comparison of methods for estimating stream channel ......comparison of methods for estimating...
TRANSCRIPT
![Page 1: Comparison of Methods for Estimating Stream Channel ......Comparison of Methods for Estimating Stream Channel Gradient Using GIS David Nagel, John Buffington, and Daniel Isaak USDA](https://reader036.vdocuments.mx/reader036/viewer/2022081515/5e896ce91d459533d61f138e/html5/thumbnails/1.jpg)
Comparison of Methods for Estimating Stream Channel
Gradient Using GIS
David Nagel, John Buffington, and Daniel Isaak
USDA Forest Service, Rocky Mountain Research StationBoise Aquatic Sciences Lab
Boise, ID
September 14, 2006
Special thanks to Sharon Parkes….
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Stream Channel GradientStream Channel Gradient
High
Low
Rate of elevation change
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Computing GradientComputing Gradient
Rise / Run = Slope
5 m
100 m
5 / 100 = .05 = 5% slope
2115 m
2110 m
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Reasons for Modeling Reasons for Modeling Stream GradientStream Gradient
• Predictor of channel morphology
Pool-riffle Plain-bed Step-pool1% 3 - 4% 10%
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Reasons for Modeling Reasons for Modeling Stream GradientStream Gradient
• Estimate distribution of aquatic organisms
“Channel gradient and channel morphology appeared to account for the observed differences in salmonid abundance,
which reflected the known preference of juvenile cohosalmon Oncorhynchus kisutch for pools.”
- Hicks, Brendan J. and James D. Hall, 2003
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Reasons for Modeling Reasons for Modeling Stream GradientStream Gradient
• Predict debris flow transport and deposition
“Transportation and deposition of material in confined channels are governed primarily by water content of
debris, channel gradient, and channel width.”
- Fannin, R. J and T. P. Rollerson, 1993
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Our Purpose for Modeling Our Purpose for Modeling Stream GradientStream Gradient
• Estimate stream bed grain size to identify
salmon spawning habitat
S = channel slope
Grain size 16 – 51 mm
( )( ) ( )( )k
aAScAg
ghSSizeGrains
nbnf
s ρρρ
τρρρ
−=
−=
−11000*
1000
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Study Study AreaArea
10,000 km of rivers and
streams
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Chinook Salmon Spawning Sites 1995 Chinook Salmon Spawning Sites 1995 -- 20042004
1) Where are the optimum spawning sites?
2) Where might spawning expand if populations increased to historical levels?
3) Can grain size prediction be applied elsewhere?
Research questionsResearch questions
50 km
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Measuring GradientMeasuring Gradient
Directly
Remotely
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Digital DataDigital Data
Some preliminary information
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Necessary DataNecessary Data
1) Elevation - to compute rise
2) Stream lines - to compute run
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Choose Elevation DataChoose Elevation Data
USGS National Elevation Dataset
(NED)USGS 1:24,000 scale
Digital Elevation Model (DEM)
Contour lines
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DEM Production ProcessDEM Production Process
1) Aircraft 2) Aerial photo 3) Stereo plotter
4) Map production 5) Scan and tag 6) LT4X
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Original Contours and 10 m DEM Original Contours and 10 m DEM ModelModel
Original 40’ contours 2 m contours derived from 10 m DEM
LT4X
Blue box = 100 m x 100 m
500 m
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Original Contours and 10 m DEM Original Contours and 10 m DEM ModelModel
Original 40’ contours 2 m contours derived from 10 m DEM
LT4X
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Choose Stream Line DataChoose Stream Line Data
National HydrographyDataset (NHD)
Synthetic stream lines
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NHD and Synthetic ComparisonNHD and Synthetic Comparison
Higher gradient Low gradient
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Synthetic Streams “Fit” the DEMSynthetic Streams “Fit” the DEM
Synthetic streams follow the flow accumulation path and fall within the
DEM channel
NHD streams often fall on DEM side slopes
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Flow
NHD and 10 m DEM ContoursNHD and 10 m DEM Contours2 m interval
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NHD and 10 m DEM ContoursNHD and 10 m DEM Contours
1
2
Flow
2 m interval
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NHD Streams Represent Sinuosity NHD Streams Represent Sinuosity More AccuratelyMore Accurately
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Shortening with Synthetic Streams Shortening with Synthetic Streams is Substantialis Substantial
In low gradient areas, synthetic streams can underestimate stream
length by approximately 25%
5412 m vs. 4092 m
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The Dilemma
Elevations along synthetic streams consistently flow down hill and represent
elevation (rise) more normally
Stream channel length, or sinuosity (run)is better represented by NHD stream lines
However….
