SPECIAL REPORT 96-11

Evaluating the SESOIL Model for

Benzene Leaching Assessment

in Alaska

Gurdarshan S. Brar May1996
Abstract

SESOIL is a seasonal soil compartment model. A one-dimensional vertical

transport model is designed to predict seasonal solute distribution in the soil

profile and watershed. CRREL received a request from the U.S. Army Engineer

District, Alaska, Environmental Technical Engineering Office, to provide technical assistance in evaluating the SESOIL model for helping to assess benzene leaching in the Alaskan environment. The major tasks outlined in the

request were as follows: work an example problem for a diesel-contaminated

site, do analytical checks and do manual SESOIL analytical calculations for

one cycle. The SESOIL model requires 57 input variables supplied by the

user. An addi-tional 8 parameters are required for the execution file. This

study did sensitivity analyses on soil bulk density, intrinsic permeability, disconnectedness index, porosity, organic carbon, adsorption coefficient on organic carbon, and bio-degradation rates of solid and liquid phases. The

model is very sensitive to all the parameters studied. Despite its several difficulties, the model is popular among regulators and users because of its simplicity compared to research models. It can be used as a screening-level tool

in assessing chemical move-ment in the soil column with considerable sitespecific calibrations.

For conversion of SI units to non-SI units of measurement consult Standard

Practice for Use of the International System of Units (SI), ASTM Standard E380-

93, published by the American Society for Testing and Materials, 1916 Race St.,

Philadelphia, Pa. 19103.

This report is printed on paper that contains a minimum of 50% recycled

material.
Special Report 96-11

Evaluating the SESOIL Model for

Benzene Leaching Assessment

in Alaska

Gurdarshan S. Brar May1996

Approved for public release; distribution is unlimited.

US Army Corps


of Engineers

Cold Regions Research &


Engineering Laboratory
PREFACE

This report was prepared by Dr. Gurdarshan S. Brar, Research Physical Scientist,

Geological Sciences Division, Research and Engineering Directorate, U.S. Army Cold

Regions Research and Engineering Laboratory.

The funding for this project was provided by the U.S. Army 6th Infantry Division

(Light), Directorate of Public Works. The author acknowledges the technical review performed by Frank Poff, U.S. Army Engineer District, Alaska, and Dr. Mansur Zakikhani,

Research Civil Engineer, U.S. Army Waterways Experiment Station.

The contents of this report are not to be used for advertising or promotional purposes. Citation of brand names does not constitute an official endorsement or approval

of the use of such commercial products.

ii
Evaluating the SESOIL Model for

Benzene Leaching Assessment in Alaska

GURDARSHAN S. BRAR

INTRODUCTION

The United States Army Engineer District, Alaska, Environmental Technical Engineering Office,

asked CRREL for technical assistance in evaluating

the SESOIL model for aiding in assessing benzene

pollutant leaching in Alaska. The major tasks outlined in the request were 1) to work an example

problem for a diesel-contaminated site, 2) do analytical checks and 3) make manual SESOIL analytical calculations for one cycle.

Drewett et al. (1993) used the SESOIL model at

Fort Greely to assess the presence and concentrations of petroleum hydrocarbons in the soil and

groundwater at five sites. In this study, a SESOIL

sensitivity analysis was made for benzene contamination in Building 110 at Fort Greely by using

input data files of Drewett et al. (1993).

SESOIL history

SESOIL stands for seasonal soil compartment

model. It is a one-dimensional vertical transport

model for the unsaturated soil zones and is designed to predict solute distribution in the soil

profile and watershed seasonally. In 1981, Arthur

D. Little, Inc. (ADL) developed the program for the

Environmental Protection Agency’s (EPA) Office

of Water and Office of Toxic Substances (OTS). The

original code included three soil columns. In 1984,

ADL updated the model and included a fourth soil

layer as well as soil erosion algorithms (Bonazountas and Wagner 1984). In 1985, the EPA’s Environmental Research Laboratory in Athens, Georgia,

thoroughly evaluated SESOIL (Watson and Brown

1985), found numerous deficiencies in the model

and recommended improvements. Furthermore,

the model was extensively tested at the Oak Ridge

National Laboratory (ORNL) and modified to enhance its capabilities (Hetrick et al. 1986, 1989;

Hetrick and Travis 1988). SESOIL was incorporated into a system called PCGEMS (Graphical

Exposure Modeling System for the PC), a complete information management tool developed

for EPA-OTS and designed to help users perform

exposure assessments (General Science Corporation 1987, 1989). General Science Corporation

(1990) further made improvements to PCGEMS

and incorporated it into a new system called

RISKPRO (Hetrick et al. 1993).

Objective

The objective of this report was to evaluate the

sensitivity of the SESOIL model for assessing benzene leaching in the Alaskan environment.

LITERATURE REVIEW

Donigian and Rao (1986a) comprehensively reviewed the model and concluded that the chemical transport part of the code needed improvements. The model did not handle the large

variations in the hydraulic properties of the soil

profile. Furthermore, they reported that SESOIL

overpredicted the mass of aldicarb movement to

groundwater (Donigian and Rao 1986b). Daugherty (1993) found that SESOIL does not simulate

the transfer of contaminants from the NAPL to

the aqueous phase, but assumes that all contaminants are dissolved.

