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To propose a new procedure for continuous discharge
estimation. The procedure is based on the use of the DORA
hydraulic model (Noto and Tucciarelli, 2001) to turn recorded
stages into discharges and the exploiting remote sensing
derived water levels for Manning's roughness calibration.
The flood event of January 2003, occurred along the Alzette
River, is investigated by using two available SAR images.
Purpose
Conclusions
Introduction
References
Method
Results
Case Study
Reliable discharge estimations at a river site depend on local hydraulic conditions, which are usually defined by recording water level. In
fact, stage monitoring is relatively inexpensive, especially when compared to the cost necessary to carry out flow velocity
measurements. However, there is the need of converting stage records into discharge values. This task is generally addressed through a
reliable rating curve, which can be unknown, in the case of gauged sites where velocity measurements cannot be carried out, or limited
for low flows. In addition, a rating curve differs from the one-to-one stage-discharge relationship when unsteady flows occur. In order to
relate stage and discharge hydrographs at a selected river section also during unsteady flow conditions, 1D hydraulic modelling can be
adopted (Corato et al., 2011). Nevertheless, a reliable use of hydraulic modelling is strictly related to the river cross sections geometry
data availability along with an accurate Manning's roughness coefficient calibration. For this latter, many studies (Aronica et al.,
2002;Hostache et al., 2009; Prestinizi et al., 2011) show that it is possible to use the remote sensing derived (RSD) information to
calibrate a hydraulic model. The most exploited sensors are the Synthetic Aperture Radar (SAR) ones, due to their high spatial
resolution and the all weather and day-and-night capability. Therefore, a reliable continuous discharge monitoring system can be
obtained using a hydraulic model and combining the in situ information provided by a stream gauge with RSD information, coming from
SAR sensors.
Ø
Ø
Ø
Ø
Ø
Ø
Aronica, G., Bates, P. D. , Horritt, M. S., Assessing the uncertainty in distributed model predictions
using observed binary pattern information with in GLUE, Hydrol. Process., vol. 16, no. 10, pp.
2001–2016, 2002.
Corato, G., Moramarco, T., and Tucciarelli, T.: Discharge estimation combining flow routing and
occasional measurements of velocity, Hydrol. Earth Syst. Sci., 15, 2979-2994.
Durand M., Rodriguez E., Alsdorf D.E., Trigg M., Estimating river depth from remote swath
interferometry measurements of river height, slope and width, IEEE Journal of selected topics in
applied Earth Observations and Remote Sensing, 3(1), 20-31, 2007.
Hostache, R., Matgen, P., Schumann, G., Puech, C., Hoffmann, L., Pfister, L., Water level estimation
and reduction of hydraulic model calibration uncertainties using satellite SAR images of floods, IEEE T.
Geosci. Remote, 47, 431–441, 2009.
Noto, L. and Tucciarelli, T.: DORA algorithm for network flow models with improved stability and
convergence properties." J Hydraul Eng, ASCE, 127(5), 380-391, 2001.
Prestininzi, P, Di Baldassarre, G, Schumann, G., Bates, PD., Selecting the appropriate hydraulic model
structure using low-resolution satellite imagery, Advances in Water Resources, 34, 38-46, 2011.
ü
ü
A new procedure for discharge estimation in natural channel has been proposed. The procedure
combines a continuous ‘in-situ’ information coming from a stream gauge with a sporadic RSD
information obtained by a SAR sensor:
The main advantage of this procedure consists in the fact that the RSD information coming from SAR
sensors is globally available, without limits of site accessibility or weather conditions. These
features make the proposed procedure suitable for
recorded water levels are turned into discharge values by
using a hydraulic model calibrated with a RSD information.
The results show that RSD information is suitable for an efficient hydraulic model calibration,
oriented to discharge estimation at river site where only stages are recorded.
gauged site not equipped for velocity
measurements or located in an area that is not easily reachable by operators. On the other hand, the
main disadvantages are related to the time resolution of the RSD information that is, at the present,
still limited to sporadic snapshots.
Next missions, like SWOT, promise to furnish more accurate information that might be used also for
bathymetry modelling (Durand et al., 2010).
ü
ü
The RSD water levels are estimated on the basis of following steps (Hostache et al., 2009):
extraction of flood extents using a double treshold set on the basis of a land use map;
estimation of water levels coupling RSD flood extents and DEM;
constrain water levels using hydraulic coherence: for subcritical flow, energy can not
increase moving from upstream to downstream.
