Frédérique Seyler

Interannual variations of river water storage from a multiple satellite approach: A case study for the Rio Negro River basin

Spatiotemporal variations of water volume over inundated areas located in a large river basin have been determined using combined observations from a multisatellite inundation data set, the TOPEX/POSEIDON (T/P) altimetry satellite, and in situ hydrographic stations for the water levels over rivers and floodplains. We computed maps of monthly surface water volume change over the period of common availability of T/P and the multisatellite data (1993–2000). The basin of the Negro River, the largest tributary in terms of discharge to the Amazon River, was selected as a test site. A strong seasonal signal is observed with minima in October and maxima in June. A strong interannual component is also present, particularly important during ENSO years. The surface water change was estimated to be 167 ± 39 km3 between October 1995 (low water) and June 1996 (high water). This result is consistent with previous estimates obtained for the 1995–1996 hydrological cycle over the same area using the JERS mosaic data. The surface water volume change is then compared to the total water volume change inferred from the GRACE satellite for an average annual cycle. The difference between the surface storage change and the total storage change derived from GRACE was computed to estimate the contribution of the soil moisture and groundwater to the total storage change. Our study supports the hypothesis that total water storage is almost equally partitioned between surface water and the combination of soil moisture and groundwater for the Negro River basin. The water volume changes are also evaluated using in situ discharge measurements and the GPCP precipitation product (correlation of 0.61). The results show the high potential for the new technique to provide valuable information to improve our understanding of large river basin hydrologic processes.

Surface freshwater storage and dynamics in the Amazon basin during the 2005 exceptional drought

The Amazon river basin has been recently affected by extreme climatic events, such as the exceptional drought of 2005, with significant impacts on human activities and ecosystems. In spite of the importance of monitoring freshwater stored and moving in such large river basins, only scarce measurements of river stages and discharges are available and the signatures of extreme drought conditions on surface freshwater dynamics at the basin scale are still poorly known. Here we use continuous multisatellite observations of inundation extent and water levels between 2003 and 2007 to monitor monthly variations of surface water storage at the basin scale. During the 2005 drought, the amount of water stored in the river and floodplains of the Amazon basin was 130 km 3 ( 70%) below its 2003‐7 average. This represents almost a half of the anomaly of minimum terrestrial water stored in the basin as estimated using the Gravity Recovery and Climate Experiment (GRACE) data.

Water level dynamics of Amazon wetlands at the watershed scale by satellite altimetry

In this study we used satellite altimetry to characterize the time and space variations in water stored in or circulating through rivers, floodplains, wetlands and lakes in the major sub-basins of the Amazon basin. Using a specific methodology to rigorously select original three-dimensional (3D) data from an Environmental Satellite (ENVISAT) mission, water level time series were calculated at the crossing path of the satellite tracks with the water bodies. We took advantage of the continuous sampling of the water level along the satellite track segments that cross the watershed to analyse both spatial and temporal relationships between: (i) the river and its floodplain and (ii) different basins. This work evidences in particular the existence of water leaking between the Negro and Solimões basins at the high water stage. It highlights that the phenomenon of a secondary flood peak occurring in the water level series in the Solimões basin at rising water, known as repiquete, is caused by the rain equatorial regime of the northern upstream tributaries of the Solimões River, but is disconnected from the same phenomenon occurring within the Rio Negro basin.

Land cover mapping and carbon pools estimates in Rondonia, Brazil

In order to estimate changes in carbon pools and fluxes to the atmosphere, we used LANDSAT/TM data to calculate the extent of areas converted to pasture to different lengths of time in a 100 x 92 km area of the southwestern Brazilian Amazon. Image processing and the supervised classification allowed the production of an accurate land cover map including forest and pastures of different ages. The results showed that almost 30% of the natural forest were deforested and occupied with pasture. From the 2800 km 2 of pasture almost 60% consists of pasture with less than three years of establishment. Estimates of carbon pools and fluxes to the atmosphere were carried out using the results of LANDSAT image analysis and published data about carbon stocks in vegetation and soil. The results showed that a large amount of carbon ( 12x10 3 g C m -2 ) is released after three years under pasture. From the initial burning and after fifth year under pasture, the system functioned as a source of CO2 to atmosphere. After this period the balance is slightly negative and the amount of CO2 released is lower than the amount released in the initial period.

Stage‐discharge rating curves based on satellite altimetry and modeled discharge in the Amazon basin

In this study, rating curves (RCs) were determined by applying satellite altimetry to a poorly gauged basin. This study demonstrates the synergistic application of remote sensing and watershed modeling to capture the dynamics and quantity of flow in the Amazon River Basin, respectively. Three major advancements for estimating basin‐scale patterns in river discharge are described. The first advancement is the preservation of the hydrological meanings of the parameters expressed by Mannings equation to obtain a data set containing the elevations of the river beds throughout the basin. The second advancement is the provision of parameter uncertainties and, therefore, the uncertainties in the rated discharge. The third advancement concerns estimating the discharge while considering backwater effects. We analyzed the Amazon Basin using nearly one thousand series that were obtained from ENVISAT and Jason‐2 altimetry for more than 100 tributaries. Discharge values and related uncertainties were obtained from the rain‐discharge MGB‐IPH model. We used a global optimization algorithm based on the Monte Carlo Markov Chain and Bayesian framework to determine the rating curves. The data were randomly allocated into 80% calibration and 20% validation subsets. A comparison with the validation samples produced a Nash‐Sutcliffe efficiency ( urn:x-wiley:00431397:media:wrcr22024:wrcr22024-math-0001) of 0.68. When the MGB discharge uncertainties were less than 5%, the urn:x-wiley:00431397:media:wrcr22024:wrcr22024-math-0002 value increased to 0.81 (mean). A comparison with the in situ discharge resulted in an urn:x-wiley:00431397:media:wrcr22024:wrcr22024-math-0003 value of 0.71 for the validation samples (and 0.77 for calibration). The urn:x-wiley:00431397:media:wrcr22024:wrcr22024-math-0004 values at the mouths of the rivers that experienced backwater effects significantly improved when the mean monthly slope was included in the RC. Our RCs were not mission‐dependent, and the urn:x-wiley:00431397:media:wrcr22024:wrcr22024-math-0005 value was preserved when applying ENVISAT rating curves to Jason‐2 altimetry at crossovers. The cease‐to‐flow parameter of our RCs provided a good proxy for determining river bed elevation. This proxy was validated against Acoustic Doppler current profiler (ADCP) cross sections with an accuracy of more than 90%. Altimetry measurements are routinely delivered within a few days, and this RC data set provides a simple and cost‐effective tool for predicting discharge throughout the basin in nearly real time.