Ladwig et al. (1993) tested the SESOIL model

for benzene, ethylbenzene, toluene, xylene and

1,2-dichloroethane under Wisconsin conditions

and discovered that the model was most sensitive

to soil type, biodegradation rate, residual concentration, residual layer thickness and organic carbon content of the soil. The model was least sensitive to climate, soil disconnectedness index, pH
and depth of contaminant burial. Furthermore,

the model was highly sensitive to intrinsic permeability for benzene in sand. However, it was

insensitive to intrinsic permeability for treatment

of benzene in till. The till was a finer grained environment, with fewer available pore spaces than

the sand.

Bonazountas and Kallidromitou (1993) reported that at the present state of scientific knowledge, SESOIL is a well-developed soil compartment model. They emphasized that the model

must be calibrated for site-specific variables such

as biodegradation rate, soil organic carbon content, local climate and depth to the water table.

Hetrick et al. (1993) recommended that predictions for the hydrology at a given site be calibrated to agree with known measurements. They

suggested that the user must conduct sensitivity

analyses or evaluate results obtained by assigning distributions to the input parameters (O’Neill

et al. 1982, Gardner 1984, Hetrick et al. 1991).

When properly used, SESOIL is an effective

screening-level tool for assessing chemical movement in soil.

Oregon State regulator Anderson (1992) tested

the SESOIL model to simulate transport of organic contaminants through the vadose zone. He also

used the MINTEQA1 model (USEPA 1987) to

simulate inorganic speciation and concentrations

under specified field conditions. Sensitivity analyses were performed on organic contaminants—

benzene, carbon tetrachloride, ethylbenzene,

methyl chloride, naphthalene, perchloroethylene,

toluene, 1,1,1-trichloroethane, 1,1,2-trichloroethylene and o-xylene. The results of the tests indicated that the most important parameters controlling organic contaminant transport in the

SESOIL/AT123D models were the thickness of

the contaminated zone, depth from the contaminated zone to groundwater, hydraulic conductivity and gradient, and the fraction of the organic

carbon in the soil.

Numerous studies have been conducted to

compare the sensitivity of the SESOIL model with

other models, using field input data (Bonazountas et al. 1982; Wagner et al. 1983; Hetrick 1984;

Kincaid et al. 1984; Watson and Brown 1985; Melancon et al. 1986; Hetrick et al. 1986, 1989; Hetrick

and Travis 1988). The model was used in risk

assessments to evaluate direct coal liquefaction

(Walsh et al. 1984), incineration of hazardous

waste (Holton et al. 1985, Travis et al. 1986), transport of benzene to the groundwater (Tucker et al.

1986), soil cleanup levels in California (Odencrantz et al. 1991, 1992) and site sensitivity ranking for Wisconsin soils (Ladwig et al. 1993).

Several computer models are in use to assess

the cleanup levels of hydrocarbon contaminated

soils. Recently, Odencrantz et al. (1992) reviewed

the following vadose zone transport models:

1. PRZM—Pesticide Root Zone Model

2. CMLS—Chemical Movement in Layered

Soils

3. GLEAMS—Groundwater Loading Effects of

Agricultural Management Systems

4. LEACHMP—Leaching Estimation And Chemistry Model-Pesticide

5. MOUSE—Method Of Underground Solute

Evaluation

6. PESTAN—Pesticide Analytical model

7. Jury’s analytical transport model

8. MOFAT—Multiphase Organic Flow And

Transport

9. SESOIL.

They recommended the SESOIL and MOFAT

models on the basis of the following vadose zone

transport criteria:

1. Needed is a one-dimensional vertical model

that can be discretized into at least three layers, with varying soil properties and chemical loading concentrations by layer.

2. The model must represent one mobile chemical component in three phases (adsorbed,

aqueous and gaseous).

3. The model must represent biodegradation,

volatilization and gaseous diffusion.

4. The model must represent the variable effects

of local climate (precipitation, temperature,

etc.).

MOFAT is a two-dimensional finite-element

modeling code that transports up to five components between four phases (air, water, oil and

soil) and also allows up to ten soil layers of different properties. MOFAT is more powerful but

harder to use than SESOIL; therefore, fewer users

have adopted it.

The Council for Health and Environmental

Safety of Soils’ (CHESS) Analysis and Environmental Fate Committee reviewed several existing

environmental fate models and recommended

the SESOIL and POSSM models for further consideration as tools to aid the risk assessment process (Calabrese and Kostecki 1992). POSSM,

which stands for PCB On-Site Spill Model, is a

contaminant transport model developed to predict environmental concentrations associated

with a chemical spill. It is a modified version of

the PRZM model and is considered as a one2
dimensional, compartmental, dynamic transport

and fate model. The model simulates daily

changes in chemical concentrations on a spill

site’s soil and vegetation, as well as losses of

chemicals attributable to volatilization, surface

runoff–soil erosion and leaching to groundwater.

