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Improving Interpolation Tools for Groundwater Data

Improving Interpolation Tools for Groundwater Data. Roger Bannister Penn State MGIS Program Advisor: Pat Kennelly Geog 596A, Spring 2013. Overview. How and why groundwater elevation is measured Basics of water table interpretation Challenges with automated contouring

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Improving Interpolation Tools for Groundwater Data

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  1. Improving Interpolation Tools for Groundwater Data Roger Bannister Penn State MGIS Program Advisor: Pat Kennelly Geog 596A, Spring 2013

  2. Overview • How and why groundwater elevation is measured • Basics of water table interpretation • Challenges with automated contouring • Ideas for new tools to improve workflows • Project schedule

  3. Background • Hydrogeologists work on “clean-water” and “dirty-water” projects • Subsurface investigations depend heavily on discrete samples • Contour maps help visualize what’s happening between samples • Automated contouring results are often unrealistic • Usually resort to manually drawing (blunder prone) or trying to “game” the algorithm with control points (tedious) – Both are inefficient!

  4. How Groundwater is Measured • Monitoring wells intersect aquifer of interest • Depth to water measured at wells with an interface probe • Data logged in field book and later entered into site database • Well 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

  5. Conceptual Site Models (CSM) • A CSM is basically a working hypothesis of what is going on overall at the site • What’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

  6. 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

  7. Factors Considered During Interpretation (and Interpolation) • Field measurements • Regional groundwater flow • Site topography • Surface water bodies • Subsurface composition (soil/geology) • Preferential flow conduits (e.g. fractures, utility lines)

  8. Common Hydraulic Features • Streams and Lakes • Gaining vs Losing • Fracture Zones • High permeability, preferential flow zones • Geologic Boundary • Changes in transmissivity • Impervious Barriers • Natural (e.g. dike or fault) or man-made (e.g. slurry wall) • No flow, contours should be perpendicular • Interceptor Trenches • High permeability linear zone with pumping • Extraction Well • Localized cone of depression due to pumping

  9. Groundwater Flow and Resulting Water Table Contours From Heath 1983

  10. Groundwater Flow and Resulting Water Table Contours From Heath 1983

  11. Groundwater Flow and Resulting Water Table Contours From Kresic and Mikszewski 2013 From Heath 1983 From Kresic and Mikszewski 2013

  12. Typical Computer Contouring Workflow It takes two steps to make contours with ArcGIS

  13. Challenges • Digitizing control points is not always intuitive • Workflow is iterative and dynamic but current outputs are static • Generates a lot of intermediate datasets to manage • Time consuming and frustrating

  14. Example Problem Manual Solution (Kresic 1997)

  15. Triangulation (TIN) Data from Kresic 1997 processed in ArcGIS 10.0 with 3D Analyst Extension • Pro: quick and simple, exact interpolator, allows breaklines • Con: angular, limited to convex hull of points Without Breakline With Breakline

  16. Natural Neighbors Data from Kresic 1997 processed in ArcGIS 10.0 with 3D Analyst Extension • Pro: nice organic curves, honors data points, allows breaklines • Con: limited to convex hull of points With Breakline

  17. Spline Data from Kresic 1997 processed in ArcGIS 10.0 with 3D Analyst Extension • Pro: nice organic curves, can extrapolate • Con: can’t use breaklines Without Control Points With Control Points

  18. Kriging Data from Kresic 1997 processed in ArcGIS 10.0 with 3D Analyst Extension • Pro: statistical method incorporating anisotropy and trend removal • Con: complex settings, requires large set of points, can’t use breaklines Without Control Points With Control Points

  19. 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

  20. Requirements • Keep it simple: Target user is a hydrogeologist with minimal training/experience in GIS • Keep additional inputs to a minimum • Make processes as interactive as possible • Distinguish between real data and control features • Produce repeatable results • Contours should honor all measurements • Entire workflow should take less than an hour • Keep licensing costs down (ArcView with few extensions)

  21. Proposed Methodology • Research automated contouring algorithms • Interview geologists about their manual contouring methods • Identify information geologists use that is not represented in the point data • Design interfaces using mockups • Develop as an ArcGIS Desktop Add-on programmed in VB.net

  22. Iterative Design/Agile Development

  23. Interface Mockups http://www.balsamiq.com/

  24. Project Timeline • Work May-September • Monthly milestones for testing design iterations • Conference abstract due August 6, 2013 • Present at Geological Society of America Annual Meeting October 27-30

  25. References • Fetter, 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.

  26. Questions? • rab5509@psu.edu

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