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

Abstract 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. Citation Roux, E., Santos da Silva, J., Vieira Getirana, A. C., Bonnet, M.-P., Calmant, S., Martinez, J.-M. & Seyler, F. (2010) Producing time series of river water height by means of satellite radar altimetry—comparative study. Hydrol. Sci. J. 55(1), 104–120.

Surface Freshwater Storage Variations in the Orinoco Floodplains Using Multi-Satellite Observations

Variations in surface water extent and storage are poorly characterized from regional to global scales. In this study, a multi-satellite approach is proposed to estimate the water stored in the floodplains of the Orinoco Basin at a monthly time-scale using remotely-sensed observations of surface water from the Global Inundation Extent Multi-Satellite (GIEMS) and stages from Envisat radar altimetry. Surface water storage variations over 2003-2007 exhibit large interannual variability and a strong seasonal signal, peaking during summer, and associated with the flood pulse. The volume of surface water storage in the Orinoco Basin was highly correlated with the river discharge at Ciudad Bolivar (R = 0.95), the closest station to the mouth where discharge was estimated, although discharge lagged one month behind storage. The correlation remained high (R = 0.73) after removing seasonal effects. Mean annual variations in surface water volume represented similar to 170 km(3), contributing to similar to 45% of the Gravity Recovery and Climate Experiment (GRACE)-derived total water storage variations and representing similar to 13% of the total volume of water that flowed out of the Orinoco Basin to the Atlantic Ocean.

Application of retracked satellite altimetry for inland hydrologic studies

We explored the application of satellite radar altimetry for the monitoring of small inland bodies of water and hydrologic studies using a water-detection algorithm, optimally retracked TOPEX/POSEIDON data at 10-Hz sampling, and investigated the use of radar backscatter to improve land cover classification. The procedure was demonstrated over Manitoba and south-western (SW) Ontario, and the Amazon River Basin study regions. Compared with an L-band synthetic aperture radar data generated water-land cover mask, the water-detection algorithm detected more water points over the Amazon basin. High correlation of 0.98 between the retracked 10-Hz altimetry and the gauge measurements in Manitoba confirmed that the retracked TOPEX data are more accurate than the non-retracked data, and with higher along-track spatial resolution by virtue of its higher sampling at 10 Hz.

Water Level Fluctuations in the Congo Basin Derived from ENVISAT Satellite Altimetry

In the Congo Basin, the elevated vulnerability of food security and the water supply implies that sustainable development strategies must incorporate the effects of climate change on hydrological regimes. However, the lack of observational hydro-climatic data over the past decades strongly limits the number of studies investigating the effects of climate change in the Congo Basin. We present the largest altimetry-based dataset of water levels ever constituted over the entire Congo Basin. This dataset of water levels illuminates the hydrological regimes of various tributaries of the Congo River. A total of 140 water level time series are extracted using ENVISAT altimetry over the period of 2003 to 2009. To improve the understanding of the physical phenomena dominating the region, we perform a K-means cluster analysis of the altimeter-derived river level height variations to identify groups of hydrologically similar catchments. This analysis reveals nine distinct hydrological regions. The proposed regionalization scheme is validated and therefore considered reliable for estimating monthly water level variations in the Congo Basin. This result confirms the potential of satellite altimetry in monitoring spatio-temporal water level variations as a promising and unprecedented means for improved representation of the hydrologic characteristics in large ungauged river basins.

Daily water stage estimated from satellite altimetric data for large river basin monitoring

Abstract Satellite radar altimetry appears to be a highly promising method that could be used to complement in situ limnimetric station surveys in remote river basins. However, a major drawback of satellite altimetry is its poor temporal resolution. The sampling period ranges from 10 to 35 days, depending on the satellite. This paper proposes a methodology for obtaining time series with a one-day sampling period. The method is based on a linear model exploiting data at a limited number of in situ limnimetric stations. Three parameter estimation methods are proposed: the least square (LS) and weighted least square (WLS) methods, and an optimization method based on a multi-objective criterion (OPT). The model and parameter estimation methods are evaluated by means of simulated altimetric time series whose characteristics are as realistic as possible. The absolute precision of the interpolation and its sensitivity to model structures, missing values and random noise are investigated. The RMS of the interpolation residuals ranges from 0.6 to 40.9 cm. Results show that taking into account more than one in situ reference station significantly decreases the RMS errors. Taking into account time shifts between stations improves the results too, reducing the RMS error by 16.4 cm (32.7%) in one case. In the ideal case, i.e. with no missing values and random noise, the OPT technique provides slightly better absolute results than the LS method, and significantly better results than the WLS approach. The OPT method is the least sensitive to missing values and random noise, two artefacts that systematically affect radar altimetric data.