Introduction to Groundwater Modelling

52,378 views 119 slides Nov 13, 2009
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C. P. Kumar
Scientist ‘F’
C. P. Kumar
Scientist ‘F’
National Institute of Hydrology
Roorkee – 247667 (Uttaranchal)
India
Email: [email protected]
Webpage: http://www.angelfire.com/nh/cpkumar/
Introduction to Groundwater Modelling

Presentation Outline
Groundwater in Hydrologic Cycle Why Groundwater Modelling is needed? Mathematical Models Modelling Protocol Model Design Calibration and Validation Groundwater Flow Models Groundwater Modelling Resources

Groundwater in Hydrologic Cycle

Types of Terrestrial Water Types of Terrestrial Water
Ground water Ground water
Soil Soil
Moisture Moisture
Surface
Water

Unsaturated Zone / Zone of Aeration / Vadose
(Soil Water)
Pores Full of Combination of Air and Water
Zone of Saturation (Ground water)
Pores Full Completely with Water

Groundwater
Important source of clean water
More abundant than SW
Linked to SW systems
Sustains flows
in streams
Baseflow

pollution
Groundwater Concerns?
groundwater mining
subsidence

Problems with groundwater ¾Groundwater overdraft / mining / subsidence
¾Waterlogging
¾Seawater intrusion
¾Groundwater pollution

Why Groundwater Modelling is needed?

Groundwater • An important component of water resource systems.
• Extracted from aquifers through pumping wells and
supplied for domestic use, industry and agriculture.
• With increased withdrawal of groundwater, the quality
of groundwater has been continuously deteriorating.
• Water can be injected into aquifers for storage and/or
quality control purposes.

Management of a groundwater system, means
making such decisionsas:
• The total volume that may be withdrawn annually from the aquifer.
• The location of pumping and artificial recharge wells, and their
rates.
• Decisions related to groundwater quality.
Groundwater contamination by:
¾Hazardous industrial wastes
¾Leachate from landfills
¾Agricultural activities such as the use of fertilizers and pesticides

™MANAGEMENTmeans making decisionsto achieve goalswithout
violating specified constraints.
™Good management requires information on the response of the
managed system to the proposed activities.
™This information enables the decisio n-maker, to compare alternative
actions and to ensure that constraints are not violated.
™Any planning of mitigation or cont rol measures, once contamination
has been detected in the saturated or unsaturated zones, requires
the prediction of the path and the fate of the contaminants, in
response to the planned activities.
™Any monitoring or observation network must be based on the
anticipated behavior of the system.

™A tool is needed that will provide this information.
™The tool for understanding the system and its behavior
and for predicting this response is the model.
™Usually, the model takes the form of a set of
mathematical equations, involving one or more partial
differential equations. We refer to such model as a
mathematical model.
™The preferred method of solution of the mathematical
model of a given problem is the analytical solution.

™The advantage of the analytical solution is that the
same solution can be applied to various numerical
values of model coefficients and parameters.
™Unfortunately, for most practical problems, because of
the heterogeneity of the considered domain, the
irregular shape of its boundaries, and the non-analytic
form of the various functions, solving the mathematical
models analytically is not possible.
™Instead, we transform the mathematical model into a
numerical one, solving it by means of computer
programs.

We should have a CALIBRATED MODELof the aquifer, especially,
we should know the aquifer’s natural replenishment (from
precipitation and through aquifer boundaries).
Prior to determining the management scheme for anyaquifer:
We should have a POLICY that dictates management objectives
and constraints.
Obviously, we also need information about the water demand
(quantity and quality, current and future), interaction with other
parts of the water resources system, economic information, sources
of pollution, effect of changes on the environment---springs, rivers,...
The model will provide the response of the aquifer (water levels,
concentrations, etc.) to the implementation of any management
alternative.

GROUND WATER MODELING
WHY MODEL?
•To make predictions about a ground-water
system’s response to a stress
•To understand the system
•To design field studies
•Use as a thinking tool

Use of Groundwater models
•Can be used for three general purposes:
•To predict or forecastexpected artificial
or natural changes in the system.
Predictive is more applied to deterministic
models since it carries higher degree of
certainty, while forecasting is used with
probabilistic (stochastic) models.

