Functional Linkage of Water
Basins and Streams:
FLoWS v1 ArcGIS tools
David Theobald, John Norman, Erin
Peterson
Natural Resource Ecology Lab, Dept of Recreation
& Tourism, Colorado State University
Fort Collins, CO 80523 USA
17 May 2006
Project context

Challenges of STARMAP (EPA STAR):
Addressing science needs Clean Water Act
 Integrate science with states/tribes needs
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Develop landscape-based indicators to assist in
testing tenable hypotheses generated using
understanding of ecological processes
Premise
Challenges to develop improved landscape-scale indicators
(Fausch et al. 2002; Gergel et al. 2002; Allan 2004) are:
- clearer representation of watersheds & hierarchical
relationship;
- incorporate nonlinearities of condition among different
watersheds and along a stream segment
Need to characterize spatial heterogeneity & scaling of
watersheds when developing indicators of biological
condition
Goal: to develop indicators that more closely represent our
understanding of how ecological processes are
operating
From watersheds/catchments as
hierarchical, overlapping regions…
River continuum concept (Vannote et al. 1980)
“Lumped” or watershed-based analyses
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% agricultural, % urban (e.g., ATtILA)
Average road density (Bolstad and Swank)
Dam density (Moyle and Randall 1998)
Road length w/in riparian zone (Arya 1999)
But ~45% of HUCs are not watersheds
EPA. 1997. An ecological assessment of the
US Mid-Atlantic Region: A landscape atlas.
EPA ATtILA 2002.
… to network of catchments
Network Dynamics Hypothesis - Benda et al. BioScience 2004
Reaches linked to catchments
1 to 1
relationship
 Properties of
the watershed
can be linked
to network for
accumulation
operation
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Covariates: landscape context
1.
Co-variate(s) at spatial location, site context
- E.g., geology, elevation, population density at a point
2.
Co-variate(s) within some distance of a location
- Housing density at multiple scales
3.
Watershed-based variables
- Proportion of urbanized area
4.
Spatial relationships between locations
- Euclidean (as the crow flies) distance between points
- Euclidean (as the fish swims) hydrologic network distance between points
5.
Functional interaction between locations
- Directed process (flow direction), anisotropic, multiple scales
- How to develop spatial weights matrix?
- Not symmetric, stationary  violate traditional geostatistical assumptions!?
Local vs. accumulated
(e.g., Human Urban Index)
Local
Accumulated
Accumulated
USGS
NHD,
NED
USGS
NHD,
NED
Pre-processing
Generating reach contributing areas (RCAs)
Automated delineation

Inputs:
stream network (from USGS
NHD or other)
 topography (USGS NED, 30 m)
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Processes:
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1. traditional WATERSHED
command requires FILLed
DEM – “hydro-conditioned”
2. Cost-distance using
Topographic Wetness & Position
Indices
“true”
“adjoint”
catchments
catchments
Segments
Generating RCAs: FILLed
1.) Filled DEM
2.) Flow Direction
Artifacts?
Generating RCAs: cost-distance
1.) DEM
2.) Topographic Wetness Index
3.) Topographic Position Index
Generating RCAs
4) Stream Reaches 
5.) RCAs (Yellow)
Evaluation of RCAs
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“Truth”
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Hand-delineated from 1:24K
Modeled (1:100K, 30 m DEM):
A. traditional (FILL-ing)
 B. cost-distance
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Measure: Jaccard’s similarity coefficient:
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b / (a + b + c)
a
b
c
Preliminary results
FILLed DEM 50 m/WATERSHED
Mean accuracy: 78%
Cost-distance RCAs
Mean accuracy: 85%
Within RCA hydro-weighting
Overland flow
(hydro distance to stream)
Instream flow
(hydro network distance to outlet)
Landscape Network
Landscape network features and associated relationships table
From graph theory perspective,
reaches are nodes, confluences are
edges
Network connectivity errors
Selections
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User-defined field
Polylines or RCAs
Cumulative (distance
from selected feature)
Analysis
Estimated discharge
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Average annual precipitation &
temperature, basin area
Vogel et al. 1999
Vogel
Analysis
Export to distance matrices
Straight-line
Instream distance
Distance matrices (cont.)
Downstream only
Upstream only
Distance matrices (cont.)
Proportion upstream
Proportion downstream
Distance matrices (cont.)
Downstream portion dist only
Number of confluences
Example:
Coho salmon
distances
Summary
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River Continuum to Network
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Open
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Simple data structure
Python linked to GeoProcessing object
Non-GIS (thru Access, SQL, etc.)
Flexible
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From overlapping waterbasins to network spatial structure
User-defined variables to accumulate, navigate network
Different selection sets, combinations
Compute framework once, use with many point configurations
(samples)
Robust
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Flow-based vs. Strahler stream order
Cost-weighted methods
Developed, tested (broken), refined
E.g, Mid-Atlantic Highlands; Oregon; Central Shortgrass Prairie; Alaska;
Next steps
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Project/tool website:
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www.nrel.colostate.edu/projects/starmap
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FLoWS database to complement tools
Attach additional attributes to FLoWS database
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FLoWS, FunConn, RRQRR
Land cover (urban, ag, “natural”)
Historical, current, future housing density
Hydro & slope weighted road density
Human accessibility
Within reach/segment
Streams as 2D features
SCALE: Grain
Terrestrial
Aquatic
Landscape
River Network
COARSE
Climate
Atmospheric deposition
Geology
Topography
Soil Type
Network Connectivity
Nested Watersheds
Land Use
Topography
Stream Network
Connectivity
Drainage Density
Flow Direction
Confluence Density
Network Configuration
Vegetation Type
Basin Shape/Size
Segment
Contributing Area
Segment
Tributary Size Differences
Network Geometry
Localized Disturbances
Land Use/ Land Cover
Reach
Riparian Zone
Riparian Vegetation Type
& Condition
Floodplain / Valley Floor Width
Microhabitat
Cross Sectional Area
Channel Slope, Bed Materials
Large Woody Debris
Substrate
FINE
Shading
Detritus Inputs
Peterson 2005
Overhanging
Vegetation
Biotic
Condition
Microhabitat
Biotic Condition, Substrate Type,
Overlapping Vegetation
Detritus, Macrophytes
Example: 2D stream in Virginia
Example: 2D stream in Virginia
Example: 2D stream in Virginia
Example: 2D stream in Virginia
Thanks!
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Comments? Questions?
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Thanks to K. Verdin at USGS EROS Data Center
for sharing EDNA datasets
Funding/Disclaimer: The work reported here was
developed under the STAR Research Assistance
Agreement CR-829095 awarded by the U.S.
Environmental Protection Agency (EPA) to
Colorado State University. This presentation has
not been formally reviewed by EPA. The views
expressed here are solely those of the presenter
and STARMAP, the Program (s)he represents. EPA
does not endorse any products or commercial
services mentioned in this presentation.
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FLoWS:
www.nrel.colostate.edu/projects/starmap

davet@nrel.colostate.edu
CR - 829095
Zonal
Accumulate
Process/Functional
Up/down (net.)
Water basin - Stream
Hydrologic
distance:
-Instream
-Up vs. down?
FLoWS
Overlapping
watersheds
Accumulate
downstream
FLoWS (and
SPARROW)
Stand-alone
watershed
Watershed-based
analyses (HUCs)
Tesselation of true,
adjoint catchments
?
Watershed
HUCs/WBD
Reach Contributing Areas (RCAs)
Grain (Resolution)