Amazon River discharge estimated from TOPEX/Poseidon altimetry

Zakharova, Elena; Kouraev, Alexei V.; Cazenave, Anny; Seyler, Frédérique

doi:10.1016/j.crte.2005.10.003

Cited by 93 publications

(60 citation statements)

References 13 publications

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“…Due to the size of the footprint, the radar altimetry technology has been widely applied to large rivers, such as the Amazon River [13][14][15][16][17][18][19], on which many altimeter sensors onboard of Geodetic Satellite (GeoSat) [13], TOPEX/POSEIDON (T/P) [14,15,18], ERS-2 and ENVISAT [19] have been tested. Few studies dedicated to a thorough assessment of the radar altimetry over rivers, such as Ob, Mekong, Negro, Gange and Brahmaputra, even without comparisons with in situ gauges, have been published [7,[20][21][22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

“…If a relationship between the water level observations derived by radar altimetry and the ones measured in situ is identified, the in situ rating curve may be applied to the altimetry-derived water levels, provided that no lateral flow is present between the gauged site and VS and that the river cross-section geometry is quite similar. Otherwise, a specific rating curve at the VS can be directly developed, relating altimetry water levels to observed discharge at the gauged station (e.g., [18,20]). For discharge (or flow velocity) estimation where no in situ data are available at the VS, Bjerklie et al [27] proposed different equations involving various combinations of potentially remotely observable variables.…”

Section: Introductionmentioning

confidence: 99%

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River Discharge Estimation by Using Altimetry Data and Simplified Flood Routing Modeling

et al. 2013

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A methodology to estimate the discharge along rivers, even poorly gauged ones, taking advantage of water level measurements derived from satellite altimetry is proposed. The procedure is based on the application of the Rating Curve Model (RCM), a simple method allowing for the estimation of the flow conditions in a river section using only water levels recorded at that site and the discharges observed at another upstream section. The European Remote-Sensing Satellite 2, ERS-2, and the Environmental Satellite, ENVISAT, altimetry data are used to provide time series of water levels needed for the application of RCM. In order to evaluate the usefulness of the approach, the results are compared with the ones obtained by applying an empirical formula that allows discharge estimation from remotely sensed hydraulic information. To test the proposed procedure, the 236 km-reach of the Po River is investigated, for which five in situ stations and four satellite tracks are available. Results show that RCM is able to appropriately represent the discharge, and its performance is better than the empirical formula, although this latter does not require upstream hydrometric data. Given its simple formal structure, the proposed approach can be conveniently utilized in ungauged sites where only the survey of the cross-section is needed.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

River Discharge Estimation by Using Altimetry Data and Simplified Flood Routing Modeling

et al. 2013

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“…Zakharova et al (2006) used JERS-1-SAR images and defined a virtual station by a rectangular window. However, several rectangular windows can be defined when islands are present.…”

Section: Literature Review Of "Virtual Station" Definitionmentioning

confidence: 99%

Producing time series of river water height by means of satellite radar altimetry—a comparative study

Roux

Silva

Getirana

et al. 2010

Hydrological Sciences Journal

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Satellite radar altimetry is complementary to in situ limnimetric surveys as a means of estimating the water height of large rivers, lakes and flood plains. Production of water height time series by satellite radar altimetry technology requires first the selection of radar ground target locations corresponding to water body surfaces under study, i.e. the definition of "virtual limnimetric stations". We propose to investigate qualitative and quantitative differences between three representative virtual station creation methodologies: (a) a fully manual method, (b) a semi-automatic method based on a land cover characterization that allows the water body surface under study to be located; and (c) an original fully automatic procedure that exploits a digital elevation model and an estimation of the river width. The results yielded by these three methods are comparable: maximum absolute magnitudes of water height differences being 0.46, 0.26 and 0.15 m for, respectively, 95, 90 and 80% of the water height values obtained. Moreover, more than 67% and 92% of time series jointly produced by the methods present root mean square differences lower than 20 and 50 cm, respectively. The results show that the fully automatic method developed herein provides as reliable results as the fully manual one. This opens the way to use of satellite radar altimetry for the generation of water height time series on a large scale, and considerably extends the applicability of satellite radar altimetry in hydrology. Key words

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“…These relations are commonly represented by rating curves and allow one to predict water discharges from observed water levels, with accuracy varying as a function of input data and flow regime characteristics. As examples, river discharges have been estimated from altimetric data in the Chari River (Coe and Birkett, 2004), Ob' River (Kouraev et al, 2004), Amazon River (Zakharova et al, 2006) and Zambezi River (Michailovsky et al, 2012). Although errors between predicted and observed water discharges are relatively small in most applications, the use of such methods is restricted to VS located near gauging stations.…”

Section: Introductionmentioning

confidence: 99%

Estimating water discharge from large radar altimetry datasets

Getirana

Peters‐Lidard

2013

Hydrol. Earth Syst. Sci.

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Abstract. The objective of this study is to evaluate the potential of large altimetry datasets as a complementary gauging network capable of providing water discharge in ungauged regions. A rating curve-based methodology is adopted to derive water discharge from altimetric data provided by the Envisat satellite at 475 virtual stations (VS) within the Amazon basin. From a global-scale perspective, the stage-discharge relations at VS are built based on radar altimetry and outputs from a modeling system composed of a land surface model and a global river routing scheme. In order to quantify the impact of model uncertainties on rating-curve based discharges, a second experiment is performed using outputs from a simulation where daily observed discharges at 135 gauging stations are introduced in the modeling system. Discharge estimates at 90 VS are evaluated against observations during the curve fitting calibration (2002)(2003)(2004)(2005) and evaluation (2006)(2007)(2008) periods, resulting in mean normalized RMS errors as high as 39 and 15 % for experiments without and with direct insertion of data, respectively. Without direct insertion, uncertainty of discharge estimates can be mostly attributed to forcing errors at smaller scales, generating a positive correlation between performance and drainage area. Mean relative streamflow volume errors (RE) of altimetry-based discharges varied from 15 to 84 % for large and small drainage areas, respectively. Rating curves produced a mean RE of 51 % versus 68 % from model outputs. Inserting discharge data into the modeling system decreases the mean RE from 51 to 18 %, and mean NRMSE from 24 to 9 %. These results demonstrate the feasibility of applying the proposed methodology to the continental or global scales.

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Amazon River discharge estimated from TOPEX/Poseidon altimetry

Cited by 93 publications

References 13 publications

River Discharge Estimation by Using Altimetry Data and Simplified Flood Routing Modeling

River Discharge Estimation by Using Altimetry Data and Simplified Flood Routing Modeling

Producing time series of river water height by means of satellite radar altimetry—a comparative study

Estimating water discharge from large radar altimetry datasets

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