effects of fluvial morphology on remote sensing measurements of discharge american geophysical...

Effects of Fluvial Morphology on Remote Sensing Measurements of

Discharge

American Geophysical Union, Fall Meeting, 2010Session on “H66, The Remote Sensing of Rivers”

G. R. BrakenridgeG. R. Brakenridge11, A.J. Kettner, A.J. Kettner11, I. Overeem, I. Overeem11, S.V. , S.V. NghiemNghiem22, T. De Groeve, T. De Groeve33, J.P. Syvitski, J.P. Syvitski11

11Dartmouth Flood Observatory and the CSDMS Facility, Dartmouth Flood Observatory and the CSDMS Facility, University of ColoradoUniversity of Colorado2 2 Jet Propulsion Laboratory , California Institute of TechnologyJet Propulsion Laboratory , California Institute of Technology33Joint Research Centre of the European CommissionJoint Research Centre of the European Commission

Can Available Orbital Remote Sensing provide useful measurements of global

river discharge variability?

The Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) is a twelve-channel, six-frequency, passive-microwave radiometer. It measures horizontally and vertically polarized brightness temperatures, including at 36.5 GHz.

AMSR-E was developed by the Japan Aerospace Exploration Agency (JAXA) and launched by the U.S. aboard Aqua in mid-2002.

Monitoring of River Discharge Changes:A Passive Microwave Approach

From USGS field dataFor this gauging station

From Smith et al, 1996, WRR.

Effective width = flow area/river length

From Gage(4.5 ft rise)

To Discharge(via a rating curve)

There is a nearly 4x increase in discharge, over a periodOf 9 days.

One day of AMSR-E data collection(high latitudes revisited most frequently)

To measure surface water change:Traditional Method : Polarization Ratio

PR=(TbVTbH)/(TbV+TbH)

C

M

M is the Measurement cell containing the riverC is the Calibration cell with no river

New Method : Pair RatioHR=TbH(C)/TbH(M)VR=TbV(C)/TbV(M)

Emission Model Analysis

Pair Ratio H-pol: HR=TbH(C)/TbH(M)Silt-loam soil:27% clay, 62% silt

Water fraction:fw=10-90%

Soil moisture %:Rain in M, not Cmv=10 M, 5 C (thin)mv=20 M, 5 C (bold)Rain in M and Cmv=10-35 (medium) in both M and C

36.5 GHz

• Use H polarization at 36.5 GHz (6.92/10.65 RFI, 18.7/28.3 GHz water line,

89 GHz oxygen line)

• C is near M to be within correlation length scale of physical temperature T

• C and M are located to minimize differences in data acquisition time, and

over similar ground cover types.

• For calibration to be unaffected by river, C is chosen at location outside of

river reach M

• M is selected to conform with river reach to maximize surface water

change

• Use rating curve to calibrate HR (the paired ratio estimator) to stream flow

Protocol for River Flow Measurement

Tb

dry

wet

Tb

dry

wet

Dry pixelWet pixel

Influence of other factors (clouds, ground temperature, etc) is much reduced by comparing dry and wet signal

Water has a lower brightness

temperature than land

1

2

3

1 2 31 2 3

flood signal

Example: Wabash River near Mount Carmel, Illinois, USA

Black square showsMeasurement pixel(blue line in next plot)

White square iscalibration pixel(green line in next plot)

Dark blue colors:Flooding mapped byMODIS

Scatter Plot of AMSR-E HR ratio (calibration site/measurement site) versusWabash River discharge. Plot is uncorrected for any lag times .

As discharge rises above bankful state, HR increased from 1.05 to 1.1.

Wabash River in U.S.Near New Harmony, Indiana

Brown = estimated discharge from AMSR-E dataBlack= USGS in-situ stream gauge data

Green = brightness temperature of calibration siteBlue= brightness temperature of river measurement site.

Portion of the estimated discharge time series (black) compared to local gauging station discharge (blue line).

Satellite-estimated discharge lags gauging station discharge..

Estimated discharge time series (black) compared to local gauging station discharge (blue line), with a lag applied.

No time lag.

With time lag.

Flood in March 2006 along the Wabash River recorded by the gauging station (lower plot, bold black line) and by HR from AMSR-E data (lower plot, thin black line).

Due to inundation dynamics, peak discharge was reached at the gauging station 2–3 days before peak discharge as inferred from the AMSRE. From Brakenridge et al (2007) WRR.

River Watch Site496, White River near Augusta.

Channel is 170 m in width, with sinuous meanders.

Circle is area of river measurement reach.

Green line is upwelling microwave radiance within 5 km radius of a calibration land targetBlue line is radiance within 5 km radius of a river measurement site targetBrown line is their ratio and is used to estimate discharge via a rating equation.

Preliminary rating curve for this site.

This equation used to estimate discharge, using remote sensing data (in black, above)

Monthly Runoff, calculated from daily mean discharge, ground station

Monthly Runoff, calculated from AMSR-E data

Annual Runoff

(mm)

60

274

298

351

169

367

549

608

482

Annual Runoff

(mm)

118

307

299

365

151

384

702

633

440

Yearly Runoff, calculated from daily mean gauging station discharge

Yearly Runoff, calculated from AMSR-E data

200220032004200520062007200820092010

200220032004200520062007200820092010

Measured rainfall (blue), modeled river Q (green), gauged Q (red) and AMSR-E Q (orange) for the Okavango R, Botswana. AMSR-E calibrated to discharge by a simple linear equation. An improved rating equation would correct the over-estimation of low flow

Can Available Orbital Remote Sensing provide useful measurements of global

river discharge variability?

Constraints

1.Data are less precise than in-situ gauging.2.Conversion of the estimator to actual discharge requires ground-based data.

Benefits

1.The signal alone, without any calibration to discharge, still allows prompt characterization of anomalies (floods and droughts).2.Adequate calibration to actual discharge has been obtained at many sites via comparison of monthly mean, maximum and minimum values: so, existing global runoff data can be used, now, to calibrate a global array of sites.3.There is clear potential for an accurate global river measurement system that can be updated in real time, and, via SSMI microwave data, extended back into the 1980s.

Location of river gauging stations on the grounds, with various data archived at the Global Runoff Data Centre. Periods of record, type of information varies widely. Many usage restrictions apply. Very little real time data are available on international basis.

Location of presently measured sites using AMSR-E data. Data can be updated daily; are consistent through time, extend back to mid-2002, could be extended to mid 1980s using DMSP/SSMI 36 GHz data.

NASA’s GPM will provide abundant new data forward in time.

Why not use what is available, from ground based data, in order to calibrate, produce rating curves, for satellite-based river measurement sites? This is optimum use of available data.

October 12, 2010

River Watch Measurement Sites

Red: Purple: Blue: Yellow:

Major flooding, > 5yr recurrenceModerate flooding, >1.3 yr recurrenceNormal flowLow flow or ice-covered

November 7, 2010

November 17, 2010

December 8, 2010