ü
ü
ü
The procedure was applied using the two SAR images, available for the flood event of January 2003. Fig. 2a
illustrates the flood limit extents estimated using the method proposed by Hostache et al. (2009), while related
water levels are shown in Fig. 2b. The model calibration has been performed with 3500 Monte Carlo simulations and
Fig. 2c shows the pattern of the objective function. Using both images, it has been possible to calibrate the hydraulic
model. The optimum parameter sets along with related performances in discharge estimation at Phaffenthal gauged
section are listed in Tab. 1. As shown in Fig. 2d and listed in tab. 2, using both images a good matching between
observed and simulated discharge hydrographs has been obtained at the upstream end (Pfaffenthal) where water
levels are recorded. Therefore rating curve can be inferred (see Fig. 2e).
Manning’s roughness set is calibrated minimizing the distance of simulated water levels
from the RSD water levels bounds:
and are the min and max RSD water levels respectively, and z| is the
simulated one.
sim
RSD information is available only for overbank flood, so that two areas with different
roughness can be identified depending on the availability of RSD information.
Fig. 2 - ERS-2 Image: (a) Flood limit extents extraction (b) water levels estimation and hydraulic coherence
constraining (c) map of error function (d) discharge estimation at Pfaffenthal gauged site.
Distance from Pfaffenthal [km]
Waterlevel[masl]
Pfaffenthal
RSD Water levelsFlood limit extents Calibration: Error Map
n1
nSAR
nSAR
Pfaffenthal Discharge
Steinsel
Hunsdorf
Lintgen
Mersch
n1
no RSD
data
no RSD
data
RSD data
noRSDdata
n1
DORA Hydraulic
Model
Calibration
Sim. hydraulic
profile
Recorded
Water Level
hydrograph
(Upstream
Boundary
Condition)
Stream gauge SAR sensor
RSDWaterLevels
Optimum
Manning set
Simulated
discharge hydrograph
q =lat q =kup upq
Ainter
Aup
Hydraulic
assumtions
min
SAR
iz
( ) ( ) ( )
=
ì <
ï
ï
= = £ £í
ï
- >ï
î
å
min min
1 min max
1,
max max
- if
, , with , 0 if
if
SAR SAR
i i i isim sim
SAR SAR
up SAR i up SAR i SAR i i isim
i n
SAR SAR
i i i isim sim
z z z z
f n n d n n d n n z z z
z z z z
max
SAR
iz
RSD
waterlevels
Calibration
Image Acquisition time Band Pixel spacing Polarization
ERS-2 2-jan-2003 11:00 C 12.5 m VV
ENVISAT 2-jan-2003 21:57 C 12.5 m VH
Image n [sm ]1
-1/3
nSAR [sm ]
-1/3
NS ΔQ [%]p
ENVISAT 0.047 0.07 0.975 16.11
ERS-2 0.053 0.10 0.990 1.34
360 km2
261 km2
Tab. 1 - Optimum parameter set and performances in discharge
estimation at Pfaffenthall in terms of Nash-sutcliffe efficency, NS,
and peak discharge error ΔQ . n and n are the Manning’s values
for the area without and with RSD information, respectevely.
p 1 SAR
Rating Curve from SAR imagery Space Applications
in Environmental Management
Space Applications
in Environmental Management
Rating Curve from SAR imagery
Luxembourg Earth Observation and Integrated Applications Dayand Integrated Applications Day
Luxembourg, 16 March 2012
1
2
3
Research Institute for Geo-hydrological Protection, National Research Council, via M. Alta 126, 06128 Perugia, Italy
Centre de Recherche Public - Gabriel Lippmann, Rue du Brill 41, L - 4422 Belvaux - Grand-Duchy of Luxembourg
Dep. of Civil,Environmental and Aerospace Engineering, University of Palermo, viale delle Scienze, I-09128 Palermo, Italy
G. Corato , R. Hostache , P. Matgen , T. Moramarco and T. Tucciarelli(1) (2) (2) (1) (3)
G. Corato , R. Hostache , P. Matgen , T. Moramarco and T. Tucciarelli(1) (2) (2) (1) (3)
(b) (c)
(d)
Discharge[m/s]
3
Time [h]
Waterlevel[masl]
Time [h]
ERS-2
ENVISAT
(a)
Lateral Inflow, and upstream discharge, , are proportional to the related basin areas,
:
q , q
A and A
lat up
inter up
is the upstream basin areaA is the interbasin area and Ainter up
Q[m/s]3
h [m]
(e)
Available
Rating Curve
ERS-2
ERS-2
ENVISAT
ENVISAT
Fig. 1 - Water levels
hydrograph of January 2003
event at Pfafenthal with
indication of the acquisition
time of the two SAR images.
