# Hydrological Systems as a Three Dimensional Surface: Toward a Predictive Spatial Model for the Aquatic/Terrestrial Transition Zone Kevin Kane Animal Ecology.

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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 Animal Ecology 518, Stream Ecology Iowa State University

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

The Mr. Potatohead Hydrologic Model (MPHM) What a Spud Can Teach Us About Modeling Spatial Relationships to Predict the ATTZ Ecology

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

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.

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

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).

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

River Continuum Concept (Vannote, et. al., 1980) l The physical basis of the RCC is l Size of the river or stream (stream order) l Location along the stream gradient l Four important physical parameters are l Current l Substrate l Temperature l Dissolved oxygen l Physical parameters of a stream define l Structure of the biotic component l Diversity of the biotic component

River Continuum Concept

Flood Pulse Concept (Junk, et. al., 1989) l 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. l 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 Concept l 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 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 Variability (Poff and Ward, 1989) l Factors l Flow variability l Flood regime patterns l Intermittency l Reasonable geographic affiliation l Constrains ecological and evolutionary processes in streams l Prediction based on constraints

Hydrologic Variability Example

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

The Mr. Potatohead Analogy (MPA) l The ATTZ (Mr. Potatohead) can be described and modeled by many factors (spatial variables - different eyes, ears, noses, etc.) l 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 Prediction Climate Vegetation Topography Geology Land use Soil characteristics

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

… To The Entire ATTZ l Outside the stream l Outside the floodplain l Looking at the earth as a Hydrologic Surface

Study Area Scott County, Iowa

Alluvium Scott Co.

Scott County Study Site Data Sets: Alluvium Soil Drainage Scott Co. Rivers

Dixon Quad and Study Site Data Sets: Alluvium Soil Drainage Scott Co. Rivers

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

Quantitative Spatial Modeling Using GIS

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

GIS Data Models Raster Vector

Raster GIS Data

Analysis Methods: Coverages, Cells, & Matrix Math DrainageWetlandSum += Vector Cov. Raster Cov.

Proximity to Hydrologic Features

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

Distance to Alluvium

Distance to 100K Rivers

Distance to Wetlands

Distance to Soil Drainages

3 Class Proximity Calculations Alluvium Wetlands 100K Rivers Soil Drainages +

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

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

3 Class Weighted Proximity Calculations Alluvium -1 Wetlands -3 100K Rivers - 2 Soil Drainages - 4 +

Final Weighted Proximity Maps ( ([Drain Dist3]*4) + ([nwi82 dist3]*3) + ([Riv82 Dist3]*2) + [Alluvium Distance 3]) 30 Classes 3 Classes

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

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

Topography

Topography Hypothesis l Prediction of the Aquatic/Terrestrial Transition Zone ecology is possible through modeling spatial variables on a three dimensional flow surface. l 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. l The holding potential, speed, and direction of water flow on a piece of land can be a predictor of possible habitat.

Elevation from DEM

Study Area Slope

Slope from Soils

Slope: DEM vs. Soils

Results of Topography Analysis l Models the holding potential, speed, and direction of water flow in an area. l Allows prediction of species habitat.

Many other variables can be modeled including... Climate  Hydrology Vegetation  Topography Geology Land use Soil characteristics

So what? l Each of these spatial variables will be used as input to a final composite model for a site. l 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. l If the hypothesis is correct, a prediction can be made about the life forms that particular cell will support.

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

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

Presentation References l Allan, J.D. 1995. Stream Ecology -- Structure and Function of Running Waters. Chapman and Hall, UK. l Vannote, RL, GW Minshall, KW Cummins, JR Sedell, and CE Cushing (1980) The River Continuum Concept. Can. J. Fish. Aquat. Sci. 37:130-137. l Bayley, Peter B., Understanding Large River- Floodplain Ecosystems, Bioscience Vol. 45 No. 3, March 1995

References (cont.) WEB SITES l Mr. Potatohead, http://apple-corps.westnet.com/ l River Continuum Concept, http://www.oaa.pdx.edu/CAE/Programs/sti/pratt/rcc.html l ESRI Online, http://www.esri.com l Myers, Robert. 1998. NASA Classroom of the Future: Exploring the Environment - Water Quality. Wheeling, WV. http://www.cotf.edu/ete/main.html PHOTOS l Arbuckle, Kelly. ISU Dept. of Animal Ecology

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