arc hydro groundwater: a geographic data model for groundwater systems by gil strassberg, david...

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

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

Outline

1. Introduction and data model goals

2. Arc Hydro groundwater data model design

3. Case studies (4 examples)

4. Conclusions

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?

Proposed hydrologic observatories (CUAHSI):

• 26 proposed hydrologic observatories

• Data needs to be integrated across observatories and from

state and national data sources

1. Standardize:

• Concepts

• Data structures

• Terminology

2. Basis for development of applications

http://www.cuahsi.org/HO/prospectus_list.htm



ArcGIS Geographic data models

www.esri.com/datamodels

About 30 ArcGIS data models for a variety of disciplines

Geosciences Network

http://www.esri.com/datamodels

Arc Hydro surface water

A data model for representing surface water systems

Flow

Time

Time Series

Hydrography

Hydro Network

Channel System

Drainage System Flow

Time

Time Series

Flow

Time

Time Series

HydrographyHydrography

Hydro NetworkHydro Network

Channel SystemChannel System

Drainage SystemDrainage System

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

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.

Data model goals

Objective

Develop a geographic data model for representing

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

http://www.edwardsaquifer.net/geology.html

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

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

• 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)

Outline




4. Conclusions

Full data model

TableHydroGeologicUnit

TableVerticalMeasurements

Raster catalogGeoRasters

HydrogeologyFeature dataset

Polygon feature classAquifer

Subtypes are aquifer boundary, confined,unconfined, and aquitard boundary

Line feature classBoreLine

Point feature classBorePoint

Polygon feature classGeoSection

Polygon feature classGeoArea

Line feature classGeoLine

Point feature classGeoPoint

Point feature classWell

Line feature classWaterLine

Polygon feature classWaterArea

Multipatch feature classGeoVolume

Relationship class

One to many

WellHasBoreLines

Relationship class

One to many

WellHasBorePoints

Relationship class

One to many

AquiferHasWells

Objects related to hydrogeology that arein the geodatabse level (not within the

feature dataset)

Relationship class

One to many

Cell2DHasCell3D

Relationship class

One to many

Cell3DHasNodesPolygon feature classBoundary

Polygon feature classCell2D

Point feature class

Node

Multipatch feature classCell3D

SimulationFeature dataset

One to many

Raster catalogRasterSeries

TableTimeSeries

TableTSType

Relationship class

One to many

TSTypeHasTimeSeries

Temporal information

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.

Framework data model

Core classes for representing spatial groundwater data



Subtypes are aquifer boundary, confinedunconfined, and aquitard boundary




Relationship class

One to many

WellHasBoreLines

Relationship class

One to many

WellHasBorePointsRelationship class

One to many

AquiferHasWells

Geospatial context

Aquifers and wells Measurements in Boreholes

TableTimeSeries

TableTSType

Relationship class

One to many

TSTypeHasTimeSeries

Time Series

Polygon feature classBoundary



Hydrogeologic units


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

wellNot 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 interval data

3D point data Time series

Representing well and aquifer features








Relationship class

One to many

WellHasBoreLines

Relationship class

One to many


One to many

AquiferHasWells

Geospatial context


TableTimeSeries

TableTSType

Relationship class

One to many

TSTypeHasTimeSeries

Time Series




Hydrogeologic units


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

Aquifer Well

HydroID AquiferID

The AquiferID of well features is the HydroID of an aquifer (one to many relationship)

Measurements along boreholes








Relationship class

One to many

WellHasBoreLines

Relationship class

One to many


One to many

AquiferHasWells

Geospatial context


TableTimeSeries

TableTSType

Relationship class

One to many

TSTypeHasTimeSeries

Time Series




Hydrogeologic units


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

HydroID WellID

Well

VerticalMeasurements table

Well

BorePoint

BoreLine





Relationship class

One to many

WellHasBoreLines

Relationship class

One to many

WellHasBorePoints

3D geospatial context








Relationship class

One to many

WellHasBoreLines

Relationship class

One to many


One to many

AquiferHasWells

Geospatial context


TableTimeSeries

TableTSType

Relationship class

One to many

TSTypeHasTimeSeries

Time Series




Hydrogeologic units








Relationship class

One to many

WellHasBoreLines

Relationship class

One to many


One to many

AquiferHasWells

Geospatial context


TableTimeSeries

TableTSType

Relationship class

One to many

TSTypeHasTimeSeries

Time Series




Hydrogeologic units


3D geospatial context

GeoVolumes created by defining a Boundary on the land surface

(GeoRaster) and extruding the boundary area into the subsurface.

Boundary

Land surface (GeoRasters)GeoVolume

The GeoVolume, boundary, and the land surface provide

the geospatial context to groundwater data.

