novel airswot measurements of river ... - swot… · • airswot wse and slope errors are compared...

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500 m N N 2.5 km AirSWOT Elevation (m) 126+ 116 AirSWOT Elevation (m) 139+ 128 Pressure Transducers June 9 AirSWOT vs. Observations: Upstream Lines Downstream Distance (km) WSE (m) 0 10 20 30 40 126 128 130 132 134 136 138 140 June 9 AirSWOT vs. Observations: Downstream Lines Downstream Distance (m) WSE (m) 0 5 10 15 20 25 30 116 118 120 122 124 85 80 70 65 60 124 122 120 118 116 75 West Profile 140 0 10 20 30 40 138 136 134 132 130 128 126 b WSE (m) East Profile a Downstream Distance (km) GPS Profile Measurements AirSWOT Orthogonal Mean Pressure Transducers Areas of High Topography AirSWOT 1 SD AirSWOT 2 SD -10 0 10 30 25 45 75 85 Downstream Distance (km) WSE Errors (cm) RMSE = 9.0 cm MAE = 7.1 cm Bias = 0.65 cm 5 20 -20 -30 65 55 35 15 Downstream Distance - Reach Center (km) Slopes 10 15 20 25 30 35 0.22 0.24 0.26 0.28 0.30 Downstream Distance - Reach Center (km) Slopes 65 70 75 80 0.20 0.25 0.30 80 70 65 30 25 20 75 West Profile NSE = 0.93 b a 10 15 20 25 30 28 26 24 22 Downstream Distance - Reach Center (km) 30 35 Slope (cm/km) East Profile NSE = 0.76 GPS Profile Slopes AirSWOT Slopes 120 100 80 60 40 20 0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 Slope Errors (cm/km) for 10 km Reaches Frequency 1. Key Points AirSWOT provides a new method for measuring river water surface elevations (WSEs) and slopes without the need for in situ data. Errors from AirSWOT are sufficiently small to allow detection of decimeter-level variations in WSEs over 1 km areas and cm/km level variations in slopes along 10 km reaches. Results indicate AirSWOT is capable of producing measurements useful for validating SWOT-quality measurements of river WSEs and slopes. 2. Data Analysis Collected a GPS profile of WSEs along the main channel of the Tanana River coincident with AirSWOT measurements on June 9, 2015 (Figure 1). Filtered AirSWOT WSEs using a ratio of radar magnitude to estimated error. This filter helps eliminate pixels effected by layover and artifacts due to the processing methodology. Calculated orthogonal means of AirSWOT WSEs for every GPS measurement along the profile (Figure 2). Estimated AirSWOT WSE errors when averaged over 1 km areas (Figure 3). Used a moving window every 100 m along the GPS profile to calculate AirSWOT and GPS profile slopes along 10 km reaches, and assessed AirSWOT’s ability to capture slope variability by calculating Nash-Sutcliffe Efficiency (NSE) values between GPS Profile and AirSWOT slopes (Figure 4). Calculated AirSWOT slope errors for the 499 overlapping 10 km reaches (Figure 5). AirSWOT WSE and slope errors are compared to the SWOT mission’s science requirements for executing robust science of surface water dynamics. These requirements are ±10 cm or better for WSEs when averaged over 1 km areas and ±1.7 cm/km for slopes after processing along a maximum of 10 km of flow distance [Biancamaria et al., 2016; Rodriguez, 2016]. Figure 2: WSE profiles derived from GPS profile (black) and AirSWOT (red) for the (a) west and (b) east regions. Standard deviations (SD) are shown for the AirSWOT WSEs in the grey shaded areas. Figure 4: Slopes from GPS profile and AirSWOT for the 499 overlapping 10 km reaches within the (a) west and (b) east regions versus the center of each reach in order of downstream distance. Successive reach segments are shifted downstream by 100 m. 3. Results Figure 3: Differences between GPS profile and AirSWOT WSEs averaged over 1 km areas. Blue dashed lines mark the SWOT science requirement for WSE accuracies (±10 cm). Figure 5: Histogram of slope errors for AirSWOT slopes relative to GPS profile slopes. Red dashed lines mark the SWOT science requirement for slope accuracies (±1.7 cm/km). Figure 1: Tanana River study reach and AirSWOT elevation measurements from June 9, 2015. Grey water mask displays river extent not covered by AirSWOT measurements. GPS profile measurements (black line) and pressure transducer locations (blue triangles) are also shown. East Region West Region Flow Direction 2 2 2 2 We used a Trimble R9 survey-grade GPS system attached to the back of a 28-foot river boat to measure the in situ WSE profile (Figure 1). Novel AirSWOT Measurements of River Height and Slope, Tanana River, AK Elizabeth H. Altenau ([email protected]), Tamlin M. Pavelsky, Delwyn Moller, Christine Lion, Lincoln H. Pitcher, George H. Allen, Paul D. Bates, Stéphane Calmant, Michael Durand, Laurence C. Smith University of North Carolina, Chapel Hill; Remote Sensing Solutions, Inc.; University of California, Los Angeles; University of Bristol; IRD/LEGOS Toulouse, France; The Ohio State University H21F-1483 Acknowledgements: This work was supported by NASA Terrestrial Hydrology Program Grant # NNX13AD05G managed by Jared Entin. We want to thank Curtis Chen, Gregory Sadowy, and Craig Stringham from the Jet Propulsion Laboratory and John Arvesen from Cirrus Digital Systems. Additionally, a special thanks goes to our boat driver Sam Demientieff. References: Biancamaria, S., D. P. Lettenmaier, and T. M. Pavelsky (2016), The SWOT Mission and Its Capabilities for Land Hydrology, Surv. Geophys., 37(2), 307–337, doi:10.1007/s10712-015-9346-y. Rodriguez, E. (2016), Surface Water and Ocean Topography Mission (SWOT) Project - Science requirements Documents. 1 2 3 4 5 6 1 1 2 1 3 1 4 5 6 3