Main properties of images
are listed in the table below.

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RatingFromSpace_A3

  • 1. To propose a new procedure for continuous discharge estimation. The procedure is based on the use of the DORA hydraulic model (Noto and Tucciarelli, 2001) to turn recorded stages into discharges and the exploiting remote sensing derived water levels for Manning's roughness calibration. The flood event of January 2003, occurred along the Alzette River, is investigated by using two available SAR images. Purpose Conclusions Introduction References Method Results Case Study Reliable discharge estimations at a river site depend on local hydraulic conditions, which are usually defined by recording water level. In fact, stage monitoring is relatively inexpensive, especially when compared to the cost necessary to carry out flow velocity measurements. However, there is the need of converting stage records into discharge values. This task is generally addressed through a reliable rating curve, which can be unknown, in the case of gauged sites where velocity measurements cannot be carried out, or limited for low flows. In addition, a rating curve differs from the one-to-one stage-discharge relationship when unsteady flows occur. In order to relate stage and discharge hydrographs at a selected river section also during unsteady flow conditions, 1D hydraulic modelling can be adopted (Corato et al., 2011). Nevertheless, a reliable use of hydraulic modelling is strictly related to the river cross sections geometry data availability along with an accurate Manning's roughness coefficient calibration. For this latter, many studies (Aronica et al., 2002;Hostache et al., 2009; Prestinizi et al., 2011) show that it is possible to use the remote sensing derived (RSD) information to calibrate a hydraulic model. The most exploited sensors are the Synthetic Aperture Radar (SAR) ones, due to their high spatial resolution and the all weather and day-and-night capability. Therefore, a reliable continuous discharge monitoring system can be obtained using a hydraulic model and combining the in situ information provided by a stream gauge with RSD information, coming from SAR sensors. Ø Ø Ø Ø Ø Ø Aronica, G., Bates, P. D. , Horritt, M. S., Assessing the uncertainty in distributed model predictions using observed binary pattern information with in GLUE, Hydrol. Process., vol. 16, no. 10, pp. 2001–2016, 2002. Corato, G., Moramarco, T., and Tucciarelli, T.: Discharge estimation combining flow routing and occasional measurements of velocity, Hydrol. Earth Syst. Sci., 15, 2979-2994. Durand M., Rodriguez E., Alsdorf D.E., Trigg M., Estimating river depth from remote swath interferometry measurements of river height, slope and width, IEEE Journal of selected topics in applied Earth Observations and Remote Sensing, 3(1), 20-31, 2007. Hostache, R., Matgen, P., Schumann, G., Puech, C., Hoffmann, L., Pfister, L., Water level estimation and reduction of hydraulic model calibration uncertainties using satellite SAR images of floods, IEEE T. Geosci. Remote, 47, 431–441, 2009. Noto, L. and Tucciarelli, T.: DORA algorithm for network flow models with improved stability and convergence properties." J Hydraul Eng, ASCE, 127(5), 380-391, 2001. Prestininzi, P, Di Baldassarre, G, Schumann, G., Bates, PD., Selecting the appropriate hydraulic model structure using low-resolution satellite imagery, Advances in Water Resources, 34, 38-46, 2011. ü ü A new procedure for discharge estimation in natural channel has been proposed. The procedure combines a continuous ‘in-situ’ information coming from a stream gauge with a sporadic RSD information obtained by a SAR sensor: The main advantage of this procedure consists in the fact that the RSD information coming from SAR sensors is globally available, without limits of site accessibility or weather conditions. These features make the proposed procedure suitable for recorded water levels are turned into discharge values by using a hydraulic model calibrated with a RSD information. The results show that RSD information is suitable for an efficient hydraulic model calibration, oriented to discharge estimation at river site where only stages are recorded. gauged site not equipped for velocity measurements or located in an area that is not easily reachable by operators. On the other hand, the main disadvantages are related to the time resolution of the RSD information that is, at the present, still limited to sporadic snapshots. Next missions, like