Vertical And Lateral Organic Redistribution

(VALOR), a two-dimensional numerical model

for immiscible multiphase fluid flow in subsurface systems, was developed by Abriola et al.

(1992). VALOR solves only flow (pressure) equations for different phases of air, water and organic

liquids; however, MOFAT solves both flow and

mass transport (concentration) equations.

SESOIL EVALUATION

SESOIL processes

SESOIL simulates the major processes that can

affect pollutant transport in the unsaturated

zone, including moisture movement, volatilization and vapor phase diffusion, adsorption, and

chemical as well as biological degradation (Ladwig et al. 1993). The hydrological cycle component is based on the theory of Eagelson (1978) that

uses a statistical approach to water balance calculations for estimating one-dimensional soil-water

movement. Parameters considered in the hydrologic cycle are rainfall, surface runoff, infiltration,

soil-water content, evapotranspiration and

groundwater runoff. The sediment cycle relates

to sediment washload as a result of rainstorms

(i.e., soil erosion from surface runoff). To incorporate the effect of washload, the sediment module

uses a combined statistical and deterministic approach. The pollutant fate cycle includes convective transport, volatilization, adsorption–desorption, chemical degradation–decay, biological

transformation, hydrolysis, photolysis, oxidation

and complexation with metals. This module uses

a deterministic approach with analytical equations describing chemical and biological processes that affect contaminant transport. Details of

these cycles, along with the transport equations,

are given in the New SESOIL User’s Guide (Hatrick

et al. 1993).

SESOIL assumptions

The SESOIL model is based on three assumptions:

1. Pollutant concentrations in all phases and in

all compartments of the soil system are at

equilibrium at all times.

2. The law of mass conservation determines the

equilibrium concentration of chemical species over a series of monthly or yearly steps.

3. Pollutant transport takes place in the unsaturated soil zone.

SESOIL input parameters

SESOIL has options for annual or monthly simulations. The annual simulations need annual climatic data and monthly simulations require

monthly input data. The annual simulation option is not available in the new RISKPRO system;

therefore, it is not included in this report with the

exception of the hydrological cycle, which implements the annual algorithm. The monthly input

data are grouped into four types: climate data,

soil data, chemical data and initial chemical distribution in the soil. The user must supply 57 input variables to run the model (Ladwig et al.

1993): 12 monthly input values are required for 33

of the parameters. In the execution file, 8 additional parameters are required. The washload input file was not used at the Fort Greely site; therefore, a discussion of the sediment module is not

included. Details of input variables for the four

categories are as follows.

Climate data

1. Average monthly temperature.

2. Average monthly fraction of cloud cover.

3. Average monthly relative humidity.

4. Average monthly shortwave albedo.

5. Monthly precipitation depth.

6. Mean storm duration.

7. Number of storms.

8. Latitude.

9. Mean length of rain period.

10. Average daily evapotranspiration rate.

Soil data

1. Description of soil type.

2. Soil bulk density.

3. Intrinsic permeability.

4. Disconnectedness index.

5. Effective soil porosity.

6. Organic carbon content.

7. Freundlich exponent.

8. Cation exchange capacity.

Chemical data

1. Description of the compound.

2. Solubility in water.

3. Diffusion coefficient in air.

4. Henry’s Law constant.

5. Adsorption coefficient on organic carbon.

6. Overall adsorption coefficient.

7. Molecular weight of the compound.

3
8. Valence of the compound.

9. Neutral hydrolysis constant.

10. Base catalyzed hydrolysis constant.

11. Acid catalyzed hydrolysis constant.

12. Biodegradation rate in the liquid phase.

13. Biodegradation rate in the solid phase.

14. Stability constant of compound–ligand complex.

15. Number of moles of ligand per mole of compound complexed.

16. Molecular weight of ligand.

Application data

1. Number of soil layers.

2. Number of years of data included in the data

set.

3. Surface area of the compartment.

4. Depth of each layer.

5. pH of each layer.

6. Intrinsic permeability of each layer.

7. Layer ratios for biodegradation in the liquid

phase.

8. Layer ratios for biodegradation in the solid

phase.

9. Layer ratios for organic carbon content.

10. Layer ratios for cation exchange capacity.

11. Layer ratios for the Freundlich exponent.

12. Layer ratios for adsorption coefficient.

13. Monthly pollutant load (mass/unit area)

entering each zone.

14. Monthly mass of pollutant transformed in

each sublayer by some other process.

15. Monthly mass of pollutant removed from

each sublayer by some other process

16. Monthly ligand mass input to each sublayer.

17. Index of volatilization–diffusion occurrence

from each layer.

18. Index of subsurface pollutant runoff.

RISKPRO contains a file management system that

simplifies data input for SESOIL. Default climatic

data for a particular state can be purchased and accessed through the RISKPRO package.

SESOIL’s merits

Being a part of PCGEMS and now RISKPRO, SESOIL is popular among regulators for risk assessment studies. The compartmental module lets

many users run the model for specific data sets or

site conditions. The model had continuous support from EPA-OTS. Periodically, SESOIL is improved and modified by the Oak Ridge National

Laboratory.