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Page 1: Novel AirSWOT Measurements of River ... - swot… · • AirSWOT WSE and slope errors are compared to the SWOT mission’s ... Tamlin M. Pavelsky, Delwyn Moller, Christine Lion, Lincoln

500 m

N

N

2.5 km

AirSWOT Elevation (m)126+116

AirSWOT Elevation (m)139+128Pressure Transducers

June 9 AirSWOT vs. Observations: Upstream Lines

Downstream Distance (km)

WSE (m)

010203040

126

128

130

132

134

136

138

140

June 9 AirSWOT vs. Observations: Downstream Lines

Downstream Distance (m)

WSE (m)

051015202530

116

118

120

122

124

85 80 70 65 60

124

122

120

118

116

75

West Profile 140

010203040

138

136

134

132

130

128

126

b

WSE

(m)

East Profilea

Downstream Distance (km)

GPS Profile MeasurementsAirSWOT Orthogonal MeanPressure TransducersAreas of High TopographyAirSWOT 1 SDAirSWOT 2 SD

Downstream Distance (km)

Hei

ght E

rror

: Obs

erva

tions

- A

irSW

OT

(m)

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85

-0.3

-0.2

-0.1

0.0

0.1

0.2

0.3

-10

010

30

25457585

Downstream Distance (km)

W

SE E

rrors

(cm

)

RMSE = 9.0 cmMAE = 7.1 cm

Bias = 0.65 cm

5

20-2

0-3

0

65 55 35 15

Slope Variations - Upstream Region

Downstream Distance - Reach Center (km)

Slopes

101520253035

0.22

0.24

0.26

0.28

0.30

Downstream Distance - Reach Center (km)

Slopes

65707580

0.20

0.25

0.30

80 70 65

3025

20

75

West Profile

NSE = 0.93

ba

10152025

3028

2624

22

Downstream Distance - Reach Center (km)3035

Slo

pe (

cm/k

m)

East Profile

NSE = 0.76

GPS Profile SlopesAirSWOT Slopes

Histogram of Slope Errors along 10 km Reaches

Slope Error (m/km)

Freq

uenc

y

-0.03 -0.02 -0.01 0.00 0.01 0.02 0.03

020

4060

8010

012

012

010

080

6040

200

-3.0 -2.0 -1.0 0.0 1.0 2.0 3.0

Slope Errors (cm/km) for 10 km Reaches

Freq

uenc

y

1. Key Points • AirSWOT provides a new method for measuring river water surface elevations (WSEs) and slopes without the need for in situ data. • Errors from AirSWOT are sufficiently small to allow detection of decimeter-level variations in WSEs over 1 km areas and cm/km level variations in slopes along 10 km reaches. • Results indicate AirSWOT is capable of producing measurements useful for validating SWOT-quality measurements of river WSEs and slopes.

