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Arc Hydro Groundwater: a geographic data model for groundwater systems

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By Gil Strassberg, David Maidment and Norman Jones ... We are discussing with ESRI the transformation of this. work into an ESRI Press Book in 2007 ... – PowerPoint PPT presentation

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Title: Arc Hydro Groundwater: a geographic data model for groundwater systems


1
Arc Hydro Groundwater a geographic data model
for groundwater systems
By Gil Strassberg, David Maidment and Norman
Jones
These slides are taken from the PhD Dissertation
defense of Gil Strassberg in Nov 2005
Reference http//www.ce.utexas.edu/prof/maidment/
giswr2006/docs/strassberg.pdf
We are discussing with ESRI the transformation of
this work into an ESRI Press Book in 2007
This model won first prize for data models at the
2006 ESRI User Conference
2
Research questions
  1. What are the primary hydrogeologic features
    common to groundwater studies in regional and
    site scales, and what is the best conceptual
    approach for describing them?
  2. What are the basic features required for
    representing structures of groundwater simulation
    models, their inputs and outputs, and how can
    these structures be integrated within GIS?
  3. What is the most efficient way to store, view,
    access, and analyze these features using current
    GIS technology?

The data model design and implementation is the
process through which these questions are answered
3
Outline
  1. Introduction and data model goals
  2. Arc Hydro groundwater data model design
  3. Case studies (4 examples)
  4. Conclusions

4
What is a 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
5
Why do we need data models?
  • Proposed hydrologic observatories (CUAHSI)
  • 26 proposed hydrologic observatories
  • Data needs to be integrated across observatories
    and from state and national data sources
  • Standardize
  • Concepts
  • Data structures
  • Terminology
  • Basis for development of applications

http//www.cuahsi.org/HO/prospectus_list.htm
6
ArcGIS Geographic data models
About 30 ArcGIS data models for a variety of
disciplines
www.esri.com/datamodels
7
Arc Hydro surface water
A data model for representing surface water
systems
Published by ESRI press, 2002
Experience from the surface water data model
design provides basic design concepts for the
groundwater component
8
Goals of the Arc Hydro groundwater data model
Objective
Develop a geographic data model for representing
groundwater systems.
Data model goals
  1. Support representation of regional groundwater
    systems.
  2. Support the representation of site scale
    groundwater data.
  3. Enable the integration of surface water and
    groundwater data.
  4. Facilitate the Integration of groundwater
    simulation models with GIS.

9
Regional groundwater systems
  • Describe groundwater systems from recharge to
    discharge
  • In many cases assumed as 2D systems, vertical
    scale gtgt horizontal scale

Eckhardt, G. Hydrogeology of the Edwards Aquifer.
http//www.edwardsaquifer.net/geology.html
10
Site scale data
  • Describe groundwater data in a small area of
    interest.
  • Usually includes 3D data (e.g. multilevel
    samplers, cores).

Multilevel samplers in the MADE site in
Mississippi
Photographs provided by Chunmiao Zheng
11
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
In the future go to 3D...
12
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)
13
Outline
  1. Introduction and data model goals
  2. Arc Hydro groundwater data model design
  3. Case studies (4 examples)
  4. Conclusions

14
Full data model
  1. Hydrogeology 2D and 3D features, tables, and
    rasters to describe hydrogeologic features such
    as wells, aquifers, cross sections, volumes,
    streams, land surface etc.
  2. Simulation Objects for georeferencing
    grids/meshes of simulation models.
  3. Time Series Temporal information stored in
    tables and as cataloged rasters.

15
Framework data model
Core classes for representing spatial groundwater
data
16
Common data structures highlighted by the
literature review
Data type Public Petroleum Data Model (PPDM) ArcGIS Marine data model EarthFX data model Water Resources Information Project (WRIP) data model
Wells /Observation points 3D Line features with measures 2D point features (marine points) Borehole table 2D point features (3D lines are optional for display and are created from the attributes of the borehole)
3D interval data along a well Line events along the well Not included Tabular information related to the borehole Borehole interval sample table
3D point data along a well Point events along the well Measurement table with Z coordinates related to the marine point Tabular information related to the borehole Borehole point sample table
Temporal information Not available Time series related to measurements Time series related to intervals Time series related to borehole points or intervals
Well
3D point data
Time series
3D interval data
17
Representing well and aquifer features
Core classes for representing spatial groundwater
data
18
Representation of wells and aquifers
  • Wells are represented as 2D points with
    attributes describing the 3D geometry of the well
    (elevation, depth) and the related aquifer.
  • Aquifers are represented as 2D polygons with
    subtypes for confined, unconfined, and aquifer
    and aquitard boundaries

