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Hydrology of Fast Response Basins

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Title: Hydrology of Fast Response Basins


1
Hydrology of Fast Response Basins
  • Baxter E. Vieux, Ph.D., P.E.
  • School of Civil Engineering and Environmental
    Science
  • University of Oklahoma
  • 202 West Boyd Street, Room CEC334
  • Norman, OK 73019
  • bvieux_at_ou.edu

2
Biosketch
  • Dr. Baxter E. Vieux, PhD, PE specializes in the
    integration of computational methods and
    visualization with Geographic Information Systems
    (GIS). Applications include simulation of water
    quality and flooding. He was recently named
    Director of the International Center for Natural
    Hazards and Disaster Research, University of
    Oklahoma. Efforts to reduce impacts on civil
    infrastructures due to severe weather are being
    undertaken by this center with an initial focus
    on flooding. Prior to joining the faculty at the
    University of Oklahoma, he was a Visiting
    Assistant Professor at Michigan State University.
    He has performed consulting and collaborative
    research with agencies and private enterprises in
    the US and abroad in Japan, France, Nicaragua,
    and Poland. Over fifty publications appearing as
    book chapters (2), refereed journal articles (14,
    3 in press), and conference proceedings (35, 2 in
    press) have been authored including a forthcoming
    text for Kluwer entitled Distributed Hydrology
    Using GIS (expected 2000). He has been on the
    Editorial Board of Transactions in GIS since
    1995, serves on the American Society of Civil
    Engineers Council on Natural Hazards and
    Disasters, and is Fellow and member of the
    Advisory Council of the Cooperative Institute for
    Mesoscale Meteorological Studies at the
    University of Oklahoma. He is a member of ASCE,
    NSPE, AGU, and AMS, Tau Beta Pi, Phi Kappa Phi,
    and ASEE. Prior to his academic career, ten years
    were spent in Kansas and Michigan with the
    USDA-Natural Resources Conservation Service
    (formerly, USDA-SCS) supervising design and
    construction of drainage, irrigation, soil
    conservation, and flood control projects.

3
Recipe for a flood
  • Ingredients
  • Take a generous amount of rainfall
  • Presoak the soil so it is saturated
  • Add the rainfall to steeply sloping land
  • Look out!

4
Flood Statistics
  • Flooding is the most deadly and costly of all
    natural disasters.
  • Read the document Summary of Natural Hazard
    Statistics.
  • From this document what would you conclude to be
    the single most important factor that might cause
    death during a flood?

5
What constitutes a flash flood
  • No firm criteria exist to discriminate between
    fast response and river floods
  • Response time in the range of 1-6 hours
  • As opposed to river floods, flash floods have a
    quick response to rainfall input
  • Upland basins are most likely killers
  • Read the document flash floods.

6
Flooding
  • Last year natural disasters killed an estimated
    100,000 people.
  • In a typical year, floods claim half the victims
    of the worlds natural disasters.

--The Economist, 11March 2000
7
Enabling Technologies
  • Ingest, storage and processing of data streams
    from radar, satellite and other mesonet sensor
    systems
  • Radar, Mesonets, remote sensing platforms are
    next generation technologies providing new data
    and information for mitigating the impact of
    flooding and drought
  • Improved modeling, warning and information
    dissemination technologies

8
WSR-88D or NEXRAD
  • Weather Surveillance Radar-1988 Doppler
  • Prototyped in Norman at NSSL
  • Scans Every 5 or 6 minutes during precipitation
  • 150 installed in US and abroad

9
Why does one basin flood and another doesnt
  • Efficient drainage network
  • Debris clogged main channel
  • Denuded or burned vegetation
  • Urbanization effects on time and volume
  • Steep topography
  • Heavy rain over large areas
  • Read the document Flash Flood Factors.

