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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.

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Arc Hydro Groundwater: a geographic data model for groundwater systems


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arc hydro groundwater a geographic data model for groundwater systems
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

research questions
Research questions
  • 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?
  • 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?
  • 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

outline
Outline
  • Introduction and data model goals
  • Arc Hydro groundwater data model design
  • Case studies (4 examples)
  • Conclusions
what is a data model
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

why do we need data models
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

arcgis geographic data models

Geosciences Network

ArcGIS Geographic data models

About 30 ArcGIS data models for a variety of disciplines

www.esri.com/datamodels

arc hydro surface water
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

goals of the arc hydro groundwater data model
Goals of the Arc Hydro groundwater data model

Objective

Develop a geographic data model for representing groundwater systems.

Data model goals

  • Support representation of regional groundwater systems.
  • Support the representation of site scale groundwater data.
  • Enable the integration of surface water and groundwater data.
  • Facilitate the Integration of groundwater simulation models with GIS.
regional groundwater systems
Regional groundwater systems
  • Describe groundwater systems from recharge to discharge
  • In many cases assumed as 2D systems, vertical scale >> horizontal scale

Eckhardt, G. Hydrogeology of the Edwards Aquifer. http://www.edwardsaquifer.net/geology.html

site scale data
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

integration of surface water and groundwater data
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...

integration of groundwater simulation models with gis
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)

outline13
Outline
  • Introduction and data model goals
  • Arc Hydro groundwater data model design
  • Case studies (4 examples)
  • Conclusions
full data model
Full data model
  • Hydrogeology – 2D and 3D features, tables, and rasters to describe hydrogeologic features such as wells, aquifers, cross sections, volumes, streams, land surface etc.
  • Simulation – Objects for georeferencing grids/meshes of simulation models.
  • Time Series – Temporal information stored in tables and as cataloged rasters.
framework data model
Framework data model

Core classes for representing spatial groundwater data

common data structures highlighted by the literature review
Common data structures highlighted by the literature review

Well

3D point data

Time series

3D interval data

representing well and aquifer features
Representing well and aquifer features

Core classes for representing spatial groundwater data

representation of wells and aquifers

HydroID

AquiferID

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

measurements along boreholes
Measurements along boreholes

Core classes for representing spatial groundwater data

representing measurements along boreholes

HydroID

WellID

Representing measurements along boreholes
  • Vertical data is stored in the VerticalMeasurements 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

3d geospatial context
3D geospatial context

Core classes for representing spatial groundwater data

3d geospatial context22

Land surface (GeoRasters)

GeoVolume

Boundary

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 geospatialcontext to groundwater data.

hydrogeologicunit table
HydroGeologicUnit table

Core classes for representing spatial groundwater data

hydrogeologicunit table24
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
time series
Time Series

Core classes for representing spatial groundwater data

time series26

Bromide (mg/l)

Arsenic (mg/l)

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

tools for implementing the data model
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

outline28
Outline
  • Introduction and data model goals
  • Arc Hydro groundwater data model design
  • Case studies (4 examples)
  • Conclusions
example 1 representing hydrostratigraphy in the north carolina coastal plain aquifer system
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.

creating wells and borelines
Creating wells and BoreLines

Tabular data: 496 wells with hydrostratigraphy

HydroID = 1137, Deppe station

www.ncwater.org

BoreLines representing hydrostratigraphy

interpolated data
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

example 2 regional scale 2d mapping of time series in the ogallala aquifer texas
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

wells in the ogallala aquifer
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

Data is from the TWDB groundwater database:

www.twdb.state.tx.us/GwRD/waterwell/well_info.asp

water level and water quality time series
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

geospatial views of time series using sql queries

Relationships between the tables

Aggregation by the well’s HydroID

Defines the criteria for the query (TSType, Date, and Aquifer)

Calculates the average water level for each well (feet above mean sea level)

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

geospatial views of time series to rasterseries
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

example 3 3d time series in the made site mississippi
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 36:637-650.

wells and borepoints

Wells with tracer data

BorePoints

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

spatial temporal views of 3d time series

Bromide (mg/L)

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

example 4 representing a gam model of the barton springs segment of the edwards aquifer texas

Confined zone of the Edwards aquifer

Unconfined zone of the Edwards aquifer

Model boundary

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

geospatially referencing the model
Geospatially referencing the model

Integrating the model within GIS requires creating a 3D geospatial reference system in which the model grid is represented

  • Define the model boundary
  • Create 2D cells and read attributes from model files (active cells, elevations)
  • Create 3D cells by extruding 2D cells
  • Create Nodes at the centroid of the 3D cells

(2)

(1)

(3)

(4)

temporally referencing the model

MODFLOW stress periods

Date time

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

  • Temporally reference model stress periods
  • Read stress data into Arc Hydro Time Series tables
  • Create geospatial views of stress data

Well discharge

Recharge

representing model results
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

creating water budgets
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

outline45
Outline
  • Introduction and data model goals
  • Arc Hydro groundwater data model design (focus on the framework)
  • Case studies (4 examples)
  • Conclusions
conclusions
Conclusions
  • 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.
conclusions47

Angle

Model origin

Conclusions
  • 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

conclusions48
Conclusions
  • 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