Use of Groundwater models
•To describethe system in order to analyse
various assumptions
•To generate a hypothetical system that
will be used to study principles of
groundwater flow associated with various
general or specific problems.

ALL GROUND-WATER HYDROLOGY WORK IS MODELING
A Model is a representation of a system.
Modeling begins when one formulates a concept of a
hydrologic system,
continues with application of, for example,
Darcy's Law to the problem,
and may
culminate in a complex numerical simulation.

Ground Water Flow Modelling
A Powerful Tool
for furthering our understanding
of hydrogeological systems
Importance of understanding ground water flow models
Construct accurate representations of hydrogeological systems Understand the interrelationships between elements of systems Efficiently develop a sound mathematical representation Make reasonable assumptions and simplifications Understand the limitations of th e mathematical representation Understand the limitations of the interpretation of the results

Introduction to Ground Water Flow Modelling
K
xq
h xh− =
0
)(
Predicting heads
(and flows)
and
Approximating parameters
Solutionsto the flow equations
Most ground water flow models are
solutions of some form of the ground
water flow equation
Potentiometric
Surface
x
x
x h
o
x
0
h(x)
x
K
q
“e.g., unidirectional, steady-state flow
within a confined aquifer
The partial differential equation needs to be solved to calculate head as a
function of position and time,
i.e., h=f(x,y,z,t)
h(x,y,z,t)?
K
xq
hh dx
K
q
dh
K
q
dx
dh
x h
h
−= − ⇒ −= ⇒ −=
∫ ∫
0
0
0
Darcy’s Law Integrated

¾¾
The only effective way to test effects of The only effective way to test effects of
groundwater management strategies groundwater management strategies
¾¾
Takes time, money to make model Takes time, money to make model
¾¾
Conceptual model Conceptual model
Steady state model Steady state model
Transient model Transient model
¾¾
The model is only as good as its calibration The model is only as good as its calibration
Groundwater Modeling Groundwater Modeling

Processes we might want to model
• Groundwater flow
calculate both heads and flow
• Solute transport–requires information
on flow (velocities)
calculate concentrations

MODELING PROCESS
ALL IMPORTANT MECHANISMS & PROCESSES MUST BE INCLUDED IN
THE MODEL, OR RESULTS WILL BE INVALID.

TYPES OF MODELS
CONCEPTUAL MODELQUALITATIVE DESCRIPTION OF SYSTEM
"a cartoon of the system in your mind"
MATHEMATICAL MODELMATHEMATICAL DESCRIPTION OF
SYSTEM
SIMPLE- ANALYTICAL (provides a continuous solution over the
model domain)
COMPLEX- NUMERICAL (provides a discrete solution - i.e. values are
calculated at only a few points)
ANALOG MODELe.g. ELECTRICAL CURRENT FLOW through a
circuit board with resistors to represent hydraulic conductivity and
capacitors to represent storage coefficient
PHYSICAL MODELe.g. SAND TANK which poses scaling problems

Mathematical Models

Mathematical model:
simulates ground-water flow and/or
solute fate and transport indirectly by
means of a set of governing equations
thought to represent the physical
processes that occur in the system.
(Anderson and Woessner, 1992)

Components of a Mathematical Model •Governing Equation
(Darcy’s law + water balance equation)
with head (h) as the dependent variable
•Boundary Conditions
•Initial conditions(for transient problems)

R Δx Δy
Q
Δy
Δx
Δz
1. Consider flux (q) through REV
2. OUT –IN = -ΔStorage
3. Combine with:q= -KKgradh
q
Derivation of the Governing Equation

Law of Mass Balance+ Darcy’s Law =
Governing Equation for Groundwater Flow
---------------------------------------------------------------
div
q= -S
s
(∂h ⁄∂t)
(Law of Mass Balance)
q= -K
grad h (Darcy’s Law)
div (K
grad h) = S
s
(∂h ⁄∂t)
(S
s
= S / Δz)

0) ( ) ( ) (=


∂∂
+


∂∂
+




z
h
K
z y
h
K
y x
h
K
x
z y x
General governing equation
for steady-state
, heterogeneous
, anisotropic
conditions, without a source/sink term
* ) ( ) ( ) (R
z
h
K
z y
h
K
y x
h
K
x
z y x
−=