2. Data Analysis • Collected a GPS profile of WSEs along the main channel of the Tanana River coincident with AirSWOT measurements on June 9, 2015 (Figure 1). • Filtered AirSWOT WSEs using a ratio of radar magnitude to estimated error. This filter helps eliminate pixels effected by layover and artifacts due to the processing methodology. • Calculated orthogonal means of AirSWOT WSEs for every GPS measurement along the profile (Figure 2). • Estimated AirSWOT WSE errors when averaged over 1 km areas (Figure 3). • Used a moving window every 100 m along the GPS profile to calculate AirSWOT and GPS profile slopes along 10 km reaches, and assessed AirSWOT’s ability to capture slope variability by calculating Nash-Sutcliffe Efficiency (NSE) values between GPS Profile and AirSWOT slopes (Figure 4). • Calculated AirSWOT slope errors for the 499 overlapping 10 km reaches (Figure 5). • AirSWOT WSE and slope errors are compared to the SWOT mission’s science requirements for executing robust science of surface water dynamics. These requirements are ±10 cm or better for WSEs when averaged over 1 km areas and ±1.7 cm/km for slopes after processing along a maximum of 10 km of flow distance [Biancamaria et al., 2016; Rodriguez, 2016].

Figure 2: WSE profiles derived from GPS profile (black) and AirSWOT (red) for the (a) west and (b) east regions. Standard deviations (SD) are shown for the AirSWOT WSEs in the grey shaded areas.

Figure 4: Slopes from GPS profile and AirSWOT for the 499 overlapping 10 km reaches within the (a) west and (b) east regions versus the center of each reach in order of downstream distance. Successive reach segments are shifted downstream by 100 m.

3. Results

Figure 3: Differences between GPS profile and AirSWOT WSEs averaged over 1 km areas. Blue dashed lines mark the SWOT science requirement for WSE accuracies (±10 cm).

Figure 5: Histogram of slope errors for AirSWOT slopes relative to GPS profile slopes. Red dashed lines mark the SWOT science requirement for slope accuracies (±1.7 cm/km).

Figure 1: Tanana River study reach and AirSWOT elevation measurements from June 9, 2015. Grey water mask displays river extent not covered by AirSWOT measurements. GPS profile measurements (black line) and pressure transducer locations (blue triangles) are also shown.

East RegionWest Region

Flow Direction

2 2

2

2

We used a Trimble R9 survey-grade GPS system attached to the back of a 28-foot river boat to measure the in situ WSE profile (Figure 1).

Novel AirSWOT Measurements of River Height and Slope, Tanana River, AKElizabeth H. Altenau ([email protected]), Tamlin M. Pavelsky, Delwyn Moller, Christine Lion, Lincoln H. Pitcher, George H. Allen, Paul D. Bates, Stéphane Calmant, Michael Durand, Laurence C. Smith

University of North Carolina, Chapel Hill; Remote Sensing Solutions, Inc.; University of California, Los Angeles; University of Bristol; IRD/LEGOS Toulouse, France; The Ohio State University H21F-1483

Acknowledgements: This work was supported by NASA Terrestrial Hydrology Program Grant # NNX13AD05G managed by Jared Entin. We want to thank Curtis Chen, Gregory Sadowy, and Craig Stringham from the Jet Propulsion Laboratory and John Arvesen from Cirrus Digital Systems. Additionally, a special thanks goes to our boat driver Sam Demientieff.

References: • Biancamaria, S., D. P. Lettenmaier, and T. M. Pavelsky (2016), The SWOT Mission and Its Capabilities for Land Hydrology, Surv. Geophys., 37(2), 307–337, doi:10.1007/s10712-015-9346-y. • Rodriguez, E. (2016), Surface Water and Ocean Topography Mission (SWOT) Project - Science requirements Documents.

1 2 3 4 5 6

1 1 2 1 3 1 4 5 6 3