ABSTRACT

The topic of ground-water modeling is introducedthrough a web-based lesson. The curriculum guidesstudents through the development of a conceptualhydrogeologic model, construction of a numerical flowmodel, and calibration of the numerical model tomeasured data. Students model a real watershed usingactual hydrologic data. Parts of the model developmentand calibration are conducted in a virtualthree-dimensional environment based upon VirtualReality Modeling Language (VRML) technology.Solutions from the industry-standard MODFLOWprogram are used, but the model is never actually run bythe students. Modeling results are pre-generated so thatexperience with numerical modeling can be acquiredwithout the frustrations inherent in operating the actualsoftware. The lesson is intended to offer a more intuitiveexperience with ground-water flow modeling thanattained through off-the-shelf ground-water software orlecture-based instruction.

INTRODUCTION

Numerical ground-water modeling is a criticalcomponent of modern hydrogeology but is typicallygiven only a very superficial treatment in undergraduatehydrogeology courses. One reason instructors mustoften gloss over ground-water modeling is that thesoftware can be extremely frustrating to learn. By thetime students learn how to run the ground-watermodeling software, little time remains to learn thescience. Alternatively, theoretical discussions ofmodeling can leave even the most computer-orientedstudent disinterested without a hands-on component. Inthe web-based curriculum described here, we try toretain the hands-on aspect of ground-water modeling,while discarding the baggage of learning a realground-water modeling program. The student is guidedthrough the conceptual exercise of building aground-water model, and then calibrates the model toactual data in a virtual three-dimensional environment.

The objective of modeling ground-water at a givenlocale may be to test specific hypotheses, predict futurebehavior, or simply to organize available hydrogeologicdata in a consistent conceptual framework (Andersonand Woessner, 1992). The modeling process is somewhatindependent of the objective. Figure 1 depicts a genericprocess of ground-water modeling. The modeler mustdefine a purpose, develop a conceptual model basedupon available field measurements, select theappropriate modeling software for the stated purpose,design the numerical model, calibrate the model tomeasured data, and then present the results. If thecalibration is not acceptable, i.e. the simulated data do

not match the measured data, then the numerical or eventhe conceptual model might have to be revisited. Thisprocesses is repeated until the model is deemedsatisfactory.

Note that the only step in Figure 1 that requiresdetailed knowledge of the numerical methods is thedesign of the numerical model. In a finite difference orfinite element model, this means selecting acomputational mesh, defining boundary conditions,assigning the correct mathematical equations andconstants to each cell in the mesh, and determiningappropriate time steps. If the conceptual model isproperly constructed, the model design stage should beprimarily an exercise in overlaying the conceptual modelon a computational grid.

Translation of a conceptual model to a numericalmodel requires some knowledge of the numerical meth-ods to be used and the particulars of the modeling pro-gram. Each program has its own peculiarities thatrequire familiarity to overcome. For example, in the in-dustry-standard MODFLOW model (McDonald andHarbaugh, 1988), each computational cell must be speci-fied as hydraulically confined, unconfined, or be forcedto depend upon the head solution at each solution itera-tion. It would seem that the simplest option is to let theprogram decide whether the cell is confined or uncon-fined, but in practice choosing this option can slow con-vergence to a solution or cause instabilities that mayprevent the program from converging to a solution at all.These numerical subtleties are important in real applica-tions, but they have more to do with numerical methodsthan ground-water.

We attempt to separate ground-water modeling as aconcept from ground-water modeling as a numericalexercise. Our approach is to guide students through theground-water modeling process (Figure 1) ignoringnumerical methods as much as possible. Students areasked to make a series of critical decisions that lead to anumerical model and then to calibrate the model toactual data. To avoid having to wait for numericalcalculations, the model results are pre-generated so thatstudents receive instant feedback from their trials. Modelresults are checked against scientific expectations andfield measurements.

