1. Arc Hydro Groundwater Data Model Gil Strassberg University of Texas at Austin

2. Pre Conference Seminar2 Outline Background: objectives, previous designBackground: objectives, previous design New design and books, FrameworkNew design and books, Framework Groundwater componentsGroundwater components ExamplesExamples

3. Pre Conference Seminar3 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

4. Pre Conference Seminar4 Developing a groundwater data model Groundwater data model (geospatial database) Time series observations Geologic maps Borehole data Geospatial vector layers Gridded data Numerical models Take a variety of spatial information and integrate into one geospatial database with a common terminology Better communication Integration of data Base for applications Hydrostratigraphy

5. Pre Conference Seminar5 Goals of the Arc Hydro groundwater data model Develop a geographic data model for representing groundwater systems. Objective: 1. 1.Support representation of regional groundwater systems. 2. 2.Support the representation of site scale groundwater data. 3. 3.Enable the integration of surface water and groundwater data. 4. 4.Facilitate the Integration of groundwater simulation models with GIS. Data model goals:

6. Pre Conference Seminar6 Regional groundwater systems Describe groundwater systems from recharge to discharge In many cases assumed as 2D systems, vertical scale >> horizontal scale

7. Pre Conference Seminar7 Site scale data Describe groundwater data in a small area of interest. Usually includes 3D data (e.g. multilevel samplers, cores). Photographs provided by Chunmiao Zheng Multilevel samplers in the MADE site in Mississippi

8. Pre Conference Seminar8 Integration of surface water and groundwater data Describe the relationship between surface water features ( e.g. streams and waterbodies) with groundwater features (aquifers, wells). Enable the connection with the surface water data model Hydro network Aquifers

9. Pre Conference Seminar9 Integration of groundwater simulation models with GIS Define data structures for representing groundwater simulation models within GIS. Support spatial and temporal referencing of model data – allows the display and analysis of model data within a “real” geospatial and temporal context. Focus on modflow as the standard model used in the groundwater community Non spatial representation (layer, row, column) Geospatial representation (x, y, and z coordinates)

10. Pre Conference Seminar10 Old design One big geodatabase with 3 conceptual components: Hydrogeology, Simulation, Temporal

11. Pre Conference Seminar11 Outline Background: objectives, previous designBackground: objectives, previous design New design and books, FrameworkNew design and books, Framework Groundwater componentsGroundwater components ExamplesExamples

12. Pre Conference Seminar12 New Design Better integrate surface water and groundwater Easier implementation Solution: 1. 1.One framework – including basic surface water and groundwater features 2. 2.Componentize the data model smaller thematic pieces

13. Pre Conference Seminar13 Network Components Framework Surface water components Drainage Hydrography Chanel Groundwater components Components can be added to the framework to represent specific themes in more detail Wells and boreholes Hydrostratigraphy Geology Simulation Temporal (enhanced) Temporal component

14. Pre Conference Seminar14 Two books Surface water Groundwater IntroductionIntroduction FrameworkFramework Space and Time (technical) 3D ArcGIS (technical) Hydro networks Geology Watersheds Wells and Boreholes River channels Hydrostratigraphy TemporalTemporal SimulationSimulation ImplementationImplementation

15. Pre Conference Seminar15 Framework Surface water features Groundwater features Time Series

16. Pre Conference Seminar16 Framework Aquifer Watershed Well MonitoringPoint Stream HydroPoint Waterbody Time Series

17. Pre Conference Seminar17 Surface water and groundwater Streamflow Gage at Comal Springs, New Braunfels Texas Well in the Edwards Aquifer (state well 6823302) In many cases collected and stored separatelyIn many cases collected and stored separately Store, visualize, and analyze in the same conferenceStore, visualize, and analyze in the same conference

18. Pre Conference Seminar18 Aquifer features Polygon features for representing aquifer boundaries and zones within them Map of major aquifers in Texas Edwards Aquifer