10
Basin Characteristics
  • Factors that affect the basin response are
  • Drainage area
  • Drainage network
  • Slope
  • Channel geometry and roughness
  • Overland flow and roughness
  • Vegetative cover
  • Soil infiltration capacity
  • Storage capacity

11
Hydraulics
  • Hydraulics of overland and channel flow
  • Turbulent flow
  • Chezy or Manning
  • Conservation of momentum and mass
  • Discharge computations using conservation
    equations is the basis for distributed hydrologic
    modeling.

12
Hydraulics of Runoff
  • Two basic flow types can be recognized 
  • Overland flow  This is conceptualized as thin
    sheet flow before the runoff concentrates in
    recognized channels. 
  • Channel flow  The channel has hydraulic
    characteristics that govern flow depth and
    velocity. 

13
Runoff Mechanisms
  • There are two runoff producing mechanisms
  • Infiltration excess
  • Saturation excess
  • Mountainous watersheds tend to be dominated by
    saturation excess.
  • Infiltration excess dominates runoff in flatter
    agricultural watersheds.

14
Saturation Excess
15
Infiltration Excess
16
Horton Infiltration Equation
17
Probabilistic Concepts
  • Key concepts--
  • Intense rainfall happens infrequently
  • The return period is inversely proportional to
    the frequency of being equaled or exceeded.
  • Intensity-Duration-Area-Frequency

18
Regional Frequency Analysis
  • Using regression analysis applied to stream gauge
    records, we can estimate the discharge associated
    with a particular frequency.
  • Most states have developed regression equations
    for ungauged basins.
  • For example in Oklahoma given the drainage area,
    A, in sq.mi. and the 2-year 24-hour storm depth,
    I, in inches we can calculate

19
USGS Regression Equations for Oklahoma
  • For Cherokee County, the 2-year 24-hour rainfall
    is 3.5 inches. Calculate the following for the
    Cottonwood Basin
  • A 49 sq mi
  • I 3.5 inches

20
Lumped Versus Distributed
  • Lumped modeling represents the basin and
    precipitation characteristics using single values
    of roughness, slope, and rainfall over each
    sub-basin.
  • Distributed modeling represents the spatial
    variability within each sub-basin or basin using
    grid cells, TINS or other computational element.

21
Cottonwood CreekStorm Total Oct 30 - Nov 1, 1998
22
Cottonwood Watershed
23
Storm Total Contours
24
HEC-HMS Model
25
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26
Hydrograph
27
HEC-HMS 50-Year Storm
28
SCS CN increased from 79 to 90
29
Rainfall increased by 20
30
Runoff Simulation
31
Model Equations

OUTPUT
INPUT
Runoff
h
Land surface
32
Runoff Flow Rates
  • Depth h is measured perpendicular to the bed and
    the velocity, V is parallel to the landsurface.
  • Continuity equation
  • Manning Equation
  • n hydraulic roughness
  • So landsurface slope
  • c 1 for metric, 1.49 english

33
Blue River Basin
  • The 1200 km2 Blue River basin was delineated from
    a 3-arc second digital elevation model
  • Aggregated to grid cell size 270 m
  • Hydrographs simulated for each sub-basin
  • Runoff is computed for each grid cell
  • Routed downslope through each cell eventually
    reaching the stream network and basin outlet

34
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35
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36
Sensitivity to Initial Conditions
37
Distribute Model Advantages
  • Distributed has advantages because the spatial
    variability of precipitation input and
    controlling parameters are represented in the
    model.
  • Incorporating spatial variability in a
    distributed model reduces the prediction
    variance.
  • Physics-based models are generally more
    responsive to radar input than lumped models.
  • River basin models based on 6-hour unit
    hydrographs are not suitable for basins with
    response times less than 6 hours.

38
Self Examination
  • Label the following with a or according to
    the effect on flood levels at a given location
  • Debris clogged main channel
  • Denuded or burned vegetation
  • Urbanized landsurface conditions and channels
  • Steep terrain
  • Clayey soil
  • Dry intial moisture conditions

39
Questions...
--Ganges River Distributary, Bangladesh
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