GIS in Environmental and Water Resources Engineering

1
GIS in Environmental and Water Resources
Engineering

• Research Progress Report
• Jan 15, 1999

2
Research Areas

• Texas data and water modeling Hudgens, Mason,
  Davis Jonsdottir, Gu, Azagra, Niazi
• Environmental Risk Assessment Hay-Wilson,
  Romanek, Kim

• Global runoff Asante, Lear
• Nonpoint source pollution Melancon, Osborne
• Flood hydrology and hydraulics Ahrens, Perales,
  Tate
• Internet Favazza,Wei

3
Research Areas

• Texas data and water modeling Hudgens, Mason,
  Davis Jonsdottir, Gu, Azagra, Niazi
• Environmental Risk Assessment Hay-Wilson,
  Romanek, Kim

• Global runoff Asante, Lear
• Nonpoint source pollution Melancon, Osborne
• Flood hydrology and hydraulics Ahrens, Bigelow,
  Perales, Tate
• Internet Favazza,Wei

4
Brad Hudgens

• Geospatial Data Development for Water
  Availability Modeling

5
Determining Watershed Properties

• Need to know at many points on a stream network
  the upstream drainage area, average precipitation
  and SCS CN value, and the downstream flow length
• Grids of these variables are computed using the
  flow accumulation function
• An attribute table is obtained using the Combine
  function

6
Weighted Flow Accumulation
AvgCNflowaccumulation(fdr, CN)CN
flowaccumulation(fdr)1
7
Combine Grids
GRID combine
8
David Mason

• Geospatial Data Development for Water
  Availability Modeling

9
Control Point Status

• FINALLY, Acquired all control points for Nueces
  and Guadalupe River basins
• STILL, Waiting for control points on the San
  Antonio River basin

10
Meanwhile..

• Finished development of a single-line stream
  network for all basins
• Attached control points with ID numbers to line
  network
• Obtained more clearly defined project goals
• Which watershed parameters are needed?
• Worked on streamlining database development
• Develop tools to automate the process

11
Trinity River TMDL

• Subtask on Network AnalystKim Davis

12
Jona Finndis Jonsdottir

• Geospatial Data for Total Maximum Daily Loads

13
New Tool Development for Water Modeling

• Richard Gu

14
Rainfall Runoff in the Guadalupe River Basin
Esteban Azagra
15
Objectives

• Run HEC-PrePro and HMS programs for a sample
  area.
• Comparison of the runoff with field data.
• Calibration of the modeling system.

16
What have I done?

• Run HEC-PrePro and HMS.
• Analysis of parameters.
• Comparison of the model with field data

17
Analyzing Parameters

• For Vx constant D X 20
• D flow _at_ 3.7
• For X constant D VX _at_ 20
• D flow _at_ 28
• Use of Manning to change the values of VX

18
Comparison and Future work

• Precipitation data used for HMS showed big
  differences between the model and the field data.
• The use of NEXRAD Precipitation could help for a
  more detailed comparison.

19
Surface/Subsurface Modeling

• By Shiva Niazi
• 1/15/99

20
GMS Model
21
Argus ONE Model
22
Argus ONE vs. GMS

• Argus ONE
• Can create interface within software- inc.
  built-in functions
• Must manually create boundary, river arcs?

• GMS
• Supports more MODFLOW packages
• Time consuming

23
Research Areas

• Texas data and water modeling Hudgens, Mason,
  Davis Jonsdottir, Gu, Azagra, Niazi
• Environmental Risk Assessment Hay-Wilson,
  Romanek, Kim

• Global runoff Asante, Lear
• Nonpoint source pollution Melancon, Osborne
• Flood hydrology and hydraulics Ahrens, Bigelow,
  Perales, Tate
• Internet Favazza,Wei

24
Lesley Hay Wilson

• Spatial Environmental Risk Assessment

25
Current Research Status

• Completed dissertation proposal defense on Dec
  11th
• Objective is to develop the spatial risk
  assessment methodology with emphasis on
  application to large, complex sites
• Working on the site conceptual model and linkages
  between Access and ArcView

26
Risk Assessment Data Model
Forward Risk Estimation
Cross-media pathways
Receptor
Source
Human, Ecological
Geographic pathways
Target Level Calculation
27
Research ApproachSpatial Site Conceptual Model

• Spatial representations of the site conceptual
  model elements (e.g., sources, receptors)
• Individual data layers for each element
• Supported by
• database of exposure pathway components
• spreadsheet of transport and transfer algorithms
• grid-based models
• Implemented in a tiered approach

28
Connection of SCM Database and RBSL Spreadsheets
Identify COC Pathway Segments Source
Concentrations
Excel Spreadsheet Perform simple fate and
transport calculations
ODBC
Access Site Conceptual Model Database
Link
Pathway Endpoint Concentrations
29
Other Activities

• Marcus Hook Project team meetings completed Jan
  11-13th (team)
• EWRE seminar presentation of dissertation
  proposal scheduled for Jan 20th

30
Andrew Romanek

• Surface Representation of the Marcus Hook Refinery

31
Activities

• 3 day meeting with BP, Langan, UT, and others
  (Mon. - Wed.)
• Update of progress
• Delineation of future tasks
• COC Transport Extension
• Thesis

