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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. - PowerPoint PPT Presentation
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Functional Linkage Functional Linkage of Water Basins and of Water Basins and
Streams: Streams: FLoWS v1 ArcGIS FLoWS v1 ArcGIS
toolstoolsDavid Theobald, John Norman, David Theobald, John Norman,
Erin PetersonErin PetersonNatural 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 17 17 May 2006May 2006
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
Develop landscape-based indicators to Develop landscape-based indicators to assist in testing tenable hypotheses assist in testing tenable hypotheses generated using understanding of generated using understanding of ecological processesecological processes
PremisePremise
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 From watersheds/catchments as watersheds/catchments as hierarchical, overlapping hierarchical, overlapping
regions…regions…
River continuum concept (Vannote et al. 1980)
““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.
… … to network of to network of catchmentscatchments
Network Dynamics Hypothesis - Benda et al. BioScience 2004
Reaches linked to Reaches 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
Covariates: landscape Covariates: landscape contextcontext1.1. 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 - Euclidean (as the fish swims) hydrologic network
distance between pointsdistance between points
5.5. Functional interaction between locationsFunctional interaction between locations- Directed process (flow direction), anisotropic, multiple - Directed process (flow direction), anisotropic, multiple
scalesscales- How to develop spatial weights matrix?- How to develop spatial weights matrix?- Not symmetric, stationary - Not symmetric, stationary violate traditional violate traditional
geostatistical assumptions!?geostatistical assumptions!?
Local vs. accumulated Local vs. accumulated (e.g., Human Urban Index)(e.g., Human Urban Index)
LocalLocal
AccumulatedAccumulated
AccumulatedAccumulated
USGSNHD,NED
USGSNHD,NED
Pre-processingPre-processingGenerating reach contributing Generating reach contributing
areas (RCAs)areas (RCAs)Automated delineationAutomated delineation
Inputs: Inputs: stream network (from stream network (from
USGS NHD or other)USGS NHD or other) topography (USGS NED, 30 topography (USGS NED, 30
m)m)
Processes:Processes: 1. traditional WATERSHED 1. traditional WATERSHED
command requires FILLed command requires FILLed DEM – “hydro-conditioned”DEM – “hydro-conditioned”
2. Cost-distance using 2. Cost-distance using Topographic Wetness & Topographic Wetness & Position IndicesPosition Indices
“true” catchments
“adjoint”catchments
Segments
Generating RCAs: FILLedGenerating RCAs: FILLed1.) Filled DEM 2.) Flow Direction
Artifacts?Artifacts?
Generating RCAs: cost-Generating RCAs: cost-distancedistance1.) DEM
2.) Topographic Wetness Index 3.) Topographic Position Index
Generating RCAsGenerating RCAs 4) Stream Reaches 5.) RCAs (Yellow)
Evaluation of RCAsEvaluation of RCAs
““Truth”Truth” Hand-delineated from 1:24KHand-delineated from 1:24K
Modeled (1:100K, 30 m DEM):Modeled (1:100K, 30 m DEM): A. traditional (FILL-ing)A. traditional (FILL-ing) B. cost-distanceB. cost-distance
Measure: Jaccard’s similarity Measure: Jaccard’s similarity coefficient: coefficient: b / (a + b + c)b / (a + b + c)
a
b
c
Preliminary resultsPreliminary resultsFILLed DEM 50 m/WATERSHEDMean accuracy: 78%
Cost-distance RCAsMean accuracy: 85%
Within RCA hydro-Within RCA hydro-weightingweighting
Overland flow Overland flow (hydro distance to stream)(hydro distance to stream)
Instream flow Instream flow
(hydro network distance to outlet)(hydro network distance to outlet)
Landscape NetworkLandscape NetworkLandscape network features and associated relationships table
From graph theory perspective, reaches are nodes, confluences are edges
Network connectivity errors
SelectionsSelections User-defined fieldUser-defined field Polylines or RCAsPolylines or RCAs Cumulative Cumulative
(distance from (distance from selected feature)selected feature)
AnalysisAnalysis
Estimated dischargeEstimated discharge
Average annual Average annual precipitation & precipitation & temperature, basin temperature, basin areaarea
Vogel et al. 1999Vogel et al. 1999
Vogel
AnalysisAnalysis
Export to distance Export to distance matricesmatrices
Straight-line Instream distance
Distance matrices (cont.)Distance matrices (cont.)Downstream only Upstream only
Distance matrices (cont.)Distance matrices (cont.)Proportion upstream Proportion downstream
Distance matrices (cont.)Distance matrices (cont.)Downstream portion dist onlyNumber of confluences
Example: Example: Coho Coho
salmon salmon distancesdistances
SummarySummary River Continuum to NetworkRiver Continuum to Network
From overlapping waterbasins to network spatial From overlapping waterbasins to network spatial structurestructure
OpenOpen Simple data structureSimple data structure Python linked to GeoProcessing objectPython linked to GeoProcessing object Non-GIS (thru Access, SQL, etc.)Non-GIS (thru Access, SQL, etc.)