Measured data and model results are displayed in avirtual three-dimensional (3-D) environment. This isaccomplished through Virtual Reality ModelingLanguage (VRML) datasets that allow students tomanipulate the terrain as a 3-D object, or even fly or walkthrough the topography. Presentation of model results inthis manner enables students to more readily comparesimulated results with their own intuition. In addition,hydraulic potential surfaces can be displayed withoutthe need for maps. Hydraulic potential contours can befrustrating for introductory-level students, and thesefrustrations distract from understanding the underlyingprinciples of ground-water flow.

506 Journal of Geoscience Education, v. 51, n. 5, November, 2003, p. 506-511

An Introduction to Ground-Water Modeling Using Virtual Reality

Modeling Language (VRML)

Matthew W. Becker Department of Geology, State University of New York at Buffalo, NSC 876,

Buffalo, NY 14260, mwbecker@geology.buffalo.edu

James W. Schuetz Department of Geology, State University of New York at Buffalo, NSC 876,

Buffalo, NY 14260

This lesson is part of an on-going Internet-basededucational project called the Mirror Lake InteractiveTeaching Database (ITD). The overarching purpose ofthe project is to distribute over 50 years of hydrologicdata collected at the Hubbard Brook ExperimentalForest. Our efforts are directed at distributing these datain a more organic format than individual publicationsand tables. Data are offered in VRML format, presentedin a historical and hydrological context, and integratedwith educational lessons add value to the information.The ITD can be found at http://www.geology.buffalo.edu/ITD.

THE MIRROR LAKE SITE ANDGROUND-WATER MODEL

This lesson concerns the Mirror Lake Watershed, locatedwithin the Hubbard Brook Experimental Forest, in theWhite Mountain National Forest, near NorthWoodstock, Grafton County, New Hampshire. TheHubbard Brook Experimental Forest is a 3,160 hectarereserve established by the USDA Forest Service in 1955as a major center for hydrologic research in NewEngland, and is a National Science Foundation LongTerm Ecological Research Site. Over 40 years ofatmospheric and surface water data have been collectedcontinuously at the site . Since the 1970’s the UnitedStates Geological Survey (USGS) has been conductingground-water studies in the Mirror Lake area. In 1979,efforts to understand the interactions of lakes andground water led to long-term gaging of streams,piezometers, bedrock wells, and weather stations in and

around Mirror Lake (Winter, 1984). In more recent years,additional research by the USGS involved fractured rockhydrogeology (Shapiro et al., 1995; Hsieh et al, 1996;Becker and Shapiro, 2000).

The study area occupies about 10 km2 composed ofglacial mountain terrain with steep hillsides and flatvalleys. Most of the land surface is covered by glacialdeposits consisting primarily of till with some local areasof sand and gravel. Glacial deposits are thin ornon-existent in the uplands, may be as thick as 50 m nearMirror Lake (Tiedeman et al., 1997). The highest point,located in the Northwest corner of the area, is about 700m above sea level, while the lowest point is along theEastern edge at about 180 m. Water in the study areadrains to Hubbard Brook or Mirror Lake. Mirror Lakedrains into Hubbard Brook and, ultimately, thePemigewasset River.

The surface-water basin of Mirror Lake (Figure 2)has changed in area since the construction of I-93 and isdivided into three sub-basins. The total basin area was1,030,000 m2 prior to the construction of I-93 (Winter,1984). After completion of the interstate, an earthen damwas built to divert road-salt contaminated surface wateraway from Mirror Lake (Rosenberry et al, 1999). Thisdam, along the west side of the highway, cut the basinarea to 850,000 m2, diverting water North.

