (ALL NODES)
_________LEGEND_________
—18Z522—— ELEVATION (FEET, MSL)
| H INACTIVE CELLS
_________LEGEND__________
—164.514—— ELEVATION (FEET, MSL)
|H| INACTIVE CELLS
_________LEGEND__________
——16.350—— AOUIFER THICKNESS (FT.)
|H| INACTIVE CELLS
wm
0
u
3.0 Head Calibration
3.1 Objective
The objective of head calibration is to obtain the best possible match between modeled and observedground water contours by trail and error of calibration parameters, within reasonable ranges.Judgement of the match is made visually and focuses on whether patterns such as increased ordecreased gradients or direction of flow is met in critical areas. Less critical areas of the site, (i.e.those where contaminants need not be simulated) weigh less on judgement.
3.2 ProcedureUsing the boundary heads identified in Section 2, steady state simulations were run for multiplecases of hydraulic conductivity zoning. A uniform distribution was used in the initial stage at theexpected upper and lower limits and geometric mean value of measured hydraulic conductivities ofthe Cockfield sands. BIOPLUME in was also used to krige the measured values at control pointsand redistribute the values among the model nodes. The following are representative distributionsapplied:
• Uniform• Zoned based on measured values
• Zoned based on measured values with selective removal of outliers
Head calibration was complete when, in MK's judgement, the modeled heads substantially matchedthose observed.
In prescribing boundary heads, key control wells drove the process as opposed to known fluxesderived independently through water balance, recharge sources, surface water controls, area ofsurface seepage, and the like. These phenomena are all implied by the calibrated head map, but not
expressly modeled. While convenient in helping the calibration, the fixing of heads at key locationsto derive the boundary conditions constrains the calibration more than modeling "root stresses ".
3.3 Fixed Input ParametersAs noted in Section 1.3, certain input parameters were fixed for calibration and reserved to vary onlyin sensitivity analysis.
Effective Porosity. Effective porosity represents the actual pore space that is available for waterconveyance. The effective porosity value used in the simulations was determined to be 0.30 based
F:\ICoemi\TBRC\T01B\C>litinaionReport\cdibipl.wpd 3-1 (Rev. a, March 1999)
on laboratory tests of a soil sample (BH-29-S-23), which indicated that the soil contains 83 percentof sand and 8.5 percent of clay, and has a 36 percent total porosity. The USDA - AMPT.EXEcomputer program (Brakensiek et al., 1984) was used to calculate the effective porosity.
Dry Bulk Density. Similar to the effective porosity, the dry bulk density was calculated to be 1.7g/cm3 based on the soil sample (BH-29-S-23) with a specific gravity of 2.62 g/cm3.
Isotropic Coefficient. The hydraulic and transport properties were assumed to be isotropic.
Aquifer Thickness. The aquifer top and bottom elevations by node, presented in Section 2, were usedby the model to calculate the thickness of flow throughout the flow regime.
Areas of Confinement, The confined and unconfined conditions were simulated by assigning thestorativity values accordingly within the simulation domain as discussed in Section 2.2. Most of theareas within the simulation domain are under confined conditions where storage coefficient is lowand pressure heads are above the aquifer top elevations. In the areas where unconfined conditionsexist, the storage coefficient equals to the effective porosity of the aquifer and the pressure headscorrespond to the water tables.
F:\KoCTig\TERC\TOl«\C«librationRcpoct\c«libcpt.wpd 3-2 (ReV. a, March 1999)
wm
0J&
4.0 Head Calibration Results
4.1 Hydraulic Conductivity Distribution SelectedFigure 4-1 shows the zoned hydraulic conductivity values for the modeled Cockfield sand horizonwhich resulted in the best head match. This distribution represents actual measured hydraulicconductivity values input to BIOPLUME ffl, then kriged, contoured, and redistributed to the nodesin an unbiased manner. The actual hydraulic conductivity distribution, though itself very uniform,improved the head match over all uniform distributions tested.
4.2 Resultant Head MatchThe results of the steady state calibration are shown on Figure 4-2, which superimposes the model-predicted potentiometric surface over the September 1998 heads contoured from monitoring welldata. For consistency, both surfaces were generated using the program Surfer (Golden Software,1997). Slight variations between the observed September 1998 potentiometric surface as reportedinMK (1999a) and on Figure 4-2 do result. The modeled and observed surfaces on Figure 4-2 arein reasonable agreement in the areas critical to contaminant modeling.
The potentiometric head differences between model-predicted and observed values on a node to nodebase are given in Table 4-1. The maximum deviation of predicted versus observed elevations is 2.46feet and the average difference in water level elevations over the site is 0.57 feet.
Figure 4-3 shows the correlation between modeled and observed head pairs throughout all nodes inthe model. The coefficient of correlation is 0.95. A significant mismatch occurred in the areaswhere observed head values are absent or scarce such as in the lower head areas along the Bayou andeast of the Bayou and in the higher head areas outside the western property fence. Based on a totalevaluation, the head match is considered good.
4.3 Flux and Pore VelocitiesUnder steady state conditions, ground water inflow into the simulation domain equals to the outflowat about 907 fr'/day. Error for the flow mass balance is nearly zero for the final calibration,indicating an acceptable numerical accuracy. Table 4-2 is a velocity map in feet per year showingthe spatial distribution of nodal ground water velocities. These nodal ground water velocities varyfrom 0.5 feet/year to 63.8 feet/year with an average value of 21.3 feet/year. The high velocitiesappear in the western to central part of the simulation domain as steep ground water gradients existdue to the drop in aquifer elevations. Ground water flow slows towards the Bayou in the east andthe northeast of the simulation domain near the Bayou.
F:\KoCTig\TEROT018\C«librati™Report\c«librpl.wp<l 4-1 (Rev. a, March 1999)
Table 4-1 Differences between Modeled and Observed Potentiometric Heads for the Calibrated Model
Table 4-2 Simulated Velocity Map (ft/year)
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.5
3.5
9.4
3.9
4.1
2.3
7.1
10.3
6.5
3.1
10.4
13.9
12.3
12.2
13.3
19.0
25.8
21.6
14.5
12.8
16.6
27.0
27.0
21.1
19.3
19.4
20.0
22.0
21.1
14.0
7.8
10.6
5.7
0.0
0.0
1.5
7.3
15.9
8.2
6.6
3.0
17.1
19.2
14.3
9.9
24.3
27.8
26.8
27.6
30.5
40.4
49.4
41.6
33.0
31.5
39.3
57.1
54.3
47.6
44.2
43.2
43.7
46.4
41.9
28.6
18.6
22.3
13.7
0.0
0.0
2.8
6.6
9.0
6.7
6.2
5.6
17.3
17.8
16.6
16.0
26.0
27.8
29.4
31.5
34.8
41.2
44.7
40.8
38.4
39.3
45.7
57.8
55.8
53.3
49.7
48.0
47.3
46.4
40.5
30.1
21.5
18.2
7.4
0.0
0.0
5.5
5.7
1.9
5.3
8.6
10.8
14.9
16.5
17.2
18.8
23.2
25.6
28.0
30.7
33.8
36.4
36.9
36.9
37.7
40.1
44.8
50.6
51.5
50.8
48.9
47.1
44.3
41.3
36.9
29.4
20.4
8.9
10.4
0.0
0.0
11.6
7.8
1.8
7.7
11.3
13.5
16.0
16.7
