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Conclusion Longer reaches smaller errors. However, wider rivers, which are less affected by random errors, had a more stable response to reach length.
Sinuosity method less variability in reach length than hydraulic controls. Few short reaches produced by the HC method could dominate pass-based error statistics, especially for narrow rivers under low discharges.
Biases caused by terrain layover dominated height error statistics for the Sacramento River. Correction methods eliminating pixels with high likelihood of layover could result in improvement
Synthetic SWOT measurements2
Geophysical data processing
Interferogram formation
Height reconstruction
Instrument and media errors
Builds perfect interferograms (no noise)
Adds noise to received power
Adds noise to interferograms (right and left)
Classifies the surface (detects bodies of water)
Reads satellite orbit
Constructs baseline origin coordinates, velocity vector, etc
Builds swath grid
Classificationerrors
Position and height errors
Jet Propulsion Lab’s SWOT Hydrology simulator
Data requirementsTerrain DEM (high resolution ~3m for realistic layover simulation) DEM of the water surface (e.g. derived from a hydraulic model) Water mask
Desirable characteristics: Simulations covering a variety of discharges with a long domain spamming several reaches (50 km and longer)
AcknowlegementsFunded by NASA SWOT Algorithm Definition Team contract to the Ohio State University.
We would like to acknowledge Brent A. Williams, Dani Esteban-Fernandez, and Eva Peral for their support operating the SWOT instrument simulator, Toby Minear for the original HEC-RAS model of the Sacramento River, and Guy Schumann and Alessio Domeneghetti for the original hydraulic model of the Po River.
Results4
Simulated overpasses
Gro
un
d t
rack
Ne
ar
ran
ge
Fa
r ra
ng
e
Legend
SwathWater depth (m)
11
0.1
Elevation (m)
60
-2
0 3015Km
Scale
Sacramento River study area Po River study area
60
-25
28
0
Swath
Elevation (m) Water depth (m)
Far
0 20 40Km n
ear
near
Gro
und
track
Simulated overpasses
Sacramento River
Average width: 102 m to 150 m3 3Discharges:118 m /s to 510 m /s
Simulation length: 6 months9 overpasses
Po River:
Average width: 340 m to 655 m 3 3Discharges: 700 m /s to 4770 m /s
Simulation length: 1 year14 overpasses showing both swaths
Heig
ht
RM
SE
, cm
8
10
12
14
16
18Sacramento River
10km reaches20km reachesHydraulic controlsSinuosity
Decreasing terrain layover
Heig
ht
RM
SE
, cm
12.5
13.5
14.5
15.5Sacramento River
Slo
pe R
MS
E, cm
/km
0
1
2
3
4Predicted errorriver widths:
50 m 150m
Height, width, slope errors
1.5
2.5
3.5
4.5
Po River
Arbitrary lengthHCSinuosity
0
1
2
3
4Predicted errorriver widths:
200 m 400m
0.05
0.07
0.09
0.11
0.13
0.15
Average reach length, km0 5 10 15 20 25
Wid
th r
RM
SE
0.03
0.04
0.05
0.06
0.07
0.08
0.09Sacramento River
Average reach length, km0 5 10 15 20 25
0.05
0.07
0.09
0.11
0.13
3Average discharge, m /s500 1500 2500 3500
Major out-of-bank flow
Wid
th r
RM
SE
0.04
0.06
0.08
0.10
3Average discharge, m /s100 200 300 400 500
Slo
pe R
MS
E, cm
/km
1.0
1.5
2.0
2.5
3.0
3.5Narrower river, more impact on shorter reaches (HC)
0.5
1.5
0.7
0.9
1.1
1.3
2
3
4
5Po River
Errors per overpass Errors per reach lengthStatement of the problem
10 km Gaussian averaging window:High resolution
returns are noisy
Reach averaging Weights
10 km averaging window
Dam
Water surface
Retrieved points
Common smoothing technique
1
How much averaging should we apply?
How do we avoid averaging different things?
Questions:
-How much is needed?
-At which point lowering resolution no longer pays off?
-How do we detect hydraulic features?
Pros: Noise reductionCons: Loss of spatial information
Improper averaging could lead to biases
e-mail:[email protected]
Impacts of river segmentation strategies on reach-averaged product uncertainties for the upcoming Surface Water and Ocean Topography (SWOT) mission
Renato P.M. Frasson, Rui Wei, Toby Minear, Stephen Tuozzolo, Alessio Domeneghetti, Michael Durand H21F-1485
Surface Water and Ocean Topography mission
Objective: detect and measure water surface elevation
Expected Launch: 2021Repeat period: 20.86 daysLatitudes from 78ºS to 78ºNResolution: 10 m to 60 m x 6 mHeight accuracy: 10 cm*Slope accuracy: 1.7 cm/km*
2*when averaged over >1km120 km
20 km
6m
60 to 10 m
50 km
Gro
und
track
Swath characteristics
Methodology3
Initial Centerline
Centerline
Water Depth [m]16.75
0Terrain DEM [m]
60
-1.96
# RiverObs Node
RiverObs Refined
Pixel CloudClassification
Land near Water
Water near Land
Interior Water
0 1000Meters
500
#
#
#
#
#
#
#
#
#
#
#
#
#
#
#
##
##
#
###
#
#
#
#
#
#
#
#
Simulated pixel cloud River nodes
Vectorization of the pixel cloud
Simulation length
Sacramento River- 152 km- 747 nodes
Po River
- 133 km total 113 km without gaps- 349 nodes
Reach definition strategies
Hydraulic controls
Estimate concavity of the water surface
Find discontinuities in the water surface
Break up reaches at inflection points
Merge short reachesBreak up reaches at discontinuities and
swath edges
Sinuosity
Calculate sinuosity
Add reach boundaries at the local maxima/minima of Merge short reaches
Break up reaches at discontinuities and
swath edges dSdx
Flow distance, km
Wate
r ele
vatio
n, m
5
10
15
20
25
30
35
40Sacramento
0 20 40 60 80 100 120 140 160
Positive concavity
Negative concavity
Discontinuity
Swath edge
Flow distance, km
Po River
-2
0
2
6
10
12
14
16
0 20 40 60 80 100 120 140
8
4
8
Swath edge
Swath edge
Reaches with similar HC and sinuosity (falling within 2 km) boundaries
HC and Sinuosity boundaries within 1km
Equally spaced nodes (~200m) containing:
- Node ID- Water surface elevation- elevation uncertainty- River width- width uncertainty- Connectivity information- Spatial information- Data quality flags
Sacramento River
Hydraulic Controls18 Reaches, average length 8.3 km
Sinuosity17 Reaches, average length 8.9 km
Po River:
Hydraulic Controls12 reaches, average length: 9.8 km
Sinuosity14 reaches, average length: 8.4 km
Sacramento
1
2
3
4
5
0 20 40 60 80 100 120 140 160
Sinuosity
Reach boundaries
Swath edge 2
3
3
2
1
Flow distance, km
Po River
0 20 40 60 80 100 120 140
Sin
uosi
ty
Flow distance, km