The scientific community engaged in chemical

fate modeling has accepted and recognized the

SESOIL model. Extensive validations that work

under different site specific scenarios must be

done to calibrate the model. The model is structured to simulate chemical transport for more than

a month. SESOIL accommodates physical, chemical and biological changes in the contaminant

leaked into the soil system.

The sensitivity analyses were conducted on adsorption and volatilization for different soil types

and in different climates. SESOIL’s hydrologic cycle has been found to be a good long-term predictor for groundwater and surface runoff, evapotranspiration and infiltration. Uncertainty analysis

is introduced into the hydrological cycle with

probability density functions, which produces

probability distributions of water balance and

yields long-term seasonal averages of the water

balance.

SESOIL’s demerits

Application of the SESOIL model in the Alaskan

environment requires extensive calibration and

modifications because it does not function at temperatures below freezing (Calabrese and Kostecki

1992). The present code for SESOIL uses a single

homogeneous soil column for the hydrological cycle. In the Alaskan environment, because soils usually have discontinuous and fractured permafrost

underneath, the model will need modifications.

SESOIL will not work at sites having large vertical

variations in soil properties.

The use of SESOIL is limited because it requires

site-specific data for calibration. When input data

are not available, the model user must use complex calculations to generate an input file. The user

needs the expertise to select the appropriate equations required for developing input data. In a situation where site-specific data are not available, using data published in the literature or default

values might simulate results that are inaccurate

by orders of magnitude.

The model does not address the free product

movement in the vadose zone, such as depth of

penetration of bulk hydrocarbons, spread and migration rate of free product, effects of large concentrations of other organics on adsorption and

mobility, and emission rate for a pure bulk hydrocarbon on a soil surface. Furthermore, the model

accommodates the migration of a single solute in

an aqueous phase rather than a nonaqueous

phase. The model’s inability to distinguish between the NAPL phase or the water phase (dominant transport carrier) can create significant errors

in simulations.

4
Simulations with SESOIL are very poor when

run with laboratory-generated input data. For instance, with laboratory input data, the model

simulated that 65.5% of the chemical released migrated to the groundwater; conversely, field data

showed only 4 to 8% of the chemical migrating to

the groundwater (Calabrese and Kostecki 1992).

Since these studies were conducted, the model

has been improved and tested in laboratory columns with six organic compounds, and results

were compared with three field studies. The

modified model delivered better simulation results for some compounds, but there was no improvement for compounds with the lowest and

highest adsorption coefficients.

The current version of the SESOIL model can

simulate vadose zone contaminant concentration

in four soil columns, with each column divided

into ten sub-layers. SESOIL’s hydrological cycle

considers the soil column as one homogeneous

compartment. Therefore, only one set of soilwater content, porosity and core-disconnectedness parameters is used to describe the entire

vadose zone. The model will not work if the soil

has low permeability. SESOIL does not address

the soil-water spatial variability and water flow

in each compartment. Therefore, chemical transport and distribution in the soil column could be

affected because the retardation coefficients and

volatilization fluxes of certain chemicals are

water-sensitive.

The model considers the internal soil moisture

at the beginning of each storm and in the interstorm periods to be uniform, at its long-term

space–time average. This assumption may be a

considerable departure from reality, as the soil

moisture profile in a later modeling period (i.e.,

1 month) cannot be influenced by the soil moisture profile resulting from a preceding modeling

period. Furthermore, the effects of snow and ice

melt on hydrological and sediment washload cycles under Alaskan conditions need to studied.

Validity of the sediment cycle has not been as

thoroughly tested as other cycles have. This cycle

ignores the chemical transport while simulating

sediment transport. The major limitation of the layered approach is that when a chemical enters a soil

layer, SESOIL considers it to be uniformly distributed throughout the layer. For instance, the model

simulates low chemical concentration for large soil

layers and high concentration for small soil layers.

Hetrick et al. (1989) reported that modified

SESOIL predictions are in good agreement with observed laboratory and field data. However, the

model underestimates the concentration near the

soil surface and they speculated that this may be a

result of SESOIL ignoring the upward movement of

the chemical with the upward movement of water

ascribable to soil evaporation losses. The model ignores the diffusive mobility of chemicals, which

may be important, depending on the Henry’s Law

constant of the compound, and does not consider

the volatilization enhancement when water evaporates. SESOIL should not be applied to a specific

site with only limited calibrations (Hetrick et al.

1989).

SENSITIVITY ANALYSIS

The preliminary sensitivity analysis of SESOIL

for benzene was done by varying the few soil and

chemical input parameter values (Table 1) to below

or above the original values used by Drewett et al.

(1993). The input data file (SSOUT034.OUT) developed by Drewett et al. (1993) in their SESOIL tests

for Fort Greely, Alaska, was used in the sensitivity

5

Table 1. Summary of sensitivity analysis in the form of time to

predict peak and maximum leachate concentration.

