Marie-Paule Bonnet

Coupled modeling of biospheric and chemical weathering processes at the continental scale

[1]xa0In this contribution, a reactive-transport model describing weathering in soil profiles and at the watershed scale is coupled to a dynamic global vegetation model to calculate the dissolved load of continental waters on a 0.5° latitude × 0.5° longitude grid. The so-called Biosphere-Weathering at the Catchment Scale (B-WITCH) model is applied to the Orinoco watershed (South America). We show that B-WITCH is able to reproduce the main cation composition of the surface waters over the watershed. Sensitivity tests demonstrate that clay mineral reactivities are key factors controlling the calculated discharge of dissolved species. More specifically, our simulations show that the dissolution and precipitation rates of clay minerals in the weathering profiles are strongly intertwined, and that this coupling must be accurately described when modeling the weathering fluxes at the continental scale. A second set of sensitivity tests show that, for the tropical environment, land plants control the total base cation discharge through their impact on the soil hydrology, rather than through enhanced soil CO2 pressures. Indeed, the complete removal of the continental vegetation leads to an increase in the dissolved fluxes to the ocean by 80% because of the collapse in the evapotranspiration, resulting in a more efficient drainage of the weathering profiles. On the other hand, neglecting the root respiration and setting the soil CO2 pressure to the atmospheric level forces the total base cation discharge to decrease by only 20%.

Denoising Satellite Gravity Signals by Independent Component Analysis

Independent component analysis (ICA) is a blind separation method based on simple assumptions of the independence of sources and the non-Gaussianity of observations. An approach based on ICA is used here to extract hydrological signals over land and oceans from the polluting striping noise due to orbit repetitiveness and present in the gravity anomalies detected by the Gravity Recovery and Climate Experiment (GRACE) satellites. We took advantage of the availability of monthly level-2 GRACE solutions from three official providers (i.e., CSR, JPL, and GFZ) that can be considered as different observations of the same phenomenon. The efficiency of the methodology is demonstrated on a synthetic case. Applied to one month of GRACE solutions, it allows for clearly separating the total water storage change from the meridional-oriented spurious gravity signals on the continents but not on the oceans. This technique gives results equivalent to the destriping method for continental water storage.

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.

Seasonal dissolved rare earth element dynamics of the Amazon River main stem, its tributaries, and the Curuaí floodplain

We present a comprehensive dissolved rare earth element (REE) data set for the Amazon River and its main tributaries, Rio Negro, Solimoes, and Madeira, as well as the Curuai floodplain. The two-year time series show that REE vary seasonally with discharge in each of the tributaries, and indicate a hydrologically dominated control. Upper crust normalized REE patterns are relatively constant throughout the year, with Ce/Ce* anomalies being positively related to discharge. We propose revised annual dissolved REE fluxes to the surface Atlantic Ocean based on an integration of the seasonal data. For Nd (<0.22 μm) this results in an average flux of 607 ± 43 T/yr, which is at least 1.6 times larger than the previous estimate of 374 T/yr (<0.45 μm) based on low water stage data. Moreover, during the high water season the maximum Nd flux measures 1277 t.yr−1, constituting 30% of the required flux to the Atlantic Ocean (Tachikawa et al., 2003). Consequently, a smaller contribution of Nd from atmospheric and river particle desorption is required than was previously suggested. A mass balance of Amazon tributaries and observed fluxes at Obidos indicates that dissolved LREE behave quasi-conservatively. Conversely, the HREE mass balance presents a deficit during the high water stages, which could be related to the passage of water through the floodplain system accompanied by solid/dissolved phase transfer.

Accuracy assessment of SRTM v4 and ASTER GDEM v2 over the Altiplano watershed using ICESat/GLAS data

The new Global Digital Elevation Model (GDEM v2) has been available since 17 October 2011. With a resolution of approximately 30 m, this model should provide more accurate information than the latest version of Shuttle Radar Topographic Mission (SRTM v4) with a resolution of 90 m outside of the USA. The accuracies of these two recently released digital elevation models (DEMs) were assessed over the Altiplano watershed in South America using ICESat/GLAS data (Ice, Cloud and Land Elevation Satellite/Geoscience Laser Altimeter System). On the global scale, GDEM v2 is more accurate than SRTM v4, which presents a negative bias of approximately 8.8 m. Strong correlations between the DEMs’ accuracies and mean slope values occurred. Regarding land cover, SRTM v4 could be more accurate or easier to correct on a smaller scale than GDEM v2. Finally, a merged and corrected DEM that considers all of these observations was built to provide more accurate information for this region. The new model featured lower absolute mean errors, standard deviations, and root mean square errors relative to SRTM v4 or GDEM v2.

