DISCHARGE SPLINTER - swot.odyseallc.net · • Evaluation of algorithms across entire river...

DISCHARGE SPLINTERM. Durand & E. Martin

www.swotdawg.wordpress.com

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Top Priority • Intercomparison of three algorithms • Evaluation of algorithms using real data • Integration of instrument simulator for testing discharge algorithms • Evaluation of algorithms across entire river networks with varying river reach lengths • Global map of rivers that SWOT will observe • Create or compile benchmark SWOT-like and in situ datasets • Determine how to define reaches Middle Priority • Identify systematic discharge algorithm testing procedures • Reducing uncertainty in cross-section area estimates, width, and height • Adapt algorithms to use wetted perimeter rather than top width • Demonstrate use of single discharge gage within a network to constrain discharge • Continue exploring new algorithms • Look at geoid slope errors globally • Demonstrate how to use and hydrologic/geomorphologic information to constrain

discharge Lower Priority • Adapt algorithm to handle coupled floodplain-channel systems • Global map of which rivers are affected by floodplains • Global map of rivers for which diffusive approximation will be adequate

Developed with WG input swotdawg.wordpress.com

Top Priority

• Intercomparison of three algorithms*

• Evaluation of algorithms across entire river networks*

• Evaluation of algorithms using real data*

• Integration of instrument simulator for testing discharge algorithms

• Evaluation of algorithms across entire river networks with varying river reach lengths

• Global map of rivers that SWOT will observe

• Create or compile benchmark SWOT-like and in situ datasets

• Determine how to define reaches

Manning’s equation

Hydraulic geometry

n and A0 unknown; all others observed

a and b are unknown. W observed

Manning validation for full St Venant 1d model of Garonne (Credit: Roux+Garambois)

Hydraulic geometry validation for full St Venant 1d model of Sacramento.

METHODS FOR DISCHARGE ESTIMATION CRUX IS ESTIMATION OF UNKNOWN PARAMETERS

Q =1

n(A0 + �A)5/3 W�2/3S1/2

Q = aW b


Hydraulic geometry


a and b are unknown. W observed

Manning validation for full St Venant 1d model of Garonne (Credit: Roux+Garambois)

Hydraulic geometry validation for full St Venant 1d model of Sacramento.

METHODS FOR DISCHARGE ESTIMATION CRUX IS ESTIMATION OF UNKNOWN PARAMETERS

Q =1

n(A0 + �A)5/3 W�2/3S1/2

Q = aW b

Paper accepted JoH!Paper submitted

COMPLETED & ONGOING CASE STUDIES

• Upper Garonne (Pierre Andre Garambois)

• Lower Garonne (Lucie Berthon)

• Sacramento (Durand, Smith, Bjerklie)

• Severn with real data (Durand et al., JOH, in press)

• Mississippi with real data (Smith, Gleason submitted)

• Athabasca with real data (Smith, Gleason submitted)

• Yangtze with real data (Smith, Gleason submitted)

• Severn (Durand)

• Platte (Durand)

• Ohio (Durand et al., JSTARS 2010)Typically, 10-30% RMSE

Top Priority









*Progress since last SDT

Algorithm intercomparison study, withholding experiments, side-by-side tests, possibilities for inter-combination for Sacramento River simulation

Perfect, daily observations, Smith method, discharge RMSE 17%

SWOT observations, Durand method, discharge RMSE 19%

Perfect, daily observations, Bjerklie method, discharge RMSE 4%

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1" 11" 21" 31" 41" 51" 61" 71" 81" 91" 101"111"121"131"141"151"

Q,#$

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Time#Data on the blog, described at: swotdawg.wordpress.com

http://swotdawg.wordpress.com

Top Priority









LARGE-SCALE BRAHMAPUTRA SIMULATION

From Faisal Hossain

Work in progress on using SRTM + Landsat to estimate Q via Manning: see blogswotdawg.wordpress.com

Interpolation of discharge: From SWOT space-time sampling to continuous Q over networks

Courtesy Rodrigo Paiva swotdawg.wordpress.com

Top Priority









Evaluation with real data — AirSWOT

AirSWOT(Discharge(–(Sacramento(River(Premilinary(results(

+"Pre&defined:"•  Bathymetry(•  Manning(Coef.((0.035)(•  Water(Mask(

swotdawg.wordpress.comCourtesy Rodrigo Paiva

AirSWOT(Discharge(–(Sacramento(River(Premilinary(results(

Slope( Width(

Depth(

Discharge(–(3(reaches( Discharge(–(6(reaches(

WSE(profile(

•  Discharge*es+mates*agree*with*USGS*gages*•  Q*decreases*downstream*(water*withdrawals?)*


swotdawg.wordpress.com Courtesy Rodrigo Paiva


There are a total of six gages — each likely has a similar flow

However, we can calculate Q at many reaches, and show Q(x) measured and observed, extending what Rodrigo has already done

This will be a validation of Manning’s equation for one particular river, at one flow condition, but for six gages, with potential for some decrease in flow downstream

AirSWOT Sacramento 2014

Evaluation with real data —OlentangyTwenty level loggers measure continuous water elevation, mapping temporal variations in slope

Width measured via undergrad+range finder

Data this week!

swotdawg.wordpress.com

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1% 62%

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Slope%

Vel%

Slope and river velocity on the Connecticut River Courtesy Dave Bjerklie

Evaluation with real data — Other sites

Suggestion by Al Pietroniro (EC/WSC)

• Deploy many (20?) water loggers and obtain slope, height, and width data along several major rivers

• Perhaps two in Canada, two in the US, two in France?