Change in peak

Test* Changed Conc. Time

Parameter value value (μg/mL) (years)

Soil density (g/cm3) 1.92 1.62 +0.12 –5

Intrinsic permeability (cm2) 1×10–7 1×10–4 +1.84 –14

Disconnectedness index (unitless) 10 6.3 –0.01 +4

Porosity (fraction) 0.25 0.35 –0.04 +12

Organic carbon content (%) 0.13 0.09 +0.056 –10

Adsorption coefficient on 83 69 –0.013 –5

organic carbon (koc)

Biodegradation rate in solid 5.48×10–4 2.74×10–4 +1.30 +2

phase (mg/kg per day)

Biodegradation rate in liquid 5.48×10–4 2.74×10–4 +0.28 +1

phase (mg/kg per day)

* Drewett et al. (1993)
6

Dissolved (μg/mL)

Adsorbed (μg/g)

Air-in-pores (μg/cm3

)

2.5

2.0

1.5

1.0

0.5

Benzene Concentration

0 20 40 60 80 100

Time (yrs)

c. Higher intrinsic permeability input parameter

(1 ×10–4 compared to 1 ×10–7 cm2).

Dissolved (μg/mL)

Adsorbed (μg/g)

Air-in-pores (μg/cm3)

0.05

0.04

0.03

0.02

0.01

0 20 40 60 80 100

Time (yrs)

Benzene Concentration

Dissolved (μg/mL)

Adsorbed (μg/g)

Air-in-pores (μg/cm3

)

0.25

0.20

0.15

0.10

0.05

0 20 40 60 80 100

Time (yrs)

Benzene Concentration

b. Lower soil bulk density input parameter (1.62 compared to 1.92 g/cm3).

Dissolved (μg/mL)

Adsorbed (μg/g)

Air-in-pores (μg/cm3

)

0.05

0.04

0.03

0.02

0.01

0 20 40 60 80 100

Time (yrs)

Benzene Concentration

a. Using Harding Lawson Associates output file

SSOUT034.OUT.

d. Decreased disconnectedness index input parameter

(6.3 compared to 10).

Figure 1. SESOIL model simulations for benzene concentration vs. time at 5330-cm depth.

tests. The sensitivity of the parameters is described in terms of change in dissolved maximum concentration of benzene and time taken to

reach the maximum benzene concentration at

5330 cm depth compared with original values (Fig.

1a). The changes in benzene concentration as adsorbed and as air-in-pores were similar to dissolved concentration.

Soil bulk density

Soil bulk density had a significant effect on the

peak concentration of benzene. The benzene concentration increased (0.12 μg/mL) compared to

the Drewett et al. (1993) estimates when the soil

bulk density was lowered from 1.92 to 1.62 g/cm3

(Fig. 1b). Furthermore, benzene was released 5

years earlier into the groundwater compared

with the Drewett et al. (1993) estimates.

Intrinsic permeability

SESOIL is highly sensitive to changes in intrinsic permeability from 1 × 10–7 to 1 × 10–4 cm2 (Ta-
7

e. Increased porosity input parameter (0.35 compared

to 0.25).

Dissolved (μg/mL)

Adsorbed (μg/g)

Air-in-pores (μg/cm3

)

0.004

0.003

0.002

0.001

0 20 40 60 80 100

Time (yrs)

Benzene Concentration

ble 1, Fig. 1c) and benzene concentration elevated

from 0.04 to 1.84 μg/mL. Benzene leached to the

groundwater 14 years earlier than in the Drewett

et al. (1993) estimates. These results agree with

the findings of Ladwig et al. (1993).

Disconnectedness index

Decreasing the value of the disconnectedness

index (10 to 6.3) lowered benzene concentration

(–0.01 μg/mL) at the bottom of the fourth soil column (Fig. 1d). Compared with the Drewett et al.

(1993) results, benzene travel time to the groundwater is increased by 4 years. These results are

consistent with the observations of Odencrantz et

al. (1991) that SESOIL was highly sensitive to the

disconnectedness index.

Effective porosity

Changing the effective porosity from 0.25 to

0.35 decreased the peak benzene concentration

(–0.037 μg/mL) and increased the peak leach

time by 12 years (Fig. 1e) compared to the

Figure 1 (cont’d).

f. Lower soil organic carbon content input parameter

(0.09 compared to 0.13%).

Dissolved (μg/mL)

Adsorbed (μg/g)

Air-in-pores (μg/cm3

)

0.8

0.6

0.4

0.2

0 20 40 60 80 100

Time (yrs)

Benzene Concentration

Dissolved (μg/mL)

Adsorbed (μg/g)

Air-in-pores (μg/cm3

)

0.25

0.20

0.15

0.10

0.05

0 20 40 60 80 100

Time (yrs)

Benzene Concentration

g. Lower adsorption coefficient of organic carbon input parameter (69 compared to 83).

Dissolved (μg/mL)

Adsorbed (μg/g)

Air-in-pores (μg/cm3

)

1.6

1.2

0.8

0.4

0 20 40 60 80 100

Time (yrs)

Benzene Concentration

h. Lower biodegradation rate in solid phase input parameter (2.74 ×10–4 compared to 5.48×10–4).
8

the benzene concentration was increased by 0.28

μg/mL (Fig. 1i). The benzene travel time through

the vadose zone was also increased (+1 years).