17.8
19.5
22.1
25.1
27.4
30.0
32.6
33.8
33.7
32.9
35.7
39.7
43.0
46.1
47.7
48.2
46.9
44.6
41.6
38.9
35.6
30.0
21.7
8.2
25.1
0.0
0.0
5.8
4.2
8.9
12.1
14.3
16.0
17.4
18.1
19.3
20.6
22.4
25.7
27.5
29.7
31.9
32.4
30.9
29.4
33.8
38.2
40.7
43.0
44.9
44.9
44.6
43.3
40.9
38.8
36.8
33.6
29.1
23.3
19.0
0.0
0.0
17.6
22.6
18.0
17.2
17.9
18.3
18.5
19.7
21.3
21.6
23.3
26.2
27.3
29.2
31.7
31.8
29.3
28.1
32.7
36.8
38.9
41.0
42.0
42.4
42.3
41.6
40.4
39.1
38.2
37.5
38.0
42.6
59.3
0.0
0.0
28.3
30.8
26.2
22.8
21.4
20.4
20.2
21.2
22.5
22.2
24.1
26.3
27.2
29.0
31.7
32.3
30.2
29.4
33.0
36.0
37.4
39.0
40.0
40.1
40.1
40.3
39.6
38.9
38.7
39.5
42.2
48.8
63.8
0.0
0.0
33.9
38.4
32.1
28.4
26.5
25.0
24.3
23.2
23.0
22.2
23.3
25.6
27.4
29.9
32.7
33.0
31.8
31.9
33.8
35.9
36.9
38.8
39.3
39.0
39.2
38.7
38.2
37.8
38.1
39.2
41.8
46.3
52.7
0.0
0.0
36.3
40.5
35.1
31.4
28.8
26.9
26.1
25.2
24.0
21.7
22.2
24.8
27.6
30.0
31.8
32.4
33.7
33.8
34.9
36.5
36.7
38.2
37.6
37.7
37.4
37.1
36.8
36.5
36.5
37.2
39.0
41.3
44.1
0.0
0.0
38.6
43.0
36.2
32.0
29.4
27.5
26.4
26.4
25.4
22.6
22.4
24.4
27.2
29.9
32.0
33.1
34.0
34.8
35.8
35.8
35.7
36.5
36.6
35.5
35.1
34.8
34.4
34.1
33.9
34.1
34.9
35.2
35.1
0.0
0.0
40.2
40.8
33.1
30.2
28.8
27.1
26.2
26.2
25.5
23.9
23.3
24.3
27.3
30.1
32.6
33.7
33.9
35.5
36.2
35.4
34.5
34.3
34.7
34.8
33.9
32.3
31.9
31.4
30.8
30.4
30.0
28.7
26.8
0.0
0.0
23.4
23.9
25.5
26.3
27.2
26.8
26.5
26.0
24.8
23.9
23.8
25.3
28.3
30.1
31.6
32.9
32.3
35.5
36.1
34.5
33.8
32.6
32.5
32.2
31.0
30.1
29.5
28.8
27.8
26.4
24.6
22.7
19.9
0.0
0.0
4.3
13.5
19.7
22.4
24.1
26.1
27.2
26.5
25.2
23.8
23.9
24.8
27.4
29.2
29.8
31.0
30.9
35.1
34.7
33.3
32.8
31.8
31.4
31.0
29.7
28.2
27.4
26.2
24.7
23.1
21.5
19.4
15.6
0.0
0.0
5.9
14.9
18.4
20.1
21.1
22.7
24.4
25.1
24.7
24.6
24.5
24.7
26.4
28.2
29.3
30.1
30.3
34.2
33.6
31.2
29.8
28.8
28.2
27.9
26.8
26.0
25.1
24.1
22.7
21.4
20.0
17.8
14.4
0.0
0.0
17.4
21.1
18.3
18.1
18.5
19.5
21.5
23.0
23.8
25.2
24.7
25.2
7.6.2
27.8
28.5
29.2
30.1
32.5
31.0
29.1
28.1
27.1
26.3
25.8
25.2
24.5
23.9
23.0
21.8
20.6
19.3
17.0
14.1
0.0
0.0
17.8
17.5
15.9
15.9
16.6
17.8
19.5
21.1
22.4
23.6
23.5
23.6
25.1
26.9
28.6
29.1
30.4
31.2
29.0
27.9
27.0
26.2
25.4
24.7
24.0
23.5
23.0
22.4
21.5
20.5
19.2
16.8
13.0
0.0
0.0
9.5
11.2
12.4
13.4
14.6
16.1
17.9
19.1
20.2
21.3
22.2
22.7
23.6
25.0
26.3
27.1
27.9
27.2
27.2
27.0
25.9
24.9
24.0
23.3
22.6
22.5
22.3
21.9
21.6
21.3
20.3
17.9
11.0
0.0
0.0
5.3
8.4
9.9
11.3
12.6
14.2
15.9
17.2
18.6
20.7
21.9
22.0
21.9
22.2
23.0
24.5
25.4
24.9
24.8
24.3
23.6
23.1
22.8
22.4
22.2
21.8
21.3
21.1
21.1
21.2
21.6
23.4
29.2
0.0
0.0
4.3
6.7
8.4
9.8
11.1
12.5
14.1
15.6
17.0
19.6
20.4
20.8
21.1
20.9
21.5
22.4
23.3
23.0
22.2
20.9
20.9
21.4
21.4
21.1
21.1
20.5
20.1
19.9
19.7
19.9
21.1
24.9
36.0
0.0
0.0
2.7
5.1
7.2
8.7
10.3
11.6
13.0
14.4
15.7
18.1
18.6
19.6
20.4
20.6
21.0
21.4
21.5
21.5
21.1
20.6
20.5
20.2
20.1
19.9
19.7
19.1
18.8
18.5
18.0
17.8
18.1
19.0
19.6
0.0
0.0
1.0
3.9
6.3
8.0
9.5
10.9
12.2
13.7
15.1
16.9
17.4
18.3
19.1
19.9
19.8
20,1
20.3
20.4
20.4
20.5
20.0
19.7
19.3
18.8
18.6
18.4
17.8
17.0
16.4
15.7
14.9
13.7
11.2
0.0
0.0
4.2
6.2
6.2
7.4
8.9-
10.2
11.4
12.8
14.3
15.8
16.4
17.3
18.0
18.3
18.5
19.1
19.2
19.4
19.6
19.6
19.4
19.0
18.4
17.8
17.6
17.4
16.4
15.7
14.9
13.8
12.2
9.8
5.8
0.0
0.0
5.8
5.4
5.2
6.5
8.1
9.4
10.8
12.2
13.6
14.8
15.7
16.7
17.3
17.2
17.7
18.2
18.3
18.5
18.6
18.7
18.6
18.5
18.3
17.8
17.0
16.4
15.9
14.8
13.7
12.5
10.6
7.7
3.3
0.0
0.0
1.7
2.0
3.1
5.2
6.9
8.4
9.9
11.4
12.8
14.0
15.2
16.1
16.7
17.6
17.7
17.5
17.5
17.6
17.8
17.9
17.9
18.0
17.9
17.4
16.8
16.1
15.5
14.5
13.1
11.8
10.1
7.3
3.2
0.0
0.0
2.7
1.5
1.7
3.8
5.6
7.5
9.2
10.8
12.1
13.6
14.6
15.4
16.1
16.6
16.7
16.9
16.9
16.S
17.0
17.2
17.3
17.4
17.2
16.9
16.5
15.5
14.9
14.2
13.2
12.0
10.5
8.5
3.7
0.0
0.0
2.6
2.0
0.9
2.4
4.6
6.7
8.6
10.2
11.7
13.1
14.2
15.1
15.7
15.9
16.3
16.3
16.2
16.2
16.3
16.6
16.8
16.9
16.8
16.5
16.1
15.5
14.7
13.9
13.2
12.2
11.9
12.5
15.5
0.0
0.0
2.4
3.1
1.9
1.3
3.5
5.8
8.0
9.8
11.4
13.0
14.1
15.1
15.6
15.8
15.8
15.6
15.4
15.5
15.6
16.0
16.4
16.6
16.5
16.3
15.9
15.4
14.3
13.5
13.0
12.7
12.7
14.4
21.0
0.0
0.0
10.5
10.9
4.7
1.2
2.6
5.1
7.4
9.4
11.4
13.1
14.3
15.3
15.9
15.9
15.4
14.8
14.6
14.7
15.1
15.8
16.2
16.4
16.2
16.3
16.0
15.3
14.3
13.2
12.5
12.3
11.6
11.3
10.3
0.0
0.0
14.9
11.4
5.2
1.8
1.8
4.4
7.0
9.3
11.5
13.4
14.8
15.9
16.5
16.2
14.7
13.7
13.5
14.0
15.0
15.9
16.2
16.2
16.1
16.6
16.3
15.5
14.1
12.5
11.8
11.6
11.2
9.6
4.6
0.0
0.0
8.1
5.3
4.2
2.2
1.3
4.1
6.8
9.3
11.7
13.8
15.5
17.0
17,9
17.4
13.1
11.2
11.8
13.6
15.4
16.7
16.5
15.9
16.0
17.1
17.2
16.6
13.5
11.5
1 1 . 1
11 .1
11.5
11.3
12.7
0.0
0.0
2.9
1.6
4.7
3.9
1.1
3.9
6.9
9.6
12.0
14.3
16.3
18.4
20.5
22.2
9.5
6.1
9.4
12.8
15.8
18.7
17.0
14.8
15.4
17.5
18.8
20.4
12.0
8.7
9.7
10.6
11.4
12.6
16.2
0.0
0.0
1.9
0.9
4.5
2.8
0.7
2.7
4.6
6.4
8.0
9.4
10.8
12.5
14.4
17.1
4.2
2.7
5.4
7.9
10.4
13.2
10.6
8.7
9.7
11.4
12.8
15.4
5.7
4.6
6.0
6.6
7.1
7.4
6.6
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
_________LEGEND__________
•—I.IXIIT*— HYDRAULIC CONDUCTIVITY (CM/SEC.)
gH| INACTIVE CELLS
_________LEGEND__________
• BOREHOLE (BH)
A SEDIMENT OR SURFACEWATER LOCATION (SO/SW)
•-EC SCAPS LOCATION
• MONITORING WELL (MW) OR PIEZOMETER (PZ)
0 ABANDONED »EU- OR PIEZOMETER
-—185-—— MODELED GROUNDWATER ELEVATION
-——185—— OBSERVED GROUNDWATER ELEVATION
Static Piezometric Heads_______(R^ 0.95)_____
wm
01
5.0 Contaminant Calibration
5.1 ObjectiveThe objective of contaminant calibration is to obtain the best possible match between modeled andobserved ground water concentration contours for PCP and Naphthalene, by trail and error ofcalibration parameters, within reasonable ranges. However, calibration of the contaminants is notas amenable to well-to-well data point comparisons for reasons which follow.
Figures 1 -2 and 1 -3 show that the PCP and Naphthalene plume concentrations were observed to varyfour orders of magnitude in less than 200 feet from the source. Owing to the fact that wells were notand could not be placed with high density within this travel distance owing to the presence of theRailroad, much of the interior plume definition is reflective of the contour algorithm as opposed toany wealth of actual data points spanning the orders of magnitude of tens, hundreds, and thousandsof micrograms per liter (ag/L). Also, within a travel distance of 40 feet in the real ground watersystem (e.g., the node size is 40 by 40 feet), it is probable that an order of magnitude change incontaminant concentration occurs. In the model domain, only one ground water concentration canbe predicted within a given node.
The Phase n RD report also indicated that the PCP and Naphthalene plumes were constructed withsoftware using a logarithmic interpolation, avoiding closed contours greater than the contaminants'solubility limits, assigning a concentration of one tenth of the detection limit (<20 ug/L Naphthalene
= 2 ug/L; and <1 ug/L PCP =0.1 ug/L) for non-detect data for contouring, and then projecting thedetection limits as the lowest magnitude contours. The results of the exercise are smooth contours,which if anything overestimate the extent of low-level (single or tens of |ig/L) concentration patternsbecause of "drawing out" of the contour control points to the non-detect control points which, inmany cases, are distant from the source.
