Flood Modeling in a Mountain Environment: A Case Study on the Watauga River in Western North Carolin - PowerPoint PPT Presentation

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Flood Modeling in a Mountain Environment: A Case Study on the Watauga River in Western North Carolin

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Title: Flood Modeling in a Mountain Environment: A Case Study on the Watauga River in Western North Carolin


1
Flood Modeling in a Mountain Environment A Case
Study on the Watauga River in Western North
Carolina A Chocolate Friday Presentation By
J. Greg Dobson GIS Research Associate NEMAC UNC-As
heville Sept. 22, 2006
2
  • Introduction
  • Flood disasters have grown significantly
  • Much research has been devoted to this topic,
    however very little accomplished in mountain
    environments
  • Focus has been to model the vertical height of a
    flood and not the horizontal extent
  • Several key issues arise including data
    availability, resolution, source

3
  • Background
  • Hurricane Floyd in 1999 brought forth the
    realization that NC floodplain maps were
    out-of-date
  • North Carolina Floodplain Mapping Program (NCFMP)
    was developed and charged with updating the
    floodplain maps
  • LIDAR data were acquired to serve as the
    elevation data

4
  • Purpose and Objectives
  • Apply integration of a GIS and a hydraulic model
    to test accuracy and utility of different
    elevation sources and resolutions
  • Determine availability of data and feasibility of
    data collection in a mountain environment and
    develop alternative methods for data collection

5
  • Hypotheses
  • Use of the highest-resolution LIDAR derived
    elevation data would yield most accurate flood
    modeling results
  • Hydraulic model parameters would have a
    significant influence on generating accurate
    water surface profiles

6
  • Geographic Setting
  • Section of the Watauga River
  • September 2004 floods due to remnants of
    Hurricanes Frances and Ivan
  • The Ivan flood
  • Second highest recorded flood level (64 years)
  • Peak discharge of 23,000cfs (average 195cfs)

7
Sugar Grove USGS Gauging Station Typical Flow /
Near Peak Flow
Photo Source Mike Mayfield
8
Hwy 321 Bridge Typical Flow / Near Peak Flow
Photo Source Baker Perry
9
  • Data Acquisition
  • - Elevation Data
  • Digital Terrain Models (DTMs)
  • Digital Elevation Models (DEMs)
  • Triangulated Irregular Networks (TINs)
  • Sources
  • NCFMP Light Detection and Ranging (LIDAR) data
  • United States Geological Survey (USGS) standard
    USGS DEM data

10
  • Elevation Data Pre-Processing
  • Data Source and Data Resolution
  • LIDAR Data Resolutions
  • 6.1m (20ft)
  • 10m (33ft)
  • 15.2m (50ft)
  • 30m (98ft)
  • USGS Data Resolutions
  • 10m (33ft)
  • 30m (98ft)

11
  • LIDAR Elevation Data Pre-Processing

12
  • Resulting TIN Surfaces
  • The mass LIDAR points were also converted
    directly to a TIN surface

The mass TIN
The USGS 30m TIN
13
  • Resulting TIN Surfaces
  • Detail view of TIN surfaces

The mass TIN
The USGS 30m TIN
14
  • Hydraulic Modeling
  • A three step process
  • Create Geometric Data in ArcGIS with the
    HEC-GeoRAS extension
  • HEC-RAS Model Simulation
  • Display HEC-RAS Flood Simulation Results

Model Simulation
Input Data
Output Data
15
Model Calibration
16
  • Diagnostic Procedures
  • Area and Volume Calculations
  • Area from the water surface profiles
  • Volume from the depth grids
  • Percent Error
  • Compares shapes of the water surface profiles to
    the profile created from the highest-resolution
    data
  • Error Area (Poly) Area (REFPoly) 2X
    (Poly intersected with REFPoly)
    Area (REFPoly)
    X100

17
Percent Error Calculation Results
18
Volume Calculation Results
19
Visual Assessments Water Surface Profile from
the LIDAR mass 6.1m data
20
Visual Assessments Water Surface Profile from
the LIDAR 6.1m data
21
Visual Assessments Water Surface Profile from
the LIDAR 10m data
22
Visual Assessments Water Surface Profile from
the USGS 10m data
23
Visual Assessments Water Surface Profile from
the LIDAR 15.2m data
24
Visual Assessments Water Surface Profile from
the LIDAR 30m data
25
Visual Assessments Water Surface Profile from
the USGS 30m data
26
Visual Assessments Water surface profiles with
high-water mark data and transect lines
USGS 30m data water surface profile
LIDAR Mass 6.1m data water surface profile
27
Visual Assessments 3D View of water surface
profiles with the DOQQ in the background draped
over the respective TIN
USGS 30m data water surface profile
LIDAR 30m data water surface profile
28
  • Conclusions
  • Elevation Data resolution and source were
    important factors for flood modeling in mountain
    environments
  • Adjustment of hydraulic model parameters did not
    have a significant influence on model outputs
  • The use of multiple diagnostic procedures was
    useful in order to make appropriate assessments

29
  • Further Research
  • Analyze different flood events
  • Comparative analysis between the coastal plains
    and mountains
  • Perform similar analysis on other watersheds in
    mountain environments

30
QUESTIONS?
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