MANUAL CHECKS OF OUTPUT FILE

For confirmation, the output results were manually checked for water balance, benzene mass input, benzene mass distribution for each layer, benzene concentration in the soil water at the lowest

soil sublayer, and maximum benzene depth. SESOIL simulated these parameters precisely as per

set equation codes.

Water balance

The water balance was checked by using the

equations

P – E – MR = S + G = Y (1)

and

I = P – S (2)

where P = precipitation

E = evapotranspiration

MR = moisture retention

S = surface runoff

G = groundwater runoff or recharge

Y = yield

I = infiltration.

SESOIL provides solutions to eq 1 and 2 by iterating on soil moisture until the calculated value

for precipitation is within 1% of the user provided

input value. After the completion of this iteration,

the individual components such as infiltration,

evapotranspiration, moisture retention, surface

runoff and the groundwater runoff (recharge) are

known. Infiltration is checked as the difference between the precipitation and the surface runoff,

which is equal to the moisture retention plus the

evapotranspiration plus the groundwater runoff.

Benzene mass input

Benzene mass (μg) includes the amount of benzene in the precipitation and the amount loaded

into each of up to four major layers. SESOIL computes the amount of benzene in the precipitation

as

[benzene concentration in rain/benzene

maximum solubility in water] × solubility in

water × infiltration rate× area of application.

The benzene load in each layer is calculated from

the area of application × benzene application. To

Dissolved (μg/mL)

Adsorbed (μg/g)

Air-in-pores (μg/cm3)

0.5

0.4

0.3

0.2

0.1

0 20 40 60 80 100

Time (yrs)

Benzene Concentration

i. Lower biodegradation rate in liquid phase input

parameter (2.74×10–4 compared to 5.48 ×10–4).

Figure 1 (cont’d). SESOIL model simulations for benzene concentration vs. time at 5330-cm depth.

Drewett et al. (1993) estimates. This may be attributable to the higher volatilization of the benzene

compound because of increased porosity, which

allowed more air-filled voids.

Soil organic carbon content (Foc, %) and koc

SESOIL showed high sensitivity to organic carbon content. Organic carbon had a significant effect

on the rate of chemical movement, as well as on the

peak leached concentration. Slight reduction in organic carbon (0.13 to 0.09%) elevated the benzene

concentration (0.56 μg/mL, Fig. 1f), and the contaminant was released to groundwater 10 years

earlier than the original estimates calculated.

The koc, adsorption coefficient on organic carbon, had a slight effect on the sensitivity of

SESOIL. By lowering the koc value from 83 to 69

(Fig. 1g), the peak concentration of benzene elevated (0.13 μg/mL) compared to the Drewett et al.

(1993) tests. Similarly, koc also lowered benzene

transport time (–5 years) to the groundwater compared with the original simulations.

Biodegradation rate in solid and liquid phases

As expected, reducing the biodegradation rate

of the solid phase (5.48 × 10–4 to 2.74 × 10–4)

increased both the benzene concentration (+1.29

μg/mL) and the travel time to groundwater (+2

years, Fig. 1h). When the biodegradation rates

of the liquid phase were reduced to 2.74 × 10–4,
9

several scientists and regulatory agencies. At the

present state of scientific knowledge, SESOIL is a

well-developed seasonal soil compartment model.

Despite its several difficulties, the model is popular among regulators and users because of its simplicity compared to research models. It can be used

as a preliminary leachate assessment screening

tool with considerable site-specific calibrations.

Different authors found different input parameters sensitive to their local conditions in reference

to a particular contaminant. The MOFAT, POSSM

and VALOR models can also be considered for

leachate assessment in Alaska.

LITERATURE CITED

Abriola, L.M., R. Rathfelder, M. Maiza and S. Yadav

(1992) VALOR Code Version 1.0: A PC Code Simulating Immiscible Contaminant Transport in Subsurface

Systems. Palo Alto, California: Electric Power Research Institute.

Anderson, M.R. (1992) Development of generic soil

cleanup levels based on analysis of the leach-ate

pathway. Portland: Oregon Department of Environmental Quality.

Bonazountas, M. and J. Wagner (1981, 1984)

SESOIL: A Seasonal Soil Compartment Model. Cambridge, Massachusetts: Arthur D. Little, Inc.

Bonazountas, M. and D. Kallidromitou (1993) Mathematical hydrocarbon fate modeling in soil systems.

In Principles and Practices for Petroleum Contaminated Soils (E.J. Calabrese and P.T. Kostecki, Ed.). Boca

Raton, Florida: Lewis Publishers, p. 131–322.

Bonazountas, M., J. Wagner and B. Goodwin (1982)

Evaluation of Seasonal Soil/Groundwater Pollutant

Pathways. Cambridge, Massachusetts: Arthur D.

Little, Inc., EPA Contract No. 68-01-5949 (9).

Calabrese, E.J. and P.T. Kostecki (1992) Risk Assessment and Environmental Fate Methodologies. Boca

Raton, Florida: Lewis Publishers, Inc.

Daugherty, S.J. (1993) Hydrocarbon contamination

in the subsurface: Realties, issues, and prospects.