The objectives of the contaminant calibration are therefore:
• To replicate the general shape and extent of the plumes with the lowest numerically modeledconcentration contour. This model contour should lie mostly within the maximum limit of theplumes as contoured from observed data.
• To replicate the occurrence of four orders of magnitude concentration changes within theplume interior, keeping in mind that well-to-well concentration matches may be fortuitous, butnot necessarily further reflective of good calibration.
F:\KoBiig\TERC\TO18\CalibiitionRcport\c«libipt.wpd 5-1 (Rev. a, March 1999)
Judgement of the contour match is made visually.
Per the Record of Decision, the COCs are PCP, and the following seven PAHs: benzo(a)pyrene,
dibenz(a,h)anthracene, benzo(a)anthracene, benzo(b)fluoranthene, benzo(k)fluoranthene, chrysene,and indeno( 1,2,3 -cd)pyrene. However, as indicted in the Phase II RD report (MK, 1999a) only PCPand Naphthalene are somewhat mobile and exhibited sufficient spatial extent to be amenable tointerpretation and calibration.
5.2 ProcedureUsing the steady state head match identified in Section 4, transient state simulations were run for 50years with an initial condition of zero contaminant concentration at all locations, and a time-independent source term (an internal boundary condition composed of concentration and flux).Principal variants in the calibration were:
Single versus dual source. The Ground Water Modeling Work Plan indicated that constantconcentrations of the simulated contaminants would be applied to the finite-difference cells in theBIOPLUME DI model in the source zone, or that algorithms would be used to calculate the flux ofthe contaminants out of the carrier fluid. The source area was subject to calibration both as to sizeand release rate. First, a small core was considered by assigning contaminant concentrations asconstant within a small area around well MW-18. This core was physically tied to the 33,700 ug/Lclosed contour for Naphthalene approximating the Process Pond 2 area. A vertical projection of thispattern through the sands would also approximate the area of where contamination is within thecarbonaceous sand unit (see Figure 2-1). For PCP or Naphthalene, a constant ground waterconcentration within this area was assigned using Raoult's law (Appendix A), which determines theequilibrium solubility of a compound in water in the presence of multiple compounds. The constantconcentration implies that ground water concentrations are no greater than their equilibriumsolubility, and not controlled by a rate of release of a contaminant out of the NAPL carrier fluid.This constant concentration approach is justified by the fact that it would take up to 8 years for theground water to pass the source area when considering the core source is 180 feet in diameter andthe ground water velocity is 21 feet/year in average.
Within the larger area identified by MK (1999a) ofresidually contaminated soils within the aquitardand the less-permeable silty and clayey sands grouped into the model layer (see Figure 2-1), a fluxrelease rate was applied to recognize different leaching mechanisms (mainly by molecular diffusion)and their impact to the modeled carbonaceous sand unit (i.e., the layer modeled for all prisms).Figure 5-1 shows the boundary conditions assigned to the core and source flux nodes.
F:\Kotnig\TERC\T018\CiilibnnionRepon\csaibrpt.i»T)d 5-2 (Rev. a, March 1999)
Peripheral source flux. The source flux rate was varied to arrive at the magnitude of concentration
contours interior to the dissolved plume.
Lack or presence of biodegradation. Biodegradation was either absent or present in the modelduring the calibration procedure.
Calibration was accomplished in the following order:
• A single constant concentration core source was used to project the shape of the ground waterplume. Early results indicated that under no circumstance could the shape of the observedplume be replicated. The modeled plume tended to be classically elongated in the directionof flow, and not nearly as wide as the contaminant pattern.
• A source flux was applied at two locations in addition to the core: (1) the total area of
residually contaminated soils around the former process ponds, and (2) a smaller area at thelocation of the former detention pond north of the process area. These areas were presentedand discussed in MK (1999a).
• Without biodegradation, the retardation factor was varied only in a cursory way (with anunderlying total organic carbon content of 0.1 and 1 percent) so that the steepness ofconcentration contours within and away from the source areas reflected the observed declineto detection limits. For PCP, the chosen retardation factor caused contaminants to project
. farther than the 1 ug/L contour created from observed data.
• Biodegradation was added at a rate that retracted the low contour range.
• The contaminant flux, applied as a mass of contaminant per unit time, was varied until thesame flux at both the former process pond and the former detention pond provided dissolvedconcentration ranges observed at each location, respectively.
5.3 Fixed Input Parameters
The contaminant transport calibration is subject to non-uniqueness much more than the headcalibration, due to the number of variables involved. The following input parameters were fixed forcalibration and reserved to vary only in sensitivity analysis.
Constant core concentration. Near the source of contamination, one of the primary processescontrolling the release of organic compounds is solubility. It is reasonable to assume that organic
P:\KoCTig\TERQTO)»\C»librationRtp(xt\c»lil»pt.i»pd 5-3 (Rev. a, March 1999)
contaminant concentration in ground water is equal to its pure product water solubility if the source
of interest was composed of a single contaminant. However, wood treating chemicals in the Popile
site consist of mixtures of multiple compounds such as those identified in Appendix A. According
to the Raoult's law, the equilibrium solubility of a compound in a mixture is proportional to the mole
fraction of the compound in the mixture (Lee et al., 1992). The constant core concentrations werespecified to equal to the equilibrium concentrations at 2,080 Hg/L for PCP and 5,460 ug/L forNaphthalene.
Dispersivity. Simple estimation techniques based on the length of the plume are available from acompilation of field test data (Gelhar et al., 1992). Typical dispersivity is a function ofLp (the
plume length in ft) as shown below.
Longitudinal Dispersivity
(XL = 3.28 * 0.83 * [log,o (Lp / 3.28)]2-414 (Xu and Eckstein, 1995)
Transverse Dispersivity
(XT = 0.33 * (XL (EPA, 1996)
The plume length (Lp) was measured to be approximately 230 feet for both PCP and Naphthalenefrom Figures 1-2 and 1-3. Therefore, the dispersivity in the longitudinal direction was calculatedto be 12 feet.
Retardation Factor. The retardation factor (R) is the ratio of the ground water velocity to the ratethat organic chemicals migrate in the ground water and can be calculated using:
R = l + K , * p b / n
K() = KO(; * fp,;
where K^ is the distribution coefficient; p,, is the bulk density; n is the effective porosity; K^ is theorganic carbon partition coefficient; and f^ is the fraction of organic carbon in the soil. As shownin Section 3.3, pi, and n were determined to be 1.7 g/cm3 and 0.3, respectively, using a soil samplefrom the aquifer. Log(K;J was found to closely agree with published values in the Phase II RDreport and was equal to 3.2 for PCP and 3.16 for Naphthalene. K^ is therefore calculated to be 1.59
F:\KoCTig\TEROT01«\C«libratK>nRcporttc«Iibipt.wpd 5-4 (Rev. a, Marrh 1999)
cm^g for PCP and 1.45 cm^g for Naphthalene when 4c is set to the Popile site representative valueof 0.1 percent. This resulted in R values of 10.01 for PCP and 9.02 for Naphthalene.
Biodegradation Parameters. As discussed in the Ground Water Modeling Work Plan (MK, 1999b),the complete mineralization of PCP and Naphthalene from aerobic degradation is simulated. Also,the reaction kinetics is represented by the Monod function which requires the input of the followingparameters: (1) stoichiometric ratio of oxygen to hydrocarbon contaminant; (2) oxygen thresholdconcentration; (3) maximum hydrocarbon contaminant utilization rate; (4) Hydrocarbon contaminanthalf-saturation constant; (5) oxygen half-saturation constant; (6) total microbial concentration; and(7) retardation factor for microorganism.
The biological reaction equation for complete mineralization of PCP is expressed as:
4CfiHOCL5 + 230; -———>24C02 + 2^0 + 20CL-
The reaction stoichiometry was used to convert the mass of oxygen consumed to the mass of PCPthat are used in the biological reaction, i.e., 23 moles of oxygen (736 grams) react with 4 moles ofPCP (1,065 grams). Therefore, the utilization factor (UF) for the aerobic degradation of PCP iscalculated to be 0.6911.
Similarly, the biological reaction equation for Naphthalene is:
C,oHs + 1202 -———> lOCO^ + 4H;0
or 12 moles of oxygen (384 grams) react with 1 mole of Naphthalene (128 grams), and the utilizationfactor for the aerobic degradation of Naphthalene is 3.0.
The oxygen threshold concentration is defined as the oxygen concentration below which aerobicbiodegradation does not occur. A concentration of 500 ug/L was used as a result of the dissolvedoxygen measurements at the Popile site (MK, 1999a) and other studies (EPA, 1998; and Stroo et al.,1997).
Biodegradation parameters such as the maximum hydrocarbon contaminant utilization rate,hydrocarbon contaminant half-saturation constant, and oxygen half-saturation constant were targetsfor calibration because the results from the Popile site field investigation and laboratory tests do notmeasure these modeling parameters. The calibration of these parameters was started with literaturevalues (Borden and Bedient, 1986; Munoz and Irarrazaval, 1998) for similar biodegradation studies.
F:\Koeni"\TBROTOlB\CalibnuionRepon\cilibTpi.wpd 5-5 (Rev. a, March 1999)
Calibration results indicated that these literature values are actually applicable to the Popile site
without modifications. The values adopted for simulation were:
Maximum Hydrocarbon Contaminant Utilization Rate =1.7 days,
Hydrocarbon Contaminant Half-Saturation Constant =130 ug/L, and
Oxygen Half-Saturation Constant =100 ug/L.
Microbial populations were measured in the laboratory tests from soil and ground water samplescollected during the Phase II RD investigation. The mean total microbial concentration (17.23 ug/L)was used in the simulations by the sum of geometric means of microbial concentrations in the soils(14.9 ug/L) and in the ground water (2.3 3 ug/L). This value was a target for sensitivity analysis dueto the wide range of values reported in the laboratory tests (MK, 1999a).