19. Pre Conference Seminar19 Aquifer features An aquifer is defined by one or a set of polygon features Aquifer features can be grouped by a hydrogeologic unit id (HGUID) FType for defining types of aquifer features

20. Pre Conference Seminar20 Well features Well 1729 State well number 6829103 Types of wells Wells represented as 2D point featuresWells represented as 2D point features Can be related with a certain AquiferCan be related with a certain Aquifer FType for defining types of wellsFType for defining types of wells

21. Pre Conference Seminar21 Hydro Features HydroID – Unique ID within the geodatabase (internal relationships) – Every feature in Arc Hydro is assigned a unique HydroIDHydroID – Unique ID within the geodatabase (internal relationships) – Every feature in Arc Hydro is assigned a unique HydroID HydroCode – Public identifier (external relationships)HydroCode – Public identifier (external relationships)

22. Pre Conference Seminar22 HydroCode links to external applications Web interface for groundwater data in TexasWeb interface for groundwater data in Texas Texas Water Information Integration & Dissemination (WIID)Texas Water Information Integration & Dissemination (WIID) The state well number becomes the HydroCode of the Well feature in Arc Hydro

23. Pre Conference Seminar23 Aquifer and well Well 1729 State well number 6829103

24. Pre Conference Seminar24 Wells and TimeSeries Well features are related with time series (water levels, water quality)

25. Pre Conference Seminar25 Surface water features Watershed – Polygon features for representing a drainage area Stream – Line features representing the path of flow as linear hydrographic features (blue lines on a map) Waterbody – Polygon features representing water bodies HydroPoint – Point features for representing any point hydrographic feature (diversion, spring, dam, etc.)

26. Pre Conference Seminar26 MonitoringPoint has time series Monitoring points are related with time series (streamflow, water quality, precipitation)

27. Pre Conference Seminar27 Surface water – groundwater linkage AquiferID is added to the surface water features Surface water and groundwater features can be linked through the AquiferID and HydroID attributes Work in progress –still trying to figure out exactly which relationships are needed

28. Pre Conference Seminar28 Surface water – groundwater linkage Relationships between surface water and aquifer enable analysis based on spatial and hydrologic relationships Stream reaches overlying an aquifer outcrop

29. Pre Conference Seminar29 Outline Background: objectives, previous designBackground: objectives, previous design New design and books, FrameworkNew design and books, Framework Groundwater componentsGroundwater components ExamplesExamples

30. Pre Conference Seminar30 Components Geology - mostly representation of data from geologic mapsGeology - mostly representation of data from geologic maps Wells and Boreholes – Description of well attributes and vertical data along wellsWells and Boreholes – Description of well attributes and vertical data along wells Hydrostratigraphy – 2D and 3D description of hydrostratigraphyHydrostratigraphy – 2D and 3D description of hydrostratigraphy Temporal - Representing time series dataTemporal - Representing time series data Simulation – Representation of groundwater simulation modelsSimulation – Representation of groundwater simulation models

31. Pre Conference Seminar31 Geology Features for representing data from geologic maps Data from USGS report: http://pubs.usgs.gov/sim/2005/2873/Caves Faults

32. Pre Conference Seminar32 Components Geology - mostly representation of data from geologic mapsGeology - mostly representation of data from geologic maps Wells and Boreholes – Description of well attributes and vertical data along wellsWells and Boreholes – Description of well attributes and vertical data along wells Hydrostratigraphy – 2D and 3D description of hydrostratigraphyHydrostratigraphy – 2D and 3D description of hydrostratigraphy Temporal - Representing time series dataTemporal - Representing time series data Simulation – representation of groundwater simulation modelsSimulation – representation of groundwater simulation models

33. Pre Conference Seminar33 Well Wells are the most basic features in groundwater databasesWells are the most basic features in groundwater databases Attributes of wells describe its location, depth, water use, owner, etc.Attributes of wells describe its location, depth, water use, owner, etc. In many cases these data are collected from driller reportsIn many cases these data are collected from driller reports