In Hydrocarbon Contaminated Soils and Groundwater

(P.T. Kostecki and E.J. Calabrese, Eds.). Boca Raton,

Florida: Lewis Publishers, Inc.

Donigian, A.S. and P.S.C. Rao (1986a) Overview of

terrestrial processes and modeling. In Vadose Zone

Modeling of Organic Pollutants (S.C. Hern and S.M.

Melancon, Eds.). Chelsea, Michigan: Lewis Publishers, p. 3–35.

Donigian, A.S. and P.S.C. Rao (1986b) Example

model testing studies. In Vadose Zone Modeling of

Organic Pollutants (S.C. Hern and S.M. Melancon,

Ed.). Chelsea, Michigan: Lewis Publishers, p. 103–

131.

calculate the load for the major layer, contained

sublayers are added to the first sublayer of that

particular major layer.

Distribution of benzene mass

Benzene mass distribution in the column was

calculated by adding the masses of the contaminant from all the phases for the year of contaminant loading. Volatilized mass was added to the

mass in moisture, adsorbed on soil and in soil air

for each sublayer down through the soil column.

The computed mass was added to the sublayer

above it in the next time step. Diffused mass was

added and divided by the time cycle.

Benzene concentration distribution

for lowest sublayer

Benzene concentrations (μg/mL) were checked

from the output file for each year until the benzene

reached the lowest soil zone. Also recorded was the

greatest benzene concentration as well as its travel

time.

Maximum pollutant depth

Drewett et al. (1993) assumed groundwater depth

at 5330 cm; therefore, benzene transport was simulated at 5330 cm as illustrated in Figure 1.

SUGGESTED IMPROVEMENTS

Several workers (Melancon et al. 1986; Anderson 1992; Odencrantz et al. 1992; Hetrick et al. 1989,

1993; Ladwig et al. 1993) performed sensitivity analyses on SESOIL, compared it with other vadose zone

chemical transport models, and modified input parameters according to the local conditions. They

emphasized that vadose zone models need to be

calibrated with measured site-specific data. The

suggested improvements for SESOIL calibration

and validation under Alaskan conditions are:

1. Adjust the input parameters of SESOIL according to different climatic regions of Alaska.

2. Propose soil input parameters as per the soil

types of Alaska.

3. Study the chemical characteristics of different

chemicals spilled at DOD installations.

4. Compare the SESOIL chemical transport simulations with other vadose zone models available in the literature.

CONCLUSIONS

Several computer models are in use to assess the

cleanup levels of hydrocarbon-contaminated soils.

Vadose zone models were extensively reviewed by
Drewett, G.M., M.J. Schmetzer and J.R. Allen

(1993) Corrective action plan release investigation,

Fort Greely, Alaska. Contract report for U.S. Army

Engineer District, Alaska. Anchorage, Alaska:

Harding Lawson Associates.

Eagelson, P.S. (1978) Climate, soil and vegetation.

Water Resources Research, 14: 1–7.

Gardner, R.H. (1984) A unified approach to sensitivity and uncertainty analysis. In Proceedings of the

10th IASTED International Symposium: Applied Simulation and Modelling, San Francisco, California.

General Sciences Corporation (1987) User’s Guide

to SESOIL Execution in GEMS. USEPA Contract No.

68-02-4281, Laural, Maryland.

General Sciences Corporation (1989) Graphical

Exposure Modeling System (GEMS) User’s Guide.

USEPA Contract No. 68-02-3770, Laurel, Maryland.

General Sciences Corporation (1990) RISKPRO

User’s Guide. Laurel, Maryland.

Hetrick, D.M. (1984) Simulation of hydrologic

cycle for watersheds. In Proceedings of the 9th IASTED International Conference, Energy, Power, and Environmental Systems, San Francisco, California.

Hetrick, D.M. and C.C. Travis (1988) Model predictions of watershed erosion components. Water Resources Bulletin, 24: 413–419.

Hetrick, D.M., C.C. Travis, P.S. Shireley and E.L. Etnier (1986) Model predictions of watershed hydrologic components: comparison and verification.

Water Resources Bulletin, 22: 803–810.

Hetrick, D.M., C.C. Travis, S.K. Leonard and R.S.

Kinerson (1989) Qualitative validation of pollutant transport components of an unsaturated soil

zone model (SESOIL). Oak Ridge National Laboratory/TM-10672.

Hetrick, D.M., A.M. Jarabek and C.C. Travis (1991)

Sensitivity analysis for physiologically based

pharmacokinetic models. Journal of Pharmacokinetics and Biopharmaceutics, 19: 1–20.

Hetrick, D.M., S.J. Scott and M.J. Barden (1993) The

new SESOIL user’s guide. Madison: Wisconsin

Department of Natural Resources, Emergency and

Remedial Response Section, Bureau of Solid and

Hazardous Waste Management.

Holton, G.A., C.C. Travis and E.L. Etnier (1985) A

comparison of human exposure to PCB emissions

from oceanic and terrestrial incineration. Hazardous Waste and Hazardous Materials, 2: 453–471.