The microbial retardation factor is a measure of the microbial population partitioning in the aquifermatrix and in the ground water and was calculated to be 7.39 using the geometric means of microbialpopulations in the soil and in the ground water.
Recharge of Dissolved Oxygen. Dissolved oxygen was assumed to be replenished due to the aquiferrecharge in the high land area in the western part of the Popile site, oxygen diffusion rechargevertically from the aquitard, and mechanical mixing of the flows from offsite areas. Constantconcentration at 4,500 ug/L was placed to the cells along the four sides of the simulation domain.
F:\Kofflig\TEROT018\CaHbrBtionReponVc«libipl.wpd 5-6 (Rev. a, March 1999)
north
»
100 50 0______TOO______200 FT.
SCALE IN FEEJ
o TO-MM ^ nmn.RgoirrA ____ . . ISSUED FOR REVIEW AND COMMENT______
«v DOTE •755 ____eesciupnoN_______
POPILE, INC. SUPERFUND SITEEL DORADO, ARKANSAS
PHASE II RD GROUNDWATER INVESTIGATION13 USAGE TULSA DBTF8CT
FIGURE 5-1
,=o7<H] MODELED CONTAMINANT CORE' ~ AND PERIPHERAL SOURCE AREA
^MORRISON KNUDSEN CORPORATION\Sjy THIO e. oaniiii m, pi —id, co wn wifM-asoo
SCMt!«S«01» I PME | • (M( ORiOl MiMBr??"
ouuti.M.mcac S/S/M 4423-1801 ^[itSiao:i8iaa. sft/w —oiuMN6NUMBt~— w"OCCKtD: I I />
V)m
a
6.0 Contaminant Calibration Results
6.1 Calibrated BIOPLUME III Model ParametersTable 6-1 presents a summary of the physicochemical, biogeochemical and biological parametervalues for the calibrated transport model. It includes all line input items actually used in the model.Units of measure in the table are converted from those units required by the code to units of measuremore customarily used (i.e., cm/sec instead of ft/sec for permeability). The best acceptablecalibration resulted from inspection of more than 50 simulation results.
6.2 Resultant PCP and Naphthalene Concentration Contour MatchFigure 6-1 shows the calibrated PCP plume with biodegradation, and Figure 6-2 shows theNaphthalene plume. Both contour surfaces were generated using the program Surfer (GoldenSoftware, 1997)). For PCP, the 1 ug/L contour line was estimated on Figure 1-2, so the visualjudgement of match between simulated and observed concentrations focused on the 10 ug/L and 100ug/L contour lines. Both the simulated and observed PCP contours at the 10 ug/L and 100 ug/Llevels generally have an oval to rectangular shape and cover roughly the same areas. The 10 ug/Lline reaches the far side of the sludge pit in the west, nearly to MW-33 in the north, between the railtrack and the east rail track fence in the east, and close to MW-26 in the south. The 100 u^g/L linereaches the near side of the slug pit in the west, the northern most portion of process pond 3 in thenorth, the rail track in the east, and about 75 ft north of MW-26 in the south. In addition, a 10 ug/Lplume, roughly in the shape of a circle, was reproduced in the north detention pond area.
For the Naphthalene plume, the 200 ug/L contour lines are compared. The locations of this contourline are described as: the sludge pit in the west, north of MW-33 and possibly connected to the northdetention pond in the north, between the rail track and the east rail track fence in the east, andMW-43 in the south.
Based on the calibration objectives listed in Section 5.1, these plumes are considered to be inreasonable agreement.
Simulation results were examined for the pattern of dissolved oxygen in the contaminant plume area.Figures 6-3 and 6-4 show the extent of depressed dissolved oxygen levels caused by PCP and
Naphthalene degradations, respectively. Although confidence is low due to the very limited datapoints, the size of dissolved oxygen depression on Figure 1-4 is greater than either the depressionplume caused by PCP degradation or the one caused by Naphthalene degradation. This is the result
F:\KoBiig\TERC\T018VMibrationRqx)n\c«liblpt.l>Tid 6-1 (Rev. a, March 1999)
of combined oxygen consumption by PCP, Naphthalene, and other biodegradable organic
compounds and so is considered acceptable in that it is consistent with expectations.
For both PCP and Naphthalene, the calibrations have determined that the core source area at constantconcentration is about 21,260 ft2. The peripheral source flux area is approximately 97,100 ft2 whilethe north detention pond flux area is about 8,800 ft2. Because of the confining conditions beneaththe source flux areas, downward movement of water (as modeled) is impossible, and the contaminantfluxes from the aquitard to the aquifer can only happen in the form of molecular diffusion due theconcentration gradients. The molecular diffusivity of most organic compounds are in the rangesbetween 9.3xl0'4 and 9.3xl0"5 ff/day (Wang and Chen, 1980), and large molecular size compoundsare associated with lower diffusivity values. One-dimensional contaminant fluxes were calculatedwith a difiusivity of 9.3xl0"5 ft^day using the Pick's law for PCP and Naphthalene. The averagetravel distance is 2.5 ft giving the residual NAPL found in the aquitard within 5 ft above the aquifer.The Pick's law contaminant fluxes for PCP and Naphthalene were calculated to be 2.03 ug/frVdayand 5.44 ug/fr'/day, respectively, very close to those calibrated values in Table 6-1 (2.12 ug/frVdayand 4.25 ug/fP/day, respectively). This is taken to mean that the calibrated flux is very credible.
Table 6-1 also shows that both contaminants have similar transport and biodegradationcharacteristics, but Naphthalene consumes almost 430 percent more dissolved oxygen than PCP perunit mass degraded. Although the equilibrium solubility of Naphthalene is 2.63 times more solublethan PCP, and the flux of Naphthalene recharged to the aquifer is twice as much as PCP, theNaphthalene plume is not migrating much further in the downgradient direction.
Figures 6-5 and 6-6 show the calibrated model without biodegradation for PCP and Naphthalene,respectively. Though these model runs are part of the sensitivity analysis, they are importantbecause biodegradation is the only attenuation mechanism that is destructive. It is theoretically truethat in steady state, and without biodegradation, all compounds will migrate to the Bayou andbeyond assuming a temporally infinite source. The reality may be that it will still take tens orhundreds of years for contaminants to reach the Bayou. These figures show that dispersion and
sorption alone can limit the plume movement.
F:\KoCTig\TERC\T018\C«librtonRcport\calibrpt.wpd 6-2 (Rev. a, March 1999)
Table 6-1 Physicochemical, Biogeochemical and Biological Parameters Usedfor the Calibrated Model
Input Parameter Name
PCP
Naphthalene
Equilibrium Solubility
Longitudinal Dispersivity
Transverse Dispersivity/Longitudinal Dispersivity
Distribution Coefficient
Utilization Factor
Oxygen Threshold Concentration
Maximum Hydrocarbon Utilization Rate
Hydrocarbon Half-Saturation Constant
Oxygen Half-Saturation Constant
Total Microbial Concentration
Microbial Retardation Factor
Dissolved Oxygen Background Concentration
Calibrated Peripheral Source Flux
Equilibrium Solubility
Longitudinal Dispersivity
Transverse Dispersivity/Longitudinal Dispersivity
Distribution Coefficient
Utilization Factor
Oxygen Threshold Concentration
Maximum Hydrocarbon Utilization Rate
Hydrocarbon Half-Saturation Constant
Oxygen Half-Saturation Constant
Total Microbial Concentration
Microbial Retardation Factor
Dissolved Oxygen Background Concentration
Calibrated Peripheral Source Flux
Values
2,080 ug/L
12ft
0.33
l^cm'/g
0.691 Ig/g
500 ug/L
1.7 days
130 ug/L
100 ug/L
17.23 ug/L
7.39
4,500 ug/L
2.12 ug/rrVday
5,460 ug/L
12ft
0.33
1.45 cm3/g,
3.0 g/g
500 ug/L
1.7 days
130 ug/L
100 ug/L
17.23 ug/L
7.39
4,500 ug/L
4.25 ug/tf/day
6-3 (Rev. a, March 1999)
_________LEGEND_________
• BOREHOLE (BH)
A SEDIMENT OR SURFACE• WATER LOCATION (SD/SW)
•-2C SCAPS LOCATION
• MONITORING WELL (MW) OR PIEZOMETER (PZ) |0 ABANDONED «ELL OR PIEZOMETER
/—100 —. ISO CONCENTRATION CONTOUR IN iig/L
_________LEGEND________
• BOREHOLE (BH)
A SEDIMENT OR SURFACE• WATER LOCATION (SD/SW)
•-BC SCAPS LOCATION
• MONITORING «ELL (MW) OR PIEZOMETER <PZ)0 ABANDONED «EU. OR PIEZOMETER
-—2000—— ISO CONCENTRATION CONTOUR IN ug/L
__________LEGEND_________ •_
• BOREHOLE (BH) _
A SEDIMENT OR SURFACEWATER LOCATION (SD/SW) -
•-eC SCAPS LOCATION
• MONITORING MELL (MW) OR PIEZOMETER (PZ)
0 ABANDONED WELL OR PIEZOMETER
-——2000—— ISO CONCENTRATION CONTOUR IN liqfl.
_________LEGEND ________
• BOREHOLE (BH)
A SEDIMENT OR SURFACE,WATER LOCATION (SD/SW)
«-£C SCAPS LOCATION
• MONITORING «ELL (MW) OR PIEZOMETER (PZ)0 ABANDONED fd-L OR PIEZOMETER
^—2000—— ISO CONCENTRATION CONTOUR IN iigfl.
