task d - multi-process and multi-scale modeling and data ... · modeling tasks at multiple scales...

ERSD Annual PI MeetingLansdowne, Virginia

April 16-19, 2007

Oak Ridge Integrated Field-Scale Research Challenge

Task D -Multi-Process and Multi-ScaleModeling and Data Analysis

Task Leader: Jack Parker

OAK RIDGE FIELD RESEARCH CENTER

U C

Task Objectives

Gain an improved understanding of hydrologic, geochemical andbiological processes and their interactions at relevant time andspace scales

Develop practical, site-independent tools for evaluating effectsof natural and engineered processes on long-term performance

i.e. provide a comprehensive framework to interpretdata and make informed practical decisions

Eureka!


Important ModelProcesses

• Flow in fractured, dipping, heterogeneous rock/saprolite• Fluid flow due to density gradients• Advective-dispersive dissolved phase transport• Diffusive fracture-matrix mass transfer• Microbial population/biomass models• Colloid transport• Permeability changes associated with biogeochemical processes• Atmospheric coupling (recharge, oxygen exchange, plant uptake)• Equilibrium and kinetic geochemical reactions:

– Aqueous speciation, complexation, polymerization reactions– Oxidation-reduction reactions– Precipitation-dissolution reactions– Hydrolysis reactions– Adsorption-desorption reactions– Acid-base reactions– Cation-anion exchange reactions (pH dependent charge)– Microbially-mediated reactions and biomass growth

C


Modeling Tasks atMultiple Scales

• Lab-Scale Modeling Studies (ORNL, UT)– Batch experiment analysis– Packed and undisturbed column analysis– Develop and calibrate geochemical/microbial reaction models

• Site-Wide Modeling (ORNL, UT)– Plume-scale analysis of groundwater monitoring, soil sampling

and geophysical data in conjunction– Upscale parameters from lab and local field-scale studies– Assess plume-scale impacts of natural and engineered

factors on long-term performance

• Local Field-Scale Experiments (ORNL, UT, Stanford, Ga Tech)– Recharge manipulation experiments– pH manipulation experiments– Org-P and Ca-oleate injection experiments– Validate models and calibrate parameters under field conditions– Test upscaling of lab model results


Modeling Approach

HydroGeoChem (HGC) v.5 will serve as the primary modeling tool

Capabilities: Three-dimensional domain with any spatial structure Transient sat/unsat flow in heterogeneous, fully anisotropic media Multispecies aqueous phase transport and coupled flow and

transport including density-dependent flow Adaptable to model reaction-flow coupling

(e.g., pore clogging) Generic biogeochemical reaction network

capability (equilibrium and kinetic) Diffusion-limited mass transfer kinetics Coupled with nonlinear inversion code

PEST to perform parameter estimation Readily applicable to any DOE site

A geochemical reaction network for aqueous and surface U reactions has beenimplemented in HGC and experimentally validated


Model Implementation

HydroGeoChem has been used to analyze lab data and field experiments from theOak Ridge site

and to implement a site-wide model for the FRC site

0

10

20

30

40

50

60

70

80

90

100

4 4.5 5 5.5 6 6.5 7 7.5 8 8.5

pH

% U

so

rbed Data

Simulation

Batch U-Sorption Experiment

0.0

0.2

0.4

0.6

0.8

1.0

1.2

0 200 400 600 800 1000 1200 1400

Pore Volume

C/C

o

Data

Simulation

Lab Column Experiment

Model domain ~160 acres

Groundwater calibration

Simulated plume withdensity-dependent flow

Observed plume


Microbial ReactionModel Integration

Microbial reactions are generally formulated using Monod kinetic models thatinvolve a number of growth, utilization and inhibition coefficients

Will incorporate a microbial reaction model developed by Stanford into HGC

Statistical models will be developed to predict microbial community structure andfunctional parameters from geochemical and other data using

- Discriminant function analysis- Multiple linear regression- Feedforward neural networks

OAK RIDGE FIELD RESEARCH CENTER Modeling pH Effects

Implement Soil Buffer / pH Dependent Surface Charge Model

2 3 4

4 3 22 3 4H X H X H H X H HX H X H

! + ! + ! + ! ++ + + +� � � �

Employ Spalding’s (2001) soil polyprotic acid model

plus Al/Fe hydrolysis, Ca/Mg/Mn carbonate/hydroxide rx, ion exchange rx, etc.

Calibrate pKa values and exchange selectivity coefficients to pH vs CEC characterizationdata and batch soil titration experiments (c/o: Baohua Gu, Dave Watson)

Soil titration curve

A

3

4

5

6

7

8

9

10

11

0 5 10 15 20 25

NaOH added (mmol/L)

pH

observed

simulated

Preliminary Results: Model versus DataFWB103 Area 3

200

400

600

800

1000

1200

1400

0 100 200 300 400

CEC (cmol/kg)

De

pth

(cm

)

pH

observed

FWB104 Area 3

200

400

600

800

1000

1200

1400

1600

1800

0 100 200 300 400

CEC (cmol/kg)

De

pth

(cm

)

pH

observed

Cation exchange capacity versus depth due to pH variations

OAK RIDGE FIELD RESEARCH CENTER Modeling pH Effects…

Observed and model-predicted aqueous phasemetal concentrations versus base added

A-(a)

0.0

0.5

1.0

1.5

2.0

2.5

0 5 10 15 20 25

NaOH added (mmol/L)

Conce

ntr

atio

n (

mM

)

Mg observedCa observedAl observedMg simulatedCa simulatedAl simulated

Mg Ca

Al

A-(d)

0.0000

0.0005

0.0010

0.0015

0.0020

0.0025

0.0030

0 5 10 15 20 25

NaOH added (mmol/L)

Conce

ntr

atio

n (

mM

)

Sr observed

Co observed

Sr simulated

Co simulated

Co

Sr

A-(c)

0.000

0.004

0.008

0.012

0.016

0.020

0 5 10 15 20 25

NaOH added (mmol/L)

Conce

ntr

atio

n (

mM

)

Fe observedU observedNi observedFe simulatedU simulatedNi simulated

Fe

Ni

A-(b)

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0 5 10 15 20 25

NaOH added (mmol/L)

Conce

ntr

atio

n (

mM

)

Mn observed

Si observed

Mn simulated

Si simulated

Si

Mn

Results clearly demonstrate the critical importance of pH to geochemistry.Favorable initial modeling results validate the proposed modeling framework, which will

be comprehensively tested by planned field pH manipulation experiments


Bench scale

Multi-scale modeling

Watershed

Field Plots

Molecular

DevelopmentCalibrationVerification

Ultimate goal:RemediationStewardshipManagement

Model validation

Experimentaldesign

DevelopmentCalibrationVerification

Experimentaldesign

DevelopmentVerification

Experimentaldesign

Integration of modeling and multi-scale experiments maximizesresearch benefits and utility

OAK RIDGE FIELD RESEARCH CENTER FY07-FY08 Plan

Planned Modeling Efforts:

• Calibrate and test soil titration model for different materials at the site(i.e., gravel fill zone)

• Incorporate in site-wide model and evaluate U transport predictions fromhistorical S-3 Pond disposal ops

• Extend reaction network to incorporate Al polymer species and determinerelevant equilibrium and kinetic parameters

• Perform simulations for planning and analysis of field pH manipulationexperiments (local-scale models)

• Implement refinements in site-wide model based on initial geophysicaltesting results

• Implement microbial kinetics in model and perform initial sensitivity analyses

task d - multi-process and multi-scale modeling and data ... · modeling tasks at multiple scales...

Documents