The ground-water model discussed in this lesson isbased upon a MODFLOW model published by theUnited States Geological Survey (USGS) (Tiedeman etal., 1997). Input files and MODFLOW code are availablethrough the USGS, and were supplied to us by theauthors. The model grid extends somewhat beyond theMirror Lake surface water basin (Figure 2). The verticaldomain is divided into five model layers. Layers 1 and 2coincide with the glacial deposits, and layers 3, 4 and 5coincide with the bedrock. Modeling of this system hasshown that the ground-water drainage basin extendswell beyond the surface-water basin at Mirror Lake(Tiedeman et al., 1997; Tiedeman et al., 1998).

VIRTUAL REALITY MODELING LANGUAGE(VRML)

Like Hyper-Text Markup Language (HTML) VRML is adata language that is read by compatible browser (Ameset al., 1996). The most current data standard for VRML isVRML97 (ISO/IEC 14772-1:1997). The next generationVRML will likely be X3D, which will include back-ward-compatible VRML encoding as well as ExtensibleMarkup Language (XML, see www.web3d.org for moreinformation). VRML content is recognized by aweb-browser through a MIME tag. If the browser is capa-ble of displaying VRML, or a VRML browser plug-in hasbeen installed, the VRML content will automatically bedisplayed when the VRML MIME tag is detected.

In spite of the enormous potential of VRML, it hasnot found universal acceptance in the web community.Common web-browsers like Netscape and Internet Ex-plorer do not include VRML viewing capability in theirmore recent versions. To view VRML content users mustdownload a web-browser plug-in. Although suchplug-ins are available free of charge for multiple plat-forms, there is no single browser available that can be in-stalled on all platforms. In addition, each browserrenders VRML content in a slightly different manner,making it difficult for VRML authors to predict how theircontent will look on a particular user’s machine. Our ex-perience is primarily with Cosmo Player, which is popu-

Becker and Schuetz - Ground-water Modeling 507

Figure 1. Flow chart illustrating a genericground-water modeling process (adapted fromAnderson and Woessner, 1992).

lar but no longer supported (see http://www.karmanaut.com/cosmo/player/) and Cortona (Parallel-Graphics, http://www.parallelgraphics.com/ prod-ucts/cortona/). Other free and proprietary VRMLbrowsers are available, and can be found through theVRML Repository (http://www.web3d.org/vrml/vrml.htm).

There are two approaches to publishing VRMLcontent on the web: server-side applications andclient-side applications (Huang and Lin, 2002).Server-side applications have the advantage ofuniformity in data handling, but rendering is slow.Client-side applications are far superior for renderinggraphics, but users must download software onto theircomputer to view the data. We have taken a hybridapproach in which CGI (Common Gateway Interface)scripts are written to serve up VRML objects of the user’schoosing, which must be viewed by a browser installedon the user’s computer. For example, the user can clickon a form button to choose a certain combination ofVRML objects, and those objects are immediatelyaggregated and served as a single VRML object. We have

developed a Java3D-based browser, but have notdistributed it because Java security protocols makeinstallation problematic for the typical user. Others havehad similar difficulties with using Java3D to distributegeologic data (Dorman and Gehringer, 2002).

THE GROUND-WATER MODELING LESSON

The Ground-Water Modeling Lesson follows the processillustrated in Figure 1. Students are expected to enterwith an understanding of Darcy’s Law, concepts ofhydraulic head, and some general understanding ofground-water flow. The lesson is, therefore, appropriatefor the latter part of most introductory hydrology orhydrogeology college-level courses, and perhaps someK-12 Earth Science courses. No specific computer ormathematical skills are required for the lesson, otherthan facility with a PC and point-and-click drawing.The lessons begins with a short introduction to thefundamentals of ground-water mass balance. We reviewthe concepts of topography-driven ground-water flow.Water enters the subsurface through recharge, and

508 Journal of Geoscience Education, v. 51, n. 5, November, 2003, p. 506-511

Figure 2. The Mirror Lake surface-water basin and MODFLOW model extent after Tiedeman et al., 1997).

generally exits through ground-water discharge atsurface-water bodies. The height of the water tabledepends upon the resistance to flow, which is calledhydraulic conductivity. With this simple explanation,students are well on their way to understandingground-water flow modeling from a practitioner’s pointof view.

