Functional linkage of Functional linkage of watersheds and watersheds and streams using streams using

landscape networks landscape networks of reach contributing of reach contributing

areasareasDavid Theobald, John Norman, David Theobald, John Norman,

Erin Peterson, Silvio FerrazErin Peterson, Silvio FerrazNatural Resource Ecology Lab, Dept of Natural Resource Ecology Lab, Dept of

Recreation & Tourism, Colorado State Recreation & Tourism, Colorado State UniversityUniversity

Fort Collins, CO 80523 USA Fort Collins, CO 80523 USA 26 July 26 July 20052005

Project contextProject context

Challenges of STARMAP (EPA STAR):Challenges of STARMAP (EPA STAR): Addressing science needs Clean Water ActAddressing science needs Clean Water Act Integrate science with states/tribes needsIntegrate science with states/tribes needs

Assisting statisticians to test tenable Assisting statisticians to test tenable hypotheses generated using hypotheses generated using understanding of ecological processesunderstanding of ecological processes

PremisePremise Goal: to find measures that more closely

represent our understanding of how ecological processes are operating

Challenges to develop improved landscape-scale indicators (Fausch et al. 2002; Gergel et al. 2002; Allan 2004) are:- a clearer representation watersheds and their hierarchical relationship;- to incorporate nonlinearities of condition among different watersheds and along a stream segment

Ignoring the spatial heterogeneity and scaling of watersheds has led to somewhat equivocal conclusions regarding general proportions of land use in a watershed as an overall indicator of biological condition.

Landscape Context of Landscape Context of MetricsMetrics1.1. Co-variate(s) at spatial location, site contextCo-variate(s) at spatial location, site context

- E.g., geology, elevation, population density at a point- E.g., geology, elevation, population density at a point

2.2. Co-variate(s) within some distance of a locationCo-variate(s) within some distance of a location- Housing density at multiple scales- Housing density at multiple scales

3.3. Watershed-based variablesWatershed-based variables- Proportion of urbanized area- Proportion of urbanized area

4.4. Spatial relationships between locationsSpatial relationships between locations- Euclidean (as the crow flies) distance between points- Euclidean (as the crow flies) distance between points- Euclidean (as the fish swims) hydrologic network distance - Euclidean (as the fish swims) hydrologic network distance

between pointsbetween points

5.5. Functional interaction between locationsFunctional interaction between locations- Directed process (flow direction), anisotropic, multiple scales- Directed process (flow direction), anisotropic, multiple scales- How to develop spatial weights matrix?- How to develop spatial weights matrix?- Not symmetric, stationary - Not symmetric, stationary violate traditional geostatistical violate traditional geostatistical

assumptions!?assumptions!?

From From watersheds/catchments as watersheds/catchments as hierarchical, overlapping hierarchical, overlapping

regions…regions…River continuum concept (Vannote et al. 1980)

… … to network of to network of catchmentscatchments

Network Dynamics Hypothesis - Benda et al. BioScience 2004

SCALE: Grain

Substrate

Biotic Condition

OverhangingVegetation

Segment

River Network

Network Connectivity

Tributary Size DifferencesNetwork Geometry

Stream Network

ConnectivityFlow Direction Network Configuration

Drainage DensityConfluence Density

Cross Sectional AreaChannel Slope, Bed MaterialsLarge Woody Debris

Biotic Condition, Substrate Type, Overlapping VegetationDetritus, Macrophytes

Microhabitat

Segment Contributing Area

Riparian Vegetation Type & ConditionFloodplain / Valley Floor Width

Localized DisturbancesLand Use/ Land Cover

Landscape

ClimateAtmospheric depositionGeology

TopographySoil Type

Microhabitat

ShadingDetritus Inputs

Riparian Zone

Nested Watersheds

Land UseTopography

Vegetation TypeBasin Shape/Size

COARSE

FINE

Reach

Terrestrial Aquatic

Peterson 2005

Pre-processing segment Pre-processing segment contributing areas (SCAs)contributing areas (SCAs)

Automated delineationAutomated delineation Inputs: Inputs:

stream network (from stream network (from USGS NHD 1:100K)USGS NHD 1:100K)

topography (USGS topography (USGS NED, 30 m)NED, 30 m)