The AquiferID of well features is the HydroID of
an aquifer (one to many relationship)
Aquifer
Well
19
Measurements along boreholes
Core classes for representing spatial groundwater
data
20
Representing measurements along boreholes
  • Vertical data is stored in the VerticalMeasurement
    s table and tools are applied to create the
    spatial features.
  • BorePoint is a 3D point representing point data
    along a borehole.
  • BoreLine is a 3D line representing interval data
    along a borehole.
  • BorePoints and BoreLines are related to well
    features

Well
BorePoint
BoreLine
Well
VerticalMeasurements table
21
3D geospatial context
Core classes for representing spatial groundwater
data
22
3D geospatial context
GeoVolumes created by defining a Boundary on the
land surface (GeoRaster) and extruding the
boundary area into the subsurface.
The GeoVolume, boundary, and the land surface
provide the geospatial context to groundwater
data.
23
HydroGeologicUnit table
Core classes for representing spatial groundwater
data
24
HydroGeologicUnit table
  • Table for storing attributes of hydrogeologic
    units.
  • Hydrogeologic units represented in the table are
    linked to spatial features.
  • The HGUID field is the key attribute for linking
    spatial features with hydrogeologic units

25
Time Series
Core classes for representing spatial groundwater
data
26
Time Series
  • TSType - describes the type of time series
  • TimeSeries - stores time series related to
    features

Spatial-temporal views are created by linking
time series with spatial features
27
Tools for implementing the data model
  • Arc Hydro groundwater tools

ArcScene toolbar for creating three-dimensional
features such as BoreLines, GeoSections, and
GeoVolumes
  • MODFLOW geoprocessing tools

Geoprocessing tools to create Cell2D, Cell3D, and
Node features and integrate modflow inputs and
outputs into GIS
  • SQL based tools for creating spatial-temporal
    views of time series data

Link spatial features such as wells and
BorePoints with time series data to create 2D and
3D geospatial views of time series
28
Outline
  1. Introduction and data model goals
  2. Arc Hydro groundwater data model design
  3. Case studies (4 examples)
  4. Conclusions

