The Advective-Transport Observation (ADV) Package (Anderman and

Hill, 1997) allows advective-transport

observations of steady-state flow fields to

be used in conjunction with the hydraulic head and flow observations originally included in the three-dimensional

ground-water flow parameter-estimation

model MODFLOWP (Hill, 1992). In the

ADV Package, advective-transport paths

and times are represented using particle

tracking. This allows advectivetransport observations to be included in

the regression with minimal increase in

computational effort. Features of the

package include:

E A particle-tracking routine that duplicates the semi-analytical method of

MODPATH (Pollock, 1994).

E Comparison of the x-, y-, and zmovements of the simulated and observed advective front at defined times.

Thus, the direction and path of travel as

well as the overall travel distance is included in the calibration process.

E Calculation of sensitivities of the

particle movement to the parameters using the exact sensitivity-equation approach. Composite scaled sensitivities

provide users with a quantitative measure of the information provided by the

observations.

E Particle tracking in a forward or

backward direction can be used to evaluate transport of contaminants or

recharges areas.

E Inclusion of effects such as retardation by adjustment of the effectiveporosity value.

Effective porosity is not included as a

parameter to be estimated in version 1.0

of the ADV package.

This publication outlines the major

features of the ADV Package and gives

information on obtaining the program

and documentation.

The ADV Package

 Observations of the advective component of contaminant transport can provide

important information for the calibration

of ground-water flow models. The addition of the Advective-Transport Observation (ADV) Package (Anderman and Hill,

1997) to MODFLOWP (Hill, 1992) allows the path and speed of advective

travel to be used in conjunction with formal parameter-estimation methods, which

are powerful tools for model calibration

(Hill, 1998; Poeter and Hill, 1997).

Applying the ADV Package

Advective-transport observations generally cannot be measured directly, but

can be inferred from a number of data

types, such as contaminant concentrations,

tracer tests, or, in some circumstances, age

datings. If contaminant concentrations are

used, advective-transport observations

can be obtained by contouring measured

concentrations and using the distribution

along the plume front to determine the

likely advective-front location, as shown

by the triangle in figure 1. In some situations, an analytical solution can help approximate an advective-front location.

A simulated equivalent to the observation is generated by tracking a particle

through the grid from the source location

for the known time of ground-water movement, as shown by the blue line in figure

1. The differences in the x-, y-, and

z-components between the simulated and

observed advective-front locations are

then used in the nonlinear regression in

conjunction with the differences between

the simulated and observed heads and

flows to estimate optimal model parameter values.

If ground-water age dates are used, the

ADV Package can be used to test hypothesized recharge areas. In this case, a

particle is tracked backwards from the

observed age-date location and the

advective-transport observation consists

of the hypothesized recharge area; regression is used to determine whether the

resulting flowpath is possible with reasonable parameter values.

It is important to include the uncertainty in approximated advectivetransport observations in the analysis.

The weighted regression procedure used

in MODFLOWP allows this uncertainty to

be included explicitly.

Improving Model Calibration

With the ADV Package

Application of the ADV Package to

the Otis Air Force Base sewage-discharge

plume (Anderman and others, 1996) illustrates the utility of the package.

Parameter sensitivities indicate the relation between changes in parameter values (e.g. hydraulic conductivity and

recharge rate) and simulated values of

head, flow, and advective transport within

the model. They also provide a measure

of the information about the system paFigure 1. Conceptual representation of advective-transport observations.

Improving Ground-Water Flow Model Calibration With the

Advective-Transport Observation (ADV) Package to MODFLOWP

LAKE 1

LAKE 2

SOURCE

OBSERVATION

WELLS

CONTAMINANT

PLUME CONTOURED

FROM MEASURED

CONCENTRATIONS

Δy

Δx

Observed AdvectiveTransport Location Simulated

Particle

Path

Δz

Defining the

discrepancy

Particle Entry Point

USGS Fact Sheet FS-059-98

June 1998

U.S. Department of the Interior

U.S. Geological Survey
rameters present in the different data types,

and indicate how well the parameters are

likely to be estimated from the available

data. In the Otis Air Force Base model,

sensitivities for the advective-transport observations are smaller than for the other

observations (fig. 2). The additional information provided by the advective-transport

observations, however, reduces parameter

correlation (fig. 3), which measures if a

coordinated change in parameter values

does not change the model solution, enough

that the parameters can be estimated

uniquely.