_________LEGEND_________
• BOREHUf (BH)
A ^^^S^ON^^SW)
•-2C SCAPS LOCATION
• MONITORING HIEU. (MW) OR PIEZOMETER (PZ)0 ABANDONED WELL OR PIEZOMETER
•-—•100 —- ISO CONCENTRATION CONTOUR IN gA
__________LEGEND_________
• BOREHOLE (BH)
A SEDIMENT OR SURFACEWATER LOCATION (SVSW)
»-2C SCAPS LOCATION
• MONITORING WELL (UW) OR PIEZOMETER (PZ)0 ABANDONED «ELL OR PIEZOMETER
^—2000—— ISO CONCENTRATION CONTOUR IN wA
wm
^
7.0 Sensitivity Analysis
Sensitivity analysis was performed to determine which parameters are sensitive to the calibrationand might require further investigation. Further investigations into parameter values could bewarranted if they have a large impact on the model and are not well-measured, or if known, are stillperceived as important to support future site decisions. Whereas calibration determined the bestcombination of parameters to replicate the observed head contours and plume conditions, it does notexplicitly measure each parameters's relative importance by systematically holding all othersconstant and subjecting the tested parameter to wider variations than used in calibration, but stillwithin measured or literature-reported practical limits.
Sensitivity analysis was performed on the following parameters:
• Aquifer thickness• Hydraulic conductivity / effective porosity• Secondary contaminant source flux• Effect of each attenuation parameter• Dispersion• Retardation factor• Biodegradation rate• Simulation time
Each parameter's variation represents a departure from the base case (i.e., the calibrated model). Theeffect of each departure, all other parameters constant, is viewed by comparing the model output's
head map, contaminant map, or dissolved oxygen map, as appropriate, to other conditions and to thebase case.
The following sections explain the parameter variations and sensitivity results. The text refers topackaged figure sets in Appendix B, each "package" containing the plotted simulation results fromBIOPLUME III. One plotted simulation result is provided per parameter value or model outputoption.
7.1 Aquifer ThicknessThe effective bottom of the flow domain (i.e.^top of the carbonaceous layers) affected the calibratedflow pattern and the contaminant distribution. Because original assignment of the aquifer bottomwas based on the appearance of layered carbonaceous zones, and not a true low-permeability aquifer
F:\Ko«iug\TERC\T018\Calibr«lionRcpon\calibn>t.wp<l 7-1 (RCV. a, March 1999)
boundary such as the Cook Mountain formation, undulations in the assigned "bedrock" topographycould create and/or accentuate shifts in the flow pattern in the reduced aquifer thickness.
Several sets of spatial results were compared to determine whether an increase in the effectiveaquifer thickness has a material effect on the results (Table 7-1). The flow and contaminant transportwas simulated with a uniformly aquifer base of the aquifer 10 feet, increasing the typical aquiferthickness in the process area from 15 to 25 feet, or by 67 percent. This has the effect of increasing,in the same proportion, the carbon absorption capacity of the aquifer per unit plan view area for thereleased contaminant mass (held constant), and so would tend to decrease contaminant movementby absorbing more contaminants nearer the source.
Appendix B.I contains maps of aquifer head, PCP distribution, and dissolved oxygen for increasedeffective aquifer thickness. Figures B-l and B-2 (Appendix B) compare the contaminantdistributions between the calibrated model and one for a thicker aquifer. The contaminantdistribution is essentially unchanged. Figures B-3 and B-4 were compared against the PCP-induced
dissolved oxygen distribution (model run PCP50FO, Figure B-39), and the calibrated water table(Figure 4-1), respectively. These results were also found largely unaffected by the increase inaquifer thickness. The conclusion is that the site flow pattern and contaminant distribution isinsensitive to the thickness of the aquifer in context of all other conditions.
In the above interpretation the average pore velocities through the site would not have been greatlychanged by the increase in thickness. In a simulation controlled by boundary heads, the modelimplicitly passes enough flux under the given permeability condition to maintain the averagegradient between the boundaries. Since the thickness added to each node is assigned that node'scalibrated permeability, the flux increases in the thicker flow zone in the same proportion as theincrease in thickness, and velocity remains constant. Velocity-dependent processes (i.e., dispersion,and biodegradation which is modeled kinetically) are therefore not as important to this sensitivityanalysis to thickness as sorption, which is modeled in BIOPLUME III as a non-kinetic (equilibrium)process.
F:\Koai(\TERaT018\CalibretionRepon\caliblpl.wpd 7-2 (Rev. a, March 1999)
Table 7-1 Sensitivity Model RunsIncreased Aquifer Thickness
Model Run ID
PCPC50FH
PCPL+10H
PCPL+100
PCPL+10W
Plot Number(Appendix B)
B-l
B-2
B-3
B-4
Description
Calibrated Model
Bottom of aquiferuniformly depressed10 feet relative tobase case. Effectivethickness increasedby approximatelytwo thirds.
Output PresentationOption
PCP Distribution
PCP Distribution
Dissolved Oxygen
Head Pattern
7.2 Hydraulic Conductivity/ Effective PorosityThe hydraulic conductivity distribution was subjected to sensitivity analysis because of its impliedeffect on diffusion and biodegradation, both of which are modeled as kinetic processes. The slowerthe flow, the more dominant these processes become because water is resident at a given localelonger for these processes to operate. On the other hand, mechanical dispersion increases directly
with velocity and can have a greater effect than diffusion at higher velocities (see Section 5.3 for thefixed and variable components of dispersion). Table 7-2 indicates that three uniformly appliedhydraulic conductivity distributions were modeled, spanning a factor of 30 between high and lowvalues. In addition, one simulation was made at an effective porosity of 0.25, speeding the porevelocity by a factor of 1.2 (i.e., 0.30/0.25) to examine its effect on the calibration. The sensitivitywas examined from the standpoint of the PCP contaminant pattern. The calibration processdemonstrated that, within a given order of magnitude of hydraulic conductivity, the pattern ofhydraulic conductivity does not greatly affect the piezometric surface.
Appendix B.2 shows the PCP contaminant distributions resulting from differing magnitudes of
hydraulic conductivity. For the minimum hydraulic conductivity. Figure B-5 shows that the ProcessPond area's 1 microgram per liter (u,g/L) PCP contour retracted compared to that of the calibratedmodel (Figure B-7). Progressing through the geometric mean (Figure B-6) and maximum (FigureB-8) hydraulic conductivity distributions, the 1 u.g/L contour increases in size. The systemperformance is consistent with biodegradation having more effect on a slower moving system.Overall, the model is sensitive, but not very much so, to hydraulic conductivity.
7-3 (Rev.a,Marohl999)
In comparing Figures B-5 through B-8, it is clear that only the calibrated flow model produced
measurable PCP concentrations in the modeled secondary source area to the north of the processponds (see also Figure 5-1). For this area, this phenomenon is interpreted as follows. At slowervelocities, biodegradation is capable of consuming all of contaminant mass flux delivered to the
aquifer. At some velocity bracketing the range of the calibrated model (Figure B-7, and hydraulicconductivity on the order of 1.1 x 10'3 cm/sec from Figure 4-1), the velocity can move the massthrough the aquifer faster than biodegradation can operate. If this were so, then at still highervelocities (run PCPKMAXH, K= 3 x 10"3 cm/sec, Figure B-8) one should also see contaminationfrom the model output, yet there is not. All else constant, it is probable that mechanical dispersionbecomes a stronger force in diluting the plume, at least to concentration that can then be consumedat the calibrated biodegradation rate.
Table 7-2 Sensitivity Model RunsHydraulic Conductivity Variable
Model Run ID
PCPKMINH
PCPKMNH
PCPC50FH
PCPKMAXH
PCPEP25H
Plot Number(Appendix B)
B-5
B-6
B-7
B-8
B-9
Description
Minimum hydraulicconductivity of lxlO' 4
cm/sec, uniformly applied
Geometric mean
hydraulic conductivity of4.5 x 10'4 cm/sec,uniformly applied
Calibrated Model
Maximum hydraulicconductivity of3x 10'3
cm/sec, uniformly applied
Effective porositydecreased to 0.25
Output PresentationOption
PCP Distribution
A lower effective porosity (Figure B-9) does not affect the PCP distribution at all.
7-4 (Rev. a, March 1999)
7.3 Secondary Contaminant Source FluxSensitivity of the PCP contaminant plume's concentration and extent in response to the magnitudeof the source flux was performed to investigate primarily how much sorptive capacity was used andstill remains relative to the mass released in the 50 year calibration period.
Table 7-3 summarizes the model runs used to simulate the secondary source flux within the (lighter
shaded) areas shown on Figure 5-1. At zero flux (run PCPFXO_H), the only contaminant source inthe system is the single constant concentration source in the core area of the plume. In the extremecase, the secondary contaminant source flux was considered a constant core concentration over theentire area where residually contaminated soils remain (run PCPFXCCH).
Table 7-3 Sensitivity Model RunsSecondary Contaminant Source Flux
Model Run ID
PCPFXOH
PPFX10%H
PCPC50FH
PPFX10XH
PPFXCCH
Plot Number(Appendix B)
B-10
B-ll
B-12
B-13
B-14
Description
Mass flux is zero. Only the
constant concentration coreis present.
Mass flux at one tenth of the
calibrated flux
Calibrated Model
Mass flux at ten times thecalibrated flux
Constant core concentrationassumed present in all
residually contaminated soilareas.
Output PresentationOption
PCP Distribution
Appendix B.3 shows the PCP contaminant distributions resulting from differing magnitudes ofsecondary source flux. With only the core concentration present (Figure B-10), none of the transportprocesses from the otherwise "calibrated" can cause contamination to appear over a much larger areathat has been observed in the field. Conversely, when the area of residually contaminated soil isassumed to release contaminants at a constant concentration which is not flux-limited (Figure B-14),
7-5 (Rev. a, March 1999)
the magnitudes of ground water concentrations are much greater than observed in the actual ground
water system. Both of these factors are interpreted to mean that there is a dual source mechanism
operative in the ground water system.