The purpose of the model is to determine the averagehydraulic conductivity of the glacial deposits and theaverage ground-water recharge within the study area.There have been slug-test estimates of hydraulicconductivity of Mirror Lake glacial deposits (Rosenberryet al., 1999), but point measurements do not necessarilyrepresent regional behavior. A model-derived estimate

of hydraulic conductivity is probably morerepresentative of the watershed as a whole. In thedevelopment of the conceptual model, we stress theimportance of proper boundary specification. Two typesof boundaries are considered: (1) a perimeter boundarythat constrains the entire model, and (2) internalboundaries that constrain localized areas within themodel. It is the former that is most important, because itdetermines the scope of the study and greatly influencesits outcome. The students investigate how hydraulicno-flow boundaries may be established in aground-water model by identifying points where flowlines are expected to converge and diverge. Atconvergence and divergence points ground-water flowis primarily upward or downward and thus no waterflows laterally in or out of the model domain.

Students can investigate how hydraulic boundariesare established by working an exercise using aJava-based finite element program developed by the U.S.Geological Survey called TopoDrive, that calculates flowlines through topography in profile view (Hsieh et al,1996). They are asked to develop a counter-example, inwhich hydraulic divides observed in shallowpiezometers are found to have only a local influence. Thepurpose of this exercise is to emphasize the point that hy-draulic boundaries are tenuous and established primar-ily out of convenience.Once the students understand how no-flow hydraulicboundaries work, they are asked to find them in theirmodel domain. The students are asked to draw aproposed perimeter boundary for their conceptualmodel based upon a topographic map of the area.Although we include a software that allows them tocarry out this exercise on the computer, in classroomtesting we found that the students were much morecomfortable drawing on a paper-printed map. Thesoftware is a very straight-forward image program, but ittakes some time to get used the mouse behavior and it isdifficult to see the whole model area on the computerscreen. We now offer the option of printing the map orworking online.

Model design is the process of translating theconceptual model into a numerical format by specifyinggrids, establishing boundaries, and providing modelparameters for every computational cell. We try to treadlightly through the discussion of numerical designbecause the treatment of these details is largelyprogram-specific. Grid design, for example, differsgreatly between finite-difference and finite elementprograms. Our goal is to discuss modeling relativelyindependent of software.

Although we avoid attention to the particular gridmethod used, we devote some discussion to meshrefinement as a concept. Mesh refinement refers to theincreased resolution of grid near areas of interest. Forexample, almost all of the available well data areclustered around Mirror Lake. The students areencouraged to think about where spatial resolution ofmeasured data warrants mesh refinement how thisrefinement affects the level of detail in the model output.We emphasize this non-uniform distribution ofmeasured data by offering a VRML rendering of thewells completed in the watershed. The wells,topography, and hydrography are shown in 3-D, so thatstudents can easily discern the density of data with depthand with position.

Calibration of the model is carried out entirely in aVRML environment (Figure 3). The objective is to find

Becker and Schuetz - Ground-water Modeling 509

Figure 3. Screen shots from the VRML-based calibra-tion exercise. Topography is light gray, water table isdark gray, and there is a 2x vertical exaggeration.On-screen images have better resolution and are incolor. From top to bottom, examples cases when thehydraulic conductivity too high, too low, and best fit.

the combination of glacial deposit hydraulicconductivity and recharge rate that best represents theobserved water table. Modern ground-water softwareallows model calibration to be accomplishedautomatically after the user defines one or more objectivefunctions. The objective function is usually based uponthe calculated difference between measured andpredicted heads and/or measured and predicted streamflow. The VRML display allows the students to intuit thecalibration directly, however. When hydraulicconductivity is too high, or recharge too low, the watertable is far below the surface. Because there are perennialstreams in the watershed, this clearly cannot be thecorrect solution. When hydraulic conductivity is too low,or recharge too high, the water table rises above thetopography. This also cannot be a reasonable solution. Ifthe student has a fundamental understanding of theinteraction between surface and ground water, he or sheshould quickly arrive at the correct solution, wherein thewater table lies just below the surface through most ofthe watershed.