Rise / Run = Slope
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Best Data Choices for Computing Best Data Choices for Computing Stream Channel GradientStream Channel Gradient
1) 10 m NED DEM
2) NHD stream lines
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Spatial Spatial Accuracy of Accuracy of
NHDNHD
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Measuring GradientMeasuring Gradient
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Measuring GradientMeasuring GradientWe used three approaches dependent
on gradient1) High slope – 3% - 50% gradient
2) Mid-slope – 1.4% mean
3) Main stem – 1.0% or less
High slope
Mid-slope
Main stem
Stream channel profile
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Why Use Three Approaches?Why Use Three Approaches?
DEM accuracy changes depending on the original quad contour spacing
and
Landscape position
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Possible ApproachesPossible Approaches
At contour crossings
Equal interval
At stream intersections
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Why Not Use Contour Why Not Use Contour Crossings for Entire Study Crossings for Entire Study
Area?Area?
1) Not available for the entire study area
2) Tag ends and stream intersections create technical problems
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High slope
Mid-slope
Main stem
High SlopeHigh Slope
We’ll use 100 m equal intervals
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10 m DEM Accuracy in Higher 10 m DEM Accuracy in Higher Gradient AreasGradient Areas
Blue = higher gradient streams
For comparison, compute slope using 1:24 k contours
and DEM
2 km
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0
5
10
15
20
25
30
35
40
45
0 5 10 15 20 25 30 35 40 45
Contour Generated Slope (%)
DEM
Gen
erat
ed S
lope
(%)
Contour and DEM Generated Contour and DEM Generated Slope ComparisonSlope Comparison
Note divergence at higher slopes
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0
5
10
15
20
25
30
35
40
45
0 100 200 300 400 500 600 700 800 900
Segment Length (m)
Slo
pe (%
)
DEM SlopeContour Slope
Slope and Segment LengthSlope and Segment Length
Contours get closer together at higher slopes and segment length
decreasesNote error in DEM model
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-8.00
-6.00
-4.00
-2.00
0.00
2.00
4.00
6.00
8.00
0 100 200 300 400 500 600 700 800 900
Segment Length (m)
Erro
r (C
onto
ur S
lope
- D
EM S
lope
)
Errors vs. Stream Segment LengthErrors vs. Stream Segment Length
Mean slope error for segment lengths:Greater than 100 m .42% ptsEqual to 100 m .68% ptsLess than 100 m 1.64% pts
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Median Stream Segment LengthMedian Stream Segment Length40’ Contour Interval
Segment length between contours
Mean = 147 m Median = 114 m
n = 411
0
10
20
30
40
50
60
70
20 60 100
140
180
220
260
300
340
380
Mor
e
Segment Length (m)
Freq
uenc
y
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Gradient Calculation for Higher Slope Gradient Calculation for Higher Slope Reaches Reaches –– 100 m Spacing100 m Spacing
1) We used 100 m interval spacing along NHD lines with 10 m DEM.