SWOT, promise to furnish more accurate information that might be used also for bathymetry modelling (Durand et al., 2010). ü ü The RSD water levels are estimated on the basis of following steps (Hostache et al., 2009): extraction of flood extents using a double treshold set on the basis of a land use map; estimation of water levels coupling RSD flood extents and DEM; constrain water levels using hydraulic coherence: for subcritical flow, energy can not increase moving from upstream to downstream. ü ü ü The procedure was applied using the two SAR images, available for the flood event of January 2003. Fig. 2a illustrates the flood limit extents estimated using the method proposed by Hostache et al. (2009), while related water levels are shown in Fig. 2b. The model calibration has been performed with 3500 Monte Carlo simulations and Fig. 2c shows the pattern of the objective function. Using both images, it has been possible to calibrate the hydraulic model. The optimum parameter sets along with related performances in discharge estimation at Phaffenthal gauged section are listed in Tab. 1. As shown in Fig. 2d and listed in tab. 2, using both images a good matching between observed and simulated discharge hydrographs has been obtained at the upstream end (Pfaffenthal) where water levels are recorded. Therefore rating curve can be inferred (see Fig. 2e). Manning’s roughness set is calibrated minimizing the distance of simulated water levels from the RSD water levels bounds: and are the min and max RSD water levels respectively, and z| is the simulated one. sim RSD information is available only for overbank flood, so that two areas with different roughness can be identified depending on the availability of RSD information. Fig. 2 - ERS-2 Image: (a) Flood limit extents extraction (b) water levels estimation and hydraulic coherence constraining (c) map of error function (d) discharge estimation at Pfaffenthal gauged site. Distance from Pfaffenthal [km] Waterlevel[masl] Pfaffenthal RSD Water levelsFlood limit extents Calibration: Error Map n1 nSAR nSAR Pfaffenthal Discharge Steinsel Hunsdorf Lintgen Mersch n1 no RSD data no RSD data RSD data noRSDdata n1 DORA Hydraulic Model Calibration Sim. hydraulic profile Recorded Water Level hydrograph (Upstream Boundary Condition) Stream gauge SAR sensor RSDWaterLevels Optimum Manning set Simulated discharge hydrograph q =lat q =kup upq Ainter Aup Hydraulic assumtions min SAR iz ( ) ( ) ( ) = ì < ï ï = = £ £í ï - >ï î å min min 1 min max 1, max max - if , , with , 0 if if SAR SAR i i i isim sim SAR SAR up SAR i up SAR i SAR i i isim i n SAR SAR i i i isim sim z z z z f n n d n n d n n z z z z z z z max SAR iz RSD waterlevels Calibration Image Acquisition time Band Pixel spacing Polarization ERS-2 2-jan-2003 11:00 C 12.5 m VV ENVISAT 2-jan-2003 21:57 C 12.5 m VH Image n [sm ]1 -1/3 nSAR [sm ] -1/3 NS ΔQ [%]p ENVISAT 0.047 0.07 0.975 16.11 ERS-2 0.053 0.10 0.990 1.34 360 km2 261 km2 Tab. 1 - Optimum parameter set and performances in discharge estimation at Pfaffenthall in terms of Nash-sutcliffe efficency, NS, and peak discharge error ΔQ . n and n are the Manning’s values for the area without and with RSD information, respectevely. p 1 SAR Rating Curve from SAR imagery Space Applications in Environmental Management Space Applications in Environmental Management Rating Curve from SAR imagery Luxembourg Earth Observation and Integrated Applications Dayand Integrated Applications Day Luxembourg, 16 March 2012 1 2 3 Research Institute for Geo-hydrological Protection, National Research Council, via M. Alta 126, 06128 Perugia, Italy Centre de Recherche Public - Gabriel Lippmann, Rue du Brill 41, L - 4422 Belvaux - Grand-Duchy of Luxembourg Dep. of Civil,Environmental and Aerospace Engineering, University of Palermo, viale delle Scienze, I-09128 Palermo, Italy G. Corato , R. Hostache , P. Matgen , T. Moramarco and T. Tucciarelli(1) (2) (2) (1) (3) G. Corato , R. Hostache , P. Matgen , T. Moramarco and T. Tucciarelli(1) (2) (2) (1) (3) (b) (c) (d) Discharge[m/s] 3 Time [h] Waterlevel[masl] Time [h] ERS-2 ENVISAT (a) Lateral Inflow, and upstream discharge, , are proportional to the related basin areas, : q , q A and A lat up inter up is the upstream basin areaA is the interbasin area and Ainter up Q[m/s]3 h [m] (e) Available Rating Curve ERS-2 ERS-2 ENVISAT ENVISAT Fig. 1 - Water levels hydrograph of January 2003 event at Pfafenthal with indication of the acquisition time of the two SAR images. Main properties of images are listed in the table below.