After arriving at a satisfactory solution in thismanner, the students can investigate the sensitivity of themodel to hydraulic conductivity and recharge. Modelerror is displayed as a contour plot, where hydraulicconductivity and recharge are the coordinate axes.Students are asked to find the best combination ofparameters to reduce the difference between measuredand simulated heads. Based upon the shape of the errorcontours, they are asked to comment on the relativesensitivity of the model to hydraulic conductivity andrecharge. If they could collect more field data, would theacquire a better estimate of hydraulic conductivity orrecharge?

The VRML environment allows the student to seethat the water table is a subdued reflection of thetopography, and that it tends to be deeper undertopographic rises. The comparison of topography andthe water table illustrates a problem in ground-watermodeling that is not usually noticed. In even the best-fitsolution, the water table rises above the topography inlimited areas. This occurs because the model does notknow the elevation of the land surface. Only hydraulichead values in the form of well levels, stream stage, orlake stage enter into the ground-water flow calculations.Thus, although the water table appears to reflect thetopography, it is really dictated by the presence ofinternal boundaries. Students are asked how the modelsimulated water table would change if recharge andinternal boundaries remained the same, but another 100m of sediments were piled on top of the model (theanswer is there would be no change).

PEDAGOGICAL BENEFITS

General principles of effective learning are incorporatedinto the ITD. Foremost, is the intuitive principle thatlearning-by-doing is the most effective method forteaching complex knowledge-domain-specific tasks(Dalton, 1986; Renshaw and Taylor, 1998; Renshaw et al.,1999). Students are given computer-based manipulativesthat allow them to test their understanding of therelationship between geologic properties andground-water flow. We introduce these concepts incontext of a larger system, to provide students amotivation for exploration. Visualization-based learningcan fail when students are disoriented and/or do notcare about the larger problems (Edelson and Gordin,1998). We offer these lessons in a laboratory environment

that promotes cooperative problem solving (Salisbury,1990).

It is difficult to compare our computer-assistedGround-Water Modeling Lesson to “traditional” instruc-tional methods, as there is no established approach toteaching ground-water modeling in general hydrologyor hydrogeology courses. Popular hydrogeology text-books (Domenico and Schwartz, 1998; Fetter, 2001) usu-ally approach the topic by describing the relevantfinite-difference equations, and then discussing the con-struction of models and case studies. There are generallyno hands-on exercises offered at this level. Hands-ontraining is typically offered in upper-level or gradu-ate-level specialized courses on ground-water modeling,which involve training in professional software pack-ages. The danger of introducing these software inlower-level courses is that, unless sufficient training andguidance is provided, students will become lost in thesoftware and lose track of the main lesson. Audet andAbegg (1998) used professional Geographic InformationSystem software in a classroom and found that noviceusers of the software tended to exercise lower-level cog-nitive skills than the more experienced users. Without in-structor supervision, students must resort totrial-and-error solutions to computer-based problems.Chang (2002) compared teacher-centered and stu-dent-centered computer assisted instruction of debrisflows, and found that the self-paced group performedmore poorly on a 30 item multiple choice test, possiblybecause they were overwhelmed with unstructured in-formation.

