Hydrological Systems as a Three Dimensional Surface: Toward a Predictive Spatial Model for the Aquatic/Terrestrial Transition Zone

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Hydrological Systems as a Three Dimensional
Surface Toward a Predictive Spatial Model for
the Aquatic/Terrestrial Transition Zone
Kevin Kane
Animal Ecology 518, Stream Ecology Iowa State
University
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OR
(You thought you had heard the end of it, but
no...)
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The Mr. Potatohead Hydrologic Model (MPHM)
What a Spud Can Teach Us About Modeling Spatial
Relationships to Predict the ATTZ Ecology
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Study Hypothesis

• Prediction of the Aquatic/Terrestrial Transition
  Zone ecology is possible through modeling spatial
  variables on a three dimensional flow surface.

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Study Definitions
Spatial Variables Any variables that affect the
ecology of the Aquatic/Terrestrial Transition
Zone.
Aquatic/Terrestrial Transition Zone Any place on
the surface of the earth.
Model Simplified Mathematical formulations that
mimic real-world phenomena so that complex
processes can be understood and predictions made.

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Topics of Discussion

• Summarize three stream models presented in class.
  
• Revisit Mr. Potatohead analogy.
• Introduce a drainage model based on runoff as a
  surface.
• Illustrate the interdependence of spatial
  variables using raster GIS as a modeling tool for
  rivers and watersheds in Iowa.
• Show how the results of this model can predict
  ATTZ ecology.

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Introduction

• Spatial relationships of climatic, terrestrial,
  and hydrological variables contribute to a runoff
  flow pattern. This pattern is not only linear,
  as viewed in the River Continuum Concept, nor
  only limited to the floodplain as in the Flood
  Pulse Concept.
• It should be viewed as a three dimensional
  surface where each square centimeter of the earth
  is affected by the hydrologic cycle, thus having
  tremendous potential bearing on the stream
  network and the environment that this runoff
  creates (the ATTZ).

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Review

• Three Class Models
• River Continuum Concept
• Flood Pulse Concept
• Hydologic Variability
• The Mr. Potatohead Analogy (MPA)

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River Continuum Concept (Vannote, et. al., 1980)

• The physical basis of the RCC is
• Size of the river or stream (stream order)
• Location along the stream gradient
• Four important physical parameters are
• Current
• Substrate
• Temperature
• Dissolved oxygen
• Physical parameters of a stream define
• Structure of the biotic component
• Diversity of the biotic component

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River Continuum Concept
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Flood Pulse Concept (Junk, et. al., 1989)

• Identifies the predictable advance and retraction
  of water on the floodplain of a pristine system
  as the principal agent controlling the
  adaptations of most of the biota.
• The flood pulse is not a disturbance instead,
  significant departures from the average
  hydrological regimen, such as the prevention of
  floods, should be regarded as a disturbance.

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Flood Pulse Concept

• The flood pulse is postulated to enhance
  biological productivity and maintain diversity in
  the system. The principal agents associated with
  this typically annual process are plants,
  nutrients, detritus, and sediments (next figure).
  

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Flood Pulse Concept
Schematic of the flood-pulse concept (derived
from Junk et al. 1989) showing a vertically
exaggerated section of a floodplain in five
snapshots of an annual hydrological cycle.
Right-hand column indicates typical
life-history traits of fish. DO dissolved
oxygen
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Hydrologic Variability (Poff and Ward, 1989)

• Factors
• Flow variability
• Flood regime patterns
• Intermittency
• Reasonable geographic affiliation
• Constrains ecological and evolutionary processes
  in streams
• Prediction based on constraints

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Hydrologic Variability Example
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So...

• Each of these models deal with spatial
  variability in some way
• Each models and predicts an aquatic environment
  although limited in its extent
• Which brings us back to

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The Mr. Potatohead Analogy (MPA)

• The ATTZ (Mr. Potatohead) can be described and
  modeled by many factors (spatial variables -
  different eyes, ears, noses, etc.)
• The sum total of these variables can predict and
  describe the ecology of the ATTZ at any
  particular point on the surface of the earth
  (what Mr. Potatohead ultimately looks like).

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Spatial Variables for Prediction
Climate Vegetation Topography Geology Land
use Soil characteristics
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Expanding the Boundaries...
?
Diagram of the relative position of geomorphic
features along streams (modified from Hupp, 1986).
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To The Entire ATTZ

• Outside the stream
• Outside the floodplain
• Looking at the earth as a Hydrologic Surface

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Study Area Scott County, Iowa
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Alluvium
Scott Co.
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Scott County Study Site
Data Sets Alluvium Soil Drainage Scott Co.
Rivers
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Dixon Quadand StudySite
Data Sets Alluvium Soil Drainage Scott Co.
Rivers
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Study factors and assumptions

• Proximity
• The closer, the more holding of water
• Slope and Aspect
• Speed to stream (flow), and drying of land
• Hydric conditions
• wetlands, hydric soils, and permeability

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Quantitative Spatial Modeling Using GIS
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Study Definitions

• GIS Coverage
• a data set containing spatial data georeferenced
  to the earth
• Vector Data
• a GIS coverage of points, lines and polygons
• Raster Data
• a GIS coverage of cells (matrix)
• DEM (digital elevation model)
• a raster data set that models the surface of the
  earth

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GIS Data Models
Raster
Vector
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Raster GIS Data
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Analysis MethodsCoverages, Cells, Matrix Math
Vector Cov.
Drainage
Wetland
Sum
Raster Cov.