Figures B-l 1 through B-13 indicate progressively increased areas of the aquifer occupied by PCPcontamination over a 100-fold increase in the flux factor, ranging from one tenth through ten timesthe calibrated flux. The PCP distribution is relatively sensitive to the magnitude of the source flux.However, attenuation processes are capable of containing contamination to a very small area outsideof the former process/ removal action excavation area. A large amount ofsorption capacity existseven if the calibrated flux for the model was greatly increased.
7.4 Effect of Each Attenuation ParameterThis sensitivity analysis examines which mechanisms are most important in limiting contaminantmovement at the site. Table 7-4 shows the model runs that were used to combine and compare theeffects of dispersion, sorption, and biodegradation. Appendix B.4 shows the PCP contaminantdistributions resulting from the model simulations described in Table 7-4.
Table 7-4 Sensitivity Model RunsDispersion, Sorption, Biodegradation Absent and Present
Model Run ID
P C P D H
P C P S H
P C P D S H
PCPC50FH
Plot Number(Appendix B)
B-15
B-16
B-17
B-18
Description
Dispersion only
no sorption
no biodegradation
Sorption only
no dispersion
no biodegradation
Dispersion and sorptiononly
no biodegradation
Calibrated Model with:
Sorption
Dispersion
Biodegradation
Output Presentation Option
Shows the effect of dispersion in the
absence ofsorption and biodegradation
Shows importance of sorption as the
sole attenuation mechanism
Shows relative importance of
dispersion in the presence of sorption
Shows added effect of biodegradation
7-6 (Rev. a, March 1999)
Figure B-15 indicates the PCP distribution with dispersion as the only operative mechanism in the
aquifer. Without other attenuation mechanisms, PCP contamination is predicted by the model tohave reached the Bayou at low microgram per liter levels. Without the binding effect of sorptionin the source areas, the 100 ^g/L concentration contour is projected east of the Ouachita Railroad,which was neither observed nor predicted by the calibrated model (Figure B-18). In the absence ofsorption, dispersion may be viewed as important. However, sensitivity analysis on dispersion in thepresence of sorption and biodegradation (Section 7.5) shows that when those processes are present,model results are insensitive to the aquifer dispersivity.
Figure B-16 shows the calibrated model with sorption only. Relative to prior model PCPD__H(Figure B-15), sorption has replaced dispersion as the major attenuation mechanism. As expected,sorption is dominant over dispersion as a mechanism keeping the contaminant plume frommigrating. When dispersion is added back to the sorption run (model PCPDS__H, Figure B-l 7),comparison of Figures B-16 and B-l 7 show that dispersion has a small effect on the contaminantdistribution. Low-level concentrations of PCP (generally below 100 ug/L) are spread over a greaterarea due to the presence of dispersion. When biodegradation is then added (Figure B-18), resultingin the calibrated model, it may be seen that the model is sensitive to the presence of biodegradation.Its effect is to degrade contamination at levels generally less than 100 ug/L. It is the key mechanismin the stabilizing of contaminant movement at low concentrations. Alternately viewed,biodegradation negates the effects of dispersion in the calibrated flow model.
7.5 DispersionTable 7-5 shows the model runs applied to determine the aquifer sensitivity to dispersion, andAppendix B.5 shows the PCP plume configurations for differing aquifer dispersivities.
Figures B-19 through B-21 (Appendix B.5) show that the contaminant distributions are virtuallyunaffected by the dispersion coefficients modeled. The site contaminant distribution is insensitiveto dispersion, in context of existing site conditions.
F:\Koeni»\TERQT01HC«lil>rationRtpon\c«libipt.wpd 7-7 (Rev. a, March 1999)
Table 7-5 Sensitivity Model RunsDispersion Variable
Model Run ID
PPD-50%H
PCPC50FH
PPD&50%H
Plot Number(Appendix B)
B-19
B-20
B-21
Description
Aquifer dispersivity is onehalf that of calibrated value
Calibrated Model;a = 12feet
aquifer dispersivity is 1.5times calibrated value
Output PresentationOption
PCP Distribution
7.6 Retardation FactorSensitivity of the PCP contaminant plume's concentration and extent in response to sorption wasperformed because sorption is an important mechanism in immobilizing large quantities ofcontaminant mass. As sorption is modeled as an equilibrium process, the effect on model sensitivitylies in the quantity of mass allowed to pass out of the general source areas, on which dispersion andbiodegradation then operate kinetically to spread and degrade.
Table 7-6 summarizes the model runs used to examine the sorption sensitivity, and Appendix B.6shows the plume maps for different retardation factors. Figures B-22 through B-24 indicate thatessentially the same areas of the aquifer are occupied by PCP contamination over a 50-fold increasein the sorption, ranging from one tenth to five times the retardation factor. The interpretation is thatat the range of practical levels of sorption, model results, in terms of the PCP distribution and extent,are insensitive. The quantities of mass released from the source and peripheral area, do not affect
the other processes that are capable of spreading and consuming contamination at low (less than 100Hg/L) levels.
Sorption still affects model results in the higher dissolved concentration ranges of contamination.When the calibrated model (Figure B-23) is simulated with sorption five times higher (Figure B-24),there is an appearance of an additional 100 pg/L closed contour zone in the process area, and a largerarea of the 10 |J.g/L contour to the north. The more sorption, the more the carbon loading and
through partitioning, the greater the ground-water concentrations. However, the apparent increasein extent of the ground water plume north of the process area in Figure B-24, as compared to FigureB-23, is probably not real. Instead it is a remnant of the grid size in concert with contouring of themodel results.
7-8 (Rev. a, March 1999)
Model results are sensitive to sorption, through not very much so, primarily through the level (but
not extent) of ground water concentrations within the source areas. A large amount of sorption
capacity still exists in the aquifer at the calibrated flux for the model.
Table 7-6 Sensitivity Model RunsRetardation Factor Variable
Model Run ID
PPS-90%H
PCPC50FH
PCPS&5XH
Plot Number(Appendix B)
B-22
B-23
B-24
Description
Retardation is one tenth ofthe calibrated value.
Calibrated Model;K, = 1.59 cm3/g;TOC= 0.001 (0.1%)
Retardation is 5 times thecalibrated value.
Output PresentationOption
PCP Distribution
7.7 Biodegradation RateAs stated in Section 5, six parameters control the simulated biodegradation in BIOPLUME in. Theparameter found most responsible in controlling the overall rate was the hydrocarbon utilizationfactor. The sensitivity model runs for biodegradation which vary this factor are shown on Table 7-7.Included for reference is a single model run examining the effect of the total microbial population.
F:VKi>n]ig\TERC\T01 Calibration Repon\calibrptwpd (Rev. a, March 1999)7-9
Table 7-7 Sensitivity Model Runsfor Differing Biodegradation Parameters
Model Run ID
PPMT10%H
PCPC50FH
PPU-10XH
PPU&10XH
Plot Number(Appendix B)
B-25
B-26
B-27
B-28
Description
Total microbial population isone tenth of the calibrated value.
Calibrated Model
Max. Hydrocarbon utilizationrate is one tenth of the calibratedvalue
Max. Hydrocarbon utilizationrate is ten times the calibratedvalue
Output PresentationOption
PCP Distribution
PCP plume maps for the differing biodegradation factors are shown in Appendix B.7, Figures B-25through B-28. Neither a ten-fold reduction in the microbial population (Figure B-25) or themaximum hydrocarbon utilization factor (Figure B-27) inhibit biological activity to point where the
calibrated plume (Figure B-26) expands. MK. (1999b) concluded that the source periphery area'stotal microbial population, and biological tests for PCP and naphthalene degraders, did not supportbiodegradation as being a dominant mechanism. No direct evidence of biodegradation was found,though indirect evidence led to the conclusion that some activity could not be ruled out. Thesensitivity analysis supports the conclusion that the calibrated biodegradation, though small, issufficient to stabilize the plume, while even very conservative parameters could do the same, giventhe existing conditions at the site.
Figure B-28 shows the PCP plume when an aggressive hydrocarbon utilization factor is used. Theplume is stabilized in an area mirroring the core area (constant concentration) of the plume. Thissuggests that all contamination emanating from the residual source area, where contaminant releaseis rate-limited, is totally degraded before it can migrate.
The foregoing interpretations lead to the following conclusion. Model output is insensitive to thebiodegradation rates lower than the calibrated rate, and sensitive to rates greater than the calibratedmodel.
7-10 (Rev. a, March 1999)
7.8 Simulation Time
Because the calibration reproduces a contaminant configuration at a fixed time, it is important tounderstand whether the source, at an assumed age of 50 years, is really just beginning to cause largemigration yet to be seen. Table 7-8 indicates the model output times examined for this sensitivityanalysis. Unlike other parameters which change the model behavior, this sensitivity analysisconsiders results all from the same model run. Appendix B.8 contains time series plots ofPCP andnaphthalene plume distributions for the calibrated model up to 50 years, and for steady state.
Figures B-29 through B-34 show that for any transport time after 30 years (i.e., any source releaseto the groundwater before 1968; Table 7-8), the plume configuration is stable. The steady statesimulation (Figure B-34) shows an occupied area of the aquifer no greater than that predicted for 50years. Figures B-35 through B-38 show similar time series for naphthalene, with similar results.Therefore, model output is insensitive to the release date of the source if more than 30 years ago, andby corollary, the current plume configuration should not change any further with time.