The impact of using VRML in this lesson, rather thanstatic images, is particularly difficult to quantify. In theirrecent review of visualization in the geosciences,Libarkin and Brick (2002) note that rigorous assessmentinstruments specifically designed for visualization ofEarth systems are not currently available but are sorelyneeded. There do seem to be some obvious advantages tocommunicating three-dimensional spatial relationshipsin a VRML environment. It is very difficult, for instance,to compare the water level surface and topographicsurface (Figure 2) in two-dimensions. It takes severalminutes to become reasonably adept at handling theVRML object, but once the students become familiar withthe interface they customize the view to their specificneeds. This has the dual advantages of displaying theinformation in a manner best suited to individuallearning needs, and involving the student in the learningprocess. It is interesting to note that some students rotatethe landscape, whereas others prefer a map view. Somestudents “fly” through the landscape while others preferto manipulate it as an object.

CONCLUDING REMARKS

The number of 3-D visualization tools for teachinggeosciences appears to be increasing rapidly and VRMLseems to be the present data format of choice (Lin et al.,1999; Moore et al., 1999; Dorman and Gehringer, 2002;Huang and Lin, 2002). In spite of the activity in this area,the technology is by no means established. As is the casewith many computer technologies, at about the time aVRML technology becomes stable it also becomesobsolete. This presents a difficulty to the development ofclassroom pedagogy that usually takes several years offield testing before it becomes effective. The DigitalLibrary for Earth Science Education (DLESE) has begunto coordinate some of these efforts through meetings andonline discussions and should result in a more concerted

510 Journal of Geoscience Education, v. 51, n. 5, November, 2003, p. 506-511

effort to bring 3-D content into the classroom (seehttp://www.dlese.org).The value of VRML technology as a teaching tool forhydrology is unknown. As is the case with geosciencevisualization in general, better tools for evaluating theeffectiveness of 3-D computer objects are needed. Expertevaluations in this area are certainly warranted given thesignificant effort being expended toward thedevelopment of visualization and virtual realitypedagogy for the geosciences.

ACKNOWLEDGEMENTS

This material is based upon work supported by theNational Science Foundation under Grant No. 9978335,Geoscience Education program, Michael Mayhewprogram director. We are grateful to Claire Tiedeman forsupplying us with the MODFLOW model of MirrorLake, to Tom Winter for providing us with hydrologicdata, and to the scientists of the Hubbard BrookExperimental Forest for their insights concerning thehydrology of the Mirror Lake Watershed. The thoughtfulreview comments of B. Saini-Eidukat, K. Thorbjarnarson,and J. Libarkin were greatly appreciated.

REFERENCES

Ames, A.L., Nadeau, D.R., and Moreland, J.L., 1996,VRML 2.0 Sourcebook, John Wiley & Sons.

Anderson, M.P., and Woessner, W.W., 1992, Appliedgroundwater modeling; simulation of flow andadvective transport, 381.

Audet, R.H., and Abegg, G.L., 1998, Geographicinformation systems: implications for problemsolving, Journal of Research in Science Teaching, v.33, p. 21-45.

Becker, M.W., and Shapiro, A.M., 2000, Tracer transportin fractured crystalline rock: evidence ofnondiffusive breakthrough tailing, Water ResourcesResearch, v. 36, p. 1677-1686.

Chang, C.Y., 2002, The impact of different forms ofmultimedia CAI on students’ science achievement,Innovative Education Teaching International, v. 39,p. 280-288.

Dalton, D.W., 1986, The efficacy of computer-assistedvideo instruction on rule learning and attitudes,Journal of Computer-Based Instruction, v. 13, p.122-128.

Domenico, P.A., and Schwartz, F.W., 1998, Physical andchemical hydrogeology, Second Edition, 506 p., NewYork, John Wiley & Sons.

Dorman, L., and Gehringer, D.D., 2002, Web BrowserApplet Allows Visualization of Three-dimensionalModels, EOS, v. 83, Electonic Supplement.

Edelson, D.C., and Gordin, D., 1998, Visualization forlearners: a framework for adapting scientists tools,Computers and Geosciences, v. 24, p. 607-616.