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.

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.

Discharge and suspended sediment flux estimated along the mainstream of the Amazon and the Madeira Rivers (from in situ and MODIS Satellite Data)

Water and suspended sediment fluxes are considered during the period 2000-2008 in a region including the full Amazon River from the confluence of the Negro River to Santarem, the end part of the Solimoes River, and the lower part of the Madeira River. Three types of data are used: water discharge estimated from field measurements, and suspended sediment obtained from field measurements and derived from MODIS satellite data. A generalized least square method including a propagating term is developed in order to propagate the signal upward and downward the river. The approach is introduced and tested. Several experiments are considered in order, first, to estimate the ability to propagate the signal from stations located before the confluences of Negro and Madeira Rivers to stations located on the Amazon River; second to investigate the possibility to propagate the signal along the Amazon River which dynamics is coupled with floodplains dynamics; and third to produce optimal solutions of water and sediment fluxes. For each experiment, the influence of field and satellite data is compared. The approach is efficient in the upper part of the region of study where the Solimoes, the Negro and the Madeira Rivers meet and fails in the lower part of the region where interactions between Amazon River and floodplains play an important role on the fluxes dynamics. The optimal experiment includes in situ and satellite data from all the stations available and is used to analyse the recent evolution of suspended sediment flux along the Amazon River and its interaction with the large coupled floodplains. A high accumulation rate is observed during the 2000-2002 period, followed by decreasing rates until 2005 and by increasing values in 2006 and 2007. Our results suggest that floodplains extending along a river reach of 390 km-long between Itacoatiara and Obidos trap about 15% of the suspended sediment flux passing at Obidos. The simulated deposition rate is of about 0.3 Mt km(-1) yr(-1) corresponding to an accretion rate of about 27 mm yr(-1).

Performance of CMORPH, TMPA, and PERSIANN rainfall datasets over plain, mountainous, and glacial regions of Pakistan

The present study aims at the assessment of six satellite rainfall estimates (SREs) in Pakistan. For each assessed products, both real-time (RT) and post adjusted (Adj) versions are considered to highlight their potential benefits in the rainfall estimation at annual, monthly, and daily temporal scales. Three geomorphological climatic zones, i.e., plain, mountainous, and glacial are taken under considerations for the determination of relative potentials of these SREs over Pakistan at global and regional scales. All SREs, in general, have well captured the annual north-south rainfall decreasing patterns and rainfall amounts over the typical arid regions of the country. Regarding the zonal approach, the performance of all SREs has remained good over mountainous region comparative to arid regions. This poor performance in accurate rainfall estimation of all the six SREs over arid regions has made their use questionable in these regions. Over glacier region, all SREs have highly overestimated the rainfall. One possible cause of this overestimation may be due to the low surface temperature and radiation absorption over snow and ice cover, resulting in their misidentification with rainy clouds as daily false alarm ratio has increased from mountainous to glacial regions. Among RT products, CMORPH-RT is the most biased product. The Bias was almost removed on CMORPH-Adj thanks to the gauge adjustment. On a general way, all Adj versions outperformed their respective RT versions at all considered temporal scales and have confirmed the positive effects of gauge adjustment. CMORPH-Adj and TMPA-Adj have shown the best agreement with in situ data in terms of Bias, RMSE, and CC over the entire study area.

Low‐water maps of the groundwater table in the central Amazon by satellite altimetry

Groundwater plays a fundamental role in rainforest environments, as it is connected with rivers, lakes, and wetlands, and helps to support wildlife habitat during dry periods. Groundwater reservoirs are however excessively difficult to monitor, especially in large and remote areas. Using concepts from groundwater-surface water interactions and ENVISAT altimetry data, we evaluated the topography of the groundwater table during low-water periods in the alluvial plain of the central Amazon. The water levels are monitored using an unprecedented coverage of 491 altimetric stations over surface waters in the central Amazon. The groundwater table maps interpolated at spatial resolutions ranging from 50 to 100km are consistent with groundwater wells data. They provide evidence of significant spatiotemporal organization at regional scale: heterogeneous flow from the hillslope toward the main rivers is observed, as well as strong memory effects and contrasted hydrological behaviors between the North and the South of the Amazon. Key Points Groundwater and surface waters coincide during low-water periods First groundwater maps in central Amazon by satellite altimetry Interannual memory effects are observed in the central Amazon groundwater system