34. Pre Conference Seminar34 Well The Well location is defined as a 2D point in the Well feature classThe 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 attributesIn the Arc Hydro model we only predefine a set of basic attributes Wells in the Edwards Aquifer

35. Pre Conference Seminar35 Well FType is a coded value domainFType is a coded value domain Can add/delete based on project requirementsCan add/delete based on project requirements

36. Pre Conference Seminar36 Wells and 3D data 3D data is referenced along the well3D data is referenced along the well From depth (top) – To depth (bottom)From depth (top) – To depth (bottom) From To

37. Pre Conference Seminar37 Wells and Boreholes Vertical data (stratigraphy, casing) are related with wells 3D information is stored as tabular data in the VerticalMeasurements table Can create 3D features (points, lines) for visualization

38. Pre Conference Seminar38 Creating 3D displays We can create 3D displays of wells with the elevation and depth attributes of the well featureWe can create 3D displays of wells with the elevation and depth attributes of the well feature Land surface Extruded well features

39. Pre Conference Seminar39 3D features (BorePoints and BoreLines) Data on 3D intervals/points along the wellData on 3D intervals/points along the well Wells with hydrostratigraphic information

40. Pre Conference Seminar40 3D features (BorePoints and BoreLines) Original data is in text formatOriginal data is in text format Each data represents the top of a formation at one wellEach data represents the top of a formation at one well Data from USGS report: http://pubs.usgs.gov/sir/2004/5226/ http://pubs.usgs.gov/sir/2004/5226/

41. Pre Conference Seminar41 3D features (BorePoints and BoreLines) Data on 3D intervals/points along the well are stored in tabular formatData on 3D intervals/points along the well are stored in tabular format Data from the vertical measurements are related through the HydroID-WellID relationshipData from the vertical measurements are related through the HydroID-WellID relationship Well HydroID = 3266

42. Pre Conference Seminar42 3D features (BorePoints and BoreLines) Combining the well geometry (x, y) and the vertical measurements we can describe a set of 3D geometries (x, y, z)Combining the well geometry (x, y) and the vertical measurements we can describe a set of 3D geometries (x, y, z) 146 128 -60 41 -81 750 -140 -217 -372 -433 Georgetown Fm. (GTOWN) Cyclic + Marine member (CYMRN) Upper confining unit Leached + collapsed member (LCCLP) Regional dense member (RGDNS) Grainstone member (GRNSTN) Kirschberg evaporite member (KSCH) Dolomitic member (DOLO) Lower confining unit, upper Glen Rose (UGLRS)

43. Pre Conference Seminar43 3D features (BorePoints and BoreLines) BorePoints representing geologic contacts along wellsBorePoints representing geologic contacts along wells Each point represents the top of a hydrogeologic formationEach point represents the top of a hydrogeologic formation Well BorePoint Land surface

44. Pre Conference Seminar44 3D features (BorePoints and BoreLines) BoreLines representing intervals along wellsBoreLines representing intervals along wells Each line represents a hydrogeologic unit (top and bottom)Each line represents a hydrogeologic unit (top and bottom) Well HydroID = 3266 BoreLines for well 3266 BorePoints and BoreLines can also be used to represent other features along wells (construction, sampling ports, screens)

45. Pre Conference Seminar45 Components Geology - mostly representation of data from geologic mapsGeology - mostly representation of data from geologic maps Wells and Boreholes – Description of well attributes and vertical data along wellsWells and Boreholes – Description of well attributes and vertical data along wells Hydrostratigraphy – 2D and 3D description of hydrostratigraphyHydrostratigraphy – 2D and 3D description of hydrostratigraphy Temporal - Representing time series dataTemporal - Representing time series data Simulation – representation of groundwater simulation modelsSimulation – representation of groundwater simulation models