F:\Kaenic\TBRC\TO)B\CBlibruionRepon\cdibTpt.wpd 7-11 (Rev. a, March ] 999)
Table 7-8 Sensitivity Model RunsCalibrated Model for Different Run Times
Model Run ID
PCPC10FH
PCPC20FH
PCPC30FH
PCPC40FH
PCPC50FH
P C P S S H
NAPC10FH
NAPC30FH
NAPC50FH
N A P S S H
PCPC50FO
NAPC50FO
Plot Number(Appendix B)
B-29
B-30
B-31
B-32
B-33
B-34
B-35
B-36
B-37
B-38
B-39
B-40
Description
Calibrated model forPCP
Calibrated model forNaphthalene
Calibrated Model forDissolved Oxygen
Calibrated Model forDissolved Oxygen
Output PresentationOption
t = 10 years; effectiveyear of release 1988
t = 20 years; effectiveyear of release 1978
t = 30 years; effectiveyear of release 1968
t = 40 years; effectiveyear of release 1958
t = 50 years (basecase) effective year
of release 1948
Calibrated Model atsteady state
t= 10 years
t = 30 years
t = 50 years (basecase)
Calibrated Model atsteady state
t = 50 years (basecase), PCP
t = 50 years (basecase). Naphthalene
7-12 (Rev. a, March 1999)
05m§0CO
8.0 Summary and Conclusion
8.1 SummaryCalibration of the BIOPLUME III model in this study was to demonstrate that the model is capableof predicting the field-measured distributions of heads and concentrations at the Popile site. Theconceptual model developed in the Ground Water Data Collection Report provided the necessaryframework to establish and run the model. The input parameters were derived from fieldinvestigations summarized in MK (1999a), and from the literature.
This model study was based on the conceptual model and observed contaminant plume patterns, inwhich a two-dimensional plan view model was developed to simulate the flow, transport, andbiodegradation of PCP, and Naphthalene within the Cockfield sand aquifer. The simulation isvertically bounded by the water table or an upper confining layer on the top, and the top of thecarbonaceous layer on the bottom. The flow domain includes upstream and downstream limits ofthe Bayou that could be affected by site ground water. Due to the lack of long-term historical groundwater level measurements, the flow model was run in steady state to match the piezometric headsin September, 1998. However, the contaminant transport simulations were run in transient modeassuming that source terms have been present for 50 years and constant as to size and their releasemechanism to the ground water.
Once the model was calibrated, sensitivity analysis was performed to determine which parameters
are sensitive to the calibration and might require further investigation. Eight parameters were varied,one at a time with all other calibrated model conditions held constant, to determine their effect onthe model results.
8.2 Conclusions
Simulations of flow and transport physical processes at the site, using the BIOPLUME III modelwith both field measured and literature-derived input parameters, have shown conclusively that thecurrent site conditions can be matched to a satisfactory level. These conditions include flow, thebiogeochemical environments, dissolved oxygen distribution, and dissolved concentrations of PCPand Naphthalene, two of the most mobile contaminants at the site. Further, these field-measuredvalues of head distribution and contaminant plume migration were predicted with a set of parametersadopted from the Ground Water Data Collection Report with minimal modification. The conclusionof this study is that the calibrated BIOPLUME III model is a good representation the processes thathave occurred at the site, and therefore can be used to predict the future fate and transport of PCPand Naphthalene at the Popile site.
F:\KoCTigWEROTO18\CalibratiiwRepori\<alibipt.wpJ 8-1 (Rev. a, March 1999)
The main parameters found to affect the calibration included the hydraulic conductivity distribution,
the types of residual sources of contaminants to the dissolved phase, and mass flux of contaminantsbeing released to the ground water. Important findings from the calibration are:
• The best match of aquifer heads came from hydraulic conductivity values distributed asactually measured, then kriged, contoured, and redistributed to the nodes in an unbiasedmanner. The actual hydraulic conductivity distribution though itself very uniform, improvedthe head match over all uniform distributions tested. The average hydraulic conductivity wason the order of 1 x 10"3 cm/sec.
• The concept of a dual source was validated. In the core of the plume, dissolved PCP andNaphthalene concentrations are at their fractional solubility limits. Within a secondary sourcearea which is more widespread, the flux of contaminants to the aquifer is limited by diffusionthrough the saturated zone in the aquitard.
• The calibrated secondary contaminant source, which cannot be directly measured, was foundto be important in calibration. The calibrated mass flux for PCP and Naphthalene whichreproduced the range of dissolved concentrations observed in the Process pond area and asecondary source area to the north, were 2.12 ug/ff/day and 4.25 ug/ff/day, repspectively.Pick's law contaminant fluxes for PCP and Naphthalene were calculated to be 2.03 ug/tf/dayand 5.44 ug/ff/day, close to those calibrated values and suggesting a credible representationof the secondary source term.
• Biodegradation is occurring.
The results of the sensitivity analysis are:
• Aquifer thickness: The site flow pattern and contaminant distribution were insensitive to thethickness of the aquifer in context of all other conditions.
• Hydraulic conductivity / effective porosity: The hydraulic conductivity distribution wassubjected to sensitivity analysis because of its implied effect on diffusion and biodegradation,both of which are modeled as kinetic processes. The slower the flow, the more dominant these
processes become because water is resident at a given locale longer for these processes tooperate. The calibration process demonstrated that, within a given order of magnitude ofhydraulic conductivity, the pattern of hydraulic conductivity does not greatly affect the
F:\Koenig\TERCTOI»Calibrati™Rq»n\calibrpt.wp(l 8-2 (Rev. a, March 1999)
piezometric surface. The model proved sensitive to hydraulic conductivity's effect on the
contaminant distribution. A lower effective porosity barely affected the PCP distribution.
• Secondary contaminant source flux: Sensitivity of the contaminant plumes' concentration andextent in response to the magnitude of the source flux was performed to investigate how muchsorptive capacity was used and still remains relative to the mass released in the 50 yearcalibration period. The analysis showed progressively increased areas of the aquifer occupiedby PCP contamination over a 100-fold increase in the flux factor, ranging from one tenththrough ten times the calibrated flux. The PCP distribution is sensitive to the magnitude of thesource flux. However, attenuation processes are capable of containing contamination to a verysmall area outside of the former process/ removal action excavation area. A large amount ofsorption capacity exists even if the calibrated flux for the model was greatly increased.
• Effect of each attenuation parameter: This sensitivity analysis examined which mechanismsare most important in limiting contamiant movement at the site. With dispersion as the onlyfate and transport mechanisms, PCP contamination was predicted to have reached the Bayouat low microgram per liter levels. This unrealistic condition showed that the importance ofdispersion is overshadowed by other attenuation mechanisms in the presence of sorption andbiodegradation. Sorption alone is not able to contain contaminant plumes within the sourcearea within the 50-year simulation period. Biodegradation appears to take effect atcontamination levels less than 100 ug/L and is the key mechanism in stabilizing the plumemigration.
• Dispersion: Dispersion is sensitive in the absence of sorption and biodegradation. However,dispersion becomes insignificant as the quantitative effects of sorption and biodegradationovercome the speading effect by dispersion.
• Retardation factor: Sensitivity of the PCP contaminant plume's concentration and extent in
response to sorption was performed because sorption is an important mechanism inimmobilizing large quantities of contaminant mass. The sensitivity analysis showedessentially the same areas of the aquifer are occupied by PCP contamination over a 50-foldincrease in the sorption, ranging from one tenth to five times the retardation factor, indicatingthat the sorption capacity of the aquifer material within the source area has been fully utilized50 years after the contaminant released
• Biodegradation rate: Sensitivity analysis showed that neither a ten-fold reduction in themicrobial population or the maximum hydrocarbon utilization factor inhibited biological
F:\K<iCTig\TERC\T018\C«librationReport\c«libipt.i«pd 8-3 (Rev. a, March 1999)
activity to point where the calibrated plume expanded. MK (1999b) had concluded that thesource periphery area's total microbial population, and biological tests for PCP andnaphthalene degraders, did not support biodegradation as being a dominant mechanism. No
direct evidence of biodegradation was found, mough indirect evidence led to the conclusionthat some activity could not be ruled out. The sensitivity analysis supports the conclusion thatthe calibrated biodegradation, though small, is sufficient to stabilize the plume, while evenvery conservative parameters could do the same, given the existing conditions at the site.
Simulation time: Sensitivity analysis showed that for any transport time greater than 30 years(i.e., any source release to the groundwater before approximately 1968), the plumeconfiguration is stable. Therefore, model output is insensitive to the release date of the sourceif more than 30 years ago, and by corollary, the current plume configuration should not changemuch more with time.
F:\KoCTig\TBROT018\C«libi*tioiiIlepon\calibrpt.wpd 8-4 (Rev. a, March 1999)
CO
0
(0
9.0 References
Borden, R.C., and P.B. Bedient, 1986. "Transport of Dissolved Hydrocarbons Influenced by
Oxygen-Limited Biodegradation, 1. Theoretical Development", Water Resources Research,
22(13)1973-1982.
Brakensiek, D.L., W.J. Rawls, and G.R. Stephenson, 1984. "Modifying SCS Hydrologic SoilGroups and Curve Numbers for Rangeland Soils", American Society of AgriculturalEngineers, Paper No. PNR-84-203.
Golden Software, Inc., 1997. "Surfer" Contour Package for Windows, version 6.04, Golden,Colorado. February.
Gelhar, L.W., C. Welty, and K.R. Rehfeldt, 1992. "A Critical Review of Data on Field-ScaleDispersion inAquifers", Water Resources Research, 28(7):1955-1974.
Lee, L.S., P.S.C. Rao, and I. Okuda, 1992. "Equilibrium Partioning ofPolycyclic Hydrocarbonsfrom Coal Tar into Water", Environmental Science & and Technology, 26(11):2110-2115.
Morrison Knudsen Corp (MK), 1998. "Quality Assurance Project Plan for Ground WaterInvestigation, Modeling and Remedial Design", Final, Prepared for USACE, June.
MK, 1999a. "Ground Water Data Collection Report, Popile, Inc. Superfund Site", Final, Preparedfor USACE, February.
MK, 1999b. "Ground Water Modeling Work Plan, Popile, Inc. Superfund Site", Final, Prepared forUSACE, February.