Federer, C.A., Flynn, L.D., Martin, C.W., Hornbeck, J.W.and Pierce, R. S., 1990, Thirty years ofhydrometeorologic data at the Hubbard Brook Ex-perimental Forest, New Hampshire., U.S. Depart-ment of Agriculture, Forest Service, NortheasternForest Experiment Station, General Technical Re-port., NE-141, v. 44.

Fetter, C.W., 2001, Applied hydrogeology, 4th Edition,598 p., Upper Saddle River, New Jersey, PrenticeHall.

Hsieh, P.A., 2001, TopoDrive and ParticleFlow—TwoComputer Models for Simulation and Visualizationof Ground-Water Flow and Transport of FluidParticles in Two Dimensions, U.S. Geological SurveyOpen-File Report 01-286,U.S. Geological SurveyOpen-File Report 01-286.

Hsieh, P.A., Shapiro, A.M., Morganwalp, D.W., andAronson, D.A., 1996, Hydraulic characteristics offractured bedrock underlying the FSE well field atthe Mirror Lake site, Grafton County, NewHampshire, in U.S. Geological Survey ToxicSubstances Hydrology Program technical meeting,p. 127-130, Colorado Springs, CO, United States.

Huang, B., and Lin, H., 2002, A Java/CGI approach todeveloping a geographic virtual reality toolkit on theInternet, Computers & Geosciences, v. 28, p. 13-19.

Libarkin, J.C., and Brick, C., 2002, Researchmethodologies in science education: visualizationand the geosciences, Journal of GeoscienceEducation, v. 50, p. 449-455.

Lin, H., Gong, J., and Wang, F., 1999, Web-basedthree-dimensional geo-referenced visualization,Computers and Geosciences, v. 25, p. 1177-1185.

McDonald, M.G., and Harbaugh, A.W., 1988, A modularthree-dimensional finite-difference ground-waterflow model, in U.S. Geological Survey Techniques ofWater-Resources Investigations, book 6, chap. A1, p.586.

Moore, K., Dykes, J., and Wood, J., 1999, Using Java tointeract with geo-referenced VRML within a virtualfield course, Computers and Geosciences, v. 25, p.1125-1136.

Renshaw, C.E., and Taylor, H.A., 2000, The educationaleffectiveness of computer-based instruction,Computers and Geosciences, v. 26, p. 677-682.

Renshaw, C.E., Taylor, H.A., andReynolds, C.H., 1998,Impact of computer-assisted instruction ofhydrogeology on critical-thinking skills, Journal ofGeoscience Education, v. 46, p. 274-279.

Rosenberry, D.O., Bukaveckas, P.A., Buso, O.C., Likens,G.E., Shapiro, A.M., and Winter, T.C., 1999,Movement of road salt to a small New Hampshirelake, Water Air and Soil Pollution, v. 109, p. 179-206.

Salisbury, D.F., 1990, Cognitive psychology and itsimplications for designing drill and practiceprograms for computers, Journal ofComputer-Based Instruction, v. 17, p. 23-30.

Shapiro, A.M., Hsieh, P.A., and Winter, T.C., 1995, TheMirror Lake fractured-rock research site; amultidisciplinary research effort in characterizingground-water flow and chemical transport infractured rock, in Fact Sheet - U. S. GeologicalSurvey, p. 2.

Tiedeman, C.R., Goode, D.J., and Hsieh, P.A., 1997, Nu-merical simulation of ground-water flow throughglacial deposits and crystalline bedrock in the MirrorLake area, Grafton County, New Hamp-shire,1044-9612.

Tiedeman, C.R., Goode,D.J., and Hsieh, P.A., 1998,Characterizing a ground water basin in a NewEngland mountain and valley terrain, GroundWater, v. 36, p. 611-620.

Winter, T.C., 1984, Geohydrologic setting of Mirror Lake,West Thornton, New Hampshire, in Water-ResourcesInvestigations - U. S. Geological Survey, p. 61

Becker and Schuetz - Ground-water Modeling 511