+




+




with a source/sink term

* ) ( ) ( ) (R
t
h
S
z
h
K
z y
h
K
y x
h
K
x
s z y x



=




+




+




General governing equation for transient,
heterogeneous, and anisotropic conditions
Specific Storage
S
s
= ΔV / (Δx Δy Δz Δh)

Figures taken from Hornberger et al. (1998)
Unconfinedaquifer
Specific yield
Confinedaquifer
Storativity
S = V / A Δh
S = S
s
b
b
Δh
Δh

* ) ( ) ( ) (R
t
h
S
z
h
K
z y
h
K
y x
h
K
x
s z y x



=




+




+




R
t
h
S
y
h
T
y x
h
T
x
y x



=




+




) ( ) (
R
t
h
S
y
h
hK
y x
h
hK
x
y x



=




+




) ( ) (
2D confined:
2D unconfined:
Storage coefficient (S) is either storativityor specific yield.
S = S
s
b & T = K b
General 3D equation

Types of Solutions of Mathematical Models •Analytical Solutions: h= f(x,y,z,t)
(example: Theisequation)
•Numerical Solutions
Finite difference methods
Finite element methods
•Analytic Element Methods (AEM)

The flexibility of analytical modeling is
limiteddue to simplifying assumptions:
Homogeneity, Isotropy, simple geometry,
simple initial conditions…
Geology is inherently complex:
Heterogeneous, anisotropic, complex geometry, complex conditions…
This complexity calls for a more
powerful solution to the flow equation ÎNumerical modeling
Limitations of Analytical Models

Numerical Methods
hAll numerical methods involve
representing the flow domain by a
limited number of discrete points called
nodes.
hA set of equations are then derived to
relate the nodal values of the
dependent variable such that they
satisfy the governing PDE, either
approximately or exactly.

• Numerical Solutions
Discrete solution of head at selected nodal points.
Involves numerical solution of a set of algebraic
equations.
Finite difference models(e.g., MODFLOW)
Finite element models(e.g., SUTRA)

Finite Difference Modelling
3-D Finite Difference Models
Requires vertical discretization (or layering) of model
K
1
K
2
K
3
K
4

Finite difference models
may be solved using:
• a computer program
(e.g., a FORTRAN program)
• a spreadsheet (e.g., EXCEL)

Finite Elements:
basis functions, variationalprinciple,
Galerkin’smethod, weighted residuals
• Nodes plus elements; elements defined by nodes
• Nodes located on flux boundaries
• Flexibility in grid design:
elements shaped to boundaries
elements fitted to capture detail
• Easier to accommodate anisotropy that occurs at an
angle to the coordinate axis
• Able to simulate point sources/sinks at nodes
• Properties (K, S) assigned to elements

Involves superposition of analytic solutions. Heads are
calculated in continuous space using a computer to do
the mathematics involved in superposition.
Hybrid
Analytic Element Method
(AEM)
The AE Method was introduced by Otto Strack.
A general purpose code, GFLOW
, was developed by
Strack’sstudent HenkHaitjema, who also wrote a
textbook on the AE Method: Analytic Element Modeling
of Groundwater Flow, Academic Press, 1995.
Currently the method is limited to steady-state,
two-dimensional, horizontal flow.

Modelling Protocol

What is a “model”?

Any “device”that represents approximation
to field system

Physical Models

Mathematical Models

Analytical

Numerical

Modelling Protocol

Establish the Purpose of the Model

Develop Conceptual Model of the System

Select Governing Equations and Computer Code

Model Design

Calibration

Calibration Sensitivity Analysis

Model Verification

Prediction

Predictive Sensitivity Analysis

Presentation of Modeling Design and Results

Post Audit

Model Redesign

Purpose -What questions do you want the
model to answer?

Prediction; System Interpretation; Generic
Modeling

What do you want to learn from the model?

Is a modeling exercise the best way to
answer the question? Historical data?

Can an analytical model provide the answer?
System Interpretation: Inverse Modeling: Sensitivity
Analysis
Generic: Used in a hypothetical sense, not necessarily
for a real site
System Interpretation: Inverse Modeling: Sensitivity
Analysis
Generic: Used in a hypothetical sense, not necessarily
for a real site

Model “Overkill”? „
Is the vast labor of characterizing the system,
combined with the vast labor of analyzing it,
disproportionateto the benefits that follow?