2) Fine enough resolution to detect some natural barriers (slope > 20%)
3) Not so coarse that undesirable averaging occurs
Average error = 0.68% pts
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High slope
Mid-slope
Main stem
Main StemMain Stem
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Gradient Calculation for Main Stem ReachesGradient Calculation for Main Stem Reaches
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3 km
Contour Slope vs. 100 m IntervalContour Slope vs. 100 m Interval
-6.0
-4.0
-2.0
0.0
2.0
4.0
6.0
0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60 1.80 2.00
Slope (%)
Erro
r (C
onto
ur S
lope
- D
EM S
lope
)
Average error = .75% pts
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3 km
Gradient Calculation for Main Stem Reaches Gradient Calculation for Main Stem Reaches Stream IntersectionsStream Intersections
-6.00
-4.00
-2.00
0.00
2.00
4.00
6.00
0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40 1.60 1.80 2.00
Slope (%)
Erro
r (C
onto
ur S
lope
- St
r. In
t. Sl
ope)
Average error = .39% pts
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3 km
Gradient Calculation for Main Stem Reaches Gradient Calculation for Main Stem Reaches at Contour Crossings at Contour Crossings
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1
2
3
1 .41% .45%2 .35% .35%3 .36% .32%
Segment No.
Contour Slope
LiDARSlope
2 km
LiDARLiDAR vs. Contour Gradient Comparisonvs. Contour Gradient Comparison
Green LiDAR
Average error = .03% pts
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3 km
Gradient Calculation for Main Stem Reaches Gradient Calculation for Main Stem Reaches
• We used quad contour crossings along main stem
• Contour crossings were digitized on-screen from DRGs
Average error = .03% pts
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High slope
Mid-slope
Main stem
MidMid--slopeslope
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MidMid--slope Reachesslope Reaches
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MidMid--slope Reaches and Flat Valley Bottom slope Reaches and Flat Valley Bottom DelineationDelineation
1) Overlay valley bottom
2) Exclude main stem reaches
Procedure
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MidMid--slope Reachesslope Reaches
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Compute Slope Between Break Lines and Compute Slope Between Break Lines and Stream Intersections with 10 m DEMStream Intersections with 10 m DEM
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Gradient Calculation for MidGradient Calculation for Mid--slope Reachesslope Reaches
1) We used 10 m DEM elevations at valley bottom break lines and stream intersections
2) Output not validated against contours, but should be better than main stem results at intersections
Average error < .39% pts
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Final Stream Gradient MapFinal Stream Gradient Map
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Field DataField Data
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50 km
n = 238
Field Calculated vs. GIS Calculated GradientField Calculated vs. GIS Calculated Gradient
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0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
16.0
0.0 2.0 4.0 6.0 8.0 10.0 12.0
Field Calculated Slope (%)
GIS
Cal
cula
ted
Slop
e (%
)
Field Calculated vs. GIS Calculated GradientField Calculated vs. GIS Calculated Gradient
Average error = 1.54% pts R-squared = .67
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ConclusionsConclusions
1) The most appropriate interval spacing for measuring slope in higher gradient areas is about 100 m when using 10 m DEM data. Average error ~ 0.68% pts.
2) For main stem, low gradient channels, gradient is best computed between quad contour intervals. Average error ~ 0.03% pts.
3) At intermediate slopes, gradient can be computed between valley bottom break lines and stream intersections with 10 m DEM data. Average error < 0.39% pts.
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RecommendationRecommendation
10 m DEM data have variable accuracy dependent on slope and landscape position
Fish and watershed models that incorporate stream gradient should
account for these errors
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AcknowledgementsRMRS – Boise Lab
John Buffington – Research Geomorphologist Dan Isaak – Research Fisheries Biologist
Bruce Rieman – Research Fisheries Biologist Russ Thurow – Research Fisheries Biologist
Sharon Parkes – GIS Specialist Dona Horan – Fisheries Biologist
Jim McKean – Research Geomorphologist Carolyn Bohn – Hydrologist
Bob Smith – Idaho Department of Lands