Kincaid, C.T., J.R. Morey, S.B. Yabusaki, A.R. Felmy

and J.E. Rogers (1984) Geohydrochemical Models for

Solute Migration. Vol. 2: Preliminary evaluation of

selected computer codes for modeling aqueous

solution and solute migration in soils and geologic

10

media. Palo Alto, California: Electric Power Research Institute, EA-3477.

Ladwig, K.J., B.R. Hensel and D.M. Hetrick (1993)

Groundwater contamination susceptibility evaluation, SESOIL modeling. Madison: Wisconsin Department of Natural Resources, Emergency and

Remedial Response Section, Bureau of Solid and

Hazardous Waste Management.

Melancon, S.M., J.E. Pollard and S.C. Hern (1986)

Evaluation of SESOIL, PRZM and PESTAN in laboratory column leaching experiment. Environment

and Toxicology Chemistry, 5: 865–878.

Odencrantz, J.E., J.M. Farr and C.E. Robinson (1991)

A better approach to soil cleanup levels determination. In Transport Model Parameter Sensitivity for

Soil Cleanup Level Determinations Using SESOIL and

AT123D in the Context of the California Leaking Underground Fuel Tank Field Manual. Proceedings of 6th

Annual Conference on Hydrocarbon Contaminated

Soils: Analysis, Fate, Environmental and Public

Health, in Regulations. University of Massachusetts

at Amherst.

Odencrantz, J.E., J.M. Farr and C.E. Robinson (1992)

Transport model parameter sensitivity for soil

cleanup level determinations using SESOIL and

AT123D in the context of the California Leaking

Underground Fuel Tank Field Manual. Journal of

Soil Contamination, 1: 159–182.

O’Neill, R.V., R.H. Gardner and J.H. Carney (1982)

Parameter constraints in a stream ecosystem model: incorporation of a priori information in Monte

Carlo Error Analysis. Ecological Modeling, 16: 51–

65.

Travis, C.C., G.A. Holton, E.L. Etnier, C. Cook, F.R.

O’Donnel, D.M. Hetrick and E. Dixon (1986) Assessment of inhalation and ingested population

exposures from incinerated hazardous wastes. Environment International, 12: 533–540.

Tucker, W.A, C. Huang and R.E. Dickinson (1986)

Environmental fate and transport. In Benzene in

Florida Groundwater, an Assessment of the Significance of Human Health. Washington, D.C.: American Petroleum Institute, p. 79–122.

USEPA (1987) MINTEQA1, an equilibrium metal

speciation model: User’s manual. Office of Research and Development, U.S. Environmental

Protection Agency, EPA/600/3-87/012.

Walsh, P.J., L.W. Barnthouse, E.E. Calle, A.C. Cooper, E.D. Copenhaver, E.D. Dixon, C.S. Dudney, G.D.

Griffin, D.M. Hetrick, G.A. Holton, T.D. Jones,

B.D. Murphy, G.W. Suter, C.C. Travis and M. Uziel

(1984) Health and environmental effects document on direct coal liquefaction. Department of

Energy, Office of Health and Environmental Re-
11

search and Office of Energy Research, Oak Ridge

National Laboratory, Oak Ridge, Tennessee,

ORNL/TM-9287.

Wagner, J., M. Bonazountas and M. Alsterberg

(1983) Potential Fate of Buried Halogenated Solvents

Via SESOIL. Cambridge, Massachusetts: Arthur

D. Little, Inc.

Watson, D.B. and S.M. Brown (1985) Testing and

Evaluation of the SESOIL model. Palo Alto, California: Anderson-Nichols and Co., Inc.
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May 1996

Evaluating the SESOIL Model for Benzene Leaching Assessment in Alaska

Gurdarshan S. Brar

U.S. Army Cold Regions Research and Engineering Laboratory

72 Lyme Road Special Report 96-11

Hanover, New Hampshire 03755-1290

Approved for public release; distribution is unlimited.

Available from NTIS, Springfield, Virginia 22161.

SESOIL is a seasonal soil compartment model. A one-dimensional vertical transport model is designed to predict

seasonal solute distribution in the soil profile and watershed. CRREL received a request from the U.S. Army

Engineer District, Alaska, Environmental Technical Engineering Office, to provide technical assistance in evaluating the SESOIL model for helping to assess benzene leaching in the Alaskan environment. The major tasks

outlined in the request were as follows: work an example problem for a diesel-contaminated site, do analytical

checks and do manual SESOIL analytical calculations for one cycle. The SESOIL model requires 57 input variables supplied by the user. An additional 8 parameters are required for the execution file. This study did sensitivity analyses on soil bulk density, intrinsic permeability, disconnectedness index, porosity, organic carbon,

adsorption coefficient on organic carbon, and biodegradation rates of solid and liquid phases. The model is

very sensitive to all the parameters studied. Despite its several difficulties, the model is popular among regulators and users because of its simplicity compared to research models. It can be used as a screening-level tool in

assessing chemical movement in the soil column with considerable site-specific calibrations.

14

UNCLASSIFIED UNCLASSIFIED UNCLASSIFIED UL

Alaska Leachate assessment SESOIL

Benzene Soil