Ground-water flow model validity can

be judged, in part, by

evaluating the reasonableness of the

parameter estimates.

Historically, unreasonable estimated parameter values have

been perceived as a

drawback of inverse

modeling; in fact,

they provide useful

information that

causes the modeler to

scrutinize the model

and, perhaps, explore

alternative conceptual models (Poeter

and Hill, 1997), resulting in a better calibrated model. In the Otis Air Force Base

model, investigation of an unreasonable

value of estimated recharge revealed that

the model is sensitive to a) the season in

which observations are obtained, and b)

the heads at the downstream boundary

conditions. This led to reevaluation of the

data collection effort, concluding that

probable errors in the stream elevations

caused significant model error.

Advective-transport observations reflect ground-water velocities and patterns

over a long period of time and provide

more complete information about the

ground-water flow system than flow measurements taken at a discrete point in time.

This results in different estimated parameter values when different observation

types are used and has a significant impact

on the probable accuracy of the transport

predictions of the model. This is clearly

demonstrated by the Otis Air Force Base

model. The plume movement simulated

by a model calibrated with only hydraulichead and flow observations significantly

underpredicted the observed plume movement, as indicated by the yellow box in

fig. 4. Including the advective transport in

the model calibration resulted in a model

that more accurately simulated subsurface

flow rate and direction, as indicated by the

blue box in fig. 4.

How to Obtain ADV Package

Program, Documentation, and

Additional Information

 The ADV Package is included with

MODFLOWP version 3.0 and later at no

cost from the USGS at World Wide Web

site http://water.usgs.gov/software/. The

site includes links to download program

source code, test data sets, and compiled

versions for some computers. Also, the

program is available by anonymous ftp

from the Internet site water.usgs.gov in directory pub/software/ground_water/.

 Reports documenting USGS model

programs can be purchased from

U.S. Geological Survey

Branch of Information Services

Box 25286

Denver, CO 80225-0286

 —E.R. Anderman and M.C. Hill

Figure 2. Composite scaled sensitivities for the Otis Air Force Base

model are one measure of the information provided by different types

of data.

References

Anderman, E.R. and Hill, M.C., 1997,

Advective-transport observation (ADV)

package, a computer program for adding

advective-transport observations of steadystate flow fields to the three-dimensional

ground-water flow parameter-estimation

model MODFLOWP: U.S. Geological Survey Open-File Report 97-14, 67 p.

Anderman, E.R., Hill, M.C., and Poeter, E.P.,

1996, Two-dimensional advective transport

Figure 4. Improved simulated plume movement using advective-transport observations.

Particle Entry Point

Plume-front location

approximated from

concentration data

Location simulated

without advectivetransport observations

Location simulated

with advectivetransport

observations

SOURCE

in ground-water flow parameter estimation:

Ground Water, v. 34(6), p. 1001-1009.

Hill, M.C., 1998, Methods and guidelines for

effective model calibration: U.S. Geological Survey Water-Resources Investigations

Report 98-4005.

Hill, M. C., 1992, A computer program

(MODFLOWP) for estimating parameters

of a transient, three-dimensional, groundwater flow model using nonlinear regression: U.S. Geological Survey Open-File

Report 91-484, 358 p.

Figure 3. Range of parameter correlation for

the Otis Air Force Base model with different

types of data. For correlation greater than 0.95,

parameters may not be estimated uniquely and

predictions may be substantially in error. For

the data set with heads only, all values equal 1.

EXTREME CORRELATION

Heads Only

Heads and Flow

Heads and

Advective Transport

0.8

0.9

1.0

Absolute Value of

Parameter Correlation

Hydraulic

Conductivity

Recharge

Northern

Boundary Flux

Sewage

Discharge Flux

Ashumet Pond

Conductance

Head Observations

Flow Observation

Advective-Transport Observations

All Observations

Composite Scaled Sensitivity

40

30

20

10

0

Poeter, E.P. and Hill, M.C., 1997, Inverse models: a necessary next step in groundwater

modeling, Ground Water: v. 35(2), p. 250-

260.

Pollock, D.W., 1994, User's guide for MODPATH/MODPATH-PLOT, Version 3, A particle tracking post-processing package for

MODFLOW, the U.S. Geological Survey

finite-difference ground-water flow model:

U.S. Geological Survey Open-File Report

94-464, 247 p.