ETHICS „
There may be a cheaper, more effective
approach

Warn of limitations

Conceptual Model “Everything should be made as simple as possible, but not simpler.” Albert
Einstein

Pictorial representation of the groundwater
flow system

Will set the dimensions of the model and
the design of the grid

“Parsimony”….conceptual model has been
simplified as much as possible yet retains
enough complexity so that it adequately
reproduces system behavior.

Select Computer Code

Select Computer Model

Code Verification

Comparison to Analytical Solutions; Other
Numerical Models

Model Design

Design of Grid, selecting time steps,
boundary and initial conditions, parameter
data set
Steady/Unsteady..1, 2, or 3-D;
…Heterogeneous/Isotropic…..Instantaneous/Continuous
Steady/Unsteady..1, 2, or 3-D; …Heterogeneous/Isotropic…..Instantaneous/Continuous

Calibration

Show that Model can reproduce field-
measured heads and flow (concentrations if
contaminant transport)

Results in parameter data set that best
represents field-measured conditions.

Calibration Sensitivity Analysis

Uncertainty in Input Conditions

Determine Effect of Uncertainty on
Calibrated Model

Model Verification

Use Model to Reproduce a Second Set of
Field Data Prediction

Desired Set of Conditions

Sensitivity Analysis

Effect of uncertainty in parameter values and
future stresses on the predicted solution

Presentation of Modelling
Design and Results

Effective Communication of
Modeling Effort

Graphs, Tables, Text etc.

Postaudit

New field data collected to
determine if prediction was correct

Site-specific data needed to
validate model for specific site
application
Model Redesign „
Include new insights into system
behavior

NUMERICAL MODELING
DISCRETIZE
Write equations of GW Flow between each node
Darcy's Law
Conservation of Mass
DefineMaterial Properties
Boundary Conditions
Initial Conditions
Stresses
At each node either H or Q is known,the other is unknown
n equations & n unknowns
solve simultaneously with matrix algebra
ResultH at each known Q node
Q at each known H node
CalibrateSteady State
Transient
Validate
Sensitivity
Predictions
Similar Process for Transport Modeling only Concentration and Flux is unknown

NUMERICAL MODELING

Model Design

MODELsNEED
Geometry
Material Properties (K, S, T,
Φ
e
, R, etc.)
Boundary Conditions (Head, Flux, Concentration etc.)
Stress -changing boundary condition

Model Design Model Design
•Conceptual Model
•Selection of Computer Code
•Model Geometry
•Grid
•Boundary array
•Model Parameters
•Boundary Conditions
•Initial Conditions
•Stresses

Concept Development Concept Development
•Developing a conceptual model is the initial
and most importantpart of every modelling
effort. It requires thorough understanding
of hydrogeology, hydrology and dynamics
of groundwater flow.

Conceptual Model
A descriptive representation
of a groundwater system that
incorporates an interpretation of the
geological
& hydrological
conditions.
Generally includes information about
the water budget
. May include
information on water chemistry
.

Selection of Computer Code Selection of Computer Code
•Which method will be used depends largely
on the type of problem and the knowledge of
the model design.
•Flow, solute, heat, density dependent etc.
•1D, 2D, 3D

Model Geometry Model Geometry
•Model geometry defines the size and the
shape of the model. It consists of model
boundaries, both external and internal, and
model grid.

Boundaries Boundaries
•Physical boundariesare well defined
geologic and hydrologic features that
permanently influence the pattern of
groundwater flow (faults, geologic units,
contact with surface water etc.)

Boundaries Boundaries
•Hydraulic boundariesare derived from the
groundwater flow net and therefore
“artificial”boundaries set by the model
designer. They can be no flow boundaries
represented by chosen stream lines, or
boundaries with known hydraulic head
represented by equipotential lines.

HYDRAULIC BOUNDARIES
A streamline(flowline) is also a
hydraulic boundary because by
definition, flow is ALWAYS
parallel to a streamflow. It can
also be said that flow NEVER
crosses a streamline; therefore it
is similar to an IMPERMEABLE
(no flow) boundary
BUT
Stress can change the flow
pattern and shift the position of
streamlines; therefore care must
be taken when using a
streamline as the outer boundary
of a model.

