Arc Hydro Groundwater Data Model

1. Arc Hydro Groundwater Data Model This presentation is adapted from the Groundwater Preconference Seminar presented at the 2008 ESRI User Conference by David Maidment, Gil Strassberg, and Norman Jones The research described here is based on the PhD dissertation of Gil Strassberg, which is accessible at: ftp://ftp.crwr.utexas.edu/pub/outgoing/strassberg/GroundwaterDataModel/Documents/Dissertaion_Strassberg.pdf

2. What is a hydrologic data model Booch et al. defined a model: “a simplification of reality created to better understand the system being created” Objects Aquifer Stream Well Volume R.M. Hirsch, USGS

3. Geologic maps Time series observations Borehole data Groundwater data model (geospatial database) Hydrostratigraphy Geospatial vector layers Numerical models Gridded data Developing a groundwater data model Take a variety of spatial information and integrate into one geospatial database with a common terminology • Better communication • Integration of data • Base for applications

4. Components Components can be added to the framework to represent specific themes in more detail Surface water components Groundwater components Network Geology Framework Drainage Borehole data Hydrography Hydrostratigraphy Channel Simulation Temporal (enhanced)

5. Arc Hydro GW Data Model

6. Arc Hydro Framework • Basic representation of surface water and groundwater • Components can be added to the framework to represent specific themes in more detail

7. Well • Wells are the most basic features in groundwater databases • Attributes of wells describe its location, depth, water use, owner, etc.

8. Well • Wells are defined as 2D point features • Only some basic attributes are predefined to describe the well use, and geometry and relationship with aquifers Wells in the Edwards Aquifer

9. Aquifer features • Polygon features for representing aquifer boundaries and zones within them • Representation of Aquifer maps

10. Aquifer features • An aquifer is defined by one or a set of polygon features • Aquifer features can be grouped by HGUID

11. Hydro Features • Key attributes for feature identification • HydroID – Unique ID within the geodatabase (internal relationships) • HydroCode – Public identifier (external relationships) Pre Conference Seminar

12. HydroID • A new ID assigned to features in a Arc Hydro geodatabase • Uniquely identifies features with a geodatabase • Is used to manage relationships between features and to relate features with tabular data (e.g. time series) • Custom tool for managing HydroIDs Pre Conference Seminar

13. HydroCode links to external applications • Web interface for groundwater data in Texas • Texas Water Information Integration & Dissemination (WIID) Pre Conference Seminar

14. Aquifer and well • Well features are related to Aquifers: The AquiferID of a well feature is equal to the HydroID of an aquifer feature • An aquifer can be associated with one or more wells (1:M relationship) • Can take a different approach to support M:N relationship

15. Aquifer and well Well HydroID = 53

16. Wells and TimeSeries Well features are related with time series (water levels, water quality)

17. MonitoringPoint has time series Monitoring points are related with time series (streamflow, water quality, precipitation)

18. Integration of surface water and groundwater data The common framework supports analysis of surface water and groundwater data together Well in the Edwards Aquifer) Streamflow Gage at Comal Springs, New Braunfels Texas Pre Conference Seminar

19. Surface water groundwater linkage Relationships between surface water and aquifer enable analysis based on spatial and hydrologic relationships Streams over the outcrop = recharge features Pre Conference Seminar

20. Components • Geology - Representation of data from geologic maps • Wells and Boreholes – Description of well attributes and borehole data • Hydrostratigraphy – 2D and 3D description of hydrostratigraphy • Temporal – Representation of time varying data • Simulation – Representation of groundwater simulation models (focus on MODFLOW)

21. Geologic maps A geologic map is a cartographic product that portrays information about the geologic character of a specific geographic area • Groundwater features are closely tied to geology • Geologic maps vary in scale (continental, regional, local) • Provide a simple data structure to support mapping Geology Aquifers Maps from the United States National (http://nationalatlas.gov/).

22. Geologic map databases “A digitally-compiled collection of spatial (geographically referenced) and descriptive geologic information about a specific geographic area” (Geologic Data Subcommittee, Federal Geographic Data Committee 2006) • Standards for archiving geologic map data • Support the development of applications for automating map creation • Complex • Examples: • North American Geologic Map Data Model (NADM) • National Geologic Map Database (NGMDB) • State geologic map databases (e.g. Geologic Atlas of Texas) • ArcGeology

23. Geologic map databases Geodatabase design for storing data from the Geologic Atlas of Texas (http://www.tnris.org/news.aspx?id=244) Arc Geology: generic geologic map database implemented within ArcGIS (figure from Raines et al. 2007

24. Geology component GeologyPoint: Point feature (e.g. springs, caves, sinks, and observation points) GeologyLine: Line features (e.g. faults, contacts, and dikes) GeologyArea: Areal features (e.g. rock units and alteration zones) Map modified from: Geologic map of the Edwards Aquifer recharge zone, south-central Texas. U.S. Geological Survey SIM 2873 Pre Conference Seminar

25. Components • Geology - Representation of data from geologic maps • Wells and Boreholes – Description of well attributes and borehole data • Hydrostratigraphy – 2D and 3D description of hydrostratigraphy • Temporal – Representation of time varying data • Simulation – Representation of groundwater simulation models (focus on MODFLOW) Pre Conference Seminar

26. Well databases • Wells are basic features in groundwater databases • Attributes of wells describe its location, depth, water use, owner, etc. • Data are collected from drilling/construction reports and permits

27. Well databases • Well databases store information on wells and related data • Data are related to wells such as construction, water levels, water quality, and stratigraphy • Usually a central table is used to describe well features and other data are linked to it through key attributes (e.g. state well number) Relationships in the TWDB groundwater database Pre Conference Seminar