29
Example 1 Representing hydrostratigraphy in the
North Carolina coastal plain aquifer system
Ten aquifers and nine confining units
Giese et al., 1997. Simulation of ground-water
flow in the coastal plain aquifer system of North
Carolina. USGS.
30
Creating wells and BoreLines
Tabular data 496 wells with hydrostratigraphy
HydroID 1137, Deppe station
www.ncwater.org
BoreLines representing hydrostratigraphy
31
Interpolated data
BoreLines
Wells
Vertical measurements
GeoSection
BorePoints created from wells and vertical
measurements
GeoVolume
GeoRasters representing top and bottom of a
formation
GeoSection from GeoVolumes
32
Example 2 Regional scale 2D mapping of time
series in the Ogallala aquifer, Texas
Boundary of the Ogallala aquifer
Boundary of the aquifer within Texas
http//www.npwd.org/new_page_2.htm
33
Wells in the Ogallala aquifer
Data is from the TWDB groundwater database. The
database contains tables describing well
locations and attributes, and water level and
water quality time series. There are about 21,000
wells designated in the Ogallala aquifer.
Wells in the Ogallala aquifer
Wells categorized by water use
Number of wells in each water use category
FType Description Count
10 MINING 1
6 FIRE 1
14 AQUACULTURE 1
5 POWER 2
11 MEDICINAL 10
3 COMMERCIAL 17
17 INSTITUTION 19
9 INDUSTRIAL (COOLING) 19
4 DEWATER 25
15 RECREATION 32
20 OTHER (see remarks) 32
0 Blank 324
12 INDUSTRIAL 385
1 AIR CONDITIONING 463
13 PUBLIC SUPPLY 1106
7 DOMESTIC 1817
16 STOCK 1928
18 UNUSED 2971
8 IRRIGATION 11824
Data is from the TWDB groundwater
database www.twdb.state.tx.us/GwRD/waterwell/well
_info.asp
34
Water level and water quality time series
Water levels and arsenic concentrations from the
TWDB database are imported into the Time Series
table of the data model. Two TSTypes are created
(1) for water levels, and (2) for dissolved
arsenic.
HydroID 1461
35
Geospatial views of time series using SQL queries
SQL (Structured Query Language) queries are used
to join spatial features (e.g. wells) with time
series and summarize data values.
Average water level in 2000
MS Access SQL query relating wells with time
series
The query is embedded within ArcObjects to create
geospatial-temporal views of time series data
36
Geospatial views of Time Series to RasterSeries
Spatial views of time series are interpolated
into rasters and stored and attributed in the
RasterSeries raster catalog
37
Example 3 3D time series in the MADE site,
Mississippi
Location of the MADE site
Wells within the MADE site
Wells in the MADE site
Harvey, C., and S. M. Gorelick. 2000.
Rate-limited mass transfer or macrodispersion
Which dominates plume evolution at the
Macrodispersion Experiment (MADE) site? Water
Resources Research 36637-650.
38
Wells and BorePoints
Within the site there are two types of wells
multilevel samplers for monitoring tracer
concentrations and water level wells.
148 water level monitoring wells and 245
multilevel sampling wells for monitoring tracer
concentrations
Well features
BorePoints represent the multilevel sampling ports
39
Spatial-temporal views of 3D time series
3D views of temporal information are created by
relating time series with BorePoint features with
SQL queries. These can then be interpolated to
create isosurfaces.
ArcScene application for creating views of 3D
time series
3D view of bromide concentrations
Isosurfaces created using ArcGIS 3D interpolation
tools
40
Example 4 Representing a GAM model of the
Barton Springs segment of the Edwards aquifer,
Texas
MODFLOW model developed for the TWDB as part of
the GAM program
Model is 1 layer, 120 by 120 cells each cell is
1000 x 500 feet
41
Geospatially referencing the model
Integrating the model within GIS requires
creating a 3D geospatial reference system in
which the model grid is represented
  1. Define the model boundary
  2. Create 2D cells and read attributes from model
    files (active cells, elevations)
  3. Create 3D cells by extruding 2D cells
  4. Create Nodes at the centroid of the 3D cells

(1)
(2)
(3)
(4)
42
Temporally referencing the model
In order to read data from modflow stress
packages into the Arc Hydro time series table,
modflow stress periods need to be referenced as
real dates
  1. Temporally reference model stress periods
  2. Read stress data into Arc Hydro Time Series
    tables
  3. Create geospatial views of stress data

Well discharge
Recharge
43
Representing model results
Simulated heads are read into the Arc Hydro time
series tables and can be analyzed using GIS tools
Raster of interpolated heads
Simulated head values are associated with model
nodes
Head contours
44
Creating water budgets
ZONEBUDGET is used to create water budgets for
zones defined within GIS
Cells selected for defining a budget zone
Water budget terms for the defined zone
Cells within the Barton Creek lower watershed
45
Outline
  1. Introduction and data model goals
  2. Arc Hydro groundwater data model design (focus on
    the framework)
  3. Case studies (4 examples)
  4. Conclusions

46
Conclusions
  1. What are the primary hydrogeologic features
    common to groundwater studies in regional and
    site scales, and what is the best conceptual
    approach for describing them?
  • The data model framework defines the core classes
    for representing spatial groundwater datasets.
    These include classes for representing data
    recorded at wells, aquifers, time series, and the
    3D geospatial context of the data.

47
Conclusions
  1. What are the basic features required for
    representing structures of groundwater simulation
    models, their inputs and outputs, and how can
    these structures be integrated within GIS?
  • To integrate simulation models with GIS the model
    has to be geospatially and temporally referenced.
    The feature classes in the simulation component
    include the model boundary, 2D and 3D cells, and
    model nodes.

Boundary
Cell2D
Cell3D
Node
48
Conclusions
  1. What is the most efficient way to store, view,
    access, and analyze these features using current
    GIS technology?

3D GIS
  • Combination of 2D features and related tables,
    and 3D features is most appropriate for managing
    3D information.
  • Time Series structures of Arc Hydro is
    appropriate for managing groundwater time series,
    and the combination with SQL queries is useful
    for creating spatial-temporal views of time
    series data.
  • Raster catalogs are useful to store, attribute,
    and index grids. GeoRasters are indexed by the
    HGUID to relate with a hydrogeologic unit, and
    RasterSeries are indexed by TSType and Date and
    Time.
  • XML is valuable for data exchange between
    applications
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