TYPES OF MODEL BOUNDARY
NO-FLOW BOUNDARY
Neither HEAD nor FLUX is
Specified. Can represent a
Physical boundary or a flow
Line (Groundwater Divide)
SPECIFIED HEAD OR
CONSTANT HEAD BOUNDARY
h = constant
q is determined by the model.
And may be +ve or –ve according
to the hydraulic gradient developed

TYPES OF MODEL BOUNDARY (cont’d)
SPECIFIED FLUX BOUNDARY
q = constant
h is determined by the model
(The common method of simulation
is to use one injection well for each
boundary cell)
HEAD DEPENDANT BOUNDARY
h
b
= constant
q = c (h
b
–h
m
)
and c = f (K,L) and is called
CONDUCTANCE
h
m
is determined by the model and
its interaction with h
b

Boundary Types
Specified Head/Concentration: a special case of constant head (ABC, EFG)
Constant Head /Concentration: could replace (ABC, EFG)
Specified Flux: could be recharge across (CD)
No Flow (Streamline): a special case of specified flux (HI)
Head Dependent Flux: could replace (ABC, EFG)
Free Surface: water-table, phreatic surface (CD)
Seepage Face: pressure = atmospheric at ground surface (DE)

Boundary conditions in Boundary conditions in Modflow Modflow
•Constant head boundary
•Head dependent flux
–River Package
–Drain Package
–General-head Boundary Package
•Known Flux
–Recharge
–Evapotranspiration
–Wells
–Stream
•No Flow boundaries

Initial Conditions Initial Conditions
•Values of the hydraulic head for each active
and constant-head cell in the model. They
must be higher than the elevation of the cell
bottom.
•For transient simulation, heads to resemble
closely actual heads (realistic).
•For steady state, only hydraulic heads in
constant head-cell must be realistic.

Model Parameters Model Parameters
•Time
•Space (layer top and bottom)
•Hydrogeologic characteristics
(hydraulic conductivity, transmissivity,
storage parameters and effective porosity)

Time Time
•Time parameters are specified when
modelling transient (time dependent)
conditions. They include time unit, length
and number of time steps.
•Length of stress periods is not relevant for
steady state simulations

Grid Grid
•In Finite Difference model, the grid is
formed by two sets of parallel lines that are
orthogonal. The blocks formed by these
lines are called cells. In the centre of each
cell is the node –the point at which the
model calculates hydraulic head. This type
of grid is called block-centeredgrid.

Grid Grid
•Grid mesh can be uniform or custom, a
uniform grid is better choice when
–Evenly distributed aquifer characteristics data
–The entire flow field is equally important
–Number of cells and size is not an issue

Grid Grid
•Grid mesh can be custom when
–There is less or no data for certain areas
–There is specific interest in one or more smaller
areas
•Grid orientation is not an issue in isotropic
aquifers. When the aquifer is anisotropic,
the model coordinate axes must be aligned
with the main axes of the hydraulic
conductivity.


Regular vsirregular grid spacing Irregular spacing may be used to obtain
detailed head distributions in selected areas
of the grid.
Finite difference equations that use irregular
grid spacing have a higher associated error
than FD equations that use regular grid spacing.

Curvature of the water table
Vertical change in head
Variability of aquifer characteristics (K,T,S)
Variability of hydraulic parameters (R, Q) Considerations in selecting the size of
the grid spacing
Desired detail around sources and sinks (e.g., rivers)

MODEL GRIDS

Grids
hIt is generally agreed that from a practical
point-of-view the differences between grid
types are minor and unimportant.
hUSGS MODFLOW employs a body-centred grid.

Boundary array (cell type) Boundary array (cell type)
•Three types of cells
–Inactive cells through which no flow into or out
of the cells occurs during the entire time of
simulation.
–Active, or variable-head cells are free to vary
in time.
–Constant-head cell, model boundaries with
known constant head.

Hydraulic conductivity and Hydraulic conductivity and
transmissivity transmissivity
•Hydraulic conductivity is the most critical
and sensitive modelling parameter.
•Realistic values of storage coefficient and
transmissivity, preferably from pumping test,
should be used.

