Hydrological Modeling of Lower Altamaha Basin

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HYDROLOGIC MODELING OF THE LOWER ALTAMAHA RIVER
BASIN
Multimedia Environmental Simulations
Laboratory Georgia Institute of Technology June
2001
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OUTLINE
1. Introduction 2. Distributed Hydrologic
Modeling 3. Data Requirements 4. Integration with
GIS 5. Lower Altamaha River Basin 6. Example
Application
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INTRODUCTION
Hydrological modeling involves the mathematical
simulation of the response (hydrograph) of an
hydrologic unit (basin, watershed) to an
hydrological event (precipitation)

• Classification of hydrologic models are based on
• process description
• scale
• solution technique

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• Combination

• Entirely random

• Entirely physical

Mixed Models
Stochastic Models
Deterministic Models
PROCESSES
Distributed Models
Lumped Models

• Spatial dimensions (X, Y, Z)

• No spatial dimension

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LUMPED vs. DISTRIBUTED MODELS
LUMPED SYSTEM
DISTRIBUTED SYSTEM

• Watershed averaged data
• Lumped description
• Low maintenance
• Black-box
• Highly Empirical

• Pixel-based data
• Distributed description
• High maintenance
• White-box
• Highly physical
• Spatial non-uniformity
• High requirements for data
• computer resources

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Hydrologic Modeling
SUBSURFACE
SURFACE
Unsaturated Zone Flow
Interception-Evapotranspiration
Infiltration
Saturated Zone Flow
Overland Flow
WATERSHED MODEL
Channel Flow
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Conservation of Mass Conservation of
Momentum Conservation of Energy
Governing Equations
WATERSHED PROCESSES
Output
Inputs
typically discharge, contaminant concentrations
Global Parameters Non-spatial Data Spatial Data

• Overland Flow Processes
• Subsurface Flow Processes
• Contaminant Transport

Initial and Boundary Conditions
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MAP ALGEBRA
MAP CALCULUS
vs.
Precipitation data map
Runoff data map
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DATA REQUIREMENTS

• Main Data Structures
• Raster
• Vector

Ref D. Tarboton
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GIS REPRESENTATION
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DATA SOURCES
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Scale and resolution is not necessarily similar!!!
Possible Other Data Sets
RESAMPLING
Pixel scale attribute data
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INTEGRATION WITH GIS

• Strong links between distributed modeling and GIS
• Increased availability of large amounts of
  spatial data requires suitable processing
  software
• Data analysis (pre- and post- processing)
• Numerical models running under GIS
• Visualization
• MESL using ArcView and ArcInfo
• Auxiliary software (Remote Sensing and Image
  Processing - ENVI)

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LOWER ALTAMAHA BASIN

• Entire Altamaha Basin
• drains about 1/4 of Georgia
• formed by Ocmulgee Oconee Ohoopee
• 3rd largest basin draining to Atlantic Ocean
• Lower Altamaha Basin
• located at the most downstream point
• area A 3,900 km2
• long term average annual precipitation P 45
  inch
• long term average Q 14,000 ft3/s
• average elevation E 50 m

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• administratively divided by 10 counties
• agricultural activities dominate
• total population (Census 1990)
• watershed 47,740 (0.7)
• 10 counties 185,144 (2.9)
• Georgia 6,478,149
• 0.7 of Georgia population
• total land area
• watershed 3,900 km2 (2.6)
• 10 counties 11,265 km2 (7.4)
• Georgia 152,800 km2
• 2.6 of Georgia land

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• Shaded relief of region ---gt Low lands of Georgia
• Topographically not complex but hydrologically is
• Highly vegetated
• Wetlands common in river banks coastal region
• Forests and pasture in other portions
• Mostly pristine (compared to other parts of
  Georgia)
• Common soil types Loam - Sand - Loamy Sand
• Agriculture dominated (Vidalia Onions)
• Forestry developed
• Main industrial establishments
• The Edwin Hatch Nuclear Power Plant (1630 MW)
  near Baxley
• Rayonier Pulp Mill at Jesup

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The Edwin Hatch Nuclear Power Plant near Baxley
on right side of Altamaha
Rayonier Pulp Mill at Jesup on right side of
Altamaha
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• Lower Altamaha river average slope 0.00018 m/m
• Gently meandering nature
• Acts like a conduit with no significant drainage
  area
• 150 km long corridor has an average width of 26
  km
• No major navigation activity

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Little Ocmulgee
Ocmulgee near Lumber City
Altamaha near Baxley
Altamaha Delta
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Typical River Channel Vegetation near Coastline
Agricultural land recovered from forest
vegetation in the backyard
Forest Clear Cut
Eutrophication in slow-running sections
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EXAMPLE APPLICATION

• SCS Curve Number Method
• runoff is a function of precipitation, initial
  abstraction and potential maximum retention

where Q runoff (inch) P precipitation
(inch) S potential maximum retention after
runoff begins Ia initial abstraction (inch)
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The parameter S is related to soil and cover
conditions of watershed through an hypothetical
parameter called CURVE NUMBER (CN).

• CURVE NUMBER is any number between 0 and 100 and
  is a function of
• Hydrologic Soil Group (A, B, C, D)
• Land Cover Type
• Land Treatment
• Antecedent Moisture Condition (Dry, Wet, Average)

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PIXEL LEVEL DATA SETS

• Application is coded in C
• Integrated with ArcView v3.2a
• User-friendly GUI

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Thank you...