32
COC Tranport Extension

• Surface water model extension to predict
  concentrations
• Steady state, conservative, mixing model (only
  decreases in concentration from additional flow)
• Initial attempt yielded a maximum benzene
  concentration of 0.26 mg/L

33
Thesis

• Intro to risk assessment and project
• Digital Facility Description
• Spatial and Tabular Databases
• Data development (Photogrammetry)
• Connection between Spatial and Tabular
• Map-Based Modeling
• Surface and Groundwater models

34
Spatial Analysis of Sources and Source Areas on
Marcus Hook

• Progress report by Julie Kim
• Friday, November 20, 1998

35
Research Areas

• Texas data and water modeling Hudgens, Mason,
  Davis Jonsdottir, Gu, Azagra, Niazi
• Environmental Risk Assessment Hay-Wilson,
  Romanek, Kim

• Global runoff Asante, Lear
• Nonpoint source pollution Melancon, Osborne
• Flood hydrology and hydraulics Ahrens, Bigelow,
  Perales, Tate
• Internet Favazza,Wei

36
Global Runoff RoutingEstimating Flow Velocity
Kwabena Asante
37
Methods

• Lag Between Runoff Stations
• Lag Between Rainfall and Runoff
• Empirical Methods

38
Rainfall Distribution in November
39
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Empirical Equations
Generally of the form P a Q b
Leopold and Maddock (1953) a 1.3, b
0.1 Matalas (1969) a 1, b 0.155
41
Grid Cell Translation from High to Low Resolution

• Mary Lear
• November 20, 1998

42
Research Areas

• Texas data and water modeling Hudgens, Mason,
  Davis Jonsdottir, Gu, Azagra, Niazi
• Environmental Risk Assessment Hay-Wilson,
  Romanek, Kim

• Global runoff Asante, Lear
• Nonpoint source pollution Melancon, Osborne
• Flood hydrology and hydraulics Ahrens, Bigelow,
  Perales, Tate
• Internet Favazza,Wei

43
Patrice Melancon

• Pollutant Loading Model for Tillamook Bay

44
Flow Contribution
Distribution matches values reported for the
watershed
45
Flow vs Load Contribution by Landuse
46
Concentration Profiles
47
Katherine Osborne

• Water Quality Master Planning for Austin

48
Research Areas

• Texas data and water modeling Hudgens, Mason,
  Davis Jonsdottir, Gu, Azagra, Niazi
• Environmental Risk Assessment Hay-Wilson,
  Romanek, Kim

• Global runoff Asante, Lear
• Nonpoint source pollution Melancon, Osborne
• Flood hydrology and hydraulics Ahrens, Bigelow,
  Perales, Tate
• Internet Favazza,Wei

49
Seth Ahrens

• Flood Forecasting in Houston

50
Rainfall Data Benefits of MATLAB over Visual
Basic
Lat. Lon. Rf.
Time (min)
Rf. (mm)
Program A
Program B
Time interval is inconsistent.
Final output is an ArcView ASCII grid in the
proper projection.
All data in one grid in ten-minute intervals.
Each time interval in own file.
Benefits Can now more efficiently prepare
rainfall data. Original technique incorporated
Visual Basic in Excel. Though it worked, the
method proved to be cumbersome, error-prone
(relied too much on user), and time-consuming.
51
Creating Animated Rainfall Maps

• Program available from www.ulead.com or
  ganges\ahrens\research\bin\animation\
• Install ga20tu program on c\temp.
• Animation program only requires frames (i.e. Gif
  files) and the time interval between frames.
• Full directions on my web site after CE server is
  fixed.

52
Sample Animation Map
Time
Incremental (left) data give insight as to how
much rain has fallen in a particular area in the
ten minutes prior to the time in the
lower-left-hand corner. The cumulative (right)
information, meanwhile, allows the user to get a
better idea how much total rain fell over the
area of interest.
N.B The incremental data range from about 0.5
in/hr to 6.0 in/hr while the cumulative data
range from 0.5 in to 8.0 in.
Incremental
Cumulative
53
Jerry Perales

• GIS-Based Infiltration Modeling

54
Eric Tate

• Mapping Flood Water Surface Elevation

55
Map-Based Hydrology and Hydraulics
ArcView Input Data DEM
ArcView Flood plain maps
CRWR-PrePro
AvRAS
HEC-RAS Water surface profiles
HEC-HMS Flood discharge
56
Flood Plain Mapping
57
Real-time flood emergency mapping
Nexrad radar rainfall input
Real time
Precomputed flood map library
Offline
Flood hydrology analysis system
58
Research Areas

• Texas data and water modeling Hudgens, Mason,
  Davis Jonsdottir, Gu, Azagra, Niazi
• Environmental Risk Assessment Hay-Wilson,
  Romanek, Kim

• Global runoff Asante, Lear
• Nonpoint source pollution Melancon, Osborne
• Flood hydrology and hydraulics Ahrens, Bigelow,
  Perales, Tate
• Internet Favazza,Wei

59
David Favazza

• Map-Based Modeling on the Internet

60
(No Transcript)
61
(No Transcript)
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(No Transcript)
63
Kevin Wei

• Displaying Environmental Maps on the Internet

64
Research Review

• Next Research Progress Report
• Friday Dec18, 1998, 2PM, ECJ 9.236