Effective porosity Effective porosity
•Required to calculate velocity, used mainly
in solute transport models

Calibration and Validation

Calibration parametersare uncertain parameters
whose values are adjusted during model calibration.
Typical calibration parameters include hydraulic
conductivity and recharge rate.
Identify calibration parameters and their reasonable
ranges.

Calibration Targets
calibration
value
associated error
20.24 m
+/−0.80 m
Target with relatively
large associated error.
Target with smaller
associated error.
In a real-world problem, we need to establish model specific calibration criteria
and define targets
including
associated error.

• Head measured in an observation well is known
as a target.
Targets
used in Model Calibration
• The simulated head at the node representing the
observation well is compared with the measured head.
• During model calibration, parameter values are
adjusted until the simulated head matches the observed
value.
• Model calibration solves the inverse problem.

Calibration to Fluxes
When recharge rate (R) is a calibration
parameter, calibrating to fluxes can help in
estimating K and/or R.

H1
H2
q = KI
In this example, flux information
helps calibrate K.

In this example, discharge
information helps calibrate R.

Calibration -Remarks
•Calibrations are non-unique.
• A good calibration does not ensure that
the model will make good predictions.
• Need for an uncertainty analysisto accompany
calibration results and predictions.
•You can never have enough field data.
•Modelers need to maintain a healthy skepticism
about their results.

Uncertainty in the Calibration
Involves uncertainty in:
9Parameter values
9Conceptual model including boundary conditions,
zonation, geometry etc.
9Targets

Ways to analyze uncertainty
in the calibration
Sensitivity analysis
is used as an uncertainty
analysis after calibration.
Use an inverse model (automated calibration)
to quantify uncertainties and optimize the
calibration.

Uncertainty in the Prediction
9
Involves uncertainty in how parameter values
(e.g., recharge) will vary in the future.
9
Reflects uncertainty in the calibration
.

Stochastic simulation
Ways to quantify uncertainty
in the prediction
Sensitivity analysis

How do we “validate”a model so that
we have confidence that it will make
accurate predictions?

Modeling Chronology
1960’s Flow models are great!
1970’s Contaminant transport models are great!
1975 What about uncertainty of flow models?
1980s Contaminant transport models don’t work.
(because of failure to account for heterogeneity)
1990s Are models reliable?

“The objective of model validationis to
determine how well the mathematical
representation of the processes describes
the actual system behavior in terms of the
degree of correlation between model
calculations and actual measured data”.

How to build confidence in a model
Calibration
(history matching)
“Verification

requires an independent set of field data
Post-Audit
: requires waiting for prediction to occur
Models as interactive management tools

KEEPING AN OPEN MIND
Consider all dimensions of the problem before coming
to a conclusion.
Considering all the stresses that might be imposed and
all the possible processes that might be involved in a
situation before reaching a conclusion.
KEEPING AN OPEN MIND is spending 95% of your
TIME DETERMINING WHAT YOU THINK IS HAPPENING
and only 5% of your TIME DEFENDING YOUR OPINION.
AVOID the common human TRAP of REVERSING
THOSE PERCENTAGES.

Groundwater Flow Models

Groundwater Flow Models •The most widely used numerical groundwater flow model is
MODFLOW which is a three-dimensional model, originally
developed by the U.S. Geological Survey.
•It uses finite difference scheme for saturated zone.
•The advantages of MODFLOW include numerous facilities
for data preparation, easy exchange of data in standard
form, extended worldwide experience, continuous
development, availability of so urce code, and relatively low
price.
•However, surface runoff and unsaturated flow are not
included, hence in case of transient problems, MODFLOW
can not be applied if the flux at the groundwater table
depends on the calculated head and the function is not
known in advance.

MODFLOW
√USGS code
√Finite Difference Model
•MODFLOW 88
•MODFLOW 96
•MODFLOW 2000

MODFLOW
(Three-Dimensional Finite-Difference Ground-Water Flow
Model)
•When properly applied, MODFLOW is the recognized
standard model.
•Ground-water flow within the aquifer is simulated in
MODFLOW using a block-centered finite-difference
approach.
•Layers can be simulated as confined, unconfined, or a
combination of both.
•Flows from external stresses such as flow to wells, areal
recharge, evapotranspiration, flow to drains, and flow
through riverbeds can also be simulated.