Munoz, J.F., and M.J. Irarrazaval, 1998. "A Numerical Model for Simulation ofBioremediation ofHydrocarbons in Aquifers", Ground Water, 36(2)215-224.
Stroo, H., C. Cosentini, T. Ronniny, and M. Larsen, 1997. "Natural Biodegradation of Wood
Preservatives", CCC 1051-5658/97/070477-18, John Wiley & Sons, Inc.
F:\Koaiig\TERC\TO18\C«)ibnttioniltponMalibrpt.wpil 9-1 . (Rev. a, March 1999)
A
Appendix A
Raoult's Law Calculation
APPENDIX AEQUILIBRIUM SOLUBILITY
Within the source of contamination, the primary process controlling the release of organiccompounds to the aquifer is the contaminants' aqueous solubility. The aqueous solubility of anorganic compound in a mixture of multiple compounds is dependent of the thermodynamicequilibrium of the water-NAPL phase partitioning. Predictive methods for estimatingequilibrium solubilities are founded on the Raoult's law assumption of ideality in the NAPLphase. It is stated that the concentration of a compound in the aqueous phase is proportional tothe mole fraction of the compound in the mixture:
c,=x.s,
where:C, = the mass concentration of solute i in the aqueous phase;X, = the mole fraction of solute i in the NAPL phase; andS; = the aqueous solubility of the pure liquid solute i.
S, is known to be 20,000 ag/L for PCP and 31,700 ug/L for Naphthalene. The mole fractions ofPCP and Naphthalene were determined using free product compositions from MW-18 which isthe only sample location at the source center. Organic compounds identified in the NAPL fromMW-18 include PAHs and phenols listed in the following calculation.
RAOULT'S LAW:
,,,where Ci is the mass concentration of solute i in the water phase, Xi is the molefraction of solute i in the water phase, and S| is the solubility of the component liquid.
Acenaphthene
Acenaphthylene
Anthracene
Benzo(a) anthracene
Benzo(a) pyrene
Benzo(b) flouranthene
Benzo(k) flouranthene
Benzo( g, h, i) peiylene
Chrysene
Dibenz(a,h) anthracene
Fluoranthene
Fluorene
Ideno (1,2,3 - cd) pyrene
Naphthalene
Phenanthrene
Pyrene
2,4 - Dimethylphenol
2 - Metfaylphenol
4 - Methylphenol
Pentachlorophenol
Phenol
2,3,4 ,6- Tetrachloro
CONC ;=
97000
27000
20000
17000
81000
86000
83000
23000
17000
16000
120000
87000
26000
200000
240000
70000
35000
21000
58000
250000
35000
15000
PAHMW:=
154.21
152.20
178.23
228.29
252.32
252.32
252.32
276.34
228.29
278.33
202.26
166.21
276.34
128.16
178.22
202.26
122.16
108.15
108.13
266.34
94.11
231.89
SOL;=
3.9
16.1
.0434
.0094
.0016
.0012
.00076
.00026
.00189
.000599
0.26
2.0
.062
31.7
1.3
0.135
0
25920
24000
20
82800
0
mg
liter
— f*{~V^f{~*
ICONC = 1.624-10 PAH%;=-———•100 IPAH% = 100ICONC
molesPAHperlOOgm := PAH%-100-gm-1-mol
PAHMW-gm/ratiomolesPAH ;=
molesPAHperlOOgm\nun(molesPAHperl OOgm) i
sumrat := ZratiomolesPAH
sumrat = 157.526 X:=ratiomolesPAH
sumratZX = 1 C := (X-SOL)
3/8/99 RAOL.TLAW3.mcd
ratiomolesPAH =
10.9'
3.1
2
1.3
5.6
5.9
5.7
1.4
1.3
1
10.3
9.1
1.6
27.1
23.4
6
5
3.4
9.3
16.3
6.5
. 1-!
X =
0.069'
0.02
0,012
0.008
0.035
0.038
0.036
0.009
0.008
0.006
0.066
0.058
0.01
0.172
0.149
0.038
0.032
0.021
0.059
0.104
0.041
.0.007
Aoenaphthene
Acenaphthylene
Anthracene
Benzo(a) anthracene
Benzo(a) pyrene
Benzo(b) flouranthene
Benzo(k) flouranthene
Benzo(g,h,i) perylene
Chrysene
Dibenz(a,h) anthracene
Fluoranthene
Fluorene
Ideno (1,2,3- cd) pyrene
Naphthalene
Phenanthrene
Pyrene
2,4- Dimethylphenol
2 - Methylphenol
4 - Methylphenol
Pentachlorophenol
Phenol
2,3,4,6-Tetrachloro
C=
0,2709014
0.3154005
0.0005378
0.0000773
0.0000567
0.0000452
0.0000276
0.0000024
0.0000155
0.0000038
0.0170346
0.1156058
0.0006442
5.462912
0.1933239
0.0051595
0
555.7957373
1421.6100195
2.0731038
3400.5569396
0
,mgliter
X,, = 0.17 C,, = 5.46 •mg ...Mote Fraction and Equilibrium Concentration of Naphthalene13 " liter
X,n = 0.1 C,o = 2.07 °ms• ...Mole Fraction and Equilibrium Concentration of Pentachlorophenol" " liter
3/8/99 RAOLTLAWS.mcd
B
Appendix B
Sensitivity Analysis Maps
Appendix B.I
Maps of Heads, PCP and Oxygen for Increased Aquifer Thickness
PCPC50FHPCPL+10HPCPL+100PCPL+10W
pcpc50fh
1.501.000H
1,500,500H
1,500,0001,106,000 1,106,500 1,107,000
B-l
pcpl. h
1,501,00(H
1,500,50(H
1,500,0001,106,000 1,106.500 1,107,000
B-2
pep I__o
1.501.000H
1,500,0001,106,000 1,106,500 1,107,000
B-3
pcpl w
1,501,000^
1,500,500-^
1,500,000-
B-4
1,106,000
Appendix B.2
PCP Distribution for Varying Magnitude of Hydraulic Conductivity
PCPKMINHPCPKMN_HPCPC50FH
PCPKMAXHPCPEP25H
pcpkminh
1,501,000-^
1,500,500^
1,500,0001,106,000 1,106,500 1,107,000
B-5
pcpkmnJi
B-6
pcpcSOfh
1,501,000-^
1,500,500^
1,500,000'1,106,000 1,106,500 1,107,000
B-7
pcpkmaxh
B-8
pcpep25h
B-9
Appendix B.3
PCP Distribution for Varying Secondary Contaminant Source Flux
PCPFXO_HPPFX10%HPCPC50FHPPFX10XHPCPFXCCH
pcpfx0_h
B-10
ppfx10%h
B-ll
pcpcSOfh
1.501,000-^
1.500.50CH
1,500,0001,106,000 1,106,500 1,107,000
B-12
ppfx10xh
1,500,500-^
1,500,0001,106,000 1,106,500 1,107,000
B-13
pcpfxcch
1,501,OOOH
1,500,50CH
1,500,0001,106
B-14
Appendix B.4
PCP Distribution for Combinations of Dispersion,Sorption, and Biodegradation
PCPD__HPCPS__HPCPDS_HPCPC50FH
pcpd__h
1,501,00(H
1,500,500-^
1,500,000
B-15
1,106,000 1,106,500 1,107,000
peps__h
B-16
pcpds_h
B-17
pcpc50fh
1,500,0001,106,000 1,106,500 1,107.000
B-18
Appendix B.5
PCP Distribution for Varying Dispersion Factors
PPS-90%HPCPC50FH
PCPD&50%H
ppd-50%h
1,501,OOCH
1,500,500-^
1,500,0001,106.000 1,106,500 1,107,000
B-19
pcpc50fh
B-20
ppd&50%h
B21
Appendix B.6
PCP Plume Maps for Varying Retardation Factors
PCPS-90%HPCPC50FHPCPS&5XH
pps-90%h
1,501,000-^
1,500,500H
1,500,0001,106,000 1,106,500 1,107,000
B-22
pcpc50fh
B-23
pcps&5xh
1,501,000d
1,500,000
B-24
Appendix B.7
PCP Plume Maps for Varying Biodegradation Factors Rates
PPMT10%HPCPC50FHPPU-10XHPPU&10XH
ppmt10%h
1,501,000^
1,500.500-i
1,500,000
B-25
pcpcSOfh
1,501,000-^
1,500,500^
1,500,0001,106,000 1,106,500 1,107,000
B-26
ppu-1 Oxh
1,501,000-1
1,500,500-!
1,500,000
B-27
ppu&IOxh
1,501,000^
1.500.50CH
1,500,0001,106,000 1.106,500 1,107,000
B-28
Appendix B.8
Time Series Plots ofPCP and NaphthaleneDistribution - Calibrated Model
Pentachlorophenol (PCP)PCPC10FHPCPC20FHPCPC30FHPCPC40FHPCPC50FHPCPSS_H
NaphthaleneNAPC10FHNAPC30FHNAPC50FHNAPSS_H
Dissolved OxygenPCPC50FONAPC50FO
pcpd Ofh
B-29
pcpc20fh
1,501,000-^
1,500,50CH
1.500.00&1,106,000 1,106,500 1,107,000
B-30
pcpc30fh
B-31
pcpc40fh
B-32
pcpc50fh
1,500,500^
1,500,0001,106,000 1,106,500 1,107,000
B-33
pcpss h
1,501,000-1
1,500,0001,106,000 1,106,500 1,107,000
B-34
napd Ofh
B-35
napc30fh
B-36
napc50fh
B-37
napss_h
B-38
pcpc50fo
1,501,000-^
1,500,50(H
1,500,0001,106,000 1,106,500 1,107,000
B-39
napc50fo
1.501.000H
1,500,50(H
1,500,0001,106,000 1,106,500 1,107,000
B-40