Process:Process: ““Grow” contributing Grow” contributing

area away from area away from segment until ridgelinesegment until ridgeline

Uses WATERSHED Uses WATERSHED commandcommand

“true” catchments

“adjoint”catchments

Segments

Segments are linked to Segments are linked to catchmentscatchments

1 to 1 1 to 1 relationshiprelationship

Properties of Properties of the the watershed watershed can be linked can be linked to network to network for for accumulation accumulation operation operation

““Lumped” or watershed-based Lumped” or watershed-based analysesanalyses % agricultural, % urban (e.g., ATtILA)% agricultural, % urban (e.g., ATtILA)

Average road density (Bolstad and Swank)Average road density (Bolstad and Swank) Dam density (Moyle and Randall 1998)Dam density (Moyle and Randall 1998) Road length w/in riparian zone (Arya 1999)Road length w/in riparian zone (Arya 1999) But ~45% of HUCs are not watershedsBut ~45% of HUCs are not watersheds

EPA. 1997. An ecological assessment of the US Mid-Atlantic Region: A landscape atlas. EPA ATtILA 2002.

Example: Human Urban Example: Human Urban IndexIndex

LocalLocal

AccumulatedAccumulated

AccumulatedAccumulated

Generating RCAsGenerating RCAs1.) Filled DEM 2.) Flow Direction

Generating RCAsGenerating RCAs 3.) Stream Reaches 4.) RCAs (Yellow)

Landscape NetworkLandscape NetworkLandscape network features and associated relationships table

From graph theory perspective, reaches are nodes, confluences are edges

Landscape networks with Landscape networks with PythonPython

Need to represent relationships between featuresNeed to represent relationships between features Using graph theory, networksUsing graph theory, networks Retain tie to geometry of featuresRetain tie to geometry of features Flow relationships table (like NHD, but flow-Flow relationships table (like NHD, but flow-

sorted!)sorted!) Implementation in ArcGISImplementation in ArcGIS

Geometric Networks (ESRI – complicated, slow)Geometric Networks (ESRI – complicated, slow) Landscape Networks: Open, simple, fastLandscape Networks: Open, simple, fast

Began with VBA (1.5 years), moved to Python (2 Began with VBA (1.5 years), moved to Python (2 months)months)

Working on integration with PySal (Python Spatial Working on integration with PySal (Python Spatial Library)Library)

USGSNHD,NED

FLoWS v1 tools for FLoWS v1 tools for ArcGIS v9.0…ArcGIS v9.0…

Will migrate to Will migrate to v9.1v9.1

Next stepsNext steps

Attach additional datasets to SCA Attach additional datasets to SCA databasedatabase Land cover (urban, ag, “natural”)Land cover (urban, ag, “natural”) Historical, current, future housing densityHistorical, current, future housing density Road densityRoad density

From segments to geomorphological From segments to geomorphological reaches, gradientreaches, gradient

Project/tool website: Project/tool website: www.nrel.colostate.edu/projects/starmapwww.nrel.colostate.edu/projects/starmap Email: Email: starmap@nrel.colostate.edustarmap@nrel.colostate.edu

Thanks!Thanks! Comments? Questions?Comments? Questions? Funding/Disclaimer: The work reported Funding/Disclaimer: The work reported

here was developed under the STAR here was developed under the STAR Research Assistance Agreement CR-Research Assistance Agreement CR-829095 awarded by the U.S. 829095 awarded by the U.S. Environmental Protection Agency (EPA) Environmental Protection Agency (EPA) to Colorado State University. This to Colorado State University. This presentation has not been formally presentation has not been formally reviewed by EPA.  The views expressed reviewed by EPA.  The views expressed here are solely those of the presenter here are solely those of the presenter and STARMAP, the Program (s)he and STARMAP, the Program (s)he represents. EPA does not endorse any represents. EPA does not endorse any products or commercial services products or commercial services mentioned in this presentation.mentioned in this presentation.

FLoWS: FLoWS: www.nrel.colostate.edu/pwww.nrel.colostate.edu/projects/starmaprojects/starmap

davet@nrel.colostate.edudavet@nrel.colostate.edu

CR - 829095