• What characteristics do we want these rivers to have?

DISCUSSION: SLOPE IN THE SRD

• Should there be a goal for slope on small (50 m) rivers?

• Should there be a science product listed in the SRD for slope?

• Note that it is a requirement to produce discharge for these small rivers

DISCUSSION: PROPOSED NEXT STEPS• Compare the three algorithms: Identify strengths & limitations of each,

discuss ways to combine

• How to define reach lengths? Use AirSWOT data combined with Manning for the 2013 data as an example to start conversation

• How well does algorithm work for real data? Discuss the Olentangy River case

• What rivers to select for in situ SWOT-like studies?

• Others?Recommend setting up a phone call within the next two weeks

Discussion

Top Priority?









• Develop schedule for when algorithms to be delivered etc.

Extra Slides

Reach length

What experiments do we need to determine the optimal reach length?

• AirSWOT and Sacramento data (2013, 2014)

• Model results

• Height profile from data

CAVEATS, OBSERVATIONS

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•Not run on exactly the same observations: Smith & Bjerklie run on true measurements, for now

•In this and other tests, Durand approach better at getting dynamics, Smith & Gleason approach better at baseflow

•Bjerklie method accuracy limited to that of a priori discharge estimates.

•For Durand & Bjerklie approaches if we had a single flow measurement, SWOT would give true discharge

ALGORITHM COMPARISON

SWOT data used Parameters estimated Comment

Durand W,H,S A0,nGood at baseflow, sometimes misses

dynamics

Smith & Gleason W a,b

Good at baseflow, sometimes misses

dynamics

Bjerklie W,H,S H0

Accuracy limited by a priori flow (e.g. minimum,

mean annual)

Spa$otemporal+discharge+es$ma$on+in+a+river+network!+SWOT+measurements+are+not+con$nuous+or+simultaneous+

+How+to+es$mate+con$nuous+spa$otemporal+fields+of+discharge?????+

Spa$otemporal+dependence+of+discharge+

Confluence(Weights(((((((((((((((((((((((((((((((((((((((((((((((((((((((((((

Variance(((( (((((((((((((((((((Correla3on(Matrix(

River+discharge+correla$on:+Physically9based+model+

Q

t#

Δt#

Advec3on(and(dispersion(of(floodwaves(

Observa3on(Errors(Covariance(matrix((((((((((((((((((((((((((((((

Q

t#

Theore3cal(correla3on(model(

Diffusive(wave(model(

Examples of daily estimates of discharge (red line) based on SWOT measurements (blue points) compared with true vales (blue line). Ganges R. (site 4) using combined SWOT and in situ data and using a linear interpolation.

Linear SWOT SWOT+3 gages

R2 0.72 0.83 0.91

Interpolation of discharge

MANNING ON BRAIDED RIVER

4

For reaches of 1,600 m in length, Manning provided good approximation of discharge.

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River Platte 2009 - Flow Velocity

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Coordinate System: NAD 1983 UTM Zone 14NProjection: Transverse MercatorDatum: North American 1983Units: Meter

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PLATTE RIVER SIMULATION

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200 M REACH AVERAGE 1600 M REACH AVERAGE

(Credit: Sanders + Schubert)

METHOD FOR ESTIMATING UNKNOWN PARAMETERS: MANNING



KEY: VARIABLE OBSERVATION TIMESERIES

•  A Bayesian approach used to solve inverse problem for reach-averaged unknown parameters. Manning Q estimates then filtered

•  Example: HEC-RAS simulation on Sacramento River (100 m width)

•  AirSWOT estimation scenario: Ten daily observations, with height (5 cm), width (7 m) and slope (0.55 cm/km) errors added

•  n and A0 estimates not unique: n underestimated; Q unbiased

Q =1

n(A0 + �A)5/3 W�2/3S1/2

(Credit: Durand+Yoon)

METHOD FOR ESTIMATING UNKNOWN PARAMETERS: HG

Hydraulic geometry Q = aW b a and b are unknown. W observed

KEY: VARIABLE OBSERVATION TIMESERIES

•  A new discovery links the a and b parameters for cross-sections within a reach (shown)

•  A genetic algorithm approach used to solve inverse problem for unknown parameters for a number of sub-reach cross-sections

•  The a and b parameters, once identified, can be used to estimate Q, averaged across all sub-reach cross-sections

(Credit: Smith+Gleason)

R² = 0.9537

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log a

Snake River from Washington/Idaho Border to Jackson Lake, WY. (~700 mi)

CASE STUDY 1: GARONNE RIVER WITH MANNING

•  Truth (blue) from 1d St Venant simulation on Garonne River with daily sampling, 15 reaches, 11 days

•  AirSWOT errors added (5 cm height, 7 m width, .75 cm/km slope)

•  A0 and n estimation enables discharge estimate (blue). Final discharge RMSE: 19%

•  Error budget sensitive to width errors. Sensitive to height errors greater than 15 cm (Credit: Roux+Garambois)

USING TIMESERIES OF SYNTHETIC AIRSWOT OBS.

DISCHARGE SPLINTER - swot.odyseallc.net · • Evaluation of algorithms across entire river...

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