28. Well • The Well location is defined as a 2D point in the Well feature class • In the Arc Hydro model we only predefine a set of basic attributes Wells in the Edwards Aquifer Pre Conference Seminar

29. Borehole data • 3D data (screens, completion intervals, stratigraphy) is referenced along the well • From depth (top) – To depth (bottom)

30. BoreholeLog table • Used to store 3D borehole data related with well features • Each row in the table represents a point/interval along a borehole • Data are related with a Well feature through the WellID attribute • 3D geometry is defined by the TopElev and BottomElev attributes

31. 3D features (BorePoints and BoreLines) • Can create 3D features representing data in the BoreholeLog table • BorePoint is a 3D point feature class for representing point locations along a borehole (e.g. geologic contacts, samplers) • BoreLine is a 3D line feature class for representing intervals along a borehole

32. Components • Geology - Representation of data from geologic maps • Wells and Boreholes – Description of well attributes and borehole data • Hydrostratigraphy – 2D and 3D description of hydrostratigraphy • Temporal – Representation of time varying data • Simulation – Representation of groundwater simulation models (focus on MODFLOW)

33. Hydrogeologic units “Hydrogeologic unit is any soil or rock unit or zone which by virtue of its hydraulic properties has a distinct influence on the storage or movement of ground water” (USGS glossary of hydrologic terms) Hydrogeology can be derived by classifying stratigraphic units Hydrogeologic units Stratigraphic units Upper confining unit Georgetown Fm. Georgetown Fm. (GTOWN) Cyclic + Marine member (CYMRN) Pearson Fm. Leached + collapsed member (LCCLP) Edwards Aquifer Regional dense member (RGDNS) Grainstone member (GRNSTN) Kirschberg evaporite member (KSCH) Kainer Fm. Dolomitic member (DOLO) Basal Nodular member (BSNOD) Upper Glen Rose (UGLRS)

34. Hydrogeologic unit table • HydroGeologicUnit table provides a conceptual description of hydrogeologic units • Hydrogeologic units are with an AquiferID such that they can be grouped to represent an aquifer • Spatial features are indexed with a HGUID to relate to the conceptual representation of the units

35. Representations of hydrogeologic units • Different spatial representations of hydrogeologic with 2D and 3D objects • Workflow for creating 3D hydrogeologic models

36. Hydrogeologic unit table • Hydrogeologic units are described with different spatial instances (outcrops, borehole intervals, surfaces, cross sections, and volumes) • HGUID is the key attribute

37. HGUArea • 2D polygons defining boundaries of hydrogeologic units • HGUArea (conceptual/interpolated boundary) ≠ GeologyArea (mapped outcrop) GeologyArea features represent data from geologic maps GeologyArea Data points representing top elevations of the Kainer formation GeoArea feature representing the Kainer hydrogeologic unit

38. Representation of Cross Sections • SectionLinedefines the 2D cross section • GeoSection represent 3D sections as 3D polygons • SectionID of the polygon relates back to the section line A B’ B’ A’ Section B-B’ (HydroID 4667) A B B A’ GeoSection 4713 HGUID = 3

39. GeoRasters • Raster catalog for storing and indexing raster datasets • Can store top and bottom of formations • Each raster is related with a HGU in the hydrogeologic unit table Georgetown Person Kainer Glen Rose

40. K (feet/day) GeoRasters • GeoRasters also store hydraulic properties such as transmissivity, conductivity, and specific yield Raster of hydraulic conductivity in the Edwards Aquifer

41. GeoVolume • Objects for representing 3D volume objects • Geometry is multipatch

42. Georgetown Person Kainer GeoVolume • Can create the volumes as a set of 3D triangles • Not real volume – can’t do any 3D operations • Volumes in this example were generated in GMS and imported to the geodatabase Volumes in GMS GeoVolumes in the geodatabase

43. Components • Geology - Representation of data from geologic maps • Wells and Boreholes – Description of well attributes and borehole data • Hydrostratigraphy – 2D and 3D description of hydrostratigraphy • Temporal – Representation of time varying data • Simulation – Representation of groundwater simulation models (focus on MODFLOW)

44. Types of time varying datasets • Single variable time series – A single variable recorded at a location, such as stream discharge or groundwater levels • Multi variable time series – Multiple variables recorded simultaneously at the same location, such as chemical analysis of a water sample • Time varying surfaces (raster series) – Raster datasets indexed by time. Each rater is a “snapshot” of the environment at a certain time. • Time varying features (feature series) – A collection of features indexed by time. Each feature in a feature series represents a variable at a single time period.

45. Time series • The most basic case is a monitoring device recording values over time (e.g. monitoring well, streamflow gage) Monitoring Well (295443097554201) Sink Creek San Marcos springs Springs San Marcos San Marcos River Pre Conference Seminar

46. Time series Time (TsTime) • TimeSeries table is the basic table for storing time series data • Need to support: what, where, and when • Variables table defines variable objects Space (FeatureID) Variables (VariableID)

47. Time series • By querying the table we can create different data views (a) TsTime (b) TsTime (c) TsTime 2791 FeatureID FeatureID 2791 FeatureID 2 2 VariableID VariableID VariableID Pre Conference Seminar

48. Time series views – create time series graph • FeatureID of the time series = HydroID of the spatial feature (e.g. Well) Well HydroID = 2791

49. Time series views – map a variable at a given time Map a certain variable (e.g. water levels) at a given time (e.g. February 2004) Feet above mean sea level TsTime 2/2004 FeatureID 2 VariableID Pre Conference Seminar

50. Multi-variable time series • Data are indexed by space (FeatureID) and by time (TsTime) but instead of one variable we store multiple variables. • The column heading is the variable key (VarKey) Variables (VarKey) Pre Conference Seminar