46. Pre Conference Seminar46 Geology to hydrogeology Georgetown Fm. (GTOWN) Cyclic + Marine member (CYMRN) Upper confining unit Leached + collapsed member (LCCLP) Regional dense member (RGDNS) Grainstone member (GRNSTN) Kirschberg evaporite member (KSCH) Dolomitic member (DOLO) Upper Glen Rose (UGLRS) Stratigraphic units Hydrogeologic units Pearson Fm. Basal Nodular member (BSNOD) Kainer Fm. Georgetown Fm. Edwards Aquifer Stratigraphic units are usually grouped into hydrogeologic unitsStratigraphic units are usually grouped into hydrogeologic units An aquifer can have a number of hydrogeologic unitsAn aquifer can have a number of hydrogeologic units Definition may change based on scale (local vs. regional) and purposeDefinition may change based on scale (local vs. regional) and purpose

47. Pre Conference Seminar47 Products and workflow

48. Pre Conference Seminar48 Hydrostratigraphy Spatial features Relates with spatial features representing instances of the HGU HydroGeologicUnit table provides a conceptual description of hydrogeologic units

49. Pre Conference Seminar49 HGUArea 2D polygons defining boundaries of hydrogeologic units Georgetown boundary Kainer boundary BorePoints representing top of hydrogeologic units

50. Pre Conference Seminar50 HGUArea A hydrogeologic unit can be represented by more than one HGUArea HGUArea is related to the hydrogeologic units in the table through the HGUID attribute HydroID = 4705 HydroID = 4706 HydroID = 4707

51. Pre Conference Seminar51 GeoSection 3D polygons representing cross sections SectionLine defines the 2D cross section line Section A-A’ (HydroID = 4666) Section line connecting a sequence of wells

52. Pre Conference Seminar52 GeoSection Each polygon is part of a section group defined by the SectionID The SectionID of the polygon relates back to the section line Section A-A’ (HydroID = 4666)

53. Pre Conference Seminar53 Georgetown Glen Rose Kainer Person GeoRasters Raster catalog for storing and indexing raster datasetsRaster catalog for storing and indexing raster datasets Can store top and bottom of formationsCan store top and bottom of formations Each raster is related with a HGU in the hydrogeologic unit tableEach raster is related with a HGU in the hydrogeologic unit table

54. Pre Conference Seminar54 GeoRasters GeoRasters also store hydraulic properties such as transmissivity, conductivity, and specific yieldGeoRasters also store hydraulic properties such as transmissivity, conductivity, and specific yield K (feet/day) Raster of hydraulic conductivity in the Edwards Aquifer

55. Pre Conference Seminar55 GeoVolume Objects for representing 3D volumesObjects for representing 3D volumes Geometry is multipatchGeometry is multipatch

56. Pre Conference Seminar56 GeoVolume Can create the volumes as a set of 3D trianglesCan create the volumes as a set of 3D triangles Not real volume – can’t do any 3D operationsNot real volume – can’t do any 3D operations Volumes in this example were generated in GMS and imported to the geodatabaseVolumes in this example were generated in GMS and imported to the geodatabase Georgetown Person Kainer Volumes in GMS GeoVolumes in the geodatabase

57. Pre Conference Seminar57 Derived GeoSections GeoSections can also be created by “cutting” through GeoVolumesGeoSections can also be created by “cutting” through GeoVolumes C-C’ D-D’ E-E’ GeoSections C-C’ D-D’ E-E’ Section lines on a 2D view of GeoVolumes Derived 3D GeoSections

58. Pre Conference Seminar58 Components Geology - mostly representation of geologic data from geologic mapsGeology - mostly representation of geologic data from geologic maps Wells and Boreholes – Description of well attributes and vertical data along wellsWells and Boreholes – Description of well attributes and vertical data along wells Hydrostratigraphy – 2D and 3D description of hydrostratigraphyHydrostratigraphy – 2D and 3D description of hydrostratigraphy Temporal - Representing time series dataTemporal - Representing time series data Simulation – representation of groundwater simulation modelsSimulation – representation of groundwater simulation models

59. Pre Conference Seminar59 Types of time varying datasets Single variable time series – A single variable recorded at a location, such as stream discharge or groundwater levelsSingle 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 sampleMulti 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 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.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.