MT3D (A Modular 3D Solute Transport Model)
•MT3D is a comprehensive three-dimensional numerical
model for simulating solute transport in complex
hydrogeologic settings.
•MT3D is linked with the USGS groundwater flow simulator,
MODFLOW, and is designed specifically to handle
advectively-dominated transport problems without the need
to construct refined models specifically for solute transport.

FEFLOW (Finite Element Subsurface Flow System)
FEFLOW is a finite-element package for simulating 3D and 2D
fluid density-coupled flow, contaminant mass (salinity) and
heat transport in the subsurface. HST3D (3-D Heat and Solute Transport Model)
The Heat and Solute Transport Model HST3D simulates
ground-water flow and associated heat and solute transport in
three dimensions.

SEAWAT (Three-Dimensional Variable-Density Ground-Water Flow)
•The SEAWAT program was developed to simulate three-
dimensional, variable-density, transient ground-water flow
in porous media.
•The source code for SEAWAT was developed by
combining MODFLOW
and MT3D
into a single program
that solves the coupled flow and solute-transport equations.

SUTRA (2-D Saturated/Unsaturated Transport Model)
•SUTRA is a 2D groundwater saturated-unsaturated
transport model, a complete saltwater intrusion and energy
transport model.
•SUTRA employs a two-dimensional hybrid finite-element
and integrated finite-difference method to approximate the
governing equations that describe the two interdependent
processes.
•A 3-D version of SUTRA has also been released.

SWIM (Soil water infiltration and movement model)
•SWIMv1 is a software package for simulating water
infiltration and movement in soils.
•SWIMv2 is a mechanistically-based model designed to
address soil water and solute balance issues.
•The model deals with a one-dimensional vertical soil
profile which may be vertically inhomogeneous but is
assumed to be horizontally uniform.
•It can be used to simulate runoff, infiltration,
redistribution, solute transport and redistribution of
solutes, plant uptake and transpiration, evaporation, deep
drainage and leaching.

VISUAL HELP
(Modeling Environment for Evaluating and Optimizing
Landfill Designs)
•Visual HELP is an advanced hydrological modeling
environment available for designing landfills, predicting
leachate mounding and evaluating potential leachate
contamination.
Visual MODFLOW
(Integrated Modeling Environment for MODFLOW and
MT3D)
•Visual MODFLOW provides professional 3D groundwater
flow and contaminant transport modeling using
MODFLOW and MT3D.

Groundwater Modelling Resources

Groundwater Modeling Resources
Kumar Links to Hydrology Resources
http://www.angelfire.com/nh/cpkumar/hydrology.html
USGS Water Resources Software Page
water.usgs.gov/software
Richard B. Winston’s Home Page
www.mindspring.com/~rbwinston/rbwinsto.htm
Geotech & Geoenviron Software Directory
www.ggsd.com
International Ground Water Modeling Center
www.mines.edu/igwmc

Ground Water Modelling Discussion Group An email discussion group related to ground water modelling and
analysis. This group is a forum fo r the communication of all aspects
of ground water modelling including technical discussions;
announcement of new public domain and commercial softwares; calls
for abstracts and papers; conference and workshop announcements;
and summaries of research results, recent publications, and case
studies.
Group home page: http://groups.yahoo.com/group/gwmodel/
Post message: [email protected]
Subscribe : [email protected]
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List owner: [email protected]

Visual MODFLOW Users Group Visual MODFLOW is a proven standard for professional 3D
groundwater flow and contaminant transport modeling using
MODFLOW-2000, MODPATH, MT3DMS AND RT3D. Visual
MODFLOW seamlessly combines the standard Visual MODFLOW
package with Win PEST and the Visual MODFLOW 3D-Explorer to give
a complete and powerful graphical modeling environment.
This group aims to provide a forum for exchange of ideas and
experiences regarding use and application of Visual MODFLOW
software.
Group home page: http://in.groups.yahoo.com/group/visual-modflow/
Post message: [email protected]
Subscribe: [email protected]
Unsubscribe: [email protected]
List owner: [email protected]

HAPPY MODELLING
THANKS