FlexibleFlexible User-defined variables to accumulate, navigate networkUser-defined variables to accumulate, navigate network Different selection sets, combinationsDifferent selection sets, combinations Compute framework once, use with many point Compute framework once, use with many point
configurations (samples)configurations (samples) RobustRobust
Flow-based vs. Strahler stream orderFlow-based vs. Strahler stream order Cost-weighted methodsCost-weighted methods Developed, tested (broken), refinedDeveloped, tested (broken), refined E.g, Mid-Atlantic Highlands; Oregon; Central Shortgrass E.g, Mid-Atlantic Highlands; Oregon; Central Shortgrass
Prairie; Alaska; Prairie; Alaska;
Next stepsNext steps Project/tool website: Project/tool website:
www.nrel.colostate.edu/projects/starmapwww.nrel.colostate.edu/projects/starmap FLoWS, FunConn, RRQRRFLoWS, FunConn, RRQRR
FLoWS database to complement toolsFLoWS database to complement tools Attach additional attributes to FLoWS Attach additional attributes to FLoWS
databasedatabase Land cover (urban, ag, “natural”)Land cover (urban, ag, “natural”) Historical, current, future housing densityHistorical, current, future housing density Hydro & slope weighted road densityHydro & slope weighted road density Human accessibilityHuman accessibility
Within reach/segmentWithin reach/segment Streams as 2D featuresStreams as 2D features
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
Example: 2D stream in Example: 2D stream in VirginiaVirginia
Example: 2D stream in Example: 2D stream in VirginiaVirginia
Example: 2D stream in Example: 2D stream in VirginiaVirginia
Example: 2D stream in Example: 2D stream in VirginiaVirginia
Thanks!Thanks! Comments? Questions?Comments? Questions? Thanks to K. Verdin at USGS EROS Data Thanks to K. Verdin at USGS EROS Data
Center for sharing EDNA datasetsCenter for sharing EDNA datasets 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) to Environmental Protection Agency (EPA) to Colorado State University. This 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 and here are solely those of the presenter and STARMAP, the Program (s)he represents. STARMAP, the Program (s)he represents. EPA does not endorse any products or EPA does not endorse any products or commercial services mentioned in this commercial services mentioned in this presentation.presentation.
FLoWS: FLoWS: www.nrel.colostate.edu/projects/stawww.nrel.colostate.edu/projects/starmaprmap
[email protected]@nrel.colostate.edu
CR - 829095
Water basin - StreamWater basin - Stream
Hydrologic Hydrologic distance:distance:-InstreamInstream-Up vs. Up vs. down?down?
FLoWSFLoWS
Overlapping Overlapping watershedswatersheds
Accumulate Accumulate downstreamdownstream
FLoWS (and FLoWS (and SPARROW)SPARROW)
Stand-alone Stand-alone watershedwatershed
Watershed-based Watershed-based analyses (HUCs)analyses (HUCs)
Tesselation of Tesselation of true, adjoint true, adjoint catchments catchments
??
Watershed HUCs/WBD Reach Contributing Areas (RCAs)
Grain (Resolution)
Pro
cess
/Fu
nct
ional
Zonal
A
ccum
ula
te
U
p/d
ow
n
(net.
)