60. Pre Conference Seminar60 TimeSeries and TSType Each measurement is indexed by space, time, and typeEach measurement is indexed by space, time, and type Space = FeatureIDSpace = FeatureID Time = TSDateTimeTime = TSDateTime Type = TSTypeIDType = TSTypeID FeatureID TSDateTime TSTypeID TSType provides information on the time series

61. Pre Conference Seminar61 Getting data views We can “slice” through the data cube to get specific views of the dataWe can “slice” through the data cube to get specific views of the data FeatureID TSDateTime TSTypeID 2791 FeatureID TSDateTime TSTypeID 2 FeatureID TSDateTime TSTypeID 2 2791 Query by location (FeatureID = 2791) Query by type (TSTypeID = 2) Query by location and type (FeatureID = 2791 TSTypeID = 2) Where? What? Where and What?

62. Pre Conference Seminar62 Data views Get all the data of TSType 2 measured at Feature 2791

63. Pre Conference Seminar63 Data views Well HydroID = 2791 FeatureID of the time series = HydroID of the spatial feature (e.g. Well)FeatureID of the time series = HydroID of the spatial feature (e.g. Well) TSTypeID relates to the TSType tableTSTypeID relates to the TSType table

64. Pre Conference Seminar64 TimeSeries Table A query by location (FeatureID) and type (TSTypeID)A query by location (FeatureID) and type (TSTypeID) Create a plot of time series related to a featureCreate a plot of time series related to a feature Well HydroID = 2791

65. Pre Conference Seminar65 Data views A type-time view: Get water levels (TSTypeID =2) for 2/2004 FeatureID TSDateTime TSTypeID 2 2/2004 Water level in the Edwards Aquifer in 2/2004 Set of layers for different times creates an animation

66. Pre Conference Seminar66 Multi-variable time series Multiple variables recorded simultaneously at the same location Indexed by location (FeatureID), and time (TSDateTime) Example – water quality parameters Variables

67. Pre Conference Seminar67 Multi-variable time series Can query for multiple variables together Well HydroID = 2833 New Braunfels Springs

68. Pre Conference Seminar68 RasterSeries Raster datasets indexed by timeRaster datasets indexed by time Each raster represents a continuous surface describing a variable for a given timeEach raster represents a continuous surface describing a variable for a given time January 1991 January 1992 January 1993

69. Pre Conference Seminar69 Feature Series A collection of features indexed by timeA collection of features indexed by time Example of particle tracksExample of particle tracks Features are indexed by TSType, TSDateTime, and GroupIDFeatures are indexed by TSType, TSDateTime, and GroupID Each group of features creates a track over timeEach group of features creates a track over time

70. Pre Conference Seminar70 Components Geology - mostly representation of geologic data from geologic mapsGeology - mostly representation of geologic data from geologic maps Wells and Boreholes – Description of well attributes and vertical data along wellsWells and Boreholes – Description of well attributes and vertical data along wells Hydrostratigraphy – 2D and 3D description of hydrostratigraphyHydrostratigraphy – 2D and 3D description of hydrostratigraphy Temporal - Representing time series dataTemporal - Representing time series data Simulation – representation of groundwater simulation modelsSimulation – representation of groundwater simulation models

71. Pre Conference Seminar71 Representing simulation models Georeference model inputs and outputs (in space and time) Focus on MODFLOW, block centered finite difference grid (nodes are in the center of the cells) Represent 2D and 3D models Block-centered finite difference grid Finite element grid Mesh-centered Finite difference grid

72. Pre Conference Seminar72 Simulation Features for representing data from simulation models Model origin Angle Boundary Cell2D Cell3D Node Cell2D Cell3DNode

73. Pre Conference Seminar73 Tools for read model inputs/outputs Example – Create water budgets for selected cells Water budget terms for the defined zone

74. Pre Conference Seminar74 Contact information gil.strassberg@beg.utexas.edugil.strassberg@beg.utexas.edugil.strassberg@beg.utexas.edu Demos