roger bannister penn state mgis program advisor: pat kennelly geog 596a, spring 2013
TRANSCRIPT
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Roger Bannister
Penn State MGIS Program
Advisor: Pat Kennelly
Geog 596A, Spring 2013
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OverviewHow and why groundwater elevation is measuredBasics of water table interpretationChallenges with automated contouringIdeas for new tools to improve workflowsProject schedule
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BackgroundHydrogeologists work on “clean-water” and “dirty-
water” projectsSubsurface investigations depend heavily on
discrete samplesContour maps help visualize what’s happening
between samplesAutomated contouring results are often unrealisticUsually resort to manually drawing (blunder prone)
or trying to “game” the algorithm with control points (tedious) – Both are inefficient!
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How Groundwater is MeasuredMonitoring wells intersect aquifer
of interestDepth to water measured at wells
with an interface probeData logged in field book and
later entered into site databaseWell reference elevations
surveyed to common datum
http://www.bodineservices.com/environmentalconsulting/groundwater-monitoring.php
http://www.in-situ.com/products/Water-Level/Pressure-Transducers/PXD-261-Pressure-Transducers
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Conceptual Site Models (CSM)A CSM is basically a working hypothesis of what is going
on overall at the siteWhat’s the geologic setting?Which direction is groundwater flowing and how fast?Are there preferential flow pathways?Where are the contaminants and what are they?Where’s the source of contamination and is it still present?Are there sensitive receptors down-gradient?Will the contaminants reach the receptor or will they
degrade before they get there?Contouring groundwater elevations play a large role in
developing the CSM
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What Hydrogeology Textbooks Have to Say… Fetter (4th ed. 2001, 1st ed. 1980) p.98-100 – Linear interpolation between sets
of three wells, influenced by topography and surface water. Hiscock (2005) p.146 – Linear interpolation. Also consider local topography,
springs, and streams. Kresic (1997) – Begin with linear triangulation and adjust based on
topography, springs, and streams. Mentions kriging. Kresic and Mikszewski (2013) – Linear interpolation a good start for manual
contouring. Several automated methods are available (e.g. IDW, Spline, Kriging) that can get close.
From Kresic and Mikscewski 2013
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Factors Considered During Interpretation (and Interpolation)Field measurementsRegional groundwater flowSite topographySurface water bodiesSubsurface composition (soil/geology)Preferential flow conduits (e.g. fractures, utility lines)
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Common Hydraulic FeaturesStreams and Lakes
Gaining vs LosingFracture Zones
High permeability, preferential flow zonesGeologic Boundary
Changes in transmissivityImpervious Barriers
Natural (e.g. dike or fault) or man-made (e.g. slurry wall)No flow, contours should be perpendicular
Interceptor TrenchesHigh permeability linear zone with pumping
Extraction WellLocalized cone of depression due to pumping
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From Heath 1983
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From Heath 1983
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From Kresic and Mikszewski 2013
From Kresic and Mikszewski 2013
From Heath 1983
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Typical Computer Contouring Workflow
It takes two steps to make contours with ArcGIS
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ChallengesDigitizing control points is not always intuitiveWorkflow is iterative and dynamic but current
outputs are staticGenerates a lot of intermediate datasets to manageTime consuming and frustrating
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Example Problem
Manual Solution (Kresic 1997)
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Triangulation (TIN)
Pro: quick and simple, exact interpolator, allows breaklinesCon: angular, limited to convex hull of points
Without Breakline With Breakline
Data from Kresic 1997 processed in ArcGIS 10.0 with 3D Analyst Extension
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Pro: nice organic curves, honors data points, allows breaklinesCon: limited to convex hull of points
Natural Neighbors
With Breakline
Data from Kresic 1997 processed in ArcGIS 10.0 with 3D Analyst Extension
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Spline
Pro: nice organic curves, can extrapolateCon: can’t use breaklines
Without Control Points With Control Points
Data from Kresic 1997 processed in ArcGIS 10.0 with 3D Analyst Extension
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Pro: statistical method incorporating anisotropy and trend removal Con: complex settings, requires large set of points, can’t use breaklines
Kriging
Without Control Points With Control Points
Data from Kresic 1997 processed in ArcGIS 10.0 with 3D Analyst Extension
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Goals and Objectives Determine how to incorporate information that is not
represented in point measurements into automated contouring
Develop intuitive interactive tools to capture interpretive information and help streamline contouring
Keep “drawing” to a minimum
NOT trying to develop a robust numerical flow model
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RequirementsKeep it simple: Target user is a hydrogeologist with
minimal training/experience in GISKeep additional inputs to a minimumMake processes as interactive as possibleDistinguish between real data and control featuresProduce repeatable resultsContours should honor all measurementsEntire workflow should take less than an hourKeep licensing costs down (ArcView with few
extensions)
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Proposed Methodology Research automated contouring algorithmsInterview geologists about their manual contouring
methodsIdentify information geologists use that is not
represented in the point dataDesign interfaces using mockupsDevelop as an ArcGIS Desktop Add-on programmed
in VB.net
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Iterative Design/Agile Development
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Interface Mockups
http://www.balsamiq.com/
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Project Timeline Work May-September
Monthly milestones for testing design iterationsConference abstract due August 6, 2013Present at Geological Society of America Annual
Meeting October 27-30
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ReferencesFetter, C.W., 2001. Applied Hydrogeology (4th ed.).Heath, R.C., 1983. Basic Ground-water Hydrology,
U.S. Geological Survey Water-Supply Paper 2220, 86p.
Hiscock, K.M., 2005. Hydrogeology Principles and Practice.
Kresic, N.,1997. Quantitative Solutions in Hydrogeology and Groundwater Modeling.
Kresic, N. and Mikszewski, A., 2013. Hydrogeological Conceptual Site Models: Data Analysis and Visualization.