Hydrological Systems as a Hydrological Systems as a Three Dimensional Surface:Three Dimensional Surface:

Toward a Predictive Spatial Model for the Toward a Predictive Spatial Model for the Aquatic/Terrestrial Transition ZoneAquatic/Terrestrial Transition Zone

Hydrological Systems as a Hydrological Systems as a Three Dimensional Surface:Three Dimensional Surface:

Toward a Predictive Spatial Model for the Toward a Predictive Spatial Model for the Aquatic/Terrestrial Transition ZoneAquatic/Terrestrial Transition Zone

Kevin KaneKevin KaneKevin KaneKevin KaneAnimal Ecology 518, Stream EcologyAnimal Ecology 518, Stream Ecology

Iowa State UniversityIowa State UniversityAnimal Ecology 518, Stream EcologyAnimal Ecology 518, Stream Ecology

Iowa State UniversityIowa State University

OR OR (You thought you had heard the end of it, but no...)

The Mr. Potatohead The Mr. Potatohead Hydrologic Model (MPHM)Hydrologic Model (MPHM)

What a Spud Can Teach Us About Modeling Spatial What a Spud Can Teach Us About Modeling Spatial Relationships to Predict the ATTZ Ecology Relationships to Predict the ATTZ Ecology

The Mr. Potatohead The Mr. Potatohead Hydrologic Model (MPHM)Hydrologic Model (MPHM)

What a Spud Can Teach Us About Modeling Spatial What a Spud Can Teach Us About Modeling Spatial Relationships to Predict the ATTZ Ecology Relationships to Predict the ATTZ Ecology

Study HypothesisStudy Hypothesis

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

Study DefinitionsStudy Definitions

Spatial VariablesAny variables that affect the ecology of the Aquatic/Terrestrial Transition Zone.

Aquatic/Terrestrial Transition ZoneAny place on the surface of the earth.

ModelSimplified Mathematical formulations that mimic real-world phenomena so that complex processes can be understood and predictions made.

Topics of DiscussionTopics 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.

IntroductionIntroduction

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).

ReviewReview

Three Class Models: River Continuum Concept Flood Pulse Concept Hydologic Variability

The Mr. Potatohead Analogy (MPA)

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

River Continuum ConceptRiver Continuum Concept

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

Flood Pulse ConceptFlood 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).

Flood Pulse ConceptFlood 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

Hydrologic VariabilityHydrologic Variability(Poff and Ward, 1989)(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

Hydrologic Variability ExampleHydrologic Variability Example

So...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…

The Mr. Potatohead Analogy (MPA)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).

Spatial Variables for PredictionSpatial Variables for Prediction

Climate

Vegetation

Topography

Geology

Land use

Soil characteristics

Expanding the Boundaries...Expanding the Boundaries...

Diagram of the relative position of geomorphic features along streams (modified from Hupp, 1986).

?

… … To The Entire ATTZTo The Entire ATTZ

Outside the stream Outside the floodplain

Looking at the earth as a Hydrologic Surface

Study Area Study Area Scott County,Scott County, Iowa Iowa

AlluviumAlluvium

Scott Co.

Scott County Study SiteScott County Study Site

Data Sets: Alluvium Soil Drainage Scott Co. Rivers

Dixon QuadDixon Quadand Studyand StudySiteSite

Data Sets: Alluvium Soil Drainage Scott Co. Rivers

Study factors and assumptionsStudy 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

Quantitative Spatial Quantitative Spatial Modeling Using GISModeling Using GIS

Study DefinitionsStudy 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

GIS Data ModelsGIS Data Models

Raster

Vector

Raster GIS DataRaster GIS Data

Analysis Methods:Analysis Methods:Coverages, Cells, & Matrix MathCoverages, Cells, & Matrix Math

Drainage Wetland Sum

+ =

VectorCov.

RasterCov.

Proximity to Proximity to Hydrologic FeaturesHydrologic Features

Proximity HypothesisProximity 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.

Distance toDistance toAlluviumAlluvium

Distance toDistance to100K Rivers100K Rivers

Distance toDistance toWetlandsWetlands

Distance to Soil DrainagesDistance to Soil Drainages

3 Class Proximity Calculations3 Class Proximity Calculations

Alluvium

Wetlands

100K Rivers

Soil Drainages

+

Proximity CalculationsProximity Calculations1. 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

Final Straight Proximity MapsFinal Straight Proximity Maps( [Drain Dist3] + [nwi82 dist3] + [Riv82 Dist3] + [Alluvium Distance 3])

3 Class Weighted Proximity 3 Class Weighted Proximity CalculationsCalculations

Alluvium -1

Wetlands -3

100K Rivers - 2

Soil Drainages - 4 +

Final Weighted Proximity MapsFinal Weighted Proximity Maps( ([Drain Dist3]*4) + ([nwi82 dist3]*3) + ([Riv82 Dist3]*2) + [Alluvium Distance 3])

30 Classes 3 Classes

Straight vs. Weighted Prox. MapsStraight vs. Weighted Prox. Maps( ([Drain Dist3]*4) + ([nwi82 dist3]*3) + ([Riv82 Dist3]*2) + [Alluvium Distance 3])

Results of Proximity AnalysisResults of Proximity Analysis

Models where water on the landscape is most likely to flow and in what relative amounts.

Allows prediction of species habitat.

TopographyTopography

Topography HypothesisTopography 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.

Elevation Elevation from DEMfrom DEM

ShadedShadedRelief ofRelief ofElevationElevation

Dixon QuadDixon QuadSlopeSlope

Study Area SlopeStudy Area Slope

Slope from SoilsSlope from Soils

Slope: Slope: DEM vs. SoilsDEM vs. Soils

Results of Topography AnalysisResults of Topography Analysis

Models the holding potential, speed, and direction of water flow in an area.

Allows prediction of species habitat.

Many other variables can be Many other variables can be modeled including...modeled including...

Climate Hydrology Vegetation Topography Geology Land use Soil characteristics

So what?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.

What’s Next?What’s 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?

SummarySummary 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.

Presentation References 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. 37:130-137.

Bayley, Peter B., Understanding Large River-Floodplain Ecosystems, Bioscience Vol. 45 No. 3, March 1995

References (cont.) References (cont.)

WEB SITES Mr. Potatohead, http://apple-corps.westnet.com/ River Continuum Concept,

http://www.oaa.pdx.edu/CAE/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/main.html

PHOTOS Arbuckle, Kelly. ISU Dept. of Animal Ecology