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Proximity to Hydrologic Features
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Proximity Hypothesis

• Prediction of the Aquatic/Terrestrial Transition
  Zone ecology is possible through modeling spatial
  variables on a three dimensional flow surface.
• The potential for water flow across an area is
  one spatial variable that can be modeled for
  predicting the ATTZ ecology.
• The amount of water available on a piece of land
  can be a predictor of possible habitat.

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Distance toAlluvium
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Distance to100K Rivers
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Distance toWetlands
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Distance to Soil Drainages
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3 Class Proximity Calculations

Alluvium
100K Rivers
Wetlands
Soil Drainages
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Proximity Calculations
1. Add data set River82 2. Compute proximity
(Find Distance) using quad boundary as clip
coverage 3. Clip to study area (Map Calculation
using ( Site Distance to Riv82)) to temp
data set 4. Reclassify continuous surface to 3
discrete values using equal interval
classification
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Final Straight Proximity Maps
( Drain Dist3 nwi82 dist3 Riv82 Dist3
Alluvium Distance 3)
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3 Class Weighted Proximity Calculations
Wetlands -3

Soil Drainages - 4
Alluvium -1
100K Rivers - 2
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Final Weighted Proximity Maps
( (Drain Dist34) (nwi82 dist33) (Riv82
Dist32) Alluvium Distance 3)
3 Classes
30 Classes
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Straight vs. Weighted Prox. Maps
( (Drain Dist34) (nwi82 dist33) (Riv82
Dist32) Alluvium Distance 3)
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Results of Proximity Analysis

• Models where water on the landscape is most
  likely to flow and in what relative amounts.
• Allows prediction of species habitat.

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Topography
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Topography Hypothesis

• Prediction of the Aquatic/Terrestrial Transition
  Zone ecology is possible through modeling spatial
  variables on a three dimensional flow surface.
• The holding potential, speed, and direction of
  water flow in an area is one spatial variable
  that can be modeled for predicting the ATTZ
  ecology.
• The holding potential, speed, and direction of
  water flow on a piece of land can be a predictor
  of possible habitat.

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Elevation from DEM
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ShadedRelief ofElevation
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Dixon QuadSlope
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Study Area Slope
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Slope from Soils
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Slope DEM vs. Soils
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Results of Topography Analysis

• Models the holding potential, speed, and
  direction of water flow in an area.
• Allows prediction of species habitat.

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Many other variables can be modeled including...
Climate FHydrology Vegetation
FTopography Geology Land use Soil
characteristics
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So what?

• Each of these spatial variables will be used as
  input to a final composite model for a site.
• From the output of this model, we will get a
  predictive map of what the ATTZ looks like for
  every cell in our study area.
• If the hypothesis is correct, a prediction can
  be made about the life forms that particular
  cell will support.

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Whats Next?

• The next step is to collect physical, chemical,
  and biological data for sites in the area.
• We can then associate and callibrate our model
  with this data.
• We will then use the model for undocumented sites
  to see how well our predictive model has worked.
• How will climate work in model?

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Summary

• The ATTZ ecology is very dependent on the
  physical and chemical factors of the water that
  flows through it.
• A specific stream environment is very dependent
  upon the spatial distribution of these factors in
  the watershed.
• The interdependence of these spatial variables
  and their analysis can predict a given stream
  environment and the ATTZ.

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Presentation References

• Allan, J.D. 1995. Stream Ecology -- Structure
  and Function of Running Waters. Chapman and
  Hall, UK.
• Vannote, RL, GW Minshall, KW Cummins, JR Sedell,
  and CE Cushing (1980) The River Continuum
  Concept. Can. J. Fish. Aquat. Sci. 37130-137.
• Bayley, Peter B., Understanding Large
  River-Floodplain Ecosystems, Bioscience Vol. 45
  No. 3, March 1995

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References (cont.)

• WEB SITES
• Mr. Potatohead, http//apple-corps.westnet.com/
• River Continuum Concept, http//www.oaa.pdx.edu/CA
  E/Programs/sti/pratt/rcc.html
• ESRI Online, http//www.esri.com
• Myers, Robert. 1998. NASA Classroom of the
  Future Exploring the Environment - Water
  Quality. Wheeling, WV. http//www.cotf.edu/ete/mai
  n.html
• PHOTOS
• Arbuckle, Kelly. ISU Dept. of Animal Ecology