HydroGeologicUnit table








Relationship class

One to many

WellHasBoreLines

Relationship class

One to many


One to many

AquiferHasWells

Geospatial context


TableTimeSeries

TableTSType

Relationship class

One to many

TSTypeHasTimeSeries

Time Series




Hydrogeologic units


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

BoreLines

BorePoints

GeoVolume

GeoSection

GeoRastersBoreLines

BorePoints

GeoVolume

GeoSection

GeoRasters







Relationship class

One to many

WellHasBoreLines

Relationship class

One to many


One to many

AquiferHasWells

Geospatial context


TableTimeSeries

TableTSType

Relationship class

One to many

TSTypeHasTimeSeries

Time Series




Hydrogeologic units


Time Series








Relationship class

One to many

WellHasBoreLines

Relationship class

One to many


One to many

AquiferHasWells

Geospatial context


TableTimeSeries

TableTSType

Relationship class

One to many

TSTypeHasTimeSeries

Time Series




Hydrogeologic units


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







Relationship class

One to many

WellHasBoreLines

Relationship class

One to many


One to many

AquiferHasWells

Geospatial context


TableTimeSeries

TableTSType

Relationship class

One to many

TSTypeHasTimeSeries

Time Series




Hydrogeologic units


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

Outline




4. Conclusions

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

Tabular data: 496 wells with hydrostratigraphy

www.ncwater.org

HydroID = 1137, Deppe station

BoreLines representing hydrostratigraphy

http://www.ncwater.org/

Interpolated data

BorePoints created from wells and vertical measurements

GeoRasters representing top and bottom of a formation

Wells BoreLines

GeoSection

GeoVolume

GeoSection from GeoVolumes

Vertical measurements

Example 2 – Regional scale 2D mapping of time series in the Ogallala aquifer, Texas

Boundary of the Ogallala aquifer

http://www.npwd.org/new_page_2.htm

Boundary of the aquifer within Texas

http://www.npwd.org/new_page_2.htm

Wells in the Ogallala aquifer

Wells in the Ogallala aquifer

Wells categorized by water use

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

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.

Number of wells in each water use category

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

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

SQL (Structured Query Language) queries are used to join spatial

features (e.g. wells) with time series and summarize data values.

Relationships between the tables

Aggregation by the well’s

HydroID

Calculates the average water level for each

well (feet above mean sea level)

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

MS Access SQL query relating wells with time series

The query is embedded within ArcObjects to create geospatial-temporal views

of time series data

Average water level in 2000

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

Location of the MADE site Wells within 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 in the MADE site

Wells and BorePoints

Within the site there are two types of wells: multilevel samplers for

monitoring tracer concentrations and water level wells.

Wells with tracer data

BorePoints

Well features

BorePoints represent the multilevel sampling ports

148 water level monitoring wells and 245 multilevel sampling wells for monitoring tracer concentrations

Spatial-temporal views of 3D time series3D 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

Bromide (mg/L)

Isosurfaces created using ArcGIS 3D interpolation tools

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

Confined zone of the Edwards aquifer

Unconfined zone of the Edwards aquifer Model

boundary

Model is 1 layer, 120 by 120 cells each cell is 1000 x 500 feet

Geospatially referencing the modelIntegrating 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)

Temporally referencing the modelIn 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

MODFLOW stress periods Date time

Recharge Well discharge1. Temporally reference model stress periods

2. Read stress data into Arc Hydro Time Series tables

3. Create geospatial views of stress data

Representing model resultsSimulated heads are read into the Arc Hydro time series tables and can

be analyzed using GIS tools

Simulated head values are associated with model nodes

Raster of interpolated heads

Head contours

Outflow terms

Inflow terms

(a)

(b)

Creating water budgets

ZONEBUDGET is used to create water budgets for zones defined within GIS

Cells selected for defining a budget zone

Cells within the Barton Creek lower watershed

Water budget terms for the defined zone

Outline



(focus on the framework)


4. Conclusions

Conclusions1. 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?



Subtypes are Aquifer boundary, Outcroparea, Confined area




Relationship class

One to many

WellHasBoreLines

Relationship class

One to many


One to many

AquiferHasWells

Geospatial context


TableTimeSeries

TableTSType

Relationship class

One to many

TSTypeHasTimeSeries

Time Series




Hydrogeologic units


• 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.

Conclusions2. 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.

Model origin

Angle

Boundary Cell2D

Cell3D Node

Conclusions

3. What is the most efficient way to store, view, access, and analyze these features

using current GIS technology?

• 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

3D GIS

arc hydro groundwater: a geographic data model for groundwater systems by gil strassberg, david...

Documents

d data

groundwater studies

groundwater datadescribe

groundwater componentgoals

arcgis data models

geographic data modelswww

gisdefine data structures

groundwater features